RIN 0938-AU84, 48780-49499 [2022-16472]

Agencies

• Centers for Medicare & Medicaid Services
• DEPARTMENT OF HEALTH AND HUMAN SERVICES

[Federal Register Volume 87, Number 153 (Wednesday, August 10, 2022)]
[Rules and Regulations]
[Pages 48780-49499]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2022-16472]



[[Page 48779]]

Vol. 87

Wednesday,

No. 153

August 10, 2022

Part II





 Department of Health and Human Services





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 Centers for Medicare & Medicaid Services





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42 CFR Parts 412, 413, et al.





Medicare Program; Hospital Inpatient Prospective Payment Systems for 
Acute Care Hospitals and the Long Term Care Hospital Prospective 
Payment System and Policy Changes and Fiscal Year 2023 Rates; Quality 
Programs and Medicare Promoting Interoperability Program Requirements 
for Eligible Hospitals and Critical Access Hospitals; Costs Incurred 
for Qualified and Non-qualified Deferred Compensation Plans; and 
Changes to Hospital and Critical Access Hospital Conditions of 
Participation; Final Rule

Federal Register / Vol. 87 , No. 153 / Wednesday, August 10, 2022 / 
Rules and Regulations

[[Page 48780]]


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DEPARTMENT OF HEALTH AND HUMAN SERVICES

Centers for Medicare & Medicaid Services

42 CFR Parts 412, 413, 482, 485, and 495

[CMS-1771-F]


RIN 0938-AU84

Medicare Program; Hospital Inpatient Prospective Payment Systems 
for Acute Care Hospitals and the Long-Term Care Hospital Prospective 
Payment System and Policy Changes and Fiscal Year 2023 Rates; Quality 
Programs and Medicare Promoting Interoperability Program Requirements 
for Eligible Hospitals and Critical Access Hospitals; Costs Incurred 
for Qualified and Non-Qualified Deferred Compensation Plans; and 
Changes to Hospital and Critical Access Hospital Conditions of 
Participation

AGENCY: Centers for Medicare & Medicaid Services (CMS), Department of 
Health and Human Services (HHS).

ACTION: Final rule.

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SUMMARY: This final rule will: revise the Medicare hospital inpatient 
prospective payment systems (IPPS) for operating and capital-related 
costs of acute care hospitals; make changes relating to Medicare 
graduate medical education (GME) for teaching hospitals; update the 
payment policies and the annual payment rates for the Medicare 
prospective payment system (PPS) for inpatient hospital services 
provided by long-term care hospitals (LTCHs). In addition it will 
establish new requirements and revise existing requirements for 
eligible hospitals and critical access hospitals (CAHs) participating 
in the Medicare Promoting Interoperability Program; and update policies 
for the Hospital Readmissions Reduction Program, Hospital Inpatient 
Quality Reporting (IQR) Program, Hospital VBP Program, Hospital-
Acquired Condition (HAC) Reduction Program, PPS-Exempt Cancer Hospital 
Reporting (PCHQR) Program, and the Long-Term Care Hospital Quality 
Reporting Program (LTCH QRP). It will also revise the hospital and 
critical access hospital (CAH) conditions of participation (CoPs) for 
infection prevention and control and antibiotic stewardship programs; 
and codify and clarify policies related to the costs incurred for 
qualified and non-qualified deferred compensation plans. Lastly, this 
final rule will provide updates on the Rural Community Hospital 
Demonstration Program and the Frontier Community Health Integration 
Project.

DATES: This final rule is effective October 1, 2022.

FOR FURTHER INFORMATION CONTACT: Donald Thompson, and Michele Hudson, 
(410) 786-4487 or [email protected], Operating Prospective Payment, MS-
DRG Relative Weights, Wage Index, Hospital Geographic 
Reclassifications, Graduate Medical Education, Capital Prospective 
Payment, Excluded Hospitals, Medicare Disproportionate Share Hospital 
(DSH) Payment Adjustment, Sole Community Hospitals (SCHs), Medicare-
Dependent Small Rural Hospital (MDH) Program, Low-Volume Hospital 
Payment Adjustment, and Critical Access Hospital (CAH) Issues.
    Emily Lipkin, and Jim Mildenberger, [email protected], Long-Term Care 
Hospital Prospective Payment System and MS-LTC-DRG Relative Weights 
Issues.
    Adina Hersko, [email protected], New Technology Add-On 
Payments and New COVID-19 Treatments Add-on Payments Issues.
    Mady Hue, [email protected], and Andrea Hazeley, 
[email protected], MS-DRG Classifications Issues.
    Siddhartha Mazumdar, siddhartha.mazumdar @cms.hhs,gov, Rural 
Community Hospital Demonstration Program Issues.
    Jeris Smith, [email protected], Frontier Community Health 
Integration Project Demonstration Issues.
    Sophia Chan, [email protected], Hospital Readmissions 
Reduction Program--Administration Issues.
    Tyson Nakashima, [email protected], Hospital Readmissions 
Reduction Program--Measures Issues.
    Jennifer Tate, [email protected], Hospital-Acquired 
Condition Reduction Program--Administration Issues
    Yuling Li, [email protected], Hospital-Acquired Condition 
Reduction Program--Measures Issues.
    Julia Venanzi, [email protected], Hospital Inpatient 
Quality Reporting Program and Hospital Value-Based Purchasing Program--
Administration Issues
    Melissa Hager, [email protected] and Ngozi Uzokwe, 
[email protected]--Hospital Inpatient Quality Reporting Program 
and Hospital Value-Based Purchasing Program--Measures Issues Except 
Hospital Consumer Assessment of Healthcare Providers and Systems 
Issues.
    Elizabeth Goldstein, [email protected], Hospital 
Inpatient Quality Reporting and Hospital Value-Based Purchasing--
Hospital Consumer Assessment of Healthcare Providers and Systems 
Measures Issues.
    Ora Dawedeit, [email protected], PPS-Exempt Cancer Hospital 
Quality Reporting--Administration Issues.
    Leah Domino, [email protected], PPS-Exempt Cancer Hospital 
Quality Reporting Program-Measure Issues
    Ariel Cress, [email protected], Long-Term Care Hospital 
Quality Reporting Program--Data Reporting Issues.
    Elizabeth Holland, [email protected], Medicare 
Promoting Interoperability Program.
    Dawn Linn, [email protected], Lela Strong, 
[email protected], and Alpha Wilson, [email protected], 
Conditions of Participation (CoP) Requirements for Hospitals and 
Critical Access Hospitals (CAHs) to Continue Reporting Data for COVID-
19 and Influenza After the PHE ends as Determined by the Secretary.

SUPPLEMENTARY INFORMATION: 

Tables Available Through the internet on the CMS website

    The IPPS tables for this fiscal year (FY) 2023 final rule are 
available through the internet on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html. Click on the link on the left side of the 
screen titled ``FY 2023 IPPS Final rule Home Page'' or ``Acute 
Inpatient--Files for Download.'' The LTCH PPS tables for this FY 2023 
final rule are available through the internet on the CMS website at 
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/LongTermCareHospitalPPS/ under the list item for Regulation 
Number CMS-1771-F. For further details on the contents of the tables 
referenced in this final rule, we refer readers to section VI. of the 
Addendum to this FY 2023 IPPS/LTCH PPS final rule.
    Readers who experience any problems accessing any of the tables 
that are posted on the CMS websites, as previously identified, should 
contact Michael Treitel, [email protected].

Table of Contents

I. Executive Summary and Background
    A. Executive Summary
    B. Background Summary
    C. Summary of Provisions of Recent Legislation Implemented in 
This Final Rule

[[Page 48781]]

    D. Issuance of Proposed Rulemaking
    E. Advancing Health Information Exchange
    F. Use of FY 2021 Data and Methodology Modifications for the FY 
2023 IPPS and LTCH PPS Ratesetting
II. Changes to Medicare Severity Diagnosis-Related Group (MS-DRG) 
Classifications and Relative Weights
    A. Background
    B. Adoption of the MS-DRGs and MS-DRG Reclassifications
    C. FY 2023 MS-DRG Documentation and Coding Adjustment
    D. Changes to Specific MS-DRG Classifications
    E. Recalibration of the FY 2023 MS-DRG Relative Weights
    F. Add-On Payments for New Services and Technologies for FY 2023
III. Changes to the Hospital Wage Index for Acute Care Hospitals
    A. Background
    B. Worksheet S-3 Wage Data for the FY 2022 Wage Index
    C. Verification of Worksheet S-3 Wage Data
    D. Method for Computing the FY 2022 Unadjusted Wage Index
    E. Occupational Mix Adjustment to the FY 2023 Wage Index
    F. Analysis and Implementation of the Occupational Mix 
Adjustment and the FY 2023 Occupational Mix Adjusted Wage Index
    G. Application of the Rural Floor, Application of the State 
Frontier Floor, and Continuation of the Low Wage Index Hospital 
Policy, and Budget Neutrality Adjustment
    H. FY 2023 Wage Index Tables
    I. Revisions to the Wage Index Based on Hospital Redesignations 
and Reclassifications
    J. Out-Migration Adjustment Based on Commuting Patterns of 
Hospital Employees
    K. Reclassification From Urban to Rural Under Section 
1886(d)(8)(E) of the Act Implemented at 42 CFR 412.103
    L. Process for Requests for Wage Index Data Corrections
    M. Labor-Related Share for the FY 2023 Wage Index
IV. Payment Adjustment for Medicare Disproportionate Share Hospitals 
(DSHs) for FY 2023 (Sec.  412.106)
    A. General Discussion
    B. Eligibility for Empirically Justified Medicare DSH Payments 
and Uncompensated Care Payments
    C. Empirically Justified Medicare DSH Payments
    D. Uncompensated Care Payments
    E. Supplemental Payment for Indian Health Service and Tribal 
Hospitals and Puerto Rico Hospitals for FY 2023 and Subsequent 
Fiscal Years
    F. Counting Days Associated With Section 1115 Demonstrations in 
the Medicaid Fraction
V. Other Decisions and Changes to the IPPS for Operating Costs
    A. Changes in the Inpatient Hospital Updates for FY 2022 (Sec.  
412.64(d))
    B. Rural Referral Centers (RRCs)--Annual Updates to Case-Mix 
Index (CMI) and Discharge Criteria (Sec.  412.96)
    C. Payment Adjustment for Low-Volume Hospitals (Sec.  412.101)
    D. Changes in the Medicare-Dependent, Small Rural Hospital (MDH) 
Program (Sec.  412.108)
    E. Indirect Medical Education (IME) Payment Adjustment Factor 
(Sec.  412.105)
    F. Payment for Indirect and Direct Graduate Medical Education 
Costs (Sec. Sec.  412.105 and 413.75 Through 413.83)
    G. Payment Adjustment for Certain Clinical Trial and Expanded 
Access Use Immunotherapy Cases (Sec. Sec.  412.85 and 412.312)
    H. Hospital Readmissions Reduction Program: Updates and Changes 
(Sec. Sec.  412.150 Through 412.154)
    I. Hospital Value-Based Purchasing (VBP) Program: Policy Changes
    J. Hospital-Acquired Conditions (HAC) Reduction Program: Updates 
and Changes (Sec.  412.170)
    K. Rural Community Hospital Demonstration Program
VI. Changes to the IPPS for Capital-Related Costs
    A. Overview
    B. Additional Provisions
    C. Annual Update for FY 2023
VII. Changes for Hospitals Excluded From the IPPS
    A. Rate-of-Increase in Payments to Excluded Hospitals for FY 
2023
    B. Critical Access Hospitals (CAHs)
VIII. Changes to the Long-Term Care Hospital Prospective Payment 
System (LTCH PPS) for FY 2023
    A. Background of the LTCH PPS
    B. Medicare Severity Long-Term Care Diagnosis-Related Group (MS-
LTC-DRG) Classifications and Relative Weights for FY 2023
    C. Changes to the LTCH PPS Payment Rates and Other Changes to 
the LTCH PPS for FY 2023
IX. Quality Data Reporting Requirements for Specific Providers and 
Suppliers
    A. Assessment of the Impact of Climate Change and Health Equity
    B. Overarching Principles for Measuring Healthcare Quality 
Disparities Across CMS Quality Programs--Request for Information
    C. Continuing To Advance to Digital Quality Measurement and the 
Use of Fast Healthcare Interoperability Resources (FHIR) in Hospital 
Quality Programs--Request for Information
    D. Advancing the Trusted Exchange Framework and Common 
Agreement--Request for Information
    E. Hospital Inpatient Quality Reporting (IQR) Program
    F. PPS-Exempt Cancer Hospital Quality Reporting (PCHQR) Program
    G. Long-Term Care Hospital Quality Reporting Program (LTCH QRP)
    H. Changes to the Medicare Promoting Interoperability Program
X. Changes for Hospitals and Other Providers and Suppliers
    A. Codification of the Costs Incurred for Qualified and Non-
Qualified Deferred Compensation Plans
    B. Condition of Participation (CoP) Requirements for Hospitals 
and CAHs To Continue Reporting Data for COVID-19 and Influenza After 
the PHE Ends as Determined by the Secretary
    C. Request for Public Comments on IPPS Payment Adjustment for 
N95 Respirators That Are Wholly Domestically Made
XI. MedPAC Recommendations
XII. Other Required Information
    A. Publicly Available Files
    B. Collection of Information Requirements

I. Executive Summary and Background

A. Executive Summary

1. Purpose and Legal Authority
    This FY 2023 IPPS/LTCH PPS final rule makes payment and policy 
changes under the Medicare inpatient prospective payment systems (IPPS) 
for operating and capital-related costs of acute care hospitals as well 
as for certain hospitals and hospital units excluded from the IPPS. In 
addition, it makes payment and policy changes for inpatient hospital 
services provided by long-term care hospitals (LTCHs) under the long-
term care hospital prospective payment system (LTCH PPS). This final 
rule also makes policy changes to programs associated with Medicare 
IPPS hospitals, IPPS-excluded hospitals, and LTCHs. In this FY 2023 
final rule, we are implementing a permanent policy to cap wage index 
decreases as well as continuing policies to address wage index 
disparities impacting low wage index hospitals. We also are making 
changes relating to Medicare graduate medical education (GME) for 
teaching hospitals and new technology add-on payments.
    We are establishing new requirements and revising existing 
requirements for eligible hospitals and CAHs participating in the 
Medicare Promoting Interoperability Program.
    This final rule also acknowledges feedback we received on requests 
for information on health impacts due to climate change, on overarching 
principles in measuring healthcare quality disparities in hospital 
quality programs and value-based purchasing programs, the LTCH QRP, and 
on advancing the Trusted Exchange Framework and Common Agreement 
(TEFCA). We thank commenters for their feedback.
    Additionally, due to the impact of the COVID-19 PHE on measure data 
used in the Hospital VBP Program and HAC Reduction Program, we are 
finalizing our proposals to suppress several measures in both of those 
programs for purposes of FY 2023 scoring and payment adjustments. For 
transparency, we will continue to publicly report measure information 
for all measures, including suppressed measures. In addition to these 
measure suppressions

[[Page 48782]]

for the Hospital VBP Program, we are finalizing our proposal to 
implement a special scoring methodology for FY 2023 that results in 
each hospital receiving a value-based incentive payment amount that 
matches their 2 percent reduction to the base operating MS-DRG payment 
amount. Similarly, we are finalizing our proposal to suppress all six 
measures in the HAC Reduction Program for the FY 2023 program year. We 
are not finalizing our proposal to not calculate measure results or 
scores for the CMS PSI 90 measure. Although we will not calculate or 
report the CMS PSI 90 measure results for use in the HAC Reduction 
Program scoring calculations for the program year, we will still 
calculate and report CMS PSI 90 that is displayed on the main pages of 
the Care Compare tool hosted by HHS after confidentially reporting 
these results to hospitals via hospital-specific reports and a 30-day 
preview period. Additionally, we will continue to calculate and report 
measure results for the NHSN CDC HAI measures. For the FY 2023 program 
year, hospitals participating in the HAC Reduction Program will not be 
given a Total HAC score, nor will hospitals receive a payment penalty. 
We are also providing estimated and newly established performance 
standards for the Hospital VBP Program. For the Hospital Readmissions 
Reduction Program, we are resuming the use of the one measure (which 
was previously suppressed for the FY 2023 applicable period) for the FY 
2024 applicable period, and incorporating measure updates to the six 
condition/procedure measures addressed by the Hospital Readmission 
Reduction Program to account for patient history of COVID-19.
    Under various statutory authorities, we either discuss continued 
program implementation or make changes to the Medicare IPPS, the LTCH 
PPS, other related payment methodologies and programs for FY 2023 and 
subsequent fiscal years, and other policies and provisions included in 
this rule. These statutory authorities include, but are not limited to, 
the following:
     Section 1886(d) of the Social Security Act (the Act), 
which sets forth a system of payment for the operating costs of acute 
care hospital inpatient stays under Medicare Part A (Hospital 
Insurance) based on prospectively set rates. Section 1886(g) of the Act 
requires that, instead of paying for capital-related costs of inpatient 
hospital services on a reasonable cost basis, the Secretary use a 
prospective payment system (PPS).
     Section 1886(d)(1)(B) of the Act, which specifies that 
certain hospitals and hospital units are excluded from the IPPS. These 
hospitals and units are: rehabilitation hospitals and units; LTCHs; 
psychiatric hospitals and units; children's hospitals; cancer 
hospitals; extended neoplastic disease care hospitals, and hospitals 
located outside the 50 States, the District of Columbia, and Puerto 
Rico (that is, hospitals located in the U.S. Virgin Islands, Guam, the 
Northern Mariana Islands, and American Samoa). Religious nonmedical 
health care institutions (RNHCIs) are also excluded from the IPPS.
     Sections 123(a) and (c) of the BBRA (Public Law (Pub. L.) 
106-113) and section 307(b)(1) of the BIPA (Pub. L. 106-554) (as 
codified under section 1886(m)(1) of the Act), which provide for the 
development and implementation of a prospective payment system for 
payment for inpatient hospital services of LTCHs described in section 
1886(d)(1)(B)(iv) of the Act.
     Sections 1814(l), 1820, and 1834(g) of the Act, which 
specify that payments are made to critical access hospitals (CAHs) 
(that is, rural hospitals or facilities that meet certain statutory 
requirements) for inpatient and outpatient services and that these 
payments are generally based on 101 percent of reasonable cost.
     Section 1886(a)(4) of the Act, which specifies that costs 
of approved educational activities are excluded from the operating 
costs of inpatient hospital services. Hospitals with approved graduate 
medical education (GME) programs are paid for the direct costs of GME 
in accordance with section 1886(h) of the Act.
     Section 1886(b)(3)(B)(viii) of the Act, which requires the 
Secretary to reduce the applicable percentage increase that would 
otherwise apply to the standardized amount applicable to a subsection 
(d) hospital for discharges occurring in a fiscal year if the hospital 
does not submit data on measures in a form and manner, and at a time, 
specified by the Secretary.
     Section 1866(k) of the Act, which provides for the 
establishment of a quality reporting program for hospitals described in 
section 1886(d)(1)(B)(v) of the Act, referred to as ``PPS-exempt cancer 
hospitals.''
     Section 1886(o) of the Act, which requires the Secretary 
to establish a Hospital Value-Based Purchasing (VBP) Program, under 
which value-based incentive payments are made in a fiscal year to 
hospitals meeting performance standards established for a performance 
period for such fiscal year.
     Section 1886(p) of the Act, which establishes a Hospital-
Acquired Condition (HAC) Reduction Program, under which payments to 
applicable hospitals are adjusted to provide an incentive to reduce 
hospital-acquired conditions.
     Section 1886(q) of the Act, as amended by section 15002 of 
the 21st Century Cures Act, which establishes the Hospital Readmissions 
Reduction Program. Under the program, payments for discharges from an 
applicable hospital as defined under section 1886(d) of the Act will be 
reduced to account for certain excess readmissions. Section 15002 of 
the 21st Century Cures Act directs the Secretary to compare hospitals 
with respect to the number of their Medicare-Medicaid dual-eligible 
beneficiaries (dual-eligibles) in determining the extent of excess 
readmissions.
     Section 1886(r) of the Act, as added by section 3133 of 
the Affordable Care Act, which provides for a reduction to 
disproportionate share hospital (DSH) payments under section 
1886(d)(5)(F) of the Act and for a new uncompensated care payment to 
eligible hospitals. Specifically, section 1886(r) of the Act requires 
that, for fiscal year 2014 and each subsequent fiscal year, subsection 
(d) hospitals that would otherwise receive a DSH payment made under 
section 1886(d)(5)(F) of the Act will receive two separate payments: 
(1) 25 percent of the amount they previously would have received under 
section 1886(d)(5)(F) of the Act for DSH (``the empirically justified 
amount''), and (2) an additional payment for the DSH hospital's 
proportion of uncompensated care, determined as the product of three 
factors. These three factors are: (1) 75 percent of the payments that 
would otherwise be made under section 1886(d)(5)(F) of the Act; (2) 1 
minus the percent change in the percent of individuals who are 
uninsured; and (3) a hospital's uncompensated care amount relative to 
the uncompensated care amount of all DSH hospitals expressed as a 
percentage.
     Section 1886(m)(5) of the Act, which requires the 
Secretary to reduce by two percentage points the annual update to the 
standard Federal rate for discharges for a long-term care hospital 
(LTCH) during the rate year for LTCHs that do not submit data in the 
form, manner, and at a time, specified by the Secretary.
     Section 1886(m)(6) of the Act, as added by section 
1206(a)(1) of the Pathway for Sustainable Growth Rate (SGR) Reform Act 
of 2013 (Pub. L. 113-67) and amended by section 51005(a) of the 
Bipartisan Budget Act of 2018 (Pub.

[[Page 48783]]

L. 115-123), which provided for the establishment of site neutral 
payment rate criteria under the LTCH PPS, with implementation beginning 
in FY 2016. Section 51005(b) of the Bipartisan Budget Act of 2018 
amended section 1886(m)(6)(B) by adding new clause (iv), which 
specifies that the IPPS comparable amount defined in clause (ii)(I) 
shall be reduced by 4.6 percent for FYs 2018 through 2026.
     Section 1899B of the Act, as added by section 2(a) of the 
Improving Medicare Post-Acute Care Transformation Act of 2014 (IMPACT 
Act) (Pub. L. 113-185), which provides for the establishment of 
standardized data reporting for certain post-acute care providers, 
including LTCHs.
     Section 1861(e) of the Act provides the specific statutory 
authority for the hospital CoPs; section 1820(e) of the Act provides 
similar authority for CAHs. The hospital provision at section 
1861(e)(9) of the Act authorizes the Secretary to issue regulations the 
Secretary deems necessary to protect the health and safety of patients 
receiving services in those facilities; the CAH provision at section 
1820(e)(3) of the Act authorizes the Secretary to issue such other 
criteria as the Secretary may require.
2. Summary of the Major Provisions
    The following is a summary of the major provisions in this final 
rule. In general, these major provisions are being finalized as part of 
the annual update to the payment policies and payment rates, consistent 
with the applicable statutory provisions. A general summary of the 
changes in this final rule is presented in section I.D. of the preamble 
of this final rule.
a. MS-DRG Documentation and Coding Adjustment
    Section 631 of the American Taxpayer Relief Act of 2012 (ATRA, Pub. 
L. 112- 240) amended section 7(b)(1)(B) of Pub. L. 110-90 to require 
the Secretary to make a recoupment adjustment to the standardized 
amount of Medicare payments to acute care hospitals to account for 
changes in MS-DRG documentation and coding that do not reflect real 
changes in case-mix, totaling $11 billion over a 4-year period of FYs 
2014, 2015, 2016, and 2017. The FY 2014 through FY 2017 adjustments 
represented the amount of the increase in aggregate payments as a 
result of not completing the prospective adjustment authorized under 
section 7(b)(1)(A) of Public Law 110-90 until FY 2013. Prior to the 
ATRA, this amount could not have been recovered under Public Law 110-
90. Section 414 of the Medicare Access and CHIP Reauthorization Act of 
2015 (MACRA) (Pub. L. 114-10) replaced the single positive adjustment 
we intended to make in FY 2018 with a 0.5 percent positive adjustment 
to the standardized amount of Medicare payments to acute care hospitals 
for FYs 2018 through 2023. (The FY 2018 adjustment was subsequently 
adjusted to 0.4588 percent by section 15005 of the 21st Century Cures 
Act.) Therefore, for FY 2023, we are making an adjustment of + 0.5 
percent to the standardized amount.
b. Use of FY 2021 Data and Methodology Modifications for the FY 2023 
IPPS and LTCH PPS Ratesetting
    For the IPPS and LTCH PPS ratesetting, our longstanding goal is 
always to use the best available data overall. In section I.F. of the 
preamble of this final rule, we discuss our return to our historical 
practice of using the most recent data available for purposes of FY 
2023 ratesetting, including the FY 2021 MedPAR claims and FY 2020 cost 
report data, with certain modifications to our usual ratesetting 
methodologies to account for the anticipated decline in COVID-19 
hospitalizations of Medicare beneficiaries at IPPS hospitals and LTCHs 
as compared to FY 2021. As discussed in greater detail in section I.F. 
of the preamble of this final rule, we believe that it is reasonable to 
assume that some Medicare beneficiaries will continue to be 
hospitalized with COVID-19 at IPPS hospitals and LTCHs in FY 2023. 
Given this expectation, we believe it is appropriate to use FY 2021 
data, as the most recent available data during the period of the COVID-
19 PHE, for purposes of the FY 2023 IPPS and LTCH PPS ratesetting. 
However, as also discussed in greater detail in section I.F. of the 
preamble of this final rule, we believe it is reasonable to assume 
based on the information available at this time that there will be 
fewer COVID-19 hospitalizations in FY 2023 than in FY 2021. Therefore, 
we are finalizing our proposal to use the FY 2021 data for purposes of 
the FY 2023 IPPS and LTCH PPS ratesetting but with modifications to our 
usual ratesetting methodologies to account for the anticipated decline 
in COVID-19 hospitalizations of Medicare beneficiaries at IPPS 
hospitals and LTCHs as compared to FY 2021.
c. Continuation of the Low Wage Index Hospital Policy
    To help mitigate wage index disparities between high wage and low 
wage hospitals, in the FY 2020 IPPS/LTCH PPS rule (84 FR 42326 through 
42332), we adopted a policy to increase the wage index values for 
certain hospitals with low wage index values (the low wage index 
hospital policy). This policy was adopted in a budget neutral manner 
through an adjustment applied to the standardized amounts for all 
hospitals. We also indicated our intention that this policy would be 
effective for at least 4 years, beginning in FY 2020, in order to allow 
employee compensation increases implemented by these hospitals 
sufficient time to be reflected in the wage index calculation. We are 
finalizing our proposals for the low wage index hospital policy to 
continue for FY 2023, and to apply this policy in a budget neutral 
manner by applying an adjustment to the standardized amounts.
d. Permanent Cap on Wage Index Decreases
    Consistent with section 1886(d)(3)(E) of the Act, we adjust the 
IPPS standardized amounts for area differences in hospital wage levels 
by a factor (established by the Secretary) reflecting the relative 
hospital wage level in the geographic area of the hospital compared to 
the national average hospital wage level and update the wage index 
annually based on a survey of wages and wage-related costs of short-
term, acute care hospitals. As described in section III.N. of the 
preamble of this final rule, we have further considered the comments we 
received during the FY 2022 rulemaking recommending a permanent 5-
percent cap policy to prevent large year-to-year variations in wage 
index values as a means to reduce overall volatility for hospitals. 
Under the authority at sections 1886(d)(3)(E) and 1886(d)(5)(I)(i) of 
the Act, for FY 2023 and subsequent years, we proposed to apply a 5-
percent cap on any decrease to a hospital's wage index from its wage 
index in the prior FY, regardless of the circumstances causing the 
decline. That is, we proposed that a hospital's wage index for FY 2023 
would not be less than 95 percent of its final wage index for FY 2022, 
and that for subsequent years, a hospital's wage index would not be 
less than 95 percent of its final wage index for the prior FY. We also 
proposed to apply the proposed wage index cap policy in a budget 
neutral manner through a national adjustment to the standardized amount 
under our authority in sections 1886(d)(3)(E) and 1886(d)(5)(I)(i) of 
the Act. After consideration of the public comments received, we are 
finalizing these proposals without modification.
e. Application of the Rural Floor
    As discussed in section III.G.1. of the preamble of this final 
rule, based on the

[[Page 48784]]

district court's decision in Citrus HMA, LLC, d/b/a Seven Rivers 
Regional Medical Center v. Becerra, No. 1:20-cv-00707 (D.D.C.) 
(hereafter referred to as Citrus) and the comments we received, we are 
not finalizing our rural floor wage index policy as proposed, which 
would have excluded Sec.  412.103 hospitals from the calculation of the 
rural floor and from the calculation of ``the wage index for rural 
areas in the State in which the county is located'' as referred to in 
section 1886(d)(8)(C)(iii) of the Act. Rather, we are finalizing a 
policy that calculates the rural floor as it was calculated before FY 
2020. For FY 2023 and subsequent years, we are finalizing a policy to 
include the wage data of hospitals that have reclassified from urban to 
rural under section 1886(d)(8)(E) of the Act (as implemented in the 
regulations at Sec.  412.103) and have no additional form of 
reclassification (MGCRB or Lugar) in the calculation of the rural 
floor, and to include the wage data of such hospitals in the 
calculation of ``the wage index for rural areas in the State in which 
the county is located'' as referred to in section 1886(d)(8)(C)(iii) of 
the Act.
f. DSH Payment Adjustment and Additional Payment for Uncompensated Care
    Under section 1886(r) of the Act, which was added by section 3133 
of the Affordable Care Act, starting in FY 2014, Medicare 
disproportionate share hospitals (DSHs) receive 25 percent of the 
amount they previously would have received under the statutory formula 
for Medicare DSH payments in section 1886(d)(5)(F) of the Act. The 
remaining amount, equal to 75 percent of the amount that otherwise 
would have been paid as Medicare DSH payments, is paid as additional 
payments after the amount is reduced for changes in the percentage of 
individuals that are uninsured. Each Medicare DSH will receive an 
additional payment based on its share of the total amount of 
uncompensated care for all Medicare DSHs for a given time period.
    In this final rule, we are updating our estimates of the three 
factors used to determine uncompensated care payments for FY 2023. We 
are also continuing to use uninsured estimates produced by CMS' Office 
of the Actuary (OACT) as part of the development of the National Health 
Expenditure Accounts (NHEA) in conjunction with more recently available 
data in the calculation of Factor 2. For FY 2023, we are using the 2 
most recent years of audited data on uncompensated care costs from 
Worksheet S-10 of the FY 2018 cost reports and the FY 2019 cost reports 
to calculate Factor 3 in the uncompensated care payment methodology for 
all eligible hospitals. In addition, for FY 2024 and subsequent fiscal 
years, we are using a 3-year average of the data on uncompensated care 
costs from Worksheet S-10 for the 3 most recent fiscal years for which 
audited data are available. Beginning in FY 2023, we are discontinuing 
the use of low-income insured days as a proxy for uncompensated care to 
determine Factor 3 for Indian Health Service (IHS) and Tribal hospitals 
and hospitals located in Puerto Rico. In addition, we are implementing 
certain methodological changes for calculating Factor 3 for FY 2023 and 
subsequent fiscal years.
    We recognize that discontinuing the use of the low-income insured 
days proxy to calculate uncompensated care payments for Indian Health 
Service (IHS) and Tribal hospitals and hospitals located in Puerto Rico 
could result in a significant financial disruption for these hospitals. 
Accordingly, we are using our exceptions and adjustments authority 
under section 1886(d)(5)(I) of the Act to establish a new supplemental 
payment for IHS and Tribal hospitals and hospitals located in Puerto 
Rico, beginning in FY 2023.
    As noted in section IV.F. of this final rule, we are not moving 
forward with the proposed revisions to the regulations relating to the 
treatment of section 1115 demonstration days for purposes of the DSH 
adjustment in this final rule. We expect to revisit the issue of 
section 1115 demonstration days in future rulemaking, and we encourage 
interested parties to review any future proposal on this issue and to 
submit their comments at that time.
g. Changes to GME Payments Based on Milton S. Hershey Medical Center, 
et al. v. Becerra Litigation
    On May 17, 2021, the U.S. District Court for the District of 
Columbia ruled against CMS's method of calculating direct GME payments 
to teaching hospitals when those hospitals' weighted full-time 
equivalent (FTE) counts exceed their direct GME FTE cap. In Milton S. 
Hershey Medical Center, et al. v. Becerra, the court ordered CMS to 
recalculate reimbursement owed, holding that CMS's regulation 
impermissibly modified the statutory weighting factors. The plaintiffs 
in these consolidated cases alleged that as far back as 2005, the 
proportional reduction that CMS applied to the weighted FTE count when 
the weighted FTE count exceeded the FTE cap conflicted with the 
Medicare statute, and it was an arbitrary and capricious exercise of 
agency discretion under the Administrative Procedure Act. The court 
held that the proportional reduction methodology impermissibly modified 
the weighting factors statutorily assigned to residents and fellows. 
The court granted the motion for summary judgment to plaintiffs' 
motions, denied defendant's, and remanded to the Agency so that it 
could recalculate plaintiffs' reimbursement payments consistent with 
the court's opinion.
    After reviewing the statutory language regarding the direct GME FTE 
cap and the court's opinion, we have decided implement a modified 
policy to be applied prospectively for all teaching hospitals, as well 
as retroactively to the providers and cost years in Hershey and certain 
other providers as described in greater detail in section V.F.2. of the 
preamble of this final rule. The modified policy will address 
situations for applying the FTE cap when a hospital's weighted FTE 
count is greater than its FTE cap, but would not reduce the weighting 
factor of residents that are beyond their initial residency period to 
an amount less than 0.5. Specifically, effective for cost reporting 
periods beginning on or after October 1, 2001, we are specifying that 
if the hospital's unweighted number of FTE residents exceeds the FTE 
cap, and the number of weighted FTE residents also exceeds that FTE 
cap, the respective primary care and obstetrics and gynecology weighted 
FTE counts and other weighted FTE counts are adjusted to make the total 
weighted FTE count equal the FTE cap. If the number of weighted FTE 
residents does not exceed that FTE cap, then the allowable weighted FTE 
count for direct GME payment is the actual weighted FTE count.
h. Reduction of Hospital Payments for Excess Readmissions
    We are making changes to policies for the Hospital Readmissions 
Reduction Program, which was established under section 1886(q) of the 
Act, as amended by section 15002 of the 21st Century Cures Act. The 
Hospital Readmissions Reduction Program requires a reduction to a 
hospital's base operating MS-DRG payment to account for excess 
readmissions of selected applicable conditions. For FY 2023, the 
reduction is based on a hospital's risk-adjusted readmission rate 
during a multi-year period for acute myocardial infarction (AMI), heart 
failure (HF), chronic obstructive pulmonary disease (COPD), elective 
primary total hip arthroplasty/total knee arthroplasty (THA/TKA), and 
coronary artery bypass graft (CABG)

[[Page 48785]]

surgery.\1\ In this FY 2023 IPPS/LTCH PPS final rule, we are discussing 
the following policies: (1) resuming use of the Hospital 30-Day, All-
Cause, Risk-Standardized Readmission Rate (RSRR) following Pneumonia 
Hospitalization measure (NQF #0506) for the FY 2024 program year; (2) 
modification of the Hospital 30-Day, All-Cause, Risk-Standardized 
Readmission Rate (RSRR) following Pneumonia Hospitalization measure 
(NQF #0506) to exclude patients with COVID-19 diagnosis present on 
admission from the measure numerator (outcome) and denominator 
(cohort),\2\ beginning with the Hospital Specific Reports (HSRs) for 
the FY 2023 program year; and (3) modification of all six condition/
procedure specific measures to include a covariate adjustment for 
patient history of COVID-19 within 12 months prior to the index 
admission beginning with the FY 2023 program year. In the FY 2023 IPPS/
LTCH PPS proposed rule we also sought comment on updating the Hospital 
Readmissions Reduction Program to incorporate provider performance for 
socially at-risk populations.
---------------------------------------------------------------------------

    \1\ We note that in the FY 2023 IPPS/LTCH PPS proposed rule we 
described the policy for FY 2017 and subsequent years, without 
reference to flexibility due to the COVID-19 PHE. We have updated 
this information to describe the policy for FY 2023.
    \2\ We note that in the FY 2023 IPPS/LTCH PPS proposed rule (87 
FR 28113) we inadvertently omitted reference to removing COVID-19 
diagnosed patients from the numerator. We have corrected this 
omission here.
---------------------------------------------------------------------------

i. Hospital Value-Based Purchasing (VBP) Program
    Section 1886(o) of the Act requires the Secretary to establish a 
Hospital VBP Program under which value-based incentive payments are 
made in a fiscal year to hospitals based on their performance on 
measures established for a performance period for such fiscal year. In 
this final rule, we are finalizing our proposals to: (1) suppress the 
Hospital Consumer Assessment of Healthcare Providers and Systems 
(HCAHPS) and five Hospital-Acquired Infection (HAI) measures for the FY 
2023 program year; and (2) update the baseline periods for certain 
measures for the FY 2025 program year. We are also finalizing our 
proposal to revise the scoring and payment methodology for the FY 2023 
program year such that hospitals will not receive Total Performance 
Scores (TPSs). Additionally, we are finalizing our proposal to award 
each hospital a payment incentive multiplier that results in a value-
based incentive payment that is equal to the amount withheld for the 
fiscal year (2 percent). We note that we are also announcing technical 
updates to the measures in the Clinical Outcomes Domain.
j. Hospital-Acquired Condition (HAC) Reduction Program
    In this FY 2023 IPPS/LTCH PPS final rule we are finalizing several 
changes to the HAC Reduction Program, which was established under 
section 1886(p) of the Act, to provide an incentive to hospitals to 
reduce the incidence of hospital-acquired conditions. We refer readers 
to the FY 2022 IPPS/LTCH PPS final rule for further details on our 
measure suppression policy (86 FR 45301 through 45304). In this FY 2023 
IPPS/LTCH PPS final rule, we are not finalizing our proposal to not 
calculate or report measure results for the CMS PSI 90 measure for the 
FY 2023 HAC Reduction Program. Although we will not calculate or report 
CMS PSI 90 measure results for use in the HAC Reduction Program scoring 
calculations for the program year, we will still calculate and report 
CMS PSI 90 that is displayed on the main pages of the Compare tool 
hosted by HHS after confidentially reporting these results to hospitals 
via CMS PSI 90 specific HSRs and a 30-day preview period. We will 
continue to calculate and report measure results for the NHSN CDC HAI 
measures.
    In this FY 2023 IPPS/LTCH PPS final rule, we are finalizing our 
proposals to: (1) suppress the CMS PSI 90 measure and the five CDC NHSN 
HAI measures from the calculation of measure scores and the Total HAC 
Score, thereby not penalizing any hospital under the HAC Reduction 
Program FY 2023 program year; (2) suppress CY 2021 CDC NHSN HAI 
measures data from the FY 2024 HAC Reduction Program Year; (3) update 
the measure specification to the minimum volume threshold for the CMS 
PSI 90 measure beginning with the FY 2023 program year; (4) update the 
measure specifications to risk-adjust for COVID-19 diagnosis in the CMS 
PSI 90 measure beginning with the FY 2024 HAC Reduction Program Year; 
and (5) update the NHSN CDC HAI data submission requirements for newly 
opened hospitals beginning in the FY 2024 HAC Reduction Program.
    In this FY 2023 IPPS/LTCH PPS final rule, we acknowledge feedback 
we received on Requests for Information from stakeholders on two 
topics: (1) the potential adoption of two digital National Healthcare 
Safety Network (NHSN) measures: the NHSN Healthcare-associated 
Clostridioides difficile Infection Outcome measure and NHSN Hospital-
Onset Bacteremia & Fungemia Outcome measure; and (2) on overarching 
principles for measuring healthcare quality disparities across CMS 
Quality Programs. In the FY 2023 IPPS/LTCH PPS proposed rule and this 
final rule, we also clarified the removal of the no mapped location 
policy beginning with the FY 2023 program year.
k. Hospital Inpatient Quality Reporting (IQR) Program
    Under section 1886(b)(3)(B)(viii) of the Act, subsection (d) 
hospitals are required to report data on measures selected by the 
Secretary for a fiscal year in order to receive the full annual 
percentage increase.
    In this FY 2023 IPPS/LTCH PPS final rule, we are finalizing several 
changes to the Hospital IQR Program. We are adopting 10 new measures: 
(1) Hospital Commitment to Health Equity beginning with the CY 2023 
reporting period/FY 2025 payment determination; (2) Screening for 
Social Drivers of Health beginning with voluntary reporting for the CY 
2023 reporting period and mandatory reporting beginning with the CY 
2024 reporting period/FY 2026 payment determination; (3) Screen 
Positive Rate for Social Drivers of Health beginning with voluntary 
reporting for the CY 2023 reporting period and mandatory reporting 
beginning with the CY 2024 reporting period/FY 2026 payment 
determination; (4) Cesarean Birth electronic clinical quality measure 
(eCQM) with inclusion in the eCQM measure set beginning with the CY 
2023 reporting period/FY 2025 payment determination, and mandatory 
reporting beginning with the CY 2024 reporting period/FY 2026 payment 
determination; (5) Severe Obstetric Complications eCQM with inclusion 
in the eCQM measure set beginning with the CY 2023 reporting period/FY 
2025 payment determination, and mandatory reporting beginning with the 
CY 2024 reporting period/FY 2026 payment determination; (6) Hospital-
Harm--Opioid-Related Adverse Events eCQM (NQF #3501e) inclusion in the 
eCQM measure set beginning with the CY 2024 reporting period/FY 2026 
payment determination; (7) Global Malnutrition Composite Score eCQM 
(NQF #3592e) inclusion in the eCQM measure set beginning with the CY 
2024 reporting period/FY 2026 payment determination; (8) Hospital-
Level, Risk Standardized Patient-Reported Outcomes Performance Measure 
Following Elective Primary Total Hip Arthroplasty (THA) and/or Total 
Knee Arthroplasty (TKA) (NQF #3559) beginning with two voluntary 
periods, followed by mandatory reporting for the

[[Page 48786]]

reporting period which runs from July 1, 2025 through June 30, 2026, 
impacting the FY 2028 payment determination; (9) Medicare Spending Per 
Beneficiary (MSPB) Hospital measure (NQF #2158) beginning with the FY 
2024 payment determination; and (10) Hospital-Level Risk-Standardized 
Complication Rate (RSCR) Following Elective Primary THA/TKA (NQF #1550) 
beginning with the FY 2024 payment determination. We are refining two 
current measures beginning with the FY 2024 payment determination: (1) 
Hospital[hyphen]Level, Risk[hyphen]Standardized Payment Associated with 
an Episode-of-Care for Primary Elective THA/TKA measure; and (2) Excess 
Days in Acute Care (EDAC) After Hospitalization for Acute Myocardial 
Infarction (AMI) measure (NQF #2881). In this FY 2023 IPPS/LTCH PPS 
final rule, we acknowledge feedback we received on the potential future 
development and inclusion of two National Healthcare Safety Network 
(NHSN) measures: (1) Healthcare-Associated Clostridioides difficile 
Infection Outcome; and (2) Hospital-Onset Bacteremia & Fungemia 
Outcome. We thank commenters for their feedback.
    We are finalizing changes to current policies related to eCQMs and 
hybrid measures: (1) Modification of the eCQM reporting and submission 
requirements to increase the number of eCQMs to be reported beginning 
with the CY 2024 reporting period/FY 2026 payment determination; (2) 
removal of the zero denominator declarations and case threshold 
exemption policies for hybrid measures beginning with the FY 2026 
payment determination; (3) adoption of data submission and reporting 
requirements for patient-reported outcome-based performance measures 
(PRO-PMs) beginning with the FY 2026 payment determination; and (4) 
modification of the eCQM validation policy to increase the requirement 
from 75 percent to 100 percent of requested medical records, beginning 
with the FY 2025 payment determination.
    With respect to public reporting, we are establishing a hospital 
designation related to maternity care to be publicly-reported on a 
public-facing website beginning in Fall 2023. In the FY 2023 IPPS/PPS 
LTCH PPS proposed rule, we sought comments on other potential 
associated activities regarding this designation (87 FR 28549 through 
28550). Additionally, we sought comments on ongoing ways we can advance 
digital quality measurement and use of Fast Healthcare Interoperability 
Resources (FHIR) (87 FR 28486 through 28489). We thank commenters for 
their feedback.
l. PPS-Exempt Cancer Hospital Quality Reporting Program
    Section 1866(k)(1) of the Act requires, for purposes of FY 2014 and 
each subsequent fiscal year, that a hospital described in section 
1886(d)(1)(B)(v) of the Act (a PPS-exempt cancer hospital, or a PCH) 
submit data in accordance with section 1866(k)(2) of the Act with 
respect to such fiscal year. There is no financial impact to PCH 
Medicare payment if a PCH does not participate.
    In this FY 2023 IPPS/LTCH PPS final rule, we are finalizing our 
proposal to adopt a patient safety exception into the measure removal 
policy. We are also finalizing our proposal to begin public display of 
the 30-Day Unplanned Readmissions for Cancer Patients measure (NQF 
#3188) (PCH-36). We are finalizing with modification our proposal to 
begin public display of the Proportion of Patients Who Died from Cancer 
Receiving Chemotherapy in the Last 14 Days of Life measure (NQF #0210) 
(PCH-32), the Proportion of Patients Who Died from Cancer Not Admitted 
to Hospice measure (NQF #0215) (PCH-34), the Proportion of Patients Who 
Died from Cancer Admitted to the ICU in the Last 30 Days of Life 
measure (NQF #0213) (PCH-33), and the Proportion of Patients Who Died 
from Cancer Admitted to Hospice for Less Than Three Days measure (NQF 
#0216) (PCH-35). In addition, along with the Hospital IQR and HAC 
Reduction Programs, we respond to comments received on our request for 
comment on the potential adoption of two digital National Healthcare 
Safety Network (NHSN) measures: the NHSN Healthcare-associated 
Clostridioides difficile Infection Outcome measure and NHSN Hospital-
Onset Bacteremia and Fungemia Outcome measure.
m. Medicare Promoting Interoperability Program
    For CY 2023, we are finalizing several proposed changes to the 
Medicare Promoting Interoperability Program. Specifically, we are: (1) 
requiring the Electronic Prescribing Objective's Query of Prescription 
Drug Monitoring Program (PDMP) measure while maintaining the associated 
points at 10 points beginning with the EHR reporting period in CY 2023; 
(2) expanding the Query of PDMP measure to not only include Schedule II 
opioids but also Schedule III and IV drugs beginning with the CY 2023 
EHR reporting period and are adding exclusions; (3) adding a new Health 
Information Exchange (HIE) Objective option, the Enabling Exchange 
under the Trusted Exchange Framework and Common Agreement (TEFCA) 
measure (requiring a yes/no response), as an optional alternative to 
fulfill the objective, beginning with the CY 2023 EHR reporting period; 
(4) modifying the Public Health and Clinical Data Exchange Objective by 
adding an Antibiotic Use and Antibiotic Resistance (AUR) measure in 
addition to the current four required measures (Syndromic Surveillance 
Reporting, Immunization Registry Reporting, Electronic Case Reporting, 
and Electronic Reportable Laboratory Result Reporting) beginning with 
the CY 2024 EHR reporting period; (5) consolidating the current options 
from three to two levels of active engagement for the Public Health and 
Clinical Data Exchange Objective, requiring the reporting of the active 
engagement option selected for the measures under the objective 
beginning with the CY 2023 EHR reporting period, and modifying the 
amount of time spent at the option 1 level of active engagement (pre-
production and validation) to one EHR reporting period beginning with 
the CY 2024 EHR reporting period; (6) modifying the scoring methodology 
for the Medicare Promoting Interoperability Program beginning in CY 
2023; (7) instituting public reporting of certain Medicare Promoting 
Interoperability Program data beginning with the CY 2023 EHR reporting 
period; (8) removing regulation text for the objectives and measures in 
the Medicare Promoting Interoperability Program from paragraph (e) 
under 42 CFR 495.24 and adding new paragraph (f) beginning in CY 2023; 
and (9) adopting two new eCQMs in the Medicare Promoting 
Interoperability Program's eCQM measure set beginning with the CY 2023 
reporting period, two new eCQMs in the Medicare Promoting 
Interoperability Program's eCQM measure set beginning with the CY 2024 
reporting period, and modifying the eCQM data reporting and submission 
requirements to increase the number of eCQMs required to be reported 
and the total number of eCQMs to be reported beginning with the CY 2024 
reporting period, which is in alignment with the eCQM updates finalized 
for the Hospital IQR Program.
n. Condition of Participation (CoP) Requirements for Hospitals and CAHs 
to Continue Reporting Data for COVID-19 and Influenza After the PHE 
ends as Determined by the Secretary
    In this final rule, we are revising the hospital and CAH infection 
prevention and control CoP requirements to continue COVID-19-related 
reporting requirements commencing either upon the conclusion of the 
current COVID-19 PHE declaration or the effective date of

[[Page 48787]]

this proposed rule, whichever is later, and lasting until April 30, 
2024 (unless the Secretary determines an earlier end date). We have 
withdrawn our proposal to establish additional data reporting 
requirements to address future PHEs related to epidemics and infectious 
diseases.
3. Summary of Costs and Benefits
    The following table provides a summary of the costs, savings, and 
benefits associated with the major provisions described in section 
I.A.3. of the preamble of this final rule.

[[Page 48788]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.000


[[Page 48789]]


[GRAPHIC] [TIFF OMITTED] TR10AU22.001


[[Page 48790]]


[GRAPHIC] [TIFF OMITTED] TR10AU22.002


[[Page 48791]]



B. Background Summary

1. Acute Care Hospital Inpatient Prospective Payment System (IPPS)
    Section 1886(d) of the Act sets forth a system of payment for the 
operating costs of acute care hospital inpatient stays under Medicare 
Part A (Hospital Insurance) based on prospectively set rates. Section 
1886(g) of the Act requires the Secretary to use a prospective payment 
system (PPS) to pay for the capital-related costs of inpatient hospital 
services for these ``subsection (d) hospitals.'' Under these PPSs, 
Medicare payment for hospital inpatient operating and capital-related 
costs is made at predetermined, specific rates for each hospital 
discharge. Discharges are classified according to a list of diagnosis-
related groups (DRGs).
    The base payment rate is comprised of a standardized amount that is 
divided into a labor-related share and a nonlabor-related share. The 
labor-related share is adjusted by the wage index applicable to the 
area where the hospital is located. If the hospital is located in 
Alaska or Hawaii, the nonlabor-related share is adjusted by a cost-of-
living adjustment factor. This base payment rate is multiplied by the 
DRG relative weight.
    If the hospital treats a high percentage of certain low-income 
patients, it receives a percentage add-on payment applied to the DRG-
adjusted base payment rate. This add-on payment, known as the 
disproportionate share hospital (DSH) adjustment, provides for a 
percentage increase in Medicare payments to hospitals that qualify 
under either of two statutory formulas designed to identify hospitals 
that serve a disproportionate share of low-income patients. For 
qualifying hospitals, the amount of this adjustment varies based on the 
outcome of the statutory calculations. The Affordable Care Act revised 
the Medicare DSH payment methodology and provides for a new additional 
Medicare payment beginning on October 1, 2013, that considers the 
amount of uncompensated care furnished by the hospital relative to all 
other qualifying hospitals.
    If the hospital is training residents in an approved residency 
program(s), it receives a percentage add-on payment for each case paid 
under the IPPS, known as the indirect medical education (IME) 
adjustment. This percentage varies, depending on the ratio of residents 
to beds.
    Additional payments may be made for cases that involve new 
technologies or medical services that have been approved for special 
add-on payments. In general, to qualify, a new technology or medical 
service must demonstrate that it is a substantial clinical improvement 
over technologies or services otherwise available, and that, absent an 
add-on payment, it would be inadequately paid under the regular DRG 
payment. In addition, certain transformative new devices and certain 
antimicrobial products may qualify under an alternative inpatient new 
technology add-on payment pathway by demonstrating that, absent an add-
on payment, they would be inadequately paid under the regular DRG 
payment.
    The costs incurred by the hospital for a case are evaluated to 
determine whether the hospital is eligible for an additional payment as 
an outlier case. This additional payment is designed to protect the 
hospital from large financial losses due to unusually expensive cases. 
Any eligible outlier payment is added to the DRG-adjusted base payment 
rate, plus any DSH, IME, and new technology or medical service add-on 
adjustments and, beginning in FY 2023 for IHS and Tribal hospitals and 
hospitals located in Puerto Rico, the new supplemental payment.
    Although payments to most hospitals under the IPPS are made on the 
basis of the standardized amounts, some categories of hospitals are 
paid in whole or in part based on their hospital-specific rate, which 
is determined from their costs in a base year. For example, sole 
community hospitals (SCHs) receive the higher of a hospital-specific 
rate based on their costs in a base year (the highest of FY 1982, FY 
1987, FY 1996, or FY 2006) or the IPPS Federal rate based on the 
standardized amount. SCHs are the sole source of care in their areas. 
Specifically, section 1886(d)(5)(D)(iii) of the Act defines an SCH as a 
hospital that is located more than 35 road miles from another hospital 
or that, by reason of factors such as an isolated location, weather 
conditions, travel conditions, or absence of other like hospitals (as 
determined by the Secretary), is the sole source of hospital inpatient 
services reasonably available to Medicare beneficiaries. In addition, 
certain rural hospitals previously designated by the Secretary as 
essential access community hospitals are considered SCHs.
    Under current law, the Medicare-dependent, small rural hospital 
(MDH) program is effective through FY 2022. For discharges occurring on 
or after October 1, 2007, but before October 1, 2022, an MDH receives 
the higher of the Federal rate or the Federal rate plus 75 percent of 
the amount by which the Federal rate is exceeded by the highest of its 
FY 1982, FY 1987, or FY 2002 hospital-specific rate. MDHs are a major 
source of care for Medicare beneficiaries in their areas. Section 
1886(d)(5)(G)(iv) of the Act defines an MDH as a hospital that is 
located in a rural area (or, as amended by the Bipartisan Budget Act of 
2018, a hospital located in a State with no rural area that meets 
certain statutory criteria), has not more than 100 beds, is not an SCH, 
and has a high percentage of Medicare discharges (not less than 60 
percent of its inpatient days or discharges in its cost reporting year 
beginning in FY 1987 or in two of its three most recently settled 
Medicare cost reporting years). As section 50205 of the Bipartisan 
Budget Act extended the MDH program through FY 2022 only, for FY 2023, 
beginning on October 1, 2022, the MDH program will no longer be in 
effect absent a change in law. Because the MDH program is not 
authorized by statute beyond September 30, 2022, beginning October 1, 
2022, all hospitals that previously qualified for MDH status under 
section 1886(d)(5)(G) of the Act will no longer have MDH status and 
will be paid based on the IPPS Federal rate.
    Section 1886(g) of the Act requires the Secretary to pay for the 
capital-related costs of inpatient hospital services in accordance with 
a prospective payment system established by the Secretary. The basic 
methodology for determining capital prospective payments is set forth 
in our regulations at 42 CFR 412.308 and 412.312. Under the capital 
IPPS, payments are adjusted by the same DRG for the case as they are 
under the operating IPPS. Capital IPPS payments are also adjusted for 
IME and DSH, similar to the adjustments made under the operating IPPS. 
In addition, hospitals may receive outlier payments for those cases 
that have unusually high costs.
    The existing regulations governing payments to hospitals under the 
IPPS are located in 42 CFR part 412, subparts A through M.
2. Hospitals and Hospital Units Excluded From the IPPS
    Under section 1886(d)(1)(B) of the Act, as amended, certain 
hospitals and hospital units are excluded from the IPPS. These 
hospitals and units are: Inpatient rehabilitation facility (IRF) 
hospitals and units; long-term care hospitals (LTCHs); psychiatric 
hospitals and units; children's hospitals; cancer hospitals; extended 
neoplastic disease care hospitals, and hospitals located outside the 50 
States, the District of Columbia, and Puerto Rico (that is, hospitals 
located in the U.S. Virgin Islands, Guam, the Northern Mariana Islands, 
and American Samoa). Religious nonmedical health care

[[Page 48792]]

institutions (RNHCIs) are also excluded from the IPPS. Various sections 
of the Balanced Budget Act of 1997 (BBA) (Pub. L. 105-33), the 
Medicare, Medicaid and SCHIP [State Children's Health Insurance 
Program] Balanced Budget Refinement Act of 1999 (BBRA, Pub. L. 106-
113), and the Medicare, Medicaid, and SCHIP Benefits Improvement and 
Protection Act of 2000 (BIPA, Pub. L. 106-554) provide for the 
implementation of PPSs for IRF hospitals and units, LTCHs, and 
psychiatric hospitals and units (referred to as inpatient psychiatric 
facilities (IPFs)). (We note that the annual updates to the LTCH PPS 
are included along with the IPPS annual update in this document. 
Updates to the IRF PPS and IPF PPS are issued as separate documents.) 
Children's hospitals, cancer hospitals, hospitals located outside the 
50 States, the District of Columbia, and Puerto Rico (that is, 
hospitals located in the U.S. Virgin Islands, Guam, the Northern 
Mariana Islands, and American Samoa), and RNHCIs continue to be paid 
solely under a reasonable cost-based system, subject to a rate-of-
increase ceiling on inpatient operating costs. Similarly, extended 
neoplastic disease care hospitals are paid on a reasonable cost basis, 
subject to a rate-of-increase ceiling on inpatient operating costs.
    The existing regulations governing payments to excluded hospitals 
and hospital units are located in 42 CFR parts 412 and 413.
3. Long-Term Care Hospital Prospective Payment System (LTCH PPS)
    The Medicare prospective payment system (PPS) for LTCHs applies to 
hospitals described in section 1886(d)(1)(B)(iv) of the Act, effective 
for cost reporting periods beginning on or after October 1, 2002. The 
LTCH PPS was established under the authority of sections 123 of the 
BBRA and section 307(b) of the BIPA (as codified under section 
1886(m)(1) of the Act). Section 1206(a) of the Pathway for SGR Reform 
Act of 2013 (Pub. L. 113-67) established the site neutral payment rate 
under the LTCH PPS, which made the LTCH PPS a dual rate payment system 
beginning in FY 2016. Under this statute, effective for LTCH's cost 
reporting periods beginning in FY 2016 cost reporting period, LTCHs are 
generally paid for discharges at the site neutral payment rate unless 
the discharge meets the patient criteria for payment at the LTCH PPS 
standard Federal payment rate. The existing regulations governing 
payment under the LTCH PPS are located in 42 CFR part 412, subpart O. 
Beginning October 1, 2009, we issue the annual updates to the LTCH PPS 
in the same documents that update the IPPS.
4. Critical Access Hospitals (CAHs)
    Under sections 1814(l), 1820, and 1834(g) of the Act, payments made 
to critical access hospitals (CAHs) (that is, rural hospitals or 
facilities that meet certain statutory requirements) for inpatient and 
outpatient services are generally based on 101 percent of reasonable 
cost. Reasonable cost is determined under the provisions of section 
1861(v) of the Act and existing regulations under 42 CFR part 413.
5. Payments for Graduate Medical Education (GME)
    Under section 1886(a)(4) of the Act, costs of approved educational 
activities are excluded from the operating costs of inpatient hospital 
services. Hospitals with approved graduate medical education (GME) 
programs are paid for the direct costs of GME in accordance with 
section 1886(h) of the Act. The amount of payment for direct GME costs 
for a cost reporting period is based on the hospital's number of 
residents in that period and the hospital's costs per resident in a 
base year. The existing regulations governing payments to the various 
types of hospitals are located in 42 CFR part 413.

C. Summary of Provisions of Recent Legislation Implemented in This 
Final Rule

1. The Medicare Access and CHIP Reauthorization Act of 2015 (Pub. L. 
114-10)
    Section 414 of the Medicare Access and CHIP Reauthorization Act of 
2015 (MACRA, Pub. L. 114-10) specifies a 0.5 percent positive 
adjustment to the standardized amount of Medicare payments to acute 
care hospitals for FYs 2018 through 2023. These adjustments follow the 
recoupment adjustment to the standardized amounts under section 1886(d) 
of the Act based upon the Secretary's estimates for discharges 
occurring from FYs 2014 through 2017 to fully offset $11 billion, in 
accordance with section 631 of the ATRA. The FY 2018 adjustment was 
subsequently adjusted to 0.4588 percent by section 15005 of the 21st 
Century Cures Act.

D. Issuance of Proposed Rulemaking

    In the FY 2023 IPPS/LTCH PPS proposed rule appearing in the May 10, 
2022 Federal Register (87 FR 28108), we set forth proposed payment and 
policy changes to the Medicare IPPS for FY 2023 operating costs and 
capital-related costs of acute care hospitals and certain hospitals and 
hospital units that are excluded from IPPS. In addition, we set forth 
proposed changes to the payment rates, factors, and other payment and 
policy-related changes to programs associated with payment rate 
policies under the LTCH PPS for FY 2023.
    The following is a general summary of the changes that we proposed 
to make.
1. Proposed Changes to MS-DRG Classifications and Recalibrations of 
Relative Weights
    In section II. of the preamble of the proposed rule, we include the 
following:
     Proposed changes to MS-DRG classifications based on our 
yearly review for FY 2023.
     Proposed adjustment to the standardized amounts under 
section 1886(d) of the Act for FY 2023 in accordance with the 
amendments made to section 7(b)(1)(B) of Public Law 110-90 by section 
414 of the MACRA.
     Proposed recalibration of the MS-DRG relative weights, 
including a proposed 10-percent cap on decreases in an MS-DRG relative 
weight from one fiscal year to the next.
     A discussion of the proposed FY 2023 status of new 
technologies approved for add-on payments for FY 2022, a presentation 
of our evaluation and analysis of the FY 2023 applicants for add-on 
payments for high-cost new medical services and technologies (including 
public input, as directed by Pub. L. 108-173, obtained in a town hall 
meeting) for applications not submitted under an alternative pathway, 
and a discussion of the proposed status of FY 2023 new technology 
applicants under the alternative pathways for certain medical devices 
and certain antimicrobial products.
     A proposal to use National Drug Codes (NDCs) to identify 
cases involving use of therapeutic agents approved for new technology 
add-on payments.
     A proposal to publicly post online future applications for 
new technology add-on payments. Specifically, beginning with the FY 
2024 application cycle, we proposed to post online the completed 
application forms and certain related materials and updated application 
information submitted subsequent to the initial application submission 
for new technology add-on payments, with the exception of certain cost 
and volume information and certain additional materials (as discussed 
more fully in section II.F.9. of the proposed rule), no later than the 
issuance of the proposed rule.

[[Page 48793]]

2. Proposed Changes to the Hospital Wage Index for Acute Care Hospitals
    In section III. of the preamble of the proposed rule, we proposed 
to make revisions to the wage index for acute care hospitals and the 
annual update of the wage data. Specific issues addressed include, but 
were not limited to, the following:
     The proposed FY 2023 wage index update using wage data 
from cost reporting periods beginning in FY 2019.
     Calculation, analysis, and implementation of the proposed 
occupational mix adjustment to the wage index for acute care hospitals 
for FY 2023 based on the 2019 Occupational Mix Survey.
     Proposed application of the rural, imputed and frontier 
State floors, and continuation of the low wage index hospital policy.
     Proposed revisions to the wage index for acute care 
hospitals, based on hospital redesignations and reclassifications under 
sections 1886(d)(8)(B), (d)(8)(E), and (d)(10) of the Act.
     Proposed adjustment to the wage index for acute care 
hospitals for FY 2023 based on commuting patterns of hospital employees 
who reside in a county and work in a different area with a higher wage 
index.
     Proposed permanent cap on annual wage index decreases.
     Proposed labor-related share for the proposed FY 2023 wage 
index.
3. Other Decisions and Proposed Changes to the IPPS for Operating Costs
    In section V. of the preamble of the proposed rule, we discuss 
proposed changes or clarifications of a number of the provisions of the 
regulations in 42 CFR parts 412 and 413, including the following:
     Proposed inpatient hospital update for FY 2023.
     Proposed updated national and regional case-mix values and 
discharges for purposes of determining RRC status.
     Proposed payment adjustment for low-volume hospitals for 
FY 2023 and subsequent years.
     The statutorily required IME adjustment factor for FY 
2023.
     Proposed changes to the methodologies for determining 
Medicare DSH payments and the additional payments for uncompensated 
care.
     Proposed new supplemental payment for IHS/Tribal and 
Puerto Rico hospitals.
     Proposed revisions to the regulations regarding the 
counting of days associated with section 1115 demonstrations in the 
Medicaid fraction.
     Discussion of statutory expiration of the MDH program at 
the end of FY 2022.
     Proposed requirements for payment adjustments under the 
Hospital Readmissions Reduction Program for FY 2023.
     The provision of estimated and newly established 
performance standards for the calculation of value-based incentive 
payments, as well as a proposal to suppress multiple measures and 
provide net-neutral payment adjustments under the Hospital Value-Based 
Purchasing Program.
     Proposed requirements for payment adjustments to hospitals 
under the HAC Reduction Program for FY 2023.
     Discussion of and proposed changes relating to the 
implementation of the Rural Community Hospital Demonstration Program in 
FY 2023.
     Proposed GME payment change in response to Milton S. 
Hershey Medical Center et al v. Becerra litigation.
     Proposed nursing and allied health education program 
Medicare Advantage (MA) add-on rates and direct GME MA percent 
reductions for CYs 2020 and 2021.
     Proposal to allow Medicare GME affiliation agreements 
within certain rural track full-time equivalent limitations.
     Proposed payment adjustment for certain clinical trial and 
expanded access use immunotherapy cases.
4. Proposed FY 2023 Policy Governing the IPPS for Capital-Related Costs
    In section VI. of the preamble to the proposed rule, we discussed 
the proposed payment policy requirements for capital-related costs and 
capital payments to hospitals for FY 2023.
5. Proposed Changes to the Payment Rates for Certain Excluded 
Hospitals: Rate-of-Increase Percentages
    In section VII. of the preamble of the proposed rule, we discussed 
the following:
     Proposed changes to payments to certain excluded hospitals 
for FY 2023.
     Proposed continued implementation of the Frontier 
Community Health Integration Project (FCHIP) Demonstration.
6. Proposed Changes to the LTCH PPS
    In section VIII. of the preamble of the proposed rule, we set forth 
proposed changes to the LTCH PPS Federal payment rates, factors, and 
other payment rate policies under the LTCH PPS for FY 2023.
7. Proposed Changes Relating to Quality Data Reporting for Specific 
Providers and Suppliers
    In section IX. of the preamble of the proposed rule, we addressed 
the following:
     Proposed requirements for the Hospital Inpatient Quality 
Reporting (IQR) Program.
     Proposed changes to the requirements for the quality 
reporting program for PPS-exempt cancer hospitals (PCHQR Program).
     For the Long Term Care Hospital Quality Reporting Program 
(LTCH QRP), we requested information on CMS' overarching principles for 
measuring healthcare disparities across CMS Quality Programs, including 
the LTCH QRP. We also requested information on the potential adoption 
of one future National Healthcare Safety Network (NHSN) digital quality 
measure (dQM) for the LTCH QRP, as well as quality measure concepts 
under consideration for future years.
     Proposed changes to requirements pertaining to eligible 
hospitals and CAHs participating in the Medicare Promoting 
Interoperability Program.
8. Other Proposals and Comment Solicitations Included in the Proposed 
Rule
    Section X. of the preamble to the proposed rule includes the 
following:
     Proposed codification of policies related to the costs 
incurred for qualified and non-qualified deferred compensation plans.
     Proposed changes pertaining to the CoPs at 42 CFR part 482 
for hospitals, and at 42 CFR part 485, subpart F, for CAHs.
     Solicitation of comments on the appropriateness of payment 
adjustments that would account for the additional resource costs for 
hospitals for the procurement of wholly domestically made NIOSH-
approved surgical N95 respirators.
9. Other Provisions of the Proposed Rule
    Section XI. of the preamble to the proposed rule includes our 
discussion of the MedPAC Recommendations.
    Section XII. of the preamble to the proposed rule included the 
following:
     A descriptive listing of the public use files associated 
with the proposed rule.
     The collection of information requirements for entities 
based on our proposals.
     Information regarding our responses to public comments.

[[Page 48794]]

10. Determining Prospective Payment Operating and Capital Rates and 
Rate-of-Increase Limits for Acute Care Hospitals
    In sections II. and III. of the Addendum to the proposed rule, we 
set forth proposed changes to the amounts and factors for determining 
the proposed FY 2023 prospective payment rates for operating costs and 
capital-related costs for acute care hospitals. We proposed to 
establish the threshold amounts for outlier cases. In addition, in 
section IV. of the Addendum to the proposed rule, we addressed the 
proposed update factors for determining the rate-of-increase limits for 
cost reporting periods beginning in FY 2023 for certain hospitals 
excluded from the IPPS.
11. Determining Prospective Payment Rates for LTCHs
    In section V. of the Addendum to the proposed rule, we set forth 
proposed changes to the amounts and factors for determining the 
proposed FY 2023 LTCH PPS standard Federal payment rate and other 
factors used to determine LTCH PPS payments under both the LTCH PPS 
standard Federal payment rate and the site neutral payment rate in FY 
2023. We are proposed to establish the adjustments for the wage index, 
labor-related share, the cost-of-living adjustment, and high-cost 
outliers, including the applicable fixed-loss amounts and the LTCH 
cost-to-charge ratios (CCRs) for both payment rates.
12. Impact Analysis
    In Appendix A of the proposed rule, we set forth an analysis of the 
impact the proposed changes would have on affected acute care 
hospitals, CAHs, LTCHs and other entities.
13. Recommendation of Update Factors for Operating Cost Rates of 
Payment for Hospital Inpatient Services
    In Appendix B of the proposed rule, as required by sections 
1886(e)(4) and (e)(5) of the Act, we provided our recommendations of 
the appropriate percentage changes for FY 2023 for the following:
     A single average standardized amount for all areas for 
hospital inpatient services paid under the IPPS for operating costs of 
acute care hospitals (and hospital-specific rates applicable to SCHs 
and MDHs).
     Target rate-of-increase limits to the allowable operating 
costs of hospital inpatient services furnished by certain hospitals 
excluded from the IPPS.
     The LTCH PPS standard Federal payment rate and the site 
neutral payment rate for hospital inpatient services provided for LTCH 
PPS discharges.
14. Discussion of Medicare Payment Advisory Commission Recommendations
    Under section 1805(b) of the Act, MedPAC is required to submit a 
report to Congress, no later than March 15 of each year, in which 
MedPAC reviews and makes recommendations on Medicare payment policies. 
MedPAC's March 2022 recommendations concerning hospital inpatient 
payment policies address the update factor for hospital inpatient 
operating costs and capital-related costs for hospitals under the IPPS. 
We addressed these recommendations in Appendix B of the proposed rule. 
For further information relating specifically to the MedPAC March 2022 
report or to obtain a copy of the report, contact MedPAC at (202) 220-
3700 or visit MedPAC's website at https://www.medpac.gov.

E. Advancing Health Information Exchange

    The Department of Health and Human Services (HHS) has a number of 
initiatives designed to encourage and support the adoption of 
interoperable health information technology and to promote nationwide 
health information exchange to improve health care and patient access 
to their digital health information.
    To further interoperability in post-acute care settings, CMS and 
the Office of the National Coordinator for Health Information 
Technology (ONC) participate in the Post-Acute Care Interoperability 
Workgroup (PACIO) to facilitate collaboration with industry 
stakeholders to develop Health Level Seven International[supreg] (HL7) 
Fast Healthcare Interoperability Resources[supreg] (FHIR) standards. 
These standards could support the exchange and reuse of patient 
assessment data derived from the post-acute care (PAC) setting 
assessment tools, such as Minimum Data Set (MDS), Inpatient 
Rehabilitation Facility-Patient Assessment Instrument (IRF-PAI), Long 
Term Care Hospital (LTCH) Continuity Assessment Record and Evaluation 
(CARE) Data Set (LCDS), Outcome and Assessment Information Set (OASIS), 
and other sources.3 4 The PACIO Project has focused on HL7 
FHIR implementation guides for functional status, cognitive status and 
new use cases on advance directives, re-assessment timepoints, and 
Speech, Language, Swallowing Cognitive communications and Hearing 
(SPLASCH).\5\ We encourage PAC provider and health information 
technology (IT) vendor participation as the efforts advance. The CMS 
Data Element Library (DEL) continues to be updated and serves as a 
resource for PAC assessment data elements and their associated mappings 
to health IT standards, such as Logical Observation Identifiers Names 
and Codes (LOINC) and Systematized Nomenclature of Medicine Clinical 
Terms (SNOMED).\6\ The DEL furthers CMS' goal of data standardization 
and interoperability. Standards in the DEL can be referenced on the CMS 
website (https://del.cms.gov/DELWeb/pubHome) and in the ONC 
Interoperability Standards Advisory (ISA). The 2022 ISA is available at 
https://www.healthit.gov/isa/sites/isa/files/inline-files/2022-ISA-Reference-Edition.pdf.
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    \3\ HL7 FHIR Release 4. Available at: https://www.hl7.org/fhir/.
    \4\ HL7 FHIR. PACIO Functional Status Implementation Guide. 
Available at: https://paciowg.github.io/functional-status-ig/.
    \5\ PACIO Project. Available at: https://pacioproject.org/about/.
    \6\ CMS Data Element Library Fact Sheet. Available at: https://www.cms.gov/newsroom/fact-sheets/cms-data-element-library-fact-sheet.
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    The 21st Century Cures Act (Cures Act) (Pub. L. 114-255, enacted 
December 13, 2016) required HHS and ONC to take steps further 
interoperability for providers in settings across the care 
continuum.\7\ Specifically, section 4003(b) of the Cures Act required 
ONC to take steps to advance interoperability through the development 
of a a Trusted Exchange Framework and Common Agreement aimed at 
establishing full network-to-network exchange of health information 
nationally. On January 18, 2022, ONC announced a significant milestone 
by releasing the Trusted Exchange Framework \8\ and Common Agreement 
Version 1.\9\ The Trusted Exchange Framework is a set of non-binding 
principles for health information exchange, and the Common Agreement is 
a contract that advances those principles. The Common Agreement and the 
incorporated by reference Qualified Health Information Network 
Technical Framework Version 1 establish the technical infrastructure

[[Page 48795]]

model and governing approach for different health information networks 
and their users to securely share clinical information with each other, 
all under commonly agreed to terms. The technical and policy 
architecture of how exchange occurs under the Common Agreement follows 
a network-of-networks structure, which allows for connections at 
different levels and is inclusive of many different types of entities 
at those different levels, such as health information networks, 
healthcare practices, hospitals, public health agencies, and Individual 
Access Services (IAS) Providers.\10\ For more information, we refer 
readers to https://www.healthit.gov/topic/interoperability/trusted-exchange-framework-and-common-agreement.
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    \7\ Public Law 114-255, sections 4001 through 4008. Available 
at: https://www.govinfo.gov/content/pkg/PLAW-114publ255/html/PLAW-114publ255.htm.
    \8\ The Trusted Exchange Framework (TEF): Principles for Trusted 
Exchange (Jan. 2022). Available at: https://www.healthit.gov/sites/default/files/page/2022-01/Trusted_Exchange_Framework_0122.pdf.
    \9\ Common Agreement for Nationwide Health Information 
Interoperability Version 1 (Jan. 2022). Available at: https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf.
    \10\ The Common Agreement defines Individual Access Services 
(IAS) as ``with respect to the Exchange Purposes definition, the 
services provided utilizing the Connectivity Services, to the extent 
consistent with Applicable Law, to an Individual with whom the QHIN, 
Participant, or Subparticipant has a Direct Relationship to satisfy 
that Individual's ability to access, inspect, or obtain a copy of 
that Individual's Required Information that is then maintained by or 
for any QHIN, Participant, or Subparticipant.'' The Common Agreement 
defines ``IAS Provider'' as: ``Each QHIN, Participant, and 
Subparticipant that offers Individual Access Services.'' See Common 
Agreement for Nationwide Health Information Interoperability Version 
1, at 7 (Jan. 2022), https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf.
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    We invite providers to learn more about these important 
developments and how they are likely to affect LTCHs.
    Comment: A commenter expressed support for efforts across HHS to 
advance health information technology exchange and encouraged use of a 
standard set of data by providers and health IT vendors, including 
efforts through the PACIO project. The commenter also noted a recent 
National Academies report describing technology barriers for PAC 
settings due to not being eligible for previous incentives to purchase 
technology certified under the ONC Health IT Certification Program. The 
commenter supported recommendations in the report for HHS to pursue 
financial incentives for post-acute care settings to adopt certified 
health information technology in order to enable health information 
exchange.
    Response: We will take this comment into consideration as we 
coordinate with Federal partners, including ONC, on interoperability 
initiatives, and to inform future rulemaking.

F. Use of FY 2021 Data and Methodology Modifications for the FY 2023 
IPPS and LTCH PPS Ratesetting

    We primarily use two data sources in the IPPS and LTCH PPS 
ratesetting: claims data and cost report data. The claims data source 
is the MedPAR file, which includes fully coded diagnostic and procedure 
data for all Medicare inpatient hospital bills for discharges in a 
fiscal year. The cost report data source is the Medicare hospital cost 
report data files from the most recent quarterly Healthcare Cost Report 
Information System (HCRIS) release. Our goal is always to use the best 
available data overall for ratesetting. Ordinarily, the best available 
MedPAR data is the most recent MedPAR file that contains claims from 
discharges for the fiscal year that is 2 years prior to the fiscal year 
that is the subject of the rulemaking. Ordinarily, the best available 
cost report data is based on the cost reports beginning 3 fiscal years 
prior to the fiscal year that is the subject of the rulemaking. 
However, in the FY 2022 IPPS/LTCH PPS final rule (86 FR 44789 through 
44793), as discussed in more detail below, we finalized our proposal to 
use FY 2019 data for the FY 2022 ratesetting for circumstances where 
the FY 2020 data (the most recently available data at the time of 
rulemaking) was significantly impacted by the COVID-19 PHE.
    As we discussed in the FY 2022 IPPS/LTCH PPS final rule, the FY 
2020 MedPAR claims file and the FY 2019 HCRIS dataset both contained 
data that was significantly impacted by the COVID-19 PHE, primarily in 
that the utilization of services at IPPS hospitals and LTCHs was 
generally markedly different for certain types of services in FY 2020 
than would have been expected in the absence of the PHE. However, the 
most recent vaccination and hospitalization data from the CDC at the 
time of development of that rule supported our belief at the time that 
the risk of COVID-19 in FY 2022 would be significantly lower than the 
risk of COVID-19 in FY 2020 and there would be fewer COVID-19 
hospitalizations for Medicare beneficiaries in FY 2022 than there were 
in FY 2020. Therefore, we finalized our proposal to use FY 2019 data 
for the FY 2022 ratesetting for circumstances where the FY 2020 data 
was significantly impacted by the COVID-19 PHE, based on the belief 
that FY 2019 data from before the COVID-19 PHE would be a better 
overall approximation of the FY 2022 inpatient experience at both IPPS 
hospitals and LTCHs. For example, we used the FY 2019 MedPAR claims 
data for purposes where we ordinarily would have used the FY 2020 
MedPAR claims data. We also used cost report data from the FY 2018 
HCRIS file for purposes where we ordinarily would have used the FY 2019 
HCRIS file (since the FY 2019 cost report data from HCRIS contained 
many cost reports ending in FY 2020 based on each hospital's cost 
reporting period).
    Similar to our analysis of the FY 2020 MedPAR claims file and the 
FY 2019 HCRIS dataset for the FY 2022 IPPS/LTCH PPS rulemaking, in the 
FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28123 through 28125) we 
discussed that the FY 2021 MedPAR claims file and the FY 2020 HCRIS 
dataset also both contain data that was significantly impacted by the 
virus that causes COVID-19, primarily in that the utilization of 
services at IPPS hospitals and LTCHs was again generally markedly 
different for certain types of services in FY 2021 than would have been 
expected in the absence of the virus that causes COVID-19. 
Specifically, the share of admissions at IPPS hospitals and LTCHs for 
MS-DRGs and MS-LTC-DRGs associated with the treatment of COVID-19 
continued to remain significantly higher than levels prior to the 
COVID-19 PHE. For example, in FY 2019, the share of IPPS cases and LTCH 
PPS standard Federal payment rate cases grouped to MS-DRG and MS-LTC-
DRG 177 (Respiratory infections and inflammations with MCC) was 
approximately 1 percent and 2 percent, respectively. In comparison, in 
FY 2021, the share of IPPS cases and LTCH PPS standard Federal payment 
rate cases grouped to MS-DRG 177 was approximately 6 percent and 8 
percent, respectively.
    In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28123 through 
28124), we reviewed the most recent data from the CDC on new inpatient 
hospital admissions of patients with confirmed COVID-19. We presented 
this CDC graph which illustrates new inpatient hospital admissions of 
patients with confirmed COVID-19 from August 1, 2020 through February 
15, 2022 (https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/02182022/images/hospitalizations_02182022.jpg?_=35767, 
accessed February 22, 2022).

[[Page 48796]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.003

    We stated that the low point of the graph (late June 2021) 
approximately coincides with the time of the development of the FY 2022 
IPPS/LTCH PPS final rule and generally supports, in conjunction with 
the other factors discussed in that rulemaking (including the most 
recent vaccination data from the CDC), our assumption in the final rule 
that the FY 2022 time period would be more similar to the time period 
prior to the PHE. We stated that the graph also shows that the virus 
that causes COVID-19 has continued to significantly impact 
hospitalizations for the time period subsequent to the development of 
the FY 2022 IPPS/LTCH PPS final rule.
    In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28124), we also 
presented information from the CDC on the likelihood of future COVID-19 
variants. We noted that the most recent increase in hospitalizations 
was primarily associated with the Omicron variant of the virus \11\ and 
that the CDC has stated that new variants will continue to emerge. 
Viruses constantly change through mutation and sometimes these 
mutations result in a new variant of the virus. The CDC and other 
public health organizations monitor all variants of the virus that 
causes COVID-19 in the United States and globally. Scientists monitor 
all variants but may classify certain ones as variants being monitored, 
variants of interest, variants of concern and variants of high 
consequence. Some variants spread more easily and quickly than other 
variants, which may lead to more cases of COVID-19. Even if a variant 
causes less severe disease in general, an increase in the overall 
number of cases could cause an increase in hospitalizations (see 
https://www.cdc.gov/coronavirus/2019-ncov/variants/about-variants.html, 
accessed February 25, 2022).
---------------------------------------------------------------------------

    \11\ https://www.cdc.gov/coronavirus/2019-ncov/variants/omicron-variant.html.
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    Given the effects of the virus that causes COVID-19 in the Medicare 
FY 2020 data, the Medicare FY 2021 data, and the CDC hospitalization 
data, coupled with the expectation for future variants, in the proposed 
rule we stated our belief that it is reasonable to assume that some 
Medicare beneficiaries will continue to be hospitalized with COVID-19 
at IPPS hospitals and LTCHs in FY 2023. Accordingly, we stated that we 
believe it would be appropriate to use FY 2021 data, specifically the 
FY 2021 MedPAR claims file and the FY 2020 HCRIS dataset (which 
contains data from many cost reports ending in FY 2021 based on each 
hospital's cost reporting period) as the most recent available data 
during the period of the COVID-19 PHE, for purposes of the FY 2023 IPPS 
and LTCH PPS ratesetting. However, we also stated our belief that it 
would be reasonable to assume based on the information available at the 
time that there will be fewer COVID-19 hospitalizations in FY 2023 than 
in FY 2021 given the more recent trends in the CDC hospitalization data 
since the Omicron variant peak in January, 2022. Accordingly, because 
we anticipated Medicare inpatient hospitalizations for COVID-19 would 
continue in FY 2023 but at a lower level, we proposed to use FY 2021 
data for purposes of the FY 2023 IPPS and LTCH PPS ratesetting but with 
modifications to our usual ratesetting methodologies to account for the 
anticipated decline in COVID-19 hospitalizations of Medicare 
beneficiaries at IPPS hospitals and LTCHs as compared to FY 2021.
    First, we proposed to modify the calculation of the FY 2023 MS-DRG 
and MS-LTC-DRG relative weights. We observed that COVID-19 cases were 
impacting the relative weights as calculated using the FY 2021 MedPAR 
data for a few COVID-19-related MS-DRGs and MS-LTC-DRGs. As an example, 
for MS-DRG and MS-LTC-DRG 870 (Septicemia or Severe Sepsis with MV >96 
hours), the MS-DRG and MS-LTC-DRG relative weights calculated using the 
FY 2021 MedPAR data are approximately 9 and 3 percent higher, 
respectively, compared to their relative weights if calculated 
excluding COVID-19 cases. Because this MS-DRG contains a mix of COVID-
19 cases and non-COVID-19 cases with different average costs, the 
relative weight for this MS-DRG is dependent on that mix of cases. As 
stated in the proposed rule, we believed it is reasonable to assume 
that there would be fewer COVID-19 hospitalizations among Medicare 
beneficiaries in FY 2023 than there were in FY 2021; however, we also 
stated that it is not possible to know precisely how COVID-19 
hospitalizations in FY 2023 will compare to FY 2021. We stated our 
belief that averaging the relative weights as calculated with and 
without the COVID-19 cases reflected in the FY 2021 MedPAR data would 
reflect a reasonable estimation of the case mix for FY 2023 based on 
the information available at the time, and more accurately estimate the 
relative resource use for the cases treated in FY 2023. Therefore, we 
proposed to calculate the relative weights for FY 2023 by first 
calculating two sets of weights, one including and one excluding COVID-
19 claims, and then averaging the two sets of relative weights to 
determine the proposed FY 2023 relative weight values. We believed this 
proposed modification to our relative weight setting methodology would 
appropriately reduce, but not remove entirely, the effect of COVID-19 
cases

[[Page 48797]]

on the relative weight calculations, consistent with our expectation 
that Medicare inpatient hospitalizations for COVID-19 will continue in 
FY 2023 at a lower level as compared to FY 2021, and provide a more 
accurate estimate of relative resource use for FY 2023 than if we were 
to calculate the proposed relative weights using all applicable cases 
in the FY 2021 data.
    We also proposed to modify our methodologies for determining the FY 
2023 outlier fixed-loss amount for IPPS cases and LTCH PPS standard 
Federal payment rate cases. The methodologies for determining both of 
these outlier fixed-loss amounts include calculating and applying a 
charge inflation factor to increase charges from the claim year to the 
rulemaking year, as well as calculating and applying cost-to-charge 
ratio (CCR) adjustment factors to adjust CCRs used to make payments in 
the current year to the rulemaking year. The charge inflation factors 
calculated using the 2 most recently available years of MedPAR claims 
data (FY 2020 and FY 2021) that would ordinarily be used for the FY 
2023 proposed rule to inflate the charges on the FY 2021 MedPAR claims 
were abnormally high as compared to recent historical levels prior to 
the PHE (for example, for the IPPS, approximately 10 percent based on 
the FY 2020 and FY 2021 MedPAR claims data as compared to approximately 
6 percent based on the FY 2018 and FY 2019 MedPAR claims data). 
Furthermore, the IPPS operating and capital CCR adjustment factors 
calculated based on the percentage changes in the CCRs from the 
December 2020 update of the Provider Specific File (PSF) to the 
December 2021 update of the PSF that would ordinarily be used for the 
FY 2023 proposed rule to adjust the CCRs from the December 2021 update 
of the PSF were also abnormally high as compared to recent historical 
levels prior to the PHE (for example, for the IPPS operating CCR 
adjustment factor, a factor of approximately 1.03 based on the December 
2020 and December 2021 updates to the PSF as compared to a factor of 
approximately 0.97 based on the March 2019 and March 2020 updates to 
the PSF). In the proposed rule, we stated our belief that these 
abnormally high charge inflation and CCR adjustment factors as compared 
to historical levels were partially due to the high number of COVID-19 
cases with higher charges that were treated in IPPS hospitals and LTCHs 
in FY 2021. We also stated our belief that there will be fewer COVID-19 
cases in FY 2023 than in FY 2021 and that therefore, we do not believe 
it is reasonable to assume charges and CCRs will continue to increase 
at these abnormally high rates. Consequently, when determining the FY 
2023 outlier fixed-loss amounts for IPPS cases and LTCH PPS standard 
Federal payment rate cases, we proposed to inflate the charges on the 
FY 2021 MedPAR claims using charge inflation factors computed by 
comparing the average covered charge per case in the March 2019 MedPAR 
file of FY 2018 to the average covered charge per case in the March 
2020 MedPAR file of FY 2019, which is the last 1-year period prior to 
the COVID-19 PHE. We also proposed to adjust the CCRs from the December 
2021 update of the PSF by comparing the percentage change in the 
national average case-weighted CCR from the March 2019 update of the 
PSF to the national average case-weighted CCR from the March 2020 
update of the PSF, which is the last 1-year period prior to the COVID-
19 PHE. We stated our belief that using the charge inflation factors 
and CCR adjustment factors derived from data prior to the COVID-19 PHE 
would provide a more reasonable approximation of the increase in costs 
that will occur from FY 2021 to FY 2023 because we do not believe the 
charge inflation that has occurred during the PHE will continue as the 
number of higher cost COVID-19 cases declines.
    In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28740 through 
28741) we also requested comments on, as an alternative to our proposed 
approach, the use of the FY 2021 data for purposes of FY 2023 
ratesetting without these proposed modifications to our usual 
methodologies for the calculation of the FY 2023 MS-DRG and MS-LTC-DRG 
relative weights or the usual methodologies used to determine the FY 
2023 outlier fixed-loss amount for IPPS cases and LTCH PPS standard 
Federal payment rate cases. We noted that the FY 2023 outlier fixed-
loss amount would be significantly higher under this alternative 
approach. In order to illustrate the effect of our proposed 
modifications on the relative weights and fixed loss amount, we made 
available supplemental information, including the relative weights and 
fixed-loss amount calculated without the proposed modifications to our 
usual methodologies.
    The comments we received on our proposal to use FY 2021 data for 
purposes of the FY 2023 IPPS and LTCH PPS ratesetting were focused on 
the specific use of FY 2021 data when determining the FY 2023 relative 
weights or outlier fixed-loss amounts. Therefore, we refer the reader 
to section II.E. of the preamble of this final rule for our summary and 
response to comments received on our proposed use of FY 2021 data and 
our proposed modifications to our usual methodology when determining 
the FY 2023 IPPS MS-DRG relative weights. We refer the reader to 
section VIII.B. of the preamble of this final rule for our summary and 
response to comments received on our proposed use of FY 2021 data and 
our proposed modifications to our usual methodology when determining 
the FY 2023 LTCH PPS MS-LTC-DRG relative weights. We refer the reader 
to section II.A.4. of the addendum to this final rule for our summary 
and response to comments received on our proposed use of FY 2021 data 
and our proposed modifications to our usual methodology when 
determining the FY 2023 outlier fixed-loss amounts for IPPS cases. We 
refer the reader to section V.D.3. of the Addendum to this final rule 
for our summary and response to comments received on our proposed use 
of FY 2021 data and our proposed modifications to our usual methodology 
when determining the FY 2023 outlier fixed-loss amounts for LTCH PPS 
standard Federal payment rate cases.
    Since the publication of the proposed rule, we have continued to 
monitor hospitalization data reported by the CDC. This CDC graph 
illustrates new inpatient hospital admissions of patients with 
confirmed COVID-19 from August 1, 2020 through July 6, 2022 (https://www.cdc.gov/coronavirus/2019-ncov/covid-data/covidview/07082022/images/Hospitalizations.png?_=90548, accessed July 08, 2022).

[[Page 48798]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.004

    The graph shows that new COVID-19 hospital admissions reached a low 
point in early April 2022, however have steadily increased since.
    After reviewing the latest CDC hospitalization data, coupled with 
the expectation for future variants,\12\ we continue to believe that it 
is reasonable to assume that some Medicare beneficiaries will continue 
to be hospitalized with COVID-19 at IPPS hospitals and LTCHs in FY 
2023. We also continue to believe that it would be reasonable to assume 
based on the information available at this time that there will be 
fewer COVID-19 hospitalizations in FY 2023 than in FY 2021 given that 
the current levels of hospitalizations are much lower than the Omicron 
variant peak in January 2022.
---------------------------------------------------------------------------

    \12\ https://www.cdc.gov/coronavirus/2019-ncov/variants/about-variants.html.
---------------------------------------------------------------------------

    Therefore, after considering the comments received and based on our 
evaluation of the information available at this time, we are finalizing 
our proposal to use FY 2021 data for purposes of the FY 2023 IPPS and 
LTCH PPS ratesetting. (That is, the FY 2021 MedPAR claims file and the 
FY 2020 HCRIS dataset (which contains data from many cost reports 
ending in FY 2021 based on each hospital's cost reporting period).) We 
are also finalizing, as proposed, modifications to our usual 
methodology for determining the FY 2023 IPPS MS-DRG relative weights 
and FY 2023 LTCH PPS MS-LTC-DRG relative weights. Specifically, for FY 
2023, we calculated the relative weights by first calculating two sets 
of weights, one including and one excluding COVID-19 claims, and then 
averaging the two sets of relative weights to determine the final 
relative weight values. The finalization of our proposal to use FY 2021 
data and to modify our methodology for determining the FY 2023 IPPS MS-
DRG relative weights is discussed in greater detail in section II.E. of 
the preamble of this final rule. The finalization of our proposal to 
use FY 2021 data and to modify our methodology for determining the FY 
2023 LTCH PPS MS-LTC-DRG relative weights is discussed in greater 
detail in section VIII.B. of the preamble of this final rule.
    As discussed in section II.A.4. and section V.D.3. of the addendum 
to this final rule, we received many comments supportive of our 
proposed modifications to our usual methodologies for determining the 
FY 2023 IPPS and LTCH PPS outlier fixed-loss amounts. As discussed in 
these sections, after considering comments received, we are finalizing 
our proposal to inflate the charges on the FY 2021 MedPAR claims using 
charge inflation factors computed by comparing the average covered 
charge per case in the March 2019 MedPAR file of FY 2018 to the average 
covered charge per case in the March 2020 MedPAR file of FY 2019, which 
is the last 1-year period prior to the COVID-19 PHE. We are also 
finalizing our proposal to adjust the CCRs from the March 2021 update 
of the PSF by comparing the percentage change in the national average 
case-weighted CCR from the March 2019 update of the PSF to the national 
average case-weighted CCR from the March 2020 update of the PSF, which 
is the last 1-year period prior to the COVID-19 PHE.
    We also received many comments that suggested other modifications 
CMS should make to our usual methodologies for determining the FY 2023 
IPPS and LTCH PPS outlier fixed-loss amounts. As also discussed in 
section II.A.4. and section V.D.3. of the addendum to this final rule, 
after consideration of the comments received, we are modifying our 
proposed methodologies for establishing the FY 2023 IPPS and LTCH PPS 
outlier fixed-loss amounts by calculating the FY 2023 IPPS and LTCH PPS 
outlier fixed-loss amounts as averages of the fixed-loss amounts as 
calculated including and excluding COVID-19 claims. We believe this 
adjustment to our proposed methodology will better reflect a reasonable 
estimation of the case mix for FY 2023 based on the information 
available at this time and is also consistent with the approach we are 
finalizing for determining the FY 2023 IPPS MS-DRG and LTCH PPS MS-LTC-
DRG relative weights.
    In addition, as discussed in section II.A.4. of the Addendum to 
this final rule, after consideration of comments received, we are also 
further modifying our proposed methodology for establishing the FY 2023 
IPPS outlier fixed-loss amount by including the increases in payments 
for COVID-19 cases provided by the CARES Act in the calculation of the 
outlier fixed-loss amount.

II. Changes to Medicare Severity Diagnosis-Related Group (MS-DRG) 
Classifications and Relative Weights

A. Background

    Section 1886(d) of the Act specifies that the Secretary shall 
establish a classification system (referred to as diagnosis-related 
groups (DRGs)) for inpatient discharges and adjust payments under the 
IPPS based on appropriate weighting factors assigned to each DRG. 
Therefore, under the IPPS, Medicare pays for inpatient hospital 
services on a rate per discharge basis that varies according to the DRG 
to which a beneficiary's stay is assigned. The formula used to 
calculate payment

[[Page 48799]]

for a specific case multiplies an individual hospital's payment rate 
per case by the weight of the DRG to which the case is assigned. Each 
DRG weight represents the average resources required to care for cases 
in that particular DRG, relative to the average resources used to treat 
cases in all DRGs.
    Section 1886(d)(4)(C) of the Act requires that the Secretary adjust 
the DRG classifications and relative weights at least annually to 
account for changes in resource consumption. These adjustments are made 
to reflect changes in treatment patterns, technology, and any other 
factors that may change the relative use of hospital resources.

B. Adoption of the MS-DRGs and MS-DRG Reclassifications

    For information on the adoption of the MS-DRGs in FY 2008, we refer 
readers to the FY 2008 IPPS final rule with comment period (72 FR 47140 
through 47189).
    For general information about the MS-DRG system, including yearly 
reviews and changes to the MS-DRGs, we refer readers to the previous 
discussions in the FY 2010 IPPS/RY 2010 LTCH PPS final rule (74 FR 
43764 through 43766) and the FYs 2011 through 2022 IPPS/LTCH PPS final 
rules (75 FR 50053 through 50055; 76 FR 51485 through 51487; 77 FR 
53273; 78 FR 50512; 79 FR 49871; 80 FR 49342; 81 FR 56787 through 
56872; 82 FR 38010 through 38085, 83 FR 41158 through 41258, 84 FR 
42058 through 42165, 85 FR 58445 through 58596, 86 FR 44795 through 
44961, respectively).

C. FY 2023 MS-DRG Documentation and Coding Adjustment

    1. Background on the Prospective MS-DRG Documentation and Coding 
Adjustments for FY 2008 and FY 2009 Authorized by Pub. L. 110-90 and 
the Recoupment or Repayment Adjustment Authorized by Section 631 of the 
American Taxpayer Relief Act of 2012 (ATRA).
    In the FY 2008 IPPS final rule with comment period (72 FR 47140 
through 47189), we adopted the MS-DRG patient classification system for 
the IPPS, effective October 1, 2007, to better recognize severity of 
illness in Medicare payment rates for acute care hospitals. The 
adoption of the MS-DRG system resulted in the expansion of the number 
of DRGs from 538 in FY 2007 to 745 in FY 2008. By increasing the number 
of MS-DRGs and more fully taking into account patient severity of 
illness in Medicare payment rates for acute care hospitals, MS-DRGs 
encourage hospitals to improve their documentation and coding of 
patient diagnoses.
    In the FY 2008 IPPS final rule with comment period (72 FR 47175 
through 47186), we indicated that the adoption of the MS-DRGs had the 
potential to lead to increases in aggregate payments without a 
corresponding increase in actual patient severity of illness due to the 
incentives for additional documentation and coding. In that final rule 
with comment period, we exercised our authority under section 
1886(d)(3)(A)(vi) of the Act, which authorizes us to maintain budget 
neutrality by adjusting the national standardized amount, to eliminate 
the estimated effect of changes in coding or classification that do not 
reflect real changes in case-mix. Our actuaries estimated that 
maintaining budget neutrality required an adjustment of -4.8 percentage 
points to the national standardized amount. We provided for phasing in 
this -4.8 percentage point adjustment over 3 years. Specifically, we 
established prospective documentation and coding adjustments of -1.2 
percentage points for FY 2008, -1.8 percentage points for FY 2009, and 
-1.8 percentage points for FY 2010.
    On September 29, 2007, Congress enacted the TMA [Transitional 
Medical Assistance], Abstinence Education, and QI [Qualifying 
Individuals] Programs Extension Act of 2007 (Pub. L. 110-90). Section 
7(a) of Public Law 110-90 reduced the documentation and coding 
adjustment made as a result of the MS-DRG system that we adopted in the 
FY 2008 IPPS final rule with comment period to -0.6 percentage point 
for FY 2008 and -0.9 percentage point for FY 2009.
    As discussed in prior year rulemakings, and most recently in the FY 
2017 IPPS/LTCH PPS final rule (81 FR 56780 through 56782), we 
implemented a series of adjustments required under sections 7(b)(1)(A) 
and 7(b)(1)(B) of Public Law 110-90, based on a retrospective review of 
FY 2008 and FY 2009 claims data. We completed these adjustments in FY 
2013 but indicated in the FY 2013 IPPS/LTCH PPS final rule (77 FR 53274 
through 53275) that delaying full implementation of the adjustment 
required under section 7(b)(1)(A) of Public Law 110-90 until FY 2013 
resulted in payments in FY 2010 through FY 2012 being overstated, and 
that these overpayments could not be recovered under Public Law 110-90.
    In addition, as discussed in prior rulemakings and most recently in 
the FY 2018 IPPS/LTCH PPS final rule (82 FR 38008 through 38009), 
section 631 of the American Taxpayer Relief Act of 2012 (ATRA) amended 
section 7(b)(1)(B) of Public Law 110-90 to require the Secretary to 
make a recoupment adjustment or adjustments totaling $11 billion by FY 
2017. This adjustment represented the amount of the increase in 
aggregate payments as a result of not completing the prospective 
adjustment authorized under section 7(b)(1)(A) of Public Law 110-90 
until FY 2013.
2. Adjustments Made for FYs 2018, 2019, 2020, 2021, and 2022 as 
Required Under Section 414 of Public Law 114-10 (MACRA) and Section 
15005 of Public Law 114-255
    As stated in the FY 2017 IPPS/LTCH PPS final rule (81 FR 56785), 
once the recoupment required under section 631 of the ATRA was 
complete, we had anticipated making a single positive adjustment in FY 
2018 to offset the reductions required to recoup the $11 billion under 
section 631 of the ATRA. However, section 414 of the MACRA (which was 
enacted on April 16, 2015) replaced the single positive adjustment we 
intended to make in FY 2018 with a 0.5 percentage point positive 
adjustment for each of FYs 2018 through 2023. In the FY 2017 
rulemaking, we indicated that we would address the adjustments for FY 
2018 and later fiscal years in future rulemaking. Section 15005 of the 
21st Century Cures Act (Pub. L. 114-255), which was enacted on December 
13, 2016, amended section 7(b)(1)(B) of the TMA, as amended by section 
631 of the ATRA and section 414 of the MACRA, to reduce the adjustment 
for FY 2018 from a 0.5 percentage point positive adjustment to a 0.4588 
percentage point positive adjustment. As we discussed in the FY 2018 
rulemaking, we believe the directive under section 15005 of Public Law 
114-255 is clear. Therefore, in the FY 2018 IPPS/LTCH PPS final rule 
(82 FR 38009) for FY 2018, we implemented the required +0.4588 
percentage point adjustment to the standardized amount. In the FY 2019 
IPPS/LTCH PPS final rule (83 FR 41157), the FY 2020 IPPS/LTCH PPS final 
rule (84 FR 42057), the FY 2021 IPPS/LTCH PPS final rule (85 FR 58444 
and 58445), and the FY 2022 IPPS/LTCH PPS final rule (86 FR 44794 and 
44795), consistent with the requirements of section 414 of the MACRA, 
we implemented 0.5 percentage point positive adjustments to the 
standardized amount for FY 2019, FY 2020, FY 2021, and FY 2022, 
respectively. We indicated the FY 2018, FY 2019, FY 2020, FY 2021, and 
FY 2022 adjustments were permanent adjustments to payment rates. We 
also

[[Page 48800]]

stated that we plan to propose a future adjustment required under 
section 414 of the MACRA for FY 2023 in future rulemaking.
3. Adjustment for FY 2023
    Consistent with the requirements of section 414 of the MACRA, we 
proposed to implement a 0.5 percentage point positive adjustment to the 
standardized amount for FY 2023. We stated that this would constitute a 
permanent adjustment to payment rates. We also stated that this 
proposed 0.5 percentage point positive adjustment is the final 
adjustment prescribed by section 414 of the MACRA. Along with the 
0.4588 percentage point positive adjustment for FY 2018, and the 0.5 
percentage point positive adjustments for FY 2019, FY 2020, FY 2021, 
and FY 2022, this final adjustment will result in combined positive 
adjustment of 2.9588 percentage points (or the sum of the adjustments 
for FYs 2018 through 2023) to the standardized amount.
    We received no public comments on the proposed adjustment for FY 
2023 and are finalizing our proposal to implement a 0.5 percentage 
point positive adjustment to the standardized amount for FY 2023. As 
indicated, this finalized 0.5 percentage point positive adjustment for 
FY 2023 is the final adjustment prescribed by section 414 of the MACRA.

D. Changes to Specific MS-DRG Classifications

1. Discussion of Changes to Coding System and Basis for FY 2023 MS-DRG 
Updates
a. Conversion of MS-DRGs to the International Classification of 
Diseases, 10th Revision (ICD-10)
    As of October 1, 2015, providers use the International 
Classification of Diseases, 10th Revision (ICD-10) coding system to 
report diagnoses and procedures for Medicare hospital inpatient 
services under the MS-DRG system instead of the ICD-9-CM coding system, 
which was used through September 30, 2015. The ICD-10 coding system 
includes the International Classification of Diseases, 10th Revision, 
Clinical Modification (ICD-10-CM) for diagnosis coding and the 
International Classification of Diseases, 10th Revision, Procedure 
Coding System (ICD-10-PCS) for inpatient hospital procedure coding, as 
well as the ICD-10-CM and ICD-10-PCS Official Guidelines for Coding and 
Reporting. For a detailed discussion of the conversion of the MS-DRGs 
to ICD-10, we refer readers to the FY 2017 IPPS/LTCH PPS final rule (81 
FR 56787 through 56789).
b. Basis for FY 2023 MS-DRG Updates
    Given the need for more time to carefully evaluate requests and 
propose updates, as discussed in the FY 2018 IPPS/LTCH PPS final rule 
(82 FR 38010), we changed the deadline to request updates to the MS-
DRGs to November 1 of each year, which provided an additional five 
weeks for the data analysis and review process. In the FY 2021 IPPS/
LTCH PPS proposed rule (85 FR 32472), we stated that with the continued 
increase in the number and complexity of the requested changes to the 
MS-DRG classifications since the adoption of ICD-10 MS-DRGs, and to 
consider as many requests as possible, more time is needed to carefully 
evaluate the requested changes, analyze claims data, and consider any 
proposed updates. We further stated we were changing the deadline to 
request changes to the MS-DRGs to October 20 of each year to allow for 
additional time for the review and consideration of any proposed 
updates. However, in the FY 2021 IPPS/LTCH PPS final rule (85 FR 
58445), due to the unique circumstances for the FY 2021 IPPS/LTCH PPS 
final rule for which we waived the delayed effective date, we 
maintained the deadline of November 1, 2020 for FY 2022 MS-DRG 
classification change requests. We also noted that we expected to 
reconsider a change in the deadline beginning with comments and 
suggestions submitted for FY 2023. In the FY 2022 IPPS/LTCH PPS 
proposed rule, we stated that while we continue to believe that a 
change in the deadline from November 1 to October 20 would provide 
hospitals sufficient time to assess potential impacts and inform future 
MS-DRG recommendations, we were maintaining the deadline of November 1 
for FY 2023 MS-DRG classification change requests. As discussed in the 
FY 2022 IPPS/LTCH PPS final rule (86 FR 44795), we received public 
comments expressing support for a future change to the deadline for 
requesting updates to the MS-DRG classifications from November 1 to 
October 20, and we noted in response that we may consider any changes 
to the deadline or frequency for submissions of requests for MS-DRG 
classification changes for future fiscal years. Beginning with FY 2024 
MS-DRG classification change requests, we are changing the deadline to 
request changes to the MS-DRGs to October 20 of each year to allow for 
additional time for the review and consideration of any proposed 
updates. As previously discussed, we continue to believe such a change 
would allow hospitals sufficient time to assess potential impacts and 
inform future MS-DRG recommendations, while also providing CMS the 
additional time needed for evaluation of the requested changes, 
analysis of claims data, and consideration of any proposed updates.
    As discussed in the FY 2023 IPPS/LTCH PPS proposed rule, we are 
also changing the process for submitting requested updates to the MS-
DRG classifications, beginning with the FY 2024 MS-DRG classification 
change requests. CMS is in the process of implementing a new electronic 
application intake system, Medicare Electronic Application Request 
Information SystemTM (MEARIS\TM\), for users to submit new 
technology add-on payment applications, requests for ICD-10-PCS 
procedure codes, and other requests. To simplify and streamline the 
process for submission of standardized applications and requests that 
inform payment policy under the IPPS, we will also be using this new 
system for submission of MS-DRG classification change requests. We 
believe that submission of MS-DRG reclassification requests through 
MEARIS\TM\ will not only help CMS to track such requests, but it will 
also create efficiencies for requestors when compared to the previous 
submission process.
    Accordingly, beginning with the FY 2024 MS-DRG classification 
change requests, CMS will only accept such requests submitted via 
MEARIS,\TM\ and will no longer consider any such requests that are sent 
via email. We note that, beginning April 5, 2022, MEARIS\TM\ became 
available for users to begin gaining familiarity with this new approach 
for submitting MS-DRG classification change requests. MEARIS,\TM\ 
including the mechanism for submitting MS-DRG classification change 
requests, can be accessed at: https://mearis.cms.gov. As stated in the 
proposed rule, within MEARIS\TM\ we have built in several resources to 
support users, including a ``Resources'' section (available at https://mearis.cms.gov/public/resources) and technical support available under 
``Useful Links'' at the bottom of the MEARIS\TM\ site. Questions 
regarding the MEARIS\TM\ system can be submitted to CMS using the form 
available under ``Contact'' at: https://mearis.cms.gov/public/resources?app=msdrg.
    We also note that, as discussed in section II.D.17. of the preamble 
of the proposed rule and this final rule, effective January 5, 2022, 
MEARIS\TM\ was made available for users to begin gaining familiarity 
with a new approach

[[Page 48801]]

and process to submit ICD-10-PCS procedure code requests.
    As noted previously, interested parties had to submit MS-DRG 
classification change requests for FY 2023 by November 1, 2021. As we 
have discussed in prior rulemaking, we may not be able to fully 
consider all of the requests that we receive for the upcoming fiscal 
year. We have found that, with the implementation of ICD-10, some types 
of requested changes to the MS-DRG classifications require more 
extensive research to identify and analyze all of the data that are 
relevant to evaluating the potential change. We note in the discussion 
that follows those topics for which further research and analysis are 
required, and which we will continue to consider in connection with 
future rulemaking. Interested parties should submit any comments and 
suggestions for FY 2024 by October 20, 2022 via the new electronic 
intake system, Medicare Electronic Application Request Information 
SystemTM (MEARISTM) at: https://mearis.cms.gov/public/home.
    We provided a test version of the ICD-10 MS-DRG GROUPER Software, 
Version 40, in connection with the FY 2023 IPPS/LTCH PPS proposed rule 
so that the public can better analyze and understand the impact of the 
proposals included in the proposed rule. We noted that this test 
software reflected the proposed GROUPER logic for FY 2023. Therefore, 
it included the new diagnosis and procedure codes that are effective 
for FY 2023 as reflected in Table 6A.--New Diagnosis Codes--FY 2023 and 
Table 6B.--New Procedure Codes--FY 2023 that were associated with the 
proposed rule and did not include the diagnosis codes that are invalid 
beginning in FY 2023 as reflected in Table 6C.--Invalid Diagnosis 
Codes--FY 2023 associated with the proposed rule. We noted that at the 
time of the development of the proposed rule there were no procedure 
codes designated as invalid for FY 2023, and therefore, there was no 
Table 6D--Invalid Procedure Codes--FY 2023 associated with the proposed 
rule. Those tables were not published in the Addendum to the proposed 
rule, but are available via the internet on the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html as described in section VI. of the 
Addendum to the proposed rule. Because the diagnosis codes no longer 
valid for FY 2023 are not reflected in the test software, we made 
available a supplemental file in Table 6P.1a that includes the mapped 
Version 40 FY 2023 ICD-10-CM codes and the deleted Version 39.1 FY 2022 
ICD-10-CM codes that should be used for testing purposes with users' 
available claims data. Therefore, users had access to the test software 
allowing them to build case examples that reflect the proposals that 
were included in the proposed rule. In addition, users were able to 
view the draft version of the ICD-10 MS-DRG Definitions Manual, Version 
40.
    The test version of the ICD-10 MS-DRG GROUPER Software, Version 40, 
the draft version of the ICD-10 MS-DRG Definitions Manual, Version 40, 
and the supplemental mapping files in Table 6P.1a of the FY 2022 and FY 
2023 ICD-10-CM diagnosis codes are available at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software.
    Following are the changes that we proposed to the MS-DRGs for FY 
2023. We invited public comments on each of the MS-DRG classification 
proposed changes, as well as our proposals to maintain certain existing 
MS-DRG classifications discussed in the proposed rule. In some cases, 
we proposed changes to the MS-DRG classifications based on our analysis 
of claims data and consultation with our clinical advisors. In other 
cases, we proposed to maintain the existing MS-DRG classifications 
based on our analysis of claims data and consultation with our clinical 
advisors. As discussed in section I.F of the preamble of the proposed 
rule, we proposed to use the FY 2021 MedPAR data for purposes of this 
FY 2023 IPPS rulemaking, with certain proposed modifications to the 
relative weight and outlier methodologies. For the FY 2023 IPPS/LTCH 
PPS proposed rule, our MS-DRG analysis was based on ICD-10 claims data 
from the September 2021 update of the FY 2021 MedPAR file, which 
contains hospital bills received from October 1, 2020 through September 
30, 2021, for discharges occurring through September 30, 2021. In our 
discussion of the proposed MS-DRG reclassification changes, we referred 
to these claims data as the ``September 2021 update of the FY 2021 
MedPAR file.''
    In this FY 2023 IPPS/LTCH PPS final rule, we summarize the public 
comments we received on our proposals, present our responses, and state 
our final policies. For this FY 2023 final rule, we generally did not 
perform any further MS-DRG analysis of claims data. Therefore, the MS-
DRG analysis is based on ICD-10 claims data from the September 2021 
update of the FY 2021 MedPAR file, as set forth in the proposed rule, 
except as otherwise noted.
    As explained in previous rulemaking (76 FR 51487), in deciding 
whether to propose to make further modifications to the MS-DRGs for 
particular circumstances brought to our attention, we consider whether 
the resource consumption and clinical characteristics of the patients 
with a given set of conditions are significantly different than the 
remaining patients represented in the MS-DRG. We evaluate patient care 
costs using average costs and lengths of stay and rely on the judgment 
of our clinical advisors to determine whether patients are clinically 
distinct or similar to other patients represented in the MS-DRG. In 
evaluating resource costs, we consider both the absolute and percentage 
differences in average costs between the cases we select for review and 
the remainder of cases in the MS-DRG. We also consider variation in 
costs within these groups; that is, whether observed average 
differences are consistent across patients or attributable to cases 
that are extreme in terms of costs or length of stay, or both. Further, 
we consider the number of patients who will have a given set of 
characteristics and generally prefer not to create a new MS-DRG unless 
it would include a substantial number of cases.
    In the FY 2021 IPPS/LTCH PPS final rule (85 FR 58448), we finalized 
our proposal to expand our existing criteria to create a new 
complication or comorbidity (CC) or major complication or comorbidity 
(MCC) subgroup within a base MS-DRG. Specifically, we finalized the 
expansion of the criteria to include the NonCC subgroup for a three-way 
severity level split. We stated our belief that applying these criteria 
to the NonCC subgroup would better reflect resource stratification as 
well as promote stability in the relative weights by avoiding low 
volume counts for the NonCC level MS-DRGs. We noted that in our 
analysis of MS-DRG classification requests for FY 2021 that were 
received by November 1, 2019, as well as any additional analyses that 
were conducted in connection with those requests, we applied these 
criteria to each of the MCC, CC, and NonCC subgroups. We also noted 
that the application of the NonCC subgroup criteria going forward may 
result in modifications to certain MS-DRGs that are currently split 
into three severity levels and result in MS-DRGs that are split into 
two severity levels. We stated that any proposed modifications to the 
MS-DRGs would be addressed in future rulemaking consistent with our 
annual process and reflected in Table 5--Proposed List of Medicare 
Severity Diagnosis Related Groups (MS-DRGs),

[[Page 48802]]

Relative Weighting Factors, and Geometric and Arithmetic Mean Length of 
Stay for the applicable fiscal year.
    In the FY 2022 IPPS/LTCH PPS final rule (86 FR 44798), we finalized 
a delay in applying this technical criterion to existing MS-DRGs until 
FY 2023 or future rulemaking, in light of the PHE. Commenters 
recommended that a complete analysis of the MS-DRG changes to be 
proposed for future rulemaking in connection with the expanded three-
way severity split criteria be conducted and made available to enable 
the public an opportunity to review and consider the redistribution of 
cases, the impact to the relative weights, payment rates, and hospital 
case mix to allow meaningful comment prior to implementation.
    In our analysis of the MS-DRG classification requests for FY 2023 
that we received by November 1, 2021, as well as any additional 
analyses that were conducted in connection with those requests, we 
applied these criteria to each of the MCC, CC, and NonCC subgroups, as 
described in the following table.
[GRAPHIC] [TIFF OMITTED] TR10AU22.005

    In general, once the decision has been made to propose to make 
further modifications to the MS-DRGs as described previously, such as 
creating a new base MS-DRG, or in our evaluation of a specific MS-DRG 
classification request to split (or subdivide) an existing base MS-DRG 
into severity levels, all five criteria must be met for the base MS-DRG 
to be split (or subdivided) by a CC subgroup. We note that in our 
analysis of requests to create a new MS-DRG, we typically evaluate the 
most recent year of MedPAR claims data available. For example, in the 
FY 2023 IPPS/LTCH PPS proposed rule we stated our MS-DRG analysis was 
based on ICD-10 claims data from the September 2021 update of the FY 
2021 MedPAR file. However, in our evaluation of requests to split an 
existing base MS-DRG into severity levels, as noted in prior rulemaking 
(80 FR 49368), we typically analyze the most recent 2 years of data. 
This analysis includes 2 years of MedPAR claims data to compare the 
data results from 1 year to the next to avoid making determinations 
about whether additional severity levels are warranted based on an 
isolated year's data fluctuation and also, to validate that the 
established severity levels within a base MS-DRG are supported. The 
first step in our process of evaluating if the creation of a new CC 
subgroup within a base MS-DRG is warranted is to determine if all the 
criteria are satisfied for a three-way split. If the criteria fail, the 
next step is to determine if the criteria are satisfied for a two-way 
split. If the criteria for both of the two-way splits fail, then a 
split (or CC subgroup) would generally not be warranted for that base 
MS-DRG. If the three-way split fails on any one of the five criteria 
and all five criteria for both two-way splits (1_23 and 12_3) are met, 
we would apply the two-way split with the highest R2 value. We note 
that if the request to split (or subdivide) an existing base MS-DRG 
into severity levels specifies the request is for either one of the 
two-way splits (1_23 or 12_3), in response to the specific request, we 
will evaluate the criteria for both of the two-way splits,

[[Page 48803]]

however we do not also evaluate the criteria for a three-way split.
    In the FY 2023 IPPS/LTCH PPS proposed rule, we stated that using 
the September 2021 update of the FY 2021 MedPAR file, we analyzed how 
applying the NonCC subgroup criteria to all MS-DRGs currently split 
into three severity levels would affect the MS-DRG structure beginning 
in FY 2023. We noted that findings from our analysis indicated that 
approximately 41 MS-DRGs would be subject to change based on the three-
way severity level split criterion finalized in FY 2021. Specifically, 
we found that applying the NonCC subgroup criteria to all MS-DRGs 
currently split into three severity levels would result in the deletion 
of 123 MS-DRGs (41 MS-DRGs x 3 severity levels = 123) and the creation 
of 75 new MS-DRGs. We further noted that these updates would also 
involve a redistribution of cases, which would impact the relative 
weights, and, thus, the payment rates proposed for particular types of 
cases. We referred the reader to Table 6P.1b associated with the 
proposed rule for the list of the 123 MS-DRGs that would be subject to 
deletion and the list of the 75 new MS-DRGs that would be proposed for 
creation for FY 2023 under this policy if the NonCC subgroup criteria 
were applied.
    We stated in the proposed rule that in light of the ongoing public 
health emergency (PHE), we continue to have concerns about the impact 
of implementing this volume of MS-DRG changes at this time, and believe 
it may be appropriate to continue to delay application of the NonCC 
subgroup criteria to existing MS-DRGs to maintain more stability in the 
current MS-DRG structure and until such time additional analyses can be 
performed to assess impacts, as discussed in response to comments in 
the FY 2022 IPPS/LTCH PPS final rule. Therefore, we proposed to delay 
application of the NonCC subgroup criteria to existing MS-DRGs with a 
three-way severity level split for FY 2023, and to instead maintain the 
current structure of the 41 MS-DRGs that currently have a three-way 
severity level split (total of 123 MS-DRGs) that would otherwise be 
subject to these criteria. We stated that we intend to address the 
application of the NonCC subgroup criteria to existing MS-DRGs with a 
three-way severity level split in future rulemaking.
    Comment: Commenters expressed overwhelming support for our proposal 
to delay application of the NonCC subgroup criteria to existing MS-DRGs 
with a three-way severity level split for FY 2023 and to maintain the 
current structure of the MS-DRGs. A few commenters who agreed with the 
proposal to delay the application of the NonCC subgroup criteria also 
requested that CMS provide interested parties with an opportunity to 
review and comment on impacts to the relative weights before a proposal 
is finalized. The commenters stated it would be helpful if CMS made 
claims data available, including volumes by MS-DRG, that support the 
proposal to reduce the 123 MS-DRGs.
    Response: We thank the commenters for their support. In response to 
the commenters who requested the opportunity to review and comment on 
impacts to the relative weights before a proposal is finalized, we 
intend to provide a comprehensive analysis in future rulemaking based 
on the comments and feedback we have received. We are providing the 
claims data from the September 2021 update of the FY 2021 MedPAR file 
that was reviewed for FY 2023 in our analyses of how applying the NonCC 
subgroup criteria to all MS-DRGs currently split into three severity 
levels would have potentially affected the MS-DRG structure beginning 
in FY 2023. We refer the reader to Table 6P.1b associated with this 
final rule and available via the internet on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS.
    Comment: A commenter who strongly agreed with the proposal to delay 
the application of the NonCC subgroup criteria stated that in addition 
to providing a detailed explanation and impact files in the future, 
that CMS should consider clarifying and addressing the following 
issues: why the list of MS-DRGs that were proposed to be removed in FY 
2022 is not the same list of MS-DRGs proposed to be removed for FY 
2023, why the list of MS-DRGs that were proposed to become a single, 
base MS-DRG for FY 2022 now appear to meet the criteria for a three-way 
severity level split for FY 2023, and why MS-DRGs proposed to maintain 
a three-way severity level split for FY 2022 now appear to meet the 
criteria for a two-way or three-way severity level split for FY 2023. 
This commenter also stated that the MS-DRGs displayed in Table 6P.1b 
associated with the proposed rule include a list of MS-DRGs that would 
be subject to deletion and a list of MS-DRGs that would be proposed for 
creation with XXX for the numbers. According to the commenter, many of 
the listed MS-DRGs have the same narrative description, however, it 
appears they would obtain a new MS-DRG number. The commenter questioned 
why MS-DRGs with the same description would have new MS-DRG numbers 
assigned. This commenter also suggested that CMS consider patient case-
mix with regard to volumes, and stated Medicare would not have the 
volume for the obstetric related MS-DRGs. The commenter requested that 
CMS also examine the impact of maternal health quality initiatives and 
maternity hospital designation in connection with the solicitation for 
comments on low volume MS-DRGs. Lastly, the commenter recommended that 
CMS utilize two years of good data to examine the impact of the 
proposed redistribution in future analyses and determine if the 
proposed MS-DRG changes and associated relative weights appropriately 
reflect resource consumption.
    Response: We appreciate the commenter's feedback. We acknowledge 
that the list of MS-DRGs identified as potentially subject to removal 
for FY 2022 differs from the list of MS-DRGs identified as potentially 
subject to removal and provided for FY 2023 in connection with the 
NonCC subgroup criteria discussion. We also acknowledge that the list 
of MS-DRGs identified as potentially subject to creation for FY 2022 
differs from the list of MS-DRGs identified as potentially subject to 
removal and provided for FY 2023 in connection with the NonCC subgroup 
criteria discussion. The lists differ as a result of the claims data 
that was analyzed for our MS-DRG analysis and rulemaking each fiscal 
year. We provided the results of both the FY 2019 and FY 2020 MedPAR 
claims data as displayed in Table 6P.11 in association with the FY 2022 
IPPS/LTCH PPS final rule (available via the internet on the CMS website 
at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS).
    By comparison, for FY 2023, consistent with our finalized policy to 
use the FY 2021 MedPAR data for purposes of this FY 2023 rulemaking, we 
have provided the FY 2021 MedPAR claims data for the listed MS-DRGs in 
Table 6P.1b in association with this final rule, as noted earlier in 
this section. Because there is variation in the claims data reported 
from year to year, it is expected that there may be fluctuations in the 
data that could affect the list of MS-DRGs potentially subject to 
change in connection with the application of the NonCC subgroup 
criteria for a particular fiscal year. However, we believe that 
reliability and stability of the data is an important consideration 
with respect to the

[[Page 48804]]

application of the NonCC subgroup criteria and will give careful 
consideration to the number of years of data to analyze in connection 
with any future proposed policy changes as well as the impacts on 
relative weights, as we continue to assess all the comments and 
feedback we have received, particularly in light of the ongoing public 
health emergency. We also take this opportunity to note that the listed 
MS-DRGs as displayed in the tables (for both FY 2022 and FY 2023) are 
for illustrative purposes as the intent was to show the MS-DRGs that 
would potentially be subject to deletion and the MS-DRGs that would 
potentially be subject to creation if the NonCC subgroup criteria were 
to be applied for the applicable fiscal year. Because we did not 
propose the application of these criteria to existing MS-DRGs with a 
three-way severity level split for either FY 2022 or FY 2023, and we 
have not yet completed the comprehensive impact analysis of any such 
future proposed changes, as previously discussed, we are clarifying 
that both the MS-DRG numbers and MS-DRG titles that may eventually be 
subject to change in connection with a future proposal to apply the 
NonCC subgroup criteria may, in the interim, be subject to further 
modifications as a result of our annual review of the MS-DRG 
classifications. As such, any future proposed MS-DRG changes will be 
considered in connection with the analysis that is performed for 
application of the MCC, CC and NonCC subgroup criteria to the MS-DRGs 
that are in effect at that time.
    In response to the commenter's question regarding why new MS-DRG 
numbers would be considered, we note that new MS-DRG numbers are 
preferred because we anticipate that individuals, payers, and 
organizations conducting analysis would need to be aware if proposed 
changes to base DRG concepts are made to allow them time to adjust 
their programs, analyses, or queries that may have hard coded the DRG 
numbers. Other agencies that utilize MS-DRGs may perform minimal 
updates to their relative weights, quality risk adjustment or exclusion 
criteria and only focus on new MS-DRGs, thereby potentially creating 
additional operational or system challenges if an existing MS-DRG 
number were to be reused. To minimize confusion for those who rely on 
MS-DRG concepts year to year, and avoid unintended consequences from 
the reuse of an existing DRG number for a different concept, we believe 
it is appropriate to consider revisions to both the MS-DRG number and 
corresponding description.
    Comment: Other commenters requested CMS consider continuing the 
delay beyond the period of the public health emergency (PHE). The 
commenters indicated that hospital claims and cost report data impacted 
by the COVID-19 pandemic should not be used as the basis of MS-DRG 
consolidation since utilization may be artificially low during the PHE.
    Response: We thank the commenters for their feedback. As stated 
earlier in this section, we are giving careful consideration to all the 
recommendations and suggestions we have received in connection with the 
NonCC subgroup criteria discussion.
    Comment: Another commenter expressed concern with regard to how the 
NonCC subgroup criteria are to be applied. The commenter stated they 
understood the policy to mean that the NonCC subgroup criteria would 
only be applied to new requests for MS-DRG splits, not to existing MS-
DRGs. The commenter also stated they were unclear when the proposal was 
finalized since, according to the commenter, CMS would have needed to 
specify the intent to apply the NonCC subgroup criteria to all existing 
MS-DRGs versus only for the creation of new MS-DRGs. Additionally, this 
commenter urged CMS to conduct a full analysis that demonstrates the 
explanatory power of the proposed new MS-DRGs is an improvement over 
the current MS-DRGs, similar to the analysis that was performed for the 
transition from CMS DRGs to MS-DRGs in FY 2008. The commenter indicated 
that a comprehensive analysis is critical for interested parties to 
provide meaningful comments.
    Response: In the FY 2022 IPPS/LTCH PPS final rule (86 FR 44796), we 
summarized the discussion pertaining to the NonCC subgroup criteria 
policy finalized for FY 2021. In that discussion we noted that the 
application of the NonCC subgroup criteria going forward may result in 
modifications to certain MS-DRGs that are currently split into three 
severity levels and result in MS-DRGs that are split into two severity 
levels. We stated that any proposed modifications to the MS-DRGs would 
be addressed in future rulemaking consistent with our annual process 
and reflected in Table 5--Proposed List of Medicare Severity Diagnosis 
Related Groups (MS-DRGs), Relative Weighting Factors, and Geometric and 
Arithmetic Mean Length of Stay for the applicable fiscal year. As 
discussed in the proposed rule, we applied the nonCC subgroup criteria 
to each of the MCC, CC, and NonCC subgroups, in our analysis of the MS-
DRG classification requests for FY 2023 that we received by November 1, 
2021, as well as any additional analyses that were conducted in 
connection with those requests. We also note that new requests to 
subdivide a MS-DRG frequently pertain to existing MS-DRGs which differs 
from requests to create a new base MS-DRG for which the criteria to 
create subgroups is subsequently applied. In response to the 
commenter's recommendation that CMS conduct a full analysis similar to 
the analysis that was performed for the transition from CMS DRGs to MS-
DRGs in FY 2008, we appreciate the commenter's suggestion and will take 
it under advisement.
    Comment: Another commenter who recognized differences between the 
list of MS-DRGs shown for FY 2022 and FY 2023 requested additional 
transparency for the data being presented for review and for CMS to 
consider analyzing data from other databases, such as Medicaid or 
States, to supplement the MS-DRGs known to have lower volumes among the 
Medicare population (for example, Obstetric MS-DRGs). This commenter 
also expressed concern about the potential impact to community 
hospitals if proposed MS-DRG changes in connection with the NonCC 
subgroup criteria result in significant MS-DRG redistribution.
    Response: We thank the commenter for their feedback. As discussed 
previously, we intend to conduct a comprehensive analysis of the 
application of the NonCC subgroup criteria that would be made publicly 
available for review and comment in connection with any proposed MS-DRG 
changes for future rulemaking.
    After consideration of the public comments we received, we are 
finalizing our proposal to delay the application of the NonCC subgroup 
criteria to existing MS-DRGs with a three-way severity level split 
until FY 2024 or later, and are finalizing for FY 2023 to maintain the 
current structure of the 41 MS-DRGs that currently have a three-way 
severity level split.
    We are making the FY 2023 ICD-10 MS-DRG GROUPER and Medicare Code 
Editor (MCE) Software Version 40, the ICD-10 MS-DRG Definitions Manual 
files Version 40 and the Definitions of Medicare Code Edits Manual 
Version 40 available to the public on our CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software.

[[Page 48805]]

2. Pre-MDC: MS-DRG 018 Chimeric Antigen Receptor (CAR) T-cell and Other 
Immunotherapies
    In the FY 2022 IPPS/LTCH PPS final rule (86 FR 44798 through 
44806), we finalized our proposal to assign procedure codes describing 
CAR T-cell, non-CAR T-cell, and other immunotherapies to Pre-MDC MS-DRG 
018 and to revise the title for Pre-MDC MS-DRG 018 to ``Chimeric 
Antigen Receptor (CAR) T-cell and Other Immunotherapies'' to reflect 
this assignment. In that discussion, we noted that a few commenters 
recommended we continue to work with interested parties on ways to 
improve the predictability and stability of hospital payments for these 
complex, novel cell therapies and that we should continue to monitor 
and assess the appropriateness of therapies assigned to MS-DRG 018, if 
they continue to be aligned on resource use, and whether additional 
refinements or MS-DRGs may be warranted in the future.
    We also noted that the process of code creation and proposed 
assignment to the most appropriate MS-DRG exists independently, 
regardless of whether there is an associated application for a new 
technology add-on payment for a product or technology submitted for 
consideration in a given fiscal year. Specifically, requests for a new 
code(s) or updates to existing codes are addressed through the ICD-10 
Coordination and Maintenance Committee meetings, held annually in the 
spring and fall, where code proposals are presented and the public is 
provided the opportunity to comment. All codes finalized from the fall 
meeting are subsequently proposed for assignment under the ICD-10 MS-
DRGs through rulemaking. We refer the reader to section II.D.17 of the 
preamble of this final rule for additional information regarding the 
ICD-10 Coordination and Maintenance Committee meeting process.
    As stated in the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28130), 
there were no requests or proposals for new procedure codes to describe 
the administration of a CAR T-cell or another type of gene or cellular 
therapy discussed at the September 14-15, 2021 ICD-10 Coordination and 
Maintenance Committee meeting. For the March 8-9, 2022 ICD-10 
Coordination and Maintenance Committee meeting, there were topics 
included on the agenda and in the related meeting materials that 
included proposals for new procedure codes to describe the 
administration of a CAR T-cell or another type of gene or cellular 
therapy product. The agenda and related meeting materials for these 
specific topics are available via the internet on the CMS website at: 
https://www.cms.gov/Medicare/Coding/ICD10/C-and-M-Meeting-Materials.
    As stated in the FY 2022 IPPS/LTCH PPS final rule (86 FR 44805) and 
noted previously, the process of code creation and proposed assignment 
to the most appropriate MS-DRG exists independently, regardless of 
whether there is an associated application for a new technology add-on 
payment for a product or technology submitted for consideration in a 
given fiscal year. We also clarified that the assignment of a procedure 
code to a MS-DRG is not dependent upon a product's FDA approval. 
Similarly, the creation of a code to describe a technology that is 
utilized in the performance of a procedure or service does not require 
FDA approval of the technology.
    Because the diagnosis and procedure code proposals that are 
presented at the March meeting for an October 1 implementation 
(upcoming FY) are not finalized in time to include in Table 6A.--New 
Diagnosis Codes and Table 6B.--New Procedure Codes in association with 
the proposed rule, as noted in prior rulemaking, we use our established 
process to examine the MS-DRG assignment for the predecessor codes to 
determine the most appropriate MS-DRG assignment. Specifically, we 
review the predecessor code and MS-DRG assignment most closely 
associated with the new procedure code, and in the absence of claims 
data, we consider other factors that may be relevant to the MS-DRG 
assignment, including the severity of illness, treatment difficulty, 
complexity of service and the resources utilized in the diagnosis or 
treatment of the condition. We have noted in prior rulemaking that this 
process does not automatically result in the new procedure code being 
assigned to the same MS-DRG or to have the same designation (O.R. 
versus Non-O.R.) as the predecessor code.
    As stated in the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28130), 
in response to commenters' recommendation that we continue to assess 
the appropriateness of the therapies assigned to Pre-MDC MS-DRG 018, we 
provided the results of our data analysis using the September 2021 
update of the FY 2021 MedPAR file for cases reporting the 
administration of a CAR T-cell or other immunotherapy in Pre-MDC MS-DRG 
018 and the number of cases reporting a secondary diagnosis of Z00.6 
(Encounter for examination for normal comparison and control in 
clinical research program). We noted that if a procedure code that is 
assigned to the logic for Pre-MDC MS-DRG 018 is not listed it is 
because there were no cases found. We also noted there were no cases 
reporting diagnosis code Z00.6 as a principal diagnosis. Our findings 
are shown in the following table.

[[Page 48806]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.006

    The data show that there is a wide range in the volume of cases (4 
cases versus 435 cases), average length of stay (11.3 days versus 20.3 
days), and average costs ($157,950 versus $310,561) reporting the 
administration of CAR T-cell therapies in MS-DRG 018. This is to be 
expected since these therapies continue to evolve and the ICD-10-PCS 
coding to identify and describe these therapies also continues to be 
refined through the ICD-10 Coordination and Maintenance Committee 
meeting process. As additional claims data becomes available for these 
therapies, we will continue to evaluate to determine if further 
modifications to Pre-MDC MS-DRG 018 are warranted.
    We noted in the proposed rule that in response to our statement in 
the FY 2022 IPPS/LTCH PPS final rule that we plan to continue engaging 
with interested parties on additional options for consideration in this 
field of cellular and gene therapies, we received additional feedback 
and suggestions, including recommendations for Town Hall meetings/
listening sessions to discuss the interconnectedness of these issues; 
exploration of what was described as a different set and kind of MS-
DRGs that would reward providers for controlling patient care costs, 
without consideration of product costs outside of their control; and 
evaluation of the creation and assignment of multiple MS-DRGs for cell 
and gene therapy cases: one to cover patient care costs, the other to 
cover product costs across therapeutic product categories.
    We stated we appreciated this additional feedback and will continue 
to consider these issues and suggestions in connection with future 
rulemaking. We also stated we intend to continue engaging with 
interested parties by sharing updates from our analysis of claims data 
as we examine and explore potential refinements for these therapies 
under the IPPS.
    Comment: Several commenters expressed support and appreciation that 
for FY 2023, CMS proposed to maintain the current structure of Pre-MDC 
MS-DRG 018 that includes ``Other Immunotherapies'', and to maintain its 
current methodology used to determine the relative weight. Some 
commenters acknowledged that it is difficult to predict what the 
associated costs will be in the future for CAR T-cell and other 
immunotherapies that remain under development. These commenters urged 
CMS to consider factors such as new or different side effects and how 
other therapeutic agents that could be administered simultaneously in 
connection with these therapies may potentially lead to toxicity, as 
continued monitoring of resource utilization and data analysis for Pre-
MDC MS-DRG 018 occurs. Other commenters commended CMS for its 
commitment to engage with interested parties as the agency continues to 
analyze claims data and consider the feedback that has been received to 
date for these therapies.
    Response: We thank the commenters for their support and appreciate 
the additional feedback on other factors to consider as we continue to 
monitor and analyze the data for Pre-MDC MS-DRG 018. As noted in prior 
rulemaking, we have received several suggestions, recommendations, and 
options pertaining to how CAR T-cell and other immunotherapies may be 
classified under the IPPS in the future. We intend to further examine 
the feedback received and maintain transparency in our approach moving 
forward, with the shared goal of enabling continued access to these and 
other vital treatments for Medicare beneficiaries.
    Comment: Similar to the public comments received in response to the 
FY 2022 IPPS/LTCH PPS proposed rule, for FY 2023, some commenters again 
expressed concerns with the non-CAR T-cell therapies and other 
immunotherapies that may be assigned to Pre-MDC MS-DRG 018 and stated 
that these potential assignments could lead to fluctuations in the 
relative weight. A few commenters requested that Pre-MDC MS-DRG 018 be 
limited to CAR T-cell therapies. Other commenters encouraged CMS to 
clarify its methodology and criteria for assigning new procedure codes 
to Pre-MDC MS-DRG 018. Some commenters expressed continued concern with 
the revision to the title for Pre-MDC MS-DRG 018 that was finalized 
effective FY

[[Page 48807]]

2022 to include ``Other Immunotherapies''.
    Response: In the FY 2022 IPPS/LTCH PPS final rule (86 FR 44798 
through 44806), we provided detailed summaries and responses to these 
same or similar concerns and comments. In the FY 2023 IPPS/LTCH PPS 
proposed rule (87 FR 28129 through 28131), we provided an overview of 
the assignment of new procedure codes to Pre-MDC MS-DRG 018 and 
reiterated much of the discussion from FY 2022 rulemaking. As stated in 
prior rulemaking, the MS-DRG system is a system of averages and it is 
expected that within the diagnostic related groups, some cases may 
demonstrate higher than average costs, while other cases may 
demonstrate lower than average costs. We have not made any changes to 
our established processes or methodologies for MS-DRG assignment of new 
procedure codes, including with regard to case assignment to Pre-MDC 
MS-DRG 018, and we refer the reader to the detailed discussion related 
to Pre-MDC MS-DRG 018 in the FY 2022 IPPS/LTCH PPS final rule. We note 
that additional claims data is needed to fully analyze and consider all 
the recommendations we have received, and to potentially develop 
alternative proposals with respect to payment for these therapies under 
the IPPS. There is also uncertainty with regard to the number and types 
of therapies currently under development or undergoing studies and how 
soon they will be available. We recognize the concerns that have been 
expressed by commenters and we are also continuing to assess the 
reliability and stability of the data in light of the ongoing public 
health emergency.
    Comment: Many commenters expressed appreciation to CMS for 
providing transparency with the cases reporting the administration of a 
CAR T-cell or other immunotherapy in the FY 2021 MedPAR claims data for 
Pre-MDC MS-DRG 018. However, a commenter indicated there was confusion 
about the coded claims data as presented in the proposed rule since the 
procedure codes described as new technology group 7 became effective 
October 1, 2021 (FY 2022), which is one year later than the FY 2021 
data that was shown in the table in the preamble of the proposed rule. 
The commenter requested that CMS provide clarification to help 
eliminate any additional confusion for readers and interested parties 
who also analyze the data for these therapies.
    Response: We thank the commenters for their support. The FY 2021 
MedPAR claims data were regrouped using the proposed FY 2023 MS-DRG 
classifications, therefore, coded claims data for the procedure codes 
describing the administration of CAR T-cell and other immunotherapy 
agents reported in FY 2021 was mapped from the FY 2021 MedPAR coded 
claims data to the procedure codes that are effective for FY 2023. 
Specifically, the codes that were effective for FY 2021 and are no 
longer valid were mapped to the new procedure codes that are valid for 
FY 2023. We also note, as generally stated in the preamble of the 
proposed rule each year, the diagnosis and procedure codes from the 
specified FY MedPAR claims data are grouped through the applicable 
version of the proposed FY GROUPER. For example, as discussed in 
section II.E.1. of the preamble of the proposed rule (87 FR 28197), the 
proposed FY 2023 relative weights are based on the ICD-10-CM diagnosis 
codes and ICD-10-PCS procedure codes from the FY 2021 MedPAR claims 
data, grouped through the ICD-10 version of the proposed FY 2023 
GROUPER (Version 40).
    Comment: A commenter suggested that CMS consider establishing a 
timeframe that would enable the public to comment on procedure codes 
that may be assigned to Pre-MDC MS-DRG 018 upon being approved and 
finalized after the spring ICD-10 Coordination and Maintenance 
Committee meeting. The commenter stated that currently, because 
procedure codes that are discussed at the spring ICD-10 Coordination & 
Maintenance (C&M) Committee meeting do not receive proposed assignments 
and are not published with the IPPS proposed rule given the timing, 
there is no opportunity for interested parties to provide feedback to 
CMS about MS-DRG assignments for new codes, including assignment to MS-
DRG-018. The commenter acknowledged the C&M meeting is not the 
appropriate forum for the public to provide input on MS-DRG assignment, 
however, because Pre-MDC MS-DRG 018 currently has a limited number of 
procedure codes assigned to it, the commenter stated that interested 
parties should have the opportunity to review and comment on potential 
assignment to Pre-MDC MS-DRG 018. This commenter also maintained that 
it has a unique relationship with the therapies currently assigned to 
Pre-MDC MS-DRG 018 as its membership is the predominant specialty 
society associated with these therapies and has the experience and 
clinical understanding related to resource utilization associated with 
the administration of these therapies.
    Response: We appreciate the commenter's feedback. As discussed 
elsewhere in this rule as well as in prior rulemaking, because the 
procedure code proposals discussed at the Spring ICD-10 Coordination 
and Maintenance Committee meeting are not finalized in time to include 
in Table 6B.--New Procedure codes associated with the proposed rule, 
CMS uses an established process to determine the most appropriate MS-
DRG assignment for these new procedure codes for the upcoming fiscal 
year. While we understand and acknowledge the uniqueness of CAR T-cell, 
gene, and cellular therapies, we believe it is necessary to further 
examine how and when we could alter our current methodology and 
timelines to provide the opportunity for interested parties to submit 
comments and feedback in the assignment of new procedure codes that are 
finalized after the spring meeting. We also note, as discussed in the 
proposed rule (87 FR 28130), all codes finalized from the fall meeting 
are subsequently proposed for assignment under the ICD-10 MS-DRGs 
through rulemaking, therefore, interested parties seeking the 
opportunity to more fully comment on potential MS-DRG assignment(s) 
have the opportunity to submit requests for consideration of proposed 
new procedure codes in association with these therapies to be discussed 
at the fall meeting versus the spring meeting. Alternatively, 
interested parties may use current coding information as shown in the 
ICD-10 Coordination and Maintenance Committee meeting materials to 
consider the potential MS-DRG assignments for any procedure codes that 
may be finalized after the March meeting and submit public comments for 
consideration.
    As noted in the proposed rule, for the March 8-9, 2022 ICD-10 
Coordination and Maintenance Committee meeting there were two topics 
included on the agenda and in the related meeting materials that 
included proposals for new procedure codes to describe the 
administration of a CAR T-cell or another type of gene or cellular 
therapy product. The two topics are Administration of afamitresgene 
autoleucel (afami-cel), a specific peptide enhanced affinity receptor 
(SPEAR) T-cell therapy and Administration of Tabelecleucel (tab-
cel[supreg]), an allogeneic Epstein-Barr virus (EBV)-specific T-cell 
immunotherapy, both of which were approved for new procedure codes 
following the March meeting. We refer the reader to the CMS website at 
https://www.cms.gov/Medicare/Coding/ICD10/C-and-M-Meeting-Materials for 
additional detailed information regarding these code requests.

[[Page 48808]]

    Because the diagnosis and procedure code proposals that are 
presented at the March ICD-10-CM Coordination and Maintenance Committee 
meeting for an October 1 implementation (upcoming FY) are not finalized 
in time to include in Table 6A.--New Diagnosis Codes and Table 6B.--New 
Procedure Codes in association with the proposed rule, as we have noted 
in prior rulemaking, we use our established process to examine the MS-
DRG assignment for the predecessor codes to determine the most 
appropriate MS-DRG assignment. Specifically, we review the predecessor 
code and MS-DRG assignment most closely associated with the new 
procedure code, and in the absence of claims data, we consider other 
factors that may be relevant to the MS-DRG assignment, including the 
severity of illness, treatment difficulty, complexity of service and 
the resources utilized in the diagnosis and/or treatment of the 
condition. We have noted in prior rulemaking that this process does not 
automatically result in the new procedure code being assigned to the 
same MS-DRG or to have the same designation (O.R. versus Non-O.R.) as 
the predecessor code. As shown in Table 6B.--New Procedure Codes 
associated with this final rule and available via the internet on the 
CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS, new procedure codes for these two therapies 
have been finalized for assignment to Pre-MDC MS-DRG 018 effective with 
discharges on and after October 1, 2022 (FY 2023).
    We appreciate the public comments we received, and, as noted, will 
continue to evaluate the recommendations and options provided by 
commenters related to these therapies as well as to monitor the 
available claims data.
3. MDC 01 (Diseases and Disorders of the Nervous System)
a. Laser Interstitial Thermal Therapy (LITT)
    In the FY 2022 IPPS/LTCH PPS final rule (86 FR 44812 through 
44814), we finalized the reassignment of 31 ICD-10-PCS procedure codes 
describing laser interstitial thermal therapy (LITT) of various body 
parts to more clinically appropriate MS-DRGs, as shown in Table 6P.2b 
associated with the FY 2022 IPPS/LTCH PPS final rule and available via 
the internet on the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS, including the 
reassignment of procedure codes D0Y0KZZ (Laser interstitial thermal 
therapy of brain) and D0Y1KZZ (Laser interstitial thermal therapy of 
brain stem), which were reassigned from MS-DRG 023 (Craniotomy with 
Major Device Implant or Acute Complex CNS Principal Diagnosis with MCC 
or Chemotherapy Implant or Epilepsy with Neurostimulator), MS-DRG 024 
(Craniotomy with Major Device Implant or Acute Complex CNS Principal 
Diagnosis without MCC), and MS-DRGs 025, 026, and 027 (Craniotomy and 
Endovascular Intracranial Procedures with MCC, with CC, and without CC/
MCC, respectively) to MS-DRGs 040, 041, and 042 (Peripheral, Cranial 
Nerve and Other Nervous System Procedures with MCC, with CC and without 
CC/MCC, respectively).
    We also finalized the redesignation of these two LITT procedures 
(codes D0Y0KZZ and D0Y1KZZ) and the reassignment from extensive O.R. 
procedures in MS-DRGs 981, 982 and 983 (Extensive O.R. Procedure 
Unrelated to Principal Diagnosis with MCC, with CC, and without CC/MCC, 
respectively) to non-extensive O.R. procedures in MS-DRGs 987, 989, and 
989 (Non-Extensive O.R. Procedure Unrelated to Principal Diagnosis with 
MCC, with CC, and without CC/MCC, respectively) (86 FR 44889).
    As discussed in the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 
28131), for FY 2023, we received two requests from the manufacturers of 
the LITT technology (Medtronic and Monteris[supreg] Medical) to reverse 
the MS-DRG reassignment for the ICD-10 procedure codes that identify 
LITT of the brain and brain stem (codes D0Y0KZZ and D0Y1KZZ) from the 
MS-DRGs for peripheral, cranial nerve and other nervous system 
procedures (MS-DRGs 040, 041, and 042) back to the MS-DRGs for 
craniotomy and endovascular procedures (MS-DRGs 023, 024, 025, 026, and 
027). The first requestor acknowledged that the technique utilized in 
the performance of LITT procedures for the brain and brain stem are 
minimally invasive and do not involve a craniotomy however, the 
requestor also stated the procedures assigned to MS-DRGs 025, 026, and 
027 are not exclusive to craniotomies. The requestor further stated 
that these LITT procedures involve a twist drill or burr hole and are 
similar to other non-craniotomy procedures in MS-DRGs 025, 026, and 027 
including radioactive elements and neurostimulator leads that involve 
inserting these devices into the brain.
    In its review of the other procedures assigned to MS-DRGs 040, 041, 
and 042, the requestor stated that there are distinct clinical 
differences between the invasiveness of LITT that involves 
instrumentation being placed deeply within the brain tissue and the 
non-invasiveness of stereotactic radiosurgery that does not involve 
entering the brain with instrumentation. The requestor also indicated 
LITT utilizes a different modality via direct thermal ablation compared 
to stereotactic radiosurgery that utilizes externally-generated 
ionizing radiation.
    The requestor performed its own data analysis for LITT procedures 
of the brain and brain stem using MedPAR data from FY 2019 through FY 
2022 impact files. According to the requestor, its findings demonstrate 
that the costs of the cases reporting LITT of the brain or brain stem 
are better aligned with MS-DRGs 025, 026, and 027 compared to MS-DRGs 
040, 041, and 042.
    The second requestor similarly discussed the steps and resources 
involved in the performance of LITT procedures for the brain and brain 
stem, provided its detailed analysis on the indications for LITT (brain 
tumors and epileptic foci), compared LITT to other procedures in MS-
DRGs 025, 026, and 027 and stated that the majority of the procedures 
currently assigned to MS-DRGs 040, 041, 042 are not performed for the 
treatment of brain cancer or epilepsy. The requestor stated that the 
LITT procedure is on the inpatient only list and is only performed on 
Medicare beneficiaries in the inpatient hospital setting. The requestor 
provided the top 10 principal diagnoses associated with LITT of brain 
cases it found based on its analysis, and identified the diagnoses for 
which there were less than 10 cases with an asterisk, as reflected in 
the following table.

[[Page 48809]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.007

    The requestor asserted that the statement in the FY 2022 IPPS/LTCH 
PPS final rule that the technique to perform the LITT procedure on 
brain and brain stem structures is considered minimally invasive and 
does not involve a craniotomy, and that therefore, continued assignment 
to the craniotomy MS-DRGs is not clinically appropriate, 
mischaracterizes both the LITT procedures and universe of services 
assigned to MS-DRGs 023 through 027. The requestor acknowledged that 
the craniotomy procedures listed in the logic for MS-DRGs 023 through 
027 include open procedures but stated the logic also lists less 
invasive procedures including percutaneous and percutaneous endoscopic 
procedures. The requestor asserted that open procedures are a minority 
of the ICD-10-PCS codes assigned to these MS-DRGs.
    In addition, the requestor stated that LITT and craniotomy are in 
fact very clinically similar; in that both procedures are intended to 
remove and destroy the targeted tumor and lesion with a different 
surgical tool used (scalpel versus heated ablation probe). According to 
the requestor, brain LITT procedures involve insertion of laser probes 
into the brain which requires opening both the skull and dura, similar 
to a craniotomy. The requestor also stated that craniotomy and LITT 
share several procedural characteristics and provided the following 
list.
     Require an operating room;
     Performed under general anesthesia;
     Require creation of burr holes and invasive skull 
fixation;
     Require a sterile field, incision, opening of the skull 
and dura;
     Cause tissue to be immediately destroyed or excised;
     Carry a risk of immediate intracranial bleeding;
     Require closure of the scalp wound;
     Risk intracranial infection; and
     Require a hospital stay of one or more nights.
    In contrast, the requestor stated that procedures assigned to MS-
DRGs 040, 041, and 042 are primarily nerve procedures or excision or 
detachment procedures performed on parts of the body other than the 
head, including the upper and lower extremities. According to the 
requestor, none of the procedures in MS-DRGs 040, 041, and 042 require 
drilling into the patient's skull, a step which is integral to LITT. 
The requestor provided the following top 10 principal diagnoses 
associated with cases it found in MS-DRGs 040, 041, and 042 during its 
analysis and stated that most of the procedures assigned to MS-DRGs 
040, 041, and 042 are not typically performed in the treatment of brain 
cancer or epilepsy.
[GRAPHIC] [TIFF OMITTED] TR10AU22.008


[[Page 48810]]


    However, the requestor stated an exception is stereotactic 
radiosurgery (SRS) procedures performed on the brain and brain stem 
that are assigned to MS-DRGs 040, 041, and 042 and are used to treat 
brain cancer. According to the requestor, craniotomy, LITT and SRS are 
all image-guided procedures used to treat a variety of brain disorders 
including tumors and epilepsy, although it stated that is where any 
similarity between LITT and SRS ends and where the procedural 
similarities between craniotomy and LITT begin.
    The requestor stated SRS is a non-invasive procedure that gradually 
destroys or inactivates tissues in or around the brain and is typically 
performed on an outpatient basis while inpatient SRS treatment is rare. 
According to the requestor, SRS does not require an operating room, is 
rarely done under general anesthesia (children and highly 
claustrophobic individuals being an exception), and does not require 
(but can use) rigid skull fixation. In addition, the requestor stated 
that because it is non-invasive, there is no need for a sterile field, 
incision, opening/closing of the skull, opening/closing of the dura, 
suturing/stapling the wound, and produces essentially no risk of 
immediate intracranial bleeding or delayed infection. According to the 
requestor, LITT is much more invasive than SRS using a head frame and 
involves and requires the same surgical skill and hospital resources as 
craniotomies.
    In the proposed rule we noted that following the submission of the 
two FY 2023 MS-DRG classification change requests for LITT, these same 
two requestors (the manufacturers of the LITT technology) submitted a 
joint code proposal requesting an overall change to how LITT is 
classified within the ICD-10-PCS classification and for consideration 
as an agenda topic to be discussed at the March 8-9, 2022 ICD-10 
Coordination and Maintenance Committee meeting. The proposal was 
presented and discussed at the March 8-9, 2022 ICD-10 Coordination and 
Maintenance Committee meeting. We referred the reader to the CMS 
website at: https://www.cms.gov/Medicare/Coding/ICD10/C-and-M-Meeting-Materials for additional detailed information regarding the request, 
including a recording of the discussion and the related meeting 
materials. Public comments in response to the code proposal were due by 
April 8, 2022.
    Because the diagnosis and procedure code proposals that are 
presented at the March ICD-10-CM Coordination and Maintenance Committee 
meeting for an October 1 implementation (upcoming FY) are not finalized 
in time to include in Table 6A. --New Diagnosis Codes and Table 6B.--
New Procedure Codes in association with the proposed rule, as we have 
noted in prior rulemaking and discuss further in this section, we use 
our established process to examine the MS-DRG assignment for the 
predecessor codes to determine the most appropriate MS-DRG assignment. 
Specifically, we review the predecessor code and MS-DRG assignment most 
closely associated with the new procedure code, and in the absence of 
claims data, we consider other factors that may be relevant to the MS-
DRG assignment, including the severity of illness, treatment 
difficulty, complexity of service and the resources utilized in the 
diagnosis and/or treatment of the condition. We have noted in prior 
rulemaking that this process does not automatically result in the new 
procedure code being assigned to the same MS-DRG or to have the same 
designation (O.R. versus Non-O.R.) as the predecessor code. Under this 
established process, the MS-DRG assignment for the upcoming fiscal year 
for any new diagnosis or procedure codes finalized after the March 
meeting would be reflected in Table 6A.--New Diagnosis Codes and Table 
6B.--New Procedure Codes associated with the final rule for that fiscal 
year. However, as stated in the proposed rule, in light of the unique 
circumstances relating to these procedures, for which there was a 
pending proposal to reclassify LITT within ICD-10-PCS and for new 
procedure codes discussed at the March meeting, as well as an MS-DRG 
reclassification request to reassign the existing codes describing 
these procedures, we addressed in this section first, the code proposal 
discussed at the March meeting and the possible MS-DRG assignments for 
any new codes that may be approved, and then secondly, the requested 
reassignment of the existing codes, in the event the new codes are not 
approved.
    To summarize, as discussed at the March meeting, the code proposal 
was to reclassify LITT procedures from the Radiation Therapy section of 
ICD-10-PCS (Section D) to the Medical and Surgical section of ICD-10-
PCS. Specifically, the proposal was to reclassify LITT procedures to 
the root operation Destruction. In ICD-10-PCS, the root operation 
Destruction is defined as physical eradication of all or a portion of a 
body part by the direct use of energy, force, or a destructive agent. 
According to the requestors, LITT is misclassified to section D-
Radiation Therapy in ICD-10-PCS possibly because of terminology that 
was used for predicate devices, whose indications included the phrase 
``interstitial irradiation or thermal therapy'' in describing LITT's 
method of action. The requestors stated LITT is thermal therapy, 
destroying soft tissue using heat generated by a laser probe at the 
target site and that the LITT procedure does not use ionizing 
radiation, which is what the term ``radiation'' commonly refers to in 
the general medical sense. The requestors also stated that by itself, 
radiation is a broad term and provided an example that the spectrum of 
electromagnetic radiation technically encompasses low energy non-
ionizing radio waves, microwaves, and infrared to high energy ionizing 
X-rays and gamma rays while ionizing radiation creates ions in the 
cells it passes through by removing electrons, a process which kills or 
alters the cells over time.
    The requestors further stated that only certain medical uses of 
radiation are classified to section D-Radiation Therapy. For instance, 
section D-Radiation Therapy categorizes treatments using ionizing 
radiation, including beam radiation, brachytherapy, and stereotactic 
radiosurgery. All of these deliver concentrated ionizing radiation to 
eradicate abnormal cells, most commonly neoplasms. Other treatments 
classified to section D-Radiation Therapy, such as hyperthermia, are 
used as adjuncts to ionizing radiation. The requestors asserted that 
while LITT eradicates abnormal cells, it does so with heat, not 
ionizing radiation and rather than a radiation therapy procedure, LITT 
is a surgical procedure. According to the requestors, LITT would be 
more appropriately classified as an ablation procedure with the root 
operation Destruction.
    As stated in the proposed rule, the original request for a new 
code(s) to describe the LITT technology was initially discussed at the 
September 24-25, 2008 ICD-9-CM Coordination and Maintenance Committee 
meeting. At that time, the requestor sought an April 1, 2009 
implementation date. Public comments opposed an April 1, 2009 
implementation date, therefore, effective October 1, 2009 (FY 2010), 
ICD-9-CM procedure codes were created to identify procedures performed 
utilizing the LITT technology. The following table lists the ICD-9-CM 
procedure codes describing LITT and their respective MDC and MS-DRG 
assignments under the ICD-9 based MS-DRGs. We refer the reader to the 
ICD-9 and ICD-10 MS-DRG Definitions Manual Files V33 (available via the

[[Page 48811]]

internet on the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/Acute-Inpatient-Files-for-Download-Items/FY2016-Final-Rule-Correction-Notice-Files in the 
Downloads section) for complete documentation of the GROUPER logic for 
ICD-9.
[GRAPHIC] [TIFF OMITTED] TR10AU22.009

    The requestors maintain that although LITT was used to treat a 
variety of anatomic sites when it was first introduced, its current 
primary use is intracranial, specifically to treat brain tumors and 
epileptic foci. However, the requestors stated it is also used to treat 
radiation necrosis, an inflammatory response from prior treatment with 
ionizing radiation.
    We noted in the proposed rule that currently, in the U.S., there 
are only two LITT systems in use, VisualaseTM MRI-Guided 
Laser Ablation (Medtronic) and the Neuroblate[supreg] System 
(Monteris[supreg] Medical). The requestors also stated that over the 
last six years, the Indications for Use (IFU) for one of the two U.S. 
approved LITT technologies (Neuroblate[supreg]) has been updated to 
reflect the system's current use in the brain and to align with the 
intended neurosurgical patient population. The requestor indicated 
applications in the spine are also anticipated in the future within the 
central nervous system.
    As previously noted, the deadline for receipt of public comments 
for the proposed reclassification of LITT procedures that was presented 
at the March 8-9, 2022 ICD-10 Coordination and Maintenance Committee 
meeting along with the corresponding proposal for new procedure codes 
was April 8, 2022, and the final code decisions on these proposals were 
not yet available for inclusion in Table 6B.--New Procedure Codes 
associated with the FY 2023 IPPS/LTCH PPS proposed rule. However, as 
discussed in prior rulemaking (86 FR 44805), codes that are finalized 
after the March meeting are reviewed and subject to our established 
process of initially reviewing the predecessor codes MS-DRG assignment 
and designation, while considering other relevant factors (for example, 
severity of illness, treatment difficulty, complexity of service and 
the resources utilized in the diagnosis and/or treatment of the 
condition) as previously described. The codes that are finalized after 
the March meeting are specifically identified with a footnote in Tables 
6A.--New Diagnosis Codes and Table 6B.--New Procedure Codes that are 
made publicly available in association with the final rule via the 
internet on the CMS website at https://www.cms.gov/medicare/medicare-
fee-for-service-payment/acuteinpatientpps. The public may provide 
feedback on these finalized assignments, which is then taken into 
consideration for the following fiscal year.
    We stated in the proposed rule that the MS-DRG assignment for any 
new procedure codes describing LITT, if finalized following the March 
meeting, would be reflected in Table 6B.--New Procedure Codes 
associated with the final rule for FY 2023. However, in light of the 
unique circumstances with respect to these procedures, for which there 
was both a proposal for reclassifying LITT from the Radiation Therapy 
section of the procedure code classification to the Medical/Surgical 
section with new ICD-10-PCS procedure code(s) and a separate MS-DRG 
reclassification request on the existing procedure codes, we provided 
the opportunity for public comment on possible MS-DRG assignments for 
the requested new procedure codes describing LITT that may apply based 
on the application of our established process and analysis, in the 
event the new codes were finalized for FY 2023. We also noted that 
while we discussed the potential MS-DRG assignments for new procedure 
codes describing LITT, interested parties may use current coding 
information to consider the potential MS-DRG assignments for any other 
procedure codes that may be finalized after the March meeting and 
submit public comments for consideration. Specifically, in the ICD-10 
Coordination and Maintenance Committee meeting materials (available via 
the internet on the CMS website at: https://www.cms.gov/Medicare/Coding/ICD10/C-and-M-Meeting-Materials), for each procedure code 
proposal we provide the current coding that is applicable within the 
classification and that should be reported in the absence of a more 
unique code, or until such time a new code is created and becomes 
effective. The procedure code(s) listed in current coding are 
generally, but not always, the same code(s) that are considered as the 
predecessor code(s) for purposes of MS-DRG assignment. As previously 
noted, our process for determining the MS-DRG assignment for a new 
procedure code does not automatically result in the new procedure code 
being assigned to the

[[Page 48812]]

same MS-DRG or having the same designation (O.R. versus Non-O.R.) as 
the predecessor code. However, this current coding information can be 
used in conjunction with the GROUPER logic, as set forth in the ICD-10 
MS-DRG Definitions Manual and publicly available via the internet on 
our CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software 
to review the MS-DRG assignment of the current code(s) and examine the 
potential MS-DRG assignment of the proposed code(s), to assist in 
formulating any public comments for submission to CMS for 
consideration.
    We noted in the proposed rule that, unlike the typical code request 
for a new or revised procedure code that involves a new technology or a 
new approach to performing an existing procedure, the circumstances for 
this particular request are distinct in that the code request would 
reclassify LITT within the ICD-10-PCS classification from section D--
Radiation Therapy to the root operation Destruction in the Medical and 
Surgical section of ICD-10-PCS. Therefore, in light of the unique 
considerations with respect to the requested reclassification of the 
LITT procedures in connection with the pending code proposal, we stated 
we believe it was appropriate to utilize the assignments and 
designations of the procedure codes describing Destruction of the 
respective anatomic body site as predecessor codes rather than the 
current codes describing LITT from the Radiation Therapy section of 
ICD-10-PCS in considering potential MS-DRG assignment for the requested 
new LITT procedure codes.
    As previously discussed, under our established process for 
determining the MS-DRG assignment for newly approved procedure codes, 
we examine the MS-DRG assignment for the predecessor codes to determine 
the most appropriate MS-DRG assignment for the new codes. Specifically, 
we review the predecessor code and MS-DRG assignment most closely 
associated with the new procedure code, and in the absence of claims 
data, we consider other factors that may be relevant to the MS-DRG 
assignment, including the severity of illness, treatment difficulty, 
complexity of service and the resources utilized in the diagnosis and/
or treatment of the condition. As we have noted in prior rulemaking, 
this process does not automatically result in the new procedure code 
being assigned to the same MS-DRG or to have the same designation (O.R. 
versus Non-O.R.) as the predecessor code.
    Applying this established review process to the proposed codes for 
the LITT procedures, we stated we believe that, based on the 
predecessor codes, and as previously noted, the potential assignments 
and designations would align with the assignments and designations of 
the procedure codes describing Destruction of the respective anatomic 
body site. For example, as discussed in the preamble of the proposed 
rule and earlier in this section of this final rule, the code request 
involved reclassifying LITT procedures from section D--Radiation 
Therapy to the root operation Destruction in the Medical and Surgical 
section of ICD-10-PCS. The root operation Destruction is appropriate to 
identify and report procedures, such as ablation, that are performed on 
various body parts. The code request also involved creating what is 
referred to as a qualifier value, to uniquely describe LITT as the 
modality. The qualifier value is the seventh character or digit, in a 
valid ICD-10-PCS procedure code.
    We presented the following ICD-10-PCS table in the proposed rule, 
which illustrates an example of the proposed procedure codes for LITT 
of the brain and brain stem, and cervical, thoracic, and lumbar spinal 
cord body parts, including the qualifier value that was presented and 
discussed at the March 8-9, 2022 ICD-10 Coordination and Maintenance 
Committee meeting.
[GRAPHIC] [TIFF OMITTED] TR10AU22.010

    We noted in the proposed rule that the code proposal presented only 
provided the body part value 0 Brain, for reporting any LITT procedures 
performed on the brain, as well as, the brain stem, consistent with the 
current available body part option in Table 005, Destruction of Central 
Nervous System and Cranial Nerves, where the predecessor code is 
located. We also noted that the predecessor code(s) and associated MS-
DRG assignments for the proposed new procedure code(s) describing LITT 
of the brain and spinal cord under MDC 01 are identified as follows.

[[Page 48813]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.011

    As shown in the table, the procedure codes describing destruction 
of brain with an open, percutaneous or percutaneous endoscopic approach 
are assigned to MS-DRGs 023 through 027 (craniotomy and endovascular 
procedures) and the procedure codes describing destruction of cervical, 
thoracic or lumbar spinal cord with an open, percutaneous or 
percutaneous endoscopic approach are assigned to MS-DRG 028 (Spinal 
Procedures with MCC), MS-DRG 029 (Spinal Procedures with CC or Spinal 
Neurostimulators), and MS-DRG 030 (Spinal Procedures without CC/MCC).
    We referred the reader to Table 6P.2a associated with the proposed 
rule (and available via the internet at: https://www.cms.gov/medicare/
medicare-fee-for-service-payment/acuteinpatientpps) to review the 
potential MDCs, MS-DRGs, and O.R. versus Non-O.R. designations 
identified based on this analysis of the proposed new procedure codes 
describing LITT as presented and discussed at the meeting. We noted 
that Table 6P.2a also includes the predecessor codes that we utilized 
to inform this analysis. We stated that if finalized, the new procedure 
codes would be included in the FY 2023 code update files that are made 
available in late May/early June via the internet on the CMS website 
at: https://www.cms.gov/medicare/coding/icd10. Additionally, we noted 
that if finalized, the new procedure codes describing LITT would be 
displayed in Table 6B.--New Procedure Codes, and the existing codes 
describing LITT would be deleted and reflected in Table 6D.--Invalid 
Procedure Codes, in association with the FY 2023 IPPS/LTCH PPS final 
rule. We referred the reader to section II.D.14. of the preamble of the 
proposed rule for further information regarding the files.
    We note that the proposal to reclassify LITT procedures of the 
brain, brain stem and other anatomic sites in ICD-10-PCS that was 
discussed at the March 8-9, 2022 ICD-10 Coordination and Maintenance 
Committee meeting was approved and new procedure codes describing LITT 
of the brain and other anatomic sites were finalized as reflected in 
the FY 2023 ICD-10-PCS Code Update files that were made publicly 
available via the internet on the CMS website at https://www.cms.gov/
Medicare/Coding/ICD10 on May 26, 2022. We also note that the new 
procedure codes effective October 1, 2022 describing LITT of the brain 
and other anatomic sites are displayed in Table 6B.--New Procedure 
Codes, and the existing codes describing LITT of the brain, brain stem, 
and other anatomic sites that are being deleted effective October 1, 
2022 are reflected in Table 6D.--Invalid Procedure Codes, in 
association with this FY 2023 IPPS/LTCH PPS final rule and available 
via the internet on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS. Below we summarize 
the public comments we received and present our responses.
    Comment: Commenters expressed appreciation that the proposal to 
reclassify LITT procedures in ICD-10-PCS that was discussed at the 
March 8-9, 2022 ICD-10 Coordination and Maintenance Committee meeting 
was approved and new procedure codes have been finalized as reflected 
in the FY 2023 ICD-10-PCS Code Update files that were made publicly 
available via the internet on the CMS website at https://www.cms.gov/
Medicare/Coding/ICD10 on May 26, 2022. Commenters also indicated it is 
appropriate to utilize procedure codes with the root operation 
Destruction as the predecessor codes for MS-DRG assignment of the new 
LITT procedure codes for all the anatomic body sites. Several 
commenters expressed support for the assignment of cases reporting new 
procedure codes for LITT of brain (includes brain stem) from MS-DRGs 
040, 041, and 042 to MS-DRGs 025, 026 and 027 and urged CMS to finalize 
this assignment. The commenters commended CMS for recognizing the 
unique clinical circumstances related to LITT procedures of the brain 
as being more appropriately aligned with MS-DRGs 025, 026 and 027. A 
commenter acknowledged that the new procedure codes for LITT of brain 
had not yet been finalized at the time of the development of the 
proposed rule and therefore, were not reflected in the V40 Test GROUPER 
software, however, the commenter encouraged CMS to ensure the final V40 
GROUPER logic reflects the new procedure codes for LITT of brain and 
assignment to MS-DRGs 025, 026 and 027.
    Response: We thank the commenters for their support. In addition to 
the new procedure codes describing LITT being made publicly available 
in the FY 2023 ICD-10-PCS Code Update files via the internet on the CMS 
website at https://www.cms.gov/Medicare/Coding/ICD10, we note that, as 
previously stated, the new procedure codes are also reflected in Table 
6B.--New Procedure Codes, in association with this final rule and 
available via the internet on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS with their 
finalized MS-DRG assignments. As shown in the table, procedure codes 
describing LITT of brain (root operation Destruction), are assigned to 
MS-DRGs 025, 026 and 027 for FY 2023. This assignment is also reflected 
in the final V40 GROUPER logic. Existing procedure

[[Page 48814]]

codes D0Y0KZZ (Laser interstitial thermal therapy of brain) and D0Y1KZZ 
(Laser interstitial thermal therapy of brain stem) will be deleted 
effective October 1, 2022, as reflected in Table 6D.--Invalid Procedure 
Codes, in association with this final rule and available via the 
internet on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS.
    As discussed in the proposed rule and previously discussed in this 
final rule, we also received requests to reassign the existing ICD-10 
procedure codes that identify LITT of the brain and brain stem (codes 
D0Y0KZZ and D0Y1KZZ). We stated in the proposed rule that in the event 
there is not support for the proposed reclassification of LITT 
procedures and the corresponding new procedure codes as presented at 
the March 8-9, 2022 ICD-10 Coordination and Maintenance Committee 
meeting, we were also providing the results of our analysis of these 
existing codes and our proposed MS-DRG assignments for FY 2023, if 
those existing codes are retained.
    In the proposed rule we stated that we examined claims data from 
the September 2021 update of the FY 2021 MedPAR file for MS-DRGs 023, 
024, 025, 026, and 027, in addition to MS-DRGs 040, 041, and 042 for 
cases reporting LITT of the brain (code D0Y0KZZ) or brain stem (code 
D0Y1KZZ). We noted that if a procedure code is not listed it is because 
there were no cases found reporting that procedure code. Our findings 
are shown in the following tables.
[GRAPHIC] [TIFF OMITTED] TR10AU22.012

[GRAPHIC] [TIFF OMITTED] TR10AU22.013

    As shown, we found a total of 123 cases reporting LITT of the brain 
across MS-DRGs 023, 025, 026, and 027. There were no cases found in MS-
DRG 024. The cases reporting LITT of the brain grouped to these MS-DRGs 
because another O.R. procedure that is assigned to the respective MS-
DRG was also reported. We referred the reader to Table 6P.2b in 
association with the proposed rule for the list of the other

[[Page 48815]]

O.R. procedures we identified that were also reported with LITT of the 
brain.
    For MS-DRGs 040, 041, and 042, we found a total of 54 cases 
reporting LITT of the brain and 2 cases reporting LITT of the brain 
stem. While the average costs of the cases reporting LITT of the brain 
were higher compared to all the cases in their respective MS-DRGs, the 
average length of stay was shorter. For example, the data demonstrates 
a shorter average length of stay (8.1 days versus 9.9 days) and higher 
average costs ($40,458 versus $30,212) for the 14 cases reporting LITT 
of brain in MS-DRG 040 compared to all the cases in MS-DRG 040. There 
were no cases found to report LITT of brain stem in MS-DRG 040. For MS-
DRG 041, we found 16 cases reporting LITT of brain with an average 
length of stay of 3.4 days and average costs of $23,278 and 1 case 
reporting LITT of brain stem with an average length of stay of 1 day 
and average costs of $10,222. The average length of stay for all the 
cases in MS-DRG 041 is 5 days with average costs of $19,090. The data 
demonstrates a shorter average length of stay (3.4 days and 1 day, 
respectively, versus 5 days) for the 16 cases reporting LITT of brain 
and the 1 case reporting LITT of brain stem. The data also demonstrates 
higher average costs ($23,278 versus $19,090) for the 16 cases 
reporting LITT of brain, and lower average costs for the 1 case 
reporting LITT of brain stem ($10,222 versus $19,090), as compared to 
the average costs of all cases in MS-DRG 041. For MS-DRG 042, we found 
24 cases reporting LITT of brain with an average length of stay of 1.7 
days and average costs of $22,426 and 1 case reporting LITT of brain 
stem with an average length of stay of 2 days and average costs of 
$32,668. The average length of stay for all the cases in MS-DRG 042 is 
2.9 days with average costs of $15,451. The data demonstrates a shorter 
average length of stay (1.7 days and 2 days, respectively, versus 2.9 
days) for the 24 cases reporting LITT of brain and the 1 case reporting 
LITT of brain stem. The data also demonstrate higher average costs 
($22,426 and $32,668, respectively versus $15,451) for the 24 cases 
reporting LITT of brain and the 1 case reporting LITT of brain stem, 
compared to all the cases in MS-DRG 042.
    We noted in the proposed rule that, based on the findings from our 
analysis, we considered whether other factors, such as the reporting of 
secondary MCC and CC diagnoses, may have contributed to the higher 
average costs for these cases. Specifically, we conducted additional 
analyses of the claims data from the September 2021 update of the FY 
2021 MedPAR file to determine what secondary MCC diagnoses were also 
reported for the 14 cases reporting LITT of brain in MS-DRG 040 and 
what secondary CC diagnoses were reported for the 17 cases (16 for LITT 
of brain and 1 for LITT of brain stem) in MS-DRG 041. Our findings are 
shown in the following tables.
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[[Page 48816]]


[GRAPHIC] [TIFF OMITTED] TR10AU22.015

    We noted that we did not find any other O.R. procedures reported on 
the claims in addition to the procedures for LITT of brain or brain 
stem for MS-DRGs 040, 041 and 042.
    The data shows that at least one of the listed secondary MCC 
diagnoses was reported with each claim for LITT of brain identified in 
MS-DRG 040 and the average length of stay for these cases ranged from 9 
days to 48 days and the average costs of these cases ranged from 
$41,486 to $80,745. We note that this data reflects the frequency with 
which each of the listed diagnoses was reported on a claim with LITT of 
brain. Therefore, multiple MCCs from this list of diagnoses may have 
been reported on a single claim. In addition, while the logic for case 
assignment to MS-DRG 040 requires at least one secondary MCC diagnosis, 
we conducted additional detailed analyses for MS-DRG 040, as shown in 
Table 6P.2f, to determine whether there were also secondary CC 
diagnoses reported in conjunction with one or more of the listed MCC 
diagnoses that may be contributing to the higher average costs for 
cases reporting LITT of brain in MS-DRG 040 in comparison to all the 
cases in MS-DRG 040. We found that 6 of the 14 cases reporting at least 
one or more secondary MCC diagnosis also reported one or more secondary 
CC diagnosis, which would appear to support that the severity of 
illness for these patients, as identified by the secondary MCC and CC 
diagnoses, may be more directly related to the higher average costs for 
these patients than the LITT procedure itself.
    Similarly, the data for MS-DRG 041 show the frequency with which 
each of the listed secondary CC diagnoses was reported with LITT of 
brain or brain stem. Results from the analysis for the 17 cases (16 for 
LITT of brain and 1 for LITT of brain stem) show the average length of 
stay for these cases ranged from 1 day to 29 days and the average costs 
ranged from $9,101 to $57,999. These data analysis findings for MS-DRG 
041 also appear to support our belief that the severity of illness for

[[Page 48817]]

these patients, as identified by the listed secondary CC diagnoses, may 
be more directly related to the higher average costs for these patients 
than the LITT procedure itself.
    As stated in the proposed rule and previously in this final rule, 
we did not find any other O.R. procedures reported on the claims in 
addition to the procedures for LITT of brain or brain stem for MS-DRGs 
040, 041 and 042. Since the logic for case assignment to MS-DRG 042 is 
not based on the reporting requirement of any CC or MCC diagnoses, we 
conducted a detailed analysis of the claims data to determine what 
other factors may be contributing to the higher average costs and 
shorter average length of stay for these cases in comparison to all the 
cases in MS-DRG 042. We refer the reader to Table 6P.2g associated with 
the proposed rule for the findings from our analysis. As shown in the 
data, the majority of the cases (15 of 25) had a principal diagnosis of 
epilepsy, 8 cases had a principal diagnosis related to malignant 
neoplasm of the brain or brain structures, 1 case had a principal 
diagnosis of hemangioma of intracranial structures and 1 case had a 
principal diagnosis of unspecified convulsions. The data also 
demonstrate that 16 of the 25 cases reported in MS-DRG 042 include 
patients who were under the age of 65, with ages ranging from 32 years 
old to 64 years old. We note that patients diagnosed with epilepsy are 
eligible for coverage since it is a condition that qualifies under 
certain criteria. It is not entirely clear if the age of these patients 
had any impact on the average length of stay since the average length 
of stay of the 24 cases reporting LITT of brain was 1.7 days and the 1 
case reporting LITT of brain stem was 2 days.
    As stated previously, the logic for case assignment to MS-DRG 042 
is not dependent on the reporting of any CC or MCC diagnoses, however, 
based on the diagnoses reflected in the claims data for MS-DRG 042, it 
is possible that conditions such as obesity and chronic conditions 
requiring the long-term use of certain therapeutic agents may be 
contributing factors to the consumption of resources, separately from 
the LITT procedure. We found 17 of the 25 cases reporting LITT of brain 
or brain stem to also report one or both of these conditions.
    We also reviewed the number of cases of LITT of the brain or brain 
stem procedures reported in the data since the transition to ICD-10. 
Specifically, we examined the claims data for cases reporting LITT of 
brain or brain stem as a standalone procedure or with another procedure 
in the FY 2016 through FY 2021 MedPAR data files across all MS-DRGs. 
The findings from our analysis are shown in table 6P.2e associated with 
the proposed rule.
    The data demonstrates that since the implementation of ICD-10, a 
shift in the reporting of LITT of brain and brain stem procedures has 
occurred. For example, the FY 2016, FY 2017 and FY 2018 MedPAR data 
reflect that the number of cases for which LITT of brain or brain stem 
procedures were reported as a standalone procedure is higher in 
comparison to the number of cases reported with another procedure. 
Conversely, the FY 2019, FY 2020, and FY 2021 MedPAR data reflect that 
the number of cases for which LITT of brain or brain stem procedures 
were reported as a standalone procedure is lower in comparison to the 
number of cases reported with another procedure. The data also reflect 
that the average length of stay is shorter and the average costs are 
lower for cases reporting LITT of brain or brain stem as a standalone 
procedure in comparison to the average length of stay and average costs 
for cases reported with another procedure across the FY 2016 through FY 
2021 MedPAR data files. Lastly, the data demonstrate that overall, the 
number of cases for which LITT of brain or brain stem procedures was 
performed had remained fairly stable at over 100 cases with increases 
in the FY 2017, FY 2020 and FY 2021 MedPAR data files of 156, 154 and 
185 cases, respectively.
    As discussed in the proposed rule, we also analyzed claims data 
from the September 2021 update of the FY 2021 MedPAR file for cases 
reporting LITT of other anatomic sites across all MS-DRGs. Although the 
requestors indicated that LITT is primarily performed on intracranial 
lesions, as shown in Table 6P.2c associated with the proposed rule, we 
identified a small number of cases reporting LITT of the lung, rectum, 
liver, breast, and prostate, for a total of 29 cases where LITT was 
performed on other body parts/anatomic sites.
    For example, we found a total of 5 cases reporting LITT of lung 
across 5 different MS-DRGs. Of these 5 cases, 2 cases had a longer 
average length of stay and higher average costs in comparison to all 
the cases in their respective MS-DRG. Specifically, for MS-DRG 163 
(Major Chest Procedures with MCC), we found 1 case reporting LITT of 
lung with an average length of stay of 17 days and average costs of 
$41,467. The average length of stay for all cases in MS-DRG 163 is 10.7 
days with average costs of $38,367. The data demonstrates a difference 
of 6.3 days (17-10.7 = 6.3) for the average length of stay and a 
difference of $3,100 in average costs ($41,467-$38,367 = $3,100) for 
the 1 case reporting LITT of lung in MS-DRG 163 compared to all the 
cases in MS-DRG 163. For MS-DRG 167 (Other Respiratory System O.R. 
Procedures with CC), we found 1 case reporting LITT of lung with an 
average length of stay of 7 days and average costs of $22,975. The 
average length of stay for all cases in MS-DRG 167 is 4.6 days with 
average costs of $15,397. The data demonstrates a difference of 2.4 
days (7-4.6 = 2.4) for the average length of stay and a difference of 
$7,578 in average costs ($22,975-$15,397 = $7,578) for the 1 case 
reporting LITT of lung in MS-DRG 167 compared to all the cases in MS-
DRG 167. The data for the remaining 3 cases reporting LITT of lung 
demonstrated a shorter average length of stay and lower average costs 
in comparison to all the cases in their respective MS-DRGs.
    We found 1 case reporting LITT of rectum in MS-DRG 357 (Other 
Digestive System O.R. Procedures with CC) with a shorter average length 
of stay (4 days versus 5.6 days) and lower average costs ($3,069 versus 
$18,065) as compared to all the cases in MS-DRG 357. We also found 1 
case reporting LITT of liver in MS-DRG 405 (Pancreas Liver and Shunt 
Procedures with MCC) with a longer average length of stay (20 days 
versus 12.3 days) and higher average costs ($49,0695 versus $43,771) as 
compared to all the cases in MS-DRG 405.We also found 1 case reporting 
LITT of right breast in MS-DRG 580 (Other Skin Subcutaneous Tissue and 
Breast Procedures with CC) with a longer average length of stay (19 
days versus 5.4 days) and higher average costs ($32,064 versus $13,767) 
as compared to all the cases in MS-DRG 580.
    Lastly, we found 21 cases reporting LITT of prostate across 14 MS-
DRGs. Of those 21 cases, 6 cases had a longer average length of stay or 
higher average costs, or both, in comparison to the average length of 
stay and average costs of all the cases in their respective MS-DRG. For 
example, in MS-DRG 650 (Kidney Transplant with Hemodialysis with MCC) 
we found 1 case reporting LITT of prostate with an average length of 
stay of 36 days and average costs of $67,238. The average length of 
stay for all cases in MS-DRG 650 is 8.1 days with average costs of 
$38,139. The data demonstrates a difference of 27.9 days (36-8.1 = 
27.9) for the average length of stay and a difference of $29,099 in 
average costs ($67,238-$38,139 = $29,099) for the 1 case reporting LITT 
of prostate in MS-

[[Page 48818]]

DRG 650 compared to all the cases in MS-DRG 650. We also found 1 case 
reporting LITT of prostate in MS-DRG 659 (Kidney and Ureter Procedures 
for Non-Neoplasm with MCC) with an average length of stay of 26 days. 
The average length of stay for all cases in MS-DRG 659 is 7.8 days, 
demonstrating a difference of 18.2 days (26-7.8 = 18.2). We found 1 
case reporting LITT of prostate in MS-DRG 712 (Testes Procedures 
without CC/MCC) with average costs of $15,669. The average costs for 
all cases in MS-DRG 712 is $10,482, demonstrating a difference of 
$5,187 ($15,669-$10,482 = $5,187). We found 1 case reporting LITT of 
prostate in MS-DRG 987 with an average length of stay of 23 days and 
average costs of $35,465. The average length of stay for all cases in 
MS-DRG 987 is 10.9 days with average costs of $26,657. The data 
demonstrates a difference of 12.1 days (23-10.9 = 12.1) for the average 
length of stay and a difference of $8,808 in average costs ($35,465-
$26,657 = $8,808) for the 1 case reporting LITT of prostate in MS-DRG 
987 compared to all the cases in MS-DRG 987. Lastly, we found 2 cases 
reporting LITT of prostate in MS-DRG 988 (Non-Extensive O.R. Procedures 
Unrelated to Principal Diagnosis with CC) with average costs of 
$17,126. The average costs for all cases in MS-DRG 988 is $13,670, 
demonstrating a difference of $3,456 ($17,126-$13,670 = $3,456) for the 
2 cases reporting LITT of prostate in MS-DRG 988.
    We refer the reader to Table 6P.2c associated with the proposed 
rule for the detailed findings from our analysis. We note that if the 
procedure code describing LITT of a specific anatomic site is not 
listed it is because there were no cases found.
    We noted in the proposed rule that for the 10 cases previously 
described, for which LITT of a different anatomic site from the brain 
or brain stem was reported and had a longer average length of stay or 
higher average costs, or both, in comparison to the average length of 
stay and average costs of all the cases in their respective MS-DRG, 
that with the exception of MS-DRG 712, all the other MS-DRGs include a 
``with MCC'' or ``with CC'' designation, or were reported in a surgical 
MS-DRG. We stated we believe that these other factors may have 
contributed to the longer average length of stay and higher average 
costs for these cases, therefore we conducted additional analyses of 
the claims data to determine what diagnoses or procedures were also 
reported. We refer the reader to Table 6P.2d associated with the 
proposed rule for the findings from our detailed analysis of these 10 
cases.
    As shown in Table 6P.2d associated with the proposed rule, the data 
demonstrate that a number of MCC and/or CC secondary diagnoses were 
reported for each of the 10 cases and that the surgical procedures that 
were reported in addition to the LITT procedure seem to have 
contributed to the longer average length of stay and higher average 
costs for those cases when compared to the average length of stay and 
average costs for all the cases in their respective MS-DRG. For 
example, in case number 1 there are 2 diagnoses that are designated as 
MCC conditions and 5 diagnoses that that are designated as CC 
conditions with procedure codes describing a kidney transplant, 
hemodialysis, and insertion of a ureteral stent that were reported 
along with LITT of prostate. For case number 3 there are 4 diagnoses 
that are designated as MCC conditions and 6 diagnoses that are 
designated as CC conditions with procedure codes describing 
bronchoscopic treatment of a bronchial tumor with and without stents, 
as well as the use of mechanical ventilation. Overall, the data appear 
to indicate that the performance of the LITT procedure was not the 
underlying reason for, or main driver of, the increase in resource 
utilization for those cases.
    As noted in the proposed rule, the requestors indicated that LITT 
is primarily being performed on intracranial lesions. However, as 
previously summarized, we identified a limited number of cases 
reporting LITT procedures for other anatomic sites. We stated in the 
proposed rule that we are interested in comments regarding the use of 
and experience with LITT for these other anatomic sites.
    As discussed in the proposed rule, based on our analysis of the FY 
2021 MedPAR claims data for cases reporting LITT of brain or brain stem 
(codes D0Y0KZZ and D0Y1KZZ) in MS-DRGs 040, 041, and 042, we agree with 
the requestors that the average costs of these cases are higher as 
compared to the average costs of all cases assigned to MS-DRGs 040, 
041, and 042. For the reasons summarized, in the proposed rule we also 
stated we believe that other factors, including the reporting of 
secondary MCC and CC diagnoses, may be contributing to the higher 
average costs for these cases. As discussed in the FY 2022 IPPS/LTCH 
PPS final rule (86 FR 44813), we examined procedure codes D0Y0KZZ and 
D0Y1KZZ describing LITT of brain and brain stem, respectively, and 
stated that the technique to perform the LITT procedure on these 
structures is considered minimally invasive and does not involve a 
craniotomy, therefore, continued assignment to the craniotomy MS-DRGs 
is not clinically appropriate. As noted in the proposed rule, our 
clinical advisors continue to maintain that LITT is a minimally 
invasive procedure, requiring only a tiny incision for purposes of a 
burr hole and that patients are often only kept overnight (as reflected 
in the detailed claims data). However, we stated that we also recognize 
that craniotomy and LITT share common procedural characteristics 
including use of an operating room, carry risk of immediate 
intracranial bleeding or infection, and cause tissue to be immediately 
destroyed or excised. We noted that while the data do not demonstrate 
that the LITT procedure is the underlying reason for the higher average 
costs and consumption of resources for the small number of cases 
reporting LITT of brain (54 cases) or brain stem (2 cases) that we 
found in MS-DRGs 040, 041, and 042, the data do demonstrate that the 
patients receiving this treatment therapy have brain tumors or epilepsy 
combined with multiple comorbidities or chronic conditions 
necessitating long-term use of medications, or both, and we noted the 
indications for LITT (brain tumors and epileptic foci) are better 
aligned with MS-DRGs 025, 026, and 027 as compared to MS-DRGs 040, 041, 
and 042.
    As discussed in the proposed rule, we intend to more fully evaluate 
the logic for the procedures specifically involving a craniotomy, as 
well as the overall structure of MS-DRGs 023 through 027, and we 
believe that reassignment of cases reporting LITT of brain or brain 
stem to MS-DRGs 025, 026, and 027 would be an appropriate first step in 
connection with these efforts. For example, while we recognize the 
distinctions between open craniotomy procedures and minimally invasive 
percutaneous intracranial procedures, we also recognize that the 
current logic for MS-DRGs 025 through 027 also includes other 
endovascular intracranial procedures performed using percutaneous or 
percutaneous endoscopic approaches, and we believe that further review 
of the clinical coherence of the procedures assigned to these MS-DRGs 
may be warranted. Our clinical advisors noted that while the typical 
patient treated with LITT usually has a single small scalp incision 
through which a hole approximately the diameter of a straw is drilled, 
with no extensive surgical exposure, that LITT

[[Page 48819]]

can still be employed for another subset of more complex patients, 
including patients with primary brain malignancies and those with 
larger metastatic lesions or multiple lesions. For this subset of more 
complex patients, a longer post-operative stay with direct medical 
supervision may be necessary. As such, we stated in the proposed rule 
that we believe reassigning these procedures to MS-DRGs 025 through 027 
for FY 2023 would be appropriate as we consider restructuring MS-DRGs 
023 through 027, including how to better align the clinical indications 
with the performance of specific intracranial procedures. Accordingly, 
for these reasons, we stated in the proposed rule that in the event 
there is not support for the proposed reclassification of LITT 
procedures and the corresponding new procedure codes as presented at 
the March 8-9, 2022 ICD-10 Coordination and Maintenance Committee 
meeting, we were proposing to reassign the existing procedure codes 
describing LITT of the brain or brain stem from MS-DRGs 040, 041, and 
042 to MS-DRGs 025, 026, and 027 for FY 2023. We also proposed to 
maintain the MS-DRG assignments for the existing procedure codes 
describing LITT of other anatomic sites as finalized and displayed in 
Table 6P.2b in association with the FY 2022 IPPS/LTCH PPS final rule, 
for FY 2023. Lastly, we noted in the proposed rule that we did not 
receive any comments or requests to reconsider those finalized MS-DRG 
assignments for FY 2023.
    As noted, we stated in the proposed rule that we were proposing to 
reassign the existing procedure codes describing LITT of the brain or 
brain stem from MS-DRGs 040, 041, and 042 to MS-DRGs 025, 026, and 027 
for FY 2023, in the event there was not support for the proposed 
reclassification of LITT procedures and the corresponding new procedure 
codes as presented at the March 8-9, 2022 ICD-10 Coordination and 
Maintenance Committee meeting. As the proposed reclassification of the 
LITT procedures and the corresponding new procedure codes were approved 
following the March meeting, and the existing procedure codes D0Y0KZZ 
(Laser interstitial thermal therapy of brain) and D0Y1KZZ (Laser 
interstitial thermal therapy of brain stem) will be deleted effective 
October 1, 2022, we are not finalizing the proposed reassignment of 
these existing codes for FY 2023. As previously noted, and as reflected 
in Table 6B.--New Procedure Codes associated with this final rule, the 
new procedure codes describing LITT of brain (root operation 
Destruction) are assigned to MS-DRGs 025, 026 and 027 for FY 2023. We 
did not receive any public comments on our proposal to maintain the MS-
DRG assignments for the existing procedure codes describing LITT of 
other anatomic sites as finalized and displayed in Table 6P.2b in 
association with the FY 2022 IPPS/LTCH PPS final rule, for FY 2023. As 
previously noted, the existing procedure codes describing LITT of other 
anatomic sites will also be deleted effective October 1, 2023; 
therefore, we are not finalizing the proposed reassignment of these 
existing codes for FY 2023. The MS-DRG assignments for the newly 
approved procedure codes describing LITT of other anatomic sites for FY 
2023 are displayed in Table 6B in association with this final rule.
    As noted in the proposed rule, in connection with our analysis of 
cases reporting LITT procedures performed on the brain or brain stem in 
MDC 01, we have started to examine the logic for case assignment to MS-
DRGs 023 through 027 to determine where further refinements could 
potentially be made to better account for differences in the technical 
complexity and resource utilization among the procedures that are 
currently assigned to those MS-DRGs. Specifically, we are in the 
process of evaluating procedures that are performed using an open 
craniotomy (where it is necessary to surgically remove a portion of the 
skull) versus a percutaneous burr hole (where a hole approximately the 
size of a pencil is drilled) to obtain access to the brain in the 
performance of a procedure. We are also reviewing the indications for 
these procedures, for example, malignant neoplasms versus epilepsy to 
consider if there may be merit in considering restructuring the current 
MS-DRGs to better recognize the clinical distinctions of these patient 
populations in the MS-DRGs. We believe it is worthwhile to also compare 
the claims data for epilepsy patients who are treated with a 
neurostimulator implant versus a LITT procedure, as well as the claims 
data for patients with a diagnosis of epilepsy or malignant neoplasms 
who undergo a LITT procedure. Our analysis also includes reviewing the 
claims data with regard to the cases that reflect a procedure that is 
generally performed with another O.R. procedure versus a standalone 
procedure.
    As we continue this analysis of the claims data with respect to MS-
DRGs 023 through 027, we stated that we are also seeking public 
comments and feedback on other factors that should be considered in the 
potential restructuring of these MS-DRGs.
    Comment: In response to CMS's request for public comment and 
feedback on the potential restructuring of the craniotomy MS-DRGs for 
future consideration, some commenters disagreed and stated that such a 
restructuring is not necessary. These commenters stated that should CMS 
consider future modifications to the logic for case assignment to MS-
DRGs 023 through 027, the agency provide adequate notice for interested 
parties to assess the impact of any proposed changes.
    Another commenter expressed appreciation that CMS indicated it is 
continuing to analyze if additional restructuring for MS-DRGs 023 
through 027 may be warranted and agreed that the logic for these MS-
DRGs has become more complex. The commenter stated they will be 
performing analyses and plan to submit their findings by the October 
20, 2022 deadline. Another commenter urged CMS to also consider the 
costs of procedures with respect to whether a device is inserted or 
implanted in combination with the approach and clinical indications 
because of the various diagnoses and procedures that may group to MS-
DRGs 023 through 027. This commenter expressed support for further 
collaboration to better align resources and clinical characteristics 
among within these MS-DRGs.
    Another commenter who also expressed appreciation that CMS has 
signaled its intent on analyzing MS-DRGs 023 through 027 recommended 
that CMS also expand its analysis to include MS-DRGs 020 through 022 
(Intracranial Vascular Procedures with Principal Diagnosis Hemorrhage 
with MCC, with CC, and without CC/MCC, respectively). According to the 
commenter, the payment rates for a subset of the procedures that group 
to these MS-DRGs appear to no longer adequately reflect the utilization 
of resources. The commenter encouraged CMS to analyze these MS-DRGs and 
determine if additional modifications may be warranted.
    Response: We thank the commenters for their feedback and will take 
these recommendations into consideration as we further examine the 
logic for case assignment. We note that we would address any proposed 
modifications to the existing logic in future rulemaking.
    As previously described in the proposed rule and this final rule, 
we are examining procedures by their approach (open versus 
percutaneous), clinical indications, and procedures that involve the 
insertion or implantation of a device. We recognize the logic for MS-
DRGs 023 through 027 has grown more

[[Page 48820]]

complex over the years and believe there is opportunity for further 
refinement. We refer the reader to the ICD-10 MS-DRG Definitions 
Manual, version 40, which is available via the internet on the CMS 
website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software for 
complete documentation of the GROUPER logic for MS-DRGs 023 through 
027. Feedback and other suggestions may be submitted by October 20, 
2022 and directed to the new electronic intake system, Medicare 
Electronic Application Request Information SystemTM 
(MEARISTM), discussed in section II.D.1.b of the preamble of 
this final rule at: https://mearis.cms.gov/public/home.
b. Vagus Nerve Stimulation
    In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28141 through 
28151), we discussed a request we received to review the MS-DRG 
assignment for cases that identify patients who receive an implantable 
vagus nerve stimulation system for heart failure. The vagus nerve, also 
called the X cranial nerve or the 10th cranial nerve, is the longest 
and most complex of the cranial nerves. There is one vagus nerve on 
each side of the body that runs from the brain through the face and 
thorax to the abdomen. According to the requestor, cranial nerve 
stimulation (CNS), which includes vagus nerve stimulation, is a well-
established therapy for various indications including epilepsy, 
treatment resistant depression (TRD) and obstructive sleep apnea (OSA), 
and is now being investigated and studied for use in patients with 
heart failure.
    According to the requestor, heart failure, or the heart's inability 
to pump an adequate supply of blood and oxygen to support the other 
organs of the body, is an autonomic nervous system dysfunction. The 
brain controls the function of the heart through the sympathetic branch 
and the parasympathetic branches of the autonomic nervous system. In 
heart failure, there is an imbalance in the autonomic nervous system. 
The vagus nerve stimulation system for heart failure is comprised of an 
implantable pulse generator, an electrical lead, and a programming 
computer system. The pulse generator, which is usually implanted just 
under the skin of the pectoral region, sends the energy to the vagus 
nerve through the lead. The lead is a flexible insulated wire that is 
guided under the skin from the chest up to the neck and is implanted 
onto the vagus nerve and transmits tiny electrical impulses from the 
generator to the nerve. These electrical impulses to the vagus nerve 
are intended to activate the parasympathetic branch of the autonomic 
nervous system to restore balance.
    The requestor stated that cases reporting a procedure code 
describing the insertion of a neurostimulator lead onto the vagus nerve 
and a procedure code describing the insertion of a stimulator generator 
with a principal diagnosis code describing epilepsy, TRD or OSA are 
assigned to surgical MS-DRGs 040, 041 and 042 (Peripheral Cranial Nerve 
and Other Nervous System Procedures with MCC, with CC or Peripheral 
Neurostimulator, and without CC/MCC, respectively) in MDC 01 (Diseases 
and Disorders of the Nervous System). However, when the same codes 
describing the insertion of a neurostimulator lead onto the vagus nerve 
and the insertion of a stimulator generator are reported with a 
principal diagnosis of heart failure, the cases instead are assigned to 
surgical MS-DRGs 252, 253 and 254 (Other Vascular Procedures with MCC, 
with CC, without MCC respectively) in MDC 05 (Diseases and Disorders of 
the Circulatory System).
    The requestor stated that the treatment of autonomic nervous system 
dysfunction is the underlying therapeutic objective of cranial nerve 
stimulation for heart failure, and therefore the diagnosis of heart 
failure is more clinically coherent with other diagnoses in MDC 01. As 
a result, the requestor, who is developing the VITARIA[supreg] System, 
an active implantable neuromodulation system that uses vagus nerve 
stimulation to deliver autonomic regulation therapy (ART) for an 
indicated use that includes patients who have moderate to severe heart 
failure, submitted a request to reassign cases reporting a procedure 
code describing the insertion of a neurostimulator lead onto the vagus 
nerve and a procedure code describing the insertion of a stimulator 
generator with a principal diagnosis code describing heart failure, 
from MS-DRGs 252, 253 and 254 in MDC 05 to MS-DRGs 040, 041 and 042 in 
MDC 01. This requestor also submitted an application for new technology 
add-on payment for FY 2023. As discussed in section II.F.7. of the 
preamble of this final rule, the new technology add-on payment 
application for the VITARIA[supreg] System for FY 2023 was withdrawn 
prior to the issuance of this final rule.
    According to the requestor, the following ICD-10-PCS procedure code 
pair identifies the insertion of a vagus nerve stimulation system for 
heart failure:
[GRAPHIC] [TIFF OMITTED] TR10AU22.016

    We stated in the FY 2023 IPPS/LTCH PPS proposed rule that the 
requestor performed its own analysis of Medicare claims from 2020 and 
stated that it found that patients enrolled in their pivotal clinical 
trials had an average length of stay of 6.38 days. According to the 
requestor this finding indicated a resource coherence more similar to 
cases assigned to MS-DRGs 040, 041 and 042, whose average lengths of 
stay ranges from 2 to 8 days, when compared to the average lengths of 
stay of 1 to 3 days for cases assigned to MS-DRGs 252 and 253. The 
requestor stated their own analysis of 2019 and 2020 Medicare claims 
data also showed that fewer than 11 cases with procedure codes 
describing the implantation of a vagus nerve stimulation system map to 
MS-DRGs 252, 253 and 254 annually but it is expected that Medicare 
patients will receive vagus nerve stimulation system for heart failure 
on an inpatient basis. Because of the shared clinical and resource 
similarity of the procedure to implant the VITARIA[supreg] system to 
other CNS procedures, regardless of indication, the requestor stated 
that CNS procedures for the treatment of heart failure should also be 
assigned to MS-DRGs 040, 041 and 042. The requestor also noted that the 
title of MS-DRGs

[[Page 48821]]

252, 253 and 254 is ``Other Vascular Procedures with MCC, with CC, 
without MCC respectively''. Since no vascular access is involved in the 
procedure to implant vagus nerve stimulation systems, the requestor 
stated MS-DRGs 252, 253 and 254 were not appropriate mappings for these 
procedures.
    We stated in the proposed rule that the ICD-10-CM diagnosis codes 
that describe heart failure are found in the following table. These 
diagnosis codes are all currently assigned to MDC 05.
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TR10AU22.017

    The ICD-10-PCS codes that identify the insertion of a 
neurostimulator lead onto the vagus nerve are listed in the following 
table.
[GRAPHIC] [TIFF OMITTED] TR10AU22.018


[[Page 48822]]


    The ICD-10-PCS codes that identify the insertion of a stimulator 
generator are listed in the following table.
[GRAPHIC] [TIFF OMITTED] TR10AU22.019


[[Page 48823]]


[GRAPHIC] [TIFF OMITTED] TR10AU22.020


[[Page 48824]]


[GRAPHIC] [TIFF OMITTED] TR10AU22.021

    We stated our analysis of this grouping issue confirmed that, when 
a procedure code describing the insertion of a neurostimulator lead 
onto the vagus nerve and a procedure code describing the insertion of a 
stimulator generator are reported with a principal diagnosis code 
describing heart failure, these cases group to surgical MS-DRGs 252, 
253 and 254 (Other Vascular Procedures with MCC, with CC, without MCC 
respectively).
    We noted that cases involving the use of a peripheral 
neurostimulator and a diagnosis from MDC 01 are assigned to MS-DRG 041 
only. The GROUPER logic for MS-DRGs 040, 041, and 042 is reflected in 
the logic table:

[[Page 48825]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.022

    We refer the reader to the ICD-10 MS-DRG Version 39.1 Definitions 
Manual (which is available via the internet on the CMS website at: 
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software) for complete 
documentation of the GROUPER logic for the listed MS-DRGs.
    In the proposed rule, we stated that we examined claims data from 
the September 2021 update of the FY 2021 MedPAR file for MS-DRGs 252, 
253 and 254 to identify the subset of cases within MS-DRGs 252, 253 and 
254 reporting a procedure code describing the insertion of a 
neurostimulator lead onto the vagus nerve and a procedure code 
describing the insertion of a stimulator generator with a principal 
diagnosis of heart failure. We stated we found zero cases in MS-DRGs 
252, 253 and 254 reporting a procedure code describing the insertion of 
a neurostimulator lead onto the vagus nerve and a procedure code 
describing the insertion of a stimulator generator with a principal 
diagnosis of heart failure. In an attempt to further examine this 
issue, we then examined claims data from the September 2021 update of 
the FY 2021 MedPAR file for MS-DRGs 252, 253 and 254 to identify the 
subset of cases within MS-DRGs 252, 253 and 254 reporting a procedure 
code describing the insertion of a neurostimulator lead onto the vagus 
nerve and a procedure code describing the insertion of a stimulator 
generator with a secondary diagnosis of heart failure and similarly 
found zero cases.
    We indicated in the proposed rule that the results of the claims 
analysis demonstrated that there was not sufficient claims data in the 
MedPAR file on which to assess the resource use of cases reporting a 
procedure code describing the insertion of a neurostimulator lead onto 
the vagus nerve and a procedure code describing the insertion of a 
stimulator generator with a principal or secondary diagnosis of heart 
failure as compared to other cases assigned to MS-DRGs 252, 253, and 
254.
    As discussed in the proposed rule, in reviewing the requestor's 
concerns regarding clinical coherence, our clinical advisors 
acknowledged that heart failure is a complex syndrome involving 
autonomic nervous system dysfunction, however our clinical advisors 
disagreed with assigning the diagnosis codes describing heart failure 
to MDC 01 (Diseases and Disorders of the Nervous System). Our clinical 
advisors noted the concept of clinical coherence requires that the 
patient characteristics included in the definition of each MS-DRG 
relate to a common organ system or etiology. As the listed diagnosis 
codes describe heart failure, we stated these diagnosis codes are 
appropriately assigned to MDC 05 (Diseases and Disorders of the 
Circulatory System). Our clinical advisors also stated it would not be 
appropriate to move these diagnoses into MDC 01 because it could 
inadvertently cause cases reporting these same MDC 05 diagnoses with a 
circulatory system procedure to be assigned to an unrelated MS-DRG 
because whenever there is a surgical procedure reported on the claim 
that is unrelated to the MDC to which the case was assigned based on 
the principal diagnosis, it results in a MS-DRG assignment to a 
surgical class referred to as ``unrelated operating room procedures''.
    To further examine the impact of moving the diagnoses describing 
heart failure into MDC 01, we stated we analyzed claims data for cases 
reporting a circulatory system O.R. procedure and a principal diagnosis 
of heart failure. Our findings are reflected in the following table.

[[Page 48826]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.023


[[Page 48827]]


[GRAPHIC] [TIFF OMITTED] TR10AU22.024


[[Page 48828]]


    As shown in the table, if we were to move diagnosis codes 
describing heart failure to MDC 01, 20,199 cases would be assigned to 
the surgical class referred to as ``unrelated operating room 
procedures'' as an unintended consequence because the surgical 
procedure reported on the claim would be considered unrelated to the 
MDC to which the case was assigned based on the principal diagnosis.
    In response to the requestor's concerns regarding the title of MS-
DRGs 252, 253 and 254, we noted that, as stated in the ICD-10 MS-DRG 
Definitions Manual, ``In each MDC there is usually a medical and a 
surgical class referred to as ``other medical diseases'' and ``other 
surgical procedures,'' respectively. The ``other'' medical and surgical 
classes are not as precisely defined from a clinical perspective. The 
other classes would include diagnoses or procedures which were 
infrequently encountered or not well defined clinically. For example, 
the ``other'' medical class for the Respiratory System MDC would 
contain the diagnoses ``other somatoform disorders'' and ``congenital 
malformation of the respiratory system,'' while the ``other'' surgical 
class for the female reproductive MDC would contain the surgical 
procedures ``excision of liver'' (liver biopsy in ICD-9-CM) and 
``inspection of peritoneal cavity'' (exploratory laparotomy in ICD-9-
CM). The ``other'' surgical category contains surgical procedures 
which, while infrequent, could still reasonably be expected to be 
performed for a patient in the particular MDC. There are, however, also 
patients who receive surgical procedures which are completely unrelated 
to the MDC to which the patient was assigned. An example of such a 
patient would be a patient with a principal diagnosis of pneumonia 
whose only surgical procedure is a destruction of prostate 
(transurethral prostatectomy in ICD-9-CM). Such patients are assigned 
to a surgical class referred to as ``unrelated operating room 
procedures.'' '' We further noted that MS-DRGs 252, 253, and 254 (Other 
Vascular Procedures with MCC, with CC, and without CC/MCC, 
respectively) are examples of the ``other'' surgical class, therefore 
it is expected that there will be procedures not as precisely 
clinically aligned within the definition (logic) of these MS-DRGs.
    We stated in the proposed rule that considering that there was no 
data in the FY 2021 MedPAR file to support a reassignment of these 
cases based on resource consumption, the analysis of clinical coherence 
as discussed previously, and the impact that moving the diagnoses 
describing heart failure into MDC 01 from MDC 05 would have on heart 
failure cases, we did not believe a reassignment of these cases was 
appropriate at this time. We stated we could continue to evaluate the 
clinical coherence and resource consumption costs that impact this 
subset of cases and their current MS-DRG assignment as data become 
available for future rulemaking.
    In summary for the reasons stated previously, we did not propose to 
reassign cases reporting a procedure code describing the insertion of a 
neurostimulator lead onto the vagus nerve and a procedure code 
describing the insertion of a stimulator generator with a principal 
diagnosis of heart failure from MS-DRGs 252, 253 and 254 to MS-DRGs 
040, 041 and 042.
    Comment: Commenters expressed support for CMS' decision to not 
propose to reassign cases reporting a procedure code describing the 
insertion of a neurostimulator lead onto the vagus nerve and a 
procedure code describing the insertion of a stimulator generator with 
a principal diagnosis of heart failure from MS-DRGs 252, 253 and 254 to 
MS-DRGs 040, 041 and 042.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to maintain the current assignment of cases 
reporting a procedure code describing the insertion of a 
neurostimulator lead onto the vagus nerve and a procedure code 
describing the insertion of a stimulator generator with a principal 
diagnosis of heart failure to MS-DRGs 252, 253 and 254, without 
modification, for FY 2023.
    We further stated in the proposed rule that as we examined the 
GROUPER logic that would determine an assignment of a case to MS-DRGs 
252, 253 and 254, we noted the logic for MS-DRGs 252, 253 and 254 
includes ICD-10-PCS procedure codes that describe the insertion of the 
stimulator generator. We refer the reader to the ICD-10 MS-DRG Version 
39.1 Definitions Manual (which is available via the internet on the CMS 
website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software) for 
complete documentation of the GROUPER logic for the listed MS-DRGs. We 
stated that during our review of the stimulator generator insertion 
procedures assigned to these MS-DRGs, we identified the following 24 
procedure codes that describe the insertion of a stimulator generator, 
differentiated by device type (for example single array or multiple 
array), that did not exist in the logic for MS-DRGs 252, 253 and 254.

[[Page 48829]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.025

    For clinical consistency with the other procedure codes describing 
the insertion of the stimulator generator currently assigned to these 
MS-DRGs, we proposed to add the 24 ICD-10-PCS codes listed previously 
to MS-DRGs 252, 253 and 254, (Other Vascular Procedures with MCC, with 
CC, and without CC/MCC, respectively) in MDC 05 (Diseases and Disorders 
of the Circulatory System) effective October 1, 2022 for FY 2023.
    Comment: Commenters supported the proposal to add the 24 ICD-10-PCS 
codes to MS-DRGs 252, 253 and 254, (Other Vascular Procedures with MCC, 
with CC, and without CC/MCC, respectively) in MDC 05 (Diseases and 
Disorders of the Circulatory System).
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to add the 24 ICD-10-PCS codes listed 
previously to MS-DRGs 252, 253 and 254, (Other Vascular Procedures with 
MCC, with CC, and without CC/MCC, respectively) in MDC 05 (Diseases and 
Disorders of the Circulatory System) without modification, effective 
October 1, 2022 for FY 2023.
    Also, in the proposed rule we stated that as we examined the 
GROUPER logic that would determine an assignment of a case to MS-DRG 
041,

[[Page 48830]]

we noted that the logic for case assignment to MS-DRG 041 as displayed 
in the ICD-10 MS-DRG Version 39.1 Definitions Manual, available via the 
internet on the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software.html contains code combinations or ``clusters'' representing 
the insertion of a neurostimulator lead and the insertion of a 
stimulator generator that are captured under a list referred to as 
``Peripheral Neurostimulators.'' During our review of the procedure 
code clusters in this list, we noted that ICD-10-PCS procedure code 
clusters describing the insertion of a neurostimulator lead and the 
insertion of the stimulator generator differentiated by device type 
(for example single array or multiple array), approach and anatomical 
site placement are captured. However, procedure code clusters 
describing the insertion of stimulator generator, that is not 
differentiated by device type, and a neurostimulator lead were 
inadvertently excluded. We refer the reader to Table 6P.3a associated 
with the proposed rule (which is available via the internet on the CMS 
website at: https://www.cms.hhs.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/) for the list of the 108 ICD-10-
PCS code clusters that were inadvertently excluded and do not exist in 
the logic for MS-DRG 041.
    For clinical consistency, our clinical advisors supported the 
addition of the 108 procedure code clusters to the GROUPER logic list 
referred to as ``Peripheral Neurostimulators'' for MS-DRG 041 that 
describe the insertion of stimulator generator, not differentiated by 
device type, and a neurostimulator lead. Therefore, we proposed to add 
the 108 ICD-10-PCS code clusters listed in Table 6P.3a in association 
with the proposed rule that describe the insertion of a stimulator 
generator, that is not differentiated by device type, and a 
neurostimulator lead to MS-DRG 041, effective October 1, 2022 for FY 
2023.
    Comment: Commenters expressed support for CMS' proposal to add the 
108 ICD-10-PCS code clusters listed in Table 6P.3a in association with 
the proposed rule that describe the insertion of a stimulator 
generator, that is not differentiated by device type, and a 
neurostimulator lead to MS-DRG 041. A commenter stated that this 
proposal will clinically align these procedures with other procedures 
in their respective MS-DRGs.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to add the 108 procedure code clusters listed 
in Table 6P.3a in association with the proposed rule that describe the 
insertion of stimulator generator, not differentiated by device type, 
and a neurostimulator lead to the GROUPER logic list referred to as 
``Peripheral Neurostimulators'' for MS-DRG 041 (Peripheral, Cranial 
Nerve and Other Nervous System Procedures with CC or Peripheral 
Neurostimulator) without modification, effective October 1, 2022 for FY 
2023.
4. MDC 02 (Diseases and Disorders of the Eye): Retinal Artery Occlusion
    In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28151 through 
28155), we discussed a request we received to reassign cases reporting 
diagnosis codes describing central retinal artery occlusion, and the 
closely allied condition branch retinal artery occlusion, from MS-DRG 
123 (Neurological Eye Disorders) in MDC 02 (Diseases and Disorders of 
the Eye) to MS-DRGs 061, 062, and 063 (Ischemic Stroke Precerebral 
Occlusion or Transient Ischemia with Thrombolytic Agent with MCC, with 
CC, and without CC/MCC, respectively) in MDC 01 (Diseases and Disorders 
of the Nervous System).
    Retinal artery occlusion refers to blockage of the retinal artery 
that carries oxygen to the nerve cells in the retina at the back of the 
eye, often by an embolus or thrombus. A blockage in the main artery in 
the retina is called central retinal artery occlusion (CRAO). A 
blockage in a smaller artery is called branch retinal artery occlusion 
(BRAO). According to the requestor, in the current mapping to MS-DRG 
123, diagnoses of CRAO and BRAO are being captured inappropriately as 
eye disorders in MDC 02. Instead, the requestor stated that CRAO and 
BRAO are forms of acute ischemic stroke which occur when a vessel 
supplying blood to the brain is obstructed.
    The requestor stated the retina is a core component of the central 
nervous system and there is growing recognition that damage to it is a 
vascular neurological problem and not an ophthalmological one. Patients 
with CRAO or BRAO are typically very sick, have an underlying 
condition, and are at imminent risk for further events including heart 
attack or brain stroke. A diagnosis of CRAO or BRAO requires an urgent, 
structured and multidisciplinary team-based examination to evaluate and 
treat other diagnoses that may be present such as high blood pressure, 
dyslipidemia, diabetes mellitus, obesity, obstructive sleep apnea and 
smoking to ameliorate the risks of a subsequent, potentially lethal, 
cardiovascular event.
    The requestor further stated new evidence outlines treatment of 
patients with CRAO with acute stroke protocols, specifically with 
intravenous thrombolysis (IV tPA) or hyperbaric oxygen therapy (HBOT), 
to improve outcomes. According to the requestor, BRAO is less commonly 
treated with IV tPA than CRAO but also requires an urgent and thorough 
diagnostic workup as with any other form of stroke. The requestor 
stated the current assignment of these conditions to MS-DRG 123 does 
not properly recognize disease complexity and allocation of resources 
for care for these cases. The requestor stated that patients with CRAO 
or BRAO more closely resemble patients currently mapped to MS-DRGs 061, 
062, and 063 in terms of in resource intensity and criticality and that 
in instances where HBOT is the chosen treatment modality, any revised 
MS-DRG mapping should include the ICD-10-PCS codes for HBOT.
    As noted in the proposed rule, the ICD-10-CM codes that describe 
CRAO and BRAO are found in the following table.

[[Page 48831]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.026

    Thrombolytic therapy is identified with the following ICD-10-PCS 
procedure codes.
[GRAPHIC] [TIFF OMITTED] TR10AU22.027

    The requestor identified three ICD-10-PCS codes that they stated 
describe HBOT.
[GRAPHIC] [TIFF OMITTED] TR10AU22.028

    We stated in the proposed rule that during our review of this 
issue, we included the three procedure codes as identified by the 
requestor as describing HBOT, as well as the similar procedure code 
5A05221 (Extracorporeal hyperbaric oxygenation, continuous) that also 
describes HBOT, differing only in duration.
    We stated that our analysis of this grouping issue confirmed that, 
when a procedure code describing the administration of a thrombolytic 
agent or a procedure code describing HBOT is reported with principal 
diagnosis code describing CRAO or BRAO, these cases group to medical 
MS-DRG 123. We began our analysis by examining claims data from the 
September 2021 update of the FY 2021 MedPAR file for MS-DRG 123 to (1) 
identify cases reporting a principal diagnosis code describing CRAO or 
BRAO without a procedure code describing the administration of a 
thrombolytic agent or a procedure code describing HBOT; (2) identify 
cases reporting diagnosis codes describing CRAO or BRAO with a 
procedure code describing HBOT; and (3) identify cases reporting 
diagnosis codes describing CRAO or BRAO with a procedure code 
describing the administration of a thrombolytic agent. Our findings are 
shown in the following table:

[[Page 48832]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.029

    As shown in the table, we identified a total of 2,642 cases within 
MS-DRG 123 with an average length of stay of 2.5 days and average costs 
of $6,457. Of these 2,642 cases, there are 774 cases that reported a 
principal diagnosis code describing CRAO or BRAO without a procedure 
code describing the administration of a thrombolytic agent or a 
procedure code describing HBOT with an average length of stay of 2.2 
days and average costs of $5,482. There are nine cases that reported a 
principal diagnosis code describing CRAO or BRAO with a procedure code 
describing HBOT with an average length of stay of 2 days and average 
costs of $6,491. There are 47 cases that reported a principal diagnosis 
code describing CRAO or BRAO with a procedure code describing the 
administration of a thrombolytic agent with an average length of stay 
of 2.3 days and average costs of $14,335.
    The data analysis shows that the 774 cases in MS-DRG 123 reporting 
a principal diagnosis code describing CRAO or BRAO without a procedure 
code describing the administration of a thrombolytic agent or a 
procedure code describing HBOT have average costs lower than the 
average costs in the FY 2021 MedPAR file for MS-DRG 123 ($5,482 
compared to $6,457), and the average length of stay is shorter (2.2 
days compared to 2.5 days). For the nine cases in MS-DRG 123 reporting 
a principal diagnosis code describing CRAO or BRAO with a procedure 
code describing HBOT, the average length of stay is shorter (2 days 
compared to 2.5 days) and the average costs ($6,491 compared to $6,457) 
are slightly higher than the average length of stay and average costs 
compared to all cases in that MS-DRG. For the 47 cases in MS-DRG 123 
reporting a principal diagnosis code describing CRAO or BRAO with a 
procedure code describing the administration of a thrombolytic agent, 
the average length of stay is slightly shorter (2.3 days compared to 
2.5 days) and the average costs are higher ($14,335 compared to $6,457) 
than the average length of stay and average costs compared to all cases 
in that MS-DRG.
    We also examined claims data from the September 2021 update of the 
FY 2021 MedPAR file for MS-DRGs 061, 062, and 063. Our findings are 
shown in the following table.
[GRAPHIC] [TIFF OMITTED] TR10AU22.030

BILLING CODE 4120-01-C
    We stated in the proposed rule that because MS-DRG 123 is a base 
DRG and there is a three-way split within MS-DRGs 061, 062, and 063, we 
also analyzed the 47 cases reporting a principal diagnosis code 
describing CRAO or BRAO with a procedure code describing the 
administration of a thrombolytic agent and the nine cases reporting a 
principal diagnosis code describing CRAO or BRAO with a procedure code 
describing HBOT for the presence or absence of a secondary diagnosis 
designated as a complication or comorbidity (CC) or a major 
complication or comorbidity (MCC).

[[Page 48833]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.031

    We stated that this data analysis showed that the cases in MS-DRG 
123 reporting a principal diagnosis code describing CRAO or BRAO with a 
procedure code describing the administration of a thrombolytic agent or 
with a procedure code describing HBOT when distributed based on the 
presence or absence of a secondary diagnosis designated as a CC or an 
MCC have average costs lower than the average costs in the FY 2021 
MedPAR file for MS-DRGs 061, 062, and 063 respectively, and the average 
lengths of stay are shorter. Accordingly, we stated that we did not 
believe the data adequately supported a potential reassignment of these 
cases to MS-DRGs 061, 062, and 063 respectively.
    Our clinical advisors reviewed this issue and the related data 
analysis and did not believe that the small subset of patients with a 
diagnosis of CRAO or BRAO receiving a thrombolytic agent or hyperbaric 
oxygen therapy warranted a separate MS-DRG or reassignment at this 
time. We stated our clinical advisors noted the average costs for cases 
of patients with a diagnosis of CRAO or BRAO receiving HBOT are only 
slightly higher than the average costs for all cases in MS-DRG 123 
($6,491 compared to $6,457). The average costs for cases of patients 
with a diagnosis of CRAO or BRAO receiving a thrombolytic agent are 
higher than the average costs for all cases in MS-DRG 123 however when 
distributed based on the presence or absence of a secondary diagnosis 
designated as a complication or comorbidity (CC) or a major 
complication or comorbidity (MCC), we stated that it was unclear to 
what degree the higher average costs for these cases are attributable 
to the severity of illness of the patient and other circumstances of 
the admission as opposed to the administration of a thrombolytic agent, 
as the claims data reflects a wide variance with regard to average 
costs for these cases.
    Our clinical advisors further noted that ischemia is defined as a 
condition in which the blood vessels become blocked, and blood flow is 
stopped or reduced. The condition has many potential causes, including 
a blockage caused by a blood clot, or due to buildup of deposits, such 
as cholesterol. Ischemia can occur anywhere in the body, and the 
different names for the condition depend on the organ or body part 
affected such as the brain (cerebral ischemia), heart (ischemic heart 
disease, myocardial ischemia, or cardiac ischemia), and intestines 
(mesenteric ischemia or bowel ischemia), legs (critical limb ischemia--
a form of peripheral artery disease), and skin (cutaneous ischemia), 
while they are similar in that they all involve a blocked blood vessel.
    In ICD-10 the body or organ system is the axis of the 
classification and diagnosis codes describing ischemia affecting other 
body parts are classified by the body or organ system affected. For 
example, codes describing myocardial ischemia are assigned to MDC 05 
(Diseases and Disorders of the Circulatory System) and codes describing 
mesenteric ischemia are assigned to MDC 06 (Diseases and Disorders of 
the Digestive System). Our clinical advisors disagreed with assigning 
the diagnosis codes describing CRAO and BRAO to MDC 01. Our clinical 
advisors noted the concept of clinical coherence generally requires 
that the patient characteristics included in the definition of each MS-
DRG relate to a common organ system or etiology and that a specific 
medical specialty should typically provide care to the patients in the 
DRG. While closely related, the eyes and the brain are different 
organs. Our clinical advisors stated that because the diagnosis codes 
used to report CRAO and BRAO describe ischemia affecting the retina, 
these diagnosis codes are appropriately assigned to MDC 02 (Diseases 
and Disorders of the Eye). The retina is a collection of cells at the 
back of the eye where the processing of visual information begins. Due 
to the retina's vital role in vision, damage to it can cause permanent 
blindness. The presence of CRAO or BRAO requires input from an 
ophthalmologist and treatment for these diagnoses would be expected to 
utilize different resources than a diagnosis of cerebral ischemia which 
may or may not involve visual impairment. Other possible interventions 
for CRAO or BRAO include attempting to lower the intraocular pressure 
with medication or by using a small-gauge needle to remove fluid to try 
to dislodge the embolus or ocular massage to dislodge the clot, which 
are not interventions generally performed for a diagnosis of acute 
ischemic stroke.
    We stated in the FY 2023 IPPS/LTCH PPS proposed rule that to 
explore other mechanisms to address this request, we also reviewed 
claims data to consider the option of adding another severity level to 
the current structure of MS-DRG 123 (Neurological Eye Disorders) and 
assigning the cases with a principal diagnosis of CRAO or BRAO with a 
procedure code describing the administration of a thrombolytic agent to 
the highest level. This option would have involved modifying the 
current base MS-DRG to a two-way severity level split or to a three-way 
severity level split of ``with MCC or thrombolytic agent, with CC, and 
without CC/MCC.'' Therefore, it would have included proposing new MS-
DRGs if the data and our clinical advisors supported creation of new 
MS-DRGs. However, as displayed in the data findings in the table that 
follows, we found that the

[[Page 48834]]

data did not support this option. We applied the five criteria as 
described in section II.D.1.b. of the preamble of the proposed rule and 
this final rule to determine if it would be appropriate to subdivide 
cases currently assigned to MS-DRG 123 into severity levels. This 
analysis generally includes two years of MedPAR claims data to compare 
the data results from one year to the next to avoid making 
determinations about whether additional severity levels are warranted 
based on an isolated year's data fluctuation and also, to validate that 
the established severity levels within a base MS-DRG are supported. 
However, as discussed in the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 
25092), our MS-DRG analysis last year was based on ICD-10 claims data 
from the March 2020 update of the FY 2019 MedPAR file, which contains 
hospital claims received from October 1, 2018 through March 31, 2020, 
for discharges occurring through September 30, 2019 and the ICD-10 
claims data from the September 2020 update of the FY 2020 MedPAR file, 
which contains hospital claims received from October 1, 2019 through 
September 30, 2020, for discharges occurring through September 30, 2020 
given the potential impact of the PHE for COVID-19. Therefore, for the 
FY 2023 IPPS/LTCH PPS proposed rule, we reviewed the claims data for 
base MS-DRG 123 using the March 2020 update of the FY 2019 MedPAR file 
and the September 2020 update of the FY 2020 MedPAR file, which were 
used in our analysis of claims data for MS-DRG reclassification 
requests for FY 2022. We also reviewed the claims data for base MS-DRG 
123 using the September 2021 update of the FY 2021 MedPAR file, which 
were used in our analysis of claims data for MS-DRG reclassification 
requests for FY 2023. Our findings are shown in the table:
[GRAPHIC] [TIFF OMITTED] TR10AU22.032

    We stated that we applied the criteria to create subgroups for the 
three-way severity level split. We referred the reader to section 
II.D.1.b. of the preamble of the FY 2023 IPPS/LTCH PPS proposed rule, 
for related discussion regarding our finalization of the expansion of 
the criteria to include the NonCC subgroup and our proposal to continue 
to delay application of the NonCC subgroup criteria to existing MS-DRGs 
with a three-way severity level split to maintain more stability in the 
current MS-DRG structure. We found that the criterion that there be at 
least 500 cases for each subgroup was not met, as shown in the table 
based on the data in the FY 2019, FY 2020, and FY 2021 MedPAR files. 
Specifically, for the ``with MCC'', ``with CC'', and ``without CC/MCC'' 
split, there were only 376 cases in the ``with MCC'' subgroup based on 
the data in the FY 2019 MedPAR file, only 345 cases in the ``with MCC'' 
subgroup based on the data in the FY 2020 MedPAR file and only 374 
cases in the ``with MCC'' subgroup based on the data in the FY 2021 
MedPAR file.
    We then applied the criteria to create subgroups for the two-way 
severity level splits. For the ``with MCC'' and ``without MCC'' 
(CC+NonCC) split, the criterion that there be at least 500 cases for 
each subgroup failed due to low volume each year, specifically, for the 
``with MCC'' subgroup as previously described. For the ``with CC/MCC'' 
and ``without CC/MCC'' (NonCC) split, we found that the criterion that 
there be at least a $2,000 difference in average costs between the 
``with CC/MCC'' and ``without CC/MCC'' subgroups also failed. In the FY 
2019 MedPAR file, our data analysis shows average costs in the 
hypothetical ``with CC/MCC'' subgroup of $6,282 and average costs in 
the hypothetical ``without CC/MCC'' subgroup of $4,832, for a 
difference of only $1,450 ($6,282 minus $4,832 = $1,450). In the FY 
2020 MedPAR file, our data analysis shows average costs in the 
hypothetical ``with CC/MCC'' subgroup of $6,573 and average costs in 
the hypothetical ``without CC/MCC'' subgroup of $5,122, for a 
difference of only $1,451 ($6,573 minus $5,122 = $1,451). In the FY 
2021 MedPAR file, our data analysis shows average costs in the 
hypothetical ``with CC/MCC'' subgroup of $7,176 and average costs in 
the hypothetical ``without CC/MCC'' subgroup of $5,364, for a 
difference of only $1,812 ($7,176 minus $5,364 = $1,812). We stated 
that our data analysis indicated that the current base MS-DRG 123 
maintains the overall accuracy of the IPPS, and that the claims data 
did not support a three-way or a two-way severity level split for MS-
DRG 123.
    Lastly, we stated we explored reassigning cases with a principal 
diagnosis of CRAO or BRAO that receive the administration of a 
thrombolytic agent to other MS-DRGs within MDC 02. However, our review 
did not support reassignment of these cases to any other medical MS-
DRGs as these cases would not be clinically coherent with the cases 
assigned to those other MS-DRGs.
    Therefore, based on the various data analyses we performed to 
explore the possible reassignment of cases with a principal diagnosis 
of CRAO or BRAO with a procedure code describing the administration of 
a thrombolytic agent or a procedure code describing hyperbaric oxygen 
therapy, and the clinical analysis as previously discussed, for FY 2023 
we did not propose any MS-DRG changes for cases with a principal 
diagnosis of CRAO or BRAO with a procedure code describing the 
administration of a thrombolytic agent or a procedure code describing 
hyperbaric oxygen therapy.
    Comment: Some commenters expressed support for CMS' decision to not 
propose any MS-DRG changes for cases with a principal diagnosis of CRAO 
or BRAO with a procedure code describing the administration of a 
thrombolytic agent or a procedure code describing hyperbaric oxygen 
therapy.
    Response: We appreciate the commenters' support.
    Comment: Other commenters opposed or expressed concerns with CMS' 
decision to not propose any MS-DRG changes for cases with a principal 
diagnosis of CRAO or BRAO with a procedure code describing the 
administration of a thrombolytic agent or a procedure code describing 
hyperbaric oxygen therapy. These commenters stated from a 
pathophysiologic perspective, CRAO is the same process as a stroke of 
the brain and that the retina, although located within the eye, is a 
core component of the central nervous system and consists of brain 
cells (neurons) that also extend

[[Page 48835]]

through the entire course of the brain. These commenters also stated 
that the relationship of any particular tissue to its organ is related 
to its structure and function, and not its location. According to the 
commenters, acute CRAO is a medical emergency, equivalent to acute 
cerebral ischemic stroke, that needs to be treated in the same way with 
urgent inpatient evaluation, cerebrovascular and cardiac workup, and 
intervention. The commenters urged CMS to assign cases reporting 
diagnosis codes describing central retinal artery occlusion with a 
procedure code describing the administration of a thrombolytic agent or 
a procedure code describing hyperbaric oxygen therapy to MS-DRGs 061, 
062, and 063 to ensure appropriate payment for these cases.
    Response: We thank the commenters for their feedback. Our clinical 
advisors reviewed the commenters' concerns and note that although 
commenters' state the relationship of any particular tissue to its 
organ is related to its structure and function, and not its location, 
in ICD-10, however, the body or organ system is the axis of the 
classification. By design, the patient characteristics included in the 
definition of each MS-DRG relate to a common organ system or etiology. 
Our clinical advisors agree with commenters that the retina is similar 
to the brain in terms of cellular and functional elements, but they 
note the retina is a part of the eye. Our clinical advisors state that 
the presence of CRAO or BRAO, which typically presents sudden, painless 
monocular loss of visual acuity and peripheral vision, requires input 
from an ophthalmologist which would not always be expected in a 
diagnosis of cerebral ischemia, which may or may not involve visual 
impairment. Our clinical advisors continue to believe CRAO and BRAO are 
appropriately classified with other eye conditions currently assigned 
to MDC 02.
    Therefore, after consideration of the public comments we received, 
and for the reasons discussed, we are finalizing our proposal, without 
modification, to maintain the current assignment of cases with a 
principal diagnosis of CRAO or BRAO with a procedure code describing 
the administration of a thrombolytic agent or a procedure code 
describing hyperbaric oxygen therapy.
5. MDC 04 (Diseases and Disorders of the Respiratory System): Acute 
Respiratory Distress Syndrome (ARDS)
    In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28155 through 
28156), we discussed a request we received to reassign cases reporting 
diagnosis code J80 (Acute respiratory distress syndrome) as the 
principal diagnosis from MS-DRG 204 (Respiratory Signs and Symptoms) to 
MS-DRG 189 (Pulmonary Edema and Respiratory Failure).
    According to the requestor, when a patient presents with the 
condition of acute respiratory failure that progresses to acute 
respiratory distress syndrome (ARDS) during the hospital stay, official 
coding guidance instructs to only report the diagnosis code for ARDS 
(code J80). The requestor stated that in the American Hospital 
Association's (AHA) Coding Clinic for ICD-10-CM and ICD-10-PCS, Fourth 
Quarter 2020 publication, for a patient who is admitted in acute 
hypoxic respiratory failure that progresses to ARDS, the advice is to 
assign code J80, Acute respiratory distress syndrome. Additionally, in 
the ICD-10-CM Tabular List of Diseases, per the Excludes 1 note under 
category J96 (Respiratory failure, not elsewhere classified) only code 
J80 should be assigned when respiratory failure and ARDS are both 
documented. The same publication also maintained that ARDS is a life-
threatening form of respiratory failure and is not an unrelated 
condition. Therefore, when acute respiratory failure is documented 
along with ARDS, only one code is reported to capture the highest level 
of severity.
    The requestor also conveyed the Fourth Quarter 2020 publication's 
reference to previously published advice from the Fourth Quarter 2017 
publication that stated, ``Acute respiratory distress syndrome (ARDS) 
is a life-threatening condition. ARDS is a rapidly progressive disorder 
that has symptoms of dyspnea, tachypnea, and hypoxemia. Fluid builds up 
in the alveoli and lowers the amount of oxygen that is circulated 
through the bloodstream. Low levels of oxygen in the blood threatens 
organ function. ARDS is often associated with sepsis, pneumonia, trauma 
and aspiration. The majority of people who develop ARDS are already in 
the hospital in critical condition from some other health complication. 
The focus of treatment is getting oxygen to the organs.''
    We examined claims data from the September 2021 update of the FY 
2021 MedPAR file for all cases in MS-DRG 204 and the cases reporting 
ARDS (code J80) as a principal diagnosis. Our findings are shown in the 
following table.
[GRAPHIC] [TIFF OMITTED] TR10AU22.033

    As shown in the table, the data demonstrate a longer average length 
of stay (7.6 days versus 2.8 days) and higher average costs ($15,077 
versus $6,780) for the 96 cases reporting ARDS (code J80) as a 
principal diagnosis when compared to all 5,241 cases in MS-DRG 204.
    We also examined claims data from the September 2021 update of the 
FY 2021 MedPAR file for all cases in MS-DRG 189. Our findings are shown 
in the following table.

[[Page 48836]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.034

    We stated in the proposed rule that the data analysis supports that 
cases reporting ARDS (code J80) are more appropriately aligned with the 
average length of stay and average costs of the cases in MS-DRG 189 in 
comparison to MS-DRG 204 when ARDS is reported as a principal 
diagnosis. We also stated in the proposed rule that we agree, 
consistent with the coding clinic advice, ARDS is a life-threatening 
form of respiratory failure and the conventions of the ICD-10-CM 
classification as displayed in the Tabular List of Diseases Excludes 
note, support the concept that cases reporting ARDS as a principal 
diagnosis are more clinically coherent with the other conditions 
currently assigned to MS-DRG 189.
    For these reasons, we proposed to reassign cases reporting ARDS 
(code J80) as a principal diagnosis from MS-DRG 204 to MS-DRG 189 
effective FY 2023.
    Comment: Commenters supported the proposal to reassign cases 
reporting diagnosis code J80 as a principal diagnosis from MS-DRG 204 
to MS-DRG 189.
    Response: We thank the commenters for their support.
    After consideration of the public comments we received, we are 
finalizing our proposal to reassign cases reporting ARDS (code J80) as 
a principal diagnosis from MS-DRG 204 to MS-DRG 189 effective FY 2023.
6. MDC 05 (Diseases and Disorders of the Circulatory System)
a. Percutaneous Transluminal Coronary Angioplasty (PTCA) Logic
    In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28156 through 
28157), we stated that we identified a replication issue from the ICD-9 
based MS-DRGs to the ICD-10 based MS-DRGs for procedure code 02UG3JE 
(Supplement mitral valve created from left atrioventricular valve with 
synthetic substitute, percutaneous approach) that was created effective 
October 1, 2016 (FY 2017), to identify and describe further 
interventions that may occur for a patient who had previously undergone 
cardiac valve surgery to correct a congenital anomaly, such as repair 
of a complete common atrioventricular canal defect.
    As stated in the proposed rule, we used our established process in 
the assignment of new procedure code 02UG3JE to the most appropriate 
MS-DRG(s) for FY 2017. Procedure code 02UG3JE was proposed for 
assignment to the same MS-DRGs as its predecessor code. The predecessor 
code for procedure code 02UG3JE as shown in the 2017 ICD-10-PCS 
conversion table (available via the internet on the CMS web page at: 
https://www.cms.gov/Medicare/Coding/ICD10/2017-ICD-10-PCS-and-GEMs) is 
02UG3JZ (Supplement mitral valve with synthetic substitute, 
percutaneous approach). The ICD-9-CM comparable translation for this 
code (02UG3JZ) is procedure code 35.97 (Percutaneous mitral valve 
repair with implant), which identifies the use of the MitraClip[supreg] 
technology that has been discussed extensively in prior rulemaking.
    In the FY 2017 rulemaking, using our established process, new 
procedure code 02UG3JE was proposed and finalized for assignment to the 
following MS-DRGs for FY 2017, as also shown in Table 6B.--New 
Procedure Codes in association with the FY 2017 IPPS/LTCH PPS proposed 
and final rules (available via the internet on the CMS web page at: 
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/Acute-Inpatient-Files-for-Download). We noted that 
the listed MS-DRGs also reflect the MS-DRGs that the predecessor code 
(02UG3JZ) was assigned to at the time of the proposed rule.
[GRAPHIC] [TIFF OMITTED] TR10AU22.035

    However, as also discussed in the FY 2017 IPPS/LTCH PPS final rule 
(81 FR 56809 through 56813), in connection with replication efforts 
between the ICD-9 and ICD-10 based MS-DRGs and the surgical hierarchy, 
the predecessor procedure code (02UG3JZ) was reassigned from MS-DRGs 
273 and 274 to MS-DRG 228 (Other Cardiothoracic Procedures with MCC) 
and revised MS-DRG 229 (Other Cardiothoracic Procedures without MCC), 
and was removed from the PTCA logic for MS-DRGs 231 and 232. However, 
these proposed and finalized MS-DRG changes for procedure code 02UG3JZ 
were not considered for purposes of the MS-DRG assignments for new 
procedure code 02UG3JE, which were instead finalized as proposed based 
on the existing MS-DRG assignments for the predecessor code, and code 
02UG3JE continued to remain on the

[[Page 48837]]

PTCA list in the GROUPER logic for MS-DRGs 231 and 232.
    As noted in the proposed rule, our clinical advisors stated that 
procedure code 02UG3JE does not describe a PTCA procedure. As also 
noted in the proposed rule, we analyzed claims data from the September 
2021 update of the FY 2021 MedPAR file for cases in MS-DRGs 231 and 232 
to determine if there were any cases reported with procedure code 
02UG3JE, and there were no such cases found.
    Accordingly, because the procedure described by procedure code 
02UG3JE is not clinically consistent with a PTCA procedure and it was 
initially assigned to the list for PTCA procedures in the GROUPER logic 
as a result of replication in the transition from ICD-9 to ICD-10 based 
MS-DRGs, we proposed to remove procedure code 02UG3JE from the list for 
PTCA procedures in the GROUPER logic for MS-DRGs 231 and 232 effective 
FY 2023. We also proposed to maintain the MS-DRG assignment for 
procedure code 02UG3JE in MS-DRGs 266 and 267 (Endovascular Cardiac 
Valve Replacement and Supplement Procedures with and without MCC, 
respectively) for FY 2023.
    Comment: Commenters agreed with the proposal to remove procedure 
code 02UG3JE from the GROUPER logic for MS-DRGs 231 and 232 and to 
maintain the assignment in MS-DRGs 266 and 267.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to remove procedure code 02UG3JE from the list 
for PTCA procedures in MS-DRGs 231 and 232 and to maintain the 
assignment for code 02UG3JE in MS-DRGs 266 and 267 in the GROUPER logic 
for FY 2023.
b. Neuromodulation Device Implant for Heart Failure 
(BarostimTM Baroreflex Activation Therapy)
    As discussed in the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 
28157 through 28162), the BAROSTIM NEOTM System is the first 
neuromodulation device system designed to trigger the body's main 
cardiovascular reflex to target symptoms of heart failure. The system 
consists of an implantable pulse generator (IPG) that is implanted 
subcutaneously in the upper chest below the clavicle, a stimulation 
lead that is sutured to either the right or left carotid sinus to 
activate the baroreceptors in the wall of the carotid artery and a 
wireless programmer system that is used to non-invasively program and 
adjust BAROSTIM NEOTM therapy via telemetry. The BAROSTIM 
NEOTM System is indicated for the improvement of symptoms of 
heart failure in a subset of patients with symptomatic New York Heart 
Association (NYHA) class II and III heart failure with low cardiac 
ejection fractions who do not benefit from guideline directed 
pharmacologic therapy or qualify for Cardiac Resynchronization Therapy 
(CRT).
    The BAROSTIM NEOTM System was approved for new 
technology add-on payments for FY 2021 (85 FR 58716 through 58717) and 
FY 2022 (86 FR 44974). We refer readers to section II.F.5.a of the 
preamble of the proposed rule and this final rule for a discussion 
regarding the FY 2023 status of technologies approved for FY 2022 new 
technology add-on payments, including the BAROSTIM NEOTM 
System.
    For the FY 2023 IPPS/LTCH PPS proposed rule, we received a request 
to (1) reassign the ICD-10-PCS procedure codes that describe the 
implantation of the BAROSTIM NEOTM System from MS-DRGs 252, 
253 and 254 (Other Vascular Procedures with MCC, with CC, without MCC 
respectively) to MS-DRGs 222, 223, 224, 225, 226, and 227 (Cardiac 
Defibrillator Implant with and without Cardiac Catheterization with and 
without AMI/HF/Shock with and without MCC, respectively) and (2) 
reassign the procedure code that describes the placement of a BAROSTIM 
NEOTM IPG alone from MS-DRGs 252, 253 and 254 to MS-DRG 245 
(AICD Generator Procedures).
    We stated in the FY 2023 IPPS/LTCH PPS proposed rule that the 
following ICD-10-PCS procedure codes uniquely identify the implantation 
of the BAROSTIM NEOTM System: 0JH60MZ (Insertion of 
stimulator generator into chest subcutaneous tissue and fascia, open 
approach) in combination with 03HK3MZ (Insertion of stimulator lead 
into right internal carotid artery, percutaneous approach) or 03HL3MZ 
(Insertion of stimulator lead into left internal carotid artery, 
percutaneous approach). The requestor noted that ICD-10-PCS codes 
0JH60MZ, 03HK3MZ and 03HL3MZ are individually assigned to MDC 05 in MS-
DRGs 252, 253, and 254 but not mapped to the logic of these MS-DRGs in 
a code combination or code cluster. According to the requestor this 
means that cases with a principal diagnosis from MDC 05 with procedure 
codes describing the implantation of a BAROSTIM NEOTM system 
(0JH60MZ with 03HL3MZ or 03HK3MZ); with procedure codes describing 
placement of the stimulator generator alone (0JH60MZ); or with 
procedure codes describing the placement of a carotid sinus lead only 
(03HL3MZ or 03HK3MZ) are all assigned to MS-DRGs 252, 253, and 254, 
despite the significant differences in the clinical coherence and 
resources required to perform these distinct procedures.
    The requestor stated that cases reporting procedure codes 
describing the implantation of a BAROSTIM NEOTM system are 
more clinically similar to, and have costs that are more closely 
aligned to, cases within MS-DRGs 222, 223, 224, 225, 226, and 227. The 
requestor stated that according to its own analysis, the population of 
Medicare patients surgically treated with procedures assigned to MS-
DRGs 222, 223, 224, 225, 226, and 227 is essentially identical to the 
population treated with the BAROSTIM NEOTM System. According 
to the requestor, this congruent patient population accounts for 
essentially all cases assigned to MS-DRGs 222, 223, 224, 225, 226, and 
227. The requestor stated their analysis demonstrated that over 80% of 
the cases in MS-DRGs 222, 223, 224, 225, 226, and 227 had a diagnosis 
of heart failure, compared to only 30% of cases with a diagnosis of 
heart failure assigned to MS-DRGs 252, 253, and 254. The requestor 
stated that the subset of patients that have an indication for the 
implantation of a BAROSTIM NEOTM system also have 
indications for the implantation of Implantable Cardioverter 
Defibrillators (ICD), Cardiac Resynchronization Therapy Defibrillators 
(CRT-D) and/or Cardiac Contractility Modulation (CCM) devices, all of 
which also require the permanent implantation of a programmable, 
electrical pulse generator and at least one electrical lead. The 
requestor specifically highlighted that the procedure code combinations 
describing the implantation of a cardiac contractility modulation (CCM) 
device system, which consists of a programmable implantable pulse 
generator (IPG) and three leads, one of which is implanted into the 
right atrium and the other two leads which are inserted into the right 
ventricle is assigned to MS-DRGs 222, 223, 224, 225, 226, and 227, and 
the codes describing the insertion of contractility modulation device 
generator alone are assigned to MS-DRG 245. The requestor stated that 
the average resource utilization required to implant the BAROSTIM 
NEOTM System demonstrates a significant disparity compared 
to all procedures within MS-DRGs 252, 253, and 254 and noted that the 
cost of the BAROSTIM NEOTM implantable device is $35,000, 
which is in range with the cost of the other

[[Page 48838]]

cardiac implantable devices (for example ICD, CRT-D, and CCM) assigned 
to MS-DRGs 222, 223, 224, 225, 226, and 227.
    The requestor stated that the majority of the procedures assigned 
to MS-DRGs 252, 253, and 254 are primarily designed to identify, 
diagnose, clear and restructure veins and arteries, excluding those 
that require implantable devices. Furthermore, the requestor stated the 
surgical procedures within MS-DRGs 252, 253, and 254 are not intended 
to treat or improve the function of the heart, nor treat the symptoms 
of heart failure.
    The requestor acknowledged that there are very few cases within the 
publicly available Medicare inpatient claims data that potentially 
includes procedure codes describing the implantation of a BAROSTIM 
NEOTM system. The requestors' own analysis revealed fewer 
than 11 cases with procedure codes describing the implantation of a 
BAROSTIM NEOTM system in the combined FY 2019 and FY 2020 
MedPAR data and noted that during much of this time period, the 
BAROSTIM NEOTM System was only implanted as part of a 
controlled clinical trial. The requestor stated that this incomplete 
data should not be used to determine initial MS-DRG assignments, 
especially for new FDA designated `breakthrough' medical technologies 
like the BAROSTIM NEOTM system. Rather, the requestor stated 
that CMS should use available information and expert knowledge to make 
initial MS-DRG assignments, while waiting for a substantial number of 
Medicare covered, post-approved claims from a disperse set of hospitals 
to reconsider MS-DRG assignments as necessary. The requestor cautioned 
that upon new technology add-on payments expiration, and if the 
inadequate MS-DRG assignment for these procedures continues, inpatient 
admissions to implant the BAROSTIM NEOTM system will be paid 
less than outpatient admissions to perform the same procedures.
    The ICD-10-CM diagnosis codes that describe heart failure are found 
in the following table. These diagnosis codes are all currently 
assigned to MDC 05.

[[Page 48839]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.036

    We stated in the proposed rule that first, we examined claims data 
from the September 2021 update of the FY 2021 MedPAR file for MS-DRGs 
252, 253 and 254 to identify cases reporting a diagnosis of heart 
failure and procedure codes describing the implantation of the BAROSTIM 
NEOTM system with or without a procedure code describing the 
performance of a cardiac catheterization as MS-DRGs 222, 223, 224, 225, 
226, and 227 are defined by the performance of cardiac catheterization. 
Our findings are shown in the following table.

[[Page 48840]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.037

    As shown in the table, the data analysis performed indicates that 
the two cases in MS-DRG 252 reporting procedure codes describing the 
implantation of a BAROSTIM NEOTM system have an average 
length of stay that is shorter than the average length of stay for all 
the cases in MS-DRG 252 (4.5 days versus 7.6 days) and higher average 
costs when compared to all the cases in MS-DRG 252 ($67,588 versus 
$27,488). These two cases did not also report a procedure code 
describing the performance of a cardiac catherization. The one case in 
MS-DRG 253 reporting procedure codes describing the implantation of a 
BAROSTIM NEOTM system had a length of stay that is shorter 
than the average length of stay for all the cases in MS-DRG 253 (1 day 
versus 5.2 days) and lower costs when compared to all the cases in MS-
DRG 253 ($19,237 versus $21,978). This case did not also report a 
procedure code describing the performance of a cardiac catherization. 
We found zero cases in MS-DRG 254 reporting procedure codes describing 
the implantation of a BAROSTIM NEOTM system.
    We stated that our clinical advisors reviewed this data and noted 
that was it is difficult to detect patterns of complexity and resource 
intensity based on the three cases that reported procedure codes 
describing the implantation of a BAROSTIM NEOTM system. The 
claims data also reflect a wide variance with regard to the length of 
stay and average costs for the three cases that did report the 
implantation of a BAROSTIM NEOTM system. We stated that the 
results of the claims analysis demonstrated we did not have sufficient 
claims data on which to base and evaluate any proposed changes to the 
current MS-DRG assignment. We also stated that our clinical advisors 
also expressed concern in equating the implantation of a BAROSTIM 
NEOTM system to the placement of ICD, CRT-D, and CCM devices 
as these devices all differ in terms of technical complexity and 
anatomical placement of the electrical lead(s). Our clinical advisors 
noted there is no intravascular component or vascular puncture involved 
when implanting a BAROSTIM NEOTM system. Our clinical 
advisors also noted the placement of ICD, CRT-D, and CCM devices 
generally involve a lead being affixed to the myocardium, being 
threaded through the coronary sinus or crossing a heart valve and are 
procedures that involve a greater level of complexity than affixing the 
stimulator lead to either the right or left carotid sinus when 
implanting a BAROSTIM NEOTM system.
    Next, to evaluate the request to reassign the procedure code that 
describes the placement of a BAROSTIM NEOTM IPG alone from 
MS-DRGs 252, 253 and 254 to MS-DRG 245 (AICD Generator Procedures), we 
stated in the proposed rule that we examined claims data from the 
September 2021 update of the FY 2021 MedPAR file for all cases in MS-
DRGs 252, 253 and 254 and compared the results to cases with a 
procedure code describing placement of the stimulator generator alone. 
Our findings are shown in the following table.
[GRAPHIC] [TIFF OMITTED] TR10AU22.038


[[Page 48841]]


    As shown in the table, the data analysis performed indicates that 
the 12 cases in MS-DRG 252 reporting a procedure code describing 
placement of the stimulator generator alone have an average length of 
stay that is longer than the average length of stay for all the cases 
in MS-DRG 252 (8.8 days versus 7.6 days) and higher average costs when 
compared to all the cases in MS-DRG 252 ($56,622 versus $27,488). The 
four cases in MS-DRG 253 reporting a procedure code describing 
placement of the stimulator generator alone have an average length of 
stay that is shorter than the average length of stay for all the cases 
in MS-DRG 253 (2.5 days versus 5.2 days) and higher average costs when 
compared to all the cases in MS-DRG 253 ($30,451 versus $21,978). We 
found zero cases in MS-DRG 254 reporting a procedure code describing 
placement of the stimulator generator alone.
    We stated that our clinical advisors reviewed this data, and found, 
similar to the analysis of the data from the three cases that reported 
procedure codes describing the implantation of a BAROSTIM 
NEOTM system, that it was difficult to detect patterns of 
complexity and resource intensity based on the few cases that reported 
procedure codes describing placement of the stimulator generator alone. 
The claims data similarly reflects a wide variance with regard to the 
length of stay and average costs for these cases that did report the 
placement of the stimulator generator alone, indicating there may have 
been other factors contributing to the higher costs. When reviewing the 
consumption of hospital resources for this small subset of cases, the 
claims data also suggest that the increased costs may be attributable 
to the severity of illness of the patient and other circumstances of 
the admission as the patients tended to have a major complication or 
co-morbid (MCC) condition reported based on the MS-DRG assigned.
    We stated in the proposed rule that we recognized the average costs 
of the small numbers of cases reporting a procedure code describing 
placement of the stimulator generator alone are greater when compared 
to the average costs of all cases in their respective MS-DRG. We noted 
that the MS-DRG system is a system of averages and it is expected that 
within the diagnostic related groups, some cases may demonstrate higher 
than average costs, while other cases may demonstrate lower than 
average costs. We further noted that section 1886(d)(5)(A) of the Act 
provides for Medicare payments to Medicare-participating hospitals in 
addition to the basic prospective payments for cases incurring 
extraordinarily high costs.
    In response to the requestor's concerns regarding procedures 
currently assigned to MS-DRGs 252, 253 and 254, as discussed in section 
II.D.3.b. of the preamble of the proposed rule and this final rule, we 
note that MS-DRGs 252, 253, and 254 (Other Vascular Procedures with 
MCC, with CC, and without CC/MCC, respectively) are examples of the 
``other'' surgical class, and therefore it is expected that there will 
be procedures not as precisely clinically aligned within the definition 
(logic) of these MS-DRGs. In regard to the concern about the 
implications for reimbursement when these procedures are performed in 
the outpatient setting as opposed to the inpatient setting, we noted 
that the goals of reviewing the MS-DRG assignments of particular 
procedures are to better clinically represent the resources involved in 
caring for these patients and to enhance the overall accuracy of the 
system.
    In the proposed rule, in response to the requestor's statement that 
CMS should use available information and expert knowledge to make 
initial MS-DRG assignments, while waiting for a substantial number of 
Medicare covered, post-approved claims from a disperse set of hospitals 
to reconsider MS-DRG assignments as necessary, we noted that we use our 
established process for GROUPER assignments for new diagnosis and 
procedure codes. Specifically, consistent with our established process 
for assigning new diagnosis and procedure codes, we stated that we 
review the predecessor code and MS-DRG assignment most closely 
associated with the new diagnosis or procedure code, and in the absence 
of claims data, we consider other factors that may be relevant to the 
MS-DRG assignment, including the severity of illness, treatment 
difficulty, complexity of service and the resources utilized in the 
diagnosis or treatment of the condition. We noted that this process 
will not automatically result in the new diagnosis or procedure code 
being assigned to the same MS-DRG or having the same designation as the 
predecessor code. Members of the public have the opportunity to provide 
feedback on the assignment and designation of the codes if they 
disagree. We referred the reader to section II.D.17 of the proposed 
rule for a more detailed discussion of this process. We noted that when 
BAROSTIM NEOTM applied for new technology add-on payment, it 
was noted that the technology could be uniquely identified using a 
combination of existing ICD-10-PCS codes that were already assigned to 
MS-DRGs, and this circumstance generally would not provide a basis for 
MS-DRG reassignment.
    Lastly, as discussed in the proposed rule, our clinical advisors 
expressed concern regarding making proposed MS-DRG changes based on a 
specific, single technology (BAROSTIM NEOTM system), 
identified by only one unique procedure code combination versus 
considering proposed changes based on a group of related procedure 
codes that can be reported to describe that same type or class of 
technology, which is more consistent with the intent of the MS-DRGs.
    We stated that we believed that as the number of cases reporting 
procedure codes describing the implantation of neuromodulation devices 
for heart failure increases, a better view of the associated costs and 
lengths of stay on average will be reflected in the data for purposes 
of assessing any reassignment of these cases. We indicated that our 
clinical advisors stated that it would not be appropriate to reassign 
cases for patients from MS-DRGs 252, 253 and 254 to MS-DRGs 222, 223, 
224, 225, 226, and 227 in the absence of additional data to better 
determine the resource utilization for this subset of patients to help 
inform whether a reassignment would be clinically warranted. Therefore, 
for the reasons stated previously, we proposed to maintain the 
assignment of cases reporting procedure codes that describe the 
implantation of a neuromodulation device in MS-DRGs 252, 253 and 254 
for FY 2023. We also proposed to maintain the assignment of cases 
reporting a procedure code describing placement of a stimulator 
generator alone in MS-DRGs 252, 253 and 254 for FY 2023.
    Comment: Commenters expressed support for CMS' proposal to maintain 
the assignment of cases reporting procedure codes that describe the 
implantation of a neuromodulation device for heart failure in MS-DRGs 
252, 253 and 254 and to maintain the assignment of cases reporting a 
procedure code describing placement of a stimulator generator alone in 
MS-DRGs 252, 253 and 254 for FY 2023.
    Response: We appreciate the commenters' support.
    Comment: A commenter opposed CMS' proposal. The commenter stated 
that in their own analysis of the MedPAR data, and from their real-
world experience, patients with an indication for implantation of a 
neuromodulation device were not always admitted with a heart failure 
diagnosis. Many patients presented with multiple comorbidities, and 
various cardiovascular diagnosis

[[Page 48842]]

(for example, syncope, tachycardia, atrial fibrillation etc.) which 
lead to heart failure or are concomitant with heart failure.
    This commenter further stated that in their review of the data that 
CMS presented, the cost of cases with a diagnosis of heart failure with 
procedure codes describing the implantation of a neuromodulation device 
without cardiac catheterization and the cost of cases with a procedure 
code describing placement of the stimulator generator alone are both 
more than twice that of all cases in MS-DRG 252. The commenter stated 
even given these disparities, they did not believe that the full costs 
of the implantation of a neuromodulation device system have been 
appreciated in the MedPAR data files. According to the commenter, the 
manufacturer did not charge a cost for the device during clinical 
trials for the BAROSTIM NEOTM so such claims do not reflect 
the full device cost. The commenter also stated that the COVID-19 
pandemic has had a negative impact on inpatient hospital uptake of this 
new technology, which in turn has also limited the data available to 
support an accurate and appropriate MS-DRG assignment. The commenter 
stated they believe the fact that there are few cases in the MedPAR 
data files to date is not a reason to allow an overly mispriced MS-DRG 
assignment. The commenter stated that while BAROSTIM NEOTM 
procedures are typically performed in the outpatient setting, it is 
important to preserve inpatient access for those patients with 
comorbidities or other risk factors that necessitate an inpatient level 
of care. According to this commenter, the current MS-DRG assignments 
for procedure codes that describe the implantation of a neuromodulation 
device for heart failure would result in a lower payment than 
procedures performed in the outpatient setting and could result in 
barriers to treatment for patients who are not suitable candidates for 
the outpatient setting.
    This commenter urged CMS to reassign the ICD-10-PCS procedure codes 
that describe the implantation of a neuromodulation device for heart 
failure from MS-DRGs 252, 253 and 254 to MS-DRGs 222, 223, 224, 225, 
226 and 227 as requested. As alternatives, the commenter recommended to 
CMS, to instead, consider reassigning the ICD-10-PCS procedure codes 
that describe the implantation of the BAROSTIM NEOTM System 
from MS-DRGs 252, 253 and 254 to MS-DRGs 270, 271 and 272 (Other Major 
Cardiovascular Procedures with MCC, with CC, and without CC/MCC, 
respectively) or even create a new MS-DRG that appropriately describes 
these procedures.
    Response: We appreciate the commenter's feedback and concern. With 
regard to the commenter's concern that patients with an indication for 
the implantation of neuromodulation devices are not always admitted 
with heart failure diagnoses, we wish to confirm that the examination 
of claims data from the September 2021 update of the FY 2021 MedPAR 
file for MS-DRGs 252, 253 and 254 to identify cases reporting a 
diagnosis of heart failure and procedure codes describing the 
implantation of neuromodulation devices for heart failure with or 
without a procedure code describing the performance of a cardiac 
catheterization, as discussed in the proposed rule, included cases 
reporting a diagnosis of heart failure as either a principal or 
secondary diagnosis.
    Our clinical advisors reviewed commenter's concerns and continue to 
note we do not have sufficient claims data on which to base and 
evaluate any proposed changes to the current MS-DRG assignment, given 
the difficulties of assessing patterns of complexity and resource 
intensity based on the limited number of cases identified. Our clinical 
advisors also continue to express concern in equating the implantation 
of neuromodulation devices for heart failure to the placement of ICD, 
CRT-D, and CCM devices as these devices all differ in terms of 
technical complexity and anatomical placement of the electrical 
lead(s), as discussed in the proposed rule. In regard to the concern 
about the implications for payment when these procedures are performed 
in the outpatient setting as opposed to the inpatient setting, as noted 
in the proposed rule, and in prior rulemaking, the goals of reviewing 
the MS-DRG assignments of particular procedures are to better 
clinically represent the resources involved in caring for these 
patients and to enhance the overall accuracy of the system.
    With regard to the commenter's concern that there may have been 
other contributing factors that limited the data available to support 
an accurate and appropriate MS-DRG assignment of these cases, our 
clinical advisors believe that as the number of cases reporting 
procedure codes describing the implantation of neuromodulation devices 
for heart failure increases, the associated resource utilization can be 
better assessed for purposes of evaluating any reassignment of these 
cases. As additional claims data becomes available, we will continue to 
analyze the clinical nature of procedure codes describing the 
implantation of neuromodulation devices for heart failure and their MS-
DRG assignments, including potential alternative MS-DRG assignments, to 
further improve the overall accuracy of the IPPS payments in future 
rulemaking.
    Therefore, after consideration of the public comments we received, 
and for the reasons stated earlier, we are finalizing our proposal to 
maintain the assignment of cases reporting procedure codes that 
describe the implantation of a neuromodulation device in MS-DRGs 252, 
253 and 254, without modification, for FY 2023. We are also finalizing 
our proposal to maintain the assignment of cases reporting a procedure 
code describing placement of a stimulator generator alone in MS-DRGs 
252, 253 and 254, without modification, effective October 1, 2022 for 
FY 2023.
    In the proposed rule, we also noted that during our review of this 
issue, as we examined the GROUPER logic that would determine an 
assignment of a case to MS-DRGs 222, 223, 224, 225, 226, and 227, we 
found two diagnosis codes describing heart failure that are not 
currently in the listed principal diagnoses in the GROUPER logic for 
MS-DRGs 222 and 223 (Cardiac Defibrillator Implant with Cardiac 
Catheterization with AMI, HF or Shock with and without MCC, 
respectively). These diagnosis codes are listed in the following table.
[GRAPHIC] [TIFF OMITTED] TR10AU22.039


[[Page 48843]]


    We stated that as a result, when either of these codes are coded as 
a principal diagnosis, MS-DRGs 224 and 225 (Cardiac Defibrillator 
Implant with Cardiac Catheterization without AMI, HF, or Shock with and 
without MCC, respectively) are instead assigned when reported with a 
procedure code combination describing the implantation of a cardiac 
defibrillator and a procedure describing the performance of a cardiac 
catherization procedure. We referred the reader to the ICD-10 MS-DRG 
Definitions Manual Version 39.1, which is available via the internet on 
the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software 
for complete documentation of the GROUPER logic for MS-DRGs 222, 223, 
224, and 225.
    In the proposed rule, we stated that our clinical advisors reviewed 
this issue and believed that cases reporting diagnosis code I97.130 or 
I97.131 as a principal diagnosis are associated with a severity of 
illness on par with cases reporting a principal diagnosis of a type of 
heart failure. We noted that in order to code postprocedural heart 
failure in ICD-10-CM, instructional notes at category I50 direct to 
``code first heart failure following surgery'' (that is, I97.130 and 
I97.131) with a second code from subcategory of I50 listed after the 
postprocedural heart failure code to specify the type of heart failure. 
We stated that our clinical advisors recommended adding diagnosis codes 
I97.130 and I97.131 to the logic list of principal diagnoses that 
describe heart failure for clinical consistency, recognizing that 
coding guidelines instruct to code I97.130 and I97.131 before the codes 
from subcategory of I50 that specify the type of heart failure, as the 
codes from subcategory of I50 are currently in the listed principal 
diagnoses in the GROUPER logic for MS-DRGs 222 and 223. Therefore, we 
proposed to modify the GROUPER logic to allow cases reporting diagnosis 
code I97.130 or I97.131 as a principal diagnosis to group to MS-DRGs 
222 and 223 when reported with qualifying procedures.
    Comment: Commenters expressed support for CMS' proposal to modify 
the GROUPER logic to allow cases reporting diagnosis code I97.130 or 
I97.131 as a principal diagnosis to group to MS-DRGs 222 and 223 when 
reported with qualifying procedures.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to modify the GROUPER logic to allow cases 
reporting diagnosis code I97.130 or I97.131 as a principal diagnosis to 
group to MS-DRGs 222 and 223 when reported with qualifying procedures, 
without modification, effective October 1, 2022 for FY 2023.
c. Cardiac Mapping
    As discussed in the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 
28162 through 28163), we identified a replication issue from the ICD-9 
based MS-DRGs to the ICD-10 based MS-DRGs for procedure code 02K80ZZ 
(Map conduction mechanism, open approach). Cardiac mapping describes 
the creation of detailed maps to detect how the electrical signals that 
control the timing of the heart rhythm move between each heartbeat to 
identify the location of rhythm disorders. Cardiac mapping is generally 
performed during open-heart surgery or performed via cardiac 
catherization.
    In the FY 2016 IPPS/LTCH PPS final rule (80 FR 49363 through 
49369), we discussed a request to remove the cardiac ablation and other 
specified cardiovascular procedures from the following MS-DRGs, and to 
create new MS-DRGs to classify these procedures:
     MS-DRG 246 (Percutaneous Cardiovascular Procedure with 
Drug- Eluting Stent with MCC or 4+ Vessels/Stents);
     MS-DRG 247 (Percutaneous Cardiovascular Procedure with 
Drug-Eluting Stent without MCC);
     MS-DRG 248 (Percutaneous Cardiovascular Procedure with 
Non-Drug-Eluting Stent with MCC or 4+ Vessels/Stents);
     MS-DRG 249 (Percutaneous Cardiovascular Procedure with 
Non- Drug-Eluting Stent without MCC);
     MS-DRG 250 (Percutaneous Cardiovascular Procedure without 
Coronary Artery Stent with MCC); and
     MS-DRG 251 (Percutaneous Cardiovascular Procedure without 
Coronary Artery Stent without MCC).
    The requestor recommended that CMS assign the following ICD-9-CM 
procedure codes that identify and describe cardiac ablation procedures 
and the other percutaneous intracardiac procedures to the newly created 
MS-DRGs:
     35.52 (Repair of atrial septal defect with prosthesis, 
closed technique);
     35.96 (Percutaneous balloon valvuloplasty);
     35.97 (Percutaneous mitral valve repair with implant);
     37.26 (Catheter based invasive electrophysiologic 
testing);
     37.27 (Cardiac mapping);
     37.34 (Excision or destruction of other lesion or tissue 
of heart, endovascular approach);
     37.36 (Excision, destruction, or exclusion of left atrial 
appendage (LAA)); and
     37.90 (Insertion of left atrial appendage device).
    We stated we agreed that creating these new MS-DRGs would better 
reflect utilization of resources and clinical cohesiveness for 
intracardiac procedures in comparison to intracoronary procedures. 
Therefore, after consideration of the public comments we received, we 
finalized our proposal to create MS-DRGs 273 (Percutaneous Intracardiac 
Procedures with MCC) and MS-DRG 274 (Percutaneous Intracardiac 
Procedures without MCC) for the FY 2016 ICD-10 MS-DRGs Version 33 and 
finalized the assignment of the procedures performed within the heart 
chambers using intracardiac techniques to the two new MS-DRGs.
    In the FY 2016 rulemaking, we stated that the comparable ICD-10-PCS 
code translations for ICD-9-CM procedure code 37.27 (Cardiac mapping) 
were ICD-10-PCS codes 02K83ZZ (Map conduction mechanism, percutaneous 
approach) and 02K84ZZ (Map conduction mechanism, percutaneous 
endoscopic approach). However, code 02K80ZZ (Map Conduction Mechanism, 
Open Approach), which is also a comparable ICD-10-PCS code translation 
for ICD-9-CM procedure code 37.27, was inadvertently excluded. 
Consequently, procedure code 02K80ZZ continued to remain in the GROUPER 
logic for MS-DRGs 246, 247, 248, 249, 250 and 251.
    In the FY 2021 IPPS/LTCH PPS final rule (85 FR 58477), we finalized 
a revision to the titles for MS-DRGs 273 and 274 to ``Percutaneous and 
Other Intracardiac Procedures with and without MCC, respectively'' to 
better reflect the procedures assigned to them.
    As discussed in the FY 2023 IPPS/LTCH PPS proposed rule, in the 
ICD-10 MS-DRGs Definitions Manual Version 39.1, procedure code 02K80ZZ 
is currently recognized as a non-O.R. procedure that affects the MS-DRG 
to which it is assigned. We stated that our clinical advisors reviewed 
this grouping issue and stated that procedure code 02K80ZZ does not 
describe a percutaneous cardiovascular procedure. We stated that our 
clinical advisors supported the reassignment of code 02K80ZZ for 
clinical coherence, noting the procedure should be appropriately 
grouped along with other procedure codes that describe cardiac mapping 
currently assigned to MS-DRGs 273 and

[[Page 48844]]

274. Accordingly, because the procedure described by procedure code 
02K80ZZ is not clinically consistent with percutaneous cardiovascular 
procedures and it was initially assigned MS-DRGs 246, 247, 248, 249, 
250 and 251 as a result of replication in the transition from ICD-9 to 
ICD-10 based MS-DRGs, we proposed the reassignment of procedure code 
02K80ZZ from MS-DRGs 246, 247, 248, 249, 250 and 251 to MS-DRGs 273 and 
274 (Percutaneous and Other Intracardiac Procedures with and without 
MCC, respectively) in MDC 05 effective FY 2023.
    As discussed in section II.D.1.b of the preamble of the proposed 
rule, we noted that we were providing a test version of the ICD-10 MS-
DRG GROUPER Software, Version 40, so that the public could better 
analyze and understand the impact of the proposals included in the 
proposed rule. We noted that at the time of the development of the test 
software this issue was unable to be addressed and therefore, it did 
not reflect the proposed reassignment of procedure code 02K80ZZ from 
MS-DRGs 246, 247, 248, 249, 250 and 251 to MS-DRGs 273 and 274 
(Percutaneous and Other Intracardiac Procedures with and without MCC, 
respectively) in MDC 05 for Version 40.
    Comment: Commenters agreed with our proposal to reassign procedure 
code 02K80ZZ from MS-DRGs 246, 247, 248, 249, 250 and 251 to MS-DRGs 
273 and 274 (Percutaneous and Other Intracardiac Procedures with and 
without MCC, respectively). A few commenters stated that they 
appreciate CMS identifying a replication issue from the ICD-9 based MS-
DRGs to the ICD-10 based MS-DRGs and supported the reassignment of 
procedure code 02K80ZZ. A commenter agreed that cardiac mapping is 
generally performed during open-heart surgery or performed via cardiac 
catheterization to create detailed maps of electrical signals to 
identify the location of rhythm disorders.
    Response: We thank the commenters for their support.
    Comment: Other commenters opposed the proposal. Several commenters 
noted that CMS stated that code 02K80ZZ affects the MS-DRG to which it 
is assigned, however, based on their review of the MS-DRG logic, code 
02K80ZZ is designated as a non-O.R procedure and does not affect MS-DRG 
assignment. Other commenters expressed concern that data was not 
analyzed to see if code 02K80ZZ had been found in MS-DRGs 246, 247, 
248, 249, 250 and 251. A commenter stated that should it be determined 
that code 02K80ZZ had not been found in MS-DRGs 246, 247, 248, 249, 250 
and 251, then they agreed with removal of code 02K80ZZ from these MS-
DRGs and reassignment to MS-DRGs 273-274. However, should the analysis 
show code 02K80ZZ assigned to MS-DRGs 246, 247, 248, 249, 250 and 251, 
this commenter suggested CMS consider if the assignment of code 02K80ZZ 
to these MS-DRGs should be maintained, and if not, what ramifications 
the reassignment would have.
    A few commenters recommended that CMS consider assigning code 
02K80ZZ to MS-DRGs 228 and 229 (Other Cardiothoracic Procedures with 
and without MCC, respectively) instead. Some commenters stated that 
they believe that procedures to map conduction mechanism share similar 
clinical and resource consumption as the surgical ablation procedures 
performed via an open approach that are currently assigned to MS-DRGs 
228 and 229. These commenters further stated that given that 02K80ZZ 
(Map conduction mechanism, open approach) does not describe a 
percutaneous cardiovascular procedure, they did not recommend the 
assignment of the code to MS-DRGs 273 and 274. A commenter stated that 
based on their own analysis, 02K80ZZ is more often assigned to MS-DRGs 
228 and 229 than to MS-DRGs 273 and 274, and furthermore, the ICD-10-
PCS codes included in MS-DRGs 273 and 274 are ablation procedures via 
percutaneous approach. Another commenter asserted that the procedures 
in MS-DRGs 273 and 274 are all percutaneous approach procedures.
    Response: We thank the commenters for their feedback.
    We note that in the ICD-10 MS-DRGs Definitions Manual Version 39.1, 
procedure code 02K80ZZ is in fact recognized as a non-O.R. procedure 
affecting MS-DRGs 246, 247, 248, 249, 250 and 251, specifically. Under 
the IPPS MS-DRGs, each ICD-10-PCS procedure code has designations that 
determine whether and in what way the presence of that procedure on a 
claim impacts the MS-DRG assignment. First, each ICD-10-PCS procedure 
code is either designated as an O.R. procedure for purposes of MS-DRG 
assignment (``O.R. procedures'') or is not designated as an O.R. 
procedure for purposes of MS-DRG assignment (``non-O.R. procedures''). 
For each procedure that is designated as a non-O.R. procedure, that 
non-O.R. procedure is further classified as either affecting the MS-DRG 
assignment or not affecting the MS-DRG assignment. We refer to these 
designations that do affect MS-DRG assignment as ``non O.R. affecting 
the MS-DRG'' because these procedure codes describe procedures that 
would generally require a greater intensity of resources for facilities 
to manage the cases included in the definition (logic) of these MS-
DRGs. We refer readers to the ICD-10 MS-DRG Version 39.1 Definitions 
Manual at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software.html for 
detailed information regarding the designation of procedures as O.R. or 
non-O.R. (affecting the MS-DRG) in Appendix E--Operating Room 
Procedures and Procedure Code/MS-DRG Index. Procedures designated as 
``non O.R. affecting the MS-DRG'' are listed in Appendix E with an 
asterisk.
    In response to the comments expressing concern that data was not 
analyzed to determine if there were any cases reported with procedure 
code 02K80ZZ in MS-DRGs 246, 247, 248, 249, 250 and 251, we refer the 
reader to Table 6P.1e associated with this final rule and available via 
the internet at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS. This table displays the findings from our 
analysis of the claims data from the September 2021 update of the FY 
2021 MedPAR file to determine if there were any cases reported with 
procedure code 02K80ZZ assigned to MS-DRGs 246, 247, 248, 249, 250 and 
251 and reflects that there were no such cases found.
    With regard to the commenters' concerns that procedures to map 
conduction mechanism share similar clinical and resource consumption as 
surgical ablation procedures performed via an open approach, our 
clinical advisors note that while cardiac mapping can be used to 
identify and localize areas responsible for rhythm disturbances to 
serve as a target for surgical ablation, each of these procedures are 
defined by clinically distinct definitions and objectives, which is why 
there are separate and unique ICD-10-PCS procedure codes within the 
classification for reporting purposes. Our clinical advisors note that 
cardiac mapping describes the creation of detailed maps, generally 
involving the use of electrodes and a mapping system (consisting of 
amplifiers and a recording and analysis system), to detect how the 
electrical signals that control the timing of the heart rhythm move 
between each heartbeat to identify the location of rhythm disorders. 
Surgical ablation, however, describes the burning or freezing of tissue 
on the inside of the heart to disrupt faulty electrical signals causing 
the arrhythmia.

[[Page 48845]]

    We also note in response to the comments received that percutaneous 
ablation procedures are not the only procedures assigned to MS-DRGs 273 
and 274. Of note, left atrial appendage closure (LAAC) procedures, with 
and without an implant, are also assigned to MS-DRGs 273 and 274. In 
response to the commenters who did not agree with the proposal to 
reassign procedure code 02K80ZZ from MS-DRGs 246, 247, 248, 249, 250 
and 251 to MS-DRGs 273 and 274 based on the open approach of the 
procedure, as noted in the proposed rule, in the FY 2021 IPPS/LTCH PPS 
final rule (85 FR 58477), we finalized a revision to the titles for MS-
DRGs 273 and 274 to ``Percutaneous and Other Intracardiac Procedures 
with and without MCC, respectively'' to better reflect the procedures 
assigned, as not only percutaneous procedures are assigned to these MS-
DRGs. We refer the reader to the ICD-10 MS-DRG Definitions Manual, 
version 39.1, which is available via the internet on the CMS website 
at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software for complete 
documentation of the GROUPER logic for MS-DRGs 273 and 274.
    Our clinical advisors continue to note that code 02K80ZZ (Map 
Conduction Mechanism, Open Approach), which is a comparable ICD-10-PCS 
code translation for ICD-9-CM procedure code 37.27 (Cardiac mapping), 
was inadvertently excluded in FY 2016 rulemaking when we finalized our 
proposal to create MS-DRGs 273 and MS-DRG 274 to better reflect 
utilization of resources and clinical cohesiveness for intracardiac 
procedures in comparison to intracoronary procedures. Our clinical 
advisors continue to support the reassignment of code 02K80ZZ for 
clinical coherence, noting the procedure should be appropriately 
grouped along with other procedure codes that describe cardiac mapping 
that are currently assigned to MS-DRGs 273 and 274.
    Therefore, after consideration of the public comments we received, 
and for the reasons discussed, we are finalizing our proposal to 
reassign procedure code 02K80ZZ from MS-DRGs 246, 247, 248, 249, 250 
and 251 to MS-DRGs 273 and 274 (Percutaneous and Other Intracardiac 
Procedures with and without MCC, respectively) in MDC 05 for Version 
40, without modification.
d. Surgical Ablation
    In the FY 2022 IPPS/LTCH PPS final rule (86 FR 44836 through 
44848), we discussed a two-part request we received to review the MS-
DRG assignments for cases involving the surgical ablation procedure for 
atrial fibrillation. The first part of the request was to create a new 
classification of surgical ablation MS-DRGs to better accommodate the 
costs of open concomitant surgical ablations. The requestor identified 
the following potential procedure combinations that would comprise an 
``open concomitant surgical ablation'' procedure.

 Open CABG + open surgical ablation
 Open MVR + open surgical ablation
 Open AVR + open surgical ablation
 Open MVR + open AVR + open surgical ablation
 Open MVR + open CABG + open surgical ablation
 Open MVR + open AVR + open CABG + open surgical ablation
 Open AVR + open CABG + open surgical ablation

    As discussed in the FY 2022 IPPS/LTCH PPS final rule, we examined 
claims data from the March 2020 update of the FY 2019 MedPAR file and 
the September 2020 update of the FY 2020 MedPAR file for cases 
reporting procedure code combinations describing open concomitant 
surgical ablations. We refer the reader to Table 6P.1o associated with 
the FY 2022 final rule (which is available via the internet on the CMS 
website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS) for data analysis findings of cases 
reporting procedure code combinations describing open concomitant 
surgical ablations. We stated our analysis showed while the average 
lengths of stay and average costs of cases reporting procedure code 
combinations describing open concomitant surgical ablations are higher 
than all cases in their respective MS-DRG, we found variation in the 
volume, length of stay, and average costs of the cases. We also stated 
findings from our analysis indicated that MS-DRGs 216, 217, and 218 
(Cardiac Valve and Other Major Cardiothoracic Procedures with Cardiac 
Catheterization with MCC, with CC, and without CC/MCC, respectively) as 
well as approximately 31 other MS-DRGs would be subject to change based 
on the three-way severity level split criterion finalized in FY 2021. 
We refer the reader to section II.D.1.b. of the FY 2022 IPPS/LTCH PPS 
final rule (86 FR 44796 through 44798), for related discussion 
regarding our finalization of the proposal to delay application of the 
NonCC subgroup criteria to existing MS-DRGs with three-way severity 
level split to maintain more stability in the current MS-DRG structure.
    In the FY 2022 final rule, we finalized our proposal to revise the 
surgical hierarchy for the MS-DRGs in MDC 05 (Diseases and Disorders of 
the Circulatory System) to sequence MS-DRGs 231-236 (Coronary Bypass) 
above MS-DRGs 228 and 229 (Other Cardiothoracic Procedures with and 
without MCC, respectively), effective October 1, 2021. In addition, we 
also finalized the assignment of cases with a procedure code describing 
coronary bypass and a procedure code describing open ablation to MS-
DRGs 233 and 234 and changed the titles of these MS-DRGs to ``Coronary 
Bypass with Cardiac Catheterization or Open Ablation with and without 
MCC, respectively'' to reflect this reassignment for FY 2022.
    In response to this final policy, as discussed in the FY 2023 IPPS/
LTCH PPS proposed rule (87 FR 28163), we received a request to again 
review the MS-DRG assignment of cases involving open concomitant 
surgical ablation procedures. The requestor stated they continue to 
believe that the average hospital costs for surgical ablation for 
atrial fibrillation demonstrates a cost disparity compared to all 
procedures within their respective MS-DRGs. The requestor suggested 
that when open surgical ablation is performed with MVR, or AVR or MVR/
AVR + CABG that these procedures are either (1) assigned to a different 
family of MS-DRGs or (2) assigned to MS-DRGs 216 and 217 (Cardiac Valve 
and Other Major Cardiothoracic Procedures with Cardiac Catheterization 
with MCC and with CC, respectively) similar to what CMS did with CABG 
and open ablation procedures in the FY 2022 rulemaking to better 
accommodate the added cost of open concomitant surgical ablation.
    In the proposed rule we stated the change to the surgical hierarchy 
in MDC 05 and the assignment of cases with a procedure code describing 
coronary bypass and a procedure code describing open ablation to MS-
DRGs 233 and 234 is recent, only becoming effective October 1, 2021. We 
stated that we believed more time was needed before considering to 
again review the MS-DRG assignment of cases reporting procedure code 
combinations describing open concomitant surgical ablations as the data 
from the September 2021 update of the FY 2021 MedPAR file does not 
reflect our FY 2022 finalization. In addition, our clinical advisors 
continued to state that in open concomitant surgical ablation 
procedures, the CABG, MVR, and AVR components of the procedure are more 
technically complex than the open surgical ablation procedure. They 
also stated that the finalized revision to the

[[Page 48846]]

surgical hierarchy leads to a grouping that is more coherent and better 
accounts for the resources expended to address the more complex 
procedures from other cases redistributed during the hierarchy change. 
As noted, we stated that we believed that additional time was needed to 
allow for further analysis of the claims data to reflect our FY 2022 
finalization, and also to determine to what extent the patient's co-
morbid conditions are also contributing to costs and to identify other 
contributing factors that might exist with respect to the increased 
length of stay and costs of this subset of cases in these MS-DRGs, as 
discussed in the FY 2022 IPPS/LTCH PPS final rule.
    Comment: Commenters expressed support of CMS' decision to allow 
additional time for the claims data to reflect our FY 2022 finalization 
before further analysis. Commenters stated that the finalized changes 
to surgical hierarchy for cardiac procedures were positive and will 
improve patient access. Other commenters stated that the finalized 
changes to the MS-DRG assignment of cases with a procedure code 
describing coronary bypass and a procedure code describing open 
ablation were timely.
    Response: We thank the commenters for their support.
    Comment: Some commenters opposed CMS' decision and suggested that 
Medicare cover both aortic valve replacement surgery and surgical 
treatment for atrial fibrillation.
    Response: We note that the Definitions Manual display of the 
GROUPER logic assignment for each procedure code is not an indication 
of whether or not a particular procedure is covered for payment 
purposes. The MS-DRG logic must specifically require a condition to 
group based on whether it is reported as a principal diagnosis or a 
secondary diagnosis, and consider any procedures that are reported, in 
addition to consideration of the patient's age, sex and discharge 
status in order to affect the MS-DRG assignment. In other words, cases 
will group according to the GROUPER logic, regardless of any coding 
guidelines or coverage policies. It is the Medicare Code Editor (MCE) 
and other payer-specific edits that identify inconsistencies in the 
coding guidelines or coverage policies. These data integrity edits 
address issues such as data validity, coding rules, and coverage 
policies. Since the inception of the IPPS, the data editing function 
has been a separate and independent step in the process of determining 
a DRG assignment. The separation of the MS-DRG grouping and data 
editing functions allows the MS-DRG GROUPER to remain stable even 
though coding rules and coverage policies may change during the fiscal 
year.
    Comment: Other commenters opposed CMS' decision and stated CMS 
needs to finish the work that was started and improve hospital payment 
for valvular procedures with surgical ablation for atrial fibrillation. 
These commenters stated that the finalization of the revision to the 
surgical hierarchy for the MS-DRGs in MDC 05 and the finalization of 
the assignment of cases with a procedure code describing coronary 
bypass and a procedure code describing open ablation to MS-DRGs 233 and 
234 in FY 2022 rulemaking does not address the increased costs of cases 
describing open concomitant surgical ablation performed with open valve 
procedures that are assigned to MS-DRGs 216 through 221. A few 
commenters asserted that hospitals are forced to lose money on these 
lifesaving treatments because CMS has not addressed this underpayment. 
Other commenters stated that CMS did not provide transparent data 
analysis of cases describing open surgical ablation for atrial 
fibrillation performed during open valve procedures so the provider 
community could appropriately evaluate.
    Commenters stated that treating atrial fibrillation during the same 
surgical session as an open valve procedure requires significant device 
costs, additional operating room time, and specialized staff. A 
commenter stated that even if the surgical ablation procedure is less 
technically complex than CABG, MVR, and/or AVR, hospitals still bear 
significant costs for furnishing the ablation procedure when the 
additional costs of the innovative device technologies (such as 
radiofrequency ablation clamps, cryoablation probes, and left atrial 
appendage management devices) that are used during the procedure are 
considered. Commenters expressed concern that given the added costs of 
performing as many as three procedures at the same time, hospitals may 
more likely schedule the patient for separate procedures even though 
guidelines of the Society for Thoracic Surgeons and the Heart Rhythm 
Society recommend performing surgical ablation for atrial fibrillation 
at the time of open-heart procedures when indicated. These commenters 
further stated they believed it did not seem financially prudent to 
compel patients to undergo multiple procedures, potentially costing 
more in the long run, when their atrial fibrillation could be treated 
during the same open-heart operation. Many commenters urged CMS to 
either (1) assign the cases to a different family of MS-DRGs or (2) 
assign these cases to MS-DRGs 216 and 217 (Cardiac Valve and Other 
Major Cardiothoracic Procedures with Cardiac Catheterization with MCC 
and with CC, respectively) as originally requested.
    Another commenter stated they respected the position of CMS' 
clinical advisors given the complexity of the involved procedures and 
noted that the issue of multiple procedures or interventions performed 
during a single hospital stay is also a problem in other areas of 
cardiology and warrants a meaningful solution. This commenter stated 
they believed that since performing procedures concomitantly is more 
efficient, more convenient, provides a better prognosis for the patient 
and could be more cost effective than the procedures being performed in 
different hospital stays, there should be a mechanism for 
differentiated payment when procedures are performed concomitantly, 
when it is best for the patient. This commenter recommended that CMS 
create a supplemental payment mechanism that could be modeled based on 
the respective costs of the individual procedures determined by claims 
data and then adjusted for efficiencies of a single operative session 
to facilitate incremental payment when two major procedures are 
performed during the same hospital admission and urged CMS to solicit 
further comment on possible methodological solutions to accommodate 
costs when two procedures are performed concomitantly.
    Response: We appreciate the commenters' feedback.
    We refer readers to Tables 6P.1c and 6P1.d associated with this 
final rule (which are available via the internet on the CMS website at: 
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS) for the data analysis of cases reporting procedure 
code combinations describing open concomitant surgical ablations in the 
September 2021 update of the FY 2021 MedPAR file. Table 6P.1c 
associated with this final rule sets forth the list of ICD-10-PCS 
procedure codes reflecting mitral valve repair or replacement (MVR), 
aortic valve repair or replacement (AVR), and coronary artery bypass 
grafting (CABG) procedures that we examined in this analysis. Table 
6P.1d associated with this final rule shows the data analysis findings 
of cases reporting procedure code combinations describing open 
concomitant surgical ablations assigned to MS-DRGs 216, 217, 218, 219, 
220 and

[[Page 48847]]

221 from the September 2021 update of the FY 2021 MedPAR file.
    As shown in Table 6P.1d associated with this final rule, while the 
average lengths of stay and average costs of cases reporting procedure 
code combinations describing open concomitant surgical ablations are 
higher than all cases in their respective MS-DRG, we found there is 
variation in the volume, length of stay, and average costs of the 
cases. For MS-DRG 216, we found 870 cases reporting procedure code 
combinations describing open concomitant surgical ablations with the 
average length of stay ranging from 16.8 days to 20.5 days and average 
costs ranging from $90,122 to $156,617 for these cases. For MS-DRG 217, 
we found 168 cases reporting procedure code combinations describing 
open concomitant surgical ablations with the average length of stay 
ranging from 7.5 days to 12 days and average costs ranging from $48,644 
to $74,594 for these cases. For MS-DRG 218, we found zero cases 
reporting procedure code combinations describing open concomitant 
surgical ablations. For MS-DRG 219, we found 1,940 cases reporting 
procedure code combinations describing open concomitant surgical 
ablations with the average length of stay ranging from 11.2 days to 
13.4 days and average costs ranging from $70,816 to $86,805 for these 
cases. For MS-DRG 220, we found 1,338 cases reporting procedure code 
combinations describing open concomitant surgical ablations with the 
average length of stay ranging from 7.1 days to 8.8 days and average 
costs ranging from $49,326 to $65,611 for these cases. For MS-DRG 221, 
we found 60 cases reporting procedure code combinations describing open 
concomitant surgical ablations with the average length of stay ranging 
from 5.6 days to 6.3 days and average costs ranging from $44,247 to 
$47,418 for these cases.
    As noted, and similar to our analysis of the data for the FY 2022 
IPPS/LTCH PPS rulemaking, the data analysis shows that while the 
average lengths of stay and average costs of cases reporting procedure 
code combinations describing open concomitant surgical ablations are 
higher than all cases in their respective MS-DRG, there is variation in 
the volume, length of stay, and average costs of the cases. As we 
discuss later in this section, the analysis also shows that the cases 
reporting an open concomitant surgical ablation code combination are 
predominately found in the higher (CC or MCC) severity level MS-DRGs of 
their current base MS-DRG assignment. Moreover, as also previously 
noted, the data from the September 2021 update of the FY 2021 MedPAR 
file does not reflect our FY 2022 finalization. We continue to believe 
that additional time is needed to allow for further analysis of the 
claims data to reflect our FY 2022 finalization, and also to determine 
to what extent the patient's co-morbid conditions or other factors may 
be contributing to the increased length of stay and costs of this 
subset of cases, as discussed previously.
    In response to comments that urged CMS to assign cases reporting 
procedure code combinations describing open concomitant surgical 
ablations currently assigned to MS-DRGs 216, 217, 218, 219, 220 and 221 
to MS-DRGs 216 and 217 only, MS-DRGs 216, 217 and 218 are defined by 
the performance of cardiac catheterization. The performance of a 
cardiac catherization procedure could be also contributing to the 
increased average costs of cases reporting procedure code combinations 
describing open concomitant surgical ablations currently assigned to 
MS-DRGs 216, 217 and 218. Our clinical advisors have expressed concern 
about the effect on clinical coherence of assigning cases reporting 
procedure code combinations describing open concomitant surgical 
ablations that do not also have a cardiac catherization procedure 
reported to MS-DRGs that are defined by the performance of that 
procedure.
    We also note, as discussed in Section D.1.b of the proposed rule 
and this final rule, using the September 2021 update of the FY 2021 
MedPAR file, we analyzed how applying the NonCC subgroup criteria to 
all MS-DRGs currently split into three severity levels would affect the 
MS-DRG structure beginning in FY 2022. Similar to our findings 
discussed in the FY 2022 IPPS/LTCH final rule, findings from our 
analysis using the September 2021 update of the FY 2021 MedPAR file 
indicated that MS-DRGs 216, 217, 218 as well as approximately 40 other 
MS-DRGs would be subject to change based on the three-way severity 
level split criterion finalized in FY 2021. While we are finalizing the 
delay of the application of the NonCC subgroup criteria to existing MS-
DRGs with a three-way severity level split until FY 2024 or later, and 
to maintain the current structure of the 41 MS-DRGs that currently have 
a three-way severity level split (total of 123 MS-DRGs) that would 
otherwise be subject to these criteria, we note that the total number 
of cases in MS-DRG 218 is again below 500, and that we may consider 
consolidating these MS-DRGs into two severity levels based on the 
application of the NonCC subgroup criteria in future rule-making. We 
refer the reader to Table 6P.1b associated with the proposed rule and 
this final rule (which is available via the internet on the CMS website 
at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS) for the list of the 123 MS-DRGs that would be 
subject to deletion and the list of the 75 new MS-DRGs that would have 
been proposed for creation under this policy if the NonCC subgroup 
criteria were applied.
    In response to comments that the finalized revision to the surgical 
hierarchy did not adequately address the increased costs of cases 
associated with open concomitant surgical ablation and that urged CMS 
to create new MS-DRGs for these open concomitant procedures as 
originally requested, our clinical advisors continue to believe 
additional time is needed to review the clinical nature of cases 
reporting an open concomitant surgical ablation code combination before 
exploring a proposal to create new MS-DRGs for this subset of cases 
currently assigned to MS-DRGs 216 through 221 given the complexity of 
these code combinations and the corresponding data. Our analysis using 
the September 2021 update of the FY 2021 MedPAR file reflects that the 
cases reporting an open concomitant surgical ablation code combination 
are predominately found in the higher (CC or MCC) severity level MS-
DRGs of their current base MS-DRG assignment, suggesting that the 
patient's co-morbid conditions may also be contributing to higher costs 
of these cases. Secondly, for the numerous procedure combinations that 
would comprise an ``open concomitant surgical ablation'' procedure, the 
increase in average costs appears to directly correlate with the number 
of procedures performed. For example, cases that describe ``Open MVR + 
open surgical ablation'' generally demonstrate costs that are lower 
than cases that describe ``Open MVR + open AVR + open CABG + open 
surgical ablation.'' Therefore, our clinical advisors continue to 
believe that additional time is needed to allow for further analysis of 
the claims data to determine to what extent the patient's co-morbid 
conditions are also contributing to higher costs and to identify other 
contributing factors that might exist with respect to the increased 
length of stay and costs of these cases in these MS-DRGs. Our clinical 
advisors continue to believe that future data findings may demonstrate 
additional variance in resource utilization for this patient 
population.
    With respect to commenters' concerns regarding a mechanism for

[[Page 48848]]

differentiated payment when procedures are performed concomitantly, we 
agree that the performance of concomitant procedures is an area that 
warrants more analysis across the MS-DRG classification, as the 
performance of ``concomitant procedures'' may affect the consumption of 
resources in other clinical scenarios as well, especially when the use 
of devices is involved. As discussed in prior rulemaking, the MS-DRGs 
are a classification system intended to group together diagnoses and 
procedures with similar clinical characteristics and utilization of 
resources. It has been difficult to identify other MS-DRGs that would 
be more appropriate MS-DRG assignments for these concomitant procedures 
based on the variance in the clinical characteristics and utilization 
of resources for concomitant procedures, which can depend on the number 
of procedures being performed concomitantly and the nature of these 
procedures. We are interested in receiving feedback on possible 
mechanisms through which we can address concomitant procedures. We are 
also interested in receiving feedback on how CMS can mitigate any 
unintended negative payment impacts to providers providing concomitant 
procedures. Commenters can continue to submit their recommendations via 
the new electronic intake system, Medicare Electronic Application 
Request Information SystemTM (MEARISTM) at: 
https://mearis.cms.gov/public/home. We will consider these public 
comments for possible proposals in future rulemaking as part of our 
annual review process.
    Comment: Some commenters noted that cases describing standalone 
hybrid percutaneous endoscopic surgical ablation are assigned MS-DRGs 
228 and 229 (Other Cardiothoracic Procedures with and without MCC, 
respectively) and noted that payment for MS-DRGs 228 and 229 has been 
trending downward over the last six years. These commenters stated that 
the downward payment trend for MS-DRGs 228 and 229 has resulted in 
hospitals being undercompensated for the costs of furnishing standalone 
hybrid percutaneous endoscopic surgical ablation procedures for atrial 
fibrillation. Other commenters stated that CMS did not provide 
transparency to the details of its analysis to support why standalone 
hybrid surgical ablation procedures should not be moved from MS-DRGs 
228 and 229.
    Some commenters stated that the decline in payment for standalone 
hybrid percutaneous endoscopic surgical ablation procedures makes it 
impossible for their facilities to continue to provide these needed 
procedures to patients suffering from atrial fibrillation. A commenter 
stated the proposed relative weight does not accurately reflect the 
costs of these device intensive procedures and that there has been no 
transparency into the cause for these significant declines. Another 
commenter stated that their facility has been especially impacted by 
COVID-19 and stated that for CMS to expect facilities to be able to 
continue to provide patients with needed medical services such as 
hybrid percutaneous endoscopic surgical ablation at such a steep 
decrease in payment is intolerable for hospitals. Other commenters 
asserted that hospitals will be forced to postpone or ``trim back'' on 
providing patients access to more complex, resource intensive 
procedures such as these, to better align their costs with what they 
asserted were Medicare's inadequate payment levels. These commenters 
proposed two possible remedies to this underpayment, that CMS either 
(1) use its statutory authority to not reduce the relative weight and 
payment for MS-DRGs 228 and 229, or (2) assign cases reporting 
procedure codes describing standalone percutaneous endoscopic surgical 
ablation from MS-DRGs 228 and 229 to the higher (MCC) severity level 
MS-DRG of its current base MS-DRG assignment, which is MS-DRG 228 
(Other Cardiothoracic Procedures with MCC), to prevent underpayment for 
these procedures and avoid disruptions in beneficiary access.
    Response: We appreciate the commenters' feedback. We note that we 
did not receive a specific request to change the MS-DRG assignment for 
standalone percutaneous endoscopic surgical ablation procedures for 
consideration for the FY 2023 IPPS/LTCH PPS proposed rule. We note a 
request to reassign cases describing standalone percutaneous endoscopic 
surgical ablation from MS-DRGs 228 and 229 (Other Cardiothoracic 
Procedures with and without MCC, respectively) to higher weighted MS-
DRGs 219 and 220 (Cardiac Valve and Other Major Cardiothoracic 
Procedures without Cardiac Catheterization with MCC and with CC, 
respectively) was discussed in the FY 2022 IPPS/LTCH PPS proposed rule. 
In the FY 2022 IPPS/LTCH final rule, in response to comments received 
on the proposed rule, we also discussed the assignment of cases 
reporting procedure codes describing standalone percutaneous endoscopic 
surgical ablation from MS-DRGs 228 and 229 to the higher (MCC) severity 
level MS-DRG of its current base MS-DRG assignment in the FY 2022 IPPS/
LTCH PPS final rule. We refer readers to the FY 2022 IPPS/LTCH PPS 
final rule (86 FR 44844 through 44848) for a complete discussion.
    In the request to again review the MS-DRG assignment of surgical 
ablation procedures in FY 2023 rulemaking, however, the requestor 
stated in their submission that while surgical ablation represents 
losses across all procedure types, they recommended focusing on 
addressing open concomitant surgical ablation in FY 2023 rulemaking and 
did not request a change to the MS-DRG assignment for standalone 
percutaneous endoscopic surgical ablation. Therefore, cases describing 
standalone percutaneous endoscopic surgical ablation were not 
considered in the FY 2023 IPPS/LTCH PPS proposed rule.
    In response to the comment that hospitals may postpone or ``trim 
back'' on providing patients access to these procedures in order to 
better align their costs with Medicare payment levels, as we have 
stated in prior rulemaking, it is not appropriate for facilities to 
deny treatment to beneficiaries needing a specific type of therapy or 
treatment that potentially involves increased costs.
    We acknowledge the reduction in the proposed FY 2023 relative 
weights for MS-DRGs 228 and 229 (approximately 7% and 4%, respectively 
from the FY 2022 relative weight), however, we note we did not propose 
a change to the GROUPER logic of MS-DRGs 228 and 229 for FY 2023. 
However, there have been previous changes to the structure of MS-DRGs 
228 and 229 over the past six years. It is to be expected that when MS-
DRGs are restructured, such as when procedure codes are reassigned or 
the hierarchy within an MDC is revised, resulting in a different case-
mix within the MS-DRGs, the relative weights of the MS-DRGs will change 
as a result. We believe the trending reduction in relative weights for 
MS-DRGs 228 and 229 over time to be appropriately driven by the 
underlying data in the six years since CMS began using the ICD-10 data 
in calculating the relative weights and is reflective of the change in 
case-mix within these MS-DRGs. Specifically, in the FY 2017 IPPS/LTCH 
PPS final rule (81 FR 56809 through 56813), we finalized our proposal 
to collapse MS-DRGs 228, 229, and 230 from three severity levels to two 
severity levels by deleting MS-DRG 230 and revised the structure of MS- 
DRG 229. We also finalized our proposal to reassign ICD-9-CM procedure 
code 35.97 and the cases reporting ICD-10-PCS procedure

[[Page 48849]]

code 02UG3JZ (Supplement mitral valve with synthetic substitute, 
percutaneous approach) from MS-DRGs 273 and 274 to MS-DRG 228 and 
revised the titles of MS-DRG 228 and 229. In the FY 2020 IPPS/LTCH PPS 
final rule (84 FR 42080 through 56813) we finalized our proposal to 
modify the structure of MS-DRGs 266 and 267 by reassigning ICD-10-PCS 
procedure code 02UG3JZ describing a transcatheter mitral valve repair 
with implant procedure from MS-DRGs 228 and 229 to MS-DRGs 266 and 267 
and revised the titles of MS-DRGs 266 and 267. Finally, as discussed in 
the FY 2022 IPPS/LTCH PPS final rule, and earlier in this section, we 
finalized a revision to the surgical hierarchy for the MS-DRGs in MDC 
05 to sequence MS-DRGs 231-236 (Coronary Bypass) above MS-DRGs 228 and 
229 for FY 2022. Therefore, the data appear to reflect that the 
difference in the relative weights shown in Table 5-List of Medicare 
Severity Diagnosis Related Groups (MS-DRGs), Relative Weighting 
Factors, and Geometric and Arithmetic Mean Length of Stay associated 
with final rule for the applicable fiscal year can be attributed to the 
fact that these previously finalized policies resulted in a different 
case-mix within the MS-DRGs, which is then being reflected in the 
relative weights. We refer the reader to section II.E. of the preamble 
of this FY 2023 IPPS/LTCH PPS final rule for a complete discussion of 
the relative weight calculations for FY 2023, including our finalized 
policies to use 50 percent of the relative weights calculated using all 
cases in the FY 2021 MedPAR data and 50 percent of the relative weights 
calculated without COVID-19 cases in the FY 2021 MedPAR data to 
calculate the relative weights for FY 2023, and to apply a permanent 
10-percent cap on the reduction in a MS-DRG's relative weight in a 
given fiscal year, beginning in FY 2023.
    We appreciate the commenters' support and feedback, and intend to 
continue to consider these issues. For the reasons summarized earlier, 
and after consideration of the public comments we received, we are not 
making any MS-DRG changes for cases involving the open concomitant 
surgical ablation procedures or for cases describing standalone 
percutaneous endoscopic surgical ablation for FY 2023.
7. MDC 06 (Diseases and Disorders of the Digestive System): 
Appendicitis
    In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28163 through 
28165), we discussed a request we received to reconsider the MS-DRG 
assignment for diagnosis code K35.20 (Acute appendicitis with 
generalized peritonitis, without abscess). According to the requestor, 
when this code is reported in combination with any one of the 
corresponding procedure codes that describe an appendectomy, the case 
is grouping to MS-DRGs 341, 342, and 343 (Appendectomy without 
Complicated Principal Diagnosis with MCC, with CC, and without CC/MCC, 
respectively). Alternatively, the requestor stated that when diagnosis 
code K35.32 (Acute appendicitis with perforation and localized 
peritonitis, without abscess) is reported in combination with any one 
of the corresponding procedure codes that describe an appendectomy, the 
case is grouping to MS-DRGs 338, 339, and 340 (Appendectomy with 
Complicated Principal Diagnosis with MCC, with CC, and without CC/MCC, 
respectively).
    The requestor asserted that the difference in MS-DRG assignment 
suggests that localized peritonitis is more severe or requires an 
additional level of care over and above that for generalized 
peritonitis. The requestor stated that clinically, both localized and 
generalized peritonitis, when treated with an appendectomy require the 
same level of patient care, including extensive intraoperative 
irrigation at the surgical site, direct inspection or imaging of the 
abdomen to look for possible abscess, use of intravenous antibiotics, 
and prolonged inpatient monitoring. The requestor added that 
generalized peritonitis can be thought of as a progression of the 
localized peritonitis condition and that patients progress from 
localized to generalized peritonitis and not vice versa.
    In the proposed rule we noted that this topic has been discussed 
previously in our FY 2019 (83 FR 41230) and FY 2021 rulemakings (85 FR 
32500 through 32503) and (85 FR 58484 through 58488). Effective FY 2019 
(October 1, 2018) diagnosis code K35.2 (Acute appendicitis with 
generalized peritonitis) was expanded to K35.20 (Acute appendicitis 
with generalized peritonitis, without abscess); and K35.21 (Acute 
appendicitis with generalized peritonitis, with abscess). In addition, 
code K35.3 (Acute appendicitis with localized peritonitis) was expanded 
to K35.30 (Acute appendicitis with localized peritonitis, without 
perforation or gangrene); K35.31 (Acute appendicitis with localized 
peritonitis and gangrene, without perforation); K35.32 (Acute 
appendicitis with perforation and localized peritonitis, without 
abscess); and K35.33 (Acute appendicitis with perforation and localized 
peritonitis, with abscess).
    We finalized the severity level designations for these new 
diagnosis codes in the FY 2019 IPPS/LTCH PPS final rule and stated our 
clinical advisors believed that the new diagnosis codes for acute 
appendicitis described as ``with abscess'' or ``with perforation'' were 
clinically qualified for the MCC severity level designation, while 
acute appendicitis ``without abscess'' or ``without perforation'' were 
clinically qualified for the CC severity level designation because 
cases with abscess or perforation would be expected to require more 
clinical resources and time to treat while those cases ``without 
abscess'' or ``without perforation'' are not as severe clinical 
conditions.
    As discussed in our FY 2021 rulemaking, we received the request to 
add K35.20 (Acute appendicitis with generalized peritonitis, without 
abscess) to the list of complicated principal diagnoses so that all 
ruptured/perforated appendicitis codes in MDC 06 group to MS-DRGs 338, 
339, and 340 (Appendectomy with Complicated Principal Diagnosis with 
MCC, with CC, and without CC/MCC, respectively) as K35.20 is the only 
ruptured appendicitis code not included in the list of complicated 
principal diagnosis codes. At that time, we noted that the inclusion 
term at subcategory K35.2 (Acute appendicitis with generalized 
peritonitis) is: ``Appendicitis (acute) with generalized (diffuse) 
peritonitis following rupture or perforation of the appendix''. The 
requestor stated that code K35.20 (Acute appendicitis with generalized 
peritonitis, without abscess) describes a generalized, more extensive 
form of peritonitis than code K35.32 (Acute appendicitis with 
perforation and localized peritonitis, without abscess). We noted that 
our clinical advisors agreed that the presence of an abscess would 
clinically determine whether a diagnosis of acute appendicitis would be 
considered a complicated principal diagnosis. As diagnosis code K35.20 
is described as ``without'' an abscess, our clinical advisors 
recommended that K35.20 not be added to the list of complicated 
principal diagnoses for MS-DRGS 338, 339, and 340. We also proposed to 
remove diagnosis code K35.32 (Acute appendicitis with perforation and 
localized peritonitis, without abscess) from the complicated principal 
diagnosis list.
    In response to that proposal, some commenters disagreed. A 
commenter stated that when ruptured appendicitis results in generalized 
peritonitis, resources are greater because the

[[Page 48850]]

infection is not walled off, not localized, and has spread to two or 
more compartments within the abdominal cavity. According to the 
commenter, clinical literature supports the statement that generalized 
peritonitis is a more morbid (severe) presentation than just 
perforation or localized abscess. After consideration of the comments 
received and for the reasons discussed in the FY 2021 final rule, we 
did not finalize our proposals in that final rule. We concurred that 
the expansion of diagnosis codes K35.2 and K35.3 to introduce 
additional clinical concepts effective October 1, 2018 significantly 
changed the scope and complexity of the diagnosis codes for this subset 
of patients. We also stated NCHS' staff acknowledged the clinical 
concerns based on the manner in which diagnosis codes K35.2 and K35.3 
were expanded and confirmed that they would consider further review of 
these newly expanded codes with respect to the clinical concepts.
    We communicated with the CDC/NCHS staff regarding this repeat 
request submitted for FY 2023 consideration. The CDC/NCHS staff 
included these codes describing appendicitis on the agenda and a 
proposal for further revisions was presented for discussion at the 
March 8-9, 2022 ICD-10 Coordination and Maintenance Committee meeting. 
Specifically, the CDC/NCHS staff proposed to expand current diagnosis 
codes K35.20 and K35.21, making them sub-subcategories and creating new 
diagnosis codes to identify and describe acute appendicitis with 
generalized peritonitis, with perforation and without perforation, and 
unspecified as to perforation, as shown in the following table.
[GRAPHIC] [TIFF OMITTED] TR10AU22.040

    We refer the reader to the CDC website at: https://www.cdc.gov/nchs/icd/icd10cm_maintenance.htm for additional detailed information 
regarding the proposal, including a recording of the discussion and the 
related meeting materials.
    We noted in the proposed rule that the deadline for submitting 
public comments on the diagnosis code proposals discussed at the March 
8-9, 2022 ICD-10 Coordination and Maintenance Committee meeting was May 
9, 2022 and according to the CDC/NCHS staff, the diagnosis code 
proposals are being considered for an October 1, 2023 implementation 
(FY 2024). We stated that any future proposed changes to the MS-DRGs 
for Appendectomy would be dependent on the diagnosis code revisions 
that are finalized by the CDC/NCHS. Since it is not clear what code 
changes may be finalized, including whether public comments expressed 
support for the proposed changes or provided alternative options for 
consideration, we stated in the proposed rule that we believe it is 
appropriate to delay any possible MS-DRG modifications for future 
rulemaking. Therefore, we did not propose a change to the MS-DRG 
assignment or the current structure for MS-DRGs 338, 339, 340, 341, 
342, and 343. Although we did not propose a change to the MS-DRG 
assignments for FY 2023, we made the findings from our data analysis 
available for the listed MS-DRGs and the associated diagnosis codes to 
help inform future comments. We referred the reader to Table 6P.4a 
associated with the proposed rule (which is available via the internet 
on the CMS website at: https://www.cms.gov/medicare/medicare-fee-for-
service-payment/acuteinpatientpps).
    Comment: Commenters agreed with our proposal to maintain the 
structure of MS-DRGs 338, 339, 340, 341, 342, and 343 including the MS-
DRG assignment for diagnosis code K35.20 to MS-DRGs 341, 342, and 343. 
However, a commenter opposed CMS's proposal and stated they agreed with 
the requestor that all diagnosis codes describing a ruptured or 
perforated appendix should group to MS-DRGs 338, 339, and 340. The 
commenter stated that the condition described by code K35.20 can be 
associated with the risk of postoperative abscess formation and 
extended length of hospital stay, thereby warranting classification as 
a complicated diagnosis. This commenter urged CMS to reassign code 
K35.20 from MS-DRGs 341, 342, and 343 to MS-DRGs 338, 339, and 340 for 
FY 2023.
    Response: We thank the commenters for their support and feedback. 
In response to the commenter who urged CMS to reassign diagnosis code 
K35.20 from MS-DRGs 341, 342, and 343 to MS-DRGs 338, 339, and 340 for 
FY 2023, we note that the CDC/NCHS staff are in the process of 
reviewing public comments related to the proposed revision to certain 
diagnosis codes describing acute appendicitis that was presented at the 
March 8-9, 2022 ICD-10 Coordination and Maintenance Committee meeting, 
as discussed in the proposed rule. Accordingly, we continue to believe 
it is appropriate to delay any potential MS-DRG modifications as we do 
not yet know what the finalized code updates, including any 
corresponding changes to the Index to Diseases and Injuries and Tabular 
List of Diseases, might be. We will continue to collaborate with the 
CDC/NCHS regarding this issue.
    After consideration of the public comments we received, we are 
maintaining the current structure of MS-DRGs 338, 339, 340, 341, 342, 
and 343 and the MS-DRG assignment of diagnosis code K35.20 for FY 2023.
8. MDC 07 (Diseases and Disorders of the Hepatobiliary System and 
Pancreas): Laparoscopic Cholecystectomy With Common Bile Duct 
Exploration
    In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28165), we stated 
that we received a request to review the MS-DRG assignment when 
procedure code 0FC94ZZ (Extirpation of matter from common bile duct, 
percutaneous endoscopic approach) that describes a common bile duct 
exploration with gallstone removal procedure using a laparoscopic 
approach, is reported with a laparoscopic cholecystectomy. The 
procedure codes describing a laparoscopic cholecystectomy are

[[Page 48851]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.041

    According to the requestor, when a laparoscopic cholecystectomy is 
reported with any one of the listed procedure codes with a common bile 
duct exploration and gallstone removal procedure that is performed 
laparoscopically and reported with procedure code 0FC94ZZ, the 
resulting assignment is MS-DRGs 417, 418 and 419 (Laparoscopic 
Cholecystectomy without C.D.E. with MCC, with CC, and without CC/MCC, 
respectively). This MS-DRG assignment does not recognize that a common 
bile duct exploration (C.D.E.) was performed. However, the requestor 
stated that when procedure code 0FC90ZZ (Extirpation of matter from 
common bile duct, open approach) that describes a common bile duct 
exploration with gallstone removal procedure using an open approach is 
reported with any one of the listed procedure codes describing a 
laparoscopic cholecystectomy, the resulting assignment is MS-DRGs 411, 
412, and 413 (Cholecystectomy with C.D.E. with MCC, with CC, and 
without CC/MCC, respectively). The requestor stated that this MS-DRG 
assignment appropriately recognizes that a common bile duct exploration 
was performed. The requestor questioned why only the common bile duct 
exploration with gallstone removal procedure performed using an open 
approach (code 0FC90ZZ) grouped appropriately when reported with the 
laparoscopic cholecystectomy.
    We stated in the proposed rule that we reviewed procedure code 
0FC94ZZ and found that it is currently designated as a non-O.R. 
procedure, therefore, the GROUPER logic does not recognize this 
procedure for purposes of MS-DRG assignment. We also noted that MS-DRGs 
411, 412, and 413 include cholecystectomy procedures performed by 
either an open or a percutaneous endoscopic (laparoscopic) approach. We 
referred the reader to the V39.1 ICD-10 MS-DRG Definitions Manual, 
which is available via the internet on the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software for complete 
documentation of the GROUPER logic for MS-DRGs 411, 412, 413, 417, 418 
and 419.
    As stated in the proposed rule, we analyzed claims data from the 
September 2021 update of the FY 2021 MedPAR file for all cases in MS-
DRGs 411, 412, 413, 417, 418, and 419. Because the logic for MS-DRGs 
411, 412, and 413 includes cholecystectomy procedures performed by 
either an open or percutaneous endoscopic (laparoscopic) approach, we 
also analyzed the cases reported with each approach separately. The 
findings from our analysis are shown in the following tables.
[GRAPHIC] [TIFF OMITTED] TR10AU22.042

[GRAPHIC] [TIFF OMITTED] TR10AU22.043


[[Page 48852]]


[GRAPHIC] [TIFF OMITTED] TR10AU22.044

    In MS-DRG 411, we found a total of 116 cases with an average length 
of stay of 8.5 days and average costs of $29,332. Of those 116 cases, 
there were 56 cases reporting an open cholecystectomy, with an average 
length of stay of 10.7 days and average costs of $36,135 and 60 cases 
reporting a laparoscopic cholecystectomy, with an average length of 
stay of 6.5 days and average costs of $22,982. The data show that the 
cases reporting an open cholecystectomy have a longer average length of 
stay (10.7 days versus 6.5 days) and higher average costs ($36,135 
versus $22,982) compared to the cases reporting a laparoscopic 
cholecystectomy. The data also show that the cases reporting an open 
cholecystectomy have a longer average length of stay (10.7 days versus 
8.5 days) and higher average costs ($36,135 versus $29,332) compared to 
all the cases in MS-DRG 411. Similar findings are demonstrated for MS-
DRGs 412 and 413, where the data show that the cases reporting an open 
cholecystectomy have a longer average length of stay and higher average 
costs compared to the cases reporting a laparoscopic cholecystectomy, 
and also, when compared to all the cases in their respective MS-DRGs.
    We then analyzed claims data from the September 2021 update of the 
FY 2021 MedPAR file for cases reporting procedure code 0FC94ZZ in MS-
DRGs 417, 418, and 419 to assess how often it was reported. The 
findings from our analysis are shown in the following table.
[GRAPHIC] [TIFF OMITTED] TR10AU22.045

    We found a total of 231 cases across MS-DRGs 417, 418, and 419 with 
an average length of stay of 4.6 days and average costs of $15,348 
reporting procedure code 0FC94ZZ. In our review of the cases reporting 
a laparoscopic cholecystectomy across MS-DRGs 411, 412, and 413, we 
found a total of 178 cases with an average length of stay of 5.3 days 
and average costs of $18,206.
    We also examined claims data from the September 2021 update of the 
FY 2021 MedPAR file for cases reporting procedure code 0FC94ZZ across 
all the MS-DRGs without another O.R. procedure reported, to assess the 
number of cases and in which MS-DRGs procedure code 0FC94ZZ was found. 
The findings from our analysis are shown in the following table.
[GRAPHIC] [TIFF OMITTED] TR10AU22.046


[[Page 48853]]


    The data analysis shows procedure code 0FC94ZZ was reported in a 
total of 32 cases across 7 MS-DRGs with an average length of stay of 
5.9 days and average costs of $16,087. While procedure code 0FC94ZZ is 
designated as non-O.R., we also analyzed the average length of stay and 
average costs of the cases found within each of the 7 MS-DRGs reporting 
procedure code 0FC94ZZ against all the cases in their respective MS-
DRGs, to determine if there was any indication that the performance of 
the procedure described by procedure code 0FC94ZZ may have had any 
impact. For instance, as shown in the table, for MS-DRG 438 we found 2 
cases reporting procedure code 0FC94ZZ with an average length of stay 
of 14 days and average costs of $26,092. In the September 2021 update 
of the FY 2021 MedPAR file, the total number of cases for MS-DRG 438 is 
10,240 with an average length of stay of 6.4 days and average costs of 
$13,341. The 2 cases reporting procedure code 0FC94ZZ have 
approximately twice the average length of stay (14 days versus 6.4 
days) and approximately twice the average costs ($26,092 versus 
$13,341) compared to all the cases for MS-DRG 438. In the absence of 
additional analysis, it is unknown if these differences can be 
attributed to other factors, such as the MCCs that were reported in 
these cases. Similar findings were found for MS-DRGs 441, 445, 446, and 
871. We noted in the proposed rule that we will consider if further 
detailed analysis may be warranted for these cases.
    As stated in the proposed rule, our clinical advisors agreed that 
procedure code 0FC94ZZ describes a common bile duct exploration 
procedure with removal of a gallstone and should be added to the logic 
for case assignment to MS-DRGs 411, 412, and 413 for clinical coherence 
with the other procedures that describe a common bile duct exploration. 
Therefore, for FY 2023, we proposed to redesignate procedure code 
0FC94ZZ from a non-O.R. procedure to an O.R. procedure and add it to 
the logic list for common bile duct exploration (CDE) in MS-DRGs 411, 
412, and 413 (Cholecystectomy with C.D.E. with MCC, with CC, and 
without CC/MCC, respectively) in MDC 07 to appropriately reflect when 
this procedure is performed and improve the clinical coherence of the 
patients assigned to these MS-DRGs.
    Comment: Commenters agreed with our proposal to redesignate 
procedure code 0FC94ZZ from a non-O.R. procedure to an O.R. procedure 
and to add it to the logic list for common bile duct exploration (CDE) 
procedures in MS-DRGs 411, 412, and 413.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to redesignate procedure code 0FC94ZZ from a 
non-O.R. procedure to an O.R. procedure and to add it to the logic list 
for common bile duct exploration (CDE) procedures in MS-DRGs 411, 412, 
and 413 for FY 2023.
    In addition, we noted in the proposed rule that MS-DRGs 414, 415, 
and 416 (Cholecystectomy Except by Laparoscope without C.D.E. with MCC, 
with CC and without CC/MCC, respectively) also reflect cholecystectomy 
procedures, however, the logic is specifically defined for open 
cholecystectomy procedures without a common bile duct exploration 
procedure performed. Since MS-DRGs 411, 412, and 413 reflect cases 
where an open or laparoscopic cholecystectomy is performed with a 
common bile duct exploration procedure, MS-DRGs 414, 415, and 416 
reflect cases where only an open cholecystectomy is performed without a 
common bile duct exploration procedure, and MS-DRGs 417, 418, and 419 
reflect cases where only a laparoscopic cholecystectomy is performed 
without a common bile duct exploration procedure, we stated we believe 
there may be an opportunity to further refine these MS-DRGs once 
additional analysis is performed for consideration in future 
rulemaking. For example, we indicated we could consider proposing to 
restructure these cholecystectomy MS-DRGs to reflect the following two 
concepts, if supported by the data, and relatedly, to determine if 
severity levels are also supported according to the existing criteria.
     Open Cholecystectomy with or without C.D.E.; and
     Laparoscopic Cholecystectomy with or without C.D.E.
    Comment: Commenters agreed that there may be an opportunity to 
further refine the MS-DRGs for cholecystectomy procedures and 
encouraged CMS to conduct further review and analysis of the procedure 
codes describing cholecystectomy with common bile duct exploration for 
consideration in future rulemaking.
    Response: We thank the commenters for their support and continue to 
solicit any additional feedback from the public on this and any 
alternative recommendations or options to further refine these MS-DRGs 
for future consideration. As discussed in section II.D.1.b. of the 
preamble of the proposed rule and this final rule, feedback and other 
suggestions should be directed to the new electronic intake system, 
Medicare Electronic Application Request Information SystemTM 
(MEARISTM) at: https://mearis.cms.gov/public/home, with any 
comments and suggestions for consideration for FY 2024 to be submitted 
by October 20, 2022.
9. MDC 10 (Diseases and Disorders of the Endocrine System): Eladocagene 
Exuparvovec Gene Therapy
    In the FY 2022 IPPS/LTCH PPS final rule (86 FR 44895), we finalized 
the redesignation of code XW0Q316 (Introduction of eladocagene 
exuparvovec into cranial cavity and brain, percutaneous approach, new 
technology group 6) from a Non-O.R. procedure to an O.R. procedure, 
assigned to MS-DRGs 628, 629, and 630 (Other Endocrine, Nutritional and 
Metabolic O.R. Procedures with MCC, with CC, and without CC/MCC, 
respectively) in MDC 10 (Endocrine, Nutritional and Metabolic Diseases 
and Disorders) and to MS-DRGs 987, 988, and 989 (Non-Extensive O.R. 
Procedure Unrelated to Principal Diagnosis with MCC, with CC and 
without MCC/CC, respectively). In the FY 2023 IPPS/LTCH PPS proposed 
rule (87 FR 28167 through 28168) we discussed a request we received to 
reconsider this assignment for FY 2023. According to the requestor, the 
clinical characteristics and costs of cases assigned to MS-DRGs 628 
through 630 are significantly different from those associated with the 
administration of eladocagene exuparvovec. The requestor performed its 
own analysis, using deep brain stimulation for epilepsy and selective 
dorsal rhizotomy for cerebral palsy as proxies, and stated that based 
on its findings for the initial cost analysis and clinical comparison, 
that MS-DRG 23 (Craniotomy with Major Device Implant or Acute Complex 
CNS Principal Diagnosis with MCC or Chemotherapy Implant or Epilepsy 
with Neurostimulator), MS-DRG 24 (Craniotomy with Major Device Implant 
or Acute Complex CNS Principal Diagnosis without MCC) and MS-DRGs 25, 
26, and 27 (Craniotomy and Endovascular Intracranial Procedures with 
MCC, with CC, and without CC/MCC, respectively) may be more 
appropriate. However, the requestor also stated that while the clinical 
aspects of eladocagene exuparvovec cases are similar to those of MS-
DRGs 23 through 27, the costs are much higher and neither MS-DRGs 628, 
629, 630 or MS-DRGs 23 through 27 are appropriate. Therefore, the 
requestor stated its belief

[[Page 48854]]

that assigning eladocagene exuparvovec cases to new MS-DRGs is 
warranted.
    Eladocagene exuparvovec is a gene therapy for the treatment of 
patients with aromatic L-amino acid decarboxylase (AADC) deficiency, a 
rare genetic and fatal condition identified with ICD-10-CM diagnosis 
code E70.81. Patients with AADC deficiency are generally observed to 
have onset of symptoms in the first year of life, most notably 
hypotonia (muscle weakness), followed by movement disorders, 
developmental delay and autonomic signs, such as hyperhidrosis (profuse 
sweating unrelated to heat or exercise). It is understood that the 
long-term implications of this disease are severe, resulting in severe 
deficits and limitations in life expectancy. Because the condition is 
primarily diagnosed in the pediatric population, we would not expect to 
find any meaningful volume of cases in the MedPAR data.
    As discussed in the proposed rule, we analyzed claims data from the 
September 2021 update of the FY 2021 MedPAR file for MS-DRGs 628, 629, 
and 630 for cases reporting procedure code XW0Q316 and did not find any 
cases. We then extended our analysis to all MS-DRGs and found 1 case 
reporting the administration of this therapy in MS-DRG 829 
(Myeloproliferative Disorders or Poorly Differentiated Neoplasms with 
Other Procedures with CC/MCC) with an average length of stay of 2 days 
and average costs of $1,544. As we have discussed elsewhere we 
generally prefer not to create a new MS-DRG unless it would include a 
substantial number of cases. However, as discussed in section 
II.D.19.b. of the preamble of the proposed rule and this final rule, we 
are seeking public comment on possible mechanisms through which we can 
address rare diseases and conditions that are represented by low 
volumes in our claims data. We believe this topic, relating to the 
administration of treatment to address the rare genetic and fatal 
condition of AADC deficiency, is appropriately aligned with and should 
be considered as part of that effort. Therefore, we stated in the 
proposed rule that we are maintaining the current structure for MS-DRGs 
628, 629, and 630 for FY 2023, but would continue to consider this 
request in connection with our evaluation of possible mechanisms to 
address rare diseases and conditions in the MS-DRG structure, as 
discussed later in this rule.
    Comment: Commenters agreed with our decision to maintain the 
current MS-DRG assignment for cases reporting the administration of 
eladocagene exuparvovec. Other commenters urged CMS to consider 
appropriate MS-DRG assignment and payment for gene therapy 
intracerebral infusion therapies. The commenters stated there is 
anticipated rapid development and potential for these therapies to help 
patients. The commenters also expressed appreciation for CMS' request 
for feedback on MS-DRG assignment for rare diseases and stated that 
gene therapy represents an area of significant innovation in treating 
these conditions. The commenters suggested that CMS carefully consider 
the MS-DRG assignment for procedures that involve an intracerebral 
infusion of gene therapy or stem cell products that are currently under 
development for several neurologic disorders including Parkinson's, 
which is very common, and aromatic L-amino acid decarboxylase 
deficiency, which is very rare. The commenters stated that 
intracerebral infusion therapies are unique procedures requiring vastly 
different hospital resources compared to more traditional neurosurgical 
procedures. According to the commenters, appropriate MS-DRG assignment 
or consideration for creating new MS-DRG categories will be essential 
to assuring access to these therapies.
    Response: We appreciate the commenters' support and feedback.
    Comment: A couple commenters disagreed with CMS's decision to 
maintain the current MS-DRG assignment for cases reporting the 
administration of eladocagene exuparvovec. The commenters requested 
that CMS consider creating a new MS-DRG for neurosurgical gene therapy. 
A commenter indicated that because eladocagene exuparvovec has not yet 
been approved by the FDA they are unable to appropriately identify 
cases in the claims data. This commenter stated that there are 
currently approximately 68 gene therapy trials for central nervous 
system disorders, therefore, the decision to create or not create a new 
MS-DRG may have broader implications.
    Response: We appreciate the commenters' feedback. As discussed in 
the proposed rule, our analysis of claims data, which identified only 
one case reporting the administration of this therapy, did not support 
a proposal to create a new MS-DRG. The MS-DRGs are a classification 
system intended to group together those diagnoses and procedures with 
similar clinical characteristics and utilization of resources. As 
discussed previously and in prior rulemaking, we generally prefer not 
to create a new MS-DRG unless it would include a substantial number of 
cases, as having large clinical cohesive groups within an MS-DRG 
provides greater stability for annual updates to the relative payment 
weights. We acknowledge the complexities related to classifying cases 
that are represented by low volumes in our claims data and believe that 
further review of this issue also aligns with our intent to consider 
how rare diseases or conditions may be classified under the IPPS.
    After consideration of the public comments we received, we are 
maintaining the current MS-DRG assignment for cases reporting the 
administration of eladocagene exuparvovec for FY 2023. We will continue 
to explore appropriate mechanisms to address therapies indicated for 
rare diseases. We also refer the reader to section II.D.19.a of the 
preamble of this final rule for a discussion of the feedback received 
in response to the comment solicitation on possible mechanisms to 
address rare diseases and conditions in the MS-DRG structure.
10. MDC 15 Newborns and Other Neonates With Conditions Originating in 
Perinatal Period: MS-DRG 795 Normal Newborn
    In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28168 through 
28170), we discussed a request we received to review the MS-DRG 
assignment of newborn encounters with diagnosis codes describing 
contact with and (suspected) exposure to COVID-19 when the condition is 
ruled out after clinical evaluation and negative workup. The requestor 
expressed concern that a newborn encounter coded with a principal 
diagnosis code from category Z38 (Liveborn infants according to place 
of birth and type of delivery), followed by codes Z05.1 (Observation 
and evaluation of newborn for suspected infectious condition ruled out) 
and Z20.822 (Contact with and (suspected) exposure to COVID-19) is 
assigned to MS-DRG 794 (Neonate with Other Significant Problems). The 
requestor stated that this assignment appears to be in error and that 
the assignment should instead be to MS-DRG 795 (Normal Newborn).
    In the proposed rule we stated that our analysis of this grouping 
issue confirmed that, when a principal diagnosis code from category Z38 
(Liveborn infants according to place of birth and type of delivery), 
followed by codes Z05.1 (Observation and evaluation of newborn for 
suspected infectious condition ruled out) and Z20.822 (Contact with and 
(suspected) exposure to COVID-19), the case is assigned to MS-DRG 794.

[[Page 48855]]

    We stated that as we examined the GROUPER logic that would 
determine an assignment of cases to MS-DRG 795, we noted the ``only 
secondary diagnosis'' list under MS-DRG 795 includes the following five 
ICD-10-CM diagnosis codes from ICD-10-CM category Z20. We refer the 
reader to the ICD-10 MS-DRG Version 39.1 Definitions Manual (which is 
available via the internet on the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software for complete documentation of the GROUPER 
logic for the MS-DRG 795.
[GRAPHIC] [TIFF OMITTED] TR10AU22.047

    As discussed in the proposed rule, in reviewing the ICD-10-CM 
diagnosis code classification and the GROUPER logic list, we noted that 
the 13 ICD-10-CM diagnosis codes, also from category Z20, listed in the 
following table were inadvertently omitted from the ``only secondary 
diagnosis'' list under MS-DRG 795.
[GRAPHIC] [TIFF OMITTED] TR10AU22.048

    We reviewed section I.C.21.c.1 of the 2022 ICD-10-CM Official 
Guidelines for Coding and Reporting which state ``category Z20 
indicates contact with, and suspected exposure to, communicable 
diseases. These codes are for patients who are suspected to have been 
exposed to a disease by close personal contact with an infected 
individual or are in an area where a disease is epidemic . . . Contact/
exposure codes may be used as a first-listed code to explain an 
encounter for testing, or, more commonly, as a secondary code to 
identify a potential risk.'' Per the Excludes1 note at category Z20, 
when applicable, diagnoses of current infectious or parasitic disease 
are coded instead of codes from category Z20.
    We stated in the proposed rule that our clinical advisors reviewed 
this issue and agreed that patients exposed to communicable diseases 
that are worked up or treated prophylactically or both, and for whom 
those conditions are later determined after study to not be present, 
are distinct from patients with identified signs or symptoms of a 
suspected problem or diagnosed with having that communicable disease. 
Our clinical advisors supported adding the 13 diagnosis codes listed 
previously to the logic of MS-DRG 795 for clinical consistency with the 
five other diagnosis codes describing contact with, and suspected 
exposure to, communicable diseases currently assigned to the ``only 
secondary diagnosis'' list under MS-DRG 795.
    After review of the coding guidelines and conventions, and 
discussion with our clinical advisors, we stated that we agreed with 
the requestor that in these circumstances, these encounters should not 
map to MS-DRG 794 (Neonate with Other Significant Problems) and should 
instead be assigned to MS-DRG 795 (Normal Newborn). Therefore, we 
proposed to add the 13 diagnosis codes listed previously that describe 
contact with and (suspected) exposure to communicable diseases to the 
``only secondary diagnosis'' list under MS-DRG 795 (Normal Newborn). 
Under this proposal, cases with a principal diagnosis described by an 
ICD-10-CM code from category Z38 (Liveborn infants according to place 
of birth and type of delivery), following by codes Z05.1 (Observation 
and evaluation of newborn for suspected infectious condition ruled out) 
and Z20.822 (Contact with and (suspected) exposure to COVID-19) will be 
assigned to MS-DRG 795.
    Comment: Commenters expressed support for CMS' proposal to add the 
13 diagnosis codes listed previously that describe contact with and 
(suspected) exposure to communicable diseases to the ``only secondary 
diagnosis'' list under MS-DRG 795 (Normal Newborn).
    Response: We appreciate the commenters' support.

[[Page 48856]]

    Comment: A few commenters opposed CMS's proposal and stated that 
newborns exposed to communicable diseases often require care and 
treatment well above that of a normal newborn in terms of requiring 
increased evaluation, monitoring, testing, and prophylactic treatment. 
Some commenters stated that these newborns are not ``normal newborns'' 
due to the specific exposures they have had. These commenters listed a 
number of communicable diseases as examples and indicated the specific 
interventions such as evaluations, screenings, assessments, extra 
monitoring, laboratory studies, prophylactic treatments and sometimes 
isolation that can be required to prevent disease or complications when 
contact or (suspected) exposure occurs. Another commenter noted that 
there is a substantial difference in the FY 2023 proposed relative 
weights between MS-DRG 795 and MSDRG 794 and stated that ``exposure 
only'' cases fall in between the two MS-DRGs in terms of resource 
utilization. This commenter stated that a review of the cases at their 
facility shows that cases assigned to MS-DRG 794 with only a diagnosis 
code describing contact with and (suspected) exposure to communicable 
diseases driving the MS-DRG assignment had longer lengths of stay and 
higher charges than cases assigned to MS-DRG 795, while having shorter 
lengths of stay and lower charges than other cases assigned to MS-DRG 
794 with diagnoses describing conditions other than contact with and 
(suspected) exposure driving the MS-DRG assignment. This commenter also 
stated that they believed that the five ICD-10-CM diagnosis codes from 
ICD-10-CM category Z20 currently listed in the ``only secondary 
diagnosis'' list under MS-DRG 795 are currently inappropriately 
included and requested that either the 13 codes for contact with and 
(suspected) exposure remain assigned to MS-DRG 794 and the five codes 
currently in MS-DRG 795 be reassigned to MS-DRG 794 or a new MS-DRG be 
created that would include newborns that fall into the ``exposure 
only'' category, with a relative weight that falls somewhere between 
the relative weights of MS-DRG 794 and 795 to accurately capture 
resource utilization.
    Response: We thank the commenters for their feedback. Our clinical 
advisors reviewed the commenters' concerns. While our clinical advisors 
agree that patients exposed to communicable diseases can require workup 
or prophylactic treatment, they continue to state these patients are 
distinct from patients with identified signs or symptoms of a suspected 
problem or diagnosed with having that communicable disease. Our 
clinical advisors noted that the subset of newborns with a principal or 
secondary diagnosis listed in the logic list for MS-DRG 794 (Neonate 
with Other Significant Problems) are clinically distinct and often 
represent a more severe set of patients. Accordingly, our clinical 
advisors continue to believe that the five other diagnosis codes 
describing contact with, and suspected exposure to, communicable 
diseases are appropriately assigned to the ``only secondary diagnosis'' 
list under MS-DRG 795, and also continue to support adding the 13 
diagnosis codes listed previously to the logic of MS-DRG 795 for 
clinical consistency. We appreciate the commenters' feedback suggesting 
further review of the newborn MS-DRGs and agree that these groupings 
warrant special consideration. As discussed in prior rulemaking, we 
generally do not adopt the same approach to refine the maternity and 
newborn MS-DRGs because of the extremely low volume of Medicare 
patients there are in these DRGs.
    After consideration of the public comments we received, and for the 
reasons discussed, we are finalizing our proposal to add the 13 
diagnosis codes listed previously that describe contact with and 
(suspected) exposure to communicable diseases to the ``only secondary 
diagnosis'' list under MS-DRG 795 (Normal Newborn), without 
modification, for FY 2023.
    In addition, as discussed in the proposed rule, as we examined the 
GROUPER logic that would determine an assignment of cases to MS-DRGs in 
MDC 15, we noted the logic for MS-DRG 790 (Extreme Immaturity or 
Respiratory Distress Syndrome Neonate) includes ICD-10-CM diagnosis 
codes that describe extremely low birth weight newborn, extreme 
immaturity of newborn and respiratory distress syndrome of newborn. We 
referred the reader to the ICD-10 MS-DRG Version 39.1 Definitions 
Manual (which is available via the internet on the CMS website at: 
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software) for complete 
documentation of the GROUPER logic for MS-DRG 790. We stated that 
during our review of the diagnosis codes assigned to these MS-DRGs, we 
identified three diagnosis codes that do not exist in the logic for MS-
DRG 790. The three diagnosis codes and their current MS-DRG assignments 
are listed in the following table.
[GRAPHIC] [TIFF OMITTED] TR10AU22.049

    We stated our clinical advisors reviewed this grouping issue and 
noted that while virtually every neonate under 1000 grams, which is the 
definition of extremely low birth weight (ELBW), will have a weight 
documented somewhere in the medical record, in the rare instance that 
it is not, if the diagnosis documented by the provider is ``ELBW'' the 
neonate would be in a higher risk category. Our clinical advisors also 
noted that whereas weight is measured with high precision, gestational 
age is more complicated. With the exception of in vitro fertilization, 
gestational age is an estimate. Our clinical advisors stated similar to 
documentation of ``ELBW'', if the diagnosis documented by the provider 
is ``extreme immaturity of newborn'' the neonate would be in a higher 
risk category. These diagnoses

[[Page 48857]]

describe conditions that require advanced care and resources similar to 
other conditions already assigned to the logic of MS-DRG 790 even in 
cases where the birth weight, or weeks of gestation, are unspecified.
    For clinical consistency, our clinical advisors supported the 
addition of these three diagnosis codes to the GROUPER logic list for 
MS-DRG 790. Therefore, we proposed to reassign ICD-10-CM diagnosis 
codes P07.00, P07.20 and P07.26 to MS-DRG 790, effective October 1, 
2022 for FY 2023.
    Comment: Commenters expressed support for CMS' proposal to reassign 
ICD-10-CM diagnosis codes P07.00, P07.20 and P07.26 to MS-DRG 790.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to reassign ICD-10-CM diagnosis codes P07.00, 
P07.20 and P07.26 to MS-DRG 790, without modification, effective 
October 1, 2022 for FY 2023.
11. Review of Procedure Codes in MS-DRGs 981 Through 983 and 987 
Through 989
    We annually conduct a review of procedures producing assignment to 
MS-DRGs 981 through 983 (Extensive O.R. Procedure Unrelated to 
Principal Diagnosis with MCC, with CC, and without CC/MCC, 
respectively) or MS-DRGs 987 through 989 (Non-Extensive O.R. Procedure 
Unrelated to Principal Diagnosis with MCC, with CC, and without CC/MCC, 
respectively) on the basis of volume, by procedure, to see if it would 
be appropriate to move cases reporting these procedure codes out of 
these MS-DRGs into one of the surgical MS-DRGs for the MDC into which 
the principal diagnosis falls. The data are arrayed in two ways for 
comparison purposes. We look at a frequency count of each major 
operative procedure code. We also compare procedures across MDCs by 
volume of procedure codes within each MDC. We use this information to 
determine which procedure codes and diagnosis codes to examine. We 
identify those procedures occurring in conjunction with certain 
principal diagnoses with sufficient frequency to justify adding them to 
one of the surgical MS-DRGs for the MDC in which the diagnosis falls. 
We also consider whether it would be more appropriate to move the 
principal diagnosis codes into the MDC to which the procedure is 
currently assigned.
    In addition to this internal review, we also consider requests that 
we receive to examine cases found to group to MS-DRGs 981 through 983 
or MS-DRGs 987 through 989 to determine if it would be appropriate to 
add procedure codes to one of the surgical MS-DRGs for the MDC into 
which the principal diagnosis falls or to move the principal diagnosis 
to the surgical MS-DRGs to which the procedure codes are assigned.
    Based on the results of our review of the claims data from the 
September 2021 update of the FY 2021 MedPAR file, as well as our review 
of the requests that we received to examine cases found to group to MS-
DRGs 981 through 983 or MS-DRGs 987 through 989, we proposed to move 
the cases reporting the procedures and/or principal diagnosis codes 
described in this section of this rule from MS-DRGs 981 through 983 or 
MS-DRGs 987 through 989 into one of the surgical MS-DRGs for the MDC 
into which the principal diagnosis or procedure is assigned.
a. Embolization of Portal and Hepatic Veins
    As discussed in the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 
28170), we received a request to reassign cases with a principal 
diagnosis from MDC 07 (Diseases and Disorders of the Hepatobiliary 
System and Pancreas) when reported with procedures involving the 
embolization of a hepatic or portal vein from MS-DRGs 981, 982 and 983 
(Extensive O.R. Procedures Unrelated to Principal Diagnosis with MCC, 
with CC, and without CC/MCC, respectively) to MS-DRGs 423, 424, and 425 
(Other Hepatobiliary or Pancreas Procedures with MCC, with CC, and 
without CC/MCC, respectively) in MDC 07.
    We noted that in ICD-10-PCS, the root operation selected to code 
embolization procedures is dependent on the objective of the procedure. 
If the objective of an embolization procedure is to completely close a 
vessel, the root operation Occlusion is coded. ICD-10-PCS procedure 
codes 06L43DZ (Occlusion of hepatic vein with intraluminal device, 
percutaneous approach) or 06L83DZ (Occlusion of portal vein with 
intraluminal device, percutaneous approach) may be reported to describe 
embolization procedures to completely close off a hepatic or portal 
vein with an intraluminal device. If the objective of an embolization 
procedure is to narrow the lumen of a vessel, the root operation 
Restriction is coded. ICD-10-PCS procedure codes 06V43DZ (Restriction 
of hepatic vein with intraluminal device, percutaneous approach) or 
06V83DZ (Restriction of portal vein with intraluminal device, 
percutaneous approach) may be reported to describe embolization 
procedures to narrow or partially occlude a hepatic or portal vein with 
an intraluminal device.
    These four ICD-10-PCS procedure codes, as well as their MDC 
assignments, are listed in the table:
[GRAPHIC] [TIFF OMITTED] TR10AU22.050

    We stated in the proposed rule that our analysis of this grouping 
issue confirmed that when a procedure code describing the percutaneous 
occlusion or restriction of the hepatic or portal vein with 
intraluminal device is reported with a principal diagnosis from MDC 07, 
these cases group to MS-DRGs 981, 982, and 983 (Extensive O.R. 
Procedure Unrelated to Principal Diagnosis with MCC, with CC, and 
without CC/MCC, respectively). Whenever there is a surgical procedure 
reported on the claim that is unrelated to the MDC to which the case 
was assigned based on the principal diagnosis, it results in an MS-DRG 
assignment to a surgical class referred to as ``unrelated operating 
room procedures''.
    As noted in the proposed rule, to understand the resource use for 
the subset of cases reporting procedure codes 06L43DZ, 06L83DZ, 06V43DZ 
or 06V83DZ with a principal diagnosis from MDC 07 that are currently 
grouping to MS-DRGs 981, 982, and

[[Page 48858]]

983, we examined claims data from the September 2021 update of the FY 
2021 MedPAR file for the average length of stay and average costs for 
these cases. Our findings are shown in the following table:
[GRAPHIC] [TIFF OMITTED] TR10AU22.051

    We also examined the data for cases in MS-DRGs 423, 424, and 425, 
and our findings are shown in the following table:
[GRAPHIC] [TIFF OMITTED] TR10AU22.052

    As noted in the proposed rule, while the claims analysis based on 
the September 2021 update of the FY 2021 MedPAR file identified only 34 
cases for which these procedures were reported with a principal 
diagnosis from MDC 07 resulting in assignment to MS-DRGs 981 through 
983, and the average length of stay and average costs for these cases 
vary in comparison to the average length of stay and average costs of 
all cases in MS-DRGs 423, 424, and 425, given the clinical indications 
for hepatic or portal vein embolization procedures, such as to induce 
regrowth on one side of the liver in advance of a planned hepatic 
resection on the other side, we stated we believed it was clinically 
appropriate to add these procedure codes describing the percutaneous 
occlusion or restriction of the hepatic or portal vein with 
intraluminal device to MS-DRGs 423, 424, and 425 in MDC 07. Our 
clinical advisors stated that these procedures are clearly related to 
the principal diagnoses as they are procedures performed for 
hepatobiliary diagnoses, namely hepatocellular carcinoma and liver 
metastases, so it is clinically appropriate for the procedures to group 
to the same MDC as the principal diagnoses. Our clinical advisors also 
stated the procedures describing the percutaneous occlusion or 
restriction of the hepatic or portal vein with intraluminal device are 
consistent with the existing procedure codes included in the logic for 
case assignment to MS-DRGs 423, 424, and 425.
    Therefore, we proposed to add ICD-10-PCS procedure codes 06L43DZ, 
06L83DZ, 06V43DZ and 06V83DZ to MDC 07 in MS-DRGs 423, 424 and 425. 
Under this proposal, cases reporting procedure codes 06L43DZ, 06L83DZ, 
06V43DZ or 06V83DZ in conjunction with a principal diagnosis code from 
MDC 07 would group to MS-DRGs 423, 424 and 425.
    Comment: Commenters expressed support for CMS' proposal to add ICD-
10-PCS procedure codes 06L43DZ, 06L83DZ, 06V43DZ and 06V83DZ to MDC 07 
in MS-DRGs 423, 424 and 425. A commenter stated that this proposal is 
in line with resources utilized in performing the procedures and also 
helps organizations better manage their Program for Evaluating Payment 
Patterns Electronic Report (PEPPER) data related to DRG 981 and 982.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to add ICD-10-PCS procedure codes 06L43DZ, 
06L83DZ, 06V43DZ and 06V83DZ to MDC 07 in MS-DRGs 423, 424 and 425, 
without modification, effective October 1, 2022 for FY 2023.
b. Percutaneous Excision of Hip Muscle
    As discussed in the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 
28171), we received a request to examine cases reporting a procedure 
describing

[[Page 48859]]

percutaneous biopsies of muscle. The requestor stated that when 
procedures describing the percutaneous excision of the left hip muscle 
for diagnostic purposes are reported with a principal diagnosis from 
MDC 06 (Diseases and Disorders of the Digestive System) such as K68.12 
(Psoas muscle abscess), the cases are assigned to MS-DRGs 981, 982, and 
983 (Extensive O.R. Procedure Unrelated to Principal Diagnosis with 
MCC, with CC, and without CC/MCC, respectively). However, when 
procedures describing the percutaneous excision of the retroperitoneum 
for diagnostic purposes are reported with the same principal diagnosis 
of psoas muscle abscess, the cases are assigned to medical MS-DRGs 371, 
372, and 373 (Major Gastrointestinal Disorders and Peritoneal 
Infections with MCC, with CC, and without CC/MCC, respectively). The 
requestor stated the cases at their facility with a principal diagnosis 
of psoas muscle abscess when reported with a procedure describing a 
biopsy of the left muscle had an average length of stay comparable to 
other cases assigned to MS-DRGs 371, 372, and 373. The requestor 
provided ICD-10-PCS procedure code 0KBP3ZX (Excision of left hip 
muscle, percutaneous approach, diagnostic) in its request and 
recommended that CMS evaluate the assignment of procedure code 0KBP3ZX 
because procedures describing the percutaneous excision of the left hip 
muscle for diagnostic purposes appear to be related to a diagnosis of 
psoas muscle abscess.
    We stated in the proposed rule that in order to analyze this 
request, we first identified the similar ICD-10-PCS procedure codes 
that also describe the excision of hip muscle. We noted that under the 
ICD-10-PCS procedure classification, biopsy procedures are identified 
by the 7th digit qualifier value ``diagnostic'' in the code 
description. The four ICD-10-PCS procedure codes that describe the 
excision of hip muscle, as well as their MDC assignments, are listed in 
the table:
[GRAPHIC] [TIFF OMITTED] TR10AU22.053

    We stated in the proposed rule that our analysis of this grouping 
issue confirmed that when procedure codes 0KBN3ZX, 0KBN3ZZ, 0KBP3ZX or 
0KBP3ZZ are reported with a principal diagnosis from MDC 06, such as 
K68.12, these cases group to MS-DRGs 981, 982, and 983. As noted in the 
previous discussion, whenever there is a surgical procedure reported on 
the claim that is unrelated to the MDC to which the case was assigned 
based on the principal diagnosis, it results in a MS-DRG assignment to 
a surgical class referred to as ``unrelated operating room 
procedures''.
    As noted in the proposed rule, we examined the claims data from the 
September 2021 update of the FY 2021 MedPAR file to identify cases 
reporting procedure codes 0KBN3ZX, 0KBN3ZZ, 0KBP3ZX, or 0KBP3ZZ with a 
principal diagnosis of K68.12 (Psoas muscle abscess) that are currently 
grouping to MS-DRGs 981, 982, and 983. Our findings are shown in this 
table:
[GRAPHIC] [TIFF OMITTED] TR10AU22.054

    As shown, in our analyses of the claims data for MS-DRGs 981 
through 983, we found a total of seven cases reporting procedures 
describing excision of hip muscle with a principal diagnosis of K68.12 
in the September 2021 update of the FY 2021 MedPAR file.
    We stated in the proposed rule that to further evaluate this issue, 
we examined claims data from the September 2021 update of the FY 2021 
MedPAR file for cases reporting any one of the four procedure codes 
(0KBN3ZX, 0KBN3ZZ, 0KBP3ZX, or 0KBP3ZZ) in MS-DRGs

[[Page 48860]]

981 through 983 with a principal diagnosis from MDC 06. Our findings 
are shown in the following table.
[GRAPHIC] [TIFF OMITTED] TR10AU22.055

    As shown, in our analyses of the claims data for MS-DRGs 981 
through 983, we found a total of 14 cases reporting procedures 
describing excision of hip muscle with a principal diagnosis from MDC 
06 in the September 2021 update of the FY 2021 MedPAR file.
    We also stated in the proposed rule that we examined the data for 
cases in MS-DRGs 371, 372, and 373, and our findings are shown in the 
following table:
[GRAPHIC] [TIFF OMITTED] TR10AU22.056

    As discussed in the proposed rule, we reviewed these procedures and 
our clinical advisors stated that procedures that describe the 
percutaneous excision of hip muscle are not surgical in nature and 
would not be the main reason for inpatient hospitalization or be 
considered the principal driver of resource expenditure. Our clinical 
advisors stated although a correlation cannot usually be made between 
procedures performed in general anatomic regions, such as the 
retroperitoneum, and procedures performed in specific body parts, such 
as muscle, because procedures coded with general anatomic region body 
parts represent a broader range of procedures that cannot be coded to a 
specific body part, they agreed that in this instance procedures that 
describe the percutaneous excision of hip muscle should have the same 
designation as the ICD-10-PCS procedure codes that describe the 
percutaneous excision of the retroperitoneum that are currently 
designated as non-O.R. procedures.
    We stated that our clinical advisors reviewed this analysis and 
believed that, for clinical coherence and consistency, it would be 
appropriate to designate ICD-10-PCS codes 0KBN3ZX, 0KBN3ZZ, 0KBP3ZX, 
and 0KBP3ZZ as non-O.R. procedures.
    Therefore, we proposed to remove codes 0KBN3ZX, 0KBN3ZZ, 0KBP3ZX, 
and 0KBP3ZZ from the FY 2023 ICD-10 MS-DRGs Version 40 Definitions 
Manual in Appendix E--Operating Room Procedures and Procedure Code/MS-
DRG Index as O.R. procedures. Under this proposal, these procedures 
would no longer impact MS-DRG assignment. Cases reporting procedure 
codes 0KBN3ZX, 0KBN3ZZ, 0KBP3ZX, and 0KBP3ZZ in conjunction with a 
principal diagnosis code from MDC 06 would group to MS-DRGs 371, 372, 
and 373.
    Comment: Some commenters expressed support for CMS' proposal to 
remove codes 0KBN3ZX, 0KBN3ZZ, 0KBP3ZX, and 0KBP3ZZ from the FY 2023 
ICD-10 MS-DRGs Version 40 Definitions Manual in Appendix E--Operating 
Room Procedures and Procedure Code/MS-DRG Index as O.R. procedures.
    Response: We appreciate the commenters' support.
    Comment: A commenter opposed CMS' proposal to designate ICD-10-PCS 
codes 0KBN3ZX, 0KBN3ZZ, 0KBP3ZX, and 0KBP3ZZ as non-O.R. procedures and 
stated that they did not believe this proposal was warranted based on 
the work involved in performing the procedures.
    Response: We thank the commenter for their feedback. Our clinical 
advisors reviewed the commenter's concerns and continue to support a 
non-O.R. designation for procedure codes 0KBN3ZX, 0KBN3ZZ, 0KBP3ZX, and

[[Page 48861]]

0KBP3ZZ that describe the percutaneous excision of hip muscle. Our 
clinical advisors continue to state that procedure codes that describe 
the percutaneous excision of hip muscle are not surgical in nature and 
these procedures should have the same designation as the ICD-10-PCS 
procedure codes that describe the percutaneous excision of the 
retroperitoneum that are currently designated as non-O.R. procedures.
    After consideration of the public comments we received, for the 
reasons stated, we are finalizing our proposal to remove codes 0KBN3ZX, 
0KBN3ZZ, 0KBP3ZX, and 0KBP3ZZ from the FY 2023 ICD-10 MS-DRGs Version 
40 Definitions Manual in Appendix E--Operating Room Procedures and 
Procedure Code/MS-DRG Index as O.R. procedures, without modification, 
effective October 1, 2022 for FY 2023. Under this final policy, these 
procedures will no longer impact MS-DRG assignment.
    In addition, as discussed in the proposed rule, we also conduct an 
internal review and consider requests that we receive to examine cases 
found to group to MS-DRGs 981 through 983 or MS-DRGs 987 through 989 to 
determine if it would be appropriate for the cases to be reassigned 
from one of the MS-DRG groups to the other. In the proposed rule, we 
stated that based on the results of our review of the claims data from 
the September 2021 update of the FY 2021 MedPAR file we did not 
identify any cases for reassignment. We also stated we did not receive 
any requests suggesting reassignment. Therefore, for FY 2023 we did not 
propose to move any cases reporting procedure codes from MS-DRGs 981 
through 983 to MS-DRGs 987 through 989 or vice versa.
    Comment: Commenters expressed support for CMS' decision to not 
propose to move any cases reporting procedure codes from MS-DRGs 981 
through 983 to MS-DRGs 987 through 989 or vice versa.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing the structure of MS-DRGs 981 through 983 and MS-DRGs 987 
through 989 for FY 2023 without modification.
12. Operating Room (O.R.) and Non-O.R. Issues
a. Background
    Under the IPPS MS-DRGs (and former CMS MS-DRGs), we have a list of 
procedure codes that are considered operating room (O.R.) procedures. 
Historically, we developed this list using physician panels that 
classified each procedure code based on the procedure and its effect on 
consumption of hospital resources. For example, generally the presence 
of a surgical procedure which required the use of the operating room 
would be expected to have a significant effect on the type of hospital 
resources (for example, operating room, recovery room, and anesthesia) 
used by a patient, and therefore, these patients were considered 
surgical. Because the claims data generally available do not precisely 
indicate whether a patient was taken to the operating room, surgical 
patients were identified based on the procedures that were performed. 
Generally, if the procedure was not expected to require the use of the 
operating room, the patient would be considered medical (non-O.R.).
    Currently, each ICD-10-PCS procedure code has designations that 
determine whether and in what way the presence of that procedure on a 
claim impacts the MS-DRG assignment. First, each ICD-10-PCS procedure 
code is either designated as an O.R. procedure for purposes of MS- DRG 
assignment (``O.R. procedures'') or is not designated as an O.R. 
procedure for purposes of MS-DRG assignment (``non-O.R. procedures''). 
Second, for each procedure that is designated as an O.R. procedure, 
that O.R. procedure is further classified as either extensive or non-
extensive. Third, for each procedure that is designated as a non-O.R. 
procedure, that non-O.R. procedure is further classified as either 
affecting the MS-DRG assignment or not affecting the MS-DRG assignment. 
We refer to these designations that do affect MS-DRG assignment as 
``non O.R. affecting the MS-DRG.'' For new procedure codes that have 
been finalized through the ICD-10 Coordination and Maintenance 
Committee meeting process and are proposed to be classified as O.R. 
procedures or non-O.R. procedures affecting the MS-DRG, our clinical 
advisors recommend the MS-DRG assignment which is then made available 
in association with the proposed rule (Table 6B.--New Procedure Codes) 
and subject to public comment. These proposed assignments are generally 
based on the assignment of predecessor codes or the assignment of 
similar codes. For example, we generally examine the MS-DRG assignment 
for similar procedures, such as the other approaches for that 
procedure, to determine the most appropriate MS-DRG assignment for 
procedures proposed to be newly designated as O.R. procedures. As 
discussed in section II.D.14 of the preamble of this final rule, we are 
making Table 6B.--New Procedure Codes--FY 2023 available on the CMS 
website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html. We also refer readers to the ICD-
10 MS-DRG Version 39.1 Definitions Manual at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software.html for detailed information regarding 
the designation of procedures as O.R. or non-O.R. (affecting the MS-
DRG) in Appendix E--Operating Room Procedures and Procedure Code/MS-DRG 
Index.
    In the FY 2020 IPPS/LTCH PPS proposed rule, we stated that, given 
the long period of time that has elapsed since the original O.R. 
(extensive and non-extensive) and non-O.R. designations were 
established, the incremental changes that have occurred to these O.R. 
and non-O.R. procedure code lists, and changes in the way inpatient 
care is delivered, we plan to conduct a comprehensive, systematic 
review of the ICD-10-PCS procedure codes. This will be a multi year 
project during which we will also review the process for determining 
when a procedure is considered an operating room procedure. For 
example, we may restructure the current O.R. and non O.R.-designations 
for procedures by leveraging the detail that is now available in the 
ICD-10 claims data. We refer readers to the discussion regarding the 
designation of procedure codes in the FY 2018 IPPS/LTCH PPS final rule 
(82 FR 38066) where we stated that the determination of when a 
procedure code should be designated as an O.R. procedure has become a 
much more complex task. This is, in part, due to the number of various 
approaches available in the ICD-10-PCS classification, as well as 
changes in medical practice. While we have typically evaluated 
procedures on the basis of whether or not they would be performed in an 
operating room, we believe that there may be other factors to consider 
with regard to resource utilization, particularly with the 
implementation of ICD-10.
    We discussed in the FY 2020 IPPS/LTCH PPS proposed rule that as a 
result of this planned review and potential restructuring, procedures 
that are currently designated as O.R. procedures may no longer warrant 
that designation, and conversely, procedures that are currently 
designated as non-O.R.

[[Page 48862]]

procedures may warrant an O.R. type of designation. We intend to 
consider the resources used and how a procedure should affect the MS-
DRG assignment. We may also consider the effect of specific surgical 
approaches to evaluate whether to subdivide specific MS DRGs based on a 
specific surgical approach. We plan to utilize our available MedPAR 
claims data as a basis for this review and the input of our clinical 
advisors. As part of this comprehensive review of the procedure codes, 
we also intend to evaluate the MS-DRG assignment of the procedures and 
the current surgical hierarchy because both of these factor into the 
process of refining the ICD-10 MS-DRGs to better recognize complexity 
of service and resource utilization.
    In the FY 2021 IPPS/LTCH PPS final rule (85 FR 58540 through 
58541), we provided a summary of the comments we had received in 
response to our request for feedback on what factors or criteria to 
consider in determining whether a procedure is designated as an O.R. 
procedure in the ICD-10-PCS classification system for future 
consideration.
    We stated in the proposed rule that in consideration of the ongoing 
PHE, we continue to believe it may be appropriate to allow additional 
time for the claims data to stabilize prior to selecting the timeframe 
to analyze for this review. Additional time is also necessary as we 
continue to develop our process and methodology. Therefore, we stated 
that we will provide more detail on this analysis and the methodology 
for conducting this review in future rulemaking.
    Comment: Commenters supported CMS' plan to continue to conduct the 
comprehensive, systematic review of the ICD-10-PCS codes that includes 
a process for determining when a procedure is designated as O.R. or 
non-O.R. These commenters expressed support of CMS' decision to allow 
additional time for the claims data to stabilize prior to selecting the 
timeframe to analyze for this review in consideration of the ongoing 
PHE. A commenter stated they appreciate that CMS is taking the 
appropriate time before deciding whether and how to restructure the 
current O.R. and non-O.R. designations. Another commenter acknowledged 
that O.R. and non-O.R. designation determinations are a substantial 
undertaking that may significantly restructure many MS-DRGs.
    Response: We thank the commenters for their support and appreciate 
their acknowledgement of the magnitude of this effort.
    Comment: Other commenters stated that designation of O.R. versus 
non-O.R. may no longer be the most critical differentiator between 
resource-intensive procedures for MS-DRG purposes. These commenters 
noted that medical practice is changing and presently, there are 
increasingly complex and resource-intensive procedures performed by 
hospitals that do not involve the use of an operating room. A commenter 
stated that because of technological advances, sophisticated resource-
intensive procedures are no longer confined to the operating room 
setting.
    Other commenters highlighted stem cell transplants (SCT), Chimeric 
Antigen Receptor (CAR) T-cell therapy, and other novel cell and gene 
therapies as examples of therapeutic interventions that have similar or 
greater resource utilization and complexity than some O.R. designated 
procedures, while not being currently designated as O.R. procedures 
themselves. Another commenter noted that some procedures performed in 
interventional radiology suites and cardiac catheterization labs can 
utilize more advanced equipment and supplies than procedures performed 
in a traditional operating room with minimally installed equipment. As 
part of the broader and continuing conversation about future MS-DRG 
assignments and designations for these procedures and therapies, these 
commenters encouraged CMS to consider how other factors influence 
resource utilization, and recommended CMS consider questions such as 
whether:
     certain types of interventions, such as the administration 
of certain complex drugs/biologics or therapies (for example, radiation 
therapy), that demonstrate higher costs and resource utilization, 
warrant consideration of a designation as an O.R. procedure or another 
equivalent designation?
     certain types of procedures and therapies make up a 
substantial percentage of the costs within a particular MS-DRG?
     there is an average amount of cost within the relative 
weight of a MS-DRG that represents significant resource utilization and 
complexity?
     complex infusion-type administration of novel and 
potentially curative cell and gene therapies should be considered for 
new category of MS-DRGs, to be added to the current categories of Pre-
MDC MS-DRGs, Surgical MS-DRGs and Medical MS-DRGs?
    Response: CMS appreciates the commenters' feedback and 
recommendations as to factors to consider in evaluating O.R. 
designations. As stated previously, we have typically evaluated 
procedures on the basis of whether or not they would be performed in an 
operating room. We agree with commenters and believe that there may be 
other factors to consider with regard to resource utilization, 
particularly with the implementation of ICD-10. As discussed in the 
proposed rule, we are exploring alternatives on how we may restructure 
the current O.R. and non-O.R. designations for procedures by leveraging 
the detail that is available in the ICD-10 claims data. We continue to 
develop our process and methodology, and will provide more detail in 
future rulemaking.
    Comment: Several commenters suggested that CMS work closely with 
physician specialty societies and interested parties to identify the 
most important drivers of complexity and resource use in the hospital 
setting. Other commenters suggested CMS engage the broader community by 
convening town halls or listening sessions. A few commenters suggested 
that CMS allow sufficient time for provider review and stated that 
thorough data analysis with provider input is critical to allow for 
appropriate insight in provider comments. A commenter recommended that 
CMS be transparent in its methodology, identify criteria or metrics 
used to determine what does and does not constitute significant 
resource utilization and complexity across MS-DRGs, and be receptive to 
public opinion. Another commenter stated that they look forward to CMS 
providing more detail on this analysis and expressed that they would 
appreciate advanced notice for comment in future rulemaking regarding 
the proposed methodology for conducting this review.
    Response: CMS appreciates this feedback. We note that CMS has 
already convened an internal workgroup comprised of clinicians, coding 
specialists and other policy analysts, and we look forward to further 
feedback from the public. Recognizing sufficient time is needed to 
provide feedback on what factors or criteria to consider in determining 
whether a procedure should be designated as an O.R. procedure in the 
ICD-10-PCS classification system, we have provided opportunity for the 
public to provide feedback beginning with the FY 2018 final rule and we 
continue to solicit input. We encourage the public to submit comments 
on other factors to consider in our refinement efforts to recognize and 
differentiate consumption of resources for the ICD-10 MS-DRGs timely 
for consideration. We will also

[[Page 48863]]

explore additional means of eliciting feedback, and will notify the 
public of any such other opportunities for communication and comment in 
the future. Once we are in a position to provide more detail on this 
analysis and the methodology for conducting this comprehensive review, 
we will do so in future rulemaking.
    As discussed in the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 
28174 through 28175), we received the following requests regarding 
changing the designation of specific ICD-10-PCS procedure codes from 
non-O.R. to O.R. procedures. In this section of this rule, as we did in 
the proposed rule, we summarize these requests and address why we are 
not considering a change to the designation of these codes at this time 
and, further, respond to the public comments we received regarding 
these requests.
    We received a request to change the designation of all ICD-10-PCS 
procedure codes that describe diagnostic and therapeutic percutaneous 
endoscopic procedures performed on thoracic and abdominal organs, from 
non-O.R. to O.R. According to the requestor, thoracoscopic and 
laparoscopic procedures are always performed in the operating room 
under general anesthesia. In the proposed rule, we stated we believed 
additional time was needed to fully examine the numerous ICD-10-PCS 
codes in the classification that describe diagnostic and therapeutic 
percutaneous endoscopic procedures performed on thoracic and abdominal 
organs as there are over 19,000 ICD-10-PCS codes in the classification 
that describe procedures performed using a percutaneous endoscopic 
approach. As we have signaled in prior rulemaking, the designation of 
an O.R. procedure encompasses more than the physical location of the 
hospital in which the procedure may be performed. We also examine if, 
and in what way, the performance of the procedure affects the resource 
expenditure in those admissions in the inpatient setting, in addition 
to examining other clinical factors such as procedure complexity, and 
need for anesthesia administration as well as other types of sedation. 
We stated we will continue to evaluate the ICD-10-PCS procedure codes 
that describe diagnostic and therapeutic percutaneous endoscopic 
procedures performed on thoracic and abdominal organs as we conduct a 
comprehensive, systematic review of the ICD-10-PCS procedure codes.
    Comment: A commenter stated that they agreed with the request to 
change the designation of all lCD-10-PCS procedure codes that describe 
diagnostic and therapeutic percutaneous endoscopic procedures performed 
on thoracic and abdominal organs from non-O.R. to O.R. and stated that 
these procedures would likely occur in an operating room under general 
anesthesia. Another commenter stated that while they did not dispute 
that there may be over 19,000 ICD-10-PCS codes that describe procedures 
performed using a percutaneous endoscopic approach, they believed that 
this list could be whittled down substantially by considering only 
codes describing procedures performed on thoracic and abdominal organs. 
This commenter stated that even with a smaller list utilizing the 
criteria they suggested, they could not think of a thoracoscopic or 
laparoscopic procedure that would not require general anesthesia and be 
performed in an operating room and urged CMS to designate all ICD-10-
PCS procedure codes that describe diagnostic and therapeutic 
percutaneous endoscopic procedures performed on thoracic and abdominal 
organs as operating room procedures.
    Response: We appreciate the commenters' feedback. We also 
appreciate the commenter's suggestion, however, as stated in the 
proposed rule, and in prior rulemaking, we plan to conduct a 
comprehensive, systematic review of the ICD-10-PCS procedure codes. Our 
clinical advisors recommended that rather than evaluating the procedure 
codes describing diagnostic and therapeutic percutaneous endoscopic 
procedures performed on thoracic and abdominal organs in isolation, 
analysis should be performed for this subset of procedure codes across 
the MS-DRGs, as part of the comprehensive procedure code review. As a 
component of our broader comprehensive procedure code review, we are 
also reviewing the process for determining when a procedure is 
considered an operating room procedure. For example, we may restructure 
the current O.R. and non-O.R. designations for procedures by leveraging 
the detail that is available in the ICD-10 claims data. Therefore, 
after consideration of the public comments we received, and for the 
reasons discussed, we are not making changes in this final rule to the 
designation of all ICD-10-PCS procedure codes that describe diagnostic 
and therapeutic percutaneous endoscopic procedures performed on 
thoracic and abdominal organs, from non-O.R. to O.R. We will provide 
more detail on the comprehensive procedure code review and the 
methodology for conducting this review in future rulemaking.
    In the FY 2022 IPPS/LTCH PPS final rule (86 FR 44892 through 44895) 
CMS finalized the proposal to remove the 22 codes that describe the 
open drainage of subcutaneous tissue and fascia listed in the following 
table from the ICD-10 MS-DRGs Version 39.1 Definitions Manual in 
Appendix E--Operating Room Procedures and Procedure Code/MS-DRG Index 
as O.R. procedures. Under this finalization, these procedures no longer 
impact MS-DRG assignment.

[[Page 48864]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.057

    In the FY 2022 final rule we noted that the designation of the 22 
procedure codes that describe the open drainage of subcutaneous tissue 
and fascia as O.R. procedures was a result of a replication error in 
transitioning to ICD-10. This replication error led to ICD-10-PCS 
procedure codes that describe the open drainage of subcutaneous tissue 
and fascia being listed as comparable translations for ICD-9-CM code 
83.09 (Other incision of soft tissue), which was designated as a non-
extensive O.R. procedure under the ICD-9-CM MS-DRGs Version 32, as 
opposed to being listed as comparable translations for ICD-9-CM code 
86.04 (Other incision with drainage of skin and subcutaneous tissue) 
which was designated as a non-O.R. procedure under the ICD-9-CM MS-DRGs 
Version 32. We stated in the FY 2022 final rule that designating the 22 
procedure codes that describe the open drainage of subcutaneous tissue 
and fascia as non-O.R. procedures would result in a more accurate 
replication of the comparable procedure, under the ICD-9-CM MS-DRGs 
Version 32 which was 86.04, not 83.09 and is more aligned with current 
shifts in treatment practices.
    As discussed in the FY 2023 IPPS/LTCH PPS proposed rule, we 
received a request to re-examine this change in designation. According 
to the requestor, open procedures for the drainage of subcutaneous 
tissue and fascia are indeed typically performed in the operating room 
under general anesthesia and involve making incisions through the 
subcutaneous tissue into fascia for therapeutic drainage, breaking up 
of loculations, and irrigation. We stated that while our clinical 
advisors did not disagree with the requestor that these procedures can 
involve making incisions through the subcutaneous tissue into fascia, 
they continued to state procedures describing the open drainage of 
subcutaneous tissue and fascia can now be safely performed in the 
outpatient setting and when performed during a hospitalization, they 
are typically performed in conjunction with another O.R. procedure. For 
the reasons discussed in the FY 2022 final rule, our clinical advisors 
stated that the non-O.R. designation of the 22 procedure codes that 
describe the open drainage of subcutaneous tissue and fascia as 
finalized in the FY 2022 final rule better reflects the associated 
technical complexity and hospital resource use of these procedures.
    Comment: Some commenters opposed the non-O.R. designation of the 22 
procedure codes that describe the open drainage of subcutaneous tissue 
and fascia as finalized in the FY 2022 final rule and urged that these 
codes be designated as O.R. procedures for FY 2023. These commenters 
stated that procedure codes that describe the open drainage of 
subcutaneous tissue and fascia are indeed performed in the operating 
room under general anesthesia, are surgical in nature, and an O.R. 
designation would more accurately capture the utilization of resources. 
A commenter stated that a review of the cases at their facility shows 
that approximately 80% of the procedures describing open drainage of 
subcutaneous tissue and fascia are performed in an O.R. setting 
requiring anesthesia, with a much lesser percentage performed at the 
bedside. Another commenter noted in the FY 2018 IPPS proposed rule, 
these same 22 ICD-10-PCS codes were identified and a commenter opposed 
the proposal to re-designate these codes at that time. In response to 
the issues raised by this commenter, CMS agreed in the FY 2018

[[Page 48865]]

IPPS final rule to maintain the designation of the 22 procedure codes. 
This commenter stated the rationale to maintain these 22 codes as O.R. 
procedures has not changed and that there is no safe way to effectively 
drain an infection involving the subfascial plane without the resources 
of an operating room.
    Response: Our clinical advisors reviewed the commenters' concerns 
and continue to state that treatment practices have continued to shift 
since FY 2018 rulemaking. As stated in the FY 2022 final rule in 
response to similar comments, procedures describing the open drainage 
of subcutaneous tissue and fascia can now be safely performed in the 
outpatient setting and when performed during a hospitalization, it is 
typically in conjunction with another O.R. procedure. In cases where 
procedures describing open drainage of subcutaneous tissue and fascia 
are the only procedures performed in an admission, the admission is 
quite likely due to need for IV antibiotics as opposed to the need for 
operating room resources in an inpatient setting.
    We refer the reader to Table 6P.1f associated with this final rule 
(which is available via the internet on the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS) for the data analysis of cases reporting the 22 
procedure codes that describe the open drainage of subcutaneous tissue 
and fascia in the September 2021 update of the FY 2021 MedPAR file. We 
note that within each MDC, the MS-DRGs are divided into medical and 
surgical categories. In general, surgical MS-DRGs are further defined 
based on the precise surgical procedure performed while the medical MS-
DRGs are further defined based on the precise principal diagnosis for 
which a patient was admitted to the hospital. In Table 6P.1f associated 
with this final rule, column B displays the category of each MS-DRG in 
MS-DRG GROUPER Version 39.1. The letter M is used to designate a 
medical MS-DRG and the letter P is used to designate a surgical MS-DRG. 
As shown in the table, when the procedure codes that describe the open 
drainage of the subcutaneous tissue and fascia are reported, 
approximately 70% of the MS-DRGs assigned are classified as surgical 
MS-DRGs which indicates at least one procedure code designated as an 
O.R. procedure was also reported in these cases. We refer the reader to 
the ICD-10 MS-DRG Version 39.1 Definitions Manual (which is available 
via the internet on the CMS website at: https://www.cms.gov/Medicare/Medicare-Feefor-Service-Payment/AcuteInpatientPPS/MS-DRGClassifications-and-Software) for complete documentation of the 
GROUPER logic for the listed MS-DRGs.
    Our clinical advisors continue to state that procedure codes that 
describe the open drainage of subcutaneous tissue and fascia do not 
reflect the technical complexity or resource intensity in comparison to 
other procedures that are designated as O.R. procedures. They also 
continue to state that the non-O.R. designation of the 22 procedure 
codes that describe the open drainage of subcutaneous tissue and fascia 
as finalized in the FY 2022 final rule better reflects the associated 
technical complexity and hospital resource use of these procedures.
    Therefore, after consideration of the public comments we received, 
and for the reasons discussed, we are not making changes in this final 
rule to the designation of the 22 codes that describe the open drainage 
of subcutaneous tissue and fascia listed in the previous table.
13. Changes to the MS-DRG Diagnosis Codes for FY 2023
a. Background of the CC List and the CC Exclusions List
    Under the IPPS MS-DRG classification system, we have developed a 
standard list of diagnoses that are considered CCs. Historically, we 
developed this list using physician panels that classified each 
diagnosis code based on whether the diagnosis, when present as a 
secondary condition, would be considered a substantial complication or 
comorbidity. A substantial complication or comorbidity was defined as a 
condition that, because of its presence with a specific principal 
diagnosis, would cause an increase in the length-of-stay by at least 1 
day in at least 75 percent of the patients. However, depending on the 
principal diagnosis of the patient, some diagnoses on the basic list of 
complications and comorbidities may be excluded if they are closely 
related to the principal diagnosis. In FY 2008, we evaluated each 
diagnosis code to determine its impact on resource use and to determine 
the most appropriate CC subclassification (NonCC, CC, or MCC) 
assignment. We refer readers to sections II.D.2. and 3. of the preamble 
of the FY 2008 IPPS final rule with comment period for a discussion of 
the refinement of CCs in relation to the MS-DRGs we adopted for FY 2008 
(72 FR 47152 through 47171).
b. Overview of Comprehensive CC/MCC Analysis
    In the FY 2008 IPPS/LTCH PPS final rule (72 FR 47159), we described 
our process for establishing three different levels of CC severity into 
which we would subdivide the diagnosis codes. The categorization of 
diagnoses as a MCC, a CC, or a NonCC was accomplished using an 
iterative approach in which each diagnosis was evaluated to determine 
the extent to which its presence as a secondary diagnosis resulted in 
increased hospital resource use. We refer readers to the FY 2008 IPPS/
LTCH PPS final rule (72 FR 47159) for a complete discussion of our 
approach. Since the comprehensive analysis was completed for FY 2008, 
we have evaluated diagnosis codes individually when assigning severity 
levels to new codes and when receiving requests to change the severity 
level of specific diagnosis codes.
    We noted in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19235 
through 19246) that with the transition to ICD-10-CM and the 
significant changes that have occurred to diagnosis codes since the FY 
2008 review, we believed it was necessary to conduct a comprehensive 
analysis once again. Based on this analysis, we proposed changes to the 
severity level designations for 1,492 ICD-10-CM diagnosis codes and 
invited public comments on those proposals. As summarized in the FY 
2020 IPPS/LTCH PPS final rule, many commenters expressed concern with 
the proposed severity level designation changes overall and recommended 
that CMS conduct further analysis prior to finalizing any proposals. 
After careful consideration of the public comments we received, as 
discussed further in the FY 2020 final rule, we generally did not 
finalize our proposed changes to the severity designations for the ICD-
10-CM diagnosis codes, other than the changes to the severity level 
designations for the diagnosis codes in category Z16- (Resistance to 
antimicrobial drugs) from a NonCC to a CC. We stated that postponing 
adoption of the proposed comprehensive changes in the severity level 
designations would allow further opportunity to provide additional 
background to the public on the methodology utilized and clinical 
rationale applied across diagnostic categories to assist the public in 
its review. We refer readers to the FY 2020 IPPS/LTCH PPS final rule 
(84 FR 42150 through 42152) for a complete discussion of our response 
to public comments regarding the proposed

[[Page 48866]]

severity level designation changes for FY 2020.
    As discussed in the FY 2021 IPPS/LTCH PPS proposed rule (85 FR 
32550), to provide the public with more information on the CC/MCC 
comprehensive analysis discussed in the FY 2020 IPPS/LTCH PPS proposed 
and final rules, CMS hosted a listening session on October 8, 2019. The 
listening session included a review of this methodology utilized to 
mathematically measure the impact on resource use. We refer readers to 
https://www.cms.gov/Outreach-and-Education/Outreach/OpenDoorForums/Downloads/10082019ListingSessionTrasncriptandQandAsandAudioFile.zip for 
the transcript and audio file of the listening session. We also refer 
readers to https://www.cms.gov/Medicare/MedicareFee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software.html for 
the supplementary file containing the mathematical data generated using 
claims from the FY 2018 MedPAR file describing the impact on resource 
use of specific ICD-10-CM diagnosis codes when reported as a secondary 
diagnosis that was made available for the listening session.
    In the FY 2021 IPPS/LTCH PPS final rule (85 FR 58550 through 
58554), we discussed our plan to continue a comprehensive CC/MCC 
analysis, using a combination of mathematical analysis of claims data 
as discussed in the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19235) 
and the application of nine guiding principles and plan to present the 
findings and proposals in future rulemaking. The nine guiding 
principles are as follows:
     Represents end of life/near death or has reached an 
advanced stage associated with systemic physiologic decompensation and 
debility.
     Denotes organ system instability or failure.
     Involves a chronic illness with susceptibility to 
exacerbations or abrupt decline.
     Serves as a marker for advanced disease states across 
multiple different comorbid conditions.
     Reflects systemic impact.
     Post-operative/post-procedure condition/complication 
impacting recovery.
     Typically requires higher level of care (that is, 
intensive monitoring, greater number of caregivers, additional testing, 
intensive care unit care, extended length of stay).
     Impedes patient cooperation or management of care or both.
     Recent (last 10 years) change in best practice, or in 
practice guidelines and review of the extent to which these changes 
have led to concomitant changes in expected resource use.
    We refer readers to the FY 2021 IPPS/LTCH PPS final rule for a 
complete discussion of our response to public comments regarding the 
nine guiding principles.
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25175 through 
25180), as another interval step in our comprehensive review of the 
severity designations of ICD-10-CM diagnosis codes, we requested public 
comments on a potential change to the severity level designations for 
``unspecified'' ICD-10-CM diagnosis codes that we were considering 
adopting for FY 2022. Specifically, we noted we were considering 
changing the severity level designation of ``unspecified'' diagnosis 
codes to a NonCC where there are other codes available in that code 
subcategory that further specify the anatomic site. As summarized in 
the FY 2022 IPPS/LTCH PPS final rule, many commenters expressed concern 
with the potential severity level designation changes overall and 
recommended that CMS delay any possible change to the designation of 
these codes to give hospitals and their physicians time to prepare. 
After careful consideration of the public comments we received, we 
maintained the severity level designation of the ``unspecified'' 
diagnosis codes currently designated as a CC or MCC where there are 
other codes available in that code subcategory that further specify the 
anatomic site for FY 2022. We refer readers to the FY 2022 IPPS/LTCH 
PPS final rule (86 FR 44916 through 44926) for a complete discussion of 
our response to public comments regarding the potential severity level 
designation changes. Instead, for FY 2022, we finalized a new Medicare 
Code Editor (MCE) code edit for ``unspecified'' codes, effective with 
discharges on and after April 1, 2022. We stated we believe finalizing 
this new edit would provide additional time for providers to be 
educated while not affecting the payment the provider is eligible to 
receive. We refer the reader to section II.D.14.e. of the FY 2022 IPPS/
LTCH PPS final rule (86 FR 44940 through 44943) for the complete 
discussion.
    As discussed in the FY 2023 IPPS/LTCH PPS proposed rule, as this 
new edit became effective beginning with discharges on and after April 
1, 2022, we stated our clinical advisors believed it was appropriate to 
not propose to change the designation of any ICD-10-CM diagnosis codes, 
including the unspecified codes that are subject to the ``Unspecified 
Code'' edit, as we continue our comprehensive CC/MCC analysis to allow 
interested parties the time needed to become acclimated to the new 
edit.
    Comment: Commenters stated that they appreciate and agree with CMS' 
decision not to propose any further changes to the designation of any 
ICD-10-CM diagnosis codes, including the unspecified codes, at this 
time. These commenters recommended that CMS allow one to two full years 
of data availability before proposing any additional changes to the 
designation of any ICD-10-CM diagnosis code, given that the new MCE 
edit was recently implemented on April 1, 2022 and stated that having 
one to two full years of data will afford more meaningful analysis in 
future rulemaking considerations as part of the comprehensive CC/MCC 
analysis.
    Response: We appreciate the commenters' support. With respect to 
the commenters who suggested allowing one to two full years of data 
availability before proposing any additional changes, we appreciate the 
feedback and will take these suggestions under consideration.
    We continue to solicit feedback regarding the guiding principles, 
as well as other possible ways we can incorporate meaningful indicators 
of clinical severity. We have made available on the CMS website updated 
impact on resource use files so that the public can review the 
mathematical data for the impact on resource use generated using claims 
from the FY 2019 MedPAR file, the FY 2020 MedPAR file and the FY 2021 
MedPAR files. The link to these files is posted on the CMS website at 
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software. When providing 
additional feedback or comments, we encourage the public to provide a 
detailed explanation of how applying a suggested concept or principle 
would ensure that the severity designation appropriately reflects 
resource use for any diagnosis code. We also continue to be interested 
in receiving feedback on how we might otherwise foster the 
documentation and reporting of the most specific diagnosis codes 
supported by the available medical record documentation and clinical 
knowledge of the patient's health condition to more accurately reflect 
each health care encounter and improve the reliability and validity of 
the coded data. Interested parties can submit any comments and 
recommendations for FY 2024 by

[[Page 48867]]

October 20, 2022 via the new electronic intake system, Medicare 
Electronic Application Request Information SystemTM 
(MEARISTM) at: https://mearis.cms.gov/public/home.
    As discussed in the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 
28177), for new diagnosis codes approved for FY 2023, consistent with 
our annual process for designating a severity level (MCC, CC or NonCC) 
for new diagnosis codes, we first review the predecessor code 
designation, followed by review and consideration of other factors that 
may be relevant to the severity level designation, including the 
severity of illness, treatment difficulty, complexity of service and 
the resources utilized in the diagnosis or treatment of the condition. 
We noted that this process does not automatically result in the new 
diagnosis code having the same designation as the predecessor code. We 
refer the reader to section II.D.14 of this final rule for the 
discussion of the proposed changes to the ICD-10-CM and ICD-10-PCS 
coding systems for FY 2023.
c. Requested Changes to Severity Levels
    In the FY 2023 IPPS/LTCH PPS proposed rule, we noted that we 
received several requests to change the severity level designations of 
specific ICD-10-CM diagnosis codes, including a request to analyze a 
subset of the social determinants of health (SDOH) diagnosis codes. We 
stated our clinical advisors believed it was appropriate to consider 
these requests in connection with our continued comprehensive CC/MCC 
analysis in future rulemaking, rather than proposing to change the 
designation of individual ICD-10-CM diagnosis codes at this time. 
However, we refer the reader to section II.D.13.d for further 
discussion related to the diagnosis codes describing social 
determinants of health. As discussed in the proposed rule and noted 
earlier in this section, we plan to continue a comprehensive CC/MCC 
analysis, using a combination of mathematical analysis of claims data 
and the application of nine guiding principles. We will consider these 
individual requests received for changes to severity level designations 
as we continue our comprehensive CC/MCC analysis and will provide more 
detail in future rulemaking.
d. Request for Information on Social Determinants of Health Diagnosis 
Codes
    As discussed in the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 
28177 through 28181), we solicited public comments on how the reporting 
of diagnosis codes in categories Z55-Z65 may improve our ability to 
recognize severity of illness, complexity of service, and/or 
utilization of resources under the MS-DRGs as described further in this 
section. Consistent with the Administration's goal of advancing health 
equity for all, including members of historically underserved and 
under-resourced communities, as described in the President's January 
20, 2021 Executive Order 13985 on ``Advancing Racial Equity and Support 
for Underserved Communities Through the Federal Government,'' \13\ we 
stated we were also interested in receiving feedback on how we might 
otherwise foster the documentation and reporting of the diagnosis codes 
describing social and economic circumstances to more accurately reflect 
each health care encounter and improve the reliability and validity of 
the coded data including in support of efforts to advance health 
equity.
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    \13\ Available at: https://www.federalregister.gov/documents/2021/01/25/2021-01753/advancing-racial-equity-and-support-for-underserved-communities-through-the-federal-government.
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    Social determinants of health (SDOH) are the conditions in the 
environments where people are born, live, learn, work, play, worship, 
and age that affect a wide range of health, functioning, and quality-
of-life outcomes and risks.\14\ These circumstances or determinants 
influence an individual's health status and can contribute to wide 
health disparities and inequities. While SDOH do not describe current 
illnesses or injuries at the individual level, they are widely 
recognized as important potential predictors of risk for developing 
medical conditions like heart disease, diabetes, and obesity. In ICD-
10-CM, the Z codes found in Chapter 21 represent reasons for 
encounters, and are provided for occasions when circumstances other 
than a disease, injury or external cause classifiable to categories 
A00-Y89 are recorded as `diagnoses' or `problems'. The subset of Z 
codes that describe the social determinants of health are found in 
categories Z55-Z65 (Persons with potential health hazards related to 
socioeconomic and psychosocial circumstances). These codes describe a 
range of issues related--but not limited--to education and literacy, 
employment, housing, ability to obtain adequate amounts of food or safe 
drinking water, and occupational exposure to toxic agents, dust, or 
radiation. We noted that effective October 1, 2021, the Centers for 
Disease Control and Prevention (CDC) National Center for Health 
Statistics (NCHS) added 11 new diagnosis codes describing SDOH to 
provide additional information regarding determinants such as housing, 
food insecurity, and transportation. In addition, section I.B.14 of the 
FY 2022 ICD-10-CM Official Guidelines for Coding and Reporting was 
updated to provide clarification of the term ``clinician'' in reporting 
codes related to social determinants of health and clarified the 
documentation that can be utilized to assign SDOH codes when included 
in the official medical record. In this context, ``clinicians'' other 
than the patient's provider refer to ``healthcare professionals 
permitted, based on regulatory or accreditation requirements or 
internal hospital policies, to document in a patient's official medical 
record.'' \15\
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    \14\ Available at: https://health.gov/healthypeople/objectives-and-data/social-determinants-health.
    \15\ Available at: https://ftp.cdc.gov/pub/Health_Statistics/NCHS/Publications/ICD10CM/2022/10cmguidelines-FY2022-April%201%20update%202-3-22.pdf.
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    As stated in the proposed rule, reporting SDOH Z codes in inpatient 
claims data could enhance quality improvement activities, track factors 
that influence people's health, and provide further insight into 
existing health inequities.16 17 18 More routine collection 
of SDOH Z codes could also likely improve coordination within hospitals 
to utilize the data across their clinical care and discharge planning 
teams, including with post-acute partners. CMS has heard from 
interested parties about a number of reasons for why there may be less 
routine documentation and reporting of SDOH in the inpatient setting. 
First, Z codes are not required to be reported by inpatient hospitals 
and generally do not affect MS-DRG assignment. Rather, these codes are 
currently reported voluntarily by providers when and if supported in 
the medical record
---------------------------------------------------------------------------

    \16\ Maksut JL, Hodge C, Van CD, Razmi, A, & Khau MT. 
Utilization of Z Codes for Social Determinants of Health among 
Medicare Fee-For-Service Beneficiaries, 2019. Office of Minority 
Health (OMH) Data Highlight No. 24. Centers for Medicare & Medicaid 
Services (CMS), Baltimore, MD, 2021.
    \17\ Truong HP, Luke AA, Hammond G, Wadhera RK, Reidhead M, 
Joynt Maddox KE. Utilization of Social Determinants of Health ICD-10 
Z-Codes Among Hospitalized Patients in the United States, 2016-2017. 
Med Care. 2020;58(12):1037-1043. doi:10.1097/MLR.0000000000001418.
    \18\ Wark K, Cheung K, Wolter E, Avey JP. Engaging stakeholders 
in integrating social determinants of health into electronic health 
records: A scoping review. International Journal of Circumpolar 
Health. 2021 Jan 1;80(1):1943983.

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[[Page 48868]]

documentation. As such, consistent protocols may not be in place for 
documenting and reporting. Second, many of the circumstances captured 
through SDOH Z codes are dependent on the willingness of patients to 
discuss personal social, economic, or environmental conditions. 
Providers may or may not be able to reliably document certain 
circumstances,\19\ as a result, in the medical records. There are also 
questions of how bias can play into screening for SDOH and how systemic 
bias within the health care system can play a role in this process.\20\ 
CMS has also heard of the significant pressures on provider time, and 
whether providers have access to comprehensive care and coordination 
teams, including social workers, who may be more appropriately skilled 
to assess certain SDOH.
---------------------------------------------------------------------------

    \19\ Garg A, Boynton-Jarrett R, Dworkin PH. Avoiding the 
Unintended Consequences of Screening for Social Determinants of 
Health. JAMA. 2016;316(8):813-814. doi:10.1001/jama.2016.9282.
    \20\ Egede LE, Walker RJ, Williams JS. Intersection of 
Structural Racism, Social Determinants of Health, and Implicit Bias 
With Emergency Physician Admission Tendencies. JAMA Netw Open. 
2021;4(9):e2126375. doi:10.1001/jamanetworkopen.2021.26375.
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    Given that SDOH diagnosis codes describe economic and environmental 
circumstances faced by patients and often correlate with substantial 
variance in health outcomes,\21\ more widely adopted consistent 
documentation and reporting in the inpatient setting could better 
identify non-medical factors affecting health and track progress toward 
addressing them. Doing so could also aid in work toward formulating 
more comprehensive and actionable policies to address health equity and 
promote the highest quality, best-value care for all beneficiaries.
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    \21\ Commission on Social Determinants of Health. Closing the 
gap in a generation: health equity through action on the social 
determinants of health: final report of the commission on social 
determinants of health. World Health Organization, 2008.
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    As we discuss more fully later in this section of this final rule, 
as we did in the proposed rule, we believe reporting of SDOH Z codes 
may also better determine the resource utilization for treating 
patients experiencing these circumstances to help inform whether a 
change to the severity designation of these codes would be clinically 
warranted as we continue a comprehensive CC/MCC analysis, using a 
combination of mathematical analysis of claims data as discussed in the 
FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19235) and the application 
of nine guiding principles.
    There are 96 diagnosis codes that describe the social determinants 
of health found in categories Z55-Z65. These 96 diagnosis codes for 
which we solicited comments as described in the proposed rule are shown 
in Table 6P.5a associated with the proposed rule (which is available 
via the internet on the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS). We note we also 
made available the data describing the impact on resource use when 
reported as a secondary diagnosis for all 96 ICD-10-CM Z codes that 
describe the social determinants of health from categories Z55-Z65. 
These data are consistent with data historically used to mathematically 
measure impact on resource use for secondary diagnoses, and the data 
which we plan to use in combination with application of the nine 
guiding principles as we continue the comprehensive CC/MCC analysis.
    In Table 6P.5a associated with the proposed rule, column C displays 
the FY 2021 severity level designation for these diagnosis codes in MS-
DRG GROUPER Version 38.1. Column D displays CMS's current FY 2022 
severity level designation in MS-DRG GROUPER Version 39.1. Columns E-N 
show data on the impact on resource use generated using discharge 
claims from the September 2021 update of the FY 2021 MedPAR file and 
MS-DRG GROUPER Version 39.1. For further information on the data on the 
impact on resource use as displayed in Columns E-N, we refer readers to 
the FY 2008 IPPS/LTCH PPS final rule (72 FR 47159) for a complete 
discussion of the methodology utilized to mathematically measure the 
impact on resource use. Also, as discussed in the FY 2021 IPPS/LTCH PPS 
proposed rule (85 FR 32550), to provide the public with more 
information on the CC/MCC comprehensive analysis discussed in the FY 
2020 IPPS/LTCH PPS proposed and final rules, CMS hosted a listening 
session on October 8, 2019. The listening session included a review of 
this methodology utilized to mathematically measure the impact on 
resource use. We refer readers to https://www.cms.gov/Outreach-and-Education/Outreach/OpenDoorForums/Downloads/10082019ListingSessionTrasncriptandQandAsandAudioFile.zip for the 
transcript and audio file of the listening session. We also refer 
readers to https://www.cms.gov/Medicare/MedicareFee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software.html for 
the supplementary file containing the data describing the impact on 
resource use of specific ICD-10-CM diagnosis codes when reported as a 
secondary diagnosis that was made available for the listening session. 
We note that the supplementary file that was made available for the 
listening session contains the mathematical data for the impact on 
resource use generated using claims from the FY 2018 MedPAR file. We 
have also made available on the CMS website updated impact on resource 
use files so that the public can review the mathematical data for the 
impact on resource use generated using claims from the FY 2019 MedPAR 
file, FY 2020 MedPAR file and the FY 2021 MedPAR files.
    In the FY 2008 IPPS/LTCH PPS final rule (72 FR 47159), we described 
the categorization of diagnoses as an MCC, a CC, or a NonCC, 
accomplished using an iterative approach in which each diagnosis was 
evaluated to determine the extent to which its presence as a secondary 
diagnosis resulted in increased hospital resource use. As such, the 
designation of CC or MCC is intended to account for the increased 
resources required to address a condition as a secondary diagnosis. In 
Version 39.1, the 96 diagnosis codes that describe the social 
determinants of health from categories Z55-Z65 have a severity 
designation of NonCC.
    In the proposed rule, we noted that if SDOH Z codes are not 
consistently reported in inpatient claims data, our methodology 
utilized to mathematically measure the impact on resource use, as 
described previously, may not adequately reflect what additional 
resources were expended by the hospital to address these SDOH 
circumstances in terms of requiring clinical evaluation, extended 
length of hospital stay, increased nursing care or monitoring or both, 
and comprehensive discharge planning. In the proposed rule, we sought 
public comment on whether CMS should consider requiring more robust 
documentation and claims data reporting to inform the impact on 
resource use these determinants have on caring for patients affected by 
these circumstances in an inpatient setting and inform our decision-
making in a future year in determining the most appropriate CC subclass 
(NonCC, CC, or MCC) assignment for each SDOH Z code as a secondary 
diagnosis. We also sought public comment on developing protocols to 
standardize the screening for SDOH for all patients, and then 
consistently document and report such codes and on whether such 
protocols should vary based on certain factors, such as hospital size 
and type. For instance, we noted in the proposed rule that we 
recognized that hospitals have different mixes of patients and volume 
of patients, and as such, may have

[[Page 48869]]

different staffing resources to devote to proper documentation and 
coding of SDOH. In particular, we stated we were interested in hearing 
the perspectives of different sized hospitals in both urban and rural 
settings, and hospitals disproportionately serving members of 
historically underserved and under-resourced communities in regard to 
their experience with reporting of SDOH. We also stated we were 
additionally interested in learning how reporting SDOH Z codes may be 
used to inform community health need assessment activities required by 
non-profit hospitals.
    In the proposed rule, we also recognized that there is a potential 
for different uses and complexity in appropriately determining and 
reporting the full range of Z codes. For instance, certain code 
categories like Z62 (Problems related to upbringing) and Z63 (Other 
problems related to principal support group, including family 
circumstances) may require specialized clinical training to diagnose 
and document, which may not be the primary purpose of the inpatient 
admission. Category Z57 describes occupational exposure to risk 
factors, which also may not be apparent in most inpatient admissions 
and would rely upon the patient providing this information voluntarily. 
Category Z60 (Problems related to social environment) also describes 
problems of adjustment to life-cycle transitions, which also may or may 
not be readily apparent or discussed by the patient in relation to the 
inpatient admission.
    Thus, we sought comment on which specific SDOH Z codes were most 
likely to influence (that is, increase) hospital resource utilization 
related to inpatient care, including any supporting information that 
correlates inpatient hospital resource use to specific SDOH Z codes. In 
the proposed rule, we stated CMS believed a potential starting point 
for discussion was consideration of the SDOH Z diagnosis codes 
describing homelessness. Homelessness can be reasonably expected to 
have an impact on hospital utilization.\22\ Healthcare needs for 
patients experiencing homelessness may be associated with increased 
resource utilization compared to other patients due to difficulty 
finding discharge destinations to meet the patient's multifaceted needs 
which can result in longer inpatient stays and can have financial 
impacts for hospitals.\23\ Longer hospital stays for these patients 
\24\ can also be associated with increased costs because patients 
experiencing homelessness are less able to access care at early stages 
of illness, and also may be exposed to communicable disease and harsh 
climate conditions, resulting in more severe and complex symptoms by 
the time they are admitted to hospitals, potentially leading to worse 
health outcomes. We stated in the proposed rule that patients 
experiencing homelessness can also be disproportionately affected by 
mental health diagnoses and issues with substance use disorders. In 
addition, patients experiencing homelessness may have limited or no 
access to prescription medicines or over-the-counter medicines, 
including adequate locations to store medications away from the heat or 
cold,\25\ and studies have shown difficulties adhering to medication 
regimens among persons experiencing homeless.\26\ Patients experiencing 
homelessness may also face challenges in accessing transplants and 
clinicians may defer care because of the uncertain post-acute 
discharge.
---------------------------------------------------------------------------

    \22\ Koh HK, O'Connell JJ. Improving Health Care for Homeless 
People. JAMA. 2016;316(24):2586-2587. doi:10.1001/jama.2016.18760.
    \23\ Canham SL, Custodio K, Mauboules C, Good C, Bosma H. Health 
and Psychosocial Needs of Older Adults Who Are Experiencing 
Homelessness Following Hospital Discharge. Gerontologist. 2020 May 
15;60(4):715-724. doi: 10.1093/geront/gnz078. PMID: 31228238. 
https://pubmed.ncbi.nlm.nih.gov/31228238/.
    \24\ Hwang SW, Weaver J, Aubry T. Hospital costs and length of 
stay among homeless patients admitted to medical, surgical, and 
psychiatric services. Med Care. 2011;49:350-354. https://journals.lww.com/lww-medicalcare/Fulltext/2019/01000/Trends,_Causes,_and_Outcomes_of_Hospitalizations.4.aspx.
    \25\ Sun R (AHRQ), Karaca Z (AHRQ), Wong HS (AHRQ). 
Characteristics of Homeless Individuals Using Emergency Department 
Services in 2014. HCUP Statistical Brief #229. October 2017. Agency 
for Healthcare Research and Quality, Rockville, MD. www.hcup-us.ahrq.gov/reports/statbriefs/sb229-Homeless-ED-Visits-2014.pdf.
    \26\ Coe, Antoinette B. Coe et al. ``Medication Adherence 
Challenges Among Patients Experiencing Homelessness in a Behavioral 
Health Clinic. https://journals.lww.com/lww-medicalcare/Fulltext/2019/01000/Trends,_Causes,_and_Outcomes_of_Hospitalizations.4.aspx.
---------------------------------------------------------------------------

    To further examine the diagnosis codes that describe SDOH, in the 
proposed rule we reviewed the data on the impact on resource use for 
diagnosis code Z59.0 (Homelessness) when reported as a secondary 
diagnosis to facilitate discussion for the purposes of the comment 
solicitation. We noted that prior to FY 2022, homelessness was one of 
the more frequently reported codes that describe social determinants of 
health. We also noted that effective FY 2022, the subcategory was 
expanded and now includes codes Z59.00 (Homelessness, unspecified), 
Z59.01 (Sheltered homelessness), and code Z59.02 (Unsheltered 
homelessness).
    In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19243 through 
19244), as part of our proposal to change the severity level 
designations for 1,492 ICD-10-CM diagnosis codes, we proposed to change 
the severity level designation of code Z59.0 (Homelessness) from NonCC 
to CC. We stated that because the C1 value (C1 = 1.5964) in the table 
was generally close to 2, the data suggested that when reported as a 
secondary diagnosis, the resources involved in caring for a patient 
experiencing homelessness supported increasing the severity level from 
a NonCC to a CC. In the FY 2020 IPPS/LTCH PPS proposed rule, we also 
stated our clinical advisors reviewed these data and believed the 
resources involved in caring for these patients are more aligned with a 
CC. As noted in section II.D.13.b of the proposed rule and this final 
rule, many commenters expressed concern with the proposed severity 
level designation changes overall and consequently we generally did not 
finalize our proposed changes to the severity designations for the 
1,492 ICD-10-CM diagnosis codes, at that time. However, the proposal to 
change the severity designation of code Z59.0 specifically did receive 
mostly supportive comments. We stated in the proposed rule that many 
commenters stated that a patient experiencing homelessness requires 
significant coordination of social services along with their health 
care. Another commenter also recommended that CMS expand the change in 
designation to all the codes in category Z59, not just code Z59.0. 
Another commenter, while indicating their support of the proposal, 
noted that it is unclear that the status/condition would result in 
increased hospital resource use.
    As discussed in the proposed rule, our proposal in FY 2020 was 
based on the data for the impact on resource use generated using claims 
from the FY 2018 MedPAR file. The following table reflects the impact 
on resource use data generated using claims from the FY 2019 MedPAR 
file, FY 2020 MedPAR file and the FY 2021 MedPAR file, respectively, 
for the diagnosis code that describes homelessness as a NonCC. We noted 
there is currently no data for codes Z59.01 (Sheltered homelessness) 
and code Z59.02 (Unsheltered homelessness) as these codes became 
effective on October 1, 2021. Again, we refer readers to the FY 2008 
IPPS/LTCH PPS final rule (72 FR 47159) for a complete discussion of our 
historical approach to mathematically evaluate the extent to which the 
presence of an ICD-

[[Page 48870]]

10-CM code as a secondary diagnosis resulted in increased hospital 
resource use, and the explanation of the columns in the table.
[GRAPHIC] [TIFF OMITTED] TR10AU22.058

    As shown in the table, we examined data for the diagnosis code(s) 
that describe homelessness as a NonCC in FY 2019 through FY 2021. When 
examining diagnosis code Z59.0 (Homelessness), the value in column C1 
is closer to 2.0 than to 1.0 in FY 2019 and FY 2020, though we noted 
that we did not use FY 2020 data for rate setting purposes in light of 
impacts related to the PHE for COVID-19 as described in the FY 2022 
IPPS/LTCH PPS final rule (86 FR 44778). The data suggests that when 
homelessness is reported as a secondary diagnosis, the resources 
involved in caring for these patients are more aligned with a CC than a 
NonCC or an MCC, as explained in the FY 2008 IPPS/LTCH PPS final rule 
(72 FR 47159). However, in FY 2021, the C1 value is generally closer to 
1, which suggest the resources involved in caring for patients 
experiencing homelessness are more aligned with a NonCC severity level 
than a CC or an MCC severity level. We also noted fluctuations in the 
C1 values year to year. We stated we were uncertain if the data from FY 
2021, in particular, reflect fluctuations that may be a result of the 
public health emergency or even reduced hospitalizations of certain 
conditions. We also stated we were uncertain if homelessness may be 
underreported when there is not an available field on the claim when 
other diagnoses are reported instead. We sought public comment on these 
possibilities, particularly to inform our understanding of the trend of 
the C1 value.
    As we have stated in prior rulemaking, these mathematical 
constructs are used in conjunction with the judgment of our clinical 
advisors to classify each secondary diagnosis reviewed. We presented 
these data to highlight that the resources expended in caring for 
patients reported to be affected by a SDOH such as homelessness during 
an inpatient hospitalization may not be consistently expressed in the 
inpatient claims data and to demonstrate how reporting the SDOH Z codes 
could more accurately reflect the health care encounter and improve the 
reliability and validity of the coded data.
    In summary, we stated we would appreciate public comment on these 
issues, including on the following questions:
     How the reporting of certain Z codes--and if so, which Z 
codes \27\--may improve our ability to recognize severity of illness, 
complexity of service, and utilization of resources under the MS-DRGs?
---------------------------------------------------------------------------

    \27\ https://www.cms.gov/files/document/zcodes-infographic.pdf.
---------------------------------------------------------------------------

     Whether CMS should require the reporting of certain Z 
codes--and if so, which ones--to be reported on hospital inpatient 
claims to strengthen data analysis?
     The additional provider burden and potential benefits of 
documenting and reporting of certain Z codes, including potential 
benefits to beneficiaries.
     Whether codes in category Z59 (Homelessness) have been 
underreported and if so, why? In particular, we stated we were 
interested in hearing the perspectives of large urban hospitals, rural 
hospitals, and other hospital types in regard to their experience. We 
also sought comments on how factors such as hospital size and type 
might impact a hospital's ability to develop standardized consistent 
protocols to better screen, document and report homelessness.
    As discussed in the proposed rule, we stated that the comments we 
receive on these issues may also be informative as we evaluate whether 
to develop a proposal in future rulemaking to change the severity level 
designation of the diagnosis codes describing homelessness from NonCC 
to CC and whether other SDOH, as described by Z codes, are also 
appropriate candidates to be proposed for designation as CCs.
    We noted that examining the severity level designation of diagnosis 
codes is just one area to possibly support documentation and reporting 
of SDOH in the inpatient setting. We stated we were also interested in 
ideas from the public on how the MS-DRG classification can be utilized 
in agency wide efforts to advance health equity, expand access, drive 
high-quality, person-centered care, and promote affordability and 
sustainability in the Medicare program. Specifically, we invited public 
comment on ways the MS-DRG classification can be useful in addressing 
the challenges of defining and collecting accurate and standardized 
self-identified socioeconomic information for the purposes of 
reporting, measure stratification, and other data collection efforts. 
We stated we were interested in learning more about the potential 
benefits and challenges associated with the collection of SDOH data in 
the inpatient setting. Feedback on the limitations and barriers 
providers could experience as they consider more robust documentation 
and reporting would also help inform our development of appropriately 
tailored efforts that address and mitigate barriers for all hospital 
types across communities and patient mixes. We stated we would take 
commenters' feedback into consideration in future policy development.
    In this FY 2023 IPPS/LTCH PPS final rule, we present a summation of 
the comments we received in response to our request for information on 
SDOH diagnosis codes, including how the reporting of SDOH diagnosis 
codes may improve our ability to recognize severity of illness, 
complexity of service, and/or utilization of resources under the MS-
DRGs, as well as how we might otherwise foster the documentation and 
reporting of the diagnosis codes describing social and economic 
circumstances to more accurately reflect each health care encounter and 
improve the reliability and validity of the coded data, including in 
support of efforts to advance health equity. We thank commenters for 
sharing their views and their willingness to support CMS in these 
efforts.
    Comment: Many commenters applauded CMS' efforts to encourage 
documentation and reporting of SDOH diagnosis codes given the impact 
that social risks can have on health outcomes. These commenters stated 
that it is critical that physicians, other health care professionals, 
and facilities

[[Page 48871]]

recognize the impact SDOH have on the health of their patients. 
Commenters stated that they agree that better reporting of these SDOH Z 
codes through inpatient claims could enhance coordination within 
hospitals across clinical care teams and discharge planning, and with 
post-acute care providers. A commenter stated that SDOH data can be 
extremely valuable and powerful tools to improve healthcare, and stated 
that they were confident that CMS' encouragement of the use of this 
data would lead to better healthcare for our country.
    Some commenters stated that while the documentation and reporting 
of SDOH diagnosis codes is important to address healthcare inequities, 
the collection of this data may place significant burden on facilities 
and providers and have tremendous operational and technology impacts. 
Commenters stated that hospitals have demonstrated significant 
variability in screening capabilities and referral practices, and 
inpatient settings require additional time to develop screening 
protocols and ensure that screening results are documented in a place 
where they can be captured for claims. Other commenters stated 
assigning codes for SDOH can be a time-consuming and labor-intensive 
process, as many electronic health records (EHRs) do not have easy 
pathways to add a Z code to the problem or diagnosis list. Other 
commenters stated that one of the major challenges to providers is 
ensuring that SDOH information documented in the EHR and reported on 
the claim is accurate as patients' circumstances are ever changing. A 
commenter stated that it is not feasible for hospitals to screen for 
every SDOH due to the time and resources involved for both patients and 
providers and suggested that rather than require this process be 
repeated with each encounter, CMS should permit SDOH information to 
carry forward across encounters until new documentation supports 
removal or revision to the initial SDOH diagnosis codes to minimize the 
administrative burden. Commenters also stated that the challenge of 
increased documentation reviews by coding staff would be further 
exacerbated by staffing shortages within the industry, as well as 
coding productivity standards. A few commenters stated for rural 
hospitals, bandwidth is already low due to workforce shortages and 
heavy caseloads. These commenters stated that adding any screening and 
documentation processes for SDOH, on top of existing workloads, may 
require more than a physician or nurse and instead may require engaging 
a staff such as social workers or psychologists who may not be standard 
members of care teams at all rural hospitals.
    Many commenters stated there was a lack of standard, nationally 
accepted definitions of the SDOH Z codes and that there are potential 
gaps that may come with the use of, and reporting related to SDOH Z 
codes. Other commenters stated that SDOH Z codes are informative but 
some descriptions lack specificity and may be too broad to distinctly 
capture enough detail around the type of care that the patient needs 
relative to their diagnosis and their SDOH challenges. Commenters also 
identified the lack of national data and exchange standards for capture 
of the SDOH Z codes as an additional barrier. Commenters stated that 
while fully supporting efforts to improve and increase the collection 
of SDOH data, they believed that other options exist that would make it 
feasible for hospitals of all sizes and types to consistently collect 
data in a standardized manner without creating undue burden and 
suggested that CMS consider developing a broader strategy for 
collecting SDOH data. A commenter specifically suggested that CMS 
coordinate with states, which are often requiring their own assessments 
to identify social risk and needs, to reduce burden. Another commenter 
stated that they believed that the creation of a new Hierarchical 
Condition Category for SDOH Z codes could help improve documentation 
efforts since, according to this commenter, organizations that treat 
these high-risk patients are reimbursed at higher rates than those 
patients who are not grouped into these HCCs.
    Commenters recommended that CMS consider reimbursement incentives 
for documenting and reporting of SDOH Z codes to help health care 
providers build and sustain systemic screening and documentation, which 
will ultimately lead to better health for patients. Many commenters 
stated that they agree that codes in category Z59 (Homelessness) have 
been underreported and that increasing the severity level of the codes 
that describe homelessness from a NonCC to a CC could prompt more 
rigorous documentation and reporting. Commenters stated that they 
believe that homelessness involves a level of care in line with 
diagnoses currently designated as CCs. Some commenters stated that 
patients experiencing homelessness can often increase inpatient costs 
by creating discharge disposition challenges that lead to an extended 
length of stay. A few commenters noted that in their experience, 
extended lengths of stay were particularly high for patients 
experiencing homelessness who underwent surgery. Another commenter 
stated that based on their own analysis, homelessness has an effect on 
resource utilization on par with other diagnoses currently designated 
as MCCs but stated elevation to a CC is the most reasonable first step 
to help drive the reporting of these SDOH Z codes, and help drive 
subsequent, meaningful evaluation of outcomes.
    Commenters encouraged CMS to examine other SDOH Z codes that 
describe circumstances such as food insecurity, lack of adequate food 
and drinking water, extreme poverty, lack of transportation and 
unemployment, to determine the hospital resource utilization related to 
addressing these factors and to analyze whether these SDOH Z codes 
should be considered for designation as CCs as well. Some commenters 
also pointed to conditions outside of the SDOH Z codes such as: medical 
debt, malnutrition, elder abuse and neglect, underdosing of medication, 
personal history of falling and awaiting organ transplant status as 
examples of other areas where fostering better documentation and 
reporting could improve health outcomes.
    Other commenters expressed concern and stated that they believed 
that while some SDOH diagnoses could have some impact for MS-DRG 
assignment due to additional efforts needed around discharge planning, 
generally SDOH diagnoses should have limited impact on severity of 
illness. Rather, according to these commenters, the impact is more 
important for risk adjustment for population-based initiatives, such as 
a readmissions program. A commenter stated that simply elevating SDOH 
Z-codes to CCs and marginally increasing reimbursement will be 
inadequate to meaningfully drive CMS' stated equity mission. Another 
commenter noted that in some cases, patients experiencing circumstances 
described by SDOH Z codes may require social services support to 
address a need post-discharge, but the complexity of the inpatient 
clinical services is not affected. A commenter, while supportive of the 
consideration of the change in designation, expressed concern that 
increasing the severity level of the codes that describe homelessness 
from a NonCC to a CC could potentially lead to fraudulent or abusive 
coding practices in order to raise the payment rate for an encounter. 
Another commenter recommended that safeguards be put in place to 
disallow oversight agencies (such as Recovery Audit Contractors (RAC) 
and third-party

[[Page 48872]]

payer validations) from challenging MS-DRG assignment, and instead 
honor the reporting of the code when supported by documentation, 
especially in instances where homelessness might be the only 
complication or comorbidity coded.
    While commending CMS' efforts, many commenters cautioned that 
mandating the reporting of SDOH Z codes could necessitate making 
changes to the institutional claim form. Currently, only 25 diagnoses 
are captured on the electronic claim form. Commenters noted that 
documenting and reporting the social and economic circumstances 
patients may be experiencing may require a substantial number of SDOH Z 
codes, and stated that this could lead to the crowding out of other 
diagnosis codes that also need to be captured on the claim form such as 
codes for medical diagnoses, comorbidities, Hierarchical Condition 
Category (HCC) coding, Hospital Acquired Conditions (HAC), and patient 
safety indicators (PSI) due to limited space.
    Several commenters expressed concern and stated that they did not 
believe that CMS proposed a clear, compelling, or significant benefit 
to patients as a result of collecting this data. These commenters 
cautioned against requiring hospitals to implement the collection of 
sensitive information for the purposes of analysis, and asserted that 
CMS will be placing hospitals in the precarious position of asking 
sensitive and intimate social questions, while often not having 
solutions to mitigate or eliminate these risks, as they stated the 
documentation of social risks does not in and of itself improve health 
outcomes. A commenter stated that studies have shown that many 
providers are wary of screening for social needs, if they believe they 
do not also have the ability to make referrals or to connect patients 
to resources to address their needs. Other commenters expressed concern 
and stated it is counterproductive for hospitals to collect SDOH data 
without having resources and pathways in place to offer help. A few 
commenters stated that by requiring medical facilities to report this 
data, CMS is diverting resources and time from patient care and stated 
that CMS should not be pursing an initiative that is meant to collect 
data on non-medical information. A commenter stated that although the 
collection of SDOH information can occur during inpatient visits, 
documentation and reporting of this data may be actually best suited to 
outpatient office visits, where providers may have a greater 
opportunity to interact with their patients and the ability to consider 
more proactive approaches to help address their social needs.
    Many other commenters also expressed concern and stated that while 
SDOH information can be useful for administrative use and payment 
adjustment, information about an individual's social risk and needs has 
been shown to be sensitive, and individuals are often hesitant to 
disclose this information for fear of bias, misuse, or discrimination. 
Commenters stated patients may not see the relevance of providing 
information to their providers related to SDOH that may not be directly 
applicable to why they are seeking care. These commenters stated that 
there are significant concerns from physicians, other providers, and 
patients about ``medicalizing'' SDOH in the electronic health record 
and stated mechanisms must be established to shield this sensitive 
information on certain forms, charts, health records, and discharge 
papers. Commenters noted that when SDOH Z codes are entered via an EHR 
or other form of collection, those results show up on the patient's 
after-visit summary, which may be concerning for patients. Commenters 
also expressed concern that SDOH Z codes may ``follow'' a patient for 
too many years and cause potential discrimination, bias, or other 
misunderstandings in the future. Commenters stated that hospitals must 
be equipped with tools to communicate the context of SDOH Z codes with 
patients at the point of screening or self-reporting so that patients 
understand the rationale for data collection and how it can help 
address their needs. Several commenters stated that CMS should also put 
in place Conditions of Participation requiring hospitals to train their 
staff on how this information can and cannot be used to prevent 
information being used in discriminatory pricing, care, or other 
purposes.
    Many commenters stated that the most immediate and important action 
CMS could take to increase the use of SDOH Z codes is to finalize the 
evidence-based ``Screening for Social Drivers of Health'' and ``Screen 
Positive Rate for Social Drivers of Health'' measures proposed to be 
adopted in the Hospital Inpatient Quality Reporting (IQR) Program. 
These commenters stated that these measures create an opportunity to 
collect inpatient SDOH data at a scale that could significantly improve 
MS-DRGs' precision and ability to recognize severity and complexity of 
service and utilization of resources. Many commenters stated that 
absent these measures and associated data, SDOH Z codes will continue 
to be underreported and unreliable. We refer the reader to section 
IX.E.5.b of the preamble of the proposed rule and this final rule for 
further discussion regarding new measures for the Hospital IQR Program 
measure set. These commenters urged CMS to start with an incremental 
approach in requiring the reporting of SDOH Z codes and suggested that 
reporting should be optional or voluntary for at least two-three years 
to allow providers and CMS to gain experience in reporting and 
collecting this data. If the reporting of the SDOH Z codes becomes 
mandatory, these commenters recommended that the requirement start with 
the subset of SDOH Z codes that directly align with the social needs 
identified in the five core domains of the proposed measures.
    Response: We again thank commenters for sharing their views and 
their willingness to support CMS in these efforts. We will take the 
commenters' feedback into consideration in future policy development.
e. Additions and Deletions to the Diagnosis Code Severity Levels for FY 
2023
    In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28181) we noted 
the following tables identify the proposed additions and deletions to 
the diagnosis code MCC severity levels list and the proposed additions 
and deletions to the diagnosis code CC severity levels list for FY 2023 
and are available via the internet on the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html
    Table 6I.1--Proposed Additions to the MCC List--FY 2023;
    Table 6I.2--Proposed Deletions to the MCC List--FY 2023;
    Table 6J.1--Proposed Additions to the CC List--FY 2023; and
    Table 6J.2--Proposed Deletions to the CC List--FY 2023.
    Comment: Commenters agreed with the proposed additions and 
deletions to the MCC and CC lists as shown in tables 6I.1, 6I.2, 6J.1, 
and 6J.2 associated with the proposed rule.
    Response: We appreciate the commenters' support.
    The following tables associated with this final rule reflect the 
finalized severity levels under Version 40 of the ICD-10 MS-DRGs for FY 
2023 and are available via the internet on the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS; Table 6I. --Complete MCC List--FY 2023; Table

[[Page 48873]]

6I.1--Additions to the MCC List--FY 2023; Table 6I.2--Deletions to the 
MCC List--FY 2022; Table 6J.--Complete CC List--FY 2023; Table 6J.1--
Additions to the CC List--FY 2023; and Table 6J.2--Deletions to the CC 
List--FY 2023.
f. CC Exclusions List for FY 2023
    In the September 1, 1987 final notice (52 FR 33143) concerning 
changes to the DRG classification system, we modified the GROUPER logic 
so that certain diagnoses included on the standard list of CCs would 
not be considered valid CCs in combination with a particular principal 
diagnosis. We created the CC Exclusions List for the following reasons: 
(1) to preclude coding of CCs for closely related conditions; (2) to 
preclude duplicative or inconsistent coding from being treated as CCs; 
and (3) to ensure that cases are appropriately classified between the 
complicated and uncomplicated DRGs in a pair.
    In the May 19, 1987 proposed notice (52 FR 18877) and the September 
1, 1987 final notice (52 FR 33154), we explained that the excluded 
secondary diagnoses were established using the following five 
principles:
     Chronic and acute manifestations of the same condition 
should not be considered CCs for one another.
     Specific and nonspecific (that is, not otherwise specified 
(NOS)) diagnosis codes for the same condition should not be considered 
CCs for one another.
     Codes for the same condition that cannot coexist, such as 
partial/total, unilateral/bilateral, obstructed/unobstructed, and 
benign/malignant, should not be considered CCs for one another.
     Codes for the same condition in anatomically proximal 
sites should not be considered CCs for one another.
     Closely related conditions should not be considered CCs 
for one another.
    The creation of the CC Exclusions List was a major project 
involving hundreds of codes. We have continued to review the remaining 
CCs to identify additional exclusions and to remove diagnoses from the 
master list that have been shown not to meet the definition of a CC. We 
refer readers to the FY 2014 IPPS/LTCH PPS final rule (78 FR 50541 
through 50544) for detailed information regarding revisions that were 
made to the CC and CC Exclusion Lists under the ICD-9-CM MS-DRGs.
    The ICD-10 MS-DRGs Version 39.1 CC Exclusion List is included as 
Appendix C in the ICD-10 MS-DRG Definitions Manual, which is available 
via the internet on the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html, and 
includes two lists identified as Part 1 and Part 2. Part 1 is the list 
of all diagnosis codes that are defined as a CC or MCC when reported as 
a secondary diagnosis. For all diagnosis codes on the list, a link is 
provided to a collection of diagnosis codes which, when reported as the 
principal diagnosis, would cause the CC or MCC diagnosis to be 
considered as a NonCC. Part 2 is the list of diagnosis codes designated 
as a MCC only for patients discharged alive; otherwise, they are 
assigned as a NonCC.
    In the FY 2023 IPPS/LTCH PPS proposed rule, we proposed additional 
changes to the ICD-10 MS-DRGs Version 40 CC Exclusion List based on the 
diagnosis and procedure code updates as discussed in section II.D.14. 
of the proposed rule and set forth in Tables 6G.1, 6G.2, 6H.1, and 6H.2 
associated with the proposed rule and available via the internet on the 
CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS.
    As discussed in section II.D.14 of the preamble of this final rule, 
we are finalizing, without modification, the proposed assignments and 
designations for the diagnosis codes after consideration of the public 
comments received. Therefore, the finalized CC Exclusions List as 
displayed in Tables 6G.1, 6G.2, 6H.1, 6H.2, and 6K, associated with 
this final rule reflect the severity levels under V40 of the ICD-10 MS-
DRGs. We have developed Table 6G.1.--Secondary Diagnosis Order 
Additions to the CC Exclusions List--FY 2023; Table 6G.2.--Principal 
Diagnosis Order Additions to the CC Exclusions List--FY 2023; Table 
6H.1.--Secondary Diagnosis Order Deletions to the CC Exclusions List--
FY 2023; and Table 6H.2.--Principal Diagnosis Order Deletions to the CC 
Exclusions List--FY 2023; and Table 6K. Complete List of CC 
Exclusions--FY 2023.
    For Table 6G.1, each secondary diagnosis code finalized for 
addition to the CC Exclusion List is shown with an asterisk and the 
principal diagnoses finalized to exclude the secondary diagnosis code 
are provided in the indented column immediately following it. For Table 
6G.2, each of the principal diagnosis codes for which there is a CC 
exclusion is shown with an asterisk and the conditions finalized for 
addition to the CC Exclusion List that will not count as a CC are 
provided in an indented column immediately following the affected 
principal diagnosis. For Table 6H.1, each secondary diagnosis code 
finalized for deletion from the CC Exclusion List is shown with an 
asterisk followed by the principal diagnosis codes that currently 
exclude it. For Table 6H.2, each of the principal diagnosis codes is 
shown with an asterisk and the finalized deletions to the CC Exclusions 
List are provided in an indented column immediately following the 
affected principal diagnosis. Tables 6G.1, 6G.2, 6H.1, and 6H.2 
associated with this final rule are available via the internet on the 
CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html.
    The ICD-10 MS-DRGs Version 40 CC Exclusion List is included as 
Appendix C of the Definitions Manual (available in two formats; text 
and HTML). The manuals are available via the internet on the CMS 
website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software and each 
format includes two lists identified as Part 1 and Part 2. Part 1 is 
the list of all diagnosis codes that are defined as a CC or MCC when 
reported as a secondary diagnosis. For all diagnosis codes on the list, 
a link (HTML version) is provided to a collection of diagnosis codes 
which, when used as the principal diagnosis, would cause the CC or MCC 
diagnosis to be considered as a NonCC. Part 2 is the list of diagnosis 
codes designated as a MCC only for patients discharged alive; 
otherwise, they are assigned as a NonCC.
14. Changes to the ICD-10-CM and ICD-10-PCS Coding Systems
    To identify new, revised and deleted diagnosis and procedure codes, 
for FY 2023, we have developed Table 6A.--New Diagnosis Codes, Table 
6B.--New Procedure Codes, Table 6C.--Invalid Diagnosis Codes, Table 
6D.--Invalid Procedure Codes, and Table 6E.--Revised Diagnosis Code 
Titles for this final rule.
    These tables are not published in the Addendum to the proposed rule 
or final rule, but are available via the internet on the CMS website 
at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html as described in section VI. of the 
Addendum to this final rule. As discussed in section II.D.17. of the 
preamble of the proposed rule and this final rule, the code titles are 
adopted as part of the ICD-10 Coordination and Maintenance Committee 
meeting process. Therefore, although we publish the code titles in the 
IPPS proposed and final rules, they are not subject to comment in the 
proposed or final rules.

[[Page 48874]]

    We are finalizing the MDC and MS-DRG assignments for the new 
diagnosis codes and procedure codes as set forth in Table 6A.--New 
Diagnosis Codes and Table 6B.--New Procedure Codes. In addition, the 
finalized severity level designations for the new diagnosis codes are 
set forth in Table 6A. and the finalized O.R. status for the new 
procedure codes are set forth in Table 6B. Consistent with our 
established process, we examined the MS-DRG assignment and the 
attributes (severity level and O.R. status) of the predecessor 
diagnosis or procedure code, as applicable, to inform our finalized 
assignments and designations.
    Specifically, we review the predecessor code and MS-DRG assignment 
most closely associated with the new diagnosis or procedure code, and 
in the absence of claims data, we consider other factors that may be 
relevant to the MS-DRG assignment, including the severity of illness, 
treatment difficulty, complexity of service and the resources utilized 
in the diagnosis or treatment of the condition. We note that this 
process does not automatically result in the new diagnosis or procedure 
code being proposed for assignment to the same MS-DRG or to have the 
same designation as the predecessor code.
    We are making available on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html 
the following tables associated with this final rule:

 Table 6A.--New Diagnosis Codes--FY 2023
 Table 6B.--New Procedure Codes--FY 2023
 Table 6C.--Invalid Diagnosis Codes--FY 2023
 Table 6D.--Invalid Procedure Codes--FY 2023
 Table 6E.--Revised Diagnosis Code Titles--FY 2023
 Table 6G.1.--Secondary Diagnosis Order Additions to the CC 
Exclusions List--FY 2023
 Table 6G.2.--Principal Diagnosis Order Additions to the CC 
Exclusions List--FY 2023
 Table 6H.1.--Secondary Diagnosis Order Deletions to the CC 
Exclusions List--FY 2023
 Table 6H.2.--Principal Diagnosis Order Deletions to the CC 
Exclusions List--FY 2023
 Table 6I.--Complete MCC List--FY 2023
 Table 6I.1.--Additions to the MCC List--FY 2023
 Table 6I.2.--Deletions to the MCC List--FY 2023
 Table 6J.--Complete CC List--FY 2023
 Table 6J.1.--Additions to the CC List--FY 2023
 Table 6J.2.--Deletions to the CC List--FY 2023
 Table 6K.--Complete List of CC Exclusions--FY 2023.
15. Changes to the Medicare Code Editor (MCE)
    The Medicare Code Editor (MCE) is a software program that detects 
and reports errors in the coding of Medicare claims data. Patient 
diagnoses, procedure(s), and demographic information are entered into 
the Medicare claims processing systems and are subjected to a series of 
automated screens. The MCE screens are designed to identify cases that 
require further review before classification into an MS-DRG.
    As discussed in the FY 2022 IPPS/LTCH PPS final rule (86 FR 44936), 
we made available the FY 2022 ICD-10 MCE Version 39 manual file. The 
manual contains the definitions of the Medicare code edits, including a 
description of each coding edit with the corresponding diagnosis and 
procedure code edit lists. The link to this MCE manual file, along with 
the link to the mainframe and computer software for the MCE Version 39 
(and ICD-10 MS-DRGs) are posted on the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software.
    In the FY 2023 IPPS/LTCH PPS proposed rule, we discussed the 
proposals we were making based on our internal review and analysis. We 
noted that we did not receive any specific MCE requests by the November 
1, 2021 deadline. In this FY 2023 IPPS/LTCH PPS final rule, we present 
a summation of the comments we received in response to the MCE 
proposals presented based on internal review and analyses in the 
proposed rule, our responses to those comments, and our finalized 
policies.
    In addition, as a result of new and modified code updates approved 
after the annual spring ICD-10 Coordination and Maintenance Committee 
meeting, we routinely make changes to the MCE. In the past, in both the 
IPPS proposed and final rules, we have only provided the list of 
changes to the MCE that were brought to our attention after the prior 
year's final rule. We historically have not listed the changes we have 
made to the MCE as a result of the new and modified codes approved 
after the annual spring ICD-10 Coordination and Maintenance Committee 
meeting. These changes are approved too late in the rulemaking schedule 
for inclusion in the proposed rule. Furthermore, although our MCE 
policies have been described in our proposed and final rules, we have 
not provided the detail of each new or modified diagnosis and procedure 
code edit in the final rule. However, we make available the finalized 
Definitions of Medicare Code Edits (MCE) file. Therefore, we are making 
available the FY 2023 ICD-10 MCE Version 40 Manual file, along with the 
link to the mainframe and computer software for the MCE Version 40 (and 
ICD-10 MS-DRGs), on the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software.
a. External Causes of Morbidity Codes as Principal Diagnosis
    In the MCE, the external cause codes (V, W, X, or Y codes) describe 
the circumstance causing an injury, not the nature of the injury, and 
therefore should not be used as a principal diagnosis.
    As discussed in section II.D.14. of the preamble of the proposed 
rule and this final rule, Table 6C.--Invalid Diagnosis Codes, lists the 
diagnosis codes that are no longer effective as of October 1, 2022. 
Included in this table are codes currently subject to the External 
causes of morbidity codes as principal diagnosis edit. We proposed to 
delete the ICD-10-CM diagnosis codes shown in Table 6P.6a associated 
with the proposed rule and available via the internet on the CMS 
website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS that are currently subject to the External 
causes of morbidity codes as principal diagnosis edit since they will 
no longer be valid for reporting purposes.
    Comment: Commenters agreed with CMS's proposal to remove the 
diagnosis codes listed in Table 6P.6a from the External Causes of 
Morbidity edit code list since they are no longer valid.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to delete the diagnosis codes listed in Table 
6P.6a associated with the proposed rule from the External Causes of 
Morbidity edit code list under the ICD-10 MCE Version 40, effective 
October 1, 2022.
b. Age Conflict Edit
    In the MCE, the Age conflict edit exists to detect inconsistencies 
between a patient's age and any diagnosis on the patient's record; for 
example, a 5-year-

[[Page 48875]]

old patient with benign prostatic hypertrophy or a 78-year-old patient 
coded with a delivery. In these cases, the diagnosis is clinically and 
virtually impossible for a patient of the stated age. Therefore, either 
the diagnosis or the age is presumed to be incorrect. Currently, in the 
MCE, the following four age diagnosis categories appear under the Age 
conflict edit and are listed in the manual and written in the software 
program:
     Perinatal/Newborn--Age 0 years only; a subset of diagnoses 
which will only occur during the perinatal or newborn period of age 0 
(for example, tetanus neonatorum, health examination for newborn under 
8 days old).
     Pediatric--Age is 0-17 years inclusive (for example, 
Reye's syndrome, routine child health exam).
     Maternity--Age range is 9-64 years inclusive (for example, 
diabetes in pregnancy, antepartum pulmonary complication).
     Adult--Age range is 15-124 years inclusive (for example, 
senile delirium, mature cataract).
(1) Maternity Diagnoses
    Under the ICD-10 MCE, the Maternity diagnoses category for the Age 
conflict edit considers the age range of 9 to 64 years inclusive. For 
that reason, the diagnosis codes on this Age conflict edit list would 
be expected to apply to conditions or disorders specific to that age 
group only.
    As discussed in section II.D.14. of the preamble of the proposed 
rule and this final rule, Table 6A.--New Diagnosis Codes, lists the 
diagnosis codes that have been approved to date which will be effective 
with discharges on and after October 1, 2022. We proposed to add new 
ICD-10-CM diagnosis codes to the edit code list for the Maternity 
diagnoses category as shown in Table 6P.6b associated with the proposed 
rule and available via the internet on the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS 
under the Age conflict edit.
    Comment: Commenters agreed with CMS's proposal to add the diagnosis 
codes listed in Table 6P.6b to the Maternity diagnoses edit code list.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to add the diagnosis codes as shown in Table 
6P.6b associated with the proposed rule to the Maternity diagnoses edit 
code list.
    In addition, as discussed in section II.D.14. of the preamble of 
the proposed rule and this final rule, Table 6C.--Invalid Diagnosis 
Codes, lists the diagnosis codes that are no longer effective as of 
October 1, 2022. We proposed to delete the following diagnosis codes 
from the Maternity diagnoses edit code list.
[GRAPHIC] [TIFF OMITTED] TR10AU22.059

    Comment: Commenters agreed with CMS's proposal to remove the 
diagnosis codes listed in the previous table from the Maternity 
diagnoses edit code list since they are no longer valid.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to remove the diagnosis codes listed in the 
previous table from the Maternity diagnoses edit code list under the 
ICD-10 MCE Version 40, effective October 1, 2022.
(2) Adult Diagnoses
    Under the ICD-10 MCE, the Adult diagnoses category for the Age 
conflict edit considers the age range of 15 to 124 years inclusive. For 
that reason, the diagnosis codes on this Age conflict edit list would 
be expected to apply to conditions or disorders specific to that age 
group only.
    As discussed in section II.D.14. of the preamble of the proposed 
rule and this final rule, Table 6A.--New Diagnosis Codes, lists the 
diagnosis codes that have been approved which will be effective with 
discharges on and after October 1, 2022. We proposed to add the 
following new ICD-10-CM diagnosis codes to the edit code list for the 
Adult diagnoses category under the Age conflict edit.

[[Page 48876]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.060

    Comment: Commenters agreed with CMS's proposal to add the diagnosis 
codes listed in the previous table to the Adult diagnoses edit code 
list.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to add the diagnosis codes listed in the 
previous table to the Adult diagnoses edit code list under the ICD-10 
MCE Version 40, effective October 1, 2022.
    In addition, as discussed in section II.D.14. of the preamble of 
the proposed rule and this final rule, Table 6C.--Invalid Diagnosis 
Codes, lists the diagnosis codes that are no longer effective as of 
October 1, 2022. We proposed to delete the following codes from the 
Adult diagnoses edit code list.

[[Page 48877]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.061

    Comment: Commenters agreed with CMS's proposal to remove the 
diagnosis codes listed in the previous table from the Adult diagnoses 
edit code list since they are no longer valid.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to remove the diagnosis codes listed in the 
previous table from the Adult diagnoses edit code list under the ICD-10 
MCE Version 40, effective October 1, 2022.
c. Sex Conflict Edit
    In the MCE, the Sex conflict edit detects inconsistencies between a 
patient's sex and any diagnosis or procedure on the patient's record; 
for example, a male patient with cervical cancer (diagnosis) or a 
female patient with a prostatectomy (procedure). In both instances, the 
indicated diagnosis or the procedure conflicts with the stated sex of 
the patient. Therefore, the patient's diagnosis, procedure, or sex is 
presumed to be incorrect.
    Comment: A commenter requested clarification on how the sex 
conflict edits consider patients who identify as transgender.
    Response: The sex conflict edit under the MCE is consistent with 45 
CFR 170.207(n) which states that birth sex must be coded as Male, 
Female or Unknown. Gender identity is a separate data element under 45 
CFR 170.207(o). We note that any proposed changes to account for gender 
identity on the CMS-1450 form would need to be submitted to the 
National Uniform Billing Committee (NUBC) for consideration.
    Comment: Another commenter expressed concerns about the existing 
ICD-10 codes and edits that appear to be sex specific (that is, male 
only or female only). According to the commenter, reporting of these 
codes for patients who identify as transgender may result in treatment 
being delayed or denied. The commenter acknowledged the necessity in 
aligning a patient's historical health data with that of their gender 
identity and personal anatomy, however, according to the commenter, 
removal of sex specific codes from the MCE would be beneficial for 
nonbinary people as well.
    Another commenter stated that transgender individuals may be 
alienated and deterred from seeking medical care in the future as a 
result of inappropriate claims denial due to the Sex conflict edit. The 
commenter stated that obstetricians-gynecologists specifically have 
conveyed the need to document and report a patient's gender identity in 
combination with their sex to provide quality, patient-centered care. 
The commenter also stated they have made recommendations to the Office 
of the National Coordinator for Health Information Technology (ONC) to 
include the data element ``gender'' in its minimum certification 
criteria for electronic health records. The commenter recommended that 
CMS work with ONC to ensure that automated claim editors, like the MCE, 
do not require obstetrician-gynecologists and other health care 
professionals to misrepresent their patients' genders to provide the 
appropriate clinical care. Lastly, the commenter encouraged CMS to 
continue its efforts to reduce the administrative burden by adapting 
the MCE and other systems to fit the needs of all physicians and their 
patients.
    Response: We appreciate the commenters' feedback. We intend to 
explore alternative options that may help to address the challenges 
described by the commenters with claims processing for individuals who 
identify as transgender or nonbinary.. We are interested in feedback 
and comments on other ways for which these issues could be considered 
from a process, systems and operational perspective. Comments should be 
directed to the new electronic intake system, Medicare Electronic 
Application Request Information SystemTM 
(MEARISTM), discussed in section II.D.1.b of the preamble of 
the proposed rule and this final rule at: https://mearis.cms.gov/public/home by October 20, 2022
(1) Diagnoses for Females Only Edit
    As discussed in section II.D.14. of the preamble of the proposed 
rule and this final rule, Table 6A.--New Diagnosis Codes, lists the new 
diagnosis codes that have been approved to date which will be effective 
with discharges on and after October 1, 2022. We proposed to add new 
ICD-10-CM diagnosis codes to the edit code list for the Diagnoses for 
females only category as shown in Table 6P.6c associated with the 
proposed rule and available via the internet on the CMS website at: 
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS under the Sex conflict edit.
    Comment: Commenters agreed with CMS's proposal to add the diagnosis 
codes listed in Table 6P.6c to the Diagnoses for females only edit code 
list.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to add the diagnosis codes as shown in Table 
6P.6c associated with the proposed rule to the Diagnoses for females 
only edit code list.
    In addition, as discussed in section II.D.14. of the preamble of 
the proposed rule and this final rule, Table 6C.--Invalid Diagnosis 
Codes, lists the diagnosis codes that are no longer effective as of 
October 1, 2022. We proposed to delete the following codes from the 
Diagnoses for females only edit code list.

[[Page 48878]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.062

    Comment: Commenters agreed with CMS's proposal to remove the 
diagnosis codes listed in the previous table from the Diagnoses for 
females only edit code list since they are no longer valid.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to remove the diagnosis codes listed in the 
previous table from the Diagnoses for female only edit code list under 
the ICD-10 MCE Version 40, effective October 1, 2022.
(2) Procedures for Males Only
    As discussed in section II.D.14. of the preamble of the proposed 
rule and this final rule, Table 6B.--New Procedure Codes, lists the new 
procedure codes that have been approved to date which will be effective 
with discharges on and after October 1, 2022. Included in this table 
are the following procedure codes we proposed to add to the edit code 
list for the Procedures for males only category under the Sex conflict 
edit.
[GRAPHIC] [TIFF OMITTED] TR10AU22.063

    Comment: Commenters agreed with CMS's proposal to add the diagnosis 
codes listed in the previous table to the Procedures for males only 
edit code list.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to add the diagnosis codes listed in the 
previous table to the Procedures for males only

[[Page 48879]]

edit code list under the ICD-10 MCE Version 40, effective October 1, 
2022.
d. Manifestation Code as Principal Diagnosis Edit
    In the ICD-10-CM classification system, manifestation codes 
describe the manifestation of an underlying disease, not the disease 
itself, and therefore should not be used as a principal diagnosis.
    As discussed in section II.D.14. of the preamble of the proposed 
rule and this final rule, Table 6A.--New Diagnosis Codes, lists the new 
diagnosis codes that have been approved which will be effective with 
discharges on and after October 1, 2022. Included in this table are the 
following new ICD-10-CM diagnosis codes that we proposed to add to the 
edit code list for the Manifestation code as principal diagnosis edit, 
because the disease itself would be required to be reported first.
[GRAPHIC] [TIFF OMITTED] TR10AU22.064

    Comment: Commenters agreed with CMS's proposal to add the diagnosis 
codes listed in the previous table to the Manifestation code as 
principal diagnosis edit code list.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to add the diagnosis codes listed in the 
previous table to the Manifestation code as principal diagnosis edit 
code list under the ICD-10 MCE Version 40, effective October 1, 2022.
    In addition, as discussed in section II.D.14. of the preamble of 
the proposed rule and this final rule, Table 6C.--Invalid Diagnosis 
Codes, lists the diagnosis codes that are no longer effective as of 
October 1, 2022. Included in this table is ICD-10-CM diagnosis code 
F02.81 (Dementia in other diseases classified elsewhere with behavioral 
disturbance), that is currently listed on the edit code list for the 
Manifestation code as principal diagnosis edit. We proposed to delete 
this code from the Manifestation code as principal diagnosis edit code 
list.
    Comment: Commenters agreed with CMS's proposal to remove diagnosis 
code F02.81 from the Manifestation code as principal diagnosis edit 
code list since it is no longer valid.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to remove diagnosis code F02.81 from the 
Manifestation code as principal diagnosis edit code list under the ICD-
10 MCE Version 40, effective October 1, 2022.
e. Unacceptable Principal Diagnosis Edit
    In the MCE, there are select codes that describe a circumstance 
which influences an individual's health status but does not actually 
describe a current illness or injury. There also are codes that are not 
specific manifestations but may be due to an underlying cause. These 
codes are considered unacceptable as a principal diagnosis. In limited 
situations, there are a few codes on the MCE Unacceptable Principal 
Diagnosis edit code list that are considered ``acceptable'' when a 
specified secondary diagnosis is also coded and reported on the claim.
    As discussed in section II.D.14. of the preamble of the proposed 
rule and this final rule, Table 6A.--New Diagnosis Codes, lists the new 
diagnosis codes that have been approved which will be effective with 
discharges on and after October 1, 2022. Additionally, as discussed in 
section II.D.1.b of the preamble of the proposed rule and this final 
rule, we provided a test version of the ICD-10 MS-DRG GROUPER Software, 
Version 40, so that the public could better analyze and understand the

[[Page 48880]]

impact of the proposals included in the proposed rule. We noted that at 
the time of the development of the test software, a subset of the 
listed codes (F01.511 through F01.C4) that were proposed for this edit 
were unable to be included and therefore, the test software does not 
reflect these codes. We proposed to add the following new ICD-10-CM 
diagnosis codes to the Unacceptable Principal Diagnosis edit code list.
[GRAPHIC] [TIFF OMITTED] TR10AU22.065


[[Page 48881]]


[GRAPHIC] [TIFF OMITTED] TR10AU22.066

    Comment: Commenters agreed with our proposal to add the diagnosis 
codes listed in the previous table to the Unacceptable Principal 
Diagnosis edit code list.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to add the diagnosis codes listed in the 
previous table to the Unacceptable Principal Diagnosis edit code list 
under the ICD-10 MCE Version 40, effective October 1, 2022.
    In addition, as discussed in section II.D.14. of the preamble of 
the proposed rule and this final rule, Table 6C.--Invalid Diagnosis 
Codes, lists the diagnosis codes that are no longer effective as of 
October 1, 2022. We proposed to delete the following codes from the 
Unacceptable Principal Diagnosis edit code list.
[GRAPHIC] [TIFF OMITTED] TR10AU22.067

    Comment: Commenters agreed with CMS's proposal to remove diagnosis 
codes Z87.76, Z91.11, and Z91.19 from the Unacceptable principal 
diagnosis edit code list since they are no longer valid.
    Response: We appreciate the commenters' support. After 
consideration of the public comments we received, we are finalizing our 
proposal to remove the diagnosis codes listed in the previous table 
from the Unacceptable Principal Diagnosis edit code list under the ICD-
10 MCE Version 40, effective October 1, 2022.

[[Page 48882]]

f. Unspecified Code
    In the FY 2022 IPPS/LTCH PPS final rule (86 FR 44940 through 
44943), we finalized the implementation of a new Unspecified code edit, 
effective with discharges on and after April 1, 2022. Unspecified codes 
exist in the ICD-10-CM classification for circumstances when 
documentation in the medical record does not provide the level of 
detail needed to support reporting a more specific code. However, in 
the inpatient setting, there should generally be very limited and rare 
circumstances for which the laterality (right, left, bilateral) of a 
condition is unable to be documented and reported.
    As discussed in section II.D.14. of the preamble of the proposed 
rule and this final rule, Table 6A.--New Diagnosis Codes, lists the new 
diagnosis codes that have been approved to date which will be effective 
with discharges on and after October 1, 2022. We proposed to add the 
following new ICD-10-CM diagnosis codes to the Unspecified code edit 
code list.
[GRAPHIC] [TIFF OMITTED] TR10AU22.068

    Comment: Commenters agreed with our proposal to add the diagnosis 
codes listed in the previous table to the Unspecified code edit code 
list.
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to add the diagnosis codes listed in the 
previous table to the Unspecified code edit code list under the ICD-10 
MCE Version 40, effective October 1, 2022.
g. Future Enhancement
    In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38053 through 38054) 
we noted the importance of ensuring accuracy of the coded data from the 
reporting, collection, processing, coverage, payment and analysis 
aspects. Subsequently, in the FY 2019 IPPS/LTCH PPS proposed rule (83 
FR 20235) we stated that we engaged a contractor to assist in the 
review of the limited coverage and non-covered procedure edits in the 
MCE that may also be present in other claims processing systems that 
are utilized by our MACs. The MACs must adhere to criteria specified 
within the National Coverage Determinations (NCDs) and may implement 
their own edits in addition to what is already incorporated into the 
MCE, resulting in duplicate edits. The objective of this review is to 
identify where duplicate edits may exist and to determine what the 
impact might be if these edits were to be removed from the MCE.
    We have also noted that the purpose of the MCE is to ensure that 
errors and inconsistencies in the coded data are recognized during 
Medicare claims processing. As we indicated in the FY 2019 IPPS/LTCH 
PPS final rule (83 FR 41228), we are considering whether the inclusion 
of coverage edits in the MCE necessarily aligns with that specific goal 
because the focus of coverage edits is on whether or not a particular 
service is covered for payment purposes and not whether it was coded 
correctly.
    Comment: A few commenters requested that CMS continue to include 
the existing coverage edits in the MCE. According to the commenters, 
the MACs software and systems may not be consistently updated and 
current, therefore, coding edits may trigger erroneously only to be 
dismissed on appeal when it is discovered that the code in question is 
covered under an NCD. The commenters stated their belief that the 
national MCE provides important safeguards for claims processing and 
coverage.
    Response: We appreciate the commenters' feedback.
    As we continue to evaluate the purpose and function of the MCE with 
respect to ICD-10, we encourage public input for future discussion. As 
we have discussed in prior rulemaking, we recognize a need to further 
examine the current list of edits and the definitions of those edits.
    We continue to encourage public comments on whether there are 
additional concerns with the current edits, including specific edits or 
language that should be removed or revised, edits that should be 
combined, or new edits that should be added to assist in detecting 
errors or inaccuracies in the coded data. Comments should be directed 
to the new electronic intake system, Medicare Electronic Application 
Request Information SystemTM (MEARISTM), 
discussed in section II.D.1.b of the preamble of the proposed rule and 
this final rule at: https://mearis.cms.gov/public/home by October 20, 
2022.
16. Changes to Surgical Hierarchies
    Some inpatient stays entail multiple surgical procedures, each one 
of which, occurring by itself, could result in assignment of the case 
to a different MS-DRG within the MDC to which the principal diagnosis 
is assigned. Therefore, it is necessary to have a decision rule within 
the GROUPER by which these cases are assigned to a single MS-DRG. The 
surgical hierarchy, an ordering of surgical classes from most resource-
intensive to least resource-intensive, performs that function. 
Application of this hierarchy ensures that cases involving multiple 
surgical procedures are assigned to the MS-DRG associated with the most 
resource-intensive surgical class.
    A surgical class can be composed of one or more MS-DRGs. For 
example, in MDC 11, the surgical class ``kidney transplant'' consists 
of a single MS-DRG (MS-DRG 652) and the class ``major bladder 
procedures'' consists of three MS-DRGs (MS-DRGs 653, 654, and 655). 
Consequently, in many cases, the surgical hierarchy has an impact on 
more than one MS-DRG. The methodology for determining the most 
resource-intensive surgical class involves weighting the average 
resources for each MS-DRG by frequency to determine the weighted 
average resources for each surgical class. For example, assume surgical 
class A includes MS-DRGs 001 and 002 and surgical class B includes MS-
DRGs 003, 004, and 005. Assume also that the average costs of MS-DRG 
001 are higher than that of MS-DRG 003, but the average costs of MS-
DRGs 004 and 005 are higher than the average costs of MS-DRG 002. To 
determine whether surgical class A should be higher or lower than 
surgical class B in the surgical hierarchy, we would weigh the

[[Page 48883]]

average costs of each MS-DRG in the class by frequency (that is, by the 
number of cases in the MS-DRG) to determine average resource 
consumption for the surgical class. The surgical classes would then be 
ordered from the class with the highest average resource utilization to 
that with the lowest, with the exception of ``other O.R. procedures'' 
as discussed in this final rule.
    This methodology may occasionally result in assignment of a case 
involving multiple procedures to the lower-weighted MS-DRG (in the 
highest, most resource-intensive surgical class) of the available 
alternatives. However, given that the logic underlying the surgical 
hierarchy provides that the GROUPER search for the procedure in the 
most resource-intensive surgical class, in cases involving multiple 
procedures, this result is sometimes unavoidable.
    We note that, notwithstanding the foregoing discussion, there are a 
few instances when a surgical class with a lower average cost is 
ordered above a surgical class with a higher average cost. For example, 
the ``other O.R. procedures'' surgical class is uniformly ordered last 
in the surgical hierarchy of each MDC in which it occurs, regardless of 
the fact that the average costs for the MS-DRG or MS-DRGs in that 
surgical class may be higher than those for other surgical classes in 
the MDC. The ``other O.R. procedures'' class is a group of procedures 
that are only infrequently related to the diagnoses in the MDC, but are 
still occasionally performed on patients with cases assigned to the MDC 
with these diagnoses. Therefore, assignment to these surgical classes 
should only occur if no other surgical class more closely related to 
the diagnoses in the MDC is appropriate.
    A second example occurs when the difference between the average 
costs for two surgical classes is very small. We have found that small 
differences generally do not warrant reordering of the hierarchy 
because, as a result of reassigning cases on the basis of the hierarchy 
change, the average costs are likely to shift such that the higher-
ordered surgical class has lower average costs than the class ordered 
below it.
    Based on the changes that we proposed to make for FY 2023, as 
discussed in section II.D. of the preamble of the proposed rule and 
this final rule, we are maintaining the existing surgical hierarchy for 
FY 2023.
17. Maintenance of the ICD-10-CM and ICD-10-PCS Coding Systems
    In September 1985, the ICD-9-CM Coordination and Maintenance 
Committee was formed. This is a Federal interdepartmental committee, 
co-chaired by the Centers for Disease Control and Prevention's (CDC) 
National Center for Health Statistics (NCHS) and CMS, charged with 
maintaining and updating the ICD-9-CM system. The final update to ICD-
9-CM codes was made on October 1, 2013. Thereafter, the name of the 
Committee was changed to the ICD-10 Coordination and Maintenance 
Committee, effective with the March 19-20, 2014 meeting. The ICD-10 
Coordination and Maintenance Committee addresses updates to the ICD-10-
CM and ICD-10-PCS coding systems. The Committee is jointly responsible 
for approving coding changes, and developing errata, addenda, and other 
modifications to the coding systems to reflect newly developed 
procedures and technologies and newly identified diseases. The 
Committee is also responsible for promoting the use of Federal and non-
Federal educational programs and other communication techniques with a 
view toward standardizing coding applications and upgrading the quality 
of the classification system.
    The official list of ICD-9-CM diagnosis and procedure codes by 
fiscal year can be found on the CMS website at: https://cms.hhs.gov/Medicare/Coding/ICD9ProviderDiagnosticCodes/codes.html. The official 
list of ICD-10-CM and ICD-10-PCS codes can be found on the CMS website 
at: https://www.cms.gov/Medicare/Coding/ICD10/.
    The NCHS has lead responsibility for the ICD-10-CM and ICD-9-CM 
diagnosis codes included in the Tabular List and Alphabetic Index for 
Diseases, while CMS has lead responsibility for the ICD-10-PCS and ICD-
9-CM procedure codes included in the Tabular List and Alphabetic Index 
for Procedures.
    The ICD-10 Coordination and Maintenance Committee holds its 
meetings in the spring and fall to update the codes and the applicable 
payment and reporting systems by October 1 or April 1 of each year. 
Items are placed on the agenda for the Committee meeting if the request 
is received at least 3 months prior to the meeting. This requirement 
allows time for staff to review and research the coding issues and 
prepare material for discussion at the meeting. It also allows time for 
the topic to be publicized in meeting announcements in the Federal 
Register as well as on the CMS website.
    The Committee encourages participation in the previously mentioned 
process by health- related organizations and other interested parties. 
In this regard, the Committee holds public meetings for discussion of 
educational issues and proposed coding changes. These meetings provide 
an opportunity for representatives of recognized organizations in the 
coding field, such as the American Health Information Management 
Association (AHIMA), the American Hospital Association (AHA), and 
various physician specialty groups, as well as individual physicians, 
health information management professionals, and other members of the 
public, to contribute ideas on coding matters. After considering the 
opinions expressed during the public meetings and in writing, the 
Committee formulates recommendations, which then must be approved by 
the agencies. A complete addendum describing details of all diagnosis 
and procedure coding changes, both tabular and index, is published on 
the CMS and NCHS websites in June of each year. Publishers of coding 
books and software use this information to modify their products that 
are used by health care providers.
    The Committee presented proposals for coding changes for 
implementation in FY 2023 at a public meeting held on September 14-15, 
2021 and finalized the coding changes after consideration of comments 
received at the meetings and in writing by November 15, 2021.
    The Committee held its 2022 meeting on March 8-9, 2022. The 
deadline for submitting comments on the procedure code proposals that 
are being considered for an October 1, 2022 implementation was April 8, 
2022. The deadline for submitting comments on the diagnosis code 
proposals that are being considered for an October 1, 2023 
implementation was May 9, 2022. It was announced at this meeting that 
any new diagnosis and procedure codes for which there was consensus of 
public support and for which complete tabular and indexing changes 
would be made by June 2022 would be included in the October 1, 2022 
update to the ICD-10-CM diagnosis and ICD-10-PCS procedure code sets. 
It was also announced at this meeting that we are changing the process 
for submitting requested updates to the ICD-10-PCS classification, 
beginning with the procedure code requests submitted for consideration 
for the September 13-14, 2022 ICD-10 Coordination and Maintenance 
Committee Meeting. As stated in section II.D.1.b. of the preamble of 
the proposed rule and this final rule, CMS is in the process of 
implementing a new electronic application intake system, MEARIS\TM\. 
Effective January 5, 2022, MEARIS\TM\ became available as an initial 
release for users to begin gaining familiarity with a

[[Page 48884]]

new approach and process to submit ICD-10-PCS procedure code requests. 
Information on this new approach for submitting an ICD-10-PCS code 
request can be accessed at: https://mearis.cms.gov. Effective March 1, 
2022, the full release of MEARIS\TM\ became active for ICD-10-PCS code 
request submissions. ICD-10-PCS code request submissions were due no 
later than June 10, 2022 to be considered for the September 13-14, 2022 
ICD-10 Coordination and Maintenance Committee Meeting. Moving forward, 
CMS will only accept ICD-10-PCS code requests submitted via MEARIS\TM\. 
Requests submitted through the ICDProcedureCodeRequest mailbox will no 
longer be considered. Within MEARIS\TM\, we have built in several 
resources to support users, including a ``Resources'' section 
(available at https://mearis.cms.gov/public/resources) and technical 
support available under ``Useful Links'' at the bottom of the 
MEARIS\TM\ site. Questions regarding MEARIS\TM\ can be submitted to CMS 
using the form available under ``Contact'' at: https://mearis.cms.gov/public/resources.
    As discussed in earlier sections of the preamble of this final 
rule, there are new, revised, and deleted ICD-10-CM diagnosis codes and 
ICD-10-PCS procedure codes that are captured in Table 6A.--New 
Diagnosis Codes, Table 6B.--New Procedure Codes, Table 6C.--Invalid 
Diagnosis Codes, Table 6D.--Invalid Procedure Codes, and Table 6E.--
Revised Diagnosis Code Titles for this final rule, which are available 
via the internet on the CMS website at: https://www.cms.gov/medicare/
medicare-fee-for-service-payment/acuteinpatientpps. The code titles are 
adopted as part of the ICD-10 Coordination and Maintenance Committee 
process. Therefore, although we make the code titles available through 
tables in association with the IPPS proposed and final rules, they are 
not subject to comment in the proposed or final rule. Because of the 
length of these tables, they are not published in the Addendum to the 
proposed or final rule. Rather, they are available via the internet as 
discussed in section VI. of the Addendum to the proposed rule and this 
final rule.
    Recordings for the virtual meeting discussions of the procedure 
codes at the Committee's September 14-15, 2021 meeting and the March 8-
9, 2022 meeting can be obtained from the CMS website at: https://www.cms.gov/Medicare/Coding/ICD10/C-and-M-Meeting-Materials. The 
materials for the discussions relating to diagnosis codes at the 
September 14-15, 2021 meeting and March 8-9, 2022 meeting can be found 
through the CDC website at: https://www.cdc.gov/nchs/icd/icd10cm_maintenance.html. These websites also provide detailed 
information about the Committee, including information on requesting a 
new code, participating in a Committee meeting, timeline requirements 
and meeting dates.
    We encourage commenters to submit questions and comments on coding 
issues involving diagnosis codes via Email to: [email protected].
    Questions and comments concerning the procedure codes should be 
submitted via Email to: [email protected].
    We stated in the proposed rule that as a result of the ongoing 
COVID-19 public health emergency, the CDC implemented three new 
diagnosis codes describing immunization status related to COVID-19 into 
the ICD-10-CM effective with discharges on and after April 1, 2022.
    The diagnosis codes are as follows:
    [GRAPHIC] [TIFF OMITTED] TR10AU22.069
    
    We refer the reader to the CDC web page at https://www.cdc.gov/nchs/icd/icd10cm.htm for additional details regarding the 
implementation of these new diagnosis codes.
    As discussed in the proposed rule, we provided the MS-DRG 
assignments for the three diagnosis codes effective with discharges on 
and after April 1, 2022, consistent with our established process for 
assigning new diagnosis codes. Specifically, we review the predecessor 
diagnosis code and MS-DRG assignment most closely associated with the 
new diagnosis code, and consider other factors that may be relevant to 
the MS-DRG assignment, including the severity of illness, treatment 
difficulty, and the resources utilized for the specific condition/
diagnosis. We note that this process does not automatically result in 
the new diagnosis code being assigned to the same MS-DRG as the 
predecessor code. The assignments for the previously listed diagnosis 
codes are reflected in Table 6A.--New Diagnosis Codes associated with 
the proposed rule and available via the internet on the CMS website at 
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS. As with the other new diagnosis codes and MS-DRG 
assignments included in Table 6A in association with the proposed rule, 
we solicited public comments on the most appropriate MDC, MS-DRG, and 
severity level assignments for these codes for FY 2023, as well as any 
other options for the GROUPER logic.
    We did not receive any comments opposing the MDC, MS-DRG, and 
severity level assignments for the listed codes and are therefore, 
finalizing the assignments as reflected in Table 6A.--New Diagnosis 
Codes in association with this final rule.
    In addition, we noted in the proposed rule that CMS implemented 
nine new procedure codes describing the introduction or infusion of 
therapeutics, including vaccines for COVID-19prevention, into the ICD-
10-PCS effective with discharges on and after April 1, 2022. The nine 
procedure codes listed in this section of this rule are designated as 
non-O.R. and do not affect any MDC or MS-DRG assignment as shown in the 
following table.

[[Page 48885]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.070

    The ICD-10 MS-DRG assignment for cases reporting any one of the 
nine procedure codes is dependent on the reported principal diagnosis, 
any secondary diagnoses defined as a CC or MCC, procedures or services 
performed, age, sex, and discharge status. The nine procedure codes are 
reflected in Table 6B.--New Procedure Codes in association with the 
proposed rule and available via the internet on the CMS website at: 
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS. As with the other new procedure codes and MS-DRG 
assignments included in Table 6B in association with the proposed rule, 
we solicited public comments on the most appropriate MDC, MS-DRG, and 
operating room status assignments for these codes for FY 2023, as well 
as any other options for the GROUPER logic.
    We did not receive any comments opposing the MDC, MS-DRG, and 
operating room status assignments for the listed codes and are 
therefore, finalizing the assignments as reflected in Table 6B.--New 
Procedure Codes in association with this final rule.
    In the proposed rule we also noted that Change Request (CR) 12578, 
Transmittal 11174, titled ``April 2022 Update to the Medicare 
Severity--Diagnosis Related Group (MS-DRG) Grouper and Medicare Code 
Editor (MCE) Version 39.1 for the International Classification of 
Diseases, Tenth Revision (ICD-10) Diagnosis Codes for 2019 Novel 
Coronavirus (COVID-19) Vaccination Status and ICD-10 Procedure Coding 
System (PCS) Codes for Introduction or Infusion of Therapeutics and 
Vaccines for COVID-19 Treatment'', was issued on January 14, 2022 
(available via the internet on the CMS website at: https://www.cms.gov/Regulations-and-Guidance/Guidance/Transmittals/Transmittals/r11174cp) 
regarding the release of an updated version of the ICD-10 MS-DRG 
GROUPER and Medicare Code Editor software, Version 39.1, effective with 
discharges on and after April 1, 2022, reflecting the new diagnosis and 
procedure codes. The updated software, along with the updated ICD-10 
MS-DRG V39.1 Definitions Manual and the Definitions of Medicare Code 
Edits V39.1 manual is available at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software.
    In the September 7, 2001 final rule implementing the IPPS new 
technology add-on payments (66 FR 46906), we indicated we would attempt 
to include proposals for procedure codes that would describe new 
technology discussed and approved at the Spring meeting as part of the 
code revisions effective the following October.
    Section 503(a) of Public Law 108-173 included a requirement for 
updating diagnosis and procedure codes twice a year instead of a single 
update on October 1 of each year. This requirement was included as part 
of the amendments to the Act relating to recognition of new technology 
under the IPPS. Section 503(a) of Public Law 108-173 amended section 
1886(d)(5)(K) of the Act by adding a clause (vii) which states that the 
Secretary shall provide for the addition of new diagnosis and procedure 
codes on April 1 of each year, but the addition of such codes shall not 
require the Secretary to adjust the payment (or diagnosis-related group

[[Page 48886]]

classification) until the fiscal year that begins after such date. This 
requirement improves the recognition of new technologies under the IPPS 
by providing information on these new technologies at an earlier date. 
Data will be available 6 months earlier than would be possible with 
updates occurring only once a year on October 1.
    In the FY 2005 IPPS final rule, we implemented section 
1886(d)(5)(K)(vii) of the Act, as added by section 503(a) of Public Law 
108-173, by developing a mechanism for approving, in time for the April 
update, diagnosis and procedure code revisions needed to describe new 
technologies and medical services for purposes of the new technology 
add-on payment process. We also established the following process for 
making those determinations. Topics considered during the Fall ICD-10 
(previously ICD-9-CM) Coordination and Maintenance Committee meeting 
were considered for an April 1 update if a strong and convincing case 
was made by the requestor during the Committee's public meeting. The 
request needed to identify the reason why a new code was needed in 
April for purposes of the new technology process. Meeting participants 
and those reviewing the Committee meeting materials were provided the 
opportunity to comment on the expedited request. We refer the reader to 
the FY 2022 IPPS/LTCH PPS final rule (86 FR 44950) for further 
discussion of the implementation of this prior April 1 update for 
purposes of the new technology add-on payment process.
    However, as discussed in the FY 2022 IPPS/LTCH PPS final rule (86 
FR 44950 through 44956), we adopted an April 1 implementation date, in 
addition to the annual October 1 update, beginning with April 1, 2022. 
We noted that the intent of this April 1 implementation date is to 
allow flexibility in the ICD-10 code update process. With this new 
April 1 update, CMS now uses the same process for consideration of all 
requests for an April 1 implementation date, including for purposes of 
the new technology add-on payment process (that is, the prior process 
for consideration of an April 1 implementation date only if a strong 
and convincing case was made by the requestor during the meeting no 
longer applies). We are continuing to use several aspects of our 
existing established process to implement new codes through the April 1 
code update, which includes presenting proposals for April 1 
consideration at the September ICD-10 Coordination and Maintenance 
Committee meeting, requesting public comments, reviewing the public 
comments, finalizing codes, and announcing the new codes with their 
assignments consistent with the new GROUPER release information. We 
note that under our established process, requestors indicate whether 
they are submitting their code request for consideration for an April 1 
implementation date or an October 1 implementation date. The ICD-10 
Coordination and Maintenance Committee makes efforts to accommodate the 
requested implementation date for each request submitted. However, the 
Committee determines which requests are to be presented for 
consideration for an April 1 implementation date or an October 1 
implementation date. As discussed earlier in this section of the 
preamble of this final rule, there were code proposals presented for an 
expedited April 1, 2022 implementation at the September 14-15, 2021 
Committee meetings that involved treatments related to the COVID-19 
PHE. One of these code proposals was also in connection with a request 
for a new technology add-on payment application. Following the receipt 
of public comments, the code proposals were approved and finalized, 
therefore, there were new codes implemented April 1, 2022.
    As discussed in the FY 2023 IPPS/LTCH PPS proposed rule, consistent 
with the process we outlined for the April 1 implementation date, we 
announced the new codes in November 2021 and provided the updated code 
files and ICD-10-CM Official Guidelines for Coding and Reporting in 
December 2021. On January 24, 2022 the Federal Register notice for the 
March 8-9, 2022 ICD-10 Coordination and Maintenance Committee Meeting 
was published that includes the tentative agenda and identifies which 
topics are related to a new technology add-on payment application. By 
February 1, 2022 we made available the updated V39.1 ICD-10 MS-DRG 
Grouper software and related materials via the internet on CMS web page 
at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/MS-DRG-Classifications-and-Software.
    Comment: A few commenters expressed concerns with the meeting 
process and timing for the implementation of new ICD-10-CM diagnosis 
codes by the CDC/NCHS. The commenters urged CMS to work with the CDC/
NCHS on expediting the finalization of proposed new diagnosis codes in 
light of the option to implement codes on April 1. Another commenter 
expressed support for the ability of an April implementation and 
expedited diagnosis codes to improve reporting and health equity. The 
commenter requested that CMS consider utilizing this April 1 pathway to 
advance the Agency's and the health care system's equity goals, 
specifically for diagnosis codes that describe social and economic 
circumstances to more accurately reflect health care encounters and 
episodes of care while also contributing to reliability and validity of 
coded claims data.
    Response: We thank the commenters for the feedback. As we have 
noted in prior rulemaking (85 FR 58556) the CDC/NCHS has lead 
responsibility for the ICD-10-CM diagnosis classification while CMS has 
lead responsibility for the ICD-10-PCS procedure classification. Each 
organization has their own established process in responding to 
requests for code updates, including when specific topics may appear on 
the agenda of an ICD-10 Coordination and Maintenance Committee meeting 
and the fiscal year in which code proposals are considered for 
implementation.
    ICD-9-CM addendum and code title information is published on the 
CMS website at: https://www.cms.gov/Medicare/Coding/ICD9ProviderDiagnosticCodes/addendum. ICD-10-CM and ICD-10-PCS addendum 
and code title information is published on the CMS website at: https://www.cms.gov/medicare/coding/icd10. CMS also sends electronic files 
containing all ICD-10-CM and ICD-10-PCS coding changes to its Medicare 
contractors for use in updating their systems and providing education 
to providers. Information on ICD-10-CM diagnosis codes, along with the 
Official ICD-10-CM Coding Guidelines, can be found on the CDC website 
at: https://www.cdc.gov/nchs/icd/icd10cm.htm. Additionally, information 
on new, revised, and deleted ICD-10-CM diagnosis and ICD-10-PCS 
procedure codes is provided to the AHA for publication in the Coding 
Clinic for ICD-10. The AHA also distributes coding update information 
to publishers and software vendors.
    In the proposed rule we noted that for FY 2022, there are currently 
72,750 diagnosis codes and 78,229 procedure codes. We also noted that 
as displayed in Table 6A.--New Diagnosis Codes and in Table 6B.--New 
Procedure Codes associated with the proposed rule (and available via 
the internet on the CMS website at https://www.cms.gov/medicare/
medicare-fee-for-service-payment/acuteinpatientpps), there were 1,176 
new diagnosis codes and 45 new

[[Page 48887]]

procedure codes that had been finalized for FY 2023 at the time of the 
development of the proposed rule. As discussed in section II.D.14 of 
the preamble of this final rule, we are making available Table 6A.--New 
Diagnosis Codes, Table 6B.--New Procedure Codes, Table 6C.--Invalid 
Diagnosis Codes, Table 6D.--Invalid Procedure Codes and Table 6E.--
Revised Diagnosis Code Titles via the internet on the CMS website at: 
https://www.cms.gov/medicare/medicare-fee-for-service-payment/
acuteinpatientpps in association with this final rule. As shown in 
Table 6B.--New Procedure Codes, there were procedure codes discussed at 
the March 8-9, 2022 ICD-10 Coordination and Maintenance Committee 
meeting that were not finalized in time to include in the proposed rule 
and are identified with an asterisk. We refer the reader to Table 6B.--
New Procedure Codes associated with this final rule and available via 
the internet on the CMS website at: https://www.cms.gov/medicare/
medicare-fee-for-service-payment/acuteinpatientpps for the detailed 
list of these additional 286 new procedure codes. The addition of these 
286 new procedure codes to the 45 procedure codes that had been 
finalized at the time of the development of the proposed rule results 
in a total of 331 (45 + 286 = 331) new procedure codes for FY 2023.
    We also note, as reflected in Table 6C.--Invalid Diagnosis Codes 
and in Table 6D.--Invalid Procedure Codes, there are a total of 287 
diagnosis codes and 64 procedure codes that will become invalid 
effective October 1, 2022. Based on these code updates, effective 
October 1, 2022, there are a total of 73,639 ICD-10-CM diagnosis codes 
and 78,496 ICD-10-PCS procedure codes for FY 2023 as shown in the 
following table.
[GRAPHIC] [TIFF OMITTED] TR10AU22.071

    As stated previously, the public is provided the opportunity to 
comment on any requests for new diagnosis or procedure codes discussed 
at the ICD-10 Coordination and Maintenance Committee meeting. The code 
titles are adopted as part of the ICD-10 Coordination and Maintenance 
Committee process. Thus, although we publish the code titles in the 
IPPS proposed and final rules, they are not subject to comment in the 
proposed or final rules.
18. Replaced Devices Offered Without Cost or With a Credit
a. Background
    In the FY 2008 IPPS final rule with comment period (72 FR 47246 
through 47251), we discussed the topic of Medicare payment for devices 
that are replaced without cost or where credit for a replaced device is 
furnished to the hospital. We implemented a policy to reduce a 
hospital's IPPS payment for certain MS-DRGs where the implantation of a 
device that subsequently failed or was recalled determined the base MS-
DRG assignment. At that time, we specified that we will reduce a 
hospital's IPPS payment for those MS-DRGs where the hospital received a 
credit for a replaced device equal to 50 percent or more of the cost of 
the device.
    In the FY 2012 IPPS/LTCH PPS final rule (76 FR 51556 through 
51557), we clarified this policy to state that the policy applies if 
the hospital received a credit equal to 50 percent or more of the cost 
of the replacement device and issued instructions to hospitals 
accordingly.
b. Changes for FY 2023
    As discussed in the FY 2023 IPPS/LTCH PPS proposed rule, for FY 
2023 we proposed not to add any MS-DRGs to the policy for replaced 
devices offered without cost or with a credit. We proposed to continue 
to include the existing MS-DRGs currently subject to the policy as 
displayed in the following table.

[[Page 48888]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.072

[GRAPHIC] [TIFF OMITTED] TR10AU22.073

    We did not receive any public comments opposing our proposal to 
continue to include the existing MS-DRGs currently subject to the 
policy. Therefore, we are finalizing the list of MS-DRGs in the table 
included in the proposed rule and in this final rule that will be 
subject to the replaced devices offered without cost or with a credit 
policy effective October 1, 2022. The final list of MS-DRGs subject to 
the IPPS policy for replaced devices offered without cost or with a 
credit will be issued to providers in the form of a Change Request 
(CR).
19. Other Policy Issues
a. Comment Solicitation on Possible Mechanisms To Address Rare Diseases 
and Conditions Represented by Low Volumes Within the MS-DRG Structure
    As discussed in section II.D.13.d of the preamble of the proposed 
rule and this final rule, we solicited public

[[Page 48889]]

comments involving how the reporting of certain diagnosis codes may 
improve our ability to recognize severity of illness, complexity of 
service, and utilization of resources under the MS-DRGs, as well as 
feedback on mechanisms to improve the reliability and validity of the 
coded data as part of an ongoing effort across CMS to evaluate and 
develop policies to reduce health disparities. In concert with that 
effort, as discussed in the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 
28195 through 28197) we also solicited comments to explore possible 
mechanisms through which we could address rare diseases and conditions 
that are represented by low volumes in our claims data.
    We stated in the FY 2023 proposed rule that one subset of our 
beneficiary population for which we sought comment on potential issues 
related to patient access in the inpatient setting were patients 
diagnosed with rare diseases and conditions that are represented by low 
volumes in our claims data. We noted that the Orphan Drug Act (ODA) 
added section 526(a)(2)(B) to the Federal Food, Drug, and Cosmetic Act 
(21 U.S.C. 360bb(a)(2)(B)), defining a rare disease or condition as 
``any disease or condition which (A) affects less than 200,000 persons 
in the United States, or (B) affects more than 200,000 in the United 
States and for which there is no reasonable expectation that the cost 
of developing and making available in the United States a drug for such 
disease or condition will be recovered from sales in the United States 
of such drug.'' Most rare diseases, however, affect far fewer people. 
The Genetic and Rare Diseases Information Center (GARD), which was 
created in 2002 by the National Institutes of Health (NIH) Office of 
Rare Diseases Research, estimates that there are as many as 7,000 
distinct rare diseases. Rare diseases, which can include genetic 
diseases, autoimmune conditions, some cancers, and uncommon infections, 
are highly diverse, may affect many organ systems and have wide 
variations in the rates and patterns of manifestations and progression.
    The ODA created a process for the U.S. Food and Drug Administration 
(FDA) to identify a drug as a drug developed for the treatment of a 
rare disease or condition called ``orphan-drug designation''. The 
sponsor of a drug that has orphan drug designation may be eligible for 
certain financial incentives, such as tax credits and potentially seven 
years of market exclusivity after approval, all of which are intended 
to incentivize developing drugs for small numbers of patients. We 
stated that we heard from some interested parties, however, that there 
may be a number of barriers to providers in treating these patients 
with these orphan designated drugs in the Medicare hospital inpatient 
setting.
    According to these interested parties, one significant barrier that 
continues to present challenges to manufacturers is accessing formulary 
coverage for potentially high cost therapeutics for rare diseases. 
These interested parties stated that hospitals utilize formularies for 
inpatient drugs as a cost-management tool that strongly incentivizes 
physicians to use on-formulary drugs over off-formulary drugs, whenever 
clinically appropriate to do so. A drug formulary is defined as a list 
of medications and continually updated related information, that 
represents the clinical judgment of pharmacists, physicians, and other 
experts in the diagnosis and treatment of disease or promotion of 
health. It is often described as a list of medications routinely 
stocked by the health care system. These interested parties stated that 
although certain therapeutics can be associated with better outcomes 
for patients with rare diseases, the lack of access to hospital 
formularies represents a hurdle under the IPPS MS-DRGs. According to 
these interested parties, when Medicare reimbursement is insufficient 
to cover the costs of certain therapeutics that treat patients with 
rare diseases, a disincentive can be created in addressing these 
conditions.
    For the purposes of the comment solicitation in the proposed rule, 
we described three selected requests we had received relating to the 
MS-DRG classification of rare diseases and conditions that are 
represented by low volumes in our claims data.
    In the FY 2013 IPPS/LTCH PPS final rule (77 FR 53311), the FY 2015 
IPPS/LTCH PPS final rule (79 FR 49901) and the FY 2019 IPPS/LTCH PPS 
final rule (83 FR 41200), we discussed requests we received to revise 
the MS-DRG classification for cases of patients diagnosed with 
porphyria to recognize the resource requirements in caring for these 
patients, to ensure appropriate payment for these cases, and to 
preserve patient access to necessary treatments. Porphyria is defined 
as a group of rare disorders (``porphyrias'') that interfere with the 
production of hemoglobin that is needed for red blood cells. While some 
of these disorders are genetic (inborn) and others are acquired, they 
all result in the abnormal accumulation of hemoglobin building blocks, 
called porphyrins, which can be deposited in the tissues where they 
particularly interfere with the functioning of the nervous system and 
the skin. Treatment for patients suffering from disorders of porphyrin 
metabolism consists of an intravenous injection of Panhematin[supreg] 
(hemin for injection).
    In the FY 2019 proposed rule, we stated our data analysis showed 
that cases reporting diagnosis code E80.21 (Acute intermittent 
(hepatic) porphyria) as the principal diagnosis in MS-DRG 642 (Inborn 
and Other Disorders of Metabolism) had higher average costs and longer 
average lengths of stay compared to the average costs and length of 
stay for all other cases in MS-DRG 642. However, after considering 
these findings in the context of the current MS-DRG structure, we 
stated that we were unable to identify an MS-DRG that would more 
closely parallel these cases with respect to average costs and length 
of stay that would also be clinically aligned. We further stated that 
our clinical advisors believed that, in the current MS-DRG structure, 
the clinical characteristics of patients in these cases are most 
closely aligned with the clinical characteristics of patients in all 
cases in MS-DRG 642. Moreover, given the small number of porphyria 
cases, we stated we did not believe there was justification for 
creating a new MS-DRG and did not propose to revise the MS-DRG 
classification for porphyria cases.
    In response, some commenters described significant difficulties 
encountered by patients with acute porphyria attacks in obtaining 
Panhematin[supreg] when presenting to an inpatient hospital, which they 
attributed to the strong financial disincentives faced by facilities to 
treat these cases on an inpatient basis. The commenters stated that, 
based on the lower than expected average cost per case and longer than 
expected length of stay for acute porphyria attacks, it appeared that 
facilities were frequently not providing Panhematin[supreg] to patients 
in this condition, and instead attempting to provide symptom relief and 
transferring patients to an outpatient setting to receive the drug 
where they can be adequately paid. The commenters stated that this is 
in contrast to the standard of care for acute porphyria attacks and 
could result in devastating long-term health consequences.
    In the FY 2019 final rule (83 FR 41200), as we have stated in prior 
rulemaking, we noted it is not appropriate for facilities to deny 
treatment to beneficiaries needing a specific type of therapy or 
treatment that involves increased costs. We further noted the MS-DRG 
system is a system of averages and it is expected that across

[[Page 48890]]

the diagnostic related groups that within certain groups, some cases 
may demonstrate higher than average costs, while other cases may 
demonstrate lower than average costs. While we recognized the average 
costs of the small number of porphyria cases were greater than the 
average costs of the cases in MS-DRG 642 overall, we also noted that an 
averaged payment system depends on aggregation of similar cases with a 
range of costs, and that we seek to identify sufficiently large sets of 
claims data with a resource/cost similarity and clinical similarity in 
developing diagnostic-related groups rather than smaller subsets of 
diagnoses. We further stated that we were sensitive to the commenters' 
concerns about access to treatment for beneficiaries who have been 
diagnosed with this condition and we would continue to explore 
mechanisms through which to address rare diseases and low volume DRGs.
    Similarly, in the FY 2022 IPPS/LTCH PPS final rule (86 FR 44869), 
we discussed a request we received to review potential access issues in 
the inpatient setting for the administration of ANDEXXA[supreg]. 
ANDEXXA[supreg] (coagulation factor Xa (recombinant), inactivated-zhzo) 
is a recombinant decoy protein that rapidly reverses the anticoagulant 
effects of two direct oral anticoagulants, apixaban and rivaroxaban, 
when reversal of anticoagulation is needed due to life-threatening or 
uncontrolled bleeding in indications such as intracranial hemorrhages 
(ICHs) and gastrointestinal bleeds (GIBs). We noted that while our data 
findings demonstrated the average costs for the cases reporting the 
intravenous administration of ANDEXXA[supreg] were higher when compared 
to all cases in their respective MS-DRG, these cases represented a very 
small percentage of the total number of cases reported in those MS-
DRGs. We stated we were unable to identify another MS-DRG that would be 
a more appropriate MS-DRG assignment for these cases based on the 
indication for this therapeutic drug. We also stated that while we were 
sensitive to the requestors' concerns about continued access to 
treatment for beneficiaries who require the reversal of anticoagulation 
due to life-threatening or uncontrolled bleeding, we indicated 
additional time was needed to explore options and other mechanisms 
through which to address low volume, high-cost drugs outside of the MS-
DRGs.
    Lastly, in the proposed rule, we discussed a request we received to 
reconsider how cases reporting the administration of Zulresso[supreg] 
(brexanolone) are recognized for payment under the ICD-10 MS-DRGs in an 
effort to improve access to treatment for maternal mental health. On 
March 19, 2019 Zulresso[supreg] (brexanolone) became the first Food and 
Drug Administration (FDA) approved drug, specifically for postpartum 
depression (PPD) in adults. According to the requestor, PPD is one of 
the most common complications during and after pregnancy. The requestor 
stated PPD is a serious but manageable disorder and that with early 
treatment, the life of the mother, baby, and the entire family could be 
positively impacted. The requestor indicated it shares CMS's goals of 
addressing disparities in access to care, and urged CMS to take 
additional steps to address inequities in women's health by permitting 
separate payment for Zulresso[supreg] (brexanolone), in addition to the 
MS-DRG payment.
    As discussed in the proposed rule, effective with discharges on and 
after October 1, 2020, cases reporting the administration of 
Zulresso[supreg] in the inpatient setting are identified by ICD-10-PCS 
procedure codes XW03306 (Introduction of brexanolone into peripheral 
vein, percutaneous approach, new technology group 6) or XW04306 
(Introduction of brexanolone into central vein, percutaneous approach, 
new technology group 6). These procedure codes are designated as non-O. 
R. procedures and do not affect the MS-DRG assignment when reported on 
an inpatient claim. We noted that an application for new technology 
add-on payment for Zulresso[supreg] (brexanolone) was discussed in the 
FY 2021 IPPS/LTCH PPS proposed rule (85 FR 32672 through 32676) and was 
not approved, as discussed in the final rule (85 FR 58709 through 
58715).
    We stated we analyzed claims from the September 2021 update of the 
FY 2021 MedPAR file for cases reporting the administration of 
Zulresso[supreg] (brexanolone). Our analysis of the claims data 
identified only one case reporting the administration of 
Zulresso[supreg] (brexanolone) in MS-DRG 870 (Septicemia or Severe 
Sepsis with MV >96 Hours) with an average length of stay of 22 days and 
average costs of $67,812. For all cases in MS-DRG 870, the average 
costs are $55,459 and the average length of stay is 15.9 days. We 
stated that while the average length of stay for the case reporting the 
administration of Zulresso[supreg] (brexanolone) was greater (22 days 
versus 15.9 days) and the average costs were higher ($67,812 versus 
$55,459), than all cases in MS-DRG 870 it was unclear if treatment with 
Zulresso[supreg] (brexanolone) was the underlying reason for these 
factors, given that the MS-DRG assigned is for sepsis and it is not 
uncommon for sepsis patients to have multiple co-morbidities and 
intensive treatment strategies to address this severe, often life 
threatening condition.
    We stated we appreciated the requestor's interest in sharing CMS's 
goal of advancing women's health, however, we noted that the population 
in which Zulresso[supreg] (brexanolone) is indicated generally does not 
include our inpatient Medicare population. As we have stated in prior 
rulemaking, (83 FR 41210), we have not adopted the same approach to 
refine the maternity and newborn MS-DRGs because of the extremely low 
volume of Medicare patients there are in these MS-DRGs. When there is 
not a high volume of these cases (for example, maternity and newborn) 
represented in the Medicare data, we generally advise that other payers 
should develop DRGs to address the needs of their patients. We stated 
we believed the same would apply with respect to administration of 
Zulresso[supreg] (brexanolone) for which, as noted, we identified only 
one case in the FY 2021 MedPAR file.
    As discussed in prior rulemaking, the MS-DRGs are a classification 
system intended to group together diagnoses and procedures with similar 
clinical characteristics and utilization of resources. Rare diseases 
and conditions that are represented by low volumes in our claims data 
however, pose a unique challenge to this methodology as these 
conditions by definition affect small subsets of the population. In the 
proposed rule, we stated that it has been difficult to identify other 
MS-DRGs that would be more appropriate MS-DRG assignments for these 
rare conditions based on the wide variance in the clinical 
characteristics and utilization of resources for each condition, 
depending on the diagnosis. Creating a new MS-DRG for these conditions 
as a distinct ``related'' group is also challenging for the same 
reasons.
    As previously noted, we generally seek to identify sufficiently 
large sets of claims data with a resource/cost similarity and clinical 
similarity in developing diagnostic-related groups rather than smaller 
subsets. In the proposed rule, we stated that we have been concerned 
that basing MS-DRG reclassification decisions on small numbers of cases 
could lead to complexities in establishing the relative payment weights 
for the MS-DRGs because several expensive cases could impact the 
overall relative payment weight. Having larger clinical cohesive groups 
within an MS-DRG provides greater stability and thus predictability

[[Page 48891]]

for hospitals for annual updates to the relative payment weights.
    As also previously noted, the MS-DRG system is a system of averages 
and it is expected that within the diagnostic related groups, some 
cases may demonstrate higher than average costs, while other cases may 
demonstrate lower than average costs. However, as noted, cases 
involving treatment of rare diseases may involve more resource use than 
other cases in their respective MS-DRG. Section 1886(d)(5)(A) of the 
Act provides for Medicare payments to Medicare-participating hospitals 
in addition to the basic prospective payments for cases incurring 
extraordinarily high costs, however we solicited feedback on other 
mechanisms we could explore through which we can address concerns 
relating to payment for patients with rare diseases and conditions that 
are represented by low volumes in our claims data. We stated we were 
also interested in receiving comments on other meaningful ways in which 
we might potentially improve access to treatment for postpartum 
depression in certain populations, including through activities 
pursuant to Vice President Harris's Call to Action to Reduce Maternal 
Mortality and Morbidity.\28\
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    \28\ Available at: https://www.whitehouse.gov/briefing-room/statements-releases/2021/12/07/fact-sheet-vice-president-kamala-harris-announces-call-to-action-to-reduce-maternal-mortality-and-morbidity/.
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    To inform decision making, we stated we were also looking for 
feedback on how to mitigate any unintended negative payment impacts to 
providers serving patients with rare diseases or conditions that are 
represented by low volumes in our claims data. In particular, we stated 
we were interested in hearing the perspectives of large urban 
hospitals, rural hospitals, and other hospital types in regard to their 
experience. We also sought comments on how factors such as hospital 
size and type might impact a hospital's ability to develop protocols to 
better address these conditions. We stated we would take commenters' 
feedback into consideration in future policy development.
    Comment: Many commenters stated they appreciated CMS' attention and 
the acknowledgment of the challenging nature of rare diseases as part 
of a reporting and payment structure. Commenters also expressed that 
they fully support the Administration's initiatives that champion 
policies to improve maternal health and equity, especially as it 
relates to PPD. Most commenters provided recommendations and suggested 
CMS explore mechanisms such as--
     Creating a ``permanent'' payment methodology approach 
which combines the MS-DRG ``fixed price'' with continued partial 
payment for the actual cost of treatment per stay;
     Creating new MS-DRGs for certain low-volume therapies or 
for orphan conditions with more flexible cost outlier funding;
     Creating new MS-DRG categories to ensure access to rapidly 
expanding transformative therapies like cell and gene therapies;
     Creating a new enhanced new technology add-on payment-like 
pathway that establishes separate payment for low volume high-cost 
drugs;
     Reimbursing hospitals for orphan drugs based on the 
Average Sales Price (ASP) as published in the HOPD Addendum B file 
using the same authority that the Agency relied on to make the recent 
COVID-19 payment adjustments;
     Carving-out ``clinical trial'' inpatient stays to ensure 
that the MS-DRG payment rate is not adversely impacted by facility-
reported costs that do not include acquisition costs;
     Exploring databases outside of the MedPAR to obtain claims 
data for inclusion analysis;
     Creating a rare disease diagnosis code designation, 
similar to the complication or comorbidity (CC) and major complication 
or comorbidity (MCC) severity designations;
     Establishing a central formulary to provide high cost 
drugs for rare conditions instead of utilizing individual hospital 
pharmacy formularies to ease burdens of carrying high cost drugs on 
rural and smaller hospitals, as drug transport can potentially be 
cheaper then patient transport;
     Waiving the 500 case threshold when deciding whether an 
MS-DRG change should be proposed.
    Specifically, in discussing how cases reporting the administration 
of Zulresso[supreg] (brexanolone) are recognized for payment, 
commenters stated that if Medicare commits to creating MS-DRGs around 
the Medicare population giving birth, the impacts of this progress 
would have far-reaching effects beyond Medicare beneficiaries as it 
will serve as the foundation for commercial and Medicaid payments.
    Response: We appreciate the input provided by commenters in 
response to this request for information and we thank commenters for 
the acknowledgment of the challenges rare diseases or conditions that 
are represented by low volumes present as part of a reporting and 
reimbursement structure. We thank the commenters for their support and 
consideration of these issues. We will take the comments received in 
response to the solicitation into consideration as we continue to 
explore mechanisms to address concerns relating to payment for patients 
with rare diseases and conditions that are represented by low volumes 
in our claims data.
20. Out of Scope Public Comments Received
    We received public comments on MS-DRG related issues that were 
outside the scope of the proposals included in the FY 2023 IPPS/LTCH 
PPS proposed rule. Because we consider these public comments to be 
outside the scope of the proposed rule, we are not addressing them in 
this final rule. As stated in section II.D.1.b. of the preamble of this 
final rule, we encourage individuals with comments about MS-DRG 
classifications to submit these comments no later than October 20, 2022 
via the new electronic intake system, Medicare Electronic Application 
Request Information SystemTM (MEARISTM) at: 
https://mearis.cms.gov/public/home so that they can be considered for 
possible inclusion in the annual proposed rule. We will consider these 
public comments for possible proposals in future rulemaking as part of 
our annual review process.

II. Changes to Medicare Severity Diagnosis-Related Group (MS-DRG) 
Classifications and Relative Weights

E. Recalibration of the FY 2023 MS-DRG Relative Weights

1. Data Sources for Developing the Relative Weights

    Consistent with our established policy, in developing the MS-DRG 
relative weights for FY 2023, we proposed to use two data sources: 
claims data and cost report data. The claims data source is the MedPAR 
file, which includes fully coded diagnostic and procedure data for all 
Medicare inpatient hospital bills. The FY 2021 MedPAR data used in this 
final rule include discharges occurring on October 1, 2020, through 
September 30, 2021, based on bills received by CMS through March 31, 
2022, from all hospitals subject to the IPPS and short-term, acute care 
hospitals in Maryland (which at that time were under a waiver from the 
IPPS).
    The FY 2021 MedPAR file used in calculating the relative weights 
includes data for approximately 7,444,003

[[Page 48892]]

Medicare discharges from IPPS providers. Discharges for Medicare 
beneficiaries enrolled in a Medicare Advantage managed care plan are 
excluded from this analysis. These discharges are excluded when the 
MedPAR ``GHO Paid'' indicator field on the claim record is equal to 
``1'' or when the MedPAR DRG payment field, which represents the total 
payment for the claim, is equal to the MedPAR ``Indirect Medical 
Education (IME)'' payment field, indicating that the claim was an ``IME 
only'' claim submitted by a teaching hospital on behalf of a 
beneficiary enrolled in a Medicare Advantage managed care plan. In 
addition, the March 2022 update of the FY 2021 MedPAR file complies 
with version 5010 of the X12 HIPAA Transaction and Code Set Standards, 
and includes a variable called ``claim type.'' Claim type ``60'' 
indicates that the claim was an inpatient claim paid as fee-for-
service. Claim types ``61,'' ``62,'' ``63,'' and ``64'' relate to 
encounter claims, Medicare Advantage IME claims, and HMO no-pay claims. 
Therefore, the calculation of the relative weights for FY 2023 also 
excludes claims with claim type values not equal to ``60.'' The data 
exclude CAHs, including hospitals that subsequently became CAHs after 
the period from which the data were taken. We note that the FY 2023 
relative weights are based on the ICD-10-CM diagnosis codes and ICD-10-
PCS procedure codes from the FY 2021 MedPAR claims data, grouped 
through the ICD-10 version of the FY 2023 GROUPER (Version 40).
    The second data source used in the cost-based relative weighting 
methodology is the Medicare cost report data files from the HCRIS. In 
general, we use the HCRIS dataset that is 3 years prior to the IPPS 
fiscal year. Specifically, for this final rule, we used the March 2022 
update of the FY 2020 HCRIS for calculating the FY 2023 cost-based 
relative weights. Consistent with our historical practice, for this FY 
2023 final rule, we are providing the version of the HCRIS from which 
we calculated these 19 CCRs on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS. Click on 
the link on the left side of the screen titled ``FY 2023 IPPS Final 
Rule Home Page'' or ``Acute Inpatient Files for Download.''
2. Methodology for Calculation of the Relative Weights
a. General
    We calculated the FY 2023 relative weights based on 19 CCRs. The 
methodology we proposed to use to calculate the FY 2023 MS-DRG cost-
based relative weights based on claims data in the FY 2021 MedPAR file 
and data from the FY 2020 Medicare cost reports is as follows:
     To the extent possible, all the claims were regrouped 
using the FY 2023 MS-DRG classifications discussed in sections II.B. 
and II.D. of the preamble of this final rule.
     The transplant cases that were used to establish the 
relative weights for heart and heart-lung, liver and/or intestinal, and 
lung transplants (MS-DRGs 001, 002, 005, 006, and 007, respectively) 
were limited to those Medicare-approved transplant centers that have 
cases in the FY 2021 MedPAR file. (Medicare coverage for heart, heart-
lung, liver and/or intestinal, and lung transplants is limited to those 
facilities that have received approval from CMS as transplant centers.)
     Organ acquisition costs for kidney, heart, heart-lung, 
liver, lung, pancreas, and intestinal (or multivisceral organs) 
transplants continue to be paid on a reasonable cost basis.
    Because these acquisition costs are paid separately from the 
prospective payment rate, it is necessary to subtract the acquisition 
charges from the total charges on each transplant bill that showed 
acquisition charges before computing the average cost for each MS-DRG 
and before eliminating statistical outliers.
    Section 108 of the Further Consolidated Appropriations Act, 2020 
provides that, for cost reporting periods beginning on or after October 
1, 2020, costs related to hematopoietic stem cell acquisition for the 
purpose of an allogeneic hematopoietic stem cell transplant shall be 
paid on a reasonable cost basis. We refer the reader to the FY 2021 
IPPS/LTCH PPS final rule for further discussion of the reasonable cost 
basis payment for cost reporting periods beginning on or after October 
1, 2020 (85 FR 58835 through 58842). For FY 2022 and subsequent years, 
we subtract the hematopoietic stem cell acquisition charges from the 
total charges on each transplant bill that showed hematopoietic stem 
cell acquisition charges before computing the average cost for each MS-
DRG and before eliminating statistical outliers.
     Claims with total charges or total lengths of stay less 
than or equal to zero were deleted. Claims that had an amount in the 
total charge field that differed by more than $30.00 from the sum of 
the routine day charges, intensive care charges, pharmacy charges, 
implantable devices charges, supplies and equipment charges, therapy 
services charges, operating room charges, cardiology charges, 
laboratory charges, radiology charges, other service charges, labor and 
delivery charges, inhalation therapy charges, emergency room charges, 
blood and blood products charges, anesthesia charges, cardiac 
catheterization charges, CT scan charges, and MRI charges were also 
deleted.
     At least 93.0 percent of the providers in the MedPAR file 
had charges for 14 of the 19 cost centers. All claims of providers that 
did not have charges greater than zero for at least 14 of the 19 cost 
centers were deleted. In other words, a provider must have no more than 
five blank cost centers. If a provider did not have charges greater 
than zero in more than five cost centers, the claims for the provider 
were deleted.
     Statistical outliers were eliminated by removing all cases 
that were beyond 3.0 standard deviations from the geometric mean of the 
log distribution of both the total charges per case and the total 
charges per day for each MS-DRG.
     Effective October 1, 2008, because hospital inpatient 
claims include a POA indicator field for each diagnosis present on the 
claim, only for purposes of relative weight-setting, the POA indicator 
field was reset to ``Y'' for ``Yes'' for all claims that otherwise have 
an ``N'' (No) or a ``U'' (documentation insufficient to determine if 
the condition was present at the time of inpatient admission) in the 
POA field.
    Under current payment policy, the presence of specific HAC codes, 
as indicated by the POA field values, can generate a lower payment for 
the claim. Specifically, if the particular condition is present on 
admission (that is, a ``Y'' indicator is associated with the diagnosis 
on the claim), it is not a HAC, and the hospital is paid for the higher 
severity (and, therefore, the higher weighted MS-DRG). If the 
particular condition is not present on admission (that is, an ``N'' 
indicator is associated with the diagnosis on the claim) and there are 
no other complicating conditions, the DRG GROUPER assigns the claim to 
a lower severity (and, therefore, the lower weighted MS-DRG) as a 
penalty for allowing a Medicare inpatient to contract a HAC. While the 
POA reporting meets policy goals of encouraging quality care and 
generates program savings, it presents an issue for the relative 
weight-setting process. Because cases identified as HACs are likely to 
be more complex than similar cases that are not identified as HACs, the 
charges associated with HAC cases are likely to be higher as well. 
Therefore, if the higher charges of these HAC claims are grouped into 
lower

[[Page 48893]]

severity MS-DRGs prior to the relative weight-setting process, the 
relative weights of these particular MS-DRGs would become artificially 
inflated, potentially skewing the relative weights. In addition, we 
want to protect the integrity of the budget neutrality process by 
ensuring that, in estimating payments, no increase to the standardized 
amount occurs as a result of lower overall payments in a previous year 
that stem from using weights and case-mix that are based on lower 
severity MS-DRG assignments. If this would occur, the anticipated cost 
savings from the HAC policy would be lost.
    To avoid these problems, we reset the POA indicator field to ``Y'' 
only for relative weight-setting purposes for all claims that otherwise 
have an ``N'' or a ``U'' in the POA field. This resetting ``forced'' 
the more costly HAC claims into the higher severity MS-DRGs as 
appropriate, and the relative weights calculated for each MS-DRG more 
closely reflect the true costs of those cases.
    In addition, in the FY 2013 IPPS/LTCH PPS final rule, for FY 2013 
and subsequent fiscal years, we finalized a policy to treat hospitals 
that participate in the Bundled Payments for Care Improvement (BPCI) 
initiative the same as prior fiscal years for the IPPS payment modeling 
and ratesetting process without regard to hospitals' participation 
within these bundled payment models (77 FR 53341 through 53343). 
Specifically, because acute care hospitals participating in the BPCI 
Initiative still receive IPPS payments under section 1886(d) of the 
Act, we include all applicable data from these subsection (d) hospitals 
in our IPPS payment modeling and ratesetting calculations as if the 
hospitals were not participating in those models under the BPCI 
initiative. We refer readers to the FY 2013 IPPS/LTCH PPS final rule 
for a complete discussion on our final policy for the treatment of 
hospitals participating in the BPCI initiative in our ratesetting 
process. For additional information on the BPCI initiative, we refer 
readers to the CMS' Center for Medicare and Medicaid Innovation's 
website at https://innovation.cms.gov/initiatives/Bundled-Payments/ and to section IV.H.4. of the preamble of the FY 2013 IPPS/
LTCH PPS final rule (77 FR 53341 through 53343).
    The participation of hospitals in the BPCI initiative concluded on 
September 30, 2018. The participation of hospitals in the BPCI Advanced 
model started on October 1, 2018. The BPCI Advanced model, tested under 
the authority of section 1115A of the Act, is comprised of a single 
payment and risk track, which bundles payments for multiple services 
beneficiaries receive during a Clinical Episode. Acute care hospitals 
may participate in BPCI Advanced in one of two capacities: as a model 
Participant or as a downstream Episode Initiator. Regardless of the 
capacity in which they participate in the BPCI Advanced model, 
participating acute care hospitals will continue to receive IPPS 
payments under section 1886(d) of the Act. Acute care hospitals that 
are Participants also assume financial and quality performance 
accountability for Clinical Episodes in the form of a reconciliation 
payment. For additional information on the BPCI Advanced model, we 
refer readers to the BPCI Advanced web page on the CMS Center for 
Medicare and Medicaid Innovation's website at https://innovation.cms.gov/initiatives/bpci-advanced/. Consistent with our 
policy for FY 2022, and consistent with how we have treated hospitals 
that participated in the BPCI Initiative, for FY 2023, we continue to 
believe it is appropriate to include all applicable data from the 
subsection (d) hospitals participating in the BPCI Advanced model in 
our IPPS payment modeling and ratesetting calculations because, as 
noted previously, these hospitals are still receiving IPPS payments 
under section 1886(d) of the Act. Consistent with the FY 2022 IPPS/LTCH 
PPS final rule, we also proposed to include all applicable data from 
subsection (d) hospitals participating in the Comprehensive Care for 
Joint Replacement (CJR) Model in our IPPS payment modeling and 
ratesetting calculations.
    The charges for each of the 19 cost groups for each claim were 
standardized to remove the effects of differences in area wage levels, 
IME and DSH payments, and for hospitals located in Alaska and Hawaii, 
the applicable cost-of-living adjustment. Because hospital charges 
include charges for both operating and capital costs, we standardized 
total charges to remove the effects of differences in geographic 
adjustment factors, cost-of-living adjustments, and DSH payments under 
the capital IPPS as well. Charges were then summed by MS-DRG for each 
of the 19 cost groups so that each MS-DRG had 19 standardized charge 
totals. Statistical outliers were then removed. These charges were then 
adjusted to cost by applying the national average CCRs developed from 
the FY 2020 cost report data.
    The 19 cost centers that we used in the relative weight calculation 
are shown in a supplemental data file, Cost Center HCRIS Lines 
Supplemental Data File, posted via the internet on the CMS website for 
this final rule and available at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS. The supplemental data file 
shows the lines on the cost report and the corresponding revenue codes 
that we used to create the 19 national cost center CCRs. In the FY 2023 
IPPS/LTCH PPS proposed rule, we stated that if we receive comments 
about the groupings in this supplemental data file, we may consider 
these comments as we finalize our policy.
    Comment: A commenter requested that CMS create a dedicated cost 
center line for cell and gene therapy product cost information, which 
would enable the agency to create a 20th cost center that is separate 
from the drugs/pharmacy cost center.
    Response: We appreciate the commenter's request regarding the 
creation of new cost centers for cell and gene therapy product cost 
information and may consider this request in connection with future 
rulemaking.
    After consideration of the comment received, we are finalizing our 
proposal to use the 19 national cost center CCRs to calculate the 
relative weights for FY 2023.
    Consistent with historical practice, we account for rare situations 
of non-monotonicity in a base MS-DRG and its severity levels, where the 
mean cost in the higher severity level is less than the mean cost in 
the lower severity level, in determining the relative weights for the 
different severity levels. If there are initially non-monotonic 
relative weights in the same base DRG and its severity levels, then we 
combine the cases that group to the specific non-monotonic MS-DRGs for 
purposes of relative weight calculations. For example, if there are two 
non-monotonic MS-DRGs, combining the cases across those two MS-DRGs 
results in the same relative weight for both MS-DRGs. The relative 
weight calculated using the combined cases for those severity levels is 
monotonic, effectively removing any non-monotonicity with the base DRG 
and its severity levels. For this FY 2023 final rule, this calculation 
was applied to address non-monotonicity for cases that grouped to MS-
DRG 793 and MS-DRG 794. In the supplemental file titled AOR/BOR File, 
we include statistics for the affected MS-DRGs both separately and with 
cases combined.
    We invited public comments on our proposals related to 
recalibration of the proposed FY 2023 relative weights and the changes 
in the relative weights from FY 2022.

[[Page 48894]]

    Comment: A commenter requested that CMS study whether it might be 
appropriate to define the labor portion individually for each of the 19 
cost centers and only standardize that portion, particularly if doing 
so improves the explanatory power of all MS-DRGs. This commenter 
requested that CMS conduct this study in collaboration with 
stakeholders and release this analysis in future rulemaking.
    Response: We appreciate the commenter's request that CMS study the 
appropriateness of defining the labor portion individually for each of 
the 19 cost centers and standardizing only that portion, and we may 
consider this request in connection with future rulemaking.
    After consideration of the comment received, we are finalizing our 
proposals related to the recalibration of the FY 2023 relative weights. 
We summarize and respond to comments relating to the methodology for 
calculating the relative weight for MS-DRG 018 in the next section of 
this final rule.
b. Relative Weight Calculation for MS-DRG 018
    As discussed in the FY 2021 IPPS/LTCH PPS final rule (85 FR 58599 
through 58600), we created MS-DRG 018 for cases that include procedures 
describing CAR T-cell therapies, which were reported using ICD-10-PCS 
procedure codes XW033C3 or XW043C3. Effective for FY 2022, we revised 
MS-DRG 018 to include cases that report the procedure codes for CAR T-
cell and non-CAR T-cell therapies and other immunotherapies (86 FR 
44798 through 448106). We refer the reader to section II.D.2. of this 
final rule for discussion of the agenda items for the March 8-9, 2022 
ICD-10 Coordination and Maintenance Committee meeting relating to new 
procedure codes to describe the administration of a CAR T-cell or 
another type of gene or cellular therapy product, as well as our 
established process for determining the MS-DRG assignment for codes 
approved at the March meeting.
    For MS-DRG 018, we include a modification to our existing relative 
weight methodology to ensure that the relative weight for MS-DRG 018 
appropriately reflects the relative resources required for providing 
CAR T-cell and non-CAR T-cell therapies and other immunotherapies 
outside of a clinical trial, while still accounting for the clinical 
trial cases in the overall average cost for all MS-DRGs. For cases that 
group to MS-DRG 018, we do not include claims determined to be clinical 
trial claims that group to MS-DRG 018 when calculating the average cost 
for MS-DRG 018 that is used to calculate the relative weight for this 
MS-DRG, with the additional refinements that: (a) when the CAR T-cell, 
non-CAR T-cell or other immunotherapy product is purchased in the usual 
manner, but the case involves a clinical trial of a different product, 
we include the claim when calculating the average cost for MS-DRG 018 
to the extent such claims can be identified in the historical data; and 
(b) when there is expanded access use of the CAR T-cell, non-CAR T-cell 
or other immunotherapy product, these cases will not be included when 
calculating the average cost for new MS DRG 018 to the extent such 
claims can be identified in the historical data (85 FR 58600). We also 
calculate an adjustment to account for the CAR T-cell, non-CAR T-cell 
and other immunotherapy cases determined to be clinical trial cases, as 
described later in this final rule and include revenue center 891 in 
our calculation of standardized drug charges for MS-DRG 018. We refer 
the reader to the FY 2021 IPPS/LTCH PPS final rule for further 
discussion of our modifications to the relative weight calculation for 
MS-DRG 018.
    We proposed to continue to use the same process to identify 
clinical trial claims in the FY 2021 MedPAR for purposes of calculating 
the FY 2023 relative weights. We continue to use the proxy of 
standardized drug charges of less than $373,000, which was the average 
sales price of KYMRIAH and YESCARTA, which are the two CAR T-cell 
biological products in the FY 2021 MedPAR data used for this final 
rule. (As previously noted, effective beginning FY 2022, we revised MS-
DRG 018 to include cases that report the procedure codes for CAR T-cell 
and non-CAR T-cell therapies and other immunotherapies (86 FR 44798 
through 448106).) Using the same methodology from the FY 2021 IPPS/LTCH 
PPS final rule, we proposed to apply an adjustment to account for the 
CAR T cell therapy cases identified as clinical trial cases in 
calculating the national average standardized cost per case that is 
used to calculate the relative weights for all MS-DRGs:
     Calculate the average cost for cases to be assigned to MS-
DRG 018 that contain ICD-10-CM diagnosis code Z00.6 or contain 
standardized drug charges of less than $373,000.
     Calculate the average cost for all other cases to be 
assigned to MS-DRG 018.
     Calculate an adjustor by dividing the average cost 
calculated in step 1 by the average cost calculated in step 2.
     Apply the adjustor calculated in step 3 to the cases 
identified in step 1 as clinical trial cases, then add this adjusted 
case count to the non-clinical trial case count prior to calculating 
the average cost across all MS-DRGs.
    Additionally, we are continuing our finalized methodology for 
calculating this payment adjustment, such that: (a) when the CAR T-
cell, non-CAR T-cell or other immunotherapy product is purchased in the 
usual manner, but the case involves a clinical trial of a different 
product, the claim will be included when calculating the average cost 
for cases not determined to be clinical trial cases; and (b) when there 
is expanded access use of immunotherapy, these cases will be included 
when calculating the average cost for cases determined to be clinical 
trial cases. However, we continue to believe to the best of our 
knowledge there are no claims in the historical data (FY 2021 MedPAR) 
used in the calculation of the adjustment for cases involving a 
clinical trial of a different product, and to the extent the historical 
data contain claims for cases involving expanded access use of 
immunotherapy we believe those claims would have drug charges less than 
$373,000.
    Applying this previously finalized methodology, based on the 
December 2021 update of the FY 2021 MedPAR file used for the proposed 
rule, we estimated that the average costs of cases assigned to MS-DRG 
018 that are identified as clinical trial cases ($61,356) were 20 
percent of the average costs of the cases assigned to MS-DRG 018 that 
are identified as non-clinical trial cases ($299,460). Accordingly, as 
we did for FY 2022, we proposed to adjust the transfer-adjusted case 
count for MS-DRG 018 by applying the proposed adjustor of 0.20 to the 
applicable clinical trial and expanded access use immunotherapy cases, 
and to use this adjusted case count for MS-DRG 018 in calculating the 
national average cost per case, which is used in the calculation of the 
relative weights. Therefore, in calculating the national average cost 
per case for purposes of the proposed rule, each case identified as an 
applicable clinical trial or expanded access use immunotherapy case was 
adjusted by 0.20. As we did for FY 2022, we applied this same adjustor 
for the applicable cases that group to MS-DRG 018 for purposes of 
budget neutrality and outlier simulations. We also proposed to update 
the value of the adjustor based on more recent data for the final rule.
    Comment: Several commenters were supportive of CMS' continued use 
of MS-DRG 018 as it is currently

[[Page 48895]]

structured, including the identification and exclusion of CAR T-cell 
clinical trial and expanded access use cases assigned to MS-DRG 018. 
Commenters stated that the stability of MS-DRG 018 will help ensure 
beneficiary access to CAR T-cell therapy services. One commenter stated 
that analysis of CAR T-cell claims data from FY 2021 through the first 
quarter of FY 2022 shows significant improvement in patient access to 
CAR T. Another commenter requested that CMS reevaluate the clinical 
trial threshold annually as acquisition costs increase and additional 
therapies are introduced to MS-DRG 018.
    Other commenters stated that they were concerned with what they 
stated were Medicare under-reimbursements for CAR T-cell technology, 
especially given the array of resources used to treat patients 
undergoing these complex, novel cell therapies and the adverse impact 
inadequate reimbursement has on beneficiary access. A commenter stated 
that payment for MS-DRG 018 is almost 30 percent below the cost of CAR 
T-cell cases and does not cover the cost of the therapy itself. A 
commenter recommended that CMS cover the full cost of the CAR T-cell 
therapy, while another commenter requested that CMS implement a policy 
solution that will ensure providers recoup at least the invoice cost of 
the CAR T-cell product. The commenter referenced prior comments about 
options for such policy solutions. Some commenters stated that the 
increase in the fixed-loss threshold makes it even more difficult to 
obtain adequate reimbursement. A commenter requested that CMS closely 
monitor reimbursement rates for CAR T-cell therapies to ensure that 
hospital facilities can continue to provide access to these treatments.
    Response: We appreciate the support and feedback on our proposal to 
use the same ratesetting methodology for MS-DRG 018 in FY 2023 as we 
have in prior years. With regard to the commenter who requested that 
CMS reevaluate the clinical trial threshold annually, we note that we 
continue to monitor the data and may engage further with the public and 
consider this comment in connection with future rulemaking. With regard 
to the comments that the MS-DRG relative weight for MS-DRG 018 is 
inadequate and does not result in payment that fully covers the 
hospital resource costs, we refer readers to the FY 2022 IPPS/LTCH 
final rule (86 FR 44965) where we responded to similar comments.
    Comment: A commenter stated that they understand that outliers are 
removed in the development of MS-DRGs so that they do not skew the 
results. The commenter found that in the calculation of the relative 
weights, MS-DRG 018 has the highest percent of cases removed as 
statistical outliers. The commenter stated the removal of these cases 
resulted in a lower standardized cost per inpatient stay. Another 
commenter requested that CMS monitor the impact that the removal of 
these statistical outliers has on MS-DRG 018 and other low volume 
services.
    Response: We examined the cases referenced by the commenter that 
were removed as statistical outliers in the FY 2021 MedPAR claims data. 
We found that these cases had very high charges and very short lengths 
of stay, with daily charges in excess of $1.2 million relative to the 
average daily charge of $114,000 for MS-DRG 018. As described earlier 
in this section, our standard method to identify and remove statistical 
outliers excludes cases with total charges and total daily charges that 
are beyond 3 standard deviations from the geometric mean of the log 
distribution of both average total charges and average total daily 
charges of the respective MS-DRG. As described in section III.B.4.b. of 
the preamble of this final rule with respect to the MS-LTC-DRGs, 
statistical outliers are removed because we believe that they may 
represent aberrations in the data that distort the measure of average 
resource use. For this reason, we believe that the cases identified by 
the commenters are appropriately excluded as outliers, as their 
inclusion could distort the measure of average resource use for MS-DRG 
018. We will continue to monitor the removal of statistical outliers in 
calculating the relative weights for MS-DRG 018.
    Comment: A commenter recommended that CMS establish a new, 
alternative payment model under CMMI for gene and cell therapies, 
outside of the constraints of the IPPS. The commenter stated that this 
would provide a clearer path to coverage and payment policy that can 
improve patient access. Another commenter stated that some exceptions 
to the standard IPPS process are and will continue to be needed to 
allow hospitals to make lifesaving therapies available at launch to 
Medicare beneficiaries as soon as possible.
    Response: We believe that is premature to make structural changes 
to the IPPS at this time to pay for gene and cell therapies. We may 
consider these comments for future rulemaking as we gain more 
experience in paying for these therapies under the IPPS.
    Comment: Some commenters expressed concern that CMS mapped revenue 
codes 087X for cell and gene therapy services furnished by hospital 
staff to the drug cost group. One commenter stated that the NUBC 
definition states this revenue code series is for ``[c]harges for 
procedures performed by staff for the acquisition and infusion/
injection of genetically modified cells''. The commenter stated that 
there is no standard cost center to report staff expense associated 
with the 087X series, but that it is inappropriate to assign the 
revenue for cell collection and processing services employed by 
hospital nursing and laboratory staff to the drug/pharmacy cost center. 
The commenter stated that if CMS finalizes this proposed mapping, it 
will be inconsistent with the mapping of revenues and expenses that 
hospitals are required to adhere to in their cost reports. A commenter 
suggested that CMS should revise the mapping of the 087X revenue codes 
to more closely reflect the departments where the staff expenses are 
recorded on the cost report. Commenters suggested that CMS map revenue 
codes 0871 and 0874 to the ``other'' cost center and 0872 and 0873 to 
the laboratory cost center. A commenter requested that CMS allow 
providers to bill for cell collection and cell processing services on 
the day that the services are rendered rather than adding them to the 
inpatient claim. The commenter stated that these are separate from the 
manufacturing process and are not included in the acquisition cost of 
the product.
    Response: We disagree with the commenters that revenue center codes 
087X are inappropriately mapped to the drug cost center. Cell 
collection and processing activities are part of the steps required to 
manufacture the drug, and thus assignment to the drug cost center 
accurately allocates these costs. Given this, we believe it is 
appropriate to apply the drug CCR to these charges for purposes of 
calculating the relative weights. With respect to the commenter who 
indicated that finalizing the proposed assignment of the 087X codes 
would be inconsistent with the mapping of revenues and expenses 
hospitals are required to adhere to in their cost reports, it is 
unclear to us what requirements are being referred to. With respect to 
the commenter who requested that CMS allow separate billing for the 
cell collection and processing services, as we discussed in the CY 2022 
OPPS final rule (86 FR 63550), CMS does not believe that separate 
payment is necessary for the various steps required to collect and 
prepare the genetically modified T-cells, and Medicare does not 
generally pay separately for each step

[[Page 48896]]

used to manufacture a drug or biological product.
    Comment: A commenter requested that CMS consider allowing hospitals 
to use expanded access condition code 90 instead of the remarks field, 
which would remove a layer of manual work required by the MACs, which 
would decrease the opportunity for errors.
    Response: We agree with the commenter that the availability of 
condition code 90 obviates the need for the use of the remarks field to 
identify expanded access claims that group to MS-DRG 018 for the 
purposes of applying the clinical trial adjustment. Effective October 
1, 2022, providers should submit condition code 90 to identify expanded 
access claims that group to MS-DRG 018, rather than the remarks field. 
The MACs will no longer flag cases as expanded access claims based on 
information submitted in the remarks field for claims submitted on or 
after October 1, 2022.
    Comment: A commenter requested that CMS provide additional 
clarification on the agency's methodology to develop the relative 
weight for both MS-DRG 018 and its overall ratesetting methodology. 
This commenter requested that CMS describe the order of operations, 
including step-by-step instructions of when to exclude certain types of 
claims. This commenter also requested that CMS clarify whether the 
agency trims claims first, and then sets aside clinical trial cases, or 
sets aside clinical trial claims and claims with less than $373,000 and 
then performs trimming.
    Response: In response to the commenter's specific question 
regarding when CMS removes clinical trial cases from MS-DRG 018, the 
trims to remove clinical trial cases from MS-DRG 018 are done prior to 
the elimination of statistical outliers. In response to the commenter's 
request that we clarify our relative weight methodology more generally, 
we note that in each year's IPPS/LTCH PPS proposed and final rules, we 
include a section describing the recalibration of the MS-DRG relative 
weights and methodology for calculating the relative weights. We refer 
readers to sections II.E.1. and E.2.a. of the preamble of this final 
rule, in which we describe the trims we apply to the MedPAR claims to 
exclude non-IPPS claims, and provide a detailed description of the 
methodology we use to calculate the relative weights. The order that 
the trims are applied is consistent with the narrative description of 
our methodology. In addition, since the creation of MS-DRG 018, we have 
provided a description of the calculation of the relative weight for 
MS-DRG 018, including a step-by-step calculation of the CAR T-cell 
clinical trial adjustment factor, as set forth earlier in this section.
    We also note that some commenters requested additional 
clarifications regarding billing instructions for CAR T-cell therapies, 
such as appropriate CAR T-cell billing and charges. We do not believe 
changes to billing guidance are needed at this time but will take these 
comments into consideration when developing policies and program 
requirements for future years for CAR T-cell therapy policy.
    After consideration of the public comments we received, we are 
finalizing our proposals regarding the calculation of the relative 
weight for MS-DRG 018. Applying this finalized methodology, based on 
the March 2022 update of the FY 2021 MedPAR file used for this final 
rule, we estimated that the average costs of cases assigned to MS-DRG 
018 that are identified as clinical trial cases ($61,540) were 21 
percent of the average costs of the cases assigned to MS-DRG 018 that 
are identified as non-clinical trial cases ($293,546). Accordingly, as 
we did for FY 2022, we are finalizing our proposal to adjust the 
transfer-adjusted case count for MS-DRG 018 by applying the adjustor of 
0.21 to the applicable clinical trial and expanded access use 
immunotherapy cases, and to use this adjusted case count for MS-DRG 018 
in calculating the national average cost per case, which is used in the 
calculation of the relative weights. Therefore, in calculating the 
national average cost per case for purposes of this final rule, each 
case identified as an applicable clinical trial or expanded access use 
immunotherapy case was adjusted by 0.21. As we did for FY 2022, we are 
applying this same adjustor for the applicable cases that group to MS 
DRG 018 for purposes of budget neutrality and outlier simulations.
c. Averaging of Relative Weights for FY 2023
    In section I.F. of the proposed rule and this final rule, we 
discuss our proposal to use the FY 2021 MedPAR data for purposes of FY 
2023 IPPS ratesetting, with certain proposed modifications to our usual 
methodologies, including an averaging approach for calculating the FY 
2023 relative weights. As discussed in the proposed rule, we observed 
that COVID-19 cases were impacting the relative weights as calculated 
using the FY 2021 claims data for a few COVID-19-related MS-DRGs. For 
example, for MS-DRG 870 (Septicemia or Severe Sepsis with MV >96 
hours), the relative weight calculated using the FY 2021 MedPAR data 
was approximately 9 percent higher than the relative weight calculated 
excluding the COVID-19 cases in the FY 2021 data. As also discussed in 
that section, we believe it is reasonable to assume that there will be 
fewer COVID-19 hospitalizations among Medicare beneficiaries in FY 2023 
than there were in FY 2021. However, we cannot know the precise number 
of COVID-19 hospitalizations among Medicare beneficiaries in FY 2023. 
To account for the anticipated decline in COVID-19 hospitalizations of 
Medicare beneficiaries as compared to FY 2021, we proposed to determine 
the MS-DRG relative weights for FY 2023 by averaging the relative 
weights as calculated with and without COVID-19 cases in the FY 2021 
data, as described in greater detail in this section. Given the 
uncertainty in the number of COVID-19 hospitalizations in FY 2023, we 
proposed to use 50 percent of the relative weights calculated using all 
applicable cases in the FY 2021 claims data and 50 percent of the 
relative weights calculated without the COVID-19 cases in the FY 2021 
claims data. We stated that we believe this proposed approach would 
appropriately reduce, but not remove entirely, the effect of COVID-19 
cases on the relative weight calculations, consistent with our 
expectation that Medicare inpatient hospitalizations for COVID-19 will 
continue in FY 2023 at a lower level as compared to FY 2021. By 
averaging the relative weights in this manner, we stated that we 
believe the result would reflect a reasonable estimation of the case 
mix for FY 2023 based on the information available at the time, as 
discussed in section I.F. of the preamble to the proposed rule and this 
final rule, and more accurately estimate the relative resource use for 
the cases treated in FY 2023 than if we were to calculate the proposed 
relative weights based on 100 percent of the relative weights as 
calculated for all applicable cases in the FY 2021 data. For the 
proposed rule, our proposed calculation was as follows:
     Step 1: Calculate a set of relative weights using all 
applicable cases in the December 2021 update of the FY 2021 MedPAR 
data, using the methodology as described earlier in this section, and 
then applying a normalization adjustment factor as described later in 
this section.
     Step 2: Calculate a set of relative weights using the 
December 2021 update of the FY 2021 MedPAR data excluding cases with a 
principal or secondary diagnosis of COVID-19 (ICD-10-CM diagnosis code 
U07.1), and

[[Page 48897]]

otherwise using the methodology as described earlier in this section, 
and then applying a normalization adjustment factor as described later 
in this section.
     Step 3: Average the results of step 1 and step 2 to 
calculate a set of averaged relative weights, geometric mean length of 
stays, and arithmetic mean length of stays.
     Step 4: Calculate the proposed FY 2023 relative weights by 
applying an additional normalization factor to these averaged relative 
weights. This additional normalization factor is necessary to ensure 
that the average case weight as calculated in step 3 of this proposed 
averaging methodology for recalibration of the FY 2023 relative weights 
is equal to the average case weight before recalibration. We note that 
this factor is very close to 1 and is described later in this section.
    We noted that in Step 5 of this proposed calculation, we applied 
the proposed 10 percent cap to the relative weights for those MS-DRGs 
for which the relative weight as calculated in Step 4 would otherwise 
have declined by more than 10 percent from the FY 2022 relative weight, 
as discussed more fully later in this section. We also noted that we 
intended to update this calculation for the final rule using the March 
2022 update of the FY 2021 MedPAR file.
    We set forth the proposed relative weights, geometric mean length 
of stay, and average length of stay as calculated using this proposed 
methodology in Table 5 associated with the proposed rule, which is 
available on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS. We also made available the 
relative weights, geometric mean length of stay, and average length of 
stay as calculated in steps 1 and 2 of this proposed methodology on our 
website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS.
    Comment: Several commenters supported our proposal to average the 
relative weights calculated with and without COVID-19 cases, stating 
that this would more accurately account for the anticipated change in 
case mix as COVID-19 cases decline.
    Another commenter supported an alternative MS-DRG relative weight 
methodology, but stated that the proposed methodology does not do 
enough to control for variability. This commenter requested that CMS 
use FY 2019 claims or some other alternate blend using the FY 2021 
claims to establish the FY 2023 relative weights.
    Some commenters expressed concern about policies that may limit the 
reimbursement for COVID-19 cases. A commenter suggested increasing the 
relative weights for the MS-DRGs that have documented COVID-19 cases, 
but recommended that CMS consider a process to differentiate patients 
who test asymptomatically for COVID-19 from those whose COVID-19 
infection is causing clinical symptoms to worsen. The commenter stated 
that this approach would better target the more resource intensive 
beneficiaries without artificially constraining reimbursement for their 
care.
    Response: We appreciate commenters' support for and feedback on our 
proposal. However, we disagree that we should blend other data sources 
or take additional steps to control for variability in the FY 2023 
relative weights. As we stated in the FY 2023 IPPS/LTCH PPS proposed 
rule, we cannot know the precise number of COVID-19 hospitalizations 
among Medicare beneficiaries as compared to FY 2021. Our proposal to 
average the relative weights is intended to reflect a reasonable 
estimation of the case mix for FY 2023 based on the information 
available at this time, not to completely remove all variability in the 
FY 2023 relative weights. Our proposed methodology uses the FY 2021 
MedPAR claims file to determine the FY 2023 relative weights, as the 
most recent available data during the period of the COVID-19 PHE, with 
modifications to account for the anticipated decline in COVID-19 
hospitalizations of Medicare beneficiaries at IPPS hospitals as 
compared to FY 2021. As discussed in section I.F. of this final rule, 
after reviewing the latest CDC hospitalization data available at this 
time, we continue to believe that it is reasonable to assume that some 
Medicare beneficiaries will be hospitalized with COVID-19 at IPPS 
hospitals in FY 2023, but that there will be fewer COVID 19 
hospitalizations as compared to FY 2021. With respect to the 
commenters' concerns about policies that may limit reimbursement for 
COVID-19 cases, we note that the majority of cases that include a 
diagnosis of COVID-19 (ICD-10-CM diagnosis code U07.1) group to MS-DRGs 
177 and 871, and that the relative weights calculated using the 
proposed averaging methodology for FY 2023 are higher than the FY 2022 
relative weights for these MS-DRGs. For MS-DRG 177, the relative weight 
calculated using the proposed averaging approach is also higher than 
the relative weight calculated using all applicable cases in the FY 
2021 MedPAR file. For MS-DRG 871, while the relative weight calculated 
using the proposed averaging approach is lower than the relative weight 
calculated using all applicable cases in the FY 2021 MedPAR file, it is 
still an increase as compared to the relative weight for FY 2022. 
Moreover, as previously discussed, we believe that use of the proposed 
averaging methodology would provide a more accurate estimate of 
relative resource use for FY 2023 than if we were to calculate the 
proposed relative weights using all applicable cases in the FY 2021 
data, and is consistent with our expectation, based on the information 
available at this time, that Medicare inpatient hospitalizations for 
COVID-19 will continue in FY 2023 at a lower level as compared to FY 
2021. With regard to the suggestion about differentiating between 
symptomatic and asymptomatic COVID-19 cases, at this time we do not 
believe it is operationally feasible to make such a distinction given 
that separate coding does not exist to differentiate these cases. We 
may consider this suggestion in connection with future rulemaking.
    After consideration of comments received, we are finalizing our 
proposal to determine the FY 2023 MS-DRG relative weights by averaging 
the relative weights as calculated with and without COVID-19 cases in 
the FY 2021 data, as previously described. As previously discussed, for 
this final rule, we are using the March 2022 update of the FY 2021 
MedPAR file to determine the final relative weights for FY 2023. The 
relative weights, geometric mean length of stay, and average length of 
stay as calculated using this methodology are set forth in Table 5 
associated with this final rule, which is available on the CMS website 
at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS. We are also making available the relative weights, 
geometric mean length of stay, and average length of stay as calculated 
in steps 1 and 2 of this methodology on our website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS.
d. Cap for Relative Weight Reductions
    In the FY 2018 IPPS/LTCH PPS final rule, we summarized comments we 
had received requesting a transition period for substantial reductions 
in relative weights in order to facilitate payment stability. 
Specifically, some commenters requested that CMS establish a cap on the 
decline in a relative weight from FY 2017 to FY 2018, or a phase-in or 
multi-year transition period in cases of substantial fluctuation of 
payment rates (82 FR 38103).

[[Page 48898]]

    After consideration of these comments, and for the reasons 
discussed in the FY 2018 final rule, we adopted a temporary one-time 
measure for FY 2018 for MS-DRGs where the relative weight would have 
declined by more than 20 percent from the FY 2017 relative weight, 
consistent with our general authority to assign and update appropriate 
weighting factors under sections 1886(d)(4)(B) and (C) of the Act (82 
FR 38103). Specifically, for these MS-DRGs, the relative weight for FY 
2018 was set at 80 percent of the FY 2017 relative weight. In the FY 
2019 IPPS/LTCH PPS final rule, in response to similar comments, we 
adopted a temporary one-time measure for FY 2019 for an MS-DRG where 
the FY 2018 relative weight declined by 20 percent from the FY 2017 
relative weight and the FY 2019 relative weight would have declined by 
20 percent or more from the FY 2018 relative weight (83 FR 41273). 
Specifically, for an MS-DRG meeting this criterion, we set the FY 2019 
relative weight equal to the FY 2018 relative weight. In the FY 2020 
IPPS/LTCH PPS final rule, in response to similar comments, we adopted a 
temporary one-time measure for FY 2020 for an MS-DRG where the FY 2018 
relative weight declined by 20 percent from the FY 2017 relative weight 
and the FY 2020 relative weight would have declined by 20 percent or 
more from the FY 2019 relative weight, which was maintained at the FY 
2018 relative weight (84 FR 42167). Specifically, for an MS-DRG meeting 
this criterion, we set the FY 2020 relative weight equal to the FY 2019 
relative weight, which was in turn set equal to the FY 2018 relative 
weight.
    In the FY 2021 IPPS/LTCH PPS proposed rule, we noted the one-time 
measure adopted for FY 2020 and sought comment on whether we should 
consider a similar policy for FY 2021, or an alternative approach such 
as averaging the FY 2020 relative weight and the otherwise applicable 
FY 2021 relative weight for MS-DRG 215, which was the only MS-DRG 
impacted by the FY 2020 policy setting the FY 2020 relative weight 
equal to the FY 2019 relative weight. Commenters generally supported 
either setting the FY 2021 weight for MS-DRG 215 equal to the FY 2020 
relative weight or an averaging approach. Some commenters requested 
that CMS consider such an approach when the relative weight for an MS-
DRG is drastically reduced in a given year, particularly when it 
follows a significant decline in prior years. After consideration of 
comments received, and for the reasons discussed in the FY 2021 final 
rule, we set the FY 2021 relative weight for MS-DRG 215 equal to the 
average of the FY 2020 relative weight and the otherwise applicable FY 
2021 weight. With regard to the concerns raised about other MS-DRGs 
with significant reductions relative to FY 2020, we noted that these 
other MS-DRGs were low volume in our claims data, and therefore 
typically experience a greater degree of year-to-year variation. We 
acknowledged the longstanding concerns related to low volume MS-DRGs 
and stated that we would take into consideration the unique issues 
relating to such MS-DRGs and the stability of their weights for future 
rulemaking.
    As we stated in the FY 2023 IPPS/LTCH PPS proposed rule, we have 
continued to consider the comments we received in response to prior 
rulemaking recommending that CMS limit significant declines in the 
relative weights for the MS-DRGs more broadly, including by 
establishing a cap on the degree to which the relative weight for an 
MS-DRG may decline from one fiscal year to the next. For prior fiscal 
years, as previously discussed, we have adopted limited, temporary 
measures to address potentially substantial declines in the relative 
weights in certain outlier circumstances to mitigate the impacts of 
such declines. However, we have also acknowledged commenters' concerns 
related to significant reductions in the weights for other MS-DRGs, in 
particular low volume MS-DRGs. For these low volume MS-DRGs, 
fluctuations in the volume or mix of cases and/or the presence of a few 
high cost or low cost cases can have a disproportionate impact on the 
calculated relative weight, thus resulting in greater year-to-year 
variation in the relative weights for these MS-DRGs. This variation may 
reduce the predictability and stability of an individual hospital's 
Medicare payments from year-to-year. We also recognize that significant 
declines in the relative weights may occur for higher-volume MS-DRGs, 
with such fluctuations likewise affecting the predictability and 
stability of hospital payments.
    In light of these concerns, we have further considered requests 
made by commenters that we address year-to-year fluctuations in 
relative weights, particularly for low volume MS-DRGs, and to mitigate 
the financial impacts of significant fluctuations. In consideration of 
the concerns that commenters have raised about year-to-year 
fluctuations in relative weights and the financial impacts of 
significant fluctuations, we stated in the proposed rule that we 
believe it would be appropriate to limit such fluctuations by applying 
a cap on reductions in the relative weight for an MS-DRG for a given 
fiscal year. Therefore, consistent with our statutory authority under 
section 1886(d)(4)(B) and (C) of the Act to assign and update 
appropriate weighting factors, we proposed a permanent 10-percent cap 
on the reduction in an MS-DRG's relative weight in a given fiscal year, 
beginning in FY 2023. This proposal is consistent with our general 
authority to assign and update appropriate weighting factors as part of 
our annual reclassification of the MS-DRGs and recalibration of the 
relative weights under sections 1886(d)(4)(B) and (C)(i) of the Act, as 
well as the requirements of section 1886(d)(4)(C)(iii) of the Act, 
which specifies that the annual DRG reclassification and recalibration 
of the relative weights be made in a manner that ensures that aggregate 
payments to hospitals are not affected. In addition, we have authority 
to implement this proposed cap and the associated budget neutrality 
adjustment under our special exceptions and adjustments authority at 
section 1886(d)(5)(I)(i) of the Act, which similarly gives the 
Secretary broad authority to provide by regulation for such other 
exceptions and adjustments to the payment amounts under section 1886(d) 
of the Act as the Secretary deems appropriate. As discussed, we believe 
this cap on declines in the relative weights would be appropriate in 
order to promote predictability and stability in hospital payments and 
to mitigate the financial impacts of significant fluctuations in the 
weights. That is, by smoothing year-to-year changes in the MS-DRG 
relative weights, we stated that this proposal would provide greater 
predictability to hospitals, allowing time to adjust to significant 
changes to relative weights. Moreover, consistent with the budget 
neutrality requirement for annual updates to the relative weights, 
including our implementation of similar caps on significant declines in 
the relative weight for prior fiscal years, we believe that application 
of this proposed 10-percent cap on relative weight reductions should 
not increase estimated aggregate Medicare payments beyond the payments 
that would be made had we never applied this cap. Accordingly, we 
proposed to apply a budget neutrality adjustment to the standardized 
amount for all hospitals to ensure that application of the proposed 10-
percent cap does not result in an increase or decrease of estimated 
aggregate payments. For a further discussion of the budget neutrality

[[Page 48899]]

adjustment, we refer readers to the Addendum of the proposed rule and 
this final rule.
    Under this proposal, in cases where the relative weight for a MS-
DRG would decrease by more than 10 percent in a given fiscal year, we 
proposed to limit the reduction to 10 percent for that fiscal year. For 
example, if the relative weight for an MS-DRG in FY 2022 is 1.100 and 
the relative weight for FY 2023 would otherwise be 0.9350, which would 
represent a decrease of 15 percent from FY 2022, the reduction would be 
limited to 10 percent, such that the proposed relative weight for FY 
2023 for MS-DRG XYZ would be 0.9900 (that is, 0.90 x FY 2022 weight of 
1.100). The proposed relative weights for FY 2023 as set forth in Table 
5 associated with the proposed rule and available on the CMS website at 
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS reflect the application of this proposed cap.
    As previously summarized, in the past, we have adopted a temporary 
cap of 20 percent on the decline in an MS-DRG's relative weight to 
address certain outlier circumstances. However, as also previously 
discussed, we recognize that hospitals may benefit from the phase-in of 
smaller declines in the relative weight that may nonetheless contribute 
to less stability and predictability in hospital payment rates. 
Accordingly, for purposes of this proposed permanent cap, we considered 
that a higher cap, such as the 20-percent cap that we have applied 
previously (see, for example, 82 FR 38103), would limit declines in the 
relative weights for fewer MS-DRGs (5 MS-DRGs in our analysis of the 
March 2022 update of the FY 2021 MedPAR claims), while a lower cap, 
such as a 5-percent cap, would limit declines in the relative weights 
for more MS-DRGs (92 MS-DRGs in our analysis of the March 2022 update 
of the FY 2021 MedPAR claims), but with a larger associated budget 
neutrality adjustment to the standardized amount. On balance, we stated 
that we believe that a 10-percent cap would mitigate financial impacts 
resulting from significant fluctuations in the relative weights, 
particularly for low volume MS-DRGs, without the larger budget 
neutrality adjustment associated with a smaller cap. We noted that this 
proposed policy would limit declines in the relative weight for 27 MS-
DRGs, based on the FY 2021 claims data used for the proposed rule; 
based on the March 2022 update of the FY 2021 claims data used for this 
final rule, we note that it would limit declines in the relative 
weights for 31 MS-DRGs.
    We noted that this proposed 10-percent cap on reductions to an MS-
DRG's relative weight would apply only to a given MS-DRG with its 
current MS-DRG number. In cases where CMS creates new MS-DRGs or 
modifies the MS-DRGs as part of its annual reclassifications resulting 
in renumbering of one or more MS-DRGs, we proposed that this limit on 
the reduction in the relative weight would not apply to any MS-DRGs 
affected by the renumbering (that is, the proposed 10-percent cap would 
not apply to the relative weight for any new or renumbered MS-DRGs for 
the fiscal year). We proposed to modify the regulations at Sec.  
412.60(b) to reflect this proposed permanent cap on relative weight 
reductions. We sought comments on our proposal to apply a 10-percent 
cap on decreases in an MS-DRG relative weight from one fiscal year to 
the next.
    Comment: Many commenters supported our proposal to cap yearly 
reductions in an MS-DRG's relative weight to 10%. Commenters stated 
that significant year-over-year reductions can disrupt patient access 
to medically necessary treatment, that large swings are inconsistent 
with the principle of payment stability, and that a permanent 10 
percent cap would provide more time for providers to adjust to 
significant changes in relative weights. A commenter stated that a cap 
on relative weight decreases could incentivize greater innovation, as 
hospitals may avoid MS-DRGs with significant declines, even if they 
offer more innovative, cost-saving treatment approaches. This commenter 
stated that mitigating large year-to-year payment changes would 
encourage providers to use the most clinically appropriate care. 
Commenters also stated that the cap is particularly helpful for low 
volume services, as they stated that shifts in these MS-DRGs are not 
reflective of true changes in the cost of care.
    Some commenters requested that CMS apply the cap in a non-budget 
neutral manner. A commenter requested that CMS monitor for any 
unintended consequences of the cap, given that it is budget neutral.
    Many commenters requested that CMS finalize a permanent lower cap, 
with some commenters expressing concern that with a 10% cap, there are 
still sizable reductions for high-cost MS-DRGs. Other commenters 
requested that CMS finalize a one-year cap of 5%, followed by a 
permanent cap of 10%. Several commenters recommended a permanent 5% 
cap, while others requested CMS set the floor as low as possible. Some 
commenters noted that a broad range of MS-DRGs have weight fluctuations 
in FY 2023 due to unique circumstances, such as the first use of 
hospital data impacted by the COVID-19 PHE for IPPS ratesetting. A 
commenter stated that the 10% cap benefits mostly medical MS-DRGs, 
while many surgical MS-DRGs would experience reductions greater than 5 
percent but less than 10 percent. This commenter stated that capping 
reductions at 5% is consistent with the rationale to blend hospital 
claims with and without COVID-19, due to the uncertainty around the 
degree to which FY 2021 will reflect hospitals' costs and case mix in 
FY 2023. One commenter noted that their analysis of the MS-DRG relative 
weights showed that the average yearly variation in relative weights 
was 5%, so a permanent 5% cap is more in line with historical MS-DRG 
variation. A commenter stated that there is precedent of a 5% cap in 
other parts of the IPPS, such as the wage index.
    One commenter requested that if CMS finalizes a 10% cap, that the 
agency continue to monitor whether a 10% cap is appropriate. A 
commenter requested that CMS update this policy clearly and 
transparently, and with additional stakeholder input, on an annual 
basis to maintain stability and predictability.
    Some commenters acknowledged that setting a lower threshold for the 
cap would necessitate a larger budget neutrality adjustment, but that 
the redistributive impact would be minimal overall. These commenters 
stated that on balance it is still preferable to smooth the impact of 
steep payment declines for a larger number of services.
    One commenter stated that it is premature for CMS to adopt a 
permanent cap, and recommended that CMS implement the 10% cap for FY 
2023 only without a budget neutrality offset. This commenter stated 
that as COVID-19 becomes more endemic in the population, and less 
severe and costly in hospitals, Medicare utilization would be expected 
to return to its former level of annual stability, negating the need 
for a permanent cap on reductions to relative weights.
    A commenter requested that any caps on the maximum annual change to 
the MS-DRG relative weights should not apply to just decreases but to 
increases as well.
    A commenter stated that any new MS-DRG or modified version of an 
existing MS-DRG would benefit from the 10% cap in subsequent years 
following its introduction or modification. This commenter requested 
that CMS apply the 10% cap to all MS-DRGs once the MS-DRG has been 
established and gone through at least one year of the relative weight 
setting

[[Page 48900]]

process. This commenter also requested that CMS consider how this type 
of policy could support long term payment stability for relative 
weights and hospital payments.
    One commenter suggested that similar caps on payment reductions 
would be beneficial under the OPPS and PFS for revised or bundled 
coding updates.
    Response: We appreciate commenters' support for and feedback on our 
proposal. However, we disagree with the suggestion that the proposed 
cap be applied in a non-budget neutral manner. As we stated in the 
IPPS/LTCH PPS proposed rule, our proposal is consistent with the 
requirements of section 1886(d)(4)(C)(iii) of the Act, which specifies 
that the annual DRG reclassification and recalibration of the relative 
weights be made in a manner that ensures that aggregate payments to 
hospitals are not affected. Consistent with this budget neutrality 
requirement for annual updates to the relative weights, we believe that 
application of this proposed 10-percent cap on relative weight 
reductions should not increase estimated aggregate Medicare payments 
beyond the payments that would be made had we never applied this cap. 
This is also consistent with our implementation of similar caps on 
significant declines in the relative weight for prior fiscal years, as 
previously summarized.
    We appreciate commenters' feedback on the size of the cap on year-
to-year declines in an MS-DRG's relative weight, however we disagree 
that we should finalize a lower cap, whether for one year or on a 
permanent basis. As discussed in the proposed rule, after considering 
larger and smaller caps, we determined that on balance, a 10-percent 
cap would promote predictability and mitigate financial impacts 
resulting from significant fluctuations in the relative weights, 
particularly for low volume MS-DRGs, without the larger budget 
neutrality adjustment associated with a smaller cap. With respect to 
commenters who stated that we should finalize a five percent cap 
because there were greater fluctuations due to the first use of the PHE 
data for ratesetting and that many surgical MS-DRGs would experience 
declines of between 5 and 10 percent, we note that declines in relative 
weights between 5 and 10 percent are not uncommon. For example, we note 
that prior to the PHE, and relative to the 25 medical MS-DRGs and 36 
surgical MS-DRGs for which the FY 2023 relative weight is declining 
between 5 and 10 percent as compared to FY 2022 (based on the March 
2022 update of the FY 2021 claims data used for this final rule), for 
the FY 2020 IPPS/LTCH PPS final rule, 27 surgical MS-DRGs and 21 
medical MS-DRGs declined between 5 and 10 percent, and for the FY 2019 
IPPS/LTCH PPS final rule, 32 surgical MS-DRGs and 25 medical MS-DRGs 
declined between 5 and 10 percent. Therefore, we do not believe that 
the number of MS-DRGs for which the FY 2023 relative weight is 
declining between 5 and 10 percent is unusual or necessarily related to 
the first use of the PHE data. We therefore continue to believe that a 
10-percent cap strikes the appropriate balance between considerations 
of promoting predictability and mitigating financial impacts resulting 
from significant fluctuations in the relative weights, without the 
larger budget neutrality adjustment associated with a smaller cap. We 
acknowledge commenters' observation that most MS-DRGs impacted by the 
cap for FY 2023 are medical MS-DRGs; we note that the particular MS-
DRGs impacted in a given year would be expected to fluctuate based on 
changes in the underlying data or as result of reclassifications.
    With respect to the commenters who requested that CMS implement a 
10-percent cap for one year only or update the policy on an annual 
basis, we believe that in order to better promote predictability and 
stability in hospital payments, it is appropriate to finalize a 
permanent 10-percent cap on year-to-year declines in the relative 
weight, beginning with the FY 2023 relative weights. We expect to 
continue to monitor the effects of this cap, including the number of 
MS-DRGs subject to the cap for any given fiscal year, and to present in 
the Addendum to the annual proposed and final rules the budget 
neutrality adjustment for reclassification and recalibration of the MS-
DRG relative weights with application of this cap. We also anticipate 
continuing to make available on the CMS website a supplemental file 
demonstrating the application of the permanent 10 percent cap for 
future years.
    With regard to the comment requesting that caps on maximum changes 
to an MS-DRG's relative weight apply to increases as well, as discussed 
in the IPPS/LTCH PPS proposed rule, our goal in smoothing year-to-year 
changes in the relative weights is to mitigate financial impacts 
associated with significant declines in an MS-DRG's relative weight and 
allow hospitals more time to adjust to such changes by phasing-in these 
declines. In cases where the underlying data or MS-DRG 
reclassifications result in an increase to an MS-DRG's relative weight, 
we do not believe a such a phase-in is appropriate.
    With regard to new or modified MS-DRGs, we are clarifying that 
after the first fiscal year that these new or modified MS-DRGs take 
effect, any changes to the relative weights for those MS-DRGs would 
also be subject to the 10-percent cap.
    With regard to the commenter's suggestion about long-term payment 
stability, we note that the goal of this policy is to smooth year-to-
year changes.
    With regard to similar caps on payment under other payment systems, 
we note that this comment is outside the scope of the proposals 
included in the FY 2023 IPPS/LTCH PPS proposed rule, and we are 
therefore not addressing this comment in this final rule. We may 
consider this comment in connection with future rulemaking.
    After consideration of comments received, we are finalizing the 
proposed permanent 10-percent cap on the reduction in an MS-DRG's 
relative weight in a given fiscal year and the associated budget 
neutrality adjustment to the standardized amount, as previously 
described in this section, beginning in FY 2023. We are also finalizing 
our proposed modifications to the regulations at Sec.  412.60(b) to 
reflect this permanent cap on relative weight reductions. The final 
relative weights for FY 2023 as set forth in Table 5 associated with 
this final rule and available on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS 
reflect the application of this finalized cap. For a further discussion 
of the budget neutrality adjustment for FY 2023, we refer readers to 
the Addendum of this final rule.
3. Development of National Average CCRs
    We developed the national average CCRs as follows:
    Using the FY 2020 cost report data, we removed CAHs, Indian Health 
Service hospitals, all-inclusive rate hospitals, and cost reports that 
represented time periods of less than 1 year (365 days). We included 
hospitals located in Maryland because we include their charges in our 
claims database. Then we created CCRs for each provider for each cost 
center (see the supplemental data file for line items used in the 
calculations) and removed any CCRs that were greater than 10 or less 
than 0.01. We normalized the departmental CCRs by dividing the CCR for 
each department by the total CCR for the hospital for the purpose of 
trimming the data. Then we took the logs of the

[[Page 48901]]

normalized cost center CCRs and removed any cost center CCRs where the 
log of the cost center CCR was greater or less than the mean log plus/
minus 3 times the standard deviation for the log of that cost center 
CCR. Once the cost report data were trimmed, we calculated a Medicare-
specific CCR. The Medicare-specific CCR was determined by taking the 
Medicare charges for each line item from Worksheet D-3 and deriving the 
Medicare-specific costs by applying the hospital-specific departmental 
CCRs to the Medicare-specific charges for each line item from Worksheet 
D-3. Once each hospital's Medicare-specific costs were established, we 
summed the total Medicare-specific costs and divided by the sum of the 
total Medicare-specific charges to produce national average, charge-
weighted CCRs.
    After we multiplied the total charges for each MS-DRG in each of 
the 19 cost centers by the corresponding national average CCR, we 
summed the 19 ``costs'' across each MS-DRG to produce a total 
standardized cost for the MS-DRG. The average standardized cost for 
each MS-DRG was then computed as the total standardized cost for the 
MS-DRG divided by the transfer-adjusted case count for the MS-DRG. The 
average cost for each MS-DRG was then divided by the national average 
standardized cost per case to determine the proposed relative weight.
    As discussed earlier in this section, we are finalizing our 
proposal to (a) use 50 percent of the relative weights calculated using 
all cases in the FY 2021 MedPAR data and 50 percent of the relative 
weights calculated without COVID-19 cases in the FY 2021 MedPAR data to 
calculate the relative weights for FY 2023; and (b) apply a permanent 
10-percent cap on the reduction in a MS-DRG's relative weight in a 
given fiscal year, beginning in FY 2023.
    In developing the relative weights consistent with these finalized 
policies, we first created a set of relative weights using all 
applicable cases in the March 2022 update of the FY 2021 MedPAR data, 
using the methodology as described earlier in this section (Step 1). 
These relative weights were then normalized by an adjustment factor of 
1.948410 so that the average case weight after recalibration was equal 
to the average case weight before recalibration. The normalization 
adjustment is intended to ensure that recalibration by itself neither 
increases nor decreases total payments under the IPPS, as required by 
section 1886(d)(4)(C)(iii) of the Act.
    Next, we created a set of relative weights using the March 2022 
update of the FY 2021 MedPAR data excluding cases with a principal or 
secondary diagnosis of COVID-19 (ICD-10-CM diagnosis code U07.1), and 
otherwise using the methodology as described earlier in this section 
(Step 2). These relative weights were then normalized by an adjustment 
factor of 1.916445.
    We then averaged the results of Step 1 and Step 2 (Step 3), and 
normalized these relative weights by applying an adjustment factor of 
1.000212 (Step 4). This normalization adjustment is intended to ensure 
that this averaging methodology for recalibration of the FY 2023 
relative weights neither increases nor decreases total payments under 
the IPPS, as required by section 1886(d)(4)(C)(iii) of the Act.
    Finally, we applied the 10 percent cap to the relative weights for 
those MS-DRGs for which the relative weight as calculated in Step 4 
would otherwise have declined by more than 10 percent from the FY 2022 
relative weight (Step 5). Specifically, for those MS-DRGs for which the 
relative weight as calculated in Step 4 declined by more than 10 
percent from the FY 2022 relative weight, we set the FY 2023 relative 
weight equal to 90 percent of the FY 2022 relative weight. The relative 
weights for FY 2023 as set forth in Table 5 associated with this final 
rule and available on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS reflect the 
application of this cap. We are also making available a supplemental 
file setting forth the relative weights as calculated with all cases 
(Step 1), excluding cases with a principal or secondary diagnosis of 
COVID-19 (Step 2), following application of the normalization factor 
and prior to the application of this cap (Step 4), and with the 
application of this cap (Step 5) along with the other supplemental 
files for this final rule, on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS.
    The 19 national average CCRs for FY 2023 are as follows:
BILLING CODE 4120-01-P

[[Page 48902]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.074

    Since FY 2009, the relative weights have been based on 100 percent 
cost weights based on our MS-DRG grouping system.
    When we recalibrated the DRG weights for previous years, we set a 
threshold of 10 cases as the minimum number of cases required to 
compute a reasonable weight. We are proposed to use that same case 
threshold in recalibrating the proposed MS-DRG relative weights for FY 
2023. Using data from the FY 2021 MedPAR file, there were 7 MS-DRGs 
that contain fewer than 10 cases. For FY 2023, because we do not have 
sufficient MedPAR data to set accurate and stable cost relative weights 
for these low-volume MS-DRGs, we proposed to compute relative weights 
for the low-volume MS-DRGs by adjusting their final FY 2022 relative 
weights by the percentage change in the average weight of the cases in 
other MS-DRGs from FY 2022 to FY 2023. The crosswalk table is as 
follows.

[[Page 48903]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.075

BILLING CODE 4120-01-C
    We did not receive any public comments on our proposals and we are 
finalizing our proposals without modification.

F. Add-On Payments for New Services and Technologies for FY 2023

1. Background
    Sections 1886(d)(5)(K) and (L) of the Act establish a process of 
identifying and ensuring adequate payment for new medical services and 
technologies (sometimes collectively referred to in this section as 
``new technologies'') under the IPPS. Section 1886(d)(5)(K)(vi) of the 
Act specifies that a medical service or technology will be considered 
new if it meets criteria established by the Secretary after notice and 
opportunity for public comment. Section 1886(d)(5)(K)(ii)(I) of the Act 
specifies that a new medical service or technology may be considered 
for new technology add-on payment if, based on the estimated costs 
incurred with respect to discharges involving such service or 
technology, the DRG prospective payment rate otherwise applicable to 
such discharges under this subsection is inadequate. The regulations at 
42 CFR 412.87 implement these provisions and Sec.  412.87(b) specifies 
three criteria for a new medical service or technology to receive the 
additional payment: (1) the medical service or technology must be new; 
(2) the medical service or technology must be costly such that the DRG 
rate otherwise applicable to discharges involving the medical service 
or technology is determined to be inadequate; and (3) the service or 
technology must demonstrate a substantial clinical improvement over 
existing services or technologies. In addition, certain transformative 
new devices and antimicrobial products may qualify under an alternative 
inpatient new technology add-on payment pathway, as set forth in the 
regulations at Sec.  412.87(c) and (d). We note that section 
1886(d)(5)(K)(i) of the Act requires that the Secretary establish a 
mechanism to recognize the costs of new medical services and 
technologies under the payment system established under that 
subsection, which establishes the system for paying for the operating 
costs of inpatient hospital services. The system of payment for capital 
costs is established under section 1886(g) of the Act. Therefore, as 
discussed in prior rulemaking (72 FR 47307 through 47308), we do not 
include capital costs in the add-on payments for a new medical service 
or technology or make new technology add-on payments under the IPPS for 
capital-related costs.
    In this rule, we highlight some of the major statutory and 
regulatory provisions relevant to the new technology add-on payment 
criteria, as well as other information. For further discussion on the 
new technology add-on payment criteria, we refer readers to the FY 2012 
IPPS/LTCH PPS final rule (76 FR 51572 through 51574), the FY 2020 IPPS/
LTCH PPS final rule (84 FR 42288 through 42300), and the FY 2021 IPPS/
LTCH PPS final rule (85 FR 58736 through 58742).
a. New Technology Add-On Payment Criteria
(1) Newness Criterion
    Under the first criterion, as reflected in Sec.  412.87(b)(2), a 
specific medical service or technology will no longer be considered 
``new'' for purposes of new medical service or technology add-on 
payments after CMS has recalibrated the MS-DRGs, based on available 
data, to reflect the cost of the technology. We note that we do not 
consider a service or technology to be new if it is substantially 
similar to one or more existing technologies. That is, even if a 
medical product receives a new FDA approval or clearance, it may not 
necessarily be considered ``new'' for purposes of new technology add-on 
payments if it is ``substantially similar'' to another medical product 
that was approved or cleared by FDA and has been on the market for more 
than 2 to 3 years. In the FY 2010 IPPS/RY 2010 LTCH PPS final rule (74 
FR 43813 through 43814), we established criteria for evaluating whether 
a new technology is substantially similar to an existing technology, 
specifically whether: (1) a product uses the same or a similar 
mechanism of action to achieve a therapeutic outcome; (2) a product is 
assigned to the same or a different MS-DRG; and (3) the new use

[[Page 48904]]

of the technology involves the treatment of the same or similar type of 
disease and the same or similar patient population. If a technology 
meets all three of these criteria, it would be considered substantially 
similar to an existing technology and would not be considered ``new'' 
for purposes of new technology add-on payments. For a detailed 
discussion of the criteria for substantial similarity, we refer readers 
to the FY 2006 IPPS final rule (70 FR 47351 through 47352) and the FY 
2010 IPPS/LTCH PPS final rule (74 FR 43813 through 43814).
(2) Cost Criterion
    Under the second criterion, Sec.  412.87(b)(3) further provides 
that, to be eligible for the add-on payment for new medical services or 
technologies, the MS-DRG prospective payment rate otherwise applicable 
to discharges involving the new medical service or technology must be 
assessed for adequacy. Under the cost criterion, consistent with the 
formula specified in section 1886(d)(5)(K)(ii)(I) of the Act, to assess 
the adequacy of payment for a new technology paid under the applicable 
MS-DRG prospective payment rate, we evaluate whether the charges of the 
cases involving a new medical service or technology will exceed a 
threshold amount that is the lesser of 75% of the standardized amount 
(increased to reflect the difference between cost and charges) or 75% 
of one standard deviation beyond the geometric mean standardized charge 
for all cases in the MS-DRG to which the new medical service or 
technology is assigned (or the case-weighted average of all relevant 
MS-DRGs if the new medical service or technology occurs in many 
different MS-DRGs). The MS-DRG threshold amounts generally used in 
evaluating new technology add-on payment applications for FY 2023 are 
presented in a data file that is available, along with the other data 
files associated with the FY 2022 IPPS/LTCH PPS final rule and 
correction notice, on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.
    We note that, under the policy finalized in the FY 2021 IPPS/LTCH 
PPS final rule (85 FR 58603 through 58605), beginning with FY 2022, we 
use the proposed threshold values associated with the proposed rule for 
that fiscal year to evaluate the cost criterion for all applications 
for new technology add-on payments and previously approved technologies 
that may continue to receive new technology add-on payments, if those 
technologies would be assigned to a proposed new MS-DRG for that same 
fiscal year.
    As finalized in the FY 2019 IPPS/LTCH PPS final rule (83 FR 41275), 
beginning with FY 2020, we include the thresholds applicable to the 
next fiscal year (previously included in Table 10 of the annual IPPS/
LTCH PPS proposed and final rules) in the data files associated with 
the prior fiscal year. Accordingly, the proposed thresholds for 
applications for new technology add-on payments for FY 2024 were 
presented in a data file that is available on the CMS website, along 
with the other data files associated with the FY 2023 final rule, by 
clicking on the FY 2023 IPPS final rule home page at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.
    As discussed in the FY 2023 IPPS/LTCH PPS proposed rule, in the FY 
2022 IPPS/LTCH PPS final rule, we finalized our proposal to use the FY 
2019 MedPAR claims data where we ordinarily would have used the FY 2020 
MedPAR claims data for purposes of FY 2022 ratesetting. Consistent with 
that final policy, we finalized our proposal to use the FY 2019 claims 
data to set the thresholds for applications for new technology add-on 
payments for FY 2023. We note that, for the reasons discussed in 
section I.F. of the preamble of the proposed rule and this final rule, 
we proposed to use the FY 2021 MedPAR claims data for FY 2023 
ratesetting, with certain proposed modifications to our relative weight 
setting and outlier methodologies. Consistent with this proposal, for 
the FY 2024 proposed threshold values, we proposed to use the FY 2021 
claims data to set the proposed thresholds for applications for new 
technology add-on payments for FY 2024. In addition, as discussed in 
section III.E.1.c. of the proposed rule and this final rule, we 
proposed to use an averaging approach for calculating the FY 2023 
relative weights, to account for the anticipated decline in COVID-19 
hospitalizations of Medicare beneficiaries as compared to FY 2021. 
Specifically, we proposed to average the relative weights as calculated 
with and without COVID-19 cases in the FY 2021 data to determine the 
MS-DRG relative weights for FY 2023. Certain steps of calculating the 
thresholds for applications for new technology add-on payments use the 
same charge data that is used to calculate the MS-DRG weights. As a 
result, different average charges per MS-DRG are calculated using the 
charge data for the relative weights as calculated with and without 
COVID-19 cases. Therefore, for purposes of calculating the FY 2024 
thresholds, we also proposed to average the data in the steps of the 
calculation that use charge data from the calculation of the MS-DRG 
weights. In addition, as discussed in section I.O. of the appendix of 
the FY 2023 IPPS/LTCH proposed rule (87 FR 28740 through 28741), we 
also considered, as an alternative to our proposal, calculating the FY 
2023 MS-DRG relative weights without the proposed averaging approach to 
account for COVID-19 cases. In connection with this alternative 
approach, we made available the threshold values as calculated without 
this averaged data on the ``FY 2023 Final Rule Homepage'' at https://
www.cms.gov/medicare/medicare-fee-for-service-payment/
acuteinpatientpps, as well as other supplemental files as discussed 
further in section I.O. of Appendix A of this final rule.
    As discussed in section I.F. of the preamble of this final rule, we 
are finalizing our proposal to use the FY 2021 MedPAR claims data for 
FY 2023 ratesetting. Also, as discussed in section II.E of this final 
rule we are finalizing our proposal to average the relative weights as 
calculated with and without COVID-19 cases in the FY 2021 data to 
determine the MS-DRG relative weights for FY 2023. We did not receive 
any public comments on our proposal to average the data in the steps of 
the calculation of the FY 2024 thresholds that use charge data from the 
calculation of the MS-DRG weights, as discussed in the proposed rule. 
Accordingly, in this final rule, we are finalizing to use FY 2021 
claims data to set the thresholds for applications for new technology 
add-on payments for FY 2024, and we are also finalizing to average the 
data in the steps of the calculation of the FY 2024 thresholds that use 
charge data from the calculation of the MS-DRG weights, as described 
previously. The finalized thresholds for applications for new 
technology add-on payments for FY 2024 are presented in a data file 
that is available on the CMS website, along with the other data files 
associated with this FY 2023 final rule, by clicking on the FY 2023 
IPPS Final Rule Home Page at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.
    In the September 7, 2001, final rule that established the new 
technology add-on payment regulations (66 FR 46917), we discussed that 
applicants should submit a significant sample of data to demonstrate 
that the medical service or technology meets the high-cost threshold. 
Specifically, applicants should submit a sample of sufficient size to 
enable us to undertake an initial

[[Page 48905]]

validation and analysis of the data. We also discussed in the September 
7, 2001, final rule (66 FR 46917) the issue of whether the Health 
Insurance Portability and Accountability Act (HIPAA) Privacy Rule at 45 
CFR parts 160 and 164 applies to claims information that providers 
submit with applications for new medical service or technology add-on 
payments. We refer readers to the FY 2012 IPPS/LTCH PPS final rule (76 
FR 51573) for further information on this issue.
(3) Substantial Clinical Improvement Criterion
    Under the third criterion at Sec.  412.87(b)(1), a medical service 
or technology must represent an advance that substantially improves, 
relative to technologies previously available, the diagnosis or 
treatment of Medicare beneficiaries. In the FY 2020 IPPS/LTCH PPS final 
rule (84 FR 42288 through 42292), we prospectively codified in our 
regulations at Sec.  412.87(b) the following aspects of how we evaluate 
substantial clinical improvement for purposes of new technology add-on 
payments under the IPPS:
     The totality of the circumstances is considered when 
making a determination that a new medical service or technology 
represents an advance that substantially improves, relative to services 
or technologies previously available, the diagnosis or treatment of 
Medicare beneficiaries.
     A determination that a new medical service or technology 
represents an advance that substantially improves, relative to services 
or technologies previously available, the diagnosis or treatment of 
Medicare beneficiaries means--
    ++ The new medical service or technology offers a treatment option 
for a patient population unresponsive to, or ineligible for, currently 
available treatments;
    ++ The new medical service or technology offers the ability to 
diagnose a medical condition in a patient population where that medical 
condition is currently undetectable, or offers the ability to diagnose 
a medical condition earlier in a patient population than allowed by 
currently available methods, and there must also be evidence that use 
of the new medical service or technology to make a diagnosis affects 
the management of the patient;
    ++ The use of the new medical service or technology significantly 
improves clinical outcomes relative to services or technologies 
previously available as demonstrated by one or more of the following: a 
reduction in at least one clinically significant adverse event, 
including a reduction in mortality or a clinically significant 
complication; a decreased rate of at least one subsequent diagnostic or 
therapeutic intervention; a decreased number of future hospitalizations 
or physician visits; a more rapid beneficial resolution of the disease 
process treatment including, but not limited to, a reduced length of 
stay or recovery time; an improvement in one or more activities of 
daily living; an improved quality of life; or, a demonstrated greater 
medication adherence or compliance; or
    ++ The totality of the circumstances otherwise demonstrates that 
the new medical service or technology substantially improves, relative 
to technologies previously available, the diagnosis or treatment of 
Medicare beneficiaries.
     Evidence from the following published or unpublished 
information sources from within the United States or elsewhere may be 
sufficient to establish that a new medical service or technology 
represents an advance that substantially improves, relative to services 
or technologies previously available, the diagnosis or treatment of 
Medicare beneficiaries: clinical trials, peer reviewed journal 
articles; study results; meta-analyses; consensus statements; white 
papers; patient surveys; case studies; reports; systematic literature 
reviews; letters from major healthcare associations; editorials and 
letters to the editor; and public comments. Other appropriate 
information sources may be considered.
     The medical condition diagnosed or treated by the new 
medical service or technology may have a low prevalence among Medicare 
beneficiaries.
     The new medical service or technology may represent an 
advance that substantially improves, relative to services or 
technologies previously available, the diagnosis or treatment of a 
subpopulation of patients with the medical condition diagnosed or 
treated by the new medical service or technology.
    We refer the reader to the FY 2020 IPPS/LTCH PPS final rule for 
additional discussion of the evaluation of substantial clinical 
improvement for purposes of new technology add-on payments under the 
IPPS.
    We note, consistent with the discussion in the FY 2003 IPPS final 
rule (67 FR 50015), that while FDA has regulatory responsibility for 
decisions related to marketing authorization (for example, approval, 
clearance, etc.), we do not rely upon FDA criteria in our evaluation of 
substantial clinical improvement for purposes of determining what 
drugs, devices, or technologies qualify for new technology add-on 
payments under Medicare. This criterion does not depend on the standard 
of safety and effectiveness on which FDA relies but on a demonstration 
of substantial clinical improvement in the Medicare population.
b. Alternative Inpatient New Technology Add-On Payment Pathway
    Beginning with applications for FY 2021 new technology add-on 
payments, under the regulations at Sec.  412.87(c), a medical device 
that is part of FDA's Breakthrough Devices Program may qualify for the 
new technology add-on payment under an alternative pathway. 
Additionally, under the regulations at Sec.  412.87(d) for certain 
antimicrobial products, beginning with FY 2021, a drug that is 
designated by FDA as a Qualified Infectious Disease Product (QIDP), 
and, beginning with FY 2022, a drug that is approved by FDA under the 
Limited Population Pathway for Antibacterial and Antifungal Drugs 
(LPAD), may also qualify for the new technology add-on payment under an 
alternative pathway. We refer the reader to the FY 2020 IPPS/LTCH PPS 
final rule (84 FR 42292 through 42297) and the FY 2021 IPPS/LTCH PPS 
final rule (85 FR 58737 through 58739) for further discussion on this 
policy. We note that a technology is not required to have the specified 
FDA designation at the time the new technology add-on payment 
application is submitted. CMS reviews the application based on the 
information provided by the applicant only under the alternative 
pathway specified by the applicant at the time of new technology add-on 
payment application submission. However, to receive approval for the 
new technology add-on payment under that alternative pathway, the 
technology must have the applicable FDA designation and meet all other 
requirements in the regulations in Sec.  412.87(c) and (d), as 
applicable.
(1) Alternative Pathway for Certain Transformative New Devices
    For applications received for new technology add-on payments for FY 
2021 and subsequent fiscal years, if a medical device is part of FDA's 
Breakthrough Devices Program and received FDA marketing authorization, 
it will be considered not substantially similar to an existing 
technology for purposes of the new technology add-on payment under the 
IPPS, and will not need to meet the requirement under Sec.  
412.87(b)(1) that it represent an advance that substantially improves,

[[Page 48906]]

relative to technologies previously available, the diagnosis or 
treatment of Medicare beneficiaries. Under this alternative pathway, a 
medical device that has received FDA marketing authorization (that is, 
has been approved or cleared by, or had a De Novo classification 
request granted by, FDA) and that is part of FDA's Breakthrough Devices 
Program will need to meet the requirements of Sec.  412.87(c). We note 
that in the FY 2021 IPPS/LTCH PPS final rule (85 FR 58734 through 
58736), we clarified our policy that a new medical device under this 
alternative pathway must receive marketing authorization for the 
indication covered by the Breakthrough Devices Program designation. We 
refer the reader to the FY 2021 IPPS/LTCH PPS final rule (85 FR 58734 
through 58736) for further discussion regarding this clarification.
(2) Alternative Pathway for Certain Antimicrobial Products
    For applications received for new technology add-on payments for 
certain antimicrobial products, beginning with FY 2021, if a technology 
is designated by FDA as a QIDP and received FDA marketing 
authorization, and, beginning with FY 2022, if a drug is approved under 
FDA's LPAD pathway and used for the indication approved under the LPAD 
pathway, it will be considered not substantially similar to an existing 
technology for purposes of new technology add-on payments and will not 
need to meet the requirement that it represent an advance that 
substantially improves, relative to technologies previously available, 
the diagnosis or treatment of Medicare beneficiaries. Under this 
alternative pathway for QIDPs and LPADs, a medical product that has 
received FDA marketing authorization and is designated by FDA as a QIDP 
or approved under the LPAD pathway will need to meet the requirements 
of Sec.  412.87(d).
    We refer the reader to the FY 2020 IPPS/LTCH PPS final rule (84 FR 
42292 through 42297) and FY 2021 IPPS/LTCH PPS final rule (85 FR 58737 
through 58739) for further discussion on this policy. We note, in the 
FY 2021 IPPS/LTCH PPS final rule (85 FR 58737 through 58739), we 
clarified that a new medical product seeking approval for the new 
technology add-on payment under the alternative pathway for QIDPs must 
receive marketing authorization for the indication covered by the QIDP 
designation. We also finalized our policy to expand our alternative new 
technology add-on payment pathway for certain antimicrobial products to 
include products approved under the LPAD pathway and used for the 
indication approved under the LPAD pathway.
c. Additional Payment for New Medical Service or Technology
    The new medical service or technology add-on payment policy under 
the IPPS provides additional payments for cases with relatively high 
costs involving eligible new medical services or technologies, while 
preserving some of the incentives inherent under an average-based 
prospective payment system. The payment mechanism is based on the cost 
to hospitals for the new medical service or technology. As noted 
previously, we do not include capital costs in the add-on payments for 
a new medical service or technology or make new technology add-on 
payments under the IPPS for capital-related costs (72 FR 47307 through 
47308).
    For discharges occurring before October 1, 2019, under Sec.  
412.88, if the costs of the discharge (determined by applying operating 
cost-to-charge ratios (CCRs) as described in Sec.  412.84(h)) exceed 
the full DRG payment (including payments for IME and DSH, but excluding 
outlier payments), CMS made an add-on payment equal to the lesser of: 
(1) 50% of the costs of the new medical service or technology; or (2) 
50% of the amount by which the costs of the case exceed the standard 
DRG payment.
    Beginning with discharges on or after October 1, 2019, for the 
reasons discussed in the FY 2020 IPPS/LTCH PPS final rule (84 FR 42297 
through 42300), we finalized an increase in the new technology add-on 
payment percentage, as reflected at Sec.  412.88(a)(2)(ii). 
Specifically, for a new technology other than a medical product 
designated by FDA as a QIDP, beginning with discharges on or after 
October 1, 2019, if the costs of a discharge involving a new technology 
(determined by applying CCRs as described in Sec.  412.84(h)) exceed 
the full DRG payment (including payments for IME and DSH, but excluding 
outlier payments), Medicare will make an add-on payment equal to the 
lesser of: (1) 65% of the costs of the new medical service or 
technology; or (2) 65% of the amount by which the costs of the case 
exceed the standard DRG payment. For a new technology that is a medical 
product designated by FDA as a QIDP, beginning with discharges on or 
after October 1, 2019, if the costs of a discharge involving a new 
technology (determined by applying CCRs as described in Sec.  
412.84(h)) exceed the full DRG payment (including payments for IME and 
DSH, but excluding outlier payments), Medicare will make an add-on 
payment equal to the lesser of: (1) 75% of the costs of the new medical 
service or technology; or (2) 75% of the amount by which the costs of 
the case exceed the standard DRG payment. For a new technology that is 
a medical product approved under FDA's LPAD pathway, beginning with 
discharges on or after October 1, 2020, if the costs of a discharge 
involving a new technology (determined by applying CCRs as described in 
Sec.  412.84(h)) exceed the full DRG payment (including payments for 
IME and DSH, but excluding outlier payments), Medicare will make an 
add-on payment equal to the lesser of: (1) 75% of the costs of the new 
medical service or technology; or (2) 75% of the amount by which the 
costs of the case exceed the standard DRG payment. As set forth in 
Sec.  412.88(b)(2), unless the discharge qualifies for an outlier 
payment, the additional Medicare payment will be limited to the full 
MS-DRG payment plus 65% (or 75% for certain antimicrobial products 
(QIDPs and LPADs)) of the estimated costs of the new technology or 
medical service. We refer the reader to the FY 2020 IPPS/LTCH PPS final 
rule (84 FR 42297 through 42300) for further discussion on the increase 
in the new technology add-on payment beginning with discharges on or 
after October 1, 2019.
    Section 503(d)(2) of Public Law 108-173 provides that there shall 
be no reduction or adjustment in aggregate payments under the IPPS due 
to add-on payments for new medical services and technologies. 
Therefore, in accordance with section 503(d)(2) of Public Law 108-173, 
add-on payments for new medical services or technologies for FY 2005 
and subsequent years have not been subjected to budget neutrality.
d. Evaluation of Eligibility Criteria for New Medical Service or 
Technology Applications
    In the FY 2009 IPPS final rule (73 FR 48561 through 48563), we 
modified our regulation at Sec.  412.87 to codify our longstanding 
practice of how CMS evaluates the eligibility criteria for new medical 
service or technology add-on payment applications. That is, we first 
determine whether a medical service or technology meets the newness 
criterion, and only if so, do we then make a determination as to 
whether the technology meets the cost threshold and represents a 
substantial clinical improvement over existing medical services or 
technologies. We specified that all applicants for new technology add-
on payments must have FDA approval or clearance by July 1 of the

[[Page 48907]]

year prior to the beginning of the fiscal year for which the 
application is being considered. In the FY 2021 IPPS/LTCH PPS final 
rule, to more precisely describe the various types of FDA approvals, 
clearances and classifications that we consider under our new 
technology add-on payment policy, we finalized a technical 
clarification to the regulation to indicate that new technologies must 
receive FDA marketing authorization (such as pre-market approval (PMA); 
510(k) clearance; the granting of a De Novo classification request, or 
approval of a New Drug Application (NDA)) by July 1 of the year prior 
to the beginning of the fiscal year for which the application is being 
considered. Consistent with our longstanding policy, we consider FDA 
marketing authorization as representing that a product has received FDA 
approval or clearance when considering eligibility for the new 
technology add-on payment under Sec.  412.87(e)(2) (85 FR 58742).
    Additionally, in the FY 2021 IPPS/LTCH PPS final rule (85 FR 58739 
through 58742), we finalized our proposal to provide conditional 
approval for new technology add-on payment for a technology for which 
an application is submitted under the alternative pathway for certain 
antimicrobial products at Sec.  412.87(d) that does not receive FDA 
marketing authorization by the July 1 deadline specified in Sec.  
412.87(e)(2), provided that the technology otherwise meets the 
applicable add-on payment criteria. Under this policy, cases involving 
eligible antimicrobial products would begin receiving the new 
technology add-on payment sooner, effective for discharges the quarter 
after the date of FDA marketing authorization provided that the 
technology receives FDA marketing authorization by July 1 of the 
particular fiscal year for which the applicant applied for new 
technology add-on payments.
e. New Technology Liaisons
    Many interested parties (including device/biologic/drug developers 
or manufacturers, industry consultants, others) engage CMS for 
coverage, coding, and payment questions or concerns. In order to 
streamline engagement by centralizing the different innovation pathways 
within CMS including new technology add-on payments, CMS has 
established a team of new technology liaisons that can serve as an 
initial resource for interested parties. This team is available to 
assist with all of the following:
     Help to point interested parties to or provide information 
and resources where possible regarding process, requirements, and 
timelines.
     Coordinate and facilitate opportunities for interested 
parties to engage with various CMS components.
     Serve as a primary point of contact for interested parties 
and provide updates on developments where possible or appropriate.
    We received many questions from interested parties with respect to 
pursuing new technology add-on payments who may not be entirely 
familiar with working with CMS. While we encourage interested parties 
to first review our resources available at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/newtech, we 
know that there may be additional questions about the application 
process. Interested parties with further questions about Medicare's 
coverage, coding, and payment processes, and about how they can 
navigate these processes, whether for new technology add-on payments or 
otherwise, can contact the new technology liaison team at 
[email protected].
f. Application Information for New Medical Services or Technologies
    Applicants for add-on payments for new medical services or 
technologies for FY 2024 must submit a formal request, including a full 
description of the clinical applications of the medical service or 
technology and the results of any clinical evaluations demonstrating 
that the new medical service or technology represents a substantial 
clinical improvement (unless the application is under one of the 
alternative pathways as previously described), along with a significant 
sample of data to demonstrate that the medical service or technology 
meets the high-cost threshold. CMS will review the application based on 
the information provided by the applicant under the pathway specified 
by the applicant at the time of application submission. Complete 
application information, along with final deadlines for submitting a 
full application, will be posted as it becomes available on the CMS 
website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/newtech.html. To allow interested parties to 
identify the new medical services or technologies under review before 
the publication of the final rule for FY 2024, the CMS website also 
will post the tracking forms completed by each applicant. We note that 
the burden associated with this information collection requirement is 
the time and effort required to collect and submit the data in the 
formal request for add-on payments for new medical services and 
technologies to CMS. The aforementioned burden is subject to the Paper 
Reduction Act (PRA) and approved under OMB control number 0938-1347, 
and has an expiration date of 11/30/2023.
    As discussed previously, in the FY 2020 IPPS/LTCH PPS final rule, 
we adopted an alternative inpatient new technology add-on payment 
pathway for certain transformative new devices and for Qualified 
Infectious Disease Products, as set forth in the regulations at Sec.  
412.87(c) and (d). The change in burden associated with these changes 
to the new technology add-on payment application process were discussed 
in a revision of the information collection requirement (ICR) request 
currently approved under OMB control number 0938-1347, with an 
expiration date of November 30, 2023. In accordance with the 
implementing regulations of the PRA, we detailed the revisions of the 
ICR and published the required 60-day notice on August 15, 2019 (84 FR 
41723), and 30-day notice on December 17, 2019 (84 FR 68936), to 
solicit public comments.
2. Public Input Before Publication of a Notice of Proposed Rulemaking 
on Add-On Payments
    Section 1886(d)(5)(K)(viii) of the Act, as amended by section 
503(b)(2) of Public Law 108-173, provides for a mechanism for public 
input before publication of a notice of proposed rulemaking regarding 
whether a medical service or technology represents a substantial 
clinical improvement. The process for evaluating new medical service 
and technology applications requires the Secretary to do all of the 
following:
     Provide, before publication of a proposed rule, for public 
input regarding whether a new service or technology represents an 
advance in medical technology that substantially improves the diagnosis 
or treatment of Medicare beneficiaries.
     Make public and periodically update a list of the services 
and technologies for which applications for add-on payments are 
pending.
     Accept comments, recommendations, and data from the public 
regarding whether a service or technology represents a substantial 
clinical improvement.
     Provide, before publication of a proposed rule, for a 
meeting at which organizations representing hospitals, physicians, 
manufacturers, and any other interested party may present comments, 
recommendations, and data

[[Page 48908]]

regarding whether a new medical service or technology represents a 
substantial clinical improvement to the clinical staff of CMS.
    In order to provide an opportunity for public input regarding add-
on payments for new medical services and technologies for FY 2023 prior 
to publication of the FY 2023 IPPS/LTCH PPS proposed rule, we published 
a notice in the Federal Register on September 24, 2021 (86 FR 53056), 
and held a virtual town hall meeting on December 14, 2021. In the 
announcement notice for the meeting, we stated that the opinions and 
presentations provided during the meeting would assist us in our 
evaluations of applications by allowing public discussion of the 
substantial clinical improvement criterion for the FY 2023 new medical 
service and technology add-on payment applications before the 
publication of the FY 2023 IPPS/LTCH IPPS proposed rule.
    Approximately 378 individuals registered to attend the virtual town 
hall meeting. We posted the recordings of the virtual town hall on the 
CMS web page at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/newtech.
    We considered each applicant's presentation made at the town hall 
meeting, as well as written comments received by the December 27, 2021, 
deadline, in our evaluation of the new technology add-on payment 
applications for FY 2023 in the development of the FY 2023 IPPS/LTCH 
PPS proposed rule. In response to the published notice and the December 
14, 2021, New Technology Town Hall meeting, we received written 
comments regarding the applications for FY 2023 new technology add on 
payments. As explained earlier and in the Federal Register notice 
announcing the New Technology Town Hall meeting (86 FR 53056 through 
53059), the purpose of the meeting was specifically to discuss the 
substantial clinical improvement criterion with regard to pending new 
technology add-on payment applications for FY 2023. Therefore, we did 
not summarize the written comments in the proposed rule that are 
unrelated to the substantial clinical improvement criterion. In section 
II.F.6. of the preamble of the proposed rule, we summarized comments 
regarding individual applications, or, if applicable, indicated that 
there were no comments received in response to the New Technology Town 
Hall meeting notice or New Technology Town Hall meeting, at the end of 
each discussion of the individual applications.
3. ICD-10-PCS Section ``X'' Codes for Certain New Medical Services and 
Technologies
    As discussed in the FY 2016 IPPS/LTCH PPS final rule (80 FR 49434), 
the ICD-10-PCS includes a new section containing the new Section ``X'' 
codes, which began being used with discharges occurring on or after 
October 1, 2015. Decisions regarding changes to ICD-10-PCS Section 
``X'' codes will be handled in the same manner as the decisions for all 
of the other ICD-10-PCS code changes. That is, proposals to create, 
delete, or revise Section ``X'' codes under the ICD-10-PCS structure 
will be referred to the ICD-10 Coordination and Maintenance Committee. 
In addition, several of the new medical services and technologies that 
have been, or may be, approved for new technology add-on payments may 
now, and in the future, be assigned a Section ``X'' code within the 
structure of the ICD-10-PCS. We posted ICD-10-PCS Guidelines on the CMS 
website at https://www.cms.gov/medicare/icd-10/2021-icd-10-pcs, 
including guidelines for ICD-10-PCS Section ``X'' codes. We encourage 
providers to view the material provided on ICD-10-PCS Section ``X'' 
codes.
    As discussed in more detail in section II.F.8. of the preamble of 
this final rule, in the FY 2023 IPPS/LTCH PPS proposed rule, we 
proposed to use NDCs instead of ICD-10-PCS Section ``X'' codes to 
identify cases involving the use of therapeutic agents approved for new 
technology add-on payments beginning with a transitional period in FY 
2023. We refer the reader to section II.F.8. of the preamble of this 
final rule for a full discussion of this proposal and the comments 
received.
4. New COVID-19 Treatments Add-On Payment (NCTAP)
    In response to the COVID-19 public health emergency (PHE), we 
established the New COVID-19 Treatments Add-on Payment (NCTAP) under 
the IPPS for COVID-19 cases that meet certain criteria (85 FR 71157 
through 71158). We believe that as drugs and biological products become 
available and are authorized for emergency use or approved by FDA for 
the treatment of COVID-19 in the inpatient setting, it is appropriate 
to increase the current IPPS payment amounts to mitigate any potential 
financial disincentives for hospitals to provide new COVID-19 
treatments during the PHE. Therefore, effective for discharges 
occurring on or after November 2, 2020 and until the end of the PHE for 
COVID-19, we established the NCTAP to pay hospitals the lesser of (1) 
65% of the operating outlier threshold for the claim or (2) 65% of the 
amount by which the costs of the case exceed the standard DRG payment, 
including the adjustment to the relative weight under section 3710 of 
the Coronavirus Aid, Relief, and Economic Security (CARES) Act, for 
certain cases that include the use of a drug or biological product 
currently authorized for emergency use or approved for treating COVID-
19.
    In the FY 2022 IPPS/LTCH PPS final rule, we finalized a change to 
our policy to extend NCTAP through the end of the FY in which the PHE 
ends for all eligible products in order to continue to mitigate 
potential financial disincentives for hospitals to provide these new 
treatments, and to minimize any potential payment disruption 
immediately following the end of the PHE. We also finalized that, for a 
drug or biological product eligible for NCTAP that is also approved for 
new technology add-on payments, we will reduce the NCTAP for an 
eligible case by the amount of any new technology add-on payments so 
that we do not create a financial disincentive between technologies 
eligible for both the new technology add-on payment and NCTAP compared 
to technologies eligible for NCTAP only (85 FR 45162).
    Further information about NCTAP, including updates and a list of 
currently eligible drugs and biologicals, is available on the CMS 
website at https://www.cms.gov/medicare/covid-19/new-covid-19-treatments-add-payment-nctap.
5. FY 2023 Status of Technologies Receiving New Technology Add-On 
Payments for FY 2022
    In this section of the final rule, we discuss the proposed FY 2023 
status of 37 technologies approved for FY 2022 new technology add-on 
payments, including 2 technologies approved for 2 separate add-on 
payments for different indications (RECARBRIOTM and 
FETROJA[supreg]), and our finalized policies, as set forth in the 
tables that follow. In general, we extend new technology add-on 
payments for an additional year only if the 3-year anniversary date of 
the product's entry onto the U.S. market occurs in the latter half of 
the upcoming fiscal year. We note that, as discussed later in this 
section, we provided a 1-year extension of new technology add-on 
payments for FY 2022 for 13 technologies for which the new technology 
add-on payment would otherwise have been discontinued beginning in FY 
2022 using our authority under section 1886(d)(5)(I) of the Act.

[[Page 48909]]

    Additionally, we note that we conditionally approved CONTEPO for FY 
2022 new technology add-on payments under the alternative pathway for 
certain antimicrobial products (86 FR 45155), subject to the technology 
receiving FDA marketing authorization by July 1, 2022. In the FY 2023 
IPPS LTCH/PPS proposed rule, we stated that if CONTEPO receives FDA 
marketing authorization prior to July 1, 2022, we were proposing to 
continue making new technology add-on payments for CONTEPO for FY 2023. 
We stated that if CONTEPO does not receive FDA marketing authorization 
by July 1, 2022, then it would not be eligible for new technology add-
on payments for FY 2022, and therefore would not be eligible for the 
continuation of new technology add-on payments for FY 2023. Because 
CONTEPO did not receive FDA approval by July 1, 2022, no new technology 
add-on payments will be made for cases involving the use of CONTEPO for 
FY 2022, and CONTEPO is therefore not eligible for the continuation of 
new technology add-on payments for FY 2023.
a. FY 2023 Status of Technologies Approved for FY 2022 New Technology 
Add-On Payments
    As noted previously, we used our authority under section 
1886(d)(5)(I) of the Act to allow a 1-year extension of new technology 
add-on payments for FY 2022 for 13 technologies for which the add-on 
payments would otherwise be discontinued beginning in FY 2022 because 
the technologies would no longer be considered ``new'' for FY 2022. In 
this section, we discuss the proposed FY 2023 status for the remaining 
24 technologies approved for FY 2022 new technology add-on payments and 
our finalized policies. Specifically, in the FY 2023 IPPS/LTCH PPS 
proposed rule (87 FR 28210-28212), we presented our proposals to 
continue the new technology add-on payment for FY 2023 for those 
technologies that were approved for the new technology add-on payment 
for FY 2022 and which would still be considered ``new'' for purposes of 
new technology add-on payments for FY 2023. We also presented our 
proposals to discontinue new technology add-on payment for FY 2023 for 
those technologies that were approved for the new technology add-on 
payment for FY 2022 and which would no longer be considered ``new'' for 
purposes of new technology add-on payments for FY 2023.
    Our policy is that a medical service or technology may continue to 
be considered ``new'' for purposes of new technology add-on payments 
within 2 or 3 years after the point at which data begin to become 
available reflecting the inpatient hospital code assigned to the new 
service or technology. Our practice has been to begin and end new 
technology add-on payments on the basis of a fiscal year, and we have 
generally followed a guideline that uses a 6-month window before and 
after the start of the fiscal year to determine whether to extend the 
new technology add-on payment for an additional fiscal year. In 
general, we extend new technology add-on payments for an additional 
year only if the 3-year anniversary date of the product's entry onto 
the U.S. market occurs in the latter half of the fiscal year (70 FR 
47362).
    In the proposed rule, we provided a table listing the technologies 
for which we proposed to continue making new technology add-on payments 
for FY 2023 because they would still be considered ``new'' for purposes 
of new technology add-on payments (87 FR 28213 through 28214). This 
table also presented the newness start date, new technology add-on 
payment start date, 3-year anniversary date of the product's entry onto 
the U.S. market, relevant final rule citations from prior fiscal years, 
proposed maximum add-on payment amount, and coding assignments for each 
technology. We referred readers to the final rules cited in the table 
for a complete discussion of the new technology add-on payment 
application, coding and payment amount for each of these technologies, 
including the applicable indications and discussion of the newness 
start date.
    We invited public comments on our proposals to continue new 
technology add-on payments for FY 2023 for the technologies listed in 
the table in the proposed rule.
    Comment: Commenters overwhelmingly supported our proposed 
continuation of new technology add-on payments for FY 2023 for those 
technologies that were approved for the new technology add-on payment 
for FY 2022 and which would still be considered ``new'' for purposes of 
new technology add-on payments for FY 2023.
    Response: We appreciate the commenters' support.
    In the proposed rule, we noted, as discussed in the FY 2022 IPPS/
LTCH PPS final rule (86 FR 45104 through 45107), on May 1, 2020, 
VEKLURY[supreg] (remdesivir) received an Emergency Use Authorization 
(EUA) from FDA for the treatment of suspected or laboratory confirmed 
COVID-19 in adults and children hospitalized with severe disease. The 
applicant asserted that between July 1, 2020 and September 30, 2020, it 
entered into an agreement with the U.S. Government to allocate and 
distribute commercially-available VEKLURY[supreg] across the country. 
The applicant stated that under this agreement, the first sale of 
VEKLURY[supreg] was completed on July 10, 2020. The applicant stated 
that they transitioned to a more traditional, unallocated model of 
distribution as of October 1, 2020. In the FY 2022 IPPS/LTCH PPS final 
rule (86 FR 45107), we determined that VEKLURY[supreg] meets the 
newness criterion with an indication for use in adults and pediatric 
patients (12 years of age and older and weighing at least 40 kg) for 
the treatment of COVID-19 requiring hospitalization. We stated that 
consistent with our longstanding policy, we considered the newness 
period for VEKLURY[supreg] to begin on October 22, 2020, when the NDA 
for VEKLURY[supreg] was approved by FDA for adults and pediatric 
patients (12 years of age and older and weighing at least 40 kg) for 
the treatment of COVID-19 requiring hospitalization. We also discussed 
comments solicited regarding the newness period for products available 
through an EUA for COVID-19 in section II.F.7. of the FY 2022 IPPS/LTCH 
PPS final rule (86 FR 45159 through 45160), including comments we 
received regarding the potential variability in cost estimates for 
technologies available under an EUA due to government price subsidies 
or variable treatment practices in the context of the global pandemic 
and comments suggesting that CMS monitor pricing changes for products 
available under an EUA once a product receives full marketing 
authorization, instead of basing the newness period on data that may 
have become available under an EUA, and indicated that we would 
consider these comments for future rulemaking.
    We stated in the proposed rule (87 FR 28212) that after further 
review of the information provided by the applicant, we believed that 
additional information related to VEKLURY[supreg]'s commercial 
availability is relevant to assessing the start of the newness period 
for VEKLURY[supreg]. We noted that the applicant stated that once 
VEKLURY[supreg] was issued an EUA, from May through June 2020, the 
entire existing supply of VEKLURY[supreg] was donated worldwide and 
distributed to hospitals free of charge.\29\ The applicant further 
stated that the commercial list price of the technology was announced 
when it entered into the agreement with the U.S.

[[Page 48910]]

Government previously described, in anticipation of the post-donation 
phase. Under this agreement, the U.S. Government allocated 
VEKLURY[supreg] to each hospital, and the hospitals would then choose 
to purchase quantities of VEKLURY[supreg] directly from the applicant's 
subsidiary who was the sole distributor.30 31
---------------------------------------------------------------------------

    \29\ https://stories.gilead.com/articles/an-update-on-covid-19-from-our-chairman-and-ceo.
    \30\ Remdesivir for the Commercial Marketplace. https://www.phe.gov/emergency/events/COVID19/investigation-MCM/Pages/factsheet.aspx.
    \31\ Department of Health and Human Services, Office of the 
Assistant Secretary for Preparedness and Response (ASPR). ASPR's 
Portfolio of COVID-19 Medical Countermeasures Made Available as a 
Licensed Product. https://www.phe.gov/emergency/events/COVID19/investigation-MCM/Pages/Veklury.aspx.
---------------------------------------------------------------------------

    We stated in the proposed rule that we continue to believe this 
issue is complex, particularly as it relates to VEKLURY[supreg] as a 
technology that has been available under both an EUA and an NDA. As 
discussed in the FY 2022 IPPS/LTCH PPS final rule (86 FR 45159 through 
45160), while an EUA is not marketing authorization within the meaning 
of Sec.  412.87(e)(2) for purposes of eligibility for new technology 
add-on payments, data reflecting the costs of products that have 
received an EUA could become available as soon as the date of the EUA 
issuance and prior to receiving FDA approval or clearance. In the case 
of VEKLURY[supreg], we stated that we believe that there may be unique 
considerations in determining the start of the newness period in light 
of the donation period, during which the technology was distributed at 
no cost. Accordingly, while we noted that we continue to believe that 
data reflecting the costs of a product that has received an EUA could 
become available as soon as the date of EUA issuance for that product, 
we believed that with respect to VEKLURY[supreg], such data may not 
have become available until after the end of the donation period, when 
the technology became commercially available, on July 1, 2020. For 
these reasons, after further consideration, we stated that we believe 
the newness period for VEKLURY[supreg] may more appropriately begin on 
July 1, 2020, the date on which the technology became available for 
sale under the allocation agreement. We noted that VEKLURY[supreg] 
would still be considered new for FY 2023 regardless of whether the 
newness period began on May 1 (the date of the EUA), July 1 (the date 
the donation phase ended), October 22 (the date of the NDA), or some 
other date in between, as in all cases the three-year anniversary date 
would occur after April 1, 2023, and therefore the product would remain 
eligible for FY 2023 new technology add-on payments.
    Therefore, we proposed to continue new technology add-on payments 
for VEKLURY[supreg] for FY 2023. We invited public comments on this 
proposal, including the newness start date for VEKLURY[supreg]. As 
discussed, while we continue to believe that data reflecting the costs 
of a product that has received an EUA could become available as soon as 
the date of EUA issuance for that product, we also recognize that there 
may be unique considerations in determining the start of the newness 
period for a product available under an EUA. We are continuing to 
consider the comments as discussed in the FY 2022 IPPS/LTCH PPS final 
rule (86 FR 45159) regarding the newness period for products available 
through an EUA for COVID-19, and we welcomed additional comments in the 
proposed rule.
    Comment: The applicant submitted a comment with respect to the 
start of the newness period for VEKLURY[supreg]. The applicant noted 
that there is no material impact on eligibility for new technology add-
on payments for VEKLURY[supreg], regardless of whether CMS uses July 1 
2020, the date VEKLURY[supreg] became available for sale under the 
allocation agreement, or October 22, 2020, the date of FDA approval as 
the start of the newness period for VEKLURY[supreg]. The applicant 
maintained that using either date and applying CMS' standard 
methodology of calculating the period of eligibility for new technology 
add-on payments would result in VEKLURY[supreg] staying within its 
newness period through FY 2023 (October 1, 2022-September 30, 2023), 
and that VEKLURY[supreg] would not be eligible for new technology add-
on payments in FY 2024 in either circumstance.
    The applicant stated that the primary effect of CMS' revisiting of 
the VEKLURY[supreg] newness determination would be to set a precedent 
that would affect the future eligibility for new technology add-on 
payments of other EUA products. To this point, the applicant referred 
to the FY 2022 IPPS final rule where CMS originally finalized the 
newness date for VEKLURY[supreg] and stated that products that do not 
have FDA approval or clearance, including products available in the 
U.S. under an EUA, are not eligible for new technology add-on payments 
(86 FR 45106-07). The applicant also pointed to 42 CFR 412.87(b) which 
outlines additional eligibility criteria for substantial clinical 
improvement, cost, and newness that must all be met in order for a 
product to be eligible for new technology add-on payments. The 
applicant stated it is reasonable to assume these requirements should 
not be in conflict with respect to how they are evaluated and 
implemented, including with respect to the timelines applied to the 
determination of eligibility for new technology add-on payments.
    Furthermore, the applicant stated that CMS confirmed that using the 
date of FDA approval as the beginning of the newness period for 
VEKLURY[supreg] was consistent with its longstanding policy, with the 
commenter referencing CMS's statement that generally, its policy is 
``to begin the newness period on the date of FDA approval or clearance 
or, if later, the date of availability of the product on the U.S. 
market, when [data] reflecting the costs of the technology begin to 
become available for the recalibration of the MS-DRGs'' (86 FR 45159) 
(emphasis added). The applicant asserted that using a date prior to FDA 
approval as the beginning of the newness period would therefore serve 
as a departure from how CMS has traditionally determined newness for 
the purposes of new technology add-on payments, as there is no 
precedent to use a date earlier than FDA approval as the date of market 
availability.
    The applicant stated that VEKLURY[supreg]'s distribution and 
commercialization framework over the course of the COVID-19 pandemic, 
through which VEKLURY[supreg] was available through emergency and 
compassionate use programs, donations, and a post-donation model in 
collaboration with the federal government, were all implemented prior 
to VEKLURY[supreg] receiving FDA approval and does not in any way 
resemble the current distribution and reimbursement paradigm. The 
applicant further stated that its experience during the EUA period does 
not reflect the type of distribution and reimbursement environment that 
would support a newness period that begins prior to the FDA approval 
date for VEKLURY[supreg]. The applicant stated that the data collected 
on utilization and resource use during the EUA period likely would not 
be representative of utilization or resource use following FDA 
approval, given that the EUA period occurred within the context of a 
global pandemic and a time of extreme uncertainty for the health care 
system. The applicant pointed to CMS's use of FY 2019 data for FY 2022 
ratesetting for circumstances where the FY 2020 data was significantly 
impacted by the COVID-19 PHE, and reasoned that VEKLURY[supreg]'s 
utilization would be similarly impacted by the PHE as its EUA period 
occurred almost entirely in FY 2020.

[[Page 48911]]

    The applicant urged that CMS continue to determine the start of the 
newness period for VEKLURY[supreg] and other products originally 
available in the U.S. under an EUA using what it stated was the same 
policy CMS has applied for all other products approved for new 
technology add-on payment, which is to use the date of FDA approval or, 
if later, the date of market availability in the U.S. For 
VEKLURY[supreg], the applicant stated that this date is October 22, 
2020, the date of FDA approval. The applicant stated that maintaining 
this policy aligns to existing precedent, simplifies the newness 
determination process, and applies a consistent policy across products.
    Response: We thank the applicant for its input. As discussed in the 
FY 2018 IPPS final rule (82 FR 38115), the period of newness does not 
necessarily start with the approval date for the medical service or 
technology and instead begins with availability of the product on the 
U.S. market, which is when data become available. We have consistently 
applied this standard and believe that it is consistent with the 
purpose of new technology add-on payments. Therefore, while generally 
our policy is to begin the newness period on the date of FDA approval 
or clearance, we may also consider a documented delay in the 
technology's market availability in our determination of newness (77 FR 
53348 and 70 FR 47341). Accordingly, we agree that in general, we have 
begun the newness period on the date of FDA approval or clearance or, 
if later, the date of availability of the product onto the US market, 
based on such a documented delay, as that is when data reflecting the 
costs of the technology begin to become available. However, as we 
discussed in the FY 2022 final rule, for a product with an EUA, the 
data reflecting the costs of that product could become available as 
soon as the date of EUA issuance, and prior to FDA approval or 
clearance. Therefore, while a product approved under an EUA and for 
which there is data reflecting the costs of the technology prior to FDA 
approval may be factually distinct from a product for which there is a 
documented delay in marketing availability following FDA approval, we 
disagree that beginning the newness period on the date of EUA issuance 
and prior to FDA approval would be inconsistent with our longstanding 
policy of beginning the newness period with the availability of the 
product on the U.S. market. With regard to the additional criteria for 
eligibility for the new technology add-on payment, we refer readers to 
the FY 2022 final rule for our discussion of the eligibility of a 
product available only through an EUA for the new technology add-on 
payment under section 412.87(e)(2) (86 FR 45048 through 45049), as well 
as the comment solicitation on the new technology add-on payment 
newness period for products available through an EUA (86 FR 45159 
through 45160). With respect to the applicant's comment that 
VEKLURY[supreg]'s utilization may have been impacted by the COVID-19 
PHE during the EUA period, we note that the EUA for VEKLURY[supreg] was 
directly related to COVID-19.
    We agree with the applicant that regardless of whether 
VEKLURY's[supreg] newness period begins on July 1, 2020, the date 
VEKLURY[supreg] became available for sale under the allocation 
agreement, or October 22, 2020, the date of FDA approval, the 
application of CMS' standard methodology for determining the period of 
eligibility for new technology add-on payments results in 
VEKLURY[supreg] remaining within its newness period through FY 2023 
(October 1, 2022-September 30, 2023), and that VEKLURY[supreg] would 
not be eligible for new technology add-on payments in FY 2024 in either 
circumstance. Accordingly, we are finalizing our proposal to continue 
new technology add-on payments for VEKLURY[supreg] for FY 2023, as 
reflected in Table II.F.-01 of this final rule. As stated previously, 
we also recognize that there may be unique considerations associated 
with determining the start of the newness period for a product 
available under an EUA prior to receiving FDA approval, including as 
discussed in the applicant's comments. Accordingly, we will continue to 
consider the comments received regarding the newness period for 
products available through an EUA for COVID-19 for future rulemaking.
    In the FY 2023 IPPS/LTCH PPS proposed rule, we noted that we also 
proposed to continue new technology add-on payments for Caption 
Guidance for FY 2023, a technology sold on a subscription basis. We 
stated we continued to welcome comments from the public as to the 
appropriate method to determine a cost per case for technologies sold 
on a subscription basis, including comments on whether the cost per 
case should be estimated based on subscriber hospital data as described 
previously, and if so, whether the cost analysis should be updated 
based on the most recent subscriber data for each year for which the 
technology may be eligible for the new technology add-on payment.
    We did not receive any comments regarding the appropriate method to 
determine a cost per case for technologies sold on a subscription 
basis, and we will continue to consider these issues.
    Comment: The applicant for Abecma[supreg] submitted a comment 
stating its strong support for the continuation of new technology add-
on payments for Abecma[supreg] for FY 2023. The applicant stated that 
although Abecma[supreg] received FDA approval on March 26, 2021, it did 
not enter the U.S. market until May 10, 2021, when the date of first 
sale occurred and the new technology was first reflected in claims 
data. The applicant stated that the newness period for Abecma[supreg] 
should therefore begin on May 10, 2021 as CMS' policy is to begin the 
newness period on the date of a product's entry onto the U.S. market. 
The applicant further stated that Abecma[supreg]'s new technology add-
on payment status should be extended beyond FY 2023, as CMS policy is 
to extend new technology add-on payments for an additional year when 
the 3-year anniversary of market entry occurs in the latter half of the 
fiscal year.
    Response: We thank the applicant for its comment. As stated 
previously, while CMS may consider a documented delay in the 
technology's market availability in our determination of newness, our 
policy for determining whether to extend new technology add-on payments 
for an additional year generally applies regardless of the volume of 
claims for the technology after the beginning of the newness period (83 
FR 41280). We do not consider the date of first sale of a product as an 
indicator of the entry of a product onto the U.S. market. The applicant 
states that the date of first sale of Abecma[supreg] was May 10, 2021, 
but it is unclear from the information provided when the technology 
first became available for sale and, absent additional information from 
the applicant, we cannot determine a newness date based on a documented 
delay in the technology's availability on the U.S. market.
    We further note that, as discussed in section II.F.6.a. of the 
preamble of this final rule, because CARVYKTITM is 
substantially similar to ABECMA[supreg], we are using a single cost for 
purposes of determining the new technology add-on payment amount for 
CARVYKTITM and ABECMA[supreg] for FY 2023. As discussed in 
section II.F.6.a., we determined a weighted average of the cost of 
CARVYKTITM and ABECMA[supreg] based upon the projected 
numbers of cases involving each technology to determine

[[Page 48912]]

the maximum new technology add-on payment. To compute the weighted cost 
average, we summed the total number of projected cases for each of the 
applicants, which equaled 420 cases (241 plus 179). We then divided the 
number of projected cases for each of the applicants by the total 
number of cases, which resulted in the following case weighted 
percentages: 57% for CARVYKTITM and 43% for ABECMA[supreg]. 
We then multiplied the cost per case for the manufacturer specific drug 
by the case-weighted percentage (0.57 * $465,000 = $265,050 for 
CARVYKTITM and 0.43 * $419,500 = $180,385 for 
ABECMA[supreg]). This resulted in a case-weighted average cost of 
$445,435 for the technology.
    Under Sec.  412.88(a)(2), we limit new technology add-on payments 
to the lesser of 65% of the average cost of the technology, or 65% of 
the costs in excess of the MS-DRG payment for the case. As a result, 
the maximum new technology add-on payment for a case involving the use 
of CARVYKTITM and ABECMA[supreg] is $289,532.75 for FY 2023, 
as is reflected in Table II.F.-01 of this final rule.
    Comment: Several commenters requested that CMS update the maximum 
new technology add-on payment amount to reflect the current Wholesale 
Acquisition Cost (WAC) per vial of their respective technologies. The 
applicant for ZepzelcaTM requested the maximum new 
technology add-on payment amount for ZepzelcaTM be updated 
from $8,622.90 to $9,145.50 to reflect the updated WAC of $7,035 per 
vial of ZepzelcaTM. The applicant for CoselaTM 
requested the maximum new technology add-on payment amount for 
CoselaTM be updated to reflect the updated WAC of $1,439 per 
vial of CoselaTM.
    Response: We appreciate the updated cost information. 
ZepzelcaTM's current new technology add-on payment amount is 
$8,622.90 for 2 single-dose vials and reflects the WAC at the time of 
ZepzelcaTM's entry onto the U.S. market (2 single-dose vials 
per dose x $6,633 per vial multiplied by 0.65). For FY 2023, the 
maximum new technology add-on payment amount using the updated WAC is 
$9,145.50 (2 single-dose vials per dose x $7,035 per vial multiplied by 
0.65), as reflected in Table II.F.-01 in this final rule.
    Similarly, CoselaTM's current new technology add-on 
payment amount is $5,526.30 (3 doses of CoselaTM x 2 single-
dose vials per dose x $1,417 per vial multiplied by 0.65). For FY 2023, 
the maximum new technology add-on payment amount using the updated WAC 
is $5,612.10 (3 doses of CoselaTM x 2 single-dose vials x 
$1,439 per vial multiplied by 0.65) as reflected in Table II.F.-01 in 
this final rule.
    After consideration of the public comments we received, we are 
finalizing our proposal to continue new technology add-on payments for 
FY 2023 for the technologies that were approved for new technology add-
on payment for FY 2022 and would still be considered ``new'' for 
purposes of new technology add-on payments for FY 2023, as listed in 
the proposed rule and in the following Table II.F.-01 in this section 
of this final rule.
    We note that Table II.F.-01 below is the same as Table II.F.-02 
that was presented in the proposed rule, but Table II.F.-01 in this 
final rule includes the updated cost information for 
ZepzelcaTM, CoselaTM, and Abecma[supreg], as 
discussed previously. Table II.F.-01 also includes updated cost 
information for aScope Duodeno[supreg] to reflect the cost of the 
technology alone, rather than a case-weighted average with EXALT Model 
DTM, as discussed later in this section. The following table 
also presents the newness start date, new technology add-on payment 
start date, 3-year anniversary date of the product's entry onto the 
U.S. market, relevant final rule citations from prior fiscal years, 
maximum add-on payment amount, and coding assignments. We refer readers 
to the final rules cited in the following table for a complete 
discussion of the new technology add-on payment application, coding and 
payment amount for these technologies, including the applicable 
indications and discussion of the newness start date.
BILLING CODE 4120-01-P

[[Page 48913]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.076


[[Page 48914]]


[GRAPHIC] [TIFF OMITTED] TR10AU22.077

BILLING CODE 4120-01-C

[[Page 48915]]

    In the proposed rule, we provided a table listing the technologies 
for which we proposed to discontinue making new technology add-on 
payments for FY 2023 because they are no longer ``new'' for purposes of 
new technology add-on payments (87 FR 28211). This table also presented 
the newness start date, new technology add-on payment start date, the 
3-year anniversary date of the product's entry onto the U.S. market, 
relevant final rule citations from prior fiscal years, and coding 
assignments for each technology. We referred readers to the final rules 
cited in the table for a complete discussion of the new technology add-
on payment application, coding and payment amount for these 
technologies, including the applicable indications and discussion of 
the newness start date.
    We invited public comments on our proposals to discontinue new 
technology add-on payments for FY 2023 for the technologies listed in 
the table in the proposed rule.
    Comment: A commenter supported our proposal to discontinue new 
technology add-on payments for AZEDRA[supreg], which will no longer be 
considered new as its 3-year anniversary date of entry onto the U.S. 
market will occur prior to FY 2023.
    Response: We appreciate the commenter's support and are finalizing 
our proposal to discontinue new technology add-on payments for 
AZEDRA[supreg] for FY 2023.
    Comment: Many commenters stated their opposition to discontinuing 
new technology add-on payments for technologies whose 3-year 
anniversary of entry onto the U.S. market will occur prior to FY 2023 
or in the first half of FY 2023. These commenters encouraged CMS to use 
its legal authority under section 1886(d)(5)(I) of the Act to extend 
new technology add-on payments through FY 2023 due to a historic 
decline in utilization during the COVID-19 pandemic.
    Response: We thank the commenters for their input. Consistent with 
the statute and our implementing regulations, a technology is no longer 
considered as ``new'' once it is more than 2 to 3 years old, 
irrespective of how frequently the medical service or technology has 
been used in the Medicare population (70 FR 47349). As such, once a 
technology has been available on the U.S. market for more than 2 to 3 
years, we consider the costs to be included in the MS-DRG relative 
weights regardless of whether the technology's use in the Medicare 
population has been frequent or infrequent. Therefore, we do not 
believe that case volume is a relevant consideration for making the 
determination as to whether a product is ``new,'' and we are not 
extending new technology add-on payments for technologies whose 3-year 
anniversary of entry onto the U.S. market will occur prior to FY 2023 
or in the first half of FY 2023. We refer readers to the FY 2022 IPPS/
LTCH PPS final rule (86 FR 44975 through 44979) and section II.F.5.b of 
this FY 2023 final rule for discussion of our policy to allow for a 1-
year extension of new technology add-on payments for FY 2022 because of 
the unique circumstances associated with ratesetting for FY 2022, for 
which CMS used FY 2019 data instead of FY 2020 data to develop the FY 
2022 relative weights.
    Comment: Several commenters disagreed with CMS's proposal to 
discontinue new technology add-on payments for EXALT Model 
DTM Single-Use Duodenoscope while continuing payments for 
aScope[supreg] Duodeno through FY 2023 based on the different FDA 
clearance dates for the two technologies. These commenters recommended 
that CMS create a single newness date and extend new technology add-on 
payments for both products through the end of FY 2023. The commenters 
noted that there is no mechanism for hospitals to distinguish between 
the two devices when reporting claims to CMS, as the duodenoscopes 
share one add-on payment amount and are identified using the same ICD-
10-PCS codes.
    Another commenter, the applicant for EXALT Model DTM, 
stated that creating a single newness date and discontinuation date for 
a combined new technology add-on payment is consistent with prior CMS 
decision-making regarding substantially similar technologies such as 
IMFINZI[supreg] and TECENTRIQ[supreg] from the FY 2021 IPPS final rule, 
and the LUTONIX[supreg] and IN.PACTTM AdmiralTM 
drug-coated balloons in the FY 2016 IPPS final rule. The commenter 
noted that, in these instances, CMS finalized the proposal to 
discontinue the new technology add-on payment for both technologies on 
the same date and calculated a case-weighted average cost resulting in 
the same maximum add-on payment for both technologies. The commenter 
further noted that CMS determined the drug-coated balloons were 
identifiable using the same ICD-10-PCS procedure codes, and that 
IMFINZI[supreg] and TECENTRIQ[supreg] received a one-year extension 
through FY 2022 based on CMS' decision to use FY 2019 data (instead of 
FY 2020 data) for the FY 2022 IPPS rate setting. The commenter 
requested that CMS discontinue the new technology add-on payments for 
both EXALT Model DTM and aScopeTM Duodeno at the 
same time, preferably at the end of FY 2023. As an alternative, the 
applicant recommended that CMS recalculate the maximum payment amount 
from the current case-weighted average of $1,715 per case to reflect 
65% of the cost of aScopeTM Duodeno only.
    Response: We thank the commenters for their input. As stated 
previously, a technology is no longer considered ``new'' once it is 
more than 2 to 3 years old, irrespective of how frequently the medical 
service or technology has been used in the Medicare population (70 FR 
47349). As such, once a technology has been available on the U.S. 
market for more than 2 to 3 years, we consider the costs to be included 
in the MS-DRG relative weights regardless of whether the technology's 
use in the Medicare population has been frequent or infrequent. 
Additionally, we note that under Sec.  412.87(c), applications received 
for new technology add-on payments for FY 2021 and subsequent fiscal 
years for medical devices that are part of FDA's Breakthrough Devices 
Program and received FDA marketing authorization will be considered not 
substantially similar to an existing technology for purposes of the new 
technology add-on payment under the IPPS. Because EXALT Model 
DTM and aScopeTM Duodeno both applied under the 
alternative pathway for transformative new technologies, the 
applicant's comparison to IMFINZI[supreg] and TECENTRIQ[supreg] from 
the FY 2021 IPPS final rule (85 FR 58672 through 58684), and the 
LUTONIX[supreg] and IN.PACTTM AdmiralTM drug-
coated balloons in the FY 2016 IPPS final rule (80 FR 49461 through 
49470), where the technologies were determined to be substantially 
similar and therefore had the same newness period, is not relevant. 
Thus, we are finalizing our proposal to discontinue new technology add-
on payment for EXALTTM Model DTM for FY 2023.
    We agree with the applicant's alternative recommendation that the 
maximum new technology add-on payment amount should reflect the cost of 
aScopeTM Duodeno only. Based on information provided in its 
application for FY 2022 new technology add-on payment, the cost of the 
aScopeTM Duodeno is $1,995. Under Sec.  412.88(a)(2), we 
limit new technology add-on payments to the lesser of 65% of the 
average cost of the technology, or 65% of the costs in excess of the 
MS-DRG payment for the case. As a result, we are finalizing that the 
maximum new technology add-on payment for a case involving the use of 
the aScopeTM Duodeno would be $1,296.75 for FY

[[Page 48916]]

2022 (that is, 65% of the average cost of the technology). Cases 
involving the use of aScopeTM Duodeno will continue to be 
identified by the following ICD-10-PCS procedure codes: XFJB8A7 
(Inspection of hepatobiliary duct using single-use duodenoscope, new 
technology group 7) or XFJD8A7 (Inspection of pancreatic duct using 
single-use duodenoscope, new technology group).
    After consideration of the public comments we received, we are 
finalizing our proposal to discontinue new technology add-on payments 
for the technologies as listed in the proposed rule and in the 
following Table II.F.-02 of this final rule for FY 2023 because they 
are no longer ``new'' for purposes of new technology add-on payments. 
This table also presents the newness start date, new technology add-on 
payment start date, the 3-year anniversary date of the product's entry 
onto the U.S. market, and relevant final rule citations from prior 
fiscal years. We also refer readers to the final rules cited in the 
following table for a complete discussion of the new technology add-on 
payment application, coding and payment amount for these technologies, 
including the applicable indications and discussion of the newness 
start date.
BILLING CODE 4120-01-P
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BILLING CODE 4120-01-C
b. Status of Technologies Provided a One-Year Extension of New 
Technology Add-On Payments in FY 2022
    As stated in the FY 2022 IPPS/LTCH PPS final rule (86 FR 44789), 
our goal is always to use the best available data overall for 
ratesetting. The best available MedPAR data will typically be the most 
recent MedPAR file that contains claims from discharges for the fiscal 
year that is 2 years prior to the fiscal year that is the subject of 
the rulemaking.
    In the FY 2022 IPPS/LTCH PPS final rule, for the reasons discussed, 
we finalized that we would use FY 2019 MedPAR data instead of FY 2020 
MedPAR data to develop the FY 2022 MS-DRG relative weights (86 FR 44789 
through 44793). Because we finalized that we would use FY 2019 MedPAR 
data instead of FY 2020 MedPAR data for the development of the FY 2022 
MS-DRG relative weights, we stated that the costs for a new technology 
for which the 3-year anniversary date of the product's entry onto the 
U.S. market occurs prior to the latter half of FY 2022 may not be fully 
reflected in the MedPAR data used to recalibrate the MS-DRG relative 
weights for FY 2022. Therefore, in light of this final policy, we 
finalized our proposal to use our authority under section 1886(d)(5)(I) 
of the Act to allow for a 1-year extension of new technology add-on 
payments for FY 2022 for 13 technologies (as listed in the proposed 
rule and in Table II.F.-03 of this final rule) for which the new 
technology add-on payment would have otherwise been discontinued 
beginning with FY 2022. We refer the reader to the FY 2022 IPPS/LTCH 
PPS final rule (86 FR 44975 through 44979) for a complete discussion 
regarding this 1-year extension for FY 2022.
    For FY 2023 ratesetting, as discussed in section I.F. of this final 
rule, we believe the best available data is the FY 2021 MedPAR file. As 
discussed in section I.F. of this final rule, for FY 2023, we are 
finalizing our proposal to use the FY 2021 MedPAR (the best available 
data at the time of this final rule) for FY 2023 ratesetting, including 
for purposes of developing the FY 2023 relative weights. We refer the 
reader to section I.F. of this final rule for a complete discussion 
regarding our final policy to use the FY 2021 MedPAR for the FY 2023 
ratesetting and recalibration of the FY 2023 MS-DRG relative weights.
    As noted previously, our policy is that a medical service or 
technology may continue to be considered ``new'' for purposes of new 
technology add-on payments within 2 or 3 years after the point at which 
data begin to become available reflecting the inpatient hospital code 
assigned to the new service or technology. For FY 2023, because we 
proposed to use FY 2021 MedPAR data to recalibrate the FY 2023 MS-DRG 
relative weights, we stated in the proposed rule that we believe the 
costs of the 13 technologies as listed in the proposed rule (87 FR 
28216 through 28217) and in Table II.F.-03 of this final rule, for 
which the 3-year anniversary date of the product's entry onto the U.S. 
market occurs prior to FY 2023 (and therefore are no longer ``new''), 
may now be fully reflected in the MedPAR data used to recalibrate the 
MS-DRG relative weights for FY 2023. As a result, we proposed to 
discontinue new technology add-on payments for these 13 technologies in 
FY 2023. We also refer readers to the final rules cited in Table II.F.-
03 for a complete discussion of the new technology add-on payment 
application, coding and payment amount for these technologies, 
including the applicable indications and discussion of the newness 
start date.
    We invited public comments on our proposals to discontinue new 
technology add-on payments for FY 2023 for these 13 technologies listed 
in the proposed rule and Table II.F.-03.
    Comment: Many commenters, including several applicants for 
technologies currently receiving new technology add-on payments, stated 
their opposition to discontinuing new technology add-on payments for 
technologies that received a one-year extension in FY 2022. These 
commenters stated that the FY 2021 MedPAR claims data are distorted due 
to effects of the COVID-19 pandemic and should not be used to 
recalibrate the MS-DRG relative weights. The commenters encouraged CMS 
to use its legal authority under section 1886(d)(5)(I) of the Act to 
extend new technology add-on payments through FY 2023.
    Another commenter stated that while it is accurate that the costs 
of the technologies are reflected in the FY 2021 MedPAR data used for 
ratesetting purposes, the existence of such claims data does not mean 
that the costs of the technology are truly captured, nor does it mean 
that the pandemic has not impacted adoption of the new technologies and 
services. This commenter referenced several studies to demonstrate the 
impact of the PHE on hospitals, including critical staff shortages and 
financial instability due to lower revenues and inflation. The 
commenter also provided an analysis of FY 2021 claims data that found 
that the average standardized costs when accounting for cases using its 
technology or comparable technology reported under the same ICD-10-PCS 
codes increased by less than 0.5% compared to average standardized 
costs that do not account for cases reported under these codes.
    Response: We thank the commenters for their input. Consistent with 
the statute and our implementing regulations, a technology is no longer 
considered as ``new'' once it is more than 2 to 3 years old, 
irrespective of how frequently the medical service or technology has 
been used in the Medicare population (70 FR 47349). As such, once a 
technology has been available on the U.S. market for more than 2 to 3 
years, we consider the costs to be included in the MS-DRG relative 
weights regardless of whether the technology's use in the Medicare 
population has been frequent or infrequent. Therefore, we do not 
believe that case volume is a relevant consideration for making the 
determination as to whether a product is ``new''. Additionally, as 
previously discussed, in the FY 2022 IPPS/LTCH PPS final rule (86 FR 
44975 through 44979), we finalized a 1-year extension of new technology 
add-on payments for FY 2022 in light of the unique circumstances 
associated with ratesetting for FY 2022, for which CMS finalized the 
use of the FY 2019 MedPAR data instead of the FY 2020 MedPAR data to 
develop the FY 2022 relative weights. For FY 2023, because we are 
finalizing the use of the FY 2021 MedPAR data for FY 2023 ratesetting, 
including for purposes of developing the FY 2023 relative weights, we 
believe the costs of these technologies are now reflected in the MedPAR 
data used to recalibrate the MS-DRG relative weights for FY 2023. 
Therefore, we are not extending new technology add-on payments for 
technologies that received a one-year extension in FY 2022. We refer 
readers to sections section I.F. and II.E. of this final rule for 
discussion of CMS's finalized policy to use the FY 2021 MedPAR claims 
data to recalibrate the FY 2023 MS-DRG relative weights, including the 
finalized modifications to the relative weight setting methodology to 
account for the anticipated decline in COVID-19 hospitalizations of 
Medicare beneficiaries at IPPS hospitals as compared to FY 2021.
    After consideration of the public comments we received, we are 
finalizing our proposal to discontinue new technology add-on payments 
for the technologies as listed in the proposed rule and in the 
following Table II.F.-03 of this final rule for FY 2023. This table 
also presents the

[[Page 48918]]

newness start date, new technology add-on payment start date, the 3-
year anniversary date of the product's entry onto the U.S. market, and 
relevant final rule citations from prior fiscal years. We also refer 
readers to the final rules cited in the following table for a complete 
discussion of the new technology add-on payment application, coding and 
payment amount for these technologies, including the applicable 
indications and discussion of the newness start date.
BILLING CODE 4120-01-P

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[[Page 48920]]


BILLING CODE 4120-01-C
6. FY 2023 Applications for New Technology Add-On Payments (Traditional 
Pathway)
    We received 18 applications for new technology add-on payments for 
FY 2023 under the traditional new technology add-on payment pathway. In 
accordance with the regulations under Sec.  412.87(e), applicants for 
new technology add-on payments must have received FDA approval or 
clearance by July 1 of the year prior to the beginning of the fiscal 
year for which the application is being considered. Five applicants 
withdrew their applications prior to the issuance of the proposed rule. 
Subsequently, seven applicants withdrew their respective applications 
for lifileucel, narsoplimab, TERLIVAZ (terlipressin), teclistamab, 
mosunetuzumab, XENOVIEW, and treosulfan prior to the issuance of this 
FY 2023 IPPS/LTCH PPS final rule. In addition, in accordance with Sec.  
412.87(c), applicants for new technology add-on payments must have FDA 
approval or clearance by July 1 of each year prior to the beginning of 
the fiscal year for which the application is being considered. One 
applicant, Boehringer Ingelheim Pharmaceuticals, Inc., for spesolimab, 
did not receive FDA approval for its technology by July 1, 2022. 
Therefore, spesolimab is not eligible for consideration for new 
technology add-on payments for FY 2023. Consistent with our standard 
approach, we are not including in this final rule the description and 
discussion of applications that were withdrawn or that are ineligible 
for consideration for FY 2023 due to not meeting the July 1 deadline, 
described previously, which were included in the FY 2023 IPPS/LTCH PPS 
proposed rule. We are also not summarizing nor responding to public 
comments received regarding these withdrawn or ineligible applications 
in this final rule. A discussion of the five remaining applications is 
presented below.
a. CARVYKTITM (Ciltacabtagene Autoleucel)
    Janssen Biotech, Inc., submitted an application for new technology 
add-on payments for CARVYKTITM (ciltacabtagene autoleucel) 
for FY 2023. CARVYKTITM is an autologous chimeric-antigen 
receptor (CAR) T-cell therapy directed against B cell maturation 
antigen (BCMA) for the treatment of patients with multiple myeloma. We 
note that Janssen Biotech, Inc. previously submitted an application for 
new technology add-on payments for CARVYKTITM for FY 2022 
under the name ciltacabtagene autoleucel, as summarized in the FY 2022 
IPPS/LTCH PPS final rule (86 FR 25233 through 25239), but withdrew that 
application prior to the issuance of the FY 2022 IPPS/LTCH PPS final 
rule (86 FR 44979).
    The applicant stated that ciltacabtagene autoleucel refers to both 
JNJ-4528, an investigational BCMA-directed CAR T-cell therapy for 
previously treated patients with multiple myeloma, and LCAR-B38M, the 
investigational product (ciltacabtagene autoleucel) being studied in 
China. Both JNJ-4528 and LCAR-B38M are representative of the same CAR 
T-cell therapy, ciltacabtagene autoleucel.
    Multiple myeloma is an incurable blood cancer that affects a type 
of white blood cell called plasma cells.\32\ Plasma cells, found in 
bone marrow, make the antibodies that help the body attack and kill 
various pathogens. According to the applicant, when damaged, malignant 
plasma cells rapidly spread and replace the normal cells in the bone 
marrow.\33\ The applicant asserted the median age of onset is 69 years 
old and only 3% of patients are less than 45 at the age of diagnosis; 
it was estimated that in 2021 nearly 35,000 people would be diagnosed 
and more than 12,000 will die from multiple myeloma in the US.\34\ 
According to the applicant, multiple myeloma is associated with 
substantial morbidity and mortality\35\ and median 5 year survival is 
56%.\36\
---------------------------------------------------------------------------

    \32\ Ho, M., Chen, T., Liu, J. et al. Targeting histone 
deacetylase 3 (HDAC3) in the bone marrow microenvironment inhibits 
multiple myeloma proliferation by modulating exosomes and IL-6 
trans-signaling. Leukemia 34, 196-209 (2020). https://doi.org/10.1038/s41375-019-0493-x.
    \33\ Utley A, Lipchick B, Lee KP, Nikiforov MA. Targeting 
Multiple Myeloma through the Biology of Long-Lived Plasma Cells. 
Cancers (Basel). 2020 Jul 30;12(8):2117.
    \34\ Surveillance, Epidemiology, and End Results (SEER) Program. 
SEER database 2020; https://seer.cancer.gov/statfacts/html/mulmy.html.
    \35\ Cowan AJ, Allen C, Barac A, Basaleem H, Bensenor I, Curado 
MP, Foreman K, Gupta R, Harvey J, Hosgood HD, Jakovljevic M, Khader 
Y, Linn S, Lad D, Mantovani L, Nong VM, Mokdad A, Naghavi M, Postma 
M, Roshandel G, Shackelford K, Sisay M, Nguyen CT, Tran TT, Xuan BT, 
Ukwaja KN, Vollset SE, Weiderpass E, Libby EN, Fitzmaurice C. Global 
Burden of Multiple Myeloma: A Systematic Analysis for the Global 
Burden of Disease Study 2016. JAMA Oncol. 2018 Sep 1;4(9):1221-1227.
    \36\ SEER database 2020; https://seer.cancer.gov/statfacts/html/mulmy.html.
---------------------------------------------------------------------------

    According to the applicant, introduction of new treatment options 
in the last 2 decades has extended the median survival of multiple 
myeloma patients. The applicant asserted that the introduction of 
proteasome inhibitors (PI) (for example, bortezomib, carfilzomib, and 
ixazomib), histone deacetylase inhibitors (for example, panobinostat, 
vorinostat), immunomodulatory agents (IMiD) (for example, thalidomide, 
lenalidomide, and pomalidomide), monoclonal antibodies (daratumumab and 
elotuzumab), and stem cell transplantation, have allowed numerous 
therapeutic options for patients with multiple myeloma (Rajkumar 2020). 
According to the applicant, the National Comprehensive Cancer Network 
(NCCN) recommended treatment regimen for first-line therapy of multiple 
myeloma is bortezomib (a PI), lenalidomide (an IMiD) and 
dexamethasone.\37\ According to the applicant, the strategy of triplet 
therapies for patients with newly diagnosed multiple myeloma, followed 
by high-dose chemotherapy and autologous stem-cell transplantation for 
eligible patients, and subsequently consolidation and maintenance 
therapy, is the current treatment roadmap for patients.\38\ However, 
despite these treatments, according to the applicant, most patients 
will relapse after first-line treatment and require further 
treatment\39\ with only 50% survival of relapsed patients after 5 
years.40 41 The applicant stated that as multiple myeloma 
progresses, each subsequent line of treatment is associated with 
shorter progression free survival (PFS) and decreased rate, depth, and 
durability of response and worsening of quality of life.\42\ In 
addition, cumulative and long-term toxicities are often associated with 
long-term therapy (Ludwig, 2018). Thus, according to the applicant, 
there remains an ongoing need for additional therapeutic approaches 
when the disease is resistant to available therapy.
---------------------------------------------------------------------------

    \37\ National Comprehensive Cancer Network (NCCN) NCCN clinical 
practice guidelines in oncology. Multiple Myeloma. Version 2. 2021--
September 9, 2020.
    \38\ Branagan A, Lei M, Lou U, Raje N. Current Treatment 
Strategies for Multiple Myeloma. JCO Oncol Pract. 2020 Jan;16(1):5-
14.
    \39\ Sonneveld P, Broij lA. Treatment of relapsed and refractory 
multiple myeloma. Haematologica. 2016;101(4):396-406.
    \40\ SEER database 2020; https://seer.cancer.gov/statfacts/html/mulmy.html.
    \41\ Global Cancer Observatory. GLOBOCAN database 2018; https://gco.iarc.fr/today/data/factsheets/populations/900-world-fact-sheets.pdf.
    \42\ Yong K, Delforge M, Driessen C, Fink L, Flinois A, 
Gonzalez-McQuire S, Safaei R, Karlin L, Mateos MV, Raab MS, Schoen 
P, Cavo M. Multiple myeloma: patient outcomes in real-world 
practice. Br J Haematol. 2016 Oct;175(2):252-264.
---------------------------------------------------------------------------

    The applicant asserted that relapsed and refractory (r/r) multiple 
myeloma (RRMM) constitutes a specific unmet medical need. According to 
the applicant, patients with r/r disease are defined as those who, 
having achieved

[[Page 48921]]

a minor response or better, relapse and then progress while on therapy, 
or experience progression within 60 days of their last 
therapy.43 44 The applicant stated the introduction of a new 
class of agents, CD38-targeting monoclonal antibodies (CD38 MoAbs), 
daratumumab and isatuximab, have improved options in r/r patients.\45\ 
The applicant asserted that given these advances, guideline 
recommendations following first-line therapy are varied, with treatment 
options including combinations of novel agents with existing standard 
of care regimens, and include triplet and quadruplet regimens, creating 
a complex treatment landscape.\46\ According to the applicant, while 
triplet regimens should be used as the standard therapy for patients 
with multiple myeloma, elderly or frail patients may be treated with 
double regimens.\47\ The applicant further stated that for patients 
with RRMM who have received at least three prior lines of therapy, 
including a PI, an IMiD and an anti-CD38, there does not exist a 
standard or consensus for treatment at this time, and often, supportive 
care/palliative care is the only option.\48\
---------------------------------------------------------------------------

    \43\ Castelli R, Orofino N, Losurdo A, Gualtierotti R, Cugno M. 
Choosing treatment options for patients with relapsed/refractory 
multiple myeloma. Expert Rev Anticancer Ther. 2014 Feb;14(2):199-
215.
    \44\ Nooka AK, Kastritis E, Dimopoulos MA, Lonial S. Treatment 
options for relapsed and refractory multiple myeloma. Blood. 2015 
May 14;125(20):3085-99.
    \45\ Van de Donk NWCJ, Richardson PG, Malavasi F. CD38 
antibodies in multiple myeloma: back to the future. Blood. 2018 Jan 
4;131(1):13-29.
    \46\ National Comprehensive Cancer Network (NCCN) NCCN clinical 
practice guidelines in oncology. Multiple Myeloma. Version 2. 2021--
September 9, 2020.
    \47\ Ibid.
    \48\ Maples KT, Joseph NS, Harvey RD. Current developments in 
the combination therapy of relapsed/refractory multiple myeloma. 
Expert Rev Anticancer Ther. 2020 Sep 24.
---------------------------------------------------------------------------

    According to the applicant, multiple myeloma remains incurable and 
most patients eventually relapse, even with the advent of new 
treatments.\49\ The applicant further stated that novel, innovative 
therapies are needed to improve long-term survival and outcomes. The 
applicant asserted that CAR T-cell-based therapies offer potential 
advantages over current therapeutic strategies. According to the 
applicant, while other therapies require long-term repetitive 
administration generally until progression of disease, CAR T-cell 
therapy is a single infusion treatment due to live T-cell expansion in 
the patient and long-term disease response. The applicant asserted that 
CARVYKTITM is an autologous CAR T-cell therapy directed 
against B cell maturation antigen (BCMA) for the treatment of patients 
with multiple myeloma. The applicant stated that BCMA, a protein that 
is highly expressed on myeloma cells\50\ and is a member of the tumor 
necrosis factor (TNF) receptor family, plays a central role in 
regulating B-cell maturation and differentiation into plasma cells.\51\ 
\52\ The applicant stated BCMA is selectively expressed on a subset of 
B cells (plasma cell neoplasms including myeloma cells) and is more 
stably expressed specifically on the B cell lineage, compared with key 
plasma cell marker CD138, which is also expressed on normal fibroblasts 
and epithelial cells.53 54 55 According to the applicant, 
these expression characteristics make BCMA an ideal therapeutic target 
for the treatment of multiple myeloma.56 57 
CARVYKTITM, according to the applicant, is a unique, 
structurally differentiated BCMA-targeting chimeric antigen receptor 
with two distinct BCMA-binding domains that can identify and eliminate 
myeloma cells.
---------------------------------------------------------------------------

    \49\ Rajkumar SV, Kumar S. Multiple myeloma current treatment 
algorithms. Blood Cancer J. 2020 Sep 28;10(9):94.
    \50\ Cho SF, Anderson KC, Tai YT. Targeting B Cell Maturation 
Antigen (BCMA) in Multiple Myeloma: Potential Uses of BCMA-Based 
Immunotherapy. Front Immunol. 2018 Aug 10;9:1821.
    \51\ Cho SF, Anderson KC, Tai YT. Targeting B Cell Maturation 
Antigen (BCMA) in Multiple Myeloma: Potential Uses of BCMA-Based 
Immunotherapy. Front Immunol. 2018 Aug 10;9:1821.
    \52\ Tai YT, Anderson KC. Targeting B-cell maturation antigen in 
multiple myeloma. Immunotherapy. 2015;7(11):1187-99.
    \53\ Cho SF, Anderson KC, Tai YT. Targeting B Cell Maturation 
Antigen (BCMA) in Multiple Myeloma: Potential Uses of BCMA-Based 
Immunotherapy. Front Immunol. 2018 Aug 10;9:1821.
    \54\ Tai YT, Anderson KC. Targeting B-cell maturation antigen in 
multiple myeloma. Immunotherapy. 2015;7(11):1187-99.
    \55\ Palaiologou M, Delladetsima I, Tiniakos D. CD138 (syndecan-
1) expression in health and disease. Histol Histopathol. 2014 
Feb;29(2):177-89.
    \56\ Ibid.
    \57\ Frigyesi I, Adolfsson J, Ali M, Christophersen MK, Johnsson 
E, Turesson I, Gullberg U, Hansson M, Nilsson B. Robust isolation of 
malignant plasma cells in multiple myeloma. Blood. 2014 Feb 
27;123(9):1336-40.
---------------------------------------------------------------------------

    The applicant asserted that CAR T-cell technology is a form of 
immunotherapy and is a ``living drug'' that utilizes specially altered 
T cells, part of the immune system, to fight cancer. According to the 
applicant, a sample of the patient's T cells are collected from the 
blood, then modified in a laboratory setting to express a CAR.\58\ The 
applicant stated chimeric antigen receptors are specifically designed 
receptor proteins that are made up of three distinct features: (1) a 
target recognition domain (typically derived from a single domain of an 
antibody) that sits on the cell's exterior; (2) a co-stimulatory domain 
on the cell's interior that boosts activation, enhances survival and 
expansion of the modified cells; and (3) an interior stimulatory domain 
that supports activation and target killing.\59\ According to the 
applicant, the binding domain expressed on the surface of T cells gives 
them the new ability to target a specific protein. The applicant 
stated, when the target is recognized, the intracellular portions of 
the receptor send signals within the T cells to destroy the target 
cells. The applicant asserted these engineered CAR T-cells are 
reinfused back into the same patient, which enables these specialized T 
cells to latch onto the target antigen and abolish the tumor cells.
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    \58\ June CH, Sadelain M. Chimeric Antigen Receptor Therapy. N 
Engl J Med. 2018 Jul 5;379(1):64-73.
    \59\ Sadelain M. Chimeric antigen receptors: driving immunology 
towards synthetic biology. Curr Opin Immunol. 2016 Aug;41:68-76.
---------------------------------------------------------------------------

    According to the applicant, CARVYKTITM is a CAR T-cell 
immunotherapy designed to recognize myeloma cells and target their 
destruction. According to the applicant, CARVYKTITM's CAR T-
cell technology consists of harvesting the patient's own T cells, 
programming them to express a chimeric antigen receptor that identifies 
BCMA, a protein highly expressed on the surface of malignant multiple 
myeloma B-lineage cells, and reinfusing these modified cells back into 
the patient where they bind to and eliminate myeloma tumor cells. The 
applicant asserted that, unlike the chimeric antigen receptor design of 
currently approved CAR T-cell immunotherapies, which are composed of a 
single-domain antibody (sdAbs), CARVYKTITM is composed of 
two antibody binding domains that allow for high recognition of human 
BCMA (CD269) and elimination of BCMA expressing myeloma cells. 
According to the applicant, the two distinct BCMA-binding domains 
confer avidity and distinguish CARVYKTITM from other BCMA-
targeting products. The applicant stated the BCMA binding domains are 
linked to the receptor's interior costimulatory (4-1BB) and signaling 
(CD3[zeta]) domains through a transmembrane linker (CD8a). The 
applicant asserted these intracellular domains are critical components 
for T cell growth and anti-tumor activity \60\ in the body once CAR T-
cells are bound to a BCMA target on multiple myeloma cells.
---------------------------------------------------------------------------

    \60\ Maher J, Brentjens RJ, Gunset G, Rivi[egrave]re I, Sadelain 
M. Human T-lymphocyte cytotoxicity and proliferation directed by a 
single chimeric TCRzeta/CD28 receptor.

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[[Page 48922]]

    With respect to the newness criterion, according to the applicant, 
CARVYKTITM was granted Breakthrough Therapy designation in 
December 2019 for the treatment of adult patients with relapsed or 
refractory multiple myeloma, who previously received a proteasome 
inhibitor, an immunomodulatory agent, and an anti-CD38 antibody. Per 
the applicant, FDA approved the Biologics License Application (BLA) for 
CARVYKTITM on February 28, 2022 for the treatment of adult 
patients with relapsed or refractory multiple myeloma after four or 
more prior lines of therapy, including a proteasome inhibitor, an 
immunomodulatory agent, and an anti-CD38 monoclonal antibody. The 
applicant stated that procedures involving the administration of 
CARVYKTITM can be uniquely identified using the following 
ICD-10-PCS procedure codes: XW033A7 (Introduction of ciltacabtagene 
autoleucel into peripheral vein, percutaneous approach, new technology 
group 7) or XW043A7 (Introduction of ciltacabtagene autoleucel into 
central vein, percutaneous approach, new technology group 7). The 
applicant also noted that they will submit a request for a Healthcare 
Common Procedure Coding System (HCPCS) code specific to the 
administration of CARVYKTITM once the product is eligible 
for such a code.
    As previously stated, if a technology meets all three of the 
substantial similarity criteria as previously described, it would be 
considered substantially similar to an existing technology and 
therefore would not be considered ``new'' for purposes of new 
technology add-on payments.
    With respect to whether a product uses the same or a similar 
mechanism of action when compared to an existing technology to achieve 
a therapeutic outcome, the applicant asserted that 
CARVYKTITM has a unique mechanism of action because it has 
two distinct binding domains that confer avidity to the BCMA antigen, a 
4-1BB costimulatory domain and a CD3z signaling domain, whereas other 
CAR T-cell products have only one target binding domain. The applicant 
asserted that ABECMA[supreg] also targets BCMA, but does so by binding 
to a single BCMA domain. In addition to detail provided in the 
applicant's FY 2022 application (as discussed in 86 FR 25235 through 
25236), the applicant asserted that CARVYKTITM differs 
significantly from ABECMA[supreg] and other BCMA-targeting agents, 
including Blenrep, because it targets BCMA with two distinct binding 
domains. According to the applicant, the distinct BCMA-binding moieties 
confer avidity and distinguish CARVYKTITM from other BCMA 
CAR T-cell constructs providing a novel mechanism of action.\61\ The 
applicant added, the 4-1BB and CD3z domains on the CAR optimize T cell 
activation and proliferation.\62\ According to the applicant, non-
clinical pharmacology and toxicology have been used to characterize the 
biological activity and mechanism of action of CARVYKTITM 
and confirm the on-target specificity to BCMA through (1) in vitro 
binding characterization; (2) in vitro co-culture assays to assess CAR 
T-cell cytotoxicity and cytokine release; (3) in vivo efficacy studies 
in mice with human CAR T- cells; and (4) an in vivo safety study. 
According to the applicant, because CARVYKTITM has a novel 
mechanism of action with two distinct BCMA-binding domains that confer 
binding avidity and unprecedented clinical activity compared with other 
novel anti-myeloma treatments in comparable study populations, it is 
unlike any existing technology utilized to treat relapsed/refractory 
multiple myeloma.
---------------------------------------------------------------------------

    \61\ Xu J, Chen LJ, Yang SS, Sun Y, Wu W, Liu YF, Xu J, Zhuang 
Y, Zhang W, Weng XQ, Wu J, Wang Y, Wang J, Yan H, Xu WB, Jiang H, Du 
J, Ding XY, Li B, Li JM, Fu WJ, Zhu J, Zhu L, Chen Z, Fan XF, Hou J, 
Li JY, Mi JQ, Chen SJ. Exploratory trial of a biepitopic CAR T-
targeting B cell maturation antigen in relapsed/refractory multiple 
myeloma. Proc Natl Acad Sci U S A. 2019 May 7;116(19):9543-9551.
    \62\ Weinkove R, George P, Dasyam N, McLellan AD. Selecting 
costimulatory domains for chimeric antigen receptors: functional and 
clinical considerations. Clin Transl Immunology. 2019 May 
11;8(5):e1049.
---------------------------------------------------------------------------

    With regard to whether a product is assigned to the same DRG when 
compared to an existing technology, the applicant asserted that because 
CMS has suggested that all inpatient hospitalizations involving a CAR 
T-cell treatment will be assigned to DRG 018 (Chimeric Antigen Receptor 
(CAR) T-Cell and Other Immunotherapies), CARVYKTITM is 
expected to be assigned to the same DRG as other multiple myeloma cases 
treated with a CAR T-cell therapy. We note that the DRG assignment was 
finalized to Pre-MDC MS-DRG 018, effective October 1, 2022 and is 
reflected in the V39.1 ICD-10 MS-DRG Grouper effective April 1, 2022 
(86 FR 58021).\63\
---------------------------------------------------------------------------

    \63\ CMS Manual System, Pub. 100-04 Medicare Claims Processing, 
Transmittal 11255. February 4, 2022; https://www.cms.gov/files/document/r11255cp.pdf.
---------------------------------------------------------------------------

    With regard to whether the new use of the technology involves the 
treatment of the same or similar type of disease and the same or 
similar patient population when compared to an existing technology, the 
applicant asserted in its application that CARVYKTITM is 
indicated for a broader population than other available therapies, 
specifically multiple myeloma patients having received three prior 
therapies. The applicant asserted in its application that Blenrep and 
ABECMA[supreg] are indicated only for those with at least 4 prior 
therapies whereas CARVYKTITM had a proposed indication for 
the treatment of patients with 3 or more prior therapies. According to 
the applicant, CARVYKTITM could potentially be used in a 
broader multiple myeloma population, that includes patients after 3 
prior therapies as opposed to 4 for Blenrep and ABECMA[supreg].
    According to the applicant, in the registrational trial CARTITUDE 
1, 17% (a total of 17 patients) of patients had only three prior lines 
of therapy; results were presented at the American Society of 
Hematology (ASH) 2021 meeting on fourth line patients. The applicant 
stated that among those with three prior lines of therapy, the response 
rate was 100%, the median duration of response (DoR) was 21.8 months, 
minimal residual disease (MRD) negativity was found in 80%, the 18-
month progression free survival (PFS) was 75.6%, and the 18-month 
overall survival (OS) was 88.2 months. According to the applicant, 
because the sample size was small (17), median endpoints may not be as 
rigorous as in the larger population.
    According to the applicant, the distinction between three and four 
previous lines of therapy is important. The applicant asserted with 
each subsequent therapy patients generally become frailer and their 
prognosis worsens. The applicant stated that studies comparing fourth 
line to fifth line are not as common as trials studying earlier lines, 
but in a real-world study by Yong et al. the percent of myeloma 
patients who were able to move from third line therapy to fourth line 
was 15% of all diagnosed myeloma patients, and only 1% of patients 
moved to a fifth line.\64\ The applicant added that in the same study 
of those patients in first line therapy, approximately 90% of patients 
were able to discontinue treatment due to remission and/or planned end 
of treatment while only 13% of those in fifth line ended treatment due 
to stable disease/remission.
---------------------------------------------------------------------------

    \64\ Yong et al. 2016. Multiple Myeloma: Patient outcomes in 
real-world practice. British Journal of Haematology, 175; 252-264. 
doi: 10.1111/bjh.14213.
---------------------------------------------------------------------------

    The applicant asserted that for these reasons, 
CARVYKTITM does not meet the third criterion and is 
therefore a new technology with regards to the

[[Page 48923]]

population having been studied and being targeted for use.
    In summary, the applicant asserted that CARVYKTITM meets 
the newness criterion because it is not substantially similar to other 
available therapies due to its unique mechanism of action, with two 
distinct binding domains that confer avidity to the BCMA antigen, and 
because it treats a different patient population, RRMM patients who 
received three prior therapies.
    In the FY 2023 IPPS/LTCH PPS proposed rule, as stated in the FY 
2022 proposed rule (86 FR 25236), we noted that CARVYKTITM 
may have a similar mechanism of action to that of ABECMA[supreg]. We 
also noted that ABECMA[supreg] received approval for new technology 
add-on payments for FY 2022 for the treatment of adult patients with 
RRMM after four or more prior lines of therapy, including an 
immunomodulatory agent, a proteasome inhibitor, and an anti-CD38 
monoclonal antibody (86 FR 45028 through 45035). We stated that 
although the number of BCMA binding domains of CARVYKTITM 
and ABECMA[supreg] differ, it appeared that the mechanism of action for 
both therapies is the binding to BCMA by a CAR construct, which results 
in T-cell activation and killing of malignant myeloma cells. We noted 
that the applicant asserted that CARVYKTITM's mechanism of 
action is unique due to its dual binding domain which affects the 
therapy's clinical activity, as compared to existing technologies with 
a single binding domain. However, we were unclear as to how the 
additional BCMA binding domain represents a change in the mechanism of 
action of this therapy, or if it may instead relate to an assessment of 
whether the technology meets the substantial clinical improvement 
criterion. Because of the potential similarity with the BCMA antigen 
and other actions, we stated our belief that the mechanism of action 
for CARVYKTITM may be the same or similar to that of 
ABECMA[supreg].
    We also noted that the applicant stated that CARVYKTITM 
may serve a new patient population if approved as a fourth line 
treatment, as existing treatments are approved for fifth line 
treatment. However, because CARVYKTITM's recent approval 
stated that it is indicated for fifth line treatment, we questioned 
whether CARVYKTITM treats a new patient population.\65\
---------------------------------------------------------------------------

    \65\ https://www.fda.gov/media/156572/download.
---------------------------------------------------------------------------

    Accordingly, as it appeared that CARVYKTITM and 
ABECMA[supreg] are purposed to achieve the same therapeutic outcome 
using the same or similar mechanism of action, are assigned to the same 
MS-DRG, and treat the same or similar patient population and disease, 
we stated our belief that these technologies may be substantially 
similar to each other. We noted that if this technology is 
substantially similar to ABECMA[supreg], we believe the newness period 
for this technology would begin on March 26, 2021, the date 
ABECMA[supreg] received FDA approval. We expressed our interest in 
information on how these two technologies may differ from each other 
with respect to the substantial similarity criteria and newness 
criterion. We invited public comment on whether CARVYKTITM 
meets the newness criterion, including whether CARVYKTITM is 
substantially similar to ABECMA[supreg] for purposes of new technology 
add-on payments.
    Comment: Several commenters voiced their support for 
CARVYKTITM in their general comments supporting all CAR T-
cell therapies. The commenters encouraged CMS to consider approving the 
new technology add-on payment for new CAR T-cell therapies, including 
CARVYKTI, as they stated this encourages hospitals to adopt 
breakthrough technologies by helping them recover some of the increased 
costs associated with offering innovative treatments to patients.
    Response: We thank the commenters for their support.
    Comment: The applicant submitted a comment in response to concerns 
raised by CMS in the proposed rule, reiterating that 
CARVYKTITM meets the newness criterion and is not 
substantially similar to ABECMA[supreg] and other multiple myeloma 
treatments. The applicant stated that, while both CARVYKTITM 
and ABECMA[supreg] are CAR T-cell therapies directed against BCMA for 
the treatment of patients with multiple myeloma, there are mechanistic 
differences that contribute to a different CAR T-cell dose, 
pharmacokinetic/pharmacodynamic profile, and a different time frame for 
the development of cytokine release syndrome (CRS) as compared to 
ABECMA[supreg]'s single binding domain. The applicant presented the 
following table outlining the key scientific differences between 
CARVYKTITM and ABECMA[supreg].

[[Page 48924]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.080

    In terms of differences in dosage, the applicant stated the 
clinical target dose of CARVYKTITM is 0.75 x10\6\ CAR-
positive viable T-cells/kg whereas ABECMA[supreg] is 300-400 x 10\6\ 
cells/kg. In terms of differences in expansion of T-cell populations, 
the applicant stated that CARVYKTITM has preferential 
expansion of CD8 T-cells as opposed to CD4 T-cells for ABECMA[supreg]. 
In terms of the differences in pharmacokinetic and pharmacodynamic 
properties, the applicant stated that the median time to reach maximum 
expansion for CARVYKTITM was approximately 13 days after 
infusion, whereas for ABECMA[supreg] it was much sooner. According to 
the applicant, because of this longer lag time for maximal expansion, 
the highest peak IL-6 levels is around 10 days for 
CARVYKTITM as opposed to 5 days with ABECMA[supreg], which 
resulted in differences in the side effect profile, as the median time 
to onset of CRS is 7 days for CARVYKTITM as opposed to 1 day 
for ABECMA[supreg]. The applicant stated that patients with CRS of 
Grade 3 severity had IL-6 peak levels of ~1,000 pg/ml with 
CARVYKTITM as opposed to over 10,000 pg/ml with 
ABECMA[supreg]. The applicant also stated that the return to baseline 
levels of IL-6 occurred in 2-3 months for patients treated with 
CARVYKTITM as opposed to 1 month with ABECMA[supreg]. 
Lastly, the applicant stated that another important distinction between 
CARVYKTITM and ABECMA[supreg] was that CARVYKTITM 
is derived from llama antibodies directed against BCMA whereas 
ABECMA[supreg] is derived from mouse antibodies. We note that the 
applicant agreed with our assessment that CARVYKTITM does 
not treat a new population.
    Another commenter requested that CARVYKTITM be 
considered for a separate new technology add-on payment and should not 
be combined with other new technologies as the commenter considers the 
newness, cost, and substantial clinical improvement requirements met 
for CARVYKTITM. Per the commenter, this would ensure the 
maximum impact for each product for CAR T-cell therapy, which the 
commenter stated is significantly underpaid.
    Response: We appreciate the information submitted by commenters 
regarding the newness criterion for CARVYKTITM. However, we 
disagree that CARVYKTITM has a unique mechanism of action. 
While the applicant highlighted differences between 
CARVYKTITM and ABECMA[supreg], such as number of domains, 
dosage, time to CRS onset, pharmacokinetic/pharmacodynamic profile, 
side effects, source of antibodies, and CD4/CD8 ratios, we do not 
believe these meaningfully differentiate the mechanism of action of 
CARVYKTITM from other BCMA-directed CAR T-cell therapies 
such as ABECMA[supreg], as they are both considered genetically 
modified autologous T-cell immunotherapies that bind to BCMA-expressing 
cancer cells.
    While CARVYKTITM has two BCMA binding domains as opposed 
to one binding domain for ABECMA[supreg], the resulting mechanism of 
action produces the same therapeutic outcome of CAR expressing CD4 and 
CD8 T-cells directed against BCMA for the treatment of multiple 
myeloma. We also disagree with applicant's assertion that 
CARVYKTITM's preferential expansion of CD8 T-cells leads to 
a different mechanism of action, as both CARVYKTITM and 
ABECMA[supreg] produce a combination of CD4 and CD8 T-cells. While the 
ratio of these T-cells may vary, it does not substantiate a difference 
in mechanism of action which, as noted previously, is the targeting of 
and binding to the BCMA-expressing cancer cells. Lastly, we disagree 
that a difference in dosage and production represents a different 
mechanism of action. We refer the reader to the FY 2022 IPPS/LTCH PPS 
final rule (86 FR 44996 through 45000) for a further discussion of this 
issue, where we determined that BREYANZI[supreg] had a similar 
mechanism of action to KYMRIAH[supreg] and YESCARTA[supreg].
    After consideration of the comments received, and for the reasons 
discussed, we believe that CARVYKTITM and ABECMA[supreg] use 
the same or a similar mechanism of action to achieve a therapeutic 
outcome, as both products are BCMA-targeting CAR T-cell immunotherapies 
that result in similar T-cell activation and killing of malignant 
myeloma cells. Furthermore, as discussed previously, 
CARVYKTITM maps to the same MS-DRG and treats the same 
patient population (those with multiple myeloma after 4 or more prior 
lines of therapy) as ABECMA[supreg] and other CAR T-cell therapies. 
Accordingly, because CARVYKTITM meets all three of the 
substantial similarity criteria, we believe that it is substantially 
similar to ABECMA[supreg]. In

[[Page 48925]]

accordance with our policy, because these technologies are 
substantially similar to each other, we use the earliest market 
availability date submitted as the beginning of the newness period for 
both technologies. Therefore, we consider the beginning of the newness 
period for CARVYKTI[supreg] to be March 26, 2021, which is the date 
that ABECMA[supreg] received FDA marketing authorization.
    Consistent with our policy statements in the past regarding 
substantial similarity, we will not be making a determination on cost 
and substantial clinical improvement for CARVYKTITM. 
Specifically, we have noted that approval of new technology add-on 
payments would extend to all technologies that are substantially 
similar, and if substantially similar technologies are submitted for 
review in different (and subsequent) years, we evaluate and make a 
determination on the first application and apply that same 
determination to the second application (85 FR 58679). Since 
ABECMA[supreg] was approved for new technology add-on payments for FY 
2022 and is still within its newness period for FY 2023, and we have 
determined that CARVYKTITM is substantially similar to 
ABECMA[supreg], we apply that same approval for new technology add-on 
payments to CARVYKTITM. We note that we received public 
comments with regard to the cost and substantial clinical improvement 
criteria for this technology, but because the determination made in the 
FY 2022 IPPS/LTCH PPS final rule for ABECMA[supreg] is applied to 
CARVYKTITM due to their substantial similarity, we are not 
summarizing comments received or making a determination on those 
criteria in this final rule.
    Cases involving the use of CARVYKTITM that are eligible 
for new technology add-on payments will be identified by procedure 
codes XW033A7 (Introduction of ciltacabtagene autoleucel into 
peripheral vein, percutaneous approach, new technology group 7) or 
XW043A7 (Introduction of ciltacabtagene autoleucel into central vein, 
percutaneous approach, new technology group 7). In its application, the 
applicant estimated that the cost of CARVYKTITM is 
$465,000.00 per patient. Because CARVYKTITM is substantially 
similar to ABECMA[supreg], we believe using a single cost for purposes 
of determining the new technology add-on payment amount is appropriate 
for CARVYKTITM and ABECMA[supreg] even though each applicant 
has its own set of codes. We also believe using a single cost provides 
predictability regarding the add-on payment when using 
CARVYKTITM and ABECMA[supreg] for the treatment of patients 
with RRMM. As such, we believe that the use of a weighted average of 
the cost of CARVYKTITM and ABECMA[supreg] based upon the 
projected numbers of cases involving each technology to determine the 
maximum new technology add-on payment would be most appropriate. To 
compute the weighted cost average, we summed the total number of 
projected cases for each of the applicants, which equaled 420 cases 
(241 plus 179). We then divided the number of projected cases for each 
of the applicants by the total number of cases, which resulted in the 
following case weighted percentages: 57% for CARVYKTITM and 
43% for ABECMA[supreg]. We then multiplied the cost per case for the 
manufacturer specific drug by the case-weighted percentage (0.57 * 
$465,000 = $265,050 for CARVYKTITM and 0.43 * $419,500 = 
$180,385 for ABECMA[supreg]). This resulted in a case-weighted average 
cost of $445,435 for the technology.
    Under Sec.  412.88(a)(2), we limit new technology add-on payments 
to the lesser of 65% of the average cost of the technology, or 65% of 
the costs in excess of the MS-DRG payment for the case. As a result, 
the maximum new technology add-on payment for a case involving the use 
of CARVYKTITM or ABECMA[supreg] is $289,532.75 for FY 2023.
b. DARZALEX FASPRO[supreg] (daratumumab and hyaluronidase-fihj)
    Janssen Biotech, Inc., submitted an application for new technology 
add-on payments for DARZALEX FASPRO[supreg] for FY 2023. DARZALEX 
FASPRO[supreg] is a combination of daratumumab (a monoclonal CD38-
directed cytolytic antibody), and hyaluronidase (an endoglycosidase) 
indicated for the treatment of light chain (AL) amyloidosis in 
combination with bortezomib, cyclophosphamide and dexamethasone 
(CyBorD) in newly diagnosed patients and is administered through a 
subcutaneous injection.
    According to the applicant, AL amyloidosis is a life-threatening 
blood disorder caused by increased production of misfolded 
immunoglobulin light chains by an abnormal proliferation of malignant 
CD38+ plasma cells. Per the applicant, these deficient immunoglobulin 
light chains aggregate into highly ordered amyloid fibrils that deposit 
in tissues, eventually resulting in progressive organ dysfunction and 
damage due to the toxic effect of the misfolded proteins 
(proteotoxicity) and the distortion of the normal tissue architecture 
by the amyloid deposits.\66\ The applicant stated that the most 
frequently affected organs are the heart, kidney, liver, spleen, 
gastrointestinal tract and nervous system. Per the applicant, patients 
often have a poor prognosis, and as many as 30% of patients with AL 
amyloidosis die within the first year after diagnosis. The applicant 
stated that approximately 4,500 people in the US develop AL amyloidosis 
each year.\67\ The applicant stated that while there were no FDA 
approved therapies prior to daratumumab, a number of therapies were 
used clinically to treat AL amyloidosis including combination therapies 
like cyclophosphamide-bortezomib-dexamethasone (CyBorD), bortezomib-
lenalidomide-dexamethasone (VRd), bortezomib-melphalan-dexamethasone 
(VMd), melphalan-dexamethasone (Md), and bortezomib-dexamethasone (Vd). 
The applicant further noted that none of these combination regimens are 
approved for use by FDA in this specific indication.
---------------------------------------------------------------------------

    \66\ Merlini et al. Systemic immunoglobin light chain 
amyloidosis. Nat Rev Dis Primers. 2018; 4:38-19.
    \67\ Amyloidosis Foundation. AL amyloidosis facts. https://www.amyloidosis.org/facts/al/. Accessed September 2021.
---------------------------------------------------------------------------

    According to the applicant, DARZALEX FASPRO[supreg] is the first 
and only FDA-approved treatment for patients with AL amyloidosis and is 
also approved for multiple indications for treatment of patients with 
multiple myeloma. The applicant stated that the indication for the 
technology for which it is submitting a new technology add-on payment 
application is for the treatment of adult patients with AL amyloidosis 
in combination with bortezomib, cyclophosphamide and dexamethasone in 
newly diagnosed patients. The applicant noted that DARZALEX 
FASPRO[supreg] is not indicated nor recommended to be used in patients 
with AL amyloidosis who have NYHA Class IIIB or Class IV cardiac 
disease or Mayo Stage IIIB, except in the context of controlled 
clinical trials.
    According to the applicant, DARZALEX FASPRO[supreg] is the 
subcutaneous formulation of daratumumab, which is a human IgG-kappa 
monoclonal antibody that targets CD38, an enzymatic protein that is 
uniformly expressed on human plasma cells. Per the applicant, in 
DARZALEX FASPRO[supreg], daratumumab is co-formulated with recombinant 
human hyaluronidase (rHuP20), which critically allows daratumumab to be 
administered in a volume of 15 mL by a 3-5 minute injection under the 
skin, compared to the 500-1000 mL volume

[[Page 48926]]

and 3-7 hour administration time required for IV daratumumab. The 
applicant further noted that given the cardiac and renal dysfunction 
which afflicts many AL amyloidosis patients and makes them poor 
candidates for large volume IV administration, rHuP20 is a critical 
component of DARZALEX FASPRO[supreg]. Per the applicant, daratumamab 
binds to the CD38 protein on the surface of the malignant plasma cells 
which are responsible for abnormal amyloid protein production in AL 
amyloidosis, directly killing the malignant CD38+ plasma cells and/or 
directing the immune system to destroy them. The immunomodulatory 
response consists of CD8+ clonal expansion, CD38 enzymatic inhibition, 
complement activation and cell recruitment to enable antibody dependent 
cellular phagocytosis (ADPC) and antibody dependent cellular 
cytotoxicity (ADCC). Per the applicant, the mechanism of actions of 
daratumumab in AL amyloidosis are the same as the mechanisms of action 
of daratumumab in multiple myeloma, since both disease entities are 
disorders of malignant CD38+ plasma cells.68 69 70
---------------------------------------------------------------------------

    \68\ de Weers et al. Daratumumab, a Novel Therapeutic Human CD38 
Monoclonal Antibody, Induces Killing of Multiple Myeloma and Other 
Hematogical Tumors. J Immunol 2011;186:1840-1848).
    \69\ Overdijk et al. Antibody-mediated phagocytosis contributes 
to the anti-tumor activity of the therapeutic antibody daratumumab 
in lymphoma and multiple myeloma. MAbs.2015;7:311-321).
    \70\ Krejcik J, Casneuf T, Nijhof IS, et al. Daratumumab 
depletes CD38+ immune regulatory cells, promotes T-cell expansion, 
and skews T-cell repertoire in multiple myeloma. Blood 2016; 128: 
384-94.
---------------------------------------------------------------------------

    The applicant stated that without hyaluronidase, it is not possible 
to inject more than 2-3 mL of drug directly into the subcutaneous 
tissue under the skin. Per the applicant rHuPH20 naturally mimics 
natural hyaluronidase and increases the permeability of subcutaneous 
tissue by degrading hyaluronan. By co-formulating daratumumab with 
rHuPH20, it becomes possible for 15 mL containing 1,800 mg of 
daratumamab to be administered subcutaneously in approximately 3 to 5 
minutes. The applicant stated that the ability to administer 
daratumumab subcutaneously reduces the reaction rate to daratumumab, 
may improve convenience and patient satisfaction, and greatly reduces 
the volume of administration, which is critical in light of the cardiac 
dysfunction and kidney dysfunction which afflict many patients with AL 
amyloidosis.
    With respect to the newness criterion, the applicant stated that 
DARZALEX FASPRO[supreg] was granted accelerated approval from FDA on 
January 15, 2021, indicated for the treatment of adult patients with 
light chain (AL) amyloidosis in combination with bortezomib, 
cyclophosphamide and dexamethasone in newly diagnosed patients. Per the 
applicant, DARZALEX FASPRO[supreg] is not indicated and recommended for 
the treatment of patients with AL amyloidosis who have NYHA Class IIIB 
or Class IV cardiac disease or Mayo Stage IIIB outside of controlled 
clinical trials.\71\ The applicant also stated that DARZALEX 
FASPRO[supreg] received FDA approval on September 26, 2019, for the 
treatment of adult patients with multiple myeloma as part of a 
combination therapy in newly diagnosed patients eligible for autologous 
stem cell transplant, and on May 1, 2020, for the treatment of patients 
with multiple myeloma. As stated previously, the indication for which 
the applicant submitted an application for new technology add-on 
payments is for the treatment of adult patients with AL amyloidosis in 
combination with bortezomib, cyclophosphamide and dexamethasone in 
newly diagnosed patients. The applicant stated that DARZALEX 
FASPRO[supreg] for newly diagnosed AL amyloidosis was commercially 
available immediately following the accelerated approval granted by 
FDA. The recommended dosage for DARZALEX FASPRO[supreg] for newly 
diagnosed AL amyloidosis is 1,800 mg of daratumumab and 30,000 units of 
hyaluronidase administered subcutaneously over approximately 3 to 5 
minutes in combination with bortezomib, cyclophosphamide and 
dexamethasone. According to the applicant, patients receiving DARZALEX 
FASPRO[supreg] for this indication receive a weekly dose for the first 
8 weeks (week 1 to week 8), one dose every 2 weeks from week 9 to week 
24, followed by one dose monthly from week 25 onward until disease 
progression for a maximum of 2 years.
---------------------------------------------------------------------------

    \71\ According to the applicant, continued approval for this 
indication may be contingent upon verification and description of 
clinical benefit in confirmatory trials.
---------------------------------------------------------------------------

    The applicant submitted a request for a unique ICD-10-PCS code to 
identify procedures involving the administration of DARZALEX 
FASPRO[supreg], and was granted approval to identify DARZALEX 
FASPRO[supreg] administration with ICD-10-PCS code XW01318 
(Introduction of daratumumab and hyaluronidase-fihj into subcutaneous 
tissue, percutaneous approach, new technology group 8), effective 
October 1, 2022. We note that DARZALEX FASPRO[supreg] is also approved 
for multiple indications for the treatment of patients with multiple 
myeloma, and this PCS code would not uniquely identify use of the 
technology for the indication for which the applicant has applied for a 
new technology add-on payment. The applicant stated that E85.81 (Light 
chain (AL) amyloidosis) may be used to currently identify the 
indication for DARZALEX FASPRO[supreg] under the ICD-10-CM coding 
system. Therefore, the administration of DARZALEX FASPRO[supreg] for 
the AL amyloidosis indication could be uniquely identified with 
XW01318, in combination with E85.81.
    As previously discussed, if a technology meets all three of the 
substantial similarity criteria under the newness criterion, it would 
be considered substantially similar to an existing technology and would 
not be considered ``new'' for the purposes of new technology add-on 
payments.
---------------------------------------------------------------------------

    \72\ Adams et al. Proteasome Inhibitors: A Novel Class of Potent 
and Effective Antitumor Agents. Cancer Res 1999;55; 2615-2622.
    \73\ Adams et al. The proteasome: a suitable antineoplastic 
target. Nat Rev Cancer 2004; 4:349-360.
---------------------------------------------------------------------------

    With respect to the first criterion, whether a technology uses the 
same or similar mechanism of action to achieve a therapeutic outcome, 
the applicant stated that it does not use the same or similar mechanism 
of action as existing technologies. The applicant stated that DARZALEX 
FASPRO[supreg] was the first drug approved by FDA for treatment of AL 
amyloidosis and its mechanism of action is different from that of any 
other drug previously used to treat AL amyloidosis. According to the 
applicant, the other therapies currently used to treat amyloidosis off-
label (for example, bortezomib, cyclophosphamide, melphalan, 
lenlidomide) all have different mechanisms of action; none of them are 
monoclonal antibodies that specifically bind to CD38 on malignant 
plasma cells. The applicant stated that bortezomib induces cell death 
of the malignant plasma cell by inhibition of the 26S proteasome which 
plays a key role in cell survival by regulating protein breakdown in a 
controlled fashion. The applicant further stated that when bortezomib 
inhibits proteasome function, the normal balance within a cell is 
disrupted, resulting in a buildup of cell cycle and regulatory proteins 
which eventually leads to cell death.72 73 Per the 
applicant, lenalidomide is an immunomodulator which modulates the E3 
ubiquitin ligase complex. Modulation of this E3 ubiquitin ligase

[[Page 48927]]

complex by lenalidomide eventually leads to enhanced function of 
specific immune cells and induction of cell death and the exact 
mechanism of action of lenalidomide is still not fully 
understood.74 75 The applicant stated that both melphalan 
and cyclophosphamide are alkylating chemotherapy drugs that add an 
alkyl group to the guanine base of the DNA molecule, preventing the 
strands of the double helix from linking, which causes breakage of the 
DNA strands, affecting the ability of the cancer cell to multiply. Per 
the applicant, like bortezomib and lenalidomide, melphalan and 
cyclophosphamide are not approved by FDA for the use in patients with 
AL amyloidosis. The applicant also noted that while the National 
Comprehensive Cancer Network[supreg] (NCCN[supreg]) Guidelines for 
Systemic Light Chain Amyloidosis state that both IV and SQ daratumumab 
can be used to treat previously treated amyloidosis,\76\ IV daratumumab 
is not approved by FDA for the treatment of patients with amyloidosis 
(newly diagnosed and previously treated). The applicant also stated 
that DARZALEX FASPRO[supreg] is the more appropriate option in the AL 
amyloidosis patient population due to the fact that subcutaneous dosing 
has a negligible volume administration (15 ml for SC vs up to 1,000 ml 
for IV), which is particularly important in patients with AL 
amyloidosis who often have compromised cardiac and renal function due 
to the amyloid deposition in cardiac and kidney tissue.
---------------------------------------------------------------------------

    \74\ Kastritis et al. Primary treatment of light chain 
amyloidosis with Bortezomib, lenalidomide and dexamethasone. Blood 
Adv 2019;3:3002-3009.
    \75\ Revlimid Prescribing Info.
    \76\ NCCN Clinical Practice Guidelines in Oncology (NCCN 
Guidelines[supreg]): Systemic Light Chain amyloidosis (Version 
1.2022). National Comprehensive Cancer Network. www.nccn.org. 
Published August 29 June 2021. Accessed July 21, 2021.
---------------------------------------------------------------------------

    With respect to the second criterion, whether a product is assigned 
to the same or a different MS-DRG, the applicant stated that this 
product is not expected to change the DRG assignment of a case when 
used for the treatment of AL amyloidosis.
    With respect to the third criterion, whether the new use of 
technology involves the treatment of the same or similar type of 
disease and the same or similar patient population when compared to an 
existing technology, the applicant stated that DARZALEX FASPRO[supreg] 
does not meet this criterion because it was the first approved drug to 
treat patients with AL amyloidosis. The applicant also stated that the 
NCCN[supreg] Guidelines for Systemic Light Chain Amyloidosis reflect 
the limited treatment options for this specific disease. The applicant 
further stated that DARZALEX FASPRO[supreg] in combination with CyBorD 
is the only treatment with a Category 1 recommendation \77\ in the 
NCCN[supreg] Guidelines for patients with newly diagnosed AL 
amyloidosis.\78\
---------------------------------------------------------------------------

    \77\ Per the NCCN[supreg], a Category 1 recommendation is 
``Based upon high-level evidence, there is uniform NCCN[supreg] 
consensus that the intervention is appropriate.''
    \78\ NCCN Clinical Practice Guidelines in Oncology (NCCN 
Guidelines[supreg]): Systemic Light Chain amyloidosis (Version 
1.2022). National Comprehensive Cancer Network. www.nccn.org. 
Published August 29 June 2021. Accessed July 21, 2021.
---------------------------------------------------------------------------

    In summary, the applicant believes that DARZALEX FASPRO[supreg] is 
not substantially similar to other currently available therapies and/or 
technologies because it has a unique mechanism of action and because it 
is the first FDA approved treatment for AL amyloidosis.
    We invited public comments on whether DARZALEX FASPRO[supreg] is 
substantially similar to existing technologies and whether DARZALEX 
FASPRO[supreg] meets the newness criterion.
    Comment: The applicant submitted a comment reiterating its belief 
that DARZALEX FASPRO[supreg] meets the newness criterion because it was 
the first drug approved by FDA for patients with newly diagnosed light 
chain amyloidosis and that the mechanism of action is different from 
that of any other drug previously used to treat AL amyloidosis in that 
it is a monoclonal antibody that specifically binds to CD38 on 
malignant cancer cells. The applicant stated that because of this 
unique mechanism of action, DARZALEX FASPRO[supreg] for AL is not 
substantially similar to current treatments for AL and therefore meets 
the newness criterion.
    Response: We thank the applicant for its comment. Based on our 
review of comments received and information submitted by the applicant 
as part of its FY 2023 new technology add-on payment application for 
DARZALEX FASPRO[supreg], we agree with the applicant that DARZALEX 
FASPRO[supreg] has a unique mechanism of action as the first FDA 
approved treatment for AL amyloidosis. Therefore, we believe that 
DARZALEX FASPRO[supreg] is not substantially similar to existing 
treatment options and meets the newness criterion. We consider the 
beginning of the newness period to commence when DARZALEX 
FASPRO[supreg] was approved by FDA for the treatment of adult patients 
with light chain (AL) amyloidosis in combination with bortezomib, 
cyclophosphamide and dexamethasone in newly diagnosed patients, on 
January 15, 2021.
    With respect to the cost criterion, the applicant presented the 
following analysis to demonstrate that DARZALEX FASPRO[supreg] meets 
the cost criterion. To identify cases representing patients who may be 
eligible for treatment with DARZALEX FASPRO[supreg], the applicant 
searched the FY 2019 MedPAR database released with the FY 2022 IPPS 
final rule and stated that it used fee-for-service IPPS discharges, 
plus Maryland hospital discharges. The applicant searched for claims 
reporting ICD-10-CM diagnosis code E85.81 (Light chain amyloidosis) in 
conjunction with at least one of the following additional ICD-10-CM 
diagnosis codes:
BILLING CODE 4120-01-P

[[Page 48928]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.081

    The applicant excluded cases with a length of stay greater than 7 
days from the analysis. According to the applicant, administration of 
DARZALEX FASPRO[supreg] would likely be delayed if a patient becomes 
seriously ill during the course of treatment, so it is unlikely a 
patient would receive DARZALEX FASPRO[supreg] during an inpatient stay 
lasting longer than 7 days. The applicant indicated that based on the 
advice of clinical experts, it also excluded cases mapped to the 
following MS-DRGs, as DARZALEX FASPRO[supreg] would not be an 
appropriate treatment for patients receiving treatment for such 
conditions:

[[Page 48929]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.082


[[Page 48930]]


[GRAPHIC] [TIFF OMITTED] TR10AU22.083

    After applying the case selection and exclusion criteria, the 
applicant's search resulted in the identification of 114 MS-DRGs using 
the FY 2019 MedPAR file dataset. The applicant imputed a case count of 
11 for 104 MS-DRGs with

[[Page 48931]]

fewer than 11 cases, resulting in a total of 1,494 cases mapping to the 
114 MS-DRGs.
[GRAPHIC] [TIFF OMITTED] TR10AU22.084


[[Page 48932]]


[GRAPHIC] [TIFF OMITTED] TR10AU22.085


[[Page 48933]]


[GRAPHIC] [TIFF OMITTED] TR10AU22.086

BILLING CODE 4120-01-C
    The applicant determined an average unstandardized case weighted 
charge per case of $47,599.
    The applicant did not remove charges for related or prior 
technologies because, per the applicant, DARZALEX FASPRO[supreg] would 
not replace other therapies a patient may receive during an inpatient 
stay. Next, the applicant standardized the charges using the FY 2022 
IPPS/LTCH PPS final rule impact file and applied a 4-year inflation 
factor of 1.281834 or 28.1834% based on the inflation factor used in 
the FY 2022 IPPS/LTCH PPS final rule to update the outlier threshold 
(86 FR 45542). The applicant then added charges for the new technology 
by multiplying the per treatment cost of DARZALEX FASPRO[supreg] by the 
inverse of the national average drug CCR of 0.187 from the FY 2022 
IPPS/LTCH PPS final rule (86 FR 44966).
    The applicant calculated a final inflated average case-weighted 
standardized charge per case of $92,916, which exceeded the average 
case-weighted threshold amount of $61,426. Because the final inflated 
average case-weighted standardized charge per case exceeded the average 
case-weighted threshold amount, the applicant maintained that DARZALEX 
FASPRO[supreg] meets the cost criterion.
    We invited public comment on whether DARZALEX FASPRO[supreg] meets 
the cost criterion.
    Comment: The applicant submitted a comment reiterating its belief 
that because the final inflated average case-weighted standardized 
charge per case exceeded the average case-weighted threshold amount, 
DARZALEX FASPRO[supreg] meets the cost criterion.
    Response: We thank the commenter for its comment. We agree the 
final inflated average case-weighted standardized charge per case 
exceeded the average case-weighted threshold amount. Therefore, 
DARZALEX FASPRO[supreg] meets the cost criterion.
    With regard to the substantial clinical improvement criterion, the 
applicant asserted that DARZALEX FASPRO[supreg] represents a 
substantial clinical improvement over existing technologies because it 
offers a treatment option for a patient population unresponsive to, or 
ineligible for, currently available treatments. The applicant also 
asserted that DARZALEX FASPRO[supreg] demonstrates significant 
improvement in a number of clinical outcomes including hematologic 
complete response (hemCR), prolonged survival free from major organ 
deterioration, increased cardiac and renal response rates, with a 
demonstrated safety and tolerability profile and no negative impact to 
health-related quality of life based on patient-reported outcomes.
    With regard to the claim that DARZALEX FASPRO[supreg] offers a 
treatment option for a patient population unresponsive to, or 
ineligible for, currently available treatments, the applicant stated 
that the initial standard of therapy (CyBorD) is considered inadequate, 
as most patients do not respond adequately to the CyBorD regimen alone. 
Furthermore, according to the applicant, the ANDROMEDA data shows that 
>80% of patients do not achieve a hemCR, >75% of patients with cardiac 
disease do not have an organ response, and >75% of patients with renal 
disease do not have an organ response when treated with the initial 
standard of therapy CyBorD. Per the applicant, there is a high unmet 
need to improve treatment for AL amyloidosis patients. The applicant 
stated that rapid and deep response like hemCR are critical and are 
strongly associated with organ response and improved survival in AL 
amyloidosis.\79\ Per the applicant, adding DARZALEX FASPRO[supreg] to 
CyBorD increases the hemCR rate by three-fold and doubles the cardiac 
and renal response rates, thereby addressing this high unmet medical 
need.
---------------------------------------------------------------------------

    \79\ Comenzo RL, Reece D, Palladini G, et al. Consensus 
guidelines for the conduct and reporting of clinical trials in 
systemic light chain amyloidosis. Leukemia. 2012;26: 2317-2325.
---------------------------------------------------------------------------

    With regard to the claim that the use of DARZALEX FASPRO[supreg] 
significantly improves clinical outcomes for a patient population as 
compared to currently available treatments, as stated previously, the 
applicant asserted that DARZALEX FASPRO[supreg] represents a 
substantial clinical improvement over existing technologies because it: 
(1) demonstrates a consistent safety profile; (2) significantly 
improves hematologic complete response (hemCR rates); (3) maintains the 
increased hemCR rates for pre-specified subgroups; (4) shortens the 
time to hemCR; (5) improves very good partial response (VGPR) or better 
rates; (6) substantially improves cardiac response at 6 and at 12 
months; (7) improves renal response at 6 and at 12 months; (8) improves 
major-organ deterioration or progression-free survival (MOD-PFS); (9) 
improves Global Health status and fatigue as of cycle 6 of treatment, 
and maintains health-related quality of life (HRQoL); and (10) provides 
important advantages for the population with AL.
    In support of these claims, the applicant submitted the ANDROMEDA 
phase 3 trial as well as presentations related to these trials. The 
applicant stated that data in the ANDROMEDA study demonstrated that 
DARZALEX FASPRO[supreg] led to significantly better outcomes both at 
the time of the

[[Page 48934]]

primary analysis \80\ as well as at the time of updated analyses which 
were presented at the 2021 ASCO annual meeting and 2021 EHA annual 
meeting.\81\
---------------------------------------------------------------------------

    \80\ Kastritis et al. Daratumumab-Based Treatment for 
Immunoglobulin Light-Chain Amyloidosis. New England Journal of 
Medicine (NEJM). 2021; 385:46-58.
    \81\ Kastritis E, et al., Subcutaneous Daratumumab + 
Cyclophosphamide, Bortezomib, and Dexamethasone (CyBorD) in Patients 
with Newly Diagnosed Light Chain (AL) Amyloidosis: Updated Results 
from the Phase 3 ANDROMEDA Study, Oral presentation at: American 
Society for Oncology (ASCO) Annual Virtual Meeting; June 4-8, 2021 & 
Oral presentation at: European Hematology Association (EHA) Annual 
Virtual Meeting; June 9-17, 2021.
---------------------------------------------------------------------------

    ANDROMEDA was a randomized, open-label, phase 3 study of 388 
patients with newly diagnosed AL amyloidosis randomized 1:1 to receive 
6 cycles of CyBorD, either alone (control group, n=193) or in 
combination with daratumumab SC (that is, DARZALEX FASPRO[supreg]), 
followed by DARZALEX FASPRO[supreg] monotherapy every 4 weeks for up to 
24 additional cycles (daratumumab group, n=195). The study enrolled 
patients between May 3, 2018 and August 15, 2019. Median age was 64 
(range 34-87). The study reported a median 11.4 month follow-up for the 
published trial, and 20.3 months for the follow-up data. The primary 
endpoint was hemCR, defined as having negative serum and urine 
immunofixation and a free light chain ratio (FLCr) within the reference 
range or abnormal free light-chain ratio if the uninvolved free light 
chain (uFLC) is higher than the involved free light chain (iFLC). 
According to the applicant, this definition of hemCR is in line with a 
recent clarification of the Internal Society of Amyloidosis 
guidelines.\82\ Secondary endpoints were survival free from major organ 
deterioration or hematologic progression (composite end point that 
included end-stage cardiac or renal failure, hematologic progression), 
or death, organ response, overall survival, hematologic complete 
response at 6 months, VGPR or better, time to and duration of 
hematologic complete response, time to next treatment, and reduction in 
fatigue. The applicant noted that the safety population in the 
ANDROMEDA study consisted of 193 patients in the daratumumab arm and 
188 patients in the control arm.
---------------------------------------------------------------------------

    \82\ Palladini et al. Daratumumab plus CyBord for patients with 
newly diagnosed AL amyloidosis: safety run-in results of ANDROMEDA. 
Blood.2020;136:71-80.
---------------------------------------------------------------------------

    The applicant also cited an oral presentation, presented at the 
American Society of Clinical Oncology (ASCO) 2021 and European 
Hematology Association (EHA) 2021 annual meetings, with updated data 
from the ANDROMEDA study after 20.3 months of follow-up, which 
described sustained primary outcome of higher rates of hemCR across 
subgroups as well as improved secondary endpoints of cardiac and renal 
response rate at 12 months. In the intent to treat population, there 
were 11 deaths in the CyBorD group compared to 7 deaths in the control 
group.\83\
---------------------------------------------------------------------------

    \83\ Kastritis E, et al., Subcutaneous Daratumumab + 
Cyclophosphamide, Bortezomib, and Dexamethasone (CyBorD) in Patients 
with Newly Diagnosed Light Chain (AL) Amyloidosis: Updated Results 
from the Phase 3 ANDROMEDA Study, Oral presentation at: American 
Society for Oncology (ASCO) Annual Virtual Meeting; June 4-8, 2021 & 
Oral presentation at: European Hematology Association (EHA) Annual 
Virtual Meeting; June 9-17, 2021.
---------------------------------------------------------------------------

    In support of its assertion that DARZALEX FASPRO[supreg] 
demonstrates a consistent safety profile, the applicant cited Kastritis 
et al., discussed previously, stating that the safety profiles of 
daratumumab and bortezomib, cyclophosphamide, and dexamethasone in the 
ANDROMEDA trial were consistent with their known profiles and the 
underlying disease from previous trials.\84\ To support its assertion 
that DARZALEX FASPRO[supreg] significantly improves hemCR rate, the 
applicant stated that the trial results showed that patients treated 
with DARZALEX FASPRO[supreg] demonstrated a statistically significant 
increase in hemCR compared to control (53.3% versus 18.1%; relative 
risk ratio, 2.9; 95% CI, 2.1 to 4.1; odds ratio, 5.1; 95% CI, 3.2 to 
8.2; p <0.001 for both comparisons) at the 11.4 month median follow-up. 
To support its assertion that DARZALEX FASPRO[supreg] results in a 
shorter time to hemCR, the applicant noted that in the trial, median 
time to hemCR was 60 days in the daratumumab group and 85 days in the 
control group. In support of its assertion that the increased hemCR 
rate was maintained for pre-specified subgroups, the applicant also 
stated that hemCR remained consistent in most prespecified subgroups 
(for example, sex, age, weight, race, cardiac stage, etc.) receiving 
daratumumab.\85\ The applicant also cited results from the oral 
presentation, discussed previously, stating that after a median follow 
up of 20.3 months, the percentage of patients who achieved hemCR 
increased to 59% in the daratumumab group vs 19% in the control group 
(odds ratio: 5.9; 95% CI, 3.7 to 9.4; P <0.001), and that this 
advantage was seen consistently across all prespecified subgroups.\86\ 
The applicant stated that rapid and deep hematologic responses are 
critical and are strongly associated with organ response and improved 
survival in AL amyloidosis.\87\
---------------------------------------------------------------------------

    \84\ Kastritis E, et al., Daratumumab-Based Treatment for 
Immunoglobulin Light-Chain Amyloidosis, N Eng J Med. 2021; 385:46-
58.
    \85\ Kastritis E, et al., Daratumumab-Based Treatment for 
Immunoglobulin Light-Chain Amyloidosis, N Eng J Med. 2021; 385:46-
58.
    \86\ Kastritis E, et al., Subcutaneous Daratumumab + 
Cyclophosphamide, Bortezomib, and Dexamethasone (CyBorD) in Patients 
with Newly Diagnosed Light Chain (AL) Amyloidosis: Updated Results 
from the Phase 3 ANDROMEDA Study, Oral presentation at: American 
Society for Oncology (ASCO) Annual Virtual Meeting; June 4-8, 2021 & 
Oral presentation at: European Hematology Association (EHA) Annual 
Virtual Meeting; June 9-17, 2021.
    \87\ Comenzo RL, Reece D, Palladini G, et al. Consensus 
guidelines for the conduct and reporting of clinical trials in 
systemic light chain amyloidosis. Leukemia. 2012;26: 2317-2325.
---------------------------------------------------------------------------

    In support of its assertion that DARZALEX FASPRO[supreg] improved 
VGPR or better rates, the applicant also stated that the trial 
demonstrated that the secondary endpoint of VGPR or better was 78.5% in 
the daratumumab group and 49.2% in the control group (relative risk 
ratio, 1.6; 95% CI, 1.4 to 1.9; odds ratio, 3.8; 95% CI, 2.4 to 
5.9).\88\ Per the applicant, the substantial improvements in 
hematologic response rates and other endpoints like cardiac and renal 
response and MOD-PFS indicate the clinical meaningfulness of these 
efficacy results.
---------------------------------------------------------------------------

    \88\ Kastritis et al., Daratumumab for immunoglobulin light-
chain amyloidosis. N Eng J Med 2021; 385:48-58.
---------------------------------------------------------------------------

    In support of its assertion that DARZALEX FASPRO[supreg] 
substantially improves cardiac response at 6 and at 12 months, 
according to the applicant, of the subgroup that was evaluated for 
cardiac response (118 in the daratumumab group and 117 in the control 
group), 41.5% in the daratumumab group and 22.2% in the control group 
(odds ratio, 2.44; 95% CI: 1.35 to 4.42) demonstrated a cardiac 
response at 6 months.\89\ The applicant noted that at a median follow 
up of 20.3 months, cardiac response rates were higher with in the 
daratumumab group compared to CyBorD alone at 6 months (42% versus 22%, 
odds ratio 2.4, 95% CI 1.4 to 4.4; P = .0029) and at 12 months (57% 
versus 28%, odds ratio 3.5 95% CI 2.0 to 6.2; P <0.0001).\90\ In 
addition, in support of its assertion that

[[Page 48935]]

DARZALEX FASPRO[supreg] improves renal response at 6 and at 12 months, 
the applicant noted that in the subgroup evaluated for renal response 
(117 in the daratumumab group and 113 in the control group), 53.0% of 
patients in the daratumumab group and 23.9% in the control group (odds 
ratio, 3.34; 95% CI: 1.88 to 5.94) demonstrated a renal response at 6 
months.\91\ The applicant noted that at a median follow up of 20.3 
months, renal response rates were higher with in the daratumumab group 
compared to CyBorD alone at 6 months (54% vs 27%; odds ratio 3.3 95% CI 
1.9 to 5.9; P <0.0001) and at 12 months (57% vs 27%; odds ratio 4.1 95% 
CI 2.3 to 7.3; P <0.0001).\92\ The applicant noted that the percentages 
of patients who had a cardiac or renal response were substantially 
higher in the daratumumab group than in the control group, which it 
stated was an important finding given that organ responses are also a 
predictor of improved survival.
---------------------------------------------------------------------------

    \89\ Kastritis E, et al., Daratumumab-Based Treatment for 
Immunoglobulin Light-Chain Amyloidosis, N Eng J Med. 2021; 385:46-
58.
    \90\ Kastritis E, et al., Subcutaneous Daratumumab + 
Cyclophosphamide, Bortezomib, and Dexamethasone (CyBorD) in Patients 
with Newly Diagnosed Light Chain (AL) Amyloidosis: Updated Results 
from the Phase 3 ANDROMEDA Study, Oral presentation at: American 
Society for Oncology (ASCO) Annual Virtual Meeting; June 4-8, 2021 & 
Oral presentation at: European Hematology Association (EHA) Annual 
Virtual Meeting; June 9-17, 2021.
    \91\ Kastritis E, et al., Daratumumab-Based Treatment for 
Immunoglobulin Light-Chain Amyloidosis, N Eng J Med. 2021; 385:46-
58.
    \92\ Kastritis E, et al., Subcutaneous Daratumumab + 
Cyclophosphamide, Bortezomib, and Dexamethasone (CyBorD) in Patients 
with Newly Diagnosed Light Chain (AL) Amyloidosis: Updated Results 
from the Phase 3 ANDROMEDA Study, Oral presentation at: American 
Society for Oncology (ASCO) Annual Virtual Meeting; June 4-8, 2021 & 
Oral presentation at: European Hematology Association (EHA) Annual 
Virtual Meeting; June 9-17, 2021.
---------------------------------------------------------------------------

    In support of its assertion that DARZALEX FASPRO[supreg] improves 
MOD-PFS, the applicant noted significant findings of secondary endpoint 
survival free from major organ deterioration or hematologic progression 
in the daratumumab group compared to control (hazard ratio for major 
organ deterioration, hematologic progression, or death, 0.58; 95% CI, 
0.36 to 0.93; P = 0.02).\93\
---------------------------------------------------------------------------

    \93\ Kastritis et al. Daratumumab-Based Treatment for 
Immunoglobulin Light-Chain Amyloidosis. NEJM. 2021;385:46-58.
---------------------------------------------------------------------------

    With regard to the claim that DARZALEX FASPRO[supreg] improves 
Global Health status (GHS) and fatigue as of cycle 6 of treatment, as 
well as maintains HRQoL, the applicant cited a poster presentation of a 
subgroup analysis on patient reported outcomes (PRO) for patients 
participating in the ANDROMEDA study.\94\ The applicant noted that the 
patients were provided with PRO questionnaires and assessed on day 1 of 
cycles -1-6 as well as every 8 weeks thereafter in the daratumumab 
group. The applicant stated that of the 388 patients randomized in the 
study, compliance rates for all PRO questionnaires were >90% at 
baseline and >83% through Cycle 6. The questionnaires included the 
European Organization for Research and Treatment of Cancer Quality of 
Life Questionnaire Core 30-item (EORTC QLQ-C30), the EuroQol 5-
dimensional descriptive system (EQ-5D-5L), and Short Form-36 (SF-36). 
Secondary endpoints centered around improvements in EORTC QLQ-C30 
global health status (GHS), fatigue scale scores, and SF-36 mental 
component summary (MCS) score. Exploratory outcomes included physical 
function assessment, symptom improvement, functional improvement, and 
health utility as measured by the SF-36, EORTC QLQC30 with supplemental 
symptom items, and the EQ-5D-5L.
---------------------------------------------------------------------------

    \94\ Sanchorawala et al., Health-Related Quality of Life in 
Patients with AL Amyloidosis Treated with Daratumumab, Bortezomib, 
Cyclophosphamide, and Dexamethasone: Results from the Phase 3 
ANDROMEDA Study, Poster presentation at: American Society of 
Hematology (ASH) Annual Virtual Meeting; December 5-8, 2020.
---------------------------------------------------------------------------

    The applicant stated that the results from this presentation show 
that following Cycle 6, improvements in GHS and fatigue were reported 
in patients in the treatment group, and that these findings further 
support the value of daratumumab SQ plus CyBorD (Dara-CyBorD) in 
patients with AL amyloidosis. The applicant also stated that patients 
with AL amyloidosis treated with Dara-CyBorD experienced clinical 
improvements without any decrement in HRQoL over 6 cycles. The 
applicant noted that the findings demonstrated that the median time to 
improvement was shorter in the treatment group than in the control 
group for EORTC QLQ-C30 GHS (CyBorD: 16.79 months, 95% CI:11.79 to NE, 
Dara-CyBorD: 7.82 months, 95% CI: 3.94 to 17.58, HR 1.53; 95% CI: 1.10 
to 2.13), fatigue scales (CyBorD: NE, 95% CI:8.44 to NE, Dara-CyBorD: 
9.30 months, 95% CI: 5.55 to 13.01, HR 1.39; 95% CI: 1.00 to 1.93) and 
EQ-5D-5L visual analog scale (CyBorD: NE, 95% CI:16.79 to NE, Dara-
CyBorD: 10.05 months, 95% CI: 8.41 to NE, HR 1.21; 95% CI: 0.86 to 
1.71). The applicant also noted that the findings demonstrated that 
median time to worsening was longer in the treatment group than in the 
control group for EORTC QLQ-C30 GHS (CyBorD: 2.89 months, 95% CI:2.23 
to 3.78, Dara-CyBorD: 4.70 months, 95% CI: 2.83 to 7.36, HR 0.87; 95% 
CI: 0.66 to 1.13) and fatigue scales (CyBorD: 3.75 months, 95% CI: 2.86 
to 4.76 Dara-CyBorD: 8.84 months, 95% CI: 3.75 to NE, HR 0.78; 95% CI: 
0.58 to 1.04) and EQ-5D-5L visual analog scale (CyBorD: 3.38 months, 
95% CI:2.79 to 4.67, Dara-CyBorD: 4.14 months, 95% CI: 2.86 to 7.66, HR 
0.89; 95% CI: 0.67 to 1.19).\95\
---------------------------------------------------------------------------

    \95\ Sanchorawala et al., Health-Related Quality of Life in 
Patients with AL Amyloidosis Treated with Daratumumab, Bortezomib, 
Cyclophosphamide, and Dexamethasone: Results from the Phase 3 
ANDROMEDA Study, Poster presentation at: American Society of 
Hematology (ASH) Annual Virtual Meeting; December 5-8, 2020.
---------------------------------------------------------------------------

    Finally, the applicant stated that DARZALEX FASPRO[supreg] provides 
important advantages to the population with AL amyloidosis because the 
subcutaneous administration allows for a negligible volume of 
administration and a reduced rate of systemic administration-related 
reactions.\96\
---------------------------------------------------------------------------

    \96\ Kastritis et al. Daratumumab-Based Treatment for 
Immunoglobulin Light-Chain Amyloidosis. NEJM. 2021;385:46-58.
---------------------------------------------------------------------------

    In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28234 through 
28235), after review of the information provided by the applicant, we 
stated we had the following concerns regarding whether DARZALEX 
FASPRO[supreg] meets the substantial clinical improvement criterion. 
First, with respect to the ANDROMEDA trial, we noted that the study's 
open label and unblinded design adds a potential risk of bias which may 
affect the treatment effect reported by the applicant. Additionally, we 
noted that the ANDROMEDA trial used stratified randomization which 
resulted in potentially substantive differences between the treatment 
and control group at baseline; for example, the control group was 
slightly older, with more males, and more people at higher cardiac 
stage (based on N-terminal pro-B-type natriuretic peptide and high-
sensitivity cardiac troponin T). The groups also differed by Eastern 
Cooperative Oncology Group (ECOG) performance-status scores and 
uninvolved free light chain (dFLC) levels, and renal function. 
Additionally, compared to control, the daratumumab group appeared to 
have higher rates of peripheral sensory neuropathy, upper respiratory 
infection, and neutropenia in the longer term data.\97\ We questioned 
whether these differences noted at baseline are in fact significant and 
would have the potential to impact the treatment effect seen in this 
study. In terms of study outcomes, the ANDROMEDA study relied on 
hematologic and organ-based laboratory-based outcomes, but we 
questioned

[[Page 48936]]

whether a primary endpoint of overall survival would have provided 
stronger evidence.
---------------------------------------------------------------------------

    \97\ Kastritis E, et al., Subcutaneous Daratumumab + 
Cyclophosphamide, Bortezomib, and Dexamethasone (CyBorD) in Patients 
with Newly Diagnosed Light Chain (AL) Amyloidosis: Updated Results 
from the Phase 3 ANDROMEDA Study, Oral presentation at: American 
Society for Oncology (ASCO) Annual Virtual Meeting; June 4-8, 2021 & 
Oral presentation at: European Hematology Association (EHA) Annual 
Virtual Meeting; June 9-17, 2021.
---------------------------------------------------------------------------

    Second, we had concerns about the generalizability of the ANDROMEDA 
population and subgroups. As clarified by the applicant during the New 
Technology Town Hall meeting, all subjects in the ANDROMEDA trial 
received DARZALEX FASPRO[supreg] in the outpatient setting. As such, we 
questioned whether the outcomes for this outpatient population are 
generalizable to patients who are sufficiently ill to require 
hospitalization. In regard to subpopulations, we noted that the 
prespecified groups and the studies of cardiac stage and Asian cohorts 
exhibit the same potential limitations of the main trial with small 
sample size, open-label, and limited follow-up. We noted that small 
sample size resulted in wider confidence intervals in some subgroups, 
which may limit the generalizability of the treatment results. For 
example, in the ANDROMEDA prespecified groups, the subgroups `other' 
race, cardiac stage I at baseline, and renal stage III had wider 
confidence intervals than other subgroups. Finally, while the applicant 
provided a phase 2 poster presentation in support of DARZALEX 
FASPRO[supreg] we questioned the extent to which these results are 
generalizable to the indication for which the applicant has applied for 
the new technology add-on payment (that is, the treatment of adult 
patients with light chain (AL) amyloidosis in combination with 
bortezomib, cyclophosphamide and dexamethasone in newly diagnosed 
patients) given that the indication within this source (that is 
monotherapy in patients with Stage 3B AL amyloidosis), does not 
match.\98\
---------------------------------------------------------------------------

    \98\ Kastritis E, et al., Subcutaneous Daratumumab + 
Cyclophosphamide, Bortezomib, and Dexamethasone (CyBorD) in Patients 
with Newly Diagnosed Light Chain (AL) Amyloidosis: Updated Results 
from the Phase 3 ANDROMEDA Study, Oral presentation at: American 
Society for Oncology (ASCO) Annual Virtual Meeting; June 4-8, 2021 & 
Oral presentation at: European Hematology Association (EHA) Annual 
Virtual Meeting; June 9-17, 2021.
---------------------------------------------------------------------------

    We noted that the applicant provided the outcomes of secondary 
endpoints which appear to be exploratory or novel for some of the data 
presented in posters in support of its claims, such as the quality of 
life assessments \99\ and hematologic response as measured by involved 
and uninvolved free light chain,\100\ and we noted that some of the 
endpoints are still being studied and validated. Specifically, we 
questioned whether these surrogate endpoints may be used to 
appropriately evaluate the measure for which they are intended to 
assess. We requested further information on whether these secondary 
endpoints have been appropriately validated in relevant clinical 
settings.
---------------------------------------------------------------------------

    \99\ Sanchorawala et al., Health-Related Quality of Life in 
Patients with AL Amyloidosis Treated with Daratumumab, Bortezomib, 
Cyclophosphamide, and Dexamethasone: Results from the Phase 3 
ANDROMEDA Study, Poster presentation at: American Society of 
Hematology (ASH) Annual Virtual Meeting; December 5-8, 2020.
    \100\ Comenzo et al., Reduction in Absolute Involved Free Light 
Chain and Difference Between Involved and Uninvolved Free Light 
Chain is Associated with Prolonged Major Organ Deterioration 
Progression Free survival in Patient with Newly Diagnosed AL 
Amyloidosis Receiving Bortezomib, Cyclophosphamide and Dexamethasone 
with or without Daratumumab: Results from ANDROMEDA, Oral 
presentation at: American Society of Hematology (ASH) Annual Virtual 
Meeting; December 5-8, 2020.
---------------------------------------------------------------------------

    We invited public comments on whether DARZALEX FASPRO[supreg] meets 
the substantial clinical improvement criterion.
    Comment: The applicant submitted a comment in response to CMS' 
concerns pertaining to substantial clinical improvement. With respect 
to our concern that the open label and unblinded study design of the 
ANDROMEDA trial may result in a biased treatment effect, the applicant 
stated that clinical trials designed to evaluate treatment effects in 
patients with AL amyloidosis need to account for the heterogeneity of 
the disease, the number of affected organs, including the heart, 
kidney, and liver, and the severity of organ involvement. Per the 
applicant, in addition to randomization by chance to the experimental 
Dara-CyBorD arm or the control CyBorD arm, subjects in the ANDROMEDA 
trial were randomized by cardiac stage, by whether transplant was 
typically offered, and by renal function. The applicant stated that 
efficacy data were adjudicated by an independent review committee whose 
members were unaware of the trial-group assignments. The applicant 
stated that patients in the control arm were marginally older and that 
there were slightly more males than females but that these small 
differences are not expected to cause a major difference in outcomes. 
The applicant also stated that the slight increase in males in this 
study is similar to an analysis of U.S. commercial and Medicare 
Supplemental claims data that found the prevalence of AL amyloidosis is 
higher in males (approximately 55% male).\101\
---------------------------------------------------------------------------

    \101\ Quock et al. Epidemiology of AL amyloidosis: a real-world 
study using US claims data. Blood Adv 2018: 2: 1046-1053.
---------------------------------------------------------------------------

    The applicant stated that the percentage of subjects in cardiac 
stage IIIA was similar in the two treatment arms.\102\ Per the 
applicant, neither the slightly higher percentage of subjects with 
cardiac stage IIIB (3.1% vs. 1.0%) in the CyBorD arm nor the observed 
small differences in the ECOG status and renal status between the two 
arms are expected to have a major difference on the final outcomes.
---------------------------------------------------------------------------

    \102\ Kastritis et al., NEJM, 2021.
---------------------------------------------------------------------------

    With regard to the concern regarding higher peripheral sensory 
neuropathy, upper respiratory infection, and neutropenia in longer term 
data for the daratumumab group compared to the control group, the 
applicant stated that the relative incidence of infections like 
pneumonia as well as peripheral sensory neuropathy and neutropenia 
should be interpreted in the context of longer treatment exposure for 
patients receiving Dara-CyBorD vs. CyBorD. The applicant stated that 
when adjusted for exposure to trial treatment, the incidence of overall 
and grade 3 or 4 adverse events was lower in the daratumumab group than 
in the control group.\103\
---------------------------------------------------------------------------

    \103\ Kastritis et al., NEJM, 2021.
---------------------------------------------------------------------------

    With regard to the concern regarding hematologic and organ-based 
laboratory-based outcomes instead of overall survival, the applicant 
stated that primary treatment is targeted toward suppression of amyloid 
light chain synthesis in order to improve organ function. The applicant 
stated that treatment efficacy is typically determined by hematologic 
response and that the current staging systems for AL amyloidosis are 
based on circulating markers of cardiac, renal, and B cell clonal 
disease and are used for clinical trial design and to determine patient 
management. The applicant stated that because clinical presentation and 
long-term outcomes depend on adequate organ function, complete response 
(CR) does not completely describe the clinical efficacy of treatment in 
patients with AL amyloidosis. The applicant stated that organ response 
rates can be used but there are limitations with only using these 
biomarkers to monitor organ response. The applicant stated that, in 
consultation with and with the approval of the FDA, major organ 
deterioration-progression free survival (MOD-PFS) and major organ 
deterioration-event free survival (MOD-EFS) were chosen as secondary 
endpoints and were calculated as a composite endpoint of clinically 
observable endpoints. The applicant stated that several clinical 
studies have demonstrated that hematologic and organ responses were

[[Page 48937]]

very strong predictors of overall survival.\104\ \105\ \106\
---------------------------------------------------------------------------

    \104\ Palladini G et al. Management of AL amyloidosis in 2020. 
Blood 2020; 136:2620-2627.
    \105\ Palladini et al., J Clin Oncology 2012.
    \106\ Comenzo et al. Leukemia 2012.
---------------------------------------------------------------------------

    With regard to the concern for generalizability of the study 
population in an outpatient setting, the applicant stated that many 
factors contribute to whether a patient is treated as an outpatient or 
as an inpatient. Per the applicant, patients with similar clinical 
status might be treated in the inpatient setting because of the 
availability of health care personnel, insurance status, and available 
outpatient resources for patient follow-up. The applicant stated that 
the ANDROMEDA study was performed in an outpatient setting but there 
were patients with cardiac organ involvement that might have been 
hospitalized for treatment of cardiac disease and may have also be 
receiving treatment for AL amyloidosis, either as initiation of 
treatment or a part of a subsequent treatment cycle. The applicant 
stated that although the number of inpatient hospitalized individuals 
receiving a treatment cycle with Dara-CyBorD is expected to be low, it 
is important to ensure health care equity and access to the only FDA 
approved drug for treatment of newly diagnosed AL amyloidosis, 
regardless of treatment setting.
    With regard to the small sample size and large confidence intervals 
in subgroup studies, the applicant stated that the variability in 
subgroup sizes could lead to wide confidence intervals, especially in 
the smaller subgroup sizes. The applicant also stated that there is 
strong numerical trend for improved outcomes with similar odds ratios 
in the Dara-CyborD arm across all subgroups.
    With regard to the concern that the poster presentation did not 
match the indication for which the applicant has applied for the new 
technology add-on payment, the applicant stated that the use of 
daratumumab monotherapy in cardiac stage IIIB is still under 
investigation and although related data might be included in supporting 
documents, this information should be considered investigational. The 
applicant stated that its request for the new technology add-on payment 
is limited to the FDA approved indication: treatment of adult patients 
with newly diagnosed AL amyloidosis with NYHA or Mayo cardiac stage 
IIIA or less in combination with CyBorD.
    With regard to our inquiry about the use of exploratory secondary 
endpoints in relevant clinical settings, the applicant stated that 
information about patient reported outcomes assessing the impact of 
treatment on quality of life provides early positive findings 
associated with the addition of DARZALEX FASPRO[supreg] to the CyBorD 
treatment combination but agreed that the information is preliminary 
and additional patient reported outcomes need to be obtained for AL 
amyloidosis patients at the time of diagnosis, during follow-up, and as 
the disease progresses. The applicant stated that the exploratory 
endpoints of iFLC <=20mg/L and dFLC <=10 mg/L also confirm the 
consistency of improved results of adding daratumumab to CyBorD. 
Finally, the applicant stated that besides the exploratory endpoints, 
the ANDROMEDA trial used the established primary endpoint of 
hematologic CR and the secondary endpoint of organ response which are 
defined in the International Society of Amyloidosis (ISA) guidelines 
and have been shown to be very good predictors for overall survival.
    We also received an additional comment stating that DARZALEX 
FASPRO[supreg] improves progression free survival and organ survival 
across staging and that its combination with CyBorD has become standard 
of care and frontline treatment for patients with AL amyloidosis. The 
commenter further stated that rapidly achieving normalization of 
circulating immunogloblin free light chain is critical to offer the 
best chances of organ response and survival as time is of the essence 
in this disease, and organ response cannot occur in the absence of a 
hematologic remission. The commenter stated that adequate reimbursement 
will allow healthcare providers to adequately serve this critically ill 
patient population in both inpatient and outpatient settings, and will 
prevent having to withhold or delay the best possible regimen in the 
face of a requirement for an inpatient stay.
    Response: We thank the commenters for their comments regarding the 
substantial clinical improvement criterion. Based on the additional 
information received, we agree that DARZALEX FASPRO[supreg] represents 
a substantial clinical improvement over existing technologies for the 
treatment of AL amyloidosis patients because it demonstrates improved 
clinical outcomes as compared to the standard of care CyBorD, including 
a higher rate of hemCR and longer major MOD-PFS.
    After consideration of the public comments we received and the 
information included in the applicant's new technology add-on payment 
application, we have determined that DARZALEX FASPRO[supreg] meets the 
criteria for approval for new technology add-on payment. Therefore, we 
are approving new technology add-on payments for this technology for FY 
2023. Cases involving the use of DARZALEX FASPRO[supreg] that are 
eligible for new technology add-on payments will be identified by ICD-
10-PCS code XW01318 (Introduction of daratumumab and hyaluronidase-fihj 
into subcutaneous tissue, percutaneous approach, new technology group 
8) in combination with ICD-10-CM code E85.81 (Light chain (AL) 
amyloidosis).
    In its application, the applicant estimated that the cost of 
DARZALEX FASPRO[supreg] is $7,937.55 per patient. Under Sec.  
412.88(a)(2), we limit new technology add-on payments to the lesser of 
65% of the average cost of the technology, or 65% of the costs in 
excess of the MS-DRG payment for the case. As a result, the maximum new 
technology add-on payment for a case involving the use of DARZALEX 
FASPRO[supreg] is $5,159.41 for FY 2023.
c. Hemolung Respiratory Assist System (Hemolung RAS)
    ALung Technologies, Inc. submitted an application for new 
technology add-on payments for the Hemolung Respiratory Assist System 
(Hemolung RAS) for FY 2023. The applicant stated that the Hemolung RAS 
is the first and only FDA authorized technology for the treatment of 
acute, hypercapnic respiratory failure using an extracorporeal circuit 
to remove CO2 directly from the blood. Per the applicant, 
patients experiencing acute, hypercapnic respiratory failure are unable 
to remove excess CO2 waste molecules from their blood via 
their lungs, resulting in accumulation of CO2 in their blood 
(hypercapnia), acid/base derangement (respiratory acidosis), and life-
threatening clinical sequelae.\107\ The applicant stated that the 
Hemolung RAS does not treat a specific disease but removes 
CO2 directly from the blood to treat a variety of underlying 
respiratory disease states, including, but not limited to, cystic 
fibrosis (CF), chronic obstructive pulmonary disease (COPD), and 
asthma, where CO2 retention (hypercapnia) is the primary 
cause of continued clinical deterioration.
---------------------------------------------------------------------------

    \107\ Nin, N. et al. Severe hypercapnia and outcome of 
mechanically ventilated patients with moderate or severe acute 
respiratory distress syndrome. Intensive Care Med 43, 200-208 
(2017).
---------------------------------------------------------------------------

    Per the applicant, the Hemolung RAS provides low-flow, veno-venous 
extracorporeal carbon dioxide removal (ECCO2R) using a 15.5 
French dual lumen catheter inserted percutaneously in the femoral or 
jugular vein, providing

[[Page 48938]]

partial ventilatory lung support independent of the lungs as an 
alternative or supplement to invasive mechanical ventilation. The 
applicant stated that the Hemolung RAS removes up to 50% of basal 
metabolic carbon dioxide (CO2) production at circuit blood 
flows of 350-550 mL/min. According to the applicant, the Hemolung RAS 
is not intended to provide therapeutic levels of oxygenation. The 
applicant stated that during the Hemolung RAS therapy, blood passing 
through the circuit is oxygenated; however, at low extracorporeal blood 
flows, the limited oxygen-carrying capacity of blood precludes 
meaningful oxygenation of mixed venous blood. The applicant explained 
that extracorporeal therapy with the Hemolung RAS requires continuous 
systemic anticoagulation with unfractionated heparin or a standard of 
care alternative to prevent clotting of blood in the circuit.
    With respect to the newness criterion, the applicant stated that 
the Hemolung RAS received Breakthrough Device Designation from FDA in 
2015 specific to COPD patients experiencing acute, refractory, 
hypercapnic respiratory failure. The applicant stated it is not 
applying under the Breakthrough Device Alternative Pathway in the 
current application for new technology add-on payments, as the 
Breakthrough Device indication is different from its FDA De Novo 
indication. The applicant explained that the Hemolung RAS was 
classified as a Class III device and received a Breakthrough Device 
designation for COPD only. According to the applicant, on April 22, 
2020, the Hemolung RAS received an Emergency Use Authorization (EUA) to 
treat lung failure due to COVID-19 when used as an adjunct to 
noninvasive or invasive mechanical ventilation in reducing hypercapnia 
and hypercapnic acidosis due to COVID-19 and/or maintaining normalized 
levels of partial pressure of carbon dioxide (PCO2) and pH 
in patients suffering from acute, reversible respiratory failure due to 
COVID-19 for whom ventilation of CO2 cannot be adequately, 
safely, or tolerably achieved. The applicant further explained Hemolung 
RAS was later classified as a Class II device under the De Novo 
pathway. The applicant indicated its De Novo classification request 
(DEN210006) was granted on November 13, 2021, for the indication of 
respiratory support providing extracorporeal carbon dioxide 
(CO2) removal from the patient's blood for up to five days 
in adults with acute, reversible respiratory failure for whom 
ventilation of CO2 cannot be adequately or safely achieved 
using other available treatment options and continued clinical 
deterioration is expected. According to the applicant, the De Novo 
classified Hemolung RAS became available on the market on November 15, 
2021, the first business day following the FDA authorization. The 
applicant indicated that it is seeking new technology add-on payments 
for FY 2023 for the FDA De Novo indication for the treatment of 
hypercapnic respiratory failure due to all causes in adults, which 
would include the EUA indication for the use of the Hemolung RAS in 
patients with respiratory failure caused by COVID-19. The applicant 
stated that the following ICD-10-PCS code may be used to uniquely 
describe procedures involving the use of the Hemolung RAS: 5A0920Z 
(Assistance with respiratory filtration, continuous, 
ECCO2R).
    As previously discussed, if a technology meets all three of the 
substantial similarity criteria under the newness criterion, it would 
be considered substantially similar to an existing technology and would 
not be considered ``new'' for the purposes of new technology add-on 
payments. According to the applicant, patients experiencing acute, 
hypercapnic respiratory failure are treated pharmacologically and with 
non-invasive ventilatory support as a first line treatment. The 
applicant stated that if these treatments are insufficient to support 
the failing lungs, escalation of ventilatory support via intubation and 
invasive mechanical ventilation (IMV) are the only available treatment 
options. According to the applicant, patients who are intubated and 
invasively mechanically ventilated are at significant risk for 
increased morbidity and mortality. The applicant stated that no 
additional treatments are available if IMV is insufficient to correct 
refractory hypercapnia and respiratory acidosis, which ultimately lead 
to cardiopulmonary collapse and death. Furthermore, the applicant 
stated that no treatment options are available for patients who have a 
Do Not Intubate (DNI) order.
    With respect to the first criterion, whether a product uses the 
same or similar mechanism of action to achieve a therapeutic outcome, 
the applicant stated that the Hemolung RAS has a different mechanism of 
action compared to existing technologies. According to the applicant, 
IMV, the only existing technology used to treat acute, refractory, 
hypercapnic respiratory failure, utilizes positive airway pressure to 
deliver oxygen and remove CO2 from the lungs, whereas the 
Hemolung RAS removes CO2 directly from the blood, 
independent of the lungs and allowing the lungs to rest and recover. 
Thus, the applicant asserted that the Hemolung RAS uses a different 
mechanism of action when compared to the existing therapeutic option 
(that is, IMV). The applicant also stated that extracorporeal membrane 
oxygenation (ECMO) is a rescue therapy for patients experiencing 
refractory hypoxemic respiratory failure, where insufficient 
oxygenation is the source of the respiratory failure. However, the 
applicant stated that ECMO is not suitable, nor FDA-approved, as a 
treatment for acute, hypercapnic respiratory failure. Therefore, the 
applicant asserted that ECMO and the Hemolung RAS are fundamentally 
different technologies used to treat different patient populations.
    With respect to the second criterion, whether a product is assigned 
to the same or a different MS-DRG when compared to an existing 
technology, the applicant stated that the Hemolung RAS is assigned to 
the same MS-DRGs when compared to an existing technology. Per the 
applicant, the Hemolung RAS is an escalation therapy to be used when 
current therapies are unable to support a patient's failing lungs and 
continued clinical deterioration is expected. The applicant noted that 
MS-DRGs 207 and 208 (Respiratory System Diagnosis with Ventilator 
Support >96 Hours and Respiratory System Diagnosis with Ventilator 
Support <=96 Hours, respectively) relate to the treatment of 
respiratory failure using mechanical ventilation, so the Hemolung RAS 
may be assigned to the same MS-DRGs if mechanical ventilation is unable 
to safely or adequately remove CO2 from the blood.
    With respect to the third criterion, whether the new use of 
technology involves the treatment of the same or similar type of 
disease and the same or similar patient population when compared to an 
existing technology, the applicant stated that the Hemolung RAS and IMV 
are both used to treat patients experiencing acute, refractory, 
hypercapnic respiratory failure due to numerous disease etiologies and 
pathophysiologies. However, the applicant noted that the Hemolung RAS 
is indicated for use as an escalation therapy when IMV is unable to 
safely or adequately remove CO2 from the blood and continued 
clinical deterioration is expected.
    In summary, the applicant maintained that the Hemolung RAS is not 
substantially similar to currently available therapies and/or 
technologies because it uses a new mechanism of

[[Page 48939]]

action and therefore the technology meets the ``newness'' criterion.
    We stated in the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28236 
through 28237) that, as noted previously, the applicant received an FDA 
De Novo classification for the device on November 13, 2021 (with the 
product becoming commercially available on November 15, 2021), for the 
FDA De Novo indication that is the subject of this application, for the 
treatment of hypercapnic respiratory failure due to all causes in 
adults. This De Novo indication would include use of the product for 
the indication for which the applicant initially received an EUA from 
FDA, for the use of the Hemolung RAS in patients with respiratory 
failure caused by COVID-19. In the FY 2005 IPPS/LTCH PPS final rule, we 
stated that the intent of section 1886(d)(5)(K) of the Act and 
regulations under Sec.  412.87(b)(2) is to pay for new medical services 
and technologies for the first 2 to 3 years that a product comes on the 
market, during the period when the costs of the new technology are not 
yet fully reflected in the MS-DRG weights (69 FR 49002). While our 
policy is, generally, to begin the newness period on the date of FDA 
approval or clearance or, if later, the date of availability of the 
product on the U.S. market as discussed in prior rulemaking (77 FR 
53348), we have noted that data reflecting the costs of products that 
have received an EUA could become available as soon as the date of the 
EUA issuance and prior to receiving FDA approval or clearance (86 FR 
45159). We refer readers to section II.F.7. of the FY 2022 IPPS/LTCH 
PPS final rule (86 FR 45159 through 45160), for discussion of our 
solicitation of comments regarding the newness period for products 
available through an EUA for COVID-19. As discussed in section II.F.4. 
of the preamble of this final rule, we are continuing to consider the 
comments we received regarding the newness period for products 
available through an EUA for COVID-19 as discussed in the FY 2022 IPPS/
LTCH PPS final rule (86 FR 45159), and we welcomed additional comments 
in the proposed rule.
    Therefore, we stated that because data reflecting the costs of the 
Hemolung RAS used for the indication of COVID-19 could be available 
beginning with the EUA on April 22, 2020, we questioned whether the 
newness period for the use of the Hemolung RAS for patients with COVID-
19 should begin with the date of EUA issuance, April 22, 2020, while 
the newness period for the use of Hemolung RAS for patients with other 
causes of hypercapnic respiratory failure unrelated to COVID-19 should 
begin on the date of commercial availability of the De Novo classified 
device, November 15, 2021. As discussed in the FY 2022 IPPS/LTCH PPS 
final rule (86 FR 45159 through 45160), under the current regulations 
at 42 CFR 412.87(e)(2) and consistent with our longstanding policy of 
not considering eligibility for new technology add-on payments prior to 
a product receiving FDA approval or clearance, a product available only 
through an EUA would not be eligible for new technology add-on 
payments. Therefore, cases involving pediatric patients, or cases 
involving the use of the Hemolung RAS for greater than 5 days, would 
not be eligible for new technology add-on payment if the Hemolung RAS 
is approved for new technology add-on payment for the patient 
population indicated in its FDA De Novo marketing authorization.
    We invited public comments on whether the newness period for the 
Hemolung RAS when used for patients with COVID-19 should begin on April 
22, 2020 (the date of its EUA), when the product became available on 
the market for this indication. We also invited public comments on 
whether the Hemolung RAS is substantially similar to existing 
technologies and whether the Hemolung RAS meets the newness criterion.
    Comment: The applicant submitted a public comment regarding the 
newness date for the Hemolung RAS. The applicant stated that the 
newness period for COVID-19 Hemolung RAS cases should begin on November 
15, 2021 (the date of commercial availability of the De Novo classified 
device), instead of April 22, 2020 (the date of the Hemolung RAS EUA). 
The applicant indicated that it provided the Hemolung RAS to hospitals 
free or at cost to swiftly respond to the global pandemic, and that it 
did not profit from EUA therapies. The applicant stated that 
additionally, during the EUA period, hospitals were not seeking payment 
for Hemolung RAS therapy. The applicant stated that, therefore, cost 
data collected during the EUA period and prior to FDA clearance do not 
accurately reflect the added cost of Hemolung RAS therapy.
    Response: We thank the applicant for its comment. We note that, as 
discussed in previous rulemaking, the intent of section 1886(d)(5)(K) 
of the Act and regulations under Sec.  412.87(b)(2) is to pay for new 
medical services and technologies for the first 2 to 3 years that a 
product comes on the market, during the period when the costs of the 
new technology are not yet fully reflected in the DRG weights. While 
the commenter stated that it provided the Hemolung RAS to hospitals 
free or at cost, and that hospitals were not seeking payment for the 
Hemolung RAS therapy during the EUA period, additional information 
regarding whether hospitals charged for use of the Hemolung RAS therapy 
between the date of its EUA and the date of commercial availability of 
the De Novo classified device, and how it impacts whether use of the 
technology may be reflected in the data, would be helpful in 
determining that data reflecting the cost of the product did not become 
available until the date of commercial availability of the De Novo 
classified device. However, we note that regardless of whether we 
consider the beginning of the newness period to commence for the use of 
the Hemolung RAS for patients with COVID-19 on April 22, 2020 (the date 
of its EUA) or November 15, 2021 (the date of commercial availability 
of the De Novo classified device), in both cases, the three-year 
anniversary date would occur after April 1, 2023, and, therefore, the 
technology would be considered new for this indication for FY 2023. As 
we discuss elsewhere in this rule, we also recognize that there may be 
unique considerations associated with determining the start of the 
newness period for a product available under an EUA prior to receiving 
FDA approval, and will continue to consider the comments received 
regarding the newness period for products available through an EUA for 
COVID-19 for future rulemaking. We consider the beginning of the 
newness period to commence for the use of the Hemolung RAS for patients 
with other causes of hypercapnic respiratory failure unrelated to 
COVID-19 on the date of commercial availability of the De Novo 
classified device, November 15, 2021. Accordingly, we consider the 
Hemolung RAS to be new for FY 2023 for use in patients with both COVID-
19 and hypercapnic respiratory failure unrelated to COVID-19, and 
therefore the product meets the newness criterion for all patient 
populations indicated in its FDA De Novo marketing authorization.
    Based on the information provided in the application for new 
technology add-on payments, and after consideration of the public 
comments we received, we believe the Hemolung RAS is not substantially 
similar to existing treatment options and meets the newness criterion.
    With respect to the cost criterion, the applicant presented the 
following analysis. The applicant searched the FY 2019 MedPAR Limited 
Data Set (LDS) for cases that received ventilator support to identify 
patients who may

[[Page 48940]]

have been eligible for the Hemolung RAS. The applicant reviewed 
multiple ICD-10-CM and ICD-10-PCS codes related to respiratory failure 
and hypercapnic disease and determined that two ICD-10-PCS codes were 
most applicable: 5A1955Z (Respiratory ventilation, greater than 96 
consecutive hours) and 5A1945Z (Respiratory ventilation, 24-96 
consecutive hours). We noted that, in the applicant's analysis, it 
listed ICD-10-PCS code 5A1955Z as 5A1935Z (Respiratory ventilation, 
greater than 96 consecutive hours), but we believed the applicant 
intended to reference the correct ICD-10-PCS code 5A1955Z (Respiratory 
ventilation, greater than 96 consecutive hours) to correctly map to MS-
DRG 207 (Respiratory System Diagnosis with Ventilator Support >96 
Hours).
    The applicant identified 68,317 cases mapping to MS-DRGs 207 
(Respiratory System Diagnosis with Ventilator Support >96 Hours) and 
208 (Respiratory System Diagnosis with Ventilator Support <= 96 Hours). 
MS-DRG 207 contained 24.6% of the cases and MS-DRG 208 contained the 
remaining 75.4% of cases.
    Next, the applicant removed 100% of the inhalation charges and 
charges associated with a 1-day length of stay (LOS) in the ICU. The 
applicant explained that it removed the 1 day of routine care plus ICU 
day charges based on an assumed LOS reduction associated with the use 
of the Hemolung RAS from relevant cases (as compared to cases without 
the Hemolung RAS) to estimate the potential decrease in costs as a 
result of the use of the Hemolung RAS.\108\ The applicant then 
standardized the charges and applied a 4-year inflation factor of 
1.281834 or 28.1834%, based on the inflation factor used in the FY 2022 
IPPS/LTCH PPS final rule and correction notice to calculate outlier 
threshold charges (86 FR 45542). The applicant then added charges for 
the new technology, which it calculated by dividing the cost of the 
Hemolung RAS by the national average CCR for inhalation therapy, which 
is 0.147 (86 FR 44966).
---------------------------------------------------------------------------

    \108\ Tiruvoipati, et al., ``Effects of Hypercapnia and 
Hypercapnic Acidosis on Hospital Mortality in Mechanically 
Ventilated Patients:'' Crit Care Med. Vol 456(7). e649-e656
---------------------------------------------------------------------------

    The applicant calculated a final inflated average case-weighted 
standardized charge per case of $178,436, which exceeded the average 
case-weighted threshold amount of $102,867. Because the final inflated 
average case-weighted standardized charge per case exceeded the average 
case-weighted threshold amount, the applicant maintained that the 
Hemolung RAS meets the cost criterion.
    After review of the cost analysis provided by the applicant, we 
questioned whether the analysis should have included patients who would 
also require a tracheostomy, which could result in cases mapping to the 
Pre-Major Diagnostic Category (Pre-MDC) MS-DRGs 003 or 004 if used with 
mechanical ventilation, and whether the inclusion of those additional 
MS-DRGs would impact the cost analysis. We sought comments on whether 
the Hemolung RAS meets the cost criterion.
    Comment: The applicant submitted a public comment and updated cost 
criterion analysis, which included a subset of cases in MS-DRG 003 and 
MS-DRG 004 in response to our concerns. The applicant stated that cases 
mapping to these MS-DRGs included non-extracorporeal membrane 
oxygenation (ECMO) cases with a tracheostomy, receiving mechanical 
ventilation, and with a primary diagnosis code for hypercapnia or 
chronic obstructive pulmonary disease (COPD). The applicant followed 
the same methodology as its original analysis and stated that even when 
including the subset of cases in MS-DRGs 003 and 004, the case-weighted 
standardized charges exceed the threshold amount, and the Hemolung RAS 
meets the cost criterion.
    Response: We appreciate the applicant providing an updated cost 
criterion analysis that includes a subset of patients who would also 
require a tracheostomy, which resulted in cases mapping to the Pre-
Major Diagnostic Category (Pre-MDC) MS-DRGs 003 or 004 if used with 
mechanical ventilation. Based on the information provided by the 
applicant, because the final inflated average case-weighted 
standardized charge per case exceeded the case-weighted threshold 
amount in all scenarios presented by the applicant, we agree with the 
applicant that the Hemolung RAS meets the cost criterion.
    With regard to the substantial clinical improvement criterion, the 
applicant asserted that the Hemolung RAS offers a treatment option for 
patients unresponsive to non-invasive mechanical ventilation (NIV), 
patients unresponsive to invasive mechanical ventilation (IMV), and 
patients ineligible for currently available treatments (that is, 
failure of NIV with DNI order). Further, the applicant asserted that 
the Hemolung RAS significantly improves clinical outcomes relative to 
available services or technologies.
    With regard to the claim that the Hemolung RAS offers a treatment 
option for patients unresponsive to NIV, the applicant noted that while 
acute respiratory failure can often be treated with NIV, which does not 
require intubation and is typically safe and well tolerated, 12-50% of 
patients are unresponsive to NIV as a result of several factors, 
including elevated respiratory rates, uncorrected respiratory acidosis, 
and reduced level of consciousness.109 110 111 Further, the 
applicant stated that if a patient fails NIV, the only currently 
indicated treatment is escalation to IMV; however, per the applicant, 
intubation and IMV following NIV failure is associated with a 200% 
increase in mortality compared to patients successfully treated with 
NIV; 27% vs 9% mortality rate, respectively.\112\
---------------------------------------------------------------------------

    \109\ Conti, V. et al. Predictors of outcome for patients with 
severe respiratory failure requiring noninvasive mechanical 
ventilation. Eur Rev Med Pharmacol Sci 19, 3855-3860 (2015).
    \110\ Bott, J. et al. Randomised controlled trial of nasal 
ventilation in acute ventilatory failure due to chronic obstructive 
airways disease. Lancet 341, 1555-1557 (1993).
    \111\ Phua, J., Kong, K., Lee, K.H., Shen, L. & Lim, T.K. 
Noninvasive ventilation in hypercapnic acute respiratory failure due 
to chronic obstructive pulmonary disease vs. other conditions: 
effectiveness and predictors of failure. Intensive Care Med 31, 533-
539 (2005).
    \112\ Chandra, D. et al. Outcomes of noninvasive ventilation for 
acute exacerbations of chronic obstructive pulmonary disease in the 
United States, 1998-2008. Am. J. Respir. Crit. Care Med. 185, 152-
159 (2012).
---------------------------------------------------------------------------

    The applicant asserted that the Hemolung RAS can be an effective 
tool for patients unresponsive to NIV by rapidly correcting respiratory 
acidosis (pH and arterial partial pressure of carbon dioxide 
(PaCO2)), thereby reducing respiratory drive and improving 
NIV efficacy. In support of this claim, the applicant submitted a 
consensus paper by Combes et al.\113\ In this consensus paper, 14 
clinical experts in critical care and respiratory support using 
ECCO2R convened to determine how ECCO2R therapy 
is applied, identify how patients are selected, and discuss how 
treatment decisions are made. Per the applicant, the results of the 
paper showed that there were two groups of patients where 
ECCO2R therapy was indicated--patients with acute 
respiratory distress syndrome (ARDS) or patients with COPD. The 
treatment goal for ECCO2R therapy in patients with ARDS is 
to provide ultra-protective lung ventilation via managing 
CO2 levels. The criteria for initiating ECCO2R 
therapy in patients with ARDS and on NIV is when there was no decrease 
in PaCO2 and no decrease in respiratory rate. In patients 
with acute

[[Page 48941]]

COPD exacerbation, treatment targets were patient comfort, pH between 
7.30-7.35, respiratory rate less than 20-25 breaths per minute, 
decrease of PaCO2 by 10-20%, weaning from NIV, decrease in 
bicarbonate levels (HCO3\-\), and maintaining hemodynamic 
stability. The clinical experts came to the consensus that 
ECCO2R therapy may be an effective support treatment for 
adults with ARDS or COPD exacerbation, but noted the need for further 
evidence from randomized clinical trials and/or high quality 
prospective studies to better guide decision-making.
---------------------------------------------------------------------------

    \113\ Combes, A. et al. ECCO2R therapy in the ICU: 
consensus of a European round table meeting. Critical Care 24, 
(2020).
---------------------------------------------------------------------------

    The applicant also submitted three peer-reviewed publications in 
support of this claim. First the applicant cited Bonin et al.,\114\ a 
case study of a 50-year-old male awaiting a bilateral lung transplant, 
admitted for COPD exacerbation caused by infection. The patient was 
initially treated with antibiotics and continuous NIV, which he 
tolerated for three days. After three days, the patient decompensated 
due to a spontaneous pneumothorax. The lung was emergently reinflated, 
but the patient's respiratory status continued to decline with a 
PaCO2 between 72-85 mmHg, pH of less than 7.3, and a 
respiratory rate of 30-40. The patient showed signs of exhaustion but 
did not qualify for intubation due to the recent pneumothorax. The 
patient consented to the Hemolung RAS therapy and within the first hour 
of treatment, the patient's respiratory rate improved to around 10 
breaths/minute. However, the patient was no longer able to tolerate the 
NIV minimum set breathing rate, so the minimum set breathing rate was 
turned off. The PaCO2 decreased to 55-60 mmHg for the 
duration of therapy (6 days). The patient was able to be successfully 
weaned from continuous NIV. The patient was also able to take oral 
nutrition and participate in interventions against pressure sores. 
After day 6, the patient was able to wean from the Hemolung RAS support 
and continue with intermittent NIV support.
---------------------------------------------------------------------------

    \114\ Bonin, F., Sommerwerck, U., Lund, L. & Teschler, H. 
Avoidance of intubation during acute exacerbation of chronic 
obstructive pulmonary disease for a lung transplant candidate using 
extracorporeal carbon dioxide removal with the Hemolung. The Journal 
of Thoracic and Cardiovascular Surgery 145, e43-e44 (2013).
---------------------------------------------------------------------------

    Second, the applicant cited a multi-national pilot study done by 
Burki et al.\115\ in India and Germany. There were 20 COPD patients 
with hypercapnic respiratory failure treated with ECCO2R therapy and 
placed into 1 of 3 groups. Group 1 had seven patients on NIV with a 
high likelihood of requiring IMV; Group 2 had two patients who could 
not be weaned from NIV; and Group 3 had 11 patients on IMV who failed 
weaning attempts. The authors found that the device was well-tolerated 
with complications and rates similar to those seen with central venous 
catheterization. The patients in Group 1 successfully avoided IMV as a 
result of ECCO2R therapy, although three patients died 
within 30 days of ECCO2R therapy due to underlying disease 
states. The patients in Group 2 were successfully weaned from 
continuous NIV after receiving ECCO2R therapy and were alive 
30 days after ECCO2R therapy, but remained on intermittent 
non-invasive, positive-pressure ventilation (NIPPV) support. Of the 
patients in Group 3, nine of the 11 patients had been on IMV for 
greater than 15 days prior to ECCO2R therapy. In Group 3, 
three patients were weaned from IMV, three patients had decreased IMV 
support, one patient expired from retroperitoneal bleed following 
catheterization, and one patient remained on the same level of 
ventilatory support despite receiving ECCO2R therapy. The 
authors concluded that the single catheter, low-flow ECCO2R 
system, provided clinically useful levels of CO2 removal in 
patients with COPD and could be a potentially valuable addition to the 
treatment of hypercapnic respiratory failure.
---------------------------------------------------------------------------

    \115\ Burki, N. et al. A novel extracorporeal CO2 
removal system: Results of a pilot study of hypercapnic respiratory 
failure in patients with COPD. Chest 143, 678-686 (2013).
---------------------------------------------------------------------------

    Third, the applicant cited a case series by Tiruvoipati et al. 
(2016),\116\ which retrospectively reviewed 15 patients among three 
Australian ICUs treated with the Hemolung RAS who had severe 
hypercapnic respiratory failure due to COPD, ARDS, asthma, or 
bronchiolitis obliterans syndrome (BOS), to show that ECCO2R 
was safe and effective in the removal of CO2. For five 
patients (four with COPD and one with BOS), the indication for the 
Hemolung RAS was to avoid intubation, whereas for the other 10 patients 
(five with acute lung injury/ARDS, three with asthma, and two with 
COPD), the indication was to institute lung-protective ventilation. The 
median age of the patients was 61.5 years; 12 patients were men, the 
median Acute Physiology and Chronic Health Evaluation III (APACHE III) 
score was 85, and the median duration of ECCO2R was 5 days. 
The primary outcome measures of the study were clearance of 
CO2 and change in pH with the use of ECCO2R. 
Secondary outcome measures included complications associated with 
Hemolung RAS use, survival to weaning from the Hemolung RAS, and 
survival to ICU and hospital discharge. There was no specified protocol 
for managing mechanical ventilation across the three centers; however, 
all centers used low-pressure ventilation for ARDS. For asthma, the 
mechanical ventilation was characterized by low tidal volume, low 
respiratory rate, and short inspiratory time associated with prolonged 
expiratory time to avoid dynamic hyperinflation. Four of the five 
patients treated for this indication, as well as all 10 patients who 
were treated to institute lung-protective ventilation, avoided 
intubation; successful lung-protective ventilation was achieved by a 
reduction in peak inspiratory pressure, tidal volume, and minute 
ventilation. The clearance of CO2 and return of 
PaCO2 to near-normal levels was achieved within 6 hours, and 
there was significant reduction in minute ventilation and peak airway 
pressures. Complications reported during the study included hemorrhage, 
thrombocytopenia, and compartment syndrome, none of which required 
cessation of the Hemolung RAS therapy. Overall, 93.3% of the patients 
survived to discontinuation of ECCO2R, 73.3% of patients 
survived to ICU discharge, and 66.66% of patients survived to hospital 
discharge. In conclusion, the study authors stated that the Hemolung 
RAS appears to be safe and effective for managing hypercapnic 
respiratory failure of various etiologies, but noted that more research 
is needed to clarify which patients may benefit most from this therapy.
---------------------------------------------------------------------------

    \116\ Tiruvoipati, R. et al. Early experience of a new 
extracorporeal carbon dioxide removal device for acute hypercapnic 
respiratory failure. Crit Care Resusc 18, 261-269 (2016).
---------------------------------------------------------------------------

    In addition to the previous peer-reviewed studies, the applicant 
also cited the Hemolung RAS Registry Program Analysis in support of its 
claim.\117\ Per the applicant, the voluntary Hemolung RAS Registry 
Program collected data from commercial use of the Hemolung RAS outside 
of the US as well as US EUA therapies. 176 patients from the Hemolung 
RAS Registry were analyzed to evaluate the benefits and safety of the 
Hemolung RAS therapy. The applicant stated that the Hemolung RAS 
Registry Program Analysis demonstrated that 86% (19/22) of patients 
failing NIV avoided

[[Page 48942]]

intubation due to the Hemolung RAS therapy.
---------------------------------------------------------------------------

    \117\ Alung, Inc., HL-CA-1600, Hemolung RAS Registry. A 
Retrospective Registry Involving Voluntary Reporting of De-
identified, Standard of Care Data Following the Commercial Use of 
the Hemolung Respiratory Assist System (RAS). ClinicalTrials.gov. 
Retrieved December 21, 2021, from Hemolung RAS Registry Program--
Full Text View--ClinicalTrials.gov.
---------------------------------------------------------------------------

    With respect to the applicant's assertion that the Hemolung RAS 
offers a treatment option for patients unresponsive to IMV and are 
retaining CO2, the applicant stated that the Hemolung RAS 
de-couples CO2 removal from the mechanical ventilator 
thereby allowing correction of hypercapnia and hypercapnic acidosis 
without a dangerous escalation of ventilator settings. The applicant 
provided 10 publications that document the use of the Hemolung RAS in 
patients unresponsive to IMV to significantly reduce ventilator 
settings to lung safe levels or to significantly correct and control 
hypercapnic acidosis, including Tiruvoipati et al. (2016) \118\ and 
Combes et al.,\119\ discussed previously.
---------------------------------------------------------------------------

    \118\ Tiruvoipati, R. et al. Early experience of a new 
extracorporeal carbon dioxide removal device for acute hypercapnic 
respiratory failure. Crit Care Resusc 18, 261-269 (2016).
    \119\ Combes, A. et al. ECCO2R therapy in the ICU: 
consensus of a European round table meeting. Critical Care 24, 
(2020).
---------------------------------------------------------------------------

    In the first case study, a 44-year-old male with acute asthma 
exacerbation went into respiratory arrest and was intubated in the 
emergency department (ED).\120\ The patient was found to have a left 
tension pneumothorax, which was decompressed, and then developed a 
second tension pneumothorax on the right side, which was also 
decompressed. The patient was transferred to the ICU for further 
management. The patient continued to deteriorate over the subsequent 48 
hours due to subcutaneous emphysema and ongoing air leaks, and after 72 
hours had uncontrollable hypercapnia (PaCO2 73, pH 7.22) 
despite optimal medical management with corticosteroids, nebulized and 
intravenous bronchodilators, magnesium, ketamine, and muscle relaxants. 
ECCO2R was indicated for hypercapnia and to facilitate de-
escalation of IMV. After initiating ECCO2R, it was possible 
to decrease the support on the IMV while maintaining satisfactory gas 
exchange and allowing the withdrawal of muscle relaxants. Within 1 hour 
of initiation of ECCO2R, the pH improved from 7.22 to 7.28, 
and the PaCO2 went from 68.1 to 60.6. The patient remained 
on ECCO2R for a total of 7 days mainly due to ongoing air 
leaks from three chest drains and a bleeding complication that was 
managed with transfusion. After discontinuing ECCO2R 
therapy, the patient received a tracheostomy to assist in weaning from 
IMV. The patient was successfully weaned from IMV after 23 days in the 
ICU and was ultimately discharged home. The authors discussed that 
while this patient could have been treated with ECMO, the use of ECMO 
is limited to specialized centers and requires a multidisciplinary 
approach for a successful outcome.
---------------------------------------------------------------------------

    \120\ Tiruvoipati R., et al. Low-flow veno-venous extracorporeal 
carbon dioxide removal in the management of severe status 
asthmatics: a case report. Clin Respir J. 2014;10(5):653-656.
---------------------------------------------------------------------------

    In the second case study, the Hemolung RAS system was used to treat 
hypercapnia in a 58-year-old male patient with an out-of-hospital 
cardiac arrest where mechanical ventilation failed to achieve 
normocapnia.\121\ The patient was intubated in the ED and treated with 
nebulized bronchodilators, corticosteroids, and therapeutic 
hypothermia. Initially, the PaCO2 was 82 mmHg (baseline 50 
mmHg) with a pH of 7.20, but as the next few hours progressed, the 
patient became more difficult to ventilate and the PaCO2 
increased to 94 mmHg. ECCO2R therapy was indicated to 
prevent lung injury and secondary brain injury. After initiating the 
Hemolung RAS, the minute ventilation and the respiratory rate could be 
decreased and the team was able to optimize the inspiratory and 
expiratory time ration to minimize the risk of barotrauma. The patient 
was on the Hemolung RAS therapy for 3 days and was able to de-escalate 
the ventilator settings, but still required mechanical ventilation. 
After cessation of the Hemolung RAS therapy, the patient started to 
show signs of significant hypoxic brain injury. Despite maximal medical 
treatment, the neurological prognosis was considered to be very poor, 
and all life-sustaining therapies were withdrawn. The authors stated 
that ECCO2R therapy is safe to use in a metropolitan 
hospital where the staff have a limited period of education, and that 
the extracorporeal therapy was delivered without complications. The 
authors also stated that ECMO is not an option in every health care 
center since it requires a specialized team including cardiac surgeons 
and perfusionists and is costly. The authors stated that 
ECCO2R is less invasive and able to provide partial 
respiratory support. Thus, the authors concluded that ECCO2R 
may have a role in patients with severe respiratory failure when IMV 
alone is inadequate and in centers that are not capable of initiating 
ECMO in the management of severe hypercapnic respiratory failure.
---------------------------------------------------------------------------

    \121\ Tiruvoipati R., et al. Management of severe hypercapnia 
post cardiac arrest with extracorporeal carbon dioxide removal. 
Anaesth Intensive Care. 2014;42(2):248-252.
---------------------------------------------------------------------------

    Next, the applicant cited a United Kingdom case study about a 48-
year-old male presenting to the ED with 7 days of cough, fever, and 
shortness of breath.\122\ He tested positive for COVID-19 via 
respiratory viral swab and had a chest x-ray demonstrating bilateral 
infiltrates. He initially required supplemental oxygen via facemask and 
oral doxycycline to treat possible bacterial co-infection. He continued 
to deteriorate, was trialed on NIV and failed, and was then 
transitioned to IMV on day four of the hospitalization and transferred 
to the ICU for further management. The patient continued to deteriorate 
and within a week and was found to be in ARDS due to COVID-19 
pneumonitis. The patient was treated with several strategies for lung 
recruitment, and was referred to ECMO but was declined on the basis of 
futility. The treatment team believed that continuing to treat the 
patient with high airway pressure was contributing to the progression 
of the ARDS, so the Hemolung RAS was initiated as a rescue therapy. 
After initiation, the PaCO2 and pH improved, which allowed 
the treatment team to reduce the tidal volume and respiratory rate. The 
patient spent 6 days on the Hemolung RAS without bleeding events or 
vasopressors and could continue to receive prone position ventilation 
without complication. The patient was successfully weaned from the 
Hemolung RAS and then completed a slow respiratory wean followed by a 
percutaneous tracheostomy. The patient was ultimately discharged from 
the ICU to home with mobility and cognition intact. The authors 
concluded that ECCO2R can be used as a rescue therapy for 
patients with hypercapnic respiratory failure resulting from ARDS in 
COVID-19 pneumonitis and to facilitate lung protective ventilation in 
patients on IMV. According to the authors, refractory hypercapnia is an 
acceptable indication for ECMO in ARDS and that ECCO2R can 
be considered as rescue therapy if ECMO is deemed inappropriate or 
cannot be delivered due to resource constraints. Per the authors, 
potential advantages of using ECCO2R over ECMO include lack 
of requirement for transfer to an ECMO center, smaller catheter size, 
and lower blood flow rate which may reduce the likelihood of 
complications.
---------------------------------------------------------------------------

    \122\ Tully R.P., et al. The successful use of extracorporeal 
carbon dioxide removal as a rescue therapy in a patient with severe 
COVID-19 pneumonitis. Anaesthesia Reports 2020; 8:113-115.
---------------------------------------------------------------------------

    The applicant also cited a case study of an 18-year-old male with 
solitary mediastinal metastasis and ARDS, in which the Hemolung RAS was 
used to facilitate de-escalation of mechanical

[[Page 48943]]

ventilation.\123\ Post-treatment with chemotherapy, a residual 
mediastinal mass was found with extension to the left lung hilum. The 
patient underwent lung resection and was extubated postoperatively 
without issue. The patient became febrile and developed a progressively 
extensive right lung infiltrate. On postoperative day five, the patient 
developed severe hypercapnia, hypoxemia, and hypotension, necessitating 
re-intubation and invasive mechanical ventilation. The Hemolung RAS was 
initiated to provide ECCO2R. Arterial PCO2 
decreased from 73 to 53 mmHg within 4 hours (with a concomitant pH 
increase from 7.28 to 7.44), permitting tidal volume reduction to 3.5 
mL/kg, and plateau airway pressure to 25 cm H2O, with simultaneous 
hemodynamic improvement. ECCO2R was titrated to maintain an 
arterial PCO2 between 45 and 50 mmHg, and the patient was 
weaned and decannulated after 71 hours of support. The patient was 
removed from mechanical ventilation within 24 hours and then 
transferred to an intermediate care unit. No ECCO2R-related 
complications were observed. The authors stated the Hemolung RAS has a 
conceptual advantage over ECMO as the Hemolung RAS uses one small dual-
lumen venous catheter, without additional arterial access and its 
attendant risks. The authors concluded that in appropriately selected 
patients, a minimally invasive ECCO2R approach may be 
useful.
---------------------------------------------------------------------------

    \123\ Akkanti B., et al. Low-flow extracorporeal carbon dioxide 
removal using the Hemolung Respiratory Dialysis System[supreg] to 
facilitate lung-protective mechanical ventilation in acute 
respiratory distress syndrome. J Extra Corpor Technol. 
2017;49(2):112-114.
---------------------------------------------------------------------------

    Next, the applicant cited a case study by Saavedra-Romero et 
al.,\124\ which describes the use of ECCO2R immediately 
administered with lung-protective mechanical ventilation on a patient 
with COVID-19 ARDS in her mid-60s. The authors stated that, upon 
arrival to the ICU, on inpatient day 5, the patient's oxygen saturation 
by pulse oximeter (SpO2) was 77%, blood pressure (BP) 90/40 
on norepinephrine at 10[thinsp]mcg/min, and the patient's initial 
arterial blood gas (ABG) results were pH = 7.14, PaCO2 = 90 
mmHg, PaO2 = 52 mmHg, and HCO3 = 30 mEq/L. The 
patient had significant whole-body subcutaneous crepitus, and the chest 
x-ray (CXR) showed an inflated right lung, subcutaneous emphysema, and 
an appropriately positioned endotracheal tube (ETT). The patient became 
increasingly tachycardic and tachypneic due to further worsening of 
hypercapnia and respiratory acidosis. ECCO2R was initiated 
using the Hemolung RAS and was administered for 17 days without 
complications. Ventilator settings were maintained at PEEP of 14, rate 
of 26, and minute ventilation at 7.8 liters during the first 24 hours. 
Respiratory rate and tidal volumes were subsequently titrated downward, 
maintaining adequate oxygen levels and permissive hypercapnia. The 
patient's chest tubes were removed 4 days after the Hemolung RAS 
decannulation, and the patient was weaned from mechanical ventilation 
28 days from ICU admission, and discharged 47 days after admission. The 
authors stated that this case report highlights the use of 
ECCO2R to facilitate effective treatment of a patient with 
severe hypercapnic respiratory failure secondary to COVID-19 ARDS and 
multiple risk factors for death. The authors stated that treatment with 
ECCO2R allowed a lung-protective ventilator management 
strategy with ultralow tidal volumes, minimizing the risk of 
ventilator-induced lung injury, attenuating severe hypercapnia and 
acidosis, and limiting the expansion of an existing pneumothorax. The 
authors concluded that ECCO2R facilitates early lung-
protective ventilation and control of refractory hypercapnia and can be 
safely utilized to increase the likelihood of survival among patients 
with severe COVID-19 ARDS.
---------------------------------------------------------------------------

    \124\ Saavedra-Romero R., et al. Treatment of Severe Hypercapnic 
Respiratory Failure Caused by SARS-CoV-2 Lung Injury with 
ECCO2R Using the Hemolung Respiratory Assist System. Case 
Reports in Critical Care 2021; 1-5.
---------------------------------------------------------------------------

    Finally, the applicant cited a case study by Bermudez et al.,\125\ 
in which a 33-year-old male with cystic fibrosis (CF), post double lung 
transplantation who developed severe hypercarbic respiratory failure 
due to adenovirus pneumonia requiring hospitalization, tracheostomy, 
and prolonged IMV for greater than 30 days. The patient was transferred 
to a tertiary care center and was treated with the Hemolung RAS because 
of persistent hypoxemia and hypercarbia. The patient was not a 
candidate for ECMO because of frail clinical condition, volume 
overload, and need for a redo lung transplantation. After 4 days of the 
Hemolung RAS support, the patient was weaned from vasopressors, and 
after 9 days, the patient was accepted as a candidate for redo lung 
transplantation because of considerable clinical improvement.
---------------------------------------------------------------------------

    \125\ Bermudez, et al. ``Prolonged Use of the Hemolung 
Respiratory Assist System as a Bridge to Redo Lung Transplantation'' 
Annals of Thorac Surg. 2015 Vol 100 (6). P. 2330-2333.
---------------------------------------------------------------------------

    Lastly, the applicant provided a retrospective, multicenter study 
of 31 patients placed on the Hemolung RAS at 8 sites across the 
U.S.\126\ The cohort was comprised of patients with COVID-19 who were 
mechanically ventilated with severe hypercapnia and respiratory 
acidosis and treated with low-flow extracorporeal CO2 
removal treated between March 4 and September 30, 2020. Two patients 
underwent cannulation but were never started on therapy due to a 
vascular access failure in one patient and immediate circuit clotting 
in the other. For the 29 patients who received the Hemolung RAS 
treatment, analysis of covariance revealed a significant improvement 
trend in both pH and PaCO2 (p < 0.0001). Comparison of time 
intervals yielded a statistically significant improvement in pH (7.24 
 0.12 to 7.35  0.07; p < 0.0001) and decrease 
in PCO2 (79  23 to 58  14; p < 
0.0001) from baseline to 24 hours after start of therapy. There were 
numerical, but not significant, decreases from baseline to 24 hours in 
respiratory rate (26.6  5.4 to 23.4  4.9), 
tidal volume (407  100 to 386  75[thinsp]mL), 
and minute ventilation (10.2  3.2 to 8.7  
2.2[thinsp]L/min). The authors indicated that this is the first 
reported use of ECCO2R in the U.S. for this patient 
population. The authors reported that limitations of the study are its 
small size and single-cohort retrospective nature. The applicant stated 
that the study results demonstrated the efficacy of ECCO2R 
using the Hemolung RAS to improve respiratory acidosis in patients with 
severe hypercapnic respiratory failure due to COVID-19.
---------------------------------------------------------------------------

    \126\ Akkanti B., et al. Physiologic Improvement in Respiratory 
Acidosis Using Extracorporeal CO2 Removal With Hemolung 
Respiratory Assist System in the Management of Severe Respiratory 
Failure From Coronavirus Disease 2019. Critical Care Explorations. 
2021;3:e0372.
---------------------------------------------------------------------------

    In addition to the case reports and retrospective study, the 
applicant also cited to the Hemolung RAS Registry Program Analysis, 
discussed previously, in support of its claim.\127\ The applicant 
stated that the Hemolung RAS Registry Program Analysis demonstrated 
clinically and statistically significant correction of pH and 
PaCO2 within the first day of the Hemolung RAS therapy 
(p<0.05).\128\ Additionally, the applicant noted that the statistical 
analysis showed this correction in pH and PaCO2

[[Page 48944]]

was independent of the patient's primary diagnosis.
---------------------------------------------------------------------------

    \127\ Alung, Inc., HL-CA-1600, Hemolung RAS Registry. A 
Retrospective Registry Involving Voluntary Reporting of De-
identified, Standard of Care Data Following the Commercial Use of 
the Hemolung Respiratory Assist System (RAS). ClinicalTrials.gov. 
Retrieved December 21, 2021, from Hemolung RAS Registry Program--
Full Text View--ClinicalTrials.gov.
    \128\ Ibid. ClinicalTrials.gov. Retrieved December 21, 2021, 
from Hemolung RAS Registry Program--Full Text View--
ClinicalTrials.gov.
---------------------------------------------------------------------------

    With respect to the applicant's assertion that the Hemolung RAS 
offers a treatment option for patients ineligible for currently 
available treatments (for example, patients with a DNI order), the 
applicant reiterated that intubation with IMV is the only currently 
available treatment option for patients failing NIV; however, the 
applicant indicated that these patients have no other therapeutic 
options if they were to fail NIV because of their preference to not be 
intubated. According to the applicant, the CO2 removal by 
the Hemolung RAS would rapidly correct the pH and PaCO2 
which would reduce the respiratory drive and improve NIV efficacy and 
prevent continued clinical deterioration.129 130
---------------------------------------------------------------------------

    \129\ Burki, N. et al. A novel extracorporeal CO2 
removal system: Results of a pilot study of hypercapnic respiratory 
failure in patients with COPD. Chest 143, 678-686 (2013).
    \130\ Tiruvoipati, R. et al. Early experience of a new 
extracorporeal carbon dioxide removal device for acute hypercapnic 
respiratory failure. Crit Care Resusc 18, 261-269 (2016).
---------------------------------------------------------------------------

    The applicant submitted three peer-reviewed case reports that have 
documented the use of the Hemolung RAS in patients failing NIV with a 
DNI order. In the first case study done in Germany,\131\ a 72-year-old 
female with a past medical history of severe COPD (GOLD 4, nocturnal 
home ventilation therapy) with a DNI order presented to an ED in a 
hypercapnic coma. The patient had a Glasgow Coma Score of 3, pH of 
6.97, and PaCO2 greater than 150 mmHg. The patient was 
hemodynamically stable on NIV with a respiratory rate of 28, oxygen 
saturation of 88% on supplemental oxygen with an inspired fraction 
(FiO2) of 30%. After 30 minutes of NIV treatment, the 
patient's PaCO2 improved, but the patient was nearly 
unconscious and was transferred to the ICU. Because of the high 
predictive mortality for patients with severe COPD who fail NIV and 
require intubation and invasive mechanical ventilation, combined with 
the patient's DNI order, the Hemolung RAS was initiated to supplement 
treatment. Within the first hour of treatment with both NIV and 
Hemolung RAS, the PaCO2 levels continued to decrease from 
109 mmHg to 89 mmHg and the patient's level of consciousness improved 
after about 25 minutes. Ultimately, the patient was able to start oral 
nutrition, communicate, and start mobilizing early because of her 
improved mental state within four hours of starting the Hemolung RAS 
and was discharged to rehabilitation.
---------------------------------------------------------------------------

    \131\ Engel, M., Albrecht, H. & Volz, S. Use of Extracorporeal 
CO2 Removal to Avoid Invasive Mechanical Ventilation in 
Hypercapnic Coma and Failure of Noninvasive Ventilation. J Pulm 
Respir Med 6, 1-3 (2016).
---------------------------------------------------------------------------

    The second case study by Mani et al. described two patients with 
severe COPD admitted to the ICU with an acute COPD exacerbation 
requiring NIV, but failed NIV treatments.\132\ A 69-year-old female in 
India was admitted with acute COPD exacerbation, waning consciousness 
and a pH of 7.20 and PaCO2 of 101 mmHg. After starting NIV 
for 2 hours, the PaCO2 had risen to 105 mmHg and pH had 
dropped to 7.193. After 1 hour of the Hemolung RAS treatment and NIV, 
the PaCO2 declined to 93 mmHg with a pH 7.25. After 6 hours 
of treatment with the Hemolung RAS and NIV, the patient was awake with 
a PaCO2 of 68 mmHg and a pH of 7.35. Ultimately, she was 
discharged to home on home oxygen and nocturnal NIV. There was also a 
report of a 78-year-old male with COPD and other comorbidities who had 
a DNI order in Germany. He was admitted with an acute COPD exacerbation 
and treated with NIV after his initial arterial blood gas (ABG) showed 
PaCO2 92 mmHg and pH of 7.24. After treatment with both the 
Hemolung RAS and NIV for 1 hour, the patient's PaCO2 dropped 
to 68 mmHg and pH 7.33. Ultimately, the patient was discharged to home 
on nocturnal NIV. Both patients were both diagnosed with 
thrombocytopenia as a known complication of extracorporeal therapy, but 
neither required transfusion.
---------------------------------------------------------------------------

    \132\ Mani, R.K., Schmidt, W., Lund, L.W. & Herth, F.J.F. 
Respiratory dialysis for avoidance of intubation in acute 
exacerbation of COPD. ASAIO J 59, 675-678 (2013).
---------------------------------------------------------------------------

    The applicant submitted a third case study in which Cole et al. 
describe a 62-year-old female with past medical history of COPD (GOLD 
class 3) and 2 recent hospitalizations for COPD exacerbations in the 
past 60 days.\133\ The patient had hypercapnic respiratory failure for 
which she did not want to be intubated, so she was started on NIV. She 
initially improved, but by day four of NIV treatment, she deteriorated, 
as evidenced by tachypnea and fatigue due to increased work of 
breathing. She was started on the Hemolung RAS and within two hours 
therapy with the Hemolung RAS alone (patient requested to stop NIV with 
the initiation of the Hemolung RAS), the patient's respiratory rate 
improved. Within 6 hours, the patient was able to converse and fully 
engage with her treatment. Ultimately the patient was discharged to 
home at her baseline activity level and did not require home oxygen 
therapy, and was not readmitted to hospital within 30 days of 
discharge.
---------------------------------------------------------------------------

    \133\ Cole, S. et al. Extracorporeal carbon dioxide removal as 
an alternative to endotracheal intubation for noninvasive 
ventilation failure in acute exacerbation of COPD. J Int Care Soc 
15, 344-346 (2014).
---------------------------------------------------------------------------

    Furthermore, the applicant claimed that the Hemolung RAS 
significantly improves clinical outcomes relative to services or 
technologies previously available by mitigating the harmful clinical 
sequelae from hypercapnic acidosis and facilitates de-escalation of 
high pressure and high volume ventilatory support or prevent 
intubation, both of which are known predictors for poor clinical 
outcomes. Thus, per the applicant, the correction of hypercapnia and 
hypercapnic acidosis (that is, pH and PaCO2) are appropriate 
surrogate markers for improved clinical outcomes in critically ill, 
mechanically ventilated patients. Per the applicant, the use of 
correction of hypercapnia and hypercapnic acidosis as surrogate markers 
for improved clinical outcomes was accepted by FDA as evidence of the 
clinical benefit of the Hemolung RAS as part of FDA's clearance of its 
De Novo request.
    The applicant asserted that the pH and PaCO2 correction 
due to the Hemolung RAS therapy provide the following six improved 
outcomes: (1) reduced mortality in intubated and IMV patients; (2) 
reduced length of stay in IMV patients; (3) de-escalation of mechanical 
ventilation settings (decreased rate of subsequent diagnostic or 
therapeutic interventions); (4) avoidance of intubation following NIV 
failure; (5) reduced mortality in NIV patients; and (6) improvement in 
activities of daily living/quality of life.
    In support of its assertion that the Hemolung RAS reduces mortality 
in intubated and IMV patients, the applicant cited two background 
studies.134 135 In the study by Nin et al., the authors 
completed a secondary analysis of 3 prospective, non-interventional 
cohort studies in 1,899 patients with ARDS among 40 ICUs. The goal of 
the study was to determine the relationship between severe hypercapnia 
(PaO2 >=50 mmHg) in the first 48 hours following onset of 
ARDS and mortality. The applicant stated that the study results 
demonstrate that severe hypercapnia in IMV patients was independently 
associated with increased risk of ICU mortality (odds

[[Page 48945]]

ratio: 1.93, 95% CI: 1.32-2.81, p = 0.001). The second study by 
Tiruvoipati et al. (2017), was a multicenter, binational, retrospective 
study that included 252,812 patients of 3 cohorts: normocapnia and 
normal pH (n = 110,104), compensated hypercapnia (n = 20,463), and 
hypercapnic acidosis (n = 122,245), that aimed to determine the 
relationship between these states and Acute Physiology and Chronic 
Health Evaluation (APACHE) III score and mortality. The study found 
that those with compensated hypercapnia and hypercapnic acidosis had 
higher APACHE III scores (49.2 vs. 53.2 vs. 68.6, p<0.01); mortality 
was highest in the hypercapnic acidosis patients (OR: 1.18, 95% CI: 
1.1-1.25) and lowest in the normocapnia and normal pH, p < 0.001. The 
applicant stated that the adjusted odds ratio for hospital mortality 
remained significantly higher in compensated hypercapnia and 
hypercapnic acidosis when compared with patients with normocapnia and 
normal pH irrespective of their P/F ratios.
---------------------------------------------------------------------------

    \134\ Nin, et al., ``Severe hypercapnia and outcome of 
mechanically ventilated patients with moderate or severe acute 
respiratory distress syndrome'' Intensive Care Med. 2017. p. 200--
208.
    \135\ Tiruvoipati, et al., ``Effects of Hypercapnia and 
Hypercapnic Acidosis on Hospital Mortality in Mechanically 
Ventilated Patients'' Crit Care Med. 2017. Vol 456(7). e649-e656.
---------------------------------------------------------------------------

    In support of the applicant's second assertion that use of the 
Hemolung RAS contributes to reduced LOS in IMV patients, the applicant 
cited Tiruvoipati et al. (2017), previously discussed.\136\ The median 
hospital LOS was 10.5 days in the normocapnia and normal pH group, 12 
days in the compensated hypercapnia group and 11 days in the 
hypercapnic acidosis group (p<0.001). The median ICU LOS was 1.9 days 
vs 2.2 days vs. 2.9 days in the normocapnia/normal pH group vs. 
compensated hypercapnia group vs. the hypercapnic acidosis group, 
respectively (p<0.001). The authors noted that that there was increased 
mortality in patients with hypercapnic acidosis and compensated 
hypercapnia with unclear cause.
---------------------------------------------------------------------------

    \136\ Ibid.
---------------------------------------------------------------------------

    In support of the applicant's assertion that use of the Hemolung 
RAS results in de-escalation of mechanical ventilation settings and 
decreased rate of subsequent diagnostic or therapeutic interventions, 
the applicant cited the Tully et al. case report,\137\ discussed 
previously, in which intubated patients had a 20% decrease in peak 
airways pressure and 30% decrease in driving pressure during the 
Hemolung RAS therapy. The applicant also cited the Tiruvoipati et al. 
(2016) study, discussed previously, in which 10 patients showed a 19% 
decrease in peak respiratory pressure and a 26% decrease in minute 
ventilation within 1 day of the Hemolung RAS therapy.\138\ The 
applicant also cited the Hemolung RAS Registry Program Analysis,\139\ 
which demonstrated statistically significant correction of pH and 
PaCO2 within the first day of the Hemolung RAS therapy 
(p<0.05).
---------------------------------------------------------------------------

    \137\ Tully R.P., et al. The successful use of extracorporeal 
carbon dioxide removal as a rescue therapy in a patient with severe 
COVID-19 pneumonitis. Anaesthesia Reports 2020; 8:113-115.
    \138\ Tiruvoipati, R., et al. Effects of Hypercapnia and 
Hypercapnic Acidosis on Hospital Mortality in Mechanically 
Ventilated Patients*: Critical Care Medicine. 2017;45(7):e649-e656.
    \139\ Alung, Inc., HL-CA-1600, Hemolung RAS Registry. A 
Retrospective Registry Involving Voluntary Reporting of De-
identified, Standard of Care Data Following the Commercial Use of 
the Hemolung Respiratory Assist System (RAS). ClinicalTrials.gov. 
Retrieved December 21, 2021, from Hemolung RAS Registry Program--
Full Text View--ClinicalTrials.gov.
---------------------------------------------------------------------------

    In support of its assertion that use of the Hemolung RAS 
contributes to avoidance of intubation following NIV failure, the 
applicant noted that respiratory acidosis is the primary determinant of 
NIV failure citing risk charts using a background study from 
Confalonieri et al.,\140\ in which data from 1,033 patients admitted to 
experienced hospital units was used to predict the likelihood of 
failure of noninvasive positive pressure ventilation (NPPV). The 
prediction charts were calculated using the APACHE II, GCS, pH, and 
respiratory rate data of 1,033 patients admitted with acute respiratory 
failure due to exacerbation of COPD treated with NIV. The applicant 
stated that the study results show that pH <7.25 (acidosis) after 2 
hours of NIV is the primary determinant of NIV failure [odds ratio: 
21.02; 95% CI: 10.07-43.87], and that additionally, a pH between 7.25 
and 7.29 (acidosis) after 2 hours of NIV is also significant predictor 
of NIV failure [odds ratio:2.92; 95% CI: 1.62-5.28]. The applicant 
stated that accuracy and generalizability of the model's ability to 
predict NIV failure was validated on an independent group of 145 COPD 
patients treated with NIV.
---------------------------------------------------------------------------

    \140\ Confalonieri M., et al. A chart of failure risk for 
noninvasive ventilation in patients with COPD exacerbation. European 
Respiratory Journal. 2005;25(2):348-355.
---------------------------------------------------------------------------

    In a prospective, single-arm feasibility study, Burki et al., 
previously discussed, stated that 100% (7/7) patients failing NIV and 
treated with the Hemolung RAS therapy avoided intubation and 100% (2/2) 
patients failing NIV with a DNI and treated with the Hemolung RAS 
therapy were successfully weaned from NIV.\141\ The applicant cited a 
retrospective review by Tiruvoipati et al. (2016), also previously 
discussed, in which 80% (4/5) of patients failing NIV and treated with 
Hemolung RAS therapy avoided intubation.\142\ Furthermore, the 
applicant cited an unpublished study of the Hemolung RAS Registry 
Program Analysis,\143\ in which 86% of patients (19 of the 22 patients 
in the analysis) who failed NIV and were treated with the Hemolung RAS 
therapy avoided intubation.
---------------------------------------------------------------------------

    \141\ Burki N., et al. A novel extracorporeal CO2 
removal system: Results of a pilot study of hypercapnic respiratory 
failure in patients with COPD. Chest. 2013;143(3):678-686.
    \142\ Tiruvoipati R., et al. Early experience of a new 
extracorporeal carbon dioxide removal device for acute hypercapnic 
respiratory failure. Crit Care Resusc. 2016;18(4):261-269.
    \143\ The applicant cited an unpublished study using data 
collected from physicians as part of the Hemolung Registry Program. 
We believe information regarding the Hemolung Registry Program is 
available here: Alung, Inc., HL-CA-1600, Hemolung RAS Registry. A 
Retrospective Registry Involving Voluntary Reporting of De-
identified, Standard of Care Data Following the Commercial Use of 
the Hemolung Respiratory Assist System (RAS). ClinicalTrials.gov. 
Retrieved December 21, 2021, from Hemolung RAS Registry Program--
Full Text View--ClinicalTrials.gov.
---------------------------------------------------------------------------

    In support of the assertion that the Hemolung RAS reduced mortality 
in NIV patients, the applicant submitted two retrospective studies as 
background studies, in addition to two case studies that utilized the 
technology. The first background study \144\ was a retrospective 
analysis of data from the Healthcare Cost and Utilization Project's 
Nationwide Inpatient Sample between 1998 and 2008 to assess the pattern 
and NIPPV use for acute exacerbations of COPD. The patient cohort was 
defined as people greater than 35-years-old admitted with a primary 
diagnosis of COPD or a primary diagnosis of respiratory failure with a 
secondary diagnosis of COPD. The study demonstrated a decline over time 
in overall in-hospital mortality for those patients treated with NIPPV 
without a subsequent need for IMV. Mortality was high and increased 
over time in patients who transitioned from NIPPV to IMV (27%) compared 
to those patients who did not transition (9%). Charges for 
hospitalization increased from 1998 to 2008, especially for patients 
who transitioned from NIPPV to IMV. LOS decreased in all patients 
except those who transitioned from NIPPV to IMV. The authors noted a 
few limitations that would have allowed for a more detailed examination 
of predictors of NIPPV failure and death, including the lack of 
information on the severity of the exacerbation, response to NIPPV 
treatment, end-of-life decision-making,

[[Page 48946]]

or location of the patient in the hospital (ICU vs. medical ward vs. 
ED, etc.).
---------------------------------------------------------------------------

    \144\ Chandra, et al, ``Outcomes of noninvasive ventilation for 
acute exacerbations of chronic obstructive pulmonary disease in the 
United States, 1998-2008'' Am J. Respir Crit Care Med. 2012. Vol 185 
(2). p. 152-159
---------------------------------------------------------------------------

    The applicant also cited a retrospective study by Sprooten et 
al.\145\ as background, that looked at patients admitted to the 
Respicare Unit located in Maastricht University Medical Center (MUMC) 
in the Netherlands between 2009 and 2011 who met the criteria of 
admitted for exacerbation of COPD requiring NIV therapy and a 
definitive COPD diagnosis. In-hospital mortality was 14% with a median 
LOS of 16.5 days. Overall, this single-center study showed that 
patients who are admitted to the hospital for a first hospitalization 
requiring NIV for acute respiratory due to COPD exacerbation have a 
high short- and long-term mortality rate. According to the article, 
older age, NIV use greater than eight days and lack of successful NIV 
response were independent prognostic factors to two-year mortality 
rather than response of levels of PaCO2 or pH.
---------------------------------------------------------------------------

    \145\ Sprooten, et al. ``Predictors for long-term mortality in 
COPD patients requiring non-invasive positive pressure ventilation 
for the treatment of acute respiratory failure'' Clinical Resp J. 
2020. Vol 14 (12). p. 1144-1152
---------------------------------------------------------------------------

    The applicant also cited two case studies where the Hemolung RAS 
was used to successfully treat patients in hypercapnic respiratory 
failure caused by COPD. The applicant stated that in these case 
reports, the Hemolung RAS therapy prevented imminent death in COPD 
patients with a DNI order who were failing NIV. In a case study by 
Engel et al., previously described,\146\ a 72-year-old female with 
hypercapnic coma due to COPD exacerbation was administered the Hemolung 
RAS; after 4 hours, PaCO2, pH, and clinical parameters 
improved, and the patient was weaned off therapy after 7 days.
---------------------------------------------------------------------------

    \146\ Engel, et al. ``Use of Extracorporeal CO2 
Removal to Avoid Invasive Mechanical Ventilation in Hypercapnic Coma 
and Failure of Noninvasive Ventilation'' J. Pulm & Resp Med. 2016 
Vol 6 (3) p.1-3.
---------------------------------------------------------------------------

    In a second study by Mani et al., previously described,\147\ the 
Hemolung RAS was used to treat two patients. The first patient, a 69-
year-old female with COPD, was placed on the Hemolung RAS after failing 
NIV treatment. After 66 hours of treatment, the patient was weaned off 
the Hemolung RAS, and was discharged home 4 days later. The second 
patient, a 78-year-old male with COPD, was placed on the Hemolung RAS 
after failing NIV treatment. After 48 hours of treatment, the patient 
was weaned off the Hemolung RAS, and was discharged home 10 days later.
---------------------------------------------------------------------------

    \147\ Mani, R.K., Schmidt, W., Lund, L.W. & Herth, F.J.F. 
Respiratory dialysis for avoidance of intubation in acute 
exacerbation of COPD. ASAIO J. 59, 675-678 (2013).
---------------------------------------------------------------------------

    In support of the assertion that the Hemolung RAS improves 
activities of daily living/quality of life, the applicant submitted one 
randomized controlled trial (RCT) abstract and three case studies. In 
the RCT abstract by Barrett at al.,\148\ 18 patients (median age: 67.5 
years) with acute hypercapnic respiratory failure due to exacerbations 
of COPD were randomized to receive NIV alone or ECCO2R and 
NIV. The applicant stated that the study included patients who were at 
high risk of failing NIV (pH<7.30 after >=1 hour of NIV). The applicant 
stated that the control arm continued to be treated with NIV only (n=9) 
and the test arm was treated with ECCO2R (n=9). The primary 
endpoint was the time to cessation of NIV. Secondary outcomes included 
device tolerance and complications, changes in arterial blood gases 
(ABGs) and hospital survival. The time to NIV discontinuation was 
shorter in the ECCO2R arm (7 hours) vs in the NIV alone arm 
(24.5 hours), p = 0.004. The study claimed that dyspnea rapidly 
improved with ECCO2R, but that ICU and hospital LOS were 
longer with the ECCO2R group and there was no difference in 
mortality or functional outcomes at follow-up. The authors concluded 
that ECCO2R can be an alternative to NIV for patients who 
are at risk of failing or cannot tolerate NIV, or for patients in whom 
a more rapid correction of hypercapnia is desirable.
---------------------------------------------------------------------------

    \148\ Barrett, N., et al. A randomized controlled trial of Non-
Invasive Ventilation compared with ECCO2R for Acute 
Hypercapnic Exacerbations of COPD. ASAIO J. 2021; 67 (Supp 3) 
Presented at the 32nd Annual ELSO Conference.
---------------------------------------------------------------------------

    The applicant referred to three case studies using the Hemolung RAS 
to treat hypercapnic respiratory failure, to demonstrate improvement in 
activities of daily living/quality of life. In the case study by Engel 
et al., previously described,\149\ the applicant stated that early 
mobilization, communication, and nutrition were facilitated with 
Hemolung therapy. In the Bermudez et al. case study, previously 
discussed,\150\ the Hemolung RAS was successfully used to bridge a 
patient with COPD to a lung transplantation. The applicant stated that 
considerable clinical improvement attributed to Hemolung therapy 
permitted the patient to be awake and mobilized to sit on the edge of 
the bed. In the Bonin et al. case study, previously discussed,\151\ the 
applicant stated that drinking and recovery from pressure sores were 
possible by day three of the Hemolung RAS.
---------------------------------------------------------------------------

    \149\ Engel, et al. ``Use of Extracorporeal CO2 
Removal to Avoid Invasive Mechanical Ventilation in Hypercapnic Coma 
and Failure of Noninvasive Ventilation'' J. Pulm & Resp Med. 2016 
Vol 6 (3) p.1-3.
    \150\ Bermudez, et al. ``Prolonged Use of the Hemolung 
Respiratory Assist System as a Bridge to Redo Lung Transplantation'' 
Annals of Thorac Surg. 2015 Vol 100 (6). p. 2330-2333.
    \151\ Bonin, et al. ``Avoidance of intubation during acute 
exacerbation of chronic obstructive pulmonary disease for a lung 
transplant candidate using extracorporeal carbon dioxide removal 
with the Hemolung''. J. Thorac Cardiovac Surg. 2013. Vol 145 (5). 
e43-e44.
---------------------------------------------------------------------------

    After review of the information provided by the applicant, we 
stated that we had the following concerns regarding whether the 
Hemolung RAS meets the substantial clinical improvement criterion. We 
noted that the evidence provided for several of the claims of 
substantial clinical improvement include small, non-randomized studies 
without the use of comparators or controls, including case studies, 
which may affect the ability to draw meaningful conclusions about 
treatment outcomes from the results of the studies. We stated that the 
benefits of avoiding intubation or de-escalating IMV settings are 
described in case studies, but the absence of comparative data may make 
it more difficult to determine whether there are clinically meaningful 
changes in these outcomes. We also noted that in the one abstract of an 
RCT using the Hemolung RAS,\152\ although the time to NIV 
discontinuation was shorter in the ECCO2R arm than in the 
NIV alone arm, the ICU and hospital length of stay were longer with the 
ECCO2R group and there were no differences in mortality or 
functional outcomes at follow-up. Additionally, while the applicant 
stated that the Hemolung RAS results in improved clinical outcomes, 
such as reducing mortality in NIV patients compared to continuing the 
patient's previous treatment, given that many of the case studies 
provided as evidence to support improved clinical outcomes included 
only one or two patients, it was not clear whether or not the results 
of these studies are generalizable to the Medicare population. We also 
noted that several of the case studies, for example, Bonin et al., Mani 
et al., Tully et al., etc., mentioned by the applicant included 
patients and cases from outside the U.S., and we questioned if there 
may be differences in treatment guidelines between these countries that 
may have affected clinical outcomes. Lastly, we noted that for several 
of the claims of substantial clinical improvement, the applicant 
provided

[[Page 48947]]

evidence from background studies that did not utilize the Hemolung RAS 
to support the use of the technology to improve clinical outcomes. For 
example, in support of its assertion that the Hemolung RAS reduces 
mortality in NIPPV patients, the study cited by the applicant only 
addressed NIPPV as a treatment option to treat exacerbations in 
patients with COPD, but did not directly address the use of the 
Hemolung RAS as an intervention.
---------------------------------------------------------------------------

    \152\ Barrett, N., et al. A randomized controlled trial of Non-
Invasive Ventilation compared with ECCO2R for Acute 
Hypercapnic Exacerbations of COPD. ASAIO J. 2021; 67 (Supp 3) 
Presented at the 32nd Annual ELSO Conference.
---------------------------------------------------------------------------

    We invited public comments on whether the Hemolung RAS meets the 
substantial clinical improvement criterion.
    Comment: The applicant submitted comments in response to CMS' 
concerns in the FY2023 IPPS/LTCH PPS proposed rule (87 FR 28243) 
regarding whether the Hemolung RAS meets the substantial clinical 
improvement criterion. In response to our concerns as to whether the 
results of non-controlled data may affect the ability to draw 
meaningful conclusions regarding treatment outcomes and the use of 
background studies to support claims of substantial clinical 
improvement, the applicant stated that it acknowledges randomized 
controlled trial (RCT) data is the gold standard and the limitations of 
non-controlled data, but that large RCTs investigating medical devices 
in the critical care setting present unique enrollment challenges. The 
applicant stated that it is currently conducting the VENT-AVOID RCT in 
the US (``the Trial''--NCT03255057) investigating the use of the 
Hemolung RAS in COPD patients, which has faced slow enrollment since it 
began in 2018, with the COVID-19 pandemic further slowing enrollment. 
The applicant explained that one reason for the slow enrollment is the 
highly specific inclusion and exclusion criteria required by RCTs, 
which is typical of COPD trials. The applicant cited a study that 
evaluated the number of patients who would meet the inclusion criteria 
commonly used in COPD clinical trials, where the results demonstrated 
only 17% of the COPD population would meet the inclusion criteria.\153\
---------------------------------------------------------------------------

    \153\ Herland K, Akselsen JP, Skj[oslash]nsberg OH, Bjermer L. 
How representative are clinical study patients with asthma or COPD 
for a larger ``real life'' population of patients with obstructive 
lung disease? Respiratory Medicine. 2005;99(1):11-19. doi:10.1016/
j.rmed.2004.03.026.
---------------------------------------------------------------------------

    The applicant stated that it believes a substantial amount of real-
world evidence supports the technology's use, and as such, the 
background studies (with a combined >200,000 mechanically ventilated 
patients) are included to provide evidence demonstrating the life-
threatening clinical sequelae that result from hypercapnia and 
respiratory acidosis in critically ill patients, including increased 
risk of ICU and hospital mortality, and longer ICU and hospital lengths 
of stay.154 155 The applicant stated that it believes the 
Hemolung evidence submitted to demonstrate substantial clinical 
improvement reflects the real-world use and the true impact the 
Hemolung RAS will have on the Medicare population, and that it is clear 
that providing clinicians with a tool to effectively correct pH and 
PaCO2 independently of the lungs will have a significant 
positive impact on the outcomes of acute respiratory failure patients.
---------------------------------------------------------------------------

    \154\ Nin N., Muriel A., Pe[ntilde]uelas O., et al. Severe 
hypercapnia and outcome of mechanically ventilated patients with 
moderate or severe acute respiratory distress syndrome. Intensive 
Care Med. 2017;43(2):200-208. doi:10.1007/s00134-016-4611-1.
    \155\ Tiruvoipati R., Pilcher D., Buscher H., Botha J., Bailey 
M. Effects of Hypercapnia and Hypercapnic Acidosis on Hospital 
Mortality in Mechanically Ventilated Patients*: Critical Care 
Medicine. 2017;45(7):e649-e656. doi:10.1097/CCM.0000000000002332.
---------------------------------------------------------------------------

    In response to our concerns as to whether the results of the 
Hemolung RAS case studies that included only one or two patients were 
generalizable to the Medicare population, the applicant stated that the 
epidemiology of acute respiratory distress and need for mechanical 
ventilation in older adults is well established. The applicant noted 
that there is a natural physiologic decline in lung function with age, 
which makes safely and adequately ventilating older patients, 
especially those with respiratory disease, challenging. The applicant 
noted that at generally accepted lung protective ventilation settings, 
older patients are more susceptible to an accumulation CO2 
due to poor baseline lung function. The applicant also stated that use 
of the Hemolung RAS in COPD patients is highly generalizable to the 
Medicare population given that the prevalence of COPD increases with 
age, and that in COPD patients failing non-invasive ventilation (NIV), 
avoiding intubation has a substantial mortality benefit (9% vs 
27%).\156\
---------------------------------------------------------------------------

    \156\ Chandra D., Stamm J.A., Taylor B., et al. Outcomes of 
noninvasive ventilation for acute exacerbations of chronic 
obstructive pulmonary disease in the United States, 1998-2008. Am J. 
Respir Crit Care Med. 2012;185(2):152-159. doi:10.1164/rccm.201106-
1094OC.
---------------------------------------------------------------------------

    In response to our concern as to whether the potential differences 
in treatment guidelines between countries of case studies may have 
affected clinical outcomes, the applicant referenced the consensus 
guideline in the US and Europe that generally the goal when ventilating 
patients is to utilize low volumes and pressures, which can result in 
CO2 accumulation in the blood. The applicant explained that 
as CO2 accumulation is a basic physiologic response to these 
ventilator settings, patient location does not affect clinical 
improvements resulting from the Hemolung RAS therapy.
    In response to our concern that the ICU and hospital stays were 
longer with the ECCO2R group and there were no differences 
in mortality or functional outcomes at follow-up, the applicant 
submitted a recently published RCT \157\ with additional data and 
analysis of its study results on LOS. The applicant cited that the ICU 
and hospital LOS were both 4-5 days longer with ECCO2R than 
with NIV, which was due to a longer ICU LOS. The applicant noted that 
time from ICU discharge to home discharge was equal in both groups. The 
applicant noted that with NIV, nurse-led weaning occurred 24/7, based 
around arterial blood gases, respiratory rate and patient preference, 
and that patients were discharged to the ward during the daytime if 
they had been off NIV overnight. In addition, the applicant stated that 
patients who consistently declined NIV were discharged to a ward bed 
regardless of pH and this will have contributed to the lower ICU length 
of stay in the NIV arm. The applicant noted that the protocol for 
patients receiving ECCO2R did not allow weaning overnight, 
and there was a median of eight hours from cessation of 
ECCO2R to decannulation and unit protocols required a 
further overnight stay for observation.
---------------------------------------------------------------------------

    \157\ Barrett N.A., Hart N., Daly K.J.R., et al. A randomised 
controlled trial of non-invasive ventilation compared with 
extracorporeal carbon dioxide removal for acute hypercapnic 
exacerbations of chronic obstructive pulmonary disease. Ann 
Intensive Care. 2022;12(1):36. doi:10.1186/s13613-022-01006-8.
---------------------------------------------------------------------------

    The applicant also explained that the study results showed that 
time to NIV cessation was significantly shorter in the 
ECCO2R arm than in the NIV arm (7 hrs. vs 24:30 hrs., p = 
0.004). The applicant noted that at one-hour post-randomization the pH 
was significantly higher in the ECCO2R arm (p<0.001), and at 
4 hours post randomization the PaCO2 was significantly lower 
(p<0.001) in the ECCO2R arm, compared to the NIV only arm. 
The applicant stated that ECCO2R also resulted in a 
significant and rapid reduction in subjective discomfort and dyspnea 
measured using a visual analogue scale (VAS), where a higher score 
indicates higher subjective discomfort and dyspnea.
    Several other commenters also indicated their support for the

[[Page 48948]]

Hemolung RAS. A commenter stated that the Hemolung RAS was used in 
their center and proved to be reliable (removing approximately 80 ccs 
of CO2/min) and was well-accepted by staff. The commenter 
noted that the staff considered it easy to use compared to ECMO, and 
were generally able to manage it while also managing other ECMO 
patients. The commenter stated that the Hemolung RAS will occupy an 
important niche in treating patients with acute hypercapnic respiratory 
failure, avoiding intubation up front in some patients as well as 
facilitating weaning off the ventilator in other cases where intubation 
was necessary initially.
    A group of commenters submitted a comment stating that their 
experience with the Hemolung RAS underscored the importance of this 
technology in the Medicare population requiring inpatient management of 
hypercapnic respiratory failure. The commenters stated that IMV not 
only does not address the underlying clinical condition leading to 
hypercapnia, but it also compounds it by elevating pressures applied to 
the lung in an attempt to increase tidal ventilation, which contributes 
to morbidity and mortality, and that prior to the introduction of the 
Hemolung, it was the only option available. The commenters stated that 
they considered the Hemolung RAS a new technology that allows the 
patient on IMV to be managed with lower pressures instead of higher, 
earlier removal from mechanical ventilation, or even avoid mechanical 
ventilation, which the commenter noted is particularly important for 
patients with a do not intubate order for whom there are no other 
treatment alternatives. The commenters considered the Hemolung RAS as 
representing a significant clinical improvement for patients with 
hypercapnic respiratory failure in the inpatient setting, particularly 
for Medicare patients due to their age and risk of complications of the 
current standard of care.
    Response: We thank the applicant and other commenters for their 
comments. Based on the additional information received, we agree with 
the applicant that the Hemolung RAS represents a substantial clinical 
improvement over existing technologies because the technology offers a 
treatment option for hypercapnic respiratory failure due to all causes 
in adults while avoiding intubation or facilitating extubation. We also 
agree with the applicant that the Hemolung RAS fills an unmet need for 
patients ineligible for currently available treatments, such as 
mechanical ventilation (for example, in patients with a DNI order). The 
Hemolung RAS provides extracorporeal CO2 removal from the 
patient's blood for up to 5 days in adults with acute, reversible 
respiratory failure for whom ventilation of CO2 cannot be 
adequately or safely achieved using other available treatment options 
and continued clinical deterioration is expected. For this reason, we 
agree that the Hemolung RAS offers a valuable treatment option for 
patients at risk for complications from, unresponsive to, and/or 
ineligible for, mechanical ventilation.
    After consideration of the public comments we received, we have 
determined that the Hemolung RAS meets the criteria for approval for 
new technology add-on payments. Therefore, we are approving new 
technology add-on payments for use of the Hemolung RAS for the 
indications approved under its FDA De Novo marketing authorization for 
FY 2023. As discussed in the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 
28236) consistent with our longstanding policy of not considering 
eligibility for new technology add-on payments prior to a product 
receiving FDA approval or clearance, a product available only through 
an EUA would not be eligible for new technology add-on payments. 
Therefore, cases involving pediatric patients, or cases involving the 
use of the Hemolung RAS for greater than 5 days, would not be eligible 
for new technology add-on payments, as they do not fall under the 
patient population indicated in its FDA De Novo marketing 
authorization. Cases involving the use of the Hemolung RAS that are 
eligible for new technology add-on payments will be identified by ICD-
10-PCS procedure code 5A0920Z (Assistance with respiratory filtration, 
continuous).
    In its application, the applicant estimated that the cost of 
Hemolung RAS is $10,000, which includes the $7,500 cost of the 
cartridge and the $2,500 cost of the catheter. Under Sec.  
412.88(a)(2), we limit new technology add-on payments to the lesser of 
65% of the average cost of the technology, or 65% of the costs in 
excess of the MS-DRG payment for the case. As a result, the maximum new 
technology add-on payment for a case involving the use of Hemolung RAS 
is $6,500 for FY 2023.
d. LIVTENCITYTM (Maribavir)
    Takeda Pharmaceuticals U.S.A., Inc. submitted an application for 
new technology add-on payments for LIVTENCITYTM (maribavir) 
for FY 2023. LIVTENCITYTM is a cytomegalovirus (CMV) pUL97 
kinase inhibitor indicated for the treatment of adults and pediatrics 
(12 years of age and older and weighing at least 35 kg) with post-
transplant CMV infection/disease that is refractory to treatment (with 
or without genotypic resistance) to ganciclovir, valganciclovir, 
cidofovir, or foscarnet.
    According to the applicant, LIVTENCITYTM is the only 
antiviral therapy indicated to treat post-transplant patients with CMV 
in solid organ transplant (SOT) and hematopoietic stem cell transplant 
(HCT). Per the applicant, LIVTENCITYTM provides multi-
targeted anti-CMV activity by inhibiting protein kinase UL97 and its 
natural substrates, which subsequently inhibits CMV DNA replication, 
encapsidation, and nuclear egress of viral capsids.
    The applicant stated that CMV is one of the most common viral 
infections experienced by transplant recipients, with an estimated 
incidence rate between 16%-56% in SOT recipients and 30%-70% in HCT 
recipients.\158\ CMV is a beta herpesvirus that commonly infects 
humans; serologic evidence of prior infection can be found in 40%-100% 
of various populations.\159\ CMV typically resides latent and 
asymptomatic in the body but may reactivate during periods of 
immunosuppression. The applicant estimated that there are approximately 
200,000 adult transplants per year globally and an estimated 1,435 
cases of CMV post-transplant in the Medicare population per year. The 
applicant stated that in transplant patients, reactivation of CMV can 
potentially lead to serious consequences including loss of the 
transplanted organ and, in extreme cases, death.
---------------------------------------------------------------------------

    \158\ Azevedo L, Pierrotti L, Abdala E, et al. Cytomegalovirus 
infection in transplant recipients. Clinics.2015;70(7):515-523. 
doi:10.6061/clinics/2015(07)09; World Health Organization (WHO). 
International Report on Organ Donation and Transplantation 
Activities--Executive Summary 2018.
    \159\ Krech U. Complement-fixing antibodies against 
cytomegalovirus in different parts of the world. Bull WHO. 
1973(49):103-106.
---------------------------------------------------------------------------

    Per the applicant, there are four FDA-approved therapies for the 
treatment and/or prevention (that is, prophylaxis) of CMV disease: 
valganciclovir, ganciclovir, foscarnet, and cidofovir. The applicant 
stated that ganciclovir and valganciclovir are approved for prevention 
of CMV disease in transplant recipients and for treatment of CMV 
retinitis in immunocompromised hosts, including those with Acquired 
Immune Deficiency Syndrome (AIDS); and foscarnet and cidofovir are 
approved for treatment of CMV retinitis in AIDS patients. Per the 
applicant, none of these four therapies are FDA-approved for the 
treatment of resistant or

[[Page 48949]]

refractory CMV infection and disease. The applicant provided a table 
that included the therapy, transplant type, mechanism of action, 
approved indications that were CMV-related, and the formulation(s).
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TR10AU22.087

BILLING CODE 4120-01-C
    With respect to the newness criterion, the applicant stated that 
LIVTENCITYTM was granted Breakthrough Therapy, Priority 
Review, and Orphan Drug designations from FDA, and subsequently 
received FDA approval for its New Drug Application on November 23, 
2021. LIVTENCITYTM is indicated for the treatment of adults 
and pediatric patients (12 years of age or older and weighing at least 
35 kg) with post-transplant CMV infection/disease that is refractory to 
treatment (with or without genotypic resistance) with ganciclovir, 
valganciclovir, cidofovir, or foscarnet. Per the applicant, 
LIVTENCITYTM became commercially available on December 2, 
2021. The applicant did not explain the reason for the delay between 
market authorization and commercial availability. The recommended 
dosing is 400 mg (two 200 mg tablets) orally twice daily with or 
without food. The applicant stated that if LIVTENCITYTM is 
co-administered with carbamazepine, then the dosage is increased to 800 
mg twice daily; if co-administered with phenytoin or phenobarbital, the 
dosage is increased to 1,200 mg twice daily.
---------------------------------------------------------------------------

    \160\ VALCTE[supreg] (valganciclovir) United States Prescibing 
Information (2018).
    \161\ CYTOVENE-IV[supreg] (ganciclovir) United States Prescibing 
Information (2018).
    \162\ FOSCAVIR[supreg] (foscarnet) United States Prescibing 
Information (2017).
    \163\ VISTIDE[supreg] (cidofovir) United States Prescibing 
Information (2010).
---------------------------------------------------------------------------

    According to the applicant, ICD-10-PCS code 3E0DX29 (Introduction 
of other anti-infective into mouth and pharynx, external approach) may 
be used to identify administration of LIVTENCITYTM but does 
not uniquely identify it. The following ICD-10-PCS procedure codes were 
created to uniquely describe the use of LIVTENCITYTM, 
effective October 1, 2022: XW0DX38 (Introduction of

[[Page 48950]]

maribavir anti-infective into mouth and pharynx, external approach, new 
technology group 8), XW0G738 (Introduction of maribavir anti-infective 
into upper gi, via natural or artificial opening, new technology group 
8), and XW0H738 (Introduction of maribavir anti-infective into lower 
gi, via natural or artificial opening, new technology group 8).
    As previously discussed, if a technology meets all three of the 
substantial similarity criteria under the newness criterion, it would 
be considered substantially similar to an existing technology and would 
not be considered ``new'' for the purposes of new technology add-on 
payments.
    With respect to the first criterion, whether a technology uses the 
same or similar mechanism of action to achieve a therapeutic outcome, 
the applicant stated that LIVTENCITYTM targets a different 
gene locus (pUL97 vs. pUL54) than the existing therapies to treat CMV 
infection, including those resistant or refractory to conventional 
therapy. Specifically, LIVTENCITYTM inhibits CMV DNA 
replication, encapsidation, and nuclear egress of viral capsids through 
inhibition of pUL97 and its natural substrates. The applicant provided 
the mechanisms of action for the other existing anti-CMV drugs, namely 
valganciclovir ganciclovir, foscarnet, and cidofovir in the table 
previously listed and concluded that LIVTENCITYTM uses a 
different mechanism of action compared to existing anti-CMV drugs.
    With respect to the second criterion, whether a technology is 
assigned to the same or a different MS-DRG when compared to an existing 
technology, the applicant stated that LIVTENCITYTM is 
expected to be assigned to the same MS-DRGs as therapies that are 
currently used off-label for the treatment of CMV infection or disease.
    With respect to the third criterion, whether the new use of 
technology involves the treatment of the same or similar type of 
disease and the same or similar patient population when compared to an 
existing technology, the applicant noted that there are no other 
existing therapies indicated to treat the same or similar type of 
disease or patient population as LIVTENCITYTM. The applicant 
noted that currently available therapies are used off-label to treat 
patients with refractory or resistant CMV infection or disease. Thus, 
the applicant maintained that LIVTENCITYTM is indicated to 
treat a different patient population compared to existing technologies.
    In summary, the applicant asserted that LIVTENCITYTM is 
not substantially similar to other currently available therapies 
because it uses a new mechanism of action and is indicated to treat a 
unique patient population and/or disease and, therefore, the technology 
meets the newness criterion. We invited public comments on whether 
LIVTENCITYTM is substantially similar to existing 
technologies and whether LIVTENCITYTM meets the newness 
criterion. As noted in the proposed rule, the applicant did not explain 
the reason for the delay between market authorization and commercial 
availability, and we requested additional information regarding this 
point.
    Comment: The applicant submitted comments in response to CMS' 
request for additional information on the delay between market 
authorization and commercial availability of LIVTENCITYTM. 
Per the applicant, between FDA marketing authorization on November 23, 
2021 and commercial availability on December 2, 2021, the applicant 
applied final packaging and labeling and worked to ship the product to 
specialty pharmacies and distributors as soon as finished goods were 
available.
    Response: We thank the applicant for the additional information 
regarding the delay between market authorization and commercial 
availability. We agree with the applicant that the beginning of the 
newness period for LIVTENCITYTM is December 2, 2021, the 
date the product became commercially available.
    Comment: A commenter agreed that LIVTENCITYTM does not 
meet the first and third substantial similarity criteria as it stated 
that there are no other antivirals with a similar mechanism of action 
and LIVTENCITYTM offers a novel treatment option for 
patients with no other antivirals currently approved for the treatment 
of post-transplant CMV refractory to traditional treatments. They 
agreed with the applicant that LIVTENCITYTM is likely to 
share the same MS-DRGs as off-label agents currently used for CMV 
infection or disease.
    Response: We thank the commenter for their input. We agree with the 
commenter that LIVTENCITYTM has a unique mechanism of action 
and offers a novel treatment option for patients with post-transplant 
CMV refractory to traditional treatments.
    Based on information submitted by the applicant in its comment and 
as part of its FY 2023 new technology add-on payment application for 
LIVTENCITYTM, as discussed in the proposed rule (87 FR 28258 
through 28259) and previously summarized, we believe that 
LIVTENCITYTM has a unique mechanism of action because it 
inhibits pUL97, which is involved in terminal DNA processing, including 
DNA elongation, encapsidation, and nuclear egress of viral capsids, 
whereas existing therapies inhibit CMV DNA polymerase (pUL54) or the 
CMV DNA terminase complex (pUL51, pUL56, and pUL89) that is required 
for viral DNA processing and packaging. We also believe that 
LIVTENCITYTM is indicated to treat a unique patient 
population and/or disease, as it is the only FDA-approved antiviral 
therapy indicated to treat post-transplant patients with CMV disease in 
solid organ transplant (SOT) and hematopoietic stem cell transplant 
(HCT). Therefore, LIVTENCITYTM is not substantially similar 
to existing treatment options and meets the newness criterion. As 
stated previously, we consider the beginning of the newness period to 
commence on December 2, 2021 based on information provided by the 
applicant that the product first became available for sale on that 
date.
    With respect to the cost criterion, the applicant presented the 
following analysis. To identify patients who may be eligible to receive 
LIVTENCITYTM as a treatment, the applicant searched the 2019 
MedPAR dataset for cases with the following ICD-10-CM codes for CMV and 
post-transplant SOT and HCT infection. The applicant included inpatient 
discharges under Medicare fee-for-service (FFS) and excluded Medicare 
Advantage discharges.
BILLING CODE 4120-01-P

[[Page 48951]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.088

    The applicant identified 1,435 claims mapping to 108 MS-DRGs. For 
MS-DRGs where the case volume was below 11, the applicant imputed a 
count of 11 cases. The table lists the nine MS-DRGs with the highest 
volume of cases.
[GRAPHIC] [TIFF OMITTED] TR10AU22.089

BILLING CODE 4120-01-C
    The applicant did not remove charges for a prior technology, as the 
applicant claimed that any current treatment that is used off-label to 
treat CMV patients post-transplant SOT and HCT may not be reflected in 
claims data. The applicant further explained that in cases where an 
off-label treatment is reflected on the claim, LIVTENCITYTM 
might be used as a second-line treatment rather than to replace the 
off-label treatment. The applicant then standardized the charges and 
applied a 4-year inflation factor of 1.281834 or 28.1834%, based on the 
inflation factor used in the FY 2022 IPPS/LTCH PPS final rule and 
correction notice to update the outlier threshold (86 FR 45542). The 
applicant added charges for the new technology by dividing the cost of 
LIVTENCITYTM by the national average CCR for drugs which is 
0.187 (86 FR 44966). The applicant estimated the costs of 
LIVTENCITYTM based on 8-week dosing regimens to complete the 
full treatment.
    The applicant calculated a final inflated average case-weighted 
standardized charge per case of $508,855 which exceeded the average 
case-weighted threshold amount of $76,739.
    We invited public comments on whether LIVTENCITYTM meets 
the cost criterion.
    We did not receive any comments on whether LIVTENCITY\TM\ meets the 
cost criterion. Based on the information submitted by the applicant as 
part of its FY 2023 new technology add-on payment application for 
LIVTENCITYTM, as discussed in the proposed rule (87 FR 28259 
through 28260) and previously summarized, the final inflated average 
case-weighted

[[Page 48952]]

standardized charge per case exceeds the average case-weighted 
threshold amount. Therefore, LIVTENCITYTM meets the cost 
criterion.
    With regard to the substantial clinical improvement criterion, the 
applicant asserted that LIVTENCITYTM represents a new 
treatment option for a patient population unresponsive to, or 
ineligible for, currently available treatments. To support this claim, 
the applicant reiterated that there are no existing therapies that are 
approved by FDA to treat post-transplant patients with refractory or 
resistant CMV infection or disease. The applicant also asserted that 
the use of LIVTENCITYTM may significantly improve clinical 
outcomes by improving efficacy and reducing adverse effects compared to 
available therapies.
    To support the claim of improved efficacy, the applicant cited 
results from SOLSTICE, a phase III, open-label, randomized controlled 
trial in which 352 transplant recipients [HCT (n=211) and SOT (n=141)] 
with refractory \164\ or resistant \165\ CMV were assigned 2:1 to 
receive 400 mg of LIVTENCITYTM twice daily (n=235) or 
investigator-assigned therapy (IAT) with drug-specific dosing (n=117) 
for 8 weeks, with 12 weeks of follow-up.\166\ The choice of specific 
IAT was at the investigators' discretion and included mono- or 
combination therapy (<=2 drugs) with intravenous (IV) ganciclovir, oral 
valganciclovir, IV foscarnet or IV cidofovir, where switching between 
ganciclovir and valganciclovir was permitted. The median (range) 
duration of exposure was 57 (2-64) days in the LIVTENCITYTM 
arm and 34 (4-64) days with IAT. The primary endpoint was the 
proportion of patients achieving CMV clearance at 8 weeks, and the key 
secondary endpoint was achievement of CMV clearance \167\ and symptom 
control \168\ at the end of week 8, maintained through week 16. With 
respect to the primary endpoint, the applicant indicated that CMV 
clearance at 8 weeks was achieved in 55.7% (n=131/235) of the 
LIVTENCITYTM group and 23.9% (n=28/117) of the IAT group 
with an adjusted difference of 32.8%, where the results achieved 
statistical significance [95% CI, 22.8-42.7%, p<0.001]. With respect to 
the secondary endpoint, the applicant indicated that 18.7% (n=44/235) 
of the LIVTENCITYTM-treated group and 10.3% (n=12/117) of 
IAT-treated group maintained CMV viremia clearance and symptom control 
through week 16 (p=0.013).\169\ The applicant stated that, based on 
these results, LIVTENCITYTM is superior to conventional 
antiviral therapies in achieving and maintaining CMV viremia clearance 
and symptom control.
---------------------------------------------------------------------------

    \164\ Failure to achieve >1 log10 decrease in CMV DNA 
after at least 14 days of anti-CMV treatment.
    \165\ At least 1 genetic mutation associated with resistance to 
ganciclovir/valganciclovir, foscarnet, and/or cidofovir.
    \166\ Avery RK, Alain S, Alexander B, et al. Maribavir for 
refractory cytomegalovirus infections with or without resistance 
post-transplant: results from a phase 3 randomized clinical trial 
(accepted manuscript). Clin Infect Dis. 2021; ciab988, https://doi.org/10.1093/cid/ciab988.
    \167\ Measured as CMV DNA level less than lower limit of 
quantification.
    \168\ Resolution or improvement in tissue-invasive CMV disease 
or syndrome for participants symptomatic at baseline or no new 
symptoms of tissue-invasive CMV disease or syndrome for participants 
asymptomatic at baseline.
    \169\ Avery RK, Alain S, Alexander B, et al. Maribavir for 
refractory cytomegalovirus infections with or without resistance 
post-transplant: results from a phase 3 randomized clinical trial 
(accepted manuscript). Clin Infect Dis. 2021; ciab988, https://doi.org/10.1093/cid/ciab988.
---------------------------------------------------------------------------

    The applicant also claimed that the efficacy of 
LIVTENCITYTM is consistent across SOT types, as evidenced by 
an unpublished subgroup analysis by Avery et al.\170\ which evaluated 
211 SOT patients from the SOLSTICE trial for CMV clearance 
(LIVTENCITYTM vs. conventional) by transplant type, with the 
following results: heart: 42.9% (n=6/14) vs. 11.1% (n=1/9) (adjusted 
difference: 30.7% [95% CI, -1.72-63.15%]); lung: 47.5% (n=19/40) vs. 
13.6% (n=3/22), adjusted difference: 38.2% [95% CI, 16.89-59.53%]; 
kidney: 59.5% (n=44/74) vs. 34.4% (n=11/32); adjusted difference: 26.7% 
[95% CI, 7.48-45.85%].
---------------------------------------------------------------------------

    \170\ Avery RK, Blumberg EA, Florescu D, et al. A randomized 
phase 3 open-label study of maribavir vs. investigator-assigned 
therapy for refractory/resistant cytomegalovirus infection in 
transplant recipients: subgroup analyses of efficacy by organ. in: 
The 2021 American Transplant Congress; 2021. Abstract LB 9.
---------------------------------------------------------------------------

    Finally, with regard to efficacy, the applicant stated that 
LIVTENCITYTM is active against refractory or resistant CMV 
infections and tolerable across doses. To support this claim, the 
applicant pointed to a randomized, dose-ranging, open-label, phase II 
study by Papanicolaou et al.,\171\ in which HCT and SOT recipients with 
refractory or resistant CMV infections (n=120) were randomized 1:1:1 to 
twice-daily LIVTENCITYTM doses of 400 mg (n=40), 800 mg 
(n=40), or 1,200 mg (n=40) for up to 24 weeks. The primary efficacy 
endpoint was the proportion of patients with confirmed undetectable 
plasma CMV DNA within 6 weeks of treatment. About two-thirds (n=80/120) 
of the patients achieved undetectable plasma CMV DNA within 6 weeks of 
treatment among all doses [95% CI, 57-75%], and 70% of patients 
receiving 400 mg of LIVTENCITYTM twice daily [95% CI, 53-
83]; 62% of patients receiving 800 mg twice daily [95% CI, 46-77%], and 
68% of patients receiving 1,200 mg twice daily [95% CI, 51-81%] 
achieved the primary endpoint. About a third of patients experienced 
recurrent CMV infection while on LIVTENCITYTM (n=25) and 13 
patients developed mutations conferring LIVTENCITYTM 
resistance.
---------------------------------------------------------------------------

    \171\ Papanicolaou GA, Silveira FP, Langston AA, et al. MBV for 
r/r CMV infections in HCT or SOT recipients: A randomized, dose-
ranging, double-blind, phase 2 study. Clin Infect Dis. 
2019;68(8):1255-1264. doi:10.1093/cid/ciy706.
---------------------------------------------------------------------------

    To support the claim of decreased adverse effects, the applicant 
cited the results of two secondary endpoints from the SOLSTICE trial. 
Per the applicant, neutropenia and acute kidney injury are known, 
common adverse effects associated with valganciclovir/ganciclovir and 
foscarnet, respectively. The applicant noted that the rates of 
treatment-related neutropenia and acute kidney injury were both 1.7% 
(n=4/234), separately, in the LIVTENCITYTM treatment group. 
The applicant also noted that the rate of neutropenia was 25% (n=14/56) 
in the valganciclovir/ganciclovir group, and the rate of acute kidney 
injury was 19.1% (n=9/47) in the foscarnet group.\172\ The applicant 
maintained that the rate of treatment-related neutropenia and acute 
kidney injury was lower in the LIVTENCITYTM group vs. 
conventional therapy group. The applicant asserted that, based on these 
results, LIVTENCITYTM has a lower incidence of treatment-
related toxicities than existing therapies.
---------------------------------------------------------------------------

    \172\ Avery R.K., Alain S., Alexander B., et al. Maribavir for 
refractory cytomegalovirus infections with or without resistance 
post-transplant: results from a phase 3 randomized clinical trial 
(accepted manuscript). Clin Infect Dis. 2021; ciab988, https://doi.org/10.1093/cid/ciab988.
---------------------------------------------------------------------------

    The applicant more specifically claimed that transplant patients 
treated with LIVTENCITYTM for CMV infection experienced a 
lower incidence of treatment-related neutropenia compared with 
valganciclovir. To support this claim, the applicant cited the primary 
safety endpoint from Maertens et al.,\173\ a parallel-group, phase II 
study. In this open-label, LIVTENCITYTM-blinded trial, 120 
HCT or SOT recipients with CMV reactivation were randomly assigned to 
receive LIVTENCITYTM at a dose of 400 mg (n=40), 800 mg 
(n=40), or 1,200 mg (n=40) twice daily or the standard dose of 
valganciclovir for 12 weeks for preemptive treatment. The primary 
efficacy endpoint was the

[[Page 48953]]

percentage of patients with a response to treatment, defined as 
confirmed undetectable CMV DNA in plasma, within 3 weeks and 6 weeks 
after the start of treatment. The primary safety endpoint was the 
incidence of adverse events that occurred or worsened during treatment. 
Specifically, the applicant cited the rate of treatment-emergent 
neutropenia in this study which was identified in 4% (n=5/118) of 
patients administered LIVTENCITYTM versus 15% (n=6/39) of 
patients administered valganciclovir through week 6. Similar results 
were found through week 12: 5% (n=6/118) vs. 18% (n=7/39). The 
statistical significance of the difference in treatment-emergent 
neutropenia between the two groups was not reported in the study.
---------------------------------------------------------------------------

    \173\ Maertens J., Cordonnier C., Jaksch P., et al. Maribavir 
for preemptive treatment of cytomegalovirus reactivation. N. Engl J. 
Med. 2019;381(12):1136-1147. doi:10.1056/NEJMoa1714656.
---------------------------------------------------------------------------

    Finally, the applicant stated that LIVTENCITYTM had a 
lower incidence of adverse events leading to discontinuation. To 
support this assertion, the applicant cited the rate of treatment-
emergent adverse effects (TEAEs) leading to discontinuation from 
SOLSTICE, which was lower in the LIVTENCITYTM group (13.2% 
(n=31/324)) vs. the conventional group (31.9% (n=37/116)).\174\
---------------------------------------------------------------------------

    \174\ Avery R.K., Alain S., Alexander B., et al. Maribavir for 
refractory cytomegalovirus infections with or without resistance 
post-transplant: results from a phase 3 randomized clinical trial 
(accepted manuscript). Clin Infect Dis. 2021; ciab988, https://doi.org/10.1093/cid/ciab988.
---------------------------------------------------------------------------

    In the proposed rule, we stated we had the following concerns 
regarding whether LIVTENCITYTM meets the substantial 
clinical improvement criterion. First, while the applicant provided 
data to demonstrate that the proportion of patients achieving CMV 
clearance at 8 weeks was higher among patients using 
LIVTENCITYTM, there were similar rates of mortality and new-
onset CMV between the 2 treatment groups in this trial: 
LIVTENCITYTM vs. comparator: 11% (n=27/235) vs. 6% (n=13/
117) and 6% (n=14/235) vs. 6% (n=7/113), respectively.\175\ We also 
noted that it is unclear whether the SOLSTICE study was sufficiently 
powered to detect a difference in CMV viremia clearance at week 16, one 
of the study's secondary endpoints.\176\ We further noted that while 
the rate of TEAEs leading to discontinuation was lower in the 
LIVTENCITYTM group, the rate of overall TEAEs and serious 
TEAEs in the SOLSTICE trial was similar between the two treatment 
groups [LIVTENCITYTM vs. comparator: any TEAE: 97.4% (n=229/
234) vs. 91.4% (n=106/116), serious TEAE: 38.5% vs. 37.1%].\177\ 
Furthermore, we stated that we would appreciate additional information 
from the applicant regarding safeguards taken to minimize or prevent 
bias from the treating physician in choosing the conventional therapy 
for patients in the investigator-assigned therapy group of the phase 
III trial.
---------------------------------------------------------------------------

    \175\ Ibid.
    \176\ Ibid.
    \177\ Ibid.
---------------------------------------------------------------------------

    We invited public comments on whether LIVTENCITYTM meets 
the substantial clinical improvement criterion.
    Comment: We received several comments in support of approving new 
technology add-on payments for LIVTENCITYTM. The applicant 
reiterated four reasons LIVTENCITYTM meets the substantial 
clinical improvement criterion, including: (1) being a new treatment 
option for a patient population unresponsive to, or ineligible for, 
currently available treatments; (2) more rapid resolution of infection/
disease; (3) reduction in at least one clinically significant adverse 
event, and (4) decreased number of hospitalizations. The applicant also 
submitted comments in response to CMS' concerns regarding the 
substantial clinical improvement criterion.
    With respect to the concern that there were similar rates of 
mortality and new-onset CMV between the two treatment groups in the 
SOLSTICE study, the applicant stated that the study was not 
sufficiently powered nor was it long enough in duration to detect a 
difference in these two endpoints. With respect to all-cause mortality, 
the applicant stated that 8 weeks is often the longest duration 
permissible due to toxicities associated with the IAT treatment group, 
and that the underlying medical history of the patients and the short 
study duration contributed to the similar rate of mortality. The 
applicant further explained that all-cause mortality rates were 
assessed based on the randomized treatment group, regardless of 
LIVTENCITYTM rescue treatment in the IAT group. With respect 
to new-onset CMV, the applicant stated that CMV treatment, either via 
secondary prophylaxis or treatment with LIVTENCITYTM, was 
not allowed after 8 weeks which could explain the similar rates between 
the two groups. They also noted that a higher proportion of 
LIVTENCITYTM patients with new onset symptomatic CMV were 
primary responders to LIVTENCITYTM treatment versus the IAT 
patients. Furthermore, the study participants had a history of multiple 
past recurrences, increasing the likelihood of CMV recurrence. Finally, 
the applicant emphasized that clinically relevant recurrence is more 
clinically meaningful than overall recurrence.
    Another commenter concurred with the applicant, stating that the 
SOLSTICE study design and imbalances in certain, therapy-independent 
baseline characteristics for the LIVTENCITYTM group (for 
example, presence of CMV disease) could make it difficult to identify 
true differences in all-cause mortality and new-onset CMV amongst 
LIVTENCITYTM and comparators.
    The applicant also responded to CMS' concern that the SOLSTICE 
study was not sufficiently powered to detect difference in CMV viremia 
clearance at week 16, one of the study's secondary endpoints. The 
applicant noted that the study was powered to detect difference in CMV 
viremia at week 8, which was the primary endpoint of the study.
    In response to CMS' concern that overall rate of TEAEs and serious 
TEAEs in the SOLSTICE trial was similar between the two treatment 
groups, the applicant stated that the similar rate of TEAEs was due to 
complexity of the patient population. They noted that the rate of TEAEs 
in the LIVTENCITYTM group was driven by mild dysgeusia. 
Similarly, a commenter stated that while the rate of any TEAEs was 
similar for LIVTENCITYTM versus IAT, patients in the 
LIVTENCITYTM group primarily experienced dysgeusia which did 
not result in treatment discontinuation, while patients in the IAT 
group experienced cytopenias and renal disorders that did lead to 
treatment discontinuation. The applicant also stated that the rate of 
TEAEs was not adjusted for drug exposure; drug exposure was longer in 
the LIVTENCITYTM group versus the IAT group due to 
toxicities in the IAT group. Finally, they noted that TEAEs leading to 
discontinuation was higher in the IAT group versus the 
LIVTENCITYTM group.
    Another commenter stated, with respect to the same concern, that 
while the rates of any serious TEAEs were similar between the groups, 
the rate of treatment-related serious TEAEs was lower in the 
LIVTENCITYTM group versus IAT (5.1% vs. 14.7%, 
respectively), with the benefit persisting when taking into account 
discontinuation rates. The commenter cited this result in support of a 
finding that LIVTENCITYTM is a unique oral therapeutic 
option for CMV that does not share the same problematic adverse events 
of currently used off-label agents which the commenter stated often 
lead to treatment discontinuation and thus,

[[Page 48954]]

suboptimal treatment of CMV infection and disease.
    The applicant also responded to CMS' request for additional 
information on safeguards taken to minimize or prevent bias from the 
treating physician in choosing the conventional therapy for patients in 
the IAT group of the SOLSTICE study. The applicant noted that SOLSTICE 
was designed as an open-label study because the investigators had to 
individualize the selection of the effective comparator in medically 
complex patients with concomitant medications and adjust dosing of the 
IAT agents based on renal function. Thus, the applicant asserted that 
an open-label design was a safe and practical way to conduct the study. 
The applicant also noted that the primary endpoint of the study was 
assessed based on an objective laboratory endpoint at a fixed 
timepoint. They stated that multiple sensitivity analyses were 
conducted to address potential bias due to different rates of early 
treatment discontinuation and that the primary endpoint was evaluated 
in subgroups to establish treatment consistency and study 
generalizability. The results of these sensitivity analyses of the 
primary efficacy endpoint were consistent with the results of the 
primary efficacy analysis and the benefit of the technology was also 
consistent across key subpopulations.
    Response: We thank the commenters for their input and appreciate 
the clarifications in response to our concerns regarding the similar 
rates of mortality and new-onset CMV between the two treatment groups, 
the insufficient power to detect a difference in CMV viremia clearance 
at week 16, and the similar rates of overall TEAEs and serious TEAEs in 
the SOLSTICE study. Based on the additional information received, we 
agree that LIVTENCITYTM represents a substantial clinical 
improvement over existing technologies because it provides a new 
treatment option for a patient population unresponsive to, or 
ineligible for, currently available treatments, and significantly 
improves the proportion of patients achieving CMV viremia at 8 weeks 
and maintaining CMV clearance and symptom control at week 8 through 
week 16, as well as reduces adverse effects such as neutropenia and 
nephrotoxicity compared to available therapies.
    After consideration of the public comments we received, we have 
determined that LIVTENCITYTM meets the criteria for approval 
for new technology add-on payment. Therefore, we are approving new 
technology add-on payments for LIVTENCITYTM for FY 2023. 
Cases involving the use of LIVTENCITYTM that are eligible 
for new technology add-on payments will be identified by ICD-10-PCS 
procedure codes XW0DX38 (Introduction of maribavir anti-infective into 
mouth and pharynx, external approach, new technology group 8), XW0G738 
(Introduction of maribavir anti-infective into upper GI, via natural or 
artificial opening, new technology group 8), or XW0H738 (Introduction 
of maribavir anti-infective into lower GI, via natural or artificial 
opening, new technology group 8).
    In its application, the applicant estimated that the cost of 
LIVTENCITYTM is $50,000 for an 8-week course of therapy. 
Under Sec.  412.88(a)(2), we limit new technology add-on payments to 
the lesser of 65% of the average cost of the technology, or 65% of the 
costs in excess of the MS-DRG payment for the case. As a result, the 
maximum new technology add-on payment for a case involving the use of 
LIVTENCITYTM is $32,500 for FY 2023.
e. UPLIZNA[supreg] (Inebilizumab-Cdon)
    HTI-DAC, the manufacturer under the distributor Horizon 
Therapeutics USA, Inc., submitted an application for new technology 
add-on payment for UPLIZNA[supreg] (inebilizumab-cdon) for FY 2023. Per 
the applicant, UPLIZNA[supreg] is the first FDA-approved anti-cluster 
of differentiation 19 (CD19) B-cell depleter for the treatment of 
neuromyelitis optica spectrum disorder (NMOSD) in adults who are anti-
aquaporin-4 (AQP4) antibody positive, for which 80% of all patients 
with NMOSD test positive.\178\ According to the applicant, the goal of 
UPLIZNA[supreg] is to reduce the risk of relapse and disability 
progression. The applicant explained UPLIZNA[supreg] is a CD19+ B cell-
directed humanized afucosylated immunoglobulin F1 (IgG1) monoclonal 
antibody. The applicant further explained that CD19 is a cell surface 
antigen expressed on a broad range of B lymphocytes. Per the applicant, 
UPLIZNA[supreg] is a B-cell depleter that binds specifically to CD19, 
allowing it to target an extended range of B-cells that play a role in 
NMOSD. The applicant stated that following cell surface binding to 
CD19+ B lymphocytes, UPLIZNA[supreg] causes antibody-dependent cellular 
cytolysis (ADCC), resulting in significant and robust B-cell depletion.
---------------------------------------------------------------------------

    \178\ Wingerchuck, D. (2009, November 15). Neuromyelitis optica: 
Effect of gender. Journal of the Neurological Sciences. Retrieved 
October 6, 2021, from https://pubmed.ncbi.nlm.nih.gov/19740485/.
---------------------------------------------------------------------------

    NMOSD is a rare, severe autoimmune disease of the central nervous 
system that causes damage to the optic nerve, spinal cord, and brain 
stem. NMOSD affects approximately 10,000-15,000 people in the United 
States, and the incidence rate may be up to 9 times higher for women 
than for men, with prevalence approximately 2- to 3-fold higher among 
Black and Asian populations.\179\ According to the applicant, NMOSD is 
characterized by unpredictable, recurrent attacks of inflammation of 
the optic nerve (optic neuritis) and/or of the spinal cord (transverse 
myelitis), and may also affect regions of the brain. The applicant 
stated that attacks can be severe and result in life-altering permanent 
disability, such as blindness and paralysis, and that recurring attacks 
can have cumulative effects resulting in significant morbidity. 
According to the applicant, aquaporin-4 antibodies are highly specific 
to NMOSD and AQP4 is expressed on astrocytes throughout the central 
nervous system. Per the applicant, in NMOSD, AQP4 antibodies bind to 
AQP4, resulting in astrocyte cell death and inflammation. The applicant 
stated that a sub-population of B-lineage cells, CD19+ plasmablasts, 
produce AQP4 antibodies and that certain CD19+ B-cells are increased in 
the blood of AQP4-seropositive individuals with NMOSD, with the highest 
levels observed during an attack. According to the applicant, by 
depleting a wide range of B-cells that express CD19 (including 
plasmablasts and some plasma cells), UPLIZNA[supreg] reduces the risk 
of relapses or attacks that may lead to permanent disability in NMOSD 
patients.
---------------------------------------------------------------------------

    \179\ Flanagan, E.P. et al. (2016, April 4). Epidemiology of 
aquaporin[hyphen]4 autoimmunity and Neuromyelitis Optica Spectrum. 
Wiley Online Library. Retrieved October 6, 2021, from https://onlinelibrary.wiley.com/doi/10.1002/ana.24617.
---------------------------------------------------------------------------

    With respect to the newness criterion, the applicant stated that 
UPLIZNA[supreg] was designated as a Breakthrough Therapy and received 
Orphan Drug designation on February 10, 2016 for the treatment of 
NMOSD.\180\ Per the applicant, UPLIZNA[supreg] received FDA approval on 
June 11, 2020, for the treatment of NMOSD in adult patients who are 
AQP4 antibody positive (BLA #761142). The applicant stated that 
UPLIZNA[supreg] became commercially available on July 9, 2020, 
following FDA approval. According to the applicant, UPLIZNA[supreg] is 
administered as an intravenous infusion, and titrated to completion, 
over approximately 90 minutes under the close supervision of an 
experienced

[[Page 48955]]

healthcare professional. The applicant stated that the recommended 
initial dose is a 300 mg intravenous infusion followed 2 weeks later by 
a second 300 mg intravenous infusion. The applicant also stated that 
subsequent doses, starting 6 months from the first infusion, consist of 
a single 300 mg intravenous infusion every 6 months.
---------------------------------------------------------------------------

    \180\ U.S. Food and Drug Administration website: https://www.accessdata.fda.gov/scripts/opdlisting/oopd/listResult.cfm.
---------------------------------------------------------------------------

    According to the applicant, the following ICD-10-PCS procedure 
codes may be used to identify administration of UPLIZNA[supreg] in the 
inpatient setting, though they are not specific to UPLIZNA[supreg]: 
3E033GC (Introduction of other therapeutic substance into the 
peripheral vein, percutaneous approach) or 3E043GC (Introduction of 
other therapeutic substance into central vein, percutaneous approach). 
Effective October 1, 2022, the following ICD-10-PCS procedure codes 
were created to uniquely describe the use of UPLIZNA[supreg]: XW03398 
(Introduction of inebilizumab-cdon into peripheral vein, percutaneous 
approach, new technology group 8) and XW04398 (Introduction of 
inebilizumab-cdon into central vein, percutaneous approach, new 
technology group 8).
    As previously discussed, if a technology meets all three of the 
substantial similarity criteria under the newness criterion, it would 
be considered substantially similar to an existing technology and would 
not be considered ``new'' for the purposes of new technology add-on 
payments. According to the applicant, the only approved treatments for 
NMOSD are UPLIZNA[supreg], Soliris[supreg] (eculizumab), and 
ENSPRYNGTM (satralizumab). We note that 
ENSPRYNGTM and Soliris[supreg] previously submitted 
applications for new technology add-on payments. Please see discussion 
of ENSPRYNGTM in the FY 2022 IPPS/LTCH PPS final rule (86 FR 
45019 through 45028) and Soliris[supreg] in the FY 2021 IPPS/LTCH PPS 
final rule (85 FR 58684 through 58689).
    With respect to the first criterion, whether a product uses the 
same or similar mechanism of action to achieve a therapeutic outcome, 
the applicant stated that UPLIZNA[supreg] is the only treatment for 
NMOSD that targets B-cells and causes B-cell depletion. The applicant 
contrasted the mechanism of action of UPLIZNA[supreg] with those of 
Soliris[supreg] and ENSPRYNGTM. Per the applicant, the 
mechanism of action of Soliris[supreg] is the inhibition of aquaporin-
4-antibody induced terminal complement C5b-9 deposition.\181\ The 
applicant explained that Soliris[supreg] specifically binds to 
complement protein C5, inhibiting its cleavage to C5a and C5b and 
preventing the generation of C5b-9. The applicant also stated that 
ENSPRYNGTM is a recombinant humanized anti-human 
interleukin-6 (IL-6) receptor monoclonal antibody. Per the applicant, 
the mechanism of action of ENSPRYNGTM involves the 
inhibition of IL-6-mediated signaling through binding to soluble and 
membrane-bound IL-6 receptors.\182\ Thus, the applicant asserted that 
each of the three FDA approved treatments for NMOSD--UPLIZNA[supreg], 
Soliris[supreg], and ENSPRYNGTM--bind to a different 
molecular target and have different mechanisms of action.
---------------------------------------------------------------------------

    \181\ U.S. Food and Drug Administration. (2019, June). Soliris 
Prescribing Information. Retrieved October 6, 2021, from https://www.accessdata.fda.gov/drugsatfda_docs/label/2019/125166s431lbl.pdf.
    \182\ Genentech. (2020, August). ENSPRYNG Factsheet. Retrieved 
October 6, 2021, from https://www.gene.com/download/pdf/genentech_enspryng_factsheet.pdf.
---------------------------------------------------------------------------

    With respect to the second criterion, whether a product is assigned 
to the same or a different MS-DRG when compared to an existing 
technology, the applicant stated that cases representing patients who 
may be eligible for treatment with UPLIZNA[supreg] map to MS-DRGs 058, 
059, or 060 (Multiple Sclerosis and Cerebellar Ataxia with MCC, with 
CC, or without CC/MCC, respectively), which are the same MS-DRGs to 
which existing technologies may also be assigned.
    With respect to the third criterion, whether the new use of 
technology involves the treatment of the same or similar type of 
disease and the same or similar patient population when compared to an 
existing technology, the applicant asserted that, while UPLIZNA[supreg] 
treats a patient population with the same type of disease (NMOSD) as 
Soliris[supreg] or ENSPRYNGTM, it offers a treatment option 
for a subset of this patient population, which differentiates it from 
existing technologies. Per the applicant, UPLIZNA[supreg] has not been 
shown to carry an increased risk of meningitis and may be used in 
patient populations who are unvaccinated with the meningococcal vaccine 
and/or are not able to use prophylactic antibiotics. The applicant 
noted that while patients with NMOSD who are unvaccinated with the 
meningococcal vaccine can still receive other approved treatments for 
NMOSD, such as Soliris[supreg] or ENSPRYNGTM, they need to 
have a risk reduction protocol instituted at the time of treatment and, 
in some cases, may require two weeks of prophylactic antibacterial 
treatment first.183 184
---------------------------------------------------------------------------

    \183\ Soliris[supreg] prescribing details: https://solirispro.com/pdf/Soliris_USPI.pdf.
    \184\ ENSPRYNGTM prescribing information: https://www.gene.com/download/pdf/enspryng_prescribing.pdf.
---------------------------------------------------------------------------

    In summary, the applicant maintained that UPLIZNA[supreg] is not 
substantially similar to other currently available therapies and/or 
technologies because it uses a new mechanism of action and treats a 
different subset of the patient population with NMOSD compared to an 
existing technology.
    In the proposed rule, we questioned whether the subset of the 
patient population with NMOSD--specifically, patients who are 
unvaccinated with the meningococcal vaccine--is considered a new 
patient population since, as previously discussed in the FY 2022 IPPS/
LTCH PPS final rule (86 FR 45021), ENSPRYNGTM is also not 
contraindicated in patients with unresolved serious Neisseria 
meningitidis infections, and therefore, may be a treatment option for 
patients with meningococcal disease as well as UPLIZNA[supreg]. 
Furthermore, as we previously stated in the FY 2022 IPPS/LTCH PPS final 
rule, individuals that are not vaccinated against Neisseria 
meningitidis are not considered a separate patient population because 
eligibility can be easily attained via a widely available vaccine (86 
FR 45027). Additionally, we questioned whether the additional 
requirements for patients taking Soliris[supreg]--namely participation 
in a risk reduction protocol related to the associated risk of 
meningococcal infections, and prophylactic antibiotic treatment that 
may result in a 2-week delay for treatment--constitute a new patient 
population for technologies without those requirements.
    We invited public comments on whether UPLIZNA[supreg] is 
substantially similar to existing technologies and whether 
UPLIZNA[supreg] meets the newness criterion.
    Comment: The applicant submitted a public comment regarding the 
newness criterion. With respect to the first criterion to determine 
newness, whether a product uses the same or similar mechanism of 
action, the applicant reiterated its assertion that UPLIZNA[supreg] has 
a novel mechanism of action which satisfies the newness criterion. The 
applicant stated that UPLIZNA[supreg] is the first and only B-cell 
depleting monotherapy approved for neuromyelitis optica spectrum 
disorder (NMOSD) in adult patients who are anti-aquaporin-4 antibody 
positive. The applicant explained that the mechanism of action of 
UPLIZNA[supreg] involves binding to CD19+ B-cells leading to antibody-
dependent, cell-mediated B-cell depletion. As a result, the applicant

[[Page 48956]]

stated UPLIZNA[supreg] reduces the damage caused to the optic nerve, 
spinal cord, and brain by NMOSD attacks, thus reducing cumulative 
damage and rates of disability.
    With respect to the third criterion to determine newness and our 
concern that patients who are unvaccinated with the meningococcal 
vaccine may not represent a new patient population for NMOSD, the 
applicant stated that in small populations such as those with rare 
diseases, special considerations such as vaccination status, prior 
therapies, drug interactions, or contraindications are important as 
certain nuances related to a particular treatment within these small 
populations can be uncovered, and providers must often choose one 
therapy over another due to specific patient attributes and health 
histories.
    Response: We appreciate the applicant's input and agree that 
UPLIZNA[supreg] has a unique mechanism of action when compared to 
existing technologies for treating NMOSD, as UPLIZNA[supreg] is the 
only CD19+ B-cell depleting monotherapy approved for NMOSD in adult 
patients who are anti-aquaporin-4 antibody positive, compared to 
Soliris[supreg] which specifically binds to complement protein C5, and 
ENSPRYNGTM which binds to soluble and membrane-bound IL-6 
receptors. However, we continue to believe that UPLIZNA[supreg] does 
not represent a treatment option for a new patient population. We 
stated in the FY 2022 IPPS/LTCH PPS final rule that individuals who are 
not vaccinated against Neisseria meningitidis are not considered a 
separate patient population because eligibility can easily be attained 
via a widely available vaccine (86 FR 45027). In addition, 
ENSPRYNGTM, another approved medication for the treatment of 
NMOSD, is also not contraindicated in patients with unresolved serious 
Neisseria meningitidis infections and therefore, may be a treatment 
option for patients with meningococcal disease along with 
UPLIZNA[supreg].
    Based on the comments received and the information submitted as 
part of the FY 2023 new technology add-on payment application for 
UPLIZNA[supreg], as discussed in the proposed rule (87 FR 28303 through 
28304) and in this final rule, we believe that UPLIZNA[supreg] has a 
unique mechanism of action and is not substantially similar to existing 
treatment options for NMOSD. While the applicant stated that it became 
commercially available on July 9, 2020, we believe that the beginning 
of the newness period for UPLIZNA[supreg] would be June 11, 2020, which 
is the date that UPLIZNA[supreg] received FDA marketing authorization, 
as the applicant did not provide documentation of a delay in commercial 
availability.
    With respect to the cost criterion, the applicant presented the 
following analysis. The applicant searched the FY 2019 Medicare 
Provider Analysis and Review (MedPAR) Hospital Limited Data Set (LDS) 
for cases with ICD-10-CM diagnosis code G36.0 for Neuromyelitis optica 
[Devic] (NMOSD) coded in the first diagnosis position. The applicant 
determined that cases representing patients who may be eligible for 
treatment with UPLIZNA[supreg] would map to MS-DRGs 058, 059, or 060 
(Multiple Sclerosis and Cerebellar Ataxia with MCC, with CC, or without 
CC/MCC, respectively).
    The applicant determined a case count of 257 after imputing a value 
of 11 for MS-DRGs with a case volume under 11. The applicant then 
removed 100% of the drug charges to estimate the potential decrease in 
costs due to the use of UPLIZNA[supreg]. The applicant noted that, 
although use of UPLIZNA[supreg] would replace current drug charges for 
therapies such as azathioprine, methotrexate, and rituximab, it is not 
possible to differentiate between drug costs on MedPAR claims, and so 
it removed all drug charges to be conservative. The applicant then 
standardized the charges and applied a 4-year inflation factor of 
1.281834, or 28.1834%, based on the inflation factor used to update the 
outlier threshold in the FY 2022 IPPS/LTCH PPS final rule (86 FR 
45542). The applicant added charges for the new technology by dividing 
the estimated cost of UPLIZNA[supreg] by the national average CCR for 
drugs which is 0.187, from the FY 2022 IPPS/LTCH PPS final rule (86 FR 
44966).
    The applicant calculated a final inflated average case-weighted 
standardized charge per case of $764,547, which exceeded the average 
case-weighted threshold amount of $48,165. Because the final inflated 
average case-weighted standardized charge per case exceeded the average 
case-weighted threshold amount, the applicant asserted that 
UPLIZNA[supreg] meets the cost criterion.
    We invited public comments on whether UPLIZNA[supreg] meets the 
cost criterion.
    We did not receive any comments on whether UPLIZNA[supreg] meets 
the cost criterion. Based on the information submitted by the applicant 
as part of its FY 2023 new technology add-on payment application for 
UPLIZNA[supreg], as discussed in the proposed rule (87 FR 28304) and 
previously summarized, the final inflated average case-weighted 
standardized charge per case exceeded the average case-weighted 
threshold amount. Therefore, UPLIZNA[supreg] meets the cost criterion.
    With regard to the substantial clinical improvement criterion, the 
applicant made two assertions. First, the applicant asserted that 
UPLIZNA[supreg] offers a treatment option for a patient population that 
is ineligible for currently available treatments. Specifically, the 
applicant asserted that UPLIZNA[supreg] is a new treatment option for 
patients who carry an increased risk of meningitis, patients following 
treatments with more frequent and burdensome dosing schedules, and 
patient populations more likely to be impacted by health disparities. 
Finally, the applicant asserted that UPLIZNA[supreg] significantly 
improves clinical outcomes relative to currently available technologies 
because it reduced the risk of NMOSD attacks and disability progression 
among patients with NMOSD when compared to placebo in the N-MOmentum 
trial, which the applicant asserted is the largest NMOSD study 
conducted.\185\
---------------------------------------------------------------------------

    \185\ Marignier, R. et al., (2021, March 26). Disability 
Outcomes in the N-MOmentum Trial of Inebilizumab in Neuromyelitis 
Optica Spectrum Disorder. Neurology[supreg] neuroimmunology & 
neuroinflammation. Retrieved October 6, 2021, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8054974/.
---------------------------------------------------------------------------

    With respect to the applicant's assertion that UPLIZNA[supreg] is a 
substantial clinical improvement over existing technologies because it 
represents a new treatment option for a patient population ineligible 
for currently available treatments, the applicant stated that 
UPLIZNA[supreg] may be used in patient populations who are unvaccinated 
with the meningococcal vaccine and/or are not able to use prophylactic 
antibiotics because UPLIZNA[supreg] has not been shown to carry an 
increased risk of meningitis, as compared with Soliris[supreg].
    To support this claim, the applicant cited an article from the CDC 
explaining that patients taking complement inhibitors, such as 
Soliris[supreg], are at an increased risk for meningococcal disease 
\186\ and referenced the CDC's recommendation that patients receive the 
meningococcal vaccination prior to initiating treatment with a 
complement inhibitor. The applicant also cited a

[[Page 48957]]

study by McNamara et al.\187\ that identified 16 cases in the U.S. 
between 2008 and 2016 of patients who were taking Soliris[supreg] who 
had meningococcal disease despite having received at least 1 dose of 
meningococcal vaccine before disease onset. Referring to the same 
article by McNamara et al., the applicant stated that some healthcare 
providers recommend prophylactic antibiotics even for vaccinated 
patients during treatment with Soliris[supreg], exposing them to long-
term antibiotic use, which carries the risk of developing antimicrobial 
resistance.
---------------------------------------------------------------------------

    \186\ Centers for Disease Control and Prevention. (2019, May 
31). Taking complement inhibitors increases risk for meningococcal 
disease/CDC. Centers for Disease Control and Prevention. Retrieved 
October 1, 2021, from https://www.cdc.gov/meningococcal/about/soliris-patients.html.
    \187\ McNamara, L. et al. (2017, July 7). High Risk for Invasive 
Meningococcal Disease Among Patients Receiving Eculizumab (Soliris) 
Despite Receipt of Meningococcal Vaccine. Retrieved October 6, 2021, 
from https://www.cdc.gov/mmwr/volumes/66/wr/pdfs/mm6627e1.pdf.
---------------------------------------------------------------------------

    Furthermore, the applicant claimed that UPLIZNA[supreg] represents 
a new treatment option for patients following treatments with more 
frequent and burdensome dosing schedules than UPLIZNA[supreg]. Per the 
applicant, the dosing schedule for UPLIZNA[supreg] consists of 2 
initial doses delivered 2 weeks apart, followed by 1 dose every 6 
months after that.\188\ In comparison, based on the FDA prescribing 
information for Soliris[supreg], the applicant asserted that 
UPLIZNA[supreg]'s 6-month dosing regimen is less frequent than that of 
Soliris[supreg], and, therefore, is less burdensome to follow.\189\ The 
applicant asserted the dosing schedule for UPLIZNA[supreg] is more 
amenable to NMOSD patients for whom more frequent intravenous infusions 
may be burdensome and stated that its characteristics as a treatment 
regimen, compared to SolirisTM, may help to improve 
medication adherence and decrease likelihood of relapse and 
hospitalization relative to placebo. To further demonstrate that 
UPLIZNA[supreg] may help to improve long-term patient adherence, 
compared to SolirisTM, the applicant provided a review by 
Vlasnik et al.\190\ noting that medication regimen complexity is one 
factor that can negatively affect adherence. The applicant emphasized 
that, for NMOSD, medication adherence to maintain immune suppression is 
essential for reducing the risk of attacks, which can lead to 
hospitalization, vision loss and paralysis. Finally, the applicant 
stated that UPLIZNA[supreg] poses less of a barrier for patient access, 
as it does not require patients or providers to participate in FDA's 
Risk Evaluation and Mitigation Strategy (REMS) program, or receive 
additional counselling regarding the program, as required by 
Soliris[supreg].\191\
---------------------------------------------------------------------------

    \188\ U.S. Food and Drug Administration. (2007, March). 
Highlights of prescribing information administration. Retrieved 
October 6, 2021, from https://www.accessdata.fda.gov/drugsatfda_docs/label/2007/125166lbl.pdf.
    \189\ U.S. Food and Drug Administration. Alexion briefing 
information for the November 18, 2014, meeting of the Drug Safety 
and Risk Management Advisory Committee. https://www.fda.gov/advisory-committees/human-drug-advisory-committees/drug-safety-and-risk-management-advisory-committee.
    \190\ Vlasnik, J. J., Aliotta, S. L., & DeLor, B. (2005, April 
7). Medication adherence: Factors influencing compliance with 
prescribed medication plans. The Case Manager. Retrieved October 6, 
2021, from https://www.sciencedirect.com/science/article/abs/pii/S1061925905000263?via%3Dihub.
    \191\ Alexion Pharmaceutical, Inc. (2020). Soliris REMS. 
Retrieved October 6, 2021, from https://solirisrems.com/.
---------------------------------------------------------------------------

    To support its claim that UPLIZNA[supreg] is a new treatment option 
for populations that are more likely to be impacted by health 
disparities, the applicant noted UPLIZNA[supreg]'s durable efficacy and 
favorable safety profile among African Americans with NMOSD. To support 
this claim, the applicant cited the safety results published by Cree et 
al.\192\ from both a randomized control period (RCP) and an open label 
period (OLP) of the N-MOmentum trial. The RCP phase of N-Momentum was a 
multicenter, double-blind, 2/3 study conducted at 99 outpatient 
specialty clinics or hospitals in 25 countries that lasted up to 197 
days. The primary endpoint was time to onset of an NMOSD attack, as 
determined by the investigator and adjudication committee. Eligible 
participants were randomized in a 3:1 ratio to receive either 300 mg 
intravenous UPLIZNA[supreg] (n=174) or a saline placebo (n=56) on days 
1 and 15. Participants continued through the RCP for up to 28 weeks 
unless they had a confirmed NMOSD attack, at which point they could 
choose to continue in the OLP phase of the trial. The OLP included 
eligible adult participants (n=230) who had had at least 1 NMOSD attack 
in the year before screening or at least 2 attacks requiring rescue 
therapy in the 2 years before screening. During the OLP, all patients 
received UPLIZNA[supreg] for at least 2 years. As recommended by an 
independent committee, enrollment in the RCP phase stopped prior to 
study completion due to the early findings where 21 of 174 participants 
(12%) receiving UPLIZNA[supreg] had an attack as compared with 22 of 
the 56 placebo recipients (39%). Marignier et al. (2021) assessed 
treatment effects in N-MOmentum by measuring score worsening of the 
Expanded Disability Status Scale (EDSS) and modified Rankin Scale (mRS) 
scores.\193\ EDSS scores were measured at baseline, then at RCP study 
weeks 12 and 28, and every 3 months during the OLP, and within 5 days 
of a potential attack. mRS scores were measured at baseline, and at 
weeks 4, 8, 12, 16, 22, and 28 of the RCP. The Marignier results from 
the N-MOmentum study found the annualized attack rate for African 
Americans was lower at 0.06 compared to an annualized attack rate of 
0.09 in the overall group exposed to UPLIZNA[supreg]. The applicant 
stated that among the 19 African American participants who received 
UPLIZNA[supreg] or placebo during the RCP and/or OLP of the N-MOmentum 
trial, three had attacks 18, 29, and 104 days after their first 
UPLIZNA[supreg] dose. The summary of baseline demographics and 
characteristics of the intent-to-treat population notes that there were 
14 African American participants who received UPLIZNA[supreg] and 5 who 
received the placebo.\194\
---------------------------------------------------------------------------

    \192\ Cree BAC, Bennett JL, Kim HJ, Weinshenker BG, Pittock SJ, 
Wingerchuk DM, Fujihara K, Paul F, Cutter GR, Marignier R, Green AJ, 
Aktas O, Hartung HP, Lublin FD, Drappa J, Barron G, Madani S, 
Ratchford JN, She D, Cimbora D, Katz E; N-MOmentum study 
investigators. Inebilizumab for the treatment of neuromyelitis 
optica spectrum disorder (N-MOmentum): a double-blind, randomised 
placebo-controlled phase 2/3 trial. Lancet. 2019 Oct 
12;394(10206):1352-1363. doi: 10.1016/S0140-6736(19)31817-3. Epub 
2019 Sep 5. PMID: 31495497.
    \193\ Marignier R, Bennett JL, Kim HJ, Weinshenker BG, Pittock 
SJ, Wingerchuk D, Fujihara K, Paul F, Cutter GR, Green AJ, Aktas O, 
Hartung HP, Lublin FD, Williams IM, Drappa J, She D, Cimbora D, Rees 
W, Smith M, Ratchford JN, Katz E, Cree BAC; N-MOmentum Study 
Investigators. Disability Outcomes in the N-MOmentum Trial of 
Inebilizumab in Neuromyelitis Optica Spectrum Disorder. Neurol 
Neuroimmunol Neuroinflamm. 2021 Mar 26;8(3):e978. doi: 10.1212/
NXI.0000000000000978. PMID: 33771837; PMCID: PMC8054974.
    \194\ Ibid.
---------------------------------------------------------------------------

    With respect to its claim that UPLIZNA[supreg] significantly 
improves clinical outcomes relative to previously available treatment 
options, the applicant stated that patients taking UPLIZNA[supreg] had 
a reduced risk of NMOSD attacks and disability progression when 
compared to placebo in the N-MOmentum trial. The applicant again 
referenced the results of the N-MOmentum trial reported by Cree et al., 
where 21 (12%) of the 174 participants receiving UPLIZNA[supreg] had an 
attack by the time enrollment ended versus 22 (39%) of the 56 
participants receiving placebo (hazard ratio (HR) 0[middot]272 [95% CI 
0[middot]150-0[middot]496]; p<0[middot]0001). The applicant also 
referred to the N-MOmentum results from the OLP and asserted that they 
show long-term treatment with UPLIZNA[supreg] provided a sustained 
reduction in NMOSD attack risk, MRI lesions, and NMOSD-related 
hospitalizations regardless of treatment provided during the RCP. The 
applicant

[[Page 48958]]

referenced the disability data published by Marignier et al.\195\ from 
the results of the N-MOmentum trial on the use of UPLIZNA[supreg] and 
asserted that they showed favorable results among patients with NMOSD 
when compared to placebo. Specifically, Marignier et al. assessed the 
treatment effects of UPLIZNA[supreg] in comparison with placebo by 
using a worsening score of the Expanded Disability Status Scale (EDSS) 
to measure confirmed disability progression (CDP). The applicant 
asserted that the results show UPLIZNA[supreg] reduced the risk of 3-
month CDP compared with placebo (HR: 0.375; 95% CI: 0.148-0.952; 
p=0.0390). The applicant also stated that UPLIZNA[supreg] showed a 
significantly lower risk of relapse among patients with NMOSD when 
compared to placebo. The applicant cited results from Pittock et 
al.,\196\ a randomized, double-blind, time-to-event trial in which 143 
adult subjects were randomly assigned to receive either UPLIZNA[supreg] 
or placebo weekly and continued use of an immunosuppressive therapy, as 
needed. The primary endpoint was the first adjudicated relapse, while 
secondary endpoints included the adjudicated annualized relapse rate. 
Pittock et al. reported that adjudicated relapses occurred in 3 of 96 
patients (3%) in the UPLIZNA[supreg] group and 20 of 47 (43%) in the 
placebo group (hazard ratio 0.06; 95% confidence interval [CI], 0.02 to 
0.20; P<0.001). The adjudicated annualized relapse rate was 0.02 in the 
eculizumab group and 0.35 in the placebo group (rate ratio, 0.04; 95% 
CI, 0.01 to 0.15; P<0.001). Referring to the results from the Pittock 
et al. study, the applicant asserted that UPLIZNA[supreg] showed a 
consistent effect in reducing the risk of attack compared to placebo, 
regardless of baseline disability status, attack history, or disease 
duration.\197\
---------------------------------------------------------------------------

    \195\ Marignier R, Bennett JL, Kim HJ, Weinshenker BG, Pittock 
SJ, Wingerchuk D, Fujihara K, Paul F, Cutter GR, Green AJ, Aktas O, 
Hartung HP, Lublin FD, Williams IM, Drappa J, She D, Cimbora D, Rees 
W, Smith M, Ratchford JN, Katz E, Cree BAC; N-MOmentum Study 
Investigators. Disability Outcomes in the N-MOmentum Trial of 
Inebilizumab in Neuromyelitis Optica Spectrum Disorder. Neurol 
Neuroimmunol Neuroinflamm. 2021 Mar 26;8(3): e978. doi: 10.1212/
NXI.0000000000000978. PMID: 33771837; PMCID: PMC8054974.
    \196\ Pittock SJ, Berthele A, Fujihara K, Kim HJ, Levy M, Palace 
J, Nakashima I, Terzi M, Totolyan N, Viswanathan S, Wang KC, Pace A, 
Fujita KP, Armstrong R, Wingerchuk DM. Eculizumab in Aquaporin-4-
Positive Neuromyelitis Optica Spectrum Disorder. N Engl J Med. 2019 
Aug 15;381(7):614-625. doi: 10.1056/NEJMoa1900866. Epub 2019 May 3. 
PMID: 31050279.
    \197\ Ibid.
---------------------------------------------------------------------------

    In the proposed rule, we stated we had the following concerns 
regarding whether UPLIZNA[supreg] meets the substantial clinical 
improvement criterion. First, we noted that while the applicant 
provided data comparing UPLIZNA[supreg] to placebo, we did not receive 
any data to demonstrate improved outcomes over existing FDA approved 
treatments. We stated that additional information comparing outcomes 
such as relapse rate, risk of relapse, and disability progression for 
patients receiving UPLIZNA[supreg] versus other currently available 
treatments would help inform our assessment of whether UPLIZNA[supreg] 
demonstrates a substantial clinical improvement over existing 
technologies. Second, while the applicant asserted that UPLIZNA[supreg] 
represents a new treatment option for patients who are unvaccinated 
with the meningococcal vaccine, similar to the discussion in the FY 
2022 IPPS/LTCH PPS final rule (86 FR 45021) in response to a similar 
assertion with respect to ENSPRYNGTM, we noted that 
ENSPRYNG[supreg] is also not contraindicated in patients with 
unresolved serious Neisseria meningitidis infection and therefore may 
also be a treatment option for patients with meningococcal disease. We 
further noted that the use of ENSPRYNGTM to treat patients 
with NMOSD does not require a meningococcal vaccination. We noted that 
the applicant sought to support its claim that UPLIZNA[supreg] 
represents a new treatment option for patients who are unvaccinated 
against Neisseria meningitidis through the inference that 
Soliris[supreg] has a high risk of causing meningitis; however, as 
stated in the proposed rule, we had concerns about the applicant's 
claim because Neisseria meningitidis may easily be mitigated through 
the use of a common vaccine or antimicrobials. As discussed in the FY 
2022 IPPS/LTCH PPS final rule in response to similar claims with 
respect to ENSPRYNG[supreg], and as noted previously, individuals that 
are not vaccinated against Neisseria mengitidis are not considered a 
separate patient population because eligibility can be easily attained 
via a widely available vaccine and are also able to receive treatment 
with UPLIZNA[supreg] which does not require a vaccine (86 FR 45027).
    With regard to the applicant's claim that UPLIZNA[supreg] is a new 
treatment option for patients following treatments with more frequent 
dosing schedules, we stated in the proposed rule that we are unsure 
whether these patients may be considered as a separate patient 
population ineligible for currently available treatments. For example, 
although the applicant compared the UPLIZNA[supreg] dosing regimen 
against Soliris[supreg], it did not provide a similar comparison 
against ENSPRYNGTM, which--similar to UPLIZNA[supreg]--does 
not require frequent intravenous infusions or participation in the FDA 
REMS program (see 86 FR 45020). Therefore, we stated that it is unclear 
whether UPLIZNA[supreg] provides a treatment option for a separate 
patient population that is ineligible for currently available 
treatments, when there are other available treatments, like 
ENSPRYNGTM, without the limitations that the applicant 
described with respect to Soliris[supreg]. In addition, while the 
applicant stated that UPLIZNA's[supreg] dosing regimen may help to 
improve long-term patient medication adherence and decrease the 
likelihood of relapse and hospitalization, we questioned the strength 
of the correlation between UPLIZNA's[supreg] dosing regimen and these 
outcomes. We stated our interest in additional information on the 
efficacy results of UPLIZNA[supreg] among African Americans with NMOSD, 
as cited by the applicant, as we understand that NMOSD 
disproportionately affects African American and Asian populations at 
rates approximately 2- to 3-fold higher than their Caucasian 
counterparts.\198\ Specifically, we questioned whether the 
retrospective analysis of the results from the N-MOmentum trial on the 
annualized attack rate for African Americans (0.06 compared with 0.09 
in the overall group) is generalizable to larger populations because 
the study included low numbers of participants. Of the 20 African 
American participants randomized in N-Momentum, 19 were AQP4 antibody 
positive and 1 was AQP4 antibody negative. As a result, of the 19 
participants, 14 received UPLIZNA[supreg], and only 5 received 
placebo.199 200 We further noted that the applicant did not 
provide comparative data on the efficacy of UPLIZNA[supreg],

[[Page 48959]]

Soliris[supreg], and ENSPRYNGTM in these populations.
---------------------------------------------------------------------------

    \198\ Flanagan, E.P. et al. (2016, April 4). Epidemiology of 
aquaporin[hyphen]4 autoimmunity and Neuromyelitis Optica Spectrum. 
Wiley Online Library. Retrieved October 6, 2021, from https://onlinelibrary.wiley.com/doi/10.1002/ana.24617.
    \199\ Bernitsas, E., Cimbora, D., Dinh, Q., She, D., Katz, E. 
Safety and Efficacy of Inebilizumab in African Americans with 
Neuromyelitis Optica Spectrum Disorder. Poster presentation at the 
15th World Congress on Controversies in Neurology (CONy Virtual). 
September 23-26, 2021.
    \200\ Cree BAC, Bennett JL, Kim HJ, Weinshenker BG, Pittock SJ, 
Wingerchuk DM, Fujihara K, Paul F, Cutter GR, Marignier R, Green AJ, 
Aktas O, Hartung HP, Lublin FD, Drappa J, Barron G, Madani S, 
Ratchford JN, She D, Cimbora D, Katz E; N-MOmentum study 
investigators. Inebilizumab for the treatment of neuromyelitis 
optica spectrum disorder (N-MOmentum): a double-blind, randomised 
placebo-controlled phase 2/3 trial. Lancet. 2019 Oct 
12;394(10206):1352-1363. doi: 10.1016/S0140-6736(19)31817-3. Epub 
2019 Sep 5. PMID: 31495497.
---------------------------------------------------------------------------

    We invited public comments on whether UPLIZNA[supreg] meets the 
substantial clinical improvement criterion.
    Comment: We received several comments in support of new technology 
add-on payments for UPLIZNA[supreg], including one from the applicant, 
in response to CMS' concerns in the proposed rule. With respect to the 
concern regarding the lack of data comparing UPLIZNA[supreg] to 
existing FDA-approved treatments, the applicant stated that conducting 
head-to-head trials is often not possible when studying rare diseases 
due to the small patient populations and potential delays if trials for 
the same indication are running simultaneously. The applicant noted 
that the timing and availability of Soliris[supreg] and 
ENSPRYNGTM (approved by FDA on June 27, 2019 and August 17, 
2020, respectively) did not allow for comparative trials, as there were 
no approved medications for the treatment of NMOSD for the entirety of 
the N-MOmentum study. The applicant stated that CMS has granted new 
technology add-on payments in situations where comparative head-to-head 
trials were not available, referencing two technologies without 
comparative clinical data that were granted new technology add-on 
payments in FY 2019 and FY 2022, as well as two additional examples 
from FY 2022 that were both FDA-approved based on the results of 
single-arm clinical trials. We note that the applicant did not identify 
the specific technologies. The applicant stated that, because these 
products were granted new technology add-on payments without direct 
comparative data with their respective clinical competitors, that 
substantial clinical improvement can be ascertained through product 
attributes and randomized clinical trial outcomes in the absence of 
direct, comparative head-to-head trials.
    With respect to the concern regarding the lack of data 
demonstrating improved outcomes over existing FDA approved treatments, 
the applicant noted that N-MOmentum is the largest-ever clinical trial 
conducted in patients with NMOSD, the results of which showed that 
patients taking UPLIZNA[supreg] experienced fewer relapses and fewer 
hospitalizations than patients on placebo. The applicant stated that 
compared with placebo, patients treated with UPLIZNA[supreg] had a 
reduced risk of 3-month EDSS-confirmed disability progression (CDP). 
The applicant also noted that although disability outcomes data cannot 
be compared across therapies, other therapies' disability data were 
studied using different endpoints as secondary measures and/or were not 
reported because of lack of statistical significance. The applicant 
referred to the PREVENT trial for Soliris[supreg], which studied EDSS 
and mRS as secondary outcome measures up to 211 weeks and noted that 
there was no significant difference in disability progression between 
the Soliris[supreg] groups and placebo. The applicant also referred to 
the SakuraStar and SakuraSky trials for ENSPRYNG and noted that no 
significant effect on disability was observed. In contrast, the 
applicant stated that UPLIZNA[supreg] showed a consistent effect in 
reducing the risk of disability worsening compared to placebo, 
regardless of baseline disability status, attack history, or disease 
duration. The applicant asserted that despite head-to-head studies not 
being possible at the time registrational trials were conducted, the 
data and efficacy and clinical efficiency attributes of UPLIZNA[supreg] 
present an improvement for patients over other therapies.
    In response to CMS' feedback regarding the comparison of dosing and 
long-term adherence to other available treatments for NMOSD, the 
applicant confirmed it had provided details of dosing for 
Soliris[supreg] in its application and included dosing details for 
ENSPRYNGTM in its comments, noting that 
ENSPRYNGTM requires more frequent administration than 
UPLIZNA[supreg]. The applicant referenced long-term adherence data 
showing that UPLIZNA[supreg] adherence was approximately 85% after two 
years. The applicant stated that the improved medication adherence data 
from analogue disease states suggest that twice yearly dosing, as with 
UPLIZNA[supreg], is associated with improved adherence over other 
regimens. The applicant also stated that the data suggest that 
adherence and persistence to therapy may lead to improved clinical 
outcomes.
    In addition, the applicant extrapolated results from a 
retrospective claims analysis looking at the use of MS disease-
modifying therapies (DMTs) that concluded that a twice-yearly dosing 
schedule achieved superior adherence and persistence at 12, 18, and 24 
months versus other dosing regimens or routes of administration. Other 
commenters also mentioned the convenient dosing schedule of 
UPLIZNA[supreg], which potentially simplifies the lives of NMOSD 
patients and thereby improves compliance, which they noted is critical 
for the prevention of disease relapse and for ensuring good patient 
outcomes.
    The applicant noted that persistence and adherence to a therapy 
such as UPLIZNA[supreg] are important to achieving positive clinical 
outcomes, and reiterated that studies have shown that relapses can lead 
to hospitalizations, long-term disability, and permanent harm to the 
patient. According to a commenter, administration of UPLIZNA[supreg] in 
the hospital setting, immediately after diagnosis and acute treatment 
of the relapse can be life saving for the patient, as early treatment 
leads to better outcomes and reduces relapse rate and subsequent 
disability. Commenters emphasized the potential for permanent damage 
related to relapses of NMOSD and therefore the importance of timely 
treatment to prevent relapse.
    The applicant also responded to CMS' question regarding the 
generalizability of the retrospective analysis of the efficacy results 
of UPLIZNA[supreg] among Black/African American patients with NMOSD, 
which the applicant provided to support its claim that UPLIZNA[supreg] 
is a new treatment option for populations that are more likely to be 
impacted by health disparities. NMOSD disproportionately affects Black/
African American and Asian populations at rates approximately 2-to 3-
fold higher than Caucasians. As noted in its application, the applicant 
stated that the annualized attack rates for Black/African American 
participants observed in the N-MOmentum study were promising, despite 
the relatively low number of participants in the study. The applicant 
noted that the FDA Statistical Review of UPLIZNA[supreg] confirmed that 
the applicant could report subgroup analyses based on sex, race, age, 
and region and these data suggest that UPLIZNA[supreg] is at least as 
effective in the Black/African American subpopulation as it is in the 
general patient population. The applicant noted the difficulty of 
enrolling large numbers of patients in studies for rare conditions, and 
stated that subgroup data provided can still represent important 
considerations in identifying a benefit in populations that face 
disproportionately higher rates of NMOSD. As is often the case with 
rare diseases such as NMOSD, relatively small numbers of participants 
result in small subpopulations; however, the applicant noted, 
interpreting results in small subgroups must be done cautiously.
    Response: We thank the commenters for their input. After further 
review, we continue to have concerns as to whether UPLIZNA[supreg] 
meets the substantial clinical improvement criterion to be approved for 
new technology add-on payments. We agree with the

[[Page 48960]]

commenters that timely treatment for relapse prevention in NMOSD is 
important. However, it is unclear whether UPLIZNA[supreg] leads to 
improved relapse prevention, or other improved outcomes, as compared to 
other available treatments for NMOSD. We note that the applicant did 
not provide data comparing outcomes such as time to first relapse and 
number of relapses with Soliris[supreg] or UPLIZNA[supreg]. We further 
note that the applicant stated that, of the available therapies, only 
UPLIZNA[supreg] demonstrated a statistically significant effect on 
disability progression compared to placebo in its clinical trial. 
However, as the applicant noted, there were differences between the 
trials, including size of the trials and disability endpoints assessed. 
We believe this makes it difficult to demonstrate superior effect on 
disability progression, especially without a comparison of relapse 
rates, with which disability is associated. We also note that time-to-
first-relapse is one endpoint that was consistent across all three 
trials, and that the results of a meta analysis comparing published 
efficacy outcomes for Soliris[supreg], UPLIZNA[supreg], and 
ENSPRYNGTM showed that Soliris[supreg] demonstrated greater 
efficacy in prolonging time-to-relapse compared to UPLIZNA[supreg] and 
ENSPRYNGTM.\201\ While we agree with the applicant that substantial 
clinical improvement can be determined without head-to-head trials, we 
note that we evaluate every application on its own data and merits to 
determine whether it meets the new technology add-on payment criterion 
for substantial clinical improvement, and we consider variations in the 
currently available technologies that an applicant technology is 
compared against for the purposes of determining whether the technology 
represents a substantial clinical improvement over existing 
technologies. We further note that it is unclear which technologies the 
applicant is referring to in stating that CMS has previously approved 
new technology add-on payments for technologies without a demonstration 
of comparative outcomes.
---------------------------------------------------------------------------

    \201\ Wingerchuck, et al. Indirect comparison analysis of FDA-
approved treatment options for adults with aquaporin-4 
immunoglobulin G-positive neuromyelitis optica spectrum disorder.
---------------------------------------------------------------------------

    Furthermore, with regard to improved adherence, while the applicant 
provided information regarding UPLIZNA[supreg] adherence, it did not 
compare these values to adherence for other therapies and therefore 
this information does not support a finding of substantial clinical 
improvement. Lastly, the retrospective claims analysis the applicant 
provided to support a correlation between long-term medication 
adherence and decreased relapse and hospitalization assessed the 
adherence and persistence of multiple sclerosis patients treated with a 
drug that had the same dosing regimen as UPLIZNA[supreg]--but not NMOSD 
patients treated with UPLIZNA[supreg].
    After review of the information submitted by the applicant as part 
of its FY 2023 new technology add-on payment application for 
UPLIZNA[supreg] and consideration of the comments received, we are 
unable to determine that UPLIZNA[supreg] meets the substantial clinical 
improvement criterion for the reasons discussed in the proposed rule 
and in this final rule, and therefore we are not approving new 
technology add-on payments for UPLIZNA[supreg] for FY 2023.
7. FY 2023 Applications for New Technology Add-On Payments (Alternative 
Pathways)
    As discussed previously, beginning with applications for FY 2021, 
under the regulations at Sec.  412.87(c), a medical device that is part 
of FDA's Breakthrough Devices Program and has received marketing 
authorization for the indication covered by the Breakthrough Device 
designation may qualify for the new technology add-on payment under an 
alternative pathway. Additionally, beginning with FY 2021, under the 
regulations at Sec.  412.87(d), a medical product that is designated by 
FDA as a QIDP and has received marketing authorization for the 
indication covered by the QIDP designation, and, beginning with FY 
2022, a medical product that is a new medical product approved under 
FDA's LPAD and used for the indication approved under the LPAD pathway, 
may also qualify for the new technology add-on payment under an 
alternative pathway. Under an alternative pathway, a technology will be 
considered not substantially similar to an existing technology for 
purposes of the new technology add-on payment under the IPPS and will 
not need to meet the requirement that it represents an advance that 
substantially improves, relative to technologies previously available, 
the diagnosis or treatment of Medicare beneficiaries. These 
technologies must still be within the 2-3 year newness period to be 
considered ``new,'' and must also still meet the cost criterion. We 
refer readers to section II.H.8. of the preamble of the FY 2020 IPPS/
LTCH PPS final rule (84 FR 42292 through 42297) and section II.F.6 of 
preamble of the FY 2021 IPPS/LTCH PPS final rule (85 FR 58715 through 
58733) for further discussion of the alternative new technology add-on 
payment pathways for these technologies.
    We note, section 1886(d)(5)(K)(ii)(II) of the Act provides for the 
collection of data with respect to the costs of a new medical service 
or technology described in subclause (I) for a period of not less than 
2 years and not more than 3 years beginning on the date on which an 
inpatient hospital code is issued with respect to the service or 
technology. Our regulations in Sec.  412.87(c)(2) for breakthrough 
devices and Sec.  412.87(d)(2) for certain antimicrobial products state 
that a medical device/product that meets the condition in paragraph 
(c)(1) or (d)(1) of Sec.  412.87 will be considered new for not less 
than 2 years and not more than 3 years after the point at which data 
begin to become available reflecting the inpatient hospital code (as 
defined in section 1886(d)(5)(K)(iii) of the Act) assigned to the new 
technology (depending on when a new code is assigned and data on the 
new technology become available for DRG recalibration). After CMS has 
recalibrated the DRGs, based on available data, to reflect the costs of 
an otherwise new medical technology, the medical technology will no 
longer be considered ``new'' under the criterion of this section.
    We received 19 applications for new technology add-on payments for 
FY 2023 under the new technology add-on payment alternative pathways. 
Six applicants withdrew applications prior to the issuance of the 
proposed rule. Subsequently, five applicants withdrew their respective 
applications for LigaPASS 2.0 PJK Prevention System, Magnus 
Neuromodulation System with SAINT Technology, the Precision 
TAVITM Coronary Module, the TOPSTM System, and 
the VITARIA[supreg] System prior to the issuance of this final rule. 
Two applicants, Phagenesis Ltd. (the applicant for Phagenyx[supreg] 
System) and Neuro Event Labs, Inc. (the applicant for the Nelli[supreg] 
Seizure Monitoring System), did not meet the July 1 deadline for FDA 
approval or clearance of the technology and, therefore, the 
technologies are not eligible for consideration for new technology add-
on payments for FY 2023. A discussion of the remaining 6 applications 
is presented in this final rule, including 5 technologies that have 
received a Breakthrough Device designation from FDA and 1 that was 
designated as a QIDP by FDA.
    In accordance with the regulations under Sec.  412.87(e)(2), 
applicants for new technology add-on payments, including Breakthrough 
Devices, must have FDA marketing authorization by July 1 of the

[[Page 48961]]

year prior to the beginning of the fiscal year for which the 
application is being considered. Under the policy finalized in the FY 
2021 IPPS/LTCH PPS final rule (85 FR 58742), we revised the regulations 
at Sec.  412.87(e) by adding a new paragraph (e)(3) which provides for 
conditional approval for a technology for which an application is 
submitted under the alternative pathway for certain antimicrobial 
products (QIDPs and LPADs) at Sec.  412.87(d) that does not receive FDA 
marketing authorization by the July 1 deadline specified in Sec.  
412.87(e)(2), provided that the technology receives FDA marketing 
authorization by July 1 of the particular fiscal year for which the 
applicant applied for new technology add-on payments. We refer the 
reader to the FY 2021 IPPS/LTCH PPS final rule for a complete 
discussion of this policy (85 FR 58737 through 58742).
    As we did in the FY 2022 IPPS/LTCH PPS proposed rule, for 
applications under the alternative new technology add-on payment 
pathway, in the FY 2023 IPPS/LTCH PPS proposed rule, we proposed to 
approve or disapprove each of these six applications for FY 2023 new 
technology add-on payments. Therefore, in this section of the preamble 
of this final rule, we provide background information on each of the 
remaining six alternative pathway applications and our determinations 
as to whether or not each technology is eligible for new technology 
add-on payments for FY 2023. Consistent with our standard approach, we 
are not including in this final rule the description and discussion of 
applications that were withdrawn or that are ineligible for 
consideration for FY 2023 due to not meeting the July 1 deadline, 
described previously, which were included in the FY 2023 IPPS/LTCH PPS 
proposed rule. We are also not summarizing nor responding to public 
comments received regarding these withdrawn or ineligible applications 
in this final rule.
a. Alternative Pathway for Breakthrough Devices
(1) CERAMENT[supreg] G
    BONESUPPORT AB submitted an application for new technology-add on 
payments for CERAMENT[supreg] G for FY 2023. Per the applicant, 
CERAMENT[supreg] G is an injectable bone-void filler made of calcium 
sulfate, hydroxyapatite, and gentamicin sulfate indicated for the 
surgical treatment of osteomyelitis. Per the applicant, this bone graft 
substitute fills gaps resulting from debridement of infected bone and 
prevents colonization of sensitive bacteria, promoting bone healing in 
two ways. The applicant stated that the primary mode of action is for 
CERAMENT[supreg] G to act as a resorbable ceramic bone-void filler 
intended to fill gaps and voids in the skeleton system created when 
infected bone is debrided. The applicant also stated that the secondary 
mode of action is to prevent the colonization of gentamicin-sensitive 
microorganisms in order to protect bone healing. Per the applicant, 
CERAMENT[supreg] G may eliminate the need to harvest autologous bone, 
avoiding pain and infection at the donor site. We note that BONESUPPORT 
Inc. previously submitted an application for new technology add-on 
payments for CERAMENT[supreg] G for FY 2022, as summarized in the FY 
2022 IPPS/LTCH PPS proposed rule (86 FR 25368 through 25373) but the 
technology did not meet the deadline of July 1, 2021, for FDA approval 
or clearance of the technology and, therefore, was not eligible for 
consideration for new technology add-on payments for FY 2022 (86 FR 
45126 through 45127).
    According to the applicant, CERAMENT[supreg] G is designated as a 
Breakthrough Device for use as a bone-void filler as an adjunct to 
systemic antibiotic therapy and surgical debridement as part of the 
surgical treatment of osteomyelitis. The technology received FDA De 
Novo marketing authorization on May 17, 2022 with an indication for use 
as a bone void filler in skeletally mature patients as an adjunct to 
systemic antibiotic therapy and surgical debridement (standard 
treatment approach to a bone infection) as part of the surgical 
treatment of osteomyelitis in defects in the extremities. The applicant 
applied for and received a unique ICD-10-PCS procedure code to identify 
cases involving the administration of CERAMENT[supreg] G in 2021. 
Effective October 1, 2021, CERAMENT[supreg] G administration can be 
identified by ICD-10-PCS procedure code XW0V0P7 (Introduction of 
antibiotic eluting bone void filler into bones, open approach, new 
technology group 7), which is unique to CERAMENT[supreg] G 
administration. The applicant stated that the following existing ICD-
10-CM codes for osteomyelitis appropriately describe the proposed 
indication for which the device received Breakthrough Device 
designation (``Breakthrough Device Indication''):
[GRAPHIC] [TIFF OMITTED] TR10AU22.090

    With respect to the cost criterion, the applicant identified 
candidate cases using ICD-10-PCS procedure and ICD-10-CM diagnosis 
codes, which are detailed in the tables in this section. With these 
codes identified, the applicant then went through the Grouper logic in 
the MS-DRG v39.0 Definitions Manual and located where cases with these 
codes would be assigned in the MS-DRG system. This process yielded 13 
MS-DRGs which the applicant used for their analysis. The applicant also 
submitted an additional subanalysis using only cases from the 
applicant's top three identified MS-DRGs (464, 493, and 504), to 
demonstrate that the technology meets the cost criterion.
    Under the first analysis, the applicant searched claims in the FY 
2019

[[Page 48962]]

MedPAR final rule dataset within the 13 identified MS-DRGs that 
reported one of the M86 ICD-10-CM diagnosis codes listed previously in 
combination with the ICD-10-PCS procedure codes listed in the following 
table, which identify procedures that could involve the use of 
CERAMENT[supreg] G as an adjunct to systemic antibiotic therapy and 
surgical debridement where there is a need for supplemental bone void 
filler material.
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TR10AU22.091


[[Page 48963]]


[GRAPHIC] [TIFF OMITTED] TR10AU22.092


[[Page 48964]]


[GRAPHIC] [TIFF OMITTED] TR10AU22.093


[[Page 48965]]


[GRAPHIC] [TIFF OMITTED] TR10AU22.094

    The applicant identified 11,620 cases across 13 MS-DRGs as 
identified in the table that follows:
[GRAPHIC] [TIFF OMITTED] TR10AU22.095

BILLING CODE 4120-01-C
    The applicant noted that candidate cases for CERAMENT[supreg] G 
with osteomyelitis would qualify for the CC/MCC MS-DRGs because 
osteomyelitis is listed in the Grouper as a CC condition. Therefore, 
the applicant concluded that cases with osteomyelitis would not be 
grouped in the uncomplicated MS-DRGs (for example, 465, 494, etc.). The 
applicant stated that because osteomyelitis is never assigned to 
uncomplicated surgical MS-DRGs, it excluded uncomplicated MS-DRGs from 
its analysis.
    The applicant then removed charges for the prior technology that 
may be replaced by CERAMENT[supreg] G. The applicant conducted a market 
analysis that identified 3 types of prior technology devices: 
Poly(methyl methacrylate) (PMMA) manually mixed with antibiotics, PMMA 
pre-loaded with antibiotics, and calcium sulfate (CaS) mixed with 
antibiotics. The applicant researched the average sales price (ASP) for 
major competitors for 5cc and 10cc of each device type and calculated a 
weighted average cost of $444 per 5cc and $727 per 10cc.\202\ Then the 
applicant converted costs to charges by dividing costs by the Supplies 
&

[[Page 48966]]

Equipment CCR of 0.297 (86 FR 44966). Using this CCR, $444 per 5cc and 
$727 per 10cc yielded an estimated hospital charge of prior 
technologies of $1,495 per 5cc and $2,449 per 10cc. The applicant 
explained that the total amount of antibiotics depends on the amount of 
product required for different sized bones. The applicant then 
standardized the charges and applied a 4-year inflation factor of 
1.281834 based on the inflation factor used to update the outlier 
threshold in the FY 2022 IPPS/LTCH PPS final rule (86 FR 45542).
---------------------------------------------------------------------------

    \202\ The applicant's analysis was informed by 2019 and 2020 
data for Osteoset, Stimulan, and Calcigen S (calcium sulfates mixed 
with antibiotics), Palacos, Cobalt (PMMA manually mixed with 
antibiotics), Cobalt G, Biomet Bone Cement R, and Refobacin Bone 
Cement R (PMMA pre-loaded with antibiotics) from three sources: an 
iData Market Research 2019 Sku Data Report, Global Data US Hospital 
Bone Grafts and Substitutes Q3 2019 Report, and feedback from sales 
representatives in the field.
---------------------------------------------------------------------------

    The applicant added estimated charges for the new technology by 
dividing the estimated, expected hospital list price for the device 
(based on expected 5/10/15 cc costs for CERAMENT[supreg] G, by MS-DRG), 
by the aforementioned Supplies & Equipment CCR of 0.297.
    The applicant calculated a final inflated case-weighted average 
standardized charge per case of $135,258 and an average case-weighted 
threshold of $86,603. Because the final inflated average case-weighted 
standardized charge per case exceeded the average case-weighted 
threshold amount, the applicant asserted that the technology meets the 
cost criterion.
    The applicant also provided an alternate cost analysis using the 
applicant's top three identified MS-DRGs (464, 493, and 504), which 
together constituted more than half of the applicant's identified 
cases. Using the same methodology and data sources noted previously, 
the applicant calculated a final inflated case-weighted average 
standardized charge per case of $112,316 and an average case-weighted 
threshold of $77,375. The applicant maintained that CERAMENT[supreg] G 
meets the cost criterion under this alternate analysis.
    We stated in the proposed rule that we agree with the applicant 
that CERAMENT[supreg] G meets the cost criterion and therefore, subject 
to the technology receiving FDA marketing authorization for use as a 
bone-void filler as an adjunct to systemic antibiotic therapy and 
surgical debridement as part of the surgical treatment of osteomyelitis 
by July 1, 2022, we proposed to approve CERAMENT[supreg] G for new 
technology add-on payments for FY 2023.
    Based on preliminary information from the applicant at the time of 
the proposed rule, the total cost of CERAMENT[supreg] G for a typical 
patient was determined to be $7,567 per procedure. Per the applicant, 
the amount of CERAMENT[supreg] G used per patient depends on the 
complexity of the patient's injury, subsequent comorbidities, as well 
as the location and size of the bone void. The applicant expects that 
an average patient will require ~10cc per procedure, based on the case 
weighted volume of expected utilization across the MS-DRGs. From this 
weighted average, the applicant derived the average, weighted cost of 
$7,567 per patient. We noted that the cost information for this 
technology may be updated in the final rule based on revised or 
additional information CMS receives prior to the final rule. Under 
Sec.  412.88(a)(2), we limit new technology add-on payments to the 
lesser of 65% of the average cost of the technology, or 65% of the 
costs in excess of the MS-DRG payment for the case. As a result, we 
proposed that the maximum new technology add-on payment for a case 
involving the use of the product CERAMENT[supreg] G would be $4,918.55 
for FY 2022 (that is, 65% of the average cost of the technology).
    We invited public comments on whether CERAMENT[supreg] G meets the 
cost criterion and our proposal to approve new technology add-on 
payments for CERAMENT[supreg] G for FY 2023, subject to 
CERAMENT[supreg] G receiving FDA marketing authorization for use as a 
bone-void filler as an adjunct to systemic antibiotic therapy and 
surgical debridement as part of the surgical treatment of osteomyelitis 
by July 1, 2022.
    Comment: We received a public comment urging CMS to finalize its 
proposals to approve new technology add-on payments for multiple 
technologies for FY 2023, including CERAMENT G[supreg], in order to 
foster innovation and make life and ability-saving devices more readily 
available to patients.
    Response: We appreciate the comment.
    Based on the information provided in the application for new 
technology add-on payments, we believe CERAMENT[supreg] G meets the 
cost criterion. The technology received FDA De Novo marketing 
authorization on May 17, 2022 with an indication for use as a bone void 
filler in skeletally mature patients as an adjunct to systemic 
antibiotic therapy and surgical debridement (standard treatment 
approach to a bone infection) as part of the surgical treatment of 
osteomyelitis in defects in the extremities, that is covered by its 
Breakthrough Device designation. Therefore, we are finalizing our 
proposal to approve new technology add-on payments for CERAMENT[supreg] 
G for FY 2023. We consider the beginning of the newness period to 
commence on May 17, 2022, the date on which the technology received its 
FDA De Novo marketing authorization for the indication covered by its 
Breakthrough Device designation.
    Based on the information available at the time of this final rule, 
the cost per case of CERAMENT[supreg] G is $7,567.00. Under Sec.  
412.88(a)(2), we limit new technology add-on payments to the lesser of 
65% of the average cost of the technology, or 65% of the costs in 
excess of the MS-DRG payment for the case. As a result, we are 
finalizing that the maximum new technology add-on payment for a case 
involving the use of CERAMENT[supreg] G is $4,918.55 for FY 2023 (that 
is, 65% of the average cost of the technology). Cases involving the use 
of CERAMENT[supreg] G that are eligible for new technology add-on 
payments will be identified by ICD-10-PCS procedure code XW0V0P7 
(Introduction of antibiotic-eluting bone void filler into bones, open 
approach, new technology group 7).
(2) GORE[supreg] TAG[supreg] Thoracic Branch Endoprosthesis (TBE 
Device)
    W.L. Gore and Associates, Inc., submitted an application for new 
technology add-on payments for the GORE[supreg] TAG[supreg] Thoracic 
Branch Endoprosthesis (TBE) device for FY 2023. According to the 
applicant, the GORE[supreg] TAG[supreg] TBE device is a modular device 
consisting of three components, an Aortic Component, a Side Branch 
Component, and an optional Aortic Extender Component, each of which is 
pre-mounted on a catheter delivery system for treatment of thoracic 
aortic aneurysms, traumatic aortic transection, and aortic dissection.
    According to the applicant, the GORE[supreg] TAG[supreg] TBE device 
was granted designation under the Expedited Access Pathway (EAP) by FDA 
(and is therefore considered part of the Breakthrough Devices Program 
by FDA) on July 17, 2015, for endovascular repair of descending 
thoracic aortic and aortic arch for patients who have appropriate 
anatomy. The applicant indicated that it anticipated receiving 
premarket approval of the GORE[supreg] TAG[supreg] TBE device as a 
Class III device from FDA in Spring 2022 with a proposed indication for 
endovascular repair of lesions of the descending thoracic aorta, while 
maintaining flow into the left subclavian artery, in patients who have 
adequate iliac/femoral access, and eligible proximal aorta, left 
subclavian, or distal landing zones (isolated lesion patients only). We 
noted in the proposed rule that since the indication for which the 
applicant anticipated receiving premarket approval was included within 
the scope of the EAP designation, it appeared that the

[[Page 48967]]

proposed PMA indication was appropriate for new technology add-on 
payment under the alternative pathway criteria. Subsequently, the 
applicant received premarket approval on May 13, 2022 with an 
indication for endovascular repair of lesions of the descending 
thoracic aorta, while maintaining flow into the left subclavian artery, 
in patients who are at high risk for debranching subclavian procedures 
and who have appropriate anatomy, which is within the scope of the EAP 
designation.
    The applicant noted that a combination of two existing ICD-10-PCS 
procedure codes can be used to uniquely identify the GORE[supreg] 
TAG[supreg] TBE: 02VW4EZ (Restriction of thoracic aorta, descending 
with branched or fenestrated intraluminal device, one or two arteries, 
percutaneous endoscopic approach), in combination with 02VX4EZ 
(Restriction of thoracic aorta, ascending/arch with branched or 
fenestrated intraluminal device, one or two arteries, percutaneous 
endoscopic approach). Per the applicant, the GORE[supreg] TAG[supreg] 
TBE device is placed such that it straddles two anatomic regions, the 
descending thoracic aorta and thoracic aortic arch, thereby 
necessitating the use of both ICD-10-PCS procedure codes to accurately 
describe the use of the device.
    With regard to the cost criterion, the applicant searched the FY 
2019 MedPAR dataset from the FY 2022 IPPS proposed rule for cases 
reporting a combination of a thoracic endovascular repair (TEVAR) 
procedure and a bypass procedure. The applicant listed the following 
ICD-10-PCS codes for TEVAR procedures and bypass procedures, which the 
applicant used to identify potential cases that may be eligible for 
treatment with the GORE[supreg] TAG[supreg] TBE device. Per the 
applicant, cases with at least one ICD-10-PCS procedure code from each 
category were included in the analysis.
[GRAPHIC] [TIFF OMITTED] TR10AU22.096

[GRAPHIC] [TIFF OMITTED] TR10AU22.097

    The applicant identified 210 cases mapping to five MS-DRGs. The 
applicant then removed charges for the technology being replaced. The 
applicant stated that the use of TAG[supreg] Conformable devices in 
cases that also use the GORE[supreg] TAG[supreg] TBE device is entirely 
dependent on the patient's anatomy. The applicant explained that the 
average case utilizing the GORE[supreg] TAG[supreg] TBE device uses 0.6 
TAG[supreg] Conformable devices, compared to an average of 1.4 
TAG[supreg] Conformable devices per procedure for current TEVAR cases, 
resulting in a difference of 0.8 TAG[supreg] Conformable devices which 
will no longer be used in cases utilizing the GORE[supreg] TAG[supreg] 
TBE device. Accordingly, 80% of all device implant charges were removed 
from the claims to be conservative, per the applicant. The applicant 
then removed other charges related to the prior technology. According 
to the applicant, a research study \203\ that compared 24 patients 
treated with TBE to 31 patients treated with the traditional method at 
one facility found that TBE device cases have a 19% reduction in 
operating room (OR) time compared to the OR time for the combined 
procedures (TEVAR with a bypass procedure), and a 48% reduction in 
length of stay. Accordingly, the applicant removed 19% of OR charges 
(revenue code 0360), removed 48% of routine charges (revenue code 01XX) 
when a claim showed routine charges, and removed 48% of intensive care 
unit (ICU) charges if a claim included no routine charges. The 
applicant then standardized the charges and applied a 4-year inflation 
factor of 1.2818 based on the inflation factor used in the FY 2022 
IPPS/LTCH PPS final rule (86 FR 45538), to update the charges from FY 
2019 to FY 2023. The applicant then added charges for the new 
technology by dividing the average per patient cost of the GORE[supreg] 
TAG[supreg] TBE device by the national CCR for implantable devices 
(0.293) from the FY

[[Page 48968]]

2022 IPPS/LTCH PPS final rule (86 FR 44966). The applicant calculated a 
final inflated case-weighted average standardized charge per case of 
$400,515 and an average case-weighted threshold of $217,182. Because 
the final inflated average case-weighted standardized charge per case 
exceeded the average case-weighted threshold amount, the applicant 
asserted that the technology meets the cost criterion.
---------------------------------------------------------------------------

    \203\ Shultze W, Baxter R, Gable C, et al. Comparison Of 
Surgical Debranching Versus Branched Endografts In Zone 2 TEVAR. 
Oral presentation at the Society for Vascular Surgery Meeting; March 
2021, Miami FL. https://symposium.scvs.org/abstracts/2021/M76.cgi.
---------------------------------------------------------------------------

    In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28324), we noted 
that the charges removed for prior technology are based on length of 
stay in a small study conducted at a single institution. Specifically, 
the study involved 24 patients who received the TBE device during 
elective procedures and 31 who had the procedures with bypass. Three of 
these procedures were emergent and only 14 and 17, respectively, were 
procedures in Zone 2 where the GORE[supreg] TAG[supreg] TBE would be 
indicated. Given the small percentage of procedures that directly 
relate to the proposed GORE[supreg] TAG[supreg] TBE indication, we 
questioned the extent to which these results are generalizable to the 
cost analysis performed above and the greater Medicare population. 
Additionally, the applicant did not specify the revenue codes used to 
identify and remove intensive care unit charges. We noted the applicant 
listed two ICD-10-PCS codes (03S43ZZ and 03SQ3ZZ) in their analysis 
which are percutaneous procedures and questioned whether the inclusion 
of these codes was appropriate as the devices currently used to repair 
the aortic arch require the creation of a bypass performed in an open 
surgery. We also questioned whether the cases that the applicant 
identified were appropriately representative of cases eligible for 
treatment with GORE[supreg] TAG[supreg] TBE and requested additional 
information to clarify this issue.
    Subject to the applicant adequately addressing these concerns, we 
stated in the proposed rule that we agreed that the technology meets 
the cost criterion and therefore proposed to approve the GORE[supreg] 
TAG[supreg] TBE device for new technology add-on payments for FY 2023, 
subject to the technology receiving FDA marketing authorization for the 
proposed indication by July 1, 2022.
    Based on preliminary information from the applicant at the time of 
the proposed rule, the per-patient anticipated hospital cost of the 
GORE[supreg] TAG[supreg] TBE device was $42,780. We noted that the cost 
information for this technology may be updated in the final rule based 
on revised or additional information CMS receives prior to the final 
rule. Under Sec.  412.88(a)(2), we limit new technology add-on payments 
to the lesser of 65% of the average cost of the technology, or 65% of 
the costs in excess of the MS-DRG payment for the case. In the proposed 
rule, we stated that in the event we were to receive supplemental 
information from the applicant to adequately address our concerns 
regarding the cost criterion, and we were to approve new technology 
add-on payments for the GORE[supreg] TAG[supreg] TBE device in the 
final rule, the maximum new technology add-on payment for a case 
involving the use of the GORE[supreg] TAG[supreg] TBE device would be 
$27,807 for FY 2023 (that is, 65% of the average cost of the 
technology).
    We invited public comments on whether the GORE[supreg] TAG[supreg] 
TBE device meets the cost criterion and our proposal to approve new 
technology add-on payments for the GORE[supreg] TAG[supreg] TBE device 
for FY 2023, subject to the technology receiving FDA marketing 
authorization for the proposed indication that corresponds to the EAP 
designation by July 1, 2022.
    Comment: The applicant provided comments and a revised cost 
analysis in response to CMS' concerns identified in the proposed rule. 
With respect to the concern that the charges removed for prior 
technology were based on length of stay in a small study conducted at a 
single institution, the applicant stated that the pivotal trial for the 
GORE[supreg] TAG[supreg] TBE device was conducted at 40 U.S. sites and 
the separate outcome sub-study was based at a site that had the highest 
numbers of enrolled participants. In addition, the applicant stated 
that the length of stay and length of time in the ICU was similar for 
all sites in the clinical trial and therefore the cost estimates from a 
single institution are reflective of the cost of care provided at other 
sites.
    With respect to the concern about results being generalizable to 
the greater Medicare population, the applicant stated that the median 
age of outcome sub-study participants was 65 years, and that half of 
all participants were of Medicare-eligible age. The applicant also 
noted that the outcome sub-study population (24 GORE[supreg] 
TAG[supreg] TBE patients and 31 SR-TEVAR patients) represented more 
than a quarter of a total of 202 GORE[supreg] TAG[supreg] TBE-eligible 
cases in the FY 2019 Medicare claims. Per the applicant, this sample of 
the 202 eligible cases in the FY 2019 Medicare claims is large enough 
to appropriately estimate the costs associated with the GORE[supreg] 
TAG[supreg] TBE procedure and that, based on the median age, the 
estimate is generalizable to the Medicare population.
    With respect to the concern as to whether the cases identified by 
the applicant were appropriately representative of cases eligible for 
treatment with GORE[supreg] TAG[supreg] TBE, the applicant stated that 
the GORE[supreg] TAG[supreg] TBE device replaces two separate operating 
room procedures: a left subclavian artery (SA) bypass procedure, 
usually an open surgery, and a percutaneous thoracic endograft implant 
procedure, commonly referred to as SR-TEVAR, because it contains a 
branched element that is inserted into the left subclavian artery 
thereby maintaining blood flow and eliminating the need for a SA bypass 
procedure. The applicant stated that the outcome sub-study provides 
information on resource use differences between patients undergoing TBE 
procedures compared to a combination of surgical revascularization and 
thoracic endograft implant. The applicant stated that including cases 
that involved both procedures (that is, the SA bypass procedure and the 
TEVAR procedure) in the cost criterion analysis and removing 100% of 
device charges as well as other related service charges (19% of OR 
charges and 48% of routine care charges) better reflects the estimate 
of the GORE[supreg] TAG[supreg] TBE standardized charges. In the 
updated analysis, the applicant removed 100% of all device charges from 
the MedPAR cases compared to removing 80%, which it did in its original 
application.
    The applicant further indicated that while every patient 
presentation of aortic disease is unique in length, type, and severity 
of disease, all patients in the outcome sub-study had serious aortic 
disease that needed repair in the left subclavian artery, even if cases 
were characterized as an elective surgery for purposes of the study 
reporting. The applicant also stated that the ends of the device must 
exceed the length of the diseased aorta on both ends, the proximal and 
distal locations of the implanted device varied, depending on the 
length of the aortic disease, and as such, the devices can span several 
zones. The applicant further noted that all cases, emergent or 
elective, had similar resource use.
    With respect to the concern that the revenue codes used to identify 
and remove intensive care unit charges were not specified, the 
applicant stated that it used CMS revenue codes 020x and 021x to 
identify intensive care unit charges in the rate-setting methodology. 
We note that revenue code descriptions for 021x and 021x are Intensive 
Care Unit and Coronary Care Unit, respectively.

[[Page 48969]]

    With respect to our inquiry about the inclusion of two codes for 
percutaneous procedures, the applicant explained that it included the 
two percutaneous approach codes in its original cost analysis in order 
to pick up all bypass surgery codes. The applicant then explained that 
eliminating these two codes from the inclusion criteria for the revised 
analysis excluded only one case. The applicant noted that removing the 
one percutaneous SA bypass case limited the revised cost criterion 
analysis to only those cases where the subclavian artery bypass surgery 
was coded as an open approach.
    The applicant reported that the updated cost criterion analysis 
resulted in a threshold amount of $217,080 and a new standardized 
charge estimate of $377,857. The applicant stated that the new 
standardized charge estimate still greatly exceeds the new technology 
add-on payment threshold and the GORE[supreg] TAG[supreg] TBE device 
meets the cost criterion requirement.
    The applicant also stated that upon further consultation with 
clinical experts, the better combination of ICD-10-PCS codes to 
identify cases utilizing the technology would be 02VW3DZ (Restriction 
of thoracic aorta, descending with intraluminal device, percutaneous 
approach), in combination with 02VX3EZ (restriction of thoracic aorta, 
ascending/arch with branched or fenestrated intraluminal device, one or 
two arteries, percutaneous approach) and requested that these codes be 
used to identify the GORE[supreg] TAG[supreg] TBE for purposes of new 
technology add-on payment instead of the codes included in the proposed 
rule.
    Another commenter familiar with the applicant's cost study 
submitted a public comment reiterating the applicant's statements 
regarding the characteristics of the single institution upon which the 
applicant's cost analysis was based, disease severity in the patient 
population, the uniform requirement of Zone 2 repair despite variation 
of distal zones treated, and generalizability of the study population 
to the Medicare population. Based on the results achieved for patients 
receiving the TBE graft as compared to the TEVAR and subclavian artery 
bypass, this commenter recommended that CMS approve the GORE[supreg] 
TAG[supreg] TBE for new technology add on payments.
    Response: We thank the commenters for their comments and appreciate 
the additional clarification regarding the cost criterion. Based on the 
information provided in the application for new technology add-on 
payments, and after consideration of the public comments we received, 
we believe the GORE[supreg] TAG[supreg] Thoracic Branch Endoprosthesis 
(TBE) meets the cost criterion. GORE[supreg] TAG[supreg] TBE received 
marketing authorization from FDA on May 13, 2022 for the indication 
covered by its Breakthrough Device designation for endovascular repair 
of lesions of the descending thoracic aorta, while maintaining flow 
into the left subclavian artery, in patients who are at high risk for 
debranching subclavian procedures and who have appropriate anatomy. 
Therefore, we are finalizing our proposal to approve new technology 
add-on payments for the GORE[supreg] TAG[supreg] TBE for FY 2023 and we 
consider the beginning of the newness period to commence on May 13, 
2022, which is the date on which the technology received FDA marketing 
authorization for the indication covered by its Breakthrough Device 
designation.
    Based on the information at the time of this final rule, the cost 
per case of the GORE[supreg] TAG[supreg] TBE is $42,780. Under Sec.  
412.88(a)(2), we limit new technology add-on payments to the lesser of 
65% of the average cost of the technology, or 65% of the costs in 
excess of the MS DRG payment for the case. As a result, we are 
finalizing that the maximum new technology add-on payment for a case 
involving the use of the GORE[supreg] TAG[supreg] TBE is $27,807 for FY 
2023 (that is, 65% of the average cost of the technology). Cases 
involving the use of GORE[supreg] TAG[supreg] TBE that are eligible for 
new technology add-on payments will be identified by ICD-10-PCS codes: 
02VW3DZ (Restriction of thoracic aorta, descending with intraluminal 
device, percutaneous approach) in combination with 02VX3EZ (Restriction 
of thoracic aorta, ascending/arch with branched or fenestrated 
intraluminal device, one or two arteries, percutaneous approach).
(3) iFuse Bedrock Granite Implant System
    SI-BONE, Inc., submitted an application for new technology add-on 
payments for the iFuse Bedrock Granite Implant System for FY 2023. 
According to the applicant, the iFuse Bedrock Granite Implant System is 
a sterile, single-use permanent implant intended to provide sacropelvic 
fusion of the sacroiliac joint and fixation to the pelvis when used in 
conjunction with commercially available pedicle screw fixation systems 
as a foundational element for segmental spinal fusion. The applicant 
stated that the joint fusion occurs as a result of the device's porous 
surface and interstices, and fixation occurs through the device's 
helical threaded design and traditional posterior fixation rod 
connection. Per the applicant, the iFuse Bedrock Granite Implant System 
can be placed into the pelvis in two trajectories: sacroalar-iliac 
(SAI) trajectory (that is, into the sacrum, across the SI joint and 
into the ilium) or directly into the ilium, and joint fusion occurs 
only when the SAI trajectory is used.
    According to the applicant, the iFuse Bedrock Granite Implant 
System received FDA Breakthrough Device designation on November 23, 
2021 for sacropelvic fixation and as an adjunct for sacroiliac joint 
fusion (when used with commercially available sacroiliac joint fusion 
promoting devices) in conjunction with commercially available posterior 
pedicle screw systems for the treatment of the acute and chronic 
instabilities or deformities of the thoracic, lumbar, and sacral spine; 
degenerative disc disease (DDD) as defined by back pain of discogenic 
origin with degeneration of the disc confirmed by patient history and 
radiographic studies; severe spondylolisthesis (Grades 3 and 4) of the 
L5-S1 vertebra in skeletally mature patients receiving fusions by 
autogenous bone graft having implants attached to the lumbar and sacral 
spine (L3 to sacrum) with removal of the implants after the attainment 
of a solid fusion; spondylolisthesis; trauma (that is, fracture or 
dislocation); spinal stenosis; deformities or curvatures (that is, 
scoliosis, kyphosis, and/or lordosis); spinal tumor; pseudarthrosis; 
and/or failed previous fusion. Subsequently, the iFuse Bedrock Granite 
Implant System received 510(k) clearance from FDA on May 26, 2022 
(K220195) for the same indication.
    The applicant stated that ICD-10-PCS codes that may be utilized to 
describe the placement of an internal fixation device into the pelvic 
bone or acetabulum, listed in the following table, do not distinctly 
identify the iFuse Bedrock Granite Implant System.

[[Page 48970]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.098

    The applicant submitted a request to the ICD-10 Coordination and 
Maintenance Committee for approval of a unique code for FY 2023 and was 
granted approval to identify the iFuse Bedrock Granite Implant System 
using the following procedure codes effective October 1, 2022:
[GRAPHIC] [TIFF OMITTED] TR10AU22.099

    With regard to the cost criterion, the applicant conducted two 
analyses based on 100% of identified claims and 78% of identified 
claims. To identify potential cases where the iFuse Bedrock Granite 
Implant System could be utilized, the applicant searched the FY 2019 
MedPAR final rule file for claims reporting a combination of at least 
one of the ICD-10-PCS procedure codes for the placement of an internal 
fixation device into the pelvic bone or acetabulum, noted previously, 
and at least one of the following ICD-10-CM diagnosis codes used to 
describe the indication under the Breakthrough Device designation.
BILLING CODE 4120-01-P

[[Page 48971]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.100


[[Page 48972]]


[GRAPHIC] [TIFF OMITTED] TR10AU22.101

    For the analysis using 100% of cases, the applicant identified 
2,165 cases mapping to the following 26 MS-DRGs:

[[Page 48973]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.102

BILLING CODE 4120-01-C
    The applicant then removed 50% of the charges associated with 
medical supplies and implantable devices (revenue centers 027x and 
0624). The applicant stated that the removal of 50% of the charges 
associated with medical supplies and implantable devices reflects a 
conservative estimate as the iFuse Bedrock Granite Implant System is 
used in conjunction with commercially available pedicle screw fixation 
systems as a foundational element for segmental spinal fusion. The 
applicant then standardized the charges and applied the three-year 
inflation factor of 20.4% used to update the outlier threshold in the 
FY 2022 IPPS/LTCH PPS final rule (86 FR 45542) to update the charges 
from FY 2019 to FY 2022. The applicant then added charges for the new 
technology by dividing the per-patient anticipated hospital cost of the 
iFuse Bedrock Granite Implant System by the national average cost-to-
charge ratio for implantable devices (0.239) from the FY 2022 IPPS/LTCH 
PPS final rule. Under the analysis based on 100% of identified claims, 
the applicant calculated a final inflated case-weighted average 
standardized charge per case of $254,264 and an average case-weighted 
threshold of $159,841.
    For the analysis using 78% of cases, the applicant identified 1,682 
cases mapping to 4 MS-DRGs. The applicant conducted the same analysis 
noted previously and determined a final inflated case-weighted average 
standardized charge per case of $253,333 and an average case-weighted 
threshold of $164,561. Because the final inflated case-weighted average 
standardized charge per case exceeded the average case-weighted 
threshold amount under both analyses, the applicant asserted that the 
technology meets the cost criterion.
    In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28327), we agreed 
with the applicant that iFuse Bedrock Granite Implant System meets the 
cost criterion and therefore we proposed to approve the iFuse Bedrock 
Granite Implant System for new technology add-on payments for FY 2023, 
subject to the technology receiving FDA marketing authorization for the 
indication corresponding to the Breakthrough Device designation by July 
1, 2022.
    Based on preliminary information from the applicant at the time of 
the proposed rule, the per-patient anticipated hospital cost of the 
iFuse Bedrock Granite Implant System was $15,120. We noted that the 
cost information for this technology may be updated in the final rule 
based on revised or additional information CMS receives prior to the 
final rule. Under Sec.  412.88(a)(2), we limit new technology add-on 
payments to the lesser of 65% of the average cost of the technology, or 
65% of the costs in excess of the MS-DRG payment for the case. As a 
result, we proposed that the maximum new technology add-on payment for 
a case involving the use of the iFuse Bedrock Granite Implant System 
would be $9,828 for FY 2023 (that is, 65% of the average cost of the 
technology).
    We invited public comments on whether the iFuse Bedrock Granite 
Implant System meets the cost criterion and our proposal to approve new 
technology add-on payments for the iFuse Bedrock Granite Implant System 
for FY 2023, subject to the technology receiving FDA marketing 
authorization for the indication corresponding to the Breakthrough 
Device designation by July 1, 2022.
    Comment: We received a few comments supporting CMS' proposal to 
approve the iFuse Bedrock Granite Implant System for new technology 
add-on payments. One of the commenters also agreed with CMS that the 
technology meets the cost criterion.
    Response: We appreciate the input from the commenters.

[[Page 48974]]

    Based on the information provided in the application for new 
technology add-on payments, and after consideration of the public 
comments we received, we believe the iFuse Bedrock Granite Implant 
System meets the cost criterion. The iFuse Bedrock Granite Implant 
System received marketing authorization from FDA on May 26, 2022 for 
the indication covered by the Breakthrough Device designation, for 
sacropelvic fixation and as an adjunct for sacroiliac joint fusion 
(when used with commercially available sacroiliac joint fusion 
promoting devices) in conjunction with commercially available posterior 
pedicle screw systems for the treatment of the acute and chronic 
instabilities or deformities of the thoracic, lumbar, and sacral spine; 
degenerative disc disease (DDD) as defined by back pain of discogenic 
origin with degeneration of the disc confirmed by patient history and 
radiographic studies; severe spondylolisthesis (Grades 3 and 4) of the 
L5-S1 vertebra in skeletally mature patients receiving fusions by 
autogenous bone graft having implants attached to the lumbar and sacral 
spine (L3 to sacrum) with removal of the implants after the attainment 
of a solid fusion; spondylolisthesis; trauma (that is, fracture or 
dislocation); spinal stenosis; deformities or curvatures (that is, 
scoliosis, kyphosis, and/or lordosis); spinal tumor; pseudarthrosis; 
and/or failed previous fusion. Therefore, we are finalizing our 
proposal to approve new technology add-on payments for the iFuse 
Bedrock Granite Implant System for FY 2023, and we consider the 
beginning of the newness period to commence on May 26, 2022, which is 
the date on which the technology received FDA marketing authorization 
for the indication covered by its Breakthrough Device designation.
    Based on the information at the time of this final rule, the cost 
per case of the iFuse Bedrock Granite Implant System is $15,120. Under 
Sec.  412.88(a)(2), we limit new technology add-on payments to the 
lesser of 65% of the average cost of the technology, or 65% of the 
costs in excess of the MS-DRG payment for the case. As a result, we are 
finalizing that the maximum new technology add-on payment for a case 
involving the use of the iFuse Bedrock Granite Implant System is $9,828 
for FY 2023 (that is, 65% of the average cost of the technology). Cases 
involving the use of the iFuse Bedrock Granite Implant System that are 
eligible for new technology add-on payments will be identified by one 
of the following ICD-10- PCS codes:
[GRAPHIC] [TIFF OMITTED] TR10AU22.103

(4) ThoraflexTM Hybrid Device
    Terumo Aortic submitted an application for new technology-add on 
payments for the ThoraflexTM Hybrid Device for FY 2023. Per 
the applicant, the device is a sterile single-use, gelatin sealed 
Frozen Elephant Trunk (FET) surgical medical device. The applicant 
explained that the device is deployed through an opened aortic arch and 
then positioned into the descending thoracic aorta. The applicant 
further explained that, once it is completely deployed, the collar is 
sutured to the aorta, and graft anastomoses are then performed in a 
manner depending upon the chosen product design (which the applicant 
specified as either the Plexus or the Ante-Flo). The device includes a 
proximal crimped polyester surgical graft, central polyester collar, 
and distal nitinol ring stents supported by thin wall polyester fabric. 
The applicant also noted that the device has a unique gelatin sealant 
that acts as a seal, preventing blood loss through the polyester fabric 
product wall. We note that Terumo Aortic previously submitted an 
application for new technology add-on payments for the 
ThoraflexTM Hybrid Device for FY 2022, as summarized in the 
FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25390) which was withdrawn 
prior to the issuance of the FY 2022 IPPS/LTCH PPS final rule (86 FR 
45127).
    According to the applicant, the ThoraflexTM Hybrid 
Device received Breakthrough Device designation on March 20, 2020 for 
the open surgical repair or replacement of damaged or diseased vessels 
of the aortic arch and descending aorta, with or without involvement of 
the ascending aorta, in cases of aneurysm and/or dissection. The 
applicant received FDA marketing authorization on April 19, 2022 for 
the same indication as the Breakthrough Device designation. According 
to the applicant, the ICD-10 Coordination and Maintenance Committee 
approved the following ICD-10-PCS codes to specifically describe the 
use of the ThoraflexTM Hybrid Device, effective October 1, 
2021: X2RX0N7 (Replacement of thoracic aorta arch with branched 
synthetic substitute with intraluminal device, new technology

[[Page 48975]]

group 7) and X2VW0N7 (Restriction of thoracic descending aorta with 
branched synthetic substitute with intraluminal device, new technology 
group 7).
    With respect to the cost criterion, the applicant conducted two 
analyses based on 100% of identified claims and 74% of identified 
claims. To identify potential cases where the ThoraflexTM 
Hybrid Device could be utilized, the applicant searched the FY 2019 
MedPAR file for claims reporting the following ICD-10-PCS codes for 
thoracic aortic replacement procedures: 02RX08Z (Replacement of 
thoracic aorta, ascending/arch with zooplastic tissue, open approach), 
02RX0JZ (Replacement of thoracic aorta, ascending/arch with synthetic 
tissue, open approach), and 02RX0KZ (Replacement of thoracic aorta, 
ascending/arch with nonautologous tissue substitute, open approach).
    For the analysis using 100% of cases, the applicant identified 
5,374 cases mapping to 21 MS-DRGs. The applicant then removed charges 
for the technology being replaced. Per the applicant, the use of the 
ThoraflexTM Hybrid device is expected to replace a portion 
of prior technologies. The applicant explained that because an estimate 
of the percentage of these total charges that would be replaced could 
not be determined, it removed 100% of charges associated with medical/
surgical supplies and devices (revenue centers 027x and 0624). The 
applicant then standardized the charges and applied the 3-year outlier 
inflation factor of 1.204686 used to update the outlier threshold in 
the FY 2022 IPPS/LTCH PPS final rule (86 FR 45542) to update the 
charges from FY 2019 to FY 2022. The applicant then added charges for 
the new technology. The applicant multiplied the cost of the technology 
by the national cost-to-charge ratio for implantable devices from the 
FY 2022 IPPS/LTCH PPS final rule (0.293) to calculate estimated average 
hospital charges associated with the device. Under this analysis, based 
on 100% of identified claims, the applicant calculated a final inflated 
case-weighted average standardized charge per case of $420,924 and an 
average case-weighted threshold of $230,659.
    Under the analysis based on 74% of cases, the applicant used the 
same methodology, which identified 3,980 cases across MS-DRGs 219 and 
220. The applicant determined the average case-weighted threshold of 
$211,423 and a final inflated average standardized charge per case of 
$373,273. Because the final inflated case-weighted average standardized 
charge per case exceeded the average case-weighted threshold amount 
under both analyses, the applicant asserted that the technology meets 
the cost criterion.
    In the proposed rule, we stated that we agree with the applicant 
that the ThoraflexTM Hybrid Device meets the cost criterion 
and therefore proposed to approve the ThoraflexTM Hybrid 
Device for new technology add-on payments for FY 2023, subject to the 
technology receiving FDA marketing authorization for the open surgical 
repair or replacement of damaged or diseased vessels of the aortic arch 
and descending aorta, with or without involvement of the ascending 
aorta, in cases of aneurysm and/or dissection by July 1, 2022.
    Based on preliminary information from the applicant at the time of 
the proposed rule, the cost of the ThoraflexTM Hybrid Device 
was $35,000 per patient. We noted that the cost information for this 
technology may be updated in the final rule based on revised or 
additional information CMS receives prior to the final rule. Under 
Sec.  412.88(a)(2), we limit new technology add-on payments to the 
lesser of 65% of the average cost of the technology, or 65% of the 
costs in excess of the MS-DRG payment for the case. As a result, we 
proposed that the maximum new technology add-on payment for a case 
involving the use of ThoraflexTM Hybrid Device would be 
$22,750 per patient for FY 2023 (that is, 65% of the average cost of 
the technology).
    We invited public comments on whether the ThoraflexTM 
Hybrid Device meets the cost criterion and our proposal to approve new 
technology add-on payments for the ThoraflexTM Hybrid Device 
for FY 2023, subject to the ThoraflexTM Hybrid Device 
receiving FDA marketing authorization by July 1, 2022 for the open 
surgical repair or replacement of damaged or diseased vessels of the 
aortic arch and descending aorta, with or without involvement of the 
ascending aorta, in cases of aneurysm and/or dissection.
    Comment: The applicant submitted a public comment expressing 
support for the approval of the ThoraflexTM Hybrid Device 
for the new technology add-on payment for FY 2023. The applicant 
emphasized that both X2RX0N7 (Replacement of thoracic aorta arch with 
branched synthetic substitute with intraluminal device, new technology 
group 7) and X2VW0N7 (Restriction of thoracic descending aorta with 
branched synthetic substitute with intraluminal device, new technology 
group 7) need to be reported concurrently to appropriately describe the 
implant procedure for the ThoraflexTM Hybrid Device.
    Response: We appreciate the applicant's support.
    Based on the information provided in the application for new 
technology add-on payments, and after consideration of the public 
comments we received, we believe the ThoraflexTM Hybrid 
Device meets the cost criterion. The ThoraflexTM Hybrid 
Device received marketing authorization from FDA on April 19, 2022 for 
the indications covered by its Breakthrough Device designation for the 
open surgical repair or replacement of damaged or diseased vessels of 
the aortic arch and descending aorta, with or without involvement of 
the ascending aorta, in cases of aneurysm and/or dissection. Therefore, 
we are finalizing our proposal to approve new technology add-on 
payments for the ThoraflexTM Hybrid Device for FY 2023, and 
we consider the beginning of the newness period to commence on April 
19, 2022, which is the date on which the technology received FDA 
marketing authorization for the indication covered by its Breakthrough 
Device designation.
    Based on the information at the time of this final rule, the cost 
per case of the ThoraflexTM Hybrid Device is $35,000 per 
patient. Under Sec.  412.88(a)(2), we limit new technology add-on 
payments to the lesser of 65% of the average cost of the technology, or 
65% of the costs in excess of the MS DRG payment for the case. As a 
result, we are finalizing that the maximum new technology add-on 
payment for a case involving the use of the ThoraflexTM 
Hybrid Device is $22,750 for FY 2023 (that is, 65% of the average cost 
of the technology). Cases involving the use of the 
ThoraflexTM Hybrid Device that are eligible for new 
technology add-on payments will be identified by the ICD-10-PCS code 
X2RX0N7 (Replacement of thoracic aorta arch with branched synthetic 
substitute with intraluminal device, new technology group 7) in 
combination with the ICD-10-PCS code X2VW0N7 (Restriction of thoracic 
descending aorta with branched synthetic substitute with intraluminal 
device, new technology group 7).
(5) ViviStim[supreg] Paired VNS System
    MicroTransponder, Inc. submitted an application for new technology 
add-on payments for the ViviStim[supreg] Paired VNS System for FY 2023. 
According to the applicant, the ViviStim[supreg] Paired VNS System is a 
paired vagus nerve stimulation therapy intended to stimulate the vagus 
nerve during rehabilitation therapy to reduce upper extremity motor 
deficits and improve

[[Page 48976]]

motor function in chronic ischemic stroke patients with moderate to 
severe arm impairment. The applicant stated that the Vivistim[supreg] 
Paired VNS System is comprised of an Implantable Pulse Generator (IPG), 
an implantable stimulation Lead, and an external paired stimulation 
controller which is composed of the external Wireless Transmitter (WT) 
and the external Stroke Application and Programming Software (SAPS). 
According to the applicant, the external paired stimulation controller 
(SAPS and WT) enables the implanted components (the IPG and Lead) to 
stimulate the vagus nerve during rehabilitation. The applicant stated 
that patients undergo 25-30 hours of in-clinic rehabilitation over 6 
weeks, where the ViviStim[supreg] Paired VNS System is actively paired 
with rehabilitation by a therapist. The applicant further stated that 
following this in-clinic rehabilitation period, when directed by a 
physician and with appropriate programming to the IPG, the patient can 
initiate at-home use by swiping a magnet over the IPG implant site 
which activates the IPG to deliver stimulation while rehabilitation 
movements are performed.
    The applicant stated that the ViviStim[supreg] Paired VNS System 
was designated as a Breakthrough Device on February 10, 2021 for use in 
stimulating the vagus nerve during rehabilitation therapy in order to 
reduce upper extremity motor deficits and improve motor function in 
chronic ischemic stroke patients with moderate to severe arm 
impairment. According to the applicant, the ViviStim[supreg] Paired VNS 
System received FDA premarket approval on August 27, 2021 as a Class 
III implantable device for the same indication. The applicant stated 
that the technology became commercially available on April 29, 2022 due 
to manufacturing delays.
    According to the applicant, there are no unique ICD-10-PCS 
procedure codes to report the implantation of the device. The applicant 
noted that together the following two ICD-10-PCS codes describe the 
insertion of the ViviStim[supreg] Paired VNS System: 0JH60BZ (Insertion 
of single array stimulator generator into chest subcutaneous tissue and 
fascia, open approach) and 00HE0MZ (Insertion of neurostimulator lead 
into cranial nerve, open approach). The applicant noted that these 
codes may be used for any cranial nerve stimulator insertion procedure, 
including VNS therapy for treatment resistant depression, VNS therapy 
for refractory epilepsy, and upper airway stimulation to treat 
obstructive sleep apnea. The applicant submitted a request to the ICD-
10 Coordination and Maintenance Committee for approval of a unique code 
for FY 2022 to identify insertion of the ViviStim[supreg] Paired VNS 
System and was granted approval for the following procedure code 
effective October 1, 2022: X0HQ3R8 (Insertion of neurostimulator lead 
with paired stimulation system into vagus nerve, percutaneous approach, 
new technology group 8).
    The applicant also provided the ICD-10-CM diagnosis codes in the 
table that follows. The applicant stated that moderate to severe upper 
limb impairment is described in the ICD-10-CM as monoplegia (single 
limb) or hemiplegia (single laterality, including upper limb). The 
applicant stated that the FY 2021 ICD-10-CM code set \204\ includes 
monoplegia and hemiplegia as a sequela of infarction (stroke), and 
delineates codes based upon stroke type (hemorrhagic versus ischemic). 
Therefore, the applicant stated that the ICD-10-CM diagnosis codes in 
the following table describe chronic moderate to severe upper arm 
impairment as a sequela of ischemic stroke, and are related to the use 
of the ViviStim[supreg] Paired VNS System.
[GRAPHIC] [TIFF OMITTED] TR10AU22.104

    With respect to the cost criterion, the applicant presented the 
following analysis. The applicant searched the FY 2019 MedPAR claims 
data set released with the FY 2022 IPPS/LTCH PPS final rule for cases 
representing patients who may be eligible for the ViviStim[supreg] 
Paired VNS System. The applicant identified cases reporting the ICD-10-
PCS codes 0JH60BZ and 00HE0MZ in combination with one of the ICD-10-CM 
diagnosis codes, noted previously, describing moderate to severe upper 
limb impairment. The applicant then mapped the cases to the appropriate 
MS-DRGs using MS-DRG Grouper Version 39.0. After imputing a case count 
of 11 for those MS-DRGs with fewer than 11 cases, the applicant 
identified 285 claims mapping to 12 MS-DRGs, with 65% of cases mapping 
to MS-DRGs 024 (Craniotomy with Major Device Implant or Acute Complex 
CNS Principal Diagnosis without MCC), 041 (Peripheral Cranial Nerve and 
Other Nervous System Procedures with CC or Peripheral Neurostimulator) 
and 042 (Peripheral Cranial Nerve and Other Nervous System Procedures 
without CC/MCC).
---------------------------------------------------------------------------

    \204\ https://www.cms.gov/medicare/icd-10/2021-icd-10-cm, 
effective October 1, 2020 through September 30, 2021.
---------------------------------------------------------------------------

    The applicant then removed 100% of charges associated with Medical/
Surgical Supplies and Devices (prior technology, revenue centers 027X, 
and 0624). The applicant asserted that the use of the Vivistim[supreg] 
Paired VNS System is expected to replace the majority of existing 
technologies, although some devices would still be required to perform 
the procedure. The applicant stated that because it could not determine 
the estimated percentage of the total charges that would be replaced, 
it removed 100% of these total charges to be as conservative as 
possible. The applicant did not remove charges related to the 
technology being replaced,

[[Page 48977]]

stating that the financial impact of utilizing the Vivistim[supreg] 
Paired VNS System on hospital resources compared to prior technologies 
other than on Medical Supplies is minimal, and that 100% of charges for 
Medical/Surgical Supplies had been removed in the previous step.
    The applicant standardized the charges by applying the three-year 
inflation factor of 1.20469 used in the FY 2022 IPPS/LTCH PPS final 
rule and correction notice to calculate outlier threshold charges (86 
FR 45542). The applicant then added charges for the new technology by 
dividing the cost of the ViviStim[supreg] Paired VNS System by the 
national average CCR for implantable devices which is 0.293 as 
published in the FY 2022 IPPS/LTCH IPPS final rule (86 FR 44966). The 
applicant calculated a final inflated average case-weighted 
standardized charge per case of $200,398 which exceeded the average 
case-weighted threshold amount of $107,963. Because the final inflated 
average case-weighted standardized charge per case exceeded the average 
case-weighted threshold amount, the applicant maintained that the 
ViviStim[supreg] Paired VNS System meets the cost criterion.
    In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28350), we agreed 
with the applicant that the ViviStim[supreg] Paired VNS System meets 
the cost criterion and therefore proposed to approve the 
ViviStim[supreg] Paired VNS System for new technology add-on payments 
for FY 2023.
    Based on preliminary information from the applicant at the time of 
the proposed rule, the total cost of the ViviStim[supreg] Paired VNS 
System to the hospital was $36,000 per patient. According to the 
applicant, this cost represents the entire per-patient cost of the 
system to hospital providers--specifically for the cost of the 
Implantable Pulse Generator and stimulation lead. Per the applicant, 
there is no charge associated with the external paired stimulation 
controller and the magnet/take-home patient programmer. The applicant 
stated that the external paired stimulation controller may be used on 
multiple patients and that it retains a service agreement with each 
provider to own, maintain, and update the hardware and software that 
resides on that device component. The applicant has also stated that 
they have this service agreement with providers for the magnet/take-
home patient programmer. Therefore, as the applicant has stated they 
retain and maintain the reusable hardware components at no charge to 
the providers, we stated that it appeared that capital components were 
not included in the cost of the technology. We welcomed public comment 
on the cost information provided by the applicant for the purpose of 
calculating the new technology add-on payment amount.
    We noted that the cost information for this technology may be 
updated in the final rule based on revised or additional information 
CMS receives prior to the final rule. Under Sec.  412.88(a)(2), we 
limit new technology add-on payments to the lesser of 65% of the 
average cost of the technology, or 65% of the costs in excess of the 
MS-DRG payment for the case. As a result, we proposed that the maximum 
new technology add-on payment for a case involving the use of the 
ViviStim[supreg] Paired VNS System would be $23,400 for FY 2023 (that 
is, 65% of the average cost of the technology).
    We invited public comments on whether the ViviStim[supreg] Paired 
VNS System meets the cost criterion and our proposal to approve new 
technology add-on payments for the ViviStim[supreg] Paired VNS System 
for FY 2023 for use in stimulating the vagus nerve during 
rehabilitation therapy in order to reduce upper extremity motor 
deficits and improve motor function in chronic ischemic stroke patients 
with moderate to severe arm impairment.
    Comment: We received a few comments supporting our proposal to 
approve new technology add-on payments for FY 2023. The applicant also 
noted that the ViviStim[supreg] Paired VNS System received FDA 
premarket approval on August 27, 2021; however, a manufacturing delay 
prevented market availability of the device until April 29, 2022. The 
applicant requested that CMS begin the newness period for the 
Vivistim[supreg] Paired VNS System using the latter market availability 
date of April 29, 2022. The applicant also supported our proposed 
maximum new technology add-on payment amount.
    Response: We thank the commenters for their support and feedback. 
We agree that the newness date for this technology is the date on which 
ViviStim[supreg] Paired VNS System became available on the market, 
April 29, 2022. We note that though, generally, our policy is to begin 
the newness period on the date of FDA approval or clearance, we may 
consider a documented delay in the technology's market availability in 
our determination of newness (77 FR 53348 and 70 FR 47341).
    Based on the information provided in the application for new 
technology add-on payments, and after consideration of the public 
comments we received, we believe the ViviStim[supreg] Paired VNS System 
meets the cost criterion. Therefore, we are finalizing our proposal to 
approve new technology add-on payments for the ViviStim[supreg] Paired 
VNS System for FY 2023, and we consider the beginning of the newness 
period to commence on April 29, 2022, which is when the technology 
became commercially available for the indication covered by its 
Breakthrough Device designation, for use in stimulating the vagus nerve 
during rehabilitation therapy in order to reduce upper extremity motor 
deficits and improve motor function in chronic ischemic stroke patients 
with moderate to severe arm impairment.
    Based on the information at the time of this final rule, the cost 
per case of the ViviStim[supreg] Paired VNS System is $36,000. 
According to the applicant, this cost represents the entire per-patient 
cost of the system to hospital providers, specifically for the 
implantable pulse generator and stimulation lead. Under Sec.  
412.88(a)(2), we limit new technology add-on payments to the lesser of 
65% of the average cost of the technology, or 65% of the costs in 
excess of the MS DRG payment for the case. As a result, we are 
finalizing that the maximum new technology add-on payment for a case 
involving the use of the ViviStim[supreg] Paired VNS System would be 
$23,400 for FY 2023 (that is, 65% of the average cost of the 
technology). Cases involving the use of the ViviStim[supreg] Paired VNS 
System that are eligible for new technology add-on payments will be 
identified by the ICD-10-PCS procedure code X0HQ3R8 (Insertion of 
neurostimulator lead with paired stimulation system into vagus nerve, 
percutaneous approach, new technology group 8).

[[Page 48978]]

b. Alternative Pathways for Qualified Infectious Disease Products 
(QIDPs)
(1) DefenCathTM (Solution of Taurolidine (13.5 mg/mL) and 
Heparin (1000 USP Units/mL))
    CorMedix Inc. submitted an application for new technology add-on 
payments for DefenCathTM (solution of taurolidine (13.5 mg/
mL) and heparin (1000 USP Units/mL)) for FY 2023. The applicant stated 
that DefenCathTM is a proprietary formulation of 
taurolidine, a thiadiazinane antimicrobial, and heparin, an anti-
coagulant, that is under development for use as catheter lock solution, 
with the aim of reducing the risk of catheter-related bloodstream 
infections (CRBI) from in-dwelling catheters in patients undergoing 
hemodialysis (HD) through a central venous catheter (CVC). According to 
the applicant, in vitro studies of DefenCathTM indicate 
broad antimicrobial activity against gram-positive and gram-negative 
bacteria, including antibiotic resistant strains as well as 
mycobacteria and clinically relevant fungi. The applicant stated that 
DefenCathTM is available in a single-dose vial, which is 
sufficient to fill both lumens of the HD catheter, and is instilled 
into the catheter lumen as a lock solution at the conclusion of each 
dialysis session and aspirated at the beginning of the next dialysis 
session. The applicant noted that DefenCathTM cannot be 
flushed or injected into the patient and that dosing is calibrated to 
the volume of the catheter lumens.
    Per the applicant, DefenCathTM was designated by FDA as 
a QIDP in 2015 for the prevention of CRBSI in patients with end-stage 
renal disease (ESRD) receiving HD through a central venous catheter, 
and has been granted FDA Fast Track status. The applicant indicated 
that it is pursuing an NDA under FDA's LPAD for the same indication, 
which the applicant also stated received Priority Review. The applicant 
noted that FDA issued a Complete Response Letter in 2021 denying the 
NDA due to concerns with the third-party manufacturing facility. The 
applicant stated that the NDA has been resubmitted and anticipates 
approval in the third quarter of CY 2022.\205\ We note that, as an 
application submitted under the alternative pathway for certain 
antimicrobial products at Sec.  412.87(d), DefenCathTM is 
eligible for conditional approval for new technology add-on payments if 
it does not receive FDA marketing authorization by the July 1 deadline 
specified in Sec.  412.87(e)(2), provided that the technology receives 
FDA marketing authorization by July 1 of the particular fiscal year for 
which the applicant applied for new technology add-on payments (that 
is, July 1, 2023).
---------------------------------------------------------------------------

    \205\ The statement in the proposed rule (87 FR 28350) that the 
applicant anticipated approval before July 1, 2022 was in error and 
has been corrected here.
---------------------------------------------------------------------------

    The applicant applied for and received a unique ICD-10-PCS 
procedure code to identify cases involving the administration of 
DefenCathTM in 2022. Effective October 1, 2022, 
DefenCathTM administration can be identified by ICD-10-PCS 
procedure XY0YX28 (Extracorporeal introduction of taurolidine anti-
infective and heparin anticoagulant, new technology group 8).
    With regard to the cost criterion, the applicant provided two 
analyses to demonstrate that DefenCathTM meets the cost 
criterion. The applicant first searched the FY 2019 MedPAR file 
released with the FY 2022 IPPS/LTCH PPS final rule for claims based on 
the presence of one of the following ICD-10-CM diagnosis codes used to 
identify ESRD, chronic kidney disease (CKD), acute kidney injury (AKI) 
or acute tubular necrosis (ATN).
[GRAPHIC] [TIFF OMITTED] TR10AU22.105

    Per the applicant, DefenCathTM will be used for patients 
receiving HD through a CVC. The applicant stated that coding to 
identify this population is difficult because the available CVC codes 
only describe the insertion of a CVC. The applicant asserted that it is 
not possible to identify in the MedPAR file those patients who had 
previously received a CVC and are now hospitalized and receiving HD. 
Therefore, the applicant developed two sets of selection criteria: 
claims with codes for HD (Analysis A) and claims with codes for both HD 
and CVC (Analysis B). The applicant asserted that Analysis A overstates 
the population of patients eligible for DefenCathTM because 
it includes any patient receiving HD, regardless of whether a central 
venous catheter is used. The applicant also asserted that Analysis B 
undercounts the potential cases because CVC codes are not always 
available on inpatient claims.
    In the first analysis (Analysis A), which included only claims with 
codes for chronic HD, the applicant searched for claims based on the 
presence of one of the ICD-10-CM diagnosis codes previously listed and 
then limited the selection criteria to claims including ICD-10-CM 
diagnosis code Z49.31 (encounter for adequacy testing for HD)

[[Page 48979]]

or one of the following ICD-10-PCS procedure codes for HD:
[GRAPHIC] [TIFF OMITTED] TR10AU22.106

    After imputing a case count of 11 to any MS-DRG with fewer than 11 
cases in the FY 2019 MedPAR file released with the FY 2022 IPPS final 
rule, the applicant identified a total of 490,790 cases mapping to 512 
MS-DRGs. The following table shows the top 20 MS-DRGs, which account 
for 57% of all cases included in Analysis A.
[GRAPHIC] [TIFF OMITTED] TR10AU22.107

    For Analysis B, the applicant used the same case selection criteria 
as Analysis A (the presence of an ICD-10-procedure or diagnosis code 
for HD only) but further limited cases to those that include one of the 
following ICD-10 procedure codes for the insertion of a CVC.

[[Page 48980]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.108

    The applicant asserted that the patient population in Analysis B 
(HD and central venous catheter) is more likely to receive 
DefenCathTM during an inpatient stay. After imputing a case 
count of 11 to any MS-DRG with fewer than 11 cases, the applicant 
identified a total of 60,679 cases mapping to 408 MS-DRGs. The 
following table shows the top 20 MS-DRGs by case count, which account 
for 72% of all cases included in Analysis B.
[GRAPHIC] [TIFF OMITTED] TR10AU22.109

    In both analyses, the applicant did not remove charges for prior 
technology because DefenCathTM would not replace other 
therapies a patient may receive during an inpatient stay. The applicant 
standardized the charges using the FY 2022 IPPS final rule impact file 
and applied a 4-year inflation factor of 1.281834 to update the charges 
from FY 2019 to FY 2023 based on the inflation factor used to update 
the outlier threshold in the FY 2022 IPPS/LTCH PPS final rule (86 FR 
45542). The applicant did not add charges for new technology as the 
cost of DefenCathTM has not yet been determined but believes 
that the technology meets the

[[Page 48981]]

cost criterion without the additional charges.
    The applicant calculated a final inflated case-weighted average 
standardized charge per case of $116,221 for Analysis A and a final 
inflated case-weighted average standardized charge per case of $203,746 
for Analysis B. The applicant also determined an average case weighted 
threshold amount of $77,290 in Scenario A and $96,645 in Scenario B. 
Because the final inflated case-weighted average standardized charge 
per case for each scenario exceeded the average case-weighted threshold 
amount for both scenarios, the applicant asserted that 
DefenCathTM meets the cost criterion.
    In the proposed rule, we agreed that the technology meets the cost 
criterion and therefore proposed to approve DefenCath\TM\ for new 
technology add on payments for FY 2023. We stated in the proposed rule 
that we expected the applicant to submit its cost per case information 
prior to the final rule, and that we would provide an update regarding 
the new technology add-on payment amount for the technology in this 
final rule. We stated that any new technology add-on payment for 
DefenCathTM would be subject to our policy under Sec.  
412.88(a)(2) where we limit new technology add-on payments for QIDPs to 
the lesser of 75% of the average cost of the technology, or 75% of the 
costs in excess of the MS-DRG payment for the case.
    We invited comments on whether DefenCathTM meets the 
cost criterion and our proposal to approve DefenCathTM for 
new technology add-on payments for FY 2023.
    Comment: The applicant submitted a public comment in support of 
CMS' proposal to approve new technology add-on payments for FY 2023 for 
DefenCathTM. The applicant requested that CMS correct 
erroneous information from the proposed rule, stating that the FDA new 
device approval date is expected later in the third quarter of 2022, 
rather than by July 1, 2022, as stated in the proposed rule. The 
applicant also provided the anticipated cost of DefenCathTM, 
which the applicant states is $5,850 to the hospital, per patient.
    Response: We appreciate the applicant's support and provision of 
the cost information. We appreciate the applicant's clarification that 
the FDA new device approval date is anticipated late in the third 
quarter of CY 2022 rather than by July 1, 2022 as stated in the 
proposed rule. This discussion now accurately reflects the anticipated 
timeline for FDA approval.
    Comment: A commenter expressed concern that without information on 
the cost of DefenCathTM at the time of the publication of 
the proposed rule, it is difficult to comment positively or negatively 
on the cost of the technology. This commenter also expressed concern 
that, without FDA approval at the time of the publication of the 
proposed rule, it is likewise difficult to comment on the potential 
impact of the technology. The commenter raised concerns that applicants 
under the Alternative Pathway for Transformative New Devices and 
Alternative Pathway for Certain Antimicrobial Products do not have to 
meet the substantial clinical improvement criterion under 412.87(d) and 
recommend that CMS incorporate substantial clinical improvement in its 
evaluation of applicants under the alternative pathways.
    Response: We thank the commenter for its input. As discussed in FY 
2020 IPPS/LTCH PPS final rule (84 FR 42294 through 42295), we believe 
that although there may be less certainty of clinical benefit or data 
representing the Medicare beneficiary population as compared to the 
evidence standard for substantial clinical improvement under the 
current new technology add-on payment policy pathway, the benefits of 
providing early access to critical and life-saving new cures and 
technologies that improve beneficiary health outcomes support the 
alternative pathway. We also stated our belief that the evidence base 
to demonstrate substantial clinical improvement may not be fully 
developed at the time of FDA marketing authorization. We refer the 
reader to the FY 2020 IPPS/LTCH PPS final rule for a further discussion 
of the development of these alternative pathways.
    With respect to cost information, consistent with the formula 
specified in section 1886(d)(5)(K)(ii)(I) of the Act, we assess the 
adequacy of the MS-DRG prospective payment rate otherwise applicable to 
discharges involving the new medical service or technology by 
evaluating whether the charges for cases involving the new technology 
exceed certain threshold amounts. The MS-DRG threshold amounts used in 
evaluating new technology add-on payment applications for FY 2023 are 
presented in a data file that is available, along with the other data 
files associated with the FY 2022 IPPS final rule on the CMS website 
at: https://www.cms.gov/medicare/acute-inpatient-pps/fy-2022-ipps-final-rule-home-page. As discussed in the proposed rule, we agreed that 
based on the applicant's cost analysis, the final inflated case-
weighted average standardized charge per case for the technology 
exceeded the applicable average case-weighted threshold amount. We also 
note that applicants for new technology add-on payment are not required 
to have FDA approval by the time of the publication of the proposed 
rule. In addition, and as discussed in the proposed rule and later in 
this final rule, where cost information is not yet available at the 
time of the proposed rule, we note our expectation is that the 
applicant will submit cost information prior to the final rule, and 
indicate that we will provide an update regarding the new technology 
add-on payment amount for the technology, if approved, in the final 
rule.
    Based on the information provided in the application for new 
technology add-on payments, and after consideration of the public 
comments we received, we believe DefenCathTM (a single dose 
vial, solution of Taurolidine (13.5 mg/mL) and Heparin (1000 USP Units/
mL)) meets the cost criterion. Therefore, we are granting a conditional 
approval for DefenCathTM for new technology add-on payments 
for FY 2023, subject to the technology receiving FDA marketing 
authorization by July 1, 2023 (that is, by July 1 of the fiscal year 
for which the applicant applied for new technology add-on payments 
(2023)). In the proposed rule we stated that as an application 
submitted under the alternative pathway for certain antimicrobial 
products at Sec.  [thinsp]412.87(d), DefenCathTM is eligible 
for conditional approval for new technology add-on payments if it does 
not receive FDA marketing authorization by the July 1 deadline 
specified in Sec.  [thinsp]412.87(e)(2), provided that the technology 
receives FDA marketing authorization by July 1 of the particular fiscal 
year for which the applicant applied for new technology add-on payments 
(that is, July 1, 2023) (87 FR 28350). If DefenCathTM 
receives FDA marketing authorization before July 1, 2023, the new 
technology add-on payment for cases involving the use of this 
technology would be made effective for discharges beginning in the 
first quarter after FDA marketing authorization is granted. If FDA 
marketing authorization is received on or after July 1, 2023, no new 
technology add-on payments will be made for cases involving the use of 
DefenCathTM for FY 2023.
    Based on the information at the time of this final rule, the cost 
per case of the DefenCathTM is $5,850. Under Sec.  
412.88(a)(2) we limit new technology add-on payments for QIDPs to the 
lesser of 75% of the average cost of the technology, or 75% of the 
costs in excess of the MS-DRG payment for the case. As a result, we are 
finalizing that,

[[Page 48982]]

subject to DefenCathTM receiving marketing authorization by 
July 1, 2023, the maximum new technology add-on payment for a case 
involving the use of DefenCathTM will be for $4,387.50 for 
FY 2023 (that is, 75% of the average cost of the technology). Cases 
involving the use of DefenCathTM that are eligible for new 
technology add-on payments will be identified by ICD-10-PCS procedure 
code XY0YX28 (Extracorporeal introduction of taurolidine anti-infective 
and heparin anticoagulant, new technology group 8).
c. Other Comments
    We received several public comments on new technology add-on 
payment alternative pathway recommendations that were outside the scope 
of the proposals included in the FY 2023 IPPS/LTCH PPS proposed rule 
and we are therefore not addressing them in this final rule. We 
appreciate these comments and may consider them for possible proposals 
in future rulemaking.
8. Use of National Drug Codes (NDCs) To Identify Cases Involving Use of 
Therapeutic Agents Approved for New Technology Add-On Payment
    As discussed in the FY 2016 IPPS/LTCH PPS final rule (80 FR 49434 
through 49435), as a part of the transition to the ICD-10-CM diagnosis 
and ICD-10-PCS procedure coding system from the ICD-9-CM coding system, 
CMS established the use of Section ``X'' New Technology codes within 
the ICD-10-PCS classification to more specifically identify new 
technologies or procedures that have historically not been captured 
through ICD-9-CM codes, or to more precisely describe information on a 
specific procedure or technology than is found with the other sections 
of ICD-10-PCS. However, as noted in the FY 2023 IPPS/LTCH PPS proposed 
rule (87 FR 28353 through 28355), CMS continued to receive comments 
from interested parties, including representatives from hospital 
associations, software vendors, professional societies, and coding 
professionals, opposing the continued creation of new ICD-10-PCS (for 
example, Section X) procedure codes for the purpose of administering 
the new technology add-on payment for drugs and biologics. 
Specifically, public comments from the ICD-10 Coordination and 
Maintenance Committee Meetings have stated that the ICD-10-PCS 
classification system was not intended to represent unique drugs/
therapeutic agents and is not an appropriate code set for this purpose. 
Commenters explained that, since the implementation of ICD-10, Section 
X codes have been established for procedures describing the 
administration of a drug/therapeutic agent, which historically were not 
typically coded in the inpatient hospital setting. Commenters stated 
their belief that it was not logical nor should it be expected for 
hospital coding professionals to seek codes for the administration of 
drugs within the ICD-10-PCS classification system. In addition, we 
noted that over the past 3 years, the number of applications for new 
technology add-on payments has continued to increase, which has 
subsequently resulted in an increasing number of requests for unique 
ICD-10-PCS (for example, Section X) procedure codes specifically for 
the purposes of administering the new technology add-on payments.
    As discussed in the proposed rule, the current process of 
requesting, proposing, finalizing and assigning new ICD-10-PCS 
procedure codes to identify and describe the administration of drugs 
involves several steps, as described further in this section, and 
frequently results in a number of procedure codes that are created 
unnecessarily when the drug/therapeutic agents do not receive approval 
for the new technology add-on payments, as the administration of drugs/
therapeutic agents is not typically coded in the inpatient hospital 
setting. Applicants seeking a unique ICD-10-PCS (for example, Section 
X) procedure code to identify the use of their technology for purposes 
of new technology add-on payments must complete the code request 
process prior to learning the outcome of their new technology add-on 
payment application. This process involves a number of steps, 
including: gathering relevant information and submitting the ICD-10-PCS 
code request; developing a slide deck for the ICD-10 Coordination and 
Maintenance Committee Meeting; and reviewing the background paper draft 
for the ICD-10 Coordination and Maintenance Committee Meeting agenda 
and meeting materials. CMS also expends significant time, effort, and 
resources to administer this process, which is compounded by the 
increasing number of requests for unique ICD-10-PCS (for example, 
Section X) procedure codes. CMS must work with applicants to review, 
prepare, and present the code proposals at ICD-10 Coordination and 
Maintenance Committee Meetings, then review and summarize public 
comments received in response to the meetings, and ultimately make a 
decision on the codes requested for new technology add-on payment 
policy purposes before the outcome of the new technology add-on payment 
application (approval or denial) is known. Following the end of the 
three-year timeframe for which a code was created in connection with a 
new technology add-on payment application, the disposition of the 
Section X code is addressed at a later ICD-10 Coordination and 
Maintenance Committee meeting and CMS subsequently receives public 
comments that must be reviewed regarding this disposition.
    We stated that interested parties had submitted comments that 
suggested alternative options to the use of Section X procedure codes 
to identify therapeutic agents for the administration of the new 
technology add-on payment policy. The majority of commenters supported 
using National Drug Codes (NDCs), because it would avoid creating 
duplicate codes within the ICD-10-PCS and NDC code sets to identify the 
same technology/product, which would allow for predictive and efficient 
coding. Commenters also stated that using NDCs would generate product 
data on inpatient claims that would allow for outcomes analyses, thus 
providing the same benefit as a unique ICD-10-PCS code. Some commenters 
suggested using the 3E0 Administration Table within the ICD-10-PCS code 
set, as opposed to Section X, as they stated this would be a more 
intuitive location for coders to look for ICD-10-PCS procedure codes 
describing the administration of therapeutic agents. However, a 
commenter noted that this would be unsustainable due to the potentially 
large number of new products coming to market. A few commenters also 
suggested using different drug terminologies, such as RxNorm, in lieu 
of using Section X codes for the time period needed to administer the 
new technology add-on payment. We also noted that we have previously 
established the use of NDCs as an alternative code set for the purposes 
of administering the new technology add-on payment in circumstances 
where an ICD-10-PCS code was not available to uniquely identify the use 
of the technology. In the FY 2013 IPPS/LTCH PPS final rule (77 FR 53351 
through 53354), we established the use of the NDC code set to identify 
oral medications where no inpatient procedure was associated, to report 
the oral administration of the drug DIFICIDTM. We finalized 
that the NDC for DIFICIDTM would be used in conjunction with 
an ICD-9-CM diagnosis code to uniquely identify the indication for 
which administration of the drug (technology) was performed for

[[Page 48983]]

new technology add-on payment purposes. In the FY 2019 IPPS/LTCH PPS 
final rule (83 FR 41311), we stated that we believed that the 
circumstances with respect to the identification of eligible cases 
reporting the use of VABOMERETM, which was administered by 
IV infusion, were similar to those addressed in the FY 2013 IPPS/LTCH 
PPS final rule with regard to DIFICIDTM because we also did 
not have current ICD-10-PCS code(s) to uniquely identify the use of 
VABOMERETM to make the new technology add-on payments. 
Therefore, consistent with our approach in FY 2013, we stated that we 
would identify cases involving the use of VABOMERETM that 
were eligible for FY 2019 new technology add-on payments using its NDCs 
65293-0009-01 or 70842-0120-01\206\ (VABOMERETM Meropenem-
Vaborbactam Vial). At the time of its new technology add-on payment 
application approval, VABOMERETM was not assigned a 
corresponding ICD-10-PCS procedure or ICD-10-CM diagnosis code along 
with its NDCs. In addition, cases involving the use of two therapeutic 
agents that qualify for NCTAP, which is administered similarly to the 
new technology add-on payment, are identified using the NDCs for these 
products for the purposes of the NCTAP, because there are not currently 
ICD-10-PCS procedure codes that uniquely describe the administration of 
these therapies.\207\
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    \206\ We note that these are not the FDA assigned NDCs, but 
rather have been converted from 10-digit NDCs assigned by FDA to the 
HIPAA compliant 11-digit format.
    \207\ New COVID-19 Treatments Add-On Payment (NCTAP) https://www.cms.gov/medicare/covid-19/new-covid-19-treatments-add-payment-nctap.
---------------------------------------------------------------------------

    In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28353 through 
28355), we stated that we believed that our previous policies regarding 
the use of NDCs to identify the administration of certain therapeutic 
agents could be consistently applied toward broader future usage of the 
NDCs to identify therapeutic agents eligible for the new technology 
add-on payment. Additionally, we stated that we believed that the use 
of an existing code set to identify therapeutic agents eligible for the 
new technology add-on payment would address concerns raised by 
commenters regarding the use of the ICD-10-PCS classification system to 
identify these agents, and reduce the need for applicants to seek a 
unique ICD-10-PCS code through the ICD-10-PCS Section X code request 
process in advance of a determination on their new technology add-on 
payment applications.
    Therefore, as we discussed further in this section of the proposed 
rule and this final rule, we proposed for FY 2024 to instead use NDCs 
to identify cases involving the use of therapeutic agents approved for 
the new technology add-on payment. We stated that we anticipated that 
this proposal would reduce work for hospital coding professionals in 
becoming familiar with newly created ICD-10-PCS Section X codes to 
describe the administration of therapeutic agents and in searching for 
these codes within the documentation and within the classification in 
what may be non-intuitive locations. We stated that we also expected 
that the proposed change would address concerns regarding the creation 
of duplicative codes within the ICD-10-PCS procedure coding system to 
describe the administration of therapeutic agents, which would also 
reduce the need for vendors to incorporate additional procedure codes 
into their coding products; for educators to provide training on these 
codes; and for programmers to maintain codes that may be seldom 
reported on inpatient claims but for the purposes of the new technology 
add-on payment, in their databases. We stated it would also reduce 
efforts associated with determining the disposition of procedure codes 
describing therapeutic agents that have reached the end of their 3-year 
new technology add-on payment timeframe.
    Furthermore, we stated that we believed that NDCs are a viable 
alternative to Section X codes for the administration of the new 
technology add-on payment for therapeutic agents. We stated that we 
believed inpatient hospital staff are familiar with using NDCs, and as 
stated earlier, we have previously utilized NDCs to administer the new 
technology add-on payment. However, to allow for adequate time to 
implement this regular usage of NDCs with the new technology add-on 
payment for health care providers and hospital coding professionals, we 
proposed a transitional period for FY 2023. During this transitional 
period, we proposed to utilize NDCs to identify the administration of 
therapeutic agents for new technology add-on payment purposes. However, 
we also proposed to utilize ICD-10-PCS Section X codes, including codes 
newly created for FY 2023, for therapeutic agents during the FY 2023 
new technology add-on payment application cycle. Beginning with the FY 
2024 new technology add-on payment application cycle, we proposed to 
utilize only NDCs to identify claims involving the administration of 
therapeutic agents approved for the new technology add-on payment, with 
the exception of claims involving therapeutic agents that are not 
assigned an NDC by FDA (for example, blood, blood products, etc.) and 
are approved for the new technology add-on payment. Cases involving the 
use of these technologies approved for the new technology add-on 
payment would continue to be identified based on the assigned ICD-10-
PCS procedure code. A unique ICD-10-PCS procedure code would also still 
be needed to identify cases involving the use of CAR T-cell and other 
immunotherapies that may be assigned to Pre-MDC MS-DRG 018, because the 
ICD-10 MS-DRG GROUPER logic for assignment to Pre-MDC MS-DRG 018 is 
comprised of the procedure codes describing these CAR T-cell and other 
immunotherapy products. Therefore, under the proposal, beginning with 
FY 2024 new technology add-on payment applications submitted for a 
therapeutic agent, CMS would review the information and inform the 
applicant, in advance of the deadline for submitting an ICD-10-PCS 
procedure code request to the ICD-10 Coordination and Maintenance 
Committee for consideration at the March meeting, if it would be 
necessary to submit such a code request for purposes of identifying 
cases involving the use of the therapeutic agent for the new technology 
add-on payment, if approved, or if, based on the information made 
available with the application, the NDC could be used to identify such 
cases, and therefore, the applicant would not need to submit an ICD-10-
PCS procedure code request. For each applicable technology that may be 
approved for new technology add-on payment, we proposed to indicate the 
NDC(s) to use to identify cases involving the administration of the 
therapeutic agent for purposes of the new technology add-on payment.
    Specifically, we proposed that, during the transitional period 
beginning with discharges on or after October 1, 2022 (FY 2023), the 
administration of therapeutic agents newly approved for new technology 
add-on payments would be uniquely identified using either their 
respective NDC(s) or ICD-10-PCS procedure code(s), in combination with 
ICD-10-CM codes when appropriate. As stated in our FY 2013 IPPS/LTCH 
PPS final rule, the use of the NDCs ``does not preclude CMS from using 
additional ICD-9-CM procedure or diagnosis codes to identify cases for 
this new technology in conjunction with this alternative code

[[Page 48984]]

set'' (77 FR 53352). Therefore, we stated when necessary, we may 
require the use of additional ICD-10-PCS procedure and/or ICD-10-CM 
diagnosis codes to uniquely identify cases using these technologies. We 
stated that we would continue the use of the existing ICD-10-PCS 
procedure codes to identify the administration of therapeutic agents 
previously approved for the new technology add-on payment and that 
remain eligible for the new technology add-on payment for FY 2023.
    We further proposed that, beginning with discharges on or after 
October 1, 2023 (FY 2024), the administration of therapeutic agents 
newly approved for the new technology add-on payments beginning FY 2024 
or a subsequent fiscal year would be uniquely identified only by their 
respective NDC(s), along with the corresponding existing ICD-10 code(s) 
required to uniquely identify the therapeutic agents, when necessary, 
to make the new technology add-on payments. For technologies that were 
newly approved for new technology add-on payments for FY 2023 
(beginning with discharges on or after October 1, 2022) and remain 
eligible for the new technology add-on payment for FY 2024 or a 
subsequent fiscal year, we proposed to continue to allow the use of 
either the existing ICD-10-PCS procedure codes or NDCs to identify the 
administration of those therapeutic agents. For technologies that were 
newly approved for new technology add-on payments prior to FY 2023 and 
remain eligible for the new technology add-on payment for FY 2024 or a 
subsequent fiscal year, we stated we would continue to use the existing 
ICD-10-PCS procedure codes to identify the administration of those 
therapeutic agents. We invited public comments on our proposal to 
utilize NDCs to identify claims involving the use of therapeutic agents 
approved for new technology add-on payments, including any potential 
concerns regarding adoption of this code set for the identification of 
therapeutic agents for purposes of new technology add-on payments.
    Comment: We received multiple comments related to the proposed 
policy. A commenter stated that the ICD-10-PCS coding system is not 
intended to represent unique therapeutic agents and is not an 
appropriate code set for this purpose. The commenter also stated that 
ICD-10-PCS codes have often been created unnecessarily because the 
therapeutic agent was not approved for a new technology add-on payment, 
and that in the absence of a new technology add-on payment, 
administration of therapeutic agents is not typically coded in the 
hospital inpatient setting. The commenter stated that assignment of 
ICD-10-PCS codes by coding professionals solely for new technology add-
on payment purposes, for services that would not otherwise be coded in 
the inpatient setting, is administratively burdensome. Another 
commenter mentioned that using FDA's NDCs would allow for superior data 
capture methods and eliminate manual intervention to complete coding. 
Another commenter stated that given the likelihood of continued 
therapeutic innovation, it viewed this proposed policy as a path toward 
earlier access to these therapies by Medicare beneficiaries. A 
commenter stated that as hospitals typically capture all NDCs related 
to a patient stay within their electronic medical record systems, these 
codes could easily be included with claims. The commenter requested 
that CMS configure its system to accept all NDC codes, not just those 
related to products eligible to receive new technology add-on payments, 
to significantly reduce administrative burden for hospitals.
    Several commenters also suggested that if CMS finalizes this 
policy, we should establish a process to promote and educate hospitals 
on this policy change to ensure that they are prepared for billing 
under the new process, including clearly indicating which NDC(s) should 
be used to identify a particular therapeutic agent for new technology 
add-on payment purposes, as some therapeutic agents may have more than 
one applicable NDC. Multiple commenters also urged CMS to extend the 
proposed transitional process from one year to two years, that is, 
through FY 2024, with NDC utilization beginning in FY 2025. Some 
commenters also suggested that during this two-year transition period, 
CMS should analyze claims data and obtain feedback from interested 
parties to understand hospitals' usage of NDCs, prior to eliminating 
the process for using ICD-10-PCS codes.
    A commenter expressed support for our proposal to continue use of 
ICD-10-PCS codes for cases assigned to Pre-MDC MS-DRG 018 (Chimeric 
Antigen Receptor (CAR) T-cell and Other Immunotherapies) because 
hospitals may not have had experience with submitting NDCs as part of 
hospital inpatient claim forms for such cases. Another commenter stated 
that it was concerned with our proposal to use NDCs in lieu of ICD-10-
PCS codes for allogeneic HSCT donor sources because providers, such as 
hospitals, primarily report ICD-10-PCS codes and are unfamiliar with 
NDCs for these donor sources. The commenter requested that CMS expand 
our proposed exceptions to the use of NDCs for therapeutic agents to 
also include the unique ICD-10-PCS codes describing the infusion of 
therapeutics that begin with the characters XW1, as well as any future 
advanced cell therapy donor sources.
    A commenter explained that it disagreed with creating individual 
ICD-10-PCS codes for specific drugs because it believed that ICD-10-PCS 
nomenclature is for surgical procedures and not specific drugs. The 
commenter expressed that coders do not routinely assign ICD-10-PCS 
codes for example, for drugs, radiology procedures, and lab tests, and 
that this would be an administrative burden on coders, as well as 
billers, to ensure these drugs are identified through ICD-10-PCS 
coding. The commenter stated that it would be more cost effective to 
identify these specific drugs by their NDC number and not an ICD-10-PCS 
code to ensure adequate reimbursement. Another commenter recommended 
that CMS reevaluate our proposal to transition to the use of NDCs to 
identify the administration of a therapeutic agent for purposes of new 
technology add-on payment because the commenter stated that it would 
add undue burden on coders who typically do not assign ICD-10-PCS codes 
for drug administration for inpatient cases. The commenter also 
requested that CMS pursue broader inpatient claims reporting 
improvements.
    Response: We appreciate the input from the commenters on our 
proposed use of NDCs to identify cases involving use of therapeutic 
agents approved for new technology add-on payment and have taken these 
comments into consideration, as discussed later in this section.
    Comment: A couple of commenters were grateful to CMS for listening 
to feedback from interested parties and putting this proposal forward, 
but had significant questions about implementation and existing 
hospital resources for CMS to address prior to finalizing the use of 
NDCs, and recommended that CMS retain the ICD-10-PCS coding for new 
technology add-on payments. Other commenters stated that CMS does not 
currently require NDC reporting on Medicare inpatient claims, except in 
rare cases of previous new technology add-on payments, and that 
reporting NDCs for only the occasional drug, and on an inpatient claim, 
would create new operational burdens for hospitals, especially smaller 
and rural hospitals, that do not currently have a system for concurrent 
scanning of NDCs upon administration

[[Page 48985]]

of therapeutic agents. Another commenter stated that some hospitals 
already have systems that would provide an automated method of 
capturing NDC codes on inpatient claims, but that other facilities, 
will face new and laborious manual processes despite reporting NDCs on 
certain outpatient claims. A commenter noted that a recent analysis of 
hospitals by Deloitte found that incorrect or missing NDC data had 
caused inaccurate billing.\208\ The commenter further stated that it 
believed the process to educate hospitals and subsequently require the 
use of NDCs could possibly create a greater administrative burden than 
it would save. Some commenters also noted that these burdens would come 
at a time when hospitals continue to address resource and staffing 
constraints resulting from the COVID-19 PHE. A commenter explained that 
the transition to NDCs may create complexity in tracking patient cases, 
which may make it difficult to perform further valuable research on 
quality of care issues and health outcomes. Another commenter stated 
that it believed any changes to the current process should be done in a 
careful manner to ensure that CMS' efforts to move to a more 
streamlined system do not have any inadvertent implications on claims 
data.
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    \208\ Evaluating Hospital Pharmacy Inventory Management and 
Revenue Cycle Processes, White Paper Guidance for Healthcare 
Internal Auditors https://ahia.org/assets/Uploads/pdfUpload/WhitePapers/EvaluatingHospitalPharmacyInventoryManagementandRevenueCycleProcesses.pdf.
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    A commenter stated that because there are multiple proposed 
exceptions to the use of NDCs, the streamlining and burden reduction of 
this policy may be limited. Another commenter stated that this proposal 
would unnecessarily require two separate standards for devices and 
drugs.
    A commenter stated that hospitals are faced with increasingly 
complex requirements to report drugs to secure reimbursement with 
variations based upon code sets and patient status. The commenter 
stated that for inpatient claims there are two ways of reporting drugs 
for additional payment: hemophilia products reported with HCPCS codes 
and billed units per date of service (DOS), and new technology add-on 
payment-eligible drugs reported with a single ICD-10-PCS code 
independent of number of doses or days administered. The commenter 
further stated that outpatient claims are reported with HCPCS code and 
billed units per DOS, with the exception of self-administered oral 
drugs that were not assigned HCPCS codes, as well as specific new drugs 
and biologicals billed under the HCPCS Code C9399 (Unclassified drug or 
biological) and for which the commenter stated that CMS requires that 
the drug name, dose, amount of waste and NDC number be manually added 
to the remarks section of the claim. The commenter stated that hospital 
pharmacy and billing IT systems need remediation with complex 
maintenance in order to accurately bill drugs based upon the type of 
drug, whether it is eligible for new technology add-on payment and the 
status of the patient, and that many hospitals currently do not bill 
some new technology add-on payment-eligible drugs due to the cumbersome 
process and amount of the anticipated reimbursement, which the 
commenter stated could lead to inadvertent billing errors or omissions 
when a business decision is made that the anticipated payment will be 
less than the cost to remediate IT systems and maintain these complex 
billing rules. The commenter further stated that inaccurate data could 
lead to erroneous future rate-setting by CMS when data is missing from 
claims. The commenter recommended that CMS instead consider that new 
technology add-on payment-eligible drugs be billed on inpatient claims 
with the same instructions as currently used to report hemophilia 
products, with HCPCS codes and billing units by DOS. The commenter 
explained that having one way to bill drugs on inpatient and outpatient 
claims would reduce IT programming expense and reduce errors with 
increased standardization. The commenter requested that the CMS HCPCS 
Working Group assign HCPCS codes to items eligible for new technology 
add-on payment, even if they normally would not be assigned a HCPCS 
code. The commenter stated that as HCPCS codes are assigned quarterly, 
this would eliminate the need for special notification if new NDCs are 
marketed after the implementation of the new technology add-on payment 
status and before the next rule-making cycle. The commenter further 
recommended that if CMS were to finalize its proposal to use NDCs, CMS 
should work with the National Uniform Billing Committee (NUBC) to 
clarify how 5010 HIPAA transaction standard units of measure and 
billing quantities should be calculated and reported. The commenter 
also recommended that CMS work with NUBC to require all payers to 
accept NDCs on inpatient claims to avoid payer-specific instructions, 
which require complex and expensive IT programming.
    This commenter and several other commenters also requested CMS 
provide additional information in rulemaking on how NDCs would be 
utilized: if a NDC may be reported on multiple DOS, or if multi-day 
therapies must be combined into a single line; whether units of 
measures and quantities would be required to be reported; if this 
policy would apply specifically for therapeutic agents eligible for new 
technology add-on payment or for all therapeutic agents used in 
Medicare; how a drug product with multiple NDCs would be handled; and 
how CMS would publish available NDCs for analysis by interested parties 
and update NDCs if the codes were changed by FDA post-rulemaking.
    Several commenters also emphasized the complexity of information 
transfer from the 10-digit FDA-assigned NDC number format to the 5010 
HIPAA transaction standard required 11-digit NDC number format used for 
billing on claims, especially when trying to reconstitute the NDC back 
to its FDA standard. Other commenters noted future concerns with 
potential changes in FDA assignment of NDC numbers from 10-digits to a 
new 16-digit format, as well as the modifications needed to the 837I/
UB-04 forms to accommodate this change.
    In addition, commenters highlighted issues regarding a lack of 
national standards for correctly coding drugs using NDCs, as well as a 
lack of acceptance of NDCs by all payers, on inpatient claims. A 
commenter further stated that without specific guidance, current NDC 
reporting is often inaccurate, resulting in increasing claim rejections 
for an invalid NDC number. A couple of commenters explained that 
currently, Form Locator 43 (FL43) on the UB-04 form is not unique to 
only the NDC number. A commenter stated that they believed that the 
proposed usage of this field may not be allowed because FL43 is 
intended for the reporting of NDCs for Medicaid drug rebates, but not 
for the new technology add-on payment. Some commenters also stated that 
there was a potential for claim line limits to be reached if multiple 
NDCs were reported on one claim. These commenters believed that this 
policy change should be considered as part of broader inpatient claims 
reporting improvements, with another commenter further stating that 
grouping together necessary changes to 837I/UB-04 claim forms, 
alongside updated instructions on NDC reporting for inpatients, would 
minimize short-term burden as well as data inaccuracies.
    Due to these concerns, a few commenters suggested that CMS further

[[Page 48986]]

study the feasibility of this proposed policy change though a Technical 
Advisory Group (TAG), consisting of industry experts, before finalizing 
and implementing this policy. A commenter further recommended that 
other suggestions noted by CMS, such as the 3E0 Administration Table 
within ICD-10-PCS code set and RxNorm, along with other options, such 
as the HCPCS code set or a revision to the process that allows the ICD-
10-PCS code to be pending assignment until the finalization of the new 
technology add-on payment determination, should be explored by the TAG 
and presented in an upcoming proposed rule. Another commenter 
recommended that CMS address alignment with timing for U.S. 
implementation of ICD-11 codes.
    Response: We appreciate the input from commenters on our proposed 
use of NDCs to identify cases involving use of therapeutic agents 
approved for new technology add-on payments. We acknowledge that 
interested parties have continued to share concerns regarding our 
current use of the ICD-10-PCS classification system to identify 
therapeutic agents eligible for new technology add-on payments. As 
discussed in the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28353 
through 28355), we had anticipated that our proposal to use the NDC, 
with its previously established use as an alternative code set for the 
purposes of administering the new technology add-on payment, would 
reduce work for hospital coding professionals in becoming familiar with 
newly created ICD-10-PCS Section X codes to describe the administration 
of therapeutic agents. We had also expected that this proposed change 
would address concerns regarding the creation of duplicative codes 
within the ICD-10-PCS procedure coding system, which would also reduce 
the need for vendors to incorporate additional procedure codes into 
their coding products; for educators to provide training on these 
codes; and for programmers to maintain codes that may be seldom 
reported on inpatient claims but for the purposes of the new technology 
add-on payment in their databases.
    However, as previously summarized, commenters have shared concerns 
that our proposed use of NDCs for this purpose may impose new 
administrative burdens to hospitals. For example, commenters indicated 
that hospital pharmacy and billing IT systems that are not currently 
required to use NDCs for billing on inpatient Medicare claims may need 
to use manual processes to report NDCs for the purposes of new 
technology add-on payments, because they may not have existing 
automated systems in place.
    Furthermore, based on review of comments, it is unclear to us the 
extent to which hospitals and health care providers would utilize NDCs 
during a transition period in FY 2023, especially if they believe 
adding these manual processes may result in inadvertent billing errors 
for therapeutic agents eligible for new technology add-on payments, 
which commenters state may be further compounded by staffing shortages 
due to the COVID-19 pandemic. This may limit our ability to obtain 
comprehensive feedback from interested parties during the transition 
period, as suggested by commenters, or perform an analysis of claims 
data to assess if NDCs are being used, prior to fully transitioning to 
using NDCs for this purpose.
    Therefore, after careful consideration of the concerns raised by 
commenters, we are not finalizing this proposed policy, and will 
instead reassess this policy proposal in future rulemaking. We believe 
that this will allow for adequate time to evaluate and consider the 
issues raised by commenters. We understand that commenters would be 
interested in further details on how NDCs would be operationalized for 
the purposes of any such policy change, along with a process to educate 
hospitals on these changes to ensure accurate billing throughout a 
transition period. We appreciate that commenters have raised a number 
of important questions on our proposal, and we will continue to engage 
the public in these conversations.
9. Proposal to Publicly Post New Technology Add-On Payment Applications
    As noted in section II.F.1.f. of the preamble of this final rule, 
applicants for new technology add-on payments for new medical services 
or technologies must submit a formal request, including a full 
description of the clinical applications of the medical service or 
technology and the results of any clinical evaluations demonstrating 
that the new medical service or technology represents a substantial 
clinical improvement (unless the application is under one of the 
alternative pathways), along with a significant sample of data to 
demonstrate the new medical service or technology meets the high-cost 
threshold (OMB-0938-1347). See section II.F.1.f. of the preamble of 
this final rule for further details on the data and evidence that can 
be submitted. We post complete application information and final 
deadlines for submitting a full application on the CMS website at 
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/newtech. We also post on the same website tracking 
forms completed by each applicant, which include the name of each 
applicant, name of the technology, and a brief description so that 
interested parties can identify the new medical services or 
technologies under review before the annual proposed rule. 
Additionally, section 1886(d)(5)(K)(viii) of the Act provides for a 
mechanism for public input before the publication of a proposed rule 
regarding whether a medical service or technology represents a 
substantial clinical improvement. Consistent with the Act, we hold an 
annual Town Hall meeting, typically in December following notice of the 
meeting in the Federal Register.
    As set forth in 42 CFR 412.87(e)(1), CMS considers whether a 
technology meets the criteria for the new technology add-on payment and 
announces the results as part of its annual updates and changes to the 
IPPS. Accordingly, in drafting the proposed rule, CMS reviews each new 
technology add-on payment application it receives under the pathway 
specified by the applicant at the time of application submission, along 
with supplemental information\209\ obtained from the applicant, 
information provided at the Town Hall meeting, and comments received in 
response to the Town Hall meeting. In the proposed rule, CMS summarizes 
the information contained in the application, including the applicant's 
explanation of what the technology does, background on the disease 
process, information about the FDA approval/clearance, and the 
applicant's assertions and supporting data on how the technology meets 
the new technology add-on payment criteria under Sec.  412.87. In 
summarizing this information for inclusion in the proposed rule, CMS 
restates or paraphrases information contained in the application and 
attempts to avoid misrepresenting or omitting any of an applicant's 
claims. CMS also tries to ensure that sufficient information is 
provided in the proposed rule to facilitate public comments on whether 
the medical service or technology meets the new technology add-on 
payment criteria. Currently, however, CMS does not make the 
applications themselves, as completed by the applicants, publicly 
available. In addition, CMS generally

[[Page 48987]]

does not take into consideration information that is marked as 
confidential when determining whether a technology meets the criteria 
for new technology add-on payments.
---------------------------------------------------------------------------

    \209\ For the FY 2023 new technology add-on payment 
applications, the supplemental information deadline to guarantee 
inclusion in the IPPS proposed rule was December 17, 2021.
---------------------------------------------------------------------------

    We note that in the past, CMS has received requests from the public 
to access and review the new technology add-on payment applications to 
further facilitate comment on whether a technology meets the new 
technology add-on payment criteria. In consideration of this issue, we 
stated in the proposed rule that we agree that review of the original 
source information from the applications for new technology add-on 
payments may help to inform public comment. Further, making this 
information publicly available may foster greater input from experts in 
the stakeholder community based on their review of the completed 
application forms and related materials. Accordingly, as we discuss 
further in this section of the proposed rule and this final rule, we 
stated that we believe that providing additional information to the 
public by publicly posting the applications and certain related 
materials online may help to further engage the public and foster 
greater input and insights on the various new medical services and 
technologies presented annually for consideration for new technology 
add-on payments.
    We stated that we also believe that posting the applications online 
would reduce the risk that we may inadvertently omit or misrepresent 
relevant information submitted by applicants, or are perceived as 
misrepresenting such information, in our summaries in the rules. It 
also would streamline our evaluation process, including the 
identification of critical questions in the proposed rule, particularly 
as the number and complexity of the applications have been increasing 
over time. That is, by making the applications available to the public 
online, we would afford more time for CMS to process and analyze the 
supporting data and evidence rather than reiterate parts of the 
application in the rule.
    Therefore, to increase transparency, enable increased stakeholder 
engagement, and further improve and streamline our evaluation process, 
we proposed in the FY 2023 IPPS/LTCH PPS proposed rule to publicly post 
online future applications for new technology add-on payments. 
Specifically, beginning with the FY 2024 application cycle, we proposed 
to post online the completed application forms and certain related 
materials (for example, attachments, uploaded supportive materials) 
that we receive from applicants. Additionally, we proposed to post 
information acquired subsequent to the application submission (for 
example, comments received after the New Technology Town Hall, updated 
application information, additional clinical studies, etc.). We 
proposed that we would not post the cost and volume information the 
applicant provides in the application form itself or as attached 
materials, or any material included with the application that the 
applicant indicates is not releasable to the public because the 
applicant does not own the copyright or the applicant does not have the 
appropriate license to make the material available to the public, as 
further described in the next paragraph. We proposed that we would 
publicly post the completed application forms and related materials no 
later than the issuance of the proposed rule, which would afford the 
public the full public comment period to review the information 
provided by the applicant in its application.
    With respect to copyrighted materials, we proposed that on the 
application form itself, the applicant would be asked to provide a 
representation that the applicant owns the copyright or otherwise has 
the appropriate license to make all the copyrighted material included 
with its application public with the exception of those materials 
identified by the applicant as not releasable to the public, as 
applicable. For any material included with the application that the 
applicant indicates as copyrighted and/or not otherwise releasable to 
the public, we proposed that the applicant must either provide a link 
to where the material can be accessed or provide an abstract or summary 
of the material that CMS can make public, and CMS will then post that 
link or abstract or summary online, along with the other posted 
application materials. We invited comments on this proposal.
    Under our current practice, we include in the final rule 
information on the cost of each technology that is approved for the new 
technology add-on payment for the purposes of calculating the maximum 
add-on payment, and information on the anticipated volume of the 
technology for purposes of the impact analysis. For the proposed rule, 
specifically for applications submitted under the alternative pathway, 
our current practice is to propose whether or not to approve the 
application based on the eligibility criteria for the alternative 
pathway under 42 CFR 412.87(c) or (d) and, where cost information is 
available from the applicant, to use this information in proposing a 
maximum add-on payment amount. Where cost information is not yet 
available, we note our expectation is that the applicant will submit 
cost information prior to the final rule, and indicate that we will 
provide an update regarding the new technology add-on payment amount 
for the technology, if approved, in the final rule. We noted that we 
would continue this same approach with respect to including cost and 
volume information in the proposed and final rules. However, as noted, 
under our proposal to post online the new technology add-on payment 
applications, we would not include cost and volume information for 
either traditional or alternative pathway applications as part of the 
application materials that would be posted online.
    We noted that at times an applicant may furnish information marked 
as proprietary or trade secret information along with its application 
for new technology add-on payments. Currently, the application 
specifies that data provided in the application or tracking form may be 
subject to disclosure and instructs the applicant to mark any 
proprietary or trade secret information so that CMS can attempt, to the 
extent allowed under Federal law, to keep the information protected 
from public view.\210\ We further stated that this instruction would 
change under our proposal such that information included in the 
application, other than cost and volume information, would be made 
publicly available online through posting of the application. We 
emphasized that the applicant should not submit as part of its 
application any such proprietary or trade secret information that it 
does not want to be made publicly available online. As noted, under our 
existing practice we stated that we generally do not consider 
information that is marked as confidential, proprietary, or trade 
secret when determining whether a technology meets the criteria for new 
technology add-on payments.
---------------------------------------------------------------------------

    \210\ See new technology add-on payment application included in 
the FY 2023 New Technology Application Packet, available at: https://www.cms.gov/files/zip/fy-2023-new-technology-application-packet.zip; and FY 2023 Tracking Forms, available at: https://www.cms.gov/files/document/fy-2023-tracking-forms-applicants.pdf.
---------------------------------------------------------------------------

    We also stated that this proposal would not change the current 
timeline or evaluation process for new technology add-on payments, the 
criteria used to assess applications, or the deadlines for various data 
submissions. Additionally, we stated that we do not expect added 
burdens on prospective applicants as a result of this

[[Page 48988]]

proposal since we did not propose to fundamentally change the 
information collected in the application itself or the supplemental 
information that would be furnished to support the application. As 
noted, the aim of the proposed policy change is to increase accuracy, 
transparency, and efficiency for both CMS and stakeholders.
    In connection with the proposal to post the new technology 
applications online, we stated that we expect we would also make 
changes to the summaries that appear in the annual proposed and final 
rules, given that the public would have access to the submitted 
applications themselves (excluding certain information and materials as 
described previously), while also continuing to provide sufficient 
information in the rules to facilitate public comments on whether a 
medical service or technology meets the new technology add-on payment 
criteria. Specifically, we stated that we do not anticipate summarizing 
each entire application in the Federal Register as we have in the past, 
given the expanded and public access to the applications under the 
proposal. In some instances, such as the discussion of the substantial 
clinical improvement criterion, we stated that we expect to provide a 
more concise summary of the evidence or a more targeted discussion of 
the applicant's claims about how that criterion is met based on the 
evidence and supporting data (although this may vary depending on the 
application, new medical service or technology, and the nature of 
supporting materials provided). We expect that we would continue to 
generally include, at a high-level, the following information in the 
proposed and final rules: the technology and applicant name; a 
description of what the technology does; background on the disease 
process; the FDA approval/clearance status; and a summary of the 
applicant's assertions. We also noted we expect to provide more 
succinct information as part of the summaries in the proposed and final 
rules regarding the applicant's assertions as to how the medical 
service or technology meets the newness, cost, and substantial clinical 
improvement criteria. For example, we would provide a list of the 
applicant's assertions for whether the technology meets the three sub-
criteria under the substantial clinical improvement criterion \211\ and 
a list of the sources of data submitted in support of the assertions, 
along with references to the application in support of these lists. In 
the proposed rule, we stated we would also continue to provide 
discussion of the concerns or issues we identified with respect to 
applications submitted under the traditional pathway, and for an 
alternative pathway application, we intend to continue to propose 
whether to approve or disapprove the application, including noting any 
concerns we have identified, and, as applicable, the maximum add-on 
payment amount, where cost information is available. In the final rule, 
we would continue to provide an explanation of our determination of 
whether a medical service or technology meets the applicable new 
technology add-on payment criteria and, for approved technologies, the 
final add-on payment amounts. We stated that as noted, we believe the 
proposal to post online the completed application forms and other 
information described previously would afford greater transparency 
during the annual rulemaking, for purposes of determining whether a 
medical service or technology is eligible for new technology add-on 
payments.
---------------------------------------------------------------------------

    \211\ Sub-criteria referenced are those listed in Question 36 of 
the new technology add-on payment application, specifically 
Questions 36a-36c.
---------------------------------------------------------------------------

    We sought public comment on our proposal to publicly post online 
the completed application forms and certain related materials and 
updated application information submitted subsequent to the initial 
application submission for new technology add-on payments, beginning 
with applications for FY 2024.
    Comment: We received many public comments regarding this policy 
proposal. Overall, commenters appreciated the agency's aims in making 
the proposal of fostering greater transparency and public input, while 
mitigating increased burdens and workloads associated with the rising 
complexity and number of new technology add-on payment applications 
submitted annually. A few commenters were fully supportive of our 
proposal, while a majority of the remaining commenters supported the 
proposal, while suggesting modifications to address concerns about the 
disclosure of certain information. In particular, these commenters were 
encouraged by CMS' proposal not to include cost and volume information 
as part of the application materials that would be posted online, but 
stated that the proposal did not go far enough to protect potentially 
confidential, commercially sensitive information (for example, 
biologics license applications (BLA) or nonpublic studies), and 
recommended that CMS modify the proposal, offering suggestions for 
ensuring that such information not be posted online.
    Some commenters requested that CMS bifurcate the application to 
allow a section for information that would not be posted online, afford 
applicants the opportunity to submit a separate file of confidential 
information, or allow information in the application to be redacted. 
Other commenters requested that CMS continue the practice of allowing 
the applicant to mark sensitive proprietary or trade secret information 
as confidential and not for posting online. Commenters stated that if 
the full application were posted online, applicants may refrain from 
submitting certain information necessary to support the application and 
meet the new technology add-on payment criteria (for example, clinical 
information cited but not yet in the public domain and prior to FDA 
approval and information concerning newness, such as engineering 
specifics), resulting in applications that are less complete or robust, 
and therefore, would compromise the goals of the new technology add-on 
payment process. Absent protection of this information, commenters 
stated that applicants could apply only after FDA approval, creating 
significant delays in new technology add-on payment approvals and 
subsequent beneficiary access.
    Commenters also acknowledged that CMS generally does not consider 
confidential or proprietary information in making a determination 
whether a new technology meets the new technology add-on payment 
criteria, but believed there could be circumstances where such 
information could contribute to the agency's overall understanding of a 
technology, therapeutic area, or other relevant question that arises 
during its review (for example, pre-publication study results, which 
are kept from public release pending their publication in peer-reviewed 
scientific publications). Another commenter asserted that such data can 
help CMS better understand the technology and make a more informed 
decision about the application. The commenters also stated that, 
without protection of such information, companies would no longer be 
able to submit such studies until after publication. Commenters also 
stated that the proposed policy puts the onus on the applicant to not 
submit this type of information without recognizing that a 
comprehensive application might require such information.
    Additionally, commenters were generally supportive of our proposal 
regarding copyrighted material.

[[Page 48989]]

    Response: We appreciate the support for our proposal and our 
efforts toward greater transparency, public input, and streamlining of 
the new technology add-on application process. In making our proposal, 
we indicated that applicants should not submit proprietary or trade 
secret information with the application, to avoid such information 
being posted online as part of the application. Moreover, we proposed 
not to continue our practice of allowing applicants to mark such 
information to be withheld from disclosure given that our general 
policy is not to consider information that is marked confidential, 
proprietary, or trade secret when determining whether a technology 
meets the criteria for new technology add-on payments and given the 
need for the public to understand the information we are relying on in 
making such decisions. However, in consideration of public comments, we 
will provide a mechanism for applicants to submit confidential 
information, including proprietary or trade secret information, that 
will not be posted online. We anticipate providing a section on the 
application where applicants can submit confidential information 
separately from non-confidential information, or otherwise marking 
sections or questions in the application for which we will not post the 
information online. Applicants would still be required to submit cost 
and volume information in the application since this information is 
necessary; however, we will indicate in the application that cost and 
volume information will not be publicly posted but certain cost and 
volume information may still be summarized and discussed in the 
proposed rule, as is consistent with our current practice. Applicants 
should expect that, unless otherwise noted in the application that 
certain information will not be posted publicly (for example, contact 
information), everything else may be posted publicly. We emphasize that 
it is the applicant's responsibility to put confidential information 
only in the areas of the application designated for confidential 
information and not elsewhere in the application. However, as 
previously noted, applicants should consider what they include in a 
confidential section of the application given that we generally do not 
consider any information that cannot be made public when determining 
whether a technology meets the new technology add-on payment criteria. 
With respect to copyrighted information, we are finalizing our proposal 
without modification.
    Additionally, we note that in the past we have received 
applications in which all the data and information in an application 
are marked as proprietary or confidential, or where certain information 
provided in support of the applicant's assertions regarding eligibility 
for the new technology add-on payment, for example a claim of 
substantial clinical improvement, is marked as such. In such cases, we 
reiterate that we generally will not be able to consider that data and 
information when determining whether a technology meets the criteria 
for new technology add-on payments. Our process provides for public 
input, so it is important that we provide the information needed for 
the public to meaningfully comment on the new technology add-on payment 
applications, including the applicants' assertions as to why a 
technology meets the new technology add-on payment criteria.
    Comment: A commenter suggested that CMS further study ways to 
improve and streamline the annual review process. Another commenter 
requested that CMS defer a decision until the FY 2025 application 
cycle, allowing more time for interested parties and the agency to more 
thoroughly consider the implications and potential options to improve 
the efficiency and capacity of the review process.
    Response: As we stated in the proposed rule, we proposed to 
publicly post online applications for new technology add-on payments to 
increase transparency, enable increased engagement with interested 
parties, and improve and streamline our evaluation process. Through 
this policy, we also are attempting to address some of the downsides 
and challenges of our current practice of summarizing the contents of 
the applications by restating or paraphrasing information, ensuring 
that sufficient information is provided in the proposed rule, and 
avoiding misrepresenting or omitting any of the applicants' claims. 
Posting the application and certain related materials online, subject 
to certain exceptions as discussed in this section, is a 
straightforward solution and strikes a balance between affording 
greater transparency and streamlining the application process. Given 
the reasons we have noted previously, the overall support for the 
proposal, and after considering the other feedback and suggestions by 
commenters, we are finalizing our proposal to post applications online, 
but as previously discussed, we will provide a mechanism for applicants 
to submit confidential information that would not be included as part 
of the application materials posted online. We also continue to welcome 
feedback on the application and review process, including potential 
options for improving the efficiency and capacity of this process, and 
we will continue to consider this issue.
    Comment: A few commenters raised concerns about the timing of when 
applications would be posted online. A commenter questioned whether the 
agency planned to post all applications and related materials online at 
the same time, or on a rolling basis as they are received and deemed 
complete, noting that the specific timing of online posting would be 
highly relevant to applicants given that under the current process, 
applicants have the opportunity to amend or withdraw an application 
prior to presentation at the New Technology Town Hall or issuance of 
the proposed rule. The commenter believed that any new online posting 
process should preserve an applicant's ability to withdraw an 
application prior to posting, noting that many applicants submit 
materials before certainty that the technology meets the criteria for a 
new technology add-on payment, and with an intent to either supplement 
or withdraw the application during the cycle, because the annual 
application cycle often requires a submission well in advance of market 
introduction. Another commenter noted the fluidity and frequent updates 
of the data collection process in these applications, which may occur 
more quickly than the public notice and comment period and therefore, 
the information made available by CMS may not be current when it is 
released.
    Response: We agree with the commenter that additional information 
related to the application may be submitted up until the release of the 
proposed rule and understand that posting the complete application and 
supplemental information all at once is preferable to continually 
updating the application information online. Accordingly, we are 
clarifying that under the final policy we are adopting, we will 
publicly post the application and any additional information received 
(with the exception of certain confidential, cost and volume, or 
copyrighted information as explained previously) at the time the 
proposed rule is published and no sooner. With regard to the 
commenter's concern about an applicant's ability to withdraw 
applications during the application process, we clarify that the policy 
we are finalizing would not change an applicant's ability to withdraw 
its application prior to the proposed rule being published and, in such 
cases, we

[[Page 48990]]

would not post those applications online or address them in the 
proposed rule. In instances, however, where the applicant withdraws its 
application from consideration after the proposed rule is issued, the 
application would remain posted online (that is, corresponding to the 
published discussion of the application in the proposed rule).
    After considering the comments, and for the reasons discussed, we 
are finalizing our proposal to publicly post online new technology add-
on payment applications, including the completed application forms, 
certain related materials (as described previously), and any additional 
updated application information submitted subsequent to the initial 
application submission (except certain volume, cost and other 
information identified by the applicant as confidential), beginning 
with the application cycle for FY 2024, at the time the proposed rule 
is published. We are finalizing as proposed our proposal with respect 
to the treatment of copyrighted information. We are finalizing a 
modification to our proposal to provide a mechanism for applicants to 
submit confidential information that would not be posted online, such 
as in a separate section of the application, or by identifying 
particular questions for which the information submitted would not be 
publicly posted. We will not publicly post cost and volume information; 
however, consistent with our current practice, we will continue to 
summarize and discuss certain cost and volume information for the 
proposed rule and will indicate as such in the application. With the 
exception of information included in a confidential information section 
of the application, cost and volume information, and materials 
identified by the applicant as copyrighted and/or not otherwise 
releasable to the public, the contents of the application and related 
materials may be posted publicly. We further clarify that we will post 
these application materials at the time of the proposed rule and no 
sooner, and that we will not post applications that are withdrawn prior 
to publication of the proposed rule.

III. Changes to the Hospital Wage Index for Acute Care Hospitals

A. Background

1. Legislative Authority
    Section 1886(d)(3)(E) of the Act requires that, as part of the 
methodology for determining prospective payments to hospitals, the 
Secretary adjust the standardized amounts for area differences in 
hospital wage levels by a factor (established by the Secretary) 
reflecting the relative hospital wage level in the geographic area of 
the hospital compared to the national average hospital wage level. We 
currently define hospital labor market areas based on the delineations 
of statistical areas established by the Office of Management and Budget 
(OMB). A discussion of the FY 2023 hospital wage index based on the 
statistical areas appears under section III.A.2. of the preamble of 
this final rule.
    Section 1886(d)(3)(E) of the Act requires the Secretary to update 
the wage index annually and to base the update on a survey of wages and 
wage-related costs of short-term, acute care hospitals. CMS collects 
these data on the Medicare cost report, CMS Form 2552-10, Worksheet S-
3, Parts II, III, IV. The OMB control number for this information 
collection request is 0938-0050, which expired on March 31, 2022. A 30-
day Federal Register notice published on June 22, 2022 (87 FR 37338) 
for the reinstatement of the information collection request. The 
comment period closed July 22, 2022. Section 1886(d)(3)(E) of the Act 
also requires that any updates or adjustments to the wage index be made 
in a manner that ensures that aggregate payments to hospitals are not 
affected by the change in the wage index. The adjustment for FY 2023 is 
discussed in section II.B. of the Addendum to this final rule.
    As discussed in section III.I. of the preamble of this final rule, 
we also take into account the geographic reclassification of hospitals 
in accordance with sections 1886(d)(8)(B) and 1886(d)(10) of the Act 
when calculating IPPS payment amounts. Under section 1886(d)(8)(D) of 
the Act, the Secretary is required to adjust the standardized amounts 
so as to ensure that aggregate payments under the IPPS after 
implementation of the provisions of sections 1886(d)(8)(B), 
1886(d)(8)(C), and 1886(d)(10) of the Act are equal to the aggregate 
prospective payments that would have been made absent these provisions. 
The budget neutrality adjustment for FY 2023 is discussed in section 
II.A.4.b. of the Addendum to this final rule.
    Section 1886(d)(3)(E) of the Act also provides for the collection 
of data every 3 years on the occupational mix of employees for short-
term, acute care hospitals participating in the Medicare program, in 
order to construct an occupational mix adjustment to the wage index. 
(The OMB control number for approved collection of this information is 
0938-0907, which expires on October 31, 2022. An extension of the 
information collection request is currently being developed. The public 
will have an opportunity to review and submit comments regarding the 
extension of this PRA package through a public notice and comment 
period separate from this rulemaking.) A discussion of the occupational 
mix adjustment that we are applying to the FY 2023 wage index appears 
under sections III.E. and F. of the preamble of this final rule.
2. Core-Based Statistical Areas (CBSAs) for the FY 2023 Hospital Wage 
Index
    The wage index is calculated and assigned to hospitals on the basis 
of the labor market area in which the hospital is located. Under 
section 1886(d)(3)(E) of the Act, beginning with FY 2005, we delineate 
hospital labor market areas based on OMB-established Core-Based 
Statistical Areas (CBSAs). The current statistical areas (which were 
implemented beginning with FY 2015) are based on revised OMB 
delineations issued on February 28, 2013, in OMB Bulletin No. 13-01. 
OMB Bulletin No. 13-01 established revised delineations for 
Metropolitan Statistical Areas, Micropolitan Statistical Areas, and 
Combined Statistical Areas in the United States and Puerto Rico based 
on the 2010 Census, and provided guidance on the use of the 
delineations of these statistical areas using standards published in 
the June 28, 2010, Federal Register (75 FR 37246 through 37252). We 
refer readers to the FY 2015 IPPS/LTCH PPS final rule (79 FR 49951 
through 49963 and 49973 through 49982)) for a full discussion of our 
implementation of the OMB statistical area delineations beginning with 
the FY 2015 wage index.
    Generally, OMB issues major revisions to statistical areas every 10 
years, based on the results of the decennial census. However, OMB 
occasionally issues minor updates and revisions to statistical areas in 
the years between the decennial censuses through OMB Bulletins. On July 
15, 2015, OMB issued OMB Bulletin No. 15-01, which provided updates to 
and superseded OMB Bulletin No. 13-01 that was issued on February 28, 
2013. The attachment to OMB Bulletin No. 15-01 provided detailed 
information on the update to statistical areas since February 28, 2013. 
The updates provided in OMB Bulletin No. 15-01 were based on the 
application of the 2010 Standards for Delineating Metropolitan and 
Micropolitan Statistical Areas to Census Bureau population estimates 
for July 1, 2012, and July 1, 2013. In the FY 2017 IPPS/LTCH PPS final 
rule (81 FR 56913), we adopted the updates set forth in OMB Bulletin 
No. 15-01 effective

[[Page 48991]]

October 1, 2016, beginning with the FY 2017 wage index. For a complete 
discussion of the adoption of the updates set forth in OMB Bulletin No. 
15-01, we refer readers to the FY 2017 IPPS/LTCH PPS final rule. In the 
FY 2018 IPPS/LTCH PPS final rule (82 FR 38130), we continued to use the 
OMB delineations that were adopted beginning with FY 2015 to calculate 
the area wage indexes, with updates as reflected in OMB Bulletin No. 
15-01 specified in the FY 2017 IPPS/LTCH PPS final rule.
    On August 15, 2017, OMB issued OMB Bulletin No. 17-01, which 
provided updates to and superseded OMB Bulletin No. 15-01 that was 
issued on July 15, 2015. The attachments to OMB Bulletin No. 17-01 
provided detailed information on the update to statistical areas since 
July 15, 2015, and were based on the application of the 2010 Standards 
for Delineating Metropolitan and Micropolitan Statistical Areas to 
Census Bureau population estimates for July 1, 2014 and July 1, 2015. 
In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41362 through 41363), we 
adopted the updates set forth in OMB Bulletin No. 17-01 effective 
October 1, 2018, beginning with the FY 2019 wage index. For a complete 
discussion of the adoption of the updates set forth in OMB Bulletin No. 
17-01, we refer readers to the FY 2019 IPPS/LTCH PPS final rule. In the 
FY 2020 IPPS/LTCH PPS final rule (84 FR 42300 through 42301), we 
continued to use the OMB delineations that were adopted beginning with 
FY 2015 (based on the revised delineations issued in OMB Bulletin No. 
13-01) to calculate the area wage indexes, with updates as reflected in 
OMB Bulletin Nos. 15-01 and 17-01.
    On April 10, 2018 OMB issued OMB Bulletin No. 18-03 which 
superseded the August 15, 2017, OMB Bulletin No. 17-01. On September 
14, 2018, OMB issued OMB Bulletin No. 18-04 which superseded the April 
10, 2018 OMB Bulletin No. 18-03. Historically OMB bulletins issued 
between decennial censuses have only contained minor modifications to 
CBSA delineations based on changes in population counts. However, OMB's 
2010 Standards for Delineating Metropolitan and Micropolitan 
Statistical Areas to Census Bureau population estimates created a 
larger mid-decade redelineation that takes into account commuting data 
from the American Commuting Survey. As a result, the September 14, 
2018, OMB Bulletin No. 18-04 included more modifications to the CBSAs 
than are typical for OMB bulletins issued between decennial censuses.
    In the FY 2021 IPPS/LTCH PPS final rule (85 FR 58743 through 58755) 
we adopted the updates set forth in OMB Bulletin No. 18-04 effective 
October 1, 2020, beginning with the FY 2021 wage index. For a complete 
discussion of the adoption of the updates set forth in OMB Bulletin No. 
18-04, we refer readers to the FY 2021 IPPS/LTCH PPS final rule.
    On March 6, 2020, OMB issued Bulletin No. 20-01, which provided 
updates to and superseded OMB Bulletin No. 18-04 that was issued on 
September 14, 2018. The attachments to OMB Bulletin No. 20-01 provided 
detailed information on the update to statistical areas since September 
14, 2018, and were based on the application of the 2010 Standards for 
Delineating Metropolitan and Micropolitan Statistical Areas to Census 
Bureau population estimates for July 1, 2017, and July 1, 2018. After 
reviewing OMB Bulletin No. 20-01, we determined that the changes in 
Bulletin 20-01 encompassed delineation changes that would not affect 
the Medicare wage index for FY 2022. While we adopted the updates set 
forth in OMB Bulletin No. 20-01 in the FY 2022 IPPS/LTCH PPS final rule 
(86 FR 45163 through 45164) consistent with our general policy of 
adopting OMB delineation updates, we also noted that specific wage 
index updates would not be necessary for FY 2022 as a result of 
adopting these updates. In other words, the updates set forth in OMB 
Bulletin No. 20-01 would not affect any hospital's geographic area for 
purposes of the wage index calculation for FY 2022. For a complete 
discussion of the adoption of the updates set forth in OMB Bulletin No. 
20-01, we refer readers to the FY 2022 IPPS/LTCH PPS final rule (86 FR 
45163 through 45164).
    For FY 2023, we are continuing to use the OMB delineations that 
were adopted beginning with FY 2015 (based on the revised delineations 
issued in OMB Bulletin No. 13-01) to calculate the area wage indexes, 
with updates as reflected in OMB Bulletin Nos. 15-01, 17-01, 18-04 and 
20-01.
    In connection with our adoption in FY 2021 of the updates in OMB 
Bulletin 18-04, we adopted a policy to place a 5-percent cap, for FY 
2021, on any decrease in a hospital's wage index from the hospital's 
final wage index in FY 2020 so that a hospital's final wage index for 
FY 2021 would not be less than 95 percent of its final wage index for 
FY 2020. We refer the reader to the FY 2021 IPPS/LTCH PPS final rule 
(85 FR 58753 through 58755) for a complete discussion of this 
transition. As finalized in the FY 2021 IPPS/LTCH PPS final rule, this 
transition was set to expire at the end of FY 2021. However, given the 
unprecedented nature of the ongoing COVID-19 public health emergency 
(PHE), we adopted a policy in the FY 2022 IPPS/LTCH PPS final rule to 
apply an extended transition to the FY 2022 wage index for hospitals 
that received the transition in FY 2021. Specifically, we continued a 
wage index transition for FY 2022 (for hospitals that received the 
transition in FY 2021) under which we applied a 5 percent cap on any 
decrease in the hospital's wage index compared to its wage index for FY 
2021 to mitigate significant negative impacts of, and provide 
additional time for hospitals to adapt to, the CMS decision to adopt 
the revised OMB delineations. We also applied a budget neutrality 
adjustment to the standardized amount so that our transition in FY 2022 
was implemented in a budget neutral manner under our authority in 
section 1886(d)(5)(I) of the Act. We refer the reader to the FY 2022 
IPPS/LTCH PPS final rule (85 FR 45164 through 45165) for a complete 
discussion of this transition. We also refer readers to section III.N. 
of the preamble of this final rule which discusses our permanent policy 
to apply a 5-percent cap on any decrease in a hospital's wage index 
compared to its wage index from the prior fiscal year.
3. Codes for Constituent Counties in CBSAs
    CBSAs are made up of one or more constituent counties. Each CBSA 
and constituent county has its own unique identifying codes. There are 
two different lists of codes associated with counties: Social Security 
Administration (SSA) codes and Federal Information Processing Standard 
(FIPS) codes. Historically, CMS has listed and used SSA and FIPS county 
codes to identify and crosswalk counties to CBSA codes for purposes of 
the hospital wage index. As we discussed in the FY 2018 IPPS/LTCH PPS 
final rule (82 FR 38129 through 38130), we have learned that SSA county 
codes are no longer being maintained and updated. However, the FIPS 
codes continue to be maintained by the U.S. Census Bureau. We believe 
that using the latest FIPS codes will allow us to maintain a more 
accurate and up-to-date payment system that reflects the reality of 
population shifts and labor market conditions.
    The Census Bureau's most current statistical area information is 
derived from ongoing census data received since 2010; the most recent 
data are from 2020. The Census Bureau maintains a complete list of 
changes to counties or county equivalent entities on the

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website at https://www.census.gov/programs-surveys/geography/technical-documentation/county-changes.html. We believe that it is important to 
use the latest counties or county equivalent entities in order to 
properly crosswalk hospitals from a county to a CBSA for purposes of 
the hospital wage index used under the IPPS.
    In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38129 through 
38130), we adopted a policy to discontinue the use of the SSA county 
codes and began using only the FIPS county codes for purposes of cross 
walking counties to CBSAs. In addition, in the same rule, we 
implemented the latest FIPS code updates, which were effective October 
1, 2017, beginning with the FY 2018 wage indexes. These updates have 
been used to calculate the wage indexes in a manner generally 
consistent with the CBSA-based methodologies finalized in the FY 2005 
IPPS final rule and the FY 2015 IPPS/LTCH PPS final rule. We refer the 
reader to the FY 2018 IPPS/LTCH PPS final rule (82 FR 38129 through 
38130) for a complete discussion of our adoption of FIPS county codes.
    Based on the latest information included in the Census Bureau's 
website at https://www.census.gov/programs-surveys/geography/technical-documentation/county-changes.2010.html, the Census Bureau has made the 
following updates to the FIPS codes for counties or county equivalent 
entities:
     Chugach Census Area, AK (FIPS State County Code 02-063) 
and Copper River Census Area, AK (FIPS State County Code 02-066), were 
created from former Valdez-Cordova Census Area (02-261) which was 
located in CBSA 02. The CBSA code for these two new county equivalents 
remains 02.
    We believe that it is important to use the latest counties or 
county equivalent entities in order to properly crosswalk hospitals 
from a county to a CBSA for purposes of the hospital wage index used 
under the IPPS. In addition, we believe that using the latest FIPS 
codes allows us to maintain a more accurate and up-to-date payment 
system that reflects the reality of population shifts and labor market 
conditions. Therefore, in the FY 2023 IPPS/LTCH PPS proposed rule (87 
FR 28359), we proposed to implement these FIPS code updates listed 
previously, effective October 1, 2022, beginning with the FY 2023 wage 
indexes. We proposed to use these update changes to calculate area wage 
indexes in a manner that is generally consistent with the CBSA-based 
methodologies finalized in the FY 2005 IPPS final rule (69 FR 49026 
through 49034) and the FY 2015 IPPS/LTCH PPS final rule (79 FR 49951 
through 49963). We note that while the county update changes listed 
previously changed the county names, the CBSAs to which these counties 
map did not change from the prior counties. Therefore, we stated that 
there would be no impact or change to hospitals in these counties for 
purposes of the hospital wage index as a result of our implementation 
of these FIPS code updates. We invited public comments on our 
proposals.
    We did not receive any public comments on our proposals. Therefore, 
for the reasons discussed earlier, we are finalizing our proposal, 
without modification, to implement the FIPS code updates listed 
previously, effective October 1, 2022, beginning with the FY 2023 wage 
indexes. As we proposed, we will use these update changes to calculate 
the area wage indexes in a manner that is generally consistent with the 
CBSA-based methodologies finalized in the FY 2005 IPPS final rule and 
the FY 2015 IPPS/LTCH PPS final rule. For FY 2023, Tables 2 and 3 
associated with this final rule and the County to CBSA Crosswalk File 
and Urban CBSAs and Constituent Counties for Acute Care Hospitals File 
posted on the CMS website reflect these FIPS code updates.

B. Worksheet S-3 Wage Data for the FY 2023 Wage Index

    The FY 2023 wage index values are based on the data collected from 
the Medicare cost reports submitted by hospitals for cost reporting 
periods beginning in FY 2019 (the FY 2022 wage indexes were based on 
data from cost reporting periods beginning during FY 2018).
1. Included Categories of Costs
    The FY 2023 wage index includes all of the following categories of 
data associated with costs paid under the IPPS (as well as outpatient 
costs):
     Salaries and hours from short-term, acute care hospitals 
(including paid lunch hours and hours associated with military leave 
and jury duty).
     Home office costs and hours.
     Certain contract labor costs and hours, which include 
direct patient care, certain top management, pharmacy, laboratory, and 
nonteaching physician Part A services, and certain contract indirect 
patient care services (as discussed in the FY 2008 final rule with 
comment period (72 FR 47315 through 47317)).
     Wage-related costs, including pension costs (based on 
policies adopted in the FY 2012 IPPS/LTCH PPS final rule (76 FR 51586 
through 51590) and modified in the FY 2016 IPPS/LTCH PPS final rule (80 
FR 49505 through 49508)) and other deferred compensation costs.
2. Excluded Categories of Costs
    Consistent with the wage index methodology for FY 2022, the wage 
index for FY 2023 also excludes the direct and overhead salaries and 
hours for services not subject to IPPS payment, such as skilled nursing 
facility (SNF) services, home health services, costs related to GME 
(teaching physicians and residents) and certified registered nurse 
anesthetists (CRNAs), and other subprovider components that are not 
paid under the IPPS. The FY 2023 wage index also excludes the salaries, 
hours, and wage-related costs of hospital-based rural health clinics 
(RHCs), and Federally Qualified Health Centers (FQHCs) because Medicare 
pays for these costs outside of the IPPS (68 FR 45395). In addition, 
salaries, hours, and wage-related costs of CAHs are excluded from the 
wage index for the reasons explained in the FY 2004 IPPS final rule (68 
FR 45397 through 45398). For FY 2020 and subsequent years, other wage-
related costs are also excluded from the calculation of the wage index. 
As discussed in the FY 2019 IPPS/LTCH final rule (83 FR 41365 through 
41369), other wage-related costs reported on Worksheet S-3, Part II, 
Line 18 and Worksheet S-3, Part IV, Line 25 and subscripts, as well as 
all other wage-related costs, such as contract labor costs, are 
excluded from the calculation of the wage index.
3. Use of Wage Index Data by Suppliers and Providers Other Than Acute 
Care Hospitals Under the IPPS
    Data collected for the IPPS wage index also are currently used to 
calculate wage indexes applicable to suppliers and other providers, 
such as SNFs, home health agencies (HHAs), ambulatory surgical centers 
(ASCs), and hospices. In addition, they are used for prospective 
payments to IRFs, IPFs, and LTCHs, and for hospital outpatient 
services. We note that, in the IPPS rules, we do not address comments 
pertaining to the wage indexes of any supplier or provider except IPPS 
providers and LTCHs. Such comments should be made in response to 
separate proposed rules for those suppliers and providers. We did not 
receive any comments on the discussion in this section.

C. Verification of Worksheet S-3 Wage Data

    The wage data for the FY 2023 wage index were obtained from 
Worksheet S-

[[Page 48993]]

3, Parts II, III and IV of the Medicare cost report, CMS Form 2552-10 
for cost reporting periods beginning on or after October 1, 2018, and 
before October 1, 2019. (As noted in section III.A.1 of the preamble of 
this final rule, the OMB control number for this information collection 
request is 0938-0050, which expired on March 31, 2022. A 30-day Federal 
Register notice published on June 22, 2022 (87 FR 37338) for the 
reinstatement of the information collection request. The comment period 
closed July 22, 2022). For wage index purposes, we refer to cost 
reports beginning on or after October 1, 2018, and before October 1, 
2019 as the ``FY 2019 cost report,'' the ``FY 2019 wage data,'' or the 
``FY 2019 data.'' Instructions for completing the wage index sections 
of Worksheet S-3 are included in the Provider Reimbursement Manual 
(PRM), Part 2 (Pub. 15-2), Chapter 40, Sections 4005.2 through 4005.4. 
The data file used to construct the FY 2023 wage index includes FY 2019 
data submitted to us as of the end of June 2022. As in past years, we 
performed an extensive review of the wage data, mostly through the use 
of edits designed to identify aberrant data.
    Consistent with the IPPS and LTCH PPS ratesettings, our policy 
principles with regard to the wage index include generally using the 
most current data and information available which is usually data on a 
4-year lag (for example, for the FY 2022 wage index we used cost report 
data from FY 2018) . In section I.F. of the preamble of this final 
rule, we discuss our analysis of the best available data for use in the 
development of this FY 2023 IPPS/LTCH PPS final rule given the 
potential impact of the public health emergency (PHE) for the 
Coronavirus Disease (COVID-19). For the FY 2023 wage index, the best 
available data typically would be from the FY 2019 wage data. Our 
review and analysis of the FY 2019 wage data shows that the data is not 
significantly impacted by COVID-19 PHE. A comparison of providers shows 
similar trends in those with cost reports ending during the PHE as 
compared to providers without cost reports ending during the PHE. The 
data also shows that changes in the average hourly wage (AHW) for 
providers were consistent between providers with cost reports ending 
during the PHE as compared to providers without cost reports ending 
during the PHE. It appears that the overall impact of the COVID-19 PHE 
on the FY 2019 wage data has been minimal. Additionally, the changes in 
the wage data from FY 2018 to FY 2019 show similar trends in the change 
of the data from FY 2017 to FY 2018. Therefore, we proposed to use the 
FY 2019 wage data for the FY 2023 wage index.
    Comment: A commenter expressed concern that the review and analysis 
of the FY 2019 wage data with regard to the impact by COVID-19 PHE was 
unclear. The commenter noted that the proposed rule did not reference 
tables or files for the public to review to confirm the agency's 
conclusion. The commenter also stated that it is confusing why CMS 
stated that the FY 2019 wage data was not impacted by the PHE given 
that the PHE did not begin until March 2020. The commenter encouraged 
CMS to share source information so stakeholders can better understand 
the agency's position, particularly given the review of data suggests 
that the cost of staffing has increased substantially.
    Response: With regard to the commenter that stated that the PHE did 
not begin until March 2020, we note that the PHE was declared on 
January 31, 2020 in response to COVID-19. We also note that in March 
2020, the World Health Organization declared the COVID-19 outbreak a 
pandemic.
    As previously stated, our review and analysis of the FY 2019 wage 
data shows that the data is not significantly impacted by COVID-19 PHE. 
We use the latest audited data to calculate the wage index. The latest 
audited data as of the FY 2023 rulemaking cycle is cost reports with a 
begin date during FY 2019. Because we use audited cost report data with 
a begin date in FY 2019 (on or after Oct 1, 2018 through on or before 
September 30, 2019), the latest cost report with a begin date in FY 
2019 would be September 30, 2019 which would end typically 12 months 
later on September 30, 2020 (which would include some months in the 
PHE). The earlier the cost report begin date the less months of data 
are included in the period of the PHE. As noted in this section of this 
rule, there are 3,136 providers included in the wage index for FY 2023.
    Approximately 1,300 hospitals have cost report data from FY 2019 
that has some months of data touching the PHE in the period of January 
31, 2020 through September 30, 2020. We note, while the PHE was 
declared January 31, 2020, the impact of the PHE began to be felt by 
hospitals beginning in March 2020 (which is re-enforced by the 
commenter that stated its belief that the PHE began in March 2020). Of 
these 1,300 hospitals:
     Approximately 80 hospitals have a cost reporting period of 
04/01/2019 through 03/30/2020 (one month of data in the period between 
March 2020 through September 2020).
     Approximately 1,000 hospitals have a cost reporting period 
of 07/01/2019 through 06/30/2020 (four months of data in the period 
between March 2020 through September 2020).
     Approximately 85 hospitals have a cost reporting period of 
09/01/2019 through 08/30/2020 (six months of data in the period between 
April 2020 through September 2020).
    Based on the previous, approximately 37 percent of hospitals 
include data from the period of March 2020 through September 2020. The 
majority of these hospitals (1,000) have a cost report begin date of 
July 1, 2019 which accounts for approximately 32 percent of all 
hospitals cost report data; also, the majority of the cost report data 
for these hospitals (8 months) is not impacted by the PHE. Therefore, 
the overwhelming majority of hospitals data has no data from the period 
of March 2020 through September 2020. While some cost reports included 
some months of data from the period of March 2020 through September 
2020, as previously stated, the data shows that changes in the average 
hourly wage (AHW) for providers were consistent between providers with 
cost reports ending during the PHE as compared to providers without 
cost reports ending during the PHE. Additionally, the changes in the 
wage data from FY 2018 to FY 2019 show similar trends in the change of 
the data from FY 2017 to FY 2018. We also note, AHW data by provider 
and CBSA is readily available in our Public Use Files released with 
each proposed and final rule each fiscal year. Therefore, any 
comparisons that CMS made within the current year data and prior year 
data can easily be replicated by the public. We did not receive any 
comments questioning whether certain providers or CBSAs AHW were 
grossly affected by the PHE. Therefore, we continue to believe that the 
data shows that changes in the average hourly wage (AHW) for providers 
were consistent between providers with cost reports ending during the 
PHE as compared to providers without cost reports ending during the 
PHE.
    We also note, in section G.2.c. of Appendix A of the FY 2023 IPPS/
LTCH proposed rule (87 FR 28709), we provided a table showing the 
projected impact of proposed changes in the area wage index values for 
urban and rural hospitals. Specifically, the table compares the shifts 
in wage index values for hospitals due to proposed changes in the 
average hourly wage data

[[Page 48994]]

for FY 2023 relative to FY 2022. We refer the commenter to this table 
as well as a similar table that is published in section G.2.c. of 
Appendix A in this final rule.
    Finally, CMS will be looking at the differential effects of the 
COVID-19 PHE on the audited wage data in future fiscal years. We plan 
to review the audited wage data, and the impacts of the COVID-19 PHE on 
such data and evaluate these data for future rulemaking.
    We requested that our MACs revise or verify data elements that 
result in specific edit failures. For the proposed FY 2023 wage index, 
we identified and excluded 86 providers with aberrant data that should 
not be included in the wage index. However, we stated that if data 
elements for some of these providers are corrected, we intended to 
include data from those providers in the final FY 2023 wage index. We 
also adjusted certain aberrant data and included these data in the wage 
index. For example, in situations where a hospital did not have 
documentable salaries, wages, and hours for housekeeping and dietary 
services, we imputed estimates, in accordance with policies established 
in the FY 2015 IPPS/LTCH PPS final rule (79 FR 49965 through 49967). We 
instructed MACs to complete their data verification of questionable 
data elements and to transmit any changes to the wage data no later 
than March 19, 2022. For the final FY 2023 wage index, we restored the 
data of 23 hospitals to the wage index because their data was either 
verified or improved, and removed the data of 0 hospitals for the first 
time after the proposed rule due to its data being aberrant. We also 
restored the data of one provider that we inadvertently excluded from 
the proposed rule that was not on the delete list in the proposed rule 
public use file. Thus, 63 hospitals with aberrant data remain excluded 
from the FY 2023 wage index (86-23 = 63).
    In constructing the proposed FY 2023 wage index, we included the 
wage data for facilities that were IPPS hospitals in FY 2019, inclusive 
of those facilities that have since terminated their participation in 
the program as hospitals, as long as those data did not fail any of our 
edits for reasonableness. We stated in the proposed rule (87 FR 28630 
through 28632) that we believe that including the wage data for these 
hospitals is, in general, appropriate to reflect the economic 
conditions in the various labor market areas during the relevant past 
period and to ensure that the current wage index represents the labor 
market area's current wages as compared to the national average of 
wages. However, we excluded the wage data for CAHs as discussed in the 
FY 2004 IPPS final rule (68 FR 45397 through 45398); that is, any 
hospital that is designated as a CAH by 7 days prior to the publication 
of the preliminary wage index public use file (PUF) is excluded from 
the calculation of the wage index. For the proposed FY 2023 wage index, 
we removed 3 hospitals that converted to CAH status on or after January 
24, 2021, the cut-off date for CAH exclusion from the FY 2022 wage 
index, and through and including January 21, 2022, the cut-off date for 
CAH exclusion from the FY 2023 wage index. Since the proposed rule, we 
learned of 0 more hospitals that converted to CAH status on or after 
January 24, 2021, and through and including January 21, 2022, the cut-
off date for CAH exclusion from the FY 2023 wage index, for a total of 
3 hospitals that were removed from the FY 2023 wage index due to 
conversion to CAH status. In summary, we calculated the FY 2023 wage 
index using the Worksheet S-3, Parts II and III wage data of 3,136 
hospitals.
    For the FY 2023 wage index, we allotted the wages and hours data 
for a multicampus hospital among the different labor market areas where 
its campuses are located using campus full-time equivalent (FTE) 
percentages as originally finalized in the FY 2012 IPPS/LTCH PPS final 
rule (76 FR 51591). Table 2, which contains the FY 2023 wage index 
associated with this final rule (available via the internet on the CMS 
website), includes separate wage data for the campuses of 26 
multicampus hospitals. The following chart lists the multicampus 
hospitals by CSA certification number (CCN) and the FTE percentages on 
which the wages and hours of each campus were allotted to their 
respective labor market areas:
BILLING CODE 4120-01-P

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[GRAPHIC] [TIFF OMITTED] TR10AU22.110


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[GRAPHIC] [TIFF OMITTED] TR10AU22.111

BILLING CODE 4120-01-C
    We noted that, in past years, in Table 2, we have placed a ``B'' to 
designate the subordinate campus in the fourth position of the hospital 
CCN. However, for the FY 2019 IPPS/LTCH PPS proposed and final rules 
and subsequent rules, we have moved the ``B'' to the third position of 
the CCN. Because all IPPS hospitals have a ``0'' in the third position 
of the CCN, we believe that placement of the ``B'' in this third 
position, instead of the ``0'' for the subordinate campus, is the most 
efficient method of identification and interferes the least with the 
other, variable, digits in the CCN.
    Comment: Commenters opposed the exclusion of hospitals' wage data. 
These commenters stated that excluding accurate and verified data is 
inconsistent with the extensive process established by CMS to ensure 
the accuracy and reliability of hospital wage index data. Commenters 
also raised concerns about the lawfulness of excluding wage data for 
these hospitals, stating that section 1886(d)(3)(E) of the Act does not 
provide the authority for CMS to delete accurately-reported wage data, 
and doing so is arbitrary and capricious.
    Specifically, a commenter opposed the exclusion of hospitals' wage 
data where hospitals timely submitted corrections or appeals. The 
commenter stated that where hospitals have available timely-submitted, 
corrected and verifiable data CMS is obligated to use such data in the 
wage index calculation. The commenter also stated that there is no 
statute or regulation authorizing CMS to exclude hospital data based on 
a unilateral determination that the data is aberrant.
    Response: We responded to similar comments in the FY 2016 IPPS/LTCH 
PPS final rule (80 FR 49490 through 49491) and the FY 2022 IPPS/LTCH 
PPS final rule (86 FR 45168 through 45169). Section 1886(d)(3)(E) of 
the Act requires the Secretary to adjust the proportion of hospitals' 
costs attributable to wages and wage-related costs for area differences 
reflecting the relative hospital wage level in the geographic area of 
the hospital compared to the national average hospital wage level. As 
previously stated in those final rules in response to similar comments, 
we believe that, under this section of the

[[Page 48997]]

Act, we have discretion to exclude aberrant hospital data from the wage 
index PUFs to help ensure that the costs attributable to wages and 
wage-related costs in fact reflect the relative hospital wage level in 
the hospitals' geographic area. We refer commenters to our previous 
responses to comments at the Federal Register pages cited earlier in 
this response with regard to the exclusion of hospitals' wage data from 
the wage index.
    Comment: Some commenters urged CMS to lessen the lag of four years 
in hospitals' cost report data used for the wage index (for example, FY 
2019 cost report data used for the FY 2023 wage index) and to consider 
alternate methods to collect more accurate data.
    Another commenter stated that CMS should offer short[hyphen]term 
assistance to the hospital community, considering inflationary updates 
to the wage index as necessary to preserve current service levels, 
which the commenter believes is a particular risk point for underserved 
populations. The commenter recommended a more time[hyphen]sensitive and 
layered approach to wage index updates to account for excess labor 
costs driven by increased contract labor and reimbursement rates to 
preserve our critical national hospital system infrastructure. The 
commenter stated that CMS could accomplish this by leveraging current 
Medicare cost report surveys to develop a wage adjustment until the 
labor market stabilizes. This approach would account for regional 
disparities and impact, use known and accepted survey data, create a 
standardized and auditable system, and support hospitals without 
disrupting the baseline Medicare wage index.
    Response: CMS used the most recent audited surveys and data to 
develop the FY 2023 wage index. We are unclear what alternative data or 
which current surveys and reporting the commenters are referring to. We 
note, audited cost report data from FY 2020 will be used for FY 2024 
and is not available at the time of this final rule. Therefore, we are 
unable to account for regional differences without audited data. Also, 
as previously noted, section 1886(d)(3)(E) of the Act requires that, as 
part of the methodology for determining prospective payments to 
hospitals, the Secretary adjust the standardized amounts for area 
differences in hospital wage levels by a factor (established by the 
Secretary) reflecting the relative hospital wage level in the 
geographic area of the hospital compared to the national average 
hospital wage level. Uniformly adjusting the salaries and hours for all 
areas (which is used to calculate an areas AHW) would lead to a 
commensurate change to the national AHW and not the wage index itself. 
This is because the wage index is required to be a relative measure. 
Further, we refer the commenter to the discussion on the market basket 
in section V. A. 1. of the preamble of this final rule for which we now 
have an updated forecast of the price proxies underlying the market 
basket that incorporates more recent historical data and reflects a 
revised outlook regarding the U.S. economy (including the more recent 
historical CPI growth, impacts of the Russia/Ukraine war, current 
expectations regarding changes to Federal Reserve interest rates, and 
tight labor markets). Additionally, we note that section 
1886(d)(3)(E)(i) of the Act requires us to make any updates or 
adjustments to the wage index in a manner that ensures that aggregate 
payments under section 1886(d) are not affected by the change in the 
wage index. Section 1886(d)(3)(E)(i) of the Act requires that we 
implement the wage index adjustment in a budget neutral manner. 
Therefore, since the wage index is subject to budget neutrality, any 
increases or decreases as a result of the data from one FY to the next 
FY would be implemented in a budget neutral manner.

D. Method for Computing the FY 2023 Unadjusted Wage Index

    As stated in the proposed rule (87 FR 28362 through 28365), the 
method used to compute the FY 2023 wage index without an occupational 
mix adjustment follows the same methodology that we used to compute the 
wage indexes without an occupational mix adjustment in the FY 2021 
IPPS/LTCH PPS final rule (see 85 FR 58758 through 58761, September 18, 
2020), and we did not propose any changes to this methodology. We have 
restated our methodology in this section of this final rule.
    Step 1.--We gathered data from each of the non-Federal, short-term, 
acute care hospitals for which data were reported on the Worksheet S-3, 
Parts II and III of the Medicare cost report for the hospital's cost 
reporting period relevant to the wage index (in this case, for FY 2023, 
these were data from cost reports for cost reporting periods beginning 
on or after October 1, 2018, and before October 1, 2019). In addition, 
we included data from some hospitals that had cost reporting periods 
beginning before October 2018 and reported a cost reporting period 
covering all of FY 2019. These data were included because no other data 
from these hospitals would be available for the cost reporting period 
as previously described, and because particular labor market areas 
might be affected due to the omission of these hospitals. However, we 
generally describe these wage data as FY 2019 data. We note that, if a 
hospital had more than one cost reporting period beginning during FY 
2019 (for example, a hospital had two short cost reporting periods 
beginning on or after October 1, 2018, and before October 1, 2019), we 
include wage data from only one of the cost reporting periods, the 
longer, in the wage index calculation. If there was more than one cost 
reporting period and the periods were equal in length, we included the 
wage data from the later period in the wage index calculation.
    Step 2.--Salaries.--The method used to compute a hospital's average 
hourly wage excludes certain costs that are not paid under the IPPS. 
(We note that, beginning with FY 2008 (72 FR 47315), we included what 
were then Lines 22.01, 26.01, and 27.01 of Worksheet S-3, Part II of 
CMS Form 2552-96 for overhead services in the wage index. Currently, 
these lines are lines 28, 33, and 35 on CMS Form 2552-10. However, we 
note that the wages and hours on these lines are not incorporated into 
Line 101, Column 1 of Worksheet A, which, through the electronic cost 
reporting software, flows directly to Line 1 of Worksheet S-3, Part II. 
Therefore, the first step in the wage index calculation is to compute a 
``revised'' Line 1, by adding to the Line 1 on Worksheet S-3, Part II 
(for wages and hours respectively) the amounts on Lines 28, 33, and 
35.) In calculating a hospital's Net Salaries (we note that we 
previously used the term ``average'' salaries in the FY 2012 IPPS/LTCH 
PPS final rule (76 FR 51592), but we now use the term ``net'' salaries) 
plus wage-related costs, we first compute the following: Subtract from 
Line 1 (total salaries) the GME and CRNA costs reported on CMS Form 
2552-10, Lines 2, 4.01, 7, and 7.01, the Part B salaries reported on 
Lines 3, 5 and 6, home office salaries reported on Line 8, and exclude 
salaries reported on Lines 9 and 10 (that is, direct salaries 
attributable to SNF services, home health services, and other 
subprovider components not subject to the IPPS). We also subtract from 
Line 1 the salaries for which no hours were reported. Therefore, the 
formula for Net Salaries (from Worksheet S-3, Part II) is the 
following:
    ((Line 1 + Line 28 + Line 33 + Line 35)-(Line 2 + Line 3 + Line 
4.01 + Line 5 + Line 6 + Line 7 + Line 7.01 + Line 8 + Line 9 + Line 
10)).

[[Page 48998]]

    To determine Total Salaries plus Wage-Related Costs, we add to the 
Net Salaries the costs of contract labor for direct patient care, 
certain top management, pharmacy, laboratory, and nonteaching physician 
Part A services (Lines 11, 12 and 13), home office salaries and wage-
related costs reported by the hospital on Lines 14.01, 14.02, and 15, 
and nonexcluded area wage-related costs (Lines 17, 22, 25.50, 25.51, 
and 25.52). We note that contract labor and home office salaries for 
which no corresponding hours are reported are not included. In 
addition, wage-related costs for nonteaching physician Part A employees 
(Line 22) are excluded if no corresponding salaries are reported for 
those employees on Line 4. The formula for Total Salaries plus Wage-
Related Costs (from Worksheet S-3, Part II) is the following: ((Line 1 
+ Line 28 + Line 33 + Line 35)-(Line 2 + Line 3 + Line 4.01 + Line 5 + 
Line 6 + Line 7 + Line 7.01 + Line 8 + Line 9 + Line 10)) + (Line 11 + 
Line 12 + Line 13 + Line 14.01 + 14.02 + Line 15) + (Line 17 + Line 22 
+ 25.50 + 25.51 + 25.52).
    Step 3.--Hours.--With the exception of wage-related costs, for 
which there are no associated hours, we compute total hours using the 
same methods as described for salaries in Step 2. The formula for Total 
Hours (from Worksheet S-3, Part II) is the following:
    ((Line 1 + Line 28 + Line 33 + Line 35)-(Line 2 + Line 3 + Line 
4.01 + Line 5 + Line 6 + Line 7 + Line 7.01 + Line 8 + Line 9 + Line 
10)) + (Line 11 + Line 12 + Line 13 + Line 14.01 + 14.02 + Line 15).
    Step 4.--For each hospital reporting both total overhead salaries 
and total overhead hours greater than zero, we then allocate overhead 
costs to areas of the hospital excluded from the wage index 
calculation. First, we determine the ``excluded rate'', which is the 
ratio of excluded area hours to Revised Total Hours (from Worksheet S-
3, Part II) with the following formula: (Line 9 + Line 10)/(Line 1 + 
Line 28 + Line 33 + Line 35)--(Lines 2, 3, 4.01, 5, 6, 7, 7.01, and 8 
and Lines 26 through 43). We then compute the amounts of overhead 
salaries and hours to be allocated to the excluded areas by multiplying 
the previously discussed ratio by the total overhead salaries and hours 
reported on Lines 26 through 43 of Worksheet S-3, Part II. Next, we 
compute the amounts of overhead wage-related costs to be allocated to 
the excluded areas using three steps:
     We determine the ``overhead rate'' (from Worksheet S-3, 
Part II), which is the ratio of overhead hours (Lines 26 through 43 
minus the sum of Lines 28, 33, and 35) to revised hours excluding the 
sum of lines 28, 33, and 35 (Line 1 minus the sum of Lines 2, 3, 4.01, 
5, 6, 7, 7.01, 8, 9, 10, 28, 33, and 35). We note that, for the FY 2008 
and subsequent wage index calculations, we have been excluding the 
overhead contract labor (Lines 28, 33, and 35) from the determination 
of the ratio of overhead hours to revised hours because hospitals 
typically do not provide fringe benefits (wage-related costs) to 
contract personnel. Therefore, it is not necessary for the wage index 
calculation to exclude overhead wage-related costs for contract 
personnel. Further, if a hospital does contribute to wage-related costs 
for contracted personnel, the instructions for Lines 28, 33, and 35 
require that associated wage-related costs be combined with wages on 
the respective contract labor lines. The formula for the Overhead Rate 
(from Worksheet S-3, Part II) is the following: (Lines 26 through 43--
Lines 28, 33 and 35)/((((Line 1 + Lines 28, 33, 35)-(Lines 2, 3, 4.01, 
5, 6, 7, 7.01, 8, and 26 through 43))-(Lines 9 and 10)) + (Lines 26 
through 43-Lines 28, 33, and 35)).
     We compute overhead wage-related costs by multiplying the 
overhead hours ratio by wage-related costs reported on Part II, Lines 
17, 22, 25.50, 25.51, and 25.52.
     We multiply the computed overhead wage-related costs by 
the previously described excluded area hours ratio.
    Finally, we subtract the computed overhead salaries, wage-related 
costs, and hours associated with excluded areas from the total salaries 
(plus wage-related costs) and hours derived in Steps 2 and 3.
    Step 5.--For each hospital, we adjust the total salaries plus wage-
related costs to a common period to determine total adjusted salaries 
plus wage-related costs. To make the wage adjustment, we estimate the 
percentage change in the employment cost index (ECI) for compensation 
for each 30-day increment from October 14, 2018, through April 15, 
2020, for private industry hospital workers from the Bureau of Labor 
Statistics' (BLS') Compensation and Working Conditions. We use the ECI 
because it reflects the price increase associated with total 
compensation (salaries plus fringes) rather than just the increase in 
salaries. In addition, the ECI includes managers as well as other 
hospital workers. This methodology to compute the monthly update 
factors uses actual quarterly ECI data and assures that the update 
factors match the actual quarterly and annual percent changes. We also 
note that, since April 2006 with the publication of March 2006 data, 
the BLS' ECI uses a different classification system, the North American 
Industrial Classification System (NAICS), instead of the Standard 
Industrial Codes (SICs), which no longer exist. We have consistently 
used the ECI as the data source for our wages and salaries and other 
price proxies in the IPPS market basket, and we did not propose to make 
any changes to the usage of the ECI for FY 2023. The factors used to 
adjust the hospital's data are based on the midpoint of the cost 
reporting period, as indicated in this rule.
    Step 6.--Each hospital is assigned to its appropriate urban or 
rural labor market area before any reclassifications under section 
1886(d)(8)(B), 1886(d)(8)(E), or 1886(d)(10) of the Act. Within each 
urban or rural labor market area, we add the total adjusted salaries 
plus wage-related costs obtained in Step 5 for all hospitals in that 
area to determine the total adjusted salaries plus wage-related costs 
for the labor market area.
    Step 7.--We divide the total adjusted salaries plus wage-related 
costs obtained under Step 6 by the sum of the corresponding total hours 
(from Step 4) for all hospitals in each labor market area to determine 
an average hourly wage for the area.
    Step 8.--We add the total adjusted salaries plus wage-related costs 
obtained in Step 5 for all hospitals in the Nation and then divide the 
sum by the national sum of total hours from Step 4 to arrive at a 
national average hourly wage.
    Step 9.--For each urban or rural labor market area, we calculate 
the hospital wage index value, unadjusted for occupational mix, by 
dividing the area average hourly wage obtained in Step 7 by the 
national average hourly wage computed in Step 8.
    Step 10.--For each urban labor market area for which we do not have 
any hospital wage data (either because there are no IPPS hospitals in 
that labor market area, or there are IPPS hospitals in that area but 
their data are either too new to be reflected in the current year's 
wage index calculation, or their data are aberrant and are deleted from 
the wage index), we finalized in the FY 2020 IPPS/LTCH PPS final rule 
(84 FR 42305) that, for FY 2020 and subsequent years' wage index 
calculations, such CBSA's wage index would be equal to total urban 
salaries plus wage-related costs (from Step 5) in the State, divided by 
the total urban hours (from Step 4) in the State, divided by the 
national average hourly wage from Step 8 (see 84 FR 42305 and 42306, 
August 16, 2019). We stated that we believe that, in the absence of 
wage data for an urban labor market area, it is reasonable to use a

[[Page 48999]]

statewide urban average, which is based on actual, acceptable wage data 
of hospitals in that State, rather than impute some other type of value 
using a different methodology. For calculation of the FY 2023 wage 
index, we note there is one urban CBSA for which we do not have IPPS 
hospital wage data. In Table 3 (which is available via the internet on 
the CMS website) which contains the area wage indexes, we include a 
footnote to indicate to which CBSAs this policy applies. These CBSAs' 
wage indexes would be equal to total urban salaries plus wage-related 
costs (from Step 5) in the respective State, divided by the total urban 
hours (from Step 4) in the respective State, divided by the national 
average hourly wage (from Step 8) (see 84 FR 42305 and 42306, August 
16, 2019). Under this step, we also apply our policy with regard to how 
dollar amounts, hours, and other numerical values in the wage index 
calculations are rounded, as discussed in this section of this rule.
    We refer readers to section II. of the Appendix of the final rule 
for the policy regarding rural areas that do not have IPPS hospitals.
    Step 11.--Section 4410 of Public Law 105-33 provides that, for 
discharges on or after October 1, 1997, the area wage index applicable 
to any hospital that is located in an urban area of a State may not be 
less than the area wage index applicable to hospitals located in rural 
areas in that State. The areas affected by this provision are 
identified in Table 2 listed in section VI. of the Addendum to the 
final rule and available via the internet on the CMS website.
    Following is our policy with regard to rounding of the wage data 
(dollar amounts, hours, and other numerical values) in the calculation 
of the unadjusted and adjusted wage index, as finalized in the FY 2020 
IPPS/LTCH final rule (84 FR 42306, August 16, 2019). For data that we 
consider to be ``raw data,'' such as the cost report data on Worksheets 
S-3, Parts II and III, and the occupational mix survey data, we use 
such data ``as is,'' and do not round any of the individual line items 
or fields. However, for any dollar amounts within the wage index 
calculations, including any type of summed wage amount, average hourly 
wages, and the national average hourly wage (both the unadjusted and 
adjusted for occupational mix), we round the dollar amounts to 2 
decimals. For any hour amounts within the wage index calculations, we 
round such hour amounts to the nearest whole number. For any numbers 
not expressed as dollars or hours within the wage index calculations, 
which could include ratios, percentages, or inflation factors, we round 
such numbers to 5 decimals. However, we continue rounding the actual 
unadjusted and adjusted wage indexes to 4 decimals, as we have done 
historically.
    As discussed in the FY 2012 IPPS/LTCH PPS final rule, in ``Step 
5,'' for each hospital, we adjust the total salaries plus wage-related 
costs to a common period to determine total adjusted salaries plus 
wage-related costs. To make the wage adjustment, we estimate the 
percentage change in the employment cost index (ECI) for compensation 
for each 30-day increment from October 14, 2018, through April 15, 
2020, for private industry hospital workers from the BLS' Compensation 
and Working Conditions. We have consistently used the ECI as the data 
source for our wages and salaries and other price proxies in the IPPS 
market basket, and we did not propose any changes to the usage of the 
ECI for FY 2023. The factors used to adjust the hospital's data were 
based on the midpoint of the cost reporting period, as indicated in the 
following table.
[GRAPHIC] [TIFF OMITTED] TR10AU22.112


[[Page 49000]]


    For example, the midpoint of a cost reporting period beginning 
January 1, 2019, and ending December 31, 2019, is June 30, 2019. An 
adjustment factor of 1.01630 was applied to the wages of a hospital 
with such a cost reporting period.
    Previously, we also would provide a Puerto Rico overall average 
hourly wage. As discussed in the FY 2017 IPPS/LTCH PPS final rule (81 
FR 56915), prior to January 1, 2016, Puerto Rico hospitals were paid 
based on 75 percent of the national standardized amount and 25 percent 
of the Puerto Rico-specific standardized amount. As a result, we 
calculated a Puerto Rico specific wage index that was applied to the 
labor-related share of the Puerto Rico-specific standardized amount. 
Section 601 of the Consolidated Appropriations Act, 2016 (Pub. L. 114-
113) amended section 1886(d)(9)(E) of the Act to specify that the 
payment calculation with respect to operating costs of inpatient 
hospital services of a subsection (d) Puerto Rico hospital for 
inpatient hospital discharges on or after January 1, 2016, shall use 
100 percent of the national standardized amount. As we stated in the FY 
2017 IPPS/LTCH PPS final rule (81 FR 56915 through 56916), because 
Puerto Rico hospitals are no longer paid with a Puerto Rico specific 
standardized amount as of January 1, 2016, under section 1886(d)(9)(E) 
of the Act, as amended by section 601 of the Consolidated 
Appropriations Act, 2016, there is no longer a need to calculate a 
Puerto Rico specific average hourly wage and wage index. Hospitals in 
Puerto Rico are now paid 100 percent of the national standardized 
amount and, therefore, are subject to the national average hourly wage 
(unadjusted for occupational mix) and the national wage index, which is 
applied to the national labor-related share of the national 
standardized amount. Therefore, for FY 2023, there is no Puerto Rico-
specific overall average hourly wage or wage index.
    Based on the methodology, as previously discussed, we stated in the 
proposed rule (87 FR 28365) that the proposed FY 2023 unadjusted 
national average hourly wage was $47.77.
    We did not receive any comments regarding the discussion of our 
method for computing the FY 2023 unadjusted wage index. Based on the 
previously described methodology, the final FY 2023 unadjusted national 
average hourly wage is the following:
[GRAPHIC] [TIFF OMITTED] TR10AU22.113

E. Occupational Mix Adjustment to the FY 2023 Wage Index

    As stated earlier, section 1886(d)(3)(E) of the Act provides for 
the collection of data every 3 years on the occupational mix of 
employees for each short-term, acute care hospital participating in the 
Medicare program, in order to construct an occupational mix adjustment 
to the wage index, for application beginning October 1, 2004 (the FY 
2005 wage index). The purpose of the occupational mix adjustment is to 
control for the effect of hospitals' employment choices on the wage 
index. For example, hospitals may choose to employ different 
combinations of registered nurses, licensed practical nurses, nursing 
aides, and medical assistants for the purpose of providing nursing care 
to their patients. The varying labor costs associated with these 
choices reflect hospital management decisions rather than geographic 
differences in the costs of labor.
1. Use of 2019 Medicare Wage Index Occupational Mix Survey for the FY 
2023 Wage Index
    Section 304(c) of the Consolidated Appropriations Act, 2001 (Pub. 
L. 106- 554) amended section 1886(d)(3)(E) of the Act to require CMS to 
collect data every 3 years on the occupational mix of employees for 
each short-term, acute care hospital participating in the Medicare 
program. As discussed in the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 
25402 through 25403) and final rule (86 FR 45173), we collected data in 
2019 to compute the occupational mix adjustment for the FY 2022, FY 
2023, and FY 2024 wage indexes. The FY 2023 occupational mix adjustment 
is based on the calendar year (CY) 2019 survey. Hospitals were required 
to submit their completed 2019 surveys (Form CMS-10079, OMB Number 
0938-0907, expiration date October 31, 2022) to their MACs by September 
3, 2020. It should be noted that this collection of information was 
approved under OMB control number 0938-0907 with an expiration date of 
October 31, 2022. An extension of the information collection request is 
currently being developed. The public will have an opportunity to 
review and submit comments regarding the extension of this PRA package 
through a public notice and comment period separate from this 
rulemaking. The preliminary, unaudited CY 2019 survey data were posted 
on the CMS website on September 8, 2020. As with the Worksheet S-3, 
Parts II and III cost report wage data, as part of the FY 2023 desk 
review process, the MACs revised or verified data elements in 
hospitals' occupational mix surveys that resulted in certain edit 
failures.
2. Calculation of the Occupational Mix Adjustment for FY 2023
    In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28366), for FY 
2023, we proposed to calculate the occupational mix adjustment factor 
using the same methodology that we have used since the FY 2012 wage 
index (76 FR 51582 through 51586) and to apply the occupational mix 
adjustment to 100 percent of the FY 2023 wage index. In the FY 2020 
IPPS/LTCH PPS final rule (84 FR 42308), we modified our methodology 
with regard to how dollar amounts, hours, and other numerical values in 
the unadjusted and adjusted wage index calculation are rounded, in 
order to ensure consistency in the calculation. According to the policy 
finalized in the FY 2020 IPPS/LTCH PPS final rule (84 FR 42308 and 
42309), for data that we consider to be ``raw data,'' such as the cost 
report data on Worksheets S-3, Parts II and III, and the occupational 
mix survey data, we continue to use these data ``as is'', and not round 
any of the individual line items or fields. However, for any dollar 
amounts within the wage index calculations, including any type of 
summed wage amount, average hourly wages, and the national average 
hourly wage (both the unadjusted and adjusted for occupational mix), we 
round such dollar amounts to 2 decimals. We round any hour amounts 
within the wage index calculations to the nearest whole number. We 
round any numbers not expressed as dollars or hours in the wage index 
calculations, which could include ratios, percentages, or inflation 
factors, to 5 decimals. However, we continue rounding the actual 
unadjusted and adjusted wage indexes to 4 decimals, as we have done 
historically.
    Similar to the method we use for the calculation of the wage index 
without occupational mix, salaries and hours for a multicampus hospital 
are allotted among the different labor market areas where its campuses 
are located. Table 2

[[Page 49001]]

associated with this final rule (which is available via the internet on 
the CMS website), which contains the final FY 2023 occupational mix 
adjusted wage index, includes separate wage data for the campuses of 
multicampus hospitals. We refer readers to section III.C. of the 
preamble of this final rule for a chart listing the multicampus 
hospitals and the FTE percentages used to allot their occupational mix 
data.
    Because the statute requires that the Secretary measure the 
earnings and paid hours of employment by occupational category not less 
than once every 3 years, all hospitals that are subject to payments 
under the IPPS, or any hospital that would be subject to the IPPS if 
not granted a waiver, must complete the occupational mix survey, unless 
the hospital has no associated cost report wage data that are included 
in the FY 2023 wage index. For the proposed FY 2023 wage index, we used 
the Worksheet S-3, Parts II and III wage data of 3,112 hospitals, and 
we used the occupational mix surveys of 3,010 hospitals for which we 
also had Worksheet S-3 wage data, which represented a ``response'' rate 
of 97 percent (3,010/3,112). For the proposed FY 2023 wage index, we 
applied proxy data for noncompliant hospitals, new hospitals, or 
hospitals that submitted erroneous or aberrant data in the same manner 
that we applied proxy data for such hospitals in the FY 2012 wage index 
occupational mix adjustment (76 FR 51586). As a result of applying this 
methodology, the proposed FY 2023 occupational mix adjusted national 
average hourly wage was $47.71.
    We did not receive any comments on our proposed calculation of the 
occupational mix adjustment to the FY 2023 wage index. Thus, for the 
reasons discussed in this final rule and in the FY 2023 IPPS/LTCH PPS 
proposed rule, we are finalizing our proposal, without modification to 
calculate the occupational mix adjustment factor using the same 
methodology that we have used since the FY 2012 wage index and to apply 
the occupational mix adjustment to 100 percent of the FY 2023 wage 
index.
    For the final FY 2023 wage index, we are using the Worksheet S3, 
Parts II and III wage data of 3,136 hospitals, and we are using the 
occupational mix surveys of 3,035 hospitals for which we also have 
Worksheet S-3 wage data, which is a ``response'' rate of 97 percent 
(3,035/3,136). For the final FY 2023 wage index, we are applying proxy 
data for noncompliant hospitals, new hospitals, or hospitals that 
submitted erroneous or aberrant data in the same manner that we applied 
proxy data for such hospitals in the FY 2012 wage index occupational 
mix adjustment (76 FR 51586). As a result of applying this methodology, 
the final FY-2023 occupational mix adjusted national average hourly 
wage is the following:
[GRAPHIC] [TIFF OMITTED] TR10AU22.114

F. Analysis and Implementation of the Proposed Occupational Mix 
Adjustment and the FY 2023 Occupational Mix Adjusted Wage Index

    As discussed in section III.E. of the preamble of this final rule, 
for FY 2023, we are applying the occupational mix adjustment to 100 
percent of the FY 2023 wage index. We calculated the occupational mix 
adjustment using data from the 2019 occupational mix survey data, using 
the methodology described in the FY 2012 IPPS/LTCH PPS final rule (76 
FR 51582 through 51586).
    The FY 2023 national average hourly wages for each occupational mix 
nursing subcategory as calculated in Step 2 of the occupational mix 
calculation are as follows:
[GRAPHIC] [TIFF OMITTED] TR10AU22.115

    The national average hourly wage for the entire nurse category is 
computed in Step 5 of the occupational mix calculation. Hospitals with 
a nurse category average hourly wage (as calculated in Step 4) of 
greater than the national nurse category average hourly wage receive an 
occupational mix adjustment factor (as calculated in Step 6) of less 
than 1.0. Hospitals with a nurse category average hourly wage (as 
calculated in Step 4) of less than the national nurse category average 
hourly wage receive an occupational mix adjustment factor (as 
calculated in Step 6) of greater than 1.0.
    Based on the 2019 occupational mix survey data, we determined (in 
Step 7 of the occupational mix calculation) the following:
[GRAPHIC] [TIFF OMITTED] TR10AU22.116


[[Page 49002]]


    We compared the FY 2023 occupational mix adjusted wage indexes for 
each CBSA to the unadjusted wage indexes for each CBSA. Applying the 
occupational mix adjustment to the wage data resulted in the following:
[GRAPHIC] [TIFF OMITTED] TR10AU22.117

    These results indicate that a smaller percentage of urban areas 
(53.6 percent) would benefit from the occupational mix adjustment than 
would rural areas (57.4 percent).

G. Application of the Rural Floor, Application of the Imputed Floor, 
Application of the State Frontier Floor, Continuation of the Low Wage 
Index Hospital Policy, and Budget Neutrality Adjustment

1. Rural Floor
    Section 4410(a) of the Balanced Budget Act of 1997 (Pub. L. 105-33) 
provides that, for discharges on or after October 1, 1997, the area 
wage index applicable to any hospital that is located in an urban area 
of a State may not be less than the area wage index applicable to 
hospitals located in rural areas in that State. This provision is 
referred to as the rural floor. Section 3141 of the Patient Protection 
and Affordable Care Act (Pub. L. 111-148) also requires that a national 
budget neutrality adjustment be applied in implementing the rural 
floor.
    In the FY 2020 IPPS/LTCH PPS final rule (84 FR 42332 through 
42336), we removed urban to rural reclassifications from the 
calculation of the rural floor to prevent inappropriate payment 
increases under the rural floor due to rural reclassifications, such 
that, beginning in FY 2020, the rural floor was calculated without 
including the wage data of hospitals that have reclassified as rural 
under section 1886(d)(8)(E) of the Act (as implemented in the 
regulations at Sec.  412.103). For FY 2023, we proposed to continue to 
calculate the rural floor without the wage data of hospitals that have 
reclassified as rural under Sec.  412.103 (87 FR 28367-28368). Also, 
for the purposes of applying the provisions of section 
1886(d)(8)(C)(iii) of the Act, effective beginning in FY 2020, we 
removed the data of hospitals reclassified from urban to rural under 
section 1886(d)(8)(E) of the Act (as implemented in the regulations at 
Sec.  412.103) from the calculation of ``the wage index for rural areas 
in the State in which the county is located'' as referred to in section 
1886(d)(8)(C)(iii) of the Act (84 FR 42333). In the IPPS/LTCH PPS 
proposed rule (87 FR 28367 and 28368), we proposed to continue to apply 
this policy for FY 2023.
    We noted in the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28368) 
that the FY 2020 rural floor policy and the related budget neutrality 
adjustment were the subject of pending litigation, including in Citrus 
HMA, LLC, d/b/a Seven Rivers Regional Medical Center v. Becerra, No. 
1:20-cv-00707 (D.D.C.) (hereafter referred to as Citrus). On April 8, 
2022, the district court in Citrus granted in part the plaintiff 
hospitals' motion for summary judgment and denied the Secretary's 
cross-motion for summary judgment. The court found that the Secretary 
did not have authority under section 4410(a) of the Balanced Budget Act 
of 1997 to establish a rural floor lower than the rural wage index for 
a state. We stated that while Citrus involves only FY 2020, the court's 
decision--which is subject to potential appeal--may have implications 
for FY 2023 payment rates. We stated that we were continuing to 
evaluate the court's decision, and although we proposed for the rural 
floor wage index policy (and the related budget neutrality adjustment) 
to continue for FY 2023, we stated we may decide to take a different 
approach in the final rule, depending on public comments or 
developments in the court proceedings.
    Comments: Several commenters supported CMS's policy established 
beginning in FY 2020 to exclude the wage data of Sec.  412.103 
hospitals from the rural floor calculation. Some commenters 
specifically stated that this policy restores fairness in the wage 
index by preventing certain states from manipulating the wage index 
system to artificially inflate the wage indexes of hospitals in the 
state at the expense of all other states, due to the rural floor 
national budget neutrality adjustment required by section 3141 of 
Public Law 111-148.
    Many commenters urged CMS to acquiesce to the district court's 
decision in Citrus, discontinue the policy of excluding the wage data 
of Sec.  412.103 hospitals from the rural floor calculation, and revert 
to the policy that existed prior to FY 2020. The commenters stated 
their belief that the court's analysis was thorough and that continuing 
the rural floor policy would

[[Page 49003]]

only increase the agency's exposure to future lawsuits. Commenters 
asserted that the plain language of the statute does not provide for a 
free-floating rural floor that is not linked to the rural wage index. 
One of the commenters advocating for CMS to revert to the policy that 
applied prior to FY 2020 requested that if CMS does choose to continue 
its current rural floor policy in FY 2023, it should do so in a non-
budget neutral manner.
    Other commenters also suggested that along with including the wage 
data of Sec.  412.103 hospitals in the rural floor calculation, CMS 
should include the wage data of Sec.  412.103 hospitals for purposes of 
the calculation required by Sec.  1886(d)(8)(C)(ii) of the Act. Two 
commenters specifically asserted that CMS should include the wage data 
of Sec.  412.103 hospitals that also have an Medicare Geographic 
Classification Review Board (MGCRB) reclassification for purposes of 
the calculation required by Sec.  1886(d)(8)(C)(ii) of the Act. 
Specifically, these commenters stated that when a geographically rural 
hospital has an active MGCRB reclassification to another area, CMS 
includes the wage data of the hospital in calculating the rural wage 
index of the state in which that hospital is located, if not doing so 
would reduce the wage index for that rural area, as described in Sec.  
1886(d)(8)(C)(ii) of the Act. However, the commenters stated that CMS 
does not treat the wage data of hospitals with a Sec.  412.103 
reclassification in addition to an MGCRB reclassification in the same 
manner as geographically rural hospitals with an MGCRB 
reclassification. A commenter stated that treating hospitals with dual 
Sec.  412.103 and MGCRB reclassifications in the same manner as other 
rural hospitals for the calculation required by Sec.  1886(d)(8)(C)(ii) 
would help address rural floor manipulation by mitigating the impact 
that one or two Sec.  412.103 hospitals remaining rural for wage index 
purposes would have on the rural wage index and rural floor.
    Response: We appreciate the commenters' input. In response to the 
comments supporting our proposal to continue our policy of excluding 
the wage data of Sec.  412.103 hospitals from the rural floor 
calculation for FY 2023, we appreciate the concern regarding wage index 
manipulation, particularly arising from high wage hospitals in certain 
states reclassifying as rural under Sec.  412.103 to inflate the rural 
wage index. However, as noted by a commenter, a national budget 
neutrality adjustment is required by section 3141 of Public Law 111-
148. As stated in response to comments in the FY 2022 IPPS/LTCH PPS 
final rule (86 FR 45175 through 45176) and in the FY 2017 IPPS/LTCH PPS 
final rule (81 FR 56920), section 3141 requires that budget neutrality 
for the rural floor be applied ``through a uniform, national adjustment 
to the area wage index'' instead of within each State beginning in FY 
2011 (75 FR 50160). Accordingly, we do not have the authority to 
calculate rural floor budget neutrality in a State-specific manner.
    With regard to the comments concerning the district court's 
decision in Citrus, prior to FY 2020, it was our policy to have the 
rural wage index set the rural floor, resulting in identical wage index 
values for a state's rural area and rural floor. We changed that policy 
in the FY 2020 IPPS/LTCH PPS final rule to prevent inappropriate 
payment increases under the rural floor due to rural reclassifications 
under Sec.  412.103 (84 FR 42332 through 42336). We explained that 
rather than raising the payment of some urban hospitals to the level of 
the average rural hospital in their State, as we believed was the 
intent of the rural floor policy, the rural floor calculation prior to 
FY 2020 enabled urban hospitals to have their payments raised to the 
relatively high level of one or more geographically urban hospitals 
reclassified as rural (84 FR 42334). This policy change beginning in FY 
2020 to exclude Sec.  412.103 hospitals from the rural floor 
calculation created a rural area wage index separate from the rural 
floor, with the rural floor for the state typically lower than the 
rural wage index.
    We understand that our policy of setting a rural floor lower than 
the rural wage index for a state is inconsistent with the district 
court's decision in Citrus. Following our review of that decision and 
the comments we received on the proposed rule, we are finalizing a 
policy that calculates the rural floor as it was calculated before FY 
2020. Specifically, for FY 2023 and subsequent years, we are finalizing 
a policy to include the wage data of hospitals that have reclassified 
from urban to rural under section 1886(d)(8)(E) of the Act (as 
implemented in the regulations at Sec.  412.103) and have no additional 
form of reclassification (MGCRB or Lugar) in the calculation of the 
rural floor, and to include the wage data of such hospitals in the 
calculation of ``the wage index for rural areas in the State in which 
the county is located'' as referred to in section 1886(d)(8)(C)(iii) of 
the Act.
    With regard to the application of the hold harmless policy that the 
commenters referenced at Sec.  1886(d)(8)(C)(ii), the statute requires 
that a rural area be held harmless from the effects of hospitals 
reclassifying under Lugar or the MGCRB. Specifically, Sec.  
1886(d)(8)(C)(ii) states: ``If the application of subparagraph (B) or a 
decision of the Medicare Geographic Classification Review Board or the 
Secretary under paragraph (10), by treating hospitals located in a 
rural county or counties as not being located in the rural area in a 
State, reduces the wage index for that rural area (as applied under 
this subsection), the Secretary shall calculate and apply such wage 
index under this subsection as if the hospitals so treated had not been 
excluded from calculation of the wage index for that rural area.''
    The commenters suggest that CMS should include the wage data of 
Sec.  412.103 hospitals that also have a MGCRB reclassification for 
purposes of the calculation required by Sec.  1886(d)(8)(C)(ii), 
thereby treating hospitals with dual Sec.  412.103 and MGCRB 
reclassifications no differently than geographically rural hospitals 
with MGCRB reclassifications for the hold-harmless comparison at Sec.  
1886(d)(8)(C)(ii). Specifically, this would involve calculating the 
rural area wage index including the data of all Sec.  412.103 
hospitals, and then comparing it to a wage index with the effect of 
MGCRB reclassifications and Lugar hospital statuses applied, in order 
to possibly hold the rural area harmless from the effect of MGCRB 
reclassifications and Lugar hospital statuses.
    As we explained in response to a similar comment in the FY 2022 
IPPS/LTCH PPS final rule (86 FR 45181), CMS continues to treat Sec.  
412.103 hospitals as rural as required by the statute even if such 
hospitals have an additional MGCRB reclassification by affording the 
hospital the benefits of rural status, such as 340B program and RRC 
eligibility. However, in developing our policies for how hospitals with 
dual reclassifications would be treated in wage index calculations 
following our April 21, 2016 IFC (81 FR 23428 through 23438), CMS 
discussed the effect of simultaneous Sec.  412.103 and MGCRB 
reclassifications. We stated that when there is both a Sec.  412.103 
reclassification and an MGCRB reclassification, the MGCRB 
reclassification would control for wage index calculation and payment 
purposes. We explained that ``In these circumstances, we believe it is 
appropriate to rely on the urban MGCRB reclassification to include the 
hospital's wage data in the calculation of the urban CBSA wage index. 
Further, we believe it is appropriate to rely on the

[[Page 49004]]

urban MGCRB reclassification to ensure that the hospital be paid based 
on its urban MGCRB wage index. While rural reclassification confers 
other rural benefits besides the wage index under section 1886(d) of 
the Act, a hospital that chooses to pursue reclassification under the 
MGCRB (while also maintaining a rural reclassification under Sec.  
412.103) would do so solely for wage index payment purposes.'' (81 FR 
23434). We continue to believe that policy, developed through 
rulemaking, is appropriate, since MGCRB reclassifications are solely 
for wage index payment purposes. Furthermore, the approach the 
commenters suggest would constitute a significant change to our current 
policy for Sec.  412.103 hospitals that also have a MGCRB 
reclassification, and would create numerous downstream effects across 
IPPS ratesetting that might not be favorable to hospitals, contrary to 
the commenters' intent. For example, some states would experience a 
decline in their rural wage index if we were to treat hospitals with 
dual Sec.  412.103 and MGCRB reclassifications no differently than 
geographically rural hospitals with MGCRB reclassifications. In 
response to the commenters' assertion that such treatment would address 
rural floor manipulation, we note that the commenters' suggested 
treatment of hospitals with dual Sec.  412.103 and MGCRB 
reclassifications would potentially allow for other forms of wage index 
manipulation. For example, high-wage hospitals could obtain Sec.  
412.103 status, reclassify back to their home area under the MGCRB, in 
order to have their Sec.  412.103 rural reclassifications raise the 
rural wage index via the hold harmless provision at Sec.  
1886(d)(8)(C)(ii), without lowering the hospitals' own wage index. We 
did not propose the policy the commenters suggest, and it would 
constitute a significant change with numerous effects on the IPPS wage 
index. We do not think it would be appropriate to adopt such a policy 
without describing it in a proposed rule and obtaining public comments 
from all interested parties. Therefore, in this final rule we are not 
adopting the policy the commenters suggest.
    Based on the district court's decision in Citrus and the comments 
we received, we are not finalizing our rural floor wage index policy as 
proposed, which would have excluded Sec.  412.103 hospitals from the 
calculation of the rural floor and from the calculation of ``the wage 
index for rural areas in the State in which the county is located'' as 
referred to in section 1886(d)(8)(C)(iii) of the Act. Rather, we are 
finalizing a policy that calculates the rural floor as it was 
calculated before FY 2020. This decision follows our review of the 
decision in Citrus and the comments received, including comments urging 
us to revert to our pre-2020 policy. For FY 2023 and subsequent years, 
we are finalizing a policy to include the wage data of hospitals that 
have reclassified from urban to rural under section 1886(d)(8)(E) of 
the Act (as implemented in the regulations at Sec.  412.103) and have 
no additional form of reclassification (MGCRB or Lugar) in the 
calculation of the rural floor, and to include the wage data of such 
hospitals in the calculation of ``the wage index for rural areas in the 
State in which the county is located'' as referred to in section 
1886(d)(8)(C)(iii) of the Act. We will apply the same policy as prior 
to the FY 2020 final rule for calculating the rural floor, in which the 
rural wage index sets the rural floor. Based on the FY 2023 wage index 
associated with this final rule (which is available via the internet on 
the CMS website) and based on the calculation of the rural floor 
including the wage data of hospitals that have reclassified as rural 
under Sec.  412.103, we estimate that 275 hospitals would receive an 
increase in their FY 2023 wage index due to the application of the 
rural floor.
2. Imputed Floor
    In the FY 2005 IPPS final rule (69 FR 49109 through 49111), we 
adopted the imputed floor policy as a temporary 3-year regulatory 
measure to address concerns from hospitals in all urban States that 
have stated that they are disadvantaged by the absence of rural 
hospitals to set a wage index floor for those States. We extended the 
imputed floor policy eight times since its initial implementation, the 
last of which was adopted in the FY 2018 IPPS/LTCH PPS final rule and 
expired on September 30, 2018. (We refer readers to further discussions 
of the imputed floor in the IPPS/LTCH PPS final rules from FYs 2014 
through 2019 (78 FR 50589 through 50590, 79 FR 49969 through 49971, 80 
FR 49497 through 49498, 81 FR 56921 through 56922, 82 FR 38138 through 
38142, and 83 FR 41376 through 41380, respectively) and to the 
regulations at 42 CFR 412.64(h)(4).) For FYs 2019, 2020, and 2021, 
hospitals in all-urban states received a wage index that was calculated 
without applying an imputed floor, and we no longer included the 
imputed floor as a factor in the national budget neutrality adjustment.
    In computing the imputed floor for an all-urban State under the 
original methodology established beginning in FY 2005, we calculated 
the ratio of the lowest-to-highest CBSA wage index for each all-urban 
State as well as the average of the ratios of lowest-to-highest CBSA 
wage indexes of those all-urban States. We then compared the State's 
own ratio to the average ratio for all-urban States and whichever was 
higher was multiplied by the highest CBSA wage index value in the 
State--the product of which established the imputed floor for the 
State. We adopted a second, alternative methodology beginning in FY 
2013 (77 FR 53368 through 53369) to address the concern that the 
original imputed floor methodology guaranteed a benefit for one all-
urban State with multiple wage indexes (New Jersey) but could not 
benefit another all-urban State, Rhode Island, which had only one CBSA. 
Under the alternative methodology, we first determined the average 
percentage difference between the post reclassified, pre-floor area 
wage index and the post-reclassified, rural floor wage index (without 
rural floor budget neutrality applied) for all CBSAs receiving the 
rural floor. The lowest post reclassified wage index assigned to a 
hospital in an all-urban State having a range of such values then was 
increased by this factor, the result of which established the State's 
alternative imputed floor. Under the updated OMB labor market area 
delineations adopted by CMS beginning in FY 2015, Delaware became an 
all-urban State, along with New Jersey and Rhode Island, and was 
subject to an imputed floor as well. In addition, we adopted a policy, 
as reflected at Sec.  412.64(h)(4)(vi), that, for discharges on or 
after October 1, 2012, and before October 1, 2018, the minimum wage 
index value for a State is the higher of the value determined under the 
original methodology or the value determined under the alternative 
methodology. The regulations implementing the imputed floor wage index, 
both the original methodology and the alternative methodology, were set 
forth at Sec.  412.64(h)(4).
    Section 9831 of the American Rescue Plan Act of 2021 (Pub. L. 117-
2) enacted on March 11, 2021, amended section 1886(d)(3)(E)(i) of the 
Act (42 U.S.C. 1395ww(d)(3)(E)(i)) and added section 1886(d)(3)(E)(iv) 
of the Act to establish a minimum area wage index for hospitals in all-
urban States for discharges occurring on or after October 1, 2021. 
Specifically, section 1886(d)(3)(E)(iv)(I) and (II) of the Act provides 
that for discharges occurring on or after October 1, 2021, the area 
wage index applicable to any hospital in

[[Page 49005]]

an all-urban State may not be less than the minimum area wage index for 
the fiscal year for hospitals in that State established using the 
methodology described in Sec.  412.64(h)(4)(vi) as in effect for FY 
2018. Thus, effective beginning October 1, 2021 (FY 2022), section 
1886(d)(3)(E)(iv) of the Act reinstates the imputed floor wage index 
policy for all-urban States, with no expiration date, using the 
methodology described in 42 CFR 412.64(h)(4)(vi) as in effect for FY 
2018. As discussed previously, under Sec.  412.64(h)(4)(vi), the 
minimum wage index value for hospitals in an all-urban State is the 
higher of the value determined using the original methodology (as set 
forth at Sec.  412.64(h)(4)(i) through (v)) or the value determined 
using alternative methodology (as set forth at Sec.  
412.64(h)(4)(vi)(A) and (B)) for calculating an imputed floor. 
Therefore, as provided in Sec.  412.64(h)(4)(vi), we apply the higher 
of the value determined under the original or alternative methodology 
for calculating a minimum wage index, or imputed floor, for all-urban 
States effective beginning with FY 2022. We note that the rural floor 
values used in the alternative methodology at Sec.  412.64(h)(4)(vi)(A) 
and (B) would now include the wage data of hospitals reclassified under 
Sec.  412.103 that have no additional form of reclassification (MGCRB 
or Lugar), according to the rural floor wage index policy finalized in 
this final rule in which we calculate the rural floor for FY 2023 
including the wage data of such hospitals.
    Unlike the imputed floor that was in effect from FYs 2005 through 
2018, section 1886(d)(3)(E)(iv)(III) of the Act provides that the 
imputed floor wage index shall not be applied in a budget neutral 
manner. Specifically, section 9831(b) of Public Law 117-2 amends 
section 1886(d)(3)(E)(i) of the Act to exclude the imputed floor from 
the budget neutrality requirement under section 1886(d)(3)(E)(i) of the 
Act. In other words, the budget neutrality requirement under section 
1886(d)(3)(E)(i) of the Act, as amended, must be applied without taking 
into account the imputed floor adjustment under section 
1886(d)(3)(E)(iv) of the Act. When the imputed floor was in effect from 
FY 2005 through FY 2018, to budget neutralize the increase in payments 
resulting from application of the imputed floor, we calculated the 
increase in payments resulting from the imputed floor together with the 
increase in payments resulting from the rural floor and applied an 
adjustment to reduce the wage index. By contrast, for FY 2022 and 
subsequent years, we apply the imputed floor after the application of 
the rural floor and apply no reductions to the standardized amount or 
to the wage index to fund the increase in payments to hospitals in all-
urban States resulting from the application of the imputed floor 
required under section 1886(d)(3)(E)(iv) of the Act.
    The imputed floor under section 1886(d)(3)(E)(iv) of the Act 
applies to all-urban States, as defined in new subclause (IV). Section 
1886(d)(3)(E)(iv)(IV) provides that, for purposes of the imputed floor 
wage index under clause (iv), the term all-urban State means a State in 
which there are no rural areas (as defined in section 1886(d)(2)(D) of 
the Act) or a State in which there are no hospitals classified as rural 
under section 1886 of the Act. Under this definition, given that it 
applies for purposes of the imputed floor wage index, we consider a 
hospital to be classified as rural under section 1886 of the Act if it 
is assigned the State's rural area wage index value. Therefore, under 
the definition at section 1886(d)(3)(E)(iv)(IV) of the Act, ``a State 
in which there are no hospitals classified as rural under this 
section'' includes a State that has a rural area but no hospitals that 
receive the rural area wage index under section 1886(d) of the Act. For 
purposes of this definition, hospitals redesignated as rural under 
section 1886(d)(8)(E) of the Act (412.103 rural reclassifications) are 
considered classified as rural if they receive the rural wage index; 
however, hospitals that are deemed urban under section 1886(d)(8)(B) of 
the Act (in Lugar counties), or are reclassified to an urban area under 
section 1886(d)(10) of the Act (MGCRB reclassifications) are not 
considered classified as rural because they do not receive the rural 
wage index. In contrast, we note that in the imputed floor policy in 
effect from FY 2005 through FY 2018, we did not consider a State to 
qualify for ``all urban status'' if there were one or more hospitals 
geographically located in the rural area of the State, even if all such 
hospitals subsequently reclassified to receive an urban area wage 
index. There is one State, Connecticut, that would be eligible for the 
imputed floor because there are currently no hospitals in Connecticut 
that are classified as rural under section 1886(d) for purposes of the 
wage index--in other words, there are no hospitals that receive the 
rural wage index. There is currently one rural county in Connecticut. 
All hospitals in this county are either deemed urban under section 
1886(d)(8)(B) of the Act or receive an MGCRB reclassification under 
section 1886(d)(10) of the Act. While several Connecticut hospitals 
were approved for rural reclassification under section 1886(d)(8)(E) of 
the Act, at this point all have received a subsequent urban 
reclassification under section 1886(d)(10) of the Act.
    Additionally, under section 1861(x) of the Act, the term State has 
the meaning given to it in section 210(h) of the Act. Because section 
210(h) of the Act defines the word State to also include the District 
of Columbia and the Commonwealth of Puerto Rico, Washington, DC and 
Puerto Rico may also qualify as all-urban States for purposes of the 
imputed floor if the requirements of section 1886(d)(3)(E)(iv)(IV) of 
the Act are met. Based on data available for this final rule, the 
following States would be all-urban States as defined in section 
1886(d)(3)(E)(iv)(IV) of the Act, and thus hospitals in such States 
would be eligible to receive an increase in their wage index due to 
application of the imputed floor for FY 2023: New Jersey, Rhode Island, 
Delaware, Connecticut, and Washington, DC.
    In the FY 2022 IPPS/LTCH PPS final rule, we revised the regulations 
at Sec.  412.64(e)(1) and (4) and (h)(4) and (5) to implement the 
imputed floor required by section 1886(d)(3)(E)(iv) of the Act for 
discharges occurring on or after October 1, 2021. The imputed floor 
will be applied for FY 2023 in accordance with the policies adopted in 
the FY 2022 IPPS/LTCH PPS final rule. For more information regarding 
our implementation of the imputed floor required by section 
1886(d)(3)(E)(iv) of the Act, we refer readers to the discussion in the 
FY 2022 IPPS/LTCH PPS final rule (86 FR 45176 through 45178).
    Comment: Several commenters supported the application of the 
imputed floor wage index policy, including the policy's definition of 
all-urban states as well as its non-budget neutral application as 
required by section 9831 of the American Rescue Plan Act of 2021. A 
commenter opposed the imputed floor policy, stating that it unfairly 
manipulates the wage index to benefit a handful of only-urban states 
and territories, but acknowledged that the imputed floor policy is 
derived from legislation enacted by Congress.
    Response: We appreciate the commenters' support of our application 
of the statutory imputed floor policy. Responding to the commenter 
opposed to this policy, we underscore that, as the commenter pointed 
out, the imputed floor was established by section 9831 of the American 
Rescue Plan Act of 2021.

[[Page 49006]]

Accordingly, CMS does not have discretion to not apply the imputed 
floor.
    After consideration of the public comments, we will apply the 
imputed floor required by section 1886(d)(3)(E)(iv) of the Act for 
discharges occurring on or after October 1, 2022 in accordance with our 
existing policies.
3. State Frontier Floor for FY 2023
    Section 10324 of Public Law 111-148 requires that hospitals in 
frontier States cannot be assigned a wage index of less than 1.0000. 
(We refer readers to the regulations at 42 CFR 412.64(m) and to a 
discussion of the implementation of this provision in the FY 2011 IPPS/
LTCH PPS final rule (75 FR 50160 through 50161).) In the FY 2023 IPPS/
LTCH PPS proposed rule, we did not propose any changes to the frontier 
floor policy for FY 2023. In the proposed rule we stated that 44 
hospitals would receive the frontier floor value of 1.0000 for their FY 
2023 proposed wage index. These hospitals are located in Montana, North 
Dakota, South Dakota, and Wyoming.
    We did not receive any public comments on the application of the 
State frontier floor for FY 2023. In this final rule, 44 hospitals will 
receive the frontier floor value of 1.0000 for their FY 2023 wage 
index. These hospitals are located in Montana, North Dakota, South 
Dakota, and Wyoming. We note that while Nevada meets the criteria of a 
frontier State, all hospitals within the State currently receive a wage 
index value greater than 1.0000. The areas affected by the rural and 
frontier floor policies for the final FY 2023 wage index are identified 
in Table 2 associated with this final rule, which is available via the 
internet on the CMS website.
4. Continuation of the Low Wage Index Hospital Policy; Budget 
Neutrality Adjustment
    To help mitigate wage index disparities, including those resulting 
from the inclusion of hospitals with rural reclassifications under 42 
CFR 412.103 in the rural floor, in the FY 2020 IPPS/LTCH PPS final rule 
(84 FR 42325 through 42339), we finalized policies to reduce the 
disparity between high and low wage index hospitals by increasing the 
wage index values for certain hospitals with low wage index values and 
doing so in a budget neutral manner through an adjustment applied to 
the standardized amounts for all hospitals, as well as by changing the 
calculation of the rural floor. We also provided for a transition in FY 
2020 for hospitals experiencing significant decreases in their wage 
index values as compared to their final FY 2019 wage index, and made 
these changes in a budget neutral manner.
    We increase the wage index for hospitals with a wage index value 
below the 25th percentile wage index value for a fiscal year by half 
the difference between the otherwise applicable final wage index value 
for a year for that hospital and the 25th percentile wage index value 
for that year across all hospitals (the low wage index hospital 
policy). We stated in the FY 2020 IPPS/LTCH PPS final rule (84 FR 42326 
through 42328) our intention that this policy will be effective for at 
least 4 years, beginning in FY 2020, in order to allow employee 
compensation increases implemented by these hospitals sufficient time 
to be reflected in the wage index calculation. We noted in the FY 2023 
IPPS/LTCH PPS proposed rule (87 FR 28369) that the FY 2020 low wage 
index hospital policy and the related budget neutrality adjustment are 
the subject of pending litigation, including in Bridgeport Hospital, et 
al., v. Becerra, No. 1:20-cv-01574 (D.D.C.) (hereafter referred to as 
Bridgeport). On March 2, 2022, the district court in Bridgeport granted 
in part the plaintiff hospitals' motion for summary judgment and denied 
the Secretary's cross-motion for summary judgment. The court found that 
the Secretary did not have authority under section 1886(d)(3)(E) or 
1886(d)(5)(I)(i) of the Act to adopt the low wage index hospital policy 
and ordered additional briefing on the appropriate remedy. We stated 
that while Bridgeport involves only FY 2020, the court's decision--
which is not final at this time and is also subject to potential 
appeal--may have implications for FY 2023 payment rates. We stated that 
we were continuing to evaluate the court's decision, and although we 
proposed the low wage index hospital policy (and the related budget 
neutrality adjustment, discussed in this section of this rule) to 
continue for FY 2023, we stated that we may decide to take a different 
approach in the final rule, depending on public comments or 
developments in the court proceedings. In order to offset the estimated 
increase in IPPS payments to hospitals with wage index values below the 
25th percentile wage index value, for FY 2023 and for subsequent fiscal 
years during which the low wage index hospital policy is in effect, we 
proposed to apply a budget neutrality adjustment in the same manner as 
we applied it in FYs 2020, 2021, and 2022, as a uniform budget 
neutrality factor applied to the standardized amount. We refer readers 
to section II.A.4.f. of the addendum to this final rule for further 
discussion of the budget neutrality adjustment for FY 2023. For 
purposes of the low wage index hospital policy, based on the data for 
this final rule, the table displays the 25th percentile wage index 
value across all hospitals for FY 2023. FY 2023 25th Percentile Wage 
Index Value 0.8427.
    Comment: Many commenters supported the low wage index hospital 
policy. Commenters praised the low wage index hospital policy for 
already beginning to reduce wage index disparities and urged the agency 
to continue with the policy for FY 2023 as proposed. Commenters 
described dire consequences of the policy ending, with a commenter 
specifically stating that Medicare payments to hospitals in Puerto Rico 
could fall drastically. Numerous commenters representing hospitals in a 
state with relatively low wages indicated that they have used the 
increased payments resulting from the low wage index hospital policy as 
CMS intended, by raising compensation for their workers. However, these 
commenters stated that the national average hourly wage increased at an 
even higher rate due to COVID-19, indicating that additional time for 
the policy and continued efforts on behalf of low wage hospitals are 
required. A commenter requested that CMS consider the effects of COVID-
19 as CMS decides how it will appropriately evaluate the effectiveness 
of its policy to raise low wage hospitals' wage indexes in the near 
future, and another commenter specifically requested that CMS extend 
the policy for at least four additional years due to COVID-19. A 
commenter stated that CMS should maintain the policy until CMS can 
verify that increased hospital compensation under the policy has led to 
increased wage indexes, consistent with original intent of the policy.
    Response: We appreciate the many comments received in support of 
our low wage index hospital policy and the feedback regarding 
achievement of the intended policy goal. We appreciate the commenters' 
requests to consider the impacts of COVID-19, to extend this policy 
beyond four years due to COVID-19, and to extend the policy until the 
intended goals of the policy are reached. We appreciate commenters' 
suggestions on how we might evaluate the effectiveness of the policy 
and may consider those suggestions in future rulemaking.
    Comment: Many commenters supported increasing the wage index values 
of low-wage hospitals, but urged CMS to do so in a non-budget-neutral

[[Page 49007]]

manner. Commenters stated that implementing the policy with a budget 
neutrality adjustment merely shifts funds from one group to another. 
Commenters urged CMS to consider wage index reforms that lift low wage 
hospitals' wage indexes without reducing the standardized operating 
rate for all hospitals, which commenters indicated already receive 
Medicare reimbursement at rates that are less than the actual cost of 
care. A commenter stated that for hospitals between the 22nd and 25th 
percentile, the reduction due to the budget neutrality adjustment is 
greater than the benefit received from the quartile adjustment. This 
commenter suggested holding hospitals under the 25th percentile 
harmless by slightly reducing the labor-related share for those 
hospitals that have a wage index greater than 1, or via a graduated 
reduction to the standardized rate based on wage index percentile. 
Other alternative methodologies and data suggested by commenters 
included: reducing the wage indexes of hospitals with wage index values 
above the 75th percentile through a budget neutrality adjustment; 
verifying local labor prices with wage data audits; working with 
Congress to create a new designated pool of funding; working with 
Congress to minimize wage index cliffs; shortening the lag in hospital 
wage data used to construct the wage index; and setting a national wage 
index floor of 1.000.
    Response: We disagree with the commenters that the low wage index 
hospital policy should be implemented in a non-budget neutral manner. 
As we stated in response to similar comments in the FY 2020 IPPS/LTCH 
PPS final rule (84 FR 42331 and 42332) and the FY 2022 IPPS/LTCH PPS 
final rule (86 FR 45180), under section 1886(d)(3)(E) of the Act, the 
wage index adjustment is required to be implemented in a budget neutral 
manner. However, even if the wage index were not required to be budget 
neutral under section 1886(d)(3)(E) of the Act, we would consider it 
inappropriate to use the wage index to increase or decrease overall 
IPPS spending. As we stated in the FY 2020 IPPS/LTCH PPS final rule (84 
FR 42331), the wage index is not a policy tool but rather a technical 
adjustment designed to be a relative measure of the wages and wage-
related costs of subsection (d) hospitals. As a result, as we explained 
in the FY 2020 IPPS/LTCH PPS final rule, if it were determined that 
section 1886(d)(3)(E) of the Act does not require the wage index to be 
budget neutral, we invoke our authority at section 1886(d)(5)(I) of the 
Act in support of such a budget neutrality adjustment.
    With regard to the commenter's assertion about a possible reduction 
to overall payment if the amount of benefit received from the wage 
index boost is less than the reduction to the standardized amount, we 
believe we have applied both the quartile policy and the budget 
neutrality policy appropriately, as we explained in response to 
comments in the FY 2022 IPPS/LTCH PPS final rule (86 FR 45180). The 
quartile adjustment is applied to the wage index, which resulted in an 
increase to the wage index for hospitals below the 25th percentile. The 
budget neutrality adjustment is applied to the standardized amount in 
order to ensure that the low wage index hospital policy is implemented 
in a budget neutral manner. Thus, consistent with our current 
methodology for implementing wage index budget neutrality under section 
1886(d)(3)(E) of the Act and with how we implemented budget neutrality 
for the low wage index hospital policy in FY 2020, we believe it is 
appropriate to continue to apply a budget neutrality adjustment to the 
national standardized amount for all hospitals so that the low wage 
index hospital policy is implemented in a budget neutral manner for FY 
2023.
    We appreciate the commenters' range of suggested alternatives. 
Because we did not propose alternatives with regard to the low wage 
index hospital policy, we consider these comments to be outside the 
scope of the FY 2023 IPPS/LTCH PPS proposed rule. We are not addressing 
them in this final rule but may consider them in future rulemaking.
    Comment: Several commenters opposed the low wage index hospital 
policy, stating that it is inappropriately redistributive, ineffective, 
and outside the agency's statutory authority under section 
1886(d)(3)(E) of the Act. Specifically, a commenter stated that 
although the policy is intended to help rural hospitals, rural 
hospitals in certain states do not benefit from this policy. 
Furthermore, the commenter stated that the policy undermines the intent 
of the wage index by not recognizing real differences in labor costs.
    Response: In response to comments opposing the low wage index 
hospital policy, we believe we addressed the stated concerns in our 
responses to comments when we first finalized the policy and the 
related budget neutrality adjustment in the FY 2020 IPPS/LTCH PPS final 
rule (84 FR 42325 through 42332). Concerning the policy's 
redistributive effect, we refer readers to our response to the comments 
above about budget neutrality. With regard to the policy's 
effectiveness, we believe the comments in support of the policy, 
specifically comments from relatively low-wage hospitals stating that 
the increased payments under the policy have allowed them to raise 
compensation for their workers, indicate that many low wage hospitals 
are benefiting from this policy. Furthermore, we stated in the FY 2020 
IPPS/LTCH PPS final rule (84 FR 42326 through 42328) our intention that 
this policy will be effective for at least 4 years, until the policy's 
effects could be reflected in the wage index data. In response to the 
comment stating that although the policy is intended to help rural 
hospitals, rural hospitals in certain states do not benefit from this 
policy, we refer readers to our response to a similar comment in the FY 
2020 IPPS/LTCH PPS final rule (84 FR 42328) regarding the policy's 
effect on rural hospitals.
    In response to comments stating the policy exceeds CMS's statutory 
authority, we refer the commenters to our prior discussion of the 
authority for the policy in the FY 2020 IPPS/LTCH PPS final rule (84 FR 
42326 through 42332).
    In response to the commenter who asserted that the low wage index 
hospital policy does not recognize real differences in labor costs, we 
continue to believe, for the reasons stated in the FY 2020 IPPS/LTCH 
PPS final rule (84 FR 42327-42328), that by preserving the rank order 
in wage index values, our policy continues to reflect meaningful 
distinctions between the employee compensation costs faced by hospitals 
in different geographic areas. Thus, under the low wage index hospital 
policy, we believe the wage index for low wage index hospitals 
appropriately reflects the relative hospital wage level in those areas 
compared to the national average hospital wage level.
    Comment: Many commenters noted that the low wage index hospital 
policy is currently the subject of pending litigation in Bridgeport. A 
few commenters urged CMS not to finalize the policy for FY 2023, or to 
wait until a final court decision is reached. One such commenter 
suggested CMS should eliminate the budget neutrality adjustments for 
FYs 2020, 2021, and 2022 in light of Bridgeport. Many commenters urged 
CMS to appeal the district court's decision in Bridgeport. These 
commenters stated that the consequences of halting the policy would be 
dire, and that CMS has broad authority under section 1886(d)(3)(E) to 
make policy adjustments, such as the

[[Page 49008]]

imputed floor policy implemented in 2005 that was implemented by CMS as 
a policy measure to address concerns from hospitals in all-urban 
states. These commenters further stated that this step towards 
achieving health equity is justified, and that CMS implemented the low 
wage index hospital policy via notice-and-comment rulemaking.
    Response: We appreciate the commenters' input. As we stated in the 
proposed rule, the FY 2020 low wage index hospital policy and the 
related budget neutrality adjustment are the subject of pending 
litigation, including in Bridgeport. As Bridgeport is pending 
litigation, we are unable to provide further information at this time. 
We disagree with the district court's conclusion that the Social 
Security Act does not authorize the Secretary to adopt the low wage 
index hospital policy, and we note that its decision remains subject to 
potential appeal. We also note that plaintiffs in Bridgeport only 
challenged the low wage index hospital and associated budget neutrality 
adjustment policies for FY 2020.
    After consideration of the comments we received, and for the 
reasons stated above and in the proposed rule, we are finalizing as 
proposed to continue the low wage index hospital policy and the related 
budget neutrality adjustment for FY 2023.

H. FY 2023 Wage Index Tables

    In the FY 2016 IPPS/LTCH PPS final rule (80 FR 49498 and 49807 
through 49808), we finalized a proposal to streamline and consolidate 
the wage index tables associated with the IPPS proposed and final rules 
for FY 2016 and subsequent fiscal years. Effective beginning FY 2016, 
with the exception of Table 4E, we streamlined and consolidated 11 
tables (Tables 2, 3A, 3B, 4A, 4B, 4C, 4D, 4F, 4J, 9A, and 9C) into 2 
tables (Tables 2 and 3). In this FY 2023 IPPS/LTCH PPS final rule, as 
provided beginning with the FY 2021 IPPS/LTCH PPS final rule, we have 
included Table 4A which is titled ``List of Counties Eligible for the 
Out-Migration Adjustment under Section 1886(d)(13) of the Act'' and 
Table 4B titled ``Counties redesignated under section 1886(d)(8)(B) of 
the Act (Lugar Counties).'' We refer readers to section VI. of the 
Addendum to this final rule for a discussion of the wage index tables 
for FY 2023.

I. Revisions to the Wage Index Based on Hospital Redesignations and 
Reclassifications

1. General Policies and Effects of Reclassification and Redesignation
    Under section 1886(d)(10) of the Act, the Medicare Geographic 
Classification Review Board (MGCRB) considers applications by hospitals 
for geographic reclassification for purposes of payment under the IPPS. 
Hospitals must apply to the MGCRB to reclassify not later than 13 
months prior to the start of the fiscal year for which reclassification 
is sought (usually by September 1). Generally, hospitals must be 
proximate to the labor market area to which they are seeking 
reclassification and must demonstrate characteristics similar to 
hospitals located in that area. The MGCRB issues its decisions by the 
end of February for reclassifications that become effective for the 
following fiscal year (beginning October 1). The regulations applicable 
to reclassifications by the MGCRB are located in 42 CFR 412.230 through 
412.280. (We refer readers to a discussion in the FY 2002 IPPS final 
rule (66 FR 39874 and 39875) regarding how the MGCRB defines mileage 
for purposes of the proximity requirements.) The general policies for 
reclassifications and redesignations and the policies for the effects 
of hospitals' reclassifications and redesignations on the wage index 
are discussed in the FY 2012 IPPS/LTCH PPS final rule for the FY 2012 
final wage index (76 FR 51595 and 51596). We note that rural hospitals 
reclassifying under the MGCRB to another State's rural area are not 
eligible for the rural floor, because the rural floor may apply only to 
urban, not rural, hospitals.
    In addition, in the FY 2012 IPPS/LTCH PPS final rule, we discussed 
the effects on the wage index of urban hospitals reclassifying to rural 
areas under 42 CFR 412.103. In the FY 2020 IPPS/LTCH PPS final rule (84 
FR 42332 through 42336), we finalized a policy to exclude the wage data 
of urban hospitals reclassifying to rural areas under 42 CFR 412.103 
from the calculation of the rural floor. In section III.G.1 of this 
final rule, for FY 2023 and subsequent years, we are finalizing a 
policy that calculates the rural floor as it was calculated before FY 
2020. Hospitals that are geographically located in States without any 
rural areas are ineligible to apply for rural reclassification in 
accordance with the provisions of 42 CFR 412.103.
    On April 21, 2016, we published an interim final rule with comment 
period (IFC) in the Federal Register (81 FR 23428 through 23438) that 
included provisions amending our regulations to allow hospitals 
nationwide to have simultaneous Sec.  412.103 and MGCRB 
reclassifications. For reclassifications effective beginning FY 2018, a 
hospital may acquire rural status under Sec.  412.103 and subsequently 
apply for a reclassification under the MGCRB using distance and average 
hourly wage criteria designated for rural hospitals. In addition, we 
provided that a hospital that has an active MGCRB reclassification and 
is then approved for redesignation under Sec.  412.103 will not lose 
its MGCRB reclassification; such a hospital receives a reclassified 
urban wage index during the years of its active MGCRB reclassification 
and is still considered rural under section 1886(d) of the Act and for 
other purposes.
    We discussed that when there is both a Sec.  412.103 redesignation 
and an MGCRB reclassification, the MGCRB reclassification controls for 
wage index calculation and payment purposes. We exclude hospitals with 
Sec.  412.103 redesignations from the calculation of the reclassified 
rural wage index if they also have an active MGCRB reclassification to 
another area. That is, if an application for urban reclassification 
through the MGCRB is approved, and is not withdrawn or terminated by 
the hospital within the established timelines, we consider the 
hospital's geographic CBSA and the urban CBSA to which the hospital is 
reclassified under the MGCRB for the wage index calculation. We refer 
readers to the April 21, 2016 IFC (81 FR 23428 through 23438) and the 
FY 2017 IPPS/LTCH PPS final rule (81 FR 56922 through 56930), in which 
we finalized the April 21, 2016 IFC, for a full discussion of the 
effect of simultaneous reclassifications under both the Sec.  412.103 
and the MGCRB processes on wage index calculations. For a discussion on 
the effects of reclassifications under Sec.  412.103 on the rural area 
wage index and the calculation of the rural floor for FY 2020 through 
FY 2022, we refer readers to the FY 2020 IPPS/LTCH PPS final rule (84 
FR 42332 through 42336). For a discussion of the effects of 
reclassifications under Sec.  412.103 on the rural area wage index and 
the calculation of the rural floor for FY 2023 and subsequent years, we 
refer readers to section III.G.1 of this final rule.
    On May 10, 2021, we published an IFC in the Federal Register (86 FR 
24735 through 24739) that included provisions amending our regulations 
to allow hospitals with a rural redesignation to reclassify through the 
MGCRB using the rural reclassified area as the geographic area in which 
the

[[Page 49009]]

hospital is located. We revised our regulation so that the redesignated 
rural area, and not the hospital's geographic urban area, is considered 
the area a Sec.  412.103 hospital is located in for purposes of meeting 
MGCRB reclassification criteria, including the average hourly wage 
comparisons required by Sec.  412.230(a)(5)(i) and (d)(1)(iii)(C). 
Similarly, we revised the regulations to consider the redesignated 
rural area, and not the geographic urban area, as the area a Sec.  
412.103 hospital is located in for the prohibition at Sec.  
412.230(a)(5)(i) on reclassifying to an area with a pre-reclassified 
average hourly wage lower than the prereclassified average hourly wage 
for the area in which the hospital is located. Effective for 
reclassification applications due to the MGCRB for reclassification 
beginning in FY 2023, a Sec.  412.103 hospital could apply for a 
reclassification under the MGCRB using the State's rural area as the 
area in which the hospital is located. We refer readers to the May 10, 
2021 IFC (86 FR 24735 through 24739) and the FY 2022 IPPS/LTCH PPS 
final rule (86 FR 45187 through 45190), in which we finalized the May 
10, 2021 IFC, for a full discussion of these policies.
2. MGCRB Reclassification and Redesignation Issues for FY 2023
a. FY 2023 Reclassification Application Requirements and Approvals
    As previously stated, under section 1886(d)(10) of the Act, the 
MGCRB considers applications by hospitals for geographic 
reclassification for purposes of payment under the IPPS. The specific 
procedures and rules that apply to the geographic reclassification 
process are outlined in regulations under 42 CFR 412.230 through 
412.280. At the time this final rule was drafted, the MGCRB had 
completed its review of FY 2023 reclassification requests. Based on 
such reviews, there are 383 hospitals approved for wage index 
reclassifications by the MGCRB starting in FY 2023. Because MGCRB wage 
index reclassifications are effective for 3 years, for FY 2023, 
hospitals reclassified beginning in FY 2021 or FY 2022 are eligible to 
continue to be reclassified to a particular labor market area based on 
such prior reclassifications for the remainder of their 3-year period. 
There were 311 hospitals approved for wage index reclassifications in 
FY 2021 that will continue for FY 2023, and 315 hospitals approved for 
wage index reclassifications in FY 2022 that will continue for FY 2023. 
Of all the hospitals approved for reclassification for FY 2021, FY 2022 
and FY 2023, based upon the review at the time of the final rule, 1,009 
hospitals are in a MGCRB reclassification status for FY 2023 (with 166 
of these hospitals reclassified back to their geographic location).
    Under the regulations at 42 CFR 412.273, hospitals that have been 
reclassified by the MGCRB are permitted to withdraw their applications 
if the request for withdrawal is received by the MGCRB any time before 
the MGCRB issues a decision on the application, or after the MGCRB 
issues a decision, provided the request for withdrawal is received by 
the MGCRB within 45 days of the date that CMS' annual notice of 
proposed rulemaking is issued in the Federal Register concerning 
changes to the inpatient hospital prospective payment system and 
proposed payment rates for the fiscal year for which the application 
has been filed. For information about withdrawing, terminating, or 
canceling a previous withdrawal or termination of a 3-year 
reclassification for wage index purposes, we refer readers to Sec.  
412.273, as well as the FY 2002 IPPS final rule (66 FR 39887 through 
39888) and the FY 2003 IPPS final rule (67 FR 50065 through 50066). 
Additional discussion on withdrawals and terminations, and 
clarifications regarding reinstating reclassifications and ``fallback'' 
reclassifications were included in the FY 2008 IPPS final rule (72 FR 
47333) and the FY 2018 IPPS/LTCH PPS final rule (82 FR 38148 through 
38150).
    We note that in the FY 2021 IPPS/LTCH final rule (85 FR 58771 
through 58778), CMS finalized an assignment policy for hospitals 
reclassified to CBSAs from which one or more counties moved to a new or 
different urban CBSA under the revised OMB delineations based on OMB 
Bulletin 18-04. We provided a table in that rule (85 FR 58777 and 
58778) which described the assigned CBSA for all the MGCRB cases 
subject to this policy. For such reclassifications that continue to be 
active or are reinstated for FY 2023, the CBSAs assigned in the FY 2021 
IPPS/LTCH final rule continue to be in effect.
    Applications for FY 2024 reclassifications are due to the MGCRB by 
September 1, 2022. We note that this is also the deadline for canceling 
a previous wage index reclassification withdrawal or termination under 
42 CFR 412.273(d). Applications and other information about MGCRB 
reclassifications may be obtained beginning in mid-July 2022, via the 
internet on the CMS website at https://www.cms.gov/Regulations-andGuidance/Review-Boards/MGCRB/, or by calling the MGCRB at 
(410) 786-1174. This collection of information was previously approved 
under OMB Control Number 0938-0573 which expired on January 31, 2021. A 
reinstatement of this PRA package is currently being developed. The 
public will have an opportunity to review and submit comments regarding 
the reinstatement of this PRA package through a public notice and 
comment period separate from this rulemaking.
    Comment: A commenter requested that in light of potential actions 
taken by CMS in response to the Bridgeport or Citrus decisions, CMS 
should allow an additional 45-day withdrawal/termination period after 
the publication of this final rule to allow hospitals to select the 
wage index that would apply for FY 2023. As an alternative, citing a FY 
2005 policy exception, the commenter suggested that CMS can assign 
hospitals to the geographic area that is most advantageous to them.
    Response: As previously discussed, in section III.G.4 of this final 
rule, CMS is finalizing as proposed to continue the low wage index 
hospital policy and the related budget neutrality adjustment for FY 
2023 and is not implementing any changes at this time due to 
Bridgeport. As previously discussed, in section III.G.1. of the 
preamble of this final rule, we are modifying for FY 2023 and 
subsequent years the calculation of the rural floor and ``the wage 
index for rural areas in the State in which the county is located'' as 
referred to in section 1886(d)(8)(C)(iii) of the Act, based on the 
Citrus decision. Presumably, the commenter is requesting that we 
provide an additional 45 days for hospitals with MGCRB 
reclassifications to submit MGCRB withdrawal or termination requests, 
or rescind such a request that was already approved. As previously 
discussed in the FY 2015 IPPS/LTCH PPS final rule (79 FR 49973) and the 
FY 2021 IPPS/LTCH PPS final rule (85 FR 58769--58770), we maintain that 
information provided in the proposed rule constitutes the best 
available data to assist hospitals in making reclassification 
decisions. In the proposed rule, we acknowledged the district court 
decisions in Bridgeport and Citrus, and we stated that we may decide to 
take a different approach to our policies in the final rule, depending 
on public comments or developments in the court proceedings. We believe 
hospitals had the ability to make informed decisions weighing potential 
outcomes based on the proposed rule.
    In particular, we note that the state rural wage index published in 
Table 3 of the FY 2023 IPPS/LTCH PPS proposed rule would be the rural 
floor if we included 412.103 hospitals in the

[[Page 49010]]

calculation of the rural floor. Therefore, information with regard to 
what the rural floor would have been if we modified our policy was 
available in the proposed rule. Further, looking at the states and 
territories in Table 3 of the proposed rule, 40 states/territories in 
the proposed rule had a rural floor that equals the rural wage index 
(which includes Puerto Rico). Four states in the proposed rule are not 
eligible for the rural floor since they are all urban states and 
receive the imputed floor instead. Using data from Table 3 of the 
proposed rule, this leaves the 8 states listed in the table that 
follows with a difference between the state rural floor and state rural 
wage index. As demonstrated in the table that follows, hospitals should 
be able to make these MGCRB decisions based on the data in the proposed 
rule as usual as an overwhelming majority of the states/territories 
show no difference between the state rural wage index and state rural 
floor, and those that do show a difference show a minimal variance. 
Therefore, we do not believe the data justifies an additional 45 days 
for hospitals with MGCRB reclassifications to submit MGCRB withdrawal 
or termination requests or to rescind such a request that was already 
approved.
[GRAPHIC] [TIFF OMITTED] TR10AU22.118

    In addition, as we discussed in the FY 2021 IPPS/LTCH PPS final 
rule (85 FR 58769--58770), section 1886(d)(8)(D) of the Act requires 
the Secretary to adjust the standardized amounts to ensure that the 
application of certain provisions of the statute, including a decision 
of the MGCRB or the Secretary under section 1886(d)(10), do not result 
in aggregate payments under section 1886 that are greater or less than 
those that would otherwise be made. If hospitals were to withdraw or 
terminate reclassification statuses after the publication of the final 
rule, as the commenter suggested CMS permit, any resulting changes in 
the wage index would not have been taken into account when calculating 
the IPPS standardized amounts in the final rule in accordance with the 
statutory budget neutrality requirement. Therefore, it is necessary 
that the values published in the final rule represent the final wage 
index values reflective of reclassification decisions.
    With regard to the FY 2005 exception referenced by the commenter, 
CMS did provide an exception to the withdrawal and termination deadline 
due to the implementation of special reclassifications under section 
508 of Pub. L. 108-173 and general concerns regarding the 
implementation of revised OMB labor market delineations based on the 
2000 decennial census (69 FR 49060 and 49061). CMS inferred certain 
wage index selections for section 508 hospitals where the preferred 
option (depending on the finalization of proposed wage index policies) 
was clear and obvious, and hospitals were granted a 30 day window after 
the final rule to withdraw their reclassification request or to rescind 
their previous withdrawal or termination request. With the relatively 
few number of reclassified hospitals in FY 2005, it was plausible for 
CMS to impute or infer the optimal reclassification status in certain 
limited circumstances, and potentially allow for an additional window 
of opportunity for hospitals to review their options to withdraw or 
terminate MGCRB status. However, when factoring the large number of 
currently reclassified hospitals and the iterative and compounding 
impacts of various forms of wage index reclassification policy, various 
wage index floor policies, and other adjustment policies; it does not 
support the premise that additional opportunities to modify MGCRB 
reclassification status would be feasible or would result in more 
accurate or consistent results.
    Comment: A commenter noted that the MGCRB issued determinations for 
FY 2023 on January 24, 2022. The commenter stated that this was earlier 
than in the past, when the MGCRB typically issued determinations mid-
February, to meet the statutory requirement for decisions to be issued 
by the end of February. The commenter requested that CMS limit the 
MGCRB from issuing decisions prior to the first week of February to 
allow hospitals ample time to submit documentation of rural 
reclassification, SCH and RRC status to the Board or to submit a 
request to withdraw an application based on review of the January PUF. 
The commenter stated that without a more definitive timeline, hospitals 
face uncertainty if their documentation will be accepted by the MGCRB 
and could be adversely affected by an early decision being issued by 
the Board.
    Response: We disagree with the commenter that hospitals are 
disadvantaged by earlier issuance of MGCRB decisions. First, we believe 
hospitals should submit applications complete with supporting 
documentation at the time MGCRB applications are due. Hospitals taking 
advantage of the MGCRB's practice of accepting supporting documentation 
to supplement applications until the date of the MGCRB's review are 
aware that the review is not held on the same date annually. 
Furthermore, rural reclassification may be obtained at any time, and 
hospitals seeking benefits of rural status for MGCRB reclassification

[[Page 49011]]

should plan accordingly. Finally, we note that hospitals dissatisfied 
with the MGCRB's decision may request the Administrator's review under 
Sec.  412.278. With regard to hospitals requesting to withdraw a 
pending reclassification application following review of the January 
PUF, hospitals may withdraw a reclassification after the MGCRB has 
issued decisions, within 45 days of the date that CMS' annual notice of 
proposed rulemaking is issued in the Federal Register, per the 
regulations at Sec.  412.273. Therefore, we do not believe hospitals 
are disadvantaged by the earlier timing of MGCRB decisions because they 
can submit supporting documentation timely, obtain a rural 
reclassification in advance, request the Administrator's review of an 
MGCRB decision, and withdraw an unwanted reclassification.
    Comment: A commenter requested that CMS change the special rule for 
RRCs applying for reclassification at the MGCRB to afford hospitals the 
same reclassification opportunities as similar hospitals competing in 
the same labor market area. The commenter specifically suggested that 
CMS revise its regulations to state that if a hospital is located 
within five miles of another acute care hospital in the same CBSA with 
a lower average hourly wage, the hospital may reclassify to the same 
area as the lower wage hospital, if the applicable average hourly wage 
requirements are met, rather than to the area that is closest to the 
hospital.
    Response: We appreciate the commenter's input. We did not propose 
any changes to the regulation referenced by the commenter, Sec.  
412.230(a)(3), the special rules for sole community hospitals and rural 
referral centers. We are not finalizing any changes to the special rule 
for RRCs applying for reclassification at the MGCRB in this final rule.
b. Clarification of Method for Submission Under Sec.  412.273
    The regulations at 42 CFR 412.273 set forth the procedures for 
withdrawing an MGCRB application, terminating an approved 3-year 
reclassification, or canceling a previous withdrawal or termination 
(also referred to as a reinstatement). The timing of such requests is 
specified at Sec.  412.273(c) for terminations and withdrawals and at 
paragraph (d)(2) for canceling a previous withdrawal or termination. 
However, the method of submission is not clearly specified in the 
regulations, other than the requirement that a request to cancel a 
previous withdrawal or termination (a reinstatement), or to withdraw an 
application or terminate an approved reclassification, be in writing 
according to Sec.  412.273(d)(2) and (e). It has come to our attention 
that this may be a source of confusion for hospital representatives 
seeking to submit such requests. It is possible that hospital 
representatives would attempt to send such requests to the MGCRB via 
mail, email, or fax, rather than in the manner that the MGCRB can most 
efficiently track and process.
    Beginning with applications from hospitals to reclassify for FY 
2020, the MGCRB requires applications, supporting documents, and 
subsequent correspondence to be filed electronically through the MGCRB 
module of the Office of Hearings Case and Document Management System 
(``OH CDMS''). The MGCRB issues all of its notices and decisions via 
email and these documents are accessible electronically through OH 
CDMS. Registration instructions and the system user manual are 
available at https://www.cms.gov/Regulations-and-Guidance/ReviewBoards/MGCRB/Electronic-Filing.html.
    In the FY 2020 IPPS/LTCH PPS final rule (84 FR 42313), we revised 
the regulations at Sec.  412.256(a)(1) to require applications for 
reclassification to be submitted to the MGCRB according to the method 
prescribed by the MGCRB. However, the regulations at Sec.  412.273 for 
withdrawals, terminations, or cancelations of a previous withdrawal or 
termination (reinstatement) do not similarly specify a required manner 
of submission. Therefore, to eliminate potential confusion about how to 
submit withdrawal, termination, or cancelation (reinstatement) 
requests, we proposed to align the regulations at Sec.  412.273 for 
withdrawal, termination, or cancelation (reinstatement) requests with 
the regulations at Sec.  412.256 for new applications by specifying 
that withdrawal, termination, or cancelation (reinstatement) requests 
also must be submitted to the MGCRB according to the method prescribed 
by the MGCRB.
    Specifically, we proposed to revise Sec.  412.273(d)(2) for timing 
and process of cancellation requests and Sec.  412.273(e) for 
withdrawal and termination requests. We proposed to revise Sec.  
412.273(d)(2) to state that cancellation requests must be submitted in 
writing to the MGCRB according to the method prescribed by the MGCRB no 
later than the deadline for submitting reclassification applications 
for the following fiscal year, as specified in Sec.  412.256(a)(2). We 
also proposed to revise Sec.  412.273(e) by adding that requests to 
withdraw an application or terminate an approved reclassification must 
be submitted in writing to the MGCRB according to the method prescribed 
by the MGCRB. We stated that we believe these proposed revisions to the 
regulations would eliminate potential confusion; align our policy for 
withdrawals, terminations, and cancelations (reinstatements) with our 
policy for applications; and ensure requests are submitted to the MGCRB 
through the method for submission that they can most efficiently 
process.
    Comment: A commenter supported the proposed changes to Sec.  
412.273. The commenter stated that these changes will eliminate 
potential confusion, align withdrawals, terminations, and cancellations 
with the MGCRB application process, and ensure submissions can be 
processed more efficiently by the MGCRB.
    Response: We thank the commenter for supporting the proposed 
changes. After consideration of the public comment we received, we are 
finalizing as proposed without modification our changes to the 
regulations at Sec.  412.273(d)(2) and (e).
3. Redesignations Under Section 1886(d)(8)(B) of the Act (Lugar Status 
Determinations)
    In the FY 2012 IPPS/LTCH PPS final rule (76 FR 51599 through 
51600), we adopted the policy that, beginning with FY 2012, an eligible 
hospital that waives its Lugar status in order to receive the out-
migration adjustment has effectively waived its deemed urban status 
and, thus, is rural for all purposes under the IPPS effective for the 
fiscal year in which the hospital receives the outmigration adjustment. 
In addition, in that rule, we adopted a minor procedural change that 
would allow a Lugar hospital that qualifies for and accepts the out-
migration adjustment (through written notification to CMS within 45 
days from the publication of the proposed rule) to waive its urban 
status for the full 3-year period for which its out-migration 
adjustment is effective. By doing so, such a Lugar hospital would no 
longer be required during the second and third years of eligibility for 
the out-migration adjustment to advise us annually that it prefers to 
continue being treated as rural and receive the out-migration 
adjustment. In the FY 2017 IPPS/LTCH PPS final rule (81 FR 56930), we 
further clarified that if a hospital wishes to reinstate its urban 
status for any fiscal year within this 3-year period, it must send a 
request to CMS within 45 days of publication of the proposed rule for 
that particular fiscal year. We indicated that such reinstatement 
requests may be sent electronically to [email protected]. In the FY 
2018 IPPS/LTCH

[[Page 49012]]

PPS final rule (82 FR 38147 through 38148), we finalized a policy 
revision to require a Lugar hospital that qualifies for and accepts the 
out-migration adjustment, or that no longer wishes to accept the out-
migration adjustment and instead elects to return to its deemed urban 
status, to notify CMS within 45 days from the date of public display of 
the proposed rule at the Office of the Federal Register. These revised 
notification timeframes were effective beginning October 1, 2017. In 
addition, in the FY 2018 IPPS/LTCH PPS final rule (82 FR 38148), we 
clarified that both requests to waive and to reinstate ``Lugar'' status 
may be sent to [email protected]. To ensure proper accounting, we 
requested that hospitals include their CCN, and either ``waive Lugar'' 
or ``reinstate Lugar'', in the subject line of these requests.
    In the FY 2020 IPPS/LTCH PPS final rule (84 FR 42314 and 42315), we 
clarified that in circumstances where an eligible hospital elects to 
receive the outmigration adjustment within 45 days of the public 
display date of the proposed rule at the Office of the Federal Register 
in lieu of its Lugar wage index reclassification, and the county in 
which the hospital is located would no longer qualify for an out-
migration adjustment when the final rule (or a subsequent correction 
notice) wage index calculations are completed, the hospital's request 
to accept the outmigration adjustment would be denied, and the hospital 
would be automatically assigned to its deemed urban status under 
section 1886(d)(8)(B) of the Act. We stated that final rule wage index 
values would be recalculated to reflect this reclassification, and in 
some instances, after taking into account this reclassification, the 
out-migration adjustment for the county in question could be restored 
in the final rule. However, as the hospital is assigned a Lugar 
reclassification under section 1886(d)(8)(B) of the Act, it would be 
ineligible to receive the county outmigration adjustment under section 
1886(d)(13)(G) of the Act.
    We did not receive any requests to waive or reinstate an eligible 
hospital's deemed urban status under section 1886(d)(8)(B) of the Act. 
We did not receive any public comments on this policy for FY 2023.

J. Out-Migration Adjustment Based on Commuting Patterns of Hospital 
Employees

    In accordance with section 1886(d)(13) of the Act, as added by 
section 505 of Public Law 108-173, beginning with FY 2005, we 
established a process to make adjustments to the hospital wage index 
based on commuting patterns of hospital employees (the ``out-
migration'' adjustment). The process, outlined in the FY 2005 IPPS 
final rule (69 FR 49061), provides for an increase in the wage index 
for hospitals located in certain counties that have a relatively high 
percentage of hospital employees who reside in the county but work in a 
different county (or counties) with a higher wage index.
    Section 1886(d)(13)(B) of the Act requires the Secretary to use 
data the Secretary determines to be appropriate to establish the 
qualifying counties. When the provision of section 1886(d)(13) of the 
Act was implemented for the FY 2005 wage index, we analyzed commuting 
data compiled by the U.S. Census Bureau that were derived from a 
special tabulation of the 2000 Census journey-to-work data for all 
industries (CMS extracted data applicable to hospitals). These data 
were compiled from responses to the ``long-form'' survey, which the 
Census Bureau used at that time and which contained questions on where 
residents in each county worked (69 FR 49062). However, the 2010 Census 
was ``short form'' only; information on where residents in each county 
worked was not collected as part of the 2010 Census. The Census Bureau 
worked with CMS to provide an alternative dataset based on the latest 
available data on where residents in each county worked in 2010, for 
use in developing a new outmigration adjustment based on new commuting 
patterns developed from the 2010 Census data beginning with FY 2016.
    To determine the out-migration adjustments and applicable counties 
for FY 2016, we analyzed commuting data compiled by the Census Bureau 
that were derived from a custom tabulation of the American Community 
Survey (ACS), an official Census Bureau survey, utilizing 2008 through 
2012 (5-year) Microdata. The data were compiled from responses to the 
ACS questions regarding the county where workers reside and the county 
to which workers commute. As we discussed in prior IPPS/LTCH PPS final 
rules, most recently in the FY 2022 IPPS/LTCH PPS final rule (86 FR 
45184), we have applied the same policies, procedures, and computations 
since FY 2012. We proposed to use them again for FY 2023, as we believe 
they continue to be appropriate. We refer readers to the FY 2016 IPPS/
LTCH PPS final rule (80 FR 49500 through 49502) for a full explanation 
of the revised data source.
    For FY 2023, the out-migration adjustment will continue to be based 
on the data derived from the custom tabulation of the ACS utilizing 
2008 through 2012 (5-year) Microdata. For future fiscal years, we may 
consider determining out-migration adjustments based on data from the 
next Census or other available data, as appropriate. For FY 2023, we 
did not propose any changes to the methodology or data source that we 
used for FY 2016 (81 FR 25071). (We refer readers to a full discussion 
of the out-migration adjustment, including rules on deeming hospitals 
reclassified under section 1886(d)(8) or section 1886(d)(10) of the Act 
to have waived the out-migration adjustment, in the FY 2012 IPPS/LTCH 
PPS final rule (76 FR 51601 through 51602).)
    We did not receive any public comments on this proposed policy for 
FY 2023. Therefore, for the reasons set forth in this final rule and in 
the FY 2023 IPPS/LTCH PPS proposed rule, for FY 2023, we are finalizing 
our proposal, without modification, to continue using the same 
policies, procedures, and computations that were used for the FY 2012 
outmigration adjustment and that were applicable for FYs 2016 through 
2022.
    Table 2 associated with this final rule (which is available via the 
internet on the CMS website) includes the out-migration adjustments for 
the FY 2023 wage index. In addition, Table 4A associated with this 
final rule, ``List of Counties Eligible for the Out-Migration 
Adjustment under Section 1886(d)(13) of the Act'' (also available via 
the internet on the CMS website) consists of the following: A list of 
counties that are eligible for the out-migration adjustment for FY 2023 
identified by FIPS county code, the final FY 2023 out-migration 
adjustment, and the number of years the adjustment will be in effect.

K. Reclassification From Urban to Rural Under Section 1886(d)(8)(E) of 
the Act Implemented at 42 CFR 412.103

    Under section 1886(d)(8)(E) of the Act, a qualifying prospective 
payment hospital located in an urban area may apply for rural status 
for payment purposes separate from reclassification through the MGCRB. 
Specifically, section 1886(d)(8)(E) of the Act provides that, not later 
than 60 days after the receipt of an application (in a form and manner 
determined by the Secretary) from a subsection (d) hospital that 
satisfies certain criteria, the Secretary shall treat the hospital as 
being located in the rural area (as defined in paragraph (2)(D)) of the 
State in which the hospital is located. We refer readers

[[Page 49013]]

to the regulations at 42 CFR 412.103 for the general criteria and 
application requirements for a subsection (d) hospital to reclassify 
from urban to rural status in accordance with section 1886(d)(8)(E) of 
the Act. The FY 2012 IPPS/LTCH PPS final rule (76 FR 51595 through 
51596) includes our policies regarding the effect of wage data from 
reclassified or redesignated hospitals. We refer readers to the FY 2020 
IPPS/LTCH PPS final rule (84 FR 42332 through 42336) for a discussion 
of our policy to calculate the rural floor without the wage data of 
urban hospitals reclassifying to rural areas under 42 CFR 412.103, and 
to section III.G.1 of this final rule for a discussion of our decision, 
for FY 2023 and subsequent years, to calculate the rural floor as it 
was calculated before FY 2020 by including the wage data of 412.103 
hospitals.
    In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41369 through 
41374), we codified certain policies regarding multicampus hospitals in 
the regulations at 42 CFR 412.92, 412.96, 412.103, and 412.108. We 
stated that reclassifications from urban to rural under 42 CFR 412.103 
apply to the entire hospital (that is, the main campus and its remote 
location(s)). We also stated that a main campus of a hospital cannot 
obtain an SCH, RRC, or MDH status, or rural reclassification under 42 
CFR 412.103, independently or separately from its remote location(s), 
and vice versa. However, we are aware that some urban hospitals operate 
one or more remote location(s) in a State's rural area. In light of 
this scenario, we wish to clarify that rural reclassification under 42 
CFR 412.103 applies to the main campus and any remote location located 
in an urban area. Under section 1886(d)(8)(E) of the Act, rural 
reclassification is available only to a hospital that is located in an 
urban area and satisfies the criteria specified in the statute. Thus, a 
remote location that is located in a rural area would not qualify for 
rural reclassification under section 1886(d)(8)(E) of the Act, as 
implemented under 42 CFR 412.103. We proposed to add 42 CFR 
412.103(a)(8) to clarify that for a multicampus hospital, approved 
rural reclassification status applies to the main campus and any remote 
location located in an urban area, including a main campus or any 
remote location deemed urban under section 1886(d)(8)(B) of the Act.
    We are also aware that CMS has not consistently reflected the 
412.103 rural reclassification status in Table 2 of the annual IPPS/
LTCH PPS rulemaking for certain remote locations of hospitals that are 
located in a different CBSA than the main campus. If a remote location 
of a hospital is located in a different CBSA than the main campus of 
the hospital, it is CMS's longstanding policy to assign that remote 
location a wage index based on its own geographic area in order to 
comply with the statutory requirement to adjust for geographic 
differences in hospital wage levels (section 1886(d)(3)(E) of the Act). 
Hospitals are required to identify and allocate wages and hours based 
on FTEs for remote locations located in different CBSA on Worksheet S-
2, Part I, Lines 165 and 166 of form CMS-2552-10. In calculating wage 
index values, CMS identifies the allocated wage data for these remote 
locations in Table 2 with a ``B'' in the third position of the CCN.
    As discussed previously, for a multicampus hospital, rural 
reclassification under 42 CFR 412.103 applies to the main campus and 
any remote location located in an urban area. The wage index 
implications of this policy are that, barring another form of wage 
index reclassification (for example, MGCRB reclassification), a main 
campus or remote location with approved 412.103 rural reclassification 
status would be assigned the rural wage index of its State. For FY 
2023, we will list the 412.103 rural reclassification status for remote 
locations (a remote location is listed with a ``B'' in the third digit 
of the CCN) in Table 2 of the appendix to the final rule. We note that, 
as of the date this final rule is issued, only one ``B'' location 
(36B020) would be assigned its State's rural wage index in FY 2023 due 
to the Sec.  412.103 rural reclassification status of the main provider 
(360020). This location appears to have ceased inpatient activities, so 
we do not expect a negative financial impact for FY 2023. However, 
hospitals with Sec.  412.103 rural reclassification status and a remote 
location in a different CBSA should evaluate potential wage index 
outcomes for its remote location(s) when withdrawing or terminating 
MGCRB reclassification, or canceling 412.103 rural reclassification 
status. For example, if a hospital with 412.103 rural reclassification 
status withdraws a separate active MGCRB reclassification for a remote 
location, that remote location may be assigned the State's rural wage 
index value, effective for FY 2023.
    Comment: A commenter supported our proposal to clarify that 
approved rural reclassification applies to a main campus and any remote 
locations in an urban area. The commenter stated that this policy 
allows for uniform treatment of all departments and campuses of the 
same hospital.
    Response: We appreciate the commenter's support. Consistent with 
our clarification regarding multicampus hospitals, we are finalizing as 
proposed without modification our addition to the regulations at 42 CFR 
412.103(a)(8) to clarify that for a multicampus hospital, approved 
rural reclassification status applies to the main campus and any remote 
location located in an urban area, including a main campus or any 
remote location deemed urban under section 1886(d)(8)(B) of the Act. 
Table 2 associated with this FY 2023 IPPS/LTCH PPS final rule will 
reflect the 412.103 rural reclassification status for remote locations 
of hospitals that are located in a different CBSA than the main campus.

L. Process for Requests for Wage Index Data Corrections

1. Process for Hospitals To Request Wage Index Data Corrections
    The preliminary, unaudited Worksheet S-3 wage data files and the CY 
2019 occupational mix data files for the proposed FY 2023 wage index 
were made available on May 24, 2021 through the internet on the CMS 
website at https://www.cms.gov/medicaremedicare-fee-service-paymentacuteinpatientppswage-index-files/fy2023-wage-index-home-page.
    On January 28, 2022, we posted a public use file (PUF) at https://www.cms.gov/medicaremedicare-fee-service-paymentacuteinpatientppswage-index-files/fy2023-wage-index-home-page containing FY 2023 wage index 
data available as of January 28, 2022. This PUF contains a tab with the 
Worksheet S-3 wage data (which includes Worksheet S-3, Parts II and III 
wage data from cost reporting periods beginning on or after October 1, 
2018 through September 30, 2019; that is, FY 2019 wage data), a tab 
with the occupational mix data (which includes data from the CY 2019 
occupational mix survey, Form CMS-10079), a tab containing the 
Worksheet S-3 wage data of hospitals deleted from the January 28, 2022 
wage data PUF, and a tab containing the CY 2019 occupational mix data 
of the hospitals deleted from the January 28, 2022 occupational mix 
PUF. In a memorandum dated January 20, 2022, we instructed all MACs to 
inform the IPPS hospitals that they service of the availability of the 
January 28, 2022 wage index data PUFs, and the process and timeframe 
for requesting revisions in accordance with the FY 2023 Hospital Wage 
Index Development Time Table available at https://www.cms.gov/files/document/fy2023-wi-time-table.pdf.

[[Page 49014]]

    In the interest of meeting the data needs of the public, beginning 
with the proposed FY 2009 wage index, we post an additional PUF on the 
CMS website that reflects the actual data that are used in computing 
the proposed wage index. The release of this file does not alter the 
current wage index process or schedule. We notify the hospital 
community of the availability of these data as we do with the current 
public use wage data files through our Hospital Open Door Forum. We 
encourage hospitals to sign up for automatic notifications of 
information about hospital issues and about the dates of the Hospital 
Open Door Forums at the CMS website at https://www.cms.gov/Outreach-and-Education/Outreach/OpenDoorForums.
    In a memorandum dated May 11, 2021, we instructed all MACs to 
inform the IPPS hospitals that they service of the availability of the 
preliminary wage index data files and the CY 2019 occupational mix 
survey data files posted on May 24, 2021, and the process and timeframe 
for requesting revisions.
    If a hospital wished to request a change to its data as shown in 
the May 24, 2021, preliminary wage data files and occupational mix data 
files, the hospital had to submit corrections along with complete, 
detailed supporting documentation to its MAC so that the MAC received 
them by September 2, 2021. Hospitals were notified of these deadlines 
and of all other deadlines and requirements, including the requirement 
to review and verify their data as posted in the preliminary wage index 
data files on the internet, through the letters sent to them by their 
MACs. We note, CMS issued a waiver due to Hurricane Ida and modified 
the September 2, 2021, deadline specified in the FY 2023 Hospital Wage 
Index Development Time Table for certain hospitals. Specifically, CMS 
granted an extension until October 4, 2021, for hospitals in the States 
of Louisiana and Mississippi to request revisions to and provide 
documentation for their FY 2019 Worksheet S-3 wage data and CY 2019 
occupational mix data as included in the May 24, 2021 preliminary 
Public Use Files (PUFs), respectively. According to the waiver, MACs 
must receive the revision requests and supporting documentation by 
October 4, 2021. If hospitals encountered difficulty meeting the 
extended deadline, hospitals were to communicate their concerns to CMS 
via their MAC for CMS to consider an additional extension if CMS 
determined it was warranted. Details regarding this waiver are 
available on the CMS website at https://www.cms.gov/current-non-covid-emergencies, Additional IPPS Hospital Blanket Waivers (https://www.cms.gov/files/document/hurrican-ida-additional-ipps-hospital-blanket-waivers.pdf). November 15, 2021, was the deadline for MACs to 
complete all desk reviews for hospital wage and occupational mix data 
and transmit revised Worksheet S-3 wage data and occupational mix data 
to CMS.
    November 4, 2021, was the date by when MACs notified State hospital 
associations regarding hospitals that failed to respond to issues 
raised during the desk reviews. Additional revisions made by the MACs 
were transmitted to CMS throughout January 2022. CMS published the wage 
index PUFs that included hospitals' revised wage index data on January 
28, 2022. Hospitals had until February 15, 2022, to submit requests to 
the MACs to correct errors in the January 28, 2022 PUF due to CMS or 
MAC mishandling of the wage index data, or to revise desk review 
adjustments to their wage index data as included in the January 28, 
2022, PUF. Hospitals also were required to submit sufficient 
documentation to support their requests. Hospitals' requests and 
supporting documentation must be received by the MAC by the February 
deadline (that is, by February 15, 2022, for the FY 2023 wage index).
    After reviewing requested changes submitted by hospitals, MACs were 
required to transmit to CMS any additional revisions resulting from the 
hospitals' reconsideration requests by March 18, 2022. Under our 
current policy as adopted in the FY 2018 IPPS/LTCH PPS final rule (82 
FR 38153), the deadline for a hospital to request CMS intervention in 
cases where a hospital disagreed with a MAC's handling of wage data on 
any basis (including a policy, factual, or other dispute) was April 1, 
2022. Data that were incorrect in the preliminary or January 28, 2022 
wage index data PUFs, but for which no correction request was received 
by the February 15, 2022 deadline, are not considered for correction at 
this stage. In addition, April 1, 2022, was the deadline for hospitals 
to dispute data corrections made by CMS of which the hospital was 
notified after the January 28, 2022, PUF and at least 14 calendar days 
prior to April 1, 2022 (that is, March 18, 2022), that do not arise 
from a hospital's request for revisions. The hospital's request and 
supporting documentation must be received by CMS (and a copy received 
by the MAC) by the April deadline (that is, by April 1, 2022, for the 
FY 2023 wage index). We refer readers to the FY 2023 Hospital Wage 
Index Development Time Table for complete details.
    Hospitals were given the opportunity to examine Table 2 associated 
with the proposed rule, which is listed in section VI. of the Addendum 
to the proposed rule and available via the internet on the CMS website 
at https://www.cms.gov/medicare/acute-inpatient-pps/fy-2023-ipps-proposed-rule-home-page. Table 2 associated with the proposed rule 
contained each hospital's proposed adjusted average hourly wage used to 
construct the wage index values for the past 3 years, including the 
proposed FY 2023 wage index which was constructed from FY 2019 data. We 
noted in the proposed rule that the proposed hospital average hourly 
wages shown in Table 2 only reflected changes made to a hospital's data 
that were transmitted to CMS by early February 2022.
    We posted the final wage index data PUFs on April 29, 2022 on the 
CMS website at https://www.cms.gov/medicaremedicare-fee-service-paymentacuteinpatientppswage-index-files/fy2023-wage-index-home-page. 
The April 2022 PUFs are made available solely for the limited purpose 
of identifying any potential errors made by CMS or the MAC in the entry 
of the final wage index data that resulted from the correction process 
previously described (the process for disputing revisions submitted to 
CMS by the MACs by March 18, 2022, and the process for disputing data 
corrections made by CMS that did not arise from a hospital's request 
for wage data revisions as discussed earlier).
    After the release of the April 2022 wage index data PUFs, changes 
to the wage and occupational mix data can only be made in those very 
limited situations involving an error by the MAC or CMS that the 
hospital could not have known about before its review of the final wage 
index data files. Specifically, neither the MAC nor CMS will approve 
the following types of requests:
     Requests for wage index data corrections that were 
submitted too late to be included in the data transmitted to CMS by the 
MACs on or before March 18, 2022.
     Requests for correction of errors that were not, but could 
have been, identified during the hospital's review of the January 28, 
2022, wage index PUFs.
     Requests to revisit factual determinations or policy 
interpretations made by the MAC or CMS during the wage index data 
correction process.
    If, after reviewing the April 2022 final wage index data PUFs, a 
hospital believes that its wage or occupational mix data are incorrect 
due to a MAC or CMS error in the entry or tabulation of the final data, 
the hospital was given the opportunity to notify both its MAC and

[[Page 49015]]

CMS regarding why the hospital believes an error exists and provide all 
supporting information, including relevant dates (for example, when it 
first became aware of the error). The hospital was required to send its 
request to CMS and to the MAC so that it was received no later than May 
27, 2022. May 27, 2022, was also the deadline for hospitals to dispute 
data corrections made by CMS of which the hospital is notified on or 
after 13 calendar days prior to April 1, 2022 (that is, March 19, 
2022), and at least 14 calendar days prior to May 27, 2022 (that is, 
May 13, 2022), that do not arise from a hospital's request for 
revisions. (Data corrections made by CMS of which a hospital was 
notified on or after 13 calendar days prior to May 27, 2022 (that is, 
May 14, 2022), may be appealed to the Provider Reimbursement Review 
Board (PRRB)). In accordance with the FY 2023 Hospital Wage Index 
Development Time Table posted on the CMS website at https://www.cms.gov/files/document/fy2023-wi-time-table.pdf, the May appeals 
were required to be sent via mail and email to CMS and the MACs. We 
refer readers to the FY 2023 Hospital Wage Index Development Time Table 
for complete details.
    Verified corrections to the wage index data received timely (that 
is, by May 27, 2022) by CMS and the MACs were incorporated into the 
final FY 2023 wage index, which will be effective October 1, 2022.
    We created the processes previously described to resolve all 
substantive wage index data correction disputes before we finalize the 
wage and occupational mix data for the FY 2023 payment rates. 
Accordingly, hospitals that do not meet the procedural deadlines set 
forth earlier will not be afforded a later opportunity to submit wage 
index data corrections or to dispute the MAC's decision with respect to 
requested changes. Specifically, our policy is that hospitals that do 
not meet the procedural deadlines as previously set forth (requiring 
requests to MACs by the specified date in February and, where such 
requests are unsuccessful, requests for intervention by CMS by the 
specified date in April) will not be permitted to challenge later, 
before the PRRB, the failure of CMS to make a requested data revision. 
We refer readers also to the FY 2000 IPPS final rule (64 FR 41513) for 
a discussion of the parameters for appeals to the PRRB for wage index 
data corrections. As finalized in the FY 2018 IPPS/LTCH PPS final rule 
(82 FR 38154 through 38156), this policy also applies to a hospital 
disputing corrections made by CMS that do not arise from a hospital's 
request for a wage index data revision. That is, a hospital disputing 
an adjustment made by CMS that did not arise from a hospital's request 
for a wage index data revision is required to request a correction by 
the first applicable deadline. Hospitals that do not meet the 
procedural deadlines set forth earlier will not be afforded a later 
opportunity to submit wage index data corrections or to dispute CMS' 
decision with respect to changes.
    Again, we believe the wage index data correction process described 
earlier provides hospitals with sufficient opportunity to bring errors 
in their wage and occupational mix data to the MAC's attention. 
Moreover, because hospitals had access to the final wage index data 
PUFs by late April 2022, they have an opportunity to detect any data 
entry or tabulation errors made by the MAC or CMS before the 
development and publication of the final FY 2023 wage index by August 
2022, and the implementation of the FY 2023 wage index on October 1, 
2022. Given these processes, the wage index implemented on October 1 
should be accurate. Nevertheless, in the event that errors are 
identified by hospitals and brought to our attention after May 27, 
2022, we retain the right to make midyear changes to the wage index 
under very limited circumstances.
    Specifically, in accordance with 42 CFR 412.64(k)(1) of our 
regulations, we make midyear corrections to the wage index for an area 
only if a hospital can show that: (1) The MAC or CMS made an error in 
tabulating its data; and (2) the requesting hospital could not have 
known about the error or did not have an opportunity to correct the 
error, before the beginning of the fiscal year. For purposes of this 
provision, ``before the beginning of the fiscal year'' means by the May 
deadline for making corrections to the wage data for the following 
fiscal year's wage index (for example, May 27, 2022, for the FY 2023 
wage index). This provision is not available to a hospital seeking to 
revise another hospital's data that may be affecting the requesting 
hospital's wage index for the labor market area. As indicated earlier, 
because CMS makes the wage index data available to hospitals on the CMS 
website prior to publishing both the proposed and final IPPS rules, and 
the MACs notify hospitals directly of any wage index data changes after 
completing their desk reviews, we do not expect that midyear 
corrections will be necessary. However, under our current policy, if 
the correction of a data error changes the wage index value for an 
area, the revised wage index value will be effective prospectively from 
the date the correction is made.
    In the FY 2006 IPPS final rule (70 FR 47385 through 47387 and 
47485), we revised 42 CFR 412.64(k)(2) to specify that, effective on 
October 1, 2005, that is, beginning with the FY 2006 wage index, a 
change to the wage index can be made retroactive to the beginning of 
the Federal fiscal year only when CMS determines all of the following: 
(1) The MAC or CMS made an error in tabulating data used for the wage 
index calculation; (2) the hospital knew about the error and requested 
that the MAC and CMS correct the error using the established process 
and within the established schedule for requesting corrections to the 
wage index data, before the beginning of the fiscal year for the 
applicable IPPS update (that is, by the May 27, 2022, deadline for the 
FY 2023 wage index); and (3) CMS agreed before October 1 that the MAC 
or CMS made an error in tabulating the hospital's wage index data and 
the wage index should be corrected.
    In those circumstances where a hospital requested a correction to 
its wage index data before CMS calculated the final wage index (that 
is, by the May 27, 2022 deadline for the FY 2023 wage index), and CMS 
acknowledges that the error in the hospital's wage index data was 
caused by CMS' or the MAC's mishandling of the data, we believe that 
the hospital should not be penalized by our delay in publishing or 
implementing the correction. As with our current policy, we indicated 
that the provision is not available to a hospital seeking to revise 
another hospital's data. In addition, the provision cannot be used to 
correct prior years' wage index data; it can only be used for the 
current Federal fiscal year. In situations where our policies would 
allow midyear corrections other than those specified in 42 CFR 
412.64(k)(2)(ii), we continue to believe that it is appropriate to make 
prospective-only corrections to the wage index.
    We note that, as with prospective changes to the wage index, the 
final retroactive correction will be made irrespective of whether the 
change increases or decreases a hospital's payment rate. In addition, 
we note that the policy of retroactive adjustment will still apply in 
those instances where a final judicial decision reverses a CMS denial 
of a hospital's wage index data revision request.
2. Process for Data Corrections by CMS After the January 28 Public Use 
File (PUF)
    The process set forth with the wage index time table discussed in 
section

[[Page 49016]]

III.L.1. of the preamble of this final rule allows hospitals to request 
corrections to their wage index data within prescribed timeframes. In 
addition to hospitals' opportunity to request corrections of wage index 
data errors or MACs' mishandling of data, CMS has the authority under 
section 1886(d)(3)(E) of the Act to make corrections to hospital wage 
index and occupational mix data in order to ensure the accuracy of the 
wage index. As we explained in the FY 2016 IPPS/LTCH PPS final rule (80 
FR 49490 through 49491) and the FY 2017 IPPS/LTCH PPS final rule (81 FR 
56914), section 1886(d)(3)(E) of the Act requires the Secretary to 
adjust the proportion of hospitals' costs attributable to wages and 
wage-related costs for area differences reflecting the relative 
hospital wage level in the geographic areas of the hospital compared to 
the national average hospital wage level. We believe that, under 
section 1886(d)(3)(E) of the Act, we have discretion to make 
corrections to hospitals' data to help ensure that the costs 
attributable to wages and wage-related costs in fact accurately reflect 
the relative hospital wage level in the hospitals' geographic areas.
    We have an established multistep, 15-month process for the review 
and correction of the hospital wage data that is used to create the 
IPPS wage index for the upcoming fiscal year. Since the origin of the 
IPPS, the wage index has been subject to its own annual review process, 
first by the MACs, and then by CMS. As a standard practice, after each 
annual desk review, CMS reviews the results of the MACs' desk reviews 
and focuses on items flagged during the desk review, requiring that, if 
necessary, hospitals provide additional documentation, adjustments, or 
corrections to the data. This ongoing communication with hospitals 
about their wage data may result in the discovery by CMS of additional 
items that were reported incorrectly or other data errors, even after 
the posting of the January 28 PUF, and throughout the remainder of the 
wage index development process. In addition, the fact that CMS analyzes 
the data from a regional and even national level, unlike the review 
performed by the MACs that review a limited subset of hospitals, can 
facilitate additional editing of the data that may not be readily 
apparent to the MACs. In these occasional instances, an error may be of 
sufficient magnitude that the wage index of an entire CBSA is affected. 
Accordingly, CMS uses its authority to ensure that the wage index 
accurately reflects the relative hospital wage level in the geographic 
area of the hospital compared to the national average hospital wage 
level, by continuing to make corrections to hospital wage data upon 
discovering incorrect wage data, distinct from instances in which 
hospitals request data revisions.
    We note that CMS corrects errors to hospital wage data as 
appropriate, regardless of whether that correction will raise or lower 
a hospital's average hourly wage. For example, as discussed in section 
III.C. of the preamble of the FY 2019 IPPS/LTCH PPS final rule (83 FR 
41364), in situations where a hospital did not have documentable 
salaries, wages, and hours for housekeeping and dietary services, we 
imputed estimates, in accordance with policies established in the FY 
2015 IPPS/LTCH PPS final rule (79 FR 49965 through 49967). Furthermore, 
if CMS discovers after conclusion of the desk review, for example, that 
a MAC inadvertently failed to incorporate positive adjustments 
resulting from a prior year's wage index appeal of a hospital's wage-
related costs such as pension, CMS would correct that data error and 
the hospital's average hourly wage would likely increase as a result.
    While we maintain CMS' authority to conduct additional review and 
make resulting corrections at any time during the wage index 
development process, in accordance with the policy finalized in the FY 
2018 IPPS/LTCH PPS final rule (82 FR 38154 through 38156) and as first 
implemented with the FY 2019 wage index (83 FR 41389), hospitals are 
able to request further review of a correction made by CMS that did not 
arise from a hospital's request for a wage index data correction. 
Instances where CMS makes a correction to a hospital's data after the 
January 28 PUF based on a different understanding than the hospital 
about certain reported costs, for example, could potentially be 
resolved using this process before the final wage index is calculated. 
We believe this process and the timeline for requesting review of such 
corrections (as described earlier and in the FY 2018 IPPS/LTCH PPS 
final rule) promote additional transparency to instances where CMS 
makes data corrections after the January 28 PUF, and provide 
opportunities for hospitals to request further review of CMS changes in 
time for the most accurate data to be reflected in the final wage index 
calculations. These additional appeals opportunities are described 
earlier and in the FY 2023 Hospital Wage Index Development Time Table, 
as well as in the FY 2018 IPPS/LTCH PPS final rule (82 FR 38154 through 
38156).

M. Labor-Related Share for the FY 2023 Wage Index

    Section 1886(d)(3)(E) of the Act directs the Secretary to adjust 
the proportion of the national prospective payment system base payment 
rates that are attributable to wages and wage related costs by a factor 
that reflects the relative differences in labor costs among geographic 
areas. It also directs the Secretary to estimate from time to time the 
proportion of hospital costs that are labor-related and to adjust the 
proportion (as estimated by the Secretary from time to time) of 
hospitals' costs that are attributable to wages and wage-related costs 
of the DRG prospective payment rates. We refer to the portion of 
hospital costs attributable to wages and wage-related costs as the 
labor-related share. The labor-related share of the prospective payment 
rate is adjusted by an index of relative labor costs, which is referred 
to as the wage index.
    Section 403 of Public Law 108-173 amended section 1886(d)(3)(E) of 
the Act to provide that the Secretary must employ 62 percent as the 
labor-related share unless this would result in lower payments to a 
hospital than would otherwise be made. However, this provision of 
Public Law 108-173 did not change the legal requirement that the 
Secretary estimate from time to time the proportion of hospitals' costs 
that are attributable to wages and wage-related costs. Thus, hospitals 
receive payment based on either a 62-percent labor-related share, or 
the labor-related share estimated from time to time by the Secretary, 
depending on which labor-related share resulted in a higher payment.
    In the FY 2022 IPPS/LTCH PPS final rule (86 FR 45194 through 
45208), we rebased and revised the hospital market basket. We 
established a 2018-based IPPS hospital market basket to replace the 
2014-based IPPS hospital market basket, effective October 1, 2021. 
Using the 2018-based IPPS market basket, we finalized a labor-related 
share of 67.6 percent for discharges occurring on or after October 1, 
2021. In addition, in FY 2022, we implemented this revised and rebased 
labor-related share in a budget neutral manner (86 FR 45529-45530). 
However, consistent with section 1886(d)(3)(E) of the Act, we did not 
take into account the additional payments that would be made as a 
result of hospitals with a wage index less than or equal to 1.0000 
being paid using a labor-related share lower than the labor-related 
share of hospitals with a wage index greater than 1.0000.

[[Page 49017]]

    The labor-related share is used to determine the proportion of the 
national IPPS base payment rate to which the area wage index is 
applied. We include a cost category in the labor related share if the 
costs are labor intensive and vary with the local labor market. In the 
FY 2022 IPPS/LTCH PPS final rule (86 FR 45204 through 45207), we 
included in the labor-related share the national average proportion of 
operating costs that are attributable to the following cost categories 
in the 2018-based IPPS market basket: Wages and Salaries; Employee 
Benefits; Professional Fees: Labor-Related; Administrative and 
Facilities Support Services; Installation, Maintenance, and Repair 
Services; and All Other: Labor-related Services. In the proposed rule, 
for FY 2023, we did not propose to make any further changes to the 
labor-related share. For FY 2023, we proposed to continue to use a 
labor-related share of 67.6 percent for discharges occurring on or 
after October 1, 2022.
    As discussed in section V.A. of the preamble of this final rule, 
prior to January 1, 2016, Puerto Rico hospitals were paid based on 75 
percent of the national standardized amount and 25 percent of the 
Puerto Rico-specific standardized amount. As a result, we applied the 
Puerto Rico-specific labor-related share percentage and nonlabor-
related share percentage to the Puerto Rico-specific standardized 
amount. Section 601 of the Consolidated Appropriations Act, 2016 (Pub. 
L. 114-113) amended section 1886(d)(9)(E) of the Act to specify that 
the payment calculation with respect to operating costs of inpatient 
hospital services of a subsection (d) Puerto Rico hospital for 
inpatient hospital discharges on or after January 1, 2016, shall use 
100 percent of the national standardized amount. Because Puerto Rico 
hospitals are no longer paid with a Puerto Rico-specific standardized 
amount as of January 1, 2016, under section 1886(d)(9)(E) of the Act as 
amended by section 601 of the Consolidated Appropriations Act, 2016, 
there is no longer a need for us to calculate a Puerto Rico-specific 
labor-related share percentage and nonlabor-related share percentage 
for application to the Puerto Rico-specific standardized amount. 
Hospitals in Puerto Rico are now paid 100 percent of the national 
standardized amount and, therefore, are subject to the national labor-
related share and nonlabor related share percentages that are applied 
to the national standardized amount. Accordingly, for FY 2023, we did 
not propose a Puerto Rico-specific labor-related share percentage or a 
nonlabor-related share percentage.
    Comment: Some commenters stated that an analysis comparing 
hospitals' average hourly wages calculated from data reported on 
schedule S-3 of their FY 2019 to their 2020 cost reports shows that the 
average hourly wage rose 4.14 percent among hospitals with a wage index 
greater than 1.0. The commenters stated that this wage growth occurred 
at the same time that hospital utilization was decreasing due to the 
effects of the pandemic, resulting in a considerable increase in the 
portion of overall hospital costs represented by labor.
    In addition to requesting that CMS update the labor share, the 
commenters requested that CMS modify its methodology to review only the 
labor costs of hospitals in areas with a wage index greater than 1.0 
because hospitals in areas with a wage index lower than 1.0 receive a 
statutorily defined labor-related share of 62 percent. The commenters 
stated that changes of the labor share are budget-neutral but updating 
the share would ensure that a more appropriate amount of funds go to 
hospitals in areas with a wage index greater than 1.0, where the 
greatest increases in labor costs have been experienced. The commenters 
explained that the same comparison of 2019 and 2020 average hourly 
wages shows that hospitals with a wage index of 1.0 or less experienced 
an increase of only 2.38 percent during that same period.
    For the reasons above, the commenters requested that CMS consider 
raising the labor-related share for hospitals with wage indexes greater 
than 1.0 for FY 2023.
    A commenter stated that it strongly supports continuing to utilize 
a labor-related share of 67.6 percent for discharges. The commenter 
also stated that given the extreme increases in labor costs industry-
wide due to the pandemic over the last three years, the commenter urged 
CMS to re-base again for FY 2023 to reflect a more accurate labor-
related share.
    A commenter stated that it experienced an exponential increase in 
the cost of labor as a result of the COVID-19 pandemic and labor 
shortages. The commenter requested that CMS evaluate the impact of 
rising labor costs on wage indices.
    Response: We appreciate the commenters' concerns regarding how 
operating expenses for hospitals may have been impacted by the PHE. 
However, we disagree with the commenters' suggestion to update the 
labor related share for FY 2023. As published in the FY 2006 IPPS final 
rule (70 FR 47403), in accordance with section 404 of Public Law 108-
173, CMS determined a new frequency for rebasing the hospital market 
basket, including the labor-related share, of every four years. 
Therefore, in the FY 2022 IPPS/LTCH final rule, we finalized to update 
the labor related share to reflect the rebased and revised IPPS market 
basket, which is based on 2018 data. The labor-related share is equal 
to the national average proportion of operating costs that are 
attributable to the following cost categories in the 2018-based IPPS 
market basket: Wages and Salaries, Employee Benefits, Professional 
Fees: Labor-Related, Administrative and Facilities Support Services, 
Installation, Maintenance, and Repair Services, and All Other: Labor-
Related Services.
    CMS did not propose to rebase and revise the IPPS market basket, 
including the labor-related share, in the FY 2023 IPPS/LTCH proposed 
rule. However, we did review the most recent Medicare cost report data 
available for IPPS hospitals submitted as of March 2022, which includes 
data for 2019-2020. The Medicare cost report data showed slight 
decreases in the compensation cost weight (reflecting wages and 
salaries, employee benefits, and direct patient care contract labor 
costs as a percent of operating costs) in 2019 and 2020 resulting in a 
compensation cost weight that is roughly 1 percentage point less than 
the 2018-based IPPS market basket cost weight. The compensation cost 
weight accounts for 53.0 percentage points of the 67.6 percentage point 
labor-related share based on the 2018-based IPPS market basket.
    We plan to review the 2021 Medicare cost report data as soon as 
complete information is available and evaluate these data for future 
rulemaking. We thank the commenters for their comments and will 
consider the comments regarding the methodology for deriving the labor-
related share for future rulemaking. After consideration of the public 
comments we received, for the reasons set forth above and in this final 
rule and in the FY 2022 IPPS/LTCH PPS final rule, we are finalizing our 
proposals, without modification, to continue to use a labor-related 
share of 67.6 percent for discharges occurring on or after October 1, 
2022 for all hospitals (including Puerto Rico hospitals) whose wage 
indexes are greater than 1.0000.
    Tables 1A and 1B, which are published in section VI. of the 
Addendum to this FY 2023 IPPS/LTCH PPS final rule and available via the 
internet on the CMS website, reflect the national labor-related share. 
Table 1C, in section VI. of the Addendum to this

[[Page 49018]]

FY 2023 IPPS/LTCH PPS final rule and available via the internet on the 
CMS website, reflects the national labor-related share for hospitals 
located in Puerto Rico. For FY 2023, for all IPPS hospitals (including 
Puerto Rico hospitals) whose wage indexes are less than or equal to 
1.0000, we are applying the wage index to a labor-related share of 62 
percent of the national standardized amount. For all IPPS hospitals 
(including Puerto Rico hospitals) whose wage indexes are greater than 
1.000, for FY 2023, we are applying the wage index to a labor-related 
share of 67.6 percent of the national standardized amount.

N. Permanent Cap on Wage Index Decreases

1. Permanent Cap Policy for the Wage Index
    In the FY 2020 IPPS/LTCH PPS final rule, CMS implemented a 
transition policy for FY 2020 to place a 5 percent cap on any decrease 
in a hospital's wage index from the hospital's final wage index in FY 
2019 so that a hospital's final wage index for FY 2020 will not be less 
than 95 percent of its final wage index for FY 2019 (84 FR 42336 
through 42337). We implemented this transition due to the combined 
effect of the policy changes for the FY 2020 wage index (including 
policies to address wage index disparities between high and low wage 
index hospitals), which we believed could lead to significant decreases 
in the wage index values for some hospitals. We stated that this 
transition would allow the effects of our policies to be phased in over 
2 years with no estimated reduction in the wage index of more than 5 
percent in FY 2020 (that is, no cap would be applied the second year). 
We also stated that we believed 5 percent is a reasonable level for the 
cap because it would effectively mitigate any significant decreases in 
the wage index for FY 2020. We applied a budget neutrality adjustment 
factor to the FY 2020 standardized amount for all hospitals to achieve 
budget neutrality for the transition policy (84 FR 42337 through 
42338).
    In the FY 2021 IPPS/LTCH PPS final rule (85 FR 58753 through 
58755), to mitigate the effect of our adoption of the revised OMB 
delineations in OMB Bulletin 18-04, we implemented for FY 2021 the same 
5 percent cap transition policy that we had implemented for FY 2020. 
Specifically, we placed a 5 percent cap on any decrease in a hospital's 
wage index from the hospital's final wage index in FY 2020 so that a 
hospital's final wage index for FY 2021 will not be less than 95 
percent of its final wage index for FY 2020. We stated that for FY 
2021, we did not believe it was necessary to implement the multifaceted 
transitions (including a 1-year blended wage index) we established in 
FY 2015 for the adoption of the new OMB delineations based on the new 
decennial census data. The 5 percent cap transition policy resulted in 
some hospitals receiving a transition adjustment that were not directly 
affected by the adoption of the revised OMB delineations (85 FR 58754). 
We applied a budget neutrality adjustment to the FY 2021 standardized 
amount to achieve budget neutrality for the transition policy (85 FR 
58755).
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25397), given the 
unprecedented nature of the ongoing COVID-19 PHE, we solicited comments 
on whether it would be appropriate to continue to apply a transition to 
the FY 2022 wage index for hospitals negatively impacted by our 
adoption of the updates in OMB Bulletin 18-04. We received several 
comments strongly recommending CMS extend a transition policy similar 
to that implemented in FY 2020 and FY 2021. Commenters also recommended 
CMS consider making a permanent 5 percent maximum reduction policy to 
protect hospitals from large year-to-year variations in wage index 
values as a means to reduce overall volatility. While we did not adopt 
the commenters' suggestion for a permanent 5 percent cap policy, we did 
finalize a transition policy for FY 2022 in the FY 2022 IPPS/LTCH PPS 
final rule (86 FR 45164). Specifically, for hospitals that received the 
transition in FY 2021, we continued a wage index transition for FY 2022 
under which we apply a 5 percent cap on any decrease in the hospital's 
wage index compared to its wage index for FY 2021 to mitigate 
significant negative impacts of, and provide additional time for 
hospitals to adapt to, the CMS decision to adopt the revised OMB 
delineations. We applied a budget neutrality adjustment to the FY 2022 
standardized amount so that the transition is implemented in a budget 
neutral manner (86 FR 45165).
    For FY 2023 and subsequent years, we further considered the 
comments we received during the FY 2022 rulemaking recommending a 
permanent 5 percent cap policy to prevent large year-to-year variations 
in wage index values as a means to reduce overall volatility for 
hospitals. In the past, we have established temporary transition 
policies (as described above) when there have been significant changes 
to wage index policy, and we have limited the duration of each 
transition in order to phase in the effects of those policy changes. In 
taking this temporary approach in the past, we have sought to mitigate 
short-term instability and fluctuations that can negatively impact 
hospitals. We also recognize that, absent any specific change in wage 
index policy, significant year-to-year fluctuations in an area's wage 
index can occur due to external factors beyond a hospital's control, 
such as the COVID-19 PHE. For an individual hospital, these 
fluctuations can be difficult to predict. We recognize that 
predictability in Medicare payments is important to enable hospitals to 
budget and plan their operations.
    In light of these considerations, in the FY 2023 IPPS/LTCH PPS 
proposed rule, we proposed a permanent approach to smooth year-to-year 
decreases in hospitals' wage indexes (87 FR 28377 through 28380). We 
proposed a policy that we believe increases the predictability of IPPS 
payments for hospitals and mitigates instability and significant 
negative impacts to hospitals resulting from changes to the wage index. 
We stated that we also believe our proposed permanent policy would 
eliminate the need for temporary and potentially uncertain transition 
adjustments to the wage index in the future due to specific policy 
changes or circumstances outside hospitals' control (for example, in 
the event we adopt any future OMB revisions to the CBSA delineations). 
As a result of this proposed policy, an otherwise rare but relatively 
large year-to-year decrease in the wage index value for an individual 
hospital would be phased in, providing the hospital with additional 
time to plan appropriately and explore potential reclassification 
options, if applicable. For example, if a change in OMB delineations 
resulted in a hospital's wage index decreasing by more than 10 percent 
in any given year, this proposed policy could provide at least one 
additional year to phase in the decrease beyond a single ``transition'' 
year methodology, such as the transition policy finalized in the FY 
2015 IPPS/LTCH PPS final rule (79 FR 49957 through 49962).
    Typical year-to-year variation in the wage index has historically 
been within 5 percent, and we stated in the proposed rule that we 
expect this will continue to be the case in future years. Because 
hospitals are usually experienced with this level of wage index 
fluctuation, we stated that we believe applying a 5-percent cap on all 
wage index decreases each year, regardless of the reason for the 
decrease, would effectively mitigate instability in IPPS payments due 
to any significant wage index decreases that may affect hospitals in a 
year. In

[[Page 49019]]

addition, we stated that we believe that the predictability resulting 
from a 5 percent cap on all wage index decreases would enable hospitals 
to more effectively budget and plan their operations. Because applying 
a 5-percent cap on all wage index decreases would represent a small 
overall impact on the labor market area wage index system, we stated 
that we believe it would ensure the wage index is a relative measure of 
the value of labor in prescribed labor market areas. In the proposed 
rule, we estimated that applying a 5-percent cap on all wage index 
decreases would have a very small effect on the budget neutrality 
factor associated with the cap applied to the standardized amount for 
FY 2023 (discussed in section III.N.2 of the preamble of the proposed 
rule). Because the wage index is a measure of the value of labor (wage 
and wage-related costs) in a prescribed labor market area relative to 
the national average, we stated that we anticipate that in the absence 
of policy changes most hospitals will not experience year-to-year wage 
index declines greater than 5 percent in any given year. Therefore, we 
stated that we anticipate that the impact to the budget neutrality 
factor associated with the cap in future years would continue to be 
minimal. We stated that we also believe that when the 5-percent cap 
would be applied under this proposal, in general it is likely that it 
would be applied similarly to all hospitals in the same labor market 
area, as the hospital average hourly wage data in the CBSA (and any 
relative decreases compared to the national average hourly wage) would 
be similar. While in certain circumstances this policy may result in 
some hospitals in a CBSA receiving a higher wage index than others in 
the same area, we stated that we believe the impact would be temporary.
    For the reasons discussed in the proposed rule, we stated that we 
believe a 5-percent cap on wage index decreases would be appropriate 
for the IPPS. Therefore, for FY 2023 and subsequent years, we proposed 
to apply a 5-percent cap on any decrease to a hospital's wage index 
from its wage index in the prior FY, regardless of the circumstances 
causing the decline. That is, we proposed that a hospital's wage index 
for FY 2023 would not be less than 95 percent of its final wage index 
for FY 2022, and that for subsequent years, a hospital's wage index 
would not be less than 95 percent of its final wage index for the prior 
FY. This also means that if a hospital's prior FY wage index is 
calculated with the application of the 5-percent cap, the following 
year's wage index would not be less than 95 percent of the hospital's 
capped wage index in the prior FY. For example, if a hospital's wage 
index for FY 2023 is calculated with the application of the 5-percent 
cap, then its wage index for FY 2024 would not be less than 95 percent 
of its capped wage index in FY 2023. We stated that we would reflect 
the proposed wage index cap policy at 42 CFR 412.64(h). Specifically, 
we proposed to add a new paragraph at 42 CFR 412.64(h)(7) to state that 
beginning with fiscal year 2023, if CMS determines that a hospital's 
wage index value for a fiscal year would decrease by more than 5 
percent as compared to the hospital's wage index value for the prior 
fiscal year, CMS limits the decrease to 5 percent for the fiscal year.
    We stated that we have authority to implement the proposed wage 
index cap policy and the associated proposed budget neutrality 
adjustment (discussed in section III.N.2. of the preamble of the 
proposed rule) under section 1886(d)(3)(E) of the Act, which gives the 
Secretary broad authority to adjust for area differences in hospital 
wage levels by a factor (established by the Secretary) reflecting the 
relative hospital wage level in the geographic area of the hospital 
compared to the national average hospital wage level, and requires 
those adjustments to be budget neutral. We also stated that in 
addition, we have authority to implement the proposed wage index cap 
policy and the associated proposed budget neutrality adjustment 
(discussed in section III.N.2. of the preamble of the proposed rule) as 
an adjustment under section 1886(d)(5)(I)(i) of the Act, which 
similarly gives the Secretary broad authority to provide by regulation 
for such other exceptions and adjustments to such payment amounts under 
subsection (d) as the Secretary deems appropriate.
    We proposed to apply the wage index cap policy described above for 
a FY using the final wage index applicable to the hospital on the last 
day of the prior FY (except for newly opened hospitals, as discussed 
below). In general, the final wage index applicable to the hospital on 
the last day of the prior FY would be the wage index value listed for 
the hospital in Table 2 of the IPPS/LTCH PPS final rule for that prior 
FY (including any correction notices, if applicable). We stated that in 
rulemaking for a FY, we intend to relist the wage index values from 
Table 2 of the IPPS/LTCH PPS final rule for the prior FY, with updates 
as described below. Under the proposed wage index cap policy described 
above, we would use these values to determine a hospital's wage index 
for a FY by capping it at 95 percent of the final wage index applicable 
to the hospital on the last day of the prior FY (in general, the wage 
index value listed for the hospital in Table 2 of the IPPS/LTCH PPS 
final rule for the prior FY). We noted in the proposed rule that, 
consistent with our past application of the 5 percent cap transition 
policy (see the FY 2020 IPPS/LTCH PPS final rule (84 FR 42337)), the 
proposed wage index cap policy described above would apply to hospitals 
whose wage index is reduced by obtaining a urban to rural 
reclassification under 42 CFR 412.103. Specifically, a hospital that 
obtains a rural reclassification under 42 CFR 412.103 may be assigned 
its State's rural wage index.\212\ While other forms of wage index 
reclassification are effective with the start of a Federal fiscal year, 
pursuant to 42 CFR 412.103(d)(1), the effective date of an approved 
rural reclassification is the filing date of the application. 
Therefore, the wage index values for hospitals that obtain rural 
reclassification under 42 CFR 412.103 may change in the middle of a 
Federal fiscal year and thus may not be reflected in Table 2 of the 
IPPS/LTCH PPS final rule for that year. For example, if a hospital was 
assigned its geographic wage index of 1.0001 in Table 2 of the FY 2022 
IPPS/LTCH PPS final rule, but obtained a rural reclassification on 
December 1, 2021 and was assigned its state's rural wage index of 
0.9600 for the remainder of FY 2022; the FY 2023 cap would be based on 
the 0.9600 value, not the 1.0001 value listed in Table 2 of the FY 2022 
IPPS/LTCH PPS final rule. We stated that as in previous years, we would 
instruct hospitals that obtain a rural reclassification under 42 CFR 
412.103 to contact their MAC to ensure that their assigned wage index 
does not result in a greater than 5 percent decrease from the 
hospital's prior year wage index value (see the FY 2020 IPPS/LTCH PPS 
final rule (84 FR 42337) and the FY 2021 IPPS/LTCH PPS final rule (85 
FR 58754)).
---------------------------------------------------------------------------

    \212\ As discussed in the FY 2016 IFC (81 FR 23428 through 
23438), hospitals with simultaneous reclassifications under 412.103 
and either Lugar or MGCRB reclassification process are not assigned 
their State's rural wage index.
---------------------------------------------------------------------------

    In Table 2 associated with this final rule, which is available via 
the internet on the CMS website, we list the FY 2022 final wage index 
value for all hospitals in column C. For additional clarity, we have 
identified hospitals that have obtained rural reclassification after 
the FY 2022 lock-in date, as described in 42 CFR 412.103(b)(6), and 
that were assigned a different wage index than what was listed in Table 
2 associated

[[Page 49020]]

with the FY 2022 IPPS/LTCH PPS correction notice (available on the 
internet at https://www.cms.gov/files/zip/fy-2022-ipps-frtables-2-3-4a-4b.zip). In Table 2 associated with this final rule, the FY 2022 wage 
index column for these hospitals will not use the values listed in 
Table 2 associated with the FY 2022 IPPS/LTCH PPS correction notice 
(available on the internet at https://www.cms.gov/files/zip/fy2022-ipps-fr-tables-2-3-4a-4b.zip), but will instead be updated with the 
wage index value that is currently assigned to the hospitals. Under our 
proposal described above, we would apply the wage index cap using the 
actual final wage index value assigned to the hospital on the last day 
of the prior Federal fiscal year rather than the value listed in Table 
2 of the prior FY final rule. In the proposed rule, we identified in 
Table 2 (posted on the FY 2023 proposed rule web page at https://
www.cms.gov/medicare/medicare-fee-for-service-payment/
acuteinpatientpps) all hospitals that obtained rural reclassification 
under 42 CFR 412.103 after the FY 2022 lock-in date and that have no 
other form of wage index reclassification applicable to them at this 
time. This column in Table 2 has been revised for this final rule 
(posted on the FY 2023 final rule web page at https://www.cms.gov/
medicare/medicare-fee-for-service-payment/acuteinpatientpps) to add 
additional hospitals without another form of reclassification that 
obtain rural reclassification under 42 CFR 412.103 before the FY 2023 
lock-in date as described in 42 CFR 412.103(b)(6).
    We stated in the proposed rule that hospitals that obtain rural 
reclassification after the FY 2023 lock-in date will not be listed as 
being reclassified as rural in the FY 2023 IPPS/LTCH PPS final rule. We 
stated that if we finalize the proposed wage index cap policy described 
above, these hospitals should contact their MAC to ensure that the 
assigned rural wage index value is not less than 95 percent of their 
final wage index value for FY 2022 (that is, the wage index assigned to 
the hospital as of September 30, 2022).
    For newly opened hospitals, we proposed to apply the proposed wage 
index cap policy for a FY using the wage index value the hospital was 
assigned for the prior FY. A new hospital would be paid the wage index 
for the area in which it is geographically located for its first full 
or partial fiscal year, and it would not receive a cap for that first 
year because it would not have been assigned a wage index in the prior 
year. Also, it is possible a new hospital may not be listed in Table 2 
for several years since the hospitals listed in Table 2 are based on 
historical data. We stated in the proposed rule that if we finalize the 
proposed wage index cap policy described above, a new hospital may 
contact their MAC to ensure that their assigned wage index value for 
the upcoming FY is not less than 95 percent of the value assigned to 
them for the prior Federal fiscal year. For example, if a hospital 
begins operations on July 1, 2022, and is assigned its area wage index 
of 0.9000 for the remainder of FY 2022, its FY 2023 wage index would be 
capped at 95 percent of that value, and could not be lower than 0.8550 
(0.95 x 0.9000) regardless of whether it was listed in Table 2 in the 
FY 2022 IPPS/LTCH PPS final rule. A hospital that opens on December 1, 
2022 would not be eligible for a capped wage index in FY 2023, as it 
was not assigned a wage index during FY 2022.
    In the proposed rule, we noted that if we adopt these proposals as 
final policy, we would examine the effects of the policy on an ongoing 
basis in the future in order to assess whether it effectively and 
appropriately accomplishes the goal of increasing predictability and 
stability in IPPS payments.
    We received comments on our proposals and summarize and respond to 
these comments in section III.N.2. below where we discuss the proposed 
budget neutrality adjustment associated with the proposed wage index 
cap policy. As we note below, we are finalizing our proposals regarding 
the wage index cap policy without modification.
2. Permanent Cap Budget Neutrality
    We proposed to implement the proposed wage index cap policy 
(discussed above in section III.N.1 of the preamble of this final rule) 
in a budget neutral manner through a national adjustment to the 
standardized amount each fiscal year as we have implemented similar 
past transition policies involving a cap on wage index decreases (for 
example, see the FY 2021 IPPS/LTCH PPS final rule (85 FR 58755) and the 
FY 2022 IPPS/LTCH PPS final rule (86 FR 45164 through 45165)). We 
stated that we believe application of the proposed wage index cap 
policy should not increase estimated aggregate Medicare payments beyond 
the payments that would be made had we never applied the cap.
    Specifically, we proposed to apply a budget neutrality adjustment 
to ensure that estimated aggregate payments under our proposed wage 
index cap policy for hospitals that would have a decrease in their wage 
indexes for the upcoming fiscal year of more than 5 percent would equal 
what estimated aggregate payments would have been without the proposed 
wage index cap policy. To determine the proposed associated budget 
neutrality factor, we stated that we would compare estimated aggregate 
IPPS payments with and without the proposed wage index cap policy. As 
discussed above in section III.N.1 of the preamble of this final rule, 
in the propose rule, we stated that we have authority to implement this 
budget neutrality adjustment under sections 1886(d)(3)(E) and 
(d)(5)(I)(i) of the Act.
    Comment: Commenters were generally supportive of CMS's proposal to 
limit any decrease in a hospital's wage index value to be no greater 
than 5 percent as compared to the hospital's wage index value for the 
prior fiscal year. Commenters supported CMS's goal of increasing the 
stability and predictability of payments under the IPPS. However, 
several commenters contend that contrary to CMS's past statements, the 
statute neither authorizes nor requires budget neutrality to offset 
adjustments made under section 1886(d)(5)(I)(i). Some commenters 
suggested that CMS should apply the cap in a manner that would not 
reduce the wage indexes of other hospitals, contending this would lead 
to less volatility in wage index values. Several commenters request CMS 
review and seek alternatives to the proposed national budget neutrality 
adjustment.
    Response: We appreciate commenters' support of the proposed 
permanent cap on wage index decreases. As discussed above in section 
III.N.1 of the preamble of this final rule, we have authority to 
implement the proposed budget neutrality adjustment associated with the 
proposed cap under sections 1886(d)(3)(E) and (d)(5)(I)(i) of the Act. 
Section 1886(d)(3)(E) gives the Secretary broad authority to adjust for 
area differences in hospital wage levels by a factor (established by 
the Secretary) reflecting the relative hospital wage level in the 
geographic area of the hospital compared to the national average 
hospital wage level, and requires those adjustments to be applied in a 
budget neutral manner. However, even if the wage index were not 
required to be budget neutral under section 1886(d)(3)(E) of the Act, 
we would not consider it an appropriate alternative to use the wage 
index and the proposed permanent cap on wage index decreases to 
increase or decrease overall IPPS spending. The wage index is not a 
policy tool but rather a technical adjustment designed to be a relative 
measure of the wages and wage-related

[[Page 49021]]

costs of subsection (d) hospitals in the United States. Contrary to the 
commenters' assertion, we also have authority to implement the proposed 
budget neutrality adjustment associated with the proposed cap as an 
adjustment under section 1886(d)(5)(I)(i) of the Act, which similarly 
gives the Secretary broad authority to provide by regulation for such 
other exceptions and adjustments to such payment amounts under 
subsection (d) as the Secretary deems appropriate. Furthermore, our 
past transition policies involving a 5 percent cap on wage index 
decreases implemented in a budget neutral manner did not result in wage 
index volatility, and we expect the same for the overall budget 
neutrality adjustments associated with the permanent cap policy.
    Comment: MedPAC supported the proposal to cap wage index decreases 
at 5 percent, but suggested also applying a cap to increases of more 
than 5 percent.
    Response: We appreciate MedPAC's suggestion that the cap on wage 
index changes of more than 5 percent should also be applied to 
increases in the wage index. However, as we discussed in the proposed 
rule, one purpose of the proposed policy is to help mitigate the 
significant negative impacts of certain wage index changes. As we 
discussed in the proposed rule, we believe applying a 5-percent cap on 
all wage index decreases would support increased predictability about 
IPPS payments for hospitals in the upcoming fiscal year, enabling them 
to more effectively budget and plan their operations. That is, we 
proposed to cap decreases because we believe that a hospital would be 
able to more effectively budget and plan when there is predictability 
about its expected minimum level of IPPS payments in the upcoming 
fiscal year. We did not propose to limit wage index increases because 
we do not believe such a policy is needed to enable hospitals to more 
effectively budget and plan their operations. Therefore, we believe it 
is appropriate for hospitals that experience an increase in their wage 
index value to receive that wage index value.
    Comment: A commenter suggested that if CMS discontinues the low 
wage index hospital policy, hospitals that benefitted in the prior year 
from that policy should not be subject to a 5 percent cap on any 
decreases.
    Response: We appreciate the commenter's suggestion. As discussed in 
section III. G. 4 of this final rule, CMS is continuing the low wage 
index hospital policy for FY 2023.
    Comment: A commenter did not support CMS's proposed policy approach 
to the wage index cap policy with regard to newly opened hospitals. 
While the commenter stated they understand the rationale for CMS's 
policy approach, they expressed concerns that it will create inequity 
in Medicare payments for hospitals within the same market. The 
commenter encouraged CMS to apply the same area wage index value for 
new and existing hospitals under this policy.
    Response: We understand the commenter's concern, but we do not 
believe the scenario they are alluding to (that is, a labor market 
where existing hospitals are receiving the cap, and new hospitals are 
not) would neither be common nor require additional consideration. We 
believe that on an ongoing basis, relatively few hospitals would 
receive the cap, and even fewer would receive the cap in consecutive 
years. As of this final rule, there will be 126 hospitals receiving the 
cap in FY 2023, and only 12 that will receive a cap increase of greater 
than 5 percent. Therefore, any potential difference in the wage index 
value hospitals in the same labor market area receive would likely be 
minimal and temporary. We proposed to examine the effects of this 
policy on an ongoing basis to assess whether it effectively and 
appropriately accomplishes the goal of increasing predictability and 
stability in IPPS payments, and may reevaluate this issue in the 
future. However, at this time, we do not believe that creating a policy 
modification for hospitals that were not assigned a wage index in the 
prior year is necessary.
    After consideration of the public comments we received, for the 
reasons discussed in this final rule and in the proposed rule, we are 
finalizing as proposed, without modification, our wage index cap policy 
and the associated budget neutrality adjustment. We will apply a 5-
percent cap on any decrease to a hospital's wage index from its wage 
index in the prior FY, regardless of the circumstances causing the 
decline. A hospital's wage index for FY 2023 will not be less than 95 
percent of its final wage index for FY 2022, and for subsequent years, 
a hospital's wage index will not be less than 95 percent of its final 
wage index for the prior FY. For example, a hospital that received a 
wage index of 1.0000 on September 30, 2022 could not receive a wage 
index of less than 0.9500 for FY 2023. If a hospital's prior FY wage 
index is calculated with the application of the 5-percent cap, the 
following year's wage index will not be less than 95 percent of the 
hospital's capped wage index in the prior FY. Except for newly opened 
hospitals, we will apply the cap for a FY using the final wage index 
applicable to the hospital on the last day of the prior FY. A newly 
opened hospital would be paid the wage index for the area in which it 
is geographically located for its first full or partial fiscal year, 
and it would not receive a cap for that first year because it would not 
have been assigned a wage index in the prior year.
    We are adding a new paragraph at 42 CFR 412.64(h)(7) to state that 
beginning with fiscal year 2023, if CMS determines that a hospital's 
wage index value for a fiscal year would decrease by more than 5 
percent as compared to the hospital's wage index value for the prior 
fiscal year, CMS limits the decrease to 5 percent for the fiscal year.
    We will apply the cap in a budget neutral manner through a national 
adjustment to the standardized amount each fiscal year. Specifically, 
we will apply a budget neutrality adjustment to ensure that estimated 
aggregate payments under our wage index cap policy for hospitals that 
would have a decrease in their wage indexes for the upcoming fiscal 
year of more than 5 percent would equal what estimated aggregate 
payments would have been without the wage index cap policy. We note 
that the budget neutrality adjustment has been updated based on the 
final rule data. We refer readers to the Addendum of this final rule 
for further information regarding the budget neutrality calculations.

IV. Payment Adjustment for Medicare Disproportionate Share Hospitals 
(DSHs) for FY 2023 (Sec.  412.106)

A. General Discussion

    Section 1886(d)(5)(F) of the Act provides for additional Medicare 
payments to subsection (d) hospitals that serve a significantly 
disproportionate number of low-income patients. The Act specifies two 
methods by which a hospital may qualify for the Medicare 
disproportionate share hospital (DSH) adjustment. Under the first 
method, hospitals that are located in an urban area and have 100 or 
more beds may receive a Medicare DSH payment adjustment if the hospital 
can demonstrate that, during its cost reporting period, more than 30 
percent of its net inpatient care revenues are derived from State and 
local government payments for care furnished to patients with low 
incomes. This method is commonly referred to as the ``Pickle method.'' 
The second method for qualifying for the DSH payment adjustment, which 
is the most common, is based on a complex statutory formula under which 
the DSH payment adjustment is based on the hospital's

[[Page 49022]]

geographic designation, the number of beds in the hospital, and the 
level of the hospital's disproportionate patient percentage (DPP). A 
hospital's DPP is the sum of two fractions: the ``Medicare fraction'' 
and the ``Medicaid fraction.'' The Medicare fraction (also known as the 
``SSI fraction'' or ``SSI ratio'') is computed by dividing the number 
of the hospital's inpatient days that are furnished to patients who 
were entitled to both Medicare Part A and Supplemental Security Income 
(SSI) benefits by the hospital's total number of patient days furnished 
to patients entitled to benefits under Medicare Part A. The Medicaid 
fraction is computed by dividing the hospital's number of inpatient 
days furnished to patients who, for such days, were eligible for 
Medicaid, but were not entitled to benefits under Medicare Part A, by 
the hospital's total number of inpatient days in the same period.
[GRAPHIC] [TIFF OMITTED] TR10AU22.119

    Because the DSH payment adjustment is part of the IPPS, the 
statutory references to ``days'' in section 1886(d)(5)(F) of the Act 
have been interpreted to apply only to hospital acute care inpatient 
days. Regulations located at 42 CFR 412.106 govern the Medicare DSH 
payment adjustment and specify how the DPP is calculated as well as how 
beds and patient days are counted in determining the Medicare DSH 
payment adjustment. Under Sec.  412.106(a)(1)(i), the number of beds 
for the Medicare DSH payment adjustment is determined in accordance 
with bed counting rules for the IME adjustment under Sec.  412.105(b).
    Section 3133 of the Patient Protection and Affordable Care Act, as 
amended by section 10316 of the same Act and section 1104 of the Health 
Care and Education Reconciliation Act (Pub. L. 111-152), added a 
section 1886(r) to the Act that modifies the methodology for computing 
the Medicare DSH payment adjustment. (For purposes of this final rule, 
we refer to these provisions collectively as section 3133 of the 
Affordable Care Act.) Beginning with discharges in FY 2014, hospitals 
that qualify for Medicare DSH payments under section 1886(d)(5)(F) of 
the Act receive 25 percent of the amount they previously would have 
received under the statutory formula for Medicare DSH payments. This 
provision applies equally to hospitals that qualify for DSH payments 
under section 1886(d)(5)(F)(i)(I) of the Act and those hospitals that 
qualify under the Pickle method under section 1886(d)(5)(F)(i)(II) of 
the Act.
    The remaining amount, equal to an estimate of 75 percent of what 
otherwise would have been paid as Medicare DSH payments, reduced to 
reflect changes in the percentage of individuals who are uninsured, is 
available to make additional payments to each hospital that qualifies 
for Medicare DSH payments and that has uncompensated care. The payments 
to each hospital for a fiscal year are based on the hospital's amount 
of uncompensated care for a given time period relative to the total 
amount of uncompensated care for that same time period reported by all 
hospitals that receive Medicare DSH payments for that fiscal year.
    Since FY 2014, section 1886(r) of the Act has required that 
hospitals that are eligible for DSH payments under section 
1886(d)(5)(F) of the Act receive 2 separately calculated payments:
[GRAPHIC] [TIFF OMITTED] TR10AU22.120


[[Page 49023]]


    Specifically, section 1886(r)(1) of the Act provides that the 
Secretary shall pay to such subsection (d) hospital (including a Pickle 
hospital) 25 percent of the amount the hospital would have received 
under section 1886(d)(5)(F) of the Act for DSH payments, which 
represents the empirically justified amount for such payment, as 
determined by the MedPAC in its March 2007 Report to Congress. We refer 
to this payment as the ``empirically justified Medicare DSH payment.''
    In addition to this empirically justified Medicare DSH payment, 
section 1886(r)(2) of the Act provides that, for FY 2014 and each 
subsequent fiscal year, the Secretary shall pay to such subsection (d) 
hospital an additional amount equal to the product of three factors. 
The first factor is the difference between the aggregate amount of 
payments that would be made to subsection (d) hospitals under section 
1886(d)(5)(F) of the Act if subsection (r) did not apply and the 
aggregate amount of payments that are made to subsection (d) hospitals 
under section 1886(r)(1) of the Act for such fiscal year. Therefore, 
this factor amounts to 75 percent of the payments that would otherwise 
be made under section 1886(d)(5)(F) of the Act.
    The second factor is, for FY 2018 and subsequent fiscal years, 1 
minus the percent change in the percent of individuals who are 
uninsured, as determined by comparing the percent of individuals who 
were uninsured in 2013 (as estimated by the Secretary, based on data 
from the Census Bureau or other sources the Secretary determines 
appropriate, and certified by the Chief Actuary of CMS), and the 
percent of individuals who were uninsured in the most recent period for 
which data are available (as so estimated and certified), minus a 
statutory adjustment of 0.2 percentage point for FYs 2018 and 2019.
    The third factor is a percent that, for each subsection (d) 
hospital, represents the quotient of the amount of uncompensated care 
for such hospital for a period selected by the Secretary (as estimated 
by the Secretary, based on appropriate data), including the use of 
alternative data where the Secretary determines that alternative data 
are available which are a better proxy for the costs of subsection (d) 
hospitals for treating the uninsured, and the aggregate amount of 
uncompensated care for all subsection (d) hospitals that receive a 
payment under section 1886(r) of the Act. Therefore, this third factor 
represents a hospital's uncompensated care amount for a given time 
period relative to the uncompensated care amount for that same time 
period for all hospitals that receive Medicare DSH payments in the 
applicable fiscal year, expressed as a percent.
    For each hospital, the product of these three factors represents 
its additional payment for uncompensated care for the applicable fiscal 
year. We refer to the additional payment determined by these factors as 
the ``uncompensated care payment.'' In brief, the uncompensated care 
payment for an individual hospital is determined as the product of the 
following 3 factors:
[GRAPHIC] [TIFF OMITTED] TR10AU22.121

    Section 1886(r) of the Act applies to FY 2014 and each subsequent 
fiscal year. In the FY 2014 IPPS/LTCH PPS final rule (78 FR 50620 
through 50647) and the FY 2014 IPPS interim final rule with comment 
period (78 FR 61191 through 61197), we set forth our policies for 
implementing the required changes to the Medicare DSH payment 
methodology made by section 3133 of the Affordable Care Act for FY 
2014. In those rules, we noted that, because section 1886(r) of the Act 
modifies the payment required under section 1886(d)(5)(F) of the Act, 
it affects only the DSH payment under the operating IPPS. It does not 
revise or replace the capital IPPS DSH payment provided under the 
regulations at 42 CFR part 412, subpart M, which was established 
through the exercise of the Secretary's discretion in implementing the 
capital IPPS under section 1886(g)(1)(A) of the Act.
    Finally, section 1886(r)(3) of the Act provides that there shall be 
no administrative or judicial review under section 1869, section 1878, 
or otherwise of any estimate of the Secretary for purposes of 
determining the factors described in section 1886(r)(2) of the Act or 
of any period selected by the Secretary for the purpose of determining 
those factors. Therefore, there is no administrative or judicial review 
of the estimates developed for purposes of applying the three factors 
used to determine uncompensated care payments, or the periods selected 
in order to develop such estimates.

B. Eligibility for Empirically Justified Medicare DSH Payments and 
Uncompensated Care Payments

    As explained earlier, the payment methodology under section 3133 of 
the Affordable Care Act applies to ``subsection (d) hospitals'' that 
would otherwise receive a DSH payment made under section 1886(d)(5)(F) 
of the Act. Therefore, hospitals must receive empirically justified 
Medicare DSH payments in a fiscal year in order to receive an 
additional Medicare uncompensated care payment for that year. 
Specifically, section 1886(r)(2) of the Act states that, in addition to 
the payment made to a subsection (d) hospital under section 1886(r)(1) 
of the Act, the Secretary shall pay to such subsection (d) hospitals an 
additional amount. Because section 1886(r)(1) of the Act refers to 
empirically justified Medicare DSH payments, the additional payment 
under section 1886(r)(2) of the Act is limited to hospitals that 
receive empirically justified Medicare DSH payments in accordance with 
section

[[Page 49024]]

1886(r)(1) of the Act for the applicable fiscal year.
    In the FY 2014 IPPS/LTCH PPS final rule (78 FR 50622) and the FY 
2014 IPPS interim final rule with comment period (78 FR 61193), we 
provided that hospitals that are not eligible to receive empirically 
justified Medicare DSH payments in a fiscal year will not receive 
uncompensated care payments for that year. We also specified that we 
would make a determination concerning eligibility for interim 
uncompensated care payments based on each hospital's estimated DSH 
status for the applicable fiscal year (using the most recent data that 
are available). For the proposed rule, we estimated DSH status for all 
hospitals using the most recent available SSI ratios and information 
from the most recent available Provider Specific File. We noted FY 2019 
SSI ratios available on the CMS website were the most recent available 
SSI ratios at the time of developing the proposed rule. If more recent 
data on DSH eligibility become available before the final rule, we 
stated that we would use such data in the final rule. For this FY 2023 
IPPS/LTCH PPS final rule, the FY 2020 SSI ratios were available at the 
time of developing this final rule. Our final determination of a 
hospital's eligibility for uncompensated care payments will be based on 
the hospital's actual DSH status at cost report settlement for FY 2023.
    In the FY 2014 IPPS/LTCH PPS final rule (78 FR 50622) and in the 
rulemaking for subsequent fiscal years, we have specified our policies 
for several specific classes of hospitals within the scope of section 
1886(r) of the Act. In the FY 2023 IPPS/LTCH PPS proposed rule, we 
discussed our specific policies regarding eligibility to receive 
empirically justified Medicare DSH payments and uncompensated care 
payments for FY 2023 with respect to the following hospitals.
    Eligible hospitals include the following:
     Subsection (d) Puerto Rico hospitals that are eligible for 
DSH payments also are eligible to receive empirically justified 
Medicare DSH payments and uncompensated care payments under section 
1886(r) of the Act (78 FR 50623 and 79 FR 50006).
     SCHs that are paid under the IPPS Federal rate receive 
interim payments based on what we estimate and project their DSH status 
to be prior to the beginning of the Federal fiscal year (based on the 
best available data at that time) subject to settlement through the 
cost report, and if they receive interim empirically justified Medicare 
DSH payments in a fiscal year, they also will receive interim 
uncompensated care payments for that fiscal year on a per discharge 
basis, subject as well to settlement through the cost report. Final 
eligibility determinations will be made at the end of the cost 
reporting period at settlement, and both interim empirically justified 
Medicare DSH payments and uncompensated care payments will be adjusted 
accordingly (78 FR 50624 and 79 FR 50007).
     Medicare-dependent, small rural hospitals (MDHs) are paid 
based on the IPPS Federal rate or, if higher, the IPPS Federal rate 
plus 75 percent of the amount by which the Federal rate is exceeded by 
the updated hospital-specific rate from certain specified base years 
(76 FR 51684). The IPPS Federal rate that is used in the MDH payment 
methodology is the same IPPS Federal rate that is used in the SCH 
payment methodology. Because MDHs are paid based on the IPPS Federal 
rate, they continue to be eligible to receive empirically justified 
Medicare DSH payments and uncompensated care payments if their DPP is 
at least 15 percent, and we apply the same process to determine MDHs' 
eligibility for interim empirically justified Medicare DSH and interim 
uncompensated care payments as we do for all other IPPS hospitals.
    Section 50205 of the Bipartisan Budget Act of 2018 (Pub. L. 115-
123), enacted on February 9, 2018, extended the MDH program for 
discharges on or after October 1, 2017, through September 30, 2022. We 
note that there has not been legislation at the time of development of 
this final rule that would extend the MDH program beyond September 30, 
2022. However, if the MDH program were to be extended beyond its 
current expiration date, similar to how it was extended under the 
Bipartisan Budget Act of 2018, we would continue to make a 
determination concerning an MDH's eligibility for interim uncompensated 
care payments based on the hospital's estimated DSH status for the 
applicable fiscal year.
     IPPS hospitals that elect to participate in the Bundled 
Payments for Care Improvement Advanced (BPCI Advanced) model starting 
October 1, 2018, will continue to be paid under the IPPS and, 
therefore, are eligible to receive empirically justified Medicare DSH 
payments and uncompensated care payments. The BPCI Advanced Model's 
final performance year will end on December 31, 2023. For further 
information regarding the BPCI Advanced model, we refer readers to the 
CMS website at https://innovation.cms.gov/initiatives/bpci-advanced/.
     IPPS hospitals that participate in the Comprehensive Care 
for Joint Replacement Model (80 FR 73300) continue to be paid under the 
IPPS and, therefore, are eligible to receive empirically justified 
Medicare DSH payments and uncompensated care payments. We refer the 
reader to the interim final rule with request for comments that 
appeared in the November 6, 2020, Federal Register for a discussion of 
the Model (85 FR 71167 through 71173). In that interim final rule, we 
extended the Model's Performance Year 5 to September 30, 2021. In a 
subsequent final rule that appeared in the May 3, 2021 Federal Register 
(86 FR 23496), we further extended the Model for an additional three 
performance years. The Model's Performance Year 8 will end on December 
31, 2024.
    Ineligible hospitals include the following:
     Maryland hospitals are not eligible to receive empirically 
justified Medicare DSH payments and uncompensated care payments under 
the payment methodology of section 1886(r) of the Act because they are 
not paid under the IPPS. As discussed in the FY 2019 IPPS/LTCH PPS 
final rule (83 FR 41402 through 41403), CMS and the State have entered 
into an agreement to govern payments to Maryland hospitals under a new 
payment model, the Maryland Total Cost of Care (TCOC) Model, which 
began on January 1, 2019. Under the Maryland TCOC Model, Maryland 
hospitals will not be paid under the IPPS in FY 2023, and will be 
ineligible to receive empirically justified Medicare DSH payments and 
uncompensated care payments under section 1886(r) of the Act.
     Sole community hospitals (SCHs) that are paid under their 
hospital-specific rate are not eligible for Medicare DSH payments.
     Hospitals participating in the Rural Community Hospital 
Demonstration Program are not eligible to receive empirically justified 
Medicare DSH payments and uncompensated care payments under section 
1886(r) of the Act because they are not paid under the IPPS (78 FR 
50625 and 79 FR 50008). The Rural Community Hospital Demonstration 
Program was originally authorized for a 5-year period by section 410A 
of the Medicare Prescription Drug, Improvement, and Modernization Act 
of 2003 (MMA) (Pub. L. 108-173), and extended for another 5-year period 
by sections 3123 and 10313 of the Affordable Care Act (Pub. L. 114-
255). The period of performance for this 5-

[[Page 49025]]

year extension period ended December 31, 2016. Section 15003 of the 
21st Century Cures Act (Pub. L. 114-255), enacted December 13, 2016, 
again amended section 410A of Public Law 108-173 to require a 10-year 
extension period (in place of the 5-year extension required by the 
Affordable Care Act), therefore requiring an additional 5-year 
participation period for the demonstration program. Section 15003 of 
Public Law 114-255 also required a solicitation for applications for 
additional hospitals to participate in the demonstration program. The 
period of performance for this 5-year extension period ended December 
31, 2021. The Consolidated Appropriations Act, 2021 (Pub. L. 116-260) 
amended section 410A of Public Law 108-173 to extend the Rural 
Community Hospital Demonstration Program for an additional 5-year 
period. The period of participation for the last hospital in the 
demonstration under this most recent legislative authorization would 
extend until June 30, 2028, as outlined in section V.K. of the preamble 
of this final rule. Under the payment methodology that applies during 
the third 5-year extension period for the demonstration program, 
participating hospitals do not receive empirically justified Medicare 
DSH payments, and they are also excluded from receiving interim and 
final uncompensated care payments. At the time of development of this 
final rule, we believe 26 hospitals may participate in the 
demonstration program at the start of FY 2023.
    We received no comments on our policy of using the best available 
data regarding a hospital's estimated DSH status for purposes of 
determining eligibility for interim uncompensated care payments for FY 
2023. Our final determination of a hospital's eligibility for 
uncompensated care payments for FY 2023 will continue to be based on 
the hospital's actual DSH status at cost report settlement for the 
payment year.

C. Empirically Justified Medicare DSH Payments

    As we have discussed earlier, section 1886(r)(1) of the Act 
requires the Secretary to pay 25 percent of the amount of the Medicare 
DSH payment that would otherwise be made under section 1886(d)(5)(F) of 
the Act to a subsection (d) hospital. Because section 1886(r)(1) of the 
Act merely requires the program to pay a designated percentage of these 
payments, without revising the criteria governing eligibility for DSH 
payments or the underlying payment methodology, we stated in the FY 
2014 IPPS/LTCH PPS final rule that we did not believe that it was 
necessary to develop any new operational mechanisms for making such 
payments. Therefore, in the FY 2014 IPPS/LTCH PPS final rule (78 FR 
50626), we implemented this provision by advising Medicare 
Administrative Contractors (MACs) to simply adjust the interim claim 
payments to the requisite 25 percent of what would have otherwise been 
paid. We also made corresponding changes to the hospital cost report so 
that these empirically justified Medicare DSH payments can be settled 
at the appropriate level at the time of cost report settlement. We 
provided more detailed operational instructions and cost report 
instructions following issuance of the FY 2014 IPPS/LTCH PPS final rule 
that are available on the CMS website at https://www.cms.gov/Regulations-and-Guidance/Guidance/Transmittals/2014-Transmittals-Items/R5P240.html.
    We received public comments that were outside the scope of this 
proposed rule. Many of these comments related to structural changes to 
the DSH program. For example, a commenter recommended creating new 
Conditions of Participation and Conditions of Coverage related to the 
DSH program. Because we consider these public comments to be outside 
the scope of the proposed rule, we are not addressing them in this 
final rule.

D. Uncompensated Care Payments

    As we discussed earlier, section 1886(r)(2) of the Act provides 
that, for each eligible hospital in FY 2014 and subsequent years, the 
uncompensated care payment is the product of three factors. These three 
factors represent our estimate of 75 percent of the amount of Medicare 
DSH payments that would otherwise have been paid, an adjustment to this 
amount for the percent change in the national rate of uninsurance 
compared to the rate of uninsurance in 2013, and each eligible 
hospital's estimated uncompensated care amount relative to the 
estimated uncompensated care amount for all eligible hospitals. In this 
section of this final rule, we discuss the data sources and 
methodologies for computing each of these factors, our final policies 
for FYs 2014 through 2022, and our final policies for FY 2023.
1. Calculation of Factor 1 for FY 2023
    Section 1886(r)(2)(A) of the Act establishes Factor 1 in the 
calculation of the uncompensated care payment. Section 1886(r)(2)(A) of 
the Act states that this factor is equal to the difference between: (1) 
the aggregate amount of payments that would be made to subsection (d) 
hospitals under section 1886(d)(5)(F) of the Act if section 1886(r) of 
the Act did not apply for such fiscal year (as estimated by the 
Secretary); and (2) the aggregate amount of payments that are made to 
subsection (d) hospitals under section 1886(r)(1) of the Act for such 
fiscal year (as so estimated).
    Therefore, section 1886(r)(2)(A)(i) of the Act represents the 
estimated Medicare DSH payments that would have been made under section 
1886(d)(5)(F) of the Act if section 1886(r) of the Act did not apply 
for such fiscal year. Under a prospective payment system, we would not 
know the precise aggregate Medicare DSH payment amount that would be 
paid for a Federal fiscal year until cost report settlement for all 
IPPS hospitals is completed, which occurs several years after the end 
of the Federal fiscal year. Therefore, section 1886(r)(2)(A)(i) of the 
Act provides authority to estimate this amount, by specifying that, for 
each fiscal year to which the provision applies, such amount is to be 
estimated by the Secretary. Similarly, section 1886(r)(2)(A)(ii) of the 
Act represents the estimated empirically justified Medicare DSH 
payments to be made in a fiscal year, as prescribed under section 
1886(r)(1) of the Act. Again, section 1886(r)(2)(A)(ii) of the Act 
provides authority to estimate this amount. Therefore, Factor 1 is the 
difference between our estimates of: (1) the amount that would have 
been paid in Medicare DSH payments for the fiscal year, in the absence 
of the new payment provision; and (2) the amount of empirically 
justified Medicare DSH payments that are made for the fiscal year, 
which takes into account the requirement to pay 25 percent of what 
would have otherwise been paid under section 1886(d)(5)(F) of the Act. 
In other words, this factor represents our estimate of 75 percent (100 
percent minus 25 percent) of our estimate of Medicare DSH payments that 
would otherwise be made, in the absence of section 1886(r) of the Act, 
for the fiscal year.
    In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28383 through 
28385), in order to determine Factor 1 in the uncompensated care 
payment formula for FY 2023, we proposed to continue the policy 
established in the FY 2014 IPPS/LTCH PPS final rule (78 FR 50628 
through 50630) and in the FY 2014 IPPS interim final rule with comment 
period (78 FR 61194) of determining Factor 1 by developing estimates of 
both the aggregate amount of Medicare DSH payments that would be made 
in the absence of section 1886(r)(1) of the Act and the aggregate 
amount of empirically justified

[[Page 49026]]

Medicare DSH payments to hospitals under section 1886(r)(1) of the Act. 
Consistent with the policy that has applied in previous years, we 
proposed that these estimates would not be revised or updated 
subsequent to the publication of our final projections in this FY 2023 
IPPS/LTCH PPS final rule.
    Therefore, in order to determine the two elements of proposed 
Factor 1 for FY 2023 (Medicare DSH payments prior to the application of 
section 1886(r)(1) of the Act, and empirically justified Medicare DSH 
payments after application of section 1886(r)(1) of the Act), for this 
final rule, we used the most recently available projections of Medicare 
DSH payments for the fiscal year, as calculated by CMS' Office of the 
Actuary (OACT) using the most recently filed Medicare hospital cost 
reports with Medicare DSH payment information and the most recent 
Medicare DSH patient percentages and Medicare DSH payment adjustments 
provided in the IPPS Impact File. The determination of the amount of 
DSH payments is partially based on OACT's Part A benefits projection 
model. One of the results of this model is inpatient hospital spending. 
Projections of DSH payments require projections for expected increases 
in utilization and case-mix. The assumptions that were used in making 
these projections and the resulting estimates of DSH payments for FY 
2020 through FY 2023 were discussed in the proposed rule in the table 
titled ``Factors Applied for FY 2020 through FY 2023 to Estimate 
Medicare DSH Expenditures Using FY 2019 Baseline'' (87 FR 28384).
    For purposes of calculating the proposed Factor 1 and modeling the 
impact of the FY 2023 IPPS/LTCH PPS proposed rule, we used the Office 
of the Actuary's January 2022 Medicare DSH estimates, which were based 
on data from the September 2021 update of the Medicare Hospital Cost 
Report Information System (HCRIS) and the FY 2022 IPPS/LTCH PPS final 
rule IPPS Impact File, published in conjunction with the publication of 
the FY 2022 IPPS/LTCH PPS final rule. Because SCHs that are projected 
to be paid under their hospital-specific rate are excluded from the 
application of section 1886(r) of the Act, these hospitals also were 
excluded from the January 2022 Medicare DSH estimates. Furthermore, 
because section 1886(r) of the Act specifies that the uncompensated 
care payment is in addition to the empirically justified Medicare DSH 
payment (25 percent of DSH payments that would be made without regard 
to section 1886(r) of the Act), Maryland hospitals, which are not 
eligible to receive DSH payments, were also excluded from the Office of 
the Actuary's January 2022 Medicare DSH estimates. The 26 hospitals 
that are anticipated to participate in the Rural Community Hospital 
Demonstration Program in FY 2023 were also excluded from these 
estimates, because under the payment methodology that applies during 
the third 5-year extension period, these hospitals are not eligible to 
receive empirically justified Medicare DSH payments or uncompensated 
care payments.
    For the proposed rule, using the data sources as previously 
discussed, the Office of the Actuary's January 2022 estimate of 
Medicare DSH payments for FY 2023 without regard to the application of 
section 1886(r)(1) of the Act, was approximately $13.266 billion. 
Therefore, also based on the January 2022 estimate, the estimate of 
empirically justified Medicare DSH payments for FY 2023, with the 
application of section 1886(r)(1) of the Act, was approximately $3.316 
billion (or 25 percent of the total amount of estimated Medicare DSH 
payments for FY 2023). Under Sec.  412.106(g)(1)(i) of the regulations, 
Factor 1 is the difference between these two OACT estimates. Therefore, 
in the proposed rule, we proposed that Factor 1 for FY 2023 would be 
$9,949,258,556.56, which was equal to 75 percent of the total amount of 
estimated Medicare DSH payments for FY 2023 ($13,266 million minus 
$3,316 million). In the FY 2023 IPPS/LTCH PPS proposed rule, we noted 
that consistent with our approach in previous rulemakings, OACT 
intended to use more recent data that may become available for purposes 
of projecting the final Factor 1 estimates for this FY 2023 IPPS/LTCH 
PPS final rule.
    As we noted in the FY 2023 IPPS/LTCH PPS proposed rule, the Factor 
1 estimates for proposed rules are generally consistent with the 
economic assumptions and actuarial analysis used to develop the 
President's Budget estimates under current law, and the Factor 1 
estimates for the final rules are generally consistent with those used 
for the Midsession Review of the President's Budget. As we have in the 
past, for additional information on the development of the President's 
Budget, we refer readers to the Office of Management and Budget website 
at https://www.whitehouse.gov/omb/budget. Consistent with historical 
practice, we indicated that we expected that the Midsession Review 
would have updated economic assumptions and actuarial analysis, which 
would be used for the development of Factor 1 estimates in the final 
rule.
    For a general overview of the principal steps involved in 
projecting future inpatient costs and utilization, we refer readers to 
the ``2021 Annual Report of the Boards of Trustees of the Federal 
Hospital Insurance and Federal Supplementary Medical Insurance Trust 
Funds'' available on the CMS website at https://www.cms.gov/research-statistics-data-and-systems/statistics-trends-and-reports/reportstrustfunds under ``Downloads.'' We note that the annual reports 
of the Medicare Boards of Trustees to Congress represent the Federal 
Government's official evaluation of the financial status of the 
Medicare Program. The actuarial projections contained in these reports 
are based on numerous assumptions regarding future trends in program 
enrollment, utilization and costs of health care services covered by 
Medicare, as well as other factors affecting program expenditures. In 
addition, although the methods used to estimate future costs based on 
these assumptions are complex, they are subject to periodic review by 
independent experts to ensure their validity and reasonableness.
    We also refer readers to the 2018 Actuarial Report on the Financial 
Outlook for Medicaid for a discussion of general issues regarding 
Medicaid projections (available at https://www.cms.gov/Research-Statistics-Data-and-Systems/Research/ActuarialStudies/MedicaidReport).
    Comment: As in previous years, a concern and/or request expressed 
by some commenters was the need for greater transparency in the 
methodology used by CMS and OACT to calculate Factor 1. Several 
commenters specifically requested that a detailed description of the 
methodology and the data behind the assumptions be made public. 
Commenters requested that this information be provided in advance of 
the publication of the final rule and in the IPPS proposed rule each 
year going forward, so that the data is available to replicate CMS' DSH 
calculation and comment sufficiently in future years.
    In particular, commenters requested further explanation regarding 
the estimate of the ``Other'' factor used to estimate Medicare DSH 
payments. Commenters noted that the rule did not discuss why the 
``Other'' factor varies so much over successive rule making cycles.
    Additionally, a commenter asserted that the lack of opportunity 
afforded to hospitals to review the data used in rulemaking is in 
violation of the Administrative Procedure Act and

[[Page 49027]]

expressed concerns about the lack of transparency in how Factor 1 is 
calculated, arguing that hospitals cannot meaningfully comment on the 
methodology given the lack of details. In particular, this commenter 
asserted that the proposed rule neither provided sufficient details nor 
an explanation of the treatment of Medicaid expansions in the 
calculation for Factor 1.
    Response: We thank the commenters for their input. We disagree with 
commenters' assertion regarding the lack of transparency with respect 
to the methodology and assumptions used in the calculation of Factor 1. 
As explained in the FY 2023 IPPS/LTCH PPS proposed rule and in this 
section of this final rule, we have been and continue to be transparent 
about the methodology and data used to estimate Factor 1. Regarding the 
commenters who reference the Administrative Procedure Act, we note 
that, under the Administrative Procedure Act, a proposed rule is 
required to include either the terms or substance of the proposed rule 
or a description of the subjects and issues involved. In this case, the 
FY 2023 IPPS/LTCH PPS proposed rule did include a detailed discussion 
of our proposed Factor 1 methodology and the data sources that would be 
used in making our final estimate. Accordingly, we believe interested 
parties were able to meaningfully comment on our proposed estimate of 
Factor 1.
    To provide context, we note that Factor 1 is not estimated in 
isolation from other projections made by OACT. The Factor 1 estimates 
for the proposed rules are generally consistent with the economic 
assumptions and actuarial analyses used to develop the President's 
Budget estimates under current law, and the Factor 1 estimates for the 
final rule are generally consistent with those used for the Midsession 
Review of the President's Budget. As we have in the past, for 
additional information on the development of the President's Budget, we 
refer readers to the Office of Management and Budget website at: 
https://www.whitehouse.gov/omb/budget. For additional information on 
the specific economic assumptions used in the Midsession Review of the 
President's FY 2023 Budget, we refer readers to the ``Midsession Review 
of the President's FY 2023 Budget'' also available on the Office of 
Management and Budget website at: https://www.whitehouse.gov/omb/budget. We recognize that our reliance on the economic assumptions and 
actuarial analyses used to develop the President's Budget and the 
Midsession Review of the President's Budget in estimating Factor 1 has 
an impact on hospitals, health systems, and other impacted parties who 
wish to replicate the Factor 1 calculation, such as modeling the 
relevant Medicare Part A portion of the budget. Yet, we believe 
commenters are able to meaningfully comment on our proposed estimate of 
Factor 1 without replicating the budget.
    For a general overview of the principal steps involved in 
projecting future inpatient costs and utilization, we refer readers to 
the ``2022 Annual Report of the Boards of Trustees of the Federal 
Hospital Insurance and Federal Supplementary Medical Insurance Trust 
Funds'' available on the CMS website at: https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/ReportsTrustFunds/ under ``Downloads.'' We note that the 
annual reports of the Medicare Boards of Trustees to Congress represent 
the Federal Government's official evaluation of the financial status of 
the Medicare Program. The actuarial projections contained in these 
reports are based on numerous assumptions regarding future trends in 
program enrollment, utilization and costs of health care services 
covered by Medicare, as well as other factors affecting program 
expenditures. In addition, although the methods used to estimate future 
costs based on these assumptions are complex, they are subject to 
periodic review by independent experts to ensure their validity and 
reasonableness.
    We also refer readers to the 2018 Actuarial Report on the Financial 
Outlook for Medicaid which is available on the CMS website at: https://www.cms.gov/files/document/2018-report.pdf for a discussion of general 
issues regarding Medicaid projections. Additionally, as described in 
more detail later in this section, in the FY 2023 IPPS/LTCH PPS 
proposed rule, we included information regarding the data sources, 
methods, and assumptions employed by the actuaries in determining the 
OACT's estimate of Factor 1. In summary, we indicated the historical 
HCRIS data update OACT used to identify Medicare DSH payments. We 
explained that the most recent Medicare DSH payment adjustments 
provided in the IPPS Impact File were used, and we provided the 
components of all update factors that were applied to the historical 
data to estimate the Medicare DSH payments for the upcoming fiscal 
year, along with the associated rationale and assumptions. This 
discussion also included a description of the ``Other'' and 
``Discharges'' assumptions, as well as additional information regarding 
how we address Medicaid and CHIP expansion.
    For further information on our assumptions regarding Medicaid 
expansion in the Factor 1 calculation, we provide a discussion of more 
recent estimates and assumptions regarding the Medicaid expansion as 
part of the discussion of the final Factor 1 for FY 2023. This 
discussion also incorporates the estimated impact of the COVID-19 
public health emergency (PHE.)
    Comment: Many commenters questioned the proposed rule's estimate of 
the ``Discharge'' component of the Factor 1 calculation. Commenters 
requested clarity on the Factor 1 calculations, which assume small 
increases in discharge volume for FY 2022 and FY 2023.
    Commenters noted that they are seeing trends that indicate that FY 
2022 and FY 2023 discharge volumes, even though lower than pre-PHE 
levels, will continue to increase substantially. Some commenters urged 
CMS to reflect the same assumptions that the agency described in the 
``April 2022 Announcement of CY 2023 Medicare Advantage Capitation 
Rates and Part C and Part D Payment Policies,'' where the agency made 
assumptions that Medicare ``utilization will begin to rebound.'' Other 
commenters referenced a Kaufman Hall study, and stated that adjusted 
national patient volume has increased by 18 percent from February 2022 
to March 2022. A commenter referred to their own analysis of Medicare-
Fee-For-service (FFS) claims data from the Chronic Condition Warehouse 
(CCW), which indicated that non-COVID-19 inpatient hospital discharge 
volume increased 22 percent from February to March 2022. Other 
commenters provided anecdotal data from their own hospitals and service 
regions that show continued sustained volumes in 2022. These commenters 
urged CMS to carefully monitor changes in discharge volume when 
estimating Factor 1.
    Commenters also urged CMS to use a later update to the claims data 
to capture more of the increases in utilization that are anticipated 
for FY 2022. Commenters noted that the ``Discharge'' factor used by the 
OACT in estimating DSH expenditures was based on the December 2021 
update of the MedPAR file, which includes data impacted by the PHE from 
FY 2021 and the first three months of FY 2022. Some commenters 
requested that CMS adjust the data used in the Factor 1 calculation for 
COVID-19 PHE impacts while others suggested that CMS exclude data from 
the latter parts of CY 2021 and early CY

[[Page 49028]]

2022. Other commenters urged CMS to consider excluding FY 2020 and FY 
2021 discharges from the FY 2023 Factor 1 calculation, as data from 
those years include atypical trends in Medicare discharges due to the 
COVID-19 PHE.
    Commenters pointed out that omitting FY 2020 and FY 2021 data would 
be consistent with CMS' exclusion of FY 2020 data in setting FY 2022 
payment rates and the agency's proposal to exclude FY 2020 data from 
the per-discharge calculation in the FY 2023 IPPS/LTCH PPS proposed 
rule. Further, some commenters noted that the completion factor CMS 
used to estimate discharge volumes for FY 2021 and FY 2022 may not 
fully account for discharges due to billing delays as a result of PHE-
related staffing shortages.
    Finally, two commenters requested that for the FY 2024 IPPS/LTCH 
PPS proposed rule, CMS consider using the latest available data for the 
factors used to estimate Medicare DSH expenditures for purposes of 
calculating Factor 1 to avoid as much change in the estimate of Factor 
1 between the proposed and final rules for FY 2024.
    Some commenters also raised concerns about the ``Case Mix'' update 
factor used in the proposed FY 2023 Factor 1 calculation. Commenters 
stated that the proposed ``Case Mix'' update factor underestimates the 
complexity of patients returning to seek care following postponement or 
deferral of care during the COVID-19 PHE. Commenters also stated that 
CMS was using assumptions that are inconsistent with those that were 
used to develop the 2023 Medicare Advantage capitation payments, where 
the agency indicated an expectation that utilization will rebound in 
2022 and finalized a risk score increase of 3.5 percentage points with 
the underlying assumption that patients put off seeking medical care 
throughout the PHE. Other commenters cited data from Kaufman Hall that 
indicate that hospitals are beginning to see more complex patients as 
shown by a nearly 5 percent increase in the average hospital length of 
stay in 2022 as compared to 2021.
    Response: We thank the commenters for their input on the impact of 
the COVID-19 PHE on the factors used to estimate DSH payments for FY 
2023. In updating our estimate of Factor 1 for this final rule, we 
considered, as appropriate, the same set of factors that we used in the 
proposed rule, which reflects the impact of the COVID-19 PHE. We then 
updated estimates for the ``Discharges'' and ``Case Mix'' factors to 
incorporate the latest available data. We provide further details on 
the updated Factor 1 estimate and data sources as part of the 
discussion of the final Factor 1 estimate for FY 2023 in this section 
of the rule.
    Regarding the comments requesting that we exclude and/or mitigate 
the impacts of the COVID-19 PHE when estimating Factor 1 for FY 2023, 
we note that the statute specifies that Factor 1 is based on the amount 
of disproportionate share payments that would otherwise be made to 
subsection (d) hospitals for the fiscal year. As discussed further in 
this section, OACT's estimates of Medicare DSH payments used in the 
development of Factor 1, reflect the estimated impact of the COVID-19 
PHE on DSH payments during FY 2023.
    We also note that, with regard to the commenters' questions and 
concerns about the use of completion factors to adjust preliminary 
data, OACT assumed a discharge completion factor of 0 percent for FY 
2020 and 0 percent for FY 2021. We believe these assumptions are 
consistent with historical patterns of completion factors that have 
been determined for discharges and appropriately account for incomplete 
claims data. We do not believe that excluding data from certain periods 
is necessary to estimate DSH payments during FY 2023 for purposes of 
the Factor 1 calculation, as required by the statute.
    Regarding the comments requesting that CMS apply the same 
assumptions the agency made when setting Medicare Advantage payment 
rates, we note that Medicare Advantage and Medicare FFS are distinct 
programs. Accordingly, the estimates for the ``Discharges'' and ``Case 
Mix'' factors used to estimate Medicare DSH expenditures incorporate 
OACT's analyses of ``Discharges'' and ``Case Mix'' using only claims 
from the Medicare FFS program rather than claims from the Medicare 
Advantage program.
    In response to commenters' request that CMS use the latest 
available estimates of historical data to avoid as much change in the 
DSH Factor 1 estimate between the proposed and final rules for FY 2024, 
we believe that the use of the most recent available data at the time 
of the proposed and final rulemaking is appropriate to calculate Factor 
1 and consistent with our approach in previous rulemakings. In this 
final rule, OACT has updated the estimate of Factor 1 with more recent 
economic assumptions and actuarial analyses.
    Comment: Commenters expressed concern regarding the proposed $800 
million reduction in the amount available to make uncompensated care 
payments in FY 2023 compared to FY 2022. Commenters stated that this 
reduction does not align with CMS' objective to reduce healthcare 
inequities as the reduction disproportionately impacts safety-net 
hospitals, which primarily serve low income and vulnerable populations.
    Response: The statute specifies that Factor 1 is based on the 
amount of disproportionate share payments that would otherwise be made 
to subsection (d) hospitals for the fiscal year. Because our estimate 
of Factor 1 is based on the best available data regarding the amount of 
DSH payments that would otherwise be made during FY 2023, we believe it 
is appropriate and consistent with the requirements of the statute.
    After consideration of the public comments we received, we are 
finalizing, as proposed, the methodology for calculating Factor 1 for 
FY 2023. We discuss the resulting Factor 1 amount for FY 2023 in this 
section. For this final rule, OACT used the most recently submitted 
Medicare cost report data from the March 31, 2022, update of HCRIS to 
identify Medicare DSH payments and the most recent Medicare DSH payment 
adjustments provided in the Impact File published in conjunction with 
the publication of the FY 2023 IPPS/LTCH PPS final rule and applied 
update factors and assumptions for future changes in utilization and 
case-mix to estimate Medicare DSH payments for the upcoming fiscal 
year.
    The June 2022 OACT estimate for Medicare DSH payments for FY 2023, 
without regard to the application of section 1886(r)(1) of the Act, was 
approximately $13.949 billion. This estimate excluded Maryland 
hospitals participating in the Maryland All-Payer Model, hospitals 
participating in the Rural Community Hospital Demonstration, and SCHs 
paid under their hospital-specific payment rate. Therefore, based on 
this June 2022 estimate, the estimate of empirically justified Medicare 
DSH payments for FY 2023, with the application of section 1886(r)(1) of 
the Act, was approximately $3.487 billion (or 25 percent of the total 
amount of estimated Medicare DSH payments for FY 2023). Under Sec.  
412.106(g)(1)(i) of the regulations, Factor 1 is the difference between 
these two OACT estimates. Therefore, the final Factor 1 for FY 2023 is 
$10,461,731,029.40, which is equal to 75 percent of the total amount of 
estimated Medicare DSH payments for FY 2023 ($13,948,974,705.87 minus 
$3,487,243,676.47).
    The Office of the Actuary's estimates of DSH expenditures for FY 
2023 for this final rule began with a baseline of $13.814 billion in 
Medicare DSH

[[Page 49029]]

expenditures for FY 2019. The following table shows the factors applied 
to update this baseline through the current estimate for FY 2023:
[GRAPHIC] [TIFF OMITTED] TR10AU22.122

    In this table, the discharges column shows the changes in the 
number of Medicare fee-for-service (FFS) inpatient hospital discharges. 
The discharge figures for FY 2020 and FY 2021 are based on Medicare 
claims data that have been adjusted by a completion factor to account 
for incomplete claims data. We note that these claims data reflect the 
impact of the pandemic. The discharge figure for FY 2022 is based on 
preliminary data. The discharge figure for FY 2023 is an assumption 
based on recent trends recovering back to the long-term trend and 
assumptions related to how many beneficiaries will be enrolled in 
Medicare Advantage (MA) plans. The discharge figures for FY 2020 to FY 
2023 incorporate the actual impact and estimated future impact of the 
COVID-19 pandemic. The case-mix column shows the estimated change in 
case-mix for IPPS hospitals. The case-mix figures for FY 2020 and FY 
2021 are based on actual claims data adjusted by a completion factor. 
We note that these claims data reflect the impact of the pandemic. The 
case-mix figure for FY 2022 is based on preliminary data and the case-
mix figure for FY 2023 is an assumption based on recent trends 
recovering back to the long-term trend. The case-mix factor figures for 
FY 2020 to FY 2023 incorporate the actual impact and estimated future 
impact of the COVID-19 pandemic. The ``Other'' column shows the 
increase in other factors that contribute to the Medicare DSH 
estimates. These factors include the difference between the total 
inpatient hospital discharges and the IPPS discharges, and various 
adjustments to the payment rates that have been included over the years 
but are not reflected in the other columns (such as the change in rates 
for the 2-midnight stay policy and the 20 percent add-on for COVID-19 
discharges). In addition, the ``Other'' column includes a factor for 
the estimated changes in Medicaid enrollment. We note that this factor 
also includes the estimated impacts on Medicaid enrollment from the 
COVID-19 pandemic. We note that, based on the most recent available 
data, Medicaid enrollment is estimated to change as follows: 2.0 
percent in FY 2020, 9.5 percent in FY 2021, 4.2 percent in FY 2022, and 
-5.7 percent in FY 2023. In the future, the assumptions regarding 
Medicaid enrollment may change based on actual enrollment in the 
States.
    For a discussion of general issues regarding Medicaid projections, 
we refer readers to the 2018 Actuarial Report on the Financial Outlook 
for Medicaid, which is available on the CMS website at https://www.cms.gov/Research-Statistics-Data-and-Systems/Research/ActuarialStudies/MedicaidReport. We note that, in developing their 
estimates of the effect of Medicaid enrollment increases on Medicare 
DSH expenditures, our actuaries have assumed that the increases in the 
number of Medicaid enrollees result in increases in Medicare DSH 
expenditures at the same rate as historical relationships have shown. 
In the future, the assumption about the average per-capita expenditures 
of Medicaid beneficiaries who enrolled due to the COVID-19 pandemic may 
change, given that the pandemic is still ongoing.
    The following table shows the factors that are included in the 
``Update'' column of the previous table:
[GRAPHIC] [TIFF OMITTED] TR10AU22.123


[[Page 49030]]


2. Calculation of Factor 2 for FY 2023
(a) Background
    Section 1886(r)(2)(B) of the Act establishes Factor 2 in the 
calculation of the uncompensated care payment. Section 
1886(r)(2)(B)(ii) of the Act provides that, for FY 2018 and subsequent 
fiscal years, the second factor is 1 minus the percent change in the 
percent of individuals who are uninsured, as determined by comparing 
the percent of individuals who were uninsured in 2013 (as estimated by 
the Secretary, based on data from the Census Bureau or other sources 
the Secretary determines appropriate, and certified by the Chief 
Actuary of CMS) and the percent of individuals who were uninsured in 
the most recent period for which data are available (as so estimated 
and certified), minus 0.2 percentage point for FYs 2018 and 2019. In FY 
2020 and subsequent fiscal years, there is no longer a reduction. We 
note that, unlike section 1886(r)(2)(B)(i) of the Act, which governed 
the calculation of Factor 2 for FYs 2014, 2015, 2016, and 2017, section 
1886(r)(2)(B)(ii) of the Act permits the use of a data source other 
than the CBO estimates to determine the percent change in the rate of 
uninsurance beginning in FY 2018. In addition, for FY 2018 and 
subsequent years, the statute does not require that the estimate of the 
percent of individuals who are uninsured be limited to individuals who 
are under 65 years of age. We proposed to use a methodology similar to 
the one that was used in FY 2018 through FY 2022 to determine Factor 2 
for FY 2023.
    In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38197 and 38198), we 
explained that we determined the data source for the rate of 
uninsurance that, on balance, best meets all of our considerations and 
is consistent with the statutory requirement that the estimate of the 
rate of uninsurance be based on data from the Census Bureau or other 
sources the Secretary determines appropriate, is the uninsured 
estimates produced by OACT as part of the development of the National 
Health Expenditure Accounts (NHEA). The NHEA represents the 
government's official estimates of economic activity (spending) within 
the health sector. The information contained in the NHEA has been used 
to study numerous topics related to the health care sector, including, 
but not limited to, changes in the amount and cost of health services 
purchased and the payers or programs that provide or purchase these 
services; the economic causal factors at work in the health sector; the 
impact of policy changes, including major health reform; and 
comparisons to other countries' health spending. Of relevance to the 
determination of Factor 2 is that the comprehensive and integrated 
structure of the NHEA creates an ideal tool for evaluating changes to 
the health care system, such as the mix of the insured and uninsured, 
because this information is integral to the well-established NHEA 
methodology. A full description of the methodology used to develop the 
NHEA is available on the CMS website at https://www.cms.gov/files/document/definitions-sources-and-methods.pdf. We note that the NHEA 
estimates of uninsurance are for the total resident-based U.S. 
population, including all people who usually reside in the 50 States or 
the District of Columbia, but excluding individuals living in Puerto 
Rico and areas under U.S. sovereignty, members of the U.S. Armed Forces 
overseas, and U.S. citizens whose usual place of residence is outside 
the U.S., plus a small (typically less that 0.2 percent of population) 
adjustment to reflect Census undercounts. Thus, the NHEA estimates of 
uninsurance are for U.S. residents of all ages and are not limited to a 
specific age cohort, such as the population under the age of 65. As we 
explained in the FY 2018 IPPS/LTCH PPS proposed and final rules, we 
believe it is appropriate to use an estimate that reflects the rate of 
uninsurance in the U.S. across all age groups. In addition, we continue 
to believe that a resident-based population estimate more fully 
reflects the levels of uninsurance in the U.S. that influence 
uncompensated care for hospitals than an estimate that reflects only 
legal residents.
    The NHEA includes comprehensive enrollment estimates for total 
private health insurance (PHI) (including direct and employer-sponsored 
plans), Medicare, Medicaid, the Children's Health Insurance Program 
(CHIP), and other public programs, and estimates of the number of 
individuals who are uninsured. Estimates of total PHI enrollment are 
available for 1960 through 2020, estimates of Medicaid, Medicare, and 
CHIP enrollment are available for the length of the respective 
programs, and all other estimates (including the more detailed 
estimates of direct-purchased and employer-sponsored insurance) are 
available for 1987 through 2020. The NHEA data are publicly available 
on the CMS website at https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/NationalHealthExpendData/.
    In order to compute Factor 2, the first metric that is needed is 
the proportion of the total U.S. population that was uninsured in 2013. 
In developing the estimates for the NHEA, OACT's methodology included 
using the number of uninsured individuals for 1987 through 2009 based 
on the enhanced Current Population Survey (CPS) from the State Health 
Access Data Assistance Center (SHADAC). The CPS, sponsored jointly by 
the U.S. Census Bureau and the U.S. Bureau of Labor Statistics (BLS), 
is the primary source of labor force statistics for the population of 
the United States. (We refer readers to the website at https://www.census.gov/programs-surveys/cps.html.) The enhanced CPS, available 
from SHADAC (available at https://datacenter.shadac.org) accounts for 
changes in the CPS methodology over time. OACT further adjusts the 
enhanced CPS for an estimated undercount of Medicaid enrollees (a 
population that is often not fully captured in surveys that include 
Medicaid enrollees due to a perceived stigma associated with being 
enrolled in the Medicaid program or confusion about the source of their 
health insurance).
    To estimate the number of uninsured individuals for 2010 through 
2018, OACT extrapolates from the 2009 CPS data through 2018 using data 
from the National Health Interview Survey (NHIS). The NHIS is one of 
the major data collection programs of the National Center for Health 
Statistics (NCHS), which is part of the Centers for Disease Control and 
Prevention (CDC). The 2019 estimate was extrapolated using the 2019/
2018 trend from the American Community Survey (ACS). The 2020 estimate 
was extrapolated using the 2020/2018 trend from the CPS as published by 
the Census Bureau. The U.S. Census Bureau is the data collection agent 
for the NHIS, the ACS, and the CPS. The results from these data sources 
have been instrumental over the years in providing data to track health 
status, health care access, and progress toward achieving national 
health objectives. For further information regarding the NHIS, we refer 
readers to the CDC website at https://www.cdc.gov/nchs/nhis/index.htm. 
For further information regarding the ACS, we refer readers to the 
Census Bureau's website at https://www.census.gov/programs-surveys/acs/
. For information regarding the data collection issues regarding the 
2020 ACS, we refer readers to the Census Bureau's website at https://www.census.gov/newsroom/blogs/random-samplings/2021/10/pandemic-impact-on-2020-acs-1-year-data.html. Since the 2020 ACS data

[[Page 49031]]

were not available, the ACS data were not used for purposes of 
estimating the number of uninsured individuals for 2020.
    The next metrics needed to compute Factor 2 for FY 2023 are 
projections of the rate of uninsurance in both CY 2022 and CY 2023. On 
an annual basis, OACT projects enrollment and spending trends for the 
coming 10-year period. The most recent projections are for 2021 through 
2030. Those projections use the latest NHEA historical data, available 
at the time of their construction. The NHEA projection methodology 
accounts for expected changes in enrollment across all of the 
categories of insurance coverage previously listed. The projected 
growth rates in enrollment for Medicare, Medicaid, and CHIP are 
developed to be consistent with the 2021 Medicare Trustees Report, 
updated where possible with more recent data. Projected rates of growth 
in enrollment for private health insurance and the uninsured are based 
largely on OACT's econometric models, which rely on a set of 
macroeconomic assumptions that are generally based on the 2021 Medicare 
Trustees Report. Greater detail can be found in OACT's report titled 
``Projections of National Health Expenditure: Methodology and Model 
Specification,'' which is available on the CMS website at https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/NationalHealthExpendData/Downloads/ProjectionsMethodology.pdf.
(b) Factor 2 for FY 2023
    As discussed in the FY 2023 IPPS/LTCH PPS proposed rule, using 
these data sources and the previously described methodologies, OACT 
estimated that the uninsured rate for the historical, baseline year of 
2013 was 14 percent and for CYs 2022 and 2023 is 8.9 percent and 9.3 
percent, respectively. As required by section 1886(r)(2)(B)(ii) of the 
Act, the Chief Actuary of CMS has certified these estimates. We refer 
readers to OACT's Memorandum on Certification of Rates of Uninsured 
prepared for the FY 2023 IPPS/LTCH PPS proposed rule for further 
details on the methodology and assumptions that were used in the 
projection of these rates of uninsurance.\213\
---------------------------------------------------------------------------

    \213\ OACT Memorandum on Certification of Rates of Uninsured. 
March 28, 2022. Available at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInPatientPPS/dsh.html.
---------------------------------------------------------------------------

    As with the CBO estimates on which we based Factor 2 for fiscal 
years before FY 2018, the NHEA estimates are for a calendar year. Under 
the approach originally adopted in the FY 2014 IPPS/LTCH PPS final 
rule, we have used a weighted average approach to project the rate of 
uninsurance for each fiscal year. We continue to believe that, in order 
to estimate the rate of uninsurance during a fiscal year accurately, 
Factor 2 should reflect the estimated rate of uninsurance that 
hospitals will experience during the fiscal year, rather than the rate 
of uninsurance during only one of the calendar years that the fiscal 
year spans. Accordingly, we proposed to continue to apply the weighted 
average approach used in past fiscal years in order to estimate the 
rate of uninsurance for FY 2023.
    The OACT certified the estimate of the rate of uninsurance for FY 
2023 determined using this weighted average approach to be reasonable 
and appropriate for purposes of section 1886(r)(2)(B)(ii) of the Act. 
In the FY 2023 IPPS/LTCH PPS proposed rule, we noted that we might also 
consider the use of more recent data that might become available for 
purposes of estimating the rates of uninsurance used in the calculation 
of the final Factor 2 for FY 2023. In the proposed rule, we outlined 
the calculation of the proposed Factor 2 for FY 2023 as follows:
    Percent of individuals without insurance for CY 2013: 14 percent.
    Percent of individuals without insurance for CY 2022: 8.9 percent.
    Percent of individuals without insurance for CY 2023: 9.3 percent.
    Percent of individuals without insurance for FY 2023 (0.25 times 
0.089) + (0.75 times 0.093): 9.2 percent.
    1- [verbar]((0.092-0.14)/0.14)[verbar] = 1-0.3429 = 0.6571 (65.71 
percent).
    For FY 2020 and subsequent fiscal years, section 1886(r)(2)(B)(ii) 
of the Act no longer includes any reduction to the previous calculation 
in order to determine Factor 2. Therefore, we proposed that Factor 2 
for FY 2023 would be 65.71 percent.
    The proposed FY 2023 uncompensated care amount was 
$9,949,258,556.56 * 0.6571 = $6,537,657,797.52.
[GRAPHIC] [TIFF OMITTED] TR10AU22.124

    In addition, we stated that it had recently come to our attention 
that the provision of the regulations that addresses Factor 2 
inadvertently omits any reference to the statutory methodology in 
section 1886(r)(2)(B)(ii) of the Act for determining Factor 2 for FY 
2018 and subsequent fiscal years. Accordingly, we proposed a technical 
change to the regulation at Sec.  412.106 to update paragraph 
(g)(1)(ii) to reflect the statutory requirements governing the 
determination of Factor 2 for FY 2018 and subsequent fiscal years. We 
explained that we have determined Factor 2 for FY 2018 through FY 2022 
consistent with the plain language of section 1886(r)(2)(B)(ii) of the 
Act; therefore, this proposed technical change is intended merely to 
update our regulations to reflect the methodology for determining 
Factor 2 that has applied since FY 2018 and will continue to apply for 
FY 2023 and subsequent fiscal years.
    We invited public comments on our proposed Factor 2 for FY 2023 and 
on the proposed technical change to the regulation at Sec.  
412.106(g)(1)(ii).
    Comment: The majority of commenters discussed Factor 2 in the 
context of the impact of the temporary COVID-19 PHE provisions, such as 
the Families First Coronavirus Response Act's Medicaid continuous 
coverage requirement and the American Rescue Plan's Marketplace 
enhanced premium tax credits, on the uninsured rate for FY 2023. 
Commenters questioned CMS' estimates for the FY 2023 uninsured rate and 
urged the Office of the Actuary (OACT) to update its estimate of Factor 
2 to account for the projected increases in the number of uninsured as 
the COVID-19 PHE provisions expire. Many commenters questioned CMS' 
estimated decrease in the uninsured rate from 9.6 percent in the FY 
2022 IPPS/LTCH PPS final rule to 9.2 percent in FY 2023 IPPS/LTCH PPS 
proposed rule and stated that they expect increases in the uninsured 
rates in their communities. Further, many commenters noted that the 
proposed decrease of $800 million in uncompensated care payments from 
the level in FY 2022 was likely, in part, driven by the projected 
uninsured rate. To that end, commenters cited CMS'

[[Page 49032]]

statement in the proposed rule that the agency might consider more 
recent data that may have become available for the calculation of 
Factor 2 in FY 2023 and urged CMS to use more recent data sources to 
account for the anticipated increase in the uninsured rate. One 
commenter requested that CMS consider temporarily changing its 
methodology for calculating Factor 2 to better account for individuals 
who may lose their healthcare coverage when various PHE provisions 
expire and noted that CMS has taken similar approaches in other 
Medicare payment areas affected by the COVID-19 PHE.
    Many commenters referenced various data sources and analyses, such 
as the Kaiser Family Foundation, the Urban Institute, and HHS' 
Assistant Secretary for Planning and Evaluation (ASPE) which project 5 
to 16 million individuals will lose their Medicaid coverage and another 
3 million additional individuals will lose their marketplace insurance 
in FY 2023. Accordingly, these commenters requested that CMS increase 
Factor 2 to reflect the anticipated increase in the uninsured 
population as suggested by these sources. In addition, one commenter 
requested that CMS exclude FY 2020 and FY 2021 data when calculating 
the uninsured rate to eliminate any irregularities due to the COVID-19 
PHE.
    Response: We thank the commenters for their input regarding the 
estimate of Factor 2 for FY 2023 included in the proposed rule. In 
response to commenters who requested that we update the estimate of the 
FY 2023 uninsured rate to fully consider any changes due to the 
anticipated expirations of the PHE and the Marketplace premium tax 
credits, we note that the rate of uninsurance used for the calculation 
of Factor 2 for the proposed rule, as well as for this final rule, 
reflects CMS' latest analyses and projections. The projected enrollment 
trends across all insurance types, as well as for the uninsured, take 
into account the expected impacts of current law including the 
termination of the Families First Coronavirus Response Act's continuous 
coverage provision for Medicaid (assumed to expire when the PHE ends in 
2022 and to be accompanied by a one-year transition of disenrollments 
from the program for those no longer eligible) and the conclusion of 
the enhanced Marketplace premium tax credits. We believe that this NHEA 
projection, on balance, best meets all of our considerations for 
ensuring that the data source that underlies the Factor 2 calculation 
of the uninsured rate meets the statutory requirement that the estimate 
be based on data sources that the Secretary determines to be 
appropriate, is certified by CMS' Chief Actuary, and provides a 
reasonable estimate for the rate of uninsurance that is available in 
conjunction with the IPPS rulemaking cycle. We refer readers to OACT's 
memorandum ``Certification of Rates of Uninsured'' and OACT's report 
titled ``Projections of National Health Expenditure: Methodology and 
Model Specification'' for further details on the methodology and 
updated assumptions used in the calculation of the projected uninsured 
rate.
    We disagree with comments' suggestions that we exclude FY 2020 and 
FY 2021 data, or any data from the COVID-19 PHE period, for purposes of 
calculating the uninsured rate for FY 2023. The projections that 
underlie the FY 2023 Factor 2 calculation should take into 
consideration, and include, those elements that are expected to 
influence health insurance enrollment trends during FY 2023, and the 
resulting rate of uninsured, including the unique circumstance 
associated with the COVID-19 pandemic.
    Comment: Some commenters suggested that CMS use a different 
estimate of the uninsured rate to calculate Factor 2 for FY 2023, while 
acknowledging that OACT accounted for the expiration of the COVID-19 
PHE provisions in its uninsurance estimates. These commenters indicated 
that because the uninsured percent change serves as a proxy for the 
change in the amount of uncompensated care that hospitals provide, it 
would be appropriate for CMS to apply a case-mix adjuster to the 
uninsured rate for FY 2023 to account for the rise in resources that 
will be used by hospitals to provide care to uninsured individuals who 
may have delayed their care during the COVID-19 PHE.
    A few commenters requested that CMS maintain the same level of 
uncompensated care funding as in FY 2022 ($7.2 billion) while another 
commenter requested that CMS consider delaying any proposed changes to 
the uncompensated care payment calculations until analyses can be 
performed to determine the actual uninsured rate and related costs 
following the end of the COVID-19 PHE. Other commenters urged CMS to be 
transparent in its calculation of Factor 2 and how it accounts for 
Medicaid expansion populations, while others urged CMS to be 
transparent regarding the data sources used for calculating Factor 2 
and the assumptions behind the uninsured rate.
    Response: Regarding the commenters that requested modifications to 
the uninsured rate, such as multiplying by a case-mix factor, we note 
that these recommendations would not be consistent with the statutory 
requirements in section 1886(r)(2)(B)(ii). The statute explicitly 
specifies that Factor 2 be based on 1 minus the percent change in the 
percent of individuals who are uninsured, as determined by comparing 
the percent of individuals who were uninsured in 2013 and the percent 
of individuals who were uninsured in the most recent period for which 
data are available.
    Regarding the comments recommending that CMS maintain total 
uncompensated care payments at the FY 2022 level or delay any changes 
to the amount available to make uncompensated care payments, we believe 
estimating Factor 2 based on the best available data regarding the 
expected rate of uninsurance in FY 2023 is appropriate and consistent 
with the statute.
    In response to the comments concerning transparency, we reiterate 
that we have been and continue to be transparent with respect to the 
methodology and data used to estimate Factor 2. The FY 2023 IPPS/LTCH 
PPS proposed rule included a detailed discussion of our proposed Factor 
2 methodology, as well as the data sources that would be used in making 
our final estimate. For purposes of this final rule, we are using 
projected rates of uninsurance for CY 2022 and CY 2023, which account 
for the effects of the COVID-19 PHE and any legislative impacts arising 
from the end of the COVID-19 PHE on insurance coverage. Section 
1886(r)(2)(B)(ii) of the Act permits us to use a data source other than 
CBO estimates to determine the percent change in the rate of 
uninsurance beginning in FY 2018. We continue to believe that the NHEA 
data and methodology used to estimate Factor 2 are transparent and best 
meet all of our considerations for ensuring reasonable estimates for 
the rate of uninsurance that are available in conjunction with the IPPS 
rulemaking cycle. Accordingly, we continue to believe that it is 
appropriate to calculate Factor 2 based on the NHEA-based projection of 
the FY 2023 rate of uninsurance as we proposed.
    After consideration of the public comments we received, we are 
finalizing, as proposed, the Factor 2 calculation for FY 2023. The 
estimates of the percent of uninsured individuals were produced and 
certified by OACT for purposes of the FY 2023 IPPS proposed rule. Those 
published CY and

[[Page 49033]]

estimated FY rates continue to be the latest available projections.
    The calculation of the final Factor 2 for FY 2023 using a weighted 
average of OACT's certified estimates is as follows:
    Percent of individuals without insurance for CY 2013: 14 percent.
    Percent of individuals without insurance for CY 2022: 8.9 percent.
    Percent of individuals without insurance for CY 2023: 9.3 percent.
    Percent of individuals without insurance for FY 2023 (0.25 times 
0.089) + (0.75 times 0.093): 9.2 percent.
    1- [verbar]((0.092-0.14)/0.14)[verbar] = 1-0.3429 = 0.6571 (65.71 
percent).
    Therefore, the final Factor 2 for FY 2023 is 65.71 percent. The 
final FY 2023 uncompensated care amount is $10,461,731,029.40* 0.6571 = 
$6,874,403,459.42.
[GRAPHIC] [TIFF OMITTED] TR10AU22.125

    We did not receive any comments on our proposed technical change to 
the regulation governing the calculation of Factor 2. We are finalizing 
the update to Sec.  412.106(g)(1)(ii), as proposed.
3. Calculation of Proposed Factor 3 for FY 2023
(a) General Background
    Section 1886(r)(2)(C) of the Act defines Factor 3 in the 
calculation of the uncompensated care payment. As we have discussed 
earlier, section 1886(r)(2)(C) of the Act states that Factor 3 is equal 
to the percent, for each subsection (d) hospital, that represents the 
quotient of: (1) the amount of uncompensated care for such hospital for 
a period selected by the Secretary (as estimated by the Secretary, 
based on appropriate data (including, in the case where the Secretary 
determines alternative data are available that are a better proxy for 
the costs of subsection (d) hospitals for treating the uninsured, the 
use of such alternative data)); and (2) the aggregate amount of 
uncompensated care for all subsection (d) hospitals that receive a 
payment under section 1886(r) of the Act for such period (as so 
estimated, based on such data).
    Therefore, Factor 3 is a hospital-specific value that expresses the 
proportion of the estimated uncompensated care amount for each 
subsection (d) hospital and each subsection (d) Puerto Rico hospital 
with the potential to receive Medicare DSH payments relative to the 
estimated uncompensated care amount for all hospitals estimated to 
receive Medicare DSH payments in the fiscal year for which the 
uncompensated care payment is to be made. Factor 3 is applied to the 
product of Factor 1 and Factor 2 to determine the amount of the 
uncompensated care payment that each eligible hospital will receive for 
FY 2014 and subsequent fiscal years. In order to implement the 
statutory requirements for this factor of the uncompensated care 
payment formula, it was necessary to determine: (1) the definition of 
uncompensated care or, in other words, the specific items that are to 
be included in the numerator (that is, the estimated uncompensated care 
amount for an individual hospital) and the denominator (that is, the 
estimated uncompensated care amount for all hospitals estimated to 
receive Medicare DSH payments in the applicable fiscal year); (2) the 
data source(s) for the estimated uncompensated care amount; and (3) the 
timing and manner of computing the quotient for each hospital estimated 
to receive Medicare DSH payments. The statute instructs the Secretary 
to estimate the amounts of uncompensated care for a period based on 
appropriate data. In addition, we note that the statute permits the 
Secretary to use alternative data in the case where the Secretary 
determines that such alternative data are available that are a better 
proxy for the costs of subsection (d) hospitals for treating 
individuals who are uninsured.
    In the course of considering how to determine Factor 3 during the 
rulemaking process for FY 2014, the first year for which section 
1886(r) of the Act was in effect, we considered defining the amount of 
uncompensated care for a hospital as the uncompensated care costs of 
that hospital and determined that Worksheet S-10 of the Medicare cost 
report would potentially provide the most complete data regarding 
uncompensated care costs for Medicare hospitals. However, because of 
concerns regarding variations in the data reported on Worksheet S-10 
and the completeness of these data, we did not use Worksheet S-10 data 
to determine Factor 3 for FY 2014, or for FYs 2015, 2016, or 2017. 
Instead, we used alternative data on the utilization of insured low-
income patients, as measured by patient days, which we believed would 
be a better proxy for the costs of hospitals in treating the uninsured 
and therefore appropriate to use in calculating Factor 3 for these 
years. Of particular importance in our decision to use proxy data was 
the relative newness of Worksheet S-10, which went into effect on May 
1, 2010. At the time of the rulemaking for FY 2014, the most recent 
available cost reports would have been from FYs 2010 and 2011 and 
submitted on or after May 1, 2010, when the new Worksheet S-10 went 
into effect. However, we indicated our belief that Worksheet S-10 could 
ultimately serve as an appropriate source of more direct data regarding 
uncompensated care costs for purposes of determining Factor 3 once 
hospitals were submitting more accurate and consistent data through 
this reporting mechanism.
    In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38202), we stated 
that we could no longer conclude that alternative data to the Worksheet 
S-10 are available for FY 2014 that are a better proxy for the costs of 
subsection (d) hospitals for treating individuals who are uninsured. 
Hospitals were on notice as of FY 2014 that Worksheet S-10 could 
eventually become the data source for CMS to calculate uncompensated 
care payments. Furthermore, hospitals' cost reports from FY 2014 had 
been publicly available for some time, and CMS had analyses of 
Worksheet S-10, conducted both internally and by stakeholders, 
demonstrating that Worksheet S-10 accuracy had improved over time. We 
refer readers to the FY 2018 IPPS/LTCH PPS final rule (82 FR 38201 
through 38203) for a complete discussion of these analyses.
    In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38206), we 
recognized commenters' concerns that, in continuing to use Medicaid 
days as part of the proxy for uncompensated care, it would be possible 
for hospitals in States that choose to expand Medicaid to receive 
higher uncompensated care payments because they may have more Medicaid 
patient days than hospitals in a State that does not choose to expand 
Medicaid. In the FY 2018 IPPS/LTCH PPS final rule, we finalized a 
methodology under which we calculated Factor 3 for all eligible 
hospitals, with the exception of Puerto Rico hospitals and Indian 
Health Service (IHS) and Tribal hospitals, using Worksheet S-10 data 
from FY 2014 cost

[[Page 49034]]

reports in conjunction with low-income insured days proxy data based on 
Medicaid days and SSI days. The time period for the Medicaid days data 
was FY 2012 and FY 2013 cost reports, which reflected the most recent 
available information regarding these hospitals' low-income insured 
days before any expansion of Medicaid (82 FR 38208 through 38212).
    In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41414), we stated 
that with the additional steps we had taken to ensure the accuracy and 
consistency of the data reported on Worksheet S-10 since the 
publication of the FY 2018 IPPS/LTCH PPS final rule, we continued to 
believe that we could no longer conclude that alternative data to the 
Worksheet S-10 were currently available for FY 2014 or FY 2015 that 
would be a better proxy for the costs of subsection (d) hospitals for 
treating individuals who are uninsured. In the FY 2019 IPPS/LTCH PPS 
final rule (83 FR 41428), we advanced the time period of the data used 
in the calculation of Factor 3 forward by 1 year and used Worksheet S-
10 data from FY 2014 and FY 2015 cost reports in combination with the 
low income insured days proxy for FY 2013 to determine Factor 3 for FY 
2019. We note that, as discussed in the FY 2020 IPPS/LTCH PPS final 
rule (84 FR 42366), the use of 3 years of data to determine Factor 3 
for FY 2018 and FY 2019 had the effect of smoothing the transition from 
the use of low-income insured days to the use of Worksheet S-10 data.
    As discussed in the FY 2019 IPPS/LTCH PPS final rule (83 FR 41424), 
we received overwhelming feedback from commenters emphasizing the 
importance of audits in ensuring the accuracy and consistency of data 
reported on the Worksheet S-10. We began auditing the Worksheet S-10 
data for selected hospitals in the Fall of 2018 so that the audited 
uncompensated care data from these hospitals would be available in time 
for use in the FY 2020 IPPS/LTCH PPS proposed rule.
    In the FY 2020 IPPS/LTCH PPS final rule (84 FR 42368), we finalized 
our proposal to use a single year of audited Worksheet S-10 cost report 
data from FY 2015 in the methodology for determining Factor 3 for FY 
2020. Although some commenters expressed support for the alternative 
policy of using the more recent FY 2017 Worksheet S-10 data to 
determine each hospital's share of uncompensated care costs in FY 2020, 
given the feedback from commenters in response to both the FY 2019 and 
FY 2020 IPPS/LTCH PPS proposed rules, emphasizing the importance of 
audits in ensuring the accuracy and consistency of data reported on the 
Worksheet S-10, we concluded that the FY 2015 Worksheet S-10 data were 
the best available audited data to be used in determining Factor 3 for 
FY 2020. We also noted that we had begun auditing the FY 2017 data in 
July 2019, with the goal of having the FY 2017 audited data available 
for future rulemaking.
    In the FY 2021 IPPS/LTCH PPS final rule (85 FR 58823 through 
58825), we finalized our proposal to use the most recent available 
single year of audited Worksheet S-10 data to determine Factor 3 for FY 
2021 and subsequent fiscal years. We explained our belief that using 
the most recent audited data available before the applicable Federal 
fiscal year, will more accurately reflect a hospital's uncompensated 
care costs, as opposed to averaging multiple years of data. We 
explained that mixing audited and unaudited data for individual 
hospitals by averaging multiple years of data could potentially lead to 
a less smooth result. We also noted that if a hospital has relatively 
different data between cost report years, we potentially would be 
diluting the effect of our considerable auditing efforts and 
introducing unnecessary variability into the calculation if we were to 
use multiple years of data to calculate Factor 3. Therefore, we also 
believed using a single year of audited cost report data would be an 
appropriate methodology to determine Factor 3 for FY 2021 and 
subsequent years, except for IHS and Tribal hospitals and hospitals 
located in Puerto Rico. For IHS and Tribal hospitals and Puerto Rico 
hospitals, we finalized the use of a low-income insured days proxy to 
determine Factor 3 for FY 2021. We did not finalize a methodology to 
determine Factor 3 for IHS and Tribal hospitals and Puerto Rico 
hospitals for FY 2022 and subsequent years because we believed further 
consideration and review of these hospitals' Worksheet S-10 data was 
necessary (85 FR 58825).
    In the FY 2021 IPPS/LTCH PPS final rule, we finalized the 
definition of ``uncompensated care'' for FY 2021 and subsequent fiscal 
years, for purposes of determining uncompensated care costs and 
calculating Factor 3 (85 FR 58825 through 58828). Specifically, 
``uncompensated care'' is defined as the amount on Line 30 of Worksheet 
S-10, which is the cost of charity care (Line 23) and the cost of non-
Medicare bad debt and non-reimbursable Medicare bad debt (Line 29). 
This is the same definition that we initially adopted in the FY 2018 
IPPS/LTCH PPS final rule. We refer readers to the FY 2021 IPPS/LTCH PPS 
rule (85 FR 58825 through 58828) for a discussion of additional topics 
related to the definition of uncompensated care. We noted in the FY 
2021 IPPS/LTCH PPS final rule that the Paper Reduction Act (PRA) 
package for Form CMS-2552-10 would offer an additional opportunity to 
comment on the cost reporting instructions. A PRA package with comment 
period appeared in the November 10, 2020, Federal Register (85 FR 
71653). We thank stakeholders for their comments on the PRA package. 
For further information, we refer the readers to the following website. 
https://www.reginfo.gov/public/do/PRAViewDocument?ref_nbr=202206-0938-017.
(b) Background on the Methodology Used To Calculate Factor 3 for FY 
2022
    Section 1886(r)(2)(C) of the Act governs both the selection of the 
data to be used in calculating Factor 3, and also allows the Secretary 
the discretion to determine the time periods from which we will derive 
the data to estimate the numerator and the denominator of the Factor 3 
quotient. Specifically, section 1886(r)(2)(C)(i) of the Act defines the 
numerator of the quotient as the amount of uncompensated care for a 
subsection (d) hospital for a period selected by the Secretary. Section 
1886(r)(2)(C)(ii) of the Act defines the denominator as the aggregate 
amount of uncompensated care for all subsection (d) hospitals that 
receive a payment under section 1886(r) of the Act for such period. In 
the FY 2014 IPPS/LTCH PPS final rule (78 FR 50638), we adopted a 
process of making interim payments with final cost report settlement 
for both the empirically justified Medicare DSH payments and the 
uncompensated care payments required by section 3133 of the Affordable 
Care Act. Consistent with that process, we also determined the time 
period from which to calculate the numerator and denominator of the 
Factor 3 quotient in a way that would be consistent with making interim 
and final payments. Specifically, we must have Factor 3 values 
available for hospitals that we estimate will qualify for Medicare DSH 
payments and for those hospitals that we do not estimate will qualify 
for Medicare DSH payments but that may ultimately qualify for Medicare 
DSH payments at the time of cost report settlement.
    In the FY 2022 IPPS/LTCH PPS final rule, we continued to apply the 
following policies as part of the Factor 3 methodology: (1) the policy 
regarding newly merged hospitals that was initially adopted in the FY 
2015 IPPS/LTCH PPS final rule; (2) the policies regarding annualization 
and long cost reports that were adopted in the FY

[[Page 49035]]

2018 and FY 2019 IPPS/LTCH PPS final rules, including a modified policy 
for the rare cases where a provider has no cost report for the fiscal 
year that is used in the Factor 3 methodology because the cost report 
for the previous fiscal year spans both years; (3) the modified new 
hospital policy that was finalized in the FY 2020 IPPS/LTCH PPS final 
rule; (4) the new merger policy adopted in the FY 2021 IPPS/LTCH PPS 
final rule that accounts for the merger effective date; and (5) the 
policies regarding the application of statistical trim methodologies to 
potentially aberrant CCRs and potentially aberrant uncompensated care 
costs reported on the Worksheet S-10. We discuss these policies in 
greater detail in this section.
    In the FY 2022 IPPS/LTCH PPS final rule (86 FR 45244), we continued 
to treat hospitals that merge after the development of the final rule 
for the applicable fiscal year similar to new hospitals. As explained 
in the FY 2015 IPPS/LTCH PPS final rule, for these newly merged 
hospitals, we do not have data currently available to calculate a 
Factor 3 amount that accounts for the merged hospital's uncompensated 
care burden (79 FR 50021). In the FY 2015 IPPS/LTCH PPS final rule, we 
finalized a policy under which Factor 3 for hospitals that we do not 
identify as undergoing a merger until after the public comment period 
and additional review period following the publication of the final 
rule or that undergo a merger during the fiscal year would be 
recalculated similar to new hospitals (79 FR 50021 and 50022). 
Consistent with past policy, interim uncompensated care payments for 
newly merged hospitals are based only on the data for the surviving 
hospital's CCN available at the time of the development of the final 
rule. However, at cost report settlement, we will determine the newly 
merged hospital's final uncompensated care payment based on the 
uncompensated care costs reported on its cost report for the applicable 
fiscal year. That is, for FY 2022, we will revise the numerator of 
Factor 3 for a newly merged hospital to reflect the uncompensated care 
costs reported on the newly merged hospital's FY 2022 cost report.
    In FY 2022 IPPS/LTCH PPS final rule, we continued the policy that 
was finalized in the FY 2018 IPPS/LTCH PPS final rule of annualizing 
uncompensated care cost data reported on the Worksheet S-10 if a 
hospital's cost report does not equal 12 months of data, except in the 
case of mergers, which would be subject to the modified merger policy 
originally adopted in FY 2021. In addition, we continued the policies 
that were finalized in the FY 2019 IPPS/LTCH PPS final rule (83 FR 
41415) regarding the use of the longest cost report available within 
the Federal fiscal year. We also applied the modified policy that was 
adopted in the FY 2021 IPPS/LTCH PPS final rule (85 FR 58829) for those 
rare situations where a hospital has a cost report that starts in one 
fiscal year but spans the entirety of the following fiscal year such 
that the hospital has no cost report starting in that subsequent fiscal 
year. Under this modified policy, we use the cost report that spans 
both fiscal years for purposes of calculating Factor 3 when data from 
the latter fiscal year are used in the Factor 3 methodology.
    In the FY 2022 IPPS/LTCH PPS final rule (86 FR 25454), we continued 
the modified new hospital policy for new hospitals that do not have 
data for the cost reporting period(s) used in the Factor 3 calculation 
(that is, the most recent cost reporting year for which audits have 
been conducted). Under the modified policy originally adopted for FY 
2020, new hospitals that have a preliminary projection of being 
eligible for Medicare DSH based on their most recent available 
disproportionate patient percentages may receive interim empirically 
justified DSH payments during the fiscal year. However, because these 
hospitals do not have a cost report for the cost reporting period used 
in the Factor 3 calculation and the projection of eligibility for DSH 
payments is still preliminary, we are unable to calculate a prospective 
Factor 3 for these hospitals and they do not receive interim 
uncompensated care payments. The MAC will make a final determination 
concerning whether the hospital is eligible to receive Medicare DSH 
payments for the fiscal year at cost report settlement. Thus, for FY 
2022, if a new hospital is ultimately determined to be eligible for 
Medicare DSH payments for FY 2022, the hospital will receive an 
uncompensated care payment calculated using a Factor 3, where the 
numerator is the uncompensated care costs reported on Worksheet S-10 of 
the hospital's FY 2022 cost report, and the denominator is the same 
denominator that was used in the prospective Factor 3 calculation for 
FY 2022 (that is, the sum of the uncompensated care costs reported on 
Worksheet S-10 of the FY 2018 cost reports for all DSH-eligible 
hospitals).
    In the FY 2022 IPPS/LTCH PPS final rule, we continued the new 
merger policy that accounts for the merger effective date, that was 
originally adopted in FY 2021. To more accurately estimate 
uncompensated care costs (UCC) for the hospitals involved in a merger 
when the merger effective date occurs partway through the surviving 
hospital's cost reporting period, we apply a policy of not annualizing 
the acquired hospital's data. Under this policy, we use only the 
portion of the acquired hospital's unannualized UCC data that reflects 
the UCC incurred prior to the merger effective date, but after the 
start of the surviving hospital's current cost reporting period. To do 
this, we calculate a multiplier to be applied to the acquired 
hospital's UCC. This multiplier represents the portion of the UCC data 
from the acquired hospital that should be incorporated with the 
surviving hospital's data to determine UCC for purposes of determining 
Factor 3 for the surviving hospital. This multiplier is obtained by 
calculating the number of days between the start of the applicable cost 
reporting period for the surviving hospital and the merger effective 
date, and then dividing this result by the total number of days in the 
reporting period of the acquired hospital. Applying this multiplier to 
the acquired hospital's unannualized UCC data will determine the final 
portion of the acquired hospital's UCC that should be added to the UCC 
of the surviving hospital for purposes of determining Factor 3 for the 
merged hospital.
    In the FY 2022 IPPS/LTCH PPS final rule (86 FR 25454 and 25455), we 
continued to apply a CCR trim methodology similar to the CCR trim 
methodology policy that has been used for purposes of determining 
uncompensated care payments since FY 2018. This CCR trim methodology is 
consistent with the approach used in the outlier payment methodology 
under Sec.  412.84(h)(3)(ii), which states that the Medicare contractor 
may use a statewide average CCR for hospitals whose operating or 
capital CCR is in excess of 3 standard deviations above the 
corresponding national geometric mean. We refer readers to the 
discussion in the FY 2021 IPPS/LTCH PPS final rule (85 FR 58831) for a 
detailed description of the steps used to determine the applicable CCR.
    In addition, we continued the UCC data trim methodology for rare 
situations where a hospital has potentially aberrant data that are 
unrelated to its CCR (86 FR 45245). However, because we audit the 
Worksheet S-10 data for a number of hospitals, we no longer believe it 
is necessary to apply the trim methodology for hospitals whose cost 
report has been audited. Accordingly, for FY 2022, we continued the 
policy adopted in FY 2021 under which we exclude hospitals that were 
part of the audits for the fiscal year used in the Factor 3 calculation 
from the trim

[[Page 49036]]

methodology for potentially aberrant UCC. We also continued to apply a 
modified trim methodology for all-inclusive rate providers (AIRPs) with 
potentially aberrant UCC (86 FR 45235). Under this modified trim 
methodology, when an AIRP's total UCC are greater than 50 percent of 
its total operating costs when calculated using the CCR included on its 
cost report for the most recent cost reporting year for which audits 
have been conducted, we recalculate the AIRP's UCC using the CCR 
reported on Worksheet S-10, line 1 of the hospital's most recent 
available prior year cost report that does not result in UCC of over 50 
percent of total operating costs.
    In addition, in the FY 2022 IPPS/LTCH PPS final rule (86 FR 45245 
and 452456), we finalized an alternative trim specific to hospitals 
that are not projected to be DSH-eligible and that do not have audited 
FY 2018 Worksheet S-10 data for use in determining Factor 3. We 
explained that we believe this new alternative trim more appropriately 
addresses potentially aberrant insured patient charity care costs 
compared to the existing trim, because the existing trim is based 
solely on the ratio of total uncompensated care costs to total 
operating costs and does not consider the level of insured patients' 
charity care costs. Specifically, we finalized that, for the hospitals 
that would be subject to the trim, if the hospital is ultimately 
determined to be DSH-eligible at cost report settlement, then the MAC 
would calculate a Factor 3 after reviewing the uncompensated care 
information reported on Worksheet S-10 of the hospital's FY 2022 cost 
report. We stated that we believe if a hospital subject to this trim is 
ultimately determined to be DSH-eligible at cost report settlement, its 
uncompensated care payment should be calculated only after the 
hospital's reporting of insured charity care costs on its FY 2022 
Worksheet S-10 has been reviewed. We noted that this approach is 
comparable to the policy for new hospitals for which we cannot 
calculate a prospective Factor 3 because they do not have Worksheet S-
10 data for the relevant fiscal year.
    In the FY 2022 IPPS/LTCH PPS final rule (86 FR 45242 and 45243), we 
continued the policy we first adopted for FY 2018 of substituting data 
regarding FY 2013 low-income insured days for the Worksheet S-10 data 
when determining Factor 3 for IHS and Tribal hospitals and subsection 
(d) Puerto Rico hospitals that have a FY 2013 cost report. We stated 
our belief that this approach was appropriate as the FY 2013 data 
reflect the most recent available information regarding these 
hospitals' low-income insured days before any expansion of Medicaid. In 
addition, because we continued to use 1 year of insured low income 
patient days as a proxy for uncompensated care for Puerto Rico 
hospitals and residents of Puerto Rico are not eligible for SSI 
benefits, we continued to use a proxy for SSI days for Puerto Rico 
hospitals consisting of 14 percent of the hospital's Medicaid days, as 
finalized in the FY 2017 IPPS/LTCH PPS final rule (81 FR 56953 through 
56956).
    We refer readers to the FY 2022 IPPS/LTCH PPS final rule (86 FR 
45236) for a discussion of the approach that we continued to apply in 
FY 2022 to determine Factor 3 for new Puerto Rico hospitals. In brief, 
Puerto Rico hospitals that do not have a FY 2013 cost report were 
considered new hospitals and subject to the new hospital policy, as 
discussed previously. Specifically, the numerator of the Factor 3 
calculation will be the uncompensated care costs reported on Worksheet 
S-10 of the hospital's cost report for the applicable fiscal year and 
the denominator is the same denominator that is determined 
prospectively for purposes of determining Factor 3 for all DSH-eligible 
hospitals.
    Consistent with the policy adopted in the FY 2021 IPPS/LTCH PPS 
final rule and codified in the regulations at Sec.  412.106(g)(8) for 
subsequent fiscal years, in the FY 2022 IPPS/LTCH PPS final rule we 
used a single year of Worksheet S-10 data from FY 2018 cost reports to 
calculate Factor 3 for FY 2022 for all eligible hospitals with the 
exception of IHS and Tribal hospitals and Puerto Rico hospitals that 
have a cost report for 2013.
    Therefore, for FY 2022, we applied the following methodology to 
compute Factor 3 for each hospital:
    Step 1: Select the provider's longest cost report from its Federal 
fiscal year (FFY) 2018 cost reports. (Alternatively, in the rare case 
when the provider has no FFY 2018 cost report because the cost report 
for the previous Federal fiscal year spanned the FFY 2018 time period, 
the previous Federal fiscal year cost report will be used in this 
step.)
    Step 2: Annualize the uncompensated care costs (UCC) from Worksheet 
S-10 Line 30, if the cost report is more than or less than 12 months. 
(If applicable, use the statewide average CCR (urban or rural) to 
calculate uncompensated care costs.)
    Step 3: Combine adjusted and/or annualized uncompensated care costs 
for hospitals that merged using the merger policy.
    Step 4: Calculate Factor 3 for IHS and Tribal hospitals and Puerto 
Rico hospitals that have a cost report for 2013 using the low-income 
insured days proxy based on FY 2013 cost report data and the most 
recent available SSI ratio (or, for Puerto Rico hospitals, 14 percent 
of the hospital's FY 2013 Medicaid days). The denominator is calculated 
using the low-income insured days proxy data from all DSH eligible 
hospitals.
    Step 5: Calculate Factor 3 for the remaining DSH eligible hospitals 
using annualized uncompensated care costs (Worksheet S-10 Line 30) 
based on FY 2018 cost report data (from Step 1, 2 or 3). New hospitals 
and the hospitals for which Factor 3 was calculated in Step 4 are 
excluded from this calculation.
    In the FY 2022 IPPS/LTCH PPS final rule, we amended the regulation 
at Sec.  412.106 by adding a new paragraph (g)(1)(iii)(C)(9) to reflect 
the methodology for computing Factor 3 for FY 2022 for IHS and Tribal 
hospitals and for Puerto Rico hospitals that have a 2013 cost report. 
We also finalized a conforming change to limit the reference to Puerto 
Rico hospitals in Sec.  412.106(g)(1)(iii)(C)(8) to those Puerto Rico 
hospitals that have a cost report for 2013.
(c) Changes to the Methodology for Calculating Factor 3 for FY 2023 and 
Subsequent Fiscal Years
    As described in the FY 2022 IPPS/LTCH PPS final rule, commenters 
expressed concerns that the use of only 1 year of data to determine 
Factor 3 would lead to significant variations in year-to-year 
uncompensated care payments. Some stakeholders recommended the use of 2 
years of historical Worksheet S-10 data (86 FR 45237). In the FY 2022 
IPPS/LTCH PPS final rule, we stated that we would consider using 
multiple years of data when the vast majority of providers have been 
audited for more than 1 fiscal year under the revised reporting 
instructions. The audits of FY 2019 cost reports began in 2021 and 
those audited reports were available in time for the development of the 
FY 2023 IPPS/LTCH PPS proposed rule. Feedback from previous audits and 
lessons learned were incorporated into the audit process for the FY 
2019 reports.
    In consideration of the comments discussed in the FY 2022 IPPS/LTCH 
PPS final rule, in the FY 2023 IPPS/LTCH PPS proposed rule, we proposed 
to determine Factor 3 for FY 2023 using the average of the audited FY 
2018 and audited FY 2019 reports. We stated our belief that this 
proposal would address concerns from stakeholders regarding

[[Page 49037]]

year-to-year fluctuations in uncompensated care payments. In addition, 
taking into consideration the comments recommending that CMS transition 
to the use of 3 years of audited data, we indicated that we expect FY 
2024 will be the first year that 3 years of audited data will be 
available at the time of rulemaking. Accordingly, for FY 2024 and 
subsequent fiscal years, we proposed to use a 3-year average of the 
uncompensated care data from the 3 most recent fiscal years for which 
audited data are available to determine Factor 3. Specifically, for FY 
2024, we would expect to use data from FY 2018, FY 2019, and FY 2020 
reports to calculate uncompensated care payments. In other words, for 
each of the 3 most recent fiscal years for which audited data are 
available at the time of rulemaking for the applicable fiscal year, we 
would divide a hospital's uncompensated care costs for the fiscal year 
by the estimated total uncompensated care costs of all DSH hospitals 
for that fiscal year. Then, we would calculate an average of those 
proportions to determine the hospital's Factor 3 for the applicable 
Federal fiscal year. We explained that we believe the proposed approach 
is generally consistent with our past practice of using the most recent 
single year of audited data from the Worksheet S-10, while also 
addressing commenters' concerns regarding year-to-year fluctuations in 
uncompensated care payments. Consistent with the approach that we 
followed when multiple years of data were previously used in the Factor 
3 methodology, we proposed that if a hospital does not have data for 
all 3 years used in the Factor 3 calculation, we would determine Factor 
3 based on an average of the hospital's available data.
    We invited public comments on our proposed methodology for 
calculating Factor 3 for FY 2023 and subsequent fiscal years, 
including, but not limited to, our proposal to use the most recent 
audited Worksheet S-10 data from FY 2018 and FY 2019 cost reports to 
determine Factor 3 for FY 2023, and our proposal to begin using the 3 
most recent years of audited Worksheet S-10 data starting in FY 2024.
    Comment: Commenters expressed continued support for the general use 
of Worksheet S-10 data to calculate each hospital's share of 
uncompensated care costs in FY 2023 and future years. Some commenters 
also noted their long-standing support for using audited Worksheet S-10 
data to promote an accurate and consistent calculation of uncompensated 
care costs. One commenter, who supported using Worksheet S-10 data, 
stressed the importance of ongoing refinements to the audit process to 
ensure data accuracy, while another recommended that CMS regularly 
assess and identify unusual or irregular trends in the data.
    Response: We appreciate the support for our proposal to use 
Worksheet S-10 data to calculate Factor 3 for FY 2023 and future years. 
Regarding those comments that noted the importance of ongoing 
refinements to the Worksheet S-10 audit process, we reiterate our 
commitment to continue working with the MACs and providers on audit 
improvements, including changes to increase the efficiency of the audit 
process and build on the lessons learned in previous audit years. As 
noted in the FY 2023 IPPS/LTCH PPS proposed rule, we believe that, on 
balance, Worksheet S-10 data are the best available data to use for 
calculating Factor 3 for FY 2023 and subsequent fiscal years.
    Comment: An overwhelming majority of commenters expressed support 
for CMS' proposal to calculate Factor 3 for FY 2023 based on a two-year 
average of audited FY 2018 and FY 2019 Worksheet S-10 data. These 
commenters also expressed support for the proposal to transition to use 
of a three-year average of the most recent available audited Worksheet 
S-10 data for FY 2024 and subsequent fiscal years. Some commenters 
explicitly stated that they agreed with CMS that the use of only one 
year of data could lead to undue fluctuations in year-to-year 
uncompensated care payments. Supporters of these proposals also 
specified several benefits from the use of a multi-year average of 
Worksheet S-10 data, such as minimizing year-to-year volatility, 
ensuring stability in future uncompensated care payments, and 
mitigating the effect of irregular trends and data anomalies, like the 
COVID-19 PHE. One commenter suggested that CMS consider working with 
hospitals in future years to ensure that Worksheet S-10 data from the 
COVID-19 PHE period is reported appropriately, given the PHE's 
significant impact on the utilization of healthcare services. To this 
end, one commenter recommended that CMS consider incorporating FY 2020 
Worksheet S-10 data into the multi-year average for FY 2023 once the 
data has been audited, as this approach would be more reflective of 
current healthcare costs.
    In contrast, only a handful of commenters expressed opposition to 
using a two-year average of audited FY 2018 and FY 2019 Worksheet S-10 
data for FY 2023 and a three-year average of Worksheet S-10 data to 
calculate uncompensated care payments moving forward. One commenter 
indicated that using a three-year average to calculate FY 2024 
uncompensated care payments would dilute the impact of the COVID-19 PHE 
on the FY 2020 Worksheet S-10 data. This commenter asserted that using 
a multi-year average would benefit hospitals that received the highest 
amount of Health Resources & Services Administration (HRSA) subsidies 
and hospitals with lower uncompensated care costs, while harming 
hospitals with higher uncompensated care cost data in FY 2020. The 
commenter also requested that CMS provide expedited procedures for 
reopening and correcting Worksheet S-10 data for the cost reporting 
periods that will be used to calculate uncompensated care payments in 
FY 2024 and future years.
    Another commenter noted that the FY 2022 methodology based on one 
year of audited Worksheet S-10 data was adequate and should not be 
modified to a multi-year average, indicating that inconsistencies in 
the methodology used to calculate Factor 3 from year to year add a 
further burden to hospitals' ability to understand and predict their 
uncompensated care payments. This commenter also urged CMS to reexamine 
the continued use of FY 2018 Worksheet S-10 data to determine payments 
for FY 2022, FY 2023, and FY 2024, as it may benefit hospitals that 
provided elevated levels of uncompensated care in FY 2018, and 
negatively impact those that provided less uncompensated care.
    Finally, some commenters suggested alternative approaches to 
calculating Factor 3 of the uncompensated care payment calculation that 
went beyond the blending of historical Worksheet S-10 data for multiple 
fiscal years.
    Response: We thank commenters who expressed their support for our 
proposal to use a two-year average of audited FY 2018 and FY 2019 
Worksheet S-10 data to determine each hospital's share of uncompensated 
care costs in FY 2023 and to use of a 3-year average of audited 
Worksheet S-10 data starting in FY 2024. As explained in the FY 2023 
IPPS/LTCH PPS proposed rule, we believe that using a multi-year average 
of Worksheet S-10 data will provide assurance that hospitals' 
uncompensated care payments remain stable and predictable and will not 
be subject to unpredictable swings and anomalies in a hospital's 
uncompensated care costs.
    We also believe that our proposal to use multiple years of data is 
responsive to past commenters' requests for the use of multiple years 
of audited data. We disagree with the commenter who stated

[[Page 49038]]

that modifying the uncompensated care payment methodology to use 
multiple years of data would put undue burden on a hospital's ability 
to understand, budget, and forecast as we believe that our proposal to 
use a multi-year average of Worksheet S-10 data to determine Factor 3 
for FY 2023 and subsequent fiscal years is responsive to past 
recommendations for smoothing fluctuations.
    In relation to the commenter who noted that the multi-year average 
will benefit hospitals that received the highest amount of HRSA 
subsidies and hospitals with lower uncompensated care costs, we note 
that cost reporting data from the COVID-19 PHE time period is not yet 
available to be analyzed. We believe it would be premature to attempt, 
in this rulemaking, to modify the methodology for determining 
uncompensated care payments for a future year, specifically to address 
the potential impact of the PHE-related subsidies.
    In response to the request that we provide expedited procedures for 
reopening and correcting Worksheet S-10 data that will be used in the 
Factor 3 calculation, we note that we do not intend to establish fixed 
timelines for reopenings across MACs, so we can retain the flexibility 
to use our limited audit resources to address and prioritize audit 
needs across all CMS programs each year. However, we note that MACs 
work closely with hospitals regarding reopenings.
    Regarding commenters' suggestions for alternative approaches to 
calculating Factor 3 beyond the previously considered methodological 
concepts for the blending of historical Worksheet S-10 data, we 
appreciate commenters' input and note that we may consider these 
suggestions in future rulemaking.
    After consideration of the comments received, we are finalizing our 
proposal to use a two-year average of audited FY 2018 and FY 2019 
Worksheet S-10 data to calculate Factor 3 in FY 2023 and a three-year 
average of audited data from the most recent fiscal years for which 
audited data are available to determine Factor 3 in subsequent years. 
We also note that the number of audited hospitals continues to increase 
year to year and, as a result, we believe data from Worksheet S-10 will 
improve in reliability over time. However, we will continue to audit 
additional years of the Worksheet S-10 data and monitor the stability 
of uncompensated care payments as we move forward with using a multi-
year average of audited Worksheet S-10 data for Factor 3 calculations.
    As discussed in the FY 2023 IPPS/LTCH PPS proposed rule, we have 
determined Factor 3 for IHS and Tribal hospitals and Puerto Rico 
hospitals, based on the low-income insured days proxy for uncompensated 
care costs. In the FY 2022 IPPS/LTCH PPS final rule, we discussed 
comments we had received from IHS/Tribal hospitals and Puerto Rico 
hospitals about the significant challenges they face in relation to 
uncompensated care reporting (86 FR 45242 and 45243). For example, a 
commenter stated that the information technology systems used by IHS 
and Tribal hospitals are not equipped to collect the necessary data for 
the Worksheet S-10, noting that while IHS recently received funding to 
upgrade its information technology system, it will take some time, 
potentially years, before it is fully functional (86 FR 45242). Another 
commenter expressed concerns that Puerto Rico hospitals were 
understating the components of uncompensated care costs, and indicated 
that technical education is needed to address the challenges Puerto 
Rico hospitals have regarding charity care and bad debt reporting, 
which the commenter stated would take years to address (86 FR 45243).
    In the FY 2023 IPPS/LTCH PPS proposed rule, we acknowledged that to 
the extent commenters have identified specific challenges for IHS/
Tribal hospitals and Puerto Rico hospitals in reporting uncompensated 
care costs on Worksheet S-10, it is possible that after a sufficient 
number of years these reporting challenges could be addressed. However, 
despite the reporting challenges described by commenters, we expressed 
our concern that the historical 2013-based data on low-income insured 
days, which has been used as an alternative to data on uncompensated 
care costs from the Worksheet S-10 to determine Factor 3 for IHS/Tribal 
hospitals and Puerto Rico hospitals, is no longer a good proxy for the 
costs of these hospitals in treating the uninsured, given the time that 
has elapsed since 2013. In 2023, this data will be 10 years old and 
there is no obvious way to update the information given our stated 
concerns surrounding the differential impact of state Medicaid 
expansions after 2013. In light of these concerns, we stated that we 
could no longer conclude that alternative data to the data on 
uncompensated care costs reported on Worksheet S-10 are currently 
available for IHS/Tribal hospitals and Puerto Rico hospitals that are a 
better proxy for the costs of these hospitals in treating the 
uninsured. Accordingly, for FY 2023 and subsequent fiscal years, we 
proposed to discontinue the use of low-income insured days as a proxy 
for the uncompensated care costs of these hospitals and proposed to use 
the same data to determine Factor 3 for IHS and Tribal hospitals and 
Puerto Rico hospitals as for other hospitals. Specifically, for FY 
2023, we would determine Factor 3 for IHS and Tribal hospitals and 
Puerto Rico hospitals based on the average of the uncompensated care 
data reported on Worksheet S-10 of their FY 2018 and FY 2019 cost 
reports. However, we sought comments on alternatives both to our 
proposal to use data on uncompensated care costs from the Worksheet S-
10 to determine Factor 3 for IHS/Tribal hospitals and Puerto Rico 
hospitals and to the continued use of low-income insured days as a 
proxy for the uncompensated care costs of these hospitals. We also 
sought comments on how to best measure and define the uncompensated 
care costs associated with these hospitals that might not otherwise be 
captured in Factor 3 calculations based on Worksheet S-10 data. Because 
we recognized that our proposal to discontinue the use of the low-
income insured days proxy and to rely solely on Worksheet S-10 data to 
calculate Factor 3 of the uncompensated care payment methodology for 
IHS/Tribal hospitals and Puerto Rico hospitals could result in a 
significant financial disruption for these hospitals, we also proposed 
to establish a new supplemental payment for IHS/Tribal hospitals and 
Puerto Rico hospitals, beginning in FY 2023. We refer readers to 
section IV.E. of the preamble of this final rule for a complete 
discussion of this proposed new supplemental payment.
    Prior to the proposed rulemaking for FY 2023, CMS consulted with 
IHS and Tribes regarding our policies for determining uncompensated 
care payments. They expressed that uncompensated care payments are 
critical to the providers and should be maintained at their current 
levels, at a minimum. As we explained in the FY 2023 IPPS/LTCH PPS 
proposed rule, we considered this recent input along with previous 
input from stakeholders in the development of our proposed policies. We 
also welcomed additional input from stakeholders regarding the unique 
circumstances of IHS/Tribal hospitals and Puerto Rico hospitals and/or 
any mitigating factors, and noted that this input would inform our 
considerations about our proposal to determine Factor 3 for these 
hospitals using data from

[[Page 49039]]

Worksheet S-10 and the related proposal to establish a new supplemental 
payment for IHS/Tribal hospitals and Puerto Rico hospitals.
    We received comments on our proposal to discontinue the use of the 
low-income insured days proxy and to rely solely on Worksheet S-10 data 
to calculate Factor 3 of the uncompensated care payment methodology for 
IHS/Tribal hospitals and Puerto Rico hospitals. Due to the close 
interrelationship between this proposal and our proposal to establish a 
new supplemental payment for IHS/Tribal hospitals and Puerto Rico 
hospitals, we discuss those comments, along with the comments received 
on the proposed new supplemental payment, and set forth our final 
policies in Section IV.E of this final rule.
    For purposes of the FY 2023 proposed rule, we used the December 
2021 HCRIS extract to calculate Factor 3. We noted that we intended to 
use the March 2022 update of HCRIS to calculate Factor 3 for the FY 
2023 IPPS/LTCH PPS final rule. However, we stated that we may consider 
the use of more recent data that may become available after March 2022, 
but prior to the development of the final rule, if appropriate, for 
purposes of calculating the final Factor 3 for this FY 2023 IPPS/LTCH 
PPS final rule.
    We received comments regarding the uncompensated care costs 
definition and Worksheet S-10 cost report instructions.
    Comment: With regard to the definition of uncompensated care, 
several commenters urged CMS to include unreimbursed costs (shortfalls) 
from Medicaid in the definition of uncompensated care. Specifically, 
some commenters urged CMS to account for Medicaid shortfalls and 
incorporate Line 31 of Worksheet S-10 along with already-utilized Line 
30. In contrast, one commenter agreed with CMS that Medicaid 
shortfalls, as currently reported on Worksheet S-10, should not be 
included in the estimation of uncompensated care costs. Instead, the 
commenter recommended that the agency revise Worksheet S-10 so data on 
Medicaid shortfalls better resemble actual shortfalls incurred by 
hospitals. The commenter further noted that such data will be 
increasingly useful for informational purposes as previously uninsured 
individuals gain access to Medicaid. Other commenters proposed 
incorporating social determinants of health methodologies into 
uncompensated care costs by including variables that describe 
socioeconomic disadvantage such as accounting for costs incurred by 
hospitals to improve access to healthy foods, transportation, health 
screenings, technology assistance, and similar community needs. 
Notably, another commenter suggested that CMS redefine uncompensated 
care to align with the definitions used to determine community benefit 
spending under the Internal Revenue Code.
    Response: We appreciate commenters' suggestions for revisions and/
or modifications to Worksheet S-10. We will consider the concerns 
raised by commenters as part of future cost report clarifications and 
will make modifications as necessary to further improve and refine the 
information that is reported on Worksheet S-10 to support collection of 
the information necessary to implement section 1886(r)(2) of the Act.
    With regard to the comments requesting that payment shortfalls from 
Medicaid be included in uncompensated care cost calculations, we 
continue to believe there are compelling arguments for excluding such 
shortfalls from the definition of uncompensated care. First, we note 
that we did not propose any changes to the definition of uncompensated 
care costs, which was first adopted in the FY 2018 IPPS/LTCH PPS final 
rule (82 FR 38215 through 38217) as the amount on Line 30 of Worksheet 
S-10, which is the cost of charity care (Line 23) and the cost of non-
Medicare bad debt and non-reimbursable Medicare bad debt (Line 29). 
Additionally, key interested parties (including MedPAC) do not consider 
Medicaid shortfalls in their definition of uncompensated care. 
Furthermore, we continue to believe that it is most consistent with 
section 1886(r)(2) of the Act for Medicare uncompensated care payments 
to target hospitals that incur a disproportionate share of 
uncompensated care for patients with no insurance coverage. We also 
note that even if we agreed that it would be appropriate to adjust the 
definition of uncompensated care to include Medicaid shortfalls, this 
would not be a feasible option at this time due to computational 
limitations. Specifically, computing such shortfalls is operationally 
problematic because Medicaid pays hospitals a single DSH payment that, 
in part, covers the hospital's costs for providing care to the 
uninsured and in part covers estimates of the Medicaid ``shortfalls.'' 
Therefore, it is not clear how CMS would determine how much of the 
``shortfall'' is left after the Medicaid DSH payment is made. In 
addition, in some States, hospitals return a portion of their Medicaid 
revenues to the State via provider taxes and receive supplemental 
payments in return (along with the federal match), making the 
computation of ``shortfalls'' even more complex.
    Regarding the request that we include costs incurred by hospitals 
to address social determinants of health in the definition of 
uncompensated care costs, we have consistently stated in past final 
rules (85 FR 58826 and 86 FR 45239) in response to similar comments 
that we believe the purpose of uncompensated care payments is to 
provide additional payment to hospitals for treating the uninsured, not 
for other costs incurred, including costs associated with addressing 
social determinants of health, as commenters have suggested. 
Accordingly, we do not believe changing the calculation of 
uncompensated care costs is appropriate, at this time.
    Comment: Commenters requested that CMS include all patient care 
costs when calculating the cost-to-charge ratio (CCR) used in Worksheet 
S-10 and urged CMS to include costs incurred for graduate medical 
education (GME), costs of paying provider taxes associated with 
Medicaid revenue, and costs of providing physician and other 
professional services when calculating the CCR used to determine 
uncompensated care costs on Worksheet S-10 in order to improve the 
accuracy of that CCR.
    Response: As we have stated in past rules (84 FR 42378, 85 FR 
58826, and 86 FR 45239) in response to similar requests that we modify 
the CCR used on Worksheet S-10, we continue to believe the CCR 
calculation that is used in Worksheet S-10 is appropriate. Regarding 
the request that we include GME costs, costs of paying provider taxes 
associated with Medicaid revenue, and costs of providing physician and 
other professional service when calculating CCR used in Worksheet S-10, 
we note that because the CCR on Line 1 of Worksheet S-10 is obtained 
from Worksheet C, Part I, and is also used in other IPPS rate setting 
contexts (such as high-cost outliers and the calculation of the MS-DRG 
relative weights) from which it is appropriate to exclude the costs 
associated with supporting GME costs and the costs of physician and 
professional services and costs of paying provider taxes, we remain 
reluctant to adjust CCRs in the narrower context of calculating 
uncompensated care costs. Therefore, as stated in past final rules, we 
continue to believe that it is not appropriate, at this time, to modify 
the calculation of the CCR on Line 1 of Worksheet S-10 to include any 
additional costs in the numerator of the CCR calculation.
    Comment: One commenter stated that large teaching hospitals (with 
100+

[[Page 49040]]

residents) would experience an even larger uncompensated care payment 
reduction, resulting in underserved and vulnerable populations having 
less access to transplant programs (as these programs are often 
operated by large teaching institutions). Another commenter expressed 
concern that hospitals in Medicaid non-expansion states depend greatly 
on uncompensated care payments for financial support, and this 
commenter urged CMS to work with providers and patient advocates in 
non-expansion states to screen patients for eligibility under either 
financial assistance policies or premium support under the Affordable 
Care Act before classifying the case as uncompensated care. The same 
commenter noted that the equal weighting of bad debt and charity care 
on the Worksheet S-10 disincentivizes hospitals from ensuring that 
eligible patients receive charity care, as obtaining the qualification 
for charity care entails long administrative processes.
    Response: We thank commenters for their continued concern regarding 
the distribution of uncompensated care payments and the impact of 
reductions in uncompensated care payments on teaching hospitals. 
However, as stated previously, the purpose of uncompensated care 
payments is to provide additional payment to hospitals for treating the 
uninsured. Uncompensated payments are not intended to provide support 
for other activities that hospitals may undertake. We also note that 
CMS does not set charity care criteria for hospitals, and within 
reason, hospitals can establish their own criteria of what constitutes 
charity care in their financial assistance policies.
    Comment: With regard to Worksheet S-10 instructions and guidance, a 
few commenters commended CMS for its efforts to provide clearer 
instructions for Worksheet S-10. A few commenters requested that CMS 
clarify inconsistent Worksheet S-10 instructions so that non-Medicare 
bad debt is not multiplied by the CCR. These commenters noted that CMS' 
revised instructions indicate that non-reimbursed Medicare bad debt is 
not reduced by the CCR, but that CMS' September 2017 transmittal states 
that non-Medicare bad debt should be multiplied by the CCR. One 
commenter indicated that such practice is inconsistent with the way 
non-reimbursable Medicare bad debt is treated.
    Response: We appreciate commenters' concerns regarding the need for 
clarification of the Worksheet S-10 instructions, as well as their 
suggestions for revisions to improve reporting. We reiterate our 
commitment to continuing to work with impacted parties to address their 
concerns regarding Worksheet S-10 instructions and reporting through 
provider education and further refinement of the instructions as 
appropriate. We also encourage providers to share with their respective 
MAC any questions regarding clarifications of instructions, reporting, 
and submission deadlines.
    We continue to believe that, as noted by a commenter, our efforts 
to refine the instructions and guidance have improved provider 
understanding of the Worksheet S-10 and added clarity to the 
instructions. We also recognize that there are continuing opportunities 
to further improve the accuracy and consistency of the information that 
is reported on the Worksheet S-10, and to the extent that commenters 
have raised new questions and concerns regarding the reporting 
requirements, we will attempt to address them through future rulemaking 
and/or sub-regulatory guidance and provider outreach. However, as 
stated in previous rules, we continue to believe that the Worksheet S-
10 instructions are now sufficiently clear and allow hospitals to 
accurately complete Worksheet S-10s.
    Regarding the commenters' request that CMS clarify whether non-
Medicare bad debt is multiplied by CCR, we believe that the Worksheet 
S-10 instructions are clear and indicate that the CCR is multiplied by 
the non-Medicare bad debt amount on line 28.
    Regarding the comments requesting specific structural changes to 
Worksheet S-10 and/or further clarification of the reporting 
instructions, we note that these comments fall outside the scope of 
this final rule. We note that a recent PRA package for hospital cost 
report is available at: https://www.cms.gov/regulations-and-guidancelegislationpaperworkreductionactof1995pra-listing/cms-2552-10.
    We received comments regarding Worksheet S-10 data and audits.
    Comment: In relation to the accuracy of the Worksheet S-10 data, 
one commenter urged CMS to refine the instructions for reporting of 
uncompensated care costs. The commenter's recommendations included that 
CMS should mitigate the effect of anomalies in the cost data for the 
COVID-19 PHE period and that CMS should consider the redistributive 
effects of the COVID-19 PHE for purposes of determining uncompensated 
care payments in future rulemaking. One commenter recommended that CMS 
work with impacted providers in upcoming years to ensure that the data 
from the COVID-19 PHE period is properly understood and correctly 
reported. Another commenter urged CMS to account for the 
unpredictability of the COVID-19 PHE, including the emergence of new 
variants, in determining uncompensated care payments for future years.
    Response: In regard to requests for CMS to mitigate the effect of 
anomalies in FY 2020 through FY 2022 cost report data and account for 
the unpredictability of the COVID-19 PHE in determining uncompensated 
care payments for future years, we note that we are finalizing the 
proposal to use a three-year average of the most recently audited cost 
report data for FY 2024 and subsequent years. Using the three-year 
average will smooth the variation in year-to-year uncompensated care 
payments and lessen the impacts of COVID-19 PHE and future unforeseen 
events. We also note that the calculations for Factor 1 and Factor 2 
reflect the estimated impact of the COVID-19 PHE on DSH payments. 
Further, we anticipate that there will be less fluctuation in cost 
report data as the PHE disruptions on healthcare utilization fade. We 
will continue to monitor the impacts of the PHE and will consider this 
issue further in future rulemaking, as appropriate.
    Comment: Some commenters commended CMS for the agency's efforts to 
develop and improve the audit process for Worksheet S-10 data. 
Specifically, one commenter commended CMS for its efforts to audit all 
hospitals rather than only a portion, while another commenter 
recommended that CMS expend all the necessary resources to continue to 
audit Worksheet S-10 data for all DSH eligible hospitals.
    Echoing concerns expressed in previous years, commenters encouraged 
CMS to work with MACs to make the audit process clearer, more 
consistent, and more complete. The same commenters provided several 
recommendations, including that CMS establish a standardized process 
across auditors, develop uniform standards regarding information 
submission and acceptable documentation to meet audit requirements, 
develop a transparent timeframe with sufficient lead time, target 
specific data aspects for the audit, and develop a process for timely 
appeals. Specifically, one commenter recommended that all hospitals be 
audited using the same protocols and that having only some hospitals 
subject to desk reviews is inequitable. A few commenters cited the 
Medicare wage index audit as a model that CMS could use for Worksheet 
S-10 audits. One commenter suggested that CMS ensure

[[Page 49041]]

that Worksheet S-10 audits impose minimal burden and are equitable and 
uniform across hospitals. The same commenter also suggested that CMS 
consider making the audit process more transparent by disclosing 
criteria used to identify hospitals for audits and publishing audit 
protocols in advance to allow hospitals time and opportunity to respond 
to audits and address findings. Other recommendations from this 
commenter included that CMS should conduct audits in advance of using 
data for payment rate setting such that data are accurate and final, 
select hospitals for audits in an equitable and systematic way, and 
review audit findings to ensure that MACs and subcontractors are 
consistently performing audits according to protocols.
    Response: We thank commenters for their feedback on the audits of 
the FY 2019 Worksheet S-10 data and their recommendations for future 
audits. As we have stated previously in response to comments regarding 
audit protocols, these are provided to the MACs in advance of the audit 
so as to assure consistency and timeliness in the audit process. We 
began auditing the FY 2019 Worksheet S-10 data for selected hospitals 
last year so that the audited uncompensated care data for these 
hospitals would be available in time for use in the FY 2023 IPPS/LTCH 
PPS proposed rule. We chose to focus the audit on the FY 2019 cost 
reports in order to maximize the available audit resources. Similarly, 
as discussed in the FY 2022 IPPS/LTCH PPS final rule, we chose to focus 
the audits on the FY 2018 cost reports in order to maximize the 
available audit resources prior to the FY 2022 rulemaking. In response 
to the consistent feedback from commenters emphasizing the importance 
of audits in ensuring the accuracy and consistency of data reported on 
the Worksheet S-10, we have also started the process of auditing FY 
2020 Worksheet S-10 data.
    We appreciate all commenters' input and recommendations on how to 
improve our audit process and reiterate our commitment to continue 
working with the MACs and providers on audit improvements, which 
include making changes to increase the efficiency of the audit process, 
building on the lessons learned in previous audit years. We will take 
these recommendations into consideration for future rulemaking. 
Regarding commenters' requests for a standard audit timeline, we do not 
intend to establish a fixed timeline for audits across MACs at this 
time such that we can retain the flexibility to use our limited audit 
resources to address and prioritize audit needs across all CMS programs 
each year. We note that MACs collaborate with providers regarding 
scheduling dates during the Worksheet S-10 audit process. We also note 
that MACs work closely with providers to balance the time needed to 
complete the Worksheet S-10 audits and to minimize the burden on 
providers and will continue to do so.
    Regarding commenters' requests that we make public the audit 
instructions and criteria, as we previously stated in the FY 2022 IPPS/
LTCH final rule and in prior rules, we do not make review protocols 
public as CMS desk review and audit protocols are confidential and are 
for CMS and MAC use only. We note that there is no requirement under 
either the Administrative Procedure Act or the Medicare statute that 
CMS establish audit protocols through notice and comment rulemaking. 
Rather, it is sufficient that we provide impacted parties with notice 
of our proposed methodology and the data sources that will be used, so 
that they may have a meaningful opportunity to submit their views on 
the proposed methodology and the adequacy of the data for the intended 
purpose. Similarly, there is no requirement that we provide an 
opportunity for comment on the actual findings or audit disallowances 
determined for each hospital as these results are confidential to each 
hospital.
    Concerning commenters' recommendations that we establish a timely 
review and appeals process for the Worksheet S-10 audits, we do not 
plan to introduce such a process at this time in order to maximize 
limited audit resources. However, we will continue to work with 
impacted parties to address their concerns regarding the accuracy and 
consistency of data reported on Worksheet S-10. We will also continue 
to work to further improve reporting through revised instructions, and 
will also work with MACs to ensure a more consistent audit process 
across providers and MACs.
    Regarding commenters' recommendations that we establish a similar 
process to that of the wage index audits, at this point we do not plan 
to introduce an audit process with such a structure in order to 
maximize limited audit resources.
    As discussed in the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 
28392), for purposes of determining Factor 3 for FY 2023 and subsequent 
fiscal years, we are continuing to apply the following policies: (1) 
the merger policies that were initially adopted in the FY 2015 IPPS/
LTCH PPS final rule (79 FR 50021), as modified in the FY 2021 IPPS/LTCH 
PPS final rule (85 FR 58828 and 58829) to incorporate the use of a 
multiplier to account for merger effective date; (2) the policy for 
hospitals with multiple cost reports, beginning in the same fiscal 
year, of using the longest cost report and annualizing uncompensated 
care data if a hospital's cost report does not equal 12 months of data; 
(3) the policy, as modified in the FY 2021 IPPS/LTCH PPS final rule (85 
FR 58829) and as further modified as proposed in the FY 2023 IPPS/LTCH 
PPS proposed rule, for the rare case where a hospital has a cost report 
that starts in one fiscal year and spans the entirety of the following 
fiscal year, such that the hospital has no cost report for that 
subsequent fiscal year, of using the cost report that spans both fiscal 
years for the latter fiscal year; (4) the new hospital policy, as 
modified in the FY 2020 IPPS/LTCH PPS final rule and as further 
modified as proposed in this section; (5) the newly merged hospital 
policy, with the modifications proposed in the FY 2023 IPPS/LTCH PPS 
proposed rule; and (6) the policies regarding the application of 
statistical trim methodologies to potentially aberrant CCRs and 
potentially aberrant uncompensated care costs reported on the Worksheet 
S-10, as modified as proposed in the FY 2023 IPPS/LTCH PPS proposed 
rule.
    Because we proposed to use multiple years of cost reports to 
determine Factor 3 starting in FY 2023, we determined that it would 
also be necessary to make a further modification to the policy 
regarding cost reports that start in one fiscal year and span the 
entirety of the following fiscal year. Specifically, in the rare cases 
when we use a cost report that starts in one fiscal year and spans the 
entirety of the subsequent Federal fiscal year to determine 
uncompensated care costs for the subsequent Federal fiscal year, we 
would not use the same cost report to determine the hospital's 
uncompensated care costs for the earlier fiscal year. We explained that 
using the same cost report to determine uncompensated care costs for 
both fiscal years would not be consistent with our intent to smooth 
year-to-year variation in uncompensated care costs. As an alternative, 
we proposed to use the hospital's most recent prior cost report, if 
that cost report spans the applicable period. In other words, in 
determining Factor 3 for FY 2023, we would not use the same cost report 
to determine the hospital's uncompensated care costs for both FY 2018 
and FY 2019. Rather, we would use the cost report that spans the 
entirety of FY 2019 to determine uncompensated care costs for FY 2019 
and we would use the hospital's most recent prior cost report to 
determine its uncompensated care costs for FY 2018,

[[Page 49042]]

provided that cost report spans some portion of Federal fiscal year 
2018.
    We did not receive comments on this proposed modification. We are 
finalizing as proposed.

 Scaling Factor

    To address the effects of the calculating Factor 3 using data from 
multiple fiscal years, in the FY 2023 IPPS/LTCH PPS proposed rule (87 
FR 28392) we proposed to apply a scaling factor to the Factor 3 values 
calculated for all DSH eligible hospitals so that total uncompensated 
care payments to hospitals that are projected to be eligible for DSH 
for a fiscal year will be consistent with the estimated amount 
available to make uncompensated care payments for that fiscal year. 
Specifically, we proposed to adopt a policy under which we divide 1 
(the expected sum of all DSH-eligible hospitals' Factor 3 values) by 
the actual sum of all DSH eligible hospitals' Factor 3 values and then 
multiply the quotient by the uncompensated care payment determined for 
each DSH eligible hospital to obtain a scaled uncompensated care 
payment amount for each hospital. This process is designed to ensure 
that the sum of the scaled uncompensated care payments for all 
hospitals that are projected to be DSH eligible is consistent with the 
estimate of the total amount available to make uncompensated care 
payments for the applicable fiscal year. In the proposed rule, we noted 
that a similar scaling factor methodology was previously used in both 
FY 2018 (82 FR 38214 and 38215) and FY 2019 (83 FR 41414), when the 
Factor 3 calculation also included multiple years of data.
    We did not receive comments on this proposed scaling factor policy. 
We are finalizing as proposed.
 Modifications to New Hospital Policy for Purposes of Factor 3
    We proposed to modify the new hospital policy that was initially 
adopted in the FY 2020 IPPS/LTCH PPS final rule to determine Factor 3 
for new hospitals. Consistent with our proposal to use multiple years 
of cost reports to determine Factor 3, we proposed to define new 
hospitals as hospitals that do not have cost report data for the most 
recent year of data being used in the Factor 3 calculation. In other 
words, the cut-off date for the new hospital policy would be the 
beginning of the Federal fiscal year after the most recent year for 
which audits of the Worksheet S-10 data have been conducted. For FY 
2023, the FY 2019 cost reports are the most recent year of cost reports 
for which audits of Worksheet S-10 data have been conducted. Thus, 
hospitals with CCNs established on or after October 1, 2019, would be 
subject to the new hospital policy in FY 2023.
    Under the proposed modification to the new hospital policy, we 
would continue the policy established in the FY 2020 IPPS/LTCH PPS 
final rule (84 FR 42370) that if a new hospital has a preliminary 
projection of being eligible for DSH payments based on its most recent 
available disproportionate patient percentage, it may receive interim 
empirically justified DSH payments. However, new hospitals would not 
receive interim uncompensated care payments during FY 2023 because we 
would have no FY 2018 or FY 2019 uncompensated care data on which to 
determine what those interim payments should be. The MAC will make a 
final determination concerning whether the hospital is eligible to 
receive Medicare DSH payments at cost report settlement based on its FY 
2023 cost report.
    We also proposed to modify the methodology used to calculate Factor 
3 for new hospitals. Specifically, we proposed to determine Factor 3 
for new hospitals using a denominator based solely on uncompensated 
care costs from cost reports for the most recent fiscal year for which 
audits have been conducted. For example, if a new hospital is 
ultimately determined to be eligible for Medicare DSH payments for FY 
2023, the hospital will receive an uncompensated care payment 
calculated using a Factor 3, where the numerator is the uncompensated 
care costs reported on Worksheet S-10 of the hospital's FY 2023 cost 
report, and the denominator is the sum of the uncompensated care costs 
reported on Worksheet S-10 of the FY 2019 cost reports for all DSH-
eligible hospitals. In addition, we proposed to apply a scaling factor, 
as discussed previously, to the Factor 3 calculation for a new 
hospital. We explained that we believe applying the scaling factor is 
appropriate for purposes of calculating Factor 3 for all hospitals, 
including new hospitals and hospitals that are treated as new 
hospitals, in order to improve consistency and predictability across 
all hospitals.
 Modifications to the Newly Merged Hospital Policy
    In the FY 2023 IPPS/LTCH PPS rule, we stated that we will continue 
to treat hospitals that merge after the development of the final rule 
for the applicable fiscal year similar to new hospitals. As explained 
in the FY 2015 IPPS/LTCH PPS final rule, for these newly merged 
hospitals, we do not have data currently available to calculate a 
Factor 3 amount that accounts for the merged hospital's uncompensated 
care burden (79 FR 50021). In the FY 2015 IPPS/LTCH PPS final rule, we 
finalized a policy under which Factor 3 for hospitals that we do not 
identify as undergoing a merger until after the public comment period 
and additional review period following the publication of the final 
rule or that undergo a merger during the fiscal year will be 
recalculated similar to new hospitals (79 FR 50021 and 50022). 
Consistent with the policy adopted in the FY 2015 IPPS/LTCH PPS final 
rule, we will continue to treat newly merged hospitals in a similar 
manner to new hospitals, such that the newly merged hospital's final 
uncompensated care payment will be determined at cost report settlement 
where the numerator of the newly merged hospital's Factor 3 will be 
based on the cost report of only the surviving hospital (that is, the 
newly merged hospital's cost report) for the current fiscal year. 
However, if the hospital's cost reporting period includes less than 12 
months of data, the data from the newly merged hospital's cost report 
will be annualized for purposes of the Factor 3 calculation. Consistent 
with the proposed modification to the methodology used to determine 
Factor 3 for new hospitals described previously, we proposed to 
determine Factor 3 for newly merged hospitals using a denominator that 
is the sum of the uncompensated care costs for all DSH-eligible 
hospitals, as reported on Worksheet S-10 of their cost reports for the 
most recent fiscal year for which audits have been conducted. In 
addition, we would apply a scaling factor, as discussed previously, to 
the Factor 3 calculation for a newly merged hospital. We stated our 
belief that applying the scaling factor is appropriate for purposes of 
calculating Factor 3 for all hospitals, including new hospitals and 
hospitals that are treated as new hospitals, in order to improve 
consistency and predictability across all hospitals.
    We also explained that consistent with past policy, interim 
uncompensated care payments for the newly merged hospital will be based 
only on the data for the surviving hospital's CCN available at the time 
of the development of the final rule. In other words, for FY 2023, the 
eligibility of a newly merged hospital to receive interim uncompensated 
care payments and the amount of any interim uncompensated care 
payments, would be based on the uncompensated care costs from the FY 
2018 and FY 2019 cost reports available for the surviving

[[Page 49043]]

CCN at the time the final rule is developed. However, at cost report 
settlement, we would determine the newly merged hospital's final 
uncompensated care payment based on the uncompensated care costs 
reported on its FY 2023 cost report. That is, we would revise the 
numerator of Factor 3 for the newly merged hospital to reflect the 
uncompensated care costs reported on the newly merged hospital's FY 
2023 cost report. The denominator would be the sum of the uncompensated 
care costs reported on Worksheet S-10 of the FY 2019 cost reports for 
all DSH-eligible hospitals, which is the most recent fiscal year for 
which audits have been conducted.
    Comment: A couple of commenters expressed support for the policy 
currently in place for newly merged hospitals under which interim 
uncompensated care payments are based on the data for the surviving 
hospital's CCN available at the time of development of the final rule. 
These commenters also indicated support for continuing the policy in 
place for new hospitals, under which new hospitals with a CCN 
established on or after October 2019 with a preliminary projection of 
being eligible for DSH payments would receive interim empirically 
justified DSH payments. MACs would then make the final determination 
concerning whether a new hospital is eligible to receive DSH payments 
at cost report settlement based on the new hospital's FY 2023 cost 
report. One commenter requested that CMS provide clarification 
regarding which cost report would be used in the numerator of the 
Factor 3 calculation for a newly merged hospital or new hospital, and 
whether the cost report beginning or ending in FY 2023 would be used.
    Response: We appreciate the support for our current policies for 
new and newly merged hospitals. In response to the comment asking for 
clarification on whether a newly merged hospital or new hospital would 
use its cost report beginning or ending in FY 2023, we note that the 
new hospital policy and the newly merged hospital policy are based on 
the start date of the hospital's cost reporting period. Specifically, 
the Factor 3 calculation for a new hospital will be based on the 
hospital's FY 2023 cost report (that is, a cost report with a start 
date on or after October 1, 2022, and on or before September 30, 2023). 
The numerator of the hospital's Factor 3 will be the hospital's total 
uncompensated care costs from the Worksheet S-10 Line 30 of its FY 2023 
cost report (annualized, if necessary). The denominator will be the 
total national uncompensated care costs from the FY 2019 cost reports 
as calculated in this FY 2023 IPPS/LTCH PPS final rule. In the case of 
a new hospital or a newly merged hospital that has a cost report that 
spans multiple Federal fiscal years, if the cost report is a FY 2023 
cost report, there is only one denominator in the Factor 3 calculation. 
In addition, the pro rata calculation (i.e., the hospital's cost 
reporting period spans different Federal fiscal years) for a new 
hospital or a newly merged hospital is calculated using only the FY2023 
total uncompensated care amount (that is, the Factor 3 is multiplied by 
the FY 2023 total uncompensated care amount, as finalized in this final 
rule.).
    After consideration of the comments received, we are finalizing the 
proposed modifications to the new hospital and newly merged policies.
 CCR Trim Methodology
    The calculation of a hospital's total uncompensated care costs on 
Worksheet S-10 requires the use of the hospital's cost to charge ratio 
(CCR). Consistent with the process for trimming CCRs used in the FY 
2021 IPPS/LTCH PPS final rule (85 FR 58831 and 58832), we explained in 
the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28393) that we will 
apply the following steps to determine the applicable CCR for FY 2018 
reports and FY 2019 reports separately:
    Step 1: Remove Maryland hospitals. In addition, we will remove all-
inclusive rate providers because their CCRs are not comparable to the 
CCRs calculated for other IPPS hospitals.
    Step 2: Calculate a CCR ``ceiling'' for the applicable fiscal year 
with the following data: for each IPPS hospital that was not removed in 
Step 1 (including non-DSH eligible hospitals), we use cost report data 
to calculate a CCR by dividing the total costs on Worksheet C, Part I, 
Line 202, Column 3 by the charges reported on Worksheet C, Part I, Line 
202, Column 8. (Combining data from multiple cost reports from the same 
fiscal year is not necessary, as the longer cost report will be 
selected.) The ceiling is calculated as 3 standard deviations above the 
national geometric mean CCR for the applicable fiscal year. This 
approach is consistent with the methodology for calculating the CCR 
ceiling used for high-cost outliers. Remove all hospitals that exceed 
the ceiling so that these aberrant CCRs do not skew the calculation of 
the statewide average CCR.
    Step 3: Using the CCRs for the remaining hospitals in Step 2, 
determine the urban and rural statewide average CCRs for the applicable 
fiscal year for hospitals within each State (including non-DSH eligible 
hospitals), weighted by the sum of total hospital discharges from 
Worksheet S-3, Part I, Line 14, Column 15.
    Step 4: Assign the appropriate statewide average CCR (urban or 
rural) calculated in Step 3 to all hospitals, excluding all-inclusive 
rate providers, with a CCR for the applicable fiscal year greater than 
3 standard deviations above the national geometric mean for that fiscal 
year (that is, the CCR ``ceiling''). For purposes of both the proposed 
rule and this final rule, the statewide average CCR was applied to 8 
hospitals' FY 2018 reports, of which 3 hospitals had FY 2018 Worksheet 
S-10 data. The statewide average CCR was applied to 14 hospitals' FY 
2019 reports, of which 6 hospitals had FY 2019 Worksheet S-10 data.
    Step 5: For hospitals that did not report a CCR on Worksheet S-10, 
Line 1, we assign them the statewide average CCR for the applicable 
fiscal year as determined in step 3.
    After completing the previously described steps, we re-calculate 
the hospital's uncompensated care costs (Line 30) for the applicable 
fiscal year using the trimmed CCR (the statewide average CCR (urban or 
rural, as applicable)).
    We did not receive any comments on the discussion of CCR trim 
methodology. We are finalizing as proposed.
 Modifications to the Uncompensated Care Data Trim Methodology
    After applying the CCR trim methodology, there are rare situations 
where a hospital has potentially aberrant uncompensated care data for a 
fiscal year that are unrelated to its CCR. Therefore, in the FY 2023 
IPPS LTCH/PPS proposed rule, we explained that under the trim 
methodology for potentially aberrant UCC that was included as part of 
the methodology for purposes of determining Factor 3 in the FY 2021 
IPPS/LTCH PPS final rule (85 FR 58832), if the hospital's uncompensated 
care costs for FY 2018 or FY 2019 are an extremely high ratio (greater 
than 50 percent) of its total operating costs in the applicable fiscal 
year, we will determine the ratio of uncompensated care costs to the 
hospital's total operating costs from another available cost report, 
and apply that ratio to the total operating expenses for the 
potentially aberrant fiscal year to determine an adjusted amount of 
uncompensated care costs for the applicable fiscal year. Specifically, 
if a hospital's FY 2018 cost report is determined to include 
potentially

[[Page 49044]]

aberrant data, data from its FY 2019 cost report will be used for the 
ratio calculation. Thus, the hospital's uncompensated care costs for FY 
2018 will be trimmed by multiplying its FY 2018 total operating costs 
by the ratio of uncompensated care costs to total operating costs from 
the hospital's FY 2019 cost report to calculate an estimate of the 
hospital's uncompensated care costs for FY 2018 for purposes of 
determining Factor 3 for FY 2023. Because we proposed to use multiple 
years of cost reports in the Factor 3 calculation for FY 2023, we would 
apply this same approach to address potentially aberrant data in the FY 
2019 cost report, by trimming based on the hospital's FY 2020 cost 
report.
    In the FY 2023 IPPS/LTCH PPS proposed rule, we noted that we have 
audited the FY 2018 and the FY 2019 Worksheet S-10 data for a number of 
hospitals. Because the UCC data for these hospitals have been subject 
to audit, we stated our belief that there is increased confidence that 
if high uncompensated care costs are reported by these audited 
hospitals, the information is accurate. Therefore, consistent with the 
policy that was adopted in the FY 2021 IPPS/LTCH PPS final rule, we 
stated that it would be unnecessary to apply the trim methodology for a 
fiscal year for which a hospital's UCC data have been audited.
    In addition to the UCC trim methodology, we stated that we would 
continue to apply a trim specific to certain hospitals that do not have 
audited FY 2018 Worksheet S-10 data and/or audited FY 2019 Worksheet S-
10 data. We noted that in rare cases, hospitals that are not currently 
projected to be DSH eligible and that do not have audited Worksheet S-
10 data may have a potentially aberrant amount of insured patients' 
charity care costs (line 23 column 2). Similar to the approach 
initially adopted in the FY 2022 IPPS/LTCH PPS final rule (86 FR 45245 
and 45246), we proposed to continue to use a threshold of t3 standard 
deviations from the mean ratio of insured patients' charity care costs 
to total uncompensated care costs (line 23 column 2 divided by line 30) 
and a dollar threshold that is the median total uncompensated care cost 
reported on most recent audited cost reports for hospitals that were 
projected to be DSH-eligible. We stated that we continue to believe 
these thresholds are appropriate, in order to address potentially 
aberrant data. However, we proposed to modify the calculation to 
include Worksheet S-10 data from IHS/Tribal hospitals and Puerto Rico 
hospitals consistent with our proposal to begin using Worksheet S-10 
data to determine Factor 3 for these hospitals. We also proposed to 
apply the same thresholds to identify potentially aberrant charity care 
costs data for all cost reporting years that are used in determining 
Factor 3. We noted that based on calculations from the FY 2019 reports, 
the threshold amounts were similar to FY 2018 reports; therefore, we 
explained that we believe it is reasonable to use the same thresholds 
to identify aberrant data for both years. Thus, under the proposal, in 
FY 2023 we would use the same thresholds to identify potentially 
aberrant data for both FY 2018 and FY 2019 reports. In addition, we 
proposed to apply the same threshold amounts originally calculated for 
the FY 2018 reports to identify potentially aberrant data for 
subsequent fiscal years in order to facilitate transparency and 
predictability. Therefore, for FY 2023 and subsequent fiscal years, we 
proposed that in the rare case that a hospital's insured patients' 
charity care costs are greater than $7 million and the ratio of the 
hospital's cost of insured patient charity care (line 23 column 2) to 
total uncompensated care costs (line 30) is greater than 60 percent, we 
would exclude the hospital from the prospective Factor 3 calculation. 
We explained that this trim would only impact hospitals that are not 
currently projected to be DSH-eligible; and therefore, are not part of 
the calculation of the denominator of Factor 3, which includes only 
uncompensated care costs for projected DSH-eligible hospitals. 
Consistent with the approach adopted in the FY 2022 IPPS/LTCH PPS final 
rule, if a hospital would be trimmed under both the UCC trim 
methodology and this alternative trim, we would apply this trim in 
place of the existing UCC trim methodology. We stated that we continue 
to believe this alternative trim more appropriately addresses 
potentially aberrant insured patient charity care costs compared to the 
UCC trim methodology, because the UCC trim is based solely on the ratio 
of total uncompensated care costs to total operating costs and does not 
consider the level of insured patients' charity care costs.
    In addition, we proposed to continue to apply the policy adopted in 
the FY 2022 IPPS/LTCH PPS final rule, for the hospitals that would be 
subject to this alternative trim and are ultimately determined to be 
DSH-eligible at cost report settlement. We explained that if a hospital 
subject to this trim is ultimately determined to be DSH-eligible at 
cost report settlement, its uncompensated care payment should be 
calculated only after the hospital's reporting of insured charity care 
costs on its FY 2023 Worksheet S-10 has been reviewed. Accordingly, the 
MAC would calculate a Factor 3 for the hospital only after reviewing 
the uncompensated care information reported on Worksheet S-10 of the 
hospital's FY 2023 cost report. Then we would calculate Factor 3 for a 
hospital subject to this alternative trim using the same methodology 
used to determine Factor 3 for new hospitals. Specifically, the 
numerator would reflect the uncompensated care costs reported on the 
hospital's FY 2023 cost report, while the denominator would reflect the 
sum of the uncompensated care costs reported on Worksheet S-10 of the 
FY 2019 cost reports of all DSH-eligible hospitals. In addition, 
consistent with our proposed approach for new hospitals, we would apply 
a scaling factor, as discussed previously, to the Factor 3 calculation 
for these hospitals. We stated that we believe applying the scaling 
factor is appropriate for purposes of calculating Factor 3 for all 
hospitals, including new hospitals and hospitals that are treated as 
new hospitals, in order to improve consistency and predictability 
across all hospitals.
    We did not receive any comments on the proposed modifications to 
the uncompensated care data trim methodology. We are finalizing as 
proposed.
 Summary of Methodology
    In summary, under the policies we are finalizing in this FY 2023 
IPPS/LTCH PPS final rule, for FY 2023, we will compute Factor 3 for 
each hospital using the following steps:
    Step 1: Select the hospital's longest cost report from its Federal 
fiscal year (FY) 2018 cost reports and the longest cost report from its 
FY 2019 cost reports. (Alternatively, in the rare case when the 
hospital has no cost report for a particular year because the cost 
report for the previous Federal fiscal year spanned the more recent 
Federal fiscal year, the previous Federal fiscal year cost report will 
be used in this step. In the rare case, that using a previous Federal 
fiscal year cost report results in a period without a report, we will 
use the prior year report, if that cost report spanned the applicable 
period. (For example, if a hospital does not have a FY 2019 cost report 
because the hospital's FY 2018 cost report spanned the FY 2019 time 
period, then we will use the FY 2018 cost report that spanned the FY 
2019 time period for this step. Using the same example, where the 
hospital's FY 2018 report is

[[Page 49045]]

used for the FY 2019 time period, then we will use the hospital's FY 
2017 report if it spans some of the FY 2018 time period. In other 
words, we will not use the same cost report for both the FY 2019 and 
the FY 2018 time periods.) In general, we note that, for purposes of 
the Factor 3 methodology, references to a fiscal year cost report are 
to the cost report that spans the relevant Federal fiscal year period.
    Step 2: Annualize the uncompensated care costs (UCC) from Worksheet 
S-10 Line 30, if a cost report is more than or less than 12 months. (If 
applicable, use the statewide average CCR (urban or rural) to calculate 
uncompensated care costs.)
    Step 3: Combine adjusted and/or annualized uncompensated care costs 
for hospitals that merged using the merger policy.
    Step 4: Calculate Factor 3 for all DSH eligible hospitals using 
annualized uncompensated care costs (Worksheet S-10 Line 30) based on 
FY 2018 cost report data and FY 2019 cost report data (from Step 1, 2 
or 3). New hospitals and other hospitals that are treated as if they 
are new hospitals for purposes of Factor 3 are excluded from this 
calculation.
    Step 5: Average the Factor 3 values from Step 4; that is, add the 
Factor 3 values for FY 2018 and FY 2019 for each hospital, and divide 
that amount by the number of cost reporting periods with data to 
compute an average Factor 3 for the hospital. Multiply by a scaling 
factor.
    For FY 2024 and subsequent fiscal years, these steps will be 
calculated using the most recent 3 years of audited cost reports. (For 
example, in FY 2024, the FY 2018, FY 2019, and FY 2020 reports would be 
used.)
    In the FY 2023 IPPS/LTCH PPS proposed rule, we proposed to make a 
conforming change to the existing regulation at Sec.  
412.106(g)(1)(iii)(C)(8) and to add a new regulation at Sec.  
412.106(g)(1)(iii)(C)(10) to reflect our proposal to calculate Factor 3 
based on the most recent two years of audited data on uncompensated 
care costs in FY 2023. We also proposed to add Sec.  
412.106(g)(1)(iii)(C)(11) to reflect our proposal to calculate Factor 3 
for FY 2024 and subsequent fiscal years based on a 3-year average of 
the most recent available audited data on uncompensated care costs.
    We did not receive any comments on these proposed changes to 
regulations. We are finalizing the proposed changes with only minor 
conforming changes for internal consistency.
(d) Per Discharge Amount of Interim Uncompensated Care Payments
    Since FY 2014, we have made interim uncompensated care payments 
during the fiscal year on a per discharge basis. We have used a 3-year 
average of the number of discharges for a hospital to produce an 
estimate of the amount of the hospital's uncompensated care payment per 
discharge. Specifically, the hospital's total uncompensated care 
payment amount for the applicable fiscal year, is divided by the 
hospital's historical 3-year average of discharges computed using the 
most recent available data to determine the uncompensated care payment 
per discharge for that fiscal year.
    In the FY 2022 IPPS/LTCH PPS final rule (86 FR 45247 and 45248), we 
modified this calculation for FY 2022 to be based on an average of FY 
2018 and FY 2019 historical discharge data, rather than a 3-year 
average that included data from FY 2018, FY 2019, and FY 2020. We 
explained our belief that computing a 3-year average with the FY 2020 
discharge data would underestimate discharges, due to the decrease in 
discharges during the COVID-19 pandemic. For the same reason, we 
proposed to modify this calculation for FY 2023 to be based on the 
average of FY 2018, FY 2019, and FY 2021 historical discharge data, 
rather than a 3-year average of the most recent 3 years of discharge 
data from FY 2019, FY 2020, and FY 2021. We stated that computing a 3-
year average using the most recent 3 years would potentially 
underestimate the number of discharges for FY 2023, due to the effects 
of the COVID-19 pandemic in FY 2020, which was the first year of the 
COVID-19 pandemic. Therefore, we explained our belief that the proposed 
modification may result in a better estimate of the number of 
discharges during FY 2023, for purposes of the interim uncompensated 
care payment calculation. In addition, we noted that our proposal to 
include discharge data from FY 2021 to compute this 3-year average was 
consistent with the proposed use of FY 2021 Medicare claims in the IPPS 
ratesetting, as discussed in section I.F. of the preamble of the FY 
2023 IPPS/LTCH PPS proposed rule. Under this proposal, the resulting 3-
year average of the number of discharges would be used to calculate a 
per discharge payment amount that will be used to make interim 
uncompensated care payments to each projected DSH-eligible hospital 
during FY 2023. We also explained that the interim uncompensated care 
payments made to a hospital during the fiscal year will be reconciled 
following the end of the year to ensure that the final payment amount 
is consistent with the hospital's prospectively determined 
uncompensated care payment for the FY 2023.
    In the FY 2021 IPPS/LTCH PPS final rule (85 FR 58833 and 58834), we 
finalized a voluntary process through which a hospital may submit a 
request to its MAC for a lower per discharge interim uncompensated care 
payment amount, including a reduction to zero, once before the 
beginning of the Federal fiscal year and/or once during the Federal 
fiscal year. In conjunction with this request, the hospital must 
provide supporting documentation demonstrating that there would likely 
be a significant recoupment (for example, 10 percent or more of the 
hospital's total uncompensated care payment or at least $100,000) at 
cost report settlement if the per discharge amount is not lowered. For 
example, a hospital might submit documentation showing a large 
projected increase in discharges during the fiscal year to support 
reduction of its per discharge uncompensated care payment amount. As 
another example, a hospital might request that its per discharge 
uncompensated care payment amount be reduced to zero midyear if the 
hospital's interim uncompensated care payments during the year have 
already surpassed the total uncompensated care payment calculated for 
the hospital.
    Under the policy we finalized in the FY 2021 IPPS/LTCH PPS final 
rule, the hospital's MAC would evaluate these requests and the 
supporting documentation before the beginning of the Federal fiscal 
year and/or with midyear requests when the historical average number of 
discharges is lower than the hospital's projected FY 2023 discharges. 
If following review of the request and the supporting documentation, 
the MAC agrees that there likely would be significant recoupment of the 
hospital's interim Medicare uncompensated care payments at cost report 
settlement, the only change that will be made is to lower the per 
discharge amount either to the amount requested by the hospital or 
another amount determined by the MAC to be appropriate to reduce the 
likelihood of a substantial recoupment at cost report settlement. If 
the MAC determines it would be appropriate to reduce the interim 
Medicare uncompensated care payment per discharge amount, that updated 
amount will be used for purposes of the outlier payment calculation for 
the remainder of the Federal fiscal year. We refer readers to the 
Addendum to this final

[[Page 49046]]

rule for a more detailed discussion of the steps for determining the 
operating and capital Federal payment rate and the outlier payment 
calculation. No change would be made to the total uncompensated care 
payment amount determined for the hospital on the basis of its Factor 
3. In other words, any change to the per discharge uncompensated care 
payment amount will not change how the total uncompensated care payment 
amount will be reconciled at cost report settlement.
    Comment: A couple of commenters recommended that CMS use the 
traditional payment reconciliation process to calculate final payments 
for uncompensated care costs pursuant to section 1886(r)(2) of the Act. 
These commenters did not object to CMS using prospective estimates, 
derived from the best data available, to calculate interim payments for 
uncompensated care costs. However, the commenters stated that interim 
payments should be subject to later reconciliation based on estimates 
derived from actual data from the federal fiscal year. These same 
commenters also asserted that CMS has failed to provide a meaningful 
opportunity to review and comment on the more recent data used in 
developing the final rule before the agency publishes the final rule.
    Response: Consistent with the position that we have taken in 
rulemaking for previous years, we continue to believe that applying our 
best estimates of the three factors used in the calculation of 
uncompensated care payments to determine payments prospectively is most 
conducive to administrative efficiency, finality, and predictability in 
payments (78 FR 50628; 79 FR 50010; 80 FR 49518; 81 FR 56949; 82 FR 
38195; 84 FR 42373; 85 FR 58833 and 86 FR 45246). We continue to 
believe that, in affording the Secretary the discretion to estimate the 
three factors used to determine uncompensated care payments and by 
including a prohibition against administrative and judicial review of 
those estimates in section 1886(r)(3) of the Act, Congress recognized 
the importance of finality and predictability under a prospective 
payment system. As a result, we do not agree with the commenters' 
suggestion that we should establish a process for reconciling our 
estimates of uncompensated care payments, which would be contrary to 
the notion of a prospective payment system. Furthermore, we note that 
this rulemaking has been conducted consistent with the requirements of 
the Administrative Procedure Act and Title XVIII of the Act. Under the 
Administrative Procedure Act, a proposed rule is required to include 
either the terms or substance of the proposed rule or a description of 
the subjects and issues involved. In this case, the FY 2023 IPPS/LTCH 
PPS proposed rule included a detailed discussion of our proposed 
methodology for calculating Factor 3 and the data that would be used. 
We made public the best data available at the time of the proposed rule 
in order to allow hospitals to understand the anticipated impact of the 
proposed methodology and submit comments, and we have considered those 
comments in determining our final policies for FY 2023.
(e) Process for Notifying CMS of Merger Updates and To Report Upload 
Issues
    As we have done for every proposed and final rule beginning in FY 
2014, in conjunction with this final rule, we will publish on the CMS 
website a table listing Factor 3 for all hospitals that we estimate 
will receive empirically justified Medicare DSH payments in FY 2023 
(that is, those hospitals that will receive interim uncompensated care 
payments during the fiscal year), and for the remaining subsection (d) 
hospitals and subsection (d) Puerto Rico hospitals that have the 
potential of receiving an uncompensated care payment in the event that 
they receive an empirically justified Medicare DSH payment for the 
fiscal year as determined at cost report settlement. However, we note 
that a Factor 3 will not be published for new hospitals and hospitals 
that are subject to the alternative trim for hospitals with potentially 
aberrant data that are not projected to be DSH-eligible.
    We also will publish a supplemental data file containing a list of 
the mergers that we are aware of and the computed uncompensated care 
payment for each merged hospital. In the DSH uncompensated care 
supplemental data file, we list new hospitals and the 10 hospitals that 
would be subject to the alternative trim for hospitals with potentially 
aberrant data that are not projected to be DSH-eligible, with a N/A in 
the Factor 3 column.
    Hospitals had 60 days from the date of public display of the FY 
2023 IPPS/LTCH PPS proposed rule in the Federal Register to review the 
table and supplemental data file published on the CMS website in 
conjunction with the proposed rule and to notify CMS in writing of 
issues related to mergers and/or to report potential upload 
discrepancies due to MAC mishandling of Worksheet S-10 data during the 
report submission process (for example, report not reflecting audit 
results due to MAC mishandling or most recent report differs from 
previously accepted amended report due to MAC mishandling). We stated 
that comments raising issues or concerns that are specific to the 
information included in the table and supplemental data file could be 
submitted by email to the CMS inbox at [email protected]. We 
indicated that we would address comments related to mergers and/or 
reporting upload discrepancies submitted to the CMS DSH inbox as 
appropriate in the table and the supplemental data file that we publish 
on the CMS website in conjunction with the publication of this FY 2023 
IPPS/LTCH PPS final rule. All other comments submitted in response to 
our proposed policies for determining uncompensated care payments for 
FY 2023 must have been submitted in one of the three ways found in the 
ADDRESSES section of the proposed rule before the close of the comment 
period in order to be assured consideration. In addition, we note that 
the CMS DSH inbox is not intended for Worksheet S-10 audit process 
related emails, which should be directed to the MACs.
    For FY 2023, we again proposed that hospitals would have 15 
business days from the date of public display of this FY 2023 IPPS/LTCH 
PPS final rule in the Federal Register to review and submit comments on 
the accuracy of the table and supplemental data file published in 
conjunction with the final rule. Any changes to Factor 3 would be 
posted on the CMS website and would be effective beginning October 1, 
2022. We also explained that we continue to believe that hospitals have 
sufficient opportunity during the comment period for the proposed rule 
to provide information about recent and/or pending mergers and/or to 
report upload discrepancies. Hospitals do not enter into mergers 
without advanced planning. A hospital can inform CMS during the comment 
period for the proposed rule regarding any merger activity not 
reflected in supplemental file published in conjunction with the 
proposed rule. As discussed in the proposed rule, we expected to use 
data from the March 2022 HCRIS extract for the FY 2023 final rule, 
which contributed to our increased confidence that hospitals would have 
be able to comment on mergers and report any upload discrepancies 
during the comment period for the FY 2023 IPPS/LTCH PPS proposed rule. 
However, we noted that in the event that there were any remaining 
merger updates and/or upload discrepancies after the final rule, the 15 
business days from the date of

[[Page 49047]]

public display of the FY 2023 IPPS/LTCH PPS final rule deadline should 
allow for the time necessary to prepare and make any corrections to 
Factor 3 calculations before the beginning of the Federal fiscal year.
    We did not receive comments on the notification process for mergers 
or data upload issues. We are finalizing our proposal to afford 
hospitals 15 business days from the public display of this FY 2023 
IPPS/LTCH PPS final rule to submit via email any updated information on 
mergers and/or to report upload discrepancies. We also note that the 
historical FY 2018 and FY 2019 cost reports are publicly available on a 
quarterly basis on the CMS website for analysis and additional review 
of cost report data, separate from the supplemental data file published 
with this final rule.

E. Supplemental Payment for Indian Health Service and Tribal Hospitals 
and Puerto Rico Hospitals for FY 2023 and Subsequent Fiscal Years

    In the IPPS/LTCH PPS rulemaking for several previous fiscal years, 
Indian Health Service (IHS) and Tribal hospitals and hospitals located 
in Puerto Rico have commented about the unique challenges they face 
with respect to uncompensated care due to structural differences in 
health care delivery and financing in these areas compared to the rest 
of the country. In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 
28396), we referred readers to the FY 2022 IPPS/LTCH PPS final rule (86 
FR 45242 and 45243) and the FY 2021 IPPS/LTCH PPS final rule (85 FR 
58824 and 58825) for a discussion of these comments. We also explained 
that we appreciated the concerns raised and the input offered by 
commenters regarding the methodology for calculating uncompensated care 
payments for IHS/Tribal hospitals and the Puerto Rico hospitals. After 
taking into consideration stakeholders' longstanding concerns and their 
input on potential approaches to address these concerns, we proposed to 
establish a new permanent supplemental payment under the IPPS for IHS/
Tribal hospitals and hospitals located in Puerto Rico. As discussed in 
greater detail in the proposed rule, we stated our belief that the 
proposed new supplemental payment would mitigate the anticipated impact 
on IHS/Tribal hospitals and hospitals located in Puerto Rico from our 
proposal to discontinue the use of low-income insured days as a proxy 
for their uncompensated care costs for purposes of determining Factor 3 
of the uncompensated care payment methodology by providing for an 
additional payment to these hospitals that would be determined based 
upon the difference between the amount of the uncompensated care 
payment determined for the hospital using Worksheet S-10 data and an 
approximation of the amount the hospital would have received if we had 
continued to use low-income insured days as a proxy for uncompensated 
care.
    As background, beginning in the FY 2018 IPPS/LTCH PPS final rule 
when we first included Worksheet S-10 data in the calculation of Factor 
3, and continuing through the FY 2022 IPPS/LTCH PPS final rule, we 
relied on the authority under section 1886(r)(2)(C)(i) of the Act to 
use alternative data that is a better proxy for the costs of hospitals 
for treating the uninsured in order to determine Factor 3 for IHS/
Tribal and Puerto Rico hospitals using low-income insured days as a 
proxy for uncompensated care costs. Since FY 2019, Factor 3 for these 
hospitals has been determined using FY 2013 Medicaid days and the most 
recent available data on SSI days. We believed this approach was 
appropriate as the FY 2013 Medicaid days data reflect the most recent 
available information regarding these hospitals' low-income insured 
days before any expansion of Medicaid. In addition, because we 
continued to use low-income insured patient days as a proxy for 
uncompensated care for Puerto Rico hospitals and residents of Puerto 
Rico are not eligible for SSI benefits, we continued to use a proxy for 
SSI days for Puerto Rico hospitals consisting of 14 percent of the 
hospital's Medicaid days, as initially adopted in the FY 2017 IPPS/LTCH 
PPS final rule (81 FR 56953 through 56956). However, we recognized that 
our proposal, which we are finalizing in this final rule, to 
discontinue the use of low-income insured days as a proxy for 
uncompensated care costs would result in a significant financial 
disruption to the IHS/Tribal hospitals and hospitals located in Puerto 
Rico. We explained that, for the vast majority of these hospitals, the 
proposal to use uncompensated care data reported on Worksheet S-10 to 
determine Factor 3 of the uncompensated care payment methodology would 
be expected to result in an approximately 90 to 100 percent reduction 
in uncompensated care payments for FY 2023 compared to FY 2022. We 
referred readers to section I.H. of Appendix A of the proposed rule for 
a discussion of the anticipated impact of the proposal to use 
uncompensated care costs from Worksheet S-10 to determine uncompensated 
care payments for IHS/Tribal hospitals and Puerto Rico hospitals and 
the proposal to establish a new supplemental payment for these 
hospitals.
    In consideration of the unique circumstances faced by the hospitals 
and the comments received from IHS/Tribal hospitals and Puerto Rico 
hospitals in response to prior rulemaking, raising concerns regarding 
financial stability in the event of a change in the data used to 
determine Factor 3, we proposed to use our exceptions and adjustments 
authority under section 1886(d)(5)(I) of the Act to establish a new 
permanent supplemental payment under the IPPS for IHS/Tribal hospitals 
and hospitals located in Puerto Rico, beginning in FY 2023. Section 
1886(d)(5)(I) of the Act authorizes the Secretary to provide by 
regulation for such other exceptions and adjustments to the payment 
amounts under section 1886(d) of the Act as the Secretary deems 
appropriate. We have determined, after taking into consideration 
stakeholders' comments from prior rulemakings, that the supplemental 
payment is necessary so as not to cause undue long-term financial 
disruption to these hospitals as a result of our proposal to 
discontinue the use of low-income insured days as a proxy for 
uncompensated care in determining Factor 3 for IHS/Tribal hospitals and 
Puerto Rico hospitals beginning in FY 2023. In the proposed rule, we 
stated our belief that the proposed supplemental payment would help to 
mitigate the anticipated impact of the proposed changes to the 
uncompensated care payment methodology for these hospitals and 
therefore prevent undue long-term financial disruption for these 
providers.
    We also stated that the proposed new supplemental payment would not 
change in any way the DSH payment methodology under section 
1886(d)(5)(F) of the Act or the uncompensated care payment methodology 
under section 1886(r) of the Act. Therefore, the total uncompensated 
care payment amount would not be affected by this proposal to establish 
a supplemental payment for IHS/Tribal and hospitals located in Puerto 
Rico nor would there be any impact on the amount of the uncompensated 
care payment determined for each DSH-eligible hospital under Sec.  
412.106(g)(1) of the regulations.
    We proposed that for IHS and Tribal hospitals and hospitals located 
in Puerto Rico for which Factor 3 of the uncompensated care payment 
methodology was determined using the low-income insured days proxy in 
FY

[[Page 49048]]

2022, we would calculate a supplemental payment as follows. We would 
use the hospital's FY 2022 uncompensated care payment as the starting 
point for this calculation. We explained that using the FY 2022 
uncompensated care payment would be an appropriate starting point 
because FY 2022 is the most recent year for which we used low-income 
insured days data in the determination of uncompensated care payments 
for IHS/Tribal hospitals and Puerto Rico hospitals and the purpose of 
the proposed supplemental payment is to avoid undue long-term financial 
disruption to these hospitals as a result of our proposal to 
discontinue the use of low-income insured days as a proxy for 
uncompensated care beginning in FY 2023. The base year amount would be 
calculated as the hospital's FY 2022 uncompensated care payment 
adjusted by one plus the percent change in the total uncompensated care 
amount between the applicable year (for example, FY 2023 for purposes 
of this rulemaking) and FY 2022, where the total uncompensated care 
amount for a year is determined as the product of Factor 1 and Factor 2 
for the applicable year. For example, if a hospital's FY 2022 
uncompensated care payment was 1 million, and the percent change 
between FY 2023 and FY 2022 total uncompensated care payments was 
negative 9.1 percent, then the hospital's FY 2023 base year amount 
would be 1 million * (1+(-0.091)), which is 909,000. For the hospitals 
that were not projected to be DSH eligible in FY 2022, we proposed to 
use the uncompensated care payment that the hospital would receive, if 
the hospital were to be determined to be DSH eligible in FY 2022 at 
cost report settlement. For purposes of the proposed rule, the percent 
change between the proposed FY 2023 uncompensated care amount and final 
FY 2022 uncompensated care amount was projected to be negative 9.1 
percent. (This negative 9.1 percent change was calculated based on the 
difference between the proposed FY 2023 uncompensated care amount of 
approximately $6.537 billion and the final FY 2022 uncompensated care 
amount of approximately $7.192 billion, divided by the final FY 2022 
uncompensated care amount). Therefore, we proposed to calculate each 
hospital's base year amount for FY 2023 by multiplying its FY 2022 
uncompensated care amount by 0.909 (1-0.091). We note that in order to 
determine the base year amount for a future fiscal year, the 
calculation would be the hospital's FY2022 uncompensated care amount 
multiplied by one plus the percent change in total uncompensated care 
payments between FY 2022 and the applicable fiscal year. The hospital's 
supplemental payment for a fiscal year would then be determined as the 
difference between the hospital's base year amount and its 
uncompensated care payment for the applicable fiscal year as determined 
under Sec.  412.106(g). If the base year amount is equal to or lower 
than the hospital's uncompensated care payment for the current fiscal 
year, the hospital would not receive a supplemental payment because the 
hospital would not be experiencing financial disruption in that year as 
a result of the use of uncompensated care data from the Worksheet S-10 
in determining Factor 3 of the uncompensated care payment methodology.
    We proposed to align the eligibility and payment processes for the 
new supplemental payment with the processes used to make uncompensated 
care payments. Consistent with the process for determining eligibility 
to receive interim uncompensated care payments adopted in the FY 2014 
IPPS/LTCH final rule, for the supplemental payment, we proposed to base 
eligibility to receive interim supplemental payments on a projection of 
DSH eligibility for the applicable fiscal year. In addition, consistent 
with the approach that is used to calculate interim uncompensated care 
payments on a per discharge basis, for the supplemental payment, we 
proposed to use an average of historical discharges to calculate a per 
discharge amount for interim supplemental payments. We referred readers 
to the FY 2014 IPPS/LTCH PPS final rule for additional background and 
discussion of uncompensated care payment processes (78 FR 50643 through 
50647). Consistent with our proposal to use 3 years of historical 
discharges to determine interim uncompensated care payments for a 
fiscal year, we proposed that the amount of a hospital's supplemental 
payment calculated for a fiscal year would be divided by the hospital's 
historical 3-year average of discharges computed using the most recent 
available data to determine an estimated per discharge payment amount.
    For FY 2023, we proposed to use FY 2018, FY 2019, and FY 2021 
discharge data to determine a hospital's historical 3-year average of 
discharges, because we continued to believe the FY 2020 discharge data 
would underestimate discharges, due to the effects of the COVID-19 
pandemic in FY 2020. In addition, consistent with the policy of 
including per-discharge uncompensated care payment amounts in the 
outlier calculation, which was initially adopted in the FY 2014 IPPS/
LTCH PPS final rule, we proposed to use our authority under section 
1886(d)(5)(I) of the Act to include the per-discharge supplemental 
payment in the outlier payment determination under section 
1886(d)(5)(A) of the Act. We referred readers to the Addendum to the 
proposed rule for further discussion of the outlier payment 
calculation.
    Consistent with the process used to reconcile interim uncompensated 
care payments, we proposed that the MAC would reconcile the interim 
supplemental payments at cost report settlement to ensure that the 
hospital receives the full amount of the supplemental payment that was 
determined prior to the start of the fiscal year. Consistent with the 
process used for cost reporting periods that span multiple Federal 
fiscal years, we proposed that a pro rata supplemental payment 
calculation may be made if the hospital's cost reporting period differs 
from the Federal fiscal year. Thus, the final supplemental payment 
amounts that would be included on a cost report spanning two Federal 
fiscal years would be the pro rata share of the supplemental payment 
associated with each Federal fiscal year. This pro rata share would be 
determined based on the proportion of the applicable Federal fiscal 
year that is included in that cost reporting period. We referred 
readers to the FY 2014 interim final rule for additional background and 
discussion of the processes for determining pro rata uncompensated care 
payments (78 FR 61191 through 61196).
    We proposed that the MAC would make a final determination with 
respect to a hospital's eligibility to receive the supplemental payment 
for a fiscal year, in conjunction with its final determination of the 
hospital's eligibility for DSH payments and uncompensated care payments 
for that fiscal year. We noted that if a hospital is determined not to 
be DSH eligible for a fiscal year then the hospital would not be 
eligible to receive a supplemental payment for that fiscal year. In the 
proposed rule, we stated our belief that linking eligibility for the 
supplemental payment to eligibility for DSH payments and the 
uncompensated care payment is appropriate because a hospital that is 
not eligible to receive an uncompensated care payment for a fiscal year 
would not experience any financial disruption due to the 
discontinuation of the low-income insured days proxy and the use of

[[Page 49049]]

Worksheet S-10 data in determining Factor 3 for that fiscal year.
    In addition, we proposed that IHS/Tribal hospitals and Puerto Rico 
hospitals that do not have a FY 2022 Factor 3 amount determined under 
Sec.  412.106(g)(1)(iii)(C)(9) using the low-income insured days proxy 
or that are new hospitals that begin participating in the Medicare 
program on or after October 1, 2022, would not be eligible to receive 
the supplemental payment. We explained that these hospitals will not 
experience any reduction to their uncompensated care payments due to 
the proposed discontinuation of the low-income insured days proxy 
because they are not currently receiving uncompensated care payments 
determined using the proxy. We proposed to redesignate the existing 
provision at Sec.  412.106(h) as Sec.  412.106(i) and to add a new 
provision at Sec.  412.106(h) to reflect the methodology for 
calculating the supplemental payment for FY 2023 and subsequent fiscal 
years.
    We sought comments on our proposal to establish this new 
supplemental payment for IHS/Tribal hospitals and Puerto Rico 
hospitals. As discussed in section IV.D.3. of this final rule, we also 
solicited comments on alternatives both to our proposal to use data on 
uncompensated care costs from the Worksheet S-10 to determine Factor 3 
for IHS/Tribal hospitals and Puerto Rico hospitals and to the continued 
use of low-income insured days as a proxy for the uncompensated care 
costs of these hospitals. In addition, we sought comments on how to 
best measure and define the uncompensated care costs associated with 
these hospitals that might not otherwise be captured in Factor 3 
calculations based on Worksheet S-10 data. Given the close 
interrelationship between our proposed changes to the methodology for 
determining Factor 3 of the uncompensated care payment methodology for 
IHS/Tribal hospitals and Puerto Rico hospitals and the proposed new 
supplemental payment for these hospitals, we discuss the comments 
received on both proposals in this section of this final rule.
    Comment: The majority of commenters expressed appreciation for CMS' 
creativity in devising the proposed new supplemental payment to 
mitigate the anticipated financial impact from the discontinuation of 
low-income insured days as a proxy for uncompensated care costs for IHS 
and Tribal hospitals and hospitals located in Puerto Rico. Some 
commenters stated there are longstanding inequities in DSH and 
uncompensated care calculations for Puerto Rico hospitals due to the 
lack of an SSI benefit for residents of the U.S. territories. These 
commenters also suggested an alternative methodology for calculating 
the supplemental payment for hospitals in Puerto Rico.
    Specifically, the commenters recommended that CMS calculate the 
supplemental payment for Puerto Rico hospitals using a base year amount 
determined from Medicaid days and an SSI days proxy of at least 40 
percent but no less than 35 percent of Medicaid days, instead of the 
current 14 percent. Commenters further suggested that CMS determine a 
second empirical DSH eligibility threshold for hospitals in Puerto Rico 
based on the suggested SSI days proxy of 40 percent of Medicaid days, 
such that if the sum of the Medicaid fraction and the SSI days proxy 
exceeds 15 percent, then the hospital would be eligible to receive 
uncompensated care payments and the new supplemental payment. A 
commenter, in support of this alternative methodology, noted that, 
under the proposed supplemental payment methodology, Puerto Rico 
hospitals would receive an 11.06 percent reduction in Medicare DSH 
payments in FY 2023 as compared to FY 2022. The same commenter noted 
that the reduction in DSH payments could also reduce Medicare Advantage 
(MA) benchmarks for Puerto Rico in 2024 and, as a result, impact 
approximately 630,000 Medicare beneficiaries enrolled in MA plans, 
including 280,000 dual-eligible individuals.
    Another commenter expressed support for the proposed 
discontinuation of low-income insured days as a proxy for uncompensated 
care costs for IHS and Tribal hospitals and hospitals located in Puerto 
Rico. However, this commenter recommended that CMS reduce the size of 
supplemental payments to hospitals in Puerto Rico to an empirically 
justified level. This commenter noted that the continued use of 
Medicaid days as a proxy for uncompensated care costs in Puerto Rico 
has resulted in a substantial increase in uncompensated care payments. 
Further, this commenter stated that maintaining the overall payments at 
the proposed levels through the supplemental payment would create high 
Medicare profit margins at Puerto Rico hospitals and distort the MA 
benchmarks, as it would increase FFS spending by more than 25 percent 
above what it would have been if Puerto Rico hospitals received 
uncompensated care payments based only on their reported uncompensated 
care costs. The commenter also opposed the disbursement of the 
supplemental payments as an add-on payment to the IPPS payment rates 
for hospitals in Puerto Rico and recommended that uncompensated care 
payments not be factored into MA benchmarks.
    A few commenters expressed support for the proposed supplemental 
payment without suggesting enhancements to the policy. One of these 
commenters emphasized the importance of implementing the supplemental 
payment as a permanent policy.
    A commenter opposed CMS' proposal to discontinue the calculation of 
uncompensated care costs using low income insured days for hospitals in 
Puerto Rico without a separate policy in place for receiving the 
supplemental payment. Instead, the commenter suggested that CMS use a 
phased approach such that the agency would continue to calculate 
uncompensated care costs for hospitals in Puerto Rico using low income 
insured days until a future rulemaking. The commenter further suggested 
that CMS eventually phase in payments calculated using Worksheet S-10 
along with the supplemental payment.
    Another commenter specifically opposed the exclusion of new 
hospitals in Puerto Rico from receiving the supplemental payment. The 
same commenter noted that because hospitals newly established after 
October 2013 did not have Medicaid days for the period before the 
Affordable Care Act was implemented, the uncompensated care costs for 
these hospitals are already calculated using Worksheet S-10 but with no 
supplemental payments. The commenter also noted that because hospitals 
established after October 2013 operate under the same conditions as 
hospitals established before October 2013, these hospitals should 
receive the proposed supplemental payments in a manner similar to those 
hospitals for which we proposed to transition to the use of Worksheet 
S-10 data to determine uncompensated care costs starting in FY 2023. 
Finally, this commenter requested that CMS consider calculating 
uncompensated care costs for an impacted Puerto Rico hospital 
(established after 2013) for the period from FY 2020 through FY 2022 
using Medicaid days and not Worksheet S-10 data.
    Response: We appreciate this input from commenters regarding the 
proposal to establish a new supplement payment for hospitals in Puerto 
Rico and IHS and Tribal hospitals and the concerns raised regarding the 
proposed changes to the data used to determine uncompensated care costs 
for these hospitals. We continue to recognize the unique financial 
circumstances and challenges

[[Page 49050]]

faced by Puerto Rico hospitals related to uncompensated care cost 
reporting on Worksheet S-10. With regard to the recommendation to 
calculate the supplemental payment using a base year amount determined 
using Medicaid days and an SSI days proxy of at least 40 percent, we 
note that since FY 2019, Factor 3 for hospitals in Puerto Rico has been 
determined using FY 2013 Medicaid days and the most recent available 
data on SSI days and because residents of Puerto Rico are not eligible 
for SSI benefits, we continued to use a proxy for SSI days for Puerto 
Rico hospitals consisting of 14 percent of the hospital's Medicaid 
days, as initially adopted in the FY 2017 IPPS/LTCH PPS final rule (81 
FR 56953 through 56956). We also note that we did not receive comments 
expressing concerns regarding this policy when it was finalized for FY 
2019. However, for the reasons explained in the FY 2023 IPPS/LTCH PPS 
proposed rule (87 FR 28391), we have determined that data on low income 
insured days is no longer a good proxy for the costs of hospitals in 
treating the uninsured and that we can no longer conclude that 
alternative data to the data on uncompensated care costs reported on 
the Worksheet S-10 are available for Puerto Rico hospitals that are a 
better proxy for the costs of these hospitals in treating the 
uninsured.
    With respect to the comment recommending that we adopt a second 
eligibility threshold for empirically justified DSH payments based on 
the suggested SSI days proxy of 40 percent of Medicaid days, we note 
that in the FY 2023 IPPS/LTCH PPS proposed rule, we did not propose to 
adopt a proxy for Puerto Rico hospitals' SSI days for purposes of 
determining eligibility to receive DSH payments and calculating the 
empirically justified Medicare DSH payment. Therefore, we consider this 
comment to be outside the scope of the proposed rule. We note, however, 
that while section 1886(r)(2)(C)(i) of the Act allows for the use of 
alternative data as a proxy to determine the costs of subsection (d) 
hospitals for treating the uninsured for purposes of determining 
uncompensated care payments, section 1886(r)(1) of the Act requires the 
Secretary to pay an empirically justified DSH payment that is equal to 
25 percent of the amount of the Medicare DSH payment that would 
otherwise be made under section 1886(d)(5)(F) of the Act to a 
subsection (d) hospital. Section 1886(d)(5)(F)(vi) of the Act, which 
prescribes the disproportionate patient percentage used to determine 
empirically justified Medicare DSH payments, specifically refers to the 
SSI days in the Medicare fraction and does not allow the use of 
alternative data. Accordingly, we disagree with the commenter's 
assertion that there is legal support for CMS to use a proxy for Puerto 
Rico hospitals' SSI days in the calculation of the empirically 
justified Medicare DSH payment.
    Regarding the comment that hospitals in Puerto Rico hospitals will 
receive an 11.06 percent reduction in Medicare DSH payments in FY 2023 
as compared to FY 2022, we note that, under the policies we are 
finalizing in this final rule, the combined amount of uncompensated 
care payments and supplemental payments for FY 2023 will be less than 
11.06 percent below the amount of uncompensated care payments for FY 
2022. We refer readers to the discussion of the impact of our final 
policies regarding Medicare uncompensated care payments and the new 
supplemental payment in Section I.H. of Appendix A of this final rule. 
In addition, we note that the base year amount used in calculating the 
supplemental payment will change over time relative to the total 
uncompensated care amount. Accordingly, for years in which there is an 
increase in the total uncompensated care total amount, the hospital's 
supplemental payment calculation would reflect a higher base year 
amount, and for the years in which there is a decrease in the total 
uncompensated care total amount, the hospital's supplemental payment 
calculation would reflect a lower base year amount.
    With regard to the comment that the supplemental payment would 
impact the Medicare Advantage benchmarks, we believe the combined 
amount of empirically justified DSH payments, uncompensated care 
payments, and supplemental payments to IHS/Tribal hospitals and Puerto 
Rico hospitals will be comparable to the amount these hospitals would 
have received if CMS had continued to use the low-income days proxy to 
determine Factor 3 of the uncompensated care payment methodology. As a 
result, the new supplemental payments are expected to have no impact on 
MA benchmarks in Puerto Rico. Given that the MA capitation calculations 
are on a different timeline than the annual rulemaking for the IPPS 
(that is, calendar year rather than Federal fiscal year), the 2024 MA 
benchmarks would be the first time any effects would be reflected.
    We disagree with the commenter who noted that there is no mechanism 
in place for receiving the supplemental payment. We refer readers to 
the FY 2014 IPPS/LTCH PPS proposed rule for additional background and 
discussion of uncompensated care payment processes (78 FR 50643 through 
50647). As discussed in the FY 2023 IPPS/LTCH PPS proposed rule, we 
proposed to determine an estimated per discharge add-on payment amount 
based on the amount of a hospital's supplemental payment calculated for 
a fiscal year divided by the hospital's historical three-year average 
of discharges, computed using the most recently available data.
    Regarding the concerns raised with respect to our proposal that 
hospitals in Puerto Rico established after October 2013 would be 
ineligible to receive the supplemental payment, we note that, as 
explained in the FY 2023 IPPS/LTCH PPS proposed rule, we proposed to 
establish the supplemental payment to mitigate any long-term financial 
disruption as a result of our proposal to discontinue the use of low-
income insured days as a proxy for uncompensated care costs in 
determining Factor 3. Uncompensated care costs for Puerto Rico 
hospitals established after October 2013 are already determined using 
Worksheet S-10 data. As a result, these hospitals will not experience 
any reduction to their uncompensated care payments due to the proposed 
discontinuation of the low-income insured days proxy because they are 
not currently receiving uncompensated care payments determined using 
the proxy. Thus, we do not believe it is appropriate to modify the 
proposed eligibility criteria for the supplemental payment to include 
these hospitals at this time. However, we intend to monitor 
uncompensated care payments to these hospitals and may revisit this 
issue in future rulemaking.
    Regarding the commenter that requested that CMS consider 
calculating the uncompensated care costs for FY 2020 through FY 2022 
for a Puerto Rico hospital (established after 2013) using Medicaid days 
and not Worksheet S-10 data, we believe this comment is out of scope of 
this rulemaking. We note that the policy for new hospitals in Puerto 
Rico was initially adopted in the FY 2019 IPPS/LTCH PPS final rule, and 
we did not propose any modifications to this policy in the FY 2023 
IPPS/LTCH PPS proposed rule.
    Comment: Commenters expressed support for CMS' proposal to 
establish a new supplemental payment for IHS and Tribal hospitals to 
mitigate the anticipated impact of the agency's proposal to discontinue 
the use of low-income insured days as a proxy to calculate 
uncompensated care payments for these hospitals. Commenters requested 
that CMS confirm that the

[[Page 49051]]

supplemental payments would result in an equal or higher uncompensated 
care payment amount than in prior years. Commenters also opposed the 
exclusion of new IHS and Tribal hospitals from receiving the 
supplemental payment, with another commenter suggesting that CMS 
finalize the supplemental payment for existing IHS/Tribal hospitals as 
an interim measure while the agency devises an alternate approach that 
would be applicable to all IHS/Tribal hospitals. These commenters also 
urged CMS to provide an option for hospitals to opt out of the new 
supplemental payment methodology in the future years if they preferred 
payment in a manner similar to non-Tribal hospitals.
    Response: We appreciate the input from commenters on our proposal 
to establish a new supplemental payment for IHS and Tribal hospitals. 
We continue to recognize the unique nature of these hospitals and the 
special circumstances they face.
    Regarding commenters' request that CMS confirm that the proposed 
supplemental payment will result in an overall payment amount that is 
equal to or higher than the uncompensated care payments for prior years 
determined using the low-income days proxy, we note that the base year 
amount used to calculate a hospital's supplemental payment will change 
over time relative to changes in the total uncompensated care amount. 
For years in which there is an increase in the total uncompensated care 
total amount, the hospital's supplemental payment calculation would use 
a higher base year amount, and for the years in which there is a 
decrease in the total uncompensated care total amount, the hospital's 
supplemental payment calculation would use a lower base year amount.
    Regarding the concerns raised by commenters with respect to our 
proposal to limit the new supplemental payment to existing IHS/Tribal 
hospitals that have a Factor 3 amount for FY 2022 determined using the 
low-income insured days proxy, we note that, as explained in the FY 
2023 IPPS/LTCH PPS proposed rule, we proposed to establish the 
supplemental payment to mitigate any long-term financial disruption as 
a result of our proposal to discontinue the use of low-income insured 
days as a proxy for uncompensated care costs in determining Factor 3. 
However, new IHS/Tribal hospitals for which uncompensated care costs 
have not previously been determined using the low-income insured days 
proxy will not experience any reduction to their uncompensated care 
payments due to the proposed discontinuation of the proxy. Thus, we do 
not believe it is appropriate to extend the supplemental payment to 
include new IHS/Tribal hospitals at this time. However, we will monitor 
uncompensated care payments to these hospitals and may revisit this 
issue in future rulemaking.
    In regard to an option for hospitals to opt out of the new 
supplemental payment methodology in the future years, we believe that 
no modification to our proposed methodology is necessary, because, 
under the proposed supplemental payment methodology, which we are 
finalizing in this final rule, an IHS/Tribal hospital or Puerto Rico 
hospital will receive the full uncompensated care payment determined 
using its Worksheet S-10 data. A hospital will only receive the 
supplemental payment if it increases the overall amount payable to the 
hospital, so there does not appear to be a clear reason for a hospital 
to opt out of the supplemental payment.
    After consideration of the comments received, we are finalizing 
both our proposal to discontinue the use of the low-income insured days 
proxy and to rely solely on Worksheet S-10 data to calculate Factor 3 
of the uncompensated care payment methodology for IHS/Tribal hospitals 
and Puerto Rico hospitals and our proposal to establish a new 
supplemental payment for Puerto Rico hospitals and IHS/Tribal 
hospitals, without modification. We are also finalizing the proposed 
provision at Sec.  412.106(h) governing the new supplemental payment 
without modification.
    The percent change between the final FY 2023 uncompensated care 
amount and final FY 2022 uncompensated care amount is negative 4.4 
percent. (This negative 4.4 percent change is calculated based on the 
difference between the final FY 2023 uncompensated care amount of 
approximately $6.874 billion and the final FY 2022 uncompensated care 
amount of approximately $7.192 billion, divided by the final FY 2022 
uncompensated care amount). Therefore, consistent with the methodology 
in Sec.  412.106(h)(3)(i), we will calculate each hospital's base year 
amount for FY 2023 by multiplying its FY 2022 uncompensated care amount 
by 0.956 (1-0.044).

F. Medicare Disproportionate Share Hospital (DSH) Payments: Counting 
Days Associated With Section 1115 Demonstrations in the Medicaid 
Fraction (Sec.  412.106)

    In the FY 2023 IPPS/LTCH PPS proposed rule, we proposed revisions 
to the regulation relating to the treatment of section 1115 
demonstration days for purposes of the DSH adjustment (87 FR 28398 
through 28402). The agency received numerous, detailed comments on this 
proposal. We thank the commenters for their input on the proposal. Due 
to the number and nature of the comments that we received on our 
proposal, and after further consideration of the issue, we have 
determined not to move forward with the current proposal. We expect to 
revisit the treatment of section 1115 demonstration days for purposes 
of the DSH adjustment in future rulemaking, and we encourage interested 
parties to review any future proposal on this issue and to submit their 
comments at that time.

V. Other Decisions and Changes to the IPPS for Operating Costs

A. Changes in the Inpatient Hospital Update for FY 2023 (Sec.  
412.64(d))

1. FY 2023 Inpatient Hospital Update
    In accordance with section 1886(b)(3)(B)(i) of the Act, each year 
we update the national standardized amount for inpatient hospital 
operating costs by a factor called the ``applicable percentage 
increase.'' For FY 2023, we stated in the proposed rule that we are 
setting the applicable percentage increase by applying the adjustments 
listed in this section in the same sequence as we did for FY 2022. (We 
note that section 1886(b)(3)(B)(xii) of the Act required an additional 
reduction each year only for FYs 2010 through 2019.) Specifically, 
consistent with section 1886(b)(3)(B) of the Act, as amended by 
sections 3401(a) and 10319(a) of the Affordable Care Act, we stated 
that we are setting the applicable percentage increase by applying the 
following adjustments in the following sequence. The applicable 
percentage increase under the IPPS for FY 2023 is equal to the rate-of-
increase in the hospital market basket for IPPS hospitals in all areas, 
subject to all of the following:
     A reduction of one-quarter of the applicable percentage 
increase (prior to the application of other statutory adjustments; also 
referred to as the market basket update or rate-of-increase (with no 
adjustments)) for hospitals that fail to submit quality information 
under rules established by the Secretary in accordance with section 
1886(b)(3)(B)(viii) of the Act.
     A reduction of three-quarters of the applicable percentage 
increase (prior to the application of other statutory adjustments; also 
referred to as the market basket update or rate-of-increase

[[Page 49052]]

(with no adjustments)) for hospitals not considered to be meaningful 
EHR users in accordance with section 1886(b)(3)(B)(ix) of the Act.
     An adjustment based on changes in economy-wide multifactor 
productivity (MFP) (the productivity adjustment).
    Section 1886(b)(3)(B)(xi) of the Act, as added by section 3401(a) 
of the Affordable Care Act, states that application of the productivity 
adjustment may result in the applicable percentage increase being less 
than zero.
    We note, in compliance with section 404 of the MMA, in the FY 2022 
IPPS/LTCH PPS final rule (86 FR 45194 through 45204), we replaced the 
2014-based IPPS operating and capital market baskets with the rebased 
and revised 2018-based IPPS operating and capital market baskets 
beginning in FY 2022.
    We proposed to base the FY 2023 market basket update used to 
determine the applicable percentage increase for the IPPS on IHS Global 
Inc.'s (IGI's) fourth quarter 2021 forecast of the 2018-based IPPS 
market basket rate-of-increase with historical data through third 
quarter 2021, which was estimated to be 3.1 percent. We also proposed 
that if more recent data subsequently became available (for example, a 
more recent estimate of the market basket update), we would use such 
data, if appropriate, to determine the FY 2023 market basket update in 
the final rule.
    Comment: Several commenters were concerned the proposed market 
basket update was not accurately reflecting hospital input inflation 
citing many examples including ongoing labor shortages, supply chain 
disruptions, prices for medical equipment, and the impact of Ukraine/
Russia war. They urged CMS to adjust its market basket update 
methodology for FY 2023 to adjust for more recent data and to further 
adjust its estimate to appropriately capture significant inflationary 
trends that will further fuel rising hospital operating costs but may 
not yet be fully captured in IGI's updated market basket forecast in 
the second quarter of 2022. Commenters requested CMS recognize that 
hospital inflation will generally lag economy-wide inflation and that 
the expectations for sustained inflation should be recognized in the 
projection of the hospital market basket for FY 2023. Several 
commenters stated the proposed market basket update is a time-lagged 
estimate that uses historical data to forecast into the future. The 
commenters stated that when historical data is no longer a good 
predictor of future changes, the market basket becomes inadequate. A 
commenter stated that the end of calendar year 2021 into calendar year 
2022 should not be considered a steady-state economic environment that 
is a continuance of past trends. A commenter encouraged CMS to err on 
the side of steadily increasing inflation into 2023 rather than any 
material deceleration assumption.
    Other commenters urged CMS to rely on more recent forecasts to 
determine the FY 2023 update. A commenter noted CBO May 2022 baseline 
projections which had a market basket increase that is 1.1 percentage 
points higher than the proposed FY 2023 IPPS market basket percentage 
increase. Several commenters requested that CMS review other inflation 
data sources such as the Consumer Price Index (CPI) and the core 
Personal Consumption Expenditures deflator, and suggested that the 
market basket increase at least match or exceed these rates of 
increases.
    Response: Section 1886(b)(3)(B)(iii) of the Act states the 
Secretary shall update IPPS payments based on a market basket 
percentage increase that reflects an index of appropriately weighted 
indicators of changes in wages and prices that are representative of 
the mix of goods and services included in such inpatient hospital 
services. The 2018-based IPPS market basket is a fixed-weight, 
Laspeyres-type price index that measures the change in price, over 
time, of the same mix of goods and services purchased by hospitals in 
the base period. The general inflation measures cited by the commenters 
would not reflect this same mix of goods and services.
    We agree with the commenters that recent higher inflationary trends 
have impacted the outlook for price growth over the next several 
quarters. At the time of the FY 2023 IPPS/LTCH PPS proposed rule, based 
on IGI's fourth quarter 2021 forecast with historical data through 
third quarter 2021, IGI forecasted the 2018-based IPPS market basket 
update of 3.1 percent for FY 2023 reflecting forecasted compensation 
prices of 3.8 percent (by comparison, compensation price growth in the 
2018-based IPPS market basket averaged 2.2 percent from 2012-2021). As 
stated previously, in the FY 2023 IPPS/LTCH PPS proposed rule, we 
proposed that if more recent data became available, we would use such 
data, if appropriate, to derive the final FY 2023 IPPS market basket 
update for the final rule. For this final rule, we now have an updated 
forecast of the price proxies underlying the market basket that 
incorporates more recent historical data and reflects a revised outlook 
regarding the U.S. economy (including the more recent historical CPI 
growth, impacts of the Russia/Ukraine war, current expectations 
regarding changes to Federal Reserve interest rates, and tight labor 
markets). Based on IGI's second quarter 2022 forecast with historical 
data through first quarter 2022, we are projecting a FY 2023 IPPS 
market basket update of 4.1 percent (reflecting forecasted compensation 
price growth of 4.8 percent) and productivity adjustment of 0.3 
percentage point. Therefore, as discussed further in this section and 
after consideration of the comments received, for FY 2023, the final 
applicable percentage increase for a hospital that submitted quality 
data and is a meaningful EHR user is 3.8 percent (4.1 percent less 0.3 
percentage point), compared to the 2.7 percent that was proposed. We 
note that the final FY 2023 IPPS market basket growth rate of 4.1 
percent would be the highest market basket update implemented in an 
IPPS final rule going back to FY 1998.
    Comment: Several commenters suggested that CMS use alternative 
sources of data that they stated better reflect input price inflation 
to calculate the FY 2023 market basket update. A commenter stated that 
in absence of such data, CMS is urged to consider an alternative 
approach to better align the market basket updates with increases in 
the costs needed to care for Medicare beneficiaries. Several commenters 
encouraged CMS to implement a higher market basket update than 
proposed, reflecting alternative sources of cost data such as the 
Medicare cost reports. A commenter requested that CMS provide a market 
basket update of at least 5 percent.
    Several commenters proposed that CMS apply a market basket increase 
of approximately 8 percent representing estimated trends in allowable 
Medicare costs per risk-adjusted discharge from the Medicare cost 
reports from FY 2019 to FY 2020. To support this method, commenters 
provided the language in the IPPS statute and stated that they believe 
that Medicare cost report data meets the statutory requirement as these 
data capture all allowable costs, including personnel costs and 
excluding non-operating costs that comprise routine, ancillary, and 
special care unit inpatient hospital services. The commenter stated 
that given that these data comprise all the costs--on a volume and 
risk-adjusted basis--necessary to deliver hospital care it represents 
``appropriately weighted indicators of changes in wages and prices 
which are representative of the mix of good and services . . .'' 
necessary to provide inpatient hospital care to Medicare beneficiaries. 
Commenters stated their belief that Medicare cost report data are a 
more

[[Page 49053]]

accurate projection of the cost inflation anticipated by hospitals 
during FY 2023 than the forecast IGI data used in the proposed rule. 
The commenters further noted that changes in volume and intensity are 
accounted for in the market basket update when CMS rebases or revises 
it, which they stated is infrequent, typically occurring once every 
four years. They believe their proposed methodology of using Medicare 
cost report data would fully account for changes in volume and acuity 
annually, thus resulting in a more accurate proxy.
    Another commenter analyzed Medicare cost report data and found that 
compensation costs increased by more than the IPPS market basket 
updates of 3.0 percent and 2.4 percent for FYs 2020 and 2021, 
respectively. The commenter recommended that CMS adjust the IGI 
compensation price indices and the overall inpatient price indices 
based on the percent change in compensation costs as derived from the 
Medicare cost reports.
    A commenter recommended that CMS use its exceptions and adjustments 
authority to substitute Premier Inc. data for the IGI forecast to 
provide hospitals with an increased payment update in FY 2023 to 
accurately reflect labor costs. Additionally, the commenter recommended 
that CMS' Office of the Actuary reevaluate the data sources that it 
uses for calculating labor costs and consider adopting new or 
supplemental data sources in future rulemaking that more accurately 
reflect the cost of labor, such as more real time data from the 
hospital community. While the commenter stated that they were unable to 
forecast a market basket update for FY 2023, they noted the substantial 
impact a 10 percent increase in the labor components would have on the 
historical market basket for FY 2021, increasing the estimate by 
several percentage points under this hypothetical scenario.
    Response: We believe the 2018-based IPPS market basket increase 
adequately reflects the average change in the price of goods and 
services hospitals purchase in order to provide IPPS medical services, 
and is technically appropriate to use as the market basket percentage 
increase in accordance with section 1886(b)(3)(B)(iii). As described in 
the FY 2022 IPPS/LTCH PPS final rule (86 FR 45194 through 45213), the 
IPPS market basket is a fixed-weight, Laspeyres-type index that 
measures price changes over time and would not reflect increases in 
costs associated with changes in the volume or intensity of input goods 
and services. As such, the IPPS market basket increase would reflect 
the prospective price pressures described by the commenters as 
increasing during a high inflation period (such as faster wage price 
growth or higher energy prices), but would inherently not reflect other 
factors that might increase the level of costs, such as the quantity of 
labor used or any shifts between contract and staff nurses (which would 
be reflected in the Medicare cost report data). We note that cost 
changes (that is, the product of price and quantities) would only be 
captured in the market basket weights when the index is rebased and the 
base year is updated to a more recent time period.
    We disagree with the commenters that costs as reported on the 
Medicare cost report are suitable for determining the trend in 
compensation prices for the market basket update. Section 
1886(b)(3)(B)(iii) of the Act states the Secretary shall estimate a 
market basket percentage increase based on an index of appropriately 
weighted indicators of changes in wages and prices which are 
representative of the mix of goods and services included in such 
inpatient hospital services. While the current IPPS market basket 
percentage increase captures price changes associated with the goods 
and services hospitals purchase in providing care, the Medicare cost 
report data also reflects factors that are beyond those that impact 
wage or price growth. For instance, overall costs as reported by 
hospitals would also reflect changes in the mix of inputs used to 
provide services; since 2020, observed IPPS case-mix (and associated 
higher payments to hospitals) has increased faster than in prior years 
and would likely reflect the use of more skilled care needed to provide 
these services.
    Regarding commenters' request that CMS consider other methods and 
data sources to calculate the final rule market basket update, we 
believe the 2018-based IPPS market basket continues to appropriately 
reflect IPPS cost structures and we believe the price proxies used 
(such as those from BLS that reflect wage and benefit price growth) are 
an appropriate representation of price changes for the inputs used by 
hospitals in providing services. We further note that we did not 
propose to use other methods or data sources to calculate the final 
market basket update for FY 2023. Consistent with our proposal, we have 
used more recent historical data and an updated forecast (that reflects 
a revised inflationary outlook) to calculate a final IPPS market basket 
percentage increase for FY 2023 of 4.1 percent, which is one percentage 
point higher than the proposed market basket percentage increase of 3.1 
percent set forth in the FY 2023 IPPS/LTCH PPS proposed rule.
    Comment: Several commenters also expressed concerns regarding the 
use of BLS' Employment Cost Index (ECI), which accounts for 53 percent 
of the market basket, stating it did not accurately reflect hospitals' 
compensation costs after the labor market changes triggered by the PHE. 
A commenter stated that this claim can be evidenced by comparing growth 
in labor costs from the Medicare cost report data to the ECI growth. 
The commenters also state that hospitals have faced a shortage of local 
labor as the PHE has progressed and have had to increasingly turn to 
contract labor, particularly for the nursing professions, which in turn 
has contributed to increased compensation costs. The commenters noted 
that CMS's proposed market basket update reflected a 3.8 percent 
increase in compensation, which they believe does not accurately 
reflect changes in current labor costs that they believe are not 
transitory.
    Commenters noted that the ECI does not capture inflation in 
contract labor compensation while the hospital market basket does 
include contract labor costs when calculating the compensation cost 
weights and stated that including the contract labor costs along with 
other compensation costs assumes contract labor compensation growth 
will grow at the same rate as non-contract labor compensation. The 
commenters stated that this assumption is not supported by evidence 
citing published studies. Commenters also noted analysis by Premier 
Inc., which showed faster hourly labor rates than the ECI for FY 2021.
    Response: As previously discussed, section 1886(b)(3)(B)(iii) of 
the Act states the Secretary shall estimate a market basket percentage 
increase based on an index of appropriately weighted indicators of 
changes in wages and prices which are representative of the mix of 
goods and services included in such inpatient hospital services. The 
2018-based IPPS market basket is a fixed-weight, Laspeyres-type price 
index that measures the change in price, over time, of the same mix of 
goods and services purchased in the base period. Any changes in the 
quantity or mix of goods and services (that is, intensity) purchased 
over time relative to a base period are not measured. This type of IPPS 
market basket has been in place since the implementation of the IPPS as 
well as used for other CMS market baskets.
    For the compensation cost weight in the 2018-based IPPS market 
basket (which includes salaried and contract

[[Page 49054]]

labor employees), we use the ECI for wages and salaries and benefits 
for all civilian hospital workers to proxy the price increases of labor 
for IPPS hospitals. The ECI (published by the BLS) measures the change 
in the hourly labor cost to employers, independent of the influence of 
employment shifts among occupations and industry categories. We note 
that the Medicare cost report data shows contract labor hours account 
for about 3 percent of total compensation hours (reflecting employed 
and contract labor staff) for IPPS hospitals in 2020. Data through 2021 
are incomplete at this time. Therefore, while we acknowledge that the 
ECI measures only reflect price changes for employed staff, we believe 
that the ECI for hospital workers is accurately reflecting the price 
change associated with the labor used to provide hospital care (as 
employed workers' hours account for 97 percent of hospital compensation 
hours) and appropriately does not reflect other factors that might 
affect labor costs. Therefore, we believe it continues to be an 
appropriate measure to use in the IPPS market basket. We also note that 
based on IGI's second quarter 2022 forecast with historical data 
through first quarter 2022, compensation price growth (using the ECIs) 
for FY 2023 is now projected to be 4.8 percent, which is 1.0 percentage 
point higher than projected price growth at the time of the FY 2023 
IPPS/LTCH PPS proposed rule (3.8 percent).
    Comment: A commenter encouraged CMS to consider whether additional 
changes are needed regarding the rebasing and revising of the market 
basket, given data from 2018 was relied upon in the FY 2022 IPPS/LTCH 
PPS final rule to determine the appropriate mix of goods and services, 
which may have been impacted by COVID-19. For example, they stated that 
during the pandemic there has been increased use of personal protective 
equipment, yet this utilization would not be captured in the market 
basket, which was rebased and revised in the FY 2022 IPPS/LTCH PPS 
final rule.
    Response: As described previously, the IPPS market basket measures 
price changes (including changes in the prices for wages and salaries) 
over time and would not reflect increases in costs associated with 
changes in the volume or intensity of input goods and services until 
the market basket is rebased. The IPPS market basket was last rebased 
in the FY 2022 IPPS/LTCH PPS final rule using 2018 Medicare cost 
reports (86 FR 45194 through 45207), the most recent year of complete 
data available at the time of the rebasing. We note that we did not 
propose to rebase the IPPS market basket in the FY 2023 IPPS/LTCH PPS 
proposed rule. However, we did review more recent Medicare cost report 
data available for IPPS hospitals submitted as of March 2022, which 
includes data for 2019-2020. The Medicare cost report data (which does 
not allow us to separately identify costs for-PPE) showed slight 
decreases in the compensation cost weight in 2019 and 2020 resulting in 
a compensation cost weight that is roughly 1 percentage point less than 
the 2018-based IPPS market basket cost weight. Data through 2021 are 
incomplete at this time. The data also showed slight increases over the 
2018 to 2020 time period in the pharmaceuticals cost weight and home 
office cost weight of about 0.3 percentage point each. Based on this 
preliminary analysis, the impact on the cost weights through 2020 are 
minimal and it is unclear whether these trends (particularly the 
compensation cost weight) through 2020 are reflective of sustained 
shifts in the cost structure for hospitals or whether they were 
temporary as a result of the PHE. Therefore, we continue to believe it 
is premature at this time to use more recent Medicare cost report data 
to derive a rebased and revised IPPS market basket. We will continue to 
monitor these data and any changes to the IPPS market basket will be 
proposed in future rulemaking.
    Comment: Several commenters expressed concerns about the market 
basket update calculations. Commenters stated that CMS calculates the 
percent change by dividing the average input price indices in the most 
recent four quarters by the average input price index in the previous 
four quarters as derived from the most recently available IGI forecast. 
However, the commenter stated that CMS does not consider the difference 
between the base year estimates (from the time when prior year payment 
rates are finalized) and updated estimates of the base year indices 
since the prior year's market basket update calculation. Therefore, 
they stated this current update method does not account for substantial 
forecast errors driven by an unusually fast acceleration of the 
inflation rate such as occurred in FY 2021. They urge CMS to leverage 
its exceptions and adjustments authority under section 1886(d)(5)(I)(i) 
of the Act to modify its methodology for FY 2023 to account for the 
substantial forecast error in FYs 2021 and 2022. A commenter added that 
it believes the understatement of the hospital market basket for FY 
2021 and FY 2022 and potentially FY 2023 as well is such an occasion 
for using the exceptions and adjustments authority. The commenter 
stated that Premier data collected directly from hospitals is showing a 
10 percent increase in 2022 to date for hospital compensation (67.6 
percent of the market basket) compared to the 3.8 percent being 
forecasted by IGI. The commenter recommended CMS make a one-time only 
forecast error correction on the FY 2021 and FY 2022 market basket of a 
combined 1.9 percentage points for FY 2023 using the exceptions and 
adjustments authority. The commenter also recommended that CMS use its 
exceptions and adjustments authority to substitute Premier data for the 
IGI forecast to provide hospitals with an increased payment update in 
FY 2023 to accurately reflect labor costs.
    A commenter urged CMS to consider a one-time adjustment to ensure 
that the FY 2023 rate increase is applied to a base rate that more 
accurately incorporates actual inflation during the pandemic. The 
commenter cited the unprecedented nature of the pandemic and its 
extraordinary impact on hospital costs alongside record inflation for 
the basis of this one-time adjustment.
    Response: Section 1886(b)(3)(B) of the Act sets forth the update to 
the standardized amounts based on the applicable percentage increase. 
Although the statute does not include a forecast error adjustment, 
commenters requested that CMS use its exceptions and adjustments 
authority under section 1886(d)(5)(I)(i) of the Act to modify its 
methodology to account for the forecast error in FYs 2021 and 2022. We 
note that we did not propose to use our authority under section 
1886(d)(5)(I)(i) of the Act to apply a forecast correction in updating 
the IPPS rates for FY 2023. While there is no precedent to adjust for 
market basket forecast error in the IPPS operating payment update, the 
forecast error for a market basket update is equal to the actual market 
basket increase for a given year less the forecasted market basket 
increase. Due to the uncertainty regarding future price trends, 
forecast errors can be both positive and negative. For example, the FY 
2020 IPPS forecast error was -1.0 percentage point, and the FY 2021 
IPPS forecast error was +0.7 percentage point; FY 2022 historical data 
are not yet available to calculate a forecast error for FY 2022. As we 
have discussed in past rulemaking, we believe that an important goal of 
a PPS is predictability. For these reasons, we do not believe it is 
appropriate to include adjustments to the market basket update for 
future years based on the difference between the actual and forecasted 
market basket increase in prior years. With regard to the comment

[[Page 49055]]

recommending the use of the Premier data, we refer to our response to 
this comment as previously discussed earlier in this section, regarding 
why we believe the 2018-based IPPS market basket increase adequately 
reflects the average change in the price of goods and services 
hospitals purchase in order to provide IPPS medical services, and is 
technically appropriate to use as the market basket percentage increase 
in accordance with section 1886(b)(3)(B)(iii).
    We thank the commenters for their comments. After consideration of 
the comments received and consistent with our proposal, we are 
finalizing to use more recent data to determine the FY 2023 market 
basket update for the final rule. Specifically, based on more recent 
data available, we determined final applicable percentage increases to 
the standardized amount for FY 2023, as specified in the table that 
appears later in this section.
    In the FY 2012 IPPS/LTCH PPS final rule (76 FR 51689 through 
51692), we finalized our methodology for calculating and applying the 
productivity adjustment. As we explained in that rule, section 
1886(b)(3)(B)(xi)(II) of the Act, as added by section 3401(a) of the 
Affordable Care Act, defines this productivity adjustment as equal to 
the 10-year moving average of changes in annual economy-wide, private 
nonfarm business MFP (as projected by the Secretary for the 10-year 
period ending with the applicable fiscal year, year, cost reporting 
period, or other annual period). The U.S. Department of Labor's Bureau 
of Labor Statistics (BLS) publishes the official measures of private 
nonfarm business productivity for the U.S. economy. We note that 
previously the productivity measure referenced in section 
1886(b)(3)(B)(xi)(II) was published by BLS as private nonfarm business 
multifactor productivity. Beginning with the November 18, 2021 release 
of productivity data, BLS replaced the term multifactor productivity 
(MFP) with total factor productivity (TFP). BLS noted that this is a 
change in terminology only and will not affect the data or methodology. 
As a result of the BLS name change, the productivity measure referenced 
in section 1886(b)(3)(B)(xi)(II) is now published by BLS as private 
nonfarm business total factor productivity. However, as mentioned, the 
data and methods are unchanged. Please see www.bls.gov for the BLS 
historical published TFP data. A complete description of IGI's TFP 
projection methodology is available on the CMS website at https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/MedicareProgramRatesStats/MarketBasketResearch. In addition, we 
note that beginning with the FY 2022 IPPS/LTCH PPS final rule, we refer 
to this adjustment as the productivity adjustment rather than the MFP 
adjustment to more closely track the statutory language in section 
1886(b)(3)(B)(xi)(II) of the Act. We note that the adjustment continues 
to rely on the same underlying data and methodology.
    For FY 2023, we proposed a productivity adjustment of 0.4 percent. 
Similar to the proposed market basket update, for the proposed rule, 
the estimate of the proposed FY 2023 productivity adjustment was based 
on IGI's fourth quarter 2021 forecast. As noted previously, we proposed 
that if more recent data subsequently became available, we would use 
such data, if appropriate, to determine the FY 2023 productivity 
adjustment for the final rule.
    Comment: Several commenters requested that CMS use its ``special 
exceptions and adjustments'' authority under section 1886(d)(5)(I)(i) 
of the Act to eliminate the productivity adjustment for FY 2023. A 
commenter requested that CMS work with Congress to permanently 
eliminate the productivity adjustment to the annual hospital payment 
updates. Another commenter stated that, if CMS does not use more recent 
figures from BLS on economy-wide non-farm total factor productivity 
when determining the adjustment to the IPPS market basket update for FY 
2023, then the highly unusual circumstances of the COVID-19 pandemic 
are sufficient reason for the Secretary to invoke section 
1886(d)(5)(I)(i) ``exceptions and adjustments'' authority to provide a 
one-time adjustment that offsets application of the otherwise 
applicable productivity adjustment for FY 2023.
    A commenter requested that CMS use its ``exceptions and 
adjustments'' authority under section 1886(d)(5)(I)(i) of the Act to 
remove the productivity adjustment for any fiscal year that was covered 
under PHE determination (for example, 2020, 2021, and 2022) from the 
calculation of market basket update for FY 2023 and any year 
thereafter.
    A commenter recommended that CMS withhold the proposed -0.4 percent 
productivity adjustment until a federal fiscal year in which hospitals 
are not operating under the public health emergency (PHE).
    Response: While we appreciate the commenters' concerns, section 
1886(b)(3)(B)(xi)(I) of the Act requires the application of the 
productivity adjustment described in section 1886(b)(3)(B)(xi)(II) of 
the Act to the IPPS market basket update when determining the 
applicable percentage increase. Section 1886(d)(5)(I)(i) of the Act 
authorizes the Secretary to provide by regulation for such other 
exceptions and adjustments to the payment amounts under section 1886(d) 
of the Act as the Secretary deems appropriate.
    We further note that we did not propose to use our authority under 
section 1886(d)(5)(I)(i) of the Act in the FY 2023 IPPS/LTCH PPS 
proposed rule to offset the productivity adjustment for FY 2023. Based 
on the updated forecast for this final rule, and as discussed 
elsewhere, we are projecting a FY 2023 IPPS market basket update of 4.1 
percent and a productivity adjustment of 0.3 percentage point for this 
final rule, as compared to the proposed market basket update of 3.1 
percent and proposed productivity adjustment of 0.4 percentage point 
set forth in the proposed rule. Additionally, we note Congress has 
provided other funding to providers as a result of the COVID-19 PHE. 
Specifically, the CARES Act provided additional payments for cases of 
COVID-19 under the IPPS and also created the Provider Relief Fund to 
reimburse providers, including IPPS providers, for increased expenses 
or lost revenue attributable to COVID-19.
    We thank the commenters for their comments. However, as previously 
noted, section 1886(b)(3)(B)(xi)(II) of the Act, as added by section 
3401(a) of the Affordable Care Act, requires a productivity adjustment 
to the IPPS market basket update when determining the applicable 
percentage increase. Consistent with our proposal, we are using more 
recent data to determine the FY 2023 productivity adjustment for the 
final rule. Specifically, based on IGI's second quarter 2022 forecast, 
we are projecting a FY 2023 IPPS market basket update of 4.1 percent 
and productivity adjustment of 0.3 percentage point. Therefore, as 
discussed further in this section and after consideration of the 
comments received, for FY 2023, the final IPPS applicable percentage 
increase for a hospital that submitted quality data and is a meaningful 
EHR user is 3.8 percent (4.1 percent less 0.3 percentage point).
    Comment: Several commenters expressed concerns about the 
productivity adjustment. A commenter stated that the measure of 
productivity used by CMS is intended to ensure payments more accurately 
reflect the true cost of providing patient care and effectively assumes 
the hospital field can mirror productivity gains across the

[[Page 49056]]

private nonfarm business sector. Several commenters stated that this 
has not been their experience during the pandemic. Commenters also 
stated that even before the pandemic, CMS Office of the Actuary 
questioned the wisdom of the underlying assumption in their analysis 
that compares private non-farm total factor productivity growth measure 
and a hospital-specific measure (https://www.cms.gov/files/document/productivity-memo.pdf). Commenters also stated that the latest data 
indicates a decrease in productivity, not gains, citing the latest BLS 
release of labor productivity data. Commenters had strong concerns 
about the proposed productivity adjustment given the extreme and 
uncertain circumstances in which their hospitals and health systems are 
currently operating. Several commenters requested CMS use the latest 
BLS data when determining the productivity adjustment for FY 2023.
    Response: Section 1886(b)(3)(B)(xi)(II) of the Act requires the 
productivity adjustment be equal to the 10-year moving average of 
changes in annual economy-wide private nonfarm business total factor 
productivity (as projected by the Secretary for the 10-year period 
ending with the applicable fiscal year, year, cost reporting period, or 
other annual period). For the FY 2023 IPPS/LTCH PPS proposed rule, 
based on IGI's fourth quarter 2021 forecast, the productivity 
adjustment was projected to be 0.4 percentage point for FY 2023. For 
this final rule, based on IGI's second quarter 2022 forecast, we are 
updating the productivity adjustment to reflect more recent historical 
data as published by BLS as well as a revised economic outlook for FY 
2022 and FY 2023. Using this more recent forecast, the FY 2023 
productivity adjustment based on the 10-year moving average growth in 
economy-wide total factor productivity for the period ending FY 2023 is 
currently estimated to be 0.3 percent.
    We thank the commenters for their comments. After consideration of 
the comments received and consistent with our proposal, we are 
finalizing as proposed to use more recent data to determine the FY 2023 
productivity adjustment for the final rule.
    Based on more recent data available for this FY 2023 IPPS/LTCH PPS 
final rule (that is, IGI's second quarter 2022 forecast of the 2018-
based IPPS market basket rate-of-increase with historical data through 
the first quarter of 2022), we estimate that the FY 2023 market basket 
update used to determine the applicable percentage increase for the 
IPPS is 4.1 percent. Based on more recent data available for this FY 
2023 IPPS/LTCH PPS final rule (that is, IGI's second quarter 2022 
forecast of the productivity adjustment), the current estimate of the 
productivity adjustment for FY 2023 is 0.3 percentage point.
    As previously discussed, based on the more recent data available, 
for this final rule, we have determined four final applicable 
percentage increases to the standardized amount for FY 2023. For FY 
2023, depending on whether a hospital submits quality data under the 
rules established in accordance with section 1886(b)(3)(B)(viii) of the 
Act (hereafter referred to as a hospital that submits quality data) and 
is a meaningful EHR user under section 1886(b)(3)(B)(ix) of the Act 
(hereafter referred to as a hospital that is a meaningful EHR user), 
there are four possible applicable percentage increases that can be 
applied to the standardized amount, as specified in this table.
[GRAPHIC] [TIFF OMITTED] TR10AU22.126

    In the FY 2020 IPPS/LTCH PPS final rule (84 FR 42344), we revised 
our regulations at 42 CFR 412.64(d) to reflect the current law for the 
update for FY 2020 and subsequent fiscal years. Specifically, in 
accordance with section 1886(b)(3)(B) of the Act, we added paragraph 
(d)(1)(viii) to Sec.  412.64 to set forth the applicable percentage 
increase to the operating standardized amount for FY 2020 and 
subsequent fiscal years as the percentage increase in the market basket 
index, subject to the reductions specified under Sec.  412.64(d)(2) for 
a hospital that does not submit quality data and Sec.  412.64(d)(3) for 
a hospital that is not a meaningful EHR user, less a productivity 
adjustment. (As previously noted, section 1886(b)(3)(B)(xii) of the Act 
required an additional reduction each year only for FYs 2010 through 
2019.)
    Section 1886(b)(3)(B)(iv) of the Act provides that the applicable 
percentage increase to the hospital-specific rates for SCHs equals the 
applicable percentage increase set forth in section 1886(b)(3)(B)(i) of 
the Act (that is, the same update factor as for all other hospitals 
subject to the IPPS). Therefore, the update to the hospital-specific 
rates for SCHs also is subject to section 1886(b)(3)(B)(i) of the Act, 
as amended by sections 3401(a) and 10319(a) of the Affordable Care Act.
    Under current law, the MDH program is effective for discharges on 
or before September 30, 2022, as discussed in the FY 2019 IPPS/LTCH PPS 
final rule (83 FR 41429 through 41430). Therefore, under current law, 
the MDH program will expire at the end of FY 2022. We

[[Page 49057]]

refer readers to section V.D. of the preamble of this final rule for 
further discussion of the expiration of the MDH program.
    For FY 2023, we proposed the following updates to the hospital-
specific rates applicable to SCHs: a proposed update of 2.7 percent for 
a hospital that submits quality data and is a meaningful EHR user; a 
proposed update of 0.375 percent for a hospital that submits quality 
data and is not a meaningful EHR user; a proposed update of 1.925 
percent for a hospital that fails to submit quality data and is a 
meaningful EHR user; and a proposed update of -0.4 percent for a 
hospital that fails to submit quality data and is not an meaningful EHR 
user. We proposed that if more recent data subsequently became 
available (for example, a more recent estimate of the market basket 
update and the productivity adjustment), we would use such data, if 
appropriate, to determine the update in the final rule.
    We did not receive any public comments on our proposed updates to 
hospital-specific rates applicable to SCHs. The general comments we 
received on the proposed FY 2023 update (including the proposed market 
basket update and productivity adjustment) are discussed earlier in 
this section. For FY 2023, we are finalizing the proposal to determine 
the update to the hospital specific rates for SCHs in this final rule 
using the more recent available data, as previously discussed.
    For this final rule, based on more recent available data, we are 
finalizing the following updates to the hospital specific rates 
applicable to SCHs: An update of 3.8 percent for a hospital that 
submits quality data and is a meaningful EHR user; an update of 0.725 
percent for a hospital that submits quality data and is not a 
meaningful EHR user; an update of 2.775 percent for a hospital that 
fails to submit quality data and is a meaningful EHR user; and an 
update of -0.3 percent for a hospital that fails to submit quality data 
and is not a meaningful EHR user.
2. FY 2023 Puerto Rico Hospital Update
    Section 602 of Public Law 114-113 amended section 1886(n)(6)(B) of 
the Act to specify that subsection (d) Puerto Rico hospitals are 
eligible for incentive payments for the meaningful use of certified EHR 
technology, effective beginning FY 2016. In addition, section 
1886(n)(6)(B) of the Act was amended to specify that the adjustments to 
the applicable percentage increase under section 1886(b)(3)(B)(ix) of 
the Act apply to subsection (d) Puerto Rico hospitals that are not 
meaningful EHR users, effective beginning FY 2022. Accordingly, for FY 
2022, section 1886(b)(3)(B)(ix) of the Act in conjunction with section 
602(d) of Public Law 114-113 requires that any subsection (d) Puerto 
Rico hospital that is not a meaningful EHR user as defined in section 
1886(n)(3) of the Act and not subject to an exception under section 
1886(b)(3)(B)(ix) of the Act will have ``three-quarters'' of the 
applicable percentage increase (prior to the application of other 
statutory adjustments), or three-quarters of the applicable market 
basket rate-of-increase, reduced by 33\1/3\ percent. The reduction to 
three-quarters of the applicable percentage increase for subsection (d) 
Puerto Rico hospitals that are not meaningful EHR users increases to 
66\2/3\ percent for FY 2023, and, for FY 2024 and subsequent fiscal 
years, to 100 percent. (We note that section 1886(b)(3)(B)(viii) of the 
Act, which specifies the adjustment to the applicable percentage 
increase for ``subsection (d)'' hospitals that do not submit quality 
data under the rules established by the Secretary, is not applicable to 
hospitals located in Puerto Rico.) The regulations at 42 CFR 
412.64(d)(3)(ii) reflect the current law for the update for subsection 
(d) Puerto Rico hospitals for FY 2022 and subsequent fiscal years. In 
the FY 2019 IPPS/LTCH PPS final rule, we finalized the payment 
reductions (83 FR 41674).
    For FY 2023, consistent with section 1886(b)(3)(B) of the Act, as 
amended by section 602 of Public Law 114-113, we are setting the 
applicable percentage increase for Puerto Rico hospitals by applying 
the following adjustments in the following sequence. Specifically, the 
applicable percentage increase under the IPPS for Puerto Rico hospitals 
will be equal to the rate of-increase in the hospital market basket for 
IPPS hospitals in all areas, subject to a 66\2/3\ percent reduction to 
three-fourths of the applicable percentage increase (prior to the 
application of other statutory adjustments; also referred to as the 
market basket update or rate-of-increase (with no adjustments)) for 
Puerto Rico hospitals not considered to be meaningful EHR users in 
accordance with section 1886(b)(3)(B)(ix) of the Act, and then subject 
to the productivity adjustment at section 1886(b)(3)(B)(xi) of the Act. 
As noted previously, section 1886(b)(3)(B)(xi) of the Act states that 
application of the productivity adjustment may result in the applicable 
percentage increase being less than zero.
    Based on IGI's fourth quarter 2021 forecast of the 2018-based IPPS 
market basket update with historical data through third quarter 2021, 
in the FY 2023 IPPS/LTCH PPS proposed rule, in accordance with section 
1886(b)(3)(B) of the Act, as discussed previously, for Puerto Rico 
hospitals we proposed a market basket update of 3.1 percent and a 
productivity adjustment of 0.4 percent. Therefore, for FY 2023, 
depending on whether a Puerto Rico hospital is a meaningful EHR user, 
we stated there would be two possible proposed applicable percentage 
increases that could be applied to the standardized amount. Based on 
these data, we determined the following proposed applicable percentage 
increases to the standardized amount for FY 2023 for Puerto Rico 
hospitals:
     For a Puerto Rico hospital that is a meaningful EHR user, 
we proposed an applicable percentage increase to the FY 2023 operating 
standardized amount of 2.7 percent (that is, the FY 2023 estimate of 
the proposed market basket rate-of-increase of 3.1 percent less an 
adjustment of 0.4 percentage point for the proposed productivity 
adjustment).
     For a Puerto Rico hospital that is not a meaningful EHR 
user, we proposed an applicable percentage increase to the operating 
standardized amount of 1.15 percent (that is, the FY 2023 estimate of 
the proposed market basket rate-of-increase of 3.1 percent, less an 
adjustment of 1.55 percentage point (the proposed market basket rate-
of-increase of 3.1 percent x 0.75 x (\2/3\) for failure to be a 
meaningful EHR user), and less an adjustment of 0.4 percentage point 
for the proposed productivity adjustment).
    We did not receive any public comments on our proposed updates to 
the standardized amount for FY 2023 for Puerto Rico hospitals. The 
general comments we received on the proposed FY 2023 update (including 
the proposed market basket update and productivity adjustment) are 
discussed in greater detail earlier in this section. For FY 2023, we 
are finalizing the proposal to determine the update to the standardized 
amount for FY 2023 for Puerto Rico hospitals in this final rule using 
the more recent available data, as previously discussed.
    As previously discussed in section V.A.1, based on more recent data 
available for this final rule (that is, IGI's second quarter 2022 
forecast of the 2018-based IPPS market basket rate-of-increase with 
historical data through the first quarter of 2022), we estimate that 
the FY 2023 market basket update used to determine the applicable 
percentage increase for the IPPS is 4.1 percent and the productivity 
adjustment is 0.3 percent. For FY 2023, depending on whether a Puerto 
Rico hospital is a meaningful EHR user, there are two

[[Page 49058]]

possible applicable percentage increases that can be applied to the 
standardized amount. Based on these data, accordance with section 
1886(b)(3)(B) of the Act, we determined the following applicable 
percentage increases to the standardized amount for FY 2023 for Puerto 
Rico hospitals:
     For a Puerto Rico hospital that is a meaningful EHR user, 
an applicable percentage increase to the FY 2023 operating standardized 
amount of 3.8 percent (that is, the FY 2023 estimate of the market 
basket rate-of-increase of 4.1 percent less an adjustment of 0.3 
percentage point for the productivity adjustment).
     For a Puerto Rico hospital that is not a meaningful EHR 
user, an applicable percentage increase to the operating standardized 
amount of 1.75 percent (that is, the FY 2023 estimate of the market 
basket rate-of-increase of 4.1 percent, less an adjustment of 2.05 
percentage point (the market basket rate-of-increase of 4.1 percent x 
0.75 x (\2/3\) for failure to be a meaningful EHR user), and less an 
adjustment of 0.3 percentage point for the productivity adjustment).
[GRAPHIC] [TIFF OMITTED] TR10AU22.127

B. Rural Referral Centers (RRCs) Annual Updates to Case-Mix Index (CMI) 
and Discharge Criteria (Sec.  412.96)

    Under the authority of section 1886(d)(5)(C)(i) of the Act, the 
regulations at Sec.  412.96 set forth the criteria that a hospital must 
meet in order to qualify under the IPPS as a rural referral center 
(RRC). RRCs receive special treatment under both the DSH payment 
adjustment and the criteria for geographic reclassification.
    Section 402 of Public Law 108-173 raised the DSH payment adjustment 
for RRCs such that they are not subject to the 12-percent cap on DSH 
payments that is applicable to other rural hospitals. RRCs also are not 
subject to the proximity criteria when applying for geographic 
reclassification. In addition, they do not have to meet the requirement 
that a hospital's average hourly wage must exceed, by a certain 
percentage, the average hourly wage of the labor market area in which 
the hospital is located.
    Section 4202(b) of Public Law 105-33 states, in part, that any 
hospital classified as an RRC by the Secretary for FY 1991 shall be 
classified as such an RRC for FY 1998 and each subsequent fiscal year. 
In the August 29, 1997, IPPS final rule with comment period (62 FR 
45999), we reinstated RRC status for all hospitals that lost that 
status due to triennial review or MGCRB reclassification. However, we 
did not reinstate the status of hospitals that lost RRC status because 
they were now urban for all purposes because of the OMB designation of 
their geographic area as urban. Subsequently, in the August 1, 2000 
IPPS final rule (65 FR 47089), we indicated that we were revisiting 
that decision. Specifically, we stated that we would permit hospitals 
that previously qualified as an RRC and lost their status due to OMB 
redesignation of the county in which they are located from rural to 
urban, to be reinstated as an RRC. Otherwise, a hospital seeking RRC 
status must satisfy all of the other applicable criteria. We use the 
definitions of ``urban'' and ``rural'' specified in subpart D of 42 CFR 
part 412. One of the criteria under which a hospital may qualify as an 
RRC is to have 275 or more beds available for use (Sec.  
412.96(b)(1)(ii)). A rural hospital that does not meet the bed size 
requirement can qualify as an RRC if the hospital meets two mandatory 
prerequisites (a minimum case-mix index (CMI) and a minimum number of 
discharges), and at least one of three optional criteria (relating to 
specialty composition of medical staff, source of inpatients, or 
referral volume). (We refer readers to Sec.  412.96(c)(1) through (5) 
and the September 30, 1988, Federal Register (53 FR 38513) for 
additional discussion.) With respect to the two mandatory 
prerequisites, a hospital may be classified as an RRC if--
     The hospital's CMI is at least equal to the lower of the 
median CMI for urban hospitals in its census region, excluding 
hospitals with approved teaching programs, or the median CMI for all 
urban hospitals nationally; and
     The hospital's number of discharges is at least 5,000 per 
year, or, if fewer, the median number of discharges for urban hospitals 
in the census region in which the hospital is located. The number of 
discharges criterion for an osteopathic hospital is at least 3,000 
discharges per year, as specified in section 1886(d)(5)(C)(i) of the 
Act.
    In the FY 2022 final rule (86 FR 45217), in light of the COVID-19 
PHE, we amended the regulations at Sec.  412.96(h)(1) to provide for 
the use of the best available data rather than the latest available 
data in calculating the national and regional CMI criteria. We also 
amended the regulations at Sec.  412.96(c)(1) to indicate that the 
individual hospital's CMI value for discharges during the same Federal 
fiscal year used to compute the national and regional CMI values is 
used for purposes of determining whether a hospital qualifies for RRC 
classification. We also amended the regulations Sec.  412.96(i)(1) and 
(2), which describe the methodology for calculating the number of 
discharges criteria, to provide for the use of the best available data 
rather than the latest available or most recent data when calculating 
the regional discharges for RRC classification.
1. Case-Mix Index (CMI)
    Section 412.96(c)(1) provides that CMS establish updated national 
and

[[Page 49059]]

regional CMI values in each year's annual notice of prospective payment 
rates for purposes of determining RRC status. The methodology we used 
to determine the national and regional CMI values is set forth in the 
regulations at Sec.  412.96(c)(1)(ii). The national median CMI value 
for FY 2023 is based on the CMI values of all urban hospitals 
nationwide, and the regional median CMI values for FY 2023 are based on 
the CMI values of all urban hospitals within each census region, 
excluding those hospitals with approved teaching programs (that is, 
those hospitals that train residents in an approved GME program as 
provided in Sec.  413.75). For the proposed rule, these values were 
based on discharges occurring during FY 2021 (October 1, 2020 through 
September 30, 2021), and include bills posted to CMS' records through 
December 2021. We believe that this is the best available data for use 
in calculating the national and regional median CMI values and is 
consistent with our finalized proposal to use the FY 2021 MedPAR claims 
data for FY 2023 ratesetting. We refer the reader to section I.F. of 
the preamble of this final rule for a complete discussion regarding our 
proposal and finalized policy to use the latest available data (that 
is, the FY 2021 MedPAR data) as the best available data for purposes of 
this FY 2023 rulemaking.
    In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28404), we 
proposed that, in addition to meeting other criteria, if rural 
hospitals with fewer than 275 beds are to qualify for initial RRC 
status for cost reporting periods beginning on or after October 1, 
2022, they must have a CMI value for FY 2021 that is at least--
     1.8251 (national--all urban); or
     The median CMI value (not transfer-adjusted) for urban 
hospitals (excluding hospitals with approved teaching programs as 
identified in Sec.  413.75) calculated by CMS for the census region in 
which the hospital is located.
    The proposed median CMI values by region were set forth in a table 
in the proposed rule (87 FR 28405). We stated in the proposed rule that 
we intended to update the proposed CMI values in the FY 2023 final rule 
to reflect the updated FY 2021 MedPAR file, which will contain data 
from additional bills received through March 2022.
    Comment: Commenters supported our proposal to use FY 2021 data to 
calculate the national and regional median CMI values for FY 2023.
    Response: We appreciate the commenters' support.
    Therefore, based on the best available data (FY 2021 bills received 
through March 2022), in addition to meeting other criteria, if rural 
hospitals with fewer than 275 beds are to qualify for initial RRC 
status for cost reporting periods beginning on or after October 1, 
2022, they must have a CMI value for FY 2021 that is at least:
     1.8262 (national--all urban); or
     The median CMI value (not transfer-adjusted) for urban 
hospitals (excluding hospitals with approved teaching programs as 
identified in Sec.  413.75) calculated by CMS for the census region in 
which the hospital is located.
    The final CMI values by region are set forth in the following 
table.
[GRAPHIC] [TIFF OMITTED] TR10AU22.128

    A hospital seeking to qualify as an RRC should obtain its hospital-
specific CMI value (not transfer-adjusted) from its MAC. Data are 
available on the Provider Statistical and Reimbursement (PS&R) System. 
In keeping with our policy on discharges, the CMI values are computed 
based on all Medicare patient discharges subject to the IPPS MS-DRG-
based payment.
3. Discharges
    Section 412.96(c)(2)(i) provides that CMS set forth the national 
and regional numbers of discharges criteria in each year's annual 
notice of prospective payment rates for purposes of determining RRC 
status. As specified in section 1886(d)(5)(C)(ii) of the Act, the 
national standard is set at 5,000 discharges. In the FY 2023 IPPS/LTCH 
PPS proposed rule (87 FR 28406), for FY 2023, we proposed to update the 
regional standards based on discharges for urban hospitals' cost 
reporting periods that began during FY 2020 (that is, October 1, 2019 
through September 30, 2020). We believe that this is the best available 
data for use in calculating the median number of discharges by region 
and is consistent with our finalized data proposal to use cost report 
data from cost reporting periods beginning during FY 2020 for FY 2023 
ratesetting. We refer the reader to section I.F. of the preamble of 
this final rule for a complete discussion regarding our proposal and 
finalized policy to use the latest available data (that is, cost 
reports beginning during FY 2020) as the best available data for 
purposes of this FY 2023 rulemaking.
    In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28405), we 
proposed that, in addition to meeting other criteria, a hospital, if it 
is to qualify for initial RRC status for cost reporting periods 
beginning on or after October 1, 2022, must have, as the number of 
discharges for its cost reporting period that began during FY 2020, at 
least--
     5,000 (3,000 for an osteopathic hospital); or
     If less, the median number of discharges for urban 
hospitals in the census region in which the hospital is located. (We 
refer readers to the table set forth in the FY 2023 IPPS/LTCH PPS 
proposed rule at 87 FR 28406). In the

[[Page 49060]]

proposed rule, we stated that we intended to update to update these 
numbers in the FY 2023 final rule based on the latest available cost 
report data.
    Comment: Commenters supported our proposal to use FY 2020 data to 
calculate median number of discharges by region for FY 2023.
    Response: We appreciate the commenters' support.
    Therefore, based on the best available discharge data at this time, 
that is, for cost reporting periods that began during FY 2020, the 
final median number of discharges for urban hospitals by census region 
are set forth in the following table.
[GRAPHIC] [TIFF OMITTED] TR10AU22.129

    We note that because the median number of discharges for hospitals 
in each census region is greater than the national standard of 5,000 
discharges, under this final rule, 5,000 discharges is the minimum 
criterion for all hospitals, except for osteopathic hospitals for which 
the minimum criterion is 3,000 discharges.

C. Payment Adjustment for Low-Volume Hospitals (Sec.  412.101)

1. Expiration of Temporary Changes to Low-Volume Hospital Payment 
Policy
    As discussed in the FY 2019 IPPS/LTCH PPS final rule (83 FR 41398 
through 41399), section 50204 of the Bipartisan Budget Act of 2018 
(Pub. L. 115-123) modified the definition of a low-volume hospital and 
the methodology for calculating the payment adjustment for low-volume 
hospitals under section 1886(d)(12) of the Act for FYs 2019 through 
2022. Beginning with FY 2023, the low-volume hospital qualifying 
criteria and payment adjustment will revert to the statutory 
requirements that were in effect prior to FY 2011, and the preexisting 
low-volume hospital payment adjustment methodology and qualifying 
criteria, as implemented in FY 2005 and discussed later in this section 
of this final rule, will resume. (For additional information on the 
temporary changes to the low-volume hospital payment policy, we refer 
readers to the FY 2019 IPPS/LTCH PPS final rule (83 FR 41398 through 
41401). We also note, in that same final rule, we amended the 
regulations at 42 CFR 412.101 to reflect the provisions of section 
50204 of the Bipartisan Budget Act of 2018.) We discuss the payment 
policies for FY 2023 in section V.C.3. of the preamble of this final 
rule.
2. Background
    Section 1886(d)(12) of the Act provides for an additional payment 
to each qualifying low-volume hospital under the IPPS beginning in FY 
2005. The additional payment adjustment to a low-volume hospital 
provided for under section 1886(d)(12) of the Act is in addition to any 
payment calculated under section 1886 of the Act. Therefore, the 
additional payment adjustment is based on the per discharge amount paid 
to the qualifying hospital under section 1886 of the Act. In other 
words, the low-volume hospital payment adjustment is based on total per 
discharge payments made under section 1886 of the Act, including 
capital, DSH, IME, and outlier payments. For SCHs and MDHs, the low-
volume hospital payment adjustment is based in part on either the 
Federal rate or the hospital-specific rate, whichever results in a 
greater operating IPPS payment.
    As discussed in the FY 2022 IPPS/LTCH PPS final rule (86 FR 45219 
through 45221), section 50204 of the Bipartisan Budget Act of 2018 
(Pub. L. 115-123) modified the definition of a low-volume hospital and 
the methodology for calculating the payment adjustment for low-volume 
hospitals for FYs 2019 through 2022. Specifically, the qualifying 
criteria for low-volume hospitals under section 1886(d)(12)(C)(i) of 
the Act were amended to specify that, for FYs 2019 through 2022, a 
subsection (d) hospital qualifies as a low-volume hospital if it is 
more than 15 road miles from another subsection (d) hospital and has 
less than 3,800 total discharges during the fiscal year. Section 
1886(d)(12)(D) of the Act was also amended to provide that, for 
discharges occurring in FYs 2019 through 2022, the Secretary determines 
the applicable percentage increase using a continuous, linear sliding 
scale ranging from an additional 25 percent payment adjustment for low-
volume hospitals with 500 or fewer discharges to a zero percent 
additional payment for low-volume hospitals with more than 3,800 
discharges in the fiscal year. Consistent with the requirements of 
section 1886(d)(12)(C)(ii) of the Act, the term ``discharge'' for 
purposes of these provisions refers to total discharges, regardless of 
payer (that is, Medicare and non-Medicare discharges).
    Beginning with FY 2023, the low-volume hospital qualifying criteria 
and payment adjustment will revert to the statutory requirements that 
were in effect prior to FY 2011. Section 1886(d)(12)(C)(i) of the Act 
defines a low-volume hospital, for FYs 2005 through 2010 and FY 2023 
and subsequent years, as a subsection (d) hospital that the Secretary 
determines is located more than 25 road miles from another subsection 
(d) hospital and that has less than 800 discharges during the fiscal 
year. Section 1886(d)(12)(C)(ii) of the Act further stipulates that the 
term ``discharge'' means an inpatient acute care discharge of an 
individual, regardless of whether the individual is entitled to 
benefits under Medicare Part A (except with respect to FYs 2011 through 
2018). Therefore, for FYs 2005 through 2010 and FY 2019 and subsequent 
years, the term ``discharge'' refers to total discharges, regardless of 
payer (that is, Medicare and non-Medicare discharges), and as such the

[[Page 49061]]

term discharge continues to refer to total discharges for FY 2023 and 
subsequent years. Furthermore, section 1886(d)(12)(B) of the Act 
requires, for discharges occurring in FYs 2005 through 2010 and FY 2023 
and subsequent years, that the Secretary determine an applicable 
percentage increase for these low-volume hospitals based on the 
``empirical relationship'' between the standardized cost-per-case for 
such hospitals and the total number of discharges of such hospitals and 
the amount of the additional incremental costs (if any) that are 
associated with such number of discharges. The statute thus mandates 
that the Secretary develop an empirically justifiable adjustment based 
on the relationship between costs and discharges for these low-volume 
hospitals. Section 1886(d)(12)(B)(iii) of the Act limits the applicable 
percentage increase adjustment to no more than 25 percent.
    Based on an analysis we conducted for the FY 2005 IPPS final rule 
(69 FR 49099 through 49102), a 25-percent low-volume adjustment to all 
qualifying hospitals with less than 200 discharges was found to be most 
consistent with the statutory requirement to provide relief to low-
volume hospitals where there is empirical evidence that higher 
incremental costs are associated with low numbers of total discharges. 
In the FY 2006 IPPS final rule (70 FR 47432 through 47434), we stated 
that multivariate analyses supported the existing low-volume adjustment 
implemented in FY 2005. Accordingly, under the existing regulations, in 
order for a hospital to continue to qualify as a low-volume hospital on 
or after October 1, 2022, it must have fewer than 200 total discharges 
during the fiscal year and be located more than 25 road miles from the 
nearest ``subsection (d)'' hospital (see Sec.  412.101(b)(2)(i)). (For 
additional information on the low-volume hospital payment adjustment 
prior to FY 2018, we refer readers to the FY 2017 IPPS/LTCH PPS final 
rule (81 FR 56941 through 56943). For additional information on the 
low-volume hospital payment adjustment for FY 2018, we refer readers to 
the FY 2018 IPPS notice (CMS-1677-N) that appeared in the April 26, 
2018, Federal Register (83 FR 18301 through 18308). For additional 
information on the low-volume hospital payment adjustment for FY 2019 
through FY 2022, we refer readers to the FY 2019 IPPS/LTCH PPS final 
rule (83 FR 41398 through 41399).)
3. Payment Adjustment for FY 2023 and Subsequent Fiscal Years
    In accordance with section 1886(d)(12) of the Act, beginning with 
FY 2023, the low-volume hospital definition and payment adjustment 
methodology will revert back to the statutory requirements that were in 
effect prior to the amendments made by the Affordable Care Act and 
subsequent legislation. Therefore, effective for FY 2023 and subsequent 
years, under current policy at Sec.  412.101(b), in order to qualify as 
a low-volume hospital, a subsection (d) hospital must be more than 25 
road miles from another subsection (d) hospital and have less than 200 
discharges (that is, less than 200 discharges total, including both 
Medicare and non-Medicare discharges) during the fiscal year. For FY 
2023 and subsequent years, the statute specifies that a low-volume 
hospital must have less than 800 discharges during the fiscal year. 
However, as required by section 1886(d)(12)(B)(i) of the Act and as 
discussed earlier, the Secretary has developed an empirically 
justifiable payment adjustment based on the relationship, for IPPS 
hospitals with less than 800 discharges, between the additional 
incremental costs (if any) that are associated with a particular number 
of discharges. Based on an analysis we conducted for the FY 2005 IPPS 
final rule (69 FR 49099 through 49102), a 25-percent low-volume 
adjustment to all qualifying hospitals with less than 200 discharges 
was found to be most consistent with the statutory requirement to 
provide relief for low-volume hospitals where there is empirical 
evidence that higher incremental costs are associated with low numbers 
of total discharges. (Under the policy we established in that same 
final rule, hospitals with between 200 and 799 discharges do not 
receive a low-volume hospital adjustment.)
    For FYs 2005 through 2010 and FY 2018 and subsequent years, the 
discharge determination is made based on the hospital's number of total 
discharges, that is, Medicare and non-Medicare discharges. The 
hospital's most recently submitted cost report is used to determine if 
the hospital meets the discharge criterion to receive the low-volume 
payment adjustment in the current year (Sec.  412.101(b)(2)(i)). We use 
cost report data to determine if a hospital meets the discharge 
criterion because this is the best available data source that includes 
information on both Medicare and non-Medicare discharges. We note that, 
for FYs 2011 through 2018, we used the most recently available MedPAR 
data to determine the hospital's Medicare discharges because only 
Medicare discharges were used to determine if a hospital met the 
discharge criterion for those years.
    In addition to the discharge criterion, a hospital must also meet 
the mileage criterion to qualify for the low-volume payment adjustment. 
As specified by section 1886(d)(12)(C)(i) of the Act, a low-volume 
hospital must be more than 25 road miles (or 15 road miles for FYs 2011 
through 2022) from another subsection (d) hospital. Accordingly, for FY 
2023 and for subsequent fiscal years, in addition to the discharge 
criterion, the eligibility for the low-volume payment adjustment is 
also dependent upon the hospital meeting the mileage criterion at Sec.  
412.101(b)(2)(i), which specifies that a hospital must be located more 
than 25 road miles from the nearest subsection (d) hospital, consistent 
with section 1886(d)(12)(C)(i) of the Act. We define, at Sec.  
412.101(a), the term ``road miles'' to mean ``miles'' as defined at 
Sec.  412.92(c)(1) (75 FR 50238 through 50275 and 50414).
    Comment: Several commenters opposed the change to the low-volume 
hospital policy in FY 2023. Many of those commenters stated that they 
are concerned about the financial impact resulting from the decrease in 
payments due to the expiration of the temporary changes to the low-
volume hospital payment policy. Some commenters requested that CMS use 
its authority to extend the use of the modified definition of a low-
volume hospital and the methodology for calculating the payment 
adjustment for low-volume hospitals. Some commenters stated their 
belief that CMS has the authority to not allow the temporary changes to 
expire. A commenter requested CMS use its discretion under the 
Emergency Pandemic Declarations to extend the low-volume hospital 
payment policy.
    Response: We appreciate the commenters' sharing their concerns 
regarding the financial impact resulting from the expiration of the 
temporary changes to the low-volume hospital payment policy. As 
previously discussed, section 1886(d)(12) of the Act sets forth the 
applicable low-volume hospital policy beginning FY 2023. In response to 
the comment that requested the temporary changes to the low-volume 
hospital policy be extended using the discretion under the Emergency 
Pandemic Declarations, we believe the commenter is referring to the use 
of waivers under Section 1135 of the Act. While this provision 
authorizes certain Medicare (and other) program requirements and 
conditions of participation to be waived during certain emergencies, 
this authority cannot be used to waive provisions of payment.
    Comment: Several commenters support legislative action through the

[[Page 49062]]

Rural Hospital Support Act (H.R. 1887/S. 4009) to extend or make 
permanent the modifications to the low-volume hospital payment policy 
enacted by section 50204 of the Bipartisan Budget Act of 2018. Many 
commenters urged CMS to collaborate with Congress to extend or make 
permanent the modifications to the low-volume hospital payment policy. 
Other commenters stated that it is not the intent of Congress for the 
low-volume hospital payment policy to revert back to the historical 
statutory requirements. Some of these commenters believe that CMS is 
ignoring the congressional intent of this policy and denying a group of 
IPPS providers low-volume hospital payments with the reversion to the 
policy that was originally established for FY 2005. These commenters 
requested expanding eligibility for the discharge criteria to match the 
statutory requirement to include IPPS providers with 200-799 
discharges. These commenters did not provide any data analysis in 
support of their comments to expand the low-volume hospital adjustment 
to qualifying hospitals that have more than 200 and less than 800 total 
discharges. A commenter requested that CMS update its regression 
analysis. The commenter stated that empirical justification used by CMS 
to determine the discharge criteria of less than 200 discharges is 
dated and that no rationale to support the ongoing validity of the 
previous analysis was provided in the proposed rule. The commenter also 
noted that even if the low-volume hospital discharge criteria were 
expanded to less than 800 total discharges, there would still only be a 
small number of hospitals to qualify for low-volume payment adjustment.
    Response: We appreciate the commenters sharing their support for 
legislative action. We disagree that is contrary to the congressional 
intent for the low-volume hospital policy to revert back to the policy 
established under the original historical statutory requirements. As 
noted earlier in the preamble of this final rule and as discussed in 
response to public comments in the FY 2013 IPPS/LTCH PPS final rule (77 
FR 53408 through 53409), the FY 2014 IPPS/LTCH PPS final rule (78 50612 
through 50613), and the FY 2018 IPPS/LTCH PPS final rule (82 FR 38184 
through 38189) to implement the original low-volume hospital payment 
adjustment provision, and as mandated by statute, we developed an 
empirically justified adjustment based on the relationship between 
costs and total discharges of hospitals with less than 800 total 
(Medicare and non-Medicare) discharges. Specifically, we performed 
several regression analyses to evaluate the relationship between 
hospitals' costs per case and discharges, and found that an adjustment 
for hospitals with less than 200 total discharges is most consistent 
with the statutory requirement to provide for additional payments to 
low-volume hospitals where there is empirical evidence that higher 
incremental costs are associated with lower numbers of discharges (69 
FR 49101 through 49102). Based on these analyses, we established a low-
volume hospital policy under which qualifying hospitals with less than 
200 total discharges receive a payment adjustment of an additional 25 
percent. (Section 1886(d)(12)(B)(iii) of the Act limits the applicable 
percentage increase adjustment to no more than 25 percent.) In the 
future, we may reevaluate the low-volume hospital adjustment policy; 
that is, the definition of a low-volume hospital and the payment 
adjustment. However, we are not aware of any analysis or empirical 
evidence that would support expanding the originally established low-
volume hospital adjustment policy and we did not make any proposals 
regarding the low-volume hospital payment adjustment for FY 2023. For 
these reasons, we are not making any changes to the low-volume hospital 
payment adjustment policy in this final rule.
    Comment: Some commenters urged CMS to expedite any changes to the 
definition of a low-volume hospital and the methodology for calculating 
the payment adjustment for low-volume hospitals, should Congress extend 
the current policy. They requested that low-volume hospital payments be 
restored quickly so that impacted providers are able to continue to 
provide quality care.
    Response: We appreciate the commenters' request and, as in the 
past, we will make every effort to implement any extension of the low-
volume payment policy as expeditiously as possible.
    Comment: A commenter questioned how a hospital would qualify for 
low-volume payments while also adhering to the inpatient hospitals 
Conditions of Participation (CoP) since only hospitals with less than 
200 total discharges would be eligible for the low-volume hospital 
adjustment beginning in FY 2023. The commenter argues that IPPS 
hospitals cannot adhere to the average daily census (ADC) and average 
length of stay (ALOS) thresholds in the discussion of the factors for 
state agencies to consider when certifying a facility as an inpatient 
hospital in the State Operations Manual (SOM).\214\ Specifically, the 
commenter cites ``the ALOS of two midnights'' benchmark and the 
expectation ``to maintain an average daily census (ADC) of two 
patients.''
---------------------------------------------------------------------------

    \214\ https://www.cms.gov/Medicare/Provider-Enrollment-and-Certification/SurveyCertificationGenInfo/Downloads/Survey-and-Cert-Letter-17-44-Revised-102717.pdf.
---------------------------------------------------------------------------

    Response: While we appreciate the commenter's concern regarding 
compliance with the COPs and hospitals' certification as an inpatient 
hospital, it is not clear to us why a low-volume hospital payment 
adjustment criterion of less than 200 discharges would prevent a 
hospital from meeting ``the ADC and ALOS thresholds required for 
maintaining its certification and status as an inpatient facility.'' 
The low-volume payment adjustment provides an additional payment to 
hospitals that meet the low-volume hospital qualifying criteria and 
does not directly impact a hospital's ADC or ALOS. We also note that 
CMS considers multiple factors when determining certification for 
inpatient hospitals. ADC and ALOS are factors in determining a 
hospital's eligibility for specialized payment categories. Hospitals 
are not required to have any specific number of inpatients for 
certification. A hospital's ability to adhere to the inpatient hospital 
CoPs is not relevant to the reversion to the low-volume hospital 
payment requirements that were in effect prior to FY 2011.
    After consideration of the public comments we received, we are 
finalizing our proposals, without modification. Consistent with current 
law, effective beginning FY 2023, the low-volume hospital definition 
and payment adjustment methodology will revert back to the policy 
established under statutory requirements that were in effect prior to 
the amendments made by the Affordable Care Act and extended through 
subsequent legislation (most recently the Bipartisan Budget Act of 
2018).
4. Process for Requesting and Obtaining the Low-Volume Hospital Payment 
Adjustment
    In the FY 2011 IPPS/LTCH PPS final rule (75 FR 50238 through 50275 
and 50414) and subsequent rulemaking, most recently in the FY 2022 
IPPS/LTCH PPS final rule (86 FR 45219 through 45221), we discussed the 
process for requesting and obtaining the low-volume hospital payment 
adjustment.
    Under this previously established process, a hospital makes a 
written

[[Page 49063]]

request for the low-volume payment adjustment under Sec.  412.101 to 
its MAC. This request must contain sufficient documentation to 
establish that the hospital meets the applicable mileage and discharge 
criteria. The MAC will determine if the hospital qualifies as a low-
volume hospital by reviewing the data the hospital submits with its 
request for low-volume hospital status in addition to other available 
data. Under this approach, a hospital will know in advance whether or 
not it will receive a payment adjustment under the low-volume hospital 
policy. The MAC and CMS may review available data such as the number of 
discharges, in addition to the data the hospital submits with its 
request for low-volume hospital status, to determine whether or not the 
hospital meets the qualifying criteria. (For additional information on 
our existing process for requesting the low-volume hospital payment 
adjustment, we refer readers to the FY 2019 IPPS/LTCH PPS final rule 
(83 FR 41399 through 41401).)
    As explained earlier, for FY 2019 and subsequent fiscal years, the 
discharge determination is made based on the hospital's number of total 
discharges, that is, Medicare and non-Medicare discharges, as was the 
case for FYs 2005 through 2010. Under Sec.  412.101(b)(2)(i) and (iii), 
a hospital's most recently submitted cost report is used to determine 
if the hospital meets the discharge criterion to receive the low-volume 
payment adjustment in the current year. As discussed in the FY 2019 
IPPS/LTCH PPS final rule (83 FR 41399 and 41400), we use cost report 
data to determine if a hospital meets the discharge criterion because 
this is the best available data source that includes information on 
both Medicare and non-Medicare discharges. (For FYs 2011 through 2018, 
the most recently available MedPAR data were used to determine the 
hospital's Medicare discharges because non-Medicare discharges were not 
used to determine if a hospital met the discharge criterion for those 
years.) Therefore, a hospital must refer to its most recently submitted 
cost report for total discharges (Medicare and non-Medicare) to decide 
whether or not to apply for low-volume hospital status for a particular 
fiscal year.
    As also discussed in the FY 2019 IPPS/LTCH PPS final rule, in 
addition to the discharge criterion, for FY 2019 and for subsequent 
fiscal years, eligibility for the low-volume hospital payment 
adjustment is also dependent upon the hospital meeting the applicable 
mileage criterion specified in Sec.  412.101(b)(2)(i) or (iii) for the 
fiscal year. Specifically, to meet the mileage criterion to qualify for 
the low-volume hospital payment adjustment for FY 2023, a hospital must 
be located more than 25 road miles from the nearest subsection (d) 
hospital. (We define in Sec.  412.101(a) the term ``road miles'' to 
mean ``miles'' as defined in Sec.  412.92(c)(1) (75 FR 50238 through 
50275 and 50414).) For establishing that the hospital meets the mileage 
criterion, the use of a web-based mapping tool as part of the 
documentation is acceptable. The MAC will determine if the information 
submitted by the hospital, such as the name and street address of the 
nearest hospitals, location on a map, and distance from the hospital 
requesting low-volume hospital status, is sufficient to document that 
it meets the mileage criterion. If not, the MAC will follow up with the 
hospital to obtain additional necessary information to determine 
whether or not the hospital meets the applicable mileage criterion.
    In accordance with our previously established process, a hospital 
must make a written request for low-volume hospital status that is 
received by its MAC by September 1 immediately preceding the start of 
the Federal fiscal year for which the hospital is applying for low-
volume hospital status in order for the applicable low-volume hospital 
payment adjustment to be applied to payments for its discharges for the 
fiscal year beginning on or after October 1 immediately following the 
request (that is, the start of the Federal fiscal year). For a hospital 
whose request for low volume hospital status is received after 
September 1, if the MAC determines the hospital meets the criteria to 
qualify as a low-volume hospital, the MAC will apply the applicable 
low-volume hospital payment adjustment to determine payment for the 
hospital's discharges for the fiscal year, effective prospectively 
within 30 days of the date of the MAC's low-volume status 
determination.
    Consistent with this previously established process, for FY 2023, 
we proposed that a hospital must submit a written request for low-
volume hospital status to its MAC that includes sufficient 
documentation to establish that the hospital meets the applicable 
mileage and discharge criteria (as described earlier). Specifically, 
for FY 2023, a hospital must make a written request for low-volume 
hospital status that is received by its MAC no later than September 1, 
2022, in order for the 25-percent, low-volume, add-on payment 
adjustment to be applied to payments for its discharges beginning on or 
after October 1, 2022. If a hospital's written request for low-volume 
hospital status for FY 2023 is received after September 1, 2022, and if 
the MAC determines the hospital meets the criteria to qualify as a low-
volume hospital, the MAC would apply the low-volume hospital payment 
adjustment to determine the payment for the hospital's FY 2023 
discharges, effective prospectively within 30 days of the date of the 
MAC's low-volume hospital status determination.
    Under this process, a hospital that qualified for the low-volume 
hospital payment adjustment for FY 2022 may continue to receive a low-
volume hospital payment adjustment for FY 2023 without reapplying if it 
meets both the discharge criterion and the mileage criterion applicable 
for FY 2023. As discussed previously, for FY 2023 the discharge and the 
mileage criteria are reverting to the statutory requirements that were 
in effect prior to FY 2011, and to the preexisting low-volume hospital 
qualifying criteria, as implemented in FY 2005 and specified in the 
existing regulations at Sec.  412.101(b)(2)(i). As in previous years, 
we proposed that such a hospital must send written verification that is 
received by its MAC no later than September 1, 2022, stating that it 
meets the mileage criterion applicable for FY 2023 (that is, is located 
more than 25 road miles from the nearest ``subsection (d)'' hospital). 
For FY 2023, we further proposed that this written verification must 
also state, based upon the most recently submitted cost report, that 
the hospital meets the discharge criterion applicable for FY 2023 (that 
is, less than 200 discharges total, including both Medicare and non-
Medicare discharges). If a hospital's request for low-volume hospital 
status for FY 2023 is received after September 1, 2022, and if the MAC 
determines the hospital meets the criteria to qualify as a low-volume 
hospital, the MAC will apply the 25-percent, low-volume, add-on payment 
adjustment to determine the payment for the hospital's FY 2023 
discharges, effective prospectively within 30 days of the date of the 
MAC's low-volume hospital status determination.
    We received no comments on our proposed process for requesting and 
obtaining the low-volume hospital payment adjustment for FY 2023 and 
therefore are finalizing this proposal without modification.
    We note, in the FY 2019 IPPS/LTCH PPS final rule (83 FR 41398 
through 41401 and 41702), in accordance with the provisions of section 
50204 of the Bipartisan Budget Act of 2018, for FY 2023 and subsequent 
fiscal years, we made conforming changes to the regulations at 42 CFR 
412.101 to reflect that the low-volume payment adjustment policy in 
effect for these

[[Page 49064]]

years is the same low-volume hospital payment adjustment policy in 
effect for FYs 2005 through 2010. Under these revisions, beginning with 
FY 2023, consistent with current law, the low-volume hospital 
qualifying criteria and payment adjustment methodology will return to 
the criteria and methodology that were in effect prior to the 
amendments made by the Affordable Care Act (that is, the low-volume 
hospital payment policy in effect for FYs 2005 through 2010). 
Therefore, no further revisions to the policy or to the regulations at 
Sec.  412.101 are required to conform them to the statutory requirement 
that the low-volume hospital policy in effect prior to the Affordable 
Care Act will again be in effect for FY 2023 and subsequent years.

D. Changes in the Medicare-Dependent, Small Rural Hospital (MDH) 
Program (Sec.  412.108)

1. Background for the MDH Program
    Section 1886(d)(5)(G) of the Act provides special payment 
protections, under the IPPS, to a Medicare-dependent, small rural 
hospital (MDH). (For additional information on the MDH program and the 
payment methodology, we refer readers to the FY 2012 IPPS/LTCH PPS 
final rule (76 FR 51683 through 51684).) As discussed in section V.B. 
of the preamble of this final rule, the MDH program provisions at 
section 1886(d)(5)(G) of the Act will expire at the end of FY 2022. 
Beginning with discharges occurring on or after October 1, 2022, all 
hospitals that previously qualified for MDH status will be paid based 
on the Federal rate.
    Since the extension of the MDH program through FY 2012 provided by 
section 3124 of the Affordable Care Act, the MDH program had been 
extended by subsequent legislation as follows: section 606 of the ATRA 
(Pub. L. 112- 240) extended the MDH program through FY 2013 (that is, 
for discharges occurring before October 1, 2013). Section 1106 of the 
Pathway for SGR Reform Act of 2013 (Pub. L. 113-67) extended the MDH 
program through the first half of FY 2014 (that is, for discharges 
occurring before April 1, 2014). Section 106 of the PAMA (Pub. L. 113-
93) extended the MDH program through the first half of FY 2015 (that 
is, for discharges occurring before April 1, 2015). Section 205 of the 
MACRA (Pub. L. 114-10) extended the MDH program through FY 2017 (that 
is, for discharges occurring before October 1, 2017). Section 50205 of 
the Bipartisan Budget Act (Pub. L. 115- 123) extended the MDH program 
through FY 2022 (that is for discharges occurring before October 1, 
2022). For additional information on the extensions of the MDH program 
after FY 2012, we refer readers to the following Federal Register 
documents:
     The FY 2013 IPPS/LTCH PPS final rule (77 FR 53404 through 
53405 and 53413 through 53414).
     The FY 2013 IPPS notice (78 FR 14689).
     The FY 2014 IPPS/LTCH PPS final rule (78 FR 50647 through 
50649).
     The FY 2014 interim final rule with comment period (79 FR 
15025 through 15027).
     The FY 2014 notice (79 FR 34446 through 34449).
     The FY 2015 IPPS/LTCH PPS final rule (79 FR 50022 through 
50024).
     The August 2015 interim final rule with comment period (80 
FR 49596).
     The FY 2017 IPPS/LTCH PPS final rule (81 FR 57054 through 
57057).
     The FY 2018 notice (83 FR 18303 through 18305).
     The FY 2019 IPPS/LTCH PPS final rule (83 FR 41429).
2. Expiration of the MDH Program
    Because section 50205 of the Bipartisan Budget Act extended the MDH 
program through FY 2022 only, beginning October 1, 2022, the MDH 
program will no longer be in effect. Because the MDH program is not 
authorized by statute beyond September 30, 2022, beginning October 1, 
2022, all hospitals that previously qualified for MDH status under 
section 1886(d)(5)(G) of the Act will no longer have MDH status and 
will be paid based on the IPPS Federal rate.
    When the MDH program was set to expire at the end of FY 2012, in 
the FY 2013 IPPS/LTCH PPS final rule (77 FR 53404 through 53405), we 
revised our sole community hospital (SCH) policies to allow MDHs to 
apply for SCH status in advance of the expiration of the MDH program 
and be paid as such under certain conditions. We codified these changes 
in the regulations at Sec.  412.92(b)(2)(i) and (v). Specifically, the 
existing regulations at Sec.  412.92(b)(2)(v) allow for an effective 
date of an approval of SCH status that is the day following the 
expiration date of the MDH program. We note that these same conditions 
apply to MDHs that intend to apply for SCH status with the expiration 
of the MDH program on September 30, 2022. Therefore, in order for an 
MDH to receive SCH status effective October 1, 2022, the MDH must apply 
for SCH status at least 30 days before the expiration of the MDH 
program; that is, the MDH must apply for SCH status by September 1, 
2022. The MDH also must request that, if approved as an SCH, the SCH 
status be effective with the expiration of the MDH program; that is, 
the MDH must request that the SCH status, if approved, be effective 
October 1, 2022, immediately after its MDH status expires with the 
expiration of the MDH program on September 30, 2022. We emphasize that 
an MDH that applies for SCH status in anticipation of the expiration of 
the MDH program would not qualify for the October 1, 2022, effective 
date for SCH status if it does not apply by the September 1, 2022, 
deadline. If the MDH does not apply by the September 1, 2022, deadline, 
the hospital would instead be subject to the usual effective date for 
SCH classification; that is, as of the date the MAC receives the 
complete application as specified at Sec.  412.92(b)(2)(i).
    We note that the regulations governing the MDH program are found at 
Sec.  412.108 and the MDH program is also cited in the general payment 
rules in the regulations at Sec.  412.90. As stated earlier, under 
current law, the MDH program will expire at the end of FY 2022, which 
is already reflected in Sec. Sec.  412.108 and 412.90(j). As such, we 
did not propose specific amendments to the regulations at Sec.  412.108 
or Sec.  412.90 to reflect the expiration of the MDH program. However, 
we proposed that if the MDH program were to be extended by law, similar 
to how it was extended through FY 2013, by the ATRA (Pub. L. 112-240); 
through March 31, 2014, by the Pathway for SGR Reform Act of 2013 (Pub. 
L. 113-167); through March 31, 2015, by the PAMA (Pub. L. 113-93); 
through FY 2017, by the MACRA (Pub. L. 114-10); and most recently 
through FY 2022, by the Bipartisan Budget Act of 2018 (Pub. L. 115-
123), we would make conforming changes to the regulations governing the 
MDH program at Sec.  412.108(a)(1) and (c)(2)(iii) and the general 
payment rules at Sec.  412.90(j) to reflect such an extension of the 
MDH program. We stated that these conforming changes would only be made 
if the MDH program were to be extended by statute beyond September 30, 
2022. As of the time of the development of this final rule, there has 
been no change in law to extend the MDH program beyond FY 2022. 
Therefore, in this final rule, we are not making any additional changes 
to the regulations governing the MDH program at Sec.  412.108 or the 
general payment rules at Sec.  412.90.
    Comment: Many commenters expressed support for extending the MDH 
program or making the MDH program permanent and noted that they would 
continue supporting congressional efforts to protect the MDH program. 
Some commenters also

[[Page 49065]]

expressed support for an additional base year for calculating MDH 
payments. A commenter urged CMS to remove the MDH program expiration 
proposal from the final rule. Several state hospital associations 
expressed their concern that hospitals in their states would experience 
significant payment decreases as a result of the expiration of the MDH 
program. A few commenters urged for action to be taken to ensure that 
the MDH program is extended, while other commenters urged CMS to 
explore alternatives and make immediate adjustments within its 
authority to provide relief and mitigate negative impacts to rural 
hospitals should Congress not act.
    Response: While we appreciate the commenters' concerns about the 
expiration of the MDH program and the financial impact to affected 
providers if the MDH program is not extended beyond FY 2022, CMS does 
not have the authority under current law to extend the MDH program 
beyond the September 30, 2022 statutory expiration date. Similarly, 
Section 1886(b)(3)(D) of the Act specifies the applicable base years or 
``target amounts'' for hospitals classified as MDHs. These comments are 
similar to comments we received previously, prior to the statutory 
extension of the MDH program for FY 2018 through FY 2022 provided by 
subsequent legislation, and discussed in the FY 2018 IPPS/LTCH PPS 
final rule (82 FR 38220 through 38221). In response to the comment 
urging CMS to explore other relief options should Congress not act, we 
will consider this for future rulemaking and explore potential ways to 
provide support to this subset of rural providers.
    Comment: Several commenters expressed support for CMS' policy that 
allows MDHs to apply for SCH status in advance of the expiration of the 
MDH program and be paid as such under certain conditions. Some 
commenters also requested that CMS also provide former MDHs with the 
ability to rescind their newly acquired SCH status and reinstate their 
MDH status in a seamless manner, if a retroactive extension to the MDH 
program is made.
    Response: We appreciate the commenters' support of our policy 
allowing MDHs to apply for SCH status in advance of the expiration of 
the MDH program and to be paid as such under certain conditions and 
allow for a seamless transition from MDH classification to SCH 
classification. In response to the suggestion that CMS provide former 
MDHs with ability to rescind their newly acquired SCH status and 
reinstate their MDH status in a seamless manner if a retroactive 
extension to the MDH program is made, we understand the desire on the 
part of hospitals for certainty in the face of MDH program expiration 
and will consider for future rulemaking any potential mechanisms to 
further streamline such transitions in connection with legislative 
extensions of the MDH program. We note that under the current 
regulations at Sec.  412.108(b)(4), the effective date for MDH 
classification is as of the date the MAC receives the complete 
application. A MDH that applied for and was classified as an SCH in 
advance of the MDH expiration per the regulations at Sec.  
412.92(b)(2)(v) could request a cancellation of its SCH status and 
simultaneously re-apply for MDH status if the MDH program were to be 
extended, and the MDH classification would be effective as of the date 
that the MAC receives the complete application. This would allow a 
former MDH to maintain special payment status as an SCH and then as an 
MDH generally without interruption in the event the MDH program is 
extended.
    Comment: Commenters urged CMS to expedite restoration of MDH 
status, should Congress act to extend these programs, stating that past 
retroactive restorations have seen delays that caused significant cash 
flow problems to affected hospitals. They requested that CMS move 
expeditiously to restore payments so that these rural facilities are 
able to continue to provide quality care to their communities and that 
CMS clarify how it might handle program extensions, should Congress 
enact legislation to extend them.
    Response: We appreciate the commenters' sharing their concerns 
relating to a retroactive restoration of the MDH program. As with past 
extensions, CMS will evaluate enacted legislation to determine the most 
appropriate approach to implement changes to the law, including 
instructions to the MACs to reinstate MDH status to eligible hospitals. 
As in the past, we will make every effort to implement any extension of 
the MDH program as expeditiously as possible.
    In summary, under current law, beginning October 1, 2022, all 
hospitals that previously qualified for MDH status will no longer have 
MDH status.

E. Indirect Medical Education (IME) Payment Adjustment Factor (Sec.  
412.105)

    Under the IPPS, an additional payment amount is made to hospitals 
with residents in an approved graduate medical education (GME) program 
in order to reflect the higher indirect patient care costs of teaching 
hospitals relative to nonteaching hospitals. The payment amount is 
determined by use of a statutorily specified adjustment factor. The 
regulations regarding the calculation of this additional payment, known 
as the IME adjustment, are located at Sec.  412.105. We refer readers 
to the FY 2012 IPPS/LTCH PPS final rule (76 FR 51680) for a full 
discussion of the IME adjustment and IME adjustment factor. Section 
1886(d)(5)(B)(ii)(XII) of the Act provides that, for discharges 
occurring during FY 2008 and fiscal years thereafter, the IME formula 
multiplier is 1.35.
    Accordingly, for discharges occurring during FY 2023, the formula 
multiplier is 1.35. We estimate that application of this formula 
multiplier for the FY 2023 IME adjustment will result in an increase in 
IPPS payment of 5.5 percent for every approximately 10 percent increase 
in the hospital's resident-to-bed ratio.
    We did not receive any comments regarding the IME adjustment 
factor, which, as noted earlier, is statutorily required. Accordingly, 
for discharges occurring during FY 2023, the IME formula multiplier is 
1.35.

F. Payment for Indirect and Direct Graduate Medical Education Costs 
(Sec. Sec.  412.105 and 413.75 Through 413.83)

1. Background
    Section 1886(h) of the Act, as added by section 9202 of the 
Consolidated Omnibus Budget Reconciliation Act (COBRA) of 1985 (Pub. L. 
99-272) and as currently implemented in the regulations at 42 CFR 
413.75 through 413.83, establishes a methodology for determining 
payments to hospitals for the direct costs of approved graduate medical 
education (GME) programs. Section 1886(h)(2) of the Act sets forth a 
methodology for the determination of a hospital-specific base-period 
per resident amount (PRA) that is calculated by dividing a hospital's 
allowable direct costs of GME in a base period by its number of full-
time equivalent (FTE) residents in the base period. The base period is, 
for most hospitals, the hospital's cost reporting period beginning in 
FY 1984 (that is, October 1, 1983 through September 30, 1984). The base 
year PRA is updated annually for inflation. In general, Medicare direct 
GME payments are calculated by multiplying the hospital's updated PRA 
by the weighted number of FTE residents working in all areas of the 
hospital complex (and at nonprovider sites, when applicable), and the 
hospital's Medicare share of total inpatient days.
    Section 1886(d)(5)(B) of the Act provides for a payment adjustment

[[Page 49066]]

known as the indirect medical education (IME) adjustment under the IPPS 
for hospitals that have residents in an approved GME program, in order 
to account for the higher indirect patient care costs of teaching 
hospitals relative to nonteaching hospitals. The regulations regarding 
the calculation of this additional payment are located at 42 CFR 
412.105. The hospital's IME adjustment applied to the DRG payments is 
calculated based on the ratio of the hospital's number of FTE residents 
training in either the inpatient or outpatient departments of the IPPS 
hospital (and, for discharges occurring on or after October 1, 1997, at 
non-provider sites, when applicable) to the number of inpatient 
hospital beds.
    The calculation of both direct GME payments and the IME payment 
adjustment is affected by the number of FTE residents that a hospital 
is allowed to count. Generally, the greater the number of FTE residents 
a hospital counts, the greater the amount of Medicare direct GME and 
IME payments the hospital will receive. In an attempt to end the 
implicit incentive for hospitals to increase the number of FTE 
residents, Congress, through the Balanced Budget Act of 1997 (Pub. L. 
105-33), established a limit on the number of allopathic and 
osteopathic residents that a hospital could include in its FTE resident 
count for direct GME and IME payment purposes. Under section 
1886(h)(4)(F) of the Act, for cost reporting periods beginning on or 
after October 1, 1997, a hospital's unweighted FTE count of residents 
for purposes of direct GME may not exceed the hospital's unweighted FTE 
count for direct GME in its most recent cost reporting period ending on 
or before December 31, 1996. Under section 1886(d)(5)(B)(v) of the Act, 
a similar limit based on the FTE count for IME during that cost 
reporting period is applied, effective for discharges occurring on or 
after October 1, 1997. Dental and podiatric residents are not included 
in this statutorily mandated cap.
    As mentioned previously, Medicare direct GME payments are 
calculated by multiplying the hospital's updated PRA by the weighted 
number of FTE residents working in all areas of the hospital complex 
(and at nonprovider sites, when applicable), and the hospital's 
Medicare share of total inpatient days. Section 1886(h)(4) of the Act 
specifies the methodology for determining the amount of FTE residents 
to be included in a hospital's direct GME payment formula. That is, the 
number of FTE residents training at a hospital (or in non-provider 
sites as applicable) would not necessarily equal the sum of those FTE 
residents used in the hospital's direct GME payment formula, since 
certain rules and factors are applied to adjust the count of FTE 
residents for direct GME payment purposes. First, section 1886(h)(4)(C) 
of the Act requires that a ``weighting factor'' of either 1.0 or 0.5 be 
applied to each FTE resident, as follows: In calculating the number of 
FTE residents in an approved residency program on or after July 1, 
1987, for a resident who is not in the resident's initial residency 
period, the weighting factor is 0.50. Section 1886(h)(5)(F) of the Act 
defines the term ``initial residency period'' as the ``period of board 
eligibility,'' with certain exceptions. Finally, section 1886(h)(4)(G) 
of the Act states that the term ``period of board eligibility'' means, 
for a resident, the minimum number of years of formal training 
necessary to satisfy the requirements for initial board eligibility in 
the particular specialty for which the resident is training. The direct 
GME calculation and our policy on applying the weighting factors to 
each FTE resident based on the FTE resident's status within or beyond 
the initial residency period (IRP) was established in the September 29, 
1989, Federal Register (54 FR 40287, 40292, 40305 and 40306), and 
implemented in the regulations at 42 CFR 413.86(f) (now 42 CFR 
413.79(a) and (b)).
    Thus, the FTE count used in the direct GME payment formula must be 
a weighted FTE count when a hospital is training residents beyond their 
IRPs. However, the direct GME FTE cap is an unweighted number. That is, 
under section 1886(h)(4)(F) of the Act, for cost reporting periods 
beginning on or after October 1, 1997, a hospital's unweighted FTE 
count of residents for purposes of direct GME may not exceed the 
hospital's unweighted FTE count for direct GME in its most recent cost 
reporting period ending on or before December 31, 1996 (that is the 
hospital's unweighted 1996 FTE cap or FTE cap). Regulations regarding 
the FTE caps and unweighted FTE counts were first published in the 
August 29, 1997, Federal Register (62 FR 45966). To address situations 
where a hospital's weighted FTE count exceeds its unweighted 1996 FTE 
cap, we established a policy effective for cost reporting periods 
beginning on or after October 1, 1997, to bring the weighted FTE count 
within the unweighted FTE cap using the following ratio on the Medicare 
cost report: ((1996 unweighted FTE cap/current year unweighted FTE 
count) x (current year total weighted FTE count)) (see 62 FR 46005 and 
63 FR 26,330 (May 12, 1998)). In the August 1, 2001, Federal Register 
(66 FR 39893 through 39896), we modified this ratio effective for cost 
reporting periods beginning on or after October 1, 2001, to separately 
account for a hospital's current year weighted primary care and 
obstetrics/gynecology (OB/GYN) FTE count and primary care and OB/GYN 
PRA, and current year weighted other FTE count and other PRA, as 
follows: (FTE cap/unweighted total FTEs in the cost reporting period) x 
(weighted primary care and OB/GYN FTEs in the cost reporting period) 
plus (FTE cap/unweighted total FTEs in the cost reporting period) x 
(weighted nonprimary care FTEs in the cost reporting period). The sum 
of the products is the current year allowable weighted FTE count. In 
addition, effective for cost reporting periods beginning on or after 
October 1, 2001, the direct GME payment is calculated using two 
separate rolling averages, one for primary care and OB/GYN FTE 
residents, and one for nonprimary care FTE residents. These 
calculations were implemented at 42 CFR 413.86(g)(4) and (5) 
respectively, currently 42 CFR 413.79(c)(2)(iii) and (d)(3).
2. Milton S. Hershey Medical Center, et al. v. Becerra Litigation
    On May 17, 2021, the U.S. District Court for the District of 
Columbia ruled against CMS's method of calculating direct GME payments 
to teaching hospitals when those hospitals' weighted FTE counts exceed 
their direct GME FTE cap. In Milton S. Hershey Medical Center, et al. 
v. Becerra (Slip. Op., 2021 WL 1966572, May 17, 2021), the court 
ordered CMS to recalculate reimbursement owed, holding that CMS's 
regulation impermissibly modified the statutory weighting factors 
discussed previously. The plaintiffs in these consolidated cases 
alleged that as far back as 2005, the proportional reduction that CMS 
applied to the weighted FTE count when the weighted FTE count exceeded 
the FTE cap conflicted with the Medicare statute, and it was an 
arbitrary and capricious exercise of agency discretion under the 
Administrative Procedure Act. The Court held that the proportional 
reduction methodology improperly modified the weighting factors 
statutorily assigned to residents and fellows. The court ordered CMS to 
pay the plaintiffs according to a more favorable method.
    For example, a hospital has a direct GME cap of 100, trains 90 FTE 
residents weighted at 1.0 and 10 FTE fellows weighted at 0.5, for a 
total unweighted

[[Page 49067]]

count of 100, and a total weighted FTE count of 95. Under current 
methodology, the proportional reduction is: (100 cap/100 current year 
unweighted count) x 95 (current year weighted count) = 95.
    If that hospital adds 10 more fellows and exceeds the cap with an 
unweighted total of 110 (90 residents and 20 fellows), its weighted FTE 
count of 100 is reduced as follows: (100 cap/110 current year 
unweighted count) x 100 (current year weighted count) = 90.91.
    The plaintiffs stated that CMS's proportional reduction method 
unlawfully reduced the weighting factor of 0.5 to an amount less than 
that, thereby reducing the capped weighted FTE amount (100 reduced to 
90.91 in the example) to which they were entitled for direct GME 
payment purposes. The court granted the plaintiffs' motion for summary 
judgment, denied defendant's, and remanded to the Agency so that it 
could recalculate plaintiffs' reimbursement payments consistent with 
the court's opinion. The court held that CMS's proportional reduction 
methodology, enacted at 42 CFR 413.79(c)(2)(iii), was inconsistent with 
the statutory weighting factors. In response to the court's decision, 
in the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28410 through 28412), 
we proposed to implement a modified policy applicable to all teaching 
hospitals, effective as of October 1, 2001, which would replace the 
existing policy at 42 CFR 413.79(c)(2)(iii). While the proportional 
reduction method struck down in Hershey was first effective for cost 
reports beginning on or after October 1, 1997, we are unaware of any 
open or reopenable NPRs for the 1997-2001 period where the proportional 
reduction method caused a provider's payments to be lower than they 
would be under our proposed new policy, but we welcomed comments 
alerting us of such NPRs. The proportional reduction method was amended 
to its present form effective for cost reporting periods beginning on 
or after October 2001. (See current 42 CFR 413.79(c)(2)(ii) and (iii).) 
Therefore, we proposed to modify the policy embodied in 42 CFR 
413.79(c)(2)(iii), which the Court found in Hershey was inconsistent 
with the statute.
    The Court's decision in Hershey held that our prior rule governing 
``computation of the approved number of full-time equivalent residents 
in an approved medical residency training program'' (Sec.  1886(h)(4) 
of the Act) was inconsistent with the statute. That statute further 
requires us to ``establish rules consistent with this paragraph'' for 
the computation of FTEs. Following our review of the district court's 
reasoning in Hershey and the statute, we concluded that our existing 
formula for computing the number of FTEs was inconsistent with the 
statutory requirements. It is also our view that the combination of the 
statutory requirement to ``establish rules'' and the Hershey court's 
conclusion that our existing rules are inconsistent with statutory 
requirements necessitates a new rulemaking. We further note that the 
Hershey decision does not mandate an alternative payment method, and we 
do not believe that the decision--or our independent conclusion that 
the formula should be modified--forecloses alternatives to the 
calculation method we finalize here. In the FY 2023 IPPS/LTCH PPS 
proposed rule (87 FR 28411), we stated our belief that, in order to 
comply with the statutory requirement to make rules governing the 
computation of FTEs, it is necessary to engage in a retroactive 
rulemaking to modify the statutorily-required rule effective for cost 
reporting periods beginning on or after October 1, 2001. While Hershey 
itself does not mandate this conclusion, we believe it would be 
inconsistent with the statute to calculate past payments for open cost 
reports based on a rule inconsistent with the law, particularly where a 
court ordered us to recalculate payments to plaintiffs. Doing so via 
notice-and-comment rulemaking is in the public interest because it will 
permit interested stakeholders to comment on the proposed approach, 
allow the agency to have the benefit of those comments in the 
development of a final rule, and calculate payments for past open cost 
years in a transparent, consistent, and efficient manner. This is 
particularly true in this situation, where the existing policy was 
promulgated via an interim final rule with comment period, and the 
agency received no comments on the policy the court found unlawful.
    In the proposed rule, we noted that because we proposed to 
establish this policy retroactively, it would cover cost reporting 
periods for which many NPRs have already been settled. Consistent with 
Sec.  405.1885(c)(2), any final rule retroactively adopting the 
proposed new policy would not be the basis for reopening final settled 
NPRs.
    After reviewing the statutory language regarding the direct GME FTE 
cap and the court's reasoning, we decided to propose a modified policy 
to be applied for cost reporting periods beginning on October 1, 2001, 
as described previously. The proposed modified policy would address 
situations for applying the FTE cap when a hospital's weighted FTE 
count was greater than its FTE cap, but would not reduce the weighting 
factor of residents that are beyond their IRP by an amount less than 
0.5. Section 1886(h)(4)(F) of the Act states that for purposes of a 
cost reporting period beginning on or after October 1, 1997, the total 
number of FTE residents before application of weighting factors may not 
exceed the number of such FTEs for the hospital's most recent cost 
reporting period ending on or before December 31, 1996. Under current 
policy, we interpreted this to mean that only a hospital's unweighted 
(before application of weighting factors) allopathic and osteopathic 
FTE count was compared to its FTE cap, and if the unweighted allopathic 
and osteopathic FTE count exceeded the FTE cap, then the proportional 
reduction is made to the weighted FTE counts. Under this modified 
proposed policy, in the instance where a hospital's unweighted 
allopathic and osteopathic FTE count exceeds its FTE cap, we proposed 
to add a step to also compare the total weighted allopathic and 
osteopathic FTE count to the FTE cap. If the total weighted allopathic 
and osteopathic FTE count is equal to or less than the FTE cap, then no 
adjustments would be made to the respective primary care & OB/GYN 
weighted FTE counts or the other weighted FTE counts. If the total 
weighted allopathic and osteopathic FTE count exceeds the FTE cap, then 
we would adjust the respective primary care & OB/GYN weighted FTE 
counts or the other weighted FTE counts to make the total weighted FTE 
count equal the FTE cap, as follows:

((primary care & OB/GYN weighted FTEs/total weighted FTEs) x FTE cap)) 
+ ((other weighted FTEs/total weighted FTEs) x FTE cap)).

    The sum would be the current year total allowable weighted FTE 
count, which would be reported on Worksheet E-4, line 9, column 3.
    More specific to the Medicare cost report, we proposed to revise 
the instructions to Worksheet E-4, line 9 to state: If line 6 is less 
than or equal to line 5, enter the amounts from line 8, columns 1 and 
2, in columns 1 and 2, of this line. Otherwise, if the total weighted 
FTE count from line 8, column 3 is greater than the amount on line 5, 
then enter in column 1 the result of ((primary care & OBGYN weighted 
FTEs/total weighted FTEs) x FTE cap)). Enter in column 2 the result of 
((other weighted FTEs/total weighted FTEs) x FTE cap)). Enter in column 
3 the sum of

((primary care & OBGYN weighted FTEs/total weighted FTEs) x FTE

[[Page 49068]]

cap)) + ((other weighted FTEs/total weighted FTEs) x FTE cap)).

    Example : [Note--see the comments and responses later in this 
section for a revised version of this Example 1] Hospital with an FTE 
cap of 100 trains 120 FTEs with a weight of 1.0, and 105 FTEs with a 
weight of 0.5, consisting of 70 weighted primary care & OBGYN FTEs and 
35 weighted other FTEs. Since the total weighted count of 105 
(Worksheet E-4, line 8, column 3) exceeds the FTE cap of 100 (Worksheet 
E-4, line 5), the Hospital reports the following adjusted weighted FTE 
counts on Worksheet E-4:
    Line 9, column 1: ((70 weighted primary care & OBGYN FTEs/105 total 
weighted FTEs) x 100 cap)) = 66.67.
    Line 9, column 2: ((35 weighted other FTEs/105 total weighted FTEs) 
x 100 cap)) = 33.33.
    Line 9, column 3: 66.67 FTEs + 33.33 FTEs = 100.
    Example 2: Hospital with an FTE cap of 100 trains 102 unweighted 
FTEs, equating to 96 weighted FTEs. This 96-weighted count consists of 
30 weighted primary care & OBGYN FTEs, and 66 weighted other FTEs. 
Since the total weighted count of 96 (Worksheet E-4, line 8, column 3) 
is less than the FTE cap of 100 (Worksheet E-4, line 5), then no 
further adjustment is needed; enter the amounts from line 8, columns 1 
and 2, in columns 1 and 2, of line 9.
    Example 3: Hospital with a cap of 100 FTEs trains 90 FTEs with a 
weight of 1.0, and 20 FTEs with a weight of 0.5. Since the total 
weighted count is 100 (90 + (20 x 0.5)), then no further adjustment is 
needed. Enter the amounts from line 8, columns 1 and 2, in columns 1 
and 2 of line 9.
    Comment: We received many comments supporting our proposed revision 
to the weighted count methodology and to the Medicare cost reporting 
instructions. Commenters urged CMS to finalize the proposed revision, 
asserting it is required by the law and the court's order, and to 
recalculate payments immediately, as over a year has passed since the 
court order.
    Response: We appreciate the commenters' support, and upon issuance 
of this final rule, we will work with the MACs and other impacted 
parties to recalculate and issue adjusted payments as soon as possible.
    Comment: Many commenters urged CMS to abandon the proposal to use 
retroactive rulemaking as the means of complying with the decision of 
the Hershey court. These commenters stated that retroactive rulemaking 
is strongly disfavored under the Medicare statute and permitted only 
under limited circumstances as specified in section 1871(e)(1)(A) of 
the Act, namely, when it is either necessary to comply with statutory 
requirements (Sec.  1871(e)(1)(A)(i)) of the Act); or when failure to 
apply the change retroactively would be contrary to the public interest 
(Sec.  1871(e)(1)(A)(ii) of the Act). Commenters asserted that neither 
of these exceptions applies in the present case.
    With respect to the exception at section 1871(e)(1)(A)(i) of the 
Act, commenters stated that retroactive rulemaking is not necessary for 
CMS to comply with statutory requirements. Commenters said that the 
Medicare statute is unambiguous with respect to the weighting of 
residents and fellows, and that the proposed revision to the 
methodology is the only way for CMS to comply with the statutory 
directive and the Hershey decision, neither of which requires any 
interpretation by the agency. Commenters also stated that the exception 
at section 1871(e)(1)(A)(ii) does not apply, since it does not serve 
the public interest for CMS to engage in retroactive rulemaking and to 
entertain public comments on actions that the agency is required to 
take under a legally binding court order. According to a commenter, 
engaging in retroactive rulemaking in this instance implicitly 
contradicts the court's decision, while others expressed concern that 
it would create a precedent whereby CMS might invoke public interest in 
receiving comments as a justification for virtually any retroactive 
rule change. Commenters also stated that it is not necessary for CMS to 
engage in retroactive rulemaking to benefit from public comments, 
pointing out that in the past the agency has made retroactive policy 
changes via program instruction and only submitted the policies to 
public comment for purposes of prospective application.
    Commenters also rejected the argument that retroactive rulemaking 
in this instance is necessary to comply with the Supreme Court's ruling 
in Azar v. Allina Health Services. Commenters observed that the Allina 
ruling established the need for notice-and-comment rulemaking to change 
a substantive legal standard governing payment where the agency engages 
in ``gap-filling'' an ambiguous statute. However, as previously stated, 
commenters believed that the statute is unambiguous with regard to the 
weighting of residents and fellows, and that therefore there are no 
gaps for the agency to fill. In other words, as stated by a commenter, 
the proposed policy is already dictated by the statute as explained in 
Hershey, and there is no room for CMS to substantively change the 
policy enacted by Congress.
    Furthermore, commenters disagreed with CMS's position, as 
originally stated in the FY 2023 IPPS/LTCH proposed rule, that 
retroactive rulemaking is necessary in the wake of the Hershey ruling 
since the Secretary ``has no promulgated rule governing'' direct GME 
payments to teaching hospitals over the cap for cost reporting periods 
beginning on or after October 1, 2001 (87 FR 28411). A number of 
commenters stated that the Hershey court did not leave CMS with a 
regulatory void to fill, but merely ruled ``that the regulation is 
unlawful as applied to the Plaintiffs''; even if the court had vacated 
the existing regulation, these commenters asserted that notice-and-
comment rulemaking would not be required or appropriate to acquiesce to 
the vacatur. By contrast, another commenter stated that the existing 
regulation is a ``legal nullity'' in light of the Hershey decision, but 
nevertheless stated that the statutory payment directive requires no 
substantive change in policy and can be properly effectuated without 
rulemaking.
    Citing a number of examples, commenters observed that historically, 
both before and after Allina, CMS has implemented policy changes to 
resolve appeals or comply with court decisions without engaging in 
retroactive rulemaking, and invoked its retroactive rulemaking 
authority only under particular circumstances, such as in response to a 
natural disaster or when a rule is published after a statute's 
effective date. Only more recently, according to commenters, has CMS 
inappropriately begun to engage in retroactive rulemaking in response 
to litigation. Rather than engage in retroactive rulemaking to comply 
with the Hershey decision, commenters urged CMS to make the change in 
regulation prospectively and to employ other appropriate means, such as 
program instruction to the MACs or settlement with hospitals, to 
implement the proposed correction for past years.
    While urging CMS to abandon retroactive rulemaking as the means of 
complying with the Hershey decision, commenters stated that, if CMS 
does engage in retroactive rulemaking, it should specify exactly which 
hospitals and past cost reporting periods will be eligible for relief 
under the revised policy. In particular, commenters pointed out that 
CMS proposed that ``certain other providers'' will be eligible for 
relief in addition to the plaintiffs in Hershey, but the preamble does 
not make it clear who those

[[Page 49069]]

providers will be. These commenters stated that CMS should reopen all 
cost reports within the three-year reopening period and recalculate 
direct GME payments consistent with the statute. At a minimum, however, 
the ``certain other providers'' should include any provider that, if 
applicable, has an appeal pending with the Provider Reimbursement 
Review Board or in federal court on the same issue as Hershey. In 
addition, if CMS does not reopen all cost reports that are within the 
three-year reopening period, it should nonetheless apply the 
methodology any time a cost report is reopened and the direct GME 
payment is altered. Other commenters likewise stated that hospitals 
should be permitted to reopen their cost reports for the purpose of 
recalculating their direct GME payments according to the revised 
weighting methodology, and that CMS should not finalize any ongoing 
cost report audits until the final rule has been issued.
    Some commenters expressed concern that CMS's proposal to extend 
relief to only certain providers is inconsistent with concept of 
retroactive rulemaking. Another commenter objected to CMS's statement 
that under 42 CFR 405.1885(c)(2), any final rule retroactively adopting 
the proposed new policy would not be the basis for reopening final 
settled NPRs (87 FR 28411). This commenter asserted that Sec.  
405.1885(c)(2) does not apply to retroactive rulemaking, and that CMS's 
proposal has ``no real retroactive effect'' if it does not serve as the 
basis for reopening settled cost reports. Another commenter similarly 
recommended that CMS make the new policy ``fully retroactive'' so that 
even final settled NPRs subject to reopening may be reopened for the 
purpose of applying the revised methodology. This commenter stated that 
withholding relief from certain providers would be arbitrary and 
capricious and result in CMS not fully complying with the statute.
    Response: We appreciate the comments regarding our proposal to 
implement the court's decision in Hershey retroactively, but for the 
reasons that follow (as well as those stated in the proposed rule), we 
are finalizing our policy as proposed, retroactive to 2001.
    We agree with commenters who objected to our statement that there 
is ``no promulgated rule governing'' direct GME payments to over-the-
cap hospitals. The Hershey court did not vacate the rule. We further 
agree that the Hershey decision itself does not require us to engage in 
retroactive rulemaking. However, the statute at issue states that 
``[t]he Secretary shall establish rules consistent with this paragraph 
for the computation of the number of full-time equivalent residents in 
an approved medical residency training program.'' Section1886(h)(4)(A) 
of the Act (emphasis added). And the Hershey court did say that the 
rules at issue were not consistent with the statute. Following our 
review of the Hershey court's reasoning and the statutory requirements, 
we decided that our method for computing FTEs was not consistent with 
statutory requirements. We therefore conclude that our existing rule, 
which does not comply with the statute, should be modified 
retroactively such that our FTE computation rules are consistent with 
the statute and payments, including payments for open cost years in 
past, are calculated pursuant to regulation.
    Several commenters state that no rule is necessary because of an 
express statutory mandate that fellows be counted as 0.5 FTE. We 
disagree, for two reasons. First, there are two express statutory 
mandates in the section cited by commenters: that the Secretary 
promulgate rules, and that those rules weight fellows at 0.5 FTE (see 
sections 1886(h)(4)(A) and 1886(h)(4)(C)(iv) of the Act). In other 
words, the statutory language cited by commenters describes the content 
of the rules the Secretary is required to promulgate, rather than 
setting an independent statutory benchmark. Second, we disagree with 
the commenters' position that the rule we proposed was the only 
possible way to compute FTE counts in light of Hershey. Section 
1886(h)(4)(C) is not the only relevant statutory provision governing 
the content of the rule; section 1886(h)(4)(F)(i) of the Act requires 
the rules to cap the number of unweighted residents based on a 
hospital's FY 1996 FTE count. In Hershey itself, the court did not 
mandate a particular method of calculation or require CMS to adopt the 
plaintiffs' proposed calculation method. We believe that there is more 
than one way to comply with the statutory requirements and the court's 
order. Our decision in this rule does not mean that all other 
alternatives were foreclosed by the Hershey decision. The Hershey court 
decision held that the prior regulation governing FTE counting for 
over-the-cap hospitals was unlawful. It did not mandate any particular 
alternative approach. We further disagree with commenters to the extent 
they suggest that we compute FTE counts without a rule in place for 
doing so. As discussed elsewhere, the statute at issue requires the 
Secretary to establish a rule.
    Even if the Hershey decision did mandate a single method of 
computing FTE counts, it was silent on how to incorporate that 
computation into the three-year rolling average. Without a rule for 
determining the inputs to the three-year-rolling average, which we 
proposed and are now finalizing, it is impossible to calculate a given 
provider's dollar reimbursement. Therefore, even if we agreed with 
commenters that the Hershey decision provided sufficient guidance for 
computing FTE counts and that no further rulemaking on that issue is 
required, we would nonetheless consider it necessary to undergo 
rulemaking to implement our response to the decision, that is, use its 
requirements to develop a method for calculating reimbursement. For 
these reasons, we disagree with commenters who believe that notice-and-
comment rulemaking is unnecessary to implement the Hershey decision, 
including for past cost years.
    We appreciate the comments about retroactive rulemaking here being 
inconsistent with CMS's historical practice. Many of the examples 
raised by commenters do not involve judicial decisions calling into 
question agency rules, which is a key factor here, as we noted in the 
proposed rule. The governing statute requires the Secretary to 
promulgate rules governing reimbursement that are consistent with 
statutory requirements, and the court's decision in Hershey concluded 
that our existing rule was not consistent with those requirements. We 
do not believe that using retroactive rulemaking in this instance is 
inconsistent with our past practice.
    We acknowledge that our statutory authority to engage in 
retroactive rulemaking is limited by section 1871(e)(1)(A) of the Act. 
As previously discussed, we believe that the explicit statutory 
requirement that the Secretary promulgate a rule governing GME 
reimbursement renders retroactive application here ``necessary to 
comply with statutory requirements.'' 1871(e)(1)(A)(i). If we 
promulgated this rule prospectively only, a necessary result would be 
that some hospitals would receive GME reimbursement based on a 
computation of FTE equivalents that was not established by rule. We 
emphasize again that the rule at issue in Hershey and the rule we 
promulgate here are not merely statutory gap-fillers. The statute 
affirmatively requires us to promulgate a rule.

[[Page 49070]]

    In the alternative, and even if it were permissible to compute the 
number of FTEs without a rule governing the methodology for doing so, 
we believe that retroactive rulemaking here is in the public interest 
(section 1871(e)(1)(A)(ii) of the Act). In response to comments, we 
want to make clear that we believe that public notice-and-comment will 
benefit the rulemaking process generally. As we noted in the preamble, 
there was limited public comment on the key provisions of the original 
rulemaking that the Hershey court found inconsistent with statutory 
requirements. And we acknowledge--and we do not believe that commenters 
disagree--that it is necessary to recalculate past payments in light of 
the Hershey decision. The public interest will be served by having past 
payments calculated in the same way as future payments, and given our 
view that it is necessary to engage in notice-and-comment rulemaking to 
implement the Hershey decision, we believe it is sensible and efficient 
to calculate past payments based on a formula promulgated with the 
benefit of notice-and-comment rulemaking. We do not mean to imply that 
the public interest requires consistency between past payments and 
future payments in all conceivable situations. However, where--as 
here-- payment was set by a regulation that a court held inconsistent 
with substantive statutory requirements and the agency engages in new 
notice-and-comment rulemaking to implement that judicial ruling, there 
is a public benefit in having past payments calculated via the same 
method as future payments. This is particularly true where the statute 
at issue requires that payments be calculated pursuant to a rule. We 
therefore believe that this is a case where the public interest in 
having a rule applicable to all payments, both past and future, 
justifies retroactive rulemaking. It would be contrary to the public 
interest for plaintiffs in Hershey and other judicial challenges to 
have their payments calculated by a different methodology (whether more 
or less generous than the methodology established by regulation) than 
other providers that are otherwise similarly situated. Retroactive 
rulemaking in this situation, benefits the public interest by achieving 
parity in payment among similarly situated hospitals.
    We also believe that the public interest is served by having 
payments for past open cost years calculated in a transparent, 
efficient, and not administratively burdensome fashion, an interest 
that is served by promulgating a rule (following notice-and-comment) 
that applies to those cost years. This rule will allow us to calculate 
payments to hospitals with open cost reports based on a universal and 
transparent formula, and it will allow many hospitals (and MACs) to 
avoid the administrative expense of calculating payments based on a 
formula that the agency has concluded should not be applied. The public 
interest is further served by reducing the need for hospitals to file 
administrative appeals in order to obtain the benefit of the new 
payment formula.
    We appreciate comments regarding the applicability of 42 CFR 
405.1885(c)(2) to this rule. We disagree that 405.1885(c)(2) does not 
apply to retroactive rules. The text of the regulation does not support 
that proposed carve-out. The rule we proposed--and finalize here--is a 
``change of legal interpretation or policy by CMS in a regulation . . . 
made in response to judicial precedent,'' and thus it is ``not a basis 
for reopening a CMS or contractor determination.'' Some commenters 
urged us to apply 42 CFR 405.1885(c)(1) to direct contractors to reopen 
cost reports, but we note that paragraph (c)(1) allows CMS to do so 
(``CMS may direct a contractor . . . to reopen and revise'') subject to 
the prohibited reopening's in paragraph (c)(2). We disagree that this 
rule will have no ``real retroactive effect,'' as a number of hospitals 
will receive increased reimbursement for past cost reporting years.
    We further disagree that it is arbitrary and capricious to apply 
405.1885(c)(2) here. This is not the first time that we have made a 
policy change that could potentially affect closed cost reports, and we 
have previously declined to direct reopening of closed cost reports 
consistent with the policy favoring finality embedded in 
405.1885(c)(2). For example, we permitted qualifying hospitals to 
request application of a policy change made in the FY 2020 IPPS rule to 
FYs 2011 through 2017, ``subject to the reopening rules at 42 CFR 
405.1885.'' (84 FR 42349) We believe that the policy we finalize here 
is consistent with our past practice and our general approach toward 
finality.
    Comment: Many commenters appreciated that CMS proposed that ``If 
the number of FTE residents weighted in accordance with paragraph (b) 
of this section does not exceed [the FTE cap], then the allowable 
weighted FTE count is the actual weighted FTE count.'' However, some 
commenters pointed out that CMS's proposed change to the instructions 
for line 9 of Worksheet E-4 does not contain language reflecting this 
scenario and requested that CMS add a third sentence to the proposed 
changes to the instructions for line 9. The sentence should state as 
follows: ``If the total weighted FTE count from line 8, column 3 is 
less than or equal to the amount on line 5, then enter the amounts from 
line 8, columns 1 and 2, in columns 1 and 2 of this line.''
    Response: We agree with the commenters' request and will revise the 
proposed instructions to Worksheet E-4, line 9 to address the 
commenters' request. However, since we are adding the sentence 
requested by the commenters, then we are removing the following: ``If 
line 6 is less than or equal to line 5, enter the amounts from line 8, 
columns 1 and 2, in columns 1 and 2, of this line.'' This latter 
sentence is not necessary, since if line 6 is less than or equal to 
line 5, then by default line 8, column 3 will also be less than or 
equal to line 5. We are revising the instructions to Worksheet E-4, 
line 9 to state: If the total weighted FTE count from line 8, column 3 
is less than or equal to the amount on line 5, then enter the amounts 
from line 8, columns 1 and 2, in columns 1 and 2 of this line (emphasis 
added). Otherwise, if the total weighted FTE count from line 8, column 
3 is greater than the amount on line 5, then enter in column 1 the 
result of ((primary care & OBGYN weighted FTEs/total weighted FTEs) x 
FTE cap)). Enter in column 2 the result of ((other weighted FTEs/total 
weighted FTEs) x FTE cap)). Enter in column 3 the sum of columns 1 and 
2.
    Under section 1886(h)(4)(G)(i) and 42 CFR 413.79(d)(3), a 
hospital's weighted FTE count for payment purposes is the 3-year 
average of its current year weighted FTEs, prior year weighted FTEs, 
and penultimate year FTEs (for primary care & OBGYN FTEs and other FTEs 
respectively). Effective for cost reporting periods beginning on or 
after October 1, 2001, we proposed to implement this modified 
methodology for the purpose of determining the prior year weighted FTE 
count on line 12 of Worksheet E-4, and for the purpose of determining 
the penultimate year's weighted FTE count on line 13 of Worksheet E-4, 
even though the prior and penultimate years' FTE counts would be from 
cost reporting periods prior to October 1, 2001. In this manner, the 
modified methodology would be fully applied to determining the direct 
GME payment for cost reporting periods beginning on or after October 1, 
2001.
    Therefore, we proposed to modify the cost report instructions on 
Worksheet E-4, lines 12 and 13, respectively to state that effective 
for cost reporting periods beginning on or after October 1, 2001, if 
subject to the cap in the prior

[[Page 49071]]

year or penultimate year respectively, if the prior/penultimate year 
total weighted FTE count from line 8, column 3 is greater than the 
amount on line 5 from the prior/penultimate year, then enter in column 
1 the result of ((primary care & OBGYN weighted FTEs/total weighted 
FTEs) x FTE cap)). Enter in column 2 the result of ((other weighted 
FTEs/total weighted FTEs) x FTE cap)) plus the amount on line 10, 
column 2. These instructions do not in any way modify or reopen final-
settled prior and penultimate year NPRs.
    Comment: Some commenters supported CMS's proposal to update the 
cost report instructions for lines 12 and 13 of Worksheet E-4 to ensure 
that the weighted resident FTE counts from the prior and penultimate 
years will be updated to reflect the new direct GME payment formula. 
However, the commenters pointed out that the proposed language for 
lines 12 and 13 does not specify how to calculate the weighted FTE 
count for the prior and/or penultimate years when the unweighted FTE 
count from those years exceeds the FTE cap, but the weighted FTE count 
from those years does not, and requested that CMS add a sentence to the 
instructions for lines 12 and 13 stating: ``If the prior/penultimate 
year total weighted FTE count from line 8, column 3 is less than or 
equal to line 5 from the prior/penultimate year, then enter the amounts 
from line 8, columns 1 and 2, in columns 1 and 2 of this line.''
    Response: We agree with the commenters' request and are revising 
the instructions on Worksheet E-4 lines 12 and 13 to state: Effective 
for cost reporting periods beginning on or after October 1, 2001, if 
the prior/penultimate year total weighted FTE count from line 8, column 
3 is less than or equal to line 5 from the prior/penultimate year, then 
enter the amounts from line 8, columns 1 and 2, in columns 1 and 2 of 
this line (emphasis added). If subject to the cap in the prior year or 
penultimate year respectively, if the prior/penultimate year total 
weighted FTE count from line 8, column 3 is greater than the amount on 
line 5 from the prior/penultimate year, then enter in column 1 the 
result of ((primary care & OBGYN weighted FTEs/total weighted FTEs) x 
FTE cap)). Enter in column 2 the result of ((other weighted FTEs/total 
weighted FTEs) x FTE cap)) plus the amount on line 10, column 2.
    Comment: Several commenters observed that CMS should have also 
proposed to apply the revised direct GME weighting methodology to the 
so-called ``section 422 MMA (Medicare Modernization Act) cap slots'' as 
well. Specifically, many teaching hospitals received additional FTE 
caps following a redistribution of unused FTE cap slots mandated by 
section 422 of the MMA. Similar to the fellowship penalty, CMS applies 
a proportional methodology when determining payment for section 422 cap 
FTEs. The commenters suggested that CMS calculate the ``Section 422 
Allowable Direct GME FTE Resident Count'' on Worksheet E-4, line 22 as 
follows:
     If the weighted FTEs on line 8 are less than or equal to 
the adjusted FTE cap on line 5, the hospital would have entered the 
weighted FTEs from line 8 on line 9. In this instance, the additional 
section 422 cap slots are unnecessary, and the hospital would enter 
zero on line 22.
     If the weighted FTEs on line 8 are greater than the 
adjusted FTE cap on line 5, the hospital would have entered the 
adjusted FTE cap on line 9. In this instance, the hospital would 
subtract line 9 from line 8 and proceed as follows:
    [cir] If line 9 minus line 8 equals or exceeds the ``Section 422 
Direct GME FTE Cap'' on line 20, then the hospital would enter the 
amount from line 20 on line 22.
    [cir] If line 9 minus line 8 is less than line 20, the hospital 
would enter line 9 minus line 8 on line 20.
    Response: We agree with the commenters' observation that the 
revised methodology should apply to the MMA section 422 FTE cap, as the 
mathematical cap concept is the same for the 422 FTE cap as it is for 
the regular FTE cap. Accordingly, for portions of cost reporting 
periods beginning on or after July 1, 2005, the effective date of 
section 422 under 42 CFR 413.79(c)(4), we will revise Worksheet E-4, 
line 22, as follows:
    For portions of cost reporting periods beginning on or after July 
1, 2005, if the weighted FTE count on line 8 is less than or equal to 
the adjusted FTE cap on line 5, the hospital would have entered the 
weighted FTEs from line 8 on line 9. In this instance, the additional 
Sec.  422 cap slots are unnecessary; do not complete lines 22 through 
24. If the weighted FTE count on line 8 is greater than the adjusted 
FTE cap on line 5, the hospital would have entered the adjusted FTE cap 
on line 9. In this instance, subtract line 9 from line 8. If line 9 
minus line 8 equals or exceeds the ``Section 422 Direct GME FTE Cap'' 
on line 20, then enter the amount from line 20 on line 22. If line 9 
minus line 8 is less than line 20, enter line 9 minus line 8 on line 
22. (We note the commenters indicated ``enter line 9 minus line 8 on 
line 20,'' but we believe they meant to say ``on line 22'').
    We proposed to amend the regulations text at 42 CFR 
413.79(c)(2)(iii) to state that, effective for cost reporting periods 
beginning on or after October 1, 2001, if the hospital's unweighted 
number of FTE residents exceeds the limit described in this section of 
the final rule, and the number of weighted FTE residents in accordance 
with Sec.  413.79(b) also exceeds that limit, the respective primary 
care and obstetrics and gynecology weighted FTE counts and other 
weighted FTE counts are adjusted to make the total weighted FTE count 
equal the limit. If the number of FTE residents weighted in accordance 
with Sec.  413.79(b) does not exceed that limit, then the allowable 
weighted FTE count is the actual weighted FTE count.
    Comment: A commenter requested that CMS make conforming changes to 
the three-year rolling average regulation at. Sec.  413.79(d)(3) to 
clarify that the weighted FTE counts for the ``preceding two cost 
reporting periods'' must be calculated in accordance with the revised 
payment formula at Sec.  413.79(c)(2)(iii).
    Response: We agree to add a parenthetical to the regulations at 
Sec.  413.79(d)(3) to state, ``For cost reporting periods beginning on 
or after October 1, 2001, the hospital's weighted FTE counts for the 
preceding two cost reporting periods are calculated in accordance with 
the payment formula at 42 CFR 413.79(c)(2)(iii)).''
    Comment: A commenter stated they would like to see the three-year 
rolling average eliminated retroactive to October 1, 2001, as it would 
delay implementation of CMS's proposed payment formula.
    Response: Under section 1886(h)(4)(G)(i) and 42 CFR 413.79(d)(3), a 
hospital's weighted FTE count for payment purposes is the 3-year 
average of its current year weighted FTEs, prior year weighted FTEs, 
and penultimate year weighted FTEs (for primary care & OBGYN FTEs and 
other FTEs respectively). Our proposed interpretation of section 
1886(h)(4)(F) of the Act regarding application of weighting factors 
does not change this portion of the statute regarding application of 
the 3-year rolling average. Therefore, we are not adopting the 
commenter's request to eliminate application of the rolling average 
under our proposed payment formula.
    Comment: Some commenters requested that CMS correct or clarify 
certain misstatements in the FY 2023 IPPS/LTCH PPS proposed rule 
regarding the Hershey case. First, CMS should be clearer about the 
position of the Hershey

[[Page 49072]]

plaintiffs. CMS described the position of the Hershey plaintiffs as 
follows: ``The plaintiffs in these consolidated cases alleged that as 
far back as 2005, the proportional reduction that CMS applied to the 
weighted FTE count when the weighted FTE count exceeded the FTE cap 
conflicted with the Medicare statute'' (87 FR 28410). According to the 
commenters, this is an incomplete description of the plaintiffs' 
position. The commenters stated that CMS's proportional reduction also 
impermissibly reduces the weighted FTE count when the weighted FTE 
count is less than unweighted FTE cap.
    Second, the commenters believed that ``Example 1'' in the preamble 
is misstated. In that example, a ``Hospital with an FTE cap of 100 
trains 120 FTEs with a weight of 1.0 and 105 FTEs with a weight of 0.5, 
consisting of 70 weighted primary care & OBGYN FTEs and 35 weighted 
other FTEs'' (87 FR 28411). The ``total weighted count'' is ``105.'' 
The commenters noted that if the hospital trained 120 FTEs with a 
weight of 1.0 and 105 FTEs with a weight of 0.5, its unweighted FTE 
count would be 225 (120 + 105), and its weighted FTE count would be 
172.5 ((120 x 1.0) + (105 x 0.5)), not 105. The commenters believed 
that CMS intended this example to say that the hospital had an 
unweighted FTE count of 120 and a weighted FTE count of 105. The 105 
weighted FTEs would consist of 90 FTEs weighted at 1.0 and 30 FTEs 
weighted at 0.5.
    Response: Regarding the first point about not fully capturing 
Plaintiffs' position, we acknowledge the commenters' assertion that the 
plaintiffs in Hershey argued that CMS's proportional reduction 
impermissibly reduced the weighted FTE count when the weighted FTE 
count was less than unweighted FTE cap.
    Regarding the second point that the commenters believe that Example 
1 is misstated, we acknowledge the confusing wording, and we are 
providing a corrected Example 1 as follows:
    Example 1 Revised: Hospital with an FTE cap of 100 trains 120 
unweighted FTEs, consisting of 105 weighted FTEs (90 FTEs weighted at 
1.0 and 30 FTEs weighted at 0.5 = 105 weighted FTEs). The 105 weighted 
FTEs further consists of 70 weighted primary care & OBGYN FTEs and 35 
weighted other FTEs. Since the total weighted count of 105 (Worksheet 
E-4, line 8, column 3) exceeds the FTE cap of 100 (Worksheet E-4, line 
5), the Hospital reports the following adjusted weighted FTE counts on 
Worksheet E-4:
    Line 9, column 1: ((70 weighted primary care & OBGYN FTEs/105 total 
weighted FTEs) x 100 cap)) = 66.67.
    Line 9, column 2: ((35 weighted other FTEs/105 total weighted FTEs) 
x 100 cap)) = 33.33.
    Line 9, column 3: 66.67 FTEs + 33.33 FTEs = 100.
    Comment: A commenter requested clarification on the implications of 
the Medicare direct GME formula change for hospitals that participate 
in the Children's Hospitals Graduate Medical Education (CHGME) program 
administered by HRSA.
    Response: Since the CHGME program is administered by HRSA and not 
by CMS, we defer to HRSA to determine the implications of CMS's change 
to the Medicare direct GME payment formula.
    After consideration of comments received, we are finalizing our 
proposed policy and regulations text at 42 CFR 413.79(c)(2)(iii) to 
state that, effective for cost reporting periods beginning on or after 
October 1, 2001, if the hospital's unweighted number of FTE residents 
exceeds the limit described in this section of the final rule, and the 
number of weighted FTE residents in accordance with Sec.  413.79(b) 
also exceeds that limit, the respective primary care and obstetrics and 
gynecology weighted FTE counts and other weighted FTE counts are 
adjusted to make the total weighted FTE count equal the limit. If the 
number of FTE residents weighted in accordance with Sec.  413.79(b) 
does not exceed that limit, then the allowable weighted FTE count is 
the actual weighted FTE count. In response to comments, we are also 
making a conforming change to the regulations text at 42 CFR 
413.79(d)(3) regarding application to the 3-year rolling average to 
state that for cost reporting periods beginning on or after October 1, 
2001, the hospital's weighted FTE counts for the preceding two cost 
reporting periods are calculated in accordance with the payment formula 
at Sec.  413.79(c)(2)(iii). In addition, in response to comments, we 
are applying the new payment methodology to the MMA section 422 FTE 
cap.
3. Reasonable Cost Payment for Nursing and Allied Health Education 
Programs
a. General
    Under section 1861(v) of the Act, Medicare has historically paid 
providers for Medicare's share of the costs that providers incur in 
connection with approved educational activities. Approved nursing and 
allied health (NAH) education programs are those that are, in part, 
operated by a provider, and meet State licensure requirements, or are 
recognized by a national accrediting body. The costs of these programs 
are excluded from the definition of inpatient hospital operating costs 
and are not included in the calculation of payment rates for hospitals 
or hospital units paid under the IPPS, IRF PPS, or IPF PPS, and are 
excluded from the rate-of-increase ceiling for certain facilities not 
paid on a PPS. These costs are separately identified and ``passed 
through'' (that is, paid separately on a reasonable cost basis). 
Existing regulations on NAH education program costs are located at 
Sec.  413.85. The most recent rulemakings on these regulations were in 
the January 12, 2001 final rule (66 FR 3358 through 3374), and in the 
August 1, 2003, final rule (68 FR 45423 and 45434).
b. Medicare+Choice Nursing and Allied Health Education Payments
    Section 541 of the Balanced Budget Refinement Act (BBRA) of 1999 
provides for additional payments to hospitals for costs of nursing and 
allied health education associated with services to Medicare+Choice 
(now called Medicare Advantage (MA)) enrollees. Hospitals that operate 
approved nursing or allied health education programs and receive 
Medicare reasonable cost reimbursement for these programs would receive 
additional payments from MA organizations. Section 541 of the BBRA 
limits total spending under the provision to no more than $60 million 
in any calendar year (CY). (In this document, we refer to the total 
amount of $60 million or less as the payment ``pool''.) Section 541 of 
the BBRA also provides that direct graduate medical education (GME) 
payments for Medicare+Choice utilization are reduced to the extent that 
these additional payments are made for nursing and allied health 
education programs. This provision was effective for portions of cost 
reporting periods occurring in a CY, on or after January 1, 2000.
    Section 512 of the Benefits Improvement and Protection Act (BIPA) 
of 2000 changed the formula for determining the additional amounts to 
be paid to hospitals for MA nursing and allied health costs. Under 
section 541 of the BBRA, the additional payment amount was determined 
based on the proportion of each individual hospital's nursing and 
allied health education payment to total nursing and allied health 
education payments made to all hospitals. However, this formula did not 
account for a hospital's specific MA utilization. Section 512 of the 
BIPA revised this payment formula to specifically account for each 
hospital's

[[Page 49073]]

MA utilization. This provision was effective for portions of cost 
reporting periods occurring in a calendar year, beginning with CY 2001, 
and was implemented in the August 1, 2001 IPPS final rule (66 FR 39909 
and 39910).
    The regulations at 42 CFR 413.87 codified both statutory 
provisions. We first implemented the BBRA NAH MA provision in the 
August 1, 2000 IPPS interim final rule with comment period (IFC) (65 FR 
47036 through 47039). In that IFC, we outlined the qualifying 
conditions for a hospital to receive the NAH MA payment, how we would 
calculate the NAH MA payment pool, and how a qualifying hospital would 
calculate its ``share'' of payment from that pool. Determining a 
hospital's NAH MA payment essentially involves applying a ratio of the 
hospital-specific NAH Part A payments, total inpatient days, and MA 
inpatient days, to national totals of those same amounts, from cost 
reporting periods ending in the fiscal year that is 2 years prior to 
the current calendar year. The formula is as follows:

(((Hospital NAH pass-through payment/Hospital Part A Inpatient Days) * 
Hospital MA Inpatient Days)/((National NAH pass-through payment/
National Part A Inpatient Days) * National MA Inpatient Days)) * 
Current Year Payment Pool.

    With regard to determining the total national amounts for NAH pass-
through payment, Part A inpatient days, and MA inpatient days, we note 
that section 1886(l) of the Act, as added by section 541 of the BBRA, 
gives the Secretary the discretion to ``estimate'' the national 
components of the formula noted previously. For example, section 
1886(l)(2)(A) of the Act states that the Secretary would estimate the 
ratio of payments for all hospitals for portions of cost reporting 
periods occurring in the year under subsection 1886(h)(3)(D) to total 
direct GME payments estimated for the same portions of periods under 
subsection 1886(h)(3) of the Act. Accordingly, we made the following 
statements in the August 1, 2000 IFC:
     Each year, we would determine and publish in a final rule 
and a final rule the total amount of nursing and allied health 
education payments made across all hospitals during the fiscal year 
that is 2 years prior to the current calendar year (65 FR 47038). We 
would use the best available cost reporting data for the applicable 
hospitals from the Hospital Cost Report Information System (HCRIS) for 
cost reporting periods in the fiscal year that is 2 years prior to the 
current calendar year (65 FR 47038).
     To calculate the pool, in accordance with section 1886(l) 
of the Act, we would ``estimate'' a total amount for each calendar 
year, not to exceed $60 million (65 FR 47038).
     To calculate the proportional reduction to Medicare+Choice 
(now MA) Direct GME payments, we stated that the percentage is 
estimated by calculating the ratio of the Medicare+Choice nursing and 
allied health payment ``pool'' for the current calendar year to the 
projected total Medicare+Choice direct GME payments made across all 
hospitals for the current calendar year. We stated that the projections 
of Medicare+Choice direct GME and Part A direct GME are based on the 
best available cost report data from the HCRIS (for example, for 
calendar year 2000, the projections are based on the best available 
cost report data from HCRIS 1998), and these payment amounts were 
increased using the increases allowed by section 1886(h) of the Act for 
these services (using the percentage applicable for the current 
calendar year for Medicare+Choice direct GME and the Consumer Price 
Index (CPI) increases for Part A direct GME). We also stated that we 
would publish the applicable percentage reduction each year in the IPPS 
proposed and final rules (65 FR 47038).
    Thus, in the August 1, 2000, IFC, we described our policy regarding 
the timing and source of the national data components for the NAH MA 
add-on payment and the percent reduction to the direct GME MA payments, 
and we stated that we would publish the rates for each calendar year in 
the IPPS proposed and final rules. While the rates for CY 2000 were 
published in the August 1, 2000, IFC (see 65 FR 47038 and 47039), the 
rates for subsequent CYs were only issued through Change Requests (CRs) 
(CR 2692, CR 11642, CR 12407). After recent issuance of the CY 2019 
rates in CR 12407 on August 19, 2021, we reviewed our update 
procedures, and were reminded that the August 1, 2000 IFC states that 
we would publish the NAH MA rates and direct GME percent reduction 
every year in the IPPS rules. Accordingly, for CY 2020 and forward, the 
NAH MA add-on rates will be proposed and included in the IPPS proposed 
and final rules, and we are also reiterating the data sources we would 
use.
    In the FY 2023 IPPS/LTCH PPS proposed rule, we proposed the NAH MA 
add-on rates as well as the direct GME MA percent reductions for CYs 
2020 and 2021. We proposed to issue the rates for CYs 2020 and 2021 
because we believe we have sufficient HCRIS data to develop the rates 
for these years, and these rate years are most needed to ensure 
accurate and timely cost report settlements of cost reports with 
portions overlapping with CYs 2020 and 2021. We expect to propose to 
issue the rates for CY 2022 in the FY 2024 IPPS/LTCH PPS proposed rule, 
and the rates for CY 2023 in the FY 2025 IPPS/LTCH PPS proposed rule, 
and so forth.
    Consistent with the use of HCRIS data for past calendar years, for 
CY 2020, we proposed to use data from cost reports ending in FY 2018 
HCRIS (the fiscal year that is 2 years prior to CY 2020) to compile 
these national amounts: NAH pass-through payment, Part A Inpatient 
Days, MA Inpatient Days. We proposed to use data from cost reports 
ending in FY 2019 HCRIS (the fiscal year that is 2 years prior to CY 
2021) to compile the same national amounts for CY 2021.
    For the proposed rule, we accessed the HCRIS data from the fourth 
quarterly HCRIS update of 2021. However, to calculate the ``pool'' and 
the direct GME MA percent reduction, we ``project'' Part A direct GME 
payments and MA direct GME payments for the current calendar years, 
which in this final rule, are CYs 2020 and 2021, based on the ``best 
available cost report data from the HCRIS'' (65 FR 47038). Next, 
consistent with the method we described previously from the August 1, 
2000 IFC, we increased these payment amounts from midpoint to midpoint 
of the appropriate calendar year using the increases allowed by section 
1886(h) of the Act for these services (using the percentage applicable 
for the current calendar year for MA direct GME, and the Consumer Price 
Index-Urban (CPI-U) increases for Part A direct GME. For CY 2020, the 
direct GME projections are based on FY 2019 HCRIS. For CY 2021, the 
direct GME projections are based on FY 2019 HCRIS. For CYs 2020 and 
2021, the proposed national rates and percentages, and their data 
sources are set forth in this table. We stated in the proposed rule 
that we intend to update these numbers in the FY 2023 final rule based 
on the latest available cost report data.

[[Page 49074]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.130

    We did not propose any changes to the regulations text at 42 CFR 
413.87, as our proposal to include the nursing and allied health MA 
rates in the IPPS rulemaking was consistent with current regulations.
    Comment: A commenter requested clarification on the calculation of 
the direct GME MA percent reduction and questioned if it is separate 
from the allocation of funds used for the NAH pass-through payment.
    Response: We appreciate the commenter's request for clarification. 
As explained previously in the background section, under sections 541 
of the BBRA and 512 of BIPA, hospitals that operate approved nursing or 
allied health education programs and receive Medicare reasonable cost 
reimbursement for these programs would receive additional payments for 
services associated with MA enrollees. Section 541 of the BBRA limits 
total spending under the provision to no more than $60 million in any 
calendar year (CY). Section 541 of the BBRA also provides for estimated 
reductions in direct GME MA payments, which are to equal the estimated 
total additional MA NAH payments. Thus, nationally, the estimated 
reductions to direct GME MA payments would not be more than $60 million 
in any CY. However, on a hospital-specific basis, the direct GME MA 
percent reduction is not necessarily tied to receipt of the MA NAH add-
on payment. That is, hospitals that are both teaching hospitals 
receiving direct GME payments and that operate approved NAH programs 
may be affected by both aspects of these laws; such hospitals may 
receive both a payment for MA NAH, while also receiving a reduced 
direct GME MA payment. Hospitals that only operate NAH programs may 
only receive the MA NAH payment; conversely, teaching hospitals with no 
approved NAH programs would only receive the reduced direct GME MA 
payment.
    We received numerous comments regarding various aspects of the MA 
NAH add-on and the direct GME MA percent reduction, expressing 
opposition to reconciliation of overpayments, voicing concerns 
regarding reimbursement that does not adequately reflect current costs 
and nursing and healthcare workforce shortages, and opposing reductions 
to direct GME payments to fund NAH programs. While concerns expressed 
in these comments may be important, we did not specifically make 
proposals related to those concerns. These comments are out of scope, 
and therefore, we are not responding to them at this time.
    For this final rule, consistent with the use of HCRIS data for past 
calendar years, for CY 2020, we use data from cost reports ending in FY 
2018 HCRIS (the fiscal year that is 2 years prior to CY 2020) to 
compile these national amounts: NAH pass-through payment, Part A 
Inpatient Days, MA Inpatient Days. We use data from cost reports ending 
in FY 2019 HCRIS (the fiscal year that is 2 years prior to CY 2021) to 
compile the same national amounts for CY 2021. For this final rule, we 
accessed the HCRIS data from the first quarterly HCRIS update of 2022. 
However, to calculate the ``pool'' and the direct GME MA percent 
reduction, we ``project'' Part A direct GME payments and MA direct GME 
payments for the current calendar years, which in this final rule, are 
CYs 2020 and 2021 as the best available cost report data. Next, 
consistent with the method we described previously from the August 1, 
2000 IFC, we increased these payment amounts from midpoint to midpoint 
of the appropriate calendar year using the increases allowed by section 
1886(h) of the Act for these services (using the percentage applicable 
for the current calendar year for MA direct GME, and the Consumer Price 
Index-Urban (CPI-U) increases for Part A direct GME. For CY 2020, the 
direct GME projections are based on FY 2019 HCRIS. For CY 2021, the 
direct GME projections are based on FY 2019 HCRIS. For CYs 2020 and 
2021, the final national rates and percentages, and their data sources 
are set forth in this table.

[[Page 49075]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.131

    In summary, after consideration of the public comments received, we 
are finalizing our proposal to use NAH MA add-on rates as well as the 
direct GME MA percent reductions for CYs 2020 and 2021, based on 
sufficient HCRIS data to develop the rates for these years. We expect 
to propose to issue the rates for CY 2022 in the FY 2024 IPPS/LTCH PPS 
proposed rule, and the rates for CY 2023 in the FY 2025 IPPS/LTCH PPS 
proposed rule, and so forth.
4. Allowance of Medicare GME Affiliation Agreements Within Certain 
Rural Track FTE Limitations
    Sections 1886(h)(4)(F) and 1886(d)(5)(B)(v) of the Act established 
limits on the number of allopathic and osteopathic residents that 
hospitals may count for purposes of calculating direct GME payments and 
the IME adjustment, respectively, thereby establishing hospital-
specific direct GME and IME full-time equivalent (FTE) resident caps. 
However, under the authority granted by section 1886(h)(4)(H)(ii) of 
the Act, the Secretary may issue rules to allow institutions that are 
members of the same affiliated group to apply their direct GME and IME 
FTE resident caps on an aggregate basis through a Medicare GME 
affiliation agreement. The Secretary's regulations permit hospitals, 
through a Medicare GME affiliation agreement, to increase or decrease 
their IME and direct GME FTE resident caps to reflect the rotation of 
residents among affiliated hospitals for agreed-upon academic years. 
Consistent with the broad authority conferred by the statute, we 
established criteria for defining an ``affiliated group'' and an 
``affiliation agreement'' in both the August 29, 1997, final rule (62 
FR 45966, 46006) and the May 12, 1998, final rule (63 FR 26318). In the 
August 1, 2002, IPPS final rule (67 FR 50069), we amended our 
regulations to require that each Medicare GME affiliation agreement 
must have a shared rotational arrangement. The term ``Medicare GME 
affiliation agreement'' is defined at 42 CFR 413.75(b) as a written, 
signed, and dated agreement by responsible representatives of each 
respective hospital in a Medicare GME affiliated group, as defined in 
Sec.  413.75(b), that specifies--
     The term of the Medicare GME affiliation agreement (which, 
at a minimum is 1 year), beginning on July 1 of a year;
     Each participating hospital's direct and indirect GME FTE 
caps in effect prior to the Medicare GME affiliation;
     The total adjustment to each hospital's FTE caps in each 
year that the Medicare GME affiliation agreement is in effect, for both 
direct GME and IME, that reflects a positive adjustment to one 
hospital's direct and indirect FTE caps that is offset by a negative 
adjustment to the other hospital's (or hospitals') direct and indirect 
FTE caps of at least the same amount;
     The adjustment to each participating hospital's FTE counts 
resulting from the FTE resident's (or residents') participation in a 
shared rotational arrangement at each hospital participating in the 
Medicare GME affiliated group for each year the Medicare GME 
affiliation agreement is in effect. This adjustment to each 
participating hospital's FTE count is also reflected in the total 
adjustment to each hospital's FTE caps (in accordance with in 
accordance with paragraph (3) of this definition); and
     The names of the participating hospitals and their 
Medicare provider numbers.
    We also define the term ``Shared Rotational Arrangement'' in that 
section of our rules as a residency training program under which a 
resident(s) participates in training at two or more hospitals in that 
program.
    To encourage the training of residents in rural areas, section 
407(c) of the Medicare, Medicaid, and SCHIP Balanced Budget Refinement 
Act of 1999 (Pub. L. 106-113) (BBRA) amended section 1886(h)(4)(H) of 
the Act to add a provision (subsection (iv)) stating that, in the case 
of a hospital that is not located in a rural area (an urban hospital) 
that establishes separately accredited approved medical residency 
training programs (or rural tracks) in a rural area, or has an 
accredited training program with an integrated rural track, the 
Secretary shall adjust the urban hospital's cap on the number of FTE 
residents under section 1886(h)(4)(F) of the Act, in an appropriate 
manner in order to encourage training of physicians in rural areas. 
Historically, the Accreditation Council for Graduate Medical Education 
(ACGME) has separately accredited family medicine programs in the ``1-2 
format'' (meaning, residents in the 1-2 format receive their first year 
experience at a core family medicine program, and their second and 
third year experiences at another site, which may or may not be rural). 
Section 407(c) of Public Law 106-113 was effective for direct GME 
payments to hospitals for cost reporting periods beginning on or after 
April 1, 2000, and for IME payments applicable to discharges occurring 
on or after April 1, 2000. We refer readers to the August 1, 2000, 
interim final rule with comment period (65 FR 47025, 47033 through 
47037) and the FY 2002 IPPS final rule (66 FR 39828, 39902 through 
39909) where we implemented section 407(c) of Public Law 106-113. The 
regulations for establishing rural track FTE limitations are located at 
42 CFR 413.79(k) for direct GME and at 42 CFR 412.105(f)(1)(x) for IME. 
(We note that additional legislative and regulatory changes were made 
to Rural Track Programs in the December 27, 2021 final rule, 86 FR 
73445.)
    When we first implemented the rural track regulations in the August 
1, 2000 IFC, we specified that the caps associated with rural tracks 
are separate and distinct from a hospital's general FTE caps. 
Specifically, we defined Rural track FTE limitation at 42 CFR 413.75(b) 
as the maximum number of residents training in a rural track residency 
program that an urban hospital may include in its FTE count and that is 
in

[[Page 49076]]

addition to the number of FTE residents already included in the 
hospital's FTE cap (emphasis added). As a result, the rural track FTE 
limitations are not part of the regular FTE caps that hospitals may 
aggregate in Medicare GME affiliation agreements.
    The rural track FTE limitations are calculated in the same manner 
as the adjustments to any allowable new program, in accordance with 42 
CFR 413.79(e)(1). That is, at the end of the 5-year cap building window 
for the rural track program, the urban hospital's and rural hospital 
respective IME and direct GME rural track FTE limitations are 
calculated as the product of three factors (limited to the number of 
accredited slots for each program):
     The highest total number of FTE residents trained in any 
program year during the fifth year of the first new program's existence 
at all of the hospitals to which the residents in the program rotate.
     The number of years in which residents are expected to 
complete the program, based on the minimum accredited length for each 
type of program.
     The ratio of the number of FTE residents in the new 
program that trained at the hospital over the entire 5-year period to 
the total number of FTE residents that trained at all hospitals over 
the entire 5-year period.
    Thus, while the calculated rural track FTE limitations calculated 
at the end of the 5-year window may reflect the division of the 
rotations between the urban and rural hospitals over the 5 initial 
years of the program, the future rotations amounts may change somewhat 
(albeit adhering to greater than 50 percent of the duration of the 
training occurring in the rural hospital/rural area). As rotations 
shift to meet patient care needs, the respective rural track FTE 
limitations may not quite match the amount of FTEs actually training in 
the urban and rural hospitals. There has been request that the same 
flexibility with cap sharing afforded to teaching hospitals to share 
general FTE cap slots via Medicare GME affiliation agreements also be 
afforded to urban and rural teaching hospitals that together train 
residents in a rural track program. This flexibility would allow the 
urban and rural hospitals to share their rural track FTE limitations in 
a manner that best matches the rotations occurring in the urban and 
rural hospitals. Stakeholders representing urban-rural training 
partnerships specifically raised this request with regard to separately 
accredited 1-2 family medicine programs that have existed for a number 
of years, and either already have established their rural track FTE 
limitations, or have just recently reached or will reach the end of 
their 5-year cap building windows.
    We have considered this request and agree it would be equitable to 
allow an urban and rural hospital jointly training residents in a 1-2 
separately accredited family medicine program to aggregate their 
respective IME and direct GME rural track FTE limitations and enter 
into a ``Rural Track Medicare GME Affiliation Agreement'' to share 
those cap slots, and facilitate the cross-training of residents. We 
proposed to allow urban and rural hospitals that participate in the 
same separately accredited 1-2 family medicine rural track program and 
have rural track FTE limitations to enter into ``Rural Track Medicare 
GME Affiliation Agreements.'' We proposed that programs that are not 
separately accredited in the 1-2 format and are not in family medicine 
would not be permitted to enter into ``Rural Track Medicare GME 
Affiliation Agreements'' under this proposal. These Rural Track 
Medicare GME Affiliation Agreements, which we proposed to define in 
this final rule, will be structured similarly to regular Medicare GME 
affiliation agreements, but we proposed two distinct requirements.
    First, in an effort to ensure that regular FTE caps and FTE 
residents in non-rural track programs are not commingled with the rural 
track FTE residents, and that rural track FTE limitations are not being 
used to provide additional cap slots for non-rural track FTE residents, 
we proposed that the responsible representatives of each urban and 
rural hospital entering into the Rural Track Medicare GME Affiliation 
Agreement must attest in that written agreement that each participating 
hospital's FTE counts and rural track FTE limitations in the agreement 
do not reflect FTE residents nor FTE caps associated with programs 
other than the rural track program. We noted this attestation is 
important for both the urban and rural hospital, as both urban and 
rural hospitals may have regular FTE caps that could be part of regular 
Medicare GME affiliation agreements (see 42 CFR 413.79(e)(1)(iv) and 
(v) and 413.79(f)). Second, we proposed to only allow urban and rural 
hospitals to participate in Rural Track Medicare GME Affiliated Groups 
if they are separately accredited 1-2 family medicine programs that 
have rural track FTE limitations in place prior to October 1, 2022. We 
proposed to choose these criteria and this date of October 1, 2022, as 
the date by which eligible hospitals must have rural track FTE 
limitations in place because the effective date of section 127 of the 
Consolidated Appropriations Act (CAA) is cost reporting periods 
beginning on or after October 1, 2022, and we proposed to limit this 
proposal to only rural track FTE limitations established under the BBRA 
of 1999 that are unaffected by section 127 of the CAA. In this final 
rule, we are distinguishing between rural track programs with rural 
track FTE limitations associated with the BBRA of 1999 in effect prior 
to October 1, 2022, and Rural Track Programs (RTPs, defined at 42 CFR 
413.75(b)) started or expanded to new participating sites under the 
authority of section 127 of the CAA. We explain this distinction later 
in this section of the final rule.
    First, we refer readers to the December 27, 2021, final rule (86 FR 
73445) for details about section 127 of the CAA. Generally, that 
provision removes the requirement that rural track programs be 
separately accredited, places in statute (previously in regulation) the 
requirement that rural track residents must spend greater than 50 
percent of their training time in a rural area, and allows urban and 
rural hospitals to receive adjustments to their rural track FTE 
limitations for adding new rural training sites to an existing rural 
track program. In that December 27, 2021, final rule, we addressed a 
comment (86 FR 73456) that requested whether multiple rural hospital 
training sites added under the new section 127 authority may share 
their rural track FTE limitations via a Medicare GME affiliation 
agreement. We responded that effective October 1, 2022, we are not 
permitting the formation of Medicare GME affiliated groups for the 
purpose of aggregating and cross-training RTP FTE limitations. First, 
we explained that we believe Medicare GME affiliated groups for RTPs 
would be premature, as only starting October 1, 2022, would hospitals 
have the first opportunity to add additional participating sites. 
Subsequently, there would be the 5-year cap building period in which 
Medicare GME affiliations are not permitted, even under existing 
Medicare GME affiliation agreement rules (42 CFR 413.79(f)). Second, we 
stated that before we create Medicare GME affiliation agreements unique 
to RTPs, we believe it would be best to first modify the Medicare cost 
report form to add spaces for the hospitals to indicate the number of 
any additional RTP FTEs, and the caps applicable to those FTEs. We also 
stated that we wish to assess flexibility within a hospital's own total 
RTP FTE limitation, before sharing those slots with other hospitals. We 
would need to be vigilant to ensure

[[Page 49077]]

that the RTP FTE limitations are not comingled with regular FTE cap 
adjustments currently used in Medicare GME affiliation agreements. 
Therefore, we concluded with our belief that it is best to reassess 
allowing Medicare GME affiliation agreements for RTP FTE limitations at 
some point in the future. For these same reasons, at this time, we 
believe it is appropriate to only propose to allow rural track Medicare 
GME affiliation agreements with urban and rural hospitals that have a 
rural track FTE limitation in place prior to October 1, 2022. We will 
assess allowing these agreements with RTP FTE limitations established 
after October 1, 2022, in the future.
    We proposed the following new definitions and requirements at 42 
CFR 413.75(b):
     ``Rural track Medicare GME affiliated group'' is an urban 
hospital and a rural hospital that participates in a rural track 
program defined in 42 CFR 413.75(b), and that have rural track FTE 
limitations in effect prior to October 1, 2022, and that comply with 42 
CFR 413.79(f)(1) through (6) for Medicare GME affiliated groups.
     ``Rural track Medicare GME affiliation agreement'' is a 
written, signed, and dated agreement by responsible representatives of 
each respective hospital in a rural track Medicare GME affiliated 
group, as defined in 42 CFR 413.75(b), that specifies--
    ++ A statement attesting that each participating hospital's FTE 
counts and rural track FTE limitations in the agreement do not reflect 
FTE residents nor FTE caps associated with programs other than the 
rural track program.
    ++ The term of the rural track Medicare GME affiliation agreement 
(which, at a minimum is 1 year), beginning on July 1 of a year;
    ++ Each participating hospital's direct and indirect GME rural 
track FTE limitations in effect prior to the rural track Medicare GME 
affiliation;
    ++ The total adjustment to each hospital's rural track FTE 
limitations in each year that the rural track Medicare GME affiliation 
agreement is in effect, for both direct GME and IME, that reflects a 
positive adjustment to one hospital's direct and indirect rural track 
FTE limitations that is offset by a negative adjustment to the other 
hospital's (or hospitals') direct and indirect rural track FTE 
limitations of at least the same amount;
    ++ The adjustment to each participating hospital's FTE counts 
resulting from the FTE resident's (or residents') participation in a 
shared rotational arrangement at each hospital participating in the 
rural track Medicare GME affiliated group for each year the Medicare 
GME affiliation agreement is in effect. This adjustment to each 
participating hospital's FTE count is also reflected in the total 
adjustment to each hospital's rural track FTE limitations (in 
accordance with paragraph (iii) of the definition (regarding the total 
adjustment to each hospital's rural track FTE limitations previously 
noted)); and
    ++ The names of the participating hospitals and their Medicare 
provider numbers.
    In addition, we proposed to require that no later than July 1 of 
the residency year during which the rural track Medicare GME 
affiliation agreement will be in effect, the urban and rural hospital 
must submit the signed agreement to the CMS contractor or MAC servicing 
the hospital and send a copy to the CMS Central Office. The hospitals 
may submit amendments to the adjustments to their respective rural 
track FTE limitations to the MAC with a copy to CMS by June 30 of the 
residency year that the agreement is in effect. We proposed that 
eligible urban and rural hospitals may enter into rural track Medicare 
GME affiliation agreements effective with the July 1, 2023, academic 
year.
    With regard to how the rural track Medicare GME affiliation 
adjustments would be reported on the Medicare cost report, first, for 
background, we noted in the proposed rule that on the previous Medicare 
cost report CMS-Form-2552-96, the rural track FTE limitation was 
combined, together with the ``cap'' add-on for new (non-rural track) 
programs on Worksheet E, Part A, line 3.05, and on Worksheet E-3, Part 
IV, line 3.02. On the current cost report CMS-Form-2552-10, the rural 
track FTE limitation is, likewise, combined together with the ``cap'' 
add-on for new (non-rural track) programs on Worksheet E, Part A, line 
6, and on Worksheet E-4, line 2. We stated in the proposed rule that 
going forward, we intend to add lines to the cost report to accommodate 
separate reporting of urban or rural hospital rural track FTE 
limitations, and the positive or negative adjustments made to the rural 
track FTE limitations, including those applicable to the affiliated 
agreements.
    In summary, we proposed to allow urban and rural hospitals that 
participate in the same separately accredited 1-2 family medicine rural 
track program and have rural track FTE limitations to enter into 
``Rural Track Medicare GME Affiliation Agreements''. We proposed that 
programs that are not separately accredited in the 1-2 format and are 
not in family medicine would not be permitted to enter into ``Rural 
Track Medicare GME Affiliation Agreements'' under this proposal. We 
proposed to add new definitions at 42 CFR 413.75(b) of rural track 
Medicare GME affiliated group and rural track Medicare GME affiliation 
agreement. We also proposed to require that the responsible 
representatives of each urban and rural hospital entering into the 
rural track Medicare GME affiliation agreement must attest in that 
agreement that each participating hospital's FTE counts and rural track 
FTE limitations in the agreement do not reflect FTE residents nor FTE 
caps associated with programs other than the rural track program. In 
addition, we proposed to only allow urban and rural hospitals to 
participate in rural track Medicare GME affiliated groups if they have 
rural track FTE limitations in place prior to October 1, 2022. We 
proposed that eligible urban and rural hospitals may enter into rural 
track Medicare GME affiliation agreements effective with the July 1, 
2023, academic year.
    Comment: The majority of commenters strongly supported CMS's 
proposal to enable rural training flexibilities through Medicare GME 
affiliation agreements between urban and rural hospitals that have 
rural track programs. Some commenters ``applauded'' CMS for its 
attention to rural GME training, and appreciated additional options for 
cap flexibilities afforded to rural hospitals. A commenter stated that 
the proposal will assist urban hospitals in providing flexibilities 
needed to address disparities affected by geography and other social 
determinants of care. Some commenters stated that the proposal will 
help provide care to Medicare beneficiaries and may create interest for 
future physicians to practice in rural settings. Many commenters who 
supported the proposal also added that CMS should engage in future 
rulemaking that will allow any RTP, not just those separately 
accredited in family medicine that were established prior to October 1, 
2022, to also engage in affiliation agreements following the conclusion 
of the cap-building period.
    Response: We thank the commenters for their feedback and support. 
As we stated in the proposed rule, we proposed to only allow urban and 
rural hospitals to participate in Rural Track Medicare GME Affiliated 
Groups if they are separately accredited 1-2 family medicine programs 
that have rural track FTE limitations in place prior to October 1, 
2022. We stated that we are distinguishing between rural track programs 
with rural track FTE

[[Page 49078]]

limitations associated with the BBRA of 1999 in effect prior to October 
1, 2022, and Rural Track Programs (RTPs, defined at 42 CFR 413.75(b)) 
started or expanded to new participating sites under the authority of 
section 127 of the CAA effective on or after October 1, 2022. We 
explained that we are not permitting the formation of Medicare GME 
affiliated groups for the purpose of aggregating and cross-training RTP 
FTE limitations effective on or after October 1, 2022, because we 
believe Medicare GME affiliated groups for RTPs would be premature, as 
only starting October 1, 2022, would hospitals have the first 
opportunity to add additional participating sites. Subsequently, there 
would be the 5-year cap building period in which Medicare GME 
affiliations would not be permitted, even under existing Medicare GME 
affiliation agreement rules (42 CFR 413.79(f)). In addition, we stated 
that before we created Medicare GME affiliation agreements unique to 
RTPs, we believe it would be best to first modify the Medicare cost 
report form to add spaces for the hospitals to indicate the number of 
any additional RTP FTEs, and the caps applicable to those FTEs. We also 
stated that we wished to assess flexibility within a hospital's own 
total RTP FTE limitation, before sharing those slots with other 
hospitals. We would need to be vigilant to ensure that the RTP FTE 
limitations were not comingled with regular FTE cap adjustments 
currently used in Medicare GME affiliation agreements. We concluded 
with our belief that it would be best to reassess allowing Medicare GME 
affiliation agreements for RTP FTE limitations at some point in the 
future. For these same reasons, at this time, we believe it is 
appropriate to only propose to allow rural track Medicare GME 
affiliation agreements with urban and rural hospitals that have a 
separately accredited rural track program and rural track FTE 
limitation in place prior to October 1, 2022. We will assess allowing 
these agreements with RTP FTE limitations established after October 1, 
2022, in the future.
    Comment: A commenter representing a group of organizations opposed 
CMS's proposal to allow Medicare GME affiliation agreements for rural 
track programs with FTE limitations prior to October 1, 2022, and did 
not believe the use of affiliation agreements resolves concerns over 
the inequity of the current method for determining a cap to be applied 
to rural track programs. The commenter was concerned that the proposal 
establishes additional barriers to many programs. The commenter 
believed that the proposal is too narrow, limited only to family 
medicine training, and only to separately accredited training tracks 
established prior to the CAA 2021. Specifically, the commenter observed 
that currently, CMS counts the time residents spend training at the 
rural site, across five years, and the time spent in the urban setting, 
and then counts the highest number (in any program year) during the 
fifth year of the cap-setting window across all participating 
hospitals. Because a rural track program typically has its residents 
train in the urban hospital in year one, rather than in the rural 
setting, the urban hospital gets more than its fair share of the cap, 
and the rural site gets less than the actual number of FTEs training in 
that site. When apportioned this way, rural sites are disadvantaged 
compared to urban hospital sites. The commenter noted that a mechanism 
already exists for Medicare affiliated groups to aggregate caps other 
than ``rural FTE limitations,'' and stated that they ``are aware of 
multiple occasions where such aggregation has occurred between urban 
and rural hospitals, always to the disadvantage of the rural hospital 
that has, for example, been acquired by the larger urban health system. 
It seems unlikely that urban hospitals would give up ``rural FTE 
limitation'' slots to benefit a participating rural hospital's cap . . 
.'' The commenter stated that CMS has the authority to make changes to 
the calculation of rural cap limitations as section 127 of the CAA 
states that the Secretary shall ``adjust in an appropriate manner the 
limitation under subparagraph (F) for such hospital and each such 
hospital located in a rural area that participates in such a training'' 
(emphasis added). As such, beginning with cost reporting periods on or 
after October 1, 2022, CMS is not restricted to only sharing positions 
through an affiliation agreement but should set appropriate caps 
associated with these training programs for the future, rather than 
institute affiliation agreements. This commenter and another commenter 
recommended that the solution is to count the highest year, rather than 
using all five years when determining the ratio for cap apportionment.
    Response: We appreciate the concerns raised by the commenter and 
acknowledge the commenter's unique perspective on rural GME training. 
We certainly want to initiate a payment mechanism that is inherently 
equitable, and believe that a policy that we finalize should encourage, 
rather than hinder, GME training in rural areas. However, we note that 
the vast majority of commenters, including others with close ties to 
rural GME training, have submitted comments in support of our proposal, 
generally stating that this proposal will facilitate training in rural 
settings.
    With regard to the commenter's point that CMS's current methodology 
of looking at all 5 years to apportion FTE caps disadvantages the rural 
hospital in a RTP because the method gives more than the fair share of 
FTE cap to the urban hospital, we acknowledge that there might be other 
mathematical apportionment methods that, if tailor-made for RTPs, would 
result in higher caps for the rural hospital. However, we note that 
this current mathematical apportionment in the regulations at 42 CFR 
413.79(e)(1) and (3) was first implemented for all hospitals in the 
August 1, 2012 LTCH PPS/IPPS final rule (77 FR 53416 through 53424). 
Then in the August 22, 2016 LTCH PPS/IPPS final rule, we adopted this 
same cap apportionment methodology for rural track FTE limitations (81 
FR 57026 through 57031), without any objection from commenters. Thus, 
we have established a single, national policy for calculating FTE caps 
for new programs and RTPs, and we have not proposed a change to this 
national method in the proposed rule. While a ``one-size-fits-all'' 
method may not be optimal in all situations, we do not believe it is 
advisable to alter the cap calculation for RTPs at this time. With the 
advent of CAA section 127, and the expectation that RTPs will develop 
not only in 3-year family medicine programs, but also in many other 
specialties of differing lengths, it is not the right time to establish 
an RTP cap calculation method, before we even understand what the RTP 
landscape will be like over the next 5 or more years. At this point, 
allowing Medicare GME affiliation agreements between the urban and 
rural hospitals participating in the same RTP may be the better 
solution, as it would allow the hospitals to customize their individual 
caps, rather than CMS instituting yet another national cap calculation 
methodology. Furthermore, because the majority of commenters supported 
our proposal to allow Rural Track Medicare GME Affiliation Agreements, 
we believe it is fair and appropriate to finalize our policy as 
proposed. In the December 27, 2021 final rule (86 FR 73456), and as 
reiterated in the proposed rule and in response to other comments in 
this final rule, we already stated that we expect to reassess allowing 
Medicare GME affiliation agreements for RTP FTE

[[Page 49079]]

limitations established after October 1, 2022 at some point in the 
future. For these same reasons, and in conjunction with observing what 
we hope will be robust growth and development of RTPs in many 
specialties, not just family medicine, we are open to reassessing at 
the appropriate time the viability of Rural Track Medicare GME 
Affiliation Agreements for appropriate payment for urban and rural 
hospitals participating in RTPs.
    Comment: Another commenter who supported our proposal added that 
they believe CMS's concerns about hospitals taking advantage of 
affiliated agreements and comingled caps are misguided, and that 
placing this limitation on affiliated agreements within RTPs is 
inappropriate. The commenter asserted that urban and rural hospitals 
participating in any RTP program for the benefit of rural communities 
should be permitted this flexibility, as it would promote the adoption 
of the model partnerships.
    Response: As we stated in the proposed rule, when we first 
implemented the rural track regulations in the August 1, 2000 IFC, we 
specified that the caps associated with rural tracks are separate and 
distinct from a hospital's general FTE caps. Specifically, we defined 
the ``rural track FTE limitation'' at 42 CFR 413.75(b) as the maximum 
number of residents training in a rural track residency program that an 
urban hospital may include in its FTE count and that is in addition to 
the number of FTE residents already included in the hospital's FTE cap 
(emphasis added). As a result, the rural track FTE limitations are not 
part of the regular FTE caps that hospitals may aggregate in Medicare 
GME affiliation agreements. In the proposed rule, we proposed that the 
responsible representatives of each urban and rural hospital entering 
into the Rural Track Medicare GME Affiliation Agreement attest in that 
written agreement that each participating hospital's FTE counts and 
rural track FTE limitations in the agreement do not reflect FTE 
residents nor FTE caps associated with programs other than the rural 
track program. We noted this attestation is important for both the 
urban and rural hospital, as both urban and rural hospitals may have 
regular FTE caps that could be part of regular Medicare GME affiliation 
agreements (see 42 CFR 413.79(e)(1)(iv) and (v) and 413.79(f)). 
Accordingly, as long as it is possible for a hospital to have both 
regular FTE caps and rural track FTE limitations, we believe it is 
appropriate to have mechanisms in place to ensure those caps are not 
inadvertently comingled. We do not believe these mechanisms limit the 
flexibility of rural hospitals seeking to create model partnerships, as 
the commenter asserts.
    Comment: A commenter offered one minor suggestion on language used 
to describe the programs encompassed in the proposal to allow Medicare 
GME affiliation agreements within certain rural track FTE limitations. 
The commenter offered these suggestions in the interest of accurate 
references to ACGME terminology and processes. The commenter suggested 
eliminating use of the outdated term ``1-2'' when referring to 
separately accredited family medicine programs. CMS could instead 
consider phrasing such as ``separately accredited family medicine 
programs with caps in place as of October 1, 2022.''
    Response: We appreciate the commenter's suggestion, and in this 
final rule, we are finalizing our policy with respect to ``separately 
accredited family medicine programs with rural track FTE limitations in 
place as of October 1, 2022.''
    After consideration of the public comments we received, we are 
finalizing our proposal, without modification, to allow urban and rural 
hospitals that participate in the same separately accredited family 
medicine RTP and have rural track FTE limitations to enter into ``Rural 
Track Medicare GME Affiliation Agreements''.
    We are finalizing the following new definitions at 42 CFR 413.75(b) 
and requirements:
     Rural track Medicare GME affiliated group is an urban 
hospital and a rural hospital that participates in a rural track 
program defined in 42 CFR 413.75(b), and that have rural track FTE 
limitations in effect prior to October 1, 2022, and that comply with 42 
CFR 413.79(f)(1) through (6) for Medicare GME affiliated groups.
     Rural track Medicare GME affiliation agreement is a 
written, signed, and dated agreement by responsible representatives of 
each respective hospital in a rural track Medicare GME affiliated 
group, as defined in 42 CFR 413.75(b), that specifies--
    ++ A statement attesting that each participating hospital's FTE 
counts and rural track FTE limitations in the agreement do not reflect 
FTE residents nor FTE caps associated with programs other than the 
rural track program.
    ++ The term of the rural track Medicare GME affiliation agreement 
(which, at a minimum is 1 year), beginning on July 1 of a year;
    ++ Each participating hospital's direct and indirect GME rural 
track FTE limitations in effect prior to the rural track Medicare GME 
affiliation;
    ++ The total adjustment to each hospital's rural track FTE 
limitations in each year that the rural track Medicare GME affiliation 
agreement is in effect, for both direct GME and IME, that reflects a 
positive adjustment to one hospital's direct and indirect rural track 
FTE limitations that is offset by a negative adjustment to the other 
hospital's (or hospitals') direct and indirect rural track FTE 
limitations of at least the same amount;
    ++ The adjustment to each participating hospital's FTE counts 
resulting from the FTE resident's (or residents') participation in a 
shared rotational arrangement at each hospital participating in the 
rural track Medicare GME affiliated group for each year the Medicare 
GME affiliation agreement is in effect. This adjustment to each 
participating hospital's FTE count is also reflected in the total 
adjustment to each hospital's rural track FTE limitations (in 
accordance with paragraph (iii)); and
    ++ The names of the participating hospitals and their Medicare 
provider numbers.
    In addition, we are requiring that no later than July 1 of the 
residency year during which the rural track Medicare GME affiliation 
agreement will be in effect, the urban and rural hospital must submit 
the signed agreement to the CMS contractor or MAC servicing the 
hospital and send a copy to the CMS Central Office. The hospitals may 
submit amendments to the adjustments to their respective rural track 
FTE limitations to the MAC with a copy to CMS by June 30 of the 
residency year that the agreement is in effect. Eligible urban and 
rural hospitals may enter into rural track Medicare GME affiliation 
agreements effective with the July 1, 2023, academic year.
    With regard to how the rural track Medicare GME affiliation 
adjustments would be reported on the Medicare cost report, first, for 
background, we note that on the previous Medicare cost report CMS-Form-
2552-96, the rural track FTE limitation was combined, together with the 
``cap'' add-on for new (non-rural track) programs on Worksheet E, Part 
A, line 3.05, and on Worksheet E-3, Part IV, line 3.02. On the current 
cost report CMS-Form-2552-10, the rural track FTE limitation is, 
likewise, combined together with the ``cap'' add-on for new (non-rural 
track) programs on Worksheet E, Part A, line 6, and on Worksheet E-4, 
line 2. Going forward, we intend to add lines to the cost report to 
accommodate separate reporting of urban or rural hospital rural

[[Page 49080]]

track FTE limitations, and the positive or negative adjustments made to 
the rural track FTE limitations, including those applicable to the 
affiliated agreements.

G. Payment Adjustment for Certain Clinical Trial and Expanded Access 
Use Immunotherapy Cases (Sec. Sec.  412.85 and 412.312)

    Effective for FY 2021, we created MS-DRG 018 for cases that include 
procedures describing CAR T-cell therapies, which were reported using 
ICD-10-PCS procedure codes XW033C3 or XW043C3 (85 FR 58599 through 
58600). Effective for FY 2022, we revised MS-DRG 018 to include cases 
that report the procedure codes for CAR T-cell and non-CAR T-cell 
therapies and other immunotherapies (86 FR 44798 through 448106). We 
refer the reader to section II.D.17. of the preamble of this final rule 
for discussion of the agenda items for the March 8-9, 2022 ICD-10 
Coordination and Maintenance Committee meeting relating to new 
procedure codes to describe the administration of a CAR T-cell or 
another type of gene or cellular therapy product, as well as our 
established process for determining the MS-DRG assignment for codes 
approved at the March meeting.
    Effective for FY 2021, we modified our relative weight methodology 
for MS-DRG 018 in order to develop a relative weight that is reflective 
of the typical costs of providing CAR T-cell therapies relative to 
other IPPS services. Specifically, under our finalized policy we do not 
include claims determined to be clinical trial claims that group to MS-
DRG 018 when calculating the average cost for MS-DRG 018 that is used 
to calculate the relative weight for this MS-DRG, with the additional 
refinements that: (a) when the CAR T-cell therapy product is purchased 
in the usual manner, but the case involves a clinical trial of a 
different product, the claim will be included when calculating the 
average cost for MS DRG 018 to the extent such claims can be identified 
in the historical data; and (b) when there is expanded access use of 
immunotherapy, these cases will not be included when calculating the 
average cost for MS-DRG 018 to the extent such claims can be identified 
in the historical data (85 FR 58600). The term ``expanded access'' 
(sometimes called ``compassionate use'') is a potential pathway for a 
patient with an immediately life-threatening condition or serious 
disease or condition to gain access to an investigational medical 
product (drug, biologic, or medical device) for treatment outside of 
clinical trials when no comparable or satisfactory alternative therapy 
options are available.\215\
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    \215\ https://www.fda.gov/news-events/expanded-access/expanded-access-keywords-definitions-and-resources.
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    Effective FY 2021, we also finalized an adjustment to the payment 
amount for applicable clinical trial and expanded access immunotherapy 
cases that group to MS-DRG 018 using the same methodology that we used 
to adjust the case count for purposes of the relative weight 
calculations (85 FR 58842 through 58844). (As previously noted, 
effective beginning FY 2022, we revised MS-DRG 018 to include cases 
that report the procedure codes for CAR T-cell and non-CAR T-cell 
therapies and other immunotherapies (86 FR 44798 through 448106).) 
Specifically, under our finalized policy we apply a payment adjustment 
to claims that group to MS-DRG 018 and include ICD-10-CM diagnosis code 
Z00.6, with the modification that when the CAR T-cell, non-CAR T-cell, 
or other immunotherapy product is purchased in the usual manner, but 
the case involves a clinical trial of a different product, the payment 
adjustment will not be applied in calculating the payment for the case. 
We also finalized that when there is expanded access use of 
immunotherapy, the payment adjustment will be applied in calculating 
the payment for the case. This payment adjustment is codified at 42 CFR 
412.85 (for operating IPPS payments) and 42 CFR 412.312 (for capital 
IPPS payments), for claims appropriately containing Z00.6, as described 
previously, and reflects that the adjustment is also applied for cases 
involving expanded access use immunotherapy, and that the payment 
adjustment only applies to applicable clinical trial cases; that is, 
the adjustment is not applicable to cases where the CAR T-cell, non-CAR 
T-cell, or other immunotherapy product is purchased in the usual 
manner, but the case involves a clinical trial of a different product. 
The regulations at 42 CFR 412.85(c) also specify that the adjustment 
factor will reflect the average cost for cases to be assigned to MS-DRG 
018 that involve expanded access use of immunotherapy or are part of an 
applicable clinical trial to the average cost for cases to be assigned 
to MS-DRG 018 that do not involve expanded access use of immunotherapy 
and are not part of a clinical trial (85 FR 58844).
    For FY 2023, we proposed to continue to apply an adjustment to the 
payment amount for expanded access use of immunotherapy and applicable 
clinical trial cases that would group to MS-DRG 018 using the same 
methodology adopted in the FY 2021 IPPS/LTCH PPS final rule (85 FR 
58842), which is the same methodology we proposed to use to adjust the 
case count for purposes of the relative weight calculations:
     Calculate the average cost for cases to be assigned to MS-
DRG 018 that contain ICD-10-CM diagnosis code Z00.6 or contain 
standardized drug charges of less than $373,000.
     Calculate the average cost for all other cases to be 
assigned to MS-DRG 018.
     Calculate an adjustor by dividing the average cost 
calculated in step 1 by the average cost calculated in step 2.
     Apply this adjustor when calculating payments for expanded 
access use of immunotherapy and applicable clinical trial cases that 
group to MS-DRG 018 by multiplying the relative weight for MS-DRG 018 
by the adjustor.
    Additionally, we proposed to continue to use our finalized 
methodology for calculating this payment adjustment, such that: (a) 
when the CAR T-cell, non-CAR T-cell, or other immunotherapy product is 
purchased in the usual manner, but the case involves a clinical trial 
of a different product, the claim will be included when calculating the 
average cost for cases not determined to be clinical trial cases; and 
(b) when there is expanded access use of immunotherapy, these cases 
will be included when calculating the average cost for cases determined 
to be clinical trial cases. However, we continue to believe to the best 
of our knowledge there are no claims in the historical data (FY 2021 
MedPAR) used in the calculation of the adjustment for cases involving a 
clinical trial of a different product, and to the extent the historical 
data contain claims for cases involving expanded access use of 
immunotherapy we believe those claims would have drug charges less than 
$373,000. We note that we are in the process of making modifications to 
the MedPAR files to include information for claims with the payer-only 
condition code ``ZC'' in the future. Payer-only condition code ``ZC'' 
is used by the IPPS Pricer to identify a case where the CAR T-cell, 
non-CAR T-cell, or other immunotherapy product is purchased in the 
usual manner, but the case involves a clinical trial of a different 
product so that the payment adjustment is not applied in calculating 
the payment for the case (for example, see Change Request 11879, 
available at https://www.cms.gov/files/document/r10571cp.pdf).

[[Page 49081]]

    Consistent with our calculation of the proposed adjustor for the 
relative weight calculations, and our proposal to use the FY 2021 data 
for the FY 2023 ratesetting, for the proposed rule we proposed to 
calculate this adjustor based on the December 2021 update of the FY 
2021 MedPAR file for purposes of establishing the FY 2023 payment 
amount. Specifically, in accordance with 42 CFR 412.85 (for operating 
IPPS payments) and 42 CFR 412.312 (for capital IPPS payments), we 
proposed to multiply the FY 2023 relative weight for MS-DRG 018 by a 
proposed adjustor of 0.20 as part of the calculation of the payment for 
claims determined to be applicable clinical trial or expanded use 
access immunotherapy claims that group to MS-DRG 018, which includes 
CAR T-cell and non-CAR T-cell therapies and other immunotherapies. We 
also proposed to update the value of the adjustor based on more recent 
data for the final rule.
    We note that a commenter requested that CMS consider allowing 
hospitals to use expanded access condition code 90 instead of the 
remarks field, which would remove a layer of manual work required by 
the MACs, which would decrease the opportunity for errors. As discussed 
more fully in our response to this comment in section II.E.2.b. of this 
final rule, we agree with the commenter's request, and effective 
October 1, 2022, providers should submit condition code 90 to identify 
expanded access claims that group to MS-DRG 018, rather than the 
remarks field. We did not receive any comments specifically relating to 
the proposed payment adjustment for applicable clinical trial and 
expanded access use immunotherapy cases.
    After consideration of the comment we received, we are finalizing 
our proposal regarding the calculation of this payment adjustment for 
FY 2023, as described previously. We are also finalizing our proposal 
to update the value of this adjustor based on more recent data for this 
final rule. Therefore, using the March 2022 update of the FY 2021 
MedPAR data, we are finalizing an adjustor of 0.21 for FY 2023, which 
will be multiplied by the final FY 2023 relative weight for MS-DRG 018 
as part of the calculation of the payment for claims determined to be 
applicable clinical trial or expanded use access immunotherapy claims 
that group to MS-DRG 018.

H. Hospital Readmissions Reduction Program: Updates and Changes 
(Sec. Sec.  412.150 Through 412.154)

1. Statutory Basis for the Hospital Readmissions Reduction Program
    Section 1886(q) of the Act, as amended by section 15002 of the 21st 
Century Cures Act, establishes the Hospital Readmissions Reduction 
Program. Under the Hospital Readmissions Reduction Program, Medicare 
payments under the acute inpatient prospective payment system (IPPS) 
for discharges from an applicable hospital, as defined under section 
1886(d) of the Act, may be reduced to account for certain excess 
readmissions. Section 15002 of the 21st Century Cures Act requires the 
Secretary to compare hospitals with respect to the proportion of 
beneficiaries who are dually eligible for Medicare and full-benefit 
Medicaid (also known as ``dually eligible beneficiaries'') in 
determining the extent of excess readmissions. We refer readers to the 
FY 2016 IPPS/LTCH PPS final rule (80 FR 49530 through 49531) and the FY 
2018 IPPS/LTCH PPS final rule (82 FR 38221 through 38240) for a 
detailed discussion of and additional information on the statutory 
history of the Hospital Readmissions Reduction Program.
2. Regulatory Background
    We refer readers to the following final rules for detailed 
discussions of the regulatory background and descriptions of the 
current policies for the Hospital Readmissions Reduction Program:
     FY 2012 IPPS/LTCH PPS final rule (76 FR 51660 through 
51676).
     FY 2013 IPPS/LTCH PPS final rule (77 FR 53374 through 
53401).
     FY 2014 IPPS/LTCH PPS final rule (78 FR 50649 through 
50676).
     FY 2015 IPPS/LTCH PPS final rule (79 FR 50024 through 
50048).
     FY 2016 IPPS/LTCH PPS final rule (80 FR 49530 through 
49543).
     FY 2017 IPPS/LTCH PPS final rule (81 FR 56973 through 
56979).
     FY 2018 IPPS/LTCH PPS final rule (82 FR 38221 through 
38240).
     FY 2019 IPPS/LTCH PPS final rule (83 FR 41431 through 
41439).
     FY 2020 IPPS/LTCH PPS final rule (84 FR 42380 through 
42390).
     FY 2021 IPPS/LTCH PPS final rule (85 FR 58844 through 
58847.
     FY 2022 IPPS/LTCH PPS final rule (86 FR 45249 through 
45266).
    We have also codified certain requirements of the Hospital 
Readmissions Reduction Program at 42 CFR 412.152 through 412.154.
3. Current Measures
    The Hospital Readmissions Reduction Program currently includes six 
applicable conditions/procedures: Acute myocardial infarction (AMI); 
heart failure (HF); pneumonia (PN); elective primary total hip 
arthroplasty/total knee arthroplasty (THA/TKA); chronic obstructive 
pulmonary disease (COPD); and coronary artery bypass graft (CABG) 
surgery.
    We continue to believe the measures we have adopted adequately meet 
the goals of the Hospital Readmissions Reduction Program. In the FY 
2022 IPPS/LTCH PPS final rule, we finalized suppression of the CMS 30-
Day Pneumonia Readmission Measure (NQF #0506) for purposes of payment 
adjustment for the FY 2023 program year due to the impact of the COVID-
19 PHE (86 FR 45254 through 45256). In this final rule, we are 
finalizing resumption of use of this measure in the Hospital 
Readmissions Reduction Program beginning with the FY 2024 program year, 
with an exclusion of patients with principal or secondary COVID-19 
diagnoses from both the denominator (cohort) and the numerator 
(outcome). We are also providing information on technical specification 
updates for all of the condition/procedure-specific readmission 
measures in the Hospital Readmissions Reduction Program to include a 
covariate adjustment for patients with a clinical history of COVID-19 
in the 12 months prior to the index admission.
    We refer readers to the FY 2019 IPPS/LTCH PPS final rule (83 FR 
41431 through 41439) for more information about how the Hospital 
Readmissions Reduction Program supports CMS' goal of bringing quality 
measurement, transparency, and improvement together with value-based 
purchasing to the hospital inpatient care setting through the 
Meaningful Measures Framework.
4. Flexibility for Changes That Affect Quality Measures During a 
Performance Period in the Hospital Readmissions Reduction Program
    In the FY 2022 IPPS/LTCH PPS final rule, we adopted a policy for 
the duration of the COVID-19 PHE that has allowed us to suppress the 
use of quality measures via adjustment to the Hospital Readmissions 
Reduction Program's program calculations if we determine that 
circumstances caused by the COVID-19 PHE significantly affected those 
measures and the associated ``excess readmissions'' calculations (86 FR 
45250 through 45253). As described under that finalized policy, if we 
were to determine

[[Page 49082]]

that the suppression of a Hospital Readmissions Reduction Program 
measure was warranted for an applicable period, we would calculate the 
measure's rates for that program year but then suppress the use of 
those rates to make changes to hospitals' Medicare payments. In the 
Hospital Readmissions Reduction Program, this policy would have the 
effect of temporarily weighting the affected measure at zero percent in 
the program's scoring methodology until adjustments were made, the 
affected portion of the performance period for the measure was made no 
longer applicable to program calculations, or the measure was removed 
entirely through rulemaking. We also explained that we would provide 
feedback reports to hospitals as part of program activities, including 
to inform their quality improvement activities, and to ensure that they 
were made aware of the changes in performance rates that we observed 
(86 FR 45251). We stated that we would publicly report a suppressed 
measure's data with appropriate caveats noting the limitations of the 
data due to the COVID-19 PHE (86 FR 45251). To provide stakeholders an 
opportunity to review this final rule prior to release of the Hospital 
Specific Reports (HSRs) that incorporate updates to the CMS 30-Day 
Pneumonia Readmission Measure (NQF #0506), we are postponing 
incorporation of the CMS 30-Day Pneumonia Readmission Measure (NQF 
#0506), which would typically be included in the July update of the 
Compare website hosted by HHS (https://www.medicare.gov/care-compare/).
    In the FY 2022 IPPS/LTCH PPS final rule, we also adopted Measure 
Suppression Factors to guide our determination of whether to suppress a 
Hospital Readmissions Reduction Program measure for one or more program 
years that include discharges during the COVID-19 PHE (86 FR 45251). We 
adopted these Measure Suppression Factors for use in the Hospital 
Readmissions Reduction Program, and for consistency, the following 
other value-based purchasing programs: Hospital Value-Based Purchasing, 
HAC Reduction Program, Skilled Nursing Facility Value-Based Purchasing 
Program, and End-Stage Renal Disease Quality Incentive Program. We 
stated our belief that these Measure Suppression Factors will help us 
evaluate the Hospital Readmissions Reduction Program's measures and 
that their adoption in the other value-based purchasing programs, as 
previously noted, would help ensure consistency in our measure 
evaluations across programs. The previously adopted Measure Suppression 
Factors are as follows:
     Significant deviation in national performance on the 
measure during the PHE for COVID-19, which could be significantly 
better or significantly worse compared to historical performance during 
the immediately preceding program years.
     Clinical proximity of the measure's focus to the relevant 
disease, pathogen, or health impacts of the PHE for COVID-19.
     Rapid or unprecedented changes in--
    ++ Clinical guidelines, care delivery or practice, treatments, 
drugs, or related protocols, or equipment or diagnostic tools or 
materials; or
    ++ The generally accepted scientific understanding of the nature or 
biological pathway of the disease or pathogen, particularly for a novel 
disease or pathogen of unknown origin.
     Significant national shortages or rapid or unprecedented 
changes in--
    ++ Healthcare personnel;
    ++ Medical supplies, equipment, or diagnostic tools or materials; 
or
    ++ Patient case volumes or facility-level case mix.
    We stated our belief that we view this measure suppression policy 
as necessary to ensure that the Hospital Readmissions Reduction Program 
did not penalize hospitals based on factors that the program's measures 
were not designed to accommodate (86 FR 45252).
    In the FY 2023 IPPS/LTCH PPS proposed rule, we did not propose any 
changes to this policy. We did not receive any comments on our 
previously finalized flexibilities in response to the COVID-19 PHE or 
our previously finalized Measure Suppression Factors.
5. Provisions That Address the Impact of COVID-19 on Current Hospital 
Readmissions Reduction Program Measures
a. Background
    As described in V.H.4 of the preamble of this final rule, in the FY 
2022 IPPS/LTCH PPS final rule, we adopted a measure suppression policy 
and Measure Suppression Factors to ensure that the Hospital 
Readmissions Reduction Program did not penalize hospitals based on 
factors that the program's measures were not designed to accommodate 
(86 FR 45252).
    Additionally, in the FY 2022 IPPS/LTCH PPS final rule, we finalized 
suppression of the CMS 30-Day Pneumonia Readmissions Measure (NQF 
#0506) for the FY 2023 program year (86 FR 45254 through 45256). We 
expressed the belief that the second Measure Suppression Factor 
(clinical proximity of the measure's focus to the relevant disease, 
pathogen, or health impacts of the COVID-19 PHE) applied to the CMS 30-
Day Pneumonia Readmissions Measure (NQF #0506). In our analysis of the 
impacts of the COVID-19 PHE on the measures in the Hospital 
Readmissions Reduction Program, we observed that pneumonia has been 
identified as a typical characteristic of individuals infected with 
COVID-19 (86 FR 45254). Using data available during and subsequent to 
the preparation of the FY 2022 IPPS/LTCH PPS final rule, we found that 
a substantial portion of the CMS 30-Day Pneumonia Readmissions Measure 
(NQF #0506) denominator (cohort) included admissions with a COVID-19 
diagnosis, ranging from 13.3 percent in April 2020 to a high of 27.1 
percent in December 2020.\216\ Furthermore, we noted that at the 
beginning of the pandemic, the 30-day observed readmission rate for 
pneumonia patients with a secondary diagnosis of COVID-19 present on 
admission was lower than the observed readmissions rate for pneumonia 
patients without a diagnosis of COVID-19 (12.4 percent versus 15.8 
percent) because patients with a secondary diagnosis of COVID-19 
present on admission had a higher risk of mortality than patients 
without a COVID-19 diagnosis (86 FR 45254 through 45255).
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    \216\ While data prior to April 1, 2020 are available, these 
data used a different method to identify COVID-19 diagnoses. To 
improve consistency of analysis we began our analysis on April 1, 
2020 with the introduction of the COVID-19 ICD-10 codes.
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    Additionally, we provided information on technical specification 
updates for the remaining five condition/procedure-specific readmission 
measures to exclude patients with a principal or secondary COVID-19 
diagnosis present on admission from the measures' numerators (outcomes) 
and denominators (cohorts) beginning in fiscal year (FY) 2023 (86 FR 
45256 through 45258). In the FY 2015 IPPS/LTCH PPS final rule, we 
finalized a subregulatory process to incorporate technical measure 
specification updates into the measure specifications adopted for the 
Hospital Readmissions Reduction Program (79 FR 50039). In the FY 2022 
IPPS/LTCH PPS final rule, we noted that to continue to account for 
readmissions as intended, we would use our subregulatory process to 
update the specifications to exclude patients with a principal or 
secondary diagnosis of

[[Page 49083]]

COVID-19 present on admission from the denominators (cohorts) and the 
numerators (outcomes) of the following five condition/procedure-
specific readmission measures: (1) Hospital 30-Day All-Cause RSRR 
Following AMI Hospitalization (NQF #0505); (2) the Hospital 30-Day, 
All-Cause, Unplanned, RSRR Following CABG Surgery (NQF #2515); (3) the 
Hospital 30-Day, All-Cause, RSRR Following COPD Hospitalization (NQF 
#1891); (4) the Hospital 30-Day, All-Cause RSRR Following Heart Failure 
Hospitalization (NQF #0330); and (5) the Hospital-Level 30-Day, RSRR 
Following Elective Primary Total Hip Arthroplasty (THA) and/or Total 
Knee Arthroplasty (TKA) (NQF #1551) beginning in FY 2023 (86 FR 45256).
    In the FY 2023 IPPS/LTCH PPS proposed rule, we did not propose any 
changes to these policies.
b. Resumption of the CMS 30-Day Pneumonia Readmission Measure (NQF 
#0506) for the FY 2024 Program Year
    Our measure suppression policy, described in section V.H.4 of the 
preamble of this final rule, focuses on a short-term, equitable 
approach during this unprecedented PHE, and was not intended for 
indefinite application. While we recognize that performance on some 
measures may not immediately return to levels seen prior to the PHE, we 
want to emphasize the long-term importance of value-based care and 
incentivizing quality care by linking provider performance to program 
payment. The Hospital Readmissions Reduction Program is an example of 
our long-standing effort to link payments to healthcare quality in the 
inpatient hospital setting as well as cross-continuum care. Our goal 
has been to resume the use of measure data for scoring and payment 
adjustment purposes. We note that in the FY 2022 IPPS/LTCH PPS final 
rule, we finalized the suppression of the CMS 30-Day Pneumonia 
Readmission Measure (NQF #0506) for the FY 2023 Program Year and stated 
that we would continue to monitor the claims that form the basis for 
this measure's calculations to evaluate the effect of the circumstances 
on quality measurement and to determine the appropriate policies for 
the future. Additionally, we recognized that it is important to 
continue tracking the impact of the COVID-19 PHE on the CMS 30-Day 
Pneumonia Readmission Measure (NQF #0506), as these data will inform 
our considerations regarding whether future measure suppression is 
necessary beyond FY 2023. We noted that the measure is important to 
improving patient safety and quality of care and stated that we would 
continue to monitor measure data to determine when it may be considered 
sufficiently reliable such that resuming full implementation of the CMS 
30-Day Pneumonia Readmission Measure (NQF #0506) is appropriate (86 FR 
45256).
    Following publication of the FY 2022 IPPS/LTCH PPS final rule, we 
have continued to monitor the claims that form the basis for this 
measure's calculations. While pneumonia continues to be a typical 
characteristic of individuals infected with COVID-19, we believe that 
coding practices enhanced by the availability of COVID-19-related ICD-
10-CM and ICD-10-PCS codes, effective since January 1, 2021, have 
enabled us to differentiate patients with COVID-19 from pneumonia 
patients without COVID-19 within certain data periods.
    In this final rule, we are finalizing that beginning in FY 2024, 
the Pneumonia Readmission Measure (NQF #0506) will no longer be 
suppressed under the Hospital Readmissions Reduction Program. We will 
resume the use of the pneumonia readmission measure for FY 2024 because 
of the following differences between the FY 2023 and FY 2024 
performance periods: (1) the improved coding practices; (2) decreased 
proportion of COVID-19 admissions in the pneumonia readmission measure 
for this performance period; and (3) sufficient available data to make 
technical updates to the measure specifications in order to further 
account for how patients with a COVID-19 diagnosis might impact the 
quality of care assessed by this measure. These differences lead us to 
believe that the clinical proximity of the measure's focus is no longer 
sufficiently close to the health impacts of the COVID-19 PHE for the 
suppression factor to continue to apply. Specifically, effective 
January 2021, the ICD-10 code J12.82, pneumonia due to coronavirus 
disease 2019, was added for use as a secondary diagnosis present on 
admission, along with a principal diagnosis of COVID-19 (U07.1) present 
on admission, to identify patients with COVID-19 pneumonia. J12.82 is 
not included within the denominator (cohort) of the pneumonia 
readmission measure, therefore readmission rates for patients with an 
index admission of COVID-19 pneumonia (J12.82) are not captured by this 
measure as of January 1, 2021. Whenever new codes are introduced, 
changes in coding practices are difficult to predict. At the time of 
the FY 2022 IPPS final rule, we did not have sufficient data to 
determine the effects of these coding changes on the proportion of 
COVID-19 patients and readmission rates with pneumonia due to COVID-19 
in the pneumonia readmission measure. As additional months of data have 
become available since early 2021, we have now seen increased use of 
these codes. Secondly, as these coding changes have occurred and as the 
COVID-19 PHE has evolved, more recent data show the proportion of 
COVID-19 admissions in the pneumonia readmission measure have decreased 
compared to 2020 data. Finally, with the availability of additional 
data and the decrease in the proportion of COVID-19 admissions in the 
pneumonia readmission measure, we are now able to make technical 
updates to the measure specifications in alignment with the technical 
updates to the five other readmission measures. All of these factors 
have led us to conclude that the suppression factor no longer applies 
to the CMS 30-Day Pneumonia Readmissions Measure (NQF #0506) measure.
    As previously discussed, we observed that in 2020, following the 
declaration of the COVID-19 PHE for COVID-19 a substantial proportion 
of the CMS 30-Day Pneumonia Readmissions Measure (NQF #0506) 
denominator (cohort) included admissions with a COVID-19 diagnosis 
present on admission. Specifically, the proportion ranged from 13.3 
percent when the COVID-19 ICD-10 diagnosis code became available in 
April 2020 to a high of 27.1 percent in December 2020. After the J12.82 
code was implemented in January 2021, the proportion of patients with 
COVID-19 diagnosis present on admission in the pneumonia measure 
dropped to 9.8 percent. Data on the proportion of patients with COVID-
19 diagnosis present on admission from April 2020 through December 2020 
are detailed in Table V.H.-01. The most recently available data at the 
time of the proposed rule on the proportion of patients with COVID-19 
diagnosis present on admission for January through September 2021, 
which do not include patients with pneumonia due to coronavirus disease 
2019 per ICD-10 code J12.82, are detailed in Table V.H-02.

[[Page 49084]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.132

[GRAPHIC] [TIFF OMITTED] TR10AU22.133

    We note that the surge of COVID-19-related hospitalizations had 
begun to subside with the rollout of the U.S. vaccination program in 
early 2021, although hospitalizations began increasing again during 
late summer 2021 with the COVID-19 Delta variant and increased over the 
fall and winter with the COVID-19 Omicron variant. We also note that 
updated data show that the proportion of admissions with a COVID-19 
diagnosis present on admission for the CMS 30-Day Pneumonia Readmission 
Measure (NQF #0506) between April 2020 and December 2020 was 13.1 
percent, whereas the proportion between January 2021 and September 2021 
was substantially lower, at 3.1 percent.
    Analyzing data available for the FY 2022 IPPS/LTCH PPS final rule 
(April 2020 through June 2020), we noted that the 30-day observed 
readmissions rate for patients with a secondary diagnosis of COVID-19 
present on admission at the index admission were lower than the 
observed readmissions rates for patients without a diagnosis of COVID-
19 (12.4 percent versus 15.8 percent). In more recent data, we have 
found that the observed readmission rate for admissions with a COVID-19 
diagnosis present on admission were similar to observed readmission 
rates for admissions without a COVID-19 diagnosis (17.3 percent vs. 
17.2 percent, respectively) as depicted in Table V.H.-03.
[GRAPHIC] [TIFF OMITTED] TR10AU22.134

    Because updated data show that following the January 2021 coding 
update patients with a diagnosis of COVID-19 now make up a smaller 
proportion of the population of pneumonia admissions than in the 
analysis described in the FY 2022 IPPS/LTCH PPS final rule, and because 
observed 30-day readmission rates are

[[Page 49085]]

similar between admissions for patients with a COVID-19 diagnosis 
present on admission and patients without a COVID-19 diagnosis present 
on admission, we believe that resuming the CMS 30-Day Pneumonia 
Readmission Measure (NQF #0506) with a modification to exclude patients 
with a primary or secondary diagnosis of COVID-19 present on admission 
beginning with the FY 2024 program year would be appropriate. As 
described in more detail in section V.H.5.c of the preamble of this 
final rule, we will also add a covariate to adjust for history of 
COVID-19 diagnosis in the 12 months prior to the index admission as a 
technical update to the measure specifications.
    In our analysis, measure scores calculated with the numerator 
(outcome) and denominator (cohort) exclusions and addition of the 
covariate for history of COVID-19 diagnosis in the 12 months prior 
resulted in mean measure scores that were closer to the prior non-
COVID-19 affected period compared with the unchanged measure. We note 
that these measure-specific modifications are in addition to 
application of the nationwide ECE granted in response to the COVID-19 
PHE, which precludes the use of data from January 1, 2020 through June 
30, 2020 from measure score calculations. Because these updates are to 
minimize the effect of COVID-19 on the pneumonia measure, which was not 
developed to account for COVID-19 diagnosed patients, we believe that 
these changes do not fundamentally change the measure such that it is 
no longer the same measure that we originally adopted, and therefore we 
believe that these are non-substantive updates. We note that in the FY 
2015 IPPS/LTCH PPS final rule, we finalized a subregulatory process to 
incorporate technical measure specification updates into the measure 
specifications we have adopted for the Hospital Readmissions Reduction 
Program (79 FR 50039). We reiterated this policy in the FY 2020 IPPS/
LTCH PPS final rule, stating our continued belief that the 
subregulatory process is the most expeditious manner possible to ensure 
that quality measures remain fully up to date while preserving the 
public's ability to comment on updates that so fundamentally change a 
measure that it is no longer the same measure that we originally 
adopted (84 FR 42385). We believe that excluding COVID-19 patients from 
the measure denominator (cohort) and numerator (outcome) and adding a 
covariate to adjust for history of a COVID-19 diagnosis in the 12 
months prior to an admission (discussed in section V.H.5.c. of the 
preamble of this final rule), will ensure that this condition-specific 
readmission measure continues to account for readmissions as intended 
and meets the goals of incentivizing patient safety and better care 
coordination of the Hospital Readmissions Reduction Program. We note 
that the readmission measure uses three years of data. The performance 
period for the FY 2023 program year includes admissions from July 1, 
2018 through June 30, 2021, with data from January 1, 2020 through June 
30, 2020 excluded due to the implementation of the nationwide ECE 
waiver. Therefore, we continue to believe it is appropriate to suppress 
the currently implemented measure for use in payment reduction 
calculations \217\ for FY 2023 as finalized in the FY 2022 IPPS/LTCH 
PPS final rule.
---------------------------------------------------------------------------

    \217\ We note that in the FY 2023 IPPS/LTCH PPS proposed rule 
(87 FR 28421) this referred to ``payment calculations,'' for 
accuracy we have revised that here to read ``payment reduction 
calculations'' as payments are not calculated by the Hospital 
Readmissions Reduction Program.
---------------------------------------------------------------------------

    Additional resources about the current measure technical 
specifications and methodology for the hospital technical specification 
of the current readmission measures are provided at our website in the 
Measure Methodology Reports (posted on the QualityNet website at 
https://qualitynet.cms.gov/inpatient/measures/readmission/methodology). 
Hospital Readmissions Reduction Program resources are located at the 
Resources web page of the QualityNet website (available at https://qualitynet.cms.gov/inpatient/hrrp/resources).
    We welcomed public comment on our proposal to resume use of the CMS 
30-Day Pneumonia Readmissions Measure (NQF #0506) beginning with the FY 
2024 program year. The comments we received, and our responses are set 
forth in this section of this rule.
    Comment: Several commenters supported suppressing the CMS 30-Day 
Pneumonia Readmission Measure (NQF #0506) from the Hospital 
Readmissions Reduction Program for the FY 2023 program year.
    Response: We thank these commenters for their support.
    Comment: A few commenters recommended that in addition to 
suppressing the CMS 30-Day Pneumonia Readmission Measure (NQF #0506) 
data from payment adjustments for FY 2023, CMS should also suppress 
these data from public reporting to avoid presenting information that 
could potentially confuse consumers regarding the quality of care. Some 
of these commenters noted their continued support for hospital-specific 
confidential reporting. A commenter recommended that CMS calculate 
measure information both with and without the exclusion for patients 
with a diagnosis of COVID-19 present on admission and provide the 
measure results from both calculations in hospital-specific reports.
    Response: We understand the commenters' concern about publicly 
reporting measure data from the COVID-19 PHE. However, we will make 
clear in the public presentation of the data that the measure has been 
suppressed for FY 2023 for purposes of payment adjustments because of 
the effects of the COVID-19 PHE. We believe that displaying this 
information will promote transparency on the impacts of the PHE due to 
COVID-19, and we will appropriately caveat the data in order to 
mitigate public confusion. Additionally, the Hospital Readmissions 
Reduction Program Hospital-Specific Report that is sent to hospitals 
provides discharge-level data for each condition/procedure. The 
discharge-level data shows whether, and why, a stay was excluded from 
the numerator (outcome) or denominator (cohort), including stays that 
are excluded due to a qualifying COVID-19 diagnosis.
    Comment: Some commenters recommended that CMS continue reporting 
all measure results, regardless of whether the measure was being 
included in program calculations because these commenters believe this 
supports transparency and accountability. Some of these commenters 
specifically recommended public and confidential reporting.
    Response: We agree with commenters that public reporting of measure 
results, regardless of whether the measure results were used for 
payment adjustments, supports transparency and accountability. 
Therefore, we will continue to report all data with appropriate caveats 
for the measure results impacted by the COVID-19 PHE. We will also 
continue to confidentially report these data to hospitals prior to 
publicly reporting in accordance with our review and correction process 
detailed in the FY 2013 IPPS/LTCH PPS final rule (77 FR 53399 through 
53401).
    Comment: Several commenters recommended suppressing the Hospital-
Level 30-Day, RSRR Following Elective Primary Total Hip Arthroplasty 
(THA) and/or Total Knee Arthroplasty (TKA) (NQF #1551) measure from 
payment calculations due to the higher complexity, higher acuity 
patient population undergoing these procedures

[[Page 49086]]

on an inpatient basis during the COVID-19 PHE.
    Response: We acknowledge that the COVID-19 PHE has impacted the 
healthcare system in unprecedented ways. However, our analyses of 
available data to date have found only minimal impacts of COVID-19 on 
the Hospital-Level 30-Day RSRR Following Elective Primary THA/TKA (NQF 
#1551) measure results. Furthermore, we believe that the COVID-19 
exclusions we have adopted combined with the covariate adjustment for 
patient history of COVID-19 within 12 months prior to admission 
described in Section V.H.5.c of this final rule account for the impacts 
of COVID-19 diagnosed patients. Our analyses have shown that for the FY 
2023 program year (that is July 1, 2018 through June 30, 2021 with 
January 1, 2020 through June 30, 2020 data excluded as a result of 
implementing the nationwide ECE due to the COVID-19 PHE) reporting 
results using the updated measure generate very similar measure score 
distributions compared with FY 2022 program year (that is July 1, 2017 
through December 1, 2019) reporting results of the original measure. 
Additionally, we note that the existing clinical risk adjustments for 
this measure (available in the Measures Methodology Report at https://qualitynet.cms.gov/inpatient/measures/readmission/methodology) are 
designed to account for the complexity and acuity of the patient 
population. Finally, we believe that hospitals which perform fewer of 
these procedures due to the shift to outpatient settings may no longer 
meet the 25-case threshold for inclusion of the measure in the Hospital 
Readmissions Reduction Program. We will, however, continue to monitor 
the volume of index admissions for the conditions and procedures that 
the Hospital Readmissions Reduction Program measures address to ensure 
that the measures remain appropriate.
    Comment: Many commenters supported resuming use of the CMS 30-Day 
Pneumonia Readmission Measure (NQF #0506) in the Hospital Readmissions 
Reduction Program. Some of these commenters observed that publishing 
hospital quality data allows trending over time and that public 
information is vital for consumers.
    Response: We thank commenters for their support.
    Comment: Several commenters who supported resuming use of the CMS 
30-Day Pneumonia Readmission Measure (NQF #0506) recommended monitoring 
to evaluate additional effects of COVID-19 on providers and patients. 
One of these commenters stated that there may be significant changes in 
Hospital Readmissions Reduction Program penalties for individual 
providers because of the effects of COVID-19.
    Response: We agree with commenters that we should monitor the 
COVID-19 PHE's ongoing effects carefully and we will work with measure 
developers to refine measure specifications as circumstances warrant. 
We will also assess performance periods, performance, and other effects 
of the COVID-19 PHE carefully, and we will monitor the policy's effects 
as we implement it.
    Comment: Many commenters recommended postponing resumption of the 
CMS-30 Day Pneumonia Readmission Measure (NQF #0506). Some of these 
commenters suggested postponing finalization of our proposal to resume 
use of the pneumonia readmission measure until the FY 2024 IPPS/LTCH 
PPS rule to provide at least a full year of use of the new ICD-10 
codes. A few commenters recommended postponing resumption until the 
performance period does not include time prior to the adoption of the 
new ICD-10 codes, specifically until the performance period does not 
include any dates prior to January 1, 2021. Other commenters 
recommended postponing resumption until the COVID-19 PHE has ended 
because many patients have delayed care, resulting in higher acuity 
when they received care, which affects the case mix.
    Response: We recognize that the COVID-19 PHE continues to affect 
communities and healthcare systems and understand commenters' concerns 
that data used in the analysis for the proposed rule may not be 
representative of the prevalence of COVID-19 and associated changes to 
admissions patterns after September 2021. However, we believe that the 
CMS 30-Day Pneumonia Readmission Measure (NQF #0506) is an important 
aspect of our goal to improve patient safety and quality of care and 
wish to resume the use of this measure in the Hospital Readmissions 
Reduction Program at the earliest point that allows for a valid and 
comparable measure. Based on our analysis of data from the start of the 
PHE through September 2021, we believe that the measure will be valid 
and comparable beginning with the FY 2024 program year.
    More recent data through March 2022 show that across all Hospital 
Readmissions Reduction Program measures, less than 3 percent of the 
cohorts have a COVID-19 diagnosis. Commenters are correct that the FY 
2024 program year does include six months after the declaration of the 
PHE for COVID-19 prior to the adoption of the new ICD-10 codes for 
COVID-19 (specifically July 1, 2020 through December 31, 2020). 
However, in our analysis, measure scores calculated based on data which 
include this period using the numerator (outcome) and denominator 
(cohort) exclusions and addition of the covariate for history of COVID-
19 diagnosis in the 12 months prior to the index admission resulted in 
mean measure scores that were closer to the prior non-COVID-19 affected 
period compared with the unchanged measure. Therefore, we believe that 
the measure is sufficiently valid and comparable to resume use in the 
FY 2024 program year, despite the six months of data not affected by 
updated coding practices. Additionally, we note that the existing 
clinical risk adjustments for this measure (available in the Measures 
Methodology Report at https://qualitynet.cms.gov/inpatient/measures/readmission/methodology) are designed to account for the complexity and 
acuity of the patient population. Because it is our goal to make 
hospitals aware of our intent to resume use of the measure as early as 
feasible, we do not believe it would be appropriate to wait until the 
FY 2024 IPPS/LTCH PPS final rule to finalize resumption of this 
measure.
    After consideration of the public comments we received, we are 
finalizing our proposal to resume use of the CMS 30-Day Pneumonia 
Readmission Measure (NQF #0506) for payment adjustments beginning with 
the FY 2024 program year.
c. Technical Measure Specification Update To Include a Covariate 
Adjustment for COVID-19 Beginning with FY 2023
    As discussed in section V.H.5.b of the preamble of this final rule, 
we have previously finalized a subregulatory process to incorporate 
technical measure specification updates into the measure specifications 
we have adopted for the Hospital Readmissions Reduction Program (79 FR 
50039) and reiterated this policy in the FY 2020 IPPS/LTCH PPS final 
rule (84 FR 42385) and the FY 2022 IPPS/LTCH PPS final rule (86 FR 
45256). As we continue to evaluate the effects of the COVID-19 PHE on 
our programs, and the effects of COVID-19 on our measures, we have 
observed that for some patients COVID-19 continues to have lasting 
effects, including fatigue, cough, palpitations, and others potentially 
related to organ damage, post-viral syndrome, post-critical care 
syndrome or other reasons.\218\ These clinical conditions

[[Page 49087]]

could affect a patient's risk factors for being readmitted following an 
index admission for any of the six conditions/procedures included in 
the Hospital Readmissions Reduction Program. Therefore, we are 
modifying the technical measure specifications of each of our six 
condition/procedure specific risk-standardized readmission measures to 
include a covariate adjustment for patient history of COVID-19 in the 
12 months prior to the admission beginning with the FY 2023 program 
year. This inclusion of the covariate adjustment for patient history of 
COVID-19 in the 12 months prior to the admission will be effective 
beginning with the FY 2023 program year and for subsequent years for 
the five non-pneumonia condition- and procedure-specific readmission 
measures. As described in V.H.5.b, the pneumonia readmission measure 
remains suppressed from scoring and payment adjustments for the FY 2023 
program year and will be resumed for the FY 2024 program year. However, 
this update will be reflected in the confidential and public reporting 
of the pneumonia readmission measure for FY 2023.\219\ For more 
information on the application of covariate adjustments, please see the 
Measure Methodology Reports (posted on the QualityNet website at 
https://qualitynet.cms.gov/inpatient/measures/readmission/methodology).
---------------------------------------------------------------------------

    \218\ Raveendran, A.V., Jayadevan, R. and Sashidharan, S., Long 
COVID: An overview. Available at https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8056514/. Accessed on December 15, 2021.
    \219\ We note that the pneumonia readmission measure would 
typically be included in the July update of the Compare website. 
However, to provide stakeholders an opportunity to provide comment 
on these updates, we are postponing incorporation of the pneumonia 
readmission measure to the January 2023 refresh of the Compare 
website. (In the proposed rule we stated that the pneumonia measure 
would be included in the October refresh, however we are correcting 
that here to the January 2023 refresh).
---------------------------------------------------------------------------

    Although we did not solicit comments on the technical measure 
specification updates to apply a covariate adjustment for patients with 
a history of COVID-19 in the 12 months prior to the index 
hospitalization, we received several comments and have summarized them 
here. We have also included the comments on our technical measure 
specification update to exclude COVID-19 patients from the measure 
denominator (cohort) and numerator (outcome) for the CMS 30-Day 
Pneumonia Readmission Measure (NQF #0506) here.
    Comment: Many commenters supported both the technical update to 
adopt a covariate adjustment for patients who have had COVID-19 in the 
12 months prior to the index admission for each of the six condition/
procedure specific readmission measures in the Hospital Readmissions 
Reduction Program and the technical update to exclude patients with a 
COVID-19 diagnosis present on admission from the numerator (outcome) 
and denominator (cohort) of the pneumonia readmission measure.
    Response: We thank these commenters for their support.
    Comment: Many commenters expressed concern that many patients with 
a history of COVID-19 would not be captured in ICD-10-CM codes, 
specifically mentioning the possibility of these patients being 
diagnosed through at-home or pharmacy-based tests and then receiving 
care in visits billed with other codes for resulting conditions. These 
commenters noted that a covariate adjustment based on data that are 
inconsistently captured could impact the reliability and validity of 
the measure results and therefore the fairness of the program. Some of 
these commenters recommended review by a Technical Expert Panel (TEP) 
convened by the NQF to ensure that COVID-19 adjustments are 
sufficiently comprehensive and include all appropriate codes. Some 
commenters recommended further data analysis to ensure appropriate data 
sources are available for this adjustment.
    Response: We understand the commenters' concerns regarding the 
prevalence of at-home or pharmacy-based testing for COVID-19 and the 
potential effects on the validity of the covariate adjustment. The 
history of COVID-19 variable \220\ is defined as U07.1 (COVID-19) or 
Z86.16 (personal history of COVID-19) in the 12 months prior to the 
admission, or Z86.16 at the index admission. Therefore, the history of 
COVID-19 variable does not rely solely on the COVID-10 specific ICD-10 
code, U07.1, but also includes the ``personal history of COVID-19'' 
code (Z86.16) which hospitals can code, even during the index 
encounter. However, we will consider these concerns and recommendations 
as we continue to evaluate and update our measure specifications, 
especially with respect to the ongoing changes to the COVID-19 PHE. We 
thank commenters for their suggestion of having a special NQF convened 
TEP review the covariate adjustment methodology to ensure that the 
adjustments are comprehensive enough to capture the long-term impacts 
of COVID-19. Any permanent changes to the measure will be submitted for 
NQF review during the endorsement maintenance process.
---------------------------------------------------------------------------

    \220\ The history of COVID-19 variable is used as part of our 
risk adjustment model which accounts for risk factors such as 
beneficiary age and other clinical risk factors. This variable has 
been added as a clinical risk factor due to effects of patient 
history of COVID-19 on readmission risk.
---------------------------------------------------------------------------

    Comment: Many commenters observed that the extended effects of 
COVID-19 on patients are still not known. These commenters recommended 
continued monitoring to ensure that the 12-month period is appropriate 
for the covariate adjustment. A commenter recommended adopting a 24-
month period as opposed to a 12-month period. A commenter expressed 
that the effects of the pandemic changing over time may decrease the 
ability to identify appropriate adjustments, including both the 
covariate adjustment for patients with a history of COVID-19 in the 12 
months prior to index admission and the update to the CMS 30-Day 
Pneumonia Readmission Measure to exclude patients who have a diagnosis 
of COVID-19 present at admission from the numerator (outcome) and 
denominator (cohort). A commenter observed that COVID-19 will likely 
become an endemic disease. A commenter recommended analyzing cohort-
specific risk adjustment and analyses for the COVID-19 patient 
population due to differences in utilization, infection risk, and 
readmission risk among these patients.
    Response: We thank these commenters for the recommendations. We 
agree that the extended effects of COVID-19 on patients are still not 
known. We will consider these recommendations as we continue to 
evaluate and update our measure specifications, especially with respect 
to the ongoing changes to the COVID-19 PHE. We note, however, that 
hospitals can use the ``personal history of COVID'' code (Z86.16) on 
the index admission which is not affected by a look-back period. We 
also note that patients who are admitted with a diagnosis of COVID-19 
present on admission are excluded from all measures within the Hospital 
Readmissions Reduction Program. We will continue to monitor and analyze 
the appropriateness of this exclusion using available data.
    Comment: A commenter observed that the measure methodology reports 
published on CMS's website in May 2022 demonstrate that history of 
COVID-19 is negatively correlated to readmissions (that is, patients 
with history of COVID-19 are less likely to be readmitted) for four out 
of the of five conditions analyzed and recommended to only include the 
covariate adjustment for conditions where patient history of COVID-19 
is a positive risk variable

[[Page 49088]]

(that is, patients with history of COVID-19 are more likely to be 
readmitted) for the performance period.
    Response: We thank the commenter for this input. Analyses using 
data from July 1, 2020 through February 28, 2021 showed that for most 
of the readmissions measures, observed (unadjusted) 30-day readmission 
rates for patients without an index admission of COVID-19, but with a 
history of COVID-19 (defined as U07.1 or Z86.16 in the 12 months prior 
to the admission, or Z86.16 at the index admission), were higher than 
patients without a history of COVID-19. Based on the higher odds of 
readmission for these patients, we decided to add the covariate across 
all of the readmission measures in the Hospital Readmissions Reduction 
Program. We are now providing updated information.
    Results using more recent data spanning the entire 3-year reporting 
period (July 1, 2018 through June 30, 2021) showed that for patients 
without an index admission of COVID-19, those with a history of COVID-
19 (defined in the previous paragraph) in the pneumonia and heart 
failure cohorts have much higher frequencies of some model risk 
variables compared with patients without a history of COVID-19, 
suggesting they are sicker. At the same time, in a multivariable model, 
we found, as the commenter notes, that unlike the bivariate 
relationship, the adjusted odds ratios for 30-day readmission for the 
history of COVID-19 variable (the odds ratios in the context of all the 
variables in the model) were less than one (for all but the Hospital 
30-day RSSR following COPD hospitalization measure--NQF #1891). 
Therefore, in these patients without COVID-19 at the time of admission, 
but with a history of COVID-19, the non-COVID-19 clinical comorbidities 
in the risk model are lessening or reversing the effect size of the 
history of COVID-19 variable. We have decided, however, to keep the 
history of COVID covariate in the model for reasons of face validity 
and to account for any future risk adjustment for long COVID that may 
not be accounted for in the measures' baseline risk models. However, we 
will consider this recommendation as we continue to evaluate and update 
our measure specifications
    Comment: A commenter opposed updates to measure specifications 
(that is, inclusion of a covariate adjustment to account for patient 
history of COVID-19 in the 12 months prior to the index admission and 
excluding patients with a diagnosis of COVID-19 present on admission 
from the pneumonia readmission measure) because these patients are 
vulnerable. This commenter stated that hospitals should be incentivized 
to care for this patient population.
    Response: We agree with the commenter that it is important that 
these patients receive high quality care when hospitalized. However, we 
note that the measures in the Hospital Readmissions Reduction Program 
were developed and adopted to identify excess readmissions for patients 
hospitalized for specific conditions or procedures. Because COVID-19 
did not exist when these measures were developed, the measures are 
neither intended nor specified to address the clinical needs of 
patients with a history of COVID-19. We will continue to assess 
specifications of the measures in the Hospital Readmissions Reduction 
Program to identify whether further updates to account for care 
provided to COVID-19 patients are appropriate.
    Comment: A commenter requested clarification regarding whether the 
updates to the measure specifications, specifically inclusion of a 
covariate adjustment for patients who have had COVID-19 in the 12 
months prior to the index admission for each of the six condition/
procedure specific readmissions measures in the Hospital Readmissions 
Reduction Program and updating the CMS 30-Day Pneumonia Readmission 
Measure (NQF #0506) to exclude patients with a diagnosis of COVID-19 
present on admission from the measure denominator (cohort) and 
numerator (outcome), will be in effect after the end of the PHE or if 
this is a form of data suppression associated with the PHE.
    Response: We have adopted this update as an update to the measure 
specifications, not as suppression of data related to the COVID-19 PHE. 
Therefore, the updated measure specifications will not necessarily 
change with the end of the PHE. However, we will continue to monitor 
the effects of COVID-19 on each of our measures and on the overall 
program to ensure that the measure specifications remain appropriate 
for evolving clinical practices.
    Comment: A commenter expressed concern that the measure 
specifications are not publicly available and therefore commenters were 
unable to assess the impact of measure updates.
    Response: We regret that the commenter was unable to find the 
measure specification information to assess the impact of measure 
updates. As described in the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 
28421), the measure specifications, which were posted in May 2022, are 
available at https://qualitynet.cms.gov/inpatient/measures/readmission/methodology.
    Because of the CMS 30 Day Pneumonia Readmission Measure (NQF #0506) 
being paused from program calculations for FY 2023, the methodology 
report for FY 2023 is not yet available. However, we believe that past 
methodology reports provide sufficient information on the measure's 
specifications that commenters were able to assess the impact of 
updates on this measure.
    Comment: A commenter recommended risk adjusting for COVID-19 during 
an encounter instead of suppressing data for reporting periods or 
populations.
    Response: We believe this commenter is recommending developing a 
risk adjustment methodology for patients admitted with a primary or 
secondary diagnosis of COVID-19 present at admission instead of 
excluding these patients from the numerator (outcome) and denominator 
(cohort). We thank the commenter for this suggestion. We will consider 
this option in the future as we continue to evaluate the effectiveness 
of our COVID-19 updates for the measures in the Hospital Readmissions 
Reduction Program.
    Comment: Several commenters recommended that CMS publicly report 
the results of analyses that show that the data being used to capture 
patients with a history of COVID-19 in the 12 months prior to the index 
admission are sufficiently reliable. A commenter recommended that CMS 
publicly report analyses of the impact of COVID-19 patients on measure 
results to support public understanding of the results of measure 
updates.
    Response: We agree with the commenters that publicly reporting 
analyses that support our updates to measure specifications advances 
our objective of transparency in program operations. We note that we 
have published our analyses to date in the FY 2023 IPPS/LTCH PPS 
proposed rule (87 FR 28419 through 28421) and in response to public 
comments in this final rule.
6. Definition of ``Applicable Period''
    We refer readers to the FY 2012 IPPS/LTCH PPS final rule (76 FR 
51671) and the FY 2013 IPPS/LTCH PPS final rule (77 FR 53375) for 
discussion of our previously finalized policy for defining ``applicable 
period.'' The definition of ``applicable period'' is also specified at 
42 CFR 412.152. The ``applicable period'' is the 3-year period from 
which data are being collected in order to calculate excess readmission 
ratios (ERRs) and payment adjustment factors

[[Page 49089]]

for the fiscal year; this includes aggregate payments for excess 
readmissions and aggregate payments for all discharges used in the 
calculation of the payment adjustment. The ``applicable period'' for 
dually eligible beneficiaries is the same as the ``applicable period'' 
that we otherwise adopt for purposes of the Hospital Readmissions 
Reduction Program.
    In order to provide greater certainty around future ``applicable 
periods'' for the Hospital Readmissions Reduction Program, in the FY 
2021 IPPS/LTCH PPS final rule (85 FR 58845 through 58846), we finalized 
the automatic adoption of ``applicable periods'' for FY 2023 and all 
subsequent program years for the Hospital Readmissions Reduction 
Program.
    Beginning in FY 2023, the ``applicable period'' for the Hospital 
Readmissions Reduction Program will be the 3-year period beginning 1 
year advanced from the previous program fiscal year's start of the 
``applicable period.'' \221\ Under this policy, for all subsequent 
years, we will advance this 3-year period by 1 year unless otherwise 
specified by the Secretary, which we would convey through notice and 
comment rulemaking. Similarly, the ``applicable period'' for dual 
eligibility will continue to correspond to the ``applicable period'' 
for the Hospital Readmissions Reduction Program, unless otherwise 
specified by the Secretary. We refer readers to the FY 2021 IPPS/LTCH 
PPS final rule (85 FR 58845 through 58846) for a more detailed 
discussion of this topic.
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    \221\ Although the FY 2023 applicable period would be July 1, 
2018 through June 30, 2021, we note that the first and second 
quarter data from CY 2020 is excluded from consideration for program 
calculation purposes due to nationwide ECE that was granted in 
response to the COVID-19 PHE.
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    In the FY 2023 IPPS/LTCH PPS proposed rule, we did not propose any 
updates to this policy.
7. Identification of Aggregate Payments for Each Condition/Procedure 
and All Discharges
    When calculating the numerator (aggregate payments for excess 
readmissions), we determine the base operating DRG payment amount for 
an individual hospital for the applicable period for each condition/
procedure using Medicare inpatient claims from the MedPAR file with 
discharge dates that are within the applicable period. Under our 
established methodology, we use the update of the MedPAR file for each 
Federal fiscal year, which is updated 6 months after the end of each 
Federal fiscal year within the applicable period, as our data source.
    In identifying discharges for the applicable conditions/procedures 
to calculate the aggregate payments for excess readmissions, we apply 
the same exclusions to the claims in the MedPAR file as are applied in 
the measure methodology for each of the applicable conditions/
procedures. For the FY 2023 applicable period, this includes the 
discharge diagnoses for each applicable condition/procedure based on a 
list of specific ICD-10-CM and ICD-10-PCS code sets, as applicable, for 
that condition/procedure.
    We identify Medicare fee-for-service (FFS) claims that meet the 
criteria as previously described for each applicable condition/
procedure to calculate the aggregate payments for excess readmissions. 
This means that services covered by Medicare Advantage are not included 
in this calculation. This policy is consistent with the methodology to 
calculate ERRs based solely on admissions and readmissions for Medicare 
FFS patients.
    In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38232), we stated 
that we would determine the neutrality modifier using the most recently 
available full year of MedPAR data. For the purpose of modeling the 
estimated FY 2023 readmissions payment adjustment factors for this 
final rule, we would use the proportion of dually eligible 
beneficiaries, excess readmission ratios, and aggregate payments for 
each condition/procedure and all discharges for applicable hospitals 
from the FY 2023 Hospital Readmissions Reduction Program applicable 
period (July 1, 2018 through June 30, 2021).\222\
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    \222\ Although the FY 2023 applicable period is July 1, 2018, 
through June 30, 2021, we note that first and second quarter data 
from CY 2020 is excluded from consideration for program calculation 
purposes due to the nationwide ECE that was granted in response to 
the COVID-19 PHE.
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    For the FY 2023 program year, applicable hospitals will have the 
opportunity to review and correct calculations based on the FY 2023 
applicable period of July 1, 2018 to June 30, 2021, before they are 
made public under our policy regarding reporting of hospital-specific 
information. Again, we reiterate that this period is intended to review 
the program calculations, and not the underlying data. For more 
information on the review and corrections process, we refer readers to 
the FY 2013 IPPS/LTCH PPS final rule (77 FR 53399 through 53401).
    We did not propose any changes to our policies for the 
identification of aggregate payments for each condition/procedure in 
the FY 2023 IPPS/LTCH PPS proposed rule.
8. Use of MedPAR Data Corresponding to the Applicable Period
    We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR 
53387 through 53390) for discussion of our previously finalized policy 
for the use of MedPAR claims data as our data source for determining 
aggregate payments for each condition/procedure and aggregate payments 
for all discharges during applicable periods. Most recently, in the FY 
2022 IPPS/LTCH PPS final rule (86 FR 45258), we finalized our policy on 
the continued use of the MedPAR data corresponding to the applicable 
period for the Hospital Readmissions Reduction Program calculations for 
the FY 2022 applicable period.
    In addition, in the FY 2022 IPPS/LTCH PPS final rule (86 FR 45259), 
we expressed our continued belief that the use of MedPAR claims data is 
the appropriate source for identifying aggregate payments for each 
condition/procedure and all discharges during the corresponding 
applicable period for the Hospital Readmissions Reduction Program. 
Therefore, we finalized our proposal to automatically adopt the use of 
MedPAR data corresponding to the applicable period (the 3-year period 
beginning 1 year advanced from the previous program fiscal year's 
MedPAR data) \223\ for Hospital Readmissions Reduction Program 
calculations for FY 2023 and all subsequent program years.
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    \223\ Although the FY 2023 applicable period is July 1, 2018, 
through June 30, 2021, we note that first and second quarter data 
from CY 2020 is excluded from consideration for program calculation 
purposes due to the nationwide ECE that was granted in response to 
the COVID-19 PHE. Taking into consideration the 30-day window to 
identify readmissions, the period for calculating DRG payments would 
be adjusted to July 1, 2018 through December 1, 2019 and July 1, 
2020 through June 30, 2021. Further information will be found in the 
FY 2023 Hospital Specific Report (HSR) User Guide located on 
QualityNet website at https://qualitynet.cms.gov/inpatient/hrrp/reports.
---------------------------------------------------------------------------

    In the FY 2023 IPPS/LTCH PPS proposed rule, we did not propose any 
changes to this policy.
9. Calculation and Application of Payment Adjustment Factors
    As we discussed in the FY 2018 IPPS/LTCH PPS final rule (82 FR 
38226), section 1886(q)(3)(D) of the Act requires the Secretary to 
group hospitals and apply a methodology that allows for separate 
comparisons of hospitals within peer groups, based on the proportion of 
dually eligible beneficiaries served by each hospital, in determining a 
hospital's adjustment factor for payments applied to discharges 
beginning in FY 2019. Section 1886(q)(3)(D) of the Act also states that 
this methodology could be

[[Page 49090]]

replaced through the application of subclause (E)(i), which states that 
the Secretary may take into account the studies conducted and the 
recommendations made by the reports required by section 2(d)(1) of the 
IMPACT Act of 2014 (Pub. L. 113-185; 42 U.S.C. 1395 note) with respect 
to risk adjustment methodologies.
    Additionally, section 1886(q)(3)(A) of the Act defines the payment 
adjustment factor for an applicable hospital for a fiscal year as 
``equal to the greater of: (i) the ratio described in subparagraph (B) 
for the hospital for the applicable period (as defined in paragraph 
(5)(D)) for such fiscal year; or (ii) the floor adjustment factor 
specified in subparagraph (C).'' Section 1886(q)(3)(B) of the Act, in 
turn, describes the ratio used to calculate the adjustment factor. 
Specifically, it states that the ratio is equal to 1 minus the ratio of 
aggregate payments for excess readmissions to aggregate payments for 
all discharges, scaled by the neutrality modifier. The calculation of 
this ratio is codified at 42 CFR 412.154(c)(l) and the floor adjustment 
factor is codified at 42 CFR 412.154(c)(2). Section 1886(q)(3)(C) of 
the Act specifies the floor adjustment factor at 0.97 for FY 2015 and 
subsequent fiscal years.
    Consistent with section 1886(q)(3) of the Act, and codified in our 
regulations at 42 CFR 412.154(c)(2), for FY 2023, the payment 
adjustment factor will be either the greater of the ratio or the floor 
adjustment factor of 0.97. Under our established policy, the ratio is 
rounded to the fourth decimal place. In other words, for FY 2023, a 
hospital subject to the Hospital Readmissions Reduction Program would 
have an adjustment factor that is between 1.0 (no reduction) and 0.9700 
(greatest possible reduction).
    We refer readers to the FY 2018 IPPS/LTCH PPS final rule (82 FR 
38226 through 38237) for a detailed discussion of the payment 
adjustment methodology. For additional information on Hospital 
Readmissions Reduction Program payment calculations, we refer readers 
to the Hospital Readmissions Reduction Program information and 
resources available on our QualityNet website.
    We did not propose any changes to our calculation of payment 
methodology in the FY 2023 IPPS/LTCH PPS proposed rule.
10. Extraordinary Circumstance Exception (ECE) Policy for the Hospital 
Readmissions Reduction Program
    In the FY 2016 IPPS/LTCH PPS final rule (80 FR 49542 through 
49543), we adopted an ECE policy for the Hospital Readmissions 
Reduction Program, which recognized that there may be periods of time 
during which a hospital is not able to submit data (from which 
readmission measures data are derived) in an accurate or timely fashion 
due to an extraordinary circumstance beyond its control. When adopting 
this policy, we noted that we considered the feasibility and 
implications of excluding data for certain measures for a limited 
period of time from the calculations for a hospital's excess 
readmission ratios for the applicable performance period. By minimizing 
the data excluded from the program, the policy enabled affected 
hospitals to continue to participate in the Hospital Readmissions 
Reduction Program for a given fiscal year if they otherwise continued 
to meet applicable measure minimum threshold requirements. We expressed 
the belief that this approach would help alleviate the burden for a 
hospital that might be adversely impacted by a natural disaster or 
other extraordinary circumstance beyond its control, while enabling the 
hospital to continue to participate in the Hospital Readmissions 
Reduction Program. We further observed that section 1886(q)(5)(D) of 
the Act permits the Secretary to determine the applicable period for 
readmissions data collection, and we interpreted the statute to allow 
us to determine that the period not include times when hospitals may 
encounter extraordinary circumstances. In the FY 2018 IPPS/LTCH PPS 
final rule (82 FR 38239 through 38240), we modified the requirements 
for the Hospital Readmissions Reduction Program ECE policy to further 
align with the processes used by other quality reporting and VBP 
programs for requesting an exception from program reporting due to an 
extraordinary circumstance not within a provider's control.
    In response to COVID-19, we announced relief for clinicians, 
providers, hospitals, and facilities participating in Medicare quality 
reporting and value-based purchasing programs. On September 2, 2020, we 
published the interim final rule with comment period (IFC), ``Medicare 
and Medicaid Programs, Clinical Laboratory Improvement Amendments 
(CLIA), and Patient Protection and Affordable Care Act; Additional 
Policy and Regulatory Revisions in Response to the COVID-19 Public 
Health Emergency'' (85 FR 54820). The IFC updated the ECE we granted in 
response to the COVID-19 PHE, for the Hospital Readmissions Reduction 
Program and several other quality reporting programs (85 FR 54827 
through 54837). In the IFC, we updated the previously announced 
application of our ECE policy for the Hospital Readmissions Reduction 
Program (85 FR 54832 through 54833) to the COVID-19 PHE to exclude any 
data submitted regarding care provided during the first and second 
quarters of CY 2020 from our calculation of performance for FY 2022, FY 
2023, and FY 2024.
    In the FY 2022 IPPS/LTCH PPS final rule (86 FR 45260 through 
45262), we clarified our ECE policy to highlight that an ECE granted 
under the Hospital Readmissions Reduction Program would exclude claims 
data during the corresponding ECE period. We stated that although we 
had considered the feasibility and implications of excluding data under 
the ECE policy for the Hospital Readmissions Reduction Program, we had 
never specified the types of data that would be excluded under an ECE 
granted to an individual hospital. Considering that the Hospital 
Readmissions Reduction Program only uses claims data, we clarified our 
ECE policy to specify that claims data will be excluded from 
calculations of measure performance under an approved ECE for the 
Hospital Readmissions Reduction Program. We further clarified that 
although an approved ECE for the Hospital Readmissions Reduction 
Program would exclude excepted data from Hospital Readmissions 
Reduction Program payment reduction calculations, we did not waive the 
data submission requirements of a hospital for claims data (86 FR 45261 
through 45262). For example, for claims data, we require a hospital to 
submit claims to receive payments for the services they provided to 
patients. Although an individual ECE approval under the Hospital 
Readmissions Reduction Program would except data submitted by a 
hospital from Hospital Readmissions Reduction Program calculations, a 
hospital would still need to submit its claims in order to receive 
payment outside the scope of the Hospital Readmissions Reduction 
Program for services provided.
    Finally, in the FY 2022 IPPS/LTCH PPS final rule, we clarified 
that, although an approved ECE for the Hospital Readmissions Reduction 
Program would exclude excepted data from Hospital Readmissions 
Reduction Program payment reduction calculations, such an ECE does not 
exempt hospitals from payment reductions under the Hospital 
Readmissions Reduction Program (86 FR 45262).
    We did not propose any changes to our previously finalized ECE 
Policy in the FY 2023 IPPS/LTCH PPS proposed rule.

[[Page 49091]]

11. Request for Public Comment on Possible Future Inclusion of Health 
Equity Performance in the Hospital Readmissions Reduction Program
    We are committed to achieving equity in healthcare outcomes for our 
beneficiaries by supporting providers' quality improvement activities 
to reduce health inequities, by enabling them to make more informed 
decisions, and by promoting provider accountability for healthcare 
disparities.\224\ As described in section IX.B. of the preamble of this 
final rule, we discussed and sought comment on overarching principles 
for measuring health care quality disparities to provide more 
actionable and comprehensive information on health care disparities 
across multiple social risk factors and demographic variables. As part 
of this request for information, we also discussed different approaches 
for identifying meaningful performance differences and guiding 
principles for reporting disparity measures.
---------------------------------------------------------------------------

    \224\ https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Qualityinitiativesgeninfo/downloads/cms-quality-strategy.pdf.
---------------------------------------------------------------------------

    As previously discussed in the FY 2018 IPPS/LTCH PPS final rule (82 
FR 38226), section 1886(q)(3)(D) of the Act requires the Secretary to 
group hospitals and apply a methodology that allows for separate 
comparisons of hospitals with differing proportions of dually eligible 
beneficiaries in determining a hospital's adjustment factor for 
payments applied to discharges beginning in FY 2019. To implement this 
provision, in the FY 2018 IPPS/LTCH PPS final rule (82 FR 38226 through 
38237), we finalized a number of changes to the payment reduction 
methodology, including our policy to stratify hospitals into quintiles, 
or peer groups, based on their proportion of dually eligible 
beneficiaries (82 FR 38229 through 38231) and our policy to use the 
median excess readmission ratio for the hospital's peer group in place 
of 1.0 in the payment reduction formula (82 FR 38231 through 38237). In 
this peer grouping methodology, dual eligibility status is used as it 
is an indicator of beneficiaries' social risk. The peer grouping 
methodology mitigates against disproportionate payment reductions for 
hospitals serving socially at-risk populations. However, this peer 
grouping methodology does not directly measure or account for 
disparities in health care quality between beneficiary groups with 
heightened social risk and groups with less social risk.
    In the FY 2018 IPPS/LTCH PPS final rule, we introduced confidential 
reporting of hospital quality measure data stratified by social risk 
factors (82 FR 38403 through 38409). We have created two complementary 
methods to calculate disparities in condition/procedure-specific 
readmission measures (the CMS Disparity Methods). The first method (the 
Within-Hospital disparity method) promotes quality improvement by 
calculating differences in outcome rates across beneficiary groups 
within a hospital while accounting for their clinical risk factors. 
This method also allows for comparison of those differences, or 
disparities, across hospitals, so hospitals could assess how well they 
are closing disparity gaps compared to other hospitals. The second 
methodological approach (the Across-Hospital method) assesses 
hospitals' outcome rates for subgroups of beneficiaries across 
hospitals, allowing for a comparison across hospitals on their 
performance serving beneficiaries with social risk factors. We refer 
readers to the FY 2018 IPPS/LTCH PPS final rule (82 FR 38405 through 
38407) and the Disparity Methods technical report and Updates and 
Specifications Report posted on the QualityNet website for additional 
details. The CMS Disparity Methods more directly measure disparities in 
health care quality between dually eligible and non-dually eligible 
beneficiary groups than the Hospital Readmissions Reduction Program's 
peer grouping methodology. For example, when considering the CMS 
Disparity Methods results calculated using data for the FY 2022 
Hospital Readmissions Reduction Program performance period, measures 
showed not only a range between low and high disparity rates within 
hospitals, but also worse overall outcome rates for beneficiaries with 
social risk using beneficiary dual eligibility status as the 
stratification variable. Of these measures, the most actionable for 
hospitals were measures that showed overall high readmission rates for 
dually eligible beneficiaries across hospitals, or a large difference 
in readmission rates between dually eligible and non-dually eligible 
beneficiaries. These gaps in care indicated that there is potential for 
improvement, or a reduction in disparity at poorly performing hospitals 
if they were able to emulate the performance of strongly performing 
hospitals.
    The Hospital Readmissions Reduction Program currently groups 
hospitals into one of five peer groups based on their proportion of 
beneficiaries who are dually eligible for Medicare and full Medicaid 
benefits. Beneficiaries' dual eligibility for Medicare and Medicaid is 
a widely used proxy for a beneficiary's financial risk. Medicaid 
enrollees have incomes and overall wealth below a certain threshold and 
thus, Medicaid eligibility may be used as a proxy for low socioeconomic 
status. The use of beneficiaries' dual eligibility in social risk 
factor analyses was supported by ASPE's First Report to Congress.\225\ 
This report found that in the context of value-based purchasing 
programs such as the Hospital Readmissions Reduction Program, dual 
eligibility, as an indicator of social risk, was among the most 
powerful predictors of poor health outcomes among those social risk 
factors that ASPE examined and tested. In alignment with the current 
program, we are considering the use of the beneficiary's dual 
eligibility status as a measure of beneficiaries' social risk that 
could be used to incorporate hospitals' performance for socially at-
risk populations in the Hospital Readmissions Reduction Program.
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    \225\ Office of the Assistant Secretary for Planning and 
Evaluation. (2016). Social risk factors and performance under 
Medicare's value-based purchasing programs. Available at: https://aspe.hhs.gov/reports/report-congress-social-risk-factors-performance-under-medicares-value-based-purchasing-programs.
---------------------------------------------------------------------------

    As part of our broader goal of achieving equity in healthcare 
outcomes for our beneficiaries, we are interested in encouraging 
providers to improve health equity and reduce health care disparities 
through the Hospital Readmissions Reduction Program. We sought comment 
on approaches to updating the Hospital Readmissions Reduction Program 
to incorporate performance for socially at-risk populations. For 
example, we are considering approaches that would account for a 
hospital's performance on readmissions for socially at-risk 
beneficiaries compared to all other hospitals, or its performance in 
treating socially at-risk beneficiaries compared to other beneficiaries 
within the hospital, or combinations of these approaches. We 
acknowledge that updating the Hospital Readmissions Reduction Program 
to encourage improved performance for socially at-risk populations can 
take many forms, and we sought to explore different approaches so we 
can find an approach that satisfies our goals without unintended 
consequences.
    In exploring approaches to incorporate performance for socially at-
risk populations in the Hospital Readmissions Reduction Program, our 
objective is to encourage providers to improve health equity and reduce 
health care disparities without

[[Page 49092]]

disincentivizing hospitals to treat socially at-risk beneficiaries or 
disproportionately penalizing hospitals that treat a large proportion 
of socially at-risk beneficiaries. We sought comment on approaches that 
would achieve this objective.
    As also discussed in our request for information on overarching 
principles for measuring health care quality disparities, as described 
in section IX.C of the preamble of this final rule, many non-clinical 
drivers of health are known to impact beneficiary outcomes, including 
social risk factors such as socioeconomic status, housing security and 
adequacy, and food security. The Hospital Readmissions Reduction 
Program currently uses beneficiaries' dual eligibility for Medicare and 
Medicaid as a proxy for a beneficiary's social risk and uses dual 
eligibility, as required by the statute, to divide hospitals into peer 
groups for comparison under the program. We sought comment on variables 
associated with or measures of social risk and beneficiary demographics 
that are already collected, as well as broader definitions of dual 
eligibility, such as those who are enrolled in a Medicare Savings 
Program or the Medicare Part D Low Income Subsidy, that could be 
included in the Hospital Readmissions Reduction Program in addition to 
dual eligibility. We note initially we would use such variables to 
stratify results within Hospital Specific Reports (HSRs) as 
confidential feedback to hospitals.
    Measures of social risk could also include indices developed for 
the purpose of identifying socially at-risk populations and measuring 
the degree of risk. For example, as described in section IX.B, we are 
considering the University of Wisconsin School of Medicine and Public 
Health and Health Resources and Services Administration's Area 
Deprivation Index (ADI),\226\ Agency for Healthcare Research and 
Quality Socioeconomic Status Index,\227\ and the Centers for Disease 
Control and Prevention's Social Vulnerability Index.\228\ For example, 
the ADI allows for rankings of neighborhoods by socioeconomic 
disadvantage in a region of interest (such as at the state or national 
level), and includes factors for income, education, employment, and 
housing quality and is used in our Everyone with Diabetes Counts 
program in order to target seniors in the most disadvantaged 
neighborhoods for diabetes education.\229\ In addition to individual 
variables or sets of variables we sought comment on the addition of one 
or more of these indices or proposals for other indices or modified 
indices that capture multiple dimensions of social risk and that have 
demonstrated relations to health outcomes or access to health care 
resources, that can be added to the Program along with dual eligibility 
as factors for stratifying data. We requested commenters to include 
information on the availability of public data sources and 
documentation of the methods and testing that establish their 
applicability and provide supporting information about availability and 
methods when suggesting variables or indices to measure social risk. 
Support from a national-level assessment of the impact of social risk 
can be particularly useful to demonstrate the relevance of a proposed 
indicator.
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    \226\ Center for Health Disparities Research. About the 
Neighborhood Atlas. Available at: https://www.neighborhoodatlas.medicine.wisc.edu/.
    \227\ Bonito A., Bann C., Eicheldinger C., Carpenter L. (2008). 
Creation of New Race-Ethnicity Codes and Socioeconomic Status (SES) 
Indicators for Medicare Beneficiaries. Final Report, Sub-Task 2. 
(Prepared by RTI International for the Centers for Medicare & 
Medicaid Services through an interagency agreement with the Agency 
for Healthcare Research and Policy, under Contract No. 500-00-0024, 
Task No. 21) AHRQ Publication No. 08-0029-EF. Rockville, MD, Agency 
for Healthcare Research and Quality.
    \228\ Flanagan, B.E., Gregory, E.W., Hallisey, E.J., Heitgerd, 
J.L., Lewis, B. (2011). A social vulnerability index for disaster 
management. Journal of Homeland Security and Emergency Management, 
8(1). Available at: https://www.atsdr.cdc.gov/placeandhealth/svi/img/pdf/Flanagan_2011_SVIforDisasterManagement-508.pdf.
    \229\ https://www.neighborhoodatlas.medicine.wisc.edu/.
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    Before any changes to the Hospital Readmissions Reduction Program 
are implemented, we plan to assess the extent to which they address our 
objective as well as their financial impact on the Hospital 
Readmissions Reduction Program. Any proposals to update the Hospital 
Readmissions Reduction Program to account for the extent to which a 
hospital is able to provide high quality and equitable care for 
beneficiaries with social risk factors, as previously described, would 
be made through future rulemaking.
    We invited public comment on the following: (1) the benefit and 
potential risks, unintended consequences, and costs of incorporating 
hospital performance for beneficiaries with social risk factors in the 
Hospital Readmissions Reduction Program; (2) the approach of linking 
performance in caring for socially at-risk populations and payment 
reductions by calculating the reductions based on readmission outcomes 
for socially at-risk beneficiaries compared to other hospitals or 
compared to performance for other beneficiaries within the hospital; 
and (3) measures or indices of social risk, in addition to dual 
eligibility, that should be used to measure hospitals' performance in 
achieving equity in the Hospital Readmissions Reduction Program.
    We received comments in response to this request for information 
and have summarized them here.
    Comment: Several commenters provided general comments regarding 
equity in the Hospital Readmissions Reduction Program. Some of these 
commenters expressed concern that current disparity methods lack 
actionable information. A commenter recommended providing financial 
support to prevent readmissions related to social needs, for example, 
by supporting hospitals' efforts to monitor post discharge outcomes and 
connect patients with necessary services. A commenter observed that 
hospitals are still experiencing the effects of the COVID-19 PHE and 
recommended that CMS wait until these effects have subsided to 
introduce new payment calculations both to ensure that any calculations 
are based on reliable data and to prevent further overwhelming 
hospitals.
    Many commenters responded to our request for input on the benefit 
and potential risks, unintended consequences, and costs of 
incorporating hospital performance for beneficiaries with social risk 
factors in the Hospital Readmissions Reduction Program. Several 
commenters expressed that the potential benefits of incorporating 
equity in the Hospital Readmissions Reduction Program are improved care 
for at-risk patients, improved understanding of the effects of the 
social risk factors, and improved care for all patients. A commenter 
stated that readmissions are a metric for healthcare equity because 
patients who receive high quality care are generally not readmitted. 
This commenter expressed that improving healthcare equity could reduce 
readmissions.
    Many commenters expressed the concern that linking payment to 
performance on equity measures may disproportionately penalize safety 
net hospitals or other providers that treat high complexity patients 
which could impact access and quality for these patients. Some of these 
commenters recommended using bonus points or incentives to avoid 
penalizing hospitals that treat at-risk patients. A commenter observed 
that addressing disparities will require a long-term systemic approach.
    Many commenters expressed concern that incorporating performance 
for beneficiaries with social risk factors in

[[Page 49093]]

the Hospital Readmissions Reduction Program could lead hospitals to be 
held accountable for factors outside of their control. These commenters 
specifically noted that there are numerous factors outside of a 
hospitals' control that affect readmission rates, including community 
and patient level factors. Some of these commenters recommended 
developing a mechanism for adjusting for confounding influences to 
ensure public reporting and payment are based exclusively on the 
quality of care provided; one of these commenters specifically 
recommended adopting a risk adjustment for patients who do not take 
responsibility for their post discharge care. Other commenters 
recommended against public reporting on stratified or other equity data 
because this publication could imply that hospitals are solely 
responsible for 30-day readmissions.
    Several commenters observed that analyzing data does not address 
the underlying disparities, it only allows the extent of the issue to 
be understood. A commenter stated that publicly reporting all data, 
both as trend reports and as raw data, allows advocates and other 
interested parties to perform analyses and evaluate equity.
    Several commenters observed that the current peer grouping and 
stratified reporting are recent changes to the Hospital Readmissions 
Reduction Program, and that much of the recent data for the Program has 
been affected by the COVID-19 PHE. These commenters recommended leaving 
the payment structure unchanged for at least three more years to 
analyze the effects of the current program prior to modifying the 
payment structure. A commenter stated the belief that the Hospital 
Readmissions Reduction Program methodology is flawed because it uses 
point estimates of risk-standardized readmission rates without respect 
to the margin of error for each estimate. This commenter requested 
clarification regarding the expectations for hospitals prior to 
including care for at-risk patients into the Hospital Readmission 
Reduction Program methodology. Another commenter observed that the 
current payment calculations are already complex and expressed concern 
that further modification to a complex system could lead to unintended 
consequences.
    Several commenters stated that linking payment to equity is 
inconsistent with the statutory requirements for calculating payment 
reductions. Some of these commenters observed that the payment system 
was designed to ensure equitable payments for hospitals that treat high 
risk patients, not to advance patient level equity in outcomes. Several 
commenters observed that tracking drivers of health data may increase 
the burden for providers. A commenter expressed concern that linking 
payment to performance on equity measures would change hospitals' focus 
to factors outside of each patient's medical diagnosis, thereby 
decreasing the quality of care. A commenter expressed concern that the 
measures in the Hospital Readmissions Reduction Program already require 
three years of data to ensure sufficient sample sizes, therefore this 
commenter is concerned that stratification of these measures could lead 
to samples too small to be reliable.
    A commenter stated that without uniformly collected patient-
reported sociodemographic data there is not a data source sufficiently 
reliable for inclusion in payment adjustments. This commenter observed 
that the NQF is preparing to release guidance on using ADI and other 
social risk factor data for quality measurement which may provide 
useful information for the Hospital Readmissions Reduction Program to 
consider. Another commenter recommended rigorous statistical testing 
prior to adopting any health equity methodologies.
    Several commenters responded to our request for input on the 
approach of linking performance in caring for socially at-risk 
populations and payment reductions by calculating the reductions based 
on readmission outcomes for socially at-risk beneficiaries compared to 
other hospitals or compared to performance for other beneficiaries 
within the hospital. Several of these commenters recommended that any 
use of the Across-Hospital Disparity method comparison should only 
compare hospitals within similar communities because community 
resources are an important factor in readmission risk. A commenter 
recommended starting with the Across-Hospital Disparity method because 
this is more likely to account for factors outside of a hospital's 
control that affect readmission rates. Another commenter recommended 
starting with Within-Hospital Disparity method because these data will 
be easier for CMS to calculate and easier for hospitals to understand.
    Several commenters supported providing both Within- and Across-
Hospital Disparity methods, but only in confidential reports for 
hospitals. One of these commenters stated that CMS does not have the 
statutory authority to include these data in Hospital Readmissions 
Reduction Program payment calculations. Other commenters observed that 
including Within- and Across-Hospital Disparity method performance in a 
hospital's readmission score (as opposed to in the measures' risk 
adjustment methodologies) is inconsistent with CMS's approach to 
clinical risk factors, specifically noting that for clinical risk 
factors CMS recognizes that these factors are largely beyond a 
hospital's control and therefore includes them in the risk adjustment 
methodology.
    Many commenters provided input to our request for potential 
measures or indices of social risk, in addition to dual eligibility, 
that should be used to measure hospitals' performance in achieving 
equity in the Hospital Readmissions Reduction Program. Many commenters 
observed that the Hospital IQR Program has proposed a Screen Positive 
Rate for Social Drivers of Health (SDOH) measure in the FY 2023 IPPS/
LTCH PPS proposed rule (87 FR 28503 through 87 28506). These commenters 
observed that the patient-level data collected by hospitals for these 
measures may be appropriate for stratification or other analysis in the 
Hospital Readmissions Reduction Program.
    Several commenters expressed concern regarding the use of dual 
eligibility for Medicare and Medicaid coverage as a proxy variable. 
These commenters observed that Medicaid eligibility requirements vary 
from state to state and therefore is not a nationally comparable 
metric. One of these commenters supported including eligibility for the 
Medicare Savings Program or the Medicare Part D Low Income Subsidy in 
analyses. Another commenter expressed concern that disability may be 
another aspect of dual eligibility that influences readmissions, and 
that using dual eligibility as a proxy for income may hinder analysis 
of the effects of disability.
    Many commenters supported the use of proxy measures (including dual 
eligible status, the ADI, the Social Vulnerability Index, the 
Neighborhood Deprivation Index, the Multidimensional Deprivation Index, 
or a custom developed index specifically related to health equity) as a 
short term solution until CMS can report data based on clearly and 
consistently defined patient-level, patient-collected data (including 
race, age, disability, sex, sexual orientation, and gender identity, 
limited English proficiency, primary language, housing instability, and 
marital status). Several commenters observed that there may be 
challenges to patient-level data collection, including technological 
challenges and patient discomfort with sharing sensitive

[[Page 49094]]

information. A few commenters recommended including the ADI with other, 
patient-level data in analyses to ensure that use of the ADI does not 
further disparities such as by providing data indicating specific 
communities need greater support, but not providing data regarding the 
subpopulations within those communities that require the most support. 
A commenter observed that available indices do not account for the role 
of segregation, gentrification, and hypersegregation in health 
outcomes. A commenter expressed concern that use of multiple factors or 
indices could create contradictory analytical findings. Without 
detailed explanation for these contradictory results, there could be 
stakeholder confusion. A commenter recommended considering how to 
incorporate data collected on claims using z-codes to analyze 
readmissions in the Hospital Readmissions Reduction Program. Another 
commenter recommended combining the analysis of social and clinical 
data to identify gaps in care. A commenter observed that the factors 
that affect disparities are systemic, community, institutional, 
interpersonal, and intrapersonal and recommended that CMS consider all 
factors.
    Several commenters agreed that non-clinical factors may affect 
readmissions and recommended conducting analyses to determine which 
factors and to what degree prior to incorporating these factors into 
the Hospital Readmissions Reduction Program. Several commenters 
recommended using patient-level social risk variables (such as race, 
age, disability, sex, sexual orientation, and gender identity, limited 
English proficiency, primary language, housing instability, and marital 
status) for peer grouping. A commenter recommended using stratification 
for analysis. A commenter recommended that CMS evaluate hospitals' 
community investments.
    Response: We appreciate all of the comments and interest in this 
topic. We believe that this input is very valuable in the continuing 
development of the CMS health equity efforts. We will continue to take 
all concerns, comments, and suggestions into account for future 
development and expansion of our health equity efforts. For more 
information on our ongoing effort we refer readers to our recently 
released CMS National Quality Strategy (https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Value-Based-Programs/CMS-Quality-Strategy) and the CMS Framework for Health Equity 
(https://www.cms.gov/About-CMS/Agency-Information/OMH/equity-initiatives/framework-for-health-equity) in which we describe our five 
priorities for advancing health equity.

I. Hospital Value-Based Purchasing (VBP) Program: Policy Changes

    Section 1886(o) of the Act requires the Secretary to establish a 
hospital value-based purchasing program (the Hospital VBP Program) 
under which value-based incentive payments are made in a fiscal year 
(FY) to hospitals that meet performance standards established for a 
performance period for such fiscal year. Both the performance standards 
and the performance period for a fiscal year are to be established by 
the Secretary.
    For more of the statutory background and descriptions of our 
current policies for the Hospital VBP Program, we refer readers to our 
codified requirements for the Hospital VBP Program at 42 CFR 412.160 
through 412.168.
1. Flexibilities for the Hospital VBP Program in Response to the Public 
Health Emergency (PHE) Due to COVID-19
a. Measure Suppression Policy for the Duration of the COVID-19 PHE
    In the FY 2022 IPPS/LTCH PPS final rule, we finalized a measure 
suppression policy and several Measure Suppression Factors for the 
duration of the COVID-19 PHE (86 FR 45266 through 45269). We stated 
that we had previously identified the need for flexibility in our 
quality programs to account for the impact of changing conditions that 
are beyond participating hospitals' control. We identified this need 
because we would like to ensure that participants in our programs are 
not affected negatively when their quality performance suffers not due 
to the care provided, but due to external factors, such as the COVID-19 
PHE.
    Specifically, we finalized a policy for the duration of the COVID-
19 PHE that enables us to suppress the use of data for a number of 
measures if we determine that circumstances caused by the COVID-19 PHE 
have affected those measures and the resulting Total Performance Scores 
(TPSs) significantly. We also finalized the adoption of Measure 
Suppression Factors which will guide our determination of whether to 
suppress a Hospital VBP Program measure for one or more program years 
where the baseline or performance period of the measure overlaps with 
the COVID-19 PHE. The finalized Measure Suppression Factors are as 
follows:
     Measure Suppression Factor 1: Significant deviation in 
national performance on the measure during the PHE for COVID-19, which 
could be significantly better or significantly worse compared to 
historical performance during the immediately preceding program years.
     Measure Suppression Factor 2: Clinical proximity of the 
measure's focus to the relevant disease, pathogen, or health impacts of 
the PHE for COVID-19.
     Measure Suppression Factor 3: Rapid or unprecedented 
changes in--
    ++ Clinical guidelines, care delivery or practice, treatments, 
drugs, or related protocols, or equipment or diagnostic tools or 
materials; or
    ++ The generally accepted scientific understanding of the nature or 
biological pathway of the disease or pathogen, particularly for a novel 
disease or pathogen of unknown origin.
     Measure Suppression Factor 4: Significant national 
shortages or rapid or unprecedented changes in--
    ++ Healthcare personnel;
    ++ Medical supplies, equipment, or diagnostic tools or materials; 
or
    ++ Patient case volumes or facility-level case mix.
    We also note that, as part of this measure suppression policy, we 
stated that we would still provide confidential feedback reports to 
hospitals on their measure rates on all measures to ensure that they 
are made aware of the changes in performance rates that we have 
observed. We also stated that we would publicly report suppressed data 
with appropriate caveats noting the limitations of the data due to the 
COVID-19 PHE. We continue to strongly believe that publicly reporting 
these data will balance our responsibility to provide transparency to 
consumers and uphold safety while ensuring that hospitals are not 
unfairly scored or penalized through payment under the Hospital VBP 
Program. We also note that, due to operational complications associated 
with the proposed changes to the scoring methodology, and in order to 
allow enough time for the appropriate notice and comment period 
process, we may not be able to provide hospitals with the feedback 
reports for FY 2023 until after August 1, 2022. We intend to provide 
hospitals with these feedback reports for FY 2023 as soon as possible 
and estimate that we will be able to provide reports before the end of 
2022.
    We did not propose any changes to the measure suppression policy.
b. Suppression of Specific Measures for the FY 2023 Program Year
(1) Background and Overview
    COVID-19 has had significant negative health effects--on 
individuals,

[[Page 49095]]

communities, nations, and globally. Consequences for individuals who 
have COVID-19 include morbidity, hospitalization, mortality, and post-
COVID-19 related conditions (also known as long COVID). As of June 
2022, over 86 million COVID-19 cases, 4.8 million new COVID-19 related 
hospitalizations, and 1 million COVID-19 deaths have been reported in 
the U.S.\230\ One analysis projected that COVID-19 would reduce life 
expectancy in 2020 by 1.13 years overall, with the estimated impact 
disproportionately affecting minority communities. According to this 
analysis, the estimated life expectancy reduction for Black and Latino 
populations is 3 to 4 times the estimate when comparing to the white 
population.\231\ With a death toll surpassing that of the 1918 
influenza pandemic, COVID-19 is the deadliest disease in American 
history.\232\
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    \230\ https://www.cdc.gov/coronavirus/2019-ncov/cases-updates/.
    \231\ Andrasfay, T., & Goldman, N. (2021). Reductions in 2020 US 
life expectancy due to COVID-19 and the disproportionate impact on 
the Black and Latino populations. Proceedings of the National 
Academy of Sciences of the United States of America, 118(5), 
e2014746118. https://www.pnas.org/content/118/5/e2014746118.
    \232\ Covid overtakes 1918 Spanish flu as deadliest disease in 
U.S. history (statnews.com).
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    Additionally, impacts of the COVID-19 pandemic have continued to 
accelerate in 2021 as compared with 2020. The Delta variant of COVID-19 
(B.1.617.2) surfaced in the United States in early-to-mid 2021. Studies 
have shown that the Delta variant is up to 60 percent more 
transmissible than the previously dominant Alpha variant in 2020.\233\ 
Further, in November 2021, the number of COVID-19 deaths for 2021 
surpassed the total deaths for 2020. According to CDC data, the total 
number of deaths involving COVID-19 reached 385,453 in 2020 and 451,475 
in 2021.\234\ With this increased transmissibility and morbidity 
associated with the Delta variant as well as new variants like Omicron 
which have impacted 2021 235 236 and worsening staffing 
shortages in Q3 and Q4 2021 associated with the ongoing PHE,\237\ we 
remain concerned about using measure data that is significantly 
impacted by COVID-19 for scoring and payment purposes for the FY 2023 
program year.
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    \233\ Allen H., Vusirikala A., Flannagan J., et al. Increased 
Household Transmission of COVID-19 cases associated with SARS-CoV-2 
Variant of Concern B.1.617.2: a national case-control study. Public 
Health England. 2021.
    \234\ https://www.cdc.gov/nchs/nvss/vsrr/covid19/index.htm.
    \235\ https://www.cdc.gov/coronavirus/2019-ncov/science/forecasting/mathematical-modeling-outbreak.html.
    \236\ https://www.cdc.gov/coronavirus/2019-ncov/variants/omicron-variant.html?s_cid=11734:omicron%20variant:sem.ga:p:RG:GM:gen
:PTN:FY22.
    \237\ Bloomberg, U.S. Hospital Staff Shortages Hit Most in a 
Year on Covid Surge, https://www.bloomberg.com/news/articles/2022-01-05/one-in-five-u-s-hospitals-face-staffing-shortages-most-in-year 
(citing HHS data).
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    As noted in section V.H.1.a., in the FY 2022 IPPS/LTCH PPS final 
rule, we finalized a measure suppression policy and several Measure 
Suppression Factors for the duration of the COVID-19 PHE (86 FR 45266 
through 45269). In addition, under that policy, we suppressed the 
following measures for the FY 2022 program year:
     Hospital Consumer Assessment of Healthcare Providers and 
Systems (HCAHPS) (NQF #0166)
     Medicare Spending per Beneficiary--Hospital (MSPB) (NQF 
#2158)
     National Healthcare Safety Network (NHSN) Catheter-
Associated Urinary Tract Infection (CAUTI) Outcome Measure (NQF #0138)
     National Healthcare Safety Network (NHSN) Central Line-
Associated Bloodstream Infection (CLABSI) Outcome Measure (NQF #0139)
     American College of Surgeons- Centers for Disease Control 
and Prevention Harmonized Procedure Specific Surgical Site Infection 
(SSI) Outcome Measure (NQF #0753)
     National Healthcare Safety Network (NHSN) Facility-wide 
Inpatient Hospital-onset Methicillin-resistant Staphylococcus aureus 
(MRSA) Bacteremia Outcomes Measure (NQF #1716)
     National Healthcare Safety Network (NHSN) Facility-wide 
Inpatient Hospital-onset Clostridium difficile Infection (CDI) Outcome 
Measure (NQF #1717)
    Since the publication of the FY 2022 IPPS/LTCH PPS final rule, we 
have conducted analyses on all Hospital VBP Program measures to 
determine whether and how COVID-19 has impacted the validity of the 
data used to calculate these measures for the FY 2023 program year. Our 
discussion of the findings from these analyses follows. Based on those 
analyses, in the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28426 
through 28445), we proposed to suppress the following measures for the 
FY 2023 program year:
     Hospital Consumer Assessment of Healthcare Providers and 
Systems (HCAHPS) (NQF #0166)
     National Healthcare Safety Network (NHSN) Catheter-
Associated Urinary Tract Infection (CAUTI) Outcome Measure (NQF #0138)
     National Healthcare Safety Network (NHSN) Central Line-
Associated Bloodstream Infection (CLABSI) Outcome Measure (NQF #0139)
     American College of Surgeons- Centers for Disease Control 
and Prevention Harmonized Procedure Specific Surgical Site Infection 
(SSI) Outcome Measure (NQF #0753)
     National Healthcare Safety Network (NHSN) Facility-wide 
Inpatient Hospital-onset Methicillin-resistant Staphylococcus aureus 
(MRSA) Bacteremia Outcome Measure (NQF #1716)
     National Healthcare Safety Network (NHSN) Facility-wide 
Inpatient Hospital-onset Clostridium difficile Infection (CDI) Outcome 
Measure (NQF #1717)
    We also note that in the FY 2022 IPPS/LTCH PPS final rule, we 
finalized our proposal to suppress the Hospital 30-Day, All Cause, Risk 
Standardized Mortality Rate Following Pneumonia (PN) Hospitalization 
measure (NQF #0468) (MORT-30-PN) for the FY 2023 program year (86 FR 
45274 through 45276).
(2) Suppression of the Hospital Consumer Assessment of Healthcare 
Providers and Systems (HCAHPS) Survey Measure (NQF #0166) for the FY 
2023 Hospital VBP Program Year
    As noted in section V.H.1.b. of the preamble of this final rule, in 
the FY 2022 IPPS/LTCH PPS final rule, we finalized the suppression of 
the HCAHPS measure for the FY 2022 program year under Measure 
Suppression Factor 1, significant deviation in national performance on 
the measures, which could be significantly better or significantly 
worse compared to historical performance during the immediately 
preceding program years. We refer readers to the FY 2022 IPPS/LTCH PPS 
final rule for additional details and a summary of public comments we 
received related to that finalized policy (86 FR 45270 through 45271).
    In the FY 2023 IPPS/LTCH PPS proposed rule, we proposed to suppress 
the HCAHPS measure for the FY 2023 program year under Measure 
Suppression Factor 1, significant deviation in national performance on 
the measure during the COVID-19 PHE, which could be significantly 
better or significantly worse as compared to historical performance 
during the immediately preceding program years, and Measure Suppression 
Factor 4, significant national shortages or rapid or unprecedented 
changes in healthcare

[[Page 49096]]

personnel (87 FR 28427 through 28429). We would calculate hospitals' 
HCAHPS measure rates, but we would not use these measure rates to 
generate achievement, improvement, or consistency points for this 
measure.
    Additionally, because the HCAHPS measure is the only measure 
included in the Person and Family Engagement domain, we would not 
calculate hospitals' FY 2023 domain scores for the Person and Family 
Engagement domain. Participating hospitals would continue to report the 
measure data to CMS so that we can monitor the effect of the 
circumstances on quality measurement and consider appropriate policies 
in the future. We would continue to provide confidential feedback 
reports to hospitals as part of program activities to allow hospitals 
to track the changes in performance rates that we observe. We also 
intend to publicly report CY 2021 measure rate data where feasible and 
appropriately caveated. As noted in section V.I.1.a. of the preamble of 
this final rule, we believe that publicly reporting suppressed measure 
data is an important step in providing transparency and upholding the 
quality of care and safety for consumers.
    Based on our analysis of HCAHPS data from Q1 2019 to Q3 2021, we 
continue to observe a sustained decline in hospital-level HCAHPS scores 
beginning in Q2 2020. This decline is associated with the COVID-19 PHE 
in 2020 and 2021. HCAHPS measure results are publicly reported as 
``top-box'', ``bottom-box'', and ``middle-box'' scores, with ``top-
box'' being the most positive response to HCAHPS Survey items.\238\
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    \238\ Summary Analyses (hcahpsonline.org): https://www.hcahpsonline.org/en/summary-analyses/.
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    In order to determine whether the COVID-19 PHE impacted the HCAHPS 
measure for the FY 2023 program year and to what extent, we conducted 
an analysis that compared the Q1 2021, Q2 2021, and Q3 2021 HCAHPS data 
to the Q1 2019, Q2 2019, and Q3 2019 HCAHPS data.\239\ This analysis 
was similar to the analysis we conducted last year when we compared Q1 
2020 and Q2 2020 HCAHPS data to Q1 2019 and Q2 2019 HCAHPS data.\240\ 
As reflected in Table V.I.-01, this analysis showed that HCAHPS measure 
top-box scores in Q1, Q2, and Q3 2021 compared to the same quarter in 
pre-COVID-19 2019 were almost always lower. The relatively steady 
decline in HCAHPS top-box scores that began in Q2 2020 became sharper 
in Q3 2021. Compared to Q3 2019, HCAHPS scores in Q3 2021 were lower by 
1 to 4 top-box points. These changes were statistically significant for 
all HCAHPS measures in Q2 2021 and Q3 2021 at the p<0.0001 level, 
meaning that changes were too large to occur by chance more than one 
time in 10,000.\241\ These changes stand in sharp contrast to the 
pattern of generally small improvements prior to Q2 2020.
---------------------------------------------------------------------------

    \239\ We note that the COVID-19 PHE was declared on January 31, 
2020: https://www.phe.gov/emergency/news/healthactions/phe/Pages/2019-nCoV.aspx.
    \240\ As described further in the FY 2022 IPPS/LTCH PPS final 
rule, in order to detect the possible impact of the COVID-19 PHE on 
patients' experience of hospital care, we previously conducted an 
``apples-to-apples'' analysis in which we compared hospitals' HCAHPS 
measure top-box scores for each quarter between Q1 2019 and Q4 2020 
to their top-box scores for each of the same quarters one year 
earlier (86 FR 45270 through 45271). We refer readers to the FY 2022 
IPPS/LTCH PPS final rule for additional details on that analysis (86 
FR 45270 through 45271).
    \241\ Comparisons for this analysis are based on hospitals with 
at least 25 completed surveys in each of the two matched quarters.
---------------------------------------------------------------------------

    We believe that the analysis of Q1, Q2, and Q3 2021 HCAHPS scores 
indicates a pattern of significant negative changes in hospital 
performance from the immediately preceding pre-COVID-19 quarters where 
HCAHPS scores generally changed by less than 1 top-box point, sometimes 
increasing and sometimes decreasing, compared to the same quarter one 
year earlier.
[GRAPHIC] [TIFF OMITTED] TR10AU22.135

    We also proposed to suppress the HCAHPS measure for the FY 2023 
program year under Measure Suppression Factor 4, significant national 
shortage or rapid or unprecedented changes in healthcare personnel. 
During the course of the PHE, an unprecedented number of healthcare 
personnel have left the workforce or ended their employment in 
hospitals.\242\ This healthcare personnel shortage worsened in 2021, 
with hospitals across the United States reporting 296,466 days of 
critical staffing shortages, an increase of 86 percent from the 159,320 
days of critical staffing shortage hospitals reported in

[[Page 49097]]

2020.\243\ Healthcare workers, especially those in areas with higher 
infection rates, have reported serious psychological symptoms, 
including anxiety, depression, and burnout.244 245
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    \242\ Health Affairs, COVID-19's Impact on Nursing Shortages, 
The Rise of Travel Nurses, and Price Gouging (Jan. 28, 2022), 
https://www.healthaffairs.org/do/10.1377/forefront.20220125.695159/.
    \243\ https://healthdata.gov/Hospital/COVID-19-Reported-Patient-Impact-and-Hospital-Capa/g62h-syeh.
    \244\ Kriti Prasad, Colleen McLoughlin, Martin Stillman, Sara 
Poplau, Elizabeth Goelz, Sam Taylor, Nancy Nankivil, Roger Brown, 
Mark Linzer, Kyra Cappelucci, Michael Barbouche, Christine A. 
Sinsky. Prevalence and correlates of stress and burnout among U.S. 
healthcare workers during the COVID-19 pandemic: A national cross-
sectional survey study. EClinicalMedicine, Volume 35. 2021. 100879. 
ISSN 2589-5370. https://doi.org/10.1016/j.eclinm.2021.100879.
    \245\ Vizheh, M., Qorbani, M., Arzaghi, S.M. et al. The mental 
health of healthcare workers in the COVID-19 pandemic: A systematic 
review. J Diabetes Metab Disord 19, 1967-1978 (2020). https://doi.org/10.1007/s40200-020-00643-9.
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    Shortages in hospital healthcare personnel have been shown to 
affect quality of care and patient satisfaction. Studies have shown 
that hospitals with greater numbers of hospitalists treating general-
medicine patients and greater availability of nursing unit support 
services have been associated with higher levels of patient 
satisfaction.246 247 Conversely, nurse burnout has been 
linked to lower nurse-assessed quality of care \248\ and lower patient 
satisfaction.\249\ Nursing shortages have also been linked with 
negative patient perceptions of care.\250\ Therefore, we believe this 
significant national change in healthcare personnel due to the COVID-19 
PHE has significantly impacted hospitals' scores on the HCAHPS measure, 
which measures patient experience of hospital care, including staff 
responsiveness, communication with hospital staff, and cleanliness of 
the hospital environment.
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    \246\ Chen L, Birkmeyer J, Saint S, Jha A. 2013. Hospitalist 
Staffing and Patient Satisfaction in the National Medicare 
Population. Journal of Hospital Medicine, https://doi.org/10.1002/jhm.2001.
    \247\ Bacon, C.T., & Mark, B. (2009). Organizational effects on 
patient satisfaction in hospital medical-surgical units. The Journal 
of nursing administration, 39(5), 220-227. https://doi.org/10.1097/NNA.0b013e3181a23d3f.
    \248\ Aiken L, Clarke S, Sloane D. Hospital staffing, 
organization, and quality of care: cross-national findings. 
International Journal for Quality in Health Care. Int J Qual Health 
Care. 2002.10.1093/intqhc/14.1.5.
    \249\ Jeannie P. Cimiotti, et al., Nurse staffing, burnout, and 
health care-associated infection, American Journal of Infection 
Control, Volume 40, Issue 6, 2012, Pages 486-490, https://doi.org/10.1016/j.ajic.2012.02.029 (citing Vahey DC, et al., Nurse burnout 
and patient satisfaction. Med Care 2004;42:II-57-66 and Leiter MP, 
Harvie P, Frizzell C. The correspondence of patient satisfaction and 
nurse burnout. Soc Sci Med 1998;47:1611-7).
    \250\ Aiken LH, Sloane DM, Ball J, et al., Patient satisfaction 
with hospital care and nurses in England: an observational study, 
https://bmjopen.bmj.com/content/8/1/e019189.
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    Additionally, reports of hospital staff shortages have varied 
widely geographically. In January 2021, half of the hospitals in New 
Mexico and over 40 percent of the hospitals in Vermont, Rhode Island, 
West Virginia, and Arizona reported staffing shortages.\251\ 
Conversely, in that same week, less than 10 percent of hospitals in 
Washington, DC, Connecticut, Alaska, Illinois, New York, Maine, 
Montana, Idaho, Texas, South Dakota and Utah reported staffing 
shortages. Given the wide variance in reported staffing shortages, and 
the impact staffing shortages has had on HCAHPS scores, we believe our 
proposal to suppress the HCAHPS measure fairly addresses the geographic 
disparity in the impact of the COVID-19 PHE on participating hospitals.
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    \251\ U.S. News, States With the Biggest Hospital Staffing 
Shortages (Jan. 13, 2022), https://www.usnews.com/news/health-news/articles/2022-01-13/states-with-the-biggest-hospital-staffing-shortages (citing data from the HHS, CDC, and Assistant Secretary 
for Preparedness and Response Community Profile Report, updated 
frequently and available here: https://healthdata.gov/Health/COVID-19-Community-Profile-Report/gqxm-d9w9).
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    Due to the emergence of COVID-19 variants, such as the Delta 
variant, which worsened staffing shortages in Q3 and Q4 2021,\252\ we 
anticipate that Q4 2021 data will continue to demonstrate a deviation 
in national performance such that scoring this measure would not be 
representative of national or individual hospital quality of care. 
Additionally, we believe that suppressing the HCAHPS measure is 
appropriate because the impact of COVID-19 on the measure cannot be 
addressed through risk adjustment for two reasons. First, we cannot 
risk adjust the measure to exclude patients whose admissions were 
related to COVID-19 because this measure does not capture patient-level 
diagnosis data. Second, even if we could exclude patients whose 
admissions were related to COVID-19 from the measure, we believe the 
HCAHPS calculations would still be impacted because hospital staffing 
and resource issues affect a hospital's entire patient population. 
Therefore, we believe that suppressing this measure for the FY 2023 
program year will address concerns about the potential unintended 
consequences of penalizing hospitals that treated COVID-19 diagnosed 
patients.
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    \252\ Bloomberg, U.S. Hospital Staff Shortages Hit Most in a 
Year on Covid Surge, https://www.bloomberg.com/news/articles/2022-01-05/one-in-five-u-s-hospitals-face-staffing-shortages-most-in-year 
(citing HHS data).
---------------------------------------------------------------------------

    For these reasons, we proposed to suppress the HCAHPS measure for 
the FY 2023 Hospital VBP Program year for purposes of scoring and 
payment under Measure Suppression Factors 1 and 4.
    We welcomed public comment on this proposal.
    Comment: Many commenters supported our proposal to suppress the 
HCAHPS measure, agreeing with our goal of ensuring that hospitals are 
not penalized or rewarded for quality measurement that was impacted by 
the COVID-19 PHE.
    Response: We thank commenters for their support in suppressing the 
HCAHPS measure for scoring and payment purposes.
    Comment: Several commenters did not support suppressing HCAHPS 
calculations because they believe that the need for transparency was 
more important. Commenters noted that patients should be aware of 
changes in the natural environment including due to the COVID-19 PHE.
    Response: We appreciate and agree with commenters' concern about 
the need for transparency. As discussed in this final rule, although 
the HCAHPS measure is suppressed for the purposes of scoring and 
payment adjustments, we will make the data publicly available where 
feasible and appropriately caveated, recognizing the importance of 
transparency. We believe that publicly reporting these data will 
balance our responsibility to provide transparency to consumers, while 
ensuring hospitals are not unfairly scored or penalized.
    Comment: A few commenters did not support our proposal to suppress 
the HCAHPS measure for the FY 2023 program year because they believe 
that suppressing measures does not incentivize resilience, noting that 
hospitals have had two years to adapt to the pandemic.
    Response: Although we agree that building a more resilient health 
care system is necessary to avoid future threats to patient 
safety,\253\ we believe that suppressing the HCAHPS measure for the FY 
2023 program year offers hospitals the flexibility to focus on delivery 
of care while also accounting for the changing conditions during a PHE 
that are beyond hospitals' control. As we note previously, our goal is 
to resume the use of measure data for scoring and payment adjustment 
purposes beginning with the FY 2024 program year.
---------------------------------------------------------------------------

    \253\ Fleisher et al. (2022). ``Health Care Safety during the 
Pandemic and Beyond--Building a System That Ensures Resilience''. 
New England Journal of Medicine. Article available here: https://www.nejm.org/doi/full/10.1056/NEJMp2118285?utm_source=STAT+Newsletters&utm_campaign=8933b7233e-MR_COPY_01&utm_medium=email&utm_term=0_8cab1d7961-8933b7233e-151759045.
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    Comment: A commenter did not support suppressing entire data and 
reporting periods, noting widespread suppression, and instead 
recommended

[[Page 49098]]

that in the absence of rigorous statistical testing we risk-adjust for 
COVID-19 diagnosis during an encounter. A commenter did not support 
suppression of the HCAHPS measure out of concern that measure 
suppression may worsen health inequities if performance is masked.
    Response: As noted in section V.I.1.b.2 of the preamble of this 
final rule, we cannot risk-adjust the HCAHPS measure to exclude 
patients whose admissions were related to COVID-19 because this measure 
does not capture patient-level diagnosis data. However, we share the 
commenter's concern about how measure suppression may impact health 
equity. We believe that our proposal to continue publicly reporting 
suppressed measure data will provide important information that could 
assist in addressing health inequities caused or exacerbated by the 
COVID-19 PHE and maintain transparency for consumers while ensuring 
hospitals are not unfairly scored or penalized based on CY 2021 HCAHPS 
data. We note our intention to resume normal scoring for FY 2024 given 
the widespread availability of vaccines in CY 2022 as well advances in 
the treatment of COVID-19.
    After consideration of the public comments we received, we are 
finalizing our proposal to suppress the HCAHPS measure for FY 2023 for 
scoring and payment purposes as proposed. We will continue to make the 
HCAHPS data publicly available, recognizing the importance of 
transparency.
(3) Suppression of the Five Healthcare-Associated Infection (HAI) 
Safety Measures for the FY 2023 Hospital VBP Program Year
    As noted in section V.H.1.b. of the preamble of this final rule, in 
the FY 2022 IPPS/LTCH PPS final rule, we finalized the suppression of 
the five HAI Safety measures (CAUTI, CLABSI, Colon and Hysterectomy 
SSI, MRSA, and CDI) for the FY 2022 program year under Measure 
Suppression Factor 1, significant deviation in national performance on 
the measures, which could be significantly better or significantly 
worse compared to historical performance during the immediately 
preceding program years. We refer readers to the FY 2022 IPPS/LTCH PPS 
final rule for additional details on that policy and a summary of 
public comments we received related to that finalized policy (86 FR 
45272 through 45274).
    In the FY 2023 IPPS/LTCH PPS proposed rule, we proposed to suppress 
the five HAI Safety measures (CAUTI, CLABSI, Colon and Hysterectomy 
SSI, MRSA, and CDI) for the FY 2023 program year under Measure 
Suppression Factor 1, significant deviation in national performance on 
the measures, which could be significantly better or significantly 
worse compared to historical performance during the immediately 
preceding program years; Measure Suppression Factor 3, rapid or 
unprecedented changes in clinical guidelines, care delivery or 
practice, treatments, drugs, or related protocols, or equipment or 
diagnostic tools or materials; and Measure Suppression Factor 4, 
significant national shortages or rapid or unprecedented changes in 
healthcare personnel and patient case volumes (87 FR 28429 through 
28431). We are concerned that the COVID-19 PHE affected measure 
performance on the HAI measures in 2021 such that we will not be able 
to score hospitals fairly or reliably for national comparison and 
payment adjustment purposes. As part of this proposal, we would 
calculate hospitals' five HAI measure rates, but we would not use these 
measure rates to generate achievement or improvement points for these 
measures. Additionally, because these five measures make up the 
entirety of the Safety domain, we would not calculate hospitals' FY 
2023 Safety domain score. Participating hospitals would continue to 
report the measure data to the CDC and CMS so that we can monitor the 
effect of the circumstances on quality measurement and consider 
appropriate policies for the future. We would continue to provide 
confidential feedback reports to hospitals as part of program 
activities to ensure that they are made aware of the changes in 
performance rates that we observe. Though we are concerned that the 
COVID-19 PHE has affected measure performance on the HAI measures in 
2021, patient safety remains a priority in our value-based purchasing 
programs. Therefore, we also intend to publicly report CY 2021 data 
where feasible and appropriately caveated. As noted in section V.I.1.a. 
of the preamble of this final rule, we believe that publicly reporting 
suppressed measure data is an important step in providing transparency 
and upholding quality of care and safety for consumers.
    We proposed to suppress three of the five CDC NHSN HAI measures 
(CLABSI, CAUTI, and MSRA bacteremia) under Measure Suppression Factor 
1, significant deviation in national performance on the measures, which 
could be significantly better or significantly worse compared to 
historical performance during the immediately preceding program years. 
We refer readers to the FY 2022 IPPS/LTCH PPS final rule (86 FR 45272 
through 45274) for previous analysis on the HAI Safety measures that 
showed that measure rates for the CLABSI, CAUTI, and MRSA measures 
increased during the CY 2020 pandemic year as compared to the pre-
COVID-19 CY 2019 year immediately preceding the COVID-19 PHE. To 
determine whether the CLABSI, CAUTI, and MRSA measure rates would 
continue to show increases for CY 2021, the CDC analyzed changes in 
standardized infection ratios (SIRs) for Q1 and Q2 of CY 2021 as 
compared to the SIRs in Q1 and Q1 of CY 2019. This analysis found that 
the CLASBI, CAUTI, and MSRA measures had statistically significant 
measure rate increases during Q1 and Q2 of CY 2021 as compared to pre-
pandemic levels in Q1 and Q2 of CY 2019. For Q1 2021, the national SIR 
increased by approximately 45 percent for the CLABSI measure, 
approximately 12 percent for the CAUTI measure, and approximately 39 
percent for the MRSA measure as compared to Q1 2019. For Q2 2021, the 
national SIR increased by approximately 15 percent for the CLABSI 
measure and approximately 8 percent for the MRSA measure. The SIRs for 
the CAUTI measure showed no statistically significant difference for Q2 
2021 as compared to Q2 2019.

[[Page 49099]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.136

    For the CDI measure, the national SIR decreased by approximately 16 
percent for Q1 2021 as compared to Q1 2019 and by approximately 14 
percent for Q2 2021 as compared to Q2 2019. The SSI measure showed no 
significant increase or decrease during Q1 2021 and Q2 2021 as compared 
to Q1 2019 and Q2 2019. Though the changes in the national SIRs for SSI 
and CDI were not as large as compared to the other Safety domain 
measures, we proposed to suppress these measures under Measure 
Suppression Factor 4, significant national shortages or rapid or 
unprecedented changes in patient case volumes and Measure Suppression 
Factor 3, rapid or unprecedented changes in clinical guidelines, care 
delivery or practice, treatments, drugs, or related protocols, or 
equipment or diagnostic tools or materials, respectively. Specifically, 
for the SSI measure, we proposed to suppress the measure for FY 2023 
under Measure Suppression Factor 4, rapid or unprecedented changes in 
patient case volumes. We note that the SSI measure has historically had 
a low procedure volume for many hospitals, which impacts our ability to 
produce SIRs for that measure. For CY 2019, 2,087 hospitals (61 
percent) did not have sufficient procedure-level data needed to 
calculate SSI SIRs for abdominal hysterectomy, and 1,262 hospitals (37 
percent) did not have sufficient data to calculate SIRs for colon 
surgery. However, nationally, procedure volumes declined even further 
during the COVID-19 PHE in 2020, compared to 2019, with decreases of up 
to 23 percent for colon procedures and 39 percent for abdominal 
hysterectomy procedures.\254\ As of July 2021, abdominal hysterectomy 
procedures were still 6 percent below predicted levels.\255\ These 
changes in patient volumes for the SSI measure limit our ability to 
calculate SSI SIRs for hospitals that do not have sufficient data in FY 
2023, which may impact the accuracy and reliability of overall national 
comparison on performance for this measure.
---------------------------------------------------------------------------

    \254\ Weiner-Lastinger, L, et al,. The impact of coronavirus 
disease 2019 (COVID-19) on healthcare-associated infections in 2020: 
A summary of data reported to the National Healthcare Safety 
Network. Infection Control & Hospital Epidemiology (2022), 43, 12-
25. doi:10.1017/ice.2021.362.
    \255\ https://epicresearch.org/articles/elective-surgeries-approach-pre-pandemic-volumes.
---------------------------------------------------------------------------

    For the CDI measure, we proposed to suppress the measure under 
Measure Suppression Factor 3, rapid or unprecedented changes in 
clinical guidelines, care delivery or practice, related protocols, or 
equipment or diagnostic tools or materials. Pandemic-related 
improvements to typical CDI prevention practices such as hand hygiene, 
PPE practices, and environmental cleaning could have contributed to the 
declines seen in the CDI SIR in 2021 compared to 2019.\256\ In 
addition, a decline in outpatient antibiotic prescribing was observed 
starting in 2020 as healthcare utilization decreased during the COVID-
19 pandemic.\257\ This, combined with the continued use of inpatient 
antibiotic stewardship programs in hospitals, may also have contributed 
to the decline in the national CDI SIRs, as reducing patient antibiotic 
exposure is a recommended strategy for CDI prevention. More information 
about CDI prevention strategies can be found at https://www.cdc.gov/cdiff/clinicians/cdi-prevention-strategies.html.
---------------------------------------------------------------------------

    \256\ Weiner-Lastinger LM, et al. (2021). The impact of 
coronavirus disease 2019 (COVID-19) on healthcare-associated 
infections in 2020: A summary of data reported to the National 
Healthcare Safety Network. Infection Control & Hospital 
Epidemiology, https://doi.org/10.1017/ice.2021.362.
    \257\ The intersection of antibiotic resistance (AR), antibiotic 
use (AU), and COVID-19. Department of Health and Human Services 
website. https://www.hhs.gov/sites/default/files/antibiotic-resistance-antibiotic-use-covid-19-paccarb.pdf. Published February 
10, 2021. Accessed June 28, 2021.
---------------------------------------------------------------------------

    Additionally, because we cannot identify all potential elements 
that could be impacting the overall HAI experience at facilities during 
an unprecedented PHE as well as potential geographic disparities in the 
impact of the PHE that could cause uneven impact on facilities based on 
their location, and in order to reduce bias toward only those measures 
that are performing well at the national level, we believe all five CDC 
NHSN HAI measures should be suppressed. Therefore, we believe it is 
appropriate to suppress all five HAI measures in the Safety domain to 
ensure an accurate and reliable national comparison of performance on 
hospital safety.
    We also proposed to suppress the five CDC NHSN HAI measures for the 
FY 2023 program year under Measure Suppression Factor 4, significant 
national shortage or rapid or unprecedented changes in healthcare 
personnel. As discussed in section V.I.1.b.(2). Of the preamble of this 
final rule, during the course of the COVID-19 PHE, an unprecedented 
number of healthcare personnel have left the workforce or ended their 
employment in hospitals.\258\ This healthcare personnel shortage 
worsened in 2021, with hospitals across the United States reporting 
296,466 days of critical staffing shortages, an increase of 86 percent 
from the 159,320 days of critical staffing shortage hospitals reported 
in 2020.\259\ Healthcare workers, especially those in areas with higher 
infection rates, have reported serious

[[Page 49100]]

psychological symptoms, including anxiety, depression, and 
burnout.260 261
---------------------------------------------------------------------------

    \258\ Health Affairs, COVID-19's Impact on Nursing Shortages, 
The Rise of Travel Nurses, and Price Gouging (Jan. 28, 2022), 
https://www.healthaffairs.org/do/10.1377/forefront.20220125.695159/.
    \259\ https://healthdata.gov/Hospital/COVID-19-Reported-Patient-Impact-and-Hospital-Capa/g62h-syeh.
    \260\ Kriti Prasad, Colleen McLoughlin, Martin Stillman, Sara 
Poplau, Elizabeth Goelz, Sam Taylor, Nancy Nankivil, Roger Brown, 
Mark Linzer, Kyra Cappelucci, Michael Barbouche, Christine A. 
Sinsky. Prevalence and correlates of stress and burnout among U.S. 
healthcare workers during the COVID-19 pandemic: A national cross-
sectional survey study. EClinicalMedicine, Volume 35. 2021. 100879. 
ISSN 2589-5370. https://doi.org/10.1016/j.eclinm.2021.100879.
    \261\ Vizheh, M., Qorbani, M., Arzaghi, S.M. et al. The mental 
health of healthcare workers in the COVID-19 pandemic: A systematic 
review. J Diabetes Metab Disord 19, 1967-1978 (2020). https://doi.org/10.1007/s40200-020-00643-9.
---------------------------------------------------------------------------

    Healthcare personnel staffing shortages and burnout has been shown 
to be significantly associated with hospital-associated infections, 
including urinary tract infections and surgical site 
infections.262 263 Along with being shown to impact quality 
of care,\264\ healthcare staffing shortages impact a hospital's ability 
to investigate infections and take corrective action.\265\ As discussed 
in section V.I.1.b.(2). Of the preamble of this final rule, reports of 
hospital staff shortages have varied widely geographically, ranging 
from 10 to 50 percent of hospitals in any particular state reporting 
staffing shortages. Given the wide variance in reported staffing 
shortages, and the impact staffing shortages may have on CDC NHSN HAI 
scores, we believe our proposal to suppress the CDC NHSN HAI measures 
fairly addresses the geographic disparity in the impact of the COVID-19 
PHE on participating hospitals.
---------------------------------------------------------------------------

    \262\ Jeannie P. Cimiotti, et al., Nurse staffing, burnout, and 
health care-associated infection, American Journal of Infection 
Control, Volume 40, Issue 6, 2012, Pages 486-490, https://doi.org/10.1016/j.ajic.2012.02.029.
    \263\ Jinjin Shang, et al., Nurse staffing and Healthcare 
Associated Infection, Unit-level Analysis, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6478399/.
    \264\ Aiken L., Clarke S., Sloane D. Hospital staffing, 
organization, and quality of care: cross-national findings. 
International Journal for Quality in Health Care. Int J Qual Health 
Care. 2002.10.1093/intqhc/14.1.5.
    \265\ Healthcare-Associated Infections Increase Dramatically 
During Pandemic, https://www.reliasmedia.com/articles/148560-healthcare-associated-infections-increase-dramatically-during-pandemic.
---------------------------------------------------------------------------

    In the FY 2022 IPPS/LTCH PPS final rule (86 FR 45272 through 
45274), we stated our belief that the distortion in measure performance 
may be due to circumstances unique to the effects of the pandemic such 
as staffing shortages and turnover, patients that are more susceptible 
to infections due to increased hospitalization stays, and longer 
indwelling catheters and central lines. We believe that the continued 
distortion in measure performance is impacted by similar circumstances 
unique to the effects of the COVID-19 PHE as hospitals and researchers 
have investigated the impact of COVID-19 on HAIs and found that COVID-
19 is associated with increases in HAIs, with changes in the SIR 
varying geographically and over time.266 267 268 269 270 
Additionally, we believe that suppressing the HAI measures is 
appropriate because the impact of COVID-19 on the measure cannot be 
addressed through risk-adjustment. Under current collection 
requirements for the CDC NHSN HAI measures, the data used for risk 
adjustment are collected at the ward or facility level, meaning that 
the hospital submits infection data for a given ward or the entire 
facility rather than at the individual patient level. Accordingly, we 
are not able to identify the number of patients with HAIs who also had 
COVID-19 and therefore cannot risk-adjust for or otherwise account for 
COVID-19 diagnoses. In order to address the impact of the ongoing 
COVID-19 PHE on HAI incidence, we proposed to suppress the CY 2021 HAI 
measure data.
---------------------------------------------------------------------------

    \266\ Fakih M.G., et al. (2021). Coronavirus disease 2019 
(COVID-19) pandemic, central-line-associated bloodstream infection 
(CLABSI), and catheter-associated urinary tract infection (CAUTI): 
The urgent need to refocus on hardwiring prevention efforts. 
Infection Control & Hospital Epidemiology, https://doi.org/10.1017/ice.2021.70.
    \267\ Palmore T.N. and Henderson D.K. (2021). Healthcare-
associated infections during the coronavirus disease 2019 (COVID-19) 
pandemic. Infection Control & Hospital Epidemiology, https://doi.org/10.1017/ice.2021.377.
    \268\ Weiner-Lastinger L.M., et al. (2021). The impact of 
coronavirus disease 2019 (COVID-19) on healthcare-associated 
infections in 2020: A summary of data reported to the National 
Healthcare Safety Network. Infection Control & Hospital 
Epidemiology, https://doi.org/10.1017/ice.2021.362.
    \269\ Baker, Meghan A. et al. ``The Impact of COVID-19 on 
Healthcare-Associated Infections.'' Clinical infectious diseases: an 
official publication of the Infectious Diseases Society of America, 
ciab688. 9 Aug. 2021, doi:10.1093/cid/ciab688.
    \270\ Advani, Sonali D. et al. ``The impact of coronavirus 
disease 2019 (COVID-19) response on hospital infection prevention 
programs and practices in the southeastern United States.'' 
Infection control and hospital epidemiology, 1-4. 2 Nov. 2021, 
doi:10.1017/ice.2021.460.
---------------------------------------------------------------------------

    We welcomed public comment on our proposal to suppress the five HAI 
Safety domain measures for the FY 2023 program year for purposes of 
scoring and payment.
    Comment: Many commenters supported suppression of the HAI measures 
and expressed appreciation that suppression would ensure that hospitals 
are not penalized for challenges brought on by the pandemic which are 
not representative of the care generally provided.
    Response: We thank the commenters for their support of the HAI 
measure suppression proposals and we agree that suppressing these 
measures for scoring and payment purposes will ensure that hospitals 
are not penalized for impacts outside of their control.
    Comment: A few commenters recommended we continue analyzing data to 
determine whether suppressions may be necessary in future fiscal years. 
A commenter also recommended careful reintroduction of the measures at 
an appropriate time.
    Response: We thank the commenters for their recommendations, and we 
will continue to monitor the COVID-19 PHE's ongoing effects. As 
discussed in the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28433) and 
section V.I.2 of this final rule, we believe that 2022 has a more 
promising outlook in the fight against COVID-19 as we enter the third 
year of the pandemic. Our goal is to resume the use of measure data for 
scoring and payment adjustment purposes beginning with the FY 2024 
program year, given the widespread availability of vaccines and 
improvement in the treatment of COVID-19, but we will continue to 
analyze data.
    Comment: A commenter supported hospitals continuing to report the 
measure data to CDC and CMS to ensure ongoing quality improvement 
monitoring and further recommended that we use those data to assess 
whether variability in reporting (for example due to relief extended to 
providers during implicated COVID-19 reporting periods) versus 
variability in actual performance could be driving variability in HAI 
rates.
    Response: We appreciate the commenter's recommendation and agree 
that it is essential that hospitals continue to report data. The FY 
2023 program year uses data from CY 2021 for the HAI measures. There 
were no widespread data submission exceptions in CY 2021 like there 
were for Q1 and Q2 of 2020 (85 FR 54820).\271\ Therefore, we believe 
our analysis of CY 2021 data shows actual variability in performance. 
With that noted, the COVID-19 PHE has caused a variety of factors to 
impact hospital performance on the HAI measures, including but not 
limited to wide variation in case rates by geographic area at different 
points in time. Therefore, we believe the best

[[Page 49101]]

approach for the FY 2023 Hospital VBP Program is measure suppression 
for purposes of scoring and payment. However, in collaboration with the 
CDC, we will continue to collect, monitor, and analyze the HAI data, as 
well as continue publicly reporting the data with appropriate caveats 
as necessary.
---------------------------------------------------------------------------

    \271\ Centers for Medicare and Medicaid Services. (2020). CMS 
Announces Relief for Clinicians, Providers, Hospitals and Facilities 
Participating in Quality Reporting Programs in Response to COVID-19. 
Available at: https://www.cms.gov/newsroom/press-releases/cms-announces-relief-clinicians-providers-hospitals-and-facilities-participating-quality-reporting.
---------------------------------------------------------------------------

    Comment: Several commenters did not support suppression of the HAI 
measures, stating their belief that hospitals should be held 
accountable for their quality of care. A commenter did not support 
suppression of infection rates because of concerns around transparency.
    Response: As discussed in section V.I.1.a of this final rule, 
although we are finalizing our proposals to suppress the HAI measures 
for the purposes of scoring and payment adjustments for the FY 2023 
program year, we are also finalizing that we will make the data 
publicly available, recognizing the importance of transparency. We 
believe that continuing to make the data publicly available ensures 
transparency for consumers as they decide where to obtain care. We will 
also continue to provide confidential feedback reports to hospitals 
through the previously established processes as part of program 
activities to ensure that hospitals are made aware of the changes in 
performance rates that we observe and to inform their quality 
improvement activities.
    Comment: A commenter did not support suppressing entire data and 
reporting periods, noting concerns about the consequences of widespread 
suppression and that, in the absence of rigorous statistical testing, 
instead recommended we risk-adjust for COVID-19 diagnosis during an 
encounter.
    Response: We appreciate the recommendation to risk adjust for 
COVID-19 diagnosis, but we cannot risk adjust the HAI measures to 
exclude patients whose admissions were related to COVID-19 because the 
HAI measures do not capture patient-level diagnosis data. Additionally, 
we believe the HAI rates would still be impacted even with COVID-19 
risk adjustment because the PHE has affected hospital staffing and 
resource issues which impact a hospital's entire patient population, 
regardless of a COVID-19 diagnosis.
    Comment: A commenter did not support suppressing HAI measures 
because of the belief that it weakens hospitals' resilience, given that 
the Measure Suppression Factors justify suppression for a wide variety 
of environmental shifts, including changes in national performance, 
guidelines, and case mix. The commenter holds the belief that 
suppressing payment incentive programs when the environment shifts does 
not strengthen hospital resilience.
    Response: We agree that building a more resilient health care 
system is necessary to avoid future threats to patient safety.\272\ 
However, we also believe that suppressing the HAI measures for purposes 
of scoring and payment for FY 2023 balances the need to provide 
hospitals with the flexibility to focus on delivery of care without 
penalizing them for the changing conditions of the COVID-19 PHE during 
the 2021 performance period that were beyond hospitals' control and to 
maintain access to care for patients. As we noted previously, our goal 
is to resume the use of measure data for scoring and payment adjustment 
purposes beginning with the FY 2024 program year.
---------------------------------------------------------------------------

    \272\ Fleisher et al. (2022). ``Health Care Safety during the 
Pandemic and Beyond--Building a System That Ensures Resilience''. 
New England Journal of Medicine. Available at: https://www.nejm.org/doi/full/10.1056/NEJMp2118285?utm_source=STAT+Newsletters&utm_campaign=8933b7233e-MR_COPY_01&utm_medium=email&utm_term=0_8cab1d7961-8933b7233e-151759045.
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    Comment: A commenter did not support the HAI suppression proposal 
and expressed concern about the Measure Suppression Factors lacking 
sufficient definition, and thus transparency, thereby suppressing 
critically important data on hospital-acquired infection measures. A 
commenter did not support HAI suppression because it was concerned 
about CMS adhering to, interpreting, and operationalizing the Measure 
Suppression Factors given that an ever-changing landscape can be tied 
to most measures.
    Response: We appreciate the commenter's concern regarding the 
definitions of the Measure Suppression Factors. We note that the 
Measure Suppression Factors we are employing to suppress the HAI 
measures for FY 2023 in this final rule were finalized in the FY 2022 
IPPS/LTCH PPS final rule, and we did not propose any changes to those 
Measure Suppression Factors in the FY 2023 IPPS/LTCH PPS proposed rule 
(86 FR 45266 through 45269). We also note that these Measure 
Suppression Factors were developed to specifically address challenges 
that arose due to the COVID-19 PHE, and we considered what 
circumstances caused by the COVID-19 PHE would affect a quality measure 
significantly enough to warrant its suppression in the Hospital VBP 
Program. Although the landscape is ever-changing, the COVID-19 PHE 
presented unique and unprecedented experiences that challenged 
hospitals in new ways beyond their control, particularly in 2020 when 
the virus was initially identified as a global pandemic and then in 
2021 as new COVID-19 variants increased infection rates to higher 
levels than 2020 for many parts of the U.S. Due to these unique 
challenges, we believe that it would be unfair to score or penalize 
hospitals based on CY 2021 data for the HAI measures. We note our 
intention to resume normal scoring for FY 2024 given the widespread 
availability of vaccines in CY 2022 as well advances in the treatment 
of COVID-19.
    Comment: A commenter did not support HAI suppression because of the 
belief that being unable to determine the causes of changes in HAI 
rates is not a rationale for suppression. The commenter stated that, in 
light of the numerous factors that can potentially impact improvement 
on a given HAI or other outcome of interest, the commenter believes 
that CMS is focusing too much on the statistical analysis rather than 
protecting the lives and health of Medicare beneficiaries and the 
public at large. The commenter questioned whether these statistical 
analysis concerns could be used to suppress virtually all measures in 
virtually all circumstances. A commenter did not support HAI 
suppression because of the belief that the rationale exceeds CMS 
authority and recommended CMS retract its stated rationale for the 
suppression of NHSN CDC HAIs in the FY 2022 IPPS/LTCH PPS final rule.
    Response: We believe that, in the face of evolving circumstances of 
the COVID-19 PHE, the level of detail in the Measure Suppression 
Factors, which were developed and finalized in the FY 2022 IPPS/LTCH 
PPS final rule to specifically address challenges that arose due to the 
COVID-19 PHE, is sufficient and applicable in suppressing the HAI 
measures. In deciding which measures to suppress, and as discussed in 
the proposed rule and this final rule, we examined each measure and 
determined that the evidence showed significant deviation in the 
individual measure's performance data associated with the COVID-19 PHE. 
We believe hospitals' experiences during the COVID-19 PHE in 2021 with 
the rise of new COVID-19 variants have been uniquely challenging, thus 
warranting the use of Measure Suppression Factors. We note our measure-
by-measure assessment in determining the impacts of COVID-19 on each 
measure and whether we should propose to suppress a measure for scoring 
and payment

[[Page 49102]]

purposes in a pay-for-performance program or not. Ultimately, we 
determined to propose to suppress the HCAHPS and HAI measures for FY 
2023 scoring and payment purposes as discussed previously, but we did 
not propose to suppress the Medicare Spending per Beneficiary or 
Clinical Outcome measures (mortality and complications), especially if 
there were technical refinements that could be made to address COVID-19 
impacts on a measure.
    Comment: A commenter did not support HAI measure suppression 
because of a concern that suppression policies may worsen health 
inequities.
    Response: We are committed to addressing health inequities, and we 
believe that our continued requirements for the collection and 
reporting by hospitals of the HAI data to CMS via the CDC's National 
Healthcare Safety Network and proposal that we are finalizing to 
publicly report the FY 2023 program year HAI measure data will provide 
important performance information that could assist in addressing 
health inequities caused by the COVID-19 PHE while maintaining 
transparency for consumers and ensuring hospitals are not unfairly 
scored or penalized. We also believe that suppressing the HAI measures 
for purposes of scoring and payment for FY 2023 balances the need to 
provide hospitals with the flexibility to focus on delivery of care 
without penalizing them for the changing conditions of the COVID-19 PHE 
during the 2021 performance period that were beyond hospitals' control 
and to maintain access to care for patients. We note that it is our 
intent to resume normal scoring for FY 2024 given the widespread 
availability of vaccines in CY 2022 as well advances in the treatment 
of COVID-19.
    Comment: A commenter expressed concern over inconsistency in the 
citation of Measure Suppression Factors across the HAC Reduction 
Program and the Hospital VBP Program for the same measures, noting that 
it appeared to be an uneven application of the Measure Suppression 
Factor policy. The commenter recommended we find ways to adapt the 
Measure Suppression Factor policy across the programs in order to use 
the critical safety measures discussed in transparency and value-based 
purchasing.
    Response: We appreciate the commenter's concern regarding 
consistency. We believe that the Measure Suppression Factors which were 
applied for the same set of HAI measures used in the Hospital VBP 
Program and the HAC Reduction Program are relevant and aligned across 
both programs. We continue to believe that suppressing the HAI measures 
for purposes of FY 2023 scoring and payment under both the Hospital VBP 
Program and the HAC Reduction Program will continue to provide 
flexibility for providers to focus on delivering quality of care to 
patients during the COVID-19 PHE.
    After consideration of the public comments we received, we are 
finalizing our proposal to suppress the HAI measures for purposes of 
scoring and payment for FY 2023 as proposed. We will continue to make 
the HAI data publicly available, recognizing the importance of 
transparency.
c. Scoring and Payment Methodology for the FY 2023 Program Year Due to 
the COVID-19 PHE
    As described in section V.I.1.b. of the preamble of this final 
rule, we proposed to suppress six measures in the Hospital VBP Program 
for FY 2023 and use a special rule for FY 2023 scoring, which we would 
codify in our regulations at 42 CFR 412.168. Specifically, we proposed 
that we would calculate measure rates for all measures in the FY 2023 
program year. For measures for which we have finalized suppression, we 
will not use the measure rates to generate achievement and improvement 
points within the Hospital VBP Program's current scoring methodology. 
We further proposed under this special rule that we would only 
calculate achievement and improvement points, as well as a domain 
score, for remaining measures in the Clinical Outcomes domain and the 
Efficiency and Cost Reduction domain that have not been proposed for 
suppression and that, because no other domains receive scores for the 
FY 2023 program year, we would not award TPSs to any hospital for FY 
2023.
    Because no hospital would receive a TPS for FY 2023, we will reduce 
each hospital's base-operating DRG payment amount by two percent, as 
required under section 1886(o)(7)(B) of the Act, and then assign to 
each hospital a value-based incentive payment amount that matches the 
two percent reduction to the base operating DRG payment amount. The net 
result of these payment adjustments will be neutral for hospitals. We 
have stated that value-based payment systems should rely on a mix of 
standards, processes, outcomes, and patient experience measures (76 FR 
26491). As such, the Hospital VBP Program scoring methodology was 
developed to be used with several measures across multiple domains and 
aims to score hospitals on their overall achievement relative to 
national benchmarks. Unlike other hospital value-based purchasing 
programs that are intentionally designed to focus on specific aspects 
of quality, such as the HAC Reduction Program and the Hospital 
Readmissions Reduction Program, the Hospital VBP Program is uniquely 
designed to address a comprehensive set of quality and efficient 
metrics that evaluate multiple facets of quality. However, as discussed 
in the measure suppression proposals in section V.I.1.b. of the 
preamble of this final rule, the data from several measures has been 
significantly impacted by the COVID-19 PHE. Awarding negative or 
positive incentive payment adjustment percentages using TPSs calculated 
using the current scoring methodology would not provide a 
representative score of a hospitals' overall performance in providing 
quality of care during a pandemic. We believe that the current scoring 
methodology remains a balanced and comprehensive approach for tying 
payment to hospitals for their performance on a set of diverse measures 
that depict quality of care provided. However, we understand that the 
COVID-19 PHE has led to sudden and unexpected changes to healthcare 
systems. Our measure suppression policy was designed as a non-permanent 
approach to provide flexibility for changing conditions outside of 
participating hospitals' control and to avoid penalizing hospitals on 
measure scores that we believe are distorted by the COVID-19 PHE and 
are thus not truly reflective of quality of care. As we enter the third 
year of the pandemic, we believe that the updated knowledge of the 
virus and access to various treatment and mitigation efforts in place 
have provided hospitals with various tools to adapt to this virus. 
Therefore, as we discuss further in section V.I.2. of the preamble of 
this final rule, our goal is to continue resuming the use of measure 
data for scoring and payment adjustment purposes beginning with the FY 
2024 program year.
    In order to ensure that hospitals are aware of changes in their 
performance rates that we have observed, in the FY 2023 IPPS/LTCH PPS 
proposed rule, we proposed to provide FY 2023 confidential feedback 
reports that contain the measure rates we have calculated for the FY 
2023 program year, along with achievement and improvement scores for 
all the measures in the Cost and Efficiency Reduction domain and the 
Clinical Outcomes domain that have not been finalized for suppression 
and a Cost and Efficiency

[[Page 49103]]

Reduction domain and a Clinical Outcomes domain score (87 FR 28431 
through 28434). However, as previously discussed, we would not 
calculate TPSs for the purpose of adjusting hospital payments under the 
FY 2023 Hospital VBP Program. We note that the proposed special scoring 
methodology for FY 2023 generally aligns with the special scoring 
methodology finalized in for FY 2022 in the FY 2022 IPPS/LTCH PPS final 
rule (86 FR 45295 through 45296).
    In the proposed rule, we also stated our understanding that, if 
finalized, the FY 2023 special scoring and payment policy proposal for 
the Hospital VBP Program would have implications for the Merit-Based 
Incentive Payment System (MIPS) program (87 FR 28432). Under the 
facility-based measurement option within MIPS described at 42 CFR 
414.1380I, clinicians eligible for facility-based measurement may have 
their MIPS quality and cost performance category scores based on the 
Total Performance Score of the applicable hospital from the Hospital 
VBP Program as determined under 42 CFR 414.1380(e)(5). As described at 
42 CFR 414.1380(e)(1)(ii) and in the CY 2019 PFS final rule, the 
scoring methodology applicable for MIPS eligible clinicians scored with 
facility-based measurement is the Total Performance Score methodology 
adopted for the Hospital VBP Program, for the fiscal year for which 
payment begins during the applicable MIPS performance period. Thus, for 
the CY 2022 MIPS performance period/CY 2024 MIPS payment year, the 
Total Performance Score under the Hospital VBP Program for the FY 2023 
program year would be applied. If a hospital does not have a Total 
Performance Score under the Hospital VBP Program for FY 2023, facility-
based measurement would not be available for the MIPS eligible 
clinicians to whom that hospital's Total Performance Score would be 
applicable. If our proposed special scoring policy for the Hospital VBP 
Program for FY 2023 is finalized, hospitals would not have a FY 2023 
Total Performance Score, and the clinicians who would normally be 
assessed through facility-based measurement would need to identify 
another method of participating in MIPS for the CY 2022 MIPS 
performance period/CY 2024 MIPS payment year or submit an application 
for reweighting a performance category or categories, if applicable.
    We invited public comment on these proposals.
    Comment: Many commenters supported our proposed scoring and payment 
methodology for the FY 2023 program year. Commenters noted that they 
believe our approach is proactive and noted that this policy will help 
ensure providers are not penalized for impacts outside of their 
control. Commenters also expressed appreciation that we are accounting 
for the on-going effects of the COVID-19 PHE in hospitals. A commenter 
noted that they believe we struck the right balance by ensuring 
transparency of quality performance data, while at the same time, not 
penalizing hospitals when their performance scores are highly related 
to the COVID-19 PHE. A few commenters thanked us for recognizing that 
COVID-19 has significantly impacted quality measures and expressed 
support for our efforts to prevent skewed payment incentives and 
inequitable payments in the Hospital VBP Program. Commenters also 
expressed appreciation for our engagement with hospitals to gauge the 
impact of COVID-19 on individual measures and programs, and for using a 
data-driven approach to inform proposals. A few commenters noted that 
this proposed policy would provide important relief and stability for 
providers, especially rural providers, regarding compliance concerns so 
they can focus on the unique challenges of providing care during the 
COVID-19 PHE.
    Response: We thank commenters for their support, and we agree that 
the policy will help ensure that providers are not penalized for 
impacts outside of their control. We also agree that our proposed 
suppression, scoring, and payment policies for the FY 2023 program year 
were developed using data-driven approaches and are intended to balance 
the importance of patient safety through data collection, transparency, 
and public reporting while allowing hospitals to focus on maintaining 
access and providing quality health care to patients during the COVID-
19 PHE.
    Comment: Several commenters urged us to continue to carefully 
review the impact of the COVID-19 PHE and revised technical 
specifications on measure performance prior to establishing a policy 
for Hospital VBP Program payment adjustments in future years. A 
commenter encouraged us to resume full implementation of hospital 
quality programs as soon as reliable data are available for evaluating 
hospital performance because the measures used in those programs are 
intended to promote improvements in critical patient safety and quality 
of care. A few commenters also encouraged us to engage interested 
parties in developing a permanent suppression policy that could be used 
for future PHEs and to include lessons learned from the COVID-19 PHE. A 
commenter urged us to continue the suppression policy through the end 
of the PHE and noted their belief that data through at least Q2 2022 
should not be used to inform penalties under any of the quality 
programs. A commenter recommended we ignore all data from CY 2020 and 
CY 2021.
    Response: We thank commenters for these suggestions. We note that 
the current measure suppression policy, as finalized in the FY 2022 
IPPS/LTCH PPS final rule (86 FR 45266 through 45269), has been adopted 
for the duration of the COVID-19 PHE. Therefore, we may continue to 
propose to suppress measures through the end of the COVID-19 PHE if we 
determine that the Measure Suppression Factor criteria have been met 
and that quality measure data continue to be significantly impacted by 
the COVID-19 PHE. We note that we did not want to take a blanket 
approach to the suppression of CY 2020 or CY 2021 data and instead have 
analyzed CY 2020 and CY 2021 data on a measure-by-measure basis for the 
measures used in the Hospital VBP Program, and have finalized specific 
policies based on the data and technical specifications for each 
particular measure (such as specific measure suppressions and updated 
baseline periods) to appropriately address any COVID-19 impacted data 
from those time periods. For example, for certain measures we 
determined that the data did not warrant proposing to suppress for FY 
2023, such as the Medicare Spending per Beneficiary measure.
    Comment: Many commenters expressed support for providing suppressed 
measure data on hospital performance in hospital confidential feedback 
reports. Commenters noted that it is helpful to continue receiving 
these reports with measure rates, which allows hospitals to analyze 
their performance and continue focusing on performance improvements.
    Response: We thank commenters for their support and agree that 
providing hospitals with information related to measure rates for 
suppressed measures can be a useful tool in evaluating and improving 
quality of care provided. We will continue to provide confidential 
reporting of all measures, including those that are suppressed from 
scoring calculations, via the Payment Percentage Summary Report (PPSR), 
though we will not calculate domain or Total Performance Scores. 
Providing confidential measure results to hospitals also serves as an 
opportunity to preview the data before they are publicly

[[Page 49104]]

reported on the Compare tool hosted by HHS.
    Comment: Several commenters supported publicly reporting suppressed 
measure data. A few commenters noted that it is important for the 
public to have access to key hospital safety data. A commenter noted 
that timely, accurate, comprehensive, and clear public reporting of 
quality measure data is meaningful for patients. Commenters encouraged 
us to include information on the Care Compare website explaining the 
appropriate use and interpretation of the publicly reported data so 
that others, who might intend to use the data for other purposes, also 
can consider whether their intended use needs to be adjusted or 
suppressed for a time period due to COVID-19 impacts.
    Response: We appreciate commenters' support and agree that it is 
important for the public to have access to Hospital VBP Program data 
through resources such as the Compare tool to continue to make informed 
health care decisions. As noted in the preamble of the final rule and 
proposed rule, we intend to publicly report suppressed data with 
appropriate caveats that explain that performance information has been 
impacted due to the COVID-19 PHE.
    Comment: A few commenters expressed concern with the proposed 
scoring methodology for the FY 2023 program year because of the 
implications it would have for the Medicare Incentive Payment System 
(MIPS) Program for eligible clinicians. Specifically, commenters were 
concerned that clinicians eligible for facility-based measurement will 
not be able to base their MIPS quality and cost performance category 
scores on the Total Performance Score of the applicable hospital from 
the Hospital VBP Program if we finalize the special scoring methodology 
for FY 2023 as proposed. A commenter noted that some clinicians may not 
have the resources or technology to report quality measures through an 
electronic health record, registry, or quality clinical data registry 
(QCDR) and suggested that we award TPSs for FY 2023, use TPSs from 
prior years, or create a hold harmless provision to ensure that 
hospital-based clinicians are not penalized and do not receive a 
downward payment adjustment under the MIPS Program. A commenter 
requested that we align the scoring and payment policies between the 
Hospital VBP Program and the MIPS Programs such that facility-based 
providers would receive net neutral payment adjustments under the MIPS 
program as well. Another commenter suggested that we offer an automatic 
Extreme and Uncontrollable Circumstances (EUC) exception to facility-
based providers for FY 2022 to avoid impacting their cost and quality 
scores under MIPS.
    Response: We understand commenters' concerns around the 
implications the special scoring methodology for FY 2023 under the 
Hospital VBP Program would have for clinicians under MIPS. However, 
because no hospitals will have a FY 2023 Total Performance Score, the 
clinicians who are normally assessed through facility-based measurement 
will need to identify another method of participating in MIPS for the 
CY 2022 MIPS performance period/CY 2024 MIPS payment year or submit an 
EUC application \273\ to request the reweighting of one or more 
performance categories, if applicable. With regard to the commenter's 
suggestion that we award TPSs for FY 2023 or use TPSs from prior years, 
we do not believe it would be an appropriate or meaningful indication 
of quality to award hospitals TPSs under the Hospital VBP Program based 
only on the unsuppressed measures in the Efficiency and Cost Reduction 
and the Clinical Outcomes domains for the FY 2023 program year because 
we do not believe it would result in nationally comparable assessment 
of quality of care for overall hospital performance without the 
inclusion of the suppressed measures. Further, we believe that awarding 
TPSs under the Hospital VBP Program from prior years would not be 
useful, equitable, or meaningful as it would not be new information and 
could potentially cause confusion for some hospitals around their 
actual performance during the COVID-19 PHE as it would be re-using data 
from prior to the COVID-19 PHE. Additionally, any changes to the 
previously established policies for MIPS, such as commenters' 
suggestions to create a hold harmless provision to ensure that 
hospital-based clinicians are not penalized and do not receive a 
downward payment adjustment under the MIPS Program or to offer an 
automatic EUC exception, would be determined by and communicated 
through the appropriate channels for MIPS.
---------------------------------------------------------------------------

    \273\ EUC Application available at: https://qpp.cms.gov/mips/exception-applications.
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    Comment: Some commenters did not support the proposed payment 
methodology for the FY 2023 program year. A commenter expressed concern 
that the proposed special payment policy for FY 2023 that would result 
in net neutral payments for hospitals does not recognize investments in 
and on-going costs of quality infrastructure made by hospitals that 
maintained strong performance on measures prior to the COVID-19 
pandemic. This commenter suggested that we consider establishing 
alternate performance periods, such as CY 2019 or a blend of prior 
performance periods, in order to score hospitals for the FY 2023 
program year. A few commenters requested that we explore the authority 
to allow payment adjustments for hospitals that would have earned a 
positive payment adjustment for the FY 2023 program to reward hospitals 
that have demonstrated positive performance under the Hospital VBP 
Program throughout the COVID-19 PHE.
    Response: We recognize that many hospitals have made important 
investments in infrastructure and processes to improve quality of care 
both before the COVID-19 PHE and during the PHE, and we encourage 
hospitals to continue investing in quality infrastructure that improves 
delivery of care. care. Though we recognize that some hospitals have 
maintained strong performance on measures throughout the COVID-19 PHE, 
we believe COVID-19 has interfered with the ability to accurately 
compare measure performance of hospitals side-by-side on a national 
level due to the variation in the impacts of the COVID-19 PHE in 2021 
across time and across geographies, and whether that performance was 
positive or negative. Additionally, to reward hospitals that have 
improved quality of care during the PHE would require penalizing 
hospitals with negative payment adjustments based on measure scores, 
which we believe to be inappropriate given that we believe these scores 
are distorted by the COVID-19 PHE during 2021 and, thus, not reflective 
of the quality of care that the measures in the Hospital VBP Program 
were designed to assess. As noted previously in this section, we 
believe that awarding TPSs to hospitals based on prior performance 
periods would not be useful or meaningful as it would not be new 
information and could potentially cause confusion for some hospitals 
around their actual performance during the COVID-19 PHE as it would be 
re-using data from prior to the COVID-19 PHE. However, the measure data 
will continue to be publicly reported, which will provide transparency 
regarding performance during the COVID-19 PHE.
    Comment: Several commenters expressed opposition to suppressing 
measure data from public reporting. A commenter noted that it was 
firmly

[[Page 49105]]

against eliminating the reporting of patient safety measures, including 
HAI and mortality rates, because they are crucial to performance 
comparisons across healthcare facilities. A few commenters expressed 
that suppressing measure data from the public would thwart the public's 
ability to evaluate the strength and resilience of the health care 
system and make informed decisions regarding health care and public 
policy. A commenter expressed their belief that the public has a right 
to know hospital infection rates and other complication rates for 
hospitals receiving federal funding, regardless of the impact of the 
COVID-19 PHE. A few commenters noted that the suppressed measure data 
are important to keep public and could be used to inform future 
improvements in delivery of care.
    Response: We agree with commenters that hospitals should continue 
collecting and reporting suppressed measure data and that we should 
continue publicly reporting suppressed measure data, and we will 
continue to do so under the policy we are finalizing for the FY 2023 
program year. As noted in section V.I.1.a. of the preamble of this 
final rule, we believe that publicly reporting suppressed measure data 
is an important step in providing transparency.
    Comment: Several commenters did not support our proposal to 
continue publicly reporting suppressed measure data. A commenter noted 
its belief that the general public does not understand the complex 
methodology behind the publicly posted data, and the uneven impacts of 
the COVID-19 PHE across geographical area might further skew how the 
public interprets the measure data. This commenter also noted that 
enterprising organizations might continue to use the publicly reported 
data without considering the effects of the COVID-19 PHE on that data 
and unfairly penalize hospitals. Several commenters noted that 
displaying suppressed measure data will have limited value and would 
likely cause confusion or misinterpretation of quality, even with 
caveats attached. A few commenters suggested that we provide hospitals 
with the option to opt-in to public reporting as part of their 
confidential feedback review. A commenter noted that publicly reporting 
data is an additional stressor that detracts from hospitals focusing on 
other priority areas during the COVID-19 PHE. A commenter expressed its 
belief that interested parties should have the opportunity to provide 
public comments on the public reporting determination in any future 
suppression policies.
    Response: We understand commenters' concerns with publicly 
reporting suppressed measure data. However, we disagree that publicly 
reporting suppressed measure data is not useful for interested parties. 
We continue to place significant value on being as transparent as 
possible with the data we collect, and we will make clear with caveats 
that performance data were affected by the COVID-19 PHE, which impacts 
occurred in different ways and at different times of the year that we 
believe impact their national comparability for payment purposes. 
However, we believe the measures themselves remain reliable and useful 
for quality improvement purposes. Further, we disagree with the 
suggestion to allow hospitals the option to opt-in to public reporting. 
We believe that hospitals would choose to opt-in based on how well they 
performed, which could cause confusion, distorting the data and 
providing an incomplete picture of the impact of COVID-19 on 
performance. We acknowledge there may be limitations of these data, but 
believe this policy will balance our responsibility to provide 
transparency to consumers while ensuring that hospitals are not 
unfairly scored or penalized through FY 2023 payment. We encourage 
hospitals to continue focusing on providing quality care, using any 
insight they might gain from their measure rates to inform their own 
priority areas for improvement.
    Comment: A commenter urged us to consider the implications of 
exempting quarters of data from reporting on measure reliability and 
accuracy in future public reporting. This commenter urged us to perform 
measure reliability analyses, using shortened performance periods to 
ensure CMS has sufficient data to calculate performance accurately, and 
to make public the results of those analyses.
    Response: We thank the commenter for their feedback, and we wish to 
clarify that we have not proposed to exempt any quarters of measure 
data or to shorten performance periods for any measures from current or 
future reporting under the Hospital VBP Program in this rule beyond the 
exception for Q1 and Q2 of 2020 (85 FR 54820).\274\ The only measures 
still affected by the nationwide COVID-19 related Extraordinary 
Circumstances Exception (ECE) that CMS issued in March 2020 are the 
mortality and complications measures. These measures use a 36-month 
performance period, and our analyses show these measures continue to 
perform with good reliability even when calculated with 30 months of 
data. We agree that reporting reliable and accurate data are important, 
and any future policies that might impact measure reliability and 
accuracy would be accompanied by relevant and comprehensive analyses.
---------------------------------------------------------------------------

    \274\ Centers for Medicare and Medicaid Services. (2020). CMS 
Announces Relief for Clinicians, Providers, Hospitals and Facilities 
Participating in Quality Reporting Programs in Response to COVID-19. 
Available at: https://www.cms.gov/newsroom/press-releases/cms-announces-relief-clinicians-providers-hospitals-and-facilities-participating-quality-reporting.
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    After consideration of the public comments we received, we are 
finalizing the scoring and payment methodology for the FY 2023 program 
year as proposed.
2. FY 2023 Program Year Payment Details
    Section 1886(o)(7)(B) of the Act instructs the Secretary to reduce 
the base operating DRG payment amount for a hospital for each discharge 
in a fiscal year by an applicable percent. Under section 1886(o)(7)(A) 
of the Act, the sum of these reductions in a fiscal year must equal the 
total amount available for value-based incentive payments for all 
eligible hospitals for the fiscal year, as estimated by the Secretary. 
We finalized details on how we would implement these provisions in the 
FY 2013 IPPS/LTCH PPS final rule (77 FR 53571 through 53573), and we 
refer readers to that rule for further details. We note that in section 
V.I.1.b. of the preamble of this final rule, we are finalizing our 
proposal to suppress several measures in the Hospital VBP Program for 
the FY 2023 program year, and in section V.I.1.c. of the preamble of 
this final rule, we are finalizing our proposal to apply special 
scoring and payment adjustment policies for the FY 2023 program year. 
Because we are finalizing these policies, each hospital will receive 
the payment reduction for the Hospital VBP Program as required by 
statute, but every hospital will receive a value-based incentive 
payment amount that matches the payment reduction amount.
    In the FY 2023 IPPS/LTCH PPS proposed rule, we stated that if our 
proposals to suppress measures and award each hospital a value-based 
payment amount that matches the reduction to the base operating DRG 
payment amount are finalized, we would not update Table 16 as Table 16A 
in the final rule. We stated in the FY 2023 IPPS/LTCH PPS proposed rule 
that if our proposals to suppress measures and award each hospital a 
value-based payment amount that matches the reduction to the base 
operating DRG payment amount are finalized, we would also not post 
Table 16B (which

[[Page 49106]]

we typically do to display the actual value-based incentive payment 
adjustment factors, exchange function slope, and estimated amount 
available for the applicable program year, after hospitals have been 
given an opportunity to review and correct their actual TPSs). Because 
we are finalizing our proposed measure suppression and scoring and 
payment policies in response to the COVID-19 PHE, we will not post a 
Table 16A or a Table 16B.
    We continue to be concerned about the impact of the COVID-19 PHE, 
but we also remain encouraged by the rollout of COVID-19 vaccinations 
to more age groups and new antiviral treatments for those diagnosed 
with COVID-19. We also believe that hospitals are better prepared to 
treat patients with COVID-19 than they were two years ago. Our measure 
suppression policy focuses on a short-term, equitable approach during 
this unprecedented PHE, and was not intended for indefinite 
application. Additionally, we want to emphasize the long-term 
importance of value-based care and incentivizing quality care tied to 
payment. The Hospital VBP Program is an example of our long-standing 
effort to link payments to healthcare quality in the inpatient hospital 
setting.\275\
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    \275\ CMS has also partnered with the CDC in a joint Call to 
Action on safety, which is focused on our core goal to keep patients 
safe. Fleisher et al. (2022). New England Journal of Medicine. 
Article available here: https://www.nejm.org/doi/full/10.1056/NEJMp2118285?utm_source=STAT+Newsletters&utm_campaign=8933b7233e-MR_COPY_01&utm_medium=email&utm_term=0_8cab1d7961-8933b7233e-151759045.
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    We understand that the COVID-19 PHE is ongoing and unpredictable in 
nature, however, we believe that 2022 has a more promising outlook in 
the fight against COVID-19. As we enter the third year of the pandemic, 
healthcare providers have gained experience managing the disease, 
surges of COVID-19 infection, and adjusting to supply chain 
fluctuations.\276\ In 2022 and the upcoming years, we anticipate 
continued availability and increased uptake in the use of 
vaccinations,\277\ including the availability and use of vaccination 
for young children ages 5-11, who were not eligible for vaccination for 
the majority of 2021 and for whom only 36 percent had received at least 
one dose as of June 29, 2022.278 279 On June 17, 2022, the 
Food and Drug Administration (FDA) also authorized emergency use of the 
COVID-19 vaccine for children as young as 6 months old, which has 
opened up eligibility to 18 million children. 280 281
---------------------------------------------------------------------------

    \276\ McKinsey and Company. (2021). How COVID-19 is Reshaping 
Supply Chains. Available at: https://www.mckinsey.com/business-functions/operations/our-insights/how-covid-19-is-reshaping-supply-chains.
    \277\ Schneider, E. et al. (2022). The Commonwealth Fund. 
Responding to Omicron: Aggressively Increasing Booster Vaccinations 
Now Could Prevent Many Hospitalizations and Deaths. Available at: 
https://www.commonwealthfund.org/blog/2022/responding-omicron.
    \278\ KFF, Update on COVID-19 Vaccination of 5-11 Year Olds in 
the U.S., https://www.kff.org/coronavirus-covid-19/issue-brief/update-on-covid-19-vaccination-of-5-11-year-olds-in-the-u-s/.
    \279\ American Academy of Pediatrics. (2022). Summary of data 
publicly reported by the Centers for Disease Control and Prevention. 
Available at: https://www.aap.org/en/pages/2019-novel-coronavirus-covid-19-infections/children-and-covid-19-vaccination-trends/.
    \280\ Food and Drug Administration. (2022). Coronavirus (COVID-
19) Update: FDA Authorizes Moderna and Pfizer-BioNTech COVID-19 
Vaccines for Children Down to 6 Months of Age. Available at: https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-authorizes-moderna-and-pfizer-biontech-covid-19-vaccines-children.
    \281\ MacMillan, C. (2022) COVID-19 Vaccines for Kids Under 5: 
What Parents Need To Know. Available at: https://www.yalemedicine.org/news/covid-19-vaccines-kids-under-5.
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    Additionally, the FDA has expanded availability of at-home COVID-19 
treatment, having issued the first emergency use authorizations (EUAs) 
for two oral antiviral drugs for the treatment of COVID-19 in December 
2021.282 283 Finally, the Biden-Harris Administration has 
mobilized efforts to distribute home test kits,\284\ N-95 masks,\285\ 
and increase COVID-19 testing in schools,\286\ providing more treatment 
and testing to the American people. Therefore, we note that our goal is 
to continue resuming the use of measure data for scoring and payment 
adjustment purposes beginning with the FY 2024 program year. That is, 
for FY 2024, for each hospital, we would plan to calculate measure 
scores for the measures in the Hospital VBP Program for which the 
hospital reports the minimum measure requirements, as well as domain 
scores for the Hospital VBP Program domains for which the hospital 
reports the minimum number of measures. We would then calculate a TPS 
for each eligible hospital and use the established methodology for 
converting the TPSs to value-based incentive payments for the given 
fiscal year.
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    \282\ U.S. Food and Drug Administration. (2021). Coronavirus 
(COVID-19) Update: FDA Authorizes First Oral Antiviral for Treatment 
of COVID-19. Available at: https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-authorizes-first-oral-antiviral-treatment-covid-19.
    \283\ U.S. Food and Drug Administration. (2021). Coronavirus 
(COVID-19) Update: FDA Authorizes Additional Oral Antiviral for 
Treatment of COVID-19 in Certain Adults. Available at: https://
www.fda.gov/news-events/press-announcements/coronavirus-covid-19-
update-fda-authorizes-additional-oral-antiviral-treatment-covid-19-
certain#:~:text=Today%2C%20the%20U.S.%20Food%20and,progression%20to%2
0severe%20COVID%2D19%2C.
    \284\ The White House. (2022). Fact Sheet: The Biden 
Administration to Begin Distributing At-Home, Rapid COVID-19 Tests 
to Americans for Free. Available at: https://www.whitehouse.gov/briefing-room/statements-releases/2022/01/14/fact-sheet-the-biden-administration-to-begin-distributing-at-home-rapid-covid-19-tests-to-americans-for-free/.
    \285\ Miller, Z. 2021. The Washington Post. Biden to give away 
400 million N95 masks starting next week Available at: https://www.washingtonpost.com/politics/biden-to-give-away-400-million-n95-masks-starting-next-week/2022/01/19/5095c050-;7915-11ec-9dce-
7313579de434_story.html.
    \286\ The White House. (2022). FACT SHEET: Biden-Harris 
Administration Increases COVID-19 Testing in Schools to Keep 
Students Safe and Schools Open. Available at: https://www.whitehouse.gov/briefing-room/statements-releases/2022/01/12/fact-sheet-biden-harris-administration-increases-covid-19-testing-in-schools-to-keep-students-safe-and-schools-open/.
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3. Retention and Removal of Quality Measures
a. Retention of Previously Adopted Hospital VBP Program Measures and 
Relationship Between the Hospital IQR and Hospital VBP Program Measure 
Sets
    In the FY 2013 IPPS/LTCH PPS final rule (77 FR 53592), we finalized 
a policy to retain measures from prior program years for each 
successive program year, unless otherwise proposed and finalized. In 
the FY 2019 IPPS/LTCH PPS final rule (83 FR 41440 through 41441), we 
finalized a revision to our regulations at 42 CFR 412.164(a) to clarify 
that once we have complied with the statutory prerequisites for 
adopting a measure for the Hospital VBP Program, the statute does not 
require that the measure continue to remain in the Hospital IQR 
Program. We did not propose any changes to these policies in the 
proposed rule.
b. Measure Removal Factors for the Hospital VBP Program
    In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41441 through 
41446), we finalized measure removal factors for the Hospital VBP 
Program, and we refer readers to that final rule for details. We did 
not propose any changes to these policies in the proposed rule.
c. Technical Measure Specification Updates To Include Covariate 
Adjustment for COVID-19 Beginning With the FY 2023 Program Year
    In the FY 2022 IPPS/LTCH PPS final rule, we stated that we were 
updating the Hospital 30-Day, All-Cause, Risk -Standardized Mortality 
Rate Following Acute Myocardial Infarction (AMI) Hospitalization (MORT-
30-AMI), Hospital 30-Day, All-Cause, Risk-

[[Page 49107]]

Standardized Mortality Rate Following Coronary Artery Bypass Graft 
(CABG) Surgery (MORT-30-CABG), Hospital 30-Day, All-Cause, Risk-
Standardized Mortality Rate Following Chronic Obstructive Pulmonary 
Disease (COPD) Hospitalization (MORT-30 COPD), Hospital 30-Day, All-
Cause, Risk-Standardized Mortality Rate Following Heart Failure (HF) 
Hospitalization (MORT-30-HF), and Hospital-Level Risk-Standardized 
Complication Rate Following Elective Primary Total Hip Arthroplasty 
(THA) and/or Total Knee Arthroplasty (TKA) (COMP-HIP-KNEE) measures to 
exclude admissions with either a principal or secondary diagnosis of 
COVID-19 present on admission from the measure denominators beginning 
in FY 2023 (86 FR 45256 through 45258). We stated that we were making 
these updates pursuant to the technical updates policy we finalized in 
the FY 2015 IPPS/LTCH PPS final rule. Under this policy, we use a 
subregulatory process to incorporate technical measure specification 
updates into the measure specifications we have adopted for the 
Hospital VBP Program (79 FR 50077 through 50079). As we stated in the 
FY 2022 IPPS/LTCH PPS final rule, we continue to believe that this 
subregulatory process is the most expeditious manner possible to ensure 
that quality measures remain fully up to date while preserving the 
public's ability to comment on updates that so fundamentally change a 
measure that it is no longer the same measure that we originally 
adopted (84 FR 42385).
    As we continue to evaluate the effects of COVID-19 on the Hospital 
VBP Program measure set, we have observed that for some patients COVID-
19 continues to have lasting effects, including fatigue, cough, 
palpitations, and others potentially related to organ damage, post 
viral syndrome, post-critical care syndrome or other reasons.\287\ 
These clinical conditions could affect a patient's risk of mortality or 
complications following an index admission and, as a result, impact a 
hospital's performance on one or more of the four condition-specific 
mortality measures or the procedure-specific complication measure 
included in the Hospital VBP Program. In order to account for case mix 
among hospitals, the current risk adjustment approach for these 
measures include covariates for clinical comorbidities present on 
admission (POA) and in the 12 months prior to the index admission that 
are relevant and have relationships with the outcome, for example 
patient history of coronary artery bypass (CABG) surgery or history of 
mechanical ventilation. In accordance with the principles used during 
measure development and to adequately account for patient case mix, we 
are further modifying the technical measure specifications for the 
MORT-30-AMI, MORT-30-CABG, MORT-30-COPD, MORT-30-HF, and COMP-HIP-KNEE 
measures to include a covariate adjustment for patient history of 
COVID-19 in the 12 months prior to the admission.
---------------------------------------------------------------------------

    \287\ Raveendran, A.V., Jayadevan, R. and Sashidharan, S., Long 
COVID: An overview. Available at https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8056514/. Accessed on December 15, 2021.
---------------------------------------------------------------------------

    This inclusion of the covariate adjustment for patient history of 
COVID-19 in the 12 months prior to the admission will be effective 
beginning with the FY 2023 program year for the MORT-30-AMI, MORT-30-
CABG, MORT-30-COPD, MORT-30-HF, and COMP-HIP-KNEE measures. We will 
also include the covariate adjustment for patient history of COVID-19 
in the 12 months prior to the admission for the Hospital 30-Day, All-
Cause, Risk-Standardized Mortality Rate Following Pneumonia 
Hospitalization (MORT-30-PN) measure. We note that, even though we 
previously finalized that we would suppress the MORT-30-PN measure for 
the FY 2023 program year, we would still publicly report the measure, 
and therefore, the inclusion of the covariate adjustment for patient 
history of COVID-19 in the 12 months prior to the admission will still 
be effective beginning with the FY 2023 program year. We will delay 
sending MORT-30-PN confidential hospital feedback reports until October 
2022 and delay public reporting until January 2023 to allow time for 
hospitals to become informed about this measure update and their 
hospital-level results. We will resume including hospital performance 
on the MORT-30-PN measure in the payment adjustment calculations, using 
the updated MORT-30-PN measure, beginning in FY 2024. We believe that 
making these updates to the MORT-30-PN measure for FY 2023 in 
hospitals' confidential feedback reports will allow hospitals the 
opportunity to preview these updates to the measure specifications in 
FY 2023 before they are used as part of payment adjustments for the FY 
2024 program year.
    For more information on the application of covariate adjustments, 
including the technical updates we are announcing in this final rule, 
please see the Measure Updates and Specifications Reports (available at 
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology).
    Comment: Many commenters strongly supported the inclusion of 
patient history of COVID-19 in the 12 months prior to the index 
hospitalization as a covariate in the measures' risk adjustment models 
for the Hospital VBP Program mortality and complication measures 
starting in FY 2023. One of these commenters specifically agreed that a 
history of COVID-19 could affect a patient's risk for readmission and 
mortality. Another commenter added that the covariate for history of 
COVID-19 infection could allow tracking and better understanding of the 
effect of `long COVID' on hospital performance and inform other 
potential pay for performance program changes, if indicated by the 
data. A few commenters stated that this update to risk-adjust measures 
for COVID-19 will be helpful to their healthcare organizations in 
particular, to prevent being unfairly penalized for caring for a high 
volume of COVID-19 patients.
    Response: We thank the commenters for their support for the 
inclusion of a covariate adjustment for patient history of COVID-19 in 
the 12 months prior to the admission for the mortality and complication 
measures included in the Hospital VBP Program.
    Comment: Among commenters who supported the technical update to the 
measure specifications for MORT-30-AMI, MORT-30-CABG, MORT-30-COPD, 
MORT-30-HF, MORT-30 PN and COMP-HIP-KNEE measures to include a 
covariate adjustment for patient history of COVID-19 in the 12 months 
prior to the admission, several commenters also strongly encouraged us 
to continue monitoring and evaluating the data to assess the full 
impact of COVID-19 on hospital operations, quality measures, and most 
importantly on patient health and outcomes, as the impact of `long 
COVID' is still unknown. A few commenters urged us to continue to 
assess the measures' risk adjustment to determine if a 12-month period 
fully accounts for the impacts of `long COVID-19' on these mortality 
measures. Another commenter noted that the most recent measure 
methodology reports show that history of COVID-19 is negatively 
correlated for outcomes measured for the five conditions in the domain 
for FY 2023. This commenter recommended that we only include the 
covariate adjustment for measures where it is a positive risk variable 
for the performance period in line with the proposal's intended 
recognition that history of COVID-19 could affect a patient's risk of 
mortality or complications.

[[Page 49108]]

    Response: With regard to the rationale for adding the history of 
COVID-19 covariate to the model, analyses using data from 7/1/2020-2/
28/2021 showed that for most of the mortality measures observed 
(unadjusted), 30-day mortality for patients without an index admission 
of COVID-19, but with a history of COVID-19 (defined as U07.1 or Z86.16 
in the 12 months prior to the admission, or Z86.16 at the index 
admission), were higher than patients without a history of COVID-19. 
Based on the higher odds of death for these patients we decided to add 
the covariate across all of the condition- and procedure-specific 
mortality and complications measures in Hospital VBP Program. In the 
months since the publication of the FY 2023 IPPS/LTCH PPS proposed 
rule, we have analyzed newly available data and are providing updated 
information in this final rule. Specifically, results using more recent 
data spanning the entire 3-year reporting period (7/1/2018-6/30/2021) 
showed that for patients without an index admission of COVID-19, those 
with a history of COVID-19 (as defined in technical update) in the 
pneumonia and heart failure cohorts have much higher frequencies of 
some model risk variables compared with patients without a history of 
COVID-19, suggesting they are sicker.
    We also found that the adjusted odds ratios for 30-day mortality 
for the history of COVID-19 variable (the odds ratios in the context of 
all of the variables in the model) are less than one (for all but the 
pneumonia mortality measure, where the odds of mortality are not 
statistically significant). In other words, in these patients without 
COVID-19, but with a history of COVID-19, the non-COVID-19 clinical 
comorbidities in the risk model are lessening or reversing the effect 
size of the history of COVID-19 variable. Nonetheless, we have decided 
to keep the history of COVID-19 covariate in the model along with the 
model's baseline risk factors in order to account for hospital case mix 
differences more effectively and for potential future impacts of long 
COVID-19 that the current measure does not currently account for.
    Comment: Several commenters, while supportive of the technical 
update to incorporate a history of COVID-19 into the measures' risk 
adjustment models, raised concerns about the adequacy of the current 
codes and reliability of the existing data. A few of them specifically 
expressed concern that the covariate adjustment methodology which 
relies on the U07.1 or Z86.16 ICD-10-CM codes may not fully capture all 
patients who have had a history of COVID-19 and recommended further 
evaluation of additional codes or claims data. The commenters also 
suggested that the covariate adjustment methodology be reviewed by a 
special NQF Technical Expert Panel (TEP) to ensure that the adjustments 
are comprehensive enough to capture the long-term impacts of COVID-19.
    Response: We appreciate commenters' concern about the adequacy of 
the current codes, and the implementation of the covariate in the 
model. Regarding coding adequacy, the history of COVID-19 variable is 
defined as U07.1 (COVID-19) or Z86.16 (personal history of COVID-1) in 
the 12 months prior to the admission, or Z86.16 at the index admission. 
Therefore, the history of COVID-19 variable does not rely solely on the 
COVID-19-specific ICD-10 code, U07.1, but also includes the ``personal 
history of COVID'' code (Z86.16) which hospitals can code even during 
the index encounter. With regard to additional variables related to a 
prior COVID-19 infection, we note that on October 1, 2021, the ICD-10 
code U09.9 (Post COVID-19 condition, unspecified) was approved for 
implementation, which is another code that can be examined for future 
use in risk adjustment.
    We thank commenters for their suggestion that a special NQF TEP 
review the covariate adjustment methodology to ensure that the 
adjustments are comprehensive enough to capture the long-term impacts 
of COVID-19. These changes to the measure, if permanent, will be 
reviewed by the NQF during the endorsement maintenance process. We will 
also continue to monitor the claims data and review the covariate 
adjustment methodology to evaluate the effect of history of COVID-19 on 
these quality measures and to determine appropriate policies in the 
future.
    Comment: A few commenters supported the inclusion of patient 
history of COVID-19 in the 12 months prior to the index hospitalization 
as a covariate in the measures' risk adjustment models for the Hospital 
VBP Program mortality and complication measures starting in FY 2023 but 
urged us to conduct further analysis before implementing this change to 
ensure prior COVID-19 data are captured across hospitals in a complete, 
consistent, and equitable way. The commenters specifically urged us to 
examine and share publicly any data on variation in how prior COVID-19 
is being captured in claims data. They also encouraged us to explore to 
what extent history of COVID-19 codes are capturing COVID-19 self-
testing that patients may perform at home, and how frequently those 
codes are being used. The commenters also expressed concern that 
relying on the history of COVID-19 code could leave out a substantial 
portion of patients that may have had COVID-19, but did not get tested 
in an inpatient or ambulatory setting in the prior 12 months. Lastly, 
they recommended we continue to monitor the evolving evidence around 
post COVID-19 conditions to determine whether the 12-month timeframe 
should be lengthened or shortened. As the field continues to learn more 
about the ways in which `long COVID' manifests itself, and the duration 
of its impacts, these commenters stated that our current approach may 
need to change.
    Response: We appreciate commenters' recommendations regarding 
conducting further analysis to ensure prior COVID-19 data are captured 
across hospitals in a complete, consistent, and equitable way. The 
history of COVID-19 variable is defined as U07.1 (COVID-19) or Z86.16 
(personal history of COVID-1) in the 12 months prior to the admission, 
or Z86.16 at the index admission. Therefore, the history of COVID-19 
variable does not rely solely on the COVID-19-specific ICD-10 code, 
U07.1, but also includes the ``personal history of COVID'' code 
(Z86.16) which hospitals can code even during the index encounter. With 
regard to additional variables related to a prior COVID-19 infection, 
we note that on October 1, 2021, the CDC's National Center for Health 
Statistics implemented the ICD-10 code U09.9 (Post COVID-19 condition, 
unspecified), which is another code that can be examined for future use 
in risk adjustment. We will continue monitoring and evaluating 
additional data as they become available to understand the full impact 
of COVID-19 on healthcare organizations and patients to inform future 
program decisions.
    Comment: A few commenters did not support risk adjusting for COVID-
19 diagnosis within the condition- and procedure-specific mortality and 
complication Hospital VBP Program measures. They recommended adjusting 
the benchmarks instead for the achievement thresholds as well as 
reestablishing baselines inclusive of COVID-19 diagnosis. They also 
stated that the COVID-19 virus became a part of normal infection 
prevention care, and therefore its inclusion would inherently risk 
adjust the 2022 baseline for 2024 outcome data, effectively and 
appropriately leveling the playing field to the new normal.
    Response: We interpret the commenter's statement to be referring to

[[Page 49109]]

adjustment of an index admission of COVID-19 and not a history of 
COVID-19, and therefore, we note that COVID-19 admissions have been 
excluded from the cohorts of these measures as outlined in the FY 2022 
IPPS/LTCH PPS final rule (86 FR 45256 through 45258). We thank 
commenters for their feedback. We will implement the inclusion of the 
covariate adjustment for patient history of COVID-19 in the 12 months 
prior to the admission effective beginning with the FY 2023 program 
year for the MORT-30-AMI, MORT-30-CABG, MORT-30-COPD, MORT-30-HF, MORT-
30-PN and COMP-HIP-KNEE measures.
d. Technical Updates to the Specifications for the MORT-30-PN Measure 
Beginning With the FY 2024 Program Year
    In the FY 2022 IPPS/LTCH PPS final rule, pursuant to the measure 
suppression policy finalized in that rule and described in section 
V.I.1. of the preamble of this final rule, we finalized suppression of 
the MORT-30-PN measure (NQF #0468) for the FY 2023 program year (86 FR 
45274 through 45276), and we refer readers to that final rule for 
additional information.
    Since the publication of the FY 2022 IPPS/LTCH PPS final rule, we 
have continued to monitor the MORT-30-PN measure and have found that 
several factors, such as improved coding practices and decreased 
proportion of COVID-19 admissions for the MORT-30-PN cohort, have 
mitigated some of the impact of COVID-19 on this measure within certain 
data periods. Beginning in FY 2024 the MORT-30-PN measure will no 
longer be suppressed under the Hospital VBP Program. We are resuming 
the use of the MORT-30-PN measure for FY 2024 because of the following 
differences between the FY 2023 and FY 2024 performance periods: (1) 
the improved coding practices; (2) decreased proportion of COVID-19 
admissions in the MORT-30-PN measure for this performance period; and 
(3) sufficient available data to make technical updates to the measure 
specifications in order to further account for how patients with a 
COVID-19 diagnosis might impact the quality of care assessed by this 
measure. Specifically, effective January 2021 the ICD10 code J12.82, 
Pneumonia due to coronavirus disease 2019, was added for use as a 
secondary diagnosis, along with a principal diagnosis of COVID-19 
(U07.1), to identify patients with COVID-19 pneumonia. J12.82 is not 
included within the cohort of the MORT-30-PN measure, therefore 
mortality rates with pneumonia due to COVID-19 are not captured by this 
measure as of January 1, 2021. Whenever new codes are introduced, 
changes in coding practices are difficult to predict. At the time of 
the FY 2022 IPPS/LTCH PPS final rule, we did not have sufficient data 
to determine the effects of these coding changes on the proportion of 
COVID-19 patients and mortality rates with pneumonia due to COVID-19 in 
the MORT-30-PN measure. As additional months of data have become 
available since early 2021, we have now seen increased use of these 
codes. Secondly, as these coding changes have occurred and as the 
COVID-19 PHE has evolved, more recent data show the proportion of 
COVID-19 admissions in the MORT-30-PN measure have decreased compared 
to 2020 data. Finally, with the availability of additional data and the 
decrease in the proportion COVID-19 admissions in the MORT-30-PN 
measure, we are now able to make technical updates to the measure 
specifications in alignment with the technical updates we are making to 
four other mortality measures and one complication measure. 
Specifically, we are updating the technical specifications for the 
MORT-30-PN measure to exclude patients with either principal or 
secondary diagnoses of COVID-19 from the measure denominator beginning 
with the FY 2024 program year.
    We are also updating the technical specifications for the MORT-30-
PN measure to add a covariate that adjusts the measure outcome for a 
history of COVID-19 diagnosis in the 12 months prior to the admission 
(as discussed in section V.I.3.c. of the preamble of this final rule) 
and ensures alignment with the other four mortality and one 
complication measures. In our analysis, hospital-level MORT-30-PN 
measure scores calculated with the cohort and denominator exclusions 
and the addition of the covariate for a history of COVID-19 diagnosis 
in the 12 months prior (using data from July 1, 2018 through June 30, 
2021, excluding admissions from December 2, 2019 through June 30, 2020 
to apply the nationwide ECE granted due to the COVID-19 PHE (85 FR 
54833 through 54835)), resulted in mean measure scores that were closer 
to the prior pre-COVID-19 period (July 1, 2017- through December 2, 
2019) compared with the unchanged measure. We believe that excluding 
COVID-19 patients from the measure denominator, in addition to 
adjusting for a prior infection with COVID-19, will mitigate the impact 
of COVID-19 on this measure as much as is currently feasibly possible 
given the unpredictable nature of the pandemic, and ensure that this 
measure continues to reflect mortality rates as intended and meet the 
goals of the Hospital VBP Program beginning in FY 2024. We note that 
the MORT-30-PN measure uses three years of data. The performance period 
for the FY 2023 program year includes admissions from July 1, 2018 
through June 30, 2021, exclusive of January 1, 2020 through June 30, 
2020 data excluded due to the ECE waiver. Therefore, we continue to 
believe it is appropriate to suppress the currently implemented measure 
for use in payment calculations as finalized in the FY 2022 IPPS/LTCH 
PPS final rule (86 FR 45274 through 45276). The MORT-30-PN measure is 
also included in confidential feedback reports and public reporting on 
CMS' Care Compare website separate from the Hospital VBP Program use of 
the measure. Technical specifications of the Hospital VBP Program 
measures are provided on our website under the Measure Methodology 
Reports section (available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.html). Additional resources about the measure 
technical specifications and methodology for the Hospital VBP Program 
are on the QualityNet website (available at https://qualitynet.cms.gov/inpatient/hvbp).
    Comment: Many commenters supported the technical updates to the 
MORT-30-PN measure to exclude admissions with either a principal or 
secondary diagnosis of COVID-19 present on admission from the measure 
denominator and to include a covariate for history of COVID-19 in the 
12 months prior to admission. A commenter supported resuming the MORT-
30-PN measure in the Hospital VBP Program in FY 2024. A few commenters 
also applauded our decision to publicly report the measure in January 
2023 (2022 reporting period), even though the measure will be 
suppressed for FY 2023.
    Response: We appreciate commenters' support. We note that the MORT-
30-PN measure is suppressed in the Hospital VBP Program for FY 2023 and 
will resume in FY 2024. The October 2022 confidential reporting and 
January 2023 public reporting of the updated measure is to provide 
transparency and information to providers and patients on this 
important measure.
    Comment: Many commenters supported the technical updates to the 
MORT-30-PN measure but urged us not to resume the use of this measure 
in the Hospital VBP Program for FY 2024 and to further evaluate the 
impact of

[[Page 49110]]

COVID-19 prior to resuming this measure. A commenter added that with 
these technical updates, the measure when considered in isolation 
appears to be structured appropriately to return to use in the Hospital 
VBP Program for FY 2024. However, we should consider the combined 
effects of the multiple program adjustments that have been made that 
would affect FY 2024 payment year determinations. The commenter 
recommended that we seriously consider the combined effects of data 
suppression and shortened performance period, along with any lingering 
impacts of COVID-19 that are uncovered by our monitoring in the 
interval prior to FY 2024 proposed rulemaking, in determining whether 
to again apply scoring and payment adjustments for FY 2024 payment 
determinations.
    A few commenters recommended we conduct further analysis to ensure 
it has minimized the overlap between this measure and COVID-19-related 
pneumonia. The commenters also agree that these specification changes 
are directionally appropriate, and data included in the proposed rule 
shows a decline in the percentage of pneumonia patients with COVID-19 
from January-July 2021. However, the commenters noted there were 
upticks in these percentages in August and September 2021 and suggested 
we run the same data for the entirety of 2021 to ensure these increases 
are anomalies rather than trends before re-introducing the MORT-30-PN 
measure into the Hospital VBP Program. This would enable agencies and 
the hospitals to determine whether additional education on the new 
codes is necessary, or if further measure specification tweaks may be 
required.
    Response: We thank commenters for their feedback to conduct further 
evaluation of data and monitor the impact of COVID-19 before resuming 
the MORT-30-PN measure. Admissions for patients with a COVID-19 
diagnosis will be removed from the measure, which means that the 
``upticks'' in the percentage of COVID-19 admissions in the unmodified 
measure will not impact the cohort for the revised MORT-30-PN measure. 
As previously stated, our goal is to resume the use of measure data for 
scoring and payment adjustment purposes beginning with the FY 2024 
program year. The October 2022 confidential reporting and January 2023 
public reporting of the updated measure is to provide transparency and 
information to providers and patients on this important measure. 
Additionally, while we shortened the performance period for certain 
measures under the nationwide COVID-19 ECE, analyses show that the 
measures have a good reliability even when using a 30-month period 
versus a 36-month period.
e. Summary of Previously Adopted Measures for FY 2023 Through FY 2026 
Program Years
    We refer readers to the FY 2022 IPPS/LTCH PPS final rule (86 FR 
45281 through 45284) for summaries of previously adopted measures for 
the FY 2024 and FY 2025 program years, and to Table V.I.-03 in this 
section of the final rule showing summaries of previously adopted 
measures for the FY 2024, FY 2025, and FY 2026 program years. We 
proposed to suppress the HCAHPS and HAI measures for the FY 2023 
program year. We did not propose to add new measures at this time. The 
Hospital VBP Program measure set for the FY 2023, FY 2024, FY 2025, and 
FY 2026 program years would contain the following measures:

[[Page 49111]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.137

4. Previously Adopted Baseline and Performance Periods
a. Background
    Section 1886(o)(4) of the Act requires the Secretary to establish a 
performance period for the Hospital VBP Program that begins and ends 
prior to the beginning of such fiscal year. We refer readers to the FY 
2017 IPPS/LTCH PPS final rule (81 FR 56998 through 57003) for a 
previously finalized schedule for all future baseline and performance 
periods for previously adopted measures. We refer readers to the FY 
2018 IPPS/LTCH PPS final rule (82 FR 38256 through 38261), the FY 2019 
IPPS/LTCH PPS final rule (83 FR 41466 through 41469), the FY 2020 IPPS/
LTCH PPS final rule (84 FR 42393 through 42395), the FY 2021 IPPS/LTCH 
PPS final rule (85 FR 58850 through 58854), and FY 2022 IPPS/LTCH PPS 
final rule (86 FR 45284 through 45290) for additional previously 
adopted baseline and performance periods for the FY 2024 and subsequent 
program years.
b. Updated Baseline Periods for Certain Measures Due to the COVID-19 
PHE
(1) Background
    We previously finalized baseline periods for the FY 2024, 2025, 
2026, 2027, and 2028 program years for all the measures included in the 
Hospital VBP Program, and we refer readers to Tables V.I.-04 through 
V.I.-08 for those previously adopted baseline periods. However, 
subsequent to finalizing those baseline periods and, as described 
further in section V.I.1.b. of the preamble of this final rule, we 
proposed to suppress the HCAHPS and five HAI measures for the purposes 
of scoring and payment for FY 2023. Because these baseline periods are 
used to determine achievement thresholds and are used in awarding 
improvement scores to hospitals, we are concerned with using COVID-19 
impacted data for the FY 2025 baseline periods for scoring and payment 
purposes.
    Accordingly, to ensure that we have reliable data that are not 
unfairly affected by the COVID-19 PHE for baselining purposes, we 
proposed several updates to the baseline periods in this final rule for 
the FY 2025 program year.
    We note that we proposed to update the baseline periods for certain 
measures under the Hospital VBP Program that have a 1-year baseline 
period. However, for measures that have baseline periods that span 
across multiple years, we believe the previously established baseline 
periods provide enough data from before and after CY 2021 to still 
calculate baseline

[[Page 49112]]

scores that would be reliable for scoring and payment purposes. 
Specifically, for the measures in the Clinical Outcomes domain (MORT-
30-AMI, MORT-30-CABG, MORT-30-COPD, MORT-30-HF, MORT-30-PN, and COMP-
HIP-KNEE), which have 36-month baseline periods, we did not propose any 
changes to the previously established baseline periods for FY 2025.
(2) Updated FY 2025 Baseline Period for the Person and Community 
Engagement Domain Measure (HCAHPS Survey)
    In the FY 2017 IPPS/LTCH PPS final rule, we finalized that the 
baseline period for Person and Community Engagement Domain Measure 
(HCAHPS Survey) for the FY 2025 program year would be January 1, 2021 
through December 31, 2021 (81 FR 56998). However, as more fully 
described in section V.I.1.b. of the preamble of this final rule, we 
have determined that the top-box scores for hospitals are significantly 
lower in Q1 and Q2 of CY 2021 than they were in Q1 and Q2 of CY 2019 
(pre-pandemic), demonstrating the impact of COVID-19 on hospital 
performance for this measure. Therefore, in order to best mitigate the 
impact of using measure data affected by the COVID-19 PHE when 
determining achievement thresholds or awarding improvement points, we 
proposed to use a baseline period of January 1, 2019 through December 
31, 2019 for the FY 2025 program year. This baseline period would be 
paired with a performance period of January 1, 2023 through December 
31, 2023. We believe using data from this period will provide 
sufficiently reliable data for evaluating hospital performance that can 
be used for FY 2025 scoring. We are selecting this revised data period 
because it would provide the most consistency for hospitals in terms of 
the comparable length to previous program years and the performance 
period, and it would capture a full year of data, including any 
seasonal effects.
    Comment: Many commenters supported our proposal to establish new 
baseline periods for the HCAHPS measure, which has been impacted by the 
COVID-19 PHE. Commenters appreciated that our proposal would allow us 
to use a full-year of data unaffected by the COVID-19 PHE to compare to 
the CY 2023 performance period.
    Response: We thank the commenters for their support of our proposal 
to update the baseline period for the HCAHPS measure for the FY 2025 
program year.
    Comment: A few commenters recommended that we continue to evaluate 
the impact of the pandemic as they set future policy and program 
adjustments related to baseline periods and performance standards.
    Response: We appreciate the commenters' suggestions and note that 
we will continue to monitor the impact of the COVID-19 PHE on Hospital 
VBP Program data.
    Comment: A commenter did not support our proposal for the HCAHPS 
2019 baseline period, stating its belief that the proposed baseline is 
not reflective of current operations, safety protocols, and staffing. 
Instead, the commenter recommended we explore using alternative 
baseline periods, such as using all or part of CY 2021 or CY 2022 
performance data as the baseline or using CY 2023 as both the baseline 
period and the performance period. The commenter also urged us to 
consider ways to modify the scoring policies for FY 2025 to incentivize 
improvement over achievement.
    Response: We thank the commenter for the recommendation and note 
that we have chosen the 2019 baseline period to ensure that we have 
reliable data that are not unfairly affected by the COVID-19 PHE. We 
believe using data from this period will provide sufficiently reliable 
data for evaluating hospital performance that can be used for FY 2025 
scoring and because it would provide the most consistency for hospitals 
in terms of the comparable length to previous program years and the 
performance period. Because the pandemic has impacted hospitals and 
health systems in many different ways, and at different times, using an 
alternative baseline may unfairly penalize certain hospitals for 
circumstances out of their control. We do not believe it would be 
appropriate to use CY 2021 data as the baseline period because, as 
noted in section V.I.1.b.(2). of this final rule, we are finalizing the 
suppression the FY 2022 HCAHPS performance period, which uses CY 2021 
data, because we believe that data has been impacted by the COVID-19 
PHE. We note that we would not be able to use CY 2022 or CY 2023 data 
as the baseline period for the FY 2025 program year due to the 
operational time it takes to calculate performance standards and we 
would not be able to notify hospitals of the performance standards 60 
days prior to the beginning of the performance period. Further, we 
believe that the current scoring methodology, which takes the higher of 
the improvement and achievement scores for a given measure, 
incentivizes hospitals to improve, while also incentivizing hospitals 
to continue striving for standards of care that would result in high 
quality of care.
    Comment: A commenter did not support the proposed baseline period 
for the HCAHPS measure for the FY 2025 program year because it excludes 
COVID-19 data. The commenter recommended adjusting benchmarks and 
baselines to include COVID-19 diagnoses in the measure data, noting its 
belief that the COVID-19 virus has become part of normal infection 
prevention care and its inclusion would inherently risk adjust the 2022 
baseline for 2024 outcome data.
    Response: We appreciate the commenter's recommendation, but we 
believe it is not appropriate to use 2021 as the baseline because 
conditions related to the COVID-19 PHE in 2021 were not alike across 
the country, with some hospitals experiencing more staff shortages than 
others and geographic disparities in COVID-19 cases, with certain parts 
of the country experiencing more cases and greater strains on their 
health systems than others. Such conditions may have been out of their 
control and using a 2021 baseline would thus unfairly penalize the 
hospitals disproportionately impacted. Our proposed suppression, 
scoring, payment, and updated baseline policies have been developed to 
provide as much flexibility as we can for providers to focus on 
delivering care during the COVID-19 PHE. We intend to continue to 
consider the evolving COVID-19 PHE while also evaluating future 
policies so as to continue incentivizing hospitals to prioritize high 
quality of care for patients.
    After consideration of the public comments we received, we are 
finalizing our proposal to update the baseline period for the HCAHPS 
measure for FY 2025 as proposed.
(3) Updated FY 2025 Baseline Period for the Safety Domain Measures
    In the FY 2017 IPPS/LTCH PPS final rule (81 FR 57000), we finalized 
the performance period for all measures in the Safety domain to run on 
the calendar year two years prior to the applicable program year and a 
baseline period that runs on the calendar year four years prior to the 
applicable program year for the FY 2019 program year and subsequent 
program years. For FY 2025, the baseline period for the Safety domain 
measures would be January 1, 2021 through December 31, 2021. However, 
as more fully described in section V.I.1.b. of the preamble of this 
final rule, we have determined that the national measure rates for the 
HAI measures have significantly deviated in national performance in CY 
2021,

[[Page 49113]]

indicating that the COVID-19 PHE has impacted performance on this 
measure. Therefore, in order to mitigate the impact of using measure 
data affected by the COVID-19 PHE when determining achievement 
thresholds or awarding improvement points, we proposed to use a 
baseline period of January 1, 2019 through December 31, 2019 for the FY 
2025 program year. This baseline period would be paired with a 
performance period of January 1, 2023 through December 31, 2023. We 
believe using data from this period will provide sufficiently reliable 
data for evaluating hospital performance that can be used for FY 2025 
scoring. We are selecting this revised data period because it would 
provide the most consistency for hospitals in terms of the comparable 
length to previous program years and the performance period, and it 
would capture a full year of data, including any seasonal effects.
    Comment: Many commenters supported our proposal to use updated 
baseline periods for the Safety Domain measures due to the COVID-19 
pandemic, noting that it would allow us to use a full-year of data 
unaffected by the COVID-19 PHE to compare to the CY 2023 performance 
period. A few commenters recommended that we consider the impact of 
COVID-19 in future policies.
    Response: We thank the commenters for their support of the updated 
baseline periods for the Safety Domain measures. We will continue to 
monitor the impact of the PHE on program data and will take commenters' 
concerns and recommendations under consideration for future rulemaking.
    Comment: A commenter did not support our proposal to use CY 2019 as 
the updated baseline period for each of the Safety Domain measures 
because the commenter believes the updated baseline periods are not 
reflective of current operations and recommended we explore alternative 
baseline periods. A commenter did not support our proposal because the 
baseline periods exclude COVID-19 data and the commenter believes that 
the pandemic has become a part of normal infection prevention care and 
should thus be included in the 2022 baseline period for 2024 outcome 
data.
    Response: We appreciate the commenter's recommendation, but we 
believe it is not appropriate to use a more recent baseline period 
inclusive of COVID-19 data because conditions related to the COVID-19 
PHE are not alike across the country, with some hospitals experiencing 
more staff shortages than others and geographic disparities in COVID-19 
cases. Such conditions may have been out of their control and using a 
more recent baseline inclusive of COVID-19 data would thus unfairly 
penalize the hospitals disproportionately impacted. Our proposed 
suppression, scoring, payment, and updated baseline policies have been 
developed to provide as much flexibility as we can for providers to 
focus on delivering care during the COVID-19 PHE. We intend to continue 
to consider the evolving COVID-19 PHE while also evaluating future 
policies so as to continue incentivizing and prioritizing high quality 
of care for patients.
    After consideration of the public comments we received, we are 
finalizing our proposal to use updated baseline periods for the 5 HAI 
measures for FY 2025 as proposed.
c. Summary of Previously Adopted and Newly Baseline and Performance 
Periods for the FY 2024 Through FY 2028 Program Years Tables V.I.-04 
Through 08 Summarize the Baseline and Performance Periods That We Have 
Previously Adopted and Those That We Are Finalizing
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5. Performance Standards for the Hospital VBP Program
a. Background
    We refer readers to sections 1886(o)(3)(A) through 1886(o)(3)(D) of 
the Act for the statutory provisions governing performance standards 
under the Hospital VBP Program. We refer readers to the Hospital 
Inpatient VBP Program final rule (76 FR 26511 through 26513) for 
further discussion of achievement and improvement standards under the 
Hospital VBP Program. We refer readers to the FY 2013 IPPS/LTCH PPS 
final rule, FY 2014 IPPS/LTCH PPS final rule, and FY 2015 IPPS/LTCH PPS 
final rule (77 FR 53599 through 53605; 78 FR 50694 through 50699; and 
79 FR 50077 through 50081, respectively) for a more detailed discussion 
of the general scoring methodology used in the Hospital VBP Program. We 
refer readers to the FY 2022 IPPS/LTCH PPS final rule (86 FR 45290 
through 45292) for previously established performance standards for the 
FY 2024 program year. We note that the measure suppression proposals 
for the FY 2023 program year, discussed more fully in section V.I.1.b. 
of this final rule, will not affect the performance standards for the 
FY 2023 program year. However, as discussed in section V.I.1.c. of this 
final rule, we proposed to not generate achievement or improvement 
points for any suppressed measures for FY 2023.
    We refer readers to the FY 2021 IPPS/LTCH PPS final rule for 
further discussion on performance standards for which the measures are 
calculated with lower values representing better performance (85 FR 
58855).
b. Previously Established and Estimated Performance Standards for the 
FY 2025 Program Year
    In the FY 2020 IPPS/LTCH PPS final rule (84 FR 42398 through 
42399), we established performance standards for the FY 2025 program 
year for the Clinical Outcomes domain measures (MORT-30-AMI, MORT-30-
HF, MORT-30-PN (updated cohort), MORT-30-COPD, MORT-30-CABG, and COMP-
HIP-KNEE) and for the Efficiency and Cost Reduction domain measure 
(MSPB). We note that the performance standards for the MSPB

[[Page 49116]]

measure are based on performance period data. Therefore, we are unable 
to provide numerical equivalents for the standards at this time. As 
discussed in section V.I.4.b. of this final rule, we proposed to update 
the FY 2025 program year baseline periods for the measures included in 
the Safety domain and Person and Community Engagement domain, and we 
have finalized these baseline periods as proposed. In the proposed 
rule, we stated that if these proposals are finalized, we would use 
data from January 1, 2019 through December 31, 2019 to calculate 
performance standards for the FY 2025 program year for these measures.
    In accordance with our methodology for calculating performance 
standards discussed more fully in the Hospital Inpatient VBP Program 
final rule (76 FR 26511 through 26513) and codified at 42 CFR 412.160, 
we are estimating additional performance standards for the FY 2024 
program year. We note that the numerical values for the performance 
standards for the Safety domain and Person and Community Engagement 
domain for the FY 2025 program year in Tables V.I.-09 and V.I.-10 were 
calculated using data from January 1, 2019 through December 31, 2019. 
Therefore, in the FY 2023 IPPS/LTCH PPS proposed rule, we stated that 
if our proposed updates to the baseline periods for these measures are 
finalized, we will not update the numerical values in the FY 2023 IPPS/
LTCH PPS final rule. As stated in section V.I.4.c. of this final rule, 
we are finalizing the proposed updates to the baseline period for these 
measures as proposed.
    The previously established and estimated performance standards for 
the measures in the FY 2025 program year have been updated and are set 
out in Tables V.I.-09 and V.I.-10.
[GRAPHIC] [TIFF OMITTED] TR10AU22.143

    The HCAHPS Base Score is calculated using the eight dimensions of 
the HCAHPS measure. For each of the eight dimensions, Achievement 
Points (0-10 points) and Improvement Points (0-9 points) are 
calculated, the larger of which is then summed across the eight 
dimensions to create the HCAHPS Base Score (0-80 points). Each of the 
eight dimensions is of equal weight; therefore, the HCAHPS Base Score 
ranges from 0 to 80 points. HCAHPS Consistency Points are then 
calculated, which range from 0 to 20 points. The Consistency Points 
take into consideration the scores of all eight Person and Community 
Engagement dimensions. The final element of the scoring formula is the 
summation of the HCAHPS Base Score and the HCAHPS Consistency Points, 
which results in the Person and Community Engagement domain score that 
ranges from 0 to 100 points. As discussed in section V.I.4.b.(2). of 
this final rule, we proposed to update the FY 2025 program year 
baseline period for the measure included in the Person and Community 
Engagement domain. We are finalizing that proposal and, according to 
our established methodology for calculating performance standards, we 
will use data from January 1, 2019 through December 31, 2019 to 
calculate performance standards for the FY 2025 program year for this 
measure.

[[Page 49117]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.144

c. Previously Established Performance Standards for Certain Measures 
for the FY 2026 Program Year
    We have adopted certain measures for the Safety domain, Clinical 
Outcomes domain, and Efficiency and Cost Reduction domain for future 
program years in order to ensure that we can adopt baseline and 
performance periods of sufficient length for performance scoring 
purposes. In the FY 2021 IPPS/LTCH PPS final rule (85 FR 58858 through 
58859), we established performance standards for the FY 2026 program 
year for the Clinical Outcomes domain measures (MORT-30-AMI, MORT-30-
HF, MORT-30-PN (updated cohort), MORT-30-COPD, MORT-30-CABG, and COMP-
HIP-KNEE) and the Efficiency and Cost Reduction domain measure (MSPB). 
We note that the performance standards for the MSPB measure are based 
on performance period data. Therefore, we are unable to provide 
numerical equivalents for the standards at this time. The previously 
established performance standards for these measures are set out in the 
Table V.I.-11.
[GRAPHIC] [TIFF OMITTED] TR10AU22.145

d. Previously Established Performance Standards for Certain Measures 
for the FY 2027 Program Year
    We have adopted certain measures for the Safety domain, Clinical 
Outcomes domain, and the Efficiency and Cost Reduction domain for 
future program years in order to ensure that we can adopt baseline and 
performance periods of sufficient length for performance scoring 
purposes. In the FY 2022 IPPS/LTCH PPS final rule (86 FR 45294 through 
45295), we established performance standards for the FY 2027 program 
year for the Clinical Outcomes domain measures (MORT-30-AMI, MORT-30-
HF, MORT-30-PN (updated cohort), MORT-30-COPD, MORT-30-CABG, and COMP-
HIP-KNEE) and the Efficiency and Cost Reduction domain measure (MSPB). 
We note that the performance standards for the MSPB measure are based 
on performance period data. Therefore, we are unable to provide 
numerical equivalents for the standards at this time. The previously 
established performance standards for these measures are set out in 
Table V.I.-12.

[[Page 49118]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.146

e. Newly Established Performance Standards for Certain Measures for the 
FY 2028 Program Year
    As discussed previously, we have adopted certain measures for the 
Clinical Outcomes domain (MORT-30-AMI, MORT-30-HF, MORT-30-PN (updated 
cohort), MORT-30-COPD, MORT-30-CABG, and COMP-HIP-KNEE) and the 
Efficiency and Cost Reduction domain (MSPB) for future program years in 
order to ensure that we can adopt baseline and performance periods of 
sufficient length for performance scoring purposes. In accordance with 
our methodology for calculating performance standards discussed more 
fully in the Hospital Inpatient VBP Program final rule (76 FR 26511 
through 26513), which is codified at 42 CFR 412.160, we are 
establishing the following performance standards for the FY 2028 
program year for the Clinical Outcomes domain and the Efficiency and 
Cost Reduction domain. We note that the performance standards for the 
MSPB measure are based on performance period data. Therefore, we are 
unable to provide numerical equivalents for the standards at this time. 
The newly established performance standards for these measures are set 
out in Table V.I.-13.
[GRAPHIC] [TIFF OMITTED] TR10AU22.147

6. Data Requirements
a. Domain Weighting for Hospitals That Receive a Score on All Domains
    In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38266), we finalized 
our proposal to retain the equal weight of 25 percent for each of the 
four domains in the Hospital VBP Program for the FY 2020 program year 
and subsequent years for hospitals that receive a score in all domains. 
We did not propose any changes to these domain weights.
b. Domain Weighting for Hospitals Receiving Scores on Fewer Than Four 
Domains
    In the FY 2015 IPPS/LTCH PPS final rule (79 FR 50084 through 
50085), we adopted a policy that hospitals must

[[Page 49119]]

receive domain scores on at least three of four quality domains in 
order to receive a TPS, for the FY 2017 program year and subsequent 
years. Hospitals with sufficient data on only three domains will have 
their TPSs proportionately reweighted (79 FR 50084 through 50085). We 
did not propose any changes to these domain weights.
c. Minimum Numbers of Measures for Hospital VBP Program Domains
    We refer readers to the FY 2018 IPPS/LTCH PPS final rule (82 FR 
38266) for our previously finalized requirements for the minimum 
numbers of measures for hospitals to receive domain scores. We did not 
propose any changes to these policies.
d. Minimum Numbers of Cases for Hospital VBP Program Measures
(1) Background
    Section 1886(o)(1)(C)(ii)(IV) of the Act requires the Secretary to 
exclude for the fiscal year hospitals that do not report a minimum 
number (as determined by the Secretary) of cases for the measures that 
apply to the hospital for the performance period for the fiscal year. 
For additional discussion of the previously finalized minimum numbers 
of cases for measures under the Hospital VBP Program, we refer readers 
to the Hospital Inpatient VBP Program final rule (76 FR 26527 through 
26531); the CY 2012 OPPS/ASC final rule (76 FR 74532 through 74534); 
the FY 2013 IPPS/LTCH PPS final rule (77 FR 53608 through 53610); the 
FY 2015 IPPS/LTCH PPS final rule (79 FR 50085 through 50086); the FY 
2016 IPPS/LTCH PPS final rule (80 FR 49570); and the FY 2018 IPPS/LTCH 
PPS final rule (82 FR 38266 through 38267). We did not propose any 
changes to these policies.
(2) Summary of Previously Adopted Minimum Numbers of Cases
    The previously adopted minimum numbers of cases for these measures 
are set forth in Table V.I.-14.
[GRAPHIC] [TIFF OMITTED] TR10AU22.148

e. Summary of Previously Adopted Administrative Policies for NHSN 
Healthcare-Associated Infection (HAI) Measure Data
    In the FY 2020 IPPS/LTCH PPS final rule (84 FR 42400 through 
42402), we finalized our proposal to use the same data to calculate the 
CDC NHSN HAI measures for the Hospital VBP Program that the HAC 
Reduction Program uses for purposes of calculating the measures under 
that program, beginning on January 1, 2020 for CY 2020 data collection, 
which would apply to the Hospital VBP Program starting with data for 
the FY 2022 program year performance period. In the FY 2020 IPPS/LTCH 
PPS final rule (84 FR 42402), we also finalized our proposal for the 
Hospital VBP Program to use the same processes adopted by the HAC 
Reduction Program for hospitals to review and correct data for the CDC 
NHSN HAI measures and to rely on HAC Reduction Program validation to 
ensure the accuracy of CDC NHSN HAI measure data used in the Hospital 
VBP Program. We did not propose any changes to these policies.
7. Extraordinary Circumstance Exception (ECE) Policy for the Hospital 
VBP Program
    We refer readers to the FY 2022 IPPS/LTCH PPS final rule (86 FR 
45298 through 45299) for additional details related to the Hospital VBP 
Program ECE policy. We did not propose any changes to the Hospital VBP 
Program ECE policy.
8. References to Requests for Information
a. NHSN Digital Quality Measures
    We also refer readers to section IX.E.9.a. of this final rule, 
where we received comments in response to our request for information 
on the potential future adoption of the National Healthcare Safety 
Network (NHSN) Healthcare-Associated Clostridioides difficile Infection 
Outcome Measure and the National Healthcare Safety Network (NHSN) 
Hospital-Onset Bacteremia & Fungemia Outcome Measure into the Hospital 
IQR Program. In addition, we requested information on the potential 
future inclusion of these digital CDC NHSN measures in the Hospital VBP 
Program. This request for information supports our goal of moving fully 
to digital quality measurement in CMS quality reporting and value-based 
purchasing programs, including the Hospital VBP Program.

[[Page 49120]]

b. Reference to the Request for Information: Overarching Principles for 
Measuring Healthcare Quality Disparities Across CMS Quality Programs
    We refer readers to section IX.B. of this final rule where we 
received input on overarching principles in measuring healthcare 
quality disparities in hospital quality and value-based purchasing 
programs.

J. Hospital-Acquired Condition (HAC) Reduction Program: Updates and 
Changes (42 CFR 412.170)

1. Regulatory Background
    We refer readers to the FY 2014 IPPS/LTCH PPS final rule (78 FR 
50707 through 50708) for a general overview of the HAC Reduction 
Program and to the same final rule (78 FR 50708 through 50709) for a 
detailed discussion of the statutory basis for the Program. For 
additional descriptions of our previously finalized policies for the 
HAC Reduction Program, we also refer readers to the following final 
rules:
     The FY 2014 IPPS/LTCH PPS final rule (78 FR 50707 through 
50729);
     The FY 2015 IPPS/LTCH PPS final rule (79 FR 50087 through 
50104);
     The FY 2016 IPPS/LTCH PPS final rule (80 FR 49570 through 
49581);
     The FY 2017 IPPS/LTCH PPS final rule (81 FR 57011 through 
57026);
     The FY 2018 IPPS/LTCH PPS final rule (82 FR 38269 through 
38278);
     The FY 2019 IPPS/LTCH PPS final rule (83 FR 41472 through 
41492);
     The FY 2020 IPPS/LTCH PPS final rule (84 FR 42402 through 
42411);
     The FY 2021 IPPS/LTCH PPS final rule (85 FR 58860 through 
58865); and
     The FY 2022 IPPS/LTCH PPS final rule (86 FR 45300 through 
45310).
    We have also codified certain requirements of the HAC Reduction 
Program at 42 CFR 412.170 through 412.172.
2. Flexibility for Changes That Affect Quality Measures During a 
Performance or Measurement Period in the HAC Reduction Program
a. Measure Suppression Policy for the Duration of the COVID-19 PHE
    In the FY 2022 IPPS/LTCH PPS final rule, we adopted a policy for 
the duration of the COVID-19 PHE enabling us to suppress a number of 
measures from the Total HAC Score calculations for the HAC Reduction 
Program if we determine that circumstances caused by the COVID-19 PHE 
have affected these measures and the resulting Total HAC Scores 
significantly (86 FR 45301 through 45304). We refer readers to the FY 
2022 IPPS/LTCH PPS final rule for further details on our measure 
suppression policy (86 FR 45301 through 45304).
    In the FY 2022 IPPS/LTCH PPS final rule, we also adopted Measure 
Suppression Factors to guide our determination of whether to propose to 
suppress HAC Reduction Program measures for one or more program years 
that overlap with the PHE for COVID-19 (86 FR 45302). We adopted these 
Measure Suppression Factors for use in the HAC Reduction Program, and, 
for consistency, in the following other value-based purchasing 
programs: Hospital Value-Based Purchasing Program, Hospital 
Readmissions Reduction Program, Skilled Nursing Facility Value-Based 
Purchasing Program, and End-Stage Renal Disease Quality Incentive 
Program. We continue to believe that these Measure Suppression Factors 
will help us evaluate the HAC Reduction Program's measures, and that 
their adoption in the other value-based purchasing programs will help 
ensure consistency in our measure evaluations across programs. The 
previously adopted Measure Suppression Factors are as follows:
     Significant deviation in national performance on the 
measure during the COVID-19 PHE, which could be significantly better or 
significantly worse compared to historical performance during the 
immediately preceding program years.
     Clinical proximity of the measure's focus to the relevant 
disease, pathogen, or health impacts of the COVID-19 PHE.
     Rapid or unprecedented changes in--
    ++ Clinical guidelines, care delivery or practice, treatments, 
drugs, or related protocols, or equipment or diagnostic tools or 
materials; or
    ++ The generally accepted scientific understanding of the nature or 
biological pathway of the disease or pathogen, particularly for a novel 
disease or pathogen of unknown origin.
     Significant national shortages or rapid or unprecedented 
changes in--
    ++ Healthcare personnel;
    ++ Medical supplies, equipment, or diagnostic tools or materials; 
or
    ++ Patient case volumes or facility-level case mix.
    We stated that we view this measure suppression policy as necessary 
to ensure that the HAC Reduction Program does not reward or penalize 
facilities based on factors that the Program's measures were not 
designed to accommodate (86 FR 45302).
    In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28446 through 
28449), we proposed changes to this measure suppression policy, which 
we discuss in section V.J.2.b.(2).
b. Proposals To Apply the Measure Suppression Policy to FY 2023 and FY 
2024 HAC Reduction Program Years
(1) Background
    Through memoranda released in March 2020 \288\ and an interim final 
rule with comment (IFC) published in September 2020 (85 FR 54830 
through 54832), in response to the COVID-19 PHE, we excluded, by 
application of our Extraordinary Circumstances Exception (ECE) policy, 
all data submitted regarding care provided during the first and second 
quarters of CY 2020 from our performance calculations for FY 2022 and 
FY 2023. We excluded such data because of our concerns about the 
national comparability of these data due to the geographic differences 
of COVID-19 incidence rates and hospitalizations, along with different 
impacts resulting from different State and local laws and policy 
changes implemented in response to COVID-19.
---------------------------------------------------------------------------

    \288\ Centers for Medicare and Medicaid Services. (2020). 
Exceptions and Extensions for Quality Reporting Requirements for 
Acute Care Hospitals, PPS-Exempt Cancer Hospitals, Inpatient 
Psychiatric Facilities, Skilled Nursing Facilities, Home Health 
Agencies, Hospices, Inpatient Rehabilitation Facilities, Long-Term 
Care Hospitals, Ambulatory Surgical Centers, Renal Dialysis 
Facilities, and MIPS Eligible Clinicians Affected by COVID-19 
Available at: https://www.cms.gov/files/document/guidance-memo-exceptions-and-extensions-quality-reporting-and-value-based-purchasing-programs.pdf.
---------------------------------------------------------------------------

    Additionally, in the FY 2022 IPPS/LTCH PPS final rule, we finalized 
our policy suppressing the third and fourth quarters of CY 2020 \289\ 
CDC NHSN HAI and the CMS Patient Safety and Adverse Events Composite 
measure (CMS PSI 90) data from our performance calculations for FY 
2022, FY 2023, and FY 2024 under the proposed Measure Suppression 
Factor 1, ``significant deviation in national performance on the 
measure, which could be significantly better or significantly worse 
compared to historical performance during the immediately preceding 
program years''; and the Measure Suppression Factor 4 subfactor, 
``significant national or regional shortages or rapid or unprecedented 
changes in patient case volumes or case mix'' (86 FR 45304 through 
45307). We explained that although Q3 and Q4 2020 data would be 
suppressed from the Total HAC Score calculation, hospitals would still 
be required to submit such

[[Page 49121]]

data and such data would be used for public reporting purposes.
---------------------------------------------------------------------------

    \289\ In the FY 2022 IPPS/LTCH PPS final rule, we finalized the 
suppression of the third and fourth quarters of CY 2020, which is 
July 1, 2020 through September 30, 2020 (Q3 2020) and October 1, 
2020 through December 31, 2020 (Q4 2020).
---------------------------------------------------------------------------

    These policies resulted in the following applicable periods for 
calculating Total HAC Scores for FY 2022, FY 2023, and FY 2024 HAC 
Reduction Programs:
[GRAPHIC] [TIFF OMITTED] TR10AU22.149

    In sections V.J.2.b.(2). and (3), of this final rule, we are 
finalizing the proposal to further modify some of these applicable 
periods.
(2) Updates to the FY 2023 HAC Reduction Program
    In the FY 2023 IPPS/LTCH proposed rule, we discussed two updates 
for the FY 2023 HAC Reduction Program's measure suppression policy: (1) 
We proposed to suppress the CMS PSI 90 measure and the five CDC NHSN 
HAI measures from the calculation of measure scores and the Total HAC 
Score, thereby not penalizing any hospital under the FY 2023 HAC 
Reduction Program; and (2) For the CMS PSI 90 measure, we proposed to 
not calculate or report measure results for the FY 2023 HAC Reduction 
Program.
    COVID-19 has had significant negative health effects--on 
individuals, communities, and the nation as a whole. Consequences for 
individuals who have COVID-19 include morbidity, hospitalization, 
mortality, and post-COVID conditions (also known as long COVID). As of 
mid-December 2021, over 50 million COVID-19 cases, three million new 
COVID-19 related hospitalizations, and over 800,000 COVID-19 deaths 
have been reported in the U.S.290 291 One analysis projected 
that COVID-19 would reduce life expectancy in 2020 by 1.13 years 
overall, with the estimated impact disproportionately affecting members 
of historically underserved and under-resourced communities. According 
to this analysis, the estimated life expectancy reduction for Black and 
Latino populations is three to four times the estimate when comparing 
to the white population.\292\ Indeed, COVID-19 has overtaken the 1918 
influenza pandemic as the deadliest disease event in American 
history.\293\ Impacts of the pandemic have continued to accelerate in 
2021. The Delta variant of COVID-19 (B.1.617.2), which was first 
identified in India, surfaced in the United States in early-to-mid 
2021. It was found that the Delta variant is 60 percent more 
transmissible compared to the previously dominant Alpha variant.\294\ 
Further, in November 2021, the number of COVID-19 deaths for 2021 
surpassed the total deaths for 2020. According to CDC data, the total 
number of deaths involving COVID-19 reached 385,453 in 2020 and 451,475 
in 2021.\295\ We continue to monitor and evaluate the measures in the 
HAC Reduction Program for impacts due to COVID-19 and the emergence of 
COVID-19 variants, such as Delta and Omicron variants, and elaborate 
further later in the section.
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    \290\ Centers for Disease Control and Prevention. (2021). COVID 
Data Tracker, https://covid.cdc.gov/covid-data-tracker/#datatracker-home.
    \291\ As of mid-June 2022, over 86 million COVID-19 cases, 
15,000 new COVID-19 related hospitalizations, and over a million 
COVID-19 deaths have been reported in the U.S.
    \292\ Andrasfay, T., & Goldman, N. (2021). Reductions in 2020 US 
life expectancy due to COVID-19 and the disproportionate impact on 
the Black and Latino populations. Proceedings of the National 
Academy of Sciences of the United States of America, 118(5), 
e2014746118. https://www.pnas.org/content/118/5/e2014746118.
    \293\ STAT News. (2021). Covid-19 overtakes 1918 Spanish flu as 
deadliest disease in American history, https://www.statnews.com/2021/09/20/covid-19-set-to-overtake-1918-spanish-flu-as-deadliest-disease-in-american-history/.
    \294\ Allen H., Vusirikala A., Flannagan J., et al. Increased 
Household Transmission of COVID-19 cases associated with SARS-CoV-2 
Variant of Concern B.1.617.2: a national case-control study. Public 
Health England. 2021.
    \295\ Centers for Disease Control. (2022). COVID-19 Death Data 
and Resources. Available at: https://www.cdc.gov/nchs/nvss/covid-19.htm.
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    As described in section V.J.2.b.(1). of this final rule, we 
previously excluded or suppressed all quarters of CY 2020 data from the 
calculation of the Total HAC Score, in part, because of concerns about 
the national comparability of these data and significant deviation in 
national performance on the measure compared to historical performance. 
We acknowledge that facilities were still adapting to the demands of 
the PHE and that subsequently national performance deviated from 
previous performance during CY 2021. Therefore, we proposed to suppress 
all HAC Reduction Program measures (CMS PSI 90, CAUTI, CLABSI, Colon 
and Hysterectomy SSI, MRSA, and CDI) from the calculation of the Total 
HAC Score for the FY 2023 HAC Reduction Program under Measure 
Suppression Factor 1 significant deviation in national performance on 
the measure, which could be significantly better or significantly worse 
compared to historical performance during the immediately preceding 
program years; Measure Suppression Factor 3, rapid or unprecedented 
changes in clinical guidelines, care delivery or practice, treatments, 
drugs, or related protocols, or equipment or diagnostic tools or 
materials; and Measure Suppression Factor 4, significant national or 
regional shortages or rapid or unprecedented changes in patient case 
volumes or case mix.
    We are concerned that the COVID-19 PHE resulted in changes in HAC 
Reduction Program measure performance such that we would not be able to 
score hospitals fairly. We refer readers to the FY 2022 IPPS/LTCH PPS 
final rule (86 FR 45304 through 45305) for previous analysis on the HAC 
Reduction Program measures that showed that measure rates for the 
CLABSI, CAUTI, and MRSA measures increased during the CY 2020 pandemic 
year as compared to the pre-COVID CY 2019 year immediately preceding 
the COVID-19 PHE.
    In the FY 2023 IPPS/LTCH PPS proposed rule, we proposed to suppress 
three of the five CDC NSHN HAI measures (CLABSI, CAUTI, and MRSA) under 
Measure Suppression Factor 1, significant deviation in national 
performance on the measures, which could be significantly better or 
significantly worse compared to

[[Page 49122]]

historical performance during the immediately preceding program years. 
To determine whether the CLABSI, CAUTI, and MRSA measure rates would 
continue to show increases for CY 2021, the CDC analyzed changes in 
standardized infection ratios (SIRs) for Q1 and Q2 of CY 2021 as 
compared to the SIRs in Q1 and Q2 of CY 2019. This analysis found that 
the CLASBI, CAUTI, and MSRA measures had statistically significant 
measure rate increases during Q1 and Q2 of CY 2021 as compared to pre-
pandemic levels in Q1 and Q2 of CY 2019. For Q1 2021, the national SIR 
increased by approximately 45 percent for the CLABSI measure, 
approximately 12 percent for the CAUTI measure, and approximately 39 
percent for the MRSA measure as compared to Q1 2019. For Q2 2021, the 
national SIR increased by approximately 15 percent for the CLABSI 
measure and approximately 8 percent for the MRSA measure. The SIRs for 
the CAUTI measure showed no statistically significant difference for Q2 
2021 as compared to Q2 2019.
    For the CDI measure, the national SIR decreased by approximately 16 
percent for Q1 2021 as compared to Q1 2019 and by approximately 14 
percent for Q2 2021 as compared to Q2 2019. The SSI measure showed no 
significant increase or decrease in SIRs during Q1 2021 and Q2 2021 as 
compared to Q1 2019 and Q2 2019, however there has been an appreciable 
decrease in procedure volume for the measure. We proposed to suppress 
the SSI and CDI measures under Measure Suppression Factor 4, 
significant national shortages or rapid or unprecedented changes in 
patient case volumes and Measure Suppression Factor 3, rapid or 
unprecedented changes in clinical guidelines, care delivery or 
practice, treatments, drugs, or related protocols, or equipment or 
diagnostic tools or materials, respectively. Specifically, for the SSI 
measure, we proposed to suppress the measure for FY 2023 under Measure 
Suppression Factor 4, rapid or unprecedented changes in patient case 
volumes. We note that the SSI measure has had a low procedure volume 
for many hospitals during the PHE, which impacts our ability to produce 
SIRs for that measure. For CY 2019, 2,087 hospitals (61 percent) did 
not have sufficient procedure-level data needed to calculate an SSI SIR 
for abdominal hysterectomy, and 1,262 hospitals (37 percent) did not 
have sufficient data to calculate an SIR for colon surgery. However, 
nationally, procedure volumes declined even further during the COVID-19 
PHE in 2020, compared to 2019, with decreases of up to 23 percent for 
colon procedures and 39 percent for abdominal hysterectomy 
procedures.\296\ As of July 2021, abdominal hysterectomy procedures 
were still 6 percent below predicted levels.\297\ These changes in 
patient volumes for the SSI measure limit our ability to calculate SSI 
SIRs for hospitals that don't have sufficient data in FY 2023, which 
may impact the accuracy and reliability of overall national comparison 
on performance for this measure.
---------------------------------------------------------------------------

    \296\ Weiner-Lastinger, L., et al,. The impact of coronavirus 
disease 2019 (COVID-19) on healthcare-associated infections in 2020: 
A summary of data reported to the National Healthcare Safety 
Network. Infection Control & Hospital Epidemiology (2022), 43, 12-
25. doi:10.1017/ice.2021.362.
    \297\ Butler, S., et al. (2021). Epic Research. Elective 
Surgeries Approach Pre-Pandemic Volumes. Available at: https://epicresearch.org/articles/elective-surgeries-approach-pre-pandemic-volumes.
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    For the CDI measure, we proposed to suppress the measure under 
Measure Suppression Factor 3, rapid or unprecedented changes in 
clinical guidelines, care delivery or practice, related protocols, or 
equipment or diagnostic tools or materials. Pandemic-related 
improvements to typical CDI prevention practices such as hand hygiene, 
PPE practices, and environmental cleaning could have contributed to the 
declines seen in the CDI SIR in 2021 compared to 2019.\298\ In 
addition, a decline in outpatient antibiotic prescribing was observed 
starting in 2020 as healthcare utilization decreased during the COVID-
19 pandemic.\299\ This, combined with the continued use of inpatient 
antibiotic stewardship programs in hospitals, may also have contributed 
to the decline in the national CDI SIRs, as reducing patient antibiotic 
exposure is a recommended strategy for CDI prevention. More information 
about CDI prevention strategies can be found at https://www.cdc.gov/cdiff/clinicians/cdi-prevention-strategies.html.
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    \298\ Weiner-Lastinger L.M., et al. (2021). The impact of 
coronavirus disease 2019 (COVID-19) on healthcare-associated 
infections in 2020: A summary of data reported to the National 
Healthcare Safety Network. Infection Control & Hospital 
Epidemiology, https://doi.org/10.1017/ice.2021.362.
    \299\ The intersection of antibiotic resistance (AR), antibiotic 
use (AU), and COVID-19. (2021). Department of Health and Human 
Services website. https://www.hhs.gov/sites/default/files/antibiotic-resistance-antibiotic-use-covid-19-paccarb.pdf. Published 
February 10, 2021. Accessed June 28, 2021.
[GRAPHIC] [TIFF OMITTED] TR10AU22.150

    Additionally, because we cannot identify all potential elements 
that could be impacting the overall HAI experience at hospitals during 
an unprecedented PHE as well as potential geographic disparities in the 
impact of the PHE that could cause uneven impact on facilities based on 
their location, like shortages of healthcare personnel, we believe all 
five CDC NHSN HAI measures should be suppressed. Therefore, we believe 
it is appropriate to suppress all five HAI measures from the HAC 
Reduction Program for the FY 2023 program year, to ensure an accurate 
and reliable national comparison of performance on hospital safety.
    In the FY 2022 IPPS/LTCH PPS final rule (86 FR 45304 through 
45305), we observed that the skewed measure

[[Page 49123]]

performance may be due to circumstances unique to the effects of the 
pandemic such as staffing shortages and turnover, patients who are more 
susceptible to infections due to increased hospitalization stays, and 
longer indwelling catheters and central lines. We believe that the 
continued skewed measure performance is impacted by similar 
circumstances unique to the effects of the COVID-19 PHE. We further 
believe that our proposal to suppress the HAI measure data from CY 2021 
was appropriate because the impact of the COVID-19 PHE on the measures 
cannot be addressed through risk-adjustment. Under current data 
collection requirements for the CDC NHSN HAI measures the data are 
collected at each hospital's ward level, meaning that the hospital 
submits infection data for a given ward rather than at the individual 
patient level. Accordingly, we are not able to identify the number of 
patients with HAIs who also had COVID-19, and therefore cannot risk-
adjust for or otherwise account for COVID-19 diagnoses. Modifying CDC's 
risk adjustment methodology is a multi-year process that requires 
substantial time to review, analyze, and implement updated methodology 
for the calculation of the SIR. In order to address the impact of the 
ongoing COVID-19 PHE on HAI incidence, as reported to CDC NHSN, we 
believe suppression of the CY 2021 measure data is the best path 
forward for participating hospitals. Therefore, we proposed to suppress 
all five HAI measures in the HAC Reduction Program for the FY 2023 
program year.
    In accordance with the previously adopted measure suppression 
policy (86 FR 45301 through 45304), we proposed to suppress the CMS PSI 
90 measure and the five CDC NHSN HAI measures for the HAC Reduction 
Program FY 2023 program year. We will continue to provide the measure 
results for the CDC NHSN HAI measures to hospitals via their hospital-
specific reports (HSRs). We will also continue providing information 
regarding hospital performance to hospitals and other interested 
persons via the Care Compare tool hosted by Health and Human Services, 
currently available at https://www.medicare.gov/care-compare, and the 
Provider Data Catalog. As previously noted, under this policy, we would 
continue to use claims data for the CMS PSI 90 measure and 
participating hospitals would continue to report CDC NHSN HAI measure 
data to the CDC, so that we can monitor the effect of the circumstances 
on quality measurement and determine appropriate policies in the 
future.
    Similarly, our analysis of the CMS PSI 90 measure suggested that 
comparability of performance on the measure has also been impacted by 
the PHE. Additionally, after the nationwide ECE (85 FR 54827 through 
54828) and the FY 2022 IPPS/LTCH PPS final rule measure suppression 
policies (86 FR 45304 through 45307) the CMS PSI 90 measure reference 
period for the FY 2023 program year does not include data affected by 
the COVID-19 PHE. Conversely, the applicable period for the CMS PSI 90 
measure does include data affected by COVID-19 PHE. Due to the fact 
that the reference period for this measure does not include data 
affected by the COVID-19 PHE and the applicable period does include 
such data, this would result in risk adjustment parameters that do not 
account for the impact of COVID-19 on affected patients. We believe 
that this misalignment would produce distorted measure results and 
potentially yield biased CMS PSI 90 measure results among hospitals 
highly impacted by the COVID-19 PHE. Therefore, for the FY 2023 program 
year we proposed to not calculate measure results for CMS PSI 90, to 
not provide the measure results for the CMS PSI 90 measure to hospitals 
via their hospital-specific reports (HSRs), and to not publicly report 
those measure results on the Care Compare tool hosted by Health and 
Human Services and the Provider Data Catalog. We refer readers to 
section V.J.3.c.(1). and (2) of this final rule where we discuss the 
impact of the COVID-19 PHE on the CMS PSI 90 measure and a technical 
update to the measure specifications to risk-adjust for COVID-19 
diagnoses.
    For the remaining measures, specifically the CDC NHSN HAI measures, 
we would use the previously finalized applicable periods \300\ to 
calculate measure results (that is, SIRs for each of the CDC NHSN HAI 
measures) the FY 2023 program year. We would use those measure results 
in feedback reports to hospitals and as part of program activities, 
fulfilling our obligation under section 1886(p)(5) of the Act to 
provide confidential reports to applicable hospitals with information 
on their performance on measures with respect to hospital-acquired 
conditions. Consumers may continue to access information on hospital 
performance with regards to hospital-acquired conditions through 
several channels, including the Care Compare tool hosted by Health and 
Human Services, currently available at https://www.medicare.gov/care-compare, the Provider Data Catalog, available at https://data.cms.gov/provider-data/.
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    \300\ In the FY 2022 IPPS/LTCH PPS final rule, we finalized that 
the applicable periods for the FY 2023 HAC Reduction Program are for 
the CDC NHSN HAI measures the 12-month period from January 1, 2021 
through December 31, 2021.
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    Ultimately, we stated in the proposed rule that if we finalize our 
proposals, all hospitals would receive a Total HAC Score of zero, and 
no hospitals would receive a penalty for FY 2023. We would report the 
measure scores of ``N/A'', Total HAC Score of zero and payment 
reduction indicators of ``no penalty'' for all hospitals for the FY 
2023 program year after confidentially reporting via HSRs and a 30-day 
preview period and then publicly reporting on the Care Compare tool 
hosted by Health and Human Services and the Provider Data Catalog. For 
the five CDC NHSN HAI measures, we would also report the measure 
results, both via HSRs and public reporting methods. For the CMS PSI 90 
measure results, we would not calculate or report on the measure 
results and would indicate `N/A' in confidential and public reporting. 
We would resume calculating measure scores in the FY 2024 program year, 
as discussed in section V.J.2.b.(3). of this final rule.
    In determining how to address the impact of the COVID-19 PHE on 
hospital performance and calculating Total HAC Scores for FY 2023, we 
also considered suppressing some CY 2021 quality measure data as an 
alternative to suppressing all measures. Under this alternative, we 
considered suppressing the CY 2021 data for the CLABSI, CAUTI, and MRSA 
measures on the basis that performance on those measures continued to 
be affected by the COVID-19 PHE. We considered scoring hospitals based 
solely on their performance on SSI, CDI, and CMS PSI 90; however, we 
had concerns about running the HAC Reduction Program on only half of 
the program's measures as this may result in measure scores that are 
significantly better or worse than in immediately preceding years. In 
addition, a Total HAC Score based on only three program measures would 
be less reliable, with more random noise in identification of bottom 
quartile hospitals, than a score based on six program measures. 
Therefore, we believe it is appropriate to suppress all five CDC NSHN 
HAI measures and the CMS PSI 90 measure from the calculation of measure 
scores and Total HAC Scores for the FY 2023 program year.
    We also considered making no modifications to the program and 
suppressing no additional measure data

[[Page 49124]]

from the FY 2023 Total HAC Scores rather than extending the measure 
suppression policy. As discussed, when considering this approach in the 
FY 2022 IPPS/LTCH PPS final rule (86 FR 45305), this alternative would 
be operationally easier to implement, but would mean assessing 
participating hospitals using quality measure data that have been 
distorted by the COVID-19 PHE without additional adjustments to the 
measure. Additionally, given the geographic disparities in the COVID-19 
PHE's effects, this policy could place hospitals in regions that were 
hit harder by the pandemic in CY 2021 at a disadvantage compared to 
hospitals in regions that were more heavily affected in CY 2020. 
Ultimately, we believe that our proposal to suppress all measures from 
the FY 2023 HAC Reduction Program more fairly addresses the impact of 
the COVID-19 PHE for participating hospitals.
    Finally, we considered reusing a previous fiscal year's applicable 
period to serve as the applicable period for FY 2023. Although this 
option would enable us to continue operating the program, it has the 
disadvantage of double penalizing hospitals that were in a prior fiscal 
year's worst performing quartile even if the hospital had implemented 
policy and operational changes to improve their performance in future 
program years. Under this option, no new quality data would be used to 
inform hospitals or drive quality improvement.
    We continue to be concerned about the pandemic, but are encouraged 
by the development and rollout of prevention techniques like COVID-19 
vaccinations and treatment for those diagnosed with COVID-19. Our 
measure suppression policy focuses on a short-term, equitable approach 
during this unprecedented PHE, and was not intended for indefinite 
application. We also recognize that measure performance for some 
measures may not immediately return to levels seen prior to the PHE, 
particularly for the CDC NHSN HAI measures for which we do not receive 
patient-level data. Additionally, we wanted to emphasize the long-term 
importance of value-based care and incentivizing quality care tied to 
payment. The HAC Reduction Program is an example of our long-standing 
effort to link payments to healthcare quality in the inpatient hospital 
setting payment.\301\ Therefore, we note that our goal is to continue 
resuming the use of measure data for the purposes of scoring and 
payment adjustment beginning with the FY 2024 program year.
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    \301\ CMS has also partnered with the CDC in a joint Call to 
Action on safety, which is focused on our core goal to keep patients 
safe. Fleisher et al. (2022). New England Journal of Medicine. 
Article available here: https://www.nejm.org/doi/full/10.1056/NEJMp2118285?utm_source=STAT+Newsletters&utm_campaign=8933b7233e-MR_COPY_01&utm_medium=email&utm_term=0_8cab1d7961-8933b7233e-151759045.
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    We understand that the COVID-19 PHE is ongoing and unpredictable in 
nature, however, we believe that CY 2022 has a more promising outlook 
in the fight against COVID-19. As we enter the third year of the 
pandemic, healthcare providers and systems have gained experience 
managing the disease, surges of COVID-19 infection, and adjusting to 
supply chain fluctuations.\302\ In CY 2022 and the upcoming years, we 
anticipate continued availability and increased uptake in the use of 
vaccinations and the associated boosters,\303\ including vaccination 
for children ages 5-11, who were not eligible for vaccination for the 
majority of 2021 and of whom only 36 percent had received at least one 
dose as of June 29, 2022.304 305 Additionally, the FDA 
issued emergency use authorizations (EUAs) for the first oral antiviral 
COVID-19 pill on December 22, 2021, and later approved a second the 
following day, expanding access to at-home COVID-19 treatment 
options.306 307 Finally, the Biden-Harris Administration has 
mobilized efforts to distribute home test kits,\308\ N-95 masks,\309\ 
and increase COVID-19 testing in schools,\310\ providing more treatment 
and testing to the American people. Given these developments, we will 
continue to assess the impact of the PHE on measure data used for the 
HAC Reduction Program.
---------------------------------------------------------------------------

    \302\ Schneider, E. et al. (2022). The Commonwealth Fund. 
Responding to Omicron: Aggressively Increasing Booster Vaccinations 
Now Could Prevent Many Hospitalizations and Deaths. Available at: 
https://www.commonwealthfund.org/blog/2022/responding-omicron.
    \303\ Schneider, E. et al. (2022). The Commonwealth Fund. 
Responding to Omicron: Aggressively Increasing Booster Vaccinations 
Now Could Prevent Many Hospitalizations and Deaths. Available at: 
https://www.commonwealthfund.org/blog/2022/responding-omicron.
    \304\ KFF, Update on COVID-19 Vaccination of 5-11 Year Olds in 
the U.S., https://www.kff.org/coronavirus-covid-19/issue-brief/update-on-covid-19-vaccination-of-5-11-year-olds-in-the-u-s/.
    \305\ American Academy of Pediatrics. (2022). Summary of data 
publicly reported by the Centers for Disease Control and Prevention. 
Available at: https://www.aap.org/en/pages/2019-novel-coronavirus-covid-19-infections/children-and-covid-19-vaccination-trends/.
    \306\ U.S. Food and Drug Administration. (2021). Coronavirus 
(COVID-19) Update: FDA Authorizes First Oral Antiviral for Treatment 
of COVID-19. Available at: https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-authorizes-first-oral-antiviral-treatment-covid-19.
    \307\ U.S. Food and Drug Administration. (2021). Coronavirus 
(COVID-19) Update: FDA Authorizes Additional Oral Antiviral for 
Treatment of COVID-19 in Certain Adults. Available at: https://
www.fda.gov/news-events/press-announcements/coronavirus-covid-19-
update-fda-authorizes-additional-oral-antiviral-treatment-covid-19-
certain#:~:text=Today%2C%20the%20U.S.%20Food%20and,progression%20to%2
0severe%20COVID%2D19%2C.
    \308\ The White House. (2022). Fact Sheet: The Biden 
Administration to Begin Distributing At-Home, Rapid COVID-19 Tests 
to Americans for Free. Available at: https://www.whitehouse.gov/briefing-room/statements-releases/2022/01/14/fact-sheet-the-biden-administration-to-begin-distributing-at-home-rapid-covid-19-tests-to-americans-for-free/.
    \309\ Miller, Z. (2021). The Washington Post. Biden to give away 
400 million N95 masks starting next week. Available at: https://www.washingtonpost.com/politics/biden-to-give-away-400-million-n95-masks-starting-next-week/2022/01/19/5095c050-7915-11ec-9dce-7313579de434_story.html.
    \310\ The White House. (2022). FACT SHEET: Biden-Harris 
Administration Increases COVID-19 Testing in Schools to Keep 
Students Safe and Schools Open. Available at: https://www.whitehouse.gov/briefing-room/statements-releases/2022/01/12/fact-sheet-biden-harris-administration-increases-covid-19-testing-in-schools-to-keep-students-safe-and-schools-open/.
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    We invited public comments on our proposals. We received a large 
volume of input from the public regarding these proposals. We first 
address the comments related to our proposal to suppress the CMS PSI 90 
measure and the five CDC NHSN HAI measures from the calculation of 
measure scores and the Total HAC Score, thereby not penalizing any 
hospital under the FY 2023 HAC Reduction Program, for the purposes of 
scoring and payment. Next, we address the proposal to suppress 
calculation and public reporting of measure results for CMS PSI 90 for 
FY 2023.
    Comment: Many commenters supported the proposal to suppress the CMS 
PSI 90 measure and the five CDC NHSN HAI measures from the calculation 
of measure scores and the Total HAC Score, thereby not penalizing any 
hospital under the FY 2023 HAC Reduction Program. Several commenters 
agreed that this policy would help ensure hospitals are not penalized 
for conditions beyond the control of hospitals and providers that may 
negatively impact hospital performance. Several supported the proposal 
due to the significant impact of the COVID-19 PHE on quality measures. 
A few commenters noted that this proposed policy would provide 
important relief and stability for providers, especially rural 
providers, regarding compliance concerns so they can focus on the 
unique challenges of providing care during the COVID-19 PHE. Several 
commenters supported the proposal because it addresses the significant

[[Page 49125]]

deviation in national performance across all program measures due to 
the COVID-19 PHE. Many commenters supported the proposal due to the 
belief that the COVID-19 PHE negatively impacted hospitals and patients 
through a number of factors including quickly changing clinical 
practices, operational changes, increased clinical acuity, staffing and 
supply shortages, and care capacity concerns. Several commenters 
supported the proposal because of the disproportionate impacts of the 
COVID-19 PHE on hospital performance given geographic and temporal 
variation in surges of cases. A commenter supported the proposal due to 
the belief that this will provide hospitals more time to focus on 
training and education rather than public reporting of measure scores. 
A commenter supported the proposal due to the belief that this will 
help alleviate hospital administrative burden.
    Response: We thank commenters for their support. We agree that the 
proposed suppression, scoring, and payment policies for the FY 2023 
program year were developed using data-driven approaches and are 
intended to balance the importance of patient safety through 
transparency and public reporting while allowing hospitals to maintain 
access to care and focus on providing quality health care to patients 
during the COVID-19 PHE. Additionally, we agree that suppressing these 
measures for scoring and payment purposes will ensure hospitals are not 
penalized for impacts outside of their control and note that hospitals 
will still be required to report measure data for the five CDC NSHN HAI 
measures and CMS PSI 90 will be calculated through claims data, so 
hospital administrative burden will remain unchanged.
    Comment: A few commenters expressed support for the proposal to 
suppress the HAI measures from scoring and payment because they believe 
that CMS could not feasibly use either risk adjustment or exclusions to 
account for COVID-19 diagnoses in calculating performance.
    Response: We thank commenters for their support and agree that the 
HAI measures cannot be risk-adjusted due to the reasons described in 
the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28449 through 28450) and 
in this final rule.
    Comment: Many commenters did not support the proposal to suppress 
the CMS PSI 90 measure and the five CDC NHSN HAI measures from the 
calculation of measure scores and the Total HAC Score. Many commenters 
recommended that instead of finalizing the proposal to not score or 
penalize hospitals for their performance, CMS should penalize the worst 
performing hospitals to incentivize quality improvement. A few 
commenters requested that CMS explore the authority to provide payment 
bonuses for hospitals to create a reward for improved patient care. 
Many commenters did not support the proposal due to the belief that not 
instituting payment penalties would not hold hospitals accountable for 
care delivered to patients. Many commenters did not support the 
proposal because they believe that suspending payment reduction would 
be poor financial stewardship of the Medicare Trust Fund and ultimately 
not help beneficiaries.
    Response: We thank the commenters for their feedback. Throughout 
the COVID-19 PHE, we have prioritized access to safe, comprehensive 
healthcare, and we continue to make patient safety our primary concern. 
As part of this dedicated commitment to patient safety, we ensure 
public access to the highest quality data regarding the performance of 
health care facilities. We continue to collect and closely monitor 
performance to ensure safety, and will continue to share that data with 
the public. We understand commenters' concerns; though we recognize 
that some hospitals have maintained strong performance on measures 
throughout the COVID-19 PHE, we do not believe it is appropriate to 
penalize any hospitals based on measure data that we believe were 
distorted by the COVID-19 PHE, the impacts of which were geographically 
and temporally varied during 2021, and, thus, would not ensure an 
accurate and reliable national comparison of performance on hospital 
safety for penalty purposes. Meanwhile, we note the HAC Reduction 
Program statute does not grant the authority to award payment bonuses 
or incentive payments to hospitals with favorable performance and 
measure outcomes. Interested parties can view the HAC Reduction Program 
statute at Sec.  412.172 for more details on the payment requirements. 
Additionally, we note that the suppression, scoring, and payment 
policies for the FY 2023 program year were developed using data-driven 
approaches that are intended to balance the importance of patient 
safety through transparency and public reporting while allowing 
hospitals to maintain access to care and focus on providing quality 
health care to patients during the COVID-19 PHE.
    Comment: A commenter expressed concern over the misalignment of the 
Measure Suppression Factors used across the Hospital VBP and HAC 
Reduction Programs for the HAI measures.
    Response: We appreciate the commenter's concern regarding 
consistency. To promote alignment across our value-based purchasing 
programs, in both the Hospital VBP and HAC Reduction Programs, we 
proposed to suppress three of the five CDC NSHN HAI measures (CLABSI, 
CAUTI, and MRSA) under Measure Suppression Factor 1, significant 
deviation in national performance on the measures, which could be 
significantly better or significantly worse compared to historical 
performance during the immediately preceding program years; to suppress 
the SSI measure under Measure Suppression Factor 4, significant 
national shortages or rapid or unprecedented changes in patient case 
volumes; and to suppress the CDI measure under Measure Suppression 
Factor 3, rapid or unprecedented changes in clinical guidelines, care 
delivery or practice, related protocols, or equipment or diagnostic 
tools or materials. We applied these measure suppression factors with 
both program-specific considerations in mind as well as cross-program 
alignment. We continue to believe that suppressing the HAI measures 
under the HAC Reduction Program and the Hospital VBP Program for 
purposes of scoring and payment will provide flexibility for providers 
to focus on delivering quality of care to patients during the COVID-19 
PHE. We refer readers to the FY 2022 IPPS/LTCH PPS final rule (86 FR 
45301 through 45304) for more information on the HAC Reduction 
Program's measure suppression factors and the FY 2022 IPPS/LTCH PPS 
final rule (86 FR 45266 through 45269) for more information on the 
Hospital VBP Program's measure suppression factors.
    Comment: Many commenters recommended that we not suppress future 
measures without seeking public comment which gives the public an 
opportunity to provide feedback.
    Response: We appreciate the commenters' recommendation. Consistent 
with our previously finalized measure suppression policy in the FY 2022 
IPPS/LTCH PPS final rule (86 FR 45301 through 45304), we intend to 
provide interested parties with the opportunity to comment on future 
suppression through the rulemaking process.
    Comment: A commenter did not support the proposal to suppress the 
HAI measures from scoring and payment and recommended that we evaluate 
whether the HAC Reduction Program is sufficiently committed to ensuring 
a deeply embedded safety culture.

[[Page 49126]]

    Response: We thank the commenter for sharing their input, and we 
agree on the importance of safety culture. We also believe building a 
more resilient health care system is necessary to avoid future threats 
to patient safety.\311\ Specifically, as to the use of 2021 HAI data 
for assessing HAC Reduction Program penalties, based on data analyses 
by the CDC, we believe that suppressing the HAI measure for the FY 2023 
program year offers hospitals and health systems the flexibility to 
focus on delivery of care while also accounting for the changing 
conditions during a PHE that are beyond hospitals' control. In 
addition, we are committed to the continued collection, reporting, and 
public availability of the HAI measure data, focusing on transparency, 
upholding quality care, and helping patients make informed decisions 
about their care. As we note previously, our goal is to resume the use 
of 2022 HAI measure data for scoring and payment adjustment purposes 
beginning with the FY 2024 program year as we believe that 2022 has a 
more promising outlook in the fight against COVID-19 as we enter the 
third year of the pandemic.
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    \311\ Fleisher et al. (2022). ``Health Care Safety during the 
Pandemic and Beyond--Building a System That Ensures Resilience''. 
New England Journal of Medicine. Article available here: https://www.nejm.org/doi/full/10.1056/NEJMp2118285?utm_source=STAT+Newsletters&utm_campaign=8933b7233e-MR_COPY_01&utm_medium=email&utm_term=0_8cab1d7961-8933b7233e-151759045.
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    Comment: Many commenters supported our proposal to continue to 
publicly and confidentially report HAI measure results. Several 
commenters supported our proposal because they believe it would promote 
transparency in reporting of HAI measure data to help interested 
parties understand the healthcare landscape and the impact of the 
COVID-19 PHE. A few commenters supported our proposal because of their 
belief that the public access to the HAI data would allow them to make 
informed decisions about care. A commenter supported our proposal and 
recommended that we provide hospitals the option to opt-in to public 
reporting of the HAI measures.
    Response: We thank the commenters for their support and agree that 
it is important for the public to have access to the HAI measure data 
to continue to make informed health care decisions. As noted in the FY 
2023 IPPS/LTCH PPS proposed rule (87 FR 28448) and in this final rule, 
we intend to publicly report HAI measure results with appropriate 
caveats that explain that performance information has been impacted due 
to the COVID-19 PHE. We continue to place significant value on being as 
transparent as possible with the performance information that we 
collect, and we will make clear with caveats that performance 
information was affected by the COVID-19 PHE.
    We disagree with the commenter's suggestion to allow hospitals the 
option to opt-in to public reporting. We believe this may cause greater 
confusion and would provide an incomplete picture of the impact of 
COVID-19 on performance data since mostly only hospitals that performed 
well might choose to opt-in. Additionally, we believe that providing 
transparent performance information to the public throughout the COVID-
19 PHE and beyond is a priority, and we do not believe publicly 
reporting suppressed measure data places additional burden on providers 
above the processes providers already have in place that are used to 
collect and report the data to CMS and the CDC. We encourage hospitals 
to continue focusing on providing quality care, and we believe that the 
continued collection and public reporting of performance information 
can be a useful tool to inform future quality improvements for health 
care providers.
    Comment: Many commenters did not support suppression of the CDC 
NHSN HAI measures from the calculation of measure scores and the Total 
HAC Score for the FY 2023 HAC Reduction Program out of concerns 
relating to access to publicly reported measure data. Many commenters 
expressed their belief that the proposal to suppress the CDC NHSN HAI 
measures from the calculation of measure scores and the Total HAC Score 
would prevent patients from making informed decisions on where to 
receive care, especially those at high risk for the measure. Similarly, 
several commenters did not support the proposal because they believe it 
violates CMS' commitment to public safety by not granting the public 
access to hospital performance data. Several commenters stated that the 
proposal would not hold hospitals accountable for patient safety and 
the level and quality of care delivered. A few commenters stated that 
suppressing the HAI measures would create the perception that the 
government is not disclosing information, reducing public trust and 
transparency.
    Response: We thank the commenters for expressing their concerns. As 
discussed in section V.J.2.b.(2)., we wish to clarify that we are 
continuing to publicly report the CDC NSHN HAI measure results--the 
suppression proposal related to the five CDC NHSN HAI measure results 
was limited to suppression of the measures from the calculation of 
measure scores and the Total HAC Score for purposes of assessing HAC 
Reduction Program penalties for FY 2023. As discussed in the FY 2023 
IPPS/LTCH PPS proposed rule (87 FR 28448) and section V.J.2.b.(2). of 
this final rule, we intend to publicly report the suppressed CDC NHSN 
HAI measure data with appropriate caveats, as we recognize the 
importance of transparency, promoting public trust, and empowering 
individuals to make data-informed decisions using the publicly reported 
HAI measure data. We will also continue to provide confidential 
feedback reports to hospitals through the previously established 
processes, including the information available to hospitals via the 
CDC's National Healthcare Safety Network, as part of program activities 
to ensure that hospitals are made aware of the changes in performance 
rates that we observe. We believe that continuing to make the data 
publicly available ensures that hospitals are still held accountable 
for their quality of care as consumers decide where to obtain care 
based on the publicly available data on hospital performance.
    Comment: A commenter did not support HAI suppression out of concern 
that we might have difficulty adhering to, interpreting, and 
operationalizing the Measure Suppression Factors, given the ever-
changing landscape. A commenter did not support HAI suppression, 
believing that being unable to determine the causes of changes in HAI 
rates is not a rationale for suppression. A commenter did not support 
HAI suppression, stating that the rationale exceeds program authority 
and recommending that CMS retract its stated rationale for the 
suppression of NHSN CDC HAIs in this final rule.
    Response: We appreciate the concern surrounding the 
operationalizing of the measure Suppression Factors. We believe that, 
in the face of evolving circumstances of the COVID-19 PHE, the level of 
detail in the Suppression Factors, which were developed and finalized 
in the FY 2022 IPPS/LTCH PPS final rule to specifically address 
challenges that arose due to the COVID-19 PHE, is sufficient and 
applicable in suppressing the HAI measures. In deciding which measures 
to suppress, and as discussed in the proposed rule and this final rule, 
we examined each measure and determined that the evidence showed 
significant deviation in the individual measure performance data 
associated with the COVID-19 PHE and/or a low reporting volume. 
Additionally, the COVID-19 PHE in

[[Page 49127]]

2021 presented unique and unprecedented experiences that challenged 
hospitals in new ways beyond their control. We believe that it would be 
unfair to score or penalize hospitals through payment during these 
unique challenges, thus warranting the use of Measure Suppression 
Factors. We do not anticipate implementing the Measure Suppression 
Factors in other instances outside of such an unprecedented and unique 
circumstance as the COVID-19 pandemic.
    Comment: A commenter questioned whether we would be publicly 
reporting the HAI measure results in the aggregate form (that is, 
deidentified).
    Response: We appreciate the commenter's question. CDC collects data 
for the HAI measures at the ward level rather than the patient level, 
and then provides aggregate results at the individual hospital CCN 
level. Therefore, the data reported publicly will not have patient 
identifiable information, but will be identifiable by hospital 
aggregated to the same CCN.
    Comment: A commenter did not support publicly reporting the HAI 
measure results until the HAI measures can be risk adjusted for COVID-
19.
    Response: We appreciate the commenter's recommendation. However, 
due to the nature of the HAI measure data being collected at the ward 
level rather than the patient level, we cannot feasibly risk adjust or 
exclude for COVID-19 diagnoses in calculating hospital performance on 
the HAI measures. Additionally, we believe the HAI rates could 
potentially still be impacted even with COVID-19 risk adjustment 
because pandemic-related hospital staffing and resource issues affect a 
hospital's entire patient population. We continue to place significant 
value on being as transparent as possible with the performance 
information that we collect, and we will make clear with caveats that 
performance information was affected by the COVID-19 PHE.
    Comment: A few commenters recommended that the HAI measures 
continue to be suppressed until the end of the COVID-19 PHE. A few 
commenters recommended that we continue to evaluate the impact of the 
COVID-19 PHE on the data as the PHE subsides. A commenter recommended 
that we suppress CY 2020 and CY 2021 data from the HAI measure to 
address the impact of the COVID-19 PHE. A few commenters expressed 
concern about publicly reporting the HAI measure results because the 
data will be distorted and of little value to the public. Several 
commenters believed that publicly reporting the data would cause 
confusion or be misinterpreted by consumers due to the impacts of the 
COVID-19 PHE outside of facilities control. A commenter recommended 
that we delay public reporting of the HAI measures so that we can 
evaluate how to best communicate the impacts of the COVID-19 PHE to 
consumers.
    Response: We thank the commenters for their recommendations and 
will continue to monitor the PHE's ongoing effects carefully on the 
measures within the HAC Reduction Program. In the September 2, 2020 
IFC,\312\ we finalized exclusion of data submitted regarding care 
provided during the first and second quarters of CY 2020 from 
calculation of scoring and payment adjustments in the HAC Reduction 
Program. In the FY 2022 IPPS/LTCH final rule (86 FR 45307 through 
45307), we finalized suppression of the third and fourth quarters of CY 
2020 CDC NSHN HAI data for purposes of scoring and payment adjustments. 
In the FY 2023 IPPS/LTCH proposed rule (87 FR 28446 through 28450), we 
proposed to suppress CY 2021 CDC NHSN HAI measure data from the FY 2024 
HAC Reduction Program for purposes of scoring and payment adjustments. 
Therefore, we have suppressed CY 2020 and CY 2021 HAI measure data from 
the HAC Reduction Program for scoring and payment purposes.
---------------------------------------------------------------------------

    \312\ Centers for Medicare and Medicaid Services. (2020). 
Exceptions and Extensions for Quality Reporting Requirements for 
Acute Care Hospitals, PPS-Exempt Cancer Hospitals, Inpatient 
Psychiatric Facilities, Skilled Nursing Facilities, Home Health 
Agencies, Hospices, Inpatient Rehabilitation Facilities, Long-Term 
Care Hospitals, Ambulatory Surgical Centers, Renal Dialysis 
Facilities, and MIPS Eligible Clinicians Affected by COVID-19. 
Available at: https://www.cms.gov/files/document/guidance-memo-exceptions-and-extensions-qualityreporting-and-value-based-purchasingprograms.pdf.
---------------------------------------------------------------------------

    We understand commenters' concerns with publicly reporting measure 
data that were suppressed for purposes of calculating the measure 
scores and Total HAC Score. However, we disagree that publicly 
reporting suppressed measure data is not useful for consumers and 
interested parties. We continue to place significant value on being as 
transparent as possible with the performance information that we 
collect, and we will make clear with caveats that that performance 
information was affected by the COVID-19 PHE. We encourage hospitals to 
continue focusing on providing quality care, and we believe that the 
continued collection and public reporting of performance information 
can be a useful tool to inform future quality improvements for health 
care providers.
    Comment: Many commenters supported the proposal to suppress the 
calculating and reporting of CMS PSI 90 measure results for the FY 2023 
HAC Reduction Program. Several commenters supported the proposal 
because they believe the impacts of the COVID-19 PHE affected the 
accuracy of the data. Several commenters supported the proposal due to 
the potential for distorted measure results because of discrepancies in 
the reference and applicable periods among hospitals impacted by COVID-
19. A few commenters supported the proposal, noting their belief that 
because hospitals are seeing COVID-19 hospitalizations increase again, 
hospital care will likely be substantially impacted by these trends for 
the foreseeable future. A commenter recommended suppressing CMS PSI 90 
through at least Q2 2022.
    Response: We thank the commenters for their support, and we 
understand and acknowledge commenter's concerns regarding the impact of 
the COVID-19 PHE on the CMS PSI 90 measure. In light of the comments 
received and in alignment with our continued commitment to 
transparency, we are not finalizing our proposal to suppress the 
calculating and public reporting of CMS PSI 90 measure results for the 
FY 2023 HAC Reduction Program. Additional detail on how the measure 
will be adjusted to exclude patients with a diagnosis of COVID-19 is 
discussed at the end of this section in this rule. In public and 
confidential reporting, we intend to annotate measure data to indicate 
that performance was affected by the COVID-19 PHE. We thank the 
commenters for their recommendations, and we will continue to monitor 
the PHE's ongoing effects carefully.
    Comment: A few commenters expressed support for the proposal to 
suppress the calculating and public reporting of CMS PSI 90 measure 
results for the FY 2023 HAC Reduction Program, noting that consumers 
may not fully understand the caveats on Care Compare and that third 
party organizations may misuse the data. A commenter expressed their 
belief that public reporting is not of any value, even with the 
appropriate caveats on data limitations.
    Response: We appreciate the commenters' support and concerns. We 
have always believed that public reporting of measure data is an 
invaluable tool for patients, providers, and the public. Public 
reporting of measure data fosters transparency and provides safety 
information to the public in order to assist them with their healthcare 
decisions. While we proposed to not calculate or publicly

[[Page 49128]]

report the CMS PSI 90 measure unadjusted for any impacts of COVID-19, 
since the publication of the proposed rule, we have been able to 
determine a method for excluding patients with a diagnosis of COVID-19 
that will allow us to calculate and publicly report valid and reliable 
measure results. Therefore, based on this measure adjustment and 
stakeholder support for continued public reporting, we are not 
finalizing our proposal to suppress the calculating and public 
reporting of CMS PSI 90 measure results for the FY 2023 HAC Reduction 
Program. We believe that publicly reporting the CMS PSI 90 measure data 
with these adjustments is of value and an important step in providing 
transparency and upholding quality of care and safety for consumers. 
Additional detail is discussed later in this rule.
    Comment: A few commenters recommended three methods we could employ 
to preserve the integrity of the CMS PSI 90 measure for the FY 2023 
program year including: applying a measure exclusion for COVID-19 
diagnosis, excluding cases with a COVID-19 diagnosis 12 months prior to 
admission, or including a COVID-19 diagnosis at admission variable in 
the risk adjustment methodology. A commenter recommended that for 
version 12 of the CMS PSI 90 software CMS extend the applicable period 
to include more data from 2021 to increase the number of hospitals 
measured and increase measure reliability. Several commenters 
recommended that we should continue to report CMS PSI 90 measure data 
on Care Compare with the caveat that the values are not adjusted for 
COVID-19 diagnosis.
    Response: We appreciate commenters' recommendations regarding 
alternatives to suppressing CMS PSI 90 measure results for the FY 2023 
program year. We note that for the FY 2023 program year, we will be 
applying an exclusion to CMS PSI 90 for patients with a diagnosis of 
COVID-19 as a few of the commenters suggested. Since the publication of 
the proposed rule, we have been able to determine a method for 
excluding patients with a diagnosis of COVID-19 that will allow us to 
calculate and publicly report valid and reliable measure results. We 
refer readers to section V.J.3.c.(2) of this final rule for more detail 
on the updates to the measure specifications being made for the FY 2024 
to risk-adjust for COVID-19 diagnoses (in any position) present on 
admission. We note that risk adjustment details are released to the 
public when each version of the software is completed and made 
available. The Risk Adjustment methodology report will be posted on the 
QualityNet website for CMS PSI 90 Resources at https://qualitynet.cms.gov/inpatient/measures/psi/resources. The risk 
adjustment methodology is part of the routine annual process to update 
the CMS PSI 90 measure, where the measure developer will submit an 
annual update to NQF that includes updates to the risk adjustment 
model.\313\ We appreciate the commenters' recommendation to extend the 
applicable period to include more data from 2021 to increase the 
measure reliability and will consider it as we continue to assess the 
impact of the COVID-19 PHE on our measure data.
---------------------------------------------------------------------------

    \313\ National Quality Forum. (2022). Maintenance of NQF-
Endorsed Performance Measures. Available at: https://www.qualityforum.org/measuring_performance/endorsed_performance_measures_maintenance.aspx.
---------------------------------------------------------------------------

    Comment: A number of commenters did not support the proposal to 
suppress the calculating and public reporting of CMS PSI 90 measure 
results for the FY 2023 HAC Reduction Program. Many commenters did not 
support the proposal because they believe the data should remain 
publicly available in order for patients to make informed decisions on 
where to receive care. Several commenters did not support the proposal 
because they believe it would reduce the usefulness of the data 
displayed on Care Compare.
    Response: We thank the commenters for sharing their concerns. As 
discussed, since the publication of the proposed rule, we have been 
able to determine a method for excluding COVID-19 patients from program 
calculations that will allow us to calculate and publicly report valid 
and reliable measure results. This exclusion method uses fields 
available in the claims form to identify patients with a diagnosis of 
COVID-19. After identifying these patients, we will exclude them from 
our measure calculation for our CMS PSI 90 measure. We agree that we 
should continue publicly reporting the CMS PSI 90 measure so patients 
can make informed decisions about where they receive care. Ultimately, 
we believe that publicly reporting this measure data with these 
exclusions is of value and an important step in providing transparency 
and upholding quality of care and safety for consumers. In light of the 
comments received and in alignment with our continued commitment to 
transparency, we are not finalizing our proposal to suppress the 
calculating and public reporting of CMS PSI 90 measure results for the 
FY 2023 program year. Additional detail is discussed at the end of this 
section in this rule. We intend to confidentially report and publicly 
report the measure results, annotated to identify where performance was 
affected by the COVID-19 PHE.
    Comment: Many commenters did not support the proposal to suppress 
the calculating and public reporting of CMS PSI 90 measure results for 
the FY 2023 HAC Reduction Program because they believe the proposal 
violates the public trust in both CMS and the medical community and 
also reduces transparency in the Medicare program. Commenters also 
suggested that this proposal could erode patient safety infrastructure 
and ultimately hurt patients. Many commenters did not support the 
proposal and expressed concern about public awareness of potentially 
increasing rates of medical errors and infections. A few commenters did 
not support the proposal due to the belief that suppression of these 
data from reporting will not improve staffing shortages or clinical 
training, which have been critical contributors to poor hospital 
performance on the measures.
    Response: We thank the commenters for sharing their concerns. As 
discussed, since the publication of the proposed rule, we have been 
able to determine a method for excluding COVID-19 patients from program 
calculations that will allow us to calculate and publicly report valid 
and reliable measure results. This exclusion method uses fields 
available in the claims form to identify patients with a diagnosis of 
COVID-19. After identifying these patients, we will exclude them from 
our measure calculation for our CMS PSI 90 measure. We agree with 
commenters that we should continue publicly reporting measure data for 
CMS PSI 90. Therefore, we note, that after consideration of the public 
comments we received, we are not finalizing our proposal to suppress 
the calculating and public reporting of CMS PSI 90 measure results for 
the FY 2023 HAC Reduction Program. Additional details are discussed 
later in this section of the rule. Ultimately, we believe that publicly 
reporting suppressed measure data is an important step in providing 
transparency and upholding quality of care and safety for consumers.
    We also believe that publicly reporting CMS PSI 90 will help 
enforce patient safety infrastructure and benefit the patient-provider 
relationship. Additionally, we believe that confidentially reporting 
these measure data will help empower hospitals to better understand 
their performance and make improvements to staffing, education, and 
training.

[[Page 49129]]

    Comment: Many commenters did not support the proposal to suppress 
the calculating and public reporting of CMS PSI 90 measure results for 
the FY 2023 HAC Reduction Program due to the belief that there is no 
other publicly available source for data on the complications included 
in PSI 90 and if we do not publicly report this data interested parties 
will not have access to the data to inform their decisions. Many 
commenters did not support the proposal because they believe that 
public reporting of CMS PSI 90 measure data helps interested parties 
understand the patient safety landscape and prevent more adverse events 
from occurring. Many commenters did not support the proposal due to the 
belief that public reporting of the CMS PSI 90 measure helps employers 
and health plans analyze care delivery and promote robust health plan 
networks. Several commenters recommended that CMS report CMS PSI 90 
measure data so that regulators and researchers can learn from the 
COVID-19 PHE and develop an action plan to improve hospital 
performance. Many commenters recommended that CMS report the PSI 90 
measure data to align with the recommendations focused on expanding 
focus and resources on patient safety contained in the 2018 Office of 
the Inspector General Report on Adverse Events in Hospitals.\314\
---------------------------------------------------------------------------

    \314\ Department of Health and Human Services, Office of the 
Inspector General. (2018). Adverse Events in Hospitals: A Quarter of 
Medicare Patients Experienced Harm in October 2018. Available at: 
https://oig.hhs.govAd/oei/reports/OEI-06-18-00400.asp.
---------------------------------------------------------------------------

    Response: We agree with the commenters concerns and recommendations 
regarding the public and confidential reporting of the CMS PSI 90 
measure and recognize that interested parties should have access to 
this data to make data-informed decisions. Therefore, we note, that 
since we were able to determine a method for excluding COVID-19 
patients from program calculations that will allow us to calculate and 
publicly report valid and reliable measure result, we are not 
finalizing our proposal to suppress the calculating and reporting of 
CMS PSI 90 measure results for the FY 2023 HAC Reduction Program. This 
exclusion method uses fields available in the claims form to identify 
patients with a diagnosis of COVID-19. After identifying these 
patients, we will exclude them from our measure calculation for our CMS 
PSI 90 measure. Additional detail is discussed at the end of this 
section in this rule. We encourage hospitals to continue maintaining 
access and focusing on providing quality care, and we believe that the 
continued collection, analysis, and public reporting of patient safety 
performance information can be a useful tool to inform future quality 
improvement for health care systems, maintain focus on patient safety, 
and ultimately improve patient care.
    Comment: Many commenters did not support the proposal to suppress 
the calculating and public reporting of CMS PSI 90 measure results for 
the FY 2023 HAC Reduction Program due to their belief that CMS PSI 90 
data provides essential information about significant health care 
disparities that exist in patient safety. These commenters stated that 
not reporting on the CMS PSI 90 measure will perpetuate these health 
inequities and prevent quality improvement efforts to decrease 
disparities. Many commenters noted that the suppression of the CMS PSI 
90 measure would impede decision-making specifically for those 
populations that are high-risk for adverse patient safety events.
    Response: We share the commenters' concern about health equity and 
high-risk patients and note that as discussed, we are not finalizing 
our proposal to suppress the calculating and reporting of CMS PSI 90 
measure results for the FY 2023 HAC Reduction Program. Additional 
detail is discussed at the end of this section in this rule.
    We believe that by continuing to publish the data for these 
measures, in a way that is accessible to consumers and researchers, 
patients can make informed decisions about their care. Additionally, we 
refer readers to section IX.B. focused on our Request for Information, 
Overarching Principles for Measuring Quality Disparities Across CMS 
Quality Programs, where we requested information on healthcare quality 
disparities in hospital quality and value-based purchasing programs, 
which will inform our Equity Plan for Improving Quality in Medicare. We 
are committed to promoting health equity through our CMS National 
Quality Strategy \315\ and CMS Framework for Health Equity 2022-
2032,\316\ which focuses on advancing health equity and addressing the 
health disparities that underlie our health system.
---------------------------------------------------------------------------

    \315\ Centers for Medicare and Medicaid Services. (2022). CMS 
Strategic Plan: Health Equity. Available at: https://www.cms.gov/files/document/cms-national-quality-strategy-fact-sheet-april-2022.pdf.
    \316\ Center for Medicare and Medicaid Services. (2022). CMS 
Framework for Health Equity 2022-2032. Available at: https://www.cms.gov/files/document/cms-framework-health-equity.pdf.
---------------------------------------------------------------------------

    Comment: A few commenters did not support the proposal to suppress 
CMS PSI 90 because they believe that we did not justify suppression 
based on any of the measure suppression factors in the FY 2023 IPPS/
LTCH PPS proposed rule.
    Response: We acknowledge the commenters' concerns, however, in the 
FY 2023 IPPS/LTCH proposed rule, we discussed our rationale that our 
analysis of the CMS PSI 90 measure suggested that comparability of 
performance on the measure has also been impacted by the PHE and our 
analysis found that there was a decrease in volume across all component 
PSI measures, especially those related to surgical procedures. We 
stated that this rationale falls under Measure Suppression Factor 4, 
``significant national or regional shortages or rapid or unprecedented 
changes in patient case volumes or case mix'' (87 FR 28446 through 
28447; and 28452). Additionally, we stated that the CMS PSI 90 
reference period does not include data affected by the COVID-19 PHE and 
the applicable period does include such data. We stated that this 
misalignment would produce distorted measure results and potentially 
yield biased CMS PSI 90 measure results among hospitals highly impacted 
by the COVID-19 PHE (87 FR 28448). We believe we have appropriately 
applied the Measure Suppression Factors in this rulemaking to address 
the impacts of the COVID-19 PHE on the HAC Reduction Program measures.
    Comment: A few commenters did not support the proposal to suppress 
CMS PSI 90 and not calculate or report CMS PSI 90 measure results for 
the FY 2023 HAC Reduction Program due to their belief that the proposal 
does not align with our priorities outlined in the 2022 CMS Strategic 
Framework.\317\ A few commenters did not support the proposal because 
they believed that hospitals do not want outdated data to represent 
their performance especially since some facilities have made quality 
improvements during the COVID-19 PHE.
---------------------------------------------------------------------------

    \317\ Centers for Medicare and Medicaid Services. (2022). 2022 
CMS Strategic Framework. Available at: https://www.cms.gov/files/document/2022-cms-strategic-framework.pdf.
---------------------------------------------------------------------------

    Response: We acknowledge the commenters' concerns regarding 
alignment with our 2022 CMS Strategic Framework as well as outdated 
measure data representing hospital performance. We note, however, that 
after consideration of the public comments we received, we are not 
finalizing our proposal to suppress the calculating and reporting of 
CMS PSI 90 measure results for the FY 2023 HAC Reduction Program. 
Additional detail is discussed at the end of this section in this rule. 
We

[[Page 49130]]

strongly believe that publicly reporting these data aligns with our 
Strategic Plan and will balance our responsibility to provide 
transparency to consumers while ensuring hospitals are not unfairly 
scored or penalized. Also, since we will calculate updated measure 
results for CMS PSI 90, hospitals will not have outdated information 
representing performance on the measure.
    Comment: A commenter recommended that if the CMS PSI 90 measure is 
suppressed from the FY 2023 HAC Reduction Program that we instead 
report the PSI 03 measure as a stand-alone measure because this will 
help maintain hospital focus on pressure ulcers and injuries and would 
lead to better reporting and improved patient care since the measure 
has a sole focus.
    Response: We agree with the commenter on the importance of 
measuring pressure ulcers and injuries which is the intent of the PSI 
03 measure. Because we are not finalizing the proposal to suppress the 
calculating and public reporting of CMS PSI 90 measure results for the 
FY 2023 HAC Reduction Program, data on pressure ulcers and injuries 
will continue to be reported publicly and confidentially as part of the 
PSI 90 measure results. We also note that PSI 03 will be publicly 
available in the Provider Data Catalog.
    Comment: Many commenters recommend that we continue to report CMS 
PSI 90 data and publish previous CMS PSI 90 data since it is important 
that interested parties have access to all previous CMS PSI 90 data 
from CY 2019 and past years. A few commenters recommended that we 
consider continuing to publicly report the CMS PSI 90 measure using 
hospital's pre-pandemic data. A few commenters recommended that we 
report CMS PSI 90 measure data on the Provider Data Catalog since this 
is valuable data for health systems to learn from but not on Care 
Compare because the data impacted by the COVID-19 PHE should not be 
used for scores, grades, or ratings.
    Response: We acknowledge the commenters' recommendations regarding 
public reporting of CMS PSI 90. We note, that after consideration of 
the public comments we received and because we identified a method for 
excluding COVID-19 patients from program calculations that will allow 
us to calculate and publicly report valid and reliable measure results, 
we are not finalizing our proposal to suppress the calculating and 
reporting of CMS PSI 90 measure results for the FY 2023 HAC Reduction 
Program. Although we will not calculate or report CMS PSI 90 measure 
results for use in the HAC Reduction Program scoring calculations for 
the program year, we will still calculate and publicly report the CMS 
PSI 90 measure displayed on the main pages of the Care Compare tool 
hosted by HHS after confidentially reporting these results to hospitals 
via CMS PSI 90-specific HSRs and a 30-day preview period. We will also 
be reporting these results on the Provider Data Catalog. We strongly 
believe that publicly reporting these data will balance our 
responsibility to provide transparency to consumers while ensuring 
hospitals are not unfairly penalized.
    We acknowledge the commenter's recommendation to continue public 
reporting of CMS PSI 90 using hospital's pre-pandemic data and 
understand that hospitals have been impacted by the pandemic. For this 
reason, for the FY 2023 HAC Reduction Program, we are not assessing 
payment penalties for hospitals which report HAC Reduction Program 
measures. This policy in combination with calculating and publicly 
reporting CMS PSI 90 ensures that interested parties can access the 
measure data but hospitals are not penalized for the differential 
effects of the COVID-19 PHE outside of their control.
    We also acknowledge the commenters recommendation to report 
historic CMS PSI 90 data, and note that CMS PSI 90 data is available 
from the last seven years on the Provider Data Catalog's Data Archive 
at this website: https://data.cms.gov/provider-data/archived-data/hospitals.
    Comment: A few commenters recommended that we begin to resume 
normal reporting of the CMS PSI 90 measure publicly and confidentially 
when hospitals are less burdened by the impacts of the COVID-19 PHE. A 
few commenters recommended that we not publicly report PSI 90 measure 
data but calculate the measure and report the data confidentially so 
hospitals can gain insight into their performance.
    Response: We appreciate the commenters' recommendation to not 
publicly report CMS PSI 90 until the COVID-19 PHE recedes, and to 
report the CMS PSI 90 measure confidentially so that hospitals can 
understand their performance. We note, that after consideration of the 
public comments we received and because we identified a method for 
excluding COVID-19 patients from program calculations that will allow 
us to calculate and publicly report valid and reliable measure results, 
we are not finalizing our proposal to suppress the calculating and 
reporting of CMS PSI 90 measure results for the FY 2023 HAC Reduction 
Program. Additional detail is discussed at the end of this section in 
this rule. We will ensure the appropriate caveats are applied to public 
reporting of the measure so that interested parties understand the data 
was impacted by the COVID-19 PHE. We also will be confidentially 
reporting these results to hospitals via CMS PSI 90-specific HSRs so 
that hospitals can evaluate their performance on the measure.
    We reiterate that ensuring patient safety, and access to safe, 
equitable, quality health care is high priority and a primary concern. 
We continue to place significant value on being as transparent as 
possible with the performance information that we collect to support 
the decision making of consumers, healthcare providers, researcher, and 
other interested parties. After consideration of the public comments we 
received, and because since the publication of the proposed rule, we 
have determined a methodology to exclude COVID-19 patients from the CMS 
PSI 90 measure that will allow us to calculate and publicly report 
valid and reliable measure results, we are not finalizing our proposal 
to suppress the calculating and reporting of CMS PSI 90 measure results 
for the FY 2023 HAC Reduction Program. Although we will not calculate 
or report CMS PSI 90 measure results for use in the HAC Reduction 
Program scoring calculations for the program year, we will still 
calculate and report the measure displayed on the main pages of the 
Care Compare tool hosted by HHS after confidentially reporting these 
results to hospitals via CMS PSI 90-specific HSRs and a 30-day preview 
period. We will continue to calculate and report measure results for 
the five CDC NSHN HAI measures. Further, we are finalizing our proposal 
to suppress the CMS PSI 90 measure and the five CDC NHSN HAI measures 
from the calculation of measure scores and Total HAC Scores for the FY 
2023 program year, thereby not penalizing any hospital under the FY 
2023 HAC Reduction Program. We thank the commenters for their comments 
and suggestions, which we will take into consideration when assessing 
potential future measure reporting and scoring decisions.
(3) Proposal To Suppress CY 2021 CDC NHSN HAI Measure Data From the FY 
2024 HAC Reduction Program Year
    As described in section V.J.2.b.(1). of this final rule, we 
previously excluded or suppressed all quarters of CY 2020 data for all 
the program measures from the calculation of the Total HAC Score, in 
part, because of concerns about the national comparability of these 
data and significant deviation in national

[[Page 49131]]

performance on the measure compared to historical performance. The 
exclusion and suppression of those data resulted in a shortened 
applicable period for the CMS PSI 90 measure for the FY 2024 HAC 
Reduction Program, specifically the 18-month period of January 1, 2021 
through June 30, 2022. The applicable period for the CDC NHSN HAI 
measures for the FY 2024 program year was unaffected and remained as 
the 24-month period of January 1, 2021, through December 31, 2022.
    As described previously, we continue to be concerned about measure 
performance and the national comparability of such performance during 
CY 2021. We therefore are proposing to suppress CY 2021 CDC NHSN HAI 
data from the FY 2024 HAC Reduction Program under Measure Suppression 
Factor 1, ``significant deviation in national performance on the 
measure, which could be significantly better or significantly worse 
compared to historical performance during the immediately preceding 
program years''; and the Measure Suppression Factor 4 subfactor, 
``significant national or regional shortages or rapid or unprecedented 
changes in patient case volumes or case mix.'' Under current data 
collection processes for the CDC NHSN HAI measures, we are not able to 
risk-adjust for or otherwise account for COVID-19 diagnoses and 
therefore must suppress the CY 2021 data in order to account for COVID-
19 diagnoses in the CDC NHSN HAI data. For the FY 2024 program year, 
the resulting applicable period for CDC NHSN HAI measures would be the 
12-month period of January 1, 2022, to December 31, 2022.
    To account for the impact of the COVID-19 PHE on CY 2021 data in 
the CMS PSI 90 measure, we are updating the measure specifications to 
risk-adjust for COVID-19 diagnoses, as described in section 
V.J.3.c.(2). of this final rule, beginning with the FY 2024 program 
year. Our analysis of the COVID-19 PHE impacts on CY 2021 data found 
that the decrease in volume continued in CY 2021 across nearly all 
component Patient Safety Indicator (PSI) measures, especially those 
related to surgical procedures (for which the denominator volume was 8 
percent to 45 percent lower in the first two quarters of CY 2021 than 
in the corresponding quarters of CY 2019). Our analysis also found that 
unadjusted rates continued to be high in CY 2021 for patients with a 
COVID-19 diagnosis compared to patients without a COVID-19 diagnosis. 
We refer readers to section V.J.3.c.(2). for more information about 
COVID-19 impacts on the CMS PSI 90 measure.
    For the CMS PSI 90 measure, the applicable period remains unchanged 
from January 1, 2021, through June 30, 2022.\318\ If finalized, these 
policies would result in the following applicable periods for FY 2023, 
FY 2024, and FY 2025 HAC Reduction Programs:
---------------------------------------------------------------------------

    \318\ For the FY 2025 HAC Reduction Program year, there is no CY 
2021 data included in the applicable period for the HAI measures so 
the applicable period remains unchanged and would be January 1, 
2022, to December 31, 2023. For the CMS PSI 90 measure, the 
applicable period is July 1, 2021, through June 30, 2023. As 
discussed, to account for the impact of the COVID-19 PHE on CY 2021 
CMS PSI 90 measure data, we are updating the measure specifications 
to risk-adjust for COVID-19 diagnoses.
[GRAPHIC] [TIFF OMITTED] TR10AU22.151

    We invited public comments on this proposal to suppress CY 2021 CDC 
NHSN HAI Measure data from the FY 2024 HAC Reduction Program.
    Comment: Many commenters supported the proposal to suppress the CY 
2021 data from the five CDC NHSN HAI measures for the FY 2024 program 
year. A few commenters supported the proposal due to the belief that 
suppression of the CY 2021 data from the five CDC NHSN HAI measures 
would address significant deviation in national performance due to 
continued disruptions in the health care system and care delivery 
process caused by the COVID-19 PHE, including staffing and supply 
shortages. A few commenters supported the proposal due to the belief 
that it would prevent hospitals from being penalized and incentivized 
based on measure data impacted by the COVID-19 PHE. A few commenters 
suggested to monitor the CDC NHSN HAI measures for fluctuations in 
performance due to the suppression of the CY 2021 data and ensure 
continued measure reliability.
    Response: We thank commenters for their support, and we agree that 
suppressing the CY 2021 data from these measures will ensure that 
hospitals are not penalized for the impacts of the COVID-19 PHE on the 
healthcare delivery system and subsequently the HAI measure data. We 
will continue to monitor performance in the CDC NHSN HAI measures and 
will consider any such issues we identify for future rulemaking.
    Comment: Several commenters did not support the suppression of the 
CY 2021 data from the five CDC NHSN HAI measures for FY 2024. A few 
commenters did not support the proposal due to the belief that 
suppressing the CY 2021 data from the five CDC NHSN HAI measures would 
prevent patients from assessing hospital performance and making 
informed decisions on where to receive care.
    Response: We acknowledge the commenters concern about suppression 
of the CY 2021 data from the CDC NHSN HAI measure for FY 2024. However, 
we continue to be concerned about measure performance and the national 
comparability of such performance during CY 2021. Under the current 
data collection processes for the CDC NHSN HAI measures, we are not 
able to risk-adjust for or otherwise account for COVID-19 diagnoses and 
therefore must suppress the CY 2021 data in order to account for COVID-
19 diagnoses in the CDC NHSN HAI data.
    Further, we understand commenters' concern regarding patients' 
ability to make informed decisions on where to receive care. We 
continue to place significant value on being transparent as possible 
with the performance

[[Page 49132]]

information that we collect with caveats of the performance information 
impacted by the COVID-19 PHE. As discussed in section V.J.2.b.(3) of 
this final rule, for the FY 2024 program year, we will continue to 
report the measure data for CY 2021, both in confidential reporting via 
HSR's and public reporting methods on Care Compare, as part of program 
activities to ensure that consumers and interested parties are able to 
assess facility performance and quality of care.
    Comment: A commenter did not support the proposal because of the 
concern regarding hospital accountability, asserting that hospitals 
utilize the data to improve the patient treatment delivery process and 
eliminate preventable medical error. A commenter believed that despite 
the impacts from the COVID-19 PHE this emergency only increases the 
need to collect and measure the HAI measure data. A commenter 
recommended to continue to report CY 2021 data including notations of 
mitigating circumstances and data abnormalities.
    Response: We thank commenters for expressing concerns regarding 
holding facilities accountable for the standard and quality of care of 
services furnished and the urgency of retaining this requirement during 
the COVID-19 PHE. We agree that the PHE underscored the importance of 
measuring hospital acquired infections to promote patient safety. We 
believe that although the collection, monitoring, and public reporting 
of COVID-19 impacted data with the appropriate caveats is important, 
such data should not be used to assess hospital performance and 
utilized for payment determination or penalties. Under current data 
collection processes for the CDC NHSN HAI measures, we are not able to 
risk-adjust for or otherwise account for COVID-19 diagnoses, thus we 
proposed to suppress the CY 2021 data in order to account for COVID-19 
diagnoses in the CDC NHSN HAI data. We agree that the HAI measure data 
should be confidentially reported and made available to facilities to 
support improvement initiatives within the patient delivery process, 
and we will report the measure results, both in confidential reporting 
via HSR's and public reporting methods on Care Compare, to ensure 
hospitals are made aware of the changes in performance rates that we 
observe, as discussed in section V.J.2.b.(2) of this final rule.
    We thank the commenter for the suggestion to report the CY 2021 
data including notations of data abnormalities. As noted in the 
preamble of the final rule, we intend to publicly report suppressed 
data with appropriate caveats that explain that performance information 
has been impacted due to the COVID-19 PHE.
    Comment: A commenter questioned if CMS intends to continue the 
policy of not assessing payment penalties for the FY 2024 program year. 
Several commenters recommended that we extend this payment and scoring 
policy to the FY 2024 program year to account for the continued impact 
of the COVID-19 PHE. A few commenters recommended that CMS provide 
additional outreach and educational materials to understand the data-
related changes and scoring impacts. Another commenter recommended that 
CMS provide HAI measure scores to hospitals to allow for evaluation of 
hospital performance.
    Response: In the FY 2023 IPPS/LTCH proposed rule (87 FR 28446 
through 28450), we did not propose to not assess payment penalties in 
the FY 2024 program year, but we understand commenters' concerns 
regarding the impact of the COVID-19 PHE and will ensure that we 
monitor and evaluate the data to determine if further suppression is 
warranted in the future. We want to emphasize the long-term importance 
of value-based care and incentivizing quality care tied to payment. 
Therefore, we note that our goal is to continue resuming the use of 
measure data for the purposes of scoring and payment adjustment 
beginning with the FY 2024 program year. Additionally, we will work to 
ensure that hospitals and providers receive additional outreach and 
educational material that clearly communicates the updates and changes 
to the HAC Reduction Program. Finally, hospitals will be able to 
evaluate their performance using the HAI measure results that they 
receive in their Hospital Specific Reports which we will provide for 
the FY 2023 program year.
    Comment: A commenter did not support the proposal due to belief 
that it would create the perception that the government is not 
disclosing information, reducing public trust and transparency.
    Response: We understand commenters' concerns regarding public 
reporting of the HAI measure data to promote public trust and 
transparency. We continue to place significant value on being 
transparent as possible with the performance information that we 
collect with caveats of the performance information impacted by the 
COVID-19 PHE. Therefore, to address challenges in national 
comparability of these data and to retain transparency with consumers 
and interested parties, we proposed to suppress the CY 2021 data for 
program calculations for payment purposes, but continue to report, both 
in confidential reporting via HSR's and public reporting methods on 
Care Compare, the five HAI measures for the FY 2024 program year with 
the resulting applicable 12-month period of January 1, 2022 to December 
31, 2022. Under the current data collection processes for the CDC NHSN 
HAI measures, we are not able to risk-adjust for or otherwise account 
for COVID-19 diagnoses and therefore we proposed to suppress the CY 
2021 data in order to account for COVID-19 diagnoses and ensure that 
hospitals are not unfairly scored or penalized through payment due to 
the COVID-19 PHE.
    Comment: Many commenters did not support the proposal due to the 
belief that the program would be heavily reliant on CMS PSI 90 if the 
CY 2021 data from the CDC NHSN HAI measures are suppressed. A few 
commenters recommended to include some limited data for the CDC NHSN 
HAI measures or to suppress all the measures for FY 2024. A few 
commenters suggested that CMS evaluate the impacts on hospital 
performance if hospitals are only scored on CMS PSI 90 for the FY 2024 
program year.
    Response: We understand the commenters' concern about the program 
being heavily reliant on CMS PSI 90 for FY 2024 due to the proposed 
suppression of the CY 2021 data for the CDC NHSN HAI measure. However, 
we disagree that FY 2024 program year performance will be too heavily 
dependent on the PSI 90 measures. We intend to continue to report all 
five HAI measures for the FY 2024 program year with the resulting 
applicable 12-month period of January 1, 2022 to December 31, 2022 and 
to report CMS PSI 90 risk adjusted for COVID-19. We will continue to 
monitor the impacts of these policies and will consider any such issues 
we identify for future rulemaking.
    After consideration of the public comments we received, we are 
finalizing our proposal to suppress CY 2021 CDC NHSN HAI measure data 
from the FY 2024 HAC Reduction Program.
3. Measures for FY 2023 and Subsequent Years
    We refer readers to the FY 2019 IPPS/LTCH PPS final rule (83 FR 
41472 through 41474) for more information about how the HAC Reduction 
Program supports our goal of bringing quality measurement, 
transparency, and improvement together with value-based purchasing to 
the hospital inpatient care setting through the Meaningful Measures 
Framework.

[[Page 49133]]

A. Current Measures

    The HAC Reduction Program has adopted six measures to date. In the 
FY 2014 IPPS/LTCH PPS final rule (78 FR 50717), we finalized the use of 
five CDC NHSN HAI measures: (1) CAUTI; (2) CDI; (3) CLABSI; (4) Colon 
and Abdominal Hysterectomy SSI; and (5) MRSA bacteremia. In the FY 2017 
IPPS/LTCH PPS final rule (81 FR 57014), we finalized the use of the CMS 
PSI 90 measure. These previously finalized measures, with their full 
measure names, are shown in this table.
[GRAPHIC] [TIFF OMITTED] TR10AU22.152

    Technical specifications for the CMS PSI 90 measure can be found on 
the QualityNet website at https://qualitynet.cms.gov/inpatient/measures/psi/resources. Technical specifications for the CDC NHSN HAI 
measures can be found at CDC's NHSN website at https://www.cdc.gov/nhsn/acute-care-hospital/. Both websites provide measure 
updates and other information necessary to guide hospitals 
participating in the collection of HAC Reduction Program data.
    In this final rule, we did not add or remove any measures. However, 
we discuss our proposal to suppress all of the measures for the FY 2023 
program year, as discussed in section V.J.2.b.(2) of the preamble of 
this final rule, and our proposal to suppress CY 2021 CDC NHSN HAI data 
from the FY 2024 program year, as discussed in section V.J.2.b.(3). Of 
the preamble of this final rule.
b. Measure Removal Factors Policy
    We refer readers to the FY 2020 IPPS/LTCH PPS final rule (84 FR 
42404 through 42406) for information about our measure removal and 
retention factors for the HAC Reduction Program. In this final rule, we 
did make any measure removal and retention factor policy changes.
c. Technical Measure Specification Updates to the CMS PSI 90 Measure
(1) Technical Measure Specification Update to the Minimum Volume 
Threshold for the CMS PSI 90 Measure Beginning With the FY 2023 Program 
Year
    In the FY 2015 IPPS/LTCH PPS final rule (79 FR 50100 through 
50101), we finalized a subregulatory process to incorporate technical 
measure specification updates into the measure specifications we have 
adopted for the HAC Reduction Program. We stated our belief that this 
policy adequately balances our need to incorporate updates to HAC 
Reduction Program measures in the most expeditious manner possible 
while preserving the public's ability to comment on updates that so 
fundamentally change an endorsed measure that it is no longer the same 
measure that we originally adopted.
    Currently, the minimum volume threshold for the CMS PSI 90 measure 
requires hospitals to have three or more eligible discharges for at 
least one component indicator in order to receive a CMS PSI 90 measure 
score for the HAC Reduction Program (81 FR 57012). Although the CMS PSI 
90 measure surpasses the accepted reliability standard, based on an 
Intracluster Correlation Coefficient (ICC) for hospital-level reporting 
of at least 0.60 (in a standard 24-month performance period, the CMS 
PSI 90 measure demonstrated median reliability of 0.74), a small subset 
of hospitals have a reliability close to zero for their CMS PSI 90 
composite score due to the current minimum volume threshold for the 
measure.
    To address this subset of hospitals with a CMS PSI 90 composite 
score with reliability close to zero, we are instituting a stricter 
minimum volume threshold for the measure, which would prevent those 
small hospitals from receiving a CMS PSI 90 composite score. Consistent 
with the current minimum volume threshold policy, hospitals that do not 
meet the threshold criteria would not receive a measure result or, 
subsequently, a measure score (that is., a Winsorized z-score) for the 
CMS PSI 90 measure and it would not factor into the calculation of 
their Total HAC Score. Accordingly, in this final rule, we are 
announcing an increased minimum volume threshold for the CMS PSI 90 
measure, under which hospitals would be required to meet both of the 
following criteria in order to receive a CMS PSI 90 composite score:
     One or more component PSI measure with at least 25 
eligible discharges; and
     Seven or more component PSI measures with at least three 
eligible discharges.
    We note that this change to the CMS PSI 90 minimum volume threshold 
criteria will be applied to both the version of the measure used in HAC 
Reduction Program scoring calculations as well as the version of the 
measure displayed on the main pages of the Care Compare tool hosted by 
the U.S. Department of Health and Human Services, currently available 
at https://www.medicare.gov/care-compare, via updates to the next 
version of the CMS PSI 90 software. Additional information regarding 
the technical specifications for the CMS PSI 90 measure can be found on 
the QualityNet website at https://qualitynet.cms.gov/inpatient/measures/psi/resources.
    An analysis of the impact of this threshold change on HAC Reduction 
Program results indicates that it would impact the scoring of a small 
number of low-volume hospitals. As a result of this threshold change, 
approximately five percent of hospitals would no longer receive a CMS 
PSI 90 composite score (and, subsequently, a CMS PSI 90 measure score) 
and approximately half of those hospitals, or 2.5 percent of all 
hospitals, would no longer receive a Total HAC Score. Accordingly, 
there will be a decrease in the number of hospitals in the worst-
performing quartile. We anticipate that the majority of the hospitals 
no longer receiving a Total HAC Score will be small hospitals with 
fewer than 100 beds. Rural

[[Page 49134]]

hospitals, which tend to have lower capacity, are also more impacted by 
the change than urban hospitals. The threshold change only impacts a 
small number of hospitals in the HAC Reduction Program while improving 
overall measure reliability.
    While we did not solicit comments on this technical measure 
specification update, we received some comments, which are summarized 
in this final rule.
    Comment: Several commenters supported the technical measure 
specification update to the minimum volume threshold for CMS PSI 90 
beginning with the FY 2023 HAC Reduction Program. A commenter expressed 
its belief that the update will minimize the unintended consequence of 
penalizing smaller or low volume hospitals based on scores that that 
may not demonstrate sufficient reliability.
    Response: We thank commenters for their support of the technical 
measure specification update to increase the minimum volume threshold 
for CMS PSI 90 beginning with the FY 2023 program year.
    Comment: A commenter expressed concern that the updated minimum 
volume threshold might omit many hospitals from being rated on CMS PSI 
90 and would remove these hospitals from accountability.
    Response: We appreciate commenter's position, however, as discussed 
in the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28451) the impact 
analysis of the threshold change indicated that it would impact the 
scoring of a small number of low-volume hospitals who have a CMS PSI 90 
measure reliability close to zero. Approximately just five percent of 
hospitals included in the HAC Reduction Program would no longer receive 
a CMS PSI 90 composite score (and, subsequently, a CMS PSI 90 measure 
score) and approximately just 2.5 percent of all hospitals would no 
longer receive a Total HAC Score. It should be noted CMS PSI 90 is 
unreliable for these very low-volume hospitals, as their computed 
scores from prior program years are tightly clustered around one (that 
is, the mean value for all hospitals).
    Comment: A commenter suggested that we obtain all-payer claims to 
drive up the denominators, increase reliability, and reduce the number 
of hospitals who do not qualify for a score. Another commenter 
recommended that we examine the ICC at minimum threshold rather than at 
the median and set the minimum volume at a number that will produce an 
ICC of 0.6 or higher.
    Response: We appreciate commenters' recommendations for additional 
refinements to the technical measure specification update to the 
minimum volume threshold for CMS PSI 90 beginning with the FY 2023 
program year. We will consider the feedback we received for future 
rulemaking.
    Comment: A commenter recommended that since the update to the 
minimum volume threshold would yield approximately 5 percent of 
hospitals no longer receiving a CMS PSI 90 score and half of those 
hospitals would no longer receive a Total HAC Score, CMS should reduce 
the number of hospitals penalized by a similar factor. The commenter 
also recommended given these changes to the measure specifications, CMS 
PSI 90 should be suppressed for the FY 2024 program year to allow time 
to evaluate the impacts of these specification updates.
    Response: We appreciate the suggestion to reduce the number of 
hospitals penalized for the FY 2024 HAC Reduction Program. We note that 
the HAC Reduction Program is statutorily required to penalize the 
worst-performing quartile (that is, the worst-performing 25 percent) of 
hospitals based on their Total HAC Score in a given program year. 
Hospitals that do not receive a Total HAC Score are not included in the 
distribution of hospitals used to determine the 75th percentile. 
Therefore, a decrease in the number of hospitals receiving a Total HAC 
Score will also lead to a decrease in the number of hospitals in the 
worst-performing quartile. We note that we did acknowledge this impact 
in the FY 2023 IPPS/LTCH proposed rule where we stated that this 
increase to the minimum volume threshold for CMS PSI 90 would likely 
yield a reduction in the number of hospitals in the worst-performing 
quartile for the HAC Reduction Program (87 FR 28451).
    We thank the commenter for their suggestion to suppress CMS PSI 90 
for the FY 2024 program year. Impact analyses have shown that this 
update to CMS PSI 90 measure specifications improves overall measure 
reliability, which in turn improves comparison between hospitals' CMS 
PSI 90 scores for HAC Reduction Program scoring purposes. Because this 
measure specification update improves the overall scoring process, we 
will not suppress CMS PSI 90 for the FY 2024 program year.
(2) Technical Measure Specification Update to Risk-Adjust for COVID-19 
Diagnoses in the CMS PSI 90 Measure Beginning With the FY 2024 HAC 
Reduction Program Year
    We refer readers to the FY 2022 IPPS/LTCH PPS final rule (86 FR 
45305) for previous analysis on the impact of the COVID-19 PHE on the 
CMS PSI 90 measure. Our analysis found that the decrease in volume 
continued in CY 2021 across all component PSI measures, especially 
those related to surgical procedures for which the denominator volume 
was 8 percent to 45 percent lower in the first two quarters of CY 2021 
than in the corresponding quarters of CY 2019. Our analysis also found 
that unadjusted rates continued to be high in CY 2021 for patients with 
a COVID-19 diagnosis compared to patients without a COVID-19 diagnosis, 
across most of the 10 component measures in CMS PSI 90. However, PSI 90 
component rates among patients without COVID-19 were virtually 
unchanged through the COVID-19 PHE. CMS has found that adjusting for 
COVID-19 at the patient level entirely removes the incremental risk 
associated with this diagnosis. After risk-adjustment for COVID-19, PSI 
component rates appear consistently flat across the first two quarters 
of 2021.
    In the FY 2015 IPPS/LTCH PPS final rule (79 FR 50100 through 
50101), we finalized a subregulatory process to make nonsubstantive 
updates to measures used for the HAC Reduction Program. To address the 
impact of the COVID-19 PHE on the CMS PSI 90 measure, we are announcing 
a technical update to the CMS PSI 90 software to include COVID-19 
diagnosis as a risk-adjustment parameter for the FY 2024 program year 
and subsequent years.
    While we did not solicit comments on this technical measure 
specification update, we received some comments, which are summarized 
in this final rule.
    Comment: Many commenters supported the technical measure 
specification update to risk-adjust for COVID-19 diagnosis in CMS PSI 
90 beginning with the FY 2024 program year. Several commenters believed 
that the update will help address the lingering impacts of the COVID-19 
PHE.
    Response: We thank commenters for their support of the technical 
measure specification update to risk-adjust for COVID-19 diagnosis 
present on admission in CMS PSI 90 beginning with the FY 2024 program 
year.
    Comment: A commenter recommended that CMS continue to monitor 
whether the PHE would necessitate additional measure changes.

[[Page 49135]]

Another commenter recommended that CMS review model performance before 
reinstituting payment penalties.
    Response: We agree with commenters' recommendations regarding 
continued monitoring of the effects of the COVID-19 PHE. We intend to 
work with measure developers to refine measure specifications as 
necessary and feasible for future rulemaking. We appreciate the 
commenter's feedback regarding reinstituting payment penalties under 
the HAC Reduction Program. As noted in section V.J.2.b.(2), we 
understand commenters' concerns regarding the impact of the COVID-19 
PHE and will ensure that we monitor and evaluate the data to determine 
if further suppression is warranted in the future. Though, we note that 
our goal is to continue resuming the use of measure data for the 
purposes of scoring and payment adjustment beginning with the FY 2024 
HACRP Program. Any proposal to suppress payment penalties for 
additional program years would be made through future notice-and-
comment rulemaking.
    Comment: A commenter does not support the technical measure 
specification update to risk-adjust for COVID-19 diagnosis in CMS PSI 
90 beginning with the FY 2024 program year and instead recommended that 
patients diagnosed with COVID-19 be included in measurement of 
preventable harms.
    Response: We appreciate the commenter's concern, however, as 
discussed in the FY 2022 IPPS/LTCH PPS final rule (86 FR 45305) where 
we conducted an analysis on the impacts of the COVID-19 PHE on CMS PSI 
90, we found that unadjusted rates continued to be high in CY 2021 for 
patients with a COVID-19 diagnosis compared to patients without a 
COVID-19 diagnosis, across most of the 10 component measures in CMS PSI 
90. In order to address the impact of the COVID-19 PHE on CMS PSI 90, 
we are implementing the technical measure specification update to risk 
adjusts for the COVID-19 to mitigate the impacts on measure results and 
ensure that hospitals are not unfairly scored or penalized through 
payment due to the COVID-19 PHE.
    Comment: A few commenters recommended that CMS release additional 
details on the CMS PSI 90 risk-adjustment methodology like whether 
risk-adjustment of COVID-19 diagnosis pertains to a patient's primary 
or secondary diagnosis. Several commenters recommended that CMS further 
assess CMS PSI 90 COVID-19 risk adjustment methodology and convene an 
NQF Technical Expert Panel to evaluate the methodology.
    Response: We seek to clarify that risk-adjustment details are 
released to the public when each version of the software is completed 
and made available. The first software version that would incorporate 
COVID-19 risk-adjustment would be version 13. The Risk Adjustment 
methodology report will be posted on the QualityNet site for CMS PSI 90 
Resources at https://qualitynet.cms.gov/inpatient/measures/psi/resources. We appreciate commenters' recommendations regarding the 
technical measure specification update to risk-adjust for COVID-19 
diagnosis present on admission in CMS PSI 90 beginning with the FY 2024 
program year. We note that the update to the risk adjustment 
methodology is part of the routine annual process to update CMS PSI 90. 
As part of that process, the measure developer will submit an annual 
update to NQF that includes updates to the risk adjustment model.\319\
---------------------------------------------------------------------------

    \319\ National Quality Forum. (2022). Maintenance of NQF-
Endorsed Performance Measures. Available at: https://www.qualityforum.org/measuring_performance/endorsed_performance_measures_maintenance.aspx.
---------------------------------------------------------------------------

    Comment: A few commenters recommended that CMS implement the COVID-
19 risk-adjustment as well as suppress CMS PSI 90 for the first two 
quarters of CY 2021 of the FY 2024 program year due to the impact of 
the COVID-19 PHE on hospitals.
    Response: We appreciate the commenter's recommendations to risk 
adjust for COVID-19 and suppress CMS PSI 90 in FY 2024. We will monitor 
performance in CMS PSI 90 and will consider any issues we identify for 
future rulemaking.
    Comment: A commenter suggested that CMS consider suppression of CMS 
PSI 90 for the FY 2024 program year based on the evaluation of the 
technical update impacts as well as impacts from the COVID-19 PHE.
    Response: We appreciate the commenter's recommendations to suppress 
CMS PSI 90 for the FY 2024 program year based on evaluation of the CMS 
PSI 90 risk adjustment for COVID-19. We will monitor performance in CMS 
PSI 90 and will consider any issues we identify for future rulemaking.
    Comment: A few commenters expressed concern that CMS PSI 90 COVID-
19 risk adjustment would reduce the amount of attention and monitoring 
for patients diagnosed with COVID-19. A commenter recommended that CMS 
not risk adjust for COVID-19 to address this concern.
    Response: We appreciate the commenters concern that CMS PSI 90 
COVID-19 risk adjustment would reduce the amount of attention and 
monitoring for patients diagnosed with COVID-19. However, in the FY 
2023 IPPS/LTCH proposed rule, we stated that our analysis of CMS PSI 90 
found that unadjusted rates continued to be high in CY 2021 for 
patients with a COVID-19 diagnosis compared to patients without a 
COVID-19 diagnosis, across most of the 10 component measures. We note 
that rates for the component PSI 90 measures among patients without 
COVID-19 were virtually unchanged through the COVID-19 PHE. We have 
found that adjusting for COVID-19 at the patient level entirely removes 
the incremental risk associated with this diagnosis (87FR 28450). In 
order to address the impact of the COVID-19 PHE on CMS PSI 90, we are 
implementing this technical measure specification update to ensure that 
hospitals are not unfairly scored or penalized through payment due to 
the COVID-19 PHE. Additionally, due to the potentially geographically 
disparate impacts of the COVID-19 PHE, we believe that risk-adjusting 
CMS PSI 90 is appropriate to ensure hospitals are not unevenly 
penalized due to their location.
    Comment: A commenter recommended that CMS only confidentially 
report, without publicly reporting, CMS PSI 90 due to the impacts of 
COVID-19 for the FY 2024 program year.
    Response: We appreciate the commenter's recommendation to not 
publicly report data for CMS PSI 90 in the FY 2024 program year. To 
account for the impact of the COVID-19 PHE on CY 2021 data in CMS PSI 
90, however, we are updating the measure specifications to risk-adjust 
for COVID-19 diagnoses present on admission. As discussed in the FY 
2023 IPPS/LTCH PPS proposed rule (87 FR 28450), our analysis of the 
COVID-19 PHE impacts on CY 2021 data found that the decrease in volume 
continued in CY 2021 across nearly all component PSI measures, 
especially those related to surgical procedures (for which the 
denominator volume was 8 percent to 45 percent lower in the first two 
quarters of CY 2021 than in the corresponding quarters of CY 2019). Our 
analysis also found that unadjusted rates continued to be high in CY 
2021 for patients with a COVID-19 diagnosis compared to patients 
without a COVID-19 diagnosis. We believe that modifying our proposal to 
publicly report the CMS PSI 90 measure data for the FY 2023 HAC 
Reduction Program and continuing to

[[Page 49136]]

publicly report measure data for the FY 2024 HAC Reduction Program will 
maintain transparency and support consumers in making informed 
decisions on where to receive care.
    Comment: A commenter expressed concern that the modified PSI 90 
measure and the partially suppressed HAI measure will not allow for 
equitable and meaningful Total HAC Scores for FY 2024.
    Response: We appreciate the commenters' concern about the 
meaningfulness of the Total HAC Score for FY 2024 due to the proposed 
measure suppression and technical measure specification updates. As 
discussed in the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28450), we 
continue to be concerned about measure performance and the national 
comparability of such performance during the CY 2021 (87 FR 28450). We 
believe national comparability of hospital performance is very 
significant, so we are pursuing suppression of the CY 2021 data of the 
CDC NHSN HAI measures and risk adjustment for COVID-19 diagnosis in CMS 
PSI 90 to account for COVID-19 diagnosis in the CY 2021.
    Comment: A commenter suggested that the COVID-19 risk adjustment 
may not accurately capture COVID-19 diagnosis due to at-home testing 
and absence of diagnosis codes.
    Response: We acknowledge the commenter's concern about the accuracy 
of risk adjusting for COVID-19 in CMS PSI 90. Although COVID-19 
diagnoses may be under-reported to public health authorities due to at-
home testing, this concern does not apply to inpatient hospitals that 
routinely repeat at-home test results.
d. HAC Reduction Program Requests for Information
(1) Digital CDC NHSN Measures
    We refer readers to section IX.E.9.a. of this final rule, for a 
discussion of the comments received regarding this cross-program 
request for information on the potential future adoption of two digital 
NHSN measures, the NHSN Healthcare-associated Clostridioides difficile 
Infection Outcome Measure and the NHSN Hospital-Onset Bacteremia & 
Fungemia Outcome Measure, into the Hospital IQR Program, PCHQR Program, 
and the LTCH QRP. In addition, we requested information on the 
potential inclusion of these digital CDC NHSN measures in the HAC 
Reduction Program. This request for information supports our goal of 
moving fully to digital quality measurement in CMS quality reporting 
and value-based purchasing programs, including the HAC Reduction 
Program.
(2) Overarching Principles for Measuring Healthcare Quality Disparities 
Across CMS Quality Programs
    We refer readers to section IX.B. of this final rule where we 
sought input on overarching principles in measuring healthcare quality 
disparities in hospital quality and value-based purchasing programs.
4. Proposal To Update the CDC NHSN HAI Data Submission Requirements for 
Newly Opened Hospitals Beginning in the FY 2023 HAC Reduction Program 
Year
    In the FY 2017 IPPS/LTCH PPS final rule (81 FR 57013), we finalized 
CDC NHSN HAI data submission requirements for newly-opened hospitals 
under the HAC Reduction Program that referred to the date that a 
hospital filed a notice of participation (NOP) with the Hospital IQR 
Program. At the time, the HAC Reduction Program obtained measure 
results that hospitals submitted to the CDC NHSN from the Hospital IQR 
Program. However, in the FY 2019 IPPS/LTCH PPS final rule (83 FR 41545 
through 41553), we transferred our collection of the CDC NHSN HAI 
measures from the Hospital IQR Program to the HAC Reduction Program 
beginning with CY 2020 data. Given the transition from the Hospital IQR 
Program, the NOP requirements noted in the FY 2017 IPPS/LTCH PPS final 
rule do not apply.
    We proposed to update the definition of ``newly-opened hospitals'' 
for the CDC NHSN HAI measures to include hospitals with a Medicare 
Accept Date within the last 12 months of the performance period.\320\ 
Under the HAC Reduction Program scoring methodology, hospitals that are 
defined as newly-opened hospitals for the CDC NHSN HAI measures would 
not receive a measure score for any of the CDC NHSN HAI measures.
---------------------------------------------------------------------------

    \320\ Because the CMS PSI 90 measure requires at least 12 months 
of measure data (81 FR 50712), hospitals that open during the final 
12 months of the performance period would also not receive a CMS PSI 
90 measure score.
---------------------------------------------------------------------------

    The number of hospitals impacted by this change in criteria is 
small, less than one-quarter percent of hospitals. Hospitals with a 
Medicare Accept Date between the 12th and the 6th month before the end 
of the HAI performance period (January 1, 2021 to June 30, 2021 for the 
FY 2023 program year) do not meet the current criteria for newly-opened 
hospitals for the CDC NHSN HAI measures, but would meet the updated 
criteria.\321\ In addition, all of these hospitals do not have 12 
months of CMS PSI 90 data and because of this already do not receive a 
measure score for that measure. Therefore, all impacted hospitals would 
not receive a Total HAC Score for the program year and could not be 
subject to the one percent payment reduction. As per the measure 
suppression policy discussed in section V.J.2.b.(2). we proposed to 
suppress all six measures in the program for the FY 2023 program year, 
so no hospitals will be impacted by this change for the FY 2023 program 
year.
---------------------------------------------------------------------------

    \321\ There is a small subset of hospitals with a Medicare 
Accept Date between the 6th and 9th month before the end of the HAI 
performance period (April 1, 2021, to June 30, 2021 for the FY 2023 
program year) and a Hospital IQR Program Notice of Participation 
Date during the last quarter of the HAI performance period (before 
October 1, 2021 or after December 31, 2021 for the FY 2023 program 
year), that are also currently defined as newly-opened hospitals. 
These hospitals' newly-opened status would not be impacted by this 
criteria change.
---------------------------------------------------------------------------

    An analysis of the number of hospitals not meeting the current 
definition of ``new hospitals'' that would meet the criteria under this 
new proposed definition indicate that 0.22 percent of hospitals would 
have been affected by this definition change in the FY 2021 program 
year and 0.09 percent in the FY 2020 program year.
    We invited public comments on this proposal to update the newly-
opened hospital definition for CDC NHSN HAI measures beginning in the 
FY 2023 program year.
    Comment: A commenter supported the proposal to update the CDC NHSN 
HAI data submission requirements for newly opened hospitals beginning 
in the FY 2023 HAC Reduction Program and recommended that CMS ensure 
the proposal does not increase hospital compliance burden.
    Response: We thank the commenter for its support and note that the 
proposal does not affect requirements for data submission, but only 
affects which hospitals receive a measure score.
    After consideration of the public comments we received, we are 
finalizing our proposal to update the ``newly-opened hospital'' 
definition for CDC NHSN HAI measures beginning in the FY 2023 program 
year.
5. HAC Reduction Program Scoring Methodology and Scoring Review and 
Corrections Period
    In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41484 through 
41489), we adopted the Equal Measure Weights approach to scoring and 
clarified the Scoring Calculations Review and

[[Page 49137]]

Correction Period (83 FR 41484) for the HAC Reduction Program. 
Hospitals must register for a QualityNet website's secure portal 
account in order to access their annual hospital-specific reports. In 
this final rule we are not making any changes to the Scoring 
Calculations Review and Correction Period process.
    We note that in the FY 2023 IPPS/LTCH PPS proposed rule, we 
proposed to temporarily suppress all measures from the FY 2023 HAC 
Reduction Program. We proposed to calculate the measure results for the 
five CDC NHSN HAI measures for the FY 2023 HAC Reduction Program, but 
to not use those measure results to calculate measure scores (that is, 
Winsorized z-scores) for any of the measures because of our concerns 
regarding the comparability of measure results. Additionally, we 
proposed to not calculate measure results for the CMS PSI 90 measure 
nor publicly report the measure on the Care Compare tool hosted by 
Health and Human Services and the Provider Data Catalog. We also 
proposed that all hospitals would receive a Total HAC Score of zero, 
and no hospitals would receive a penalty for FY 2023. We intend to 
resume the previously adopted HAC Reduction Program scoring methodology 
in FY 2024 (with the proposed suppression of CY 2021 CDC NHSN HAI data 
as discussed in section V.J.2.b.(3).) and for subsequent years. In 
section V.J.2.b.(2)., we invited public comment on the proposal to 
temporarily suppress all measures from the FY 2023 HAC Reduction 
Program.
6. Validation of HAC Reduction Program Data
    In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41478 through 
41484), we adopted processes to validate the CDC NHSN HAI measure data 
used in the HAC Reduction Program, because the Hospital IQR Program 
finalized its proposals to remove CDC NHSN HAI measures from its 
program. In the FY 2020 IPPS/LTCH PPS final rule (84 FR 42406 through 
42410), we provided additional clarification to the validation 
selection and scoring methodology. We also refer readers to the 
QualityNet website for more information regarding chart-abstracted data 
validation of measures. In the FY 2020 IPPS/LTCH PPS final rule (85 FR 
58862 through 58865), we finalized our policy to align the HAC 
Reduction Program validation process with that of the Hospital IQR 
Program. Specifically, we aligned the hospital selection and submission 
quarters beginning with CY 2021 data for the FY 2024 Hospital IQR and 
HAC Reduction Programs validation so that we only require one pool of 
hospitals to submit data for validation. Additionally, we finalized a 
policy requiring hospitals to submit digital files when submitting 
medical records for validation of HAC Reduction Program measures, for 
the FY 2024 program year and subsequent years.
    In the FY 2021 IPPS/LTCH PPS final rule (85 FR 58862 through 
58865), we finalized our policy that for the FY 2024 program year and 
subsequent years, we will use measure data from all of CY 2021 for both 
the HAC Reduction Program and the Hospital IQR Program, which must be 
reported using the validation schedule posted on the QualityNet Secure 
Portal (also referred to as the Hospital Quality Reporting (HQR) 
System.
    In the FY 2023 IPPS/LTCH PPS proposed rule, we proposed to suppress 
all measures from the FY 2023 program and CY 2021 CDC NHSN HAI data 
from the FY 2024 HAC Reduction Program, respectively. As discussed in 
those sections, hospitals are still required to submit such data and 
such data will be used for validation purposes. If hospitals do not 
submit measure data for validation during the FY 2024 program year, 
then those hospitals will automatically receive the maximum Winsorized 
z-score for the measure in the FY 2024 program year payment 
calculation. We therefore are not making any changes to the policies 
regarding measure validation in this final rule.
7. Clarification of the Removal of the ``No Mapped Locations'' Policy 
Beginning With the FY 2023 Program Year
    Under the HAC Reduction Program, hospitals have historically been 
able to receive a ``no mapped locations (NML)'' exemption \322\ for the 
CLABSI and CAUTI measures.\323\ This exemption has been applied when 
hospitals do not map an applicable ward (that is, Intensive Care Units 
(ICUs), surgical, medical, and medical-surgical wards) in the NHSN 
system, do not submit data for the measures, and do not submit an IPPS 
Measure Exception Form.\324\
---------------------------------------------------------------------------

    \322\ Prior to FY 2018, the program used the term No Facilities 
Waiver for this same situation. Centers for Medicare & Medicaid 
Services. (2017). HACRP HAI Webinar Slides Final. Available at: 
https://www.qualityreportingcenter.com/globalassets/migrated-pdf/vbp-iqr-hacrp_hai_webinar_slides_vfinal508.pdf.
    \323\ Centers for Medicare and Medicaid Services. (2021). FY 
2022 HACRP HSR User Guide. Available at: https://qualitynet.cms.gov/files/61152cf0a248cb001efce449?filename=FY_2022_HACRP_HSR_User_Guide.pdf.
    \324\ The valid OMB control number for the IPPS Measure 
Exception Form is 0938-1022.
---------------------------------------------------------------------------

    In this final rule we would like to clarify the removal of the No 
Mapped Locations (NML) policy. The CDC has confirmed that the NML 
exemption does not indicate that a hospital does not need to report 
data, and that hospitals requesting to be exempt from reporting for CMS 
quality programs including the HAC Reduction Program, should submit an 
IPPS Measure Exception Form on the QualityNet website at https://qualitynet.cms.gov/files/5e3459aa152a7d001f93d36c?filename=IPPS_MeasureExceptionForm_CY2020.pdf. 
Therefore, we want to clarify that beginning in FY 2023 and subsequent 
years, the NML designation will no longer apply, and hospitals will be 
required to appropriately submit data to the NHSN or, if hospitals do 
not have the applicable locations for the CLABSI and CAUTI measures, 
the hospital must submit an IPPS Measure Exception Form to be exempt 
from CLABSI and CAUTI reporting for CMS programs. If the hospitals do 
not submit an IPPS Measure Exception Form and continue to not submit 
data to the NHSN, these hospitals would receive the maximum measure 
score (that is., Winsorized z-score) under the HAC Reduction Program 
for not reporting data. In the FY 2020 IPPS/LTCH PPS final rule, we 
instructed hospitals that do not have adequate locations for CLABSI or 
CAUTI reporting to submit the IPPS Measure Exception Form to the HAC 
Reduction Program beginning on January 1, 2020 (84 FR 42406), and the 
removal of the NML policy has previously been communicated in the FY 
2022 HAC Reduction Program Frequently Asked Questions \325\ and the FY 
2022 HAC Reduction Program HSR User Guide.\326\ Additionally, because 
NML only applies to a small subset of hospitals, we plan to execute 
targeted outreach via email to those hospitals that had received the 
exception in the past two program years notifying them of the removal 
of the NML policy.
---------------------------------------------------------------------------

    \325\ Centers for Medicare and Medicaid Services. (2021). FY 
2022 HACRP FAQs. Available at: https://qualitynet.cms.gov/files/61152d1252b92f00229e9717?filename=FY_2022_HACRP_FAQ.pdf.
    \326\ Centers for Medicare and Medicaid Services. (2021). FY 
2022 HACRP HSR User Guide. Available at: https://qualitynet.cms.gov/files/61152cf0a248cb001efce449?filename=FY_2022_HACRP_HSR_User_Guide.pdf.
---------------------------------------------------------------------------

    For more details on the NML designation and policy, we refer 
readers to the FY 2022 Hospital Specific Report (HSR) User Guide 
located on QualityNet website at https://qualitynet.cms.gov/files/61152cf0a248cb001efce449?filename=FY_2022_HACRP_HSR_User_Guide.pdf and 
the FY 2022 HAC Reduction Program Frequently Asked Questions website at 
https://

[[Page 49138]]

qualitynet.cms.gov/files/61152d1252b92f00229e9717?filename=FY_2022_HACRP_FAQ.pdf.
    While we did not solicit comments on this clarification, we 
received some comments, which are summarized later in this section.
    Comment: A commenter supported the clarification of the removal of 
the No Mapped Locations policy and recommended that targeted outreach 
to affected hospitals be expanded beyond email.
    Response: We thank the commenter for its support for the removal of 
the No Mapped Locations policy and we will take into consideration the 
recommendation to expand targeted outreach to additional modalities 
beyond email correspondence.
    Comment: A commenter did not support the requirement for hospitals 
to submit an IPPS Measure Exception Form to be exempt from CLABSI and 
CAUTI reporting for our programs when they have no applicable 
locations.
    Response: We appreciate the commenter's concern; however, we 
believe that this requirement is necessary to maintain alignment with 
the CDC's recommendations as well as ensure clear and transparent 
hospital reporting.
8. Extraordinary Circumstances Exception (ECE) Policy for the HAC 
Reduction Program
    We refer readers to the FY 2016 IPPS/LTCH PPS final rule (80 FR 
49579 through 49581) and the FY 2018 IPPS/LTCH PPS final rule (82 FR 
38276 through 38277) for discussion of our Extraordinary Circumstances 
Exception (ECE) policy. In the FY 2016 IPPS/LTCH PPS final rule (80 FR 
49579 through 49581), we adopted an ECE policy for the HAC Reduction 
Program, which recognized that there may be periods of time during 
which a hospital is not able to submit data in an accurate or timely 
fashion due to an extraordinary circumstance beyond its control. When 
adopting this policy, we noted that we considered the feasibility and 
implications of excluding data for certain measures for a limited 
period of time from the calculations for a hospital's measure results 
or Total HAC Score for the applicable performance period. By minimizing 
the data excluded from the program, the policy enabled affected 
hospitals to continue to participate in the HAC Reduction Program for a 
given fiscal year if they otherwise continued to meet applicable 
measure minimum threshold requirements. We expressed the belief that 
this approach would help alleviate the burden for a hospital that might 
be adversely impacted by a natural disaster or other extraordinary 
circumstance beyond its control, while enabling the hospital to 
continue to participate in the HAC Reduction Program. In developing 
this policy, we considered a policy and process similar to that for the 
Hospital IQR Program, as finalized in the FY 2012 IPPS/LTCH PPS final 
rule (76 FR 51651), modified by the FY 2014 IPPS/LTCH PPS final rule 
(78 FR 50836) (designation of a non-CEO hospital contact), and further 
modified in the FY 2015 IPPS/LTCH PPS final rule (79 FR 50277) (amended 
Sec.  412.40(c)(2)) to refer to ``extension or exemption'' instead of 
the former ``extension or waiver''). We also considered how best to 
align an extraordinary circumstance exception policy for the HAC 
Reduction Program with existing extraordinary circumstance exception 
policies for other IPPS quality reporting and payment programs, such as 
the Hospital Value-Based Purchasing (VBP) Program, to the extent 
feasible. In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38276 through 
38277), we modified the requirements for the HAC Reduction Program ECE 
policy to further align with the processes used by other quality 
reporting and value-based purchasing programs for requesting an 
exception from program reporting due to an extraordinary circumstance 
not within a provider's control.
    In response to the COVID-19 PHE, we announced relief for 
clinicians, providers, hospitals, and facilities participating in 
Medicare quality reporting and value-based purchasing programs. On 
September 2, 2020, we published the interim final rule with comment 
period (IFC), ``Medicare and Medicaid Programs, Clinical Laboratory 
Improvement Amendments (CLIA), and Patient Protection and Affordable 
Care Act; Additional Policy and Regulatory Revisions in Response to the 
COVID-19 Public Health Emergency'' (85 FR 54820). The IFC updated the 
ECE we granted in response to the COVID-19 PHE, for the HAC Reduction 
Program and several other quality reporting programs (85 FR 54827 
through 54838). In the IFC, we updated the previously announced 
application of our ECE policy for the HAC Reduction Program (85 FR 
54830 through 54832) to the COVID-19 PHE to exclude any CDC NHSN HAI 
data submitted regarding care provided during the first and second 
quarters of CY 2020 from our calculation of performance for FY 2022 and 
FY 2023.
    In the FY 2022 IPPS/LTCH PPS final rule (86 FR 45308 through 
45310), we clarified our ECE policy to highlight that an ECE granted 
under the HAC Reduction Program may allow an exception from quality 
data reporting requirements and may grant a request to exclude any data 
submitted (whether submitted for claims purposes or to the CDC NHSN) 
from the calculation of a hospital's measure results or Total HAC Score 
for the applicable period, depending on the exact circumstances under 
which the request was made.
    Finally, in the FY 2022 IPPS/LTCH PPS final rule we clarified that, 
although an approved ECE for the HAC Reduction Program would exclude 
excepted data and grant an exception with respect to data reporting 
requirements for the period during which performance or ability to 
submit data was impacted or both, a hospital would still be evaluated 
for the remainder of the applicable period during which performance and 
ability to submit data was not impacted (to the extent that enough data 
are available to ensure that the calculation is statistically sound) or 
both. We clarified that an approved ECE for the HAC Reduction Program 
does not exempt hospitals from payment reductions under the HAC 
Reduction Program (86 FR 45309 through 45310).
    We have not made any changes to our previously finalized ECE Policy 
in this final rule.

K. Rural Community Hospital Demonstration Program

1. Introduction
    The Rural Community Hospital Demonstration was originally 
authorized by section 410A of the Medicare Prescription Drug, 
Improvement, and Modernization Act of 2003 (MMA) (Pub. L. 108-173). The 
demonstration has been extended three times since the original 5-year 
period mandated by the MMA, each time for an additional 5 years. These 
extensions were authorized by sections 3123 and 10313 of the Affordable 
Care Act (ACA) (Pub. L. 111-148), section 15003 of the 21st Century 
Cures Act (Pub. L. 114-255) (Cures Act) enacted in 2016, and most 
recently, by section 128 of the Consolidated Appropriations Act of 2021 
(Pub. L. 116-260). In this final rule, we follow upon the FY 2023 IPPS 
proposed rule, and summarize the status of the demonstration program, 
and the ongoing methodologies for implementation and budget neutrality.
    We are also stating the finalized amount to be applied to the 
national IPPS payment rates to account for the costs of the 
demonstration in FY 2023, and, in addition, the reconciled amount of 
demonstration costs for FY 2017, the

[[Page 49139]]

most recent year for which finalized cost reports have become 
available.
2. Background
    Section 410A(a) of Public Law 108-173 required the Secretary to 
establish a demonstration program to test the feasibility and 
advisability of establishing rural community hospitals to furnish 
covered inpatient hospital services to Medicare beneficiaries. The 
demonstration pays rural community hospitals under a reasonable cost-
based methodology for Medicare payment purposes for covered inpatient 
hospital services furnished to Medicare beneficiaries. A rural 
community hospital, as defined in section 410A(f)(1), is a hospital 
that--
     Is located in a rural area (as defined in section 
1886(d)(2)(D) of the Act) or is treated as being located in a rural 
area under section 1886(d)(8)(E) of the Act;
     Has fewer than 51 beds (excluding beds in a distinct part 
psychiatric or rehabilitation unit) as reported in its most recent cost 
report;
     Provides 24-hour emergency care services; and
     Is not designated or eligible for designation as a CAH 
under section 1820 of the Act.
3. Policies for Implementing the 5-Year Extension Period Authorized by 
Public Law 116-260
    Our policy for implementing the 5-year extension period authorized 
by Public Law 116-260 (the Consolidated Appropriations Act of 2021) 
follows upon that for the previous extensions, under the ACA (Pub. L. 
111-148) and the Cures Act (Pub. L.114-255).
    Section 410A of Public Law 108-173 (MMA) initially required a 5-
year period of performance. Subsequently, sections 3123 and 10313 of 
Pub. L. 111-148 (ACA) required the Secretary to conduct the 
demonstration program for an additional 5-year period, to begin on the 
date immediately following the last day of the initial 5-year period. 
Public Law 111-148 required the Secretary to provide for the continued 
participation of rural community hospitals in the demonstration program 
during this 5-year extension period, in the case of a rural community 
hospital participating in the demonstration program as of the last day 
of the initial 5-year period, unless the hospital made an election to 
discontinue participation. In addition, Public Law 111-148 limited the 
number of hospitals participating to no more than 30.
    Section 15003 of the Cures Act required the Secretary to conduct 
the demonstration for a 10-year extension period (in place of the 5-
year extension period required by Public Law 111-148 (ACA)). 
Specifically, section 15003 of Public Law 114-255 (Cures Act) amended 
section 410A(g)(4) of Public Law 108-173 (MMA) to require that, for 
hospitals participating in the demonstration as of the last day of the 
initial 5-year period, the Secretary would provide for continued 
participation of such rural community hospitals in the demonstration 
during the 10-year extension period, unless the hospital made an 
election, in such form and manner as the Secretary may specify, to 
discontinue participation. In addition, section 15003 of Public Law 
114-255 added subsection (g)(5) to section 410A of Public Law 108-173 
to require that, during the second 5 years of the 10-year extension 
period, the Secretary would apply the provisions of section 410A(g)(4) 
of Public Law 108-173 to rural community hospitals not described in 
subsection (g)(4) but that were participating in the demonstration as 
of December 30, 2014, in a similar manner as such provisions apply to 
hospitals described in subsection (g)(4).
    In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38280), we finalized 
our policy with regard to the effective date for the application of the 
reasonable cost-based payment methodology under the demonstration for 
those previously participating hospitals choosing to participate in the 
second 5-year extension period. According to our finalized policy, each 
previously participating hospital began the second 5 years of the 10-
year extension period and payment for services provided under the cost-
based payment methodology under section 410A of Public Law 108-173 (as 
amended by section 15003 of Pub. L. 114-255) on the date immediately 
after the period of performance ended under the first 5-year extension 
period.
    Seventeen of the 21 hospitals that completed their periods of 
participation under the extension period authorized by Public Law 111-
148 (ACA) elected to continue in the 5-year extension period authorized 
by Public Law 114-255 (Cures Act). Therefore, for these hospitals, this 
third 5-year period of participation started on dates ranging from May 
1, 2015 through January 1, 2017, depending on when they had initially 
started.
    On November 20, 2017, we announced that 13 additional hospitals 
were selected to participate in the demonstration in addition to these 
17 hospitals continuing participation from the first 5-year extension 
period. (These two groups are referred to as ``newly participating'' 
and ``previously participating'' hospitals, respectively.) We announced 
that each of these newly participating hospitals would begin its 5-year 
period of participation effective with the start of the first cost-
reporting period on or after October 1, 2017. One of the newly 
participating hospitals withdrew from the demonstration program prior 
to beginning participation in the demonstration on July 1, 2018. In 
addition, one of the previously participating hospitals closed 
effective January 2019, and another withdrew effective October 1, 2019. 
Therefore, 27 hospitals were participating in the demonstration as of 
October 1, 2019--15 previously participating and 12 newly 
participating.
    Each hospital has had its own end date applicable to this third 
five-year period for the demonstration. For four of the previously 
participating hospitals, this end date fell within FY 2020, while for 
11 of the previously participating hospitals, the end date fell within 
CY 2021. (One of the hospitals within this group chose in February of 
2020 to withdraw effective September of the previous year). The newly 
participating hospitals were all scheduled to end their participation 
either at the end of FY 2022 or during FY 2023.
    Section 128 of the Consolidated Appropriations Act of 2021 (CAA), 
Public Law 116-260 requires a 15-year extension period, to begin on the 
date immediately following the last day of the initial 5-year period, 
instead of the 10-year extension period mandated by the Public Law 114-
255 (Cures Act). In addition, the statute provides for continued 
participation for all hospitals participating in the demonstration 
program as of December 30, 2019. Therefore, in the FY 2022 IPPS final 
rule (86 FR 45314), we stated our interpretation of the statute as 
providing for an additional 5-year period under the reasonable cost-
based reimbursement methodology for the demonstration for the 26 
hospitals whose effective participation extended back to December 30, 
2019.
    Given that four hospitals ended the 5-year period authorized by the 
Cures Act during FY 2020, we finalized the policy from previous 
extensions, that is, to apply the cost-based reimbursement methodology 
to the date following the last day of this previous period for each 
hospital that elects to continue participation. Likewise, each of the 
22 hospitals with a scheduled end date during 2021, 2022, or 2023 is 
eligible for an additional 5-year period starting from the day after 
the specified end date. Accordingly, the period of participation for 
the last hospital in the demonstration under this most recent

[[Page 49140]]

legislative authorization would extend until June 30, 2028.
4. Budget Neutrality
a. Statutory Budget Neutrality Requirement
    Section 410A(c)(2) of Public Law 108-173 requires that, in 
conducting the demonstration program under this section, the Secretary 
shall ensure that the aggregate payments made by the Secretary do not 
exceed the amount that the Secretary would have paid if the 
demonstration program under this section was not implemented. This 
requirement is commonly referred to as ``budget neutrality.'' 
Generally, when we implement a demonstration program on a budget 
neutral basis, the demonstration program is budget neutral on its own 
terms; in other words, the aggregate payments to the participating 
hospitals do not exceed the amount that would be paid to those same 
hospitals in the absence of the demonstration program. We note that the 
payment methodology for this demonstration, that is, cost-based 
payments to participating small rural hospitals, makes it unlikely that 
increased Medicare outlays will produce an offsetting reduction to 
Medicare expenditures elsewhere. Therefore, in the 12 IPPS final rules 
spanning the period from FY 2005 through FY 2016, we adjusted the 
national inpatient PPS rates by an amount sufficient to account for the 
added costs of this demonstration program, thus applying budget 
neutrality across the payment system as a whole rather than merely 
across the participants in the demonstration program. (A different 
methodology was applied for FY 2017.) As we discussed in the FYs 2005 
through 2017 IPPS/LTCH PPS final rules (69 FR 49183; 70 FR 47462; 71 FR 
48100; 72 FR 47392; 73 FR 48670; 74 FR 43922, 75 FR 50343, 76 FR 51698, 
77 FR 53449, 78 FR 50740, 77 FR 50145; 80 FR 49585; and 81 FR 57034, 
respectively), we believe that the statutory language of the budget 
neutrality requirements permits the agency to implement the budget 
neutrality provision in this manner.
b. General Budget Neutrality Methodology
    We have generally incorporated two components into the budget 
neutrality offset amounts identified in the final IPPS rules in 
previous years. First, we have estimated the costs of the demonstration 
for the upcoming fiscal year, generally determined from historical, 
``as submitted'' cost reports for the hospitals participating in that 
year. Update factors representing nationwide trends in cost and volume 
increases have been incorporated into these estimates, as specified in 
the methodology described in the final rule for each fiscal year. 
Second, as finalized cost reports became available, we determined the 
amount by which the actual costs of the demonstration for an earlier, 
given year differed from the estimated costs for the demonstration set 
forth in the final IPPS rule for the corresponding fiscal year, and 
incorporated that amount into the budget neutrality offset amount for 
the upcoming fiscal year. If the actual costs for the demonstration for 
the earlier fiscal year exceeded the estimated costs of the 
demonstration identified in the final rule for that year, this 
difference was added to the estimated costs of the demonstration for 
the upcoming fiscal year when determining the budget neutrality 
adjustment for the upcoming fiscal year. Conversely, if the estimated 
costs of the demonstration set forth in the final rule for a prior 
fiscal year exceeded the actual costs of the demonstration for that 
year, this difference was subtracted from the estimated cost of the 
demonstration for the upcoming fiscal year when determining the budget 
neutrality adjustment for the upcoming fiscal year.
    We note that we have calculated this difference for FYs 2005 
through 2016 between the actual costs of the demonstration as 
determined from finalized cost reports once available, and estimated 
costs of the demonstration as identified in the applicable IPPS final 
rules for these years.
c. Budget Neutrality Methodology for the Extension Period Authorized by 
Public Law 116-260
    For the newly enacted extension period, under the CAA, we continue 
upon the general budget neutrality methodology used in previous years, 
and to specifically follow upon the determinations for the previous 
extension period, under the Cures Act.
(1) Budget Neutrality Methodology for Previous Extension Period Under 
the Cures Act
    We finalized our budget neutrality methodology for periods of 
participation under this previous 5-year extension period in the FY 
2018 IPPS/LTCH PPS final rule (82 FR 38285 through 38287). Similar to 
previous years, we stated in this rule, as well as in the FY 2019 and 
FY 2020 IPPS/LTCH PPS proposed and final rules (83 FR 20444 and 41503, 
and 84 FR 19452 and 42421, respectively) that we would incorporate an 
estimate of the costs of the demonstration, generally determined from 
historical, ``as submitted'' cost reports for the participating 
hospitals, and appropriate update factors, into a budget neutrality 
offset amount to be applied to the national IPPS rates for the upcoming 
fiscal year. In addition, we stated that we would continue to apply our 
general policy from previous years of including, as a second component 
to the budget neutrality offset amount, the amount by which the actual 
costs of the demonstration for an earlier, given year (as determined 
from finalized cost reports, when available) differed from the 
estimated costs for the demonstration set forth in the final IPPS rule 
for the corresponding fiscal year.
    In these proposed and final rules, we described several distinct 
components to the budget neutrality offset amount for the specific 
fiscal years of the extension period authorized by Public Law 114-255 
(Cures Act).
    We included a component to our overall methodology similar to 
previous years, according to which an estimate of the costs of the 
demonstration for both previously and newly participating hospitals for 
the upcoming fiscal year is incorporated into a budget neutrality 
offset amount to be applied to the national IPPS rates for the upcoming 
fiscal year. In the FY 2019 IPPS final rule (83 FR 41506), we included 
such an estimate of the costs of the demonstration for each of FYs 2018 
and 2019 into the budget neutrality offset amount for FY 2019. In the 
FY 2020 IPPS final rule (84 FR 42421), we included an estimate of the 
costs of the demonstration for FY 2020 for 28 hospitals. In the FY 2021 
IPPS final rule (85 FR 58873), we included an estimate of the costs of 
the demonstration for FY 2021 for the 22 hospitals for which the cost-
based reimbursement methodology was to apply for all or part of FY 
2021. In the FY 2022 IPPS final rule (86 FR 45316), we included an 
estimate of the costs of the demonstration for FY 2022 for the 26 
hospitals expected to participate in that fiscal year.
    Similar to previous years, we continued to implement the policy of 
determining the difference between the actual costs of the 
demonstration as determined from finalized cost reports for a given 
fiscal year and the estimated costs indicated in the corresponding 
year's final rule, and including that difference as a positive or 
negative adjustment in the upcoming year's final rule. (For each 
previously participating hospital that decided to participate in the 5-
year extension period under the Cures Act, the cost-based payment 
methodology under the demonstration

[[Page 49141]]

began on the date immediately following the end date of its period of 
performance for the still previous extension period (under the ACA). In 
addition, for previously participating hospitals that converted to CAH 
status during the time period of the second 5-year extension period, 
the demonstration payment methodology was applied to the date following 
the end date of its period of performance for the first extension 
period to the date of conversion). In the FY 2020 final rule, we 
included the difference between the amount determined for the cost of 
the demonstration in each of FYs 2014 and 2015 and the estimated amount 
included in the budget neutrality offset in the final rule for each of 
these respective fiscal years. In the FY 2022 final rule, we included 
the difference between the amount determined for the cost of the 
demonstration in FY 2016 and the estimated amount included in the 
budget neutrality offset in the final rule for that fiscal year.
(2) Methodology for Estimating Demonstration Costs for FY 2022
    We are using a methodology similar to previous years, according to 
which an estimate of the costs of the demonstration for the upcoming 
fiscal year is incorporated into a budget neutrality offset amount to 
be applied to the national IPPS rates for the upcoming fiscal year, 
that is, FY 2023. We are conducting this estimate for FY 2023 based on 
the 26 hospitals that are continuing participation in demonstration for 
the fiscal year. The methodology for calculating this amount for FY 
2023 proceeds according to the following steps:
    Step 1: For each of these 26 hospitals, we identify the reasonable 
cost amount calculated under the reasonable cost-based methodology for 
covered inpatient hospital services, including swing beds, as indicated 
on the ``as submitted'' cost report for the most recent cost reporting 
period available. For each of these hospitals, the ``as submitted'' 
cost report is that with cost report period end date in CY 2020. We sum 
these hospital-specific amounts to arrive at a total general amount 
representing the costs for covered inpatient hospital services, 
including swing beds, across the total 26 hospitals eligible to 
participate during FY 2023.
    Then, we multiply this amount by the FYs 2021, 2022 and 2023 IPPS 
market basket percentage increases, which are calculated by the CMS 
Office of the Actuary. (Unlike in the proposed rule, where used the 
proposed market basket percentage increase for FY 2023, for this final 
rule, we use the final market basket percentage increase, which can be 
found at section X.XX of the preamble to this final rule). The result 
for the 26 hospitals is the general estimated reasonable cost amount 
for covered inpatient hospital services for FY 2022.
    Consistent with our methods in previous years for formulating this 
estimate, we are applying the IPPS market basket percentage increases 
for FYs 2021 through 2023 to the applicable estimated reasonable cost 
amount (previously described) in order to model the estimated FY 2023 
reasonable cost amount under the demonstration. We believe that the 
IPPS market basket percentage increases appropriately indicate the 
trend of increase in inpatient hospital operating costs under the 
reasonable cost methodology for the years involved.
    Step 2: For each of the participating hospitals, we identify the 
estimated amount that would otherwise be paid in FY 2023 under 
applicable Medicare payment methodologies for covered inpatient 
hospital services, including swing beds (as indicated on the same set 
of ``as submitted'' cost reports as in Step 1), if the demonstration 
were not implemented. We sum these hospital-specific amounts, and, in 
turn, multiply this sum by the FYs 2021, 2022 and 2023 IPPS applicable 
percentage increases. (For FY 2023, we are using the final applicable 
percentage increase for FY 2023, per section X.XX of the preamble of 
this final rule). This methodology differs from Step 1, in which we 
apply the market basket percentage increases to the hospitals' 
applicable estimated reasonable cost amount for covered inpatient 
hospital services. We believe that the IPPS applicable percentage 
increases are appropriate factors to update the estimated amounts that 
generally would otherwise be paid without the demonstration. This is 
because IPPS payments constitute the majority of payments that would 
otherwise be made without the demonstration and the applicable 
percentage increase is the factor used under the IPPS to update the 
inpatient hospital payment rates.
    Step 3: We subtract the amount derived in Step 2 from the amount 
derived in Step 1. According to our methodology, the resulting amount 
indicates the total difference for the 26 hospitals (for covered 
inpatient hospital services, including swing beds), which will be the 
general estimated amount of the costs of the demonstration for FY 2023.
    For this final rule, the resulting amount is $72,449,896, which we 
are incorporating into the budget neutrality offset adjustment for FY 
2023. This estimated amount is based on the specific assumptions 
regarding the data sources used, that is, recently available ``as 
submitted'' cost reports and historical update factors for cost and 
payment. In the proposed rule, we stated that if updated data become 
available prior to the final rule, we would use them as appropriate to 
estimate the costs for the demonstration program for FY 2023 in 
accordance with our methodology for determining the budget neutrality 
estimate. Accordingly, we are using the specific market basket and 
applicable percentage increases identified in this final rule in 
estimating the budget neutrality offset amount for FY 2023. In future 
years, we will also incorporate any statutory change that might affect 
the methodology for determining hospital costs either with or without 
the demonstration.
(3) Reconciling Actual and Estimated Costs of the Demonstration for 
Previous Years
    As described earlier, we have calculated the difference for FYs 
2005 through 2016 between the actual costs of the demonstration, as 
determined from finalized cost reports once available, and estimated 
costs of the demonstration as identified in the applicable IPPS final 
rules for these years. As we stated in the FY 2023 proposed rule, all 
of the finalized cost reports are available for the 17 hospitals that 
completed cost report periods beginning in FY 2017 under the 
demonstration payment methodology; these cost reports show the actual 
costs of the demonstration for this fiscal year to be $35,989,928. This 
amount is unchanged from the proposed rule.
    We note that the FY 2017 IPPS final rule included no budget 
neutrality offset amount for that fiscal year. The final rule for FY 
2017 preceded the re-authorization of the demonstration under the Cures 
Act. Anticipating that the demonstration would end in 2016, we 
projected no demonstration cost estimate for the upcoming fiscal year, 
FY 2017, while we stated our plan to continue to reconcile actual costs 
when all finalized cost reports for previous fiscal years under the 
demonstration became available (81 FR 57037).
    Thus, keeping with past practice, as described in the proposed 
rule, we are including the actual costs of the demonstration as 
determined from finalized cost reports for FY 2017 within the budget 
neutrality offset amount for this upcoming fiscal year.

[[Page 49142]]

(4) Total Proposed Budget Neutrality Offset Amount for FY 2023
    Therefore, for this FY 2023 IPPS/LTCH PPS final rule, the budget 
neutrality offset amount for FY 2023 is based on the sum of two 
amounts:
    (a) the amount determined under section X.4.c.(2) of the preamble 
of this final rule, representing the difference applicable to FY 2023 
between the sum of the estimated reasonable cost amounts that would be 
paid under the demonstration for covered inpatient services to the 26 
hospitals participating in the fiscal year and the sum of the estimated 
amounts that would generally be paid if the demonstration had not been 
implemented. This estimated amount is $72,449,896.
    (b) the amount determined under section X.4.c.(3) of the preamble 
of this final rule, indicating the amount by which the actual costs of 
the demonstration in FY 2017 as shown by finalized cost reports from 
that fiscal year exceed the estimated amount identified in the FY 2017. 
Since no budget neutrality offset was conducted in FY 2017, the amount 
of this difference is the actual cost amount for FY 2017 ($35,989,928)
    Thus, we are subtracting the sum of these amounts ($108,439,824) 
from the national IPPS rates for FY 2023.
    Comment: The parent company for two of the participating hospitals 
expressed support for the continuation of the Rural Community Hospital 
Demonstration program, but noted that it does not offer long-term 
financial stability needed to maintain health care access in rural 
areas. The commenter requests that the demonstration be made a 
permanent program, and, in addition, requests several technical 
modifications to how payment is conducted and costs are audited under 
the demonstration:
    Response: We appreciate the first comment. We have conducted the 
demonstration program in accordance with Congressional mandates. Title 
XVIII does not extend authority to make the demonstration a permanent 
program. With regard to the further comments, we will work with the 
entire group of hospitals participating in the demonstration in 
examining the relevant policy and administrative issues.

VI. Changes to the IPPS for Capital Related Costs

A. Overview

    Section 1886(g) of the Act requires the Secretary to pay for the 
capital-related costs of inpatient acute hospital services in 
accordance with a prospective payment system established by the 
Secretary. Under the statute, the Secretary has broad authority in 
establishing and implementing the IPPS for acute care hospital 
inpatient capital-related costs. We initially implemented the IPPS for 
capital-related costs in the FY 1992 IPPS final rule (56 FR 43358). In 
that final rule, we established a 10-year transition period to change 
the payment methodology for Medicare hospital inpatient capital-related 
costs from a reasonable cost-based payment methodology to a prospective 
payment methodology (based fully on the Federal rate).
    FY 2001 was the last year of the 10-year transition period that was 
established to phase in the IPPS for hospital inpatient capital-related 
costs. For cost reporting periods beginning in FY 2002, capital IPPS 
payments are based solely on the Federal rate for almost all acute care 
hospitals (other than hospitals receiving certain exception payments 
and certain new hospitals). (We refer readers to the FY 2002 IPPS final 
rule (66 FR 39910 through 39914) for additional information on the 
methodology used to determine capital IPPS payments to hospitals both 
during and after the transition period.)
    The basic methodology for determining capital prospective payments 
using the Federal rate is set forth in the regulations at 42 CFR 
412.312. For the purpose of calculating capital payments for each 
discharge, the standard Federal rate is adjusted as follows:
    (Standard Federal Rate) x (DRG Weight) x (Geographic Adjustment 
Factor (GAF) x (COLA for hospitals located in Alaska and Hawaii) x (1 + 
Capital DSH Adjustment Factor + Capital IME Adjustment Factor, if 
applicable).
    In addition, under Sec.  412.312(c), hospitals also may receive 
outlier payments under the capital IPPS for extraordinarily high-cost 
cases that qualify under the thresholds established for each fiscal 
year.

B. Additional Provisions

1. Exception Payments
    The regulations at 42 CFR 412.348 provide for certain exception 
payments under the capital IPPS. The regular exception payments 
provided under Sec.  412.348(b) through (e) were available only during 
the 10-year transition period. For a certain period after the 
transition period, eligible hospitals may have received additional 
payments under the special exceptions provisions at Sec.  412.348(g). 
However, FY 2012 was the final year hospitals could receive special 
exceptions payments. For additional details regarding these exceptions 
policies, we refer readers to the FY 2012 IPPS/LTCH PPS final rule (76 
FR 51725).
    Under Sec.  412.348(f), a hospital may request an additional 
payment if the hospital incurs unanticipated capital expenditures in 
excess of $5 million due to extraordinary circumstances beyond the 
hospital's control. Additional information on the exception payment for 
extraordinary circumstances in Sec.  412.348(f) can be found in the FY 
2005 IPPS final rule (69 FR 49185 and 49186).
2. New Hospitals
    Under the capital IPPS, the regulations at 42 CFR 412.300(b) define 
a new hospital as a hospital that has operated (under previous or 
current ownership) for less than 2 years and lists examples of 
hospitals that are not considered new hospitals. In accordance with 
Sec.  412.304(c)(2), under the capital IPPS, a new hospital is paid 85 
percent of its allowable Medicare inpatient hospital capital related 
costs through its first 2 years of operation, unless the new hospital 
elects to receive full prospective payment based on 100 percent of the 
Federal rate. We refer readers to the FY 2012 IPPS/LTCH PPS final rule 
(76 FR 51725) for additional information on payments to new hospitals 
under the capital IPPS.
3. Payments for Hospitals Located in Puerto Rico
    In the FY 2017 IPPS/LTCH PPS final rule (81 FR 57061), we revised 
the regulations at 42 CFR 412.374 relating to the calculation of 
capital IPPS payments to hospitals located in Puerto Rico beginning in 
FY 2017 to parallel the change in the statutory calculation of 
operating IPPS payments to hospitals located in Puerto Rico, for 
discharges occurring on or after January 1, 2016, made by section 601 
of the Consolidated Appropriations Act, 2016 (Pub. L. 114-113). Section 
601 of Public Law 114-113 increased the applicable Federal percentage 
of the operating IPPS payment for hospitals located in Puerto Rico from 
75 percent to 100 percent and decreased the applicable Puerto Rico 
percentage of the operating IPPS payments for hospitals located in 
Puerto Rico from 25 percent to zero percent, applicable to discharges 
occurring on or after January 1, 2016. As such, under revised Sec.  
412.374, for discharges occurring on or after October 1, 2016, capital 
IPPS payments to hospitals located in Puerto Rico are based on 100 
percent of the capital Federal rate.

[[Page 49143]]

C. Annual Update for FY 2023

    The annual update to the national capital Federal rate, as provided 
for in 42 CFR 412.308(c), for FY 2023 is discussed in section III. of 
the Addendum to this FY 2023 IPPS/LTCH PPS final rule.
    In section II.C. of the preamble of this FY 2023 IPPS/LTCH PPS 
final rule, we present a discussion of the MS-DRG documentation and 
coding adjustment, including previously finalized policies and 
historical adjustments, as well as the adjustment to the standardized 
amount under section 1886(d) of the Act that we are making for FY 2023, 
in accordance with the amendments made to section 7(b)(1)(B) of Public 
Law 110-90 by section 414 of the MACRA. Because these provisions 
require us to make an adjustment only to the operating IPPS 
standardized amount, we are not making a similar adjustment to the 
national capital Federal rate (or to the hospital-specific rates).

VII. Changes for Hospitals Excluded From the IPPS

A. Rate-of-Increase in Payments to Excluded Hospitals for FY 2023

    Certain hospitals excluded from a prospective payment system, 
including children's hospitals, 11 cancer hospitals, and hospitals 
located outside the 50 States, the District of Columbia, and Puerto 
Rico (that is, hospitals located in the U.S. Virgin Islands, Guam, the 
Northern Mariana Islands, and American Samoa) receive payment for 
inpatient hospital services they furnish on the basis of reasonable 
costs, subject to a rate-of-increase ceiling. A per discharge limit 
(the target amount, as defined in Sec.  413.40(a) of the regulations) 
is set for each hospital based on the hospital's own cost experience in 
its base year, and updated annually by a rate-of-increase percentage. 
For each cost reporting period, the updated target amount is multiplied 
by total Medicare discharges during that period and applied as an 
aggregate upper limit (the ceiling as defined in Sec.  413.40(a)) of 
Medicare reimbursement for total inpatient operating costs for a 
hospital's cost reporting period. In accordance with Sec.  403.752(a) 
of the regulations, religious nonmedical health care institutions 
(RNHCIs) also are subject to the rate-of-increase limits established 
under Sec.  413.40 of the regulations discussed previously. 
Furthermore, in accordance with Sec.  412.526(c)(3) of the regulations, 
extended neoplastic disease care hospitals also are subject to the 
rate-of-increase limits established under Sec.  413.40 of the 
regulations discussed previously.
    As explained in the FY 2006 IPPS final rule (70 FR 47396 through 
47398), beginning with FY 2006, we have used the percentage increase in 
the IPPS operating market basket to update the target amounts for 
children's hospitals, the 11 cancer hospitals, and RNHCIs. Consistent 
with the regulations at Sec. Sec.  412.23(g) and 413.40(a)(2)(ii)(A) 
and (c)(3)(viii), we also have used the percentage increase in the IPPS 
operating market basket to update target amounts for short-term acute 
care hospitals located in the U.S. Virgin Islands, Guam, the Northern 
Mariana Islands, and American Samoa. In the FY 2018 IPPS/LTCH PPS final 
rule, we rebased and revised the IPPS operating basket to a 2014 base 
year, effective for FY 2018 and subsequent fiscal years (82 FR 38158 
through 38175), and finalized the use of the percentage increase in the 
2014-based IPPS operating market basket to update the target amounts 
for children's hospitals, the 11 cancer hospitals, RNHCIs, and short-
term acute care hospitals located in the U.S. Virgin Islands, Guam, the 
Northern Mariana Islands, and American Samoa for FY 2018 and subsequent 
fiscal years.
    As discussed in section IV. of the preamble of the FY 2022 IPPS/
LTCH PPS final rule (86 FR 45194 through 45207), we rebased and revised 
the IPPS operating basket to a 2018 base year. Therefore, we used the 
percentage increase in the 2018-based IPPS operating market basket to 
update the target amounts for children's hospitals, the 11 cancer 
hospitals, RNHCIs, and short-term acute care hospitals located in the 
U.S. Virgin Islands, Guam, the Northern Mariana Islands, and American 
Samoa for FY 2022 and subsequent fiscal years.
    For the FY 2023 IPPS/LTCH PPS proposed rule, based on IGI's 2021 
fourth quarter forecast, we estimated that the 2018-based IPPS 
operating market basket update for FY 2023 would be 3.1 percent (that 
is, the estimate of the market basket rate-of-increase). However, we 
proposed that if more recent data became available for the FY 2023 
IPPS/LTCH PPS final rule, we would use such data, if appropriate, to 
calculate the final IPPS operating market basket update for FY 2023. We 
did receive updated data. Therefore, for this FY 2023 IPPS/LTCH PPS 
final rule, based on IGI's 2022 second quarter forecast, we estimate 
that the 2018-based IPPS operating market basket update for FY 2023 is 
4.1 percent. Based on this estimate, the FY 2023 rate-of-increase 
percentage that will be applied to the FY 2022 target amounts in order 
to calculate the FY 2023 target amounts for children's hospitals, the 
11 cancer hospitals, RNCHIs, and short-term acute care hospitals 
located in the U.S. Virgin Islands, Guam, the Northern Mariana Islands, 
and American Samoa will be 4.1 percent, in accordance with the 
applicable regulations at 42 CFR 413.40.
    In addition, payment for inpatient operating costs for hospitals 
classified under section 1886(d)(1)(B)(vi) of the Act (which we refer 
to as ``extended neoplastic disease care hospitals'') for cost 
reporting periods beginning on or after January 1, 2015, is to be made 
as described in 42 CFR 412.526(c)(3), and payment for capital costs for 
these hospitals is to be made as described in 42 CFR 412.526(c)(4). 
(For additional information on these payment regulations, we refer 
readers to the FY 2018 IPPS/LTCH PPS final rule (82 FR 38321 through 
38322).)
    Section 412.526(c)(3) provides that the hospital's Medicare 
allowable net inpatient operating costs for that period are paid on a 
reasonable cost basis, subject to that hospital's ceiling, as 
determined under Sec.  412.526(c)(1), for that period. Under Sec.  
412.526(c)(1), for each cost reporting period, the ceiling was 
determined by multiplying the updated target amount, as defined in 
Sec.  412.526(c)(2), for that period by the number of Medicare 
discharges paid during that period. Section 412.526(c)(2)(i) describes 
the method for determining the target amount for cost reporting periods 
beginning during FY 2015. Section 412.526(c)(2)(ii) specifies that, for 
cost reporting periods beginning during fiscal years after FY 2015, the 
target amount will equal the hospital's target amount for the previous 
cost reporting period updated by the applicable annual rate-of-increase 
percentage specified in Sec.  413.40(c)(3) for the subject cost 
reporting period (79 FR 50197).
    For FY 2023, in accordance with Sec. Sec.  412.22(i) and 
412.526(c)(2)(ii) of the regulations, for cost reporting periods 
beginning during FY 2023 the proposed update to the target amount for 
extended neoplastic disease care hospitals (that is, hospitals 
described under Sec.  412.22(i)) is the applicable annual rate-of-
increase percentage specified in Sec.  413.40(c)(3) for FY 2023, which 
would be equal to the percentage increase in the hospital market 
basket, which is estimated to be the percentage increase in the 2018-
based IPPS operating market basket (that is, the estimate of the market 
basket rate-of-increase). Accordingly, the proposed update to an 
extended neoplastic disease care hospital's target amount for FY 2023 
was 3.1 percent, which was

[[Page 49144]]

based on IGI's fourth quarter 2021 forecast. Furthermore, we proposed 
that if more recent data became available for the FY 2023 IPPS/LTCH PPS 
final rule, we would use such data, if appropriate, to calculate the 
IPPS operating market basket update for FY 2023. For this FY 2023 IPPS/
LTCH PPS final rule, based on IGI's second quarter 2022 forecast, we 
estimate that the 2018-based IPPS operating market basket update for FY 
2023 is 4.1 percent.
    We received no comments on this proposal and therefore are 
finalizing this provision without modification. Incorporating more 
recent data available for this final rule, as we proposed, we are 
adopting a 4.1 percent update for FY 2023.

B. Report on Adjustment (Exception) Payments

    Section 4419(b) of Public Law 105-33 requires the Secretary to 
publish annually in the Federal Register a report describing the total 
amount of adjustment payments made to excluded hospitals and hospital 
units by reason of section 1886(b)(4) of the Act during the previous 
fiscal year.
    The process of requesting, adjusting, and awarding an adjustment 
payment is likely to occur over a 2-year period or longer. First, 
generally, an excluded hospital must file its cost report for the 
fiscal year in accordance with Sec.  413.24(f)(2) of the regulations. 
The MAC reviews the cost report and issues a notice of provider 
reimbursement (NPR). Once the hospital receives the NPR, if its 
operating costs are in excess of the ceiling, the hospital may file a 
request for an adjustment payment. After the MAC receives the 
hospital's request in accordance with applicable regulations, the MAC 
or CMS, depending on the type of adjustment requested, reviews the 
request and determines if an adjustment payment is warranted. This 
determination is sometimes not made until more than 180 days after the 
date the request is filed because there are times when the request 
applications are incomplete and additional information must be 
requested in order to have a completed request application. However, in 
an attempt to provide interested parties with data on the most recent 
adjustment payments for which we have data, we are publishing data on 
adjustment payments that were processed by the MAC or CMS during FY 
2021.
    The table that follows includes the most recent data available from 
the MACs and CMS on adjustment payments that were adjudicated during FY 
2021. As indicated previously, the adjustments made during FY 2021 only 
pertain to cost reporting periods ending in years prior to FY 2020. 
Total adjustment payments made to IPPS-excluded hospitals during FY 
2021 are $25,950,692. The table depicts for each class of hospitals, in 
the aggregate, the number of adjustment requests adjudicated, the 
excess operating costs over the ceiling, and the amount of the 
adjustment payments.
[GRAPHIC] [TIFF OMITTED] TR10AU22.153

C. Critical Access Hospitals (CAHs)

1. Background
    Section 1820 of the Act provides for the establishment of Medicare 
Rural Hospital Flexibility Programs (MRHFPs), under which individual 
States may designate certain facilities as critical access hospitals 
(CAHs). Facilities that are so designated and meet the CAH conditions 
of participation under 42 CFR part 485, subpart F, will be certified as 
CAHs by CMS. Regulations governing payments to CAHs for services to 
Medicare beneficiaries are located in 42 CFR part 413.
2. Frontier Community Health Integration Project Demonstration
a. Introduction
    The Frontier Community Health Integration Project Demonstration was 
originally authorized by section 123 of the Medicare Improvements for 
Patients and Providers Act of 2008 (Pub. L. 110-275). The demonstration 
has been extended by section 129 of the Consolidated Appropriations 
Act, 2021 (Pub. L. 116-260) for an additional 5 years. In this final 
rule, we are summarizing the status of the demonstration program, and 
the ongoing methodologies for implementation and budget neutrality for 
the demonstration extension period.
b. Background and Overview
    As discussed in the FY 2022 IPPS/LTCH PPS final rule (86 FR 45323 
through 45328), section 123 of the Medicare Improvements for Patients 
and Providers Act of 2008, as amended by section 3126 of the Affordable 
Care Act, authorized a demonstration project to allow eligible entities 
to develop and test new models for the delivery of health care services 
in eligible counties in order to improve access to and better integrate 
the delivery of acute care, extended care and other health care 
services to Medicare beneficiaries. The demonstration was titled 
``Demonstration Project on Community Health Integration Models in 
Certain Rural Counties,'' and commonly known as the Frontier Community 
Health Integration Project (FCHIP) Demonstration.
    The authorizing statute stated the eligibility criteria for 
entities to be able to participate in the demonstration. An eligible 
entity, as defined in section 123(d)(1)(B) of Public Law 110-275, as 
amended, is a Medicare Rural Hospital Flexibility Program (MRHFP) 
grantee under section 1820(g) of the Act (that is, a CAH); and is 
located in a state in which at least 65 percent of the counties in the 
state are counties that have 6 or less residents per square mile.
    The authorizing statute stipulated several other requirements for 
the demonstration. In addition, section 123(g)(1)(B) of Pub. L. 110-275 
required that the demonstration be budget neutral. Specifically, this 
provision stated that, in conducting the demonstration project, the 
Secretary shall ensure that the aggregate payments made by the 
Secretary do not exceed the amount which the Secretary estimates would 
have been paid if the demonstration project under the section were not 
implemented. Furthermore, section 123(i) of Public Law 110-275

[[Page 49145]]

stated that the Secretary may waive such requirements of titles XVIII 
and XIX of the Act as may be necessary and appropriate for the purpose 
of carrying out the demonstration project, thus allowing the waiver of 
Medicare payment rules encompassed in the demonstration. CMS selected 
CAHs to participate in four interventions, under which specific waivers 
of Medicare payment rules would allow for enhanced payment for 
telehealth, skilled nursing facility/nursing facility beds, ambulance 
services, and home health services. These waivers were formulated with 
the goal of increasing access to care with no net increase in costs.
    Section 123 of Public Law 110-275 initially required a 3-year 
period of performance. The FCHIP Demonstration began on August 1, 2016, 
and concluded on July 31, 2019 (referred to in this section of the 
final rule as the ``initial period''). Subsequently, section 129 of the 
Consolidated Appropriations Act, 2021 (Pub. L. 116-260) extended the 
demonstration by 5 years (referred to in this section of the final rule 
as the ``extension period''). The Secretary is required to conduct the 
demonstration for an additional 5-year period. CAHs participating in 
the demonstration project during the extension period shall begin such 
participation in the cost reporting year that begins on or after 
January 1, 2022.
    As described in the FY 2022 IPPS/LTCH PPS final rule (86 FR 45323 
through 45328), 10 CAHs were selected for participation in the 
demonstration initial period. The selected CAHs were located in three 
states--Montana, Nevada, and North Dakota--and participated in three of 
the four interventions identified in the FY 2017 IPPS/LTCH PPS final 
rule (81 FR 57064 through 57065), the FY 2018 IPPS/LTCH PPS final rule 
(82 FR 38294 through 38296), and the FY 2019 IPPS/LTCH PPS final rule 
(83 FR 41516 through 41517), the FY 2020 IPPS/LTCH PPS final rule (84 
FR 42427 through 42428) and the FY 2021 IPPS/LTCH PPS final rule (85 FR 
58894 through 58896) and the FY 2022 IPPS/LTCH PPS final rule (86 FR 
45323 through 45328). Each CAH was allowed to participate in more than 
one of the interventions. None of the selected CAHs were participants 
in the home health intervention, which was the fourth intervention.
    In the FY 2022 IPPS/LTCH PPS final rule, CMS concluded that the 
initial period of the FCHIP Demonstration (covering the performance 
period of August 1, 2016, to July 31, 2019) had satisfied the budget 
neutrality requirement described in section 123(g)(1)(B) of Public Law 
110-275. Therefore, CMS did not apply a budget neutrality payment 
offset policy for the initial period of the demonstration.
    Section 129 of Public Law 116-260, stipulates that only the 10 CAHs 
that participated in the initial period of the FCHIP Demonstration are 
eligible to participate during the extension period. Among the eligible 
CAHs, six have elected to participate in the extension period. The 
selected CAHs are located in two states--Montana and North Dakota--and 
are implementing three of the four interventions. The eligible CAH 
participants elected to change the number of interventions and payment 
waivers they would participate in during the extension period. CMS 
accepted and approved the CAHs intervention and payment waiver updates. 
For the extension period, five CAHs are participants in the telehealth 
intervention, four CAHs are participants in the skilled nursing 
facility/nursing facility bed intervention, and three CAHs are 
participants in the ambulance services intervention. As with the 
initial period, each CAH was allowed to participate in more than one of 
the interventions during the extension period. None of the selected 
CAHs are participants in the home health intervention, which was the 
fourth intervention.
c. Intervention Payment and Payment Waivers
    As described in the FY 2022 IPPS/LTCH PPS final rule (86 FR 45323 
through 45328), CMS waived certain Medicare rules for CAHs 
participating in the demonstration initial period to allow for 
alternative reasonable cost-based payment methods in the three distinct 
intervention service areas: telehealth services, ambulance services, 
and skilled nursing facility/nursing facility (SNF/NF) beds expansion. 
The payments and payment waiver provisions only apply if the CAH is a 
participant in the associated intervention. Given updates to Medicare 
payment rules and regulations, CMS has modified and/or updated the 
Intervention Payment and Payment Waivers for the extension period. The 
FCHIP payment waivers for the demonstration extension period consist of 
the following:
(1) Telehealth Services Intervention Payments
    CMS waives section 1834(m)(2)(B) of the Act, which specifies the 
facility fee to the originating site. CMS modifies the facility fee 
payment specified under section 1834(m)(2)(B) of the Act to make 
reasonable cost-based reimbursement to the participating CAH where the 
participating CAH serves as the originating site for a telehealth 
service furnished to an eligible telehealth individual, as defined in 
section 1834(m)(4)(B) of the Act. CMS would reimburse the participating 
CAH serving as the originating site at 101 percent of its reasonable 
costs for overhead, salaries and fringe benefits associated with 
telehealth services at the participating CAH. CMS would not fund or 
provide reimbursement to the participating CAH for the purchase of new 
telehealth equipment.
    CMS waives section 1834(m)(2)(A) of the Act, which specifies the 
payment made for a telehealth service furnished by the distant site 
practitioner. CMS modifies the distant site payment specified under 
section 1834(m)(2)(A) of the Act to make reasonable cost-based 
reimbursement to the participating CAH for telehealth services 
furnished by a physician or practitioner located at distant site that 
is a participating CAH that is billing for the physician or 
practitioner professional services. Whether the participating CAH has 
or has not elected Optional Payment Method II for outpatient services, 
CMS would pay the participating CAH 101 percent of reasonable costs for 
telehealth services when a physician or practitioner has reassigned 
their billing rights to the participating CAH and furnishes telehealth 
services from the participating CAH as a distant site practitioner. 
This means that participating CAHs that are billing under the Standard 
Method on behalf of employees who are physicians or practitioners (as 
defined in section 1834(m)(4)(D) and (E) of the Act, respectively) 
would be eligible to bill for distant site telehealth services 
furnished by these physicians and practitioners. Additionally, CAHs 
billing under the Optional Method would be reimbursed based on 101 
percent of reasonable costs, rather than paid based on the Medicare 
physician fee schedule, for the distant site telehealth services 
furnished by physicians and practitioners who have reassigned their 
billing rights to the CAH. For distant site telehealth services 
furnished by physicians or practitioners who have not reassigned 
billing rights to a participating CAH, payment to the distant site 
physician or practitioner would continue to be made as usual under the 
Medicare physician fee schedule. Currently these services are eligible 
to be furnished and paid in this way due to a waiver issued during the 
PHE. Except as described herein, CMS does not waive any other 
provisions of section 1834(m) of the Act

[[Page 49146]]

for purposes of the telehealth services intervention payments, 
including the scope of Medicare telehealth services as established 
under section 1834(m)(4)(F) of the Act. We received no comments on this 
proposal and therefore are finalizing this provision without 
modification.
(2) Ambulance Services Intervention Payments
    CMS waives 42 CFR 413.70(b)(5)(D) and section 1834(l)(8) of the 
Act, which provides that payment for ambulance services furnished by a 
CAH, or an entity owned and operated by a CAH, is 101 percent of the 
reasonable costs of the CAH or the entity in furnishing the ambulance 
services, but only if the CAH or the entity is the only provider or 
supplier of ambulance services located within a 35-mile drive of the 
CAH, excluding ambulance providers or suppliers that are not legally 
authorized to furnish ambulance services to transport individuals to or 
from the CAH. The participating CAH would be paid 101 percent of 
reasonable costs for its ambulance services regardless of whether there 
is any provider or supplier of ambulance services located within a 35-
mile drive of the participating CAH or participating CAH-owned and 
operated entity. CMS would not make cost-based payment to the 
participating CAH for any new capital (for example, vehicles) 
associated with ambulance services. This waiver does not modify any 
other Medicare rules regarding or affecting the provision of ambulance 
services. We received no comments on this proposal and therefore are 
finalizing this provision without modification.
(3) SNF/NF Beds Expansion Intervention Payments
    CMS waives 42 CFR 485.620(a), 42 CFR 485.645(a)(2), and section 
1820(c)(2)(B)(iii) of the Act which limit CAHs to maintaining no more 
than 25 inpatient beds, including beds available for acute inpatient or 
swing bed services. CMS waives 1820(f) of the Act permitting 
designating or certifying a facility as a critical access hospital for 
which the facility at any time is furnishing inpatient beds which 
exceed more than 25 beds. Under this waiver, if the participating CAH 
has received swing bed approval from CMS, the participating CAH may 
maintain up to ten additional beds (for a total of 35 beds) available 
for acute inpatient or swing bed services; however, the participating 
CAH may only use these 10 additional beds for nursing facility or 
skilled nursing facility level of care. CMS would pay the participating 
CAH 101 percent of reasonable costs for its SNF/NF services furnished 
in the 10 additional beds. We received no comments on this proposal and 
therefore are finalizing this provision without modification.
d. Budget Neutrality
(1) Budget Neutrality Requirement
    In the FY 2022 IPPS/LTCH PPS final rule (86 FR 45323 through 
45328), we finalized a policy to address the budget neutrality 
requirement for the demonstration initial period. We also discussed 
this policy in the FY 2017 IPPS/LTCH PPS final rule (81 FR 57064 
through 57065), the FY 2018 IPPS/LTCH PPS final rule (82 FR 38294 
through 38296), the FY 2019 IPPS/LTCH PPS final rule (83 FR 41516 
through 41517), the FY 2020 IPPS/LTCH PPS final rule (84 FR 42427 
through 42428) and the FY 2021 IPPS/LTCH PPS final rule (85 FR 58894 
through 58996). As explained in the FY 2022 IPPS/LTCH PPS final rule, 
we based our selection of CAHs for participation in the demonstration 
with the goal of maintaining the budget neutrality of the demonstration 
on its own terms meaning that the demonstration would produce savings 
from reduced transfers and admissions to other health care providers, 
offsetting any increase in Medicare payments as a result of the 
demonstration. However, because of the small size of the demonstration 
and uncertainty associated with the projected Medicare utilization and 
costs, the policy we finalized for the demonstration initial period of 
performance in the FY 2022 IPPS/LTCH PPS final rule provides a 
contingency plan to ensure that the budget neutrality requirement in 
section 123 of Public Law 110-275 is met.
    For the FY 2023 proposed rule, we proposed to adopt the same budget 
neutrality policy contingency plan used during the demonstration 
initial period to ensure that the budget neutrality requirement in 
section 123 of Public Law 110 275 is met during the demonstration 
extension period. If analysis of claims data for Medicare beneficiaries 
receiving services at each of the participating CAHs, as well as from 
other data sources, including cost reports for the participating CAHs, 
shows that increases in Medicare payments under the demonstration 
during the 5-year extension period are not sufficiently offset by 
reductions elsewhere, we would recoup the additional expenditures 
attributable to the demonstration through a reduction in payments to 
all CAHs nationwide.
    As explained in the FY 2022 IPPS/LTCH PPS final rule (86 FR 45323 
through 45328), because of the small scale of the demonstration, we 
indicated that we did not believe it would be feasible to implement 
budget neutrality for the demonstration initial period by reducing 
payments to only the participating CAHs. Therefore, in the event that 
this demonstration extension period is found to result in aggregate 
payments in excess of the amount that would have been paid if this 
demonstration extension period were not implemented, CMS policy is to 
comply with the budget neutrality requirement finalized in the FY 2022 
IPPS/LTCH PPS final rule, by reducing payments to all CAHs, not just 
those participating in the demonstration extension period.
    In the FY 2022 IPPS/LTCH PPS final rule, we stated that we believe 
it is appropriate to make any payment reductions across all CAHs 
because the FCHIP Demonstration was specifically designed to test 
innovations that affect delivery of services by the CAH provider 
category. We explained our belief that the language of the statutory 
budget neutrality requirement at section 123(g)(1)(B) of Public Law 
110-275 permits the agency to implement the budget neutrality provision 
in this manner. The statutory language merely refers to ensuring that 
aggregate payments made by the Secretary do not exceed the amount which 
the Secretary estimates would have been paid if the demonstration 
project was not implemented, and does not identify the range across 
which aggregate payments must be held equal.
    Under the policy finalized in the FY 2022 IPPS/LTCH PPS final rule, 
we adopted the policy finalized in the FY 2017 IPPS/LTCH PPS final 
rule, in the event the demonstration initial period was found not to 
have been budget neutral, any excess costs would be recouped over a 
period of 3 cost reporting years. In the FY 2023 IPPS/LTCH PPS proposed 
rule, we sought public comment on this proposal, since we were revising 
an aspect of the policy finalized in the FY 2022 IPPS/LTCH PPS final 
rule. Our new proposed policy is in the event the demonstration 
extension period is found not to have been budget neutral, any excess 
costs would be recouped within one fiscal year. We believe our new 
policy is a more efficient timeframe for the government to conclude the 
demonstration operational requirements (such as analyzing claims data, 
cost report data and/or other data sources) to adjudicate the budget 
neutrality payment recoupment process due to any excess cost that 
occurred as result of the demonstration extension period. We

[[Page 49147]]

received no comments on this proposal and therefore are finalizing this 
provision without modification.
(2) FCHIP Budget Neutrality Methodology and Analytical Approach
    As explained in the FY 2022 IPPS/LTCH PPS final rule, we finalized 
a policy to address the demonstration budget neutrality methodology and 
analytical approach for the initial period of the demonstration. In the 
FY 2023 IPPS/LTCH PPS proposed rule, we proposed to adopt the budget 
neutrality methodology and analytical approach used during the 
demonstration initial period to ensure budget neutrality for the 
extension period. The analysis of budget neutrality during the initial 
period of the demonstration identified both the costs related to 
providing the intervention services under the FCHIP Demonstration and 
any potential downstream effects of the intervention-related services, 
including any savings that may have accrued.
    The budget neutrality analytical approach for the demonstration 
initial period incorporated two major data components: (1) Medicare 
cost reports; and (2) Medicare administrative claims. As described in 
the FY 2022 IPPS/LTCH PPS final rule (86 FR 45323 through 45328), CMS 
computed the cost of the demonstration for each fiscal year of the 
demonstration initial period using Medicare cost reports for the 
participating CAHs, and Medicare administrative claims and enrollment 
data for beneficiaries who received demonstration intervention 
services.
    In addition, in order to capture the full impact of the 
interventions, CMS developed a statistical modeling, Difference-in-
Difference (DiD) regression analysis to estimate demonstration 
expenditures and compute the impact of expenditures on the intervention 
services by comparing cost data for the demonstration and non-
demonstration groups using Medicare administrative claims across the 
demonstration period of performance under the initial period of the 
demonstration. The DiD regression analysis would compare the direct 
cost and potential downstream effects of intervention services, 
including any savings that may have accrued, during the baseline and 
performance period for both the demonstration and comparison groups.
    Second, the Medicare administrative claims analysis would be 
reconciled using data obtained from auditing the participating CAHs' 
Medicare cost reports. We would estimate the costs of the demonstration 
using ``as submitted'' cost reports for each hospital's financial 
fiscal year participation within each of the demonstration extension 
period performance years. Each CAH has its own Medicare cost report end 
date applicable to the 5-year period of performance for the 
demonstration extension period. The cost report is structured to gather 
costs, revenues and statistical data on the provider's financial fiscal 
period. As a result, we would determine the final budget neutrality 
results for the demonstration extension once complete data is available 
for each CAH for the demonstration extension period. We received no 
comments on this proposal and therefore are finalizing this provision 
without modification.
d. Policies for Implementing the 5-Year Extension and Provisions 
Authorized By Section 129 of the Consolidated Appropriations Act, 2021 
(Pub. L. 116-260)
    As stated in the FY 2022 IPPS/LTCH PPS final rule (86 FR 45323 
through 45328), our policy for implementing the 5-year extension period 
for section 129 of Public Law 116-260 follows same budget neutrality 
methodology and analytical approach as the demonstration initial period 
methodology. While we expect to use the same methodology that was used 
to assess the budget neutrality of the FCHIP Demonstration during 
initial period of the demonstration to assess the financial impact of 
the demonstration during this extension period, upon receiving data for 
the extension period, we may update and/or modify the FCHIP budget 
neutrality methodology and analytical approach to ensure that the full 
impact of the demonstration is appropriately captured. In the FY 2023 
IPPS/LTCH PPS proposed rule, we proposed to adopt the same budget 
neutrality methodology and analytical approach used during the 
demonstration initial period to be used for the demonstration extension 
period.
    Comment: A commenter expressed support of CMS implementation of the 
FCHIP demonstration initial period of performance, the demonstration 
intervention payment waivers and of the budget neutrality methodology 
for the extension period. The commenter urged CMS to continue 
implementing the five-year extension period of the demonstration 
project with the same budget neutrality and analytical approach as it 
used in the demonstration initial period. In addition, the commenter 
requested that CMS increase the number of CAHs participating in the 
demonstration extension period. The commenter explained that several 
other CAH service areas have unique topography that could benefit by 
participation in the demonstration extension period, specifically, 
special consideration should be granted to allow additional 
participants within the demonstration ambulance service intervention.
    Response: We appreciate the commenter's support of the 
demonstration project and the budget neutrality methodology. We 
acknowledge the commenter's request for CMS to expand the number of 
CAHs participating in the demonstration extension period. However, we 
note that section 129(b)(C) of Public Law 116-260, stipulates ``[a]n 
entity shall only be eligible to participate in the demonstration 
project under this section during the extension period if the entity 
participated in the demonstration project under this section during the 
initial period.'' As such, expanding the number of CAHs participating 
within the demonstration extension period would require legislative 
action to the eligible entities, as defined in section 129(b)(C) of 
Public Law 116-260. After consideration of the public comments we 
received, we are finalizing our proposal to adopt the same budget 
neutrality methodology and analytical approach used during the 
demonstration initial period to be used for the demonstration extension 
period without modification.
e. Total Budget Neutrality Offset Amount for FY 2023
    At this time, for the FY 2023 IPPS/LTCH PPS proposed rule, while 
this discussion represents our anticipated approach to assessing the 
financial impact of the demonstration extension period based on upon 
receiving data for the full demonstration extension period, we may 
update and/or modify the FCHIP Demonstration budget neutrality 
methodology and analytical approach to ensure that the full impact of 
the demonstration is appropriately captured.
    Therefore, we did not propose to apply a budget neutrality payment 
offset to payments to CAHs in FY 2023. This policy will have no impact 
for any national payment system for FY 2023. We received no comments on 
this proposal and therefore are finalizing this provision without 
modification.

[[Page 49148]]

VIII. Changes to the Long-Term Care Hospital Prospective Payment System 
(LTCH PPS) for FY 2023

A. Background of the LTCH PPS

1. Legislative and Regulatory Authority
    Section 123 of the Medicare, Medicaid, and SCHIP (State Children's 
Health Insurance Program) Balanced Budget Refinement Act of 1999 (BBRA) 
(Pub. L. 106-113), as amended by section 307(b) of the Medicare, 
Medicaid, and SCHIP Benefits Improvement and Protection Act of 2000 
(BIPA) (Pub. L. 106-554), provides for payment for both the operating 
and capital-related costs of hospital inpatient stays in long-term care 
hospitals (LTCHs) under Medicare Part A based on prospectively set 
rates. The Medicare prospective payment system (PPS) for LTCHs applies 
to hospitals that are described in section 1886(d)(1)(B)(iv) of the 
Act, effective for cost reporting periods beginning on or after October 
1, 2002.
    Section 1886(d)(1)(B)(iv)(I) of the Act originally defined an LTCH 
as a hospital that has an average inpatient length of stay (as 
determined by the Secretary) of greater than 25 days. Section 
1886(d)(1)(B)(iv)(II) of the Act also provided an alternative 
definition of LTCHs (``subclause II'' LTCHs). However, section 15008 of 
the 21st Century Cures Act (Pub. L. 114-255) amended section 1886 of 
the Act to exclude former ``subclause II'' LTCHs from being paid under 
the LTCH PPS and created a new category of IPPS-excluded hospitals, 
which we refer to as ``extended neoplastic disease care hospitals,'' to 
be paid as hospitals that were formally classified as ``subclause 
(II)'' LTCHs (82 FR 38298).
    Section 123 of the BBRA requires the PPS for LTCHs to be a ``per 
discharge'' system with a diagnosis-related group (DRG) based patient 
classification system that reflects the differences in patient resource 
use and costs in LTCHs.
    Section 307(b)(1) of the BIPA, among other things, mandates that 
the Secretary shall examine, and may provide for, adjustments to 
payments under the LTCH PPS, including adjustments to DRG weights, area 
wage adjustments, geographic reclassification, outliers, updates, and a 
disproportionate share adjustment.
    In the August 30, 2002 Federal Register, we issued a final rule 
that implemented the LTCH PPS authorized under the BBRA and BIPA (67 FR 
55954). For the initial implementation of the LTCH PPS (FYs 2003 
through 2007), the system used information from LTCH patient records to 
classify patients into distinct long-term care-diagnosis-related groups 
(LTCDRGs) based on clinical characteristics and expected resource 
needs. Beginning in FY 2008, we adopted the Medicare severity-long-term 
care-diagnosis related groups (MS-LTC-DRGs) as the patient 
classification system used under the LTCH PPS. Payments are calculated 
for each MS-LTC-DRG and provisions are made for appropriate payment 
adjustments. Payment rates under the LTCH PPS are updated annually and 
published in the Federal Register.
    The LTCH PPS replaced the reasonable cost-based payment system 
under the Tax Equity and Fiscal Responsibility Act of 1982 (TEFRA) 
(Pub. L. 97248) for payments for inpatient services provided by an LTCH 
with a cost reporting period beginning on or after October 1, 2002. 
(The regulations implementing the TEFRA reasonable-cost-based payment 
provisions are located at 42 CFR part 413.) With the implementation of 
the PPS for acute care hospitals authorized by the Social Security 
Amendments of 1983 (Pub. L. 98-21), which added section 1886(d) to the 
Act, certain hospitals, including LTCHs, were excluded from the PPS for 
acute care hospitals and paid their reasonable costs for inpatient 
services subject to a per discharge limitation or target amount under 
the TEFRA system. For each cost reporting period, a hospital specific 
ceiling on payments was determined by multiplying the hospital's 
updated target amount by the number of total current year Medicare 
discharges. (Generally, in this section of the preamble of this final 
rule, when we refer to discharges, we describe Medicare discharges.) 
The August 30, 2002 final rule further details the payment policy under 
the TEFRA system (67 FR 55954).
    In the August 30, 2002 final rule, we provided for a 5-year 
transition period from payments under the TEFRA system to payments 
under the LTCH PPS. During this 5-year transition period, an LTCH's 
total payment under the PPS was based on an increasing percentage of 
the Federal rate with a corresponding decrease in the percentage of the 
LTCH PPS payment that is based on reasonable cost concepts, unless an 
LTCH made a one-time election to be paid based on 100 percent of the 
Federal rate. Beginning with LTCHs' cost reporting periods beginning on 
or after October 1, 2006, total LTCH PPS payments are based on 100 
percent of the Federal rate. In addition, in the August 30, 2002 final 
rule, we presented an in-depth discussion of the LTCH PPS, including 
the patient classification system, relative weights, payment rates, 
additional payments, and the budget neutrality requirements mandated by 
section 123 of the BBRA. The same final rule that established 
regulations for the LTCH PPS under 42 CFR part 412, subpart O, also 
contained LTCH provisions related to covered inpatient services, 
limitation on charges to beneficiaries, medical review requirements, 
furnishing of inpatient hospital services directly or under 
arrangement, and reporting and recordkeeping requirements. We refer 
readers to the August 30, 2002 final rule for a comprehensive 
discussion of the research and data that supported the establishment of 
the LTCH PPS (67 FR 55954).
    In the FY 2016 IPPS/LTCH PPS final rule (80 FR 49601 through 
49623), we implemented the provisions of the Pathway for Sustainable 
Growth Rate (SGR) Reform Act of 2013 (Pub. L. 113-67), which mandated 
the application of the ``site neutral'' payment rate under the LTCH PPS 
for discharges that do not meet the statutory criteria for exclusion 
beginning in FY 2016. For cost reporting periods beginning on or after 
October 1, 2015, discharges that do not meet certain statutory criteria 
for exclusion are paid based on the site neutral payment rate. 
Discharges that do meet the statutory criteria continue to receive 
payment based on the LTCH PPS standard Federal payment rate. For more 
information on the statutory requirements of the Pathway for SGR Reform 
Act of 2013, we refer readers to the FY 2016 IPPS/LTCH PPS final rule 
(80 FR 49601 through 49623) and the FY 2017 IPPS/LTCH PPS final rule 
(81 FR 57068 through 57075).
    In the FY 2018 IPPS/LTCH PPS final rule, we implemented several 
provisions of the 21st Century Cures Act (``the Cures Act'') (Pub. L. 
114-255) that affected the LTCH PPS. (For more information on these 
provisions, we refer readers to 82 FR 38299.)
    In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41529), we made 
conforming changes to our regulations to implement the provisions of 
section 51005 of the Bipartisan Budget Act of 2018 (Pub. L. 115-123), 
which extends the transitional blended payment rate for site neutral 
payment rate cases for an additional 2 years. We refer readers to 
section VII.C. of the preamble of the FY 2019 IPPS/LTCH PPS final rule 
for a discussion of our final policy. In addition, in the FY 2019 IPPS/
LTCH PPS final rule, we removed the 25-percent threshold policy under 
42 CFR 412.538, which was a payment adjustment that was applied to

[[Page 49149]]

payments for Medicare patient LTCH discharges when the number of such 
patients originating from any single referring hospital was in excess 
of the applicable threshold for given cost reporting period.
    In the FY 2020 IPPS/LTCH PPS final rule (84 FR 42439), we further 
revised our regulations to implement the provisions of the Pathway for 
SGR Reform Act of 2013 (Pub. L. 113-67) that relate to the payment 
adjustment for discharges from LTCHs that do not maintain the requisite 
discharge payment percentage and the process by which such LTCHs may 
have the payment adjustment discontinued.
2. Criteria for Classification as an LTCH
a. Classification as an LTCH
    Under the regulations at Sec.  412.23(e)(1), to qualify to be paid 
under the LTCH PPS, a hospital must have a provider agreement with 
Medicare. Furthermore, Sec.  412.23(e)(2)(i), which implements section 
1886(d)(1)(B)(iv) of the Act, requires that a hospital have an average 
Medicare inpatient length of stay of greater than 25 days to be paid 
under the LTCH PPS. In accordance with section 1206(a)(3) of the 
Pathway for SGR Reform Act of 2013 (Pub. L. 113-67), as amended by 
section 15007 of Public Law 114-255, we amended our regulations to 
specify that Medicare Advantage plans' and site neutral payment rate 
discharges are excluded from the calculation of the average length of 
stay for all LTCHs, for discharges occurring in cost reporting period 
beginning on or after October 1, 2015.
b. Hospitals Excluded From the LTCH PPS
    The following hospitals are paid under special payment provisions, 
as described in Sec.  412.22(c) and, therefore, are not subject to the 
LTCH PPS rules:
     Veterans Administration hospitals.
     Hospitals that are reimbursed under State cost control 
systems approved under 42 CFR part 403.
     Hospitals that are reimbursed in accordance with 
demonstration projects authorized under section 402(a) of the Social 
Security Amendments of 1967 (Pub. L. 90-248) (42 U.S.C. 1395b-1), 
section 222(a) of the Social Security Amendments of 1972 (Pub. L. 92-
603) (42 U.S.C. 1395b1 (note)) (Statewide-all payer systems, subject to 
the rate-of increase test at section 1814(b) of the Act), or section 
3201 of the Patient Protection and Affordable Care Act (Pub. L. 111-
148) (42 U.S.C. 1315a).
     Nonparticipating hospitals furnishing emergency services 
to Medicare beneficiaries.
3. Limitation on Charges to Beneficiaries
    In the August 30, 2002 final rule, we presented an in-depth 
discussion of beneficiary liability under the LTCH PPS (67 FR 55974 
through 55975). This discussion was further clarified in the RY 2005 
LTCH PPS final rule (69 FR 25676). In keeping with those discussions, 
if the Medicare payment to the LTCH is the full LTC-DRG payment amount, 
consistent with other established hospital prospective payment systems, 
Sec.  412.507 currently provides that an LTCH may not bill a Medicare 
beneficiary for more than the deductible and coinsurance amounts as 
specified under Sec. Sec.  409.82, 409.83, and 409.87, and for items 
and services specified under Sec.  489.30(a). However, under the LTCH 
PPS, Medicare will only pay for services furnished during the days for 
which the beneficiary has coverage until the short-stay outlier (SSO) 
threshold is exceeded. If the Medicare payment was for a SSO case (in 
accordance with Sec.  412.529), and that payment was less than the full 
LTC-DRG payment amount because the beneficiary had insufficient 
coverage as a result of the remaining Medicare days, the LTCH also is 
currently permitted to charge the beneficiary for services delivered on 
those uncovered days (in accordance with Sec.  412.507). In the FY 2016 
IPPS/LTCH PPS final rule (80 FR 49623), we amended our regulations to 
expressly limit the charges that may be imposed upon beneficiaries 
whose LTCHs' discharges are paid at the site neutral payment rate under 
the LTCH PPS. In the FY 2017 IPPS/LTCH PPS final rule (81 FR 57102), we 
amended the regulations under Sec.  412.507 to clarify our existing 
policy that blended payments made to an LTCH during its transitional 
period (that is, an LTCH's payment for discharges occurring in cost 
reporting periods beginning in FYs 2016 through 2019) are considered to 
be site neutral payment rate payments.
4. Best Available Data
    We refer readers to section I.F. of the preamble of this final rule 
for our discussion on our use of the most recent data available for the 
FY 2023 LTCH PPS ratesetting, including the FY 2021 MedPAR claims and 
FY 2020 cost report data. In section I.F. of the preamble of this final 
rule we also discuss our modification of our ratesetting methodology 
for FY 2023 to account for the ongoing COVID-19 PHE.
    Comment: We received several comments unrelated to LTCH PPS 
proposals included in the proposed rule. For example, some commenters 
requested changes to the structure of the site neutral payment policy 
or the calculation of the average length of stay.
    Response: We appreciate the commenters' feedback and will keep 
these comments in mind for future rulemaking.

B. Medicare Severity Long-Term Care Diagnosis-Related Group (MS-LTC-
DRG) Classifications and Relative Weights for FY 2023

1. Background
    Section 123 of the BBRA required that the Secretary implement a PPS 
for LTCHs to replace the cost-based payment system under TEFRA. Section 
307(b)(1) of the BIPA modified the requirements of section 123 of the 
BBRA by requiring that the Secretary examine the feasibility and the 
impact of basing payment under the LTCH PPS on the use of existing (or 
refined) hospital DRGs that have been modified to account for different 
resource use of LTCH patients.
    Under both the IPPS and the LTCH PPS, the DRG-based classification 
system uses information on the claims for inpatient discharges to 
classify patients into distinct groups (for example, DRGs) based on 
clinical characteristics and expected resource needs. When the LTCH PPS 
was implemented for cost reporting periods beginning on or after 
October 1, 2002, we adopted the same DRG patient classification system 
utilized at that time under the IPPS. We referred to this patient 
classification system as the ``long-term care diagnosis-related groups 
(LTC-DRGs).'' As part of our efforts to better recognize severity of 
illness among patients, in the FY 2008 IPPS final rule with comment 
period (72 FR 47130), we adopted the MS-DRGs and the Medicare severity 
long-term care diagnosis-related groups (MS-LTC-DRGs) under the IPPS 
and the LTCH PPS, respectively, effective beginning October 1, 2007 (FY 
2008). For a full description of the development, implementation, and 
rationale for the use of the MS-DRGs and MS-LTC-DRGs, we refer readers 
to the FY 2008 IPPS final rule with comment period (72 FR 47141 through 
47175 and 47277 through 47299). (We note that, in that same final rule, 
we revised the regulations at Sec.  412.503 to specify that for LTCH 
discharges occurring on or after October 1, 2007, when applying the 
provisions of 42 CFR part 412, subpart O, applicable to LTCHs for 
policy descriptions and payment calculations, all references to LTC-
DRGs would be considered a reference to MS-LTC-DRGs. For the remainder 
of this section, we present the discussion

[[Page 49150]]

in terms of the current MS-LTC-DRG patient classification system unless 
specifically referring to the previous LTC-DRG patient classification 
system that was in effect before October 1, 2007.)
    Consistent with section 123 of the BBRA, as amended by section 
307(b)(1) of the BIPA, and Sec.  412.515 of the regulations, we use 
information derived from LTCH PPS patient records to classify LTCH 
discharges into distinct MS-LTC-DRGs based on clinical characteristics 
and estimated resource needs. As noted previously, we adopted the same 
DRG patient classification system utilized at that time under the IPPS. 
The MS-DRG classifications are updated annually, which has resulted in 
the number of MS-DRGs changing over time. For FY 2023, there will be 
767 MS-DRG, and by extension, MS-LTC-DRG, groupings based on the 
changes, as discussed in section II.E. of the preamble of this final 
rule.
    Although the patient classification system used under both the LTCH 
PPS and the IPPS are the same, the relative weights are different. The 
established relative weight methodology and data used under the LTCH 
PPS result in relative weights under the LTCH PPS that reflect the 
differences in patient resource use of LTCH patients, consistent with 
section 123(a)(1) of the BBRA. That is, we assign an appropriate weight 
to the MS-LTC-DRGs to account for the differences in resource use by 
patients exhibiting the case complexity and multiple medical problems 
characteristic of LTCH patients.
2. Patient Classifications Into MS-LTC-DRGs
a. Background
    The MS-DRGs (used under the IPPS) and the MS-LTC-DRGs (used under 
the LTCH PPS) are based on the CMS DRG structure. As noted previously 
in this section, we refer to the DRGs under the LTCH PPS as MS-LTC-DRGs 
although they are structurally identical to the MS-DRGs used under the 
IPPS.
    The MS-DRGs are organized into 25 major diagnostic categories 
(MDCs), most of which are based on a particular organ system of the 
body; the remainder involve multiple organ systems (such as MDC 22, 
Burns). Within most MDCs, cases are then divided into surgical DRGs and 
medical DRGs. Surgical DRGs are assigned based on a surgical hierarchy 
that orders operating room (O.R.) procedures or groups of O.R. 
procedures by resource intensity. The GROUPER software program does not 
recognize all ICD-10-PCS procedure codes as procedures affecting DRG 
assignment. That is, procedures that are not surgical (for example, 
EKGs) or are minor surgical procedures (for example, a biopsy of skin 
and subcutaneous tissue (procedure code 0JBH3ZX)) do not affect the MS-
LTC-DRG assignment based on their presence on the claim. Generally, 
under the LTCH PPS, a Medicare payment is made at a predetermined 
specific rate for each discharge that varies based on the MS-LTC-DRG to 
which a beneficiary's discharge is assigned. Cases are classified into 
MS-LTC-DRGs for payment based on the following six data elements:
     Principal diagnosis.
     Additional or secondary diagnoses.
     Surgical procedures.
     Age.
     Sex.
     Discharge status of the patient.
    Currently, for claims submitted using the version ASC X12 5010 
format, up to 25 diagnosis codes and 25 procedure codes are considered 
for an MS-DRG assignment. This includes one principal diagnosis and up 
to 24 secondary diagnoses for severity of illness determinations. (For 
additional information on the processing of up to 25 diagnosis codes 
and 25 procedure codes on hospital inpatient claims, we refer readers 
to section II.G.11.c. of the preamble of the FY 2011 IPPS/LTCH PPS 
final rule (75 FR 50127).)
    Under the HIPAA transactions and code sets regulations at 45 CFR 
parts 160 and 162, covered entities must comply with the adopted 
transaction standards and operating rules specified in subparts I 
through S of part 162. Among other requirements, on or after January 1, 
2012, covered entities are required to use the ASC X12 Standards for 
Electronic Data Interchange Technical Report Type 3--Health Care Claim: 
Institutional (837), May 2006, ASC X12N/005010X223, and Type 1 Errata 
to Health Care Claim: Institutional (837) ASC X12 Standards for 
Electronic Data Interchange Technical Report Type 3, October 2007, ASC 
X12N/005010X233A1 for the health care claims or equivalent encounter 
information transaction (45 CFR 162.1102(c)).
    HIPAA requires covered entities to use the applicable medical data 
code sets when conducting HIPAA transactions (45 CFR 162.1000). 
Currently, upon the discharge of the patient, the LTCH must assign 
appropriate diagnosis and procedure codes from the International 
Classification of Diseases, 10th Revision, Clinical Modification (ICD-
10-CM) for diagnosis coding and the International Classification of 
Diseases, 10th Revision, Procedure Coding System (ICD-10-PCS) for 
inpatient hospital procedure coding, both of which were required to be 
implemented October 1, 2015 (45 CFR 162.1002(c)(2) and (3)). For 
additional information on the implementation of the ICD-10 coding 
system, we refer readers to section II.F.1. of the preamble of the FY 
2017 IPPS/LTCH PPS final rule (81 FR 56787 through 56790) and section 
II.E.1. of the preamble of this final rule. Additional coding 
instructions and examples are published in the AHA's Coding Clinic for 
ICD-10-CM/PCS.
    To create the MS-DRGs (and by extension, the MS-LTC-DRGs), base 
DRGs were subdivided according to the presence of specific secondary 
diagnoses designated as complications or comorbidities (CCs) into one, 
two, or three levels of severity, depending on the impact of the CCs on 
resources used for those cases. Specifically, there are sets of MS-DRGs 
that are split into 2 or 3 subgroups based on the presence or absence 
of a CC or a major complication or comorbidity (MCC). We refer readers 
to section II.D. of the preamble of the FY 2008 IPPS final rule with 
comment period for a detailed discussion about the creation of MS-DRGs 
based on severity of illness levels (72 FR 47141 through 47175).
    MACs enter the clinical and demographic information submitted by 
LTCHs into their claims processing systems and subject this information 
to a series of automated screening processes called the Medicare Code 
Editor (MCE). These screens are designed to identify cases that require 
further review before assignment into a MS-LTC-DRG can be made. During 
this process, certain types of cases are selected for further 
explanation (74 FR 43949).
    After screening through the MCE, each claim is classified into the 
appropriate MS-LTC-DRG by the Medicare LTCH GROUPER software on the 
basis of diagnosis and procedure codes and other demographic 
information (age, sex, and discharge status). The GROUPER software used 
under the LTCH PPS is the same GROUPER software program used under the 
IPPS. Following the MS-LTC-DRG assignment, the MAC determines the 
prospective payment amount by using the Medicare PRICER program, which 
accounts for hospital-specific adjustments. Under the LTCH PPS, we 
provide an opportunity for LTCHs to review the MS-LTC-DRG assignments 
made by the MAC and to submit additional information within a specified 
timeframe as provided in Sec.  412.513(c).

[[Page 49151]]

    The GROUPER software is used both to classify past cases to measure 
relative hospital resource consumption to establish the MS-LTC-DRG 
relative weights and to classify current cases for purposes of 
determining payment. The records for all Medicare hospital inpatient 
discharges are maintained in the MedPAR file. The data in this file are 
used to evaluate possible MS-DRG and MS-LTC-DRG classification changes 
and to recalibrate the MS-DRG and MS-LTC-DRG relative weights during 
our annual update under both the IPPS (Sec.  412.60(e)) and the LTCH 
PPS (Sec.  412.517), respectively.
b. Changes to the MS-LTC-DRGs for FY 2023
    As specified by our regulations at Sec.  412.517(a), which require 
that the MS-LTC-DRG classifications and relative weights be updated 
annually, and consistent with our historical practice of using the same 
patient classification system under the LTCH PPS as is used under the 
IPPS, in this final rule, as proposed, we updated the MS-LTC-DRG 
classifications effective October 1, 2022 through September 30, 2023 
(FY 2023) consistent with the changes to specific MS-DRG 
classifications presented in section II.D. of the preamble of this 
final rule. Accordingly, the MS-LTC-DRGs for FY 2023 are the same as 
the MS-DRGs being used under the IPPS for FY 2023. In addition, because 
the MS-LTC-DRGs for FY 2023 are the same as the MS-DRGs for FY 2023, 
the other changes that affect MS-DRG (and, by extension, MS-LTC-DRG) 
assignments under GROUPER Version 40, as discussed in section II.D. of 
the preamble of this final rule, including the changes to the MCE 
software and the ICD-10-CM/PCS coding system, are also applicable under 
the LTCH PPS for FY 2023.
3. General Summary of the FY 2023 MS-LTC-DRG Relative Weights 
Methodology
    In this section of this final rule, we provide a general summary of 
our modifications to the methodology for determining the FY 2023 MS-
LTC-DRG relative weights under the LTCH PPS.
a. Averaging of Relative Weights for FY 2023
    In section I.F. of the preamble to this final rule, we discuss our 
use of FY 2021 claims data for the FY 2023 LTCH PPS ratesetting. As we 
discussed in the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28466), we 
recognize the impact COVID-19 cases in the FY 2021 claims data have on 
the relative weight calculations for a few COVID-19-related MS-LTC-
DRGs. Specifically, we have determined that the COVID-19 cases grouped 
to a few MS-LTC-DRGs have, on average, meaningfully different costs 
than the non-COVID-19 cases grouped to these MS-LTC-DRGs. As a result, 
for these MS-LTC-DRGs, the relative weights calculated using all cases 
will be meaningfully different than the relative weights calculated 
excluding COVID-19 cases. For example, using the FY 2021 MedPAR data, 
the relative weight for MS-LTC-DRG 870 (Septicemia or severe sepsis 
with MV >96 hours) is approximately 3.1 percent higher when the 
relative weights are calculated including COVID-19 cases compared to 
when the relative weights are calculated excluding COVID-19 cases.
    In section I.F. of the preamble to this final rule, we also discuss 
that we believe it is reasonable to assume there will be fewer COVID-19 
hospitalizations among Medicare beneficiaries in LTCHs in FY 2023 than 
there were in FY 2021, although we cannot know the actual number of 
COVID-19 hospitalizations among Medicare beneficiaries in LTCHs in FY 
2023. In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28466), we 
proposed to modify our relative weight methodology for FY 2023 to align 
with an assumption that there will be fewer, but not zero, COVID-19 
cases in FY 2023 compared to FY 2021. To account for this assumption, 
we proposed an averaging approach to determine the MS-LTC-DRG relative 
weights for FY 2023. Specifically, we proposed to calculate the 
relative weights both including and excluding COVID-19 cases, and then 
average the two sets of relative weights together. We stated our belief 
that this would be appropriate as it would reduce, but not remove 
entirely, the effect of COVID-19 cases on the relative weight 
calculations, particularly given the uncertainty in the number of 
COVID-19 cases in FY 2023. By averaging the relative weights in this 
manner, we stated our belief that the result would reflect a reasonable 
estimation of the mix of cases for FY 2023 based on the information 
available at the time on the trajectory of the COVID-19 PHE (as 
discussed in section I.F. of the preamble to this final rule), and a 
more accurate estimate of the relative resource use for cases treated 
in FY 2023. We believe the relative weights calculated using our 
modified methodology would be more accurate than if we applied our 
standard methodology, that is, with relative weights calculated based 
on 100 percent of the relative weights calculated using all applicable 
LTCH cases. As discussed in section I.O of Appendix A of the proposed 
rule, as an alternative to our proposed approach, we considered 
following our historical approach for calculating the relative weights 
and not proposing this modification. That is, we considered determining 
the FY 2023 MS-LTC-DRG weights using all applicable LTCH cases without 
any modifications to account for COVID-19 cases.
    Comment: We received comments that were supportive of our proposal 
to use FY 2021 data when determining the FY 2023 MS-LTC-DRG relative 
weights. We also received comments that were supportive of our proposal 
to calculate the relative weights both including and excluding COVID-19 
cases, and then averaging the two sets of relative weights together. A 
commenter stated that this is a sensible approach to account for the 
effects of COVID-19 on the data CMS uses for ratesetting.
    Some commenters disagreed with the proposed approach for 
determining the FY 2023 MS-LTC-DRG relative weights. These commenters 
believe a more appropriate approach would be to determine the relative 
weights based on an average of the relative weights calculated using FY 
2019 data and FY 2021 data. These commenters stated that COVID-19 has 
not only influenced LTCH costs of care through higher direct input 
costs, but also through other factors such as challenges in discharging 
patients. Since it is uncertain whether these factors will remain in FY 
2023, these commenters believe their suggested approach, which blends 
claims data prior to the PHE with claims data during the PHE, better 
reflects the overall uncertainty of the future impact of COVID-19.
    We did not receive any comments in support of the alternative 
approach that we discussed in section I.O of Appendix A of the proposed 
rule.
    Response: We thank the commenters for their support. With respect 
to the commenters who suggested we determine the relative weights based 
on an average of the relative weights calculating using FY 2019 and FY 
2021 data, we recognize that there is uncertainty regarding the 
utilization and costs that LTCHs will experience in FY 2023. While the 
commenters' approach for addressing this uncertainty is not 
unreasonable, we believe that our proposed approach will result in a 
more accurate reflection of the types of cases expected to be treated 
by LTCHs in FY 2023. Specifically, we believe that the mix and resource 
use of non-COVID-19 cases is better represented by more recent MedPAR 
claims data than is

[[Page 49152]]

reflected in the cases in the FY 2019 data. Therefore, while we 
considered this alternative approach, we continue to believe that the 
relative weights determined as an average of the relative weights 
calculated with and without the COVID-19 cases reflected in the FY 2021 
MedPAR data are a more reasonable estimation of the mix and relative 
resource use of cases that will be treated at LTCHs in FY 2023.
    Therefore, after consideration of the public comments we received, 
we are finalizing our proposal to use FY 2021 MedPAR claims data to 
calculate the FY 2023 MS-LTC-DRG relative weights. We also are 
finalizing our proposal to establish the FY 2023 MS-LTC-DRG relative 
weights as an average of the relative weights calculated both including 
and excluding COVID-19 cases identified in the FY 2021 MedPAR claims. 
The technical details of the relative weight calculations are discussed 
in section VIII.B.4. of the preamble to this final rule. We note this 
averaging approach for the calculation of the FY 2023 MS-LTC-DRG 
relative weights is consistent with the approach being adopted under 
the IPPS for FY 2023, as discussed in section II.E.c. of the preamble 
to this final rule.
b. Cap on Relative Weight Decreases
    In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28466 through 
28467), we discussed comments we have received in recent years about 
significant fluctuations in the relative weights for some MS-LTC-DRGs. 
We stated that some commenters have requested that CMS establish a 
transition policy to mitigate the negative effects of significant year-
to-year reductions to relative weights. We stated that predictability 
and stability of rates is one of the fundamental principles of a 
prospective payment system. Instability in the relative weights for MS-
LTC-DRGs can reduce the predictability and stability of an individual 
LTCH's Medicare payments from year to year. Therefore, given the 
concerns commenters have raised about the financial impacts of 
significant year-to-year fluctuations in MS-LTC-DRGs relative weights, 
we proposed a policy to address these concerns.
    Consistent with the broad authority conferred upon the Secretary by 
section 123 of the BBRA, as amended by section 307(b) of the BIPA, to 
determine appropriate payment adjustments under the LTCH PPS, including 
adjustments to DRG weights, in the FY 2023 IPPS/LTCH PPS proposed rule 
(87 FR 28466 through 28467), we proposed to establish a permanent 10-
percent cap on the reduction to a MS-LTC-DRG's relative weight in a 
given year, beginning in FY 2023. We proposed that this 10-percent cap 
would be applied to the relative weights for MS-LTC-DRGs with 
applicable LTCH cases. Under this policy, the 10-percent cap would not 
apply to no-volume MS-LTC-DRGs (that is, an MS-LTC-DRG with no 
applicable LTCH cases) whose relative weight was determined by a cross-
walk to another MS-LTC-DRG's relative weight. We stated our belief that 
it is not necessary to apply the 10-percent cap to no-volume MS-LTC-
DRGs because the financial impact of fluctuations in the relative 
weights for these no-volume MS-LTC-DRGs is extremely small, as evident 
by there being zero applicable LTCH cases grouped to these MS-LTC-DRGs 
in the MedPAR claims data.
    We also proposed that the 10-percent cap on the reduction in a MS-
LTC-DRG's relative weight in a given year be budget neutral, meaning we 
would apply a budget neutrality adjustment to the MS-LTC-DRG relative 
weights, after application of the 10-percent cap, to ensure that our 
proposed 10-percent cap on relative weight reductions policy results in 
no change in aggregate LTCH PPS standard Federal rate payments. We 
stated that our application of the proposed 10-percent cap on the 
reduction in a MS-LTC-DRG's relative weight in a given year in a budget 
neutral manner is consistent with the existing budget neutrality 
requirement for annual MS-LTC-DRG reclassification and recalibration, 
which we adopted to mitigate estimated fluctuations in estimated 
aggregate LTCH PPS payments (72 FR 26881-26882).
    In the proposed rule, we stated our belief that the impact of the 
application of a cap on relative weight reductions on an LTCH's total 
LTCH PPS payments in a given year would be relatively small because a 
change in the relative weight would be applied to a single MS-LTC-DRG, 
unlike the impact of the wage index adjustment, which adjusts the 
payment for each discharge and impacts approximately two-thirds of an 
LTCH's total LTCH PPS payments in a given year. In considering the 
amount of the cap for our proposal, we explained that we balanced the 
number of MS-LTC-DRGs that would receive the cap with the magnitude of 
the budget neutrality factor that would be applied to all MS-LTC-DRGs, 
while also maintaining an accurate reflection of the relative resource 
use across the MS-LTC-DRG weights overall. We considered that a higher 
cap, such as 20-percent cap, would limit declines in the relative 
weights for fewer MS-LTC-DRGs while a lower cap, such as a 5-percent 
cap, would limit declines in the relative weights for more MS-LTC-DRGs, 
but would also result in a larger budget neutrality adjustment. We 
stated our belief that on balance, a 10-percent cap would mitigate 
financial impacts resulting from fluctuations in the relative weights, 
particularly for low-volume MS-LTC-DRGs, without the larger budget 
neutrality adjustment associated with a smaller cap, and without 
distorting the integrity of the MS-LTC-DRG relative weights overall as 
a reflection of relative resource use.
    We noted that this proposed 10-percent cap on reductions to a MS-
LTC-DRG's relative weight would apply only to a given MS-LTC-DRG with 
its current MS-LTC-DRG number. In cases where CMS creates new MS-LTC-
DRGs or modifies existing MS-LTC-DRGs as part of its annual 
reclassifications resulting in renumbering of one or more MS-LTC-DRGs, 
we proposed that this limit on the reduction in the relative weight 
would not apply to any MS-LTC-DRGs affected by the renumbering (that 
is, the 10-percent cap would not apply to the relative weight for any 
new or renumbered MS-LTC-DRGs for the fiscal year).
    Comment: Commenters generally agreed with our proposal to cap MS-
LTC-DRG relative weights decreases at 90 percent of the value of the 
MS-LTC-DRG relative weight in the previous year. However, several 
commenters questioned the appropriateness of applying a budget 
neutrality adjustment to the 10-percent cap on relative weight 
reductions. These commenters expressed concern that the budget 
neutrality adjustment could result in a decrease to the relative 
weights for the most commonly used MS-LTC-DRGs (the ''high-volume'' MS-
LTC-DRGs).
    Although none of the proposed relative weights for the top five 
high volume MS-LTC-DRGs would decrease by more than 10-percent in FY 
2023, commenters noted, the proposed budget neutrality adjustment to 
offset the 10-percent cap on relative weight decreases for other MS-
LTC-DRGs will reduce the relative weights for these five most commonly 
used MS-LTC-DRGs. A commenter stated that ``high-volume'' MS-LTC-DRGs 
are less likely than ``low-volume'' MS-LTC-DRGs to decrease more than 
10-percent, in which case applying the proposed 10-percent cap in a 
budget neutral manner would generally result in increases to the 
relative weights of low-volume MS-LTC-DRGs at the expense of decreases 
to the relative weights of high-volume MS-LTC-DRGs. A commenter 
recommended that CMS should only apply the 10-percent cap to an MS-

[[Page 49153]]

LTC-DRG relative weight if it is one of the top five MS-LTC-DRGs, by 
volume, of LTCH discharges. This, the commenter stated, would target 
payment relief where it is most needed and would have more of a 
beneficial effect on payment stability from year to year.
    A number of commenters who disagreed with applying a budget 
neutrality adjustment to relative weights after application of the 10-
percent cap maintained that CMS has the statutory authority to make 
adjustments, including waiving the budget neutrality adjustment to the 
cap, under section 123 of the BBRA, as amended by section BIPA 
307(b)(1).
    Response: We appreciate the comments in support of the proposed 10-
percent cap on MS-LTC-DRG relative weight decreases. We agree that CMS 
has the statutory authority to implement this policy in a non-budget 
neutral manner. However, we continue to believe it is appropriate to 
implement this policy in a budget neutral manner, consistent with the 
existing budget neutrality requirement for annual MS-LTC-DRG 
reclassification and recalibration, which we adopted to mitigate 
estimated fluctuations in estimated aggregate LTCH PPS payments (72 FR 
26881-26882).
    However, we understand commenters' concerns regarding potential 
negative impacts of the budget neutrality adjustment on the highest 
volume MS-LTC-DRG relative weights. We recognize, as commenters stated, 
that the application of a 10-percent cap on decreases in MS-LTC-DRG 
relative weights, applied in a budget neutral manner, may inadvertently 
partially negate our stated intent to stabilize and increase 
predictability to LTCH payments. In response to these concerns, we 
conducted additional analysis regarding the cap on MS-LTC-DRG weights 
and the impact of the budget neutrality adjustment. Based on the March 
2022 update of the FY 2021 MedPAR file used for calculating the MS-LTC-
DRG relative weights in this final rule, under our proposal, 139 MS-
LTC-DRGs would be subject to the 10-percent cap in FY 2023.
    These 139 MS-LTC-DRGs accounted for approximately 5.1 percent of 
all standard Federal payment rate cases in FY 2021. After application 
of the cap to these 139 MS-LTC-DRGs, the budget neutrality adjustment, 
based on the data used for this final rule, would have reduced the 
relative weights of all MS-LTC-DRGs by 0.34 percent. We note that the 
proposed budget neutrality adjustment we calculated in the proposed 
rule was similar in magnitude and reduced the proposed relative weights 
by 0.33 percent. When developing this policy for the proposed rule, we 
considered the magnitude of the proposed budget neutrality adjustment 
against the overall benefits of our stated policy goal. As discussed in 
the proposed rule and noted previously, we believed the proposed policy 
would provide LTCHs more predictable and stable MS-LTC-DRG relative 
weights from year to year. When we made our proposal, it was our belief 
that the overall benefits of the policy would outweigh the effect of 
the corresponding budget neutrality adjustment on the MS-LTC-DRG 
relative weights. However, based on public comments received, it clear 
that not all commenters share this belief.
    Therefore, we have explored whether placing a limit on MS-LTC-DRGs 
subject to the cap, similar to the approach suggested by a commenter, 
would reduce both the number of MS-LTC-DRGs capped and the size of the 
budget neutrality adjustment. We found that limiting the application of 
the 10-percent cap to MS-LTC-DRGs with at least 25 cases resulted in a 
significant decrease to the number of MS-LTC-DRGs subject to the cap, 
from 139 to 25. The MS-LTC-DRGs capped under such policy accounted for 
3.9 percent of all standard Federal payment rate cases in FY 2021, and 
the associated budget neutrality adjustment for this cap would result 
in a much smaller reduction to the relative weights of all MS-LTC-DRGs 
(that is, -0.13 percent).
    We believe that modifying our proposed policy so that the 10-
percent cap on MS-LTC-DRG relative weight decreases only applies to MS-
LTC-DRGs with 25 or more cases addresses commenters' concerns about the 
destabilizing impact of the budget neutrality adjustment, as the budget 
neutrality adjustment associated with this more limited cap policy (-
0.13 percent reduction to the relative weights) is meaningfully less 
than the budget neutrality adjustment associated with our proposed cap 
policy. We believe that 25 cases is an appropriate threshold since that 
threshold is already used in establishing the low-volume MS-LTC-DRGs 
that are grouped into quintiles for purposes of calculating the MS-LTC-
DRG relative weights (As discussed in section VIII.B.4. of the preamble 
to this final rule, for purposes of calculating the MS-LTC-DRG relative 
weights, we group low-volume MS-LTC-DRGs, that is those MS-LTC-DRGs 
that contain between 1 and 24 applicable LTCH cases, into five 
categories (quintiles) based on average charges). We also believe that 
modifying our proposed policy to limit the application of the 10-
percent cap to MS-LTC-DRGs with 25 or more cases will still result in 
more predictable and stable MS-LTC-DRG relative weights from year to 
year, especially for high-volume MS-LTC-DRGs that generally have the 
largest financial impact on an LTCH's operations. We note that this 
modification to our 10-percent cap policy will treat MS-LTC-DRGs with 
1-24 cases (low-volume MS-LTC-DRGs) the same as we proposed to treat 
no-volume MS-LTC-DRGs. That is, the 10-percent cap will not apply to 
either MS-LTC-DRGs with 1-24 cases (low-volume) or no-volume MS-LTC-
DRGs.
    Comment: MedPAC, while agreeing with the proposal to cap decreases 
in MS-LTC-DRG weights at 90 percent of the MS-LTC-DRG relative weight 
from the previous year, recommended extending this policy to MS-LTC-DRG 
relative weights increasing by more than 10 percent, as well.
    Response: We appreciate the suggestion that the cap should apply to 
increases in MS-LTC-DRG relative weights as well as decreases. However, 
as we discussed in the proposed rule, our goal in smoothing year-to-
year changes in MS-LTC-DRG relative weights is to increase 
predictability for LTCHs to enable them to better plan; when hospitals 
have more time to adjust to significant changes to relative weights, 
they can mitigate financial impacts. We did not propose to limit 
increases in MS-LTC-DRG relative weights because we do not believe such 
a policy is needed to enable hospitals to more effectively budget and 
plan their operations.
    In this final rule, after consideration of public comments 
received, we are finalizing our proposed policy to cap decreases in MS-
LTC-DRG relative weights to 10 percent of the previous year's relative 
weight, with a modification that limits the application of the cap to 
only MS-LTC-DRGs with at least 25 applicable LTCH cases in the claims 
data used to calculate the relative weights for the fiscal year. We 
also are finalizing our proposal that the 10-percent cap on the 
reduction in a MS-LTC-DRG's relative weight in a given year will be 
budget neutral. As an example, if the relative weight for an MS-LTC-DRG 
with at least 25 applicable LTCH cases was 1.100 in FY 2022 and the 
relative weight for FY 2023 would otherwise be 0.9350, which would 
represent a decrease of 15 percent from FY 2022, the reduction would be 
limited to 10 percent such that the relative weight for FY 2023 would 
be 0.9900 (that is, 0.90 x FY 2022 weight of 1.100) prior to the 
application of the

[[Page 49154]]

budget neutrality adjustment (as described later in this section in 
Step 13 of our methodology). In cases where CMS creates new MS-LTC-DRGs 
or modifies the MS-LTC-DRGs as part of its annual reclassifications 
resulting in renumbering of one or more MS-LTC-DRGs, we are finalizing 
our proposal that this the 10-percent cap will not apply to the 
relative weight for any new or renumbered MS-LTC-DRGs for the fiscal 
year.
    Consequently, we are amending our proposed regulation at 42 CFR 
412.515 to reflect the modification we are adopting in this final rule 
to limit the application of the 10-percent cap on MS-LTC-DRG relative 
weight reductions to only MS-LTC-DRGs with at least 25 applicable LTCH 
cases in the claims data used to calculate the relative weights for the 
fiscal year. The technical details of this provision are discussed in 
section VIII.B.4. of the preamble to this final rule. We note that this 
provision is similar to the permanent 10-percent cap on decreases to a 
MS-DRG relative weight being adopted under the IPPS, as discussed in 
section II.E.d. of the preamble of this final rule.
c. Conforming Changes to Other Components of the FY 2023 MS-LTC-DRG 
Relative Weights Methodology
    In general, for FY 2023, we continue to apply the other components 
of our existing methodology for determining the MS-LTC-DRG relative 
weights (as discussed in greater detail in section VIII.B.4. of the 
preamble of this final rule) that are not impacted by our previously 
described modifications to our methodology. As discussed previously, we 
are establishing the FY 2023 MS-LTC-DRG relative weights using an 
average of the relative weights calculated both including and excluding 
the COVID-19 claims to align with an assumption that there will be 
fewer, but not zero, COVID-19 cases in FY 2023 compared to FY 2021. We 
note that in conjunction with this modification, we applied the MS-LTC-
DRG relative weights methodology, described later in this section, 
twice--once to determine the relative weights based on claims data that 
include COVID-19 cases and again to determine the relative weights 
based on claims data that exclude COVID-19 cases. Specifically, in 
determining the relative weights based on both sets of claims, we 
applied our established policies related to the hospital-specific 
relative value methodology, the treatment of severity levels in the MS 
LTC DRGs, low-volume and no-volume MS LTC DRGs, and adjustments for 
nonmonotonicity, only using data from applicable LTCH cases (which 
includes our policy of only using cases that would meet the criteria 
for exclusion from the site neutral payment rate). We discuss all 
components of our MS-LTC-DRG relative weight methodology in greater 
detail in section VIII.B.4.g. of the preamble of this final rule.
4. Development of the FY 2023 MS-LTC-DRG Relative Weights
a. General Overview of the MS-LTC-DRG Relative Weights
    One of the primary goals for the implementation of the LTCH PPS is 
to pay each LTCH an appropriate amount for the efficient delivery of 
medical care to Medicare patients. The system must be able to account 
adequately for each LTCH's case-mix to ensure both fair distribution of 
Medicare payments and access to adequate care for those Medicare 
patients whose care is costlier (67 FR 55984). To accomplish these 
goals, we have annually adjusted the LTCH PPS standard Federal 
prospective payment rate by the applicable relative weight in 
determining payment to LTCHs for each case. Under the LTCH PPS, 
relative weights for each MS-LTC-DRG are a primary element used to 
account for the variations in cost per discharge and resource 
utilization among the payment groups (Sec.  412.515). To ensure that 
Medicare patients classified to each MS-LTC-DRG have access to an 
appropriate level of services and to encourage efficiency, we calculate 
a relative weight for each MS-LTC-DRG that represents the resources 
needed by an average inpatient LTCH case in that MS-LTC-DRG. For 
example, cases in an MS-LTC-DRG with a relative weight of 2 would, on 
average, cost twice as much to treat as cases in an MS-LTC-DRG with a 
relative weight of 1.
    The established methodology to develop the MS-LTC-DRG relative 
weights is generally consistent with the methodology established when 
the LTCH PPS was implemented in the August 30, 2002 LTCH PPS final rule 
(67 FR 55989 through 55991). However, there have been some 
modifications of our historical procedures for assigning relative 
weights in cases of zero volume or nonmonotonicity or both resulting 
from the adoption of the MS-LTC-DRGs, along with the change made in 
conjunction with the implementation of the dual rate LTCH PPS payment 
structure beginning in FY 2016 to use LTCH claims data from only LTCH 
PPS standard Federal payment rate cases (or LTCH PPS cases that would 
have qualified for payment under the LTCH PPS standard Federal payment 
rate if the dual rate LTCH PPS payment structure had been in effect at 
the time of the discharge). (For details on the modifications to our 
historical procedures for assigning relative weights in cases of zero 
volume and nonmonotonicity or both, we refer readers to the FY 2008 
IPPS final rule with comment period (72 FR 47289 through 47295) and the 
FY 2009 IPPS final rule (73 FR 48542 through 48550).) For details on 
the change in our historical methodology to use LTCH claims data only 
from LTCH PPS standard Federal payment rate cases (or cases that would 
have qualified for such payment had the LTCH PPS dual payment rate 
structure been in effect at the time) to determine the MS-LTC-DRG 
relative weights, we refer readers to the FY 2016 IPPS/LTCH PPS final 
rule (80 FR 49614 through 49617).
    For purposes of determining the MS-LTC-DRG relative weights, under 
our historical methodology, there are three different categories of MS-
LTC-DRGs based on volume of cases within specific MS-LTC-DRGs: (1) MS-
LTC-DRGs with at least 25 applicable LTCH cases in the data used to 
calculate the relative weight, which are each assigned a unique 
relative weight; (2) low-volume MS-LTC-DRGs (that is, MS-LTC-DRGs that 
contain between 1 and 24 applicable LTCH cases that are grouped into 
quintiles (as described later in this section in Step 3 of our 
methodology) and assigned the relative weight of the quintile); and (3) 
no-volume MS-LTC-DRGs that are cross-walked to other MS-LTC-DRGs based 
on the clinical similarities and assigned the relative weight of the 
cross-walked MS-LTC-DRG (as described later in this section in Step 8 
of our methodology). For FY 2023, we are continuing to use applicable 
LTCH cases to establish the same volume-based categories to calculate 
the FY 2023 MS-LTC-DRG relative weights.
    As discussed in section VIII.B.3.a. of the preamble to this final 
rule, for FY 2023, we are establishing the MS-LTC-DRG relative weights 
as an average of the relative weights calculated both including and 
excluding the COVID-19 claims. As discussed in section VIII.B.3.b. of 
the preamble to this final rule, we also are establishing a 10-percent 
cap on the reduction in a MS- LTC-DRG's relative weight, beginning in 
FY 2023 for MS-LTC-DRGs with at least 25 applicable LTCH cases in the 
claims data used to calculate the relative weights for the fiscal year.

[[Page 49155]]

b. Development of the MS-LTC-DRG Relative Weights for FY 2023
    In this section, we present our methodology for determining the MS-
LTC-DRG relative weights for FY 2023. In general, we are continuing to 
apply the components of our existing methodology that are not impacted 
by our modifications to use an average of the relative weights 
calculated both including and excluding the COVID-19 claims and the 
application of a 10-percent cap on the reduction in a MS-LTC-DRG's 
relative weight, as discussed in section VIII.B.3 of the preamble to 
this final rule. For example, we are continuing with the application of 
established policies related to the hospital-specific relative value 
methodology, the treatment of severity levels in the MS-LTC-DRGs, low-
volume and no-volume MS-LTC-DRGs, adjustments for nonmonotonicity, and 
only using data from applicable LTCH cases (which includes our policy 
of only using cases that would meet the criteria for exclusion from the 
site neutral payment rate). We note that in our establishment of MS-
LTC-DRG relative weights using an average of the relative weights 
calculated both including and excluding the COVID-19 claims, particular 
components of our existing relative weight methodology are performed 
twice (once when determining relative weights based on claims data that 
include COVID-19 cases and again when determining relative weights 
based on claims data that exclude COVID-19 cases). Later in this 
section we list and provide a brief description of our steps for 
determining the FY 2023 MS-LTC-DRG relative weights. Each step is 
discussed in greater detail later in this section.
     Step 1--Prepare data for MS-LTC-DRG relative 
weight calculation. In this step, we select and group the applicable 
claims data used in the development of the MS-LTC-DRG relative weights. 
For FY 2023, we are preparing two sets of claims: a claims dataset that 
includes COVID-19 cases and a claims dataset that excludes COVID-19 
cases.
     Step 2--Remove cases with a length of stay of 7 
days or less. In this step, we trim the applicable claims data to 
remove cases with a length of stay 7 days or less. For FY 2023, we are 
performing this step on each set of claims data (claims dataset that 
includes COVID-19 cases and claims dataset that excludes COVID-19 
cases).
     Step 3--Establish low-volume MS-LTC-DRG quintiles. In this 
step, we employ our established quintile methodology for low-volume MS-
LTC-DRGs (that is, MS-LTC-DRGs with less than 25 cases). For FY 2023, 
we are performing this step on each set of claims data (claims dataset 
that includes COVID-19 cases and claims dataset that excludes COVID-19 
cases).
     Step 4--Remove statistical outliers. In this step, we trim 
the applicable claims data to remove statistical outlier cases. For FY 
2023, we are performing this step on each set of claims data (claims 
dataset that includes COVID-19 cases and claims dataset that excludes 
COVID-19 cases).
     Step 5--Adjust charges for the effects of Short Stay 
Outliers (SSOs). In this step, we adjust the number of applicable cases 
in each MS-LTC-DRG (or low-volume quintile) for the effect of SSO 
cases. For FY 2023, we are performing this step on each set of claims 
data (claims dataset that includes COVID-19 cases and claims dataset 
that excludes COVID-19 cases).
     Step 6--Calculate the relative weights on an iterative 
basis using the hospital-specific relative weights methodology. In this 
step, we use our established hospital-specific relative value (HSRV) 
methodology, which is an iterative process, to calculate the relative 
weights. For FY 2023, we are using the HSRV methodology to calculate 
relative weights using the claims that include COVID-19 cases and again 
using the claims that exclude the COVID-19 cases.
     Step 7-- Adjust the relative weights to account for 
nonmonotonically increasing relative weights. In this step, we make 
adjustments that ensure that within each base MS-LTC-DRG, the relative 
weights increase by MS-LTC-DRG severity. For FY 2023, we are adjusting 
each set of relative weights (that is, the relative weights calculated 
including COVID-19 cases and the relative weights calculated excluding 
COVID-19 cases).
     Step 8--Determine a relative weight for MS-LTC-DRGs with 
no applicable LTCH cases. In this step, we cross-walk each no-volume 
MS-LTC-DRG to another MS-LTC-DRG for which we calculated a relative 
weight. For FY 2023, we are cross-walking no-volume MS-LTC-DRGs in each 
set of relative weights (that is, the set of relative weights 
calculated including COVID-19 cases and the set of relative weights 
calculated excluding COVID-19 cases).
     Step 9--Normalize each set of relative weights. In this 
step, we make a normalization adjustment so that the recalibration of 
the MS-LTC-DRG relative weights (that is, the process itself) neither 
increases nor decreases the average case-mix index. For FY 2023, we are 
normalizing the set of relative weights calculated including COVID-19 
cases and the set relative weights calculated excluding COVID-19 cases.
     Step 10--Average the two sets of normalized 
relative weights. In this step, we average the set of normalized 
relative weights calculated including COVID-19 cases and the set of 
normalized relative weights calculated excluding COVID-19 cases. In 
addition to the relative weights, we also average the geometric mean 
length of stays and arithmetic mean length of stays.
     Step 11--Budget neutralize the averaged relative 
weights. In this step, to ensure budget neutrality in the annual update 
to the MS-LTC-DRG classifications and relative weights, we adjust the 
relative weights by a normalization factor and budget neutrality factor 
that ensures estimated aggregate LTCH PPS payments will be unaffected 
by the updates to the MS-LTC-DRG classifications and relative weights. 
This step is performed prior to applying the 10-percent cap.
     Step 12--Apply the 10-percent cap to decreases 
in MS-LTC-DRG relative weights. In this step we limit the reduction of 
the relative weight for a MS-LTC-DRG to 10 percent of its prior year 
value. This 10-percent cap does not apply to zero-volume MS-LTC-DRGs or 
low-volume MS-LTC-DRGs.
     Step 13--Calculate the MS-LTC-DRG cap budget 
neutrality factor. In this step, to ensure budget neutrality in the 
application of the MS-LTC-DRG cap policy, we adjust the relative 
weights by a budget neutrality factor that ensures estimated aggregate 
LTCH PPS payments will be unaffected by our application of the cap to 
the MS-LTC-DRG relative weights.
    Later in this section we describe each of the 13 steps for 
calculating the FY 2023 MS-LTC-DRG relative weights in greater detail. 
In this discussion, we note when the step was performed twice under our 
provisions for averaging relative weights calculated including COVID-19 
cases and relative weights calculated excluding COVID-19 cases.
    Step 1--Prepare data for MS-LTC-DRG relative weight calculation.
    In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28469), 
consistent with our proposals regarding the calculation of the proposed 
MS-LTC-DRG relative weights for FY 2023, we obtained total charges from 
FY 2021 Medicare LTCH claims data from the December 2021 update of the 
FY 2021 MedPAR file, which was the best available data at that time, 
and we proposed to use Version 40 of the GROUPER to classify LTCH 
cases. Consistent with our historical practice, we proposed that if 
better data became

[[Page 49156]]

available, we would use those data and the finalized Version 40 of the 
GROUPER in establishing the FY 2023 MS-LTC-DRG relative weights in the 
final rule. Accordingly, for this final rule, we are establishing the 
FY 2023 MS-LTC-DRG relative weights based on updated FY 2021 Medicare 
LTCH claims data from the March 2022 update of the FY 2021 MedPAR file, 
which is the best available data at the time of development of this 
final rule, and the finalized Version 40 of the GROUPER to classify 
LTCH cases.
    To calculate the FY 2023 MS-LTC-DRG relative weights under the dual 
rate LTCH PPS payment structure, as we proposed, we continue to use 
applicable LTCH data, which includes our policy of only using cases 
that meet the criteria for exclusion from the site neutral payment rate 
(or would have met the criteria had they been in effect at the time of 
the discharge) (80 FR 49624). Specifically, we began by first 
evaluating the LTCH claims data in the March 2022 update of the FY 2021 
MedPAR file to determine which LTCH cases would meet the criteria for 
exclusion from the site neutral payment rate under Sec.  412.522(b) or 
had the dual rate LTCH PPS payment structure applied to those cases at 
the time of discharge. We identified the FY 2021 LTCH cases that were 
not assigned to MS-LTC-DRGs 876, 880, 881, 882, 883, 884, 885, 886, 
887, 894, 895, 896, 897, 945, and 946, which identify LTCH cases that 
do not have a principal diagnosis relating to a psychiatric diagnosis 
or to rehabilitation; and that either--
     The admission to the LTCH was ``immediately preceded'' by 
discharge from a subsection (d) hospital and the immediately preceding 
stay in that subsection (d) hospital included at least 3 days in an 
ICU, as we define under the ICU criterion; or
     The admission to the LTCH was ``immediately preceded'' by 
discharge from a subsection (d) hospital and the claim for the LTCH 
discharge includes the applicable procedure code that indicates at 
least 96 hours of ventilator services were provided during the LTCH 
stay, as we define under the ventilator criterion. Claims data from the 
FY 2021 MedPAR file that reported ICD-10-PCS procedure code 5A1955Z 
were used to identify cases involving at least 96 hours of ventilator 
services in accordance with the ventilator criterion. We note that we 
have previously addressed the treatment of cases that would have been 
excluded from the site neutral payment rate under the statutory 
provisions that provided for temporary exception from the site neutral 
payment rate under the LTCH PPS for certain spinal cord specialty 
hospitals or for certain severe wound care discharges from certain 
LTCHs provided by sections 15009 and 15010 of Public Law 114-255, 
respectively. These statutory provisions were not in effect for any 
discharges occurring in FY 2021 (or beyond), so it is no longer 
necessary to address their treatment for purposes of developing the MS-
LTC-DRG relative weights. We also note that section 3711(b)(2) of the 
CARES Act, which provided a waiver of the application of the site 
neutral payment rate for LTCH cases admitted during the COVID-19 PHE 
period, was in effect for the entirety of FY 2021. Therefore, all LTCH 
PPS cases in FY 2021 were paid the LTCH PPS standard Federal rate 
regardless of whether the discharge met the statutory patient criteria. 
However, for purposes of setting rates for LTCH PPS standard Federal 
rate cases for FY 2023 (including MS-LTC-DRG relative weights), we used 
FY 2021 cases that meet the statutory patient criteria without 
consideration to how those cases were paid in FY 2021.
    Furthermore, consistent with our historical methodology, we 
excluded any claims in the resulting data set that were submitted by 
LTCHs that were all-inclusive rate providers and LTCHs that are paid in 
accordance with demonstration projects authorized under section 402(a) 
of Public Law 90-248 or section 222(a) of Public Law 92-603. In 
addition, consistent with our historical practice and our policies, we 
excluded any Medicare Advantage (Part C) claims in the resulting data. 
Such claims were identified based on the presence of a GHO Paid 
indicator value of ``1'' in the MedPAR files.
    In addition, as discussed in section VIII.B.3.a. of this final 
rule, for FY 2023, we are establishing the MS-LTC-DRG relative weights 
as an average of the relative weights calculated both including and 
excluding the COVID-19 claims. To calculate the set of relative weights 
based on claims that excluded COVID-19 cases, we performed an 
additional trim to remove COVID-19 cases. We identified COVID-19 cases 
as any claim in the FY 2021 MedPAR file with a principal or secondary 
diagnosis of COVID-19 (ICD-10-CM diagnosis code U07.1).
    In summary, in general, we identified the claims data used in the 
development of the FY 2023 MS-LTC-DRG relative weights in this final 
rule by trimming claims data that would have been paid the site neutral 
payment rate had the provisions of the CARES Act not been in effect. We 
trimmed the claims data of all-inclusive rate providers reported in the 
March 2022 update of the FY 2021 MedPAR file and any Medicare Advantage 
claims data. There were no data from any LTCHs that are paid in 
accordance with a demonstration project reported in the March 2022 
update of the FY 2021 MedPAR file, but, had there been any, we would 
have trimmed the claims data from those LTCHs as well, in accordance 
with our established policy.
    We used the remaining data (that is, the applicable LTCH data) in 
the subsequent steps to calculate the set of relative weights based on 
claims that include COVID-19 cases. In addition, we performed a trim to 
remove COVID-19 cases based on a principal or secondary diagnosis of 
COVID-19. We used these data in the subsequent steps to calculate the 
set of relative weights based on claims that exclude COVID-19 cases.
    Step 2--Remove cases with a length of stay of 7 days or less.
    The next step in our calculation of the FY 2023 MS-LTC-DRG relative 
weights is to remove cases with a length of stay of 7 days or less. The 
MS-LTC-DRG relative weights reflect the average of resources used on 
representative cases of a specific type. Generally, cases with a length 
of stay of 7 days or less do not belong in an LTCH because these stays 
do not fully receive or benefit from treatment that is typical in an 
LTCH stay, and full resources are often not used in the earlier stages 
of admission to an LTCH. If we were to include stays of 7 days or less 
in the computation of the FY 2023 MS-LTC-DRG relative weights, the 
value of many relative weights would decrease and, therefore, payments 
would decrease to a level that may no longer be appropriate. We do not 
believe that it would be appropriate to compromise the integrity of the 
payment determination for those LTCH cases that actually benefit from 
and receive a full course of treatment at an LTCH by including data 
from these very short stays. Therefore, as we proposed, consistent with 
our existing relative weight methodology, in determining the FY 2023 
MS-LTC-DRG relative weights, we removed LTCH cases with a length of 
stay of 7 days or less from applicable LTCH cases for both sets of 
claims (that is the applicable LTCH claims that include COVID-19 cases 
and the applicable LTCH claims that exclude COVID-19 cases). (For 
additional information on what is removed in this step of the relative 
weight methodology, we refer readers to 67 FR 55989 and 74 FR 43959.)
    Step 3--Establish low-volume MS-LTC-DRG quintiles.

[[Page 49157]]

    To account for MS-LTC-DRGs with low-volume (that is, with fewer 
than 25 applicable LTCH cases), consistent with our existing 
methodology, as we proposed, we are continuing to employ the quintile 
methodology for low-volume MS-LTC-DRGs, such that we grouped the ``low-
volume MS-LTC-DRGs'' (that is, MS-LTC-DRGs that contain between 1 and 
24 applicable LTCH cases into one of five categories (quintiles) based 
on average charges (67 FR 55984 through 55995; 72 FR 47283 through 
47288; and 81 FR 25148)). Under our provision in section VIII.B.3.a. of 
the preamble to this final rule to establish the FY 2023 MS-LTC-DRG 
relative weights as an average of the relative weights calculated both 
including and excluding the COVID-19 claims, we employed our quintile 
methodology when calculating the relative weights for each set of 
claims (that is the claims that include COVID-19 cases and the claims 
that exclude COVID-19 cases).
    In this final rule, based on the best available data (that is, the 
March 2022 update of the FY 2021 MedPAR files), we identified 233 MS-
LTC-DRGs that contained between 1 and 24 applicable LTCH cases in the 
claims data that included COVID-19 cases, and 232 MS LTC-DRGs that 
contained between 1 and 24 applicable LTCH cases in the claims data 
that excluded COVID-19 cases. These lists of MS-LTC-DRGs were then 
divided into 1 of the 5 low-volume quintiles. We assigned the low-
volume MS-LTC-DRGs to specific low-volume quintiles by sorting the low-
volume MS-LTC-DRGs in ascending order by average charge in accordance 
with our established methodology. Based on the data available for this 
final rule, the number of MS-LTC-DRGs with less than 25 applicable LTCH 
cases in each set of claims was not evenly divisible by 5. The 
quintiles based on the claims data that included COVID-19 cases each 
contained at least 46 MS-LTC-DRGs (233/5 = 46 with a remainder of 3). 
Meanwhile, the quintiles based on the claims data that excluded COVID-
cases also each contained at least 46 MS-LTC-DRGs (232/5 = 46 with a 
remainder of 2). We employed our historical methodology of assigning 
each remainder low-volume MS-LTC-DRG to the low-volume quintile that 
contains an MS-LTC-DRG with an average charge closest to that of the 
remainder low-volume MS-LTC-DRG.
    For the claims that include COVID-19 cases, the application of our 
quintile methodology resulted in 2 low-volume quintiles containing 46 
MS-LTC DRGs (Quintiles 1 and 5) and 3 low-volume quintiles containing 
47 MS-LTC-DRGs (Quintiles 2, 3, and 4). For the claims that excluded 
COVID-19 cases, the application of our quintile methodology resulted in 
3 low-volume quintiles containing 46 MS-LTC DRGs (Quintiles 1, 3, and 
5) and 2 low-volume quintiles containing 47 MS-LTC-DRGs (Quintiles 2 
and 4). In cases where these initial assignments of low-volume MS-LTC-
DRGs to quintiles results in nonmonotonicity within a base-DRG, we are 
making adjustments to the resulting low-volume MS-LTC-DRGs to preserve 
monotonicity, as discussed in Step 7 of our methodology.
    To determine the FY 2023 relative weights for the low-volume MS-
LTC-DRGs, consistent with our historical practice, we used the five 
low-volume quintiles from each set of claims described previously. We 
determined a relative weight and (geometric) average length of stay for 
each of the five low-volume quintiles using the methodology described 
in Step 6 of our methodology. We assigned the same relative weight and 
average length-of-stay to each of the low-volume MS-LTC-DRGs that make 
up an individual low-volume quintile. These calculations were performed 
separately for the relative weight set based on claims that include 
COVID-19 cases and the relative weight set based on claims that exclude 
COVID-19 cases. We note that, as this system is dynamic, it is possible 
that the number and specific type of MS-LTC-DRGs with a low-volume of 
applicable LTCH cases would vary in the future.
    Furthermore, we note that we continue to monitor the volume (that 
is, the number of applicable LTCH cases) in the low-volume quintiles to 
ensure that our quintile assignments used in determining the MS-LTC-DRG 
relative weights result in appropriate payment for LTCH cases grouped 
to low-volume MS-LTC-DRGs and do not result in an unintended financial 
incentive for LTCHs to inappropriately admit these types of cases. In 
the proposed rule, we noted our description in previous rules did not 
specify the point in our methodology when the low-volume MS-LTC-DRG 
quintiles are established. We stated that although we are now including 
this step explicitly, this is not a change to our historical 
methodology for determining the MS-LTC-DRG relative weights.
    For this final rule, we are providing the lists of the composition 
of the low-volume quintiles for low-volume MS-LTC-DRGs in a 
supplemental data file for public use posted via the internet on the 
CMS website for this final rule at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html to 
streamline the information made available to the public that is used in 
the annual development of Table 11. This supplemental data file 
includes the composition of low-volume quintiles for low-volume MS-LTC-
DRGs based on the claims that include COVID-19 cases and the 
composition of the low-volume quintiles for low-volume MS-LTC-DRGs 
based on the claims that exclude COVID-19 cases.
    Step 4--Remove statistical outliers.
    The next step in our calculation of the FY 2023 MS-LTC-DRG relative 
weights is to remove statistical outlier cases from the LTCH cases with 
a length-of-stay of at least 8 days. Consistent with our existing 
relative weight methodology, as we proposed, we are continuing to 
define statistical outliers as cases that are outside of 3.0 standard 
deviations from the mean of the log distribution of both charges per 
case and the charges per day for each MS-LTC-DRG. These statistical 
outliers are removed prior to calculating the relative weights because 
we believe that they may represent aberrations in the data that distort 
the measure of average resource use.
    Including those LTCH cases in the calculation of the relative 
weights could result in an inaccurate relative weight that does not 
truly reflect relative resource use among those MS-LTC-DRGs. (For 
additional information on what is removed in this step of the relative 
weight methodology, we refer readers to 67 FR 55989 and 74 FR 43959.) 
This step was performed on both sets of claims (that is the applicable 
LTCH claims that include COVID-19 cases and the applicable LTCH claims 
that exclude COVID-19 cases). After removing cases with a length of 
stay of 7 days or less and statistical outliers, in each set of claims, 
we were left with applicable LTCH cases that have a length of stay 
greater than or equal to 8 days. In this final rule, we refer to these 
cases as ``trimmed applicable LTCH cases.''
    Step 5--Adjust charges for the effects of Short Stay Outliers 
(SSOs).
    As the next step in the calculation of the FY 2023 MS-LTC-DRG 
relative weights, consistent with our historical approach, as we 
proposed, we adjusted each LTCH's charges per discharge for those 
remaining cases in each set of claims (that is, trimmed applicable LTCH 
cases that include COVID-19 cases and the trimmed applicable LTCH cases 
that exclude COVID-19 cases) for the effects of SSOs (as defined in 
Sec.  412.529(a) in conjunction with Sec.  412.503). Specifically, as 
we proposed, we made this adjustment by counting an

[[Page 49158]]

SSO case as a fraction of a discharge based on the ratio of the length 
of stay of the case to the average length of stay of all cases grouped 
to the MS-LTC-DRG. This has the effect of proportionately reducing the 
impact of the lower charges for the SSO cases in calculating the 
average charge for the MS-LTC-DRG. This process produces the same 
result as if the actual charges per discharge of an SSO case were 
adjusted to what they would have been had the patient's length of stay 
been equal to the average length of stay of the MS-LTC-DRG.
    Counting SSO cases as full LTCH cases with no adjustment in 
determining the FY 2023 MS-LTC-DRG relative weights would lower the 
relative weight for affected MS-LTC-DRGs because the relatively lower 
charges of the SSO cases would bring down the average charge for all 
cases within a MS-LTC-DRG. This would result in an ``underpayment'' for 
non-SSO cases and an ``overpayment'' for SSO cases. Therefore, we are 
continuing to adjust for SSO cases under Sec.  412.529 in this manner 
because it would result in more appropriate payments for all LTCH PPS 
standard Federal payment rate cases. (For additional information on 
this step of the relative weight methodology, we refer readers to 67 FR 
55989 and 74 FR 43959.)
    Step 6--Calculate the relative weights on an iterative basis using 
the hospital-specific relative value (HSRV) methodology.
    By nature, LTCHs often specialize in certain areas, such as 
ventilator-dependent patients. Some case types (MS-LTC-DRGs) may be 
treated, to a large extent, in hospitals that have, from a perspective 
of charges, relatively high (or low) charges. This nonrandom 
distribution of cases with relatively high (or low) charges in specific 
MS-LTC-DRGs has the potential to inappropriately distort the measure of 
average charges. To account for the fact that cases may not be randomly 
distributed across LTCHs, consistent with the methodology we have used 
since the implementation of the LTCH PPS, in this FY 2023 IPPS/LTCH PPS 
final rule, as we proposed, we are continuing to use a hospital-
specific relative value (HSRV) methodology to calculate the MS-LTC-DRG 
relative weights for FY 2023. We believe that this method removes this 
hospital-specific source of bias in measuring LTCH average charges (67 
FR 55985). Specifically, under this methodology, we reduced the impact 
of the variation in charges across providers on any particular MS-LTC-
DRG relative weight by converting each LTCH's charge for an applicable 
LTCH case to a relative value based on that LTCH's average charge for 
such cases.
    Under the HSRV methodology, we standardize charges for each LTCH by 
converting its charges for each applicable LTCH case to hospital-
specific relative charge values and then adjusting those values for the 
LTCH's case-mix. The adjustment for case-mix is needed to rescale the 
hospital-specific relative charge values (which, by definition, average 
1.0 for each LTCH). The average relative weight for an LTCH is its 
case-mix; therefore, it is reasonable to scale each LTCH's average 
relative charge value by its case-mix. In this way, each LTCH's 
relative charge value is adjusted by its case-mix to an average that 
reflects the complexity of the applicable LTCH cases it treats relative 
to the complexity of the applicable LTCH cases treated by all other 
LTCHs (the average LTCH PPS case-mix of all applicable LTCH cases 
across all LTCHs). In other words, by multiplying an LTCH's relative 
charge values by the LTCH's case-mix index, we account for the fact 
that the same relative charges are given greater weight at an LTCH with 
higher average costs than they would at an LTCH with low average costs, 
which is needed to adjust each LTCH's relative charge value to reflect 
its case-mix relative to the average case-mix for all LTCHs. By 
standardizing charges in this manner, we count charges for a Medicare 
patient at an LTCH with high average charges as less resource-intensive 
than they would be at an LTCH with low average charges. For example, a 
$10,000 charge for a case at an LTCH with an average adjusted charge of 
$17,500 reflects a higher level of relative resource use than a $10,000 
charge for a case at an LTCH with the same case-mix, but an average 
adjusted charge of $35,000. We believe that the adjusted charge of an 
individual case more accurately reflects actual resource use for an 
individual LTCH because the variation in charges due to systematic 
differences in the markup of charges among LTCHs is taken into account.
    Consistent with our historical relative weight methodology, as we 
proposed, we calculated the FY 2023 MS-LTC-DRG relative weights using 
the HSRV methodology, which is an iterative process. Under our 
provision in section VIII.B.3.a. of the preamble to this final rule to 
establish the FY 2023 MS-LTC-DRG relative weights as an average of the 
relative weights calculated both including and excluding the COVID-19 
claims, we applied the HSRV methodology when calculating the relative 
weights for each sets of claims (that is the claims that include COVID-
19 cases and the claims that exclude COVID-19 cases).
    Therefore, in accordance with our established methodology, for FY 
2023, we continued to standardize charges for each applicable LTCH case 
by first dividing the adjusted charge for the case (adjusted for SSOs 
under Sec.  412.529 as described in Step 5 of our methodology) by the 
average adjusted charge for all applicable LTCH cases at the LTCH in 
which the case was treated. The average adjusted charge reflects the 
average intensity of the health care services delivered by a particular 
LTCH and the average cost level of that LTCH. The average adjusted 
charge was then multiplied by the LTCH's case-mix index to produce an 
adjusted hospital-specific relative charge value for the case. We used 
an initial case-mix index value of 1.0 for each LTCH.
    For each MS-LTC-DRG, we calculated the FY 2023 relative weight by 
dividing the SSO-adjusted average of the hospital-specific relative 
charge values for applicable LTCH cases for the MS-LTC-DRG (that is, 
the sum of the hospital-specific relative charge value, as previously 
stated, divided by the sum of equivalent cases from Step 5 for each MS-
LTC-DRG) by the overall SSO-adjusted average hospital-specific relative 
charge value across all applicable LTCH cases for all LTCHs (that is, 
the sum of the hospital-specific relative charge value, as previously 
stated, divided by the sum of equivalent applicable LTCH cases from 
Step 5 for each MS-LTC-DRG). Using these recalculated MS-LTC-DRG 
relative weights, each LTCH's average relative weight for all of its 
SSO-adjusted trimmed applicable LTCH cases (that is, its case-mix) was 
calculated by dividing the sum of all the LTCH's MS-LTC-DRG relative 
weights by its total number of SSO-adjusted trimmed applicable LTCH 
cases. The LTCHs' hospital-specific relative charge values (from 
previous) are then multiplied by the hospital-specific case-mix 
indexes. The hospital-specific case-mix adjusted relative charge values 
were then used to calculate a new set of MS-LTC-DRG relative weights 
across all LTCHs. This iterative process continued until there was 
convergence between the relative weights produced at adjacent steps, 
for example, when the maximum difference was less than 0.0001.
    Step 7--Adjust the relative weights to account for nonmonotonically 
increasing relative weights.
    The MS-DRGs contain base DRGs that have been subdivided into one, 
two, or three severity of illness levels. Where there are three 
severity levels, the most severe level has at least one secondary

[[Page 49159]]

diagnosis code that is referred to as an MCC (that is, major 
complication or comorbidity). The next lower severity level contains 
cases with at least one secondary diagnosis code that is a CC (that is, 
complication or comorbidity). Those cases without an MCC or a CC are 
referred to as ``without CC/MCC.'' When data do not support the 
creation of three severity levels, the base MS-DRG is subdivided into 
either two levels or the base MS-DRG is not subdivided. The two-level 
subdivisions may consist of the MS-DRG with CC/MCC and the MS-DRG 
without CC/MCC. Alternatively, the other type of two-level subdivision 
may consist of the MS-DRG with MCC and the MS-DRG without MCC.
    In those base MS-LTC-DRGs that are split into either two or three 
severity levels, cases classified into the ``without CC/MCC'' MS-LTC-
DRG are expected to have a lower resource use (and lower costs) than 
the ``with CC/MCC'' MS-LTC-DRG (in the case of a two-level split) or 
both the ``with CC'' and the ``with MCC'' MS-LTC-DRGs (in the case of a 
three-level split). That is, theoretically, cases that are more severe 
typically require greater expenditure of medical care resources and 
would result in higher average charges. Therefore, in the three 
severity levels, relative weights should increase by severity, from 
lowest to highest. If the relative weights decrease as severity 
increases (that is, if within a base MS-LTC-DRG, an MS-LTC-DRG with CC 
has a higher relative weight than one with MCC, or the MS-LTC-DRG 
``without CC/MCC'' has a higher relative weight than either of the 
others), they are nonmonotonic. We continue to believe that utilizing 
nonmonotonic relative weights to adjust Medicare payments would result 
in inappropriate payments because the payment for the cases in the 
higher severity level in a base MS-LTC-DRG (which are generally 
expected to have higher resource use and costs) would be lower than the 
payment for cases in a lower severity level within the same base MS-
LTC-DRG (which are generally expected to have lower resource use and 
costs). Therefore, in determining the FY 2023 MS-LTC-DRG relative 
weights based on each set of claims (that is claims that include COVID-
19 cases and the claims that exclude COVID-19 cases), consistent with 
our historical methodology, as we proposed, we continued to combine MS-
LTC-DRG severity levels within a base MS-LTC-DRG for the purpose of 
computing a relative weight when necessary to ensure that monotonicity 
is maintained. For a comprehensive description of our existing 
methodology to adjust for nonmonotonicity, we refer readers to the FY 
2010 IPPS/RY 2010 LTCH PPS final rule (74 FR 43964 through 43966). For 
both sets of weights, the one based on claims that include COVID-19 
cases and the one based on claims that exclude COVID-19 cases, any 
adjustments for nonmonotonicity that were made in determining the FY 
2023 MS-LTC-DRG relative weights by applying this methodology are 
denoted in Table 11, which is listed in section VI. of the Addendum to 
this final rule and is available via the internet on the CMS website.
    Step 8--Determine a relative weight for MS-LTC-DRGs with no 
applicable LTCH cases.
    Using the trimmed applicable LTCH cases, consistent with our 
historical methodology, we identified the MS-LTC-DRGs for which there 
were no claims in the March 2022 update of the FY 2021 MedPAR file and, 
therefore, for which no charge data was available for these MS-LTC-
DRGs. Because patients with a number of the diagnoses under these MS-
LTC-DRGs may be treated at LTCHs, consistent with our historical 
methodology, we generally assign a relative weight to each of the no-
volume MS-LTC-DRGs based on clinical similarity and relative costliness 
(with the exception of ``transplant'' MS-LTC-DRGs, ``error'' MS-LTC-
DRGs, and MS-LTC-DRGs that indicate a principal diagnosis related to a 
psychiatric diagnosis or rehabilitation (referred to as the 
``psychiatric or rehabilitation'' MS-LTC-DRGs), as discussed later in 
this section of this final rule). (For additional information on this 
step of the relative weight methodology, we refer readers to 67 FR 
55991 and 74 FR 43959 through 43960.)
    Consistent with our existing methodology, as we proposed, we cross-
walked each no-volume MS-LTC-DRG to another MS-LTC-DRG for which we 
calculated a relative weight (determined in accordance with the 
methodology as previously described). Then, the ``no-volume'' MS-LTC-
DRG was assigned the same relative weight (and average length of stay) 
of the MS-LTC-DRG to which it was cross-walked (as described in greater 
detail in this section of this final rule).
    For this final rule, there was only one claim grouped to MS-LTC-DRG 
273 (Percutaneous and other intracardiac procedures with MCC) in the 
March 2022 update of the FY 2021 MedPAR file. This claim had a COVID-19 
diagnosis code. Therefore, when determining relative weights based on 
all applicable LTCH claims, a relative weight was computed for MS-LTC-
DRG 273. However, when determining relative weights based on the set of 
claims that excluded COVID-19 cases, a relative was not computed for 
MS-LTC-DRG 273. When establishing the relative weights based on claims 
that exclude COVID-19 cases, instead of assigning a cross-walked 
relative weight for MS-LTC-DRG 273, as we proposed, we assigned MS-LTC-
DRG 273 the relative weight calculated using all applicable LTCH cases. 
In the absence of a non-COVID-19 claim for this MS-LTC-DRG, we believe 
the relative weight based on a COVID-19 claim grouped to this same MS-
LTC-DRG would more accurately reflect the relative resource use of this 
MS-LTC-DRG than a relative weight based on a cross-walked MS-LTC-DRG.
    Of the 767 MS-LTC-DRGs for FY 2023, we identified 427 MS-LTC-DRGs 
for which there were no trimmed applicable LTCH cases. We do not 
include MS-LTC-DRG 273, discussed previously, in this count. The 427 MS 
LTC DRGs for which there were no trimmed applicable LTCH cases includes 
the 11 ``transplant'' MS-LTC-DRGs, the 2 ``error'' MS-LTC-DRGs, and the 
15 ``psychiatric or rehabilitation'' MS-LTC-DRGs, which are discussed 
in this section of this rule, such that we identified 399 MS-LTC-DRGs 
that for which, we assigned a relative weight using our existing ``no-
volume'' MS-LTC-DRG methodology (that is, 427-11-2-15 = 399). As we 
proposed, we assigned relative weights to each of the 399 no-volume MS-
LTC-DRGs based on clinical similarity and relative costliness to 1 of 
the remaining 340 (767-427 = 340) MS-LTC-DRGs for which we calculated 
relative weights based on the trimmed applicable LTCH cases in the FY 
2021 MedPAR file data using the steps described previously. (For the 
remainder of this discussion, we refer to the ``cross-walked'' MS-LTC-
DRGs as one of the 340 MS-LTC-DRGs to which we cross-walked each of the 
399 ``no-volume'' MS-LTC-DRGs.) Then, in general, we assigned the 399 
no-volume MS-LTC-DRGs the relative weight of the cross-walked MS-LTC-
DRG (when necessary, we made adjustments to account for 
nonmonotonicity).
    We cross-walked the no-volume MS-LTC-DRG to a MS-LTC-DRG for which 
we calculated relative weights based on the March 2022 update of the FY 
2021 MedPAR file, and to which it is similar clinically in intensity of 
use of resources and relative costliness as determined by criteria such 
as care provided during the period of time surrounding surgery, 
surgical approach (if applicable), length of time of surgical 
procedure, postoperative care, and length of stay.

[[Page 49160]]

(For more details on our process for evaluating relative costliness, we 
refer readers to the FY 2010 IPPS/RY 2010 LTCH PPS final rule (73 FR 
48543).) We believe in the rare event that there would be a few LTCH 
cases grouped to one of the no-volume MS-LTC-DRGs in FY 2023, the 
relative weights assigned based on the cross-walked MS-LTC-DRGs would 
result in an appropriate LTCH PPS payment because the crosswalks, which 
are based on clinical similarity and relative costliness, would be 
expected to generally require equivalent relative resource use.
    Then we assigned the relative weight of the cross-walked MS-LTC-DRG 
as the relative weight for the no-volume MS-LTC-DRG such that both of 
these MS-LTC-DRGs (that is, the no-volume MS-LTC-DRG and the cross-
walked MS-LTC-DRG) have the same relative weight (and average length of 
stay) for FY 2023. We note that, if the cross-walked MS-LTC-DRG had 25 
applicable LTCH cases or more, its relative weight (calculated using 
the methodology as previously described in Steps 1 through 4) is 
assigned to the no-volume MS-LTC-DRG as well. Similarly, if the MS-LTC-
DRG to which the no-volume MS-LTC-DRG was cross-walked had 24 or less 
cases and, therefore, was designated to 1 of the low-volume quintiles 
for purposes of determining the relative weights, we assigned the 
relative weight of the applicable low-volume quintile to the no-volume 
MS-LTC-DRG such that both of these MS-LTC-DRGs (that is, the no-volume 
MS-LTC-DRG and the cross-walked MS-LTC-DRG) have the same relative 
weight for FY 2023. (As we noted previously, in the infrequent case 
where nonmonotonicity involving a no-volume MS-LTC-DRG resulted, 
additional adjustments are required to maintain monotonically 
increasing relative weights.)
    For this final rule, we are providing the list of the no-volume MS-
LTC-DRGs and the MS-LTC-DRGs to which each was cross-walked (that is, 
the cross-walked MS-LTC-DRGs) for FY 2023 in a supplemental data file 
for public use posted via the internet on the CMS website for this 
final rule at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html to streamline the information made 
available to the public that is used in the annual development of Table 
11.
    To illustrate this methodology for determining the relative weights 
for the FY 2023 MS-LTC-DRGs with no applicable LTCH cases, we are 
providing the following example.
    Example: There were no trimmed applicable LTCH cases in the FY 2021 
MedPAR file that we are using for this final rule for MS-LTC-DRG 061 
(Ischemic stroke, precerebral occlusion or transient ischemia with 
thrombolytic agent with MCC). We determined that MS-LTC-DRG 070 
(Nonspecific cerebrovascular disorders with MCC) is similar clinically 
and based on resource use to MS-LTC-DRG 061. Therefore, we assigned the 
same relative weight (and average length of stay) of MS-LTC-DRG 70 of 
0.837 for FY 2023 to MS-LTC-DRG 061 (we refer readers to Table 11, 
which is listed in section VI. of the Addendum to this final rule and 
is available via the internet on the CMS website).
    Again, we note that, as this system is dynamic, it is entirely 
possible that the number of MS-LTC-DRGs with no volume would vary in 
the future. Consistent with our historical practice, as we proposed, we 
used the best available claims data to identify the trimmed applicable 
LTCH cases from which we determined the relative weights in the final 
rule.
    For FY 2023, consistent with our historical relative weight 
methodology, as we proposed, we are establishing a relative weight of 
0.0000 for the following transplant MS-LTC-DRGs: Heart Transplant or 
Implant of Heart Assist System with MCC (MS-LTC-DRG 001); Heart 
Transplant or Implant of Heart Assist System without MCC (MS-LTC-DRG 
002); Liver Transplant with MCC or Intestinal Transplant (MS-LTC-DRG 
005); Liver Transplant without MCC (MS-LTC-DRG 006); Lung Transplant 
(MS-LTC-DRG 007); Simultaneous Pancreas/Kidney Transplant (MS-LTC-DRG 
008); Simultaneous Pancreas/Kidney Transplant with Hemodialysis (MS-
LTC-DRG 019); Pancreas Transplant (MS-LTC-DRG 010); Kidney Transplant 
(MS-LTC-DRG 652); Kidney Transplant with Hemodialysis with MCC (MS-LTC-
DRG 650), and Kidney Transplant with Hemodialysis without MCC (MS LTC 
DRG 651). This is because Medicare only covers these procedures if they 
are performed at a hospital that has been certified for the specific 
procedures by Medicare and presently no LTCH has been so certified. At 
the present time, we include these 11 transplant MS-LTC-DRGs in the 
GROUPER program for administrative purposes only. Because we use the 
same GROUPER program for LTCHs as is used under the IPPS, removing 
these MS-LTC-DRGs would be administratively burdensome. (For additional 
information regarding our treatment of transplant MS-LTC-DRGs, we refer 
readers to the RY 2010 LTCH PPS final rule (74 FR 43964).) In addition, 
consistent with our historical policy, we are establishing a relative 
weight of 0.0000 for the 2 ``error'' MS-LTC-DRGs (that is, MS-LTC-DRG 
998 (Principal Diagnosis Invalid as Discharge Diagnosis) and MS-LTC-DRG 
999 (Ungroupable)) because applicable LTCH cases grouped to these MS-
LTC-DRGs cannot be properly assigned to an MS-LTC-DRG according to the 
grouping logic.
    Additionally, we are establishing a relative weight of 0.0000 for 
the following ``psychiatric or rehabilitation'' MS-LTC-DRGs: MS-LTC-DRG 
876 (O.R. Procedure with Principal Diagnoses of Mental Illness); MS-
LTC-DRG 880 (Acute Adjustment Reaction & Psychosocial Dysfunction); MS-
LTC-DRG 881 (Depressive Neuroses); MS-LTC-DRG 882 (Neuroses Except 
Depressive); MS-LTC-DRG 883 (Disorders of Personality & Impulse 
Control); MS-LTC-DRG 884 (Organic Disturbances & Mental Retardation); 
MS-LTC-DRG 885 (Psychoses); MS-LTC-DRG 886 (Behavioral & Developmental 
Disorders); MS-LTC-DRG 887 (Other Mental Disorder Diagnoses); MS-LTC-
DRG 894 (Alcohol/Drug Abuse or Dependence, Left Ama); MS-LTC-DRG 895 
(Alcohol/Drug Abuse or Dependence, with Rehabilitation Therapy); MS-
LTC-DRG 896 (Alcohol/Drug Abuse or Dependence, without Rehabilitation 
Therapy with MCC); MS-LTC-DRG 897 (Alcohol/Drug Abuse or Dependence, 
without Rehabilitation Therapy without MCC); MS-LTC-DRG 945 
(Rehabilitation with CC/MCC); and MS-LTC-DRG 946 (Rehabilitation 
without CC/MCC). We are establishing a relative weight 0.0000 for these 
15 ``psychiatric or rehabilitation'' MS-LTC-DRGs because the blended 
payment rate and temporary exceptions to the site neutral payment rate 
would not be applicable for any LTCH discharges occurring in FY 2023, 
and as such payment under the LTCH PPS would be no longer be made in 
part based on the LTCH PPS standard Federal payment rate for any 
discharges assigned to those MS-LTC-DRGs.
    Step 9--Normalize the two sets of relative weights.
    The next step in our calculation of the FY 2023 MS-LTC-DRG relative 
weights is to normalize the set of relative weights that were 
calculated using claims that include COVID-19 cases and to normalize 
the set of relative weights that were calculated using claims that 
excluded COVID-19 cases. The normalization adjustment is intended to 
ensure that the recalibration of the MS-

[[Page 49161]]

LTC-DRG relative weights (that is, the process itself) neither 
increases nor decreases the average case-mix index. To calculate the 
normalization factors, we grouped applicable LTCH cases from each set 
of claims using the FY 2023 Version 40 GROUPER, and used the FY 2023 
MS-LTC-DRG relative weights associated with each set to calculate the 
average case-mix index (CMI) for each set; we grouped the same 
applicable LTCH cases from each set of claims using the FY 2022 GROUPER 
Version 39 and MS-LTC-DRG relative weights and calculated the average 
CMI for each set; and computed the ratio by dividing the average CMI 
for each set for FY 2022 by the average CMI for each set for FY 2023. 
These ratios are the normalization factors that were applied to each 
respective set of unnormalized weights. Because the calculation of the 
normalization factor involves the relative weights for the MS-LTC-DRGs 
that contained applicable LTCH cases to calculate the average CMIs, any 
low-volume MS-LTC-DRGs are included in the calculation (and the MS-LTC-
DRGs with no applicable LTCH cases are not included in the 
calculation). The table displays the normalization factors that were 
calculated and applied for each set of relative weights.
[GRAPHIC] [TIFF OMITTED] TR10AU22.154

    Step 10--Average the two sets of normalized relative weights.
    After each set of relative weights was normalized, we computed a 
simple average of the normalized relative weights and geometric mean 
length of stays from each set, by using 50 percent of the relative 
weights calculated using applicable LTCH cases that include COVID-19 
cases and 50 percent of the relative weights calculated using 
applicable LTCH cases that exclude COVID-19 cases.
    Step 11-- Budget neutralize the averaged relative weights.
    In accordance with the regulations at Sec.  412.517(b) (in 
conjunction with Sec.  412.503), the annual update to the MS-LTC-DRG 
classifications and relative weights is done in a budget neutral manner 
such that estimated aggregate LTCH PPS payments would be unaffected, 
that is, would be neither greater than nor less than the estimated 
aggregate LTCH PPS payments that would have been made without the MS-
LTC-DRG classification and relative weight changes. (For a detailed 
discussion on the establishment of the budget neutrality requirement 
for the annual update of the MS-LTC-DRG classifications and relative 
weights, we refer readers to the RY 2008 LTCH PPS final rule (72 FR 
26881 and 26882).
    To achieve budget neutrality under the requirement at Sec.  
412.517(b), under our established methodology, for each annual update 
the MS-LTC-DRG relative weights are uniformly adjusted to ensure that 
estimated aggregate payments under the LTCH PPS would not be affected 
(that is, decreased or increased). Consistent with that provision, as 
we proposed, we continued to apply budget neutrality adjustments in 
determining the FY 2023 MS-LTC-DRG relative weights so that our update 
the MS-LTC-DRG classifications and relative weights for FY 2023 are 
made in a budget neutral manner. In addition, as discussed in section 
VIII.B.3.b. of the preamble to this final rule, we are finalizing our 
proposal that the 10-percent cap on the reduction in a MS-LTC-DRG's 
relative weight in a given year be budget neutral. Therefore, for FY 
2023, we are applying two budget neutrality factors to determine the 
MS-LTC-DRG relative weights. In this step, we describe the 
determination of the budget neutrality adjustment that accounts for the 
update of the MS-LTC-DRG classifications and relative weights prior to 
the application of the 10-percent cap. In steps 12 and 13, we describe 
the application of the 10-percent cap policy (step 12) and the 
determination of the budget neutrality factor that accounts for the 
application of the 10-percent cap policy (step 13).
    As described previously, the relative weights constructed up to 
this point in our methodology were calculated based on two different 
set of claims (the applicable LTCH cases that included COVID-19 cases 
and the applicable LTCH cases that excluded COVID-19 cases) and then 
averaged together. However, in the FY 2023 IPPS/LTCH PPS proposed rule 
(87 FR 28475), when modeling payments for determining the budget 
neutrality factors, we proposed to use the set of LTCH cases that 
include COVID-19 cases. In the absence of a set of MedPAR claims that 
reflect our expectation that there will be fewer (but not zero) COVID-
19 cases in FY 2023 as compared to the COVID-19 cases in the FY 2021 
claims data, we stated our belief that this is the best data available 
for determining the budget neutrality factors. We solicited feedback 
from commenters on alternative ways to use the FY 2021 claims data for 
purposes of calculating the FY 2023 budget neutrality factors. We 
received no comments on this proposal and are finalizing this proposal 
without modification. Therefore, for this final rule, when modeling 
payments for determining the budget neutrality factors we used the set 
of LTCH cases that include COVID-19 cases.
    In this final rule, to ensure budget neutrality for the update to 
the MS-LTC-DRG classifications and relative weights prior to the 
application of the 10-percent cap (that is, uncapped relative weights), 
under Sec.  412.517(b), we continued to use our established two-step 
budget neutrality methodology. Therefore, in the first step of our MS-
LTC-DRG update budget neutrality methodology, for FY 2023, we 
calculated and applied a normalization factor to the recalibrated 
relative weights (the result of Steps 1 through 10 discussed 
previously) to ensure that estimated payments are not affected by 
changes in the composition of case types or the changes to the 
classification system. That is, the normalization adjustment is 
intended to ensure that the recalibration of the MS-LTC-DRG relative 
weights (that is, the process itself) neither increases nor decreases 
the average case-mix index.
    To calculate the normalization factor for FY 2023, we used the 
following three steps: (1.a.) use the applicable LTCH cases from the 
best available data (that is, LTCH discharges from the FY 2021 MedPAR 
file, including the COVID-19 cases as discussed previously) and group 
them using the FY 2023 GROUPER (that is, Version 40 for FY 2023) and 
the recalibrated FY 2023 MS-LTC-DRG uncapped relative weights 
(determined in Steps 1 through 10 discussed previously) to calculate 
the average case-mix index; (1.b.) group the same applicable LTCH cases 
(as are used in Step 1.a.) using the FY 2022 GROUPER (Version 39) and 
FY 2022 MS-LTC-DRG relative weights and calculate the average case-mix 
index; and (1.c.) compute the ratio of these average case-mix indexes 
by dividing the average case-mix index for FY 2022 (determined in Step 
1.b.) by the average

[[Page 49162]]

case-mix index for FY 2023 (determined in Step 1.a.). As a result, in 
determining the MS-LTC-DRG relative weights for FY 2023, each 
recalibrated MS-LTC-DRG uncapped relative weight was multiplied by the 
normalization factor of 0.99884 (determined in Step 1.c.) in the first 
step of the budget neutrality methodology, which produces ``normalized 
relative weights.''
    In the second step of our MS-LTC-DRG update budget neutrality 
methodology, we calculated a budget neutrality adjustment factor 
consisting of the ratio of estimated aggregate FY 2023 LTCH PPS 
standard Federal payment rate payments for applicable LTCH cases (the 
sum of all calculations under Step 1.b. stated previously) before 
reclassification and recalibration to estimated aggregate payments for 
FY 2023 LTCH PPS standard Federal payment rate payments for applicable 
LTCH cases after reclassification and recalibration (that is, the sum 
of all calculations under Step 1.a. stated previously).
    That is, for this final rule, for FY 2023, we determined the budget 
neutrality adjustment factor using the following three steps: (2.a.) 
simulate estimated total FY 2023 LTCH PPS standard Federal payment rate 
payments for applicable LTCH cases using the uncapped normalized 
relative weights for FY 2023 and GROUPER Version 40 (as described 
previously); (2.b.) simulate estimated total FY 2023 LTCH PPS standard 
Federal payment rate payments for applicable LTCH cases using the FY 
2022 GROUPER (Version 39) and the FY 2022 MS-LTC-DRG relative weights 
in Table 11 of the FY 2022 IPPS/LTCH PPS final rule; and (2.c.) 
calculate the ratio of these estimated total payments by dividing the 
value determined in Step 2.b. by the value determined in Step 2.a. In 
determining the FY 2023 MS-LTC-DRG relative weights, each uncapped 
normalized relative weight was then multiplied by a budget neutrality 
factor of 0.9937739 (the value determined in Step 2.c.) in the second 
step of the budget neutrality methodology.
    Step 12--Apply the 10-percent cap to decreases in MS-LTC-DRG 
relative weights.
    As discussed in section VIII.B.3.b. of the preamble to this final 
rule, we are establishing a 10-percent cap on the reduction in a MS-
LTC-DRG's relative weight in a given year, beginning in FY 2023. 
Specifically, in cases where the relative weight for a MS-LTC-DRG would 
decrease by more than 10-percent in a given year, we are limiting the 
reduction to 10-percent for that year. Under this provision, this 10-
percent cap will only be applied to the relative weights for MS-LTC-
DRGs with 25 or more applicable LTCH cases and will not be applied to 
the low-volume MS-LTC-DRGs identified in Step 3 or the no-volume MS-
LTC-DRGs identified in Step 8. Therefore, in this step, for each FY 
2023 MS-LTC-DRG with 25 or more applicable LTCH cases (excludes low-
volume and zero-volume MS-LTC-DRGs) we compared its FY 2023 relative 
weight (after application of the normalization and budget neutrality 
factors determined in Step 11), to its FY 2022 MS-LTC-DRG relative 
weight. For any MS-LTC-DRG where the FY 2023 relative weight would 
otherwise have declined more than 10 percent, we established a capped 
FY 2023 MS-LTC-DRG relative weight that would be equal to 90 percent of 
that MS-LTC-DRG's FY 2022 relative weight (that is, we set the FY 2023 
relative weight equal to the FY 2022 weight x 0.90).
    Step 13--Calculate the MS-LTC-DRG cap budget neutrality factor.
    As discussed in section VIII.B.3.b. of the preamble to this final 
rule, we also are applying a budget neutrality adjustment to the MS-
LTC-DRG relative weights so that the 10-percent cap on relative weight 
reductions is implemented in a budget neutral manner. Therefore, we are 
determining the budget neutrality adjustment factor for our 10-percent 
cap on relative weight reductions using the following three steps: (a) 
simulate estimated total FY 2023 LTCH PPS standard Federal payment rate 
payments for applicable LTCH cases using the capped relative weights 
for FY 2023 (determined in Step 12) and GROUPER Version 40; (b) 
simulate estimated total FY 2023 LTCH PPS standard Federal payment rate 
payments for applicable LTCH cases using the uncapped relative weights 
for FY 2023 (determined in Step 11) and GROUPER Version 40; and (c) 
calculate the ratio of these estimated total payments by dividing the 
value determined in step (b) by the value determined in step (a). In 
determining the FY 2023 MS-LTC-DRG relative weights, each capped 
relative weight was then multiplied by a budget neutrality factor of 
0.998734 (the value determined in step (c)) to achieve the budget 
neutrality requirement.
    Table 11, which is listed in section VI. of the Addendum to this 
final rule and is available via the internet on the CMS website, lists 
the MS-LTC-DRGs and their respective relative weights, geometric mean 
length of stay, and five-sixths of the geometric mean length of stay 
(used to identify SSO cases under Sec.  412.529(a)) for FY 2023. We 
also are making available on our website the two sets of relative 
weights that were averaged together in determining the FY 2023 MS-LTC-
DRG relative weights. That is, the set of relative weights based on 
applicable LTCH cases that included COVID-19 cases and the set of 
relative weights based on applicable LTCH cases that excluded COVID-19 
cases. We also are making available on the website the MS-LTC-DRG 
relative weights prior to the application of the 10-percent cap on MS-
LTC-DRG relative weight reductions and corresponding cap budget 
neutrality factor.

C. Changes to the LTCH PPS Payment Rates and Other Changes to the LTCH 
PPS for FY 2023

1. Overview of Development of the LTCH PPS Standard Federal Payment 
Rates
    The basic methodology for determining LTCH PPS standard Federal 
payment rates is currently set forth at 42 CFR 412.515 through 412.533 
and 412.535. In this section of the final rule, we discuss the factors 
that we used to update the LTCH PPS standard Federal payment rate for 
FY 2023, that is, effective for LTCH discharges occurring on or after 
October 1, 2022 through September 30, 2023. Under the dual rate LTCH 
PPS payment structure required by statute, beginning with discharges in 
cost reporting periods beginning in FY 2016, only LTCH discharges that 
meet the criteria for exclusion from the site neutral payment rate are 
paid based on the LTCH PPS standard Federal payment rate specified at 
42 CFR 412.523. (For additional details on our finalized policies 
related to the dual rate LTCH PPS payment structure required by 
statute, we refer readers to the FY 2016 IPPS/LTCH PPS final rule (80 
FR 49601 through 49623).)
    Prior to the implementation of the dual payment rate system in FY 
2016, all LTCH discharges were paid similarly to those now exempt from 
the site neutral payment rate. That legacy payment rate was called the 
standard Federal rate. For details on the development of the initial 
standard Federal rate for FY 2003, we refer readers to the August 30, 
2002 LTCH PPS final rule (67 FR 56027 through 56037). For subsequent 
updates to the standard Federal rate from FYs 2003 through 2015, and 
LTCH PPS standard Federal payment rate from FY 2016 through present, as 
implemented under 42 CFR 412.523(c)(3), we refer readers to the FY 2020 
IPPS/LTCH PPS final rule (84 FR 42445 through 42446).
    In this FY 2023 IPPS/LTCH PPS final rule, we present our policies 
related to the annual update to the LTCH PPS

[[Page 49163]]

standard Federal payment rate for FY 2023.
    The update to the LTCH PPS standard Federal payment rate for FY 
2023 is presented in section V.A. of the Addendum to this final rule. 
The components of the annual update to the LTCH PPS standard Federal 
payment rate for FY 2023 are discussed in this section of the final 
rule, including the statutory reduction to the annual update for LTCHs 
that fail to submit quality reporting data for FY 2023 as required by 
the statute (as discussed in section VIII.C.2.c. of the preamble of 
this final rule). As we proposed in the FY 2023 IPPS/LTCH PPS proposed 
rule (87 FR 28476), we also made an adjustment to the LTCH PPS standard 
Federal payment rate to account for the estimated effect of the changes 
to the area wage level for FY 2023 on estimated aggregate LTCH PPS 
payments, in accordance with 42 CFR 412.523(d)(4) (as discussed in 
section V.B. of the Addendum to this final rule).
2. FY 2023 LTCH PPS Standard Federal Payment Rate Annual Market Basket 
Update
a. Overview
    Historically, the Medicare program has used a market basket to 
account for input price increases in the services furnished by 
providers. The market basket used for the LTCH PPS includes both 
operating and capital-related costs of LTCHs because the LTCH PPS uses 
a single payment rate for both operating and capital-related costs. We 
adopted the 2017-based LTCH market basket for use under the LTCH PPS 
beginning in FY 2021 (85 FR 58907 through 58909). For additional 
details on the historical development of the market basket used under 
the LTCH PPS, we refer readers to the FY 2013 IPPS/LTCH PPS final rule 
(77 FR 53467 through 53476), and for a complete discussion of the LTCH 
market basket and a description of the methodologies used to determine 
the operating and capital-related portions of the 2017-based LTCH 
market basket, we refer readers to the FY 2021 IPPS/LTCH PPS final rule 
(85 FR 58909 through 58926).
    Section 3401(c) of the Affordable Care Act provides for certain 
adjustments to any annual update to the LTCH PPS standard Federal 
payment rate and refers to the timeframes associated with such 
adjustments as a ``rate year.'' We note that, because the annual update 
to the LTCH PPS policies, rates, and factors now occurs on October 1, 
we adopted the term ``fiscal year'' (FY) rather than ``rate year'' (RY) 
under the LTCH PPS beginning October 1, 2010, to conform with the 
standard definition of the Federal fiscal year (October 1 through 
September 30) used by other PPSs, such as the IPPS (75 FR 50396 through 
50397). Although the language of sections 3004(a), 3401(c), 10319, and 
1105(b) of the Affordable Care Act refers to years 2010 and thereafter 
under the LTCH PPS as ``rate year,'' consistent with our change in the 
terminology used under the LTCH PPS from ``rate year'' to ``fiscal 
year,'' for purposes of clarity, when discussing the annual update for 
the LTCH PPS standard Federal payment rate, including the provisions of 
the Affordable Care Act, we use ``fiscal year'' rather than ``rate 
year'' for 2011 and subsequent years.
b. Annual Update to the LTCH PPS Standard Federal Payment Rate for FY 
2023
    As previously noted, we adopted the 2017-based LTCH market basket 
for use under the LTCH PPS beginning in FY 2021. The 2017-based LTCH 
market basket is primarily based on the Medicare cost report data 
submitted by LTCHs and, therefore, specifically reflects the cost 
structures of only LTCHs. (For additional details on the development of 
the 2017-based LTCH market basket, we refer readers to the FY 2021 
IPPS/LTCH PPS final rule (85 FR 58909 through 58926).) We continue to 
believe that the 2017-based LTCH market basket appropriately reflects 
the cost structure of LTCHs for the reasons discussed when we adopted 
its use in the FY 2021 IPPS/LTCH PPS final rule. Therefore, in this 
final rule, as we proposed in the FY 2023 IPPS/LTCH PPS proposed rule 
(87 FR 28476), we used the 2017-based LTCH market basket to update the 
LTCH PPS standard Federal payment rate for FY 2023.
    Section 1886(m)(3)(A) of the Act provides that, beginning in FY 
2010, any annual update to the LTCH PPS standard Federal payment rate 
is reduced by the adjustments specified in clauses (i) and (ii) of 
subparagraph (A), as applicable. Clause (i) of section 1886(m)(3)(A) of 
the Act provides for a reduction, for FY 2012 and each subsequent rate 
year, by ``the productivity adjustment'' described in section 
1886(b)(3)(B)(xi)(II) of the Act. Clause (ii) of section 1886(m)(3)(A) 
of the Act provided for a reduction, for each of FYs 2010 through 2019, 
by the ``other adjustment'' described in section 1886(m)(4)(F) of the 
Act; therefore, it is not applicable for FY 2023.
    Section 1886(m)(3)(B) of the Act provides that the application of 
paragraph (3) of section 1886(m) of the Act may result in the annual 
update being less than zero for a rate year, and may result in payment 
rates for a rate year being less than such payment rates for the 
preceding rate year.
c. Adjustment to the LTCH PPS Standard Federal Payment Rate Under the 
Long-Term Care Hospital Quality Reporting Program (LTCH QRP)
    In accordance with section 1886(m)(5) of the Act, the Secretary 
established the Long-Term Care Hospital Quality Reporting Program (LTCH 
QRP). The reduction in the annual update to the LTCH PPS standard 
Federal payment rate for failure to report quality data under the LTCH 
QRP for FY 2014 and subsequent fiscal years is codified under 42 CFR 
412.523(c)(4). The LTCH QRP, as required for FY 2014 and subsequent 
fiscal years by section 1886(m)(5)(A)(i) of the Act, applies a 2.0 
percentage points reduction to any update under 42 CFR 412.523(c)(3) 
for an LTCH that does not submit quality reporting data to the 
Secretary in accordance with section 1886(m)(5)(C) of the Act with 
respect to such a year (that is, in the form and manner and at the time 
specified by the Secretary under the LTCH QRP) (42 CFR 
412.523(c)(4)(i)). Section 1886(m)(5)(A)(ii) of the Act provides that 
the application of the 2.0 percentage points reduction may result in an 
annual update that is less than 0.0 for a year, and may result in LTCH 
PPS payment rates for a year being less than such LTCH PPS payment 
rates for the preceding year. Furthermore, section 1886(m)(5)(B) of the 
Act specifies that the 2.0 percentage points reduction is applied in a 
noncumulative manner, such that any reduction made under section 
1886(m)(5)(A) of the Act shall apply only with respect to the year 
involved, and shall not be taken into account in computing the LTCH PPS 
payment amount for a subsequent year. These requirements are codified 
in the regulations at 42 CFR 412.523(c)(4). (For additional information 
on the history of the LTCH QRP, including the statutory authority and 
the selected measures, we refer readers to section VIII.C. of the 
preamble of this final rule.)
d. Annual Market Basket Update Under the LTCH PPS for FY 2023
    Consistent with our historical practice, we estimate the market 
basket increase and the productivity adjustment based on IGI's forecast 
using more recent available data. Based on IGI's fourth quarter 2021 
forecast, the proposed FY 2023 market basket update for the LTCH PPS 
using the 2017-based LTCH market basket was 3.1 percent. The proposed 
productivity adjustment for FY 2023 based on IGI's fourth quarter 2021 
forecast was 0.4 percent.

[[Page 49164]]

For FY 2023, section 1886(m)(3)(A)(i) of the Act requires that any 
annual update to the LTCH PPS standard Federal payment rate be reduced 
by the productivity adjustment, described in section 
1886(b)(3)(B)(xi)(II) of the Act. Consistent with the statute, we 
proposed in the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28477), to 
reduce the FY 2023 market basket increase by the FY 2023 productivity 
adjustment. To determine the proposed market basket increase for LTCHs 
for FY 2023, as reduced by the proposed productivity adjustment, 
consistent with our established methodology, we subtracted the proposed 
FY 2023 productivity adjustment from the FY 2023 market basket 
increase. (For additional details on our established methodology for 
adjusting the market basket increase by the productivity adjustment, we 
refer readers to the FY 2012 IPPS/LTCH PPS final rule (76 FR 51771).)
    For FY 2023, section 1886(m)(5) of the Act requires that, for LTCHs 
that do not submit quality reporting data as required under the LTCH 
QRP, any annual update to an LTCH PPS standard Federal payment rate, 
after application of the adjustments required by section 1886(m)(3) of 
the Act, shall be further reduced by 2.0 percentage points. Therefore, 
for LTCHs that fail to submit quality reporting data under the LTCH 
QRP, the proposed 3.1 percent market basket update to the LTCH PPS 
standard Federal payment rate for FY 2023 would be reduced by the 0.4 
percentage point productivity adjustment as required under section 
1886(m)(3)(A)(i) of the Act and by the additional 2.0 percentage points 
reduction required by section 1886(m)(5) of the Act.
    In the FY 2023 IPPS/LTCH PPS proposed rule, in accordance with the 
statute, we proposed to reduce the proposed FY 2023 market basket 
update of 3.1 percent (based on IGI's fourth quarter 2021 forecast of 
the 2017-based LTCH market basket) by the proposed FY 2023 productivity 
adjustment of 0.4 percentage point (based on IGI's fourth quarter 2021 
forecast). Therefore, under the authority of section 123 of the BBRA as 
amended by section 307(b) of the BIPA, consistent with 42 CFR 
412.523(c)(3)(xvii), we proposed to establish an annual market basket 
update to the LTCH PPS standard Federal payment rate for FY 2023 of 2.7 
percent (that is, more recent estimate of the LTCH PPS market basket 
increase of 3.1 percent less the productivity adjustment of 0.4 
percentage point). For LTCHs that fail to submit quality reporting data 
under the LTCH QRP, under 42 CFR 412.523(c)(3)(xvii) in conjunction 
with 42 CFR 412.523(c)(4), we proposed to further reduce the annual 
update to the LTCH PPS standard Federal payment rate by 2.0 percentage 
points, in accordance with section 1886(m)(5) of the Act. Accordingly, 
we proposed to establish an annual update to the LTCH PPS standard 
Federal payment rate of 0.7 percent (that is, 2.7 percent minus 2.0 
percentage points) for FY 2023 for LTCHs that fail to submit quality 
reporting data as required under the LTCH QRP. Consistent with our 
historical practice, we proposed in the FY 2023 IPPS/LTCH PPS proposed 
rule (86 FR 28477) to use a more recent estimate of the market basket 
and the productivity adjustment, if appropriate, in the final rule to 
establish an annual update to the LTCH PPS standard Federal payment 
rate for FY 2023. We note that, consistent with historical practice, we 
also proposed to adjust the FY 2023 LTCH PPS standard Federal payment 
rate by an area wage level budget neutrality factor in accordance with 
42 CFR 412.523(d)(4) (as discussed in section V.B.5. of the Addendum to 
the proposed rule).
    Comment: A number of commenters expressed concern that the proposed 
2017-based LTCH market basket growth rate of 3.1 percent was inadequate 
and did not reflect current inflationary trends. These commenters cited 
several reasons why they believe the proposed market basket was 
underestimated, including significant rises in hospital labor costs 
(especially contract nursing costs), as well as rises in other hospital 
costs (such as equipment and supplies). Several commenters cited recent 
growth in the Bureau of Labor Statistics (BLS) Consumer Price Index 
(CPI) as evidence of the inflationary pressures inflicted upon 
hospitals.
    Several commenters expressed that, since the market basket is a 
time-lagged estimate that uses historical data to forecast into the 
future, it is most suitable for forecasting changes in a steady-state 
economy with small and stable changes in inflation and costs. However, 
these commenters believe the current inflationary environment is not a 
typical economic environment and therefore the resulting market basket 
estimates are inadequate. A commenter stated that the construction of 
the market basket itself does not allow it to fully capture unexpected 
shocks because it is a time-lagged rolling average estimate.
    Commenters requested CMS to ensure that the market basket and 
update factor reflect the actual experiences of LTCHs and be modified 
accordingly. Several commenters urged CMS to identify more accurate and 
up-to-date data inputs to calculate a market basket update that better 
represents the inflationary pressures that hospitals are facing.
    Response: CMS has historically used a market basket to account for 
input price increases in the services furnished by fee-for-service 
providers. The market basket used for the LTCH PPS includes both 
operating and capital-related costs of LTCHs because the LTCH PPS uses 
a single payment rate for both operating and capital-related costs. We 
adopted the 2017-based LTCH market basket for use under the LTCH PPS 
beginning in FY 2021 (85 FR 58907 through 58909). We believe the 2017-
based LTCH market basket increase adequately reflects the average 
change in the price of goods and services hospitals purchase in order 
to provide LTCH medical services, and is appropriate to use as the 
market basket percentage increase. As described in the FY 2021 final 
rule (86 FR 45194 through 45213), the LTCH market basket is a fixed-
weight, Laspeyres-type index that measures price changes over time and 
would not reflect increases in costs associated with changes in the 
volume or intensity of input goods and services. As such, the LTCH 
market basket increase would reflect the prospective price pressures 
described by the commenters as increasing during a high inflation 
period (such as faster wage price growth or higher energy prices), but 
would inherently not reflect other factors that might increase the 
level of costs, such as the quantity of labor used or any shifts 
between contract and staff nurses. We note that cost changes (that is, 
the product of price and quantities) would only be captured in the 
market basket weights when the index is rebased and the base year is 
updated to a more recent time period. Comments requesting that CMS 
rebase the LTCH market basket and our response are discussed later in 
this section.
    We agree with the commenters that recent higher inflationary trends 
have impacted the outlook for price growth over the next several 
quarters. At the time of the FY 2023 IPPS/LTCH proposed rule, based on 
IGI's fourth quarter 2021 forecast with historical data through the 
third quarter of 2021, IGI forecasted the 2017-based LTCH market basket 
update of 3.1 percent for FY 2023 reflecting forecasted compensation 
prices of 3.9 percent (by comparison, compensation price growth in the 
2017-based LTCH market basket averaged 2.1 percent from 2012-2021). In 
the FY 2023 IPPS/LTCH proposed rule, we proposed that if more recent 
data became available, we would use such data, if appropriate, to 
derive the final FY 2023 LTCH market basket

[[Page 49165]]

update for the final rule. For this final rule, we now have an updated 
forecast of the price proxies underlying the market basket that 
incorporates more recent historical data and reflects a revised outlook 
regarding the U.S. economy (including the more recent historical CPI 
growth, impacts of the Russia/Ukraine war, current expectations 
regarding changes to Federal Reserve interest rates, and tight labor 
markets). Based on IGI's second quarter 2022 forecast with historical 
data through the first quarter of 2022, we are projecting a FY 2023 
LTCH market basket update of 4.1 percent (reflecting forecasted 
compensation price growth of 4.8 percent) and productivity adjustment 
of 0.3 percentage point. Therefore, for FY 2023, we are finalizing an 
LTCH update of 3.8 percent (4.1 percent less 0.3 percentage point), 
compared to 2.7 percent that we had proposed. We note that the final FY 
2023 LTCH market basket growth rate of 4.1 percent would be the highest 
market basket update implemented in an IPPS/LTCH final rule going back 
to RY 2004.
    Comment: Some commenters maintained that, in consideration of 
rapidly increasing labor costs, it would be appropriate for CMS to 
implement a temporary payment adjustment increase or add-on payment to 
LTCH payments for FY 2023. The commenters stated their belief that CMS 
has the authority to determine appropriate adjustments to the LTCH PPS 
under section 123 of the BBRA as amended by section 307(b)(1) of the 
BIPA. A commenter requested that such a payment adjustment continue to 
be applied until CMS rebases the LTCH PPS market basket.
    Response: We disagree with the commenters that CMS should apply a 
temporary payment adjustment or add-on payment to the LTCH PPS to 
account for the increases in labor costs at LTCHs that they believe 
were not being captured in the market basket. As discussed earlier, we 
believe the LTCH market basket increase appropriately reflects the 
input price growth (including compensation price growth) that LTCHs 
incur in providing medical services. As also described earlier, we are 
using an updated forecast of the price proxies underlying the market 
basket that incorporates more recent historical data and reflects a 
revised outlook regarding the U.S. economy (including the more recent 
historical CPI growth, impacts of the Russia/Ukraine war, current 
expectations regarding changes to Federal Reserve interest rates, and 
tight labor markets). As a result, the update for FY 2023 of 3.8 
percent is 1.1 percentage points higher than the proposed update of 2.7 
percent.
    Comment: Several commenters requested that CMS apply a 
retrospective payment adjustment that accounts for the difference 
between the 2.6 percent market basket increase that was implemented in 
FY 2022 and what the market basket is currently projected to be for FY 
2022. Several commenters stated that the FY 2022 market basket increase 
that was used to determine the annual update did not capture 
significant increases in labor expenses that occurred in FY 2022.
    Response: Under the law, the LTCH PPS is a per-discharge 
prospective payment system that uses a market basket increase to set 
the annual update prospectively. This means that the update relies on a 
mix of both historical data for part of the period for which the update 
is calculated and forecasted data for the remainder. For instance, the 
2017-based LTCH market basket growth rate for FY 2023 in this final 
rule is based on IGI's second quarter 2022 forecast with historical 
data through the first quarter of 2022. While there is currently no 
mechanism to adjust for market basket forecast error in the LTCH 
payment update, the forecast error for a market basket update is equal 
to the actual market basket increase for a given year less the 
forecasted market basket increase. Due to the uncertainty regarding 
future price trends, forecast errors can be both positive and negative. 
We note that FY 2022 historical data are not yet available to calculate 
a forecast error for FY 2022. For this final rule, we have incorporated 
more recent historical data and forecasts to capture the price and wage 
pressures facing LTCHs and believe the market basket increase that we 
are finalizing is the best available projection of inflation to 
determine the applicable percentage increase for the LTCH payments in 
FY 2023. For these reasons we are not adopting the commenters' 
suggestion to adjust for the difference between the currently projected 
market basket increase for FY 2022 and the forecasted market basket 
increase used in determining the FY 2022 update.
    Comment: We received numerous comments about our proposed 
productivity adjustment to the FY 2023 LTCH market basket update. 
Commenters generally stated that a negative productivity adjustment is 
inappropriate because evidence suggests that productivity for LTCHs has 
decreased, rather than increased over the past year. Commenters 
requested CMS to use its existing statutory authority to remove the 
productivity adjustment for FY 2023. A commenter requested that we 
remove the productivity adjustment for FY 2023, and any fiscal year 
during which the PHE for COVID-19 was in effect.
    A subset of these commenters also requested that CMS reconsider the 
appropriateness of the productivity adjustment to LTCHs more broadly. 
They stated that the productivity adjustment, based on a 10-year moving 
average of changes in the annual economy-wide private nonfarm business 
total factor productivity, is not representative of the cost structure 
of LTCHs. These commenters expressed concern that hospital work is 
extremely dependent on human capital and that increased operational 
efficiencies are relatively limited for LTCHs compared with industries 
that are able to produce greater efficiencies through automation. 
Commenters specifically cited evidence for why they believe it is 
unrealistic for hospitals to achieve the same productivity gains as the 
private nonfarm business sector in FY 2023. For example, a commenter 
cited the significant decrease in hospital employment levels that have 
occurred during the pandemic and the resulting reliance on contract 
staffing firms to address staffing shortages as a reason why they 
believe hospitals are experiencing declines in productivity during the 
pandemic.
    Response: Section 1886(m)(3)(A)(i) of the Act requires that any 
annual update to the LTCH PPS standard Federal payment rate be reduced 
by the productivity adjustment, described in section 1886(b)(3)(B)(xi) 
of the Act; therefore, we do not have the authority to eliminate the 
productivity adjustment. In section V.A.1. of this preamble, in 
response to similar comments, we explained that we do not believe it is 
appropriate to eliminate the productivity adjustment for FY 2023 in 
this final rule. In that same section, we discuss the methodology for 
calculating and applying the productivity adjustment required by 
section 1886(b)(3)(B)(xi) of the Act that we finalized in the FY 2012 
IPPS/LTCH PPS final rule (76 FR 51689 through 51692). As we explained 
in that rule, section 1886(b)(3)(B)(xi)(II) of the Act defines this 
productivity adjustment as equal to the 10-year moving average of 
changes in annual economy-wide, private nonfarm business multi-factor 
productivity (as projected by the Secretary for the 10-year period 
ending with the applicable fiscal year, year, cost reporting period, or 
other annual period) and BLS publishes the official measures of private 
nonfarm business productivity for the U.S. economy. (We note, beginning 
with the November 18,

[[Page 49166]]

2021 release of productivity data, BLS replaced the term multifactor 
productivity (MFP) with total factor productivity (TFP), and beginning 
with the FY 2022 IPPS/LTCH PPS final rule, we refer to this adjustment 
as the productivity adjustment rather than the MFP adjustment. The 
adjustment continues to rely on the same underlying data and 
methodology.)
    For the FY 2023 IPPS/LTCH proposed rule, based on IGI's fourth 
quarter 2021 forecast, the productivity adjustment was projected to be 
0.4 percentage point for FY 2023. For this final rule, based on IGI's 
second quarter 2022 forecast, we are updating the productivity 
adjustment to reflect more recent historical data as published by BLS 
as well as a revised economic outlook for FY 2022 and FY 2023. Using 
this more recent forecast, the FY 2023 productivity adjustment based on 
the 10-year moving average growth in economy-wide total factor 
productivity for the period ending FY 2023 is 0.3 percent.
    Comment: Several commenters requested that CMS rebase and revise 
the 2017-based LTCH market basket for FY 2023 using the most recent 
LTCH data on labor costs in order for the FY 2023 market basket 
estimate to accurately reflect recent inflationary trends. A commenter 
stated that the unprecedented COVID-19 pandemic has drastically changed 
hospital operations and the costs associated with operating a hospital. 
This commenter also stated its view that the market basket update that 
CMS applies each year is simply unable to account for many of the 
changes to hospital operations and costs since the pandemic.
    Response: As described previously, the LTCH market basket measures 
price changes (including changes in the prices for wages and salaries) 
over time and would not reflect increases in costs associated with 
changes in the volume or intensity of input goods and services until 
the market basket is rebased. The LTCH market basket was last rebased 
in the FY 2021 IPPS/LTCH PPS final rule using 2017 Medicare cost 
reports (85 FR 58909 through 58926), the most recent year of complete 
data available at the time of the rebasing. We note that we did not 
propose to rebase the LTCH market basket in the FY 2023 IPPS/LTCH 
proposed rule; however, we did review the most recent Medicare cost 
report data available for LTCHs submitted as of March 2022, which 
includes data for 2018-2020. The Medicare cost report data showed that 
between 2017 and 2019 the compensation cost weight (which reflects 
expenses for wages and salaries, employee benefits, and contract labor) 
was relatively unchanged, decreasing by roughly 1.2 percentage points 
relative to the 2017-based LTCH market basket compensation cost weight. 
We note that data through 2021 are incomplete at this time and 
therefore, we are not able to estimate a compensation cost share weight 
for 2021 at this time. We have concluded that based on this preliminary 
analysis it is unclear whether these trends through 2020 are reflective 
of sustained shifts in the cost structure for long-term care hospitals 
or whether they were temporary as a result of the COVID-19 PHE. 
Therefore, we believe it is premature at this time to use more recent 
Medicare cost report data to derive a rebased and revised LTCH market 
basket. We will continue to monitor these data and any changes to the 
LTCH market basket will be proposed in future rulemaking.
    Comment: A few commenters expressed concern that the 2023 rate 
increase CMS finalized for Medicare Advantage plans was significantly 
higher than the proposed FY 2023 update for LTCH PPS payments. These 
commenters believe this difference supports their view that the 
proposed FY 2023 update for LTCH PPS payments was inadequate.
    Response: As stated previously, the Medicare program has 
historically used a market basket to account for input price increases 
in the services furnished by fee-for-service providers; in most 
instances, basing these updates on input price indexes is statutorily 
required. For the LTCH PPS we adopted a similar approach of using a 
market basket to update PPS payments, and beginning in FY 2021 this 
update reflected the percentage change in the 2017-based LTCH market 
basket (85 FR 58907 through 58909). For this FY 2023 IPPS/LTCH final 
rule, based on a more recent forecast than was used for the proposed 
rule, the LTCH market basket increase is 4.1 percent (one percentage 
point higher than the estimated market basket increase published in the 
FY 2023 IPPS/LTCH proposed rule).
    After consideration of public comments, we are finalizing the LTCH 
payment update using more recent forecast of the market basket and 
productivity adjustment. As such, based on IGI's second quarter 2022 
forecast, the FY 2023 market basket update for the LTCH PPS using the 
2017-based LTCH market basket is 4.1 percent. The current estimate of 
the productivity adjustment for FY 2023 based on IGI's second quarter 
2022 forecast is 0.3 percent. Therefore, under the authority of section 
123 of the BBRA as amended by section 307(b) of the BIPA, consistent 
with 42 CFR 412.523(c)(3)(xvii), we are establishing an annual market 
basket update to the LTCH PPS standard Federal payment rate for FY 2023 
of 3.8 percent (that is, more recent estimate of the LTCH PPS market 
basket increase of 4.1 percent less the productivity adjustment of 0.3 
percentage point).
    For LTCHs that fail to submit quality reporting data under the LTCH 
QRP, under Sec.  412.523(c)(3)(xvii) in conjunction with 42 CFR 
412.523(c)(4), as we proposed, we further reduced the annual update to 
the LTCH PPS standard Federal payment rate by 2.0 percentage points, in 
accordance with section 1886(m)(5) of the Act. Accordingly, we are 
establishing an annual update to the LTCH PPS standard Federal payment 
rate of 1.8 percent (that is, 3.8 percent minus 2.0 percentage points) 
for FY 2023 for LTCHs that fail to submit quality reporting data as 
required under the LTCH QRP.

IX. Quality Data Reporting Requirements for Specific Providers and 
Suppliers

    In section IX. of the preamble of the FY 2023 IPPS/LTCH PPS 
proposed rule (87 FR 28477 through 28612), we sought public comment on 
the following focus areas and proposed changes to the Medicare quality 
reporting programs:
     In section IX.A., assessment of the impact of climate 
change and health equity.
     In section IX.B., overarching principles in measuring 
healthcare quality disparities in hospital quality programs.
     In section IX.C., advancement of digital quality 
measurement and use of Fast Healthcare Interoperability Resources 
(FHIR) in hospital quality programs.
     In section IX.D., advancing the Trusted Exchange Framework 
and Common Agreement (TEFCA).
     In section IX.E., the Hospital IQR.
     In section IX.F., the PCHQR Program.
     In section IX.G., the LTCH QRP.
     In section IX.H. the Medicare Promoting Interoperability 
Program for Eligible Hospitals and Critical Access Hospitals (CAHs) 
(previously known as the Medicare EHR Incentive Program).

A. Current Assessment of Climate Change Impacts on Outcomes, Care, and 
Health Equity--Request for Information

1. Background
    A recent consensus statement signed by more than 200 medical 
journals

[[Page 49167]]

noted climate change represents the greatest threat to global public 
health of the coming century.\327\ Pollution associated with the 
burning of fossil fuels is known to cause serious harm and loss in 
productivity, and resultant climate instability introduces a 
combination of catastrophic weather events and chronic disease impacts 
that create serious burdens on organizations providing health 
care.\328\ There is also evidence that climate change 
disproportionately harms underserved populations (for example, racial 
and ethnic minority groups, indigenous people, members of religious 
minorities, people with disabilities, sexual and gender minorities, 
individuals with limited English proficiency, older adults, and rural 
populations).\329\ Long-term discrimination and disparities based on 
social determinants of health mean that these groups are often less 
equipped to withstand climate threats and are more susceptible to 
associated harm.\330\ For example, Black Americans are much likelier to 
experience premature mortality as a result of extreme heat, and 
childhood asthma rates related to warming temperatures will be much 
higher in minority communities, as well.\331\ Out of concern for the 
health of individuals, and to maintain uninterrupted operations in 
service of patients, we believe the healthcare sector more fully 
explore how to effectively prepare for climate threats. Because 
healthcare facilities also emit greenhouse gases (GHGs) that contribute 
to climate change and its impacts, we believe that they study how best 
to reduce those emissions, as well.
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    \327\ Atwoli, L., Banqui A., Benfield T., et al. (2021). Call 
for emergency action to limit global temperature increases, restore 
biodiversity, and protect health. Lancet, 398(10304):939-41.
    \328\ Eckelman, M., Huang K., et al. (2020). Health Care 
Pollution and Public Health Damage in the United States: An Update. 
Health Affairs, 39:12.
    \329\ U.S. Environmental Protection Agency. (2021). Climate 
Change and Social Vulnerability in the United States: A Focus on Six 
Impacts. U.S. Environmental Protection Agency, EPA 430-R-21-003.
    \330\ U.S. Environmental Protection Agency. (2021). Climate 
Change and Social Vulnerability in the United States: A Focus on Six 
Impacts. U.S. Environmental Protection Agency, EPA 430-R-21-003.
    \331\ U.S. Environmental Protection Agency. (2021). Climate 
Change and Social Vulnerability in the United States: A Focus on Six 
Impacts. U.S. Environmental Protection Agency, EPA 430-R-21-003.
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2. Solicitation of Comments on the Current State of Health System 
Climate Change Efforts
    In the Request for Information (RFI) in the FY 2023 IPPS/LTCH PPS 
proposed rule (87 FR 28478 through 28479), we sought comment on how 
hospitals, nursing homes, hospices, home health agencies, and other 
providers can better prepare for the harmful impacts of climate change 
on their patients, and how we can support them in doing so. Because 
research has shown that climate change causes harm to individuals 
(through both catastrophic events and chronic disease)\332\ and because 
there is evidence to show that climate change will disproportionately 
harm underserved populations,\333\ we believe that it is critical to 
study and prepare for these impacts.
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    \332\ Eckelman, M., Huang K., et al. (2020). Health Care 
Pollution and Public Health Damage in the United States: An Update. 
Health Affairs, 39:12.
    \333\ U.S. Environmental Protection Agency. (2021). Climate 
Change and Social Vulnerability in the United States: A Focus on Six 
Impacts. U.S. Environmental Protection Agency, EPA 430-R-21-003.
---------------------------------------------------------------------------

    Generally, we sought input on what the U.S. Department of Health 
and Human Services (HHS) and CMS can do to support hospitals, nursing 
homes, hospices, home health agencies, and other providers in more 
effectively: (a) Determining likely climate impacts (that is, both 
immediate impacts associated with climate-related disasters and long-
term chronic disease implications of climate change) on their patients, 
residents and consumers so that they can develop plans to mitigate 
those impacts; (b) understanding exceptional threats that climate-
related emergencies (for example., storms, floods, extreme heat, 
wildfires) present to continuous facility operations (including 
potential disruptions in patient services associated with catastrophic 
events as a result of power loss, limited transportation, evacuation 
challenges, etc.) so they can better address those; and (c) 
understanding how to take action on reducing their emissions and 
tracking their progress in this regard. We believe this will inform the 
development and updating of policies that can assist providers in 
responding to climate-related challenges (for example, policies related 
to emergency preparedness) as well as the updating of HHS climate-
health tools and resources.
    We also invited public comments on the following topics 
(understanding that some provider types might have done more work in 
this area than others):
     The availability of information, such as analyses of 
climate change impacts (whether developed internally or collected from 
outside sources), that hospitals, nursing homes, hospices, home health 
agencies, and other providers can access to better understand climate 
threats to their patients, community, and staff.
     The degree to which different provider types currently 
complete comprehensive climate change risk assessments to better 
understand risks to their patient populations and the costs incurred 
due to catastrophic climate events and climate-related chronic disease.
     The degree to which facility efforts to prepare for 
climate impacts overlap with the work they already complete to meet 
CMS's Emergency Preparedness Requirements for Medicare and Medicaid 
Participating Providers and Suppliers, and the degree to which related 
CMS requirements sufficiently (or insufficiently) prepare them for the 
threats created by climate change and help or hinder these efforts.
     The degree to which hospitals, nursing homes, hospices, 
home health agencies, and other providers measure and share performance 
associated with their response to climate-related catastrophes (for 
example, measuring harm to vulnerable populations as a result of such 
events, or extent of disruption in service).
     The nature of facility plans for assisting the community 
and patients to prepare for and recover from climate-related events, as 
well as the nature of plans for evacuating patients with differing 
needs, including those with disabilities.
     The degree to which climate change, and climate change 
linked to health equity, is publicly addressed in strategic plans and 
objectives in your facility or system, and the degree to which hospital 
leadership regularly reviews progress on goals related to climate 
preparedness and mitigation and invests in health professional training 
on this topic.
     Whether health systems and facilities have time-bound, 
public aims for GHG emissions reduction, and, if yes, whether those 
aims relate to direct facility emissions, emissions associated with 
purchased energy, emissions associated with supply chain or some 
combination of these.
     The measures that health systems and facilities use to 
track their progress on GHG emissions reduction and use of renewable 
energy, as well as the data collection tools that they may use support 
this tracking.
     The tools and supports that health systems and facilities 
most heavily rely on to support their efforts to reduce GHG emissions.
     How HHS and CMS can support hospitals, nursing homes, 
hospices, home health agencies, and other providers in their efforts to 
more fully prepare for climate change's catastrophic and chronic 
impacts on

[[Page 49168]]

their operations and the people they serve, as well as what incentives 
(for example, recognition, payment, reporting) might assist them in 
taking more action on climate readiness and emissions reduction.
     Whether accrediting organizations assess facilities' 
readiness for climate-related threats and their efforts to reduce GHG 
emissions.
    We received comments on these topics.
    Comment: We received many comments expressing support for this 
request for information on health impacts due to climate change and how 
we could potentially support hospitals, nursing homes, hospices, home 
health agencies, and other providers to more effectively determine and 
plan for climate impacts. Many commenters underscored the impacts of 
climate change, particularly on specific disease and services lines, as 
well as on underserved populations. Many commenters provided sources of 
public data and analyses that depict healthcare's impact on climate. 
Many commenters also identified pledges to which they committed in 
pursuit of reducing their climate impact.
    The vast majority of commenters suggested that we incentivize and 
provide funding for participation in climate change initiatives. 
Several commenters proposed a value-based purchasing program as a 
potential format for such participation. A commenter suggested projects 
that reduce climate footprint could count towards community benefit.
    Many commenters provided feedback and insights regarding how we can 
assess the impact of climate change on patients. Many commenters 
recommended undertaking additional analysis as the first step towards 
helping the healthcare industry understand and impact climate change. A 
commenter recommended hospitals study their internal patient level data 
to identify climate impacts on patients. A few commenters also 
recommended updating screening tools to include climate change health 
impact topics.
    Commenters identified many initiatives and projects they are 
pursuing to reduce their footprint. Commenters recommended that we 
develop a repository of data and projects that have addressed climate 
change; highlight the impact of single use products versus reprocessing 
medical equipment and forced device obsolescence; encourage the 
reduction and recycling of anesthesia gases; leverage lessons learned 
from the reduction of highly enriched uranium; understand data storage 
and its impact on the environment; update aging healthcare 
infrastructure and building codes, especially on temperature regulation 
requirements; update guidance for on-site alternative energy sources 
and micro-grids; and add education on climate topics for clinicians. 
Many commenters also identified the need to update hospital emergency 
preparedness plans to include responses to climate-related disasters, 
including short-term, long-term, and post-disaster responses.
    Commenters emphasized that climate change is not just a hospital 
issue. They recommended the that we engage with relevant groups 
including suppliers, advocacy groups, and other government agencies. A 
few commenters suggested that we work with interested parties to 
perform a life cycle analysis to identify high emission, low value 
clinical devices or services. A few commenters suggested that we 
continue to consider, and perhaps expand, the definition of climate 
change.
    A few commenters cautioned us about considering new initiatives 
against the backdrop of the challenges stemming from the COVID-19 
pandemic. A commenter specifically encouraged us to ensure that our 
work on addressing climate change does not detract from the mission of 
improving health. A commenter shared that climate related initiatives 
are funded through tax-exemption, which is not available to non-profit 
healthcare entities. Furthermore, A commenter questioned whether HHS 
has the authority to impose climate-change requirements. Finally, a 
commenter advised that any expansion of emergency preparedness 
requirements be non-burdensome.
    In summary, the organizations and individuals that submitted 
comments almost uniformly embraced the importance of setting goals for 
reduced emissions and increased climate resilience but also repeatedly 
requested the following:
     More timely data to understand threats and health impacts 
associated with climate change, especially for vulnerable and 
marginalized populations, as well as information on cost impacts for 
care providers.
     Financing supports and incentives to help deepen their 
work in this area (with attention to the needs of different provider 
types).
     Technical assistance tools to assist operational and 
clinical improvements in this area (with attention to frontline 
specialties whose work intersects with climate health).
     Standardized measures and measurement frameworks to help 
with progress tracking and reporting (with mixed views on whether such 
reporting be mandatory or voluntary).
     Updates to/simplification of emergency preparedness 
requirements, conditions of participation and other regulations to help 
all provider and supplier types to be more responsive to climate-
related challenges.
     Attention to the challenges different provider types, 
already under strain from the pandemic, must address to take on this 
work and ensure no compromise in the quality of care delivery.
     Attention to the importance of engaging supply chain 
stakeholders in order to fully address the challenge of reducing 
emissions.
    Response: We thank the commenters for their input, recommendations, 
and many ideas. We will consider all the feedback received as we 
continue to understand how hospitals, nursing homes, hospices, home 
health agencies, and other providers can better prepare for the harmful 
impacts of climate change on their patients, and how we can support 
them in doing so. We additionally appreciate the many commenters who 
would like to volunteer to be a part of groups to help develop any 
future policies on this topic. We will continue to engage all 
interested parties via multiple avenues including future notice-and-
comment rulemaking.

[[Page 49169]]

B. Overarching Principles for Measuring Healthcare Quality Disparities 
Across CMS Quality Programs--Request for Information

1. Background
    Significant and persistent inequities in healthcare outcomes exist 
in the United States (U.S.). Belonging to a racial or ethnic minority 
group; being a member of a religious minority; living with a 
disability; being a member of the lesbian, gay, bisexual, transgender, 
and queer (LGBTQ+) community; living in a rural area; or being near or 
below the poverty level, are often associated with worse health 
outcomes.334 335 336 337 338 339 340 341 342 343 We are 
committed to achieving equity in healthcare outcomes for our 
beneficiaries by supporting healthcare providers' quality improvement 
activities to reduce health disparities, enabling beneficiaries to make 
more informed decisions, and promoting healthcare provider 
accountability for healthcare disparities.\344\
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    \334\ Joynt KE, Orav E, Jha AK. (2011). Thirty-day readmission 
rates for Medicare beneficiaries by race and site of care. JAMA, 
305(7): 675-681.
    \335\ Vu M. et al. (2016). Predictors of Delayed Healthcare 
Seeking Among American Muslim Women, Journal of Women's Health 
26(6). doi: 10.1089/jwh.2015.5517.
    \336\ Nadimpalli SB, Cleland CM, Hutchinson MK, Islam N, Barnes 
LL, Van Devanter N. (2016) The Association between Discrimination 
and the Health of Sikh Asian Indians. Health Psychology, 35(4), 351-
355. https://doi.org/10.1037/hea0000268.
    \337\ Lindenauer PK, Lagu T, Rothberg MB, et al. (2013). Income 
inequality and thirty-day outcomes after acute myocardial 
infarction, heart failure, and pneumonia: Retrospective cohort 
study. British Medical Journal, 346.
    \338\ Trivedi AN, Nsa W, Hausmann LRM, et al. (2014). Quality 
and equity of care in U.S. hospitals. New England Journal of 
Medicine, 371(24): 2298-2308.
    \339\ Polyakova, M., et al. (2021). Racial disparities in excess 
all-cause mortality during the early COVID-19 pandemic varied 
substantially across states. Health Affairs, 40(2): 307-316.
    \340\ Rural Health Research Gateway. (2018). Rural communities: 
age, income, and health status. Rural Health Research Recap. 
Available at: https://www.ruralhealthresearch.org/assets/2200-8536/rural-communities-age-income-health-status-recap.pdf.
    \341\ HHS Office of Minority Health. (2020). Progress Report to 
Congress: 2020 Update on the Action Plan to Reduce Racial and Ethnic 
Health Disparities. Available at: https://www.minorityhealth.hhs.gov/omh/browse.aspx?lvl=2&lvlid=57.
    \342\ Heslin, KC, Hall, JE. (2021). Sexual Orientation 
Disparities in Risk Factors for Adverse COVID-19-Related Outcomes, 
by Race/Ethnicity--Behavioral Risk Factor Surveillance System, 
United States, 2017-2019. MMWR Morb Mortal Wkly Rep 2021;70:149-154. 
Available at: https://www.cdc.gov/mmwr/volumes/70/wr/mm7005a1.htm.
    \343\ Poteat TC, Reisner SL, Miller M, Wirtz AL. (2020). COVID-
19 vulnerability of transgender women with and without HIV infection 
in the Eastern and Southern U.S. preprint. medRxiv. 2020;2020.07.21. 
20159327. doi:10.1101/2020.07.21.20159327. Available at: https://pubmed.ncbi.nlm.nih.gov/32743608/.
    \344\ Centers for Medicare and Medicaid Services. (2016). CMS 
Quality Strategy. Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Qualityinitiativesgeninfo/downloads/cms-quality-strategy.pdf.
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    Health equity is an important component of an equitable society. 
Equity, as defined in Executive Order 13985, is ``the consistent and 
systematic fair, just, and impartial treatment of all individuals, 
including individuals who belong to underserved communities that have 
been denied such treatment, such as Black, Latino, and Indigenous and 
Native American persons, Asian Americans and Pacific Islanders and 
other persons of color; members of religious minorities; LGBTQ+ 
persons; persons with disabilities; persons who live in rural areas; 
and persons otherwise adversely affected by persistent poverty or 
inequality.'' \345\ We define health equity as the attainment of the 
highest level of health for all people, where everyone has a fair and 
just opportunity to attain their optimal health regardless of race, 
ethnicity, disability, sexual orientation, gender identity, religion, 
socioeconomic status, geography, preferred language, or other factors 
that affect access to care and health outcomes. We are working to 
advance health equity by designing, implementing, and operationalizing 
policies and programs that support health for all the people served by 
our programs, eliminating avoidable differences in health outcomes 
experienced by people who are disadvantaged or underserved, and 
providing the care and support that our beneficiaries need to 
thrive.\346\
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    \345\ Federal Register. (2021). Advancing Racial Equity and 
Support for Underserved Communities Through the Federal Government. 
Available at: https://www.federalregister.gov/documents/2021/01/25/2021-01753/advancing-racial-equity-and-support-for-underserved-communities-through-the-federal-government.
    \346\ Centers for Medicare & Medicaid Services. (2022). Health 
Equity. Available at: https://www.cms.gov/pillar/health-equity.
---------------------------------------------------------------------------

    Advancing health equity will require a variety of efforts across 
the healthcare system. The reduction in healthcare disparities is one 
aspect of improving equity that we have prioritized. In a RFI that we 
included in the FY 2022 IPPS/LTCH PPS final rule, titled ``Closing the 
Health Equity Gap in CMS Hospital Quality Programs'' (86 FR 45349 
through 45360), we described programs and policies we have implemented 
over the past decade with the aim of identifying and reducing 
healthcare disparities, including: the CMS Mapping Medicare Disparities 
Tool \347\ and the CMS Disparity Methods stratified reporting.\348\ CMS 
has also supported HHS' efforts to implement the National Standards for 
Culturally and Linguistically Appropriate Services (CLAS) in Health and 
Health Care (78 FR 58539); \349\ as well as improvement of the 
collection of drivers of health in standardized patient assessment data 
in four post-acute care settings and the collection of health-related 
social need data by model participants in the Accountable Health 
Communities Model.350 351 352
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    \347\ Centers for Medicare and Medicaid Services. (2021). CMS 
Office of Minority Health. Available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/OMH-Mapping-Medicare-Disparities.
    \348\ Centers for Medicare and Medicaid Services. Disparity 
Methods Confidential Reporting. Available at: https://qualitynet.cms.gov/inpatient/measures/disparity-methods.
    \349\ Federal Register. (2013). National Standards for 
Culturally and Linguistically Appropriate Services (CLAS) in Health 
and Health Care. Available at: https://www.federalregister.gov/documents/2013/09/24/2013-23164/national-standards-for-culturally-and-linguistically-appropriate-services-clas-in-health-and-health.
    \350\ Centers for Medicare and Medicaid Services. (2021). 
Accountable Health Communities Model. Available at: https://innovation.cms.gov/innovation-models/ahcm.
    \351\ Centers for Medicare and Medicaid Services. The 
Accountable Health Communities Health-Related Social Needs Screening 
Tool. Available at: https://innovation.cms.gov/files/worksheets/ahcm-screeningtool.pdf.
    \352\ Centers for Medicare and Medicaid Services. (2021). IMPACT 
Act Standardized Patient Assessment Data Elements. Available at: 
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/-IMPACT-Act-Standardized-Patient-Assessment-Data-Elements.
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    Measuring healthcare disparities and reporting these results to 
healthcare providers is a cornerstone of our approach to advancing 
healthcare equity. It is important to consistently measure differences 
in care received by different groups of our beneficiaries, and this can 
be achieved by methods to stratify quality measures. Measure 
stratification is defined for this purpose as calculating measure 
results for specific groups or subpopulations of patients. Assessing 
healthcare disparities through stratification is only one method for 
using healthcare quality measurement to address health equity, but it 
is an important approach that allows healthcare providers to tailor 
quality improvement initiatives, decrease disparity, track improvement 
over time, and identify opportunities to evaluate upstream drivers of 
health. The use of measure stratification to assess disparities has 
been identified by our Office of Minority Health as a critical 
component of an organized response to health disparities.\353\ To date, 
we have

[[Page 49170]]

performed analyses of disparities in our quality programs by using a 
series of stratification methodologies identifying quality of care for 
patients with heightened social risk or with demographic 
characteristics with associations to poorer outcomes. In 2015, we began 
providing entity-level quality and member experience data to all 
Medicare Part C/D health plans stratified by race and ethnicity. In 
2018, we introduced confidential reporting of hospital quality measure 
data stratified by dual eligibility in the Hospital IQR Program (81 FR 
25199; 82 FR 38403 through 38409).\354\
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    \353\ Centers for Medicare & Medicaid Services. (2021). Building 
an Organizational Response to Health Disparities [Fact Sheet]. U.S. 
Department of Health and Human Services. Available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/Health-Disparities-Guide.pdf.
    \354\ Centers for Medicare & Medicaid Services, Office of 
Minority Health. Racial, Ethnic, & Gender Disparities in Health Care 
in Medicare Advantage. (2021). Available at: https://www.cms.gov/files/document/racial-ethnic-gender-disparities-health-care-medicare-advantage.pdf.
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    We are continuing to evaluate opportunities to expand our measure 
stratification reporting initiatives using existing sources of data. 
Our goal is to provide comprehensive and actionable information on 
health disparities to healthcare providers participating in our quality 
programs to support quality improvement efforts. We are doing this, in 
part, by starting with confidential reporting of stratified measure 
results that highlight potential gaps in care between groups of 
patients. This includes examining the possibility of reporting 
disparities in care based on additional social risk factors and 
demographic variables associated with historic disadvantage in the 
healthcare system, and examining disparities through the use of 
stratified healthcare quality measures across a variety of care 
settings. As we consider expanding our disparity measurement 
initiatives through the use of measure stratification, we believe that 
we model these efforts on existing best practices, such as considering 
feedback and making use of lessons learned through the development of 
our existing disparity reporting efforts.
    There are several key elements that we intend to take into account 
as we consider advancing the use of measurement and stratification as 
tools to address healthcare disparities and advance healthcare equity. 
In the FY 2023 IPPS/LTCH PPS proposed rule, we sought input on key 
considerations in five specific areas that could inform our approach 
(87 FR 28479 through 28486). Each is described in more detail later in 
this section:
     Identification of Goals and Approaches for Measuring 
Healthcare Disparities and Using Measure Stratification Across CMS 
Quality Programs--This section identifies potential approaches for 
measuring healthcare disparities through measure stratification in CMS 
quality reporting programs.
     Guiding Principles for Selecting and Prioritizing Measures 
for Disparity Reporting Across CMS Quality Reporting Programs--This 
section describes considerations that could inform the selection of 
healthcare quality measures to prioritize for stratification.
     Principles for Social Risk Factor and Demographic Data 
Selection and Use--This section describes several types of social risk 
factor and demographic data that could be used in stratifying measures 
for healthcare disparity measurement.
     Identification of Meaningful Performance Differences--This 
section reviews several strategies for identifying meaningful 
differences in performance when measure results are stratified.
     Guiding Principles for Reporting Disparity Results--This 
section reviews considerations we could take into account in 
determining how quality programs will report measure results stratified 
by social risk factors and demographic variables to healthcare 
providers, as well as the ways different reporting strategies could 
hold healthcare providers accountable for identified disparities.
2. Identification of Goals and Approaches for Measuring Healthcare 
Disparities and Using Measure Stratification Across CMS Quality 
Programs
    One of our goals in developing methods to measure disparities in 
care for beneficiaries is to provide actionable and useful results to 
healthcare providers. By quantifying healthcare disparities (for 
example, through quality measure stratification), we aim to provide 
useful tools for healthcare providers to drive improvements. We hope 
that these results support healthcare provider efforts to examine the 
underlying drivers of disparities in their patients' care and to 
develop their own innovative and targeted quality improvement 
interventions. With stratified disparity information available, it may 
be possible to drive system-wide advancement through incremental, 
provider-level improvement.
    There are multiple conceptual approaches to stratifying measures. 
Since 2018, we have focused on illuminating healthcare disparities by 
reporting stratified results of existing quality measures by dual 
eligible status in two complementary ways.\355\ First, after 
stratification by dual eligible status, measure results for subgroups 
of patients served by an individual healthcare provider can be directly 
compared. This type of comparison identifies such disparities, or gaps 
in care or outcomes between groups at a hospital. This approach is 
sometimes referred to as ``within-provider'' disparity and can be done 
for most measures that include patient-level data for most care 
settings. ``Within-provider'' disparities are a helpful means by which 
to quantitatively express disparities in care at the provider 
level.\356\ Second, a healthcare provider's performance on a measure 
for only dual eligible patients is compared to other healthcare 
providers' performance for that same subgroup of patients (sometimes 
referred to as ``across-provider'' disparities measurement). This type 
of comparison illuminates the healthcare provider's performance for 
only the dual eligible subgroup, allowing comparisons for specific 
performance to be better understood and compared to peers, or against 
state and national benchmarks.
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    \355\ QualityNet. Disparity Methods Confidential Reporting 
Overview. Available at: https://qualitynet.cms.gov/inpatient/measures/disparity-methods.
    \356\ Centers for Medicare & Medicaid Services. (2015). Risk 
Adjustment Fact Sheet. Available at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/PhysicianFeedbackProgram/Downloads/Risk-Adjustment-Fact-Sheet.pdf.
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    Taken separately, each approach may provide an incomplete picture 
of disparities in care for a particular measure, but when reported 
together with overall quality performance, these results can give 
detailed information about where differences in care exist. Using dual 
eligibility as an example, a healthcare provider may underperform when 
compared to national averages for their dual eligible population 
(``across-provider'' disparity), but if they also underperform for 
patients who are not dual eligible, the measured difference, or 
``within-provider'' disparity, could be negligible even though 
performance for the group that has been historically marginalized 
remains poor. In this case, simply providing stratified within-provider 
results could show little difference in care between patient groups 
seen by the provider but the combined results show the provider is 
underperforming on care for some patients compared to other providers.
    Similar approaches have been recommended by the Assistant Secretary 
of Planning and Evaluation (ASPE) as ways to measure health

[[Page 49171]]

equity in their 2020 Report to Congress.\357\ In their report, ASPE 
suggested measuring and reporting quality specifically for 
beneficiaries with social risk factors, stratifying measures by social 
risk factors, and encouraging the development of health equity measures 
such as these for incorporation into quality reporting programs.
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    \357\ ASPE. (2020). Social Risk Factors and Performance in 
Medicare's Value-Based Purchasing Program: The Second of Two Reports 
Required by the Improving Medicare Post-Acute Care Transformation 
(IMPACT) Act of 2014. Available at: https://aspe.hhs.gov/sites/default/files/migrated_legacy_files//195191/Second-IMPACT-SES-Report-to-Congress.pdf.
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    We are especially sensitive to the need to ensure all disparity 
reporting avoids measurement bias. Stratified results must be carefully 
examined for potential measurement or algorithmic bias \358\ that is 
introduced through stratified reporting. Furthermore, results of 
stratified reporting must be evaluated for any type of selection bias 
that fails to capture disparity due to inadequate representation of 
subgroups of patients in measure cohorts. As part of the implementation 
of any type of measure stratification, we would carefully examine 
stratified results and methods to mitigate the potential for drawing 
incorrect conclusion from results.
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    \358\ Obermeyer Z, Powers B, Vogeli C, Mullainathan S. 
Dissecting racial bias in an algorithm used to manage the health of 
populations. Science. 2019;366(6464):447-53.
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3. Guiding Principles for Selecting and Prioritizing Measures for 
Disparity Reporting Across CMS Quality Reporting Programs
    We are considering expanding our efforts to provide stratified 
reporting for additional clinical quality measures, provided they offer 
meaningful and valid feedback to healthcare providers on their care for 
populations that may face social disadvantage or other forms of 
discrimination or bias. Further development of stratified reporting of 
healthcare quality measures can provide healthcare providers with more 
granular results that support targeting resources and initiatives to 
improve health equity as a means to improving the overall quality of 
care. We are mindful that it may not be possible to calculate 
stratified results for all quality measures, or that there may be 
situations where stratified reporting may not be desired. To help 
inform prioritization of the next generation of candidate measures for 
stratified reporting, we solicited feedback on several systematic 
principles under consideration that we believe will help us prioritize 
measures for disparity reporting across quality programs.
    These considerations would help guide the use of stratified measure 
results to provide information on healthcare disparities broadly across 
our quality programs. While we aim to standardize approaches where 
possible, disparity identification requires an understanding of the 
specific context and measures used by each program. To ensure that 
results provide the most actionable data possible, and to limit the 
potential for the introduction of bias, we believe decisions about how 
to identify and prioritize measures for possible stratification be made 
at the program level.
     Prioritize Existing Clinical Quality Measures--When 
considering disparity reporting of stratified quality measures, there 
are several advantages to focusing on measures that we have already, 
through notice and comment rulemaking, adopted for one or more CMS 
quality programs. These measures assess the quality of care on agreed 
upon topics for quality measurement specific to a quality program 
setting. These measures have gone through an extensive development 
process and validation testing with significant opportunity for public 
input. Adapting these existing quality measures to measure disparity 
through stratification maintains adherence to the measurement 
priorities identified through expert review and validation completed 
through measure development and testing. The application of measure 
stratification to these measures would also minimize any new reporting 
burden on healthcare providers.
     Prioritize Measures with Identified Disparity in Treatment 
or Outcomes for the Selected Social or Demographic Factor--Candidate 
measures for stratification be supported by evidence of underlying 
healthcare disparities in the procedure, condition, or outcome being 
measured. A review of peer-reviewed research studies be conducted to 
identify disparities related to treatment, procedure, or outcome 
associated with the measure, and carefully consider both social risk 
factors and patient demographics. In addition, analysis of Medicare-
specific data be done to demonstrate evidence of disparity in care 
among the Medicare population. In addition, consideration also be given 
to conditions that have highly disproportionate prevalence in certain 
populations.
     Prioritize Measures with Sufficient Sample Size to Allow 
for Reliable and Representative Comparisons--Sample size holds specific 
significance for statistical calculations; however, it holds additional 
importance in the context of disparity reporting. Candidate measures 
for stratification will need to have sufficient cohort sample size to 
ensure that reported results of the disparity calculation are reliable 
and representative of the healthcare provider's patient population. 
This may be challenging if cohorts with a given social risk factor are 
small.
    Carefully establishing reliability and representation standards for 
measure reporting is important for considering measures to stratify. 
Reliability, in this case, refers to the minimum case count needed to 
achieve reliable results. Metrics for reliability are used in non-
stratified quality measure reporting, such as when measures require a 
certain number of procedures for their rates to be considered reliable. 
The use of a reliability standard for disparity reporting will ensure 
consistently reliable results are calculated.
    Representation standards are also important and may involve 
requiring a minimum number or percent of healthcare providers or 
patients to be eligible to receive stratified results with reliable 
estimates before a measure is considered for disparity reporting. This 
requirement aims to ensure that meaningful comparisons can be made. As 
we noted previously, when only a small proportion of healthcare 
providers can receive statistically significant results, it may not be 
prudent for quality programs to pursue stratified reporting for that 
particular measure. Doing so can create challenges when generalizing 
rates of disparity for conditions or procedures when only a small 
proportion of a healthcare provider's results are considered. If, for 
example, only 10 percent of healthcare providers can report results, 
results must be clearly presented to ensure they are not understood to 
represent disparity in care for the measurement taking place in all 
care settings, as shown in this example, where 90 percent of them would 
not be included in reporting.
    Quality programs may further consider measures for disparity 
reporting based on the size of the calculated disparity by prioritizing 
measures for stratification that show large differences in care between 
patient groups. Large differences in care for patients along social or 
demographic lines may indicate high potential that targeted initiatives 
could be effective. However, measures with disparities of smaller 
magnitude but with large cohorts affect many patients because they may 
have very large aggregate impacts on the national scale.

[[Page 49172]]

     Prioritize Outcome Measures and Measures of Access and 
Appropriateness of Care-- Quality measurement in CMS programs often 
focus on outcomes of care, such as mortality or readmission. Outcomes 
measures remain a priority in the context of disparities measurement. 
However, measures that focus on access to care, when available, are 
also critical tools for addressing healthcare disparities. Measures 
that address healthcare access can counterbalance the risk of creating 
perverse incentives. If only differences in care between groups are 
measured, performance on a measure of disparity could be improved by 
limiting access to care for high-risk patients in the populations that 
are historically underserved or marginalized.
    To complement stratification of measures focused on clinical 
outcomes, quality programs may consider prioritizing measures with a 
focus on access to or the appropriateness of care. These measures, when 
reported in tandem with clinical outcomes, would provide a broader 
picture of care provided by a healthcare provider, illuminate potential 
drivers of performance, and highlight organizations that fail to 
address barriers in access to care for groups that have been 
historically marginalized. We acknowledge that the measurement of 
access and appropriateness of care is a growing field, and that there 
are currently a limited number of developed quality measures on these 
topics. However, as our ability to measure these facets of healthcare 
improves, we expect that they will be high priority for measure 
stratification.
4. Principles for Social Risk Factor and Demographic Data Selection and 
Use
    There are a wide array of non-clinical drivers of health known to 
impact patient outcomes, including social risk factors such as 
socioeconomic status, housing availability, and nutrition, as well as 
marked inequity in outcomes based on patient demographics such as race 
and ethnicity, being a member of a minority religious group, geographic 
location, sexual orientation, and gender identity, religion, and 
disability status.359 360 361 362 363 364 365 366 367 The 
World Health Organization (WHO) defines social risk factors as ``non-
medical factors that influence health outcomes. They are the conditions 
in which people are born, grow, work, live, and age, and the wider set 
of forces and systems shaping the conditions of daily life.''\368\ 
These include factors such as income, education, job security, food 
security, housing, social inclusion and non-discrimination, access to 
affordable health services, and any others. Research has indicated that 
these social factors may have as much or more impact on health outcomes 
as clinical care itself.369 370 Additionally, differences in 
outcomes based on patient race and ethnicity have been identified as 
significant, persistent, and of high priority for CMS and other federal 
agencies.\371\
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    \359\ Joynt KE, Orav E, Jha AK. (2011). Thirty-day readmission 
rates for Medicare beneficiaries by race and site of care. JAMA, 
305(7):675-681.
    \360\ Lindenauer PK, Lagu T, Rothberg MB, et al. (2013). Income 
inequality and thirty-day outcomes after acute myocardial 
infarction, heart failure, and pneumonia: retrospective cohort 
study. British Medical Journal, 346.
    \361\ Trivedi AN, Nsa W, Hausmann LRM, et al. (2014). Quality 
and equity of care in U.S. hospitals. New England Journal of 
Medicine, 371(24):2298-2308.
    \362\ Polyakova, M., et al. (2021). Racial disparities in excess 
all-cause mortality during the early COVID-19 pandemic varied 
substantially across states. Health Affairs, 40(2): 307-316.
    \363\ Rural Health Research Gateway. (2018). Rural communities: 
Age, income, and health status. Rural Health Research Recap. 
Available at: https://www.ruralhealthresearch.org/assets/2200-8536/rural-communities-age-income-health-status-recap.pdf.
    \364\ HHS Office of Minority Health (2020). 2020 Update on the 
Action Plan to Reduce Racial and Ethnic Health Disparities. 
Available at: https://www.minorityhealth.hhs.gov/assets/PDF/Update_HHS_Disparities_Dept-FY2020.pdf.
    \365\ Poteat TC, Reisner SL, Miller M, Wirtz AL. (2020). COVID-
19 vulnerability of transgender women with and without HIV infection 
in the Eastern and Southern U.S. medRxiv [Preprint]. 
2020.07.21.20159327. doi: 10.1101/2020.07.21.20159327. PMID: 
32743608; PMCID: PMC7386532.
    \366\ Vu M. et al. (2016). Predictors of Delayed Healthcare 
Seeking Among American Muslim Women, Journal of Women's Health 
26(6). doi: 10.1089/jwh.2015.5517.
    \367\ Nadimpalli SB, Cleland CM, Hutchinson MK, Islam N, Barnes 
LL, Van Devanter N. (2016) The Association between Discrimination 
and the Health of Sikh Asian Indians. Health Psychology, 35(4), 351-
355. https://doi.org/10.1037/hea0000268.
    \368\ World Health Organization. Social Determinants of Health. 
Available at: https://www.who.int/health-topics/social-determinants-of-health#tab=tab_1.
    \369\ Hood, C., Gennuso K., Swain G., Catlin B. (2016). County 
Health Rankings: Relationships Between Determinant Factors and 
Health Outcomes. Am J Prev Med. 50(2):129-135. doi:10.1016/
j.amepre.2015.08.024.
    \370\ Chepaitis, A.E., Bernacet, A., Kordomenos, C., Greene, 
A.M., Walsh, E.G. (2020). Addressing social determinants of health 
in demonstrations under the financial alignment initiative. RTI 
International. Available at: https://innovation.cms.gov/data-and-reports/2021/fai-sdoh-issue-brief.
    \371\ White House. (2021). Executive Order On Advancing Racial 
Equity and Support for Underserved Communities Through the Federal 
Government. Available at: https://www.whitehouse.gov/briefing-room/presidential-actions/2021/01/20/executive-order-advancing-racial-equity-and-support-for-underserved-communities-through-the-federal-government/.
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    Identifying and prioritizing specific indicators of social risk or 
demographic variables to consider for stratified analyses and measure 
reporting can be challenging due to the large number of variables 
identified in the literature as potential risk factors for disparities 
in health care and poorer health outcomes. And yet, the limited 
availability of data for many self-reported social risk factors and 
demographic factors across the healthcare sector further complicates 
our ability to choose effective metrics to evaluate disparity.
    Disparity reporting in the Hospital IQR Program has focused on 
stratification by dual eligibility for Medicare and Medicaid. Dual 
eligibility has been used in this and other CMS quality programs as an 
indicator of financial risk, as the majority of Medicaid beneficiaries 
are eligible based on meeting thresholds for low patient income and/or 
assets. The use of dual eligibility is consistent with recommendations 
from ASPE's First Report to Congress which was required by the 
Improving Medicare Post-Acute Care Transformation (IMPACT) Act of 2014 
(Pub. L. 113-185).\372\ This report found that, in the context of 
value-based purchasing (VBP) programs, dual eligibility, as an 
indicator of social risk, was among the most powerful predictors of 
poor health outcomes among those social risk factors that ASPE examined 
and tested.
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    \372\ Office of the Assistant Secretary For Planning and 
Evaluation. (2016). Report to Congress: Social Risk Factors and 
Performance Under Medicare's Value-Based Purchasing Programs. 
Available at: https://aspe.hhs.gov/reports/report-congress-social-risk-factors-performance-under-medicares-value-based-purchasing-programs.
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    Financial risk is only one metric of social risk, and 
stratification of quality measures by additional social risk factors 
and demographics (such as race, ethnicity, language, religion, sexual 
orientation, and gender identity) or disability, is important to 
provide more granular information for healthcare providers to act upon. 
As we consider prioritizing and expanding the variables used for 
measure stratification, we will carefully consider both social risk 
factors and patient demographics as well as other variables associated 
with historic disadvantage in healthcare, such as disability status.
    As noted previously, a growing body of literature identifies the 
association between social risk factors and demographic variables with 
poorer health outcomes.373 374 375 While social

[[Page 49173]]

risk factors and demographic variables are both associated with worse 
healthcare outcomes and experiences, they are distinct constructs, and 
be identified, measured, and reported as such. Patient demographic 
variables such as race and ethnicity are often identified as indicators 
of social risk driven by the differences in care received by persons 
who belong to minority racial and ethnic groups. The disparity in 
outcomes can be attributed to many factors, including discrimination in 
the healthcare system, challenges accessing quality healthcare, and 
societal inequity in other factors connected to social risk. 
Attributing differences in outcomes to race may inappropriately place 
the driver of poorer health outcomes on the patient, rather than on 
structural factors, such as racism in society and the healthcare system 
that drive the provision of lower quality care.\376\ It is important, 
in identification of non-clinical drivers of health, to identify that 
race and ethnicity are not the social risk factor, but markers of 
exposure to other factors.
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    \373\ National Academies of Sciences, Engineering, and Medicine. 
(2016). Accounting for social risk factors in Medicare payment: 
Identifying social risk factors. Washington, DC: The National 
Academies Press. https://doi.org/10.17226/21858. Available at: 
https://www.nap.edu/catalog/21858/accounting-for-social-risk-factors-in-medicare-payment-identifying-social.
    \374\ Office of the Assistant Secretary For Planning and 
Evaluation. (2016). Report to Congress: Social Risk Factors and 
Performance Under Medicare's Value-Based Purchasing Programs. 
Available at: https://aspe.hhs.gov/reports/report-congress-social-risk-factors-performance-under-medicares-value-based-purchasing-programs.
    \375\ Office of the Assistant Secretary For Planning and 
Evaluation. (2020). Report to Congress: Social Risk Factors and 
Performance Under Medicare's Value-Based Purchasing Programs. 
Available at: https://aspe.hhs.gov/reports/second-report-congress-social-risk-medicares-value-based-purchasing-programs.
    \376\ Gee G.C., Ford C.L. (2011). Structural Racism and health 
inequities: Old Issues, New Directions. Du Bois Review: Social 
science research on race, 8(1), 115-132. Available at: https://doi.org/10.1017/S1742058X11000130.
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    In prioritizing among social risk factors and demographic 
variables, disability, and other markers of disadvantage for stratified 
reporting, we anticipate that each individual quality program would 
design an approach appropriate to their care setting. We strive to 
operationalize our programs consistently where possible to decrease the 
burden on healthcare providers, however, the deeply contextual nature 
of this type of reporting may require the development of an approach 
specific to the quality programs based on care setting, patient 
population, and data availability.
    The availability of data is a crucial consideration when examining 
data sources for use in stratified quality reporting. In many cases, 
the lack of available patient-reported data on patient social risk or 
demographic variables limits the ability to conduct disparity analyses. 
While improving the collection of patient-reported demographic 
information and information on social risk is an ongoing goal, other 
methods and data sources for estimating social risk (as described 
further in this section) could potentially fill in gaps in existing 
data sets, and could include area-based indicators or imputation 
techniques that use existing information about patient populations to 
estimate approximations about related population information. Each of 
these types of data sources have advantages and disadvantages.
    Patient-reported data are considered to be the gold standard for 
evaluating care for patients with social risk factors or who belong to 
certain demographic groups as this is an accurate and preferred way to 
attribute social risk.\377\ Currently, there are many efforts underway 
to further develop data standards for collection for self-reported 
patient social risk and demographic variables. Yet, given that national 
data sources of reliable, self-reported data are not yet available, we 
also intend to consider other options for social risk factor data. We 
note efforts to standardize the collection of demographic and social 
risk factor data include prior work done by both CMS and the Office of 
the National Coordinator for Health Information Technology (ONC) with 
federal and private partners to better collect and leverage data on 
social risk. This work includes: (1) The development of an Inventory of 
Resources for Standardized Demographic and Language Data Collection; 
378 379 (2) CMS' work to support specialized International 
Classification of Diseases, (ICD) 10th Revision, Clinical Modification 
(ICD-10-CM) codes for describing the socioeconomic, cultural, and 
environmental drivers of health; \380\ and (3) the CMS sponsorship of 
several initiatives to statistically estimate race and ethnicity 
information when it is absent.381 382
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    \377\ Jarr[iacute]n OF, Nyandege AN, Grafova IB, Dong X, Lin H. 
(2020). Validity of race and ethnicity codes in Medicare 
administrative data compared with gold-standard self-reported race 
collected during routine home health care visits. Med Care, 
58(1):e1-e8. doi: 10.1097/MLR.0000000000001216. PMID: 31688554; 
PMCID: PMC6904433.
    \378\ Centers for Medicare & Medicaid Services. (2020). Building 
an Organizational Response to Health Disparities Inventory of 
Resources for Standardized Demographic and Language Data Collection. 
Available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/Data-Collection-Resources.pdf.
    \379\ The Office of the National Coordinator for Health 
Information Technology (ONC). Health IT Standards Bulletin. 
HealthIT.gov: 2021. URL: https://www.healthit.gov/sites/default/files/page/2021-05/Standards_Bulletin_2021-2.pdf.
    \380\ Centers for Medicare & Medicaid Services (2019). 
Utilization of Z Codes for Social Determinants of Health among 
Medicare Fee-for-Service Beneficiaries, 2019. Available at: https://www.cms.gov/files/document/z-codes-data-highlight.pdf.
    \381\ Centers for Medicare & Medicaid Services (2021). A New 
Method to Improve measurement of Race-and-Ethnicity in CMS Data and 
Applications to Inequities in Quality of Care. Available at: https://www.cms.gov/files/document/new-method-improve-measurement-race-and-ethnicity-cms-data-and-applications-inequalities-quality.pptx.
    \382\ Eicheldinger, C., & Bonito, A. (2008). More accurate 
racial and ethnic codes for Medicare administrative data. Health 
Care Financing Review, 29(3), 27-42.
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    One example of improving sources of data come from the certified 
health IT utilized by hospitals to meet the requirements of the 
Promoting Interoperability program. This includes health IT certified 
to the ``demographics'' certification criterion (45 CFR 170.315(a)(5)), 
which provides for the capability to record race and ethnicity at a 
detailed level of granularity consistent with the Centers for Disease 
Control and Prevention's (CDC) Race & Ethnicity--CDC code system. This 
code system includes more than 900 concepts for race and ethnicity, 
which gives patients very specific options for self-identifying their 
demographic information. The 900 concepts are organized in a way to 
eventually ``roll up'' to the Office of Management and Budget's (OMB) 
minimum categories for race and ethnicity,\383\ which can support 
aggregation and reporting needs when the OMB standard is necessary. It 
also includes social, psychological, and behavioral standards in health 
IT certification criteria (80 FR 62601), providing interoperability 
standards (LOINC [Logical Observation Identifiers Names and Codes] and 
SNOMED CT [Systematized Nomenclature of Medicine--Clinical Terms]) for 
financial strain, education, social connection and isolation, and 
others. The Agency for Healthcare Research and Quality (AHRQ) has also 
worked with the Gravity Project which is a multistakeholder effort to 
expand capabilities to capture additional drivers of health data 
elements, to identify and harmonize social risk factor data for 
interoperable electronic health information exchange for electronic 
health record (EHR) fields,\384\ and make recommendations on the 
expansion of

[[Page 49174]]

the ICD-10 (International Classification of Diseases, 10th Revision) Z-
codes, the alphanumeric codes used worldwide to represent diagnoses, to 
include additional social risk diagnoses.\385\
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    \383\ Federal Register. (1997). Revisions to the Standards for 
the Classification of Federal Data on Race and Ethnicity. Available 
at: https://www.federalregister.gov/documents/1997/10/30/97-28653/revisions-to-the-standards-for-the-classification-of-federal-data-on-race-and-ethnicity.
    \384\ Gravity Project. Available at: https://thegravityproject.net/.
    \385\ Centers for Medicare and Medicaid Services. (2020). Z 
Codes Utilization among Medicare Fee-for-Service (FFS) Beneficiaries 
in 2017. Available at: https://www.cms.gov/files/document/cms-omh-january2020-zcode-data-highlightpdf.pdf.
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    We expect to continue evaluating patient-reported sources of social 
risk and demographic information. We are also considering three sources 
of social risk and demographic data that would allow us to report 
stratified measure results:
     Billing and Administrative Data--The majority of quality 
measurement tools used in our quality programs focus on utilizing 
existing claims and administrative data for Medicare beneficiaries. 
Using these existing data to assess disparity, for example by the use 
of dual enrollment for Medicare and Medicaid, allows for high impact 
analyses with negligible healthcare provider burden. There are, 
however, limitations in these data's usability for stratification 
analysis. CMS's current administrative race and ethnicity data have 
been shown to have historical inaccuracies due to limited collection 
classifications and attribution techniques, and are generally 
considered not to be accurate enough for stratification and disparity 
analyses.\386\ International Classification of Diseases, 10th Revision 
(ICD-10) codes for socioeconomic and psychosocial circumstances (``Z 
codes'' Z55 to Z65) represent an important opportunity to document 
patient-level social risk factors in Medicare beneficiaries, however, 
they are rarely used in clinical practice, limiting their usability in 
disparities measurement.\387\ If the collection of social risk factor 
data improves in administrative data, we will continue to evaluate its 
applicability for stratified reporting in the future.
---------------------------------------------------------------------------

    \386\ Jarr[iacute]n OF, Nyandege AN, Grafova IB, Dong X, Lin H. 
(2020). Validity of race and ethnicity codes in Medicare 
administrative data compared with gold-standard self-reported race 
collected during routine home health care visits. Med Care, 
58(1):e1-e8. doi: 10.1097/MLR.0000000000001216. PMID: 31688554; 
PMCID: PMC6904433.
    \387\ Centers for Medicare & Medicaid Services, Office of 
Minority Health. (2021). Utilization of Z codes for social 
determinants of health among Medicare fee-for-service beneficiaries, 
2019. Available at: https://www.cms.gov/files/document/z-codes-data-highlight.pdf.
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    Dual eligibility is a widely used proxy for low socioeconomic 
status and is an exception to the previously discussed limitations, 
making it an effective indicator for worse outcomes due to low 
socioeconomic status. The use of dual eligibility in social risk factor 
analyses was supported by ASPE's First and Second Reports to 
Congress.388 389 These reports found that in the context of 
VBP programs, dual eligibility, as an indicator of social risk, was 
among the most powerful predictor of poor health outcomes among those 
social risk factors that ASPE examined and tested.
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    \388\ Office of the Assistant Secretary for Planning and 
Evaluation. (2016). Social risk factors and performance under 
Medicare's value-based purchasing programs. Available at: https://aspe.hhs.gov/reports/report-congress-social-risk-factors-performance-under-medicares-value-based-purchasing-programs.
    \389\ Office of the Assistant Secretary For Planning and 
Evaluation. (2020). Report to Congress: Social Risk Factors and 
Performance Under Medicare's Value-Based Purchasing Programs. 
Available at: https://aspe.hhs.gov/reports/second-report-congress-social-risk-medicares-value-based-purchasing-programs.
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     Area-based Indicators of Social Risk Information and 
Patient Demographics--Area-based indicators pool area-level information 
to create approximations of patient risk or describe the neighborhood 
or context that a patient resides in. Popular among them are the use of 
the American Community Survey (ACS), which is commonly used to 
attribute social risk to populations at the ZIP code or Federal 
Information Processing Standards (FIPS) county level. Several indices, 
such as the Agency for Healthcare Research and Quality (AHRQ) 
Socioeconomic Status (SES) Index,\390\ Centers for Disease Control and 
Prevention/Agency for Toxic Substances and Disease Registry Social 
Vulnerability Index (CDC/ATSDR SVI),\391\ and Health Resources and 
Services Administration Area Deprivation Index,\392\ combine multiple 
indicators of social risk into a single score which can be used to 
provide multifaceted contextual information about an area and may be 
considered as an efficient way to stratify measures that include many 
social risk factors.
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    \390\ Bonito A., Bann C., Eicheldinger C., Carpenter L. (2008). 
Creation of New Race-Ethnicity Codes and Socioeconomic Status (SES) 
Indicators for Medicare Beneficiaries. Final Report, Sub-Task 2. 
(Prepared by RTI International for the Centers for Medicare & 
Medicaid Services through an interagency agreement with the Agency 
for Healthcare Research and Policy, under Contract No. 500-00-0024, 
Task No. 21) AHRQ Publication No. 08-0029-EF. Rockville, MD, Agency 
for Healthcare Research and Quality.
    \391\ Flanagan, B.E., Gregory, E.W., Hallisey, E.J., Heitgerd, 
J.L., Lewis, B. (2011). A social vulnerability index for disaster 
management. Journal of Homeland Security and Emergency Management, 
8(1). Available at: https://www.atsdr.cdc.gov/placeandhealth/svi/img/pdf/Flanagan_2011_SVIforDisasterManagement-508.pdf.
    \392\ Center for Health Disparities Research. About the 
Neighborhood Atlas. Available at: https://www.neighborhoodatlas.medicine.wisc.edu/.
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     Imputed Sources of Social Risk Information and Patient 
Demographics--Imputed data sources use statistical techniques to 
estimate patient-reported factors, including race and ethnicity. In the 
case of race and ethnicity, indirect estimation improves upon imperfect 
and incomplete data by drawing on information about a person's name and 
address and the linkage of those variables to race and ethnicity. One 
such tool is the Medicare Bayesian Improved Surname Geocoding (MBISG) 
method (currently in version 2.1), which combines information from 
administrative data, surname, and residential location to estimate 
patient race and ethnicity.\393\ We have customized this tool for the 
Medicare population to improve our existing administrative data on race 
and ethnicity.
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    \393\ Haas A., Elliott M.N., Dembosky J.W., Adams J.L., Wilson-
Frederick S.M., Mallett J.S. et al. (2019). Imputation of race/
ethnicity to enable measurement of HEDIS performance by race/
ethnicity. Health Serv Res, 54(1):13-23. doi: 10.1111/1475-
6773.13099. Epub 2018 Dec 3. PMID: 30506674; PMCID: PMC6338295. 
Available at: https://pubmed.ncbi.nlm.nih.gov/30506674/.
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    The MBISG 2.1 method does not assign a single race and ethnicity to 
an individual; instead, it generates a set of six probabilities, each 
estimating how the individual would self-identify if provided with a 
set of racial and ethnic groups to choose from including: American 
Indian or Alaska Native, Asian or Pacific Islander, Black, Hispanic, 
Multiracial, and White. In no case would the estimated probability be 
used for making inferences about a specific beneficiary; only self-
reported data on race and ethnicity be used for that purpose. However, 
in aggregate, these results can provide insight and accurate 
information at the population level, such as the patients of a given 
hospital, or the members of a given plan. MBISG 2.1 is currently used 
by our Office of Minority Health (OMH) to undertake various analyses, 
such as comparing scores on clinical quality of care measures from the 
Healthcare Effectiveness Database and Information Set (HEDIS) by race 
and ethnicity for Medicare Part C/D health plans, and in developing a 
Health Equity Summary Score (HESS) for Medicare Advantage (MA) health 
plans.\394\
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    \394\ Agniel D., Martino S.C., Burkhart Q., Hambarsoomian K., 
Orr N., Beckett M.K, et al. (2021). Incentivizing excellent care to 
at-risk groups with a health equity summary score. J Gen Intern Med, 
36(7):1847-1857. doi: 10.1007/s11606-019-05473-x. Epub 2019 Nov 11. 
PMID: 31713030; PMCID: PMC8298664. Available at: https://pubmed.ncbi.nlm.nih.gov/31713030/.
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    While the use of area-based indicators and imputed data sources are 
not meant to replace efforts to improve patient-level data collection, 
we are considering how they might be used to begin

[[Page 49175]]

population-level disparity reporting of stratified measure results 
while being conscientious about data limitations.
    Imputed data sources, particularly when used to identify patient 
populations for measurement, must be carefully evaluated for their 
potential to negatively affect the populations being studied. For this 
reason, imputed data sources only be considered after a significant 
validation study has been completed, including evaluation by key 
stakeholders for face validity, and any calculations that incorporate 
these methods be continuously evaluated for the accuracy of their 
results and the necessity of their use. While neither imputed nor area-
level geographic data be considered a replacement for improved data 
collection, researchers have found their use to be a simple and cost-
efficient way to make general estimations of social risk at a community 
level.\395\ In place of patient-level information when it is not 
available, the combination of several sources of imputed or area-level 
data can provide actionable estimations of social risk of a population.
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    \395\ Bi, Q., He, F., Konty, K., Gould, L.H., Immerwahr, S., & 
Levanon Seligson, A. (2020). ZIP code-level estimates from a local 
health survey: Added value and limitations. Journal of Urban Health: 
Bulletin of the New York Academy of Medicine, 97(4), 561-567.
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5. Identification of Meaningful Performance Differences
    In examining potential ways to report healthcare disparity data, 
that is, the results of quality measure stratification, we expect to 
consider different approaches to identifying meaningful differences in 
performance. Stratified results can be presented in several ways to 
describe to providers how well or poorly they are performing, or how 
they perform when compared to other care facilities. For this reason, 
it is important to identify how best to present meaningful differences 
in performance for measures of disparity reporting. While we aim to use 
standardized approaches where possible, we also expect that decisions 
about how to identify meaningful differences in performance would 
ultimately be tailored to each individual program. We welcomed feedback 
on the benefits and limitations of the possible disparity reporting 
approaches we described in this RFI.
     Statistical Differences--When aiming to examine 
differences in disparities results among healthcare providers, the use 
of statistical testing can be helpful. There are many statistical 
approaches that can be used to reliably group results, such as using 
confidence intervals, creating cut points based on standard deviations, 
or using a clustering algorithm. Importantly, these approaches may 
result in groupings that are statistically different, but not 
meaningfully different depending on the distribution of results.
     Rank Ordering and Percentiles--Ordering healthcare 
providers in a ranked system is another option for reporting disparity 
results in a meaningful way. In this system, healthcare providers could 
be ranked based on their performance on disparity measures to quickly 
allow them to compare their performance to other similar healthcare 
providers. We may consider using an ordered system to report healthcare 
provider results by categorizing healthcare providers into groups, for 
example, into quintile or decile groups. This approach works well as a 
way for healthcare providers to easily compare their own performance 
against others; however, a potential drawback is that it does not 
identify the overall magnitude of disparity. For example, if a measure 
shows large disparity in care for patients based on a given factor, and 
that degree of disparity has very little variation between healthcare 
providers, the difference between the top and bottom ranked healthcare 
providers would be very small even if the overall disparity is large.
     Threshold Approach--A categorization system could also be 
considered for reporting disparity results. In this system, healthcare 
providers could be grouped based on their performance using defined 
metrics, such as fixed intervals of results of disparity measures, 
indicating different levels of performance. Using a categorized system 
may be more easily understood by stakeholders by giving a clear 
indication that outcomes are not considered equal. However, this method 
does not convey the degree of disparity between healthcare providers or 
the potential for improvement based on the performance of other 
healthcare providers. Furthermore, it requires a determination of what 
is deemed `acceptable disparity' when developing categories.
     Benchmarking--Benchmarking, or comparing individual 
results to, for example, state or national averages, is another 
potential reporting strategy. This type of approach could be done, 
especially in combination with a ranked or threshold approach, to give 
healthcare providers more information about how they compare to the 
average care for a patient group.
    Another consideration for each of these approaches is grouping 
similar care settings together for comparison through a peer grouping 
step, especially if a ranked system is used to compare healthcare 
providers. Some stakeholders have stated that comparisons between 
healthcare providers have limited meaning if the healthcare providers 
are not similar, and that peer grouping would improve their ability to 
interpret results. Overall, the value of peer grouping must be weighed 
against the potential to set different standards of meaningful 
disparity among different care settings.
6. Guiding Principles for Reporting Disparity Results
    Confidential reporting for a short period that is not followed by 
public reporting of the same measure data is one approach we have used 
for newly adopted measures in a CMS quality program to give healthcare 
providers an opportunity to become more familiar with calculation 
methods and to begin improvement activities before their measure 
results are publicly reported. Providing early results to healthcare 
providers is an important way to provide healthcare providers the 
information they need to design impactful strategies to reduce 
disparity. Public reporting is a statutory requirement in all of our 
quality programs. Public reporting provides all stakeholders with 
important information on healthcare provider quality, and in turn, 
relies on market forces to incentivize healthcare providers to improve 
and become more competitive in their markets.
    Payment accountability for performance is also statutorily required 
in some of our quality programs. Payment accountability refers to tying 
payment to the results of quality measure performance, and in general 
rewards better performance with higher payment rates. Payment 
accountability allows us to reward healthcare providers for having low 
disparity rates and performing well for vulnerable patient groups.
    We are exploring whether it would be prudent to first 
confidentially report all stratified measure results, where adopted 
into a quality reporting program, to give healthcare providers an 
opportunity to understand those results so they can begin to implement 
programs to reduce disparities before we report the results publicly.
    We also believe it is important to report stratified measure data 
alongside overall measure results. Review of both overall measure 
results along with stratified results can illuminate greater levels of 
detail about quality of care for subgroups of patients, providing

[[Page 49176]]

important information to drive quality improvement. Unstratified 
quality measure results address general differences in quality of care 
between healthcare providers and promote improvement for all patients, 
but unless stratified results are available, it may be unclear whether 
there are subgroups of patients that would benefit most from targeted 
quality improvement initiatives. Notably, even if overall quality 
measure scores were to improve, without identifying and measuring 
differences in outcomes between groups of patients, it could be 
impossible to track progress in reducing disparity between patients 
with and without heightened risk of poor outcomes due to social 
factors.
7. Solicitation of Comments
    The goal of this RFI was to describe key considerations in 
determining how to develop future policies around the use of measure 
stratification as one quality measurement tool to address healthcare 
disparities and advance health equity across our quality programs. This 
is important as a means of setting priorities and expectations for the 
use of stratified measure results.
    We invited general comments on the principles and approaches listed 
previously, as well as additional recommendations about disparity 
measurement or stratification guidelines suitable for overarching 
consideration across our quality programs. Specifically, we invited 
comment on:
     Overarching goals for measuring disparity that be 
considered across CMS quality programs, including the importance of 
pairing stratified results with overall measure results to evaluate 
gaps in care among groups of patients attributed to a given healthcare 
provider and comparison of care for a subgroup of patients across 
healthcare providers.
     Principles to consider for prioritization of measures for 
disparity reporting, including prioritizing stratification for: valid 
clinical quality measures; measures with established disparities in 
care; measures that have adequate sample size and representation among 
healthcare providers; and, measures that consider access and 
appropriateness of care.
     Principles to be considered for the selection of social 
risk factors and demographic data for use measuring disparities, 
include the importance of identifying new social risk factor and 
demographic variables to use to stratify measures. We also sought 
comment on the use of imputed and area-based social risk and 
demographic indicators for measure stratification when patient reported 
data are unavailable.
     Preferred ways that meaningful differences in disparity 
results can be identified or be considered.
     Guiding principles for the use and application of the 
results of disparity measurement such as providing confidential 
reporting initially.
    We received comments on these topics.
    Comment: Many commenters responded to the overarching goals for 
measuring disparity across CMS quality programs described in the RFI. 
In general, commenters supported the goals of measure stratification 
set out in the proposed rule and suggested that these efforts could 
lead to a better understanding of longitudinal, geographic and provider 
disparity trends. Commenters noted that stratification of applicable 
measures by social risk factors will support hospital decision making 
and encourage CMS to be more explicit in describing the relationship 
between stratification methods and the concept of ``health equity,'' as 
well as the implications of those views for the specific proposals 
being made. Commenters also suggested that these methods be designed to 
have the greatest impact possible on patient care and experience.
    Many commenters supported considering multiple approaches to 
measuring healthcare disparities, specifically, using the existing 
``within-provider'' and ``across-provider'' approaches included in the 
CMS Disparity Methods. Commenters supported the current use of dual-
eligibility for Medicare and Medicaid as a stratification variable, but 
suggested stratification by additional social risk factors and noted 
that appropriate considerations for confounding factors be accounted 
for.
    Many commenters urged that CMS consider any additional provider 
burden associated with disparity measurement and that CMS acknowledge 
the need to provide actionable, useful, consistent, valid, reliable, 
comparable, and robust measures and data. A commenter recommended that 
CMS establish consistent measures across CMS's various quality programs 
to reduce reporting burden and to enhance robustness of the data 
collected; however, other commenters agreed that approaches may need to 
be tailored to individual settings. Commenters expressed that there are 
many challenges in the implementation of stratified measure reporting 
and offered several comments and suggestions. Commenters noted the need 
for CMS to contextualize disparity results, the need for more resources 
for providers to address disparity results, and the potential utility 
of peer grouping especially when using approaches that compare 
performance across providers to allow for more `like to like' 
comparisons.
    A commenter suggested using performance thresholds and benchmarking 
for the entire patient population instead of performance threshold by 
subgroup like the ``across-provider'' approach.'' Another commenter 
suggested that, in order not to reward low-quality care, reductions in 
disparities be measured against total quality of care.
    A commenter noted that the inclusion of health equity as a 
strategic goal in the FY 2023 IPPS/LTCH PPS proposed rule assumes a 
meaningful relationship between the processes and outcomes of care at 
the inpatient hospital level and the broad measures of population 
health that are generally subsumed under the concept of ``health 
equity.'' The commenter encouraged CMS to be more explicit in 
describing its views of this relationship, and the implications of 
those views for the specific proposals being made.
    A few commenters opposed measure stratification or the direction of 
CMS's health equity efforts noting that ranking and comparing provider 
performance may lead to performance competition and gaming but may not 
result in improved care for patients. Another commenter noted that CMS 
could potentially create a healthcare provider ranking system based on 
the results of the nonmedical, social risk factors included in the 
stratification method but that this would be an unacceptable and 
inappropriate use of the healthcare system's resources.
    Response: We appreciate the feedback and suggestions provided by 
the commenters regarding overarching goals for measuring disparity 
across CMS quality programs; particularly, the importance of balancing 
the pursuit of meaningful impact with burden reduction in 
implementation. We will take commenters' feedback into consideration in 
future policy development.
    Comment: Several commenters emphasized the importance of avoiding 
measurement bias as a key goal for measuring disparity. Commenters 
expressed concerns that stratification, specifically when combined with 
the use of imputed data to identify demographic and social risk factors 
and variables, could lead to measurement bias, and potentially deepen 
inequities. Commenters recommended that CMS disclose methods and 
algorithms for imputed data to maintain consumer trust and confidence.

[[Page 49177]]

    Several commenters suggested that methods be introduced to adjust 
quality measures and measurement tools for patient social risk or race 
and ethnicity. These commenters noted that this is important to ensure 
that providers, such as safety-net hospitals, who care for large 
proportions of patients with social risk factors are not unfairly 
penalized under these performance metrics.
    Response: We appreciate the feedback and suggestions provided by 
the commenters regarding attention to the importance of avoiding 
measurement bias when stratifying measures in CMS programs. We will 
take commenters' feedback into consideration in future policy 
development.
    We would also like to clarify that the RFI does not directly 
address risk adjustment for patient social factors or demographic 
variables within measures, which may set different expected quality 
results for persons with certain social risk factors, but rather 
discusses approaches to distinguish performance between groups to 
highlight underlying disparities.
    Comment: Commenters responding to principles for the prioritization 
of measures for disparity reporting supported using existing clinical 
quality measures, particularly outcome measures and measures of access 
and appropriateness of care, as a guiding principle in selecting and 
prioritizing measures for quality reporting across CMS quality 
reporting programs.
    A commenter expressed support for the proposed prioritization of 
existing clinical quality measures for disparity stratification, 
particularly those classified as outcomes measures and measures of 
access and appropriateness of care, rather than developing entirely new 
disparity-focused measures. The commenter stated that this will limit 
any additional administrative burden for facilities to understand, 
implement, and report new quality measures while focusing on the most 
meaningful results for patients.
    A commenter appreciated CMS's efforts to test and validate these 
measures, though others cautioned the agency to balance reducing the 
burden of developing purpose-fit measures with potential problems or 
limitations in many existing measures and recommended that existing 
clinical measures be further reviewed and validated prior to 
implementation within CMS's reporting programs. Other commenters 
cautioned that individual measures' risk-adjustment methods must be 
assessed for their impact on disparity results.
    Many commenters supported using measures with identified disparity 
in treatment or outcomes for the selected social or demographic factor 
as a guiding principle in selecting and prioritizing measures for 
quality reporting across CMS quality reporting programs. A commenter 
urged CMS to prioritize measures that relate to the conditions in which 
the inequities are starkest. Another commenter cautioned that measures 
with known disparities in care be judged carefully--that is, that 
reporting disparity results must be actionable, and not just be 
descriptive of large disparities. Several additional topics and 
conditions were suggested for disparity measurement, including maternal 
morbidity and mortality, sickle cell disease, cancer, cardiovascular 
disease, chronic kidney disease and End-Stage Renal Disease.
    Response: We appreciate the feedback and suggestions provided by 
the commenters regarding the prioritization of quality measures for 
stratification; again, with particular appreciation for the importance 
of reducing burden in implementation. We will take commenters' feedback 
into consideration in future policy development.
    Comment: Many commenters commented on priorities for selecting 
measures for stratification particularly related to sample size and 
reliability of measures. They supported using measures with sufficient 
sample size to allow for reliable and representative comparisons to be 
made.
    Commenters noted that focusing on statistical reliability and 
representation meets two important criteria. First, the reportability 
and reliability of a measure will have an impact on how appropriate 
different types of reporting will be, and second, not reporting results 
for all providers due to statistical considerations risks drawing 
conclusions about disparity from an incomplete set of results. For 
example, disparity in hospitals with low sample sizes may not be 
calculated and reported, even if differences in care in this setting 
are the greatest. The commenters stated that unintended consequences of 
this approach could allow for disparities to go unnoticed in 
communities already historically disadvantaged and marginalized by the 
healthcare system.
    Commenters suggested that CMS consider innovative applications of 
statistical methodologies for the design and analysis of small sample 
data including: (1) Research designs and analytic methods that can 
maximize statistical power for analyses of interventions conducted with 
small, culturally distinct samples--including dynamic wait list 
research designs, Bayesian approaches, matching, imputation, or 
increasing look back periods, (2) strategies for reducing error and 
bias in measures applied in studies with culturally distinct samples 
such as the Rasch Measurement Model, and (3) use of qualitative methods 
and mixed methods combining qualitative and quantitative data.
    A commenter noted that statistical reliability and representative 
sampling are important but could prove difficult (depending on census 
composition) for facilities to maintain with fluctuating demographics 
and recommended that any representation standards be applied over the 
duration of the performance year to maximize the chance of capturing 
data on individuals with social risk factors.
    A commenter noted that while blending performance across years also 
encourages sustained high quality, pooling data across years could 
dampen a provider's drive to improve if their recent better results are 
blended with older, poorer performance. The commenter noted that in 
such a case, the provider's improved performance would not be fully 
recognized in its payment incentive payment for several years and 
suggested that, in order to counter this disincentive, CMS could 
consider weighting the more recent years more heavily or CMS could also 
pool data across years only for low-volume providers, while reporting 
just the most recent year's performance for providers that meet a 
minimum count in a single year.
    Response: We appreciate the feedback and suggestions provided by 
the commenters regarding sample size and representation in disparity 
analyses. We will take commenters' feedback into consideration in 
future policy development.
    Comment: Commenters on principles for prioritizing measurement 
suggested that measures be prioritized for stratification based on many 
criteria, such as identifying measures that: target the most high-value 
and impactful measures; meaningfully advance health equity or reduce 
healthcare disparities; provide a person-centered and holistic view of 
quality, including consideration of Social Drivers of Health (SDOH) and 
experience of care; provide meaningful and usable information, or are 
linked to an intervention; are tailored to specific community needs and 
socioeconomic circumstances that focus on improvements within those 
populations rather than exist as flat standards to meet; and, 
incentivize work on disparities reduction and improvement rather than 
penalize providers and

[[Page 49178]]

payers who serve more patients that are socially-disadvantaged.
    A commenter stated that CMS not prioritize measures for 
stratification based on the type of measure (for example, structure, 
process, outcome, access), but that CMS instead prioritize measures for 
stratification if disparities exist in these measures and they can be 
measured accurately and reliably. This commenter noted that while the 
trend has been towards prioritizing outcome and access measures, these 
measures are also highly susceptible to factors outside a provider's 
control.
    Response: We appreciate the feedback and suggestions provided by 
the commenters regarding prioritization of measures for disparity 
reporting. We will take commenters' feedback into consideration in 
future policy development.
    Comment: Commenters offered a variety of views regarding principles 
for social risk factor and demographic data selection and use in 
stratification. A commenter expressed support for CMS's ongoing work to 
collect and make data publicly available related to social risk factors 
that affect patient outcomes.
    Commenters agreed with the examples of social risk factors in the 
proposed rule (88 FR 28482 through 28483), including our current use of 
dual eligibility for Medicare and Medicaid as a social risk factor. 
Commenters also recommended that CMS use other financial risk factors 
in addition to dual eligibility, because the commenters believed that 
dual eligibility is better understood as a proxy for extreme financial 
risk.
    Commenters suggested that CMS work to enhance the use of SDOH Z-
codes for use in disparity reporting. that CMS work to enhance the 
capture of standardized data sets, and that CMS conduct research to 
identify the factors that have disproportionate impact on health 
outcomes and prioritize their collection. Commenters also suggested CMS 
review tools used to capture patient demographic and social risk 
factors that are validated and widely used but noted that ideally 
providers have the ability to choose the tool that best suit their 
patient population. Other commenters recommended that CMS explore using 
existing data, such as SSDOH Z-codes, before imposing new data 
reporting requirements.
    Commenters suggested the use of additional social risk factors such 
as broadband internet access, social isolation, vision, mental health 
status, immigration status, and health literacy. Commenters suggested 
using gender as a social risk factor (as well as a demographic 
variable).
    Commenters recommended that CMS explore using existing data before 
imposing new data reporting requirements.
    Response: We appreciate the feedback and suggestions provided by 
the commenters regarding selection of social risk factors to use for 
measure stratification. We will take commenters' feedback into 
consideration in future policy development.
    In addition we want to note that conceptually, equity related 
terms, such as ``health related social needs'', ``social determinants 
of health'', and ``social risk factors'' are all used to describe 
upstream factors that can adversely affect the health of individuals 
and communities (87 FR 28497). These terms are often conflated and used 
interchangeably and the variety of terms can create confusion, 
prompting some leaders in the field to adopt ``drivers of health'' 
instead. In the future, CMS is considering using ``drivers of health'' 
terminology to more holistically capture aforementioned and related 
concepts, while minimizing potential misinterpretation or negative 
connotation.
    Comment: Several commenters addressed the identification of new 
demographic variables. Many commenters agreed that the collection of 
race and ethnicity data as well as data regarding the other demographic 
variables discussed in the preamble of the proposed rule was needed and 
will be essential for tracking disparities as well as guiding the 
design and application of culturally specific public health approaches. 
A commenter suggested that CMS add tribal membership as a variable.
    Other comments suggested using current OMB race and ethnicity 
standards. A few commenters believed that CMS ensure collection of data 
on race and ethnicity, as well as certain other demographic data 
including patients' disability status, sexual orientation, gender 
identity, and physical and cogitative disabilities.
    A commenter believed that ``race'' and ``ethnicity'' are so overly 
broad, vague, and ill-defined that, even in combination with other 
indicators, they are unlikely to provide useful information and may 
even obscure individual experience to the detriment of individualized 
patient care.
    Some commenters supported using imputation, or estimation, methods 
for demographic variables. A commenter stated that CMS use strong, 
vetted algorithms for indirect/imputed data attribution. Another 
commenter noted that the indirect estimations as described in the 
proposed rule have very high predictiveness statistics and are often 
used in other facets of health research and analysis, including the 
annual report on Racial, Ethnic, & Gender Disparities in Health Care in 
Medicare Advantage. The commenter believed that these estimations are 
largely built on assumptions and that such algorithms often have issues 
with how race and ethnicity is defined and how the data are collected. 
Because self-reported race and ethnicity data are the gold standard and 
not be replaced with less reliable estimations, this commenter 
recommended that CMS move away from utilizing indirect estimations to 
collect race and ethnicity data and rather focus on efforts to promote 
collection of self-reported data in hospital settings.
    Some commenters did not support using estimated patient race and 
ethnicity. Several commenters believed that estimating an individual's 
race or ethnicity based on name and geography is inappropriate. A 
commenter expressed several specific concerns regarding CMS's potential 
use of the Medicare Bayesian Improved Surname Geocoding (MBISG) model 
to estimate race and ethnicity for the purpose of risk stratification, 
and recommended CMS review the Urban Institute's Design Thinking 
Workshop on the Ethics of Imputation and Related Methods and subsequent 
report, ``Five Ethical Risks to Consider before Filling Missing Race 
and Ethnicity Data.''
    Response: We appreciate the feedback and suggestions provided by 
the commenters regarding selection of demographic variables to use for 
measure stratification, and acknowledge the complexities involved in 
accurately capturing race, ethnicity, and other nuanced demographic 
information. While we will continue to explore rigorous estimation 
methods, we are committed to improving the collection and reporting of 
self-reported data as well as its use for risk stratification and other 
quality measurement purposes. We will take commenters' feedback into 
consideration in future policy development.
    Comment: Several commenters expressed appreciation for CMS's 
identification of systemic racism as a driver of inequitable health. A 
commenter believed that data analysis include proactive steps to 
explicitly name racism and longstanding structural racism as root 
causes of inequities when interpreting and communicating findings, and 
whenever possible, make clear that observed health inequities are not 
due to biological traits, gender identities or

[[Page 49179]]

other characteristics of ethnically and racially diverse individuals or 
groups.
    Commenters suggested CMS be wary of quality adjustment policies 
based on race or ethnicity due to the potential of measurement bias or 
other unintended consequences related to the implementation of well-
intentioned models that may be biased.
    Commenters believed that regular and ongoing implicit and explicit 
bias training for all healthcare team members is critical to addressing 
disparities and pursuing equity, and additional training will be 
necessary to support collecting patient-reported social risk and 
demographic data.
    Response: We appreciate the feedback and suggestions provided by 
the commenters regarding the identification of structural racism as a 
driver of inequitable health, and agree that addressing the impact of 
racism, bias, and other forms of discrimination must be centered in the 
pursuit of health equity across CMS quality programs. We will take 
commenters' feedback into consideration in future policy development.
    Comment: Commenters agreed with CMS that the availability of data 
on patient demographics and social risk factors is a crucial 
consideration when choosing variables to use for stratifying quality 
measures. Commenters agreed that patient self-reported data are 
preferred and are the gold standard because they are the most accurate 
and reflect a patient-centered focus; however, many clinicians already 
find it difficult to collect this information from their patients due 
to workflow issues, resource constraints, and the reluctance of some 
patients to self-report demographic and social risk data.
    Commenters offered suggestions regarding how to improve data self-
reporting. Commenters suggested CMS consider opportunities for consumer 
education and notification on the importance of self-reported data, and 
that any entities that will be collecting and using these data also be 
prepared to address the privacy and security of the data.
    Commenters noted the difficulty in collecting patient data. A 
commenter recommended that CMS consider how it can support hospitals 
and other providers to improve the collection of patient self-reported 
social risk and demographic data, potentially by working with 
stakeholders to identify and share best practices on consumer-centered 
data collection approaches and workflows to expand and improve 
available options for demographic and social risk data collection. The 
commenter also recommended that CMS make efforts to ensure the data can 
be collected and reported efficiently and without undue burden.
    A commenter stated that while that patient-level data remain the 
gold standard, depending on the proposed application, imputed data 
could have some potential utility to fill gaps in availability. The 
commenter expressed reluctance to support the use of imputed indices 
with approaches like risk adjustment, peer grouping, and other 
comparative performance applications unless CMS tests their use on 
specific measures and scoring methodologies.
    Several commenters expressed some support for the use of the Health 
Resources and Services Administration Area Deprivation Index (ADI). A 
commenter stated that tools like the ADI have shown some utility and 
are worth consideration, but that the literature is less clear on the 
validity and utility of imputing individual race, ethnicity, or other 
variables. Commenters suggested that CMS avoid public reporting of 
disparity reports that use imputed data sources because this could 
unintentionally introduce measurement bias or discourage patients from 
selecting providers that care for patients in communities that have 
been marginalized.
    Commenters urged that CMS adopt and endorse the Office of the 
National Coordinator for Health Information Technology's (ONC's) 2015 
Edition standards for collecting disaggregated data for all hospitals 
and for all CMS quality programs. A commenter noted that the ONC's 2015 
Edition Health Information Technology Certification Criteria Final 
Rule, the ``2015 Edition'' establishes HIT certification requirements 
that include full disaggregation of race and ethnicity, language, 
sexual orientation, gender identity, and social and behavioral risk 
factors.
    Response: We appreciate the feedback and suggestions provided by 
the commenters regarding the availability of social risk and 
demographic data for use in stratified reporting. We especially 
recognize the importance of establishing and sustaining trust in the 
collection of such data to ensure both patients and providers 
understand intentions for its use and opportunities for impact. We will 
take commenters' feedback into consideration in future policy 
development.
    Comment: Commenters had significant feedback on ways to identify 
meaningful performance differences in stratified disparity results. 
Commenters suggested that CMS work to develop metrics for measuring 
specific disparities and requested that CMS perform analyses with 
various reporting approaches--including statistical differences, rank 
ordering and percentiles, threshold, and benchmarking. A commenter also 
stated that the field needs to develop science and analytics to 
understand if a difference in performance on a given measure is a true 
disparity in care that is statistically significant. A commenter 
recommended that CMS conduct analyses to compare the results of 
different methods for identifying meaningful differences and publish 
the results of these analyses for stakeholder review and public 
comment.
    A commenter stated that the identification of ``meaningful,'' 
included at least two major concepts--one is clinical importance 
(including lives saved, quality-adjusted life years gained, numbers of 
patients affected) and the other is size of disparity. The commenter 
suggested that not all available healthcare ``performance'' measures 
truly reflect performance by the measured entities in a clear and 
meaningful way and that this is particularly the case for many outcome 
measures that focus on endpoints removed both in time and location from 
the hospital providing care.
    A few commenters recommended that CMS create a minimum threshold of 
acceptability from a statistical standpoint that defines what would 
constitute a disparity. More specifically, a commenter suggested that 
CMS adopt and use metrics for which success is not solely based on 
percentage point improvement as this may incentivize bias in the 
selection of members and inappropriately reward efforts that have 
minimal actual impact on population-level disparities in care.
    The majority of commenters did not support rank orderings and 
percentiles, while a commenter cautioned that particular care is 
required with these approaches to avoid unintentional harm and another 
commenter agreed with CMS's recommendation that many approaches be 
considered. A commenter stated that rankings, or ordering, particularly 
when it impacts reimbursement, may lead to unintended consequences 
specifically when these are in large part due to factors outside the 
provider's control. These commenters believe that using these 
approaches will likely defeat the purpose of an evolving disparity 
effort in a quality program.
    Commenters had mixed feedback on the threshold approach. Some 
commenters supported it because it uses statistical testing as to 
whether a hospital is significantly better, no different, or worse than 
a national

[[Page 49180]]

threshold or benchmark, while other commenters suggested it will not 
adequality highlight differences between groups that do not account for 
the error associated with performance estimates. A commenter stated 
that this approach may identify differences that are not practically 
meaningful, and it also places significant burden on CMS to determine 
an appropriate or acceptable level of performance.
    A commenter recommended that CMS prioritize methods for the 
identification of meaningful performance differences that include a 
combination of approaches, such as peer grouping, benchmarking, and 
using a measure of statistical significance.
    A commenter noted that benchmarking, depending on how it is 
applied, may also be effective and that relying on statistical 
differences is not enough. A commenter noted that with time, and 
maturity, national or state benchmarking could become a key tool for 
helping providers understand and contextualize their own performance in 
relation to that of their peers. A commenter recommended that if 
benchmarking is pursued, that it not be done using national or state 
averages, but rather comparing like facilities or communities. Another 
commenter noted that benchmarking may mask local or regional 
differences in patient populations and resource access, inadvertently 
penalizing providers serving communities that are some of the most 
under-resourced and historically marginalized across the country.
    Several commenters suggested that across-hospital comparisons and 
comparisons of within-hospital results be done individually by hospital 
types or peer groups, to give more fair comparisons. A commenter 
suggested that peer hospitals could be identified based on patient 
demographic profile, payer mix, dual-eligible percentage, geographic 
location (urban vs. rural), and/or bed size.
    Response: We appreciate the feedback and suggestions provided by 
the commenters regarding the availability of social risk and 
demographic data for use in stratified reporting, and particularly 
acknowledge the implications stratification approaches may have on 
provider responsibility and accountability. We will take commenters' 
feedback into consideration in future policy development.
    Comment: Many commenters provided feedback on the proposed guiding 
principles for the use and application of the results of disparity 
measurement on reporting strategies for stratified measure results. In 
general, commenters supported confidential reporting for a short 
period, although they provided mixed feedback on the appropriateness of 
public reporting.
    Commenters offered several suggestions concerning whether public 
reporting occur. Some commenters urged CMS to refrain from public 
reporting measures with stratified data. A commenter suggested that 
some measures may be important for internal quality improvement but may 
not be appropriate for public reporting. Other commenters suggested 
that stratified measures that contained imputed data, or area-based 
data, not be publicly reported while others expressed concerns about 
whether the data would be misunderstood by patients and the public. 
Some commenters noted that public reporting could lead to unintended 
consequences, for example, the perpetuation of stereotypes about the 
type of care provided by the hospital or its providers to certain 
groups of patients or patient selection bias.
    A commenter stated that in its modeling of value incentive 
programs, it concluded that there is a need for better measures of 
patient social risk than are currently available. This commenter also 
recognized that another approach to capture beneficiary social risk 
would be to use area-level measures of social risk.
    A commenter outlined another potential unintended consequence as 
discouraging more resourced patients from receiving care at hospitals 
with poor disparity scores, which may not necessarily be indicative of 
the quality of care the hospital provides. The commenter noted that 
this could contribute to deepening resource inequity for patients who 
rely on safety net hospitals. Another commenter requested that CMS 
provide resources and support to help hospitals and providers 
interpret, understand, and act upon any stratified data provided to 
them, which may support less resourced hospitals and discourage this 
type of gaming.
    Other commenters agreed with a period of confidential reporting, 
followed by public reporting, and offered several suggestions as to 
when public reporting begin. Several commenters suggested that public 
reporting not begin until: complete, accurate and up-to-date data 
become available; there is a review and correction period; disparity 
reports are validated; or, there are risk adjustments.
    Many commenters supported moving to public reporting of stratified 
measure results. They noted that public reporting enable comparisons of 
individual providers with state and national averages to give consumers 
meaningful reference points and that quality improvement activities, 
through public reporting, would allow patients and their family members 
to make more informed health care decisions and health care provider 
choices. A few commenters noted that if information about disparities 
is made public, health insurance providers and health plans would be 
better able to understand which health care providers in their networks 
were taking meaningful action to improve health equity.
    Commenters expressed concerns that public reporting, which included 
demographic data derived using imputed methodology, was less accurate 
than self-reported data and therefore could lead to measure bias. A 
commenter expressed concerns regarding the privacy implications under 
the HIPAA of public disclosure of self-reported data and how it might 
affect patients' willingness to self-report these data. Other 
commenters believed that stratified measures not be publicly reported 
because, in their view, public reporting of stratified measures would 
not add value for consumers, who generally select providers based on 
proximity, insurance coverage, provider referral, and recommendations 
from family and friends, among other criteria.
    Response: We appreciate the feedback and suggestions proposed 
guiding principles for the use and application of the results of 
disparity measurement on reporting strategies for stratified measure 
results, including the importance of ensuring that both patients and 
providers are given the tools and resources to adequately interpret 
these results. We will take commenters' feedback into consideration in 
future policy development.
    Comment: Many commenters supported CMS's goal of advancing health 
equity. Many commenters also supported CMS's efforts to measure 
healthcare disparities and report these results to healthcare providers 
and to use quality measures stratified by demographic variables and 
social risk factors as a part of these efforts. Commenters also 
supported CMS's efforts to improve data collection as a part of its 
health equity efforts.
    Commenters suggested that CMS establish feedback loops to ensure 
health equity quality measures keep up with evolving practices in the 
field and measurement science, consider using a Technical Expert Panel 
or other mechanism to advise it on this process, and partner with other 
organizations as it continues to refine its principles so

[[Page 49181]]

that any unintended consequences of this work are identified and 
avoided.
    A commenter recommended expanding health equity efforts to other 
settings such as outpatient hospital and ambulatory surgical centers. 
Commenters also suggested measures be selected and prioritized that: 
can be impacted by an intervention; protect the safety net; are within 
the locus of control of the measured entity; minimize burden; and, 
strike a balance between innovation and feasibility.
    Response: We appreciate the general feedback and suggestions 
provided by the commenters regarding stratified reporting. We are 
committed to continued transparency in the reporting of performance, 
particularly with regards to achievement on health equity goals, to 
providers and to the patients they serve. This commitment extends 
across hospitals and to all other providers and care settings 
participating in CMS quality programs. We will take commenters' 
feedback into consideration in future policy development.

C. Continuing To Advance to Digital Quality Measurement and the Use of 
Fast Healthcare Interoperability Resources (FHIR) in Hospital Quality 
Programs--Request for Information

    In the FY 2022 IPPS/LTCH PPS final rule, we stated the aim to move 
fully to digital quality measurement in CMS quality reporting and 
value-based purchasing programs (86 FR 45342). As part of this 
modernization of our quality measurement enterprise, we issued this RFI 
to gather broad public input on the transition to digital quality 
measurement. Any updates to specific program requirements related to 
providing data for quality measurement and reporting provisions would 
be addressed through future notice-and-comment rulemaking. In the FY 
2023 IPPS/LTCH PPS proposed rule, we discussed this RFI which contains 
five parts (87 FR 28486 through 28489):
     Background. This part provides an overview of our goals 
and strategies to achieve digital quality measurement, and notes input 
and learnings relevant to these goals and strategies.
     Refined definition of Digital Quality Measures (dQMs). 
This part outlines potential revisions for a future definition for 
dQMs.
     Data Standardization Activities to Leverage and Advance 
Standards for Digital Data. This part discusses data standardization 
strategies and potential venues for advancing data standardization.
     Approaches to Achieve FHIR[supreg] eCQM Reporting. This 
part describes activities we are undertaking and considering to achieve 
FHIR-based electronic clinical quality measure (eCQM) reporting (for 
example, via FHIR APIs) as our initial implementation of dQMs.
     Solicitation of Comments. This part lists all requests for 
input included in the sections of this RFI.
1. Background
    In the FY 2022 IPPS/LTCH PPS final rule, we noted the continued 
focus on use of digital data and advancements in technology and 
technical standards to improve interoperability of healthcare data 
which creates opportunity to significantly improve our quality 
measurement systems (86 FR 45342). In a learning health system, 
standardized and interoperable digital data from a single point of 
collection can support multiple use cases, including quality 
measurement, quality improvement efforts, clinical decision support, 
research, and public health. We believe data used for quality 
measurement, as well as these other use cases, be a seamless outgrowth 
of data generation from routine workflows. Data sharing be standards-
based to maximize interoperability, minimize burden, and facilitate the 
development and use of common tooling across use cases. This approach 
supports data analysis, rapid-cycle feedback, and quality measurement 
that are aligned for continuous improvement in patient-centered care.
    We are continuing to define how we can leverage existing policy to 
transform all CMS quality measurement to digital reporting, such as 
policy finalized in the ONC 21st Century Cures Act final rule (85 FR 
25642). In that rule, ONC finalized a ``Standardized API for Patient 
and Population Services'' certification criterion (45 CFR 
170.315(g)(10)) for certified health information technology (IT) 
requiring the use of FHIR Release 4 and several other implementation 
specifications. Health IT certified to this criterion will offer single 
patient and multiple patient services that can be accessed by third 
party applications (85 FR 25742). The ONC 21st Century Cures Act final 
rule (85 FR 25642) also required health IT developers to update their 
certified health IT to support the United States Core Data for 
Interoperability (USCDI) standard, Version 1.\396\ By aligning 
technology requirements for payers, healthcare providers, and health IT 
developers, HHS can advance an interoperable health IT infrastructure 
that ensures providers and patients have access to health data when and 
where it is needed.
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    \396\ https://www.healthit.gov/isa/united-states-core-data-interoperability-uscdi.
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    In the FY 2022 IPPS/LTCH PPS final rule, we outlined actions in 
four areas to transition to digital quality measures: (1) leverage and 
advance standards for digital data and obtain all electronic health 
record (EHR) data required for quality measures via provider FHIR-based 
application programming interfaces (APIs); (2) redesign our quality 
measures to be self-contained tools; (3) better support data 
aggregation; and (4) work to align measure requirements across our 
reporting programs, other Federal programs and agencies, and the 
private sector where appropriate (86 FR 45342). The actions are further 
described in CMS' Digital Quality Measurement Strategic Roadmap 
available at: https://ecqi.healthit.gov/dQM. In this RFI, we focused on 
data standardization activities related to leveraging and advancing 
standards for digital data and approaches to transition to FHIR eCQM 
reporting in the future, as initial steps in our transition to digital 
quality measurement.
    In the FY 2022 IPPS/LTCH PPS final rule, we also stated our goal of 
moving to digital quality measurement for all CMS quality reporting and 
value-based purchasing programs (86 FR 45342). In the FY 2023 IPPS/LTCH 
PPS proposed rule (87 FR 28487), we further clarified that we plan to 
transition incrementally, beginning with the uptake of FHIR API 
technology and shifting to eCQM reporting using FHIR standards as 
described subsequently in section IX.C.4. of the preamble of the 
proposed rule. We aim to achieve a quality measurement system fully 
based on digital measures. The goals of a fully digital measurement 
system include: Reduced burden of reporting; provision of multi-
dimensional data in a timely fashion, rapid feedback, and transparent 
reporting of quality measures; digital measures leveraged for advanced 
analytics to define, measure, and predict key quality issues; and 
quality measures that support development of a learning health system, 
which uses key data that are also used for care, quality improvement, 
public health, research, etc.
2. Refined Definition of Digital Quality Measures (dQMs)
    In the FY 2022 IPPS/LTCH PPS final rule, we sought to define a dQM 
as software that processes digital data to produce a measure score or 
measure scores (86 FR 45342). In the FY 2023 IPPS/LTCH PPS proposed 
rule (87 FR 28487), based on feedback regarding

[[Page 49182]]

confusion by the term ``software,'' we further clarified that dQMs are 
quality measures, organized as self-contained measure specifications 
and code packages, that use one or more sources of health information 
that is captured and can be transmitted electronically via 
interoperable systems. We continue to note data sources for dQMs may 
include administrative systems, electronically submitted clinical 
assessment data, case management systems, EHRs, laboratory systems, 
prescription drug monitoring programs (PDMPs), instruments (for 
example, medical devices and wearable devices), patient portals or 
applications (for example, for collection of patient-generated data 
such as a home blood pressure monitor, or patient-reported health 
data), health information exchanges (HIEs) or registries, and other 
sources. We are currently considering how eCQMs, which use EHR data, 
can be refined or repackaged to fit within the dQM umbrella. While 
eCQMs meet the definition for dQMs in many respects, limitations in 
data standards, requirements, and technology have limited their 
interoperability. In the current state, there are multiple standards 
that must be supported (for example, Health Quality Measurement Format 
(HQMF) \397\ and Quality Reporting Document Architecture (QRDA) \398\) 
for eCQM data collection and reporting. Mapping EHR data can be 
challenging and burdensome for providers as there is often novel data 
collection occurring to support quality measurement. For example, eCQMs 
require steps to map data elements from the EHR to the appropriate 
format. Future dQMs would leverage interoperability standards to 
decrease mapping burden and align standards for quality measurement 
with interoperability standards used in other healthcare exchange 
methods.
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    \397\ https://www.hl7.org/implement/standards/product_brief.cfm?product_id=97.
    \398\ https://ecqi.healthit.gov/qrda.
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    We sought comment on this refined definition of dQMs and feedback 
on potential considerations or challenges related to non-EHR data 
sources.
3. Data Standardization Activities To Leverage and Advance Standards 
for Digital Data
    As noted in the FY 2022 IPPS/LTCH PPS final rule (86 FR 45342), we 
are considering implementing eCQM quality reporting via FHIR-based APIs 
based on standardized, interoperable data. Advancing data 
standardization is a critical step for this implementation, and for 
long-term digital measurement strategies. Utilizing standardized data 
for EHR-based measurement (based on the FHIR standard) and aligning 
where possible with other interoperability requirements can reduce the 
data collection burden incurred by providers for the purpose of 
reporting quality measures and supports achieving the goals of 
transitioning to a fully digital quality measurement system identified 
in section IX.C.1. previously, including provision of timely feedback, 
leveraging the same data for multiple use cases, and contributing to a 
learning health system.
    We intend to utilize standardized data for quality measurement as 
one use case of digital data in a learning health system. In a learning 
health system, standardized digital data can support multiple use 
cases, including quality measurement, quality improvement efforts, 
clinical decision support, research, and public health. We believe that 
standardization across data elements and data models is necessary to 
ensure data are accessible across use cases and enable the transmission 
of data through each stage of the health system's learning process. 
Standardized data and FHIR APIs are important for advancing 
interoperability; the goal is for data to be sent and received via 
trusted exchanges, and for patients to have access to their data. 
Operations activities (for example, prior authorization) are also 
dependent on standardized, interoperable data. Additionally, 
standardization is necessary across implementation guides, or rules for 
how a particular interoperability standard be used,\399\ and across 
value sets that organize the specific terminologies and codes that 
define clinical concepts.\400\
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    \399\ Resource Implementation Guide--Content. Available at: 
https://www.hl7.org/fhir/implementationguide.html.
    \400\ National Library of Medicine, Value Set Authority Center. 
Available at: https://vsac.nlm.nih.gov/.
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    Commenters on the RFI in the FY 2022 IPPS/LTCH PPS proposed rule 
encouraged the use of data elements for quality measurement that are 
consistent with ONC's USCDI standard,\401\ where possible. We agree 
with this approach. To advance the use of standardized data, models, 
implementation guides, and value sets in quality measurement, we 
continue to focus on leveraging the interoperability data requirements 
for standardized APIs in certified health IT, set by the ONC 21st 
Century Cures Act final rule and any future updates made in rulemaking, 
as a vehicle to support modernization of CMS quality measure reporting. 
These API requirements are being implemented as part of a series of 
updates to certified health IT (85 FR 84825), and include availability 
of data included in the USCDI via standards-based APIs. In the CY 2021 
Physician Fee Schedule final rule, we finalized that eligible 
clinicians and eligible hospitals and CAHs participating in the Merit-
based Incentives Payment System (MIPS) and the Medicare Promoting 
Interoperability Program, respectively, must transition to use of 
certified technology updated consistent with the 2015 Edition Cures 
Update by 2023 (85 FR 84825). We aim to align with these standardized 
data requirements as the basis for data used in quality measurement.
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    \401\ https://www.healthit.gov/isa/united-states-core-data-interoperability-uscdi.
---------------------------------------------------------------------------

    We are collaborating with federal agencies to define and prioritize 
additional data standardization needs and develop consensus with 
federal partners on recommendations for future versions of the USCDI. 
We are also directly collaborating with ONC to build requirements to 
support data standardization and alignment with requirements for 
quality measurement. ONC recently launched the USCDI+ initiative 
focused on supporting identification and establishment of domain 
specific datasets that build on the USCDI foundation.\402\ A USCDI+ 
quality measurement domain currently being explored could support 
defining additional data specifications for quality measurement that 
harmonize, where possible, with other federal agency data needs and 
inform supplemental standards necessary to support quality measurement.
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    \402\ USCDI+. Available at: https://www.healthit.gov/topic/interoperability/uscdi-plus.
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    We also received feedback on the RFI in the FY 2022 IPPS/LTCH PPS 
proposed rule that the use of Health Level Seven (HL7[supreg]) 
Implementation Guides are foundational to FHIR measure reporting. To 
advance implementation of standardized data, we continue to collaborate 
with consensus standards-setting bodies such as HL7. We are considering 
how best to leverage existing implementation guides that are routinely 
updated and maintained by HL7 to define data standards and exchange 
mechanisms for FHIR-based dQMs, in a fashion that supports the learning 
health system and alignment across use cases, including the following 
existing HL7 Implementation Guides:
     US Core Implementation Guide; \403\
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    \403\ HL7 FHIR US Core Implementation Guide. Available at: 
https://hl7.org/fhir/us/core/.

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[[Page 49183]]

     Quality Improvement Core (QI Core) Implementation Guide; 
\404\
---------------------------------------------------------------------------

    \404\ HL7 FHIR QI Core Implementation Guide. Available at: 
https://hl7.org/fhir/us/qicore/.
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     Data Exchange for Quality Measures (DEQM) Implementation 
Guide; \405\ and
---------------------------------------------------------------------------

    \405\ HL7 Data Exchange For Quality Measures. Available at: 
https://hl7.org/fhir/us/davinci-deqm/.
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     Quality Measure (QM) Implementation Guide.\406\
---------------------------------------------------------------------------

    \406\ HL7 Quality Measure Implementation Guide. Available at: 
https://hl7.org/fhir/us/cqfmeasures/.
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    We are also considering what, if any, additional CMS-specific 
implementation guides may be necessary to support future digital 
quality measurement such as guidance on aggregation mechanisms for 
reporting.
    We recognize the importance of considering how implementation 
guides used across quality measurement and other use cases (for 
example, public health reporting, clinical decision support) work 
together to support a learning health system. For example, the Clinical 
Guidelines (CPG) Implementation Guide \407\ connects computable 
guidelines, clinical decision support, quality reporting, and case 
reporting. The mechanisms for reporting across use cases are also 
critical to consider, as each time a different mechanism for reporting 
is needed across different use cases, it creates more burden. We are 
collaborating closely with federal partners, such as the Centers for 
Disease Control and Prevention (CDC), to align where possible.
---------------------------------------------------------------------------

    \407\ HL7 FHIR Clinical Guidelines Implementation Guide. 
Available at: https://hl7.org/fhir/uv/cpg/.
---------------------------------------------------------------------------

    We believe developing appropriately defined implementation guides 
will be a key component of supporting standardized FHIR APIs that 
enable access to standardized data elements for particular use cases, 
such as quality measurement.
    We sought comment on the specific Implementation Guides noted 
previously, additional implementation guides to consider, and other 
data and reporting components (for example, data vocabulary/
terminology, alignment with other types of reporting) where 
standardization may be considered to advance data standardization for a 
learning health system.
4. Approaches to Achieve FHIR eCQM Reporting
    We previously noted in the FY 2022 IPPS/LTCH PPS final rule (86 FR 
45342) activities we are conducting to begin structuring and reporting 
eCQMs using FHIR. eCQMs are a subset of dQMs. We consider the 
transition to FHIR-based eCQM reporting the first step to dQM 
reporting, and a potential model for how future digital reporting can 
occur.
    To support the transition, we continue to undertake and consider 
activities necessary for reporting of FHIR-based eCQMs and future dQMs:
     In the near term, we plan to continue to convert current 
Quality Data Model (QDM)-based eCQMs to the FHIR standard and test the 
implementation of measures respecified to FHIR and submission of data 
elements represented in FHIR through ongoing HL7 Connectathons.
     In the near term, we also plan to develop a unified CMS 
FHIR receiving system. This system would allow for a singular point of 
data receipt to be used for quality reporting requirements, and 
modernization of programmatic data receiving systems to leverage 
opportunities related to digital data.
     We are committed to working with implementers and partners 
to optimize interoperable data exchange to support FHIR-based eCQM 
reporting (for example, via FHIR APIs) and eventually other dQMs, while 
ensuring solutions and implementations that require patients to engage 
with technology that also support health equity.
     In the near term, we plan to identify opportunities for 
the public to provide feedback on FHIR-based measure specifications 
prior to implementation, such as during measure development/conversion 
activities.
     We also plan to identify opportunities for collaboration 
with vendors and implementers via systems testing of FHIR-based eCQM 
reporting to ensure involvement in systems development.
     Finally, we are exploring venues for continued feedback on 
CMS future measurement direction and data aggregation approaches in 
anticipation of FHIR-based API reporting of eCQMs.
     To support both near term FHIR-based eCQMs and other 
future dQMs, as noted in section IX.C.3., we intend to continue 
engaging with standards development organizations to advance and 
maintain implementation guides to support the FHIR standard and API 
reporting of quality measures.
     We also anticipate that prior to the implementation of any 
mandatory FHIR-based eCQM reporting requirements within our quality 
programs, it would be necessary to undertake voluntary reporting of 
FHIR-based eCQMs to allow time to learn and enhance systems and 
processes, both internally and among providers and vendors.
    We also continue to consider how best to leverage the FHIR API 
technology implemented to meet ONC's interoperability requirements to 
access and electronically transmit interoperable data for quality 
measurement. Based on feedback on the FY 2022 IPPS/LTCH PPS proposed 
rule RFI, many supported the use of FHIR APIs, while others expressed 
concern around infrastructure readiness. We continue to explore how to 
leverage FHIR APIs to decrease reporting burden and support implementor 
readiness. We sought comment on approaches to optimize data flows for 
quality measurement to retrieve data from EHRs via FHIR APIs, and to 
combine data needed for measure score calculation for measures that 
require aggregating data across multiple providers (for example, risk-
adjusted outcome measures) and multiple data sources (for example, 
hybrid claims-EHR measures). We were interested in data flows that 
support using the same data for measurement and to provide feedback to 
providers at multiple levels of accountability, such as at the 
individual clinician, group, accountable care organization and health 
plan levels, as are used for patient care and other use cases (for 
example, public health reporting).
    We sought comment on additional venues to engage with implementors 
during the transition to digital quality measurement, and other 
critical considerations during the transition. We also sought comment 
on data flow options to support FHIR-based eCQM reporting.
5. Solicitation of Comments
    As noted previously, we sought input on the following:
     Refined potential future Definition of dQMs. We sought 
feedback on the following as described in section IX.C.2.:
    ++ Do you have feedback on the potential refined definition of 
digital quality measures (dQMs)?
    ++ Do you have feedback on potential considerations or challenges 
related to non-EHR data sources?
     Data Standardization Activities to Leverage and Advance 
Standards for Digital Data. We sought feedback on the following as 
described in section IX.C.3.:
    ++ Do you have feedback on the specific implementation guides we 
are considering, additional FHIR implementation guides we consider, or 
other data and reporting components where standardization be considered 
to advance data standardization for a learning health system?
     Approaches to Achieve FHIR eCQM Reporting. We sought 
feedback on the following as described in section IX.C.4.:

[[Page 49184]]

    ++ Are there additional venues to engage with implementors during 
the transition to digital quality measurement?
    ++ What data flow options we consider for FHIR-based eCQM 
reporting, including retrieving data from EHRs via FHIR APIs and other 
mechanisms?
    ++ Are there other critical considerations during the transition?
    We received several comments on these topics.
    Comment: There was widespread support among commenters for CMS' 
efforts to transition to digital quality measurement and support for 
leveraging the FHIR standard and FHIR APIs. A couple of commenters 
pointed out that improved electronic health record (EHR) 
interoperability for the exchange and use of electronic health data 
holds great promise to not only improve quality measurement and patient 
outcomes, but also to reduce burden on providers. A commenter noted 
that dQMs are a critical component of a fully interoperable learning 
health system that generates knowledge beyond the quality reporting use 
case, and suggested CMS make this clear in its transition plans. A 
commenter supported CMS's iterative approach to transition quality 
reporting programs to the use of dQMs and the FHIR standard. Another 
commenter noted that leveraging EHRs for dQM must not interfere, delay, 
or hinder patient care. While there was general support for use of the 
FHIR standard, a few commenters noted the standard was not yet fully 
mature, and a commenter recommended allowing for flexibility in 
standards used, focusing on a set of standards rather than using only 
FHIR. Additionally, a commenter stated that the FHIR standard is not 
broad enough to support all potential use cases, and that some EHR data 
does not map to the standard. The commenter recommended CMS work with 
ONC to advance the adoption and consistent implementation of data and 
interoperability standards, so that provider data collection and 
reporting requirements are enabled by health IT.
    Commenters differed in their input on the time to transition to 
dQMs. Although CMS did not indicate transition by 2025 in the RFI in 
the FY 2023 IPPS/LTCH PPS proposed rule, some commenters noted 
feasibility to transition by 2025, whereas some expressed concerns 
regarding the timeline for dQM rollout. Some commenters noted it would 
be feasible to submit EHR data by 2025, and many commenters agreed with 
beginning the transition with EHR-based APIs and expand into other data 
sources, as technology development and testing allows. A commenter 
noted if the data submission requirements extend beyond EHR data, there 
would need to be changes to infrastructure which would be burdensome. 
Many commenters requested the transition be delayed beyond 2025, until 
the technology evolves further. A commenter suggested CMS account for 
at least two to three years to accommodate EHR vendor development, 
budget considerations, and testing, implementation, and validation 
activities as it transitions to dQMs.
    Another commenter recommended CMS provide at least three to four 
years between finalizing any policies around the transition timeline to 
requiring FHIR-based API functionality for health IT products/systems 
that are not already going through ONC's Health IT Certification 
Program (Certification Program). A few commenters requested CMS provide 
transparency and more detailed plans about the transition to dQMs, or 
suggested CMS be flexible with the deadline for launching dQMs.
    Several commenters recommended CMS use the Trusted Exchange 
Framework and Common Agreement (TEFCA) or CareQuality, which are 
interoperability frameworks, through the beginning of this transition. 
The commenters suggested that CMS move ahead in this transition using 
data tools that CMS already has access to and are already in use. They 
also requested CMS release more information regarding the current 
system capabilities. Conversely, a commenter suggested that CMS not use 
preexisting tools, but instead use new and innovative data tools.
    Several commenters stated that while the transition to dQMs occurs, 
it is imperative that quality measurement continues, and that quality 
of care is not affected by the transition. A commenter stated that 
there are still current eCQM operational challenges that must be 
addressed prior to the transition to dQMs. Commenters also questioned 
which dQMs would be implemented first. Several commenters suggested 
dQMs rolled out first be clinically relevant and useful.
    Response: We appreciate all of the comments on and interest in this 
topic. This input is very valuable in our continuing planning for the 
transition to the digital quality measurement in CMS quality reporting 
and value-based purchasing programs. We continue to take all input into 
account as we develop future regulatory proposals for our digital 
quality measurement transition efforts.
    Comment: Many commenters supported the refined dQM definition 
noting it provides a ``good overview of the intent behind dQMs'' and it 
captures ``the full range of evolving healthcare information sources.'' 
Some commenters noted the definition is still too broad and requested 
clarification on components of the definition and examples of dQMs. A 
commenter encouraged CMS to continue with refinement of its dQMs 
definition and set clear, specific parameters for what it hopes to 
achieve and what it expects of hospitals. A commenter requested CMS 
clarify what would make a successful dQM interoperable or conversely 
not interoperable. Another commenter noted that establishing dQMs as 
free-standing software, as defined, may disincentivize the use of 
clinical data registries, which add additional value to the healthcare 
ecosystem.
    A commenter stated that not all data sources identified for use in 
dQMs are ready for inclusion in quality measurement. As an example, the 
commenter stated that wearable devices and patient-generated health 
data have not been vetted as valid and reliable interoperable data 
sources or as usable data for clinical quality improvement and 
assessment, and wearable devices, such as smartwatches and fitness 
trackers are not universally adopted and may introduce bias or 
inequities. Another commenter suggested the definition include the 
potential for dQMs to be developed in a way that allows their 
components to support a variety of use cases, such as decision support 
and quality improvement.
    Several commenters noted the ambiguity around eCQMs compared to 
dQMs and requested for further distinction. A commenter requested 
clarification as to whether eCQMs will be separate and distinct from 
dQMs or incorporated into dQMs. Some commenters expressed concern 
around the introduction of new eCQMs if CMS is transitioning to dQMs 
given the resources and investments necessary for supporting new 
measures.
    Response: We appreciate all of the comments on and interest in this 
topic. We believe that this input is very valuable in the continuing 
development of our transition to digital quality measurement in CMS 
quality reporting and value-based purchasing programs. We will continue 
to take all comments into account as we refine the digital quality 
measure definition.
    Comment: Commenters were divided on the use of non-EHR data sources 
for dQMs. Several commenters indicated non-EHR data sources could 
enhance the accuracy and completeness of data

[[Page 49185]]

to determine hospital quality performance. A commenter encouraged CMS 
to continue to leverage a broad set of data sources for digital quality 
measurement rather than relying solely on EHR-derived, standardized 
data, which would limit the completeness, accuracy, and timeliness of 
the data used to determine hospital quality performance. Commenters 
recommended CMS align with other federal initiatives such as the FDA's 
use of non-EHR data sources such as patient-generated health data. 
Other commenters expressed concern that hospitals and clinicians may be 
unable to calculate or understand their performance internally if other 
data sources are incorporated into dQMs. Some commenters stated that 
because non-EHR data are often not standardized or not yet 
standardized, non-EHR data sources could increase mapping burden, and 
that platforms are not yet available to support electronic capture, 
extraction, and access from non-EHR data sources. A commenter noted CMS 
would need to address unintended consequences of inadequate data 
quality for non-EHR data sources. Some commenters noted that patient 
matching must be considered when aggregating or combining data from 
disparate systems or sources. A commenter suggested that CMS' initial 
focus of dQMs remain on measures that emphasize the use of data 
available in EHRs. Another commenter requested CMS to provide specific 
details for how hospitals are expected to make data from non-EHR 
sources available. A commenter noted that other health IT are not 
required to certify to ONC's Health IT Certification program and that 
there are no FHIR-based API requirements for other health IT, which 
poses challenges for integrating non-EHR data sources. The commenter 
suggested CMS will need to establish specific requirements on its own, 
or in collaboration with ONC, to require other health IT systems/
products to develop and maintain FHIR-based APIs that CMS could 
leverage to query the data necessary for dQMs.
    Several commenters noted additional burden when considering non-EHR 
data for interoperability and data standardization. A couple of 
commenters noted requiring data capture beyond what clinicians document 
in their typical workflows would add development and documentation 
burden and require infrastructure changes. A commenter expressed 
concern with CMS' vision for an ecosystem with a broad set of data 
sources when the calculation of existing quality measures using data 
from source EHRs still uncovers gaps in data which hinder quality 
measure calculations.
    A few commenters noted that as CMS moves toward dQMs that use data 
sources across various non-EHR health IT, that EHRs not be the data 
aggregator or be expected to capture, store, and share information that 
would not be routinely captured in an EHR. Commenters recommended CMS 
aim to obtain data from the data's source system when possible.
    Commenters requested more specific transition plans for the 
incorporation of non-EHR data sources into dQMs, and a commenter 
strongly suggested CMS consider how the use of non-EHR data would 
impact dQM development and timelines.
    Response: We appreciate all of the comments on and interest in this 
topic. We believe that this input is very valuable in the continuing 
development of our transition to digital quality measurement in CMS 
quality reporting and value-based purchasing programs. We will continue 
to take all comments into account as we refine the dQM definition and 
consider the use of non-EHR data sources for digital quality 
measurement.
    Comment: Many commenters expressed support for the implementation 
guides CMS is considering using for digital quality measurement, 
including the Quality Improvement (QI) Core and the Data Exchange for 
Quality Measures (DEQM) Implementation Guides. Several commenters also 
specifically supported the use of the Da Vinci Implementation Guide and 
the C-CDA Implementation Guide. A commenter also supported 
standardization across implementation guides as CMS outlined in this 
RFI. Commenters also recommended CMS consider the following additional 
IGs: the Clinical Guidelines (CPG) Implementation Guide, the FHIR Bulk 
Data Access Implementation Guide, Carequality's FHIR-Based Exchange 
Implementation Guide, and specialty-specific implementation guides. A 
commenter noted it could provide more effective feedback when CMS 
clarifies what data elements and APIs the agency intends to use, and 
from where they intend to access data. The commenter provided the 
example that if CMS would like to access health information typically 
stored in a financial or billing product along with clinical health 
information for a dQM, the implementation guidance would likely be 
different than if CMS is looking to use clinical data only for a dQM.
    Several commenters encouraged CMS to continue testing and 
validating the implementation guides, recommending implementation 
guides be fully developed and sufficiently tested for successful 
implementation of truly interoperable sharing and transparency. Several 
commenters recommended that implementation guides be mature, defined by 
a commenter as broad adoption and completion of the balloting process. 
A commenter recommended CMS seek input from stakeholders through 
Connectathons and public comment to further refine the implementation 
guides.
    Several commenters expressed concerns that alignment, testing, and 
maturity of the standards need to be completed before the 
implementation guides can be used for CMS programs. One of these 
commenters specifically noted alignment of definitions of common 
quality measurement concepts across implementation guides still must be 
accomplished. A commenter noted they could not provide feedback on the 
specific implementation guides until CMS communicates decisions on what 
dQMs CMS intends to implement, what data elements and APIs CMS intends 
to use, and where CMS is intending to pull the data from. Several 
commenters also encouraged CMS to provide implementers sufficient time 
after implementation guides are completed before initiating program 
requirements.
    Several commenters expressed concerns about the limitations of the 
currently available implementation guides, such as the DEQM defining 
methods for exchange at the individual resource or data element level, 
while data are currently exchanged at the measure document level and 
enabling EHRs to push quality reporting data via FHIR APIs only at the 
aggregate level, but not at the patient level. Another commenter 
expressed the need for specialty-specific implementation guides.
    Several commenters recommended CMS develop further implementation 
guidance, including clarifying which exchange methods will be required 
for use in FHIR eCQM reporting, aggregation of data across 
interoperable systems for the purpose of quality measurement, and 
methods for collection of social determinants of health data for 
measure stratification and risk adjustment. A commenter suggested 
bucketing guidance into two categories: (1) content or context IGs 
(such as measures specifications) and (2) operational IGs (such as for 
data aggregation or CMS reporting). Regarding aggregation guidance, 
commenters noted the importance of aggregation activities including 
normalizing, standardizing, and quality assurance activities via valid 
methods.

[[Page 49186]]

Some commenters also noted that some data, for example EHR notes, are 
free text and in their current state cannot be extrapolated and 
therefore require manual abstraction. An additional commenter 
recommended optimizing these resources for better care that is safe, 
affordable, and equitable, prioritizing which IGs are being built to 
align with the goals for quality improvement programs. A commenter 
noted that in terms of guidelines and standardization of data within 
the implementation guides, CMS avoid a ``one size fits all'' approach. 
Another commenter suggested the importance of consistency of data 
definitions, as they believe this is fundamentally critical to ensure 
analysis and interpretations can be applied across the healthcare 
system.
    Commenters also supported alignment with ONC's USCDI and 
development of USCDI+ for quality measurement. A commenter specifically 
supported replacing the Common Clinical Data Set (CCDS) for information 
exchange with the more robust USCDI. These commenters noted that the 
USCDI may not include all data elements necessary for quality 
measurement, and that the USCDI+ must still be defined. Therefore, 
additional standards may still be required to support quality 
measurement. A commenter suggested the USCDI+ be incorporated into 
certified EHR technology requirements to support implementation. 
Another commenter noted the importance of federal and commercial 
alignment on data needs included in USCDI and USCDI+. Another commenter 
pointed out that a holistic approach is needed for data standards 
whereby standards are developed and adopted for use across care 
settings. The commenter added that there are at present a limited 
number of common data elements across inpatient, outpatient, and post-
acute care; however, these elements could serve as a starting point for 
cross-continuum patient assessment.
    Response: We appreciate all of the comments and suggestions on this 
topic. We believe that this input is very valuable in the continuing 
development of our transition to digital quality measurement in CMS 
quality reporting and value-based purchasing programs underpinned by 
data standardization activities. We will continue to take all comments 
into account as we refine implementation guides and additional guidance 
for dQM reporting.
    Comment: Several commenters provided input on additional venues to 
engage with implementors and other stakeholders during the transition 
to digital quality measurement. Several commenters requested CMS 
continue to solicit feedback from the public and other agencies on the 
transition to dQMs. Many commenters suggested CMS continue to 
participate in and host events, such as Connectathons, conferences, 
webinars, and the CMS Quality Conference to further explain CMS' plans 
to advance digital quality measures and to solicit feedback.
    Commenters also suggested CMS collaborate with and solicit feedback 
from a variety of other stakeholders including, but not limited to: the 
Core Quality Measures Collaborative (CQMC), the National Quality Forum 
(NQF), the National Committee for Quality Assurance (NCQA), technical 
expert panels, health insurers, clinicians, EHR Association, hospitals, 
clinical registries, and health IT developers. Commenters also 
suggested CMS work with health information exchanges (HIEs) and 
regional health information exchanges (RHIEs), which have experience 
with data flow options and dQM data collection and exchange. Some 
commenters also offered to provide CMS with additional feedback as the 
agency works on transitioning to dQMs.
    Commenters also recommended CMS work with ONC to update 
certification criteria if FHIR-based dQMs require the implementation of 
additional FHIR APIs. A commenter expressed concern that development 
and documentation burden would increase, if CMS would require data 
capture beyond what clinicians document in their typical workflows.
    Regarding testing of dQMs, several commenters recommended CMS 
conduct sufficient large-scale testing and consult with multi-
stakeholder groups such as the Health Information Technology Advisory 
Committee (HITAC) and NQF prior to wide-spread adoption. Several 
commenters also noted the utility of Connectathons for testing.
    Response: We thank commenters for their suggestions for soliciting 
feedback. CMS will continue to solicit feedback from the implementers 
and other stakeholders throughout the transition planning and 
implementation of dQMs.
    Comment: Regarding data flow options, several commenters supported 
CMS' overall direction towards using Clinical Quality Language (CQL), 
FHIR, and FHIR-based APIs for digital quality measurement, as common 
language and data source availability would promote data consistency 
across health IT systems.
    Several commenters expressed concerns and suggestions regarding 
data privacy and security. Some commenters expressed concerns regarding 
privacy of the non-EHR data sources, noting that non-EHR data sources 
do not have to abide by the Health Insurance Portability and 
Accountability Act of 1996 (HIPAA) and expressed concerns about the 
security of Protected Health Information (PHI) in non-EHR environments. 
Commenters also expressed concerns about privacy of data accessed via 
FHIR APIs. A commenter requested clarification about whether FHIR 
receiving systems will hold PHI, and if so for how long and how PHI 
would be secured. Commenters inquired whether patients would have the 
ability to opt-out of their information being transferred. Another 
commenter expressed concern about private information being shared with 
entities that are not covered by HIPAA and requested CMS work with 
Congress to fill the gap in the national privacy framework by 
developing robust federal privacy laws and regulations applicable to 
organizations that obtain healthcare data but are not subject to HIPAA. 
In addition, the commenter suggested HHS and the Federal Trade 
Commission (FTC) work together to find an effective stop-gap measure 
that can be implemented to protect potentially personally identifiable 
information that could be shared via APIs.
    While several commenters supported CMS's vision in accelerating the 
use of the FHIR standard and FHIR APIs to improve the exchange of 
health information to improve patient satisfaction and care, some 
commenters noted they do not themselves guarantee data quality, 
accuracy, or completeness. Commenters suggested CMS clarify how data 
integrity would be maintained for CMS dQM reporting and consider 
unintended consequences if the data quality is inadequate. A commenter 
noted using existing FHIR US Core-based APIs may not be an ideal 
approach for CMS dQM reporting, depending on the volume of data being 
considered and the frequency of data access. The commenter also stated 
that the FHIR resources needed to calculate dQMs may go beyond those 
available through FHIR US Core-based APIs. Another commenter stated 
concern about the variation of FHIR versions, and lack of version 
requirements. A commenter noted there are limitations on a provider's 
ability to connect to certain applications to submit data with multiple 
versions of FHIR and no version requirements.
    A few commenters expressed concern that API data providers, 
healthcare systems and provider practices may be unfairly burdened by 
fees and costs incurred from API technology providers. A commenter 
expressed concern that

[[Page 49187]]

payers or providers could be required to purchase certain software or 
be forced to pay to join registries or HIEs. A commenter expressed an 
additional concern that the API implementation costs would be shifted 
onto healthcare systems and physician practices, which could have a 
significant deleterious effect on smaller practices.
    Several commenters provided input on other considerations.
    A couple of commenters provided input on CMS' vision for the FHIR-
based measure calculation tool, described in CMS's Digital Quality 
Measurement Strategic Roadmap, although CMS did not request comment on 
the tool in this RFI. CMS previously requested comment on the tool in 
the FY 2022 IPPS/LTCH PPS proposed rule. A commenter requested 
clarification about whether measure calculation tools that would be 
created by CMS would enable real-time performance monitoring and about 
the frequency of measure calculation tool queries. The same commenter 
noted validation would need to be redone to verify that accurate 
measure outcomes were calculated by a measure calculation tool after 
measures are expressed in FHIR. Another commenter recognized the 
promise of an end-to-end measure calculation tool for distributing 
digital quality measures from a measure calculation tool to end users.
    A commenter requested CMS provide information on the CMS FHIR 
receiving system to be used for digital quality measurement. The 
commenter requested clarification on the CMS FHIR receiving system's 
attributes including how the system would know which APIs to query for 
which information, and if the CMS FHIR receiving system would rely on 
querying APIs or publication/subscription functionality not currently 
required by ONC or CMS.
    Many commenters raised concern with burden. Several commenters 
noted CMS consider the burden of transitioning to dQMs and ensure dQMs 
do not increase overall quality reporting burden. A commenter 
acknowledged the potential of dQMs as an end-to-end reporting solution 
and stated their belief that dQMs could enable a true learning health 
system in which real-time feedback from dQMs could be shared with 
providers for clinical decision support at the point-of-care. 
Commenters noted that while FHIR-based quality collection and reporting 
may potentially reduce the effort involved in measurement in the longer 
term, there are several precursor steps that need to be taken as 
setting up this capability will be burdensome for health IT vendors and 
providers.
    As noted previously, several commenters provided input on the 
timeline for transition and timeline feasibility. Commenters requested 
clarity from CMS on the transition timelines, including timelines for 
the phase-out of or addition of eCQMs, the use of USCDI+, the use of 
FHIR-based API, and when CMS would publish the required data elements 
and specifications for required dQMs.
    Several commenters noted the timeline to transition to dQMs is the 
biggest challenge and that period would significantly increase burden 
on providers, with even greater concerns noted for LTCHs and small 
rural hospitals. Commenters noted the long-term benefit of the 
transition to dQMs and FHIR however acknowledged the up-front burden. 
While beyond the scope of concern for the Hospital IQR Program or this 
RFI, commenters expressed similar concerns for other Medicare payment 
systems and other provider types that use non-certified health IT that 
also would have little historical reason for adoption of FHIR-based 
APIs. These commenters stated that if CMS is considering adoption of 
dQMs for the quality reporting programs for post-acute care, home 
health or other provider types, they believe it will be challenging to 
incentivize these other provider types to adopt updates to their health 
IT and to push health IT vendors and developers to develop those 
capabilities.
    Many commenters also noted data mapping challenges and associated 
burden. Some commenters noted they do not anticipate less mapping 
burden than current state with the transition to FHIR. Other commenters 
noted that data mapping guidance is necessary to ensure that the 
underlying data being accessed via FHIR APIs is accurate, valid, and 
consistent across providers. A commenter suggested CMS publish a 
deliberative roadmap that focuses on how source systems can generate 
the relevant source data set into an agreed-upon FHIR-based format 
mapping to the source health IT's internal data structures, before 
attempting to access such data directly through data element level 
FHIR-based APIs. The commenter noted the approach would also enable 
more focus initially on data mapping, quality, and completeness, and on 
patient matching across health IT to ensure data is properly correlated 
for dQMs beyond EHRs.
    Some commenters identified FHIR bulk data as a critical component 
to using FHIR for eCQMs. Commenters noted bulk FHIR transactions 
simplify and speed transmission and reduce risk of overtaxing source 
APIs depending on the volume of data and frequency of access required 
for dQMs. A few commenters noted bulk FHIR would be required for 
providers to support FHIR implementation.
    A few commenters suggested the current method of pulling and 
submitting files yearly to the HQR portal is burdensome and often 
encounters issues with data validation. The commenters noted that a 
direct connection for data submission and validation would reduce 
burden, because providers would not need to do anything more than 
initiate data retrieval and authorize data submission once it has been 
processed. Several commenters explained that due to the burden this 
transition would put on care facilities, CMS provide financial, 
technical, and educational support to these facilities during the 
transition. Commenters also stated that patient data may not be 
complete until weeks after the patient encounter, and therefore 
providers be able to resubmit data for calculations at any point.
    A few commenters requested CMS consider mechanisms that would 
provide resource support to assist and incentives for FHIR eCQM 
reporting. A commenter noted resource support is especially important 
for providers who care for underserved and vulnerable populations to 
ensure all providers can successfully transition to FHIR-based eCQM 
reporting and that no providers are left behind. A commenter suggested 
ensuring availability of free education sessions on FHIR-based digital 
quality measure development, and the provision of user-friendly measure 
authoring and testing tools. Another commenter suggested monetary 
incentives to participating in dQM testing.
    A commenter recommended participation in standards development 
processes will continue to provide CMS with the best channels to engage 
with the health IT developer community during the transition to digital 
quality measurement. The commenter noted the processes used in 
standards development give developers an opportunity to provide 
technical feedback on implementation guides based on their knowledge of 
how hospitals and clinicians use their software and their experience 
supporting users' participation in quality reporting programs. The 
commenter recommended CMS also provide developers access to test 
submission portals and other testing tools, even if the developer does 
not submit on behalf of its clients, because testing tools will allow 
developers to validate that data captured during

[[Page 49188]]

clinical workflows is accurately retrieved via FHIR APIs when used for 
quality reporting. The commenter stated that FHIR-based eCQM reporting 
will need to support push flows for data correction and revision 
because hospitals and clinicians may not finalize the clinical or 
billing documentation for an encounter until weeks after discharge. If 
the measure calculation tool has already retrieved data for that 
encounter, hospitals will need a way to re-trigger retrieval so that 
revised/final data is reflected in the measure outcome calculation. The 
commenter expressed concern that the DEQM Implementation Guide enables 
EHRs to push quality reporting data via FHIR APIs, but only at the 
aggregate level, meanwhile pushing patient level quality reporting 
outcomes would be required to reconcile discrepancies between quality 
measure reports before and after revisions took place.
    Several commenters recommended real-time, bi-directional data 
exchange between organizations and CMS, and across the healthcare 
system, to increase the value of this effort to patients and providers. 
Commenters noted that data collected and analyzed for dQMs could 
provide significant benefit for clinical decision support, shared and 
coordinated care across providers and facilities, and increased ability 
to track patients' outcomes. A commenter recommended that if dQM 
calculation is conducted outside of the EHR, it will be essential for 
those tools to engage in bi-directional data exchange with EHRs to 
allow users to have actionable insight into their quality measure 
performance. A commenter emphasized the need for bi-directional 
exchange of SDOH data with all members of the care team in real-time to 
support communication around the patients' goals and enable high-
quality care for all patients. A commenter questioned whether the 
measure calculation tools introduced in CMS's Digital Quality 
Measurement Strategic Roadmap would enable real-time performance 
monitoring for currently admitted patients.
    Response: We appreciate all of the comments on and interest in this 
topic. This input is very valuable in our continuing planning for the 
transition to the digital quality measurement in CMS quality reporting 
and value-based purchasing programs. We continue to take all input into 
account as we develop future regulatory proposals for our digital 
quality measurement transition efforts.

D. Advancing the Trusted Exchange Framework and Common Agreement--
Request for Information

    Section 4003(b) of the 21st Century Cures Act (Pub. L. 114-255), 
enacted in 2016, amended section 3001(c) of the Public Health Service 
Act (42 U.S.C. 300jj-11(c)), and required HHS to take steps to advance 
interoperability for the purposes of ensuring full network-to-network 
exchange of health information. Specifically, Congress directed the 
National Coordinator to ``develop or support a trusted exchange 
framework, including a common agreement among health information 
networks nationally.'' Since the enactment of the 21st Century Cures 
Act, HHS has pursued development of a Trusted Exchange Framework and 
Common Agreement (TEFCA). ONC's goals for TEFCA are as follows:
    Goal 1: Establish a universal policy and technical floor for 
nationwide interoperability.
    Goal 2: Simplify connectivity for organizations to securely 
exchange information to improve patient care, enhance the welfare of 
populations, and generate health care value.
    Goal 3: Enable individuals to gather their health care 
information.\408\
---------------------------------------------------------------------------

    \408\ See https://www.healthit.gov/buzz-blog/interoperability/321tefca-is-go-for-launch.
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    On January 18, 2022, ONC announced a significant TEFCA milestone by 
releasing the Trusted Exchange Framework \409\ and Common Agreement 
Version 1.\410\ The Trusted Exchange Framework is a set of non-binding 
principles for health information exchange, and the Common Agreement 
for Nationwide Health Information Interoperability Version 1 (also 
referred to as Common Agreement) is a contract that advances those 
principles. The Common Agreement and the incorporated by reference 
Qualified Health Information Network (QHIN) Technical Framework Version 
1 (QTF) \411\ establish the technical infrastructure model and 
governing approach for different health information networks and their 
users to securely share clinical information with each other, all under 
commonly agreed to terms. The Common Agreement is a legal contract that 
QHINs \412\ sign with the ONC Recognized Coordinating Entity 
(RCE),\413\ a private-sector entity that implements the Common 
Agreement and ensures QHINs comply with its terms.
---------------------------------------------------------------------------

    \409\ Trusted Exchange Framework (Jan. 2022), https://www.healthit.gov/sites/default/files/page/2022-01/Trusted_Exchange_Framework_0122.pdf.
    \410\ Common Agreement for Nationwide Health Information 
Interoperability Version 1 (Jan. 2022), https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf.
    \411\ Qualified Health Information Network (QHIN) Technical 
Framework (QTF) Version 1.0 (Jan. 2022), https://rce.sequoiaproject.org/wp-content/uploads/2022/01/QTF_0122.pdf.
    \412\ The Common Agreement defines a QHIN as ``to the extent 
permitted by applicable SOP(s), a Health Information Network that is 
a U.S. Entity that has been Designated by the RCE and is a party to 
the Common Agreement countersigned by the RCE.'' See Common 
Agreement for Nationwide Health Information Interoperability Version 
1, at 10 (Jan. 2022), https://www.healthit.gov/sites/default/files/page/2022-.
    \413\ In August 2019, ONC awarded a cooperative agreement to The 
Sequoia Project to serve as the initial RCE. The RCE will 
operationalize and enforce the Common Agreement, oversee QHIN-
facilitated network operations, and ensure compliance by 
participating QHINs. The RCE will also engage stakeholders to create 
a roadmap for expanding interoperability over time. See ONC Awards 
The Sequoia Project a Cooperative Agreement for the Trusted Exchange 
Framework and Common Agreement to Support Advancing Nationwide 
Interoperability of Electronic Health Information (September 3, 
2019), https://sequoiaproject.org/onc-awards-the-sequoia-project-a-cooperative-agreement-for-the-trusted-exchange-framework-and-common-agreement-to-support-advancing-nationwide-interoperability-of-electronic-health-information.

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[[Page 49189]]

    The technical and policy architecture of how exchange occurs under 
TEFCA follows a network-of-networks structure, which allows for 
connections at different levels and is inclusive of many different 
types of entities at those different levels, such as health information 
networks, care practices, hospitals, public health agencies, and 
Individual Access Services (IAS) \414\ Providers.\415\ QHINs connect 
directly to each other to facilitate nationwide interoperability, and 
each QHIN can connect Participants, which can connect 
Subparticipants.\416\ Compared to most nationwide exchange today, the 
Common Agreement includes an expanded set of Exchange Purposes beyond 
Treatment to include Individual Access Services, Payment, Health Care 
Operations, Public Health, and Government Benefits Determination 
\417\--all built upon common technical and policy requirements to meet 
key needs of the U.S. health care system. This flexible structure 
allows stakeholders to participate in the way that makes most sense for 
them, while supporting simplified, seamless exchange.
---------------------------------------------------------------------------

    \414\ The Common Agreement defines Individual Access Services 
(IAS) as ``with respect to the Exchange Purposes definition, the 
services provided utilizing the Connectivity Services, to the extent 
consistent with Applicable Law, to an Individual with whom the QHIN, 
Participant, or Subparticipant has a Direct Relationship to satisfy 
that Individual's ability to access, inspect, or obtain a copy of 
that Individual's Required Information that is then maintained by or 
for any QHIN, Participant, or Subparticipant.'' See Common Agreement 
for Nationwide Health Information Interoperability Version 1, at 7 
(Jan. 2022), https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf.
    \415\ The Common Agreement defines ``IAS Provider'' as: ``Each 
QHIN, Participant, and Subparticipant that offers Individual Access 
Services.'' See Common Agreement for Nationwide Health Information 
Interoperability Version 1, at 7 (Jan. 2022), https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf.
    \416\ For the Common Agreement definitions of QHIN, Participant, 
and Subparticipant, see Common Agreement for Nationwide Health 
Information Interoperability Version 1, at 8-12 (Jan. 2022), https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf.
    \417\ For the Common Agreement definitions of Payment, Health 
Care Operations, Public Health, and Government Benefits 
Determination, see Common Agreement for Nationwide Health 
Information Interoperability Version 1, at 6-10 (Jan. 2022), https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf.
---------------------------------------------------------------------------

    The QTF,\418\ which was developed and released by the RCE, 
describes the functional and technical requirements that a Health 
Information Network (HIN) \419\ must fulfill to serve as a QHIN under 
the Common Agreement. The QTF specifies the technical underpinnings for 
QHIN-to-QHIN exchange and certain other responsibilities described in 
the Common Agreement. The technical and functional requirements 
described in the QTF enable different types of information exchange, 
including querying and message delivery across participating entities.
---------------------------------------------------------------------------

    \418\ Qualified Health Information Network (QHIN) Technical 
Framework (QTF) Version 1.0 (Jan. 2022), https://rce.sequoiaproject.org/wp-content/uploads/2022/01/QTF_0122.pdf.
    \419\ ``Health Information Network'' under TEFCA has the meaning 
assigned to the term ``Health Information Network or Health 
Information Exchange'' in the information blocking regulations at 45 
CFR 171.102.
---------------------------------------------------------------------------

    In 2022, prospective QHINs are anticipated to begin signing the 
Common Agreement and applying for designation. The RCE will then begin 
onboarding and designating QHINs to share information. In 2023, HHS 
expects stakeholders across the care continuum to have increasing 
opportunities to enable exchange under TEFCA. Specifically, this would 
mean such stakeholders would be: (1) signatories to either the Common 
Agreement or an agreement that meets the flow-down requirements of the 
Common Agreement (called a Framework Agreement \420\ under the Common 
Agreement), (2) in good standing (that is, not suspended) under that 
agreement, and (3) enabling secure, bi-directional exchange of 
information to occur, in production. TEFCA is expected to give 
individuals and entities easier, more efficient, access to more health 
information while requiring strong privacy and security protections.
---------------------------------------------------------------------------

    \420\ The Common Agreement defines ``Framework Agreement(s)'' 
as: ``any one or combination of the Common Agreement, a Participant-
QHIN Agreement, a Participant-Subparticipant Agreement, or a 
Downstream Subparticipant Agreement, as applicable.'' See Common 
Agreement for Nationwide Health Information Interoperability Version 
1, at 6 (Jan. 2022) https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf.
---------------------------------------------------------------------------

    We believe that exchange of health information enabled by the 
Common Agreement can advance CMS policy and program objectives related 
to care coordination, cost efficiency, and patient-centeredness in a 
variety of ways. We also believe that CMS policy and programs can help 
to accelerate nationwide connectivity through TEFCA by health care 
providers as well as other stakeholders.
    We are considering other ways that available CMS policy and program 
levers can advance information exchange under TEFCA. For instance, 
similar to the proposal in the current rule, there may be opportunities 
for CMS to incentivize exchange under TEFCA through other programs that 
incentivize high quality care, or through program features in value-
based payment models that encourage certain activities that can improve 
care delivery.
    In addition to programs focused on providers, we are interested in 
opportunities to encourage exchange under TEFCA through CMS regulations 
for certain health care payers, including Medicare Advantage, Medicaid 
Managed Care, and CHIP issuers. For instance, we believe there may be 
opportunities to encourage information exchange under TEFCA to support 
recently finalized requirements for these payers to make information 
available to patients and to make patient information available to 
other payers as beneficiaries transition between plans in the 
``Medicare and Medicaid Programs; Patient Protection and Affordable 
Care Act; Interoperability and Patient Access for Medicare Advantage 
Organization and Medicaid Managed Care Plans, State Medicaid Agencies, 
CHIP Agencies and CHIP Managed Care Entities, Issuers of Qualified 
Health Plans on the Federally-Facilitated Exchanges, and Health Care 
Providers'' final rule (85 FR 25510). Finally, we are considering 
future opportunities to encourage information exchange under TEFCA for 
payment and operations activities such as submission of clinical 
documentation to support claims adjudication and prior authorization 
processes.
    We are requesting input from the public on the ideas described 
previously and related concepts for future exploration, as well as the 
following questions:
     What are the most important use cases for different 
stakeholder groups that could be enabled through widespread information 
exchange under TEFCA? What key benefits would be associated with 
effectively implementing these use cases, such as improved care 
coordination, reduced burden, or greater efficiency in care delivery?
     What are key ways that the capabilities of TEFCA can help 
to advance the goals of CMS programs? Should CMS explore policy and 
program mechanisms to encourage exchange between different 
stakeholders, including those in rural areas, under TEFCA? In addition 
to the ideas discussed previously, are there other programs CMS should 
consider in

[[Page 49190]]

order to advance exchange under TEFCA?
     How should CMS approach incentivizing or encouraging 
information exchange under TEFCA through CMS programs? Under what 
conditions would it be appropriate to require information exchange 
under TEFCA by stakeholders for specific use cases?
     What concerns do commenters have about enabling exchange 
under TEFCA? Could enabling exchange under TEFCA increase burden for 
some stakeholders? Are there other financial or technical barriers to 
enabling exchange under TEFCA? If so, what could CMS do to reduce these 
barriers?
    Comment: We received a wide range of comments on this request for 
information. Many did not recommend requiring TEFCA participation at 
this time. Some stated that there was confusion about TEFCA in the 
provider community. A commenter stated that there are difficulties in 
managing readmissions management under TEFCA that would create 
productivity decreases and recommended the creation of TECFA billing 
codes so that hospitals can be compensated. Many commenters raised 
concerns about the costs associated with participation noting that the 
costs may be a barrier for many health care providers.
    A commenter stated that data sharing for purposes of use beyond 
medical treatment holds tremendous possibility for advancing the goals 
of CMS programs and healthcare delivery. Others requested that we 
provide additional education on the benefits of TEFCA and why it 
remains essential when there are others ways to accomplish the 
objective of exchanging information. Another commenter suggested that 
CMS align any TEFCA Use Cases with the required Exchange Purposes: 
Treatment; Payment; Health Care Operations; Public Health; Benefits 
Determination; and Individual Access Services (IAS).
    Response: We appreciate the feedback and suggestions provided by 
the commenters regarding TEFCA. We plan to share all the input with ONC 
and will take commenters' feedback into consideration in future policy 
development.

E. Hospital Inpatient Quality Reporting (IQR) Program

1. Background and History of the Hospital IQR Program
    Through the Hospital IQR Program, we strive to put patients first 
by ensuring they are empowered to make decisions about their own 
healthcare along with their clinicians by using information from data-
driven insights that are increasingly aligned with meaningful quality 
measures. We support technology that reduces burden and allows 
clinicians to focus on providing high-quality healthcare for their 
patients. We also support innovative approaches to improve quality, 
accessibility, and affordability of care, while paying particular 
attention to improving clinicians' and beneficiaries' experiences when 
interacting with CMS programs. In combination with other efforts across 
HHS, we believe the Hospital IQR Program incentivizes hospitals to 
improve healthcare quality and value, while giving patients the tools 
and information needed to make the best decisions for themselves.
    We seek to promote higher quality and more efficient healthcare for 
Medicare beneficiaries. The adoption of widely agreed upon quality and 
cost measures supports this effort. We work with relevant stakeholders 
to define measures in almost every care setting and currently measure 
some aspect of care for almost all Medicare beneficiaries. These 
measures assess clinical processes, patient safety and adverse events, 
patient experiences with care, care coordination, and clinical 
outcomes, as well as cost of care. We have implemented quality measure 
reporting programs for multiple settings of care. To measure the 
quality of hospital inpatient services, we implemented the Hospital IQR 
Program, previously referred to as the Reporting Hospital Quality Data 
for Annual Payment Update (RHQDAPU) Program. We refer readers to the 
following final rules for detailed discussions of the history of the 
Hospital IQR Program, including statutory history, and for the measures 
we have previously adopted for the Hospital IQR Program measure set:
     The FY 2010 IPPS/LTCH PPS final rule (74 FR 43860 through 
43861);
     The FY 2011 IPPS/LTCH PPS final rule (75 FR 50180 through 
50181);
     The FY 2012 IPPS/LTCH PPS final rule (76 FR 51605 through 
61653);
     The FY 2013 IPPS/LTCH PPS final rule (77 FR 53503 through 
53555);
     The FY 2014 IPPS/LTCH PPS final rule (78 FR 50775 through 
50837);
     The FY 2015 IPPS/LTCH PPS final rule (79 FR 50217 through 
50249);
     The FY 2016 IPPS/LTCH PPS final rule (80 FR 49660 through 
49692);
     The FY 2017 IPPS/LTCH PPS final rule (81 FR 57148 through 
57150);
     The FY 2018 IPPS/LTCH PPS final rule (82 FR 38326 through 
38328 and 82 FR 38348);
     The FY 2019 IPPS/LTCH PPS final rule (83 FR 41538 through 
41609);
     The FY 2020 IPPS/LTCH PPS final rule (84 FR 42448 through 
42509);
     The FY 2021 IPPS/LTCH PPS final rule (85 FR 58926 through 
58959); and
     The FY 2022 IPPS/LTCH PPS final rule (86 FR 45360 through 
45426).
    We also refer readers to 42 CFR 412.140 for Hospital IQR Program 
regulations.
2. Retention of Previously Adopted Hospital IQR Program Measures for 
Subsequent Payment Determinations
    We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR 
53512 through 53513) for our finalized measure retention policy. 
Pursuant to this policy, when we adopt measures for the Hospital IQR 
Program beginning with a particular payment determination, we 
automatically readopt these measures for all subsequent payment 
determinations unless a different or more limited time period is 
proposed and finalized. Measures are also retained unless we propose to 
remove, suspend, or replace the measures. We did not propose any 
changes to these policies in the proposed rule.
3. Removal Factors for Hospital IQR Program Measures
    We refer readers to the FY 2019 IPPS/LTCH PPS final rule (83 FR 
41540 through 41544) for a summary of the Hospital IQR Program's 
removal factors. We did not propose any changes to these policies in 
the proposed rule.
4. Considerations in Expanding and Updating Quality Measures
    We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR 
53510 through 53512) for a discussion of the previous considerations we 
have used to expand and update quality measures under the Hospital IQR 
Program. We also refer readers to the FY 2019 IPPS/LTCH PPS final rule 
(83 FR 41147 through 41148), in which we describe the Meaningful 
Measures Framework, our objectives under this Framework for quality 
measurement, and the quality topics that we have identified as high-
impact measurement areas that are relevant and meaningful to both 
patients and providers. In 2021, we launched Meaningful Measures 2.0 to 
promote innovation and modernization of all aspects of quality, and to 
address a wide variety of settings, stakeholders, and measure 
requirements (we note that Meaningful Measures 2.0 is still under 
development).\421\ We did not propose

[[Page 49191]]

any changes to these policies in the proposed rule.
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    \421\ Centers for Medicare and Medicaid Services. (2021). 
Meaningful Measures 2.0: Moving from Measure Reduction to 
Modernization. Available at: https://www.cms.gov/meaningful-measures-20-moving-measure-reduction-modernization. We note that 
Meaningful Measures 2.0 is still under development.
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    We also note that the Hospital IQR Program must first adopt 
measures and publicly report them on the Compare tool hosted by HHS, 
currently available at: https://www.medicare.gov/care-compare, or its 
successor website, for at least one year before the Hospital Value-
Based Purchasing (VBP) Program is able to adopt them. We view the 
value-based purchasing programs, including the Hospital VBP Program, as 
the next step in promoting higher quality care for Medicare 
beneficiaries by transforming Medicare from a passive payer of claims 
into an active purchaser of quality healthcare for its beneficiaries.
5. New Measures for the Hospital IQR Program Measure Set
    In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28491 through 
29535), we proposed to adopt 10 new measures, including four electronic 
clinical quality measures (eCQMs): (1) Hospital Commitment to Health 
Equity measure, beginning with the CY 2023 reporting period/FY 2025 
payment determination; (2) Screening for Social Drivers of Health 
measure, beginning with voluntary reporting in the CY 2023 reporting 
period and mandatory reporting beginning with the CY 2024 reporting 
period/FY 2026 payment determination; (3) Screen Positive Rate for 
Social Drivers of Health measure, beginning with voluntary reporting in 
the CY 2023 reporting period and mandatory reporting beginning with the 
CY 2024 reporting period/FY 2026 payment determination; (4) Cesarean 
Birth eCQM, beginning with the CY 2023 reporting period/FY 2025 payment 
determination and mandatory reporting beginning with the CY 2024 
reporting period/FY 2026 payment determination; (5) Severe Obstetric 
Complications eCQM, beginning with the CY 2023 reporting period/FY 2025 
payment determination and mandatory reporting beginning with the CY 
2024 reporting period/FY 2026 payment determination; (6) Hospital-
Harm--Opioid-Related Adverse Events eCQM, beginning with the CY 2024 
reporting period/FY 2026 payment determination; (7) Global Malnutrition 
Composite Score eCQM, beginning with the CY 2024 reporting period/FY 
2026 payment determination; (8) Hospital-Level, Risk Standardized 
Patient-Reported Outcomes Performance Measure (PRO-PM) Following 
Elective Primary Total Hip Arthroplasty (THA) and/or Total Knee 
Arthroplasty (TKA), beginning with two voluntary reporting periods 
followed by mandatory reporting for the reporting period which runs 
from July 1, 2025 through June 30, 2026, impacting the FY 2028 payment 
determination; (9) Medicare Spending Per Beneficiary (MSPB) Hospital 
measure beginning with the FY 2024 payment determination; and (10) 
Hospital-Level Risk-Standardized Complication Rate (RSCR) Following 
Elective Primary Total THA/TKA measure beginning with the FY 2024 
payment determination.
    We provide more details on each of these proposals in the 
subsequent sections.
a. Hospital Commitment to Health Equity Measure Beginning With the CY 
2023 Reporting Period/FY 2025 Payment Determination and for Subsequent 
Years
(1) Background
    Significant and persistent disparities in healthcare outcomes exist 
in the U.S. For example, belonging to a racial or ethnic minority 
group, living with a disability, being a member of the lesbian, gay, 
bisexual, transgender, and queer (LGBTQ+) community, being a member of 
a religious minority, living in a rural area, having a disability, or 
being near or below the poverty level, is often associated with worse 
health outcomes.422 423 424 425 426 427 428 429 430 431 
Numerous studies have shown that among Medicare beneficiaries, racial 
and ethnic minority individuals often receive lower quality of hospital 
care, report lower experiences of care, and experience more frequent 
hospital readmissions and procedural 
complications.432 433 434 435 436 437
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    \422\ Joynt KE, Orav E, Jha AK. (2011). Thirty-Day Readmission 
Rates for Medicare Beneficiaries by Race and Site of Care. JAMA, 
305(7), 675-681. Available at: doi:10.1001/jama.2011.123.
    \423\ Lindenauer PK, Lagu T, Rothberg MB, et al. (2013). Income 
Inequality and Thirty-Day Outcomes After Acute Myocardial 
Infarction, Heart Failure, and Pneumonia: Retrospective Cohort 
Study. BMJ, 346. Available at: https://doi.org/10.1136/bmj.f521.
    \424\ Trivedi AN, Nsa W, Hausmann LRM, et al. (2014). Quality 
and Equity of Care in U.S. Hospitals. N Engl J Med, 371(24), 2298-
2308. Available at: doi: 10.1056/NEJMsa1405003.
    \425\ Polyakova, M, Udalova V, Kocks, G, Genadek K, Finlay K, 
Finkelstein AN. (2021). Racial Disparities In Excess All-Cause 
Mortality During The Early COVID-19 Pandemic Varied Substantially 
Across States. Health Affairs, 40(2), 307-316. Available at: https://doi.org/10.1377/hlthaff.2020.02142.
    \426\ Rural Health Research Gateway. (2018). Rural Communities: 
Age, Income, and Health Status. Rural Health Research Recap. 
Available at: https://www.ruralhealthresearch.org/assets/2200-8536/rural-communities-age-income-health-status-recap.pdf.
    \427\ HHS Office of Minority Health. (2020). Progress Report to 
Congress, 2020 Update on the Action Plan to Reduce Racial and Ethnic 
Health Disparities. Department of Health and Human Services. 
Available at: https://www.minorityhealth.hhs.gov/assets/PDF/Update_HHS_Disparities_Dept-FY2020.pdf.
    \428\ Heslin KC, Hall JE. (2021). Sexual Orientation Disparities 
in Risk Factors for Adverse COVID-19-Related Outcomes, by Race/
Ethnicity--Behavioral Risk Factor Surveillance System, United 
States, 2017-2019. MMWR Morb Mortal Wkly Rep, 70(5), 149. doi: 
10.15585/mmwr.mm7005a1.
    \429\ Poteat TC, Reisner SL, Miller M, Wirtz AL. (2020). COVID-
19 Vulnerability of Transgender Women With and Without HIV Infection 
in the Eastern and Southern U.S. medRxiv. doi: 10.1101/
2020.07.21.20159327.
    \430\ Vu M, Azmat A, Radejko T, Padela AI. (2016). Predictors of 
Delayed Healthcare Seeking Among American Muslim Women. Journal of 
Women's Health, 25(6), 586-593. doi: 10.1089/jwh.2015.5517
    \431\ Nadimpalli SB, Cleland CM, Hutchinson MK, Islam N, Barnes 
LL, Van Devanter N. (2016). The Association Between Discrimination 
and the Health of Sikh Asian Indians. Health Psychology, 35(4), 351-
355. https://doi.org/10.1037/hea0000268.
    \432\ CMS Office of Minority Health. (2020). Racial, Ethnic, and 
Gender Disparities in Healthcare in Medicare Advantage. Baltimore, 
MD: Centers for Medicare & Medicaid Services. Available at: https://www.cms.gov/files/document/2020-national-level-results-race-ethnicity-and-gender-pdf.pdf.
    \433\ CMS Office of Minority Health. (Updated August 2018). 
Guide to Reducing Disparities in Readmissions. Baltimore, MD: 
Centers for Medicare & Medicaid Services. Available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/OMH_Readmissions_Guide.pdf.
    \434\ Singh JA, Lu X, Rosenthal GE, Ibrahim S, Cram P. (2014). 
Racial Disparities in Knee and Hip Total Joint Arthroplasty: An 18-
year analysis of national Medicare data. Ann Rheum Dis., 73(12), 
2107-15. Available at: doi:10.1136/annrheumdis-2013-203494.
    \435\ Rivera-Hernandez M, Rahman M, Mor V, Trivedi AN. (2019). 
Racial Disparities in Readmission Rates among Patients Discharged to 
Skilled Nursing Facilities. J Am Geriatr Soc., 67(8), 1672-1679. 
Available at: https://doi.org/10.1111/jgs.15960.
    \436\ Joynt KE, Orav E, Jha AK. (2011). Thirty-Day Readmission 
Rates for Medicare Beneficiaries by Race and Site of Care. JAMA, 
305(7), 675-681. Available at: doi:10.1001/jama.2011.123.
    \437\ Tsai TC, Orav EJ, Joynt KE. (2014). Disparities in 
Surgical 30-day Readmission Rates for Medicare Beneficiaries by Race 
and Site of Care. Ann Surg., 259(6), 1086-1090. Available at: doi: 
10.1097/SLA.0000000000000326.

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[[Page 49192]]

Readmission rates in the Hospital Readmission Reduction Program have 
shown to be higher among Black and Hispanic Medicare beneficiaries with 
common conditions, including congestive heart failure and acute 
myocardial infarction.438 439 440 441 442 Data indicate 
that, even after accounting for factors such as socioeconomic 
conditions, members of racial and ethnic minority groups reported 
experiencing lower quality of healthcare.\443\ Evidence of differences 
in quality of care received among racial and ethnic minority groups 
show worse health outcomes including diabetes complications such as 
retinopathy.\444\ Additionally, inequities in the social determinants 
of health affecting these groups, such as poverty and healthcare 
access, are interrelated and influence a wide range of health and 
quality-of-life outcomes and risks.\445\
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    \438\ Rodriguez F, Joynt KE, Lopez L, Saldana F, Jha AK. (2011). 
Readmission Rates for Hispanic Medicare Beneficiaries with Heart 
Failure and Acute Myocardial Infarction. Am Heart J., 162(2), 254-
261 e253. Available at: https://doi.org/10.1016/j.ahj.2011.05.009.
    \439\ Centers for Medicare & Medicaid Services. (2014). Medicare 
Hospital Quality Chartbook: Performance Report on Outcome Measures. 
Available at: https://www.hhs.gov/guidance/document/medicare-hospital-quality-chartbook-performance-report-outcome-measures.
    \440\ CMS Office of Minority Health. (Updated August 2018). 
Guide to Reducing Disparities in Readmissions. Baltimore, MD: 
Centers for Medicare & Medicaid Services. Available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/OMH_Readmissions_Guide.pdf.
    \441\ Prieto-Centurion V, Gussin HA, Rolle AJ, Krishnan JA. 
(2013). Chronic Obstructive Pulmonary Disease Readmissions at 
Minority-Serving Institutions. Ann Am Thorac Soc., 10(6), 680-684. 
Available at: https://doi.org/10.1513/AnnalsATS.201307-223OT.
    \442\ Joynt KE, Orav E, Jha AK. (2011). Thirty-Day Readmission 
Rates for Medicare Beneficiaries by Race and Site of Care. JAMA, 
305(7), 675-681. Available at: doi:10.1001/jama.2011.123.
    \443\ Nelson AR. (2003). Unequal Treatment: Report of the 
Institute of Medicine on Racial and Ethnic Disparities in 
Healthcare. The Annals of Thoracic Surgery, 76(4), S1377-S1381. doi: 
10.1016/s0003-4975(03)01205-0.
    \444\ Peek, ME, Odoms-Young, A, Quinn, MT, Gorawara-Bhat, R, 
Wilson, SC, & Chin, MH. (2010). Race and Shared Decision-Making: 
Perspectives of African-Americans with diabetes. Social Science & 
Medicine, 71(1), 1-9. Available at: doi:10.1016/
j.socscimed.2010.03.014.
    \445\ Department of Health and Human Services. (2021). Healthy 
People 2020: Disparities. Available at: www.healthypeople.gov/2020/about/foundation-health-measures/Disparities.
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    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25592), we 
identified potential opportunities specific to the Hospital IQR Program 
by which we could leverage current measures or develop new measures to 
address the gap in healthcare disparities. In that rule, we sought 
public comment on addressing this gap, specifically requesting input on 
the inclusion of a structural measure to assess the degree of hospital 
leadership commitment to collecting and monitoring health equity 
performance data. We sought feedback on conceptual and measurement 
priorities to better illuminate organizational efforts to improve 
health equity, and on an appropriate measure regarding organizational 
commitment to health equity and accessibility for individuals with 
intellectual and developmental disabilities (86 FR 25593). In the FY 
2022 IPPS/LTCH PPS final rule (86 FR 45414 through 45416), we 
summarized the public comments we received, including support for the 
development and implementation of a health equity structural measure. 
We refer readers to the ``Closing the Health Equity Gap in CMS Quality 
Programs--Request for Information'' (86 FR 45349) and ``Potential 
Future Efforts to Address Health Equity in the Hospital IQR Program'' 
(86 FR 45414) in the FY 2022 IPPS/LTCH PPS final rule for more details.
    We note that the Agency for Healthcare Research and Quality (AHRQ) 
and The Joint Commission identified that hospital leadership plays an 
important role in promoting a culture of quality and 
safety.446 447 AHRQ research shows that hospital boards can 
influence quality and safety in a variety of ways; not only through 
strategic initiatives, but also through more direct interactions with 
frontline workers.\448\ Because we are working toward the goal of all 
patients receiving high quality healthcare when hospitalized, 
regardless of individual characteristics, we are committed to 
supporting healthcare organizations in building a culture of equity 
that focuses on educating and empowering their workforce to recognize 
and eliminate health disparities. This includes patients receiving the 
right care, at the right time, in the right setting for their 
condition(s), regardless of those characteristics.
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    \446\ Agency for Healthcare Research and Quality. Leadership 
Role in Improving Patient Safety. Patient Safety Primer, September 
2019. Available at: https://psnet.ahrq.gov/primer/leadership-role-improving-safety.
    \447\ Joint Commission on Accreditation of Healthcare 
Organizations, USA. Leadership Committed to Safety. Sentinel Event 
Alert. 2009 Aug 27;(43):1-3. PMID: 19757544.
    \448\ Agency for Healthcare Research and Quality. Leadership 
Role in Improving Patient Safety. Patient Safety Primer, September 
2019: Available at: https://psnet.ahrq.gov/primer/leadership-role-improving-safety.
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    We believe that strong and committed leadership from hospital 
executives and board members is essential and can play a role in 
shifting organizational culture and advancing equity goals. 
Additionally, studies demonstrate that hospital leadership can 
positively influence culture for better quality, patient outcomes, and 
experience of care.449 450 451 A systematic review of 122 
published studies showed that strong leadership that prioritized 
safety, quality, and the setting of clear guidance with measurable 
goals for improvement resulted in a high-performing hospital with 
better patient outcomes.\452\ We believe leadership commitment to 
health equity will have a parallel effect in contributing to a 
reduction in health disparities.
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    \449\ Bradley EH, Brewster AL, McNatt Z, et al. (2018) How 
Guiding Coalitions Promote Positive Culture Change in Hospitals: A 
Longitudinal Mixed Methods Interventional Study. BMJ Qual Saf., 
27(3), 218-225. doi:10.1136/bmjqs-2017-006574.
    \450\ Smith SA, Yount N, Sorra J. (2017). Exploring 
Relationships Between Hospital Patient Safety Culture and Consumer 
Reports Safety Scores. BMC Health Services Research, 17(1), 143. 
doi:10.1186/s12913-017-2078-6.
    \451\ Keroack MA, Youngberg BJ, Cerese JL, Krsek C, Prellwitz 
LW, Trevelyan EW. (2007). Organizational Factors Associated with 
High Performance in Quality and Safety in Academic Medical Centers. 
Acad Med., 82(12), 1178-86. doi: 10.1097/ACM.0b013e318159e1ff.
    \452\ Millar R, Mannion R, Freeman T, et al. (2013). Hospital 
Board Oversight of Quality and Patient Safety: A Narrative Review 
and Synthesis of Recent Empirical Research. The Milbank Quarterly, 
91(4), 738-70. doi:10.1111/1468-0009.12032.
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    The Institute of Healthcare Improvement's (IHI's) research of 23 
health systems throughout the U.S. and Canada also shows that health 
equity must be a priority championed by leadership teams to improve 
both patient access to needed healthcare services and outcomes among 
disadvantaged populations.\453\ This IHI study specifically identified 
concrete actions to make health equity a core strategy, including 
making health equity a leader-driven priority alongside organizational 
development structures and processes that support equity.\454\ Based 
upon these findings, we believe that hospital leadership can be 
instrumental in setting specific, measurable, attainable, realistic, 
and time-based (SMART) goals to assess progress towards achieving 
equity priorities and ensuring high-quality care is equally accessible 
to all individuals. Therefore, in the FY 2023 IPPS/LTCH PPS proposed 
rule (87 FR 28492 through 28497), we proposed to adopt an attestation-
based structural measure,

[[Page 49193]]

Hospital Commitment to Health Equity, beginning with the CY 2023 
reporting period/FY 2025 payment determination and for subsequent 
years.
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    \453\ Mate KS and Wyatt R. (2017). Health Equity Must Be a 
Strategic Priority. NEJM Catalyst. Available at: https://catalyst.nejm.org/doi/full/10.1056/CAT.17.0556.
    \454\ Mate KS and Wyatt R. (2017). Health Equity Must Be a 
Strategic Priority. NEJM Catalyst. Available at: https://catalyst.nejm.org/doi/full/10.1056/CAT.17.0556.
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    The first pillar of our strategic priorities \455\ reflects our 
deep commitment to improvements in healthcare equity by addressing the 
health disparities that underly our health system. We developed this 
structural measure to assess hospital commitment to health equity 
across five domains (see Table IX.E-01. in the subsequent section) 
using a suite of organizational competencies aimed at achieving health 
equity for racial and ethnic minority groups, people with disabilities, 
members of the LGBTQ+ community, individuals with limited English 
proficiency, rural populations, religious minorities, and people facing 
socioeconomic challenges. We believe these elements are actionable 
focus areas, and assessment of hospital leadership commitment to them 
is foundational. We also believe this measure will incentivize 
providers to collect and utilize data to identify critical equity gaps, 
implement plans to address said gaps, and ensure that resources are 
dedicated toward addressing healthcare equity initiatives. While many 
factors contribute to health equity, we believe this measure is an 
important step toward assessing hospital leadership commitment, and a 
fundamental step toward closing the gap in equitable care for all 
populations. We note that this measure is not intended to encourage 
hospitals to take action on any one given element of collected data, 
but instead encourages hospitals to analyze their own data to 
understand many factors, including race, ethnicity, and various social 
drivers of health, such as housing status and food security, in order 
to deliver more equitable care.
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    \455\ Brooks-LaSure, C. (2021). My First 100 Days and Where We 
Go From Here: A Strategic Vision for CMS. Centers for Medicare & 
Medicaid. Available at: https://www.cms.gov/blog/my-first-100-days-and-where-we-go-here-strategic-vision-cms.
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    We believe this measure builds on current health disparities 
reporting, supports hospitals in quality improvement, promotes 
efficient and effective use of resources, and leverages available data. 
The five questions of the proposed structural measure are adapted from 
the CMS Office of Minority Health's Building an Organizational Response 
to Health Disparities framework, which focuses on data collection, data 
analysis, culture of equity, and quality improvement.\456\
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    \456\ Centers for Medicare & Medicaid Services. (2021). Building 
an Organizational Response to Health Disparities [Fact Sheet]. U.S. 
Department of Health and Human Services. Available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/Health-Disparities-Guide.pdf.
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    This measure also aligns with our efforts under the Meaningful 
Measures Framework, which identifies high-priority areas for quality 
measurement and improvement to assess core issues most critical to 
high-quality healthcare and improving patient outcomes.\457\ In 2021, 
we launched Meaningful Measures 2.0 to promote innovation and 
modernization of all aspects of quality, and to address a wide variety 
of settings, stakeholders, and measure requirements.\458\ We plan to 
address healthcare priorities and gaps with Meaningful Measures 2.0 by 
leveraging quality measures to promote equity and close gaps in care. 
The Hospital Commitment to Health Equity measure supports these efforts 
and is aligned with the Meaningful Measures Area of ``Equity of Care'' 
and the Meaningful Measures 2.0 goal to ``Leverage Quality Measures to 
Promote Equity and Close Gaps in Care.'' This measure also supports the 
Meaningful Measures 2.0 objective to ``Commit to a patient-centered 
approach in quality measure and value-based incentives programs to 
ensure that quality and safety measures address healthcare equity.''
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    \457\ Centers for Medicare & Medicaid Services. Meaningful 
Measures Framework. Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/CMS-Quality-Strategy.
    \458\ Centers for Medicare & Medicaid Services. (2021). 
Meaningful Measures 2.0: Moving from Measure Reduction to 
Modernization. Available at: https://www.cms.gov/meaningful-measures-20-moving-measure-reduction-modernization. We note that 
Meaningful Measures 2.0 is still under development.
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(2) Overview of Measure
    The Hospital Commitment to Health Equity measure assesses hospital 
commitment to health equity using a suite of equity-focused 
organizational competencies aimed at achieving health equity for racial 
and ethnic minority groups, people with disabilities, members of the 
LGBTQ+ community, individuals with limited English proficiency, rural 
populations, religious minorities, and people facing socioeconomic 
challenges. Table IX.E-01. includes the five attestation domains and 
the elements within each of those domains that a hospital must 
affirmatively attest to for the hospital to receive credit for that 
domain.

[[Page 49194]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.155

    The Hospital Commitment to Health Equity measure was included in 
the publicly available ``List of Measures Under Consideration for 
December 1, 2021'' (MUC List), a list of measures under consideration 
for use in various Medicare programs.\459\ The National Quality Forum 
(NQF) Measure Applications Partnership (MAP) Rural Health Advisory 
Group reviewed the MUC List and the Hospital Commitment to Health 
Equity measure (MUC 2021-106) in detail on December 8, 2021.\460\ The 
MAP Rural Health Workgroup initially raised concerns that this measure 
may cause undue burden to rural hospitals that may not yet be directing 
resources or have available resources to dedicate toward implementing 
the measure. We acknowledge that for some hospitals, the implementation 
of this structural measure may impose additional data collection 
efforts. However, we believe this measure builds on hospitals'

[[Page 49195]]

current quality improvement activities through participation in the 
Hospital IQR Program. Additionally, we believe the activities outlined 
in the previous table are foundational best practices for advancing 
health equity for patients and communities. The Rural Health Workgroup 
agreed that this is an important measure and for that reason should be 
added to the Hospital IQR Program measure set as the intent of the 
measure is to identify these gaps and make the needed investments in 
workforce training, leadership development, and other related areas to 
improve equity.\461\ The MAP Rural Health Workgroup's recommendation 
was majority support for the Hospital Commitment to Health Equity 
measure.\462\
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    \459\ Centers for Medicare & Medicaid Services. (2021). List of 
Measures Under Consideration for December 1, 2021. Available at: 
https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96464.
    \460\ National Quality Forum. (2021). Measure Applications 
Partnership Rural Health Advisory Group Virtual Review Meeting: 
Meeting Summary for December 8, 2021. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96571.
    \461\ National Quality Forum. (2021). Measure Applications 
Partnership Rural Health Advisory Group Virtual Review Meeting: 
Meeting Summary for December 8, 2021. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96571.
    \462\ National Quality Forum. (2021). Measure Applications 
Partnership Rural Health Advisory Group Virtual Review Meeting: 
Meeting Summary for December 8, 2021. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96571.
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    In addition, on December 9, 2021, the MAP Health Equity Advisory 
Group reviewed the 2021 MUC List.\463\ The MAP Health Equity Advisory 
Group was convened at the request of CMS to provide input on the MUC 
List with the goal of reducing health disparities closely linked with 
social, economic, or environmental disadvantages.\464\ The MAP Health 
Equity Advisory Group is charged with providing feedback related to the 
relative priority of each measure in advancing health equity, and input 
on potential data, reporting, and/or methodological concerns on 
reporting measures adjusting for healthcare disparities.\465\ The MAP 
Health Equity Advisory Group provided input on potential unintended 
consequences or measurement gap areas related to health 
disparities.\466\ After discussion of each measure under consideration, 
the Workgroup was polled on the potential impact on health disparities 
if the measure were to be included in a specific program. Like the MAP 
Rural Health Advisory Group, the MAP Health Equity Advisory Group 
agreed this is an important measure for advancing healthcare equity in 
the Hospital IQR Program and a fundamental first step toward future 
measure development and innovation.\467\ The MAP Health Equity Advisory 
Group's feedback was supportive of this measure and its potential to 
decrease health disparities.\468\
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    \463\ Centers for Medicare & Medicaid Services. (2021). List of 
Measures Under Consideration for December 1, 2021. Available at: 
https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96464.
    \464\ National Quality Forum. (2022). Measure Applications 
Partnership Health Equity Advisory Group Virtual Review Meeting: 
Meeting Summary for December 9, 2021. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96599.
    \465\ National Quality Forum. (2022). Measure Applications 
Partnership Health Equity Advisory Group Virtual Review Meeting: 
Meeting Summary for December 9, 2021. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96599.
    \466\ National Quality Forum. (2022). Measure Applications 
Partnership Health Equity Advisory Group Virtual Review Meeting: 
Meeting Summary for December 9, 2021. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96599.
    \467\ National Quality Forum. (2022). Measure Applications 
Partnership Health Equity Advisory Group Virtual Review Meeting: 
Meeting Summary for December 9, 2021. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96599.
    \468\ National Quality Forum. (2022). Measure Applications 
Partnership Health Equity Advisory Group Virtual Review Meeting: 
Meeting Summary for December 9, 2021. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96599.
---------------------------------------------------------------------------

    The MUC List, including this measure (MUC2021-106), was also 
reviewed by the MAP Hospital Workgroup on December 15, 2021.\469\ MAP 
stakeholders expressed concerns about whether measure data will be 
actionable and how improvements in clinical healthcare equity outcomes 
will be measured.\470\ The MAP Hospital Workgroup had concerns about 
how this measure would be publicly reported, specifically, how it would 
be and interpreted by patients/consumers.\471\ For these reasons, the 
MAP Hospital Workgroup recommended that the MAP not support the measure 
for rulemaking.\472\ In response to this feedback, we wish to explain 
that we will publicly report the numerator indicating how many of the 
competencies hospitals attest to, and we refer readers to section 
IX.E.5.a.(3). for our proposed measure calculation methodology and 
section IX.E.5.a.(4). for the proposed public reporting. Thereafter, 
the MAP Coordinating Committee deliberated and ultimately voted to 
conditionally support this measure for rulemaking given its importance 
in being a first step towards the future development of outcome-based 
measures.\473\ We agree that this measure is an important foundation of 
a comprehensive quality reporting program. Our approach to developing 
health equity measures is incremental and will evolve over time to 
capture healthcare equity outcomes in the Hospital IQR Program. We 
additionally believe this measure to be a building block that lays the 
groundwork for a future meaningful suite of measures that would assess 
progress in providing high-quality healthcare for all patients 
regardless of social risk factors or demographic characteristics.
---------------------------------------------------------------------------

    \469\ National Quality Forum. (2022). Measure Applications 
Partnership Hospital Workgroup Web Review Meeting: Meeting Summary 
for December 15, 2021. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96629.
    \470\ National Quality Forum. (2022). Measure Applications 
Partnership Hospital Workgroup Web Review Meeting: Meeting Summary 
for December 15, 2021. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96629.
    \471\ National Quality Forum. (2022). Measure Applications 
Partnership Hospital Workgroup Web Review Meeting: Meeting Summary 
for December 15, 2021. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96629.
    \472\ National Quality Forum. (2022). Measure Applications 
Partnership Hospital Workgroup Web Review Meeting: Meeting Summary 
for December 15, 2021. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96629.
    \473\ National Quality Forum. (2022). Measure Applications 
Partnership (MAP) 2021-2022 Final Recommendations. Available at: 
https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96698.
---------------------------------------------------------------------------

    We have not submitted this measure for NQF endorsement at this 
time. We note that under section 1866(b)(3)(B)(viii)(IX)(aa) of the 
Act, each measure specified by the Secretary shall be endorsed by the 
entity with a contract under section 1890(a) of the Act (the NQF is the 
entity that currently holds this contract). Under section 
1886(b)(3)(B)(viii)(IX)(bb) of the Act, in the case of a specified area 
or medical topic determined appropriate by the Secretary for which a 
feasible and practical measure has not been endorsed by the entity with 
a contract under section 1890(a) of the Act, the Secretary may specify 
a measure that is not so endorsed as long as due consideration is given 
to a measure that has been endorsed or adopted by a consensus 
organization identified by the Secretary. We reviewed NQF-endorsed 
measures and were unable to identify any other NQF-endorsed measures on 
this topic, and, therefore we believe the exception in section 
1886(b)(3)(B)(viii)(IX)(bb) of the Act applies.
(3) Measure Calculation
    The Hospital Commitment to Health Equity measure consists of five 
domains, and a hospital will need to evaluate and determine whether it 
can affirmatively attest to each domain. Some of these domains have 
multiple elements to which a hospital must attest. For a hospital to 
affirmatively attest to a domain, and receive credit for

[[Page 49196]]

that domain, the hospital will evaluate and determine whether it 
engages in each of the elements that comprise the domain. Each of the 
domains will be represented in the denominator as a point, for a total 
of 5 points (one per domain).
    For example, for Domain 1 (``Hospital commitment to reducing 
healthcare disparities is strengthened when equity is a key 
organizational priority''), a hospital will evaluate and determine 
whether its strategic plan meets each of the elements described in (A) 
through (D) (see Table IX.E-01.). If the hospital's plan meets all four 
of these elements, the hospital will affirmatively attest to Domain 1 
and will receive a point for that attestation. A hospital will not be 
able to receive partial credit for a domain. In other words, if a 
hospital's strategic plan meets elements (A) and (B) but not (C) and 
(D), the hospital will not be able to affirmatively attest to Domain 1 
and will not receive a point for that attestation.
    The numerator will capture the total number of domain attestations 
that the hospital is able to affirm. For example, a hospital that 
affirmatively attests each element of the 5 domains will receive the 
maximum 5 points.
(4) Data Submission and Reporting
    Specifications for the measure are available on the CMS Measure 
Methodology page with the file name ``Hospital Commitment to Health 
Equity Structural Measure Specifications'' at: https://qualitynet.cms.gov/inpatient/iqr/resources. Hospitals are required to 
submit information for structural measures once annually using a CMS-
approved web-based data collection tool available within the Hospital 
Quality Reporting (HQR) System. Hospitals will follow established 
submission and reporting requirements as previously finalized for 
structural measures and refer readers to section IX.E.10.i. of the 
preamble of this final rule for more details on our previously 
finalized data submission and deadline requirements for structural 
measures.
    We proposed this measure for the CY 2023 reporting period/FY 2025 
payment determination and for subsequent years. In developing this 
proposal, we considered proposing an incremental approach to the 
implementation of this measure. However, we ultimately decided to 
propose mandatory reporting given the importance of this measure and 
how it aligns with our healthcare quality goal of closing the racial 
and ethnic disparity gaps.
    We invited public comment on this proposal.
    Comment: Many commenters supported the addition of the Hospital 
Commitment to Health Equity measure beginning with the CY 2023 
reporting period/FY 2025 payment determination and for subsequent 
years. Commenters supported this measure as a first step towards robust 
measurement of equitable healthcare delivery. Commenters believed this 
measure would help increase awareness for the importance of improving 
healthcare equity and send an important signal to hospital leadership. 
Additionally, commenters supported this measure, citing its importance 
for addressing disparities in healthcare outcomes and experience among 
populations that have been disadvantaged and/or underserved by the 
healthcare system. Others supported this measure because they believed 
it would assess commitment to establishing a culture of equity and help 
identify and address institutional biases. A commenter supported 
adoption of this measure because it highlights the importance of 
developing strategic initiatives, collecting data, and incorporating 
learnings in to care delivery and quality improvement initiatives. A 
commenter supported this measure because it presents the opportunity to 
address the lack of data that are comprehensive, consistent, and 
accurate to improve access and include participants from communities 
that have been disadvantaged and/or underserved by the healthcare 
system. A few commenters supported this measure as proposed.
    Response: We thank commenters for their support of our proposal to 
adopt the Hospital Commitment to Health Equity measure and agree that 
adopting this measure is in line with our goal of improving healthcare 
equity.
    Comment: A few commenters believed that starting with a structural 
measure is a good policy before proposing future process or outcome 
measures. A few commenters noted that the Hospital Commitment to Health 
Equity structural measure is strong for a structural measure. A few 
commenters agreed that this measure is actionable and will incentivize 
providers to collect and use data to close equity gaps. A commenter 
believed it would encourage hospitals to be more accountable for health 
disparities and help drive local commitment to health equity and 
advance health equity goals in the nation overall.
    Response: We thank commenters for their support to adopt this 
measure into the Hospital IQR Program measure set.
    Comment: A few commenters did not support this measure and 
recommended the measure should be further refined or alternative 
measure concepts should be developed. A commenter did not support and 
recommended hospitals be required to provide evidence in meeting each 
question. A few commenters did not support adopting the measure, citing 
concerns about whether the data will be meaningful and lead to progress 
or change.
    Response: We appreciate commenters' recommendations to further 
refine or develop alternative measure concepts. We wish to note this 
measure has been reviewed by the Measure Application Partnership (MAP) 
Coordinating Committee, which voted to conditionally support the 
measure given its importance in being a first step towards the future 
development of outcome-based measures. We also acknowledge concerns 
related to whether this measure will lead to meaningful change. 
However, we respectfully disagree that data from this measure will not 
lead to progress or change. As previously stated, our approach to 
developing health equity measures is incremental and will evolve over 
time to capture healthcare equity outcomes in the Hospital IQR Program. 
We additionally believe this measure to be a building block that lays 
the groundwork for a more comprehensive suite of measures in the future 
that would assess progress in providing high-quality healthcare for all 
patients regardless of social risk factors or demographic 
characteristics (87 FR 28496). We will monitor the data and any 
unintended consequences of the measure as part of standard measure 
maintenance.
    Comment: A few commenters did not support this measure because of 
concerns that public reporting could be misleading to the public by 
failing to recognize other steps hospitals are taking to advance health 
equity. A few commenters expressed concern about public reporting and 
requested additional guidance on interpreting partial scores as to not 
mislead patients and communities. A commenter recommended alternative 
public reporting options including reporting the data as a part of a 
publicly available dataset instead of on the Care Compare website. A 
commenter requested clarification on how this measure will be publicly 
reported.
    Response: We acknowledge commenters' concern about public reporting 
of this measure and interpretation by the public. We refer readers to 
sections IX.E.5.(a).(3). and IX.E.5.(a).(4). (Measure Calculation and 
Data Submission and Reporting, respectively) of this final rule for 
detailed descriptions of how we

[[Page 49197]]

calculate and publicly report this measure on the Compare tool hosted 
by HHS, currently available at: https://www.medicare.gov/care-compare. 
This measure includes five attestation-based questions, each 
representing a separate domain of commitment. Hospitals receive one 
point for each domain to which they attest ``yes,'' stating they are 
meeting the required competencies. For each domain there are between 
one and four associated yes/no sub-questions for related structures or 
activities within the hospital. Hospitals will only receive a point for 
each domain if they attest ``yes'' to all related sub-questions. A 
hospital's score can be a total of zero to five points.\474\ This 
measure will be publicly reported on the Compare tool hosted by HHS, 
currently available at https://www.medicare.gov/care-compare, or its 
successor website (87 FR 28562). We believe this measure will provide 
insightful information to healthcare providers and the public on the 
number of hospitals currently participating in health equity strategic 
planning, collecting data, using this data to identify equity gaps, 
establishing key performance indicators, and reviewing them with 
hospital senior leaders. We intend to provide educational materials as 
part of our outreach and public reporting of this measure to ensure 
understanding and interpretation of publicly reported data.
---------------------------------------------------------------------------

    \474\ Centers for Medicare & Medicaid Services. (2022). Hospital 
Commitment to Health Equity Structural Measure Specifications. 
Available at: https://qualitynet.cms.gov/files/62629ee35e40610016f30140?filename=Hosp_Commit_HlthEqStrct_Meas.pdf.
---------------------------------------------------------------------------

    Comment: A few commenters did not support measure adoption due to 
resource constraints and timing of mandatory reporting and recommended 
delaying reporting to allow time for hospitals to build and deploy 
processes. A few commenters expressed concern that all hospitals will 
not have capabilities within their EHR to meet the criteria set forth 
by this measure. A few commenters expressed concern about the burden 
this may place on hospitals and systems, particularly those that are 
under resourced. Specifically, commenters noted attestation to this 
measure would be difficult for small rural hospitals.
    Response: We acknowledge commenters' concerns regarding resources 
and timing of mandatory reporting; however, we believe achieving health 
equity is an issue, which deserves serious focus and rapid action for 
improvement. Although measure results will be publicly posted, we note 
that hospitals will receive credit for the reporting of their measure 
results regardless of their responses to the attestation questions 
because the Hospital IQR Program is a pay-for-reporting program.
    With regard to comments about EHR capabilities, we are sensitive to 
the potential for increased administrative burden associated with 
adding new capabilities within EHR to meet the criteria set forth in 
this measure and will take commenters' feedback into consideration in 
future policy development. Furthermore, we acknowledge that 
facilitating quality improvement for rural hospitals and small 
hospitals can present unique challenges and is a high priority under 
the Meaningful Measures Framework. We continue to consider ways to 
support small and rural hospital efforts toward achieving health 
equity.
    Comment: A few commenters expressed concern about this measure not 
being NQF endorsed.
    Response: We thank commenters for their recommendations. While we 
recognize the value of measures undergoing NQF endorsement review, 
given the urgency of achieving health equity and, as there are 
currently no NQF-endorsed measures that address hospital commitment to 
health equity, we believe it is important to implement this measure as 
soon as possible. We note that under section 
1866(b)(3)(B)(viii)(IX)(aa) of the Act, each measure specified by the 
Secretary shall be endorsed by the entity with a contract under section 
1890(a) of the Act (the NQF is the entity that currently holds this 
contract). Under section 1886(b)(3)(B)(viii)(IX)(bb) of the Act, in the 
case of a specified area or medical topic determined appropriate by the 
Secretary for which a feasible and practical measure has not been 
endorsed by the entity with a contract under section 1890(a) of the 
Act, the Secretary may specify a measure that is not so endorsed as 
long as due consideration is given to a measure that has been endorsed 
or adopted by a consensus organization identified by the Secretary. We 
reviewed NQF-endorsed measures and were unable to identify any other 
NQF-endorsed measures on this topic, and, therefore we believe the 
exception in section 1886(b)(3)(B)(viii)(IX)(bb) of the Act applies.
    Comment: A commenter requested clarification on whether this 
measure would be a pay-for-reporting measure since it is part of the 
Hospital IQR Program, or if affirmation in each of the five attestation 
domains would have a performance value.
    Response: We note that the Hospital IQR Program is a pay-for-
reporting program, and hospitals' payments are not based on their 
performance on measures. We note that hospitals will receive credit for 
the reporting of their measure results regardless of their responses to 
the attestation questions.
    Comment: A commenter requested clarification on how this measure 
will be validated.
    Response: We thank the commenter for their question. We wish to 
clarify that this measure will not be included in the Hospital IQR 
Program validation at this time. We require all hospitals participating 
in the Hospital IQR Program to complete the Data Accuracy and 
Completeness Agreement (DACA) each year which requires attestation that 
all of the information reported to CMS is accurate and complete (77 FR 
53554).
    Comment: A few commenters indicated that hospitals are not yet 
uniformly collecting disaggregated sociodemographic data and suggested 
that as a first step, we encourage hospitals to collect disaggregated 
data since it leads to a more complete data set. A commenter 
recommended changing the language to require hospitals to stratify 
performance indicators by demographic variables and state which 
demographic variables hospitals must use when stratifying quality data.
    Response: We appreciate commenters' recommendations to uniformly 
collect disaggregated data and interest regarding the collection and 
standardization of sociodemographic data. We believe this measure 
allows for significant flexibility in the approach to data collection 
and believe this is an appropriate first step for this structural 
measure and our first health equity-related quality measure. Though we 
will not be revising the measure to require stratification of 
performance indicators by identified demographic variables at this 
time, we will take commenters' feedback into consideration for future 
policy development. Additionally, we refer readers to our Overarching 
Principles for Measuring Healthcare Quality Disparities Across CMS 
Quality Programs--Request for Information in section IX.B. for more 
information about potential future measure stratification.
    Comment: A commenter suggested that for purposes of the Hospital 
IQR Program, we focus on assessing clinical quality rather than the 
quality of data collection.
    Response: We appreciate the commenters' feedback. We intend to 
continue research and assessments on improving clinical quality through 
quality measurement reporting to achieve health equity and have 
evaluated research, existing frameworks, and various tools in the 
development of

[[Page 49198]]

this measure as described in section IX.E.5.a. As discussed in the 
proposed rule, the five domains of this measure were adapted from the 
CMS Office of Minority Health's Building and Organizational Response to 
Health Disparities framework, which focuses on data collection, data 
analysis, culture of equity, and quality improvement (87 FR 28492). 
Further, we believe this measure is an important first step toward 
development of a more comprehensive suite of measures in the future (87 
FR 28496). Additionally, the MAP Rural Health Workgroup agreed that 
this is an important measure and that the intent of the measure is to 
identify gaps and make the needed investments in workforce training, 
leadership development, and other related areas to improve equity (87 
FR 28496).
    Comment: A commenter recommended that if we move forward with the Z 
codes and social drivers of health screening quality measures, there is 
no need to attest to data collection and analysis.
    Response: We thank the commenter for their recommendation regarding 
minimizing provider reporting burden by removing data collection and 
analysis (Domain 2 and Domain 3) attestation questions if we move 
forward with finalization of other proposals such as Z codes (discussed 
as a RFI in section II.D.13.d. of this final rule) and social drivers 
of health screening quality measures such as the Screening for Social 
Drivers of Health and Screen Positive Rate both discussed in section 
IX.E.5.b. of this final rule. We agree that any future measures or 
measure refinements should carefully consider alignment with other 
quality measure reporting requirements and efforts in a manner that 
minimizes provider reporting burden. We will take commenters' feedback 
into consideration in future policy development.
    Comment: A few commenters raised concerns that the measure is 
potentially duplicative of other measure reporting requirements such as 
eCQMs. A commenter questioned the need for this measure given that 
there are equity standards that are already developed. A commenter 
recommended a complete environment scan, listening sessions, focus 
groups, and/or a technical expert panel to catalogue what hospitals are 
doing to identify and address health disparities and ensure there is no 
redundancy in reporting requirements. Another commenter stated that a 
requirement of the Hospital Readmissions Reduction Program is to 
provide hospitals with risk-stratified reports, thus, requiring 
stratified reports in Domain 3 in this structural measure is 
duplicative. A few commenters recommended considering opportunities for 
alignment with existing tools to reduce reporting burden.
    Response: We thank the commenter for their recommendations, and we 
will continue to engage interested parties as we continue to build on 
our efforts to address unmet needs. Additionally, we wish to refer 
readers to our thorough discussion and RFIs on our ongoing evaluation 
of appropriate initiatives to reduce health disparities (see section 
IX.B., ``Closing the Health Equity Gap in CMS Hospital Quality 
Programs--Request for Information,'' in the FY 2022 IPPS/LTCH PPS final 
rule (86 FR 45349)) as well as section IX.B. of this final rule). We 
additionally appreciate commenter concerns related to potentially 
duplicative efforts and continually look for ways to minimize provider 
reporting burden. We will take this into consideration for future 
program years. We wish to reiterate that our approach to developing 
health equity measures is incremental and will evolve over time to 
capture healthcare equity outcomes in the Hospital IQR Program. We 
additionally believe this measure to be a building block that lays the 
groundwork for a more comprehensive suite of measures that would assess 
progress in providing high-quality healthcare for all patients 
regardless of social risk factors or demographic characteristics.
    Additionally, we continually look for ways to minimize provider 
reporting burden and do not believe that this measure is duplicative of 
other efforts or currently available eCQMs in the Hospital IQR Program 
at this time. With regard to the commenters recommending alignment, we 
interpret the commenters to mean that they have existing tools 
integrated into their EHRs or similar systems that assess the domains 
evaluated by this measure. We agree and encourage hospitals to utilize 
existing tools in their assessment of meeting reporting requirements of 
this measure.
    In regard to the comment on the Hospital Readmissions Reduction 
Program, while the Hospital Readmissions Reduction Program does provide 
hospitals with reports stratified by dual-eligibility, these reports 
are specific to the six condition/procedure specific readmissions 
measures within that program. Therefore, we believe that the data 
collected regarding Hospital Commitment to Health Equity will be 
complementary to the stratified data provided to hospitals within the 
Hospital Readmissions Reduction Program.
    Comment: Several commenters recommended that we broaden the scope 
of this measure to address more health equity factors and indicators. A 
few commenters believed that we should require collection of more 
granular and more specific data in order to thoroughly assess a 
hospital's commitment to equity. A commenter recommended inclusion of 
the elderly and veterans. Another commenter expressed concern this 
measure will not provide specific enough information to identify equity 
gaps and determine where improvements are most needed.
    Response: We appreciate commenters recommendations. At this time, 
this measure is a hospital-level measure that is assessing hospital 
commitment to health equity. We believe that the domains covered by 
this measure are inclusive of a hospital's commitment to the care of 
the population they serve, inclusive of the elderly and veterans. We 
refer readers to section IX.E.5.b. for discussion of the Social Drivers 
of Health measures and section IX.E.5.f. for discussion of the Global 
Malnutrition Composite Score eCQM which we believe address further the 
health equity factors. With regard to commenter concerns about 
sufficient measure specificity to identify equity gaps, as stated in 
the proposed rule, we encourage providers to analyze their own data to 
understand many factors, including race, ethnicity, and various drivers 
of health, such as housing stability and food security, in order to 
deliver more equitable care (87 FR 28493). The five domains of this 
measure were adapted from the CMS Office of Minority Health's Building 
an Organizational Response to Health Disparities framework, which 
focuses on data collection, data analysis, culture of equity, and 
quality improvement, and we encourage its use for data analysis to 
further understand the factors we have highlighted.\475\ Additionally, 
we wish to highlight the recently published CMS Framework for Health 
Equity 2022-2032 that provides guidance on designing, implementing, and 
operationalizing policies and programs.\476\
---------------------------------------------------------------------------

    \475\ Centers for Medicare & Medicaid Services. (2021). Building 
an Organizational Response to Health Disparities [Fact Sheet]. U.S. 
Department of Health and Human Services. Available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/Health-Disparities-Guide.pdf.
    \476\ Centers for Medicare & Medicaid Services. (2022). CMS 
Framework for Health Equity 2022-2032. Available at: https://www.cms.gov/files/document/cms-framework-health-equity.pdf.

---------------------------------------------------------------------------

[[Page 49199]]

    Comment: A commenter recommended we remove the requirement to 
collect data relating to race and ethnicity out of concern that 
collecting the data might worsen patient care and trust. Another 
commenter recommended removal of references to drivers of health data 
to maintain focus on healthcare related actions.
    Response: We appreciate commenters' concern and recognize the 
importance of establishing and maintaining patient trust in health 
equity initiatives. We wish to clarify that this measure does not 
require the collection of race and ethnicity data as a part of 
reporting. Rather, the measure assesses hospital commitment to health 
equity using a suite of equity-focused organizational competencies 
aimed at achieving health equity for racial and ethnic minority groups, 
people with disabilities, members of the LGBTQ+ community, individuals 
with limited English proficiency, rural populations, religious 
minorities, and people facing socioeconomic challenges. We believe this 
measure is an important foundational measure for improving health 
equity among those that have been disadvantaged and/or underserved by 
the healthcare system, and there is substantial research showing 
differences in care and experiences among these populations (87 FR 
28492 through 28493). We encourage providers to analyze their own data 
to understand the many factors, including race, ethnicity, and various 
drivers of health, such as housing stability and food security, in 
order to deliver more equitable care. Further, we note that although 
measure results will be publicly posted, hospitals will receive credit 
for the reporting of their measure results regardless of their 
responses to the attestation questions.
    Comment: A few commenters expressed concern about the need for 
training and education on implementing and structuring a program to 
engage leadership in improving health equity.
    Response: We appreciate commenters' concerns and agree that 
training and education is important for establishing and implementing 
any new measures in the Hospital IQR Program. We wish to highlight the 
various resources available through the CMS Office of Minority Health's 
Building an Organizational Response to Health Disparities framework, 
from which this measure was adapted, and the recently published CMS 
Framework for Health Equity 2022-2032 that provides guidance on 
designing, implementing, and operationalizing policies and 
programs.477 478
---------------------------------------------------------------------------

    \477\ Centers for Medicare & Medicaid Services. (2021). Building 
an Organizational Response to Health Disparities [Fact Sheet]. U.S. 
Department of Health and Human Services. Available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/Health-Disparities-Guide.pdf.
    \478\ Centers for Medicare & Medicaid Services. (2022). CMS 
Framework for Health Equity 2022-2032. Available at: https://www.cms.gov/files/document/cms-framework-health-equity.pdf.
---------------------------------------------------------------------------

    Comment: A commenter expressed concern about including Domain 3: 
Data Analysis in this attestation-based measure and recommended 
removing attestation to a performance dashboard that stratifies 
findings from this proposal as this activity is viewed as a next step. 
Another commenter expressed concerns that Domain 4 would be resource 
intensive as described. Instead, the commenter recommended this should 
be optional with a requirement to attest whether equity is embedded in 
the hospital's quality improvement processes and workflows or attest to 
having initiatives focused on addressing an inequity identified in 
hospital data analysis. A commenter recommended revising specifications 
for Domains 2, 3, and 4 as attestations to the inclusion of hospitals' 
strategic plans, timelines for implementation, and specific steps for 
achieving all five domains. A commenter recommended adding attestations 
regarding community and patient perspectives related to health equity 
and ongoing education to the leadership domain.
    Response: We appreciate the commenter's recommendations regarding 
domains. As we noted in the FY 2023 IPPS/LTCH PPS proposed rule, we 
believe all the activities outlined in the five domains of this 
attestation measure are foundational best practices for advancing 
health equity for patients and communities (87 FR 28496). We 
acknowledge not all hospitals will be engaged in all activities 
outlined across the five domains. Further, we wish to reiterate that 
hospitals will receive credit for the reporting of their measure 
results regardless of their responses to the attestation questions. As 
previously stated, our approach to developing health equity measures is 
incremental and will evolve over time to capture healthcare equity 
outcomes in the Hospital IQR Program. We additionally believe that a 
hospital's attestation to the action of the elements of the domains and 
not just the inclusion of the elements is important. Moreover, we do 
not anticipate that every hospital will be able to affirmatively attest 
to each domain. We note that this measure will be included in the 
Hospital IQR Program beginning with the CY 2023 reporting period/FY 
2025 payment determination and for subsequent years. With each 
additional year, we hope to see that each hospital is able to attest to 
more domains as part of their growth strategy and commitment to equity-
focused organizational improvements. We expect variability across 
hospitals and we believe this is important as part of our long-term 
strategy to improve health equity.
    Comment: Many commenters expressed concern about the scoring of 
this structural measure, citing it as an ``all or nothing'' approach, 
and recommended awarding partial credit within each domain. 
Specifically, many requested to receive a point for each element within 
a domain, resulting in a denominator of 11 rather than 5. A commenter 
recommended scoring collection of social drivers of health information 
separately from demographic data, suggesting this would highlight the 
importance of capturing both sets of data.
    Response: We thank the commenters for their feedback. We believe 
the five domains of this measure are actionable focus areas, and 
assessment of hospital leadership commitment to them is foundational. 
We also believe this measure will incentivize providers to collect and 
utilize data to identify critical equity gaps, implement plans to 
address said gaps, and ensure that resources are dedicated toward 
addressing healthcare equity initiatives (87 FR 28493). The five 
questions of the proposed structural measure are adapted from the CMS 
Office of Minority Health's Building an Organizational Response to 
Health Disparities framework, which focuses on data collection, data 
analysis, culture of equity, and quality improvement (87 FR 28494). We 
believe that each element within a domain is important together to help 
hospitals identify, prioritize, and take action on health disparities. 
Additionally, we wish to note that the Hospital IQR Program is a pay-
for-reporting program, and hospitals are not scored based on their 
performance on measures.
    Comment: A commenter requested clarification on whether providers 
would receive a special designation for attesting to all five domains.
    Response: We appreciate the commenter's request for clarification. 
We wish to clarify that we are not proposing a hospital designation 
related to health equity at this time. We commend and encourage 
hospitals to establish the necessary suite of equity-

[[Page 49200]]

focused organizational competencies aimed at achieving health equity.
    Comment: Many commenters recommended CMS provide guidance to ensure 
attestations are meaningful, accurate, complete, and applied 
consistently across hospitals. Specifically, commenters requested we 
provide a standard set of definitions and key terms. Several commenters 
recommended establishing guidelines or minimum benchmarks for each 
domain to create a more standardized methodology to reduce ambiguity. 
Commenters expressed concerns that the lack of clear definitions and 
benchmarks limit data from being truly actionable with respect to 
illuminating equity gaps, as the elements allow a large degree of 
ambiguity on how hospitals are evaluating whether they have met the 
requirements. A commenter requested clarification for which instances a 
hospital's participation in a regional framework (such as an HIE and 
related use cases), would constitute evidence of data collection, data 
analysis, and quality improvement. A commenter requested clarification 
on the intent by leaving the questions subject to interpretation.
    Response: We thank commenters for their feedback. Regarding a more 
standardized measure methodology, we note that the measure 
specifications as proposed (87 FR 28497) are available on the CMS 
Measure Methodology page with the file name ``Hospital Commitment to 
Health Equity Structural Measure Specifications'' at: https://qualitynet.cms.gov/inpatient/iqr/resources. As stated in the proposed 
rule, the five domains of this measure were adapted from the CMS Office 
of Minority Health's Building an Organizational Response to Health 
Disparities framework, which focuses on data collection, data analysis, 
culture of equity, and quality improvement, and we encourage its use 
for data analysis to further understand the factors we have highlighted 
(87 FR 28492). Further, we stated that this measure is an important 
foundation and the MAP Coordinating Committee supported the measure for 
rulemaking given its importance in being a first step towards the 
future development of outcome-based measures (87 FR 28496). 
Additionally, we wish to highlight the recently published CMS Framework 
for Health Equity 2022-2032 that provides guidance on designing, 
implementing, and operationalizing policies and programs.\479\ We 
encourage providers to analyze their own data to understand many 
factors, including race, ethnicity, and various drivers of health, such 
as housing stability and food security, and encourage hospitals to use 
these data to set specific, measurable, attainable, and realistic, and 
time-based (SMART) goals that support delivery of equitable care (87 FR 
28493).
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    \479\ Centers for Medicare & Medicaid Services. (2022). CMS 
Framework for Health Equity 2022-2032. Available at: https://www.cms.gov/files/document/cms-framework-health-equity.pdf.
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    We wish to clarify that we will provide educational and training 
materials to help with consistent implementation which will be conveyed 
through routine communication channels to hospitals, vendors, and QIOs, 
including, but not limited to, issuing memos, emails, and notices on 
the QualityNet website.
    Regarding the request for benchmarks and clarification on which 
instances a hospital's participation in a regional framework would 
constitute evidence of data collection, data analysis, and quality 
improvement, we remind readers that the Hospital IQR Program is a pay-
for-reporting program, and therefore, there are no set performance 
targets. We refer readers to the measure specifications at https://qualitynet.cms.gov/inpatient/iqr/resources for more details.
    Comment: Many commenters recommended starting with voluntary 
reporting beginning with the CY 2023 reporting period. A commenter 
recommended voluntary reporting to allow for time to refine measure 
elements and direct educational and technical assistance resources 
appropriately. A commenter recommended delaying mandatory reporting 
until at least CY 2024 to allow to allow additional time to allocate 
the necessary resources to fully implement the measure elements. 
Several commenters recommended delaying mandatory reporting until 
additional testing and greater specificity is further developed.
    Response: We appreciate commenters' concerns about mandatory 
reporting; however, we believe that achieving health equity is a 
pressing issue which deserves serious focus and rapid action. We note 
that hospitals will receive credit for the reporting of their measure 
results regardless of their responses to the attestation questions. We 
emphasize that the measure was proposed for inclusion beginning in the 
CY 2023 reporting period/FY 2025 payment determination, which will 
allow hospitals time during the remainder of CY 2022 to begin assessing 
their activities and levels of engagement in the identified domains. We 
additionally believe this measure to be a building block that lays the 
groundwork for a more comprehensive suite of measures that would assess 
progress in providing high-quality healthcare for all patients 
regardless of social risk factors or demographic characteristics.
    Comment: A commenter requested allowing hospitals to report as a 
system to reduce burden and duplicative reporting.
    Response: We thank the commenter for their request. We interpret 
the commenter to mean that they want a hospital system to report as one 
instead of separately by hospital. We wish to clarify that as part of 
the measure reporting, a hospital would be required to report under 
their CMS certification number (CCN) as part of their normal Hospital 
IQR Program reporting operations.
    Comment: A commenter recommended focusing on hospital-level 
practices and data, promoting collaboration between hospitals, ensuring 
measures are appropriately specified and tested before implementation, 
establishing feedback loops, fostering alignment and standardized 
approaches to data collection, and prioritizing the use of existing 
data. A commenter recommended enhanced coordination with local public 
health systems and sharing the measure data in the Community Health 
Needs Assessment (CHNA) processes, which are shared with local public 
health systems to guide public and private resource allocation.
    Response: We appreciate the commenter's recommendations. We agree 
that these are all important elements to monitoring and evaluating a 
quality reporting program. We believe this measure, the other measures 
we are proposing for adoption in the Hospital IQR Program, and our 
current measure set address a range of priorities. We are consistently 
committed to developing, adopting, assessing, and maintaining 
appropriate measures to put patients first and ensure they are 
empowered to make decisions about their own healthcare along with their 
clinicians by using information from data-driven insights. We equally 
encourage hospitals to collaborate, both with other hospitals and with 
local, state, and regional partners to align where possible to help 
supplement our efforts. We will continue to take these recommendations 
into consideration for future policy development.
    Comment: Another commenter recommended robust evaluation and 
monitoring of the measure.

[[Page 49201]]

    Response: We thank the commenter for their feedback. We will 
monitor measure implementation and data reporting as part of standard 
program and measure review. After consideration of the public comments 
we received, we are finalizing the proposal as proposed.
b. Adoption of Two Social Drivers of Health Measures Beginning With 
Voluntary Reporting in the CY 2023 Reporting Period and Mandatory 
Reporting Beginning With the CY 2024 Reporting Period/FY 2026 Payment 
Determination and for Subsequent Years
    Health-related social needs (HRSNs), which we have previously 
defined as individual-level, adverse social conditions that negatively 
impact a person's health or healthcare, are significant risk factors 
associated with worse health outcomes as well as increased healthcare 
utilization.\480\ We believe that consistently pursuing identification 
of HRSNs will have two significant benefits. First, because social risk 
factors disproportionately impact historically \481\ Second, these 
measures could support ongoing hospital quality improvement initiatives 
by providing data with which to stratify patient risk and 
organizational performance.
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    \480\ Centers for Medicare & Medicaid Services. (2021). A Guide 
to Using the Accountable Health Communities Health-Related Social 
Needs Screening Tool: Promising Practices and Key Insights. June 
2021. Available at: https://innovation.cms.gov/media/document/ahcm-screeningtool-companion. Accessed: November 23, 2021.
    \481\ American Hospital Association. (2020). Health Equity, 
Diversity & Inclusion Measures for Hospitals and Health System 
Dashboards. December 2020. Accessed: January 18, 2022. Available at: 
https://ifdhe.aha.org/system/files/media/file/2020/12/ifdhe_inclusion_dashboard.pdf.
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    Further, we believe collecting patient-level HRSN data through 
screening is essential in the long-term in encouraging meaningful 
collaboration between healthcare providers and community-based 
organizations and in implementing and evaluating related innovations in 
health and social care delivery. We note that advancing health equity 
by addressing the health disparities that underlie the country's health 
system is one of our strategic pillars \482\ and a Biden-Harris 
Administration priority.
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    \482\ Brooks-LaSure, C. (2021). My First 100 Days and Where We 
Go From Here: A Strategic Vision for CMS. Centers for Medicare & 
Medicaid. Available at: https://www.cms.gov/blog/my-first-100-days-and-where-we-go-here-strategic-vision-cms.
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    As a first step towards addressing the role of HRSNs in closing the 
health equity gap, we have developed two evidence-based measures--
Screening for Social Drivers of Health and Screen Positive Rate for 
Social Drivers of Health. These two Social Drivers of Health measures 
will support identification of specific risk factors for inadequate 
healthcare access and adverse health outcomes among patients. We note 
that these measures will enable systematic collection of HRSN data 
which aligns with our other efforts, including the CY 2023 Medicare 
Advantage and Part D proposed rule in which we proposed that all 
Special Needs Plans (SNPs) complete health risk assessments (HRAs) of 
enrollees that include specific standardized questions on housing 
stability, food security, and access to transportation (87 FR 1858). 
(We also note that this proposal was finalized with modification in the 
CY 2023 Medicare Advantage and Part D final rule (87 FR 27726). We 
finalized that all SNPs include one or more questions on housing 
stability, food security, and access to transportation in their HRA 
using questions from a list of screening instruments specified in sub-
regulatory guidance instead of the proposed use of the same 
standardized questions (82 FR 27726)).
    These standardized measures will identify patients with HRSNs, who 
are known to experience the greatest risk of poor health outcomes, 
thereby improving the accuracy of high-risk prediction calculations. 
Improvement in risk prediction has the potential to reduce healthcare 
access barriers, address the disproportionate expenditures attributed 
to high-risk population groups, and improve the hospital's quality of 
care.483 484 485 486 Further, these data could guide future 
public and private resource allocation to promote targeted 
collaboration between hospitals and health systems and appropriate 
community-based organizations and ultimately contribute to improved 
patient outcomes following inpatient hospitalization.
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    \483\ Baker, M.C., Alberti, P.M., Tsao, T.Y., Fluegge, K., 
Howland, R.E., & Haberman, M. (2021). Social Determinants Matter for 
Hospital Readmission Policy: Insights From New York City. Health 
Affairs, 40(4), 645-654. Available at: https://doi.org/10.1377/hlthaff.2020.01742.
    \484\ Hammond, G., Johnston, K., Huang, K., Joynt Maddox, K. 
(2020). Social Determinants of Health Improve Predictive Accuracy of 
Clinical Risk Models for Cardiovascular Hospitalization, Annual 
Cost, and Death. Circulation: Cardiovascular Quality and Outcomes, 
13 (6) 290-299. Available at: https://doi.org/10.1161/CIRCOUTCOMES.120.006752.
    \485\ Hill-Briggs, F. (2021, January 1). Social Determinants of 
Health and Diabetes: A Scientific Review. Diabetes Care. Available 
at: https://pubmed.ncbi.nlm.nih.gov/33139407/.
    \486\ Jaffrey, J.B., Safran, G.B., Addressing Social Risk 
Factors in Value-Based Payment: Adjusting Payment Not Performance to 
Optimize Outcomes and Fairness. Health Affairs Blog, April 19, 2021. 
Available at: https://www.healthaffairs.org/do/10.1377/forefront.20210414.379479/full/.
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    In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28497 through 
28506), we proposed voluntary reporting of these two measures beginning 
with the CY 2023 reporting period and mandatory reporting beginning 
with the CY 2024 reporting period/FY 2026 payment determination and for 
subsequent years. We believe incremental implementation of these 
measures beginning with one year of voluntary reporting will allow 
hospitals who are not yet screening patients for HRSNs to get 
experience with the measure and equally allow hospitals who already 
undertake screening efforts to report data already being collected.
    We provide further details on both measures in the subsequent 
discussion. Additionally, consistent with our strategy to incorporate 
social drivers of health factors into Medicare quality reporting and 
payment, we refer readers to section II.D.13.(d). where we sought 
comment on how the reporting of diagnosis codes may improve our ability 
to advance health equity.

[[Page 49202]]

(1) Screening for Social Drivers of Health Measure
(a) Background
    In the FY 2022 IPPS/LTCH PPS final rule, we sought feedback on the 
development of new measures that could address the gap in existing 
health disparities, focusing on social risk factors for which providers 
should screen (85 FR 45414). As a result, we identified the Screening 
for Social Drivers of Health measure, which assesses the percent of 
patients admitted to the hospital who are 18 years or older at time of 
admission and are screened for food insecurity, housing instability, 
transportation needs, utility difficulties, and interpersonal safety.
    Health disparities manifest primarily as worse health outcomes in 
population groups where access to care is 
inequitable.487 488 489 490 491 Such differences persist 
across geography and healthcare settings irrespective of improvements 
in quality of care over time.492 493 494 Assessment of HRSNs 
is an essential mechanism for capturing the interaction between social, 
community, and environmental factors associated with health status and 
health outcomes.495 496 497 While widespread interest in 
addressing HRSNs exists, action is inconsistent, with 92 percent of 
hospitals screening for one or more of the five HRSNs--food insecurity, 
housing instability, transportation needs, utility difficulties, and 
interpersonal safety--specified in the proposed measures, but only 24 
percent of hospitals screening for all five HRSNs.\498\
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    \487\ Seligman, H.K., & Berkowitz, S.A. (2019). Aligning 
Programs and Policies to Support Food Security and Public Health 
Goals in the United States. Annual Review of Public Health, 40(1), 
319-337. Available at: https://pubmed.ncbi.nlm.nih.gov/30444684/.
    \488\ The Physicians Foundation. (2020). Survey of America's 
Patients, Part Three. Available at: https://physiciansfoundation.org/wp-content/uploads/2020/10/2020-Physicians-Foundation-Survey-Part3.pdf.
    \489\ Office of the Assistant Secretary for Planning and 
Evaluation (ASPE) (2020). Report to Congress: Social Risk Factors 
and Performance Under Medicare's Value-Based Purchasing Program 
(Second of Two Reports). Available at: https://aspe.hhs.gov/pdf-report/second-impact-report-to-congress.
    \490\ Trivedi AN, Nsa W, Hausmann LRM, et al. Quality and Equity 
of Care in U.S. Hospitals. New England Journal of Medicine. 2014; 
371(24):2298- 2308.
    \491\ Billioux, A., Verlander, K., Anthony, S., & Alley, D. 
(2017). Standardized Screening for Health-Related Social Needs in 
Clinical Settings: The Accountable Health Communities Screening 
Tool. NAM Perspectives, 7(5). Available at: https://doi.org/10.31478/201705b.
    \492\ Office of the Assistant Secretary for Planning and 
Evaluation (ASPE) (2020). Report to Congress: Social Risk Factors 
and Performance Under Medicare's Value-Based Purchasing Program 
(Second of Two Reports). Available at: https://aspe.hhs.gov/pdf-report/second-impact-report-to-congress.
    \493\ Hill-Briggs, F. (2021, January 1). Social Determinants of 
Health and Diabetes: A Scientific Review. Diabetes Care. Available 
at: https://pubmed.ncbi.nlm.nih.gov/33139407/.
    \494\ Khullar, D., MD. (2020, September 8). Association Between 
Patient Social Risk and Physician Performance American academy of 
Family Physicians. Addressing Social Determinants of Health in 
Primary Care team-based approach for advancing health equity. 
Available at: https://www.aafp.org/dam/AAFP/documents/patient_care/everyone_project/team-based-approach.pdf.
    \495\ Institute of Medicine. (2014). Capturing Social and 
Behavioral Domains and Measures in Electronic Health Records: Phase 
2. Washington, DC: The National Academies Press. Available at: 
https://doi.org/10.17226/18951.
    \496\ Alley, D.E., C.N. Asomugha, P.H. Conway, and D.M. 
Sanghavi. (2016). Accountable Health Communities--Addressing Social 
Needs through Medicare and Medicaid. The New England Journal of 
Medicine 374(1):8-11. Available at: https://doi.org/10.1056/NEJMp1512532.
    \497\ Centers for Disease Control and Prevention. CDC COVID-19 
Response Health Equity Strategy: Accelerating Progress Towards 
Reducing COVID-19 Disparities and Achieving Health Equity. July 
2020. Available at: https://www.cdc.gov/coronavirus/2019-ncov/community/health-equity/cdc-strategy.html. Accessed November 17, 
2021.
    \498\ TK Fraze, AL Brewster, VA Lewis, LB Beidler, GF Murray, CH 
Colla. Prevalence of screening for food insecurity, housing 
instability, utility needs, transportation needs, and interpersonal 
violence by US physician practices and hospitals. JAMA Network Open 
2019; 2:e1911514.10.1001/jamanetworkopen.2019.11514.31532515.
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    Growing evidence demonstrates that specific social risk factors are 
directly associated with patient health outcomes as well as healthcare 
utilization, costs, and performance in quality-based payment 
programs.499 500 In 2017, CMS' Center for Medicare and 
Medicaid Innovation (CMMI) launched the Accountable Health Communities 
(AHC) Model to test the impact of systematically identifying and 
addressing the HRSNs of Medicare and Medicaid beneficiaries (through 
screening, referral, and community navigation on their health outcomes 
and related healthcare utilization and 
costs).501 502 503 504 Although there are models that 
address HRSNs, the AHC Model is one of the first federal pilots to 
systematically test whether identifying and addressing core HRSNs 
improves healthcare costs, utilization, and outcomes.\505\ It also 
tested the ability of hospitals and health systems to implement HRSN 
screening, referral, and community navigation in over 600 clinical 
sites in 21 states.\506\ The AHC Model has a 5-year period of 
performance that began in May 2017 and will end in April 2022, with 
beneficiary screening beginning in the summer of 2018 following an 
implementation period.507 508
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    \499\ Zhang Y, Li J, Yu J, Braun RT, Casalino LP (2021). Social 
Determinants of Health and Geographic Variation in Medicare per 
Beneficiary Spending. JAMA Network Open. 2021;4(6):e2113212. 
doi:10.1001/jamanetworkopen.2021.13212.
    \500\ Khullar, D., Schpero, W.L., Bond, A.M., Qian, Y., & 
Casalino, L.P. (2020). Association Between Patient Social Risk and 
Physician Performance Scores in the First Year of the Merit-based 
Incentive Payment System. JAMA, 324(10), 975-983. https://doi.org/10.1001/jama.2020.13129.
    \501\ Centers for Medicare & Medicaid Services. (2021). A Guide 
to Using the Accountable Health Communities Health-Related Social 
Needs Screening Tool: Promising Practices and Key Insights. June 
2021. Accessed: November 23, 2021. Available at: https://innovation.cms.gov/media/document/ahcm-screeningtool-companion.
    \502\ Alley, D.E., C.N. Asomugha, P.H. Conway, and D.M. 
Sanghavi. 2016. Accountable Health Communities--Addressing Social 
Needs through Medicare and Medicaid. The New England Journal of 
Medicine 374(1):8-11. Available at: https://doi.org/10.1056/NEJMp1512532.
    \503\ Billioux, A., Verlander, K., Anthony, S., & Alley, D. 
(2017). Standardized Screening for Health-Related Social Needs in 
Clinical Settings: The Accountable Health Communities Screening 
Tool. NAM Perspectives, 7(5). Available at: https://doi.org/10.31478/201705b.
    \504\ Centers for Medicare & Medicaid Services. (2021). 
Accountable Health Communities Model. Accountable Health Communities 
Model [verbar] CMS Innovation Center. Accessed November 23, 2021. 
Available at: https://innovation.cms.gov/innovation-models/ahcm.
    \505\ RTI International. (2020). Accountable Health Communities 
(AHC) Model Evaluation. Available at: https://innovation.cms.gov/data-and-reports/2020/ahc-first-eval-rpt.
    \506\ RTI International. (2020). Accountable Health Communities 
(AHC) Model Evaluation. Available at: https://innovation.cms.gov/data-and-reports/2020/ahc-first-eval-rpt.
    \507\ RTI International. (2020). Accountable Health Communities 
(AHC) Model Evaluation. Available at: https://innovation.cms.gov/data-and-reports/2020/ahc-first-eval-rpt.
    \508\ We note that the model officially concluded in April 2022 
but many awardees are continuing with no-cost extensions to continue 
utilizing unspent cooperative agreement funding and all awardees 
will conclude by April 2023.
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    While social risk factors account for 50 to 70 percent of health 
outcomes, the mechanisms by which this connection emerges are complex 
and multifaceted.509 510 511 512 The persistent

[[Page 49203]]

interactions between individuals' HRSNs, medical providers' practices/
behaviors, and community resources significantly impact healthcare 
access, quality, and ultimately costs, as described in the CMS Equity 
Plan for Improving Quality in Medicare.513 514 In their 2018 
survey of 8,500 physicians, The Physicians Foundation found almost 90 
percent of physician respondents reported their patients had a serious 
health problem linked to poverty or other social conditions.\515\ 
Additionally, associations between disproportionate health risk, 
hospitalization, and adverse health outcomes have been highlighted and 
magnified by the COVID-19 pandemic.516 517
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    \509\ Kaiser Family Foundation. (2021). Racial and Ethnic Health 
Inequities and Medicare. Available at: https://www.kff.org/medicare/report/racial-and-ethnic-health-inequities-and-medicare/. Accessed 
November 23, 2021.
    \510\ Khullar, D., MD. (2020, September 8). Association Between 
Patient Social Risk and Physician Performance American academy of 
Family Physicians. (2020). Addressing Social Determinants of Health 
in Primary Care team-based approach for advancing health equity.
    \511\ Hammond, G., Johnston, K., Huang, K., Joynt Maddox, K. 
(2020). Social Determinants of Health Improve Predictive Accuracy of 
Clinical Risk Models for Cardiovascular Hospitalization, Annual 
Cost, and Death. Circulation: Cardiovascular Quality and Outcomes, 
13 (6) 290-299. Available at: https://doi.org/10.1161/CIRCOUTCOMES.120.006752.
    \512\ The Physicians Foundation. (2021). Viewpoints: Social 
Determinants of Health. Available at: https://physiciansfoundation.org/wp-content/uploads/2019/08/The-Physicians-Foundation-SDOH-Viewpoints.pdf. Accessed December 8, 2021.
    \513\ Centers for Medicare & Medicaid Services. (2021). Paving 
the Way to Equity: A Progress Report. Accessed January 18, 2022. 
Available at: https://www.cms.gov/files/document/paving-way-equity-cms-omh-progress-report.pdf.
    \514\ Centers for Medicare & Medicaid Services Office of 
Minority Health. (2021). The CMS Equity Plan for Improving Quality 
in Medicare. 2015-2021. Available at: https://www.cms.gov/About-CMS/
Agency-Information/OMH/OMH_Dwnld-
CMS_EquityPlanforMedicare_090615.pdf#:~:text=The%20Centers%20for%20Me
dicare%20%26%20Medicaid%20Services%20%28CMS%29,evidence%20base%2C%20i
dentifying%20opportunities%2C%20and%20gathering%20stakeholder%20input
.
    \515\ The Physicians Foundation. (2019). Viewpoints: Social 
Determinants of Health. Available at: https://physiciansfoundation.org/wp-content/uploads/2019/08/The-Physicians-Foundation-SDOH-Viewpoints.pdf. Accessed December 8, 2021.
    \516\ Centers for Disease Control and Prevention. (2020). CDC 
COVID-19 Response Health Equity Strategy: Accelerating Progress 
Towards Reducing COVID-19 Disparities and Achieving Health Equity. 
July 2020. Available at: https://www.cdc.gov/coronavirus/2019-ncov/community/health-equity/cdc-strategy.html. Accessed November 17, 
2021.
    \517\ Kaiser Family Foundation. (2021). Racial and Ethnic Health 
Inequities and Medicare. Available at: https://www.kff.org/medicare/report/racial-and-ethnic-health-inequities-and-medicare/. Accessed 
November 23, 2021.
    \518\ Billioux, A., Verlander, K., Anthony, S., & Alley, D. 
(2017). Standardized Screening for Health-Related Social Needs in 
Clinical Settings: The Accountable Health Communities Screening 
Tool. NAM Perspectives, 7(5). Available at: https://doi.org/10.31478/201705b.
    \519\ Billioux, A., Verlander, K., Anthony, S., & Alley, D. 
(2017). Standardized Screening for Health-Related Social Needs in 
Clinical Settings: The Accountable Health Communities Screening 
Tool. NAM Perspectives, 7(5). Available at: https://doi.org/10.31478/201705b.
    \520\ Centers for Medicare & Medicaid Services. (2021). 
Accountable Health Communities Model. Accountable Health Communities 
Model [verbar] CMS Innovation Center. Accessed November 23, 2021. 
Available at: https://innovation.cms.gov/innovation-models/ahcm.
    \521\ Kamyck, D., Senior Director of Marketing. (2019). CMS 
releases standardized screening tool for health-related social 
needs. Activate Care. Available at: https://blog.activatecare.com/standardized-screening-for-health-related-social-needs-in-clinical-settings-the-accountable-health-communities-screening-tool/.
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    In developing this measure, we identified core HRSN domains based 
on the following criteria: (1) The availability of high-quality 
scientific evidence linking a given HRSN to adverse health outcomes and 
increased healthcare utilization, including hospitalizations, and 
associated costs; (2) the HRSNs can be screened and identified in the 
inpatient setting prior to hospital discharge, addressed by community-
based services, and potentially improve healthcare outcomes, including 
reduced hospital re-admission; and (3) the HRSNs are not systematically 
addressed by healthcare providers.\518\ Based on those criteria, the 
following five domains were selected to screen for social risk factors 
in Medicare and Medicaid beneficiaries under the AHC Model: (1) Food 
insecurity; (2) housing instability; (3) transportation needs; (4) 
utility difficulties; and (5) interpersonal safety. In addition to 
established evidence of their association with health status, risk, and 
outcomes, these five domains were selected because they can be assessed 
across the broadest spectrum of individuals in a variety of 
settings.519 520 521 The five core HRSN domains are 
described in Table IX.E-02.

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[GRAPHIC] [TIFF OMITTED] TR10AU22.156

     
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    \522\ Berkowitz SA, Seligman HK, Meigs JB, Basu S. Food 
insecurity, healthcare utilization, and high cost: a longitudinal 
cohort study. Am J Managed Care. 2018 Sep;24(9):399-404. PMID: 
30222918; PMCID: PMC6426124.
    \523\ Hill-Briggs, F. (2021, January 1). Social Determinants of 
Health and Diabetes: A Scientific Review. Diabetes Care. Available 
at: https://pubmed.ncbi.nlm.nih.gov/33139407/.
    \524\ Seligman, H.K., & Berkowitz, S.A. (2019). Aligning 
Programs and Policies to Support Food Security and Public Health 
Goals in the United States. Annual Review of Public Health, 40(1), 
319-337. Available at: https://pubmed.ncbi.nlm.nih.gov/30444684/.
    \525\ National Academies of Sciences, Engineering, and Medicine 
2006. Executive Summary: Cost-Benefit Analysis of Providing Non-
Emergency Medical Transportation. Washington, DC: The National 
Academies Press. Available at: https://doi.org/10.17226/23285.
    \526\ Hill-Briggs, F. (2021, January 1). Social Determinants of 
Health and Diabetes: A Scientific Review. Diabetes Care. Available 
at: https://pubmed.ncbi.nlm.nih.gov/33139407/.
    \527\ Berkowitz SA, Seligman HK, Meigs JB, Basu S. Food 
insecurity, healthcare utilization, and high cost: a longitudinal 
cohort study. Am J Managed Care. 2018 Sep;24(9):399-404. PMID: 
30222918; PMCID: PMC6426124.
    \528\ Dean, E.B., French, M.T., & Mortensen, K. (2020a). Food 
insecurity, health care utilization, and health care expenditures. 
Health Services Research, 55(S2), 883-893. Available at:  https://doi.org/10.1111/1475-6773.13283.
    \529\ Larimer, M.E. (2009). Health Care and Public Service Use 
and Costs Before and After Provision of Housing for Chronically 
Homeless Persons with Severe Alcohol Problems. JAMA, 301(13), 1349. 
Available at: https://doi.org/10.1001/jama.2009.414.
    \530\ Hill-Briggs, F. (2021). Social Determinants of Health and 
Diabetes: A Scientific Review. Diabetes Care. Available at: https://pubmed.ncbi.nlm.nih.gov/33139407/.
    \531\ Henry, M., de Sousa, T., Roddey, C., Gayen, S., Bednar, 
T.; Abt Associates. The 2020 Annual Homeless Assessment Report 
(AHAR) to Congress; Part 1: Point-in-Time Estimates of Homelessness, 
January 2021. U.S. Department of Housing and Urban Development. 
Accessed November 24, 2021. Available at: https://www.huduser.gov/portal/sites/default/files/pdf/2020-AHAR-Part-1.pdf.
    \532\ Larimer, M.E. (2009). Health Care and Public Service Use 
and Costs Before and After Provision of Housing for Chronically 
Homeless Persons with Severe Alcohol Problems. JAMA, 301(13), 1349. 
Available at: https://doi.org/10.1001/jama.2009.414.
    \533\ Baxter, A., Tweed, E., Katikireddi, S., Thomson, H. 
(2019). Effects of Housing First approaches on health and well-being 
of adults who are homeless or at risk of homelessness: systematic 
review and meta-analysis of randomized controlled trials. Journal of 
Epidemiology and Community Health, 73; 379-387. Available at: 
https://jech.bmj.com/content/jech/73/5/379.full.pdf.
    \534\ National Academies of Sciences, Engineering, and Medicine 
2006. Executive Summary: Cost-Benefit Analysis of Providing Non-
Emergency Medical Transportation. Washington, DC: The National 
Academies Press. Available at: https://doi.org/10.17226/23285.
    \535\ National Academies of Sciences, Engineering, and Medicine 
2006. Executive Summary: Cost-Benefit Analysis of Providing Non-
Emergency Medical Transportation. Washington, DC: The National 
Academies Press. Available at: https://doi.org/10.17226/23285.
    \536\ Hill-Briggs, F. (2021, January 1). Social Determinants of 
Health and Diabetes: A Scientific Review. Diabetes Care. Available 
at: https://pubmed.ncbi.nlm.nih.gov/33139407/.
    \537\ Billioux, A., Verlander, K., Anthony, S., & Alley, D. 
(2017). Standardized Screening for Health-Related Social Needs in 
Clinical Settings: The Accountable Health Communities Screening 
Tool. NAM Perspectives, 7(5). Available at: https://doi.org/10.31478/201705b.
    \538\ Shier, G., Ginsburg, M., Howell, J., Volland, P., & 
Golden, R. (2013). Strong Social Support Services, Such as 
Transportation And Help For Caregivers, Can Lead To Lower Health 
Care Use And Costs. Health Affairs, 32(3), 544-551. Available at: 
https://doi.org/10.1377/hlthaff.2012.0170.
    \539\ Baxter, A., Tweed, E., Katikireddi, S., Thomson, H. 
(2019). Effects of Housing First approaches on health and well-being 
of adults who are homeless or at risk of homelessness: systematic 
review and meta-analysis of randomized controlled trials. Journal of 
Epidemiology and Community Health, 73; 379-387. Available at: 
https://jech.bmj.com/content/jech/73/5/379.full.pdf.
    \540\ Wright, B.J., Vartanian, K.B., Li, H.F., Royal, N., & 
Matson, J.K. (2016). Formerly Homeless People Had Lower Overall 
Health Care Expenditures After Moving into Supportive Housing. 
Health Affairs, 35(1), 20-27. Available at: https://doi.org/10.1377/hlthaff.2015.0393.
    \541\ Billioux, A., Verlander, K., Anthony, S., & Alley, D. 
(2017). Standardized Screening for Health-Related Social Needs in 
Clinical Settings: The Accountable Health Communities Screening 
Tool. NAM Perspectives, 7(5). Available at: https://doi.org/10.31478/201705b.
    \542\ Henry M., de Sousa, T., Roddey, C., Gayen, S., Bednar, T.; 
Abt Associates. The 2020 Annual Homeless Assessment Report (AHAR) to 
Congress; Part 1: Point-in-Time Estimates of Homelessness, January 
2021. U.S. Department of Housing and Urban Development. Accessed 
November 24, 2021. Available at: https://www.huduser.gov/portal/sites/default/files/pdf/2020-AHAR-Part-1.pdf.
    \543\ Larimer, M.E. (2009). Health Care and Public Service Use 
and Costs Before and After Provision of Housing for Chronically 
Homeless Persons with Severe Alcohol Problems. JAMA, 301(13), 1349. 
Available at: https://doi.org/10.1001/jama.2009.414.

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[[Page 49205]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.157

    Utilization of screening tools to identify the burden of unmet 
HRSNs can be a helpful first step in identifying necessary community 
partners and connecting individuals to resources in their communities. 
We believe collecting data across the same five HRSN domains that were 
screened under the AHC Model will illuminate their impact on health 
outcomes and disparities and the care-cost burden for hospitals, and in 
particular for hospitals that serve patients with disproportionately 
high levels of social risk factors. This data collection could inform 
meaningful and sustainable solutions for other provider-types through 
similar collections in other quality reporting 
programs.544 545 546 547 548
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    \544\ The Physicians Foundation: 2020 Survey of America's 
Patients, Part Three. Available at: https://physiciansfoundation.org/wp-content/uploads/2020/10/2020-Physicians-Foundation-Survey-Part3.pdf.
    \545\ Office of the Assistant Secretary for Planning and 
Evaluation (ASPE) (2020). Report to Congress: Social Risk Factors 
and Performance Under Medicare's Value-Based Purchasing Program 
(Second of Two Reports). Available at: https://aspe.hhs.gov/pdf-report/second-impact-report-to-congress.
    \546\ Billioux, A., Verlander, K., Anthony, S., & Alley, D. 
(2017). Standardized Screening for Health-Related Social Needs in 
Clinical Settings: The Accountable Health Communities Screening 
Tool. NAM Perspectives, 7(5). Available at: https://doi.org/10.31478/201705b.
    \547\ Baker, M.C., Alberti, P.M., Tsao, T.Y., Fluegge, K., 
Howland, R.E., & Haberman, M. (2021). Social Determinants Matter for 
Hospital Readmission Policy: Insights From New York City. Health 
Affairs, 40(4), 645-654. Available at: https://doi.org/10.1377/hlthaff.2020.01742.
    \548\ De Marchis, E., Knox, M., Hessler, D., Willard-Grace, R., 
Oliyawola, JN, et al. (2019). Physician Burnout and Higher Clinic 
Capacity to Address Patients' Social Needs. The Journal of the 
American Board of Family Medicine, 32 (1), 69-78.

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[[Page 49206]]

    For data collection of this measure, providers could use a self-
selected screening tool and collect these data in multiple ways, which 
can vary to accommodate the population they serve and their individual 
needs.549 550 One example of such data collection is the AHC 
Model, which uses the standard 10-item AHC Health-Related Social Needs 
Screening Tool to enable providers to identify HRSNs in the five core 
domains (described in Table IX.E-02.) of community-dwelling Medicare, 
Medicaid, and dually eligible beneficiaries.\551\ Since its inception, 
the AHC Model has been implemented across many care delivery sites in 
diverse geographic locations across the U.S.\552\ More than one million 
Medicare and Medicaid beneficiaries have been screened using the AHC 
Health-Related Social Needs Screening Tool, which has been evaluated 
psychometrically and demonstrated evidence of both reliability and 
validity, including inter-rater reliability and concurrent and 
predictive validity.\553\ Moreover, the screening instrument can be 
implemented in a variety of clinical settings, including primary care, 
EDs, labor and delivery units, inpatient units (including mental and 
behavioral health settings), and other places where patients seek 
healthcare.\554\
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    \549\ Social Interventions Research & Evaluation Network. 
(2019). Social Needs Screening Tool Comparison Table. Available at: 
https://sirenetwork.ucsf.edu/tools-resources/resources/screening-tools-comparison. Accessed January 18, 2021.
    \550\ Centers for Medicare & Medicaid Services. (2021). A Guide 
to Using the Accountable Health Communities Health-Related Social 
Needs Screening Tool: Promising Practices and Key Insights (June 
2021). Available at: https://innovation.cms.gov/media/document/ahcm-screeningtool-companion. Accessed January 18, 2021.
    \551\ More information on the HRSN Screening Tool is available 
at: https://innovation.cms.gov/files/worksheets/ahcm-screeningtool.pdf.
    \552\ RTI International. (2020). Accountable Health Communities 
(AHC) Model Evaluation. Available at: https://innovation.cms.gov/data-and-reports/2020/ahc-first-eval-rpt.
    \553\ Lewis C., Wellman R., Jones S., Walsh-Bailey C., Thompson 
E., Derus A., Paolino A., Steiner J., De Marchis E., Gottlieb L., 
and Sharp A. (2020). Comparing the Performance of Two Social Risk 
Screening Tools in a Vulnerable Subpopulation. J Family Med Prim 
Care. 2020 Sep; 9(9): 5026-5034. Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7652127/.
    \554\ CMS. A Guide to Using the Accountable Health Communities 
Health-Related Social Needs Screening Tool: Promising Practices and 
Key Insights. June 2021. Accessed: November 23, 2021. Available at: 
https://innovation.cms.gov/media/document/ahcm-screeningtool-companion.
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    The intent of this measure is to promote adoption of HRSN screening 
by hospitals. We encourage hospitals to use the screening as a basis 
for developing their own individual action plans (which could include 
navigation services), as well as opportunities for initiating and 
improving partnerships between healthcare delivery and community-based 
services. This effort will yield actionable information to close the 
disparity gap by encouraging hospitals to identify patients with HRSNs, 
with a reciprocal goal of partnering with community-based organizations 
to connect those individuals to community support to help address those 
risks.
    Under our Meaningful Measures Framework,\555\ the Screening for 
Social Drivers of Health measure addresses the quality priority of 
``Work with Communities to Promote Best Practices of Healthy Living'' 
through the Meaningful Measures Area of ``Equity of Care.'' 
Additionally, pursuant to Meaningful Measures 2.0, this measure 
addresses the ``healthcare equity'' priority area and aligns with our 
commitment to introduce plans to close health equity gaps and promote 
equity through quality measures, including to ``develop and implement 
measures that reflect social and economic determinants.'' \556\ 
Development and proposal of this measure also aligns with our strategic 
pillar to advance health equity by addressing the health disparities 
that underlie our health system.\557\
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    \555\ Centers for Medicare & Medicaid Services. Meaningful 
Measures Framework. Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/CMS-Quality-Strategy.
    \556\ Centers for Medicare & Medicaid Services. Meaningful 
Measures 2.0: Moving from Measure Reduction to Modernization. 
Available at: https://www.cms.gov/meaningful-measures-20-moving-measure-reduction-modernization. We note that Meaningful Measures 
2.0 is still under development.
    \557\ Brooks-LaSure, C. (2021). My First 100 Days and Where We 
Go From Here: A Strategic Vision for CMS. Available at: https://www.cms.gov/blog/my-first-100-days-and-where-we-go-here-strategic-vision-cms.
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    This measure (alongside the Screen Positive Rate for Social Drivers 
of Health measure) will be the first patient-level measurement of 
social drivers of health in the Hospital IQR Program. We believe this 
measure is appropriate for the measurement of the quality of care 
furnished by hospitals in inpatient settings. Screening during 
inpatient hospitalization will allow healthcare providers to identify 
and potentially help address HRSNs as part of discharge planning and 
contribute to long-term improvements in patient outcomes. This will 
have a direct and positive impact on hospital quality performance. 
Collecting baseline data via this measure is crucial in informing 
design of future measures that could enable us to set appropriate 
performance targets for hospitals.
(b) Overview of Measure
    The Screening for Social Drivers of Health measure assesses whether 
a hospital implements screening for all patients that are 18 years or 
older at time of admission for food insecurity, housing instability, 
transportation needs, utility difficulties, and interpersonal safety. 
To report on this measure, hospitals will provide: (1) The number of 
inpatients admitted to the hospital who are 18 years or older at time 
of admission and who are screened for all \558\ of the five HRSNs: Food 
insecurity, housing instability, transportation needs, utility 
difficulties, and interpersonal safety; and (2) the total number of 
patients who are admitted to the hospital who are 18 years or older on 
the date they are admitted.
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    \558\ In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28502), 
we stated ``for each of the five HRSNs.'' We have updated the 
preamble of the final rule to state ``for all five HRSNs'' as per 
the measure specifications and in alignment with the language 
throughout the preamble.
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    The Screening for Social Drivers of Health (MUC21-136) measure was 
included in the publicly available ``List of Measures Under 
Consideration for December 1, 2021'' (MUC List).\559\ The MAP Rural 
Health Workgroup and the Health Equity Advisory Group reviewed the 
measure on December 8, 2021, and December 9, 2021, respectively. Both 
groups indicated that screening for social risk factors would inform 
future efforts to expand capabilities to capture data that demonstrate 
the extent to which improvements in healthcare quality contribute to 
reductions in health disparities and the impact of serving patients at 
higher risk for adverse health outcomes on healthcare quality at the 
organization level. Although MAP stakeholders expressed concerns 
regarding standardization and the need to emphasize the link between 
the measure and better healthcare outcomes for patients, the measure 
developer stated that the focus at this point was to establish standard 
social drivers of health screening measures and not to dictate to 
hospitals and providers which tool they use or how to address the needs 
of their patients, citing that multiple CMS models have demonstrated 
the feasibility of implementing HRSN screening. However, we acknowledge 
the value and importance of tools which support

[[Page 49207]]

the interoperability of HRSN data and encourage the use of health IT-
enabled assessment instruments with coded questions. We also refer 
readers to sections IX.E.5.b.(1).(g). where we discuss measure 
reporting. The MAP Health Equity Advisory Group majority voted that 
this measure has potential or high potential to have a positive impact 
by decreasing health disparities. The MAP Rural Health Workgroup 
majority voted agreement or strong agreement that this measure is 
suitable for use with rural providers.
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    \559\ Centers for Medicare & Medicaid Services. (2021). List of 
Measures Under Consideration for December 1, 2021. Available at: 
https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96464.
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    On December 15, 2021, the MAP Hospital Workgroup reviewed the MUC 
List, including the Screening for Social Drivers (MUC21-136) measure. 
The MAP Hospital Workgroup discussion was similar to that of the MAP 
Health Equity Advisory Group and MAP Rural Health Workgroup, and 
ultimately voted to conditionally support the measure pending NQF 
endorsement. On January 19, 2022, the MAP Coordinating Committee 
reviewed the MUC List including the Screening for Social Drivers of 
Health (MUC21-136) measure and voted to uphold the MAP Hospital 
Workgroup recommendation of conditional support for rulemaking.\560\
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    \560\ National Quality Forum. (2022). Measure Applications 
Partnership (MAP) 2021-2022 Final Recommendations. Available at: 
https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96698.
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    We intend to submit this measure in future for NQF endorsement. We 
note that under section 1866(b)(3)(B)(viii)(IX)(aa) of the Act, each 
measure specified by the Secretary shall be endorsed by the entity with 
a contract under section 1890(a) of the Act (the NQF is the entity that 
currently holds this contract). Under section 
1886(b)(3)(B)(viii)(IX)(bb) of the Act, in the case of a specified area 
or medical topic determined appropriate by the Secretary for which a 
feasible and practical measure has not been endorsed by the entity with 
a contract under section 1890(a) of the Act, the Secretary may specify 
a measure that is not so endorsed as long as due consideration is given 
to measures that have been endorsed or adopted by a consensus 
organization identified by the Secretary. We reviewed NQF-endorsed 
measures and were unable to identify any other NQF-endorsed measures on 
this this topic, and, therefore we believe the exception in section 
1886(b)(3)(B)(viii)(IX)(bb) of the Act applies.
    Measure specifications for this measure are available on the 
QualityNet website at: https://qualitynet.cms.gov (or other successor 
CMS designated websites).
(c) Cohort
    The Screening for Social Drivers of Health measure assesses the 
total number of patients, aged 18 years and older, screened for social 
risk factors (specifically, food insecurity, housing instability, 
transportation needs, utility difficulties, and interpersonal safety) 
during a hospital inpatient stay. The measure cohort includes patients 
who are admitted to an inpatient hospital stay and are 18 years or 
older on the date of admission.
(d) Numerator
    The numerator consists of the number of patients admitted to an 
inpatient hospital stay who are 18 years or older on the date of 
admission and are screened for all \561\ of the following five HRSNs: 
Food insecurity, housing instability, transportation needs, utility 
difficulties, and interpersonal safety during their hospital inpatient 
stay.
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    \561\ In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28502), 
we stated ``one or all of the following five HRSNs.'' We have 
updated the preamble of the final rule in this instance to state 
``all five HRSNs'' as per the measure specifications and in 
alignment with the language throughout the preamble.
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(e) Denominator
    The denominator consists of the number of patients who are admitted 
to a hospital inpatient stay and who are 18 years or older on the date 
of admission. The following patients will be excluded from the 
denominator: (1) Patients who opt-out of screening; and (2) patients 
who are themselves unable to complete the screening during their 
inpatient stay and have no legal guardian or caregiver able to do so on 
the patient's behalf during their inpatient stay.
(f) Measure Calculation
    The Screening for Social Drivers of Health measure will be 
calculated as the number of patients admitted to an inpatient hospital 
stay who are 18 years or older on the date of admission screened for 
all \562\ five HRSNs (food insecurity, housing instability, 
transportation needs, utility difficulties, and interpersonal safety) 
divided by the total number of patients 18 years or older on the date 
of admission admitted to the hospital.
---------------------------------------------------------------------------

    \562\ In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28502), 
we stated ``one or all of the following five HRSNs.'' We have 
updated the preamble of the final rule in this instance to state 
``all five HRSNs'' as per the measure specifications and in 
alignment with the language throughout the preamble.
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(g) Data Submission and Reporting

    We are finalizing voluntary reporting of the Screening for Social 
Drivers of Health measure beginning with the CY 2023 reporting period, 
followed by mandatory reporting on an annual basis beginning with the 
CY 2024 reporting period/FY 2026 payment determination and for 
subsequent years.
    Due to variability across hospital settings and the populations 
they serve, we are allowing hospitals flexibility with selection of 
tools to screen patients for food insecurity, housing instability, 
transportation needs, utility difficulties, and interpersonal safety.
    Potential sources of these data could include, for example, 
administrative claims data, electronic clinical data, standardized 
patient assessments, or patient-reported data and surveys. Multiple 
screening tools exist and many hospitals already have screening tools 
integrated into their electronic health records (EHRs). We suggest 
hospitals refer to the Social Interventions Research and Evaluation 
Network (SIREN) website, for example, for comprehensive information 
about the most widely used HRSN screening tools.563 564 
SIREN contains descriptions of the content and characteristics of 
various tools, including information about intended populations, 
completion time, and number of questions.
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    \563\ Social Interventions Research & Evaluation Network. 
(2019). Social Needs Screening Tool Comparison Table. Available at: 
https://sirenetwork.ucsf.edu/tools-resources/resources/screening-tools-comparison. Accessed January 18, 2021.
    \564\ The Social Interventions Research and Evaluation Network 
(SIREN) at University of California San Francisco was launched in 
the spring of 2016 to synthesize, disseminate, and catalyze research 
on the social determinants of health and healthcare delivery.
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    We note that providers participating in the Hospital IQR Program 
must use certified EHR technology (CEHRT) that has been certified to 
the 2015 Edition of health IT certification criteria under the Office 
of the National Coordinator for Health Information Technology (ONC) 
Health IT Certification Program, and extraction of structured data from 
a certified EHR can make the data more accessible for utilization and 
submission for quality measurement reporting (86 FR 45383). Use of 
certified health IT can also support capture of HRSN information in an 
interoperable fashion so that this data can be shared across the care 
continuum to support coordinated care. For instance, in the 2020 ONC 
21st Century Cures Act final rule, ONC adopted a new framework for the 
core data set which certified health IT products must exchange, called 
the United States Core Data for Interoperability (USCDI) (85 FR 25669). 
Version 2 of the USCDI, published in July 2021, included new data 
classes for social determinants of health (SDOH). These include 
standards to capture

[[Page 49208]]

SDOH Problems/Health Concerns, SDOH Interventions, SDOH Goals, and SDOH 
Assessments. ONC recently published USCDI Version 3, which maintains 
the SDOH elements in Version 2 while adding additional data 
elements.\565\ While adoption of USCDI Version 2 is not a requirement 
for ONC Health IT Certification at this time, under ONC's Standards 
Version Advancement Process,\566\ developers of certified health IT may 
upgrade their certified health IT products to USCDI Version 2 to 
support the availability of information about social drivers of health. 
Version 3 will also be considered under the SVAP process.
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    \565\ Office of the National Coordinator for Health IT. (2022). 
United States Core Data for Interoperability, Version 3 (July 2022). 
Available at: https://www.healthit.gov/isa/sites/isa/files/2022-07/USCDI-Version-3-July-2022-Final.pdf.
    \566\ Office of the National Coordinator for Health IT. (2022). 
Standards Version Advancement Process. Available at: https://www.healthit.gov/topic/standards-version-advancement-process-svap.
---------------------------------------------------------------------------

    Additional stakeholder efforts are underway to expand capabilities 
to capture additional social determinants of health data elements 
include initiatives such as the Gravity Project \567\ to identify and 
harmonize social risk factor data for interoperable electronic health 
information exchange. We note these various efforts and encourage use 
of tools that will meet information exchange standards and facility 
interoperability. We also encourage providers to identify and utilize 
tools that rely on standards-based approaches to data collection and 
utilization to support interoperability of these data.
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    \567\ See https://thegravityproject.net/.
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    Hospitals are required to submit information for structural 
measures once annually using a CMS-approved web-based data collection 
tool available within the Hospital Quality Reporting (HQR) System 
(previously referred to as the QualityNet Secure Portal). We refer 
readers to section IX.E.10. of the preamble of this final rule (Form, 
Manner, and Timing of Quality Data Submission) for more details on our 
previously finalized data submission and deadline requirements across 
measure types, and specifically, section IX.E.10.i. for our data and 
submission requirements for structural measures.
    We invited public comment on this proposal.
    We note to readers that due to the complementary nature of the 
Screening for Social Drivers of Health and the Screen Positive Rate for 
Social Drivers of Health, most of the public comments received were 
indicated as applicable for both measures. We are summarizing and 
responding to those comments relevant to the Screening for Social 
Drivers of Health first and then providing a summary and responses to 
both measures afterwards. Comments specifically about the Screen 
Positive Rate for Social Drivers of Health measure are in the 
subsequent section.
    Comment: Many commenters emphasized support for requiring screening 
and reporting for all five HRSN domains, including housing instability, 
food insecurity, transportation needs, utility difficulties, and 
interpersonal safety. A few commenters expressed support for the 
measure but requested that we confirm their understanding that the 
measure as specified requires hospitals to screen for all five HRSNs.
    Response: We thank the commenters for their support and confirm 
that hospitals would screen for all five HRSN domains. We note that 
there were two instances in the preamble of the FY 2023 IPPS/LTCH PPS 
proposed rule in which we made a technical error by inconsistently 
stating screening for ``one or all'' of the five HRSNs (87 FR 28502 and 
87 FR 28503; sections IX.E.7.b.(1).(d). and IX.E.7.b.(1).(f).). The 
language should have indicated that this measure requires screening for 
all five HRSNs as per the measure specifications that we referred to 
throughout the preamble of the proposed rule (87 FR 28497) and as 
reviewed as part of the MUC review process.\568\ We have now updated 
and footnoted these two instances in the preamble of this final rule 
and clarify here that this measure requires that patients be screened 
for all five HRSNs.
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    \568\ National Quality Forum. Measure Applications Partnership 
Hospital Workgroup (2021). Virtual Review Meeting Summary available 
at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96629.
---------------------------------------------------------------------------

    Comment: Many commenters supported our proposal to adopt the 
Screening for Social Drivers of Health measure beginning with voluntary 
reporting for the CY 2023 reporting period and mandatory reporting 
beginning with the CY 2024 reporting period/FY 2026 payment 
determination and for subsequent years. Specifically, many commenters 
applauded this proposal as one of the first patient-centered quality 
measures that will allow health systems and care providers to use a 
data-driven approach to account for the impact of drivers of health on 
patient health outcomes and healthcare access, including illness 
complexity, variations in severity, and resource utilization. Several 
commenters expressed their belief that adoption of this measure, 
together with the Screen Positive Rate for Social Drivers of Health 
measure, will improve health outcomes and healthcare costs. Some 
commenters stated that adopting both Social Drivers of Health measures 
could lay the foundation for future policy initiatives that will 
increase equitable access to healthy foods, safe and affordable 
housing, safe physical environments, and affordable healthcare.
    Response: We thank commenters for their support of the Screening 
for Social Drivers of Health measure. We appreciate all of the comments 
and interest in this important topic. Public input is very valuable in 
the continuing development of our health equity quality measurement 
efforts and broader commitment to health equity. We agree that this 
measure, in combination with the Screen Positive Rate for Social 
Drivers of Health measure, will be a significant first step towards 
addressing the role of HRSNs in improving health equity, one of our 
quality improvement goals.
    Comment: Many commenters expressed support for the measure and 
applauded what they believe is a necessary step towards accounting for 
the role of drivers of health in persistent health disparities that 
perpetuate the health equity gap and inflate healthcare costs for 
populations that have been historically underserved. Many commenters 
supported the adoption of the measure, noting it would enable 
healthcare providers and other healthcare professionals to take a data-
driven approach to identifying important social risk factors and unmet 
needs among under-resourced populations across settings. Several 
commenters referenced the role the COVID-19 pandemic has played in 
magnifying pre-existing disparities in drivers of health and their 
impact on health outcomes and healthcare access among historically 
underserved populations in the U.S. Some commenters identified specific 
opportunities for drivers of health data to enhance care continuity 
that is essential for under-resourced population groups. A commenter 
recommended we start drivers of health screening in vulnerable 
populations first.
    Response: We thank the commenters for their support of the measure 
and the input shared on its utility. We agree with commenters that 
drivers of health data are a critical first step towards accounting for 
the profound influence these factors have on health outcomes, 
especially in patient groups that experienced the disproportionate 
effects of the COVID-19 pandemic, healthcare providers who deliver care 
to groups

[[Page 49209]]

who have been historically underserved by the healthcare system, and 
ultimately, the costs associated with health disparities. We are 
committed to closing the health equity gap and this measure is a step 
towards that goal. The five HRSN domains are derived from a robust 
evidence base that has demonstrated over time both direct correlations 
between these drivers of health and patient outcomes and significant 
benefits associated with relevant interventions (87 FR 24898). We 
expect the data captured by this measure will inform meaningful and 
sustainable solutions for other provider-types through similar data 
collection in other quality reporting programs. While we appreciate the 
recommendation to address screening in populations who have been 
historically underserved by the healthcare system first, we believe 
national implementation of this measure in conjunction with the Screen 
Positive Rate for Social Drivers of Health measure will allow us to 
more accurately identify those hospital communities where there may be 
higher rates of patients who indicate one or more of the five HRSNs.
    Comment: Several commenters supported our proposal, noting their 
belief that the measure will advance CMS' strategic pillars, 
specifically relative to advancing health equity. Some commenters 
viewed adoption of this measure as an initial, necessary, and logical 
outgrowth from CMS' strategic pillar around health equity because it 
will address the interactions between social conditions and health 
outcomes on a broad scale and facilitate true care continuity for 
patients experiencing the impact of drivers of health. Some commenters 
noted the measure presents opportunity for alignment across public and 
private quality performance measurement, potential to inform healthcare 
benefit design across systems of care and payment programs, and 
alignment with the CY 2023 Medicare Advantage and Part D rule and the 
Accountable Care Organization Realizing Equity, Access, and Community 
Health (ACO REACH) Model, both of which they note include requirements 
for including drivers of health in enrollee health risk assessments.
    Response: We thank the commenters for their support and appreciate 
their input. We agree that drivers of health data will account for 
critical factors that impact patient outcomes and, consequently, 
quality performance. We believe HRSN screening will help healthcare 
professionals to explain the direct relationship between HRSNs and poor 
health outcomes and also strengthen collaboration between hospitals and 
community-based service providers. Further, we believe this data 
collection will inform meaningful and sustainable solutions for other 
provider types through similar collections in other quality reporting 
programs (87 FR 28501). We also agree that this measure aligns with 
proposals included in the CY 2023 Medicare Advantage and Part D rule 
(82 FR 27726) and the ACO REACH Model \569\ as they both included 
proposals with a focus on inclusion of drivers of health and promotion 
of health equity.
---------------------------------------------------------------------------

    \569\ Centers for Medicare & Medicaid Services. ACO REACH. 
(Accessed July 19, 2022). Available at: https://innovation.cms.gov/innovation-models/aco-reach.
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    Comment: Many commenters supported our proposal to adopt this 
measure, noting it would help support efforts to connect patients with 
relevant community resources, which in turn could interrupt the 
downstream effects of poor health outcomes and ultimately generate cost 
savings associated with healthcare delivery. Several commenters 
emphasized that adoption of the two Social Drivers of Health measures 
will support hospitals and health systems in addressing health 
disparities by encouraging meaningful collaboration with existing 
community-based organizations and guiding future public and private 
resource allocation to enhance these partnerships. Many commenters 
acknowledged that the measure data can be leveraged to support 
investments in and linkage to community resources; for example, 
building closed-loop referrals that link patients, healthcare 
providers, and community resources. A commenter identified community-
based organizations and federally qualified health centers (FQHCs) as 
priority recipients of referral capacity-building resources from CMS. A 
commenter noted that the proposal will contribute to innovations in 
health and social care delivery.
    Response: We thank the commenters for their feedback and support. 
We agree with commenters that availability of drivers of health quality 
data will potentially identify innovative opportunities to support 
enhanced availability of community resources to meet the needs 
identified by both these Social Drivers of Health quality measures. We 
share the commenters' belief that this measure could support efforts to 
connect patients in need with community resources.
    Comment: Some commenters identified promotion and support for 
healthy aging as a potential benefit of adopting this measure. A few 
commenters described how the burdens experienced by patients with HRSNs 
often extend to caregivers. Some commenters expressed particular 
support for the emphasis this measure would place on food insecurity, 
given the direct association between food insecurity and chronic 
disease risk, healthcare utilization, and adverse health outcomes.
    Response: We agree and thank the commenters for their support. We 
agree that HRSNs often extend to caregivers and other household 
members. We refer readers to our Caregiver Partners Workgroup which 
works to build bridges with caregiver organizations, both federal and 
non-federal, to better serve Americans in need with national and local 
resources to assist in their caregiving efforts.\570\ We also refer 
readers to section IX.E.5.f. of the preamble of this final rule in 
which we discuss our proposal to adopt the Global Malnutrition 
Composite Score eCQM.
---------------------------------------------------------------------------

    \570\ Centers for Medicare & Medicaid Services. (2022). 
Caregiver Partners. Available at: https://www.cms.gov/Outreach-and-Education/Outreach/Partnerships/Caregiver.
---------------------------------------------------------------------------

    Comment: Many commenters noted that physicians are held clinically 
and financially accountable for patient outcomes without consideration 
of the extensive toll that HRSNs take on health outcomes over time. 
Several commenters believed the COVID-19 pandemic was instrumental in 
revealing the impact of health disparities on physician burnout, 
especially among providers who primarily deliver healthcare in 
communities that have been historically under-resourced. Several 
commenters supported our proposal to adopt the measure believing it 
could provide data that could be used to modify risk adjustment 
performance and payment standards to reflect more accurately the role 
of HRSNs in contributing to poor health outcomes and associated costs. 
A commenter described the dilemma of providing care to patients with 
significant unmet HRSNs and subsequent financial penalization for poor 
health outcomes as ``psychic risk'' that contributes to physician 
burnout. Some commenters noted their expectation that by facilitating 
investments in community resources, adoption of both Social Drivers of 
Health measures may reduce healthcare provider burden.
    Response: We appreciate the commenters' feedback and acknowledge 
the burden that many healthcare providers experience in providing care 
to patients with significant drivers of health needs. Healthcare 
providers face

[[Page 49210]]

the challenges of trying to meet complex patient needs while being 
tasked with achieving quality performance standards that inevitably are 
impacted by their patients' unmet needs. We are committed to developing 
a better understanding of the role that drivers of health play in 
patient outcomes and hospital and physician quality performance. This 
measure is a first step towards achieving greater health equity and we 
recognize the central roles that hospitals and healthcare providers 
will continue to play in creating sustainable improvements in our 
quality programs.
    Comment: Several commenters expressed support for the measure but 
requested we extend the proposed voluntary reporting period and delay 
mandatory reporting. Commenters cited a number of specific reasons, 
including: Operational complexity of developing new data collection and 
reporting protocols as well as revising workflows and training staff, 
ongoing constraints related to the COVID-19 PHE, and other resource 
limitation challenges such as addressing the numerous EHR-related 
reporting requirements. A commenter recommended we implement the 
measures over a longer period of time to ensure that resources to 
support health equity advancement result in improved health outcomes 
and avoid eroding patient trust in the healthcare system.
    A commenter recommended further measure development prior to 
implementation to allow time for determination of data collection 
requirements. Several commenters did not support adoption of the 
measure, noting their belief that the CY 2024 reporting period/FY 2026 
payment determination timeline for mandatory reporting would be too 
soon for generating reliable baseline data, and instead recommended 
extending the voluntary reporting period and delaying the mandatory 
reporting period. A commenter believed the proposed timeline for 
implementation will be inadequate for hospitals despite the proposed 
flexibilities.
    Response: We thank the commenters for their support and feedback. 
We appreciate their concerns about the operational complexity of 
introducing drivers of health quality measures into existing clinical 
workflows and EHR systems. While we agree implementation of these two 
Social Drivers of Health measures will be a major undertaking for some 
providers, especially given the ongoing COVID-19 PHE, we also recognize 
that the COVID-19 PHE magnified the disproportionate burden of drivers 
of health on communities who have been historically under-
resourced.\571\ Beginning to collect the data remains imperative as we 
continue to build on our strategic pillar to advance health equity by 
addressing the health disparities that underlie our health system. We 
have therefore determined that the proposed voluntary and mandatory 
reporting periods prioritize the urgency of capturing drivers of health 
data and taking actionable steps towards closing the health equity gap. 
As stated in the proposed rule, potential sources of these data could 
include, for example, administrative claims data, electronic clinical 
data, standardized patient assessments, or patient-reported data and 
surveys (87 FR 28503). Additionally, we note that 92 percent of 
hospitals already screen for one or more of the five HRSNs--food 
insecurity, housing instability, transportation needs, utility 
difficulties, and interpersonal safety--specified in the proposed 
measures (87 FR 28498). We believe that this is a strong indication 
that hospitals have processes in place to conduct the screening 
required.
---------------------------------------------------------------------------

    \571\ Centers for Disease Control and Prevention.(2020). CDC 
COVID-19 Response Health Equity Strategy: Accelerating Progress 
Towards Reducing COVID-19 Disparities and Achieving Health Equity. 
July 2020. Available at: https://www.cdc.gov/coronavirus/2019-ncov/community/health-equity/cdc-strategy.html. Accessed November 17, 
2021.
---------------------------------------------------------------------------

    Comment: A commenter recommended we require mandatory reporting 
without delay to encourage hospitals with existing screening 
capabilities to start data collection.
    Response: We thank the commenter for this feedback. We believe the 
voluntary reporting period will be necessary for some hospitals as they 
integrate this measure specifications into their workflow. We encourage 
hospitals that already have such capacity and processes in place to 
initiate screening at the start of the voluntary period.
    Comment: A few commenters supported the measure but recommended it 
not be included in the Hospital IQR Program. A commenter believed the 
measure would achieve its intended purpose in the Hospital Outpatient 
Quality Reporting (OQR) Program instead. A commenter was concerned 
about the inclusion of this structural measure in quality performance 
programs.
    Response: We thank the commenters for their recommendation, but we 
respectfully disagree that the proposed measure is not suited for the 
Hospital IQR Program. We believe this measure, alongside the Screen 
Positive Rate for Social Drivers of Health measure, serves as a key 
first step in measuring and promoting quality improvement in the care 
delivered by hospitals in inpatient settings and will additionally 
encourage hospitals to collaborate with community-based organizations 
as part of discharge planning and implement closed-loop referrals that 
will more adequately address unmet social needs that drive hospital 
readmissions and diminished health outcomes following hospitalization. 
Given that individuals with high HRSNs also have greater healthcare 
needs that result in hospitalization, we believe the proposed Screening 
for Social Drivers of Health measure is appropriate for the measurement 
of the quality of care furnished by hospitals in inpatient settings. 
Moreover, hospital accountability for screening is a critical step 
towards eliminating health disparities in health outcomes among 
populations that have been historically underserved by the healthcare 
system.
    Comment: A commenter requested clarification of how hospitals will 
report the Screening for Social Drivers of Health data.
    Response: We appreciate the commenter's request for clarification. 
In the proposed rule, we describe the measure specifications and data 
submission requirements, which can be found at https://qualitynet.cms.gov/inpatient/iqr/resources (87 FR 28502). Hospitals are 
required to submit information for structural measures once annually 
using a CMS-approved web-based data collection tool available within 
the HQR System (87 FR 28503). We also refer readers to section IX.E.10. 
of the preamble of this final rule (Form, Manner, and Timing of Quality 
Data Submission) for more details on our previously finalized data 
submission and deadline requirements across measure types, and 
specifically, section IX.E.10.i. for our data and submission 
requirements for structural measures.
    Comment: Several commenters commented on our flexibility with 
screening tool selection. Several commenters supported this 
flexibility. Several commenters recommended we require hospitals take a 
standardized screening approach to implementing drivers of health 
assessments. A commenter believed that requiring standardized 
screenings would allow for more valid comparisons between hospitals.
    A commenter supported the measure and emphasized the importance of 
allowing flexibility in screening tool selection until more is 
understood about data capture. A few commenters recommended we 
encourage hospitals to use validated, widely-accepted

[[Page 49211]]

screening instruments to ensure data reliability and comparability to 
inform risk adjustment and further policy development. A commenter 
recommended we prioritize high-quality screening over volume of 
screening and track the number of patients who are linked to community-
based resources to promote capacity-building for collaboration. A 
commenter recommended we clearly define screening to ensure active 
screening of drivers of health directly with the patient. Some 
commenters supported establishment of drivers of health screening but 
did not support the proposed approach of allowing hospitals flexibility 
with tool selection. A few commenters believed this flexibility will 
produce results that are not reliable and questioned whether there 
would be adequate denominator sizes to calculate reliable and valid 
comparisons.
    Response: We appreciate all the commenters' support and input on 
the use of a screening tool. We share the enthusiasm of many of the 
commenters about the potential for improving quality of care and 
advancing health equity by addressing the unmet social needs of 
hospital patients. We agree that allowing hospitals flexibility with 
tool selection is a tradeoff, but, as we discussed previously, we 
believe it is necessary to allow hospitals flexibility because this 
measure is the first step in what we see as a longer journey to address 
unmet needs. This is the first time we will be collecting drivers of 
health screening data as part of quality performance measurement and we 
want to ensure that all hospitals are working towards initial 
screening, in a form that works for them. As we indicated previously, 
health equity is a key priority and we intend to continue to develop 
relevant measures. We recognize that hospitals often employ different 
strategies for screening for social needs across their patient 
populations. As such, in the FY 2023 IPPS/LTCH PPS proposed rule, we 
noted that hospitals pursuing this quality measure may use a self-
selected screening instrument, which can vary to accommodate the 
population they serve and their individual needs, and that social needs 
data collected to satisfy this quality measure could include, for 
example, administrative claims data, electronic clinical data, 
standardized patient assessments, or patient-reported data and surveys 
(87 FR 28501). We also encouraged standards-based approaches to data 
collection and utilization to support interoperability of these data 
(87 FR 28503).
    We are sensitive to the concerns raised by some commenters about 
the lack of standardization across screening instruments or data 
collection practices, and the challenges this may introduce in the 
consistency of the information collected across hospitals. While we 
acknowledge the potential benefits of a single screening instrument or 
prescribed set of standards, we also recognize the benefits of 
providing hospitals with flexibility to customize screening and data 
collection to their local community contexts and patient populations, 
especially in the initial stages of implementing screening protocols.
    Currently, we intend to continue providing hospitals with 
flexibility regarding the selection of tools to screen patients. 
However, we anticipate additional emphasis on standardized and 
validated screening instruments in future versions of this measure. We 
encourage hospitals to prioritize screening tools that have undergone 
adequate testing to ensure they are accurate and reliable. We believe 
that this measure should promote high-quality screening practices 
which, among other things, ensure accurate identification of unmet 
social needs. We look forward to additional input from stakeholders on 
this topic.
    We also recognize that digital data collection is a necessary path 
for effective and efficient measurement. As part of our Meaningful 
Measures 2.0 Framework \572\ we aim to further shape the entire 
ecosystem of quality measures that promote innovation and modernization 
of all aspects of quality. A priority of the Meaningful Measure 2.0 
Framework is transforming measures to improve quality measure 
efficiency by transitioning to digital measures and using advanced data 
analytics. We aim to transform to all digital quality measures, 
accelerate development of and testing electronic clinical quality 
measures using FHIR API technology for transmitting and receiving 
quality measurement, transform data collection to use FHIR API 
technology, and leverage centralized data analytic tools to examine 
programs and measures.
---------------------------------------------------------------------------

    \572\ We note that Meaningful Measures 2.0 is still under 
development.
---------------------------------------------------------------------------

    Currently, to the extent possible, we encourage hospitals to use 
certified health IT that can also support capture and exchange of 
drivers of health information in a structured and interoperable fashion 
so that these data can be shared across the care continuum to support 
coordinated care. We anticipate additional emphasis on data collection 
using certified health IT in future versions of this measure. We will 
continue to take all concerns, comments, and suggestions into account 
for future development and expansion of this measure. We agree that 
allowing hospitals flexibility with tool selection is a tradeoff. This 
is the first time we will be collecting drivers of health screening 
data as part of quality performance measurement. We believe allowing 
hospitals flexibility during this initial first step will further 
enable them to adopt solutions that use structured EHR data elements to 
reflect patients' drivers of health status. We are taking commenters' 
recommendations under consideration to inform future notice-and-comment 
rulemaking.
    We are taking commenters' recommendations under consideration to 
inform future notice-and-comment rulemaking.
    Comment: Several commenters supported screening for drivers of 
health but expressed concerns regarding individual patient rights and 
transparency. A commenter recommended that patients be granted 
flexibility with timing of screening completion and adequate privacy is 
provided to the patient in the process. A commenter noted patients and 
families should be clearly informed that they can opt-out of screening 
and that their decision would not affect their care. A commenter 
recommended that the language and documentation of HRSNs in patient 
health records be non-stigmatizing and free of bias. Specifically, the 
commenter noted screening should not be included in hospital visit 
charges and that patients should be informed of the right to opt-out of 
screening. A commenter recommended we consider providing hospitals with 
comparative opt-out rates to provide benchmarks for individual 
hospitals to understand their own opt-out rates.
    Response: We thank the commenters for their input. We underscore 
that patients and families will be able to opt-out of screening. 
Specifically, the measure specifications as proposed state that the 
following patients would be excluded from the denominator: (1) Patients 
who opt-out of screening; and (2) patients who are themselves unable to 
complete the screening during their inpatient stay and have no legal 
guardian or caregiver able to do so on the patient's behalf during 
their inpatient stay (87 FR 28502). As discussed earlier, this measure 
does not require use of a specific screening tool. During measure 
development, we gave commenters' concerns significant consideration. As 
we noted in the FY 2023 IPPS/LTCH PPS proposed rule, we

[[Page 49212]]

recommend that hospitals incorporate inclusive language in their 
screening activities to address this potential concern among patient 
and caregiver respondents (87 FR 28505). We strongly recommend that 
hospitals incorporate inclusive language in their screening activities 
to reassure patients that whether they choose to opt-out or answer the 
screenings, the information provided would not be used to stigmatize 
patients or reduce their healthcare benefits. We defer to hospitals to 
make the appropriate disclosures to their patients regarding how the 
collected data are used as well as ensuring that the patient and their 
caregiver(s) are informed of their option to opt-out of screening. 
Commenters' input is very valuable to our continuing development of 
health equity quality measurement and our aims to address the impact of 
HRSNs on healthcare access, utilization, outcomes, and costs.
    Comment: A few commenters expressed concern regarding hospital 
staff training, recommending that staff members who conduct screening 
and follow-up on the results are adequately trained. A few commenters 
recommended delegating screening duties to frontline hospital workers 
who may have demographic congruence with patients.
    Response: We thank the commenters for their input and agree that 
staff training on culturally sensitive engagement and trauma-centered 
care would be helpful. Throughout the FY 2023 IPPS/LTCH PPS proposed 
rule (87 FR 25498 through 25504), we referred to the performance 
evaluation of the AHC Model which reported utilization of multiple 
staffing models that could be adapted to meet the specific workflow 
needs of participating providers, which allowed providers to optimize 
resources to complete screening, navigation, and reporting 
requirements.\573\ AHC Model organizations developed and provided 
structured, systematic training for staff in screening, referral, and 
navigation roles.\574\ Most used routine training approaches that 
included presentations (in person or online), experienced staff 
shadowing, role-playing of routine and challenging activities, staff 
performance reviews, and coaching. Quality was ensured through 
observing screening or navigation encounters, monitoring number of 
screenings completed, and tracking navigation follow-up. Many 
organizations also used innovative training strategies they believed 
were particularly effective. The training strategies included trauma-
informed care, racial inequity and cultural competency training, 
motivational interviewing, and patient engagement.
---------------------------------------------------------------------------

    \573\ RTI International. (2020). Accountable Health Communities 
(AHC) Model Evaluation. Available at: https://innovation.cms.gov/data-and-reports/2020/ahc-first-eval-rpt.
    \574\ Ibid.
---------------------------------------------------------------------------

    Based on the experiences of AHC Model participating providers, we 
believe staff training is feasible, tools and resources are available, 
and the benefits of such trainings could apply beyond the activity of 
screening for HRSNs. As we discussed in the FY 2023 IPPS/LTCH PPS 
proposed rule, 92 percent of hospitals are already screening for one or 
more of the five HRSNs (87 FR 28498). And while only 24 percent are 
screening for all five HRSNs (87 FR 28498), we believe this data is a 
strong indication that screening is occurring in the inpatient hospital 
setting. We encourage hospitals to ensure staff are adequately trained 
to conduct screenings.
    Comment: Some commenters expressed concerns about the timeline for 
screening in the hospital setting. A commenter requested clarification 
on whether screening must take place during each hospital admission, 
especially if screening has already been completed and data captured in 
the EHR during outpatient visits that occurred during the measure 
performance period. A few commenters noted that screening at the time 
of admission may not be feasible due to the patient's physical state 
and medical staff members' focus on stabilization. Some commenters 
noted screening may introduce undue burden to patients. A commenter 
recommended annual distinct patient screening. A few commenters 
recommended we permit hospitals to utilize drivers of health screening 
data previously documented in patient EHRs from care provided in 
ambulatory settings.
    Response: We thank the commenters for their feedback, questions, 
and recommendations. We wish to clarify for stakeholders that screening 
should occur during the hospital stay as noted in the Cohort section of 
the preamble of the proposed rule in which we explain that the measure 
assesses the total number of patients 18 years and older, screened for 
social risk factors during a hospital inpatient stay (87 FR 28502). We 
refer readers to the Data Submission and Reporting section of the 
preamble of the proposed rule in which we explain that hospitals will 
have flexibility with screening and that potential sources of the 
drivers of health data could include, for example, administrative 
claims data, electronic clinical data, standardized patient 
assessments, or patient-reported data and surveys (87 FR 28503). For 
patients frequently admitted to the hospital due to chronic health 
conditions which are exacerbated by HRSNs, hospitals could confirm the 
current status of any previously reported drivers of health and inquire 
about others not previously reported. However, if this information has 
been captured in the EHR in the outpatient setting prior to repeat 
hospital admission, it could be included in hospital reporting of 
numerator and denominator data, during the performance measurement 
period. We will continue evaluating screening requirements in future 
notice-and-comment rulemaking.
    Comment: Several commenters expressed support for the measure but 
recommended modifications and refinements related to the proposed five 
HRSN domains. Some commenters recommended adding more domains in 
addition to the five domains. A commenter suggested eight additional 
domains including financial strain, employment status, family and 
community support, education, physical activity, substance use, mental 
health, and disabilities. A commenter suggested we allow for optional 
reporting of additional domains to inform hospital discharge planning 
and facilitate linkages to community resources. A commenter questioned 
whether the utility difficulties domain would be redundant and better 
suited as a component of the housing instability domain. A few 
commenters recommended removal of the interpersonal safety domain due 
to uniquely sensitive considerations associated with interpersonal 
safety compared to the other four domains. A commenter recommended CMS 
not specify screening domains at all. A commenter believed health 
systems should be allowed to select additional non-essential domains 
and their own specific questions. A commenter expressed concern that 
hospitals might focus on domains and questions that align with existing 
resources that are already offered to patients with given HRSNs. A 
commenter supported the measure and recommended CMS prioritize 
collection of self-reported drivers of health data.
    Response: We thank the commenters for their support and appreciate 
their acknowledgement of the relevance of other drivers of health that 
influence health outcomes and contribute to persistent health 
disparities. We have prioritized selection of the proposed five HRSN 
domains based on existing evidence from both the AHC Model, including 
recommendations from a TEP that informed the initial selection, and

[[Page 49213]]

emerging evidence of correlations between given drivers of health and 
worse health outcomes and/or drivers of health for which interventions 
have shown marked improvements in health outcomes and healthcare 
utilization (87 FR 28498). We remind stakeholders that the proposed 
measure is a first step towards development of a long-term strategy to 
integrate drivers of health data into hospital quality performance 
measurement and our broader commitment to health equity. We believe it 
is imperative that hospitals screen for all five domains, irrespective 
of resource availability.
    Additionally, regarding the concern that hospitals will focus on 
domains that align with their existing resources, we believe that each 
hospital best understands the patient population they serve. As they 
collect these data, we hope that they can then best discern whether 
they have existing resources to meet their populations' unmet needs or 
dedicate further resources to a domain beyond the five required HRSNs 
for which they knew a need exists and now have evidence of the extent 
that resource allocation is necessary. In addition, we highlight that 
the Hospital IQR Program is a pay-for-reporting program, and hospitals 
are not scored based on their performance on measures.
    We thank the commenters for the additional domain suggestions and 
we will consider them as part of any potential future modifications to 
these measures or potential new measure development in future notice-
and-comment rulemaking.
    Comment: Several commenters expressed concern about the lack of 
current NQF endorsement of the proposed measure at the time of proposed 
rule display. A few commenters recommended we delay adoption of the 
measure until NQF endorsement is obtained.
    Response: We have submitted this measure for NQF review and the 
decision is currently pending. Under section 
1886(b)(3)(B)(viii)(IX)(bb) of the Act, in the case of a specified area 
or medical topic determined appropriate by the Secretary for which a 
feasible and practical measure has not been endorsed by the entity with 
a contract under section 1890(a) of the Act, the Secretary may specify 
a measure that is not so endorsed as long as due consideration is given 
to measures that have been endorsed or adopted by a consensus 
organization identified by the Secretary. We reviewed NQF-endorsed 
measures and were unable to identify any other NQF-endorsed measures on 
this topic, and, therefore we believe the exception in section 
1886(b)(3)(B)(viii)(IX)(bb) of the Act applies. We note that the MAP 
also voted to conditionally support this measure for rulemaking (87 FR 
28502).
    Comment: Several commenters recommended we use consistent 
terminology when describing social risk factors related to health 
outcomes.
    Response: We thank the commenters for this feedback. HRSNs, which 
we have previously defined as individual-level, adverse social 
conditions that negatively impact a person's health or healthcare, are 
significant risk factors associated with worse health outcomes as well 
as increased healthcare utilization (87 FR 28502). Conceptually, HRSNs 
exist along a continuum with other equity-related terms--such as 
``social determinants of health'' and ``social risk factors''--used to 
describe upstream factors that can adversely affect the health of 
individuals and communities (87 FR 28497).\575\ We agree these terms 
are often conflated and even used interchangeably, and the variety of 
terms has created both confusion as well as concern, prompting leaders 
in the field to adopt ``drivers of health'' instead.\576\ In the 
future, we intend to utilize ``drivers of health'' terminology to more 
holistically capture aforementioned and related concepts, while 
minimizing potential misinterpretation or negative connotation.
---------------------------------------------------------------------------

    \575\ Institute of Medicine 2014. Capturing Social and 
Behavioral Domains and Measures in Electronic Health Records: Phase 
2. Washington, DC: The National Academies Press. Available at: 
https://doi.org/10.17226/18951. https://innovation.cms.gov/media/document/ahcm-screeningtool-companion.
    \576\ https://www.healthaffairs.org/do/10.1377/forefront.20210429.335599/.
---------------------------------------------------------------------------

    Comment: Several commenters expressed concerns regarding follow-on 
resources not being readily available to address the drivers of health 
for which patients might screen positive. A few commenters noted 
screening should not occur for resources that are not easily obtained.
    Response: We thank the commenters for their input and appreciate 
the concerns noted. During development of both proposed Social Drivers 
of Health measures, we gave this topic significant consideration. The 
intent of the two measures is to promote adoption of HRSNs screening by 
hospitals as well as taking action to connect patients who identify one 
or more HRSNs with available resources (87 FR 28501). Evaluation of the 
AHC Model concluded that universal screening may identify needs that 
would otherwise remain undetected.\577\ While broad availability of 
community-based resources that address patients' health-related social 
needs would be ideal, we believe that one of the benefits of screening 
data will be identification of opportunities to enable meaningful 
action, including prioritizing and investing in such resources (87 FR 
28505). Beginning to collect the data remains imperative and such data 
collection has already allowed some entities to reallocate resources to 
address particular HRSNs that disproportionately affect a given patient 
population or geographic region.\578\
---------------------------------------------------------------------------

    \577\ RTI International. (2020). Accountable Health Communities 
(AHC) Model Evaluation. Available at: https://innovation.cms.gov/data-and-reports/2020/ahc-first-eval-rpt.
    \578\ National Quality Forum (2022). Measure Applications 
Partnership. MAP 2021-2022 Considerations for Implementing Measures 
Final Report--Clinicians, Hospitals, and PAC-LTC. Available at: 
https://www.qualityforum.org/Publications/2022/03/MAP_2021-2022_Considerations_for_Implementing_Measures_Final_Report_-_Clinicians,_Hospitals,_and_PAC-LTC.aspx.
---------------------------------------------------------------------------

    As we noted in the FY 2023 IPPS/LTCH PPS proposed rule, this data 
collection could inform meaningful and sustainable solutions for other 
provider-types through similar collections in other quality reporting 
programs (87 FR 28501). We believe this input is very valuable in the 
continuing development of the CMS health equity quality measurement 
efforts and our aims to acknowledge the impact of HRSNs on healthcare 
access, utilization, outcomes, and costs. We will continue to take all 
concerns, comments, and suggestions into account for any potential 
future development and expansion of our health equity quality 
measurement efforts.
    Comment: Several commenters recommended we ensure alignment with 
Project Gravity standards and promote interoperability standards for 
data collection. A few commenters expressed concerns about 
implementation due to existence of other CMS initiatives that address 
social drivers of health in patient assessments and that this can 
create duplicative performance measures, cause confusion, and waste 
resources. A commenter recommended harmonization of drivers of health 
assessment approaches between CMS and the National Committee for 
Quality Assurance (NCQA).
    Response: We thank the commenters for this feedback. We believe 
this data collection will inform meaningful and sustainable solutions 
for other provider types through similar collections in other quality 
reporting programs (87 FR 28501). We will continue identifying 
opportunities for collaboration with other stakeholders to align 
drivers of health assessment across CMS

[[Page 49214]]

programs. We commend additional stakeholder efforts currently underway 
to expand capabilities to capture additional drivers of health data 
elements, including the Gravity Project.\579\ We support harmonization 
of social risk factor data for interoperable electronic health 
information exchange that will meet information exchange standards (87 
FR 28503).
---------------------------------------------------------------------------

    \579\ https://thegravityproject.net/.
---------------------------------------------------------------------------

    We will continue building the overarching strategy for integrating 
social drivers of health screening into hospital quality improvement 
and future rulemaking, where appropriate. We note that hospitals and 
CAHs participating in the Hospital IQR and Medicare Promoting 
Interoperability Programs must use CEHRT that has been certified to the 
2015 Edition of health IT certification criteria under the ONC Health 
IT Certification Program, and extraction of structured data from a 
certified EHR can make the data more accessible for utilization and 
submission for quality measurement reporting (86 FR 45383). Use of 
certified health IT can also support capture of HRSN information in an 
interoperable fashion so that these data can be shared across the care 
continuum to support coordinated care. We note these various efforts 
and encourage use of tools that will meet information exchange 
standards and facility interoperability (87 FR 28503). We also 
encourage providers to identify and utilize tools that rely on 
standards-based approaches to data collection and utilization to 
support interoperability of these data.
    Comment: Several commenters recommended that we take an incremental 
approach to using the Screening for Social Drivers of Health measure 
data.
    Response: We thank the commenters for their feedback and 
recommendations for an incremental approach. In the proposed rule, we 
stated that collecting these baseline data via this measure would be 
crucial in informing design of future measures (87 FR 28502). If we add 
any data use for risk adjustment of the measure, we would do so in 
future notice-and-comment rulemaking. As noted previously, it would be 
ideal if there were broad availability of community-based resources 
that address patients' HRSNs such that we could evaluate their impact 
on health outcomes. However, the COVID-19 PHE revealed the significant 
and disproportionate burden of drivers of health in historically 
underserved communities. We believe that one of the benefits of 
screening data will be identification of opportunities to enable 
meaningful action, including prioritizing and investing in such 
resources (87 FR 28505). We remain hopeful that these actions will 
enhance patient trust in the healthcare system and trustworthiness of 
the system itself.
    Comment: A commenter requested that future public reporting and 
payment adjustments correlate with care delivered to avoid bias 
stemming from local community sociodemographic characteristics. A 
commenter recommended that instead of requiring low-resourced hospitals 
report on this measure (who may not be able to implement data 
collection and workflow requirements), that we consider incentivizing 
screening instead.
    Response: We note that the Hospital IQR Program is a pay-for-
reporting program, and hospitals' payments are not based on their 
performance on measures. We note that hospitals will receive credit for 
the reporting of their measure results regardless of patients' 
responses to the questions. We refer readers to section 
IX.E.5.b.(1).(g). of this final rule for information on the submission 
and reporting requirements for this measure and to section IX.B. for 
our request for information on the Overarching Principles for Measuring 
Healthcare Quality Disparities Across CMS Quality Reporting Programs.
    Comment: A commenter stated that interpretation of the proposed 
measure is challenging due to the absence of a meaningful goal or 
benchmark for the measure. The commenter believed if a hospital reports 
very low positive screen rates, this may indicate very low HRSNs among 
the patient population, or, a high level of mistrust and discomfort of 
patients to disclose sensitive needs to clinical staff.
    Response: We thank the commenter for this feedback, but we 
respectfully disagree. We refer readers to the Overview section in the 
preamble of the proposed rule where we state, the measure is intended 
to provide information to hospitals on the level of unmet social needs 
among patients served and the extent to which these factors impact 
quality measure performance in the hospital inpatient setting (87 FR 
28505). The Screening for Social Drivers of Health and Screen Positive 
Rate for Social Drivers of Health measures are closely related but 
inform distinct measure results, meaning it would be possible for a 
hospital to have a high screening rate and a lower screen positive 
rate, or a low screening rate and higher screen positive rate, in one 
or more of the five domains.
    Comment: Commenters offered recommendations for future 
consideration for our drivers of health strategy. A commenter 
recommended including the measure in other CMS quality performance 
programs including the Merit-based Incentive Payment System (MIPS) and 
Outpatient Quality Reporting programs, such as the Hospital OQR 
Program. A commenter recommended we conduct outreach with voluntary 
reporters to assess data collection processes and identify potential 
challenges and determine the extent to which the screening information 
supports health equity improvements. A commenter recommended we conduct 
outreach to hospitals to provide education on available screening 
methods.
    Response: We thank the commenters for these recommendations and 
will consider their input. The Social Drivers of Health measures are 
the first of their kind in CMS quality programs. Through adoption of 
these measures in the Hospital IQR Program, we encourage hospitals to 
initiate screening if they have not already done so. In the CY 2023 
Physician Fee Schedule proposed rule, we are also proposing to adopt 
the Screening for Social Drivers of Health measure for MIPS.\580\ 
Further, we believe this data collection will inform meaningful and 
sustainable solutions for other provider types through similar 
collections in other quality reporting programs (87 FR 28501).
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    \580\ Currently on display at: https://www.federalregister.gov/public-inspection/2022-14562/medicare-and-medicaid-programs-calendar-year-2023-payment-policies-under-the-physician-fee-schedule.
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    Comment: A commenter stated there was a lack of evidence to support 
a direct relationship between drivers of health screening and positive 
impact on hospital quality performance because this was not tested in 
the AHC Model.
    Response: We appreciate the commenter's concern, but we 
respectfully disagree. The two Social Drivers of Health measures are 
derived from existing evidence from both the AHC Model \581\ and 
emerging evidence of correlations between the designated drivers of 
health and higher healthcare utilization of emergency departments and 
hospitals, worse health outcomes and/or drivers of health for which 
interventions have shown marked improvements in health outcomes and 
health care utilization (87 FR 28498).
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    \581\ RTI International. (2020). Accountable Health Communities 
(AHC) Model Evaluation. Available at: https://innovation.cms.gov/data-and-reports/2020/ahc-first-eval-rpt.

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[[Page 49215]]

    After consideration of the public comments we received, we are 
finalizing our proposal as proposed.
(2) Screen Positive Rate for Social Drivers of Health Measure
(a) Background
    The impact of social risk factors on health outcomes has been well-
established in the literature. 582 583 584 585 586 The 
Physicians Foundation reported that 73 percent of the physician 
respondents to their annual survey agreed that social risk factors like 
housing instability and food insecurity would drive health services 
demand in 2021.\587\ As noted in the FY 2023 IPPS/LTCH PPS proposed 
rule (87 FR 28497 through 28506), recognizing the need for a more 
comprehensive approach to eliminating the health equity gap, we have 
prioritized development and implementation of quality measures that 
will capture social risk factors and facilitate assessment of their 
impact on health outcomes and disparities and healthcare utilization 
and costs.588 589 590 Specifically, in the inpatient 
setting, we aim to identify patient HRSNs as part of discharge planning 
with the intention of promoting linkages with relevant community-based 
services that will address those needs and support improvements in 
health outcomes following hospitalization.
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    \582\ Institute of Medicine 2014. Capturing Social and 
Behavioral Domains and Measures in Electronic Health Records: Phase 
2. Washington, DC: The National Academies Press. Available at: 
https://doi.org/10.17226/18951.
    \583\ Centers for Medicare & Medicaid Services. (2021). 
Accountable Health Communities Model. Accountable Health Communities 
Model [verbar] CMS Innovation Center. Available at: https://innovation.cms.gov/innovation-models/ahcm. Accessed November 23, 
2021.
    \584\ Kaiser Family Foundation. (2021). Racial and Ethnic Health 
Inequities and Medicare. Available at: https://www.kff.org/medicare/report/racial-and-ethnic-health-inequities-and-medicare/. Accessed 
November 23, 2021.
    \585\ Milkie Vu et al. Predictors of Delayed Healthcare Seeking 
Among American Muslim Women, Journal of Women's Health 26(6) (2016) 
at 58; Nadimpalli SB, Cleland CM, Hutchinson MK, Islam N, Barnes LL, 
Van Devanter N. (2016) The Association between Discrimination and 
the Health of Sikh Asian Indians. Health Psychology, 35(4), 351-355. 
https://doi.org/10.1037/hea0000268.
    \586\ Office of the Assistant Secretary for Planning and 
Evaluation (ASPE). (2020). Report to Congress: Social Risk Factors 
and Performance Under Medicare's Value-Based Purchasing Program 
(Second of Two Reports). Available at: https://aspe.hhs.gov/pdf-report/second-impact-report-to-congress.
    \587\ The Physicians Foundation. (2020) 2020 Survey of America's 
Patients, Part Three. Available at: https://physiciansfoundation.org/wp-content/uploads/2020/10/2020-Physicians-Foundation-Survey-Part3.pdf.
    \588\ Alley, D.E., C.N. Asomugha, P.H. Conway, and D.M. 
Sanghavi. 2016. Accountable Health Communities-Addressing Social 
Needs through Medicare and Medicaid. The New England Journal of 
Medicine 374(1):8-11. Available at: https://doi.org/10.1056/NEJMp1512532.
    \589\ Centers for Medicare & Medicaid Services. (2021). 
Accountable Health Communities Model. Accountable Health Communities 
Model [verbar] CMS Innovation Center. Available at: https://innovation.cms.gov/innovation-models/ahcm. Accessed November 23, 
2021.
    \590\ Billioux, A., Verlander, K., Anthony, S., & Alley, D. 
(2017). Standardized Screening for Health-Related Social Needs in 
Clinical Settings: The Accountable Health Communities Screening 
Tool. NAM Perspectives, 7(5). Available at: https://doi.org/10.31478/201705b.
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    While the Screening for Social Drivers of Health process measure 
(discussed previously in section IX.E.5.b.(1).) enables identification 
of individuals with HRSNs, use of the Screen Positive Rate for Social 
Drivers of Health structural measure will allow us to estimate the 
impact of individual-level HRSNs on healthcare utilization, including 
hospitalizations, when evaluating quality of 
care.591 592 593 The Screen Positive Rate for Social Drivers 
of Health structural measure will require the reporting of the 
resulting screen positive rates for each domain. Reporting the social 
drivers of health screen positive rate for each domain will inform 
actionable planning by hospitals towards closing health equity gaps and 
enable the development of individual patient action plans (including 
navigation and referral). We believe this effort could yield actionable 
information to close the health equity gap in CMS programs and 
policies.
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    \591\ Baker, M.C., Alberti, P.M., Tsao, T.Y., Fluegge, K., 
Howland, R.E., & Haberman, M. (2021). Social Determinants Matter for 
Hospital Readmission Policy: Insights From New York City. Health 
Affairs, 40(4), 645-654. Available at: https://doi.org/10.1377/hlthaff.2020.01742.
    \592\ CMS. Accountable Health Communities Model. Accountable 
Health Communities Model [verbar] CMS Innovation Center. Available 
at: https://innovation.cms.gov/innovation-models/ahcm. Accessed 
November 23, 2021.
    \593\ Hammond, G., Johnston, K., Huang, K., Joynt Maddox, K. 
(2020). Social Determinants of Health Improve Predictive Accuracy of 
Clinical Risk Models for Cardiovascular Hospitalization, Annual 
Cost, and Death. Circulation: Cardiovascular Quality and Outcomes, 
13 (6) 290-299. Available at: https://doi.org/10.1161/CIRCOUTCOMES.120.006752.
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    In the FY 2022 IPPS/LTCH PPS final rule, we discussed ongoing 
consideration of potential approaches that could be implemented to 
address health equity through the Hospital IQR Program (85 FR 45414). 
As a result of the feedback we received, we identified the Screen 
Positive Rate for Social Drivers of Health measure to help inform 
efforts to address health equity. This structural measure assesses the 
percent of patients admitted to the hospital who are 18 years or older 
at time of admission who were screened for HRSNs and who screen 
positive for one or more of the core HRSNs, including food insecurity, 
housing instability, transportation needs, utility difficulties, or 
interpersonal safety (reported as five separate rates).\594\ We refer 
readers to section IX.E.5.b.(1).(a). of the preamble of this final rule 
where we previously discussed the CMS identification process resulting 
in the selection of these five domains.
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    \594\ Billioux, A., Verlander, K., Anthony, S., & Alley, D. 
(2017). Standardized Screening for Health-Related Social Needs in 
Clinical Settings: The Accountable Health Communities Screening 
Tool. NAM Perspectives, 7(5). Available at: https://doi.org/10.31478/201705b.
---------------------------------------------------------------------------

    The COVID-19 pandemic underscored the overwhelming impact that 
these five core domains have on disparities, health risk, healthcare 
access, and health outcomes, including premature 
mortality.595 596 Adoption of the Screen Positive Rate for 
Social Drivers of Health structural measure will encourage hospitals to 
track prevalence of specific HRSNs among patients over time and use the 
data to stratify risk as part of quality performance improvement 
efforts. This measure may also prove helpful for patients by providing 
data transparency and signifying hospitals' familiarity, expertise, and 
commitment regarding these issues. Evaluation of AHC Model 
participation demonstrated positive feedback and enhanced trust among 
patients.\597\ This measure also has the potential to reduce healthcare 
provider burnout by systematically acknowledging patients' social needs 
that contribute to adverse health outcomes and linking providers with 
community-based organizations to enhance patient-centered treatment and 
discharge planning.598 599 600 Finally, we

[[Page 49216]]

believe there is a potential further value of this measure to 
facilitate data-informed collaboration with community-based services 
and targeted community investments, and enable quality improvement 
activities and efforts to address disparities, including the 
development of pathways and infrastructure to connect patients to 
community resources.
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    \595\ Kaiser Family Foundation. (2021). Racial and Ethnic Health 
Inequities and Medicare. Available at: https://www.kff.org/medicare/report/racial-and-ethnic-health-inequities-and-medicare/. Accessed 
November 23, 2021.
    \596\ Centers for Disease Control and Prevention. (2019). CDC 
COVID-19 Response Health Equity Strategy: Accelerating Progress 
Towards Reducing COVID-19 Disparities and Achieving Health Equity. 
July 2020. Available at: https://www.cdc.gov/coronavirus/2019-ncov/community/health-equity/cdc-strategy.html. Accessed November 17, 
2021.
    \597\ RTI International. (2020). Accountable Health Communities 
(AHC) Model Evaluation. Available at: https://innovation.cms.gov/data-and-reports/2020/ahc-first-eval-rpt.
    \598\ The Physicians Foundation. (2020). Survey of America's 
Patients, Part Three. Available at: https://physiciansfoundation.org/wp-content/uploads/2020/10/2020-Physicians-Foundation-Survey-Part3.pdf.
    \599\ De Marchis, E., Knox, M., Hessler, D., Willard-Grace, R., 
Oliyawola, JN, et al. (2019). Physician Burnout and Higher Clinic 
Capacity to Address Patients' Social Needs. The Journal of the 
American Board of Family Medicine, 32 (1), 69-78.
    \600\ Kung, A., Cheung, T., Knox, M., Willard-Grace, R., 
Halpern, J., et.al, (2019). Capacity to Address Social Needs Affect 
Primary Care Clinician Burnout. Annals of Family Medicine. 17 (6), 
487-494. Available at: https://doi.org/10.1370/afm.2470.
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    Underserved communities are disproportionately impacted by HRSNs, 
such as food insecurity, that impact health outcomes and 
cost.601 602 Unmet HRSNs have been directly associated with 
healthcare utilization, including hospitalization, especially for 
hospitals that serve such communities.\603\ In pursuit of eliminating 
health equity gaps, we are focused on supporting effective and 
sustainable collaboration between healthcare delivery and community-
based services organizations to meet the unmet needs of historically 
underserved populations. Reporting data from both the Screening for 
Social Drivers of Health measure and the proportion of admitted 
patients who screen positive for HRSNs across the five domains (via 
this complementary measure) will enable quantification of the levels of 
HRSNs in local communities served by a hospital and greater visibility 
into the interaction between HRSNs and health status, healthcare 
utilization, and quality of care. These measures harmonize, as it is 
important to know both if a hospital or health system is using a 
screening tool and the results from the screening. Ultimately, we 
believe that, together, these two social drivers of health measures 
could enhance collaboration to meet the needs of historically 
underserved populations by identifying high-risk individuals who will 
benefit from engagement with community-based service providers. As with 
the theory of change for the AHC Model, we would expect such 
collaboration, and associated increase in capacity and community 
investments, to yield a net reduction in costly healthcare utilization, 
such as ED visits and avoidable hospitalizations and promote more 
appropriate healthcare service consumption.\604\
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    \601\ RTI International. (2020). Accountable Health Communities 
(AHC) Model Evaluation. Available at: https://innovation.cms.gov/data-and-reports/2020/ahc-first-eval-rpt.
    \602\ U.S. Department of Agriculture Economic Research Service 
(2021). Food Security in the U.S. Accessed January 18, 2022. 
Available at: https://www.ers.usda.gov/topics/food-nutrition-assistance/food-security-in-the-us/key-statistics-graphics.aspx. 
Accessed January 18, 2022.
    \603\ Office of the Assistant Secretary for Planning and 
Evaluation (ASPE) (2020). Report to Congress: Social Risk Factors 
and Performance Under Medicare's Value-Based Purchasing Program 
(Second of Two Reports). Available at: https://aspe.hhs.gov/pdf-report/second-impact-report-to-congress.
    \604\ Centers for Medicare & Medicaid Services. (2021). 
Accountable Health Communities Model. Accountable Health Communities 
Model [verbar] CMS Innovation Center. Available at: https://innovation.cms.gov/innovation-models/ahcm. Accessed November 23, 
2021.
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    Pursuant to Meaningful Measures 2.0, this measure addresses the 
``healthcare equity'' priority area and aligns with our commitment to 
introduce plans to close health equity gaps and promote equity through 
quality measures, including to ``develop and implement measures that 
reflect social and economic determinants.'' \605\ Under CMS' Meaningful 
Measures Framework, the Screen Positive Rate for Social Drivers of 
Health structural measure addresses the quality priority of ``Work with 
Communities to Promote Best Practices of Healthy Living'' through the 
Meaningful Measures Area of ``Equity of Care.'' \606\ Development of 
this measure also aligns with our strategic pillar to advance health 
equity by addressing the health disparities that underlie our health 
system.\607\
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    \605\ Centers for Medicare & Medicaid Services. Meaningful 
Measures 2.0: Moving from Measure Reduction to Modernization. 
Available at: https://www.cms.gov/meaningful-measures-20-moving-measure-reduction-modernization. We note that Meaningful Measures 
2.0 is still under development.
    \606\ Centers for Medicare & Medicaid Services. (2021). CMS 
Measures Management System Blueprint (Blueprint v 17.0). Available 
at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/MMS/MMS-Blueprint.
    \607\ Brooks-LaSure, C. (2021). My First 100 Days and Where We 
Go From Here: A Strategic Vision for CMS. Available at: https://www.cms.gov/blog/my-first-100-days-and-where-we-go-here-strategic-vision-cms.
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(b) Overview of Measure
    The Screen Positive Rate for Social Drivers of Health structural 
measure is intended to enhance standardized data collection that can 
identify high-risk individuals who will benefit from connection via the 
hospital to targeted community-based services.\608\ The measure will 
identify the proportion of patients who screened positive on the date 
of hospital admission for one or more of the following five HRSNs: Food 
insecurity, housing instability, transportation needs, utility 
difficulties, and interpersonal safety. Hospitals will report this 
measure as five separate rates. We note that this measure is intended 
to provide information to hospitals on the level of unmet social needs 
among patients served, and not for comparison between hospitals.
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    \608\ Centers for Medicare & Medicaid Services. (2021). A Guide 
to Using the Accountable Health Communities Health-Related Social 
Needs Screening Tool: Promising Practices and Key Insights (June 
2021). Available at: https://innovation.cms.gov/media/document/ahcm-screeningtool-companion. Accessed November 23, 2021.
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    The Screen Positive Rate for Social Drivers of Health (MUC21-134) 
measure was included in the publicly available ``List of Measures Under 
Consideration for December 1, 2021'' (MUC List), a list of measures 
under consideration for use in various Medicare and Medicaid 
programs.\609\ The MAP Rural Health Advisory Group and the Health 
Equity Advisory Group reviewed the measure on December 8, 2021, and 
December 9, 2021, respectively. Both groups expressed concerns about 
standardization of the measure and operationalization approaches that 
will yield real solutions for patients and clinicians. We intend to 
prioritize consideration of potential standardization approaches in 
future rulemaking. The MAP Health Equity Advisory Group members 
emphasized the importance of explaining to patients that self-report of 
HRSNs will not be used to stigmatize them or reduce healthcare 
benefits. We recommend that hospitals incorporate inclusive language in 
their screening activities to address this potential concern among 
patient and caregiver respondents. The measure developer stated that 
the focus of this measure is to establish standard social drivers of 
health screening measures, referencing data from the AHC Model as 
having demonstrated the feasibility of implementing HRSN screening and 
how essential the screening results are to enable action. Stakeholders' 
support for the measure was attributed, in part, to potential for 
hospitals, health systems, and community-based organizations to use the 
data to identify and prioritize opportunities for investment in 
community resources to address these HRSNs. Likewise, discussants 
reported that screening for HRSNs has allowed payors to enhance their 
understanding of the scope of such challenges among their patients, 
target resource investments, initiate changes in benefits designs, and 
prioritize community partnerships. We expect that hospitals will report 
similar findings and use the data to enhance resource allocation that 
will support referrals to relevant

[[Page 49217]]

community-based services organizations.
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    \609\ Centers for Medicare & Medicaid Services. (2021). List of 
Measures Under Consideration for December 1, 2021. Available at: 
https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96464.
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    On December 15, 2021, the MAP Hospital Workgroup met and reviewed 
the MUC List, including the Screen Positive Rate for Social Drivers of 
Health (MUC21-134) measure. Similar concerns and support as raised 
during the MAP Health Equity Advisory Group and MAP Rural Health 
Workgroup were also discussed during the MAP Hospital Workgroup 
meeting. The MAP Hospital Workgroup voted to conditionally support the 
measure for rulemaking pending NQF endorsement. On January 19, 2022, 
the MAP Coordinating Committee met and reviewed the MUC List including 
the Screen Positive Rate for Social Drivers of Health (MUC21-134) 
measure. The Coordinating Committee upheld the vote of the MAP Hospital 
Workgroup.\610\
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    \610\ National Quality Forum. (2022). Measure Applications 
Partnership (MAP) 2021-2022 Final Recommendations. Available at: 
https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96698.
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    We intend to submit this measure in future for NQF endorsement. We 
note that under section 1866 (b)(3)(B)(viii)(IX)(aa) of the Act, each 
measure specified by the Secretary shall be endorsed by the entity with 
a contract under section 1890(a) of the Act (the NQF is the entity that 
currently holds this contract). Under section 
1886(b)(3)(B)(viii)(IX)(bb) of the Act, in the case of a specified area 
or medical topic determined appropriate by the Secretary for which a 
feasible and practical measure has not been endorsed by the entity with 
a contract under section 1890(a) of the Act, the Secretary may specify 
a measure that is not so endorsed as long as due consideration is given 
to measures that have been endorsed or adopted by a consensus 
organization identified by the Secretary. We reviewed NQF-endorsed 
measures and were unable to identify any other NQF-endorsed measures on 
this topic, and, therefore we believe the exception in section 
1886(b)(3)(B)(viii)(IX)(bb) of the Act applies.
    This measure (alongside the Screening for Social Drivers of Health) 
will be the first patient-level measurement of social drivers of 
health. We believe this is an important measure to include because of 
the connection between HRSNs and patient health. When patients are 
admitted to hospital for inpatient care, there is substantial 
opportunity to screen for HRSNs and include relevant community services 
referrals as part of discharge planning. Providers will be able to 
identify if patients have unmet health-related social needs and the 
rate will help gauge what percentage of the population they serve (who 
are screened) indicate they need help, by HRSN domain. We envision that 
hospitals could implement and assess their quality improvement efforts 
to address patients' unmet social needs such as by connecting admitted 
patients identified with unmet social needs to local community 
resources. These efforts could include referring patients to services 
available through the hospital or the community. The information from 
this structural measure may serve as a baseline in the future to assess 
the proportion of admitted patients whose unmet social needs were 
addressed by the hospital during the hospital stay to support safe 
discharge and improved health outcomes.
    Measure specifications for this measure are available on the 
QualityNet website at: https://qualitynet.cms.gov (or other successor 
CMS designated websites).
(c) Cohort
    The Screen Positive Rate for Social Drivers of Health is a 
structural measure that provides information on the percent of patients 
admitted for an inpatient hospital stay and who are 18 years or older 
on the date of admission, were screened for an HRSN, and who screen 
positive for one or more of the following five HRSNs: Food insecurity, 
housing instability, transportation needs, utility difficulties, or 
interpersonal safety.
(d) Numerator
    The numerator consists of the number of patients admitted for an 
inpatient hospital stay who are 18 years or older on the date of 
admission, who were screened for an HRSN, and who screen positive for 
having a need in one or more of the following five HRSNs (calculated 
separately): Food insecurity, housing instability, transportation 
needs, utility difficulties or interpersonal safety.
(e) Denominator
    The denominator consists of the number of patients admitted for an 
inpatient hospital stay who are 18 years or older on the date of 
admission and are screened for an HRSN (food insecurity, housing 
instability, transportation needs, utility difficulties and 
interpersonal safety) during their hospital inpatient stay. The 
following patients will be excluded from the denominator: (1) Patients 
who opt-out of screening; and (2) patients who are themselves unable to 
complete the screening during their inpatient stay and have no 
caregiver able to do so on the patient's behalf during their inpatient 
stay.
(f) Measure Calculation
    The result of this measure will be calculated as five separate 
rates. Each rate is derived from the number of patients admitted for an 
inpatient hospital stay and who are 18 years or older on the date of 
admission, screened for an HRSN, and who screen positive for each of 
the five HRSNs--food insecurity, housing instability, transportation 
needs, utility difficulties, or interpersonal safety--divided by the 
total number of patients 18 years or older on the date of admission 
screened for all five HRSNs.
(g) Data Submission and Reporting
    We are finalizing voluntary reporting of the Screen Positive Rate 
for Social Drivers of Health measure beginning with the CY 2023 
reporting period, followed by mandatory reporting on an annual basis, 
beginning with the CY 2024 reporting period/FY 2026 payment 
determination and for subsequent years.
    Hospitals are required to submit information for structural 
measures once annually using a CMS-approved web-based data collection 
tool available within the HQR System. We refer readers to section 
IX.E.10. (Form, Manner, and Timing of Quality Data Submission) of the 
preamble of this final rule for more details on our previously 
finalized data submission and deadline requirements across measure 
types, and specifically, section IX.E.10.i. for our data and submission 
requirements for structural measures.
    We invited public comment on this proposal.
    Comment: Many commenters supported the proposal to adopt the Screen 
Positive Rate for Social Drivers of Health measure beginning with 
voluntary reporting for the CY 2023 reporting period and mandatory 
reporting beginning with the CY 2024 reporting period/FY 2026 payment 
determination and for subsequent years. Those commenters agreed with 
our described rationale for the proposal. Commenters believed the 
Screen Positive Rate for Social Drivers of Health measure would advance 
CMS' strategic pillar to advance health equity by providing data about 
the impact of drivers of health on patients' health outcomes, health 
disparities, physician quality performance, and health care costs. 
Several commenters applauded the proposal of the first drivers of 
health measures in hospital quality performance measurement. A 
commenter referenced recent studies that have quantified the 
significant

[[Page 49218]]

impact of drivers of health on physician performance and Medicare 
spending. A commenter referenced recent research reports of 
approximately 80 percent of health outcomes being directly associated 
with drivers of health and many physicians reporting that such factors 
influence patients' health and health outcomes. Several commenters 
stated the measure would improve healthcare transparency, promote data-
driven community resource investments, and inform and strengthen 
quality improvement efforts addressing health equity.
    Response: We thank commenters for their support of the measure and 
agree that it, in combination with the Screening for Social Drivers of 
Health measure, will be a first step towards addressing drivers of 
health to improve health equity, which is one of our strategic pillars.
    Comment: Many commenters supported the measure because it would 
provide data needed to identify factors that perpetuate health 
disparities. A commenter stated the measure would provide data on key 
contributors to poor physical and mental health outcomes. A few 
commenters noted the measure would provide additional data on the 
specific drivers of health challenges faced by patients in complement 
to the Screening for Social Drivers of Health measure. A few commenters 
believed the measure would highlight variability in drivers of health 
prevalence across hospitals, thereby reflecting the challenges faced by 
hospitals that disproportionately serve patients with higher HRSN 
burden. Several commenters believed the measure would allow CMS to 
account for HRSNs in risk adjustment for quality performance scoring 
and support targeted quality improvement activities. A few commenters 
noted the measure would promote data transparency and build credibility 
for hospitals engaging in social drivers of health screening and 
intervention activities. A few commenters emphasized the measure would 
be person- or patient-level which will support enhanced evaluation of 
the economic implications of HRSNs on healthcare billing, risk 
adjustment, and cost benchmarks. A commenter noted the measure would be 
especially important for practicing physicians and their patients 
because it would accelerate quality improvement activities that address 
health disparities. A few commenters believed the measure would enable 
public and private institutions to make strategic investments that will 
strengthen capacity-building for addressing patients' HRSNs.
    Response: We thank commenters for their support of the measure and 
the multiple ways in which the data could potentially be used to inform 
evidence-based decision making. We believe this measure is the next 
logical step after screening for HRSNs. We agree with commenters that 
data from the measure will contribute to efforts to close the health 
equity gap. Specifically, for the Hospital IQR Program, we recognize 
that drivers of health contribute significantly to unplanned hospital 
re-admissions and other patient outcomes in the hospital inpatient 
setting which impacts hospitals and healthcare providers that serve 
patients who are disproportionately burdened with unmet HRSNs. We 
intend for the two measures to encourage hospitals' accountability for 
addressing health disparities and, specifically, that the Screen 
Positive Rate for Social Drivers of Health will enable identification 
of specific unmet needs among patients.
    Comment: Several commenters did not support adoption of the Screen 
Positive Rate for Social Drivers of Health measure. A commenter did not 
support adoption of the Screen Positive Rate for Social Drivers of 
Health measure because they believed the measure would be inappropriate 
for CMS quality measurement.
    Response: We thank the commenters for their input, but respectfully 
disagree. The intent of both measures is to promote adoption of HRSN 
screening by hospitals as part of a larger long-term strategy to 
improve patient outcomes and eliminate health equity gaps in the 
hospital inpatient setting. We refer readers to the Overview section in 
the proposed rule (87 FR 28505) where we state that the measure is 
intended to provide information to hospitals on the level of unmet 
social needs among patients served. We also refer the reader to our 
definition of quality measures as noted in our Measure Management 
System.\611\ We believe the Screen Positive Rate for Social Drivers of 
Health measure will function as tools to help us measure and quantify 
healthcare processes and patient outcomes in the hospital inpatient 
setting.
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    \611\ https://mmshub.cms.gov/about-quality/new-to-measures/what-is-a-measure.
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    Comment: A few commenters stated the measure lacks comparability 
across hospitals.
    Response: We thank the commenters for their input. We refer readers 
to the Overview section in the proposed rule where we state that the 
measure is intended to provide information to hospitals on the level of 
unmet social needs among patients served, and not for comparison 
between hospitals (87 FR 28505).
    Comment: A few commenters believed the measure would be difficult 
to interpret. Specifically, a commenter believed the Screen Positive 
Rate for Social Drivers of Health measure interpretation would be 
extremely difficult because the denominator will not be specific to the 
numerator's drivers of health domains. A few commenters expressed 
concern about potential confusion among patients and unclear 
interpretation that could lead to data misuse.
    Response: We thank the commenters for their input. We appreciate 
the concerns noted and we will take them into consideration for our 
future outreach efforts aimed at enhancing understanding of the 
measures and how the data will be used. We do not agree with the 
commenters that the measure may lack specificity or clarity or create 
confusion. We refer readers to the explanation of the measure 
specifications and specifically, the Measure Calculation section (IX. 
E.5.b.(2).(f).), in which we discuss the relationship between the 
numerator and denominator.
    Comment: A few commenters stated the measure does not capture 
response to screening or whether intervention occurred and was 
effective.
    Response: We thank the commenters for their input. We stated in the 
proposed rule that utilization of screening tools to identify the 
burden of unmet HRSNs can be a helpful first step in identifying 
necessary community partners connecting individuals to resources in 
their communities (87 FR 28500). The measure does not currently include 
measurement of intervention efficacy, and we will consider this in 
future rulemaking.
    Comment: A commenter questioned the value of public reporting of 
the Screen Positive Rate for Social Drivers of Health measure data.
    Response: We thank the commenter for their input. Collecting 
healthcare quality data related to social drivers can promote 
transparency in delivery of care by increasing involvement of 
leadership in healthcare quality improvement, increasing a sense of 
accountability, helping to focus organizational priorities and 
providing a means of delivering important healthcare information to 
patients. We believe this will be especially important as we advance 
the aims of our strategic pillar to improve health equity in general 
and address the disproportionate impact that drivers of health have on 
hospital quality performance for organizations

[[Page 49219]]

that serve patient populations with high HRSN levels.
    Comment: Several commenters stated the proposed timeline for 
voluntary and mandatory reporting is inadequate. A commenter stated the 
work required to make the measures meaningful and establish effective 
workflows would take many years to develop.
    Response: We thank the commenters for their feedback. We appreciate 
the concerns about the operational complexity of introducing drivers of 
health quality measures into existing clinical workflows. While the 
implementation of these two Social Drivers of Health measures may be a 
major undertaking for some providers, especially given the ongoing 
COVID-19 PHE, we also recognize that the COVID-19 PHE magnified the 
disproportionate burden of drivers of health on communities who have 
been historically under-resourced.\612\ We have therefore determined 
that the proposed voluntary and mandatory reporting periods balance the 
time needed to implement these measures with the urgency of capturing 
drivers of health data and taking actionable steps towards closing the 
health equity gap. As stated in the proposed rule, potential sources of 
these data could include, for example, administrative claims data, 
electronic clinical data, standardized patient assessments, or patient-
reported data and surveys (87 FR 28503). Additionally, we note that 92 
percent of hospitals already screen for one or more of the five HRSNs--
food insecurity, housing instability, transportation needs, utility 
difficulties, and interpersonal safety--specified in the proposed 
measures (87 FR 28498). We believe that this is a strong indication 
that hospitals have processes in place to conduct the screening 
required.
---------------------------------------------------------------------------

    \612\ Centers for Disease Control and Prevention. (2020). CDC 
COVID-19 Response Health Equity Strategy: Accelerating Progress 
Towards Reducing COVID-19 Disparities and Achieving Health Equity. 
July 2020. Available at: https://www.cdc.gov/coronavirus/2019-ncov/community/health-equity/cdc-strategy.html. Accessed November 17, 
2021.
---------------------------------------------------------------------------

    Comment: A commenter identified inadequate measure design and lack 
of measure specification and testing to support adoption as challenges 
to implementation of the proposed measures; the commenter recommended 
an attestation-based data collection approach.
    Response: We thank the commenters for their input. We respectfully 
disagree with the commenter that the measures lack specification and 
testing. We appreciate the concerns noted and we refer readers to the 
Overview of Measure section in the proposed rule (and section 
E.5.b.(2).(b). of this final rule) where we provide the measure 
specifications (87 FR 28506). Specifically, we explain the numerator, 
denominator, and measure calculation for both measures. Moreover, 
evidence from the AHC Model evaluation supports adoption of the measure 
as proposed because it demonstrated the ability of drivers of health 
screening to identify higher cost and utilization patients in the 
hospital inpatient setting. The measures were reviewed by the MAP 
Hospital Workgroup, MAP Health Equity Workgroup, and the MAP Rural 
Health Workgroup and all supported inclusion of the measures in the 
Hospital IQR Program. We expect this will advance efforts for hospitals 
to reduce unplanned readmission rates.
    Comment: A commenter was concerned about the appropriateness of 
including the measure in the Hospital IQR Program. The commenter 
believed the measure is a hospital ``case-mix'' measure instead of a 
structural measure. The commenter believed the measure does not reflect 
hospital quality performance because hospitals are not resourced to 
address the problems identified in HRSN screening.
    Response: We thank the commenter for this input. We define a 
structural quality measure, also known as a structure measure, in the 
CMS Measurement Management System Blueprint as a measure that 
``assesses features of a healthcare organization or clinician relevant 
to its capacity to provide healthcare.'' \613\ This is particularly 
relevant in the hospital patient setting where patients with high 
levels of HRSNs tend to have higher utilization and costs related to 
care delivery. While case mix reflects the diversity, complexity, and 
severity of patient illnesses treated at a given hospital, patients' 
HRSNs and the levels of unmet need among screened patients have not 
previously been measured or publicly reported on a national scale. 
Moreover, while HRSNs contribute to case mix components such as illness 
severity and complexity, our initial aim with these measures centers on 
using drivers of health screening to understand the precursors of 
patient illnesses and disparities in health outcomes over time. We aim 
to encourage hospitals to address patient-level HRSNs in care delivery 
because patient characteristics greatly influence healthcare 
organizations' and healthcare professionals' capacity to deliver 
healthcare. We emphasize that screening for and reporting of HRSN 
prevalence among patients are intended to be initial steps towards more 
robust accounting of the impact of HRSNs on patient health and related 
outcomes during and following hospitalization. Hospitals will not be 
expected to address the problems identified by screening but instead 
will be expected to facilitate linkage to community resources that can 
assist patients in meaningful ways.
---------------------------------------------------------------------------

    \613\ Centers for Medicare & Medicaid Services. Measure 
Management System (MMS): Glossary. Available at: https://mmshub.cms.gov/glossary. Accessed July 22, 2022.
---------------------------------------------------------------------------

    Comment: A few commenters recommended against publicly reporting 
the data for this measure. A few commenters specifically recommended 
against reporting data on the Compare tool due to risk of 
misinterpretation by consumers. A few commenters were concerned that 
public reporting of the data might suggest that hospitals serving 
communities with high HRSNs are under-performing. A commenter believed 
that public reporting the data would discourage hospitals from 
screening patients with higher risk. A commenter recommended we ensure 
the measures are implemented consistently to allow fair comparisons 
across providers and regions due to differences in capacity for 
screening and making follow-on services available. Several commenters 
recommended we provide outreach and education to patients and providers 
to address the meaning, reasons, and interpretation of the measures. A 
commenter recommended developing guidance on effective education on the 
measures for patients and providers. A commenter recommended we 
evaluate the ability of consumers to interpret the measure rate(s) 
accurately.
    Response: We appreciate the commenters' concerns. We wish to remind 
readers that the measure is intended to provide information to 
hospitals on the level of unmet need among their patients, and not for 
comparison between hospitals (87 FR 28505). We intend to conduct 
outreach and education in conjunction with public reporting of the data 
for the two Social Drivers of Health measures. We believe public 
reporting of healthcare quality data promotes transparency in the 
delivery of care by increasing the involvement of leadership in 
healthcare quality improvement, creating a sense of accountability, 
helping to focus organizational priorities, and providing a means of 
delivering important healthcare information to consumers.\614\

[[Page 49220]]

We intend to conduct outreach and education with providers and patients 
to share information about the two Social Drivers of Health measures in 
conjunction with public reporting.
---------------------------------------------------------------------------

    \614\ Centers for Medicare & Medicaid Services Quality Net. 
Public Reporting Overview. Available at: https://qualitynet.cms.gov/inpatient/public-reporting/public-reporting.
---------------------------------------------------------------------------

    Comment: A commenter believed the name of the measure is misleading 
and recommending changing the name because patients may misinterpret 
``screening positive'' as a positive event.
    Response: We thank the commenter for their input about potential 
misinterpretation of the measure name. While we are not changing the 
measure name at this time, we appreciate this feedback and will 
consider it in outreach and education in conjunction with public 
reporting of the data and potential future development of this and 
other related measures.
    Comment: A commenter recommended considering a minimum level of 
cross-cultural validation of the measures and/or demonstration of how 
community members and patients participated in domain prioritization.
    Response: We appreciate the commenters recommendations. We will 
consider this input as part of future measure maintenance analyses as 
well as future policy development.
    Comment: A commenter recommended modifying the measure so that in 
addition to capturing the five separate rates, one for each of the HRSN 
domains, the measure would ``drill down'' into sub-components to 
include three options for each: Screen positive, screen negative, and 
did not screen. A commenter recommended reconsideration of the measure 
specifications to reduce risk of small denominator sizes that would 
impede calculation and/or interpretation.
    Response: We thank the commenter for their input. We will consider 
this input as part of future measure maintenance analyses as well as 
policy development.
    Comment: A commenter recommended consolidating the two Screening 
for Social Drivers measures into a single measure and adding a 
component that would capture screening follow-up. The commenter 
believed that one single measure then could be stratified by whether an 
individual screened positive or negative.
    Response: We thank the commenter for their input. We will consider 
this input as part of future measure maintenance analyses as well as 
policy development.
    After consideration of the public comments we received, we are 
finalizing our proposal as proposed.
c. Cesarean Birth eCQM Beginning With the CY 2023 Reporting Period/FY 
2025 Payment Determination With Mandatory Reporting Beginning With the 
CY 2024 Reporting Period/FY 2026 Payment Determination and for 
Subsequent Years
    In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28506 through 
28510), we proposed to adopt the Cesarean Birth eCQM as one of the 
eCQMs in the Hospital IQR Program measure set that hospitals can self-
select to report for the CY 2023 reporting period/FY 2025 payment 
determination. We also proposed to make reporting of this eCQM 
mandatory beginning with the CY 2024 reporting period/FY 2026 payment 
determination and for subsequent years.
(1) Background
    A Cesarean section (C-section) is the use of surgery to deliver a 
baby (or babies) in lieu of vaginal delivery. The procedure entails 
surgical and anesthesia risks and requires mothers to undergo several 
days of inpatient, post-operative recovery. A C-section may occur on an 
elective or nonelective basis.\615\ Elective C-sections may be planned 
due to the presence of a complicating medical condition, abnormal 
positioning of the baby, or other medical indications.\616\ Elective C-
sections may also occur for non-medical reasons, including maternal 
preference (in consultation with their healthcare provider), local 
practice patterns, malpractice risk, or other 
factors.617 618 619 C-sections that occur upon a mother's 
request are rare, but occur after consultation with a clinician.\620\
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    \615\ National Quality Forum. Quality Measure PC- 02 (Cesarean 
Birth). Available at: https://www.qualityforum.org/QPS/0471.
    \616\ Xu, X., Yan, J.Y., Chen, L.C. (2021). Risk factors and 
maternal-fetal outcomes of pregnancies complicated by pre-eclampsia, 
following cesarean section after a trial vaginal birth. Chin Med J 
(Engl). 2021;134(18):2249-2251. doi:10.1097/CM9.0000000000001452.
    \617\ Caughey AB, Cahill AG, Guise JM, Rouse DJ. (2014). Safe 
prevention of the primary cesarean delivery. Am J Obstet Gynecol. 
2014 Mar;210(3):179-93. doi: 10.1016/j.ajog.2014.01.026.
    \618\ Schifrin BS, Cohen WR. (2013). The effect of malpractice 
claims on the use of caesarean section. Best Pract Res Clin Obstet 
Gynaecol. 2013 Apr;27(2):269-83. doi: 10.1016/j.bpobgyn.2012.10.004. 
Epub 2012 Dec 1. Review.
    \619\ Chen CS, Liu TC, Chen B, Lin CL. (2014). The failure of 
financial incentive? The seemingly inexorable rise of cesarean 
section. Soc Sci Med. 2014 Jan;101:47-51. doi: 10.1016/
j.socscimed.2013.11.010. Epub 2013 Nov 15.
    \620\ Committee on Obstetric Practice. (2019) Cesarean Delivery 
on Maternal Request. The American College of Obstetricians and 
Gynecologists, 133(1). Available at: https://www.acog.org/clinical/clinical-guidance/committee-opinion/articles/2019/01/cesarean-delivery-on-maternal-request.
---------------------------------------------------------------------------

    The total rate of (elective and nonelective) C-sections has risen 
in the U.S. since the 1990s.\621\ C-sections accounted for 31.8 percent 
of U.S. live births in 2020,\622\ and there is a considerable amount of 
variation in the rates based on U.S. region, state, and healthcare 
institution.\623\ There is also substantial variability across races 
and ethnicities; the rate of C-sections is: 30.8 percent among Non-
Hispanic White women, 36.3 percent among Black women, 28.8 percent 
among American Indian or Alaska Native women, 32.6 among Asian women, 
and 31.4 percent among Hispanic women.\624\ U.S. practice guidelines 
have not indicated an optimal rate of C-section or an appropriate 
variance rate; while international studies suggest a preference for a 
lower range than current U.S. rates.625 626 627
---------------------------------------------------------------------------

    \621\ Osterman, M.J.K., Martin, J.A. (2014). Trends in Low-risk 
Cesarean Delivery in the United States, 1990-2013. National Vital 
Statistics Reports, 63(6): 1-16.
    \622\ Hamilton, B.E., Martin, J.A., Osterman, M.J.K. (2020). 
Births: Provisional Data for 2020. National Vital Statistics Rapid 
Release, no 12. DOI: https://doi.org/10.15620/cdc:104993.
    \623\ Kozhimannil, K.B., Law, M.R. & Virnig, B.A. (2013). 
Cesarean delivery rates vary tenfold among US hospitals; reducing 
variation may address quality and cost issues. Health Affairs, 
32(3): 527-35.
    \624\ Hamilton, B.E., Martin, J.A., Osterman, M.J.K. (2020). 
Births: Provisional Data for 2020. National Vital Statistics Rapid 
Release, no 12. DOI: https://doi.org/10.15620/cdc:104993.
    \625\ National Collaborating Centre for Women's and Children's 
Health. (2011). Caesarean Section: NICE Clinical Guideline 
(commissioned by the United Kingdom National Institute for Health 
and Clinical Excellence).
    \626\ Caughey AB, Cahill AG, Guise JM, Rouse DJ. (2014). Safe 
prevention of the primary cesarean delivery. Am J Obstet Gynecol, 
210(3): 179-93. doi: 10.1016/j.ajog.2014.01.026.
    \627\ Keag, O.E., Norman, J.E. & Stock, S.J. (2018). Long-term 
risks and benefits associated with cesarean delivery for mother, 
baby, and subsequent pregnancies: Systematic review and meta-
analysis. Plos Med, 15(1): e1002494.
---------------------------------------------------------------------------

    When medically indicated, a C-section can effectively prevent 
maternal and neonatal morbidity and mortality.\628\ However, clinicians 
and consensus groups agree that increased C-section rates have not 
improved overall perinatal outcomes and that C-sections are 
overused.629 630

[[Page 49221]]

Additionally, low risk C-sections--defined as deliveries by 
nulliparous, term, or singleton vertex (NTSV) women--have seen an 
increase. ``Nulliparous'' women are those who have never given birth to 
a live baby but may have had a miscarriage, stillbirth, or elective 
abortion. They have a lower risk of maternal morbidity and mortality 
during vaginal birth than do women who have undergone a previous C-
section.\631,632\ ``Term'' indicates a term birth (that is on or after 
37 weeks' gestation), which has better outcomes than a preterm birth, 
and ``singleton'' refers to the birth of a single child during one 
delivery. Vertex presentations, which are those where the child is 
positioned headfirst, carry less risk than breech or transverse 
presentations.\633\ The rate of low-risk C-section deliveries also 
varies by race and ethnicity; low-risk C-section births in 2020 were: 
24.9 percent among NTSV Non-Hispanic White women, 30.6 percent among 
NTSV Non-Hispanic Black women, 23.6 percent among NTSV American Indian 
or Alaska Native women, 27.7 percent among NTSV Asian women, and 25.2 
percent among NTSV Hispanic women.\634\ A majority of which are still 
higher than the Centers for Disease Control and Prevention's (CDC's) 
Healthy People 2020 goal to reduce C-section births among NTSV women to 
23.9 percent by 2020.\635\
---------------------------------------------------------------------------

    \628\ Caughey AB, Cahill AG, Guise JM, Rouse DJ. (2014). Safe 
prevention of the primary cesarean delivery. Am J Obstet Gynecol, 
210(3): 179-93. doi: 10.1016/j.ajog.2014.01.026.
    \629\ Caughey AB, Cahill AG, Guise JM, Rouse DJ. (2014). Safe 
prevention of the primary cesarean delivery. Am J Obstet Gynecol, 
210(3): 179-93. doi: 10.1016/j.ajog.2014.01.026.
    \630\ National Collaborating Centre for Women's and Children's 
Health. (2011). Caesarean Section: NICE Clinical Guideline 
(commissioned by the United Kingdom National Institute for Health 
and Clinical Excellence).
    \631\ Caughey AB, Cahill AG, Guise JM, Rouse DJ. (2014). Safe 
prevention of the primary cesarean delivery. Am J Obstet Gynecol, 
210(3): 179-93. doi: 10.1016/j.ajog.2014.01.026.
    \632\ National Quality Forum. (2016). Perinatal and Reproductive 
Health 2015-2016 Final Report. Available at: https://www.qualityforum.org/Publications/2016/12/Perinatal_and_Reproductive_Health_2015-2016_Final_Report.aspx.
    \633\ Caughey AB, Cahill AG, Guise JM, Rouse DJ. (2014). Safe 
prevention of the primary cesarean delivery. Am J Obstet Gynecol, 
210(3): 179-93. doi: 10.1016/j.ajog.2014.01.026.
    \634\ Hamilton, B.E., Martin, J.A., Osterman, M.J.K. (2020). 
Births: Provisional Data for 2020. National Vital Statistics Rapid 
Release, no 12. DOI: https://doi.org/10.15620/cdc:104993.
    \635\ Centers for Disease Control and Prevention, Maternal Child 
and Infant Health. Healthy People 2020. Available at: https://www.cdc.gov/nchs/data/hpdata2020/HP2020MCR-C26-MICH.pdf.
---------------------------------------------------------------------------

    C-sections have higher morbidity and mortality (9.2 percent) than 
vaginal deliveries (8.6 percent).\636\ Existing literature largely does 
not distinguish whether inferior outcomes derive from cause (higher-
risk patients undergo C-section) or effect (surgery carries inherent 
risks due to anesthesia, bleeding, infection, post-operative recovery, 
etc.).\637\ However, taking an aggregate view of multiple studies over 
time, it appears that C-sections carry a higher risk of subsequent 
miscarriage, placental abnormalities, and repeat C-section.\638\ The 
rates of transfusions, ruptured uteri, unplanned hysterectomies, and 
intensive care unit (ICU) admissions are higher among women who deliver 
via C-section for the first time than those who deliver vaginally for 
the first time across all races and ethnicities. However, non-Hispanic 
Black women who deliver via C-section for the first time had the 
highest rates of uterine rupture and ICU admission compared with all 
other races and ethnicities.\639\
---------------------------------------------------------------------------

    \636\ Caughey AB, Cahill AG, Guise JM, Rouse DJ. (2014). Safe 
prevention of the primary cesarean delivery. Am J Obstet Gynecol, 
210(3): 179-93. doi: 10.1016/j.ajog.2014.01.026.
    \637\ Keag, O.E., Norman, J.E. & Stock, S.J. (2018). Long-term 
risks and benefits associated with cesarean delivery for mother, 
baby, and subsequent pregnancies: Systematic review and meta-
analysis. Plos Med, 15(1): e1002494.
    \638\ Keag, O.E., Norman, J.E. & Stock, S.J. (2018). Long-term 
risks and benefits associated with cesarean delivery for mother, 
baby, and subsequent pregnancies: Systematic review and meta-
analysis. Plos Med, 15(1): e1002494.
    \639\ Curtin, S.C., Gregory, K.D., Korst, L.M., Uddin, S.F.G. 
(2015) Maternal Morbidity for Vaginal and Cesarean Deliveries, 
According to Previous Cesarean History: New Data from the Birth 
Certificate, 2013. National Vital Statistics Reports. Volume 64, 
Number 4. Available at: https://www.cdc.gov/nchs/data/nvsr/nvsr64/nvsr64_04.pdf.
---------------------------------------------------------------------------

    In terms of neonatal outcomes, C-sections have higher respiratory 
morbidity (1 percent to 4 percent) than vaginal births (<1 
percent).\640\ Again, it is unclear whether this is because of cause 
(high-risk fetuses are more likely to be delivered by C-section) or 
effect (surgery carries inherent risks due to anesthesia, bleeding, 
infection, post-operative recovery, etc.). The medical indications for 
a C-section entail broad provider discretion because of the need to: 
(1) Balance any conflicting medical conditions of mother versus fetus; 
and (2) balance the C-section against any other competing clinical 
considerations or external constraints (for example, availability of 
operation room, personnel, and/or blood). It should also be noted that 
reducing the rate of C-sections does not result in worse outcomes for 
the mother or newborn, with newborn complications even declining in 
some hospitals with significant C-section reductions.\641\
---------------------------------------------------------------------------

    \640\ Caughey AB, Cahill AG, Guise JM, Rouse DJ. (2014). Safe 
prevention of the primary cesarean delivery. Am J Obstet Gynecol, 
210(3): 179-93. doi: 10.1016/j.ajog.2014.01.026.
    \641\ Main, E.K., Chang, S.C., Cape, V., Sakowski, C. Smith, H., 
Vasher, J. (2019) Safety Assessment of a Large-Scale Improvement 
Collaborative to Reduce Nulliparous Cesarean Delivery Rates. 
Obstetrics & Gynecology, 133(4):613-623. doi: 10.1097/
AOG.0000000000003109.
---------------------------------------------------------------------------

    Furthermore, C-sections receive higher reimbursement than vaginal 
deliveries (typically about 50 percent more). The prevalence of non-
medically indicated C-sections carries economic impacts because C-
sections are more expensive than vaginal deliveries and may be 
accompanied by adverse outcomes and complications, which similarly have 
substantial cost implications.\642\
---------------------------------------------------------------------------

    \642\ Kozhimannil, K.B., Law, M.R. & Virnig, B.A. (2013). 
Cesarean delivery rates vary tenfold among US hospitals; reducing 
variation may address quality and cost issues. Health Affairs, 
32(3): 527- 35. doi: 10.1377/hlthaff.2012.1030.
---------------------------------------------------------------------------

    We believe this eCQM will help further our goal of addressing 
maternal health outcomes in the Hospital IQR Program. Currently, the 
Hospital IQR Program includes two measures that address improving 
maternal health: The Elective Delivery measure (PC-01) (77 FR 53530) 
and the Maternal Morbidity Structural measure (86 FR 45361 through 
45365). However, neither of these measures directly address the factors 
contributing to maternal mortality, such as the high rates of C-
sections in the U.S. We believe adopting measures like the Cesarean 
Birth eCQM presents unique opportunities for large-scale quality 
measurement and activities that can improve the short- and long-term 
health outcomes for mothers and children.\643\ We also refer readers to 
section IX.E.5.d. of the preamble of this final rule, where we also 
finalized the adoption of the Severe Obstetric Complications eCQM as 
part of the Hospital IQR Program measure set.
---------------------------------------------------------------------------

    \643\ Department of Health and Human Services. (2020). Healthy 
Women, Healthy Pregnancies, Health Futures: Action Plan to Improve 
Maternal Health in America. Available at: https://aspe.hhs.gov/sites/default/files/private/aspe-files/264076/healthy-women-healthy-pregnancies-healthy-future-action-plan_0.pdf.
---------------------------------------------------------------------------

    In response to increases in low-risk C-sections, HHS has included a 
goal of reducing low-risk C-sections by 25 percent in the next five 
years as part of the Maternal Action Plan.\644\ To build on the 
previously established HHS Maternal Health Action Plan, the Vice 
President's nationwide call to action to reduce maternal morbidity and 
mortality, and ongoing efforts with HHS and across the federal 
government,\645\

[[Page 49222]]

the Biden-Harris Administration seeks to use a whole-of-government 
approach for improving maternal health and advancing maternal health 
equity that reduces maternal mortality and morbidity, reduces 
persistent disparities, and among other activities, increases hospital 
participation in HHS-sponsored maternal health quality improvement 
initiatives. A critical focus is reducing existing disparities in 
maternal health outcomes across race, ethnicity, and geographic area. 
The Cesarean Birth eCQM is intended to facilitate safer patient care by 
assessing the rate of NTSV C-sections to ultimately reduce the 
occurrence of non-medically indicated C-sections, promoting adherence 
to recommended clinical guidelines, and encouraging hospitals to track 
and improve their practices of appropriate monitoring and maternity 
care delivery for pregnant and postpartum patients. The 2020 
performance measurement data for the Cesarean Birth eCQM indicates a 
27.5 percent average rate of C-section birth for NTSV women (across 15 
hospitals, N=933). A group of subject matter experts for NQF noted that 
decreasing the rate of non-medically indicated C-sections can result in 
increased patient safety, decreased maternal and neonatal morbidity, 
and substantial savings in healthcare costs.\646\ Additionally, 
considering that Non-Hispanic Black women have the highest rate of low-
risk C-sections along with the highest rates of uterine ruptures and 
ICU admissions as a result of C-sections, reducing low-risk C-section 
rates could improve maternal health outcomes for this population in 
particular by reducing the excess maternal morbidity they 
experience.647 648 649
---------------------------------------------------------------------------

    \644\ Department of Health and Human Services. HHS Initiative to 
Improve Maternal Health. Available at: https://aspe.hhs.gov/topics/public-health/hhs-initiative-improve-maternal-health.
    \645\ Department of Health and Human Services. HHS Initiative to 
Improve Maternal Health. Available at: https://aspe.hhs.gov/topics/public-health/hhs-initiative-improve-maternal-health.
    \646\ National Quality Forum. (2008) Perinatal and Reproductive 
Health Project NQF #0471 PC-02 Cesarean Section: Measure Submission 
and Evaluation Worksheet 5.0. Available at: https://www.qualityforum.org/Projects/n-r/Perinatal_Care_Endorsement_Maintenance_2011/0471.aspx.
    \647\ Department of Health and Human Services. (2020). Healthy 
Women, Healthy Pregnancies, Health Futures: Action Plan to Improve 
Maternal Health in America. Available at: https://aspe.hhs.gov/sites/default/files/private/aspe-files/264076/healthy-women-healthy-pregnancies-healthy-future-action-plan_0.pdf.
    \648\ Curtin, S.C., Gregory, K.D., Korst, L.M., Uddin, S.F.G. 
(2015) Maternal Morbidity for Vaginal and Cesarean Deliveries, 
According to Previous Cesarean History: New Data from the Birth 
Certificate, 2013. National Vital Statistics Reports. Volume 64, 
Number 4. https://www.cdc.gov/nchs/data/nvsr/nvsr64/nvsr64_04.pdf.
    \649\ Debbink, M.P. Ugwu, L.G. Grobman, W.A. et al. (2022) 
Racial and Ethnic Inequities in Cesarean Birth and Maternal 
Morbidity in a Low-Risk, Nulliparous Cohort. Obstetrics & 
Gynecology;139(1): 73-82. doi: 10.1097/AOG.0000000000004620.
---------------------------------------------------------------------------

    Under CMS' Meaningful Measures Framework,\650\ the Cesarean Birth 
eCQM addresses the quality priority of ``Make Care Safer by Reducing 
Harm Caused in the Delivery of Care'' through the Meaningful Measures 
Area of ``Preventable Healthcare Harm.'' \651\ Additionally, pursuant 
to Meaningful Measures 2.0,\652\ this measure addresses the ``Safety'' 
priority area and aligns with our commitment to a patient-centered 
approach in quality measurement to ensure that patients are safe and 
receive the highest quality care.\653\ Finally, this measure aligns 
with our strategic priorities including the pillar to advance health 
equity by addressing the health disparities that underlie our health 
system.\654\
---------------------------------------------------------------------------

    \650\ Centers for Medicare & Medicaid Services. Meaningful 
Measures Framework. Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/CMS-Quality-Strategy.
    \651\ CMS' Meaningful Measures Framework can be found at: 
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/MMF/General-info-Sub-Page.
    \652\ Centers for Medicare & Medicaid Services. Meaningful 
Measures 2.0: Moving from Measure Reduction to Modernization. 
Available at: https://www.cms.gov/meaningful-measures-20-moving-measure-reduction-modernization. We note that Meaningful Measures 
2.0 is still under development.
    \653\ Centers for Medicare & Medicaid Services. (2021) CMS 
Quality Measurement Action Plan. Available at: https://www.cms.gov/files/document/2021-cms-quality-conference-cms-quality-measurement-action-plan-march-2021.pdf.
    \654\ Brooks-LaSure, C. (2021). My First 100 Days and Where We 
Go From Here: A Strategic Vision for CMS. Centers for Medicare & 
Medicaid. Available at: https://www.cms.gov/blog/my-first-100-days-and-where-we-go-here-strategic-vision-cms.
---------------------------------------------------------------------------

    Therefore, in the proposed rule, we proposed the adoption of the 
Cesarean Birth eCQM beginning with the CY 2023 reporting period/FY 2025 
payment determination. As part of the currently finalized eCQM 
reporting and submission requirements, hospitals must report on three 
self-selected eCQMs and the Safe Use of Opioids--Concurrent Prescribing 
eCQM, for a total of four eCQMs (85 FR 58939). Hospitals may choose to 
report it as one of the three self-selected eCQMs for the CY 2023 
reporting period/FY 2025 payment determination. After which, beginning 
with the CY 2024 reporting period/FY 2026 payment determination and for 
subsequent years, the Cesarean Birth eCQM would be required to be 
reported by all hospitals, except those hospitals that do not have an 
obstetrics department and do not perform deliveries. We also refer 
readers to section IX.E.10.e. of the preamble of this final rule for 
our policy to modify the eCQM reporting and submission requirements 
beginning with the CY 2024 reporting period/FY 2026 payment 
determination.
(2) Overview of Measure
    This measure assesses the rate of NTSV pregnancies delivered via C-
section. Determining the NTSV C-section rate permits a hospital to 
compare its outcomes to other hospitals while focusing only on the NTSV 
population which can impact the rates of first time and possibly 
subsequent C-section rates. We note that the NQF has endorsed the 
chart-abstracted form of this measure (PC-02: Cesarean Birth, NQF 
#0471) as a voluntary consensus standard since 2008 and continuously 
renewed its endorsement (most recently in 2020).\655\ The Rural Health 
Workgroup of the NQF's MAP also identified the chart-abstracted version 
as a measure that holds particular relevance for rural hospitals, 
noting how important it is to focus on best practices in obstetric care 
in rural areas.\656\ We acknowledge that there are instances where C-
sections are medically indicated, and we emphasize that this measure is 
not intended to discourage practitioners from performing C-sections 
when they are medically indicated. We believe that assessing the rate 
of NTSV C-sections may ultimately reduce the occurrence of non-
medically indicated C-sections. We encourage hospitals whose measure 
rates are higher than rates at other hospitals to explore and evaluate 
differences in the clinical management of women in labor.\657\ Further, 
this measure will help ensure that the Hospital IQR Program includes 
measures which are applicable to rural hospitals.
---------------------------------------------------------------------------

    \655\ National Quality Forum. Quality Measure PC- 02 (Cesarean 
Birth). Available at: https://www.qualityforum.org/QPS/0471.
    \656\ National Quality Forum, Measure Applications Partnership. 
(2018). A Core Set of Rural-Relevant Measures and Measuring and 
Improving Access to Care: 2018 Recommendations from the MAP Rural 
Health Workgroup. Available at: https://www.qualityforum.org/Publications/2018/08/MAP_Rural_Health_Final_Report_-_2018.aspx.
    \657\ Centers for Medicare & Medicaid Services. (2015). Cesarean 
Birth (PC-02) Measure Public Comment Summary. Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/MMS/Downloads/PC-02-Public-Comment-Summary-Memo.pdf?msclkid=a582dfc0b52411ecbab8ba3255a5b678.
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    The Cesarean Birth eCQM was included in a publicly available 
document entitled ``List of Measures Under Consideration for December 
1, 2018'' (MUC List).\658\ The MAP's Final Report on February 15, 2019

[[Page 49223]]

conditionally supported the eCQM for rulemaking pending NQF evaluation 
and endorsement.\659\ The MAP suggested further feasibility testing, 
consultation with multiple stakeholders, and examination of unintended 
consequences.
---------------------------------------------------------------------------

    \658\ Centers for Medicare & Medicaid Services. (2018). List of 
Measures Under Consideration for December 1, 2018. Available at: 
https://www.cms.gov/files/document/2018rmuc-listclearancerpt.pdf.
    \659\ National Quality Forum.(2019). Measure Applications 
Partnership, MAP 2019 Considerations for Implementing Measures in 
Federal Programs: Hospitals Final Report. Available at: https://www.qualityforum.org/Publications/2019/02/MAP_2019_Considerations_for_Implementing_Measures_Final_Report_-_Hospitals.aspx.
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    Given the importance of this measure, we sought stakeholder input 
on the potential future inclusion of this measure in the FY 2020 IPPS/
LTCH PPS proposed rule (84 FR 19491 through 19494). Many stakeholders 
supported inclusion of the measure, though some stakeholders shared 
similar concerns as the MAP (84 FR 42493 through 42496). Thereafter, 
the measure steward conducted further reliability and validity testing 
in 2021 and submitted the measure to the NQF for consideration of 
endorsement in Spring 2022. Given the additional testing performed and 
feedback provided, we proposed this measure in the proposed rule.
    We also note that in 2020, the measure steward introduced the 
Cesarean Birth eCQM as one of the available eCQMs hospitals can choose 
for data submission to meet The Joint Commission's ORYX[supreg] 
requirements.\660\ The ORYX initiative integrates performance 
measurement data into The Joint Commission's accreditation 
process.\661\ Currently, we understand that The Joint Commission uses 
both the chart-abstracted (PC-02) and the eCQM versions. A total of 15 
hospitals (representing 6 sites) submitted production data for one 
quarter of calendar year 2020. We note that the measure steward reached 
out to all 15 hospitals to recruit sites willing to participate in 
reliability testing on the data submitted. Seven hospitals 
(representing 2 sites) volunteered. One site is a system representing 
six hospitals. The seventh hospital is a stand-alone facility that uses 
a different EHR system. During the third quarter of 2021, feasibility 
scorecards were completed, and the feasibility rate was found to be 98 
percent across the two EHR systems. Reliability and validity testing 
revealed the Cesarean Births eCQM to have a measure outcome agreement 
rate of 83.7 percent with a kappa score of .750 indicating substantial 
agreement. Overall, the data element agreement rate for all hospitals 
was 92.2 percent.
---------------------------------------------------------------------------

    \660\ The Joint Commission. (2020). 2020 ORYX Performance 
Measure Reporting Requirements. Available at: https://www.jointcommission.org/-/media/tjc/documents/measurement/oryx/cy2020-oryx-reporting-requirements_.pdf.
    \661\ The Joint Commission. Accreditation-ORYX. Available at: 
https://www.jointcommission.org/measurement/reporting/accreditation-oryx/.
---------------------------------------------------------------------------

    As mentioned previously, the NQF has endorsed the chart-abstracted 
form of this measure. Additionally, the measure steward submitted the 
eCQM to the NQF for consideration of endorsement during Spring 2022. We 
note that section 1866(b)(3)(B)(viii)(IX)(aa) of the Act requires that 
any measure specified by the Secretary must have been endorsed by the 
entity with a contract under section 1890(a) of the Act (the NQF is the 
entity that currently holds this contract). Under section 
1886(b)(3)(B)(viii)(IX)(bb) of the Act, in the case of a specified area 
or medical topic determined appropriate by the Secretary for which a 
feasible and practical measure has not been endorsed by the entity with 
a contract under section 1890(a) of the Act, the Secretary may specify 
a measure that is not endorsed as long as due consideration is given to 
measures that have been endorsed or adopted by a consensus organization 
identified by the Secretary. We reviewed NQF-endorsed measures and note 
that while the chart-abstracted version is endorsed, we were unable to 
identify any other NQF-endorsed measures on this topic, and, therefore 
we believe the exception in section 1886(b)(3)(B)(viii)(IX)(bb) of the 
Act applies.
    The measure specifications for the Cesarean Birth eCQM can be found 
on the eCQI Resource Center website, available at: https://ecqi.healthit.gov/pre-rulemaking-eh-cah-ecqms.
(3) Data Sources
    The eCQM uses data collected through hospitals' EHRs. The measure 
is designed to be calculated by the hospitals' CEHRT using the patient-
level data and then submitted by hospitals to CMS.
(4) Measure Calculation
    This eCQM assesses the rate of nulliparous women with a term, 
singleton baby in a vertex position delivered by C-section birth.\662\ 
The eCQM uses one of the following: Nulliparous defined as Parity = 0, 
Gravidity = 0, or Preterm and Term both = 0. Parity is the number of 
completed pregnancies reaching 20 weeks gestation regardless of the 
number of fetuses or outcome of the pregnancy. Gravidity is the number 
of pregnancies, current and past, regardless of the pregnancy outcome. 
Preterm is less than 37 weeks and 0 days, and Term is greater than or 
equal to 37 weeks and 0 days using best Estimated Due Delivery (EDD).
---------------------------------------------------------------------------

    \662\ The Joint Commission. (2021). eCQM Specifications 2022 
Reporting Period. Available at: https://www.jointcommission.org/-/media/tjc/documents/measurement/specification-manuals/2022-reporting-period/january-2022/ecqm_specifications_reportingperiod_2022.zip.
---------------------------------------------------------------------------

(5) Outcome
    The outcome of interest is the number of C-sections to NTSV women 
divided by all live, term (>=37 weeks gestation) singleton deliveries 
to NTSV women.
(6) Cohort
    The cohort consists of all patients in the denominator: Nulliparous 
women with a singleton, vertex fetus at >=37 weeks of gestation who 
deliver a liveborn infant. The cohort includes all pertinent patients 
regardless of payer (for example, Medicare, Medicaid, other public 
programs, private insurance, self-pay, or charity care) or admission 
source (for example, home, ED, nursing home, hospice, another hospital, 
or law enforcement).
(7) Numerator
    The measure numerator consists of the subset of patients delivering 
by C-section.
(8) Denominator
    The measure denominator consists of the number of nulliparous women 
with a singleton, vertex fetus at >=37 weeks of gestation who deliver a 
liveborn infant.
(9) Exclusion Criteria
    The measure excludes patients with abnormal presentations or 
placenta previa.
(10) Risk Adjustment
    This measure is not currently risk adjusted. When developing the 
measure, the exclusion criteria were chosen to ensure that the focus 
population will be women with NTSV pregnancies. Nulliparous women are 
those experiencing their first birth. These women have a lower risk of 
maternal morbidity and mortality during a vaginal birth delivery than 
do women who have undergone a previous C-section.\663\ The population 
of women in the denominator as a result of the exclusions allow the 
measure to focus on a more homogeneous group of women where the 
greatest improvement opportunity exists as evidenced by variation in 
rates of NTSV C-sections,

[[Page 49224]]

indicating clinical practice patterns may affect this rate.\664\ 
Lowering the C-section rate in NTSV pregnancies is important because C-
sections may carry a higher risk of subsequent miscarriage, placental 
abnormalities, and repeat C-section.\665\ The rates of ruptured uteri, 
unplanned hysterectomies, and ICU admission are higher among women who 
deliver via C-section for the first time than those who deliver 
vaginally for the first time across all races and ethnicities. However, 
non-Hispanic Black women who deliver via C-section for the first time 
had the highest rates of uterine rupture and ICU admission compared 
with all other races.\666\ Focusing on the NTSV population aligns with 
the measure intent to have a significant effect on cesarean birth 
rates. We believe this could encourage a decrease in C-section rates in 
the NTSV population, which will in turn have a meaningful impact on 
future pregnancies and maternal health. Including a comprehensive set 
of maternal medical exclusions will add data collection burdens without 
commensurate benefit.
---------------------------------------------------------------------------

    \663\ Caughey AB, Cahill AG, Guise JM, Rouse DJ. (2014). Safe 
prevention of the primary cesarean delivery. Am J Obstet Gynecol, 
210(3): 179-93. doi: 10.1016/j.ajog.2014.01.026.
    \664\ Caughey AB, Cahill AG, Guise JM, Rouse DJ. (2014). Safe 
prevention of the primary cesarean delivery. Am J Obstet Gynecol, 
210(3): 179-93. doi: 10.1016/j.ajog.2014.01.026.
    \665\ Keag, O.E., Norman, J.E. & Stock, S.J. (2018). Long-term 
risks and benefits associated with cesarean delivery for mother, 
baby, and subsequent pregnancies: Systematic review and meta-
analysis. Plos Med, 15(1): e1002494.
    \666\ Curtin, S.C., Gregory, K.D., Korst, L.M., Uddin, S.F.G. 
(2015) Maternal Morbidity for Vaginal and Cesarean Deliveries, 
According to Previous Cesarean History: New Data from the Birth 
Certificate, 2013. National Vital Statistics Reports, 64(4). 
Available at: https://www.cdc.gov/nchs/data/nvsr/nvsr64/nvsr64_04.pdf.
---------------------------------------------------------------------------

(11) Data Submission and Reporting
    We refer readers to: Section IX.E.10.e. of the preamble of this 
final rule for a discussion of our previously finalized eCQM reporting 
and submission policies; and section IX.E.13.b. for the public 
reporting of eCQM data. Additionally, we refer readers to section 
IX.E.10.e.(4). where we discuss the use of the zero denominator 
declarations and case threshold exemption policies for hospitals.
    We also refer readers to four related proposals discussed in the 
preamble of this final rule: (1) Section IX.E.10.e. where we discuss 
modifications to our reporting and submission requirements for eCQMs, 
including a discussion of our policy to require hospitals to report on 
the Cesarean Birth eCQM; (2) section IX.E.5.d. for our policy to adopt 
the Severe Obstetric Complications eCQM; (3) section IX.H.10.a.(2).of 
the preamble of this final rule for a discussion of similar policies to 
adopt these two perinatal eCQMs in the Medicare Promoting 
Interoperability Program for Eligible Hospitals and Critical Access 
Hospitals (CAHs); and (4) section IX.E.8. where we are establishing a 
publicly-reported hospital designation to capture the quality and 
safety of maternity care and other related activities in advancing 
maternal health equity.
    We invited public comment on this proposal.
    Comment: Many commenters supported adoption of the Cesarean Birth 
eCQM beginning with the CY 2023 reporting period/FY 2025 payment 
determination and mandatory reporting beginning with the CY 2024 
reporting period/FY 2026 payment determination and for subsequent 
years. Commenters agreed with our rationale in the preamble of the FY 
2023 IPPS/LTCH PPS proposed rule and underscored their beliefs that the 
measure could support the provision of high- quality maternity care, 
that this data is necessary for addressing the maternal health crisis, 
and that the measure could lead to improved clinical practices. 
Additionally, a few commenters indicated that their support was tied to 
the measure's alignment with their state's or The Joint Commission's 
reporting practices.
    Response: We thank the commenters for their support of the Cesarean 
Birth eCQM and agree that measure is in line with best practices for 
reducing low-risk C-sections. As we noted in the preamble of the FY 
2023 IPPS/LTCH PPS proposed rule, we believe the measure addresses a 
key priority area and will further our goal of addressing maternal 
health outcomes in the Hospital IQR Program (87 FR 28507).
    Comment: A few commenters supported the proposal, but recommended 
staggered implementation, extending the voluntary reporting period for 
an additional year, or making the measure voluntary permanently.
    Response: We thank commenters for their input on the timeline of 
adoption and implementation of the Cesarean Birth eCQM. We believe 
adopting measures like the Cesarean Birth eCQM presents unique 
opportunities for large-scale quality measurement and activities that 
can improve the short- and long-term health outcomes for mothers and 
children (87 FR 28508). As a result, we believe the proposed timeline 
of inclusion of this eCQM into the Hospital IQR Program measure set 
beginning in CY 2023 reporting period/FY 2025 payment determination (in 
which hospitals can choose to self-select reporting of this measure) 
followed by mandatory reporting beginning with the CY 2024 reporting 
period/FY 2026 payment determination and for subsequent years is 
sufficient for EHR vendors and hospitals to incorporate, adopt, and 
implement this measure.
    Comment: A few commenters supported the proposal and recommended 
monitoring the measures in the future to track performance or to modify 
or expand the exclusion criteria as needed.
    Response: We thank commenters for their support and agree that 
continued monitoring of the measures is important. We believe 
collecting data and reporting results will provide a critical baseline 
and we will monitor the data and any unintended consequences of the 
measure as part of standard measure maintenance.
    Comment: A commenter supported the measure and requested 
clarification on how non-birthing hospitals would be affected by the 
adoption of this eCQM.
    Response: We thank the commenter for their requested clarification 
on how hospitals which do not provide labor and delivery services would 
be affected. As stated in the FY 2023 IPPS/LTCH PPS proposed rule, the 
Cesarean Birth eCQM would be reported by all hospitals participating in 
the Hospital IQR Program, except those hospitals that do not have an 
obstetrics department and do not perform deliveries (87 FR 28507). We 
also refer readers to section IX.E.10.e.(4). of this final rule where 
we discuss the Hospital IQR Program's zero denominator declarations and 
case threshold exemption policies for eCQMs. Zero denominator 
declarations allow a hospital whose EHR is capable of reporting eCQM 
data to submit a zero in the denominator for the reporting of an eCQM 
if the hospital does not have patients that meet the denominator 
criteria of that hybrid measure (82 FR 38387). Similarly, the case 
threshold exemptions policy allows for a hospital with five or fewer 
inpatient discharges per quarter or 20 or fewer inpatient discharges 
per year in a given denominator declaration be exempted from reporting 
on that individual eCQM (82 FR 38387). We refer readers to the FY 2016 
IPPS/LTCH PPS final rule (80 FR 49705 through 49708) and the FY 2017 
IPPS/LTCH PPS final rule (81 FR 57170) for our previously adopted eCQM 
file format requirements. Hospitals can continue to meet the reporting 
requirements by submitting data via QRDA I files, zero denominator 
declaration, or case threshold exemption (82 FR 38387).

[[Page 49225]]

    Comment: Many commenters did not support the adoption of the 
Cesarean Birth eCQM. Several commenters believed the measure is 
misaligned with factors that contribute to negative outcomes, or that 
testing and validation of the eCQM has been insufficient to establish 
that the measure is appropriately aligned. Several commenters did not 
support the measure because it does not have NQF endorsement. A few 
commenters recommended the adoption of alternative measures which they 
believed would more appropriately align with the equity goal. A few 
commenters did not support the measure because they believed there is 
no ideal rate of C-sections. A commenter did not support because they 
believed that diverting natural birth from C-section begins earlier 
than when a patient seeks hospital labor and delivery services, which 
the measure does not capture.
    Response: We thank the commenters for their input. As stated in the 
FY 2023 IPPS/LTCH PPS proposed rule, the NQF has endorsed the chart-
abstracted version of this measure and the measure steward has 
submitted the eCQM to NQF for consideration of endorsement (87 FR 
28509). We also note that section 1886(b)(3)(B)(viii)(IX)(bb) offers an 
exception in the case of a specified area or medical topic determined 
appropriate by the Secretary for which a feasible and practical measure 
has not been endorsed by the entity under contract under section 
1890(a) of the Act, and the Secretary may specify a measure that is not 
endorsed as long as due consideration is given to measures that have 
been endorsed or adopted by a consensus organization identified by the 
Secretary. We reviewed NQF-endorsed measures and note that while the 
chart-abstracted measure is endorsed, we were unable to identify any 
other NQF-endorsed measures on this topic and therefore believe the 
exception at 1886(b)(3)(B)(viii)(IX)(bb) applies. Given the severity of 
the maternal morbidity crisis and as there are currently no NQF-
endorsed measures that address Cesarean birth we believe it is 
important to implement this measure as soon as possible. We appreciate 
the suggestions of alternative measures and will consider them for 
potential future rulemaking.
    Regarding commenter concerns about testing and validation, the 
measure steward conducted additional testing in 2021. The reliability 
and validity testing found the measure to have an overall data element 
agreement rate of 92.2 percent and we therefore believe the measure to 
be reliable and valid for use in the Hospital IQR Program. We believe 
that this measure serves as a key first step in measuring and promoting 
quality improvement in maternity care by encouraging hospitals to track 
their rate of low- risk C-sections and practices that may be 
contributing to trends in low-risk C-sections in the United States. 
While we agree that there is no ideal rate of low-risk C-sections, we 
noted in the FY 2023 IPPS/LTCH PPS proposed rule, the Cesarean Birth 
eCQM is intended to facilitate safer patient care by assessing the rate 
of NTSV C-sections to ultimately reduce the occurrence of non-medically 
indicated C-sections, promoting adherence to recommended clinical 
guidelines, and encouraging hospitals to track and improve their 
practices in caring for pregnant and postpartum patients (87 FR 28508). 
Additionally, we acknowledged that there are instances where C-sections 
are medically indicated and continue to emphasize that this measure is 
not intended to discourage practitioners from performing C-sections 
writ large (87 FR 28508). A group of subject matter experts for NQF 
noted that decreasing the rate of non-medically indicated C-sections 
can result in increased patient safety, decreased maternal and neonatal 
morbidity, and substantial savings in healthcare costs.\667\
---------------------------------------------------------------------------

    \667\ National Quality Forum. (2008) Perinatal and Reproductive 
Health Project NQF #0471 PC-02 Cesarean Section: Measure Submission 
and Evaluation Worksheet 5.0. Available at: https://www.qualityforum.org/Projects/n-r/Perinatal_Care_Endorsement_Maintenance_2011/0471.aspx.
---------------------------------------------------------------------------

    Comment: A commenter did not support adoption and expressed concern 
that the time to implement the measure was insufficient.
    Response: We thank the commenter for their input and respectfully 
disagree that the timeline for adoption is not appropriate. We 
emphasize that as proposed, hospitals may choose to report the Cesarean 
Birth eCQM as one of the three self-selected eCQMs for the CY 2023 
reporting period/FY 2025 payment determination. After which, beginning 
with the CY 2024 reporting period/FY 2026 payment determination and for 
subsequent years, the Cesarean Birth eCQM would be required to be 
reported by all hospitals, except those hospitals that do not have an 
obstetrics department and do not perform deliveries. This timeline will 
allow hospitals at least one year to prepare and implement the measure 
before they are required to report it.
    Comment: A few commenters did not support the proposal because they 
believed the exclusion criteria are not broad enough and should be risk 
adjusted. A few commenters did not support adoption of the measure 
because it does not distinguish between medically necessary and non-
medically necessary procedures. A commenter requested that CMS clarify 
that the measure is not intended to discourage medically necessary C-
sections.
    Response: We thank the commenters for their input. While we agree 
that there are many ways to track data related to the C-section rate in 
the United States, and ultimately reduce excess non-medically indicated 
C-sections, the standards and comprehensiveness of initiatives can vary 
widely, and we do not believe broadening exclusion criteria or risk 
adjustment is necessary at this time. As we noted in the FY 2023 IPPS/
LTCH PPS proposed rule, when developing the measure, the exclusion 
criteria were chosen to ensure that the focus population would be women 
with NTSV pregnancies (86 FR 28510). Barring the presence of other co-
morbidities, such women often have a lower risk of maternal morbidity 
and mortality at the time of delivery than their counterparts who have 
undergone a previous C-section (87 FR 28510). As a result of the 
existing exclusion criteria, the population denominator allows the 
measure to focus on a more homogeneous group where the greatest 
improvement opportunity exists. As evidenced by variation in rates of 
NTSV C-sections, clinical practice patterns in particular may affect 
this rate (87 FR 28510). Lowering the C-section rate in NTSV 
pregnancies is important because C-sections may carry a higher risk of 
subsequent miscarriage, placental abnormalities, and repeat C-section 
(87 FR 28510). The rates of ruptured uteri, unplanned hysterectomies, 
and ICU admission are higher among women who deliver via C-section for 
the first time than those who deliver vaginally for the first time 
across all races and ethnicities (87 FR 28507). However, non-Hispanic 
Black women who deliver via C-section for the first time had the 
highest rates of uterine rupture and ICU admission compared with all 
other races.\668\ Including a comprehensive set of maternal medical 
exclusions would add data collection burdens without commensurate 
benefit. Regarding commenters' concerns based on a lack of distinction 
between medically indicated and non-medically indicated procedures, the 
measure is designed to

[[Page 49226]]

track C-section prevalence in the lowest-risk population, and we 
believe that any reduction in the rate will inherently overburden non-
medically indicated C-sections.
---------------------------------------------------------------------------

    \668\ Curtin, S.C., Gregory, K.D., Korst, L.M., Uddin, S.F.G. 
(2015) Maternal Morbidity for Vaginal and Cesarean Deliveries, 
According to Previous Cesarean History: New Data from the Birth 
Certificate, 2013. National Vital Statistics Reports, 64(4). 
Available at: https://www.cdc.gov/nchs/data/nvsr/nvsr64/nvsr64_04.pdf.
---------------------------------------------------------------------------

    Comment: A few commenters did not support the eCQM because they 
believed the chart-abstracted version of the measure was acceptable.
    Response: We thank the commenters for their input. We note that the 
NQF has endorsed the chart-abstracted form of this measure (PC-02: 
Cesarean Birth, NQF #0471) as a voluntary consensus standard since 2008 
and continuously renewed its endorsement (most recently in 2020) (87 FR 
28508). Additionally, the measure steward introduced the Cesarean Birth 
eCQM as one of the available eCQMs hospitals can choose for data 
submission to meet The Joint Commission's ORYX[supreg] requirements (87 
FR 28509). We believe that the proposal for use of the eCQM version 
continues our approach to collect data derived from EHRs and make 
progress toward a transition to fully digital measurement. We refer 
readers to section IX.C. of the preamble of this final rule--
``Continuing to Advance to Digital Quality Measurement and the Use of 
Fast Healthcare Interoperability Resources (FHIR) in Hospital Quality 
Programs--Request for Information''--where we outlined and solicited 
comments on ongoing efforts to advance digital quality measurement.
    Comment: Many commenters recommended delaying adoption of the 
measure because they requested we conduct additional testing for 
validity and reliability testing.
    Response: We thank commenters for their input and feedback on this 
measure. As we noted in the FY 2023 IPPS/LTCH PPS proposed rule, the 
measure steward submitted the eCQM to the NQF for consideration of 
endorsement during Spring 2022 (87 FR 28509). As part of that process, 
it has gone through the Scientific Methods Panel and no major issues 
were raised around measure reliability. Regarding reliability concerns, 
we refer readers to the discussion in FY 2023 IPPS/LTCH PPS proposed 
rule (87 FR 28509) and in section IX.E.5.c. of the preamble of this 
final rule where we discuss the validity and reliability testing which 
found that this measure has a measure outcome agreement rate of 83.7 
percent with a kappa score of .750 indicating substantial agreement. 
Overall, the data element agreement rate for all hospitals was 92.2 
percent. Additionally, the measure developer notes that the Cesarean 
Birth eCQM rates for the 13 hospitals who submitted both eCQM and 
chart-abstracted measure results to the measure developer for 2020 
discharges were correlated. A correlation of 0.1-0.3 is considered 
weak, 0.3-0.5 is considered moderate, and over 0.5 is considered 
strong. The measure developer also clarified that the eCQM and the 
chart-based (NQF-endorsed) versions of the measure correlate at 0.88 
which is strong and is statistically significant (p<0.01). Given the 
severity of the maternal morbidity crisis we believe it is important to 
implement this measure as soon as possible.
    Comment: A few commenters suggested additions to the measure to 
increase alignment with the measure's goals. The comments included 
recommendations that the measure: (1) track efforts taken to eliminate 
disparities in maternal health outcomes; (2) track unexpected 
complications in term newborns; (3) data be disaggregated; (4) track 
how social drivers of health contribute to C-section rates; (5) 
exclusion criteria be broadened; and (6) be monitored closely to 
determine if the measure is tracking useful data.
    Response: We thank commenters for their recommendations on changes 
to the measure specifications. We note the current scope of the 
exclusion criteria are selected based on the most up-to-date literature 
and then were rigorously tested by the measure steward. While we agree 
that there are many ways to track data related to the C-section rate in 
the United States, the standards and comprehensiveness of initiatives 
can vary widely. We will keep the recommendations in mind in the future 
if any changes to the eCQM are necessary as part of our regular measure 
maintenance. Regarding monitoring of the measure's impact, we note 
that, as with all Hospital IQR Program measures, we will monitor the 
data as part of the standard measure maintenance.
    Comment: A commenter recommended that the specifications for the 
measure be published concurrently with the final rule.
    Response: As part of notice-and-comment rulemaking, we publish 
measure specifications on a CMS website for interested parties to 
review. As we noted in the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 
28509), measure specifications for eCQMs, including the Cesarean Birth 
eCQM, can be found on the eCQI Resource Center website, available at: 
https://ecqi.healthit.gov.
    Comment: A commenter recommended that CMS clarify that the measure 
tracks all procedures, regardless of payer.
    Response: As we noted in the FY 2023 IPPS/LTCH PPS proposed rule 
that the cohort includes all pertinent patients regardless of payer (87 
FR 28509).
    Comment: A few commenters expressed concerns about the consistency 
of performance data extraction from clinical data or patient charts or 
requested clarification on extracting data from clinical notes. 
Specifically, a commenter expressed concern that not all components of 
the proposed measure are identifiable using standard coding data.
    Response: We thank the commenters for their feedback. We interpret 
the commenters to mean that they have concerns about extracting 
clinical data from paper charts or notes. We refer readers to the FY 
2016 IPPS/LTCH PPS final rule (80 FR 49705 through 49708) and the FY 
2017 IPPS/LTCH PPS final rule (81 FR 57169 through 57170) for our 
previously adopted eCQM file format requirements. Under these 
requirements, hospitals: (1) Must submit eCQM data via the Quality 
Reporting Document Architecture Category I (QRDA I) file format as was 
previously required; (2) may use third parties to submit QRDA I files 
on their behalf; and (3) may either use abstraction or pull the data 
from noncertified sources in order to then input these data into CEHRT 
for capture and reporting QRDA I files. Hospitals can continue to meet 
the reporting requirements by submitting data via QRDA I files, zero 
denominator declaration, or case threshold exemption (82 FR 38387). We 
encourage hospitals to continue to work with their EHR vendors to 
refine their processes optimally.
    After consideration of the public comments we received, we are 
finalizing our proposal as proposed.
d. Severe Obstetric Complications eCQM Beginning With the CY 2023 
Reporting Period/FY 2025 Payment Determination With Mandatory Reporting 
Beginning With the CY 2024 Reporting Period/FY 2026 Payment 
Determination and for Subsequent Years
    In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28510 through 
28515), we proposed to adopt the Severe Obstetric Complications eCQM as 
one of the eCQMs in the Hospital IQR Program measure set on which 
hospitals can self-select to report for the CY 2023 reporting period/FY 
2025 payment determination. We also proposed to make reporting of this 
eCQM mandatory beginning with the CY 2024 reporting period/FY 2026 
payment determination and for subsequent years.

[[Page 49227]]

(1) Background
    Severe maternal morbidity (SMM) refers to unexpected outcomes due 
to complications at labor and delivery that result in significant 
consequences to a woman's health, and includes, but is not limited to, 
hemorrhage, embolism, severe hypertension, stroke, and other serious 
complications.\669\ Despite the highest rate of spending on maternity 
care, totaling $1.4 billion dollars in FY 2021,\670\ the U.S. ranks 
worse than most other developed nations in pregnancy-related deaths and 
the rate of SMM is continuing to steadily increase.671 672 
As reported by the CDC, the overall rate of SMM increased almost 200 
percent, from 49.5 per 10,000 delivery hospitalizations in 1993 to 144 
per 10,000 delivery hospitalizations in 2014.673 674 675 
Increasing rates of SMM are resulting in increased healthcare costs, 
longer hospitalization stays, and short- and long-term negative 
outcomes to women's health.676 677 678 679
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    \669\ Centers for Disease Control and Prevention. (2021). Severe 
Maternal Morbidity in the United States. Available at: https://www.cdc.gov/reproductivehealth/maternalinfanthealth/severematernalmorbidity.html.
    \670\ Kaiser Family Foundation. (2021). The U.S. Government and 
Global Maternal and Child Health Efforts. Available at: https://www.kff.org/global-health-policy/fact-sheet/the-u-s-government-and-global-maternal-and-child-health-efforts/.
    \671\ Centers for Disease Control and Prevention. (2021). Severe 
Maternal Morbidity in the United States. Available at: https://www.cdc.gov/reproductivehealth/maternalinfanthealth/severematernalmorbidity.html.
    \672\ Maternal Health Task Force. (2015). Maternal Health in the 
United States. Available at: https://www.mhtf.org/topics/maternal-health-in-the-united-states/.
    \673\ Centers for Disease Control and Prevention. (2021). Severe 
Maternal Morbidity in the United States. Available at: https://www.cdc.gov/reproductivehealth/maternalinfanthealth/severematernalmorbidity.html.
    \674\ Leonard SA et al. (2019). Racial and ethnic disparities in 
severe maternal morbidity prevalence and trends. Annals of 
epidemiology. 2019;33:30-36.
    \675\ Petersen EE, Davis NL, Goodman D, et al. (2019). Vital 
signs: pregnancy-related deaths, United States, 2011-2015, and 
strategies for prevention, 13 states, 2013-2017. Morbidity and 
Mortality Weekly Report. 68(18):423.
    \676\ Vesco KK et al. (2020). Costs of Severe Maternal Morbidity 
During Pregnancy in U.S. Commercially Insured and Medicaid 
Populations: An Observational Study. Maternal and Child Health 
Journal,24(1):30-38.
    \677\ Chen HY, Chauhan SP, Blackwell SC. (2018). Severe Maternal 
Morbidity and Hospital Cost among Hospitalized Deliveries in the 
United States. Am J Perinatol. 2018 Nov;35(13):1287-1296. doi: 
10.1055/s-0038-1649481. Epub 2018 May 3. PMID: 29723900.
    \678\ Lin, Ching-Ching Claire, et al. (2020). ``Rural-urban 
differences in delivery hospitalization costs by severe maternal 
morbidity status.'' Annals of Internal Medicine 173.11_Supplement: 
S59-S62.
    \679\ Premier Inc. (2019). Report 2: The Added Cost of 
Complications During and After Delivery. Available at: https://explore.premierinc.com/Global/FileLib/Quick_Start_Cloud/19250_BudleofJoyReport_Report2_v7_digital.pdf.
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    Without proper treatment and awareness surrounding SMM, such 
complications can lead to mortality.\680\ While partially attributed to 
changes in reporting standards, the maternal mortality rate has also 
risen in the U.S. from 17 deaths per 100,000 live births in 1990 to 26 
deaths per 100,000 live births in 2015.\681\ Recent maternal mortality 
data from 2018 reveal that 658 women died from pregnancy-related 
complications, resulting in a rate of 17.4 deaths per 100,000 live 
births, with 77 percent of the deaths attributed to direct obstetric 
causes like hemorrhage, preeclampsia, obstetric embolism, and other 
complications.682 683 Researchers have found that the 
presence of select maternal morbidities such as chronic hypertension, 
preeclampsia, and sepsis were strongly associated with increased odds 
of mortality at the time of delivery.684 685 Similar to 
maternal mortality, the existing literature on maternal morbidity 
indicates that a significant proportion of maternal morbidity is highly 
preventable.\686\ Therefore, timely and appropriate treatment of 
maternal morbidities is imperative to prevent complications that can 
lead to maternal mortality.\687\
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    \680\ Kilpatrick, S.K., Ecker, J.L. (2016). Severe Maternal 
Morbidity: Screening and Review. American Journal of Obstetrics and 
Gynecology, 215(3):B17-B22.
    \681\ Maternal Health Task Force. (2015). Maternal Health in the 
United States. Available at: https://www.mhtf.org/topics/maternal-health-in-the-united-states/.
    \682\ Hoyert, D. L., & Mini[ntilde]o, A. M. (2020). Maternal 
mortality in the United States: changes in coding, publication, and 
data release, 2018.
    \683\ St Pierre A, Zaharatos J, Goodman D, Callaghan WM. 
Challenges and Opportunities in Identifying, Reviewing, and 
Preventing Maternal Deaths. Obstet Gynecol. 2018 Jan;131(1):138-142. 
doi: 10.1097/AOG.0000000000002417. PMID: 29215526; PMCID: 
PMC6511983.
    \684\ Campbell, K. H. et al. (2013). Maternal Morbidity and Risk 
of Death at Delivery Hospitalization. Obstetrics and Gynecology, 
122(3): 627-633. Available at: https://journals.lww.com/greenjournal/fulltext/2013/09000/Maternal_Morbidity_and_Risk_of_Death_at_Delivery.20.aspx.
    \685\ Mocumbi, A. O., Sliwa, K., & Soma-Pillay, P. (2016). 
Medical disease as a cause of maternal mortality: the pre-imminence 
of cardiovascular pathology: review articles. Cardiovascular journal 
of Africa, 27(2), 84-88.
    \686\ Kilpatrick, S.K., Ecker, J.L. (2016). Severe Maternal 
Morbidity: Screening and Review. American Journal of Obstetrics and 
Gynecology, 215(3): B17.
    \687\ Kilpatrick, S.K., Ecker, J.L. (2016). Severe Maternal 
Morbidity: Screening and Review. American Journal of Obstetrics and 
Gynecology. 215(3): B17.
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    Additionally, racial and ethnic disparities are significant; non-
Hispanic Black women are at considerably higher risk for developing 
these maternal complications than are non-Hispanic White 
women.688 689 Maternal death rate data indicate wide ethnic 
and racial gaps exist in maternal healthcare and outcomes. The maternal 
death rate for Black women is more than double that of White women--
37.1 deaths per 100,000 live births compared to 14.7--and almost three 
times the rate compared to Hispanic women--11.8 deaths per 100,000 live 
births.\690\
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    \688\ Leonard, S.A., Main, E.K., Scott, K.A., Profit, J., & 
Carmichael, S.L. (2019). Racial and ethnic disparities in severe 
maternal morbidity prevalence and trends. Annals of epidemiology, 
33, 30-36.
    \689\ Petersen, E.E. et al. (2019). Vital signs: pregnancy-
related deaths, United States, 2011-2015, and strategies for 
prevention, 13 states, 2013-2017. Morbidity and Mortality Weekly 
Report, 68(18), 423.
    \690\ Centers for Disease Control and Prevention. (2020). First 
Data Released on Maternal Mortality in Over a Decade. Available at: 
https://www.cdc.gov/nchs/pressroom/nchs_press_releases/2020/202001_MMR.htm.
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    As stated in the HHS Action Plan to Improve Maternal Health in 
America,\691\ we are pursuing a vision for improving maternal health by 
focusing on: (1) Reducing maternal mortality, including disparities by 
race, ethnicity, and geography, in 5 years; (2) reducing SMM, including 
disparities by race and ethnicity, in five years; and (3) increasing 
hospital participation in HHS-sponsored maternal health quality 
improvement initiatives. As reflected in these goals, a critical focus 
of our maternal health efforts is reducing existing disparities in 
maternal health outcomes across race, ethnicity, and geographic area. 
This is further reflected in the Biden-Harris Administration's first 
ever Presidential Proclamation recognizing Black Maternal Health 
Week.\692\ CMS is also interested in promoting policies that ensure 
Americans who live in rural areas have access to high quality care, 
particularly in the area of maternal health where residents in rural 
settings have a 9 percent greater probability of SMM and mortality, 
compared with urban residents.\693\ Ultimately, driving the development 
and execution of evidence-based best practices in maternity care, 
improving overall maternal health, and closing the racial and ethnic 
disparity gaps in outcomes are among our

[[Page 49228]]

agency's top healthcare quality and safety goals.\694\
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    \691\ U.S. Department of Health and Human Services. Healthy 
Women, Healthy Pregnancies, Healthy Futures: Action Plan to Improve 
Maternal Health in America. Available at: https://aspe.hhs.gov/sites/default/files/private/aspe-files/264076/healthy-women-healthy-pregnancies-healthy-future-action-plan_0.pdf.
    \692\ White House. (2021). A Proclamation on Black Maternal 
Health Week. Available at: https://www.whitehouse.gov/briefing-room/presidential-actions/2021/04/13/a-proclamation-on-black-maternal-health-week-2021/.
    \693\ Kozhimannil, K.B., Interrante, J.D., Henning-Smith, C., & 
Admon, L.K. (2019). Rural-urban differences in severe maternal 
morbidity and mortality in the US, 2007-15. Health affairs, 38(12), 
2077-2085.
    \694\ Centers for Medicare & Medicaid Services. (2021). 
Evidence-based best practices for hospitals in managing obstetric 
emergencies and other key contributors to maternal health 
disparities. Available at: https://www.cms.gov/files/document/qso-22-05-hospitals.pdf.
---------------------------------------------------------------------------

    Currently, the Hospital IQR Program includes two measures that 
address improving maternal health: The Elective Delivery measure (PC-
01) (77 FR 53530) and the Maternal Morbidity Structural measure (86 FR 
45361 through 45365). In section IX.E.5.c. of the preamble of this 
final rule, we are finalizing the adoption of the Cesarean Birth eCQM 
as part of the Hospital IQR Program measure set. However, there are 
currently no maternal morbidity or obstetric complications outcome-
based measures in the Hospital IQR Program.
    The Severe Obstetric Complications eCQM has been developed to focus 
on the high maternal morbidity and mortality rates in the U.S., which 
we believe will present important opportunities for large-scale quality 
measurement and improvement activities in the Hospital IQR 
Program.\695\ Statistics on preventability vary but suggest that a 
considerable proportion of maternal morbidity and mortality events 
could be prevented.696 697 This measure is intended to 
facilitate safer patient care by increasing awareness of the danger of 
obstetric complications, promoting adherence to recommended clinical 
guidelines, and encouraging hospitals to track and improve their 
practices of appropriate monitoring and care delivery for pregnant and 
postpartum patients.
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    \695\ National Quality Forum. (2022). Measure Applications 
Partnership (MAP) 2021-2022 Final Recommendations. Available at: 
https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96698.
    \696\ Davis, N.L., Smoots, A.N., & Goodman, D.A. (2019). 
Pregnancy-Related Deaths: Data from 14 US Maternal Mortality Review 
Committees. Education, 40(36), 8-2.
    \697\ Geller SE, Rosenberg D, Cox SM, et al. (2004). The 
continuum of maternal morbidity and mortality: factors associated 
with severity. American journal of obstetrics and gynecology, 
191(3):939-944.
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    Under CMS' Meaningful Measures Framework, the Severe Obstetric 
Complications eCQM addresses the quality priority of ``Make Care Safer 
by Reducing Harm Caused in the Delivery of Care'' through the 
Meaningful Measures Area of ``Preventable Healthcare Harm.'' 
Additionally, pursuant to Meaningful Measures 2.0, this measure 
addresses the ``Safety'' priority area and aligns with our commitment 
to a patient-centered approach in quality measurement to ensure that 
patients are safe and receive the highest quality care.\698\
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    \698\ Centers for Medicare & Medicaid Services. Meaningful 
Measures 2.0: Moving from Measure Reduction to Modernization. 
Available at: https://www.cms.gov/meaningful-measures-20-moving-measure-reduction-modernization. We note that Meaningful Measures 
2.0 is still under development.
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    Therefore, in the proposed rule, we proposed the adoption of the 
Severe Obstetric Complications eCQM beginning with the CY 2023 
reporting period/FY 2025 payment determination. We previously finalized 
that hospitals must report on three self-selected eCQMs and the Safe 
Use of Opioids--Concurrent Prescribing eCQM, for a total of four eCQMs 
in the CY 2023 reporting period/FY 2025 payment determination (85 FR 
58939). In the proposed rule, we proposed to include this measure as 
part of the measure set in the Hospital IQR Program which hospitals 
will be able to self-select for the CY 2023 reporting period/FY 2025 
payment determination. After which, beginning with the CY 2024 
reporting period/FY 2026 payment determination and for subsequent 
years, we proposed to require reporting of the Severe Obstetric 
Complications eCQM by all hospitals except those hospitals that do not 
perform deliveries or have an obstetrics department. We refer readers 
to section IX.E.10.e. of preamble of this final rule for our related 
policy to modify the eCQM reporting and submission requirements 
beginning with the CY 2024 reporting period/FY 2026 payment 
determination.
(2) Overview of Measure
    This measure assesses the proportion of patients with severe 
obstetric complications which occur during the inpatient delivery 
hospitalization. The Severe Obstetric Complications eCQM was included 
in the publicly available ``List of Measures Under Consideration for 
December 1, 2021'' (MUC List).\699\ The MAP Rural Health Advisory Group 
reviewed the MUC List and the Severe Obstetric Complications eCQM (MUC 
2021-104) on December 8, 2021.\700\ The MAP Rural Health Advisory 
Workgroup discussed questions regarding the specifications of the 
measure. First, there was discussion about the use of blood 
transfusions as an intervention and concern that blood transfusions 
would be excluded and/or delayed when clinical evidence indicates that 
patients would benefit from transfusions as an earlier intervention. 
The measure developer provided clarification that this measure reports 
two outcomes, one that includes all patients that meet the numerator 
criteria, and one that excludes patients whose only qualification for 
the numerator is a transfusion.\701\ This is as a recognition that 
transfusions may be necessary for a number of reasons and for less 
severe complications. Second, the MAP Rural Health Advisory Workgroup 
discussed that rural settings have high maternal morbidity and 
mortality and that this measure would help improve maternal health 
outcomes, and that since the measure is risk adjusted for the presence 
of economic/housing instability the measure has a focus on accounting 
for potential disparities. The measure developer added that as an EHR-
based measure, these data are patient-specific and the measure was 
tested in both rural and urban settings.\702\ The Workgroup voted 
majority support in agreement of the applicability of the Severe 
Obstetric Complications eCQM to rural health settings.\703\
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    \699\ Centers for Medicare & Medicaid Services. (2021). List of 
Measures Under Consideration for December 1, 2021. Available at: 
https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96464.
    \700\ National Quality Forum. (2022). Measure Applications 
Partnership Rural Health Advisory Group Virtual Review Meeting. 
Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96571.
    \701\ National Quality Forum. (2022). Measure Applications 
Partnership Rural Health Advisory Group Virtual Review Meeting. 
Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96571.
    \702\ National Quality Forum. (2022). Measure Applications 
Partnership Rural Health Advisory Group Virtual Review Meeting. 
Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96571.
    \703\ National Quality Forum. (2022). Measure Applications 
Partnership Rural Health Advisory Group Virtual Review Meeting. 
Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96571.
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    The Severe Obstetric Complications eCQM (MUC2021-104) was also 
reviewed by the NQF MAP Hospital Workgroup on December 15, 2021, and 
received conditional support pending NQF endorsement.\704\ Some MAP 
stakeholders expressed concerns about the minimum sample size and low 
case volumes as well as the risk adjustment methodology. The measure 
developer underscored for the MAP that this measure was tested in ten 
health systems which represented 28 hospitals and tested over 60,000 
delivery encounters, and there was no concern

[[Page 49229]]

about case volumes.\705\ The measure developer also clarified that 
testing was underway to evaluate the ideal risk adjustment methodology 
to determine approaches that would consider stratification based on 
sociodemographic factors, such as race and ethnicity, pre- and post-
risk adjustment. We emphasized the importance of this measure and its 
role in helping hospitals to understand the disparities existent in 
maternal health outcomes.\706\ Ultimately, MAP Hospital Workgroup 
stakeholders supported this measure and recommended conditional support 
because it would assist in surveillance on maternal morbidity, a 
clinical area that needs further measurement.\707\ The MAP Coordinating 
Committee, which provides direction to the MAP workgroups, reviewed the 
Severe Obstetric Complications eCQM (MUC2021-104) on January 19, 2022, 
and voted to uphold the MAP Hospital Workgroup recommendation for 
conditional support pending NQF endorsement.\708\
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    \704\ National Quality Forum. (2022). Measure Applications 
Partnership 2021-2022 Considerations for Implementing Measures in 
Federal Programs: Clinician, Hospital, and Post-Acute Care Long-Term 
Care: Final Report. Available at: https://www.qualityforum.org/Publications/2022/03/MAP_2021-2022_Considerations_for_Implementing_Measures_Final_Report_-_Clinicians,_Hospitals,_and_PAC-LTC.aspx.
    \705\ National Quality Forum. (2022). Meeting Transcript--
Virtual Review Meeting. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96632.
    \706\ National Quality Forum. (2022). Meeting Transcript--
Virtual Review Meeting. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96632.
    \707\ National Quality Forum. (2022). Measure Applications 
Partnership 2021-2022 Considerations for Implementing Measures in 
Federal Programs: Clinician, Hospital, and Post-Acute Care Long-Term 
Care: Final Report. Available at: https://www.qualityforum.org/Publications/2022/03/MAP_2021-2022_Considerations_for_Implementing_Measures_Final_Report_-_Clinicians,_Hospitals,_and_PAC-LTC.aspx.
    \708\ National Quality Forum. (2022). Measure Applications 
Partnership 2021-2022 Considerations for Implementing Measures in 
Federal Programs: Clinician, Hospital, and Post-Acute Care Long-Term 
Care: Final Report. Available at: https://www.qualityforum.org/Publications/2022/03/MAP_2021-2022_Considerations_for_Implementing_Measures_Final_Report_-_Clinicians,_Hospitals,_and_PAC-LTC.aspx.
---------------------------------------------------------------------------

    In January 2022, the Severe Obstetric Complications eCQM was 
submitted for endorsement by NQF, and is currently under review. We 
note that section 1866(b)(3)(B)(viii)(IX)(aa) of the Act requires that 
any measure specified by the Secretary must have been endorsed by the 
entity with a contract under section 1890(a) of the Act (the NQF is the 
entity that currently holds this contract). Under section 
1886(b)(3)(B)(viii)(IX)(bb) of the Act, in the case of a specified area 
or medical topic determined appropriate by the Secretary for which a 
feasible and practical measure has not been endorsed by the entity with 
a contract under section 1890(a) of the Act, the Secretary may specify 
a measure that is not so endorsed as long as due consideration is given 
to measures that have been endorsed or adopted by a consensus 
organization identified by the Secretary. We reviewed NQF-endorsed 
measures and were unable to identify any other NQF-endorsed measures on 
this topic, and, therefore, we believe the exception in section 
1886(b)(3)(B)(viii)(IX)(bb) of the Act applies.
    To evaluate the validity, feasibility, and reliability of the 
measure, in 2021, the measure developer, conducted pilot testing in a 
total of 10 sites, consisting of 28 hospitals. The measure developer 
conducted alpha testing (formative testing) \709\ and beta testing 
(field testing) \710\ on the measure. Feasibility testing was conducted 
to assess data collection and accessibility, and included nine sites in 
the analysis, which consisted of 27 hospitals and three different EHR 
systems.\711\ Using NQF's eCQM Feasibility Scorecard template,\712\ the 
measure developer calculated results which indicated high feasibility 
of data elements defining the measure specifications (98 percent), 
clinical and documentation workflows compared to measure intent (99 
percent), data element availability (95 percent) and accuracy (98 
percent), and use of data standards (96 percent).
---------------------------------------------------------------------------

    \709\ Centers for Medicare & Medicaid Services. (2018). Alpha 
tests include methods to determine if individual data elements are 
available and if the form in which they exist is consistent with the 
intent of the measure. Measure Testing NMS Newsletter. Available at: 
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/MMS/Downloads/Measure_Testing_MMS_Newsletter_April_2018.pdf.
    \710\ Centers for Medicare & Medicaid Services. (2018). Beta 
tests serve as the primary means to assess scientific acceptability 
and usability of a measure including gathering further information 
about feasibility. Measure Testing NMS Newsletter. Available at: 
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/MMS/Downloads/Measure_Testing_MMS_Newsletter_April_2018.pdf.
    \711\ Centers for Medicare & Medicaid Services. (2018). eCQM 
Feasibility: How Stakeholders Inform Measure Development. Available 
at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/MMS/Downloads/eCQM-Feasibility.pdf.
    \712\ National Quality Forum. (2022). NQF eCQM Feasibility 
Scorecard. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=89036.
---------------------------------------------------------------------------

    Following feasibility testing, one site representing two hospitals 
withdrew from the project, one site representing one hospital was 
unable to submit beta testing data in the timeline requested, and one 
site representing one hospital was added; as a result, the measure 
developer conducted beta testing in eight healthcare test sites and 25 
hospitals, representing three different EHR systems. The measure 
developer pulled data for delivery hospital encounters discharged from 
January 1 to December 31, 2020. During measure testing, the measure 
score reliability was assessed, which is the degree to which repeated 
measurements of the same entity agree with each other.\713\ The measure 
developer estimated the measure score reliability using a signal-to-
noise ratio to assess the values according to conventional standards. 
They assessed signal-to-noise reliability that describes how well the 
measure can distinguish the performance of one hospital from another. 
The signal is the proportion of the variability in measured performance 
that can be explained by real differences in performance. Scores can 
range from zero to one, where a score of zero implies that all the 
variability in a measure is attributable to measurement error, and a 
score of one implies that all the variability is attributable to real 
difference in performance. The reliability analysis yielded a median 
reliability score of 0.991 (range: 0.983-0.997) for any severe 
obstetric complication and 0.957 (range: 0.918-0.984) for severe 
obstetric complications excluding blood transfusion-only cases.
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    \713\ Centers for Medicare & Medicaid Services. (2018). CMS 
Measures Management System (MNS) Testing Scientific Acceptability 
for de novo eCQMS. Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/MMS/Downloads/CMS-MMS-Webinar-BP101-%E2%80%93-Scientific-Acceptability-of-eCQMs.pptx.
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    The measure developer completed validity testing on six sites 
representing 15 hospitals, which was a statistically relevant sample of 
electronically submitted inpatient encounters selected for re-
abstraction for reliability testing and clinical adjudication from six 
of the beta testing sites. Validity testing of the measure refers to 
the correctness of conclusions about the quality of measured entities 
that can be made based on the measure scores (that is a higher score on 
a quality measure reflects higher quality).\714\ Overall, the data 
element agreement rate for all six sites was 90.4 percent. Further, 
validity testing of the measure showed a performance score agreement 
rate of 91.2 percent with a kappa score of .881 indicating good 
agreement. Measure score validity testing revealed a high positive 
predictive value (rate of agreement) of 94.7 percent, and a

[[Page 49230]]

negative predictive value of 100 percent. Likewise, sensitivity 
(responsiveness to change) and specificity (accuracy) across test sites 
for the measure score were high, at 100 percent and 90.5 percent, 
respectively.
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    \714\ National Quality Forum. (2011). Guidance for Measure 
Testing and Evaluating Scientific Acceptability of Measure 
Properties. Available at: https://www.qualityforum.org/
Measuring_Performance/Improving_NQF_Process/
Measure_Testing_Task_Force_Final_Report.aspx#:~:text=Validity%20of%20
the%20measure%20score,quality%20measure%20reflects%20higher%20quality
.
---------------------------------------------------------------------------

    The measure developer conducted testing of the Severe Obstetric 
Complications eCQM and found that across 60,184 delivery encounters at 
8 different sites, the current observed rate of any severe obstetric 
complications was 244 and the mean risk-standardized rate across test 
sites was 247 (per 10,000 delivery hospitalizations). The severe 
obstetric complications rate excluding blood transfusion-only cases was 
50 for both the observed rate and the mean risk-standardized rate 
across test sites (per 10,000 delivery hospitalizations). Through 
rigorous testing, the measure developer found that the measure was 
feasible, reliable, and valid.
    The measure specifications for the Severe Obstetric Complications 
eCQM can be found on the eCQI Resource Center website, available at: 
https://ecqi.healthit.gov/pre-rulemaking-eh-cah-ecqms.
(3) Data Sources
    The eCQM uses data collected through hospitals' EHRs. The measure 
is designed to be calculated by the hospitals' CEHRT using the patient-
level data and then submitted by hospitals to CMS.
(4) Outcome
    The outcome of interest (numerator) for the Severe Obstetric 
Complications eCQM is the number of inpatient hospitalizations for 
patients with severe obstetric complications occurring during the 
delivery hospitalization, not present on admission, which include the 
following: Severe maternal morbidity diagnoses (we refer readers to the 
subsequent table); severe maternal morbidity procedures, including 
blood transfusion, conversion of cardiac rhythm, hysterectomy, 
temporary tracheostomy, and ventilation; or a discharge disposition of 
expired.715 716 Table IX.E-03. summarizes the severe 
maternal morbidity categories along with their corresponding diagnoses:
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    \715\ eCQI Resource Center. (2022). Eligible Hospital/Critical 
Access Hospital Pre-rulemaking eCQMs. Available at: https://ecqi.healthit.gov/pre-rulemaking-eh-cah-ecqms.
    \716\ The Joint Commission. (2021). eCQM Specifications 2022 
Reporting Period. Available at: https://www.jointcommission.org/-/media/tjc/documents/measurement/specification-manuals/2022-reporting-period/january-2022/ecqm_specifications_reportingperiod_2022.zip.
[GRAPHIC] [TIFF OMITTED] TR10AU22.158

    This measure is intended to report two outcomes: (1) Severe 
obstetric complications; and (2) severe obstetric complications, but 
excluding delivery hospitalizations for which blood transfusion was the 
only numerator event.
(5) Cohort
    The measure cohort (denominator) consists of inpatient 
hospitalizations for patients between eight years of age and less than 
65 years of age admitted to the hospital for inpatient acute care who 
undergo a delivery procedure for a stillbirth or livebirth greater than 
or equal to 20 weeks' gestation, with a discharge date that ends during 
the measurement period. Patients with confirmed diagnosis of COVID-19 
with COVID-19-related respiratory condition or patients with confirmed 
diagnosis of COVID-19-related respiratory procedure are excluded from 
the measure calculation.\717\
---------------------------------------------------------------------------

    \717\ eCQI Resource Center. (2022). Eligible Hospital/Critical 
Access Hospital Pre-rulemaking eCQMs. Available at: https://ecqi.healthit.gov/pre-rulemaking-eh-cah-ecqms.
---------------------------------------------------------------------------

(6) Risk Adjustment
    The Severe Obstetric Complications eCQM is a risk-adjusted measure. 
The measure developer identified candidate risk variables for severe 
obstetric complications for consideration in the measure risk 
adjustment model by utilizing literature and research findings, 
consulting with an expert clinical consultant, and by soliciting input 
from a technical expert panel (TEP). Following the identification of 
candidate risk adjustment variables, the measure developer developed 
risk models for the outcomes of severe obstetric complications and 
severe obstetric complications excluding blood transfusion-only 
encounters. The measure developer then utilized the variables included 
in the final risk models for use as the risk adjustment variables when 
calculating the risk

[[Page 49231]]

standardized severe obstetric complication rates for the two versions 
of the measure outcome (with and without transfusion-only encounters).
    Variables included in the measure's risk adjustment are: patient 
age; several preexisting conditions that are present on admission 
defined by ICD-10 codes (listed later in the section); pregnancy 
characteristics; laboratory tests and vital signs upon hospital arrival 
(hematocrit, white blood cell (WBC) count, heart rate, systolic blood 
pressure); long term anticoagulant medication use; and social risk 
measured by the presence of economic/housing instability.
    The following preexisting conditions and pregnancy characteristics, 
defined by ICD-10 codes, are included in the measure's risk adjustment: 
Anemia, asthma, autoimmune disease, bariatric surgery, bleeding 
disorder, Body Mass Index (BMI), cardiac disease, gastrointestinal 
disease, gestational diabetes, Human Immunodeficiency Virus (HIV), 
Hypertension, mental health disorder, multiple pregnancy, neuromuscular 
disease, obstetric venous thromboembolism (VTE), other pre-eclampsia, 
placental accreta spectrum, placental abruption, placenta previa, 
preexisting diabetes, preterm birth, previous cesarean, pulmonary 
hypertension, renal disease, severe pre-eclampsia, substance abuse, and 
thyrotoxicosis.
(7) Measure Calculation
    The measure is an outcome measure that assesses the risk-
standardized proportion of eligible patients with severe obstetric 
complications, and the risk-standardized proportion of eligible 
patients with severe obstetric complications excluding transfusion-only 
hospital delivery encounters, which occur during the inpatient delivery 
hospitalization. The measure calculates the proportion of inpatient 
hospitalizations with severe obstetric complications occurring during 
the delivery hospitalization out of the total number of inpatient 
hospitalizations for patients delivering stillborn or live birth with 
greater than or equal to least 20 weeks and 0 days of gestation 
completed. The measure score will be reported as a rate per 10,000 
deliveries.
(8) Data Submission and Reporting
    We refer readers to: Section IX.E.10.e. of the preamble of this 
final rule for discussion of our previously finalized eCQM reporting 
and submission policies; and section IX.E.13.b. for the public 
reporting of eCQM data. Additionally, we refer readers to section 
IX.E.10.e.(4). where we discuss the use of the zero denominator 
declarations and case threshold exemption policies for hospitals.
    We also refer readers to four related proposals discussed in the 
preamble of this final rule: (1) Section IX.E.10.e. where we discuss 
modifications to our reporting and submission requirements for eCQMs, 
including a discussion of our policy to require hospitals to report on 
the Severe Obstetric Complications eCQM; (2) section IX.E.5.c. for our 
policy to adopt the Cesarean Birth eCQM; (3) section IX.H.10.a.(2). of 
the preamble of this final rule for a discussion of similar policies to 
adopt these two perinatal eCQMs in the Medicare Promoting 
Interoperability Program for Eligible Hospitals and CAHs; and (4) 
section IX.E.8. where we are establishing a publicly-reported hospital 
designation to capture the quality and safety of maternity care and 
other related activities in advancing maternal health equity.
    We invited public comment on this proposal.
    Comment: Many commenters support the proposed adoption of the 
Severe Obstetric Complications eCQM beginning with the CY 2023 
reporting period/FY 2025 payment determination and mandatory reporting 
beginning with the CY 2024 reporting period/FY 2026 payment 
determination and for subsequent years. A few commenters indicated that 
they supported the measure because the measure aligns with existing 
state or Joint Commission reporting practices.
    Response: We thank the commenters for their support and agree that 
the measure is in line with best practices for improving maternal 
morbidity and mortality rates.
    Comment: A few commenters expressed support for the measure but had 
recommendations for how the measure should be implemented. A commenter 
recommended that COVID-19 patients not be excluded. A commenter 
recommended monitoring the measure in the future to determine whether 
modifications would be appropriate.
    Response: We thank commenters for their recommendations. Regarding 
ongoing monitoring of the measure's performance, impact on reporters, 
and alignment with the measure's goals, we will monitor the data for 
any unintended consequences as part of the standard measure 
maintenance. Regarding the COVID-19 exclusions, at this time patients 
with confirmed diagnosis of COVID-19, with COVID-19-related respiratory 
condition or with COVID-19-related respiratory procedure are excluded 
from the measure calculation (87 FR 28514). The measure currently 
excludes COVID-19 patients from the measure cohort due to potential 
concerns of the COVID-19 impact on maternal health. We will continue to 
monitor the impact of COVID-19 on the measure's performance and 
alignment with the measure's goals as part of the standard measure 
maintenance.
    Comment: A few commenters either expressed concern about the impact 
that public reporting may have on low volume hospitals or requested 
clarification on how non-birthing hospitals would be affected by the 
adoption of the measure.
    Response: We thank the commenter for their requested clarification 
on how hospitals without birthing programs would be affected. In the FY 
2023 IPPS/LTCH PPS proposed rule, we stated the Severe Obstetric 
Complications eCQM would be reported by all hospitals participating in 
the Hospital IQR Program except those hospitals that do not have an 
obstetrics department (87 FR 28512). We refer readers to section 
IX.E.10.e.(4). of this final rule where we discuss the Hospital IQR 
Program's zero denominator declarations and case threshold exemption 
policies for eCQMs. Zero denominator declarations allow a hospital 
whose EHR is capable of reporting eCQM data to submit a zero in the 
denominator for the reporting of an eCQM if the hospital does not have 
patients that meet the denominator criteria of that measure. Similarly, 
the case threshold exemptions policy allows for a hospital with five or 
fewer inpatient discharges per quarter or 20 or fewer inpatient 
discharges per year in a given denominator declaration be exempted from 
reporting on that individual eCQM. We refer readers to the FY 2016 
IPPS/LTCH PPS final rule (80 FR 49705 through 49708) and the FY 2017 
IPPS/LTCH PPS final rule (81 FR 57170) for our previously adopted eCQM 
file format requirements. Hospitals can continue to meet the reporting 
requirements by submitting data via QRDA I files, zero denominator 
declaration, or case threshold exemption (82 FR 38387).
    Comment: A commenter requested clarification on the definition and 
appropriate documentation of ``housing instability.''
    Response: Housing instability is included in the risk adjustment 
for this measure due to evidence for its inclusion and availability in 
the EHR.\718\

[[Page 49232]]

While not explained in the proposed ruled, we are clarifying here that 
for purposes of this measure consistent with the measure specifications 
available on the eCQI Resource Center website at: https://ecqi.healthit.gov/, economic housing instability is defined by the 
National Library of Medicine (NLM) value set \719\ 
(2.16.840.1.113762.1.4.1029.292) comprising the following ICD-10 Z 
codes:
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    \718\ Centers for Medicare & Medicaid Services. (2021). Severe 
Obstetric Complications Electronic Clinical Quality Measure (eCQM) 
Methodology Report: Version 1. Available at: https://www.cms.gov/files/document/measure-methodology-report.pdf.
    \719\ https://vsac.nlm.nih.gov/valueset/2.16.840.1.113762.1.4.1029.292/expansion/Latest.
[GRAPHIC] [TIFF OMITTED] TR10AU22.159

    Comment: Several commenters did not support the measure because 
they believed it does not provide a meaningful measure for driving 
improvements in maternal health disparities and would not encourage 
hospitals to take the desired actions to mitigate severe maternal 
morbidity.
    Response: We appreciate the commenters' concerns and respectfully 
disagree that the proposed measure does not provide a meaningful 
measure for driving improvements in maternal health disparities. We 
believe that this measure serves as a key activity in measuring and 
promoting quality improvement in maternity care by incentivizing 
hospitals to track and report severe obstetric complications and to 
publicly report measure data for transparency.
    Comment: A commenter believed the measure may not be feasible.
    Response: The measure developer's testing established the 
feasibility of the measure, first in 25 hospitals across eight 
healthcare sites and then in an additional hospital unaffiliated with 
the first 25, and across several different electronic health record 
systems. Based on the testing performed, we respectfully disagree that 
the measure is not feasible. All numerator indicators and 30 of 34 risk 
factors use easily mapped ICD-10 codes.\720\ The two laboratory and two 
vital sign risk factors were chosen in part because of their 
availability and high rates of extractability from the medical record.
---------------------------------------------------------------------------

    \720\ eCQI Resource Center. (2022). Eligible Hospital/Critical 
Access Hospital Pre-rulemaking eCQMs. Available at: https://ecqi.healthit.gov/pre-rulemaking-eh-cah-ecqms.
---------------------------------------------------------------------------

    Comment: Several commenters either did not support the measure or 
expressed concerns about the proposed eCQM due to perceived resource 
limitations or because they believed the adoption timeline is too 
rapid.
    Response: We acknowledge commenters' concerns and believe that the 
maternal health crisis requires urgent action without delay. In 
addition, we refer readers to section XII.B.4. for information on 
measure burden and note that, as with all Hospital IQR Program 
measures, we will monitor the data and any unintended consequences of 
the measure as part of the standard measure maintenance.
    Comment: Many commenters recommended that the measure be adopted 
only once it is NQF endorsed. A few commenters recommended that the 
measure be risk adjusted or the exclusion criteria broadened. A few 
commenters recommended disaggregated or stratified data reporting. A 
commenter recommended that the measure be finalized with voluntary 
reporting and believed facilities are better positioned to set clinical 
priorities. A commenter recommended making the measure modifiable in 
case new risk factors are identified.
    Response: We acknowledge commenters' recommendations that we seek 
NQF endorsement for the measure. As we stated in the FY 2023 IPPS/LTCH 
PPS proposed rule that the Severe Obstetric Complication eCQM was 
submitted to NQF in January 2022 and is currently under review (87 FR 
28512). As there are currently no NQF-endorsed measures that address 
severe obstetric complications, we believe the exception at section 
1886(b)(3)(B)(viii)(IX)(bb) of the Act applies.
    We further thank commenters for their recommendations on changes to 
the measure specifications. We note that the measure is risk adjusted 
by several variables including patient age, several preexisting 
conditions, pregnancy characteristics, laboratory test results, long 
term anticoagulant medication use, and social risk (87 FR 28514). In 
the FY 2023 IPPS/LTCH PPS proposed rule, we also stated that the 
measure developer is currently conducting testing to determine 
approaches that would consider stratification based on sociodemographic 
factors (87 FR 28512). We also refer readers to section IX.B. 
(Overarching Principles for Measuring Healthcare Quality Disparities 
Across CMS Quality Programs--Request for Information) for additional 
discussion on CMS' potential use of measure stratification in the 
future. We also regularly conduct measure maintenance and evaluate 
whether any modifications to measures are necessary. Any substantive 
changes to measures would be proposed in future notice-and-comment 
rulemaking.
    In regard to voluntary reporting and prioritization, we believe 
that the maternal health crisis is urgent, maternal health inequities 
are unacceptable, and this persistent problem requires prompt action. 
Therefore, we believe allowing hospitals to self-select reporting 
beginning with the CY 2023 reporting period/FY 2025 payment 
determination and require

[[Page 49233]]

reporting beginning with the CY 2024 reporting period/FY 2026 payment 
determination is imperative.
    Comment: A commenter recommended that the measure only report the 
second outcome of the Severe Obstetric Complications eCQM (the outcome 
of severe complications excluding transfusion-only encounters) because 
the commenter believes it would be inappropriate to publicly report the 
outcome of the severe obstetric complications with transfusion as the 
measure does not place a threshold on the number of units of blood 
involved in the transfusion. A commenter expressed concern that there 
may be negative unintended consequences.
    Response: We appreciate commenters' concerns. As proposed, this 
measure is intended to report two outcomes: (1) Severe obstetric 
complications; and (2) severe obstetric complications but excluding 
delivery hospitalizations for which blood transfusion was the only 
numerator event (87 FR 28512, 28514). We believe that reporting on both 
outcomes is necessary to advance the goals of this eCQM. We note that 
we do not anticipate any unintended consequences, but as with all 
Hospital IQR Program measures, we will monitor the data for any 
unintended consequences as part of the standard measure maintenance.
    Comment: A commenter expressed concern about the complexity of 
documenting the procedures and outcomes indicated in this measure and 
suggested that CMS assess whether the procedures reportable in the 
measures are documented in medical records (specifically, ventilation 
and transfusion).
    Response: We thank the commenter for their recommendation. We 
appreciate the commenter's recommendation about evaluating the accuracy 
and applicability of the procedures reported under this measure. We 
note that these procedures are currently defined with ICD-10 procedure 
codes in the measure specifications, which can be found at https://ecqi.healthit.gov/ (87 FR 28513 through 28514). The measure developer 
conducted medical record reviews to test the validity of the procedure 
codes and found high positive predictive value for both ventilation and 
transfusion.
    Comment: A few commenters raised concerns that conditions accounted 
for in the numerator may not be predictable, preventable, or indicators 
of the quality of care provided. A commenter raised concerns that the 
eCQM data requirement is not aligned with current clinical practice 
guides on data collected, meaning that standards of practice will be 
negatively affected. A commenter raised concerns that the non-birthing 
hospitals may score disproportionately high if the measure is adopted 
because they may have zero-denominator measures. A few commenters 
requested clarification on how rates would be reportable if the volume 
of delivery hospitalizations was so low as to make only one rate 
reportable.
    Response: We appreciate the commenters' concerns about measure 
data. As discussed in the FY 2023 IPPS/LTCH PPS proposed rule, the 
measure developer conducted rigorous testing and found the measure to 
be valid, feasible, and reliable (87 FR 28513). With regard to concerns 
about low rates, we note that the measure developer conducted measure 
score reliability testing in both rural and urban settings, and that 
the thresholds for consideration for implementation of public reporting 
were found to be appropriate due to the risk-adjustment for the 
presence of economic/housing instability, the measure has a focus on 
accounting for potential disparities; the measure was tested in ten 
health systems with varying case volumes and no concerns were 
identified for low-volume hospitals (87 FR 28512). Regarding potential 
zero-denominator reporting hospitals, we believe this will not be a 
problem because, as stated previously, in the FY 2023 IPPS/LTCH PPS 
proposed rule that the Severe Obstetric Complications eCQM would be 
reported by all hospitals except those hospitals that do not have an 
obstetrics department and therefore zero-denominator hospitals would be 
exempt (87 FR 28512).
    We refer readers to section IX.E.10.e.(4). of this final rule where 
we discuss the Hospital IQR Program's zero denominator declarations and 
case threshold exemption policies for eCQMs. Zero denominator 
declarations allow a hospital whose EHR is capable of reporting eCQM 
data to submit a zero in the denominator for the reporting of an eCQM 
if the hospital does not have patients that meet the denominator 
criteria of that hybrid measure (82 FR 38387). Similarly, the case 
threshold exemptions policy allows for a hospital with five or fewer 
inpatient discharges per quarter or 20 or fewer inpatient discharges 
per year in a given denominator declaration be exempted from reporting 
on that individual eCQM (82 FR 38387).
    Comment: A commenter requested guidance on extrapolating data from 
clinical notes and patient records.
    Response: We reiterate that this is an eCQM in which the data is 
collected through hospitals' EHR and designed to be calculated by the 
hospital's CEHRT (87 FR 28513). For more information regarding data 
submission, we refer readers to section IX.E.10.a. for discussion of 
our previously finalized eCQM reporting and submission requirements and 
to the measure specifications, which can be found at https://ecqi.healthit.gov.
    After consideration of the public comments we received, we are 
finalizing our proposal as proposed.
e. Hospital-Harm--Opioid-Related Adverse Events eCQM (NQF #3501e) 
Beginning With the CY 2024 Reporting Period/FY 2026 Payment 
Determination and for Subsequent Years
(1) Background
    Opioids are among the most frequently implicated medications in 
adverse drug events among hospitalized patients.\721\ The most serious 
opioid-related adverse events include those involving respiratory 
depression, which can lead to brain damage and death.\722\ \723\ \724\ 
Opioid-related adverse events have both a negative impact on patients 
and financial implications. Patients who experience adverse events due 
to opioid administration have been noted to have 55 percent longer 
lengths of stay, 47 percent higher costs, 36 percent higher risk of 30-
day readmission, and 3.4 times higher payments than patients without 
these adverse events.\725\ While noting that data are limited, The 
Joint Commission suggested that opioid-induced respiratory arrest may 
contribute

[[Page 49234]]

substantially to the 350,000 to 750,000 in-hospital cardiac arrests 
annually.\726\
---------------------------------------------------------------------------

    \721\ Davies EC, Green CF, Taylor S, Williamson PR, Mottram DR, 
et al. (2009) Adverse Drug Reactions in Hospital In-Patients: A 
Prospective Analysis of 3695 Patient-Episodes. PLoS ONE 4(2): e4439. 
doi:10.1371/journal.pone.0004439.
    \722\ Jungquist CR, Quinlan-Colwell A, Vallerand A, et al. 
(2020). American Society for Pain Management Nursing Guidelines on 
Monitoring for Opioid-Induced Advancing Sedation and Respiratory 
Depression: Revisions. Pain Manag Nurs.21(1):7-25. Epub 2019 Jul 31.
    \723\ Ramachandran SK, Haider N, Saran KA, et al. (2011). Life-
threatening critical respiratory events: a retrospective study of 
postoperative patients found unresponsive during analgesic therapy. 
Journal of Clinical Anesthesia. 23(3):207-213.
    \724\ Dahan A, Aarts L, Smith TW. (2010). Incidence, Reversal, 
and Prevention of Opioid-induced Respiratory Depression. 
Anesthesiology. 112(1):226-238.
    \725\ Kessler, E.R., Shah, M., Gruschkkus, S.K., et al. (2013). 
Cost and quality implications of opioid-based postsurgical pain 
control using administrative claims data from a large health system: 
opioid-related adverse events and their impact on clinical and 
economic outcomes. Pharmacotherapy, 33(4): 383-91.
    \726\ Overdyk, F.J. (2009). Postoperative Respiratory Depression 
and Opioids. Initiatives in Safe Patient Care. Available at: https://www.initiatives-patientsafety.org/_files/ugd/ba15f5_d52da446e2f141d7be95d3a99b538a42.pdf.
---------------------------------------------------------------------------

    Most opioid-related adverse events are preventable.\727\ Of the 
opioid-related adverse drug events reported to The Joint Commission's 
Sentinel Event database, 47 percent were due to a wrong medication 
dose, 29 percent due to improper monitoring, and 11 percent due to 
other causes (for example, medication interactions and/or drug 
reactions).\728\ In addition, in a review of cases from a malpractice 
claims database in which there was opioid-induced respiratory 
depression among post-operative surgical patients, 97 percent of these 
adverse events were judged preventable with better monitoring and 
response.\729\
---------------------------------------------------------------------------

    \727\ Lee LA, Caplan RA, Stephens LS, et al. Postoperative 
opioid-induced respiratory depression: a closed claims analysis. 
Anesthesiology. 2015;122(3):659-665.
    \728\ The Joint Commission. (2012.) Safe Use of Opioids in 
Hospitals. The Joint Commission Sentinel Event Alert, 49:1-5. 
Available at: https://www.jointcommission.org/-/media/deprecated-unorganized/imported-assets/tjc/system-folders/topics-library/sea_49_opioids_8_2_12_finalpdf.pdf?db=web&hash=0135F306FCB10D919CF7572ECCC65C84.
    \729\ Lee, L.A., Caplan, R.A., Stephens, L.S., et al. (2015). 
Postoperative opioid-induced respiratory depression: a closed claims 
analysis. Anesthesiology, 122(3): 659-65.
---------------------------------------------------------------------------

    While hospital quality interventions such as proper dosing, 
adequate monitoring, and attention to potential drug interactions that 
can lead to overdose are key to prevention of opioid-related adverse 
events, the use of these practices can vary substantially across 
hospitals.730 731 732 In addition, administration of opioids 
also varies widely by hospital, ranging from 5 percent in the lowest-
use hospital to 72 percent in the highest-use hospital.\733\ Notably, 
hospitals that use opioids most frequently have increased adjusted risk 
of severe opioid-related adverse events.\734\ The measure developer, 
under contract with CMS, developed the Hospital Harm-Opioid-Related 
Adverse Events eCQM to assess the rates of adverse events as well as 
the variation in rates among hospitals.
---------------------------------------------------------------------------

    \730\ Willens JS, Jungquist CR, Cohen A, Polomano R. (2013). 
ASPMN survey--nurses' practice patterns related to monitoring and 
preventing respiratory depression. Pain Management Nursing. 
14(1):60-65.
    \731\ Meisenberg B, Ness J, Rao S, Rhule J, Ley C. (2017). 
Implementation of solutions to reduce opioid-induced oversedation 
and respiratory depression. Am J Health Syst Pharm. 74:162-169.
    \732\ Jungquist CR, Correll DJ, Fleisher LA, et al. (2016). 
Avoiding Adverse Events Secondary to Opioid-Induced Respiratory 
Depression: Implications for Nurse Executives and Patient Safety. 
Journal of Nursing Administration. 46(2):87-94.
    \733\ Herzig, S.J., Rothberg, M.B., Cheung, M., et al. (2014). 
Opioid utilization and opioid-related adverse events in nonsurgical 
patients in US hospitals. Journal of Hospital Medicine, 9(2): 73-81.
    \734\ Ibid.
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(2) Overview of Measure
    The Hospital Harm--Opioid-Related Adverse Events eCQM is an outcome 
measure focusing specifically on opioid-related adverse events during 
an admission to an acute care hospital by assessing the administration 
of naloxone. Naloxone is a lifesaving emergent therapy with clear and 
unambiguous applications in the setting of opioid 
overdose.735 736 737 738 Naloxone administration has also 
been used in a number of studies as an indicator of opioid-related 
adverse events to indicate harm to a patient during inpatient admission 
to a hospital.\739\ \740\ The intent of this measure is for hospitals 
to track and improve their monitoring and response to patients 
administered opioids during hospitalization, and to avoid harm, such as 
respiratory depression, which can lead to brain damage and death. This 
measure focuses specifically on in-hospital opioid-related adverse 
events, rather than opioid overdose events that happen in the community 
and may bring a patient into the ED.
---------------------------------------------------------------------------

    \735\ Surgeon General's Advisory on Naloxone and Opioid 
Overdose. (2018). Available at: https://www.surgeongeneral.gov/priorities/opioid-overdose-prevention/naloxone-advisory.html.
    \736\ Agency for Healthcare Research and Quality (AHRQ). (2017). 
Management of Suspected Opioid Overdose with Naloxone by Emergency 
Medical Services Personnel. Comparative Effectiveness Review No. 
193. Available at: https://effectivehealthcare.ahrq.gov/topics/emt-naloxon/systematic-review.
    \737\ Substance Abuse and Mental Health Services Administration 
(SAMHSA). (2018). Opioid Overdose Prevention Toolkit: Information 
for Prescribers. Available at: https://store.samhsa.gov/product/Opioid-Overdose-Prevention-Toolkit/SMA18-4742.
    \738\ Harm Reduction Coalition. (2020). Guide To Developing and 
Managing Overdose Prevention and Take-Home Naloxone Projects. 
Available at: https://harmreduction.org/issues/overdose-prevention/developing-overdose-prevention-and-naloxone-projects/.
    \739\ Eckstrand, J.A., Habib, A.S., Williamson, A., et al. 
(2009). Computerized surveillance of opioid-related adverse drug 
events in perioperative care: a cross-sectional study. Patient 
Safety Surgery, 3:18.
    \740\ Nwulu, U., Nirantharakumar, K., Odesanya, R., et al. 
(2013). Improvement in the detections of adverse drug events by the 
use of electronic health and prescription records: an evaluation of 
two trigger tools. European Journal of Clinical Pharmacology, 69(2): 
255-59.
---------------------------------------------------------------------------

    The goal of this measure is to incentivize hospitals to closely 
monitor patients who receive opioids during their hospitalization to 
prevent serious adverse events. The measure requires evidence of 
hospital opioid administration prior to the naloxone administration 
during the first 24 hours after hospital arrival to ensure that the 
harm was hospital acquired and not due to an overdose that happened 
outside of the hospital.\741\ This measure does not identify 
preventability of an individual harm instance or whether each instance 
of harm was an error, but rather, it assesses the overall rate of harm 
within a hospital by incorporating a definition of harm that is likely 
to be reduced as a result of hospital best practice.
---------------------------------------------------------------------------

    \741\ #3501e Hospital Harm--Opioid-Related Adverse Events, Apr 
02, 2021. Measure Information Form. https://nqfappservicesstorage.blob.core.windows.net/proddocs/27/Spring/2021/measures/3501e/shared/3501e.zip.
---------------------------------------------------------------------------

    The Hospital Harm--Opioid-Related Adverse Events eCQM was included 
as a measure undergoing field testing in the publicly available ``List 
of Measures Under Consideration for December 1, 2017'' (MUC List).\742\ 
The measure was reviewed by the NQF MAP Hospital Workgroup in December 
2017, and received the recommendation to refine and resubmit with 
completed test results demonstrating reliability and validity prior to 
rulemaking, as referenced in the ``2017-2018 Spreadsheet of Final 
Recommendations to HHS and CMS.'' \743\
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    \742\ National Quality Forum. (2017). List of Measures Under 
Consideration for December 1, 2017. Available at: https://www.qualityforum.org/ProjectMaterials.aspx?projectID=75369.
    \743\ National Quality Forum. 2017-2018 Spreadsheet of Final 
Recommendations to HHS and CMS. Available at: https://www.qualityforum.org/ProjectMaterials.aspx?projectID=75369.
---------------------------------------------------------------------------

    This measure was submitted for endorsement consideration to NQF's 
Patient Safety Standing Committee for the Spring 2019 cycle. NQF 
reviewed the measure on June 21, 2019, but did not proceed with full 
endorsement consideration due to concerns with the performance gap 
criterion. In the FY 2020 IPPS/LTCH PPS proposed rule (84 FR 19477), we 
proposed but did not finalize the adoption of the Hospital-Harm--
Opioid-Related Adverse Events eCQM. Commenters provided measure 
suggestions and refinements, as outlined in the FY 2020 IPPS/LTCH PPS 
final rule (84 FR 42459), and we decided to further assess the measure 
and the suggested considerations with intent to re-propose the measure. 
The main areas of suggestions were to better establish the connection 
between naloxone administration and an opioid-related event and 
consider narrowing the broad denominator that, as specified, may result 
in the calculation of very low rates of adverse events.
    In response to the feedback received, the measure developer refined 
and retested the measure specifications. The measure developer limited 
the

[[Page 49235]]

denominator to encounters where patients received at least one opioid 
during the hospitalization. The measure developer constrained the 
numerator to those patients with an opioid administration that preceded 
the subsequent naloxone administration by no more than a 12-hour time 
window, to ensure that a hospital administered opioid was the cause for 
the naloxone administration. The measure developer also updated the 
value sets to ensure that the most current codes for hospital 
administered opioids and naloxone are used and that the codes harmonize 
across other current eCQMs in our quality reporting programs. Finally, 
the measure was re-tested by the measure developer for feasibility at 
23 hospital test sites using four different EHR vendor systems and for 
the scientific acceptability of the measure's properties including 
reliability and validity at six beta implementation test sites.\744\ 
Participant test sites varied by EHR vendor systems, bed size, 
geographic location, teaching/non-teaching status, and urban/rural 
representation.
---------------------------------------------------------------------------

    \744\ National Quality Forum. #3501e Hospital Harm--Opioid-
Related Adverse Events. Available at: https://www.qualityforum.org/ProjectTemplateDownload.aspx?SubmissionID=3501e.
---------------------------------------------------------------------------

    The Hospital Harm--Opioid-Related Adverse Events eCQM (NQF #3501e) 
was then re-submitted to the NQF for the Spring 2021 review cycle and 
received NQF endorsement on December 7, 2021.\745\ The MAP Rural Health 
Advisory Group also reviewed the MUC List and Hospital Harm--Opioid-
Related Adverse Events eCQM (MUC2021-084) on December 8, 2021 and voted 
majority support in agreement on the applicability of the eCQM to rural 
health settings.\746\ The refined and retested eCQM was also re-
considered by the MAP Hospital Workgroup on December 15, 2021, which 
voted to support the measure for rulemaking.\747\ The MAP Coordinating 
Committee, which provides direction to the MAP workgroups, then 
reviewed the measure on January 19, 2022 \748\ and upheld the MAP 
Hospital Workgroup recommendation to support the measure for 
rulemaking.\749\
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    \745\ National Quality Forum. (2021). Hospital Harm--Opioid 
Related Adverse Events. Available at: https://www.qualityforum.org/QPS/3501e.
    \746\ National Quality Forum. (2022). Measure Applications 
Partnership Rural Health Advisory Group Virtual Review Meeting 
Summary, December 8, 2021. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96571.
    \747\ Measure Applications Partnership Hospital Workgroup Web 
Review Meeting: Meeting Summary. December 15, 2021. Available at: 
https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96629.
    \748\ Measure Applications Partnership Coordinating Committee 
2021-2022 Review Web Meeting: Meeting Summary. January 19, 2022. 
Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96709.
    \749\ Measure Applications Partnership 2021-2022 Considerations 
for Implementing Measures in Federal Programs: Clinician, Hospital, 
and Post-Acute Care Long-Term Care Final Report. March 3, 2022. 
Available at: https://www.qualityforum.org/Publications/2022/03/MAP_2021-2022_Considerations_for_Implementing_Measures_Final_Report_-_Clinicians,_Hospitals,_and_PAC-LTC.aspx.
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    We believe this measure will provide hospitals with reliable and 
timely measurement of their opioid-related adverse event rates, which 
is a high-priority measurement area. We believe implementation of this 
measure can lead to safer patient care by incentivizing hospitals to 
implement or refine clinical workflows that facilitate evidence-based 
use and monitoring when administering opioids. We also believe 
implementation of this measure may result in fewer patients 
experiencing adverse events associated with the administration of 
opioids, such as respiratory depression, which can lead to brain damage 
and death. This measure addresses the quality priority of ``Making Care 
Safer by Reducing Harm Caused in the Delivery of Care'' through the 
Meaningful Measures Area of ``Preventable Healthcare Harm.''\750\
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    \750\ More information on CMS' Meaningful Measures Framework is 
available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/MMF/General-info-Sub-Page.html.
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    For detailed information on the Hospital Harm--Opioid-Related 
Adverse Events eCQM, we refer readers to the measure specifications, 
available at: https://ecqi.healthit.gov/pre-rulemaking-eh-cah-ecqms.
(3) Data Sources
    The eCQM uses data collected through hospitals' EHRs. The measure 
is designed to be calculated by the hospitals' CEHRT using the patient-
level data and then submitted by hospitals to CMS.
    As with all quality measures we develop, testing was performed to 
confirm the feasibility of the measure, data elements, and validity of 
the numerator, using clinical adjudicators who validated the EHR data 
compared with medical chart-abstracted data. Testing demonstrated no 
missing or erroneous data (0 percent) for all six implementation test 
sites. These results suggest that all critical data elements are 
reliably and consistently captured in patient EHRs, and that measure 
implementation is feasible. Testing also showed that the positive 
predictive value (PPV),\751\ which describes the probability that a 
patient with a positive result (numerator case) identified by the EHR 
data was also a positive result verified by review of the patient's 
medical record done by a clinical adjudicator, was high at all hospital 
testing sites (98 percent in one hospital to 100 percent in the five 
other hospitals). Testing was completed using output from the Measure 
Authoring Tool (MAT) in 23 hospitals using four different EHR systems 
for feasibility and six different hospitals for implementation testing 
for reliability and validity.
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    \751\ ``Predictive Value.'' Farlex Partner Medical Dictionary. 
Available at: https://medical-dictionary.thefreedictionary.com/predictive+value.
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(4) Outcome
    This measure assesses the proportion of inpatient hospital 
encounters where patients 18 years of age or older have been 
administered an opioid medication, subsequently suffer the harm of an 
opioid-related adverse event, and are administered an opioid antagonist 
(naloxone) within 12 hours. This measure excludes opioid antagonist 
(naloxone) administration occurring in the operating room setting.
(5) Cohort
    This measure's cohort includes all patients ages 18 years and older 
at the start of the encounter, and for whom at least one opioid 
medication was administered during the encounter. An inpatient 
hospitalization includes time spent in the ED or in observation status 
when the patients are ultimately admitted to inpatient status.
(6) Inclusion and Exclusion Criteria
    This measure excludes opioid antagonist (naloxone) administration 
occurring in the operating room setting. There are no denominator 
exclusions.
(7) Risk Adjustment
    This measure is not risk adjusted for chronic opioid use, as most 
instances of opioid-related adverse events should be preventable for 
all patients regardless of prior exposure to opioids or chronic opioid 
use.
    Generally, patient characteristics, including gender, age, race/
ethnicity, reasons for hospitalization, clinical status when patients 
arrive at the hospital, or comorbidities can influence the risk of harm 
occurring during a hospitalization.\752\ Therefore, if hospitals care 
for patients with different

[[Page 49236]]

degrees of risk, then it may be important to account for such case mix 
to compare hospital performance.\753\ However, opioid-related adverse 
events should be avoidable regardless of patient risk, particularly 
when the opioid was given after patients have arrived at the 
hospital.\754\ During measure development, in evaluating whether this 
measure needed to be risk adjusted, the measure developer considered 
the following in determining whether risk adjustment is warranted for 
this measure: Patients are at risk of the harm regardless of their 
demographic and clinical characteristics; most incidents of harm are 
linkable to care provision under the hospital control, for example, 
harms caused by excessive or inappropriate medication dosing; and there 
is evidence that the risk of harm can be largely reduced by following 
best care practices independent of patient inherent risks. For example, 
patients with multiple risk factors can still avoid the harm event when 
providers adhere to care guidelines.
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    \752\ National Quality Forum. Glossary of Terms. Available at: 
https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=73681.
    \753\ National Quality Forum. Developing and Testing Risk 
Adjustment Models for Social and Functional Status-Related Risk 
Within Healthcare Performance Measurement: Final Technical 
Guidance--Version 4. August 30, 2021. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96087.
    \754\ The Joint Commission. (2012). Safe Use of Opioids in 
Hospitals. The Joint Commission Sentinel Event Alert, 49:1-5. 
Available at: https://www.jointcommission.org/-/media/deprecated-unorganized/imported-assets/tjc/system-folders/topics-library/sea_49_opioids_8_2_12_finalpdf.pdf?db=web&hash=0135F306FCB10D919CF7572ECCC65C84.
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    Opioid-related adverse events should be avoidable regardless of 
patient risk, particularly when the opioid was given after patients 
have arrived at the hospital.\755\ While certain patients may require 
higher doses to achieve pain control or are more sensitive to opioids 
(depending on their age, sex, and weight), the most common cause is 
hospital administration of excessive doses and inadequate 
monitoring.\756\ Because the dosing of opioids and the intensity of 
patient monitoring is entirely under the control of providers in 
hospitals, the risk of an opioid-related adverse event can be reduced 
by following best practices.\757\ \758\ \759\ Therefore, the measure 
developer did not think risk adjustment is warranted for this measure.
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    \755\ Ibid.
    \756\ Dahan A, Aarts L, Smith TW. Incidence, Reversal, and 
Prevention of Opioid-induced Respiratory Depression. Anesthesiology. 
2010;112(1):226-238.
    \757\ Practice Guidelines for the Prevention, Detection, and 
Management of Respiratory Depression Associated with Neuraxial 
Opioid Administration: An Updated Report by the American Society of 
Anesthesiologists Task Force on Neuraxial Opioids and the American 
Society of Regional Anesthesia and Pain Medicine. Anesthesiology. 
2016 Mar;124(3):535-52.
    \758\ Jungquist CR, Quinlan-Colwell A, Vallerand A, et al. 
American Society for Pain Management Nursing Guidelines on 
Monitoring for Opioid-Induced Advancing Sedation and Respiratory 
Depression: Revisions. Pain Manag Nurs. 2020 Feb;21(1):7-25. Epub 
2019 Jul 31.
    \759\ Dahan A, Aarts L, Smith TW. Incidence, Reversal, and 
Prevention of Opioid-induced Respiratory Depression. Anesthesiology. 
2010;112(1):226-238.
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    To provide supportive evidence of the clinical rationale for not 
risk adjusting, the measure developer examined the measure performance 
rate in various subgroups of population. All these analyses 
demonstrated no pattern in measure performance rates across 
subgroups.\760\ During measure development, TEP members gave feedback 
on whether the measure required risk adjustment and agreed with this 
rationale. Subsequently the NQF Scientific Methods Panel (SMP), the 
Patient Safety Standing Committee, and the Consensus Standards Advisory 
Committee (CSAC) also agreed with this approach.761 762 763
---------------------------------------------------------------------------

    \760\ #3501e Hospital Harm--Opioid-Related Adverse Events, Apr 
02, 2021. Measure Information Form. https://nqfappservicesstorage.blob.core.windows.net/proddocs/27/Spring/2021/measures/3501e/shared/3501e.zip.
    \761\ National Quality Forum. Scientific Methods Panel Measure 
Evaluation Web Meeting--Spring 2021 Meeting Summary. Available at: 
https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=95246.
    \762\ National Quality Forum. Patient Safety Spring 2021 Cycle. 
Memo: Consensus Standards Approval Committee (CSAC). November 30, 
2021. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96423.
    \763\ National Quality Forum. Consensus Standards Approval 
Committee (CSAC) Voting Results and Decisions for Spring 2021 
Measures. November 30, 2021. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96528.
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(8) Measure Calculation
    The Hospital Harm--Opioid-Related Adverse Events eCQM is an outcome 
measure that defines the indication of a harm for an opioid-related 
adverse event by assessing administration of an opioid antagonist 
(naloxone). The numerator is the number of inpatient hospitalizations 
where an opioid antagonist (naloxone) was administered outside of the 
operating room and within 12 hours following administration of an 
opioid medication. Only one numerator event is counted per encounter. 
The denominator includes inpatient hospitalizations for patients 18 
years or older during which at least one opioid medication was 
administered. An inpatient hospitalization includes time spent in the 
ED or in observation status when the patients are ultimately admitted 
to inpatient status.
    To calculate the hospital-level measure result, divide the total 
numerator events by the total number of qualifying inpatient encounters 
(denominator). Qualifying inpatient encounters include all patients 18 
years of age or older at the start of the encounter with at least one 
opioid medication administered during the encounter. The measure does 
not include naloxone use in the operating room where it could be part 
of the sedation plan as administered by an anesthesiologist or nurse 
anesthetist. Uses of naloxone for procedures outside of the operating 
room (such as bone marrow biopsy) are counted in the numerator as its 
use will indicate the patient was over sedated.\764\ The measure 
numerator identifies a harm using the administration of naloxone, and 
purposely does not include any medications that combine naloxone with 
other agents.
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    \764\ Nwulu, U., Nirantharakumar, K., Odesanya, R., McDowell, 
S.E., & Coleman, J.J. Improvement in the detection of adverse drug 
events by the use of electronic health and prescription records: an 
evaluation of two trigger tools. Eur J Clin Pharmacol. 2013;69(2), 
255-259.
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(9) Data Submission and Reporting
    We proposed the adoption of the Hospital-Harm--Opioid-Related 
Adverse Events eCQM as part of the Hospital IQR Program for which 
hospitals can self-select beginning with the CY 2024 reporting period/
FY 2026 payment determination and for subsequent years. We refer 
readers to section IX.E.10.e. of the preamble of this final rule for a 
discussion of our previously finalized eCQM reporting and submission 
policies, as well as our proposal to modify these eCQM reporting and 
submission requirements. Additionally, we refer readers to section 
IX.H.10.a.(2). of the preamble of this final rule for a discussion of a 
similar proposal to adopt this measure in the Medicare Promoting 
Interoperability Program for Eligible Hospitals and CAHs.
    We invited public comment on this proposal.
    Comment: Many commenters supported adoption of the Hospital Harm--
Opioid-Related Adverse Events eCQM (NQF #3501e) beginning with the CY 
2024 reporting period/FY 2026 payment determination and for subsequent 
years. Several commenters believed that measure implementation will 
result in fewer adverse events associated with the administration of 
opioids (for example, respiratory depression) and will lead to safer 
patient care and saved lives. A few commenters agreed that the measure

[[Page 49237]]

will incentivize hospitals to implement or refine clinical workflows 
and implement continual monitoring protocols when administering 
opioids. Several commenters recognized and appreciated the refinements 
made to the measure since its earlier proposal in the FY 2020 IPPS/LTCH 
PPS proposed rule (84 FR 19477). A few commenters applauded CMS for 
expanding the choices of available eCQMs for reporting in the Hospital 
IQR Program.
    A few commenters highlighted the potential positive impact measure 
reporting may have on vulnerable populations. A commenter noted that 
opioid use is a serious concern in rural health and appreciated the 
transparency this measure will bring. Another commenter noted this 
measure will help to track and improve quality for older adult patients 
and a commenter stated that the measure will help to address the 
disproportionate overdose deaths occurring among racial and ethnic 
minorities.
    Response: We thank commenters for their support and input on the 
inclusion of the measure. We agree that this measure captures important 
quality information that is critical to patient safety and improving 
patient outcomes.
    Comment: A few commenters did not support the inclusion of the 
measure due to concerns that implementation could lead to unintended 
consequences for care delivery, as the potential for lower performance 
could lead to hesitancy in hospitals' or clinicians' use of naloxone in 
clinically appropriate, rapid-response situations. These commenters 
also noted that implementation could lead to undertreatment of pain 
after surgery. A commenter recommended that a more robust methodology 
be developed for identifying the cause of the event as opioid-related. 
Another commenter suggested we consider ways to distinguish appropriate 
use of naloxone in the measure specifications.
    Response: We thank commenters for their input and feedback on this 
measure. We acknowledge that some stakeholders have expressed concern 
that implementation of the measure could result in deterring or 
delaying clinically appropriate administration of naloxone or under-
prescribing of opioids for pain control when clinically necessary. We 
reiterate that naloxone is a life-saving emergent therapy with clear 
and unambiguous applications in the setting of opioid 
overdose,765 766 767 768 and we outline below the 
methodology deployed to ascertain that numerator cases flagged by the 
measure are true positives.
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    \765\ Surgeon General's Advisory on Naloxone and Opioid 
Overdose. Available at: https://www.surgeongeneral.gov/priorities/opioidoverdose-prevention/naloxone-advisory.html.
    \766\ Agency for Healthcare Research and Quality (AHRQ). (2017). 
Management of Suspected Opioid Overdose with Naloxone by Emergency 
Medical Services Personnel. Comparative Effectiveness Review No. 
193. Available at: https://effectivehealthcare.ahrq.gov/topics/emt-naloxon/systematic-review.
    \767\ Substance Abuse and Mental Health Services Administration 
(SAMHSA). (2018). Opioid Overdose Prevention Toolkit: Information 
for Prescribers. Available at: https://store.samhsa.gov/product/Opioid-Overdose-Prevention-Toolkit/SMA18-4742.
    \768\ Harm Reduction Coalition. (2020). Guide To Developing and 
Managing Overdose Prevention and Take-Home Naloxone Projects. 
Available at: https://harmreduction.org/issues/overdose-prevention/developing-overdose-prevention-and-naloxone-projects/.
---------------------------------------------------------------------------

    During testing at six sites, the measure developer examined whether 
numerator cases identified by the measure were true positives and found 
that in 98 percent of cases naloxone was administered for respiratory 
depression or reduced arousal or for opioid reversal and resulted in 
improvement in the patient's level of consciousness.\769\ To examine if 
the numerator cases identified by the quality reporting engine are true 
positives, clinical abstractors pulled additional information regarding 
the indication for and subsequent reaction to the naloxone 
administration from the nurse notes and physician orders. We also found 
that some, but not all, test sites also used the Pasero Opioid-induced 
Sedation Scale (POSS) \770\ in recording the appropriateness of opioid 
dosage, which is a 5 point scale as follows:
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    \769\ #3501e Hospital Harm--Opioid-Related Adverse Events, Apr 
02, 2021. Testing Attachment. https://nqfappservicesstorage.blob.core.windows.net/proddocs/27/Spring/2021/measures/3501e/shared/3501e.zip.
    \770\ Davis, C., Geik, C., Arthur, K., Fuller, J., Johnston, E., 
Levitt, F., Leung, E., McCart, G., McMichael, D., Painter, J., 
Staublin, T., & Walroth, T. (2017). A Multisite Retrospective Study 
Evaluating the Implementation of the Pasero Opioid-Induced Sedation 
Scale (POSS) and Its Effect on Patient Safety Outcomes. Pain 
management nursing: official journal of the American Society of Pain 
Management Nurses, 18(4), 193-201. https://doi.org/10.1016/j.pmn.2017.03.006.
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     S = Sleep, easy to arouse; acceptable; no action 
necessary; may increase opioid dose if needed.
     1 = Awake and alert: acceptable; no action necessary; may 
increase opioid dose if needed.
     2 = Slightly drowsy, easily aroused; acceptable; no action 
necessary; may increase opioid dose if needed.
     3 = Frequently drowsy, arousable, drifts off to sleep 
during conversation; unacceptable; monitor respiratory status and 
sedation level closely until sedation level is stable at less than 3 
and respiratory status is satisfactory; decrease opioid dose 25 percent 
to 50 percent or notify prescriber or anesthesiologist for orders; 
consider administering a non-sedating, opioid-sparing nonopioid, such 
as acetaminophen or a NSAID, if not contraindicated.
     4 = Somnolent, minimal or no response to verbal and 
physical stimulation; unacceptable; stop opioid; consider administering 
naloxone; notify prescriber or anesthesiologist; monitor respiratory 
status and sedation level closely until sedation level is stable at 
less than 3 and respiratory status is satisfactory.
    The POSS is a valid, reliable tool used to assess sedation when 
administering opioid medications to manage pain. The POSS is endorsed 
by The Joint Commission and the American Society for Pain Management 
Nursing to help prevent adverse opioid-related respiratory events.\771\ 
Of the identified numerator cases where POSS were used, most showed an 
initial POSS of 3 or 4. After the naloxone administration, patients' 
POSS decreased to 1 or 2. We also note that patients showing no 
immediate responses may be due to the inadequate dosage of naloxone, as 
there were some instances identified during the manual abstraction 
where patients became responsive only after the second naloxone. 
Overall, the developer found that the use of naloxone in the absence of 
opioid toxicity was rare.\772\ We are confident that hospitals and 
clinicians will continue to administer naloxone when it is clinically 
necessary and will monitor for evidence of unintended consequences as 
we do for all Hospital IQR Program measures.
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    \771\ Davis, C., Geik, C., Arthur, K., Fuller, J., Johnston, E., 
Levitt, F., Leung, E., McCart, G., McMichael, D., Painter, J., 
Staublin, T., & Walroth, T. (2017). A Multisite Retrospective Study 
Evaluating the Implementation of the Pasero Opioid-Induced Sedation 
Scale (POSS) and Its Effect on Patient Safety Outcomes. Pain 
management nursing: official journal of the American Society of Pain 
Management Nurses, 18(4), 193-201. https://doi.org/10.1016/j.pmn.2017.03.006.
    \772\ #3501e Hospital Harm--Opioid-Related Adverse Events, Apr 
02, 2021. Testing Attachment. https://nqfappservicesstorage.blob.core.windows.net/proddocs/27/Spring/2021/measures/3501e/shared/3501e.zip.
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    Comment: A few commenters raised concerns about implementation 
burden. Two commenters highlighted that there is a substantial cost and 
time burden faced by hospitals when adopting new eCQMs. A commenter 
also reported they are already collecting a similar opioid measure.

[[Page 49238]]

    Response: We thank commenters for their feedback. We highlight that 
this measure is one of the available (not required) eCQMs hospitals may 
self-select for submission beginning with the CY 2024 reporting period. 
The addition of this eCQM further advances CMS' goal of transitioning 
to a fully digital quality measures landscape, promoting 
interoperability that will help decrease burden.
    We also recognize there is an opioid measure in the Hospital IQR 
Program, Safe Use of Opioids--Concurrent Prescribing (NQF #3316e) (84 
FR 42598). While both measures are designed to reduce adverse events or 
harms associated with opioid use, the main focus of each measure is 
different. The Safe Use of Opioids--Concurrent Prescribing eCQM focuses 
on concurrent prescriptions of opioids and benzodiazepines at 
discharge, an area of high-risk prescribing (84 FR 42598). The Hospital 
Harm--Opioid-Related Adverse Events eCQM is designed to reduce adverse 
events associated with the administration of opioids in the hospital 
setting by assessing the administration of naloxone as an indicator of 
harm (87 FR 28516). We believe implementation of the Hospital Harm--
Opioid-Related Adverse Events eCQM can lead to safer patient care by 
incentivizing hospitals to track and improve their monitoring of 
patients who receive opioids during hospitalization.
    Comment: A few commenters offered recommendations to augment the 
measure's exclusions; for example, by excluding patients who receive 
naloxone for indications other than over-sedation (for example, 
pruritis).
    Response: We thank commenters for their input and recommendations 
regarding potential measure exclusions. We note the exclusions as 
presented in the measure specifications in the proposed rule (87 FR 
28516) were evaluated and endorsed by the NQF Scientific Methods Panel 
(SMP),\773\ the Patient Safety Standing Committee,\774\ and the 
Consensus Standards Advisory Committee (CSAC).\775\ This eCQM was also 
evaluated by the MAP Hospital Workgroup and the MAP Coordinating 
Committee,776 777 778 who both supported the measure for 
rulemaking. We aim to be as inclusive as possible in defining a measure 
cohort to ensure the measure will have the most impact on important 
subgroups of patients. We will take these suggestions into 
consideration and are assessing the feasibility of capturing the 
indication(s) for administration of naloxone.
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    \773\ National Quality Forum. Scientific Methods Panel Measure 
Evaluation Web Meeting--Spring 2021 Meeting Summary. Available at: 
https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=95246. 1096.
    \774\ National Quality Forum. Patient Safety Spring 2021 Cycle. 
Memo: Consensus Standards Approval Committee (CSAC). November 30, 
2021. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96423. 1097.
    \775\ National Quality Forum. Consensus Standards Approval 
Committee (CSAC) Voting Results and Decisions for Spring 2021 
Measures. November 30, 2021. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96528.
    \776\ Measure Applications Partnership Hospital Workgroup Web 
Review Meeting: Meeting Summary. December 15, 2021. Available at: 
https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96629.
    \777\ Measure Applications Partnership Coordinating Committee 
2021-2022 Review Web Meeting: Meeting Summary. January 19, 2022. 
Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96709.
    \778\ Measure Applications Partnership 2021-2022 Considerations 
for Implementing Measures in Federal Programs: Clinician, Hospital, 
and Post- Acute Care Long-Term Care Final Report. March 3, 2022. 
Available at: https://www.qualityforum.org/Projects/i-/MAP/MAP_2021-2022_Considerations_for_Implementing_Measures_Final_Report.aspx#onclick=%E2%80%9D_gaq.push.%E2%80%98_trackEvent%E2%80%99,%E2%80%99Download%E2%80%99,%E2%80%99PDF%E2%80%99,this.href;%E2%80%9D.
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    Comment: Two commenters requested clarifications on the measure. A 
commenter requested if CMS has target data for hospitals to compare 
their own results to and whether zero events is an attainable target. 
Another commenter requested more information about which opioids would 
be included in the calculations of ``opioid-related adverse events'' 
and if the measure is based on prescription history within a provider's 
electronic health record.
    Response: We thank commenters for their questions. Regarding the 
commenter's question on benchmarks, we note that the Hospital IQR 
Program does not implement benchmarks or target levels of performance 
for its measures as it is a pay-for-reporting quality program. 
Moreover, the intent of this measure is not to reduce clinically 
appropriate use of naloxone, nor to bring the measure rate to zero, but 
to identify if hospitals have particularly high rates of naloxone use 
as an indicator of high rates of over-administration of opioids in the 
inpatient setting, and thereby incentivize improved clinical practices 
when administering opioids (87 FR 28516).
    Regarding which opioids are included in the calculation of opioid-
related adverse events, the opioid value set includes all formulations 
of opioids that may be administered in an inpatient or outpatient 
setting regardless of intended use (87 FR 28516). It also includes 
combination medications that contain both an opioid and another class 
of medication, as it is possible to overdose on these combination 
medications (87 FR 28516).
    Comment: A few commenters were generally supportive of the measure 
but questioned whether the adoption will be impactful (especially given 
the resources and time needed for hospitals to implement the measure) 
as they noted the overall number of inpatient naloxone rescue events is 
small. A commenter did not support measure adoption noting it focused 
on rare events in the inpatient setting rather than targeting the 
primary drivers of the opioid epidemic. A commenter recommended 
additional testing in a broader range of hospitals and vendor systems 
to further assess variation in performance scores. A few commenters 
requested we collect and analyze several years of data before adding 
this measure to a pay-for-performance program.
    Response: We acknowledge that some stakeholders have expressed 
concern regarding the measure's impact given the small number of 
overall events. However, our overall analysis during testing 
demonstrated the rate of ORAE ranged from 1.1 to 6.1 per 1,000 
qualified inpatient encounters, signaling there is still opportunity 
for improvement. As noted in the proposed rule, we tested feasibility 
at 23 hospital test sites using four different EHR vendor systems and 
for the scientific acceptability of the measure's properties including 
reliability and validity at six beta implementation test sites (87 FR 
28516). Participant test sites varied by EHR vendor systems, bed size, 
geographic location, teaching/non-teaching status, and urban/rural 
representation. This far exceeds NQF measure evaluation criteria for 
testing eCQMs, which requires testing using at least two EHR vendor 
systems (87 FR 28516). We will monitor the performance gap as hospitals 
begin to report this measure. Future potential use of the measure for a 
pay-for-performance program would be through notice-and-comment 
rulemaking.
    Comment: A few commenters supported inclusion of the measure into 
the Hospital IQR Program but requested changes to the reporting 
schedule and requirements. A commenter stated the measure should not 
impact hospital payment until the CY 2025 reporting period/FY 2027 
payment determination, while another commenter suggested mandating 
opioid-related adverse event reporting by all hospitals in the program.
    Response: We thank commenters for their support and input. This 
measure

[[Page 49239]]

was proposed for inclusion as one of the eCQMs hospitals can self-
select for reporting beginning with the CY 2024 reporting period/FY 
2026 payment determination, which we believe allows sufficient time for 
hospitals to prepare and implement the measure. The addition of this 
eCQM further advances CMS' goal of transitioning to a fully digital 
quality measures landscape, and we will take the commenter's suggestion 
to make this eCQM mandatory under consideration for future rulemaking.
    Comment: A few commenters requested we monitor clinical literature 
and hospital administration practices in the coming years to determine 
if the measurement area remains of critical importance.
    Response: We thank the commenters for their feedback. We will 
continue to evaluate and refine the measure through implementation as 
necessary.
    Comment: A commenter suggested considering the potential value of 
risk adjustment for the measure.
    Response: We thank the commenter for their feedback to consider 
risk adjusting this measure. We did not apply risk adjustment in the 
measure, given strong evidence that most instances of severe over-
sedation requiring naloxone for reversal can be avoided by following 
best practices; and given that opioid dosing and patient monitoring are 
under the control of providers in hospitals, such that risk can be 
minimized by following best practices.\779\ \780\
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    \779\ Practice Guidelines for the Prevention, Detection, and 
Management of Respiratory Depression Associated with Neuraxial 
Opioid Administration: An Updated Report by the American Society of 
Anesthesiologists Task Force on Neuraxial Opioids and the American 
Society of Regional Anesthesia and Pain Medicine. Anesthesiology. 
2016 Mar;124(3):535-52.
    \780\ Lee LA, Caplan RA, Stephens LS, et al. Postoperative 
opioid-induced respiratory depression: a closed claims analysis. 
Anesthesiology. 2015;122(3):659-665.
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    We will continue to evaluate and refine the measure through 
implementation as necessary.
    After consideration of the public comments we received, we are 
finalizing our proposal as proposed.
f. Global Malnutrition Composite Score eCQM (NQF #3592e) Beginning With 
the CY 2024 Reporting Period/FY 2026 Payment Determination and for 
Subsequent Years
(1) Background
    From 1960 until the start of the COVID-19 pandemic,\781\ life 
expectancy for the total population in the U.S. increased by almost 10 
years.\782\ While adults are living longer lives, the amount of time 
spent in poor health at the end of life is similarly increasing.\783\ 
Studies found that healthy nutrition is indeed more important for 
healthy aging than generally recognized.\784\ Malnutrition includes 
undernutrition (wasting, stunting, underweight), inadequate vitamins or 
minerals, overweight, and obesity, and can result in diet-related 
noncommunicable diseases.\785\ The developmental, economic, social, and 
medical impacts of the global burden of malnutrition are serious and 
lasting, for individuals and their families, for communities, and for 
countries.\786\ Malnutrition is complex and may be both associated with 
and exacerbated by chronic conditions, age-related cognitive or 
physical changes, medication side effects, and poverty.\787\ Evidence 
shows that healthy eating contributes to prevention and risk reduction 
of many common chronic health conditions prevalent in older adults 
including hypertension, heart disease, heart failure, diabetes, 
obesity, certain cancers, and osteoporosis.\788\ While it is estimated 
that sixty percent of older adults manage two or more chronic health 
conditions, many underuse preventive services, including those related 
to nutrition.\789\ Research indicates that preventive screening and 
interventions may reduce risk of malnutrition in older adults and 
improve quality of life, particularly for individuals with chronic 
conditions.\790\ While disease-related malnutrition is not limited to 
older adults, it is more frequent among those with higher age, and the 
consequences appear to be more severe in older persons due to their 
impaired regenerative capacity, inflammation, and other factors.\791\ 
Malnutrition remains a challenge for older adults in the U.S. as 
approximately 7.7 percent of seniors, or 5.5 million, are food insecure 
annually with reports of reduced quality, variety, or desirability of 
diet while 3.1 percent, or 2.1 million are very low food insecure with 
reports of multiple indications of disrupted eating patterns and 
reduced food intake.792 793 From late September through mid-
October 2021, U.S. Census Bureau data indicates that more than 2.5 
million adults ages 65 and older responded ``sometimes'' or ``often'' 
when questioned about the frequency of not having enough food to eat in 
the past seven days.\794\ As our population continues to age, it is 
expected that 1 in 5 residents will be 65 years or older by the year 
2030 \795\ and malnutrition risk among seniors is likely to 
increase.\796\
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    \781\ Islam N, Jdanov D A, Shkolnikov V M, Khunti K, Kawachi I, 
White M et al. (2021). Effects of covid-19 pandemic on life 
expectancy and premature mortality in 2020: time series analysis in 
37 countries. BMJ 375:e066768 doi:10.1136/bmj-2021-066768.
    \782\ United States Census Bureau. (2020). Living Longer: 
Historical and Projected Life Expectancy in the United States, 1960 
to 2060. Available at: https://www.census.gov/content/dam/Census/library/publications/2020/demo/p25-1145.pdf.
    \783\ Roberts SB, Silver RE, Das SK, Fielding RA, Gilhooly CH, 
Jacques PF, et al. (2021) Healthy Aging-Nutrition Matters: Start 
Early and Screen Often. Adv Nutr. 12(4):1438-1448. doi: 10.1093/
advances/nmab032.
    \784\ Ibid.
    \785\ World Health Organization. (2021). Malnutrition. Available 
at: https://www.who.int/news-room/fact-sheets/detail/malnutrition.
    \786\ World Health Organization. (2021). Malnutrition. Available 
at: https://www.who.int/news-room/fact-sheets/detail/malnutrition.
    \787\ Barker CA, Gout BS, et al. (2011). Hospital malnutrition 
prevalence, identification, and impact on patients and the 
healthcare system. International Journal of Environmental Research 
and Public Health.8:514-527.
    \788\ Wright NC, Looker AC, Saag KG, et al. (2014). The recent 
prevalence of osteoporosis and low bone mass in the United States 
based on bone mineral density at the femoral neck or lumbar spine. J 
Bone Miner Res. 29(11):2520-2526. https://onlinelibrary.wiley.com/doi/10.1002/jbmr.2269/epdf.
    \789\ US Department of Health and Human Services. (2020). Office 
of Disease Prevention and Health Promotion. Older Adults: Overview. 
Healthy People 2020 website. Available at: https://www.healthypeople.gov/2020/topics-objectives/topic/older-adults.
    \790\ Mangels, AR. (2018). Malnutrition in Older Adults. 
American Journal of Nursing. 118(3):34-41. doi: 10.1097/
01.NAJ.0000530915.26091.be.
    \791\ Norman K, Ha[szlig] U, Pirlich M. (2021). Malnutrition in 
Older Adults--Recent Advances and Remaining Challenges. Nutrients. 
13, 2764. Available at: https://doi.org/10.3390/nu13082764.
    \792\ Feeding America. (2019). The State of Senior Hunger in 
America in 2017: An Annual Report. Available at: https://www.feedingamerica.org/sites/default/files/2019-05/state-of-senior-hunger-2017_full-report.pdf.
    \793\ United States Department of Agriculture Economic Research 
Service. (2021). Definitions of Food Security. Available at: https://www.ers.usda.gov/topics/food-nutrition-assistance/food-security-in-the-us/definitions-of-food-security.aspx.
    \794\ United States Census Bureau. (2021). Week 39 Household 
Pulse Survey: September 29--October 11. Available at: https://www.census.gov/data/tables/2021/demo/hhp/hhp39.html.
    \795\ United States Census Bureau. (2018). Older People 
Projected to Outnumber Children for First Time in U.S. History. 
Available at: https://www.census.gov/newsroom/press-releases/2018/cb18-41-population-projections.html.
    \796\ Haines J, LeVan D, Roth-Kauffman MM. (2020). Malnutrition 
in the Elderly: Underrecognized and Increasing in Prevalence. 
Clinical Advisor. Available at: https://www.clinicaladvisor.com/home/topics/geriatrics-information-center/malnutrition-in-the-elderly-underrecognized-and-increasing-in-prevalence/.
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    One factor contributing to the burden of malnutrition is health 
disparity across racial and ethnic groups. Black, Hispanic, and other 
non-White older adult populations have higher hunger

[[Page 49240]]

rates than White populations.\797\ Black Americans and Hispanic 
Americans are nearly 2.5 times and 1.4 times as likely as White 
Americans, respectively, to lack access to a full-service grocery 
store; this contributes to higher rates of food insecurity and can 
increase risk of malnutrition.\798\ Black, Hispanic, and other non-
White Americans are also at higher risk for many chronic diseases, 
emphasizing the importance of addressing nutrition through both 
prevention and management of these condition--especially when they 
cannot access healthy food.\799\
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    \797\ United States Department of the Treasury CDFI Fund 
Capacity Building Initiative. (2012). A Summary of Searching for 
Markets: The Geography of Inequitable Access to Healthy & Affordable 
Food in the United States. Available at: https://www.reinvestment.com/wp-content/uploads/2015/12/Searching_For_Markets-Summary_2011.pdf.
    \798\ Ibid.
    \799\ Dawson MD, Blancato B. (2021). To Advance Health Equity, 
Measure Hospital Malnutrition Care. Health Affairs. Available at: 
https://www.healthaffairs.org/do/10.1377/hblog20210930.667648/full/.
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    Patients over 65 comprise more than one-third of all discharges and 
nearly 13 million seniors are hospitalized each year.\800\ \801\ While 
federal data indicate that approximately 8 percent of all hospitalized 
adults have a diagnosis of malnutrition,802 803 additional 
research finds that malnutrition and malnutrition risk can be found in 
20 to 50 percent of hospitalized adults.804 805 This 
indicates that between 910,000 and 6.5 million hospitalized seniors may 
experience malnutrition.\806\ Hospitalized adults with a diagnosis of 
malnutrition have a longer length of stay, higher costs, more 
comorbidities, five times the likelihood of death, and greater risk of 
infectious disease and injury compared with other adult inpatients 
without malnutrition.807 808 Malnutrition may also 
contribute to post-hospital syndrome--described as ``an acquired, 
transient period of vulnerability'' following hospitalization\809\--
which may dramatically increase the risk of 
readmission.810 811
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    \800\ Gorman A. (2016). Elderly Hospital Patients Arrive Sick, 
Often Leave Disabled. Kaiser Health Network. Available at: https://khn.org/news/elderly-hospital-patients-arrive-sick-often-leave-disabled/.
    \801\ Mattison M. (2021). Hospital Management of Older Adults. 
Available at: https://www.uptodate.com/contents/hospital-management-of-older-adults.
    \802\ United States Agency for Healthcare Research and Quality. 
(2016). Non-maternal and non-neonatal inpatient stays in the United 
States involving malnutrition, 2016. Available at: https://hcup-us.ahrq.gov/reports/ataglance/HCUPMalnutritionHospReport_083018.pdf.
    \803\ Valladares AF, McCauley SM, Khan M, D'Andrea C, Kilgore K, 
Mitchell K. (2021). Development and Evaluation of a Global 
Malnutrition Composite Score. Journal of the Academy of Nutrition 
and Dietetics. doi: https://doi.org/10.1016/j.jand.2021.02.002.
    \804\ Pereira GF., Bulik CM, Weaver MA, Holland WC, Platts-Mills 
TF. (2015). Malnutrition among cognitively intact, noncritically ill 
older adults in the emergency department. Ann Emerg Med. 65: 85-91.
    \805\ Barker CA, Gout BS, et al. (2011). Hospital malnutrition 
prevalence, identification, and impact on patients and the 
healthcare system. International Journal of Environmental Research 
and Public Health. 8:514-527.
    \806\ United States Government Accountability Office. (2019). 
Report to Congressional Requestors. Nutrition Assistance Programs: 
Agencies Could Do More to Help Address the Nutritional Needs of 
Older Adults. Available at: https://www.gao.gov/assets/gao-20-18.pdf.
    \807\ United States Agency for Healthcare Research and Quality. 
(2016). Healthcare Cost and Utilization Project: Non-maternal and 
Non-Neonatal Inpatient Stays in the United States Involving 
Malnutrition 2016. Available at: https://hcup-us.ahrq.gov/reports/ataglance/HCUPMalnutritionHospReport_083018.pdf.
    \808\ United States Agency for Healthcare Research and Quality. 
(2013). Characteristics of Hospital Stays Involving Malnutrition, 
2013. HCUP Statistical Brief #210. Available at: https://www.hcup-us.ahrq.gov/reports/statbriefs/sb210-Malnutrition-Hospital-Stays-2013.jsp.
    \809\ Krumholz, HM. (2013). Post-hospital syndrome--an acquired, 
transient condition of generalized risk. New England Journal of 
Medicine. 368(2):100-2.
    \810\ Sauer, A, Luo M. (2015) Role of Malnutrition in Increasing 
Risk of Hospital Readmissions. Abbott Nutrition Health Institute. 
Available at: https://static.abbottnutrition.com/cms-prod/anhi.org/img/Role-Of-Malnutrition-In-Increasing-Risk-OfHospital-Readmissions-article.pdf.
    \811\ Guenter P, Jensen G, Patel V, Miller S, Mogensen KM, 
Malone A, et al. (2015). Addressing disease-related malnutrition in 
hospitalized patients: a call for a national goal. Joint Commission 
Journal on Quality and Patient Safety.41(10):469-73.
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    Partly due to the substantial impacts on clinical outcomes,\812\ 
malnutrition imposes a serious burden on the healthcare system.\813\ 
Hospitalized patients with poor nutrition have been estimated to incur 
approximately 300 percent higher healthcare costs than those who are 
adequately nourished.\814\ Reports indicate that the average cost for 
an individual hospital stay (including both direct and indirect costs) 
for a malnourished patient is $25,600 while it is only $13,900 for a 
well-nourished patient; \815\ further, malnutrition-associated diseases 
among older adults in the US has been estimated to cost $51.3 billion 
annually.\816\
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    \812\ Norman K., Pichard C., Lochs H., Pirlich M. (2008). 
Prognostic impact of disease-related malnutrition. Clin. Nutr. 27, 
5-15.
    \813\ Khalatbari-Soltani S., Marques-Vida, P. (2015). The 
economic cost of hospital malnutrition in Europe; a narrative 
review. Clin. Nutr. ESPEN. 10, e89-e94.
    \814\ Correia M.I., Waitzberg D.L. (2003). The impact of 
malnutrition on morbidity, mortality, length of hospital stay and 
costs evaluated through a multivariate model analysis. Clin Nutr. 
22(3):235-9.
    \815\ Ibid.
    \816\ Snider J.T., Linthicum M.T., Wu Y., et al. (2014). 
Economic burden of community-based disease-associated malnutrition 
in the United States. JPEN. 38(2 Suppl):77s-85s.
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    Hospitals have an opportunity to identify malnutrition during the 
patient admission process and to address it efficiently and effectively 
with individualized interventions that could optimize outcomes 
including reduced readmissions and lengths of stay.\817\ Research 
demonstrates that there is significant room to improve identification, 
diagnosis, and treatment of malnutrition in hospitalized 
patients.818 819 Nutrition screening is the first step in 
optimal malnutrition care and triggers a nutrition assessment for 
patients found to be at risk.820 821
---------------------------------------------------------------------------

    \817\ Ibid.
    \818\ Kabashneh S., Alkassis S., Shanah L., Ali H.. (2020). A 
Complete Guide to Identify and Manage Malnutrition in Hospitalized 
Patients. Cureus. doi: 10.7759/cureus.8486.
    \819\ Fitall E., Jones Pratt K., McCauley S.M., Astrauskas G., 
Heck T., Hernandez B., et al. (2019). Improving Malnutrition in 
Hospitalized Older Adults: The Development, Optimization, and Use of 
a Supportive Toolkit. Journal of the Academy of Nutrition and 
Dietetics. 119(9):S25-S31 Available at: https://www.sciencedirect.com/science/article/pii/S2212267219305039.
    \820\ Skipper A. (2008). Nutrition care process and model part 
I: the 2008 update. J Am Diet Assoc.108(7):1113-7.
    \821\ Swan W., Vivanti A., Hakel-Smith N.A., Trostler N., Beck 
Howarter N., Papoutsakis C. (2017). Nutrition Care Process and Model 
Update: Toward Realizing People-Centered Care and Outcomes 
Management. Journal of the Academy of Nutrition and Dietetics. 
117(12):2003-2014.
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    We have consistently received stakeholder input requesting the 
addition of nutrition measures to the Hospital IQR Program measure set 
to address malnutrition of hospitalized patients, including comments 
described in the FY 2012 IPPS/LTCH PPS final rule (76 FR 51639), the FY 
2013 IPPS/LTCH PPS final rule (77 FR 53535), the FY 2014 IPPS/LTCH PPS 
final rule (78 FR 50810), the FY 2015 IPPS/LTCH PPS final rule (79 FR 
50056), and the FY 2016 IPPS/LTCH PPS final rule (80 FR 49561). In the 
FY 2018 IPPS/LTCH PPS proposed rule, we solicited public comments on 
potential future inclusion of malnutrition eCQMs in the Hospital IQR 
Program (82 FR 20060 through 20061), and in the FY 2018 IPPS/LTCH PPS 
final rule we provided a summary of these comments (82 FR 38379 through 
38380). Commenters expressed support and stated that Medicare 
beneficiaries would benefit from the adoption of malnutrition eCQMs 
that support prompt malnutrition screening, assessment, diagnosis, and 
development of a care plan (82 FR 38379). In addition, the commenters 
stated that eCQMs specifically designed and tested to be used with 
patient data documented directly in the EHR would likely impose minimal 
data collection

[[Page 49241]]

and reporting burden (82 FR 38379 through 38380). The commenters 
further stated that the inclusion of malnutrition eCQMs in the Hospital 
IQR Program measure set could help improve outcomes and quality of life 
for patients, especially for seniors and the disadvantaged (82 FR 
38380). We believe adopting a malnutrition measure will address several 
priority areas identified in the CMS Equity Plan for Medicare, 
including evaluating impacts of disparities, integrating equity 
solutions across CMS programs, and increasing the ability of the 
healthcare workforce to meet the needs of 822 823
---------------------------------------------------------------------------

    \823\ Centers for Medicare & Medicaid Services. CMS Equity Plan 
for Medicare. Available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/equity-initiatives/equity-plan.
---------------------------------------------------------------------------

    Therefore, in the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28518 
through 28523) rule, we proposed to adopt the Global Malnutrition 
Composite Score eCQM (NQF #3592e) beginning with the CY 2024 reporting 
period/FY 2026 payment determination and for subsequent years. At this 
time, CMS quality reporting programs do not include quality measures 
that specifically address malnutrition. In the CY 2022 Physician Fee 
Schedule (PFS) final rule (86 FR 65970 through 65971), we adopted the 
Implement Food Insecurity and Nutrition Risk Identification and 
Treatment Protocols Improvement Activity (IA) as part of the Merit-
based Incentives Payment System (MIPS), which incentivizes MIPS-
eligible clinicians to create or improve, and then implement, protocols 
for identifying and providing appropriate support to: a) Patients with 
or at risk for food insecurity, and b) patients with or at risk for 
poor nutritional status.\824\ In conjunction with adopting the IA under 
MIPS, we believe adoption of the Global Malnutrition Composite Score 
eCQM in the Hospital IQR Program has the potential to improve care 
delivery in the inpatient setting and is likely to ameliorate food 
insecurity and malnutrition and lead to better health outcomes.
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    \824\ Centers for Medicare & Medicaid Services. Quality Payment 
Program. Improvement Activities Performance Category: Traditional 
MIPS Requirements. Available at: https://qpp.cms.gov/mips/improvement-activities.
---------------------------------------------------------------------------

    Under the CMS Meaningful Measures Framework,\825\ the Global 
Malnutrition Composite Score eCQM addresses the quality priority of 
``Promote Effective Communication & Coordination of Care'' as well as 
``Promote Effective Prevention and Treatment of Chronic Disease.'' 
Under the CMS Meaningful Measures 2.0 Initiative, the Global 
Malnutrition Composite Score eCQM addresses the quality priority of 
``Affordability and Efficiency.'' \826\
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    \825\ Centers for Medicare & Medicaid Services. Meaningful 
Measures Framework. Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/CMS-Quality-Strategy.
    \826\ Centers for Medicare & Medicaid Services. Meaningful 
Measures 2.0: Moving from Measure Reduction to Modernization. 
Available at: https://www.cms.gov/meaningful-measures-20-moving-measure-reduction-modernization. We note that Meaningful Measures 
2.0 is still under development.
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(2) Overview of Measure
    The Global Malnutrition Composite Score eCQM assesses adults 65 
years of age and older admitted to inpatient hospital service who 
received care appropriate to their level of malnutrition risk and 
malnutrition diagnosis, if properly identified. Best practices for 
malnutrition care recommend inpatients be screened for malnutrition 
risk, assessed to confirm findings of malnutrition if found at-risk, 
and have the proper severity of malnutrition indicated in their 
diagnosis along with a corresponding nutrition care plan that addresses 
the respective severity of malnutrition.827 828
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    \827\ Nepple K.G., Tobert C.M., Valladares A.F., Mitchell K., 
Yadrick M. (2019). Enhancing Identification and Management of 
Hospitalized Patients Who Are Malnourished: A Pilot Evaluation of 
Electronic Quality Improvement Measures. Journal of the Academy of 
Nutrition and Dietetics. 119(9):S32-S39.
    \828\ McCauley S.M., Barrocas A., Malone A. (2019). Hospital 
Nutrition Care Betters Patient Clinical Outcomes and Reduces Costs: 
The Malnutrition Quality Improvement Initiative Story. Journal of 
the Academy of Nutrition and Dietetics. 119(9):S11-S14.
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    The malnutrition composite measure includes four component 
measures, which are first scored separately, and then integrated into 
an overall composite score. The overall composite score is derived from 
averaging the individual performance scores of the following four 
component measures:
     Screening for malnutrition risk at admission;
     Completing a nutrition assessment for patients who 
screened for risk of malnutrition;
     Appropriate documentation of malnutrition diagnosis in the 
patient's medical record if indicated by the assessment findings; and
     Development of a nutrition care plan for malnourished 
patients including the recommended treatment plan.
    Together, the four component measures represent the key processes 
of care of malnutrition associated with the risk identification, 
diagnosis, and treatment of malnutrition in older hospitalized adults 
as supported by clinical guidelines and submitted evidence.\829\
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    \829\ Valladares A.F., McCauley S.M., Khan M., D'Andrea C., 
Kilgore K., Mitchell K. (2021). Development and Evaluation of a 
Global Malnutrition Composite Score. Journal of the Academy of 
Nutrition and Dietetics. 122(2):P251-P253.
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    The four component measures were initially submitted for 
endorsement as individual process measures in the NQF 2015-2017 Health 
and Well-Being Project.\830\ The NQF declined to endorse any of the 
individual component measures based on evidence, provider burden 
concern (including timing of malnutrition screening and assessment), 
and the unavailability of necessary data elements to report the 
eCQMs.\831\ The 2015-2017 Health and Well-Being Standing Committee 
recommended combining individual measures or all measures into a 
composite measure to make the measure more meaningful by including both 
the screening and the development of a nutrition care plan into one 
measure.\832\
---------------------------------------------------------------------------

    \830\ National Quality Forum. Health and Well-Being Project 
2015-2017. Available at: https://www.qualityforum.org/ProjectDescription.aspx?projectID=80741.
    \831\ National Quality Forum. Prevention and Population Health, 
Fall 2020 Cycle: CDP Report. Available at: https://www.qualityforum.org/ProjectMaterials.aspx?projectID=86178.
    \832\ National Quality Forum. Health and Well-Being 2015-2017 
Final Report. Available at: https://www.qualityforum.org/Publications/2017/04/Health_and_Well-Being_2015-2017_Final_Report.aspx.
---------------------------------------------------------------------------

    Based on these recommendations, the measure developer conducted 
additional testing. The four component measures were piloted as a 
single composite measure at a large hospital in the Midwest and the 
testing results demonstrated that the measures were usable for 
identifying key improvement areas in malnutrition care related to 
identifying risk, assessing for malnutrition, developing the 
appropriate care plan, and ensuring the diagnosis of malnutrition was 
documented to support follow-up care.\833\ Subsequently, a group of 27 
hospitals adopted and reported on the use of the four component 
measures to guide various projects focused on improving care provided 
to hospitalized patients who were malnourished or at risk of 
malnutrition.\834\ The

[[Page 49242]]

participating hospitals reported changes in measure performance based 
on implementation of cyclical quality improvement initiatives at their 
respective institutions. Multivariate analyses were then conducted to 
identify the relationships between performance on the four component 
measures with patient outcomes of 30-day readmission and length of 
stay. The study results concluded that the four component measures 
could be implemented in a cohort of diverse hospitals and lead to 
meaningful improvements in measure performance as all four components 
of the composite measure were significantly associated with improved 
outcomes for 30-day readmissions.835 836 Prior analyses also 
reported early nutrition interventions were associated with reduced 
patient length of stay.837 838 839 840 841 Following measure 
testing, the measure developer returned to NQF with the composite eCQM 
for consideration in the Fall 2020 measure cycle.
---------------------------------------------------------------------------

    \833\ Nepple K.G., Tobert C.M., Valladares A.F., Mitchell K., 
Yadrick M. (2019). Enhancing identification and management of 
hospitalized patients who are malnourished: a pilot evaluation of 
electronic quality improvement measures. Journal of the Academy of 
Nutrition and Dietetics. 119: S32-S39.
    \834\ Valladares A.F., Kilgore K.M., Partridge J., Sulo S., Kerr 
K.W., McCauley S. (2021). How a malnutrition quality improvement 
initiative furthers malnutrition measurement and care: results from 
a hospital learning collaborative. JPEN J Parenter Enteral Nutr. 45: 
366-371.
    \835\ Ibid.
    \836\ Anghel S., Kerr K.W., Valladares A.F., Kilgore K.M., Sulo 
S. (2021). Identifying patients with malnutrition and improving use 
of nutrition interventions: A quality study in four US hospitals. 
Nutrition. 91-92; 111360.
    \837\ Silver H.J., Pratt K.J., Bruno M., Lynch J., Mitchell K., 
McCauley S.M. (2018). Effectiveness of the malnutrition quality 
improvement initiative on practitioner malnutrition knowledge and 
screening, diagnosis, and timeliness of malnutrition-related care 
provided to older adults admitted to a tertiary care facility: a 
pilot study. Journal of the Academy of Nutrition and Dietetics. 
118(1): 101-109.
    \838\ Meehan A., Loose C., Bell J., Partridge J., Nelson J., 
Goates S. (2017). Health system quality improvement: impact of 
prompt nutrition care on patient outcomes and health care costs. J 
Nurs Care Qual. 2016; 31(3): 217-223.
    \839\ Sriram K., Sulo S., VanDerBosch G., et al. A comprehensive 
nutrition-focused Quality Improvement Program reduces 30-day 
readmissions and length of stay in hospitalized patients. JPEN J 
Parenter Enteral Nutr. 41(3): 384-391.
    \840\ Somanchi M., Tao X., Mullin G.E. (2011). The facilitated 
early enteral and dietary management effectiveness trial in 
hospitalized patients with malnutrition. JPEN J Parenter Enteral 
Nutr. 35(2): 209-216.
    \841\ Deutz N.E., Matheson E.M., Matarese L.E., et al. (2016). 
Readmission and mortality in malnourished, older, hospitalized 
adults treated with a specialized oral nutritional supplement: A 
randomized clinical trial. Clin Nutr. 35(1): 18-26.
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    The Global Malnutrition Composite Score eCQM (MUC20-0032) was 
included in the publicly available ``List of Measures Under 
Consideration for December 21, 2020'' (MUC List).\842\ The measure was 
voted on and approved by the Scientific Methods Panel in October 
2020.\843\ The MAP Rural Health Advisory Group reviewed the measure 
during its January 2021 meeting and agreed that this measure was 
suitable for use with rural providers in the Hospital IQR Program.\844\ 
The MAP subsequently offered conditional support for rulemaking, 
pending NQF endorsement of the measure.\845\
---------------------------------------------------------------------------

    \842\ Centers for Medicare & Medicaid Services. List of Measures 
Under Consideration for December 21, 2020. Available at: https://www.cms.gov/files/document/measures-under-consideration-list-2020-report.pdf.
    \843\ National Quality Forum. MAP 2020-2021 Considerations for 
Implementing Measures in Federal Programs: Clinician, Hospital & 
PAC/LTC. Available at: https://www.qualityforum.org/Publications/2021/03/MAP_2020-2021_Considerations_for_Implementing_Measures_Final_Report_-_Clinicians,_Hospitals,_and_PAC-LTC.aspx.
    \844\ National Quality Forum. Measure Applications Partnership 
Rural Health Workgroup Virtual Review Meeting Summary. January 2021. 
Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=94656.
    \845\ National Quality Forum. MAP 2020-2021 Considerations for 
Implementing Measures Final Report--Clinicians, Hospitals, and PAC-
LTC. March 2021. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=94894.
---------------------------------------------------------------------------

    The composite measure was initially reviewed by the NQF Prevention 
and Population Health (PPH) Standing Committee for endorsement 
suitability during its February 2021 measure evaluation meeting \846\ 
and the full review of the measure was detailed in the NQF Prevention 
and Population Health Fall 2020 Consensus Development Process (CDP) 
Report.\847\ The NQF PPH Standing Committee members agreed malnutrition 
is a significant contributor to infections and pressure ulcers 
requiring treatment, especially for patients transferred to other care 
facilities (such as an inpatient rehabilitation hospital), and held a 
robust discussion with most members supporting the presented evidence 
and topic area importance that assigns accountability to the hospital 
team.\848\ Some PPH Standing Committee members questioned the lack of 
validated and standardized screening and assessment tools specified in 
the first two components. The measure developer along with the measure 
steward stated that objective, validated screening tools \849\ and 
standardized assessment tools \850\ can be implemented to capture 
variables from structured EHR data fields, such as BMI, dietary 
history, recent weight loss, illness severity, laboratory values, and 
age. After further discussion on performance gaps and the ability to 
discern differences within and between populations, many PPH Standing 
Committee members stated they wanted to review additional performance 
data for the eCQM.\851\ The measure developer submitted the requested 
performance data for the PPH NQF Standing Committee to review, discuss, 
and revote at the NQF Standing Committee post-comment meeting on June 
3, 2021.\852\ At that time, the NQF PPH Standing Committee voted on the 
overall suitability for endorsement and the NQF Consensus Standards 
Approval Committee (CSAC) subsequently endorsed the measure (NQF 
#3592e).\853\
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    \846\ National Quality Forum. Measure Evaluation Web Meeting #1: 
Prevention and Population Health. February 2021. Available at: 
https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=94816.
    \847\ National Quality Forum. Prevention and Population Health 
Fall 2020 CDP Report. October 2021. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96457.
    \848\ National Quality Forum. Measure Worksheet--3592--Fall 2020 
Cycle. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=95961.
    \849\ Skipper A., Coltman A., Tomesko J., Piemonte T.A., Handu 
D., Cheng F.W., et al. Position of the Academy of Nutrition and 
Dietetics: Malnutrition (Undernutrition) Screening Tools for All 
Adults. Journal of the Academy of Nutrition and Dietetics. 
120(4):709-713.
    \850\ White J.V., Guenter P., Jensen G., Malone A., Schofield M. 
Consensus Statement of the Academy of Nutrition and Dietetics/
American Society for Parenteral and Enteral Nutrition: 
Characteristics Recommended for the Identification and Documentation 
of Adult Malnutrition (Undernutrition). J Am Diet Assoc;112(5):730-
738.
    \851\ National Quality Forum. Post-Comment Web Meeting (Fall 
2020 Cycle) Comments Received. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=95422.
    \852\ National Quality Forum. Post-Comment Web Meeting (Fall 
2020 Cycle) Memo. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=95421.
    \853\ National Quality Forum. Consensus Standards Approval 
Committee Prevention and Population Health Fall 2020 Review. 
Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=95602.
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    The measure specifications for the Global Malnutrition Composite 
Score eCQM can be found on the eCQI Resource Center website, available 
at: https://ecqi.healthit.gov/pre-rulemaking-eh-cah-ecqms.
(3) Data Sources
    The eCQM uses data collected through hospitals' EHRs. The measure 
is designed to be calculated by the hospitals' CEHRT using the patient-
level data and then submitted by hospitals to CMS.
(4) Measure Calculation
    The Global Malnutrition Composite Score eCQM consists of four 
component measures, which are first scored 
separately.854 855 The overall composite

[[Page 49243]]

score is derived from averaging the individual performance scores of 
the four component measures. The malnutrition component measures are 
all fully specified for use in EHRs. Table IX.E-04. outlines the data 
specification(s) and data sources for each of the four components.
---------------------------------------------------------------------------

    \854\ Valladares A.F., McCauley S.M., Khan M., D'Andrea C., 
Kilgore K., Mitchell K. (2021). Development and Evaluation of a 
Global Malnutrition Composite Score. Journal of the Academy of 
Nutrition and Dietetics. Available at: https://www.jandonline.org/article/S2212-2672(21)00075-7/fulltext.
    \855\ National Quality Forum. #3592e Global Malnutrition 
Composite Score. Available at: https://www.qualityforum.org/ProjectTemplateDownload.aspx?SubmissionID=3592e.
[GRAPHIC] [TIFF OMITTED] TR10AU22.160

(5) Measure Numerator
    The Global Malnutrition Composite Score eCQM numerator is comprised 
of the four component measures, that are individually scored for 
patients 65 years of age and older who are admitted to an acute 
inpatient hospital. Details on the numerator for each component are 
specified in Table IX.E-05.
[GRAPHIC] [TIFF OMITTED] TR10AU22.161

(6) Measure Denominator
    The measure denominator is the composite, or total, of the four 
component measures for patients aged 65 years and older who are 
admitted to an acute inpatient hospital. Details on the denominator 
(and any exclusions) for each component are specified in Table IX.E-06.

[[Page 49244]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.162

    Each measure component is a proportion with a possible performance 
score of 0 to 100 percent. After each component score is calculated 
individually, an unweighted average of all four scores is completed to 
determine the final composite score with a total score ranging from 0 
to 100 percent.\856\
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    \856\ Valladares A.F., McCauley S.M., Khan M., D'Andrea C., 
Kilgore K., and Mitchell K. (2021). Development and Evaluation of a 
Global Malnutrition Composite Score. Journal of the Academy of 
Nutrition and Dietetics. 122(2): p251-253.
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(7) Data Submission and Reporting
    We are proposed the adoption of the Global Malnutrition Composite 
Score eCQM as part of the Hospital IQR Program measure set for which 
hospitals can self-select beginning with the CY 2024 reporting period/
FY 2026 payment determination and for subsequent years. We refer 
readers to section IX.E.10.e. of this final rule for our previously 
finalized eCQM reporting and submission requirements, as well as 
proposed modifications for these requirements. We also refer readers to 
section IX.H.10.a.(2). of the preamble of this final rule for 
discussion of a similar proposal to adopt this measure in the Medicare 
Promoting Interoperability Program for Eligible Hospitals and CAHs.
    We invited public comment on this proposal.
    Comment: Many commenters supported our proposal to adopt the Global 
Malnutrition Composite Score eCQM beginning with the CY 2024 reporting 
period/FY 2026 payment determination and for subsequent years. Many 
commenters supported our proposal to adopt this measure, expressing 
their beliefs that the measure will provide valuable information and 
insights to providers, patients, families, communities, as well as 
policymakers. Many commenters supported this measure because of its 
positive implications for healthcare, including improving care 
coordination and the quality of life after hospitalization, providing 
timely interventions and connections to community resources, and 
reducing issues like costly outcomes, readmissions, lengths of stay, 
complications, and mortality. Many commenters appreciated that this 
measure may help close the gap between identification of and 
intervention for malnutrition. Several commenters indicated 
appreciation that this measure may help raise awareness and support for 
screening for malnutrition by clinicians, helping to ensure that 
hospitals are consistently screening patients. Many commenters 
supported our proposal because they believe that malnutrition is a 
significant issue for aging populations and is tied to health outcomes. 
Several commenters appreciated that this measure is a step toward 
improving and standardizing care for malnutritioned older adults. 
Several commenters appreciated our proposal, noting that it will fill a 
measurement gap because malnutrition is otherwise unaddressed by our 
other quality reporting and value-based purchasing programs. A few 
commenters suggested that we should focus on whether patients received 
appropriate nutrition while in the hospital, or whether their 
nutritional needs were met after discharge. A commenter noted that 
operationalizing this measure may be more challenging for rural 
hospitals without full-time dietician support. A commenter suggested we 
consider trying to assess upstream flagging measures for nutrition 
prior to hospitalization.
    Response: We thank the commenters for their support of our proposal 
to adopt the Global Malnutrition Composite Score eCQM. The 
developmental, economic, social, and medical impacts of the global 
burden of malnutrition are serious and lasting, for individuals and 
their families, for communities, and for countries (87 FR 28518). We 
agree that this measure may provide valuable information and may help 
us begin to address the serious burden that malnutrition imposes on the 
healthcare system. We agree that disease-related malnutrition, while 
not limited to older adults, is more frequent among those with higher 
age, and the consequences appear to be more severe in older persons (87 
FR 28518). This measure will capture important information that may be 
critical to improving care for aging people with malnutrition. Further, 
we believe that adoption of the Global Malnutrition Composite Score 
eCQM has the potential to improve care delivery in the inpatient 
setting and is likely to ameliorate food insecurity and malnutrition 
and lead to better health outcomes by delivering necessary attention 
and resources to hospitalized individuals with nutrition needs that can 
improve their quality of care. With regard to dietician support, while 
we acknowledge that hospitals have different staffing levels, we 
believe that nutrition screening is an important aspect of a patient's 
holistic health and it is the responsibility of all clinicians to 
support appropriate nutrition, particularly in inpatient settings where 
hospitalized individuals can receive

[[Page 49245]]

resources, education, and appropriate nutrition to address their needs.
    Comment: Many commenters supported our proposal because it aligns 
with our health equity priorities for reducing disparities in 
healthcare. Many commenters supported our proposal because they believe 
that malnutrition disproportionately affects vulnerable populations and 
anticipate this measure may be important to advancing health equity. 
Several commenters appreciated that the measure will help provide a 
safety net for vulnerable patients and historically underserved 
populations. A few commenters noted that malnutrition 
disproportionately impacts rural residents and emphasized that this 
measure may be particularly helpful for rural communities.
    Response: We thank the commenters for their support. We agree that 
adopting a malnutrition measure may help address several priority areas 
identified in the CMS Framework for Health Equity,\857\ including 
evaluating impacts of disparities, integrating equity solutions across 
CMS programs, and increasing the ability of the healthcare workforce to 
meet the needs of underserved populations (87 FR 28520). We also note 
that addressing nutrition disparities is a priority for the Biden-
Harris administration, which has set a goal of ending hunger and 
increasing healthy eating so fewer Americans experience diet-related 
diseases.\858\ We agree that health disparities are one factor that 
contributes to the burden of malnutrition across racial and ethnic 
groups and inpatient hospitals have an opportunity to identify 
malnutrition and optimize outcomes for patients including reduced 
readmissions, which are significantly higher for Black and Hispanic 
Americans as well as American Indian and Alaskan 
Natives.859 860 This measure may help underscore the 
importance of addressing nutrition for the health of vulnerable 
patients in historically underserved populations (87 FR 28519). We also 
note that the MAP Rural Health Advisory Group reviewed this measure and 
determined it would be suitable for use with rural providers in the 
Hospital IQR Program (87 FR 28521).
---------------------------------------------------------------------------

    \857\ Centers for Medicare & Medicaid Services. CMS Framework 
for Health Equity. Available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/equity-initiatives/framework-for-health-equity.
    \858\ The White House. White House Announces Conference on 
Hunger, Nutrition, and Health in September. May 4, 2022. Available 
at: https://www.whitehouse.gov/briefing-room/statements-releases/2022/05/04/white-house-announces-conference-on-hunger-nutrition-and-health-in-september/.
    \859\ Rodriguez-Gutierrez R., Herrin J., Lipska K.J. Racial and 
Ethnic Differences in 30-Day Hospital Readmissions Among US Adults 
With Diabetes. (2019). JAMA Network Open. 2019;2(10):e1913249. 
Available at: https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2752820.
    \860\ Centers for Medicare & Medicaid Services Office of 
Minority Health. Medicare Hospital Readmissions Among Minority 
Populations. (2015). Available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/OMH_Dwnld-MedicareHospitalReadmissionsAmongMinorityPopulations.pdf.
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    Comment: A commenter requested that we provide a direction score to 
help hospitals better understand their performance.
    Response: We appreciate the commenter's suggestion and will 
consider it as part of our educational materials and outreach during 
implementation of this measure. We note that the Hospital IQR Program 
does not implement benchmarks or target levels of performance for its 
measures as it is a pay-for-reporting program. However, a higher score 
on the Global Malnutrition Composite Score eCQM represents better 
quality of care.
    Comment: A commenter recommended that we refine the exclusion 
criteria to give more time for sufficient nutrition assessments.
    Response: We thank the commenter for their feedback. We note that 
the NQF assessed and endorsed this measure with the current exclusion 
criteria.\861\ We will continue to evaluate the appropriateness of 
refinements to the exclusion criteria upon implementation of the 
measure.
---------------------------------------------------------------------------

    \861\ National Quality Forum. Consensus Standards Approval 
Committee Prevention and Population Health Fall 2020 Review. 
Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=95602.
---------------------------------------------------------------------------

    Comment: A commenter expressed concern that the measure could be 
overly subjective and noted that providers do not control patient 
choices regarding the management of their own health.
    Response: We acknowledge the commenter's concern that providers do 
not control patient choices; however, we respectfully disagree that the 
measure is overly subjective. The four component measures that make up 
this composite eCQM represent the key processes of care of malnutrition 
associated with the risk and identification, diagnosis, and treatment 
of malnutrition in older hospitalized adults as supported by clinical 
guidelines and submitted evidence (87 FR 28520). Measure testing across 
a group of 27 hospitals found that the four component measures could be 
implemented in a cohort of diverse hospitals and lead to meaningful 
improvements in measure performance as all four components of the 
composite measure were significantly associated with improved outcomes 
for 30-day readmissions (87 FR 28521). Based on the measure testing and 
ultimate NQF endorsement of this measure, we believe that adoption of 
the Global Malnutrition Composite Score eCQM has the potential to 
improve the quality of care delivery in the inpatient setting and is 
likely to ameliorate food insecurity and malnutrition and lead to 
better health outcomes, particularly in inpatient settings where 
hospitalized individuals can receive resources, education, and 
appropriate nutrition to address their needs.
    Comment: A few commenters expressed concern that this measure may 
be duplicative of the food insecurity attestation proposed in the 
Screening for Social Drivers of Health measure. A commenter did not 
support our proposal to adopt this measure for that same concern.
    Response: We acknowledge the commenters' concern, however we 
believe that the measures, while related, are not duplicative. The 
Screening for Social Drivers of Health measure, discussed in section 
IX.E.5.b.(1). of the preamble of this final rule, and the Global 
Malnutrition Composite Score eCQM both speak to nutrition as a driver 
of health because it is an important contributor to a healthful 
population. However, the measures address different but related goals. 
The Screening for Social Drivers of Health measure focuses on 
incentivizing the screening and identifying of patients for food 
insecurity, defined as limited or uncertain access to adequate quality 
and quantity of food (87 FR 28500), while the Global Malnutrition 
Composite Score eCQM focuses not only on screening for malnutrition 
risk (of which food insecurity may be a contributing factor), but also 
the performance of a nutrition assessment and development of a care 
plan for identified malnourished patients (87 FR 28520). We believe 
these two measures are equally important and complementary, but not 
duplicative as they measure different aspects of quality care 
processes.
    Comment: Several commenters addressed requiring reporting of this 
measure. A few commenters suggested we require reporting on this eCQM. 
A few commenters specifically supported the measure as a measure that 
hospitals can choose to self-select. A few commenters expressed their 
belief that this measure may not be relatively important for the 
Hospital IQR Program and recommended that we not require reporting of 
it in the future. A commenter suggested that we not

[[Page 49246]]

require reporting of this measure until after several years' worth of 
the measure data have been validated.
    Response: We appreciate the commenters' feedback on our proposal to 
adopt, but not yet require, reporting on this eCQM. We believe that our 
proposal is balanced so as to provide hospitals with the option of 
reporting on this new eCQM. The addition of this eCQM further advances 
CMS' goal of transitioning to a fully digital quality measures 
landscape, and we will take the commenters' suggestion to make this 
eCQM mandatory under consideration as we begin to collect data. We note 
that any proposal to require reporting this eCQM would be made through 
future notice-and-comment rulemaking.
    Comment: Several commenters expressed concern about implementing 
and operationalizing this measure given the detailed and complex nature 
of the measure specification and because of competing EHR-related 
proposals and reporting requirements. They believe that implementation 
would require updates to EHRs and workflows. A commenter requested 
additional implementation guidance to support standardized 
implementation across hospitals.
    Response: We appreciate the commenters' concerns about 
implementation of the measure and note that the measure uses data 
collected through hospital's EHRs and is designed to be calculated by 
the hospital's CEHRT, thereby reducing reporting burden and complexity. 
Regarding resource commitments and the proposed adoption schedule, we 
believe that the design of the measure is balanced to provide hospitals 
sufficient information for driving healthful outcomes by quickly 
identifying and addressing patients' nutrition needs and additional 
resource allocations to support reporting for this eCQM, particularly 
in the hospital inpatient older adult population of which up to 6.5 
million patients experience malnutrition (87 FR 28519). We also remind 
hospitals that they may self-select to report on this eCQM; it is not a 
required eCQM for the CY 2024 reporting period/FY 2026 performance 
period. As we noted in the FY 2023 IPPS/LTCH PPS proposed rule, the 
measure developer conducted testing on this measure across a group of 
27 hospitals and concluded that the four component measures could be 
implemented in a cohort of diverse hospitals and lead to meaningful 
improvements in measure performance (87 FR 28521). For implementation 
guidance, we refer readers to the measure specifications, 
implementation guide, and other resources, which can be found on the 
eCQI Resource Center website, available at: https://ecqi.healthit.gov.
    After consideration of the public comments we received, we are 
finalizing our proposal as proposed.
g. Hospital-Level, Risk Standardized Patient-Reported Outcomes 
Following Elective Primary Total Hip Arthroplasty (THA) and/or Total 
Knee Arthroplasty (TKA) (NQF #3559), Beginning With Two Voluntary 
Reporting Periods in CYs 2025 and 2026, Followed by Mandatory Reporting 
for Eligible Elective Procedures Occurring July 1, 2025 Through June 
30, 2026, Impacting the FY 2028 Payment Determination and for 
Subsequent Years
(1) Background
    Approximately six million adults aged 65 or older suffer from 
osteoarthritis in the U.S.\862\ Osteoarthritis accounts for more than 
half of all arthritis-related hospitalizations,\863\ and in 2013 there 
were approximately 1,023,000 hospitalizations for osteoarthritis.\864\ 
Hip and knee osteoarthritis is one of the leading causes of disability 
among non-institutionalized adults,\865\ and roughly 80 percent of 
patients with osteoarthritis have some limitation in mobility.\866\ 
Elective total hip arthroplasty (THA) and total knee arthroplasty (TKA) 
are most commonly performed for degenerative joint disease or 
osteoarthritis, which affects more than 30 million Americans.\867\ THA 
and TKA offer significant improvement in quality of life by decreasing 
pain and improving function in a majority of patients, without 
resulting in a high risk of complications or 
death.868 869 870 871 However, not all patients experience 
benefit from these procedures.\872\ Many patients note that their pre-
operative expectations for functional improvement have not been 
met.873 874 875 876 In addition, clinical practice variation 
has been well documented in the U.S.,877 878 879 readmission 
and complication rates vary across hospitals,880 881 and 
international

[[Page 49247]]

experience documents wide hospital-level variation in patient-reported 
outcome measure results following THA and TKA.\882\
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    \862\ Arthritis Foundation. Arthritis By the Numbers Book of 
Trusted Facts and Figures. 2018: https://www.arthritis.org/getmedia/e1256607-fa87-4593-aa8a-8db4f291072a/2019-abtn-final-march-2019.pdf. 
Accessed March 8, 2019.
    \863\ Levit K., Stranges E., Ryan K., Elixhauser A. HCUP Facts 
and Figures, 2006: Statistics on Hospital-based Care in the United 
States. 2008. Available at: https://www.hcup-us.ahrq.gov/reports.jsp.
    \864\ Torio C.M., B.J., National inpatient hospital costs: the 
most expensive conditions by payer, 2013. HCUP statistical brief 
#204. Healthcare Cost and Utilization Project (HCUP) Statistical 
Briefs. Rockville, MD, Agency for Healthcare Research and Quality. 
https://www.hcup-us.ahrq.gov/reports/statbriefs/sb204-Most-Expensive-Hospital-Conditions.pdf. Accessed February 2021.
    \865\ Guccione A.A., Felson D.T., Anderson J.J., et al. The 
effects of specific medical conditions on the functional limitations 
of elders in the Framingham Study. American journal of public 
health. 1994;84(3):351-358.
    \866\ Michaud C.M., McKenna M.T., Begg S., et al. The burden of 
disease and injury in the United States 1996. Population health 
metrics. 2006;4:11. doi: 10.1186/1478-7954-4-11.
    \867\ Centers for Disease Control and Prevention (CDC). 
Osteoarthritis (OA). Accessed March 8, 2019. Available at: https://www.cdc.gov/arthritis/basics/osteoarthritis.htm.
    \868\ Rissanen P., Aro S., Slatis P., Sintonen H., Paavolainen 
P. Health and quality of life before and after hip or knee 
arthroplasty. The Journal of arthroplasty. 1995;10(2):169-175.
    \869\ Wiklund I., Romanus B. A comparison of quality of life 
before and after arthroplasty in patients who had arthrosis of the 
hip joint. The Journal of bone and joint surgery. American volume. 
1991;73(5):765-769.
    \870\ Laupacis A., Bourne R., Rorabeck C., et al. The effect of 
elective total hip replacement on health-related quality of life. 
The Journal of bone and joint surgery. American volume. 
1993;75(11):1619-1626.
    \871\ Ritter M.A., Albohm M.J., Keating E.M., Faris P.M., Meding 
J.B. Comparative outcomes of total joint arthroplasty. The Journal 
of arthroplasty. 1995;10(6):737-741.
    \872\ National Joint Registry. National Joint Registry for 
England and Wales 9th Annual Report 2012. Available at: https://www.hqip.org.uk/wp-content/uploads/2018/02/national-joint-registry-9th-annual-report-2012.pdf.
    \873\ Suda A.J., Seeger J.B., Bitsch R.G., Krueger M., Clarius 
M. Are patients' expectations of hip and knee arthroplasty 
fulfilled? A prospective study of 130 patients. Orthopedics. 
2010;33(2):76-80.
    \874\ Ghomrawi H.M., Franco Ferrando N., Mandl L.A., Do H., Noor 
N., Gonzalez Della Valle A. How Often are Patient and Surgeon 
Recovery Expectations for Total Joint Arthroplasty Aligned? Results 
of a Pilot Study. HSS journal: The musculoskeletal journal of 
Hospital for Special Surgery. 2011;7(3):229-234.
    \875\ Harris I.A., Harris A.M., Naylor J.M., Adie S., Mittal R., 
Dao A.T. Discordance between patient and surgeon satisfaction after 
total joint arthroplasty. The Journal of arthroplasty. 
2013;28(5):722-727.
    \876\ Jourdan C., Poiraudeau S., Descamps S., et al. Comparison 
of patient and surgeon expectations of total hip arthroplasty. PloS 
one. 2012;7(1):e30195.
    \877\ Roos E.M. Effectiveness and practice variation of 
rehabilitation after joint replacement. Current opinion in 
rheumatology. 2003;15(2):160-162.
    \878\ Anderson F.A, Jr., Huang W., Friedman R.J., Kwong L.M., 
Lieberman J.R., Pellegrini V.D., Jr. Prevention of venous 
thromboembolism after hip or knee arthroplasty: findings from a 2008 
survey of US orthopedic surgeons. The Journal of arthroplasty. 
2012;27(5):659-666 e655.
    \879\ American Academy of Orthopaedic Surgeons (AAOS). 
Preventing Venous Thromboembolic Disease in Patients Undergoing 
Elective Hip and Knee Arthroplasty: Evidence-Based Guideline and 
Evidence Report. 2011.
    \880\ Suter L.G., Grady J.N., Lin Z., et al. 2013 Measure 
Updates and Specifications: Elective Primary Total Hip Arthroplasty 
(THA) And/OR Total Knee Arthroplasty (TKA) All-Cause Unplanned 30-
Day Risk-Standardized Readmission Measure (Version 2.0). March 2013.
    \881\ Suter L.G., Parzynski C.S., Grady J.N., et al. 2013 
Measures Update and Specifications: Elective Primary Total Hip 
Arthroplasty (THA) AND/OR Total Knee Arthroplasty (TKA) Risk-
Standardized Complication Measure (Version 2.0). March 2013; 
Available at: https://qualitynet.org/.
    \882\ Rolfson O. Patient-reported Outcome Measures and Health-
economic Aspects of Total Hip Arthroplasty: A study of the Swedish 
Hip Arthroplasty Register. (2010). https://gupea.ub.gu.se/bitstream/handle/2077/23722/gupea_2077_23722_1.pdf?sequence=1. Accessed July 
20, 2013.
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    For example, data from the United Kingdom demonstrate that there is 
a greater than 15 percent difference across hospitals in the proportion 
of patients showing improvement after surgery.883 884
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    \883\ National Health System: The Information Centre for Health 
and Social Care. HESonline Hospital Episode Statistics: Proms Data. 
https://www.hesonline.nhs.uk/Ease/ 
ContentServer?siteID=1937&categoryID=1295, 2012.
    \884\ Neuburger J., Hutchings A., van der Meulen J., Black N. 
Using patient-reported outcomes (PROs) to compare the providers of 
surgery: Does the choice of measure matter? Medical care. 
2013;51(6):517-523.
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    Peri-operative care and care coordination across provider groups 
and specialties have important effects on clinical 
outcomes.885 886 The goal of a hospital-level outcome 
measure is to capture the full spectrum of care to incentivize 
collaboration and shared responsibility for improving patients' health 
and reducing the burden of their disease. THA and TKA procedures 
provide a suitable environment for optimizing care, as there are many 
studies indicating how hospitals and providers can improve outcomes of 
their patients by addressing aspects of pre-, peri-, and post-operative 
care.887 888 889 890 891 892
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    \885\ Feng J., Novikov D., Anoushiravani A., Schwarzkopf R. 
Total knee arthroplasty: improving outcomes with a multidisciplinary 
approach. J Multidiscip Healthc. 2018;11:63-73.
    \886\ Saufl N., Owens A., Kelly I., Merrill B., Freyaldenhouen 
L. A multidisciplinary approach to total joint replacement. Journal 
of Perianesthesia Nursing. 2007;22(3):195.
    \887\ Monticone M., Ferrante S., Rocca B., et al. Home-based 
functional exercises aimed at managing kinesiophobia contribute to 
improving disability and quality of life of patients undergoing 
total knee arthroplasty: a randomized controlled trial. Archives of 
physical medicine and rehabilitation. 2013;94(2):231-239.
    \888\ Brown K., Topp R., Brosky J.A., Lajoie A.S. 
Prehabilitation and quality of life three months after total knee 
arthroplasty: A pilot study. Perceptual and motor skills. 
2012;115(3):765-774.
    \889\ Choong P.F., Dowsey M.M., Stoney J.D. Does accurate 
anatomical alignment result in better function and quality of life? 
Comparing conventional and computer-assisted total knee 
arthroplasty. The Journal of arthroplasty. 2009;24(4):560-569.
    \890\ Galea M.P., Levinger P., Lythgo N., et al. A targeted 
home- and center-based exercise program for people after total hip 
replacement: A randomized clinical trial. Archives of physical 
medicine and rehabilitation. 2008;89(8):1442-1447.
    \891\ McGregor A.H., Rylands H., Owen A., Dore C.J., Hughes S.P. 
Does preoperative hip rehabilitation advice improve recovery and 
patient satisfaction? The Journal of arthroplasty. 2004;19(4):464-
468.
    \892\ Moffet H, Collet J.P., Shapiro S.H., Paradis G., Marquis 
F., Roy L. Effectiveness of intensive rehabilitation on functional 
ability and quality of life after first total knee arthroplasty: A 
single-blind randomized controlled trial. Archives of physical 
medicine and rehabilitation. 2004;85(4):546-556.
---------------------------------------------------------------------------

    Due to the absence of large scale and uniformly collected patient-
reported outcome (PRO) data available from patients undergoing elective 
primary THA/TKA, in November 2015 we established an incentivized, 
voluntary PRO data collection opportunity within the Comprehensive Care 
for Joint Replacement (CJR) model \893\ to support measure development. 
Requirements for successful submission of PRO data for eligible 
elective primary THA/TKA procedures were set forth in the 2015 CJR 
final rule (80 FR 73274). This Hospital-Level, Risk-Standardized 
Patient-Reported Outcomes Following Elective Primary Total Hip and/or 
Total Knee Arthroplasty (THA/TKA) performance measure (THA/TKA PRO-PM) 
was developed and tested using PRO instruments and risk variable data 
collected and submitted by CJR participant hospitals. PRO data from the 
first few performance years for the CJR model revealed hospital-level 
variation in these outcomes across U.S. hospitals, although the full 
degree and extent of variation is unknown.
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    \893\ Centers for Medicare & Medicaid Services. Comprehensive 
Care for Joint Replacement Model. Available at: https://innovation.cms.gov/innovation-models/cjr.
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    In October 2017, we launched the Meaningful Measures Framework to 
identify high priority areas for quality measurement that improve 
patient outcomes while also reducing burden on providers.\894\ The 
initiative captures the agency's vision in evaluating and streamlining 
regulations with a goal to reduce unnecessary cost and burden, increase 
efficiencies, and improve beneficiary experience. The scope of the 
Meaningful Measures Framework continues to evolve as the healthcare 
environment continues to change. Meaningful Measures 2.0 \895\ is 
currently underway and aims to promote better collection and 
integration of patients' voices by incorporating patient reported 
outcome measures that are embedded into the clinical workflow, are easy 
to use, and reduce reporting burden.\896\ The THA/TKA PRO-PM is fully 
developed and aligns with these future Meaningful Measures 2.0 goals, 
which are still under development.
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    \894\ CMS' Meaningful Measures Framework can be found at: 
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/MMF/General-info-Sub-Page.
    \895\ Centers for Medicare & Medicaid Services. Meaningful 
Measures 2.0: Moving from Measure Reduction to Modernization. 
Available at: https://www.cms.gov/meaningful-measures-20-moving-measure-reduction-modernization. We note that Meaningful Measures 
2.0 is still under development.
    \896\ https://www.cms.gov/meaningful-measures-20-moving-measure-reduction-modernization.
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    Elective THA/TKAs are important, effective procedures performed on 
a broad population, and the patient outcomes for these procedures (such 
as pain, mobility, and quality of life) can be measured in a 
scientifically sound 
way,897 898 899 900 901 902 903 904 905 906 907 908 909 are 
influenced by a range of

[[Page 49248]]

improvements in care,910 911 912 913 914 915 916 917 and 
demonstrate hospital-level variation even after patient case mix 
adjustment.918 919 Further, THA/TKA procedures are 
specifically intended to improve function and reduce pain, making 
patient reported outcomes a meaningful outcome metric to assess.\920\
---------------------------------------------------------------------------

    \897\ Alviar M.J., Olver J., Brand C., Hale T., Khan F. Do 
patient-reported outcome measures used in assessing outcomes in 
rehabilitation after hip and knee arthroplasty capture issues 
relevant to patients? Results of a systematic review and ICF linking 
process. J. Rehabil Med. 2011;43(5):374-381.
    \898\ Alviar M.J., Olver J., Brand C., et al. Do patient- 
reported outcome measures in hip and knee arthroplasty 
rehabilitation have robust measurement attributes? A systematic 
review. J Rehabil Med. 2011;43(7):572-583.
    \899\ Bauman S., Williams D., Petruccelli D., Elliott W., de 
Beer J. Physical activity after total joint replacement: a cross-
sectional survey. Clin J Sport Med. 2007;17(2):104-108.
    \900\ Collins N.J., Roos E.M. Patient-reported outcomes for 
total hip and knee arthroplasty: Commonly used instruments and 
attributes of a ``good'' measure. Clin Geriatr Med. 2012;28(3):367- 
394.
    \901\ Jones C.A., Beaupre L.A., Johnston D.W., Suarez-Almazor 
M.E. Total joint arthroplasties: Current concepts of patient 
outcomes after surgery. Rheum Dis Clin North Am. 2007;33(1):71-86.
    \902\ Lau R.L., Gandhi R., Mahomed S., Mahomed N. Patient 
satisfaction after total knee and hip arthroplasty. Clin Geriatr 
Med. 2012;28(3):349-365.
    \903\ Liebs T.R., Herzberg W., Ruther W., Russlies M., 
Hassenpflug J., Multicenter Arthroplasty Aftercare Project M. 
Quality-adjusted life years gained by hip and knee replacement 
surgery and its aftercare. Archives of physical medicine and 
rehabilitation. 2016;97(5):691-700.
    \904\ Montin L., Leino-Kilpi H., Suominen T., Lepisto J. A 
systematic review of empirical studies between 1966 and 2005 of 
patient outcomes of total hip arthroplasty and related factors. J 
Clin Nurs. 2008;17(1):40-45.
    \905\ Papalia R., Del Buono A., Zampogna B., Maffulli N., Denaro 
V. Sport activity following joint arthroplasty: A systematic review. 
Br Med Bull. 2012;101:81-103.
    \906\ Rolfson O., Rothwell A., Sedrakyan A., et al. Use of 
patient-reported outcomes in the context of different levels of 
data. J Bone Joint Surg Am. 2011;93 Suppl 3:66-71.
    \907\ Suter L.G., Potteiger J., Cohen D.B., Lin Z., Drye E.E., 
Bernheim S.M. Environmental Scan/Literature Review: Total Hip and 
Total Knee Arthroplasty Patient-Reported Outcome Measure. Report 
prepared for Centers for Medicare & Medicaid Services. 2012.
    \908\ Thorborg K., Roos E.M., Bartels E.M., Petersen J., Holmich 
P. Validity, reliability and responsiveness of patient-reported 
outcome questionnaires when assessing hip and groin disability: A 
systematic review. BJSM online. 2010;44(16):1186-1196.
    \909\ White D., Master H. Patient Reported Measures of Physical 
Function in Knee Osteoarthritis. Rheum Dis Clin North Am. 
2016;42(2):239-252.
    \910\ Brown K., Topp R., Brosky J.A., Lajoie A.S. 
Prehabilitation and quality of life three months after total knee 
arthroplasty: A pilot study. Perceptual and motor skills. 
2012;115(3):765-774.
    \911\ Choong P.F., Dowsey M.M., Stoney J.D. Does accurate 
anatomical alignment result in better function and quality of life? 
Comparing conventional and computer-assisted total knee 
arthroplasty. The Journal of arthroplasty. 2009;24(4):560-569.
    \912\ Galea M.P., Levinger P., Lythgo N., et al. A targeted 
home- and center-based exercise program for people after total hip 
replacement: A randomized clinical trial. Arch Phys Med Rehabil. 
2008;89(8):1442-1447.
    \913\ Kim K., Anoushiravani A., Chen K., et al. Perioperative 
Orthopedic Surgical Home: Optimizing Total Joint Arthroplasty 
Candidates and Preventing Readmission. Journal of Arthroplasty. 
2019;34(7):S91-S96.
    \914\ McGregor A.H., Rylands H., Owen A., Dore C.J., Hughes S.P. 
Does preoperative hip rehabilitation advice improve recovery and 
patient satisfaction? The Journal of arthroplasty. 2004;19(4):464-
468.
    \915\ Moffet H., Collet J.P., Shapiro S.H., Paradis G., Marquis 
F., Roy L. Effectiveness of intensive rehabilitation on functional 
ability and quality of life after first total knee arthroplasty: A 
single-blind randomized controlled trial. Arch Phys Med Rehabil. 
2004;85(4):546-556.
    \916\ Monticone M., Ferrante S., Rocca B., et al. Home-based 
functional exercises aimed at managing kinesiophobia contribute to 
improving disability and quality of life of patients undergoing 
total knee arthroplasty: A randomized controlled trial. Arch Phys 
Med Rehabil. 2013;94(2):231-239.
    \917\ Walters M., Chambers M., Sayeed Z., Anoushiravani A., El-
Othmani M., Saleh K. Reducing Length of Stay in Total Joint 
Arthroplasty Care. Orthopedic Clinics of North America. 
2016;47(4):653-660.
    \918\ Bozic K.J., Grosso L.M., Lin Z., et al. Variation in 
hospital-level risk-standardized complication rates following 
elective primary total hip and knee arthroplasty. JBJS. 
2014;96(8):640-647.
    \919\ Ma kela K.T., Peltola M., Sund R, Malmivaara A., Ha kkinen 
U., Remes V.. Regional and hospital variance in performance of total 
hip and knee replacements: A national population-based study. Annals 
of medicine. 2011;43(sup1):S31-S38.
    \920\ Liebs T., Herzberg W., Gluth J., et al. Using the 
patient's perspective to develop function short forms specific to 
total hip and knee replacement based on WOMAC function items. Bone 
Joint J. 2013;95(B):239-243.
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    Several stakeholder groups were engaged throughout the development 
process of the THA/TKA PRO-PM, as recommended in the Measures 
Management System (MMS) Blueprint,\921\ including a Technical Advisory 
Group (TAG), a Patient Working Group, and a national, multi-stakeholder 
TEP consisting of a diverse set of stakeholders, including providers 
and patients. These groups were convened by the measure developer under 
contract with CMS and provided feedback on the measure concept, 
outcome, cohort, risk model variables, reporting results, and data 
collection. We received feedback from patients and providers that they 
had a desire for a flexible data collection approach. For example, 
providers wanted the option to choose to collect their own data or have 
data collected through an external entity, such as a vendor. Patients 
wanted to choose from multiple modes of data collection, such as 
telephone, paper, and/or electronic. We also received feedback from 
patients and providers that they would like to utilize their patient 
reported outcome results as part of the shared decision-making process. 
Patients were more willing to report data if they knew the survey was 
from their provider, they understood the importance and use of the 
survey, and they had access to their own survey responses. In response 
to this feedback, we did not propose a specific mode for data 
collection for the THA/TKA PRO-PM. Rather, we proposed that hospitals 
may determine a data collection mode that accommodates their clinical 
workflow. We also received multiple public comments as summarized in 
the 2015 CJR final rule (80 FR 73274) that we used to support the 
development of this measure.
---------------------------------------------------------------------------

    \921\ Centers for Medicare & Medicaid Services. (2021). CMS 
Measures Management System Blueprint (Blueprint v 17.0). Available 
at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/MMS/MMS-Blueprint.
---------------------------------------------------------------------------

    The THA/TKA PRO-PM (MUC20- 0003) was included in the publicly 
available ``2020 Measures Under Consideration List.'' \922\ The MAP 
Coordinating Committee supported the measure, as referenced in the 
2020-2021 Final Recommendations report to HHS and CMS.\923\ The NQF 
endorsed the THA/TKA PRO-PM (NQF #3559) in November 2020.\924\
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    \922\ 2020 Measures Under Consideration List. Available at 
https://www.cms.gov/media/492911.
    \923\ MAP 2020-2021 Considerations for Implementing Measures 
Final Report--Clinicians, Hospitals, and PAC-LTC. NQF. 2021. 
Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=94894.
    \924\ NQF Quality Positioning System. Available at https://www.qualityforum.org/QPS.
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    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25588 through 
25592), we requested public comment on the potential future inclusion 
of the THA/TKA PRO-PM in the Hospital IQR Program. Many commenters 
expressed support for the measure, with many commending joint-specific 
PRO-PMs as an effective way to provide insights to quality improvement 
opportunities, PRO-PMs for assessing results of surgery as interpreted 
by patients, and describing the measure as essential for value-based 
payment models (86 FR 45411 through 45414). Many commenters recommended 
that the measure be implemented in a phased approach, with voluntary 
reporting occurring prior to public reporting (86 FR 45411 through 
45414). In response to these comments, we proposed a phased 
implementation approach, with two voluntary reporting periods in CY 
2025 and 2026 reporting periods prior to mandatory reporting beginning 
with the CY 2027 reporting period/FY 2028 payment determination, as 
described in further detail in our discussion on data submission in 
section IX.E.5.g.(9).
    Furthermore, many commenters recommended that we offer multiple 
options for data submission, including through the hospital directly or 
by an external vendor engaged by a hospital for this purpose, to ensure 
hospitals have the flexibility needed to implement the measure (86 FR 
45411 through 45414). In response to those comments, in the FY 2023 
IPPS/LTCH PPS proposed rule (87 FR 28526 through 28529), we proposed 
flexible options for data submission as discussed in more detail in 
subsequent section. For a more detailed description of the public 
comments received, we refer readers to the FY 2022 IPPS/LTCH PPS final 
rule (86 FR 45411 through 45414).
    Additionally, we note that many hospitals have already incorporated 
PRO data collection into their workflows. While we did not propose to 
require how hospitals collect data, hospitals new to collecting PRO 
data have multiple options for when and how they will collect this data 
and can best determine the mode of data collection that works for their 
patient population.
(2) Overview of Measure
    The THA/TKA PRO-PM reports the hospital-level risk-standardized 
improvement rate (RSIR) in patient reported outcomes following elective 
primary THA/TKA for Medicare FFS beneficiaries aged 65 years and older.
    Substantial clinical improvement will be measured by achieving a 
pre-defined improvement in score on joint-specific PRO instruments 
measuring hip or knee pain and functioning, from the pre-operative 
assessment (data collected 90 to 0 days before surgery) to the post-
operative assessment (data collected 300 to 425 days following 
surgery). For additional details regarding the measure specifications, 
we refer readers to the Patient-Reported Outcomes (PROs) Following 
Elective Primary Total Hip and/or Total Knee Arthroplasty: Hospital-
Level Performance Measure--

[[Page 49249]]

Measure Methodology Report, available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.
(3) Data Sources
    The THA/TKA PRO-PM uses four sources of data for the calculation of 
the measure: (1) PRO data; (2) claims data; (3) Medicare enrollment and 
beneficiary data; and (4) U.S. Census Bureau survey data. The measure 
uses PRO data collected by hospitals pre-operatively and post-
operatively (described in section IX.E.5.g.(9).) and limited patient-
level risk factor data collected with PRO data and identified in 
claims. The measure includes PRO data collected with several PRO 
instruments, among them are two joint-specific PRO instruments--the Hip 
dysfunction and Osteoarthritis Outcome Score for Joint Replacement 
(HOOS, JR) \925\ for completion by THA recipients and the Knee injury 
and Osteoarthritis Outcome Score for Joint Replacement (KOOS, JR) \926\ 
for completion by TKA recipients--from which scores are used to assess 
substantial clinical improvement. For risk adjustment by pre-operative 
mental health score, hospitals will submit one of two additional PRO 
instruments, either all of the items in the Patient-Reported Outcomes 
Measurement Information System (PROMIS)-Global Mental Health subscale 
or all of the items in the Veterans RAND 12-Item Health Survey (VR-12) 
Mental Health subscale.927 928 The risk model also includes 
a one-question patient-reported assessment of health literacy--the 
Single Item Literacy Screener questionnaire.
---------------------------------------------------------------------------

    \925\ Lyman S., Lee Y-Y., Franklin P.D., Li W., Mayman D.J., 
Padgett D.E. Validation of the HOOS, JR: A Short-form Hip 
Replacement Survey. Clinical Orthopaedics and Related 
Research[supreg]. 2016;474(6):1472-1482.
    \926\ Lyman S., Lee Y-Y., Franklin P.D., Li W., Cross M.B., 
Padgett D.E. Validation of the KOOS, JR: A Short-form Knee 
Arthroplasty Outcomes Survey. Clinical Orthopaedics and Related 
Research[supreg]. 2016;474(6):1461-1471.
    \927\ National Institutes of Health (NIH). (Patient Reported 
Outcomes Measurement Information Systems) PROMIS Instrument Details. 
Available at: https://www.healthmeasures.net/explore-measurement-systems/promis.
    \928\ Iqbal U.S., Rogers W., Selim A., et al. The Veterans Rand 
12 Item Health Survey (VR-12): What It Is and How It Is Used. https://www.hosonline.org/globalassets/hos-online/publications/veterans_rand_12_item_health_survey_vr-12_2007.pdf.
---------------------------------------------------------------------------

    Furthermore, the following data are collected for identification of 
the measure cohort, outcome and for risk adjustment purposes. Claims 
data are used to identify eligible elective primary THA/TKA procedures 
for the measure cohort to which submitted PRO data can be matched, and 
to identify additional variables for risk adjustment and in the 
statistical approach to accounting for response bias, including patient 
demographics and clinical comorbidities up to 12 months prior to 
surgery. The Medicare Enrollment Database (EDB) identifies Medicare FFS 
enrollment and race, and the Master Beneficiary Summary File allows for 
determination of Medicare and Medicaid dual eligibility enrollment 
status. Demographic information from the U.S. Census Bureau's American 
Community Survey \929\ allows for derivation of the AHRQ SES Index 
score. Race, dual eligibility, and AHRQ SES Index score are used in the 
statistical approach to accounting for non-response bias. We refer 
readers to section IX.E.5.g.(9). for further details regarding the 
variables required for data collection and submission.
---------------------------------------------------------------------------

    \929\ American Community Survey, available at: https://www.census.gov/programs-surveys/acs.
---------------------------------------------------------------------------

(4) Outcome
    The measure outcome (numerator) is the risk-standardized proportion 
of patients undergoing elective primary THA/TKA who meet or exceed a 
substantial clinical improvement threshold between pre-operative and 
post-operative assessments on two joint-specific PRO instruments. The 
measure outcome will assess patient improvement in PROs using the HOOS, 
JR following elective primary THA and the KOOS, JR following elective 
primary TKA. PRO data will be collected 90 to zero days prior to 
surgery and 300 to 425 days following surgery. These PRO collection 
periods align with typical patient visits prior to and following 
surgery.
    The measure outcome defines patient improvement as a binary outcome 
(``Yes''/``No'') of meeting or exceeding the pre-defined improvement 
threshold between pre-operative and post-operative assessments on the 
joint-specific PRO instruments: Specifically, for THA patients, meeting 
or exceeding the threshold of 22 points on the HOOS, JR and, for TKA 
patients, meeting or exceeding the threshold of 20 points on the KOOS, 
JR.
(5) Cohort
    The measure cohort (denominator) is Medicare FFS beneficiaries aged 
65 years and older undergoing elective primary THA/TKA procedures as 
inpatients in acute care hospitals. We are aware that elective primary 
THA/TKA procedures are increasingly occurring in hospital outpatient 
and ambulatory surgical center settings and we will be evaluating 
options to address measurement of those procedures and settings.
    For additional details regarding the measure cohort, we refer 
readers to the Patient-Reported Outcomes (PROs) Following Elective 
Primary Total Hip and/or Total Knee Arthroplasty: Hospital-Level 
Performance Measure--Measure Methodology Report, available in Hip and 
Knee Arthroplasty Patient-Reported Outcomes folder at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.
(6) Inclusion and Exclusion Criteria
    The THA/TKA PRO-PM includes patients who are:
     Enrolled in Medicare FFS Part A and Part B for the 12 
months prior to the date of the index admission and enrolled in Part A 
during the index admission;
     Aged 65 or older; and
     Discharged alive from a non-Federal short-term acute care 
hospital.
    The measure includes only elective primary THA/TKA procedures 
(patients with fractures and revisions are not included). The measure 
excludes patients with staged procedures, defined as more than one 
elective primary THA or TKA performed on the same patient during 
distinct hospitalizations during the measurement period, and patients 
who leave the hospital against medical advice following the procedure.
(7) Risk Adjustment
    The risk model was developed with clinically relevant risk 
variables identified by public comment in the 2015 CJR final rule (80 
FR 73274), the TEP, and expert orthopedic consultants, and supported by 
empirical analyses. The risk model includes some of the same risk 
variables collected with PRO data by hospitals in the CJR model as well 
as risk variables identified in claims. The pre-operative score of the 
Mental Health subscale from one of two global PRO instruments (the 
PROMIS-Global or the VR-12) is included as a risk variable. In 
addition, the risk model includes a validated, one-question patient-
reported assessment of health literacy--the Single Item Literacy 
Screener questionnaire.
    Furthermore, poorly or incompletely collected PRO data may be 
asymmetrically distributed across lower socioeconomic or disadvantaged 
populations, potentially affecting measure scores. Research on PRO-PM 
response has indicated that patients of non-White race, patients of 
lower socio-economic status, and patients with

[[Page 49250]]

Medicare and Medicaid coverage have lower response 
rates.930 931 932 Therefore, the measure developer used 
empirical analyses and stakeholder input to develop an approach to 
account for response bias in the measure calculation. The approach uses 
comorbidities, social drivers of health, and demographic variables 
(such as non-White individuals, dual eligibility, and AHRQ SES index 
lowest quartile) to predict response to the PRO survey. Weighting the 
responders based on their likelihood of response (given their patient 
characteristics) helps reduce non-response bias when calculating the 
RSIR.
---------------------------------------------------------------------------

    \930\ Hutchings A., Neuburger J., Frie K., Black N., van der 
Meulen J. Factors associated with nonresponse in routine use of 
patient reported outcome measures after elective surgery in England. 
Health and Quality of Life Outcomes. 2012;10(34).
    \931\ Schamber E., Takemoto S., Chenok K., Bozic K. Barriers to 
completion of patient reported outcome measures. The Journal of 
arthroplasty. 2013;28:1449-1453.
    \932\ Patel J., Lee J., Zhongmin L., SooHoo N., Bozic K., 
Huddleston J. Predictors of low patient-reported outcomes response 
rates in the California Joint Replacement Registry. The Journal of 
arthroplasty. 2015;30:2071-2075.
---------------------------------------------------------------------------

    For additional details regarding the approach to risk adjustment 
and the full risk model, we refer readers to the Patient-Reported 
Outcomes (PROs) Following Elective Primary Total Hip and/or Total Knee 
Arthroplasty: Hospital-Level Performance Measure--Measure Methodology 
Report, available in Hip and Knee Arthroplasty Patient-Reported 
Outcomes folder at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.
(8) Measure Calculation
    The hospital-level THA/TKA PRO-PM measure result is calculated by 
aggregating all patient-level results across the hospital. At the 
hospital level, this measure will be calculated and presented as a 
RSIR, producing a performance measure per hospital which accounts for 
patient case mix, addresses potential non-response bias, and represents 
a measure of quality of care following elective primary THA and TKA. 
Response rates for PRO data will be calculated as the percentage of 
elective primary THA or TKA procedures for which complete and matched 
pre-operative and post-operative PRO data have been submitted divided 
by the total number of eligible THA or TKA procedures performed at each 
hospital.
(9) Data Submission
    Comments submitted on a request for information in the FY 2022 
IPPS/LTCH PPS proposed rule and summarized in the FY 2022 IPPS/LTCH PPS 
final rule (86 FR 45411 through 45414) recommended CMS provide multiple 
options for data submission mechanisms to ensure flexibility, including 
through qualified clinical data registries, as well as through the 
hospital.
    In response to ongoing stakeholder feedback and public comments in 
the FY 2022 IPPS/LTCH PPS final rule (86 FR 45411 through 45414), we 
proposed in the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28527) to 
adopt the THA/TKA PRO-PM in the Hospital IQR Program utilizing multiple 
submission approaches. For example, hospitals may choose to: (1) Send 
their data to CMS for measure calculation directly; or (2) utilize an 
external entity, such as through a vendor or registry, to submit data 
on behalf of the hospital to CMS for measure calculation. Furthermore, 
hospitals or vendors will use the HQR System as part of data submission 
for the THA/TKA PRO-PM. Use of the HQR System leverages existing CMS 
infrastructure already utilized for other quality measures (such as the 
Hospital Consumer Assessment of Healthcare Providers and Systems 
(HCAHPS) Survey). The HQR System allows for data submission using 
multiple file formats (such as CSV, XML) and a manual data entry 
option, allowing hospitals and vendors additional flexibility in data 
submission. We will provide hospitals with more detailed instructions 
and information regarding data submission through CMS' existing website 
QualityNet, and through list servs. This data submission approach is 
consistent with stakeholder input received by the measure developer 
during measure development and comments as summarized in the FY 2022 
IPPS/LTCH PPS final rule (86 FR 45411 through 45414) which recommended 
CMS provide multiple options for data submission mechanisms to ensure 
flexibility.
    Hospitals will submit the following pre-operative assessment 
variables collected between 90 and zero days prior to the THA/TKA 
procedure: Medicare provider number, Medicare health insurance claim 
(HIC) number/Medicare beneficiary identifier (MBI), date of birth, date 
of procedure, date of PRO data collection, procedure type, mode of 
collection, person completing the survey, date of admission to anchor 
hospitalization, generic patient reported outcome measure version, 
PROMIS-Global (mental health subscale items) or VR-12 (mental health 
subscale items), HOOS, JR (for THA patients), KOOS, JR (for TKA 
patients), Single-Item Health Literacy Screening (SILS2) questionnaire, 
BMI or weight (kg)/height (cm), chronic (>= 90 day) narcotic use, total 
painful joint count (patient-reported in non-operative lower extremity 
joint), and quantified spinal pain (patient-reported back pain, 
Oswestry index question933 934).
---------------------------------------------------------------------------

    \933\ Fairbank J.C., Pynsent P.B. The Oswestry Disability Index. 
Spine (Phila Pa 1976). 2000 Nov 15;25(22):2940-52; discussion 2952. 
doi: 10.1097/00007632-200011150-00017. PMID: 11074683.
    \934\ The Oswestry Disability Index is in the public domain and 
available for all hospitals to use.
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    Hospitals will submit the following post-operative assessment 
variables collected between 300 and 425 days following the THA/TKA 
procedure: Medicare provider number, Medicare health insurance claim 
number/Medicare beneficiary identifier, date of birth, procedure date, 
date of PRO data collection, procedure type, mode of collection, person 
completing the survey, date of admission to anchor hospitalization, 
KOOS, JR (TKA patients), and HOOS, JR (THA patients). The data 
submission period for the THA/TKA PRO-PM will also serve as the review 
and correction period. Data will not be able to be corrected following 
the submission deadline.
    For additional details we refer readers to the Patient-Reported 
Outcomes (PROs) Following Elective Primary Total Hip and/or Total Knee 
Arthroplasty: Hospital-Level Performance Measure-- Measure Methodology 
Report, available in Hip and Knee Arthroplasty Patient-Reported 
Outcomes folder at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.
(a) Voluntary Reporting Period

[[Page 49251]]

    We proposed a phased implementation approach for adoption of this 
measure to the Hospital IQR Program, with two voluntary reporting 
periods prior to mandatory reporting in the Hospital IQR Program. 
Voluntary reporting prior to mandatory reporting will allow time for 
hospitals to incorporate the THA/TKA PRO-PM data collection into their 
clinical workflows and is responsive to stakeholder comments as 
summarized in the FY 2022 IPPS/LTCH PPS final rule (86 FR 45411 through 
45414). For each voluntary and subsequent mandatory reporting period, 
we will collect data on the THA/TKA PRO-PM in accordance with, and to 
the extent permitted by, the HIPAA Privacy and Security Rules (45 CFR 
parts 160 and 164, subparts A, C, and E), and other applicable law.
    We proposed that the first voluntary reporting period for CY 2025 
would include pre-operative PRO data collection from October 3, 2022 
through June 30, 2023 (for eligible elective primary THA/TKA procedures 
performed from January 1, 2023 through June 30, 2023) and post-
operative PRO data collection from October 28, 2023 to August 28, 2024. 
Hospitals will submit pre-operative data in 2023 and post-operative 
data in 2024, and we intend to provide hospitals with their results in 
confidential feedback reports in 2025. We refer readers to section 
IX.E.10.k., where we discuss the form, manner, and timing for PRO-PMs, 
including submission deadlines.
    The second voluntary reporting period for CY 2026 will include pre-
operative PRO data collection from April 2, 2023 through June 30, 2024 
(for eligible elective primary THA/TKA procedures performed from July 
1, 2023 through June 30, 2024) and post-operative PRO data collection 
from April 26, 2024 to August 29, 2025. Hospitals will submit pre-
operative data in 2024 and post-operative data in 2025, and we intend 
to provide hospitals with their results in confidential feedback 
reports in 2026. We refer readers to section IX.E.10.k., where we 
discuss the form, manner, and timing for PRO-PMs, including submission 
deadlines.
    Hospitals that voluntarily submit data for this measure will 
receive confidential feedback reports that detail submission results 
from the reporting period. If feasible, we will calculate and provide 
each participating hospital with their risk-standardized improvement 
rate as part of the confidential feedback reports. This will provide 
each hospital with an indication of their performance relative to the 
other hospitals that participate in the voluntary reporting period. We 
refer readers to Table IX.E-07. for an overview of the pre- and post-
operative performance periods, data collection windows, and data 
submission deadlines during voluntary reporting.
[GRAPHIC] [TIFF OMITTED] TR10AU22.163

(b) Mandatory Reporting
    Following the two voluntary reporting periods, we proposed that 
mandatory reporting of the THA/TKA PRO-PM would begin with eligible 
elective primary THA/TKA procedures from July 1, 2024 through June 30, 
2025 with affecting the FY 2028 payment determination. Hospitals' data 
reporting requirements will be based on pre-operative PRO data 
collection from April 2, 2024 through June 30, 2025 (for eligible 
elective THA/TKA procedures from July 1, 2024 through June 30, 2025) 
and post-operative PRO data collection from April 27, 2025 to August 
29, 2026. Pre-operative data submission will occur in 2025 and post-
data submission in 2026 and we intend to provide hospitals with their 
results in 2027 before publicly reporting results on the Compare tool 
hosted by HHS, currently available at: https://www.medicare.gov/care-compare, or its successor website. For this first mandatory reporting 
period, hospitals that fail to timely meet the reporting requirements 
will receive a reduction of their Annual Payment Update (APU) in FY 
2028. We refer readers to the section IX.E.10.k., where we discuss the 
form, manner, and timing for PRO-PMs, including submission deadlines. 
We refer readers to Table IX.E-08. for an overview of the pre- and 
post-operative performance periods, data collection windows, and data 
submission deadlines during mandatory reporting.
[GRAPHIC] [TIFF OMITTED] TR10AU22.164


[[Page 49252]]


(10) Public Reporting
(a) Voluntary Reporting Periods
    We proposed to provide hospitals with their THA/TKA PRO-PM results 
in confidential feedback reports during the two voluntary reporting 
periods occurring in 2025 and 2026. While we did not propose to 
publicly report voluntary THA/TKA PRO-PM hospital-level risk-
standardized improvement rates (RSIR) during this period, to 
acknowledge the efforts of stakeholders who choose to participate in 
voluntary reporting, and to support their efforts to improve quality in 
this important area, we proposed to publicly report which hospitals 
choose to participate in voluntary reporting and/or the percent of pre-
operative data submitted by participating hospitals for the first 
voluntary reporting period, and their percent of pre-operative and 
post-operative matched PRO data submitted for subsequent voluntary 
reporting periods. For example, if out of 100 eligible procedures a 
hospital submits 45 pre-operative cases that match to post-operative 
cases, then we will report that hospital submitted 45 percent of 
matched pre-operative and post-operative PRO surveys during voluntary 
reporting
(b) Mandatory Reporting
    The THA/TKA PRO-PM results and response rates will be publicly 
reported on the Compare tool hosted by HHS, currently available at: 
https://www.medicare.gov/care-compare, or its successor website, 
beginning with the first mandatory reporting period for the FY 2028 
payment determination. Reporting will be based on pre-operative PRO 
data April 2, 2024 through June 30, 2025 (for eligible elective THA/TKA 
procedures from July 1, 2024 through June 30, 2025) and post-operative 
PRO data collection from April 27, 2025 to August 29, 2026. Hospitals 
will receive confidential feedback reports prior to public reporting 
that detail results from the reporting period. If feasible, 
confidential feedback reports will include the risk-standardized 
improvement rate as well as other results that support understanding of 
their performance.
    We invited public comment on this proposal.
    Comment: Many commenters expressed support for the adoption of the 
THA/TKA PRO-PM in the Hospital IQR Program. A commenter strongly 
supported the adoption of the measure as it provides patients with 
valuable information on the quality of joint care provided by 
hospitals, as well as information on post-operative functional 
improvements. Another commenter strongly supported the adoption of the 
measure as it assesses the success of procedures based on outcomes that 
are important to patients while also supplying clinical teams with 
information essential to a patient's recovery. The commenter noted this 
information is useful to other patients seeking care and should be 
publicly posted. A commenter stated patient-reported outcomes for 
elective primary THA and TKA procedures are critical to ensure the 
procedure quality is accurately captured. Another commenter supported 
the measure's adoption as it incentivizes collaboration in patient care 
between hospitals and providers, both pre- and post-operatively, which 
improves patient outcomes. Many commenters expressed support for the 
collection of PRO data for hospital quality improvement efforts, and 
use of PRO-PMs in CMS programs, generally. A commenter stated that THA 
and TKA procedures offer the majority of patients significant 
improvement in quality of life by decreasing pain and improving 
function without high risk of complication or death and, therefore, 
supported collection of PRO data for total joint replacements. A 
commenter supported adoption of the measure for Critical Access 
Hospitals that provide THA and TKA services. A commenter supported the 
adoption of the measure and requested more information on the mechanism 
for data collection for providers and patients.
    Response: We thank commenters for their support and agree with the 
importance of measuring patient-reported outcomes for elective primary 
THA and TKA procedures, particularly to measure functional improvement 
following the applicable surgical procedure. We will conduct education 
and outreach activities for hospitals and other stakeholders with 
detailed information, including data collection and reporting processes 
for the THA/TKA PRO-PM to support preparation for the voluntary 
reporting periods in the Hospital IQR Program.
    Comment: Many commenters did not support the proposed adoption of 
the THA/TKA PRO-PM to the Hospital IQR Program because of the volume of 
newly proposed quality measures and EHR-related reporting requirements 
proposed by CMS for the Hospital IQR Program. Many commenters expressed 
concern that the adoption of the THA/TKA PRO-PM to the Hospital IQR 
Program would be burdensome to hospitals. Many commenters stated that 
the financial, resource, and labor costs required to collect, track, 
and submit data would burden hospitals and make successful 
implementation of the measure difficult, even if hospitals opt to use a 
third-party vendor for data collection and submission. A commenter 
expressed concern about the burden specifically for small and rural 
hospitals. A few commenters noted that data are not collected in a 
standardized way and EHRs are not integrated with patient portals that 
would allow hospitals to collect patient-reported information, adding 
manual burden to extrapolate data or infrastructure investments. A 
commenter noted their belief that the measure is counter to CMS's 
efforts to reduce administrative burden for hospitals and detracts from 
their primary mission of direct patient care. A few commenters urged 
CMS to work with stakeholders to develop a less burdensome measure or 
reassess the burden compared to the value of this measure following 
voluntary reporting.
    A few commenters expressed concerns regarding the burden of 
tracking patients pre- and post-operatively to collect PRO data, 
stating that data are not centrally housed, patients receive post-
operative care outside the hospital, and the tracking of patients for 
the duration of the post-operative data collection timeframe of 300 to 
425 days would be expensive and burdensome. Additionally, a few 
commenters stated that reaching out to patients to collect surveys in 
multiple modes would be expensive; however, other commenters encouraged 
having multiple modes of survey collection.
    Response: We acknowledge commenters' concerns with the volume of 
measures and reporting requirements proposed for the Hospital IQR 
Program. We will continue to evaluate the Hospital IQR Program measure 
set and take this feedback into consideration. However, we believe that 
measuring patient-reported outcomes is an important aspect of patient-
centered healthcare and continue to emphasize, as highlighted in our 
Meaningful Measures 2.0 Framework,\935\ that the patient voice should 
be prioritized across healthcare systems and providers. Our aim is to 
promote better collection and integration of patients' voices by 
incorporating PROMs that are embedded into clinical workflow, easy to 
use, and as minimally burdensome to patients and providers as possible.
---------------------------------------------------------------------------

    \935\ https://www.cms.gov/medicare/meaningful-measures-framework/meaningful-measures-20-moving-measure-reduction-modernization.
---------------------------------------------------------------------------

    We thank commenters for their feedback regarding the financial, 
labor, and resource burdens associated with adopting the THA/TKA PRO-PM 
to the Hospital IQR Program. We acknowledge

[[Page 49253]]

that while PROMs and PRO-PMs may involve more burden and initial 
implementation resources compared to some other types of quality 
measures, we believe the benefit of collecting direct functional 
improvement information from the patients outweighs the burden. We are 
carefully considering public comments and are seeking to advance 
patient-centered measurement with as little burden as possible to both 
providers and patients. While PRO-PMs require providers to integrate 
data collection into clinical workflows, this integration provides an 
important opportunity for patient-reported outcomes to inform clinical 
decision making and benefit patients by engaging them in discussions 
about potential outcomes. To provide more flexibility, we are not 
requiring hospitals to collect data in a standardized way. In fact, we 
acknowledge hospitals may use a variety of data collection, storage, 
and submission approaches, and we encourage hospitals to use processes 
best suited to them. Instead, we are standardizing the specific data 
elements that need to be collected and reported to CMS. Further, we 
believe that clinicians, providers, and hospitals should determine 
practices that avoid duplication across care settings. We will continue 
to monitor data collection burden and duplication during the voluntary 
reporting period.
    The PRO instruments used to calculate pre- and post-operative 
scores for this THA/TKA PRO-PM were carefully considered, with 
extensive stakeholder input, including from clinicians, to be low 
burden and are non-proprietary for free use. We will evaluate data 
collection burden and response rates associated with the THA/TKA PRO-PM 
and will also consider this information in future measure reevaluation.
    Comment: A few commenters expressed concern about the data 
collection burden for patients, with a commenter specifically citing 
survey fatigue as patients are already responding to the HCAHPS survey 
measure. Another commenter expressed concern that completion of surveys 
for the measure beyond only the HOOS, JR and KOOS, JR would burden 
patients resulting in lower completion rates.
    Response: This measure was developed with extensive input from 
patients, who indicated strong support for a PRO-PM following elective 
primary THA and TKA. We anticipate data collection for this measure to 
present a low burden to patients. Regarding survey fatigue, we designed 
the measure to illuminate a patient's pain and functional status before 
and after a THA or TKA, which is different than other surveys such as 
HCAHPS that capture patient experience. Regarding the comment that the 
THA/TKA PRO-PM may have a reporting impact on other measures, such as 
HCAHPS, we anticipate a minimal impact to other measures as the THA/TKA 
PRO-PM's eligible population is procedure-specific which reduces the 
likelihood of the same patient receiving the HCAHPS and a PRO survey. 
Additionally, the THA/TKA PRO-PM pre-operative assessment (90 to 0 days 
before surgery) and post-operative assessment (300 to 425 days 
following surgery) timeframe is different than HCAHPS, which is two 
weeks after a hospital visit.
    Comment: Another commenter requested CMS assess survey completion 
rates during voluntary reporting of the measure as part of the Hospital 
IQR Program compared to the CJR Model. A few commenters requested CMS 
not adopt the THA/TKA PRO-PM in the Hospital IQR Program until 
operational challenges identified by CJR participating hospitals are 
shared publicly, independently analyzed, and addressed. Commenters 
expressed concern that reporting of the THA/TKA PRO-PM as part of the 
CJR Model has been challenging and burdensome, potentially impacting 
completion rates.
    Response: We appreciate commenters' request for information about 
use of the measure in the CJR Model. We have collected feedback from 
CJR participating hospitals and applied lessons learned to the THA/TKA 
PRO-PM proposal for adoption into the Hospital IQR Program. These 
lessons learned include requiring hospitals to collect and submit fewer 
variables, allowing hospitals flexibility in data collection options to 
better integrate into their workflows, and influenced the decision to 
set the reporting threshold to a moderate rate of 50 percent. We 
highlight that our proposal includes two voluntary reporting periods in 
which we will gather feedback from participating hospitals on their 
experience collecting and submitting data and apply any lessons learned 
prior to mandatory reporting.
    We thank commenters for their feedback. We will continue to 
evaluate feedback on challenges with data collection during voluntary 
reporting and consider them prior to mandatory reporting.
    Comment: A few commenters suggested ways to reduce data collection 
and submission burden for hospitals and providers. A commenter 
suggested CMS align THA/TKA PRO-PM data collection with The Joint 
Commission Advanced Hip and Knee certification requirements. Another 
commenter suggested data collection should occur through registries, 
specifically the American Academy of Orthopedic Surgeons American Joint 
Replacement registry. A few commenters recommended CMS only use claims 
data or develop a new measure using Medicare claims to assess total 
joint arthroplasty revisions and mortality rates. A commenter 
recommended CMS directly collect post-operative surveys because CMS has 
access to current beneficiary information, could collect surveys for 
different surgeries across care settings, and reduce burden on 
providers.
    Response: We thank commenters for their recommendations to reduce 
burden of data collection and submission associated with adoption of 
the THA/TKA PRO-PM to the Hospital IQR Program. We confirm that the 
measure as proposed notes registries as an acceptable form of data 
collection for the measure (87 FR 28527 through 28528). We agree with 
use of registries to reduce data collection burden for hospitals. 
Regarding alignment of the THA/TKA PRO-PM with The Joint Commission 
Advanced Hip and Knee certification requirements, we note that 
alignment exists in the PRO instruments, specifically the HOOS, JR and 
KOOS, JR (collected for the measure outcome for the THA/TKA PRO-PM) as 
well as the PROMIS-10 or VR-12 (collected for the risk model of the 
THA/TKA PRO-PM).\936\ We will continue to monitor potential areas for 
alignment, as appropriate. We will also consider commenter suggestions 
about CMS's role in post-operative data collection, and the development 
of claims-based joint arthroplasty measures.
---------------------------------------------------------------------------

    \936\ The Joint Commission. R3 Report Issue 26: Advanced Total 
Hip and Total Knee Replacement Certification Standards; 2020. 
https://www.jointcommission.org/-/media/tjc/documents/standards/r3-reports/thkr-standards-r3-final-copy-1_17_20.pdf.
---------------------------------------------------------------------------

    Comment: Many commenters expressed concerns with the 300 through 
425 days post-operative data collection window related to 
appropriateness, feasibility, and burden to hospitals and other care 
settings, though a commenter supported assessment of longer-term 
outcomes generally. A few commenters stated that the proposed post-
operative data collection window is not aligned with clinical practice 
where patients receive follow up care from their surgeons ranging 
between three to eight weeks post-operatively. A few commenters

[[Page 49254]]

added that most improvement is demonstrated before the 300 through 425 
post-operative data collection windows: for example, within 80 or 90 
days. A commenter stated the proposed post-operative data collection 
window will introduce unnecessary health care encounters which add risk 
to patients. A few commenters noted challenges with tracking patients 
during the post-operative data collection window, stating beneficiaries 
do not always return for follow up care or may relocate. A commenter 
was concerned the post-operative data collection window was too far 
removed from the surgery and patient survey responses could be 
inaccurate. Several commenters recommended CMS shorten the post-
operative data collection window. Commenters offered the following 
suggestions: 3 months, 3 through 6 months, and 8 through 12 months.
    Response: We appreciate commenters' concerns with the 300 through 
425-day post-operative data collection window; however, we disagree 
that the proposed post-operative window should be changed at this time. 
In development of the THA/TKA PRO-PM, the measure developer conducted 
extensive stakeholder engagement, a thorough literature review, and 
reviewed registry data capture to inform the post-operative assessment 
window (initially 270 to 365 days) for capture of full recovery from 
both THA and TKA and alignment with the typically scheduled one-year 
post-surgery appointments so that the collection of the post-operative 
data collection would not require an additional appointment. Following 
several years of PRO data collection through the CJR Model, clinical 
experts expressed concern that the initial 365-day upper limit missed 
patients who were scheduled or rescheduled for this one-year follow-up 
beyond 365 days, and they strongly advocated for shifting the post-
operative data collection window to better align with clinical practice 
and increase PRO data collection. For additional details we refer 
readers to the Patient-Reported Outcomes (PROs) Following Elective 
Primary Total Hip and/or Total Knee Arthroplasty: Hospital-Level 
Performance Measure--Measure Methodology Report, available in Hip and 
Knee Arthroplasty Patient-Reported Outcomes folder at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.
    Comment: Many commenters provided feedback on the proposed 
voluntary and mandatory reporting timelines for the THA/TKA PRO-PM 
adoption into the Hospital IQR Program but expressed a mix of support 
and recommended changes. A few commenters supported the proposed 
voluntary and mandatory reporting timelines, noting they give hospitals 
an opportunity to incorporate data collection into clinical workflows. 
However, a few commenters supported only the voluntary reporting 
timeline without mandatory reporting. A few commenters requested CMS 
extend the voluntary reporting timeline and delay mandatory reporting 
to support hospitals learning and their incorporation of data 
collection into clinical workflows; to allow CMS to assess the success, 
value, and burden of the measure; and to allow time for data collection 
challenges to be reduced. A commenter suggested four years of voluntary 
reporting. Another commenter recommended CMS use multiple six- month 
reporting periods before requiring a full year of reporting data.
    Response: We thank commenters for their support of the phased 
approach of adopting the THA/TKA PRO-PM in the Hospital IQR Program. We 
have considered commenters' recommendations regarding voluntary and 
mandatory reporting timelines. We believe the proposed voluntary and 
mandatory reporting implementation approach will allow hospitals 
sufficient time to make the necessary enhancements to their clinical 
workflow to successfully report this measure. We highlight that our 
proposal includes two voluntary reporting periods prior to mandatory 
reporting which balances the need to allow hospitals time to prepare 
for mandatory reporting with the need to make this information public 
for patient use. We will carefully consider feedback received during 
voluntary reporting to inform improvements that may be made for 
mandatory reporting. We also refer readers to section IX.E.10.k. of 
this final rule where we discuss in more detail the form, manner, and 
timing of reporting the THA/TKA PRO-PM.
    Comment: A few commenters did not support the adoption of the THA/
TKA PRO-PM into the Hospital IQR Program as proposed. A commenter 
expressed that physician performance cannot be differentiated using 
patient-reported outcomes, noting many factors that influence an 
outcome are beyond an individual physician's influence, such as those 
related to patient factors and quality of care received overall.
    Response: We acknowledge commenters' concerns regarding the 
adoption of the THA/TKA PRO-PM and patient-reported outcomes generally. 
However, we believe that PRO-PMs are an important aspect of patient-
centered healthcare and continue to emphasize our position in our 
Meaningful Measures 2.0 Framework \937\ that the patient voice is 
prioritized across healthcare systems and providers. Our aim is to 
promote better collection and integration of patients' voices by 
incorporating PRO-PMs that are embedded into clinical workflow, easy to 
use, and reduce reporting burden. We agree with the commenter that many 
factors influence a patient's outcome after a THA or TKA procedure, 
many of which are related to the overall quality of care the patient 
received at the hospital. As such, we are beginning to measure patient 
reported outcomes for these procedures at the hospital level but 
believe future measurement in other care settings, such as for HOPDs, 
ASCs, or at the clinician level, is important to understanding quality 
of care across settings.
---------------------------------------------------------------------------

    \937\ https://www.cms.gov/medicare/meaningful-measures-framework/meaningful-measures-20-moving-measure-reduction-modernization.
---------------------------------------------------------------------------

    Comment: Many commenters discussed the appropriateness of CMS' use 
of the THA/TKA PRO-PM in the hospital setting. A few commenters 
recommended CMS expand use of the measure across other care settings 
where THA/TKA procedures are performed. Many commenters noted the 
transition of THA/TKA procedures from the inpatient hospital setting to 
the outpatient setting and encouraged use of the measure in the 
Hospital Outpatient Quality Reporting (OQR) Program or the Ambulatory 
Surgical Center Quality Reporting (ASCQR) Program, and at the clinician 
level, with a few commenters recommending CMS monitor shifts in volume 
of procedures between settings during the voluntary reporting period. A 
few commenters expressed concern that, given the shift of procedures to 
the outpatient setting, only the sickest and most complex patients 
would undergo THA/TKA procedures in the hospital, and this could skew 
hospital results on the measure. A few commenters suggested that CMS 
consider risk adjusting to account for trends in greater acuity of 
inpatient patients undergoing THA/TKA procedures. A few commenters had 
concerns attributing outcomes to hospitals because surgeons' offices or 
other settings commonly administer PRO surveys. Another commenter 
requested CMS consider its future public reporting approach to ensure 
inappropriate comparisons cannot be made between hospital and 
outpatient THA/TKA PRO-PM results.

[[Page 49255]]

A commenter suggested CMS consider efficiencies gained by linking 
hospital data with MIPS data for providers.
    Response: We thank commenters for their support for expanding this 
measure to other programs and settings. We agree that monitoring trends 
and transition of THA/TKA procedures to outpatient settings is also 
important. We appreciate commenter insights on the differences in 
patient complexity across care settings and will continue to monitor 
this during reevaluation of the measure's risk adjustment model. We 
disagree that the measure is not appropriate for the inpatient hospital 
setting at this time. We note that the proposed THA/TKA PRO-PM measure 
is case mix adjusted for patient comorbidities and is a relative 
performance measure for hospitals performing these elective THA and TKA 
procedures (87 FR 28527).\938\ As such, we believe that this measure 
accurately reflects hospital performance even if patients receiving 
these procedures in the inpatient setting tend to be sicker, on 
average, than those treated in an outpatient setting.
---------------------------------------------------------------------------

    \938\ Patient-Reported Outcomes (PROs) Following Elective 
Primary Total Hip and/or Total Knee Arthroplasty: Hospital-Level 
Performance Measure (Version 1.0 Methodology Report). March 2021.
---------------------------------------------------------------------------

    Given the relatively recent removal of TKA and THA from the 
Inpatient Only (IPO) list (82 FR 52521 through 52526) (84 FR 61352 
through 61355), we expect that the volume of THA and TKA procedures 
will continue to increase in HOPDs and ASCs, and that significant 
numbers of Medicare beneficiaries 65 and older will potentially undergo 
these procedures in the outpatient setting in future years. We 
recognize that potential future adoption and implementation of a 
respecified version of the THA/TKA PRO-PM in the Hospital OQR Program 
would require sufficient numbers of procedures for each measured HOPD 
and ASC to ensure a reliable measure score. We proposed the measure in 
the inpatient setting at this time and will consider potential 
expansion to other outpatient settings. We refer readers to the CY 2022 
OPPS final rule for a summary of comments on the request for comment on 
the potential future adoption of the measure into the Hospital OQR and 
ASCQR Programs (86 FR 63851 through 63854 and 63896 through 63898). We 
also agree that there is value in measurement at the clinician level, 
however, the hospital level measure helps capture the quality of care 
provided during a patient's stay and provides the opportunity for more 
entities to have sufficient case volume to be included in the measure. 
A respecified version of the measure at the clinician level, the 
Clinician-Level and Clinician Group-Level Total Hip and/or Total Knee 
Arthroplasty Patient-Reported Outcome-Based Performance Measure, was 
included on the 2021 Measures Under Consideration List. For additional 
details we refer readers to the List of Measures Under Consideration 
for December 1, 2021 at: https://www.cms.gov/files/document/measures-under-consideration-list-2021-report.pdf. Any proposal to implement the 
measure in other CMS programs would be announced through future 
rulemaking.
    Comment: A few commenters provided recommendations on reimbursement 
and incentives for adopting the THA/TKA PRO-PM in the Hospital IQR 
Program. A commenter stated CMS should not use the measure in 
determining hospital reimbursement due to limits in risk 
stratification. Another commenter stated it is too early to compare 
hospital scores to determine reimbursement as PRO scores are not fully 
understood at the patient level. Another commenter urged CMS not to 
impose penalties if the measure is adopted. A few commenters 
recommended CMS provide incentives for hospitals to report the measure. 
Another commenter stated rural hospitals that are burdened by the 
measure would benefit from incentives similar to the facility bonus 
used in the Quality Payment Program (QPP). A few commenters encouraged 
CMS to consider reimbursing hospitals for data collection, such as 
using a CPT code with a bonus, similar to QPP. Another commenter 
recommended a quality bonus payment similar to the CJR Model or Bundled 
Payments for Care Improvement Initiative.
    Response: We thank commenters for their recommendations about 
reimbursement and incentives for reporting the THA/TKA PRO-PM. We are 
not able to provide incentive payments under the Hospital IQR Program. 
We note that the Hospital IQR Program is a pay-for-reporting program, 
and hospitals' payments are not based on their performance on measures; 
hospitals will receive credit for the reporting of their measure data 
regardless of their measure score.
    Comment: A few commenters provided recommendations regarding the 
measure specifications. A commenter supported the risk adjustment 
approach for the measure. However, another commenter recommended CMS 
include social determinants of health, body mass index, and smoking as 
risk variables and a third commenter requested CMS also consider 
variables that are outside of providers' influence that impact 
outcomes, such as patient adherence to surgical instructions or 
comorbidities. A few commenters recommended separating THA and TKA into 
their own procedure specific measures, stating that THA procedures have 
a higher success rate for improvement while the same level of 
improvement is not reached for TKA procedures. A few commenters 
suggested CMS calculate the change in PRO survey scores for individual 
patients pre- and post-operatively rather than the measure calculation 
approach as currently proposed. A commenter requested CMS exclude 
patients with history of prosthetic knee joint infections for 
reimplantation of knee arthroplasty and arthroplasties where the 
medical record includes a diagnosis of nonunion where the surgery is 
performed on a joint previously fractured that failed to heal. The 
commenter expressed concern that these surgeries are highly complex and 
dissimilar to other procedures captured in the THA/TKA PRO-PM's cohort 
as proposed.
    Response: We thank commenters for their input on the THA/TKA PRO-
PM's specifications for the cohort, risk adjustment, and measure 
calculation. We note that the measure is risk adjusted for several risk 
variables including but not limited to health literacy, body mass 
index, and several comorbidities (87 FR 28527). The threshold 
improvement approach to measure score calculation was strongly 
supported by clinical experts and patients during measure development 
and preferred to averaging patient change scores. We note that the 
National Quality Forum endorsed the THA/TKA PRO-PM as proposed.\939\ 
For additional details we refer readers to the Patient-Reported 
Outcomes (PROs) Following Elective Primary Total Hip and/or Total Knee 
Arthroplasty: Hospital-Level Performance Measure--Measure Methodology 
Report, available in Hip and Knee Arthroplasty Patient- Reported 
Outcomes folder at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology. We will review these recommendations and consider any 
adjustments to the measure as appropriate as part of normal ongoing 
measure reevaluation.
---------------------------------------------------------------------------

    \939\ National Quality Forum. Patient Experience and Function 
Final Report--Spring 2020 Cycle; 2021. Available at: https://www.qualityforum.org/Publications/2021/03/Patient_Experience_and_Function_Final_Report_-_Spring_2020_Cycle.aspx.
---------------------------------------------------------------------------

    Comment: A few commenters provided input on the PRO instruments

[[Page 49256]]

selected for the THA/TKA PRO-PM. A commenter requested CMS clarify 
rationale for collecting quantified spinal pain in the Oswestry 
Disability index. Another commenter opposed limiting the THA/TKA PRO-PM 
to just HOOS, JR and KOOS, JR instruments and suggested CMS allow 
communities to decide which validated PRO instrument to use for their 
patient population. The commenter noted the HOOS, JR and KOOS, JR lack 
cross cultural validation and suggested use of HOOS and KOOS full 
forms, Joint Replacement Shortforms, Physical Function Shortform, or 
PROMIS Physical Function.
    Response: We thank commenters for their feedback on the selected 
PRO instruments. Use of the HOOS, JR and KOOS, JR instruments to 
calculate pre- and post-operative scores for this THA/TKA PRO-PM were 
carefully considered, with extensive stakeholder input from clinicians, 
and found to be low burden. The clinicians also believed, and data 
demonstrated, that joint-specific functional status tools such as the 
HOOS, JR and KOOS, JR are more relevant for clinical decision making 
and are more responsive than other PROMs that are not as specific. We 
believe the use of different PRO instruments by different facilities 
would prevent a valid comparison of hospital performance and quality. 
In response to the commenter's objection to collection of Quantified 
Spinal Pain as part of the Oswestry Disability index,940 941 
we note that variable was identified as a clinical risk variable 
supported by the Technical Expert Panel and orthopedic experts as 
relevant and important for risk adjustment of outcomes following 
elective primary THA and TKA procedures. We note that the National 
Quality Forum endorsed the THA/TKA PRO-PM as proposed.\942\ For 
additional details we refer readers to the Patient-Reported Outcomes 
(PROs) Following Elective Primary Total Hip and/or Total Knee 
Arthroplasty: Hospital-Level Performance Measure--Measure Methodology 
Report, available in Hip and Knee Arthroplasty Patient-Reported 
Outcomes folder at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.
---------------------------------------------------------------------------

    \940\ Fairbank JC, Pynsent PB. The Oswestry Disability Index. 
Spine (Phila Pa 1976). 2000 Nov 15;25(22):2940-52; discussion 2952. 
doi: 10.1097/00007632-200011150-00017. PMID: 11074683.
    \941\ The Oswestry Disability Index is in the public domain and 
available for all hospitals to use.
    \942\ National Quality Forum. Patient Experience and Function 
Final Report--Spring 2020 Cycle; 2021. https://www.qualityforum.org/Publications/2021/03/Patient_Experience_and_Function_Final_Report_-_Spring_2020_Cycle.aspx.
---------------------------------------------------------------------------

    Comment: A few commenters discussed concerns with the THA/TKA PRO-
PM's impact on health disparities and response bias. A few commenters 
stated that surveys may only provide a limited sample of patient data, 
introducing bias and masking lower completion rates among marginalized 
groups. Surveys administered through technologies such as Epic, text, 
or third-party vendors could worsen racial disparities, introduce 
barriers, and limit a hospital's ability to collect a representative 
sample of patients from all races, socioeconomic statuses, and 
languages. A commenter questioned whether the THA/TKA PRO-PM as 
proposed adjusts for non-response bias for patients with limited 
English language proficiency, as such patients would be challenged to 
complete surveys, and hospitals with a high proportion of patients with 
limited English proficiency may have a lower response rate. A commenter 
suggested CMS provide reimbursement to hospitals to overcome these 
challenges in data collection. Another commenter encouraged 
stratification and reporting of results to hospitals for 
underrepresented populations.
    Response: We thank commenters for their input regarding health 
disparities and response bias. We agree with commenters that 
considering the unique experience of populations with social risk 
factors is important. As proposed, the measure accounts for potential 
non-response bias (inverse probability weighting) and considers patient 
characteristics, including non-White race, dual eligibility, and the 
AHRQ SES index score (87 FR 28527). The AHRQ SES index score is 
computed using US census data and considers factors including zip code, 
median household income, percentage of persons below the Federal 
poverty line, unemployment, education, property value, and percentage 
of persons in crowded households.\943\ Although preferred language 
spoken is not a variable currently included in the non-response bias 
approach, the measure as proposed includes health literacy in the risk 
model. For additional details we refer readers to the Patient-Reported 
Outcomes (PROs) Following Elective Primary Total Hip and/or Total Knee 
Arthroplasty: Hospital-Level Performance Measure--Measure Methodology 
Report, available in Hip and Knee Arthroplasty Patient-Reported 
Outcomes folder at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology. We appreciate the comments regarding the importance of 
considering disadvantaged populations within the measure specifications 
and implementation, and we will continue to assess any impact of social 
risk factors on the measure and response rates over time.
---------------------------------------------------------------------------

    \943\ Bonito A, Bann C, Eicheldinger C, Carpenter L. Creation of 
new race-ethnicity codes and socioeconomic status (SES) indicators 
for Medicare beneficiaries. Final Report, Sub-Task. 2008;2.
---------------------------------------------------------------------------

    Regarding non-response bias and the measure results, we encourage 
hospitals to consider a variety of PRO data collection methods to 
support responses from all eligible patients. We also recognize that 
addressing health disparities and response bias are complex issues. We 
are firmly committed to addressing health disparities and response bias 
for patient reported outcomes. We believe finalizing the Hospital 
Commitment to Health Equity structural measure and the two Social 
Drivers of Health screening measures, discussed in sections IX.E.5.a. 
and IX.E.5.b. of this final rule, respectively, supports addressing 
these issues and incentivizes structural quality improvement. We 
believe it will take a complementary set of quality measures focused on 
health equity to see significant improvements.
    Comment: A few commenters expressed concern about reporting 
thresholds as well as the pre- and post-operative survey matching 
requirements. A commenter suggested CMS lower the reporting threshold 
for the measure and study response rates before finalizing a threshold. 
Another commenter urged CMS to use the voluntary reporting periods to 
set realistic matching percentages between pre- and post-operative 
surveys. A commenter noted the transition from performing THA and TKA 
procedures from hospitals to outpatient settings may affect hospital's 
ability to meet reporting thresholds. A commenter noted that the CJR 
Model uses an 80% reporting threshold which is challenging for 
hospitals to meet. The commenter encouraged CMS to analyze response 
rates from CJR participating hospitals and identify ways to increase 
pre- and post-operative survey responses. Another commenter questioned 
if hospitals will be penalized for not meeting reporting thresholds due 
to low response rates.
    Response: We selected the 50 percent reporting threshold after 
considering numerous factors and the experience of CJR Model 
participants. The proposed reporting threshold is based on average 
response rates for both pre-operative

[[Page 49257]]

and post-operative surveys collected by participating hospitals in the 
CJR Model. The proposed reporting threshold for adoption of the measure 
into the Hospital IQR Program is lower than that currently used in the 
CJR Model (50 percent versus 80 percent). Additionally, hospitals are 
not held to reporting thresholds until mandatory reporting; therefore, 
we believe hospitals will have time to develop their data collection 
and reporting processes. Lastly, the proposed thresholds for the 
Hospital IQR Program are percentages based on the number of eligible 
inpatient procedures performed by a hospital; therefore, we do not 
expect any potential future transition of procedures to outpatient 
settings to impact a hospital's ability to meet reporting thresholds 
(87 FR 28559 through 28560).
    We will continue to consider the appropriate pre- and post-
operative matched survey response rate, as well as reporting 
thresholds. We will evaluate our proposed approach during voluntary 
reporting and consider adjustments based on feedback prior to mandatory 
reporting.
    Comment: A few commenters requested CMS adjust the threshold of 
functional improvement of 20 and 22 points for KOOS, JR and HOOS, JR, 
respectively. A commenter requested CMS to adopt an average functional 
gain for HOOS, JR and KOOS, JR scores to better capture the extent of 
patient-reported post-operative improvement, stating that the proposed 
approach sets the quality bar too low and is not aligned with the 
literature.
    Response: The substantial clinical benefit thresholds of a 20-point 
improvement on the KOOS, JR and a 22-point improvement on the HOOS, JR 
were selected based on our analyses of published literature and measure 
development data and with considerable stakeholder input to capture 
variation in patient outcomes among hospitals that reflect differences 
in care quality among hospitals. During measure development, these 
improvement thresholds were supported by the Technical Expert Panel and 
patients. For additional details, we refer readers to the Patient-
Reported Outcomes (PROs) Following Elective Primary Total Hip and/or 
Total Knee Arthroplasty: Hospital-Level Performance Measure--Measure 
Methodology Report, available in the Hip and Knee Arthroplasty Patient-
Reported Outcomes folder at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology. We thank commenters for their recommendations and 
will consider this feedback during routine measure reevaluation.
    After consideration of the public comments we received, we are 
finalizing the proposal as proposed.
h. Medicare Spending per Beneficiary (MSPB) Hospital Measure (NQF 
#2158) Beginning With the FY 2024 Payment Determination
    For the purpose of continuing to assess hospitals' efficiency and 
resource use and to meet statutory requirements under section 
1886(o)(2)(B)(ii) of the Act, in the FY 2023 IPPS/LTCH PPS proposed 
rule (87 FR 28529 through 28532) we proposed the adoption of the re-
evaluated version of the MSPB Hospital measure in the Hospital IQR 
Program. We plan to subsequently propose this for the Hospital VBP 
Program measure set under the Efficiency and Cost Reduction Domain 
sometime in the future.
(1) Background
    In the FY 2012 IPPS/LTCH PPS final rule, we adopted a prior version 
of the MSPB Hospital measure in both the Hospital IQR Program (76 FR 
51618) and the Hospital VBP Program (under the Efficiency and Cost 
Reduction Domain) (76 FR 51654). The original MSPB Hospital measure was 
subsequently removed from the Hospital IQR Program beginning with the 
FY 2020 payment determination, under the proposed removal Factor 8, the 
costs associated with a measure outweigh the benefit of its continued 
use in the program (83 FR 41559). The original version of the MSPB 
Hospital measure that was removed from the Hospital IQR Program was 
identical to the version that was concurrently, and continues to be 
used in the Hospital VBP Program. For more information on the removal 
of the original MSPB Hospital measure from the Hospital IQR Program, 
please see section VIII.A.4.b of the FY 2019 IPPS/LTCH PPS final rule 
(83 FR 41540 through 41544). We note that adding the updated MSPB 
Hospital measure with the refinements outlined previously to the 
Hospital IQR Program would follow the process associated with adopting 
new measures into the Hospital VBP Program, as specified under section 
1889(o)(2)(C)(i) of the Act, and provide beneficiaries, hospitals, and 
other stakeholders with an opportunity to familiarize themselves with 
this updated version of the measure before we propose to replace the 
original MSPB Hospital measure in the Hospital VBP Program and 
calculate incentive payment adjustments for eligible hospitals. Given 
that the proposed updated MSPB Hospital measure is different from the 
original MSPB Hospital measure currently in use in the Hospital VBP 
Program, we believe that including the updated MSPB Hospital measure in 
the Hospital IQR Program will not incur costs that justified the 
removal of the original MSPB Hospital measure from the Hospital IQR 
Program in the FY 2019 IPPS/LTCH PPS final rule.
    The original MSPB Hospital measure evaluated hospitals' efficiency 
relative to the efficiency of the national median hospital. 
Specifically, it assessed the cost to Medicare during an episode of 
care, which is composed of the period three days prior to an IPPS 
hospital admission through 30 days after discharge. The measure 
included Medicare Part A and B payments for services provided to a 
Medicare beneficiary during an episode. The costs included in this 
measure were payment standardized to remove sources of variation not 
directly related to hospitals' care decisions, such as geographic 
differences in practice expenses. The measure was risk adjusted to 
account for factors outside of hospitals' influence. The details of the 
original MSPB Hospital episode construction and measure calculation can 
be found in the FY 2012 IPPS/LTCH PPS final rule (76 FR 51618 through 
51627).
    As part of our measure maintenance process (as required in section 
8 of the Blueprint for the CMS Measures Management System Version 17.0 
available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/MMS/Downloads/Blueprint.pdf), we comprehensively 
re-evaluated the original MSPB Hospital measure in 2020, after it was 
removed from the Hospital IQR Program beginning with the FY 2020 
payment determination period. The re-evaluation was informed by 
feedback received on this measure through prior public comment periods 
\944\ and the literature. Specifically, regarding the all-cost nature 
of the measure, some stakeholders raised concerns that an all-cost 
approach may result in the measure capturing services that are not 
under the influence of the facilities or practitioners, while others 
noted that there is a need for all-cost/condition measures such as the 
MSPB Hospital

[[Page 49258]]

measure to promote broad incentives for care coordination. Regarding 
readmissions triggering new episodes, commenters noted that potentially 
high cost services occurring after an inpatient readmission are not 
fully captured under the current methodology that does not allow 
readmissions to initiate new episodes, and that the correlation between 
the MSPB Hospital measure and the Hospital Readmission Reduction 
Program's readmission measures is weak. Finally, some commenters 
suggested potential need for social risk factor (SRF) adjustments.\945\ 
Relatedly, the literature has identified dual enrollment in Medicare 
and Medicaid as a potentially meaningful SRF to adjust for in the VBP 
programs.\946\
---------------------------------------------------------------------------

    \944\ We received feedback during the public comment periods of 
the FY 2012 and FY 2013 IPPS/LTCH PPS proposed rules. We refer 
readers to the FY 2012 IPPS/LTCH PPS final rule (76 FR 51619 through 
51627) and the FY 2013 IPPS/LTCH PPS final rule (77 FR 53584 through 
53592) for a summary of the comments received.
    \945\ FY 2012 IPPS/LTCH PPS final rule (76 FR 51624 through 
51625) and FY 2013 IPPS/LTCH PPS final rule (77 FR 53586 through 
53587).
    \946\ Johnston, K.J. & Maddox, K.E.J. (2019). The Role of 
Social, Cognitive, And Functional Risk Factors In Medicare Spending 
For Dual And Nondual Enrollees.
---------------------------------------------------------------------------

    In the process of evaluating this feedback, the TEP reviewed four 
main topics to explore as potential changes to the specifications, 
including:
    (1) Narrowing the all-cost approach through service inclusion and 
exclusion rules;
    (2) Including SRFs in the measure's risk adjustment model;
    (3) Allowing readmissions to trigger a new episode and include an 
indicator variable in the risk adjustment model for whether there was 
an inpatient stay in the 30 days prior to episode start date; and
    (4) Changing the measure calculation from the sum of observed costs 
divided by the sum of expected costs to the mean of observed costs 
divided by expected costs.
    After reviewing the analyses prepared by the measure development 
contractor and discussed during the February 2020 meeting, the TEP 
members provided feedback on each of the potential refinements during 
the process of re-evaluation. In brief, the TEP believed that the 
current all-cost methodology approach appropriately reflected the broad 
scope of a hospital's responsibility of care, and that this was needed 
to promote broad incentive for care coordination. TEP members 
highlighted the need for further testing around the impact of including 
SRF variables in the risk adjustment model. The TEP supported the 
refinement to allow readmissions to trigger new episodes, as they 
believed it was clinically appropriate to hold the hospital responsible 
for these costs. The members also agreed that the slight change to the 
measure calculation would reduce the impact of outliers on the final 
measure scores. The summary of the TEP's discussions of the MSBP 
Hospital measure is in the February 2020 Physician Cost Measures and 
Patient Relationship Codes TEP Summary Report.\947\
---------------------------------------------------------------------------

    \947\ Physician Cost Measures and Patient Relationship Codes TEP 
Summary Report. (2020). Available at: https://www.cms.gov/files/zip/physician-cost-measures-and-patient-relationship-codes-pcmp.zip.
---------------------------------------------------------------------------

    Through the re-evaluation process and the feedback that was 
provided by the TEP, we identified three refinements to the measure 
which will ensure a more comprehensive and consistent reflection of 
hospital performance by capturing more episodes and adjusting the 
measure calculation. First, we refined the measure to include all 
readmissions to trigger new episodes to account for episodes and costs 
that are currently not included in the measure but that could be within 
the hospital's reasonable influence. Second, we added an indicator 
variable in the risk adjustment model for whether there was an 
inpatient stay in the 30 days prior to episode start date. And third, 
we revised the measure to change one step in the measure calculation 
from the sum of observed costs divided by the sum of expected costs 
(ratio of sums) to the mean of observed costs divided by expected costs 
(mean of ratios). Based on our measure development contractor's 
recommendations, informed by the guidance from the TEP and the 
additional testing of the potential refinements suggested by the TEP, 
we believe that these changes will benefit the MSPB Hospital measure's 
relevance and statistical stability as well as ensure a more 
comprehensive and consistent reflection of hospital performance by 
capturing more episodes and adjusting the measure calculation. We 
describe these changes in a summary of the measure re-evaluation on the 
CMS QualityNet website posted in July 2020.\948\
---------------------------------------------------------------------------

    \948\ Medicare Spending Per Beneficiary (MSPB) Measure 
Methodology. Available at: https://qualitynet.cms.gov/inpatient/measures/mspb/methodology.
---------------------------------------------------------------------------

    We proposed the updated MSPB Hospital measure for the Hospital IQR 
Program that incorporates the three changes, which are detailed in the 
subsequent discussion. We note that aside from these three described 
refinements, all other aspects of the updated measure are the same as 
compared to the original measure.
(a) Update To Allow Readmissions To Trigger New Episodes
    First, we refined the measure to allow readmissions to trigger new 
episodes to account for episodes and costs that are currently not 
included in the measure but that could be within the hospital's 
reasonable influence. It is clinically appropriate to hold the hospital 
responsible for the costs that are associated with the readmissions 
(that is, from 3 days prior to the readmission through 30 days post-
discharge) to encourage care transitions and coordination in improving 
patient care and reducing unnecessary readmissions. Under the 
previously adopted measure methodology, the measure only included 
episodes that are triggered by initial hospital admissions, and 
inpatient readmissions occurring in the 30-day post-discharge period of 
an existing episode are excluded from initiating new episodes (76 FR 
51620 through 51624). Allowing readmissions to trigger new episodes 
will increase the number of episodes for which a provider can be scored 
and align the incentives of the measure during readmissions, by 
encouraging hospitals to provide cost efficient care and improve care 
coordination not only during initial hospitalizations, but also during 
readmissions. This refinement will also ensure that the measure 
captures potentially high-cost services that would otherwise be 
excluded.
    To illustrate this refinement, take for example a beneficiary who 
is admitted to an inpatient hospital for a spinal procedure with major 
complication or comorbidity (MS-DRG 028). This hospital admission 
triggers an episode (Episode 1), where the episode window starts three 
days prior to the admission date and ends 30 days after discharge. 
Episode 1 is attributed to the hospital where the inpatient stay 
occurs. Fifteen days after being discharged from the hospital, the 
beneficiary needs to receive additional inpatient hospital care for 
pneumonia (MS-DRG 194). This readmission occurs within the 30-day post-
discharge period of Episode 1 (that is, the episode triggered by the 
initial hospitalization), and will trigger a new episode (Episode 2). 
Episode 2's window will start three days prior to this readmission and 
end 30 days after discharge. Episode 2 will be attributed to the 
hospital managing this readmission. Under the previous methodology, the 
readmission would not be calculated under the measure as a new episode 
because it occurred during the 30-day post-discharge period of Episode 
1. However, under the proposed new methodology, the

[[Page 49259]]

readmission will trigger a new episode (Episode 2), and the episode 
will be included in the MSPB rate for the hospital managing the 
readmission. Episode 2 will include the costs in the post-discharge 
period of the readmission that would not be previously captured. 
Additionally, the costs where Episode 1 and Episode 2 overlap will be 
counted towards each episode. We note that the services being assigned 
to these episodes will only be counted once per episode. In other 
words, costs will not be double-counted. The revised measure 
calculation compares each hospital's observed episode costs to 
predicted episode costs among their peers for patients with the same 
observable characteristics, rather than to a pre-defined standard. By 
comparing hospitals to other hospitals that are all attributed in the 
same way, we expect this comparison to be fair. This also helps to 
maintain care coordination incentives of the MSPB Hospital measure.
(b) New Indicator Variable in the Risk Adjustment Model
    Additionally, to account for the differences in expected costs for 
episodes that are triggered by readmissions, the updated methodology 
includes an indicator variable in the risk adjustment model showing 
whether there was an inpatient stay in the 30 days prior to episode 
start date. The previous methodology does not include this indicator 
variable, given that all episodes with an inpatient stay in the 30 days 
prior to the episode start date (that is, episodes that are based on a 
hospital readmission) are excluded from the measure calculation (76 FR 
51620 through 51624). Continuing with the example used earlier, given 
that Episode 2 is based on a hospital readmission and there was an 
inpatient stay within 30 days prior to its episode start date, the risk 
adjustor indicator will be turned on for Episode 2. This means that 
when we calculate predicted spending for Episode 2, the risk adjustment 
model will take into account the fact that this episode was triggered 
by a readmission, and not an initial admission. This will ensure that 
the hospital is not unfairly penalized for providing care to the 
patient during the episode that could be more high cost due to its 
readmission status.
    An illustration of this refinement that compares the previously 
adopted methodology where a readmission does not trigger a new episode 
and the proposed new methodology where a readmission does trigger a new 
episode, is available in Appendix B of the Measure Information Form 
(MIF) document available at: https://qualitynet.cms.gov/files/5f1b3bd12bd4670021abc1b4?filename=MSPB_Hospital_MIF_2020.pdf.
(c) Updated MSPB Amount Calculation Methodology
    The third refinement changes one step in the measure calculation 
from the sum of observed costs divided by the sum of expected costs 
(ratio of sums) to the mean of observed costs divided by expected costs 
(mean of ratios). Under the previously adopted methodology, we 
calculated the MSPB Amount as follows: ((Sum of Observed Costs//# of 
Attributed Episodes)/(Sum of Expected Costs/# of Attributed Episodes)) 
* Average Observed Cost Nationally (76 FR 51626). The revised 
methodology calculates the MSPB Amount instead as follows: (Sum 
(Observed Costs/Expected Costs)/# of Attributed Episodes) * Average 
Observed Cost Nationally. Under this refinement, changing the measure 
calculation will: (a) Slightly increase measure reliability with 
minimal score changes; and (b) evenly weight attributed episodes in the 
final performance score, where previously good or poor performance on 
more expensive episodes will have more weight in the provider's final 
score. Specifically, by changing the measure calculation, the impact of 
outlier episodes on a measure score will be reduced (under the 
previously adopted calculation methodology, most costly episodes are 
weighted proportionately, which will make the measure slightly more 
sensitive to outlier episodes).
    Additionally, the updated MSPB Hospital measure will further align 
with MSPB cost measures in other settings, including the MSPB Clinician 
measure in MIPS (84 FR 62974 through 62977), and the MSPB-Post Acute 
Care (PAC) measures, including MSPB-PAC for Inpatient Rehabilitation 
Facilities (81 FR 52087 through 52095), Long-Term Care Hospitals (81 FR 
57199 through 57207), Skilled Nursing Facilities (81 FR 52014 through 
52021), and Home Health Agencies (81 FR 76757 through 76765). The 
updated MSPB Hospital measure will also align with the acute inpatient 
medical condition episode-based cost measures in MIPS (83 FR 59767 
through 59773, 84 FR 62962 through 62968. and 86 FR 65446 through 
65453). We note that while the scope of care is different for 
clinician, hospital, and post-acute care level measures, we believe 
aligning these measures will help to ensure consistent care 
coordination incentives between the hospital, post-acute care facility, 
and the clinician(s) providing care in those settings.
(2) NQF Re-Endorsement
    This original MSPB Hospital measure was first endorsed by the NQF 
in 2013 \949\ and then again in 2017.\950\ We presented the updated 
MSPB Hospital measure (NQF ID #2158) with these three refinements to 
NQF in the Fall 2020 cycle for measure re-endorsement. During the Fall 
2020 NQF endorsement cycle, the updated MSPB Hospital measure was 
reviewed by the Scientific Methods Panel (SMP), Cost and Efficiency 
Standing Committee, and Consensus Standards Approval Committee (CSAC) 
during the 11-month endorsement process.\951\ The updated measure 
passed on the reliability and validity criteria when reviewed by the 
SMP. The Cost and Efficiency Standing Committee reviewed each aspect of 
the updated measure in detail across three meetings. They also closely 
reviewed our testing around the impact of social risk factors. 
Specifically, we had tested whether the inclusion of sex, dual 
eligibility status, race/ethnicity, the AHRQ SES index, components of 
the AHRQ SES index, and the Area Deprivation Index could meaningfully 
be incorporated into the measure, so as not to penalize the hospital 
for the patients they treat, while also not setting a lower standard of 
care for hospitals with patients that have social risk factors. Results 
showed that the inclusion of these social risk factors had a limited 
and inconsistent effect on measure scores, and some of the variation 
that was captured by tested covariates was attributable to the hospital 
in which the episodes were initiated. Therefore, social risk factors 
continue to not be included in the measure's risk adjustment model. The 
CSAC approved the Standing Committee's endorsement recommendation 
unanimously, meaning that the updated MSPB Hospital measure (NQF #2158) 
was re-endorsed in June 2021 with the three refinements discussed.\952\
---------------------------------------------------------------------------

    \949\ The NQF Cost and Resource Use--Phase 3 Final Report is 
available at: https://www.qualityforum.org/Publications/2015/02/Cost_and_Resource_Use_-_Phase_3_Final_Report.aspx, and the 2013 NQF 
measure evaluation form is available at: https://www.qualityforum.org/Projects/c-d/Cost_and_Resource_Project/2158.aspx.
    \950\ NQF. (2017). Cost and Resource Use 2016-2017 Final 
Technical Report. Available at: https://www.qualityforum.org/Publications/2017/08/Cost_and_Resource_Use_2016-2017_Final_Technical_Report.aspx.
    \951\ The submission materials, including the testing results, 
are available at: https://www.qualityforum.org/ProjectMeasures.aspx?projectID=86056&cycleNo=2&cycleYear=2020.
    \952\ NQF. (2020). Cost and Efficiency Final Report--Fall 2020 
Cycle. Available at: https://www.qualityforum.org/Publications/2021/09/Cost_and_Efficiency_Final_Report_-_Fall_2020_Cycle.aspx.

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[[Page 49260]]

(3) Measure Applications Partnership Review
    Following NQF re-endorsement, the updated measure was included in 
CMS's ``List of Measures Under Consideration for December 1, 2021.'' 
\953\ The updated MSPB Hospital measure (MUC2021-131) underwent MAP 
review during the 2021-2022 cycle. On December 15, 2021, the MAP 
Hospital Workgroup supported the updated measure for rulemaking. On 
January 19, 2022, the MAP Coordinating Committee upheld the MAP 
Hospital Workgroup's preliminary recommendation to support the updated 
measure for rulemaking. More detail on the discussion is available in 
the MAP's final report.\954\
---------------------------------------------------------------------------

    \953\ Centers for Medicare & Medicaid Services. (2021). List of 
Measures Under Consideration for December 1, 2021. Available at: 
https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96464.
    \954\ National Quality Forum, (2022) Measure Applications 
Partnership 2021-2022 Considerations for Implementing Measures in 
Federal Programs: Clinician, Hospital, and Post-Acute Care Long-Term 
Care (https://www.qualityforum.org/Publications/2022/03/MAP_2021-2022_Considerations_for_Implementing_Measures_Final_Report_-_Clinicians,_Hospitals,_and_PAC-LTC.aspx).
---------------------------------------------------------------------------

    We proposed the updated MSPB Hospital measure (NQF #2158) for the 
Hospital IQR Program beginning with the FY 2024 payment determination 
and for subsequent years. This will allow us to assess hospitals' 
efficiency and resource use and meet statutory requirements for future 
adoption in the Hospital VBP Program.\955\
---------------------------------------------------------------------------

    \955\ Sections 1886(o)(2)(B)(ii) and 1886(o)(2)(C)(i) of the 
Social Security Act (https://www.ssa.gov/OP_Home/ssact/title18/1886.htm).
---------------------------------------------------------------------------

    We invited public comment on this proposal.
    Comment: Several commenters supported the proposed revisions to the 
MSPB Hospital measure, and the measure's adoption in the Hospital IQR 
Program in general. Some commenters expressed specific support for the 
refinement to allow readmissions to trigger a new episode, with a 
commenter stating that this refinement would encourage greater care 
coordination and shared accountability for avoidable readmissions. A 
commenter supported the refinement to add an indicator in the risk 
adjustment model for a previous inpatient stay within 30 days of the 
episode start date. A few commenters were also appreciative that the 
revised measure was NQF-endorsed prior to its proposal to be included 
in the Hospital IQR Program.
    Response: We appreciate the commenters' support for inclusion of 
the revised MSPB Hospital measure in the Hospital IQR Program.
    Comment: While some commenters supported the proposed revisions to 
the MSPB Hospital measure, a few commenters urged that we share 
information on the impact of proposed refinements on the measure. A few 
commenters requested that we provide example calculations under the 
revised and original measure versions to illustrate the potential 
effects of the proposed measure calculation changes and their impact on 
hospitals. A commenter noted that they would be interested to see how 
the revised version of the MSPB Hospital measure and the measure scores 
compare to those of the current version of the measure that is 
currently used in the Hospital VBP Program. The commenter further noted 
that they would be interested in how the refinement of the measure 
calculation would affect Hospital VBP Program scores and outcomes. 
Finally, a commenter urged that we closely monitor the results for both 
versions of the measure in the Hospital IQR and Hospital VBP Programs 
for any unintended consequences, especially during the period of time 
when the measure specifications are not aligned.
    Response: We thank the commenters for their feedback. We note that 
as part of the NQF endorsement process, we provided statistics on the 
impacts of the proposed refinements to the measure. For example, Table 
3.b of the testing appendix that was submitted to NQF contains an 
analysis of changes in MSPB Hospital measure scores between the current 
version of the measure and the version of the measure with proposed 
refinements implemented. In addition, Table 3.a includes testing 
results on the MSPB Hospital measure episodes stratified by whether an 
episode was triggered by an original hospitalization or a readmission. 
The submission materials that include these testing results are 
available at: https://www.qualityforum.org/ProjectMeasures.aspx?projectID=86056&cycleNo=2&cycleYear=2020. 
Additional information on the impact of the refinements and the TEP's 
discussion on each refinement is also available in the February 2020 
Physician Cost Measures and Patient Relationship Codes TEP Summary 
Report available at: https://www.cms.gov/files/zip/physician-cost-measures-and-patient-relationship-codes-pcmp.zip. In order to evaluate 
the impact of the refinements on the Hospital VBP Program scores (that 
is, the Total Performance Scores that are used to adjust hospital 
payments) and outcomes, the measure would need to be implemented in the 
Hospital VBP Program, so that hospital performance on the measure can 
be aggregated with hospital performance on measures in other domains. 
We will continue monitoring the results for both versions of the 
measure in each program for any unintended consequences in the future.
    Comment: Some commenters expressed concerns that for a period of 
time, there would be two slightly different versions of the measure 
used to assess hospital performance in the Hospital IQR and the 
Hospital VBP Programs, respectively. Commenters noted that this could 
make it difficult for hospitals to interpret performance results and 
could lead to additional burden on providers who would need to track 
two different reporting rates. Some commenters also expressed concerns 
about publicly reporting two versions of the MSPB Hospital measure, 
with a commenter requesting clarification on how these measures would 
be distinguished for the public. Some commenters recommended that we 
suppress one set of measures from public reporting, but maintain both 
results in downloadable files. To reduce any confusion caused by having 
two version of the measures being simultaneously reported publicly, a 
few commenters recommended only publicly reporting the current measure 
that is used in Hospital VBP Program, while waiting for at least one 
year before starting to publicly report the revised version of the 
measure. Another commenter recommended suppressing the version used in 
Hospital VBP Program if the revised version is used in the Hospital IQR 
Program and made publicly available.
    Response: We thank the commenters for raising these concerns. As we 
have previously stated (87 FR 28529), a couple of goals of adopting the 
revised version of the measure in the Hospital IQR Program is to 
publicly report it for at least a year in order to meet requirements 
for potential future use in the Hospital VBP Program (as required by 
the Hospital VBP Program statute at section 1886(o) of the Act) as well 
as to provide interested parties with an opportunity to become familiar 
with the new version of the measure and provide feedback. Therefore, we 
do not want to delay the public reporting of the measure by one year, 
as suggested by the commenters. Additionally, by statute, there must be 
a cost measure in the Hospital VBP Program, which is the MSPB Hospital 
measure, so we are unable to remove the current version of the measure 
from Hospital VBP Program, as it is the only cost measure under the 
Efficiency and Cost Reduction

[[Page 49261]]

domain and we believe this domain is an essential part of assessing 
value in addition to quality in the program. We will work to clearly 
identify the version of the measure when publicly reporting the revised 
MSPB Hospital measure and help address any potential confusion. The 
updated version of the measure will be posted with other Hospital IQR 
Program data on the Compare tool, which displays data in a consumer-
focused way. Hospital VBP Program data will continue to be posted to 
data.cms.gov which presents the data as downloadable files and is 
targeted more towards data analysts and researchers rather than 
consumers. We also plan to publicly post educational materials and 
provide support via help desk to respond to stakeholder inquiries.
    Comment: Several commenters did not support the measure and 
expressed concerns that allowing readmissions to trigger a new episode 
in the revised MSPB Hospital measure could lead to the same costs being 
attributed to hospitals twice and potentially result in a misleading 
portrayal of hospital performance. Another commenter expressed concern 
that a facility would be penalized twice related to readmissions, once 
through in the Hospital IQR Program based on their performance on the 
revised MSPB Hospital measure, and again through the Hospital 
Readmissions Reduction Program.
    Response: We thank the commenters for raising these concerns. As 
previously stated in the proposed rule(87 FR 28530), the refinement 
allows readmissions to trigger new episodes which would result in some 
services being assigned to multiple episodes. These services, however, 
would only be counted once per episode, so the cost of these services 
would not be counted twice within the same episode. Additionally, the 
presence of an inpatient admission within 30 days before the start date 
of an episode based on a readmission is controlled for in the risk 
adjustment model to account for the additional complexity that 
readmissions may entail.\956\ Further, the inclusion of episodes 
triggered by readmissions does not necessarily result in a worse 
measure score for the provider. Such episodes still use the observed 
over expected cost ratios, where it is possible for the observed cost 
to be lower than expected cost, if the hospital performed better on the 
episode than expected. Additionally, we do not agree with the 
commenter's statement that this refinement would result in hospitals 
being penalized twice. The revised MSPB Hospital measure, whether used 
in the Hospital IQR Program or Hospital VBP Program, and the condition- 
and procedure-specific readmission measures used in the Hospital 
Readmissions Reduction Program assess readmissions for different 
purposes (for example, assess hospitals' cost efficiency on 
readmissions and reduce avoidable readmissions, respectively) to help 
encourage hospitals to provide higher value care to their patients; 
thus, it is beneficial to have this alignment. Additionally, allowing 
readmissions to trigger new MSPB Hospital episodes does not impact a 
hospital's readmissions rates, given that it merely captures episodes 
that are based on existing readmissions so that those episodes can be 
used to assess hospital performance.
---------------------------------------------------------------------------

    \956\ Medicare Spending Per Beneficiary (MSPB) Measure 
Methodology. Available at: https://qualitynet.cms.gov/inpatient/measures/mspb/methodology.
---------------------------------------------------------------------------

    Comment: Several commenters did not support the measure, expressing 
concerns that the reliability and validity of the revised MSPB Hospital 
measure are low.
    Response: We respectfully disagree with the comments that the 
reliability and validity of the revised MSPB Hospital measure are low. 
The NQF rated reliability as high when endorsing the measure. The 
average reliability score of hospitals with at least 25 episodes was 
0.92,957 958 which far exceeds the standard generally 
considered as `high' reliability. The NQF rated validity as moderate 
when endorsing the measure.959 960 As part of the NQF 
endorsement submission, we undertook three approaches to empirically 
examine the extent to which the revised MSPB Hospital measure captures 
what it intends to capture. Firstly, we examined the relationship 
between risk adjusted episode cost ratios and episodes with and without 
post-admission events that are known indicators of high cost or 
intensive care. Secondly, we examined the relationship between a 
hospital's average expected episode cost and average episode rates of 
several service use categories, to test whether the risk adjustment 
model can predict patient need for certain services. Thirdly, we 
examined the relationship between the revised MSPB Hospital measure and 
other cost-specific measures, efficiency-related measures, and measures 
in other Hospital VBP Program domains. For all three types of validity 
testing, we observed results that were in line with our expectations, 
demonstrating that the measure is functioning as intended.
---------------------------------------------------------------------------

    \957\ The submission materials, including the testing results, 
are available at: https://www.qualityforum.org/ProjectMeasures.aspx?projectID=86056&cycleNo=2&cycleYear=2020.
    \958\ NQF's Cost and Efficiency Final Report with the summary of 
the Scientific Methods Panel's and Standing Committee's discussion 
is available here: https://www.qualityforum.org/Publications/2021/09/Cost_and_Efficiency_Final_Report_-_Fall_2020_Cycle.aspx.
    \959\ The submission materials, including the testing results, 
are available at: https://www.qualityforum.org/ProjectMeasures.aspx?projectID=86056&cycleNo=2&cycleYear=2020.
    \960\ NQF's Cost and Efficiency Final Report with the summary of 
the Scientific Methods Panel's and Standing Committee's discussion 
is available here: https://www.qualityforum.org/Publications/2021/09/Cost_and_Efficiency_Final_Report_-_Fall_2020_Cycle.aspx.
---------------------------------------------------------------------------

    Comment: Some commenters raised concerns about the risk adjustment 
approach for the revised MSPB Hospital measure. Specifically, a few 
commenters were concerned that the measure does not adjust for social 
risk factors. A commenter stated that social risk factors should not be 
considered supplementary to clinical risk factors in risk adjustment 
models. Additionally, a commenter did not believe that the risk 
adjustment model's fit with the unadjusted and adjusted R-squared 
(ranging from 0.11 to 0.67) was sufficiently addressed. Finally, a 
commenter requested for additional clarification on whether the revised 
MSPB Hospital measure takes into account patient acuity, impact of 
patient social drivers of health, supply chain impact, COVID-19 
impacts, and short staffing as variables that could impact Medicare 
spending per beneficiary.
    Response: We thank the commenters for their feedback. As noted 
previously, as part of the NQF endorsement submission we assessed the 
impact of social drivers of health on the measure, conducting testing 
based on NQF precedents, as well as supplemented with novel testing and 
in response to specific stakeholder feedback. The NQF's Scientific 
Methods Panel carefully reviewed the testing results on the impacts of 
social risk factors on the measure and our recommendation to continue 
not including them in the measure's risk adjustment model, and passed 
the measure on validity criterion. Additionally, as part of normal 
measure maintenance, we plan to continue to conduct testing and 
monitoring of the impact of social risk factors on the measure.
    Regarding the commenter's note about the measure's low R-squared 
metrics that were included in the NQF endorsement submission materials, 
we would like to clarify that R-squared metrics, which are calculated 
to analyze the proportion of cost variation explained by the risk 
adjustment model,

[[Page 49262]]

should be interpreted within the context of the measure construction, 
what it is intended to capture, and its use. A low R-squared is 
conceptually neither required nor expected for a ``valid'' measure, so 
some valid measures will have low R-squared metrics, while others will 
have high R-squared metrics. We also note that extensive testing 
demonstrates the validity of the risk adjustment models for the revised 
MSPB Hospital measure, with model discrimination and calibration 
results demonstrating predictive ability across the full range of 
episodes, from low to high spending risk. There was no evidence of 
excessive under- or over-estimation at the extremes of episode risk.
    Given that the revised MSPB Hospital measure is calculated using 
administrative claims data, the measure is unable to directly account 
for supply chain impacts and short staffing. Regarding the commenter's 
note on the impact of COVID-19 on the measure, given that the measure 
uses a risk adjustment model that is run separately for each Major 
Diagnostic Category (MDC), and COVID-19 diagnoses are mapped to 
particular Diagnosis-Related Groups (DRGs), the measure would adjust 
for COVID-19 when risk adjusting by the DRG of the hospitalization. We 
also observed that COVID-19 hospitalizations are highly concentrated 
within MDC 4 (Respiratory System), which further improves comparability 
of COVID-19 episodes to non-COVID-19 episodes. We will continue 
monitoring the effects of COVID-19 on both the current and revised 
versions of the MSPB Hospital measure, however, because of the ways the 
measure already accounts for COVID-19 hospitalizations as described, we 
do not believe any additional adjustments for COVID-19 are needed at 
this time.
    Finally, the measure's risk adjustment methodology accounts for 
patient case-mix and other factors by adjusting for patient age and 
severity of illness. Specifically, the risk adjustment methodology 
includes 12 age categorical variables, 79 hierarchical condition 
category (HCC) indicators, status indicator variables for whether the 
beneficiary qualifies for Medicare through disability or age and End-
Stage Renal Disease (ESRD), indicators to account for disease 
interactions, an indicator of whether the beneficiary recently required 
long-term care, and the Medicare Severity-Diagnosis Related Group (MS-
DRG) of the index hospitalization. We believe this provides adequate 
adjustment for patient acuity.
    Comment: A few commenters raised concerns about a lack of alignment 
between the revised MSPB Hospital measure and relevant quality data, 
and stated that without this alignment or the incorporation of these 
data into the revised MSPB Hospital measure, it cannot accurately 
assess efficiency. The commenters believe that efficiency of care must 
be a measure of cost of care associated with a specified level of 
quality of care. They also believe measures should be grounded in 
current best evidence, should evaluate clinical outcomes concurrently 
with resource use, and should be interpretable based on outcomes 
achieved with resources expended. The commenter added that to fully 
interpret cost measure data, relevant quality data must also be 
available. The inclusion of cost measures alone could discourage the 
provision of needed care or innovative treatments to reduce costs. As a 
result, the commenter encouraged that we investigate alternative 
frameworks for efficiency measurement to properly align the evaluation 
of cost and quality.
    Response: We thank the commenters for their feedback. For the 
purposes of the Hospital IQR Program, we determine the quality of care 
provided by hospitals to their patients by using a variety of measures 
that include both cost and quality measures, thus ensuring alignment 
between cost and quality. Specifically, such measures include payment 
measures (including four condition-specific measures and the revised 
MSPB Hospital measure being proposed), patient safety, morality 
outcome, patient experience of care survey, and others. Similarly, in 
the Hospital VBP Program, the revised MSPB Hospital measure would be 
used in alignment with several quality measures that span Clinical 
Outcomes, Person and Community Engagement, and Safety measure domains, 
so together these measures would facilitate profiling hospital value, 
from both the cost and quality perspectives. In addition, to ensure 
that hospitals are able to understand their performance on the revised 
MSPB Hospital measure and identify areas for improvement, eligible 
hospitals will receive Hospital-Specific Reports (HSRs) that contain 
different breakdowns of the hospital's performance on the measure. 
Providing these files to hospitals would also allow them to provide 
informed feedback on the measure to the measure developer and CMS.
    We also add that the measure itself safeguards against potential 
care stinting by including the costs of consequences of care. For 
example, if the attributed hospital attempts to reduce costs by 
discharging a patient too early, it could result in higher post-acute 
care costs, re-hospitalization for complications, or emergency 
department visits soon after the discharge, which would be captured by 
the measure, resulting in worse performance. Testing submitted as part 
of the NQF endorsement cycle demonstrated that the measure accurately 
reflects high-cost adverse outcomes, confirming that the measure can 
appropriately distinguish that better providers tend to have fewer 
downstream re-hospitalizations and post-acute care use.\961\ Thus, by 
being able to differentiate between good and poor performance, the 
measure is able to accurately assess a hospital's efficiency as 
compared to other hospitals.
---------------------------------------------------------------------------

    \961\ The submission materials, including the testing results, 
are available at: https://www.qualityforum.org/ProjectMeasures.aspx?projectID=86056&cycleNo=2&cycleYear=2020.
---------------------------------------------------------------------------

    Finally, to address a commenter's feedback that the measure should 
be grounded in current best evidence and practices, we note that prior 
to being proposed in the FY 2023 IPPS/LTCH PPS proposed rule, the NQF 
and MAP reviewed the revised MSPB Hospital measure against the measure 
evaluation criteria, which include importance to measure and report, 
scientific acceptability of measure properties, feasibility, usability 
and use, and related/competing measures, to ensure the measure's 
suitability, and subsequently recommended the measure for endorsement 
and implementation in the Hospital IQR Program.
    Comment: A commenter recommended that CMS delay adopting the 
revised MSPB Hospital measure in the Hospital IQR Program until the FY 
2025 payment determination due the impact that COVID-19 could have on 
measure calculations.
    Response: We appreciate the commenter's concern that the impact of 
COVID-19 on the healthcare system has been profound. We intend to 
closely monitor the effect of COVID-19 on the revised MSPB Hospital 
measure and the Hospital IQR Program. As noted previously, by 
construction the revised MSPB Hospital measure adjusts for COVID-19 
when risk adjusting by the DRG of the hospitalization. Additionally, 
for the MSPB Hospital measure currently used in the Hospital VBP 
Program, our analyses using data from the first three quarters of 2021 
showed that admission volumes returned to near pre-COVID-19 levels, 
while cost ratios were not significantly different for episodes with 
and without COVID-19. Based on the findings

[[Page 49263]]

indicating that COVID-19 had a small impact on the measure in 2021, we 
did not propose to suppress the measure for the purposes of Hospital 
VBP Program scoring. We disagree about delaying the implementation of 
the measure in the Hospital IQR Program as this would prevent 
stakeholders from familiarizing themselves with the revised version of 
the measure and would further delay the potential future implementation 
of the measure in the Hospital VBP Program.
    After consideration of the public comments we received, we are 
finalizing our proposal as proposed.
i. Hospital-Level Risk-Standardized Complication Rate (RSCR) Following 
Elective Primary Total Hip Arthroplasty (THA) and/or Total Knee 
Arthroplasty (TKA) Measure (NQF#1550) Beginning With the FY 2024 
Payment Determination
(1) Background
    In the FY 2013 IPPS/LTCH PPS final rule (77 FR 53516 through 53521) 
and the FY 2015 IPPS/LTCH PPS final rule (79 FR 50062 through 50063), 
we adopted the Hospital-Level RSCR Following Elective Primary THA/TKA 
(hereinafter referred to as the THA/TKA Complication measure) for use 
in both the Hospital IQR and Hospital VBP Programs, respectively. We 
refer readers to the FY 2016 IPPS/LTCH PPS final rule (80 FR 49674) for 
information on the previously adopted measure specifications. Although 
the measure is still included in the Hospital VBP Program and measure 
results are still publicly reported, in the FY 2018 IPPS/LTCH PPS final 
rule (83 FR 41150) we finalized the removal of the measure from the 
Hospital IQR Program as part of agency-wide efforts to reduce provider 
burden since the measure was also being reported under the Hospital VBP 
Program. We, however, believe it is important to assess the quality of 
care provided to Medicare beneficiaries who undergo one or both of 
these procedures. In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 
28532 through 28534), we proposed to adopt the re-evaluated form of the 
THA/TKA Complication measure with an expanded measure outcome. Since 
the measure was removed from the Hospital IQR Program, it has been 
revised to include 26 additional mechanical complication ICD-10 codes 
which were identified during measure maintenance. The statutory 
requirements of the Hospital VBP Program are set forth in section 
1886(o) of the Social Security Act. As noted at 42 CFR 412.164(b) 
measures must be publicly reported for one year prior to the beginning 
of the performance period in the Hospital VBP Program. Therefore, we 
proposed to adopt this measure into the Hospital IQR Program with the 
intention to eventually propose the updated measure into the Hospital 
VBP Program after the required year of public reporting in Hospital IQR 
Program.
    THA and TKA are commonly performed procedures for the Medicare 
population that improve quality of life. From 2016 to 2019, there were 
1,012,190 THA and TKA procedures performed on Medicare fee-for-service 
(FFS) patients 65 years and older.\962\ The number of procedures being 
performed has steadily increased over the last decade and is projected 
to reach over four million by 2030.\963\ \964\ While these procedures 
can dramatically improve a person's quality of life, they are costly. 
Based on projections of the annual demand for THA and TKA procedures, 
researchers estimate that Medicare expenditures on Total Joint 
Arthroplasty (TJA) could climb from $3.95 billion and $7.42 billion for 
both primary THA and TKA, respectively, in 2005, \965\ to $50 billion 
by 2030.\966\ Complications following elective THA and TKA procedures 
are rare, but the results can be devastating. Evidence shows that 
periprosthetic joint infection rates following THA and TKA range from 
0.7 percent to 1.6 percent depending upon the population. \967\ \968\ 
Reported 30- and 90-day death rates following THA range from 0.4 
percent to 0.7 percent.\969\ Rates for pulmonary embolism following THA 
range from 0.5 percent to 1.22 percent \970\ and range from 0.5 percent 
to 0.9 percent \971\ following TKA. Rates for wound infection in 
Medicare population-based studies vary between 0.21 percent and 1.0 
percent.\972\ Rates for sepsis/septicemia range from 0.09 percent 
during the index admission to 0.3 percent 90 days following discharge 
for primary TKA. Rates for bleeding and hematoma following TKA range 
from 0.94 percent to 1.7 percent.\973\
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    \962\ Triche, E., J.N. Grady, and J.e.a. Debuhr, Procedure 
Specific Complication Measure Updates and Specifications Report: 
Elective Primary Total Hip Arthroplasty (THA) and/or Total Knee 
Arthroplasty (TKA) Risk-Standardized Complication Measure (Version 
9.0). 2020.
    \963\ Kurtz, S., et al., Projections of primary and revision hip 
and knee arthroplasty in the United States from 2005 to 2030. J Bone 
Joint Surg Am, 2007. 89(4): p. 780-5.
    \964\ Kurtz, S.M., et al., Impact of the economic downturn on 
total joint replacement demand in the United States: updated 
projections to 2021. J Bone Joint Surg Am, 2014. 96(8): p. 624-30.
    \965\ Kurtz, S.M., et al., Future clinical and economic impact 
of revision total hip and knee arthroplasty. J Bone Joint Surg Am, 
2007. 89 Suppl 3: p. 144-51.
    \966\ Wilson, N.A., et al., Hip and knee implants: current 
trends and policy considerations. Health Aff (Millwood), 2008. 
27(6): p. 1587-98.
    \967\ Kurtz S, Ong K, Lau E, Bozic K, Berry D, Parvizi J. 
Prosthetic joint infection risk after TKA in the Medicare 
population. Clin Orthop Relat Res. 2010; 468:5.
    \968\ Bozic KJ, Grosso LM, Lin Z, et al. Variation in hospital-
level risk-standardized complication rates following elective 
primary total hip and knee arthroplasty. J Bone Joint Surg Am. 
2014;96(8):640[hyphen]647. doi:10.2106/JBJS.L.01639.
    \969\ Soohoo NF, Farng E, Lieberman JR, Chambers L, Zingmond DS. 
Factors That Predict Short-term Complication Rates After Total Hip 
Arthroplasty. Clin Orthop Relat Res. Sep 2010;468(9):2363-2371.
    \970\ Arshi A, Leong NL, Wang C, Buser Z, Wang JC, SooHoo NF. 
Outpatient total hip arthroplasty in the United States: A 
population-based comparative analysis of complication rates. J Am 
Acad Orthop Surg. 2019;27(2):61-7.
    \971\ Khatod M, Inacio M, Paxton EW, et al. Knee replacement: 
epidemiology, outcomes, and trends in Southern California: 17,080 
replacements from 1995 through 2004. Acta Orthop. Dec 
2008;79(6):812-819.
    \972\ Browne J, Cook C, Hofmann A, Bolognesi M. Postoperative 
morbidity and mortality following total knee arthroplasty with 
computer navigation. Knee. Mar 2010;17(2):152-156.
    \973\ Huddleston JI, Maloney WJ, Wang Y, Verzier N, Hunt DR, 
Herndon JH. Adverse Events After Total Knee Arthroplasty: A National 
Medicare Study. The Journal of Arthroplasty. 2009;24(6, Supplement 
1):95-100.
---------------------------------------------------------------------------

    The updated THA/TKA Complication measure was listed in the publicly 
available document entitled ``List of Measures Under Consideration for 
December 1, 2021'' \974\ (MUC List) with identification number MUC2021-
118. The MAP reviewed the updated measure and voted to conditionally 
support the measure for rulemaking for use in the Hospital IQR Program 
pending NQF review and endorsement of the measure update. The MAP Rural 
Health Advisory Group reviewed this updated measure on December 8, 2021 
and voted to majority support the measure given that there would be no 
undue consequences for rural hospitals.\975\
---------------------------------------------------------------------------

    \974\ https://www.cms.gov/files/document/measures-under-consideration-list-2021-report.pdf.
    \975\ https://www.qualityforum.org/Publications/2022/03/MAP_2021-2022_Considerations_for_Implementing_Measures_Final_Report_-_Clinicians,_Hospitals,_and_PAC-LTC.aspx.
---------------------------------------------------------------------------

    The NQF re-endorsed the original measure in July of 2021; and we 
intend to submit the updated measure to NQF for endorsement in Fall 
2024.\976\ We note that section 1866(b)(3)(B)(viii)(IX)(aa) of the Act 
requires that any measure specified by the Secretary must have been 
endorsed by the entity with a contract under section 1890(a) of the Act 
(the NQF is the entity that currently holds this

[[Page 49264]]

contract). Under section 1886(b)(3)(B)(viii)(IX)(bb) of the Act, in the 
case of a specified area or medical topic determined appropriate by the 
Secretary for which a feasible and practical measure has not been 
endorsed by the entity with a contract under section 1890(a) of the 
Act, the Secretary may specify a measure that is not so endorsed as 
long as due consideration is given to measures that have been endorsed 
or adopted by a consensus organization identified by the Secretary. We 
reviewed NQF-endorsed measures and were unable to identify any other 
NQF-endorsed measures on this topic, and, therefore, we believe the 
exception in section 1886(b)(3)(B)(viii)(IX)(bb) of the Act applies.
---------------------------------------------------------------------------

    \976\ National Quality Forum. Hospital-level risk-standardized 
complication rate (RSCR) following elective primary total hip 
arthroplasty (THA) and/or total knee arthroplasty (TKA) Measure 
Specifications. 2021. https://www.qualityforum.org/QPS/1550.
---------------------------------------------------------------------------

(2) Overview of Measure
    The original THA/TKA Complication measure (NQF # 1550) was 
previously removed from the Hospital IQR Program, but is currently 
implemented in the Hospital VBP Program (79 FR 50062 through 50063). 
Adopting the newly refined version of this measure into the Hospital 
IQR Program will expand the measure outcome to include 26 additional 
mechanical complication ICD-10 codes. We note that aside from the 
additional ICD-10 codes, measure specifications align with the version 
of the measure currently in use in the Hospital VBP Program.
(3) Data Sources
    The updated THA/TKA Complication measure uses index admission 
diagnoses and in-hospital comorbidity data from Medicare Part A claims. 
Additional comorbidities prior to the index admission are assessed 
using Part A inpatient, outpatient, and Part B office visit Medicare 
claims in the 12 months prior to index (initial) admission. Enrollment 
status is obtained from the Medicare Enrollment Database which contains 
beneficiary demographic, benefit/coverage, and vital status 
information. We proposed to use claims data with admission dates 
beginning from April 1, 2019-March 31, 2022 (excluding data from the 
period covered by the ECE granted by CMS related to the COVID-19 Public 
Health Emergency (PHE)) that is associated with the FY 2024 payment 
determination. As a claims-based measure, hospitals will not be 
required to submit additional data for calculating the measure.
(4) Outcome
    The outcome for the updated THA/TKA Complication measure is any 
complication occurring during the index admission (not coded as present 
on admission (POA)) to 90 days post-date of the index admission. 
Complications are counted in the measure only if they occur during the 
index hospital admission or during a readmission. The complication 
outcome is a dichotomous (yes/no) outcome. If a patient experiences one 
or more of these complications in the applicable time period, the 
complication outcome for that patient is counted in the measure as a 
``yes.''
    The updated measure includes the following 26 additional clinically 
vetted mechanical complication ICD-10 codes:
     M96.65 Fracture of pelvis following insertion of 
orthopedic implant, joint prosthesis, or bone plate;
     M96.661 Fracture of femur following insertion of 
orthopedic implant, joint prosthesis, or bone plate, right leg;
     M96.662 Fracture of femur following insertion of 
orthopedic implant, joint prosthesis, or bone plate, left leg;
     M96.669 Fracture of femur following insertion of 
orthopedic implant, joint prosthesis, or bone plate, unspecified leg;
     M96.671 Fracture of tibia or fibula following insertion of 
orthopedic implant, joint prosthesis, or bone plate, right leg;
     M96.672 Fracture of tibia or fibula following insertion of 
orthopedic implant, joint prosthesis, or bone plate, left leg;
     M96.679 Fracture of tibia or fibula following insertion of 
orthopedic implant, joint prosthesis, or bone plate, unspecified leg;
     M97.01XA Periprosthetic fracture around internal 
prosthetic right hip joint, initial encounter;
     M97.01XD Periprosthetic fracture around internal 
prosthetic right hip joint, subsequent encounter;
     M97.01XS Periprosthetic fracture around internal 
prosthetic right hip joint, sequela;
     M97.02XA Periprosthetic fracture around internal 
prosthetic left hip joint, initial encounter;
     M97.02XD Periprosthetic fracture around internal 
prosthetic left hip joint, subsequent encounter;
     M97.02XS Periprosthetic fracture around internal 
prosthetic left hip joint, sequela;
     M97.11XA Periprosthetic fracture around internal 
prosthetic right knee joint, initial encounter;
     M97.11XD Periprosthetic fracture around internal 
prosthetic right knee joint, subsequent encounter;
     M97.11XS Periprosthetic fracture around internal 
prosthetic right knee joint, sequela;
     M97.12XA Periprosthetic fracture around internal 
prosthetic left knee joint, initial encounter;
     M97.12XD Periprosthetic fracture around internal 
prosthetic left knee joint, subsequent encounter;
     M97.12XS Periprosthetic fracture around internal 
prosthetic left knee joint, sequela;
     M97.8XXA Periprosthetic fracture around other internal 
prosthetic joint, initial encounter;
     M97.8XXD Periprosthetic fracture around other internal 
prosthetic joint, subsequent encounter;
     M97.8XXS Periprosthetic fracture around other internal 
prosthetic joint, sequela;
     M97.9XXA Periprosthetic fracture around unspecified 
internal prosthetic joint, initial encounter;
     M97.9XXD Periprosthetic fracture around unspecified 
internal prosthetic joint, subsequent encounter;
     M97.9XXS Periprosthetic fracture around unspecified 
internal prosthetic joint, sequela; and
     M96.69 Fracture of other bone following insertion of 
orthopedic implant, joint prosthesis, or bone plate.
    During routine measure maintenance, our analyses showed the 
addition of these clinically relevant codes contributed to an increase 
in the THA/TKA national observed complication rate. Findings 
demonstrated an increase of approximately 0.5 percent (from 2.42 
percent to 2.93 percent) in the THA/TKA national observed complication 
rate when evaluated for the FY 2021 performance period (April 1, 2016 
through March 30, 2019). These findings suggest that the expanded 
outcome will allow the updated THA/TKA Complication measure to capture 
a more complete outcome.
    The updated THA/TKA Complication measure as with the version of 
measure currently implemented in the Hospital VBP Program (86 FR 45279 
through 45281), excludes admissions with a principal or secondary 
COVID-19 diagnosis, POA, from the measure outcome, as outcomes for 
patients with COVID-19 who are receiving THA/TKA surgery may differ 
from patients without COVID-19. The four medical complication outcomes 
that this applies to are:
    (1) Acute myocardial infarction (AMI) during a subsequent inpatient 
admission that occurs within seven days from the start of the index 
admission; (2) pneumonia or other acute respiratory complication during 
a subsequent inpatient admission that occurs within seven days from the 
start of the index admission, (3) sepsis/septicemia/shock during a 
subsequent inpatient

[[Page 49265]]

admission that occurs within seven days from the start of the index 
admission, and (4) pulmonary embolism during the index admission or a 
subsequent inpatient admission within 30 days from the start of the 
index admission. In these cases, readmissions with a principal or 
secondary diagnosis POA of COVID-19 (U07.1) will be removed from the 
numerator.
    We refer readers to the Hip and Knee Arthroplasty Complications 
(ZIP) folder on the CMS.gov Measure Methodology website at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology for measure 
specification details on this newly restructured measure.
(5) Cohort
    The updated THA/TKA Complication measure continues to include 
Medicare FFS beneficiaries, aged 65 years or older, having a qualifying 
elective primary THA or TKA procedure during the index admission. 
Beneficiaries must be enrolled in Medicare FFS Part A and Part B for 
the 12 months prior to the date of admission and enrolled in Part A 
during the index admission. We also note that the updated THA/TKA 
Complication measure excludes admissions with a principal or secondary 
COVID-19 diagnosis, POA, from the measure cohort.
(6) Risk Adjustment
    The updated THA/TKA Complication measure is risk adjusted using 
clinically relevant risk variables identified from inpatient and 
outpatient claims in the 12 months prior to the procedure. We will also 
include a covariate adjustment for patient history of COVID-19 in the 
12 months prior to the admission.
(7) Measure Calculation
    The updated THA/TKA Complication measure will be calculated using a 
hospital risk-standardized complication rate by producing a ratio of 
the number of ``predicted'' complications (that is, the adjusted number 
of complications at a specific hospital based on its patient 
population) to the number of ``expected'' complications (that is, the 
number of complications if an average quality hospital treated the same 
patients) for each hospital and then multiplying the ratio by the 
national observed complication rate. For each hospital, the numerator 
of the ratio is the number of complications within the specified time 
period (up to 90 days) predicted on the basis of the hospital's 
performance with its observed case mix, and the denominator is the 
number of complications expected based on the nation's performance with 
that hospital's case mix. This approach is analogous to a ratio of 
``observed'' to ``expected'' used in other types of statistical 
analyses. It conceptually allows for a comparison of a particular 
hospital's performance given its case mix to an average hospital's 
performance with the same case mix.
    We proposed to adopt the newly restructured version of the THA/TKA 
Complication measure beginning with admission dates from April 1, 2019-
March 31, 2022 (excluding data from the period covered by the ECE 
granted by CMS related to the COVID-19 Public Health Emergency (PHE)) 
affecting the FY 2024 payment determination.
(8) Public Reporting
    We will also publicly report the updated THA/TKA Complication 
measure on the Compare tool hosted by HHS, currently available at: 
https://www.medicare.gov/care-compare, or its successor website, 
beginning in 2023.
    We invited public comment on this proposal.
    Comment: Many commenters expressed their support for the proposed 
adoption into the Hospital IQR Program of the updated THA/TKA 
Complication measure beginning with the FY 2024 payment determination. 
A commenter noted that they believe the additional complications codes 
are clinically appropriate to be paired with arthroplasty and will 
improve the measure's accuracy. A few commenters noted that they 
believe measuring and reporting risk-standardized complications rates 
will inform health care providers about opportunities to improve care, 
strengthen incentives for quality improvement, and promote improvements 
in the quality of care received by patients and the outcomes they 
experience. A few commenters reiterated that they believe this measure 
will provide patients with beneficial information that could guide 
their choices regarding where they seek care for these procedures, 
increase transparency for consumers and that it has the potential to 
lower health care costs by decreasing the likelihood of costly 
readmissions associated with these complications.
    Response: We thank the commenters for their support.
    Comment: A few commenters did not support the proposed adoption of 
the updated THA/TKA Complication measure. A commenter expressed concern 
that, because they believe that the majority of these procedures take 
place in outpatient settings, hospitals subject to this measure will be 
caring for the sickest patients and therefore subject to improper 
penalties. A commenter did not support the proposed adoption of the 
updated the THA/TKA Complication measure because they did not believe 
the updated measure accurately reflects hospital performance. 
Specifically, they expressed concern that the ICD-10 codes proposed to 
be included reflect falls and fractures since THA/TKA patients are at a 
greater risk for falls regardless of the level of care provided at the 
hospital. A commenter recommended that using the ratio of observed to 
expected would be an easier concept to understand than the currently 
used ratio of predicted to expected.
    Response: We thank the commenters for their feedback and 
acknowledge their concerns. We are monitoring the shifts of THA/TKA 
from the inpatient to outpatient setting as well as the potential 
impacts on this inpatient only measure. The proposed updated THA/TKA 
Complication measure is case mix adjusted for patient comorbidities and 
is a relative performance measure for hospitals performing these 
elective THA/TKA procedures.\977\ As such, we believe that this measure 
accurately reflects hospital performance even if patients receiving 
these procedures in the inpatient setting tend to be sicker, on 
average, than those treated in an outpatient setting.
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    \977\ For more detailed measure specifications, we refer readers 
to the ``2022 Procedure-Specific Complication Measure Updates and 
Specifications: THA/TKA'' at the CMS.gov QualityNet website at: 
https://qualitynet.cms.gov/inpatient/measures/complication/methodology.
---------------------------------------------------------------------------

    We believe this updated measure provides an accurate representation 
of hospital performance. As noted in the FY 2023 IPPS/LTCH PPS proposed 
rule (87 FR 28532 through 28534), during routine measure maintenance, 
our internal analyses showed the addition of these clinically relevant 
codes contributed to an increase in the THA/TKA national observed 
complication rate. Findings demonstrated an increase of approximately 
0.5 percent (from 2.42 percent to 2.93 percent) in the THA/TKA national 
observed complication rate when evaluated for the FY 2021 performance 
period (April 1, 2016 through March 30, 2019). These findings suggest 
that the expanded outcome will allow the updated THA/TKA Complication 
measure to capture a more complete assessment of complications. We note 
while conducting these analyses, orthopedic surgeons and clinical 
coding experts vetted the additional 26 mechanical complication ICD-10 
codes and agreed they should be included. Thus, these additions are

[[Page 49266]]

directly responsive to input from stakeholders, including hospitals.
    Lastly, we thank the commenter for their recommendation related to 
the reporting ratio. We reiterate that, as proposed in the FY 2023 
IPPS/LTCH PPS proposed rule (87 FR 28532 through 28534), the proposed 
updated THA/TKA Complication measure is calculated using a hospital 
risk-standardized complication rate by producing a ratio of the number 
of ``predicted'' complications (that is, the adjusted number of 
complications at a specific hospital based on its patient population) 
to the number of ``expected'' complications (that is, the number of 
complications if an average quality hospital treated the same patients) 
for each hospital and then multiplying the ratio by the national 
observed complication rate. For each hospital, the numerator of the 
ratio is the number of complications within the specified time period 
(up to 90 days) predicted on the basis of the hospital's performance 
with its observed case mix, and the denominator is the number of 
complications expected based on the nation's performance with that 
hospital's case mix.\978\ This approach is analogous to a ratio of 
``observed'' to ``expected'' used in other types of statistical 
analyses, and it conceptually allows for a comparison of a particular 
hospital's performance given its case mix to an average hospital's 
performance with the same case mix. Further details on the predicted/
expected calculation approach are provided within the THA/TKA 
Complication Measure Methodology Report and other publicly available 
resources on our QualityNet website, available at: https://qualitynet.cms.gov/inpatient/measures/complication/methodology.
---------------------------------------------------------------------------

    \978\ For more detailed measure specifications, we refer readers 
to the ``2022 Procedure-Specific Complication Measure Updates and 
Specifications: THA/TKA'' at the CMS.gov QualityNet website at: 
https://qualitynet.cms.gov/inpatient/measures/complication/methodology.
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    Comment: A few commenters expressed concern that the required data 
collection will be burdensome to hospitals.
    Response: We respectfully disagree that the proposed updated THA/
TKA Complication measure with the additional 26 complication codes will 
cause significant data collection burden. Hospitals will not be 
required to submit additional data for calculating the measure as it is 
a claims-based measure. As stated in the in the FY 2023 IPPS/LTCH PPS 
proposed rule (87 FR 28532 through 28534), the proposed updated THA/TKA 
Complication measure uses index admission diagnoses and in-hospital 
comorbidity data from Medicare Part A claims. Additional comorbidities 
prior to the index admission are assessed using Part A inpatient, 
outpatient, and Part B office visit Medicare claims in the 12 months 
prior to index (initial) admission. Enrollment status is obtained from 
the Medicare Enrollment Database which contains beneficiary 
demographic, benefit/coverage, and vital status information.\979\
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    \979\ For more detailed measure specifications, we refer readers 
to the ``2022 Procedure-Specific Complication Measure Updates and 
Specifications: THA/TKA'' at the CMS.gov QualityNet website at: 
https://qualitynet.cms.gov/inpatient/measures/complication/methodology.
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    Comment: A few commenters expressed concern that the proposed 
updates to the THA/TKA Complication measure would result in two 
similar, but not identical, measures in the Hospital IQR Program and 
the Hospital VBP Program. The commenters believe that public reporting 
of both measures, which could yield different results, has the 
potential to be misleading or confusing for providers and patients. A 
commenter requested clarification on how the versions of the measure 
will be distinguished in public reporting and which version of the 
measure will be in use for the Overall Hospital Quality Star Ratings.
    Response: We acknowledge the commenters' concerns that two slightly 
different versions of the measure would be in use in the Hospital IQR 
and Hospital VBP Programs simultaneously. However, the statutory 
requirements of the Hospital VBP Program, as set forth in section 
1886(o) of the Act and at 42 CFR 412.164(b), state that measures must 
be publicly reported for one year prior to the beginning of the 
performance period in the Hospital VBP Program. Therefore, we proposed 
to adopt this updated version of the THA/TKA Complication measure into 
the Hospital IQR Program with the intention to consider proposing the 
updated measure for use in the Hospital VBP Program in the future. As 
proposed in the FY 2023 IPPS/LTCH PPS proposed rule, the proposed 
updated THA/TKA Complication measure would be publicly reported on the 
Compare tool hosted by HHS, currently available at: https://www.medicare.gov/care-compare, or its successor website, beginning in 
2023 (87 FR 28532 through 28534). Overall Hospital Quality Star Ratings 
utilize the publicly reported version of the measure on the Compare 
tool, as finalized in the CY 2021 OPPS/ASC final rule (85 FR 86202). 
That is, those ratings would use the proposed updated THA/TKA 
Complication measure with the additional 26 complication codes once it 
is publicly reported beginning in 2023. Results for the THA/TKA 
Complication measure currently implemented in the Hospital VBP Program 
will continue to be available according to program policies (for 
example, on the Provider Data Catalog) as noted in the FY 2015 IPPS/
LTCH PPS final rule (79 FR 50062 through 50063).
    Comment: A commenter expressed interest in obtaining detailed 
information about all relevant complications, including the 26 newly 
added complications, so they can prepare for potential implementation 
of the new measure.
    Response: We thank the commenter for their interest in obtaining 
the detailed information on the newly added mechanical complication 
ICD-10 codes. We refer the commenter to the measure specifications as 
proposed in the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28532 
through 28534) and ICD-10 resources provided publicly here: https://www.cms.gov/medicare/icd-10/2023-icd-10-pcs. The annual Procedure-
Specific Complication Measure Updates and Specifications Report will be 
posted during the 2023 spring preview period and will contain any 
further details related to the added codes. This is expected to be 
available on our QualityNet website at: https://qualitynet.cms.gov/inpatient/measures/complication/methodology.
    Comment: A commenter was concerned by the lack of inclusion of 
social risk factors in the measure.
    Response: We appreciate commenter's feedback. We are committed to 
measuring and improving health equity and addressing social risk 
factors in quality measurement. During the last NQF endorsement 
maintenance submission for the original THA/TKA Complication measure 
prior to 2022, comprehensive testing was completed which included an 
assessment of the impact of social risk as captured by dual eligibility 
and the AHRQ SES Index.\980\ The AHRQ SES Index score considers aspects 
of socioeconomic status and is computed using U.S. census data, and 
considers factors including median household income, percentage of 
persons below the Federal poverty line, unemployment, education, 
property value, and percentage of persons in crowded households at the 
9-digit zip code level.\981\ We found wide variation

[[Page 49267]]

in the prevalence of the two social risk factors we examined, with a 
large proportion of hospitals treating zero patients with these risk 
factors. We also found that both had some association with complication 
risk. However, adjustment for these factors did not have a material 
impact on hospital RSCRs.\982\ Our decisions about which risk factors 
should be included in each measure's risk adjustment model are based on 
whether inclusion of such variables is likely to make the measures more 
successful at illuminating quality differences and motivating quality 
improvement. Given these empiric findings and program considerations, 
we chose not to include these two social risk factors in the final risk 
model. In presenting these results and interpretation, the NQF re-
endorsed the original measure (NQF #1550) in June of 2021 without 
adjustment for patient-level social risk factors.\983\ We acknowledge 
the importance of balancing these competing considerations and we plan 
to continue to reevaluate this risk adjustment model and available risk 
factors on an ongoing basis, with the goal of producing the most 
accurate and fair risk adjustment models for assessing provider 
performance. Further details related to social risk testing for this 
measure can be found from downloading the measure specifications from 
NQF's Surgery Fall Cycle 2020 project here: https://nqfappservicesstorage.blob.core.windows.net/proddocs/22/Fall/2020/measures/1550/shared/1550.zip.
---------------------------------------------------------------------------

    \981\ Bonito A, Bann C, Eicheldinger C, Carpenter L. Creation of 
new race-ethnicity codes and socioeconomic status (SES) indicators 
for Medicare beneficiaries. Final Report, Sub-Task. 2008;2.
    \982\ National Quality Forum. Surgery Fall Cycle 2020. Measure 
Testing (subcriteria 2a2, 2b1-2b6) Document. November 3, 2020. 
Available at: https://nqfappservicesstorage.blob.core.windows.net/proddocs/22/Fall/2020/measures/1550/shared/1550.zip.
    \983\ National Quality Forum. Consensus Standards Approval 
Committee--Measure Evaluation Web Meeting, June 2021. Available at: 
https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=95862.
---------------------------------------------------------------------------

    Comment: A few commenters encouraged CMS to seek NQF endorsement of 
this measure.
    Response: We thank the commenters for their feedback. The NQF re-
endorsed the original measure (NQF #1550) in June of 2021; \984\ and we 
intend to submit the updated measure to the NQF for endorsement 
maintenance in Fall 2024.
---------------------------------------------------------------------------

    \984\ National Quality Forum. Consensus Standards Approval 
Committee--Measure Evaluation Web Meeting, June 2021. Available at: 
https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=95862.
---------------------------------------------------------------------------

    After consideration of the public comments we received, we are 
finalizing our proposal as proposed.
6. Refinements to Current Measures in the Hospital IQR Program Measure 
Set
    In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28534), we 
proposed refinements to two measures currently in the Hospital IQR 
Program measure set--Hospital-Level, Risk-Standardized Payment 
Associated with an Episode-of-Care for Primary Elective THA and/or TKA 
and Excess Days in Acute Care (EDAC) After Hospitalization for Acute 
Myocardial Infarction (AMI)--beginning with the FY 2024 payment 
determination. We provide more details on our proposals in the 
subsequent discussion.
a. Refinement of the Hospital-Level, Risk-Standardized Payment 
Associated With an Episode of Care for Primary Elective Total Hip 
Arthroplasty (THA) and/or Total Knee Arthroplasty (TKA) Measure (NQF 
#3474) Beginning With the FY 2024 Payment Determination and for 
Subsequent Years
(1) Background
    In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28534 through 
28536), we proposed a refinement to the Hospital-Level, Risk-
Standardized Payment Associated with an Episode of Care for Primary 
Elective THA and/or TKA Measure (NQF #3474) (hereinafter referred to as 
the THA/TKA Payment measure), which expands the measure outcome to 
include 26 clinically vetted mechanism complication ICD-10 codes, for 
the FY 2024 payment determination and subsequent years. For the 
purposes of describing the refinement of this measure, we note that the 
``outcome'' is defined as hospital-level, risk-standardized payment 
associated with a 90-day episode-of-care for primary elective THA and/
or TKA.
    The THA/TKA Payment measure was first adopted into the Hospital IQR 
Program in the FY 2016 IPPS/LTCH PPS final rule (80 FR 49680) for the 
FY 2018 payment determination and subsequent years. Prior to adopting 
the measure, the MAP conditionally supported it on December 10, 2014, 
pending a timely review by the NQF Cost and Resource Use Standing 
Committee.\985\ The MAP recommended harmonizing and determining the 
most parsimonious approach to measure the costs of hip and knee 
replacements to minimize the burden and confusion of competing 
methodologies.\986\ The original measure was initially NQF endorsed in 
June 2019 and will be submitted for the first re-endorsement in Fall 
2022.\987\
---------------------------------------------------------------------------

    \985\ https://www.qualityforum.org/Publications/2014/01/MAP_Pre-Rulemaking_Report__2014_Recommendations_on_Measures_for_More_than_20_Federal_Programs.aspx.
    \986\ https://www.qualityforum.org/Publications/2014/01/MAP_Pre-Rulemaking_Report__2014_Recommendations_on_Measures_for_More_than_20_Federal_Programs.aspx.
    \987\ https://www.qualityforum.org/QPS/QPSTool.aspx.
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    The proposed refined measure was included on a publicly available 
document entitled ``List of Measures Under Consideration for December 
1, 2021'' \988\ (MUC List) with identification number MUC2021-120. The 
refined measure was reviewed by the MAP and conditionally supported for 
rulemaking pending NQF review and endorsement of the measure 
update.\989\
---------------------------------------------------------------------------

    \988\ https://www.qualityforum.org/Publications/2022/03/MAP_2021-2022_Considerations_for_Implementing_Measures_Final_Report_-_Clinicians,_Hospitals,_and_PAC-LTC.aspx.
---------------------------------------------------------------------------

    As noted earlier we intend to submit the revised measure for the 
first NQF re-endorsement in the Fall of 2022. We note that section 
1866(b)(3)(B)(viii)(IX)(aa) of the Act requires that any measure 
specified by the Secretary must have been endorsed by the entity with a 
contract under section 1890(a) of the Act (the NQF is the entity that 
currently holds this contract). Under section 
1886(b)(3)(B)(viii)(IX)(bb) of the Act, in the case of a specified area 
or medical topic determined appropriate by the Secretary for which a 
feasible and practical measure has not been endorsed by the entity with 
a contract under section 1890(a) of the Act, the Secretary may specify 
a measure that is not so endorsed as long as due consideration is given 
to measures that have been endorsed or adopted by a consensus 
organization identified by the Secretary. We reviewed NQF-endorsed 
measures and were unable to identify any other NQF-endorsed measures on 
this topic, and, therefore, we believe the exception in section 
1886(b)(3)(B)(viii)(IX)(bb) of the Act applies.
(2) Overview of Measure
    The proposed measure refinement will expand the measure outcome to 
include 26 mechanical complication ICD-10 codes to the outcome. This 
refinement is in alignment with the refinement of the updated THA/TKA 
Complication measure in section IX.E.5.i. of this final rule. The data 
sources, cohort, inclusion and exclusion criteria, and risk adjustment 
remain substantively unchanged. We proposed this measure refinement for 
the FY 2024 payment determination and subsequent years, reflecting data 
collected beginning from April 1, 2019 through March 31, 2022 
admissions (excluding data from the period covered by the ECE

[[Page 49268]]

granted by CMS related to the COVID-19 PHE).
(3) Data Sources
    We did not propose any changes to the data sources for the THA/TKA 
Payment measure. The measure uses Part A and Part B Medicare 
administrative claims data that contain payments for Medicare FFS 
beneficiaries who were hospitalized and underwent an elective THA/TKA. 
This measure uses three years of data.
(4) Outcome
    The primary outcome of this measure is the hospital-level risk-
standardized payment for an elective primary THA/TKA episode-of-care. 
This measure captures payments for Medicare FFS patients across 
multiple care settings, services, and supplies (inpatient, outpatient, 
skilled nursing facility, home health, hospice, physician/clinical 
laboratory/ambulance services, and durable medical equipment, 
prosthetics/orthotics, and supplies). This measure includes patient 
copayments as well as payments from coinsurance.
    This measure uses the index admission for an elective primary THA/
TKA to 90 days postadmission. The measurement includes all payments for 
the first 30 days after admission and only certain payments based on a 
pre-defined set of care settings and services for days 31-90. Payments 
in the 31-90-day window include readmissions for complications as 
defined in the THA/TKA Complication measure (Mechanical Complications 
and Periprosthetic Joint Infection/Wound Infection and Other Wound 
Complications) (see section IX.E.5.i. of this final rule for discussion 
on this measure), therefore, the expansion of the definition of 
mechanical complications impacts this measure as well.
    As we did not propose any changes besides the addition of the 26 
mechanical complication codes, we refer readers to the FY 2016 IPPS/
LTCH PPS final rule (80 FR 49674) for information on the previously 
adopted measure specifications. We refer readers to Hip and Knee 
Arthroplasty Payment (ZIP) folder on the CMS.gov Methodology website 
at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology for 
updated specifications on this measure.
    The proposed additional 26 mechanical complication ICD-10 codes are 
the following:
     M96.65 Fracture of pelvis following insertion of 
orthopedic implant, joint prosthesis, or bone plate;
     M96.661 Fracture of femur following insertion of 
orthopedic implant, joint prosthesis, or bone plate, right leg;
     M96.662 Fracture of femur following insertion of 
orthopedic implant, joint prosthesis, or bone plate, left leg;
     M96.669 Fracture of femur following insertion of 
orthopedic implant, joint prosthesis, or bone plate, unspecified leg;
     M96.671 Fracture of tibia or fibula following insertion of 
orthopedic implant, joint prosthesis, or bone plate, right leg;
     M96.672 Fracture of tibia or fibula following insertion of 
orthopedic implant, joint prosthesis, or bone plate, left leg;
     M96.679 Fracture of tibia or fibula following insertion of 
orthopedic implant, joint prosthesis, or bone plate, unspecified leg;
     M97.01XA Periprosthetic fracture around internal 
prosthetic right hip joint, initial encounter;
     M97.01XD Periprosthetic fracture around internal 
prosthetic right hip joint, subsequent encounter;
     M97.01XS Periprosthetic fracture around internal 
prosthetic right hip joint, sequela;
     M97.02XA Periprosthetic fracture around internal 
prosthetic left hip joint, initial encounter;
     M97.02XD Periprosthetic fracture around internal 
prosthetic left hip joint, subsequent encounter;
     M97.02XS Periprosthetic fracture around internal 
prosthetic left hip joint, sequela;
     M97.11XA Periprosthetic fracture around internal 
prosthetic right knee joint, initial encounter;
     M97.11XD Periprosthetic fracture around internal 
prosthetic right knee joint, subsequent encounter;
     M97.11XS Periprosthetic fracture around internal 
prosthetic right knee joint, sequela;
     M97.12XA Periprosthetic fracture around internal 
prosthetic left knee joint, initial encounter;
     M97.12XD Periprosthetic fracture around internal 
prosthetic left knee joint, subsequent encounter;
     M97.12XS Periprosthetic fracture around internal 
prosthetic left knee joint, sequela;
     M97.8XXA Periprosthetic fracture around other internal 
prosthetic joint, initial encounter;
     M97.8XXD Periprosthetic fracture around other internal 
prosthetic joint, subsequent encounter;
     M97.8XXS Periprosthetic fracture around other internal 
prosthetic joint, sequela;
     M97.9XXA Periprosthetic fracture around unspecified 
internal prosthetic joint, initial encounter;
     M97.9XXD Periprosthetic fracture around unspecified 
internal prosthetic joint, subsequent encounter;
     M97.9XXS Periprosthetic fracture around unspecified 
internal prosthetic joint, sequela; and
     M96.69 Fracture of other bone following insertion of 
orthopedic implant, joint prosthesis, or bone plate.
    We proposed the addition of these codes as proposed refinements to 
the THA/TKA Payment measure in response to recent analyses during 
routine measure maintenance showing that the addition of these codes 
will increase the national observed complication rate within the 
proposed THA/TKA Complication measure (NQF #1550) discussed earlier in 
this final rule. This demonstrates that the exclusion of these codes 
could result in missed complications. A number of clinicians in the 
field of orthopedics vetted the proposed addition of the new ICD-10 
codes to identify the complications of care. As described in section 
IX.E.5.i. of the preamble of this final rule, we anticipate the 
inclusion of these additional complication codes will increase the 
national observed complication rate and therefore may impact payments. 
Payments in the 31-90-day window are included readmissions for 
complications as defined in the proposed THA/TKA Complication measure 
(Mechanical Complications and Periprosthetic Joint Infection/Wound 
Infection and Other Wound Complications), therefore, the expansion of 
the definition of mechanical complications impacts the THA/TKA Payment 
measure as well. Since the payment measure uses these codes for payment 
included in the post-30-day window, we also anticipate an increase in 
total payments.
    These refinements to the measure will be effective for admissions 
from April 1, 2019 through March 31, 2022 (excluding data from the 
period covered by the ECE granted by CMS related to the COVID-19 PHE) 
and impacting the FY 2024 payment determination and subsequent years.
    We invited public comment on this proposal.
    Comment: Several commenters expressed their support for adoption of 
refinements to the THA/TKA Payment measure beginning with the FY 2024 
payment determination.
    Response: We thank the commenters for their support.

[[Page 49269]]

    Comment: A few commenters recommended we update the testing and 
achieve endorsement of the proposed refinements from NQF before 
implementation in the Hospital IQR Program. They additionally 
recommended we consider delaying measure adoption until NQF endorsement 
is achieved, if unable to be endorsed prior to the proposed 
implementation timeline. A commenter expressed that they do believe the 
refined measure to be an improvement over the current version, and 
while they agreed that it would capture complications being missed by 
the current measure version, they noted a concern about overlap between 
this episode payment measure and the MSPB Hospital measure that we are 
also proposing to adopt into to the Hospital IQR Program beginning with 
the FY 2024 payment determination.
    Response: We thank the commenters for their feedback. As noted in 
the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28534 through 28536), we 
intend to submit the revised measure for the first NQF re-endorsement 
cycle in the Fall of 2022. Under section 1886(b)(3)(B)(viii)(IX)(bb) of 
the Act, in the case of a specified area or medical topic determined 
appropriate by the Secretary for which a feasible and practical measure 
has not been endorsed by the entity with a contract under section 
1890(a) of the Act, the Secretary may specify a measure that is not so 
endorsed as long as due consideration is given to measures that have 
been endorsed or adopted by a consensus organization identified by the 
Secretary. We reviewed NQF-endorsed measures and were unable to 
identify any other NQF-endorsed measures on this topic, and, therefore, 
we believe the exception in section 1886(b)(3)(B)(viii)(IX)(bb) of the 
Act applies.
    We acknowledge the commenters concerns about overlap between the 
episode payment measure and the revised MSPB Hospital measure discussed 
in section IX.E.5.h. of the preamble of this final rule. Although the 
revised MSPB Hospital and THA/TKA Payment measures are aligned in how 
the outcome is determined by using the same claim standardization 
process, the revised MSBP Hospital measure cohort includes most, if not 
all inpatient admissions at a hospital (that is, it is broader) while 
the cohort of the THA/TKA Payment measure is more narrow and aligns 
with the THA/TKA Complication measure. The THA/TKA Payment measure was 
developed to be viewed in combination with the THA/TKA Complication 
measure as an indicator of value of care. Therefore, the revised MSPB 
Hospital and THA/TKA Payment measures serve different purposes.
    After consideration of the public comments we received, we are 
finalizing our proposal as proposed.
b. Refinement of the Excess Days in Acute Care (EDAC) After 
Hospitalization for Acute Myocardial Infarction (AMI) Measure (NQF 
#2881) Beginning With the FY 2024 Payment Determination and for 
Subsequent Years
(1) Background
    The EDAC After Hospitalization for AMI (hereinafter referred to as 
AMI EDAC) measure was initially adopted in the Hospital IQR Program in 
the FY 2016 IPPS/LTCH PPS final rule (FR 80 49660 through 49690) 
beginning with the FY 2018 payment determination. The measure is 
intended to capture the quality-of-care transitions provided to 
discharged patients hospitalized with AMI by collectively measuring a 
set of adverse acute care outcomes that can occur post-discharge: (1) 
ED visits, (2) observation stays, and (3) unplanned readmissions at any 
time during the 30 days post-discharge. Safely transitioning patients 
from hospital to home requires a complex series of tasks including 
timely and effective communication between providers, prevention of and 
response to complications, patient education about post-discharge care 
and self-management, timely follow-up, and more. Suboptimal transitions 
contribute to a variety of adverse events post-discharge, including ED 
evaluation, need for observation, and readmission. Within the Hospital 
IQR Program's measure set, the AMI EDAC measure illuminates post-
discharge outcomes that are important to patients, better informs 
consumers about care quality, and incentivizes improvement in 
transitional care.
(2) Overview of Measure
    We proposed to refine this measure by increasing the minimum case 
count for reporting. The NQF Scientific Methods Panel Committee and 
stakeholder feedback indicated that the measure's reliability was not 
adequate. Therefore, we proposed to increase the reporting threshold to 
50 cases in an effort to balance the need to include as many hospitals 
as possible while maintaining acceptable measure reliability.\990\ The 
remainder of the AMI EDAC measure specifications, including the data 
sources, outcome, cohort, exclusion criteria, risk adjustment approach, 
and measure calculation will remain unchanged as compared to what is 
currently adopted in the Hospital IQR Program.
---------------------------------------------------------------------------

    \990\ National Quality Forum. Scientific Methods Panel: Spring 
2021 Measure Evaluation Meeting Transcript. March 30, 2021. https://www.qualityforum.org/Measuring_Performance/Scientific_Methods_Panel/Docs/Transcript_03302021.aspx.
---------------------------------------------------------------------------

    For more detailed measure specifications, we refer readers to the 
``2017 Condition-Specific Measures Updates and Specifications Report 
Hospital-Level 30-Day Risk-Standardized Excess Days in Acute Care 
Measures: Acute Myocardial Infarction--Version 2.0'' available in the 
AMI, HF Excess Days in Acute Care folder on the CMS.gov Measure 
Methodology website at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology and the CMS.gov QualityNet website at: https://qualitynet.cms.gov/inpatient/measures/complication/methodology.
(3) Update to Minimum Case Count
    In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28536), we 
proposed a refinement to the currently adopted version of the AMI EDAC 
measure to increase the minimum case count of 25 to a minimum case 
count of 50 during the measurement period. The increase to the minimum 
case count will improve the measure's reliability. Based on internal 
analyses using the reporting period July 1, 2016 through June 30, 2019, 
the split-sample intraclass correlation (ICC) with Spearman Brown 
Adjustment increased when we increased the minimum case count from .384 
with 25 admissions to .402 with 50 admissions. Based on our analysis, 
the mean performance rate for all hospitals was 3.6 excess days per 100 
discharges, with a standard deviation of 26.3. For hospitals with at 
least 50 admissions in the same performance period, the mean 
performance rate was 6.9 per 100 discharges, with a standard deviation 
of 22. Additionally, 1,805 hospitals of 4,074 hospitals (or 44.3 
percent) meet the minimum case count of 50 admissions for the same 
performance period.
    Based on this improvement in reliability, we proposed to increase 
the AMI EDAC measure's minimum case count reporting threshold from 25 
to 50 beginning with the FY 2024 payment determination using the 
reporting period July 1, 2019 through June 30, 2022 (excluding data 
from the period covered by the ECE granted by CMS related to the COVID-
19 PHE), for which public display of the measure results will occur as 
part of a 2023 Compare website refresh (or as soon as operationally 
feasible thereafter), and

[[Page 49270]]

for subsequent years. Hospitals with fewer than 50 cases for the AMI 
EDAC measure will continue to receive confidential feedback reports 
containing measure results to understand their performance. Public 
reporting of measure results on the Compare tool hosted by HHS, 
currently available at: https://www.medicare.gov/care-compare, or its 
successor website, will only occur for hospitals meeting the 50 minimum 
cases required for reporting. Hospitals will not need to submit 
additional data as the AMI EDAC measure is calculated using 
administrative claims submitted to CMS for payment purposes.
    We invited public comment on this proposal.
    Comment: Several commenters expressed their support for the 
proposed refinements to the AMI EDAC measure beginning with the FY 2024 
payment determination. A few commenters noted that they believe 
increasing the minimum denominator for the AMI EDAC measure from 25 to 
50 cases improves measure reliability.
    Response: We thank the commenters for their support of our proposal 
to increase the AMI EDAC measure's minimum case count reporting 
threshold from 25 to 50 cases.
    Comment: A few commenters recommended that the AMI EDAC measure be 
removed from the Hospital IQR Program. A commenter stated they do not 
believe the measure adds value to the Hospital IQR Program. Other 
commenters expressed concerns with the measure outcome being a 
combination of readmissions, observation stays, and ED visits into a 
single category, stating their belief that each of these settings 
reflect widely different approaches to patient-centered care and cannot 
be meaningfully interpreted from a single number of days. Commenters 
added that they believe CMS added the AMI EDAC measure with the 
assumption that the then-new readmission measures would increase use of 
observation stays and ED visits and stated that evidence to support 
that assumption is not available.
    Response: We thank the commenters for their input but we 
respectfully disagree that the measure does not add value to the 
Hospital IQR Program or that it should be removed. We believe the 
measure adds value to the Hospital IQR Program because the measure 
illuminates additional post-discharge outcomes that are important to 
patients beyond readmissions only, better informs consumers about care 
quality, and incentivizes improvement in transitional care. Regarding 
the commenters' concern about combining the count of days for 
readmissions, observation stays or ED visits, we believe this single 
count can be meaningfully interpreted because, from a patient 
perspective, it is the count of total days that is most meaningful and 
representative of the disruption, cost, or risk. This measure is meant 
to provide patients with a complete picture of potential post-discharge 
acute care use. For this reason, the AMI EDAC measure's outcome is 
expressed in days, and we combine day counts for each type of event and 
do not publicly report rates of each type of event. Further information 
on the public reporting of the measure can be accessed here: https://data.cms.gov/provider-data/topics/hospitals/unplanned-hospital-visits/. 
Regarding the commenters' concern related to different approaches to 
patient centered care, we note that the measure developer's discussions 
with patients and the TEP, as well as published literature, indicate 
that acute care utilization after discharge (that is, return to the ED, 
observation stay, and readmission), for any reason, is disruptive to 
patients and caregivers, costly to the healthcare system, and puts 
patients at additional risk of hospital-acquired infections and 
complications. We are confident that for most patients, remaining home 
or remaining in a non-acute setting rather than returning to the 
hospital indicates a better outcome. Although some hospital returns are 
unavoidable, others may result from poor quality of care, 
overutilization of care, or inadequate transitional care. Transitional 
care includes effective discharge planning, transfer of information at 
the time of discharge, patient assessment and education, and 
coordination-of-care and monitoring in the post-discharge period. When 
appropriate care transition processes are in place (for example, a 
patient is discharged to a suitable location, communication occurs 
between clinicians, medications are correctly reconciled, timely 
follow-up is arranged), fewer patients return to an acute care setting, 
either for an ED visit, observation stay, or hospital readmission 
during the 30 days post-discharge. Numerous studies have found an 
association between quality of inpatient or transitional care and early 
(typically 30-day) readmission rates \991\ \992\ \993\ \994\ \995\ 
\996\ \997\ \998\ \999\ and ED visits \1000\ \1001\ \1002\ \1003\ 
\1004\ for a wide range of conditions including AMI.
---------------------------------------------------------------------------

    \991\ Corrigan JM, Martin JB. Identification of factors 
associated with hospital readmission and development of a predictive 
model. Health Serv Res. Apr 1992;27(1):81-101.
    \992\ Oddone EZ, Weinberger M, Horner M, et al. Classifying 
general medicine readmissions. Are they preventable? Veterans 
Affairs Cooperative Studies in Health Services Group on Primary Care 
and Hospital Readmissions. Journal of General Internal Medicine. 
1996;11(10):597-607.
    \993\ Benbassat J, Taragin M. Hospital readmissions as a measure 
of quality of health care: advantages and limitations. Arch Intern 
Med. Apr 24 2000;160(8):1074-1081.
    \994\ Frankl SE, Breeling JL, Goldman L. Preventability of 
emergent hospital readmission. Am J Med. Jun 1991;90(6):667-674.
    \995\ Halfon P, Eggli Y, Pr, et al. Validation of the 
potentially avoidable hospital readmission rate as a routine 
indicator of the quality of hospital care. Medical Care. Nov 
2006;44(11):972-981.
    \996\ Hernandez AF, Greiner MA, Fonarow GC, et al. Relationship 
between early physician follow-up and 30-day readmission among 
Medicare beneficiaries hospitalized for heart failure. JAMA: the 
journal of the American Medical Association. May 5 
2010;303(17):1716-1722.
    \997\ Courtney EDJ, Ankrett S, McCollum PT. 28-Day emergency 
surgical re-admission rates as a clinical indicator of performance. 
Ann R Coll Surg Engl. Mar 2003;85(2):75-78.
    \998\ Hernandez AF, Greiner MA, Fonarow GC, et al. Relationship 
between early physician follow-up and 30-day readmission among 
Medicare beneficiaries hospitalized for heart failure. JAMA: the 
journal of the American Medical Association. May 5 
2010;303(17):1716-1722.
    \999\ Ashton CM, Del Junco DJ, Souchek J, Wray NP, Mansyur CL. 
The association between the quality of inpatient care and early 
readmission: a meta-analysis of the evidence. Med Care. Oct 
1997;35(10):1044-1059.
    \1000\ Baer RB, Pasternack JS, Zwemer FL, Jr. Recently 
discharged inpatients as a source of emergency department 
overcrowding. Academic emergency medicine: official journal of the 
Society for Academic Emergency Medicine. Nov 2001;8(11):1091-1094.
    \1001\ Kuo YF, Goodwin JS. Association of hospitalist care with 
medical utilization after discharge: evidence of cost shift from a 
cohort study. Annals of internal medicine. Aug 22011;155(3):152-159.
    \1002\ Nunez S, Hexdall A, Aguirre-Jaime A. Unscheduled returns 
to the emergency department: an outcome of medical errors? Quality & 
safety in health care. Apr 2006;15(2):102-108.
    \1003\ Balaban RB, Weissman JS, Samuel PA,Woolhandler S. 
Redefining and redesigning hospital discharge to enhance patient 
care: a randomized controlled study. J Gen Intern Med.Aug 
2008;23(8):1228-1233.
    \1004\ Koehler BE, Richter KM, Youngblood L, et al. Reduction of 
30-day postdischarge hospital readmission or emergency department 
(ED) visit rates in high-risk elderly medical patients through 
delivery of a targeted care bundle. J Hosp Med. Apr 2009;4(4):211-
218.
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    In response to the commenters' stated assumption that the AMI EDAC 
measure may have been developed out of concern for the use of 
observation stays and ED visits in lieu of readmission without evidence 
that either are being substituted for readmissions, we reiterate that 
we developed the measure to provide a broad perspective on post-
discharge events. The goal of the measure is not to prevent hospitals 
from keeping patients in the ED or observation units; it is to help 
patients and providers understand variation among hospitals in the days 
that are spent by patients in acute care settings

[[Page 49271]]

following a discharge for AMI, as discussed in the FY 2016 IPPS/LTCH 
PPS proposed rule (80 FR 24574 through 24576).
    Comment: A commenter noted they appreciate our responsiveness to 
the concerns of the NQF's Scientific Methods Panel and thereby 
increased the case minimum to 50 patients to improve the intraclass 
correlation coefficient (ICC) result but suggested that measures should 
have a minimum ICC reliability threshold of 0.6 or higher. The 
commenter noted that reaching 0.6 or higher for this measure would 
require a minimum of 300 cases, which would in turn exclude too many 
hospitals from the measure and therefore believe it is not appropriate 
for use in the Hospital IQR Program.
    Response: We thank the commenter for their feedback. We agree that 
is it important to balance the need to include as many hospitals as 
possible while maintaining acceptable measure reliability. We would 
like to further clarify that during the NQF Spring 2021 Measure 
Evaluation Meeting, the NQF Scientific Methods Panel Committee 
indicated that a split-sample ICC threshold of around 0.4 or higher is 
considered acceptable measure reliability.\1005\ As noted previously in 
the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28536), the proposed 
refinement of increasing the minimum case count from 25 to 50 will 
increase the ICC with Spearman Brown Adjustment from 0.384 to 0.402, 
therefore improving the measure's reliability and meeting an acceptable 
threshold as determined by the NQF Scientific Methods Panel Committee's 
guidance at that time. As guidance on acceptable reliability is often 
changing, we will continue to take this into consideration as we 
conduct routine measure maintenance.
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    \1005\ National Quality Forum. Scientific Methods Panel: Spring 
2021 Measure Evaluation Meeting Transcript. March 30, 2021. 
Available at: https://www.qualityforum.org/Measuring_Performance/Scientific_Methods_Panel/Docs/Transcript_03302021.aspx.
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    Comment: A few commenters offered recommendations for ongoing 
reevaluation of the AMI EDAC measure. A commenter recommended we 
consider how the COVID-19 pandemic may pose challenges to timely 
discharge, as hospitals may face constraints due to other health care 
settings (for example, a skilled nursing facility) being unable to 
promptly accept patients. Another commenter recommended that we should 
identify methods to address the issue of fewer hospitals meeting the 
proposed increased minimum case count and suggested that we could 
remedy this issue by using all-payer claims data to increase the 
denominator, improve reliability, include additional risk factors, and 
increase the relevancy of the measure to a broader base of providers 
and consumers.
    Response: We thank the commenter for their feedback to consider the 
impact of the COVID-19 pandemic on timely discharge, specifically the 
concern that the pandemic has presented novel circumstances that might 
extend the length of a patient's stay in situations in which a hospital 
is ready to discharge a patient to another healthcare setting but is 
unable to do so because the other setting, for instance, is unable or 
unwilling to accept new patients due to issues related to COVID-19. The 
following COVID-19 adjustments have been made to the AMI EDAC measure 
for 2022 public reporting as technical updates: (1) Exclusion of COVID-
19 patients (ICD-10-CM U07.1) from the cohort; (2) claims for ED 
visits, observation stays, and readmissions with COVID-19 coding (ICD-
10-CM U07.1) are not eligible for the AMI EDAC outcome and are 
excluded; and (3) addition of a new ``History of COVID-19'' risk 
variable for risk adjustment. The COVID-19 pandemic continues to have 
significant and enduring effects on the provision of medical care in 
the country and around the world. It affects care decisions, including 
readmissions to the hospital. National or regional shortages or changes 
in healthcare personnel, medical supplies, equipment, diagnostic tools, 
and patient case volumes or facility-level case mix may affect quality 
measurement data.\1006\ Adjustments to public reporting methodologies 
and specifications for 2022 help to ensure the intent of the measures 
is maintained. Further details of COVID-19 adjustment can be accessed 
by viewing the 2022 Condition-Specific Excess Days in Acute Care 
Measures Updates and Specifications Report: AMI, HF, and the Pneumonia 
and 2022 AMI EDAC Measure Code Specifications Supplemental File, both 
available on the QualityNet website here: https://qualitynet.cms.gov/inpatient/measures/edac/methodology.
---------------------------------------------------------------------------

    \1006\ The Centers for Medicare and Medicaid. 2022 Condition-
Specific Excess Days in Acute Care Measures Updates and 
Specifications Report: AMI, HF. Available at: https://qualitynet.cms.gov/inpatient/measures/edac/methodology.
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    We appreciate the suggestion of utilizing all-payer claims data to 
increase the number of hospitals with at least 50 cases, and we will 
take this into consideration when planning ongoing measure maintenance 
analyses. Hospitals with fewer than 50 cases for the AMI EDAC measure 
will continue to receive confidential feedback reports containing 
measure results to understand their performance.
    Comment: A commenter requested that CMS explain their rationale for 
proposing the case minimum refinements based on reliability concerns 
for only the AMI EDAC measure and not including the Excess Days in 
Acute Care after Hospitalization for Pneumonia (NQF #2882) (Pneumonia 
EDAC) and Excess Days in Acute Care after Hospitalization for Heart 
Failure (NQF #2880) (Heart Failure EDAC) measures for consistency. The 
commenter expressed an assumption that the Pneumonia EDAC and Heart 
Failure EDAC measures would also be affected by the same reliability 
concerns as the AMI EDAC measure and would therefore need to adopt the 
same minimum case count to improve reliability.
    Response: We thank the commenter for sharing these concerns. We 
would like to clarify that the NQF Scientific Methods Panel Committee 
did not raise concerns with reliability regarding the Pneumonia EDAC or 
Heart Failure EDAC measures, therefore, refinements for these measures 
were not proposed alongside those for the AMI EDAC measure. During the 
Spring 2021 project cycle, NQF's Scientific Methods Panel Committee 
reviewed and passed both Pneumonia EDAC and Heart Failure EDAC measures 
on reliability with a rating of moderate, and NQF's All-Cause 
Admissions and Readmissions Standing Committee voted to uphold the 
Scientific Methods Panel Committee's rating on reliability. Thus, as 
both Pneumonia EDAC and Heart Failure EDAC measures were found to have 
met the NQF's Scientific Acceptability criteria, we did not propose 
reliability related refinements to these measures at this time.\1007\ 
Further details regarding NQF's ratings on reliability for these 
measures can be accessed here: https://www.qualityforum.org/Publications/2022/02/All-Cause_Admissions_and_Readmissions_Final_Report_-_Spring_2021_Cycle.aspx.
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    \1007\ National Quality Forum. All-Cause Admissions and 
Readmissions, Spring 2021 Cycle: CDP Report February 14, 2022. 
Available at: https://www.qualityforum.org/Publications/2022/02/All-Cause_Admissions_and_Readmissions_Final_Report_-_Spring_2021_Cycle.aspx.

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[[Page 49272]]

    After consideration of the public comments we received, we are 
finalizing our proposal as proposed.
7. Summary of Previously Finalized and New Hospital IQR Program 
Measures
a. Summary of Previously Finalized and New Hospital IQR Program 
Measures for the FY 2024 Payment Determination
    This table summarizes the previously finalized and newly finalized 
Hospital IQR Program measure set for the FY 2024 payment determination:
BILLING CODE 4120-01-P

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[GRAPHIC] [TIFF OMITTED] TR10AU22.165


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b. Summary of Previously Finalized and New Hospital IQR Program 
Measures for the FY 2025 Payment Determination
    This table summarizes the previously finalized and newly finalized 
Hospital IQR Program measure set for the FY 2025 payment determination:

[[Page 49275]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.166


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[GRAPHIC] [TIFF OMITTED] TR10AU22.167

c. Summary of Previously Finalized and New Hospital IQR Program 
Measures for the FY 2026 Payment Determination
    This table summarizes the previously finalized and newly finalized 
Hospital IQR Program measure set for the FY 2026 payment determination:

[[Page 49277]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.168

d. Summary of Previously Finalized and New Hospital IQR Program 
Measures for the FY 2027 Payment Determination
    This table summarizes the previously finalized and newly finalized 
Hospital IQR Program measure set for the FY 2027 payment determination:

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[GRAPHIC] [TIFF OMITTED] TR10AU22.170


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[GRAPHIC] [TIFF OMITTED] TR10AU22.171

e. Summary of Previously Finalized and New Hospital IQR Program 
Measures for the FY 2028 Payment Determination and for Subsequent Years
    This table summarizes the previously finalized and newly finalized 
Hospital IQR Program measure set for the FY 2028 payment determination 
and for subsequent years:

[[Page 49281]]

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[[Page 49282]]


[GRAPHIC] [TIFF OMITTED] TR10AU22.173

BILLING CODE 4120-01-C
8. Establishment of a Publicly-Reported Hospital Designation To Capture 
the Quality and Safety of Maternity Care
    In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28547 through 
28550), we proposed to establish a hospital quality designation that we 
would publicly report on a CMS website beginning in Fall 2023. We 
proposed this designation would be awarded to hospitals based on their 
attestation of submission of the Maternal Morbidity Structural measure, 
which we believe will reflect their commitment to the quality and 
safety of maternity care they furnish. This will be the first-ever 
hospital quality designation by HHS or CMS that specifically focuses on 
maternal health. We proposed this policy in conjunction with Vice 
President Harris' ``Maternal Health Day of Action'' announcement \1008\ 
which also signaled CMS' intent to establish this proposed ``birthing-
friendly'' hospital designation. Additionally, we requested feedback on 
potential additional activities that we could undertake to advance 
maternal health equity.
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    \1008\ The White House. (2021). Fact Sheet: Vice President 
Kamala Harris Announces Call to Action to Reduce Maternal Mortality 
and Morbidity. Accessed January 26, 2022. Available at: https://www.whitehouse.gov/briefing-room/statements-releases/2021/12/07/fact-sheet-vice-president-kamala-harris-announces-call-to-action-to-reduce-maternal-mortality-and-morbidity/.
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a. The U.S. Maternal Health Crisis
    Despite the highest rate of spending on maternity care, maternal 
mortality rates in the U.S. are among the highest in the developed 
world. Every year, approximately 700 women die of complications related 
to pregnancy and childbirth, and over 25,000 women experience severe 
complications of pregnancy (severe maternal 
morbidity).1009 1010 Approximately one-third of all 
pregnancy-related deaths occur at the time of delivery and immediately 
postpartum, with nearly 20 percent occurring between one and six days 
postpartum.\1011\ Yet, three out of five pregnancy-related deaths are 
considered preventable.\1012\
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    \1009\ Petersen EE et al. Vital Signs: Pregnancy-Related Deaths, 
United States, 2011-2015, and Strategies for Prevention, 13 States, 
2013-2017. MMWR Morbidity and Mortality Weekly Report 2019;68:423-
29.
    \1010\ Maternal and Child Health Bureau. Federally Available 
Data (FAD) Resource Document. Health Resources and Services 
Administration. Available at: https://mchb.tvisdata.hrsa.gov/Admin/FileUpload/DownloadContent?fileName=FadResourceDocument.pdf&isForDownload=False.

    \1011\ Davis N.L., Smoots A.N., and Goodman D.A. (2019). 
Pregnancy-Related Deaths: Data from 14 U.S. Maternal Mortality 
Review Committees, 2008-2017. Available at: https://www.cdc.gov/reproductivehealth/maternal-mortality/erase-mm/MMR-Data-Brief_2019-h.pdf.
    \1012\ The Centers for Disease Control and Prevention. 
Pregnancy-Related Deaths in the United States. September 2021. 
Available at: https://www.cdc.gov/hearher/pregnancy-related-deaths/.
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    Racial, ethnic, disability, and geographic disparities intensify 
the U.S. maternal health crisis. Adverse maternal health outcomes vary 
considerably by race and ethnicity, and are highest among Black and 
American Indian/Alaskan Native women, regardless of their income or 
education levels.1013 1014 Black and American Indian/Alaskan 
Native women die from pregnancy-related causes at a rate two to three 
times higher \1015\ and experience severe maternal morbidity at a rate 
nearly two

[[Page 49283]]

times higher than their White, Asian Pacific Islander, and Hispanic 
counterparts.\1016\ The COVID-19 pandemic in the U.S. has exacerbated 
such racial and ethnic disparities in maternal outcomes, likely 
associated with Black and Hispanic women facing higher rates of 
economic hardship and reporting higher rates of mental health concerns 
compared to their White counterparts.1017 1018 1019 1020 
Women with disabilities have a higher mortality risk and significantly 
higher risk in almost all adverse maternal outcomes compared with women 
without disabilities.\1021\ Finally, geographic disparities in maternal 
outcomes also exist. Pregnant women who live in rural communities are 
at higher risk for severe maternal morbidity and about 60 percent more 
likely to die before, during, or after delivery than those living in 
urban settings.\1022\
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    \1013\ Hoyert DL and Mini[ntilde]o AM. Maternal Mortality in the 
United States: Changes in Coding, Publication, and Data Release. 
National Vital Statistics Report. Vol 69, No. 2 (Jan. 2020): 1-18.
    \1014\ Centers for Disease Control and Prevention. Racial/Ethnic 
Disparities in Pregnancy-Related Deaths -- United States, 2007-2016. 
September 6, 2019. Vol. 68, No. 35. Available at: https://www.cdc.gov/mmwr/volumes/68/wr/pdfs/mm6835a3-H.pdf.
    \1015\ Centers for Disease Control and Prevention. Pregnancy 
Mortality Surveillance System. Available at: https://www.cdc.gov/reproductivehealth/maternal-mortality/pregnancy-mortality-surveillance-system.htm. Accessed November 10, 2021.
    \1016\ US Government Accountability Office. MATERNAL MORTALITY 
Trends in Pregnancy-Related Deaths and Federal Efforts to Reduce 
Them. March 2020. Available at: https://www.gao.gov/assets/gao-20-248.pdf.
    \1017\ Raman S. COVID-19 Amplifies Racial Disparities in 
Maternal Health. Roll Call. May 14, 2020. Available at: https://www.rollcall.com/2020/05/14/covid-19-amplifies-racial-disparities-in-maternal-health/.
    \1018\ National Partnership for Women & Families. Black Women's 
Maternal Health: A Multifaceted Approach to Addressing Persistent 
and Dire Health Disparities. April 2018. Available at: https://www.nationalpartnership.org/our-work/health/reports/black-womens-maternal-health.html.
    \1019\ Bion X-S. Efforts to Reduce Black Maternal Mortality 
Complicated by COVID-19. California Health Care Foundation. April 
2020. Available at: https://www.chcf.org/blog/efforts-reduce-black-maternal-mortality-complicated-covid-19/.
    \1020\ Getachew Y et al. Beyond the Case Count: The Wide-Ranging 
Disparities of COVID-19 in the United States The Commonwealth Fund. 
September 2020. Available at: https://www.commonwealthfund.org/publications/2020/sep/beyond-case-count-disparities-covid-19-united-states.
    \1021\ Brown, Hilary K, ``Disparities in Severe Maternal 
Morbidity and Mortality--A Call for Inclusion of Disability in 
Obstetric Research and Health Care Professional Education,'' JAMA 
Netw Open. 2021;4(12):e2138910. doi:10.1001/
jamanetworkopen.2021.38910. Online at: https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2787181.
    \1022\ White House Fact Sheet: Vice President Kamala Harris 
Announces Call to Action to Reduce Maternal Mortality and Morbidity. 
https://www.whitehouse.gov/briefing-room/statements-releases/2021/12/07/fact-sheet-vice-president-kamala-harris-announces-call-to-action-to-reduce-maternal-mortality-and-morbidity/.
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b. HHS Focus on Improving Maternal Health in the U.S.
    To build on the previously established HHS Maternal Health Action 
Plan, the Vice President's nationwide call to action to reduce maternal 
morbidity and mortality, and ongoing efforts with HHS and across the 
federal government,\1023\ the Administration seeks to use a whole-of-
government approach for improving maternal health and advancing 
maternal health equity that reduces maternal mortality and morbidity, 
reduces persistent disparities, and among other activities, increases 
hospital participation in HHS-sponsored maternal health quality 
improvement initiatives. A critical focus is reducing existing 
disparities in maternal health outcomes across race, ethnicity, and 
geographic area. This targeted strategy is further embodied by other 
efforts spearheaded by the Biden-Harris Administration, including the 
first-ever Presidential Proclamation in recognition of Black Maternal 
Health Week in April 2021, as well as the first-ever federal ``Maternal 
Health Day of Action'' on December 7, 2021. 1024 1025
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    \1023\ HHS Initiative to Improve Maternal Health. https://aspe.hhs.gov/topics/public-health/hhs-initiative-improve-maternal-health.
    \1024\ A Proclamation on Black Maternal Health Week, 2021. 
Available at: https://www.whitehouse.gov/briefing-room/presidential-actions/2021/04/13/a-proclamation-on-black-maternal-health-week-2021/.
    \1025\ The White House. (2021). Fact Sheet: Vice President 
Kamala Harris Announces Call to Action to Reduce Maternal Mortality 
and Morbidity. Accessed January 26, 2022. Available at: https://www.whitehouse.gov/briefing-room/statements-releases/2021/12/07/fact-sheet-vice-president-kamala-harris-announces-call-to-action-to-reduce-maternal-mortality-and-morbidity/.
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    As part of the ``Day of Action,'' Vice President Harris issued a 
nationwide call to action to reduce maternal mortality and morbidity 
and made several key announcements, including CMS' intention to 
establish the proposed hospital designation.\1026\ Additionally, we 
released a quality, safety, and oversight memorandum (QSO-22-05-
Hospitals) to state survey agencies. In that memorandum, we encourage 
hospitals to consider implementation of evidence-based best practices 
for the management of obstetric emergencies, along with interventions 
to address other key contributors to maternal health disparities, to 
support the delivery of equitable, high-quality care for all pregnant 
and postpartum individuals.\1027\ Such best practices include 
participation in local/regional perinatal quality collaboratives, 
application of early warning sign tools, and the use of patient safety 
``bundles.'' We encourage hospitals to review the guidance and 
resources provided in the memorandum to assess their own capacity to 
provide optimal management of obstetric emergencies and to combat 
maternal health disparities.
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    \1026\ Ibid.
    \1027\ Centers for Medicare & Medicaid Services. Evidence-Based 
Best Practices for Hospitals in Managing Obstetric Emergencies and 
Other Key Contributors to Maternal Health Disparities. Accessed 
December 20, 2021. Available at: https://www.cms.gov/files/document/qso-22-05-hospitals.pdf.
---------------------------------------------------------------------------

    As part of our commitment to reducing high maternal morbidity and 
mortality rates, the Hospital IQR Program adopted the Maternal 
Morbidity Structural measure in the FY 2022 IPPS/LTCH PPS final rule 
(86 FR 45361 through 45365). This measure is designed to determine 
hospital participation in a state or national Perinatal Quality 
Improvement (QI) Collaborative and implementation of patient safety 
practices or bundles through that QI initiative. As noted in the FY 
2022 IPPS/LTCH PPS final rule (86 FR 45361 through 45365), hospital 
participation in QI collaboratives has been shown to be effective in 
improving the infrastructure surrounding management of obstetric 
conditions that may lead to severe maternal morbidity or 
mortality.\1028\ Additionally, hospital implementation of related QI 
efforts has been associated with both enhanced quality and safety of 
care as well as a reduction in the maternal health disparity 
gap.1029 1030 1031 1032
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    \1028\ Main, E.K., Cape, V., Abreo, A., Vasher, J., Woods, A., 
Carpenter, A., Gould, J.B. (2017). Reduction of Severe Maternal 
Morbidity from Hemorrhage Using a State Perinatal Quality 
Collaborative. American Journal of Obstetrics and Gynecology, 
216(3): 298.e1. Available at: https://www.ncbi.nlm.nih.gov/pubmed/
28153661.
    \1029\ Callaghan-Koru JA et al. Implementation of the Safe 
Reduction of Primary Cesarean Births safety bundle during the first 
year of a statewide collaborative in Maryland. Obstet Gynecol 
2019;134:109-19.
    \1030\ Main EK et al. Reduction of severe maternal morbidity 
from hemorrhage using a state perinatal quality collaborative. Am J 
Obstet Gynecol 2017;216(3):298.e1-298.e11.
    \1031\ King PL et al. Reducing time to treatment for severe 
maternal hypertension through statewide quality improvement. Am J 
Obstet Gynecol 2018;218:S4.
    \1032\ Main EK et al. Reduction in racial disparities in severe 
maternal morbidity from hemorrhage in a large-scale quality 
improvement collaborative. Am J Obstet Gynecol 2020;223:123.e1-14.
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    The Maternal Morbidity Structural measure is specified to capture 
whether hospitals are: (1) Currently participating in a structured 
state or national Perinatal QI Collaborative; and (2) implementing 
patient safety practices or bundles as part of these QI initiatives. In 
reporting on this measure, hospitals respond ``Yes,'' ``No,'' or ``N/A 
(our hospital does not provide inpatient labor/delivery care)'' to a 
two-part question assessing these two topic areas.\1033\ Data 
collection began with

[[Page 49284]]

fourth quarter 2021 data, which hospitals must have reported by May 
2022. We refer readers to the FY 2022 IPPS/LTCH PPS final rule (86 FR 
45361 through 45365) for more details on the measure.
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    \1033\ To report on this measure, hospitals will respond to a 
two-part question: ``Does your hospital or health system participate 
in a Statewide and/or National Perinatal Quality Improvement 
Collaborative Program aimed at improving maternal outcomes during 
inpatient labor, delivery and post-partum care, and has it 
implemented patient safety practices or bundles related to maternal 
morbidity to address complications, including, but not limited to, 
hemorrhage, severe hypertension/preeclampsia or sepsis?.'' Further 
details on this measure can be found in the FY 2022 IPPS/LTCH PPS 
final rule at 86 FR 45361 through 45365.
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c. Establishment of a Publicly-Reported Hospital Designation To Capture 
the Quality and Safety of Maternity Care
    In alignment with the announcement made during the ``Maternal 
Health Day of Action''\1034\ we proposed to establish a hospital 
designation to be publicly reported on a CMS website beginning in Fall 
2023. We will give this designation to hospitals that report ``Yes'' to 
both questions in the Maternal Morbidity Structural measure. This 
designation will initially be based only on data from hospitals 
reporting an affirmative attestation to the Maternal Morbidity 
Structural measure. This will allow us to initially award the 
designation based on the data hospitals are currently reporting on the 
Maternal Morbidity Structural measure under the Hospital IQR Program. 
In future notice and comment rulemaking, we intend to propose a more 
robust set of metrics for awarding the designation that may include 
other maternal health-related measures that may be finalized for the 
Hospital IQR Program measure set in the future. We note that in the FY 
2023 IPPS/LTCH PPS proposed rule (87 FR 28506 through 28515), we 
proposed to adopt two new electronic clinical quality measures (eCQMs) 
for the Hospital IQR Program--the Cesarean Birth (ePC-02) and Severe 
Obstetric Complications (ePC-07)--in sections IX.E.5.c. and IX.E.5.d, 
respectively, which are discussed in sections IX.E.5.c. and IX.E.5.d., 
respectively, of this final rule.
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    \1034\ The White House. (2021). Fact Sheet: Vice President 
Kamala Harris Announces Call to Action to Reduce Maternal Mortality 
and Morbidity. Accessed January 26, 2022. Available at: https://www.whitehouse.gov/briefing-room/statements-releases/2021/12/07/fact-sheet-vice-president-kamala-harris-announces-call-to-action-to-reduce-maternal-mortality-and-morbidity/.
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    Section 1886(b)(3)(B)(viii)(VII) of the Social Security Act 
requires that the Secretary establish procedures for making information 
regarding Hospital IQR Program measures available to the public (74 FR 
43864; 75 FR 50184 through 50815). We believe adding this designation 
to a consumer-facing CMS website will allow patients and families to 
choose hospitals that have demonstrated a commitment to improving 
maternal health through their participation in related perinatal QI 
collaboratives and their implementation of best practices that support 
the delivery of high-quality maternity care.
    We invited public comment on this proposal.
    Comment: Many commenters supported the creation of a public 
designation related to maternity care.
    Response: We thank commenters for their support of our proposal to 
establish a maternity care hospital designation to be publicly reported 
on a CMS website beginning in Fall 2023. We believe that adoption of 
this designation represents a first step in informing the public in a 
meaningful and consumer-friendly manner about hospitals' commitment to 
the provision of high-quality maternity care and it will empower the 
public to make more informed decisions as to where they choose to 
obtain care during pregnancy and postpartum (87 FR 28549). We also note 
that since the publication of the FY 2023 IPPS/LTCH PPS proposed rule, 
the White House has published the ``White House Blueprint for 
Addressing the Maternal Health Crisis'' which further outlines how the 
hospital designation will fit in with the HHS' maternal health 
strategy.\1035\
---------------------------------------------------------------------------

    \1035\ White House Blueprint for Addressing the Maternal Health 
Crisis. (2022). Available at: https://www.whitehouse.gov/wp-content/uploads/2022/06/Maternal-Health-Blueprint.pdf.
---------------------------------------------------------------------------

    Comment: While many commenters supported the creation of the 
designation, many of these commenters also stated that they believe the 
attestation-based Maternal Morbidity Structural measure is not 
sufficient in fully addressing maternal health. The commenters 
encouraged CMS to, in the near future, push beyond the use of an 
attestation by incorporating more rigorous quality reporting components 
that incentivize hospitals to deliver high-quality care and provide 
consumers with more detailed, reliable data on hospital results in 
improving maternal health. Several commenters emphasized the importance 
of including clear, consistent, patient-centered, and evidence-based 
measures on maternal health and encouraged our engagement with 
hospitals, clinicians, and consumers to design and apply a maternal 
health designation. A few commenters expressed support for the 
designation's potential to increase participation in perinatal quality 
collaboratives and other quality improvement initiatives. A couple of 
commenters noted the proposal builds off an existing Hospital IQR 
Program measure and will therefore mitigate administrative burden for 
hospitals. A commenter supported the designation's potential to address 
the issue of maternal hemorrhage and facilitate timely initiation of 
interventions.
    Response: We appreciate commenters' feedback and support for the 
maternity care hospital designation. We acknowledge and agree that this 
iteration of the proposed designation is a first step towards informing 
the public in a meaningful and consumer-friendly manner about maternity 
care quality, and advancing maternal health equity more broadly, using 
a measure that was already finalized in the Hospital IQR Program. As we 
stated in the FY 2023 IPPS/LTCH PPS proposed rule, we intend to propose 
a more robust set of criteria for awarding the designation in future 
notice-and-comment rulemaking (87 FR 28549). We thank the commenters 
for their support and agree that the designation could support greater 
participation in perinatal quality improvement collaboratives and 
implementation of best practices. We are committed to engaging with 
interested parties as we continue to improve upon this designation in 
future notice-and-comment rulemaking.
    Comment: Many commenters did not support the proposal as currently 
proposed, indicating that the attestation of participation in a 
perinatal quality improvement collaborative (as captured by the 
Maternal Morbidity Structural measure) is insufficient to demonstrate 
hospital maternity care quality. The commenters suggested that 
participation in quality improvement collaboratives and initiatives 
should be considered the floor for acceptable maternity care rather 
than the ceiling. A few of these commenters noted that participation in 
such collaboratives varies and using it as the basis for the 
designation may not be meaningful. A few commenters noted that the 
designation will be particularly unhelpful in states where the vast 
majority of birthing facilities participate in perinatal quality 
improvement collaboratives because the designation would not offer 
distinction in quality among hospitals. Another commenter questioned 
whether the designation as proposed meaningfully informs patients 
beyond the information that is currently available and publicly 
reported. A few commenters stated further concern that, as proposed, 
the designation will mislead consumers who believe it indicates an 
exceptional level of quality when it reflects a less stringent

[[Page 49285]]

criterion. A commenter noted that some state perinatal quality 
improvement collaboratives have had to suspend initiatives due to the 
COVID-19 pandemic and introduction of a designation based on measures 
or initiatives that are unattainable for many hospitals is not 
appropriate at this time. Relatedly, a commenter noted that they used 
to participate in perinatal quality improvement collaboratives but 
found the cost of paid membership to be a barrier.
    Response: We appreciate the commenters' feedback and acknowledge 
their concerns. As we stated in the FY 2023 IPPS/LTCH PPS proposed 
rule, at this time we will base the designation only on data from 
hospitals reporting an affirmative attestation to the Maternal 
Morbidity Structural measure under the Hospital IQR Program (87 FR 
28549). This measure is already reported as part of the Hospital IQR 
Program measure set (as finalized in the FY 2022 IPPS/LTCH PPS final 
rule (86 FR 45361)) and we believe using an existing measure will 
reduce burden for hospitals during the first year of the designation 
which is particularly critical in light of the ongoing public health 
emergency. This is a first step. In future notice-and-comment 
rulemaking, we intend to propose a more robust set of metrics for 
awarding the designation that may include other maternal health-related 
measures that may be finalized for the Hospital IQR Program measure set 
(87 FR 28549). In the Biden-Harris Administration Blueprint to Address 
the Maternal Health Crisis (hereto referred to as the Blueprint), we 
acknowledge that full-scale adoption of perinatal quality improvement 
collaboratives has not happened for several reasons: Not all states 
have been funded to support this key infrastructure; hospitals are not 
required to adopt these best practices and therefore may struggle to 
procure the resources needed to implement them; and, hospitals are not 
externally incentivized to do so.\1036\ In the Blueprint, we state our 
intent to explore opportunities to advance equitable, high-quality 
maternity care provided by hospitals in several ways, including through 
this hospital designation and through the FY 2023 President's Budget 
which, would support a perinatal quality collaborative in every 
state.\1037\ We believe this will further support hospitals in areas 
where perinatal quality collaboratives have not been available due to 
resource or access issues. We acknowledge commenters' concerns that 
participation in perinatal quality improvement collaboratives may vary. 
However, as stated in the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 
28548) and the FY 2022 IPPS/LTCH PPS final rule (86 FR 45361 through 
45365), hospital participation in quality improvement collaboratives 
has been shown to be effective in improving the infrastructure 
surrounding management of obstetric conditions that may lead to severe 
maternal morbidity or mortality, and hospital implementation of quality 
improvement efforts has been associated with both enhanced quality and 
safety of maternity care as well as a reduction in the maternal health 
disparity gap. We believe supporting hospital participation in such 
efforts is critical to addressing maternal health. In addition, we 
believe that while the Maternal Morbidity Structural measure and the 
hospital designation do not directly mandate participation in perinatal 
quality collaboratives and other quality improvement initiatives, they 
create strong incentives to the over 3,000 participating hospitals and 
CAHs that voluntarily participate in the Hospital IQR Program to begin 
active participation if they have not yet done so or to continue 
participation in such activities that are an important part of 
improving the quality of maternity care offered in hospitals.
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    \1036\ The White House. White House Blueprint for Addressing the 
Maternal Health Crisis. June 2022. Available at: https://www.whitehouse.gov/wp-content/uploads/2022/06/Maternal-Health-Blueprint.pdf.
    \1037\ The White House. Budget of the U.S. Government Fiscal 
Year 2023. Accessed June 24, 2022. Available at: https://www.whitehouse.gov/wp-content/uploads/2022/03/budget_fy2023.pdf.
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    Comment: Several commenters recommended that hospitals that 
participate in any state, national, or regional quality improvement 
activities or collaboratives be considered for the designation. A few 
commenters noted this flexibility is particularly important for rural 
hospitals, safety net hospitals, and hospitals in states or regions 
where a perinatal quality improvement collaborative is not available. A 
commenter suggested that state Medicaid programs may use national or 
state Alliance for Innovation on Maternal Health (AIM) or other quality 
improvement initiatives and these should be considered for the 
designation. A couple of commenters encouraged us to consider 
recognizing hospitals that already participate in maternal health 
designation programs as recipients of the CMS designation.
    Response: We thank the commenters for their recommendations. We 
recognize that hospitals are involved in a variety of quality 
improvement activities. As stated in the FY 2022 IPPS/LTCH PPS final 
rule, for purposes of the Maternal Morbidity Structural measure in the 
Hospital IQR Program, we define a State or national perinatal quality 
improvement collaborative as a Statewide or a multi-State network 
working to improve women's health and maternal health outcomes by 
addressing the quality and safety of maternity care (86 FR 45362). 
(Specifications for the measure are available on the CMS Measure 
Methodology page under the file name `Maternal Morbidity Structural 
Measure Specifications,' available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.) We believe this provides 
hospitals with some flexibility to identify a perinatal quality 
improvement collaborative, of which the HRSA-funded AIM Program is one 
example, in their state or region in addition to national 
options.\1038\ However, we acknowledge that some hospitals, and 
especially those in rural areas, may lack immediate access to a 
collaborative. We continue to consider additional measures for future 
years of the designation. In the interim, we direct commenters and 
providers to the December 2021 quality, safety, and oversight memo that 
provides information on a variety of maternity care quality improvement 
resources.\1039\
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    \1038\ Health Resources & Services Administration. Alliance for 
Innovation on Maternal Health (AIM) and Alliance for Innovation on 
Maternal Health Community Care Initiative (AIM CCI). 2022. Available 
at: https://mchb.hrsa.gov/programs-impact/programs/alliance-innovation-maternal-health-aim-community-care-aim-cci.
    \1039\ Centers for Medicare & Medicaid Services. Evidence-Based 
Best Practices for Hospitals in Managing Obstetric Emergencies and 
Other Key Contributors to Maternal Health Disparities. Accessed 
December 20, 2021. Available at: https://www.cms.gov/files/document/qso-22-05-hospitals.pdf.
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    Comment: A few commenters stated that the Maternal Morbidity 
Structural measure has yet to receive NQF endorsement and therefore 
should not be the only metric used to designate maternity care quality.
    Response: We stated in the FY 2022 IPPS/LTCH PPS final rule (86 FR 
45364) that section 1886(b)(3)(B)(viii)(IX)(bb) of the Act provides an 
exception for NQF endorsement that, in the case of a specified area or 
medical topic determined appropriate by the Secretary for which a 
feasible and practical measure has not been endorsed by the entity with 
a contract under section 1890(a) of the Act, the Secretary may specify 
a measure that is not so endorsed as long as due consideration is given 
to measures that have been endorsed or adopted by a consensus 
organization identified by the Secretary.

[[Page 49286]]

We reviewed NQF-endorsed measures and were unable to identify any other 
NQF-endorsed measures that addressed maternal morbidity through 
hospital participation in perinatal quality improvement initiatives and 
the implementation of associated bundles or patient safety practices. 
We found no other feasible and practical measures on the topic of 
maternal health; therefore, we believe the exception in section 
1886(b)(3)(B)(viii)(IX)(bb) of the Act applies. In future notice-and-
comment rulemaking, we intend to propose a more robust set of measures 
for the designation. We believe that the maternal health crisis is 
urgent, maternal health inequities are unacceptable, and this 
persistent problem requires prompt action. We will consider commenter 
suggestions received as part of the related request for comment 
included in the FY 2023 IPPS/LTCH PPS proposed rule.
    Comment: Many commenters questioned the intent and purpose of the 
designation. A few commenters disagreed with the designation's narrow 
focus on maternal health. A commenter stated that a ``birthing-
friendly'' designation without neonatal health components is inadequate 
and suggested that a designation that includes maternal and neonatal 
health care would be most appropriate for such a designation.
    Response: We thank the commenters for their feedback. As previously 
stated, the proposed designation is intended as a first step in our 
efforts to adopt policies that address maternal health. In the FY 2023 
IPPS/LTCH PPS proposed rule (87 FR 28549), we expressed our intent to 
propose a more robust set of criteria for awarding the designation, 
such as other maternal health-related measures that may be finalized 
for the Hospital IQR Program in the future; which could include two 
maternal health eCQMs-Cesarean Birth and Severe Obstetric 
Complications- that we are finalizing in this final rule (in sections 
IX.E.5.c. and IX.E.5.d., respectively). We acknowledge that there may 
be other measures that could be candidates for the designation, and we 
reiterate our intention to continue exploring opportunities across 
future notice-and-comment rulemaking to continue refining the 
designation so that it remains meaningful and useful for patients and 
hospitals.
    Comment: A few commenters noted that patients often have limited 
choice in their delivery location, due to, for example, insurance 
coverage or provider admitting privileges, and questioned whether this 
designation could therefore be impactful when considering where to 
deliver. A commenter stated that because Medicare beneficiaries tend to 
produce relatively few claims for services related to maternity care, 
the desired impact with the designation is unclear.
    Response: We thank these commenters for their feedback. We 
acknowledge that for some patients, including those in emergent 
situations, there may not be opportunities to choose the hospital in 
which they deliver. However, for many patients, there is an opportunity 
for some choice and we believe it is important to provide meaningful 
and user-friendly information to help inform those choices. We also 
note that there are other important uses for collecting and publishing 
the data, including transparency to incentivize continuous improvement. 
We appreciate the commenter's feedback that Medicare claims would 
likely be less useful as sources of quality data for a maternity care 
quality designation, which is why we have focused on the use of an 
attestation measure to begin, and will explore potential EHR-based and 
other quality measure data to base future iterations of the 
designation.
    Comment: Many commenters expressed concern about potential 
consequences of evolving the designation over time. Several commenters 
noted that changing the criteria for the designation without properly 
educating and informing consumers is likely to impact the integrity of 
the initiative and the perception of care delivered in hospitals with 
birthing facilities that may gain and then lose designation. A few 
commenters stated that hospitals may lose their designation, but 
continue to prominently feature their previous recognition and create a 
false assurance of quality to consumers. A commenter expressed concern 
that CMS could choose to add criteria or metrics to the designation 
from outside of the Hospital IQR Program or quality measures that have 
not been reviewed or endorsed through the NQF process, both of which 
they believe could negatively impact the integrity and accuracy of the 
designation.
    Response: We thank the commenters for their feedback, and we 
acknowledge commenters' concerns about potential evolution of the 
designation. We understand many public-facing quality indicators and 
summary scores, such as star ratings, rankings, or grades, undergo 
revisions over time rather than remain static to continuously improve 
the data quality, reliability, and validity, as well as to ensure 
information remain meaningful to users and align with the state of the 
field. We do not believe that such revisions jeopardize the integrity 
of the designation. In addition, as participating facilities continue 
to provide quality data for the Maternal Morbidity Structural measure 
each year, the designation will be accordingly refreshed to reflect the 
most current data. We believe that future refinements to the 
designation will be needed in order to continue to provide hospitals 
and consumers the opportunity to access timely quality and safety data 
to inform decision-making. We encourage hospitals to routinely and 
accurately update public-facing materials related to the designation to 
provide the most up-to-date information and avoid misleading the 
public. We additionally intend to provide additional outreach, 
communication, and educational materials as we rollout and improve upon 
this designation. We also note that interested parties may review any 
future new measures included for the designation as they would be 
proposed through notice-and-comment rulemaking. With regard to concerns 
about future adoption of measures for the designation that may lack NQF 
endorsement, while we prioritize measures that are endorsed when 
available, we reiterate that section 1886(b)(3)(B)(viii)(IX)(bb) of the 
Act provides an exception that, in the case of a specified area or 
medical topic determined appropriate by the Secretary for which a 
feasible and practical measure has not been endorsed by the entity with 
a contract under section 1890(a) of the Act, the Secretary may specify 
a measure that is not so endorsed as long as due consideration is given 
to measures that have been endorsed or adopted by a consensus 
organization identified by the Secretary. As noted earlier, we believe 
the maternal health crisis is urgent, maternal health inequities are 
unacceptable, and this persistent problem requires immediate action.
    Comment: Several commenters requested additional support or 
consideration for certain hospital and facility types. Several 
commenters expressed concern that the designation would have unintended 
consequences for small and rural hospitals as well as hospitals, 
including Indian Health Service (IHS) hospitals, caring for populations 
that have been historically underserved. Commenters cautioned that such 
a designation could potentially exacerbate disparities and limit access 
in areas where hospitals struggle to maintain labor and delivery units 
due to low volume. Commenters worried that patients with the means to

[[Page 49287]]

seek care elsewhere could bypass local undesignated hospitals due to a 
perception of low-value care, further reducing the availability and 
provision of maternity care in those communities. A few commenters 
requested CMS consider exempting IHS providers from the designation.
    A few commenters recommended the designation consider hospital 
capacity and offer special consideration to low-volume hospitals to 
avoid penalizing those hospitals by withholding a designation that 
could improve access to quality maternity care. The commenters noted 
that rural hospitals may lack the resources to participate in perinatal 
quality improvement collaboratives. The commenters suggested providing 
incentives and resources to rural hospitals to collaborate with any 
nearby hospital to achieve collective designation, thereby allowing 
more pregnant individuals to seek care at a local hospital. Similarly, 
another commenter requested CMS set aside funding for technical 
assistance for rural hospitals and other facilities to fill in gaps in 
training and workforce shortages that limit a hospital from 
participating in a perinatal quality improvement collaborative.
    A commenter requested clarification on whether IPPS-exempt, self-
governing children's hospitals would be eligible for the designation.
    Response: We appreciate commenters sharing their concerns. As 
stated in the FY 2023 IPPS/LTCH PPS proposed rule, geographic 
disparities in maternal outcomes persist and we recognize the 
challenges faced by small and rural hospitals that offer maternity care 
in these areas, as well as poor maternal health outcomes 
disproportionately affecting rural communities of color, including 
American Indian/Alaska Native people (87 FR 28548). We additionally 
appreciate commenters' concerns regarding the resources required to 
participate in a perinatal quality improvement collaborative and 
subsequently affirmatively attest to the Maternal Morbidity Structural 
measure in order to earn the designation. We recognize that rural and 
low-volume hospitals may face challenges achieving the designation. We 
intend to work with HRSA to explore approaches that could support 
maternity care quality improvement in those facilities in the future. 
In the Blueprint, the Biden-Harris Administration states its intent to 
improve rural obstetric readiness at hospitals and IHS facilities by 
developing guidelines and standards so that facilities without 
obstetric units are still ``obstetric ready,'' expanding HRSA's Rural 
Maternity and Obstetrics Management Strategies (RMOMS) Program to 
enhance access to maternal and obstetric care in rural communities, and 
providing free readily-accessible online obstetrical trainings to HRSA-
funded health centers and free clinics to support the delivery of 
competent preconception, prenatal, intrapartum, and postpartum 
care.\1040\
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    \1040\ The White House. White House Blueprint for Addressing the 
Maternal Health Crisis. June 2022. Available at: https://www.whitehouse.gov/wp-content/uploads/2022/06/Maternal-Health-Blueprint.pdf.
---------------------------------------------------------------------------

    With regard to the recommendation to offer financial or technical 
assistance, we note that the Hospital IQR Program statute does not 
authorize incentive payments based on performance as it is a pay-for-
reporting program. However, with our federal partners, we will explore 
opportunities to offer technical and other resources to providers. With 
regard to considerations for hospital capacity, we will consider the 
suggestions for potential modifications to the designation in the 
future and explore additional variables that can affect quality of 
maternity care, including but not limited to delivery volume, staffing 
capabilities, and levels of risk-appropriate care. Any additional 
changes would be made through future rulemaking. Regarding a commenter 
requesting clarification on IPPS-exempt children's hospitals, we note 
that we use data from participating subsection (d) hospitals and CAHs 
that voluntarily participate in the Hospital IQR Program for the 
designation, which means IPPS-exempt children's hospitals are excluded. 
We further wish to clarify that subsection (d) hospitals participating 
in the Hospital IQR Program receive credit under the Hospital IQR 
Program for the reporting of their Maternal Morbidity Structural 
measure results, whether they attest to the affirmative or not because 
it is a pay-for-reporting program (86 FR 45365). This designation is in 
addition to, but separate from, the reporting of the Maternal Morbidity 
Structural measure. We continue to assess opportunities to improve 
maternity care quality, safety, and equity through this designation and 
will consider strategies focused on rural and low-volume hospitals in 
future notice-and-comment rulemaking.
    Comment: Several commenters requested that any measures used to 
inform the designation be risk-adjusted. Some commenters also requested 
that publicly reported measure data be disaggregated and stratified 
across drivers of health. A few commenters requested that publicly 
reported data from the designation should include indicators for 
consumers when a hospital delivers care primarily to populations that 
are disadvantaged and/or underserved by the healthcare system.
    Response: We thank the commenters for their feedback. The initial 
implementation of the designation would be based on the Maternal 
Morbidity Structural measure, which is an attestation-based measure 
that is not risk-adjusted or stratified. We will consider the 
feasibility, applicability, and appropriateness of risk-adjustment and 
stratification of measures as we continue to develop this designation 
in future years. We refer readers to the Overarching Principles for 
Measuring Healthcare Quality Disparities Across CMS Quality Programs--
Request for Information in section IX.B. of the preamble of this final 
rule for more information on CMS' potential use of measure 
stratification in the future.
    Comment: A few commenters recommended CMS develop a monitoring 
program to inform consumers on the efficacy of the designation, both 
for hospitals that receive the designation and those that do not. The 
commenters recommended hospitals that did not receive the designation 
should be monitored to determine whether a lack of designation may 
contribute to a reduction in maternity care access and/or quality, 
including the closure of obstetric units.
    Response: We thank commenters for this recommendation and as we 
monitor hospital performance on the Maternal Morbidity Structural 
measure and the new designation, we will consider mechanisms to assess 
the implementation and impact of the designation.
    Comment: Several commenters emphasized the importance of engaging 
interested parties at state, local, and national levels prior to 
implementing the designation and in advance of making any modifications 
to the qualification requirements for the designation. Some commenters 
noted that the designation is likely to lack value to hospitals, 
patients, and communities without engagement with relevant interested 
parties across the spectrum of maternal health. Several commenters also 
expressed disappointment and concern that more outreach was not done 
prior to the creation of the designation and requested a delay in 
implementation so that hospitals have time to allocate the resources 
required to qualify for the designation. A commenter noted that labor 
and resource shortages resulting from the ongoing COVID-19 PHE continue 
to impact hospitals and a delay in implementation is needed.

[[Page 49288]]

    Response: We appreciate feedback from interested parties and the 
value it adds to proposals set forth for the Hospital IQR Program. We 
finalized the adoption of the Maternal Morbidity Structural measure for 
the Hospital IQR Program in the FY 2022 IPPS/LTCH PPS final rule with a 
reporting period starting October 1, 2021 (86 FR 45361). We 
additionally indicated our commitment to a serious focus and rapid 
action for maternal health improvement (86 FR 45365). We seek to use a 
whole-of-government approach for improving maternal health and 
advancing maternal health equity to reduce maternal mortality and 
morbidity, reduce persistent disparities, and increase hospital 
participation in evidence-based maternal health quality improvement 
initiatives. As mentioned earlier, we signaled our intent for this 
designation in December 2021 alongside Vice President Harris' 
``Maternal Health Day of Action.'' It is our intention to consider 
ongoing opportunities for engagement with interested parties as we 
continue to improve upon the designation across future years. While we 
recognize that hospitals may participate in a variety of quality 
improvement activities with a focus on maternal health and that many 
hospitals face challenges due to the COVID-19 PHE, we believe that the 
maternal health crisis is urgent, maternal health inequities are 
unacceptable, and this persistent problem requires prompt action. Thus, 
we do not believe delaying the fall 2023 implementation timeframe to 
launch the hospital designation information to the public is 
sufficiently responsive nor appropriate.
    Comment: A few commenters expressed concern about the reputational 
impact to birth centers and other non-hospital birthing facilities that 
may provide especially high-quality care but will be excluded from the 
designation as they do not participate in the Hospital IQR Program.
    Response: We thank the commenters, and we recognize that people may 
receive maternity care in a non-hospital birthing facility for a 
variety of reasons. Birth centers, for example, are not subsection (d) 
hospitals, so they cannot participate in the Hospital IQR Program, and 
would therefore not be eligible for a designation. We encourage 
consumers to utilize publicly reported quality information to better 
understand the quality of maternity services and care available in 
their communities. We also intend to provide additional outreach, 
communication, and educational materials as we launch the designation.
    After consideration of the public comments we received, we are 
finalizing our proposal as proposed.
d. Solicitation of Comments on Designation Name and Additional Data 
Sources To Consider for Purposes of Awarding This Publicly-Reported 
Hospital Designation
    While our ultimate goal is to designate hospitals with demonstrated 
commitment to the provision of high-quality, safe, and equitable 
maternity care, we wish to do so in a way that is meaningful and useful 
to patients and their families as well as clinicians and hospitals. 
Therefore, we solicited comments on a name for this designation for 
future years.
    In addition as noted previously, we proposed to designate hospital 
commitment to maternity care quality and safety based initially on data 
collected on the Maternal Morbidity Structural measure. Our intent is 
to expand the criteria we use to award this designation so that it more 
comprehensively captures the quality and safety of the maternity care 
delivered by hospitals. Other future sources of data potentially 
include data collected on the two eCQMs we proposed to add to the 
Hospital IQR Program measure set, or data on other Hospital IQR Program 
maternal health measures, should such measures be adopted in the 
future. We also considered the feasibility of including other quality 
measurement data sources. In particular, we welcomed comments about 
patient experience measures that could be relevant for this 
designation, including patient experience measures that are currently 
in use in other care settings, patient experience measures that have 
been developed but require additional testing in pilot settings, or 
other measures of patient experience that would be appropriate for 
inclusion in the designation.
    We invited public comment on these and other potential quality 
measurement data sources that would be appropriate to include in a 
designation that captures the quality and safety of maternity care 
furnished by hospitals, including quality measures used in other 
quality reporting programs or care delivery settings. In the previous 
section IX.E.8.c., we address related comments in the discussion of the 
maternity care hospital designation. This section of this document 
contains additional comments received related to the designation name 
and additional sources of data to consider.
    Comment: Many commenters shared other recommendations related to 
potential future iterations of the designation. Many commenters urged 
CMS to use evidence-based outcome measures to inform a designation 
instead of the attestation-based Maternal Morbidity Structural measure. 
Several commenters recommended inclusion of existing levels of maternal 
care (LoMC) \1041\ in the designation, including those already promoted 
and endorsed by national stakeholder groups, accrediting bodies, and 
commissions, as an alternative to participation in a perinatal quality 
improvement collaborative. Another commenter suggested CMS consider 
other payment models, including trauma activation or a maternal and 
fetal health disproportionate share reimbursement model that combines 
U.S. Census indices with Healthcare Effectiveness Data and Information 
Set (HEDIS) and CCO data. A commenter suggested designated hospitals be 
required to offer remote patient monitoring to high-risk patients. One 
commenter believes that the designation would be better managed by an 
accreditation agency rather than CMS.
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    \1041\ American College of Obstetricians and Gynecologists. 
Levels of Maternal Care. 2021. Available at: https://www.acog.org/clinical/clinical-guidance/obstetric-care-consensus/articles/2019/08/levels-of-maternal-care.
---------------------------------------------------------------------------

    Response: We appreciate commenters' suggestions. We note that the 
Hospital IQR Program specifically uses quality measures to improve the 
quality of care as a pay-for-reporting program. As previously stated, 
we intend to continue exploring opportunities to refine the designation 
for the future based on measures that are meaningful and useful for 
patients and hospitals.
    Comment: A few commenters urged CMS to dedicate sufficient 
resources to clearly and deliberately communicate with and educate 
consumers so they are easily able to understand what the designation 
does and does not indicate. A couple of commenters recommended a 
consumer-focused campaign with details about the designation and where 
to find information on which hospitals are designated. The commenters 
also recommended that such a campaign include resources on safe and 
healthy birth for consumers who may not have access to a designated 
facility or may not have a provider with clinical privileges in a 
designated hospital. A commenter suggested we partner with local health 
departments and Medicaid offices to share information in multiple 
formats and languages with consumers.
    Response: We agree with commenters about the importance of clear 
communication, and are dedicated to communicate in a way that is 
culturally and linguistically appropriate and

[[Page 49289]]

accessible by people with disabilities, with consumers. We intend to 
work with hospitals and other interested parties to make information 
about the designation available and accessible to patients, their 
families, and communities in a way that clearly describes what the 
designation means and where they can find additional information and 
resources.
    Comment: Commenters had varying recommendations on whether other 
maternal health measures proposed for the Hospital IQR Program would be 
appropriate for inclusion in the designation. Several commenters 
supported the future inclusion of the Cesarean Birth eCQM and Severe 
Obstetrics Complications eCQM in the designation. Conversely, a few 
commenters opposed the potential inclusion of these two eCQMs into the 
designation citing potential burden concerns. A few commenters 
specifically noted that they would not support the inclusion of the 
Cesarean Birth eCQM as part of the designation until it receives NQF 
endorsement.
    Response: We thank commenters for their recommendations on the 
potential future inclusion of the Cesarean Birth eCQM and Severe 
Obstetrics Complications eCQM as part of the designation. We will 
consider these measures as we continue to develop this designation. Any 
additional measures or data sources would undergo notice-and-comment 
rulemaking before inclusion in the designation. In regard to NQF 
endorsement, we remind readers that both of these eCQMs are currently 
undergoing NQF review and refer readers to our response in sections 
IX.E.5.c. and IX.E.5.d. to similar comments. While we prioritize 
measures that are endorsed when available, we reiterate that section 
1886(b)(3)(B)(viii)(IX)(bb) of the Act provides an exception that, in 
the case of a specified area or medical topic determined appropriate by 
the Secretary for which a feasible and practical measure has not been 
endorsed by the entity with a contract under section 1890(a) of the 
Act, the Secretary may specify a measure that is not so endorsed as 
long as due consideration is given to measures that have been endorsed 
or adopted by a consensus organization identified by the Secretary. We 
further reiterate, as stated in the FY 2022 IPPS/LTCH PPS final rule 
(86 FR 45365) that, given the severity of the maternal morbidity crisis 
and as there are currently no NQF-endorsed measures that address 
maternal morbidity through hospital participation in Statewide or 
national Perinatal QI Collaboratives, we believe it is important to 
implement this measure as soon as possible.
    Comment: Many commenters suggested other measures for inclusion in 
the designation requirements. Several commenters recommended 
breastfeeding measures. Several commenters recommended that the 
designation include a requirement to demonstrate the provision of 
respectful maternity care, which could include training on cultural 
competency, implicit bias, and antiracism. A few commenters suggested 
demonstration of hiring practices that are culturally and community 
representative. A couple of commenters recommended maternity 
adaptations of the sixth CAHPS development cycle to track disrespect 
and related forms of provider behavior. The commenters also suggested 
Patient Reported Outcome Measures (PROMs) and Patient-Reported Outcome-
based Performance Measures (PRO-PMs) measuring the various dimensions 
of respect and experience of care. Several commenters emphasized the 
importance of a designation that highlights hospitals providing access 
to a diverse maternity care workforce. Commenters cited certified nurse 
midwives and certified midwives, doulas, certified lactation 
consultants, community health workers, mental health professionals, and 
substance use treatment clinicians as vital members of the team. Some 
commenters recommended the designation include a requirement for 
hospitals to report whether or not they provide access to such 
providers. A commenter recommended CMS adopt a sufficient minimum 
staffing rate as a designation criterion to ensure quality and safety 
in maternity care delivery. One commenter recommended hospitals seeking 
the designation conduct simulations of urgent or emergency obstetric 
scenarios, attest that they have regional transport agreements in 
place, and that emergency department staff are trained in neonatal 
resuscitation. Another commenter recommended a measure of postpartum 
patients with new medical conditions who are discharged with at least 
seven days of medication. Another commenter recommended requiring 
implementation of the AIM Postpartum Discharge Transition Patient 
Safety Bundle.\1042\ Another commenter suggested a structural measure 
of hospital participation in Maternal Early Warning System (MEWS) 
programs.\1043\ Another commenter recommended measurement of the rate 
of completion of two-week postpartum visits. Another commenter 
recommended a measure of access to a certified lactation consultant. 
Another commenter suggested a measure of skin-to-skin rates. Another 
commenter recommended a measure of access to postpartum contraception 
(NQF #2902) as well as a measure of unexpected complications of the 
healthy newborn (NQF #0716). A couple of commenters recommended CMS 
include the establishment of a hemorrhage protocol as a requirement of 
the designation. Another commenter recommended implementation of a 
triage acuity tool specifically designed for obstetric units as a 
component of the designation.
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    \1042\ American College of Obstetrics and Gynecology. Alliance 
for Innovation on Maternal Health (AIM). 2014. Available at: https://www.acog.org/practice-management/patient-safety-and-quality/partnerships/alliance-for-innovation-on-maternal-health-aim.
    \1043\ TCHMB. Maternal Early Warning System. Available at: 
https://www.tchmb.org/maternal-early-warning-
system#:~:text=The%20Maternal%20Early%20Warning%20System,avoiding%20m
ajor%20morbidity%20and%20mortality.
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    Several commenters expressed concern about the rights of patients 
and their ability to access medically necessary care. A couple of 
commenters recommended that any hospitals that receive the designation 
be required to transparently report any non-medical restrictions on 
care, including bans on postpartum tubal ligations, offering other 
forms of postpartum contraception, and treatments for ectopic pregnancy 
or premature rupture of membranes. The commenters also requested a 
commitment from designated hospitals to publicly report the number of 
patients who are denied those forms of care each year. Additionally, 
the commenters recommended that designated hospitals not be allowed to 
send away patients with emergency medical conditions and should be 
required to comply with Emergency Medical Treatment and Labor Act 
(EMTALA). The commenters further encouraged CMS to utilize Beneficiary 
and Family Care Quality Improvement Organizations (BFCC-QIOs) and 
Quality Innovation Network (QIN) QIOs to help patients better 
understand the quality of care to which they are entitled, work with 
hospitals to improve delivery of care, assist patients with complaint 
processes, and help patients understand their rights and hospitals 
their obligations under EMTALA.
    Response: We thank the commenters for their feedback and appreciate 
their robust recommendations. We note that we recently communicated 
with hospitals regarding their existing obligations to comply with 
EMTALA and refer readers to https://www.cms.gov/files/document/qso-22-

[[Page 49290]]

22-hospitals.pdf for more details.\1044\ We further reaffirm our 
ongoing commitment to improving maternal health and note that actions 
related to many suggestions from commenters are discussed in more 
detail in the Biden-Harris Administration's Blueprint for Addressing 
the Maternal Health Crisis, including the call to eliminate coverage 
gaps for postpartum women by encouraging states to extend Medicaid 
coverage from 60 days to a full 12 months postpartum.\1045\ The 
Blueprint also discusses plans to address the gaps in our perinatal 
workforce, including increasing the number of physicians, licensed 
midwives, doulas, and community health workers in communities that are 
historically underserved and under-resourced by the healthcare system; 
providing guidance to states to help them expand access to licensed 
midwives, doulas, and freestanding birth centers in Medicaid; and 
encouraging insurance companies to improve reimbursement for and 
coverage of licensed midwives and perinatal supports, such as doulas 
and nurse home visits.\1046\ Additionally, the FY 2023 President's 
Budget allocates funds to help train providers on implicit biases as 
well as culturally and linguistically appropriate care and to educate 
and empower more pregnant women and families to know the early warning 
signs of pregnancy-related complications and behavioral health 
needs.\1047\ We appreciate these recommendations as we consider future 
direction and policy related to the designation for future notice-and-
comment rulemaking.
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    \1044\ Centers for Medicare & Medicaid Services Center for 
Clinical Standards and Quality. QSO-22-22-Hospitals. Reinforcement 
of EMTALA Obligations specific to Patients who are Pregnant or are 
Experiencing Pregnancy Loss (QSO-21-22-HospitalsUPDATED JULY 2022). 
July 2022. Available at: https://www.cms.gov/files/document/qso-22-22-hospitals.pdf.
    \1045\ The White House. White House Blueprint for Addressing the 
Maternal Health Crisis. June 2022. Available at: https://www.whitehouse.gov/wp-content/uploads/2022/06/Maternal-Health-Blueprint.pdf.
    \1046\ The White House. White House Blueprint for Addressing the 
Maternal Health Crisis. June 2022. Available at: https://www.whitehouse.gov/wp-content/uploads/2022/06/Maternal-Health-Blueprint.pdf.
    \1047\ The White House. Budget of the U.S. Government Fiscal 
Year 2023. Accessed June 24, 2022. Available at: https://www.whitehouse.gov/wp-content/uploads/2022/03/budget_fy2023.pdf.
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    Comment: A commenter recommended future measures be submitted 
through the Measures Under Consideration (MUC) process.
    Response: We thank the commenter for the suggestion and note that 
measures adopted for the Hospital IQR Program are required to go 
through the pre-rulemaking process (which includes the MUC process and 
review of the MAP) in compliance with section 1890A of the Act.
    Comment: Another commenter cautioned that hospitals should not be 
penalized through components in the designation that fail to account 
for patients who choose to receive care from non-physician 
practitioners and are then transferred to physician care late in 
pregnancy due to an advanced complication. The commenter stated that 
many factors remain outside of the control of the hospital or treating 
physician and designation components should take this into account. A 
few commenters urged CMS to maintain facility-level measures under the 
designation and cautioned against the adoption of physician-level 
measures.
    Response: We acknowledge the commenter's concern and understand the 
commenter to mean that hospitals may provide care to pregnant patients 
in labor or delivery who have not previously received care at that 
hospital and the commenter is concerned about the impact such 
situations may have on a hospital's ability to earn the designation. At 
this time, the designation is based solely on affirmative attestation 
to the Maternal Morbidity Structural measure and we do not believe that 
situations such as those described by the commenter would negatively 
affect a hospital's ability to attest to that measure. We further 
recognize that there are factors beyond the control of hospitals when 
treating pregnant women, but we believe that the maternal health crisis 
requires urgent action, and that this designation can support hospital 
action on maternal health quality improvement activities.
    Comment: Several commenters suggested names for the new maternity 
care hospital designation. A few commenters suggested ``Quality 
Birthing Hospital'' as a possible name. A commenter recommended use of 
``Birth Star Hospital'' or ``Better Birthing Hospital'' to reflect the 
quality of birthing care. Another commenter suggested ``Quality Care 
for Birthing People'' while another commenter recommended ``Quality 
Care and Birth Equity'' or ``Excellence in Birthing Outcomes.'' Another 
commenter suggested ``Birthing-Conscious Hospital'' to reflect the 
maternal and neonatal process. Another commenter suggested ``Center of 
Excellence in Maternity Care.''
    Several commenters stated that the designation name should reflect 
the data it is measuring and meaningfully represent the population of 
interest. A commenter recommended that the name emphasize our 
commitment to excellence. Another commenter cautioned against a name 
that could be mistaken for marketing.
    Several commenters were concerned that use of ``birthing-friendly'' 
was too similar to the Baby-Friendly Hospital Initiative, a program 
developed by the World Health Organization (WHO) and the United Nations 
International Children's Emergency Fund (UNICEF). The commenters 
encouraged moving away from use of ``birthing-friendly'' to avoid any 
potential confusion.
    Response: We thank commenters for their suggestions and will take 
them into consideration for a future name for the designation.
e. Additional Activities To Advance Maternal Health Equity--Request for 
Information
    We are committed to advancing equity for all, including those in 
historically underserved and under-resourced communities (American 
Indian or Alaska Native, Asian or Pacific Islander, Black, Hispanic, 
and other persons of color; members of religious minorities; lesbian, 
gay, bisexual, transgender, and queer (LGBTQ+) persons; persons with 
disabilities; persons who live in rural areas and others who have been 
historically underserved, marginalized, and adversely affected by 
persistent poverty and inequality).
    We specifically sought to explore how we can address the U.S. 
maternal health crisis through policies and programs, including, but 
not limited to, the Conditions of Participation (CoPs) and through 
measures in our quality reporting programs. The CoPs are the health and 
safety standards that Medicare-certified providers and suppliers must 
meet to receive Medicare and Medicaid payment. CMS has broad statutory 
authority to establish health and safety regulations for various 
providers and suppliers; that statutory authority is usually found 
within the statutory definition of each provider and supplier type. In 
the case of hospitals, for instance, section 1861(e)(1) through (8) of 
the Act sets out specified requirements that hospitals must meet; in 
addition, section 1861(e)(9) of the Act requires hospitals to ``meet[ ] 
such other requirements as the Secretary finds necessary in the 
interest of the health and safety of individuals who are furnished 
services in the institution.''
    We invited public comment on the following:
     CMS outlines best practices in the memorandum to state 
survey agencies entitled ``Evidence-Based Best Practices for Hospitals 
in Managing Obstetric

[[Page 49291]]

emergencies and Other Key Contributors to Maternal Health 
Disparities.'' \1048\ What other additional effective best practices or 
quality improvement initiatives are currently being utilized by 
hospitals? How else can hospitals improve maternal health outcomes, 
enhance their quality of maternity care, and reduce maternal health 
disparities?
---------------------------------------------------------------------------

    \1048\ Evidence-based best practices for hospitals in managing 
obstetric emergencies and other key contributors to maternal health 
disparities. U.S. Department of Health and Human Services. https://www.hhs.gov/guidance/document/evidence-based-best-practices-hospitals-managing-obstetric-emergencies-and-other-key.
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     For hospitals that offer inpatient maternity services, 
including labor and delivery care, how could the CoPs be modified to 
improve maternity care and address disparities in maternal health 
outcomes? How would hospitals focus their governance, provider and 
staff training, and care-delivery activities to effectively demonstrate 
compliance with CoPs related to improving maternal health outcomes? 
What types of measurable activities targeting maternal health outcomes 
might demonstrate a reduction in maternal health care disparities or 
improvement in maternal health care delivery?
     Are there new requirements that could be established in 
the CoPs that would require hospitals to address and improve the 
quality of postpartum care and support provided to patients? How can 
the CoPs specifically address the need to improve behavioral health 
services and monitoring offered during prenatal and postpartum care?
     Might the potential additional maternal health-focused 
CoPs have unintended consequences on providers with certain 
characteristics (such as being located in a rural area or having low-
volume)? Please provide details on how certain providers might be 
differentially affected by potential maternal health CoPs. Are there 
barriers or facilitators that would influence rural hospital 
achievement of a publicly-reported maternal health designation that may 
not relate directly to the quality of services provided? How might 
maternal health CoPs impact providers considering whether it is 
feasible or viable to offer labor and delivery services in their area?
     What services and staff training should hospitals without 
inpatient maternity services have in place in preparation for patients 
in labor?
     What are the best practices that hospitals are utilizing 
to educate and conduct outreach to patients in underserved communities 
to increase access to timely maternity care?
     What are best practices for hospitals to actively engage 
with patients and their families, community-based organizations, and 
others within their local community to obtain information on ways to 
improve maternity care? Are there barriers to such engagement (if so, 
what are the barriers)?
     Do hospitals provide prevention-related education and 
community outreach on the specific maternal health conditions that have 
the greatest impact on disadvantaged and underserved communities?
     How can hospitals review and monitor aggregate data on the 
maternal health risks of the patient population that they serve? What 
data should hospitals review related to the maternal health risks of 
the patient population they serve? What data sharing best practices are 
required for hospitals to share data with external entities, including 
local and state health departments, community-based organizations, or 
other health care providers? How can hospitals connect data collected 
for mothers and their babies after delivery to support research and 
evaluation of maternal health care after delivery?
     What challenges are there to collecting data on patients 
with specific maternal health risks? Can these data be stratified by 
demographics (for example, race and ethnicity)? In addition, how can 
these data be used in a hospital's quality improvement efforts, and 
specifically, in their quality assurance and performance improvement 
(QAPI) program, to improve maternal health outcomes and advance health 
equity and reduce disparities within their facility? How can maternity 
care can be incorporated into an ongoing QAPI program?
     How do hospitals conduct reviews of maternal deaths that 
have occurred within the facility?
     Are hospitals currently utilizing community health needs 
assessments to determine the specific maternity care needs and social 
determinants of health of the patient population that they serve? For 
those hospitals that are utilizing community health needs assessments, 
are there certain best practices or examples of ways that this 
assessment can be used to reduce disparities in maternal outcomes?
     Do hospitals have reporting relationships or mechanisms 
among primary care physicians, obstetrician-gynecologists, and other 
health care providers such as nurses and certified nurse midwives, and 
community-based perinatal workers, such as doulas, for optimal 
coordination of care?
     Do hospitals have readily available referral relationships 
and points of contact with community resources or community-based 
organizations to address additional services that a postpartum patient 
may need upon discharge? This could include the consideration of 
behavioral and mental health services or resources to address health-
related social needs, such as food insecurity, housing instability, and 
transportation challenges. If hospitals do not have readily available 
referral relationships and points of contact within the community, what 
barriers and facilitators impact hospital relationships with community 
resources or community-based organizations?
     How do hospitals evaluate their perinatal customer 
experience? What are best practices that are currently being utilized 
for getting robust input from patients on their perinatal experience?
     What best practices exist for ensuring systemic racism and 
biases, including implicit bias, are not perpetuated in maternity care?
    We received comments on this topic.
    Comment: Commenters provided many recommendations for additional 
maternal health considerations. These included suggestions on how to 
effectively disseminate best practices in maternity care, the potential 
applicability of CoPs related to maternal health outcomes, staff 
training on antiracism and implicit bias in maternity care, approaches 
for risk-adjustment and stratification of maternal health data, 
frameworks for implementing maternal health safety monitoring programs, 
integration of comprehensive clinical and community-based maternity 
care delivery systems, opportunities for hospitals to build referral 
relationships with community-based providers, staffing cross-functional 
and holistic maternity care teams, and designing customer experience 
and evaluation tools for maternity care patients and families.
    Commenters additionally shared examples from state, local, and 
regional groups as well as individual hospitals working to improve 
maternity care. Commenters also urged our pursuit of meaningful, 
continuous outreach with interested parties to ensure that future 
maternal health actions are effective and add value to hospitals, 
patients, and communities.
    Response: We appreciate learning about the many meaningful programs 
and practices hospitals are utilizing across our nation and the 
commitment to implementation of evidence-based practices to improve 
maternal health and maternity care delivery. We also

[[Page 49292]]

thank commenters for the range of recommendations and measure 
suggestions. As noted in the Blueprint, every person should have a 
safe, dignified pregnancy and birth and equitable access to health care 
before, during, and after pregnancy.\1049\ We will consider all input 
as we continue to develop and make progress in strategies that address 
maternity care quality, safety, and equity in the Hospital IQR Program, 
through potential new CoPs, and other CMS activities, and will continue 
outreach to interested parties on future maternal health actions.
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    \1049\ The White House. White House Blueprint for Addressing the 
Maternal Health Crisis. June 2022. Available at: https://www.whitehouse.gov/wp-content/uploads/2022/06/Maternal-Health-Blueprint.pdf.
---------------------------------------------------------------------------

9. Future Considerations
    We seek to develop a comprehensive set of quality measures to be 
available for widespread use for informed decision-making and quality 
and cost improvements through the inpatient hospital setting. We have 
identified potential future measures for future development, which we 
believe address areas that are important to stakeholders, but which are 
not currently covered in the Hospital IQR Program. Therefore, in the FY 
2023 IPPS/LTCH PPS proposed rule (87 FR 28550) we sought comment on 
these potential future considerations, as detailed later in the 
section.
    We also refer readers to the following sections: (1) section IX.A. 
where we sought comments from stakeholders on the health impacts due to 
climate change, especially on underserved populations, and how we could 
potentially support hospitals and health systems to more effectively 
determine and plan for climate impacts, reduce greenhouse gas 
emissions, and track progress; (2) section IX.B. where we sought input 
on overarching principles in measuring healthcare quality disparities 
in hospital quality programs and value-based purchasing programs; and 
(3) section IX.C. where we sought input on ongoing ways we can advance 
digital quality measurement and use of Fast Healthcare Interoperability 
Resources (FHIR) in quality reporting programs.
a. Potential Future Inclusion of Two Digital National Healthcare Safety 
Network (NHSN) Measures
    The Hospital IQR Program previously included NHSN measures that 
were finalized for removal from the measure set in the FY 2019 IPPS/
LTCH PPS final rule (83 FR 4157 through 41553), and retained in the 
Hospital-Acquired Condition (HAC) Reduction Program (83 FR 41474 
through 41477; 83 FR 41449 through 41452) and the Hospital VBP Program 
(83 FR 41449 through 41452). We have recently identified two new 
potential measures that utilize EHR-derived data to help address 
hospital-based adverse events, specifically, hospital-onset infections.
    In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28550 through 
28554), we discussed these two measures in more detail and sought 
public comment on the future inclusion of these measures in the 
Hospital IQR Program. We also invited public comment on other aspects 
of these two measures related to future implementation. In addition, we 
sought public comment on the application of one or both of these 
measures in other quality reporting programs, including the HAC 
Reduction Program, the Hospital VBP Program, the PCHQR Program, and the 
LTCH QRP.
(1) National Healthcare Safety Network (NHSN) Healthcare-Associated 
Clostridioides difficile Infection Outcome Measure
(a) Background
    Clostridioides difficile \1050\ is a bacterium that causes 
diarrhea, pseudomembranous colitis, and toxic megacolon which can lead 
to sepsis or death.1051 1052 1053 
Clostridioides difficile infections (CDI) can be reduced in healthcare 
settings using a multi-faceted approach, including development of an 
infrastructure for monitoring CDI, implementation of effective 
antibiotic stewardship to reduce the use of unnecessary antibiotics, 
isolation and contact precautions for patients with CDI, performance of 
environmental cleaning with sporicidal agents, and other 
measures.\1054\ CDI is one of the most common healthcare-associated 
infections (HAIs) in the U.S.1055 1056 At any 
given time, 1 in 31 patients has an HAI in the U.S., and over a million 
cases of HAIs are reported every year, making HAIs one of the most 
common adverse events that occurs in a healthcare 
setting.1057 1058
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    \1050\ The Clostridioides difficile bacterium was previously 
called clostridium difficile. The naming was updated in 2016 due to 
taxonomic updates.
    \1051\ Centers for Disease Control and Prevention (CDC). What is 
C. diff? Available at: https://www.cdc.gov/cdiff/what-is.html.
    \1052\ Centers for Disease Control and Prevention (CDC). 
Clostridioides difficile Infection (CDI) Tracking. Available at: 
https://www.cdc.gov/hai/eip/cdiff-tracking.html.
    \1053\ Centers for Medicare & Medicaid Services National 
Healthcare Safety Network (NHSN) Facility-wide Inpatient Hospital-
onset Clostridium difficile Infection (CDI) Outcome Measure. 
Available at: https://cmit.cms.gov/cmit/#/MeasureView?variantId=606§ionNumber=1.
    \1054\ Centers for Disease Control and Prevention (CDC) CDI 
Prevention Strategies. Available at: https://www.cdc.gov/cdiff/clinicians/cdi-prevention-strategies.html.
    \1055\ Kwon, J.H., Olsen, M.A., Dubberke, E.R. (2015). The 
Morbidity, Mortality, and Costs Associated with Clostridium 
difficile Infection. Infect Dis Clin North Am. 29(1):123-34. 
Available at: https://www.sciencedirect.com/science/article/abs/pii/S0891552014000804?via%3Dihub.
    \1056\ Magil, S.S., O'Leary, E., Janelle, S.J., Thompson, D.L., 
Ghinwa, D., Nadle, J., et al. (2018). Changes in Prevalence of 
Health Care-Associated Infections in U.S. Hospitals. N Engl J Med. 
379:1732-1744. DOI: 10.1056/NEJMoa1801550.
    \1057\ Magil, S.S., O'Leary, E., Janelle, S.J., Thompson, D.L., 
Ghinwa, D., Nadle, J., et al. (2018). Changes in Prevalence of 
Health Care-Associated Infections in U.S. Hospitals. N Engl J Med. 
379:1732-1744. DOI: 10.1056/NEJMoa1801550.
    \1058\ Haque M, Sartelli M, McKimm J, Abu Bakar M. (2018). 
Health care-associated infections--an overview. Infect Drug Resist. 
11:2321-2333. doi:10.2147/IDR.S177247.
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    As one of the most common HAIs, CDIs are a significant contributor 
to inpatient morbidity and mortality, particularly among older 
adults.\1059\ Incidence of CDI is higher among White patients, female 
patients, and patients over 65 years of age.\1060\ CDIs result in an 
estimated 500,000 cases annually and between 15,000 and 20,000 
deaths.\1061\ Additionally, costs associated with CDIs average about 
$11,400 per case and can have a significant impact on the U.S. 
healthcare system.\1062\ More broadly, HAIs cost over $9.8 billion 
dollars annually with CDIs contributing to 15.4 percent, or about $1.5 
billion dollars of these total annual costs.\1063\ Therefore, we 
currently require reporting of CDI outcomes, along with other HAIs, in 
value-based purchasing programs like the Hospital VBP Program and HAC

[[Page 49293]]

Reduction Program, in order to connect performance on HAI measures with 
payment adjustments.\1064\
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    \1059\ Centers for Disease Control and Prevention. (2018). 
Analysis and Recommendations on the NHSN Clostridioides difficile 
Outcome. Available at: https://www.cdc.gov/hicpac/pdf/NHSN-C-diff-
H.pdf#:~:text=NHSN%20is%20the%20most%20widely%20used%20secure%2C%20in
ternet-based,decreasing%20in%20contrast%20to%20other%20healthcare-
associated%20infections.%202.
    \1060\ Lessa FC, Mu Y, Bamberg WM, et al. (2015). Burden of 
Clostridium difficile infection in the United States. N Engl J Med. 
372(9):825-34. doi: 10.1056/NEJMoa1408913.
    \1061\ Zaver, H.B., Moktan, V.P, Harper, E.P., et al. (2021). 
Reduction in Health Care Facility--Onset Clostridioides difficile 
Infection: A Quality Improvement Initiative. Mayo Clin Proc Innov 
Qual Outcomes. 5(6):1066-1074. doi: 10.1016/j.mayocpiqo.2021.09.004.
    \1062\ Zimlichman E, Henderson D, Tamir O, et al. (2013). Health 
care-associated infections: a meta-analysis of costs and financial 
impact on the US health care system. JAMA Intern Med. 173(22):2039-
46. doi: 10.1001/jamainternmed.2013.9763.
    \1063\ Zimlichman E, Henderson D, Tamir O, et al. (2013). Health 
care-associated infections: a meta-analysis of costs and financial 
impact on the US health care system. JAMA Intern Med.173(22):2039-
46. doi: 10.1001/jamainternmed.2013.9763.
    \1064\ Centers for Disease Control and Prevention. (2018). 
Analysis and Recommendations on the NHSN Clostridioides difficile 
Outcome. Available at: https://www.cdc.gov/hicpac/pdf/NHSN-C-diff-
H.pdf#:~:text=NHSN%20is%20the%20most%20widely%20used%20secure%2C%20in
ternet-based,decreasing%20in%20contrast%20to%20other%20healthcare-
associated%20infections.%202.
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    The CDC has developed the National Healthcare Safety Network (NHSN) 
Healthcare-Associated Clostridioides difficile Infection Outcome 
measure that utilizes EHR-derived data. The goal of this measure is to 
drive an increase in prevention practices, which would result in fewer 
CDI cases and reduced morbidity and mortality in patients. We believe 
this would be especially useful given that most cases of CDIs may be 
prevented or stopped from spreading to other patients when inpatient 
facilities utilize infection control steps recommended by the CDC. We 
believe utilizing the CDC's NHSN reporting and submission 
infrastructure will impose less administrative burden related to data 
collection and submission for this measure.
    Previously, the Hospital IQR Program included a CDI measure which 
only required CDI facility-wide Lab-ID event reporting (we refer 
readers to the FY 2012 IPPS/LTCH PPS final rule, 76 FR 51630 through 
51631).\1065\ The newly developed version of the measure would improve 
on the original version of the measure by requiring both microbiologic 
evidence of CDI in stool and evidence of antimicrobial treatment, 
whereas the original measure only required CDI facility-wide Lab-ID 
event reporting. The addition of anti-microbial treatment evidence may 
provide further validity in the reporting of CDIs, as it serves as a 
surrogate for test results that were clinically interpreted as true 
infections.
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    \1065\ In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41547 
through 41553) we removed the NHSN Facility-Wide Inpatient Hospital-
Onset Clostridium difficile Infection (CDI) Outcome measure (NQF 
#1717) from the Hospital IQR Program measure set but retained it in 
the HAC Reduction Program and Hospital VBP Program where it is 
reported via the CDC NHSN portal (83 FR 41474 through 41477; 83 FR 
41449 through 41452). We removed this measure under removal Factor 
8, the costs associated with a measure outweigh the benefit of its 
continued use in the program (83 FR 41547).
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    The NHSN Healthcare-Associated Clostridioides difficile Infection 
Outcome measure addresses the quality priority of ``Make Care Safer by 
Reducing Harm Caused in the Delivery of Care'' through the Meaningful 
Measures Area of ``Healthcare Associated Infections.'' \1066\ 
Additionally, pursuant to Meaningful Measures 2.0, this measure 
addresses the ``Safety'' and ``Wellness and Prevention'' priority areas 
and aligns with our commitment to a patient-centered approach in 
quality measurement to ensure that patients are safe and receive the 
highest quality care.\1067\
---------------------------------------------------------------------------

    \1066\ Centers for Medicare & Medicaid Services. (2021). 
Meaningful Measures Hub. Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/MMF/General-info-Sub-Page.
    \1067\ Centers for Medicare & Medicaid Services. (2021). Quality 
Measurement Action Plan. Available at: https://www.cms.gov/files/document/2021-cms-quality-conference-cms-quality-measurement-action-plan-march-2021.pdf. We note that Meaningful Measures 2.0 is still 
under development.
---------------------------------------------------------------------------

    In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28551 through 
28552), we requested feedback on the potential future inclusion of the 
NHSN Healthcare-Associated Clostridioides difficile Infection Outcome 
measure into the Hospital IQR Program measure set to aid in disease 
monitoring, provide hospitals and patients with more information to 
inform care delivery, and improve patient outcomes.
(b) Overview of Measure
    The NHSN Healthcare-Associated Clostridioides difficile Infection 
Outcome measure would track the development of new CDIs among patients 
already admitted to healthcare facilities, using algorithmic 
determinations from data sources widely available in EHRs. Both the 
original and new measure employ the Standardized Infection Ratio (SIR), 
a statistic used to track HAIs over time. Along with the SIR, this new 
measure would also use the Adjusted Ranking Metric (ARM) of hospital-
onset CDIs among hospitalized patients. The SIR is a primary summary 
statistic used by the NHSN to track HAIs, and ARM is a new statistic 
available for acute care hospitals that accounts for differences in the 
volume of exposure (specifically, denominator) between facilities. ARM 
provides complementary information to the SIR as ARM provides the 
reliability-adjusted number of events and allows for ranking 
facilities.\1068\
---------------------------------------------------------------------------

    \1068\ More information on how ARM and SIR compare can be found 
at: https://www.cdc.gov/nhsn/ps-analysis-resources/arm/.
---------------------------------------------------------------------------

    The measure was previously endorsed by MAP on June 11, 2019. The 
CDC submitted the measure for re-endorsement and it was included in the 
publicly available ``List of Measures Under Consideration for December 
1, 2021'' (MUC List),\1069\ a list of measures under consideration for 
use in various Medicare programs. The NHSN Healthcare-Associated 
Clostridioides difficile Infection Outcome measure (MUC2021-098) was 
reviewed by the NQF MAP Hospital Workgroup on December 15, 2021, and 
received conditional support pending NQF review and re-endorsement once 
the revised measure is fully tested.\1070\ The MAP Coordinating 
Committee, which provides direction to the MAP workgroups, concurred 
with the recommendations of the MAP Hospital Workgroup.\1071\ We 
understand that the CDC intends to submit the measure in the future for 
NQF review and endorsement.
---------------------------------------------------------------------------

    \1069\ Centers for Medicare & Medicaid Services. (2021). List of 
Measures Under Consideration for December 1, 2021. Available at: 
https://www.cms.gov/files/document/measures-under-consideration-list-2021-report.pdf.
    \1070\ National Quality Forum. (2022). Measure Applications 
Partnership (MAP) 2021-2022 Final Recommendations. Available at: 
https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96698.
    \1071\ National Quality Forum. (2022). Measure Applications 
Partnership 2021-2022 Considerations for Implementing Measures in 
Federal Programs: Clinician, Hospital, and Post-Acute Care Long-Term 
Care: Final Report. Available at: https://www.qualityforum.org/Publications/2022/03/MAP_2021-2022_Considerations_for_Implementing_Measures_Final_Report_-_Clinicians,_Hospitals,_and_PAC-LTC.aspx.
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(c) Data Sources
    Hospitals would provide data for this measure from their EHRs. The 
primary sources of data for determining numerator events include 
microbiology data (CDI test), medication administration data (CDI 
antimicrobial treatment), and patient encounter, demographic, and 
location information.
    To facilitate rapid, automated, and secure data exchange, the CDC's 
NHSN is planning to enable and promote reporting of this measure using 
FHIR. However, as FHIR capabilities are evolving and not yet uniform 
across healthcare systems, the CDC is also planning on enabling 
reporting using the existing Health Level 7 (HL7) Clinical Document 
Architecture (CDA), and potentially other formats as well to provide 
all facilities with an option for reporting. We are also working with 
the CDC and ONC to consider how certified health IT can support 
reporting of data for this measure.
    We invited public comment on potential reporting formats for this 
measure.
(d) Outcome
    The outcome of interest is the number of new CDIs among patients 
already admitted to healthcare facilities.

[[Page 49294]]

(e) Cohort
    The measure cohort consists of all patients in the denominator: the 
expected number of hospital-acquired CDIs based on predictive models 
using facility- and patient- care location data as predictors.
(f) Exclusion Criteria
    The measure excludes patients in the denominator who are not 
assigned to an inpatient bed in an applicable location, including 
outpatient clinics and ED visits. Patients <365 days old will also be 
excluded. As an aside, inpatient rehabilitation locations and inpatient 
psychiatric locations that have their own CMS Certification Number 
(CCN) are also excluded from the denominator.
(g) Risk adjustment
    The risk adjustment was developed with a statistical risk model. 
The SIR is risk adjusted for each facility, and the ARM adjusts for 
volume of exposure between facilities as well as risk adjustment.
(h) Measure Calculation
    The measure assesses the development of new CDI among patients 
already admitted to healthcare facilities.
(i) Numerator and Denominator
    The measure's denominator consists of the expected number of 
hospital-associated CDIs based on predictive models using facility and 
patient care location data as predictors. The numerator consists of the 
total observed number of observed CDIs among all inpatients in the 
facility based on the combination of laboratory test for CDIs plus a 
therapeutic administered within a window period around the specimen 
date.
    We received comments on this topic.
    Comment: Many commenters supported the potential inclusion of the 
NHSN Healthcare-Associated Clostridioides difficile Infection Outcome 
measure in the Hospital IQR Program, stating that it is an improvement 
over the previously developed CDC NHSN Facility-wide Inpatient 
Hospital-onset Clostridium difficile Outcome Measure and will prevent 
hospital-acquired infections. A few commenters suggested that we use a 
phased adoption timeline to give hospitals time to familiarize 
themselves with reporting measure data. A commenter supported the 
measure on the condition that certified health IT systems can support 
data reporting for this measure.
    Response: We thank the commenters for their support and suggestions 
to improve the measure. We will continue to collaborate with the CDC 
and take the feedback into account for future notice-and-comment 
rulemaking.
    Comment: Several commenters did not support potential inclusion of 
the NHSN Healthcare-Associated Clostridioides difficile Infection 
Outcome measure into the Hospital IQR Program. A commenter opposed 
adoption because the measure has not received NQF endorsement yet, 
while another cited uncertainties in the measure definitions. A 
commenter stated that the measure does not take into account patient 
factors that increase the risk of developing CDIs. A commenter believed 
that the technology to report this measure is currently not ready for 
use. Another commenter did not support providing evidence of 
antimicrobial treatment for CDI.
    Response: We thank the commenters for their feedback and for 
sharing their concerns. We will continue to collaborate with the CDC 
and consider this feedback during future notice-and-comment rulemaking.
    Comment: Many commenters requested that we postpone adopting the 
NHSN Healthcare-Associated Clostridioides difficile Infection Outcome 
measure until it has been fully tested for validity and reliability and 
receives NQF endorsement. Several commenters recommended that the 
measure exclude immunocompromised patients or include risk adjustment 
based on patients' vulnerability to infections. A commenter recommended 
that the measure include an exclusion for infections following the use 
of antibiotics and expressed concern about the measure's impact on 
rural and low-volume hospitals. A few commenters requested additional 
clarification and guidance on the measure definitions.
    Response: We appreciate the commenters' recommendations. We note 
that the CDC is still refining the measure specifications. We will take 
this feedback into consideration as part of future notice-and-comment 
rulemaking.
    Comment: Several commenters were concerned that the NHSN 
Healthcare-Associated Clostridioides difficile Infection Outcome 
measure might have unintended side effects, such as hospitals 
discouraging health care practitioners from testing or treating 
patients for CDIs to reduce the number of patients reported in the 
numerator. To prevent this, a few suggested that we consider working 
with the CDC to monitor for such practices, or conduct parallel 
monitoring of complementary metrics. A few commenters expressed concern 
over the administrative burden of reporting the measure, especially 
while Fast Healthcare Interoperability Resources (FHIR) and other 
electronic reporting capabilities are still evolving. A few others 
suggested that CMS delay mandatory reporting to provide hospitals with 
enough time to develop their digital reporting capabilities. A 
commenter recommended that the measure include incentives to hire 
infection prevention staff given that existing staff are already 
overworked.
    Response: We thank commenters for their feedback and share their 
concern for avoiding any negative effects on patient care arising from 
adoption of this measure. We note that this measure is not being 
proposed for adoption at this time and we requested input as we 
consider its future inclusion into quality reporting and value-based 
programs. We will take these comments into consideration as part of 
future notice-and-comment rulemaking.
    Comment: Several commenters shared their feedback on including the 
NHSN Healthcare-Associated Clostridioides difficile Infection Outcome 
measure in the Hospital VBP and HAC Reduction Programs. A few 
commenters were supportive of including the measure in the value-based 
purchasing programs, with a commenter noting that including this 
potential future measure in the Hospital VBP and HAC Reduction Programs 
could improve quality of care, especially for the most vulnerable 
patients. A few commenters expressed concern that the new digital 
measure is not yet ready for the value-based purchasing programs 
because it lacks baseline testing data, the measure definitions need 
refinement, and the risk adjustment methodology does not account for 
patient factors that increase the risk of developing CDIs. They urged 
that this measure be fully defined, validated, and NQF endorsed prior 
to implementation. A commenter expressed their belief that CMS should 
not adopt this measure for the Hospital VBP Program or HAC Reduction 
Program until hospitals can consistently report using FHIR or testing 
confirms comparable results using different reporting methods. A 
commenter sought clarification on how this potential future measure 
would be weighted in the Hospital VBP and HAC Reduction Programs and 
how CMS would establish baseline data from which to determine 
percentiles and rankings that would impact Hospital VBP and HAC 
Reduction Program payments. Another commenter recommended that the CDC 
NHSN MRSA and CLABSI measures be maintained in their current programs 
because they are more specific and better understood by consumers. A 
commenter stated that CMS should

[[Page 49295]]

match the measure definition with the one utilized in the CDI project 
as part of the CDC's Emerging Infections Program (EIP) and consider 
general measure alignment with EIP.
    Response: We thank commenters for their feedback on the potential 
future inclusion of this measure in the Hospital VBP and HAC Reduction 
Programs, and we will consider it for future notice-and-comment 
rulemaking. We note that specifics about weighting and scoring of any 
future measures would be proposed in future notice and comment 
rulemaking.
    Comment: A commenter supported the potential inclusion of the NHSN 
Healthcare-Associated Clostridioides difficile Infection Outcome 
measure in the PCHQR Program pending removal of the previously adopted 
NHSN Facility-wide Inpatient Hospital-onset Clostridium difficile 
Infection (CDI) Outcome Measure. The commenter also requested that the 
measure take into consideration that cancer hospitals using PCR testing 
for CDIs may be penalized unfairly because of the test's higher 
sensitivity than other testing options. Another commenter supported the 
measure once it has been fully refined and receives NQF endorsement, 
stating that the measure would protect patients at cancer hospitals, 
who as a population are at a higher risk of contracting HAIs.
    Response: We thank the commenters for their support and will take 
their feedback into consideration.
(2) National Healthcare Safety Network (NHSN) Hospital-Onset Bacteremia 
& Fungemia Outcome Measure
(a) Background
    HAIs are the most frequent adverse event in the delivery of 
healthcare globally.\1072\ Incidence rates for most types of HAIs had 
been declining for several years in the U.S., but the COVID-19 pandemic 
reversed these trends.\1073\ Central line-associated bloodstream 
infections (CLABSI) declined 31 percent between 2015 and 2019.\1074\ 
Despite this initial trend, the SIR for CLABSI increased in 2020 
compared to 2019 in the later quarters due to the pandemic. The NHSN 
found a 47 percent increase in CLABSI in Quarter 4 of 2020 compared to 
Quarter 4 of 2019. Overall, CLABSI increased by 24 percent from 2019 to 
2020, with the largest increase (50 percent) being found in the ICU. 
Other types of infections also rose during this period, including 
hospital-onset MRSA by 15 percent, and Ventilator-Associated Events 
(VAE) by 35 percent.\1075\
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    \1072\ Hongsuwan M, Srisamang P, Kanoksil M, et al. (2014). 
Increasing incidence of hospital-acquired and healthcare-associated 
bacteremia in northeast Thailand: a multicenter surveillance study. 
PLoS One. 2014;9(10):e109324. doi:10.1371/journal.pone.0109324.
    \1073\ Weiner-Lastinger, L., Pattabiraman, V., Konnor, R., 
Patel, P., Wong, E., Xu, S., Dudeck, M. (2022). The impact of 
coronavirus disease 2019 (COVID-19) on healthcare-associated 
infections in 2020: A summary of data reported to the National 
Healthcare Safety Network. Infection Control & Hospital 
Epidemiology, 43(1), 12-25. doi:10.1017/ice.2021.362.
    \1074\ Centers for Disease Control and Prevention. Central Line-
Associated Bloodstream Infections. Accessed on Available at: https://arpsp.cdc.gov/profile/infections/clabsi?year-select-report=year2019&year-select-hai-state-list=year2019.
    \1075\ Centers for Disease Control and Prevention. 2020 National 
and State Healthcare-Associated Infections Progress Report. 
Available at: https://www.cdc.gov/hai/pdfs/progress-report/2020-Progress-Report-Executive-Summary-H.pdf.
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    One likely reason for this reversal was the staffing and 
institutional challenges of caring for COVID-19 patients, which led to 
a breakdown in previous standards of care. In qualitative studies, 
infection prevention teams have reported that the pandemic made it 
difficult to maintain routine CLABSI prevention practices in the 
ICU.\1076\ Another possible reason is that many hospitals underwent 
large staffing changes, leading to more workers who were not accustomed 
to the hospital's standard HAI prevention practices.\1077\
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    \1076\ Fakih, M., Bufalino, A., Sturm, L., Huang, R., 
Ottenbacher, A., Saake, K. Cacchione, J. (2021). Coronavirus disease 
2019 (COVID-19) pandemic, central-line-associated bloodstream 
infection (CLABSI), and catheter-associated urinary tract infection 
(CAUTI): The urgent need to refocus on hardwiring prevention 
efforts. Infection Control & Hospital Epidemiology, 1-6. 
doi:10.1017/ice.2021.70.
    \1077\ Fakih, M., Bufalino, A., Sturm, L., Huang, R., 
Ottenbacher, A., Saake, K. Cacchione, J. (2021). Coronavirus disease 
2019 (COVID-19) pandemic, central-line-associated bloodstream 
infection (CLABSI), and catheter-associated urinary tract infection 
(CAUTI): The urgent need to refocus on hardwiring prevention 
efforts. Infection Control & Hospital Epidemiology, 1-6. 
doi:10.1017/ice.2021.70.
---------------------------------------------------------------------------

    The NHSN Hospital-Onset Bacteremia & Fungemia Outcome measure was 
developed to help further our goal of addressing patient safety 
outcomes in the hospital care setting. The frequency of hospital 
fungemia and bacteremia infection rates in the U.S. present unique 
opportunities for large-scale quality measurement and improvement 
activities. Statistics on preventability vary but suggest that a 
considerable proportion of fungemia and bacteremia could be 
prevented.\1078\ The NHSN Hospital-Onset Bacteremia & Fungemia Outcome 
measure is intended to facilitate safer patient care by increasing 
awareness of the dangers of fungemia and bacteremia, promoting 
adherence to recommended clinical guidelines, and encouraging hospitals 
to track and improve their practices of appropriate monitoring and care 
delivery for patients. For these reasons, we requested feedback on the 
potential future inclusion of this measure into the Hospital IQR 
Program measure set to aid in disease monitoring, provide hospitals and 
patients with more information to inform care delivery, and improve 
patient outcomes.
---------------------------------------------------------------------------

    \1078\ Dantes RB, Rock C, Milstone AM, Jacob JT, Chernetsky-
Tejedor S, Harris AD, Leekha S. (2019). Preventability of hospital 
onset bacteremia and fungemia: A pilot study of a potential 
healthcare-associated infection outcome measure. Infect Control Hosp 
Epidemiol, 40(3):358-361. doi: 10.1017/ice.2018.339.
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    Under CMS' Meaningful Measures Framework, the NHSN Hospital-Onset 
Bacteremia & Fungemia Outcome measure addresses the quality priority of 
``Make Care Safer by Reducing Harm Caused in the Delivery of Care'' 
through the Meaningful Measures Area of ``Healthcare Associated 
Infection.'' \1079\ Additionally, pursuant to Meaningful Measures 2.0, 
this measure addresses the ``Safety'' priority area and aligns with our 
commitment to a patient-centered approach in quality measurement to 
ensure that patients are safe and receive the highest quality 
care.\1080\
---------------------------------------------------------------------------

    \1079\ Centers for Medicare & Medicaid Services. Meaningful 
Measures 2.0: Moving from Measure Reduction to Modernization. 
Available at: https://www.cms.gov/meaningful-measures-20-moving-measure-reduction-modernization. We note that Meaningful Measures 
2.0 is still under development.
    \1080\ Centers for Medicare & Medicaid Services. (2021). CMS 
Quality Measurement Action Plan. Available at: https://www.cms.gov/files/document/2021-cms-quality-conference-cms-quality-measurement-action-plan-march-2021.pdf.
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    While the HAC Reduction Program and Hospital VBP Program use 
several HAI measures, we believe that the NHSN Hospital-Onset 
Bacteremia & Fungemia Outcome measure may be necessary to build upon 
previous efforts to reduce HAIs because it encompasses all types of 
bacteremia and fungemia that occur among already hospitalized patients. 
Meanwhile, the NHSN Central Line-Associated Bloodstream Infection 
(CLABSI) Outcome measure and NHSN Facility-wide Inpatient Hospital-
onset Methicillin-resistant Staphylococcus aureus (MRSA) Bacteremia 
Outcome measure only capture specific types of HAIs.
    In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28553), we 
invited public comment on the potential use of this measure in the 
Hospital IQR Program. We are also considering its use in the PCHQR 
Program and the possibility of replacing the current CLABSI and MRSA 
measures in the

[[Page 49296]]

HAC Reduction Program and Hospital VBP Program with the NHSN Hospital-
Onset Bacteremia & Fungemia Outcome measure.
(b) Overview of Measure
    This measure captures the development of new bacteremia and 
fungemia among patients already admitted to acute care hospitals, using 
algorithmic determinations from data sources widely available in EHRs.
    The NHSN Hospital-Onset Bacteremia & Fungemia Outcome measure was 
previously endorsed by MAP on June 11, 2019. The CDC submitted the 
measure for re-endorsement and it was included in the publicly 
available ``List of Measures Under Consideration for July 15, 2021'' 
(MUC List),\1081\ a list of measures under consideration for use in 
various Medicare programs. The NHSN Hospital-Onset Bacteremia & 
Fungemia Outcome measure (MUC2021-100) was reviewed by the NQF MAP 
Hospital Workgroup on December 15, 2021 and received conditional 
support pending NQF review and re-endorsement once the revised measure 
is fully tested.\1082\ The MAP Coordinating committee, which provides 
direction to the MAP workgroups, concurred with the recommendations of 
the MAP Hospital Workgroup. We understand that the CDC intends to 
submit the measure in the future for NQF review and endorsement.
---------------------------------------------------------------------------

    \1081\ Centers for Medicare & Medicaid Services. (2021). List of 
Measures Under Consideration for December 1, 2021. Available at: 
https://www.cms.gov/files/document/measures-under-consideration-list-2021-report.pdf.
    \1082\ National Quality Forum. (2022). Measure Applications 
Partnership (MAP) 2021-2022 Final Recommendations. Available at: 
https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96698.
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(c) Data Sources
    The data submission and reporting standard procedures for the NHSN 
Hospital-Onset Bacteremia & Fungemia Outcome measure have been set 
forth by the CDC for NHSN participation in general and for submission 
of measure data. Although the NHSN Hospital-Onset Bacteremia & Fungemia 
Outcome measure is not specified as an eCQM, manual data entry is not 
available. The primary sources of data for determining numerator events 
include microbiology data (blood culture) and patient encounter, 
demographic, and location information often located in Admission-
Discharge-Transfer data (Fast Healthcare Interoperability Resources 
(FHIR): Encounter, Patient, Observation, Location).
    To facilitate rapid, automated, and secure data exchange, the CDC's 
NHSN is planning to enable and promote reporting of this measure using 
FHIR. However, as FHIR capabilities are evolving and not uniform across 
healthcare systems, the CDC is also planning on enabling reporting 
using the existing Health Level 7 (HL7) Clinical Document Architecture 
(CDA), and potentially other formats as well to provide all facilities 
with an option for reporting. We are also working with the CDC and ONC 
to consider how certified health IT can support reporting of data for 
this measure.
    We invited public comment on potential reporting formats for this 
measure.
(d) Outcome
    The measures outcome (numerator) is defined as the observed number 
of HOB events. This is defined as growth of a recognized bacterial or 
fungal pathogen from a blood culture specimen collected on the 4th 
calendar day of admission or later (where the date of admission to an 
inpatient location is calendar day 1).
(e) Cohort
    The measures outcome (numerator) is defined as the observed number 
of hospital-onset bacteremia and fungemia (HOB) events based on 
predictive models using facility-level factors (community-onset 
incidence of bacteremia and fungemia, blood culture utilization rates), 
patient care location, and potentially other data as predictors.
(f) Exclusion Criteria
    The measure has two numerator exclusions for patients with previous 
matching POA bacteremia or fungemia. The first numerator exclusion is 
HOB infections in which the pathogen is the same species or genus level 
as the one identified from a blood specimen by culture that the 
hospital collected in the POA window (defined as hospital calendar day 
three or earlier). Additionally, if multiple pathogens are identified 
from the same blood culture, then a match of any of those pathogens to 
a POA blood pathogen is sufficient to exclude the event from the HOB 
measure. The measure also excludes patients with a previous HOB event 
who experience additional HOB events during the same hospital 
admission. We understand that the CDC may consider additional exclusion 
criteria for patients with significant risk factors for bacteremia or 
fungemia infections that are judged not likely to be preventable in 
rigorous studies.
    The measure has one denominator exclusion for data from patients 
who are not assigned to an inpatient bed in an applicable location. As 
an aside, denominator counts exclude data from inpatient rehabilitation 
units and inpatient psychiatric units with a unique CCN from the acute 
care facility.
(g) Measure Calculation
    The measure is an outcome measure that assesses the observed number 
of HOB events. The measure calculates the ratio of the observed number 
of HOB events out of the expected number of HOB events based on 
predictive models using facility and patient care location data as 
predictors.
    We received comments on this topic.
    Comment: Many commenters supported the potential inclusion of the 
NHSN Hospital-Onset Bacteremia & Fungemia Outcome measure to the 
Hospital IQR Program. Numerous commenters stated that the measure would 
improve patient safety by preventing hospital-acquired infections. 
Several commenters supported the digital reporting aspect of the 
measure, expressing their belief that it would make reporting less 
subjective, make data more traceable, and reduce the administrative 
burden on hospital staff. A commenter specifically supported the 
flexibility of reporting via either FHIR or HL7. A commenter supported 
the measure for adoption in the Hospital IQR Program prior to adding 
the measure to other quality programs to determine the measure's 
validity.
    Response: We thank the commenters for their support. We will 
continue to collaborate with the CDC and keep this feedback in mind as 
part of future notice-and-comment rulemaking.
    Comment: Many commenters did not support the potential inclusion of 
the NHSN Hospital-Onset Bacteremia & Fungemia Outcome measure in the 
Hospital IQR Program. Numerous commenters opposed adoption because the 
measure has not received NQF endorsement and has yet to be fully 
tested, while a few others stated that hospitals would incur a 
significant burden to prepare for reporting electronically sourced 
data. Several commenters opposed adoption of this measure because it 
does not take into account patient factors that can increase their risk 
of developing CDIs. Some expressed concern over potential unintended 
side effects of this measure, such as the overuse of antibiotics and 
placing major teaching hospitals at a disadvantage. A commenter cited 
the uncertainties in measure definitions.
    Response: We thank the commenters for their feedback and 
acknowledge their concerns. We will continue to collaborate with the 
CDC and consider this feedback as we determine the

[[Page 49297]]

potential future inclusion of this measure.
    Comment: Many commenters expressed their belief that the measure 
specifications need to be further refined. Several commenters suggested 
that the measure exclude immunocompromised patients or include risk 
adjustment based on patients' vulnerability to infections, to account 
for factors outside of hospitals' control. Several other commenters 
posed questions about the measure definitions and requested additional 
clarification. A commenter recommended that the measure account for the 
type of vascular access device used in patients with HOBs. Several 
commenters recommended that we postpone adoption of the measure to the 
Hospital IQR Program until the measure has been validated and NQF 
endorsed.
    Response: We appreciate the recommendations and requests for 
information. We note that the CDC is still refining the measure 
specifications. We will take this feedback into consideration as part 
of future notice-and-comment rulemaking.
    Comment: Many commenters were concerned that collecting, reviewing, 
and reporting data for the NHSN Hospital-Onset Bacteremia & Fungemia 
Outcome measure would be a major burden to hospital staff. Several 
stated that preparing for digital reporting would be time- and 
resource-intensive for hospitals while a few others expressed their 
belief that the measure would be overly burdensome to infection control 
staff. To improve the measure implementation process, a few commenters 
recommended that we implement voluntary reporting until the measure has 
been fully refined, hospitals have time to prepare for reporting, and 
the technology for data submission is mature.
    A few other commenters were concerned about unintended consequences 
for patient care, including that hospitals might use antimicrobials 
inappropriately or reduce blood culture orders. To prevent this, A 
commenter recommended that we consider another measure focused on 
specific types of bacteremia and fungemia instead. A few commenters 
recommended that we monitor additional sources of data for surveillance 
in addition to the NHSN Hospital-Onset Bacteremia & Fungemia Outcome 
measure, such as complementary NHSN metrics.
    Response: We appreciate commenters sharing their concerns. We will 
consider the recommendations for improving the measure and preventing 
unintended consequences as we consider the potential future inclusion 
of this measure.
    Comment: Several commenters provided feedback on including the NHSN 
Hospital-Onset Bacteremia & Fungemia Outcome measure in the Hospital 
VBP and HAC Reduction Programs. A few commenters supported the 
inclusion of this measure in the value-based purchasing programs, with 
a commenter noting it was a step in the right direction. A few 
commenters expressed concern that the new digital measure is not yet 
ready for adoption because it lacks baseline testing data, the measure 
definitions need refinement, and the risk adjustment methodology does 
not account for patient factors that increase the risk of developing 
CDIs. They urged that we ensure that this measure is fully defined, 
validated, and NQF endorsed prior to implementation. A commenter stated 
that CMS should not adopt this measure for the Hospital VBP Program or 
HAC Reduction Program until hospitals can consistently report using 
FHIR or testing confirms comparable results using different reporting 
methods. A commenter recommended that the HOB measure replace the CDC 
NHSN MRSA and CLABSI measures. Another commenter suggested that the CDC 
NHSN MRSA and CLABSI measures be maintained in the Hospital VBP and HAC 
Reduction Programs because they are more specific and better understood 
by consumers. A commenter recommended peer baselining the measure to 
account for institutional differences in demographics and size.
    Response: We thank commenters for their feedback on the potential 
future inclusion of this measure in the Hospital VBP and HAC Reduction 
Programs. We will consider all input and note that any future proposal 
to implement such a measure would be announced through future notice-
and-comment rulemaking.
10. Form, Manner, and Timing of Quality Data Submission
a. Background
    Sections 1886(b)(3)(B)(viii)(I) and (b)(3)(B)(viii)(II) of the Act 
state that the applicable percentage increase for FY 2015 and each 
subsequent year shall be reduced by one-quarter of such applicable 
percentage increase (determined without regard to sections 
1886(b)(3)(B)(ix), (xi), or (xii) of the Act) for any subsection (d) 
hospital that does not submit data required to be submitted on measures 
specified by the Secretary in a form and manner, and at a time, 
specified by the Secretary. To successfully participate in the Hospital 
Inpatient Quality Reporting (IQR) Program, hospitals must meet specific 
procedural, data collection, submission, and validation requirements. 
Previously, the applicable percentage increase for FY 2007 and each 
subsequent fiscal year until FY 2015 was reduced by 2.0 percentage 
points for subsection (d) hospitals failing to submit data in 
accordance with the previous description. In accordance with the 
statute, the FY 2023 payment determination will begin the ninth year 
that the Hospital IQR Program will reduce the applicable percentage 
increase by one-quarter of such applicable percentage increase.
b. Maintenance of Technical Specifications for Quality Measures
    For each Hospital IQR Program payment determination, we require 
that hospitals submit data on each specified measure in accordance with 
the measure's specifications for a particular period of time. We refer 
readers to the FY 2019 IPPS/LTCH PPS final rule (83 FR 41538), in which 
we summarized how the Hospital IQR Program maintains the technical 
measure specifications for quality measures and the subregulatory 
process for incorporation of nonsubstantive updates to the measure 
specifications to ensure that measures remain up-to-date. We did not 
propose any changes to these policies in the proposed rule.
    The data submission requirements, Specifications Manual, and 
submission deadlines are posted on the QualityNet website at: https://qualitynet.cms.gov (or other successor CMS designated websites). The 
CMS Annual Update for the Hospital Quality Reporting Programs (Annual 
Update) contains the technical specifications for electronic clinical 
quality measures (eCQMs). The Annual Update contains updated measure 
specifications for the year prior to the reporting period. For example, 
for the CY 2022 reporting period/FY 2024 payment determination, 
hospitals are collecting and will submit eCQM data using the May 2021 
Annual Update and any applicable addenda. The Annual Update and 
implementation guidance documents are available on the Electronic 
Clinical Quality Improvement (eCQI) Resource Center website at: https://ecqi.healthit.gov/.
    Hospitals must register and submit quality data through the 
Hospital Quality Reporting (HQR) System (previously referred to as the 
QualityNet Secure Portal) (86 FR 45520). The HQR System is safeguarded 
in accordance with the HIPAA Privacy and Security Rules to protect 
submitted patient information. See 45 CFR parts 160 and 164, subparts 
A, C, and E.

[[Page 49298]]

    We also refer readers to section IX.C. of the preamble of the FY 
2023 IPPS/LTCH PPS proposed rule (87 FR 28486 through 28491) where we 
requested information on potential actions that would continue to 
transform the Hospital IQR Program's quality measurement enterprise 
toward the use of the FHIR standard for data submission.
c. Procedural Requirements
    The Hospital IQR Program's procedural requirements are codified in 
regulation at 42 CFR 412.140. We refer readers to these codified 
regulations for participation requirements, as further explained by the 
FY 2014 IPPS/LTCH PPS final rule (78 FR 50810 through 50811) and the FY 
2017 IPPS/LTCH PPS final rule (81 FR 57168). The previously finalized 
requirements, including setting up a QualityNet account and the 
associated timelines, are described at 42 CFR 412.140(a)(2), 42 CFR 
412.140(e)(2)(iii), and in the FY 2012 IPPS/LTCH PPS final rule (76 FR 
51639 through 51640). In the FY 2022 IPPS/LTCH PPS final rule, we 
finalized the following changes to the Hospital IQR Program regulation 
text: (1) Update references to the QualityNet website at 42 CFR 
412.140(a)(1) and 42 CFR 412.140(c)(2)(i); and (2) use the term 
``QualityNet security official'' instead of ``QualityNet 
Administrator'' at 42 CFR 412.140(a)(2). We did not propose any changes 
to these policies in the proposed rule.
d. Data Submission Requirements for Chart-Abstracted Measures
    We refer readers to the FY 2012 IPPS/LTCH PPS final rule (76 FR 
51640 through 51641), the FY 2013 IPPS/LTCH PPS final rule (77 FR 53536 
through 53537), and the FY 2014 IPPS/LTCH PPS final rule (78 FR 50811) 
for details on the Hospital IQR Program data submission requirements 
for chart-abstracted measures. We did not propose any changes to these 
policies in the proposed rule.
e. Reporting and Submission Requirements for eCQMs
(1) Background
    For a discussion of our previously finalized eCQMs and policies, we 
refer readers to the FY 2014 IPPS/LTCH PPS final rule (78 FR 50807 
through 50810; 50811 through 50819), the FY 2015 IPPS/LTCH PPS final 
rule (79 FR 50241 through 50253; 50256 through 50259; and 50273 through 
50276), the FY 2016 IPPS/LTCH PPS final rule (80 FR 49692 through 
49698; and 49704 through 49709), the FY 2017 IPPS/LTCH PPS final rule 
(81 FR 57150 through 57161; and 57169 through 57172), the FY 2018 IPPS/
LTCH PPS final rule (82 FR 38355 through 38361; 38386 through 38394; 
38474 through 38485; and 38487 through 38493), the FY 2019 IPPS/LTCH 
PPS final rule (83 FR 41567 through 41575; 83 FR 41602 through 41607), 
the FY 2020 IPPS/LTCH PPS final rule (84 FR 42501 through 42506), the 
FY 2021 IPPS/LTCH PPS final rule (85 FR 58932 through 58940), and the 
FY 2022 IPPS/LTCH PPS final rule (86 FR 45417 through 45421).
    In the FY 2018 IPPS/LTCH PPS final rule, we finalized eCQM 
reporting and submission requirements such that hospitals were required 
to report only one, self-selected calendar quarter of data for four 
self-selected eCQMs for the CY 2018 reporting period/FY 2020 payment 
determination (82 FR 38358 through 38361). Those reporting requirements 
were extended to the CY 2019 reporting period/FY 2021 payment 
determination through the CY 2021 reporting period/FY 2023 payment 
determination (83 FR 41603 through 41604; 84 FR 42501 through 42503). 
In the FY 2020 IPPS/LTCH PPS final rule, we finalized that for the CY 
2022 reporting period/FY 2024 payment determination, hospitals would be 
required to report one, self-selected calendar quarter of data for: (a) 
Three self-selected eCQMs; and (b) the Safe Use of Opioids--Concurrent 
Prescribing eCQM, for a total of four eCQMs (84 FR 42503 through 
42505).
    In the FY 2021 IPPS/LTCH PPS final rule, we finalized a progressive 
increase in the number of required reported quarters of eCQM data, from 
one self-selected quarter of data to four quarters of data over a 
three-year period (85 FR 58932 through 58939). Specifically, for the CY 
2021 reporting period/FY 2023 payment determination, hospitals were 
required to report two self-selected calendar quarters of data for each 
of the four self-selected eCQMs (85 FR 58939). For the CY 2022 
reporting period/FY 2024 payment determination, hospitals are required 
to report three self-selected calendar quarters of data for each eCQM: 
(a) Three self-selected eCQMs, and (b) the Safe Use of Opioids--
Concurrent Prescribing eCQM (85 FR 58939). We clarified in the FY 2021 
IPPS/LTCH PPS final rule that until hospitals are required to report 
all four quarters of data beginning with the CY 2023 reporting period/
FY 2025 payment determination, they may submit consecutive or non-
consecutive self-selected quarters of data (85 FR 58939). In the FY 
2022 IPPS/LTCH PPS final rule, we did not propose any changes to these 
policies, and we clarified that the self-selected eCQMs must be the 
same eCQMs across quarters in a given reporting year (86 FR 45418). We 
did not propose any changes to these policies in the proposed rule. The 
following Table IX.E-14. summarizes our finalized policy:
[GRAPHIC] [TIFF OMITTED] TR10AU22.174

    For the CY 2023 reporting period/FY 2025 payment determination and 
subsequent years, hospitals are required to report four calendar 
quarters of data for each eCQM: (a) Three self-selected eCQMs, and (b) 
the Safe Use of Opioids-Concurrent Prescribing eCQM (85 FR 58939). We 
did not propose any changes to the eCQM reporting or submission 
requirements for the CY 2023 reporting period/FY 2025 payment 
determination.
    In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28555 through 
28556), we proposed to modify eCQM reporting and submission 
requirements beginning with the CY 2024 reporting period/FY 2026 
payment determination and for subsequent years.

[[Page 49299]]

(2) Reporting and Submission Requirements for eCQMs for the CY 2024 
Reporting Period/FY 2026 Payment Determination and for Subsequent Years
    In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28555 through 
28556), we proposed to modify the eCQM reporting and submission 
requirements, such that beginning with the CY 2024 reporting period/FY 
2026 payment determination hospitals would be required to report four 
calendar quarters of data for each required eCQM: (1) Three self-
selected eCQMs; (2) the Safe Use of Opioids--Concurrent Prescribing 
eCQM; (3) the proposed Cesarean Birth eCQM; and (4) the proposed Severe 
Obstetric Complications eCQM; for a total of six eCQMs. We refer 
readers to Table IX.E-15. which represents the progressive increase in 
eCQM reporting requirements, including our proposed changes.
[GRAPHIC] [TIFF OMITTED] TR10AU22.175

    This  proposal is made in conjunction with our proposals discussed 
in sections IX.E.5.c. and IX.E.5.d. of the preamble of this final rule, 
in which we are adopting the Cesarean Birth eCQM and Severe Obstetric 
Complications eCQM, respectively. Addressing the maternal health 
crisis, improving maternal health, and closing any gaps that exist as a 
result of health disparities are among our top goals for quality 
improvement. The high maternal mortality and morbidity rates in the 
U.S. necessitate large-scale quality measurement and improvement 
activities. As part of the effort to reduce maternal mortality and 
morbidity, we believe it to be important to receive data from all 
hospitals that provide perinatal care and not to limit data to just 
hospitals that may self-select those eCQMs. Requiring these eCQMs will 
also aid in the surveillance of maternal morbidity, mortality, and 
associated comorbidities and complications as we collect data from all 
of the hospitals participating in the Hospital IQR Program. 
Additionally, no maternal morbidity or obstetric complications outcome-
based measures exist in national reporting programs, and we believe 
these measures have the potential to reduce preventable harm and costs 
associated with adverse events related to perinatal care.
---------------------------------------------------------------------------

    \1083\ In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28556), 
we stated in Table IX.E-15. ``Four self-selected eCQMs'' for the 
eCQMs required to be reported for the CY 2022 reporting period/FY 
2024 payment determination. We correct this error in table IX.E-15 
of this final rule to ``Three self-selected eCQMs; and Safe Use of 
Opioids--Concurrent Prescribing eCQM'' in alignment with the 
language throughout the preamble and as finalized in previous 
policy.
---------------------------------------------------------------------------

    Accordingly, after consideration of public comments and as we are 
finalizing to adopt the Cesarean Birth eCQM and the Severe Obstetric 
Complications eCQM, all hospitals participating in the Hospital IQR 
Program will also be required to report these two eCQMs, increasing the 
total number of eCQMs reported from four to six beginning with the CY 
2024 reporting period/FY 2026 payment determination and for subsequent 
years as discussed further below.
    At the start of required eCQM reporting, we stated that increasing 
the reporting requirements over time is consistent with our goal of 
reporting on all eCQMs in the Hospital IQR Program in a stepwise manner 
while being responsive to hospitals' concerns about timing, readiness, 
and burden associated with the increased number of measures required to 
be reported (81 FR 57151 through 57152). With the addition of new 
measures to the eCQM measure set and increasing the quarters of eCQM 
data to be reported, our approach to eCQM reporting requirements has 
supported the goal to incrementally increase eCQM reporting 
requirements as hospitals continue to gain experience with eCQMs (84 FR 
42502). After several years of a steady eCQM reporting requirement, we 
believe a proposed change to the reporting requirement is timely. We 
believe that allowing hospitals to continue self-selection of three 
eCQMs from the measure set for the CY 2024 reporting period/FY 2026 
payment determination while requiring reporting of three additional 
eCQMs provides sufficient flexibility to report on eCQMs applicable to 
a hospital's quality improvement priorities while also reporting on 
measures that address the opioid and maternal health crises and that 
advance health equity. Additionally, we believe that our proposal for 
hospitals to submit data from three self-selected eCQMs and three 
required eCQMs continues our approach to collect data derived from EHRs 
and make progress toward a transition to fully digital quality 
measurement (86 FR 45345).
    We invited public comment on our proposal to increase the number of

[[Page 49300]]

mandatory measures to be reported from one to three, as described 
previously, and thereby increase the total number of required eCQMs 
from four to six.
    We refer readers to section IX.H.10.b. of the preamble of this 
final rule for a discussion of a similar proposal by the Medicare 
Promoting Interoperability Program for Eligible Hospitals and Critical 
Access Hospitals (CAHs).
    Comment: Several commenters supported our proposal to modify the 
reporting and submission requirements for eCQMs such that beginning 
with the CY 2024 reporting period/FY 2026 payment determination 
hospitals would be required to submit four calendar quarters of data 
and three required eCQMs. Commenters cited improved transparency and 
oversight over eCQM submissions, increased data ensuring comparison of 
quality on priority topics, and enabling hospitals to leverage 
electronic data collection and reporting to the greatest extent 
possible.
    Response: We thank commenters for their support.
    Comment: A commenter supported the proposal to modify eCQM 
reporting and submission requirements and requested two years of 
voluntary reporting for the Severe Obstetric Complications eCQM before 
mandatory reporting.
    Response: We thank the commenter for its support of our proposal. 
Regarding the recommendation to increase the voluntary reporting period 
from one year to two years, which would delay the start of mandatory 
reporting of these two finalized perinatal eCQMs, we reiterate that 
addressing the maternal health crisis, improving maternal health, and 
closing any gaps that exist as a result of health disparities are among 
our top goals for quality improvement. By proposing a one-year 
voluntary reporting period, we sought to balance the need for hospitals 
and their vendors to prepare for reporting the new eCQMs with the 
urgency of measuring at a national scale and addressing the high 
maternal mortality and morbidity rates in the U.S. by requiring 
mandatory reporting of both the Severe Obstetric Complications eCQM and 
the Cesarean Birth eCQM beginning with the CY 2024 reporting period/FY 
2026 payment determination.
    Comment: Several commenters did not support the proposal to modify 
eCQM reporting and submission requirements, expressing concerns about 
the pace of change in eCQM reporting and submission proposals, 
including the amount of time for hospital workflow changes, measure 
validation, and EHR vendor readiness for eCQM changes. A few commenters 
recommended a longer timeframe prior to increased requirements for eCQM 
reporting, including two years of optional reporting prior to mandatory 
reporting of an eCQM due to the need to address current eCQM challenges 
before additional eCQMs are required to be reported. Specifically, 
commenters noted difficulties extracting data from production ready 
eCQM products delivered by developers, the cost and time associated 
with eCQM adoption, the demands on hospital resources to meet COVID-19 
PHE needs, other CMS quality reporting requirements, and federal EHR 
requirements given the competing demands on limited hospital quality 
and health IT resources.
    Response: We appreciate commenters' concerns related to additions 
to the eCQM measure set when some hospitals are experiencing challenges 
with eCQM reporting and submission. We establish program requirements 
considering all hospitals that participate in the Hospital IQR Program 
at a national level, which involves a wide spectrum of capabilities and 
resources with respect to eCQM reporting. In establishing our eCQM 
policies, we must balance the needs of hospitals with variable 
preferences and capabilities. We believe our finalized policy to modify 
the eCQM reporting and submission requirements will offer opportunities 
for hospitals that are prepared to voluntarily report the two perinatal 
eCQMs--Cesarean Birth and Severe Obstetric Complications--to do so for 
the CY 2023 reporting period/FY2025 payment determination, while 
providing more than one year for other hospitals to prepare and 
implement the two perinatal eCQMs for the CY 2024 reporting period/FY 
2026 payment determination and for subsequent years. We believe the 
long-term benefits associated with reporting a full year of data for 
six eCQMs will outweigh the burdens and that increasing the number of 
eCQMs for which hospitals are required to report will produce more 
comprehensive and reliable quality information for patients and 
providers.
    Hospitals have had several years to gain experience reporting eCQM 
data. In the FY 2021 IPPS/LTCH PPS final rule, we stated that, after 
holding eCQM reporting and submission policies constant for a number of 
years in order to give hospitals and their vendors additional time to 
improve eCQM reporting capabilities, we intended to transition to more 
robust reporting (85 FR 58934). We reiterate our intention to continue 
a transition toward more robust eCQM reporting (82 FR 38356 and 84 FR 
42502). We believe that increasing the amount of eCQM data reported is 
in line with our goals to increase electronic reporting of clinical 
quality measures. We add that eCQM reporting and submission will be 
supported by technology certified to the 2015 Edition Cures Update that 
hospitals have had several years to possess, implement, and use in 
advance of the December 31, 2022 deadline (86 FR 45418). We recognize 
the cost and time associated with eCQM adoption and refer readers to 
section XII.B.4.f. of the preamble of this final rule (information 
collection requirements) for a detailed discussion of our burden 
estimates associated with the modification of our eCQM reporting and 
submission requirements.
    We acknowledge the commenters' concern that modifying the eCQM 
reporting and submission requirement for the CY 2024 reporting period/
FY 2026 payment determination will require hospital quality and health 
IT resources to support Hospital IQR Program and other CMS quality 
reporting requirements and federal EHR requirements, however, we point 
to the alignment between Hospital IQR Program's reporting requirements 
and other quality programs, such as the Medicare Promoting 
Interoperability Program for hospitals and critical access hospitals 
(CAHs). We refer readers to the FY 2016 IPPS/LTCH PPS final rule (80 FR 
49705 through 49708) and the FY 2017 IPPS/LTCH PPS final rule (81 FR 
57170) for our previously adopted eCQM file format requirements, zero 
denominator declaration, and case threshold exemption policies, and the 
FY 2018 IPPS/LTCH PPS final rule (81 FR 57255 through 57257) where we 
stated the finalized successful submission requirements in the Hospital 
IQR Program align with the CQM electronic reporting requirements of 
Medicare Promoting Interoperability Program for eligible hospitals and 
CAHs. We will continue to look across all quality programs to identify 
areas for further streamlining of quality reporting requirements. As 
referenced in section IX.C., in the ``Continuing to Advance Digital 
Quality Measurement and Use of Fast Healthcare Interoperability 
Resources (FHIR) in Hospital Quality Programs--Request for 
Information,'' we also believe utilizing standardized data for EHR-
based measurement (based on the FHIR standard) and aligning where 
possible with other interoperability requirements can reduce the data 
collection burden incurred by providers for the purpose of reporting 
quality measures. We appreciate the comments on, and interest in, 
opportunities to reduce reporting burden and we will continue to take 
all comments into

[[Page 49301]]

account as we develop future regulatory proposals or other guidance for 
our quality measurement policies.
    We also recognize the burden that the COVID-19 PHE has had on the 
healthcare system and will continue to monitor the impact that the 
COVID-19 PHE has on hospitals, including small, rural hospitals. 
Additionally, if, due to COVID-19 or any other extraordinary 
circumstance, we emphasize that hospitals may be eligible for an 
extraordinary circumstances exception (ECE). Hospitals may request an 
ECE if they are unable to fulfill program requirements due to 
extraordinary circumstances beyond their control. We refer readers to 
section IX.E.15 of this final rule, the eCQM ECE resources on the 
QualityNet website (available at: https://qualitynet.cms.gov/inpatient/measures/ecqm/participation#tab2), and 42 CFR 412.140(c)(2) for more 
information about the Hospital IQR Program's Extraordinary 
Circumstances Exceptions policy.
    Comment: A few commenters did not support the proposal to revise 
eCQM reporting and submission requirements due to concerns with 
vendors' timelines to complete upgrades and programming.
    Response: We appreciate the commenters' concern, and we urge 
hospitals to continue to work with their vendor to secure timely 
delivery of their products. We acknowledge the effort required for 
hospitals to adopt and implement updated technology to meet the eCQM 
reporting and submission requirements. However, we respectfully 
disagree that our proposal would not permit adequate time for product 
implementation and use. We believe our finalized policy to modify the 
eCQM reporting and submission requirements will offer opportunities for 
hospitals that are prepared to voluntarily report the two perinatal 
eCQMs to do so for the CY 2023 reporting period while providing more 
than one year for other hospitals to prepare and implement the two 
perinatal eCQMs for the CY 2024 reporting period/FY 2026 payment 
determination.
    Comment: A few commenters did not support our proposal to modify 
eCQM reporting and submission requirements due to the cost and time 
required for EHR changes and updates for small and rural hospitals with 
limited IT and staffing resources. A commenter requested clarification 
for hospitals without obstetric departments or who do not perform 
deliveries and the proposal to require reporting of the two perinatal 
eCQMs, inquiring if such hospitals replace the measures or omit the 
perinatal measures.
    Response: We acknowledge that facilitating quality improvement for 
small or rural hospitals can present unique challenges. When selecting 
eCQMs for inclusion in the measure set we have, and will continue to, 
consider the recommendations from the rural stakeholders to ensure 
eCQMs are meaningful to quality improvement for small, rural hospitals 
(85 FR 58935). As stated in sections IX.E.5.c. and IX.E.5.d., a 
critical focus in the national approach for improving maternal health 
and advancing maternal health equity is reducing existing disparities 
in maternal health outcomes by race, ethnicity, and geography. If a 
hospital does not have an obstetrics department or has few or no 
deliveries during a reporting period, the hospital would submit a zero 
denominator declaration for the measure that allows a hospital to meet 
the reporting requirements for a particular eCQM if a hospital does not 
have patients that meet the denominator criteria. We refer readers to 
the FY 2015 IPPS/LTCH PPS final rule (79 FR 50258), the FY 2016 IPPS/
LTCH PPS final rule (80 FR 49705 through 49708), and the FY 2017 IPPS/
LTCH PPS final rule (81 FR 57170) for our previously adopted eCQM file 
format requirements. A QRDA Category I file with patients meeting the 
initial patient population of the applicable measures, a zero 
denominator declaration, and/or a case threshold exemption all count 
toward a successful submission for eCQMs for the Hospital IQR Program 
(82 FR 38387).
    Comment: A few commenters did not support the proposal to modify 
eCQM reporting and submission requirements due to the as yet determined 
benefit relative to the administrative costs and the need for more 
comprehensive, frequent, and actionable eCQM performance feedback.
    Response: We thank the commenters for their input and we appreciate 
their concern, but reiterate our eCQM policies further advance our goal 
of incrementally increasing the use of EHR data for quality measurement 
and improvement and is responsive to the feedback of some interested 
parties urging a faster transition to full electronic reporting (84 FR 
42503). We also use a validation process to address concerns about 
reliability and validity of eCQM data. As stated in the FY 2021 IPPS/
LTCH PPS final rule (85 FR 58935), we have conducted an eCQM validation 
pilot (OMB Control #0938-1022) and completed eCQM data validation from 
the CY 2017 reporting period and the CY 2018 reporting period. Based on 
our internal review of the CY 2017 and CY 2018 eCQM data submitted for 
validation, over half of the measures validated had agreement rates of 
80 percent or better. As discussed in section IX.E.11.b. of this final 
rule, we have an ongoing goal of continuing to assess the accuracy of 
eCQM measure data (81 FR 57155). Through the finalized modifications to 
the existing processes for validation of Hospital IQR Program eCQM data 
discussed in section IX.E.11.b. of this final rule and our finalized 
policy to modify eCQM reporting and submission requirements we expect 
to gain a better understanding of how to increase the accuracy of eCQM 
data by continuing to analyze the validation process and the results 
(85 FR 58935). We appreciate commenters' statements in support of 
comprehensive, frequent, and actionable eCQM performance feedback. The 
implementation of the updated HQR System has provided a more 
comprehensive platform for eCQM performance feedback as compared to the 
legacy system. The new HQR System provides various reports and user 
interfaces to be used by the hospitals to validate their submissions 
and overall performance. Overall measure outcomes, including the 
ability to review individual measure outcomes, are available on the 
eCQM user interface in near real time. Users of the HQR System for eCQM 
reporting can generate reports real time instead of waiting on the 
system refresh. This enhanced functionality in the HQR System allows 
submitters to export a downloadable report for rejected files providing 
details, including the associated conformance number of the error to 
make it easier for the submitter to troubleshoot, correct and resubmit 
the file to achieve the expected outcome.
    Comment: A few commenters did not support the proposal to increase 
the number of mandatory measures, citing concerns about the two 
proposed perinatal eCQMs and the support for self-selection as an 
appropriate approach to achieving quality improvement goals. They 
recommended continuation of the current reporting and submission 
requirements to provide time for hospitals and the CMS platform to 
acclimate to the existing requirement to report four quarters of eCQM 
data.
    Response: We appreciate commenters' position regarding mandatory 
reporting of the two perinatal eCQMs, but note our longstanding view 
that electronic reporting of quality measure data derived from the EHR 
will, over time, reduce the burden on hospitals to collect and submit 
data for the Hospital IQR Program (78 FR 50956). We believe that 
mandatory reporting of the two perinatal eCQMs in order to gain 
comprehensive, national measure data

[[Page 49302]]

are important tools in addressing the maternal health crisis, as no 
maternal morbidity or obstetric complications outcome-based measures 
exist in national reporting programs.
    Regarding comments about the CMS platform, we launched the HQR 
System for reporting quality data (beginning with the CY 2019 reporting 
period) to improve the experience for program participants (82 FR 38390 
and 85 FR 58958). After several years of requiring only one quarter of 
eCQM data for reporting, at the end of March 2022, we successfully 
completed the submission period for two quarters of CY 2021 eCQM data. 
Three quarters of CY 2022 eCQM data will be due by February 28, 2023, 
and four quarters of CY 2023 eCQM data will not be due until February 
29, 2024. We believe this progressive increase in the quarters of data 
to be reported allows sufficient time for system readiness. In 
addition, we plan to continue to make changes to improve the system's 
usability as needed.
    Comment: A commenter requested clarification on the proposals for 
new eCQMs in the Hospital IQR Program given the stated intent to 
transition to FHIR-based quality measures.
    Response: We appreciate the commenter's request for clarification. 
We consider eCQMs to be a type of digital quality measure (87 FR 
28487). As we stated in section IX.C., in the ``Continuing to Advance 
Digital Quality Measurement and Use of Fast Healthcare Interoperability 
Resources (FHIR) in Hospital Quality Programs--Request for 
Information,'' while eCQMs meet the definition for dQMs in many 
respects, limitations in data standards, requirements, and technology 
have limited their interoperability. We appreciate the comments on, and 
interest in, this topic and we will continue to take all comments into 
account as we develop future regulatory proposals or other guidance for 
our digital quality measurement efforts.
    Comment: A commenter noted an error in Table IX.E-15 of the 
preamble of the FY 2023 IPPS/LTCH PPS proposed rule indicating the 
number of eCQMs required to be reported for the CY 2022 reporting 
period/FY 2024 payment determination.
    Response: We thank the commenter for the comment. In the FY 2023 
IPPS/LTCH PPS proposed rule(87 FR 28556), Table IX.E.15, first row, 
erroneously stated ``Four self-selected eCQMs'' for the eCQMs required 
to be reported for the CY 2022 reporting period/FY 2024 payment 
determination. We correct this error in Table IX.E-15 of this final 
rule to state ``Three self-selected eCQMs; and Safe Use of Opioids--
Concurrent Prescribing eCQM'' in alignment with the language throughout 
the preamble and as finalized in previous policy. To be clear, this was 
an inadvertent technical error. As finalized in the FY 2020 IPPS/LTCH 
PPS final rule, four eCQMs are required to be reported for the CY 2022 
reporting period/FY 2024 payment determination of which three are self-
selected and the Safe Use of Opioids--Concurrent Prescribing eCQM is 
required (84 FR 42505). In this final rule, we have revised Table IX. 
E-15 to correct the error.
    Comment: A commenter supported the proposal to modify eCQM 
reporting and submission requirements if CMS mandates the specific 
eCQMs to be reported, removing the ability of facilities to self-select 
eCQMs.
    Response: We thank the commenter for their input. For the present 
state, particularly before the implementation of the FHIR standard for 
eCQM reporting, we believe it is beneficial for hospitals to have the 
flexibility to self-select eCQMs for reporting and submission in 
addition to submitting data from high priority eCQMs that are mandatory 
for reporting. However, as we continue to transition toward more robust 
eCQM reporting, we will consider the commenter's feedback in future 
rulemaking.
    Comment: A commenter cautioned that public reporting before four 
quarters of data are reported for a reporting period may not show 
correct trends or patterns within the quality of care being provided by 
the organization.
    Response: We appreciate the commenter's concern and refer readers 
to the FY 2020 IPPS/LTCH PPS final rule where we finalized eCQM 
reporting and submission requirements for the CY 2023 reporting period/
FY 2025 payment determination to require hospitals to report four 
calendar quarters of data for each required eCQM: (a) Three self-
selected eCQMs; and (b) the Safe Use of Opioids--Concurrent Prescribing 
eCQM (85 FR 58974 through 58975). In the FY 2020 IPPS/LTCH PPS final 
rule, we also finalized public reporting requirements of eCQMs for the 
CY 2021 reporting period/FY 2023 payment determination and subsequent 
years, specifically publicly reporting two quarters of data for the CY 
2021 reporting period/FY 2023 payment determination, three quarters of 
data for the CY 2022 reporting period/FY 2024 payment determination, 
and for the CY 2023 reporting period/FY 2025 payment determination and 
subsequent years, we will publicly report four quarters of eCQM data 
(85 FR 58956). We believe that, beginning with the CY 2023 reporting 
period, the four quarters of data reported will provide more robust 
insight on the trends and patterns in the quality of care.
    After consideration of the public comments we received, we are 
finalizing our proposal as proposed.
(3) Continuation of Certification Requirements for eCQM Reporting
(a) Requiring Use of the 2015 Edition and 2015 Edition Cures Update 
Certification Criteria
    In the CY 2021 Physician Fee Schedule (PFS) final rule (85 FR 84825 
through 84828), we expanded flexibility under the Hospital IQR Program 
for the CY 2020 reporting period/FY 2022 payment determination and for 
subsequent years to allow hospitals to use either: (1) Technology 
certified to the 2015 Edition criteria as was previously finalized for 
reporting eCQMs in the FY 2019 IPPS/LTCH PPS final rule (83 FR 41537 
through 41608), or (2) certified technology updated consistent with the 
2015 Edition Cures Update as finalized in the ONC 21st Century Cures 
Act final rule (85 FR 25642 through 25961). We adopted this flexible 
approach to encourage hospitals to be early implementers of the 2015 
Edition Cures Update while remaining in compliance with Hospital IQR 
Program data submission requirements and maintaining alignment with 
requirements in the Medicare Promoting Interoperability Program for 
Eligible Hospitals and CAHs.
    In the FY 2022 IPPS/LTCH PPS final rule, beginning with the CY 2023 
reporting period/FY 2025 payment determination and subsequent years, we 
finalized the requirement for hospitals to use only certified 
technology updated consistent with the 2015 Edition Cures Update to 
submit data for the Hospital IQR Program data (86 FR 45418). We refer 
readers to the ONC 21st Century Cures Act final rule for additional 
information about the updates included in the 2015 Edition Cures Update 
(85 FR 25665). We did not propose any changes to this policy.
(b) Requiring EHR Technology To Be Certified to All Available eCQMs
    In the FY 2020 IPPS/LTCH PPS final rule (84 FR 42505 through 
42506), we finalized the requirement that EHRs be certified to all 
available eCQMs used in the Hospital IQR Program for the CY 2020 
reporting period/FY 2022 payment determination and subsequent years. In 
the FY 2022 IPPS/LTCH PPS final rule (86 FR 45418), we finalized the 
requirement for hospitals to use the 2015 Edition Cures Update 
beginning

[[Page 49303]]

with the CY 2023 reporting period/FY 2025 payment determination, then 
all available eCQMs used in the Hospital IQR Program for the CY 2023 
reporting period/FY 2025 payment determination and subsequent years 
would need to be reported using certified technology updated to the 
2015 Edition Cures Update. We did not propose any changes to this 
policy.
(4) File Format for EHR Data, Zero Denominator Declarations, and Case 
Threshold Exemptions
    We refer readers to the FY 2016 IPPS/LTCH PPS final rule (80 FR 
49705 through 49708) and the FY 2017 IPPS/LTCH PPS final rule (81 FR 
57170) for our previously adopted eCQM file format requirements. Under 
these requirements, hospitals: (1) Must submit eCQM data via the 
Quality Reporting Document Architecture Category I (QRDA I) file 
format, (2) may use third parties to submit QRDA I files on their 
behalf, and (3) may either use abstraction or pull the data from non-
certified sources to then input these data into Certified EHR 
Technology (CEHRT) for capture and reporting QRDA I. Hospitals can 
continue to meet the reporting requirements by submitting data via QRDA 
I files, zero denominator declaration, or case threshold exemption (82 
FR 38387).
    More specifically regarding the use of QRDA I files, we refer 
readers to the FY 2017 IPPS/LTCH PPS final rule (81 FR 57169 through 
57170) and the FY 2020 IPPS/LTCH PPS final rule (85 FR 58940), in which 
we stated that we expect QRDA I files to reflect data for one patient 
per file per quarter, and identified the five key elements that are 
utilized to identify the file:
     CMS Certification Number (CCN);
     CMS Program Name;
     EHR Patient ID;
     Reporting period specified in the Reporting Parameters 
Section per the CMS Implementation Guide for the applicable reporting 
year, which is published on the eCQI Resource Center website at: 
https://ecqi.healthit.gov/QRDA; and
     EHR Submitter ID (beginning with the CY 2021 reporting 
period/FY 2023 payment determination).
    We did not propose any changes to this policy.
(5) Submission Deadlines for eCQM Data
    We refer readers to the FY 2015 IPPS/LTCH PPS final rule (79 FR 
50256 through 50259), the FY 2016 IPPS/LTCH PPS final rule (80 FR 49705 
through 49709), and the FY 2017 IPPS/LTCH PPS final rule (81 FR 57169 
through 57172) for our previously adopted policies to align eCQM data 
reporting periods and submission deadlines for both the Hospital IQR 
Program and the Medicare Promoting Interoperability Program for 
Eligible Hospitals and CAHs. In the FY 2017 IPPS/LTCH PPS final rule 
(81 FR 57172), we finalized the alignment of the Hospital IQR Program 
eCQM submission deadline with that of the Medicare Promoting 
Interoperability Program for Eligible Hospitals and CAHs--the end of 
two months following the close of the calendar year--for the CY 2017 
reporting period/FY 2019 payment determination and subsequent years. We 
note the submission deadline will be moved to the next business day if 
it falls on a weekend or Federal holiday. We did not propose any 
changes to this policy.
f. Data Submission and Reporting Requirements for Hybrid Measures
(1) Background
    The Hospital IQR Program recently adopted hybrid measures into the 
program's measure set. In the FY 2018 IPPS/LTCH PPS final rule (82 FR 
38350 through 38355), we finalized voluntary reporting of the Hybrid 
Hospital-Wide Readmission (Hybrid HWR) measure for the CY 2018 
reporting period. In the FY 2020 IPPS/LTCH PPS final rule, we finalized 
the adoption of the Hybrid HWR measure for the Hospital IQR Program (84 
FR 42465 through 42481) such that, beginning with the FY 2026 payment 
determination, hospitals are required to report on the Hybrid HWR 
measure (84 FR 42479). In the FY 2022 IPPS/LTCH PPS final rule, we also 
finalized the adoption of the Hybrid Hospital-Wide All-Cause Risk 
Standardized Mortality (Hybrid HWM) measure in a stepwise fashion, 
beginning with a voluntary reporting period from July 1, 2022 through 
June 30, 2023, and followed by mandatory reporting from July 1, 2023 
through June 30, 2024, affecting the FY 2026 payment determination and 
for subsequent years (86 FR 45365). We also finalized several 
requirements related to data submission and reporting requirements for 
hybrid measures under the Hospital IQR Program (84 FR 42506 through 
42508). In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28557 through 
28558), we proposed changes specific to the zero denominator 
declarations and case threshold exemptions policies for hybrid 
measures, as discussed further in the subsequent section.
(2) Certification and File Format Requirements
    We refer readers to the FY 2020 IPPS/LTCH PPS final rule (84 FR 
19498 through 19499), the FY 2021 IPPS/LTCH PPS final rule (85 FR 
58941), and the CY 2021 PFS final rule (85 FR 84472) for our previously 
adopted policies regarding certification and file format requirements 
for hybrid measures in the Hospital IQR Program.
    In the CY 2021 PFS final rule (85 FR 84825 through 84828), we 
finalized flexibility to allow hospitals to use either: (1) Technology 
certified to the 2015 Edition criteria as was previously finalized in 
the FY 2019 IPPS/LTCH PPS final rule (83 FR 41537 through 41608) or (2) 
certified technology updated consistent with the 2015 Edition Cures 
Update as finalized in the ONC 21st Century Cures Act final rule (85 FR 
25642 through 25961, 85 FR 50271), beginning with the CY 2020 reporting 
period/FY 2022 payment determination and subsequent years. The Hospital 
IQR Program offers flexibility to meet hybrid measure submission 
requirements to facilitate successful reporting during the period of 
transition as providers are updating certified technology to be 
consistent with the 2015 Edition Update. This flexibility applies to 
all Hospital IQR Program measures which use EHR data elements to 
calculate measure rates, including eCQMs and hybrid measures.
    In the FY 2022 IPPS/LTCH PPS final rule, to align with the health 
IT certification requirements for eCQM reporting, we finalized to 
require hospitals to use only certified technology that has been 
updated consistent with the 2015 Edition Cures Update to submit hybrid 
measure data beginning with the CY 2023 reporting period/FY 2025 
payment determination and for subsequent years (86 FR 45421). We did 
not propose any changes to these policies in the proposed rule.
(3) Additional Submission Requirements
    In the FY 2020 IPPS/LTCH PPS final rule, we finalized allowing 
hospitals to meet the hybrid measure reporting and submission 
requirements by submitting any combination of data via QRDA I files, 
zero denominator declarations, and case threshold exemptions (84 FR 
42507). We also finalized applying similar zero denominator declaration 
and case threshold exemption policies to hybrid measure reporting as we 
allow for eCQM reporting (84 FR 42507 through 42508).
    We note that the ONC 21st Century Cures Act final rule revises the 
clinical

[[Page 49304]]

quality measurement criterion at 45 CFR 170.315(c)(3) to refer to CMS 
QRDA IGs and remove the HL7[supreg] QRDA standard requirements (85 FR 
25645). We encourage all hospitals and their health IT vendors to 
submit QRDA I files early, and to use one of the pre-submission testing 
tools for electronic reporting, such as submitting test files to the 
HQR System, to allow additional time for testing and make sure all 
required data files are successfully submitted by the deadline.
(4) Modification of the Zero Denominator Declarations Policy and Case 
Threshold Exemptions Policy for Hybrid Measures
    As stated in the previous section (section IX.E.10.f.(3).), in the 
FY 2020 IPPS/LTCH PPS final rule, we finalized applying the zero 
denominator declarations policy and case threshold exemptions policy to 
hybrid measure reporting (84 FR 42507 through 42508). Additionally, in 
the FY 2020 IPPS/LTCH PPS final rule, we indicated that zero 
denominator declarations and case threshold exemptions would not be 
necessary during the voluntary reporting periods for hybrid measures 
but would be an option for hospitals to utilize when hybrid measure 
reporting became mandatory (84 FR 42508).
    In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28558), we 
proposed to remove zero denominator declarations and case threshold 
exemptions as an option for the reporting of hybrid measures beginning 
with the FY 2026 payment determination for reasons discussed in the 
subsequent section. We note that the FY 2026 payment determination is 
the first year for which hybrid measures, finalized as part of the 
Hospital IQR Program measure set, will become mandatory for reporting.
    Zero denominator declarations allow a hospital whose EHR is capable 
of reporting hybrid measure data to submit a zero in the denominator 
for the reporting of a measure if the hospital does not have patients 
that meet the denominator criteria of that hybrid measure (84 FR 
42507). Similarly, the case threshold exemptions policy allows for a 
hospital with five or fewer inpatient discharges per quarter or 20 or 
fewer inpatient discharges per year in a given denominator declaration 
be exempted from reporting on that individual hybrid measure (84 FR 
42507). These policies were originally developed for eCQMs and were 
extended to hybrid measures to ensure hospitals were not penalized for 
the absence of patients that meet the denominator criteria in the 
reporting of those measures.
    Upon further analysis, however, we do not believe that these 
policies are applicable for hybrid measures due to the process of 
reporting the measure data. Hybrid measures do not require that 
hospitals report a traditional denominator as is required for the 
submission of eCQMs. Instead, hybrid measures utilize the Initial 
Patient Population (IPP), as per their measure specifications, that 
identifies the patients for which hospitals need to extract the EHR 
data and annual claims data. Additionally, we calculate hybrid measures 
by merging both the claims and EHR data received. Therefore, since we 
will confirm the measure cohort to determine whether a hospital has met 
the denominator criteria, both the zero denominator declaration and the 
case threshold exemption for hybrid measures will not be applicable to 
hospitals.
    We invited public comment on this proposal.
    Comment: A commenter supported our proposal to remove the zero 
denominator declarations and case threshold exemptions policies for 
hybrid measures beginning with the FY 2026 payment determination.
    Response: We thank the commenter for the support.
    After consideration of the public comments we received, we are 
finalizing our proposal as proposed.
(5) Submission Deadlines for Hybrid Measures
    We refer readers to the FY 2020 IPPS/LTCH PPS final rule (84 FR 
42508), where we finalized submission deadlines for hybrid measures. We 
did not propose any changes to these policies in the proposed rule.
g. Sampling and Case Thresholds for Chart-Abstracted Measures
    We refer readers to the FY 2011 IPPS/LTCH PPS final rule (75 FR 
50221), the FY 2012 IPPS/LTCH PPS final rule (76 FR 51641), the FY 2013 
IPPS/LTCH PPS final rule (77 FR 53537), the FY 2014 IPPS/LTCH PPS final 
rule (78 FR 50819), and the FY 2016 IPPS/LTCH PPS final rule (80 FR 
49709) for details on our sampling and case thresholds for the FY 2016 
payment determination and subsequent years. We did not propose any 
changes to these policies in the proposed rule.
h. HCAHPS Administration and Submission Requirements
    We refer readers to the FY 2011 IPPS/LTCH PPS final rule (75 FR 
50220), the FY 2012 IPPS/LTCH PPS final rule (76 FR 51641 through 
51643), the FY 2013 IPPS/LTCH PPS final rule (77 FR 53537 through 
53538), and the FY 2014 IPPS/LTCH PPS final rule (78 FR 50819 through 
50820) for details on previously-adopted HCAHPS submission 
requirements. We also refer hospitals and HCAHPS Survey vendors to the 
official HCAHPS website at https://www.hcahpsonline.org for new 
information and program updates regarding the HCAHPS Survey, its 
administration, oversight, and data adjustments. We did not propose any 
changes to these policies in the proposed rule.
i. Data Submission Requirements for Structural Measures
    We refer readers to the FY 2012 IPPS/LTCH PPS final rule (76 FR 
51643 through 51644) and the FY 2013 IPPS/LTCH PPS final rule (77 FR 
53538 through 53539) for details on the data submission requirements 
for structural measures. Hospitals are required to submit information 
for structural measures once annually using a CMS-approved web-based 
data collection tool available within the HQR System. The data 
submission period for structural measures begins in April and has the 
same submission deadline as the fourth calendar quarter chart-
abstracted measure deadline. For example, for the FY 2025 payment 
determination, hospitals would be required to submit the required 
information between April 1, 2024 and May 15, 2024, with respect to the 
time period of January 1, 2023 through December 31, 2023.
    We note that, in the FY 2022 IPPS/LTCH PPS final rule (86 FR 
45361), for the Maternal Morbidity Structural Measure and the CY 2021 
reporting period/FY 2023 payment determination only, we finalized a 
shortened reporting period from October 1, 2021 through December 31, 
2021, while retaining the standard data submission period. 
Specifically, for the shortened reporting period hospitals will be 
required to submit the data between April 1, 2022 and May 16, 2022 (we 
note that May 15, 2022 falls on a weekend and therefore the close of 
this data submission period is moved to May 16, 2022). Thereafter, we 
finalized that the reporting period for the Maternal Morbidity 
Structural Measure will run from: January 1 through December 31 on an 
annual basis, and that the data submission period will continue to be 
consistent with our current policy (beginning in April until the same 
submission deadline as for the fourth calendar quarter of the chart-
abstracted measures with respect to the reporting period for

[[Page 49305]]

the previous calendar year) (86 FR 45361).
    We did not propose any changes to these policies in the proposed 
rule.
j. Data Submission and Reporting Requirements for CDC NHSN Measures
    For details on the data submission and reporting requirements for 
measures reported via the CDC's National Healthcare Safety Network 
(NHSN), we refer readers to the FY 2012 IPPS/LTCH PPS final rule (76 FR 
51629 through 51633; 51644 through 51645), the FY 2013 IPPS/LTCH PPS 
final rule (77 FR 53539), the FY 2014 IPPS/LTCH PPS final rule (78 FR 
50821 through 50822), and the FY 2015 IPPS/LTCH PPS final rule (79 FR 
50259 through 50262). The data submission deadlines are posted on the 
QualityNet website.
    We note that in the FY 2022 IPPS/LTCH PPS final rule, we finalized 
the adoption of the COVID-19 Vaccination Among Health Care Personnel 
measure, beginning in October 2021 for the October 1, 2021 through 
December 31, 2021 reporting period affecting the FY 2023 payment 
determination and continuing for each quarter in subsequent years (86 
FR 45374). Specific details on data submission for this measure can be 
found in the CDC's Overview of the Healthcare Safety Component, 
available at: https://www.cdc.gov/nhsn/PDFs/slides/NHSN-Overview-HPS_Aug2012.pdf. We did not propose any changes to these policies in 
the proposed rule.
k. Data Submission and Reporting Requirements for Patient-Reported 
Outcome-Based Performance Measures (PRO-PMs)
    In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28559 through 
28560), in section IX.E.5.g., we proposed the adoption of the hospital-
level THA/TKA PRO-PM into the Hospital IQR Program measure set. In this 
section of the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28559 through 
28560), we proposed the reporting and submission requirements for PRO-
PM measures as a new type of measure to the Hospital IQR Program.
(1) Submission of PRO-PM Data
(a) Data Submission
    In section IX.E.5.g. of the preamble of this final rule, we discuss 
adoption of the THA/TKA PRO-PM in the Hospital IQR Program. In the FY 
2023 IPPS/LTCH PPS proposed rule (87 FR 28527), we proposed that 
hospitals would have the choice of selecting from multiple submission 
approaches.
    First hospitals may choose to: (1) Send their data to CMS for 
measure calculation directly; or (2) utilize an external entity, such 
as through a vendor or registry, to submit their data on behalf of the 
hospital to CMS for measure calculation. This data submission approach 
is consistent with stakeholder input received by the measure developer 
during measure development and comments as summarized in the FY 2022 
IPPS/LTCH PPS final rule (86 FR 45411 through 45414) which recommended 
CMS provide multiple options for data submission mechanisms to ensure 
flexibility.
    Whether a hospital chooses to submit the data itself or via a 
vendor, we would allow a range of file formats. Both hospitals and 
vendors would use the HQR System for data submission for the THA/TKA 
PRO-PM. Use of the HQR System leverages existing CMS infrastructure 
already utilized for other quality measures (such as, HCAHPS or the 
Sepsis measure). The HQR System allows for data submission using the 
following file formats: CSV, XML, and a manual data entry option; 
allowing hospitals and vendors flexibility in data submission. We would 
provide hospitals with additional detailed information and instructions 
for submitting data using the HQR System through CMS' existing 
websites, such as on QualityNet, and through listservs or both.
(b) Data Submission Reporting Requirements
(1) Voluntary Reporting Requirements for the Proposed THA/TKA PRO-PM
    As discussed earlier, we proposed a phased implementation approach 
for adoption of the THA/TKA PRO-PM, with two voluntary reporting 
periods for the CY 2025 and 2026 reporting periods prior to mandatory 
reporting beginning with the FY 2028 payment determination. Voluntary 
reporting prior to mandatory reporting would allow time for hospitals 
to incorporate the THA/TKA PRO-PM data collection into their clinical 
workflows and is responsive to stakeholder comments summarized in the 
FY 2022 IPPS/LTCH PPS final rule (86 FR 45411 through 45414). For each 
voluntary and subsequent mandatory reporting periods, we would collect 
data on the THA/TKA PRO-PM in accordance with, and to the extent 
permitted by, the HIPAA Privacy and Security Rules (45 CFR parts 160 
and 164, Subparts A, C, and E), and other applicable federal law.
    For hospitals participating in voluntary reporting, hospitals would 
submit pre-operative PRO data, as well as matching post-operative PRO 
data for at least 50 percent of their eligible elective primary THA/TKA 
procedures. The first voluntary reporting period for CY 2025 would 
include pre-operative PRO data collection from October 3, 2022 through 
June 30, 2023 (for eligible elective THA/TKA procedures performed from 
January 1, 2023 through June 30, 2023) and post-operative PRO data 
collection from October 28, 2023 to August 28, 2024. Hospitals would 
submit pre-operative data in 2023 and post-operative data in 2024, and 
we intend to provide hospitals with their results in confidential 
feedback reports in 2025. Hospitals would submit pre-operative data for 
the first voluntary reporting three months following the end of the 
performance period. For post-operative data, hospitals would be 
required to submit data one month following the end of the performance 
period. If that day falls on a weekend, submissions will be due the 
following Monday. For example, for procedures performed between January 
1, 2023 and June 30, 2023, pre-operative data will need to be submitted 
by October 2, 2023. After the initial submission of pre-operative data 
in the first voluntary period, hospitals would submit both pre-
operative and post-operative data by the same day, but for different 
time periods. For example, hospitals would need to submit: (1) Post-
operative data for the first voluntary reporting (for procedures 
performed between January 1, 2023 and June 30, 2023); and (2) pre-
operative data for the second voluntary reporting (for procedures 
performed between July 1, 2023 and June 30, 2024) of the THA/TKA PRO-PM 
by September 30, 2024.
    The second voluntary reporting period will include pre-operative 
PRO data collection from April 2, 2023 through June 30, 2024 (for 
eligible elective THA/TKA procedures performed from July 1, 2023 
through June 30, 2024) and post-operative PRO data collection from 
April 26, 2024 to August 29, 2025. Hospitals would submit pre-operative 
data in 2024 and post-operative data in 2025, and we noted our 
intention to provide hospitals with their results in confidential 
feedback reports in 2026.
    We refer readers to Table IX.E-16. for an overview of the proposed 
performance period, pre- and post-operative data collection timeframes, 
and data submission deadlines during voluntary reporting.

[[Page 49306]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.176

(2) Mandatory Reporting
    Following the two voluntary reporting periods, we proposed the 
mandatory reporting of the THA/TKA PRO-PM would begin with reporting 
PRO data for eligible elective THA/TKA procedures from July 1, 2024 
through June 30, 2025 (performance period), impacting the FY 2028 
payment determination. This initial mandatory reporting would include 
pre-operative PRO data collection from three months preceding the 
applicable performance period and from 10 to 14 months after the 
performance period. For example, pre-operative data from April 2, 2024 
through June 30, 2025 (for eligible elective primary THA/TKA procedures 
from July 1, 2024 through June 30, 2025) and post-operative PRO data 
collection from April 27, 2025 to August 29, 2026. Pre-operative data 
submission would occur in 2025 and post-operative data submission in 
2026 and we noted our intention to provide hospitals with their results 
in 2027 before publicly reporting results on the Compare tool hosted by 
HHS, currently available at: https://www.medicare.gov/care-compare, or 
its successor website. Hospitals would be required to submit 50 percent 
of eligible, complete pre-operative data with matching eligible, 
complete post-operative data as a minimum amount of data for mandatory 
reporting in the Hospital IQR Program.
    We refer readers to Table IX.E-17. for an overview of the proposed 
performance period, pre- and post-operative data collection timeframes, 
and data submission deadlines during the mandatory reporting period.
[GRAPHIC] [TIFF OMITTED] TR10AU22.177

    We invited public comment on this proposal.
    Comment: Several commenters supported the adoption of the Hospital-
Level, Risk Standardized Patient-Reported Outcomes Performance Measure 
(PRO-PM) Following Elective Primary Total Hip Arthroplasty (THA) and/or 
Total Knee Arthroplasty (TKA) (THA/TKA PRO-PM), beginning with two 
voluntary reporting periods followed by mandatory reporting for the 
reporting period which runs from July 1, 2025, through June 30, 2026, 
impacting the FY 2028 payment determination. A commenter specifically 
supported patient-reported outcome measures as a way to assess quality 
of care and effectiveness from the patient perspective. A commenter 
generally supported the addition of PRO-PMs into quality programs for 
clinical scenarios where reliable PRO instruments are available for 
patients to complete. A commenter supported CMS beginning PRO-PMs using 
elective procedures. A few commenters specifically supported the 
adoption of the THA/TKA PRO-PM to the Hospital IQR Program stating it 
enables patient voices to be heard throughout all phases of their care 
and recovery, and the measure is important as it includes the patient 
voice in assessment of outcomes which should be reflected in quality 
and safety performance.
    Response: We thank commenters for their support.
    Comment: Several commenters discussed the data collection approach 
and burden associated with the adoption of the THA/TKA PRO-PM into the 
Hospital IQR Program. A few commenters supported having multiple modes 
for data collection and submission of PRO data, including the use of 
registries. A commenter supported the use of Medicare enrollment data 
as the source to identify dual eligibility status and variables for 
risk adjustment.
    Many commenters stated specifically that the financial, resource, 
and labor costs required to collect, track, and submit data would 
burden hospitals and make successful implementation of the measure 
difficult. A commenter encouraged delayed adoption for several years to 
give health systems time to recover resources and staffing impacted by 
the COVID-19 pandemic. Another commenter expressed concern about small 
hospitals' ability to collect and report data and suggested we 
institute technical support as well as financial bonuses for them to 
utilize. A commenter urged us to consider technical difficulties of 
adopting a PRO-PM and noted limitations in data infrastructure and EHR 
systems, and a lack of integration between PRO data. The commenter 
expressed that progress in this area will require adoption of newer 
technologies such as machine learning and artificial intelligence to 
advance the healthcare system.
    Response: We thank commenters for their feedback regarding data 
collection and burden. We agree that having multiple modes of data 
collection, including use of registries, would be

[[Page 49307]]

beneficial to hospitals and reduce burden. We acknowledge the concerns 
regarding financial, labor, and resource burdens associated with 
adopting the THA/TKA PRO-PM into the Hospital IQR Program and are 
seeking to advance patient-centered measurement with as little burden 
as possible to both providers and patients. While PRO-PMs require 
providers to integrate data collection into clinical workflows, this 
integration provides an opportunity for patient-reported outcomes to 
inform clinical decision making and benefits patients by engaging them 
in discussions about potential outcomes.
    The PRO instruments used to calculate pre- and post-operative 
scores for this THA/TKA PRO-PM were carefully considered, with 
extensive stakeholder input from clinicians, to be low burden and are 
non-proprietary for free use. We will evaluate data collection burden 
and response rates associated with the THA/TKA PRO-PM. Any feedback on 
data collection will be considered in future measure development and 
reevaluation.
    We thank commenters for their feedback, and will provide hospitals 
and other interested parties with more information on data collection 
and reporting for the THA/TKA PRO-PM through education and outreach 
activities prior to implementation. We will continue to evaluate 
feedback on challenges with data collection during voluntary reporting 
and consider them prior to mandatory reporting.
    Comment: A commenter encouraged us to minimize data collection 
burden to patients by leveraging technology and considering other 
surveys they are requested to complete, such as HCAHPS. Another 
commenter requested additional research to understand the burden of the 
measure on hospitals and patients, including patient survey fatigue, 
impact of new PRO-PMs on established survey measures like HCAHPS, and 
acceptable level of burden for use of the measure.
    Response: This measure was developed with extensive input from 
patients, who indicated strong support for a PRO-PM following elective 
primary THA and TKA. We anticipate data collection for this measure to 
present a low burden to patients. Regarding survey fatigue, we designed 
the measure to illuminate a patient's pain and functional status before 
and after a THA or TKA, which is different than other surveys such as 
HCAHPS that capture patient experience. Regarding the comment that the 
THA/TKA PRO-PM may have a reporting impact on other measures, such as 
HCAHPS, we anticipate a minimal impact to other measures as the THA/TKA 
PRO-PM's eligible population is procedure-specific which reduces the 
likelihood of the same patient receiving the HCAHPS and PRO survey. 
Additionally, the THA/TKA PRO-PM pre-operative assessment (90 to 0 days 
before surgery) and post-operative assessment (300 to 425 days 
following surgery) timeframe is different than HCAHPS, which is two 
weeks after a hospital visit.
    Comment: A commenter requested we not adopt the THA/TKA PRO-PM in 
the Hospital IQR Program until operational challenges identified by CJR 
participating hospitals are shared publicly, independently analyzed, 
and addressed. Commenters expressed concern that reporting of the THA/
TKA PRO-PM as part of the CJR Model has been challenging and 
burdensome, resulting in potentially impacting completion rates. A 
commenter expressed concern response rates will be insufficient to 
calculate reliable and valid results for comparison of hospital 
performance. Another commenter stated hospitals have not been able to 
meet high reporting thresholds and have challenges with survey response 
rates for the THA/TKA PRO-PM as part of the CJR Model. The commenter 
recommended CMS analyze pre- and post-operative response rates in the 
CJR Model and consider ways to support hospitals in increasing 
responsiveness. Another commenter requested CMS lower the 50 percent 
submission requirement proposal until it is clear hospitals can produce 
this.
    Response: We appreciate commenters' request for information about 
use of the measure in the CJR Model. We have gathered feedback from 
several years of PRO data collection by CJR participating hospitals and 
applied lessons learned to the THA/TKA PRO-PM proposal for adoption in 
the Hospital IQR Program, including requiring hospitals to collect and 
submit fewer variables, allowing hospitals flexibility in data 
collection options to better integrate into their workflows, and 
influenced the decision to set the initial reporting threshold to a 
moderate rate of 50 percent reporting threshold. We highlight that our 
proposal included two voluntary reporting periods in which we would 
gather additional feedback from participating hospitals on their 
experience collecting and submitting data and apply any lessons learned 
prior to mandatory reporting.
    The proposed reporting threshold is based on average response rates 
for both pre-operative and post-operative surveys collected by 
participating hospitals in the CJR Model. The proposed reporting 
threshold for adoption of the measure to the Hospital IQR Program is 
lower than that currently used in the CJR Model. Additionally, 
hospitals are not held to reporting thresholds until mandatory 
reporting. We believe hospitals will therefore have time to develop 
their data collection and reporting processes. We will continue to 
consider the appropriate pre- and post-operative matched survey 
response rate, as well as reporting thresholds. We will evaluate this 
approach during voluntary reporting and consider adjustments based on 
feedback prior to mandatory reporting.
    Comment: A few commenters supported the proposed phased 
implementation timeline. A few commenters requested CMS delay mandatory 
reporting of the measure to allow hospitals time to enhance 
interoperability and develop processes for successful data collection 
and submission. A commenter stated the proposed voluntary and mandatory 
reporting timeline does not provide hospitals sufficient time to gain 
experience or use results to improve data collection processes. A 
commenter requested three years of voluntary reporting.
    Response: We thank commenters for their support of the phased 
approach of adopting the THA/TKA PRO-PM in the Hospital IQR Program. We 
have considered commenters' recommendations regarding voluntary and 
mandatory reporting timelines. We believe the proposed voluntary and 
mandatory reporting implementation approach allows hospitals time and 
notice to make the necessary enhancements to their clinical workflow to 
successfully report this measure. We highlight that our proposal 
included two voluntary reporting periods prior to mandatory reporting 
which balances the need to allow hospitals time to prepare for 
mandatory reporting with the importance of measuring patients' 
functional status for these common surgical procedures and the need to 
make this information publicly available for patient use and quality 
improvement (87 FR 28528 through 28529). We also note that the proposed 
first voluntary reporting period uses just six months of data to allow 
hospitals an opportunity to receive feedback more quickly on, and 
improve, their data collection and submission processes (87 FR 28528). 
We intend to carefully consider feedback received during voluntary 
reporting to inform improvements that may be made for mandatory 
reporting.
    Comment: A commenter requested reimbursement to incentivize 
reporting

[[Page 49308]]

of the THA/TKA PRO-PM and suggested we create a G code for near term 
use, and a CPT code for permanent use.
    Response: We acknowledge commenters' feedback on reimbursement 
incentives. The Hospital IQR Program statutory authority in section 
1886(b)(3)(B)(viii) of the Act does not provide for the ability to 
award incentive payments for meeting program requirements as it is a 
pay-for-reporting quality program.
    Comment: Another commenter requested CMS share performance results 
with hospitals transparently and in real time for use in shared 
decision making.
    Response: We confirm that hospitals will receive performance 
results confidentially as part of both voluntary and mandatory 
reporting. We encourage hospitals to use these results as part of 
shared decision making with their patients.
    Comment: A commenter expressed concern with response bias and noted 
accounting for patient socioeconomic status, race, or dual eligibility 
in the risk model is not adequate to address lack of response.
    Response: We thank the commenter for their input regarding health 
disparities and response bias. We agree that considering the unique 
experience of populations with social risk factors is important. The 
measure as proposed accounts for potential non-response bias through 
inverse probability weighting and considers patient characteristics, 
including non-white race, dual eligibility, and the AHRQ SES index 
score.\1084\ The AHRQ SES index score is computed using US census data 
and considers factors including zip code, median household income, 
percentage of persons below the Federal poverty line, unemployment, 
education, property value, and percentage of persons in crowded 
households.\1085\ The measure also includes health literacy in the risk 
model.\1086\ We encourage hospitals to consider a variety of PRO data 
collection methods to support responses from all eligible patients. We 
will continue to assess the impact of social risk factors on the 
measure and response rates over time.
---------------------------------------------------------------------------

    \1084\ Patient-Reported Outcomes (PROs) Following Elective 
Primary Total Hip and/or Total Knee Arthroplasty: Hospital-Level 
Performance Measure (Version 1.0 Methodology Report). March 2021.
    \1085\ Bonito A, Bann C, Eicheldinger C, Carpenter L. Creation 
of new race-ethnicity codes and socioeconomic status (SES) 
indicators for Medicare beneficiaries. Final Report, Sub-Task. 
2008;2.
    \1086\ Patient-Reported Outcomes (PROs) Following Elective 
Primary Total Hip and/or Total Knee Arthroplasty: Hospital-Level 
Performance Measure (Version 1.0 Methodology Report). March 2021.
---------------------------------------------------------------------------

    After consideration of the public comments we received, we are 
finalizing our proposal as proposed.
11. Validation of Hospital IQR Program Data
    In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28560 through 
28562), we proposed to update our eCQM validation process. 
Specifically, we proposed to update our validation requirements for 
eCQMs from our current requirement that hospitals submit timely and 
complete data for 75 percent of requested records to submission of 
timely and complete data for 100 percent of requested records beginning 
with CY 2022 eCQM data affecting the FY 2025 payment determination and 
for subsequent years. We note that this will not affect finalized 
policies with respect to validation of chart-abstracted measures.
a. Background
    We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR 
53539 through 53553), the FY 2014 IPPS/LTCH PPS final rule (78 FR 50822 
through 50835), the FY 2015 IPPS/LTCH PPS final rule (79 FR 50262 
through 50273), the FY 2016 IPPS/LTCH PPS final rule (80 FR 49710 
through 49712), the FY 2017 IPPS/LTCH PPS final rule (81 FR 57173 
through 57181), the FY 2018 IPPS/LTCH PPS final rule (82 FR 38398 
through 38403), the FY 2019 IPPS/LTCH PPS final rule (83 FR 41607 
through 41608), the FY 2020 IPPS/LTCH PPS final rule (84 FR 42509), the 
FY 2021 IPPS/LTCH PPS final rule (85 FR 58942 through 58953), and the 
FY 2022 IPPS/LTCH PPS final rule (86 FR 45423 through 45426) for 
detailed information on and previous changes to chart-abstracted and 
eCQM validation requirements for the Hospital IQR Program.
    In the FY 2017 IPPS/LTCH PPS final rule, we finalized our policy to 
require submission of at least 75 percent of sampled eCQM medical 
records in a timely and complete manner for validation (81 FR 57181). 
To ensure we have adequate data to assess and validate eCQMs, we 
finalized a requirement that hospitals submit at least 75 percent of 
sampled eCQM medical records (81 FR 57173 through 57175). In the FY 
2021 IPPS/LTCH PPS final rule, we combined the validation processes for 
eCQMs and chart-abstracted measures, but did not update the threshold 
submission percent for eCQM medical records (85 FR 58952 through 
58944). In that rule, we adopted a policy to remove the separate 
process for eCQM validation, beginning with the validation affecting 
the FY 2024 payment determination (for validation commencing in CY 2022 
using data from the CY 2021 reporting period) (85 FR 58942 through 
58953). Beginning with validation affecting the FY 2024 payment 
determination and subsequent years, we finalized a policy to 
incorporate eCQMs into the existing validation process for chart-
abstracted measures such that there would be one pool of hospitals 
selected through random selection and one pool of hospitals selected 
using targeting criteria, for both chart-abstracted measures and eCQMs 
(85 FR 58942 through 58953). Under the aligned validation process, a 
single hospital could be selected for validation of both eCQMs and 
chart-abstracted measures and is expected to submit data for both 
chart-abstracted measures and eCQMs (85 FR 58942 through 58953). We 
refer readers to the FY 2017 IPPS/LTCH PPS final rule (81 FR 57179 
through 57180) for details on the Hospital IQR Program data submission 
requirements for chart-abstracted measures. We did not propose any 
changes to finalized policies for validation of chart-abstracted 
measures.
b. Modifications to the Existing Processes for Validation of Hospital 
IQR Program eCQM Data
    In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28561), we 
proposed to update our eCQM validation requirement to require that 
hospitals selected for validation submit timely and complete data for 
100 percent of requested records for eCQM validation beginning with CY 
2022 eCQM data, affecting the FY 2025 payment determination and for 
subsequent years. Hospitals selected for eCQM validation are required 
to submit timely and sufficient medical records. As finalized in the FY 
2017 IPPS/LTCH PPS final rule (81 FR 57178 through 57179), hospitals 
must submit timely medical records--within 30 days of the records 
request--to meet eCQM validation requirements. To meet the eCQM 
validation requirement for sufficient medical records, we proposed to 
increase the submission threshold from 75 percent to 100 percent 
beginning with validation of CY 2022 eCQM data affecting the FY 2025 
payment determination and for subsequent years.
    Ever since validation of eCQMs commenced with CY 2017 data (81 FR 
57173 through 57181), all hospitals selected for eCQM validation have 
successfully submitted at least 75 percent of eCQM medical records

[[Page 49309]]

requested by the Clinical Data Abstraction Center (CDAC). Additionally, 
95 percent of hospitals selected for participation in eCQM validation 
for the FY 2020 and FY 2021 payment determinations, which are the most 
recently available periods, voluntarily and successfully submitted 100 
percent of requested records. We believe that increasing the submission 
threshold from 75 percent to 100 percent of the requested records will 
support our ongoing goal of continuing to assess the accuracy of eCQM 
measure data (81 FR 57155). Also, given the high rate of hospitals 
voluntarily submitting 100 percent of records, we believe updating the 
submission threshold to 100 percent will be feasible for hospitals.
    We note that under our current policy, the accuracy of eCQM data 
(the extent to which data abstracted for validation matches the data 
submitted in the QRDA I file) submitted for validation does not affect 
a hospital's validation score as described in the FY 2017 IPPS/LTCH PPS 
final rule (81 FR 57180 through 57181) and will not be impacted by this 
finalized update to the submission threshold. We also note that 
hospitals that fail to submit timely and complete medical records will 
not meet the eCQM validation requirement and will be subject to payment 
reduction as described in our previously finalized policy (81 FR 
57180). Chart-abstracted data continue to be weighted at 100 percent 
for payment determination as finalized in the FY 2021 IPPS/LTCH PPS 
final rule (85 FR 58942 through 58953) and will not be impacted by our 
proposed modification to the eCQM validation.
    The previously finalized eCQM validation requirements, including 
data submission requirements, are described at 42 CFR 
412.140(d)(2)(ii). We also proposed to update the references to ``at 
least 75 percent'' in this Hospital IQR Program regulation text. 
Specifically, we proposed to remove the phrase ``at least 75 percent'' 
and add in its place the phrase ``100 percent.'' We continue to 
evaluate data submitted for validation for potential future policy 
changes.
    Our previously finalized and newly proposed validation scoring 
changes are summarized in Table IX.E-18.
[GRAPHIC] [TIFF OMITTED] TR10AU22.178

    We invited public comment on this proposal.
    Comment: Several commenters supported our proposal to increase the 
requested medical records for eCQM validation from 75 percent to 100 
percent. A commenter emphasized its belief that the vast majority of 
hospitals already provide 100 percent of requested medical records for 
eCQM validation.
    Response: We thank the commenters for their support.
    Comment: A few commenters did not support our proposal. A commenter 
requested that the 75 percent threshold be maintained until after the 
end of the COVID-19 PHE. A commenter did not support this modification 
requesting the current requirement be maintained until scoring is 
satisfactory enough to score based on performance. Another commenter 
recommended focusing on accuracy and quality for eCQM validation.
    Response: We thank the commenters for their feedback. We 
acknowledge that hospitals continue to be affected by COVID-19 and we 
do not wish to further burden these hospitals, but respectfully 
disagree that we should delay this requirement. As we noted in the FY 
2023 IPPS/LTCH PPS proposed rule, ever since validation of eCQMs 
commenced with CY 2017 data (81 FR 57173 through 57181), all hospitals 
selected for eCQM validation have successfully submitted at least 75 
percent of eCQM medical records requested by the Clinical Data 
Abstraction Center (CDAC) (86 FR 28561). Additionally, 95 percent of 
hospitals selected for participation in eCQM validation for the FY 2020 
and FY 2021 payment determinations, which are the most recently 
available periods, voluntarily and successfully submitted 100 percent 
of requested records (86 FR 28561). Given the high rate of hospitals 
voluntarily submitting 100 percent of records, we believe updating the 
submission threshold to 100 percent will be feasible for hospitals (86 
FR 28561). We note that under our current policy, the accuracy of eCQM 
data (the extent to which data abstracted

[[Page 49310]]

for validation matches the data submitted in the QRDA I file) submitted 
for validation does not affect a hospital's validation score as 
described in the FY 2017 IPPS/LTCH PPS final rule (81 FR 57180 through 
57181). We will consider the commenters' feedback for future notice-
and-comment rulemaking as we continue to improve our current 
requirements.
    Comment: A few commenters shared concerns about vendor-related 
issues. A commenter requested that hospitals not be penalized for 
vendor delays. Another commenter requested that vendor systems be 
thoroughly vetted before these changes are implemented. A commenter 
noted concerns about the timeliness and value of validation results 
that they have received back from the validation vendor.
    Response: We thank the commenters for their feedback. We encourage 
hospitals to work closely with their vendors to ensure they are up-to-
date with previous and newly finalized requirements. We note that 
hospitals have had several years to meet the functional and operational 
demands of eCQM reporting and validation (81 FR 57173 through 57181). 
We wish to clarify that the accuracy of eCQM data submitted for 
validation currently does not affect a hospital's payment determination 
as described in the FY 2017 IPPS/LTCH PPS final rule (81 FR 57181).
    We did not receive any comments on our proposal to update the 
regulatory language at 42 CFR 412.140(d)(2)(ii) to reflect this change 
in our validation policy.
    After consideration of the public comments we received, we are 
finalizing our proposal as proposed.
12. Data Accuracy and Completeness Acknowledgement (DACA) Requirements
    We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR 
53554) for previously adopted details on DACA requirements. We did not 
propose any changes to this policy.
13. Public Display Requirements
a. Background
    Section 1886(b)(3)(B)(viii)(VII) of the Act requires the Secretary 
to report quality measures of process, structure, outcome, patients' 
perspectives on care, efficiency, and costs of care that relate to 
services furnished in inpatient settings in hospitals on the internet 
website of CMS. Section 1886(b)(3)(B)(viii)(VII) of the Act also 
requires that the Secretary establish procedures for making information 
regarding measures available to the public after ensuring that a 
hospital has the opportunity to review its data before they are made 
public. Our current policy is to report data from the Hospital IQR 
Program as soon as it is feasible on CMS websites such as the Compare 
tool hosted by HHS, currently available at: https://www.medicare.gov/care-compare, or its successor website, after a 30-day preview period 
(78 FR 50776 through 50778). We refer readers to the FY 2008 IPPS/LTCH 
PPS final rule (72 FR 47364), the FY 2011 IPPS/LTCH PPS final rule (75 
FR 50230), the FY 2012 IPPS/LTCH PPS final rule (76 FR 51650), the FY 
2013 IPPS/LTCH PPS final rule (77 FR 53554), the FY 2014 IPPS/LTCH PPS 
final rule (78 FR 50836), the FY 2015 IPPS/LTCH PPS final rule (79 FR 
50277), the FY 2016 IPPS/LTCH PPS final rule (80 FR 49712 through 
49713), the FY 2018 IPPS/LTCH PPS final rule (82 FR 38403 through 
38409), the FY 2019 IPPS/LTCH PPS final rule (83 FR 41538 through 
41539), and the FY 2021 IPPS/LTCH PPS final rule (85 FR 58953) for 
details on public display requirements. The Hospital IQR Program 
quality measures are typically reported on the Compare tool hosted by 
HHS, currently available at: https://www.medicare.gov/care-compare.
    In the FY 2023 IPPS/LTCH PPS proposed rule, we also proposed a 
publicly-reported hospital designation on a public-facing website to 
capture the quality and safety of maternity care. We refer readers to 
section IX.E.8. of the preamble of this final rule for more details.
b. Public Reporting of eCQM Data
    We direct readers to the FY 2021 IPPS/LTCH PPS final rule (85 FR 
58954 through 58959) where we finalized public reporting requirements 
of eCQM data reported by hospitals for the CY 2021 reporting period/FY 
2023 payment determination and for subsequent years. We note that this 
policy incrementally increases the eCQM data publicly reported to four 
quarters of data for the CY 2023 reporting period/FY 2025 payment 
determination and subsequent years. We did not propose any changes to 
these policies in the proposed rule.
c. Overall Hospital Star Ratings
    In the CY 2021 OPPS/ASC final rule with comment period and interim 
final rule with comment period (85 FR 86193 through 86236), we 
finalized a methodology to calculate the Overall Hospital Quality Star 
Rating (Overall Star Ratings). The Overall Star Ratings utilizes data 
collected on hospital inpatient and outpatient measures that are 
publicly reported on a CMS website, including data from the Hospital 
IQR Program. We refer readers to section XVI. of the CY 2021 OPPS/ASC 
final rule with comment period for details (85 FR 86193 through 86236). 
We did not propose any changes to these policies in the proposed rule. 
However, we refer readers to the CY 2023 OPPS/ASC proposed rule \1087\ 
where we proposed to amend the language of 42 CFR 412.190(c) to state 
that we would use publicly available measure results on Hospital 
Compare or its successor websites from a quarter within the prior 
twelve months (instead of the ``prior year'').
---------------------------------------------------------------------------

    \1087\ Federal Register unpublished display version available 
at: https://www.federalregister.gov/public-inspection/2022-15372/medicare-program-hospital-outpatient-prospective-payment-and-ambulatory-surgical-center-payment
---------------------------------------------------------------------------

14. Reconsideration and Appeal Procedures
    We refer readers to the FY 2012 IPPS/LTCH PPS final rule (76 FR 
51650 through 51651), the FY 2014 IPPS/LTCH PPS final rule (78 FR 
50836), and 42 CFR 412.140(e) for details on reconsideration and appeal 
procedures for the FY 2017 payment determination and subsequent years. 
We did not propose any changes to these policies in the proposed rule.
15. Hospital IQR Program Extraordinary Circumstances Exceptions (ECE) 
Policy
    We refer readers to the FY 2012 IPPS/LTCH PPS final rule (76 FR 
51651 through 51652), the FY 2014 IPPS/LTCH PPS final rule (78 FR 50836 
through 50837), the FY 2015 IPPS/LTCH PPS final rule (79 FR 50277), the 
FY 2016 IPPS/LTCH PPS final rule (80 FR 49713), the FY 2017 IPPS/LTCH 
PPS final rule (81 FR 57181 through 57182), the FY 2018 IPPS/LTCH PPS 
final rule (82 FR 38409 through 38411), and 42 CFR 412.140(c)(2) for 
details on the current Hospital IQR Program ECE policy. We also refer 
readers to the QualityNet website at: https://qualitynet.cms.gov for 
our current requirements for submission of a request for an exception. 
As finalized in the FY 2017 IPPS/LTCH PPS final rule, if a hospital is 
granted an Extraordinary Circumstances Exception with respect to eCQM 
reporting for the applicable eCQM reporting period, the hospital would 
be excluded from the eCQM validation sample due to its inability to 
supply data for validation (81 FR 57181). We did not propose any 
changes to these policies in the proposed rule.

[[Page 49311]]

F. Updates to the PPS-Exempt Cancer Hospital Quality Reporting (PCHQR) 
Program

1. Background
    The PPS-Exempt Cancer Hospital Quality Reporting (PCHQR) Program is 
authorized by section 1866(k) of the Act and applies to hospitals 
described in section 1886(d)(1)(B)(v) (referred to as ``PPS-Exempt 
Cancer Hospitals'' or ``PCHs''). For additional background information, 
including previously finalized measures and other policies for the 
PCHQR Program, we refer readers to all of the following final rules:

 The FY 2013 IPPS/LTCH PPS final rule (77 FR 53555 through 
53567).
 The FY 2015 IPPS/LTCH PPS final rule (79 FR 50277 through 
50286).
 The FY 2016 IPPS/LTCH PPS final rule (80 FR 49713 through 
49723).
 The FY 2017 IPPS/LTCH PPS final rule (81 FR 57182 through 
57193).
 The FY 2018 IPPS/LTCH PPS final rule (82 FR 38411 through 
38425).
 The FY 2019 IPPS/LTCH PPS final rule (83 FR 41609 through 
41624).
 The CY 2019 OPPS/ASC final rule with comment period (83 FR 
59149 through 59154).
 The FY 2020 IPPS/LTCH PPS final rule (84 FR 42509 through 
42524).
 The FY 2021 IPPS/LTCH PPS final rule (85 FR 58959 through 
58966).
 The FY 2022 IPPS/LTCH PPS final rule (86 FR 45426 through 
45437).

    We also refer readers to 42 CFR 412.23(f) and 412.124 for the PCHQR 
Program regulations.
2. Measure Retention and Removal Factors for the PCHQR Program
a. Current Measure Retention and Removal Factors
    For a detailed discussion regarding our retention and removal 
factors, we refer readers to the FY 2017 IPPS/LTCH PPS final rule (81 
FR 57182 through 57183), where we adopted policies for measure 
retention and removal, and the FY 2019 IPPS/LTCH PPS final rule (83 FR 
41609 through 41611), where we updated our measure removal factors. We 
did not propose any changes to our measure retention policy. We 
describe our proposal to update our measure removal policy in the 
following section.
b. Adoption of a Patient Safety Exception to the Measure Removal Policy
    To further align with the measure removal policies adopted in other 
quality programs such as the Hospital IQR Program (74 FR 43864), 
Hospital VBP Program (83 FR 41446), and HAC Reduction Program (84 FR 
42404 to 42406), we proposed that if we believe continued use of a 
measure in the PCHQR Program raises specific patient safety concerns, 
we may promptly remove the measure from the program without rulemaking 
and notify hospitals and the public of the removal of the measure, 
along with the reasons for its removal through routine communication 
channels to hospitals, vendors, and QIOs, including, but not limited 
to, issuing memos, emails, and notices on the QualityNet website. We 
would then provide notice of the removal in the Federal Register. In 
circumstances where we do not believe that continued use of a measure 
raises specific patient safety concerns, we would use the regular 
rulemaking process to remove a measure. We stated that the proposed 
policy mirrors that of the Hospital IQR Program, Hospital VBP Program, 
and HAC Reduction Program, and we continue to believe that a mechanism 
to immediately remove a quality measure that is causing specific and 
unintended patient harm aligns with our patient-centered focus.
    We further proposed to add this patient safety exception to our 
regulations by revising 42 CFR 412.24(d)(3) to add a new paragraph 
(d)(3)(iii). We invited public comment on these proposals.
    Comment: Commenters supported the proposal to adopt a patient 
safety exception to the measure removal policy and revise 42 CFR 
412.24(d)(3) to add a new paragraph (d)(3)(iii).
    Response: We appreciate the commenters' support.
    After consideration of the public comments we received, we are 
finalizing our proposal to adopt a patient safety exception to the 
measure removal policy and revise 42 CFR 412.24(d)(3) to add a new 
paragraph (d)(3)(iii) beginning in FY 2023.
3. Potential Adoption of Two National Healthcare Safety Network (NHSN) 
Measures--Request for Information
    In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28563), we sought 
comment on a potential future proposal to adopt the NHSN Healthcare-
associated Clostridioides difficile Infection Outcome measure and NHSN 
Hospital-Onset Bacteremia & Fungemia Outcome measure into the PCHQR 
Program. We refer readers to section IX.E.9.a. of the preamble of the 
proposed rule, where we requested information on potentially adopting 
them for the Hospital IQR Program, and we noted that we are also 
considering proposing them for the HAC Reduction Program. With respect 
to the PCHQR Program, we stated that we were considering proposing 
these measures because cancer patients are often immunosuppressed and 
therefore more vulnerable to healthcare-associated infections (HAIs). 
We stated that we believed these measures will drive an increase in 
prevention practices, which may lead to a reduction in the number of 
HAI cases, morbidity, and mortality. We refer readers to section 
IX.E.9.a. of the preamble of this final rule for a discussion of the 
comments received regarding this cross-program RFI.
4. Summary of PCHQR Program Measures for the FY 2024 Program Year and 
Subsequent Years
    Table IX.F.-01 summarizes the PCHQR Program measure set for the FY 
2024 program year and subsequent years. We did not propose any changes 
to the PCHQR Program measure set.

[[Page 49312]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.179

5. Maintenance of Technical Specifications for Quality Measures
    We maintain and periodically update technical specifications for 
the PCHQR Program measures. The specifications may be found on the 
QualityNet website at https://qualitynet.cms.gov/pch. We also refer 
readers to the FY 2015 IPPS/LTCH PPS final rule (79 FR 50281), where we 
adopted a policy to use a subregulatory process to make nonsubstantive 
updates to measures used for the PCHQR Program. We did not propose any 
changes to our processes for maintaining technical specifications for 
PCHQR Program measures.
6. Public Display Requirements
a. Background
    Under section 1866(k)(4) of the Act, we are required to establish 
procedures for making the data submitted under the PCHQR Program 
available to the public. Such procedures must ensure that a PCH has the 
opportunity to review its data before they are made public. We are 
specifically required to report quality measures of process, structure, 
outcome, patients' perspective on care, efficiency, and costs of care 
that relate to services furnished by PCHs on the CMS website.
    In the FY 2017 IPPS/LTCH PPS final rule (81 FR 57191 through 
57192), we finalized that although we would continue to use rulemaking 
to establish what year we first publicly report data on each measure, 
we would publish the data as soon as feasible during that year. We also 
stated that our intent is to make the data available on at least a 
yearly basis, and that the time period for PCHs to review their data 
before the data are made public would be approximately 30 days in 
length. We announce the exact data review and public reporting 
timeframes on a CMS website and our applicable Listservs. Currently, 
the PCHQR measures' performance data are made publicly available on the 
Provider Data Catalog available at https://data.cms.gov/provider-data/.
    We recognize the importance of being transparent and keeping the 
public abreast of any changes that arise with the PCHQR Program measure 
set. As such, in this final rule, we are finalizing our proposals to 
begin public display of the four end-of-life measures with modification 
and the 30-Day Unplanned Readmissions for Cancer Patients measure.
b. Public Display of the End-of-Life (EOL) Measures
    We proposed to begin public display of the EOL-Chemo, EOL-Hospice, 
EOL-ICU, and EOL-3DH measures (collectively, the ``EOL measures'') 
beginning with FY 2024 program year data. We adopted these measures for 
the PCHQR measure set beginning with FY 2020 program year data (82 FR 
38414 through 38420). In the FY 2020 IPPS/LTCH PPS final rule (84 FR 
42523

[[Page 49313]]

through 42524), we finalized that we would confidentially report PCH 
performance on these measures to individual PCHs, and we indicated that 
we would propose to publicly display PCH performance on the measures 
after this initial confidential reporting period. We stated that we 
anticipated providing confidential reports on the data collected on the 
measures for the FY 2022 and FY 2023 program years, which correspond to 
data collected from July 1, 2019, to June 30, 2020 and July 1, 2020, to 
June 30, 2021, respectively, within calendar year 2022. We also stated 
that under our current policy, the measures are calculated on a yearly 
basis based on data collected from July 1 of the year 3 years prior to 
the program year to June 30 of the year 2 years prior to the program 
year. Therefore, we proposed to begin public reporting of these 
measures beginning with the FY 2024 program year data, which 
corresponds to data collected from July 1, 2021 through June 30, 2022. 
We stated that we would make these data publicly available following a 
30-day period in which PCHs would have an opportunity to review the 
data. Public display would occur during the July 2023 refresh cycle or 
as soon as feasible thereafter. We further stated that we would 
announce the exact timeframe on a CMS website and our applicable 
listservs.
    We invited public comment on the proposal to begin public display 
of the four EOL measures beginning with the FY 2024 program year data.
    Comment: A few commenters supported the proposal to begin public 
display of the four EOL measures, stating that this public display will 
provide valuable information about hospital performance to patients. 
Another commenter specifically supported public display of the EOL-
Chemo and EOL-ICU measures, stating that the data from these measures 
would complement the ADCC Serious Illness project.
    Response: We thank the commenters for their support of publicly 
displaying the four EOL measures. We also thank the commenter who 
supported public display of the EOL-Chemo and EOL-ICU measures.
    Comment: Several commenters requested that CMS delay public 
reporting of the EOL measures until hospitals can review their FY 2022 
confidential reports, the release of which was delayed by one year.
    Response: We thank the commenters for their feedback. The FY 2022 
confidential feedback reports were made available to PCHs in June 2022. 
We anticipate the FY 2023 confidential reports will be made available 
to PCHs in August 2022 or as soon as feasible thereafter. We agree that 
the delay in releasing the FY 2022 and FY 2023 confidential feedback 
reports necessitates a delay in public reporting in order to provide 
PCHs with sufficient time to gain familiarity with the measure 
calculation and results. We believe a one-year delay, which is the 
minimum delay possible due to measure reporting timelines, will be 
sufficient to provide PCHs with additional time while balancing the 
importance of transparency of the EOL measure data.
    Comment: Another commenter expressed concern about the lack of 
context for publicly displayed measure data such as individual 
patients' preferences and needs, which may lead to misrepresentation of 
the quality of cancer care.
    Response: We thank the commenter for sharing their concern. The 
measure information will initially be available only via the Provider 
Data Catalog (PDC), and we are in the process of making this data 
available via Care Compare for public display. We would like to 
reiterate that PCHs will have a 30-day review period to confirm 
accuracy of the measure data before public display, and measures rates 
will be displayed with any appropriate context for ease of 
understanding the results.
    After consideration of the public comments we received, we are 
finalizing our proposal to begin public reporting of the four EOL 
measures, with modification. Specifically, we are finalizing to begin 
public reporting beginning with FY 2025 program year data, which 
corresponds to data collected from July 1, 2022, through June 30, 2023, 
to provide hospitals with enough time to review their confidential 
reports. Public display will occur during the July 2024 refresh cycle 
or as soon as feasible thereafter. We will announce the exact timeframe 
on a CMS website and PCHQR Program listservs.
c. Public Display of the 30-Day Unplanned Readmissions for Cancer 
Patients Measure Beginning With the FY 2024 Program Year Data
    We proposed to begin public display of the 30-Day Unplanned 
Readmissions for Cancer Patients measure beginning with FY 2024 program 
year data. We adopted this measure for the PCHQR measure set beginning 
with FY 2021 program year data (83 FR 41613 through 41616). In the FY 
2020 IPPS/LTCH PPS final rule (84 FR 42523 through 42524), we finalized 
that we would confidentially report this measure to individual PCHs, 
and we indicated that we would propose public display after this 
initial confidential reporting period. We provided confidential reports 
on the data collected on this measure for the FY 2022 program year in 
July 2021. In addition, we stated that we anticipated confidentially 
reporting data collected on the measure for the FY 2023 program year, 
which corresponds to data collected from October 1, 2020 to September 
30, 2021, in July 2022.
    Under our current policy, the measure is calculated on a yearly 
basis based on data collected from October 1 of the year 3 years prior 
to the program year to September 30 of the year 2 years prior to the 
program year. We proposed to begin public reporting of this measure 
beginning with the FY 2024 program year data, which corresponds to data 
collected from October 1, 2021 through September 30, 2022. We stated 
that we would make these data publicly available following a 30-day 
period in which PCHs would have an opportunity to review the data. 
Public display would occur during the October 2023 refresh cycle or as 
soon as feasible thereafter. We stated that we would announce the exact 
timeframe on a CMS website and our applicable listservs.
    We invited public comment on the proposal to begin public display 
of the 30-Day Unplanned Readmissions for Cancer Patients measure 
beginning with the FY 2024 program year data.
    Comment: Several commenters supported the proposal to begin public 
display of the 30-Day Unplanned Readmissions for Cancer Patients 
measure beginning with the FY 2024 program year data. A few commenters 
noted that that the FY 2021 confidential reports were reflective of 
measure specifications. A few commenters applauded CMS' early release 
of the confidential reports, allowing for proactive review prior to 
reporting periods. A commenter stated their belief that the measure 
will provide valuable information about hospital performance to 
patients.
    Response: We thank the commenters for their support.
    After consideration of the public comments we received, we are 
finalizing our proposal to begin public display of the 30-Day Unplanned 
Readmissions for Cancer Patients measure beginning with the FY 2024 
program year data.
d. Summary of Previously Finalized and Newly Finalized Public Display 
Requirements for the PCHQR Program
    Our previously finalized and newly finalized public display 
requirements for the PCHQR Program measures are shown in the following 
Table IX.F.-02:

[[Page 49314]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.180

7. Form, Manner, and Timing of Data Submissions
    We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR 
53563 through 53567) for our previously finalized procedural 
requirements for the PCHQR Program. Data submission requirements and 
deadlines for the PCHQR Program are posted on the QualityNet website. 
We did not propose any updates to our previously finalized data 
submission requirements and deadlines.
8. Extraordinary Circumstances Exceptions (ECE) Policy Under the PCHQR 
Program
    We refer readers to the FY 2019 IPPS/LTCH PPS final rule (83 FR 
41623 through 41624), for a discussion of the Extraordinary 
Circumstances Exceptions (ECE) policy under the PCHQR Program. We did 
not propose any changes to this policy.
G. Long-Term Care Hospital Quality Reporting Program (LTCH QRP)
1. Background and Statutory Authority
    The Long-Term Care Hospital Quality Reporting Program (LTCH QRP) is 
authorized by section 1886(m)(5) of the Act, and it applies to all 
hospitals certified by Medicare as Long-Term Care Hospitals (LTCHs). 
Section 1886(m)(5)(C) of the Act requires LTCHs to submit to the 
Secretary quality measure data specified under section 1886(m)(5)(D) in 
a form and manner, and at a time, specified by the Secretary. In 
addition, section 1886(m)(5)(F) of the Act requires LTCHs to submit 
data on quality measures under section 1899B(c)(1) of the Act, resource 
use or other measures under section 1899B(d)(1) of the Act, and 
standardized patient assessment data required under section 1899B(b)(1) 
of the Act. LTCHs must submit the data required under section 
1886(m)(5)(F) of the Act in the form and manner, and at the time, 
specified by the Secretary. Under the LTCH QRP, the Secretary must 
reduce by 2 percentage points the annual update to the LTCH PPS 
standard Federal rate for discharges for an LTCH during a fiscal year 
if the LTCH has not complied with the LTCH QRP requirements specified 
for that fiscal year. For more information on the background for the 
LTCH QRP, we refer readers to the FY 2012 IPPS/LTCH PPS final rule (76 
FR 51743 through 51744), the FY 2013 IPPS/LTCH PPS final rule (77 FR 
53614), the FY 2014 IPPS/LTCH PPS final rule (78 FR 50853), the FY 2015 
IPPS/LTCH PPS final rule (79 FR 50286), the FY 2016 IPPS/LTCH PPS final 
rule (80 FR 49723 through 49725), the FY 2017 IPPS/LTCH PPS final rule 
(81 FR 57193), the FY 2018 IPPS/LTCH PPS final rule (82 FR 38425 
through 38426), the FY 2019 IPPS/LTCH PPS

[[Page 49315]]

final rule (83 FR 41624 through 41634), the FY 2020 IPPS/LTCH PPS final 
rule (84 FR 42524 through 42591), and the FY 2022 IPPS/LTCH PPS final 
rule (86 FR 45438 through 45446). For more information on the 
requirements under the LTCH QRP, we refer readers to 42 CFR 412.560.
2. General Considerations Used for the Selection of Quality Measures 
for the LTCH QRP
    For a detailed discussion of the considerations we historically use 
for the selection of LTCH QRP quality, resource use, and other 
measures, we refer readers to the FY 2016 IPPS/LTCH PPS final rule (80 
FR 49728).
3. Quality Measures Currently Adopted for the FY 2023 LTCH QRP
    The LTCH QRP currently has 18 measures for the FY 2023 LTCH QRP, 
which are set out in the following Table IX.G.-01. For a discussion of 
the factors used to evaluate whether a measure should be removed from 
the LTCH QRP, we refer readers to the FY 2019 IPPS/LTCH PPS final rule 
(83 FR 41624 through 41634) and to the regulations at 42 CFR 
412.560(b)(3).
[GRAPHIC] [TIFF OMITTED] TR10AU22.181


[[Page 49316]]


    There were no proposals in the proposed rule for new measures for 
the LTCH QRP.
4. LTCH QRP Quality Measure Concepts Under Consideration for Future 
Years: Request for Information (RFI) Included in the FY 2023 IPPS/LTCH 
PPS Proposed Rule
    In the FY 2023 IPPS/LTCH PPS proposed rule, we sought input on the 
importance, relevance, and applicability of the concepts under 
consideration listed in Table IX.G.-02 for future years in the LTCH 
QRP. More specifically, we sought input on a cross-setting functional 
measure that would incorporate the domains of self-care and mobility. 
Our measure development contractor for the cross-setting functional 
outcome measure convened a Technical Expert Panel (TEP) on June 15 and 
June 16, 2021 to obtain expert input on the development of a functional 
outcome measure for PAC. During this meeting, the possibility of 
creating one measure to capture both self-care and mobility was 
discussed. We also sought input on measures of health equity, such as 
structural measures that assess an organization's leadership in 
advancing equity goals or assess progress towards achieving equity 
priorities. Finally, we sought input on the value of a COVID-19 
Vaccination Coverage measure that would assess whether LTCH patients 
were up to date on their COVID-19 vaccine.
[GRAPHIC] [TIFF OMITTED] TR10AU22.182

    Comment: Commenters were generally supportive of a cross-setting 
functional outcome measure, although some commenters expressed concern 
over the potential burden of collecting additional information. Some 
commenters emphasized that the measure should provide meaningful 
information to patients, caregivers, discharge planners, providers, and 
payers, and noted that LTCH patients often have different levels of 
acuity and treatment needs so a future measure must be able to 
differentiate LTCHs from one another. Two commenters stated that since 
LTCH patients have different levels of acuity and treatment needs, it 
may make comparisons to other ``PAC'' settings not appropriate, even 
when risk adjustment is used. These commenters urged CMS to consider 
measures that incorporate improvement in function, but also recognize 
that some patients may not demonstrate improvement due to their medical 
condition(s). A commenter stated they preferred separate quality 
measures for self-care and mobility, but would support the initial use 
of a composite measure reflecting both self-care and mobility function. 
Another commenter opposed the inclusion of a measure that was based on 
provider-reported assessment data.
    We received mixed comments regarding a health equity measure in the 
LTCH QRP. Two commenters were concerned with how accurate a health 
equity measure could be for LTCHs given their small sample sizes, and 
whether LTCHs would be able to meaningfully improve a measure of health 
equity. Other commenters were strongly supportive of including health 
equity measures in the LTCH QRP in a future year.
    Commenters stated they understood why CMS was considering a COVID-
19 Vaccination Coverage among Patients measure, but noted CMS should 
postpone considering this measure since the definition of ``fully 
vaccinated'' is evolving.
    We also received comments suggesting CMS consider other measure 
concepts for the LTCH QRP, including malnutrition and patient-reported 
outcomes. A commenter urged CMS to consider a measure of malnutrition 
screening since malnutrition is a risk factor for several clinical 
events, including falls and delayed healing. Another commenter 
suggested measures of patient experience, patient and workforce safety 
and reliability, clinical quality, and caregiver engagement that are 
evidence-based, targeted, and meaningful to patients and caregivers.
    Response: As discussed in the proposed rule, we are not responding 
to specific comments submitted in response to this RFI in this final 
rule, but we intend to use this input to inform our future measure 
development efforts.
5. Inclusion of the National Healthcare Safety Network (NHSN) 
Healthcare-Associated Clostridioides difficile Infection Outcome 
Measure in the LTCH QRP--Request for Information (RFI) Included in the 
FY 2023 IPPS/LTCH PPS Proposed Rule
a. Solicitation of Public Comment
    In the FY 2023 IPPS/LTCH PPS proposed rule, we requested 
stakeholder input on the potential electronic submission of quality 
data from LTCHs via their electronic health records (EHRs) under the 
LTCH QRP. We specifically sought public comment on the future inclusion 
of the NHSN Healthcare-Associated Clostridioides difficile Infection 
Outcome measure (HA-CDI) (MUC2021-098) as a digital quality measure in 
the LTCH QRP.
    Specifically, we sought public comment on the following:
     Would you support utilizing LTCH EHRs as the mechanism of 
data collection and submission for LTCH QRP measures?
     Would your EHR support exposing data via HL7 Fast 
Healthcare Interoperability Resources (FHIR) to a locally installed 
Measure Calculation Tool (MCT)? For LTCHs using certified health IT 
systems, how can existing certification criteria under the Office of 
the National Coordinator (ONC) Health Information Technology (IT) 
Certification Program support reporting of these data? What updates, if 
any, to the Certification Program would be needed to better support 
capture and submission of these data?
     Is a transition period between the current method of data 
submission and

[[Page 49317]]

an electronic submission method necessary? If so, how long of a 
transition would be necessary, and what specific factors are relevant 
in determining the length of any transition?
     Would vendors, including those that service LTCHs, be 
interested in or willing to participate in pilots or voluntary 
electronic submission of quality data?
     Do LTCHs anticipate challenges, other than the adoption of 
EHR, to adopting the NHSN HA-CDI measure, and if so, what are potential 
solutions for those challenges?
    We received several comments on this RFI, which are summarized in 
this section of this document:
    Comment: Commenters were mixed in their support of utilizing LTCH 
EHRs as the mechanism for data collection and submission for LTCH QRP 
measures. While all commenters supported the concept of reducing 
provider burden through using fully digital measures, commenters did 
note several barriers. A commenter noted that the transition would take 
time and staffing hours away from other clinical initiatives. Most 
commenters raised concerns about the cost associated with LTCHs t 
adopting EHR systems that are equipped to collect and exchange digital 
quality measure (dQM) data. They stated that EHR adoption has been 
slower and less uniform than it was in acute care hospitals, due to the 
lack of incentive payments available to LTCHs. They urged CMS to 
provide incentive payments to LTCHs as they did for acute care 
hospitals through the Health Information Technology for Economic and 
Clinical Health (HITECH) Act prior to requiring LTCHs' transition to 
dQMs.
    A commenter stated that their EHR would support exposing data via 
HL7 FHIR to a locally installed MCT. Another commenter stated they had 
concerns about the definition of treatment, as well as potential gaming 
of the measure that could lead to the untended consequences of overuse 
of antimicrobials or the undertreatment of patients with CDI. This 
commenter also suggested CMS to work with CMS to determine whether risk 
adjustment based on hospital characteristics is needed. Finally, they 
cautioned that electronic reporting is evolving and they requested CMS 
work with the Office of the National Coordinator for Health Information 
Technology (ONC) and other EHR vendors to fully integrate electronic 
reporting options before implementation.
    Commenters universally agreed that a transition period would be 
necessary to set up processes capable of electronic submission of data. 
They stressed that LTCHs would need significant lead time to ensure 
they could be compliant with new digital reporting requirements, and 
estimated it would take a minimum of 2 years to transition to digital 
reporting. Another commenter stated that a switch to dQMs would involve 
a number of different workflows, and that sufficient testing would be 
important since LTCHs could be penalized 2% for an entire year if they 
were found non-compliant.
    A commenter urged CMS to allow LTCH provider organizations, in 
addition to vendors, to participate in any pilots or testing of dQMs 
before implementation.
    Response: We will consider all input as we develop future 
regulatory proposals. Any updates to specific program requirements 
related to quality measurement and reporting provisions would be 
addressed through separate and future notice-and-comment rulemaking, as 
necessary.
6. Overarching Principles for Measuring Equity and Healthcare Quality 
Disparities Across CMS
a. Solicitation of Public Comment
    The goal of this request for information was to describe some key 
principles and approaches that we will consider when advancing the use 
of quality measure development and stratification to address healthcare 
disparities and advance health equity across our programs.
    We invited general comments on the principles and approaches 
described previously in this section of the rule, as well as additional 
thoughts about disparity measurement guidelines suitable for 
overarching consideration across CMS's QRP programs. Specifically, we 
invited comment on the following:
     Identification of Goals and Approaches for Measuring 
Healthcare Disparities and Using Measure Stratification Across CMS 
Quality Reporting Programs
    ++ The use of the within- and between-hospital disparity methods in 
LTCHs to present stratified measure results.
    ++ The use of decomposition approaches to explain possible causes 
of measure performance disparities.
    ++ Alternative methods to identify disparities and the drivers of 
disparities.
     Guiding Principles for Selecting and Prioritizing Measures 
for Disparity Reporting
    ++ Principles to consider for prioritization of health equity 
measures and measures for disparity reporting, including prioritizing 
stratification for validated clinical quality measures, those measures 
with established disparities in care, measures that have adequate 
sample size and representation among healthcare providers and outcomes, 
and measures of appropriate access and care.
     Principles for Social Risk Factor (SRF) and Demographic 
Data Selection and Use
    ++ Principles to be considered for the selection of SRFs and 
demographic data for use in collecting disparity data including the 
importance of expanding variables used in measure stratification to 
consider a wide range of SRFs, demographic variables, and other markers 
of historic disadvantage. In the absence of patient-reported data we 
will consider use of administrative data, area-based indicators, and 
imputed variables as appropriate.
     Identification of Meaningful Performance Differences
    ++ Ways that meaningful difference in disparity results should be 
considered.
     Guiding Principles for Reporting Disparity Measures
    ++ Guiding principles for the use and application of the results of 
disparity measurement.
     Measures Related to Health Equity
    ++ The usefulness of a Health Equity Summary Score (HESS) for 
LTCHs, both in terms of provider actionability to improve health 
equity, and in terms of whether this information would support Care 
Compare website users in making informed healthcare decisions.
    ++ The potential for a structural measure assessing an LTCH's 
commitment to health equity, the specific domains that should be 
captured, and options for reporting these data in a manner that would 
minimize burden.
    ++ Options to collect facility-level information that could be used 
to support the calculation of a structural measure of health equity.
    ++ Other options for measures that address health equity.
    We received several comments on the RFI for Overarching Principles 
for Measuring Equity and Healthcare Quality Disparities Across CMS 
Quality Programs. While we will not be responding to specific comments 
submitted in response to this RFI, the following is a summary of some 
comments received:
    Comment: Many commenters provided feedback on the use of the 
within-provider and between provider disparity methods to present 
stratified measure results. Overall, comments were generally supportive 
of implementing both methods in order to provide a more complete 
picture of the

[[Page 49318]]

quality of care provided to beneficiaries with SRFs.
    In terms of specific feedback related to the implementation of 
these stratification approaches, a few commenters stated CMS should 
prioritize expansion of the within-provider method over the between-
provider method due to the fact that the latter method might provide an 
incomplete picture of disparity and would not inform a LTCH's an 
understanding of its own performance. Other commenters suggested CMS 
consider using peer groups for between-provider comparisons, such as 
peer LTCHs identified based patient demographic profile, geographic 
location, or bed size. A commenter noted concern that within-provider 
methods may place excessive responsibility on providers to mitigate the 
disparities without providing the resources to take action. Another 
commenter stated the feedback would be more actionable and useful if 
the results included information beyond what hospitals already collect. 
Finally, a commenter recommended feedback methods should be carefully 
considered for each type of measure, and specifically pointed out that 
patient experience measures may not be appropriate to compare between 
subgroups since it could lend itself to misinterpretation and labeling 
of certain subgroups of patients.
    Several commenters responded to the disparity decomposition 
approach presented in the proposed rule. A commenter noted the 
decomposition approach described could be a promising method to 
identify specific drivers of performance disparities, which would 
increase the actionability of stratified measure information while 
adding no additional burden to providers. Other commenters supported 
the method, but a commenter did caution that LTCHs would be limited in 
their ability to address patients' needs while under their care. A few 
commenters opposed the use of decomposition techniques, citing their 
concern that if statistical methods are poorly chosen, some LTCHs may 
be labeled discriminatory unintentionally, causing harm to 
beneficiaries, providers and the Medicare program.
    Commenters were overwhelmingly supportive of prioritizing existing 
quality measures for disparity reporting, and most commenters were also 
supportive of prioritizing measures with identified disparities in 
treatment or outcomes, or conditions that have highly disproportionate 
prevalence in certain populations. Many commenters stated CMS should 
focus on: (1) outcome measures over process measures; (2) use existing 
collected patient data and prevent additional reporting burdens on 
providers; and (3) have a meaningful and quantifiable impact on overall 
patient health and system cost. For those reasons, these commenters 
suggested measures such as hospital readmissions, mortality associated 
with certain health conditions, and potentially avoidable events. 
Support for prioritizing measures with adequate sample sizes and 
measures that seek to determine patient access to care and the 
appropriate use of care were suggested by many commenters as well.
    Commenter also suggested additional guiding principles. A commenter 
recommended the measures should have essential characteristics such as 
being data-driven, actionable, feasible, have utility and be 
constructed such that providers have prompt feedback. Another commenter 
suggested CMS should focus on the areas of clinical quality, clinical 
safety and patient experience, while still another stressed alignment 
with other programs and agencies, where possible and appropriate.
    We received a number of other comments on the guiding principles 
for selecting and prioritizing measures for disparity reporting. A 
commenter suggested the only criteria that should be used is whether 
the measure highlights disparities in care. Another commenter requested 
CMS clarify how it defines ``industry standards for measure reliability 
and validity.'' Finally, another commenter cautioned CMS against using 
this information to single out healthcare providers and take punitive 
action against them.
    A number of commenters provider feedback on considerations for the 
selection of SRFs and demographic data for use in collecting disparity 
data. A majority of commenters supported using race and ethnicity, 
although a commenter recommended using any SRFs other than dual 
eligibility, race and ethnicity. Several commenters suggested using 
disability status, and two of these commenters also suggested using 
primary language. Other data points were suggested, including sexual 
orientation, gender identity, age, and health literacy. Finally, a 
commenter recommended CMS use a standard definition of the term 
``disparity'' that can be used as a measurable benchmark across 
programs.
    The feedback received on methods for determining meaningful 
performance differences in disparity results was mixed. First, we 
summarize the comments regarding the four possible reporting approaches 
discussed in section IX.E.6.1.4 the proposed rule, and then summarize 
comments recommending other approaches.
    While several commenters were generally supportive of benchmarking, 
one provider stated the data was too limited at the current time to 
apply benchmarks and another commenter noted it could mask local or 
regional differences in patient populations and thus inadvertently 
penalize providers. A commenter provided feedback specific to using 
statistical differences to identifying meaningful performance 
differences, and the commenter recommended that if this approach were 
used the measure, along with an estimate of its variability, such as a 
confidence interval, be displayed with it to aid in its interpretation. 
Several commenters did not support ranked orderings and percentiles and 
cautioned they could lead to significant unintended consequences, and 
two of these commenters noted that they do not necessarily translate to 
meaningful clinical differences. Finally we received two comments 
supporting the use of defined thresholds, such as fixed intervals of 
results of disparity reporting, but several commenters did not support 
this method. The most notable reason given was their concern this 
method created an artificial cutoff where small performance differences 
are either acceptable or unacceptable, and it could result in 
inappropriately characterizing some LTCHs as practicing discrimination. 
We also received one comment recommending CMS use a combination of peer 
group benchmarking and statistical significance.
    Commenters also recommended other approaches. A commenter 
recommended CMS conduct analyses to compare the results of different 
methods and publish the results of these analyses for stakeholder 
review and public comment. Other commenters urged CMS not to apply a 
one-size-fits-all approach, and suggested CMS may need to tailor the 
approaches to the individual patient populations and quality program. A 
few commenters noted that before any analyses are completed, CMS will 
need to define a statistically acceptable minimum threshold for 
determining a disparity exists as well as a high reliability standard 
for determining the minimum number of observations required for a 
provider's performance to be stratified and reported.
    Several commenters responded to CMS' request for information about 
measures CMS could develop to assess and encourage health equity, 
including

[[Page 49319]]

comments regarding the usefulness and actionability of HESS and the 
potential for a structural measure to assess SNFs' commitment to health 
equity. We first summarize the comments regarding the HESS, then 
summarize comments related to a structural measure to assess commitment 
to equity.
    Several commenters specifically addressed the HESS. A commenter 
simply encouraged CMS to clarify that the HESS would assess individual 
SNFs as a whole, as opposed to the individual clinicians within each 
SNF. The two remaining commenters either supported or appreciated the 
HESS score in concept, but raised several concerns pertaining to 
technical barriers, ambiguity in the methodology, and usability of the 
measure. In terms of technical concerns, a commenter noted that the 
availability of a standardized set of demographic data elements must be 
available for each patient, and stated that demographic data elements 
are not yet standardized across healthcare setting and organizations. 
Regarding methodological concerns, a commenter questioned how one could 
combine within-facility disparities and disparities across facilities 
into a single summary score in a manner that would accurately reflect 
both the individual and potentially independent factors that may result 
in these different types of disparities. Other commenters raised 
similar concerns about the usability the HESS, primarily stemming from 
the extent to which disparities across multiple measures and SRFs are 
aggregated into a single score. Specifically, commenters noted that one 
SRF included in the HESS could mask the effects of other SRFs, which 
could potentially lead to misinterpretation of the overall score. 
Another commenter stated the measure was vague and therefore would not 
be actionable by their members or meaningful to the public.
    Several commenters addressed the potential for a structural 
measures to assess health equity. A commenter stated that a structural 
measure would have a low level of burden, while signaling to the LTCH 
community the importance of focusing improvement efforts on health 
equity and prompting the healthcare organization to consider their 
ongoing or needed efforts to address each domain. Another commenter 
noted that the development of a structural measure to assess engagement 
and commitment of leadership toward advancing health equity should be 
included as one of several guiding principles to address health 
disparities and achieve health equity. Another commenter cautioned 
against the development of structural measures, suggesting that such 
measures would only demonstrate whether an organization is ``good at 
checking the box'' for the purpose of meeting the requirements of a 
measure.
    Response: We appreciate all of the comments and interest in this 
important topic. Public input is very valuable in the continuing 
development of CMS's health equity quality measurement efforts and 
broader commitment to health equity, a key pillar of our strategic 
vision as well as a core agency function. Thus, we will continue to 
take all concerns, comments, and suggestions into account for future 
development and expansion of policies to advance health equity across 
the LTCH QRP, including by supporting LTCHs in their efforts to ensure 
equity for all of their patients, and to identify opportunities for 
improvements in health outcomes. Any updates to specific program 
requirements related to quality measurement and reporting provisions 
would be addressed through separate and future notice-and-comment 
rulemaking, as necessary.
7. Form, Manner, and Timing of Data Submission Under the LTCH QRP
    We refer readers to the regulatory text at 42 CFR 412.560(b) for 
information regarding the current policies for reporting LTCH QRP data.
    For more details about the required reporting periods of measures 
or standardized patient assessment data during the first and subsequent 
years upon adoption, please refer to the FY 2020 IPPS/LTCH PPS final 
rule (84 FR 24588 through 24590).
    We did not propose any new policies regarding the form, manner, and 
timing of data submission under the LTCH QRP.
8. Policies Regarding Public Display of Measure Data for the LTCH QRP
    We did not propose any new policies regarding the public display of 
LTCH QRP measure data.

H. Changes to the Medicare Promoting Interoperability Program

1. Statutory Authority for the Medicare Promoting Interoperability 
Program for Eligible Hospitals and Critical Access Hospitals (CAHs)
    The Health Information Technology for Economic and Clinical Health 
Act (HITECH Act) (Title IV of Division B of the American Recovery and 
Reinvestment Act of 2009 (ARRA), together with Title XIII of Division A 
of the ARRA) authorized incentive payments under Medicare and Medicaid, 
as well as downward payment adjustments under Medicare, for the 
adoption and meaningful use of certified electronic health record 
technology (CEHRT). Incentive payments under Medicare were available to 
eligible hospitals and CAHs for certain payment years (as authorized 
under sections 1886(n) and 1814(l) of the Act, respectively) if they 
successfully demonstrated meaningful use of CEHRT, which included 
reporting on clinical quality measures using CEHRT. In accordance with 
the timeframe set forth in the statute, these incentive payments under 
Medicare are no longer available. Sections 1886(b)(3)(B)(ix) and 
1814(l)(4) of the Act authorize downward payment adjustments under 
Medicare, beginning with Federal fiscal year (FY) 2015 (and beginning 
with FY 2022 for subsection (d) Puerto Rico hospitals), for eligible 
hospitals and CAHs that do not successfully demonstrate meaningful use 
of CEHRT for certain associated electronic health record (EHR) 
reporting periods.
2. EHR Reporting Period
    Under the definition of ``EHR reporting period for a payment 
adjustment year'' at 42 CFR 495.4, for eligible hospitals and CAHs that 
are new or returning participants in the Medicare Promoting 
Interoperability Program, the EHR reporting period in calendar year 
(CY) 2023 is a minimum of any continuous 90-day period within CY 2023, 
and the EHR reporting period in CY 2024 is a minimum of any continuous 
180-day period within CY 2024. For more information, we refer readers 
to the discussion in the FY 2022 Hospital Inpatient Prospective Payment 
Systems for Acute Care Hospitals and the Long-Term Care Hospital (IPPS/
LTCH) Prospective Payment System (PPS) final rule (86 FR 45460 through 
45462).
a. CEHRT Requirements
    The Promoting Interoperability Program and the Quality Payment 
Program (QPP) require the use of CEHRT as defined at 42 CFR 495.4 and 
414.1305, respectively. Since 2019, in general, this has consisted of 
EHR technology (which could include multiple technologies) certified 
under the Office of the National Coordinator for Health Information 
Technology (ONC) Health Information Technology (IT) Certification 
Program that meets the 2015 Edition Base EHR definition (as defined at 
45 CFR 170.102) and has been certified to certain other 2015 Edition 
health IT certification criteria as specified in the definition.

[[Page 49320]]

    The ``21st Century Cures Act: Interoperability, Information 
Blocking, and the ONC Health IT Certification Program'' final rule 
(also referred to as the ``ONC 21st Century Cures Act final rule''), 
published in the May 1, 2020, Federal Register (85 FR 25642 through 
25961), finalized a number of updates to the 2015 Edition of health IT 
certification criteria (also referred to as the 2015 Edition Cures 
Update) and introduced new 2015 Edition certification criteria. In 
connection with these updates, ONC also finalized that health IT 
developers have 24 months from the publication date of the final rule 
(until May 2, 2022) to make technology available that is certified to 
the updated, or new criteria. In response to additional calls for 
flexibility in response to the Public Health Emergency (PHE) for COVID-
19, ONC published an interim final rule with comment period on November 
4, 2020 entitled, ``Information Blocking and the ONC Health IT 
Certification Program: Extension of Compliance Dates and Timeframes in 
Response to the COVID-19 Public Health Emergency'' (hereinafter the 
``ONC interim final rule'') (85 FR 70064). In this interim final rule, 
ONC finalized extended compliance dates for certain 2015 Edition 
certification criteria. Specifically, where the ONC 21st Century Cures 
Act final rule provided that developers of certified health IT have 24 
months from the publication date of the final rule to make technology 
certified to new or updated criteria available, ONC extended the 
timeline until December 31, 2022 (and until December 31, 2023, for 45 
CFR[thinsp]170.315(b)(10), ``electronic health information (EHI) 
export'').
    In the CY 2021 Physician Fee Schedule (PFS) final rule (85 FR 84815 
through 84825), we finalized that the technology used by health care 
providers to satisfy the definitions of CEHRT at 42 CFR 495.4 and 
414.1305 must be certified under the ONC Health IT Certification 
Program, in accordance with the updated 2015 Edition certification 
criteria as finalized in the ONC 21st Century Cures Act final rule (85 
FR 25642). We further finalized aligning the transition period during 
which health care providers participating in the Promoting 
Interoperability Program or QPP may use technology certified to either 
the existing or updated 2015 Edition certification criteria, with the 
December 31, 2022, date established in the ONC interim final rule for 
health IT developers to make updated certified health IT available. 
After this date, health care providers will be required to use only 
certified technology updated to the 2015 Edition Cures Update for an 
EHR reporting period or performance period in CY 2023. We did not 
propose any changes to this policy.
    We remind readers that health care providers would not be required 
to demonstrate that they are using updated technology to meet the CEHRT 
definitions immediately upon the transition date of December 31, 2022. 
In accordance with the EHR reporting period and performance period 
established for the Promoting Interoperability Program and the Merit-
based Incentive Payment System (MIPS) Promoting Interoperability 
performance category, participants are only required to use technology 
meeting the CEHRT definitions during a self-selected EHR reporting 
period or performance period of a minimum of any consecutive 90 days in 
CY 2023, including the final 90 days of 2023 (86 FR 45460 through 45462 
and 86 FR 65466, respectively). The eligible hospital, CAH, or MIPS 
eligible clinician is not required to demonstrate meaningful use of 
technology meeting the 2015 Edition Cures Update until the EHR 
reporting period or performance period they have selected.
3. Electronic Prescribing Objective: Changes to the Query of 
Prescription Drug Monitoring Program Measure and Technical Update to 
the E-Prescribing Measure
a. Query of Prescription Drug Monitoring Program Measure Background
    We have adopted the Query of Prescription Drug Monitoring Program 
(PDMP) measure under the Electronic Prescribing Objective. For 
background on this measure, we refer readers to the FY 2019 IPPS/LTCH 
PPS final rule (83 FR 41648 through 41653), the FY 2020 IPPS/LTCH PPS 
final rule (84 FR 42593 through 42595), the FY 2021 IPPS/LTCH PPS final 
rule (85 FR 58967 through 58969), and the FY 2022 IPPS/LTCH PPS final 
rule (86 FR 45462 through 45464). In the FY 2021 IPPS/LTCH PPS final 
rule (85 FR 58967 through 58969), we finalized that the Query of PDMP 
measure will remain optional and eligible for 5 bonus points for EHR 
reporting periods in CY 2021. In the FY 2022 IPPS/LTCH PPS final rule 
(86 FR 45464), we finalized that the Query of PDMP measure will remain 
optional and increased the eligible bonus points to 10 points for CY 
2022.
    In the FY 2020 IPPS/LTCH PPS final rule (84 FR 42593 through 
42596), FY 2021 IPPS/LTCH PPS final rule (85 FR 58967 through 58969), 
and FY 2022 IPPS/LTCH PPS final rule (86 FR 45462 through 45464), we 
described the concern expressed by interested parties who believed it 
was premature for the Medicare Promoting Interoperability Program to 
require the Query of PDMP measure and to score it based on performance. 
We heard extensive feedback from EHR developers that effectively 
incorporating the ability to count the number of PDMP queries in the 
EHR would require more robust measurement specifications. These 
interested parties stated that EHR developers may face significant cost 
burdens if they fully develop numerator and denominator calculations 
and are then required to change the specification at a later date. 
Interested parties stated that the costs of additional development 
would likely be passed on to health care providers without additional 
benefit, as this development would be solely for the purpose of 
calculating the measure, rather than furthering the clinical goal of 
the measure. While we recognize that a numerator/denominator-based 
measure remains challenging, we also note (as discussed in more detail 
later in this section of the final rule) that the widespread 
availability of PDMPs across the country, and recent progress toward 
solutions for connecting PDMPs with provider EHR systems, has made use 
of PDMPs feasible through a wide variety of approaches.
b. Current Status of PDMP Adoption
    Today, all 50 states and several localities host PDMPs.\1088\ The 
final state to establish a PDMP, the state of Missouri, passed 
legislation to address this issue in 2021, and is currently working to 
make its PDMP operational. A 2021 American Medical Association report 
found that physicians and others used state PDMPs more than 910 million 
times in 2020.\1089\ An assessment of PDMPs conducted by the PDMP 
Training and Technical Assistance Center (TTAC) at the Institute for 
Intergovernmental Research (IIR) found an increase in the number of 
PDMPs that are integrated with Health Information Exchanges (HIEs), 
EHRs, and/or Pharmacy Dispensing Systems (PDSs), with 44 PDMPs 
integrated in

[[Page 49321]]

2021 reflecting an increase from 28 PDMPs with at least one type of 
integration in 2017. We refer readers to Table IX.H.-01. for the 
report's findings on the type of integration and the number of PDMPs 
that have implemented that type of integration in 2021.
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    \1088\ Prescription Drug Monitoring Program Training and 
Technical Assistance Center, PDMP Policies and Capabilities: Results 
From 2021 State Assessment, September 2021, https://www.pdmpassist.org/pdf/PDMP%20Policies%20and%20Capabilities%202021%20Assessment%20Results_20210921.pdf.
    \1089\ American Medical Association, 2021 Overdose Epidemic 
Report, https://www.ama-assn.org/system/files/ama-overdose-epidemic-report.pdf.
[GRAPHIC] [TIFF OMITTED] TR10AU22.183

    Moreover, a number of enhancements to PDMPs and related initiatives 
are occurring across the country, including enhancements to RxCheck, 
which is a free, federally supported interstate exchange hub for PDMP 
data. RxCheck is connected to 50 out of 54 PDMPs in states and 
territories and does not require providers to pay to have access to 
PDMP data from other states and territories that are also live on 
RxCheck. The CDC, in partnership with ONC and other industry 
stakeholders, have been working to connect RxCheck to the eHealth 
Exchange as an alternative pathway for providers to conduct interstate 
queries of patient medication histories. The goal of the project is to 
allow any health care provider who is live on the eHealth Exchange to 
use that existing connection to query a patient's record through the 
RxCheck Hub, which routes the query to individual State PDMPs that are 
also live on RxCheck. This solution enables health care providers to 
query PDMPs via existing connections to health information exchange 
networks. Most states use either RxCheck or Prescription Monitoring 
Program (PMP) InterConnect or both to facilitate the sharing of PDMP 
information between states, allowing health care providers to query 
other states' PDMP.\1091\
---------------------------------------------------------------------------

    \1090\ PDMP Policies and Capabilities: Results From 2021 State 
Assessment, September 2021, https://www.pdmpassist.org/pdf/PDMP%20Policies%20and%20Capabilities%202021%20Assessment%20Results_20210921.pdf.
    \1091\ Government Accountability Office. GAO-21-22, PRESCRIPTION 
DRUG MONITORING PROGRAMS: Views on Usefulness and Challenges of 
Programs.
---------------------------------------------------------------------------

    We also note that the Substance Use-Disorder Prevention that 
Promotes Opioid Recovery and Treatment (SUPPORT) for Patients and 
Communities Act (Pub. L. 115-271), enacted in 2018, has focused on ways 
to address the nation's opioid epidemic. The SUPPORT for Patients and 
Communities Act included new requirements for PDMP enhancement and 
integration, to help reduce opioid misuse and overprescribing and 
promote the effective prevention and treatment of opioid use disorder 
beginning in October of 2021. Enhanced Federal matching funds were 
available to states to support related PDMP design, development, and 
implementation activities during fiscal years 2019 and 2020.
c. Changes to the Query of PDMP Measure and Related Policies
(1) Changes to the Query of PDMP Measure Description
    The description of the Query of PDMP measure provides that for at 
least one Schedule II opioid electronically prescribed using CEHRT 
during the EHR reporting period, the eligible hospital or CAH uses data 
from CEHRT to conduct a query of a PDMP for prescription drug history, 
except where prohibited and in accordance with applicable law (42 CFR 
495.24(e)(5)(iii)(B)). In the FY 2023 IPPS/LTCH PPS proposed rule (87 
FR 28579), beginning with the EHR reporting period in CY 2023, we 
proposed to require the Query of PDMP measure for eligible hospitals 
and CAHs participating in the Medicare Promoting Interoperability 
Program. We also noted that should we finalize our proposal to require 
the Query of PDMP measure beginning with the EHR reporting period in CY 
2023, we proposed two exclusions beginning with the EHR reporting 
period in CY 2023: (1) Any eligible hospital or CAH that does not have 
an internal pharmacy that can accept electronic prescriptions for 
controlled substances that include drugs from Schedules II, III, and 
IV, and is not located within 10 miles of any pharmacy that accepts 
electronic prescriptions for controlled substances at the start of 
their EHR reporting period; and (2) any eligible hospital or CAH that 
cannot report on this measure in accordance with applicable law (87 FR 
28581). We also noted in the FY 2023 IPPS/LTCH PPS proposed rule that 
should we finalize the proposals to require the Query of PDMP measure 
and the associated exclusions, we believe the inclusion of the phrase 
``except where prohibited and in accordance with applicable law'' in 
the description of the Query of PDMP measure and the inclusion of the 
phrase ``in accordance with applicable law'' in the second proposed 
exclusion for the Query of PDMP measure would be duplicative and 
potentially cause confusion (87 FR 28578). Therefore, we proposed to 
remove the phrase ``except where prohibited and in accordance with 
applicable law'' from the description of the Query of PDMP measure 
should our proposals to require the Query of PDMP measure and the 
associated exclusions be finalized. For additional information on 
proposed changes to the Query of PDMP measure, we referred readers to 
the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28580).
    We also stated in the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 
28579) that should our proposal to remove associated regulatory text 
related to measures and objectives for the Medicare Promoting 
Interoperability Program not be finalized, we propose to update the 
regulatory text to reflect these proposed changes at 42 CFR 
495.24(e)(5). We invited public comment on these proposals.
    Comment: A few commenters expressed support for our proposal to 
change the Query of PDMP measure description.
    Response: We thank commenters for their support.
    After consideration of the public comments we received, we are 
finalizing our proposal to change the

[[Page 49322]]

Query of PDMP measure description to remove the phrase ``except where 
prohibited and in accordance with applicable law''; we refer the reader 
to section IX.H.3.c.(3) for the finalized measure description. In 
section IX.H.8. of this final rule, we are finalizing our proposal to 
remove the associated regulatory text related to measures and 
objectives for the Medicare Promoting Interoperability Program, and 
therefore, we will not be updating 42 CFR 495.24(e)(5) with our 
finalized changes to the Query of PDMP measure description.
(2) Changes To Require the Query of PDMP Measure
    In the FY 2022 IPPS/LTCH PPS final rule (86 FR 45462), we noted 
that the decision to maintain the Query of PDMP as an optional measure 
for EHR reporting periods in CY 2022 considered the current efforts to 
improve the technical foundation for EHR-PDMP integration, the 
continued implementation of the SUPPORT for Patients and Communities 
Act, our ongoing review of alternative measure approaches, and 
interested party concerns about the current readiness across states for 
implementation of the existing measure. We also noted that this measure 
can play an important role in helping health care providers to improve 
clinical decision making by utilizing this information to identify 
potential opioid use disorders, inform the development of care plans, 
and develop effective interventions (86 FR 45463); maintaining it as an 
optional measure with bonus points signals to the hospital and vendor 
community that this is an important measure which can help spur 
development and innovation to reduce barriers and challenges (86 FR 
45463).
    We continue to believe that PDMPs play an important role in patient 
safety by assisting in the identification of patients who have multiple 
prescriptions for controlled substances or may be misusing or overusing 
them. Querying the PDMP is important for tracking dispensed controlled 
substances and improving prescribing practices. Efforts to expand the 
use of PDMPs and integrate PMDPs with health information technology 
systems are supported by Federal agencies including ONC, the Centers 
for Disease Control and Prevention (CDC), the Department of Justice 
(DOJ), and the Substance Abuse and Mental Health Services 
Administration (SAMHSA). The Query of PDMP measure offers a way to 
reward health care providers who participate in current PDMP 
initiatives that are supported by Federal partners.
    While work continues to improve standardized approaches to PDMP and 
EHR interoperability, we believe that it is feasible at this time to 
require health care providers to report the current Query of PDMP 
measure requiring a ``yes/no'' response. Given our policies for the 
Query of PDMP measure that included increasing the eligible bonus 
points to reward eligible hospitals and CAHs that could report the 
measure, as well as the recent progress in the availability of PDMPs in 
all fifty states, and solutions which support accessibility of PDMPs to 
health care providers, we believe eligible hospitals and CAHs have had 
time to grow familiar with what this measure requires of them, even as 
technical approaches to the use of PDMPs continue to advance. By 
requiring a ``yes/no'' response the current measure allows health care 
providers to use a variety of technical solutions to conduct a query of 
the PDMP and receive credit for the measure.
    Therefore, beginning with the EHR reporting period in CY 2023, we 
proposed to require the current Query of PDMP measure requiring a 
``yes/no'' response for eligible hospitals and CAHs participating in 
the Medicare Promoting Interoperability Program. We stated that we 
would maintain the associated points at 10 points and referred readers 
to section IX.H.6. of the proposed rule for a discussion of our scoring 
methodology and proposed concurrent changes. As a result of this 
proposal, the maximum total points available for the Electronic 
Prescribing Objective would remain at 20 points for EHR reporting 
periods in CY 2023. We also stated in the FY 2023 IPPS/LTCH PPS 
proposed rule (87 FR 28579) that should our proposal to remove 
associated regulatory text related to measures and objectives for the 
Medicare Promoting Interoperability Program not be finalized, we 
propose to update the regulatory text to reflect these proposed changes 
at 42 CFR 495.24(e)(5)(iii)(B).
    We invited public comment on these proposals.
    Comment: Many commenters expressed support for requiring the Query 
of PDMP measure because it remains a ``yes/no'' attestation-based 
measure; they noted that it allows for use of a variety of technical 
solutions to report the measure, and includes exclusions. Several 
commenters supported requiring the measure because querying a PDMP is 
critical to understanding a patient's medication history to inform 
effective, quality care, particularly when Schedule II opioids and 
Schedules III and IV drugs are prescribed and dispensed. They further 
stated that it is important for future public health initiatives and 
drug abuse prevention efforts.
    Response: We would like to thank the commenters for their support. 
We agree that the Query of PDMP measure is an important tool for 
clinicians, and for improving prescribing practices geared towards 
overall patient safety.
    Comment: Several commenters expressed their support stating that 
eligible hospitals and CAHs have had ample time to prepare for this 
change. For eligible hospitals and CAHs with continued challenges, a 
commenter shared that there are technological solutions available to 
make this requirement feasible. Last, commenters shared that the 
benefits of the measure outweigh concerns with implementation of 
improved systems to support access to PDMP data health IT system 
design, and that requiring the measure will continue to promote data 
exchange and more advanced EHR workflows.
    Response: We appreciate the commenters' support for requiring the 
Query of PDMP measure. We agree that eligible hospitals and CAHs have 
had ample time to prepare for this requirement, and have had time to 
grow familiar with what this measure requires of them. As states 
continue to improve the accessibility of PDMPs through technical 
advances, we believe eligible hospitals and CAHs have an increasing 
number of solutions available to effectively query PDMPs.
    Comment: Several commenters offered suggestions and recommendations 
for our consideration. A commenter recommended that CMS ensure that 
requiring the Query of PDMP measure would not create a barrier for 
clinicians appropriately prescribing opioids for patients. Another 
commenter recommended that CMS consider accounting for state laws that 
already require PDMP queries, and adjusting for known challenges, 
including state variability of PDMP requirements and processes and the 
availability of interstate data. A commenter recommended that CMS 
require States to work with EHR vendors to continue the integration 
process, thereby improving clinician workflow. A commenter recommended 
that CMS monitor the ability of CAHs and small rural hospitals to 
comply with the Query of PDMP measure and provide flexibility, support 
and technical assistance if disparities in capacity and ability to use 
IT systems are identified.
    Response: We appreciate the commenters' support, including their

[[Page 49323]]

recommendations for our proposal. We agree it is important that the 
measure not create barriers for appropriate prescribing or create 
additional administrative burden, and believe that maintaining the 
measure as requiring a ``yes/no'' response allows eligible hospitals 
and CAHs to report while minimizing burden. Regarding the 
recommendation that CMS require states to work with EHR vendors and 
continuously monitor for known challenges, we thank commenters for this 
suggestion. CMS maintains communication with ONC, and together, we 
assess and monitor challenges that eligible hospitals and CAHs face 
with vendors and state-specific PDMPs. We appreciate commenters' 
concerns about the impact of requiring the Query of PDMP measure on 
CAHs and small rural hospitals. The Query of PDMP measure requires a 
``yes/no'' response, and we believe this helps to minimize potential 
burden for small rural hospitals. We also refer readers to the 
finalized measure description for the Query of PDMP measure of this 
final rule at section IX.H.3.c.(3), where we state that we require a 
minimum of ``at least one'' query of the PDMP and that no maximum or 
suggested number of queries have been established. Last, CMS, as well 
as other HHS agencies, are supporting a number of initiatives to enable 
better integration between PDMPs and health IT systems used by health 
care providers. We refer readers to the FY 2023 IPPS/LTCH PPS proposed 
rule for further discussion (87 FR 28577 through 28578).
    Comment: A few commenters expressed support for making the Query of 
PDMP measure required, so long as it is delayed until CY 2024. A few 
commenters have requested a delay in requiring the measure until every 
state has an operational statewide PDMP, or until there is an exclusion 
for those eligible hospitals and CAHs without a statewide PDMP. A few 
commenters cited the need for additional time for network development 
and nationwide integration between EHRs and PDMPs. A commenter noted 
that EHR vendors require a minimum of 24 months to complete development 
and deployment of any new functionality.
    Response: We disagree that requiring the Query of PDMP measure 
should be delayed until CY 2024. While we appreciate the importance of 
ongoing work to improve interoperability of PDMP data and integration 
systems, we also believe that at this time, there is sufficient 
technical capacity across the country to support finalizing the measure 
in its current form, requiring a ``yes/no'' attestation. We also 
understand that there is currently only one state without an 
operational statewide PDMP, and that this remaining state is moving 
towards an operational status. Last, we note that we are not finalizing 
any new technology requirements to support the completion of the 
actions associated with this measure.
    Comment: Many commenters did not support requiring the Query of 
PDMP measure citing inconsistencies across state lines with regard to 
interoperability standards, varying degrees of implementation, and the 
complexities resulting from inconsistent state laws and licensing 
requirements. Some commenters did not support requiring the Query of 
PDMP measure due to a lack of standardized privacy and security 
protocols.
    Response: CMS recognizes the work required to improve integration 
between PDMPs and health care provider health IT systems, as well as 
the efforts required to standardize data sharing between the systems 
that may include consideration of privacy and security protocols, and 
that these efforts are ongoing across the country. While we believe 
that the importance of querying the PDMP, and the widespread 
availability of PDMPs at this time is sufficient to finalize requiring 
the current measure requiring a ``yes/no'' response, we will continue 
to support efforts to improve the technical approaches supporting data 
exchange between systems. As these approaches mature, we will work with 
ONC to consider whether these approaches should be incorporated into 
the ONC Health IT Certification Program and the Medicare Promoting 
Interoperability Program.
    After consideration of the public comments we received, we are 
finalizing our proposal to require the Query of PDMP measure beginning 
with the EHR reporting period in CY 2023. In section IX.H.8. of this 
final rule, we are finalizing our proposal to remove the associated 
regulatory text related to measures and objectives for the Medicare 
Promoting Interoperability Program, and therefore, we will not be 
updating 42 CFR 495.24(e)(5) with our finalized changes to the Query of 
PDMP measure.
(3) Changes to the Query of PDMP Measure To Include Schedule II Opioids 
and Schedule III and IV Drugs
    Under 42 CFR 495.24(e)(5)(iii)(B), the Query of PDMP measure 
provides that for at least one Schedule II opioid electronically 
prescribed using CEHRT during the EHR reporting period, the eligible 
hospital or CAH uses data from CEHRT to conduct a query of a PDMP for 
prescription drug history, except where prohibited and in accordance 
with applicable law. The Query of PDMP measure was adopted in the FY 
2019 IPPS/LTCH PPS final rule as one of two measures under the 
Electronic Prescribing Objective intended to support HHS initiatives 
related to the treatment of opioid and substance use disorders by 
helping health care providers avoid inappropriate prescriptions, 
improving coordination of prescribing amongst health care providers, 
and focusing on the advanced use of CEHRT (83 FR 41648 through 41653).
    Under the Controlled Substances Act (CSA),\1092\ the Drug 
Enforcement Administration classifies drugs, substances, and certain 
chemicals used to make drugs into five distinct categories or schedules 
depending upon the drug's acceptable medical use and the drug's abuse 
or dependency potential. A drug's abuse rate is a factor used to 
determine its classification; for example, Schedule I medications have 
the highest abuse potential while medications in Schedule V have a low 
abuse potential. We refer readers to Table IX. H.-02. for information 
on each Schedule, including abuse potential, medicinal use, if any, and 
drug examples. For additional information, we refer readers to the 
listing of drugs and their schedule located at CSA Scheduling at 
https://www.deadiversion.usdoj.gov/schedules/orangebook/c_cs_alpha.pdf.\1093\
---------------------------------------------------------------------------

    \1092\ Public Law 91-513, tit. II, 84 Stat. 1236, 1242-84 
(1970); codified, as amended, at 21 U.S.C. 801 et seq.
    \1093\ See also https://www.dea.gov/sites/default/files/2020-04/Drugs%20of%20Abuse%202020-Web%20Version-508%20compliant-4-24-20_0.pdf.

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[[Page 49324]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.184

    PDMPs are operated at the state level and individual state 
requirements for reporting and use differ from state to state.\1095\ 
Currently, every state collects data on schedules II, III, and IV 
drugs.\1096\ Some states collect information about certain non-
controlled substances that are potentially subject to abuse or on all 
prescription drugs.\1097\ While state laws vary, we note that most 
state PDMPs require physicians and dispensing pharmacists to review a 
patient's prescribing information for the past twelve months prior to 
prescribing or dispensing any Schedule II, III, and IV drugs.\1098\
---------------------------------------------------------------------------

    \1094\ GAO-21-22, Prescription Drug Monitoring Programs: Views 
on Usefulness and Challenges of Programs; 21 U.S.C. 812, and the 
U.S. Drug Enforcement Administration.
    \1095\ For additional information, we refer readers to https://www.cdc.gov/drugoverdose/pdf/Leveraging-PDMPs-508.pdf; https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4605194/; and https://www.pdmpassist.org/Policies/Legislative/StatutesAndRegulations.
    \1096\ https://www.pdmpassist.org/State.
    \1097\ GAO report, GAO-21-22 Prescription Drug Monitoring 
Programs.
    \1098\ https://www.pdmpassist.org/State.
---------------------------------------------------------------------------

    PDMPs play an important role in patient safety by assisting in the 
identification of patients who have multiple prescriptions for 
controlled substances or may be misusing or overusing them. We believe 
that expanding the requirements of the Query of PDMP measure to include 
not only Schedule II opioids, and but also Schedule III and IV drugs, 
this would further support HHS initiatives related to the treatment of 
opioid and substance use disorders by expanding the types of drugs 
included in the Query of PDMP measure while aligning with the PDMP 
requirements in a majority of states. We also believe this expansion to 
include additional Scheduled drugs would facilitate more informed 
prescribing practices and improve patient outcomes. Therefore, in the 
FY 2023 IPPS/LTCH PPS proposed rule, we proposed to expand the Query of 
PDMP measure to include Schedule II opioids, and Schedule III and IV 
drugs beginning with the EHR reporting period in CY 2023 (87 FR 28579 
through 28581).
    Proposed Measure Description: For at least one Schedule II opioid 
or Schedule III or IV drug electronically prescribed using CEHRT during 
the EHR reporting period, the eligible hospital or CAH uses data from 
CEHRT to conduct a query of a PDMP for prescription drug history.
    To align with the policy for the Query of PDMP measure with regard 
to Schedule II opioids, we proposed in the FY 2023 IPPS/LTCH PPS 
proposed rule that the query of the PDMP for prescription drug history 
must occur prior to the electronic transmission of an electronic 
prescription for a Schedule II opioid or Schedule III or IV drug (87 FR 
28580). We also proposed that this measure would include all 
permissible prescriptions and dispensing of Schedule II opioids, and 
Schedule III or IV drugs, no matter how small the dose prescribed 
during an encounter. This would allow eligible hospitals and CAHs to 
identify multiple health care provider episodes (physician shopping), 
prescriptions of dangerous combinations of drugs, and controlled 
substances prescribed in high quantities (87 FR 28580). We also 
proposed that multiple prescriptions for Schedule II opioids or 
Schedule III and IV drugs prescribed on the same date, by the same 
eligible hospital or CAH would not require multiple queries of the 
PDMP, and at least one query would have to be performed for this 
measure. We proposed that eligible hospitals and CAHs would have 
flexibility to query the PDMP using data from CEHRT in

[[Page 49325]]

any manner allowed under state law (87 FR 28580). We also stated in the 
FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28580 through 28581) that 
should our proposal to remove associated regulatory text related to 
measures and objectives for the Medicare Promoting Interoperability 
Program not be finalized, we proposed to update the regulatory text to 
reflect these proposed changes at 42 CFR 495.24(e)(5)(iii)(B).
    We invited public comment on these proposals. We also invited 
public comment on whether to expand this measure to include Schedule V 
or other drugs with the potential for abuse.
    Comment: Many commenters expressed support to expand the Query of 
PDMP measure to include Schedule III and IV drugs. A commenter 
expressed their belief that understanding a patient's medication 
history is critical to safe, effective, quality care, particularly when 
Schedule II opioids and Schedule III and IV drugs are prescribed and 
dispensed. A commenter expressed its belief that the proposed expansion 
makes sense because many states also require similar queries.
    Response: We thank commenters for their support, and agree that in 
expanding our measure to also include Schedule III and IV drugs, this 
will offer eligible hospitals and CAHs a broader clinical picture, 
aimed at overall patient safety efforts, and agree that expanding these 
schedules will support better alignment with state regulations.
    Comment: A commenter expressed support to include Schedule III and 
IV drugs, and further recommended that CMS consider similar state laws 
that require PDMP queries, and how those requirements differ from CMS's 
requirements.
    Response: We thank the commenter for their support. While state 
laws do vary, we generally understand that many states' PDMPs require 
physicians and dispensing pharmacists to review each patient's 
prescribing information for twelve months prior to prescribing or 
dispensing any Schedule II opioids or Schedule III and IV controlled 
substances. We may consider the additional feedback in future 
rulemaking.
    Comment: A few commenters did not support expanding the Query of 
PDMP measure to include Schedule III and IV drugs citing the lack of 
harmony between state requirements, the potential for confusion, and 
that some states do not have an operational statewide PDMP.
    Response: We disagree with the commenter that expanding the Query 
of PDMP measure to include Schedule III and IV drugs would contribute 
to a lack of harmony between state requirements, thereby causing 
potential confusion. We note that currently, every state collects data 
on Schedule II opioids, and Schedule III and IV drugs. We believe that 
in collecting similar data this would minimize the potential for 
confusion, and instead, promote harmony.
    Comment: A few commenters requested clarification on whether the 
expansion includes all Schedule II drugs.
    Response: We proposed expanding the Query of PDMP measure to 
include Schedule III and IV drugs, but did not propose any changes to 
the language in the measure description that references Schedule II 
opioids, and clarify that the Query of PDMP measure does not include or 
apply to Schedule II drugs that are not opioids (for example, central 
nervous system stimulants).
    Comment: A few commenters recommended furthering the expansion of 
the Query of PDMP measure to also include Schedule V drugs if there 
would be value in doing so.
    Response: We appreciate the commenters' feedback. While we are not 
including Schedule V drugs at this time due to the current low 
potential for abuse in that category, we may consider this in future 
rulemaking.
    After consideration of the public comments we received, we are 
finalizing our proposals related to the expansion of the Query of PDMP 
measure to include Schedule II opioids, and Schedule III and IV drugs 
beginning with the EHR reporting period in CY 2023, as well as the 
proposed Query of PDMP measure description, and our proposals related 
to requiring that the query of the PDMP for prescription drug history 
must occur prior to the electronic transmission of an electronic 
prescription for a Schedule II opioid or Schedule III or IV drug; that 
the measure would include all permissible prescriptions and dispensing 
of Schedule II opioids, and Schedule III or IV drugs, no matter how 
small the dose prescribed during an encounter; that multiple 
prescriptions for Schedule II opioids or Schedule III and IV drugs 
prescribed on the same date, by the same eligible hospital or CAH would 
not require multiple queries of the PDMP, and at least one query would 
have to be performed for this measure; and that eligible hospitals and 
CAHs would have flexibility to query the PDMP using data from CEHRT in 
any manner allowed under state law . In section IX.H.8. of this final 
rule, we are finalizing our proposal to remove the associated 
regulatory text related to measures and objectives for the Medicare 
Promoting Interoperability Program, and therefore, we will not be 
updating 42 CFR 495.24(e)(5) with our finalized changes to the Query of 
PDMP measure.
(4) Exclusions
    In FY 2019 IPPS/LTCH PPS final rule, we finalized exclusions for 
eligible hospitals and CAHs from reporting the Query of PDMP measure 
beginning with EHR reporting period in CY 2020 when the measure would 
have been required by the Medicare Promoting Interoperability Program 
(83 FR 41653). The finalized exclusions included: (1) Any eligible 
hospital or CAH that does not have an internal pharmacy that can accept 
electronic prescriptions for controlled substances and is not located 
within 10 miles of any pharmacy that accepts electronic prescriptions 
for controlled substances at the start of their EHR reporting period; 
and (2) any eligible hospital and CAH that could not report on this 
measure in accordance with applicable law. We also finalized that 
beginning with EHR reporting period in CY 2020, an eligible hospital or 
CAH that qualifies for the e-Prescribing measure exclusion is also 
excluded from reporting on the Query of PDMP measure (83 FR 41649). We 
noted our intention to propose a third exclusion where integration with 
a statewide PDMP was not yet feasible or widely available (83 FR 
41652).
    In FY 2020 IPPS/LTCH PPS final rule (84 FR 42595), we finalized the 
removal of the exclusions associated with the Query of PDMP measure, 
noting that exclusions were not necessary because we finalized the 
Query of PDMP measure as optional for the EHR reporting period in CY 
2020. We also finalized the Query of the PDMP measure as an optional 
measure for EHR reporting periods in CY 2021 and CY 2022 in FY 2021 
IPPS/LTCH PPS final rule (85 FR 58969) and the FY 2022 IPPS/LTCH PPS 
final rule (86 FR 45464), respectively.
    In the FY 2023 IPPS/LTCH PPS proposed rule, beginning with the EHR 
reporting period in CY 2023, we proposed to require the Query of PDMP 
measure for eligible hospitals and CAHs participating in the Medicare 
Promoting Interoperability Program (87 FR 28581). We noted that should 
we finalize our proposal to require the Query of PDMP measure beginning 
with CY 2023, we believed that exclusions for the measure would be 
necessary (87 FR 28581). We revisited the exclusions established in the 
FY 2019 IPPS/LTCH PPS final rule and subsequently removed in the FY 
2020 IPPS/LTCH PPS final rule because

[[Page 49326]]

the Query of PDMP measure would continue to be an optional measure. In 
the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28581), we stated that 
if we finalize our proposal to require the Query of PDMP measure, we 
proposed the following exclusions beginning with the EHR reporting 
period in CY 2023: (1) Any eligible hospital or CAH that does not have 
an internal pharmacy that can accept electronic prescriptions for 
controlled substances that include drugs from Schedules II, III, and 
IV, and is not located within 10 miles of any pharmacy that accepts 
electronic prescriptions for controlled substances at the start of 
their EHR reporting period; and (2) any eligible hospital or CAH that 
cannot report on this measure in accordance with applicable law. We 
also referred readers to our proposed policy to redistribute points to 
the e-Prescribing measure under the Electronic Prescribing Objective 
should an eligible hospital or CAH claim an exclusion for the Query of 
PDMP measure for an EHR reporting period (87 FR 28589 through 28592). 
We also stated in the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28581) 
that should our proposal to remove associated regulatory text related 
to measures and objectives for the Medicare Promoting Interoperability 
Program not be finalized, we proposed to update the regulatory text to 
reflect these proposed changes at 42 CFR 495.24(e)(5).
    In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41652), we signaled 
our intention to propose an additional exclusion beginning in CY 2020 
for health care providers in states where integration with a statewide 
PDMP is not yet feasible or not yet widely available. In the FY 2023 
IPPS/LTCH PPS proposed rule (87 FR 28581), we expressed our belief that 
this exclusion is no longer needed given the flexibility of the Query 
PDMP measure, which requires a ``yes/no'' response, as well as the 
implementation of PDMPs in all 50 states and several localities and the 
increasing number of PDMPs offering some degree of integration with 
EHRs (from 28 PDMPs with at least one type of integration in 2017 to 44 
PDMPs that are integrated with HIEs, EHRs, and/or PDSs in 2021 \1099\). 
We also expressed our belief that broadly requiring this measure across 
health care providers who may access PDMPs in different ways would help 
to continue to drive development of improved solutions for PDMP access. 
In addition, we stated that while we believe the Query of PDMP measure 
is achievable for eligible hospitals and CAHs and that the proposed 
exclusions offer significant flexibilities such that most health care 
providers would be able to meet the measure or claim an exclusion, we 
welcomed public comment on other barriers, including barriers related 
to technology solutions, cost, and workflow, that should be considered. 
We also requested comment on any additional exclusions that we should 
consider for this measure and may propose in the future.
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    \1099\ PDMP Policies and Capabilities: Results From 2021 State 
Assessment, September 2021, https://www.pdmpassist.org/pdf/PDMP%20Policies%20and%20Capabilities%202021%20Assessment%20Results_20210921.pdf.
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    We invited public comment on these proposals.
    Comment: Several commenters expressed support for our proposed 
exclusions.
    Response: We thank commenters for their support.
    Comment: Several commenters recommended that CMS consider 
additional exclusions. Suggestions included allowing an exclusion for 
eligible hospitals and CAHs in states where EHR-PDMP integration is 
limited, not possible, or where there is no operational statewide PDMP. 
A few commenters recommended an exclusion, waiver, or discretion 
enforcement for the Query of PDMP measure noting it could be burdensome 
on clinician workflows to compile supporting documentation for 
attestation using multiple systems, and that this is not the time to 
put additional burden on clinicians until states have improved their 
technologies to enable more efficient inquiries. Other commenters 
recommended that CMS consider exclusions for eligible hospitals and 
CAHs that are required by the state to use their PDMP outside of, and 
independent from, their CEHRT, and may not be able to meet the 
requirements of the Query of PDMP measure.
    Response: We thank commenters for their recommendations to include 
additional exclusions. After reviewing the comments, we agree with 
commenters that an additional exclusion is needed for eligible 
hospitals and CAHs for one year. We understand that, for some, 
accessing state PDMPs can be time-consuming and disruptive to clinical 
workflow, if technology requires exiting the hospital medical record, 
connecting with the state PDMP, then compiling supporting documentation 
for attestation using multiple systems. We also understand that while 
most states have an operational statewide PDMP, for those eligible 
hospitals and CAHs located in a state that does not have an operational 
statewide PDMP, they would need to check a limited county-level PDMP to 
meet the requirements of the Query of PDMP measure, and we agree, that 
could interrupt workflows for providers. We believe that this 
additional, and temporary, exclusion would address concerns raised by 
CAHs and small rural hospitals where disparities in capacity, and the 
ability to use IT systems, make meeting the requirements of the Query 
of PDMP measure costly or burdensome.
    We believe that offering an additional exclusion for the CY 2023 
EHR reporting period for eligible hospitals or CAHs would provide more 
time for technologies to improve and for increased EHR-PDMP integration 
to enable more efficient queries of the PDMP. This exclusion would be 
available for a limited time (CY 2023), because we believe that one 
year would offer eligible hospitals and CAHs time to become familiar 
with new technologies, processes and make necessary adjustments to 
their workflow with minimal burden and allow for improved readiness.
    We appreciate the commenter's recommendation for an exclusion to 
address when state laws may not allow for an eligible hospital or CAH 
to meet the requirements of the Query of PDMP measure, and believe the 
proposed exclusion for ``any eligible hospital or CAH that cannot 
report on this measure in accordance with applicable law'' would 
address that scenario.
    After consideration of the public comments we received, we are 
finalizing our proposals with modification to include the following 
three exclusions for the Query of PDMP measure: (1) Any eligible 
hospital or CAH that does not have an internal pharmacy that can accept 
electronic prescriptions for controlled substances that include 
Schedule II, III and IV drugs, and is not located within 10 miles of 
any pharmacy that accepts electronic prescriptions for controlled 
substances at the start of their EHR reporting period; (2) Any eligible 
hospital or CAH that cannot report on this measure in accordance with 
applicable law; and (3) Any eligible hospital or CAH for which querying 
a PDMP would impose an excessive workflow or cost burden prior to the 
start of the EHR reporting period they select in CY 2023. We note that 
we are finalizing this third exclusion related to workflow and cost 
burden on a time-limited basis for those eligible hospitals and CAHs 
that believe they would face significant burden associated with 
querying a PDMP at least once when reporting the measure during an EHR

[[Page 49327]]

reporting period in CY 2023. This exclusion will no longer be available 
for EHR reporting periods after CY 2023. We expect that those eligible 
hospitals and CAHs claiming this exclusion in 2023 will be able to 
utilize the additional time provided by this time-limited exclusion to 
resolve any remaining barriers to reporting the measure. In section 
IX.H.8. of this final rule, we are finalizing our proposal to remove 
the associated regulatory text related to measures and objectives for 
the Medicare Promoting Interoperability Program, and therefore, we will 
not be updating 42 CFR 495.24(e)(5) with our finalized changes to the 
Query of PDMP measure.
d. Future Direction
    While we believe that finalizing our proposals for the Query of 
PDMP measure are feasible and appropriate at this time, we continue to 
work with industry and Federal partners to advance common standards for 
the exchange of information between PDMPs, EHRs, pharmacy information 
systems, and exchange networks. We believe this work will ultimately 
allow us to achieve our ideal state, where we would further modify the 
Query of PDMP measure to be numerator/denominator-based, and require 
use of standardized functionality within CEHRT to support the actions 
associated with the measure while reporting on a numerator and 
denominator. We will continue to collaborate with ONC to monitor 
developments across the industry, efforts made toward advancing 
relevant standards, and plan to revisit this measure in the future to 
explore further specifying health IT requirements if they become 
available and are incorporated into the ONC Health IT Certification 
Program.
    Federally supported activities continue to focus on developing and 
refining standards-based approaches to enable effective integration 
into clinical workflows; exploring emerging technical solutions to 
enhance access to and use of PDMP data; and providing technical 
resources to a variety of interested parties to advance and scale the 
interoperability of health IT systems and PDMPs. Moreover, updates to 
certified health IT systems incorporating application programming 
interfaces (APIs) based on HL7[supreg] FHIR[supreg] standard version 
Release 4 (85 FR 25642) can help support future technical approaches 
that enable more seamless exchange of data between CEHRT and PDMP 
systems. For more information about current and emerging standards 
related to PDMP data capture and exchange, we refer readers to the ONC 
Interoperability Standards Advisory.\1100\
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    \1100\ https://www.healthit.gov/isa/allows-a-provider-request-a-patients-medication-history-a-state-prescription-drug-monitoring.
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e. Technical Update to the E-Prescribing Measure
    The ONC 21st Century Cures Act final rule (85 FR 25642; 85 FR 25660 
through 25661) retired the ``drug-formulary and preferred drug list 
checks'' certification criterion at 45 CFR 170.315(a)(10) which was 
associated with measures under the Electronic Prescribing Objective for 
the Medicare Promoting Interoperability Program and the MIPS Promoting 
Interoperability performance category (80 FR 62882 and 83 FR 59817). 
ONC retired this criterion after January 1, 2022 (85 FR 26661).
    In the CY 2021 PFS final rule, we finalized that the ``drug-
formulary and preferred drug list checks'' criterion will no longer be 
associated with measures under the Electronic Prescribing Objective and 
will no longer be required to meet the CEHRT definition for the 
Medicare Promoting Interoperability Program and the MIPS Promoting 
Interoperability performance category, beginning with CY 2021 EHR 
reporting and performance periods (85 FR 84815 through 84825).
    In the FY 2022 IPPS/LTCH PPS final rule, we inadvertently omitted a 
revision to TABLE IX.F.-02.: Objectives and Measures for the Medicare 
Promoting Interoperability Program in 2022 to reflect this change and 
included the text ``queried for a drug formulary'' in the measure 
description and in the numerator of the e-Prescribing measure (86 FR 
45484). In an effort to more clearly capture the previously established 
policy finalized in the CY 2021 PFS final rule with respect to the e-
Prescribing measure, we proposed in the FY 2023 IPPS/LTCH PPS proposed 
rule (87 FR 28582) to revise the measure description in TABLE 56 to 
read, ``For at least one hospital discharge, medication orders for 
permissible prescriptions (for new and changed prescriptions) are 
transmitted electronically using CEHRT'' and the numerator will be 
updated to read to indicate ``[t]he number of prescriptions in the 
denominator generated and transmitted electronically'' to reflect the 
removal of the health IT certification criterion ``drug-formulary and 
preferred drug list checks'' (86 FR 65478).
    We invited comment on our proposal.
    Comment: A few commenters supported our proposal.
    Response: We thank commenters for their support. After 
consideration of the public comments we have received, we are 
finalizing our proposal to revise the measure description in [TABLE XX] 
to read ``For at least one hospital discharge, medication orders for 
permissible prescriptions (for new and changed prescriptions) are 
transmitted electronically using CEHRT,'' and the numerator will be 
updated to read to indicate ``[t]he number of prescriptions in the 
denominator generated and transmitted electronically'' to reflect the 
removal of the health IT certification criterion ``drug-formulary and 
preferred drug list checks''.
4. Health Information Exchange (HIE) Objective: Addition of An 
Alternative Measure for Enabling Exchange Under the Trusted Exchange 
Framework and Common Agreement (TEFCA)
a. Background on the Health Information Exchange Objective
    The Health Information Exchange (HIE) Objective and its associated 
measures for eligible hospitals and CAHs hold particular importance 
because of the role they play within the care continuum. In addition, 
these measures encourage and leverage interoperability on a broader 
scale and promote health IT-based care coordination. The Health 
Information Exchange Objective currently includes three measures: 
Support Electronic Referral Loops by Sending Health Information, 
Support Electronic Referral Loops by Receiving and Reconciling Health 
Information, and Health Information Exchange Bi-Directional Exchange. 
For background on this objective and its associated measures, we refer 
readers to the FY 2019 IPPS/LTCH PPS final rule (83 FR 41656 through 
41661), the FY 2020 IPPS/LTCH PPS final rule (84 FR 42596 through 
42597), the FY 2021 IPPS/LTCH PPS final rule (85 FR 58969), and the FY 
2022 IPPS/LTCH PPS final rule (86 FR 45465 through 45470).
    In the FY 2022 IPPS/LTCH PPS final rule, we finalized the HIE Bi-
Directional Exchange measure, under the Health Information Exchange 
Objective (86 FR 45465 through 45470). The HIE Bi-Directional Exchange 
measure is worth 40 points, the maximum number of points of the Health 
Information Exchange Objective, and was finalized as an alternative to 
reporting on the two existing Health Information Exchange Objective 
measures: The Support Electronic Referral Loops by Sending Health 
Information measure (42 CFR 495.24(e)(6)(ii)(A)) and the Support 
Electronic Referral Loops by Receiving and Reconciling Health 
Information measure (42 CFR 495.24(e)(6)(ii)(B)). To

[[Page 49328]]

meet the measure requirements, eligible hospitals and CAHs must attest 
to the following statements:
     Statement 1: Participating in an HIE to enable secure, bi-
directional exchange of information to occur for all unique patients 
discharged from the eligible hospital or CAH inpatient or emergency 
department (POS 21 or 23), and all unique patient records stored or 
maintained in the EHR for these departments, during the EHR reporting 
period in accordance with applicable law and policy.
     Statement 2: Participating in an HIE that is capable of 
exchanging information across a broad network of unaffiliated exchange 
partners including those using disparate EHRs, and not engaging in 
exclusionary behavior when determining exchange partners.
     Statement 3: Using the functions of CEHRT to support bi-
directional exchange with an HIE.
    We stated that, by enabling bi-directional exchange of information 
between health care providers and aggregating data across health care 
providers with disparate systems, HIEs (including a wide range of 
organizations facilitating health information exchange) can bring 
together the information needed to create a true longitudinal care 
record and support improved care coordination by facilitating timely 
access to robust health information across care settings (86 FR 45465). 
We further described how participation in HIEs can amplify health care 
providers' capacity to share information beyond what a health care 
provider can achieve through the sending and receiving actions 
described in the existing measures under the Health Information 
Exchange Objective, for instance, by facilitating information exchange 
when a health care provider is unaware of another health care 
provider's need to receive information about a patient (86 FR 45466). 
By finalizing this measure for eligible hospitals and CAHs, we sought 
to ensure that eligible hospitals and CAHs participating in the 
Medicare Promoting Interoperability Program would be rewarded for 
connecting to exchange arrangements that can enable this type of robust 
information sharing.
b. Background on TEFCA
    Section 4003(b) of the 21st Century Cures Act (Pub. L. 114-255), 
enacted in 2016, amended section 3001(c) of the Public Health Service 
Act (42 U.S.C. 300jj-11(c)), and required HHS to take steps to advance 
interoperability for the purpose of ensuring full network-to-network 
exchange of health information. Specifically, Congress directed the 
National Coordinator to ``develop or support a trusted exchange 
framework, including a common agreement among health information 
networks nationally.'' Since the enactment of the 21st Century Cures 
Act, HHS has pursued development of a Trusted Exchange Framework and 
Common Agreement, or TEFCA. ONC's goals for TEFCA are: \1101\
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    \1101\ See https://www.healthit.gov/buzz-blog/interoperability/321tefca-is-go-for-launch.
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    Goal 1: Establish a universal policy and technical floor for 
nationwide interoperability.
    Goal 2: Simplify connectivity for organizations to securely 
exchange information to improve patient care, enhance the welfare of 
populations, and generate health care value.
    Goal 3: Enable individuals to gather their health care information.
    In the FY 2019 IPPS/LTCH PPS proposed rule (83 FR 20537), we 
requested comment on whether eligible hospital or CAH participation in 
TEFCA should be considered a health IT activity that could count for 
credit within the Health Information Exchange Objective in lieu of 
reporting on measures for this objective. We received comments in 
support of this concept, although some commenters disagreed indicating 
that they were concerned about adding additional burden (83 FR 41669).
    In the FY 2022 IPPS/LTCH PPS proposed rule (86 FR 25631 through 
25634), in which we proposed the HIE Bi-Directional Exchange measure 
for eligible hospitals and CAHs, we noted that the proposed attestation 
statements for the measure did not explicitly refer to participation in 
a health information network or partnering with a health information 
network that enables exchange under TEFCA. However, we stated TEFCA was 
likely to be an important way for eligible hospitals and CAHs to enable 
bi-directional health information exchange in the future and that we 
would continue to explore ways to provide further guidance or update 
this measure to align with the use of health information networks that 
enable exchange under TEFCA in the future (86 FR 25634). In the final 
rule, we noted that several commenters were encouraged to see our 
acknowledgement that this measure could align with the efforts on TEFCA 
(86 FR 45468).
    Since the publication of the FY 2022 IPPS/LTCH PPS final rule, 
important additional developments have occurred with respect to 
TEFCA.\1102\ On January 18, 2022, ONC announced a significant TEFCA 
milestone by releasing the Trusted Exchange Framework \1103\ and Common 
Agreement Version 1.\1104\ The Trusted Exchange Framework is a set of 
non-binding principles for health information exchange, and the Common 
Agreement for Nationwide Health Information Interoperability Version 1 
(also referred to as Common Agreement) is a contract that advances 
those principles. The Common Agreement and the incorporated by 
reference Qualified Health Information Network (QHIN) Technical 
Framework Version 1 (QTF) \1105\ establish the technical infrastructure 
model and governing approach for different health information networks 
and their users to securely share clinical information with each 
other--all under commonly agreed-to terms. The Common Agreement is a 
legal contract that QHINs \1106\ sign with the ONC Recognized 
Coordinating Entity (RCE),\1107\ a private-sector entity that 
implements the Common Agreement and ensures QHINs comply with its 
terms.
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    \1102\ For more information on current developments related to 
TEFCA, we refer readers to www.HealthIT.gov/TEFCA.
    \1103\ Trusted Exchange Framework (Jan. 2022), https://www.healthit.gov/sites/default/files/page/2022-01/Trusted_Exchange_Framework_0122.pdf.
    \1104\ Common Agreement for Nationwide Health Information 
Interoperability Version 1 (Jan. 2022), https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf.
    \1105\ Qualified Health Information Network (QHIN) Technical 
Framework (QTF) Version 1.0 (Jan. 2022), https://rce.sequoiaproject.org/wp-content/uploads/2022/01/QTF_0122.pdf.
    \1106\ The Common Agreement defines a QHIN as ``to the extent 
permitted by applicable SOP(s), a Health Information Network that is 
a U.S. Entity that has been Designated by the RCE and is a party to 
the Common Agreement countersigned by the RCE.'' See Common 
Agreement for Nationwide Health Information Interoperability Version 
1, at 10 (Jan. 2022), https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf.
    \1107\ In August 2019, ONC awarded a cooperative agreement to 
The Sequoia Project to serve as the initial RCE. The RCE will 
operationalize and enforce the Common Agreement, oversee QHIN-
facilitated network operations, and ensure compliance by 
participating QHINs. The RCE will also engage interested parties to 
create a roadmap for expanding interoperability over time. https://sequoiaproject.org/onc-awards-the-sequoia-project-a-cooperative-agreement-for-the-trusted-exchange-framework-and-common-agreement-to-support-advancing-nationwide-interoperability-of-electronic-health-information/.
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    The technical and policy architecture of how exchange occurs under 
TEFCA follows a network-of-networks structure, which allows for 
connections at different levels and is inclusive of many different 
types of entities at different levels, such as health information 
networks, care practices, hospitals, public health agencies, and 
Individual

[[Page 49329]]

Access Services (IAS) \1108\ Providers.\1109\ QHINs connect directly to 
each other to facilitate nationwide interoperability, and each QHIN can 
connect Participants, which can connect Subparticipants.\1110\ Compared 
to most nationwide exchange today, the Common Agreement includes an 
expanded set of Exchange Purposes beyond Treatment to include 
Individual Access Services, Payment, Health Care Operations, Public 
Health, and Government Benefits Determination \1111\--all built upon 
common technical and policy requirements to meet key needs of the U.S. 
health care system.\1112\ This flexible structure allows interested 
parties to participate in the way that makes the most sense for them, 
while supporting simplified, seamless exchange.
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    \1108\ The Common Agreement defines Individual Access Services 
(IAS) as ``with respect to the Exchange Purposes definition, the 
services provided utilizing the Connectivity Services, to the extent 
consistent with Applicable Law, to an Individual with whom the QHIN, 
Participant, or Subparticipant has a Direct Relationship to satisfy 
that Individual's ability to access, inspect, or obtain a copy of 
that Individual's Required Information that is then maintained by or 
for any QHIN, Participant, or Subparticipant.'' See Common Agreement 
for Nationwide Health Information Interoperability Version 1, at 7 
(Jan. 2022), https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf.
    \1109\ The Common Agreement defines ``IAS Provider'' as: ``Each 
QHIN, Participant, and Subparticipant that offers Individual Access 
Services.'' See Common Agreement for Nationwide Health Information 
Interoperability Version 1, at 7 (Jan. 2022), https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf.
    \1110\ For the Common Agreement definitions of QHIN, 
Participant, and Subparticipant, see Common Agreement for Nationwide 
Health Information Interoperability Version 1, at 8-12 (Jan. 2022), 
https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf.
    \1111\ For the Common Agreement definitions of Payment, Health 
Care Operations, Public Health, and Government Benefits 
Determination, see Common Agreement for Nationwide Health 
Information Interoperability Version 1, at 6-10 (Jan. 2022), https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf.
    \1112\ Exchange Purpose(s): means the reason, as authorized by 
[the] Common Agreement including the Exchange Purposes SOP, for a 
Request, Use, Disclosure, or Response transmitted via QHIN-to-QHIN 
exchange as one step in the transmission. Authorized Exchange 
Purposes are: Treatment, Payment, Health Care Operations, Public 
Health, Government Benefits Determination, Individual Access 
Services, and any other purpose authorized as an Exchange Purpose by 
the Exchange Purposes SOP, each to the extent permitted under 
Applicable Law, under all applicable provisions of [the] Common 
Agreement, and, if applicable, under the implementation SOP for the 
applicable Exchange Purpose. Definitions for each of these exchange 
purposes can be found in the Common Agreement for Nationwide Health 
Information Interoperability Version 1, at 6 (Jan. 2022), https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf.
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    The QTF,\1113\ which was developed and released by the RCE, 
describes the functional and technical requirements that a Health 
Information Network (HIN) \1114\ must fulfill to serve as a QHIN under 
the Common Agreement. The QTF specifies the technical underpinnings for 
QHIN-to-QHIN exchange and certain other responsibilities described in 
the Common Agreement. The technical and functional requirements 
described in the QTF enable information exchange modalities, including 
querying and message delivery across participating entities.
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    \1113\ Qualified Health Information Network (QHIN) Technical 
Framework (QTF) Version 1.0 (Jan. 2022), https://rce.sequoiaproject.org/wp-content/uploads/2022/01/QTF_0122.pdf.
    \1114\ ``Health Information Network'' under TEFCA has the 
meaning assigned to the term ``Health Information Network or Health 
Information Exchange'' in the information blocking regulations at 45 
CFR 171.102.
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    In general, the information to be exchanged within the TEFCA 
ecosystem allows for the use of the Health Level Seven (HL7[supreg]) 
Implementation Guide for Clinical Document Architecture (CDA[supreg]) 
Release 2: Consolidated CDA Templates for Clinical Notes (US Realm) 
Draft Standard for Trial Use Release 2.1 (C-CDA 2.1) document format, 
including data defined as part of U.S. Core Data for Interoperability 
(USCDI), with allowance for flexibility to further expand the content 
to support a multitude of use cases.\1115\ The Common Agreement and the 
QTF do not require HL7[supreg] Fast Healthcare Interoperability 
Resource (FHIR[supreg])-based exchange. TEFCA allows for the optional 
exchange of FHIR content using more traditional, established standards 
to enable the transport of that content. However, TEFCA can nonetheless 
be a strong catalyst for network enablement of FHIR maturation. To that 
end, the RCE released a three-year FHIR Roadmap for TEFCA Exchange, 
which lays out a deliberate strategy to add FHIR-based exchange under 
TEFCA in the near future.\1116\
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    \1115\ User's Guide to the Trusted Exchange Framework and Common 
Agreement--TEFCA (Jan 2022), https://rce.sequoiaproject.org/wp-content/uploads/2022/01/Common-Agreement-Users-Guide.pdf.
    \1116\ FHIR[supreg] Roadmap for TEFCA Exchange Version 1 (Jan. 
2022), https://rce.sequoiaproject.org/wp-content/uploads/2022/01/FHIR-Roadmap-v1.0_updated.pdf.
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c. New Enabling Exchange Under TEFCA Measure
    In 2022, prospective QHINs are anticipated to begin signing the 
Common Agreement and applying for designation. The RCE will then begin 
onboarding and designating QHINs to share information. In 2023, HHS 
expects interested parties across the care continuum to have increasing 
opportunities to enable exchange under TEFCA. Specifically, this would 
mean such interested parties would be: (1) signatories to either the 
Common Agreement or an agreement that meets the flow-down requirements 
of the Common Agreement (called a Framework Agreement \1117\ under the 
Common Agreement), (2) in good standing (that is not suspended) under 
that agreement, and (3) enabling secure, bi-directional exchange of 
information to occur, in production. TEFCA is expected to give 
individuals and entities easier, more efficient access to more health 
information. The Common Agreement will require strong privacy and 
security protections for all entities who elect to participate, 
including entities not covered by the Health Insurance Portability and 
Accountability Act (HIPAA).\1118\
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    \1117\ The Common Agreement defines ``Framework Agreement(s)'' 
as: ``any one or combination of the Common Agreement, a Participant-
QHIN Agreement, a Participant-Subparticipant Agreement, or a 
Downstream Subparticipant Agreement, as applicable.'' See Common 
Agreement for Nationwide Health Information Interoperability Version 
1, at 6 (Jan. 2022) https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf.
    \1118\ Common Agreement for Nationwide Health Information 
Interoperability Version 1 (Jan. 2022), https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf.
---------------------------------------------------------------------------

    By connecting to an entity that connects to a QHIN or connecting 
directly to a QHIN, an eligible hospital or CAH can share health 
information in the same manner as described in the attestation 
statements previously finalized for the HIE Bi-Directional Exchange 
measure (42 CFR 495.24(e)(6)(ii)(C)). By connecting to an entity that 
connects to a QHIN, or connecting directly to a QHIN, that supports 
sharing information on patients as part of a Framework Agreement,\1119\ 
an eligible hospital or

[[Page 49330]]

CAH would be thereby enabling bi-directional exchange with other health 
care providers as described in Statement 1 of the HIE Bi-Directional 
Exchange measure. Since participation in a Framework Agreement as a 
QHIN, Participant, or Sub-participant will be open to all qualifying 
entities and will not be restricted by use of a single vendor, a 
connection via a Framework Agreement would also satisfy the 
requirements of Statement 2 of the HIE Bi-Directional Exchange measure. 
Finally, as discussed previously, the technical requirements for 
exchanging information by entities through the Common Agreement and 
Framework Agreements utilize standards included in certified technology 
referenced under the CEHRT definition (see 42 CFR 495.4), including the 
ability to exchange and receive data using the C-CDA standard (see 
certification criteria at 45 CFR 170.315(b)(1) and (2)), thus health 
care providers participating in a Framework Agreement can use the 
functions of CEHRT to support bi-directional exchange with an HIE.
---------------------------------------------------------------------------

    \1119\ The Common Agreement defines ``Framework Agreement(s)'' 
as: ``any one or combination of the Common Agreement, a Participant-
QHIN Agreement, a Participant-Subparticipant Agreement, or a 
Downstream Subparticipant Agreement, as applicable.'' See Common 
Agreement for Nationwide Health Information Interoperability Version 
1, at 6 (Jan. 2022) https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf.
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    To offer health care providers more opportunities to earn credit 
for the Health Information Exchange Objective, and given the alignment 
between enabling exchange under TEFCA and the existing HIE Bi-
Directional Exchange measure, in the FY 2023 IPPS/LTCH PPS proposed 
rule (87 FR 28582 through 28585), we proposed to add an additional 
measure through which an eligible hospital or CAH could earn credit for 
the Health Information Exchange Objective by connecting to an entity 
that connects to a QHIN or connecting directly to a QHIN. Specifically, 
we proposed to add the following new measure to the Health Information 
Exchange Objective beginning with the EHR reporting period in CY 2023: 
Enabling Exchange Under TEFCA measure. We proposed that eligible 
hospitals and CAHs would have three reporting options for the Health 
Information Exchange Objective: (1) report on both the Support 
Electronic Referral Loops by Sending Health Information measure and the 
Support Electronic Referral Loops by Receiving and Reconciling Health 
Information measure, (2) report on the HIE Bi-Directional Exchange 
measure, or (3) report on the proposed Enabling Exchange Under TEFCA 
measure.
    We proposed that the Enabling Exchange Under TEFCA measure would be 
worth the total amount of points available for the Health Information 
Exchange Objective. Under the current scoring methodology finalized in 
the FY 2022 IPPS/LTCH PPS final rule, the Health Information Exchange 
Objective is worth a total of 40 points (86 FR 45466). We noted in the 
FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28589) that we were 
proposing changes to the scoring methodology beginning with the EHR 
reporting period in CY 2023 such that the Health Information Exchange 
Objective would be worth no more than 30 points. Therefore, under our 
proposal, the proposed Enabling Exchange Under TEFCA measure would be 
worth 30 points. We proposed this change to the scoring methodology as 
a result of our proposal in the FY 2023 IPPS/LTCH PPS proposed rule (87 
FR 28579) to make the Query of PDMP measure required and worth 10 
points. However, we stated that should we not finalize the Query of 
PDMP measure proposal, we proposed that the Enabling Exchange Under 
TEFCA measure would be worth 40 points (the current total point value 
of the Health Information Exchange Objective). In no case could more 
than 40 points total be earned for the Health Information Exchange 
Objective. In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28593 
through 28594), we proposed to remove text for the objectives and 
measures from paragraph (e) under 42 CFR 495.24 beginning in CY 2023. 
We stated that if we do not finalize that proposal, we would revise 42 
CFR 495.24(e) to reflect the addition of the proposed Enabling Exchange 
Under TEFCA measure.
    We stated that we believe the new measure for enabling exchange 
under TEFCA that we proposed would incentivize eligible hospitals and 
CAHs to exchange information by connecting directly or indirectly to a 
QHIN and support health information exchange at a national level. We 
believe that fulfillment of this measure is an extremely high value 
action. The overall TEFCA goal of establishing a universal floor of 
interoperability across the country aligns with our commitment to 
promoting and prioritizing interoperability and exchange of healthcare 
data. Incentivizing providers to enable exchange under TEFCA is a 
critical component to advancing healthcare data exchange nationwide. We 
proposed that eligible hospitals and CAHs would report the Enabling 
Exchange Under TEFCA measure by attestation, and the measure would 
require a ``yes/no'' response. A ``yes'' response would enable eligible 
hospitals and CAHs to earn the proposed 30 points allotted to the 
Health Information Exchange Objective. Further, we proposed that this 
measure may be calculated by reviewing only the actions for patients 
whose records are maintained using CEHRT. A patient's record is 
maintained using CEHRT if sufficient data were entered in the CEHRT to 
allow the record to be saved, and not rejected due to incomplete data.
    We proposed that eligible hospitals and CAHs would attest to the 
following:
     Participating as a signatory to a Framework Agreement (as 
that term is defined by the Common Agreement for Nationwide Health 
Information Interoperability as published in the Federal Register and 
on ONC's website) (in good standing, that is, not suspended) and 
enabling secure, bi-directional exchange of information to occur, in 
production, for all unique patients discharged from the eligible 
hospital or CAH inpatient or emergency department (POS 21 or 23), and 
all unique patient records stored or maintained in the EHR for these 
departments, during the EHR reporting period in accordance with 
applicable law and policy.
     Using the functions of CEHRT to support bi-directional 
exchange of patient information, in production, under this Framework 
Agreement.
    Similar to the HIE Bi-Directional Exchange measure, to successfully 
attest to this measure, we proposed the eligible hospital or CAH must 
use the capabilities of CEHRT to support bi-directional exchange under 
a Framework Agreement, which includes capabilities that support 
exchanging the clinical data within the Common Clinical Data Set (CCDS) 
or the United States Core Data for Interoperability (USCDI). This is 
consistent with the other measures under the Health Information 
Exchange Objective, which point to the use of CEHRT to support the 
exchange of the clinical data within the CCDS or the USCDI. We note 
that, beginning in 2023, when this measure would be available for 
eligible hospitals and CAHs to report eligible hospitals and CAHs must 
use certified health IT that has been updated consistent with the 2015 
Edition Cures Update, including updates to relevant certification 
criteria to reference the USCDI instead of the CCDS (85 FR 25642).
    We stated that we believe there are numerous certified health IT 
capabilities that can support bi-directional exchange under a Framework 
Agreement. For instance, participants may exchange information under a 
Framework Agreement by using technology certified to the criterion at 
45 CFR 170.315(b)(1), ``Care

[[Page 49331]]

coordination--Transitions of care,'' to transmit C-CDAs across a 
network. Where supported, participants could also utilize API 
technology certified to either the criterion at 45 CFR 170.315(g)(8), 
``Design and performance--Application access--data category request,'' 
or (g)(10), ``Design and performance--Standardized API for patient and 
population services,'' as finalized in the ONC 21st Century Cures Act 
final rule (85 FR 25742), to enable exchange of data in the USCDI from 
a participant's EHR. Additional certified health IT modules may also 
support exchange of information under a Framework Agreement for 
transitions of care, including modules certified to certification 
criteria at 45 CFR 170.315(g)(7), ``Design and performance--Application 
access--patient selection,'' and (g)(9), ``Design and performance--
Application access--all data request,'' which support information 
exchange via API; the certification criterion at 45 CFR 170.315(e)(1), 
``Patient engagement--View, download, and transmit to 3rd party,'' 
which supports patient access to their information; and the 
certification criterion at 45 CFR 170.315(g)(6), ``Design and 
performance--Consolidated CDA creation performance,'' which supports 
creation of a summary of care record. We recognize that entities that 
will connect directly or indirectly to a QHIN are currently interacting 
with health care providers using certified health IT in a variety of 
ways, and, as with the HIE Bi-Directional Exchange measure, believe 
that we should allow for substantial flexibility in how health care 
providers use certified health IT to exchange data under a Framework 
Agreement.
    We stated that the Enabling Exchange Under TEFCA measure could 
offer health care providers an alternative to earn credit for the 
Health Information Exchange Objective. The Enabling Exchange Under 
TEFCA measure would not require an eligible hospital or CAH to assess 
whether they participate in a health information exchange that meets 
the attributes of attestation Statement 2 under the HIE Bi-Directional 
Exchange measure regarding exchange across a broad network of 
unaffiliated exchange partners including those using disparate EHRs. 
These attributes are key to the goals of TEFCA, which aims to offer 
health care providers a uniform set of expectations around information 
sharing regardless of which network for information exchange they 
participate in.
    We invited public comment on these proposals.
    Comment: Many commenters expressed support for the proposal. A few 
commenters believed the measure would allow health care providers to 
have options to meet this objective that enable more broad-based data 
exchange across the health ecosystem and utilize TEFCA when 
appropriate. Many commenters expressed support for the adoption of the 
Enabling Exchange Under TEFCA measure as a means to advance health 
information exchange and interoperability on a national level. A 
commenter suggested that this improved means toward interoperability 
would help optimize patient care. Another commenter believed the 
measure would support compliance with the regulations finalized in the 
ONC 21st Cures Act Final Rule. Several commenters noted the measure 
would promote capabilities for bi-directional exchange, which they 
believed would be critical to advancing effective interoperability. A 
few commenters noted the measure would help improve health care 
provider reporting. A few commenters thanked CMS for a flexible model 
that would allow newly created programs to mature and reduce burdens 
associated with participation requirements, all while incentivizing 
participation in TEFCA.
    Response: We thank commenters for their support and feedback. We 
agree that adding a third measure under the Health Information Exchange 
Objective to offer an additional path to earn credit and accelerate the 
bi-directional exchange of health information is consistent with the 
goals of the HIE Objective and aligns with the overall goal to promote 
nationwide interoperability.
    Comment: A few commenters expressed specific support for CMS' and 
ONC's collaboration in making TEFCA a key pillar in the nationwide 
strategy to establish a ``floor'' and framework for health data 
interoperability and exchange.
    Response: We thank commenters for recognizing our continued efforts 
toward alignment and inter-agency collaboration. CMS and ONC will 
continue to collaborate and work with interested parties on TEFCA 
implementation to support advancements in health information exchange.
    Comment: A few commenters expressed support for the Enabling 
Exchange under TEFCA measure as a means to position TEFCA to be a more 
effective mechanism for data delivery for a range of important use 
cases, such as patient access and patient-centered care.
    Response: We thank commenters for their support. We believe that 
widespread adoption of the Common Agreement will facilitate patients, 
health care providers, payers, HINs, health IT developers, and other 
interested parties having access to data when and where it is needed to 
better support patient care.
    Comment: Many commenters expressed support around the optional or 
alternative nature of this measure, specifically citing concerns around 
the technical maturity and functionality of TEFCA. Several commenters 
cautioned against requiring this measure without first confirming that 
the infrastructure is mature and widespread enough to support the 
requirements. For example, a few commenters expressed concern around 
whether there would be an available QHIN in which to participate in 
time for the 2023 reporting period.
    Response: We thank the commenters for their support and acknowledge 
these concerns. We note that TEFCA will be operationalized in 2022 
before the start of the EHR reporting period in CY 2023, and that the 
Enabling Exchange under TEFCA measure was proposed as an optional 
alternative for the HIE Objective beginning with the EHR reporting 
period in CY 2023. We anticipate that TEFCA will provide a valuable 
pathway for health care providers to access information needed to 
support value-based care, care management, and population health. By 
connecting a set of nationwide, trusted health information networks and 
creating baseline legal and technical requirements that would enable 
secure information sharing across different networks nationwide, TEFCA 
has the potential to significantly reduce the need for duplicative 
network connectivity interfaces, which are costly, complex to create 
and maintain, and an inefficient use of health care provider and health 
IT developer resources. As more eligible hospitals and CAHs enable 
exchange under TEFCA and are able to report on this new measure, we 
believe technical maturity and functionality of health information 
exchange will also continue to significantly improve.
    Comment: A commenter suggested CMS should consider the impact on 
eligible hospitals and CAHs if TEFCA participation were to become 
unstable due to entities that facilitate exchange not meeting relevant 
terms and conditions and offer a hardship exception if a health care 
provider's ability to exchange information under TEFCA were to be 
limited or terminated due to suspension/termination of an entity which 
a provider relies upon in

[[Page 49332]]

order to exchange information under TEFCA. Another commenter expressed 
related concerns and stated that CMS should add exceptions to the 
Enabling Exchange under TEFCA measure to allow for potential trickle-
down effect disruptions that are beyond the control of eligible 
hospitals and CAHs.
    Response: We understand that there could be a scenario in which an 
eligible hospital or CAH is unable to exchange information under the 
Common Agreement or a Framework Agreement for the duration of a 
reporting period using a specific entity due to that entity being 
terminated or suspended under the terms of the Common Agreement or an 
associated Framework Agreement. In such cases, an eligible hospital or 
CAH could explore connecting to a different QHIN, Participant, or 
Subparticipant, which could enable the exchange of health information 
by the eligible hospital or CAH, limit the disruption, and potentially 
allow the eligible hospital or CAH to continue to attest to the 
statements required for the measure. If the eligible hospital or CAH is 
not able to connect to a different QHIN, Participant, or 
Subparticipant, the eligible hospital or CAH would likely no longer be 
able to attest ``yes'' to the statements required for the measure. In 
such cases, the eligible hospital or CAH could select one or more of 
the other measures that are included under the HIE Objective (for 
instance, the HIE Bi-directional measure could still be relevant if an 
eligible hospital or CAH can continue to use a network previously 
connected under TEFCA). We do not believe a hardship exception would be 
necessary for the Enabling Exchange Under TEFCA measure because it is 
an optional measure.
    Comment: Several commenters, in addition to expressing support for 
the proposed measure, offered additional recommendations for future 
efforts. A few commenters suggested continued collaboration among CMS, 
ONC and other entities to support TEFCA implementation. A commenter 
recommended CMS consider future measures that would further support 
health care provider interactions with payers for processes such as 
coverage requirements discovery and submission of prior authorization 
requests. Another commenter noted there are similar, already existing 
private sector solutions that seek to accomplish the same goals as this 
measure. This commenter recommended government participation in those 
efforts to expand impact of this measure. A commenter recommended CMS 
consider innovative technologies like blockchain within TEFCA.
    Response: We appreciate these recommendations. ONC and CMS will 
continue to work together to explore how TEFCA can support a wide range 
of CMS programs and activities. Furthermore, we note that ONC and CMS 
invite collaboration around TEFCA by all private sector solutions that 
are seeking to accomplish the same goal of advancing interoperability 
nationwide.
    Comment: Several commenters did not support the proposed measure. 
These commenters suggested CMS proceed with caution when adding a new 
measure related to TEFCA before additional TEFCA milestones are 
achieved, citing uncertainties around how TEFCA will function and the 
lack of details around participation to fully understand all of its 
implications. A commenter suggested CMS wait to implement the measure 
until TEFCA transitions from the ``TEFCA Transitional Council'' 
advisory group to the full ``TEFCA Governing Council,'' which, 
according to the commenter, would signal that the QHINs are operational 
and ready to govern the Common Agreement themselves. Another commenter 
cited the lack of standard operating procedures released by the RCE. 
This commenter believed that the measure could encourage eligible 
hospitals and CAHs to shift from more mature and interoperable 
networks, leading to an overall decrease in interoperability. Another 
commenter suggested CMS postpone this measure until at least CY 2024, 
after data exchange under TEFCA has been initiated.
    Response: We thank the commenters for their feedback and 
acknowledge these concerns. The Trusted Exchange Framework and the 
Common Agreement Version 1 were published in January 2022, and entities 
will soon be able to apply to be designated as QHINs. By proposing this 
as an optional measure, hospitals may opt into reporting if they are 
ready to exchange information under TEFCA, but including this optional 
measure does not create any requirement for eligible hospitals and CAHs 
to exchange information under TEFCA if they choose not to at this time 
due to concerns such as those expressed by commenters around postponing 
the measure. We are hopeful that the finalization of this proposal will 
help incentivize readiness as well as increase participation in 
exchange under TEFCA. We disagree with commenters that this measure 
should be postponed, or that the measure would pose a threat to current 
progress towards interoperability.
    Comment: A few commenters did not support the measure because they 
believed it duplicates the HIE Bi-Directional Exchange measure and 
therefore may be confusing to health care providers. These commenters 
state that the current HIE Bi-Directional measure would allow 
participants in TEFCA to claim credit for the objective. A commenter 
recommended a step-wise approach for facilities to allow a ramp up to 
compliance while meeting other interoperability requirements 
simultaneously.
    Response: We thank the commenters for their feedback and 
acknowledge this concern. We disagree that the Enabling Exchange under 
TEFCA measure is duplicative of the HIE Bi-Directional Exchange 
measure. Instead, we believe the optional Enabling Exchange under TEFCA 
measure would complement the HIE Bi-Directional Exchange measure by 
providing a convenient option for those who enable exchange under TEFCA 
to claim credit for the HIE objective. At this time, we believe, it is 
unclear what a step-wise approach would look like, given the binary 
nature of TEFCA participation, and do not believe a step-wise approach 
would more effectively support participation. We expect that many 
eligible hospitals and CAHs will already be participating in health 
information networks that will enable exchange under the TEFCA and 
would not need to engage in an incremental process in order to begin 
attesting to this measure in 2023.
    Comment: Several commenters offered recommendations for CMS with 
regard to this measure. A few commenters suggested CMS should add this 
optional measure for eligible clinicians to report under the Promoting 
Interoperability performance category of MIPS. Several commenters 
suggested CMS provide resources on the benefits of TEFCA and reasons 
why eligible hospitals and CAHs should invest in exchanging information 
under TEFCA, including how eligible hospitals or CAHs can justify 
additional investments to hospital boards and communities for exchange 
under TEFCA.
    Response: We appreciate this feedback and will take these comments 
into consideration for future rulemaking. Regarding a complementary 
proposal for eligible clinicians in MIPS, we refer readers to the 2023 
PFS NPRM, in which we have proposed a similar measure for inclusion in 
the Promoting Interoperability performance category.\1120\
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    \1120\ See https://www.federalregister.gov/public-inspection/2022-14562/medicare-and-medicaid-programs-calendar-year-2023-payment-policies-under-the-physician-fee-schedule.

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[[Page 49333]]

    Regarding resources on the benefits of TEFCA and reasons why 
eligible hospitals and CAHs should invest in exchanging information 
under TEFCA, we note that some resources are already available on this 
topic, including an information resource developed by the RCE entitled 
``The Nationwide Network Based on the Common Agreement Benefits for 
Health Care Providers Across the Continuum.'' \1121\ However, we will 
continue to collaborate with ONC and other partners to identify 
resources that can help providers to better understand the benefits of 
TEFCA, and invite public comment on what kinds of resources would be 
most useful to stakeholders.
---------------------------------------------------------------------------

    \1121\ See https://rce.sequoiaproject.org/wp-content/uploads/2022/01/RCE_Leveraging-Nationwide-Exchange_Providers_1.2-RCE-Final.pdf.
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    Comment: Commenters recommended that the alternative measure 
require eligible hospitals and CAHs to attest to facilitating exchange 
for all required Exchange Purposes, including Individual Access 
Services. A commenter recommended that CMS should increase incentives 
for the use of HIEs for Exchange Purposes beyond Treatment, so as not 
to go against information blocking rules, furthering the need for HIEs 
to facilitate data exchange for a broad range of purposes authorized by 
law. Another commenter suggested that CMS and ONC coordinate to ensure 
measures that reference TEFCA include measurement of participation in 
the Individual Access Services Exchange Purpose in addition to 
Treatment, Payment, and Health Care Operations Exchange Purposes.
    Response: For this Enabling Exchange under TEFCA measure, we have 
focused on aligning with the goals of the HIE Objective which pertains 
to care coordination and exchange between health care providers. 
However, we will consider whether this model can be applied to other 
Promoting Interoperability objectives that may align with other TEFCA 
Exchange Purposes, such as IAS, in the future. We do believe that HIEs 
can support other Exchange Purposes beyond Treatment and will continue 
to explore ways to incentivize these use cases. Finally, we do not 
believe there is any conflict between incentives for care coordination 
under this proposal and the information blocking rules. We refer 
readers to the resources around TEFCA cited in the FY 2023 IPPS/LTCH 
PPS proposed rule (87 FR 28582 through 28585).\1122\ \1123\ \1124\ 
\1125\ \1126\ \1127\ CMS will continue to explore additional 
opportunities to provide further education and outreach regarding 
TEFCA.
---------------------------------------------------------------------------

    \1122\ Blog post, 3...2...1...TEFCA is Go for Launch. Published: 
January 19, 2022. https://www.healthit.gov/buzz-blog/interoperability/321tefca-is-go-for-launch.
    \1123\ Website, Trusted Exchange Framework and Common Agreement 
(TEFCA), January 2022. https://www.HealthIT.gov/TEFCA.
    \1124\ Policy document, The Trusted Exchange Framework (TEF): 
Principles for Trusted Exchange, January 2022. Available at https://www.healthit.gov/sites/default/files/page/2022-01/Trusted_Exchange_Framework_0122.pdf.
    \1125\ Policy document, Common Agreement for Nationwide Health 
Information Interoperability Version 1, January 2022. Available at 
https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf.
    \1126\ Policy document, Qualified Health Information Network 
(QHIN) Technical Framework (QTF) Version 1.0, January 2022. 
Available at https://rce.sequoiaproject.org/wp-content/uploads/2022/01/QTF_0122.pdf.
    \1127\ Press release, ONC Awards The Sequoia Project a 
Cooperative Agreement for the Trusted Exchange Framework and Common 
Agreement to Support Advancing Nationwide Interoperability of 
Electronic Health Information. Published September 4, 2019. 
Available at https://sequoiaproject.org/onc-awards-the-sequoia-project-a-cooperative-agreement-for-the-trusted-exchange-framework-and-common-agreement-to-support-advancing-nationwide-interoperability-of-electronic-health-information/.
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    Comment: A commenter requested clarification from CMS on 
requirements for health care providers participating in multiple state 
HIEs, including hospitals near state borders.
    Response: For health care providers near state borders, there is no 
specific requirement that an eligible hospital or CAH must ensure that 
exchange enabled under TEFCA includes health care providers in a 
neighboring state with which a health care provider may need to share 
information. However, we believe that by enabling exchange across 
networks nationwide, providers exchanging information under TEFCA will 
be more likely to be able to effectively exchange information across 
state lines.
    Comment: A commenter suggested CMS should clarify that the exchange 
of patient summaries or other patient data need not occur for all 
unique patients but only as needed or requested. A commenter requested 
clarity on the definition of ``enable'' in the context of this measure.
    Response: We thank commenters for their feedback. The first 
attestation statement, as proposed, would require an eligible hospital 
or CAH to enable secure, bi-directional exchange of information to 
occur under a Framework Agreement. As we noted in our discussion of the 
final policy for the HIE Bi-Directional Measure (86 FR 45468), enabling 
bi-directional exchange does not mean that an eligible hospital or CAH 
would be required to conduct information transactions that are not 
clinically necessary. Rather, it means that an eligible hospital or CAH 
has established the capabilities necessary to complete exchanges of 
information for its patients at the appropriate time. In the case of 
the Enabling Exchange under TEFCA measure, this means the capabilities 
to exchange information under a Framework Agreement.
    Comment: Commenters requested clarity around what data is to be 
exchanged and whether there is an expectation to incorporate any of the 
exchanged information into the patient chart as with the current HIE 
Objective measure ``Support Electronic Referral Loops by Receiving and 
Reconciling Health Information,'' for instance, through reconciliation 
of parsed data from received C-CDAs.
    Response: We note that, at a minimum, TEFCA requires the exchange 
of all available data elements from USCDI Version 1.\1128\ Health care 
providers participating in a Framework Agreement and attesting to this 
measure would be required to exchange data according to the terms of 
the Framework Agreement. Regarding reconciliation of information, the 
requirements for the measure are limited to attesting to the statements 
related to engaging in bi-directional exchange under a Framework 
Agreement using the functions of CEHRT. There are no additional 
explicit requirements related to how the health care provider must 
incorporate information received under the Framework Agreement into the 
patient's record.
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    \1128\ See QHIN Technical Framework, at QTF-047 and QTF-092, 
available at https://rce.sequoiaproject.org/wp-content/uploads/2022/01/QTF_0122.pdf.
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    Comment: Another commenter requested clarity on the definition of 
``calculated'' in the context of this measure.
    Response: Thank you for the comment. We wish to clarify that the 
proposed attestation statements do not require an eligible hospital or 
CAH to perform calculations, as part of this measure, such as those 
necessary for measures that are based on reporting of a numerator and 
denominator and count unique patients or actions. Therefore, we are not 
finalizing our proposal that this measure may be calculated by 
reviewing only the actions for patients whose records are maintained 
using CEHRT, as this proposal is not relevant to the measure.
    Comment: A commenter requested CMS provide further clarity on how 
to document completion of this measure and what would suffice as a

[[Page 49334]]

demonstration of the capacity to exchange information with others 
efficiently and effectively.
    Response: In order to successfully ``complete'' this measure, 
eligible hospitals and CAHs must attest to the required statements. 
Completion of the measure would be limited to attesting to the required 
statements. For audit purposes, eligible hospitals and CAHs should 
retain evidence of their agreement with a QHIN, Participant, or 
Subparticipant that includes the terms of a Framework Agreement.
    Comment: A few commenters who supported the measure also expressed 
some concerns regarding this measure. A commenter believed CMS is 
adding technical requirements without confirming that the functionality 
of vendor systems is useful with regard to system integration, user 
interface, or workflow of the technology, placing this burden on 
eligible hospitals and CAHs. This commenter requested that CMS and ONC 
reassess measurement of compliance for vendor systems. Another 
commenter cautioned CMS against offering a measure based on enabling 
information exchange under TEFCA because they believed TEFCA 
implementation will be slow and additional milestones should be 
confirmed and achieved first.
    Response: We appreciate commenters' feedback and acknowledge these 
concerns. In order to attest to this measure, the eligible hospital or 
CAH must use the functions of CEHRT to connect directly or indirectly 
to a QHIN. As noted in the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 
28585) and reiterated above, there are currently a number of certified 
health IT capabilities that support the technical requirements for 
exchange under TEFCA, thus these capabilities would be useful for 
participation in exchange under TEFCA and earning credit under this 
measure. We believe that by finalizing this measure as optional, 
eligible hospitals and CAHs can opt in to reporting it once they are 
ready to enable exchange under TEFCA and are confident in the 
infrastructure.
    After consideration of the public comments we received, we are 
finalizing our proposal to add an additional measure through which an 
eligible hospital or CAH could earn credit for the Health Information 
Exchange Objective by connecting to an entity that connects to a QHIN 
or connecting directly to a QHIN. We are finalizing our proposal to add 
this measure to the Health Information Exchange Objective beginning 
with the EHR reporting period in CY 2023: Enabling Exchange Under TEFCA 
measure. We are finalizing our proposal that eligible hospitals and 
CAHs will now have three reporting options for the Health Information 
Exchange Objective: (1) Report on both the Support Electronic Referral 
Loops by Sending Health Information measure and the Support Electronic 
Referral Loops by Receiving and Reconciling Health Information measure, 
(2) report on the HIE Bi-Directional Exchange measure, or (3) report on 
the Enabling Exchange Under TEFCA measure. We are finalizing our 
proposal that the Enabling Exchange Under TEFCA measure would be worth 
the total amount of points available for the Health Information 
Exchange Objective. We are finalizing our proposal in the FY 2023 IPPS/
LTCH PPS proposed rule (87 FR 28589 through 28591) to change the 
scoring methodology beginning with the EHR reporting period in CY 2023, 
such that the Health Information Exchange Objective would be worth no 
more than 30 points, therefore we are finalizing our proposal that the 
Enabling Exchange Under TEFCA measure would be worth 30 points. We are 
finalizing our proposal that eligible hospitals and CAHs would report 
the Enabling Exchange Under TEFCA measure by attestation, and that the 
measure would require a ``yes/no'' response. We are not finalizing our 
proposal that this measure be calculated by reviewing only the actions 
for patients whose records are maintained using CEHRT as calculations 
are not necessary for this measure, which instead requires attestation 
to the specified statements. We are finalizing our proposal that 
eligible hospitals and CAHs would attest to the following: 
Participating as a signatory to a Framework Agreement (as that term is 
defined by the Common Agreement for Nationwide Health Information 
Interoperability as published in the Federal Register and on ONC's 
website) (in good standing that is, not suspended) and enabling secure, 
bi-directional exchange of information to occur, in production, for all 
unique patients discharged from the eligible hospital or CAH inpatient 
or emergency department (POS 21 or 23), and all unique patient records 
stored or maintained in the EHR for these departments, during the EHR 
reporting period in accordance with applicable law and policy; and 
using the functions of CEHRT to support bi-directional exchange of 
patient information in production, under this Framework Agreement. We 
refer readers to the FY 2023 IPPS/LTCH PPS proposed rule for additional 
information on certified health IT capabilities that can support bi-
directional exchange under a Framework Agreement (87 FR 28582 through 
28585). Additionally, we are finalizing our proposal in the FY 2023 
IPPS/LTCH PPS proposed rule (87 FR 28593 through 28594) to remove 
associated regulatory text, therefore, we will not be updating 42 CFR 
495.24(e) to reflect the addition of the Enabling Exchange Under TEFCA 
measure.
5. Public Health and Clinical Data Exchange Objective
a. Background
    The Medicare Promoting Interoperability Program for eligible 
hospitals and CAHs has been an important mechanism for encouraging 
healthcare data exchange for public health purposes through the Public 
Health and Clinical Data Exchange Objective. Effective responses to 
public health events, such as the COVID-19 PHE, require fast, accurate 
exchange of data between health care providers and Federal, state, and 
local public health agencies (PHAs). Health care providers collect 
these data for patient care, and PHAs need them to protect the public, 
whether to track an outbreak, initiate contact tracing, find gaps in 
vaccine coverage, or pinpoint the source of a foodborne outbreak.
    There are six measures under the Public Health and Clinical Data 
Exchange Objective: Immunization Registry Reporting, Syndromic 
Surveillance Reporting, Electronic Case Reporting, Electronic 
Reportable Laboratory (ELR) Result Reporting, Public Health Registry 
Reporting, and Clinical Data Registry Reporting. For background on this 
objective and its associated measures, we refer readers to the FY 2019 
IPPS/LTCH PPS final rule (83 FR 41665 through 41667), and the FY 2022 
IPPS/LTCH PPS final rule (86 FR 45470 through 45479). In the FY 2022 
IPPS/LTCH PPS final rule (86 FR 45470 through 45479), we finalized the 
requirement for eligible hospitals and CAHs to report four of the six 
of the measures associated with the Public Health and Clinical Data 
Exchange Objective, beginning with the EHR reporting period in CY 2022: 
Syndromic Surveillance Reporting; Immunization Registry Reporting; 
Electronic Case Reporting; and Electronic Reportable Laboratory Result 
Reporting. These four measures will put PHAs on better footing for 
future health threats and a long-term COVID-19 pandemic recovery by 
strengthening three important public health functions: (1) early 
warning surveillance, (2) case surveillance, and (3) vaccine uptake. 
Requiring these measures will enable nationwide

[[Page 49335]]

syndromic surveillance for early warning of emerging outbreaks and 
threats; automated case and laboratory reporting for fast public health 
response; and local and national visibility on immunization uptake so 
PHAs can tailor vaccine distribution strategies.
b. Modifications to the Reporting Requirements for the Public Health 
and Clinical Data Exchange Objective: Antimicrobial Use and Resistance 
(AUR) Surveillance Measure
    Antimicrobial-resistant (AR) infections are caused by pathogens 
that no longer respond to the drugs designed to kill them and directly 
threaten patient and population health. An effective national response 
to the threat presented by antimicrobial resistant bacteria requires 
robust systems for systematically collecting, analyzing, and using 
antimicrobial use and resistance data to direct action.
    Each year in the United States, more than three million people are 
infected by an antimicrobial-resistant pathogen or C. difficile (an 
opportunistic pathogen associated with antimicrobial use), and nearly 
50,000 people die.\1129\ As more pathogens become resistant to 
available antimicrobials, options for reliably and rapidly treating 
infections--including pneumonias, foodborne illnesses, and healthcare-
associated infections--become increasingly limited, more expensive and, 
in some cases, nonexistent. The CDC has found that one-third to one-
half of all antimicrobials used in inpatient and outpatient settings 
are either unnecessary or prescribed incorrectly.\1130\ The misuse and 
overuse of antimicrobials both facilitates the emergence of drug-
resistant pathogens and exposes patients to needless risk for adverse 
effects. AR infections can also complicate the response to and recovery 
from other serious health risks, such as COVID-19. Rates of AR 
infections have increased in healthcare settings since the beginning of 
the COVID-19 pandemic, reversing previous prevention successes such as 
declines of AR infections by as much as 30 percent prior to the 
pandemic.\1131\ Additionally, Methicillin-resistant Staphylococcus 
aureus (MRSA) infections increased five consecutive quarters from 2020 
to 2021, including some quarter over quarter increases of 39 
percent.\1132\ Strengthening of infection prevention and control and 
antibiotic stewardship is needed to address these challenges and ensure 
a solid foundation for future public health emergencies.
---------------------------------------------------------------------------

    \1129\ CDC. Antibiotic Resistance Threats in the United States, 
2019. Atlanta, GA: U.S. Department of Health and Human Services, 
CDC; 2019.
    \1130\ CDC. Antibiotic Use in the United States, 2018 Update: 
Progress and Opportunities. Atlanta, GA: US Department of Health and 
Human Services, CDC; 2019.
    \1131\ CDC. 2020 National and State Healthcare-Associated 
Infections Progress Report. Atlanta, GA: U.S. Department of Health 
and Human Services, CDC; 2021.
    \1132\ Weiner-Lastinger, Lindsey M., et al. ``The Impact of 
Coronavirus Disease 2019 (COVID-19) on Healthcare-Associated 
Infections in 2020: A Summary of Data Reported to the National 
Healthcare Safety Network.'' Infection Control & Hospital 
Epidemiology, vol. 43, no. 1, 2022, pp. 12-25., doi:10.1017/
ice.2021.362.
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    As outlined in the National Action Plan for Combating Antibiotic-
Resistant Bacteria (CARB), 2020-2025,\1133\ an effective national 
response to the threat presented by AR bacteria and fungi depends in 
part on slowing the emergence of new resistant threats and preventing 
the spread of existing resistant infections. Successfully meeting this 
goal, in turn, requires robust systems for collecting, analyzing, and 
using AUR data to direct action. Systematically collecting AUR data 
also helps inform the availability and potential need for new 
antibiotics to address emerging forms of resistance.
---------------------------------------------------------------------------

    \1133\ Office of the Assistant Secretary for Planning and 
Evaluation (ASPE). (2020). National Action Plan for Combatting 
Antibiotic-Resistant Bacteria, 2020-2025. Available at: https://aspe.hhs.gov/reports/national-action-plan-combating-antibiotic-resistant-bacteria-2020-2025.
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    Antimicrobial use (AU) data delivered to antimicrobial stewardship 
programs (ASPs) enable stewards to develop, select, and assess 
interventions aimed at optimizing antimicrobial prescribing. These 
interventions, in turn, serve to improve antimicrobial treatment 
effectiveness, protect patients from harms caused by unnecessary 
antimicrobial exposure, and curb antimicrobial resistance associated 
with prophylactic and therapeutic excess. Studies have shown that ASPs 
can help slow the emergence of antimicrobial resistance while 
optimizing treatment and minimizing costs--all in support of safe and 
appropriate care for patients.
    Antimicrobial resistance data can aid in clinical decision making 
(hospital cumulative antibiograms) and direct transmission prevention 
and antimicrobial stewardship efforts. With timely and complete 
reporting, these data can also facilitate rapid identification and 
control of potential outbreaks, as well as longer term assessment of 
progression or improvement to guide public health response efforts. 
Currently, acute care hospitals and CAHs voluntarily report to CDC's 
National Healthcare Safety Network's (NHSN) AUR Module with 
approximately 2000 eligible hospitals and 1000 CAHS reporting on AUR 
NHSN. Compared to the hospitals that have not reported AUR data, those 
that reported were more likely to be larger and teaching hospitals.
    The extensive voluntary participation in NHSN's AUR surveillance, 
which calls for hospitals to buy or build an AUR reporting solution, 
indicates that thousands of hospitals see value in NHSN's AUR 
surveillance. However, incomplete participation in NHSN's AUR 
surveillance limits the generalizability of the AUR data: The data are 
subject to selection bias and do not provide a comprehensive national 
picture. Other comparable NHSN reporting pathways--such as those used 
to report data on blood stream infections, urinary tract infections, 
and other healthcare-associated infections--are required under CMS 
quality reporting and value-based payment programs, including the 
Hospital Value-Based Purchasing (VBP) and Hospital-Acquired Condition 
(HAC) Reduction Programs. In the Hospital VBP and HAC Reduction 
Programs, the reporting coverage and compliance with NHSN measures is 
routinely approximately 97 percent. The benefits of monitoring AUR data 
for patient care and public health are most likely to be achieved when 
data collection and analysis are systematic, standardized, and achieve 
complete coverage across eligible facilities. In fact, as more 
hospitals participate, the system becomes better at detecting emerging 
threats as the network for data collection grows.
    We believe that requiring an AUR measure under the Medicare 
Promoting Interoperability Program would enable the development of a 
true national picture of the threat posed by antimicrobial overuse and 
resistance. Requiring AUR reporting through CDC's NHSN would produce 
inpatient AU and AR benchmarks that can be used to guide clinical and 
public health action and enable a true national picture of the threat 
posed by antimicrobial overuse and resistance. In the FY 2023 IPPS/LTCH 
PPS proposed rule (87 FR 28586 through 28587), we proposed the 
following new AUR Surveillance measure under the Public Health and 
Clinical Data Exchange Objective:
    AUR Surveillance measure: The eligible hospital or CAH is in active 
engagement with CDC's National Healthcare Safety Network (NHSN) to 
submit antimicrobial use and resistance (AUR) data for the EHR 
reporting period and receives a report from NHSN indicating their 
successful submission of AUR data for the EHR reporting period.
    We proposed to require eligible hospitals and CAHs to report this

[[Page 49336]]

measure beginning with the EHR reporting period in CY 2023. Eligible 
hospitals and CAHs that report a ``yes'' response or an exclusion for 
which they are eligible would receive credit for reporting the measure. 
Eligible hospitals and CAHs that report a ``no'' response or fail to 
report any response would not receive credit for reporting the measure 
and would fail to satisfy the Public Health and Clinical Data Exchange 
Objective. No additional points would be associated with the reporting 
of this measure, but it would be one of five required measures required 
to satisfy the Public Health and Clinical Data Exchange Objective. See 
the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28589) for further 
detail on the proposals and section IX.H.6 of this final rule for the 
finalized modification of the scoring of this objective.
    For purposes of this proposed measure, we proposed eligible 
hospitals and CAHs must use technology certified to the criterion at 45 
CFR 170.315(f)(6), ``Transmission to public health agencies--
antimicrobial use and resistance reporting.'' We also stated we were 
aware of an updated version of the standard referenced in the criterion 
\1134\ and that we would work with our partners at CDC and ONC to 
consider avenues for addressing use of this specification within the 
ONC Health IT Certification program. We provide additional information 
on use of this updated version below.
---------------------------------------------------------------------------

    \1134\ https://www.hl7.org/implement/standards/product_brief.cfm?product_id=426.
---------------------------------------------------------------------------

    We proposed three exclusions for the AUR Surveillance measure as 
follows: the eligible hospital or CAH: (1) Does not have any patients 
in any patient care location for which data are collected by NHSN 
during the EHR reporting period; (2) Does not have electronic 
medication administration records (eMAR)/barcoded medication 
administration (BCMA) records or an electronic admission discharge 
transfer (ADT) system during the EHR reporting period; or (3) Does not 
have an electronic laboratory information system (LIS) or electronic 
ADT system during the EHR reporting period (87 FR 28587). We anticipate 
reevaluating exclusions #2 and #3 for future EHR reporting periods. The 
AUR Surveillance measure would leverage the standards and functionality 
included in certified technology referenced under the CEHRT definition, 
including the ability to transmit to PHAs for antimicrobial use and 
resistance reporting.
    We invited public comment on these proposals. We also invited 
comments on the feasibility of the timeline and any additional 
exclusions that we should consider for this measure for proposal in 
future rulemaking.
    Comment: Many commenters supported the proposal to add the AUR 
Surveillance measure agreeing on the critical role this measure would 
play in improving antibiotic use and reducing antibiotic resistance, 
facilitating targeting areas for improvement, providing data critical 
to tracking threats and identifying trends nationwide, informing 
clinicians, public health agencies, government, and policymakers alike. 
Several commenters noted the importance of this measure to provide a 
much needed national, generalizable comparison and benchmarks. A few 
commenters noted the utility of this data to potentially drive 
increased investment from Congress to address the rising threat of 
adverse events such as antibiotic resistance.
    Response: We appreciate commenters' support of the proposal to 
require the AUR Surveillance measure under the Public Health and 
Clinical Data Exchange Objective. We believe that this measure will 
help produce inpatient AU and AR benchmarks that can be used to guide 
clinical and public health action and enable a true national picture of 
the threat posed by antimicrobial overuse and resistance.
    Comment: Many commenters did not support the proposal to add the 
AUR Surveillance measure. Several commenters stated that the 
implementation timeline was too ambitious and that the financial burden 
on health care providers was substantial. A commenter pointed out that 
it is already too late to include this in the budget for CY 2023 which 
has, at the time of the FY 2023 IPPS/LTCH PPS proposed rule being 
published, already been approved. A few commenters highlighted that the 
majority of CAHs will not be ready and thus find themselves at a 
substantial disadvantage. A few commenters noted that eligible 
hospitals are still dealing with burden related to the PHE and these 
proposals overwhelm systems already tasked with substantial COVID-19 
related reporting and clinical requirements. Many commenters offered 
recommendations to delay the adoption of the AUR Surveillance measure 
to the Public Health and Data Exchange Objective with most recommending 
a delay of at least one year and several recommending alternative 
periods of delay. A commenter requested that the adoption of the 
measure be delayed until CEHRT criteria are adopted and vendors and 
hospitals have sufficient time to implement the CEHRT criteria. A few 
commenters requested adoption be delayed until the end of the PHE. 
Several commenters recommend making the measure optional to allow time 
for implementation. A commenter noted that smaller and resource-limited 
facilities may need a phase in time not to exceed two years and another 
commenter recommended a phase-in time with stronger incentives.
    Response: We thank the commenters for their feedback. We believe 
that the AUR Surveillance measure is critical to stem AR infections 
nationwide, by providing the necessary AUR data to direct action. 
However, we also heard very clearly from commenters that eligible 
hospitals and CAHs continue to face enormous operational challenges as 
a result of the ongoing PHE.
    We understand that many commenters believe that more time may be 
needed for health care providers and EHR vendors to implement the 
necessary changes in workflows, infrastructure and functionality to 
report the AUR Surveillance measure. We recognize more time may be 
beneficial for eligible hospitals and CAHs to implement the necessary 
infrastructure. Therefore, we are delaying our adoption of this measure 
by one year, so that it will be included in the Public Health and 
Clinical Data Exchange Objective and will be a required measure 
beginning with the EHR reporting period in CY 2024. Regarding the 
concern over a lack of applicable certification criteria referenced in 
the CEHRT definition, we inform readers that the applicable criteria is 
available in ``Transmission to public health agencies--antimicrobial 
use and resistance reporting'' in 45 CFR 170.315(f)(6), and was 
finalized in the ``2015 Edition Health Information Technology (Health 
IT) Certification Criteria, 2015 Edition Base Electronic Health Record 
(EHR) Definition, and ONC Health IT Certification Program 
Modifications'' final rule published on October 16, 2015 (80 FR 62668).
    Comment: A few commenters recommended adding exceptions for 
hospitals when they encounter situations related to bi-directional 
exchange that are outside their control such as encountering 
deficiencies in the state/local public health agency. A commenter 
recommended adding an exclusion for eligible hospitals and CAHs using 
CEHRT that does not include technology certified per Sec.  
170.315(f)(6) at the beginning of the EHR reporting period. This type 
of exclusion would be similar to the one year exclusion that is 
available for MIPS eligible clinicians for the Electronic Case 
Reporting measure under the

[[Page 49337]]

Public Health and Clinical Data Exchange Objective for those clinicians 
in CY 2022 using CEHRT that does not include technology certified to 
the electronic case reporting certification criterion. Some commenters 
expressed concern that their ability to successfully fulfill this 
measure is limited based on dependence their health IT vendor team, and 
potentially by delays at the state level.
    Response: We thank commenters for their feedback.
    We do not believe that additional exclusions related to state and 
local readiness to engage in bi-directional exchange are necessary, as 
data within the AUR measure are reported directly to CDC through NHSN. 
We believe that granting eligible hospitals and CAHs an additional year 
to prepare to report on this measure will alleviate the concerns that 
the commenters have raised. Any health IT vendors that have not yet 
certified under 45 CFR 170.315(f)(6) ``Transmission to public health 
agencies--antimicrobial use and resistance reporting,'' will have 
sufficient time to update their product and complete certification due 
to the one year delay.
    Comment: A few commenters requested clarification around the 
specific standards submitters are required to use, additional 
information on a minimum period for hospitals to transmit data, and 
technical assistance and support during the implementation period.
    Response: As noted in the FY 2023 IPPS/LTCH PPS proposed rule (87 
FR 28587), for purposes of this measure, we proposed that eligible 
hospitals and CAHs must use technology certified to the criterion at 45 
CFR 170.315(f)(6), ``Transmission to public health agencies--
antimicrobial use and resistance reporting.'' This certification 
criterion references the ``HL7[supreg] Implementation Guide for 
CDA[supreg] Release 2--Level 3: Healthcare Associated Infection (HAI) 
Reports, Release 1, U.S. Realm, August 2013'' implementation 
specification, adopted at Sec.  170.205(r)(1).
    We note that an updated version of this this implementation 
specification has been approved under ONC's Standards Version 
Advancement Process. The Standards Version Advancement Process (SVAP) 
permits health IT developers to voluntarily update health IT products 
certified under the ONC Health IT Certification Program to newer 
versions of adopted standards and implementation specifications (85 FR 
25775). Specifically, as part of the 2022 SVAP cycle, ONC has approved 
the use of ``HL7 CDA[supreg] R2 Implementation Guide: Healthcare 
Associated Infection (HAI) Reports, Release 3--US Realm, December 
2020'' for the ``Transmission to public health agencies--antimicrobial 
use and resistance reporting'' at 45 CFR 170.315(f)(6). Health IT 
developers may begin voluntarily incorporating this specification into 
Certified Health IT Modules beginning August 29, 2022.
    Our experience with NHSN has shown that reporting is not just 
broadly feasible but also highly valuable for hospitals and their 
state/local public health partners. As previously noted, over 2000 
hospitals currently submit AU and/or AR data through CDC's NHSN. 
Eligible hospitals and CAHs that do encounter challenges submitting, 
reviewing, interpreting and using their AU and AR data have access to a 
robust suite of training and technical assistance resources, as well as 
one-on-one assistance from subject matter experts via a help desk 
system. NHSN gives eligible hospitals and CAHs the ability to see and 
analyze their data in real-time, as well as share that information with 
clinicians and facility leadership, as well as with other facilities 
(for example, a multi-hospital system) and partners such as health 
departments or quality improvement organizations. The measure must be 
fulfilled during the eligible hospital or CAH's EHR reporting period 
but it is hoped that once they are able to submit data that they will 
do so throughout the year.
    Comment: Several commenters offered suggestions to support health 
care provider implementation and reduce participant burden associated 
with validation. A commenter recommended NHSN and CMS validation 
reports be aligned to reduce burden on health care providers. A 
commenter recommended that RxNorm codes be used. Finally, a commenter 
recommended that CMS allow health care providers to alternatively 
report on any 5 of the 7 available measures in the Public Health and 
Clinical Data Exchange Objective to achieve the 10 points.
    Response: We thank them for their comments and agree with the 
importance of ensuring eligible hospitals and CAHs have the resources 
and support they need to meet requirements without undue reporting 
burden. CDC already offers a wide array of tools and resources to 
support onboarding, testing and validation, and data submission (see 
https://www.cdc.gov/nhsn/pdfs/cda/PHDI-Facility-Guidance-508.pdf). And 
CDC and CMS will work together to build upon these resources as needed 
to support health care provider participation. Similarly, CDC and CMS 
will work together to align and streamline accountability processes 
(for example, reporting validation; (letters from the NHSN to the 
hospitals to serve as proof of their active engagement). With respect 
to the commenter's suggestion that the AUR measure support the use of 
RxNorm codes, the CDC has confirmed that the measure already does so. 
Finally, as we have previously discussed, we believe that requiring 
reporting for specific measures under the Public Health and Clinical 
Data Exchange objective is necessary to better prepare for and support 
public health responses to health threats. For a thorough discussion of 
our reasoning for selecting each required measure we refer readers to 
the FY 2022 IPPS/LTCH final rule (86 FR 45470 through 45479).
    After consideration of the public comments we received, we are 
finalizing our proposal to require eligible hospitals and CAHs to 
report the AUR surveillance measure, with the modification that it will 
be required beginning with the EHR reporting period in CY 2024. 
Eligible hospitals and CAHs that report a ``yes'' response or an 
exclusion for which they are eligible will receive credit for reporting 
the measure. Eligible hospitals and CAHs must use technology certified 
to the criterion at 45 CFR 170.315(f)(6), ``Transmission to public 
health agencies--antimicrobial use and resistance reporting.'' We are 
adopting three exclusions as proposed for the AUR Surveillance measure 
as follows: the eligible hospital or CAH: (1) Does not have any 
patients in any patient care location for which data are collected by 
NHSN during the EHR reporting period; (2) Does not have electronic 
medication administration records (eMAR)/barcoded medication 
administration (BCMA) records or an electronic admission discharge 
transfer (ADT) system during the EHR reporting period; or (3) Does not 
have an electronic laboratory information system (LIS) or electronic 
ADT system during the EHR reporting period.
c. Revisions to Active Engagement
(1) Background
    The Medicare Promoting Interoperability Program has been an 
important mechanism for encouraging data exchange between health care 
providers and PHAs through the Public Health and Clinical Data Exchange 
Objective. In the FY 2022 IPPS/LTCH PPS final rule (86 FR 45470 through 
45479), we finalized beginning with the EHR reporting period in CY 
2022, eligible hospitals and CAHs must report

[[Page 49338]]

on the four required measures to obtain points under the Public Health 
and Clinical Data Exchange Objective: (1) Syndromic Surveillance 
Reporting; (2) Immunization Registry Reporting; (3) Electronic Case 
Reporting; and, (4) Electronic Reportable Laboratory Result Reporting. 
We believe these required measures will motivate health IT vendors to 
implement the necessary capabilities in their products and encourage 
eligible hospitals and CAHs to engage in the reporting activities 
described in the measures.
    Despite these gains, ensuring the nation's thousands of hospitals 
implement and initiate data production for these vital public health 
capabilities remains an ongoing and important effort. The Medicare 
Promoting Interoperability Program provides an opportunity to continue 
strengthening the incentives for eligible hospitals and CAHs to engage 
in these essential reporting activities. Without adequate incentives, 
it will be difficult to attain the comprehensive data exchange needed 
to ensure fast, complete, actionable data in response to future public 
health threats.
    In the EHR Incentive Program Stage 3 final rule (80 FR 62862 
through 62864), beginning with the EHR reporting period in 2016, we 
established a definition for active engagement under the Public Health 
and Clinical Data Registry Reporting Objective. Active engagement is 
defined as when an eligible hospital or CAH is in the process of moving 
towards sending ``production data'' to a public health agency or 
clinical data registry, or is sending production data to a public 
health agency or clinical data registry. We noted that the term 
``production data'' refers to data generated through clinical processes 
involving patient care and it is used to distinguish between this data 
and ``test data'' which may be submitted for the purposes of enrolling 
in and testing electronic data transfers. We established the following 
three options for eligible hospitals and CAHs to demonstrate active 
engagement:
    Option 1--Completed registration to submit data: The eligible 
hospital or CAH registered to submit data with the PHA or, where 
applicable, the clinical data registry (CDR) to which the information 
is being submitted; registration was completed within 60 days after the 
start of the EHR reporting period; and the eligible hospital or CAH is 
awaiting an invitation from the PHA or CDR to begin testing and 
validation. Eligible hospitals or CAHs that have registered in previous 
years do not need to submit an additional registration to meet this 
requirement for each EHR reporting period.
    Option 2--Testing and validation: The eligible hospital or CAH is 
in the process of testing and validation of the electronic submission 
of data. Eligible hospitals or CAHs must respond to requests from the 
PHA or, where applicable, the CDR within 30 days; failure to respond 
twice within an EHR reporting period would result in that health care 
provider not meeting the measure.
    Option 3--Production: The eligible hospital or CAH has completed 
testing and validation of the electronic submission and is 
electronically submitting production data to the PHA or CDR. For more 
information about the current options for active engagement, we refer 
readers to the EHR Incentive Program Stage 3 final rule (80 FR 62862 
through 62864).
(2) Revision to Options for Active Engagement
    The three active engagement options provided flexibility for 
eligible hospitals and CAHs to meet the measures under the Public 
Health and Clinical Data Exchange Objective in a variety of ways, but 
they did not provide an incentive to move through the options and get 
to option 3, production, where there is the ongoing electronic 
submission of data. Option 1, completed registration to submit data, 
was an important option in 2016 as many PHAs and CDRs were starting to 
come online, and thus the provision of this option recognized that many 
eligible hospitals and CAHs were just beginning to engage in electronic 
data exchange with PHAs and CDRs. Now many years have passed, and we 
believe that eligible hospitals and CAHs have had ample time to 
complete option 1.
    Thus, in the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28588), we 
proposed to consolidate current options 1 and 2 into one option 
beginning with the EHR reporting period in CY 2023. We did not propose 
any substantive changes to the individual options or requirements for 
selecting the individual options; rather, we would combine current 
options 1 and 2 into a single option, as follows:
    1. Proposed Option 1. Pre-production and Validation (a combination 
of current option 1, completed registration to submit data, and current 
option 2, testing and validation);
    2. Proposed Option 2. Validated Data Production (current option 3, 
production).
    Eligible hospitals and CAHs must demonstrate their level of active 
engagement as either proposed Option 1 (pre-production and validation) 
or proposed Option 2 (validated data production) to fulfill each 
measure. We invited public comment on these proposed changes to the 
options for active engagement.
    Comment: Many commenters supported the proposal to modify the 
active engagement options under the Public Health and Clinical Data 
Exchange Objective.
    Response: We thank commenters for their support of our proposal to 
modify the options of active engagement under the Public Health and 
Clinical Data Exchange Objective.
    Comment: A commenter requested clarification on the consolidation 
of options 1 and 2 for the levels of active engagement with regard to 
eligible hospitals and CAHs that have completed registration but not 
yet begun testing and validation.
    Response: The proposed active engagement option 1: Pre-Production 
and Validation includes both the completion of registration to submit 
data with the PHA or CDR, as applicable, and being in the process of 
testing and validation of the electronic submission of data. Upon 
receiving an invitation from the PHA or CDR to begin testing and 
validation, the eligible hospital or CAH should begin testing and 
validation, as we understand the validation process can take some time. 
If, at any point in the process, an eligible hospital or CAH encounters 
a lack of readiness on the part of the PHA or CDR, the eligible 
hospital or CAH could consider whether it could report an exclusion for 
one or more of the measures associated with the Public Health and 
Clinical Data Exchange Objective.
    Comment: A few commenters expressed concern that eligible hospitals 
and CAHs are determining their active engagement status without input 
from the appropriate public health agency. These commenters requested 
that CMS provide further guidance to define the active engagement 
option 2 criteria, and identify at what point an eligible hospital or 
CAH can move from active engagement option 1 to active engagement 
option 2.
    Response: To move from Active Engagement Option 1: Pre-production 
and Validation, to Active Engagement Option 2: Validated Data 
Production, the eligible hospital or CAH must finish validation. 
Validation is an effort to ensure that the data exchanged with a public 
health agency is high quality and useful, and meets the appropriate HL7 
implementation guide standard. Only the PHA or CDR can confirm 
validation

[[Page 49339]]

has been completed and a ``production'' state has been reached.
    Comment: Several commenters did not support the proposal, stating 
that the reduction of levels obscures the necessary granularity of 
where hospitals are in the onboarding process. The commenters stated 
that since eligible hospitals and CAHs do not control the onboarding 
process, and that this varies based on the resources at the public 
health departments, it is important to distinguish between those who 
are waiting to begin testing and validation from those who are actively 
engaged in testing and validation.
    Response: CMS does not agree that it is important to differentiate 
between those who are registered and those who have begun testing and 
validation. CMS has collaborated with the PHA community and has 
received comments that PHAs currently do not have any waitlists, and 
the eligible hospitals or CAHs who register are immediately invited to 
begin testing and validation. CMS agrees that eligible hospitals and 
CAHs should not be held accountable for actions outside of their 
control. However, at this time, registration is no longer a meaningful 
status, as PHAs are ready to begin testing and validation with those 
who register right away. CMS is not concerned with the loss of 
granularity, and we believe that this will facilitate easier reporting 
from our partners.
    Additionally, we do not believe that allowing eligible hospitals 
and CAHs to remain at the registration stage fulfills the intent of the 
public health measures. Validation is critical as it ensures that the 
data from eligible hospitals and CAHs meets the needs of public health 
for both routine and emergency reporting. This is true across the 
Electronic Case Reporting measure, the Electronic Reportable Laboratory 
Result Reporting measure, the Syndromic Surveillance Reporting measure, 
the Immunization Registry Reporting measure, and in the future, the AUR 
Surveillance measure. In addition, public health capabilities for 
onboarding may have been delayed at the state level due to the COVID-19 
pandemic. As such, CDC is providing funding for PHAs to improve and 
modernize their data infrastructure, which will result in more rapid 
testing and validation.
    After consideration of the public comments we received, we are 
finalizing our proposal to consolidate current options 1 and 2 into a 
new combined option called Pre-production and Validation and renaming 
the current option 3 as Validated Data Production beginning with EHR 
reporting periods in CY 2023. Our goal continues to be that all 
eligible hospitals and CAHs will be at the Validated Data Production 
option as successful exchange of data is needed because that is where 
that data can be utilized to combat current and future PHEs.
(3) Reporting Requirement for Level of Engagement
    Although we established the active engagement options, eligible 
hospitals and CAHs currently are not required to report their level of 
active engagement for any of the measures associated with the Public 
Health and Clinical Data Exchange Objective. During the recent COVID-19 
PHE, we recognized the importance of public health reporting, as 
discussed further in the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 
28585 through 28586), and we believe that knowing the level of active 
engagement that an eligible hospital or CAH selects would provide 
information on the types of registries and geographic areas with health 
care providers in the Pre-production and Validation stage. Our goal is 
for all health care providers nationwide to be at the Validated Data 
Production stage so that data will be actively flowing and public 
health threats can be monitored. Therefore, as proposed in the FY 2023 
IPPS/LTCH PPS proposed rule (87 FR 28588), for the Public Health and 
Clinical Data Exchange Objective, in addition to submitting responses 
for the required measures and any optional measures an eligible 
hospital or CAH chooses to report, we proposed to require eligible 
hospitals and CAHs to submit their level of active engagement, either 
Pre-production and Validation or Validated Data Production) for each 
measure they report beginning with the EHR reporting period in CY 2023. 
We believe that this information regarding the level of active 
engagement would be helpful as it would enable HHS to identify 
registries and PHAs which may be having difficulty onboarding eligible 
hospitals and CAHs and moving them to the Validated Data Production 
level. If we can identify the PHAs with which eligible hospitals and 
CAHs are encountering difficulties, we believe we will be able to 
identify the barriers that prevent them from moving to the Validated 
Data Production level and work to develop solutions to overcome the 
barriers.
    We invited public comment on the proposal to require submission of 
the level of active engagement.
    Comment: Many commenters supported the proposal to require eligible 
hospitals and CAHs to report level of active engagement on measures in 
the Public Health and Clinical Data Exchange Objective. Many commenters 
cited that bi-directional data exchange is integral to achieve 
meaningful impacts in health care delivery and the importance of 
reporting the level of active engagement to promote transparency of 
active engagement status at a national level.
    Response: We thank the commenters for their support of our proposal 
to require eligible hospitals and CAHs to report their level of active 
engagement on measures in the Public Health and Clinical Data Exchange 
Objective. We agree with commenters that bi-directional data exchange 
is integral in health care delivery.
    Comment: A commenter requested that hospitals be required to 
provide proof from a public health agency of their active engagement 
status through a letter or other forms of acknowledgement as through 
HL7 messages and emails indicating confirmation.
    Response: At this time, eligible hospitals and CAHs attest to CMS. 
PHAs have no role in the attestation process. Many eligible hospitals 
and CAHs request documentation from the PHA to support their active 
engagement status, which is used in case of an audit by CMS. CMS agrees 
that this is a best practice. CMS does acknowledge the desire of PHAs 
to become more engaged in the attestation process for eligible 
hospitals and CAHs but to date we have not established what that 
relationship might be. However, eligible hospitals and CAHs will be 
required to report their level of active engagement for the first time. 
If CMS learns that there is a mismatch between the active engagement 
records at PHAs and the active engagement status provided through 
attestation, CMS may consider making a future change to the attestation 
process. No change will be made until CMS has more evidence about 
eligible hospitals' and CAHs' self-reported active engagement status.
    Comment: A few commenters did not support the proposal to require 
reporting the Active Engagement option selected under the Public Health 
and Clinical Data Exchange Objective and requested this not be required 
until the technology can facilitate the reporting. Some raised concerns 
that PHAs may not be able to offer documentation of level of active 
engagement in a reasonable amount of time to support compliance with a 
90-day reporting period. Commenters also recommended active engagement 
be demonstrated with information provided either by the eligible 
hospital or CAH, or the PHA, or that CMS incentivize PHAs to turn

[[Page 49340]]

around this information in a timely manner. A few commenters requested 
that CMS provide further guidance illustrating expectations for 
completion of active engagement options and how eligible hospitals and 
CAHs can prove their active engagement status. A commenter requested 
that CMS allow eligible hospitals and CAHs at least one year of stable 
reporting of public health measures without implementing this active 
engagement reporting requirement. Many commenters supported an 
exclusion for situations in which the state or public health department 
has not declared readiness or lacks resources for timely onboarding.
    Response: We acknowledge commenters' concerns regarding our 
proposal to require eligible hospitals and CAHs to report their level 
of active engagement for each Public Health and Clinical Data Exchange 
measure. However, we believe that this information will be extremely 
valuable to better understand progress with reporting over time and 
readiness for public health emergencies.
    We offer the following examples as ways an eligible hospital or CAH 
may demonstrate their level of active engagement:
     A dated report or screenshot from CEHRT that documents 
successful submission to the registry or PHA. The report should include 
evidence to support that it was generated for that eligible hospital's 
or CAH's system (for example, identified by CMS certification number 
[CCN] and eligible hospital or CAH) name or;
     A dated report or screenshot of successful registration or 
electronic transmission (for example, screenshot from another system, 
etc.). The report should include evidence to support that it was 
generated for that eligible hospital or CAH (for example, identified by 
CMS certification number [CCN] and eligible hospital or CAH name) or;
     A letter or email from a registry or PHA confirming 
registration.
    With respect to the recommendation to include an exclusion, we 
refer readers to the existing exclusions for each measure within the 
Public Health and Clinical Data Exchange Objective (See Table IX.H.-
07.). For instances when there is an issue with the ability of a PHA or 
CDR to receive the data in the specific standards required to meet the 
CEHRT definition or where no PHA has declared readiness to receive data 
from eligible hospitals or CAHs, there are exclusions available for 
eligible hospitals and CAHs (42 CFR 495.24 (e)(8)(iii)). While we 
recognize that there may be variability in ability to quickly test and 
validate state to state, PHAs have been requiring transmission of 
electronic laboratory reporting, immunization registry reporting, and 
syndromic surveillance reporting for many years. To help address the 
existing variability, CDC is providing funding for PHAs to improve and 
modernize their data infrastructure, which will result in more rapid 
testing and validation. In addition, most eligible hospitals and CAHs 
are successfully reporting these measures.
    Comment: A few commenters requested that CMS provide further 
guidance on whether the previous EHR Incentive Program registration 
satisfies current program requirements. A few commenters requested that 
CMS address concerns over lack of vendor readiness. A few commenters 
requested that CMS provide more clarity on how active engagement status 
is impacted by eligible hospitals and CAHs that registered with PHAs in 
the past but will only now be engaging in data exchange with the PHA.
    Response: If an eligible hospital or CAH has previously registered 
and has not received an invitation to proceed to testing and 
validation, we recommend that they reach out to the PHA to confirm that 
they remain actively engaged and to discuss their timeline for moving 
into testing and validation.
    After consideration of the public comments we received, we are 
finalizing our proposal for the Public Health and Clinical Data 
Exchange Objective to require that in addition to submitting responses 
for the required measures and any optional measures an eligible 
hospital or CAH chooses to report, that they submit their level of 
active engagement, either Option 1: Pre-production and Validation or 
Option 2: Validated Data Production (as finalized in section H.5.c(2)), 
for each measure they report beginning with the EHR reporting period in 
CY 2023.
(4) Changes to the Duration of Active Engagement Options
    As discussed in the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 
28588), eligible hospitals and CAHs currently are not required to 
report their level of active engagement, or advance from one option to 
the next option within a certain period of time. As we proposed 
requiring eligible hospitals and CAHs to submit their level of active 
engagement for each measure they report, we also proposed, beginning 
with the EHR reporting period in CY 2023, that eligible hospitals and 
CAHs may spend only one EHR reporting period at the Option 1: Pre-
production and Validation level of active engagement per measure, and 
that they must progress to the Option 2: Validated Data Production 
level for the next EHR reporting period for which they report a 
particular measure. For example, under this proposal, if an eligible 
hospital or CAH submits a level of active engagement at the proposed 
option 1 level (Pre-production and Validation) for the Syndromic 
Surveillance Reporting measure for the EHR reporting period in CY 2023, 
the eligible hospital must report a level of active engagement at the 
proposed option 2 level (Validated Data Production) for the next EHR 
reporting period for which it reports the Syndromic Surveillance 
Reporting measure, or it would fail to satisfy the Public Health and 
Clinical Data Exchange Objective for its next EHR reporting period. The 
options for active engagement assume the same PHA or CDR is used by the 
hospital. In the event an eligible hospital or CAH chooses to switch 
between one or more CDRs or PHAs, we proposed they would be permitted 
to spend an additional EHR reporting period at the Option 1: Pre-
production and Validation level to assist with onboarding to the new 
CDR or PHA. As electronic transmission of high-quality data is achieved 
at the Option 2: Validated Data Production level, we want all eligible 
hospitals and CAHs to reach this level.
    We invited public comments on these proposed changes to the 
duration of the active engagement options.
    Comment: Many commenters supported the proposal to limit the amount 
of time an eligible hospital or CAH may spend at the pre-production and 
validation level of active engagement to one EHR reporting period. Many 
commenters noted the importance of eligible hospitals and CAHs 
exchanging data with public health agencies, as highlighted by the 
COVID-19 PHE, as well as how this limit on duration in the pre-
production and validation level promotes and incentivizes progress 
through the levels of active engagement and data exchange.
    Response: We thank the commenters for their support of our proposal 
to limit the amount of time an eligible hospital or CAH may spend in 
the pre-production and validation level of active engagement. We agree 
on the importance of data exchange between eligible hospitals and 
public health agencies and clinical registries, particularly in light 
of the ongoing COVID-19 PHE, and thus have prioritized efforts to 
promote data exchange with public health agencies and clinical 
registries.
    Comment: While offering support, several commenters expressed 
concern

[[Page 49341]]

about the readiness of state and local public health agencies and 
registries to accept production data and urged CMS to implement changes 
to the duration of active engagement levels in a phased approach or 
offer exclusions for circumstances that are out of the control of the 
eligible hospital or CAH.
    Response: We appreciate commenters' recommendations regarding 
including exclusions for when state and local jurisdictions may not be 
ready or capable of accepting production data, or are slow to onboard, 
and refer readers to the existing exclusions for each Public Health and 
Clinical Data Exchange measure. For instance, when there is an issue 
with the ability of a PHA or CDR to receive the data in the specific 
standards required to meet the CEHRT definition or where no PHA has 
declared readiness to receive data from eligible hospitals or CAHs, 
there are exclusions available for eligible hospitals and CAHs (42 CFR 
495.24 (e)(8)(iii)).
    Comment: Many commenters did not support the proposal to limit the 
duration of Pre-production and Validation level of active engagement to 
one EHR reporting period citing that progression out of this level is 
often not under hospital control and depends on the resources available 
from a given PHA and their technical capabilities and timeliness in 
communications. A few commenters recommended adding an exclusion to 
allow for when public health agencies have limited resources to 
validate and onboard. A few commenters suggested this could lead to 
rushed validation and poor data quality, particularly with a move to a 
180-day EHR reporting period. A few commenters stated concerns that EHR 
vendors may not be ready for testing in 2023 or 2024 and suggested CMS 
allow hospitals multiple reporting years under the Pre-Production and 
Validation level. A commenter requested that CMS allow hospitals at 
least one year of stable reporting of public health measures without 
implementing this active engagement reporting requirement. Another 
commenter did not support the proposal because the commenter stated CMS 
lacks a baseline as it has never collected eligible hospitals or CAHs 
active engagement level.
    Response: We acknowledge commenters' concerns regarding the lack of 
control that eligible hospitals or CAHs may have when moving through 
the levels of active engagement. In particular, we recognize that an 
eligible hospital's or CAH's successful progression through the levels 
of active engagement is partially dependent on the readiness, 
resources, and technical capabilities of the PHAs to which it reports. 
We further recognize that public health capacity remains somewhat 
variable and constrained--particularly as PHAs continue to direct 
substantial resources to the COVID-19 PHE response efforts. 
Accordingly, we agree with the commenter who suggested allowing at 
least one year of stable reporting of public health measures before 
instituting limits on the length of time eligible hospitals and CAHs 
can spend in the pre-production and validation level of active 
engagement.
    For these reasons, we are delaying the implementation of this 
requirement by one year, such that it will apply beginning with the EHR 
reporting period in CY 2024. This delay balances the urgent need to 
move eligible hospitals and CAHs into data production with the need 
identified by the commenters for additional time for public health 
agencies and health care providers to prepare for this change. Without 
this requirement, facilities can linger in registration, testing or 
validation for years, which provides little benefit to the public in a 
PHE or to address health threats. Moreover, existing data PHAs have 
shared with CDC indicate that registration, testing and validation 
completion rates are already fairly rapid--typically less than 3 months 
in many cases. Admittedly, there are exceptions--in particular, the 
validation stage can take longer, as it depends on PHA readiness, as 
well as the quality of the data a provider is sending and the CEHRT 
product being used. However, we anticipate that testing and validation 
cycle times will continue to shrink over the next year as public health 
agencies use CDC funding to modernize their data infrastructures.
    Nonetheless, we appreciate and agree with commenters' 
recommendations regarding the need for exclusions when state and local 
jurisdictions are not ready or capable of accepting production data, or 
are slow to onboard facilities (for example, an eligible hospital is 
unable to complete testing and validation in a single EHR reporting 
period because the PHA has a backlog of validation requests). We 
believe an eligible hospital or CAH could consider whether the existing 
exclusions for each measure associated with the Public Health and 
Clinical Data Exchange Objective could be claimed in these cases and 
refer readers to these exclusions at 42 CFR 495.24 (e)(8)(iii). 
However, we will continue to examine this issue in collaboration with 
CDC and, if additional exclusions are warranted, we may address them 
and any other changes warranted in future rulemaking.
    Comment: A few commenters had questions regarding allowances for 
when hospitals need to migrate from testing/validation to production 
and back if the public health department performs systems updates, for 
unforeseen outages, or if hospitals move to a different vendor and 
their testing does not line up well to be in production during their 
next reporting period. A few commenters expressed concern over the lack 
of control hospitals have in moving from one level to another, or in 
receiving documentation that proves they have achieved a certain level 
of active engagement. A commenter requested that CMS work with other 
agencies to support state organizations in providing the technical 
support necessary and suggested including an exclusion for situations 
in which a state has limited capacity for engagement.
    Response: We appreciate commenters' feedback on the proposal to 
limit the time spent in the Pre-production and Validation level of 
active engagement to one EHR reporting period. With respect to the 
concern about moving to different vendors, PHAs, or CDRs, the options 
for active engagement assume the same PHA or CDR is used by the 
hospital. In the event an eligible hospital or CAH chooses to switch 
between one or more CDRs or PHAs, we proposed they would be permitted 
to spend an additional EHR reporting period at the Pre-production and 
Validation level to assist with onboarding to the new CDR or PHA (87 FR 
28588). As we have previously stated, we acknowledge commenters' 
concerns regarding the lack of control that eligible hospitals or CAHs 
may have when moving through the levels of active engagement and the 
dependency on resources and technical capabilities at public health 
departments and registries. We refer readers to the existing exclusions 
for each Public Health and Clinical Data Exchange measure. For 
instances when there is an issue with the ability of a PHA or CDR to 
receive the data in the specific standards required to meet the CEHRT 
definition or where no PHA has declared readiness to receive data from 
eligible hospitals or CAHs, there are exclusions available for eligible 
hospitals and CAHs (42 CFR 495.24 (e)(8)(iii)).
    Comment: A commenter expressed concern for smaller hospitals who 
may need more time to progress to production and stated that 
establishing a time limit should be based on a solid understanding of 
the barriers hospitals face to moving between levels of active 
engagement. A commenter recommended that CMS incentivize

[[Page 49342]]

health care organizations (HCOs) and vendors to continue to engage with 
PHAs once initial validated production data are flowing to ensure that 
accurate, complete, and timely data for reportable conditions are 
available to PHAs as required by jurisdictional laws and regulations 
and for effective public health response activities. A commenter 
recommended CMS create a list of states where certain types of public 
health and clinical data exchange is immature to identify potential 
scoring issues.
    Response: We appreciate commenters' feedback regarding the impact 
of this policy on smaller hospitals and recommendations to provide 
incentives for continued engagement with PHAs as well as developing 
resources to identify where public health and clinical data exchange is 
immature. We will monitor implementation and consider future changes if 
necessary.
    Comment: Several commenters noted that local and state health 
departments have limitations and offer variable levels of technical 
capacity to support this type of data exchange and that CMS should 
follow and support development efforts at the state and local levels of 
PHAs and registries.
    Response: We agree with the importance of ensuring health care 
providers and PHAs have the ability to set up data exchange within a 
reasonable timeframe. Our goal is that all parties continue to move 
towards validated production, which will prepare the nation for a more 
effective response to public health emergencies. As we discussed above, 
given the many challenges identified in the comments, we are delaying 
the implementation of this requirement until the beginning of the EHR 
reporting period in CY 2024.
    Additionally, among the core objectives of CDC's DMI are seamless 
reporting to public health agencies and interoperability among core 
public health surveillance strategies. As such, CDC is providing 
funding to public health agencies to improve and modernize their data 
infrastructure. We are working closely with CDC to coordinate 
healthcare program requirements and public health modernization 
investments to foster co-maturation and readiness for bi-directional 
data exchange.
    After consideration of the public comments we received, we are 
finalizing the proposals to limit the amount of time an eligible 
hospital or CAH may spend at the pre-production and validation level of 
active engagement to one EHR reporting period with the modification 
that this limitation will apply beginning with the EHR reporting period 
in CY 2024.
(5) Public Health Reporting and Information Blocking
    The ONC 21st Century Cures Act final rule (85 FR 25642) implemented 
policies related to information blocking as authorized under section 
4004 of the 21st Century Cures Act, as discussed further in the FY 2023 
IPPS/LTCH PPS proposed rule (87 FR 28588 through 28589).
6. Changes to Scoring Methodology for the EHR Reporting Period in CY 
2023
    In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41636 through 
41645), we adopted a new performance-based scoring methodology for 
eligible hospitals and CAHs attesting under the Medicare Promoting 
Interoperability Program beginning with the EHR reporting period in CY 
2019, which included a minimum scoring threshold of a total score of 50 
points or more which eligible hospitals and CAHs must meet to satisfy 
the requirement to report on the objectives and measures of meaningful 
use under 42 CFR 495.24. In the FY 2022 IPPS/LTCH PPS final rule (86 FR 
45491 through 45492), we increased the minimum scoring threshold from 
50 points to 60 points beginning with the EHR reporting period in CY 
2022. As shown in Table IX.H.-03, the points associated with the 
required measures sum to 100 points, and the optional measures may add 
additional bonus points. The scores for each of the measures are added 
together to calculate a total score of up to 100 possible points for 
each eligible hospital or CAH (83 FR 41636 through 41645). We note in 
the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28589), we erroneously 
stated that we calculate a total score of up to 105 possible points, 
but we want to clarify that we cap the number of points at 100.
    Table IX.H.-03 reflects the objectives and measures for the EHR 
reporting period in CY 2022 and was included in the FY 2022 IPPS/LTCH 
PPS final rule (86 FR 45492).

[[Page 49343]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.185

    In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28590), we noted 
that in proposing to make the Query of PDMP measure required, we would 
retain the 10 points associated with it, which are allocated as bonus 
points for the EHR reporting period in CY 2022. If finalized, we 
proposed to reduce the points associated with the Health Information 
Exchange Objective measures from the current 40 points to 30 points 
beginning with the CY 2023 EHR reporting period. The Public Health and 
Clinical Data Exchange Objective, with its current four required 
measures, is currently worth 10 points. Despite increasing the number 
of required measures from two to four to make the objective more 
effective in promoting public health data electronic exchange, the 
total number of points did not change between CY 2021 and CY 2022. We 
believe that increasing the point value of the Public Health and 
Clinical Data Exchange Objective would create a more meaningful 
incentive for eligible hospitals and CAHs to engage in the electronic 
reporting of public health information and recognize the importance of 
public health systems affirmed by the COVID-19 pandemic. Increasing the 
point value would make the Public Health and Clinical Data Exchange 
Objective a more central piece of the Promoting Interoperability 
Program, and better incentivize eligible hospitals and CAHs to 
implement these essential public health data exchange capabilities. 
Without adequate incentives, there remains a risk that eligible 
hospitals and CAHs will simply not prioritize implementing these 
capabilities, which are essential to ongoing efforts to address COVID-
19 and will be indispensable for responding to future public health 
threats and emergencies. Increasing the point value would more 
appropriately incentivize eligible hospitals and CAHs to engage in the 
electronic reporting of public health information, and would align the 
value of the objective with the objective's importance and the effort 
necessary to meet the required measures.
    Thus, we proposed to increase the points allocated to the Public 
Health and Clinical Data Exchange Objective from 10 to 25 points to 
better align with the true value of this objective beginning with the 
EHR reporting period in CY 2023. This proposal was independent of our 
proposal to add the AUR Surveillance measure to the objective, and we 
considered increasing the points regardless of whether the proposal to 
add the AUR Surveillance measure to the objective was finalized. We 
believe assigning 25 points to the objective reflects the importance of 
comprehensive, nationwide health care data exchange between eligible 
hospitals and CAHs and public health agencies. Nationwide health care 
data exchange would provide immense value to the public by improving 
the speed and effectiveness of public health responses, as well as to 
eligible hospitals and CAHs, since better public health response 
reduces pressure on hospitals, which can be overwhelmed in a public 
health crisis. To balance the increase in the points associated with 
the Public Health and Clinical Data Exchange Objective, we also 
proposed to reduce the points associated with the Provide Patients 
Electronic Access to Their Health Information measure from the current 
40 points to 25 points beginning with the EHR reporting period in CY 
2023.
    We included Table IX.H.-04. in the FY 2023 IPPS/LTCH PPS proposed 
rule, which reflects the objectives, measures, and maximum points 
available for the EHR reporting period in CY 2023, if the proposals 
discussed (87 FR 28598) are finalized.

[[Page 49344]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.186


[[Page 49345]]


    The maximum points available in Table [IX.H.-04.] do not include 
the points that would be redistributed in the event an exclusion is 
claimed. For ease of reference, in the FY 2023 IPPS/LTCH PPS proposed 
rule, we included Table [IX.H.-054 at 87 FR 28592] which shows the 
point redistribution among the objectives and measures for the EHR 
reporting period in CY 2023 in the event an eligible hospital or CAH 
claims an exclusion, if the proposals made in the FY 2023 IPPS/LTCH PPS 
proposed rule are finalized.
[GRAPHIC] [TIFF OMITTED] TR10AU22.187

    We invited public comment on these proposed changes to our scoring 
methodology.
    Comment: A few commenters expressed support for the proposed 
changes to the scoring methodology. A commenter expressed support for 
increasing the points associated with the Electronic Prescribing 
Objective from 10 to 20 to further incentivize electronic prescribing. 
A few commenters supported the proposed reduction in points of the HIE 
Objective from 40 to 30 points. Many commenters supported the 
adjustment of the Public Health and Clinical Data Exchange Objective 
from 10 to 25 points. Several agreed with the importance of 
incentivizing efforts related to the COVID-19 pandemic.
    Response: We thank the commenters for their support.
    Comment: A few commenters did not support our proposal to reduce 
the number of points assigned to the HIE Objective citing that the 
current point allocation reflects the push for the continued adoption 
and expansion of clinical data exchange. A few commenters did not 
support the point reduction of the Provider to Patient Exchange 
Objective citing that such a reduction would signal that CMS devalues 
the exchange of data between patients and health care providers. A few 
commenters did not support our proposal to increase the total score of 
the Public Health and Clinical Data Exchange Objective citing the lack 
of readiness of, and variability among, states and public health 
agencies to receive and process data.
    Response: We thank commenters for their concerns and feedback. 
Point changes across objectives reflect the importance of shifting 
priorities, especially during the COVID-19 pandemic. Thus we are 
reducing the points associated with the Provider to Patient Exchange 
Objective so we can increase the points associated with the Public 
Health and Clinical Data Exchange Objective due to the importance of 
public health data during PHEs. The reduction to the HIE Objective was 
to accommodate the requirement of the Query of PDMP measure which 
increased the points associated with the Electronic Prescribing 
Objective.
    Comment: A commenter recommended increasing the number of points 
that hospitals can earn to accommodate the necessary point increases.
    Response: While we appreciate this suggestion, we believe that 
increasing the number of points may inflate scores and would not 
reflect the priorities that are conveyed through the reallocation of 
points.
    After consideration of the public comments we received, we are 
finalizing our proposals for changes to the scoring methodology for the 
EHR reporting period in CY 2023 without modification.

[[Page 49346]]

7. Public Reporting of Medicare Promoting Interoperability Program Data
    Section 1886(n)(4)(B) of the Act requires the Secretary to post in 
an easily understandable format a list of the names and other relevant 
data, as determined appropriate by the Secretary, of eligible hospitals 
and CAHs who are meaningful EHR users under the Medicare FFS program, 
on a CMS website. In addition, that section requires the Secretary to 
ensure that an eligible hospital or CAH has the opportunity to review 
the other relevant data that are to be made public with respect to the 
eligible hospital or CAH prior to such data being made public.
    As the Medicare Promoting Interoperability Program has evolved over 
the years, we have continued to expand the scope of relevant data 
points across the Medicare Promoting Interoperability Program. For 
example, we post information on a CMS website available to the public 
regarding those eligible hospitals and CAHs who attest to limiting or 
restricting the compatibility or interoperability of CEHRT under 42 CFR 
495.40(b)(2)(i)(I), as established in the 2020 Patient Access and 
Interoperability final rule (85 FR 25578 through 25580). Additionally, 
in alignment with the Hospital IQR Program, we finalized proposals to 
begin publicly reporting eCQM data beginning with the CY 2021 reporting 
period, and subsequent years (85 FR 58975 through 58976).
    To date, we have not publicly reported eligible hospitals' and 
CAHs' total scores for the Medicare Promoting Interoperability Program. 
We calculate a total score of up to 100 possible points by adding 
together the points earned for each required measure and any optional 
measures reported by an eligible hospital or CAH (83 FR 41636 through 
41645). In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28592 through 
28593), we proposed to post the eligible hospital's or CAH's actual 
score, up to 105 possible points, so that consumers can clearly see the 
high performing hospitals. We wish to clarify in this final rule that 
although we cap the total score at 100 points, the actual score 
includes the addition of any bonus points earned by the eligible 
hospital or CAH that could total up to 105 possible points. We believe 
an eligible hospital's or CAH's actual score for the Medicare Promoting 
Interoperability Program measures, which includes any bonus points 
earned, could constitute other relevant data because it would help 
consumers make informed decisions regarding their health care team, 
such as knowing whether and to what extent their health care provider 
is involved in health information exchange or providing patients with 
electronic access to their health information. We believe that publicly 
reporting additional Medicare Promoting Interoperability Program data 
demonstrates our commitment to providing data to patients, consumers, 
and health care providers, to assist them in their decision-making; 
promoting enhanced health information exchange processes across 
eligible hospitals and CAHs; and continually aligning processes and 
policies with the Hospital IQR Program and the MIPS Promoting 
Interoperability performance category. For example, for the MIPS 
Promoting Interoperability performance category, individual measure 
scores and the total performance score across all measures reported by 
eligible clinicians are posted on a CMS website available to the 
public.
    Therefore, in alignment with our goals to encourage 
interoperability and transparency, in the FY 2023 IPPS/LTCH PPS 
proposed rule, we proposed to publicly report certain Medicare 
Promoting Interoperability Program data submitted by eligible hospitals 
and CAHs beginning with the EHR reporting period in CY 2023 (87 FR 
28592 through 28593). In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 
28592 through 28593), we used the term ``total score'' within the 
public reporting proposals and wish to clarify that we were referring 
to the ``actual score'' that includes bonus points that could add up to 
105 possible points. The language in this final rule has been updated 
to reflect the distinction and clarification. Specifically, as a first 
step, we proposed to publish on a CMS website available to the public, 
the actual score of up to 105 points for each eligible hospital and 
CAH, and the CMS EHR certification ID that represents the CEHRT used by 
the eligible hospital or CAH, beginning with the scores and CMS EHR 
certification IDs for the EHR reporting period in CY 2023. We did not 
propose to publish individual measure scores at this time, but we will 
continue to evaluate that possibility for future rulemaking. For 
example, under our proposal, if an eligible hospital scored a total of 
75 points for the EHR reporting period in CY 2023, we would publish the 
score of 75 points, and not the number of points earned for each 
individual measure within the score.
    We stated that if our proposal is finalized, the actual score and 
CMS EHR certification ID data could be made available to the public as 
early as the Fall of CY 2024, or as soon as operationally feasible. In 
addition, as required by section 1886(n)(4)(B) of the Act, we proposed 
that eligible hospitals and CAHs would have the opportunity to review 
their data that we would publish, during a 30-day preview period before 
the data are made public. We proposed to follow our current policy and 
operational process that eligible hospitals and CAHs are already 
familiar with for the Hospital IQR Program and use the Hospital Quality 
Reporting (HQR) system (formerly, the QualityNet Secure Portal) for 
eligible hospitals and CAHs to access and review their Medicare 
Promoting Interoperability Program data during a 30-day preview period 
before publication. We proposed to post the Medicare Promoting 
Interoperability Program data using the Compare tool hosted by Health 
and Human Services currently available at https://www.medicare.gov/care-compare.
    We invited public comments on these proposals. Specifically, we are 
interested in comments that provide information on how these proposals 
might affect existing incentives and burdens under the Medicare 
Promoting Interoperability Program, as well as the benefit and utility 
of such data being publicly available. We also sought comments on which 
Medicare Promoting Interoperability Program data points to publish in 
future years, including specific objective or measure performance 
rates.
    Comment: A few commenters expressed general support for our 
proposal to publicly report Medicare Promoting Interoperability Program 
actual scores because they believe it will promote data transparency 
and help consumers make informed decisions.
    Response: We thank commenters for their support of our proposal and 
agree that it will help promote data transparency and help consumers 
make informed decisions.
    Comment: A few commenters noted their support for allowing a 30-day 
review and dispute period prior to publicly posting data. A commenter 
recommended CMS notify eligible hospitals and CAHs prior to the 30-day 
review, and another commenter suggested that CMS not publish data until 
any concerns or disputes that arise during the 30-day review are 
resolved.
    Response: We appreciate commenters' feedback regarding CMS 
notifying eligible hospitals and CAHs prior to the 30-day review 
period, and the request that CMS address and resolve any disputes prior 
to publication. As stated previously, we proposed to follow our current 
policy and operational process for the 30-day review period that 
eligible hospitals and CAHs are already

[[Page 49347]]

familiar with for the Hospital IQR Program. We proposed to use the 
Hospital Quality Reporting (HQR) system (formerly, the QualityNet 
Secure Portal) for eligible hospitals and CAHs to access and review 
their Medicare Promoting Interoperability Program data during a 30-day 
preview period before publication.
    Comment: Many commenters did not support the proposal to publicly 
report data stating they do not believe the data would be of interest, 
hold meaning, or be understandable to consumers; thus, it would not 
help consumers make informed health care decisions. A few commenters 
cited that given the complexity of the Medicare Promoting 
Interoperability Program, the actual score may not accurately reflect 
eligible hospitals' or CAHs' levels of interoperability, such as 
supporting patient access to health information. A commenter did not 
support the proposal to publicly report the EHR Certification ID, 
stating that health IT vendors do not have control over which 
functionality eligible hospitals or CAHs choose to implement, therefore 
this information should not be publicly reported.
    Response: We appreciate commenters' feedback and concerns regarding 
whether the Medicare Promoting Interoperability Program data would be 
of interest, meaningful, or understandable to consumers, especially as 
a tool used to help make informed decisions about their health care. As 
we have previously stated, we believe public reporting demonstrates our 
commitment to transparency and providing data to consumers, and that 
these data would help consumers make informed decisions regarding their 
health care team. This would extend to knowing whether, and to what 
extent, their health care provider is involved in health information 
exchange or providing patients with electronic access to their health 
information. We believe these data depict levels of health IT adoption 
and functionality across eligible hospitals and CAHs. Additionally, we 
believe it is important to align policies across CMS programs, and this 
proposal to publicly report Medicare Promoting Interoperability Program 
data for eligible hospitals and CAHs aligns with the current policy for 
the MIPS Promoting Interoperability performance category, wherein 
individual measure scores and the total performance score across all 
measures reported by eligible clinicians are posted on a CMS website 
available to the public.
    Comment: Several commenters provided recommendations for CMS to 
consider if the proposal to publicly report Medicare Promoting 
Interoperability Program data is finalized. These recommendations 
include providing explanations of what the Medicare Promoting 
Interoperability Program score indicates, what the EHR Certification ID 
is, and the process for searching for the information within the CHLP 
site. This would allow consumers to understand and determine how the 
actual score is calculated, emphasizing the importance of presenting 
data in a format that is both valuable and understandable to multiple 
audiences. A few commenters recommended CMS include the data in the CMS 
Provider Data Catalog so it is available to researchers and others 
seeking to understand the current variability and performance within 
the Medicare Promoting Interoperability Program. A commenter suggested 
implementing a ``star rating'' program based on national benchmarks to 
provide more meaningful information to patients and another commenter 
urged CMS to ensure any publicly reported data will not have unintended 
impacts on health care providers or the health care system. A few 
commenters recommended aligning with the Hospital IQR Program's policy 
for publicly reporting performance data to ensure information is easily 
understood. A commenter recommended, if CMS finalizes the proposal, to 
publish points available and points earned along with the yes and no 
attestations for measures within the Medicare Promoting 
Interoperability Program.
    Response: We appreciate commenters' recommendations to include 
explanations of what the Medicare Promoting Interoperability score 
indicates, as well as recommendations for the specific data points to 
publish in the future. We also appreciate commenters' recommendations 
to align with the Hospital IQR Program's policy for publicly reporting. 
As we have previously stated, we proposed to publicly report these data 
to align with the Hospital IQR Program and the MIPS Promoting 
Interoperability performance category public reporting policies. We 
also appreciate the recommendation to include a key for consumers 
alongside the publicly reported data allowing consumers to better 
understand the data. We may consider this feedback in future 
rulemaking.
    After consideration of the public comments we received, we are 
finalizing our proposal to publicly report certain Medicare Promoting 
Interoperability program data submitted by eligible hospitals and CAHs 
beginning with the EHR reporting period in CY 2023. We are finalizing 
our proposal to publish, on a CMS website available to the public, the 
actual score of up to 105 points for each eligible hospital and CAH, 
and the CMS EHR certification ID that represents the CEHRT used by the 
eligible hospital or CAH, beginning with the EHR reporting period in CY 
2023. Additionally, and as required by section 1886(n)(4)(B) of the 
Act, we are finalizing our proposal that eligible hospitals and CAHs 
would have the opportunity to review their data that we would publish, 
during a 30-day preview period before the data are made public. We 
finalized our proposal to follow our current policy and operational 
process that eligible hospitals are already familiar with for the 
Hospital IQR Program and use the Hospital Quality Reporting (HQR) 
system (formerly, the QualityNet Secure Portal) for eligible hospitals 
and CAHs to access and review their Medicare Promoting Interoperability 
Program data during a 30-day preview period before publication. We are 
also finalizing our proposal to post the Medicare Promoting 
Interoperability Program data using the Compare tool hosted by Health 
and Human Services currently available at: https://www.medicare.gov/care-compare.
8. Modifications and Additions to the Regulatory Text
    In the FY 2019 IPPS/LTCH PPS final rule (83 FR 41636 through 
41668), we finalized the objectives, measures, exclusion criteria, and 
scoring methodology for eligible hospitals and CAHs attesting under the 
Medicare Promoting Interoperability Program beginning with the EHR 
reporting period in CY 2019 and codified these policies in paragraph 
(e) under 42 CFR 495.24. We have updated the regulatory text to reflect 
policy changes in the FY 2020 IPPS/LTCH PPS final rule (84 FR 42616), 
the FY 2021 IPPS/LTCH PPS final rule (85 FR 59026), and the FY 2022 
IPPS/LTCH PPS final rule (86 FR 45522).
    We note that historically, the objectives, measures, exclusion 
criteria, and associated scoring methodology for the Medicare Promoting 
Interoperability Program have been included in both the preamble and 
associated regulatory text under 42 CFR part 495 (see, for example, the 
Medicare and Medicaid EHR Incentive Programs Stage 1 final rule (75 FR 
44314)). We also note that many CMS quality reporting and performance-
based programs, including, but not limited to, the Hospital VBP 
Program, Hospital IQR Program, the End-Stage Renal Disease Quality 
Incentive Program (ESRD QIP), and Quality Payment Program/MIPS, do not

[[Page 49348]]

include the text of the measures (also referred to as the measure 
specifications) adopted for those programs in the Code of Federal 
Regulations. Instead, the measure specifications generally are included 
in the rulemaking preamble or maintained by measure stewards outside of 
CMS and referenced in the preamble. For example, the specifications for 
the objectives and measures for the Promoting Interoperability 
performance category of MIPS are not included in the regulatory text 
for the program under 42 CFR part 414 and instead appear in the 
preamble only (for example, see CY 2022 PFS final rule (86 FR 65466 
through 65485)).
    We believe that aligning with the approach taken by other CMS 
programs to include measures only in the preamble would simplify the 
Medicare Promoting Interoperability Program and minimize confusion by 
ensuring consistency across similar CMS programs. We also believe 
taking this approach for the Medicare Promoting Interoperability 
Program would reduce burden on regulated parties, CMS, and the general 
public both during and outside of the rulemaking process. Ensuring the 
objectives and measures are described consistently in the preamble and 
regulation text can involve significant effort in terms of time and 
resources, and inconsistency has the potential to create confusion for 
regulated parties and the general public. For these reasons, we 
proposed to remove the text of the objectives and measures for the 
Medicare Promoting Interoperability Program from paragraph (e) under 42 
CFR 495.24 beginning in CY 2023 (87 FR 28593 through 28594). We noted 
that this proposal does not include any changes in policy for the 
Medicare Promoting Interoperability Program, including changes to the 
objectives and measures (87 FR 285593). We referred readers to the 
proposed changes in policies related to objectives and measures in the 
FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28579 through 28581). We 
also emphasized that this proposal does not change our view that the 
objectives and measures are rules intended to bind regulated parties, 
nor does it change our intention to enforce the objectives and 
measures. Specifically, we proposed to modify the introductory 
paragraph to 42 CFR 495.24 and paragraph (e) and to establish a new 
paragraph (f), under 42 CFR 495.24 as described in the FY 2023 IPPS/
LTCH PPS proposed rule (87 FR 28593 through 28594). In the event that 
our proposals are not finalized, we proposed that we would update the 
regulatory text to reflect those policy changes to the objectives and 
measures in this final rule.

[[Page 49349]]

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    We invited public comment on our proposed modifications and 
additions to the regulatory text at 42 CFR 495.24 beginning in CY 2023.
    We received no comments on this proposal, and for the reasons 
stated in the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28593 through 
28594), we are finalizing our proposal without modification.
9. Overview of Objectives and Measures for the Medicare Promoting 
Interoperability Program for the EHR Reporting Period in CY 2023
    For ease of reference, Table [IX.H.-07.] lists the objectives and 
measures for the Medicare Promoting Interoperability Program for the 
EHR reporting period in CY 2023 as revised to reflect the final 
policies established in this final rule. Due to our modifications to 
the regulatory text at 42 CFR 495.24(e) (described in section [IX.H.8.] 
of the preamble of this final rule), we are adding a column to Table 
[IX.H.-07.] indicating whether the measures that count unique patients 
or actions may be calculated by reviewing only the actions for patients 
whose records are maintained using CEHRT or must be calculated by 
reviewing all patient records, which is intended to reflect the

[[Page 49350]]

policy codified at 42 CFR 495.24(e)(3). Table [IX.H.-08.] lists the 
2015 Edition certification criteria required to meet the objectives and 
measures.
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BILLING CODE 4120-01-C
10. Clinical Quality Measurement for Eligible Hospitals and CAHs 
Participating in the Medicare Promoting Interoperability Program
a. Changes to Clinical Quality Measures in Alignment With the Hospital 
IQR Program
(1) Background
    Under sections 1814(l)(3)(A) and 1886(n)(3)(A) of the Act and the 
definition of ``meaningful EHR user'' under 42 CFR 495.4, eligible 
hospitals and CAHs must report on clinical quality measures selected by 
CMS using CEHRT (also referred to as electronic clinical quality 
measures, or eCQMs), as part of being a meaningful EHR user under the 
Medicare Promoting Interoperability Program.
    Tables IX.H.-09. through IX.H.-11. summarize the previously 
finalized eCQMs available for eligible hospitals and CAHs to report 
under the Medicare Promoting Interoperability Program for the CY 2022 
reporting period, the CY 2023 reporting period, and the CY 2024 
reporting period and subsequent years (86 FR 45496 through 45497). The 
tables include the Safe Use of Opioids--Concurrent Prescribing measure 
(NQF #3316e), which we finalized as mandatory for reporting beginning 
with the CY 2022 reporting period (84 FR 42598 through 42600).
BILLING CODE 4120-01-P

[[Page 49360]]

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[[Page 49361]]


(2) eCQM Adoptions
    As we have stated previously in rulemaking (82 FR 38479), we intend 
to continue to align the eCQM reporting requirements for the Medicare 
Promoting Interoperability Program with similar requirements under the 
Hospital IQR Program to the extent feasible. Section 
1886(n)(3)(B)(i)(I) of the Act provides in part that in selecting 
clinical quality measures for the Medicare Promoting Interoperability 
Program, the Secretary shall provide preference to such measures that 
have been selected for purposes of the Hospital IQR Program (section 
1886(b)(3)(B)(viii) of the Act). In addition, section 
1886(n)(3)(B)(iii) of the Act provides that in selecting clinical 
quality measures for the Medicare Promoting Interoperability Program, 
and in establishing the form and manner for reporting, the Secretary 
shall seek to avoid redundant or duplicative reporting with reporting 
otherwise required, including reporting under the Hospital IQR Program. 
To minimize redundant or duplicative reporting, while maintaining a set 
of meaningful clinical quality measures that continue to incentivize 
improvement in the quality of care provided to patients, we proposed to 
adopt four new eCQMs for the Medicare Promoting Interoperability 
Program in alignment with the Hospital IQR Program, as further 
discussed in this section of the final rule.
    In alignment with proposals for the Hospital IQR Program eCQM 
measure set, we proposed two new eCQMs that address factors 
contributing to maternal mortality and morbidity, beginning with the CY 
2023 reporting period. Specifically, we proposed to add the following 
eCQMs in the Medicare Promoting Interoperability Program eCQM measure 
set beginning with the CY 2023 reporting period: (1) Severe Obstetric 
Complications eCQM (NQF NA); and (2) Cesarean Birth eCQM (NQF NA) (87 
FR 28609). We also proposed to require mandatory reporting of the 
Severe Obstetric Complications eCQM and Cesarean Birth eCQM for the CY 
2024 reporting period and for subsequent years. We refer readers to the 
discussion of the same proposals for the Hospital IQR Program in 
sections IX.E.5.d. and IX.E.5.c. of the preamble of this final rule for 
more information about these proposed measures.
    We invited public comments on these proposed measures for the 
Medicare Promoting Interoperability Program.
    Comment: Several commenters support our proposal to adopt the 
Severe Obstetric Complications eCQM in alignment with the Hospital IQR 
Program. A few commenters requested a delay in mandatory reporting 
until the CY 2025 reporting period, or until the measure receives NQF 
endorsement. A commenter recommended optional reporting if NQF 
endorsement is received.
    Response: We thank commenters for their support. We disagree with 
commenters who have suggested delaying reporting until the CY 2025 
reporting period. Addressing factors contributing to maternal mortality 
and morbidity is one of our priorities. The Severe Obstetric 
Complications eCQM has been developed to focus on the high maternal 
morbidity and mortality rates in the U.S. which we believe will present 
important opportunities for large-scale quality measurement and 
improvement activities.\1135\ The Severe Obstetric Complications eCQM 
was also reviewed by the NQF Measure Applications Workgroup (MAP) 
Hospital Workgroup on December 15, 2021 and received conditional 
support pending NQF endorsement.\1136\ The MAP Coordinating Committee, 
which provides direction to the MAP workgroups, reviewed the Severe 
Obstetric Complications eCQM on January 19, 2022, and voted to uphold 
the MAP Hospital Workgroup recommendation for conditional support 
pending NQF endorsement.\1137\ We acknowledge commenters' 
recommendations that we seek NQF endorsement for the measure; the 
Severe Obstetric Complication eCQM was submitted to NQF in January 2022 
and is currently under review (87 FR 28512).
---------------------------------------------------------------------------

    \1135\ National Quality Forum. (2022). Measure Applications 
Partnership (MAP) 2021-2022 Final Recommendations. Available at: 
https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=96698.
    \1136\ National Quality Forum. (2022). Measure Applications 
Partnership 2021-2022 Considerations for Implementing Measures in 
Federal Programs: Clinician, Hospital, and Post-Acute Care Long-Term 
Care: Final Report. Available at: https://www.qualityforum.org/Publications/2022/03/MAP_2021-.
    \1137\ National Quality Forum. (2022). Measure Applications 
Partnership 2021-2022 Considerations for Implementing Measures in 
Federal Programs: Clinician, Hospital, and Post-Acute Care Long-Term 
Care: Final Report. Available at: https://www.qualityforum.org/Publications/2022/03/MAP_2021-2022_Considerations_for_Implementing_Measures_Final_Report_-_Clinicians,_Hospitals,_and_PAC-LTC.aspx.
---------------------------------------------------------------------------

    Comment: Several commenters supported the proposal to add the 
Cesarean Birth eCQM and mandatory reporting of this measure. A 
commenter supported the adoption of the measure for self-selection 
rather than mandatory reporting. A commenter supported adoption and 
mandatory reporting and recommended identification of community 
partners such as HIEs for data capture and sharing. A few commenters 
supported the measure adoption and requested an adoption delay until 
NQF endorsement is received. A commenter supported the proposal and 
requested clarifications on the reporting requirements for non-birthing 
eligible hospitals and CAHs.
    Response: We thank commenters for their support of the Cesarean 
Birth eCQM. We believe adopting the Cesarean Birth eCQM addresses a 
priority area.\1138\ We also believe adopting measures like the 
Cesarean Birth eCQM presents unique opportunities for large-scale 
quality measurement and activities that can improve the short- and 
long-term health outcomes for mothers and children (87 FR 28508). As a 
result, we believe that the timeline should not be further delayed as 
the urgency of the quality issues necessitates making the measure 
mandatory for data collection from all participating hospitals, not 
just those hospitals that self-select to report on the measure. We also 
believe the voluntary reporting in the CY 2023 reporting period before 
mandatory reporting beginning with the CY 2024 reporting period 
balances the urgency of the measure with the need for EHR vendors and 
hospitals to incorporate, adopt, and implement this measure. We 
acknowledge the comment regarding community partners such as HIEs for 
data capture and sharing and refer readers to the FY 2016 IPPS/LTCH PPS 
final rule (80 FR 49705 through 49708) and the FY 2017 IPPS/LTCH PPS 
final rule (81 FR 57170) for our previously adopted eCQM file format 
requirements. Under these requirements, hospitals: (1) Must submit eCQM 
data via the Quality Reporting Document Architecture Category I (QRDA 
I) file format, (2) may use third parties to submit QRDA I files on 
their behalf, and (3) may either use abstraction or pull the data from 
noncertified sources in order to then input these data into CEHRT for 
capture and reporting QRDA I. However, we do not currently have a 
policy to publicly identify any such third parties. We acknowledge 
commenters' recommendations that we seek NQF endorsement for the 
measure. As stated in the FY 2023 IPPS/LTCH PPS proposed rule, the NQF 
has endorsed the chart-abstracted version of this measure and the 
measure steward has submitted the eCQM to NQF for

[[Page 49362]]

consideration of endorsement (87 FR 28509). We also note that the 
measure steward submitted this measure for endorsement in the Spring of 
2022. Non-birthing eligible hospitals and CAHs that do not perform 
deliveries would submit a zero denominator declaration that allows a 
hospital to meet the reporting requirements for an eCQM if the hospital 
does not have patients that meet the denominator criteria of the 
measure. We refer readers to the FY 2017 IPPS/LTCH PPS final rule (81 
FR 57153) where we stated that utilization of the zero denominator 
declaration and case threshold exemptions are considered as part of the 
criteria for successful submissions when reporting eCQMs (81 FR 57170). 
Hospitals can continue to meet the reporting requirements by submitting 
data via QRDA I files, zero denominator declaration, or case threshold 
exemption (82 FR 38387). We also refer readers to the FY 2018 IPPS/LTCH 
PPS final rule (81 FR 57255 through 57257) where we stated the 
finalized successful submission requirements in the Hospital IQR 
Program align with the CQM electronic reporting requirements of the 
Medicare Promoting Interoperability Program for eligible hospitals and 
CAHs. For additional information about the requirements for successful 
submission of eCQMs, we refer readers to our QualityNet website 
(https://qualitynet.cms.gov/inpatient/measures/ecqm/participation).
---------------------------------------------------------------------------

    \1138\ Department of Health and Human Services. (2020). Healthy 
Women, Healthy Pregnancies, Health Futures: Action Plan to Improve 
Maternal Health in America. Available at: https://aspe.hhs.gov/sites/default/files/private/aspe-files/264076/healthy-women-healthy-pregnancies-healthy-future-action-plan_0.pdf.
---------------------------------------------------------------------------

    Comment: Several commenters did not support the proposal to adopt 
the Severe Obstetric Complications eCQM in the measure set, expressing 
concerns about feasibility and reliability and the lack of NQF 
endorsement, the proposal for mandatory reporting, vendors' ability to 
support the measure, and the measure's achievement of its stated goal. 
A few commenters offered recommendations about the proposal including 
securing NQF endorsement before requiring reporting in the Medicare 
Promoting Interoperability Program. A commenter encouraged CMS to 
collaborate with eligible hospitals and CAHs, and connect the 
measurement to community-involved initiatives to reduce complications.
    Response: We appreciate commenters' concerns and believe that this 
measure serves as a key activity in measuring and promoting quality 
improvement in maternity care by incentivizing eligible hospitals and 
CAHs to track and report severe obstetric complications and to publicly 
report the measure data for transparency. As with the Cesarean Birth 
eCQM, due to the priority on improving maternity care particularly to 
reduce morbidity and mortality during inpatient births, we believe the 
timeline for reporting the Severe Obstetric Complications eCQM is 
appropriate and should not be further delayed. We acknowledge 
commenters' recommendations that we seek NQF endorsement for the 
measure; the Severe Obstetric Complication eCQM was submitted to NQF in 
January 2022 and is currently under review (87 FR 28512). Testing 
established the feasibility of the measure, first in 25 hospitals 
across eight healthcare sites and then in additional hospitals 
unaffiliated with the first 25. The data elements were feasible to 
collect across three different electronic health record systems.\1139\ 
All numerator indicators and 30 of 34 risk factors use easily mapped 
ICD-10 codes. The two laboratory and two vital sign risk factors were 
chosen in part because of their availability and high rates of 
extractability from the medical record. Using NQF's eCQM Feasibility 
Scorecard template,\1140\ the measure developer calculated results 
which indicated high feasibility of data elements defining the measure 
specifications (98 percent), clinical and documentation workflows 
compared to measure intent (99 percent), data element availability (95 
percent) and accuracy (98 percent), and use of data standards (96 
percent).
---------------------------------------------------------------------------

    \1139\ Centers for Medicare & Medicaid Services. (2018). eCQM 
Feasibility: How Stakeholders Inform Measure Development. Available 
at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/MMS/Downloads/eCQM-Feasibility.pdf.
    \1140\ National Quality Forum. (2022). NQF eCQM Feasibility 
Scorecard. Available at: https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=89036.
---------------------------------------------------------------------------

    Comment: Several commenters did not support the proposal to adopt 
the Cesarean Birth eCQM due to concerns about feasibility and validity, 
the adequacy of the adoption timeline for hospitals and vendors, and 
the measure as an indicator of quality performance. A few commenters 
recommended that CMS consider further refining the measure exclusions.
    Response: We thank commenters for sharing their concerns and their 
input on the timeline of adoption, and implementation of the Cesarean 
Birth eCQM. With regard to feasibility and validity, the measure 
steward conducted additional measure testing in 2021. The reliability 
and validity testing found the measure to have an overall data element 
agreement rate of 92.2 percent and we therefore believe the measure to 
be reliable and valid for use. As we noted in the preamble of the FY 
2023 IPPS/LTCH PPS proposed rule, we are proposing eCQMs that address 
factors contributing to maternal mortality and morbidity (87 FR 28609) 
in alignment with proposals for the Hospital IQR Program that address 
maternal health outcomes. We believe the proposed timeline of inclusion 
of this eCQM into the Medicare Promoting Interoperability Program 
measure set beginning with the CY 2023 EHR reporting period, followed 
by mandatory reporting beginning with the CY 2024 reporting period and 
for subsequent years, provides sufficient time for EHR vendors and 
hospitals to incorporate, adopt, and implement the measure. We believe 
one year of voluntary reporting is sufficient because as noted in the 
FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28509), in 2020, the measure 
steward introduced the Cesarean Birth eCQM as one of the available 
eCQMs hospitals can choose for data submission to meet The Joint 
Commission's ORYX[supreg] requirements.
    We agree that continued monitoring of the measure is important. We 
believe collecting data and reporting results will provide a critical 
baseline and we will monitor the data and any unintended consequences 
of the measure. While we agree that there are many ways to track data 
related to the C-section rate in the United States, and ultimately 
reduce excess non-medically indicated C-sections, the standards and 
comprehensiveness of initiatives can vary widely and we do not believe 
broadening exclusion criteria or risk adjustment is necessary at this 
time. As we noted in the FY 2023 IPPS/LTCH PPS proposed rule, when 
developing the measure, the exclusion criteria were chosen to ensure 
that the focus population would be women with NTSV pregnancies (86 FR 
28510). Barring the presence of other co-morbidities, such women often 
have a lower risk of maternal morbidity and mortality at the time of 
delivery than their counterparts who have undergone a previous C-
section (87 FR 28510). As a result of the existing exclusion criteria, 
the population denominator allows the measure to focus on a more 
homogeneous group where the greatest improvement opportunity exists. As 
evidenced by variation in rates of NTSV C-sections, clinical practice 
patterns in particular may affect this rate (87 FR 28510). Lowering the 
C-section rate in NTSV pregnancies is important because C-sections may 
carry a higher risk of subsequent miscarriage, placental abnormalities, 
and repeat C-section (87 FR 28510). The rates of ruptured uteri, 
unplanned hysterectomies, and ICU admission are higher among women who 
deliver via C-section for the first time than those who deliver 
vaginally

[[Page 49363]]

for the first time across all races and ethnicities. However, non-
Hispanic Black women who deliver via C-section for the first time had 
the highest rates of uterine rupture and ICU admission compared with 
all other races.\1141\ Including a comprehensive set of maternal 
medical exclusions would add data collection burdens without 
commensurate benefit. After consideration of the public comments we 
received, we are finalizing our proposal to add the following eCQMs in 
the Medicare Promoting Interoperability Program eCQM measure set 
beginning with the CY 2023 reporting period: (1) Severe Obstetric 
Complications eCQM (NQF NA); and (2) Cesarean Birth eCQM (NQF NA), and 
we are finalizing our proposal to require mandatory reporting of the 
Severe Obstetric Complications eCQM and the Cesarean Birth eCQM for the 
CY 2024 reporting period and for subsequent years. We refer readers to 
the discussion of the same proposals for the Hospital IQR Program in 
sections IX.E.5.d. and IX.E.5.c. of the preamble of this final rule for 
more information about these finalized policies.
---------------------------------------------------------------------------

    \1141\ Curtin, S.C., Gregory, K.D., Korst, L.M., Uddin, S.F.G. 
(2015) Maternal Morbidity for Vaginal and Cesarean Deliveries, 
According to Previous Cesarean History: New Data from the Birth 
Certificate, 2013. National Vital Statistics Reports, 64(4). 
Available at: https://www.cdc.gov/nchs/data/nvsr/nvsr64/nvsr64_04.pdf.
[GRAPHIC] [TIFF OMITTED] TR10AU22.202

    We also proposed, in alignment with the proposals for the Hospital 
IQR Program eCQM measure set, to adopt two new eCQMs which eligible 
hospitals and CAHs can self-select to report on for the CY 2024 
reporting period and subsequent years. These eCQMs focus on opioid-
related adverse events during an admission to an acute care hospital, 
and malnutrition. Specifically, we proposed to add the following two 
additional eCQMs to the Medicare Promoting Interoperability Program 
eCQM measure set on which hospitals can self-select to report beginning 
with the CY 2024 reporting period: Hospital Harm-Opioid-Related Adverse 
Event eCQM (NQF #3501e) and Global Malnutrition Composite Score eCQM 
(NQF #3592e). Table IX.H.-13 summarizes the finalized eCQMs in the 
Medicare Promoting Interoperability Program for the CY 2024 reporting 
period and subsequent years. We refer readers to the discussion of the 
same proposals for the Hospital IQR Program in sections IX.E.5.e. and 
IX.E.5.f. of the preamble of this final rule for more information about 
these measures and our policy reasons for proposing them.
    We invited public comments on these proposed measures for the 
Medicare Promoting Interoperability Program.
    Comment: Many commenters expressed support for our proposal to 
adopt the Hospital Harm--Opioid Related Adverse Events eCQM (NQF 
#3501e), stating that its implementation will incentivize opioid 
adverse event monitoring and reporting, which commenters believe may 
also address a disproportionate number of inpatient overdose deaths 
among racial and ethnic minorities. A commenter supported the measure 
and requested information about performance and what the intended 
action with the collected data would be.
    Response: We thank commenters for their support of the measure. The 
intent of the measure is to identify if hospitals have particularly 
high rates of naloxone use, as an indicator of high rates of over-
administration of opioids in the inpatient setting, and thereby 
incentivize improved clinical practices when administering opioids.
    Comment: A commenter did not support the proposed adoption of the 
Hospital Harm--Opioid Related Adverse Events eCQM (NQF #3501e), because 
the measure focuses on a rare event rather than large population- based 
approaches and could create unintended consequences and recommended CMS 
consider or create an alternative measure. A commenter suggested 
considering a re-specification of the measure for the outpatient 
setting. A commenter expressed concern that the Hospital Harm--Opioid-
Related Adverse Event eCQM does not focus on undertreatment of pain or 
other symptoms for which opioids may be appropriately prescribed.

[[Page 49364]]

    Response: We thank commenters for their support of the measure. The 
intent of the measure is not to reduce clinically appropriate use of 
naloxone, nor to bring the measure rate to zero, but to identify if 
hospitals have particularly high rates of naloxone use as an indicator 
of high rates of over-administration of opioids in the inpatient 
setting, and thereby incentivize improved clinical practices when 
administering opioids. We acknowledge that some interested parties have 
expressed concern regarding the measure's impact given the small number 
of overall events. However, our overall analysis during testing 
demonstrated the rate of ORAE ranged from 1.1 to 6.1 per 1,000 
qualified inpatient encounters, signaling there is still opportunity 
for improvement. We also acknowledge that some interested parties have 
expressed concern that implementation of the measure could result in 
deterring or delaying clinically appropriate administration of naloxone 
or under-prescribing of opioids for pain control when clinically 
necessary. However, we reiterate that naloxone is a life-saving 
emergent therapy with clear and unambiguous applications in the setting 
of opioid overdose and we note that it would be unethical to withhold 
lifesaving medication.
    Comment: Many commenters expressed support for our proposal to 
adopt the Global Malnutrition Composite Score eCQM as there is a gap 
between performance measures focused on nutrition care and 
malnutrition. With malnutrition contributing to increased lengths of 
stay, complications and mortality, commenters believe this measure will 
benefit patients, families, caregivers and health care providers.
    Response: We thank the commenters for their support of our proposal 
and agree that the adoption of the Global Malnutrition Composite Score 
eCQM may help address several priority areas identified in the CMS 
Equity Plan for Medicare. This would allow us to further evaluate the 
impact of disparities, while integrating equity solutions across CMS 
programs, and increasing the ability of the healthcare workforce to 
meet the needs of populations that have been disadvantaged and/or 
underserved by the healthcare system.
    Comment: A commenter did not support our proposal to adopt the 
Global Malnutrition Composite Score due to the practicality of 
translating a complex multi-step measure into an eCQM, and have instead 
requested delaying its adoption for one additional year. A few 
commenters expressed concern about operationalizing and implementing 
the measure, its value, and potential duplication with the CMS proposed 
Health Related Social Needs screening measure.
    Response: We appreciate the commenters' concerns about our proposed 
measure. The Screening for Social Drivers of Health measure, discussed 
in section IX.E.5.b. of the preamble of this final rule, and the Global 
Malnutrition Composite Score eCQM both speak to nutrition as a driver 
of health because it is an important contributor to a healthful 
population. However, the measures address different but related goals. 
The Screening for Social Drivers of Health measure focuses on 
incentivizing the screening and identifying of patients for food 
insecurity, defined as limited or uncertain access to adequate quality 
or quantity of food (87 FR 28500). The Global Malnutrition Composite 
Score eCQM focuses not only on screening for malnutrition risk (of 
which food insecurity may be a contributing factor) but also the 
performance of a nutrition assessment and development of a care plan 
for identified malnourished patients (87 FR 28520). We believe these 
two measures are equally important and complementary, but not 
duplicative as they measure different aspects of the care process. We 
also appreciate the recommendation to delay adoption for one additional 
year, however we disagree because we have proposed to adopt this as a 
self-select eCQM. Additionally, we have not yet determined future plans 
with respect to requiring reporting of this measure. Any proposal to 
mandate reporting this eCQM would be made through future notice-and-
comment rulemaking.
    After consideration of the public comments we received, we are 
finalizing our proposals as proposed. We refer readers to the 
discussion of the same proposals for the Hospital IQR Program in 
sections IX.E.5.e. and IX.E.5.f. of the preamble of this final rule for 
more information about these finalized policies.

[[Page 49365]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.203

b. eCQM Reporting and Submission Requirements for the CY 2024 Reporting 
Period and Subsequent Years
    Consistent with our goal to align the eCQM reporting periods and 
criteria in the Medicare Promoting Interoperability Program and the 
Hospital IQR Program, we previously finalized the requirement that 
eligible hospitals and CAHs reporting eCQMs for the Medicare Promoting 
Interoperability Program must report four calendar quarters of data 
from CY 2023 and each subsequent year for: (a) Three self-selected 
eCQMs from the set of available eCQMs for CY 2023 and each subsequent 
year, and (b) the Safe Use of Opioids-Concurrent Prescribing eCQM (NQF 
#3316e), for a total of four eCQMs (85 FR 58975). We did not propose to 
change the data reporting and submission requirements for the CY 2023 
reporting period.
    In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28610), in 
alignment with proposals for the Hospital IQR Program, we proposed to 
modify the eCQM reporting and submission requirements under the 
Medicare Promoting Interoperability Program for eligible hospitals and 
CAHs beginning with the CY 2024 reporting period such that hospitals 
would be required to report four calendar quarters of data for each 
required eCQM: (1) Three self-selected eCQMs; (2) the Safe Use of 
Opioids--Concurrent Prescribing eCQM; (3) the proposed Severe Obstetric 
Complications eCQM; and (4) the proposed Cesarean Birth eCQM, for a 
total of six eCQMs, beginning with the CY 2024 reporting period and for 
subsequent years. We noted that the number of calendar quarters of data 
required and the number of self-selected eCQMs would remain the same, 
but we proposed to increase the number of eCQMs that all eligible 
hospitals and CAHs would be required to report from one to three. This 
proposal was made in conjunction with our proposals discussed in the FY 
2023 IPPS/LTCH PPS proposed rule (87 FR 28609), in which we proposed to 
adopt the Severe Obstetric Complications eCQM and Cesarean Birth eCQM, 
respectively. We stated that we believe by 2024, eligible hospitals and 
CAHs will have had sufficient experience with eCQM reporting to propose 
an increase in the number of required eCQMs from four to six eCQMs. In 
addition, we stated that we believe in light of the maternal health 
crisis as described in sections IX.E.5.d.(1) and IX.E.5.c.(1) of this 
final rule, and our commitment to reducing unacceptably high maternal 
morbidity and mortality rates, it is important to collect and utilize 
quality measure data focused on maternal health to incentive improved 
quality of care.
    As detailed in the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 
28610), we proposed that if our proposals to adopt the Severe Obstetric 
Complications eCQM and the Cesarean Birth eCQM are finalized, these 
measures would be available for eligible hospitals and CAHs to select 
as one of their three self-selected eCQMs for the CY 2023 reporting 
period, and then beginning with the CY 2024 reporting period, all 
eligible hospitals and CAHs would be required to report these two 
eCQMs. We referred readers to the FY 2023 IPPS/LTCH PPS proposed rule 
(87 FR 28555) for the reporting and submission requirements associated 
with the proposal to modify the eCQM reporting requirements for the 
Hospital IQR Program. We invited public comments on these proposed eCQM 
reporting requirements.
    Comment: A few commenters supported our proposal to modify the 
reporting and submission requirements for eCQMs such that beginning 
with the CY 2024 reporting period/FY 2026 payment determination 
hospitals would be required to submit four calendar quarters of data 
from three self-selected eCQMs and three required eCQMs.
    Response: We thank commenters for their support.
    Comment: A commenter supported the proposal to modify eCQM 
reporting

[[Page 49366]]

and submission requirements and requested two years of voluntary 
reporting for the Severe Obstetric Complications eCQM before mandatory 
reporting.
    Response: We thank the commenter for their support of our proposal 
but, regarding a delay in mandatory reporting of our two finalized 
perinatal eCQMs, reiterate that addressing the maternal health crisis, 
improving maternal health, and closing any gaps that exist as a result 
of health disparities are among our top goals and mandatory reporting 
of the Severe Obstetric Complications eCQM beginning with the CY 2024 
reporting period advances that goal.
    Comment: Many commenters did not support the proposal to modify 
eCQM reporting and submission requirements due to current eCQM 
challenges such as the lack of frequent and actionable eCQM performance 
feedback, difficulties extracting data from production ready eCQM 
products delivered by developers, insufficient time for vendor design 
and development and for hospitals to complete testing, validation, 
staff education before required reporting, and the costly and prolonged 
process of eCQM health care provider adoption. A few commenters 
recommended a delayed and phase implementation of modified reporting 
and submission requirements as clinical quality measure reporting is 
moving from eCQMs to dQMs.
    Response: We appreciate commenters' concerns related to 
modifications of the eCQM reporting and submission requirements due to 
eCQM reporting challenges experienced by hospitals. We urge hospitals 
to continue to work with their vendor to secure timely delivery of 
their products and we believe our finalized policy will offer 
opportunities for hospitals that are prepared to voluntarily report the 
two perinatal eCQMs to do so for the CY 2023 reporting period while 
providing more than one year for other hospitals to prepare and 
implement the two perinatal eCQMs for the CY 2024 reporting period.
    With respect to the challenges of extracting eCQM data, we believe 
that our proposal to modify the eCQM reporting and submission 
requirements advances our goal of increasing the use of EHR data for 
quality measurement and improvement. We also believe the implementation 
of the production ready product supports feasible data extraction 
processes, and we will be considerate of this feedback in future 
rulemaking.
    We understand commenters' concerns related to the effort by 
hospitals to customize their health IT and to potentially update 
workflows and train staff following vendor delivery of their product; 
however, we expect the burden for hospitals to be no greater than that 
already required to comply with CMS annual updates which includes the 
eCQM specifications, educational materials, value sets, code systems 
direct reference codes, and terminology that are posted on the eCQI 
Resource Center.\1142\
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    \1142\ https://ecqi.healthit.gov/.
---------------------------------------------------------------------------

    We recognize the process of hospital adoption of eCQMs can be 
costly and prolonged. We refer readers to section XII.B.9.e. of the 
preamble of this final rule (information collection requirements) for a 
detailed discussion of our burden estimates associated with the 
modification of our eCQM reporting and submission requirements. We 
believe the long-term benefits associated with reporting a full year of 
data for six eCQMs will outweigh the burdens and that increasing the 
number of eCQMs for which hospitals are required to report will produce 
more comprehensive and reliable quality information for patients and 
health care providers. We will continue to look across CMS programs to 
identify areas for further streamlining of reporting requirements. 
Also, as referenced in section IX.C. of the preamble of this final 
rule, in the ``Continuing to Advance Digital Quality Measurement and 
Use of Fast Healthcare Interoperability Resources (FHIR) in Hospital 
Quality Programs--Request for Information,'' we also believe utilizing 
standardized data for EHR-based measurement (based on the FHIR 
standard) and aligning where possible with other interoperability 
requirements can reduce the data collection burden incurred by health 
care providers.
    For the purpose of reporting quality measures and alleviating the 
concern about the costly and prolonged process of eCQM adoption. We 
appreciate the comments and interest in opportunities to reduce 
reporting burden, and we will continue to take all under consideration 
as we develop future regulatory proposals.
    Comment: A commenter did not support due to the cost, time and 
limited IT resources barriers faced by small rural hospitals for EHR 
changes and updates.
    Response: We appreciate the commenter's concern regarding the cost, 
time and IT resources required to in eCQM reporting and submission. We 
establish program requirements considering all hospitals and CAHs that 
participate in the Medicare Promoting Interoperability Program for 
eligible hospitals and CAHs, which involves a wide spectrum of 
capabilities and resources with respect to eCQM reporting. We 
acknowledge that advancing quality improvement supported by health IT 
can present unique challenges for small or rural hospitals. We believe 
our finalized policy to modify the eCQM reporting and submission 
requirements will offer opportunities for hospitals that are prepared 
to voluntarily report the two perinatal eCQMs--Cesarean Birth and 
Severe Obstetric Complications--to do so for the CY 2023 reporting 
period, while providing more than one year for other hospitals to 
prepare and implement the two perinatal eCQMs for mandatory reporting 
in the CY 2024 reporting period and subsequent years. We recognize the 
cost and time associated with eCQM adoption and refer readers to 
section XII.B.9.k. of the preamble of this final rule (information 
collection requirements) for a discussion of our burden estimates 
associated with the modification of our eCQM reporting and submission 
requirements. When considering modifications to program requirements, 
we have, and may continue to, consider the recommendations from the 
rural health care providers to ensure eCQMs policies are meaningful to 
quality improvement for small, rural hospitals.
    Comment: A few commenters did not support the proposal to modify 
eCQM reporting and submission requirements and recommended a phased and 
incremental timeline for increasing the number of required eCQMs. A 
commenter recommended financial incentives to support hospitals with 
changing eCQM requirements.
    Response: We thank the commenters and acknowledge the concerns 
about the pace of change in eCQM reporting and submission policy. 
However, we believe that hospitals have had several years to report 
eCQM data. After holding eCQM reporting and submission policies 
constant for a number of years in order to give hospitals and their 
vendors additional time to improve eCQM reporting capabilities, we 
intended to transition to more robust reporting.
    Comment: Several commenters offered recommendations such as 
alignment of eCQM data submissions with the quarterly timeline for 
submission of Hospital IQR Program's chart-based measure data, an 
analysis of required measures and a proposal to remove measures less 
impactful to improved health outcomes, limit eCQMs to self-selection 
until hospitals gain experience to confirm feasibility and reliability, 
delay of public reporting

[[Page 49367]]

until one year of data is reported and a proposal for a quarter 
exception rather than a full year hardship exception for eCQM reporting 
in future rulemaking. A commenter recommended reconsideration of the 
proposal.
    Response: We thank commenters for their comments. Concerning the 
eCQM data submission timeline, the data submission deadline for eCQM 
data under the Medicare Promoting Interoperability Program for eligible 
hospitals and CAHs continues to be the end two months following the 
close of the calendar year. We note the submission deadline may be 
moved to the next business day if it falls on a weekend or Federal 
holiday. We did not propose any changes to this policy in the FY 2023 
IPPS/LTCH proposed rule. We plan to monitor the implementation of the 
finalized eCQM data reporting and submission requirements and welcome 
continued feedback from stakeholders through webinars, listservs, and 
help desk questions.
    We utilize principles and frameworks to assess clinical quality 
measures included in our programs including the CMS National Quality 
Strategy \1143\ and the Meaningful Measures Initiative,\1144\ which 
identifies high-priority areas for quality measurement and improvement 
to assess core issues most critical to high-quality healthcare and 
improving patient outcomes. In 2021, we launched Meaningful Measures 
2.0 to promote innovation and modernization of all aspects of quality, 
and to address a wide variety of settings, stakeholders, and measure 
requirements.\1145\ We will continue to utilize this approach.
---------------------------------------------------------------------------

    \1143\ https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Value-Based-Programs/CMS-Quality-Strategy.
    \1144\ https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/MMF/General-info-Sub-Page.
    \1145\ Centers for Medicare & Medicaid Services. (2021). 
Meaningful Measures 2.0: Moving from Measure Reduction to 
Modernization. Available at: https://www.cms.gov/meaningful-measures-20-moving-measure-reduction-modernization. We note that 
Meaningful Measures 2.0 is still under development.
---------------------------------------------------------------------------

    We believe the Cesarean Birth eCQM and Severe Obstetric 
Complications eCQM present unique opportunities for large-scale quality 
measurement and activities that can improve the short- and long-term 
health outcomes for mothers and children (87 FR 28508) and self-
selection of these measures would not advance us toward our short-and 
long-term goals.
    We acknowledge commenters' concern about public reporting and refer 
readers to the FY2021 IPPS/LTCH PPS final rule (85 FR 58976) for a 
discussion of our previously finalized public reporting of eCQM data 
policy. Additionally, we would like to remind readers that the Medicare 
Promoting Interoperability Program allows hardship exception 
applications for extreme and uncontrollable circumstances, including 
vendor issues. Additional information on this process is available at: 
https://www.cms.gov/Regulations-and-Guidance/Legislation/EHRIncentivePrograms/PaymentAdj_Hardship. We did not propose any 
changes to this policy in the FY 2023 IPPS/LTCH PPS proposed rule. We 
thank commenters for their recommendations. We acknowledge commenters' 
recommendations, and we may continue to take all comments into account 
as we develop future regulatory proposals.
    Comment: A commenter requested clarification for hospitals without 
obstetric departments or providing labor and delivery services. A 
commenter expressed concern that hospitals could be penalized due to 
hospital or vendor inability to meet reporting and submission 
requirements.
    Response: If a hospital does not have an obstetrics department or 
has few or no deliveries during a reporting period, the hospital may 
submit a zero-denominator declaration or a case threshold exemption for 
an eCQM that is being reported. A QRDA Category I file with patients 
meeting the initial patient population of the applicable measures, a 
zero-denominator declaration and/or a case threshold exemption all 
count toward a successful submission for eCQMs for the Medicare EHR 
Incentive Program (now called the Promoting Interoperability Program) 
(82 FR 38482). Hospitals may request a hardship exception if they are 
unable to fulfill program requirements due to extreme and 
uncontrollable circumstances, including vendor issues. Additional 
information on this process is available at: https://www.cms.gov/Regulations-and-Guidance/Legislation/EHRIncentivePrograms/PaymentAdj_Hardship.
    After consideration of the public comments we received, we are 
finalizing our proposal as proposed.
11. Patient Access to Health Information Measure--Request for 
Information (RFI)
    Patient use of portals to access their health information has been 
tied to benefits such as improvements in access, quality of care, and 
health outcomes, and reductions in healthcare expenditures.\1146\ In 
particular, access to health information has been shown to enable the 
discovery of medical errors, to improve medication adherence, and to 
promote communication between the patient and health care 
provider.\1147\ However, despite the fact that surveyed patients 
experiencing shared access to notes with health care providers has been 
largely positive,\1148\ voluntary uptake and use of patient portals has 
been low, with nearly two-thirds of hospitals having less than 25 
percent of patients activate access to the hospital's patient portal in 
2017.\1149\ Health care provider encouragement (and other facilitating 
conditions), perceived usefulness, ease of use, control of health 
information, and enhanced communication are demonstrated as 
facilitators, while concerns of privacy, security, and lack of 
awareness have been tied to barriers of use.1150 1151
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    \1146\ Ronda MC, Dijkhorst-Oei LT, Rutten GE. Reasons and 
barriers for using a patient portal: survey among patients with 
diabetes mellitus. J Med internet Res. 2014 Nov 25;16(11):e263. doi: 
10.2196/jmir.3457. PMID: 25424228; PMCID: PMC4260081.
    \1147\ Wildenbos GA, Peute L, Jaspers M. Facilitators and 
Barriers of Electronic Health Record Patient Portal Adoption by 
Older Adults: A Literature Study. Stud Health Technol Inform. 
2017;235:308-312. PMID: 28423804.
    \1148\ Walker J, Leveille S, Bell S, Chimowitz H, Dong Z, Elmore 
JG, Fernandez L, Fossa A, Gerard M, Fitzgerald P, Harcourt K, 
Jackson S, Payne TH, Perez J, Shucard H, Stametz R, DesRoches C, 
Delbanco T. OpenNotes After 7 Years: Patient Experiences With 
Ongoing Access to Their Clinicians' Outpatient Visit Notes. J Med 
internet Res.
    \1149\ Henry J, Barker W, Kachay L. Office of the National 
Coordinator for Health Information Technology (ONC) Data Brief No. 
45 (April 2019). Electronic Capabilities for Patient Engagement 
among U.S. Non-Federal Acute Care Hospitals: 2013-2017. Available 
at: https://www.healthit.gov/sites/default/files/page/2019-04/AHApatientengagement.pdf.
    \1150\ Powell KR. Patient-Perceived Facilitators of and Barriers 
to Electronic Portal Use: A Systematic Review. Comput Inform Nurs. 
2017 Nov;35(11):565-573. doi: 10.1097/CIN.0000000000000377. PMID: 
28723832.
    \1151\ Alaa A. Abd-alrazaq, Bridgette M. Bewick, Tracey 
Farragher, Peter Gardner, Factors that affect the use of electronic 
personal health records among patients: A systematic review, 
International Journal of Medical Informatics, Volume 126, 2019, 
Pages 164-175, ISSN 1386-5056, https://doi.org/10.1016/j.ijmedinf.2019.03.014.
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    The Health Information National Trends Survey (HINTS), a large, 
nationally representative survey operated by the National Cancer 
Institute (with support from ONC), is conducted routinely and contains 
key utilization data on consumer access and use of their online medical 
record through patient portals. The HINTS results showed the rates of 
individuals being offered and subsequently using their health 
information through a patient portal, as well as use of mobile health 
applications (apps) and the role health care providers play in

[[Page 49368]]

encouraging use.\1152\ Results showed that health care providers and 
staff have a substantial role in influencing patient use of the portal.
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    \1152\ Johnson C, Richwine C, Patel V. Office of the National 
Coordinator for Health Information Technology (ONC) Data Brief, No. 
57 (September 2021). Individuals' Access and Use of Patient Portals 
and Smartphone Health Apps, 2020.
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    In the past for the Medicare Promoting Interoperability Program, we 
attempted to promote patient access to their health information through 
measuring the number of patients who actively engaged with the 
electronic health record through the View, Download, or Transmit (VDT) 
measure at 42 CFR 495.24(c)(6)(ii)(A). In the FY 2019 IPPS/LTCH PPS 
final rule (83 FR 41636 through 41668), we renamed the Patient 
Electronic Access Objective to the Provider to Patient Exchange 
Objective and updated the measures within the Provider to Patient 
Exchange Objective. Specifically, we removed the standalone VDT measure 
from the Medicare Promoting Interoperability Program in response to 
interested party feedback, including hospitals and hospital 
associations detailing the significant challenges they faced in 
implementing measures that require patient action (83 FR 41665). These 
challenges included, but were not limited to, patients who have limited 
knowledge of, proficiency with, or access to information technology; 
patients declining to access the portals provided by the eligible 
hospital or CAH to view, download, and transmit their health 
information via this platform; as well as the lack of availability of 
user-friendly portals and the immaturity of the health IT 
infrastructure needed to facilitate useful access and use of their own 
health information. We also noted that data analysis of the VDT measure 
showed low percentages of patients taking action to view, download, and 
transmit their health information (83 FR 41665). Additionally, in the 
FY 2019 IPPS/LTCH PPS final rule (83 FR 41661 through 41663) we changed 
the name of the Provide Patient Access measure at 42 CFR 
495.24(c)(5)(ii)(A) to Provide Patients Electronic Access to Their 
Health Information at 42 CFR 495.24(e)(7)(ii) and finalized changes to 
the measure description. These measure changes included a requirement 
for eligible hospitals or CAHs to provide timely access for viewing, 
downloading or transmitting their health information for at least one 
unique patient discharged using any application of the patient's choice 
(83 FR 41661 through 41663). This change emphasized timely electronic 
access of patient health information rather than requiring health care 
providers to be accountable for patient actions.
    Through the current Provide Patients Electronic Access to Their 
Health Information measure in the Provider to Patient Exchange 
Objective, we are ensuring that patients have access to their health 
information through any application of their choice that is configured 
to meet the technical specifications of the Application Programing 
Interface (API) in the CEHRT of the eligible hospital or CAH. Promoting 
the use of API-enabled applications that provide timely access to 
updated information whenever the patient needs that information is an 
integral step in enhancing patient access and use of their health 
information. These API-enabled applications should be configured using 
standardized technology and contain the information the patient needs 
to make informed decisions about their care in a way the patient 
understands, and that recognizes the community's level of access to 
devices and internet connectivity. While we removed the VDT measure 
holding eligible hospitals and CAHs responsible for patient action (83 
FR 41665), we still require that the technical capabilities be in place 
within an eligible hospital's or CAH's CEHRT through the Provide 
Patients Electronic Access to Their Health Information measure should 
patients choose to access and use their health information (83 FR 41661 
through 41663).
    We continue to believe in the importance of taking a patient-
centered approach to health information access and moving to a system 
in which patients have immediate access to their electronic health 
information and can be assured that their health information will 
follow them as they move throughout the health care system. Recognizing 
the concerns and barriers with the previous VDT measure discussed 
previously, but acknowledging the advancements made within the health 
IT industry over the past few years, this request for information (RFI) 
sought a broad array of public comments regarding how to further 
promote equitable patient access and use of their health information 
without adding unnecessary burden on the hospital or health care 
provider. Specifically, we sought public comment on the following 
questions:
     Moving beyond providing the information and technical 
capabilities to access their data, are there additional approaches to 
promote patient access and use of their health information? Are there 
examples of successful approaches or initiatives that have enhanced 
patient access and use of their health information?
    ++ Would allowing patients to add information to their records be 
useful in promoting patient access and utilization? Are there other 
incentives that would promote patient access?
    ++ Are there potential unintended consequences in allowing patients 
to add information to their records? What could be done to mitigate any 
potential unintended consequences?
    ++ Are there certain tools found to be useful in promoting patient 
access and use of their health information?
     Recent studies have raised concerns about the presence of 
racial bias and stigmatizing language within EHRs that could lead to 
unintended consequences if patients were to obtain disparaging notes 
regarding their medical care.1153 1154
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    \1153\ Sun M, Oliwa T, Peek ME, Tung EL. Negative Patient 
Descriptors: Documenting Racial Bias in the Electronic Health 
Record. Health Affairs 41, No. 2 (2022): 203-211. doi:10.1377/
hlthaff.2021.01423.
    \1154\ Himmelstein G, Bates D, Zhou L. Examination of 
Stigmatizing Language in the Electronic Health Record. JAMA Netw 
Open. 2022;5(1):e2144967. doi:10.1001/jamanetworkopen.2021.44967.
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    ++ What policy, implementation strategies, or other considerations 
are necessary to address existing racial bias or other biases and 
prevent use of stigmatizing language?
     Additional analysis of HINTS data provides insights into 
common barriers to patient portal access and use as well as 
characteristics that can help predict which individuals are more likely 
to experience certain barriers (for example, preference for in-person 
communication with their health care provider is one of the most 
prevalent barriers experienced more often by older adults and 
women).\1155\
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    \1155\ Turner K, Clary A, Hong Y, Alishahi Tabriz A, Shea CM. 
Patient Portal Barriers and Group Differences: Cross-Sectional 
National Survey Study. J Med internet Res 2020;22(9):e18870.
---------------------------------------------------------------------------

    ++ What are the most common barriers to patient access and use of 
their health information that have been observed? Are there differences 
by populations or individual characteristics?
     Patients' health information may be found in multiple 
patient portals. How could CMS or HHS facilitate individuals' ability 
to access all their health information in one place?
    ++ If patient portals connected to a network participating in the 
recently launched TEFCA,1156 1157 would this

[[Page 49369]]

enable more seamless access to individual health information across 
various patient portals?
---------------------------------------------------------------------------

    \1156\ The Trusted Exchange Framework (TEF): Principles for 
Trusted Exchange. ONC January 2022: https://www.healthit.gov/sites/default/files/page/2022-01/Trusted_Exchange_Framework_0122.pdf.
    \1157\ Common Agreement for Nationwide Health Information 
Interoperability V1. ONC. January 2022: https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf.
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     With the advancement of HIT, EHRs and other health-related 
communication technologies, there are concerns of equity to health 
outcomes and access with populations who could receive greater benefits 
from these technologies but are less likely to adopt 
them.1158 1159 What policy, governance and implementation 
strategies or other considerations are necessary to ensure equal access 
to patient portals, equitable portal implementation, appropriate design 
and encouragement of use?
---------------------------------------------------------------------------

    \1158\ Sarkar U, Karter AJ, Liu JY, et al. The literacy divide: 
health literacy and the use of an internet-based patient portal in 
an integrated health system--results from the diabetes study of 
Northern California (DISTANCE). J Health Commun 2010; 15 (Suppl 2): 
183-96.
    \1159\ Ackerman SL, Sarkar U, Tieu L, et al. Meaningful use in 
the safety net: a rapid ethnography of patient portal implementation 
at five community health centers in California. J Am Med Inform 
Assoc 2017; 24 (5): 903-12.
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     What challenges do eligible hospitals and CAHs face when 
addressing patient questions and requests resulting from patient access 
of patient portals or access of data through use of a mobile app? What 
can be done to mitigate potential burden?
     For patients who access their health information, how 
could CMS, HHS, and health care providers help patients manage their 
health through the use of their personal health information?
     Do you believe the API and app ecosystem is at the point 
where it would be beneficial to revisit adding a measure of patient 
access to their health information which assesses health care providers 
on the degree to which their patients actively access their health 
information?
    * What should be considered when designing a measure of patient 
access of their health information through portals or apps?
    We welcomed input on how we can encourage and enable patient access 
to and use of their health information to manage and improve their care 
across the care continuum. We thank the interested parties who 
submitted comments for our review and consideration.
    Comment: Many commenters provided input on additional approaches to 
promote patient access and use of patient health information. Several 
commenters supported individuals contributing to their own records as 
an approach to promote patient access to and engagement with their 
health information. These commenters offered a number of successful 
suggestions for individuals to contribute to their records, as well as 
important considerations regarding potentially duplicative or erroneous 
information being added, and the need for clinical review of 
information entered by individuals before inclusion in the medical 
record. A commenter recommended CMS work with ONC to develop 
certification criteria and technical capabilities to amend or update 
their records. Several commenters recommended including beneficial 
capabilities within the patient portal to promote patient access, such 
as appointment scheduling, prescription refills, immediate release of 
lab results, push notifications to patients, and secure physician 
messaging. Many commenters provided support for TEFCA implementation 
and the use of HIEs as an approach to promote a standard nationwide 
method of collecting patient health data and consolidating into one 
view for seamless patient access. Commenters stated that TEFCA has a 
lot of potential to improve patient access to health information, but 
CMS should monitor the progress of TEFCA implementation.
    Many commenters provided input on potential unintended consequences 
and concerns around increasing patient access to their health 
information related to racial bias and stigmatizing language. A few 
commenters stated the importance of developing educational materials 
for health care providers to reduce stigmatizing language, including 
providing guidance on the information blocking regulations so health 
care providers are aware of requirements for patient access to clinical 
notes, and provide patient-facing resources to address questions when 
reviewing records. A few commenters stated the importance of accurate 
translation of health information from other languages and how 
technology can provide reliable real-time translation of information 
contained in a portal. A commenter recommended implementing a policy to 
permit patients to complete sexual orientation, and gender identity 
fields within the patient portal.
    Many commenters provided input on the potential barriers to patient 
access including those associated with individuals having limited 
access to technology or insufficient understanding of how to use health 
technology who encounter difficulties navigating portals. Several 
commenters stated that racial and ethnic minority groups, 
socioeconomically disadvantaged, rural, elderly, and people who are at 
risk of poor health outcomes lack physical tools including computers, 
email addresses, smartphones, and inconsistent internet access. 
Commenters discussed the absence of technical assistance to help 
patients access information as well as the lack of understanding of 
their rights under the Health Insurance Portability and Accountability 
Act of 1996 (HIPAA) Privacy Rule, including the right to access an 
electronic copy when their health information is stored electronically. 
A commenter stated the success of publishing health care provider 
compliance rates with patient access requirements under HIPAA and 
recommended similar approaches to help improve patient access. A few 
commenters discussed the complications and potential barriers regarding 
proxy access to patient portals and patient applications. Additionally, 
commenters stated the lack of a unique patient identifier or identity 
proofing and authentication creates a barrier to access health 
information.
    Many commenters provided input on challenges and burdens faced by 
hospitals including cumbersome and decentralized processes for 
requesting records as well as the manual workflows for health 
information professionals fulfilling requests. Commenters recommended 
CMS continue to monitor challenges related to patient access of data 
and solicit feedback from interested parties, particularly health 
information professionals who field patient questions and concerns 
related to the access of data.
    Many commenters provided input and recommendations on policy, 
governance, and implementation considerations for promoting patient 
access and the role of CMS and HHS. Commenters recommended continued 
collaboration with OCR and ONC to develop guidance regarding HIPAA 
requirements, particularly in the context of health information 
exchanges and networks, as well as guidance regarding the lack of HIPAA 
protections when data moves to third-party applications. Commenters 
recommended CMS remain actively engaged in the work of standards 
development organizations to determine the best avenue for regulatory 
alignment. Commenters also recommended CMS work with ONC to improve 
patient matching and identification to promote longitudinal records, 
and further advance and ensure adoption of standards. Many commenters 
recommended providing funding for equipment and studying the optimal 
use of digital technology including wearable devices. A few

[[Page 49370]]

commenters recommended CMS use their authority and exercise enforcement 
to ensure health plans subject to CMS oversight facilitate patient 
access and implement APIs.
    Many commenters provided input on the prospect of adding a measure 
of patient access. A few commenters supported adding a measure for 
patient access to their health information but several commenters did 
not support adding a new measure of patient access stating many reasons 
including lack of control, unnecessary burden, and existing patient 
access barriers.
    Response: We appreciate the comments and suggestions we have 
received. While we will not be responding to specific comments 
submitted in response to this RFI, we believe that this input is 
valuable in our efforts to continue to promote patient access to their 
health information. We may consider these suggestions in future 
rulemaking.

X. Changes for Hospitals and Other Providers

A. Codification of the Costs Incurred for Qualified and Non-Qualified 
Deferred Compensation Plans

1. Background
    Currently, certain costs incurred on behalf of Deferred 
Compensation Plans may be allowable costs under Medicare to the extent 
such costs are related to the reasonable and necessary cost of 
providing patient care and represent costs actually incurred. 
Reasonable cost reimbursement is addressed in section 1861(v)(1)(A) of 
the Act. Section 1861(v)(1)(A) of the Act defines ``reasonable cost,'' 
in part, as the cost actually incurred, excluding costs found to be 
unnecessary in the efficient delivery of needed health services. 
Section 1861(v)(1)(A) of the Act does not specifically address the 
determination of reasonable costs, but authorizes the Secretary to 
promulgate regulations and principles to be applied in determining 
reasonable costs.
    We have issued regulations implementing this provision of the Act, 
including 42 CFR 413.9(a), which provides that the payments ``must be 
based on the reasonable cost of services covered under Medicare and 
related to the care of beneficiaries.'' In addition, Sec.  
[thinsp]413.9(c)(2) states that ``[t]he provision in Medicare for 
payment of reasonable cost of services is intended to meet the actual 
costs.'' Further, Sec.  413.9(c)(3) provides that ``[r]easonable cost 
includes all necessary and proper expenses incurred in furnishing 
services . . . .'' Therefore, in accordance with the statute, the 
regulations include two principles that help guide the determination of 
which expenses may be considered allowable reasonable costs that can be 
paid under Medicare; that is, such costs must be ``related'' to the 
care of Medicare beneficiaries, and such costs must actually be 
``incurred.''
    Consistent with these provisions, we have issued instructions in 
sections 2140 through 2142 of the Medicare Provider Reimbursement 
Manual, Part I (PRM-I) for determining and reporting the policies that 
govern how providers of services are to determine and report the 
allowable costs of Deferred Compensation Plans. Section 2140.1 of PRM-I 
defines Deferred Compensation as ``remuneration currently earned by an 
employee but which is not received until a subsequent period, usually 
after retirement. Accordingly, a Deferred Compensation Plan defers the 
receipt of income beyond the year in which it is earned.'' The policies 
for Deferred Compensation plans that we have established in sections 
2140 through 2142 of PRM-I vary depending on whether a plan is funded 
using an allowable funding mechanism or unfunded, and whether a plan is 
a Defined Contribution plan or a Defined Benefit plan. The term funded 
essentially means that funds are set aside to protect payment of future 
benefits for plan participants, and not simply paid out of current 
revenues, as is the case with unfunded plans. Allowable Non-Qualified 
Deferred Compensation Plan costs that are considered unfunded are based 
on reasonable benefits that providers of services paid to participating 
employees.
    Allowable Defined Contribution plan costs are based on reasonable 
contributions made by providers of services to Defined Contribution 
accounts. Prior to August 2011, allowable funded Defined Benefit plan 
costs were based on Employee Retirement Income Security Act of 1974 
(ERISA) components of accrued pension costs (for example, Normal Cost, 
Actuarial Accrued Liability, Actuarial Value of Assets) if the 
resulting computation of costs was funded into an approved account. In 
August 2011, the FY 2012 IPPS/LTCH PPS final rule (76 FR 51693 through 
51697), established regulations for reporting costs of Qualified 
Defined Benefit plans for Medicare cost-finding purposes. Specifically, 
for cost reporting periods beginning on or after October 1, 2011, a 
provider of services cost equals the cash basis contribution deposits 
plus any carry forward contributions, subject to a limitation (Sec.  
413.100(c)(2)(vii)(D)(1)). Providers of services with current 
contributions and carry forward contributions that exceed the limit may 
request approval of excess contributions, which are reviewed by the 
contractor on a case-by-case basis (Sec.  413.100(c)(2)(vii)(D)(3)).
    At the time the FY 2012 IPPS/LTCH final rule was issued, the 
regulations at Sec. Sec.  413.24 and 413.100 specified that pension 
costs of Qualified Defined Benefit plans were reported on an accrual 
basis of accounting method. To conform this accrual requirement in the 
regulations with the cash-basis methodology for reporting pension costs 
finalized in the FY 2012 IPPS/LTCH PPS final rule, in the FY 2013 IPPS/
LTCH PPS final rule (77 FR 53448), we amended the general cost 
reporting rules under Sec. Sec.  413.24(a)(2) and 413.100(c)(2)(vii)(D) 
to note the exception for recognizing actual contributions funded 
during the cost reporting period on a cash basis.
    In the FY 2023 IPPS/LTCH proposed rule (87 FR 28612 through 28618), 
we proposed to codify and clarify additional policies relating to 
Deferred Compensation in a new section in part 413, subpart F. We did 
not propose to change our current policies for allowable Deferred 
Compensation costs associated with Qualified and Non-Qualified Deferred 
Compensation Plans (the plans) that are included in Medicare cost 
reports. Nor did we propose to change the way in which Deferred 
Compensation costs are to be audited by the Medicare Administrative 
Contractors (MACs).
    In the paragraphs that follow, we discuss our proposals in the FY 
2023 IPPS/LTCH proposed rule. We received no comments on these 
proposals and are finalizing our proposals without modification.
2. Qualified and Funded Non-Qualified Deferred Compensation Plans 
(Sec.  413.99)
    In accordance with section 1861(v)(1)(A) of the Act, in the FY 2023 
IPPS/LTCH proposed rule (87 FR 28613), we proposed to add a new Sec.  
413.99 in subpart F of part 413 of title 42, titled ``Qualified and 
Funded Non-Qualified Deferred Compensation Plans,'' to establish rules 
for allowable and non-allowable costs incurred for the plans, by 
providers of services, under the program. Our proposals, which we 
discuss in more detail throughout this section of this final rule, set 
forth general requirements; definitions; requirements for costs of the 
plans to be allowable under the program; additional requirements for 
payments to funded defined benefit plans; data and documentation 
requirements to support payments/contributions to the plans;

[[Page 49371]]

and allowable administrative and other costs associated with the plans, 
including costs related to the Pension Benefit Guaranty Corporation 
(PBGC).
    We received no comments on these proposals and are finalizing our 
proposals without modification.
3. Statutory Basis, Scope, and Definitions (Sec.  413.99(a))
    In accordance with section 1861(v)(1)(A) of the Act, in the FY 2023 
IPPS/LTCH proposed rule (87 FR 28613), we proposed to establish the 
``Basis,'' ``Scope,'' and ``Definitions'' of these regulations that 
determine the allowable and non-allowable costs of the plans under the 
program at proposed new Sec.  413.99(a)(1), (2), and (3), respectively. 
Specifically, we proposed at new Sec.  413.99(a)(1) to specify that all 
payments to providers of services must be based on the ``reasonable 
cost'' of services covered under Title XVIII in accordance with section 
1861(v) of the Act and the regulations in 42 CFR part 413. In addition, 
we proposed at new Sec.  413.99(a)(2) to specify that this section and 
Sec.  413.100(c)(2)(vii) will apply to Medicare's treatment of the 
costs incurred for Qualified and Non-Qualified Deferred Compensation 
Plans.
    CMS has previously defined certain terms related to the program's 
policies on Deferred Compensation and the plans in sections 2140 
through 2142 of PRM-I. In the FY 2023 IPPS/LTCH proposed rule (87 FR 
28613), we proposed to codify these definitions, with clarifications 
where appropriate, at new Sec.  413.99(a)(3). We also proposed to add 
definitions for several new terms to ensure clarity and consistent 
application. Specifically, we proposed at new Sec.  413.99(a)(3) to 
establish, for purposes of Sec.  413.99, definitions for the following 
terms: Deferred Compensation, Employee Retirement Income Security Act 
of 1974 (ERISA), Funded Plan, Non-Qualified Deferred Compensation Plan 
(NQDC), Non-Qualified Defined Benefit Plan (NQDB), Pension Benefit 
Guaranty Corporation (PBGC), Qualified Defined Benefit Plan (QDBP), 
Qualified Defined Contribution or Individual Account Plan (QDCP), and 
Unfunded plan. The specific definitions we proposed to codify at Sec.  
413.99(a)(3) appear in the proposed rule at 87 FR 28648 through 28649.
    We received no comments on this proposal and are finalizing this 
proposal without modification.
4. Principle Requirements (Sec.  413.99(b))
    In the FY 2023 IPPS/LTCH proposed rule (87 FR 28613 through 28614), 
we proposed to establish at new Sec.  413.99(b) the ``Principle 
requirements'' that must be satisfied by all Deferred Compensation 
Plans in order for costs incurred by a provider of services in 
connection with such plans to be allowable under the program. A formal 
Deferred Compensation Plan is an agreement between the provider of 
services and its participating employees, in which the agreeing parties 
can make contributions to the plan for the exclusive benefit of its 
participating employees. Proposed Sec.  413.99(b)(1) would specify that 
amounts be contributed by a provider of services, or an employee of the 
provider of services, to a Qualified or Non-Qualified Deferred 
Compensation Plan, established and maintained by the provider of 
services to provide retirement income to employees or to result in the 
deferral of income by employees for periods extending to the 
termination of covered employment or beyond. Contributions or payments 
made by a provider of services for the benefit of its employees to a 
Qualified or Non-Qualified Deferred Compensation Plan are allowable 
when, and to the extent that, such costs are actually incurred by the 
provider of services and found to be reasonable and necessary under the 
principles of reasonable cost.
    Contracts or agreements between hospital-based physicians and 
hospitals involve a variety of arrangements under which the physician 
is compensated by the hospital for the full range of services within 
the institution. We proposed to include requirements for recognition of 
the costs incurred to fund the plans for hospital-based physician 
patient care services and guarantee arrangements for physician 
emergency room services. Deferred compensation paid for physician 
services to hospitals and SNFs is part of physician compensation under 
Sec.  415.60(a) and is directly attributable to an employee's salary. 
Deferred compensation is salary earned in the current period that is 
not received until a subsequent period, usually after retirement. 
Defined Contribution plans and Defined Benefit plans generally specify 
contributions and benefits as a percentage of employee salary. Deferred 
compensation based on unallowable compensation is also unallowable. 
Consistent with the policies in PRM-I, we proposed in Sec.  
413.99(b)(2) to specify that costs incurred by a hospital or SNF to 
fund a Qualified or Non-Qualified Deferred Compensation Plan for a 
provider-based physician must meet certain requirements to be 
allowable. These proposed requirements at Sec.  413.99(b)(2)(i) through 
(iii) would establish that: (i) the allocation of physician 
compensation costs required under Sec.  415.60 does not attribute the 
provider-based physician's Deferred Compensation entirely to one 
category of service and his current compensation to another; (ii) 
contributions or payments toward the Qualified or Non-Qualified 
Deferred Compensation Plan do not include any cost excluded from the 
definition of physician compensation at Sec.  415.60(a); and (iii) the 
amount of Deferred Compensation does not exceed the amount specified in 
the agreement required by Sec.  415.60(g).
    In situations where the provider is merely acting as the billing 
agent for the physician whose remuneration is derived from billing for 
patient care services, the Medicare program will not recognize such 
remuneration. As a result, these proposed requirements would also 
specify that an arrangement between a physician and a provider of 
services under which the physician is reimbursed for patient charges, 
but the provider of services does the billing as a Deferred 
Compensation agreement, is not allowed. We proposed to codify this 
policy at Sec.  413.99(b)(2)(iv).
    We proposed to codify at Sec.  413.99(b)(2)(v) that the costs 
incurred for physician guarantee arrangements for hospital emergency 
room availability services must also meet the additional requirements 
that: (1) the terms of both the guarantee arrangement and the Deferred 
Compensation plan establish the amounts to be included at the beginning 
of the hospital's cost reporting period; (2) the amount of Deferred 
Compensation is included in the guaranteed amount; (3) the hospital 
contributes to the fund established under the Deferred Compensation 
Plan from its own funds; (4) the amount of Deferred Compensation that 
is allowable is limited to the amount by which the guarantee, including 
Deferred Compensation, exceeds the total billed by the hospital to all 
patients for the physician's patient care services; and (5) when the 
physician's charges to all patients equal or exceed the amount 
guaranteed by the hospital, the program does not recognize a Deferred 
Compensation contribution/payment.
    We received no comments on the proposed principle requirements of 
Sec.  413.99(c) and are finalizing this proposal without modification.
5. Requirements for Non-Qualified and Qualified Deferred Compensation 
Plans (Sec.  413.99(c))
    In the FY 2023 IPPS/LTCH proposed rule (87 FR 28614 through 28615), 
we proposed to codify the guidance from sections 2140 through 2142 of 
PRM-I regarding the requirements that must be

[[Page 49372]]

met in order for costs incurred by providers of services to be 
allowable for inclusion as Deferred Compensation in the Medicare cost 
report. The requirements vary based on the type of plan established by 
the provider of services. The plans currently recognized by the program 
include Deferred Compensation Plans, currently set forth in section 
2140 of PRM-I, Qualified Defined Contribution Deferred Compensation 
Plans set forth in section 2141 of PRM-I, and Qualified Defined Benefit 
Pension Plans set forth in section 2142 of PRM-I. As discussed 
previously in section X.A.1. of this final rule, we proposed to codify 
the definitions of these types of plans and related terms, with 
clarifications where appropriate, in proposed new Sec.  413.99(a)(3). 
We proposed to establish at new Sec.  413.99(c) the plan-specific 
requirements that each type of Qualified or Non-Qualified Deferred 
Compensation Plan must meet in order for a provider of servicers 
contributions or payments to the plan to be allowable under the 
program.
    Employer contributions for the benefit of employees under a 
Deferred Compensation Plan are allowable when, and to the extent that, 
such costs are actually incurred by the provider or services. 
Contributions to a funded Deferred Compensation Plan are allowable 
costs when they are made to the plan, to the extent they fall under the 
computed limit. Benefits paid for an unfunded Deferred Compensation 
Plans are allowable costs only when actually paid to the participating 
employees (or their beneficiaries), and only to the extent considered 
reasonable.
    First, we proposed to codify at Sec.  413.99(c)(1) the requirements 
for NQDCs, which can be funded or unfunded. Proposed Sec.  
413.99(c)(1)(i) would establish that an NQDC must meet the requirements 
for document compliance and operational compliance set forth in 
Internal Revenue Code (IRC) section 409A. Proposed paragraph (c)(1)(ii) 
would specify that a funded NDQC must meet the proposed definition of a 
Funded Plan in Sec.  413.99(a)(3) and comply with the requirements in 
proposed Sec.  413.99(c)(5) (discussed later in this section of this 
final rule). Proposed paragraph (c)(1)(iii) would provide that an 
unfunded NQDC must meet the definition of an Unfunded Plan as proposed 
in Sec.  413.99(a)(3), and there must be no constructive receipt of 
income for employees from the NQDC as a result of contributions made by 
a provider of services.
    Second, we proposed to codify at Sec.  413.99(c)(2) the 
requirements for QDCPs. Consistent with our existing policies for 
Defined Contribution Deferred Compensation Plans found in section 
2141.1 of PRM-I, proposed paragraph (c)(2)(i) would specify that a QDCP 
must meet the applicable requirements of ERISA, as amended, and the 
requirements set forth in IRC section 401(a), and, if applicable, 
section 401(k). In addition, proposed paragraph (c)(2)(ii) would 
specify that a QDCP must meet the proposed definition for a Funded Plan 
in Sec.  413.99(a)(3) and comply with the requirements in proposed 
Sec.  413.99(c)(5).
    Third, we proposed to codify at Sec.  413.99(c)(3) the requirements 
for QDBPs. Specifically, proposed Sec.  413.99(c)(3)(i) would establish 
that a QDBP must meet the applicable requirements of ERISA, as amended, 
and the requirements for a QDBP under IRC section 401(a). Proposed 
paragraph (c)(3)(ii) would specify that a QDBP must meet the definition 
of a Funded Plan as proposed in Sec.  413.99(a)(3) and comply with the 
requirements in proposed Sec.  413.99(c)(5).
    Fourth, we proposed to codify at Sec.  413.99(c)(4) the 
requirements for NQDBs, which may be funded or unfunded. Proposed Sec.  
413.99(c)(4)(i) would establish that an NQDB must meet the requirements 
for document compliance and operational compliance set forth in 
Internal Revenue Code (IRC) section 409A. Proposed paragraph (c)(4)(ii) 
would specify that a funded NQDB must meet the definition of a Funded 
Plan as proposed in Sec.  413.99(a)(3) and comply with the requirements 
in proposed Sec.  413.99(c)(5). Proposed paragraph (c)(4)(iii) would 
provide that an unfunded NQDB must meet the definition of an Unfunded 
Plan as proposed in Sec.  413.99(a)(3), and there must be no 
constructive receipt of income for employees from the NQDC as a result 
of contributions made by a provider of services.
    We proposed to codify at Sec.  413.99(c)(5) certain requirements 
for Funded Plans. We proposed to establish at paragraph (c)(5)(i) the 
types of funding mechanisms that Funded Plans must use in order for 
provider of services contributions and employee contributions to such 
plans to be included in allowable costs. Specifically, a Funded Plan 
would be required to use either to purchase an insured plan with a 
commercial insurance company, to establish a custodial bank account, or 
to establish a trust fund administered by a trustee. Proposed paragraph 
(c)(5)(ii) would codify our longstanding policy, set forth in section 
2140.3.B of PRM-I, disallowing the use of an ordinary life insurance 
contract as a funding mechanism for a Funded Plan. Specifically, 
proposed paragraph (c)(5)(ii) would specify that the purchase of an 
ordinary life insurance contract (for example, whole life, straight 
life, or other) is not a deferral of compensation and is not recognized 
as a funding mechanism, even where it is convertible at the normal 
retirement date specified in the policy to an annuity payable over the 
remaining life of the employee. Proposed paragraph (c)(5)(iii) would 
establish that, regardless of the funding mechanism utilized, all 
provider of services and employee contributions to the fund established 
under the Deferred Compensation Plan and income therefrom must be used 
for the sole benefit of the participating employees.
    The proposed requirements for a Funded Plan are based on the 
generally accepted definition of a Funded Plan, along with existing CMS 
policies on the funding of Deferred Compensation Plans found in section 
2140.3 of PRM-I.
    We received no comments on the proposed requirements of Sec.  
413.99(c) for Non-Qualified and Qualified Deferred Compensation plans 
and are finalizing this proposal without modification.
6. Recognition of Contributions or Payments to Qualified and Non-
Qualified Deferred Compensation Plans (Sec.  413.99(d))
    In the FY 2023 IPPS/LTCH proposed rule (87 FR 28615 through 28616), 
at proposed Sec.  413.99(d), we proposed to codify rules and 
requirements that determine when payments or contributions by a 
provider to Qualified or Non-Qualified Deferred Compensation Plans that 
meet the applicable plan-specific requirements at proposed Sec.  
413.99(c) are recognized and included in allowable costs under the 
program. In general, the rules in proposed Sec.  413.99(d) vary 
depending on whether a plan is qualified or non-qualified. In addition, 
certain special rules apply to contributions to QDBPs and NQDBs that 
are deposited into trusts.
    First, for unfunded Deferred Compensation Plans (which include 
unfunded NQDBs), we proposed to codify at proposed Sec.  
413.99(d)(1)(ii) that payments made to such plans are included in 
allowable costs only during the cost reporting period in which an 
actual payment is made to the participating employees (or their 
beneficiaries) and only to the extent considered reasonable in 
accordance with Sec.  413.100(c)(2)(vii)(A). This proposed requirement 
incorporates the existing regulatory requirement for

[[Page 49373]]

payments to unfunded Deferred Compensation Plans at Sec.  
413.100(c)(2)(vii)(A), to aid the reader in understanding related 
policies that appear in other sections of this part that affect 
unfunded NQDCs and unfunded NQDBs.
    Second, regarding certain funded Deferred Compensation Plans 
(specifically funded Defined Contribution Plans, but excluding QDBPs 
and funded NQDBs), we proposed to include at Sec.  413.99(d)(1)(ii) a 
cross reference to Sec.  413.100(c)(2)(vii)(B), which requires that 
accrued costs related to matching or non-elective contributions to a 
funded Deferred Compensation Plan must be liquidated within 1 year 
after the end of the cost reporting period in which the liability is 
incurred. Under Sec.  413.100(c)(2)(viii)(B), an extension, not to 
exceed 3 years beyond the end of the cost reporting year in which the 
liability was incurred, may be granted for good cause if the provider 
of services, within the 1-year time limit, furnishes to the contractor 
sufficient written justification for non-payment of the liability. 
Applying this requirement to QDCPs is consistent with Sec.  
413.100(c)(2)(vii)(B) and with policies established in section 2141.2 
of PRM-I.
    Third, contributions into a protected trust for QDBPs and funded 
NQDBs are allowable. We require that these assets be protected solely 
for the plan participants and to pay reasonable plan administrative 
expenses. Contributions or payments must be made by the provider into a 
protected trust and accounted for on a cash basis. For these plans, we 
proposed to establish at Sec.  413.99(d)(1)(iii) that contributions by 
providers must satisfy the following four requirements to be allowable: 
first, the contributions must be paid to the plan participants or the 
plan trust; second, contributions are accounted for on a cash basis; 
third, money refunded from a plan must be treated as a negative 
contribution; and fourth, the allowable cost must be computed in 
accordance with the calculation defined in Sec.  413.100(c)(2)(vii)(D). 
We described each of these proposed requirements in greater detail in 
the paragraphs that follow.
    First, we proposed to establish at Sec.  413.99(d)(1)(iii)(A) that 
QDBP or funded NQDB contributions are found to have been incurred only 
if paid directly to participants or beneficiaries under the terms of 
the plan or to the QDBP or NQDB. Proposed paragraph (d)(1)(iii)(A) 
codifies our existing policy, which is described in section 2142.6.A of 
PRM-I. Section 2142.6 states that provider contributions or payments 
made to a defined benefit pension plan are allowable only to the extent 
that costs are actually incurred by the provider. Such costs are found 
to have been incurred only if paid directly to participants or 
beneficiaries under the terms of the plan or paid to a pension fund 
which meets the applicable tax qualification requirements under IRC 
section 401(a).
    Second, we proposed to codify at Sec.  413.99(d)(1)(iii)(B) the 
existing regulatory requirement at Sec.  413.100(c)(2)(vii)(D) for 
contributions to a QDBP or funded NQDB. Specifically, proposed Sec.  
413.99(d)(1)(iii)(B) would require that payments to a QDBP or funded 
NQDB for a cost reporting period be measured on a cash basis. A 
contribution or payment would be deemed to occur on the date it is 
credited to the fund established for the QDBP or funded NQDB, or for 
provider of services payments made directly to a plan participant or 
beneficiary, on the date the provider of services account is debited.
    Third, we proposed to clarify the treatment of pension 
contributions when a QDBP or funded NQDB is terminated at Sec.  
413.99(d)(1)(iii)(C) as payments/contributions made to fully fund a 
terminating QDBP or funded NQDB are to be included as funding on the 
date they are paid. Excess assets withdrawn from a QDBP or funded NQDB 
are to be treated as negative contributions on the date that they are 
withdrawn. We believe our proposal to recognize negative contributions 
by reference to the date of withdrawal provides greater clarity than 
the standard under our current guidance under section 2140.3 of PRM-I, 
which refers to the ``year of plan termination,'' which is less 
specific and subject to interpretation.
    Fourth, we proposed to specify at Sec.  413.99(d)(1)(iii)(D) that 
QDBP and funded NQDB costs and limits are computed in accordance with 
the existing regulatory requirements at Sec.  413.100(c)(2)(vii)(D). 
For purposes of determining the QDBP or funded NQDB cost limit under 
Sec.  413.100(c)(2)(vii)(D)(2), we propose that provider of services 
contribution payments for each applicable cost reporting period shall 
be determined on a cash basis in accordance with proposed Sec.  
413.99(d)(1)(iii)(B), without regard to any limit determined for the 
period during which the contributions were made, and excluding any 
contributions deposited in a prior period and treated as carry forward 
contributions. We proposed that the averaging period used to determine 
the QDBP or funded NQDB cost limit shall be determined without regard 
to a provider of services period of participation in the Medicare 
program. Periods that are not Medicare cost reporting periods (for 
example, periods prior to the hospital's participation in the Medicare 
program) shall be defined as consecutive twelve-month periods ending 
immediately prior to the provider of services initial Medicare cost 
reporting period. We proposed that the averaging period used to 
determine the QDBP or funded NQDB cost limit shall exclude all periods 
ending prior to the initial effective date of the plan (or a 
predecessor plan in the case of a merger). Lastly, we proposed that in 
general, the current period defined benefit cost and limit shall be 
computed and applied separately for each QDBP or funded NQDB offered by 
a provider of services. In the case of a plan merger, the contribution 
payments made by a provider of services to a predecessor QDBP or funded 
NQDB and reflected in the assets subsequently transferred to a 
successor plan shall be treated as contribution payments made to the 
successor plan.
    In the FY 2012 IPPS/LTCH PPS final rule, we established separate 
methodologies for measuring pension costs for Medicare cost-finding 
purposes (76 FR 51693 through 51697) and for purposes of updating the 
hospital wage index (76 FR 51586 through 51590). Under the methodology 
we established for the wage index, the pension costs that are to be 
included in the wage index equal a hospital's average cash 
contributions deposited to its defined benefit pension plan over a 3-
year period or, if less than a 3-year period, the number of years that 
the hospital has sponsored a defined benefit plan. The 3-year average 
was centered on the base cost reporting period for the wage index. For 
example, the FY 2013 wage index is based on Medicare cost reporting 
periods beginning during Federal FY 2009 and reflects the average 
pension contributions made in hospitals' cost reporting periods 
beginning during Federal FYs 2008, 2009, and 2010. In the FY 2016 IPPS/
LTCH PPS final rule (80 FR 49505 through 49508), we modified the policy 
such that the 3-year average is based on pension contributions made 
during the base cost reporting period plus the prior 2 cost reporting 
years. For example, the FY 2017 wage index is based on Medicare cost 
reporting periods beginning during Federal FY 2013. Therefore, the FY 
2017 wage index reflects the average pension contributions made in 
hospitals' cost

[[Page 49374]]

reporting periods beginning during Federal FYs 2011, 2012, and 2013 
(rather than Federal FYs 2012, 2013, and 2014 under the prior policy 
established in the FY 2012 IPPS/LTCH PPS final rule (76 FR 51586 
through 51590)). While the QDBP cost for cost-finding purposes is 
computed using the cost period annual contributions limited by a cap 
(as codified in Sec.  413.100(c)(2)(vii)(D)), the wage index QDBP cost 
is a 3-year average of annual plan contributions without adjustment or 
cap.
    We received no comments on the proposed recognition under Sec.  
413.99(d) of contributions or payments to Qualified and Non-Qualified 
Deferred Compensation Plans and are finalizing this proposal without 
modification.
7. Documentation Requirements (Sec.  413.99(e))
    In the FY 2023 IPPS/LTCH proposed rule (87 FR 28616 through 28617), 
we proposed to codify at Sec.  413.99(e) that a provider of services 
must maintain and make available upon request documentation to 
substantiate the costs incurred for the plans included in its Medicare 
cost report. These proposed requirements for documentation are based on 
the existing regulatory requirements at Sec.  413.20, which require 
providers of services to maintain sufficient financial records and 
statistical data for proper determination of costs payable under the 
program.
    In addition, these requirements are based in part on the policy 
established when CMS revised the calculation for a QDBP and funded NQDB 
in the FY 2012 IPPS/LTCH PPS final rule (76 FR 51693 through 51697). 
Section 2142.5.F of PRM-I states that the provider must have available 
data to show the amount(s) and date(s) of contribution payments made to 
a defined benefit pension plan during the current reporting period and 
any applicable prior periods. If the pension costs included in the cost 
report for a period differ from the pension contribution payments made 
during the reporting period (for example, as a result of carry forward 
contributions), the provider must also have data available to track and 
reconcile the difference.
    Specifically, we proposed at Sec.  413.99(e) that documentation 
must be maintained by the provider of services in accordance with Sec.  
413.20 to substantiate the allowability of the payments or 
contributions to Qualified or Non-Qualified Deferred Compensation Plans 
(or both) that it has included in its cost reports. With respect to 
required documentation, we proposed to specify at Sec.  413.99(e)(1) 
that the provider of services must maintain and make available, upon 
request from the contractor or CMS, certain specified documentation, to 
substantiate the allowability of payments or contributions made by the 
provider of services to a Qualified or Non-Qualified Deferred 
Compensation Plan. Under proposed Sec.  413.99(e)(1), the following 
documentation would be required: documentation that demonstrates that 
the provider of services is in compliance with IRC section 409A and IRC 
section 409A(a), and if applicable IRC section 457; ledger accounts/
account statements for each plan participant noting current year 
deferrals, distributions, and loans, including any deferral election 
forms completed by employees, any change requests, and the approval of 
such requests; documentation that demonstrates the amount(s) and 
date(s) of actual payment/contributions made to the Non-Qualified or 
Qualified Deferred Compensation Plan during the current cost reporting 
period; Schedule SB of Form 5500 (tri-agency form (Department of Labor 
(DOL), Internal Revenue Service (IRS), PBGC) that plans file with the 
DOL's ``EFAST'' electronic filing system. The ``Form 5500'' is the 
Annual Return/Report of Employee Benefit Plan for a QDBP for the 
current cost reporting period, or any applicable prior periods; and, in 
the case of a system wide (multiple employer) plan, the home office 
shall identify the contributions attributed to each participating 
provider of services. If the costs included in the cost report for a 
period differ from the contributions made during the reporting period 
(for example, as a result of carry forward contributions), the provider 
of services must also have data available to track and reconcile the 
difference.
    We also proposed to establish at Sec.  413.99(e)(2) that the 
following additional documentation must be made available, upon request 
by the contractor or CMS, to substantiate the allowability of payments 
or contributions made by a provider of services to a Qualified or Non-
Qualified Deferred Compensation Plan: the plan document, the trust 
document and all amendments related to the current cost reporting 
period; if applicable, any Form 5330, Return of Excise Taxes Related to 
Employee Benefit Plans, for the cost reporting period; supporting 
documents for all plan assets and liabilities, such as broker's 
statements, bank statements, insurance contracts, loan documents, 
deeds, etc., and verification of how assets are valued; trustee or 
administrator reports; ledgers; journals; trustee, administrator and 
investment committee minutes; certified audit report; and other 
financial reports for the trust. Any other financial reports, including 
receipt and disbursement statements, a detailed income statement and a 
detailed balance sheet; and, for each covered QDBP, documentation of 
the certified premium information and payments to the PBGC.
    We received no comments on the proposed documentation requirements 
of Sec.  413.99(e) and are finalizing this proposal without 
modification.
8. Administrative and Other Costs Associated With Qualified and Non-
Qualified Deferred Compensation Plans (Sec.  413.99(f))
    In the FY 2023 IPPS/LTCH proposed rule (87 FR 28617), in proposed 
Sec.  413.99(f), we proposed to codify our current policies, as set 
forth in sections 2140, 2141, and 2142 of PRM-I, regarding the 
treatment of certain administrative and other costs related to Deferred 
Compensation Plans as allowable or non-allowable under the program. In 
the paragraphs that follow, we discuss our proposed treatment of 
various administrative costs related to Deferred Compensation Plans. 
First, we proposed to establish at Sec.  413.99(f) that the provider of 
services shall file a cost report required under Sec. Sec.  413.20 and 
413.24(f) that is consistent with the proposed policies set forth in 
proposed Sec.  413.99.
    We received no comments on this proposal and are finalizing this 
proposal without modification.
a. Trustee and Custodial Fees
    In the FY 2023 IPPS/LTCH proposed rule (87 FR 28617), we proposed 
to codify at Sec.  413.99(f)(1) that reasonable trustee or custodial 
fees, including PBGC premiums, paid by the provider of services are 
allowed as an administrative cost, except where the plan provides that 
such fees are paid out of the corpus or earnings of the fund. Fees paid 
out of the corpus or earnings of the fund would not be allowed, based 
on the rationale that, because contributions into the plan trust pay 
for benefits and expenses that are paid from the trust, that means 
administrative costs paid out of the plan trust have already been 
accounted for through the allowance of contributions made by the 
provider of services. This proposed provision would codify our current 
policy, which is set forth in section 2140.3.B.1.d of PRM-I.
    We received no comments on this proposal and are finalizing this 
proposal without modification.

[[Page 49375]]

b. Vested Benefits
    In the FY 2023 IPPS/LTCH proposed rule (87 FR 28617), we proposed 
to codify at Sec.  413.99(f)(2) that the forfeiture of an employee's 
benefits for cause (as defined in the plan) is recognized as an 
allowable cost provided that such forfeited amounts are used to reduce 
the provider of services contributions or payments to the plan during 
the cost reporting period in which the forfeiture occurs. This proposed 
provision would codify our policy on the effects of a forfeiture of 
vested benefits on the plan costs that are allowable under the program, 
as set forth at section 2140.3.D of PRM-I, with the added clarification 
that the reduction must occur in the cost reporting period in which the 
forfeiture occurs.
    We proposed to codify at Sec.  413.99(f)(3) our existing policy on 
the effects of employees' termination of participation in a plan before 
their rights are vested in the contributions/payments to the plan that 
are allowable under the program. Specifically, proposed Sec.  
413.99(f)(3) would specify that if an employee terminates participation 
in the Deferred Compensation Plan before their rights are vested, the 
applicable non-vested contributions/payments cannot be applied to 
increase the benefits of the surviving participants. Instead, the non-
vested contributions/payments should be used to reduce the provider of 
services contributions/payments to the Deferred Compensation Plan, in 
the cost reporting period wherein the employee terminated participation 
in the Deferred Compensation Plan. Otherwise, the contributions/
payments made by the provider of services must be applied to reduce the 
subsequent contributions/payments to the Deferred Compensation Plan in 
the next cost reporting period. If subsequent provider of services 
contributions/payments to the Deferred Compensation Plan are not made, 
then provider of services costs will be reduced by the contractor to 
the extent of such non-vested funds.
    We received no comments on this proposal and are finalizing this 
proposal without modification.
c. DOL, IRS, and PBGC Penalties
    Providers of services who maintain a Deferred Compensation Plan are 
required to comply with regulatory requirements related to the plan 
that are established by the Department of Labor (DOL), the IRS and the 
PBGC. Where providers of services fail to follow these requirements, a 
penalty may be levied. For example, the IRS levies an excise tax when 
payments are not timely filed. Section 1861(v)(8) of the Act sets forth 
items unrelated to patient care that are not considered reasonable 
under the program. In other words, these items are unallowable, and 
therefore cannot be included in the allowable costs of the provider of 
services. One of these items is the cost for fines and penalties 
resulting from violations of Federal, State, or local laws. 
Accordingly, in the FY 2023 IPPS/LTCH proposed rule (87 FR 28617), we 
proposed at Sec.  413.99(f)(4) to specify that if the provider of 
services is assessed an excise tax or other remedy by DOL or IRS or 
PBGC for failure to follow the DOL, IRS, or PBGC requirements under 
ERISA, or any other penalty fee or penalty interest applicable to its 
Deferred Compensation Plan, the associated cost is unallowable, in 
accordance with section 1861(v)(8)(iv) of the Act.
    We received no comments on this proposal and are finalizing this 
proposal without modification.
d. Loans Made From a Deferred Compensation Plan
    Under our current policy, as set forth in section 2140.3.C of PRM-I 
providers of services are able to make a loan to themselves out of 
either corpus or income from their Qualified or Non-Qualified Deferred 
Compensation Plan on the conditions that the fund receive adequate 
security and a reasonable rate of interest on the loan. This existing 
policy is inconsistent with ERISA section 406 (29 U.S.C. 1106(1)(B)) 
which specifically prohibits lending of money or other extension of 
credit between the plan and a party in interest, unless found to be 
excepted under 29 U.S.C. 1108. The definition of a ``party in 
interest'' includes an employer any of whose employees are covered by 
such plan. The same provision exists in the IRC at 26 U.S.C. 4975. We 
believe that the policy we proposed to codify in new Sec.  413.99 
should reflect these provisions in ERISA and the IRS rules that are 
designed to protect Deferred Compensation Plans and the plans' 
participants and beneficiaries. Accordingly, in the FY 2023 IPPS/LTCH 
proposed rule (87 FR 28617), we proposed at Sec.  413.99(f)(5) to 
specify that a provider of services cannot make a loan to itself from a 
Deferred Compensation Plan where ERISA or IRS rules prohibit such a 
transaction, except where specifically excepted. In cases where an 
exception applies, our existing policy on allowable interest expense at 
Sec.  413.153 continues to apply.
    We received no comments on this proposal and are finalizing this 
proposal without modification.
e. Termination/Discontinuation of a Deferred Compensation Plan
    Sections 2140.3.D and 2141.3.D of PRM-I set forth CMS's policy on 
the effect of a provider of services declining to vest its outstanding 
required contributions/payments as a result of a termination, in full 
or in part, or a discontinuation of contributions or payments to a 
Deferred Compensation Plan. Under this policy, we proposed n the FY 
2023 IPPS/LTCH proposed rule (87 FR 28617 through 28618), to codify at 
Sec.  413.99(f)(6), where the provider of services declines to vest its 
outstanding required contributions/payments (that is, matching and non-
elective or both) to a Deferred Compensation Plan, as a result of a 
termination, in full or in part, or a discontinuation of contributions 
or payments to a Deferred Compensation Plan, then the provider of 
services total outstanding required contributions or payments to the 
Deferred Compensation Plan during the cost reporting period wherein 
such termination is initiated cannot be included in the provider of 
services allowable cost for the cost reporting period in which the 
termination is initiated, nor any future period.
    We received no comments on this proposal and are finalizing this 
proposal without modification.
f. Required Offset Against Interest Expense
    In section 2140.3.D of PRM-I, CMS has established a policy that 
investment income earned on a fund after its termination but prior to 
liquidation of the fund's assets and distribution to the provider is 
offset against the provider's allowable interest expense. In the FY 
2023 IPPS/LTCH proposed rule (87 FR 28618), we proposed to adopt the 
current policy in section 2140.3 of PRM-I at proposed Sec.  
413.99(f)(7), which would state that investment income earned on a 
Deferred Compensation Plan after its termination but prior to 
liquidation of the plan's assets and distribution to the provider of 
services must be offset against the provider of services allowable 
interest expense under Sec.  413.153.
    We received no comments on this proposal and are finalizing this 
proposal without modification.
g. Treatment of Residual Assets Following Termination of a Funded Plan
    In section 2140.3.D of PRM-I, CMS has established a policy 
describing how residual assets arising from the termination of a funded 
plan are to be handled on the Medicare cost report. In

[[Page 49376]]

the FY 2023 IPPS/LTCH proposed rule (87 FR 28618), we proposed to adopt 
the current policy, as it appears in section 2140.3.D of PRM-I, at new 
Sec.  413.99(f)(8). Specifically, we proposed that Sec.  413.99(f)(8) 
would specify that residual assets arising from the termination of a 
funded plan must be recouped in the year of the plan termination only 
against the cost center(s) in which the provider of services reported 
its plan contributions/payments, usually the administrative and general 
cost center. Residual assets exceeding the amount in the administrative 
and general (or other) cost center are not further offset in the 
current or subsequent years. The Medicare share of the reversion is 
based on the Medicare utilization rate in the year the reversion occurs 
(or the year the actuarial surplus is determined), and not Medicare's 
utilization in the years the contributions to the plan were made.
    We received no comments on this proposal and are finalizing this 
proposal without modification.
9. Treatment of Costs Associated With the Pension Benefit Guaranty 
Corporation (PBGC) (Sec.  413.99(g))
    Since 1974, the PBGC has protected retirement security and the 
retirement incomes of over 33 million American workers, retirees, and 
their families in private sector defined benefit pension plans. A 
Qualified Defined Benefit Plan (defined previously as a QDBP) provides 
a specified monthly benefit at retirement, often based on a combination 
of salary and years of service. The PBGC was created by ERISA to 
encourage the continuation and maintenance of private sector defined 
benefit pension plans, provide timely and uninterrupted payment of 
pension benefits, and keep pension insurance premiums at a minimum.
    General tax revenues do not fund the PBGC Single-Employer Program. 
The PBGC collects insurance premiums from employers that sponsor 
insured pension plans, earns money from investments, and receives funds 
from pension plans it takes over (see https://www.pbgc.gov/about/how-pbgc-operates).
    Providers of services who offer a QDBP may incur costs related to 
the PBGC premiums. The proposed regulations outlined in this section of 
this final rule establish which costs incurred by providers of services 
who maintain a QDBP and pay premiums for basic benefits to the PBGC are 
allowable under the program. We proposed to include these provisions on 
the treatment of costs associated with the PBGC in paragraph (g) of 
proposed Sec.  413.99.
    In 29 U.S.C. 1306 the schedule for the premium rates, and the bases 
for application of those rates are set forth. Under 29 U.S.C. 1306, 
premiums are established for basic benefits, non-basic benefits, and 
reimbursement for uncollectible withdrawal liability. In the FY 2023 
IPPS/LTCH proposed rule (87 FR 28618), we proposed at Sec.  
413.99(g)(1) that PBGC premiums and costs paid out of the corpus or 
earnings of the trust are included in the contributions allowed by 
Sec.  413.99(d)(3)(ii), and therefore are not allowable as separate 
costs. We note, in the proposed rule we inadvertently made a 
typographical error and referred to Sec.  413.99(d)(3)(ii) when we 
intended to refer to Sec.  413.99(d)(1)(iii)(A). We also proposed at 
Sec.  413.99(g)(2) that the amount of PBGC premiums paid for basic 
benefits (that is, flat rate or variable, excluding amounts paid out of 
the corpus or earnings of the trust) by a provider of services who 
sponsors a QDBP are allowable under the program. Similar to allowance 
of Administrative Costs as stated in proposed Sec.  413.99(f)(1), while 
PBGC premiums are an allowable cost, they are not allowed if they are 
paid from the plan trust.
    In 29 CFR part 4050, the rules for PBGC's program that holds 
retirement benefits for missing participants and beneficiaries of 
terminated retirement plans and pays those benefits to participants and 
beneficiaries when found, are provided. A Missing Participant is a 
former employee of a provider of services who has a liability remaining 
with the plan but cannot be located or is unresponsive when the plan 
terminates and closes out. Transfers of funds to the PBGC by the 
provider of services to cover this liability under the PBGC Missing 
Participant Program are allowable as long as they are not paid out of 
the corpus or earnings of the trust. In the FY 2023 IPPS/LTCH proposed 
rule (87 FR 28618), we proposed at new Sec.  413.99(g)(3) that the 
total amount paid to the PBGC by a provider of services who sponsors a 
QDBP (excluding amounts paid out of the corpus or earnings of the 
trust) of the benefit transfer amount (see 29 CFR 4050.103(d)) for all 
missing participants or beneficiaries of the QDBP is allowable under 
the program.
    After entering into a trusteeship agreement with the employer or 
after receiving an order issued by a U.S. district court approving 
termination, the PBGC guarantees employee plan benefits will be paid up 
to a certain limit if the QDBP has insufficient assets as part of a 
Distress Termination (as described in 29 CFR part 4041) or as part of a 
PBGC-initiated termination under 29 U.S.C. 1342. In the FY 2023 IPPS/
LTCH proposed rule (87 FR 28618), we proposed at Sec.  413.99(g)(4) 
that for terminated plans with insufficient assets to pay all of the 
plan benefits, where the PBGC guarantees the payment of vested benefits 
up to limits defined by law, only contributions to the QDBP made by a 
provider of services are allowable. Benefits paid to the participants 
and beneficiaries of the QDBP by the PBGC are unallowable.
    In 29 CFR part 4047, PBGC is given the authority to restore a plan 
from terminated status to ongoing. Contributions and benefits paid by 
the provider of services to the PBGC or the plan or its participants 
and beneficiaries are allowable in this situation. In the FY 2023 IPPS/
LTCH proposed rule (87 FR 28618), we proposed at Sec.  413.99(g)(5) 
that where the PBGC issues or has issued a plan restoration order as 
described in 29 CFR part 4047, the amounts that the provider of 
services repays to the PBGC for guaranteed benefits and related 
expenses under the plan while the plan was in terminated status, and 
any administrative costs assessed by the PBGC, excluding penalties, are 
allowable.
    We received no comments on the proposed treatment of costs 
associated with the PBGC under Sec.  413.99(g) and are generally 
finalizing this proposal without modification, except we are revise the 
proposed regulation text at Sec.  413.99(g)(1) so that the erroneous 
reference to Sec.  413.99(d)(3)(ii) is corrected in the finalized 
regulation text and instead refers to Sec.  413.99(d)(1)(iii)(A).

B. Condition of Participation (CoP) Requirements for Hospitals and CAHs 
To Continue Reporting Data for COVID-19 and Influenza After the PHE 
Ends as Determined by the Secretary

    Under sections 1866 and 1902 of the Act, providers of services 
seeking to participate in the Medicare or Medicaid program, or both, 
must enter into an agreement with the Secretary or the state Medicaid 
agency, as appropriate. Hospitals (all hospitals to which the 
requirements of 42 CFR part 482 apply, including short-term acute care 
hospitals, LTC hospitals, rehabilitation hospitals, psychiatric 
hospitals, cancer hospitals, and children's hospitals) and CAHs seeking 
to be Medicare and Medicaid providers of services under 42 CFR part 
485, subpart F, must be certified as meeting Federal participation 
requirements. Our conditions of participation (CoPs), conditions for 
coverage (CfCs), and requirements set out the patient health

[[Page 49377]]

and safety protections established by the Secretary for various types 
of providers and suppliers. The specific statutory authority for 
hospital CoPs is set forth in section 1861(e) of the Act; section 
1820(e) of the Act provides similar authority for CAHs. The hospital 
provision at section 1861(e)(9) of the Act authorizes the Secretary to 
issue any regulations he or she deems necessary to protect the health 
and safety of patients receiving services in those facilities; the CAH 
provision at section 1820(e)(3) of the Act authorizes the Secretary to 
issue such other criteria as he or she may require. The CoPs are 
codified in the implementing regulations at part 482 for hospitals, and 
at 42 CFR part 485, subpart F, for CAHs.
    Our CoPs at Sec.  [thinsp]482.42 for hospitals and Sec.  
[thinsp]485.640 for CAHs require that hospitals and CAHs, respectively, 
have active facility-wide programs, for the surveillance, prevention, 
and control of healthcare-associated infections (HAIs) and other 
infectious diseases and for the optimization of antibiotic use through 
stewardship. Additionally, the programs must demonstrate adherence to 
nationally recognized infection prevention and control guidelines, as 
well as to best practices for improving antibiotic use where 
applicable, and for reducing the development and transmission of HAIs 
and antibiotic-resistant organisms. Infection prevention and control 
problems and antibiotic use issues identified in the required hospital 
and CAH programs must also be addressed in coordination with facility-
wide quality assessment and performance improvement (QAPI) programs.
    Infection prevention and control is a primary goal of hospitals and 
CAHs in their normal day-to-day operations, and these programs have 
been at the center of initiatives taking place in hospitals and CAHs 
during the PHE for COVID-19. Our regulations at Sec. Sec.  
[thinsp]482.42(a)(3) and 485.640(a)(3) require infection prevention and 
control program policies to address any infection control issues 
identified by public health authorities. We proposed to revise the 
hospital and CAH infection prevention and control and antibiotic 
stewardship programs CoPs to extend the current COVID-19 reporting 
requirements and to establish new reporting requirements for any future 
PHEs related to a specific infectious disease or pathogen.
    Specifically, we proposed to revise the COVID-19 and Seasonal 
Influenza reporting standards for hospitals and CAHs (at Sec. Sec.  
482.42(e) and (f); and 485.640(d) and (e), respectively) to require 
that, beginning at the conclusion of the current COVID-19 PHE 
declaration and continuing until April 30, 2024, a hospital (or a CAH) 
must electronically report information about COVID-19 and seasonal 
influenza in a standardized format specified by the Secretary. In 
addition, we proposed additional requirements to address future PHEs 
related to infectious diseases at Sec. Sec.  482.42(g) and 485.640(f), 
for hospitals and CAHs respectively. Specifically, when the Secretary 
has declared a PHE, we proposed to require hospitals and CAHs to report 
specific data elements to the CDC's National Health Safety Network 
(NHSN), or other CDC-supported surveillance systems, as determined by 
the Secretary. We noted that the proposed requirements of this section 
would apply to local, state, and national PHEs as declared by the 
Secretary.
    In the proposed rule, we highlighted the various interim final 
rules with comment (IFC) that currently require hospitals and CAHs to 
report important data critical to support the fight against COVID-19 
and noted that these requirements are both tied to the current PHE 
(meaning they would no longer be required post-PHE) and emphasized that 
COVID-19 reporting, by all hospitals and CAHs, have been, and continue 
to be, important in supporting surveillance of, and response to, the 
PHE for COVID-19. We stressed that such reporting requirements are 
necessary for CMS to monitor whether individual hospitals and CAHs are 
appropriately tracking, responding to, and mitigating the spread and 
impact of viral and bacterial pathogens and infectious diseases of 
pandemic or epidemic potential on patients, the staff who care for 
them, and the general public and the important role that such reporting 
plays when considering future planning. Additionally, we noted our 
concern that current reporting, while appropriately focused on the 
current COVID-19 pandemic, are too limited in scope for potential 
future use and noted that we are considering ways to ensure a more 
flexible regulatory framework to promote a nimble and informed response 
to the next potential pandemic or epidemic, so that we are able to 
immediately respond to the situation at hand. We refer readers to the 
FY 2023 IPPS proposed rule for this detailed discussion (87 FR 28618-
28622).
    In response to the proposed rule, we received approximately 757 
public comments that specifically addressed the proposals to continue 
COVID-19-related data reporting and to establish reporting in the event 
of a future PHE declaration involving an infectious disease. Commenters 
included individuals, health care professionals and corporations, 
national associations, health department and emergency management 
professionals, and individual facilities that would be impacted by the 
regulation. We have organized our responses to the comments as follows: 
(1) general comments, (2) comments focused on the proposals for 
continued COVID-19-related data reporting, and (3) comments pertaining 
to the proposals for data reporting in the event of a future PHE 
declaration. We note that for many comments, CMS was unable to discern 
if the content was applicable to both proposals or specific to either 
the proposals for continued COVID-19-related reporting or future data 
reporting for a declared PHE involving an infectious diseases. We 
address these comments as general comments. To the extent possible, in 
those instances where commenters clearly referenced specific 
requirements in the proposals for either continued COVID-19-related 
reporting or reporting in the event of a future PHE, we address those 
comments in the applicable section. Comments related to the collection 
of information requirements and burden estimates are addressed in 
sections XII.B.10 and XII.H.11, ``Collection of Information 
Requirements'' and ``Regulatory Impact Analysis'' of this final rule, 
as appropriate.
A. General Comments
    Comment: Several commenters agreed with our goal to ensure patient 
health and safety by continuing and establishing a flexible framework 
for data-driven surveillance and response for COVID-19 and future PHEs 
involving infectious diseases, respectively. Commenters stated that 
although collecting and reporting data may consume resources and 
increase demands on staff, such data are important for establishing and 
maintaining situational awareness during a PHE and beyond. They noted 
that these data are critical and used in decision making at the local, 
state, and federal levels. In addition, while these commenters noted 
the increased demands experienced by health care facilities and their 
staff during the COVID-19 PHE, they shared that efforts to recover and 
resume normal operations are well under way and re-enforced their 
commitment to providing the highest quality and safe level of care to 
patients at all times.
    Response: We appreciate the support from commenters. We agree that 
data are critical for monitoring the spread of infectious diseases, 
informing research and guidance development by government and non-
governmental

[[Page 49378]]

entities, and responding during and after a public health emergency. We 
commend health care facilities and their staff for their efforts 
throughout the COVID-19 pandemic and recovery, and we are also 
committed to ensuring high quality and safe care to patients.
    Comment: While several commenters supported the overall policy 
goal, many commenters disagreed with our approach to achieve a flexible 
regulatory framework for data-driven surveillance and response for 
COVID-19 and future infectious diseases in the event of a PHE 
declaration. Commenters noted that these proposals would place undue 
burden on facilities, and particularly during and/or directly after 
PHEs, when patient care demands and stress and burnout among staff are 
increased. Some commenters stated the proposed data categories 
reflected a high level of detail that would be burdensome to collect 
and report thereby negatively impacting the accuracy of the data and 
taking time away from patient care, infection prevention and control, 
and quality improvement activities. Commenters also raised concerns 
regarding duplicative reporting and encouraged increased coordination 
at the local, state, and federal level to ease the burden on providers 
and limit the need to report the same information through multiple 
streams. Commenters also suggested reviewing the use case for each data 
category and eliminating those that are not providing valuable 
information. A few commenters stated that more reimbursement would be 
needed to support any additional reporting requirements. Others 
suggested that incentives for reporting data would be helpful.
    Response: We understand the burden concerns expressed by 
commenters. As indicated in the proposed rule, CMS recognizes that the 
health and safety benefits associated with any reporting requirements 
must be carefully weighed against the potential burden they impose on 
facility operations--particularly in situations, like a public health 
emergency, where staff resources are stretched. We appreciate the 
comments about reimbursement and incentives; however, reimbursement and 
incentives are outside of the scope of the CoPs. As suggested by the 
commenters, we reviewed the use case for each data category, and we 
discuss this in greater detail in sections B and C. As with the current 
COVID-19 reporting required during the ongoing PHE, CDC and ASPR are 
working with states and other jurisdictions for the continuation of 
COVID-19-related reporting to ensure that states have access to the 
data reported directly to the federal government and that jurisdictions 
so inclined can continue to report on behalf of the hospitals within 
their jurisdictions. According to ASPR, approximately half of the 
states currently submit data on behalf of the hospitals in their 
jurisdictions and many have expressed their interest in continuing this 
capability. CDC, CMS, and ASPR concur and will continue to leverage 
this capability--where desired by jurisdictions--so that they may 
receive the data directly from hospitals to fulfill local 
jurisdictional reporting requirements and then pass the data to the 
federal government to alleviate the burden of hospitals reporting to 
both state health departments and the federal government.
    Comment: Many commenters noted the significant administrative 
burden associated with manual entry, configuration, and submission of 
required data elements, and most agreed that greater automation of the 
reporting enterprise would be critical to minimizing future hospital 
burden. A few of these commenters also believed that, given widespread 
adoption of certified EHR technologies and associated interoperability 
standards, such automation was within reach for most hospitals. The 
majority, however, shared concern about the extent to which the 
technical and technological architecture to support automated, 
electronic reporting was in place--or would be soon, given the complex 
array of systems from which hospitals have to pull and assemble 
required data. These commenters noted that small, rural hospitals and 
CAHs in particular often lack the resources and IT expertise to 
establish and maintain the necessary system interfaces. Most commenters 
focused more on the capabilities necessary for automated data 
reporting, while some commenters focused on specific systems for data 
reporting. Specifically, some commenters recommended use of NHSN as a 
single pathway for data reporting and indicated that this would 
streamline reporting guidance and the systems for submitting data. Some 
commenters suggested that the data reporting pathways currently in 
place for the COVID-19 PHE should remain available for continued COVID-
19-related reporting after the PHE ends and for reporting in the event 
of a future PHE declaration. These commenters noted that changing 
reporting systems requires modifying workflows and making these changes 
would increase burden.
    Response: We thank commenters for their feedback and agree that 
greater automation of the reporting enterprise will greatly reduce 
burden on providers. We expect reporting to become increasingly 
automated and real-time as data systems and standards continue to 
mature and become more interoperable. As noted in the proposed rule, 
the CDC is investing in increasing the automation capabilities of 
surveillance systems, like the NHSN, and their ability to connect with 
other data submission techniques, vendors, and systems (87 FR 28622). 
We look forward to continuing the work in this space and are excited 
about the future possibilities as we continue efforts to protect and 
ensure the health and safety of patients.
    Comment: Some commenters stated there was a lack of transparency in 
why CMS would need the data, who would use the data, and how the data 
would be used. These commenters also indicated that there should be a 
bi-directional flow of the information reported and that the data 
should be accessible to all health partners to both increase 
transparency and inform emergency management efforts.
    Response: As CMS noted in the proposals, the proposed rule aimed to 
minimize data reporting while maintaining transparency \1160\ and 
ensuring that public health agencies, researchers, and the public have 
sufficient awareness \1161\ of overall health system capacity amid 
evolving epidemiological conditions in order to rapidly direct 
preventive and response actions. In addition, NHSN provides ready 
access to data to state and many local public health agencies for the 
facilities in their jurisdictions via their NHSN accounts and 
contributes aggregate data to multiple public-facing platforms, 
including HHS Protect and CMS Care Compare. For example, the COVID-19-
related data pertaining to bed census and occupancy, vaccination of 
staff, and PPE supplies reported by hospitals and CAHs throughout the 
COVID-19 PHE has been publicly posted in aggregate on a regular basis 
on HHS Protect and/or NHSN websites.
---------------------------------------------------------------------------

    \1160\ https://obamawhitehouse.archives.gov/the-press-office/2013/05/09/executive-order-making-open-and-machine-readable-new-default-government-
    \1161\ https://digital.gov/open-data-policy-m-13-13/
---------------------------------------------------------------------------

    Requiring the collection of the data supports our responsibility 
and commitment to protect the health and safety of hospital and CAH 
patients. These data would allow CMS to monitor whether individual 
hospitals and CAHs were appropriately tracking, responding to, and 
mitigating the impact on patients, the staff who care for them, and the 
general public. A streamlined approach will greatly assist government 
leaders in tracking, identifying new

[[Page 49379]]

threats, and ultimately inform decision-making, resource allocation, 
and the ability to inform a coordinated response effort across the 
nation. For example, during the COVID-19 PHE, the data collected and 
reported by hospitals and CAHs enabled CMS, in partnership with CDC and 
ASPR, to monitor the ability of facilities to provide safe care for 
patients by determining the number of COVID-19 patients being cared for 
in facilities; the amount of resources facilities were using; and 
facilities' continued capacity to provide safe care based on these 
factors. Throughout the COVID-19 pandemic, HHS and state and local 
agencies used these data to provide resources (such as PPE, staffing, 
strike teams, financial resources) to hospitals to ensure safe care and 
used these data to update guidance on the provision of care to patients 
during periods of scarce staffing, scarce PPE, and limited hospital 
capacity.
    Comment: In response to our request for strategies to support a 
smooth transition, several commenters suggested implementation 
approaches that CMS could take to support compliance with the proposed 
reported policies. Commenters emphasized that the data definitions 
across facility types and different reporting organizations need to be 
clearly defined and consistent. These commenters noted that as an 
example, for healthcare worker COVID-19 vaccination data, the 
definition of a ``week'' is different depending on to which 
organization the data are being reported. Commenters stated that 
providing education to facilities on the context for data requests and 
usage would improve the quality, timeliness, and participation of 
reporting. Some commenters stated that data reporting requirements and 
relevant interpretative guidance should be clearly communicated with 
adequate lead time so that facilities could develop, implement, and 
update workflows and procedures for collecting and reporting the 
necessary data, as well as any changes in the data they are required to 
report. A few commenters suggested that facilities would need this 
interpretive guidance with a minimum notice of 30 to 60 days to prepare 
data reporting workflows and procedures.
    Response: We appreciate the feedback and suggestions provided 
regarding strategies to help support implementation and a smooth 
transition. As stated in the proposed rule, facilities will be notified 
of the specific reporting requirements (start date, data elements and 
definitions, frequency, etc.) and subsequent changes in guidance, such 
as a Quality, Safety, and Oversight (QSO) memorandum, consistent with 
the notification methods used previously for COVID-19-related reporting 
(87 FR 28620); (see QSO-21-03-Hospitals/CAHs at https://www.cms.gov/files/document/qso-21-03-hospitalscahs.pdf-0). We will consider these 
comments when developing the interpretive guidance for this final rule.
B. Comments Focused on the Proposals for Continued COVID-19-Related 
Data Reporting
    Comment: A few commenters stated that the proposal for continued 
COVID-19-related data was unclear, because the proposal indicated that 
hospitals and CAHs would report data in a standardized format specified 
by the Secretary. These commenters recommended that the rule clearly 
identify the systems by which hospitals and CAHs would be able to 
report data, to include HHS Protect.
    Response: We agree that the rule does not identify specific systems 
for data reporting by hospitals and CAHs. Current regulations for 
COVID-19 reporting and reporting of acute respiratory illness, 
including seasonal influenza virus, influenza-like illness, and severe 
acute respiratory infection at Sec.  482.42(e) and (f) (hospitals) and 
Sec.  485.640(d) and (e) (CAHs) state that hospitals and CAHs must 
report information in a standardized format specified by the Secretary. 
We adopted that approach because it affords flexibility to adapt data 
reporting requirements in response to changing circumstances. In this 
rule, we maintain this regulatory language (in a standardized format as 
specified by the Secretary) thereby ensuring a sustained, flexible 
approach for continued COVID-19-related data reporting after the PHE 
ends. As indicated in the proposed rule, throughout the COVID-19 PHE, 
CMS notified hospitals and CAHs of the reporting requirements with QSO 
memorandums (for example, see QSO-21-03-Hospitals/CAHs at https://www.cms.gov/files/document/qso-21-03-hospitalscahs.pdf-0.) We 
anticipate a similar model of notification for the continued COVID-19-
related data reporting requirements finalized in this rule.
    Comment: A few commenters stated that it was difficult to 
understand the purpose of continuing COVID-19-related reporting beyond 
the current PHE declaration. The commenters stated that the data is of 
questionable value given the current state of the pandemic. Some 
commenters recommended that the COVID-19-related reporting requirements 
end when the current PHE expires and restart in the event another PHE 
is declared.
    Response: We acknowledge the concerns raised by commenters, however 
disagree that there is no value in continued COVID-19 reporting beyond 
the current PHE. Due to the unpredictable nature of the novel SARS-CoV-
2 virus that causes COVID-19, we believe that continuing COVID-19-
related data reporting is necessary to protect the health and safety of 
hospital and CAH patients as well as the communities in which the 
hospitals and CAHs are located. The COVID-19-related data reported by 
all hospitals and CAHs, have been, and continue to be, important in 
supporting surveillance of, and response to, COVID-19 and other 
respiratory illnesses. These data play an important role in evaluating 
spread of respiratory viruses and infections, including but not limited 
to COVID-19 and influenza. Retaining the data reporting requirements 
after the end of the current COVID-19 PHE is an important element of 
maintaining effective surveillance of this novel virus. Timely and 
actionable surveillance will enable CMS to continue to respond to 
facilities in need of additional technical support and oversight, 
should they experience increased cases or outbreaks of COVID-19 and/or 
influenza. Furthermore, we note that these requirements will sunset 
April 2024, unless the Secretary establishes an earlier end date, based 
upon the statutory authority in the Social Security Act that authorizes 
the Secretary to issue any regulations deemed necessary to protect the 
health and safety of patients receiving services in hospitals (section 
1861(e)(9) of the Act) and CAHs (section 1820(e)(3) of the Act).
    Comment: Some commenters stated that our proposal to continue 
COVID-19-related data reporting beyond the current PHE declaration was 
burdensome and labor intensive, especially for infection preventionists 
and nurses who have worked additional hours and taken on additional 
duties since the start of the COVID-19 pandemic in March 2020. These 
commenters indicated that the proposals would add to an already high 
level of stress among health care personnel, prompting individuals to 
leave their positions and thereby exacerbating staffing shortages. Some 
commenters offered suggestions for reducing the data categories 
required to mitigate concerns regarding burden, particularly those 
pertaining to suspected cases, staff vaccination, and staffing 
shortages as these have already been made optional or retired from

[[Page 49380]]

current reporting requirements under the PHE (available at https://www.hhs.gov/sites/default/files/covid-19-faqs-hospitals-hospital-laboratory-acute-care-facility-data-reporting.pdf). In addition, a few 
commenters suggested reducing or changing specific data elements for 
health care worker vaccination status, including but not limited to 
those elements for vaccine manufacturer and first and second doses in a 
series. Some commenters suggested that we reevaluate the data 
categories and reduce where necessary without identifying specific data 
categories to remove. Other commenters stated that the proposed data 
categories were reasonable and represented a balance between burden on 
facilities and patient health and safety considerations associated with 
COVID-19.
    Response: We understand the burden concerns shared by commenters 
and appreciate the suggestions offered to mitigate those concerns. As 
noted previously, we believe this information collection and record is 
vital to ensure the health and safety of patients and the communities 
in which they live. However, we agree that in a post-PHE posture that 
certain COVID-19 specific data categories may not provide additional 
value to inform our surveillance and mitigation efforts. Therefore, as 
further discussed in this section, we have re-evaluated the proposed 
data elements in consideration of the feedback shared by commenters and 
the evolving state of the current PHE and are modifying our proposal to 
remove the following from the list of required data categories to 
report:
     Suspected COVID-19 infections among patients and staff--
Although data pertaining to suspected cases were valuable throughout 
the COVID-19 PHE, particularly in instances when testing supplies were 
limited and cases were often identified based on clinical signs and 
symptoms, this information is less meaningful now that testing supplies 
are readily available to confirm the presence of infection. Thus, we do 
not believe suspected COVID-19 infection data would be necessary to 
collect from hospitals and CAHs once the PHE declaration ends, and 
therefore, we removed this data category.
     Confirmed COVID-19 and influenza infections among staff, 
confirmed co-morbid influenza and COVID-19 infections among staff, and 
COVID-19 and influenza deaths among staff--The data categories for 
staff (suspected infections among staff; confirmed COVID-19, influenza, 
and co-morbid infections among staff; COVID-19 and influenza deaths 
among staff) have not been among the information that hospitals and 
CAHs were required to report throughout the COVID-19 PHE. Hospitals and 
CAHs were required to report suspected, confirmed, and comorbid 
infections, as well as deaths, for patients only. Upon reflection, we 
do not believe collecting these data for staff from hospitals and CAHs 
post-PHE is necessary.
    While beneficial during an active PHE and the specific 
circumstances of the COVID-19 PHE, we believe the data categories 
previously noted are not necessary to provide the most valuable 
information during a post-PHE state for continued monitoring, and as 
such we are removing these data categories to be responsive to 
commenter concerns regarding increased burden on facilities and staff, 
while also attempting to provide quality care for patients.
    The data categories that we are finalizing in this rule that 
hospitals and CAHs will be required to report relevant to COVID-19, to 
the extent as determined by the Secretary, are as follows: Confirmed 
infections among patients; Total deaths among patients; Personal 
protective equipment and testing supplies; Ventilator use, capacity, 
and supplies; Total bed and intensive care unit bed census and 
capacity; Staffing shortages; Vaccine administration data of patients 
and staff; and Relevant therapeutic inventories or usage, or both. The 
data categories that we are finalizing in this rule that hospitals and 
CAHs will be required to report relevant to influenza, to the extent as 
determined by the Secretary, are as follows: Confirmed infections among 
patients; Total deaths among patients; and Confirmed co-morbid 
influenza and COVID-19 infections among patients. We believe these data 
will offer the most valuable information during a post-PHE state by 
continuing to capture critical data on COVID-19 for ongoing 
surveillance and to inform any potential action to protect patient 
health and safety. As previously discussed, these data will enable the 
federal government to monitor the ability of facilities to provide safe 
care for patients by determining the number of COVID-19 and influenza 
infections being treated by facilities; the quantity of resources 
available to facilities and the volume of resources they are using; and 
facilities' continued capacity to provide safe patient care. In 
addition, as done throughout the COVID-19 pandemic, local, state, and 
federal authorities will continue to use these data to identify 
possible resurgence in cases and outbreaks, for resource allocation 
purposes, and to update guidance pertaining to the safe provision of 
patient care.
    As indicated in the proposal, we do not expect continued daily 
reporting for COVID-19 or influenza outside of a declared PHE. 
Moreover, the rule allows for the scope of data categories and 
frequency of data collection and reporting to be reduced and limited, 
as determined by the Secretary, responsive to evolving clinical and 
epidemiology circumstances. This approach to reducing the proposed set 
of required data categories will provide a path towards winding down 
the overall reporting of COVID-19-related data between the end of the 
current PHE and April 2024, when these requirements will sunset. These 
requirements will not be implemented and enforced until the current 
COVID-19 PHE declaration concludes, and CMS will issue guidance 
indicating such a transition. As discussed previously, we expect the 
method of notification to follow a model similar to that which we used 
to inform regulated entities at the beginning of the COVID-19 PHE (see 
QSO-21-03-Hospitals/CAHs at https://www.cms.gov/files/document/qso-21-03-hospitalscahs.pdf-0).
C. Comments Pertaining to the Proposals for Data Reporting in the Event 
of a Future PHE Declaration
    Comment: In the proposed rule, we solicited comment on the 
potential that long-term data collection in the event of a future PHE 
may duplicate elements already reported elsewhere and on the 
feasibility of such a requirement. Many commenters acknowledged the 
hard work of the hospital system during the COVID-19 PHE and the many 
efforts taken by facilities to quickly adapt and respond to both the 
demands of the PHE and the requirements to report critical data for 
monitoring and surveillance. When considering the feasibility of 
maintaining these efforts long-term, a few commenters questioned the 
appropriateness of requiring its collection as a CoP (noting that many 
hospitals provided such data voluntarily prior to mandating its 
collection), especially within the CoPs for infection prevention and 
control and antibiotic stewardship. Specifically, these commenters 
indicated that the COVID-19 data do not directly or indirectly reflect 
a facility's infection control policies or practices, but rather, are 
descriptive of public health information (such as, infection rate, bed 
capacity, supplies, etc.). With regard to duplication, some commenters 
raised concerns about accessibility and the flow of reported 
information across various government entities and response partners. 
Many noted that, throughout the COVID-19 PHE,

[[Page 49381]]

hospitals have been required to report similar (but not necessarily 
standardized) data elements to multiple agencies (federal, state, 
local) and through multiple platforms. Likewise, commenters also 
reiterated that various reporting requirements already exist such as 
requirements to report quality measures and shared concerns that the 
new requirements proposed would perpetuate, if not exacerbate, 
reporting redundancies that tax already limited facility and staff time 
and resources--particularly if state and local public health and 
emergency management agencies do not have timely or complete access to 
data reported through federal systems. Nearly all of these commenters 
called for CMS and other HHS agencies to work closely with facilities, 
as well as state and local agencies, to align and streamline future 
reporting requirements.
    Response: We appreciate this informative feedback regarding the 
challenges and often redundant efforts associated with current 
reporting. As noted in the proposed rule, CMS does not intend to 
supplant or duplicate existing state and local requirements and 
mechanisms for reporting of public health and disease surveillance data 
(87 FR 28622). We believe that the reporting requirements proposed for 
health care facilities in these CoPs are distinct from and serve a 
different purpose than case surveillance of notifiable diseases and 
conditions that is conducted by state and local health departments. 
State and local authorities define their own reporting requirements and 
data definitions, but differences among these data neither enable 
comparisons across states and local jurisdictions nor provide a 
national perspective. Moreover, HHS does not have easy access to the 
data reported to state and local authorities; these authorities are not 
required to report the data to the federal government, and, unless such 
authorities are also directly providing health services, CMS has no 
authority to require state and local authorities to collect certain 
data, standardize the data collected, and report such data to the 
federal government. However, as discussed previously in this rule, 
during the COVID-19 PHE, HHS worked with states and other jurisdictions 
to ensure they had access to the data reported by hospitals and CAHs 
directly to the federal government, and several states submitted data 
to the federal government on behalf of hospitals and CAHs within their 
jurisdictions. HHS will continue to partner with state and local 
jurisdictions, health care facilities, and stakeholders to coordinate 
data collection, sharing, and accessibility in a streamlined fashion 
that satisfies the needs of all stakeholders while reducing duplicative 
reporting requirements, to the extent possible. Also as previously 
discussed, data collected and reported by hospitals and CAHs during the 
COVID-19 PHE enabled the federal government to monitor the ability of 
facilities to provide safe care to patients, and these date were used 
by local, state, and federal government agencies to allocate resources 
(such as PPE, staff, strike teams, funding) to hospitals and to update 
guidance on the provision of care, which was particularly important 
during periods of staffing and PPE scarcity and limited capacity. 
Therefore, we continue to see the value in creating long-term 
opportunities to activate the collection of this data and the need for 
increased preparedness across the health care system in the event of a 
future PHE. Lessons learned from the COVID-19 PHE have also highlighted 
the need for and importance of community engagement and collaboration 
amongst hospitals and CAHs, but also across provider types.
    Throughout the COVID-19 pandemic, it has been imperative for 
facilities to have the ability to both assess and communicate their 
needs and to monitor their ability to continue to provide safe care. 
While we can appreciate the concerns shared by commenters regarding the 
burden and appropriateness of including a requirement for surveillance 
reporting as a long-term CoP in a facility's infection control and 
prevention standards, we disagree that such reporting is not 
appropriate for the CoPs in an effort to protect patient health and 
safety. However, we agree that additional consideration is necessary to 
fully establish a long-term solution for ensuring the preparedness of 
the healthcare system in the event of another PHE. Therefore, we are 
withdrawing our proposal to require future infectious disease reporting 
in the event of a declared PHE. We agree that continued collaboration 
across government partners and engagement with interested parties to 
standardize and streamline reporting efforts would be beneficial. We 
also echo commenters encouragement to continue efforts to further 
enhance the infrastructure used to support the submission of data for 
the long-term in hopes of mitigating many of the burden concerns raised 
by comments. We appreciate the commenters who have acknowledged the 
ongoing efforts by facilities to meet the current reporting 
requirements and the willingness of many hospitals to report the 
information voluntarily. While CMS considers a longer-term solution for 
ensuring overall preparedness as previously noted, it is our 
expectation that hospitals and CAHs will continue increasing their 
readiness and will be prepared to report data in the event of a future 
declared PHE.
    Comment: We received a mixed response to our proposal to require 
facilities to report person-level data during a pandemic. Commenters 
who supported the proposal noted that person-level data would provide 
information about how different groups are affected by an infectious 
disease thereby supporting efforts focused on advancing health equity 
and suggested this data should include socioeconomic status. Commenters 
who disagreed noted concerns related to burden and indicated that such 
reporting would be unreasonable, particularly for larger facilities or 
those facilities lacking automated processes to collect and report such 
data. These commenters also questioned the use of and need for person-
level data. Other commenters acknowledged our efforts to limit any 
directly or potentially individually identifiable person-level data, 
but noted the that local health departments currently use information 
such as name, date of birth, and patient addresses to link case and 
exposure data to identify clusters and inform infection prevention and 
control efforts by local jurisdictions.
    Response: We thank commenters for their feedback. We believe that 
person-level data elements, such as race, ethnicity, age, sex 
residential county and zip code, and relevant comorbidities for 
affected patients, will help to inform response management and address 
health equity issues. In the absence of these data, it is challenging 
to take actions to reduce disparities in disease incidence and 
severity, access, and effectiveness of relevant preventive and 
therapeutic services (for example, vaccines) among vulnerable or 
otherwise marginalized populations. As noted in the proposed rule, the 
lack of individual data elements was an important gap raised during the 
COVID-19 PHE and we are seeking ways to increase our ability to follow 
patients through the health care system to provide actionable 
information on outcomes and health care facility capacities. We will 
consider all of the feedback received as we continue to explore issues 
of if and when person-level data may be warranted in the context of 
future PHE reporting requirements.
    Comment: Many commenters supported our proposal to require 
facilities to report the required data to

[[Page 49382]]

the NHSN or some other CDC- supported surveillance system. Commenters 
acknowledged the CDC's NHSN as a leader for data collection and 
reporting in health care settings and supported our goal of promoting a 
standardized and streamlined framework for data reporting. However, 
while supporting the use of NHSN commenters emphasized that its usage 
must complement, not replace, existing data collection efforts that 
provide awareness and inform health care practices, especially those at 
the local level. Commenters noted that local health departments are 
increasingly called to facilitate coordination between health care 
facilities, provide leadership in response efforts, and often leverage 
their jurisdictional data to establish trends for their jurisdiction, 
and target stewardship and infection prevention and control 
initiatives. These commenters shared concerns regarding the likelihood 
that critical data would continue to be reported to both NHSN and any 
local surveillance systems given the resource burden that would be 
placed on providers. Specifically, commenters noted systems such as 
those used for case reporting, laboratory data, and vaccination 
registries.
    Response: We appreciate the feedback and the additional comments 
noted previously regarding additional reporting streams and data 
collection efforts. In the proposed rule, we noted that we proposed 
reporting the CDC's NHSN because it is a vendor-neutral, federally 
owned system and as such provides ready access to data to state and 
many local public health agencies and can accept data submitted by 
outside vendors contracted either by hospitals, jurisdictions, or other 
Federal entities to submit data on behalf of providers (87 FR 28622). 
Additionally, as previously noted in the proposed rule, through 
resources provided by the American Rescue Plan Act and its Data 
Modernization Initiative, CDC is investing in increasing the automation 
capabilities of surveillance systems, like NHSN, and its ability to 
connect with other data submission techniques, vendors, and systems to 
further automate data collection, reduce provider burden, and increase 
data accessibility for stakeholders. In the proposed rule, CMS also 
noted the existing requirement for eligible hospitals and CAHs 
participating in the Promoting Interoperability Program to report four 
of the six of the measures associated with the Public Health and 
Clinical Data Exchange Objective (Syndromic Surveillance Reporting, 
Immunization Registry Reporting, Electronic Case Reporting, and 
Electronic Reportable Laboratory Result Reporting), and that to take 
advance of other reporting streams, CMS would consider other CDC-
supported surveillance systems, as determined by the Secretary, for 
data reporting to allow for flexibility in the designation of future 
systems that are most capable of meeting these needs. We will consider 
all of these comments as we continue to seek opportunities to work with 
interested parties to explore the most effective approaches for data 
reporting that informs the success of our response efforts, 
incentivizes and encourages preparedness among providers in the event 
of a future PHE, and ensures health and safety for patients and 
communities served by providers.
    Final Rule Action: After consideration of the public comments, we 
are finalizing our proposal with the following changes--
    1. We are modifying our proposal at Sec. Sec.  482.42(e) and (f) 
for hospitals and Sec. Sec.  485.640(d) and (e) for CAHs, to decrease 
the scope of data categories required for continued COVID-19 and 
seasonal influenza reporting.
    2. We are withdrawing our proposal to add new paragraphs at 
482.42(g) (hospitals) and 485.640(f) (CAHs), to establish reporting 
requirements for an infectious disease in the event of a PHE 
declaration. CMS believes that additional consideration is necessary to 
establish a longer-term solution for data collection and reporting that 
ensures the ongoing preparedness of the entire health care system in 
the event of another PHE involving an infectious disease or a PHE 
resulting from natural or human-made factors. We also believe that 
continued collaboration among government and interested parties would 
be beneficial to standardize and streamline data reporting to the 
extent possible thereby reducing burden on facilities, particularly 
during emergencies when resources are stretched and patient care-
related work demands are elevated. As previously discussed, while CMS 
considers a longer-term solution for ensuring overall preparedness in 
the event of future emergencies, it is our expectation that hospitals 
and CAHs will continue assessing and improving their readiness to 
report data in the event of a future declared PHE, consistent with 
their existing requirements for emergency preparedness.
C. Public Comments Requested on IPPS and OPPS Payment Adjustments for 
Wholly Domestically Made NIOSH-Approved Surgical N95 Respirators
    In the FY 2023 IPPS/LTCH PPS proposed rule, we requested public 
comments on potential IPPS and OPPS payment adjustments for wholly 
domestically made National Institute for Occupational Safety & Health 
(NIOSH)-approved surgical N95 respirators (87 FR 28622 through 28625). 
Given the importance of NIOSH-approved surgical N95 respirators in 
protecting hospital personnel and beneficiaries from the SARS-CoV-2 
virus and future respiratory pandemic illnesses, we indicated we were 
considering whether it might be appropriate to provide payment 
adjustments to hospitals to recognize the additional resource costs 
they incur to acquire NIOSH-approved surgical N95 respirators that are 
wholly domestically made. We stated that NIOSH-approved surgical N95 
respirators, which faced severe shortage at the onset of the COVID-19 
pandemic, are essential for the protection of patients and hospital 
personnel that interface with patients. We indicated that procurement 
of NIOSH-approved surgical N95 respirators that are wholly domestically 
made, while critical to pandemic preparedness and protecting health 
care workers and patients, can result in additional resource costs for 
hospitals.
    We stated we were interested in feedback and comments on the 
appropriateness of payment adjustments that would account for these 
additional resource costs. We stated that we believed such payment 
adjustments could help achieve a strategic policy goal, namely, 
sustaining a level of supply resilience for NIOSH-approved surgical N95 
respirators that is critical to protect the health and safety of 
personnel and patients in a public health emergency. We stated we were 
considering such payment adjustments for 2023 and potentially 
subsequent years.
    We received many comments that were helpful in developing the 
payment adjustment that we proposed in the CY 2023 OPPS/ASC proposed 
rule. For instance, many commenters were supportive of a payment 
adjustment, acknowledging the importance of surgical N95 respirators in 
keeping health care workers and patients safe and attesting to the 
difficulties of procuring surgical N95 respirators during the height of 
the COVID-19 pandemic. The majority of commenters supported an approach 
of CMS making biweekly interim lump-sum payments

[[Page 49383]]

that would be reconciled at cost report settlement, although some 
commenters preferred a claims-based approach. Many commenters urged CMS 
to minimize the administrative burden on hospitals in the development 
of any N95 payment policy. We also acknowledge the comments of MedPAC 
and others stating that Medicare payment policy is not the most 
appropriate mechanism to support domestic manufacturing of medical 
supplies.
    In the CY 2023 OPPS/ASC proposed rule, we proposed to make a 
payment adjustment under the OPPS and IPPS for the additional resource 
costs of domestic NIOSH-approved surgical N95 respirators for cost 
reporting periods beginning on or after January 1, 2023. We refer the 
reader to the CY 2023 OPPS/ASC proposed rule for the complete 
discussion on this proposal.

XI. MedPAC Recommendations

    Under section 1886(e)(4)(B) of the Act, the Secretary must consider 
MedPAC's recommendations regarding hospital inpatient payments. Under 
section 1886(e)(5) of the Act, the Secretary must publish in the annual 
proposed and final IPPS rules the Secretary's recommendations regarding 
MedPAC's recommendations. We have reviewed MedPAC's March 2022 ``Report 
to the Congress: Medicare Payment Policy'' and have given the 
recommendations in the report consideration in conjunction with the 
policies set forth in this final rule. MedPAC recommendations for the 
IPPS for FY 2023 are addressed in Appendix B to this final rule.
    For further information relating specifically to the MedPAC reports 
or to obtain a copy of the reports, contact MedPAC at (202) 653-7226, 
or visit MedPAC's website at https://www.medpac.gov.

XII. Other Required Information

A. Publicly Available Files

    IPPS-related data are available on the internet for public use. The 
data can be found on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index. We listed the 
data files available in the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 
28625 through 28627).
    Commenters interested in discussing any data files used in 
construction of this final rule should contact Michael Treitel at (410) 
786-4552.

B. Collection of Information Requirements

1. Statutory Requirement for Solicitation of Comments
    Under the Paperwork Reduction Act (PRA) of 1995, we are required to 
provide 60-day notice in the Federal Register and solicit public 
comment before a collection of information requirement is submitted to 
the Office of Management and Budget (OMB) for review and approval. In 
order to fairly evaluate whether an information collection should be 
approved by OMB, section 3506(c)(2)(A) of the PRA of 1995 requires that 
we solicit comment on the following issues:
     The need for the information collection and its usefulness 
in carrying out the proper functions of our agency.
     The accuracy of our estimate of the information collection 
burden.
     The quality, utility, and clarity of the information to be 
collected.
     Recommendations to minimize the information collection 
burden on the affected public, including automated collection 
techniques.
    In the FY 2023 IPPS/LTCH PPS proposed rule, we solicited public 
comment on each of these issues for the following sections of this 
document that contain information collection requirements (ICRs).
2. ICRs for the Hospital Wage Index for Acute Care Hospitals
    Section III.E.1. of the preamble of this final rule, use of 2019 
Medicare wage index occupational mix survey for the FY 2023 wage index, 
references the information collection request currently approved under 
0938-0907. There were no proposed changes to the currently approved 
information collection request associated with this rulemaking; 
however, we note that the information collection expires October 31, 
2022. An extension of the information collection request is currently 
being developed. The public will have an opportunity to review and 
submit comments regarding the extension of this PRA package through a 
public notice and comment period separate from this rulemaking.
    Section III.I.2.a. of the preamble of this final rule, FY 2023 
Reclassification Application Requirements and Approvals, references the 
information collection request 0938-0573 which expired on January 31, 
2021. A reinstatement of the information collection request is 
currently being developed. The public will have an opportunity to 
review and submit comments regarding the reinstatement of this PRA 
package through a public notice and comment period separate from this 
rulemaking.
    We did not receive comments regarding the ICRs for the hospital 
wage index for acute care hospitals.
3. ICRs for Payments for Low-Volume Hospitals
    As discussed in section V.C. of this final rule, in accordance with 
section 1886(d)(12) of the Act, beginning with FY 2023, the low-volume 
hospital definition and payment adjustment methodology will revert back 
to the statutory requirements that were in effect prior to the 
amendments made by the Affordable Care Act and subsequent legislation. 
Therefore, effective for FY 2023 and subsequent years, under current 
policy at Sec.  412.101(b), in order to qualify as a low-volume 
hospital, a subsection (d) hospital must be more than 25 road miles 
from another subsection (d) hospital and have less than 200 discharges 
during the fiscal year. In that section we also discuss the process for 
requesting and obtaining the low-volume hospital payment adjustment 
under Sec.  412.101. Specifically, a hospital makes a written request 
to its MAC that contains sufficient documentation to establish that the 
hospital meets the applicable statutory mileage and discharge criteria. 
While this information collection requirement would normally be subject 
to the PRA, we believe in this instance it is exempt. Based on 
historical data, we estimated there are fewer than 5 hospitals among 
all subsection (d) hospitals that will meet the applicable mileage and 
discharge criteria for FY 2023. In accordance with the implementing 
regulations of the PRA at 5 CFR 1320.3(c)(4), the requirement will be 
exempt as it affects less than 10 entities in a 12-month period.
    We did not receive comments regarding the ICRs for payments for 
low-volume hospitals.
4. ICRs Relating to the Hospital Readmissions Reduction Program
    In section V.H of the preamble of this final rule, we discuss 
requirements for the Hospital Readmissions Reduction Program. In this 
rule, we are not removing or adopting any new measures into the 
Hospital Readmissions Reduction Program for FY 2023. All six of the 
current Hospital Readmissions Reduction Program's measures are claims-
based measures. We believe that continuing to use these claims-based 
measures would not create or reduce any information collection burden 
for hospitals because they will continue to be collected using Medicare 
FFS claims that hospitals are already submitting to

[[Page 49384]]

the Medicare program for payment purposes.
5. ICRs for the Hospital Value--Based Purchasing (VBP) Program
    In section V.I. of the preamble of this final rule, we discuss new 
requirements we are finalizing for the Hospital VBP Program. 
Specifically, in this final rule, with respect to quality measures, we 
are finalizing our proposals to suppress the Hospital Consumer 
Assessment of Healthcare Providers and Systems (HCAHPS) Survey and the 
five Healthcare--Associated Infection (HAI) measures for the FY 2023 
program year. We are also finalizing our proposal to continue requiring 
hospitals to report data for all measures, including measures we are 
suppressing for FY 2023. Because the FY 2023 Hospital VBP Program will 
use data that are also used to calculate quality measures in other 
programs and Medicare FFS claims data that hospitals are already 
submitting to CMS for payment purposes, we do not anticipate any change 
in burden associated with this final rule.
6. ICRs Relating to the Hospital-Acquired Condition (HAC) Reduction 
Program
    In this final rule, we are not removing any measures, adopting any 
new measures into the HAC Reduction Program, or updating our validation 
procedures.\1162\ The HAC Reduction Program has previously adopted six 
measures: the CMS PSI 90 measure and five CDC NHSN HAI measures. We are 
not finalizing our proposal to not calculate measure results for PSI 90 
and thus will be calculating measure results for the FY 2023 HAC 
Reduction program. We do not believe that the claims-based CMS PSI 90 
measure in the HAC Reduction Program creates additional burden for 
hospitals because the measure is calculated using the Medicare FFS 
claims that hospitals have submitted to the Medicare program for 
payment purposes. Accordingly, we do not believe that our finalized 
policy in sections V.J.3.c.(1). to increase the minimum volume 
threshold for the CMS PSI 90 measure changes any information collection 
burden for hospitals.
---------------------------------------------------------------------------

    \1162\ Burden associated with the validation procedures in the 
HAC Reduction Program are accounted for under OMB Control Number 
0938-1352.
---------------------------------------------------------------------------

    We note the burden associated with collecting and submitting data 
for the HAI measures (CAUTI, CLABSI, Colon and Abdominal Hysterectomy 
SSI, MRSA bacteremia, and CDI) via the CDC's NHSN system is captured 
under a separate OMB control number, 0920-0666 (expiration January 1, 
2025). As discussed in sections V.J.2.b.(2). and V.J.2.b.(3). of the 
preamble of this final rule, we are suppressing the five NHSN measures 
from the FY 2023 HAC Reduction Program. We are also suppressing CY 2021 
CDC NHSN HAI data from the FY 2024 program year. Because hospitals 
would continue to report data for the HAI measures, this policy does 
not change information collection burden for hospitals as accounted for 
under CDC's OMB control number 0920-1066.
    In section V.J.7. of the preamble of this final rule, we clarify 
the removal of the No Mapped Locations (NML) policy beginning in FY 
2023. Hospitals will be required to appropriately submit data to the 
NHSN or, if hospitals do not have the applicable locations for the 
CLABSI and CAUTI measures, the hospital must submit an IPPS Measure 
Exception Form to be exempt from CLABSI and CAUTI reporting for CMS 
programs. The burden for all hospitals to submit data to the NHSN is 
already accounted for under OMB control number 0920-0666, therefore 
there is no increase in burden for hospitals which submit data as a 
result of this clarification. In addition, the burden associated with 
completion of forms (including the IPPS Measure Exception Form) is 
already accounted for under OMB control number 0938-1022 (expiration 
date December 31, 2022), therefore there is no increase in burden for 
hospitals which elect to submit this form as a result of this 
clarification. This clarification does not necessitate substantive 
changes to the IPPS Measure Exception Form, therefore any change in 
burden is negligible and our currently approved burden estimates under 
OMB control number 0938-1022 are conservative enough to accommodate the 
change. Revisions to the IPPS Measure Exception Form, will be submitted 
for approval under OMB control number 0938-1022.
    We did not receive comments regarding the ICRs for the HAC 
Reduction Program.
7. ICRs for the Hospital Inpatient Quality Reporting (IQR) Program
a. Background
    The Hospital IQR Program (formerly referred to as the Reporting 
Hospital Quality Data for Annual Payment Update (RHQDAPU) Program) was 
originally established to implement section 501(b) of the MMA, Public 
Law 108-173. OMB has currently approved 1,572,810 hours of burden and 
approximately $65 million under OMB control number 0938-1022 
(expiration date December 31, 2022), accounting for information 
collection burden experienced by approximately 3,300 IPPS hospitals and 
1,100 non-IPPS hospitals for the FY 2024 payment determination. In the 
proposed rule (87 FR 28627 through 28635) and this final rule, we 
describe the burden changes regarding collection of information under 
OMB control number 0938-1022 (expiration date December 31, 2022) for 
IPPS hospitals.
    For more detailed information on our finalized policies for the 
Hospital IQR Program, we refer readers to section IX.E. of the preamble 
of this final rule. We are adopting four measures that we expect to 
affect our collection of information burden estimates: (1) The Hospital 
Commitment to Health Equity structural measure, beginning with the CY 
2023 reporting period/FY 2025 payment determination and for subsequent 
years; (2) the Screening for Social Drivers of Health measure, 
beginning with voluntary reporting for the CY 2023 reporting period and 
mandatory reporting beginning with the CY 2024 reporting period/FY 2026 
payment determination; (3) the Screen Positive Rate for Social Drivers 
of Health measure, beginning with voluntary reporting for the CY 2023 
reporting period and mandatory reporting beginning with the CY 2024 
reporting period/FY 2026 payment determination; and (4) the Hospital-
level THA/TKA PRO-PM, beginning with voluntary reporting across two 
periods, followed by mandatory reporting of the measure for the 
reporting period which runs from July 1, 2025 through June 30, 2026, 
impacting the FY 2028 payment determination. We are also modifying our 
eCQM reporting and submission requirements which will increase the 
total number of eCQMs to be reported from four to six eCQMs beginning 
with the CY 2024 reporting period/FY 2026 payment determination, which 
will additionally affect our collection of information burden. The 
estimated collection of burden associated with our finalized proposals 
is discussed in this section of this final rule.
    We are also finalizing policies which will not affect the 
information collection burden associated with the Hospital IQR Program. 
As discussed in section IX.E. of the preamble of this final rule, we 
are adopting four eCQMs: (1) Cesarean Birth electronic clinical quality 
measure (eCQM), with inclusion in the eCQM measure set beginning with 
the CY 2023 reporting period/FY 2025 payment determination, followed by 
mandatory reporting beginning with the CY 2024 reporting period/FY 2026 
payment

[[Page 49385]]

determination; (2) Severe Obstetric Complications eCQM, with inclusion 
in the eCQM measure set beginning with the CY 2023 reporting period/FY 
2025 payment determination, followed by mandatory reporting beginning 
with the CY 2024 reporting period/FY 2026 payment determination; (3) 
Hospital-Harm--Opioid-Related Adverse Events eCQM, beginning with 
inclusion in the eCQM measure set in the CY 2024 reporting period/FY 
2026 payment determination; and (4) Global Malnutrition Composite Score 
eCQM, beginning with inclusion in the eCQM measure set in the CY 2024 
reporting period/FY 2026 payment determination. We are also adopting 
two claims-based measures beginning with the FY 2024 payment 
determination: (1) MSPB Hospital; and (2) the Hospital-Level RSCR 
Following Elective Primary THA/TKA. We are refining two current 
Hospital IQR Program claims-based measures beginning with the FY 2024 
payment determination: (1) Hospital-Level, Risk-Standardized Payment 
Associated with an Episode of Care for Primary Elective THA/TKA; and 
(2) The Acute Myocardial Infarction (AMI) Excess Days in Acute Care 
(EDAC). Lastly, we are: (1) Establishing a hospital designation related 
to patient care to be publicly-reported on a public-facing website 
beginning in Fall 2023; (2) modifying our case threshold exemptions and 
zero denominator declaration policies for hybrid measures as we believe 
they are not applicable for this measure type beginning with the FY 
2026 payment determination; and (3) modifying our eCQM validation 
policy to increase the reporting of medical requests from 75 percent of 
records to 100 percent of records, beginning with the validation of CY 
2022 eCQM data affecting the FY 2025 payment determination.
    The most recent data from the Bureau of Labor Statistics reflects a 
median hourly wage of $21.20 per hour for a medical records and health 
information technician professional.\1163\ We calculated the cost of 
overhead, including fringe benefits, at 100 percent of the median 
hourly wage, consistent with previous years. This is necessarily a 
rough adjustment, both because fringe benefits and overhead costs vary 
significantly by employer and methods of estimating these costs vary 
widely in the literature. Nonetheless, we believe that doubling the 
hourly wage rate ($21.20 x 2 = $42.40) to estimate total cost is a 
reasonably accurate estimation method. Accordingly, unless otherwise 
specified, we will calculate cost burden to hospitals using a wage plus 
benefits estimate of $42.40 per hour throughout the discussion in this 
section of this rule for the Hospital IQR Program.
---------------------------------------------------------------------------

    \1163\ U.S. Bureau of Labor Statistics. Occupational Outlook 
Handbook, Medical Records and Health Information Technicians. 
Accessed on January 13, 2022. Available at: https://www.bls.gov/ooh/healthcare/medical-records-and-health-information-technicians.htm.
---------------------------------------------------------------------------

    In the FY 2022 IPPS/LTCH PPS final rule (86 FR 45507), our burden 
estimates were based on an assumption of approximately 3,300 IPPS 
hospitals. For this final rule, we are updating our assumption to 3,150 
IPPS hospitals based on recent data from the FY 2022 Hospital IQR 
Program payment determination which reflects a closer approximation of 
the total number of hospitals reporting data to the Hospital IQR 
Program.
b. Information Collection Burden Estimate for the Hospital Commitment 
to Health Equity Structural Measure Beginning With the CY 2023 
Reporting Period/FY 2025 Payment Determination
    In section IX.E.5.a. of the preamble of this final rule, we are 
finalizing adoption of the Hospital Commitment to Health Equity 
structural measure beginning with the CY 2023 reporting period/FY 2025 
payment determination. Hospitals will report data through the Hospital 
Quality Reporting (HQR) System.
    Hospitals will submit the response on an annual basis during the 
submission period. We estimate the information collection burden 
associated with this structural measure to be, on average across all 
3,150 IPPS hospitals, no more than 10 minutes per hospital per year, as 
it involves attesting to as many as five questions one time per year 
for a given reporting period. While we understand some hospitals may 
require more than 10 minutes to research the information needed to 
respond, we believe that the majority of hospitals will have the 
information readily available to respond to the questions listed in 
section IX.E.5.a. of the preamble of this final rule and will require 
less than 10 minutes. In addition, we believe that many hospitals will 
be able to submit similar responses in future years, thereby reducing 
the actual time to respond in subsequent reporting periods. Using the 
estimate of 10 minutes (or 0.167 hours) per hospital per year, and the 
updated wage estimate as described previously, we estimate that this 
policy will result in a total annual burden increase of 525 hours 
across all participating IPPS hospitals (0.167 hours x 3,150 IPPS 
hospitals) at a cost of $22,260 (525 hours x $42.40). With respect to 
any costs/burdens unrelated to data submission, we refer readers to the 
Regulatory Impact Analysis (section I.K. of Appendix A of this final 
rule).
c. Information Collection Burden Estimate for the Screening for Social 
Drivers of Health Measure Beginning With Voluntary Reporting in the CY 
2023 Reporting Period and Mandatory Reporting in the CY 2024 Reporting 
Period/FY 2026 Payment Determination
    In section IX.E.5.b.(1). of the preamble of this final rule, we are 
adopting the Screening for Social Drivers of Health measure beginning 
with voluntary reporting in the CY 2023 reporting period and mandatory 
reporting beginning with the CY 2024 reporting period/FY 2026 payment 
determination. Hospitals will report data through the HQR System.
    As discussed in the preamble of this final rule, hospitals will be 
able to collect data and report the measure via multiple methods. We 
believe that most hospitals will likely collect data through a 
screening tool incorporated into their electronic health record (EHR) 
or other patient intake process.
    We believe the Outcome and Assessment Information Set (OASIS), 
which is currently used in the Home Health Quality Reporting Program, 
is a reasonable comparison for estimating the information collection 
burden for the Screening for Social Drivers of Health measure due to 
analogous assessment of patient-level need. The OASIS is a core 
standard assessment data set home health agencies integrate into their 
own patient-specific, comprehensive assessment to identify each 
patient's need for home care that meets the patient's medical, nursing, 
rehabilitative, social, and discharge planning needs. For OASIS, the 
currently approved information collection burden under OMB 0938-1279 
(expiration date November 30, 2024) is estimated to be 0.3 minutes per 
data element (18 seconds). For the five HRSN domains screened for by 
the Social Drivers of Health measure under the Hospital IQR Program, we 
estimate a total of 2 minutes (0.033 hours) per patient to conduct this 
screening. The most recent data from the Bureau of Labor Statistics 
reflects an Average Hourly Earnings of $31.31.\1164\ Based on 
information collected by the American Hospital Association,\1165\ we 
estimate

[[Page 49386]]

approximately 21,000,000 patients (34,251,159 total admissions in U.S. 
community hospitals x 3,150 IPPS hospitals / 5,198 total U.S. community 
hospitals) will be screened annually across all participating IPPS 
hospitals. For the purposes of calculating burden, we estimate that 
during the voluntary period, 50 percent of hospitals will survey 50 
percent of patients. We estimate during the mandatory period, hospitals 
would submit for 100 percent of patients. For the CY 2023 voluntary 
reporting period, we estimate a total burden of 175,000 hours 
(21,000,000 respondents x 50 percent of patients x 50 hospitals of 
hospitals x 0.033 hours) at a cost of $5,479,250 (175,000 hours x 
$31.31) across all participating IPPS hospitals. For the CY 2024 
reporting period and subsequent years, we estimate a total annual 
burden of 700,000 hours (21,000,000 respondents x 0.033 hours) at a 
cost of $21,917,000 (700,000 hours x $31.31) across all participating 
IPPS hospitals.
---------------------------------------------------------------------------

    \1164\ U.S. Bureau of Labor Statistics. Economy at a Glance, 
Average Hourly Earnings. Accessed on January 24, 2022; available at: 
https://www.bls.gov/eag/eag.us.htm.
    \1165\ https://www.aha.org/system/files/media/file/2020/01/2020-aha-hospital-fast-facts-new-Jan-2020.pdf.
---------------------------------------------------------------------------

    Measure data will be submitted via the HQR System annually. Similar 
to the currently approved data submission and reporting burden estimate 
for eCQMs in the Hospital IQR Program and web-based measures for the 
Ambulatory Surgical Center Quality Reporting (ASCQR) Program (OMB 
control number 0938-1270; expiration date July 31, 2024) reported via 
the HQR System, we estimate a burden of 10 minutes per hospital 
response to transmit the measure data. Therefore, we estimate that each 
participating facility will spend 10 minutes (0.1667 hours) annually to 
collect and submit the data via this portal. For the purposes of 
calculating burden, we estimate that during the voluntary period, 50 
percent of hospitals will submit data. For the CY 2023 voluntary 
reporting period, we estimate a total burden of 263 hours (0.1667 hours 
x 3,150 hospitals x 50 percent of hospitals) at a cost of $11,151 (263 
hours x $42.40) across all participating IPPS hospitals. For the CY 
2024 reporting period and subsequent years, we estimate a total annual 
burden for all participating IPPS hospitals of 525 hours (0.1667 hours 
x 3,150 hospitals) at a cost of $22,260 (525 hours x $42.40).
    With respect to any costs/burdens unrelated to data submission, we 
refer readers to the Regulatory Impact Analysis (section I.K. of 
Appendix A of this final rule).
d. Information Collection Burden Estimate for the Screen Positive Rate 
for Social Drivers of Health Process Measure Beginning With Voluntary 
Reporting in the CY 2023 Reporting Period and Mandatory Reporting 
Beginning With the CY 2024 Reporting Period/FY 2026 Payment 
Determination
    In section IX.E.5.b.(2). of the preamble of this final rule, we are 
adopting the Screen Positive Rate for Social Drivers of Health measure 
beginning with voluntary reporting in the CY 2023 reporting period and 
mandatory reporting beginning with the CY 2024 reporting period/FY 2026 
payment determination. Hospitals will report data through the HQR 
System. For this measure, hospitals will be required to report on an 
annual basis the number of patients who screen positive for one or more 
of the five domains (reported as five separate rates) divided by the 
total number of patients screened.
    We previously included the burden associated with screening 
patients in our discussion of the Screening for Social Drivers of 
Health measure. For this measure, we estimate only the additional 
burden for a hospital reporting via the HQR System since patients would 
not need to provide any additional information for this measure. We 
estimate that each participating facility will spend 10 minutes (0.1667 
hours) annually to collect and submit the data. For the purposes of 
calculating burden, we estimate that during the voluntary period, 50 
percent of hospitals would submit data. For the CY 2023 voluntary 
reporting period, we estimate a total burden of 263 hours (0.1667 hours 
x 3,150 hospitals x 50 percent of hospitals) at a cost of $11,130 (263 
hours x $42.40) across all participating IPPS hospitals. For the CY 
2024 reporting period and subsequent years, we estimate a total annual 
burden estimate for all IPPS hospitals of 525 hours (0.1667 hours x 
3,150 hospitals) at a cost of $22,260 (525 hours x $42.40).
e. Information Collection Burden Estimate for the Hospital-Level, Risk 
Standardized Patient-Reported Outcomes Performance Measure (PRO-PM) 
Following Elective Primary Total Hip Arthroplasty (THA) and/or Total 
Knee Arthroplasty (TKA) Beginning With Two Voluntary Reporting Periods 
Followed by Mandatory Reporting for Eligible Elective Procedures 
Occurring July 1, 2025 Through June 30, 2026, Impacting the FY 2028 
Payment Determination, and for Subsequent Years
    In section IX.E.5.g. of the preamble of this final rule, we are 
adopting the THA/TKA PRO-PM beginning with voluntary reporting across 
two periods (July 1, 2023 through June 30, 2024 and July 1, 2024 
through June 30, 2025), followed by mandatory reporting of the measure 
beginning with the reporting period which runs from July 1, 2025 
through June 30, 2026, impacting the FY 2028 payment determination.
    The THA/TKA PRO-PM uses four sources of data for the calculation of 
the measure: (1) PRO data; (2) claims data; (3) Medicare enrollment and 
beneficiary data; and (4) U.S. Census Bureau survey data. We estimate 
no additional burden associated with claims data, Medicare enrollment 
and beneficiary data, and U.S. Census Bureau survey data as these data 
are already collected via other mechanisms.
    Many hospitals have already incorporated patient-reported outcome 
(PRO) data collection into their workflows. While we are not requiring 
how hospitals collect data, hospitals new to collecting PRO data have 
multiple options for when and how they would collect this data so they 
can best determine the mode and timing of collection that works best 
for their patient population. The possible patient touchpoints for pre-
operative PRO data collection include the doctor's office, pre-surgical 
steps such as education classes, or medical evaluations that can occur 
in an office or at the hospital. The modes of PRO data collection can 
include completion of the pre-operative surveys using electronic 
devices (such as an iPad or tablet), pen and paper, mail, phone call, 
or through the patient's portal. Post-operative PRO data collection 
modes are similar to pre-operative modes. The possible patient 
touchpoints for post-operative data collection can occur before the 
follow-up appointment, at the doctor's office, or after the follow-up 
appointment. The potential modes of PRO data collection for post-
operative data are the same as for pre-operative data. If the patient 
does not or cannot attend a follow-up appointment, the modes of 
collection can include completion of the post-operative survey using 
email, mail, phone, or through the patient portal. Use of multiple 
modes will increase response rates as it allows for different patient 
preferences.
    For the THA/TKA PRO-PM data, hospitals will be able to submit data 
during two voluntary periods, followed by mandatory reporting for 
eligible elective procedures occurring July 1, 2025 through June 30, 
2026, impacting the FY 2028 payment determination and for subsequent 
years. Hospitals will need to submit data twice (pre-operative data and 
post-operative data). For the

[[Page 49387]]

purposes of calculating burden, we estimate that during the voluntary 
periods, 50 percent of hospitals that perform at least one THA/TKA 
procedure would submit data, and will do so for 50 percent of THA/TKA 
patients. We estimate during the mandatory period, hospitals will 
submit for 100 percent of patients. While we are requiring hospitals to 
submit, at minimum, 50 percent of eligible, complete pre-operative data 
with matching eligible, complete post-operative data, we are 
conservative in our estimate for the mandatory period in case hospitals 
exceed this threshold.
    Under OMB control number 0938-0981 (expiration date September 30, 
2024), the currently approved burden per respondent to complete the 
Hospital Consumer Assessment of Healthcare Providers and Systems 
(HCAHPS) Survey measure is 7.25 minutes (0.120833 hours). We estimate 
that the time to complete both the preoperative and post-operative 
surveys is analogous to completing the HCAHPS Survey once. The most 
recent data from the Bureau of Labor Statistics reflects an Average 
Hourly Earnings of $31.31.\1166\ For burden estimating purposes, we 
assume that most hospitals will likely undertake PRO data collection 
through a screening tool incorporated into their EHR or other patient 
intake process. We estimate that approximately 330,000 THA/TKA 
procedures occur in the inpatient setting each year, and that many 
patients could complete both the pre-operative and postoperative 
questionnaires, although from our experience with using this measure in 
the Comprehensive Joint Replacement model, we are also aware that not 
all patients who complete the pre-operative questionnaire would 
complete the post-operative questionnaire. Due to the performance 
period for the first voluntary reporting period being 6 months, we 
assume 41,250 patients will complete the survey (165,000 patients x 
0.50 x 0.50 of hospitals) for a total of 4,984 hours annually (41,250 
respondents x 0.120833 hours) at a cost of $156,049 (4,984 hours x 
$31.31) across all IPPS hospitals. For the second voluntary reporting 
periods, we assume 82,500 patients will complete the survey (330,000 
patients x 0.50 x 0.50 hospitals) for a total of 9,969 hours annually 
(82,500 respondents x 0.120833 hours) at a cost of $312,122 (9,969 
hours x $31.31) across all IPPS hospitals. Beginning with mandatory 
reporting for the FY 2028 payment determination, we estimate a total of 
39,875 hours (330,000 patients x 0.120833 hours) at a cost of 
$1,248,486 (39,875 hours x $31.31) across all IPPS hospitals.
---------------------------------------------------------------------------

    \1166\ U.S. Bureau of Labor Statistics. Economy at a Glance, 
Average Hourly Earnings. Accessed on January 24, 2022; available at: 
https://www.bls.gov/eag/eag.us.htm.
---------------------------------------------------------------------------

    For the data submission, which will be reported via the HQR System, 
we estimate a burden of 10 minutes per response. For each of the two 
voluntary reporting periods, we estimate that each hospital will spend 
20 minutes (0.33 hours) annually (10 minutes x 2 surveys) to collect 
and submit the data via this tool. We estimate a resulting burden for 
all participating IPPS hospitals of 525 hours (0.33 hours x 3,150 
hospitals x 50 percent) at a cost of $22,260 (525 hours x $42.40). 
Beginning with mandatory reporting for the FY 2028 payment 
determination, we estimate a total of 1,050 hours (0.33 hours x 3,150 
hospitals) at a cost of $44,520 (1,050 hours x $42.40).
    With respect to any costs/burdens unrelated to data submission, we 
refer readers to the Regulatory Impact Analysis (section I.K. of 
Appendix A of this final rule).
f. Information Collection Burden Estimate for the Modification of the 
eCQM Reporting and Submission Requirements Beginning With the CY 2024 
Reporting Period/FY 2026 Payment Determination
    In section IX.E.10.e. of the preamble of this final rule, we are 
modifying our eCQM reporting and submission requirements whereby we are 
increasing the total number of eCQMs to be reported from four to six 
eCQMs beginning with the CY 2024 reporting period/FY 2026 payment 
determination.
    We previously finalized in the FY 2020 IPPS/LTCH PPS final rule 
that, for the CY 2021 reporting period/FY 2023 payment determination, 
hospitals are required to submit data for four self-selected eCQMs each 
year (84 FR 42503). Additionally, for the CY 2022 reporting period/FY 
2024 payment determination, hospitals are required to submit data for 
three self-selected eCQMs and the Safe Use of Opioids-Concurrent 
Prescribing eCQM for a total of four eCQMs (84 FR 42505). We also 
finalized in the FY 2021 IPPS/LTCH PPS final rule to require hospitals 
to submit four quarters of eCQM data beginning in the CY 2023 reporting 
period/FY 2025 payment determination (85 FR 59008 through 59009). We 
continue to estimate the information collection burden associated with 
the eCQM reporting and submission requirements to be 10 minutes per 
measure per quarter. For the increase in submission from four to six 
eCQMs, we estimate a total of 20 minutes or 0.33 hours (10 minutes x 2 
eCQMs) per hospital per quarter. We estimate a total burden increase of 
1,050 hours across all participating IPPS hospitals (0.33 hour x 3,150 
IPPS hospitals) for each quarter of eCQM data or 4,200 hours annually 
(1,050 hours x 4 quarters) at a cost of $178,080 (4,200 hours x 
$42.40).
g. Information Collection Burden Estimate for the Adoption of Four 
eCQMs: Two Perinatal eCQMs Beginning With the CY 2023 Reporting Period/
FY 2025 Payment Determination; One Opioid-Related Hospital-Harm eCQM 
and One Malnutrition eCQM Beginning With the CY 2024 Reporting Period/
FY 2026 Payment Determination
    In sections IX.E.5.c. and IX.E.5.d. of the preamble of this final 
rule, we are adopting two perinatal eCQMs--Cesarean Birth and Severe 
Obstetric Complications--beginning with the CY 2023 reporting period/FY 
2025 payment determination, followed by mandatory reporting beginning 
with the CY 2024 reporting period/FY 2026 payment determination and for 
subsequent years. Also, in sections IX.E.5.e. and IX.E.5.f. of the 
preamble of this final rule, we are adopting the Hospital-Harm--Opioid-
Related Adverse Events eCQM and the Global Malnutrition Composite Score 
eCQM, respectively, beginning with the CY 2024 reporting period/FY 2026 
payment determination and for subsequent years.
    The addition of these four eCQMs do not affect the information 
collection burden of submitting eCQMs under the Hospital IQR Program. 
Current Hospital IQR Program policy requires hospitals to select four 
eCQMs from the eCQM measure set on which to report (84 FR 42503 through 
4250). In other words, although these new eCQMs are being added to the 
eCQM measure set, hospitals are not required to report more than a 
total of six eCQMs, as finalized in section IX.E.10.e. of the preamble 
of this final rule. In the previous section XII.B.4.f. (of the 
Collection of Information section of this final rule), we account for 
the burden of reporting six eCQMs.
    With respect to any costs/burdens unrelated to data submission, we 
refer readers to the Regulatory Impact Analysis (section I.K. of 
Appendix A of this final rule).

[[Page 49388]]

h. Information Collection Burden Estimate for the Adoption or 
Refinement of Four Claims-Based Measures
    In sections IX.E.5.h., IX.E.5.i., IX.E.6.a., and IX.E.6.b. of the 
preamble of this final rule, we are adopting two claims-based 
measures--MSPB Hospital and Hospital-Level RSCR Following Elective 
Primary THA/TKA--and refining two claims-based measures currently in 
the Hospital IQR Program measure set--Hospital-Level, Risk-Standardized 
Payment Associated with an Episode of Care for Primary Elective THA/TKA 
and AMI EDAC. We are adopting the Hospital MSPB measure and the 
Hospital-Level RSCR Following Elective Primary THA/TKA beginning with 
the FY 2024 payment determination and are refining the other two 
measures beginning with the FY 2024 payment determination and for 
subsequent years. Because these measures are calculated using data that 
are already reported to the Medicare program for payment purposes, 
adopting and refining these measures does not result in a change to the 
burden estimates provided in the FY 2022 IPPS/LTCH PPS final rule (86 
FR 45507 through 45512).
i. Information Collection Burden Estimate for Addition of the Publicly-
Reported Hospital Designation To Capture Hospital Commitment to the 
Quality and Safety of Maternal Health Beginning Fall 2023
    In section IX.E.8. of the preamble of this final rule, we are 
establishing the publicly-reported hospital designation to capture 
hospital commitment to the quality and safety of maternity care on a 
CMS website, for hospitals who qualify for the designation, beginning 
in Fall 2023. In the FY 2022 IPPS/LTCH PPS final rule, we finalized 
adoption of the Maternal Morbidity Structural measure (86 FR 45365) and 
accounted for that burden under OMB control number 0938-1022 
(expiration date December 31, 2022). We expect that our policy will not 
yield a change in burden as it does not require any additional 
information collection nor affect the requirements for data submission 
for hospitals.
j. Information Collection Burden Estimate for the Modification of the 
Case Threshold Exemptions and Zero Denominator Declaration Policies for 
Hybrid Measures Beginning With the FY 2026 Payment Determination
    In section IX.E.10.f.(4). of the preamble of this final rule, we 
are modifying our case threshold exemptions and zero denominator 
declaration policies for hybrid measures as we believe they are not 
applicable for those measure types, beginning with the FY 2026 payment 
determination and for subsequent years.
    In the FY 2020 IPPS/LTCH PPS final rule, we finalized the adoption 
of the Hybrid Hospital-Wide Readmission Measure with Claims and 
Electronic Health Record Data (Hybrid HWR) (84 FR 42505 through 42508) 
and in the FY 2022 IPPS/LTCH PPS final rule, we finalized the Hybrid 
Hospital-Wide Mortality Measure with Claims and Electronic Health 
Record Data (Hybrid HWM) (86 FR 45508). For each hybrid measure, all 
IPPS hospitals are required to submit one of three things: Data via 
QRDA I file, a zero denominator declaration, or a case threshold 
exemption. Of these three options, submission of data via QRDA I file 
is the most burden-intensive. For both hybrid measures, our currently 
approved burden estimates assume data submission via QRDA I file for 
all IPPS hospitals; therefore, we do not believe this modification 
results in an increase in burden.
k. Information Collection Burden Estimate for the Modification of the 
eCQM Validation Policy Medical Record Requests Beginning With the FY 
2025 Payment Determination
    In section IX.E.11.b. of the preamble of this final rule, we are 
modifying our eCQM validation policy to increase the reporting of 
medical requests from at least 75 percent of records to 100 percent of 
records beginning with the FY 2025 payment determination and for 
subsequent years.
    In the FY 2017 IPPS/LTCH PPS final rule, we finalized to require 
submission of at least 75 percent of sampled eCQM medical records in a 
timely and complete manner (81 FR 57181). While we adopted a policy to 
require submission of at least 75 percent of sampled records, we 
estimated the burden associated with this finalized policy with the 
assumption that hospitals would submit 100 percent of sampled eCQM 
medical records (81 FR 57261). Based on this estimate, we believe the 
currently approved burden already encompasses burden associated with 
our finalized policy.
l. Information Collection Burden Estimate To Add Reporting and 
Submission Requirements for PRO-PMs Beginning With the FY 2026 Payment 
Determination
    In section IX.E.10.k. of the preamble of this final rule, we are 
adopting reporting and submission requirements for PRO-PMs beginning 
with the FY 2026 payment determination. Our policy does not yield a 
change in burden beyond that which is discussed in section X.B.6.e. of 
the preamble of this final rule for the THA/TKA PRO-PM.
m. Summary of Information Collection Burden Estimates for the Hospital 
IQR Program
    In summary, under OMB control number 0938-1022 (expiration date 
December 31, 2022), we estimate that the policies promulgated in this 
final rule will result in a total increase of 746,300 hours annually 
for 3,150 IPPS hospitals from the CY 2023 reporting period/FY 2025 
payment determination through the CY 2026 reporting period/FY 2028 
payment determination. The total cost increase related to this 
information collection is approximately $23,437,906. The subsequent 
tables summarize the total burden changes for each respective FY 
payment determination compared to our currently approved information 
collection burden estimates (the table for the FY 2028 payment 
determination reflects the total burden change associated with all 
proposals). For the THA/TKA PRO-PM, only one survey will be 
administered during the CY 2023 reporting period due to the start of 
reporting occurring in 3Q and the beginning of mandatory reporting 
would take place in 3Q of the CY 2025 reporting period. We will submit 
the revised information collection estimates to OMB for approval under 
OMB control number 0938-1022 which expires December 31, 2022.

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8. ICRs for PPS-Exempt Cancer Hospital Quality Reporting (PCHQR) 
Program
    OMB has currently approved 0 hours of burden under OMB control 
number 0938-1175 (expiration date January 31, 2025), accounting for the 
information collection requirements for 11 PCHs for the FY 2024 program 
year.
    For more detailed information on our finalized policies for the 
PCHQR Program, we refer readers to section IX.F. of the preamble of 
this final rule. We are: (1) adopting and codifying a patient safety 
exemption for the measure removal policy; (2) beginning public display 
of the End-of-Life (EOL) measures with modification to begin with FY 
2025 program year data; and (3) beginning public display of the 30-Day 
Unplanned Readmissions for Cancer Patients measure beginning with FY 
2024 program year data. These new requirements do not impact our 
currently approved information collection burden estimates.
    We did not receive comments regarding the ICRs for the PCHQR 
Program.
9. ICRs for the Medicare Promoting Interoperability Program
a. Historical Background
    In section IX.H. of the preamble of this final rule, we discussed 
several policies for the Medicare Promoting Interoperability Program. 
An information collection request under OMB control number 0938-1278 
(expiration date July 31, 2022) reflecting program policies finalized 
in the FY 2022 IPPS/LTCH PPS final rule (86 FR 45514) is pending 
approval, which

[[Page 49393]]

includes an estimated total burden of 21,450 hours and $879,450, 
accounting for information collection burden experienced by 
approximately 3,300 eligible hospitals that attest to CMS under the 
Medicare Promoting Interoperability Program. We will be submitting an 
updated information collection request under OMB control number 0938-
1278 in connection with this FY 2023 IPPS/LTCH PPS final rule that will 
reflect the inclusion of CAHs and additional new information pertinent 
to the collection requirements. The collection of information burden 
analysis in this final rule focuses on all eligible hospitals and CAHs 
that could participate in the Medicare Promoting Interoperability 
Program and attest to the objectives and measures, and report eCQMs, 
under the Medicare Promoting Interoperability Program for the EHR 
reporting periods in CY 2023, CY 2024, and CY 2025.
    For more detailed information on our finalized policies for the 
Medicare Promoting Interoperability Program, we refer readers to 
section IX.H. of the preamble of this final rule. We are finalizing the 
following changes for eligible hospitals and CAHs that attest to CMS 
under the Medicare Promoting Interoperability Program that we expect to 
affect our collection of information burden estimates: (1) requiring 
the Electronic Prescribing Objective's Query of Prescription Drug 
Monitoring Program (PDMP) measure beginning in the CY 2023 electronic 
health record (EHR) reporting period while maintaining its associated 
points at 10 points and with the two exclusions that we proposed and an 
additional exclusion based on public comment; (2) adopting a new 
Antimicrobial Use and Resistance (AUR) Surveillance measure that will 
be required for eligible hospitals and CAHs under the Medicare 
Promoting Interoperability Program's Public Health and Clinical Data 
Exchange Objective with associated exclusions beginning with the CY 
2024 EHR reporting period, and (3) requiring eligible hospitals and 
CAHs to submit their level of active engagement in addition to 
submitting responses for the Public Health and Clinical Data Exchange 
Objective required measures and the optional measures beginning with 
the CY 2023 EHR reporting period. We are also modifying our eCQM 
reporting and submission requirements whereby we are increasing the 
total number of eCQMs to be reported from four to six eCQMs beginning 
with the CY 2024 reporting period. Details on these policies and 
associated burden changes are discussed further in this section of this 
final rule.
    We are also finalizing several policies which will not affect the 
information collection burden associated with the Medicare Promoting 
Interoperability Program. As discussed in section IX.H.10.a.(2) of the 
preamble to this final rule, we are adopting four eCQMs: (1) Severe 
Obstetric Complications eCQM with inclusion in the eCQM measure set 
beginning with the CY 2023 reporting period, followed by mandatory 
reporting beginning with the CY 2024 reporting period; (2) Cesarean 
Birth (ePC-02) eCQM with inclusion in the eCQM measure set beginning 
with the CY 2023 reporting period, followed by mandatory reporting 
beginning with the CY 2024 reporting period; (3) Hospital-Harm--Opioid-
Related Adverse Events eCQM with inclusion in the eCQM measure set 
beginning with the CY 2024 reporting period; and (4) Global 
Malnutrition Composite Score eCQM with inclusion in the eCQM measure 
set beginning with the CY 2024 reporting period. We are also: (1) 
expanding the Query of PDMP measure to include not only Schedule II 
opioids, but also Schedule III and IV drugs, beginning with the EHR 
reporting period in CY 2023; (2) adding the Enabling Exchange Under 
TEFCA measure to the Health Information Exchange Objective as an 
optional alternative to the three existing measures and updating the 
scoring methodology for the Health Information Exchange Objective 
beginning with EHR reporting period in CY 2023; (3) reducing the active 
engagement options for the Public Health and Clinical Data Exchange 
Objective from three to two options beginning with the CY 2023 EHR 
reporting period; (4) modifying the scoring methodology for the 
Medicare Promoting Interoperability Program beginning with EHR 
reporting period in CY 2023; (5) instituting public reporting of 
certain Medicare Promoting Interoperability Program data beginning with 
data from EHR reporting period in CY 2023; and (6) removing regulation 
text for the objectives and measures under 42 CFR 495.24(e) and adding 
new paragraph (f) beginning in CY 2023.
    The most recent data from the Bureau of Labor Statistics reflects a 
median hourly wage of $21.20 per hour for a medical records and health 
information technician professional.\1167\ We calculated the cost of 
overhead, including fringe benefits, at 100 percent of the median 
hourly wage, consistent with previous years. This is necessarily a 
rough adjustment, both because fringe benefits and overhead costs vary 
significantly by employer and methods of estimating these costs vary 
widely in publicly available literature. Nonetheless, we believe that 
doubling the hourly wage rate ($21.20 x 2 = $42.40) to estimate total 
cost is a reasonably accurate estimation method and is consistent with 
OMB guidance. Accordingly, we will calculate cost burden to hospitals 
using a wage plus benefits estimate of $42.40 per hour throughout the 
discussion in this section of this rule for the Medicare Promoting 
Interoperability Program.
---------------------------------------------------------------------------

    \1167\ U.S. Bureau of Labor Statistics. Occupational Outlook 
Handbook, Medical Records and Health Information Technicians. 
Accessed on January 13, 2022. Available at: https://www.bls.gov/ooh/healthcare/medical-records-and-health-information-technicians.htm.
---------------------------------------------------------------------------

    In the FY 2022 IPPS/LTCH PPS final rule (86 FR 45514), our burden 
estimates were based on an assumption of 3,300 eligible hospitals and 
CAHs. We have determined that our assumption was in error as we 
inadvertently omitted the number of CAHs in our estimate. For this 
final rule, we are updating our assumption to 3,150 eligible hospitals 
and 1,350 CAHs based on data from the CY 2020 EHR reporting period, for 
a total number of 4,500 respondents. These estimates differ from those 
of the information collection request under OMB control number 0938-
1278 as they are based on updated data from the CY 2020 EHR reporting 
period and reflect the addition of the number of CAHs. As indicated 
earlier, an updated information collection request will be submitted 
with updated numbers inclusive of CAHs. We are making this adjustment 
to reflect the total number of potential eligible hospitals and CAHs 
that could report under the Medicare Promoting Interoperability 
Program.
b. Information Collection Burden Estimate for the Electronic 
Prescribing Objective's Query of PDMP Measure Beginning with the CY 
2023 EHR Reporting Period
    In section IX.H.3.c.(2) of the preamble of this final rule, we are 
requiring the Query of PDMP measure for eligible hospitals and CAHs 
participating in the Medicare Promoting Interoperability Program 
beginning in CY 2023 and maintain the associated points at 10 points.
    In the FY 2020 IPPS/LTCH PPS final rule, we estimated the burden 
associated with reporting the Electronic Prescribing Objective and 
associated measures to be 10 minutes (84 FR 42608) coinciding with the 
finalized change to the Query of PDMP measure to require a ``yes/no'' 
response instead of a numerator/denominator calculation.

[[Page 49394]]

However, the burden associated with the Query of PDMP measure was not 
accounted for in the burden estimate of 10 minutes for the Electronic 
Prescribing Objective in the FY 2020 IPPS/LTCH PPS final rule (84 FR 
42608 through 42609), the FY 2021 IPPS/LTCH PPS final rule (85 FR 
59014), or the FY 2022 IPPS/LTCH PPS final rule (86 FR 45516). In the 
FY 2022 IPPS/LTCH PPS final rule (86 FR 45464), we finalized that the 
Query of PDMP measure will remain optional. As a result of the 
finalized policy to require the Query of PDMP measure beginning with 
the EHR reporting period in CY 2023, and considering the burden 
estimate of 30 seconds (0.5 minutes) for similar ``yes/no'' response 
measures for the Public Health and Clinical Data Exchange Objective as 
reflected in the FY 2022 IPPS/LTCH PPS final rule (86 FR 45515), we 
have updated our burden estimate for the Electronic Prescribing 
Objective to 10.5 minutes to reflect the additional burden of reporting 
the Query of PDMP measure. Therefore, we estimate a total increase in 
burden of 38 hours across all eligible hospitals and CAHs (0.5 minutes 
x 4,500 eligible hospitals and CAHs) annually at a cost of $1,590 (38 
hours x $42.40).
    In addition, in section IX.H.3.c.(3) of the preamble of this final 
rule, we are refining the Query of PDMP measure to include not only 
Schedule II opioids, but also Schedule III and IV drugs, beginning with 
EHR reporting period in CY 2023. Our policy will not yield a change in 
burden as it does not affect the requirements for data submission for 
eligible hospitals or CAHs as we continue to assume all eligible 
hospitals and CAHs will report this measure once per year.
c. Information Collection Burden Estimate for the Antimicrobial Use and 
Resistance (AUR) Surveillance Measure Beginning With the CY 2024 EHR 
Reporting Period
    In section IX.H.5.b. of the preamble of this final rule, we are 
finalizing the requirement to report a new Antimicrobial Use and 
Resistance (AUR) Surveillance measure for eligible hospitals and CAHs 
under the Medicare Promoting Interoperability Program's Public Health 
and Clinical Data Exchange Objective with a modification to delay the 
beginning of reporting until the EHR reporting period in CY 2024 
instead of the EHR reporting period in CY 2023. Eligible hospitals and 
CAHs will be required to attest to active engagement with CDC's 
National Healthcare Safety Network (NHSN) to submit AUR data and 
receive a report from NHSN indicating their successful submission of 
AUR data for the EHR reporting period.
    In the FY 2022 IPPS/LTCH PPS final rule, we finalized that eligible 
hospitals and CAHs are required to report four measures for the Public 
Health and Clinical Data Exchange Objective with a total estimated 
burden of 2 minutes annually (30 seconds x 4 measures) (86 FR 45516). 
Therefore, we estimate the burden associated with this new measure to 
be 30 seconds, or 0.5 minutes, per eligible hospital or CAH annually. 
We estimate a total increase in burden of 38 hours across all eligible 
hospitals and CAHs (0.5 minutes x 4,500 eligible hospitals and CAHs) 
annually at a cost of $1,611 (38 hours x $42.40).
    While the burden associated with attesting to active engagement for 
the AUR Surveillance measure will be accounted for under OMB control 
number 0938-1278 (expiration date July 31, 2022), the burden associated 
with the actual submission of AUR data to NHSN is accounted for under 
OMB control number 0920-0666 (expiration date January 31, 2025).
d. Information Collection Burden Estimate for the Policy To Require 
Eligible Hospitals and CAHs To Submit Their Level of Active Engagement 
for the Public Health and Clinical Data Exchange Objective
    In section IX.H.5.c.(3) of the preamble of this final rule, we are 
requiring eligible hospitals and CAHs to submit their level of 
engagement for the measures under the Public Health and Clinical Data 
Exchange Objective, either Pre-production and Validation or Validated 
Data Production. This requirement is in addition to submitting 
responses for the required measures and the optional measures, if 
applicable.
    The burden associated with this requirement is similar to the 
burden associated with the attestation that eligible hospitals and CAHs 
must complete for the four previously finalized measures under this 
objective and the finalized AUR Surveillance measure. Therefore, we 
estimate the burden associated with this new requirement to be 30 
seconds, or 0.5 minutes, per eligible hospital or CAH annually. We 
estimate a total increase in burden of 38 hours across all eligible 
hospitals and CAHs (0.5 minutes/hospital x 4,500 eligible hospitals and 
CAHs) annually at a cost of $1,611 (38 hours x $42.40).
    In addition, in section IX.H.c.(2) of the preamble of this final 
rule, we are reducing the active engagement options for the Public 
Health and Clinical Data Exchange Objective from three to two options 
beginning with EHR reporting period in CY 2023. We are delaying the 
requirement that eligible hospitals and CAHs may spend only one EHR 
reporting period at the pre-production and validation phase until the 
EHR reporting period in CY 2024. Our policy will not yield a change in 
burden as it does not affect the requirements for data submission for 
eligible hospitals or CAHs but instead will motivate health IT vendors 
to implement these capabilities in their products and encourage 
healthcare organizations to engage in these reporting activities.
e. Information Collection Burden Estimate for the Modification of the 
eCQM Reporting and Submission Requirements Beginning With the CY 2024 
Reporting Period
    In section IX.H.10.b of the preamble of this final rule, we are 
modifying our eCQM reporting and submission requirements whereby we are 
increasing the total number of eCQMs to be reported from four to six 
eCQMs beginning with the CY 2024 reporting period. In addition, the six 
eCQMs must be comprised of: (1) Three self-selected eCQMs; (2) the Safe 
Use of Opioids--Concurrent Prescribing eCQM; (3) the finalized Severe 
Obstetric Complications eCQM; and (4) the finalized Cesarean Birth 
eCQM, for a total of six eCQMs.
    We previously finalized in the FY 2021 IPPS/LTCH PPS final rule 
that, for the CY 2023 reporting period, eligible hospitals and CAHs are 
required to submit data for three self-selected eCQMs each year and the 
Safe Use of Opioids-Concurrent Prescribing eCQM for a total of four 
eCQMs (85 FR 58975). We also finalized in the FY 2021 IPPS/LTCH PPS 
final rule to require eligible hospitals and CAHs to submit four 
quarters of eCQM data beginning in the CY 2023 reporting period (85 FR 
58975). We continue to estimate the information collection burden 
associated with the eCQM reporting and submission requirements to be 10 
minutes per measure per quarter. As discussed in the section IX.E.4.f. 
of the preamble of this final rule, we already account for the burden 
associated with the reporting of eCQM measures for eligible hospitals 
as part of the Hospital Inpatient Quality Reporting Program, therefore 
the burden for the 3,150 eligible hospitals is included there. For the 
submission of six eCQM measures for CAHs, we estimate a total of 1 hour 
(0.167 hours/eCQM x 6 eCQMs) per CAH per quarter. We estimate a total 
burden of 1,350 hours across all CAHs (1 hour x 1,350 CAHs) for each 
quarter of eCQM data or 5,400 hours annually (1,350 hours x 4

[[Page 49395]]

quarters) at a cost of $228,960 (5,400 hours x $42.40/).
f. Information Collection Burden Estimate for the Adoption of Two eCQMs 
Beginning With the CY 2023 Reporting Period and Two eCQMs Beginning 
With the CY 2024 Reporting Period
    In section IX.H.10.a. of the preamble of this final rule, we are 
adopting four eCQMs: (1) Severe Obstetric Complications eCQM beginning 
with the CY 2023 reporting period, followed by mandatory reporting 
beginning with the CY 2024 reporting period; (2) Cesarean Birth (ePC-
02) eCQM beginning with the CY 2023 reporting period, followed by 
mandatory reporting beginning with the CY 2024 reporting period; (3) 
Hospital-Harm--Opioid-Related Adverse Events eCQM beginning with the CY 
2024 reporting period; and (4) Global Malnutrition Composite Score eCQM 
beginning with the CY 2024 reporting period.
    The addition of these four eCQMs do not affect the information 
collection burden of submitting eCQMs under the Medicare Promoting 
Interoperability Program beyond the burden described in section 
IX.B.4.f. of the preamble of this final rule. Current Medicare 
Promoting Interoperability Program policy requires hospitals to submit 
data for three self-selected eCQMs each year and the Safe Use of 
Opioids-Concurrent Prescribing eCQM for a total of four eCQMs (85 FR 
58975). In other words, although these new eCQMs are being added to the 
eCQM measure set, hospitals are not required to report more than a 
total of six eCQMs as discussed in section IX.10. of the preamble of 
this final rule.
    With respect to any costs unrelated to data submission, we refer 
readers to section I.K. of Appendix A of this final rule.
g. Information Collection Burden Estimate To Add the Enabling Exchange 
Under TEFCA Measure to the Health Information Exchange Objective 
Beginning With the CY 2023 EHR Reporting Period
    In section IX.H.4.c. of the preamble of this final rule, we are 
adding the Enabling Exchange Under TEFCA measure to the Health 
Information Exchange Objective as an optional alternative to the three 
existing measures (Support Electronic Referral Loops by Sending Health 
Information measure and the Support Electronic Referral Loops by 
Receiving and Reconciling Health Information measure, or the HIE Bi-
Directional Exchange measure) and updating the scoring methodology for 
the Health Information Exchange Objective beginning with EHR reporting 
period in the CY 2023. Our policy does not yield a change in burden as 
eligible hospitals and CAHs may choose to report the two Support 
Electronic Referral Loop measures, or may choose to report the HIE Bi-
Directional Exchange measure, or may choose to report the new Enabling 
Exchange Under TEFCA measure.
h. Information Collection Burden Estimate To Modify the Scoring 
Methodology for the Medicare Promoting Interoperability Program 
Beginning With the CY 2023 EHR Reporting Period
    In section IX.H.6. of the preamble of this final rule, we are 
finalizing the following changes to the scoring methodology:
     Increasing the points allocated to the Public Health and 
Clinical Data Exchange Objective from 10 points to 25 points,
     Increasing the points allocated to the Electronic 
Prescribing Objective from 10 points to 20 points,
     Decreasing the points allocated to the Health Information 
Exchange Objective from 40 points to 30 points, and
     Decreasing the points allocated to the Provide to Patient 
Exchange Objective from 40 points to 25 points.
    Our policy does not yield a change in burden as it does not affect 
the requirements for data submission for eligible hospitals or CAHs but 
only changes the scoring methodology.
i. Information Collection Burden Estimate To Institute Public Reporting 
of Medicare Promoting Interoperability Program Data Beginning With Data 
From the CY 2023 EHR Reporting Period
    In section IX.H.7. of the preamble of this final rule, we are 
finalizing to publicly report certain Medicare Promoting 
Interoperability Program data submitted by eligible hospitals and CAHs 
beginning with EHR reporting period in CY 2023. Specifically, we are 
finalizing that we will publish eligible hospitals' and CAHs' actual 
scores and their CMS EHR certification ID, beginning with data 
submitted for the CY 2023 EHR reporting period. Our policy does not 
yield a change in burden as it does not affect the requirements for 
data submission for eligible hospitals or CAHs.
j. Information Collection Burden Estimate for Modifications to 
Regulatory Text
    In section IX.H.8. of the preamble of this final rule, we are 
removing references to objectives and measures and making modifications 
to regulatory text at 42 CFR 495.24 beginning in CY 2023. Our policy 
does not yield a change in burden as it does not affect the 
requirements for data submission for eligible hospitals or CAHs since 
the changes only modify regulatory text.
k. Summary of Estimates Used To Calculate the Collection of Information 
Burden
    In summary, under OMB control number 0938-1278 (expiration date 
July 31, 2022), we estimate that the policies in this final rule result 
in a total increase in burden of 5,513 hours through the CY 2024 EHR 
reporting period. The total cost increase related to this information 
collection is approximately $233,730 (5,513 hours x $42.40) across 
4,500 eligible hospitals and CAHs. The tables summarize the total 
burden changes for the CY 2023 and for CY 2024 EHR reporting periods 
compared to our currently approved information collection burden 
estimates (the table for the CY 2024 EHR reporting period reflects the 
total burden change associated with all policies being finalized).
    In the FY 2022 IPPS/LTCH PPS final rule, we estimated each eligible 
hospital and CAH would require 6.5 hours annually to participate in the 
Medicare Promoting Interoperability Program (86 FR 45517). As a result 
of the policies in this final rule, we estimate the new total annual 
burden to be 6.6 hours per eligible hospital and CAH as well as an 
additional 4 hours annually for CAHs to report eCQMs. Therefore, we 
estimate the adjustment in the number of eligible hospitals and CAHs 
from 3,300 to 4,500 results in an increase of approximately +13,290 
hours ((6.6 hours x -150 eligible hospitals) + (10.6 hours x 1,350 
CAHs)) at a cost of +$563,496 (+13,290 hours x $42.40).
    We will submit the revised information collection estimates to OMB 
for approval under OMB control number 0938-1278 (expiration date July 
31, 2022).

[[Page 49396]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.208


[[Page 49397]]


[GRAPHIC] [TIFF OMITTED] TR10AU22.209


[[Page 49398]]


    We did not receive comments regarding the ICRs for the Medicare 
Promoting Interoperability Program.
10. ICRs for the Codification of the Costs Incurred for Qualified and 
Non-Qualified Deferred Compensation Plans
    As discussed in section X.A. of the preamble of this final rule, we 
are finalizing proposed codifications and clarifications for certain 
policies relating to Deferred Compensation. This finalized provision 
will not change our current policies for allowable Deferred 
Compensation costs associated with Qualified and Non-Qualified Deferred 
Compensation Plans that are included in Medicare cost reports. The 
documentation requirements will require that a provider of services 
must maintain and make available to its contractor and CMS, 
documentation to substantiate the costs incurred for the plans included 
in its Medicare cost report. These documentation requirements are based 
on the recordkeeping requirements at current Sec.  413.20, which 
require providers of services to maintain sufficient financial records 
and statistical data for proper determination of costs payable under 
Medicare. The OMB control number for this information collection 
request is 0938-0050, which expired on March 31, 2022. A 30-day Federal 
Register notice published on June 22, 2022 (87 FR 37338) for the 
reinstatement of the information collection request. The comment period 
closed July 22, 2022.
    We did not receive comments regarding the ICRs for the codification 
of the costs incurred for qualified and non-qualified deferred 
compensation plans.
11. ICRs for Condition of Participation (CoP) Requirements for 
Hospitals and CAHs To Continue Reporting Data for COVID-19 and 
Influenza After the PHE Ends as Determined by the Secretary
a. Continued COVID-19 and Seasonal Influenza Reporting
    We are finalizing proposed revisions the regulations by adding 
provisions to the CoPs (Sec.  482.42 for hospitals and Sec.  485.640 
for CAHs) requiring hospitals and CAHs, after the conclusion of the 
current COVID-19 PHE, to continue COVID-19 and seasonal influenza-
related reporting. The revisions will continue to apply upon conclusion 
of the COVID-19 Public Health Emergency (PHE) and would continue until 
April 30, 2024, unless the Secretary establishes an earlier ending 
date. The data elements align closely with those COVID-19 reporting 
requirements for long-term care (LTC) facilities that were finalized on 
November 9, 2021 (86 FR 62421) and are representative of the guidance 
provided to hospitals and CAHs for reporting. Therefore, we do not 
expect that these categories of data elements will require hospitals 
and CAHs to report any information beyond that which they have already 
been reporting. Furthermore, similar to the requirements for LTC 
facilities, this provision will also allow for the scope and frequency 
of data collection to be reduced and limited responsive to the evolving 
clinical and epidemiological circumstances.
    Specifically, as discussed in section XX.B.2 of the preamble of 
this final rule, we have re-evaluated the proposed data elements in 
consideration of the feedback shared by commenters and the evolving 
state of the current PHE and are modifying our proposal to remove the 
following from the list of required data categories to report:

 Suspected COVID-19 infections among patients and staff
 Confirmed COVID-19 and influenza infections among staff
 COVID-19 and influenza deaths among staff
 Confirmed co-morbid influenza and COVID-19 infections among 
staff

    Although data pertaining to suspected cases were valuable 
throughout the COVID-19 PHE, particularly in instances when testing 
supplies were limited and cases were often identified based on clinical 
signs and symptoms, this information is less meaningful now that 
testing supplies are readily available to confirm the presence of 
infection. Thus, we do not believe suspected COVID-19 infection data 
would be necessary to collect from hospitals and CAHs once the PHE 
declaration ends, and therefore, we removed this data category.
    The data categories for staff (suspected infections among staff; 
confirmed COVID-19, influenza, and co-morbid infections among staff; 
COVID-19 and influenza deaths among staff) have not been among the 
information that hospitals and CAHs were required to report throughout 
the COVID-19 PHE. Hospitals and CAHs were required to report suspected, 
confirmed, and comorbid infections, as well as deaths, for patients 
only. In the proposed rule, CMS did not intend to extend these data 
categories to include staff. The inclusion of staff in the proposed 
rule for these data categories was a technical error; therefore, we 
removed these data categories.While beneficial during an active PHE and 
the specific circumstances of the COVID-19 PHE, we believe the above 
data categories are not necessary to provide the most valuable 
information during a post-PHE state for continued monitoring and as 
such we are removing these data categories to be responsive to 
commenter concerns regarding increased burden on facilities and staff, 
while also attempting to provide quality care for patients.
    The data categories that we are finalizing in this rule that 
hospitals and CAHs will be required to report relevant to COVID-19, to 
the extent as determined by the Secretary, are as follows: Confirmed 
infections among patients; Total deaths among patients; Personal 
protective equipment and testing supplies; Ventilator use, capacity, 
and supplies; Total bed and intensive care unit bed census and 
capacity; Vaccine administration data of patients and staff; and 
Relevant therapeutic inventories or usage, or both. The data categories 
that we are finalized in this rule that hospitals and CAHs will be 
required to report relevant to influenza, to the extend as determined 
by the Secretary, are as follows: Confirmed infections among patients; 
Total deaths among patients; and Confirmed co-morbid influenza and 
COVID-19 infections among patients. We believe these data will offer 
the most valuable information during a post-PHE state by continuing to 
capture critical information on COVID-19 and seasonal influenza for 
ongoing surveillance and to inform any potential action to protect 
patient health and safety. As previously discussed, these data will 
enable the federal government to monitor the ability of facilities to 
provide safe care for patients by determining the number of COVID-19 
and influenza infections being treated by facilities; the quantity of 
resources available to facilities and the volume of resources they are 
using; and facilities' continued capacity to provide safe patient care. 
In addition, as done throughout the COVID-19 pandemic, local, state, 
and federal authorities will continue to use these data to identify 
possible resurgence in cases and outbreaks, for resource allocation 
purposes, and to update guidance pertaining to the safe provision of 
patient care.
    As indicated in the proposal, we do not expect continued daily 
reporting for COVID-19 or influenza outside of a declared PHE. 
Moreover, the rule allows for the scope of data categories and 
frequency of data collection and reporting to be reduced and limited, 
as determined by the Secretary, responsive to evolving clinical and 
epidemiology circumstances. This approach to reducing the proposed set 
of required data categories will provide a path towards winding down 
the overall

[[Page 49399]]

reporting of COVID-19-related data between the end of the current PHE 
and April 2024 when these requirements will sunset. These requirements 
will not be implemented and enforced until the current COVID-19 PHE 
declaration concludes, and CMS will issue guidance indicating such a 
transition. As discussed previously, we expect the method of 
notification to follow a model similar to that which we used to inform 
regulated entities at the beginning of the COVID-19 PHE (see QSO-21-03-
Hospitals/CAHs at https://www.cms.gov/files/document/qso-21-03-hospitalscahs.pdf-0). The data that hospitals and CAHs will be required 
to report are consistent with the information they have already been 
reporting throughout the COVID-19 PHE (OMB control numbers 0938-0328 
for hospitals and 0938-1043 for CAHs).
    For purposes of burden estimates, we do not differentiate among 
hospitals and CAHs as they all will complete the same data collection.
    For the estimated costs contained in the analysis that follows, we 
used data from the U.S. Bureau of Labor Statistics (BLS) to determine 
the mean hourly wage for the staff member responsible for reporting the 
required information for a hospital (or a CAH).\1168\ Based on our 
experience with hospitals and CAHs and the current COVID-19 and related 
reporting requirements, we believe that this will primarily be the 
responsibility of a registered nurse and we have used this position in 
this analysis at an average hourly salary of $39.27. For the total 
hourly cost, we doubled the mean hourly wage for a 100 percent increase 
to cover overhead and fringe benefits, according to standard HHS 
estimating procedures. If the total cost after doubling resulted in 
0.50 or more, the cost was rounded up to the next dollar. If it was 
0.49 or below, the total cost was rounded down to the next dollar. 
Therefore, we estimated the total hourly cost for a registered nurse to 
perform these duties would be $79.
---------------------------------------------------------------------------

    \1168\ BLS. May 2020 National Occupational Employment and Wage 
Estimates United States. United States Department of Labor. Accessed 
at https://www.bls.gov/oes/current/oes_nat.htm. Accessed on August 
25, 2021.
---------------------------------------------------------------------------

    According to the most recent COVID-19 hospital reporting guidance 
(available at https://www.hhs.gov/sites/default/files/covid-19-faqs-hospitals-hospital-laboratory-acute-care-facility-data-reporting.pdf), 
hospitals are reporting COVID-19 and influenza-related data on a daily 
basis, with backdating permitted for weekends and holidays, except 
psychiatric and rehabilitation hospitals who report weekly. Some data 
element reporting fields are inactive for data collection, and 
therefore, hospitals can optionally report data for these fields. The 
inactive fields and active fields together reflect what is listed in 
this final rule for continued COVID-19 and influenza-related reporting 
as well as future reporting in the event of a declared PHE, which we 
discuss next. We do not expect, nor did we propose, continued daily 
reporting for COVID-19 or influenza outside of a declared PHE. If we 
were to assume a weekly reporting frequency, we would anticipate that 
there are reduced cases and fewer data elements (with no line level 
patient data) being reported. Based on these assumptions, we estimated 
that total annual burden hours for all participating hospitals and CAHs 
to comply with these requirements would be 483,600 hours based on 
weekly reporting of the required information by approximately 6,200 
hospitals and CAHs x 52 weeks per year and at an average weekly 
response time of 1.5 hours for a registered nurse with an average 
hourly salary of $79. Therefore, the estimate for total annual costs 
for all hospitals and CAHs to comply with the required reporting 
provisions weekly would be $38,204,400 or approximately $6,162 per 
facility annually. We acknowledge that the data elements and reporting 
frequency could increase or decrease over the next 2 years, and those 
changes would impact this burden estimate.
    We note that this estimate is assumed to be a 1-day snapshot of 
reporting information as opposed to a cumulative weekly report 
accounting for information based on each day of that week. If we 
assumed a cumulative weekly account, we can assume reduced burden 
related to the actual reporting time, but anticipate that the estimate 
would be slightly higher to account for the need to track closely to 
daily reporting. We also acknowledged that respondents may have to 
track and invest in infrastructure in order to timely and accurately 
report on the specified frequency. Thus, respondents may face ongoing 
burdens associated with this collection even in the case of reduced 
frequency of submissions. We solicited comment on this potentiality.
    Furthermore, we note that this estimate likely overestimates the 
costs associated with reporting because it assumes that all hospitals 
and CAHs will report manually. Efforts are underway to automate 
hospital and CAH reporting that have the potential to significantly 
decrease reporting burden and improve reliability. Our preliminary 
estimates for these reporting activities (OMB control numbers 0938-0328 
for hospitals and 0938-1043 for CAHs) can be found in the tables that 
follow.
[GRAPHIC] [TIFF OMITTED] TR10AU22.210


[[Page 49400]]


[GRAPHIC] [TIFF OMITTED] TR10AU22.211

b. Future Reporting in the Event of a PHE Declaration
    In addition, we proposed to establish reporting requirements for 
future PHEs related to infectious diseases by requiring hospitals and 
CAHs to electronically report information on Acute Respiratory Illness 
(including, but not limited to, Seasonal Influenza Virus, Influenza-
like Illness, and Severe Acute Respiratory Infection), SARS-CoV-2/
COVID-19, and other viral and bacterial pathogens or infectious 
diseases of pandemic or epidemic potential only when the Secretary has 
declared a PHE directly related to such specific pathogens and 
infectious diseases. Specifically, we proposed that when the Secretary 
has declared a PHE, hospitals and CAHs would be required to report 
specific data elements to the CDC's National Health Safety Network 
(NHSN), or other CDC-supported surveillance systems, as determined by 
the Secretary.
    We also proposed to require that a hospital (or a CAH) would be 
required to report each applicable infection (confirmed and suspected) 
and the applicable vaccination data in a format that provides person-
level information, to include medical record identifier, race, 
ethnicity, age, sex, residential county and zip code, and relevant 
comorbidities for affected patients, unless the Secretary specifies an 
alternative format by which the hospital (or CAH) would be required to 
report these data elements. Lastly, we proposed that a hospital (or a 
CAH) would provide the information specified on a daily basis, unless 
the Secretary specifies a lesser frequency, to the Centers for Disease 
Control and Prevention's National Healthcare Safety Network (NHSN) or 
other CDC-supported surveillance systems as determined by the 
Secretary. We noted that in this final rule, we have withdrawn this 
proposal to establish requirements for hospitals and CAHs to report 
certain data in the event of a future PHE declaration.
    We solicited comment on the burden associated with these proposed 
requirements given the intended flexibility provided in reducing or 
limiting the scope and frequency of reporting based on the state of the 
PHE and ongoing circumstances, requested comment on the potential 
burden associated with the proposed reporting requirements as they 
might relate to any differences in the public health response to one 
specific pathogen or infectious disease versus another that would be 
directly related to the declared PHE, and requested public comments 
addressing burden estimates (and the potential differences in those 
estimates) for variations in the required reporting response for a 
local PHE versus a regional PHE versus a national PHE that might be 
declared by the Secretary based on the specific circumstances at the 
time of the declaration.
    Comment: A few commenters indicated that our cost estimate for 
continued COVID-19-related data reporting was inaccurate and 
underestimated. The commenters stated that collecting and reporting 
these data involves multiple staff from nursing, human resources, 
medical staff, infection prevention and control, laboratory, 
respiratory, materials, pharmacy, and information technology 
departments, and these staff have had to repeatedly adjust how they 
collect and report data in response to changes in guidance throughout 
the COVID-19 PHE while also performing their other duties. Likewise, a 
few commenters indicated that data collection and reporting was solely 
performed by infection prevention and control staff, while and other 
commenters stated that quality staff solely compiled and reported the 
data. One commenter also noted that lost revenue due to nursing 
staffing having to devote time and resources to non-direct care 
activities, such as manual data collection/reporting, and the current 
staffing shortages, should also be considered in the burden estimate 
acknowledging that this is an opportunity cost that is difficult to 
quantify.
    Response: We agree that data collection and reporting procedures, 
including but not limited to the number and type of staff involved (job 
title, direct care or non-direct care) vary among hospitals and CAHs. 
After reviewing these comments and other feedback we received, we also 
believe the method of collecting the data (automated or manual) varies 
among hospitals and CAHs. As discussed in detail in section X.B. of 
this final rule, we modified our proposal to decrease the amount of 
data categories required for continued COVID-19-related reporting 
beginning at the conclusion of the current PHE. Specifically, we are 
finalizing the proposed revisions at Sec.  482.42(e) and (f) and Sec.  
485.640(d) and (e) for hospitals and CAHs, respectively, with the 
following information no longer required to be reported: (1) Suspected 
COVID-19 infections among patients and staff, (2) Confirmed COVID-19 
and influenza infections among staff, (3) COVID-19 and influenza deaths 
among staff, and (4) Confirmed co-morbid influenza and COVID-19 
infections among staff. Given that this final rule decreases the scope 
of data categories and that the data collecting and reporting 
procedures among hospitals and CAHs varies, we believe the estimate 
reflects an accurate average burden.
    Comment: With regard to reporting frequency and the burden 
associated, commenters provided various suggestions for the appropriate 
frequency of reporting including weekly, Mondays through Fridays only, 
while excluding holidays, and Mondays, Wednesdays, and Fridays only. 
One commenter noted that even if reporting were reduced from a daily 
requirement to once per week the burden would still be far greater than 
1.5 hours per week. However, other commenters emphasized that, while 
more burdensome, standardized data reporting on a daily basis is 
necessary to detect trends and outbreaks in a timely manner and 
improves accuracy of real-time models developed to forecast spread of 
infectious diseases. Some commenters also noted the proposal as an 
unfunded mandate and indicated that CMS payment rates do not keep up 
with inflation rates.
    Response: As noted in the proposed rule, we do not expect, nor did 
we propose, continued daily reporting for COVID-19 or seasonal 
influenza data outside of a declared PHE (87 FR 28642). We appreciate 
the suggestions from commenters and will consider them as decisions are 
made over the

[[Page 49401]]

next two years until this requirement sunsets in April 2024. 
Ultimately, the scope and frequency of reporting will be informed by 
the ongoing circumstances and evolving state of the public health 
response efforts.
13. Summary of All Burden in This Final Rule
    The following chart reflects the total burden and associated costs 
for the ICRs presented in this section of this final rule.

[[Page 49402]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.212

    Chiquita Brooks-LaSure, Administrator of the Centers for Medicare & 
Medicaid Services, approved this document on July 22, 2022.

[[Page 49403]]

List of Subjects

42 CFR Part 412

    Administrative practice and procedure, Health facilities, Medicare, 
Puerto Rico, Reporting and recordkeeping requirements.

42 CFR Part 413

    Diseases, Health facilities, Medicare, Puerto Rico, Reporting and 
recordkeeping requirements.

42 CFR Part 482

    Grant programs--health, Hospitals, Medicaid, Medicare, Reporting 
and recordkeeping requirements.

42 CFR Part 485

    Grant programs--health, Health facilities, Medicaid, Privacy, 
Reporting and recordkeeping requirements.

42 CFR Part 495

    Administrative practice and procedure, Health facilities, Health 
maintenance organizations (HMO), Health professions, Health records, 
Medicaid, Medicare, Penalties, Privacy, Reporting and recordkeeping 
requirements.

    For the reasons set forth in the preamble, the Centers for Medicare 
and Medicaid Services amends 42 CFR chapter IV as set forth below:

PART 412--PROSPECTIVE PAYMENT SYSTEMS FOR INPATIENT HOSPITAL 
SERVICES

0
1. The authority citation for part 412 continues to read as follows:

    Authority:  42 U.S.C. 1302 and 1395hh.

0
2. Section 412.24 is amended by adding paragraph (d)(3)(iii) to read as 
follows:


Sec.  412.24  Requirements under the PPS-Exempt Cancer Hospital Quality 
Reporting (PCHQR) Program.

* * * * *
    (d) * * *
    (3) * * *
    (iii) Patient safety exception. Upon a determination by CMS that 
the continued requirement for PCHs to submit data on a measure raises 
specific patient safety concerns, CMS may elect to immediately remove 
the measure from the PCHQR measure set. CMS will, upon removal of the 
measure--
    (A) Provide notice to PCHs and the public at the time CMS removes 
the measure, along with a statement of the specific patient safety 
concerns that would be raised if PCHs continued to submit data on the 
measure; and
    (B) Provide notice of the removal in the Federal Register.
* * * * *

0
3. Section 412.60 is amended by revising paragraph (b) to read as 
follows:


Sec.  412.60  DRG classification and weighting factors.

* * * * *
    (b) DRG weighting factors. CMS assigns, for each DRG, an 
appropriate weighting factor that reflects the estimated relative cost 
of hospital resources used with respect to discharges classified within 
that group compared to discharges classified within other groups, 
subject to a maximum ten percent reduction to the weighting factor for 
a DRG as compared to the weighting factor for the same DRG for the 
prior fiscal year.
* * * * *

0
4. Section 412.64 is amended by adding paragraph (h)(7) to read as 
follows:


Sec.  412.64  Federal rates for inpatient operating costs for Federal 
fiscal year 2005 and subsequent fiscal years.

* * * * *
    (h) * * *
    (7) Beginning with fiscal year 2023, if CMS determines that a 
hospital's wage index value for a fiscal year would decrease by more 
than 5 percent as compared to the hospital's wage index value for the 
prior fiscal year, CMS limits the decrease to 5 percent for the fiscal 
year.
* * * * *

0
5. Section 412.103 is amended by adding paragraph (a)(8) to read as 
follows:


Sec.  412.103  Special treatment: Hospitals located in urban areas and 
that apply for reclassification as rural.

    (a) * * *
    (8) For a hospital with a main campus and one or more remote 
locations under a single provider agreement where services are provided 
and billed under the inpatient hospital prospective payment system and 
that meets the provider-based criteria at Sec.  413.65 of this chapter 
as a main campus and a remote location of a hospital, approved rural 
reclassification status applies to the main campus and any remote 
location located in an urban area (as defined in Sec.  412.64(b) and 
including a main campus or any remote location deemed urban under 
section 1886(d)(8)(B) of the Act).
* * * * *

0
6. Section 412.106 is amended by--
0
a. Revising paragraph (g)(1)(ii);
0
b. In paragraph (g)(1)(iii)(C)(8), removing the phrase ``For each 
subsequent fiscal year,'' and adding in its place the phrase ``For 
fiscal year 2022,'';
0
c. Adding paragraphs (g)(1)(iii)(C)(10) and (11);
0
d. Redesignating paragraph (h) as paragraph (i); and
0
e. Adding a new paragraph (h).
    The revisions and additions read as follows:


Sec.  412.106  Special treatment: Hospitals that serve a 
disproportionate share of low-income patients.

* * * * *
    (g) * * *
    (1) * * *
    (ii) Factor 2. (A) For each of fiscal years 2014, 2015, 2016, and 
2017, a factor equal to 1 minus the percent change in the percent of 
individuals under the age of 65 who are uninsured (and subtracting from 
the factor 0.1 percentage point for fiscal year 2014 and 0.2 percentage 
point for each of fiscal years 2015, 2016, and 2017), as determined by 
comparing--
    (1) 18 percent, the percent of such individuals who are uninsured 
in 2013, based on the March 20, 2010, estimate of the ``Insured Share 
of the Nonelderly Population Including All Residents'' by the 
Congressional Budget Office.
    (2) The percent of such individuals who are uninsured in the 
applicable fiscal year, based on the most recent estimate of the 
``Insured Share of the Nonelderly Population Including All Residents'' 
by the Congressional Budget Office available at the time of development 
of the annual final rule for the hospital inpatient prospective payment 
system.
    (B) For FY 2018 and subsequent fiscal years, a factor equal to 1 
minus the percent change in the percent of individuals who are 
uninsured (and subtracting from the factor 0.2 percentage point for 
each of fiscal years 2018 and 2019), as determined by comparing the 
percent of individuals who are uninsured in--
    (1) 2013 (as estimated by the Secretary, based on data from the 
Census Bureau or other sources the Secretary determines appropriate, 
and certified by the Chief Actuary of the CMS); and
    (2) The most recent period for which data is available (as so 
estimated and certified).
    (iii) * * *
    (C) * * *
    (10) For fiscal year 2023, for all eligible hospitals, CMS will 
base its estimates of the amount of hospital uncompensated care on data 
on uncompensated care costs, defined as charity care costs plus non-
Medicare and non-reimbursable Medicare bad debt costs from cost reports 
from the two most recent cost reporting years for

[[Page 49404]]

which audits have been conducted. If a hospital is a new hospital (that 
is, a hospital that began participation in the Medicare program after 
the two most recent cost reporting years for which audits have been 
conducted) or if the hospital is treated as a new hospital for purposes 
of Factor 3, the Medicare administrative contractor (MAC) will 
determine Factor 3 as the ratio of the hospital's uncompensated care 
costs from its FY 2023 cost report to the sum of uncompensated care 
costs for all DSH-eligible hospitals as estimated by CMS from the most 
recent cost reporting year for which audits have been conducted.
    (11) For fiscal year 2024 and subsequent fiscal years, for all 
eligible hospitals, CMS will base its estimates of the amount of 
hospital uncompensated care on data on uncompensated care costs, 
defined as charity care costs plus non-Medicare and non-reimbursable 
Medicare bad debt costs from cost reports from the three most recent 
cost reporting years for which audits have been conducted. If a 
hospital is a new hospital (that is, a hospital that began 
participation in the Medicare program after the three most recent cost 
reporting years for which audits have been conducted) or if the 
hospital is treated as a new hospital for purposes of Factor 3, the 
Medicare administrative contractor (MAC) will determine Factor 3 as the 
ratio of the hospital's uncompensated care costs from its cost report 
for the applicable fiscal year to the sum of uncompensated care costs 
for all disproportionate share hospital (DSH)-eligible hospitals as 
estimated by CMS from the most recent cost reporting year for which 
audits have been conducted.
    (h) Supplemental payment for Indian Health Service and Tribal 
hospitals and Puerto Rico hospitals. (1) For fiscal year 2023 and each 
subsequent fiscal year, Indian Health Service and Tribal Hospitals and 
Puerto Rico hospitals that qualify for an additional payment for 
uncompensated care under paragraph (g) of this section for the 
applicable fiscal year may also qualify to receive a supplemental 
payment.
    (2) Indian Health Service and Tribal Hospitals and Puerto Rico 
hospitals that do not have a Factor 3 amount for fiscal year 2022 
determined under paragraph (g)(1)(iii)(C)(9) of this section are not 
eligible to receive a supplemental payment under this paragraph (h).
    (3) The amount of the supplemental payment for a fiscal year is 
determined as the difference between the following:
    (i) A base year amount defined as the FY 2022 uncompensated care 
payment determined for the hospital, in accordance with paragraph 
(g)(1) of this section, adjusted by 1 plus the percent change in the 
aggregate amount of uncompensated care payments as estimated by CMS in 
accordance with paragraphs (g)(1)(i) and (ii) of this section between 
fiscal year 2022 and the applicable fiscal year. If the hospital did 
not qualify for an additional payment for uncompensated care under 
paragraph (g) of this section for fiscal year 2022, CMS uses the Factor 
3 determined for the hospital under paragraph (g)(1)(iii)(C)(9) of this 
section to estimate the amount of the additional payment for 
uncompensated care that the hospital would have received in fiscal year 
2022 if the hospital had qualified for an additional payment for 
uncompensated care under paragraph (g)(1) of this section for that 
fiscal year.
    (ii) The additional payment for uncompensated care determined for 
the hospital for the applicable fiscal year, in accordance with 
paragraph (g)(1) of this section.
    (4) If the base year amount under paragraph (h)(3)(i) of this 
section is equal to or lower than the additional payment for 
uncompensated care determined for the hospital for the applicable 
fiscal year in accordance with paragraph (g)(1) of this section, the 
hospital will not receive a supplemental payment under paragraph (h) of 
this section for that fiscal year.
* * * * *


Sec.  412.140  [Amended]

0
7. Section 412.140 is amended in paragraph (d)(2)(ii) by removing the 
phrase ``at least 75 percent'' and adding in its place the phrase ``100 
percent''.

0
8. Section 412.168 is amended by--
0
a. Revising the section heading;
0
b. In paragraph (a), removing the phrase ``for the fiscal year 2022'' 
and adding in its place ``for each of fiscal years 2022 and 2023''; and
0
c. By adding paragraphs (g) through (k).
    The revision and additions read as follows:


Sec.  412.168  Special rules for FY 2022 and FY 2023.

* * * * *
    (g) CMS calculates a measure rate for all measures selected under 
Sec.  412.164(a) for fiscal year 2023 but only applies Sec.  412.165(a) 
to the measures included in the Clinical Outcomes Domain and the 
Efficiency and Cost Reduction Domain for that fiscal year, which are 
the following:
    (1) Hospital 30-Day, All-Cause, Risk-Standardized Mortality Rate 
Following Acute Myocardial Infarction (AMI) Hospitalization (MORT-30-
AMI).
    (2) Hospital 30-Day, All-Cause, Risk-Standardized Mortality Rate 
Following Heart Failure (HF) Hospitalization (MORT-30-HF).
    (3) Hospital 30-Day, All-Cause, Risk-Standardized Mortality Rate 
Following Pneumonia Hospitalization (MORT-30-PN (updated cohort)).
    (4) Hospital 30-Day, All-Cause, Risk-Standardized Mortality Rate 
Following Chronic Obstructive Pulmonary Disease (COPD) Hospitalization 
(MORT-30-COPD).
    (5) Hospital 30-Day, All-Cause, Risk-Standardized Mortality Rate 
Following Coronary Artery Bypass Graft (CABG) Surgery (MORT-30-CABG).
    (6) Hospital-Level Risk-Standardized Complication Rate Following 
Elective Primary Total Hip Arthroplasty (THA) and/or Total Knee 
Arthroplasty (TKA) (COMP-HIP-KNEE).
    (7) Medicare Spending Per Beneficiary (MSPB)--Hospital.
    (h) CMS calculates--
    (1) A Clinical Outcomes Domain score for fiscal year 2023 for 
hospitals that report the minimum number of cases and measures with 
respect to the measures described in paragraphs (g)(1) through (6) of 
this section; and
    (2) An Efficiency and Cost Reduction Domain score for fiscal year 
2023 for hospitals that report the minimum number of cases with respect 
to the measure described in paragraph (g)(7) of this section.
    (i) CMS does not award a Total Performance Score to any hospital 
for fiscal year 2023.
    (j) The total amount available for value-based incentive payments 
for fiscal year 2023 is equal to the total amount of base-operating DRG 
payment reductions for that fiscal year, as estimated by the Secretary.
    (k) CMS awards a value-based incentive payment percentage (as 
defined in Sec.  412.160) for fiscal year 2023 to all hospitals to 
ensure that each hospital receives a value-based incentive payment 
amount equal to the amount of the reduction made to its base-operating 
DRG payment amounts.

0
9. Section 412.273 is amended by revising paragraphs (d)(2) and (e) to 
read as follows:


Sec.  412.273  Withdrawing an application, terminating an approved 3-
year reclassification, or canceling a previous withdrawal or 
termination.

* * * * *
    (d) * * *
    (2) Timing and process of cancellation request. Cancellation 
requests must be submitted in writing to the MGCRB according to the 
method prescribed by the MGCRB no later than the deadline

[[Page 49405]]

for submitting reclassification applications for the following fiscal 
year, as specified in Sec.  412.256(a)(2).
* * * * *
    (e) Written request only. (1) A request to withdraw an application 
must be submitted in writing to the MGCRB according to the method 
prescribed by the MGCRB by all hospitals that are party to the 
application.
    (2) A request to terminate an approved reclassification must be 
submitted in writing to the MGCRB according to the method prescribed by 
the MGCRB by an individual hospital or by an individual hospital that 
is party to a group classification.
* * * * *

0
10. Section 412.515 is revised to read as follows:


Sec.  412.515  LTC-DRG weighting factors.

    (a) For each LTC-DRG, CMS assigns an appropriate weight that 
reflects the estimated relative cost of hospital resources used within 
that group compared to discharges classified within other groups.
    (b)(1) Beginning FY 2023, each LTC-DRG weight is subject to a 
maximum 10 percent reduction as compared to the weight for the same 
LTC-DRG for the prior fiscal year, except as provided in paragraph 
(b)(2) of this section.
    (2) The limitation described in paragraph (b)(1) of this section 
does not apply to LTC-DRGs with less than 25 applicable LTCH cases in 
the data used to determine the relative weights for the fiscal year.

0
11. Section 412.525 is amended by revising paragraph (c)(1) to read as 
follows:


Sec.  412.525  Adjustments to the Federal prospective payment.

* * * * *
    (c) * * *
    (1) The labor portion of a long-term care hospital's Federal 
prospective payment is adjusted to account for geographical differences 
in the area wage levels using an appropriate wage index (established by 
CMS), which reflects the relative level of hospital wages and wage-
related costs in the geographic area (that is, urban or rural area as 
determined in accordance with the definitions set forth in Sec.  
412.503) of the hospital compared to the national average level of 
hospital wages and wage-related costs.
    (i)(A) The appropriate wage index that is established by CMS is 
updated annually.
    (B) Beginning in fiscal year 2023, if CMS determines that an LTCH's 
wage index value for a fiscal year would decrease by more than 5 
percent as compared to the LTCH's wage index value for the prior fiscal 
year, CMS limits the decrease to 5 percent for the fiscal year.
    (ii) The labor portion of a long-term care hospital's Federal 
prospective payment is established by CMS and is updated annually.
* * * * *

0
12. Section 412.529 is amended by revising paragraphs (d)(4)(ii)(B) and 
(d)(4)(iii)(B) to read as follows:


Sec.  412.529  Special payment provision for short-stay outliers.

* * * * *
    (d) * * *
    (4) * * *
    (ii) * * *
    (B)(1) Is adjusted for different area wage levels based on the 
geographic classifications set forth at Sec.  412.503 and the 
applicable hospital inpatient prospective payment system (IPPS) labor-
related share, using the applicable hospital inpatient prospective 
payment system wage index value for nonreclassified hospitals (an 
LTCH's applicable IPPS wage index).
    (2) Beginning in fiscal year 2023, if CMS determines that an LTCH's 
applicable IPPS wage index value for a fiscal year would decrease by 
more than 5 percent as compared to the LTCH's applicable IPPS wage 
index value for the prior fiscal year, CMS limits the decrease to 5 
percent for the fiscal year.
    (3) For LTCHs located in Alaska and Hawaii, the amount specified in 
paragraph (d)(4)(ii) of this section is also adjusted by the applicable 
hospital inpatient prospective payment system cost of living adjustment 
factors.
* * * * *
    (iii) * * *
    (B)(1) Is adjusted for the applicable geographic adjustment 
factors, including local cost variation based on the geographic 
classifications set forth at Sec.  412.503 and the applicable full 
hospital inpatient prospective payment system (IPPS) wage index value 
for nonreclassified hospitals (an LTCH's applicable IPPS wage index) 
and applicable cost of living adjustment factors for LTCHs in Alaska 
and Hawaii.
    (2) Beginning in fiscal year 2023, if CMS determines that an LTCH's 
applicable IPPS wage index value for a fiscal year would decrease by 
more than 5 percent as compared to the LTCH's applicable IPPS wage 
index value for the prior fiscal year, CMS limits the decrease to 5 
percent for the fiscal year.
* * * * *

PART 413--PRINCIPLES OF REASONABLE COST REIMBURSEMENT; PAYMENT FOR 
END-STAGE RENAL DISEASE SERVICES; PROSPECTIVELY DETERMINED PAYMENT 
RATES FOR SKILLED NURSING FACILITIES; PAYMENT FOR ACUTE KIDNEY 
INJURY DIALYSIS

0
13. The authority citation for part 413 continues to read as follows:

    Authority:  42 U.S.C. 1302, 1395d(d), 1395f(b), 1395g, 1395l(a), 
(i), and (n), 1395x(v), 1395hh, 1395rr, 1395tt, and 1395ww.

0
14. Section 413.75 is amended in paragraph (b) by adding in 
alphabetical order the definitions of ``Rural track Medicare GME 
affiliated group'' and ``Rural track Medicare GME affiliation 
agreement'' to read as follows:


Sec.  413.75  Direct GME payments: General requirements.

* * * * *
    (b) * * *
    Rural track Medicare GME affiliated group means an urban hospital 
and a rural hospital that--
    (i) Participate in a rural track program defined in this paragraph 
(b);
    (ii) Have rural track FTE limitations in effect prior to October 1, 
2022; and
    (iii) Comply with the regulations at Sec.  413.79(f)(1) through (6) 
for Medicare GME affiliated groups.
    Rural track Medicare GME affiliation agreement means a written, 
signed, and dated agreement by responsible representatives of each 
respective hospital in a rural track Medicare GME affiliated group, as 
defined in this paragraph (b), that specifies all of the following:
    (i) A statement attesting that each participating hospital's FTE 
counts and rural track FTE limitations in the agreement do not reflect 
FTE residents nor FTE caps associated with programs other than the 
rural track program.
    (ii) The term of the rural track Medicare GME affiliation agreement 
(which, at a minimum is 1 year), beginning on July 1 of a year.
    (iii) Each participating hospital's direct and indirect GME rural 
track FTE limitations in effect prior to the rural track Medicare GME 
affiliation.
    (iv) The total adjustment to each hospital's rural track FTE 
limitations in each year that the rural track Medicare GME affiliation 
agreement is in effect, for both direct GME and indirect medical 
education (IME), that reflects a positive adjustment to one hospital's 
direct and indirect rural track FTE limitations that is offset by a 
negative adjustment to the other hospital's (or

[[Page 49406]]

hospitals') direct and indirect rural track FTE limitations of at least 
the same amount.
    (v) The adjustment to each participating hospital's FTE counts 
resulting from the FTE resident's (or residents') participation in a 
shared rotational arrangement at each hospital participating in the 
rural track Medicare GME affiliated group for each year the Medicare 
GME affiliation agreement is in effect. This adjustment to each 
participating hospital's FTE count is also reflected in the total 
adjustment to each hospital's rural track FTE limitations (in 
accordance with paragraph (iii) of this definition).
    (vi) The names of the participating hospitals and their Medicare 
provider numbers.
* * * * *

0
15. Section 413.79 is amended by revising paragraphs (c)(2)(iii) and 
adding a sentence at the end of paragraph (d)(3) to read as follows:


Sec.  413.79  Direct GME payments: Determination of the weighted number 
of FTE residents.

* * * * *
    (c) * * *
    (2) * * *
    (iii) Effective for cost reporting periods beginning on or after 
October 1, 2001, if the hospital's unweighted number of FTE residents 
exceeds the limit described in this section, and the number of weighted 
FTE residents in accordance with paragraph (b) of this section also 
exceeds that limit, the respective primary care and obstetrics and 
gynecology weighted FTE counts and other weighted FTE counts are 
adjusted to make the total weighted FTE count equal the limit. If the 
number of FTE residents weighted in accordance with paragraph (b) of 
this section does not exceed that limit, then the allowable weighted 
FTE count is the actual weighted FTE count.
* * * * *
    (d) * * *
    (3) * * * For cost reporting periods beginning on or after October 
1, 2001, the hospital's weighted FTE counts for the preceding two cost 
reporting periods are calculated in accordance with the payment formula 
in paragraph (c)(2)(iii) of this section.

0
16. Subpart F is amended by adding Sec.  413.99 to read as follows:


Sec.  413.99  Qualified and Non-Qualified Deferred Compensation Plans.

    (a) Statutory basis, scope, and definitions--(1) Basis. All 
payments to providers of services must be based on the reasonable cost 
of services covered under Title XVIII in accordance with section 
1861(v) of the Act and the regulations in this part.
    (2) Scope. This section and Sec.  413.100(c)(2)(vii) apply to 
Medicare's treatment of the costs incurred for Qualified and Non-
Qualified Deferred Compensation Plans.
    (3) Definitions. As used in this section the following definitions 
apply:
    Deferred Compensation means remuneration currently earned by an 
employee that is not received until a subsequent period, usually after 
retirement.
    Employee Retirement Income Security Act of 1974 (ERISA) is a 
Federal law that sets standards of protection for individuals in most 
voluntarily established, private-sector retirement plans. The law is 
set forth in Title 29, Chapter 18 of the U.S. Code.
    Funded Plan means a plan in which assets have been irrevocably and 
unconditionally set aside with a third party for the payment of plan 
benefits (for example, in a trust or escrow account), and those assets 
are beyond the reach of the employer or its general creditors.
    Non-Qualified Deferred Compensation Plan (NQDC) means an elective 
or non-elective plan, agreement, method, or arrangement between an 
employer and an employee to pay the employee compensation in the 
future. In comparison with qualified plans, nonqualified plans do not 
provide employers and employees with the tax benefits associated with 
qualified plans because NQDC plans do not satisfy all the requirements 
of 26 U.S.C. 401(a).
    Non-Qualified Defined Benefit Plan (NQDB) means a type of NQDC that 
is established and maintained by the employer primarily to provide 
definitely determinable benefits to its employees usually over a period 
of years, or for life, after retirement. Such benefits are generally 
measured by, and based on, such factors as age of employees, years of 
service, and compensation received by the employees.
    Pension Benefit Guaranty Corporation (PBGC) is a Federal agency 
created by ERISA to protect benefits in private-sector QDBP plans 
described in section 3(35) of ERISA.
    Qualified Defined Benefit Plan (QDBP) means a type of Qualified 
Deferred Compensation Plan that is established and maintained by the 
employer primarily to provide definitely determinable benefits to its 
employees usually over a period of years, or for life, after 
retirement. Such benefits are generally measured by, and based on, such 
factors as age of employees, years of service, and compensation 
received by the employees. A QDBP meets the applicable requirements of 
ERISA, as amended, and the requirements for a QDBP under 26 U.S.C. 
401(a). Under a qualified plan, employers are entitled to deduct 
expenses in the year the employer makes contributions even though 
employees will not recognize income until the receipt of distributions.
    Qualified Defined Contribution or Individual Account Plan (QDCP) 
means a type of Deferred Compensation Plan in which the employee, the 
employer, or both, contribute to an employee's individual account under 
the plan. The amount in the account at distribution includes the 
contributions and investment gains or losses, minus any investment and 
administrative fees. The value of the account changes based on 
contributions and the value and performance of the investments. A QDCP 
meets the applicable requirements of ERISA, as amended, and the 
requirements set forth in 26 U.S.C. 401(a), and, if applicable 26 
U.S.C. 401(k).
    Unfunded Plan means a plan in which benefits are supported by 
assets that have not been set aside (that is, a ``pay as you go'' 
plan), or by assets that have been set aside, but remain subject to the 
claims of the employer's general creditors.
    (b) Principle requirements--(1) General. Deferred Compensation 
contributions or payments must be made by a provider of services, or an 
employee of the provider of services, to a Qualified or Non-Qualified 
Deferred Compensation Plan, established and maintained by the provider 
of services to provide retirement income to employees or to result in 
the deferral of income by employees for periods extending to the 
termination of covered employment or beyond. Contributions or payments 
made by a provider of services for the benefit of its employees to a 
Qualified or Non-Qualified Deferred Compensation Plan are allowable, 
when, and to the extent that, such costs are actually incurred by the 
provider of services and found to be reasonable and necessary under the 
principles of reasonable cost.
    (2) Deferred Compensation for provider-based physicians services in 
a hospital or SNF. Costs incurred by a hospital or SNF to fund a 
Qualified or Non-Qualified Deferred Compensation Plan for a provider-
based physician must meet the following requirements to be allowable 
under the program:
    (i) The allocation of physician compensation costs required under 
Sec.  415.60 of this chapter does not attribute the provider-based 
physician's Deferred Compensation entirely to one

[[Page 49407]]

category of service and his current compensation to another.
    (ii) Contributions or payments toward the Qualified or Non-
Qualified Deferred Compensation Plan do not include any cost excluded 
from the definition of physician compensation at Sec.  415.60(a) of 
this chapter.
    (iii) The amount of Deferred Compensation does not exceed the 
amount specified in the agreement required by Sec.  415.60(g) of this 
chapter.
    (iv) An arrangement between a physician and a provider of services 
under which the physician is reimbursed for patient charges, but the 
provider of services does the billing as a Deferred Compensation 
agreement, is not allowed.
    (v) The costs incurred for physician guaranteed arrangements for 
hospital emergency room availability services, must meet the following 
additional requirements:
    (A) The terms of both the guarantee arrangements and the Deferred 
Compensation Plan establish the amounts to be included at the beginning 
of the hospital's cost reporting period.
    (B) The amount of Deferred Compensation is included in the 
guaranteed amount.
    (C) The hospital contributes to the Deferred Compensation Plan from 
its own funds.
    (D) The amount of Deferred Compensation that is allowable is 
limited to the amount by which the guarantee, including Deferred 
Compensation, exceeds the total billed by the hospital to all patients 
for the physician's patient care services.
    (E) When the physician's charges to all patients equal or exceed 
the amount guaranteed by the hospital, the program does not recognize a 
Deferred Compensation contribution/payment.
    (c) Requirements for Non-Qualified and Qualified Deferred 
Compensation Plans--(1) NQDC requirements. In order for contributions 
or payments by a provider of services to an NQDC as defined at 
paragraph (a)(3) of this section to be allowable under the program, the 
NQDC must meet the general requirements at paragraph (c)(1)(i) of this 
section, and it must either meet the requirements for a funded NQDC at 
paragraph (c)(1)(ii) of this section or the requirements for an 
unfunded NQDC at paragraph (c)(1)(iii) of this section, as applicable.
    (i) General requirements. An NQDC must satisfy the requirements for 
document compliance and operational compliance set forth in 26 U.S.C. 
409A.
    (ii) Funded NQDCs. A funded NQDC must meet the definition of a 
Funded Plan in paragraph (a)(3) of this section and comply with the 
requirements in paragraph (c)(5) of this section.
    (iii) Unfunded NQDCs. An NQDC that is unfunded must meet the 
definition of an Unfunded Plan in paragraph (a)(3) of this section, and 
there must be no constructive receipt of income for employees from a 
NQDC as a result of contributions made by a provider of services.
    (2) QDCP requirements. A QDCP must meet the applicable requirements 
of ERISA, as amended, and the requirements set forth in 26 U.S.C. 
401(a), and if applicable 26 U.S.C. 401(k). A QDCP must meet the 
definition of a Funded Plan in paragraph (a)(3) of this section and 
comply with the requirements in paragraph (c)(5) of this section.
    (3) QDBP requirements. A QDBP must meet the applicable requirements 
of ERISA, as amended, and the requirements for a defined benefit plan 
under 26 U.S.C. 401(a). A QDBP must meet the definition of a Funded 
Plan in paragraph (a)(3) of this section and comply with the 
requirements in paragraph (c)(5) of this section.
    (4) NQDB requirements. In order for contributions or payments by a 
provider of services to an NQDB as defined at paragraph (a)(3) of this 
section to be allowable under the program, the NQDB must meet the 
general requirements at paragraph (c)(4)(i) of this section, and it 
must either meet the requirements for a funded NQDB at paragraph 
(c)(4)(ii) of this section or the requirements for an unfunded NQDB at 
paragraph (c)(4)(iii) of this section, as applicable.
    (i) General requirements. An NQDB must satisfy the requirements for 
document compliance set forth in 26 U.S.C. 409A and operational 
compliance set forth in 26 U.S.C. 409A(a).
    (ii) Funded NQDBs. An NQDB that is funded must meet the definition 
of a Funded Plan in paragraph (a)(3) of this section and comply with 
the requirements in paragraph (c)(5) of this section.
    (iii) Unfunded NQDBs. An NQDB that is unfunded must meet the 
definition of an Unfunded Plan in paragraph (a)(3) of this section, and 
there must be no constructive receipt of income for employees from a 
NQDB as a result of contributions made by a provider of services.
    (5) Funded Plan requirements--(i) Acceptable funding mechanism. 
Both provider of services contributions and employee contributions must 
be used either to purchase an insured plan with a commercial insurance 
company, to establish a custodial bank account, or to establish a trust 
fund administered by a trustee.
    (ii) Life insurance contracts. The purchase of an ordinary life 
insurance contract (for example, whole life, straight life, or other) 
is not a deferral of compensation and is not recognized as a funding 
mechanism, even where it is convertible at the normal retirement date 
specified in the policy to an annuity payable over the remaining life 
of the employee.
    (iii) Sole benefit of participating employees. Regardless of the 
funding mechanism utilized, all provider of services and employee 
contributions to the fund established under the Deferred Compensation 
Plan and income therefrom must be used for the sole benefit of the 
participating employees.
    (d) Recognition of contributions or payments to Qualified and Non-
Qualified Deferred Compensation Plans--(1) General rule. Except as 
provided for in paragraph (c)(1)(iii) of this section with respect to 
QDBPs and funded NQDBs, contributions to Qualified Deferred 
Compensation Plans or payments to plan participants from Non-Qualified 
Deferred Compensation Plans are recognized as allowable costs in 
accordance with paragraph (c)(1)(i) of this section (in the case of 
Unfunded Plans) and paragraph (c)(1)(ii) of this section (in the case 
of Funded Plans).
    (i) Unfunded Plans. Contributions or payments made to an unfunded 
Deferred Compensation Plans (including unfunded NQDBs) by a provider of 
services on behalf of its employees are included in allowable costs 
only during the cost reporting period in which an actual payment is 
made to the participating employees (or their beneficiaries) and only 
to the extent considered reasonable, in accordance with Sec.  
413.100(c)(2)(vii)(A).
    (ii) Funded Plans. Reasonable provider of services payments made 
under funded Deferred Compensation Plans (specifically, funded Defined 
Contribution Plans, but excluding QDBPs and funded NQDBs) are included 
in allowable costs in accordance with Sec.  413.100(c)(2)(vii)(B).
    (iii) Exception for QDBPs and funded NQDBs. (A) QDBP and NQDB 
contributions are found to have been incurred only if paid directly to 
participants or beneficiaries under the terms of the plan or to the 
QDBP or NQDB.
    (B) Payments to a QDBP or funded NQDB for a cost reporting period 
must be measured on a cash basis. A contribution or payment is deemed 
to occur on the date it is credited to the fund established for the 
QDBP or funded NQDB, or for provider of

[[Page 49408]]

services payments made directly to a plan participant or beneficiary, 
on the date the provider of services account is debited.
    (C) Payments or contributions made to fully fund a terminating QDBP 
or funded NQDB are to be included as funding on the date they are paid. 
Excess assets withdrawn from a QDBP or funded NQDB are to be treated as 
negative contributions on the date that they are withdrawn.
    (D) QDBP and funded NQDB annual allowable costs are computed as 
follows:
    (1) QDBP and funded NQDB costs and limits are computed in 
accordance with Sec.  413.100(c)(2)(vii)(D).
    (2) For purposes of determining the QDBP or funded NQDB cost limit 
under Sec.  413.100(c)(2)(vii)(D)(2), provider of services contribution 
payments for each applicable cost reporting period must be determined 
on a cash basis without regard to any limit determined for the period 
during which the contributions were made, and excluding any 
contributions deposited in a prior period and treated as carry forward 
contributions.
    (3) The averaging period used to determine the QDBP or funded NQDB 
cost limit must be determined without regard to a provider of services 
period of participation in the Medicare program. Periods that are not 
Medicare cost reporting periods (for example, periods prior to the 
hospital's participation in the Medicare program) must be defined as 
consecutive 12-month periods ending immediately prior to the provider 
of services initial Medicare cost reporting period.
    (4) The averaging period used to determine the QDBP or funded NQDB 
cost limit must exclude all periods ending prior to the initial 
effective date of the plan (or a predecessor plan in the case of a 
merger).
    (5) In general, the current period defined benefit cost and limit 
is computed and applied separately for each QDBP or funded NQDB offered 
by a provider of services. In the case of a plan merger, the 
contributions or payments made by a provider of services to a 
predecessor QDBP or funded NQDB and reflected in the assets 
subsequently transferred to a successor plan are treated as 
contribution payments made to the successor plan.
    (2) [Reserved]
    (e) Documentation requirements. Documentation must be maintained by 
the provider of services in accordance with Sec.  413.20 to 
substantiate the allowability of contributions or payments to Qualified 
and Non-Qualified Deferred Compensation Plan(s) that it has included in 
its cost reports.
    (1) Required documentation. The provider of services must maintain 
and make available, upon request by the contractor or CMS, certain 
specified documentation, to substantiate the allowability of the 
contributions or payments to its Qualified or Non-Qualified Deferred 
Compensation Plan(s), or both:
    (i) Documentation that demonstrates that the provider of services 
is in compliance with 26 U.S.C. 409A and 409A(a), and, if applicable, 
26 U.S.C. 457.
    (ii) Ledger accounts/account statements for each plan participant 
noting current year deferrals, distributions and loans, including any 
deferral election forms completed by employees, any change requests, 
and the approval of such requests.
    (iii) Documentation that demonstrates the amount(s) and date(s) of 
actual contributions or payments made to the Qualified or Non-Qualified 
Deferred Compensation Plan during the current cost reporting period.
    (iv) Schedule SB of Form 5500 (tri-agency form (Department of Labor 
(DOL), Internal Revenue Service (IRS), and PBGC) that plans file with 
the DOL's ``EFAST'' electronic filing system) for a QDBP for the 
current cost reporting period, or any applicable prior periods.
    (v) In the case of a system-wide (multiple employer) plan, the home 
office shall identify the contributions attributed to each 
participating provider of services. If the costs included in the cost 
report for a period differ from the contributions made during the 
reporting period (that is, as a result of carry forward contributions), 
the provider of services must also have data available to track and 
reconcile the difference.
    (2) Additional documentation. The following additional 
documentation must be made available, upon request by the contractor or 
CMS, to substantiate the allowability of the payments/contributions by 
a provider of services to a Qualified or Non-Qualified Deferred 
Compensation Plan:
    (i) The plan document, the trust document and all amendments 
related to the current cost reporting period.
    (ii) If applicable, any Form 5330, Return of Excise Taxes Related 
to Employee Benefit Plans, for the cost reporting period.
    (iii)(A) Supporting documents for all plan assets and liabilities, 
such as broker's statements, bank statements, insurance contracts, loan 
documents, deeds, etc.
    (B) Verification of how assets are valued.
    (iv)(A) Trustee or administrator reports.
    (B) Ledgers.
    (C) Journals.
    (D) Trustee, administrator, and investment committee minutes.
    (E) Certified audit report and other financial reports for the 
trust.
    (F) Any other financial reports, including receipt and disbursement 
statements, a detailed income statement, and a detailed balance sheet.
    (v) For each covered QDBP, documentation of the certified premium 
information and payments to the PBGC.
    (f) Administrative and other costs associated with Deferred 
Compensation Plans. The provider of services shall file a cost report 
required under Sec. Sec.  413.20 and 413.24(f) that is consistent with 
the policies set forth in this section.
    (1) Trustee and custodial fees. Reasonable trustee or custodial 
fees, including PBGC premiums, paid by the provider of services are 
allowed as an administrative cost except where the plan provides that 
such fees are paid out of the corpus or earnings of the fund.
    (2) Vested benefits. The forfeiture of an employee's benefits for 
cause (as defined in the plan) is recognized as an allowable cost 
provided that such forfeited amounts are used to reduce the provider of 
services contributions or payments to the plan during the cost 
reporting period in which the forfeiture occurs.
    (3) Benefits to be paid. If an employee terminates participation in 
the Deferred Compensation Plan before their rights are vested, the 
applicable non-vested contributions/payments cannot be applied to 
increase the benefits of the surviving participants. Instead the non-
vested contributions or payments should be used to reduce the provider 
of services contributions or payments to the Deferred Compensation 
Plan, in the cost reporting period in which the employee terminated 
participation in the Deferred Compensation Plan. Otherwise, the 
contributions/payments made by the provider of services must be applied 
to reduce the subsequent contributions or payments to the Deferred 
Compensation Plan in the next cost reporting period. If subsequent 
provider of services contributions/payments to the Deferred 
Compensation Plan are not made, then the provider of services costs are 
reduced by the contractor to the extent of such non-vested funds.
    (4) DOL, IRS, or PBGC penalties. If the provider of services is 
assessed an excise tax or other remedy by the DOL, IRS, or PBGC for 
failure to follow DOL,

[[Page 49409]]

IRS, or PBGC requirements under ERISA or any other penalty fee or 
penalty interest applicable to its Deferred Compensation Plan, the cost 
is unallowable in accordance with section 1861(v)(8) of the Act.
    (5) Loans made from a Deferred Compensation Plan. A provider of 
services cannot make a loan to itself from a Deferred Compensation Plan 
where ERISA or IRS rules prohibit such a transaction, except where 
specifically excepted.
    (6) Termination/discontinuation of a Deferred Compensation Plan. If 
the provider of services declines to vest its outstanding required 
contributions or payments (that is, matching or non-elective) to a 
Deferred Compensation Plan as a result of a termination in full or in 
part or a discontinuation of contributions or payments to a Deferred 
Compensation Plan, then the provider of services total outstanding 
required contributions or payments to the Deferred Compensation Plan 
during the cost reporting period wherein such termination is initiated 
cannot be included in the provider of services allowable cost for the 
cost reporting period in which the termination is initiated, nor any 
future period.
    (7) Required offset against interest expense. Investment income 
earned on a Deferred Compensation Plan after its termination but prior 
to liquidation of the plan's assets and distribution to the provider of 
services must be offset against the provider of services allowable 
interest expense under Sec.  413.153.
    (8) Treatment of residual assets following termination of a Funded 
Plan. (i) Residual assets arising from the termination of a funded 
Deferred Compensation Plan must be recouped in the year of the plan 
termination only against the cost center(s) in which the provider of 
services reported its plan contributions or payments, usually the 
administrative and general cost center.
    (ii) Residual assets exceeding the amount in the administrative and 
general (or other) cost center are not further offset in the current or 
subsequent years.
    (iii) The Medicare share of the reversion is based on the Medicare 
utilization rate in the year the reversion occurs (or the year the 
actuarial surplus is determined), and not Medicare's utilization in the 
years the contributions to the plan were made.
    (g) Treatment of costs associated with the PBGC. Costs associated 
with the requirements set forth in ERISA and by the PBGC and incurred 
by a provider of services who sponsors a QDBP are allowable or 
unallowable under the program as provided for in this paragraph (g).
    (1) Costs paid out of the plan trust. PBGC premiums and costs paid 
out of the corpus or earnings of the trust are included in the 
contributions allowed under paragraph (d)(1)(iii)(A) of this section, 
and are not allowable as separate costs.
    (2) Premium payments for single- and multi-employer plans. The 
amount of PBGC premiums paid for basic benefits (flat rate or variable, 
excluding amounts paid out of the corpus or earnings of the trust) by a 
provider of services who sponsors a QDBP are allowable under the 
program.
    (3) Liability for missing participants or beneficiaries. The total 
amount paid to the PBGC by a provider of services who sponsors a QDBP 
(excluding amounts paid out of the corpus or earnings of the trust) of 
the benefit transfer amount (as described in 29 CFR 4050.103(d)) for 
all missing participants or beneficiaries of the QDBP, is allowable 
under the program.
    (4) Plan termination due to distress. For a defined benefit plan 
that terminated with insufficient assets to pay all of the plan 
benefits, which resulted in the PBGC making payment of vested benefits 
up to limits defined by law in accordance with 29 CFR part 4022, such 
amounts contributed to the QDBP by the provider of services who 
sponsors the QDBP are allowable. Benefits paid to the participants and 
beneficiaries of the QDBP by the PBGC are unallowable.
    (5) Restored plan payments. If the PBGC issues or has issued a plan 
restoration order as described in 29 CFR part 4047, the amounts that 
the provider of services repays to the PBGC for guaranteed benefits and 
related expenses under the plan while the plan was in terminated 
status, and any administrative costs assessed by the PBGC, excluding 
penalties, are allowable.

PART 482--CONDITIONS OF PARTICIPATION FOR HOSPITALS

0
17. The authority citation for part 482 continues to read as follows:

    Authority: 42 U.S.C. 1302, 1395hh, and 1395rr, unless otherwise 
noted.

0
18. Section 482.42 is amended by revising paragraphs (e) and (f) to 
read as follows:


Sec.  482.42  Condition of participation: Infection prevention and 
control and antibiotic stewardship programs.

* * * * *
    (e) COVID-19 reporting. (1) During the Public Health Emergency, as 
defined in Sec.  400.200 of this chapter, the hospital must report 
information in accordance with a frequency as specified by the 
Secretary on COVID-19 in a standardized format specified by the 
Secretary. This report must include, but not be limited to, the 
following data elements:
    (i) The hospital's current inventory supplies of any COVID-19-
related therapeutics that have been distributed and delivered to the 
hospital under the authority and direction of the Secretary.
    (ii) The hospital's current usage rate for any COVID-19-related 
therapeutics that have been distributed and delivered to the hospital 
under the authority and direction of the Secretary.
    (2) Beginning at the conclusion of the COVID-19 Public Health 
Emergency, as defined in Sec.  400.200 of this chapter, and continuing 
until April 30, 2024, except when the Secretary specifies an earlier 
end date for the requirements of this paragraph (e)(2), the hospital 
must electronically report information about COVID-19 in a standardized 
format specified by the Secretary. To the extent as required by the 
Secretary, this report must include the following data elements:
    (i) Confirmed COVID-19 infections among patients.
    (ii) Total deaths among patients.
    (iii) Personal protective equipment and testing supplies.
    (iv) Ventilator use, capacity, and supplies.
    (v) Total bed and intensive care unit bed census and capacity.
    (vi) Staffing shortages.
    (vii) COVID-19 vaccine administration data of patients and staff.
    (viii) Relevant therapeutic inventories or usage, or both.
    (f) Standard: Reporting of acute respiratory illness, including 
seasonal influenza virus, influenza-like illness, and severe acute 
respiratory infection. (1) During the Public Health Emergency, as 
defined in Sec.  400.200 of this chapter, the hospital must report 
information, in accordance with a frequency as specified by the 
Secretary, on Acute Respiratory Illness (including, but not limited to, 
Seasonal Influenza Virus, Influenza-like Illness, and Severe Acute 
Respiratory Infection) in a standardized format specified by the 
Secretary.
    (2) Beginning at the conclusion of the COVID-19 Public Health 
Emergency, as defined in Sec.  400.200 of this chapter, and continuing 
until April 30, 2024, except when the Secretary specifies an earlier 
end date for the requirements of this paragraph (f)(2), the hospital 
must electronically report information about seasonal influenza in a 
standardized format specified by the Secretary. To the

[[Page 49410]]

extent as required by the Secretary, this report must include the 
following data elements:
    (i) Confirmed influenza infections among patients.
    (ii) Total deaths among patients.
    (ii) Confirmed co-morbid influenza and COVID-19 infections among 
patients.

PART 485--CONDITIONS OF PARTICIPATION: SPECIALIZED PROVIDERS

0
19. The authority citation for part 485 is revised to read as follows:

    Authority: 42 U.S.C. 1302 and 1395(hh).

0
20. Section 485.640 is amended by revising paragraphs (d) and (e) to 
read as follows:


Sec.  485.640  Condition of participation: Infection prevention and 
control and antibiotic stewardship programs.

* * * * *
    (d) COVID-19 reporting. (1) During the Public Health Emergency, as 
defined in Sec.  400.200 of this chapter, the CAH must report 
information in accordance with a frequency as specified by the 
Secretary on COVID-19 in a standardized format specified by the 
Secretary. This report must include, but not be limited to, the 
following data elements:
    (i) The CAH's current inventory supplies of any COVID-19-related 
therapeutics that have been distributed and delivered to the CAH under 
the authority and direction of the Secretary; and
    (ii) The CAH's current usage rate for any COVID-19-related 
therapeutics that have been distributed and delivered to the CAH under 
the authority and direction of the Secretary.
    (2) Beginning at the conclusion of the COVID-19 Public Health 
Emergency, as defined in Sec.  400.200 of this chapter, and continuing 
until April 30, 2024, except when the Secretary specifies an earlier 
end date for the requirements of this paragraph (d)(2), the CAH must 
electronically report information about COVID-19 in a standardized 
format specified by the Secretary. To the extent as required by the 
Secretary, this report must include the following data elements:
    (i) Confirmed COVID-19 infections among patients.
    (ii) Total deaths among patients.
    (iii) Personal protective equipment and testing supplies.
    (iv) Ventilator use, capacity, and supplies.
    (v) Total bed and intensive care unit bed census and capacity.
    (vi) Staffing shortages.
    (vii) COVID-19 vaccine administration data of patients and staff.
    (viii) Relevant therapeutic inventories or usage, or both.
    (e) Standard: Reporting of acute respiratory illness, including 
seasonal influenza virus, influenza-like illness, and severe acute 
respiratory infection. (1) During the Public Health Emergency, as 
defined in Sec.  400.200 of this chapter, the CAH must report 
information, in accordance with a frequency as specified by the 
Secretary, on Acute Respiratory Illness (including, but not limited to, 
Seasonal Influenza Virus, Influenza-like Illness, and Severe Acute 
Respiratory Infection) in a standardized format specified by the 
Secretary.
    (2) Beginning at the conclusion of the COVID-19 Public Health 
Emergency, as defined in Sec.  400.200 of this chapter, and continuing 
until April 30, 2024, except when the Secretary specifies an earlier 
end date for the requirements of this paragraph (e)(2), the CAH must 
electronically report information about seasonal influenza in a 
standardized format specified by the Secretary. To the extent as 
required by the Secretary, this report must include the following data 
elements:
    (i) Confirmed influenza infections among patients.
    (ii) Total deaths among patients.
    (iii) Confirmed co-morbid influenza and COVID-19 infections among 
patients.
* * * * *

PART 495--STANDARDS FOR THE ELECTRONIC HEALTH RECORD TECHNOLOGY 
INCENTIVE PROGRAM

0
21. The authority citation for part 495 continues to read as follows:

    Authority: 42 U.S.C. 1302 and 1395hh.

0
22. Section Sec.  495.24 is amended--
0
a. In the introductory text, by revising the last sentence and adding a 
new sentence at the end of the paragraph;
0
b. In paragraph (e), in the paragraph heading by removing the phrase 
``for 2019 and subsequent years'' and adding in its place the phrase 
``for 2019 through 2022.'';
0
c. In paragraph (e)(1)(i)(C), by removing the phrase ``In 2022 and 
subsequent years, earn'' and adding in its place the phrase ``In 2022, 
earn'';
0
d. In paragraph (e)(4)(ii), by removing the phrase ``In 2022 and 
subsequent years'' and adding in its place the phrase ``In 2022'';
0
e. In paragraph (e)(5)(ii)(B), by removing the phrase ``In 2020 and 
subsequent years'' and adding in its place the phrase ``In 2020 through 
2022'';
0
f. In paragraph (e)(5)(iii)(A), by removing the phrase ``in CY 2019 and 
subsequent years'' and adding in its place ``in CY 2019 through CY 
2022.'';
0
g. In paragraph (e)(5)(v), by removing the phrase ``Beginning with the 
EHR reporting period in CY 2019'' and adding in its place ``For the EHR 
reporting periods in CY 2019 through CY 2022'';
0
h. In paragraph (e)(7)(ii) introductory text, by removing the phrase 
``beginning in CY 2019'' and adding in its place the phrase ``for CY 
2019 through CY 2022'';
0
i. In paragraph (e)(8)(ii), by removing the phrase ``For CY 2022 and 
subsequent years'' and adding in its place ``For CY 2022'';
0
j. In paragraph (e)(8)(ii)(A), by removing the phrase ``For CY 2022 and 
subsequent years'' and adding in its place ``For CY 2022'';
0
k. In paragraphs (e)(8)(iii) introductory text, by removing the phrase 
``For CY 2022 and subsequent years'' and adding in its place ``For CY 
2022'';
0
l. In paragraph (e)(8)(iii)(A)(2), by removing the phrase ``For CY 2022 
and subsequent years'' and adding in its place ``For CY 2022'';
0
m. In paragraph (e)(8)(iii)(D)(2), by removing the phrase ``For CY 2022 
and subsequent years'' and adding in its place ``For CY 2022'';
0
n. In paragraph (e)(8)(iii)(E)(2), by removing the phrase ``For CY 2022 
and subsequent years'' and adding in its place ``For CY 2022''; and
0
o. Adding paragraph (f).
    The revision and addition read as follows:


Sec.  495.24  Stage 3 meaningful use objectives and measures for EPs, 
eligible hospitals and CAHs for 2019 and subsequent years.

    * * * The criteria specified in paragraph (e) of this section are 
applicable for eligible hospitals and CAHs attesting to CMS for 2019 
through 2022. The criteria specified in paragraph (f) of this section 
are applicable for eligible hospitals and CAHs attesting to CMS for 
2023 and subsequent years
* * * * *
    (f) Stage 3 objectives and measures for eligible hospitals and CAHs 
attesting to CMS for 2023 and subsequent years. (1) General rule. (i) 
Except as specified in paragraph (f)(2) of this section, eligible 
hospitals and CAHs must do all of the following as part of meeting the 
definition of a meaningful EHR user under Sec.  495.4:
    (A) Meet all objectives and associated measures selected by CMS 
under section 1886(n)(3) of the Act for an EHR reporting period.

[[Page 49411]]

    (B) In 2023 and subsequent years, earn a total score of at least 60 
points.
    (ii) The numerator and denominator of the measures increment based 
on actions occurring during the EHR reporting period selected by the 
eligible hospital or CAH, unless otherwise indicated.
    (2) Exclusion for nonapplicable measures. (i) Exclusion of a 
particular measure. An eligible hospital or CAH may exclude a 
particular measure that includes an option for exclusion if the 
eligible hospital or CAH meets the following requirements:
    (A) Meets the criteria in the applicable measure that would permit 
the exclusion.
    (B) Attests to the exclusion.
    (ii) Distribution of points for nonapplicable measures. For 
eligible hospitals or CAHs that claim such exclusion, the points 
assigned to the excluded measure are distributed to other measures as 
specified by CMS for an EHR reporting period.

    Dated: July 27, 2022.
Xavier Becerra,
Secretary, Department of Health and Human Services.

    Note: The following Addendum and Appendixes will not appear in 
the Code of Federal Regulations.

Addendum--Schedule of Standardized Amounts, Update Factors, Rate-of-
Increase Percentages Effective With Cost Reporting Periods Beginning on 
or After October 1, 2022, and Payment Rates for LTCHs Effective for 
Discharges Occurring on or After October 1, 2022

I. Summary and Background

    In this Addendum, we are setting forth a description of the 
methods and data we used to determine the prospective payment rates 
for Medicare hospital inpatient operating costs and Medicare 
hospital inpatient capital-related costs for FY 2023 for acute care 
hospitals. We also are setting forth the rate-of-increase percentage 
for updating the target amounts for certain hospitals excluded from 
the IPPS for FY 2023. We note that, because certain hospitals 
excluded from the IPPS are paid on a reasonable cost basis subject 
to a rate-of-increase ceiling (and not by the IPPS), these hospitals 
are not affected by the proposed figures for the standardized 
amounts, offsets, and budget neutrality factors. Therefore, in this 
final rule, we are setting forth the rate-of-increase percentage for 
updating the target amounts for certain hospitals excluded from the 
IPPS that will be effective for cost reporting periods beginning on 
or after October 1, 2022. In addition, we are setting forth a 
description of the methods and data we used to determine the LTCH 
PPS standard Federal payment rate that will be applicable to 
Medicare LTCHs for FY 2023.
    In general, except for SCHs, for FY 2023, each hospital's 
payment per discharge under the IPPS is based on 100 percent of the 
Federal national rate, also known as the national adjusted 
standardized amount. This amount reflects the national average 
hospital cost per case from a base year, updated for inflation. 
Under current law, the MDH program is effective for discharges on or 
before September 30, 2022. Therefore, under current law, the MDH 
program will expire at the end of FY 2022.
    Sole Community Hospitals (SCHs) are paid based on whichever of 
the following rates yields the greatest aggregate payment: the 
Federal national rate (including, as discussed in section IV.G. of 
the preamble of this final rule, uncompensated care payments under 
section 1886(r)(2) of the Act); the updated hospital-specific rate 
based on FY 1982 costs per discharge; the updated hospital-specific 
rate based on FY 1987 costs per discharge; the updated hospital-
specific rate based on FY 1996 costs per discharge; or the updated 
hospital-specific rate based on FY 2006 costs per discharge.
    As discussed in section V.A.2. of the preamble of this final 
rule, section 1886(n)(6)(B) of the Act was amended to specify that 
the adjustments to the applicable percentage increase under section 
1886(b)(3)(B)(ix) of the Act apply to subsection (d) Puerto Rico 
hospitals that are not meaningful EHR users, effective beginning FY 
2022. In general, Puerto Rico hospitals are paid 100 percent of the 
national standardized amount and are subject to the same national 
standardized amount as subsection (d) hospitals that receive the 
full update. Accordingly, our discussion later in this section does 
not include references to the Puerto Rico standardized amount or the 
Puerto Rico-specific wage index.
    As discussed in section II. of this Addendum, we are making 
changes in the determination of the prospective payment rates for 
Medicare inpatient operating costs for acute care hospitals for FY 
2023. In section III. of this Addendum, we discuss our policy 
changes for determining the prospective payment rates for Medicare 
inpatient capital-related costs for FY 2023. In section IV. of this 
Addendum, we are setting forth the rate-of-increase percentage for 
determining the rate-of-increase limits for certain hospitals 
excluded from the IPPS for FY 2023. In section V. of this Addendum, 
we discuss policy changes for determining the LTCH PPS standard 
Federal rate for LTCHs paid under the LTCH PPS for FY 2023. The 
tables to which we refer in the preamble of this final rule are 
listed in section VI. of this Addendum and are available via the 
internet on the CMS website.

II. Changes to Prospective Payment Rates for Hospital Inpatient 
Operating Costs for Acute Care Hospitals for FY 2023

    The basic methodology for determining prospective payment rates 
for hospital inpatient operating costs for acute care hospitals for 
FY 2005 and subsequent fiscal years is set forth under Sec.  412.64. 
The basic methodology for determining the prospective payment rates 
for hospital inpatient operating costs for hospitals located in 
Puerto Rico for FY 2005 and subsequent fiscal years is set forth 
under Sec. Sec.  412.211 and 412.212. In this section, we discuss 
the factors we are using for determining the proposed prospective 
payment rates for FY 2023. In summary, the standardized amounts set 
forth in Tables 1A, 1B, and 1C that are listed and published in 
section VI. of this Addendum (and available via the internet on the 
CMS website) reflect--
     Equalization of the standardized amounts for urban and 
other areas at the level computed for large urban hospitals during 
FY 2004 and onward, as provided for under section 
1886(d)(3)(A)(iv)(II) of the Act.
     The labor-related share that is applied to the 
standardized amounts to give the hospital the highest payment, as 
provided for under sections 1886(d)(3)(E) and 1886(d)(9)(C)(iv) of 
the Act. For FY 2023, depending on whether a hospital submits 
quality data under the rules established in accordance with section 
1886(b)(3)(B)(viii) of the Act (hereafter referred to as a hospital 
that submits quality data) and is a meaningful EHR user under 
section 1886(b)(3)(B)(ix) of the Act (hereafter referred to as a 
hospital that is a meaningful EHR user), there are four possible 
applicable percentage increases that can be applied to the national 
standardized amount. We refer readers to section IV.A. of the 
preamble of this final rule for a complete discussion on the FY 2023 
inpatient hospital update. The table that follows shows these four 
scenarios:

[[Page 49412]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.213

    We note that section 1886(b)(3)(B)(viii) of the Act, which 
specifies the adjustment to the applicable percentage increase for 
``subsection (d)'' hospitals that do not submit quality data under 
the rules established by the Secretary, is not applicable to 
hospitals located in Puerto Rico.
    In addition, section 602 of Public Law 114-113 amended section 
1886(n)(6)(B) of the Act to specify that Puerto Rico hospitals are 
eligible for incentive payments for the meaningful use of certified 
EHR technology, effective beginning FY 2016, and also to apply the 
adjustments to the applicable percentage increase under section 
1886(b)(3)(B)(ix) of the Act to subsection (d) Puerto Rico hospitals 
that are not meaningful EHR users, effective beginning FY 2022. 
Accordingly, for FY 2022, section 1886(b)(3)(B)(ix) of the Act in 
conjunction with section 602(d) of Public Law 114-113 requires that 
any subsection (d) Puerto Rico hospital that is not a meaningful EHR 
user (as defined in section 1886(n)(3) of the Act) and not subject 
to an exception under section 1886(b)(3)(B)(ix) of the Act will have 
``three-quarters'' of the applicable percentage increase (prior to 
the application of other statutory adjustments), or three-quarters 
of the applicable market basket update, reduced by 33\1/3\ percent. 
The reduction to three-quarters of the applicable percentage 
increase for subsection (d) Puerto Rico hospitals that are not 
meaningful EHR users increases to 66\2/3\ percent for FY 2023, and, 
for FY 2024 and subsequent fiscal years, to 100 percent. In the FY 
2019 IPPS/LTCH PPS final rule, we finalized the payment reductions 
(83 FR 41674). The regulations at 42 CFR 412.64(d)(3)(ii) reflect 
the current law for the update for subsection (d) Puerto Rico 
hospitals for FY 2023 and subsequent fiscal years.
     An adjustment to the standardized amount to ensure 
budget neutrality for DRG recalibration and reclassification, as 
provided for under section 1886(d)(4)(C)(iii) of the Act.
     An adjustment to the standardized amount to ensure 
budget neutrality for our permanent 10-percent cap on the reduction 
in a MS-DRG's relative weight in a given fiscal year beginning FY 
2023, as discussed in section II.E.2.d. of the preamble of this 
final rule, consistent with our current methodology for implementing 
DRG recalibration and reclassification budget neutrality under 
section 1886(d)(4)(C)(iii) of the Act.
     An adjustment to ensure the wage index and labor-
related share changes (depending on the fiscal year) are budget 
neutral, as provided for under section 1886(d)(3)(E)(i) of the Act 
(as discussed in the FY 2006 IPPS final rule (70 FR 47395) and the 
FY 2010 IPPS final rule (74 FR 44005)). We note that section 
1886(d)(3)(E)(i) of the Act requires that when we compute such 
budget neutrality, we assume that the provisions of section 
1886(d)(3)(E)(ii) of the Act (requiring a 62-percent labor-related 
share in certain circumstances) had not been enacted.
     An adjustment to ensure the effects of geographic 
reclassification are budget neutral, as provided for under section 
1886(d)(8)(D) of the Act, by removing the FY 2022 budget neutrality 
factor and applying a revised factor.
     A positive adjustment of 0.5 percent in FYs 2019 
through 2023 as required under section 414 of the MACRA.
     An adjustment to the standardized amount to implement 
in a budget neutral manner the increase in the wage index values for 
hospitals with a wage index value below the 25th percentile wage 
index value across all hospitals (as described in section III.N. of 
the preamble of this final rule).
     An adjustment to the standardized amount to implement 
in a budget neutral manner our permanent wage index cap policy, as 
discussed in section III. N of the preamble of this final rule.
     An adjustment to ensure the effects of the Rural 
Community Hospital Demonstration program required under section 410A 
of Public Law 108-173 (as amended by sections 3123 and 10313 of 
Public Law 111-148; section 15003 of Public Law 114-255; and 
Division CC, section 128 of Public Law 116-260, which extended the 
program), are budget neutral, as required under section 410A(c)(2) 
of Public Law 108-173.
     An adjustment to remove the FY 2022 outlier offset and 
apply an offset for FY 2023, as provided for in section 
1886(d)(3)(B) of the Act.
    For FY 2023, consistent with current law, we are applying the 
rural floor budget neutrality adjustment to hospital wage indexes. 
Also, consistent with section 3141 of the Affordable Care Act, 
instead of applying a State-level rural floor budget neutrality 
adjustment to the wage index, we are applying a uniform, national 
budget neutrality adjustment to the FY 2023 wage index for the rural 
floor.
    For FY 2023, we proposed to not remove the Stem Cell Acquisition 
Budget Neutrality Factor from the prior year's standardized amount 
and to not apply a new factor. If we removed the prior year's 
adjustment, we would not satisfy budget neutrality. We believe this 
approach ensures the effects of the reasonable cost-based payment 
for allogeneic hematopoietic stem cell acquisition costs under 
section 108 of the Further Consolidated Appropriations Act, 2020 
(Pub. L. 116-94) are budget neutral as required under section 108 of 
Public Law 116-94. For a discussion of Stem Cell Acquisition Budget 
Neutrality Factor, we refer the reader to the FY 2021 IPPS/LTCH PPS 
final rule (85 FR 59032 and 59033). When cost report data regarding 
reasonable cost of acquisition become available, we intend to 
consider using that reasonable cost data in future rulemaking for 
budget neutrality.
    We did not receive comments on stem cell acquisition budget 
neutrality. We are finalizing as proposed without modification.

A. Calculation of the Adjusted Standardized Amount

1. Standardization of Base-Year Costs or Target Amounts

    In general, the national standardized amount is based on per 
discharge averages of adjusted hospital costs from a base period 
(section 1886(d)(2)(A) of the Act), updated and otherwise adjusted 
in accordance with the provisions of section 1886(d) of the Act. The 
September 1, 1983, interim final rule (48 FR 39763) contained a 
detailed explanation of how base-year cost data (from cost reporting 
periods ending during FY 1981) were established for urban and rural 
hospitals in the initial development of standardized amounts for the 
IPPS.
    Sections 1886(d)(2)(B) and 1886(d)(2)(C) of the Act require us 
to update base-year per discharge costs for FY 1984 and then 
standardize the cost data in order to remove the effects of certain 
sources of cost

[[Page 49413]]

variations among hospitals. These effects include case-mix, 
differences in area wage levels, cost-of-living adjustments for 
Alaska and Hawaii, IME costs, and costs to hospitals serving a 
disproportionate share of low-income patients.
    For FY 2023, as we proposed, we are continuing to use the 
national labor-related and nonlabor-related shares (which are based 
on the 2018-based IPPS market basket) that were used in FY 2022. 
Specifically, under section 1886(d)(3)(E) of the Act, the Secretary 
estimates, from time to time, the proportion of payments that are 
labor-related and adjusts the proportion (as estimated by the 
Secretary from time to time) of hospitals' costs which are 
attributable to wages and wage-related costs of the DRG prospective 
payment rates. We refer to the proportion of hospitals' costs that 
are attributable to wages and wage-related costs as the ``labor-
related share.'' For FY 2023, as discussed in section III.M. of the 
preamble of this final rule, as we proposed, we are using a labor-
related share of 67.6 percent for the national standardized amounts 
for all IPPS hospitals (including hospitals in Puerto Rico) that 
have a wage index value that is greater than 1.0000. Consistent with 
section 1886(d)(3)(E) of the Act, as proposed, we are applying the 
wage index to a labor-related share of 62 percent of the national 
standardized amount for all IPPS hospitals (including hospitals in 
Puerto Rico) whose wage index values are less than or equal to 
1.0000.
    The standardized amounts for operating costs appear in Tables 
1A, 1B, and 1C that are listed and published in section VI. of the 
Addendum to this final rule and are available via the internet on 
the CMS website.

2. Computing the National Average Standardized Amount

    Section 1886(d)(3)(A)(iv)(II) of the Act requires that, 
beginning with FY 2004 and thereafter, an equal standardized amount 
be computed for all hospitals at the level computed for large urban 
hospitals during FY 2003, updated by the applicable percentage 
update. Accordingly, as proposed, we are calculating the FY 2023 
national average standardized amount irrespective of whether a 
hospital is located in an urban or rural location.

3. Updating the National Average Standardized Amount

    Section 1886(b)(3)(B) of the Act specifies the applicable 
percentage increase used to update the standardized amount for 
payment for inpatient hospital operating costs. We note that, in 
compliance with section 404 of the MMA, we are using the 2018-based 
IPPS operating and capital market baskets for FY 2023. As discussed 
in section IV.B. of the preamble of this final rule, in accordance 
with section 1886(b)(3)(B) of the Act, as amended by section 3401(a) 
of the Affordable Care Act, we are reducing the FY 2023 applicable 
percentage increase (which for this final rule is based on IGI's 
second quarter 2022 forecast of the 2018-based IPPS market basket) 
by the productivity adjustment, as discussed elsewhere in this final 
rule.
    Based on IGI's second quarter 2022 forecast (as discussed in 
Appendix B of this final rule), the forecast of the IPPS market 
basket increase for FY 2023 for this final rule is 4.1 percent. As 
discussed earlier, for FY 2023, depending on whether a hospital 
submits quality data under the rules established in accordance with 
section 1886(b)(3)(B)(viii) of the Act and is a meaningful EHR user 
under section 1886(b)(3)(B)(ix) of the Act, there are four possible 
applicable percentage increases that can be applied to the 
standardized amount. We refer readers to section V.B. of the 
preamble of this final rule for a complete discussion on the FY 2023 
inpatient hospital update to the standardized amount. We also refer 
readers to the previous table for the four possible applicable 
percentage increases that would be applied to update the national 
standardized amount. The standardized amounts shown in Tables 1A 
through 1C that are published in section VI. of this Addendum and 
that are available via the internet on the CMS website reflect these 
differential amounts.
    Although the update factors for FY 2023 are set by law, we are 
required by section 1886(e)(4) of the Act to recommend, taking into 
account MedPAC's recommendations, appropriate update factors for FY 
2023 for both IPPS hospitals and hospitals and hospital units 
excluded from the IPPS. Section 1886(e)(5)(A) of the Act requires 
that we publish our recommendations in the Federal Register for 
public comment. Our recommendation on the update factors is set 
forth in Appendix B of this final rule.

4. Methodology for Calculation of the Average Standardized Amount

    The methodology we used to calculate the FY 2023 standardized 
amount is as follows:
     To ensure we are only including hospitals paid under 
the IPPS in the calculation of the standardized amount, we applied 
the following inclusion and exclusion criteria: include hospitals 
whose last four digits fall between 0001 and 0879 (section 2779A1 of 
Chapter 2 of the State Operations Manual on the CMS website at 
https://www.cms.gov/Regulations-and-Guidance/Guidance/Manuals/Downloads/som107c02.pdf); exclude CAHs at the time of this final 
rule; exclude hospitals in Maryland (because these hospitals are 
paid under an all payer model under section 1115A of the Act); and 
remove PPS excluded-cancer hospitals that have a ``V'' in the fifth 
position of their provider number or a ``E'' or ``F'' in the sixth 
position.
     As in the past, we are adjusting the FY 2023 
standardized amount to remove the effects of the FY 2022 geographic 
reclassifications and outlier payments before applying the FY 2023 
updates. We then applied budget neutrality offsets for outliers and 
geographic reclassifications to the standardized amount based on FY 
2023 payment policies.
     We do not remove the prior year's budget neutrality 
adjustments for reclassification and recalibration of the DRG 
relative weights and for updated wage data because, in accordance 
with sections 1886(d)(4)(C)(iii) and 1886(d)(3)(E) of the Act, 
estimated aggregate payments after updates in the DRG relative 
weights and wage index should equal estimated aggregate payments 
prior to the changes. If we removed the prior year's adjustment, we 
would not satisfy these conditions.
    Budget neutrality is determined by comparing aggregate IPPS 
payments before and after making changes that are required to be 
budget neutral (for example, changes to MS-DRG classifications, 
recalibration of the MS-DRG relative weights, updates to the wage 
index, and different geographic reclassifications). We include 
outlier payments in the simulations because they may be affected by 
changes in these parameters.
     Consistent with our methodology established in the FY 
2011 IPPS/LTCH PPS final rule (75 FR 50422 through 50433), because 
IME Medicare Advantage payments are made to IPPS hospitals under 
section 1886(d) of the Act, we believe these payments must be part 
of these budget neutrality calculations. However, we note that it is 
not necessary to include Medicare Advantage IME payments in the 
outlier threshold calculation or the outlier offset to the 
standardized amount because the statute requires that outlier 
payments be not less than 5 percent nor more than 6 percent of total 
``operating DRG payments,'' which does not include IME and DSH 
payments. We refer readers to the FY 2011 IPPS/LTCH PPS final rule 
for a complete discussion on our methodology of identifying and 
adding the total Medicare Advantage IME payment amount to the budget 
neutrality adjustments.
     Consistent with the methodology in the FY 2012 IPPS/
LTCH PPS final rule, in order to ensure that we capture only fee-
for-service claims, we are only including claims with a ``Claim 
Type'' of 60 (which is a field on the MedPAR file that indicates a 
claim is an FFS claim).
     Consistent with our methodology established in the FY 
2017 IPPS/LTCH PPS final rule (81 FR 57277), in order to further 
ensure that we capture only FFS claims, we are excluding claims with 
a ``GHOPAID'' indicator of 1 (which is a field on the MedPAR file 
that indicates a claim is not an FFS claim and is paid by a Group 
Health Organization).
     Consistent with our methodology established in the FY 
2011 IPPS/LTCH PPS final rule (75 FR 50422 through 50423), we 
examine the MedPAR file and remove pharmacy charges for anti-
hemophilic blood factor (which are paid separately under the IPPS) 
with an indicator of ``3'' for blood clotting with a revenue code of 
``0636'' from the covered charge field for the budget neutrality 
adjustments. We are removing organ acquisition charges, except for 
cases that group to MS-DRG 018, from the covered charge field for 
the budget neutrality adjustments because organ acquisition is a 
pass-through payment not paid under the IPPS. Revenue centers 081X-
089X are typically excluded from ratesetting. However, we are not 
removing revenue center 891 charges from MS-DRG 018 claims during 
ratesetting, because those revenue 891 charges were included in the 
relative weight calculation for MS-DRG 018, which is consistent with 
the policy finalized in FY 2021 final rule (85 FR 58600). We note 
that a new MedPAR variable for revenue code 891 charges was 
introduced in April 2020.

[[Page 49414]]

     For FY 2023, we are continuing to remove allogeneic 
hematopoietic stem cell acquisition charges from the covered charge 
field for budget neutrality adjustments. As discussed in the FY 2021 
IPPS/LTCH PPS final rule, payment for allogeneic hematopoietic stem 
cell acquisition costs is made on a reasonable cost basis for cost 
reporting periods beginning on or after October 1, 2020 (85 FR 58835 
through 58842).
     The participation of hospitals under the BPCI (Bundled 
Payments for Care Improvement) Advanced model started on October 1, 
2018. The BPCI Advanced model, tested under the authority of section 
3021 of the Affordable Care Act (codified at section 1115A of the 
Act), is comprised of a single payment and risk track, which bundles 
payments for multiple services beneficiaries receive during a 
Clinical Episode. Acute care hospitals may participate in the BPCI 
Advanced model in one of two capacities: as a model Participant or 
as a downstream Episode Initiator. Regardless of the capacity in 
which they participate in the BPCI Advanced model, participating 
acute care hospitals would continue to receive IPPS payments under 
section 1886(d) of the Act. Acute care hospitals that are 
Participants also assume financial and quality performance 
accountability for Clinical Episodes in the form of a reconciliation 
payment. For additional information on the BPCI Advanced model, we 
refer readers to the BPCI Advanced web page on the CMS Center for 
Medicare and Medicaid Innovation's website at https://innovation.cms.gov/initiatives/bpci-advanced/.
    For FY 2023, consistent with how we treated hospitals that 
participated in the BPCI Advanced Model in the FY 2021 IPPS/LTCH PPS 
final rule (85 FR 59029 and 59030), as we proposed, we are including 
all applicable data from subsection (d) hospitals participating in 
the BPCI Advanced model in our IPPS payment modeling and ratesetting 
calculations. We believe it is appropriate to include all applicable 
data from the subsection (d) hospitals participating in the BPCI 
Advanced model in our IPPS payment modeling and ratesetting 
calculations because these hospitals are still receiving IPPS 
payments under section 1886(d) of the Act. For the same reasons, as 
we proposed, we included all applicable data from subsection (d) 
hospitals participating in the Comprehensive Care for Joint 
Replacement (CJR) Model in our IPPS payment modeling and ratesetting 
calculations.
     Consistent with our methodology established in the FY 
2013 IPPS/LTCH PPS final rule (77 FR 53687 through 53688), we 
believe that it is appropriate to include adjustments for the 
Hospital Readmissions Reduction Program and the Hospital VBP Program 
(established under the Affordable Care Act) within our budget 
neutrality calculations.
    Both the hospital readmissions payment adjustment (reduction) 
and the hospital VBP payment adjustment (redistribution) are applied 
on a claim-by-claim basis by adjusting, as applicable, the base-
operating DRG payment amount for individual subsection (d) 
hospitals, which affects the overall sum of aggregate payments on 
each side of the comparison within the budget neutrality 
calculations.
    In order to properly determine aggregate payments on each side 
of the comparison, consistent with the approach we have taken in 
prior years, for FY 2023, we are continuing to apply a proxy based 
on the prior fiscal year hospital readmissions payment adjustment 
(for FY 2023 this would be FY 2022 final adjustment factors from 
Table 15 of the FY 2022 IPPS/LTCH PPS final rule) and a proxy based 
on the prior fiscal year hospital VBP payment adjustment (for FY 
2023, this proxy would be an adjustment factor of 1 to reflect our 
policy for the FY 2022 program year to suppress measures and award 
each hospital a value-based payment amount that matches the 
reduction to the base operating DRG payment amount) on each side of 
the comparison, consistent with the methodology that we adopted in 
the FY 2013 IPPS/LTCH PPS final rule (77 FR 53687 through 53688). 
That is, we are applying a proxy readmissions payment adjustment 
factor from the prior final rule and a proxy hospital VBP payment 
adjustment factor from the prior final rule on both sides of our 
comparison of aggregate payments when determining all budget 
neutrality factors described in section II.A.4. of this Addendum.
     The Affordable Care Act also established section 
1886(r) of the Act, which modifies the methodology for computing the 
Medicare DSH payment adjustment beginning in FY 2014. Beginning in 
FY 2014, IPPS hospitals receiving Medicare DSH payment adjustments 
receive an empirically justified Medicare DSH payment equal to 25 
percent of the amount that would previously have been received under 
the statutory formula set forth under section 1886(d)(5)(F) of the 
Act governing the Medicare DSH payment adjustment. In accordance 
with section 1886(r)(2) of the Act, the remaining amount, equal to 
an estimate of 75 percent of what otherwise would have been paid as 
Medicare DSH payments, reduced to reflect changes in the percentage 
of individuals who are uninsured and any additional statutory 
adjustment, would be available to make additional payments to 
Medicare DSH hospitals based on their share of the total amount of 
uncompensated care reported by Medicare DSH hospitals for a given 
time period. In order to properly determine aggregate payments on 
each side of the comparison for budget neutrality, prior to FY 2014, 
we included estimated Medicare DSH payments on both sides of our 
comparison of aggregate payments when determining all budget 
neutrality factors described in section II.A.4. of this Addendum.
    To do this for FY 2023 (as we did for the last 9 fiscal years), 
as we proposed, we are including estimated empirically justified 
Medicare DSH payments that would be paid in accordance with section 
1886(r)(1) of the Act and estimates of the additional uncompensated 
care payments made to hospitals receiving Medicare DSH payment 
adjustments as described by section 1886(r)(2) of the Act. That is, 
we considered estimated empirically justified Medicare DSH payments 
at 25 percent of what would otherwise have been paid, and also the 
estimated additional uncompensated care payments for hospitals 
receiving Medicare DSH payment adjustments on both sides of our 
comparison of aggregate payments when determining all budget 
neutrality factors described in section II.A.4. of this Addendum.
     When calculating total payments for budget neutrality, 
to determine total payments for SCHs, we model total hospital-
specific rate payments and total Federal rate payments and then 
include whichever one of the total payments is greater. As discussed 
in section IV.G. of the preamble to this final rule and later in 
this section, we are continuing to use the FY 2014 finalized 
methodology under which we take into consideration uncompensated 
care payments in the comparison of payments under the Federal rate 
and the hospital-specific rate for SCHs. Therefore, we are including 
estimated uncompensated care payments in this comparison.
     As we proposed, we included an adjustment to the 
standardized amount for those hospitals that are not meaningful EHR 
users in our modeling of aggregate payments for budget neutrality 
for FY 2023. Similar to FY 2022, we are including this adjustment 
based on data on the prior year's performance. Payments for 
hospitals will be estimated based on the applicable standardized 
amount in Tables 1A and 1B for discharges occurring in FY 2023.
     In our determination of all budget neutrality factors 
described in section II.A.4. of this Addendum, we used transfer-
adjusted discharges. Specifically, we calculated the transfer-
adjusted discharges using the statutory expansion of the postacute 
care transfer policy to include discharges to hospice care by a 
hospice program as discussed in section IV.A.2. of the preamble of 
the FY 2020 IPPS/LTCH PPS final rule (84 FR 45239 through 42342).
    We note that prior to FY 2020, the Rural Community Hospital 
(RCH) Demonstration budget neutrality factor was typically applied 
to the standardized amount after all wage index and other budget 
neutrality factors were applied. In the past we completed all the 
wage index budget neutrality factors and then applied the RCH 
Demonstration budget neutrality factor. Beginning with FY 2020, we 
finalized and implemented additional policies in a budget neutral 
manner such as the increase in the wage index values for hospitals 
with a wage index value below the 25th percentile wage index value 
across all hospitals and the transitional wage indexes. When these 
new policies were implemented beginning with FY 2020, the associated 
budget neutrality adjustments were applied to the standardized 
amount after the RCH Demonstration budget neutrality factor was 
applied. Taking into consideration that we are placing a permanent 
cap on wage index decreases beginning FY 2023, we believe the RCH 
Demonstration budget neutrality factor should revert to the order 
prior to FY 2020 and be applied after all wage index and other 
budget neutrality adjustments. Therefore, in the FY 2023 IPPS/LTCH 
proposed rule (87 FR 28659), beginning in FY 2023 we proposed to 
change the ordering of budget

[[Page 49415]]

neutrality factors with the RCH Demonstration budget neutrality 
factor applied after all wage index and other budget neutrality 
factors. We stated that we believe this re-ordering of applying the 
RCH Demonstration budget neutrality factor after all wage index and 
other budget neutrality factors will have a minimal impact and minor 
interactive affects.
    We received no comments on our proposal and therefore are 
finalizing as proposed without modification to change the ordering 
of budget neutrality factors with the RCH Demonstration budget 
neutrality factor applied after all wage index and other budget 
neutrality factors.

a. Reclassification and Recalibration of MS-DRG Relative Weights Before 
Cap

    Section 1886(d)(4)(C)(iii) of the Act specifies that, beginning 
in FY 1991, the annual DRG reclassification and recalibration of the 
relative weights must be made in a manner that ensures that 
aggregate payments to hospitals are not affected. As discussed in 
section II.E of this final rule, we are determining the MS DRG 
relative weights for FY 2023 by averaging the relative weights as 
calculated with and without COVID-19 cases in the FY 2021 data. We 
refer the reader to section II.E.2.c for complete details. As 
discussed in section II.E. of the preamble of this final rule, we 
normalized the recalibrated MS-DRG relative weights by an adjustment 
factor so that the average case relative weight after recalibration 
is equal to the average case relative weight prior to recalibration. 
However, equating the average case relative weight after 
recalibration to the average case relative weight before 
recalibration does not necessarily achieve budget neutrality with 
respect to aggregate payments to hospitals because payments to 
hospitals are affected by factors other than average case relative 
weight. Therefore, as we have done in past years, we are making a 
budget neutrality adjustment to ensure that the requirement of 
section 1886(d)(4)(C)(iii) of the Act is met.
    For this FY 2023 final rule, as we proposed, to comply with the 
requirement that MS-DRG reclassification and recalibration of the 
relative weights be budget neutral for the standardized amount and 
the hospital-specific rates, we used FY 2021 discharge data to 
simulate payments and compared the following:
     Aggregate payments using the FY 2022 labor-related 
share percentages, the FY 2022 relative weights, and the FY 2022 
pre-reclassified wage data, and applied the estimated FY 2023 
hospital readmissions payment adjustments and estimated FY 2023 
hospital VBP payment adjustments; and
     Aggregate payments using the FY 2022 labor-related 
share percentages, the FY 2023 relative weights before applying the 
10-percent cap, and the FY 2022 pre-reclassified wage data, and 
applied the estimated FY 2023 hospital readmissions payment 
adjustments and estimated FY 2023 hospital VBP payment adjustments 
applied previously.
    Because this payment simulation uses the FY 2023 relative 
weights (before application of the 10-percent cap), consistent with 
our policy in section IV.I. of the preamble to this final rule, we 
applied the adjustor for certain cases that group to MS-DRG 018 in 
our simulation of these payments. We note that because the 
simulations of payments for all of the budget neutrality factors 
discussed in this section also use the FY 2023 relative weights, we 
are applying the adjustor for certain MS-DRG 18 cases in all 
simulations of payments for the budget neutrality factors discussed 
later in this section. We refer the reader to section IV.I. of the 
preamble of this final rule for a complete discussion on the 
adjustor for certain cases that group to MS-DRG 018 and to section 
II.E.2.b. of the preamble of this final rule, for a complete 
discussion of the adjustment to the FY 2023 relative weights to 
account for certain cases that group to MS-DRG 018.
    Based on this comparison, we computed a budget neutrality 
adjustment factor and applied this factor to the standardized 
amount. As discussed in section IV. of this Addendum, as we 
proposed, we are applying the MS-DRG reclassification and 
recalibration budget neutrality factor to the hospital-specific 
rates that are effective for cost reporting periods beginning on or 
after October 1, 2022. Please see the table later in this section 
setting forth each of the FY 2023 budget neutrality factors.

b. Budget Neutrality Adjustment for Reclassification and Recalibration 
of MS-DRG Relative Weights With Cap

    As discussed in section II.E.2.d of this final rule, as proposed 
we are establishing a permanent 10-percent cap on the reduction in a 
MS-DRG's relative weight in a given fiscal year, beginning in FY 
2023. As discussed in section II.E.2.d of this final rule, and 
consistent with our current methodology for implementing budget 
neutrality for MS-DRG reclassification and recalibration of the 
relative weights under section 1886(d)(4)(C)(iii) of the Act, we are 
applying a budget neutrality adjustment to the standardized amount 
for all hospitals so that this 10-percent cap on relative weight 
reductions does not increase estimated aggregate Medicare payments 
beyond the payments that would be made had we never applied this 
cap. We refer the reader to section II.E.2.d of this final rule for 
further discussion on our permanent 10-percent cap on the reduction 
in a MS-DRG's relative weight in a given fiscal year, including the 
budget neutrality adjustment to the standardized amount.
    To calculate this budget neutrality adjustment factor for FY 
2023, we used FY 2021 discharge data to simulate payments and 
compared the following:
     Aggregate payments using the FY 2022 labor-related 
share percentages, the FY 2023 relative weights before applying the 
10-percent cap, and the FY 2022 pre-reclassified wage data, and 
applied the estimated FY 2023 hospital readmissions payment 
adjustments and estimated FY 2023 hospital VBP payment adjustments.
     Aggregate payments using the FY 2022 labor-related 
share percentages, the FY 2023 relative weights with the 10-percent 
cap, and the FY 2022 pre-reclassified wage data, and applied the 
estimated FY 2023 hospital readmissions payment adjustments and 
estimated FY 2023 hospital VBP payment adjustments applied 
previously.
    Because this payment simulation uses the FY 2023 relative 
weights, consistent with our policy in section IV.I. of the preamble 
to this final rule, we applied the adjustor for certain cases that 
group to MS-DRG 018 in our simulation of these payments. We note 
that because the simulations of payments for all of the budget 
neutrality factors discussed in this section also use the FY 2023 
relative weights, we are applying the adjustor for certain MS-DRG 18 
cases in all simulations of payments for the budget neutrality 
factors discussed later in this section. We refer the reader to 
section IV.I. of the preamble of this final rule for a complete 
discussion on the adjustor for certain cases that group to MS-DRG 
018 and to section II.E.2.b. of the preamble of this final rule, for 
a complete discussion of the adjustment to the FY 2023 relative 
weights to account for certain cases that group to MS-DRG 018.
    In addition, we applied the MS-DRG reclassification and 
recalibration budget neutrality adjustment factor before the cap 
(derived in the first step) to the payment rates that were used to 
simulate payments for this comparison of aggregate payments from FY 
2022 to FY 2023. Based on this comparison, we computed a budget 
neutrality adjustment factor and applied this factor to the 
standardized amount. As discussed in section IV. of this Addendum, 
we are applying this budget neutrality factor to the hospital-
specific rates that are effective for cost reporting periods 
beginning on or after October 1, 2022. Please see the table later in 
this section setting forth each of the FY 2023 budget neutrality 
factors.

c. Updated Wage Index--Budget Neutrality Adjustment

    Section 1886(d)(3)(E)(i) of the Act requires us to update the 
hospital wage index on an annual basis beginning October 1, 1993. 
This provision also requires us to make any updates or adjustments 
to the wage index in a manner that ensures that aggregate payments 
to hospitals are not affected by the change in the wage index. 
Section 1886(d)(3)(E)(i) of the Act requires that we implement the 
wage index adjustment in a budget neutral manner. However, section 
1886(d)(3)(E)(ii) of the Act sets the labor-related share at 62 
percent for hospitals with a wage index less than or equal to 
1.0000, and section 1886(d)(3)(E)(i) of the Act provides that the 
Secretary shall calculate the budget neutrality adjustment for the 
adjustments or updates made under that provision as if section 
1886(d)(3)(E)(ii) of the Act had not been enacted. In other words, 
this section of the statute requires that we implement the updates 
to the wage index in a budget neutral manner, but that our budget 
neutrality adjustment should not take into account the requirement 
that we set the labor-related share for hospitals with wage indexes 
less than or equal to 1.0000 at the more advantageous level of 62 
percent. Therefore, for purposes of this budget neutrality 
adjustment, section 1886(d)(3)(E)(i) of the Act prohibits us from 
taking into account the fact that hospitals with a wage index less 
than or equal to 1.0000 are paid using a labor-related share of 62 
percent.

[[Page 49416]]

Consistent with current policy, for FY 2023, as we proposed, we are 
adjusting 100 percent of the wage index factor for occupational mix. 
We describe the occupational mix adjustment in section III.E. of the 
preamble of this final rule.
    To compute a budget neutrality adjustment factor for wage index 
and labor-related share percentage changes, we used FY 2021 
discharge data to simulate payments and compared the following:
     Aggregate payments using the FY 2023 relative weights 
and the FY 2022 pre-reclassified wage indexes, applied the FY 2022 
labor-related share of 67.6 percent to all hospitals (regardless of 
whether the hospital's wage index was above or below 1.0000), and 
applied the FY 2023 hospital readmissions payment adjustment and the 
estimated FY 2023 hospital VBP payment adjustment.
     Aggregate payments using the FY 2023 relative weights 
and the FY 2023 pre-reclassified wage indexes, applied the labor-
related share for FY 2023 of 67.6 percent to all hospitals 
(regardless of whether the hospital's wage index was above or below 
1.0000), and applied the same FY 2023 hospital readmissions payment 
adjustments and estimated FY 2023 hospital VBP payment adjustments 
applied previously.
    In addition, we applied the MS-DRG reclassification and 
recalibration budget neutrality adjustment factor before the cap 
(derived in the first step) and the 10-percent cap on relative 
weight reductions adjustment factor (derived from the second step) 
to the payment rates that were used to simulate payments for this 
comparison of aggregate payments from FY 2022 to FY 2023. Based on 
this comparison, we computed a budget neutrality adjustment factor 
and applied this factor to the standardized amount for changes to 
the wage index. Please see the table later in this section for a 
summary of the FY 2023 budget neutrality factors.

d. Reclassified Hospitals--Budget Neutrality Adjustment

    Section 1886(d)(8)(B) of the Act provides that certain rural 
hospitals are deemed urban. In addition, section 1886(d)(10) of the 
Act provides for the reclassification of hospitals based on 
determinations by the MGCRB. Under section 1886(d)(10) of the Act, a 
hospital may be reclassified for purposes of the wage index.
    Under section 1886(d)(8)(D) of the Act, the Secretary is 
required to adjust the standardized amount to ensure that aggregate 
payments under the IPPS after implementation of the provisions of 
sections 1886(d)(8)(B) and (C) and 1886(d)(10) of the Act are equal 
to the aggregate prospective payments that would have been made 
absent these provisions.
    As discussed in section III.G.1. of the preamble of this final 
rule, for FY 2023 and subsequent years, we are finalizing a policy 
to include the wage data of hospitals that have reclassified from 
urban to rural under section 1886(d)(8)(E) of the Act (as 
implemented in the regulations at Sec.  412.103) and have no 
additional form of reclassification (MGCRB or Lugar) in the 
calculation of the rural floor, and to include the wage data of such 
hospitals in the calculation of ``the wage index for rural areas in 
the State in which the county is located'' as referred to in section 
1886(d)(8)(C)(iii) of the Act. We refer the reader to the FY 2015 
IPPS final rule (79 FR 50371 and 50372) for a complete discussion 
regarding the requirement of section 1886(d)(8)(C)(iii) of the Act. 
We further note that the wage index adjustments provided for under 
section 1886(d)(13) of the Act are not budget neutral. Section 
1886(d)(13)(H) of the Act provides that any increase in a wage index 
under section 1886(d)(13) of the Act shall not be taken into account 
in applying any budget neutrality adjustment with respect to such 
index under section 1886(d)(8)(D) of the Act. To calculate the 
proposed budget neutrality adjustment factor for FY 2023, we used FY 
2021 discharge data to simulate payments and compared the following:
     Aggregate payments using the FY 2023 labor-related 
share percentage, the FY 2023 relative weights, and the FY 2023 wage 
data prior to any reclassifications under sections 1886(d)(8)(B) and 
(C) and 1886(d)(10) of the Act, and applied the estimated FY 2023 
hospital readmissions payment adjustments and the estimated FY 2023 
hospital VBP payment adjustments.
     Aggregate payments using the FY 2023 labor-related 
share percentage, the FY 2023 relative weights, and the FY 2023 wage 
data after such reclassifications, and applied the same estimated FY 
2023 hospital readmissions payment adjustments and the estimated FY 
2023 hospital VBP payment adjustments applied previously.
    We note that the reclassifications applied under the second 
simulation and comparison are those listed in Table 2 associated 
with this final rule, which is available via the internet on the CMS 
website. This table reflects reclassification crosswalks for FY 
2023, and applies the policies explained in section III. of the 
preamble of this final rule. Based on this comparison, we computed a 
budget neutrality adjustment factor and applied this factor to the 
standardized amount to ensure that the effects of these provisions 
are budget neutral, consistent with the statute. Please see the 
table later in this section for a summary of the FY 2023 budget 
neutrality factors.
    The FY 2023 budget neutrality adjustment factor was applied to 
the standardized amount after removing the effects of the FY 2022 
budget neutrality adjustment factor. We note that the FY 2023 budget 
neutrality adjustment reflects FY 2023 wage index reclassifications 
approved by the MGCRB or the Administrator at the time of 
development of this final rule.

e. Rural Floor Budget Neutrality Adjustment

    Under Sec.  412.64(e)(4), we make an adjustment to the wage 
index to ensure that aggregate payments after implementation of the 
rural floor under section 4410 of the BBA (Pub. L. 105-33) is equal 
to the aggregate prospective payments that would have been made in 
the absence of this provision. Consistent with section 3141 of the 
Affordable Care Act and as discussed in section III.G. of the 
preamble of this final rule and codified at Sec.  412.64(e)(4)(ii), 
the budget neutrality adjustment for the rural floor is a national 
adjustment to the wage index.
    Similar to our calculation in the FY 2015 IPPS/LTCH PPS final 
rule (79 FR 50369 through 50370), for FY 2023, as we proposed, we 
calculated a national rural Puerto Rico wage index. Because there 
are no rural Puerto Rico hospitals with established wage data, our 
calculation of the FY 2023 rural Puerto Rico wage index is based on 
the policy adopted in the FY 2008 IPPS final rule with comment 
period (72 FR 47323). That is, we use the unweighted average of the 
wage indexes from all CBSAs (urban areas) that are contiguous (share 
a border with) to the rural counties to compute the rural floor (72 
FR 47323; 76 FR 51594). Under the OMB labor market area 
delineations, except for Arecibo, Puerto Rico (CBSA 11640), all 
other Puerto Rico urban areas are contiguous to a rural area. 
Therefore, based on our existing policy, the FY 2023 rural Puerto 
Rico wage index is calculated based on the average of the FY 2023 
wage indexes for the following urban areas: Aguadilla-Isabela, PR 
(CBSA 10380); Guayama, PR (CBSA 25020); Mayaguez, PR (CBSA 32420); 
Ponce, PR (CBSA 38660); San German, PR (CBSA 41900); and San Juan-
Carolina-Caguas, PR (CBSA 41980).
    We also note, as discussed in section III.G.1. of the preamble 
of this final rule, based on the district court's decision in Citrus 
and the comments we received, we are not finalizing our rural floor 
wage index policy as proposed, which would have excluded Sec.  
412.103 hospitals from the calculation of the rural floor and from 
the calculation of ``the wage index for rural areas in the State in 
which the county is located'' as referred to in section 
1886(d)(8)(C)(iii) of the Act. Rather, we are finalizing a policy 
that calculates the rural floor as it was calculated before FY 2020. 
For FY 2023 and subsequent years, we are finalizing a policy to 
include the wage data of hospitals that have reclassified from urban 
to rural under section 1886(d)(8)(E) of the Act (as implemented in 
the regulations at Sec.  412.103) and have no additional form of 
reclassification (MGCRB or Lugar) in the calculation of the rural 
floor, and to include the wage data of such hospitals in the 
calculation of ``the wage index for rural areas in the State in 
which the county is located'' as referred to in section 
1886(d)(8)(C)(iii) of the Act.
    To calculate the national rural floor budget neutrality 
adjustment factor, we used FY 2021 discharge data to simulate 
payments, and the post-reclassified national wage indexes and 
compared the following:
     National simulated payments without the rural floor.
     National simulated payments with the rural floor.
    Based on this comparison, we determined a national rural floor 
budget neutrality adjustment factor. The national adjustment was 
applied to the national wage indexes to produce rural floor budget 
neutral wage indexes. Please see the table later in this section for 
a summary of the FY 2023 budget neutrality factors.
    As further discussed in section III.G.2. of the preamble of this 
final rule, we note that section 9831 of the American Rescue Plan 
Act of 2021 (Pub. L. 117-2), enacted on March 11, 2021 amended 
section

[[Page 49417]]

1886(d)(3)(E)(i) of the Act (42 U.S.C. 1395ww(d)(3)(E)(i)) and added 
section 1886(d)(3)(E)(iv) of the Act to establish a minimum area 
wage index (or imputed floor) for hospitals in all-urban States for 
discharges occurring on or after October 1, 2021. Unlike the imputed 
floor that was in effect from FY 2005 through FY 2018, section 
1886(d)(3)(E)(iv)(III) of the Act provides that the imputed floor 
wage index shall not be applied in a budget neutral manner. 
Specifically, section 9831(b) of Public Law 117-2 amends section 
1886(d)(3)(E)(i) of the Act to exclude the imputed floor from the 
budget neutrality requirement under section 1886(d)(3)(E)(i) of the 
Act. In the past, we budget neutralized the estimated increase in 
payments each year resulting from the imputed floor that was in 
effect from FY 2005 through FY 2018. For FY 2022 and subsequent 
years, in applying the imputed floor required under section 
1886(d)(3)(E)(iv) of the Act, we are applying the imputed floor 
after the application of the rural floor and applying no reductions 
to the standardized amount or to the wage index to fund the increase 
in payments to hospitals in all-urban States resulting from the 
application of the imputed floor. We refer the reader to section 
III.G.2. of the preamble of this final rule for a complete 
discussion regarding the imputed floor.

f. Continuation of the Low Wage Index Hospital Policy--Budget 
Neutrality Adjustment

    As discussed in section III.G.3. of the preamble of this final 
rule, we are continuing for FY 2023 the wage index policy finalized 
in the FY 2020 IPPS/LTCH PPS final rule to address wage index 
disparities by increasing the wage index values for hospitals with a 
wage index value below the 25th percentile wage index value across 
all hospitals (the low wage index hospital policy). As discussed in 
section III.G.3. of this final rule, consistent with our current 
methodology for implementing wage index budget neutrality under 
section 1886(d)(3)(E) of the Act, we are making a budget neutrality 
adjustment to the national standardized amount for all hospitals so 
that the increase in the wage index for hospitals with a wage index 
below the 25th percentile wage index, is implemented in a budget 
neutral manner.
    To calculate this budget neutrality adjustment factor for FY 
2023, we used FY 2021 discharge data to simulate payments and 
compared the following:
     Aggregate payments using the FY 2023 labor-related 
share percentage, the FY 2023 relative weights, and the FY 2023 wage 
index for each hospital before adjusting the wage indexes under the 
low wage index hospital policy, and applied the estimated FY 2023 
hospital readmissions payment adjustments and the estimated FY 2023 
hospital VBP payment adjustments, and the operating outlier 
reconciliation adjusted outlier percentage discussed later in this 
section.
     Aggregate payments using the FY 2023 labor-related 
share percentage, the FY 2023 relative weights, and the FY 2023 wage 
index for each hospital after adjusting the wage indexes under the 
low wage index hospital policy, and applied the same estimated FY 
2023 hospital readmissions payment adjustments and the estimated FY 
2023 hospital VBP payment adjustments applied previously, and the 
operating outlier reconciliation adjusted outlier percentage 
discussed later in this section.
    This FY 2023 budget neutrality adjustment factor was applied to 
the standardized amount.

g. Permanent Cap Policy for the Wage Index--Budget Neutrality 
Adjustment

    As noted previously, in section III.N. of the preamble of this 
final rule, for FY 2023 and subsequent years, we are finalizing as 
proposed to apply a 5-percent cap on any decrease to a hospital's 
wage index from its wage index in the prior FY, regardless of the 
circumstances causing the decline. That is, a hospital's wage index 
for FY 2023 would not be less than 95 percent of its final wage 
index for FY 2022, and that for subsequent years, a hospital's wage 
index would not be less than 95 percent of its final wage index for 
the prior FY. In section III.N.2. of this final rule, we are also 
applying this wage index cap policy in a budget neutral manner 
through an adjustment to the standardized amount to ensure that 
estimated aggregate payments under our wage index cap policy for 
hospitals that will have a decrease in their wage indexes for the 
upcoming fiscal year of more than 5 percent will equal what 
estimated aggregate payments would have been without the wage index 
cap policy. We refer readers to sections III.N.1 and III.N.2 of the 
preamble of this final rule for a complete discussion regarding this 
policy.
    To calculate a wage index cap budget neutrality adjustment 
factor for FY 2023, we used FY 2021 discharge data to simulate 
payments and compared the following:
     Aggregate payments without the 5-percent cap using the 
FY 2023 labor-related share percentages, the FY 2023 relative 
weights, the FY 2023 wage index for each hospital after adjusting 
the wage indexes under the low wage index hospital policy with the 
associated budget neutrality adjustment to the standardized amount, 
and applied the estimated FY 2023 hospital readmissions payment 
adjustments and the estimated FY 2023 hospital VBP payment 
adjustments, and the operating outlier reconciliation adjusted 
outlier percentage discussed later in this section.
     Aggregate payments with the 5-percent cap using the FY 
2023 labor-related share percentages, the FY 2023 relative weights, 
the FY 2023 wage index for each hospital after adjusting the wage 
indexes under the low wage index hospital policy with the associated 
budget neutrality adjustment to the standardized amount, and applied 
the same estimated FY 2023 hospital readmissions payment adjustments 
and the estimated FY 2023 hospital VBP payment adjustments applied 
previously, and the operating outlier reconciliation adjusted 
outlier percentage discussed later in this section.
    We note, Table 2 associated with this final rule contains the 
wage index by provider before and after applying the low wage index 
hospital policy and the cap.

h. Rural Community Hospital Demonstration Program Adjustment

    In section V.K. of the preamble of this final rule, we discuss 
the Rural Community Hospital (RCH) Demonstration program, which was 
originally authorized for a 5-year period by section 410A of the 
Medicare Prescription Drug, Improvement, and Modernization Act of 
2003 (MMA) (Pub. L. 108-173) and extended for another 5-year period 
by sections 3123 and 10313 of the Affordable Care Act (Pub. L. 111-
148). Subsequently, section 15003 of the 21st Century Cures Act 
(Pub. L. 114-255), enacted December 13, 2016, amended section 410A 
of Pub. L. 108-173 to require a 10-year extension period (in place 
of the 5-year extension required by the Affordable Care Act, as 
further discussed later in this section). Finally, Division CC, 
section 128(a) of the Consolidated Appropriations Act of 2021 (Pub. 
L. 116-260) again amended section 410A to require a 15-year 
extension period in place of the 10-year period. We make an 
adjustment to the standardized amount to ensure the effects of the 
RCH Demonstration program are budget neutral as required under 
section 410A(c)(2) of Public Law 108-173. We refer readers to 
section V.K. of the preamble of this final rule for complete details 
regarding the Rural Community Hospital Demonstration.
    With regard to budget neutrality, as mentioned earlier, we make 
an adjustment to the standardized amount to ensure the effects of 
the Rural Community Hospital Demonstration are budget neutral, as 
required under section 410A(c)(2) of Public Law 108-173. For FY 
2023, based on the latest data for this final rule, the total amount 
that we will apply to make an adjustment to the standardized amounts 
to ensure the effects of the Rural Community Hospital Demonstration 
program are budget neutral is $108,439,824. Accordingly, using the 
most recent data available to account for the estimated costs of the 
demonstration program, for FY 2023, we computed a factor for the 
Rural Community Hospital Demonstration budget neutrality adjustment 
that will be applied to the standardized amount. Please see the 
table later in this section for a summary of the FY 2023 budget 
neutrality factors. We refer readers to section V.K. of the preamble 
of this final rule for complete details regarding the calculation of 
the amount we will apply to make an adjustment to the standardized 
amounts.
    The following table is a summary of the FY 2023 budget 
neutrality factors, as discussed in the previous sections.

[[Page 49418]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.214

    As discussed in section II.A. of this final rule, we are using 
the FY 2021 data for FY 2023 ratesetting, with certain modifications 
to our relative weight and outlier methodologies. As discussed 
elsewhere in this final rule and in this Addendum, we solicited 
comments on, as an alternative to our proposed approach, the use of 
the FY 2021 MedPAR claims for purposes of FY 2023 ratesetting 
without these proposed modifications to our usual methodologies. In 
order to facilitate comments on this alternative approach, we made 
available budget neutrality and other ratesetting adjustments 
calculated under this alternative approach, which can be found on 
the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index. We refer the reader to 
section I.O. of Appendix A of this final rule for further discussion 
of the files that we made available with regard to our alternative 
approach.

i. Adjustment for FY 2023 Required Under Section 414 of Public Law 114-
10 (MACRA)

    As stated in the FY 2017 IPPS/LTCH PPS final rule (81 FR 56785), 
once the recoupment required under section 631 of the ATRA was 
complete, we had anticipated making a single positive adjustment in 
FY 2018 to offset the reductions required to recoup the $11 billion 
under section 631 of the ATRA. However, section 414 of the MACRA 
(which was enacted on April 16, 2015) replaced the single positive 
adjustment we intended to make in FY 2018 with a 0.5 percent 
positive adjustment for each of FYs 2018 through 2023. (As noted in 
the FY 2018 IPPS/LTCH PPS proposed and final rules, section 15005 of 
the 21st Century Cures Act (Pub. L. 114-255), which was enacted 
December 13, 2016, reduced the adjustment for FY 2018 from 0.5 
percentage points to 0.4588 percentage points.) Therefore, for FY 
2023, we are implementing the required +0.5 percent adjustment to 
the standardized amount. This is a permanent adjustment to the 
payment rates.

j. Outlier Payments

    Section 1886(d)(5)(A) of the Act provides for payments in 
addition to the basic prospective payments for ``outlier'' cases 
involving extraordinarily high costs. To qualify for outlier 
payments, a case must have costs greater than the sum of the 
prospective payment rate for the MS-DRG, any IME and DSH payments, 
uncompensated care payments, any new technology add-on payments, and 
the ``outlier threshold'' or ``fixed-loss'' amount (a dollar amount 
by which the costs of a case must exceed payments in order to 
qualify for an outlier payment). We refer to the sum of the 
prospective payment rate for the MS-DRG, any IME and DSH payments, 
uncompensated care payments, any new technology add-on payments, and 
the outlier threshold as the outlier ``fixed-loss cost threshold.'' 
(As discussed later in this section, we are also including the 
supplemental payment for eligible IHS/Tribal hospitals and Puerto 
Rico hospitals in the computation of the outlier fixed-loss cost 
threshold beginning in FY 2023.) To determine whether the costs of a 
case exceed the fixed-loss cost threshold, a hospital's CCR is 
applied to the total covered charges for the case to convert the 
charges to estimated costs. Payments for eligible cases are then 
made based on a marginal cost factor, which is a percentage of the 
estimated costs above the fixed-loss cost threshold. The marginal 
cost factor for FY 2023 is 80 percent, or 90 percent for burn MS-
DRGs 927, 928, 929, 933, 934 and 935. We have used a marginal cost 
factor of 90 percent since FY 1989 (54 FR 36479 through 36480) for 
designated burn DRGs as well as a marginal cost factor of 80 percent 
for all other DRGs since FY 1995 (59 FR 45367).
    In accordance with section 1886(d)(5)(A)(iv) of the Act, outlier 
payments for any year are projected to be not less than 5 percent 
nor more than 6 percent of total operating DRG payments (which does 
not include IME and DSH payments) plus outlier payments. When 
setting the outlier threshold, we compute the percent target by 
dividing the total operating outlier payments by the total operating 
DRG payments plus outlier payments. As discussed in the next 
section, for FY 2023, we are incorporating an estimate of outlier 
reconciliation when setting the outlier threshold. We do not include 
any other payments such as IME and DSH within the outlier target 
amount. Therefore, it is not necessary to include Medicare Advantage 
IME payments in the outlier threshold calculation. Section 
1886(d)(3)(B) of the Act requires the Secretary to reduce the 
average standardized amount by a factor to account for the estimated 
proportion of total DRG payments made to outlier cases. More 
information on outlier payments may be found on the CMS website at 
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/outlier.html.

(1) Methodology To Incorporate an Estimate of Outlier Reconciliation in 
the FY 2023 Outlier Fixed-Loss Cost Threshold

    The regulations in 42 CFR 412.84(i)(4) state that any outlier 
reconciliation at cost report settlement will be based on operating 
and capital cost-to-charge ratios (CCRs) calculated based on a ratio 
of costs to charges computed from the relevant cost report and 
charge data determined at the time the cost report coinciding with 
the discharge is settled. We have instructed MACs to identify for 
CMS any instances where: (1) A hospital's actual CCR for the cost 
reporting period fluctuates plus or minus 10 percentage points 
compared to the interim CCR used to calculate outlier payments when 
a bill is processed; and (2) the total outlier payments for the 
hospital exceeded $500,000.00 for that cost reporting period. If we 
determine that a hospital's outlier payments should be reconciled, 
we reconcile both operating and capital outlier payments. We refer 
readers to section 20.1.2.5 of Chapter 3 of the Medicare Claims 
Processing Manual (available on the CMS website at https://www.cms.gov/Regulations-and-Guidance/Guidance/Manuals/Downloads/clm104c03.pdf) for complete details regarding outlier 
reconciliation. The regulation at Sec.  412.84(m) further states 
that at the time of any outlier reconciliation under Sec.  
412.84(i)(4), outlier payments may be adjusted to account for the 
time value of any underpayments or overpayments. Section 20.1.2.6 of 
Chapter 3 of the Medicare Claims Processing Manual contains 
instructions on how to assess the time value of money for reconciled 
outlier amounts.
    If the operating CCR of a hospital subject to outlier 
reconciliation is lower at cost report settlement compared to the 
operating CCR used for payment, the hospital would owe CMS money 
because it received an outlier overpayment at the time of claim 
payment. Conversely, if the operating CCR increases at cost report 
settlement compared to the operating CCR used for payment, CMS would 
owe the hospital money because the hospital outlier payments were 
underpaid.
    In the FY 2020 IPPS/LTCH PPS final rule (84 FR 42623 through 
42635), we finalized a methodology to incorporate outlier 
reconciliation in the FY 2020 outlier fixed

[[Page 49419]]

loss cost threshold. As discussed in the FY 2020 IPPS/LTCH PPS 
proposed rule (84 FR 19592), we stated that rather than trying to 
predict which claims and/or hospitals may be subject to outlier 
reconciliation, we believe a methodology that incorporates an 
estimate of outlier reconciliation dollars based on actual outlier 
reconciliation amounts reported in historical cost reports would be 
a more feasible approach and provide a better estimate and predictor 
of outlier reconciliation for the upcoming fiscal year. We also 
stated that we believe the methodology addresses stakeholder's 
concerns on the impact of outlier reconciliation on the modeling of 
the outlier threshold. For a detailed discussion of additional 
background regarding outlier reconciliation, we refer the reader to 
the FY 2020 IPPS/LTCH PPS final rule.

(a) Incorporating a Projection of Outlier Payment Reconciliations for 
the FY 2023 Outlier Threshold Calculation

    Based on the methodology finalized in the FY 2020 IPPS/LTCH PPS 
final rule (84 FR 42623 through 42625), for FY 2023, as we proposed, 
we are continuing to incorporate outlier reconciliation in the FY 
2023 outlier fixed loss cost threshold.
    As discussed in the FY 2020 IPPS/LTCH PPS final rule, for FY 
2020, we used the historical outlier reconciliation amounts from the 
FY 2014 cost reports (cost reports with a begin date on or after 
October 1, 2013, and on or before September 30, 2014), which we 
believed would provide the most recent and complete available data 
to project the estimate of outlier reconciliation. We refer the 
reader to the FY 2020 IPPS/LTCH PPS final rule (84 FR 42623 through 
42625) for a discussion on the use of the FY 2014 cost report data 
for purposes of projecting outlier payment reconciliations for the 
FY 2020 outlier threshold calculation. For FYs 2021 and 2022, we 
applied the same methodology finalized in FY 2020, using the 
historical outlier reconciliation amounts from the FY 2015 cost 
reports (cost reports with a begin date on or after October 1, 2014, 
and on or before September 30, 2015) and the FY 2016 cost reports 
(cost reports with a begin date on or after October 1, 2015, and on 
or before September 30, 2016), respectively.
    Similar to the FY 2022 methodology, in this final rule, we are 
determining a projection of outlier payment reconciliations for the 
FY 2023 outlier threshold calculation, by advancing the methodology 
by 1 year. Specifically, we are using FY 2017 cost reports (cost 
reports with a begin date on or after October 1, 2016, and on or 
before September 30, 2017).
    For FY 2023, as we proposed, we are using the same methodology 
from FY 2020 to incorporate a projection of operating outlier 
payment reconciliations for the FY 2023 outlier threshold 
calculation. The following steps are the same as those finalized in 
the FY 2020 final rule but with updated data for FY 2023:
    Step 1.--Use the Federal FY 2017 cost reports for hospitals paid 
under the IPPS from the most recent publicly available quarterly 
HCRIS extract available at the time of development of the proposed 
and final rules, and exclude sole community hospitals (SCHs) that 
were paid under their hospital-specific rate (that is, if Worksheet 
E, Part A, Line 48 is greater than Line 47). We note that when there 
are multiple columns available for the lines of the cost report 
described in the following steps and the provider was paid under the 
IPPS for that period(s) of the cost report, then we believe it is 
appropriate to use multiple columns to fully represent the relevant 
IPPS payment amounts, consistent with our methodology for the FY 
2020 final rule.
    Step 2.--Calculate the aggregate amount of historical total of 
operating outlier reconciliation dollars (Worksheet E, Part A, Line 
2.01) using the Federal FY 2017 cost reports from Step 1.
    Step 3.--Calculate the aggregate amount of total Federal 
operating payments using the Federal FY 2017 cost reports from Step 
1. The total Federal operating payments consist of the Federal 
payments (Worksheet E, Part A, Line 1.01 and Line 1.02, plus Line 
1.03 and Line 1.04), outlier payments (Worksheet E, Part A, Line 2 
and Line 2.02), and the outlier reconciliation payments (Worksheet 
E, Part A, Line 2.01). We note that a negative amount on Worksheet 
E, Part A, Line 2.01 for outlier reconciliation indicates an amount 
that was owed by the hospital, and a positive amount indicates this 
amount was paid to the hospital.
    Step 4.--Divide the amount from Step 2 by the amount from Step 3 
and multiply the resulting amount by 100 to produce the percentage 
of total operating outlier reconciliation dollars to total Federal 
operating payments for FY 2017. This percentage amount would be used 
to adjust the outlier target for FY 2023 as described in Step 5.
    Step 5.--Because the outlier reconciliation dollars are only 
available on the cost reports, and not in the Medicare claims data 
in the MedPAR file used to model the outlier threshold, we are 
targeting 5.1 percent minus the percentage determined in Step 4 in 
determining the outlier threshold. Using the FY 2017 cost reports 
based on the December 2021 HCRIS extract, because the aggregate 
outlier reconciliation dollars from Step 2 are negative, we are 
targeting an amount higher than 5.1 percent for outlier payments for 
FY 2023 under our methodology.
    In the FY 2023 proposed rule, we used the December 2021 HCRIS 
extract of the cost report data to calculate the proposed percentage 
adjustment for outlier reconciliation. For the FY 2023 final rule, 
we proposed to use the latest quarterly HCRIS extract that is 
publicly available at the time of the development of that rule 
which, for FY 2023, would be the March 2022 extract. Similar to the 
FY 2022 final rule, we stated that we may also consider the use of 
more recent data that may become available for purposes of 
projecting the estimate of operating outlier reconciliation used in 
the calculation of the final FY 2023 outlier threshold.
    In the FY 2023 proposed rule, based on the December 2021 HCRIS, 
10 hospitals had an outlier reconciliation amount recorded on 
Worksheet E, Part A, Line 2.01 for total operating outlier 
reconciliation dollars of negative $11,939,505 (Step 2). The total 
Federal operating payments based on the December 2021 HCRIS was 
$88,388,722,611 (Step 3). The ratio (Step 4) is a negative 0.013508 
percent, which, when rounded to the second digit, is -0.01 percent. 
Therefore, for FY 2023, we proposed to incorporate a projection of 
outlier reconciliation dollars by targeting an outlier threshold at 
5.11 percent [5.1 percent-(-0.01 percent)].
    When the percentage of operating outlier reconciliation dollars 
to total Federal operating payments rounds to a negative value (that 
is, when the aggregate amount of outlier reconciliation as a percent 
of total operating payments rounds to a negative percent), the 
effect is a decrease to the outlier threshold compared to an outlier 
threshold that is calculated without including this estimate of 
operating outlier reconciliation dollars. In section II.A.4.i.(2). 
of the Addendum to the proposed rule, we provided the proposed FY 
2023 outlier threshold as calculated for the proposed rule both with 
and without including this percentage estimate of operating outlier 
reconciliation.
    As explained in the FY 2020 IPPS/LTCH PPS final rule, we 
finalized the continued use a 5.1 percent target (or an outlier 
offset factor of 0.949) in calculating the outlier offset to the 
standardized amount. In the past, the outlier offset was six 
decimals because we targeted and set the threshold at 5.1 percent by 
adjusting the standardized amount by the outlier offset until 
operating outlier payments divided by total operating Federal 
payments plus operating outlier payments equaled approximately 5.1 
percent (this approximation resulted in an offset beyond 3 
decimals). However, under our methodology, we believe a 3-decimal 
offset of 0.949 reflecting 5.1 percent is appropriate rather than 
the unrounded 6-decimal offset that we have calculated for prior 
fiscal years. Specifically, as discussed in section II.A.5. of this 
Addendum, we proposed to determine an outlier adjustment by applying 
a factor to the standardized amount that accounts for the projected 
proportion of total estimated FY 2023 operating Federal payments 
paid as outliers. Our proposed modification to the outlier threshold 
methodology is designed to adjust the total estimated outlier 
payments for FY 2023 by incorporating the projection of negative 
outlier reconciliation. That is, under this proposal, total 
estimated outlier payments for FY 2023 would be the sum of the 
estimated FY 2023 outlier payments based on the claims data from the 
outlier model and the estimated FY 2023 total operating outlier 
reconciliation dollars. We stated that we believe the proposed 
methodology would more accurately estimate the outlier adjustment to 
the standardized amount by increasing the accuracy of the 
calculation of the total estimated FY 2023 operating Federal 
payments paid as outliers. In other words, the net effect of our 
proposal to incorporate a projection for outlier reconciliation 
dollars into the threshold methodology would be that FY 2023 outlier 
payments (which included the proposed estimated recoupment 
percentage for FY 2023 of 0.01 percent) would be 5.1 percent of 
total operating Federal payments plus total outlier payments. 
Therefore, the proposed

[[Page 49420]]

operating outlier offset to the standardized amount is 0.949 (1-
0.051).
    We invited public comment on our proposed methodology for 
projecting an estimate of outlier reconciliation and incorporating 
that estimate into the modeling for the fixed-loss cost outlier 
threshold for FY 2023.
    We did not receive any comments on the proposed methodology, and 
for the reasons discussed in the proposed rule and in this final 
rule, we are finalizing the methodology described previously for 
incorporating the outlier reconciliation in the outlier threshold 
calculation. Therefore, for this final rule we used the same steps 
described previously and in the proposed rule to incorporate a 
projection of operating outlier payment reconciliations for the 
calculation of the FY 2023 outlier threshold calculation. The March 
2022 HCRIS contained data for 15 hospitals. As stated previously, 
while we proposed to use the March 2022 HCRIS extract to calculate 
the reconciliation adjustment for this FY 2023 IPPS final rule, we 
also stated that similar to the FY 2022 final rule, we may also 
consider the use of more recent data that may become available for 
purposes of projecting the estimate of operating outlier 
reconciliation used in the calculation of the final FY 2023 outlier 
threshold. Data for 2 additional outlier reconciliations were made 
available to CMS outside of the March 2022 HCRIS update. Similar to 
our discussion of the estimated operating outlier reconciliation for 
FY 2021 in the FY 2021 IPPS/LTCH PPS final rule (85 FR 59036) and FY 
2022 in the FY 2022 IPPS/LTCH PPS final rule (86 FR 45535), we 
believe supplementing with 2 hospitals' outlier reconciliation data 
will lend additional accuracy to project the estimate of operating 
outlier reconciliation used in the calculation of the outlier 
threshold. Therefore, in order to use the most complete data for FY 
2017 cost reports, we are using the March 2022 HCRIS extract, 
supplemented by these 2 additional hospitals' data for this FY 2023 
IPPS final rule. Based on March 2022 HCRIS and supplemental data for 
2 hospitals, a total of 17 hospitals had an outlier reconciliation 
amount recorded on Worksheet E, Part A, Line 2.01 for total 
operating outlier reconciliation dollars of negative $17,153,313 
(Step 2). The total Federal operating payments based on the March 
2022 HCRIS and supplemental data for 2 hospitals is $ 88,414,357,653 
(Step 3). The ratio (Step 4) is a negative 0.019401 percent, which, 
when rounded to the second digit, is negative 0.02 percent. 
Therefore, for FY 2023, using the finalized methodology, we 
incorporated a projection of operating IPPS outlier reconciliation 
dollars by targeting an outlier threshold at 5.12 percent [5.1 
percent-(-0.02 percent)]. As noted previously, when the percentage 
of operating outlier reconciliation dollars to total Federal 
operating payments is negative (such is the case when the aggregate 
amount of outlier reconciliation is negative), the effect is a 
decrease to the outlier threshold compared to an outlier threshold 
that is calculated without including this estimate of operating 
outlier reconciliation dollars.

(b) Reduction to the FY 2023 Capital Standard Federal Rate by an 
Adjustment Factor To Account for the Projected Proportion of Capital 
IPPS Payments Paid as Outliers

    We establish an outlier threshold that is applicable to both 
hospital inpatient operating costs and hospital inpatient capital 
related costs (58 FR 46348). Similar to the calculation of the 
adjustment to the standardized amount to account for the projected 
proportion of operating payments paid as outlier payments, as 
discussed in greater detail in section III.A.2. of this Addendum, we 
proposed to reduce the FY 2023 capital standard Federal rate by an 
adjustment factor to account for the projected proportion of capital 
IPPS payments paid as outliers. The regulations in 42 CFR 
412.84(i)(4) state that any outlier reconciliation at cost report 
settlement would be based on operating and capital CCRs calculated 
based on a ratio of costs to charges computed from the relevant cost 
report and charge data determined at the time the cost report 
coinciding with the discharge is settled. As such, any 
reconciliation also applies to capital outlier payments.
    For FY 2023, we proposed to use the same methodology from FY 
2020 to adjust the FY 2023 capital standard Federal rate by an 
adjustment factor to account for the projected proportion of capital 
IPPS payments paid as outliers. Similar to FY 2020, as part of our 
proposal for FY 2023 to incorporate into the outlier model the total 
outlier reconciliation dollars from the most recent and most 
complete fiscal year cost report data, we also proposed to adjust 
our estimate of FY 2023 capital outlier payments to incorporate a 
projection of capital outlier reconciliation payments when 
determining the adjustment factor to be applied to the capital 
standard Federal rate to account for the projected proportion of 
capital IPPS payments paid as outliers (that is, the capital outlier 
payment adjustment factor). To do so, we proposed to use the 
following methodology, which generally parallels the proposed 
methodology to incorporate a projection of operating outlier 
reconciliation payments for the FY 2023 outlier threshold 
calculation.
    Step 1.--Use the Federal FY 2017 cost reports for hospitals paid 
under the IPPS from the most recent publicly available quarterly 
HCRIS extract available at the time of development of the proposed 
and final rules, and exclude SCHs that were paid under their 
hospital-specific rate (that is, if Worksheet E, Part A, Line 48 is 
greater than Line 47). We note that when there are multiple columns 
available for the lines of the cost report described in the 
following steps and the provider was paid under the IPPS for that 
period(s) of the cost report, then we believe it is appropriate to 
use multiple columns to fully represent the relevant IPPS payment 
amounts, consistent with our methodology for the FY 2020 final rule. 
We used the December 2021 HCRIS extract for the proposed rule and we 
stated that we expect to use the March 2022 HCRIS extract for the FY 
2023 final rule. Similar to the FY 2022 final rule, we stated that 
we may also consider the use of more recent data that may become 
available for purposes of projecting the estimate of capital outlier 
reconciliation used in the calculation of the final FY 2023 
adjustment to the FY 2023 capital standard Federal rate.
    Step 2.--Calculate the aggregate amount of the historical total 
of capital outlier reconciliation dollars (Worksheet E, Part A, Line 
93, Column 1) using the Federal FY 2017 cost reports from Step 1.
    Step 3.--Calculate the aggregate amount of total capital Federal 
payments using the Federal FY 2017 cost reports from Step 1. The 
total capital Federal payments consist of the capital DRG payments, 
including capital indirect medical education (IME) and capital 
disproportionate share hospital (DSH) payments (Worksheet E, Part A, 
Line 50, Column 1) and the capital outlier reconciliation payments 
(Worksheet E, Part A, Line 93, Column 1). We note that a negative 
amount on Worksheet E, Part A, Line 93 for capital outlier 
reconciliation indicates an amount that was owed by the hospital, 
and a positive amount indicates this amount was paid to the 
hospital.
    Step 4.--Divide the amount from Step 2 by the amount from Step 3 
and multiply the resulting amount by 100 to produce the percentage 
of total capital outlier reconciliation dollars to total capital 
Federal payments for FY 2017. This percentage amount would be used 
to adjust the estimate of capital outlier payments for FY 2023 as 
described in Step 5.
    Step 5.--Because the outlier reconciliation dollars are only 
available on the cost reports, and not in the specific Medicare 
claims data in the MedPAR file used to estimate outlier payments, we 
proposed that the estimate of capital outlier payments for FY 2023 
would be determined by adding the percentage in Step 4 to the 
estimated percentage of capital outlier payments otherwise 
determined using the shared outlier threshold that is applicable to 
both hospital inpatient operating costs and hospital inpatient 
capital-related costs. (We note that this percentage is added for 
capital outlier payments but subtracted in the analogous step for 
operating outlier payments. We have a unified outlier payment 
methodology that uses a shared threshold to identify outlier cases 
for both operating and capital payments. The difference stems from 
the fact that operating outlier payments are determined by first 
setting a ``target'' percentage of operating outlier payments 
relative to aggregate operating payments which produces the outlier 
threshold. Once the shared threshold is set, it is used to estimate 
the percentage of capital outlier payments to total capital payments 
based on that threshold. Because the threshold is already set based 
on the operating target, rather than adjusting the threshold (or 
operating target), we adjust the percentage of capital outlier to 
total capital payments to account for the estimated effect of 
capital outlier reconciliation payments. This percentage is adjusted 
by adding the capital outlier reconciliation percentage from Step 4 
to the estimate of the percentage of capital outlier payments to 
total capital payments based on the shared threshold.) Because the 
aggregate capital outlier reconciliation dollars from Step 2 are 
negative, the estimate of capital outlier payments for FY 2023 under

[[Page 49421]]

our proposed methodology would be lower than the percentage of 
capital outlier payments otherwise determined using the shared 
outlier threshold.
    Similarly, for the FY 2023 proposed rule, we used the December 
2021 HCRIS extract of the cost report data to calculate the proposed 
percentage adjustment for outlier reconciliation. For this FY 2023 
final rule, we proposed to use the latest quarterly HCRIS extract 
that is publicly available at the time of the development of that 
rule which, for FY 2023, would be the March 2022 extract. As 
previously noted, we stated that may also consider the use of more 
recent data that may become available for purposes of projecting the 
estimate of capital outlier reconciliation used in the calculation 
of the final FY 2023 adjustment to the FY 2023 capital standard 
Federal rate.
    For the FY 2023 proposed rule, the estimated percentage of FY 
2023 capital outlier payments otherwise determined using the shared 
outlier threshold was 5.56 percent (estimated capital outlier 
payments of $394,593,407 divided by (estimated capital outlier 
payments of $394,593,407 plus the estimated total capital Federal 
payment of $6,707,033,365)). Based on the December 2021 HCRIS, 9 
hospitals had an outlier reconciliation amount recorded on Worksheet 
E, Part A, Line 93 for total capital outlier reconciliation dollars 
of negative $759,945 (Step 2). The total Federal capital payments 
based on the December 2021 HCRIS was $7,992,953,494 (Step 3) which 
results in a ratio (Step 4) of -0.01 percent. Therefore, for FY 
2023, taking into account projected capital outlier reconciliation 
payments under our proposed methodology would decrease the estimated 
percentage of FY 2023 aggregate capital outlier payments by 0.01 
percent.
    As discussed in section III.A.2. of this Addendum, we proposed 
to incorporate the capital outlier reconciliation dollars from Step 
5 when applying the outlier adjustment factor in determining the 
capital Federal rate based on the estimated percentage of capital 
outlier payments to total capital Federal rate payments for FY 2023.
    We invited public comment on our proposed methodology for 
projecting an estimate of capital outlier reconciliation and 
incorporating that estimate into the modeling of the estimate of FY 
2023 capital outlier payments for purposes of determining the 
capital outlier adjustment factor.
    We did not receive comments about the proposed capital outlier 
reconciliation methodology. Therefore, we are finalizing the 
methodology for projecting an estimate of capital outlier 
reconciliation as previously described. We stated in the proposed 
rule that while we expect to use the March 2022 HCRIS extract for 
the FY 2023 final rule, similar to the FY 2022 final rule, we may 
also consider the use of more recent data that may become available 
for purposes of projecting the estimate of capital outlier 
reconciliation used in the calculation of the final FY 2023 
adjustment to the FY 2023 capital standard Federal rate. For this 
final rule, for projecting the estimate of capital outlier 
reconciliation, similar to our projection of the estimate of 
operating outlier reconciliation, we are using cost report data of 
12 hospitals from the March 2022 HCRIS supplemented for 2 hospitals 
for a total of 14 hospitals, which we believe will lend additional 
accuracy to the projection of estimated capital outlier 
reconciliation for FY 2023. We note that a difference in the number 
of cost reports for the operating and capital outlier reconciliation 
projections is possible and may be due to new hospitals defined in 
the regulations at 42 CFR 412.300(b) that may receive capital cost-
based payments (in lieu of Federal rate payments), and therefore 
would not receive capital outlier payments. As a result, capital 
outlier reconciliation is not applicable to such hospitals since 
there is no capital outlier payment.
    Based on the March 2022 HCRIS and supplemental data for 2 
hospitals, 14 hospitals had an outlier reconciliation amount 
recorded on Worksheet E, Part A, Line 93 for total capital outlier 
reconciliation dollars of negative $1,101,225 (Step 2). The total 
Federal capital payments based on the March 2022 HCRIS is 
approximately $7,995,731,783 (Step 3). The ratio (Step 4) is a 
negative 0.013773 percent, which, when rounded to the second digit, 
is negative 0.01 percent (Step 4). Therefore, for FY 2023, taking 
into account projected capital outlier reconciliation payments under 
our methodology will decrease the estimated percentage of FY 2023 
aggregate capital outlier payments by 0.01 percent. Accordingly, 
under our methodology as previously discussed, we are applying the 
0.01 percent adjustment to our estimate of the capital outlier 
percentage (described below).
    To determine the FY 2023 IPPS fixed-loss amount (shared 
threshold) in this final rule (as discussed in greater detail later 
in this section), after consideration of public comments we are 
incorporating modifications to our proposed methodology. 
Specifically, one of the modifications we are making is to determine 
the shared threshold as an average of the thresholds calculated when 
including and excluding COVID-19 cases. Because of this averaging, 
it is necessary to make a minor modification to the proposed 
methodology for incorporating the estimate of capital outlier 
reconciliation into the modeling of the estimate of FY 2023 capital 
outlier payments for purposes of determining the capital outlier 
adjustment factor. (We refer the reader to the discussion below in 
section II.A.4.j.(2). of this Addendum for complete details 
regarding the calculation of the shared threshold for FY 2023 based 
on the averaging of the thresholds as calculated including and 
excluding COVID-19 cases.)
    Therefore, to incorporate the estimate of capital outlier 
reconciliation, after calculating the shared threshold based on the 
average of the thresholds as calculated with and without COVID-19 
cases, for this final rule we are using the same steps as described 
in the proposed rule to reduce the FY 2023 capital standard Federal 
rate by an adjustment factor to account for the projected proportion 
of capital IPPS payments paid as outliers. However, with regard to 
Step 5 above, as discussed in more detail below, for this final rule 
we are determining the estimate of capital outlier payments for FY 
2023 by adding the percentage in Step 4 to the estimated percentage 
of capital outlier payments calculated by averaging the estimated 
percentage of capital outlier payments including and excluding 
COVID-19 cases.
    As explained previously, once a shared threshold is set, it is 
used to estimate the percentage of capital outlier payments to total 
capital payments based on that threshold. Therefore, our modified 
methodology produces two separate estimates of the percentage of 
capital outlier payments to total capital payments. One estimate is 
based on the shared threshold that was determined using all cases in 
the FY 2021 claims data, including COVID-19 cases. The other 
estimate is based on the shared threshold that was determined using 
FY 2021 claims data excluding COVID-19 cases. We then averaged these 
two estimates of capital outlier payments to total capital payments 
to estimate the percentage of capital outlier payments in FY 2023 
using the final FY 2023 shared outlier threshold. This approach is 
also consistent with our belief that it is reasonable to assume 
there will be fewer COVID-19 cases in FY 2023 as compared to FY 2021 
(as discussed later in this section and in section I.F of the 
preamble to this final rule).
    For this final rule, we first determined a capital outlier 
percentage of 5.66 percent (estimated capital outlier payments of 
$406,733,862 divided by $7,190,928,057 (estimated capital outlier 
payments of $406,733,862 plus the estimated total capital Federal 
payment of $6,784,194,195)) based on the shared threshold that was 
calculated using all claims, including COVID-19 cases. We next 
determined a capital outlier percentage of 5.40 percent (estimated 
capital outlier payments of $346,066,050 divided by $6,412,816,596 
(estimated capital outlier payments of $346,066,050 plus the 
estimated total capital Federal payment of $6,066,750,547)) based on 
the shared threshold that was calculated excluding COVID-19 cases. 
Therefore, taking the average of these two estimates, we estimate 
capital outlier payments to be 5.53 percent of total capital 
payments prior to incorporating the estimate of capital outlier 
reconciliation. Finally, under our methodology for accounting for 
capital outlier reconciliation as discussed previously, we are 
applying the 0.01 percent adjustment to this estimate of the capital 
outlier percentage as calculated using the average of the two 
estimates based on the shared thresholds including and excluding 
COVID-19 data of 5.53 percent, as previously described. Therefore, 
accounting for estimated capital outlier reconciliation, we estimate 
outlier payments for capital-related PPS payments will equal 5.52 
percent (5.53 percent--0.01 percent) of inpatient capital-related 
payments based on the capital Federal rate in FY 2023.

[[Page 49422]]

(2) FY 2023 Outlier Fixed-Loss Cost Threshold

    In the FY 2014 IPPS/LTCH PPS final rule (78 FR 50977 through 
50983), in response to public comments on the FY 2013 IPPS/LTCH PPS 
proposed rule, we made changes to our methodology for projecting the 
outlier fixed-loss cost threshold for FY 2014. We refer readers to 
the FY 2014 IPPS/LTCH PPS final rule for a detailed discussion of 
the changes.
    As we have done in the past, to calculate the FY 2023 outlier 
threshold, we simulated payments by applying FY 2023 payment rates 
and policies using cases from the FY 2021 MedPAR file. As noted in 
section II.C. of this Addendum, we specify the formula used for 
actual claim payment which is also used by CMS to project the 
outlier threshold for the upcoming fiscal year. The difference is 
the source of some of the variables in the formula. For example, 
operating and capital CCRs for actual claim payment are from the PSF 
while CMS uses an adjusted CCR (as described later in this section) 
to project the threshold for the upcoming fiscal year. In addition, 
charges for a claim payment are from the bill while charges to 
project the threshold are from the MedPAR data with an inflation 
factor applied to the charges (as described earlier).
    In order to determine the proposed FY 2023 outlier threshold, we 
inflated the charges on the MedPAR claims by 2 years, from FY 2021 
to FY 2023. Consistent with the FY 2020 IPPS/LTCH PPS final rule (84 
FR 42626 and 42627), we proposed to use the following methodology to 
calculate the charge inflation factor for FY 2023:
     Include hospitals whose last four digits fall between 
0001 and 0899 (section 2779A1 of Chapter 2 of the State Operations 
Manual on the CMS website at https://www.cms.gov/Regulations-and-Guidance/Guidance/Manuals/Downloads/som107c02.pdf); include CAHs 
that were IPPS hospitals for the time period of the MedPAR data 
being used to calculate the charge inflation factor; include 
hospitals in Maryland; and remove PPS-excluded cancer hospitals who 
have a ``V'' in the fifth position of their provider number or a 
``E'' or ``F'' in the sixth position.
     Include providers that are in both periods of charge 
data that are used to calculate the 1-year average annual rate of-
change in charges per case. We note this is consistent with the 
methodology used since FY 2014.
     We excluded Medicare Advantage IME claims for the 
reasons described in section I.A.4. of this Addendum. We refer 
readers to the FY 2011 IPPS/LTCH PPS final rule for a complete 
discussion on our methodology of identifying and adding the total 
Medicare Advantage IME payment amount to the budget neutrality 
adjustments.
     In order to ensure that we capture only FFS claims, we 
included claims with a ``Claim Type'' of 60 (which is a field on the 
MedPAR file that indicates a claim is an FFS claim).
     In order to further ensure that we capture only FFS 
claims, we excluded claims with a ``GHOPAID'' indicator of 1 (which 
is a field on the MedPAR file that indicates a claim is not an FFS 
claim and is paid by a Group Health Organization).
     We examined the MedPAR file and removed pharmacy 
charges for anti-hemophilic blood factor (which are paid separately 
under the IPPS) with an indicator of ``3'' for blood clotting with a 
revenue code of ``0636'' from the covered charge field. We also 
removed organ acquisition charges from the covered charge field 
because organ acquisition is a pass-through payment not paid under 
the IPPS. As noted previously, we are removing allogeneic 
hematopoietic stem cell acquisition charges from the covered charge 
field for budget neutrality adjustments. As discussed in the FY 2021 
IPPS/LTCH PPS final rule, payment for allogeneic hematopoietic stem 
cell acquisition costs is made on a reasonable cost basis for cost 
reporting periods beginning on or after October 1, 2020 (85 FR 
58835-58842).
     Because this payment simulation uses the FY 2023 
relative weights, consistent with our policy discussed in section 
IV.I. of the preamble to this final rule, we applied the proposed 
adjustor for certain cases that group to MS-DRG 018 in our 
simulation of these payments. As discussed in section II.E.2.b. of 
the preamble of this final rule, we are applying an adjustment to 
account for certain cases that group to MS-DRG 018 in calculating 
the FY 2023 relative weights and for purposes of budget neutrality 
and outlier simulations.
    Our general methodology to inflate the charges computes the 1-
year average annual rate-of-change in charges per case which is then 
applied twice to inflate the charges on the MedPAR claims by 2 years 
since we typically use claims data for the fiscal year that is 2 
years prior to the upcoming fiscal year.
    In the FY 2020 IPPS/LTCH PPS final rule (84 FR 42627), we 
modified our charge inflation methodology. We stated that we believe 
balancing our preference to use the latest available data from the 
MedPAR files and stakeholders' concerns about being able to use 
publicly available MedPAR files to review the charge inflation 
factor can be achieved by modifying our methodology to use the 
publicly available Federal fiscal year period (that is, for FY 2020, 
we used the charge data from Federal fiscal years 2017 and 2018), 
rather than the most recent data available to CMS which, under our 
prior methodology, was based on calendar year data. We refer the 
reader to the FY 2020 IPPS/LTCH PPS final rule for a complete 
discussion regarding this change.
    For FY 2023, under our policy of computing the charge inflation 
factor using the publicly available Federal fiscal year period, we 
would ordinarily use charge data from the MedPAR files for Federal 
fiscal years 2020 and 2021 to compute the 1-year average annual 
rate-of-change in charges per case. Specifically, for the proposed 
rule, we would ordinarily use the December 2020 MedPAR file of FY 
2020 (October 1, 2019, through September 30, 2020) charge data and 
the December 2021 MedPAR file of FY 2021 (October 1, 2021, through 
September 30, 2021) charge data to compute the proposed charge 
inflation factor. However, based on our analysis, the charge 
inflation factors calculated using these two most recently available 
years of MedPAR claims data (FY 2020 and FY 2021) are abnormally 
high as compared to recent historical levels prior to the COVID-19 
PHE period. Specifically, in the proposed rule we stated that we 
calculated a 1-year average annual rate-of-change in charges per 
case of approximately 10 percent based on the FY 2020 and FY 2021 
MedPAR claims data, as compared to approximately 6 percent based on 
the FY 2018 and 2019 MedPAR claims data for the two most recent 
Federal fiscal year time periods prior to the PHE. We stated that we 
believe this abnormally high charge inflation as compared to 
historical levels was partially due to the high number of COVID-19 
cases with higher charges that were treated in IPPS hospitals in FY 
2021. As discussed in section I.F of the preamble of this final 
rule, we believe there will be fewer COVID-19 cases in FY 2023 than 
in FY 2021. Therefore, we do not believe it is reasonable to assume 
charges will continue to increase at these abnormally high rates.
    Therefore, in the FY 2023 IPPS/LTCH proposed rule (87 FR 28667), 
we proposed for FY 2023 to use the same methodology as FY 2020, with 
a proposed modification to use the most recent 1-year average annual 
rate-of-change in charges per case for the period prior to the 
COVID-19 PHE, and based on the same data used in the FY 2021 IPPS/
LTCH PPS final rule to determine the charge inflation factor for the 
proposed rule. We further noted that this is the same data used to 
determine the charge inflation factor for the FY 2022 IPPS/LTCH PPS 
rulemaking. Specifically, for FY 2023, we proposed to use the MedPAR 
files for the two most recent available Federal fiscal year time 
periods prior to the COVID-19 PHE to calculate the charge inflation 
factor. Specifically, for the proposed rule we proposed to use the 
March 2019 MedPAR file of FY 2018 (October 1, 2017, to September 30, 
2018) charge data (released for the FY 2020 IPPS/LTCH PPS final 
rule) and the March 2020 MedPAR file of FY 2019 (October 1, 2018, to 
September 30, 2019) charge data (released for the FY 2021 IPPS/LTCH 
PPS final rule) to compute the proposed charge inflation factor. We 
proposed that for the FY 2023 IPPS/LTCH PPS final rule, we would 
continue to use the charge inflation estimate from the FY 2021 IPPS/
LTCH PPS final rule. Under this proposed methodology, to compute the 
1-year average annual rate-of-change in charges per case for FY 
2023, we compared the average covered charge per case of $61,578.82 
($584,618,863,834/9,493,830 cases) from October 1, 2017, through 
September 31, 2018, to the average covered charge per case of 
$65,522.10 ($604,209,834,327/9,221,466 cases) from October 1, 2018, 
through September 31, 2019. This rate-of-change was 6.4 percent 
(1.06404) or 13.2 percent over 2 years (1.13218). Because we 
proposed to use the FY 2021 MedPAR for the FY 2023 ratesetting, we 
applied a factor of 13.2 percent over 2 years. The billed charges 
are obtained from the claim from the MedPAR file and inflated by the 
inflation factor specified previously.
    In the FY 2023 IPPS/LTCH proposed rule (87 FR 28667-28668), we 
also solicited comments on the alternative approach of

[[Page 49423]]

using the data we would ordinarily use to determine the charge 
inflation factor for purposes of this FY 2023 rule (that is, charge 
data from FYs 2020 and 2021 to compute the 1-year average annual 
rate of change in charges per case), and noted that under this 
alternative approach, if finalized, we would anticipate using more 
recently updated data from FYs 2020 and 2021 for purposes of the FY 
2023 IPPS/LTCH PPS final rule. As previously noted, in order to 
facilitate comments on our alternative approach of using the FY 2021 
MedPAR claims for purposes of FY 2023 ratesetting but without the 
proposed modifications to our usual methodologies, including use of 
the same data that we would ordinarily use for purposes of 
determining the charge inflation factor for this FY 2023 rulemaking, 
and which we stated we may consider finalizing for FY 2023 based on 
consideration of comments received, we made available budget 
neutrality and other ratesetting adjustments, including the charge 
inflation factor, calculated under this alternative approach, which 
can be found on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index. We 
included in a supplemental data file the following: budget 
neutrality factors, charge inflation factor, the CCR adjustment 
factors, an impact file and outlier threshold based on this 
alternative approach. Consistent with historical practice, we stated 
that if we were to finalize this alternative approach, we would use 
the most recent available data for the final rule, as appropriate.
    As discussed previously, in the FY 2023 IPPS/LTCH PPS proposed 
rule (87 FR 28668), we proposed to establish the FY 2023 outlier 
threshold using hospital CCRs from the December 2021 update to the 
Provider-Specific File (PSF), the most recent available data at the 
time of developing the proposed rule. We proposed to apply the 
following edits to providers' CCRs in the PSF. We stated that we 
believe these edits are appropriate in order to accurately model the 
outlier threshold. We first searched for Indian Health Service 
providers and those providers assigned the statewide average CCR 
from the current fiscal year. We then replaced these CCRs with the 
statewide average CCR for the upcoming fiscal year. We also assigned 
the statewide average CCR (for the upcoming fiscal year) to those 
providers that have no value in the CCR field in the PSF or whose 
CCRs exceed the ceilings described later in this section (3.0 
standard deviations from the mean of the log distribution of CCRs 
for all hospitals). We did not apply the adjustment factors 
described later in this section to hospitals assigned the statewide 
average CCR. For FY 2023, we also proposed to continue to apply an 
adjustment factor to the CCRs to account for cost and charge 
inflation (as explained further in this section).
    In the FY 2014 IPPS/LTCH PPS final rule (78 FR 50979), we 
adopted a new methodology to adjust the CCRs. Specifically, we 
finalized a policy to compare the national average case-weighted 
operating and capital CCR from the most recent update of the PSF to 
the national average case-weighted operating and capital CCR from 
the same period of the prior year.
    In the FY 2023 IPPS/LTCH proposed rule (87 FR 28668) we stated 
that ordinarily, for the proposed rule, we would apply a proposed 
adjustment factor to adjust the CCRs from the December 2021 update 
of the PSF by comparing the percentage change in the national 
average case-weighted operating CCR and capital CCR from the 
December 2020 update of the PSF to the national average case-
weighted operating CCR and capital CCR from the December 2021 update 
of the PSF. However, the operating and capital CCR adjustment 
factors based on the data we ordinarily would use are above 1.0. 
Since the implementation of our new methodology to adjust the CCRs 
in the FY 2014 IPPS/LTCH PPS final rule (78 FR 50979), the operating 
and capital CCR adjustment factors have typically been below 1.0 
(for example, operating and capital CCR adjustment factors of 
approximately 1.03 and 1.03, respectively, based on the December 
2020 and December 2021 updates to the PSF as compared to operating 
and capital CCR adjustment factors of approximately 0.97 and 0.96, 
respectively, based on the March 2019 and March 2020 updates to the 
PSF). As stated in section I.F. of the preamble to this final rule, 
we believe this abnormally high CCR adjustment factor as compared to 
historical levels is partially due to the high number of COVID-19 
cases with higher charges that were treated in IPPS hospitals in FY 
2021. As we previously stated, we believe there will be fewer COVID-
19 cases in FY 2023 than in FY 2021. Therefore, we stated that we do 
not believe it is reasonable to assume CCRs will continue to 
increase at these abnormally high rates. Therefore, we proposed to 
adjust the CCRs from the December 2021 update of the PSF by 
comparing the percentage change in the national average case-
weighted operating CCR and capital CCR from the March 2019 update of 
the PSF to the national average case-weighted operating CCR and 
capital CCR from the March 2020 update of the PSF, which is the last 
update of the PSF prior to the PHE. We noted that this is the same 
data used to adjust the CCRs for the FY 2022 IPPS/LTCH PPS 
rulemaking. We stated that we believe using these data for the 
latest available period prior to the PHE, for which the percentage 
change in the national average case weighted operating CCR and 
capital CCR is below 1.0, is appropriate in light of our expectation 
that the CCRs will not continue to increase at these abnormally high 
rates for FY 2023. We noted that we used total transfer-adjusted 
cases from FY 2019 to determine the national average case-weighted 
CCRs for both sides of the comparison. As stated in the FY 2014 
IPPS/LTCH PPS final rule (78 FR 50979), we believe that it is 
appropriate to use the same case count on both sides of the 
comparison, because this would produce the true percentage change in 
the average case-weighted operating and capital CCR from 1 year to 
the next without any effect from a change in case count on different 
sides of the comparison.
    Using the proposed methodology, for the proposed rule, we 
calculated a March 2019 operating national average case-weighted CCR 
of 0.254027 and a March 2020 operating national average case-
weighted CCR of 0.247548. We then calculated the percentage change 
between the two national operating case-weighted CCRs by subtracting 
the March 2019 operating national average case-weighted CCR from the 
March 2020 operating national average case-weighted CCR and then 
dividing the result by the March 2019 national operating average 
case-weighted CCR. This resulted in a proposed 1-year national 
operating CCR adjustment factor of 0.974495. In the proposed rule, 
we noted that because we proposed to use CCRs from the December 2021 
update of the PSF for FY 2023, we applied a 1-year proposed national 
operating CCR adjustment.
    We used this same proposed methodology to adjust the capital 
CCRs. Specifically, we calculated a March 2019 capital national 
average case-weighted CCR of 0.02073 and a March 2020 capital 
national average case-weighted CCR of 0.019935. We then calculated 
the percentage change between the two national capital case-weighted 
CCRs by subtracting the March 2019 capital national average case-
weighted CCR from the March 2020 capital national average case-
weighted CCR and then dividing the result by the March 2019 capital 
national average case-weighted CCR. This resulted in a proposed 1-
year national capital CCR adjustment factor of 0.96165. Because we 
proposed to use CCRs from the December 2021 update of the PSF for FY 
2023, we applied a 1-year proposed national capital CCR adjustment.
    As discussed in section I.F. of the proposed rule and in section 
I.O. of Appendix A of the proposed rule, we solicited comments on an 
alternative approach of using the data that we would ordinarily use 
for purposes of adjusting the CCRs for this FY 2023 rulemaking, 
which we stated we may consider finalizing for FY 2023 based on 
consideration of comments received. As previously noted, in order to 
facilitate comments on our alternative approach of using the FY 2021 
MedPAR claims for purposes of FY 2023 ratesetting but without the 
proposed modifications to our usual methodologies, we made available 
supplemental data files, including the following: budget neutrality 
factors, charge inflation factor, the CCR adjustment factors, and 
outlier threshold based on this alternative approach. Consistent 
with historical practice, we stated in the proposed rule if we were 
to finalize this alternative approach, we would use the most recent 
available data for the final rule, as appropriate.
    For purposes of estimating the proposed outlier threshold for FY 
2023, we used a wage index that reflects the policies discussed in 
the proposed rule. This includes all of the following:
     The proposed frontier State floor adjustments in 
accordance with section 10324(a) of the Affordable Care Act.
     The proposed out-migration adjustment as added by 
section 505 of Public Law 108-173.
     Incorporating the proposed FY 2023 low wage index 
hospital policy (described in section III. G. 4 of the FY 2023 IPPS/
LTCH proposed rule (87 FR 28369)) for hospitals

[[Page 49424]]

with a wage index value below the 25th percentile, where the 
increase in the wage index value for these hospitals would be equal 
to half the difference between the otherwise applicable final wage 
index value for a year for that hospital and the 25th percentile 
wage index value for that year across all hospitals.
     Incorporating our proposed policy (described in section 
III.N. of the preamble of the proposed rule) to apply a 5-percent 
cap on any decrease to a hospital's wage index from its wage index 
in the prior FY, regardless of the circumstances causing the 
decline.
    If we did not take the aforementioned into account, our estimate 
of total FY 2023 payments would be too low, and, as a result, our 
proposed outlier threshold would be too high, such that estimated 
outlier payments would be less than our projected 5.1 percent of 
total payments (which includes outlier reconciliation).
    As described in sections V.K. and V.L., respectively, of the 
preamble of this final rule, sections 1886(q) and 1886(o) of the Act 
establish the Hospital Readmissions Reduction Program and the 
Hospital VBP Program, respectively. We stated in the proposed rule 
that we do not believe that it is appropriate to include the 
proposed hospital VBP payment adjustments and the hospital 
readmissions payment adjustments in the proposed outlier threshold 
calculation or the proposed outlier offset to the standardized 
amount. Specifically, consistent with our definition of the base 
operating DRG payment amount for the Hospital Readmissions Reduction 
Program under Sec.  412.152 and the Hospital VBP Program under Sec.  
412.160, outlier payments under section 1886(d)(5)(A) of the Act are 
not affected by these payment adjustments. Therefore, outlier 
payments would continue to be calculated based on the unadjusted 
base DRG payment amount (as opposed to using the base-operating DRG 
payment amount adjusted by the hospital readmissions payment 
adjustment and the hospital VBP payment adjustment). Consequently, 
we proposed to exclude the estimated hospital VBP payment 
adjustments and the estimated hospital readmissions payment 
adjustments from the calculation of the proposed outlier fixed-loss 
cost threshold.
    We noted in the proposed rule that, to the extent section 
1886(r) of the Act modifies the DSH payment methodology under 
section 1886(d)(5)(F) of the Act, the uncompensated care payment 
under section 1886(r)(2) of the Act, like the empirically justified 
Medicare DSH payment under section 1886(r)(1) of the Act, may be 
considered an amount payable under section 1886(d)(5)(F) of the Act 
such that it would be reasonable to include the payment in the 
outlier determination under section 1886(d)(5)(A) of the Act. As we 
have done since the implementation of uncompensated care payments in 
FY 2014, for FY 2023, we proposed to allocate an estimated per-
discharge uncompensated care payment amount to all cases for the 
hospitals eligible to receive the uncompensated care payment amount 
in the calculation of the outlier fixed-loss cost threshold 
methodology. We stated that we continue to believe that allocating 
an eligible hospital's estimated uncompensated care payment to all 
cases equally in the calculation of the outlier fixed-loss cost 
threshold would best approximate the amount we would pay in 
uncompensated care payments during the year because, when we make 
claim payments to a hospital eligible for such payments, we would be 
making estimated per-discharge uncompensated care payments to all 
cases equally. Furthermore, we stated that we continue to believe 
that using the estimated per-claim uncompensated care payment amount 
to determine outlier estimates provides predictability as to the 
amount of uncompensated care payments included in the calculation of 
outlier payments. Therefore, consistent with the methodology used 
since FY 2014 to calculate the outlier fixed-loss cost threshold, 
for FY 2023, we proposed to include estimated FY 2023 uncompensated 
care payments in the computation of the proposed outlier fixed-loss 
cost threshold. Specifically, we proposed to use the estimated per-
discharge uncompensated care payments to hospitals eligible for the 
uncompensated care payment for all cases in the calculation of the 
proposed outlier fixed-loss cost threshold methodology.
    In addition, as discussed in section IV.E. of the preamble of 
the proposed rule, we proposed to establish a supplemental payment 
for eligible IHS/Tribal hospitals and Puerto Rico hospitals, 
beginning in FY 2023. We proposed to make interim payments of this 
proposed new supplement payment on a per-discharge basis. Consistent 
with the policy of including estimated uncompensated care payments 
in the computation of the proposed outlier fixed-loss cost 
threshold, as previously summarized, we proposed to use our 
authority under section 1886(d)(5)(I) of the Act to include the 
estimated supplemental payments in the computation of the proposed 
outlier fixed-loss cost threshold. Specifically, we proposed to use 
the estimated per-discharge supplemental payments to hospitals 
eligible for the supplemental payment for all cases in the 
calculation of the proposed outlier fixed-loss cost threshold 
methodology.
    Using this methodology, we used the formula described in section 
I.C.1. of this Addendum to simulate and calculate the Federal 
payment rate and outlier payments for all claims. In addition, as 
described in the earlier section to this Addendum, we proposed to 
incorporate an estimate of FY 2023 outlier reconciliation in the 
methodology for determining the outlier threshold. As noted 
previously, for the FY 2023 proposed rule, the ratio of outlier 
reconciliation dollars to total Federal Payments (Step 4) is a 
negative 0.013508 percent, which, when rounded to the second digit, 
is -0.01 percent. Therefore, for FY 2023, we proposed to incorporate 
a projection of outlier reconciliation dollars by targeting an 
outlier threshold at 5.11 percent [5.1 percent-(-.01 percent)]. 
Under this proposed approach, we determined a proposed threshold of 
$43,214 and calculated total outlier payments of $4,709,906,314 and 
total operating Federal payments of $88,837,735,468. We then divided 
total outlier payments by total operating Federal payments plus 
total outlier payments and determined that this threshold matched 
with the 5.11 percent target, which reflected our proposal to 
incorporate an estimate of outlier reconciliation in the 
determination of the outlier threshold (as discussed in more detail 
in the previous section of this Addendum). We noted that, if 
calculated without applying our proposed methodology for 
incorporating an estimate of outlier reconciliation in the 
determination of the outlier threshold, the proposed threshold would 
be $43,292. We proposed an outlier fixed-loss cost threshold for FY 
2023 equal to the prospective payment rate for the MS-DRG, plus any 
IME, empirically justified Medicare DSH payments, estimated 
uncompensated care payment, proposed estimated supplemental payment 
for eligible IHS/Tribal hospitals and Puerto Rico hospitals, and any 
add-on payments for new technology, plus $43,214.
    As previously noted, and as discussed further in section I.O of 
the Appendix A of this final rule, we also considered an alternative 
approach of using the FY 2021 MedPAR claims for purposes of FY 2023 
ratesetting but without the proposed modifications to our usual 
methodologies, including use of the same data we would ordinarily 
use for purposes of this FY 2023 rulemaking to compute the charge 
inflation factors and CCR adjustment factors in determining the FY 
2023 outlier fixed-loss amount for IPPS cases. Under this 
alternative approach, we estimated an outlier threshold of $58,798 
rather than the proposed threshold of $43,214 noted previously.
    Comment: Commenters expressed concern about the increase to the 
fixed-loss threshold for FY 2023. Several commenters acknowledged 
the steps CMS took to account for some of the COVID-19 pandemic-
related factors that have driven the increase, which may not 
continue in FY 2023. Specifically, many commenters supported the use 
of pre-PHE data for charge inflation and CCR adjustment factors.
    Several other commenters opposed the use of the charge inflation 
data and CCR adjustment factors from the period preceding the PHE 
for the following reasons.
     A commenter stated that the use of pre COVID-19 data 
for the charge inflation does not appear to consider the unusually 
high inflation currently facing hospitals. The commenter encouraged 
CMS to recognize that hospitals continue to experience atypical 
costs from COVID-19 care, along with historic inflation levels, 
continued labor shortages, and supply chain disruptions and to fully 
reflect these costs in the data and methodologies used for FY 2023.
     Another commenter believes that the charge inflation 
that has occurred during the PHE will continue as this trend has 
been consistent since before the pandemic.
     Another commenter stated that it does not support the 
use of an inflation factor preceding the COVID-19 PHE as this does 
not accurately reflect today's environment. The commenter stated 
that providers are experiencing the rise of inflation and additional 
costs that are not likely to resolve within the next fiscal year and 
while COVID-

[[Page 49425]]

19 hospitalizations may continue to decline, providers are also 
seeing higher acuity patients, many who delayed care and are now 
sicker and costlier to treat. The commenter recommended that CMS 
reevaluate the use of a pre-COVID-19 inflation factor and instead 
use 2021 data.
    Some commenters supported the use of the FY 2021 claims data. 
Another commenter opposed the use of unadjusted FY 2021 claims data, 
stating that more recent data suggests that there should be far 
fewer high-cost COVID-19 cases in FY 2023 relative to FY 2021. This 
commenter suggested that CMS trim COVID-19 cases with costs that are 
more than three standard deviations from the geometric mean. Several 
other commenters suggested that CMS remove high-cost cases in MS-
DRGs identified as COVID-19 related, while others suggested that CMS 
remove all COVID-19 cases. Other commenters suggested using a blend 
of FY 2019 and FY 2021 data, using a blend of FY 2019 and FY 2020 
data with COVID-19 cases removed, reducing the weight of COVID-19 
cases in the FY 2021 data by 50 percent, using claims data from 
prior to the PHE, or using an average of the current FY 2022 
threshold with the newly proposed threshold. MedPAC suggested 
calculating the FY 2023 fixed-loss amount as an average of the 
outlier fixed-loss amounts calculated with and without COVID-19 
cases in the FY 2021 data. MedPAC believes that this approach would 
be consistent with the approach CMS proposed for calculating the MS-
DRG relative weights and would reflect the assumption that there 
will be fewer COVID-19 cases in FY 2023 as compared to FY 2021.
    A commenter suggested that CMS model the inclusion of NCTAP 
payments and the increased payments for COVID-19 cases provided by 
the CARES Act in the FY 2021 claims data when calculating the fixed-
loss threshold. This commenter stated that conservatively, the PHE 
is anticipated to end no earlier than mid-October 2022, which means 
that NCTAP payments will continue for all of FY 2023. This commenter 
stated that in using the FY 2021 MedPAR data, CMS is assuming that 
COVID-19 hospitalizations in FY 2023 will mirror those in FY 2021, 
which implies that the PHE will be further renewed, and that the 
increased payments for COVID-19 cases provided by the CARES Act will 
continue in FY 2023. (Section 3710 of the CARES Act provides for an 
increase in the MS-DRG weighting factor of 20 percent for an 
individual diagnosed with COVID-19 discharged during the period of 
the PHE for COVID-19.)
    Some commenters suggested that CMS phase in the large proposed 
increase to the fixed-loss threshold over time. Many commenters 
suggested that CMS reexamine its methodology more closely and adopt 
additional changes to offset substantial increases in the outlier 
threshold. A commenter suggested that CMS better account for the 
data anomalies created by the pandemic until patient mix becomes 
more predictable and the data used for ratesetting reflects a more 
stable healthcare environment.
    A commenter stated they believe that inadequate market basket 
updates in prior years and for the upcoming fiscal year do not 
accurately capture increases in costs which also drive increases to 
the outlier threshold. The commenter stated that smaller market 
basket adjustments leave IPPS payments too low, pushing the costs of 
too many claims above the MS-DRG payment amount and driving 
untenable growth in the fixed loss threshold. The commenter 
requested that CMS calculate the final rule outlier threshold using 
a higher market basket percentage increase.
    Response: We appreciate commenters' support regarding the use of 
pre-PHE data for charge inflation and CCR adjustment factors. With 
respect to those commenters that opposed the use of this data, it 
appears that these commenters believe that the charge inflation 
factor is a measure of cost inflation, and that a higher charge 
inflation factor would more accurately account for the costs of 
providing medical care. The charge inflation factor is typically a 
1-year average annual rate-of-change in charges which is applied to 
inflate the charges on the MedPAR claims by 2 years since we 
typically use claims data for the fiscal year that is 2 years prior 
to the upcoming fiscal year. For the reasons discussed in the 
proposed rule, we continue to believe that use of the pre-PHE data 
for the FY 2023 charge inflation and CCR adjustment factors is most 
appropriate given our belief that there will be fewer COVID-19 cases 
in FY 2023 than in FY 2021, based on the information available at 
this time. As mentioned in the proposed rule, the charge inflation 
factors calculated using the two most recently available years of 
MedPAR claims data (FY 2020 and FY 2021) are abnormally high as 
compared to recent historical levels prior to the COVID-19 PHE 
period. With regard to the CCR adjustment factors, the operating and 
capital CCR adjustment factors based on the data we ordinarily would 
use are above 1.0 while the operating and capital CCR adjustment 
factors have typically been below 1.0. We also continue to believe 
that these abnormal charges were partially due to the high number of 
COVID-19 cases with higher charges. Because we anticipate that there 
will be fewer COVID-19 cases in FY 2023 as compared to FY 2021, 
based on the information available at this time and as explained 
previously, we believe the use of the most recent available data 
prior to the COVID-19 PHE is appropriate for FY 2023. We also note 
that lower charges per case due to a lower charge inflation factor 
and lower CCRs based on a CCR adjustment factor below 1 will result 
in lower costs per case and will result in a lower threshold in 
order to ensure outlier payments are 5.1 percent of total payments. 
As discussed in the proposed rule, under the alternative approach of 
using the same data we would ordinarily use for purposes of this FY 
2023 rulemaking to compute the charge inflation factors and CCR 
adjustment factors in determining the FY 2023 outlier fixed-loss 
amount for IPPS cases, we estimated an outlier threshold of $58,798 
rather than the proposed threshold of $43,214.
    With respect to commenters' recommendations of various 
approaches to modify the data or methodology to calculate the fixed-
loss threshold, we continue to recognize that there is uncertainty 
regarding the utilization and costs that hospitals will experience 
in FY 2023. However, based on the information available at this time 
on the trajectory of the COVID-19 PHE, consistent with the 
discussion in section I.F. of the preamble to this final rule, we 
believe averaging the outlier-fixed loss thresholds calculated using 
FY 2021 data including and excluding COVID-19 claims, as suggested 
by MedPAC, would best reflect our belief that it is reasonable to 
assume there will be fewer COVID-19 hospitalizations among Medicare 
beneficiaries in FY 2023 than there were in FY 2021 (as discussed in 
section I.F of the preamble to this final rule). While another 
commenter recommended to reduce the weight of COVID-19 cases in the 
FY 2021 data by 50 percent, we believe that averaging the outlier-
fixed loss thresholds as calculated with and without COVID-19 claims 
in the FY 2021 data as described would be most consistent with the 
approach we proposed and are finalizing for calculating the MS-DRG 
relative weights for FY 2023, as discussed in section II.E.2.c of 
the preamble to this final rule. As discussed below, we are adopting 
the approach suggested by MedPAC when determining the FY 2023 
outlier fixed loss amount.
    With regard to averaging the data with claims pre COVID-19 for 
modeling the fixed loss threshold, we note that the FY 2021 and FY 
2022 thresholds used claims from FY 2019 to set the fixed loss 
threshold. The thresholds in FY 2021 and FY 2022 were $29,064 and 
$30,988 respectively. As noted in the proposed rule, if we made no 
modifications to our methodology to set the FY 2023 fixed loss 
threshold, the proposed fixed loss threshold would have been 
$58,798. Even with our modifications to the methodology that we 
proposed in the FY 2023 IPPS/LTCH proposed rule, the proposed 
threshold was lowered from $58,798 to $43,214. Because of this large 
variance in the thresholds as determined using pre and post COVID-19 
data, we do not believe it would be appropriate to average the data 
used to calculate the threshold with pre COVID-19 data (including, 
as suggested by the commenters, by using a blend of FY 2019 and FY 
2021 data, or using a blend of FY 2019 and FY 2020 data with COVID-
19 cases removed) as we do not believe this approach would provide a 
reasonable estimate of outlier payments for FY 2023 as 5.1 percent 
of estimated total payments for FY 2023.
    We also agree with the commenter that suggested that we include 
the increase in payments for COVID-19 cases provided by the CARES 
Act, based on the information available at this time on the 
trajectory of the COVID-19 PHE. Therefore, we incorporating these 
two suggested modifications to our proposed methodology for 
determining the FY 2023 outlier fixed-loss amount. Specifically, we 
calculated two fixed-loss thresholds, one using FY 2021 claims data 
including COVID-19 cases that reflect the payment increase provided 
by the CARES Act and one using FY 2021 claims data excluding COVID-
19 cases, and then averaged these two fixed-loss thresholds to 
determine the final fixed-loss threshold for

[[Page 49426]]

FY 2023. We believe these adjustments to our proposed methodology 
will best reflect a reasonable estimation of the case mix and 
relative resource use of FY 2023 cases based on the information 
available at this time.
    With respect to the comment that we should include NCTAP 
payments in the COVID-19 cases in the FY 2021 claims data, we note 
that, as stated in the Interim Final Rule Additional Policy and 
Regulatory Revisions in Response to the COVID-19 Public Health 
Emergency (85 FR 71142), the NCTAP will not be included as part of 
the calculation of the operating outlier payments. Therefore, 
including the NCTAP payments in the COVID-19 cases would not impact 
the calculation of the outlier threshold.
    With respect to the comment that CMS phase in the large proposed 
increase to the fixed-loss threshold over time, if we used a phase 
in approach then the fixed loss threshold for FY 2023 would not meet 
the requirement that outlier payments result in 5.1 percent of 
estimated total payments.
    In response to the commenters that suggested that CMS reexamine 
its methodology more closely and adopt additional changes to offset 
substantial increases in the outlier threshold, in addition to the 
proposed modifications in the proposed rule, we are making 
additional changes to the methodology for FY 2023 in this final rule 
in response to comments, specifically the averaging of the two 
fixed-loss thresholds and accounting for the payment increase 
provided by the CARES Act.
    With respect to the commenter that suggested that CMS better 
account for the data anomalies created by the pandemic until patient 
mix becomes more predictable and the data used for ratesetting 
reflects a more stable healthcare environment, as previously 
discussed, we recognize that there is uncertainty regarding the 
utilization and costs that hospitals will experience in FY 2023. 
Therefore, we believe that based on the information available at 
this time on the trajectory of the COVID-19 PHE, our averaging of 
the outlier-fixed loss thresholds as previously described represents 
the best estimate of the fixed loss threshold for FY 2023.
    With respect to commenters who expressed concerns regarding the 
effect of the market basket update on the calculation of the fixed-
loss threshold, we refer readers to section V.A of the preamble of 
this final rule for our response to comments about the market basket 
update. We note, for this final rule, we now have an updated 
forecast of the price proxies underlying the market basket that 
incorporates more recent historical data and reflects a revised 
outlook regarding the U.S. economy (which incorporates more recent 
historical CPI growth, estimated impacts of the Russia/Ukraine war, 
expectations regarding changes to Federal Reserve interest rates, 
and the estimated impacts of continued tight labor markets).
    Comment: A commenter requested that CMS consider whether it is 
appropriate to include extreme cases when calculating the threshold. 
This commenter explained that high charge cases have a significant 
impact on the threshold. The commenter stated that it examined the 
data to understand the factors that drove an increase of over $7,000 
in the threshold between FY 2017 and FY 2022 and stated that it 
observed that the inclusion of extreme cases in the calculation of 
the threshold, the rate of which are increasing over time, 
significantly impacts CMS' determination of the fixed-loss 
threshold. If this trend continues (that is, if the number (and 
proportion) of extreme cases continues to increase each year), the 
commenter stated that the impact of this population of cases on the 
threshold will likewise increase. Thus, the commenter recommended 
that CMS carefully consider what is causing this trend, whether the 
inclusion of these cases in the calculation of the threshold is 
appropriate, or whether a separate outlier mechanism should apply to 
these cases that more closely hews outlier payments to marginal 
costs. The commenter believes this is consistent with the 
calculation process used for IPPS rate setting generally and that a 
2013 OIG Report, Medicare Hospital Outlier Payments Warrant 
Increased Scrutiny, https://oig.hhs.gov/oei/reports/oei-06-10-00520.asp, concurs with this view. Another commenter suggested that 
CMS take steps to ensure that the outlier threshold approximates the 
FY 2022 outlier threshold.
    Response: As we explained when responding to a similar comment 
in the FY 2018 IPPS/LTCH PPS final rule (82 FR 38526), the 
methodology used to calculate the outlier threshold includes all 
claims in order to account for all different types of cases, 
including high charge cases, to ensure that CMS meets the 5.1 
percent target. As the commenter pointed out, the volume of these 
cases continues to rise, making their impact on the threshold 
significant. We believe excluding these cases would artificially 
lower the threshold. We believe it is important to include all cases 
in the calculation of the threshold no matter how high or low the 
charges. Including these cases with high charges lends more accuracy 
to the threshold, as these cases have an impact on the threshold and 
continue to rise in volume. Therefore, we believe the inclusion of 
the high-cost outlier cases in the calculation of the outlier 
threshold is appropriate.
    Also, with regard to the 2013 OIG report that the commenter 
references, this report studied the distribution of outlier payments 
and made recommendations based on the OIG findings, but did not 
mention concerns or make any recommendations with regard to the 
calculation of the outlier threshold. Therefore, we do not agree 
with the commenter that the OIG report concurs with its view.
    Comment: A commenter stated that it believes that ordinarily it 
is important to the process for setting the outlier threshold that 
CMS accurately calculate prior year actual payment comparisons to 
the 5.1 percent target. Without doing so, the commenter stated it is 
impossible for CMS to appropriately modify its methodology to 
achieve an accurate result. The commenter also noted that CMS' 
estimates of past outlier payments also routinely exceed the 
calculations of outlier payments based on HCRIS cost report data. 
The commenter emphasized the importance of CMS using the most recent 
data available to more accurately assess the outlier payment level. 
The commenter stated that CMS has generally fallen short of its 5.1 
percent outlier target virtually every FY since at least 2013 (the 
exceptions being meeting it in FY 2019 and exceeding it during the 
PHE) and yet is still proposing a significant increase in the 
threshold this year with no rationale offered to explain the prior 
years' shortfalls in outlier payments. Another commenter stated that 
to the extent an increase in the fixed loss threshold is necessary, 
it should be limited to the market basket increase.
    Response: As noted previously, section 1886(d)(5)(A)(iv) of the 
Act states that outlier payments may not be not less than 5 percent 
nor more than 6 percent of the total payments projected or estimated 
to be made based on DRG prospective payment rates for discharges in 
that year. With regard to the comment that CMS has generally fallen 
short of its 5.1% outlier target virtually every FY since at least 
2013 (the exceptions being meeting it in FY 2019 and exceeding it 
during the PHE) and yet is still proposing a significant increase in 
the threshold this year with no rationale offered to explain the 
prior year shortfalls in payment, as we have previously stated in 
the FY 2015 IPPS/LTCH PPS final rule (79 FR 50379) and the FY 2016 
IPPS/LTCH PPS final rule (80 FR 49783), when we conduct our modeling 
to determine the outlier threshold, we generally factor in all 
payments and policies that would affect actual payments for the 
current year in order to estimate that outlier payments are 5.1 
percent of total MS-DRG payments. While we recognize that outlier 
payments sometimes are below the 5.1 percent target in prior fiscal 
years, we do not believe that these lower payouts are relevant to 
the current fiscal year because they do not lend greater accuracy to 
the estimate of payments that are 5.1 percent of total MS-DRG 
payments for the upcoming fiscal year for FY 2023. We also note that 
in response to concerns such as the commenters', over the years we 
have modified our outlier threshold calculation by changing the way 
we adjust the CCRs, changing the measure of inflation and 
incorporating an adjustment for outlier reconciliation. While the 
commenter has expressed their concern, we note they have not 
provided any suggestions for how CMS can improve the calculation of 
the outlier threshold (based on the concerns expressed by this 
commenter). As in prior years, CMS will continue to evaluate our 
methodology of calculating the fixed loss threshold and consider any 
suggestions made by the commenters to improve the accuracy of the 
calculation of the outlier threshold.
    We did not receive comments on our proposal to use the estimated 
per-discharge supplemental payments for eligible IHS/Tribal 
hospitals and Puerto Rico hospitals to hospitals eligible for the 
supplemental payment for all cases in the calculation of the 
proposed outlier fixed-loss cost threshold methodology. Therefore, 
we are finalizing as proposed without modification to include the 
estimated per-discharge supplemental payments to hospitals eligible 
for the

[[Page 49427]]

supplemental payment for all cases in the calculation of the 
proposed outlier fixed-loss cost threshold methodology.
    After consideration of the public comments we received, we are 
finalizing the methodology we proposed to calculate the final 
outlier threshold with the two modifications described previously. 
That is, we are using the same methodology as proposed, which 
includes the use of charge inflation data and the CCR adjustment 
factors from the period preceding the PHE, with the modification 
that we calculated two fixed-loss thresholds using this methodology, 
one using FY 2021 claims data including COVID-19 cases that reflect 
the payment increase provided by the CARES Act and one using FY 2021 
claims data excluding COVID-19 cases, and then averaged these two 
fixed-loss thresholds to determine the final fixed-loss threshold 
for FY 2023.
    As discussed previously, we are finalizing as proposed to 
calculate charge inflation using the publicly available FY 2018 and 
FY 2019 claims data and to incorporate a projection of outlier 
payment reconciliations for the FY 2023 outlier threshold 
calculation. For the FY 2023 final outlier threshold, we used the 
March 2019 MedPAR file of FY 2018 (October 1, 2017 through September 
30, 2018) charge data (released in conjunction with the FY 2020 
IPPS/LTCH PPS final rule) and the March 2020 MedPAR file of FY 2019 
(October 1, 2018 through September 30, 2019) charge data (released 
in conjunction with the FY 2021 IPPS/LTCH PPS final rule) to 
determine the charge inflation factor. To compute the 1 year average 
annual rate of change in charges per case, we compared the average 
covered charge per case of $61,578.82 ($584,618,863,834/9,493,830 
cases) from October 1, 2017 through September 31, 2018, to the 
average covered charge per case of $65,522.10 ($604,209,834,327/
9,221,466 cases) from October 1, 2018 through September 31, 2019. 
This rate-of-change was 6.4 percent (1.06404) or 13.2 percent over 2 
years (1.13218) . Because are using the FY 2021 MedPAR for the FY 
2023 ratesetting, we applied a factor of 13.2 percent over 2 years. 
The billed charges are obtained from the claim from the MedPAR file 
and inflated by the inflation factor specified previously.
    For FY 2023, as we have done in the past, we are establishing 
the FY 2023 outlier threshold using hospital CCRs from the March 
2022 update to the Provider-Specific File (PSF); the most recent 
available data at the time of the development of the final rule. We 
applied the following edits to providers' CCRs in the PSF. We 
believe these edits are appropriate in order to accurately model the 
outlier threshold. We first search for Indian Health Service 
providers and those providers assigned the statewide average CCR 
from the current fiscal year. We then replaced these CCRs with the 
statewide average CCR for the upcoming fiscal year. We also assigned 
the statewide average CCR (for the upcoming fiscal year) to those 
providers that have no value in the CCR field in the PSF or whose 
CCRs exceed the ceilings described later in this section (3.0 
standard deviations from the mean of the log distribution of CCRs 
for all hospitals). We did not apply the adjustment factors 
described below to hospitals assigned the statewide average CCR. For 
FY 2023, we also are continuing to apply an adjustment factor to the 
CCRs to account for cost and charge inflation (as explained below).
    As previously discussed, ordinarily, for the final rule, using 
the latest available data at the time of this final rule, we would 
apply an adjustment factor to adjust the CCRs from the March 2022 
update of the PSF by comparing the percentage change in the national 
average case-weighted operating CCR and capital CCR from the March 
2021 update of the PSF to the national average case-weighted 
operating CCR and capital CCR from the March 2022 update of the PSF. 
However, for the reasons as previously discussed, we are finalizing 
as proposed to adjust the CCRs from the March 2022 update of the PSF 
by comparing the percentage change in the national average case-
weighted operating CCR and capital CCR from the March 2019 update of 
the PSF to the national average case-weighted operating CCR and 
capital CCR from the March 2020 update of the PSF, which is the last 
update of the PSF prior to the PHE. We note that this is the same 
data used to adjust the CCRs for the FY 2022 IPPS/LTCH PPS 
rulemaking. As previously stated, we believe using these data for 
the latest available period prior to the PHE, for which the 
percentage change in the national average case weighted operating 
CCR and capital CCR is below 1.0, is appropriate in light of our 
expectation that the CCRs will not continue to increase at these 
abnormally high rates for FY 2023. We note that we used total 
transfer-adjusted cases from FY 2019 to determine the national 
average case-weighted CCRs for both sides of the comparison. As 
stated in the FY 2014 IPPS/LTCH PPS final rule (78 FR 50979), we 
believe that it is appropriate to use the same case count on both 
sides of the comparison, because this would produce the true 
percentage change in the average case-weighted operating and capital 
CCR from 1 year to the next without any effect from a change in case 
count on different sides of the comparison.
    Using this methodology, for this final rule, we calculated a 
March 2019 operating national average case-weighted CCR of 0.254027 
and a March 2020 operating national average case-weighted CCR of 
0.247548. We then calculated the percentage change between the two 
national operating case-weighted CCRs by subtracting the March 2019 
operating national average case-weighted CCR from the March 2020 
operating national average case-weighted CCR and then dividing the 
result by the March 2019 national operating average case-weighted 
CCR. This resulted in a 1-year national operating CCR adjustment 
factor of 0.974495. Similar to the proposed rule, because we are 
using CCRs from the March 2022 update of the PSF for FY 2023, we 
applied a 1-year national operating CCR adjustment.
    We used this same methodology to adjust the capital CCRs. 
Specifically, we calculated a March 2019 capital national average 
case-weighted CCR of 0.02073 and a March 2020 capital national 
average case-weighted CCR of 0.019935. We then calculated the 
percentage change between the two national capital case-weighted 
CCRs by subtracting the March 2019 capital national average case-
weighted CCR from the March 2020 capital national average case-
weighted CCR and then dividing the result by the March 2019 capital 
national average case-weighted CCR. This resulted in a 1-year 
national capital CCR adjustment factor of 0.96165. Similar to the 
proposed rule, because we use CCRs from the March 2022 update of the 
PSF for FY 2023, we applied a 1-year national capital CCR 
adjustment.
    As discussed previously, consistent with the proposed rule, for 
FY 2023, we applied the following policies (as discussed in more 
detail earlier):
     We used a wage index based on the FY 2023 wage index 
that hospitals will be paid. This included our final policy to 
include the wage data of hospitals that have reclassified from urban 
to rural under section 1886(d)(8)(E) of the Act (as implemented in 
the regulations at Sec.  412.103) in the calculation of the rural 
floor (see section III.G.1. of the preamble of this final rule for a 
complete discussion on this policy); application of the imputed 
floor adjustment, the frontier State floor adjustment in accordance 
with section 10324(a) of the Affordable Care Act, and the out 
migration adjustment as added by section 505 of Public Law 108-173; 
and application of our wage index policies to: (1) increase the wage 
index values for hospitals with a wage index value below the 25th 
percentile wage index value across all hospitals, and (2) apply a 5-
percent cap on any decrease to a hospital's wage index from its wage 
index in the prior FY, regardless of the circumstances causing the 
decline (described in section III. N of the preamble of this final 
rule). As stated previously, if we did not take the above into 
account, our estimate of total FY 2023 payments would be too low, 
and, as a result, our outlier threshold would be too high, such that 
estimated outlier payments would be less than our projected 5.12 
percent of total payments (which reflects the estimate of outlier 
reconciliation calculated for this final rule).
     We excluded the hospital VBP payment adjustments and 
the hospital readmissions payment adjustments from the calculation 
of the outlier fixed-loss cost threshold.
     We used the estimated per-discharge uncompensated care 
payments to hospitals eligible for the uncompensated care payment 
for all cases in the calculation of the outlier fixed-loss cost 
threshold methodology.
     Based on the policy finalized, as previously described, 
we used the estimated per-discharge supplemental payments to 
hospitals eligible for the supplemental payment for all cases in the 
calculation of the proposed outlier fixed-loss cost threshold 
methodology.
    Using this methodology, we used the formula described in section 
I.C.1 of this Addendum to simulate and calculate the Federal payment 
rate and outlier payments for all claims. In addition, as described 
in the earlier section to this Addendum, we are finalizing to 
incorporate an estimate of FY 2023 outlier reconciliation in the 
methodology for determining the outlier threshold. As noted 
previously, for this FY

[[Page 49428]]

2023 final rule, the ratio of outlier reconciliation dollars to 
total Federal Payments (Step 4) is a negative 0.019401 percent, 
which when rounded to the second digit, is 0.02 percent. Therefore, 
for FY 2023, we incorporated a projection of outlier reconciliation 
dollars by targeting an outlier threshold at 5.12 percent [5.1 
percent-(0.02 percent)].
    As previously discussed, after consideration of the comments we 
received, we are modifying elements of our calculation of the fixed-
loss threshold by averaging the fixed-loss thresholds calculated 
including and excluding COVID-19 cases in the FY 2021 claims data. 
We also agreed with the commenter's suggestion that we include the 
payment increase for COVID-19 cases provided by the CARES Act. As 
discussed previously, we calculated two fixed-loss thresholds, one 
using FY 2021 claims data including COVID-19 cases that reflect the 
payment increase provided by the CARES Act and one using FY 2021 
claims data excluding COVID-19 cases, and then averaged these two 
fixed-loss thresholds to determine the final fixed-loss threshold 
for FY 2023.
    Based on this finalized averaging approach, the following are 
the steps we used to determine the final fixed-loss threshold for FY 
2023 using FY 2021 claims data.
    Step 1: Using all claims, which included COVID-19 cases and 
incorporating the payment increase provided by the CARES Act, we 
determined a threshold of $39,389 and calculated total outlier 
payments of $4,658,400,549 and total operating Federal payments of 
$86,325,462,972. We then divided total outlier payments by total 
operating Federal payments plus total outlier payments and 
determined that this threshold matched with the 5.12 percent target, 
which reflects our methodology to incorporate an estimate of outlier 
reconciliation in the determination of the outlier threshold (as 
discussed in more detail in the previous section of this Addendum).
    Step 2: Excluding COVID-19 cases, we determined a threshold of 
$38,328 and calculated total outlier payments of $4,073,729,554 and 
total operating Federal payments of $75,488,568,943. We then divided 
total outlier payments by total operating Federal payments plus 
total outlier payments and determined that this threshold matched 
with the 5.12 percent target, which reflects our methodology to 
incorporate an estimate of outlier reconciliation in the 
determination of the outlier threshold (as discussed in more detail 
in the previous section of this Addendum).
    Step 3: We averaged the two fixed-loss thresholds from steps 1 
and 2 to determine a final fixed-loss threshold for FY 2023 of 
$38,859 (($39,389 + $38,328)/2)).
    We are finalizing an outlier fixed-loss cost threshold for FY 
2023 equal to the prospective payment rate for the MS-DRG, plus any 
IME, empirically justified Medicare DSH payments, estimated 
uncompensated care payment, estimated supplemental payment for 
eligible IHS/Tribal hospitals and Puerto Rico hospitals and any 
addon payments for new technology, plus $38,859.
    Comment: A commenter stated that the COVID-19 PHE increased case 
acuity and payments due to the suspension of the 2% sequestration. 
Therefore, the commenter recommended that payments should be 
adjusted from the FY 2022 estimated outlier threshold because of the 
temporal nature of these additional payments.
    Response: We appreciate the commenter's input. The sequestration 
reduction is a 2-percent reduction to overall payments and is 
applied after calculating individual payments such as outlier 
payments. Therefore, CMS has not made any adjustments that consider 
the 2-percent reduction in our modeling of outlier payments. As a 
result, no change to the outlier model for FY 2023 is necessary. 
With regard to the commenter noting the increased case acuity, we 
refer the reader to section I.F. of this FY 2023 IPPS/LTCH final 
rule for a discussion of our final policy .

(3) Other Changes Concerning Outliers

    As stated in the FY 1994 IPPS final rule (58 FR 46348), we 
establish an outlier threshold that is applicable to both hospital 
inpatient operating costs and hospital inpatient capital-related 
costs. When we modeled the combined operating and capital outlier 
payments, we found that using a common threshold resulted in a 
higher percentage of outlier payments for capital-related costs than 
for operating costs. We project that the threshold for FY 2023 
(which reflects our methodology to incorporate an estimate of 
operating outlier reconciliation) would result in operating outlier 
payments that would equal 5.1 percent of operating DRG payments. As 
discussed previously, once an outlier threshold is set, it is used 
to estimate the percentage of capital outlier payments to total 
capital payments based on that threshold. Therefore, our modified 
methodology produces two separate estimates of the percentage of 
capital outlier payments to total capital payments. One estimate is 
based on the shared threshold that was determined using all cases in 
the FY 2021 data. The other estimate is based on the shared 
threshold that was determined excluding COVID-19 cases in the FY 
2021 data. As stated, we averaged these two estimates together to 
establish the final estimate of capital outlier payments to total 
capital payments for FY 2023. Therefore, based on this finalized 
methodology to average these two estimates, we estimate that capital 
outlier payments would equal 5.52 percent of capital payments based 
on the Federal rate (which reflects our methodology discussed 
previously to incorporate an estimate of capital outlier 
reconciliation).
    In accordance with section 1886(d)(3)(B) of the Act and as 
discussed previously, we are reducing the FY 2023 standardized 
amount by 5.1 percent to account for the projected proportion of 
payments paid as outliers.
    The outlier adjustment factors that would be applied to the 
operating standardized amount and capital Federal rate based on the 
FY 2023 outlier threshold are as follows:
[GRAPHIC] [TIFF OMITTED] TR10AU22.215

    We are applying the outlier adjustment factors to the FY 2023 
payment rates after removing the effects of the FY 2022 outlier 
adjustment factors on the standardized amount.
    To determine whether a case qualifies for outlier payments, we 
currently apply hospital-specific CCRs to the total covered charges 
for the case. Estimated operating and capital costs for the case are 
calculated separately by applying separate operating and capital 
CCRs. These costs are then combined and compared with the outlier 
fixed-loss cost threshold.
    Under our current policy at Sec.  412.84, we calculate operating 
and capital CCR ceilings and assign a statewide average CCR for 
hospitals whose CCRs exceed 3.0 standard deviations from the mean of 
the log distribution of CCRs for all hospitals. Based on this 
calculation, for hospitals for which the MAC computes operating CCRs 
greater than 1.224 or capital CCRs greater than 0.134 or hospitals 
for which the MAC is unable to calculate a CCR (as described under 
Sec.  412.84(i)(3) of our regulations), statewide average CCRs are 
used to determine whether a hospital qualifies for outlier payments. 
Table 8A listed in section VI. of this Addendum (and available via 
the internet on the CMS website) contains the statewide average 
operating CCRs for urban hospitals and for rural hospitals for which 
the MAC is unable to compute a hospital-specific CCR within the 
range previously specified. These statewide average ratios would be 
effective for discharges occurring on or after October 1, 2022, and 
would replace the statewide average ratios from the prior fiscal 
year. Table 8B listed in section VI. of this Addendum (and available 
via the internet on the CMS website) contains the comparable 
statewide average capital CCRs. As previously stated, the CCRs in 
Tables 8A and 8B would be used during FY 2023 when hospital-specific 
CCRs based on the latest settled cost report either are not 
available or are outside the range noted previously. Table

[[Page 49429]]

8C listed in section VI. of this Addendum (and available via the 
internet on the CMS website) contains the statewide average total 
CCRs used under the LTCH PPS as discussed in section V. of this 
Addendum.
    We finally note that section 20.1.2 of chapter three of the 
Medicare Claims Processing Manual (on the internet at https://www.cms.gov/Regulations-and-Guidance/Guidance/Manuals/Downloads/clm104c03.pdf) covers an array of topics, including CCRs, 
reconciliation, and the time value of money. We encourage hospitals 
that are assigned the statewide average operating and/or capital 
CCRs to work with their MAC on a possible alternative operating and/
or capital CCR as explained in the manual. Use of an alternative CCR 
developed by the hospital in conjunction with the MAC can avoid 
possible overpayments or underpayments at cost report settlement, 
thereby ensuring better accuracy when making outlier payments and 
negating the need for outlier reconciliation. We also note that a 
hospital may request an alternative operating or capital CCR at any 
time as long as the guidelines of the manual are followed. In 
addition, the manual outlines the outlier reconciliation process for 
hospitals and Medicare contractors. We refer hospitals to the manual 
instructions for complete details on outlier reconciliation.

(4) FY 2021 Outlier Payments

    Our current estimate, using available FY 2021 claims data, is 
that actual outlier payments for FY 2021 were approximately 5.66 
percent of actual total MS-DRG payments. Therefore, the data 
indicate that, for FY 2021, the percentage of actual outlier 
payments relative to actual total payments is higher than we 
projected for FY 2021. Consistent with the policy and statutory 
interpretation we have maintained since the inception of the IPPS, 
we do not make retroactive adjustments to outlier payments to ensure 
that total outlier payments for FY 2021 are equal to 5.1 percent of 
total MS-DRG payments. As explained in the FY 2003 Outlier final 
rule (68 FR 34502), if we were to make retroactive adjustments to 
all outlier payments to ensure total payments are 5.1 percent of MS-
DRG payments (by retroactively adjusting outlier payments), we would 
be removing the important aspect of the prospective nature of the 
IPPS. Because such an across-the-board adjustment would either lead 
to more or less outlier payments for all hospitals, hospitals would 
no longer be able to reliably approximate their payment for a 
patient while the patient is still hospitalized. We believe it would 
be neither necessary nor appropriate to make such an aggregate 
retroactive adjustment. Furthermore, we believe it is consistent 
with the statutory language at section 1886(d)(5)(A)(iv) of the Act 
not to make retroactive adjustments to outlier payments. This 
section states that outlier payments be equal to or greater than 5 
percent and less than or equal to 6 percent of projected or 
estimated (not actual) MS-DRG payments. We believe that an important 
goal of a PPS is predictability. Therefore, we believe that the 
fixed-loss outlier threshold should be projected based on the best 
available historical data and should not be adjusted retroactively. 
A retroactive change to the fixed-loss outlier threshold would 
affect all hospitals subject to the IPPS, thereby undercutting the 
predictability of the system as a whole.
    We note that, because the MedPAR claims data for the entire FY 
2022 period would not be available until after September 30, 2022, 
we are unable to provide an estimate of actual outlier payments for 
FY 2022 based on FY 2022 claims data in the proposed rule and this 
final rule. We will provide an estimate of actual FY 2022 outlier 
payments in the FY 2024 IPPS/LTCH PPS proposed rule.

5. FY 2023 Standardized Amount

    The adjusted standardized amount is divided into labor-related 
and nonlabor-related portions. Tables 1A and 1B listed and published 
in section VI. of this Addendum (and available via the internet on 
the CMS website) contain the national standardized amounts that we 
are applying to all hospitals, except hospitals located in Puerto 
Rico, for FY 2023. The standardized amount for hospitals in Puerto 
Rico is shown in Table 1C listed and published in section VI. of 
this Addendum (and available via the internet on the CMS website). 
The amounts shown in Tables 1A and 1B differ only in that the labor-
related share applied to the standardized amounts in Table 1A is 
67.6 percent, and the labor-related share applied to the 
standardized amounts in Table 1B is 62 percent. In accordance with 
sections 1886(d)(3)(E) and 1886(d)(9)(C)(iv) of the Act, we are 
applying a labor-related share of 62 percent, unless application of 
that percentage would result in lower payments to a hospital than 
would otherwise be made. In effect, the statutory provision means 
that we would apply a labor-related share of 62 percent for all 
hospitals whose wage indexes are less than or equal to 1.0000.
    In addition, Tables 1A and 1B include the standardized amounts 
reflecting the applicable percentage increases for FY 2023.
    The labor-related and nonlabor-related portions of the national 
average standardized amounts for Puerto Rico hospitals for FY 2023 
are set forth in Table 1C listed and published in section VI. of 
this Addendum (and available via the internet on the CMS website). 
Similarly, section 1886(d)(9)(C)(iv) of the Act, as amended by 
section 403(b) of Public Law 108-173, provides that the labor-
related share for hospitals located in Puerto Rico be 62 percent, 
unless the application of that percentage would result in lower 
payments to the hospital.
    The following table illustrates the changes from the FY 2022 
national standardized amounts to the FY 2023 national standardized 
amounts. The second through fifth columns display the changes from 
the FY 2022 standardized amounts for each applicable FY 2023 
standardized amount. The first row of the table shows the updated 
(through FY 2022) average standardized amount after restoring the FY 
2022 offsets for outlier payments, geographic reclassification, 
rural demonstration, lowest quartile, and transition budget 
neutrality. The MS-DRG reclassification and recalibration, wage 
index, and stem cell acquisition budget neutrality factors are 
cumulative (that is, we have not restored the offsets). Accordingly, 
those FY 2022 adjustment factors have not been removed from the base 
rate in the following table. Additionally, for FY 2023 we have 
applied the budget neutrality factors for the lowest quartile 
hospital policy, described previously.

[[Page 49430]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.216


[[Page 49431]]



B. Adjustments for Area Wage Levels and Cost-of-Living

    Tables 1A through 1C, as published in section VI. of this 
Addendum (and available via the internet on the CMS website), 
contain the labor-related and nonlabor-related shares that we are 
using to calculate the prospective payment rates for hospitals 
located in the 50 States, the District of Columbia, and Puerto Rico 
for FY 2023. This section addresses two types of adjustments to the 
standardized amounts that are made in determining the prospective 
payment rates as described in this Addendum.

1. Adjustment for Area Wage Levels

    Sections 1886(d)(3)(E) and 1886(d)(9)(C)(iv) of the Act require 
that we make an adjustment to the labor-related portion of the 
national prospective payment rate to account for area differences in 
hospital wage levels. This adjustment is made by multiplying the 
labor-related portion of the adjusted standardized amounts by the 
appropriate wage index for the area in which the hospital is 
located. For FY 2023, as discussed in section IV.B.3. of the 
preamble of this final rule, we are applying a labor-related share 
of 67.6 percent for the national standardized amounts for all IPPS 
hospitals (including hospitals in Puerto Rico) that have a wage 
index value that is greater than 1.0000. Consistent with section 
1886(d)(3)(E) of the Act, we are applying the wage index to a labor-
related share of 62 percent of the national standardized amount for 
all IPPS hospitals (including hospitals in Puerto Rico) whose wage 
index values are less than or equal to 1.0000. In section III. of 
the preamble of this final rule, we discuss the data and methodology 
for the FY 2023 wage index.

2. Adjustment for Cost-of-Living in Alaska and Hawaii

    Section 1886(d)(5)(H) of the Act provides discretionary 
authority to the Secretary to make adjustments as the Secretary 
deems appropriate to take into account the unique circumstances of 
hospitals located in Alaska and Hawaii. Higher labor-related costs 
for these two States are taken into account in the adjustment for 
area wages described previously. To account for higher non-labor 
related costs for these two States, we multiply the nonlabor-related 
portion of the standardized amount for hospitals in Alaska and 
Hawaii by an adjustment factor.
    In the FY 2013 IPPS/LTCH PPS final rule, we established a 
methodology to update the COLA factors for Alaska and Hawaii that 
were published by the U.S. Office of Personnel Management (OPM) 
every 4 years (at the same time as the update to the labor related 
share of the IPPS market basket), beginning in FY 2014. We refer 
readers to the FY 2013 IPPS/LTCH PPS proposed and final rules for 
additional background and a detailed description of this methodology 
(77 FR 28145 through 28146 and 77 FR 53700 through 53701, 
respectively). For FY 2022, in the FY 2022 IPPS/LTCH PPS final rule 
(86 FR 45546 through 45547), we updated the COLA factors published 
by OPM for 2009 (as these are the last COLA factors OPM published 
prior to transitioning from COLAs to locality pay) using the 
methodology that we finalized in the FY 2013 IPPS/LTCH PPS final 
rule. Based on the policy finalized in the FY 2013 IPPS/LTCH PPS 
final rule, we are continuing to use the same COLA factors in FY 
2023 that were used in FY 2022 to adjust the nonlabor-related 
portion of the standardized amount for hospitals located in Alaska 
and Hawaii. The following table lists the COLA factors for FY 2023.
[GRAPHIC] [TIFF OMITTED] TR10AU22.217

    Lastly, as we finalized in the FY 2013 IPPS/LTCH PPS final rule 
(77 FR 53700 and 53701), we intend to update the COLA factors based 
on our methodology every 4 years, at the same time as the update to 
the labor-related share of the IPPS market basket.

C. Calculation of the Prospective Payment Rates

1. General Formula for Calculation of the Prospective Payment Rates for 
FY 2023

    In general, the operating prospective payment rate for all 
hospitals (including hospitals in Puerto Rico) paid under the IPPS, 
except SCHs, for FY 2023 equals the Federal rate (which includes 
uncompensated care payments). Under current law, the MDH program is 
effective for discharges on or before September 30, 2022. Therefore, 
under current law, the MDH program will expire at the end of FY 
2022.
    SCHs are paid based on whichever of the following rates yields 
the greatest aggregate payment: the Federal national rate (which, as 
discussed in section VI.G. of the preamble of this final rule, 
includes uncompensated care payments); the updated hospital-specific 
rate based on FY 1982 costs per discharge; the updated hospital-
specific rate based on FY 1987 costs per discharge; the updated 
hospital-specific rate based on FY 1996 costs per discharge; or the 
updated hospital-specific rate based on FY 2006 costs per discharge 
to determine the rate that yields the greatest aggregate payment.
    The prospective payment rate for SCHs for FY 2022 equals the 
higher of the applicable Federal rate, or the hospital-specific rate 
as described later in this section.

2. Operating and Capital Federal Payment Rate and Outlier Payment 
Calculation

    Note: The formula specified in this section is used for actual 
claim payment and is also used by CMS to project the outlier 
threshold for the upcoming fiscal year. The difference is the source 
of some of the variables in the formula. For example, operating and 
capital CCRs for actual claim payment are from the PSF while CMS 
uses an adjusted CCR (as described previously) to project the 
threshold for the upcoming fiscal year. In addition, charges for a 
claim payment are from the bill while charges to project the 
threshold are from the MedPAR data with an inflation factor applied 
to the charges (as described earlier). We note that the formula 
specified below reflects our finalized policy to include the 
estimated supplemental payment for eligible IHS/Tribal hospitals and 
Puerto Rico hospitals in the computation of the outlier fixed-loss 
cost threshold.
    Step 1--Determine the MS-DRG and MS-DRG relative weight (from 
Table 5) for each claim based on the ICD-10-CM diagnosis and ICD-10-
PCS procedure codes on the claim.

[[Page 49432]]

    Step 2--Select the applicable average standardized amount 
depending on whether the hospital submitted qualifying quality data 
and is a meaningful EHR user, as described previously.
    Step 3--Compute the operating and capital Federal payment rate:

-- Federal Payment Rate for Operating Costs = MS-DRG Relative Weight 
x [(Labor-Related Applicable Standardized Amount x Applicable CBSA 
Wage Index) + (Nonlabor-Related Applicable Standardized Amount x 
Cost-of-Living Adjustment)] x (1 + IME + (DSH * 0.25))
-- Federal Payment for Capital Costs = MS-DRG Relative Weight x 
Federal Capital Rate x Geographic Adjustment Fact x (l + IME + DSH)

    Step 4--Determine operating and capital costs:

-- Operating Costs = (Billed Charges x Operating CCR)
-- Capital Costs = (Billed Charges x Capital CCR).

    Step 5--Compute operating and capital outlier threshold (CMS 
applies a geographic adjustment to the operating and capital outlier 
threshold to account for local cost variation):

-- Operating CCR to Total CCR = (Operating CCR)/(Operating CCR + 
Capital CCR)
-- Operating Outlier Threshold = [Fixed Loss Threshold x ((Labor-
Related Portion x CBSA Wage Index) + Nonlabor-Related portion)] x 
Operating CCR to Total CCR + Federal Payment with IME, DSH + 
Uncompensated Care Payment + Supplemental Payment for IHS/Tribal 
hospitals and Puerto Rico hospitals + New Technology Add-On Payment 
Amount
-- Capital CCR to Total CCR = (Capital CCR)/(Operating CCR + Capital 
CCR)
-- Capital Outlier Threshold = (Fixed Loss Threshold x Geographic 
Adjustment Factor x Capital CCR to Total CCR) + Federal Payment with 
IME and DSH

    Step 6--Compute operating and capital outlier payments:

-- Marginal Cost Factor = 0.80 or 0.90 (depending on the MS-DRG)
-- Operating Outlier Payment = (Operating Costs--Operating Outlier 
Threshold) x Marginal Cost Factor
-- Capital Outlier Payment = (Capital Costs--Capital Outlier 
Threshold) x Marginal Cost Factor
    The payment rate may then be further adjusted for hospitals that 
qualify for a low-volume payment adjustment under section 
1886(d)(12) of the Act and 42 CFR 412.101(b). The base-operating DRG 
payment amount may be further adjusted by the hospital readmissions 
payment adjustment and the hospital VBP payment adjustment as 
described under sections 1886(q) and 1886(o) of the Act, 
respectively. Payments also may be reduced by the 1-percent 
adjustment under the HAC Reduction Program as described in section 
1886(p) of the Act. We also make new technology add-on payments in 
accordance with section 1886(d)(5)(K) and (L) of the Act. In 
addition, we add the uncompensated care payment to the total claim 
payment amount. As noted in the previous formula, we take 
uncompensated care payments and new technology add-on payments into 
consideration when calculating outlier payments. Finally, as 
previously discussed, we are finalizing, beginning in FY 2023, to 
take into consideration the supplemental payment for eligible IHS/
Tribal hospitals and Puerto Rico hospitals when calculating outlier 
payments.

3. Hospital-Specific Rate (Applicable Only to SCHs and MDHs)

a. Calculation of Hospital-Specific Rate

    Section 1886(b)(3)(C) of the Act provides that SCHs are paid 
based on whichever of the following rates yields the greatest 
aggregate payment: the Federal rate; the updated hospital-specific 
rate based on FY 1982 costs per discharge; the updated hospital-
specific rate based on FY 1987 costs per discharge; the updated 
hospital-specific rate based on FY 1996 costs per discharge; or the 
updated hospital-specific rate based on FY 2006 costs per discharge 
to determine the rate that yields the greatest aggregate payment. 
(We note, under current law, the MDH program is effective for 
discharges on or before September 30, 2022. Therefore, under current 
law, the MDH program will expire at the end of FY 2022.)
    For a more detailed discussion of the calculation of the 
hospital-specific rates, we refer readers to the FY 1984 IPPS 
interim final rule (48 FR 39772); the April 20, 1990 final rule with 
comment period (55 FR 15150); the FY 1991 IPPS final rule (55 FR 
35994); and the FY 2001 IPPS final rule (65 FR 47082).

b. Updating the FY 1982, FY 1987, FY 1996, FY 2002 and FY 2006 
Hospital-Specific Rate for FY 2023

    Section 1886(b)(3)(B)(iv) of the Act provides that the 
applicable percentage increase applicable to the hospital-specific 
rates for SCHs equals the applicable percentage increase set forth 
in section 1886(b)(3)(B)(i) of the Act (that is, the same update 
factor as for all other hospitals subject to the IPPS). Because the 
Act sets the update factor for SCHs equal to the update factor for 
all other IPPS hospitals, the update to the hospital-specific rates 
for SCHs is subject to the amendments to section 1886(b)(3)(B) of 
the Act made by sections 3401(a) and 10319(a) of the Affordable Care 
Act. Accordingly, the proposed applicable percentage increases to 
the hospital-specific rates applicable to SCHs are the following:
[GRAPHIC] [TIFF OMITTED] TR10AU22.218

    For a complete discussion of the applicable percentage increase 
applied to the hospital-specific rates for SCHs, we refer readers to 
section V.B. of the preamble of this final rule.
    In addition, because SCHs use the same MS-DRGs as other 
hospitals when they are paid based on the hospital-specific rate, 
the hospital-specific rate is adjusted by a budget neutrality factor 
to ensure that changes to the MS-DRG classifications and the 
recalibration of the MS-DRG relative weights are made in a manner so 
that aggregate IPPS payments are unaffected. Therefore, the hospital 
specific-rate for an SCH is adjusted by the MS-DRG reclassification 
and recalibration budget neutrality factor, as discussed in section 
III. of this Addendum and listed in the table in section II. of this 
Addendum. In addition, as discussed in section II.E.2.d of this 
final rule, we are establishing a permanent 10-percent cap on the 
reduction in a MS-DRG's relative weight in a given fiscal year, 
beginning in FY 2023. As discussed in section II.E.2.d of this final 
rule, and consistent with our current methodology for implementing 
budget neutrality for DRG reclassification and recalibration of the 
relative weights, we are applying a budget neutrality adjustment to 
the standardized amount for all hospitals so that this 10-percent 
cap on relative weight reductions does not increase estimated 
aggregate Medicare payments beyond the payments that would be made 
had we never applied this cap. As mentioned previously, SCHs use the 
same MS-DRGs as other hospitals when they are paid based on the

[[Page 49433]]

hospital-specific rate. Therefore, we are establishing that the 
hospital specific-rate for an SCH would be adjusted by the MS-DRG 
10-percent cap budget neutrality factor. The resulting rate is used 
in determining the payment rate that an SCH would receive for its 
discharges beginning on or after October 1, 2022. We note that, in 
this final rule, for FY 2023, we are not making a documentation and 
coding adjustment to the hospital specific-rate. We refer readers to 
section II.D. of the preamble of this final rule for a complete 
discussion regarding our policies and previously finalized policies 
(including our historical adjustments to the payment rates) relating 
to the effect of changes in documentation and coding that do not 
reflect real changes in case mix. We note, as mentioned previously, 
under current law, the MDH program is effective for discharges on or 
before September 30, 2022. Therefore, under current law, the MDH 
program will expire at the end of FY 2022.

III. Changes to Payment Rates for Acute Care Hospital Inpatient 
Capital-Related Costs for FY 2023

    The PPS for acute care hospital inpatient capital-related costs 
was implemented for cost reporting periods beginning on or after 
October 1, 1991. The basic methodology for determining Federal 
capital prospective rates is set forth in the regulations at 42 CFR 
412.308 through 412.352. In this section of this Addendum, we 
discuss the factors that we used to determine the capital Federal 
rate for FY 2023, which would be effective for discharges occurring 
on or after October 1, 2022.
    All hospitals (except ``new'' hospitals under Sec.  
412.304(c)(2)) are paid based on the capital Federal rate. We 
annually update the capital standard Federal rate, as provided in 
Sec.  412.308(c)(1), to account for capital input price increases 
and other factors. The regulations at Sec.  412.308(c)(2) also 
provide that the capital Federal rate be adjusted annually by a 
factor equal to the estimated proportion of outlier payments under 
the capital Federal rate to total capital payments under the capital 
Federal rate. In addition, Sec.  412.308(c)(3) requires that the 
capital Federal rate be reduced by an adjustment factor equal to the 
estimated proportion of payments for exceptions under Sec.  412.348. 
(We note that, as discussed in the FY 2013 IPPS/LTCH PPS final rule 
(77 FR 53705), there is generally no longer a need for an exceptions 
payment adjustment factor.) However, in limited circumstances, an 
additional payment exception for extraordinary circumstances is 
provided for under Sec.  412.348(f) for qualifying hospitals. 
Therefore, in accordance with Sec.  412.308(c)(3), an exceptions 
payment adjustment factor may need to be applied if such payments 
are made. Section 412.308(c)(4)(ii) requires that the capital 
standard Federal rate be adjusted so that the effects of the annual 
DRG reclassification and the recalibration of DRG weights and 
changes in the geographic adjustment factor (GAF) are budget 
neutral.
    Section 412.374 provides for payments to hospitals located in 
Puerto Rico under the IPPS for acute care hospital inpatient 
capital-related costs, which currently specifies capital IPPS 
payments to hospitals located in Puerto Rico are based on 100 
percent of the Federal rate.

A. Determination of the Federal Hospital Inpatient Capital-Related 
Prospective Payment Rate Update for FY 2023

    In the discussion that follows, we explain the factors that we 
used to determine the capital Federal rate for FY 2023. In 
particular, we explain why the FY 2023 capital Federal rate would 
increase approximately 2.36 percent, compared to the FY 2022 capital 
Federal rate. As discussed in the impact analysis in Appendix A to 
this final rule, we estimate that capital payments per discharge 
will increase approximately 0.6 percent during that same period. 
Because capital payments constitute approximately 10 percent of 
hospital payments, a 1-percent change in the capital Federal rate 
yields only approximately a 0.1 percent change in actual payments to 
hospitals.
    As discussed in section I.F. of the preamble to this final rule, 
we are finalizing our proposal to use FY 2021 data for purposes of 
FY 2023 IPPS ratesetting. Consistent with this policy, for this 
final rule we are finalizing our proposal to use claims from the 
March 2022 update of the FY 2021 MedPAR file for purposes of 
calculating the budget neutrality adjustment factors for changes 
resulting from the annual DRG reclassification and recalibration and 
changes in the GAF. However, as we also discuss in section I.F. of 
the preamble to this final rule, we are finalizing certain 
modifications to our usual methodologies to account for the 
anticipated decline in COVID-19 hospitalizations of Medicare 
beneficiaries at IPPS hospitals in FY 2023 as compared to FY 2021. 
First, we are modifying the calculation of the FY 2023 MS-DRG 
relative weights by first calculating two sets of weights, one 
including and one excluding COVID-19 claims in the FY 2021 data, and 
then averaging the two sets of relative weights to determine the FY 
2023 MS-DRG relative weight values (as described in greater detail 
in section II.E. of the preamble to this final rule). Second, we are 
modifying our methodology for determining the FY 2023 outlier fixed-
loss amount for IPPS cases by using charge inflation factors and CCR 
adjustment factors based on the last 1-year period prior to the 
COVID-19 PHE. We also are modifying our methodology for determining 
the FY 2023 outlier fixed-loss amount for IPPS cases by establishing 
the fixed-loss amount as an average of fixed-loss amounts calculated 
including and excluding COVID-19 claims in the FY 2021 data. Lastly, 
we are modifying our methodology for determining the FY 2023 outlier 
fixed-loss amount for IPPS cases by including the increases in 
payments to COVID-19 cases provided by the CARES Act in the 
calculation of the fixed-loss amount. The modifications we have made 
to our methodology for determining the FY 2023 outlier fixed-loss 
amount for IPPS cases are discussed in greater detail in section 
II.A.4. of the Addendum to this final rule.

1. Projected Capital Standard Federal Rate Update

    Under Sec.  412.308(c)(1), the capital standard Federal rate is 
updated on the basis of an analytical framework that takes into 
account changes in a capital input price index (CIPI) and several 
other policy adjustment factors. Specifically, we adjust the 
projected CIPI rate of change, as appropriate, each year for case-
mix index-related changes, for intensity, and for errors in previous 
CIPI forecasts. The update factor for FY 2023 under that framework 
is 2.5 percent based on a projected 2.5 percent increase in the 
2018-based CIPI, a 0.0 percentage point adjustment for intensity, a 
0.0 percentage point adjustment for case-mix, a 0.0 percentage point 
adjustment for the DRG reclassification and recalibration, and a 
forecast error correction of 0.0 percentage point. As discussed in 
section III.C. of this Addendum, we continue to believe that the 
CIPI is the most appropriate input price index for capital costs to 
measure capital price changes in a given year. We also explain the 
basis for the FY 2023 CIPI projection in that same section of this 
Addendum. In this final rule, we describe the policy adjustments 
that we applied in the update framework for FY 2023.
    The case-mix index is the measure of the average DRG weight for 
cases paid under the IPPS. Because the DRG weight determines the 
prospective payment for each case, any percentage increase in the 
case-mix index corresponds to an equal percentage increase in 
hospital payments.
    The case-mix index can change for any of several reasons--
     The average resource use of Medicare patient changes 
(``real'' case-mix change);
     Changes in hospital documentation and coding of patient 
records result in higher-weighted DRG assignments (``coding 
effects''); or
     The annual DRG reclassification and recalibration 
changes may not be budget neutral (``reclassification effect'').
    We define real case-mix change as actual changes in the mix (and 
resource requirements) of Medicare patients, as opposed to changes 
in documentation and coding behavior that result in assignment of 
cases to higher-weighted DRGs, but do not reflect higher resource 
requirements. The capital update framework includes the same case-
mix index adjustment used in the former operating IPPS update 
framework (as discussed in the May 18, 2004 IPPS proposed rule for 
FY 2005 (69 FR 28816)). (We no longer use an update framework to 
make a recommendation for updating the operating IPPS standardized 
amounts, as discussed in section II. of Appendix B to the FY 2006 
IPPS final rule (70 FR 47707).)
    For FY 2023, we project a 1.0 percent total increase in the 
case-mix index. We estimated that the real case-mix increase would 
equal 1.0 percent for FY 2023. The net adjustment for change in 
case-mix is the difference between the projected real increases in 
case mix and the projected total increase in case mix. Therefore, as 
proposed, the net adjustment for case-mix change in FY 2023 is 0.0 
percentage point.
    The capital update framework also contains an adjustment for the 
effects of DRG

[[Page 49434]]

reclassification and recalibration. This adjustment is intended to 
remove the effect on total payments of prior year's changes to the 
DRG classifications and relative weights, to retain budget 
neutrality for all case-mix index-related changes other than those 
due to patient severity of illness. Due to the lag time in the 
availability of data, there is a 2-year lag in data used to 
determine the adjustment for the effects of DRG reclassification and 
recalibration. For example, for this FY 2023 IPPS/LTCH PPS final 
rule, we have the FY 2021 MedPAR claims data available to evaluate 
the effects of the FY 2021 DRG reclassification and recalibration as 
part of our update for FY 2023. We assume for purposes of this 
adjustment, that the estimate of FY 2021 DRG reclassification and 
recalibration would result in no change in the case-mix when 
compared with the case mix index that would have resulted if we had 
not made the reclassification and recalibration changes to the DRGs. 
Therefore, as proposed, we are making a 0.0 percentage point 
adjustment for reclassification and recalibration in the update 
framework for FY 2023.
    The capital update framework also contains an adjustment for 
forecast error. The input price index forecast is based on 
historical trends and relationships ascertainable at the time the 
update factor is established for the upcoming year. In any given 
year, there may be unanticipated price fluctuations that may result 
in differences between the actual increase in prices and the 
forecast used in calculating the update factors. In setting a 
prospective payment rate under the framework, we make an adjustment 
for forecast error only if our estimate of the change in the capital 
input price index for any year is greater than 0.25 percentage point 
in absolute terms. There is a 2-year lag between the forecast and 
the availability of data to develop a measurement of the forecast 
error. Historically, when a forecast error of the CIPI is greater 
than 0.25 percentage point in absolute terms, it is reflected in the 
update recommended under this framework. A forecast error of -0.1 
percentage point was calculated for the FY 2021 update, for which 
there are historical data. That is, current historical data 
indicated that the forecasted FY 2021 CIPI (1.1 percent) used in 
calculating the FY 2021 update factor is 0.1 percentage point higher 
than actual realized price increases (1.0 percent). As this does not 
exceed the 0.25 percentage point threshold, as proposed we are not 
making an adjustment for forecast error in the update for FY 2023.
    Under the capital IPPS update framework, we also make an 
adjustment for changes in intensity. Historically, we calculate this 
adjustment using the same methodology and data that were used in the 
past under the framework for operating IPPS. The intensity factor 
for the operating update framework reflects how hospital services 
are utilized to produce the final product, that is, the discharge. 
This component accounts for changes in the use of quality-enhancing 
services, for changes within DRG severity, and for expected 
modification of practice patterns to remove noncost-effective 
services. Our intensity measure is based on a 5-year average.
    We calculate case-mix constant intensity as the change in total 
cost per discharge, adjusted for price level changes (the CPI for 
hospital and related services) and changes in real case-mix. Without 
reliable estimates of the proportions of the overall annual 
intensity changes that are due, respectively, to ineffective 
practice patterns and the combination of quality-enhancing new 
technologies and complexity within the DRG system, we assume that 
one-half of the annual change is due to each of these factors. Thus, 
the capital update framework provides an add-on to the input price 
index rate of increase of one-half of the estimated annual increase 
in intensity, to allow for increases within DRG severity and the 
adoption of quality-enhancing technology.
    In this final rule, as proposed, we are continuing to use a 
Medicare-specific intensity measure that is based on a 5-year 
adjusted average of cost per discharge for FY 2023 (we refer readers 
to the FY 2011 IPPS/LTCH PPS final rule (75 FR 0436) for a full 
description of our Medicare-specific intensity measure). 
Specifically, for FY 2023, we are using an intensity measure that is 
based on an average of cost-per-discharge data from the 5-year 
period beginning with FY 2016 and extending through FY 2020. Based 
on these data, we estimated that case-mix constant intensity 
declined during FYs 2016 through 2020. In the past, when we found 
intensity to be declining, we believed a zero (rather than a 
negative) intensity adjustment was appropriate. Consistent with this 
approach, because we estimated that intensity would decline during 
that 5-year period, we believe it is appropriate to continue to 
apply a zero-intensity adjustment for FY 2023. Therefore, as 
proposed, we are making a 0.0 percentage point adjustment for 
intensity in the update for FY 2023.
    Earlier, we described the basis of the components we used to 
develop the 2.5 percent capital update factor under the capital 
update framework for FY 2023, as shown in the following table.
[GRAPHIC] [TIFF OMITTED] TR10AU22.219

2. Outlier Payment Adjustment Factor

    Section 412.312(c) establishes a unified outlier payment 
methodology for inpatient operating and inpatient capital-related 
costs. A shared threshold is used to identify outlier cases for both 
inpatient operating and inpatient capital-related payments. Section 
412.308(c)(2) provides that the standard Federal rate for inpatient 
capital-related costs be reduced by an adjustment factor equal to 
the estimated proportion of capital-related outlier payments to 
total inpatient capital-related PPS payments. The outlier threshold 
is set so that operating outlier payments are projected to be 5.1 
percent of total operating IPPS DRG payments. For FY 2023, we have 
incorporated the estimated outlier reconciliation payment amounts 
into the outlier threshold model, as we did for FY 2022. (For more 
details on our incorporation of the estimated outlier reconciliation 
payment amounts into the outlier threshold model, please see section 
II.A. of this Addendum to this final rule.)
    For FY 2022, we estimated that outlier payments for capital-
related PPS payments would equal 5.29 percent of inpatient capital-
related payments based on the capital Federal rate. As discussed 
previously and in section II.A.4.j. of the Addendum to this final 
rule, we are modifying our methodology for determining the FY 2023 
outlier threshold for IPPS cases. For FY 2023, this threshold is 
being determined as an average of the thresholds calculated when 
including and excluding COVID-19 cases in the FY 2021 claims data. 
As also discussed in section

[[Page 49435]]

II.A., this modification results in two separate estimates of 
outlier payments for capital related costs as a percentage of 
inpatient capital-related payments (prior to taking into account 
projected capital outlier reconciliation payments). One estimate is 
based on the outlier threshold that was calculated using all cases 
(that is including COVID-19 cases). The other estimate is based on 
the outlier threshold that was calculated excluding COVID-19 cases. 
Consistent with our modification to average the outlier thresholds 
in determining the final FY 2023 outlier threshold, we are 
estimating the capital outlier percentage for FY 2023 as the average 
of these two estimates. Accordingly, as discussed in more detail in 
section II.A.4.j. of the Addendum to this final rule, we estimate 
that prior to taking into account projected capital outlier 
reconciliation payments, outlier payments for capital-related costs 
will equal 5.53 percent of inpatient capital-related payments based 
on the capital Federal rate in FY 2023.
    Using the methodology outlined in section II.A.4.j.(2). of this 
Addendum, we estimate that taking into account projected capital 
outlier reconciliation payments will decrease FY 2023 aggregate 
estimated capital outlier payments by 0.01 percent. Therefore, 
accounting for estimated capital outlier reconciliation, the 
estimated outlier payments for capital-related PPS payments would 
equal 5.52 percent (5.53 percent--0.01 percent) of inpatient 
capital-related payments based on the capital Federal rate in FY 
2023. Accordingly, we applied an outlier adjustment factor of 0.9448 
in determining the capital Federal rate for FY 2023. Thus, we 
estimate that the percentage of capital outlier payments to total 
capital Federal rate payments for FY 2023 will be higher than the 
percentage for FY 2022.
    The outlier reduction factors are not built permanently into the 
capital rates; that is, they are not applied cumulatively in 
determining the capital Federal rate. The FY 2023 outlier adjustment 
of 0.9448 is a -0.24 percent change from the FY 2022 outlier 
adjustment of 0.9471. Therefore, the net change in the outlier 
adjustment to the capital Federal rate for FY 2023 is 0.9976 
(0.9448/0.9471) so that the outlier adjustment will decrease the FY 
2023 capital Federal rate by approximately -0.24 percent compared to 
the FY 2022 outlier adjustment.

3. Budget Neutrality Adjustment Factor for Changes in DRG 
Classifications and Weights and the GAF

    Section 412.308(c)(4)(ii) requires that the capital Federal rate 
be adjusted so that aggregate payments for the fiscal year based on 
the capital Federal rate, after any changes resulting from the 
annual DRG reclassification and recalibration and changes in the 
GAF, are projected to equal aggregate payments that would have been 
made on the basis of the capital Federal rate without such changes.
    As discussed in section III.G.3. of the preamble of this final 
rule, in the FY 2020 IPPS/LTCH PPS final rule (84 FR 42325 through 
42339), we finalized a policy to help reduce wage index disparities 
between high and low wage index hospitals by increasing the wage 
index values for hospitals with a wage index value below the 25th 
percentile wage index. We stated our intention that this policy will 
be effective for at least 4 years, beginning in FY 2020. As 
discussed in section III.G.3 of the preamble of this final rule, 
this policy was applied in FYs 2020, 2021, and 2022, and will 
continue to apply in FY 2023 as we proposed. In addition, in FYs 
2020 and 2021, we placed a 5-percent cap on any decrease in a 
hospital's wage index from the hospital's final wage index in the 
prior fiscal year (see (84 FR 42336 through 42338) and (85 FR 58753 
through 58755)). In FY 2022, we finalized a policy that for 
hospitals that received the transition in FY 2021 (that is hospitals 
that received a 5 percent cap on their FY 2021 wage index), we 
continued a wage index transition for FY 2022 under which we applied 
a 5-percent cap on any decrease in the hospital's wage index 
compared to its wage index for FY 2021 (86 FR 45164 through 45165). 
Beginning in FY 2023, as discussed in section III.N. of the preamble 
to this final rule, we finalized a permanent 5-percent cap on any 
decrease to a hospital's wage index from its wage index in the prior 
FY, regardless of the circumstances causing the decline. That is, a 
hospital's wage index will not be less than 95 percent of its final 
wage index for the prior FY.
    As we discussed in the FY 2020 IPPS/LTCH PPS final rule (84 FR 
42638 through 42639), we augmented our historical methodology for 
computing the budget neutrality factor for changes in the GAFs in 
light of the effect of those wage index changes on the GAFs. 
Specifically, we established a 2-step methodology, under which we 
first calculate a factor to ensure budget neutrality for changes to 
the GAFs due to the update to the wage data, wage index 
reclassifications and redesignations, and application of the rural 
floor policy, consistent with our historical GAF budget neutrality 
factor methodology. In the second step, we calculate a factor to 
ensure budget neutrality for changes to the GAFs due to our policy 
to increase the wage index for hospitals with a wage index value 
below the 25th percentile wage index and our policy to place a 5-
percent cap on any decrease in a hospital's wage index from the 
hospital's final wage index in the prior fiscal year. In this 
section of this Addendum, we refer to these two policies as the 
lowest quartile hospital wage index adjustment and the 5-percent cap 
on wage index decreases. We further note that in this section of 
this Addendum, for this final rule, we also refer to the permanent 
cap on wage index decreases beginning in FY 2023 as the 5-percent 
cap on wage index decreases policy.
    The budget neutrality factors applied for changes to the GAFs 
due to the update to the wage data, wage index reclassifications and 
redesignations, and application of the rural floor policy are built 
permanently into the capital Federal rate; that is, they are applied 
cumulatively in determining the capital Federal rate. In the FY 2022 
IPPS/LTCH PPS final rule (86 FR 45552), we finalized our proposal to 
not permanently apply the budget neutrality factor for the lowest 
quartile hospital wage index adjustment and the 5 percent cap on 
wage index decreases such that they would not be applied 
cumulatively in determining the capital Federal rate. We believe 
this is more technically appropriate because the GAFs with the 
lowest quartile hospital wage index adjustment and the 5-percent cap 
on wage index decreases policies applied from the previous year are 
not used in the budget neutrality factor calculations for the 
current year. Accordingly, and consistent with this approach, prior 
to calculating the GAF budget neutrality factors for FY 2023, we 
removed from the capital Federal rate the budget neutrality factor 
applied in FY 2022 for the lowest quartile hospital wage index 
adjustment and the 5-percent cap on wage index decreases. 
Specifically, we divided the capital Federal rate by the FY 2022 
budget neutrality factor of 0.9974 (86 FR 45552). We refer the 
reader to the FY 2022 IPPS/LTCH PPS final rule (86 FR 45552) for 
additional discussion on our policy of removing the prior year 
budget neutrality factor for the lowest quartile hospital wage index 
adjustment and the 5 percent cap on wage index decreases from the 
capital Federal rate.
    In light of the changes to the wage index and other wage index 
policies for FY 2023 discussed previously, which directly affect the 
GAF, we continue to compute a budget neutrality adjustment for 
changes in the GAFs in two steps. We discuss our 2-step calculation 
of the GAF budget neutrality factors for FY 2023 as follows.
    To determine the GAF budget neutrality factors for FY 2023, we 
first compared estimated aggregate capital Federal rate payments 
based on the FY 2022 MS-DRG classifications and relative weights and 
the FY 2022 GAFs to estimated aggregate capital Federal rate 
payments based on the FY 2022 MS-DRG classifications and relative 
weights and the FY 2023 GAFs without incorporating the lowest 
quartile hospital wage index adjustment and the 5-percent cap on 
wage index decreases policy. To achieve budget neutrality for these 
changes in the GAFs, we calculated an incremental GAF budget 
neutrality adjustment factor of 1.0008 for FY 2023. Next, we 
compared estimated aggregate capital Federal rate payments based on 
the FY 2023 GAFs with and without the lowest quartile hospital wage 
index adjustment and the 5 percent cap on wage index decreases 
policy. For this calculation, estimated aggregate capital Federal 
rate payments were calculated using the FY 2023 MS-DRG 
classifications and relative weights (after application of the 10-
percent cap discussed later in this section of the Addendum) and the 
FY 2023 GAFs (both with and without the lowest quartile hospital 
wage index adjustment and the 5-percent cap on wage index decreases 
policy). (We note, for this calculation the GAFs included the 
imputed floor, out-migration and Frontier state adjustments.) To 
achieve budget neutrality for the effects of the lowest quartile 
hospital wage index adjustment and the 5-percent cap on wage index 
decreases policy on the FY 2023 GAFs, we calculated an incremental 
GAF budget neutrality adjustment factor of 0.9972. As discussed 
earlier in this section of the Addendum, the budget neutrality 
factor for the lowest quartile hospital wage index adjustment factor 
and the 5-percent cap on

[[Page 49436]]

wage index decreases is not permanently built into the capital 
Federal rate. Consistent with this, we present the budget neutrality 
factor for the lowest quartile hospital wage index adjustment and 
the 5-percent cap on wage index decreases calculated under the 
second step of this 2-step methodology separately from the other 
budget neutrality factors in the discussion that follows, and this 
factor is not included in the calculation of the combined GAF/DRG 
adjustment factor described later in this section of the Addendum.
    In section II.E.2. of the preamble to this final rule, we 
finalized our proposal to apply a permanent 10-percent cap on the 
reduction in a MS-DRG's relative weight in a given year. Consistent 
with our current methodology for adjusting the capital standard 
Federal rate to ensure that the effects of the annual DRG 
reclassification and the recalibration of DRG weights are budget 
neutral under Sec.  412.308(c)(4)(ii), as we proposed, we are 
applying an additional budget neutrality factor to the capital 
standard Federal rate so that the 10-percent cap on decreases in an 
MS-DRG's relative weight is implemented in a budget neutral manner. 
Specifically, in light of this provision, as proposed, we are 
augmenting our historical methodology for computing the budget 
neutrality factor for the annual DRG reclassification and 
recalibration by computing a budget neutrality adjustment for the 
annual DRG reclassification and recalibration in two steps. We first 
calculate a budget neutrality factor to account for the annual DRG 
reclassification and recalibration prior to the application of the 
10-percent cap on MS-DRG relative weight decreases. Then we 
calculate an additional budget neutrality factor to account for the 
application of the 10-percent cap on MS-DRG relative weight 
decreases.
    To determine the DRG budget neutrality factors for FY 2023, we 
first compared estimated aggregate capital Federal rate payments 
based on the FY 2022 MS-DRG classifications and relative weights to 
estimated aggregate capital Federal rate payments based on the FY 
2023 MS-DRG classifications and relative weights prior to the 
application of the 10-percent cap. For these calculations, estimated 
aggregate capital Federal rate payments were calculated using the FY 
2023 GAFs without the lowest quartile hospital wage index adjustment 
and the 5-percent cap on wage index decreases. The incremental 
adjustment factor for DRG classifications and changes in relative 
weights prior to the application of the 10-percent cap is 1.0006. 
Next, we compared estimated aggregate capital Federal rate payments 
based on the FY 2023 MS-DRG classifications and relative weights 
prior to the application of the 10-percent cap to estimated 
aggregate capital Federal rate payments based on the FY 2023 MS-DRG 
classifications and relative weights after the application of the 
10-percent cap. For these calculations, estimated aggregate capital 
Federal rate payments were also calculated using the FY 2023 GAFs 
without the lowest quartile hospital wage index adjustment and the 
5-percent cap on wage index decreases. The incremental adjustment 
factor for the application of the 10-percent cap on relative weight 
decreases is 0.9998. Therefore, to achieve budget neutrality for the 
FY 2023 MS-DRG reclassification and recalibration (including the 10-
percent cap), based on the calculations described previously, we are 
applying an incremental budget neutrality adjustment factor of 
1.0004 (1.0006 x 0.9998) for FY 2023 to the capital Federal rate. We 
note that all the values are calculated with unrounded numbers.
    The incremental adjustment factor for the FY 2023 MS-DRG 
reclassification and recalibration (1.0004) and for changes in the 
FY 2023 GAFs due to the update to the wage data, wage index 
reclassifications and redesignations, and application of the rural 
floor policy (1.0008) is 1.0012 (1.0004 x 1.0008). This incremental 
adjustment factor is built permanently into the capital Federal 
rates. To achieve budget neutrality for the effects of the lowest 
quartile hospital wage index adjustment and the 5-percent cap on 
wage index decreases policy on the FY 2023 GAFs, as described 
previously, we calculated a budget neutrality adjustment factor of 
0.9972 for FY 2023. We refer to this budget neutrality factor for 
the remainder of this section as the lowest quartile/cap adjustment 
factor.
    We applied the budget neutrality adjustment factors described 
previously to the capital Federal rate. This follows the requirement 
under Sec.  412.308(c)(4)(ii) that estimated aggregate payments each 
year be no more or less than they would have been in the absence of 
the annual DRG reclassification and recalibration and changes in the 
GAFs.
    The methodology used to determine the recalibration and 
geographic adjustment factor (GAF/DRG) budget neutrality adjustment 
is similar to the methodology used in establishing budget neutrality 
adjustments under the IPPS for operating costs. One difference is 
that, under the operating IPPS, the budget neutrality adjustments 
for the effect of updates to the wage data, wage index 
reclassifications and redesignations, and application of the rural 
floor policy are determined separately. Under the capital IPPS, 
there is a single budget neutrality adjustment factor for changes in 
the GAF that result from updates to the wage data, wage index 
reclassifications and redesignations, and application of the rural 
floor policy. In addition, there is no adjustment for the effects 
that geographic reclassification, the lowest quartile hospital wage 
index adjustment, or the 5-percent cap on wage index decreases 
policy described previously have on the other payment parameters, 
such as the payments for DSH or IME.
    The incremental GAF/DRG adjustment factor of 1.0012 accounts for 
the MS-DRG reclassifications and recalibration (including 
application of the 10-percent cap on relative weight decreases) and 
for changes in the GAFs that result from updates to the wage data, 
the effects on the GAFs of FY 2023 geographic reclassification 
decisions made by the MGCRB compared to FY 2022 decisions, and the 
application of the rural floor policy. The lowest quartile/cap 
adjustment factor of 0.9972 accounts for changes in the GAFs that 
result from our policy to increase the wage index values for 
hospitals with a wage index value below the 25th percentile wage 
index and the 5-percent cap on wage index decreases policy. However, 
these factors do not account for changes in payments due to changes 
in the DSH and IME adjustment factors.

4. Capital Federal Rate for FY 2023

    For FY 2022, we established a capital Federal rate of $472.59 
(86 FR 45553, as corrected in 86 FR 58026). We are establishing an 
update of 2.5 percent in determining the FY 2023 capital Federal 
rate for all hospitals. As a result of this update and the budget 
neutrality factors discussed earlier, we are establishing a national 
capital Federal rate of $483.76 for FY 2023. The national capital 
Federal rate for FY 2023 was calculated as follows:
     The FY 2023 update factor is 1.025; that is, the update 
is 2.5 percent.
     The FY 2023 GAF/DRG budget neutrality adjustment factor 
that is applied to the capital Federal rate for changes in the MS-
DRG classifications and relative weights (including application of 
the 10-percent cap on relative weight decreases) and changes in the 
GAFs that result from updates to the wage data, wage index 
reclassifications and redesignations, and application of the rural 
floor policy is 1.0012.
     The FY 2023 lowest quartile/cap budget neutrality 
adjustment factor that is applied to the capital Federal rate for 
changes in the GAFs that result from our policy to increase the wage 
index values for hospitals with a wage index value below the 25th 
percentile wage index and the 5-percent cap on wage index decreases 
policy is 0.9972.
     The FY 2023 outlier adjustment factor is 0.9448.
    We are providing the following chart that shows how each of the 
factors and adjustments for FY 2023 affects the computation of the 
FY 2023 national capital Federal rate in comparison to the FY 2022 
national capital Federal rate. The FY 2023 update factor has the 
effect of increasing the capital Federal rate by 2.5 percent 
compared to the FY 2022 capital Federal rate. The GAF/DRG budget 
neutrality adjustment factor has the effect of increasing the 
capital Federal rate by 0.12 percent. The FY 2023 lowest quartile/
cap budget neutrality adjustment factor has the effect of decreasing 
the capital Federal rate by 0.02 percent compared to the FY 2022 
capital Federal rate. The FY 2023 outlier adjustment factor has the 
effect of decreasing the capital Federal rate by 0.24 percent 
compared to the FY 2022 capital Federal rate. The combined effect of 
all the changes will increase the national capital Federal rate by 
approximately 2.36 percent, compared to the FY 2022 national capital 
Federal rate.

[[Page 49437]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.220

B. Calculation of the Inpatient Capital-Related Prospective 
Payments for FY 2023

    For purposes of calculating payments for each discharge during 
FY 2023, the capital Federal rate is adjusted as follows: (Standard 
Federal Rate) x (DRG weight) x (GAF) x (COLA for hospitals located 
in Alaska and Hawaii) x (1 + DSH Adjustment Factor + IME Adjustment 
Factor, if applicable). The result is the adjusted capital Federal 
rate.
    Hospitals also may receive outlier payments for those cases that 
qualify under the threshold established for each fiscal year. 
Section 412.312(c) provides for a shared threshold to identify 
outlier cases for both inpatient operating and inpatient capital-
related payments. The outlier threshold for FY 2023 is in section 
II.A. of this Addendum. For FY 2023, a case will qualify as a cost 
outlier if the cost for the case is greater than the prospective 
payment rates for the MS-DRG plus IME and DSH payments (including 
the empirically justified Medicare DSH payment and the estimated 
uncompensated care payment), any add-on payments for new technology, 
and, as we finalized beginning in FY 2023, the estimated 
supplemental payment for eligible IHS/Tribal hospitals and Puerto 
Rico hospitals (as discussed in section IV.E. of the preamble of 
this final rule), plus the fixed-loss amount of $38,859.
    Currently, as provided under Sec.  412.304(c)(2), we pay a new 
hospital 85 percent of its reasonable costs during the first 2 years 
of operation, unless it elects to receive payment based on 100 
percent of the capital Federal rate. Effective with the third year 
of operation, we pay the hospital based on 100 percent of the 
capital Federal rate (that is, the same methodology used to pay all 
other hospitals subject to the capital PPS).

C. Capital Input Price Index

1. Background

    Like the operating input price index, the capital input price 
index (CIPI) is a fixed-weight price index that measures the price 
changes associated with capital costs during a given year. The CIPI 
differs from the operating input price index in one important 
aspect--the CIPI reflects the vintage nature of capital, which is 
the acquisition and use of capital over time. Capital expenses in 
any given year are determined by the stock of capital in that year 
(that is, capital that remains on hand from all current and prior 
capital acquisitions). An index measuring capital price changes 
needs to reflect this vintage nature of capital. Therefore, the CIPI 
was developed to capture the vintage nature of capital by using a 
weighted-average of past capital purchase prices up to and including 
the current year.
    We periodically update the base year for the operating and 
capital input price indexes to reflect the changing composition of 
inputs for operating and capital expenses. For this final rule, we 
are using the IPPS operating and capital market baskets that reflect 
a 2018 base year. For a complete discussion of this rebasing, we 
refer readers to the FY 2022 IPPS/LTCH PPS final rule (86 FR 45194 
through 45213).

2. Forecast of the CIPI for FY 2023

    Based on IHS Global Inc.'s second quarter 2022 forecast, for 
this final rule, we are forecasting the 2018-based CIPI to increase 
2.5 percent in FY 2023. This reflects a projected 2.9 percent 
increase in vintage-weighted depreciation prices (building and fixed 
equipment, and movable equipment), and a projected 6.7 percent 
increase in other capital expense prices in FY 2023, partially 
offset by a projected 1.7 percent decline in vintage-weighted 
interest expense prices in FY 2023. The weighted average of these 
three factors produces the forecasted 2.5 percent increase for the 
2018-based CIPI in FY 2023. As proposed, we are using the more 
recent data available for this final rule to determine the FY 2023 
increase in the 2018-based CIPI for this final rule.

IV. Changes to Payment Rates for Excluded Hospitals: Rate-of-Increase 
Percentages for FY 2023

    Payments for services furnished in children's hospitals, 11 
cancer hospitals, and hospitals located outside the 50 States, the 
District of Columbia and Puerto Rico (that is, short-term acute care 
hospitals located in the U.S. Virgin Islands, Guam, the Northern 
Mariana Islands, and American Samoa) that are excluded from the IPPS 
are made on the basis of reasonable costs based on the hospital's 
own historical cost experience, subject to a rate-of-increase 
ceiling. A per discharge limit (the target amount, as defined in 
Sec.  413.40(a) of the regulations) is set for each hospital, based 
on the hospital's own cost experience in its base year, and updated 
annually by a rate-of-increase percentage specified in Sec.  
413.40(c)(3). In addition, as specified in the FY 2018 IPPS/LTCH PPS 
final rule (82 FR 38536), effective for cost reporting periods 
beginning during FY 2018, the annual update to the target amount for 
extended neoplastic disease care hospitals (hospitals described in 
Sec.  412.22(i) of the regulations) also is the rate-of-increase 
percentage specified in Sec.  413.40(c)(3). (We note that, in 
accordance with Sec.  403.752(a), religious nonmedical health care 
institutions (RNHCIs) are also subject to the rate-of-increase 
limits established under Sec.  413.40 of the regulations.)
    In the FY 2023 IPPS/LTCH PPS proposed rule, based on IGI's 2021 
fourth quarter forecast, we estimated the 2018-based IPPS operating 
market basket update for FY 2023 to be 3.1 percent (that is, the 
estimate of the market basket rate-of-increase). However, we 
proposed that if more recent data subsequently became available (for 
example, a more recent estimate of the market basket update), we 
would use such data, if appropriate, to calculate the IPPS operating 
market basket update for FY 2023. More recent data did subsequently 
become available. Thus, for this FY 2023 IPPS/LTCH PPS final rule, 
based on IGI's second quarter 2022 forecast, the FY 2023 rate-of-
increase percentage that will be applied to the FY 2022 target 
amounts in order to calculate the FY 2023 target amounts for 
children's hospitals, the 11 cancer hospitals, RNCHIs, short-term 
acute care hospitals located in the U.S. Virgin Islands, Guam, the 
Northern Mariana Islands, and American Samoa, and extended 
neoplastic disease care hospitals is 4.1 percent, in accordance with 
the applicable regulations at 42 CFR 413.40.
    IRFs and rehabilitation distinct part units, IPFs and 
psychiatric units, and LTCHs are

[[Page 49438]]

excluded from the IPPS and paid under their respective PPSs. The IRF 
PPS, the IPF PPS, and the LTCH PPS are updated annually. We refer 
readers to section VIII. of the preamble and section V. of the 
Addendum of this final rule for the changes to the Federal payment 
rates for LTCHs under the LTCH PPS for FY 2023. The annual updates 
for the IRF PPS and the IPF PPS are issued by the agency in separate 
Federal Register documents.
    We received no comments on this proposal and therefore are 
finalizing this provision without modification.

V. Changes to the Payment Rates for the LTCH PPS for FY 2023

A. LTCH PPS Standard Federal Payment Rate for FY 2023

1. Overview

    In section VIII. of the preamble of this final rule, we discuss 
our annual updates to the payment rates, factors, and specific 
policies under the LTCH PPS for FY 2023.
    Under Sec.  412.523(c)(3) of the regulations, for FY 2012 and 
subsequent years, we updated the standard Federal payment rate by 
the most recent estimate of the LTCH PPS market basket at that time, 
including additional statutory adjustments required by sections 
1886(m)(3) (citing sections 1886(b)(3)(B)(xi)(II) and 1886(m)(4) of 
the Act as set forth in the regulations at Sec.  412.523(c)(3)(viii) 
through (xvii)). (For a summary of the payment rate development 
prior to FY 2012, we refer readers to the FY 2018 IPPS/LTCH PPS 
final rule (82 FR 38310 through 38312) and references therein.)
    Section 1886(m)(3)(A) of the Act specifies that, for rate year 
2012 and each subsequent rate year, any annual update to the 
standard Federal payment rate shall be reduced by the productivity 
adjustment described in section 1886(b)(3)(B)(xi)(II) of the Act as 
discussed in section VIII.C.2. of the preamble of this final rule. 
This section of the Act further provides that the application of 
section 1886(m)(3)(B) of the Act may result in the annual update 
being less than zero for a rate year, and may result in payment 
rates for a rate year being less than such payment rates for the 
preceding rate year. (As noted in section VIII.C.2. of the preamble 
of this final rule, the annual update to the LTCH PPS occurs on 
October 1 and we have adopted the term ``fiscal year'' (FY) rather 
than ``rate year'' (RY) under the LTCH PPS beginning October 1, 
2010. Therefore, for purposes of clarity, when discussing the annual 
update for the LTCH PPS, including the provisions of the Affordable 
Care Act, we use the term ``fiscal year'' rather than ``rate year'' 
for 2011 and subsequent years.)
    For LTCHs that fail to submit the required quality reporting 
data in accordance with the LTCH QRP, the annual update is reduced 
by 2.0 percentage points as required by section 1886(m)(5) of the 
Act.

2. Development of the FY 2023 LTCH PPS Standard Federal Payment Rate

    Consistent with our historical practice and Sec.  
412.523(c)(3)(xvii), for FY 2023, as we proposed, we are applying 
the annual update to the LTCH PPS standard Federal payment rate from 
the previous year. Furthermore, in determining the LTCH PPS standard 
Federal payment rate for FY 2023, we are also making certain 
regulatory adjustments, consistent with past practices. 
Specifically, in determining the FY 2023 LTCH PPS standard Federal 
payment rate, as we proposed, we are applying a budget neutrality 
adjustment factor for the changes related to the area wage level 
adjustment (that is, changes to the wage data and labor-related 
share) as discussed in section V.B.5. of this Addendum to this final 
rule.
    In this final rule, we are establishing an annual update to the 
LTCH PPS standard Federal payment rate of 3.8 percent (that is, the 
most recent estimate of the LTCH PPS market basket increase of 4.1 
percent less the productivity adjustment of 0.3 percentage point). 
Therefore, in accordance with Sec.  412.523(c)(3)(xvii), we are 
applying an update factor of 1.038 to the FY 2022 LTCH PPS standard 
Federal payment rate of $44,713.67 to determine the FY 2023 LTCH PPS 
standard Federal payment rate. Also, in accordance with Sec.  
412.523(c)(3)(xvii) and (c)(4), we are required to reduce the annual 
update to the LTCH PPS standard Federal payment rate by 2.0 
percentage points for LTCHs that fail to submit the required quality 
reporting data for FY 2023 as required under the LTCH QRP. 
Therefore, we are establishing an annual update to the LTCH PPS 
standard Federal payment rate of 1.8 percent (that is, an update 
factor of 1.018) for FY 2023 for LTCHs that fail to submit the 
required quality reporting data for FY 2023 as required under the 
LTCH QRP. Consistent with Sec.  412.523(d)(4), we are applying an 
area wage level budget neutrality factor to the FY 2023 LTCH PPS 
standard Federal payment rate of 1.0004304, based on the best 
available data at this time, to ensure that any changes to the area 
wage level adjustment (that is, the annual update of the wage index 
(including application of the 5-percent cap on wage index decreases, 
discussed later in this section of this final rule), and labor-
related share) will not result in any change (increase or decrease) 
in estimated aggregate LTCH PPS standard Federal payment rate 
payments. Accordingly, we are establishing an LTCH PPS standard 
Federal payment rate of $46,432.77 (calculated as $44,713.67 x 1.038 
x 1.0004304) for FY 2023. For LTCHs that fail to submit quality 
reporting data for FY 2023, in accordance with the requirements of 
the LTCH QRP under section 1866(m)(5) of the Act, we are 
establishing an LTCH PPS standard Federal payment rate of $45,538.11 
(calculated as $44,713.67 x 1.018 x 1.0004304) for FY 2023.

B. Adjustment for Area Wage Levels Under the LTCH PPS for FY 2023

1. Background

    Under the authority of section 123 of the BBRA, as amended by 
section 307(b) of the BIPA, we established an adjustment to the LTCH 
PPS standard Federal payment rate to account for differences in LTCH 
area wage levels under Sec.  412.525(c). The labor-related share of 
the LTCH PPS standard Federal payment rate is adjusted to account 
for geographic differences in area wage levels by applying the 
applicable LTCH PPS wage index. The applicable LTCH PPS wage index 
is computed using wage data from inpatient acute care hospitals 
without regard to reclassification under section 1886(d)(8) or 
section 1886(d)(10) of the Act.
    The FY 2023 LTCH PPS standard Federal payment rate wage index 
values that will be applicable for LTCH PPS standard Federal payment 
rate discharges occurring on or after October 1, 2022, through 
September 30, 2023, are presented in Table 12A (for urban areas) and 
Table 12B (for rural areas), which are listed in section VI. of the 
Addendum to this final rule and available via the internet on the 
CMS website.

2. Geographic Classifications (Labor Market Areas) for the LTCH PPS 
Standard Federal Payment Rate

    In adjusting for the differences in area wage levels under the 
LTCH PPS, the labor-related portion of an LTCH's Federal prospective 
payment is adjusted by using an appropriate area wage index based on 
the geographic classification (labor market area) in which the LTCH 
is located. Specifically, the application of the LTCH PPS area wage 
level adjustment under existing Sec.  412.525(c) is made based on 
the location of the LTCH--either in an ``urban area,'' or a ``rural 
area,'' as defined in Sec.  412.503. Under Sec.  412.503, an ``urban 
area'' is defined as a Metropolitan Statistical Area (MSA) (which 
includes a Metropolitan division, where applicable), as defined by 
the Executive OMB, and a ``rural area'' is defined as any area 
outside of an urban area (75 FR 37246).
    The geographic classifications (labor market area definitions) 
currently used under the LTCH PPS, effective for discharges 
occurring on or after October 1, 2014, are based on the Core Based 
Statistical Areas (CBSAs) established by OMB, which are based on the 
2010 decennial census data. In general, the current statistical 
areas (which were implemented beginning with FY 2015) are based on 
revised OMB delineations issued on February 28, 2013, in OMB 
Bulletin No. 13-01. (We note we have adopted minor revisions and 
updates in the years between the decennial censuses.) We adopted 
these labor market area delineations because they were at that time 
based on the best available data that reflect the local economies 
and area wage levels of the hospitals that are currently located in 
these geographic areas. We also believed that these OMB delineations 
would ensure that the LTCH PPS area wage level adjustment most 
appropriately accounted for and reflected the relative hospital wage 
levels in the geographic area of the hospital as compared to the 
national average hospital wage level. We noted that this policy was 
consistent with the IPPS policy adopted in FY 2015 under Sec.  
412.64(b)(1)(ii)(D) (79 FR 49951 through 49963). (For additional 
information on the CBSA-based labor market area (geographic 
classification) delineations currently used under the LTCH PPS and 
the history of the labor market area definitions used under the LTCH 
PPS, we refer readers to the FY 2015 IPPS/LTCH PPS final rule (79 FR 
50180 through 50185).)
    In general, it is our historical practice to update the CBSA-
based labor market area delineations annually based on the most 
recent updates issued by OMB. Generally, OMB issues major revisions 
to statistical

[[Page 49439]]

areas every 10 years, based on the results of the decennial census. 
However, OMB occasionally issues minor updates and revisions to 
statistical areas in the years between the decennial censuses. OMB 
Bulletin No. 17-01, issued August 15, 2017, established the 
delineations for the Nation's statistical areas, and the 
corresponding changes to the CBSA-based labor market areas were 
adopted in the FY 2019 IPPS/LTCH PPS final rule (83 FR 41731). A 
copy of this bulletin may be obtained on the website at https://www.whitehouse.gov/wp-content/uploads/legacy_drupal_files/omb/bulletins/2017/b-17-01.pdf.
    On April 10, 2018, OMB issued OMB Bulletin No. 18-03, which 
superseded the August 15, 2017 OMB Bulletin No. 17-01. On September 
14, 2018, OMB issued OMB Bulletin No. 18-04, which superseded the 
April 10, 2018 OMB Bulletin No. 18-03. Historically OMB bulletins 
issued between decennial censuses have only contained minor 
modifications to CBSA delineations based on changes in population 
counts. However, OMB's 2010 Standards for Delineating Metropolitan 
and Micropolitan Standards created a larger mid-decade redelineation 
that takes into account commuting data from the American Commuting 
Survey. As a result, the September 14, 2018 OMB Bulletin No. 18-04 
included more modifications to the CBSAs than are typical for OMB 
bulletins issued between decennial censuses. We adopted the updates 
set forth in OMB Bulletin No. 18-04 in the FY 2021 IPPS/LTCH PPS 
final rule (85 FR 59050 through 59051). A copy of the September 14, 
2018 OMB Bulletin No. 18-04, may be obtained at https://www.whitehouse.gov/wp-content/uploads/2018/09/Bulletin-18-04.pdf.
    On March 6, 2020, OMB issued Bulletin No. 20-01, which provided 
updates to and superseded OMB Bulletin No. 18-04, which was issued 
on September 14, 2018. The attachments to OMB Bulletin No. 20-01 
provided detailed information on the update to statistical areas 
since September 14, 2018. (For a copy of this bulletin, we refer 
readers to the following website: https://www.whitehouse.gov/wp-content/uploads/2020/03/Bulletin-20-01.pdf.) In OMB Bulletin No. 20-
01, OMB announced one new Micropolitan Statistical Area and one new 
component of an existing Combined Statistical Area. After reviewing 
OMB Bulletin No. 20-01, we determined that the changes in Bulletin 
20-01 encompassed delineation changes that would not affect the 
CBSA-based labor market area delineations used under the LTCH PPS. 
Therefore, we adopted the updates set forth in OMB Bulletin No. 20-
01 in the FY 2022 IPPS/LTCH PPS final rule (86 FR 45556 through 
45557) consistent with our general policy of adopting OMB 
delineation updates; however, the LTCH PPS area wage level 
adjustment was not altered as a result of adopting the updates 
because the CBSA-based labor market area delineations were the same 
as the CBSA-based labor market area delineations adopted in the FY 
2021 IPPS/LTCH PPS final rule based on OMB Bulletin No. 18-04 (85 FR 
59050 through 59051).
    We believe the CBSA-based labor market area delineations, as 
established in OMB Bulletin 20-01, ensure that the LTCH PPS area 
wage level adjustment most appropriately accounts for and reflects 
the relative hospital wage levels in the geographic area of the 
hospital as compared to the national average hospital wage level 
based on the best available data that reflect the local economies 
and area wage levels of the hospitals that are currently located in 
these geographic areas (81 FR 57298). Therefore, for FY 2023, we did 
not propose any changes to the CBSA-based labor market area 
delineations as established in OMB Bulletin 20-01 and adopted in the 
FY 2022 IPPS/LTCH final rule.
    CBSAs are made up of one or more constituent counties. Each CBSA 
and constituent county has its own unique identifying codes. The 
Census Bureau maintains a complete list of changes to counties or 
county equivalent entities on their website at https://www.census.gov/programs-surveys/geography/technical-documentation/county-changes.html. We believe that it is important to use the 
latest counties or county equivalent entities to properly crosswalk 
LTCHs from a county to a CBSA for purposes of the wage indexes used 
under the LTCH PPS. Based on the latest information included in the 
Census Bureau's website at https://www.census.gov/programs-surveys/geography/technical-documentation/county-changes.2010.html, the 
Census Bureau has made the following updates to the Federal 
Information Processing Series (FIPS) codes for counties or county 
equivalent entities:
     Chugach Census Area, AK (FIPS State County Code 02-063) 
and Copper River Census Area, AK (FIPS State County Code 02-066) 
were created from former Valdez-Cordova Census Area (02-261) which 
was located in CBSA 02. The CBSA code for these two new county 
equivalents remains 02.
    We believe using the latest FIPS codes allows us to maintain a 
more accurate and up-to-date payment system that reflects population 
shifts and labor market conditions. Therefore, we are adopting these 
FIPS code updates listed previously, effective October 1, 2022. We 
note that while the county update changes listed previously changed 
the county names, the CBSAs to which these counties map did not 
change from the prior counties. We also note that there are 
currently no LTCHs located in these counties. However, if an LTCH 
were to open in one of these counties, there would be no impact or 
change to the LTCH for purposes of the LTCH PPS wage indexes as a 
result of our implementation of these FIPS code updates. We are 
publishing, as a supplemental file to this final rule, an updated 
county-to-CBSA crosswalk that reflects this provision.

3. Labor-Related Share for the LTCH PPS Standard Federal Payment Rate

    Under the payment adjustment for the differences in area wage 
levels under Sec.  412.525(c), the labor-related share of an LTCH's 
standard Federal payment rate is adjusted by the applicable wage 
index for the labor market area in which the LTCH is located. The 
LTCH PPS labor-related share currently represents the sum of the 
labor-related portion of operating costs and a labor-related portion 
of capital costs using the applicable LTCH market basket. Additional 
background information on the historical development of the labor-
related share under the LTCH PPS can be found in the RY 2007 LTCH 
PPS final rule (71 FR 27810 through 27817 and 27829 through 27830) 
and the FY 2012 IPPS/LTCH PPS final rule (76 FR 51766 through 51769 
and 51808).
    For FY 2013, we rebased and revised the market basket used under 
the LTCH PPS by adopting a 2009-based LTCH market basket. In 
addition, for FY 2013 through FY 2016, we determined the labor-
related share annually as the sum of the relative importance of each 
labor-related cost category of the 2009-based LTCH market basket for 
the respective fiscal year based on the best available data. (For 
more details, we refer readers to the FY 2013 IPPS/LTCH PPS final 
rule (77 FR 53477 through 53479).) For FY 2017, we rebased and 
revised the 2009-based LTCH market basket to reflect a 2013 base 
year. In addition, for FY 2017 through FY 2020, we determined the 
labor-related share annually as the sum of the relative importance 
of each labor-related cost category of the 2013-based LTCH market 
basket for the respective fiscal year based on the best available 
data. (For more details, we refer readers to the FY 2017 IPPS/LTCH 
PPS final rule (81 FR 57085 through 57096).) Then, effective for FY 
2021, we rebased and revised the 2013-based LTCH market basket to 
reflect a 2017 base year and determined the labor-related share 
annually as the sum of the relative importance of each labor-related 
cost category in the 2017-based LTCH market basket using the most 
recent available data. (For more details, we refer readers to the FY 
2021 IPPS/LTCH PPS final rule (85 FR 58909 through 58926).)
    In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28683 through 
26864), consistent with our historical practice, we proposed that 
the LTCH PPS labor-related share for FY 2023 is the sum of the FY 
2023 relative importance of each labor-related cost category in the 
LTCH market basket using the most recent available data. 
Specifically, we proposed that the labor-related share for FY 2023 
would continue to include the sum of the labor-related portion of 
operating costs from the 2017-based LTCH market basket (that is, the 
sum of the FY 2023 relative importance shares of Wages and Salaries; 
Employee Benefits; Professional Fees: Labor-Related; Administrative 
and Facilities Support Services; Installation, Maintenance, and 
Repair Services; All Other: Labor-related Services) and a portion of 
the relative importance of Capital-Related cost weight from the 
2017-based LTCH market basket. The relative importance reflects the 
different rates of price change for these cost categories between 
the base year (2017) and FY 2023. Based on IHS Global Inc.'s fourth 
quarter 2021 forecast of the 2017-based LTCH market basket, the sum 
of the FY 2023 relative importance for Wages and Salaries; Employee 
Benefits; Professional Fees: Labor-Related; Administrative and 
Facilities Support Services; Installation, Maintenance, & Repair 
Services; and All Other: Labor-Related Services was 64.0 percent. 
The portion of capital-related costs that is influenced by the local 
labor market is estimated to be 46

[[Page 49440]]

percent (that is, the same percentage applied to the 2009-based and 
2013-based LTCH market baskets). Since the FY 2023 relative 
importance for capital-related costs was 9.2 percent based on IHS 
Global Inc.'s fourth quarter 2021 forecast of the 2017-based LTCH 
market basket, we took 46 percent of 9.2 percent to determine the 
labor-related share of capital-related costs for FY 2023 of 4.2 
percent. Therefore, in the IPPS/LTCH PPS proposed rule (87 FR 
28684), we proposed a total labor-related share for FY 2023 of 68.2 
percent (the sum of 64.0 percent for the operating costs and 4.2 
percent for the labor-related share of capital-related costs). We 
also proposed that if more recent data became available after the 
publication of the proposed rule and before the publication of the 
final rule (for example, a more recent estimate of the relative 
importance of each labor-related cost category of the 2017-based 
LTCH market basket), we would use such data, if appropriate, to 
determine the FY 2023 LTCH PPS labor-related share.
    Comment: A commenter opposed the increase in labor-related share 
for LTCHs for FY 2023. The commenter noted that the increase in 
labor-related share adversely impacts any LTCH with a wage index of 
less than 1.0. According to the commenter, limiting the increase 
would help mitigate the growing disparity between high-wage and low-
wage states.
    Response: We thank the commenter for the feedback. As noted 
previously, effective for FY 2021, we rebased and revised the 2013-
based LTCH market basket to reflect a 2017 base year and determined 
the labor-related share annually as the sum of the relative 
importance of each labor-related cost category in the 2017-based 
LTCH market basket using the most recent available data (85 FR 58909 
through 58926). We continue to believe that this approach is the 
most appropriate methodology for determining the labor-related 
portion of the LTCH PPS standard Federal payment rate. We note that 
the proposed labor related share of 68.2 percent, which was based on 
IHS Global Inc's fourth quarter 2021 forecast of the 2017-based LTCH 
market basket, has been updated to reflect IHS Global Inc's second 
quarter 2022 forecast, and that this update, resulting in a labor 
related share of 68.0 percent, is a slightly smaller increase over 
the labor share from FY 2022, which was 67.9 percent.
    After consideration of public comments, we are finalizing the FY 
2023 labor-related share using the most recently available data. 
Based on IHS Global Inc.'s second quarter 2022 forecast of the 2017-
based LTCH market basket, the sum of the FY 2023 relative importance 
for Wages and Salaries; Employee Benefits; Professional Fees: Labor-
Related; Administrative and Facilities Support Services; 
Installation, Maintenance, & Repair Services; and All Other: Labor-
Related Services is 63.8 percent. The portion of capital-related 
costs that is influenced by the local labor market is estimated to 
be 46 percent (that is, the same percentage applied to the 2009-
based and 2013-based LTCH market baskets). Since the FY 2023 
relative importance for capital-related costs is 9.1 percent based 
on IHS Global Inc.'s second quarter 2022 forecast of the 2017-based 
LTCH market basket, we took 46 percent of 9.1 percent to determine 
the labor-related share of capital-related costs for FY 2023 of 4.2 
percent. Therefore, we are finalizing a total labor-related share 
for FY 2023 of 68.0 percent (the sum of 63.8 percent for the 
operating costs and 4.2 percent for the labor-related share of 
capital-related costs).
    4. Wage Index for FY 2023 for the LTCH PPS Standard Federal 
Payment Rate
    Historically, we have established LTCH PPS area wage index 
values calculated from acute care IPPS hospital wage data without 
taking into account geographic reclassification under sections 
1886(d)(8) and 1886(d)(10) of the Act (67 FR 56019). The area wage 
level adjustment established under the LTCH PPS is based on an 
LTCH's actual location without regard to the ``urban'' or ``rural'' 
designation of any related or affiliated provider. As with the IPPS 
wage index, wage data for multicampus hospitals with campuses 
located in different labor market areas (CBSAs) are apportioned to 
each CBSA where the campus (or campuses) are located. We also employ 
a policy for determining area wage index values for areas where 
there are no IPPS wage data.
    Consistent with our historical methodology, to determine the 
applicable area wage index values for the FY 2023 LTCH PPS standard 
Federal payment rate, under the broad authority of section 123 of 
the BBRA, as amended by section 307(b) of the BIPA, as we proposed, 
we are continuing to employ our historical practice of using the 
same data we used to compute the FY 2023 acute care hospital 
inpatient wage index, as discussed in section III. of the preamble 
of this final rule (that is, wage data collected from cost reports 
submitted by IPPS hospitals for cost reporting periods beginning 
during FY 2019) because these data are the most recent complete data 
available.
    In addition, as we proposed, we computed the FY 2023 LTCH PPS 
standard Federal payment rate area wage index values consistent with 
the ``urban'' and ``rural'' geographic classifications (that is, the 
proposed labor market area delineations as previously discussed in 
section V.B. of this Addendum) and our historical policy of not 
taking into account IPPS geographic reclassifications under sections 
1886(d)(8) and 1886(d)(10) of the Act in determining payments under 
the LTCH PPS. As we proposed, we also continued to apportion the 
wage data for multicampus hospitals with campuses located in 
different labor market areas to each CBSA where the campus or 
campuses are located, consistent with the IPPS policy. Lastly, 
consistent with our existing methodology for determining the LTCH 
PPS wage index values, for FY 2023 as we proposed, we continued to 
use our existing policy for determining area wage index values for 
areas where there are no IPPS wage data. Under our existing 
methodology, the LTCH PPS wage index value for urban CBSAs with no 
IPPS wage data is determined by using an average of all of the urban 
areas within the State, and the LTCH PPS wage index value for rural 
areas with no IPPS wage data is determined by using the unweighted 
average of the wage indices from all of the CBSAs that are 
contiguous to the rural counties of the State.
    Based on the FY 2019 IPPS wage data that we used to determine 
the FY 2023 LTCH PPS area wage index values in this final rule, 
there are no IPPS wage data for the urban area of Hinesville, GA 
(CBSA 25980). Consistent with our existing methodology, we 
calculated the FY 2023 wage index value for CBSA 25980 as the 
average of the wage index values for all of the other urban areas 
within the State of Georgia (that is, CBSAs 10500, 12020, 12060, 
12260, 15260, 16860, 17980, 19140, 23580, 31420, 40660, 42340, 46660 
and 47580), as shown in Table 12A, which is listed in section VI. of 
the Addendum to this final rule.
    Based on the FY 2019 IPPS wage data that we used to determine 
the FY 2023 LTCH PPS standard Federal payment rate area wage index 
values in this final rule, there are no rural areas without IPPS 
hospital wage data. Therefore, it is not necessary to use our 
established methodology to calculate a LTCH PPS wage index value for 
rural areas with no IPPS wage data for FY 2023. We note that, as 
IPPS wage data are dynamic, it is possible that the number of rural 
areas without IPPS wage data will vary in the future.

5. Permanent Cap on Wage Index Decreases

a. Permanent Cap on LTCH PPS Wage Index Decreases

    In the past, we have proposed and finalized temporary transition 
policies to mitigate significant changes to payments due to changes 
to the LTCH PPS wage index, particularly when adopting changes that 
have large negative impacts on an LTCH's payments. In the FY 2021 
IPPS/LTCH final rule (85 FR 59052), we implemented a 5-percent cap 
on any decrease in an LTCH's wage index from the LTCH's final wage 
index in FY 2020, so that the hospital's final wage index for FY 
2021 would not be less than 95 percent of its final wage index for 
FY 2020. We implemented this policy to mitigate potential negative 
consequences of finalizing the adoption of revised CBSA delineations 
announced in OMB Bulletin 18-04 for FY 2021. In particular, we 
acknowledged that a significant portion of Medicare LTCH PPS 
payments are adjusted by the wage index and that some changes in OMB 
delineations destabilized payments to LTCHs. We stated our belief 
that applying the 5-percent cap to all wage index decreases for FY 
2021 provided an adequate safeguard against significant payment 
reductions related to the adoption of the revised CBSAs and that it 
would improve stability and predictability in payment levels to 
LTCHs. We applied a budget neutrality adjustment to the FY 2021 
standard Federal payment rate to achieve budget neutrality for this 
policy (85 FR 59053).
    Although we did not propose or implement a cap on wage index 
decreases for LTCH's in FY 2022, we acknowledged that some 
commenters requested that we extend the FY 2021 transition policy, 
citing the continuing impact of changes related to the OMB updates 
and the unprecedented nature of the ongoing COVID-19 PHE. In 
response to those comments, we reiterated that our policy principles 
with regard to the wage index include generally using the most 
current data and information available and providing that

[[Page 49441]]

data and information, as well as addressing significant year-over-
year variations in Medicare payments in notice and comment 
rulemaking.
    For FY 2023, we further considered comments received during the 
FY 2022 rulemaking, including requests for a broader, permanent wage 
index policy to mitigate unpredictable changes in payments to LTCHs 
resulting from large wage index decreases. We recognize that changes 
to the wage index have the potential to create instability and 
significant negative impacts on certain providers even when we have 
not adopted specific changes to wage index policy. That is, year to 
year fluctuations in an area's wage index can occur due to external 
factors that can be difficult for an LTCH to predict and are often 
outside an LTCH's ability to directly control, such as the COVID-19 
PHE. We recognize that predictability in Medicare payments is 
important to enable hospitals to budget and plan their operations. 
For LTCHs, in particular, we further recognize that a significant 
portion of Medicare LTCH PPS payments are adjusted by the wage index 
and that a large decrease from one year to the next can have 
significant implications for LTCH payments.
    For these reasons, under the broad authority of section 123 of 
the BBRA, as amended by section 307(b) of the BIPA, in the FY 2023 
IPPS/LTCH PPS proposed rule (87 FR 28684 through 28685), we 
proposed, beginning with FY 2023, to apply a permanent 5-percent cap 
on any decrease to an LTCH's wage index from its wage index in the 
prior year. In the proposed rule, we stated our belief that a 5-
percent reduction is an appropriate threshold to mitigate large 
negative financial impacts on hospitals and limit the magnitude of 
the associated proposed budget neutrality adjustment (discussed 
later in section V.A.5. of the Addendum). Typical year-to-year 
variations in the LTCH wage index have historically been within 5 
percent, and we expect this will continue to be the case in future 
years. Because providers typically experience some level of wage 
index fluctuation, we stated our belief that applying a 5-percent 
cap on all wage index decreases each year, regardless of the reason 
for the decrease, would effectively mitigate instability and 
increase predictability in LTCH PPS payments due to any significant 
wage index decreases.
    In the proposed rule, we stated our belief that this proposed 
policy of applying a permanent cap to wage index decreases would 
provide greater predictability to LTCHs. That is, the policy would 
smooth year-to-year changes in LTCHs' wage indexes and provide for 
increased predictability in their wage index and thus their LTCH PPS 
payments. We also stated our belief that our proposed permanent 
policy would mitigate significant payment reductions due to changes 
in wage index policy, such as the adoption of the revised CBSAs in 
FY 2021, thereby eliminating the need for one-off temporary 
transition adjustments to wage index levels in the future. Because 
applying a 5-percent cap on all wage index decreases would generally 
represent a small overall impact on the adjustment for area wage 
levels, we stated our belief that the 5-percent cap would not 
distort the integrity of the wage index as a relative measure of the 
value of labor in a labor market area.
    Furthermore, consistent with the requirement at Sec.  
412.525(c)(2), that changes to area wage level adjustments are made 
in a budget neutral manner, we proposed that the 5-percent cap on 
the decrease on an LTCH's wage index would not result in any change 
in estimated aggregate LTCH PPS payments by including the 
application of this policy in the determination of the area wage 
level budget neutrality factor that is applied to the standard 
Federal payment rate, as is discussed later in section V.B.6. of the 
Addendum to the final rule.
    We proposed that an LTCH's wage index cap adjustment would be 
determined based on the wage index value applicable to the LTCH on 
the last day of the prior Federal fiscal year. We proposed that new 
LTCHs that became operational during the prior Federal fiscal year 
would be subject to the LTCH PPS wage index cap. For example, if an 
LTCH begins operations on July 1, 2022 and is paid its area wage 
index of 0.9000 for the remainder of FY 2022, its FY 2023 wage index 
would be capped at 95 percent of that value and could not be lower 
than 0.8550 (0.95 x 0.9000). However, for newly opened LTCHs that 
become operational on or after the first day of the fiscal year to 
which this final rule would apply, we proposed that these LTCHs 
would not be subject to the LTCH PPS wage index cap since they were 
not paid under the LTCH PPS in the prior year. These LTCHs would 
receive the calculated wage index for the area in which they are 
geographically located, even if other LTCHs in the same geographic 
area are receiving a wage cap. For example, a hospital that opens on 
December 1, 2022 would not be eligible for a capped wage index in FY 
2023, as it was not paid a wage index during FY 2022.
    Comment: We received several comments expressing support for our 
proposed permanent 5-percent cap on any decrease to an LTCH's wage 
index from its wage index in the prior year beginning with FY 2023. 
Commenters generally agreed that the cap would help mitigate 
significant payment decreases and provide stability and 
predictability to LTCH payments. Some commenters encouraged CMS to 
apply this general principle of increasing stability to other 
aspects of LTCH payment policies.
    Response: We appreciate the support for our proposal. We agree 
with commenters about the importance of stability and predictability 
in LTCH PPS payments. We will continue to consider additional policy 
options to achieve this objective in future rulemaking.
    Comment: MedPAC supported our proposal to cap LTCH's wage index 
decreases at 5 percent, but suggested also applying a cap to 
increases of more than 5 percent.
    Response: We appreciate MedPAC's suggestion that CMS should 
apply a cap on wage index increases greater than 5 percent. However, 
as we discussed in the proposed rule, the purpose of the proposed 
policy is to help mitigate the significant negative impacts of 
certain wage index changes. We believe applying a 5-percent cap on 
all wage index decreases would support increased predictability 
about LTCH PPS payments for providers, enabling them to more 
effectively budget and plan their operations. That is, we believe 
that a provider would be able to more effectively budget and plan 
when there is predictability about its expected minimum level of 
LTCH PPS payments in the upcoming fiscal year. We did not propose to 
limit wage index increases because we do not believe such a policy 
is needed to enable LTCHs to more effectively budget and plan their 
operations. So, we believe it is appropriate for providers that 
would experience an increase in their wage index value to receive 
the wage index value that most accurately reflects the labor costs 
in that area.
    Comment: A number of commenters disagreed with our proposal to 
implement the proposed 5-percent cap on wage index decreases in a 
budget neutral manner and maintained that CMS has the statutory 
authority to implement the proposed policy in a non-budget neutral 
manner. Some of these commenters indicated that their support of the 
cap was conditional on CMS not implementing the cap in a budget 
neutral manner.
    Response: While CMS's statutory authority is broad, we continue 
to believe it is appropriate to implement this policy in a budget 
neutral manner which is consistent with the requirement at Sec.  
412.525(c)(2) that changes to area wage level adjustments are made 
in a budget neutral manner. That is, we continue to believe that 
changes to area wage level adjustments, including the proposed 5-
percent cap on the decrease on an LTCH's wage index, should not 
result in any change in estimated aggregate LTCH PPS payments. We 
also anticipate that in the absence of proposed policy changes most 
LTCHs will not experience year-to-year wage index declines greater 
than 5 percent in any given year and that the overall budget 
neutrality adjustments associated with the policy will be relatively 
small and would not create volatility in LTCH PPS payments.
    Comment: A commenter recommended that CMS retroactively apply 
the 5-percent cap policy to the FY 2022 wage index for LTCHs that 
experienced wage index decreases due to their transition to a new 
CBSA based on the new OMB delineations that were finalized for FY 
2021.
    Response: As noted previously, in FY 2021, we implemented a 
transition to mitigate any negative effects of wage index changes by 
applying a 5-percent cap on any decrease in an LTCH's wage index 
from the LTCH's final wage index in FY 2020; we indicated that no 
cap would be applied to the reduction in the second year, FY 2022. 
In the FY 2023 IPPS/LTCH PPS proposed rule, we did not propose to 
modify that transition policy to extend the transition period for FY 
2022. We have historically implemented transitions of limited 
duration to address CBSA changes due to substantial updates to OMB 
delineations. In accordance with our policy principles that we use 
the most updated data and information available with regard to the 
wage index, we proposed that the FY 2023 5-percent cap wage index 
policy would be prospective to mitigate any significant decreases 
beginning in FY 2023.

[[Page 49442]]

    Comment: Some commenters disagreed with our proposal to apply 
the 5-percent cap on decreases to an LTCH's wage index only to 
existing hospitals; that is, hospitals that were already operational 
on the last day of the prior Federal fiscal year. The commenters 
stated that this policy would create unnecessary inequity in 
Medicare payments for hospitals in the same market. They encouraged 
CMS to apply the same area wage index value for new and existing 
hospitals.
    Response: We appreciate the commenters' concerns about equity 
and fairness. As we have stated, however, the primary purpose of 
applying a 5-percent cap on decreases to an LTCH's wage index is to 
support predictability about LTCH payments, mitigate financial 
instability from one year to the next, and enable LTCHs to more 
effectively budget and plan their operations. LTCHs that were not 
operational on the last day of the prior Federal fiscal year could 
not experience LTCH PPS payment decreases relative to the prior year 
since they would have received no LTCH PPS payments in the prior 
year. In addition, we do not expect that there would be many LTCHs 
in this situation. There are few newly created LTCHs, in general, 
and even fewer that will open in an area that is receiving an 
adjustment under the policy. Finally, we note that any differential 
in the wage index related to a newly operational LTCH and an 
existing LTCH in the same labor market area will generally be 
limited to a single year, since typical year-to-year variations in 
the LTCH wage index have historically been, and we expect will 
continue to be, within 5 percent.
    Comment: A commenter, while supportive of the proposed 5-percent 
cap on wage index decreases, believes it does not correct for an 
ongoing problem with the range in wage index values amongst LTCHs. 
This commenter believes the range in wage index values is too large 
and that CMS should establish an annual cap that would be placed on 
CBSAs with high wage index values. Furthermore, the same commenter 
believes that LTCHs should have the option to reclassify to a 
different CBSA as is permitted for IPPS hospitals.
    Response: We disagree with the commenters' suggestion that we 
establish a cap for CBSAs with high wage index values. We believe 
the LTCH PPS wage index accurately reflects the relative labor costs 
in areas with both high wage index and low wage index values. In 
reference to the comment on LTCHs having an option to reclassify to 
a different CBSA, we did not propose this specific policy suggested 
by the commenters, but we will take this comment into consideration 
to potentially inform future rulemaking.
    After consideration of the public comments we received, we are 
finalizing as proposed, that, beginning in FY 2023, we will apply a 
permanent 5-percent cap on any decrease to an LTCH's wage index from 
its wage index in the prior year. Also, after consideration of the 
public comments we received, we are establishing that this wage 
index cap policy will be implemented in a budget neutral manner by 
including the application of this policy in the area wage level 
budget neutrality factor that is applied to the standard Federal 
payment rate. We believe that this policy appropriately mitigates 
instability and significant negative impacts to LTCHs resulting from 
significant changes to the wage index and increases predictability 
of LTCH payments. We note that this provision is similar to our 
provision establishing a permanent 5-percent cap on annual wage 
index decreases for IPPS hospitals, as discussed in section III.N. 
of the preamble to this final rule.
    We received no comments about our proposal to modify text at 
Sec.  412.525(c)(1) to reflect the permanent cap on wage index 
decreases. Therefore, as we proposed, we are reflecting the 
permanent cap on wage index decreases at Sec.  412.525(c)(1) by 
adding paragraphs (c)(1)(i) and (ii) to specify that CMS updates the 
wage index for LTCHs annually and that, beginning in FY 2023, if CMS 
determines that an LTCH's wage index value for a fiscal year would 
decrease by more than 5 percent as compared to the LTCH's wage index 
value for the prior year, we will limit the decrease to 5 percent 
for the fiscal year.
    For each LTCH we identify in our rulemaking data, we are 
including in a supplemental data file the wage index values from 
both fiscal years used in determining its capped wage index. This 
includes the LTCH's final prior year wage index value, the LTCH's 
uncapped current year wage index value, and the LTCH's capped 
current year wage index value. Due to the lag in rulemaking data, a 
new LTCH may not be listed in this supplemental file for a few 
years. For this reason, a newly opened LTCH could contact their MAC 
to ensure that its wage index value is not less than 95 percent of 
the value paid to it for the prior Federal fiscal year. This 
supplemental data file for public use will be posted on the CMS 
website for this final rule at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html.

b. Permanent Cap on IPPS Comparable Wage Index Decreases

    Determining LTCH PPS payments for short-stay-outlier cases 
(reflected in Sec.  412.529) and site neutral payment rate cases 
(reflected in Sec.  412.522(c)) requires calculating an ``IPPS 
comparable amount.'' For information on this ``IPPS comparable 
amount'' calculation, we refer the reader to the FY 2016 IPPS/LTCH 
PPS final rule (80 FR 49608 through 49610). Determining LTCH PPS 
payments for LTCHs that do not meet the applicable discharge payment 
percentage (reflected in Sec.  412.522(d)) requires calculating an 
``IPPS equivalent amount.'' For information on this ``IPPS 
equivalent amount'' calculation, we refer the reader to the FY 2020 
IPPS/LTCH PPS final rule (84 FR 42439 through 42445).
    Calculating both the ``IPPS comparable amount'' and the ``IPPS 
equivalent amount'' requires adjusting the IPPS operating and 
capital standardized amounts by the applicable IPPS wage index for 
nonreclassified IPPS hospitals. That is, the standardized amounts 
are adjusted by the IPPS wage index for nonreclassified IPPS 
hospitals located in the same geographic area as the LTCH. 
Consistent with our proposal to apply a 5-percent cap on decreases 
in the LTCH PPS wage index and under the broad authority of section 
123 of the BBRA, as amended by section 307(b) of the BIPA, in the FY 
2023 IPPS/LTCH PPS proposed rule (87 FR 28685 through 28686), we 
also proposed, beginning with FY 2023 to apply a permanent 5-percent 
cap on decreases in an LTCH's applicable IPPS comparable wage index 
from its applicable IPPS comparable wage index in the prior year. As 
with our proposed policy to apply a cap on decreases in the LTCH PPS 
wage index each year, we stated our belief that a permanent cap on 
applicable IPPS comparable wage index decreases would provide 
greater predictability to LTCHs by mitigating instability and 
significant negative impacts to LTCHs resulting from significant 
changes to the wage index and increase predictability of LTCH 
payments. Historically, we have not budget neutralized changes to 
LTCH PPS payments that result from the annual update of the IPPS 
wage index for nonreclassified IPPS hospitals. Consistent with this 
approach, we proposed that the cap on decreases in an LTCH's 
applicable IPPS comparable wage index not be applied in a budget 
neutral manner.
    We proposed that an LTCH's applicable IPPS comparable wage index 
cap adjustment would be determined based on the wage index value 
assigned to the LTCH on the last day of the prior Federal fiscal 
year. We also proposed that new LTCHs that became operational during 
the prior Federal fiscal year be subject to the applicable IPPS 
comparable wage index cap. However, for newly opened LTCHs that 
become operational on or after the first day of the fiscal year to 
which this final rule applies, we proposed that these LTCHs would 
not be subject to the applicable IPPS comparable wage index cap 
since they were not paid under the LTCH PPS in the prior year.
    We received no comments on our proposal to apply a permanent 5-
percent cap on decreases in an LTCH's applicable IPPS comparable 
wage index from its applicable IPPS comparable wage index in the 
prior year. Therefore, we are finalizing this proposal without 
modification.
    We received no comments about our proposal to modify text at 
Sec.  412.529(d)(4)(ii)(B) and Sec.  412.529(d)(4)(iii)(B) to 
reflect the permanent cap on IPPS comparable wage index decreases. 
Similarly, we received no comments on our proposal to remove the 
reference in Sec.  412.529(d)(4)(iii)(B) related to the applicable 
large urban location adjustment. Therefore, as proposed, we are 
reflecting the permanent cap on IPPS comparable wage index decreases 
at Sec.  412.529(d)(4)(ii)(B) to state that, beginning in FY 2023, 
an LTCH's applicable IPPS wage index used to adjust the IPPS 
operating standardized amount is subject to a 5-percent cap on 
decreases to an LTCH's applicable IPPS wage index value from the 
prior fiscal year. We also are reflecting the permanent cap on IPPS 
comparable wage index decreases at Sec.  412.529(d)(4)(iii)(B) to 
state that, beginning in FY 2023, an LTCH's applicable IPPS wage 
index used to adjust the IPPS capital Federal rate is subject to a 
5-percent cap on decreases to an LTCH's

[[Page 49443]]

applicable IPPS wage index value from the prior fiscal year. In 
addition, we are finalizing our proposal to remove the reference in 
Sec.  412.529(d)(4)(iii)(B) related to the applicable large urban 
location adjustment because this policy is no longer applicable 
under the IPPS effective with discharges occurring on or after 
October 1, 2007 (72 FR 47400).
    Similar to the information we made available for the cap on the 
LTCH PPS wage index values (described previously), for each LTCH we 
identify in our rulemaking data, we are including in a supplemental 
data file the wage index values from both fiscal years used in 
determining its capped applicable IPPS comparable wage index. Due to 
the lag in rulemaking data, a new LTCH may not be listed in this 
supplemental file for a few years. For this reason, a newly opened 
LTCH could contact its MAC to ensure that its applicable IPPS 
comparable wage index value is not less than 95 percent of the value 
paid to them for the prior Federal fiscal year. This supplemental 
data file for public use will be posted on the CMS website for this 
final rule at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html.

6. Budget Neutrality Adjustments for Changes to the LTCH PPS Standard 
Federal Payment Rate Area Wage Level Adjustment

    Historically, the LTCH PPS wage index and labor-related share 
are updated annually based on the latest available data. Under Sec.  
412.525(c)(2), any changes to the area wage index values or labor-
related share are to be made in a budget neutral manner such that 
estimated aggregate LTCH PPS payments are unaffected; that is, will 
be neither greater than nor less than estimated aggregate LTCH PPS 
payments without such changes to the area wage level adjustment. 
Under this policy, we determine an area wage level adjustment budget 
neutrality factor that is applied to the standard Federal payment 
rate to ensure that any changes to the area wage level adjustments 
are budget neutral such that any changes to the area wage index 
values or labor-related share would not result in any change 
(increase or decrease) in estimated aggregate LTCH PPS payments. 
Accordingly, under Sec.  412.523(d)(4), we have applied an area wage 
level adjustment budget neutrality factor in determining the 
standard Federal payment rate, and we also established a methodology 
for calculating an area wage level adjustment budget neutrality 
factor. (For additional information on the establishment of our 
budget neutrality policy for changes to the area wage level 
adjustment, we refer readers to the FY 2012 IPPS/LTCH PPS final rule 
(76 FR 51771 through 51773 and 51809).)
    For FY 2023, in accordance with Sec.  412.523(d)(4), as we 
proposed, we applied an area wage level budget neutrality factor to 
adjust the LTCH PPS standard Federal payment rate to account for the 
estimated effect of the adjustments or updates to the area wage 
level adjustment under Sec.  412.525(c)(1) on estimated aggregate 
LTCH PPS payments, consistent with the methodology we established in 
the FY 2012 IPPS/LTCH PPS final rule (76 FR 51773). As discussed in 
section V.B.5. of the Addendum to this final rule, for each year, 
beginning with FY 2023, we are limiting a hospital's LTCH PPS wage 
index value for the coming year by capping it at 95 percent of its 
prior year value. As also discussed previously, we are applying the 
5-percent cap on wage index decreases, consistent with Sec.  
412.525(c)(2), in a budget neutral manner.
    Specifically, as we proposed, we determined an area wage level 
adjustment budget neutrality factor that is applied to the LTCH PPS 
standard Federal payment rate under Sec.  412.523(d)(4) for FY 2023 
using the following methodology, which will incorporate our 5-
percent cap on decreases in a hospital's wage index:
    Step 1--Simulate estimated aggregate LTCH PPS standard Federal 
payment rate payments using the FY 2022 wage index values and the FY 
2022 labor-related share of 67.9 percent.
    Step 2--Simulate estimated aggregate LTCH PPS standard Federal 
payment rate payments using the FY 2023 wage index values (including 
application of the 5-percent cap on wage index decreases) and the FY 
2023 labor-related share of 68.0 percent. (As noted previously, the 
changes to the wage index values based on updated hospital wage data 
are discussed in section V.B.4. of this Addendum to this final rule 
and the labor-related share is discussed in section V.B.3. of this 
Addendum to this final rule.)
    Step 3--Calculate the ratio of these estimated total LTCH PPS 
standard Federal payment rate payments by dividing the estimated 
total LTCH PPS standard Federal payment rate payments using the FY 
2022 area wage level adjustments (calculated in Step 1) by the 
estimated total LTCH PPS standard Federal payment rate payments 
using the FY 2023 updates to the area wage level adjustment 
(calculated in Step 2) to determine the budget neutrality factor for 
updates to the area wage level adjustment for FY 2023 LTCH PPS 
standard Federal payment rate payments.
    Step 4--Apply the FY 2023 updates to the area wage level 
adjustment budget neutrality factor from Step 3 to determine the FY 
2023 LTCH PPS standard Federal payment rate after the application of 
the FY 2023 annual update.
    In section I.F. of the preamble to this final rule, we discuss 
our use of FY 2021 claims data for the FY 2023 LTCH PPS ratesetting. 
We also state our belief that it is reasonable to assume that there 
will be fewer COVID-19 hospitalizations among Medicare beneficiaries 
at LTCHs in FY 2023 than there were in FY 2021. For this reason, we 
are making modifications in our determination of the FY 2023 MS-LTC-
DRG relative weights and outlier fixed-loss amount for LTCH PPS 
standard Federal payment rate cases. We believe that these 
modifications will account for an anticipated decline in, but not 
elimination of, COVID-19 hospitalizations at LTCHs in FY 2023. 
However, in the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28687), 
when modeling payments for determining the area wage level 
adjustment budget neutrality factor, we proposed to use the full set 
of LTCH PPS standard Federal payment rate cases (including all 
COVID-19 cases) identified in the FY 2021 claims data. We stated 
that in the absence of a set of MedPAR claims that reflect our 
expectation that there will be fewer (but not zero) COVID-19 cases 
in FY 2023 as compared to the COVID-19 cases in the FY 2021 claims 
data, we believe this is the best data available for determining the 
budget neutrality factors. We also solicited feedback from 
commenters on alternative ways to use the FY 2021 claims data for 
purposes of calculating the FY 2023 budget neutrality factors. We 
received no comments on this proposal or our request for feedback on 
alternatives and are finalizing this proposal without modification. 
Therefore, for this final rule, when modeling payments for 
determining the budget neutrality factors, we used the full set of 
standard Federal payment rate cases (including all COVID-19 cases) 
identified in the FY 2021 claims data. We note this is consistent 
with the calculation of the budget neutrality factors for changes to 
the MS-LTC-DRG classifications and relative weights (including the 
10-percent cap) discussed in section VIII.B.4.b. (Step 11) of the 
preamble of this final rule. We also note this is consistent with 
the approach under the IPPS as discussed in section II.A.4. of the 
Addendum of this final rule.
    We note that, because the area wage level adjustment under Sec.  
412.525(c) is an adjustment to the LTCH PPS standard Federal payment 
rate, consistent with historical practice, we only used data from 
claims that qualified for payment at the LTCH PPS standard Federal 
payment rate under the dual rate LTCH PPS to calculate the FY 2023 
LTCH PPS standard Federal payment rate area wage level adjustment 
budget neutrality factor. For this final rule, using the steps in 
the methodology previously described, we determined a FY 2023 LTCH 
PPS standard Federal payment rate area wage level adjustment budget 
neutrality factor of 1.0004304. Accordingly, in section V.A. of the 
Addendum to this final rule, we applied the area wage level 
adjustment budget neutrality factor of 1.0004304 to determine the FY 
2023 LTCH PPS standard Federal payment rate, in accordance with 
Sec.  412.523(d)(4).

C. Cost-of-Living Adjustment (COLA) for LTCHs Located in Alaska and 
Hawaii

    Under Sec.  412.525(b), a cost-of-living adjustment (COLA) is 
provided for LTCHs located in Alaska and Hawaii to account for the 
higher costs incurred in those States. Specifically, we apply a COLA 
to payments to LTCHs located in Alaska and Hawaii by multiplying the 
nonlabor-related portion of the standard Federal payment rate by the 
applicable COLA factors established annually by CMS. Higher labor-
related costs for LTCHs located in Alaska and Hawaii are taken into 
account in the adjustment for area wage levels previously described. 
The methodology used to determine the COLA factors for Alaska and 
Hawaii is based on a comparison of the growth in the Consumer Price 
Indexes (CPIs) for Anchorage, Alaska, and Honolulu, Hawaii, relative 
to the growth in the CPI for the average U.S. city as published by 
the Bureau of Labor Statistics (BLS). It also includes a 25-percent 
cap on the CPI-updated COLA factors. Under our

[[Page 49444]]

current policy, we update the COLA factors using the methodology as 
previously described every 4 years (at the same time as the update 
to the labor-related share of the IPPS market basket) and we last 
updated the COLA factors for Alaska and Hawaii published by OPM for 
2009 in FY 2022 (86 FR 45559 through 45560).
    We continue to believe that determining updated COLA factors 
using this methodology would appropriately adjust the nonlabor-
related portion of the LTCH PPS standard Federal payment rate for 
LTCHs located in Alaska and Hawaii. Therefore, in this final rule, 
for FY 2023, under the broad authority conferred upon the Secretary 
by section 123 of the BBRA, as amended by section 307(b) of the 
BIPA, to determine appropriate payment adjustments under the LTCH 
PPS, as we proposed, we are continuing to use the COLA factors based 
on the 2009 OPM COLA factors updated through 2020 by the comparison 
of the growth in the CPIs for Anchorage, Alaska, and Honolulu, 
Hawaii, relative to the growth in the CPI for the average U.S. city 
as established in the FY 2022 IPPS/LTCH PPS final rule. (For 
additional details on our current methodology for updating the COLA 
factors for Alaska and Hawaii and for a discussion on the FY 2022 
COLA factors, we refer readers to the FY 2022 IPPS/LTCH PPS final 
rule (86 FR 45559 through 45560).)
[GRAPHIC] [TIFF OMITTED] TR10AU22.221

D. Adjustment for LTCH PPS High Cost Outlier (HCO) Cases

1. HCO Background

    From the beginning of the LTCH PPS, we have included an 
adjustment to account for cases in which there are extraordinarily 
high costs relative to the costs of most discharges. Under this 
policy, additional payments are made based on the degree to which 
the estimated cost of a case (which is calculated by multiplying the 
Medicare allowable covered charge by the hospital's overall hospital 
CCR) exceeds a fixed-loss amount. This policy results in greater 
payment accuracy under the LTCH PPS and the Medicare program, and 
the LTCH sharing the financial risk for the treatment of 
extraordinarily high-cost cases.
    We retained the basic tenets of our HCO policy in FY 2016 when 
we implemented the dual rate LTCH PPS payment structure under 
section 1206 of Public Law 113-67. LTCH discharges that meet the 
criteria for exclusion from the site neutral payment rate (that is, 
LTCH PPS standard Federal payment rate cases) are paid at the LTCH 
PPS standard Federal payment rate, which includes, as applicable, 
HCO payments under Sec.  412.523(e). LTCH discharges that do not 
meet the criteria for exclusion are paid at the site neutral payment 
rate, which includes, as applicable, HCO payments under Sec.  
412.522(c)(2)(i). In the FY 2016 IPPS/LTCH PPS final rule, we 
established separate fixed-loss amounts and targets for the two 
different LTCH PPS payment rates. Under this bifurcated policy, the 
historic 8-percent HCO target was retained for LTCH PPS standard 
Federal payment rate cases, with the fixed-loss amount calculated 
using only data from LTCH cases that would have been paid at the 
LTCH PPS standard Federal payment rate if that rate had been in 
effect at the time of those discharges. For site neutral payment 
rate cases, we adopted the operating IPPS HCO target (currently 5.1 
percent) and set the fixed-loss amount for site neutral payment rate 
cases at the value of the IPPS fixed-loss amount. Under the HCO 
policy for both payment rates, an LTCH receives 80 percent of the 
difference between the estimated cost of the case and the applicable 
HCO threshold, which is the sum of the LTCH PPS payment for the case 
and the applicable fixed-loss amount for such case.
    To maintain budget neutrality, consistent with the budget 
neutrality requirement at Sec.  412.523(d)(1) for HCO payments to 
LTCH PPS standard Federal rate payment cases, we also adopted a 
budget neutrality requirement for HCO payments to site neutral 
payment rate cases by applying a budget neutrality factor to the 
LTCH PPS payment for those site neutral payment rate cases. (We 
refer readers to Sec.  412.522(c)(2)(i) of the regulations for 
further details.) We note that, during the 4-year transitional 
period, the site neutral payment rate HCO budget neutrality factor 
did not apply to the LTCH PPS standard Federal payment rate portion 
of the blended payment rate at Sec.  412.522(c)(3) payable to site 
neutral payment rate cases. (For additional details on the HCO 
policy adopted for site neutral payment rate cases under the dual 
rate LTCH PPS payment structure, including the budget neutrality 
adjustment for HCO payments to site neutral payment rate cases, we 
refer readers to the FY 2016 IPPS/LTCH PPS final rule (80 FR 49617 
through 49623).)

2. Determining LTCH CCRs Under the LTCH PPS

a. Background

    As noted previously, CCRs are used to determine payments for HCO 
adjustments for both payment rates under the LTCH PPS and also are 
used to determine payments for site neutral payment rate cases. As 
noted earlier, in determining HCO and the site neutral payment rate 
payments (regardless of whether the case is also an HCO), we 
generally calculate the estimated cost of the case by multiplying 
the LTCH's overall CCR by the Medicare allowable charges for the 
case. An overall CCR is used because the LTCH PPS uses a single 
prospective payment per discharge that covers both inpatient 
operating and capital-related costs. The LTCH's overall CCR is 
generally computed based on the sum of LTCH operating and capital 
costs (as described in Section 150.24, Chapter 3, of the Medicare 
Claims Processing Manual (Pub. 100-4)) as compared to total Medicare 
charges (that is, the sum of its operating and capital inpatient 
routine and ancillary charges), with those values determined from 
either the most recently settled cost report or the most recent 
tentatively settled cost report, whichever is from the latest cost 
reporting period. However, in certain instances, we use an 
alternative CCR, such as the statewide average CCR, a CCR that is 
specified by CMS, or one that is requested by the hospital. (We 
refer readers to Sec.  412.525(a)(4)(iv) of the regulations for 
further details regarding CCRs and HCO adjustments for either LTCH 
PPS payment rate and Sec.  412.522(c)(1)(ii) for the site neutral 
payment rate.)
    The LTCH's calculated CCR is then compared to the LTCH total CCR 
ceiling. Under our established policy, an LTCH with a calculated CCR 
in excess of the applicable maximum CCR threshold (that is, the LTCH 
total CCR ceiling, which is calculated as 3 standard deviations from 
the national geometric average CCR) is generally assigned the 
applicable statewide CCR. This policy is premised on a belief that 
calculated CCRs in excess of the LTCH total CCR ceiling are most 
likely due to faulty data reporting or entry, and CCRs based on 
erroneous data should

[[Page 49445]]

not be used to identify and make payments for outlier cases.

b. LTCH Total CCR Ceiling

    Consistent with our historical practice, as we proposed, we used 
the best available data to determine the LTCH total CCR ceiling for 
FY 2023 in this final rule. Specifically, in this final rule, we 
used our established methodology for determining the LTCH total CCR 
ceiling based on IPPS total CCR data from the March 2022 update of 
the Provider Specific File (PSF), which is the most recent data 
available. Accordingly, we are establishing an LTCH total CCR 
ceiling of 1.312 under the LTCH PPS for FY 2023 in accordance with 
Sec.  412.525(a)(4)(iv)(C)(2) for HCO cases under either payment 
rate and Sec.  412.522(c)(1)(ii) for the site neutral payment rate. 
(For additional information on our methodology for determining the 
LTCH total CCR ceiling, we refer readers to the FY 2007 IPPS final 
rule (71 FR 48117 through 48119).)
    We did not receive any public comments on our proposals. 
Therefore, we are finalizing our proposals as described previously, 
without modification.

c. LTCH Statewide Average CCRs

    Our general methodology for determining the statewide average 
CCRs used under the LTCH PPS is similar to our established 
methodology for determining the LTCH total CCR ceiling because it is 
based on ``total'' IPPS CCR data. (For additional information on our 
methodology for determining statewide average CCRs under the LTCH 
PPS, we refer readers to the FY 2007 IPPS final rule (71 FR 48119 
through 48120).) Under the LTCH PPS HCO policy at Sec.  
412.525(a)(4)(iv)(C), the SSO policy at Sec.  412.529(f)(4)(iii), 
and the site neutral payment rate at Sec.  412.522(c)(1)(ii), the 
MAC may use a statewide average CCR, which is established annually 
by CMS, if it is unable to determine an accurate CCR for an LTCH in 
one of the following circumstances: (1) New LTCHs that have not yet 
submitted their first Medicare cost report (a new LTCH is defined as 
an entity that has not accepted assignment of an existing hospital's 
provider agreement in accordance with Sec.  489.18); (2) LTCHs whose 
calculated CCR is in excess of the LTCH total CCR ceiling; and (3) 
other LTCHs for whom data with which to calculate a CCR are not 
available (for example, missing or faulty data). (Other sources of 
data that the MAC may consider in determining an LTCH's CCR include 
data from a different cost reporting period for the LTCH, data from 
the cost reporting period preceding the period in which the hospital 
began to be paid as an LTCH (that is, the period of at least 6 
months that it was paid as a short-term, acute care hospital), or 
data from other comparable LTCHs, such as LTCHs in the same chain or 
in the same region.)
    Consistent with our historical practice of using the best 
available data, in this final rule, we are using our established 
methodology for determining the LTCH statewide average CCRs, based 
on the most recent complete IPPS ``total CCR'' data from the March 
2022 update of the PSF. As we proposed, we are establishing LTCH PPS 
statewide average total CCRs for urban and rural hospitals that will 
be effective for discharges occurring on or after October 1, 2022, 
through September 30, 2023, in Table 8C listed in section VI. of the 
Addendum to this final rule (and available via the internet on the 
CMS website). Consistent with our historical practice, as we also 
proposed, we used the best available data to determine the LTCH PPS 
statewide average total CCRs for FY 2023 in the final rule.
    Under the current LTCH PPS labor market areas, all areas in 
Delaware, the District of Columbia, New Jersey, and Rhode Island are 
classified as urban. Therefore, there are no rural statewide average 
total CCRs listed for those jurisdictions in Table 8C. This policy 
is consistent with the policy that we established when we revised 
our methodology for determining the applicable LTCH statewide 
average CCRs in the FY 2007 IPPS final rule (71 FR 48119 through 
48121) and is the same as the policy applied under the IPPS. In 
addition, although Connecticut has areas that are designated as 
rural, in our calculation of the LTCH statewide average CCRs, there 
were no short-term, acute care IPPS hospitals classified as rural or 
LTCHs located in these rural areas as of March 2022. Therefore, 
consistent with our existing methodology, we used the national 
average total CCR for rural IPPS hospitals for rural Connecticut in 
Table 8C. While Massachusetts also has rural areas, the statewide 
average CCR for rural areas in Massachusetts is based on one IPPS 
provider whose CCR is an atypical 1.205. Because this is much higher 
than the statewide urban average (0.484) and furthermore implies 
costs greater than charges, as with Connecticut, we used the 
national average total CCR for rural IPPS hospitals for rural 
Massachusetts in Table 8C. Furthermore, consistent with our existing 
methodology, in determining the urban and rural statewide average 
total CCRs for Maryland LTCHs paid under the LTCH PPS, as we 
proposed, we are continuing to use, as a proxy, the national average 
total CCR for urban IPPS hospitals and the national average total 
CCR for rural IPPS hospitals, respectively. We are using this proxy 
because we believe that the CCR data in the PSF for Maryland 
hospitals may not be entirely accurate (as discussed in greater 
detail in the FY 2007 IPPS final rule (71 FR 48120)).
    We did not receive any public comments on our proposals. 
Therefore, we are finalizing our proposals as described previously, 
without modification.

d. Reconciliation of HCO Payments

    Under the HCO policy at Sec.  412.525(a)(4)(iv)(D), the payments 
for HCO cases are subject to reconciliation (regardless of whether 
payment is based on the LTCH standard Federal payment rate or the 
site neutral payment rate). Specifically, any such payments are 
reconciled at settlement based on the CCR that was calculated based 
on the cost report coinciding with the discharge. For additional 
information on the reconciliation policy, we refer readers to 
sections 150.26 through 150.28 of the Medicare Claims Processing 
Manual (Pub. 100-4), as added by Change Request 7192 (Transmittal 
2111; December 3, 2010), and the RY 2009 LTCH PPS final rule (73 FR 
26820 through 26821).

3. High-Cost Outlier Payments for LTCH PPS Standard Federal Payment 
Rate Cases

a. High-Cost Outlier Payments for LTCH PPS Standard Federal Payment 
Rate Cases

    Under the regulations at Sec.  412.525(a)(2)(ii) and as required 
by section 1886(m)(7) of the Act, the fixed-loss amount for HCO 
payments is set each year so that the estimated aggregate HCO 
payments for LTCH PPS standard Federal payment rate cases are 
99.6875 percent of 8 percent (that is, 7.975 percent) of estimated 
aggregate LTCH PPS payments for LTCH PPS standard Federal payment 
rate cases. (For more details on the requirements for high-cost 
outlier payments in FY 2018 and subsequent years under section 
1886(m)(7) of the Act and additional information regarding high-cost 
outlier payments prior to FY 2018, we refer readers to the FY 2018 
IPPS/LTCH PPS final rule (82 FR 38542 through 38544).)

b. Fixed-Loss Amount for LTCH PPS Standard Federal Payment Rate Cases 
for FY 2023

    When we implemented the LTCH PPS, we established a fixed-loss 
amount so that total estimated outlier payments are projected to 
equal 8 percent of total estimated payments (that is, the target 
percentage) under the LTCH PPS (67 FR 56022 through 56026). When we 
implemented the dual rate LTCH PPS payment structure beginning in FY 
2016, we established that, in general, the historical LTCH PPS HCO 
policy would continue to apply to LTCH PPS standard Federal payment 
rate cases. That is, the fixed-loss amount for LTCH PPS standard 
Federal payment rate cases would be determined using the LTCH PPS 
HCO policy adopted when the LTCH PPS was first implemented, but we 
limited the data used under that policy to LTCH cases that would 
have been LTCH PPS standard Federal payment rate cases if the 
statutory changes had been in effect at the time of those 
discharges.
    To determine the applicable fixed-loss amount for LTCH PPS 
standard Federal payment rate cases, we estimate outlier payments 
and total LTCH PPS payments for each LTCH PPS standard Federal 
payment rate case (or for each case that would have been an LTCH PPS 
standard Federal payment rate case if the statutory changes had been 
in effect at the time of the discharge) using claims data from the 
MedPAR files. In accordance with Sec.  412.525(a)(2)(ii), the 
applicable fixed-loss amount for LTCH PPS standard Federal payment 
rate cases results in estimated total outlier payments being 
projected to be equal to 7.975 percent of projected total LTCH PPS 
payments for LTCH PPS standard Federal payment rate cases.
    In the FY 2022 IPPS/LTCH PPS final rule (86 FR 45562 through 
45566), we finalized a number of technical changes to the 
methodology for determining the charge inflation factor and the CCR 
used when calculating the fixed-loss amount, while maintaining 
estimated HCO payments at the projected 7.975 percent of total 
estimated LTCH PPS payments for LTCH PPS standard Federal payment 
rate cases. First, we

[[Page 49446]]

finalized a technical change to the methodology for determining the 
charge inflation factor applied to the charges on the MedPAR claims 
when calculating the fixed-loss amount for each FY. Second, we 
finalized a technical change to the methodology for determining the 
CCRs used when calculating the fixed-loss amount for each FY. These 
methodologies are described in greater detail later in this section 
of this Addendum.

(1) Charge Inflation Factor for Use in Determining the Fixed-Loss 
Amount for LTCH PPS Standard Federal Payment Rate Cases for FY 2023

    Under the LTCH PPS, the cost of each claim is estimated by 
multiplying the charges on the claim by the provider's CCR. Due to 
the lag time in the availability of claims data, when estimating 
costs for the upcoming payment year we typically inflate the charges 
from the claims data by a uniform factor.
    For greater accuracy in calculating the fixed-loss amount, in 
the FY 2022 IPPS/LTCH PPS final rule (86 FR 45562 through 45566), we 
finalized a technical change to our methodology for determining the 
charge inflation factor. Similar to the method used under the IPPS 
hospital payment methodology (as discussed in section II.A.4.h.(2) 
of the Addendum to this final rule), our methodology determines the 
LTCH charge inflation factor based on the historical growth in 
charges for LTCH PPS standard Federal payment rate cases, calculated 
using historical MedPAR claims data. In this section of this 
Addendum, we describe our charge inflation factor methodology using 
the most recently available data. However, as discussed in further 
detail later in this section, we did not propose to use the charge 
inflation factor derived from the most recently available data. 
Rather, we proposed using the charge inflation factor used in the FY 
2022 IPPS/LTCH PPS final rule that was based on the growth in 
charges that occurred between FY 2018 and FY 2019.
    Step 1--Identify LTCH PPS Standard Federal Payment Rate Cases
    The first step in our methodology is to identify LTCH PPS 
standard Federal payment rate cases from the MedPAR claim files for 
the two most recently available Federal fiscal year time periods. 
For both fiscal years, consistent with our historical methodology 
for determining payment rates for the LTCH PPS, we remove any claims 
submitted by LTCHs that were all-inclusive rate providers as well as 
any Medicare Advantage claims. For both fiscal years, we also remove 
claims from providers that only had claims in one of the fiscal 
years.
    Step 2--Remove Statistical Outliers
    The next step in our methodology is to remove all claims from 
providers whose growth in average charges was a statistical outlier. 
We remove these statistical outliers prior to calculating the charge 
inflation factor because we believe they may represent aberrations 
in the data that would distort the measure of average charge growth. 
To perform this statistical trim, we first calculate each provider's 
average charge in both fiscal years. Then, we calculate a charge 
growth factor for each provider by dividing its average charge in 
the most recent fiscal year by its average charge in the prior 
fiscal year. Then we remove all claims for providers whose 
calculated charge growth factor was outside 3 standard deviations 
from the mean provider charge growth factor.
    Step 3--Calculate the Charge Inflation Factor
    The final step in our methodology is to use the remaining claims 
to calculate a national charge inflation factor. We first calculate 
the average charge for those remaining claims in both fiscal years. 
Then we calculate the national charge inflation factor by dividing 
the average charge in the more recent fiscal year by the average 
charge in the prior fiscal year.
    Following the methodology described previously, in the FY 2023 
IPPS/LTCH PPS proposed rule (87 FR 28690 through 28691), we computed 
a charge inflation factor based on the most recently available data. 
Specifically, we used the December 2021 update of the FY 2021 MedPAR 
file and the December 2020 update of the FY 2020 MedPAR as the basis 
of the LTCH PPS standard Federal payment rate cases for the two most 
recently available Federal fiscal year time periods, as described 
previously in our methodology. Therefore, we trimmed the December 
2021 update of the FY 2021 MedPAR file and the December 2020 update 
of the FY 2020 MedPAR file as described in steps 1 and 2 of our 
methodology. To compute the 1-year average annual rate-of-change in 
charges per case, we compared the average covered charge per case of 
$239,245 ($14,013,531,722/58,574 cases) from FY 2020 to the average 
covered charge per case of $266,358 ($13,426,298,925/50,407 cases) 
from FY 2021. This rate-of-change was 11.3327 percent, which results 
in a 1-year charge inflation factor of 1.113327, and a 2-year charge 
inflation factor of 1.239497 (calculated by squaring the 1-year 
factor).
    In the proposed rule, we recognized that this LTCH charge 
inflation factor calculated using the established methodology was 
abnormally high compared to recent historical levels prior to the 
COVID-19 PHE. We stated our belief that this abnormally high charge 
inflation factor is partially due to the high number of COVID-19 
cases that were treated in LTCHs in FY 2021. We also stated our 
belief that there will be fewer COVID-19 cases in FY 2023 than in FY 
2021 and therefore do not believe it is reasonable to assume charges 
will continue to increase at this abnormally high rate. 
Consequently, when determining the proposed fixed-loss amount for 
LTCH PPS standard Federal payment rate cases for FY 2023, we did not 
propose to use this charge inflation factor, which was based on the 
growth in charges that occurred between FY 2020 and FY 2021. Rather, 
we proposed to use the charge inflation factor determined in the FY 
2022 IPPS/LTCH PPS final rule (86 FR 45565), which was based on the 
growth in charges that occurred between FY 2018 and FY 2019 (the 
last 1-year period prior to the COVID-19 PHE).
    The rate of LTCH charge growth determined in the FY 2022 IPPS/
LTCH PPS final rule, based on the growth in charges that occurred 
between FY 2018 and FY 2019, was 6.0723 percent. This results in a 
1-year charge inflation factor of 1.060723, and a 2-year charge 
inflation factor of 1.125133 (calculated by squaring the 1-year 
factor). Therefore, we proposed to inflate the billed charges 
obtained from the FY 2021 MedPAR file by this 2-year charge 
inflation factor of 1.125133 when determining the fixed-loss amount 
for LTCH PPS standard Federal payment rate cases for FY 2023.
    Comment: Nearly all commenters were appreciative of CMS's 
efforts to account for some of the pandemic-related factors in 
calculating the fixed-loss amount by applying the final FY 2022 
charge inflation factor rather than the calculated amounts using our 
previously established methodology.
    Response: We appreciate the support for this modification to our 
methodology in determining the charge inflation factor. We are 
finalizing our proposal to use the 2-year charge inflation factor of 
1.125133 determined in the FY 2022 IPPS/LTCH PPS final rule, which 
was based on the growth in charges that occurred between FY 2018 and 
FY 2019 (the last 1-year period prior to the COVID-19 PHE) in 
calculating the fixed-loss amount. We note that using our ordinary 
data for this final rule, we calculated a 2-year charge inflation of 
1.241308.

(2) CCRs for Use in Determining the Fixed-Loss Amount for LTCH PPS 
Standard Federal Payment Rate Cases for FY 2023

    For greater accuracy in calculating the fixed-loss amount, in 
the FY 2022 IPPS/LTCH PPS final rule (86 FR 45562 through 45566), we 
finalized a technical change to our methodology for determining the 
CCRs used to calculate the fixed-loss amount. Similar to the 
methodology used for IPPS hospitals (as discussed in section 
II.A.4.h.(2). of the Addendum to this final rule), our methodology 
adjusts CCRs obtained from the best available PSF data by an 
adjustment factor that is calculated based on historical changes in 
the average case-weighted CCR for LTCHs. We believe these adjusted 
CCRs more accurately reflect CCR levels in the upcoming payment year 
because they account for historical changes in the relationship 
between costs and charges for LTCHs. In this section of this 
Addendum, we describe our CCR adjustment factor methodology using 
the most recently available data. However, as discussed in further 
detail later in this section of this Addendum, we did not propose to 
use the CCR adjustment factor derived from the most recently 
available data. Rather, we proposed using the CCR adjustment factor 
that was derived in the FY 2022 IPPS/LTCH PPS final rule, which is 
based on the change in CCRs that occurred between the March 2019 PSF 
and the March 2020 PSF.

Step 1--Assign Providers Their Historical CCRs

    The first step in our methodology is to identify providers with 
LTCH PPS standard Federal payment rate cases in the most recent 
MedPAR claims file (excluding all-inclusive rate providers and 
providers with only Medicare Advantage claims). For each of these 
providers, we then identify the CCR from the most recently available 
PSF. For each of these providers we also identify the CCR from the 
PSF that was made available

[[Page 49447]]

one year prior to the most recently available PSF.

Step 2--Trim Providers With Insufficient CCR Data

    The next step in our methodology is to remove from the CCR 
adjustment factor calculation any providers for which we cannot 
accurately measure changes to their CCR using the PSF data. We first 
remove any provider whose CCR was missing in the most recent PSF or 
prior year PSF. We next remove any provider assigned the statewide 
average CCR for their State in either the most recent PSF or prior 
year PSF. We lastly remove any provider whose CCR was not updated 
between the most recent PSF and prior year PSF (determined by 
comparing the effective date of the records).

Step 3--Remove Statistical Outliers

    The next step in our methodology is to remove providers whose 
change in their CCR is a statistical outlier. To perform this 
statistical trim, for those providers remaining after application of 
Step 2, we calculate a provider-level CCR growth factor by dividing 
the provider's CCR from the most recent PSF by its CCR in the prior 
year's PSF. We then remove any provider whose CCR growth factor was 
outside 3 standard deviations from the mean provider CCR growth 
factor. These statistical outliers are removed prior to calculating 
the CCR adjustment factor because we believe that they may represent 
aberrations in the data that would distort the measure of average 
annual CCR change.

Step 4--Calculate a CCR Adjustment Factor

    The final step in our methodology is to calculate, across all 
remaining providers after application of Step 3, an average case-
weighted CCR from both the most recent PSF and prior year PSF. The 
provider case counts that we use to calculate the case-weighted 
average are determined from claims for LTCH standard Federal rate 
cases from the most recent MedPAR claims file. We note when 
determining these case counts, consistent with our historical 
methodology for determining the MS-LTC-DRG relative weights, we do 
not count short-stay outlier claims as full cases but instead as a 
fraction of a case based on the ratio of covered days to the 
geometric mean length of stay for the MS-LTC-DRG grouped to the 
case. We calculate the national CCR adjustment factor by dividing 
the case-weighted CCR from the most recent PSF by the case-weighted 
CCR from the prior year PSF.
    Following the methodology described previously, in the FY 2023 
IPPS/LTCH PPS proposed rule (87 FR 28691 through 28692) we computed 
a CCR adjustment factor based on the most recently available data. 
Specifically, we used the December 2021 PSF as the most recently 
available PSF and the December 2020 PSF as the PSF that was made 
available one year prior to the most recently available PSF, as 
described in our methodology. In addition, we used claims from the 
December 2021 update of the FY 2021 MedPAR file in our calculation 
of average case-weighted CCRs described in Step 4 of our 
methodology. Specifically, following the methodology described 
previously and, for providers with LTCH PPS standard Federal payment 
rate cases in the December 2021 update of the FY 2021 MedPAR file, 
we identified their CCRs from both the December 2020 PSF and 
December 2021 PSF. After performing the trims outlined in our 
methodology, we used the LTCH PPS standard Federal payment rate case 
counts from the FY 2021 MedPAR file (classified using proposed 
Version 40 of the GROUPER) to calculate case-weighted average CCRs. 
Based on this data, we calculated a December 2020 national average 
case-weighted CCR of 0.244856 and a December 2021 national average 
case-weighted CCR of 0.234409. We then calculated a national CCR 
adjustment factor by dividing the December 2021 national average 
case-weighted CCR by the December 2020 national average case-
weighted CCR. This results in a 1-year national CCR adjustment 
factor of 0.957334.
    Unlike the charge inflation factor calculated using the most 
recently available data, the CCR adjustment factor calculated 
previously is not significantly different from historical levels. 
However, consistent with our proposal to derive our proposed charge 
inflation factor for FY 2023 based on data from the last 1-year 
period prior to the COVID-19 PHE, we proposed using the CCR 
adjustment factor determined in the FY 2022 IPPS/LTCH PPS final rule 
(86 FR 45565), which was based on the change in CCRs that occurred 
between the March 2019 PSF and the March 2020 PSF (the last 1-year 
period prior to the COVID-19 PHE). We note that the CCR adjustment 
factor of 0.961554 determined in the FY 2022 IPPS/LTCH PPS final 
rule is close to the CCR adjustment factor we calculated previously 
using the most recently available data.
    Comment: Nearly all commenters were appreciative of CMS's 
efforts to account for some of the pandemic-related factors in 
calculating the fixed-loss amount by applying the final FY 2022 CCR 
adjustment factor rather than the calculated amounts using our 
previously established methodology.
    Response: We appreciate the support for our modified methodology 
for determining the CCR adjustment factor. We are finalizing our 
proposal to use the CCR adjustment factor of 0.961554 determined in 
the FY 2022 IPPS/LTCH PPS final rule, which was based on the change 
in CCRs that occurred between the March 2019 PSF and the March 2020 
PSF (the last 1-year period prior to the COVID-19 PHE) in 
calculating the fixed loss amount. When calculating the fixed-loss 
amount for FY 2023, consistent with our proposal, we assigned the 
statewide average CCR for the upcoming fiscal year to all providers 
who were assigned the statewide average in the March 2022 PSF or 
whose CCR was missing in the March 2022 PSF. For all other 
providers, we multiplied their CCR from the March 2022 PSF by the 1-
year national CCR adjustment factor of 0.961554. We note that using 
our ordinary data for this final rule, we calculated a 1-year 
national CCR adjustment factor of 0.959468.

(3) Fixed-Loss Amount for LTCH PPS Standard Federal Payment Rate Cases 
for FY 2023

    In the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28123 through 
28125), we discussed our proposed use of FY 2021 claims data for the 
FY 2023 LTCH PPS ratesetting. In the proposed rule, we stated our 
belief that it is reasonable to assume that there will be fewer 
COVID-19 hospitalizations among Medicare beneficiaries at LTCHs in 
FY 2023 than there were in FY 2021. For this reason, as discussed 
previously, we proposed modifications to the charge inflation and 
CCR adjustment factors used in determining the outlier fixed-loss 
amount for LTCH PPS standard Federal payment rate cases.
    However, when modeling payments for the outlier fixed-loss 
amount for LTCH PPS standard Federal payment rate cases, we proposed 
to use the full set of LTCH PPS standard Federal payment rate cases 
(including all COVID-19 cases) identified in the FY 2021 claims 
data. In the absence of a set of MedPAR claims that reflect our 
expectation that there will be fewer (but not zero) COVID-19 cases 
in FY 2023 as compared to the COVID-19 cases in the FY 2021 claims 
data, we stated our belief that this is the best data available for 
determining the outlier fixed-loss amount for LTCH PPS standard 
Federal payment rate cases. In the proposed rule, we solicited 
feedback from commenters on alternative ways to use the FY 2021 
claims data for purposes of calculating the FY 2023 outlier fixed-
loss amount for LTCH PPS standard Federal payment rate cases.
    In the proposed rule, for FY 2023, using the best available 
data, we calculated a fixed-loss amount that would maintain 
estimated HCO payments at the projected 7.975 percent of total 
estimated LTCH PPS payments for LTCH PPS standard Federal payment 
rate cases (based on the payment rates and policies for these cases 
presented in the final rule). Therefore, based on LTCH claims data 
from the December 2021 update of the FY 2021 MedPAR file adjusted 
for charge inflation and adjusted CCRs from the December 2021 update 
of the PSF, under the broad authority of section 123(a)(1) of the 
BBRA and section 307(b)(1) of the BIPA, we proposed a fixed-loss 
amount for LTCH PPS standard Federal payment rate cases for FY 2023 
of $44,182 that would result in estimated outlier payments projected 
to be equal to 7.975 percent of estimated FY 2023 payments for such 
cases. We also proposed to continue making an additional HCO payment 
for the cost of an LTCH PPS standard Federal payment rate case that 
exceeds the HCO threshold amount that is equal to 80 percent of the 
difference between the estimated cost of the case and the outlier 
threshold (the sum of the adjusted LTCH PPS standard Federal payment 
rate payment and the fixed-loss amount for LTCH PPS standard Federal 
payment rate cases of $44,182). Consistent with our historical 
practice, we proposed to use the best available LTCH claims data and 
CCR data, if applicable, when determining the fixed-loss amount for 
LTCH PPS standard Federal payment rate cases for FY 2023. In the FY 
2023 IPPS/LTCH PPS proposed rule (87 FR 28740 through 28741), we 
also considered as an alternative, to use the FY 2021 data without 
any of our methodological changes that account for an anticipated 
decline in COVID-19 cases in FY 2023. We noted in the proposed rule 
that,

[[Page 49448]]

under this alternative, the fixed-loss amount for LTCH PPS standard 
Federal payment rate cases would be $61,842
    Comment: We received numerous comments objecting to our proposed 
fixed-loss amount of $44,182 for standard Federal payment rate 
cases. Commenters stated that the increase over last year's fixed-
loss amount of $33,015, particularly on top of the increase to the 
FY 2021 threshold of $27,195, would have a significant financial 
impact on LTCHs. Moreover, commenters stated their belief that the 
proposed fixed-loss amount would result in underpayments to LTCHs 
treating high-cost patients, hindering the ability of LTCHs to 
provide care to the sickest beneficiaries. Some commenters stated 
that CMS should lower the outlier fixed-loss amount in response to 
rising costs that have and will continue to impact LTCHs.
    Several commenters expressed concern about our proposed use of 
FY 2021 claims data in determining the outlier fixed-loss amount for 
LTCH PPS standard Federal payment rate cases. Commenters recommended 
several alternative data sources or methodologies for calculating 
the outlier fixed-loss amount that they believed would more 
accurately reflect the impact of the COVID-19 pandemic on 
utilization in FY 2023.
    The most commonly recommended approach by commenters was to 
determine the outlier fixed-loss amount as an average of the outlier 
fixed-loss amounts calculated using both FY 2019 and FY 2021 claims 
data, thereby incorporating data from one year before the COVID-19 
PHE and one year during the COVID-19 PHE. Some commenters believed 
that this approach would better account for the uncertainty on 
whether the abnormal levels of charges and costs reflected in the FY 
2021 claims data caused by the COVID-19 pandemic will normalize in 
FY 2023. Another commenter, while suggesting this alternative 
methodology, expressed its belief that costs in FY 2023 will more 
closely resemble pre-pandemic costs than what was experienced in FY 
2021. Some commenters stated that this approach would be consistent 
with other FY 2023 proposals aimed to institute stability and 
predictability in payments from year to year.
    Some commenters suggested that CMS use its regulatory authority 
under the PHE to establish the FY 2023 outlier fixed-loss amount for 
LTCH PPS standard Federal payment rate cases at the FY 2022 level. 
Other commenters, while expressing concerns that the FY 2021 claims 
were atypical, requested CMS to reexamine its methodology and better 
account for data anomalies.
    In its comment letter, MedPAC presented an alternative approach 
for CMS to consider in which the FY 2023 fixed-loss amount would be 
established by averaging the outlier fixed-loss amounts calculated 
with and without COVID-19 cases in the FY 2021 data. MedPAC believes 
that this approach would be consistent with the approach CMS 
proposed for calculating the MS-LTC-DRG relative weights and would 
reflect the assumption that there will be fewer COVID-19 cases in FY 
2023 as compared to FY 2021.
    Commenters strongly objected to the alternative fixed loss 
amount we considered in section I.O. of Appendix A of the proposed 
rule which was calculated using FY 2021 data without any of the 
methodological changes to account for anticipated declines in COVID-
19 cases in FY 2023.
    Response: We thank commenters for their feedback. In response to 
commenters' concerns, we considered recommendations made by 
commenters on how we could better account for the impact of the 
COVID-19 PHE on the data used for determining the outlier fixed-loss 
amount.
    We do not agree with commenters who recommend that CMS use it 
regulatory authority under the PHE to establish an alternative 
outlier fixed-loss amount or commenters who suggested that CMS lower 
the outlier-fixed loss amount in response to rising costs at LTCHs. 
We note that in accordance with Sec.  412.525(a)(2)(ii), which 
implements section 1886(m)(7)(B) of the Act, CMS must determine a 
fixed-loss amount for LTCH PPS standard Federal payment rate cases 
that we project will result in total outlier payments for FY 2023 
being equal to 7.975 percent of projected total LTCH PPS payments 
for LTCH PPS standard Federal payment rate cases. We do not believe 
that CMS has the statutory authority to establish an outlier fixed-
loss amount that does not meet this requirement.
    With respect to the commenters who suggested we determine the 
outlier fixed-loss amount based on an average of the fixed-loss 
amounts calculated using FY 2019 and FY 2021 data, we continue to 
recognize that there is uncertainty regarding the utilization and 
costs that LTCHs will experience in FY 2023. However, based on the 
information available at this time on the trajectory of the COVID-19 
PHE, consistent with the discussion in section I.F. of the preamble 
to this final rule, we do not believe averaging the fixed-loss 
amounts calculated using FY 2019 and FY 2021 data is the best 
approach for determining an outlier fixed-loss amount that will 
reflect a reasonable estimation of the mix and relative resource use 
of cases that will be treated at LTCHs in FY 2023. Rather, we 
believe averaging the outlier-fixed loss thresholds calculated using 
FY 2021 data including and excluding COVID-19 claims, as suggested 
by MedPAC, better reflects our belief that it is reasonable to 
assume there will be fewer COVID-19 hospitalizations among Medicare 
beneficiaries in LTCHs in FY 2023 than there were in FY 2021 (as 
discussed in section I.F of the preamble to this final rule). In 
addition, we agree this approach would be most consistent with the 
approach we proposed and are finalizing for calculating the MS-LTC-
DRG relative weights, as discussed in section VIII.B.3.a. of the 
preamble to this final rule. As discussed later in this section, we 
are adopting the approach suggested by MedPAC when determining the 
FY 2023 outlier fixed loss amount.
    With respect to commenters' concerns about data anomalies 
contributing to a higher outlier fixed-loss amount, we note we 
recently became aware of an anomaly in the data that contributed to 
the increase in the proposed outlier fixed-loss amount. Under our 
existing outlier policy, in general, the CCR from an LTCH's latest 
settled or tentatively settled cost report is used in determining 
its outlier payments. In the case of one LTCH, in particular, we 
observed that its rate-of-charge increases greatly exceed their 
rate-of-cost increases. In other words, the charges reported on its 
claims were increasing at a significantly faster pace than their 
reported costs. Because there is a time lag between the CCR from the 
latest settled or tentatively settled cost report and current 
charges, this sizable differential in the rate-of-increases for 
charges and costs results in CCRs that are too high relative to the 
actual relationship between the LTCH's charges and costs at the time 
of the discharge. This in turn results in an overestimation of the 
LTCH's current costs per case at the time of the discharge, and high 
amounts of HCO payments. In FY 2021, this LTCH's charges per case 
increased to extreme levels. In the FY 2021 MedPAR file, we 
identified over 50 LTCH PPS standard Federal payment rate cases for 
this LTCH with charges that exceed $9 million. In addition, this 
LTCH received outlier payments for over 80 percent of its LTCH PPS 
standard Federal payment rate cases identified in the FY 2021 MedPAR 
file. As discussed previously, under the HCO policy at Sec.  
412.525(a)(4)(iv)(D), the payments for HCO cases are subject to 
reconciliation (regardless of whether payment is based on the LTCH 
standard Federal payment rate or the site neutral payment rate). 
Specifically, any such payments are reconciled at cost report 
settlement based on the CCR that was calculated for the cost 
reporting period coinciding with the discharge. Based on information 
from the provider, we believe that these extreme levels of charges 
will not persist into FY 2023. For this reason, we do not believe it 
would be appropriate to include cases for this LTCH (CCN 312024) in 
our model for determining the FY 2023 outlier fixed-loss amount. 
Therefore, as discussed later in this section, we are excluding them 
from our calculations of the FY 2023 outlier fixed-loss amount.
    After consideration of all comments received, we are modifying 
our proposed approach for determining the FY 2023 outlier fixed-loss 
amount. As discussed, we are adopting the suggested approach to 
establish the FY 2023 outlier fixed-loss amount based on the average 
of the outlier-fixed loss thresholds calculated using FY 2021 data 
including and excluding COVID-19 claims. As discussed, we are also 
excluding claims from CCN 312024 from the FY 2021 claims data used 
in determining the FY 2023 outlier fixed-loss amount. As discussed 
previously, we also are finalizing our proposal to use the charge 
inflation and CCR adjustment factors determined in the FY 2022 IPPS/
LTCH PPS final rule when calculating the FY 2023 outlier fixed-loss 
amount.
    For this final rule, for FY 2023, using the best available data, 
we calculated a fixed-loss amount that would maintain estimated HCO 
payments at the projected 7.975 percent of total estimated LTCH PPS 
payments for LTCH PPS standard Federal payment rate cases (based on 
the payment rates and policies for these cases presented in this 
final rule). Based on the full set of LTCH claims

[[Page 49449]]

data (including COVID-19 cases) from the March 2022 update of the FY 
2021 MedPAR file adjusted for charge inflation and using adjusted 
CCRs from the March 2022 update of the PSF, we calculated a fixed-
loss amount of $37,900. Based on the set of LTCH claims data that 
excludes COVID-19 cases from the March 2022 update of the FY 2021 
MedPAR file adjusted for charge inflation and using adjusted CCRs 
from the March 2022 update of the PSF, we calculated a fixed-loss 
amount of $39,135. We identified COVID-19 cases as any claim in the 
FY 2021 MedPAR file with a principal or secondary diagnosis of 
COVID-19 (ICD-10-CM diagnosis code U07.1), just as we did for the 
calculation of the FY 2023 MS-LTC-DRG relative weights. Accordingly, 
under the broad authority of section 123(a)(1) of the BBRA and 
section 307(b)(1) of the BIPA, we are establishing a fixed-loss 
amount for LTCH PPS standard Federal payment rate cases for FY 2023 
of $38,518, which is the average of the fixed-loss amounts 
calculated from FY 2021 claims data including and excluding COVID-19 
cases. We project that this fixed-loss amount will result in 
estimated outlier payments projected to be equal to 7.975 percent of 
estimated FY 2023 payments for such cases. We are continuing, as 
proposed, to make additional HCO payment for the cost of an LTCH PPS 
standard Federal payment rate case that exceeds the HCO threshold 
amount that is equal to 80 percent of the difference between the 
estimated cost of the case and the outlier threshold (the sum of the 
adjusted LTCH PPS standard Federal payment rate payment and the 
fixed-loss amount for LTCH PPS standard Federal payment rate cases 
of $38,518). We note that this revised amount is considerably lower 
than our proposed fixed-loss amount of $44,182. We also note that if 
we had not excluded CCN 312024 from our calculations, the averaged 
fixed-loss amount would have been $39,556.

4. High-Cost Outlier Payments for Site Neutral Payment Rate Cases

    When we implemented the application of the site neutral payment 
rate in FY 2016, in examining the appropriate fixed-loss amount for 
site neutral payment rate cases issue, we considered how LTCH 
discharges based on historical claims data would have been 
classified under the dual rate LTCH PPS payment structure and the 
CMS' Office of the Actuary projections regarding how LTCHs will 
likely respond to our implementation of policies resulting from the 
statutory payment changes. We again relied on these considerations 
and actuarial projections in FY 2017 and FY 2018 because the 
historical claims data available in each of these years were not all 
subject to the LTCH PPS dual rate payment system. Similarly, for FYs 
2019 through 2022, we continued to rely on these considerations and 
actuarial projections because, due to the transitional blended 
payment policy for site neutral payment rate cases, FY 2018 and FY 
2019 claims for these cases were not subject to the full effect of 
the site neutral payment rate.
    For FYs 2016 through 2022, our actuaries projected that the 
proportion of cases that would qualify as LTCH PPS standard Federal 
payment rate cases versus site neutral payment rate cases under the 
statutory provisions would remain consistent with what is reflected 
in the historical LTCH PPS claims data. Although our actuaries did 
not project an immediate change in the proportions found in the 
historical data, they did project cost and resource changes to 
account for the lower payment rates. Our actuaries also projected 
that the costs and resource use for cases paid at the site neutral 
payment rate would likely be lower, on average, than the costs and 
resource use for cases paid at the LTCH PPS standard Federal payment 
rate and would likely mirror the costs and resource use for IPPS 
cases assigned to the same MS-DRG, regardless of whether the 
proportion of site neutral payment rate cases in the future remains 
similar to what is found based on the historical data. As discussed 
in the FY 2016 IPPS/LTCH PPS final rule (80 FR 49619), this 
actuarial assumption is based on our expectation that site neutral 
payment rate cases would generally be paid based on an IPPS 
comparable per diem amount under the statutory LTCH PPS payment 
changes that began in FY 2016, which, in the majority of cases, is 
much lower than the payment that would have been paid if these 
statutory changes were not enacted. In light of these projections 
and expectations, we discussed that we believed that the use of a 
single fixed-loss amount and HCO target for all LTCH PPS cases would 
be problematic.
    In addition, we discussed that we did not believe that it would 
be appropriate for comparable LTCH PPS site neutral payment rate 
cases to receive dramatically different HCO payments from those 
cases that would be paid under the IPPS (80 FR 49617 through 49619 
and 81 FR 57305 through 57307). For those reasons, we stated that we 
believed that the most appropriate fixed-loss amount for site 
neutral payment rate cases for FYs 2016 through 2022 would be equal 
to the IPPS fixed-loss amount for that particular fiscal year. 
Therefore, we established the fixed-loss amount for site neutral 
payment rate cases as the corresponding IPPS fixed-loss amounts for 
FYs 2016 through 2022. In particular, in FY 2022, we established the 
fixed-loss amount for site neutral payment rate cases as the FY 2021 
IPPS fixed-loss amount of $30,988 (86 FR 45567).
    As discussed in section I.F. of the preamble of this final rule, 
we are finalizing our proposal to use FY 2021 data in the FY 2023 
LTCH PPS ratesetting. Section 3711(b)(2) of the CARES Act, which 
provided a waiver of the application of the site neutral payment 
rate for LTCH cases admitted during the COVID-19 PHE period, was in 
effect for the entirety of FY 2021. Therefore, all LTCH PPS cases in 
FY 2021 were paid the LTCH PPS standard Federal rate regardless of 
whether the discharge met the statutory patient criteria. Because 
not all FY 2021 claims in the data used for this final rule were 
subject to the site neutral payment rate, we continue to rely on the 
same considerations and actuarial projections used in FYs 2016 
through 2022 when developing a fixed-loss amount for site neutral 
payment rate cases for FY 2023. Our actuaries continue to project 
that the costs and resource use for FY 2023 cases paid at the site 
neutral payment rate would likely be lower, on average, than the 
costs and resource use for cases paid at the LTCH PPS standard 
Federal payment rate and will likely mirror the costs and resource 
use for IPPS cases assigned to the same MS-DRG, regardless of 
whether the proportion of site neutral payment rate cases in the 
future remains similar to what was found based on the historical 
data. (Based on the FY 2021 LTCH claims data used in the development 
of this final rule, if the provisions of the CARES Act had not been 
in effect, approximately 72 percent of LTCH cases would have been 
paid the LTCH PPS standard Federal payment rate and approximately 28 
percent of LTCH cases would have been paid the site neutral payment 
rate for discharges occurring in FY 2021.)
    For these reasons, we proposed that the most appropriate fixed-
loss amount for site neutral payment rate cases for FY 2023 is the 
IPPS fixed-loss amount for FY 2023. Therefore, consistent with past 
practice, we proposed that the applicable HCO threshold for site 
neutral payment rate cases is the sum of the site neutral payment 
rate for the case and the IPPS fixed-loss amount. That is, we 
proposed a fixed-loss amount for site neutral payment rate cases of 
$43,214, which is the same proposed FY 2023 IPPS fixed-loss amount 
discussed in section II.A.4.j.(1). of the Addendum to the proposed 
rule. Accordingly, for FY 2023, we proposed to calculate a HCO 
payment for site neutral payment rate cases with costs that exceed 
the HCO threshold amount that is equal to 80 percent of the 
difference between the estimated cost of the case and the outlier 
threshold (the sum of the site neutral payment rate payment and the 
fixed-loss amount for site neutral payment rate cases of $43,214).
    Comment: Some commenters opposed the proposed fixed-loss amount 
for site neutral payment rate cases. A commenter stated that 
increases in the fixed-loss amount for site neutral payment rate 
cases should be limited to no more than the market basket percent 
increase. Other commenters stated that CMS should calculate the 
fixed-loss amount for site neutral payment rate cases using a 
combination of FY 2019 and FY 2021 data.
    Response: As stated earlier, our actuaries continue to project 
that site neutral payment rate cases in FY 2023 will mirror an IPPS 
case paid under the same MS-DRG. That is, our actuaries continue to 
project that the costs and resource use for FY 2023 cases paid at 
the site neutral payment rate would likely be lower, on average, 
than the costs and resource use for cases paid at the LTCH PPS 
standard Federal payment rate and will likely mirror the costs and 
resource use for IPPS cases assigned to the same MS DRG, on average, 
regardless of whether the proportion of site neutral payment rate 
cases in the future remains similar to what was found based on the 
historical data. For these reasons, we continue to believe that the 
most appropriate fixed-loss amount for site neutral payment rate 
cases for FY 2023 is the IPPS fixed-loss amount for FY 2023. With 
respect to comments on the data used in determining the site neutral 
fixed-loss amount, we refer the reader to section II.A.4. of the 
addendum to this final rule for a complete summary and

[[Page 49450]]

response to comments received on our proposed use of FY 2021 data 
and our proposed modifications to our usual methodology when 
determining the FY 2023 outlier fixed-loss amounts for IPPS cases, 
which as described later in this section, is the same as the site 
neutral fixed-loss amount.
    In this final rule, after considering public comments on our 
proposals, we are finalizing our proposals as described previously, 
without modification. Therefore, for FY 2023, as we proposed, we are 
establishing that the applicable HCO threshold for site neutral 
payment rate cases is the sum of the site neutral payment rate for 
the case and the IPPS fixed loss amount. That is, we are 
establishing a fixed-loss amount for site neutral payment rate cases 
of $38,859, which is the same FY 2023 IPPS fixed loss amount 
discussed in section II.A.4.j.(1). of the Addendum to this final 
rule. Accordingly, under this policy, for FY 2023, we will calculate 
a HCO payment for site neutral payment rate cases with costs that 
exceed the HCO threshold amount, which is equal to 80 percent of the 
difference between the estimated cost of the case and the outlier 
threshold (the sum of site neutral payment rate payment and the 
fixed loss amount) for site neutral payment rate cases of $38,859.
    In establishing a HCO policy for site neutral payment rate 
cases, we proposed a budget neutrality adjustment under Sec.  
412.522(c)(2)(i). We proposed this requirement because we believed, 
and continue to believe, that the HCO policy for site neutral 
payment rate cases should be budget neutral, just as the HCO policy 
for LTCH PPS standard Federal payment rate cases is budget neutral, 
meaning that estimated site neutral payment rate HCO payments should 
not result in any change in estimated aggregate LTCH PPS payments.
    To ensure that estimated HCO payments payable to site neutral 
payment rate cases in FY 2023 would not result in any increase in 
estimated aggregate FY 2023 LTCH PPS payments, under the budget 
neutrality requirement at Sec.  412.522(c)(2)(i), it is necessary to 
reduce site neutral payment rate payments by 5.1 percent to account 
for the estimated additional HCO payments payable to those cases in 
FY 2023. Consistent with our historical practice, we proposed 
continuing this policy.
    As discussed earlier, consistent with the IPPS HCO payment 
threshold, we estimate the proposed fixed-loss threshold would 
result in FY 2023 HCO payments for site neutral payment rate cases 
to equal 5.1 percent of the site neutral payment rate payments that 
are based on the IPPS comparable per diem amount. As such, to ensure 
estimated HCO payments payable for site neutral payment rate cases 
in FY 2023 would not result in any increase in estimated aggregate 
FY 2023 LTCH PPS payments, under the budget neutrality requirement 
at Sec.  412.522(c)(2)(i), it is necessary to reduce the site 
neutral payment rate amount paid under Sec.  412.522(c)(1)(i) by 5.1 
percent to account for the estimated additional HCO payments payable 
for site neutral payment rate cases in FY 2023. To achieve this, for 
FY 2023, we proposed applying a budget neutrality factor of 0.949 
(that is, the decimal equivalent of a 5.1 percent reduction, 
determined as 1.0-5.1/100 = 0.949) to the site neutral payment rate 
for those site neutral payment rate cases paid under Sec.  
412.522(c)(1)(i). We proposed that, consistent with our current 
policy, this HCO budget neutrality adjustment would not be applied 
to the HCO portion of the site neutral payment rate amount (81 FR 
57309).
    Comment: A commenter, in keeping with comments we have received 
since the inception of the dual rate payment system that created the 
site neutral payment rate, objected to the proposed site neutral 
payment rate HCO budget neutrality adjustment. The commenter's 
objection continues to be based on the belief that, because the IPPS 
base rates used in the IPPS comparable per diem amount calculation 
of the site neutral payment rate include a budget neutrality 
adjustment for IPPS HCO payments (for example, a 5.1 percent 
adjustment on the operating IPPS standardized amount), a ``second'' 
budget neutrality factor is unnecessary and duplicative.
    Response: We continue to disagree with the commenters that a 
budget neutrality adjustment for site neutral payment rate HCO 
payments is unnecessary or duplicative. We have stated such 
disagreement during each previous rulemaking cycle. We refer readers 
to 84 FR 42648 through 42649, 83 FR 41737 through 41738, 82 FR 38545 
through 38546, 81 FR 57308 through 57309, and 80 FR 49621 through 
49622 for a more detailed discussion in response to such comments.
    After consideration of public comments, for the reasons 
discussed previously, we are adopting our proposed site neutral 
payment rate HCO budget neutrality adjustment as final without 
modification. Specifically, for FY 2023, as we proposed, we are 
applying a budget neutrality factor of 0.949 (that is, the decimal 
equivalent of a 5.1 percent reduction, determined as 1.0- 5.1/100 = 
0.949) to the site neutral payment rate for those site neutral 
payment rate cases paid under Sec.  412.522(c)(1)(i). We note that, 
consistent with our current policy, this HCO budget neutrality 
adjustment will not apply to the HCO portion of the site neutral 
payment rate amount.

E. Update to the IPPS Comparable Amount To Reflect the Statutory 
Changes to the IPPS DSH Payment Adjustment Methodology

    In the FY 2014 IPPS/LTCH PPS final rule (78 FR 50766), we 
established a policy to reflect the changes to the Medicare IPPS DSH 
payment adjustment methodology made by section 3133 of the 
Affordable Care Act in the calculation of the ``IPPS comparable 
amount'' under the SSO policy at Sec.  412.529 and the ``IPPS 
equivalent amount'' under the site neutral payment rate at Sec.  
412.522. Historically, the determination of both the ``IPPS 
comparable amount'' and the ``IPPS equivalent amount'' includes an 
amount for inpatient operating costs ``for the costs of serving a 
disproportionate share of low-income patients.'' Under the statutory 
changes to the Medicare DSH payment adjustment methodology that 
began in FY 2014, in general, eligible IPPS hospitals receive an 
empirically justified Medicare DSH payment equal to 25 percent of 
the amount they otherwise would have received under the statutory 
formula for Medicare DSH payments prior to the amendments made by 
the Affordable Care Act. The remaining amount, equal to an estimate 
of 75 percent of the amount that otherwise would have been paid as 
Medicare DSH payments, reduced to reflect changes in the percentage 
of individuals who are uninsured and any additional statutory 
adjustment, is made available to make additional payments to each 
hospital that qualifies for Medicare DSH payments and that has 
uncompensated care. The additional uncompensated care payments are 
based on the hospital's amount of uncompensated care for a given 
time period relative to the total amount of uncompensated care for 
that same time period reported by all IPPS hospitals that receive 
Medicare DSH payments.
    To reflect the statutory changes to the Medicare DSH payment 
adjustment methodology in the calculation of the ``IPPS comparable 
amount'' and the ``IPPS equivalent amount'' under the LTCH PPS, we 
stated that we will include a reduced Medicare DSH payment amount 
that reflects the projected percentage of the payment amount 
calculated based on the statutory Medicare DSH payment formula prior 
to the amendments made by the Affordable Care Act that will be paid 
to eligible IPPS hospitals as empirically justified Medicare DSH 
payments and uncompensated care payments in that year (that is, a 
percentage of the operating Medicare DSH payment amount that has 
historically been reflected in the LTCH PPS payments that are based 
on IPPS rates). We also stated that the projected percentage will be 
updated annually, consistent with the annual determination of the 
amount of uncompensated care payments that will be made to eligible 
IPPS hospitals. We believe that this approach results in appropriate 
payments under the LTCH PPS and is consistent with our intention 
that the ``IPPS comparable amount'' and the ``IPPS equivalent 
amount'' under the LTCH PPS closely resemble what an IPPS payment 
would have been for the same episode of care, while recognizing that 
some features of the IPPS cannot be translated directly into the 
LTCH PPS (79 FR 50766 through 50767).
    For FY 2023, as discussed in the FY 2023 IPPS/LTCH PPS proposed 
rule (87 FR 28694) and in greater detail in section V.E.4.b. of the 
preamble of this final rule, based on the most recent data 
available, our estimate of 75 percent of the amount that would 
otherwise have been paid as Medicare DSH payments (under the 
methodology outlined in section 1886(r)(2) of the Act) is adjusted 
to 65.71 percent of that amount to reflect the change in the 
percentage of individuals who are uninsured. The resulting amount is 
then used to determine the amount available to make uncompensated 
care payments to eligible IPPS hospitals in FY 2023. In other words, 
the amount of the Medicare DSH payments that would have been made 
prior to the amendments made by the Affordable Care Act is adjusted 
to 49.28 percent (the product of 75 percent and 65.71 percent) and 
the resulting amount is used to calculate the uncompensated care 
payments to eligible hospitals. As a result, for FY 2023, we

[[Page 49451]]

projected that the reduction in the amount of Medicare DSH payments 
pursuant to section 1886(r)(1) of the Act, along with the payments 
for uncompensated care under section 1886(r)(2) of the Act, will 
result in overall Medicare DSH payments of 74.28 percent of the 
amount of Medicare DSH payments that would otherwise have been made 
in the absence of the amendments made by the Affordable Care Act 
(that is, 25 percent + 49.28 percent = 74.28 percent).
    Therefore, for FY 2023, in the FY 2023 IPPS/LTCH PPS proposed 
rule, we proposed to establish that the calculation of the ``IPPS 
comparable amount'' under Sec.  412.529 would include an applicable 
operating Medicare DSH payment amount that is equal to 74.28 percent 
of the operating Medicare DSH payment amount that would have been 
paid based on the statutory Medicare DSH payment formula absent the 
amendments made by the Affordable Care Act. Furthermore, consistent 
with our historical practice, we proposed that if more recent data 
became available, we would use that data to determine this factor in 
the final rule.
    We did not receive any public comments in response to our 
proposal. In addition, there are no more recent data available to 
use that would affect the calculations determined in the proposed 
rule. Therefore, we are finalizing our proposal that, for FY 2023, 
the calculation of the ``IPPS comparable amount'' under Sec.  
412.529 would include an applicable operating Medicare DSH payment 
amount that is equal to 74.28 percent of the operating Medicare DSH 
payment amount that would have been paid based on the statutory 
Medicare DSH payment formula absent the amendments made by the 
Affordable Care Act.

F. Computing the Adjusted LTCH PPS Federal Prospective Payments for FY 
2023

    Section 412.525 sets forth the adjustments to the LTCH PPS 
standard Federal payment rate. Under the dual rate LTCH PPS payment 
structure, only LTCH PPS cases that meet the statutory criteria to 
be excluded from the site neutral payment rate are paid based on the 
LTCH PPS standard Federal payment rate. Under Sec.  412.525(c), the 
LTCH PPS standard Federal payment rate is adjusted to account for 
differences in area wages by multiplying the labor-related share of 
the LTCH PPS standard Federal payment rate for a case by the 
applicable LTCH PPS wage index (the proposed FY 2023 values are 
shown in Tables 12A through 12B listed in section VI. of the 
Addendum to this final rule and are available via the internet on 
the CMS website). The LTCH PPS standard Federal payment rate is also 
adjusted to account for the higher costs of LTCHs located in Alaska 
and Hawaii by the applicable COLA factors (the final FY 2023 factors 
are shown in the chart in section V.C. of this Addendum) in 
accordance with Sec.  412.525(b). In this final rule, we are 
establishing an LTCH PPS standard Federal payment rate for FY 2023 
of $46,432.77 as discussed in section V.A. of the Addendum to this 
final rule. We illustrate the methodology to adjust the LTCH PPS 
standard Federal payment rate for FY 2023, applying our finalized 
LTCH PPS amounts for the standard Federal payment rate, MS-LTC-DRG 
relative weights, and wage index in the following example:
    Example:
    During FY 2023, a Medicare discharge that meets the criteria to 
be excluded from the site neutral payment rate, that is, an LTCH PPS 
standard Federal payment rate case, is from an LTCH that is located 
in CBSA 16984, which has a FY 2023 LTCH PPS wage index value of 
1.0437 (as shown in Table 12A listed in section VI. of the Addendum 
to this final rule). The Medicare patient case is classified into 
proposed MS-LTC-DRG 189 (Pulmonary Edema & Respiratory Failure), 
which has a relative weight for FY 2023 of 0.9606 (as shown in Table 
11 listed in section VI. of the Addendum to this final rule). The 
LTCH submitted quality reporting data for FY 2023 in accordance with 
the LTCH QRP under section 1886(m)(5) of the Act.
    To calculate the LTCH's total adjusted Federal prospective 
payment for this Medicare patient case in FY 2023, we computed the 
wage-adjusted Federal prospective payment amount by multiplying the 
unadjusted FY 2023 LTCH PPS standard Federal payment rate 
($46,432.77) by the labor-related share (0.680 percent) and the wage 
index value (1.0437). This wage-adjusted amount was then added to 
the proposed nonlabor-related portion of the unadjusted proposed 
LTCH PPS standard Federal payment rate (0.320 percent; adjusted for 
cost of living, if applicable) to determine the adjusted LTCH PPS 
standard Federal payment rate, which is then multiplied by the MS-
LTC-DRG relative weight (0.9606) to calculate the total adjusted 
LTCH PPS standard Federal prospective payment for FY 2023 
($45,928.75). The table illustrates the components of the 
calculations in this example.
[GRAPHIC] [TIFF OMITTED] TR10AU22.222

VI. Tables Referenced in This Final Rule Generally Available Through 
the Internet on the CMS Website

    This section lists the tables referred to throughout the 
preamble of this final rule and in the Addendum. In the past, a 
majority of these tables were published in the Federal Register as 
part of the annual proposed and final rules. However, similar to FYs 
2012 through 2022, for the FY 2023 rulemaking cycle, the IPPS and 
LTCH PPS tables will not be published in the Federal Register in the 
annual IPPS/LTCH PPS proposed and final rules and will be available 
through the internet. Specifically, all IPPS tables listed in the 
final rule, with the exception of IPPS Tables 1A, 1B, 1C, and 1D, 
and LTCH PPS Table 1E, will generally be available through the 
internet. IPPS Tables 1A, 1B, 1C, and 1D, and LTCH PPS Table 1E are 
displayed at the end of this section and will continue to be 
published in the Federal Register as part of the annual proposed and 
final rules. For additional discussion of the information included 
in the IPPS and LTCH PPS tables associated with the IPPS/LTCH PPS 
proposed and final rules, as well as prior changes to the 
information included in these tables, we refer readers to the FY 
2022 IPPS/LTCH PPS final rule (86 FR 45569 through 45571).
    In addition, under the HAC Reduction Program, established by 
section 3008 of the Affordable Care Act, a hospital's total payment 
may be reduced by 1 percent if it is in the lowest HAC performance 
quartile. The hospital-level data for the FY 2023 HAC Reduction 
Program will be made publicly available once it has undergone the 
review and corrections process.
    In the FY 2023 IPPS/LTCH proposed rule (87 FR 28695), we noted 
that Tables 7A and 7B historically contained the Medicare 
prospective payment system selected percentile lengths of stay for 
the MS-DRGs for the prior year and upcoming fiscal year. As 
discussed in section II.E of the FY 2023 IPPS/LTCH proposed rule (87 
FR 28197--28204), we proposed to determine the MS-DRG relative 
weights for FY 2023 by averaging the relative weights as calculated 
with and without COVID-19 cases in the FY 2021 data. Because we 
proposed to use MS-DRG weights based on an average of the relative 
weights, we stated that the percentile lengths of stay, which are 
based on separate sets of MS-DRG relative weights prior to averaging 
are not applicable to the proposed averaged MS-DRG relative weights 
for FY 2023. The separate percentile lengths of stay statistics are 
only applicable to the relative weights as calculated with and 
without COVID-19 cases. Additionally, we also stated that unlike the 
other files listed as tables in this section of the final rule that 
typically

[[Page 49452]]

contain information/variables relating to a hospital's IPPS claim 
for payment, Tables 7A and 7B are informational files containing 
percentile lengths of stay that are not used for claim payment. 
Therefore, in the FY 2023 IPPS/LTCH proposed rule (87 FR 28695), 
beginning with the FY 2023 IPPS/LTCH PPS proposed rule, we proposed 
to instead provide the percentile length of stay information 
previously included in Tables 7A and 7B in the supplemental AOR/BOR 
data file, as described in section XII.A. of this final rule, which 
contains additional data relevant to the MS-DRG relative weights. 
For FY 2023, because we proposed to average the relative weights, in 
the proposed rule we provided an AOR/BOR file for the relative 
weights calculated with COVID-19 cases in the December 2021 update 
of the FY 2021 MedPAR file and an AOR/BOR file for the relative 
weights calculated without COVID-19 cases in the December 2021 
update of the FY 2021 MedPAR file (we note, for this final rule we 
used the March 2022 update of the FY 2021 MedPAR file). Therefore, 
instead of including the percentile lengths of stay that are 
typically in Tables 7A and 7B (that is, for the proposed rule, the 
selected percentile lengths of stay based on the MedPAR data and MS-
DRGs for the prior year and upcoming fiscal year (for FY 2023, this 
would be the version 40 GROUPER and version 39 GROUPER)) we proposed 
to include this statistical information in the AOR/BOR File for the 
relative weights as calculated with and without COVID-19 cases. The 
AOR/BOR files can be found on the FY 2023 IPPS final rule home page 
on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html. We note, as discussed 
in section II.E of this final rule, after consideration of the 
public comments, we are finalizing our proposal to determine the MS-
DRG relative weights for FY 2023 by averaging the relative weights 
as calculated with and without COVID-19 cases in the FY 2021 data.
    We did not receive any comments on our proposal previously 
noted. Therefore, we are finalizing as proposed without modification 
that beginning with the FY 2023 IPPS/LTCH PPS proposed and final 
rules, to provide the percentile length of stay information 
previously included in Tables 7A and 7B in the supplemental AOR/BOR 
data file.
    For this FY 2023 IPPS/LTCH final rule, because we are finalizing 
to average the relative weights, similar to the proposed rule, we 
are providing an AOR/BOR file for the relative weights calculated 
with COVID-19 cases in the March 2022 update of the FY 2021 MedPAR 
file and an AOR/BOR file for the relative weights calculated without 
COVID-19 cases in the March 2022 update of the FY 2021 MedPAR file. 
Both of these files will include the percentile lengths of stay that 
were typically in Tables 7A and 7B.
    As was the case for the FY 2022 IPPS/LTCH PPS proposed and final 
rules, we are no longer including Table 15, which had typically 
included the fiscal year readmissions payment adjustment factors 
because hospitals have not yet had the opportunity to review and 
correct the data before the data are made public under our policy 
regarding the reporting of hospital-specific data. After hospitals 
have been given an opportunity to review and correct their 
calculations for FY 2023, we will post Table 15 (which will be 
available via the internet on the CMS website) to display the final 
FY 2023 readmissions payment adjustment factors that will be 
applicable to discharges occurring on or after October 1, 2022. We 
expect Table 15 will be posted on the CMS website in the fall of 
2022.
    Readers who experience any problems accessing any of the tables 
that are posted on the CMS websites identified in this final rule 
should contact Michael Treitel at (410) 786-4552.
    The following IPPS tables for this final rule are generally 
available through the internet on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html. Click on the link on the left side of 
the screen titled ``FY 2023 IPPS Final Rule Home Page'' or ``Acute 
Inpatient-Files-for Download.'' We refer readers to section I.O. of 
the Appendix A of this final rule for a discussion of the 
supplemental data files we are making available based on the use of 
the FY 2021 data without the modifications to our usual 
methodologies for the calculation of the FY 2023 MS-DRG and MS-LTC-
DRG relative weights or our usual methodologies for the 
determination of the FY 2023 outlier fixed-loss amount for IPPS 
cases and LTCH PPS standard Federal payment rate cases for this FY 
2023 ratesetting, which we are also making available on the CMS 
website.

Table 2--Case-Mix Index and Wage Index Table by CCN--FY 2023 Final Rule

Table 3--Wage Index Table by CBSA--FY 2023 Final Rule

Table 4A--List of Counties Eligible for the Out-Migration Adjustment 
Under Section 1886(d)(13) of the Act--FY 2023 Final Rule

Table 4B--Counties Redesignated Under Section 1886(d)(8)(B) of the Act 
(LUGAR Counties)--FY 2023 Final Rule

Table 5--List of Medicare Severity Diagnosis-Related Groups (MS-DRGs), 
Relative Weighting Factors, and Geometric and Arithmetic Mean Length of 
Stay--FY 2023

Table 6A--New Diagnosis Codes--FY 2023

Table 6B--New Procedure Codes--FY 2023

Table 6C--Invalid Diagnosis Codes--FY 2023

Table 6D--Invalid Procedure Codes--FY 2023

Table 6E.--Revised Diagnosis Code Titles--FY 2023

Table 6G.1.--Secondary Diagnosis Order Additions to the CC Exclusions 
List--FY 2023

Table 6G.2.--Principal Diagnosis Order Additions to the CC Exclusions 
List--FY 2023

Table 6H.1.--Secondary Diagnosis Order Deletions to the CC Exclusions 
List--FY 2023

Table 6H.2.--Principal Diagnosis Order Deletions to the CC Exclusions 
List--FY 2023

Table 6I.--Complete MCC List--FY 2023

Table 6I.1.--Additions to the MCC List--FY 2023

Table 6I.2.--Deletions to the MCC List--FY 2023

Table 6J.--Complete CC List--FY 2023

Table 6J.1.--Additions to the CC List--FY 2023

Table 6J.2.--Deletions to the CC List--FY 2023

Table 6K.--Complete List of CC Exclusions--FY 2023

Table 6P.--ICD-10-CM and ICD-10-PCS Codes for MS-DRG Changes--FY 2023

    (Table 6P contains multiple tables, 6P.1a. through 6P.1f that 
include the ICD-10-CM and ICD-10-PCS code lists relating to specific 
MS-DRG changes. These tables are referred to throughout section 
II.D. of the preamble of this final rule.)

[[Page 49453]]

Table 8A.--FY 2023 Statewide Average Operating Cost-to-Charge Ratios 
(CCRs) for Acute Care Hospitals (Urban and Rural)

Table 8B.--FY 2023 Statewide Average Capital Cost-to-Charge Ratios 
(CCRs) for Acute Care Hospitals

Table 18.--FY 2023 Medicare DSH Uncompensated Care Payment Factor 3

    The following LTCH PPS tables for this FY 2023 final rule are 
available through the internet on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/LongTermCareHospitalPPS/ under the list item for 
Regulation Number CMS-1771-F:

Table 8C.--FY 2023 Statewide Average Total Cost-to-Charge Ratios (CCRs) 
for LTCHs (Urban and Rural)

Table 11.--MS-LTC-DRGs, Relative Weights, Geometric Average Length of 
Stay, and Short-Stay Outlier (SSO) Threshold for LTCH PPS Discharges 
Occurring from October 1, 2022, through September 30, 2023

Table 12A.--LTCH PPS Wage Index for Urban Areas for Discharges 
Occurring from October 1, 2022, through September 30, 2023

Table 12B.--LTCH PPS Wage Index for Rural Areas for Discharges 
Occurring from October 1, 2022, through September 30, 2023
[GRAPHIC] [TIFF OMITTED] TR10AU22.223

[GRAPHIC] [TIFF OMITTED] TR10AU22.224

[GRAPHIC] [TIFF OMITTED] TR10AU22.225

[GRAPHIC] [TIFF OMITTED] TR10AU22.226


[[Page 49454]]


[GRAPHIC] [TIFF OMITTED] TR10AU22.227

Appendix A: Economic Analyses

I. Regulatory Impact Analysis

A. Statement of Need

    This final rule is necessary in order to make payment and policy 
changes under the IPPS for Medicare acute care hospital inpatient 
services for operating and capital-related costs as well as for 
certain hospitals and hospital units excluded from the IPPS. This 
final rule also is necessary to make payment and policy changes for 
Medicare hospitals under the LTCH PPS. Also, as we note later in 
this Appendix, the primary objective of the IPPS and the LTCH PPS is 
to create incentives for hospitals to operate efficiently and 
minimize unnecessary costs, while at the same time ensuring that 
payments are sufficient to adequately compensate hospitals for their 
legitimate costs in delivering necessary care to Medicare 
beneficiaries. In addition, we share national goals of preserving 
the Medicare Hospital Insurance Trust Fund.
    We believe that the changes in this final rule, such as the 
updates to the IPPS and LTCH PPS rates, and the final policies and 
discussions relating to applications for new technology add-on 
payments, are needed to further each of these goals while 
maintaining the financial viability of the hospital industry and 
ensuring access to high quality health care for Medicare 
beneficiaries.
    We expect that these changes will ensure that the outcomes of 
the prospective payment systems are reasonable and provide equitable 
payments, while avoiding or minimizing unintended adverse 
consequences.

1. Acute Care Hospital Inpatient Prospective Payment System (IPPS)

a. Update to the IPPS Payment Rates

    In accordance with section 1886(b)(3)(B) of the Act and as 
described in section V.A. of the preamble to this final rule, we 
updated the national standardized amount for inpatient hospital 
operating costs by the applicable percentage increase of 3.8 percent 
(that is, a 4.1 percent market basket update with a reduction of 0.3 
percentage point for the productivity adjustment) and by a 0.5 
percentage point adjustment required under section 414 of the MACRA. 
We are also applying the applicable percentage increase (including 
the market basket update and the productivity adjustment) to the 
hospital-specific rates.
    Hospitals that do not submit quality information under rules 
established by the Secretary and that are meaningful EHR users under 
section 1886(b)(3)(B)(ix) of the Act would receive an applicable 
percentage increase of 2.775 percent. Hospitals that are identified 
as not meaningful EHR users and do submit quality information under 
section 1886(b)(3)(B)(viii) of the Act would receive an applicable 
percentage increase of 0.725 percent.
    Hospitals that are identified as not meaningful EHR users under 
section 1886(b)(3)(B)(ix) of the Act and also do not submit quality 
data under section 1886(b)(3)(B)(viii) of the Act will receive an 
applicable percentage increase of -0.3 percent, which reflects a 
one-quarter percent reduction of the market basket update for 
failure to submit quality data and a three-quarter percent reduction 
of the market basket update for being identified as not a meaningful 
EHR user.

b. Use of FY 2021 Data in the FY 2023 IPPS and LTCH PPS Ratesetting

    As discussed in section I.A. of the preamble of this final rule, 
we believe that it is reasonable to assume that some Medicare 
beneficiaries will continue to be hospitalized with COVID-19 at IPPS 
hospitals and LTCHs in FY 2023. Accordingly, we believe it is 
appropriate to use FY 2021 data, specifically the FY 2021 MedPAR 
claims file and the FY 2020 HCRIS dataset (which contains data from 
many cost reports ending in FY 2021 based on each hospital's cost 
reporting period) as the most recent available data during the 
period of the COVID-19 PHE, for purposes of the FY 2023 IPPS and 
LTCH PPS ratesetting. However, we also believe it is reasonable to 
assume based on the information available at this time that there 
will be fewer COVID 19 hospitalizations in FY 2023 than in FY 2021 
given the more recent trends in the CDC hospitalization data since 
the Omicron variant peak in January, 2022. Accordingly, because we 
anticipate Medicare inpatient hospitalizations for COVID-19 will 
continue in FY 2023 but at a lower level, we are using FY 2021 data 
for purposes of the FY 2023 IPPS and LTCH PPS ratesetting but with 
modifications to our usual ratesetting methodologies to account for 
the anticipated decline in COVID-19 hospitalizations of Medicare 
beneficiaries at IPPS hospitals and LTCHs as compared to FY 2021.
    First, we are modifying the calculation of the FY 2023 MS-DRG 
and MS LTC DRG relative weights. The final policy to modify the 
methodology for determining the FY 2023 IPPS MS-DRG relative weights 
is discussed in section II.E. of the preamble of this final rule. 
The final policy to modify the methodology for determining the FY 
2023 LTCH PPS MS-LTC-DRG relative weights is discussed in greater 
detail in section VIII.B. of the preamble of this final rule. This 
modification primarily impacts MS-DRGs and MS-LTC DRGs with larger 
numbers of COVID-19 cases, for example MS-DRG 870 (Septicemia or 
Severe Sepsis with MV >96 hours). IPPS hospitals that 
disproportionately treat high numbers of COVID-19 cases will 
generally see increased non-outlier payments compared to what those 
payments would have been had we excluded the COVID-19 cases 
entirely, and lower payments compared to if we had not made any 
modifications to our usual methodology for calculating the relative 
weights. This final policy reflects our belief that there will be 
fewer COVID-19 cases in FY 2023 than in FY 2021, but there will 
still be COVID-19 cases in FY 2023.
    Second, we also are modifying our methodologies for determining 
the FY 2023 outlier fixed-loss amount for IPPS cases and LTCH PPS 
standard Federal payment rate cases. The final policy to modify the 
methodology for determining the FY 2023 outlier fixed-loss amounts 
for IPPS cases is discussed in section II.A.4. of the Addendum to 
this final rule. The final policy to modify the methodology for 
determining the FY 2023 outlier fixed loss amounts for LTCH PPS 
standard Federal payment rate cases is discussed in section V.D.3. 
of the Addendum to this final rule. This modification has a greater 
impact on hospitals with larger numbers of outlier cases. IPPS 
hospitals that receive outlier payments will see lower outlier 
payments compared to what those payments would have been had we 
excluded the COVID-19 cases entirely, and higher outlier payments 
compared to if we had not made any modifications to our usual 
methodology for calculating the outlier fixed loss amount. Again, 
this final policy reflects our belief that there will be fewer 
COVID-19 cases in FY 2023 than in FY 2021, but there will still be 
COVID-19 cases in FY 2023.

c. Cap on Reductions in Medicare Severity Diagnosis-Related Group (MS-
DRG) Relative Weights

    As described in section II.E.2. of the preamble of this final 
rule, we have further considered requests made by commenters that we 
address year-to-year fluctuations in relative weights, particularly 
for low volume MS-DRGs, and to mitigate the financial impacts of 
significant fluctuations. As described in section II.E.2. of this 
final rule, for these low volume MS-DRGs, fluctuations in the volume 
or mix of cases and/or the presence of a few high cost or low cost 
cases can have a disproportionate impact on the calculated relative 
weight, thus resulting in greater year-to-year variation in the 
relative weights for these MS-DRGs. Consistent with

[[Page 49455]]

our statutory authority under section 1886(d)(4)(B) and (C) of the 
Act to assign and update appropriate weighting factors, beginning in 
FY 2023, we are finalizing a permanent 10-percent cap on the 
reduction in a MS-DRG's relative weight in a given fiscal year. This 
final policy is consistent with our general authority to assign and 
update appropriate weighting factors as part of our annual 
reclassifications of the MS-DRGs and recalibration of the relative 
weights under sections 1886(d)(4)(B) and (C)(i) of the Act, as well 
as the requirements of section 1886(d)(4)(C)(iii) of the Act, which 
specifies that the annual DRG reclassification and recalibration of 
the relative weights be made in a manner that ensures that aggregate 
payments to hospitals are not affected. In addition, we have 
authority to implement this cap and the associated budget neutrality 
adjustment under our special exceptions and adjustments authority at 
section 1886(d)(5)(I)(i) of the Act, which similarly gives the 
Secretary broad authority to provide by regulation for such other 
exceptions and adjustments to the payment amounts under section 
1886(d) of the Act as the Secretary deems appropriate. For the vast 
majority of hospitals, the impact of the 10-percent cap, inclusive 
of the budget neutrality factor, is less than 0.1 percent. We note 
that the impact of not finalizing a 10-percent cap for FY 2023, or 
finalizing a higher cap, such as 15 or 20 percent, would be most 
marked for hospitals whose case mix includes more MS-DRGs 
experiencing reductions of greater than 10-percent for FY 2023. The 
impact of finalizing a lower cap, such as 5 percent, would be 
increases to hospitals whose case mix includes more MS-DRGs 
experiencing reductions of between 5 and 10 percent, with a 
corresponding increase in the budget neutrality adjustment for all 
hospitals.

d. Add-On Payments for New Services and Technologies

    Consistent with sections 1886(d)(5)(K) and (L) of the Act, CMS 
reviews applications for new technology add-on payments based on the 
eligibility criteria at 42 CFR 412.87. As set forth in 42 CFR 
412.87(e)(1), CMS considers whether a technology meets the criteria 
for the new technology add-on payment and announces the results as 
part of its annual updates and changes to the IPPS.

(1) Proposal To Use National Drug Codes (NDCs) for Identification of 
Certain Therapeutic Agents Approved for New Technology Add-On Payment

    In section II.F.8. of the preamble of this final rule, we detail 
our proposal to use National Drug Codes (NDCs) to identify cases 
involving use of therapeutic agents approved for new technology add-
on payments, and discuss comments received. After consideration of 
the comments received, including concerns that our proposed use of 
NDCs for this purpose may impose new administrative burdens to 
hospitals, we are not finalizing this proposal, and will instead 
reassess this policy proposal in future rulemaking.

(2) Publicly Post Applications for New Technology Add-On Payments

    As discussed in section II.F.9. of the preamble of this final 
rule, beginning with the FY 2024 application cycle for new 
technology add-on payments, we are finalizing our proposal to 
publicly post online the completed application forms and certain 
related materials, including updated application information 
submitted subsequent to the initial application submission, with the 
exception of cost and volume information and certain additional 
information and materials, as discussed more fully in section 
II.F.9. of the preamble of this final rule. We have received 
requests from the public to access and review the new technology 
add-on payment applications to further facilitate comment on whether 
a technology meets the new technology add-on payment criteria. 
Making this information publicly available may also foster greater 
input from interested parties based on their review of the completed 
application forms and related materials.
    Additionally, we believe that posting the applications online 
will reduce the risk that we may inadvertently omit or misrepresent 
relevant information submitted by applicants, or are perceived as 
misrepresenting such information, in our summaries in the rules. It 
also will streamline our evaluation process, including the 
identification of critical questions in the proposed rule, 
particularly as the number and complexity of the applications have 
been increasing over time. That is, by making the applications 
available to the public online, we will afford more time for CMS to 
process and analyze the supporting data and evidence rather than 
reiterate parts of the application in the rule.

e. Permanent Cap on Wage Index Decreases

    Consistent with section 1886(d)(3)(E) of the Act, we adjust the 
IPPS standardized amounts for area differences in hospital wage 
levels by a factor (established by the Secretary) reflecting the 
relative hospital wage level in the geographic area of the hospital 
compared to the national average hospital wage level and update the 
wage index annually based on a survey of wages and wage-related 
costs of short-term, acute care hospitals. As described in section 
III.N. of the preamble of this final rule, we have further 
considered the comments we received during the FY 2022 rulemaking 
recommending a permanent 5-percent cap policy to prevent large year-
to-year variations in wage index values as a means to reduce overall 
volatility for hospitals. Under the authority at sections 
1886(d)(3)(E) and 1886(d)(5)(I)(i) of the Act, for FY 2023 and 
subsequent years, we proposed to apply a 5-percent cap on any 
decrease to a hospital's wage index from its wage index in the prior 
FY, regardless of the circumstances causing the decline. That is, we 
proposed that a hospital's wage index for FY 2023 would not be less 
than 95 percent of its final wage index for FY 2022, and that for 
subsequent years, a hospital's wage index would not be less than 95 
percent of its final wage index for the prior FY. We also proposed 
to apply the proposed wage index cap policy in a budget neutral 
manner through a national adjustment to the standardized amount 
under our authority in sections 1886(d)(3)(E) and 1886(d)(5)(I)(i) 
of the Act. As described in section III.N. of the preamble of this 
final rule, after consideration of the public comments received, we 
are finalizing these proposals without modification.
    We note that the impact of not finalizing a 5 percent cap, or 
finalizing a higher cap, such as 10 percent, would be most marked 
for hospitals who have wage index changes of greater than 5 percent 
but less than the selected cap level, if any, in a given fiscal 
year. For example, in FY 2023 if the cap were 10 percent instead of 
5 percent, approximately 12 hospitals would qualify vs approximately 
125 hospitals under our adopted policy. The impact of finalizing a 
lower cap would be increases in payment to hospitals with wage index 
changes between a lower level and 5 percent, with a corresponding 
increase in the size of the budget neutrality adjustment for all 
hospitals.

f. Continuation of the Low Wage Index Hospital Policy

    To help mitigate wage index disparities between high wage and 
low wage hospitals, in the FY 2020 IPPS/LTCH PPS rule (84 FR 42326 
through 42332), we adopted a policy to increase the wage index 
values for certain hospitals with low wage index values (the low 
wage index hospital policy). This policy was adopted in a budget 
neutral manner through an adjustment applied to the standardized 
amounts for all hospitals. We also indicated our intention that this 
policy would be effective for at least 4 years, beginning in FY 
2020, in order to allow employee compensation increases implemented 
by these hospitals sufficient time to be reflected in the wage index 
calculation. As discussed in section III.G.4. of the preamble of 
this final rule, for FY 2023, we are continuing the low wage index 
hospital policy, and are also applying this policy in a budget 
neutral manner by applying an adjustment to the standardized 
amounts.

g. Application of the Rural Floor

    As discussed in section III.G.1. of the preamble of this final 
rule, based on the district court's decision in Citrus HMA, LLC, d/
b/a Seven Rivers Regional Medical Center v. Becerra, No. 1:20-cv-
00707 (D.D.C.) and the comments we received, we are not finalizing 
our rural floor wage index policy as proposed, which would have 
excluded Sec.  412.103 hospitals from the calculation of the rural 
floor and from the calculation of ``the wage index for rural areas 
in the State in which the county is located'' as referred to in 
section 1886(d)(8)(C)(iii) of the Act. Rather, we are finalizing a 
policy that calculates the rural floor as it was calculated before 
FY 2020. For FY 2023 and subsequent years, we are finalizing a 
policy to include the wage data of hospitals that have reclassified 
from urban to rural under section 1886(d)(8)(E) of the Act (as 
implemented in the regulations at Sec.  412.103) and have no 
additional form of reclassification (MGCRB or Lugar) in the 
calculation of the rural floor, and to include the wage data of such 
hospitals in the calculation of ``the wage index for rural areas in 
the State in which the county is located'' as referred to in section 
1886(d)(8)(C)(iii) of the Act.
    The rural floor, which is budget neutral overall, increases 
payments to urban

[[Page 49456]]

hospitals whose wage index would otherwise be below the rural floor 
for their state. The policy we are adopting in section III.G.1. of 
the preamble of this final rule increases the rural floor in some 
states (for example, Arizona, Utah). This will generally increase 
payments to some urban hospitals in those states because their wage 
index will be higher than it otherwise would have been in the 
absence of this change. After application of the rural floor, we 
reduce the wage index of all hospitals by applying a budget 
neutrality factor to offset the increased payments. We note that 
there is either no increase in the rural floor or the increase in 
the rural floor is nominal in the majority of states, and the 
majority of hospitals will only experience payment decreases due to 
the effect of the increase in the budget neutrality adjustment.

h. Payment Adjustment for Medicare Disproportionate Share Hospitals 
(DSHs)

    In this final rule, as required by section 1886(r)(2) of the 
Act, we are updating our estimates of the three factors used to 
determine uncompensated care payments for FY 2023. We are finalizing 
our proposal to adopt a multiyear averaging methodology to determine 
Factor 3 of the uncompensated care payment methodology, which will 
help to mitigate against large fluctuations in uncompensated care 
payments from year to year. Specifically, we are using a 2-year 
average of audited data on uncompensated care costs from Worksheet 
S-10 from the FY 2018 and FY 2019 cost reports to calculate Factor 3 
for FY 2023 for all eligible hospitals, including Indian Health 
Service (IHS) and Tribal hospitals and hospitals located in Puerto 
Rico. In addition, for FY 2024 and subsequent fiscal years, we will 
determine Factor 3 for all eligible hospitals using a 3-year average 
of the data on uncompensated care costs from Worksheet S-10 for the 
3 most recent fiscal years for which audited data are available.
    We recognize that discontinuing the use of the low-income 
insured days proxy to calculate Factor 3 in the uncompensated care 
payment methodology for IHS and Tribal hospitals and Puerto Rico 
hospitals could result in a significant financial disruption for 
these hospitals. Accordingly, we are also finalizing our proposal to 
use our authority under section 1886(d)(5)(I) of the Act to 
establish a new supplemental payment for these hospitals for FY 2023 
and subsequent fiscal years. Refer to section I.H.2. of this 
Appendix for additional analysis on this new supplemental payment 
for FY 2023.
    In the FY 2023 IPPS/LTCH PPS proposed rule, we proposed to 
revise our regulation governing the calculation of the Medicaid 
fraction of the DSH calculation with respect to the treatment of 
section 1115 demonstration days. As discussed in section IV.F. of 
the preamble of this final rule, we are not moving forward with the 
proposed revisions to the regulations relating to the treatment of 
section 1115 demonstration days for purposes of the DSH adjustment 
in this final rule. We expect to revisit the issue of section 1115 
demonstration days in future rulemaking, and we encourage interested 
parties to review any future proposal on this issue and to submit 
their comments at that time.

i. Effects of Implementation of the Rural Community Hospital 
Demonstration Program in FY 2023

    The Rural Community Hospital Demonstration (RCHD) was authorized 
originally for a 5-year period by section 410A of the Medicare 
Prescription Drug, Improvement, and Modernization Act of 2003 (MMA) 
(Pub. L. 108-173), and it was extended for another 5-year period by 
section 3123 and 10313 of the Affordable Care Act (Pub. L. 111-148). 
Section 15003 of the 21st Century Cures Act (Cures Act) (Pub. L. 
114-255) extended the demonstration for an additional 5-year period, 
and section 128 of the Consolidated Appropriations Act of 2021(Pub. 
L. 116-159) included an additional 5-year re-authorization through 
2028. CMS has conducted the demonstration since 2004, which allows 
enhanced, cost-based payment for Medicare inpatient services for up 
to 30 small rural hospitals.
    The authorizing legislation imposes a strict budget neutrality 
requirement. In this final rule, we summarized the status of the 
demonstration program, and the ongoing methodologies for 
implementation and budget neutrality.

2. Payments for Graduate Medical Education (GME)

    On May 17, 2021, the U.S. District Court for the District of 
Columbia ruled against CMS's method of calculating direct GME 
payments to teaching hospitals when those hospitals' weighted full-
time equivalent (FTE) counts exceed their direct GME FTE cap. In 
Milton S. Hershey Medical Center, et al. v. Becerra, the court 
ordered CMS to recalculate reimbursement owed, holding that CMS's 
regulation impermissibly modified the statutory weighting factors.
    After reviewing the statutory language regarding the direct GME 
FTE cap and the court's opinion in Milton S. Hershey Medical Center, 
et al. v. Becerra, we are finalizing, as described in greater detail 
in section V.F.2. of the preamble of this final rule, a modified 
policy to be applied retroactively and prospectively for all 
teaching hospitals. Specifically, effective for cost reporting 
periods beginning on or after October 1, 2001 that are open or 
reopenable, we specified that if the hospital's unweighted number of 
FTE residents exceeds the FTE cap, and the number of weighted FTE 
residents also exceeds that FTE cap, the respective primary care and 
obstetrics and gynecology weighted FTE counts and other weighted FTE 
counts are adjusted to make the total weighted FTE count equal the 
FTE cap. If the number of weighted FTE residents does not exceed 
that FTE cap, then the allowable weighted FTE count for direct GME 
payment is the actual weighted FTE count. We estimate the impact of 
this modified policy to be $170 million for FY 2023.

3. Frontier Community Health Integration Project (FCHIP) Demonstration

    The Frontier Community Health Integration Project (FCHIP) 
demonstration was authorized under section 123 of the Medicare 
Improvements for Patients and Providers Act of 2008 (Pub. L. 110-
275), as amended by section 3126 of the Affordable Care Act (ACA) of 
2010 (Pub. L. 114-158), and most recently re-authorized and extended 
by the Consolidated Appropriations Act of 2021 (Pub. L. 116-159). 
The legislation authorized a demonstration project to allow eligible 
entities to develop and test new models for the delivery of health 
care in order to improve access to and better integrate the delivery 
of acute care, extended care and other health care services to 
Medicare beneficiaries in certain rural areas. The FCHIP 
demonstration initial period was conducted in 10 critical access 
hospitals (CAHs) from August 1, 2016, to July 31, 2019, and the 
demonstration ``extension period'' began on January 1, 2022, and run 
through June 30, 2027.
    The authorizing legislation requires the FCHIP demonstration to 
be budget neutral. In this final rule, we will continue with the 
budget neutrality approach used in the demonstration initial period 
for the demonstration extension period--to offset payments across 
CAHs nationally--should the demonstration incur costs to Medicare.

4. Update to the LTCH PPS Payment Rates

    As described in section VIII.C.2. of the preamble of this final 
rule, in order to update payments to LTCHs using the best available 
data, we updated the LTCH PPS standard Federal payment rate by 3.8 
percent (that is, a 4.1 percent market basket update with a 
reduction of 0.3 percentage point for the productivity adjustment, 
as required by section 1886(m)(3)(A)(i) of the Act). LTCHs that 
failed to submit quality data, as required by 1886(m)(5)(A)(i) of 
the Act and described in section VIII.C.2. of the preamble of this 
final rule, will receive an update of 1.8 percent, which reflects a 
2.0 percentage points reduction for failure to submit quality data.

5. Hospital Quality Programs

    Section 1886(b)(3)(B)(viii) of the Act requires subsection (d) 
hospitals to report data in accordance with the requirements of the 
Hospital IQR Program for purposes of measuring and making publicly 
available information on health care quality, and links the quality 
data submission to the annual applicable percentage increase. 
Sections 1886(b)(3)(B)(ix), 1886(n), and 1814(l) of the Act require 
eligible hospitals and CAHs to demonstrate they are meaningful users 
of certified EHR technology for purposes of electronic exchange of 
health information to improve the quality of health care, and links 
the submission of information demonstrating meaningful use to the 
annual applicable percentage increase for eligible hospitals and the 
applicable percent for CAHs. Section 1886(m)(5) of the Act requires 
each LTCH to submit quality measure data in accordance with the 
requirements of the LTCH QRP for purposes of measuring and making 
publicly available information on health care quality, and in order 
to avoid a 2-percentage point reduction. Section 1886(o) of the Act 
requires the Secretary to establish a value-based purchasing program 
under which value-based incentive payments are made in a fiscal year 
to hospitals that meet the performance standards established on an

[[Page 49457]]

announced set of quality and efficiency measures for the fiscal 
year. The purposes of the Hospital VBP Program include measuring the 
quality of hospital inpatient care, linking hospital measure 
performance to payment, and making publicly available information on 
hospital quality of care. Section 1886(p) of the Act requires a 
reduction in payment for subsection (d) hospitals that rank in the 
worst-performing 25 percent with respect to measures of hospital-
acquired conditions under the HAC Reduction Program for the purpose 
of measuring, linking measure performance to payment, and making 
publicly available information on health care quality. Section 
1886(q) of the Act requires a reduction in payment for subsection 
(d) hospitals for excess readmissions based on measures for 
applicable conditions under the Hospital Readmissions Reduction 
Program for the purpose of measuring, linking measure performance to 
payment, and making publicly available information on health care 
quality. Section 1866(k) of the Act applies to hospitals described 
in section 1886(d)(1)(B)(v) of the Act (referred to as ``PPS-Exempt 
Cancer Hospitals'' or ``PCHs'') and requires PCHs to report data in 
accordance with the requirements of the PCHQR Program for purposes 
of measuring and making publicly available information on the 
quality of care furnished by PCHs, however, there is no reduction in 
payment to a PCH that does not report data.

6. Other Provisions

a. Codification of the Costs Incurred for Qualified and Non-Qualified 
Deferred Compensation Plans

    As discussed in section X.A. of the preamble of this final rule, 
we codify in regulation certain general requirements; definitions; 
requirements for costs of the plans to be allowable under the 
program; additional requirements for payments to funded defined 
benefit plans; data and documentation requirements to support 
payments/contributions to the plans; and allowable administrative 
and other costs associated with the plans, including costs related 
to the Pension Benefit Guarantee Corporation.

b. Condition of Participation (CoP) Requirements for Hospitals and CAHs 
To Continue Reporting Data for COVID-19 and Influenza After the PHE 
Ends as Determined by the Secretary

    Section X.B. of the preamble of this final rule revises the 
hospital and CAH infection prevention and control CoP requirements 
to require hospitals and CAHs, after the conclusion of the current 
COVID-19 PHE, to continue COVID-19 and seasonal influenza related 
reporting. The revisions will continue to apply upon conclusion of 
the COVID-19 PHE and will continue until April 30, 2024, unless the 
Secretary establishes an earlier ending date. In addition, as noted 
previously, we have withdrawn our proposal to establish additional 
data reporting requirements to address future PHEs related to 
epidemics and infectious diseases.
    We believe these data will offer the most valuable information 
during a post-PHE state by continuing to capture critical data on 
COVID-19 for ongoing surveillance and to inform any potential action 
to protect patient health and safety. As previously discussed, these 
data will enable the federal government to monitor the ability of 
facilities to provide safe care for patients by determining the 
number of COVID-19 and influenza infections being treated by 
facilities; the quantity of resources available to facilities and 
the volume of resources they are using; and facilities' continued 
capacity to provide safe patient care. In addition, as done 
throughout the COVID-19 pandemic, local, state, and federal 
authorities will continue to use these data to identify possible 
resurgence in cases and outbreaks, for resource allocation purposes, 
and to update guidance pertaining to the safe provision of patient 
care.
    As discussed in section X.B. of this rule, due to the 
unpredictable nature of the novel SARS-CoV-2 virus that causes 
COVID-19, in the event that the PHE declaration ends, we believe 
that continuing COVID-19-related data reporting through April 2024 
is necessary to protect the health and safety of hospital and CAH 
patients as well as the communities in which the hospitals and CAHs 
are located. The COVID-19-related data reported by all hospitals and 
CAHs, have been, and continue to be, important in supporting 
surveillance of, and response to, COVID-19 and other respiratory 
illnesses. These data play an important role in evaluating spread of 
respiratory viruses and infections, including but not limited to 
COVID-19 and influenza. Retaining the data reporting requirements 
after the end of the current COVID-19 PHE is an important element of 
maintaining effective surveillance of this novel virus. Timely and 
actionable surveillance will enable CMS to continue to respond to 
facilities in need of additional technical support and oversight, 
should they experience increased cases or outbreaks of COVID-19 and/
or influenza.
    As noted, we do not expect continued daily reporting for COVID-
19 or influenza outside of a declared PHE. Moreover, the rule allows 
for the scope of data categories and frequency of data collection 
and reporting to be reduced and limited, as determined by the 
Secretary, responsive to evolving clinical and epidemiology 
circumstances. These requirements will not be implemented and 
enforced until the current COVID-19 PHE declaration concludes, and 
CMS will issue guidance indicating such a transition. Reporting 
frequency and requirements will be communicated to hospitals, 
stakeholders, and the public following a model similar to that which 
we used to inform regulated entities at the beginning of the COVID-
19 PHE (see QSO-21-03-Hospitals/CAHs at https://www.cms.gov/files/document/qso-21-03-hospitalscahs.pdf-0). As discussed in section 
XII.B. of the preamble of this final rule, Collection of Information 
Requirements, we expect a burden increase of $38,204,400 or 
approximately $6,162 per facility annually for weekly reporting (an 
average response time of 1.5 hours per week for a registered nurse 
with an average hourly salary of $79). We note that efforts are 
underway to automate hospital and CAH reporting that have the 
potential to significantly decrease reporting burden and improve 
reliability.

B. Overall Impact

    We have examined the impacts of this final rule as required by 
Executive Order 12866 on Regulatory Planning and Review (September 
30, 1993), Executive Order 13563 on Improving Regulation and 
Regulatory Review (January 18, 2011), the Regulatory Flexibility Act 
(RFA) (September 19, 1980, Pub. L. 96-354), section 1102(b) of the 
Social Security Act, section 202 of the Unfunded Mandates Reform Act 
of 1995 (March 22, 1995; Pub. L. 104-4), Executive Order 13132 on 
Federalism (August 4, 1999), and the Congressional Review Act (5 
U.S.C. 804(2)).
    Executive Orders 12866 and 13563 direct agencies to assess all 
costs and benefits of available regulatory alternatives and, if 
regulation is necessary, to select regulatory approaches that 
maximize net benefits (including potential economic, environmental, 
public health and safety effects, distributive impacts, and equity). 
Section 3(f) of Executive Order 12866 defines a ``significant 
regulatory action'' as an action that is likely to result in a rule: 
(1) having an annual effect on the economy of $100 million or more 
in any 1 year, or adversely and materially affecting a sector of the 
economy, productivity, competition, jobs, the environment, public 
health or safety, or state, local or tribal governments or 
communities (also referred to as ``economically significant''); (2) 
creating a serious inconsistency or otherwise interfering with an 
action taken or planned by another agency; (3) materially altering 
the budgetary impacts of entitlement grants, user fees, or loan 
programs or the rights and obligations of recipients thereof; or (4) 
raising novel legal or policy issues arising out of legal mandates, 
the President's priorities, or the principles set forth in the 
Executive order.
    A regulatory impact analysis (RIA) must be prepared for major 
rules with significant regulatory action/s and/or with economically 
significant effects ($100 million or more in any 1 year). Based on 
our estimates, OMB's Office of Information and Regulatory Affairs 
has determined this rulemaking is ``economically significant'' as 
measured by the $100 million threshold, and hence also a major rule 
under Subtitle E of the Small Business Regulatory Enforcement 
Fairness Act of 1996 (also known as the Congressional Review Act). 
Accordingly, we have prepared a Regulatory Impact Analysis that to 
the best of our ability presents the costs and benefits of the 
rulemaking. OMB has reviewed these finalized regulations, and the 
Departments have provided the following assessment of their impact.
    We estimate that the changes for FY 2023 acute care hospital 
operating and capital payments will redistribute amounts in excess 
of $100 million to acute care hospitals. The applicable percentage 
increase to the IPPS rates required by the statute, in conjunction 
with other payment changes in this final rule, will result in an 
estimated $1.4 billion increase in FY 2023 payments, primarily 
driven by: (a) a combined $2.4 billion increase in FY 2023 operating 
payments, including uncompensated care payments and supplemental 
payments; and (b) a combined decrease of $ 1.0 billion resulting 
from estimated changes in new technology add-on

[[Page 49458]]

payments, the change to the GME weighting methodology, the 
expiration of the low-volume payment adjustment, and FY 2023 capital 
payments. These changes are relative to payments made in FY 2022. 
The impact analysis of the capital payments can be found in section 
I.I. of this Appendix. In addition, as described in section I.J. of 
this Appendix, LTCHs are expected to experience an increase in 
payments by approximately $71 million in FY 2023 relative to FY 
2022.
    Our operating impact estimate includes the 0.5 percentage point 
adjustment required under section 414 of the MACRA applied to the 
IPPS standardized amount, as discussed in section II.D. of the 
preamble of this final rule. In addition, our operating payment 
impact estimate includes the 3.8 percent hospital update to the 
standardized amount (which includes the estimated 4.1 percent market 
basket update reduced by the 0.3 percentage point for the 
productivity adjustment). The estimates of IPPS operating payments 
to acute care hospitals do not reflect any changes in hospital 
admissions or real case-mix intensity, which will also affect 
overall payment changes.
    The analysis in this Appendix, in conjunction with the remainder 
of this document, demonstrates that this final rule is consistent 
with the regulatory philosophy and principles identified in 
Executive Orders 12866 and 13563, the RFA, and section 1102(b) of 
the Act. This final rule will affect payments to a substantial 
number of small rural hospitals, as well as other classes of 
hospitals, and the effects on some hospitals may be significant. 
Finally, in accordance with the provisions of Executive Order 12866, 
the Office of Management and Budget has reviewed this final rule.

C. Objectives of the IPPS and the LTCH PPS

    The primary objective of the IPPS and the LTCH PPS is to create 
incentives for hospitals to operate efficiently and minimize 
unnecessary costs, while at the same time ensuring that payments are 
sufficient to adequately compensate hospitals for their costs in 
delivering necessary care to Medicare beneficiaries. In addition, we 
share national goals of preserving the Medicare Hospital Insurance 
Trust Fund.
    We believe that the changes in this final rule would further 
each of these goals while maintaining the financial viability of the 
hospital industry and ensuring access to high quality health care 
for Medicare beneficiaries. We expect that these changes will ensure 
that the outcomes of the prospective payment systems are reasonable 
and equitable, while avoiding or minimizing unintended adverse 
consequences.
    Because this final rule contains a range of policies, we refer 
readers to the section of the final rule where each policy is 
discussed. These sections include the rationale for our decisions, 
including the need for the policy.

D. Limitations of Our Analysis

    The following quantitative analysis presents the projected 
effects of our policy changes, as well as statutory changes 
effective for FY 2023, on various hospital groups. We estimate the 
effects of individual policy changes by estimating payments per 
case, while holding all other payment policies constant. We use the 
best data available, but, generally unless specifically indicated, 
we do not attempt to make adjustments for future changes in such 
variables as admissions, lengths of stay, case mix, changes to the 
Medicare population, or incentives. In addition, we discuss 
limitations of our analysis for specific policies in the discussion 
of those policies as needed.

E. Hospitals Included In and Excluded From the IPPS

    The prospective payment systems for hospital inpatient operating 
and capital-related costs of acute care hospitals encompass most 
general short-term, acute care hospitals that participate in the 
Medicare program. There were 25 Indian Health Service hospitals in 
our database, which we excluded from the analysis due to the special 
characteristics of the prospective payment methodology for these 
hospitals. Among other short term, acute care hospitals, hospitals 
in Maryland are paid in accordance with the Maryland Total Cost of 
Care Model, and hospitals located outside the 50 States, the 
District of Columbia, and Puerto Rico (that is, 6 short-term acute 
care hospitals located in the U.S. Virgin Islands, Guam, the 
Northern Mariana Islands, and American Samoa) receive payment for 
inpatient hospital services they furnish on the basis of reasonable 
costs, subject to a rate-of-increase ceiling.
    As of March 2022, there were 3,142 IPPS acute care hospitals 
included in our analysis. This represents approximately 53 percent 
of all Medicare-participating hospitals. The majority of this impact 
analysis focuses on this set of hospitals. There also are 
approximately 1,425 CAHs. These small, limited service hospitals are 
paid on the basis of reasonable costs, rather than under the IPPS. 
IPPS-excluded hospitals and units, which are paid under separate 
payment systems, include IPFs, IRFs, LTCHs, RNHCIs, children's 
hospitals, cancer hospitals, extended neoplastic disease care 
hospital, and short-term acute care hospitals located in the Virgin 
Islands, Guam, the Northern Mariana Islands, and American Samoa. 
Changes in the prospective payment systems for IPFs and IRFs are 
made through separate rulemaking. Payment impacts of changes to the 
prospective payment systems for these IPPS-excluded hospitals and 
units are not included in this final rule. The impact of the final 
update and policy changes to the LTCH PPS for FY 2023 is discussed 
in section I.J. of this Appendix.

F. Effects on Hospitals and Hospital Units Excluded From the IPPS

    As of July 2022, there were 92 children's hospitals, 11 cancer 
hospitals, 6 short term- acute care hospitals located in the Virgin 
Islands, Guam, the Northern Mariana Islands and American Samoa, 1 
extended neoplastic disease care hospital, and 14 RNHCIs being paid 
on a reasonable cost basis subject to the rate-of-increase ceiling 
under Sec.  413.40. (In accordance with Sec.  403.752(a) of the 
regulation, RNHCIs are paid under Sec.  413.40.) Among the remaining 
providers, the rehabilitation hospitals and units, and the LTCHs, 
are paid the Federal prospective per discharge rate under the IRF 
PPS and the LTCH PPS, respectively, and the psychiatric hospitals 
and units are paid the Federal per diem amount under the IPF PPS. As 
stated previously, IRFs and IPFs are not affected by the rate 
updates discussed in this final rule. The impacts of the changes on 
LTCHs are discussed in section I.J. of this Appendix.
    For the children's hospitals, cancer hospitals, short-term acute 
care hospitals located in the Virgin Islands, Guam, the Northern 
Mariana Islands, and American Samoa, the extended neoplastic disease 
care hospital, and RNHCIs, the update of the rate-of-increase limit 
(or target amount) is the estimated FY 2023 percentage increase in 
the 2018-based IPPS operating market basket, consistent with section 
1886(b)(3)(B)(ii) of the Act, and Sec. Sec.  403.752(a) and 413.40 
of the regulations. Consistent with current law, based on IGI's 
second quarter 2022 forecast of the 2018-based IPPS market basket 
increase, we are estimating the FY 2023 update to be 4.1 percent 
(that is, the estimate of the market basket rate-of-increase), as 
discussed in section V.A. of the preamble of this final rule. 
However, the Affordable Care Act requires a productivity adjustment 
(0.3 percentage point reduction for FY 2023), resulting in a 3.8 
percent applicable percentage increase for IPPS hospitals that 
submit quality data and are meaningful EHR users, as discussed in 
section V.A. of the preamble of this rule. Children's hospitals, 
cancer hospitals, short term acute care hospitals located in the 
Virgin Islands, Guam, the Northern Mariana Islands, and American 
Samoa, the extended neoplastic disease care hospital, and RNHCIs 
that continue to be paid based on reasonable costs subject to rate-
of-increase limits under Sec.  413.40 of the regulations are not 
subject to the reductions in the applicable percentage increase 
required under the Affordable Care Act. Therefore, for those 
hospitals paid under Sec.  413.40 of the regulations, the update is 
the percentage increase in the 2018-based IPPS operating market 
basket for FY 2023, estimated at 4.1 percent.
    The impact of the update in the rate-of-increase limit on those 
excluded hospitals depends on the cumulative cost increases 
experienced by each excluded hospital since its applicable base 
period. For excluded hospitals that have maintained their cost 
increases at a level below the rate-of-increase limits since their 
base period, the major effect is on the level of incentive payments 
these excluded hospitals receive. Conversely, for excluded hospitals 
with cost increases above the cumulative update in their rate-of-
increase limits, the major effect is the amount of excess costs that 
would not be paid.
    We note that, under Sec.  413.40(d)(3), an excluded hospital 
that continues to be paid under the TEFRA system and whose costs 
exceed 110 percent of its rate-of-increase limit receives its rate-
of-increase limit plus the lesser of: (1) 50 percent of its 
reasonable costs in excess of 110 percent of the limit; or (2) 10 
percent of its limit. In addition, under the various provisions set 
forth in Sec.  413.40, hospitals can obtain payment adjustments for 
justifiable increases in operating costs that exceed the limit.

[[Page 49459]]

G. Quantitative Effects of the Policy Changes Under the IPPS for 
Operating Costs

1. Basis and Methodology of Estimates

    In this final rule, we are announcing policy changes and payment 
rate updates for the IPPS for FY 2023 for operating costs of acute 
care hospitals. The FY 2023 updates to the capital payments to acute 
care hospitals are discussed in section I.I. of this Appendix.
    Based on the overall percentage change in payments per case 
estimated using our payment simulation model, we estimate that total 
FY 2023 operating payments will increase by 2.6 percent, compared to 
FY 2022. In addition to the applicable percentage increase, this 
amount reflects the +0.5 percentage point permanent adjustment to 
the standardized amount required under section 414 of MACRA. The 
impacts do not reflect changes in the number of hospital admissions 
or real case-mix intensity, which would also affect overall payment 
changes.
    We have prepared separate impact analyses of the changes to each 
system. This section deals with the changes to the operating 
inpatient prospective payment system for acute care hospitals. Our 
payment simulation model relies on the best available claims data to 
enable us to estimate the impacts on payments per case of certain 
changes in this final rule. As discussed in section I.F of this 
final rule, we believe that the FY 2021 claims data is the best 
available data for purposes of the FY 2023 ratesetting and this 
impact analysis reflects the use of that data. However, there are 
other changes for which we do not have data available that would 
allow us to estimate the payment impacts using this model. For those 
changes, we have attempted to predict the payment impacts based upon 
our experience and other more limited data.
    The data used in developing the quantitative analyses of changes 
in payments per case presented in this section are taken from the FY 
2021 MedPAR file, as discussed previously in this final rule, and 
the most current Provider-Specific File (PSF) that is used for 
payment purposes. Although the analyses of the changes to the 
operating PPS do not incorporate cost data, data from the best 
available hospital cost reports were used to categorize hospitals, 
as also discussed previously in this final rule. Our analysis has 
several qualifications. First, in this analysis, we do not adjust 
for future changes in such variables as admissions, lengths of stay, 
or underlying growth in real case-mix. Second, due to the 
interdependent nature of the IPPS payment components, it is very 
difficult to precisely quantify the impact associated with each 
change. Third, we use various data sources to categorize hospitals 
in the tables. In some cases, particularly the number of beds, there 
is a fair degree of variation in the data from the different 
sources. We have attempted to construct these variables with the 
best available source overall. However, for individual hospitals, 
some miscategorizations are possible.
    Using cases from the FY 2021 MedPAR file, we simulate payments 
under the operating IPPS given various combinations of payment 
parameters. As described previously, Indian Health Service hospitals 
and hospitals in Maryland were excluded from the simulations. The 
impact of payments under the capital IPPS, and the impact of 
payments for costs other than inpatient operating costs, are not 
analyzed in this section. Estimated payment impacts of the capital 
IPPS for FY 2023 are discussed in section I.I. of this Appendix.
    We discuss the following changes:
     The effects of the application of the applicable 
percentage increase of 3.8 percent (that is, a 4.1 percent market 
basket update with a reduction of 0.3 percentage point for the 
productivity adjustment), and a 0.5 percentage point adjustment 
required under section 414 of the MACRA to the IPPS standardized 
amount, and the applicable percentage increase (including the market 
basket update and the productivity adjustment) to the hospital-
specific rates.
     The effects of the changes to the relative weights and 
MS-DRG GROUPER.
     The effects of the changes in hospitals' wage index 
values reflecting updated wage data from hospitals' cost reporting 
periods beginning during FY 2019, compared to the FY 2018 wage data, 
to calculate the FY 2023 wage index.
     The effects of the geographic reclassifications by the 
MGCRB (as of publication of this final rule) that will be effective 
for FY 2023.
     The effects of the rural floor with the application of 
the national budget neutrality factor to the wage index.
     The effects of the imputed floor wage index adjustment. 
This provision is not budget neutral.
     The effects of the frontier State wage index adjustment 
under the statutory provision that requires hospitals located in 
States that qualify as frontier States to not have a wage index less 
than 1.0. This provision is not budget neutral.
     The effects of the implementation of section 
1886(d)(13) of the Act, as added by section 505 of Public Law 108-
173, which provides for an increase in a hospital's wage index if a 
threshold percentage of residents of the county where the hospital 
is located commute to work at hospitals in counties with higher wage 
indexes for FY 2023. This provision is not budget neutral.
     The effects of the expiration of the special payment 
status for MDHs at the end of FY 2022 under current law as a result 
of which MDHs that currently receive the higher of payments made 
based on the Federal rate or the payments made based on the Federal 
rate plus 75 percent of the difference between payments based on the 
Federal rate and the hospital-specific rate will be paid based on 
the Federal rate starting in FY 2023.
     The total estimated change in payments based on the FY 
2023 policies relative to payments based on FY 2022 policies.
    To illustrate the impact of the FY 2023 changes, our analysis 
begins with a FY 2022 baseline simulation model using: the FY 2022 
applicable percentage increase of 2.0 percent; the 0.5 percentage 
point adjustment required under section 414 of the MACRA applied to 
the IPPS standardized amount; the FY 2022 MS-DRG GROUPER (Version 
39); the FY 2022 CBSA designations for hospitals based on the OMB 
definitions from the 2010 Census; the FY 2022 wage index; and no 
MGCRB reclassifications. Outlier payments are set at 5.1 percent of 
total operating MS-DRG and outlier payments for modeling purposes.
    Section 1886(b)(3)(B)(viii) of the Act, as added by section 
5001(a) of Public Law 109-171, as amended by section 4102(b)(1)(A) 
of the ARRA (Pub. L. 111-5) and by section 3401(a)(2) of the 
Affordable Care Act (Pub. L. 111-148), provides that, for FY 2007 
and each subsequent year through FY 2014, the update factor will 
include a reduction of 2.0 percentage points for any subsection (d) 
hospital that does not submit data on measures in a form and manner, 
and at a time specified by the Secretary. Beginning in FY 2015, the 
reduction is one-quarter of such applicable percentage increase 
determined without regard to section 1886(b)(3)(B)(ix), (xi), or 
(xii) of the Act, or one-quarter of the market basket update. 
Therefore, hospitals that do not submit quality information under 
rules established by the Secretary and that are meaningful EHR users 
under section 1886(b)(3)(B)(ix) of the Act would receive an 
applicable percentage increase of 2.775 percent. At the time this 
impact was prepared, 24 hospitals are estimated to not receive the 
full market basket rate-of-increase for FY 2023 because they failed 
the quality data submission process or did not choose to 
participate, but are meaningful EHR users. For purposes of the 
simulations shown later in this section, we modeled the payment 
changes for FY 2023 using a reduced update for these hospitals.
    For FY 2023, in accordance with section 1886(b)(3)(B)(ix) of the 
Act, a hospital that has been identified as not a meaningful EHR 
user will be subject to a reduction of three-quarters of such 
applicable percentage increase determined without regard to section 
1886(b)(3)(B)(ix), (xi), or (xii) of the Act. Therefore, hospitals 
that are identified as not meaningful EHR users and do submit 
quality information under section 1886(b)(3)(B)(viii) of the Act 
would receive an applicable percentage increase of 0.725 percent. At 
the time this impact analysis was prepared, 158 hospitals are 
estimated to not receive the full market basket rate-of-increase for 
FY 2023 because they are identified as not meaningful EHR users that 
do submit quality information under section 1886(b)(3)(B)(viii) of 
the Act. For purposes of the simulations shown in this section, we 
modeled the payment changes for FY 2023 using a reduced update for 
these hospitals.
    Hospitals that are identified as not meaningful EHR users under 
section 1886(b)(3)(B)(ix) of the Act and also do not submit quality 
data under section 1886(b)(3)(B)(viii) of the Act would receive an 
applicable percentage increase of -0.3 percent, which reflects a 
one-quarter reduction of the market basket update for failure to 
submit quality data and a three-quarter reduction of the market 
basket update for being identified as not a meaningful EHR user. At 
the time this impact was prepared, 20 hospitals are estimated to not 
receive the full market basket rate-of-increase for FY 2023 because 
they are identified as not meaningful EHR users that do not submit 
quality data under section 1886(b)(3)(B)(viii) of the Act.

[[Page 49460]]

    Each policy change, statutory or otherwise, is then added 
incrementally to this baseline, finally arriving at an FY 2023 model 
incorporating all of the changes. This simulation allows us to 
isolate the effects of each change.
    Our comparison illustrates the percent change in payments per 
case from FY 2022 to FY 2023. Two factors not discussed separately 
have significant impacts here. The first factor is the update to the 
standardized amount. In accordance with section 1886(b)(3)(B)(i) of 
the Act, we are updating the standardized amounts for FY 2023 using 
an applicable percentage increase of 3.8 percent. This includes the 
FY 2023 forecasted IPPS operating hospital market basket increase of 
4.1 percent with a 0.3 percentage point reduction for the 
productivity adjustment. Hospitals that fail to comply with the 
quality data submission requirements and are meaningful EHR users 
will receive a update of 2.775 percent. This update includes a 
reduction of one-quarter of the market basket update for failure to 
submit these data. Hospitals that do comply with the quality data 
submission requirements but are not meaningful EHR users will 
receive an update of 0.725 percent, which includes a reduction of 
three-quarters of the market basket update. Furthermore, hospitals 
that do not comply with the quality data submission requirements and 
also are not meaningful EHR users would receive an update of -0.3 
percent. Under section 1886(b)(3)(B)(iv) of the Act, the update to 
the hospital-specific amounts for SCHs is also equal to the 
applicable percentage increase, or 3.8 percent, if the hospital 
submits quality data and is a meaningful EHR user.
    A second significant factor that affects the changes in 
hospitals' payments per case from FY 2022 to FY 2023 is the change 
in hospitals' geographic reclassification status from one year to 
the next. That is, payments may be reduced for hospitals 
reclassified in FY 2022 that are no longer reclassified in FY 2023. 
Conversely, payments may increase for hospitals not reclassified in 
FY 2022 that are reclassified in FY 2023.

2. Analysis of Table I

    Table I displays the results of our analysis of the changes for 
FY 2023. The table categorizes hospitals by various geographic and 
special payment consideration groups to illustrate the varying 
impacts on different types of hospitals. The top row of the table 
shows the overall impact on the 3,142 acute care hospitals included 
in the analysis.
    The next two rows of Table I contain hospitals categorized 
according to their geographic location: urban and rural. There are 
2,420 hospitals located in urban areas and 722 hospitals in rural 
areas included in our analysis. The next two groupings are by bed-
size categories, shown separately for urban and rural hospitals. The 
last groupings by geographic location are by census divisions, also 
shown separately for urban and rural hospitals.
    The second part of Table I shows hospital groups based on 
hospitals' FY 2023 payment classifications, including any 
reclassifications under section 1886(d)(10) of the Act. For example, 
the rows labeled urban and rural show that the numbers of hospitals 
paid based on these categorizations after consideration of 
geographic reclassifications (including reclassifications under 
sections 1886(d)(8)(B) and 1886(d)(8)(E) of the Act that have 
implications for capital payments) are 1,861, and 1,281, 
respectively.
    The next three groupings examine the impacts of the changes on 
hospitals grouped by whether or not they have GME residency programs 
(teaching hospitals that receive an IME adjustment) or receive 
Medicare DSH payments, or some combination of these two adjustments. 
There are 1,939 nonteaching hospitals in our analysis, 929 teaching 
hospitals with fewer than 100 residents, and 274 teaching hospitals 
with 100 or more residents.
    In the DSH categories, hospitals are grouped according to their 
DSH payment status, and whether they are considered urban or rural 
for DSH purposes. The next category groups together hospitals 
considered urban or rural, in terms of whether they receive the IME 
adjustment, the DSH adjustment, both, or neither.
    The next six rows examine the impacts of the changes on rural 
hospitals by special payment groups (SCHs and RRCs) and 
reclassification status from urban to rural in accordance with 
section 1886(d)(8)(E) of the Act. Of the hospitals that are not 
reclassified from urban to rural, there are 148 RRCs, 256 SCHs, and 
122 hospitals that are both SCHs and RRCs. Of the hospitals that are 
reclassified from urban to rural, there are 470 RRCs, 47 SCHs, and 
39 hospitals that are both SCHs and RRCs.
    The next series of groupings are based on the type of ownership 
and the hospital's Medicare and Medicaid utilization expressed as a 
percent of total inpatient days. These data were taken from the most 
recent available Medicare cost reports.
    The next grouping is based on hospitals' reporting of diagnosis 
codes describing patients experiencing homelessness. This row 
reflects hospitals whose claims indicate that at least 5 percent of 
their IPPS cases involve these patients based on the reporting of 
ICD-10-CM diagnosis code Z59.0 (Homelessness). We note that 
hospitals are not required to identify these patients on their 
claims, and reporting this information on the claim does not 
currently impact Medicare payment. There may be other hospitals with 
at least 5 percent of their IPPS cases involving these patients, 
however we are unable to identify these hospitals. We refer the 
reader to Section II.D.13.d. of this FY 2023 IPPS/LTCH PPS final 
rule for discussion of the comments we received in response to our 
request for information on the reporting of social determinants of 
health diagnosis codes, such as diagnosis code Z59.0 (Homelessness), 
in the FY 2023 IPPS/LTCH PPS proposed rule (87 FR 28177).
    The next grouping concerns the geographic reclassification 
status of hospitals. The first subgrouping is based on whether a 
hospital is reclassified or not. The second and third subgroupings 
are based on whether urban and rural hospitals were reclassified by 
the MGCRB for FY 2023 or not, respectively. The fourth subgrouping 
displays hospitals that reclassified from urban to rural in 
accordance with section 1886(d)(8)(E) of the Act. The fifth 
subgrouping displays hospitals deemed urban in accordance with 
section 1886(d)(8)(B) of the Act.

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a. Effects of the Hospital Update and Other Adjustments (Column 1)

    As discussed in section V.A. of the preamble of this final rule, 
this column includes the hospital update, including the 4.1 percent 
market basket update reduced by the 0.3 percentage point for the 
productivity adjustment. In addition, as discussed in section II.D. 
of the preamble of this final rule, this column includes the FY 2023 
+0.5 percentage point adjustment required under section 414 of the 
MACRA. As a result, we are making a 4.3 percent update to the 
national standardized amount. This column also includes the update 
to the hospital-specific rates which includes the 4.1 percent market 
basket update reduced by the 0.3 percentage point for the 
productivity adjustment. As a result, we are making a 3.8 percent 
update to the hospital-specific rates.
    Overall, hospitals will experience a 4.2 percent increase in 
payments primarily due to the combined effects of the hospital 
update to the national standardized amount and the hospital update 
to the hospital-specific rate. Hospitals that are paid under the 
hospital-specific rate will experience a 3.8 percent increase in 
payments; therefore, hospital categories containing hospitals paid 
under the hospital-specific rate will experience a lower than 
average increase in payments.

b. Effects of the Changes to the MS-DRG Reclassifications and Relative 
Cost-Based Weights With Recalibration Budget Neutrality (Column 2)

    Column 2 shows the effects of the changes to the MS-DRGs and 
relative weights with the application of the recalibration budget 
neutrality factor to the standardized amounts. Section 
1886(d)(4)(C)(i) of the Act requires us annually to make appropriate 
classification changes in order to reflect changes in treatment 
patterns, technology, and any other factors that may change the 
relative use of hospital resources. Consistent with section 
1886(d)(4)(C)(iii) of the Act, we calculated a recalibration budget 
neutrality factor to account for the changes in MS-DRGs and relative 
weights to ensure that the overall payment impact is budget neutral. 
As discussed in section VIII.B.3.b. of the preamble of this final 
rule, we are also establishing a permanent 10-percent cap on the 
reduction in a MS-DRG's relative weight in a given year and an 
associated recalibration cap budget neutrality factor to account for 
the 10-percent cap on relative weight reductions to ensure that the 
overall payment impact is budget neutral.
    As discussed in section II.E. of the preamble of this final 
rule, the FY 2023 MS-DRG relative weights will be 100 percent cost-
based and 100 percent MS-DRGs. For FY 2023, we are calculating the 
MS-DRGs using the FY 2021 MedPAR data grouped to the Version 40 (FY 
2023) MS-DRGs. The reclassification changes to the GROUPER are 
described in more detail in section II.D. of the preamble of this 
final rule.
    The ``All Hospitals'' line in Column 2 indicates that changes 
due to the MS-DRGs and relative weights will result in a 0.0 percent 
change in payments with the application of the recalibration budget 
neutrality factor of 1.000509 and the recalibration cap budget 
neutrality factor of 0.999764 to the standardized amount.

c. Effects of the Wage Index Changes (Column 3)

    Column 3 shows the impact of the updated wage data, with the 
application of the wage budget neutrality factor. The wage index is 
calculated and assigned to hospitals on the basis of the labor 
market area in which the hospital is located. Under section 
1886(d)(3)(E) of the Act, beginning with FY 2005, we delineate 
hospital labor market areas based on the Core Based Statistical 
Areas (CBSAs) established by OMB. The current statistical standards 
used in FY 2023 are based on OMB standards published on February 28, 
2013 (75 FR 37246 and 37252), and 2010 Decennial Census data (OMB 
Bulletin No. 13-01), as updated in OMB Bulletin Nos. 15-01, 17-01, 
18-04, and 20-01. (We refer readers to the FY 2015 IPPS/LTCH PPS 
final rule (79 FR 49951 through 49963) for a full discussion on our 
adoption of the OMB labor market area delineations, based on the 
2010 Decennial Census data, effective beginning with the FY 2015 
IPPS wage index; to the FY 2017 IPPS/LTCH PPS final rule (81 FR 
56913) for a discussion of our adoption of the CBSA updates in OMB 
Bulletin No. 15-01, which were effective beginning with the FY 2017 
wage index; to the FY 2020 IPPS/LTCH PPS final rule (83 FR 41362) 
for a discussion of our adoption of the CBSA update in OMB Bulletin 
No. 17-01 for the FY 2020 wage index; to the FY 2021 IPPS/LTCH PPS 
final rule (85 FR 58743 through 58755) for a discussion of our 
adoption of the CBSA update in OMB Bulletin No. 18-04 for the FY 
2021 wage index; and to the FY 2022 IPPS/LTCH PPS final rule (86 FR 
45163) for a discussion of our adoption of the CBSA update in OMB 
Bulletin No. 20-01 for the FY 2022 wage index.)
    Section 1886(d)(3)(E) of the Act requires that, beginning 
October 1, 1993, we annually update the wage data used to calculate 
the wage index. In accordance with this requirement, the wage index 
for acute care hospitals for FY 2023 is based on data submitted for 
hospital cost reporting periods, beginning on or after October 1, 
2018 and before October 1, 2019. The estimated impact of the updated 
wage data and the OMB labor market area delineations on hospital 
payments is isolated in Column 3 by holding the other payment 
parameters constant in this simulation. That is, Column 3 shows the 
percentage change in payments when going from a model using the FY 
2022 wage index, the labor-related share of 67.6 percent, under the 
OMB delineations and having a 100-percent occupational mix 
adjustment applied, to a model using the FY 2023 pre-
reclassification wage index with the labor-related share of 67.6 
percent, under the OMB delineations, also having a 100-percent 
occupational mix adjustment applied, while holding other payment 
parameters, such as use of the Version 40 MS-DRG GROUPER constant. 
The FY 2023 occupational mix adjustment is based on the CY 2019 
occupational mix survey.
    In addition, the column shows the impact of the application of 
the wage budget neutrality to the national standardized amount. In 
FY 2010, we began calculating separate wage budget neutrality and 
recalibration budget neutrality factors, in accordance with section 
1886(d)(3)(E) of the Act, which specifies that budget neutrality to 
account for wage index changes or updates made under that 
subparagraph must be made without regard to the 62 percent labor-
related share guaranteed under section 1886(d)(3)(E)(ii) of the Act. 
Therefore, for FY 2023, as proposed, we are calculating the wage 
budget neutrality factor to ensure that payments under updated wage 
data and the labor-related share of 67.6 percent are budget neutral, 
without regard to the lower labor-related share of 62 percent 
applied to hospitals with a wage index less than or equal to 1.0. In 
other words, the wage budget neutrality is calculated under the 
assumption that all hospitals receive the higher labor-related share 
of the standardized amount. The FY 2023 wage budget neutrality 
factor is 1.000968 and the overall payment change is 0 percent.
    Column 3 shows the impacts of updating the wage data. Overall, 
the new wage data and the labor-related share, combined with the 
wage budget neutrality adjustment, will lead to no change for all 
hospitals, as shown in Column 3.
    In looking at the wage data itself, the national average hourly 
wage will increase 2.7 percent compared to FY 2022. Therefore, the 
only manner in which to maintain or exceed the previous year's wage 
index was to match or exceed the 2.7 percent increase in the 
national average hourly wage. Of the 3,117 hospitals with wage data 
for both FYs 2022 and 2023, 1,427 or 45.8 percent will experience an 
average hourly wage increase of 2.7 percent or more.
    The following table compares the shifts in wage index values for 
hospitals due to changes in the average hourly wage data for FY 2023 
relative to FY 2022. These figures reflect changes in the ``pre-
reclassified, occupational mix-adjusted wage index,'' that is, the 
wage index before the application of geographic reclassification, 
the rural floor, the out-migration adjustment, and other wage index 
exceptions and adjustments. We note that the ``post-reclassified 
wage index'' or ``payment wage index,'' which is the wage index that 
includes all such exceptions and adjustments (as reflected in Tables 
2 and 3 associated with this final rule) is used to adjust the 
labor-related share of a hospital's standardized amount, either 67.6 
percent or 62 percent, depending upon whether a hospital's wage 
index is greater than 1.0 or less than or equal to 1.0. Therefore, 
the pre-reclassified wage index figures in the following table may 
illustrate a somewhat larger or smaller change than will occur in a 
hospital's payment wage index and total payment.
    The following table shows the projected impact of changes in the 
area wage index values for urban and rural hospitals.

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d. Effects of MGCRB Reclassifications (Column 4)

    Our impact analysis to this point has assumed acute care 
hospitals are paid on the basis of their actual geographic location 
(with the exception of ongoing policies that provide that certain 
hospitals receive payments on bases other than where they are 
geographically located). The changes in Column 4 reflect the per 
case payment impact of moving from this baseline to a simulation 
incorporating the MGCRB decisions for FY 2023.
    By spring of each year, the MGCRB makes reclassification 
determinations that will be effective for the next fiscal year, 
which begins on October 1. The MGCRB may approve a hospital's 
reclassification request for the purpose of using another area's 
wage index value. Hospitals may appeal denials by the MGCRB of 
reclassification requests to the CMS Administrator. Further, 
hospitals have 45 days from the date the IPPS proposed rule is 
issued in the Federal Register to decide whether to withdraw or 
terminate an approved geographic reclassification for the following 
year (we refer readers to the discussion of our clarification of 
this policy in section III.I.2. of the preamble of this final rule.)
    The overall effect of geographic reclassification is required by 
section 1886(d)(8)(D) of the Act to be budget neutral. Therefore, 
for purposes of this impact analysis, as proposed, we are applying 
an adjustment of 0.984399 to ensure that the effects of the 
reclassifications under sections 1886(d)(8)(B) and (C) and 
1886(d)(10) of the Act are budget neutral (section II.A. of the 
Addendum to this final rule).
    Geographic reclassification generally benefits hospitals in 
rural areas. We estimate that the geographic reclassification will 
increase payments to rural hospitals by an average of 1.0 percent. 
By region, most rural hospital categories will experience increases 
in payments due to MGCRB reclassifications.
    Table 2 listed in section VI. of the Addendum to this final rule 
and available via the internet on the CMS website reflects the 
reclassifications for FY 2023.

e. Effects of the Rural Floor, Including Application of National Budget 
Neutrality (Column 5)

    As discussed in section III.B. of the preamble of the FY 2009 
IPPS final rule, the FY 2010 IPPS/RY 2010 LTCH PPS final rule, the 
FYs 2011 through 2022 IPPS/LTCH PPS final rules, and this FY 2023 
IPPS/LTCH PPS final rule, section 4410 of Public Law 105-33 
established the rural floor by requiring that the wage index for a 
hospital in any urban area cannot be less than the wage index 
applicable to hospitals located in rural areas in the same state. We 
apply a uniform budget neutrality adjustment to the wage index. 
Column 5 shows the effects of the rural floor.
    The Affordable Care Act requires that we apply one rural floor 
budget neutrality factor to the wage index nationally. We have 
calculated an FY 2023 rural floor budget neutrality factor to be 
applied to the wage index of 0.991909, which would reduce wage 
indexes by 0.8 percent.
    Column 5 shows the projected impact of the rural floor with the 
national rural floor budget neutrality factor applied to the wage 
index based on the OMB labor market area delineations. The column 
compares the post-reclassification FY 2023 wage index of providers 
before the rural floor adjustment and the post-reclassification FY 
2023 wage index of providers with the rural floor adjustment based 
on the OMB labor market area delineations. Only urban hospitals can 
benefit from the rural floor. Because the provision is budget 
neutral, all other hospitals that do not receive an increase to 
their wage index from the rural floor adjustment (that is, all rural 
hospitals and those urban hospitals to which the adjustment is not 
made) would experience a decrease in payments due to the budget 
neutrality adjustment that is applied to the wage index nationally. 
(As discussed in section III.G.1. of the preamble of this final 
rule, based on the district court's decision in Citrus, we 
calculated the rural floor for FY 2023 including the wage data of 
hospitals that have reclassified as rural under Sec.  412.103.)
    We estimate that 275 hospitals will receive the rural floor in 
FY 2023. All IPPS hospitals in our model will have their wage 
indexes reduced by the rural floor budget neutrality adjustment of 
0.991909. We project that, in aggregate, rural hospitals will 
experience a 0.2 percent decrease in payments as a result of the 
application of the rural floor budget neutrality because the rural 
hospitals do not benefit from the rural floor, but have their wage 
indexes downwardly adjusted to ensure that the application of the 
rural floor is budget neutral overall. We project that, in the 
aggregate, hospitals located in urban areas will experience no 
change in payments because increases in payments to hospitals 
benefitting from the rural floor offset decreases in payments to 
nonrural floor urban hospitals whose wage index is downwardly 
adjusted by the rural floor budget neutrality factor. Urban 
hospitals in the New England region would experience a 3.8 percent 
increase in payments primarily due to the application of the rural 
floor in Massachusetts.

f. Effects of the Application of the Imputed Floor, Frontier State Wage 
Index and Out-Migration Adjustment (Column 6)

    This column shows the combined effects of the application of the 
following: (1) the imputed floor under section 1886(d)(3)(E)(iv)(I) 
and (II) of the Act, which provides that for discharges occurring on 
or after October 1, 2021, the area wage index applicable to any 
hospital in an all-urban State may not be less than the minimum area 
wage index for the fiscal year for hospitals in that State 
established using the methodology described in Sec.  
412.64(h)(4)(vi) as in effect for FY 2018; (2) section 10324(a) of 
the Affordable Care Act, which requires that we establish a minimum 
post-reclassified wage index of 1.00 for all hospitals located in 
``frontier States;'' and (3) the effects of section 1886(d)(13) of 
the Act, as added by section 505 of Public Law 108-173, which 
provides for an increase in the wage index for hospitals located in 
certain counties that have a relatively high percentage of hospital 
employees who reside in the county, but work in a different area 
with a higher wage index.
    These three wage index provisions are not budget neutral and 
will increase payments overall by 0.3 percent compared to the 
provisions not being in effect.
    Section 1886(d)(3)(E)(iv)(III) of the Act provides that the 
imputed floor wage index for all-urban States shall not be applied 
in a budget neutral manner. Therefore, the imputed floor adjustment 
is estimated to increase IPPS operating payments by approximately 
$124 million. There are an estimated 66 providers in Connecticut, 
Delaware, Washington DC, New Jersey, and Rhode Island that will 
receive the imputed floor wage index.
    The term ``frontier States'' is defined in the statute as States 
in which at least 50 percent of counties have a population density 
less than 6 persons per square mile. Based on these criteria, 5 
States (Montana, Nevada, North Dakota, South Dakota, and Wyoming) 
are considered frontier States and an estimated 44 hospitals located 
in Montana, North Dakota, South Dakota, and Wyoming would receive a 
frontier wage index of 1.0000. We note, the rural floor for Nevada 
exceeds the frontier state wage index of 1.000

[[Page 49466]]

and therefore no hospitals in Nevada receive the frontier state wage 
index. Overall, this provision is not budget neutral and is 
estimated to increase IPPS operating payments by approximately $71 
million.
    In addition, section 1886(d)(13) of the Act provides for an 
increase in the wage index for hospitals located in certain counties 
that have a relatively high percentage of hospital employees who 
reside in the county, but work in a different area with a higher 
wage index. Hospitals located in counties that qualify for the 
payment adjustment will receive an increase in the wage index that 
is equal to a weighted average of the difference between the wage 
index of the resident county, post-reclassification and the higher 
wage index work area(s), weighted by the overall percentage of 
workers who are employed in an area with a higher wage index. There 
are an estimated 210 providers that will receive the out-migration 
wage adjustment in FY 2023. This out-migration wage adjustment is 
not budget neutral, and we estimate the impact of these providers 
receiving the out-migration increase will be approximately $53 
million.

g. Effects of the Expiration of MDH Special Payment Status (Column 7)

    Column 7 shows our estimate of the changes in payments due to 
the expiration of MDH status, a nonbudget neutral payment provision. 
Section 50205 of the Bipartisan Budget Act of 2018 (Pub. L. 115-123, 
enacted on February 9, 2018) extended the MDH program (which, under 
previous law, was to be in effect for discharges before October 1, 
2017 only) for discharges occurring on or after October 1, 2017, 
through FY 2022 (that is, for discharges occurring on or before 
September 30, 2022). Therefore, under current law, the MDH program 
will expire at the end of FY 2022. Hospitals that qualified to be 
MDHs receive the higher of payments made based on the Federal rate 
or the payments made based on the Federal rate amount plus 75 
percent of the difference between payments based on the Federal rate 
and payments based on the hospital-specific rate (a hospital-
specific cost-based rate). Because this provision was not budget 
neutral, the expiration of this payment provision results in a 0.2 
percent decrease in payments overall. There are currently 173 MDHs, 
of which we estimate 91 would have been paid under the blended 
payment of the Federal rate and hospital-specific rate if the MDH 
program had not expired. Because those 91 MDHs will no longer 
receive the blended payment and will be paid only under the Federal 
rate in FY 2023, it is estimated that those hospitals would 
experience an overall decrease in payments of approximately $180 
million.

h. Effects of All FY 2022 Changes (Column 8)

    Column 8 shows our estimate of the changes in payments per 
discharge from FY 2022 and FY 2023, resulting from all changes 
reflected in this rule for FY 2023. It includes combined effects of 
the year-to-year change of the previous columns in the table.
    The average increase in payments under the IPPS for all 
hospitals is approximately 2.6 percent for FY 2023 relative to FY 
2022 and for this row is primarily driven by the changes reflected 
in Column 1. Column 8 includes the annual hospital update of 3.8 
percent to the national standardized amount. This annual hospital 
update includes the 4.1 percent market basket update reduced by the 
0.3 percentage point productivity adjustment. As discussed in 
section II.D. of the preamble of this final rule, this column also 
includes the +0.5 percentage point adjustment required under section 
414 of the MACRA. Hospitals paid under the hospital-specific rate 
would receive a 3.8 percent hospital update. As described in Column 
1, the annual hospital update with the +0.5 percent adjustment for 
hospitals paid under the national standardized amount, combined with 
the annual hospital update for hospitals paid under the hospital-
specific rates, combined with the other adjustments described 
previously and shown in Table I, will result in a 2.6 percent 
increase in payments in FY 2023 relative to FY 2022.
    This column also reflects the estimated effect of outlier 
payments returning to their targeted levels in FY 2023 as compared 
to the estimated outlier payments for FY 2022 produced from our 
payment simulation model. As discussed in section II.A.4.j. of the 
Addendum to this final rule, the statute requires that outlier 
payments for any year are projected to be not less than 5 percent 
nor more than 6 percent of total operating DRG payments plus outlier 
payments, and also requires that the average standardized amount be 
reduced by a factor to account for the estimated proportion of total 
DRG payments made to outlier cases. As proposed, we are continuing 
to use a 5.1 percent target (or an outlier offset factor of 0.949) 
in calculating the outlier offset to the standardized amount, just 
as we did for FY 2022. Therefore, our estimate of payments per 
discharge for FY 2023 from our payment simulation model reflects 
this 5.1 percent outlier payment target. Our payment simulation 
model shows that estimated outlier payments for FY 2022 exceed that 
target by approximately 1.7 percent. Therefore, our estimate of the 
changes in payments per discharge from FY 2022 and FY 2023 in Column 
8 reflects the estimated -1.7 percent change in outlier payments 
produced by our payment simulation model when returning to the 5.1 
percent outlier target for FY 2023. There are also interactive 
effects among the various factors comprising the payment system that 
we are not able to isolate, which may contribute to our estimate of 
the changes in payments per discharge from FY 2022 and FY 2023 in 
Column 8.
    Overall payments to hospitals paid under the IPPS due to the 
applicable percentage increase and proposed changes to policies 
related to MS-DRGs, geographic adjustments, and outliers are 
estimated to increase by 2.6 percent for FY 2023. Hospitals in urban 
areas will experience a 2.6 percent increase in payments per 
discharge in FY 2023 compared to FY 2022. Hospital payments per 
discharge in rural areas are estimated to increase by 2.4 percent in 
FY 2023.
    3. Impact Analysis of Table II
    Table II presents the projected impact of the changes for FY 
2023 for urban and rural hospitals and for the different categories 
of hospitals shown in Table I. It compares the estimated average 
payments per discharge for FY 2022 with the estimated average 
payments per discharge for FY 2023, as calculated under our models. 
Therefore, this table presents, in terms of the average dollar 
amounts paid per discharge, the combined effects of the changes 
presented in Table I. The estimated percentage changes shown in the 
last column of Table II equal the estimated percentage changes in 
average payments per discharge from Column 8 of Table I.

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H. Effects of Other Policy Changes

    In addition to those policy changes discussed previously that we 
are able to model using our IPPS payment simulation model, we are 
making various other changes in this final rule. As noted in section 
I.D. of this Appendix A, our payment simulation model uses the most 
recent available claims data to estimate the impacts on payments per 
case of certain changes in this final rule. Generally, we have 
limited or no specific data available with which to estimate the 
impacts of these changes using that payment simulation model. For 
those changes, we have attempted to predict the payment impacts 
based upon our experience and other more limited data. Our estimates 
of the likely impacts associated with these other changes are 
discussed in this section.

1. Effects of Policy Changes Relating to New Medical Service and 
Technology Add-On Payments

a. FY 2023 Status of Technologies Approved for FY 2022 New Technology 
Add-On Payments

    As discussed in section II.F.5.a. of the preamble of this final 
rule, we are continuing new technology add-on payments in FY 2023 
for the 15 technologies that are still within their newness period. 
Under Sec.  412.88(a)(2), the new technology add-on payment for each 
case involving use of an approved technology would be limited to the 
lesser of: (1) 65 percent of the costs of the new technology (or 75 
percent of the costs for technologies designated as Qualified 
Infectious Disease Products (QIDPs) or approved under the Limited 
Population Pathway for Antibacterial and Antifungal Drugs (LPAD) 
pathway); or (2) 65 percent of the amount by which the costs of the 
case exceed the standard MS-DRG payment for the case (or 75 percent 
of the amount for technologies designated as QIDPs or approved under 
the LPAD pathway). Because it is difficult to predict the actual new 
technology add-on payment for each case, the estimated total 
payments in this final rule are based on the applicant's estimated 
cost and volume projections at the time they submitted their 
original application (unless the applicant provided updated figures 
in a public comment) and the assumption that every claim that would 
qualify for a new technology add-on payment would receive the 
maximum add-on payment.
    In the following table, we present estimated total payments for 
the 15 technologies for which we are continuing to make new 
technology add-on payments in FY 2023:

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b. FY 2023 Applications for New Technology Add-On Payments

    In sections II.F.6. and 7. of the preamble to this final rule, 
we discussed 11 technologies for which we received applications for 
new technology add-on payments for FY 2023. We noted that of the 37 
applications (19 alternative and 18 traditional) we received, 23 
applicants withdrew their application (11 alternative and 12 
traditional) prior to the issuance of this final rule, and 3 
technologies (2 alternative and 1 traditional) did not meet the July 
1 deadline for FDA approval or clearance of the technology and were 
therefore ineligible for consideration for new technology add-on 
payments for FY 2023. As explained in the preamble to this final 
rule, add-on payments for new medical services and technologies 
under section 1886(d)(5)(K) of the Act are not required to be budget 
neutral.
    As discussed in section II.F.7. of the preamble of this final 
rule, under the alternative pathway for new technology add-on 
payments, new technologies that are medical products with a QIDP 
designation, approved through the FDA LPAD pathway, or are part of 
the Breakthrough Device program will be considered not substantially 
similar to an existing technology for purposes of the new technology 
add-on payment under the IPPS, and will not need to demonstrate that 
the technology represents a substantial clinical improvement. These 
technologies must still be within the 2-3 year newness period, as 
discussed in II.F.1.a.(1) of this final rule, and must also still 
meet the cost criterion.
    As fully discussed in section II.F.7. of the preamble of this 
final rule, we are approving or conditionally approving 6 
alternative pathway applications for FY 2023 new technology add-on 
payments, including 5 technologies that received a Breakthrough 
Device designation from FDA and 1 that was designated as a QIDP by 
FDA. Based on information from the applicants at the time of the 
final rule, we estimate that total payments for the 6 technologies 
approved under the alternative pathway will be approximately $88.45 
million for FY 2023. Total estimated FY 2023 payments for new 
technologies that are designated as a QIDP are approximately $33.9 
million, and total estimated FY 2023 payments for new technologies 
that are part of the Breakthrough Device program are approximately 
$54.6 million.
    In the following table, we present detailed estimates for the 
six technologies for which we are approving new technology add-on 
payments under the alternative pathway in FY 2023:

[[Page 49470]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.235

    As fully discussed in section II.F.6. of the preamble of this 
final rule, we are approving three technologies that applied under 
the traditional pathway for new technology add-on payments for FY 
2023, and providing new technology add-on payments for one 
application that is substantially similar to a current NTAP-approved 
technology. Based on information from the applicants at the time of 
rulemaking, we estimate that total payments for the four 
technologies for which we are making new technology add-on payments 
is approximately $75.16 million for FY 2023.
    In the following table, we present detailed estimates for the 
four technologies for which we are providing new technology add-on 
payments under the traditional pathway in FY 2023:
[GRAPHIC] [TIFF OMITTED] TR10AU22.236

c. Total Estimated Costs for NTAP in FY 2023

    In the following table, we present summary estimates for all 
technologies approved for new technology add-on payments for FY 
2023:
[GRAPHIC] [TIFF OMITTED] TR10AU22.237

    As discussed in section IV.D. of the preamble of this final 
rule, under section 3133 of the Affordable Care Act, hospitals that 
are eligible to receive Medicare DSH payments will receive 25 
percent of the amount they previously would have received under the 
statutory formula for Medicare DSH payments under section 
1886(d)(5)(F) of the Act. The remainder, equal to an estimate of 75 
percent of what formerly would have been paid as Medicare DSH 
payments (Factor 1), reduced to reflect changes in the percentage of 
uninsured individuals and any additional statutory adjustment 
(Factor 2), is available to make additional payments to each 
hospital that qualifies for Medicare DSH payments and that has 
uncompensated care. Each hospital eligible for Medicare DSH payments 
will receive an additional payment based on its estimated share of 
the total amount of uncompensated care for all hospitals eligible 
for Medicare DSH payments. The uncompensated care payment 
methodology has redistributive effects based on the proportion of a 
hospital's amount of uncompensated care relative to the aggregate 
amount of uncompensated care for all

[[Page 49471]]

hospitals eligible for Medicare DSH payments (Factor 3). The change 
to Medicare DSH payments under section 3133 of the Affordable Care 
Act is not budget neutral.
    In this final rule, we are establishing the amount to be 
distributed as uncompensated care payments to DSH eligible 
hospitals, which for FY 2023 is $6,874,403,459.42. This figure 
represents 75 percent of the amount that otherwise would have been 
paid for Medicare DSH payment adjustments adjusted by a Factor 2 of 
65.71 percent. For FY 2022, the amount available to be distributed 
for uncompensated care was $7,192,008,709.70 or 75 percent of the 
amount that otherwise would have been paid for Medicare DSH payment 
adjustments adjusted by a Factor 2 of 68.57 percent. In addition, 
under the new supplemental payment for Indian Health Service (IHS) 
and Tribal Hospitals and Puerto Rico Hospitals, which we are 
establishing in this final rule, these hospitals will receive 
approximately $96.3 million in supplemental payments, as determined 
based on the difference between each hospital's FY 2022 UCP (reduced 
by negative 4.4 percent, which is the projected change between the 
FY 2023 total uncompensated care payment amount and the total 
uncompensated care payment amount for FY 2022) and its FY 2023 UCP 
as calculated using the methodology adopted in this final rule for 
FY 2023. For this final rule, the total uncompensated care payments 
and supplemental payments equal approximately $6.971 billion. For FY 
2023, we are using 2 years of data on uncompensated care costs from 
Worksheet S-10 of the FY 2018 and 2019 cost reports to calculate 
Factor 3 for all DSH-eligible hospitals, including IHS/Tribal 
hospitals and Puerto Rico hospitals. For a complete discussion of 
the methodology for calculating Factor 3 for FY 2023 and the 
methodology for calculating the new supplemental payments, we refer 
readers to sections IV.D. and IV.E. of the preamble of this final 
rule.
    To estimate the impact of the combined effect of the changes in 
Factors 1 and 2, as well as the changes to the data used in 
determining Factor 3, on the calculation of Medicare uncompensated 
care payments along with the new supplemental payment for Puerto 
Rico hospitals and IHS and Tribal hospitals, which we are 
establishing using our authority under section 1886(d)(5)(I) of the 
Act, we compared total uncompensated care payments estimated in the 
FY 2022 IPPS/LTCH PPS final rule to the combined total of 
uncompensated care payments and supplemental payments estimated in 
this FY 2023 IPPS/LTCH PPS final rule. For FY 2022, we calculated 75 
percent of the estimated amount that would be paid as Medicare DSH 
payments absent section 3133 of the Affordable Care Act, adjusted by 
a Factor 2 of 68.57 percent and multiplied by a Factor 3 calculated 
using the methodology described in the FY 2022 IPPS/LTCH PPS final 
rule. For FY 2023, we calculated 75 percent of the estimated amount 
that would be paid as Medicare DSH payments during FY 2023 absent 
section 3133 of the Affordable Care Act, adjusted by a Factor 2 of 
65.71 percent and multiplied by a Factor 3 calculated using the 
methodology described previously. For the supplemental payments for 
IHS/Tribal hospitals and Puerto Rico hospitals, we calculated the 
difference between the hospital's adjusted base year amount (as 
determined based on the hospital's FY 2022 uncompensated care 
payment) and the hospital's FY 2023 uncompensated care payment.
    Our analysis included 2,368 hospitals that are projected to be 
eligible for DSH in FY 2023. It did not include hospitals that had 
terminated their participation in the Medicare program as of June 3, 
2022, Maryland hospitals, new hospitals, and SCHs that are expected 
to be paid based on their hospital-specific rates. The 26 hospitals 
that are anticipated to be participating in the Rural Community 
Hospital Demonstration Program were excluded from this analysis, as 
participating hospitals are not eligible to receive empirically 
justified Medicare DSH payments and uncompensated care payments. In 
addition, the data from merged or acquired hospitals were combined 
under the surviving hospital's CMS certification number (CCN), and 
the non-surviving CCN was excluded from the analysis. The estimated 
impact of the changes in Factors 1, 2, and 3 on uncompensated care 
payments and of establishing the new supplemental payment for IHS/
Tribal hospitals and Puerto Rico hospitals across all hospitals 
projected to be eligible for DSH payments in FY 2023, by hospital 
characteristic, is presented in the following table:

[[Page 49472]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.238


[[Page 49473]]


[GRAPHIC] [TIFF OMITTED] TR10AU22.239

    The changes in projected FY 2023 uncompensated care payments and 
supplemental payments compared to the total uncompensated care 
payments in FY 2022 are driven by a decrease in Factor 1 and a 
decrease in Factor 2 and the establishment of a new supplemental 
payment for DSH-eligible IHS/Tribal hospitals and Puerto Rico 
hospitals. Factor 1 has decreased from the FY 2022 final rule's 
Factor 1 of $10.489 billion to this final rule's Factor 1 of $10.461 
billion, while the percent change in the percent of individuals who 
are uninsured (Factor 2) has decreased from 68.57 percent to 65.71 
percent. In addition, we note that there is a slight increase in the 
number of projected DSHs to 2,368 at the time of the development for 
this final rule compared to the projected 2,365 DSHs in the FY 2022 
IPPS/LTCH PPS correction notice (86 FR 58034). Based on the changes, 
the impact analysis found that, across all projected DSH eligible 
hospitals, FY 2023 uncompensated care payments and supplemental 
payments are estimated at approximately $6.971 billion, or a 
decrease of approximately 3.08 percent from FY 2022 uncompensated 
care payments (approximately $7.192 billion). While these changes 
will result in a net decrease in the total amount available to be 
distributed in uncompensated care payments and supplemental 
payments, the projected payment decreases vary by hospital type.

[[Page 49474]]

This redistribution of payments is caused by changes in Factor 3 and 
the establishment the new supplemental payment for DSH-eligible IHS/
Tribal hospitals and Puerto Rico hospitals. As seen in the previous 
table, a percent change of less than negative 3.08 percent indicates 
that hospitals within the specified category are projected to 
experience a larger decrease in payments, on average, compared to 
the universe of projected FY 2023 DSH hospitals. Conversely, a 
percent change greater than negative 3.08 percent indicates that a 
hospital type is projected to have a smaller decrease in payments or 
an increase compared to the overall average. The variation in the 
distribution of overall payments by hospital characteristic is 
largely dependent on a given hospital's uncompensated care costs as 
reported on the Worksheet S-10 and used in the Factor 3 computation 
and whether the hospital is eligible to receive the new supplemental 
payment.
    Rural hospitals, in general, are projected to experience larger 
decreases in uncompensated care payments and supplemental payments 
compared to their uncompensated care payments in FY 2022, than their 
urban counterparts. Overall, rural hospitals are projected to 
receive a 6.00 percent decrease in payments, which is a greater 
decrease than the overall hospital average, while urban hospitals 
are projected to receive a 2.90 percent decrease in payments, which 
is a slightly smaller decrease than the overall hospital average.
    By bed size, larger rural hospitals are projected to receive the 
smallest decreases in uncompensated care payments and supplemental 
payments among rural hospitals. Rural hospitals with 250+ beds are 
projected to receive a 4.52 percent payment decrease, and rural 
hospitals with 100-249 beds are projected to receive a 6.81 percent 
decrease. Smaller rural hospitals with 0-99 beds are projected to 
receive a 5.81 percent payment decrease. Among urban hospitals, the 
smallest hospitals, those with 0-99 beds, are projected to receive a 
6.55 percent decrease in payments, which is a greater decrease than 
the overall hospital average. In contrast, urban hospitals with 100-
249 beds and those with 250+ beds are projected to receive decreases 
in payments of 2.57 and 2.80 percent, respectively, which are 
smaller decreases than the overall hospital average.
    By region, rural hospitals are generally expected to receive 
larger than average decreases in uncompensated care payments and 
supplemental payments in most regions. The exceptions are rural 
hospitals in the South Atlantic Region, which are projected to 
receive a smaller than average decrease of 1.81 percent in payments 
and rural hospitals in the East North Central Region and the Pacific 
Region, which are projected to receive payment increases of 8.09 and 
24.45 percent, respectively. Regionally, urban hospitals are 
projected to receive a more varied range of payment changes. Urban 
hospitals in the New England, Middle Atlantic, and South Atlantic 
Regions, as well as hospitals in Puerto Rico, are projected to 
receive larger than average decreases in payments. Urban hospitals 
in the East South Central, West North Central, West South Central, 
and Mountain Regions are projected to receive smaller than average 
decreases in payments. Urban hospitals in the East North Central and 
Pacific Regions are projected to receive increases in average 
payments of 1.03 percent and 0.52 percent, respectively.
    By payment classification, although hospitals in urban payment 
areas overall are expected to receive a 2.46 percent decrease in 
uncompensated care payments and supplemental payments, hospitals in 
large urban payment areas are expected to see a decrease in payments 
of 1.27 percent, while hospitals in other urban payment areas are 
projected to receive the largest decrease of 4.76 percent. Hospitals 
in rural payment areas are expected to receive a decrease in 
payments of 4.10 percent.
    Nonteaching hospitals are projected to receive a payment 
decrease of 2.82 percent, teaching hospitals with fewer than 100 
residents are projected to receive a decrease of 2.40 percent, and 
teaching hospitals with 100+ residents have a projected payment 
decrease of 3.88 percent. Proprietary and voluntary hospitals are 
projected to receive smaller than average decreases of 2.37 and 1.95 
percent respectively, while government hospitals are expected to 
receive a larger than average payment decrease of 5.65 percent. 
Hospitals with less than 25 percent Medicare utilization and 
hospitals with 50 to 65 percent Medicare utilization are projected 
to receive smaller than average payment decreases of 2.94 and 0.38 
percent, respectively, while hospitals with 25-50 percent and 
hospitals with greater than 65 percent Medicare utilization are 
projected to receive larger than average payment decreases of 3.25 
and 23.82 percent, respectively. All hospitals with less than 50 
percent Medicaid utilization are projected to receive smaller 
decreases in uncompensated care payments and supplemental payments 
than the overall hospital average percent change, while hospitals 
with 50-65 percent Medicaid utilization are projected to receive 
larger than average decreases of 10.49 percent. Hospitals with 
greater than 65 percent Medicaid utilization are projected to 
receive an increase of 6.67 percent.
    The previous impact table reflects the total combined 
uncompensated care payments and supplemental payments modeled for FY 
2023 for IHS/Tribal and Puerto Rico hospitals. In FY 2023, IHS/
Tribal hospitals' and Puerto Rico hospitals' aggregate uncompensated 
care payments are estimated to decrease by approximately $103 
million while the aggregate supplemental payments to these hospitals 
are estimated to be approximately $96 million, a net decrease of 
approximately $7 million. This difference is primarily attributable 
to the change in the estimated amount available for uncompensated 
care payments in FY 2023 and estimated changes in DSH status. We 
refer readers to the discussion of the methodology for calculating 
the new supplemental payments in sections IV.E. of the preamble of 
this final rule. For the estimated impacts on individual IHS/Tribal 
hospitals and Puerto Rico hospitals, we refer readers to the IPPS 
Payment Impact File, which can be found on the FY 2023 IPPS final 
rule home page on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/index.html. We 
note that the amounts for this final rule differ from the proposed 
rule amounts primarily due to updated estimates of the amount 
available for uncompensated care payments for FY 2023.

3. Effects of Changes to Low-Volume Hospital Payment Adjustment Policy

    In section V.C. of the preamble of this final rule, we discuss 
the expiration of the temporary changes to the low-volume hospital 
payment policy originally provided for by the Affordable Care Act 
and extended through FY 2022 by subsequent legislation. Effective 
for FY 2023 and subsequent years, in order to qualify as a low-
volume hospital, a subsection (d) hospital must be more than 25 road 
miles from another subsection (d) hospital and have less than 200 
discharges (that is, less than 200 discharges total, including both 
Medicare and non-Medicare discharges) during the fiscal year. Based 
upon the best available data at this time, we estimate the 
expiration of the temporary changes to the low-volume hospital 
payment policy will decrease aggregate low-volume hospital payments 
by $437 million in FY 2023 as compared to FY 2022. These payment 
estimates were determined based on the estimated payments for the 
632 providers that are expected to no longer qualify under the 
criteria that will apply in FY 2023, and were calculated using the 
same methodology used in developing the quantitative analyses of 
changes in payments per case discussed previously in section I.G. of 
this Appendix A.

4. Effects of Reductions Under the Hospital Readmissions Reduction 
Program for FY 2023

    In section V.H of the preamble of this final rule, we discuss 
our policies for the FY 2023 Hospital Readmissions Reduction 
Program. This program requires a reduction to a hospital's base 
operating MS-DRG payment to account for excess readmissions of 
selected applicable conditions and procedures. The table and 
analysis in this final rule illustrate the estimated financial 
impact of the Hospital Readmissions Reduction Program payment 
adjustment methodology by hospital characteristics. In the proposed 
rule, for the purpose of modeling the estimated FY 2023 payment 
adjustment factors that account for the suppression of the pneumonia 
readmission measure, we used the data from the FY 2022 Hospital 
Readmissions Reduction Program for the five non-suppressed measures 
(acute myocardial infarction--AMI, heart failure--HF, chronic 
obstructive pulmonary disease--COPD, coronary artery bypass graft--
CABG, and total hip arthroplasty/total knee arthroplasty--THA/TKA) 
and the FY 2022 Hospital IPPS Proposed Rule Impact File to analyze 
results by hospital characteristics. In this final rule, we are 
updating the estimated financial impact using the estimated payment 
adjustment factors from the FY 2023 Hospital Readmissions Reduction 
Program and the FY 2023 Hospital IPPS Proposed Rule Impact File to 
analyze results by hospital characteristics.
    Hospitals are sorted into quintiles based on the proportion of 
dual-eligible stays among Medicare fee-for-service (FFS) and managed

[[Page 49475]]

care stays between July 1, 2018 and December 1, 2019 and July 1, 
2020 through June 30, 2021 (that is, the data period used for the FY 
2023 Hospital Readmissions Reduction Program). Hospitals' excess 
readmission ratios (ERRs) are assessed relative to their peer group 
median and a neutrality modifier is applied in the payment 
adjustment factor calculation to maintain budget neutrality. In this 
final rule, we are providing an updated estimate of the financial 
impact using the proportion of dually-eligible beneficiaries, ERRs, 
and aggregate payments for each condition/procedure and all 
discharges for applicable hospitals from the FY 2023 Hospital 
Readmissions Reduction Program applicable period. We note that for 
the FY 2023 applicable period, we will only be assessing data from 
July 1, 2018 through December 1, 2019 and from July 1, 2020 through 
June 30, 2021 due to the COVID-19 public health emergency (PHE) 
nationwide Extraordinary Circumstance Exception (ECE) which excluded 
data from January 1, 2020 through June 30, 2020 from the Hospital 
Readmissions Reduction Program calculations.\1169\
---------------------------------------------------------------------------

    \1169\ Although the FY 2023 performance period is July 1, 2018 
through June 30, 2021, first and second quarter data from CY 2020 is 
excluded from program calculations due to the nationwide ECE that 
was granted in response to the COVID-19 PHE. Taking into 
consideration the 30-day window to identify readmissions, the period 
for calculating MS-DRG payments will be adjusted to July 1, 2018 
through December 1, 2019 and then July 1, 2020 through June 30, 
2021. Taking into consideration the 30-day window to identify 
readmissions, the period for identifying index stays will be 
adjusted to July 1, 2018 through December 1, 2019 and July 1, 2020 
through June 30, 2021.
---------------------------------------------------------------------------

    The results in the table include 2,849 non-Maryland hospitals 
eligible to receive a penalty during the performance period. 
Hospitals are eligible to receive a penalty if they have 25 or more 
eligible discharges for at least one measure between July 1, 2018 
through December 1, 2019 and July 1, 2020 through June 30, 2021. The 
second column in the table indicates the total number of non-
Maryland hospitals with available data for each characteristic that 
have an estimated payment adjustment factor less than 1 (that is, 
penalized hospitals).
    The third column in the table indicates the percentage of 
penalized hospitals among those eligible to receive a penalty by 
hospital characteristic. For example, 74.85 percent of eligible 
hospitals characterized as non-teaching hospitals are expected to be 
penalized. Among teaching hospitals, 86.77 percent of eligible 
hospitals with fewer than 100 residents and 88.06 percent of 
eligible hospitals with 100 or more residents are expected to be 
penalized.
    The fourth column in the table estimates the financial impact on 
hospitals by hospital characteristic. The table shows the share of 
penalties as a percentage of all base operating DRG payments for 
hospitals with each characteristic. This is calculated as the sum of 
penalties for all hospitals with that characteristic over the sum of 
all base operating DRG payments for those hospitals between October 
1, 2020 through September 30, 2021 (FY 2021). For example, the 
penalty as a share of payments for non-teaching hospitals is 0.47 
percent. This means that total penalties for all non-teaching 
hospitals are 0.47 percent of total payments for non-teaching 
hospitals. Measuring the financial impact on hospitals as a 
percentage of total base operating MS-DRG payments accounts for 
differences in the amount of base operating MS-DRG payments for 
hospitals with the characteristic when comparing the financial 
impact of the program on different groups of hospitals.

[[Page 49476]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.240


[[Page 49477]]


[GRAPHIC] [TIFF OMITTED] TR10AU22.241

5. Effects of Changes Under the FY 2023 Hospital Value-Based Purchasing 
(VBP) Program

    In section V.I. of the preamble of this final rule, we discuss 
the Hospital VBP Program under which the Secretary makes value-based 
incentive payments to hospitals based on their performance on 
measures during the performance period with respect to a fiscal 
year. We are finalizing our proposals to suppress the Hospital 
Consumer Assessment of Healthcare Providers and Systems (HCAHPS) 
survey and five Healthcare-Associated Infection (HAI) measures, as 
well as to change the scoring and payment methodologies for the FY 
2023 program year, such that hospitals would receive a value-based 
incentive payment percentage that results in a value-based incentive 
payment amount that is equal to the applicable percentage (2 
percent). Specifically, we are finalizing our proposal such that we 
would calculate the measure rates for all of the measures we have 
selected for the FY 2023 program year, but we would not generate 
achievement or improvement points for any of the measures we are 
finalizing for suppression. Additionally, we are finalizing our 
proposal to not award domain scores for the Person and Community 
Engagement and Safety domains. We are also not awarding hospitals a 
Total Performance Score (TPS), and will instead award hospitals a 
payment incentive multiplier that results in a value-based incentive 
payment amount that is equal to the amount withheld for the fiscal 
year (2 percent). That is, each hospital will receive a 2-percent 
reduction to its base operating DRG payment amount for each FY 2023 
discharge and will then receive a value-based incentive payment 
percentage that will result in a value-based incentive payment 
amount that is equal to the 2 percent withheld. Because we are 
finalizing these proposals, the impact for every hospital under the 
Hospital VBP Program will be a net percentage payment adjustment of 
zero.
    In the FY 2023 IPPS/LTCH PPS proposed rule, we provided the 
estimated impact of the FY 2023 program because those impacts would 
apply if the proposals discussed previously were not finalized. 
However, because we are finalizing the policies as proposed, all 
adjustment factors for all hospitals will reflect a net-neutral 
payment adjustment for hospitals in accordance with the finalized FY 
2023 special scoring policy at Sec.  412.168.

6. Effects of Changes Under the HAC Reduction Program for FY 2023

    In the FY 2023 IPPS/LTCH PPS proposed rule, we presented the 
estimated impact of the FY 2023 Hospital-Acquired Condition (HAC) 
Reduction Program on hospitals by hospital characteristics in the 
following table. The table in this section presents the estimated 
proportion of hospitals in the worst-performing quartile of Total 
HAC Scores by hospital characteristic and includes 3,119 non-
Maryland hospitals that participate in the HAC Reduction Program. 
The first column presents a breakdown of each characteristic and the 
second column indicates the number of hospitals for the respective 
characteristic. The third column in the table indicates the number 
of hospitals for each characteristic that would be in the worst-
performing quartile of Total HAC Scores. The fourth column in the 
table indicates the proportion of hospitals for each characteristic 
that would be in the worst performing quartile of Total HAC Scores.
    In section V.J.2.b.(2). of this FY 2023 IPPS/LTCH PPS final 
rule, we are finalizing our proposal to suppress all six measures 
from the HAC Reduction Program, calculate only measure results for 
the HAI measures for the FY 2023 program, and not calculate measure 
scores or Total HAC Scores. Additionally, we are not finalizing our 
proposal to not calculate measure results for the CMS PSI 90 measure 
and thus will be calculating measure results for purposes of public 
reporting for the FY 2023 program.

[[Page 49478]]

Accordingly, since we are finalizing the measure suppression 
proposal, no hospitals will receive a payment reduction in the FY 
2023 HAC Reduction Program.\1170\ In Table 1, we present the 
estimated impact of the FY 2023 HAC Reduction Program on hospitals 
by hospital characteristic for the finalized proposal in section 
V.J.2.b.(2). whereby FY 2023 HAC Reduction Program measure scores 
and Total HAC scores are not calculated. Therefore, Table 1 
illustrates the number of hospitals participating in the FY 2023 HAC 
Reduction Program by hospital characteristic; however, the remaining 
two columns reflect values of zero because no hospital would be in 
the worst-performing quartile.
---------------------------------------------------------------------------

    \1170\ Based on finalizing our suppression proposals, we 
anticipate reduced savings to the Medicare trust fund that is 
otherwise estimated at approximately $350 million.

---------------------------------------------------------------------------

[[Page 49479]]

[GRAPHIC] [TIFF OMITTED] TR10AU22.242


[[Page 49480]]


[GRAPHIC] [TIFF OMITTED] TR10AU22.243

7. Effects of the Changes to IME and Direct GME Payments

a. Change to Direct GME Calculation in Response to Decision in Milton 
S. Hershey Medical Center et al v. Azar II

    As discussed in section V.F.2. of the preamble of this final 
rule, we are implementing a modified direct GME payment policy for 
all teaching hospitals. Specifically, effective for cost reporting 
periods beginning on or after October 1, 2001, for cost reports that 
are reopenable or open, if the hospital's unweighted number of FTE 
residents exceeds the FTE cap, and the number of weighted FTE 
residents also exceeds that FTE cap, the respective primary care and 
obstetrics and gynecology weighted FTE counts and other weighted FTE 
counts are adjusted to make the total weighted FTE count equal the 
FTE cap. If the number of weighted FTE residents does not exceed 
that FTE cap, then the allowable weighted FTE count for direct GME 
payment is the actual weighted FTE count. We have estimated the 
impact of this change for FY 2023 to be $170 million.

b. Effects of Allowing Medicare GME Affiliation Agreements Within 
Certain Rural Track FTE Limitations

    In section V.F.4. of the preamble of this final rule, we are 
finalizing a policy to allow urban and rural hospitals that 
participate in the same separately accredited 1-2 family medicine 
rural track program and have rural track FTE limitations to enter 
into ``rural track Medicare GME affiliation agreements'' in order to 
share those cap slots, and facilitate the cross-training of 
residents. In addition, the final policy only allows urban and rural 
hospitals to participate in rural track Medicare GME affiliated 
groups if they have rural track FTE limitations in place prior to 
October 1, 2022. Under the final policy, eligible urban and rural 
hospitals may enter into rural track Medicare GME affiliation 
agreements effective with the July 1, 2023, academic year. Because 
no newly funded cap slots will be created, only existing funded cap 
slots would be shared between the participating affiliated 
hospitals, there is no financial impact to this provision.

8. Effects of Implementation of the Rural Community Hospital 
Demonstration Program in FY 2022

    In section V.K. of the preamble of this final rule for FY 2023, 
we discussed our implementation and budget neutrality methodology 
for section 410A of Public Law 108-173, as amended by sections 3123 
and 10313 of Public Law 111-148, by section 15003 of Public Law 114-
255, and most recently, by section 128 of Public Law 116-260, which 
requires the Secretary to conduct a demonstration that would modify 
payments for inpatient services for up to 30 rural hospitals.
    Section 128 of Public Law 116-260 requires the Secretary to 
conduct the Rural Community Hospital Demonstration for a 15-year 
extension period (that is, for an additional 5 years beyond the 
previous extension period). In addition, the statute provides for 
continued participation for all hospitals participating in the 
demonstration program as of December 30, 2019.
    Section 410A(c)(2) of Public Law 108-173 requires that in 
conducting the demonstration program under this section, the 
Secretary shall ensure that the aggregate payments made by the 
Secretary do not exceed the amount which the Secretary would have 
paid if the demonstration program under this section was not 
implemented (budget neutrality). We propose to adopt the general 
methodology used in previous years, whereby we estimated the 
additional payments made by the program for each of the 
participating hospitals as a result of the demonstration, and then 
adjusted the national IPPS rates by an amount sufficient to account 
for the added costs of this demonstration. In other words, we have 
applied budget neutrality across the payment system as a whole 
rather than across the participants of this demonstration. The 
language of the statutory budget neutrality requirement permits the 
agency to implement the budget neutrality provision in this manner. 
The statutory language requires that aggregate payments made by the 
Secretary do not exceed the amount which the Secretary would have 
paid if the demonstration was not implemented, but does not identify 
the range across which aggregate payments must be held equal.
    For this final rule, the resulting amount applicable to FY 2023 
is $72,449,896, which we are including in the budget neutrality 
offset adjustment for FY 2023. This estimated amount is based on the 
specific assumptions regarding the data sources used, that is, 
recently available ``as submitted'' cost reports and historical and 
currently finalized update factors for cost and payment.
    In previous years, we have incorporated a second component into 
the budget neutrality offset amounts identified in the final IPPS 
rules. As finalized cost reports became available, we determined the 
amount by which the actual costs of the demonstration for an 
earlier, given year differed from the estimated costs for the 
demonstration set forth in the final IPPS rule for the corresponding 
fiscal year, and we incorporated that amount into the budget 
neutrality offset amount for the upcoming fiscal year. We have 
calculated this difference for FYs 2005 through 2016 between the 
actual costs of the demonstration as determined from finalized cost 
reports once available, and estimated costs of the demonstration as 
identified in the applicable IPPS final rules for these years.
    With the extension of the demonstration for another 5-year 
period, as authorized by section 128 of Public Law 116-260, we will 
continue this general procedure. At the time of the FY 2023 proposed 
rule, all of the finalized cost reports are available for the 17 
hospitals that completed cost report periods beginning in FY 2017 
under the demonstration payment methodology; these cost reports show 
the actual costs of the demonstration for this fiscal year to be 
$35,989,928. We note that the FY 2017 IPPS final rule included no 
budget neutrality offset amount for that fiscal year. The final rule 
for FY 2017 preceded the re-authorization of the demonstration under 
the Cures Act. Anticipating that the demonstration would end in 
2016, we projected no demonstration cost estimate for the upcoming 
fiscal year, FY 2017, while we stated that we would continue to 
reconcile actual costs when all finalized cost reports for previous 
fiscal years under the demonstration became available

[[Page 49481]]

(81 FR 57037). Thus, keeping with past practice, for this final rule 
we are including the actual costs of the demonstration as determined 
from finalized cost reports for FY 2017 within the budget neutrality 
offset amount for this upcoming fiscal year.
    Therefore, for this FY 2023 IPPS/LTCH PPS final rule, the budget 
neutrality offset amount for FY 2023 is based on the sum of two 
amounts:
     The amount representing the difference applicable to FY 
2023 between the sum of the estimated reasonable cost amounts that 
would be paid under the demonstration for covered inpatient services 
to the 26 hospitals participating in the fiscal year and the sum of 
the estimated amounts that would generally be paid if the 
demonstration had not been implemented. This estimated amount is 
$72,449,896.
     The amount by which the actual costs of the 
demonstration in FY 2017 (as shown by finalized cost reports from 
that fiscal year) differ from the amount determined for FY 2017. 
Since no budget neutrality offset was conducted in FY 2017, the 
amount of this difference is the actual cost amount for FY 2017 
$35,989,928.
    We are thus subtracting the sum of these amounts ($108,439,824) 
from the national IPPS rates for FY 2023.

9. Effects of Continued Implementation of the Frontier Community Health 
Integration Project (FCHIP) Demonstration

    In section VIIB.2. of the preamble of this final rule we discuss 
the implementation of the FCHIP Demonstration, which allows eligible 
entities to develop and test new models for the delivery of health 
care services in eligible counties in order to improve access to and 
better integrate the delivery of acute care, extended care, and 
other health care services to Medicare beneficiaries in no more than 
four States. Section 123 of Public Law 110-275 initially required a 
3-year period of performance. The FCHIP Demonstration began on 
August 1, 2016, and concluded on July 31, 2019 (referred to in this 
section as the ``initial period''). Section 129 of the Consolidated 
Appropriations Act (Pub. L. 116-159) extended the FCHIP 
Demonstration by 5 years (referred to in this section as the 
``extension period'' of the demonstration). The FCHIP Demonstration 
resumed on January 1, 2022 and CAHs participating in the 
demonstration project during the extension period shall begin such 
participation in the cost reporting year that begins on or after 
January 1. Budget neutrality estimates for the demonstration 
described in the preamble of this final rule are based on the 
demonstration extension period.
    As described in the FY 2022 IPPS/LTCH PPS final rule (86 FR 
45323 through 45328), CMS waived certain Medicare rules for CAHs 
participating in the demonstration initial period to allow for 
alternative reasonable cost-based payment methods in the three 
distinct intervention service areas: telehealth services, ambulance 
services, and skilled nursing facility/nursing facility services. 
These waivers were implemented with the goal of increasing access to 
care with no net increase in costs. As we explained in the FY 2022 
IPPS/LTCH PPS final rule (86 FR 45323 through 45328), 10 CAHs were 
selected for participation in the demonstration initial period. 
Section 129 of Public Law 116-159, stipulates that only the 10 CAHs 
that participated in the initial period of the FCHIP Demonstration 
are eligible to participate during the extension period. Among the 
eligible CAHs, six elected to participate in the extension period. 
The selected CAHs are located in two states--Montana and North 
Dakota--and are implementing the three intervention services. In the 
FY 2022 IPPS/LTCH PPS final rule, CMS concluded that the initial 
period of the FCHIP Demonstration had satisfied the budget 
neutrality requirement described in section 123(g)(1)(B) of Public 
Law 110-275. Therefore, CMS did not apply a budget neutrality 
payment offset policy for the initial period of the demonstration. 
In addition, in the FY 2022 IPPS/LTCH PPS final rule (86 FR 45323 
through 45328), we finalized a policy to address the budget 
neutrality requirement for the demonstration initial period. We also 
discussed this policy in the FY 2017 IPPS/LTCH PPS final rule (81 FR 
57064 through 57065), the FY 2018 IPPS/LTCH PPS final rule (82 FR 
38294 through 38296), the FY 2019 IPPS/LTCH PPS final rule (83 FR 
41516 through 41517), the FY 2020 IPPS/LTCH PPS final rule (84 FR 
42427 through 42428) and the FY 2021 IPPS/LTCH PPS final rule (85 FR 
58894 through 58996).
    As explained in the FY 2022 IPPS/LTCH PPS final rule, we based 
our selection of CAHs for participation in the demonstration with 
the goal of maintaining the budget neutrality of the demonstration 
on its own terms meaning that the demonstration would produce 
savings from reduced transfers and admissions to other health care 
providers, offsetting any increase in Medicare payments as a result 
of the demonstration. However, because of the small size of the 
demonstration and uncertainty associated with the projected Medicare 
utilization and costs, the policy we finalized for the demonstration 
initial period of performance in the FY 2022 IPPS/LTCH PPS final 
rule provides a contingency plan to ensure that the budget 
neutrality requirement in section 123 of Public Law 110-275 is met.
    For this final rule, we are adopting the same budget neutrality 
policy contingency plan used during the demonstration initial period 
to ensure that the budget neutrality requirement in section 123 of 
Public Law 110-275 is met during the demonstration extension period. 
If analysis of claims data for Medicare beneficiaries receiving 
services at each of the participating CAHs, as well as from other 
data sources, including cost reports for the participating CAHs, 
shows that increases in Medicare payments under the demonstration 
during the 5-year extension period is not sufficiently offset by 
reductions elsewhere, we will recoup the additional expenditures 
attributable to the demonstration through a reduction in payments to 
all CAHs nationwide.
    Under the policy finalized in the FY 2022 IPPS/LTCH PPS final 
rule, we adopted the policy finalized in the FY 2017 IPPS/LTCH PPS 
final rule, in the event the demonstration initial period was found 
not to have been budget neutral, any excess costs would be recouped 
over a period of 3 cost reporting years. In the FY 2023 IPPS/LTCH 
PPS proposed rule, we sought public comment on the proposal, as we 
proposed to revise an aspect of the policy finalized in the FY 2022 
IPPS/LTCH PPS final rule. Our new proposed policy is in the event 
the demonstration extension period is found not to have been budget 
neutral, any excess costs would be recouped within 1 fiscal year. We 
believe our new proposed policy is a more efficient timeframe for 
the government to conclude the demonstration operational 
requirements (such as analyzing claims data, cost report data and/or 
other data sources) to adjudicate the budget neutrality payment 
recoupment process due to any excess cost that occurred as result of 
the demonstration extension period. As explained in the FY 2022 
IPPS/LTCH PPS final rule (86 FR 45323 through 45328), because of the 
small scale of the demonstration, we indicated that we did not 
believe it would be feasible to implement budget neutrality for the 
demonstration initial period by reducing payments to only the 
participating CAHs. Therefore, in the event that this demonstration 
extension period is found to result in aggregate payments in excess 
of the amount that would have been paid if this demonstration 
extension period were not implemented, our policy is to comply with 
the budget neutrality requirement finalized in the FY 2022 IPPS/LTCH 
PPS final rule, by reducing payments to all CAHs, not just those 
participating in the demonstration extension period. We stated that 
we believe it is appropriate to make any payment reductions across 
all CAHs because the FCHIP Demonstration was specifically designed 
to test innovations that affect delivery of services by the CAH 
provider category. As we explained in the FY 2022 IPPS/LTCH PPS 
final rule, we believe that the language of the statutory budget 
neutrality requirement at section 123(g)(1)(B) of Public Law 110-275 
permits the agency to implement the budget neutrality provision in 
this manner. The statutory language merely refers to ensuring that 
aggregate payments made by the Secretary do not exceed the amount 
which the Secretary estimates would have been paid if the 
demonstration project was not implemented, and does not identify the 
range across which aggregate payments must be held equal.
    As explained in the FY 2022 IPPS/LTCH PPS final rule, we 
finalized a policy to address the demonstration budget neutrality 
methodology and analytical approach for the initial period of the 
demonstration. Therefore, for the proposed rule, we proposed to 
adopt the same budget neutrality methodology and analytical approach 
used during the demonstration initial period to ensure budget 
neutrality for the extension period. While we expect to use the same 
methodology that was used to assess the budget neutrality of the 
FCHIP Demonstration during initial period of the demonstration to 
assess the financial impact of the demonstration during this 
extension period, upon receiving data for the extension period, we 
may update and/or modify the FCHIP budget neutrality methodology and

[[Page 49482]]

analytical approach to ensure that the full impact of the 
demonstration is appropriately captured. Therefore, we did not 
propose to apply a budget neutrality payment offset to payments to 
CAHs in FY 2023. This policy will have no impact for any national 
payment system for FY 2023.

10. Effects of Codification of the Costs Incurred for Qualified and 
Non-Qualified Deferred Compensation Plans

    In section X.A. of the preamble of this final rule, we set forth 
our provisions to codify the costs incurred for qualified and non-
qualified deferred compensation plans. We do not believe that there 
are any costs associated with the codification of this policy.

11. Effects of Condition of Participation (CoP) Requirements for 
Hospitals and CAHs To Continue Reporting Data for COVID-19 and 
Influenza After the PHE Ends as Determined by the Secretary

    Section X.B. of the preamble of this final rule revises the 
hospital and CAH infection prevention and control CoP requirements 
to require hospitals and CAHs, after the conclusion of the current 
COVID-19 PHE, to continue COVID-19 and seasonal influenza related 
reporting. The revisions will continue to apply upon conclusion of 
the COVID-19 PHE and will continue until April 30, 2024, unless the 
Secretary establishes an earlier ending date. Reporting frequency 
and requirements will be communicated to hospitals, stakeholders, 
and the public following a model similar to that which we used to 
inform regulated entities at the beginning of the COVID-19 PHE (see 
QSO-21-03-Hospitals/CAHs at https://www.cms.gov/files/document/qso-21-03-hospitalscahs.pdf-0). As discussed in section XII.B. of the 
preamble of this final rule, Collection of Information Requirements, 
we expect a burden increase of $38,204,400 or approximately $6,162 
per facility annually for weekly reporting. We note that efforts are 
underway to automate hospital and CAH reporting that have the 
potential to significantly decrease reporting burden and improve 
reliability.
    Comment: Commenters noted that the data being collected for 
automating this type of reporting would not generally come from a 
single system, noting that for example, clinical data might come 
from the EHR, bed capacity from a bed management system, PPE from 
inventory systems, and medication and vaccination inventory from 
pharmacy information. These commenters noted that resources will 
vary among facilities and that some might use a combination of 
manual and automated solutions because they may not have (or need) 
all of these different systems. Commenters also emphasized the 
importance of IT staff in the deployment and maintenance of such 
systems. A commenter noted that estimates are available for the 
initial costs for the development of various interfaces, ranging 
from $3,000 to $25,000 depending on complexity and features, however 
did not cite any specific resources. In total, the commenter 
indicated that the cost for the development of the initial software 
to support long-term data collection could be as much as $250,000 
depending on the specific needs of the facility and that maintenance 
costs to support the infrastructure could be between 10 and 25 
percent of the initial software cost, totaling around $300,000 for a 
2-year period. The commenter noted that some of these costs may be 
offset by the ability of the IT staff to repurpose existing 
automated solutions, but noted this may only be feasible in larger 
hospitals with more advanced IT staff and capabilities. Lastly, the 
commenter indicated that many CAHs have a much lower capacity to 
support IT innovation and are unable to fund extensive IT 
departments. Therefore, the costs for this type of innovation are 
likely to be much higher.
    Response: We acknowledge that there are uncertainties in 
planning for future emergencies, and we understand that there are 
lots of incentives and pathways to consider with regard to 
preparedness. These comments are helpful in understanding the 
actions necessary and effort involved in tracking and investing in 
infrastructure to be prepared to timely and accurately report in the 
event of a future PHE declaration. We will consider this feedback as 
we continue to assess the best way to align and incentivize 
preparedness, while also reducing ongoing burden and costs on 
regulated entities, and ensuring flexibility to quickly respond to 
emergencies.

I. Effects of Changes in the Capital IPPS

1. General Considerations

    For the impact analysis presented in this section of the final 
rule, we used data from the March 2022 update of the FY 2021 MedPAR 
file and the March 2022 update of the Provider-Specific File (PSF) 
that was used for payment purposes. Although the analyses of the 
changes to the capital prospective payment system do not incorporate 
cost data, we used the March 2022 update of the most recently 
available hospital cost report data to categorize hospitals. Our 
analysis has several qualifications and uses the best data 
available, as described later in this section of the final rule.
    Due to the interdependent nature of the IPPS, it is very 
difficult to precisely quantify the impact associated with each 
change. In addition, we draw upon various sources for the data used 
to categorize hospitals in the tables. In some cases (for instance, 
the number of beds), there is a fair degree of variation in the data 
from different sources. We have attempted to construct these 
variables with the best available sources overall. However, it is 
possible that some individual hospitals are placed in the wrong 
category.
    Using cases from the March 2022 update of the FY 2021 MedPAR 
file, we simulated payments under the capital IPPS for FY 2022 and 
the payments for FY 2023 for a comparison of total payments per 
case. Short-term, acute care hospitals not paid under the general 
IPPS (for example, hospitals in Maryland) are excluded from the 
simulations.
    The methodology for determining a capital IPPS payment is set 
forth at Sec.  412.312. The basic methodology for calculating the 
capital IPPS payments in FY 2023 is as follows:
    (Standard Federal rate) x (DRG weight) x (GAF) x (COLA for 
hospitals located in Alaska and Hawaii) x (1 + DSH adjustment factor 
+ IME adjustment factor, if applicable).
    In addition to the other adjustments, hospitals may receive 
outlier payments for those cases that qualify under the threshold 
established for each fiscal year. We modeled payments for each 
hospital by multiplying the capital Federal rate by the geographic 
adjustment factor (GAF) and the hospital's case-mix. Then we added 
estimated payments for indirect medical education, disproportionate 
share, and outliers, if applicable. For purposes of this impact 
analysis, the model includes the following assumptions:
     The capital Federal rate was updated, beginning in FY 
1996, by an analytical framework that considers changes in the 
prices associated with capital-related costs and adjustments to 
account for forecast error, changes in the case-mix index, allowable 
changes in intensity, and other factors. As discussed in section 
III.A.1. of the Addendum to this final rule, the update to the 
capital Federal rate is 2.5 percent for FY 2023.
     In addition to the FY 2023 update factor, the FY 2023 
capital Federal rate was calculated based on a GAF/DRG budget 
neutrality adjustment factor of 1.0012, a budget neutrality factor 
for the lowest quartile hospital wage index adjustment and the 5-
percent cap on wage index decreases policy of 0.9972, and a outlier 
adjustment factor of 0.9448.

2. Results

    We used the payment simulation model previously described in 
section I.I. of Appendix A of this final rule to estimate the 
potential impact of the changes for FY 2023 on total capital 
payments per case, using a universe of 3,142 hospitals. As 
previously described, the individual hospital payment parameters are 
taken from the best available data, including the March 2022 update 
of the FY 2021 MedPAR file, the March 2022 update to the PSF, and 
the most recent available cost report data from the March 2022 
update of HCRIS. In Table III, we present a comparison of estimated 
total payments per case for FY 2022 and estimated total payments per 
case for FY 2023 based on the FY 2023 payment policies. Column 2 
shows estimates of payments per case under our model for FY 2022. 
Column 3 shows estimates of payments per case under our model for FY 
2023. Column 4 shows the total percentage change in payments from FY 
2022 to FY 2023. The change represented in Column 4 includes the 
2.50 percent update to the capital Federal rate and other changes in 
the adjustments to the capital Federal rate. The comparisons are 
provided by: (1) geographic location; (2) region; and (3) payment 
classification.
    The simulation results show that, on average, capital payments 
per case in FY 2023 are expected to increase 0.6 percent compared to 
capital payments per case in FY 2022. This expected increase is 
primarily due to the 2.50 percent update to the capital Federal rate 
for FY 2023 being partially offset by an expected decrease in 
capital outlier payments. As discussed in section III.A.2. of the 
Addendum to this final rule, we estimate for FY 2023 that outlier 
payments for capital-

[[Page 49483]]

related PPS payments would equal 5.52 percent of inpatient capital-
related payments. Although in the FY 2022 IPPS/LTCH PPS final rule 
we estimated for FY 2022 that outlier payments for capital-related 
PPS payments would equal 5.29 percent of inpatient capital related 
payments, our payment simulation model for this final rule shows 
that for FY 2022, estimated outlier payments for capital-related PPS 
payments are approximately 7.16 percent of inpatient capital-related 
payments. This difference in our estimate of FY 2022 outlier 
payments compared to our estimate of FY 2023 outlier payments is 
reflected in the average change in capital payments per case in FY 
2023 as compared to FY 2022. Other factors that contribute to the 
expected change in average capital payments per case in FY 2023 as 
compared to FY 2022 include changes in capital DSH payments for 
hospitals that reclassify from urban to rural under Sec.  412.103. 
In general, regional variations in estimated capital payments per 
case in FY 2023 as compared to capital payments per case in FY 2022 
are primarily due to the changes in GAFs, and are generally 
consistent with the projected changes in payments due to changes in 
the wage index (and policies affecting the wage index), as shown in 
Table I in section I.G. of this Appendix A.
    The net impact of these changes is an estimated 0.6 percent 
increase in capital payments per case from FY 2022 to FY 2023 for 
all hospitals (as shown in Table III).
    The geographic comparison shows that, on average, hospitals in 
both urban and rural classifications will experience an increase in 
capital IPPS payments per case in FY 2023 as compared to FY 2022. 
Capital IPPS payments per case will increase by an estimated 0.5 
percent for hospitals in urban areas while payments to hospitals in 
rural areas will increase by 0.4 percent in FY 2022 to FY 2023.
    The comparisons by region show that the change in capital 
payments per case from FY 2022 to FY 2023 for urban areas range from 
a 0.1 percent increase for the New England region to a 1.6 percent 
increase for the Mountain region. Meanwhile, the change in capital 
payments per case from FY 2022 to FY 2023 for rural areas range from 
a 0.7 percent decrease for the Mountain rural region to a 1.2 
percent increase for the East South Central rural region. These 
regional differences are primarily due to the changes in the GAFs 
and estimated changes in outlier and DSH payments.
    The comparison by hospital type of ownership (Voluntary, 
Proprietary, and Government) shows that proprietary hospitals are 
expected to experience the highest increase in capital payments per 
case from FY 2022 to FY 2023 of 0.9 percent. Meanwhile, government 
hospitals and voluntary hospitals are expected to experience an 
increase in capital payments per case from FY 2022 to FY 2023 of 0.6 
percent and 0.5 percent, respectively.
    Section 1886(d)(10) of the Act established the MGCRB. Hospitals 
may apply for reclassification for purposes of the wage index for FY 
2023. Reclassification for wage index purposes also affects the GAFs 
because that factor is constructed from the hospital wage index. To 
present the effects of the hospitals being reclassified as of the 
publication of this final rule for FY 2023, we show the average 
capital payments per case for reclassified hospitals for FY 2023. 
Urban reclassified hospitals are expected to experience an increase 
in capital payments of 0.3 percent; urban nonreclassified hospitals 
are expected to experience an increase in capital payments of 0.7 
percent. The lower expected increase in payments for urban 
reclassified hospitals compared to urban nonreclassified hospitals 
is primarily due to estimated decreases in capital DSH payments to 
urban reclassified hospitals caused by the number of hospitals that 
reclassify from urban to rural under Sec.  412.103. Rural 
reclassified hospitals are expected to experience an increase in 
capital payments of 0.9 percent; rural nonreclassified hospitals are 
expected to experience a decrease in capital payments of 0.3 
percent.

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J. Effects of Payment Rate Changes and Policy Changes Under the 
LTCH PPS

1. Introduction and General Considerations

    In section VII. of the preamble of this final rule and section 
V. of the Addendum to this final rule, we set forth the annual 
update to the payment rates for the LTCH PPS for FY 2023. In the 
preamble of this final rule, we specify the statutory authority for 
the provisions that are presented, identify the policies for FY 
2023, and present rationales for our provisions as well as 
alternatives that were considered. In this section of Appendix A to 
this final rule, we discuss the impact of the changes to the payment 
rate, factors, and other payment rate policies related to the LTCH 
PPS that are presented in the preamble of this final rule in terms 
of their estimated fiscal impact on the Medicare budget and on 
LTCHs.
    There are 339 LTCHs included in this impact analysis. We note 
that, although there are currently approximately 346 LTCHs, for 
purposes of this impact analysis, we

[[Page 49486]]

excluded the data of all-inclusive rate providers consistent with 
the development of the FY 2023 MS-LTC-DRG relative weights 
(discussed in section VII.B.3.c. of the preamble of this final 
rule). Moreover, in the claims data used for this final rule, two of 
these 339 LTCHs only have claims for site neutral payment rate cases 
and, therefore, do not affect our impact analysis for LTCH PPS 
standard Federal payment rate cases.
    In the impact analysis, we used the payment rate, factors, and 
policies presented in this final rule, the 3.8 percent annual update 
to the LTCH PPS standard Federal payment rate, the update to the MS-
LTC-DRG classifications and relative weights, the update to the wage 
index values and labor-related share, and the best available claims 
and CCR data to estimate the change in payments for FY 2023.
    Under the dual rate LTCH PPS payment structure, payment for LTCH 
discharges that meet the criteria for exclusion from the site 
neutral payment rate (that is, LTCH PPS standard Federal payment 
rate cases) is based on the LTCH PPS standard Federal payment rate. 
Consistent with the statute, the site neutral payment rate is the 
lower of the IPPS comparable per diem amount as determined under 
Sec.  412.529(d)(4), including any applicable outlier payments as 
specified in Sec.  412.525(a), reduced by 4.6 percent for FYs 2018 
through 2026; or 100 percent of the estimated cost of the case as 
determined under Sec.  412.529(d)(2). In addition, there are two 
separate high cost outlier targets--one for LTCH PPS standard 
Federal payment rate cases and one for site neutral payment rate 
cases. We note that section 3711(b)(2) of the CARES Act has provided 
a waiver of the application of the site neutral payment rate for 
LTCH cases admitted during the COVID-19 PHE period. At the time of 
development of this final rule, the COVID-19 PHE is still in effect. 
Therefore, all LTCH PPS cases up to this point in FY 2022 have been 
paid the LTCH PPS standard Federal rate regardless of whether the 
discharge met the statutory patient criteria. Since the expiration 
date of the COVID-19 PHE is not yet known, for purposes of this 
impact analysis, estimates of total LTCH PPS payments for site 
neutral payment rate cases in FYs 2022 and 2023 were calculated 
using the site neutral payment rate determined under Sec.  
412.522(c) and the provisions of the CARES Act were not considered.
    Based on the best available data for the 339 LTCHs in our 
database that were considered in the analyses used for this final 
rule, we estimate that overall LTCH PPS payments in FY 2023 will 
increase by approximately 2.4 percent (or approximately $71 million) 
based on the rates and factors presented in section VII. of the 
preamble and section V. of the Addendum to this final rule.
    Based on the FY 2021 LTCH cases that were used for the analysis 
in this final rule, approximately 28 percent of those cases were 
classified as site neutral payment rate cases (that is, 28 percent 
of LTCH cases did not meet the statutory patient-level criteria for 
exclusion from the site neutral payment rate). Our Office of the 
Actuary currently estimates that the percent of LTCH PPS cases that 
will be paid at the site neutral payment rate in FY 2023 will not 
change significantly from the most recent historical data. We 
estimate IPPS comparable per diem amounts using the prior year's 
IPPS rates and factors, updated to reflect estimated changes to the 
IPPS rates and payments finalized for FY 2023. Taking this into 
account along with other changes that will apply to the site neutral 
payment rate cases in FY 2023, we estimate that aggregate LTCH PPS 
payments for these site neutral payment rate cases will increase by 
approximately 2.8 percent (or approximately $9 million). This 
projected increase in payments to LTCH PPS site neutral payment rate 
cases is primarily due to the finalized updates to the IPPS rates 
and payments reflected in our estimate of the IPPS comparable per 
diem amount, as well as an estimated increase in costs for these 
cases determined using the charge and CCR adjustment factors 
described in section V.D.3.b. of the Addendum to this final rule. We 
noted, we estimate payments to site neutral payment rate cases in FY 
2023 will represent approximately 11 percent of estimated aggregate 
FY 2023 LTCH PPS payments.
    Based on the FY 2021 LTCH cases that were used for the analysis 
in this final rule, approximately 72 percent of LTCH cases will meet 
the patient-level criteria for exclusion from the site neutral 
payment rate in FY 2023, and will be paid based on the LTCH PPS 
standard Federal payment rate for the full year. We estimate that 
total LTCH PPS payments for these LTCH PPS standard Federal payment 
rate cases in FY 2023 will increase approximately 2.3 percent (or 
approximately $61 million). This estimated increase in LTCH PPS 
payments for LTCH PPS standard Federal payment rate cases in FY 2023 
is primarily due to the 3.8 percent annual update to the LTCH PPS 
standard Federal payment rate for FY 2023 and the projected 1.2 
percent decrease in high cost outlier payments as a percentage of 
total LTCH PPS standard Federal payment rate payments, which is 
discussed later in this section of the final rule.
    Based on the 339 LTCHs that were represented in the FY 2021 LTCH 
cases that were used for the analyses in this final rule presented 
in this Appendix, we estimate that aggregate FY 2022 LTCH PPS 
payments will be approximately $2.985 billion, as compared to 
estimated aggregate FY 2023 LTCH PPS payments of approximately 
$3.056 billion, resulting in an estimated overall increase in LTCH 
PPS payments of approximately $71 million. We note that the 
estimated $71 million increase in LTCH PPS payments in FY 2023 does 
not reflect changes in LTCH admissions or case-mix intensity, which 
will also affect the overall payment effects of the policies in this 
final rule.
    The LTCH PPS standard Federal payment rate for FY 2022 is 
$44,713.67. For FY 2023, we are establishing an LTCH PPS standard 
Federal payment rate of $46,432.77 which reflects the 3.8 percent 
annual update to the LTCH PPS standard Federal payment rate and the 
budget neutrality factor for updates to the area wage level 
adjustment of 1.0004304 (discussed in section V.B.6. of the Addendum 
to this final rule). For LTCHs that fail to submit data for the LTCH 
QRP, in accordance with section 1886(m)(5)(C) of the Act, we are 
establishing an LTCH PPS standard Federal payment rate of 
$45,538.11. This LTCH PPS standard Federal payment rate reflects the 
updates and factors previously described, as well as the required 
2.0 percentage point reduction to the annual update for failure to 
submit data under the LTCH QRP.
    Table IV shows the estimated impact for LTCH PPS standard 
Federal payment rate cases. The estimated change attributable solely 
to the annual update of 3.8 percent to the LTCH PPS standard Federal 
payment rate is projected to result in an increase of 3.6 percent in 
payments per discharge for LTCH PPS standard Federal payment rate 
cases from FY 2022 to FY 2023, on average, for all LTCHs (Column 6). 
The estimated increase of 3.6 percent shown in Column 6 of Table IV 
also includes estimated payments for short-stay outlier (SSO) cases, 
a portion of which are not affected by the annual update to the LTCH 
PPS standard Federal payment rate, as well as the reduction that is 
applied to the annual update for LTCHs that do not submit the 
required LTCH QRP data. For most hospital categories, the projected 
increase in payments based on the LTCH PPS standard Federal payment 
rate to LTCH PPS standard Federal payment rate cases also rounds to 
approximately 3.6 percent.
    For FY 2023, we are updating the wage index values based on the 
most recent available data (data from cost reporting periods 
beginning during FY 2019 which is the same data used for the FY 2023 
IPPS wage index). In addition, we are establishing a labor-related 
share of 68.0 percent for FY 2023, based on the most recent 
available data (IGI's second quarter 2022 forecast) on the relative 
importance of the labor-related share of operating and capital costs 
of the 2017-based LTCH market basket. We also applying an area wage 
level budget neutrality factor of 1.0004304 to ensure that the 
changes to the area wage level adjustment will not result in any 
change in estimated aggregate LTCH PPS payments to LTCH PPS standard 
Federal payment rate cases.
    For LTCH PPS standard Federal payment rate cases, we currently 
estimate high cost outlier payments as a percentage of total LTCH 
PPS standard Federal payment rate payments will decrease from FY 
2022 to FY 2023. Based on the FY 2021 LTCH cases that were used for 
the analyses in this final rule, we estimate that the FY 2022 high 
cost outlier threshold of $33,015 (as established in the FY 2022 
IPPS/LTCH PPS final rule) will result in estimated high cost outlier 
payments for LTCH PPS standard Federal payment rate cases in FY 2022 
that are projected to exceed the 7.975 percent target. Specifically, 
we currently estimate that high cost outlier payments for LTCH PPS 
standard Federal payment rate cases will be approximately 9.15 
percent of the estimated total LTCH PPS standard Federal payment 
rate payments in FY 2022. Combined with our estimate that FY 2023 
high cost outlier payments for LTCH PPS standard Federal payment 
rate cases will be 7.975 percent of estimated total LTCH PPS 
standard Federal payment rate payments in FY 2023, this will result 
in an estimated decrease in high cost

[[Page 49487]]

outlier payments as a percentage of total LTCH PPS standard Federal 
payment rate payments of approximately 1.2 percent between FY 2022 
and FY 2023. We note that, in calculating these estimated high cost 
outlier payments, we inflated charges reported on the FY 2021 claims 
by the charge inflation factor in section V.D.3.b. of the Addendum 
to this final rule. We also note that, in calculating these 
estimated high cost outlier payments, we estimated the cost of each 
case by multiplying the inflated charges by the adjusted CCRs that 
we determined using our finalized methodology described in section 
V.D.3.b. of the Addendum to this final rule.
    Table IV shows the estimated impact of the payment rate and 
policy changes on LTCH PPS payments for LTCH PPS standard Federal 
payment rate cases for FY 2023 by comparing estimated FY 2022 LTCH 
PPS payments to estimated FY 2023 LTCH PPS payments. (As noted 
earlier, our analysis does not reflect changes in LTCH admissions or 
case-mix intensity.) We note that these impacts do not include LTCH 
PPS site neutral payment rate cases for the reasons discussed in 
section I.J.3. of this Appendix.
    Comment: We received comments expressing concern about the 0.7 
percent increase in payments to LTCH PPS standard Federal payment 
rate cases that we projected in the proposed rule. Many commenters 
stated that this projected increase was insufficient and failed to 
recognize the impact of increases in healthcare delivery costs on 
LTCHs. A commenter stated that the inadequacy of Medicare payments 
would continue to challenge the financial viability of LTCHs and 
their ability to provide care to Medicare and other patients. 
Another commenter stated that this projected increase is 
insufficient and would not allow LTCHs to compete for resources 
needed to care for patients.
    Response: We appreciate commenters' concerns about the proposed 
0.7 percent increase in payments to LTCH PPS standard Federal 
payment rate cases. Based on the finalized payment rates and factors 
in this final rule, we now project a 2.3 percent increase in 
payments to LTCH PPS standard Federal payment rate cases for FY 
2023. This change in projected payments is primarily being driven by 
the annual update factor of 3.8 percent (that is, the most recent 
estimate of the LTCH PPS market basket increase of 4.1 percent less 
the productivity adjustment of 0.3 percentage point) which is 1.1 
percent higher than the proposed annual update factor. As discussed 
in section VIII.C.2. of the preamble to this final rule, we believe 
this LTCH market basket increase appropriately reflects the input 
price growth that LTCHs will incur while providing medical services 
in FY 2023. We note that the final FY 2023 LTCH market basket growth 
rate of 4.1 percent is the highest market basket update implemented 
in an IPPS/LTCH final rule since RY 2004.
    Comment: Multiple commenters expressed concern about the 
immediate, full implementation of the site neutral payment policy 
following the end of the PHE waiver. Several of these commenters 
stated their belief that cases paid at the site neutral payment rate 
will continue to be underpaid as those cases, according to 
commenters, have on average higher levels of clinical complexity and 
costs that significantly exceed IPPS-level payment. Some commenters 
requested that CMS implement transition policies once the PHE ends 
that would phase in the full implementation of the site neutral 
payment policy, believing such a transition period would help 
prevent disruptions to LTCHs' operations. A commenter recommended 
that CMS pay site neutral cases a blended site neutral and standard 
Federal payment rate during this transition period.
    Response: We acknowledge commenters' concerns about the costs of 
treating site neutral cases, however, as noted by some commenters 
and discussed previously, the site neutral payment rate is a 
statutory requirement and the statutory waiver of the site neutral 
payment is only authorized for the duration of the COVID-19 PHE. We 
did not propose any transition policies that would take effect 
following the end of the PHE waiver. We note that on January 22, 
2021, then-acting Secretary of HHS, Norris Cochran, sent a letter to 
governors announcing that when a decision is made to terminate the 
public health emergency or let it expire, HHS will provide states 
with 60 days' notice prior to termination.\1171\ Therefore, LTCHs 
will have at least 60 days' notice before the statutory waiver of 
the site neutral payment rate expires.
---------------------------------------------------------------------------

    \1171\ https://ccf.georgetown.edu/wp-content/uploads/2021/01/Public-Health-Emergency-Message-to-Governors.pdf.
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    As we discuss in detail throughout this final rule, based on the 
best available data, we believe that the provisions of this final 
rule relating to the LTCH PPS, which are projected to result in an 
overall increase in estimated aggregate LTCH PPS payments, and the 
resulting LTCH PPS payment amounts, result in appropriate Medicare 
payments that are consistent with the statute.

2. Impact on Rural Hospitals

    For purposes of section 1102(b) of the Act, we define a small 
rural hospital as a hospital that is located outside of an urban 
area and has fewer than 100 beds. As shown in Table IV, we are 
projecting a 2.2 percent increase in estimated payments for LTCH PPS 
standard Federal payment rate cases for LTCHs located in a rural 
area. This estimated impact is based on the FY 2021 data for the 17 
rural LTCHs (out of 337 LTCHs) that were used for the impact 
analyses shown in Table IV.

3. Anticipated Effects of LTCH PPS Payment Rate Changes and Policy 
Changes

a. Budgetary Impact

    Section 123(a)(1) of the BBRA requires that the PPS developed 
for LTCHs ``maintain budget neutrality.'' We believe that the 
statute's mandate for budget neutrality applies only to the first 
year of the implementation of the LTCH PPS (that is, FY 2003). 
Therefore, in calculating the FY 2003 standard Federal payment rate 
under Sec.  412.523(d)(2), we set total estimated payments for FY 
2003 under the LTCH PPS so that estimated aggregate payments under 
the LTCH PPS were estimated to equal the amount that would have been 
paid if the LTCH PPS had not been implemented.
    Section 1886(m)(6)(A) of the Act establishes a dual rate LTCH 
PPS payment structure with two distinct payment rates for LTCH 
discharges beginning in FY 2016. Under this statutory change, LTCH 
discharges that meet the patient-level criteria for exclusion from 
the site neutral payment rate (that is, LTCH PPS standard Federal 
payment rate cases) are paid based on the LTCH PPS standard Federal 
payment rate. LTCH discharges paid at the site neutral payment rate 
are generally paid the lower of the IPPS comparable per diem amount, 
reduced by 4.6 percent for FYs 2018 through 2026, including any 
applicable high cost outlier (HCO) payments, or 100 percent of the 
estimated cost of the case, reduced by 4.6 percent.
    As discussed in section I.J.2. of this Appendix, we project an 
increase in aggregate LTCH PPS payments in FY 2023 of approximately 
$71 million. This estimated increase in payments reflects the 
projected increase in payments to LTCH PPS standard Federal payment 
rate cases of approximately $61 million and the projected increase 
in payments to site neutral payment rate cases of approximately $9 
million under the dual rate LTCH PPS payment rate structure required 
by the statute beginning in FY 2016.
    As discussed in section V.D. of the Addendum to this final rule, 
our actuaries project cost and resource changes for site neutral 
payment rate cases due to the site neutral payment rates required 
under the statute. Specifically, our actuaries project that the 
costs and resource use for cases paid at the site neutral payment 
rate will likely be lower, on average, than the costs and resource 
use for cases paid at the LTCH PPS standard Federal payment rate, 
and will likely mirror the costs and resource use for IPPS cases 
assigned to the same MS-DRG. While we are able to incorporate this 
projection at an aggregate level into our payment modeling, because 
the historical claims data that we are using in this final rule to 
project estimated FY 2023 LTCH PPS payments (that is, FY 2021 LTCH 
claims data) do not reflect this actuarial projection, we are unable 
to model the impact of the change in LTCH PPS payments for site 
neutral payment rate cases at the same level of detail with which we 
are able to model the impacts of the changes to LTCH PPS payments 
for LTCH PPS standard Federal payment rate cases. Therefore, Table 
IV only reflects changes in LTCH PPS payments for LTCH PPS standard 
Federal payment rate cases and, unless otherwise noted, the 
remaining discussion in section I.J.3. of this Appendix refers only 
to the impact on LTCH PPS payments for LTCH PPS standard Federal 
payment rate cases. In the following section, we present our 
provider impact analysis for the changes that affect LTCH PPS 
payments for LTCH PPS standard Federal payment rate cases.

b. Impact on Providers

    The basic methodology for determining a per discharge payment 
for LTCH PPS standard Federal payment rate cases is

[[Page 49488]]

currently set forth under Sec. Sec.  412.515 through 412.533 and 
412.535. In addition to adjusting the LTCH PPS standard Federal 
payment rate by the MS-LTC-DRG relative weight, we make adjustments 
to account for area wage levels and SSOs. LTCHs located in Alaska 
and Hawaii also have their payments adjusted by a COLA. Under our 
application of the dual rate LTCH PPS payment structure, the LTCH 
PPS standard Federal payment rate is generally only used to 
determine payments for LTCH PPS standard Federal payment rate cases 
(that is, those LTCH PPS cases that meet the statutory criteria to 
be excluded from the site neutral payment rate). LTCH discharges 
that do not meet the patient-level criteria for exclusion are paid 
the site neutral payment rate, which we are calculating as the lower 
of the IPPS comparable per diem amount as determined under Sec.  
412.529(d)(4), reduced by 4.6 percent for FYs 2018 through 2026, 
including any applicable outlier payments, or 100 percent of the 
estimated cost of the case as determined under existing Sec.  
412.529(d)(2). In addition, when certain thresholds are met, LTCHs 
also receive HCO payments for both LTCH PPS standard Federal payment 
rate cases and site neutral payment rate cases that are paid at the 
IPPS comparable per diem amount.
    To understand the impact of the changes to the LTCH PPS payments 
for LTCH PPS standard Federal payment rate cases presented in this 
final rule on different categories of LTCHs for FY 2023, it is 
necessary to estimate payments per discharge for FY 2022 using the 
rates, factors, and the policies established in the FY 2022 IPPS/
LTCH PPS final rule and estimate payments per discharge for FY 2023 
using the rates, factors, and the policies in this FY 2023 IPPS/LTCH 
PPS final rule (as discussed in section VII. of the preamble of this 
final rule and section V. of the Addendum to this final rule). As 
discussed elsewhere in this final rule, these estimates are based on 
the best available LTCH claims data and other factors, such as the 
application of inflation factors to estimate costs for HCO cases in 
each year. The resulting analyses can then be used to compare how 
our policies applicable to LTCH PPS standard Federal payment rate 
cases affect different groups of LTCHs.
    For the following analysis, we group hospitals based on 
characteristics provided in the OSCAR data, cost report data in 
HCRIS, and PSF data. Hospital groups included the following:
     Location: large urban/other urban/rural.
     Participation date.
     Ownership control.
     Census region.
     Bed size.

c. Calculation of LTCH PPS Payments for LTCH PPS Standard Federal 
Payment Rate Cases

    For purposes of this impact analysis, to estimate the per 
discharge payment effects of our policies on payments for LTCH PPS 
standard Federal payment rate cases, we simulated FY 2022 and FY 
2023 payments on a case-by-case basis using historical LTCH claims 
from the FY 2021 MedPAR files that met or would have met the 
criteria to be paid at the LTCH PPS standard Federal payment rate if 
the statutory patient-level criteria had been in effect at the time 
of discharge for all cases in the FY 2021 MedPAR files. For modeling 
FY 2022 LTCH PPS payments, we used the FY 2022 standard Federal 
payment rate of $44,713.67 (or $43,836.08 for LTCHs that failed to 
submit quality data as required under the requirements of the LTCH 
QRP). Similarly, for modeling payments based on the finalized FY 
2023 LTCH PPS standard Federal payment rate, we used the FY 2023 
standard Federal payment rate of $46,432.77 (or $45,538.11 for LTCHs 
that failed to submit quality data as required under the 
requirements of the LTCH QRP). In each case, we applied the 
applicable adjustments for area wage levels and the COLA for LTCHs 
located in Alaska and Hawaii. Specifically, for modeling FY 2022 
LTCH PPS payments, we used the current FY 2022 labor-related share 
(67.9 percent), the wage index values established in the Tables 12A 
and 12B listed in the Addendum to the FY 2022 IPPS/LTCH PPS final 
rule (which are available via the internet on the CMS website), the 
FY 2022 HCO fixed-loss amount for LTCH PPS standard Federal payment 
rate cases of $33,015 (as reflected in the FY 2022 IPPS/LTCH PPS 
final rule), and the FY 2022 COLA factors (shown in the table in 
section V.C. of the Addendum to that final rule) to adjust the FY 
2022 nonlabor-related share (32.1 percent) for LTCHs located in 
Alaska and Hawaii. Similarly, for modeling FY 2023 LTCH PPS 
payments, we used the FY 2023 LTCH PPS labor-related share (68.0 
percent), the FY 2023 wage index values from Tables 12A and 12B 
listed in section VI. of the Addendum to this final rule (which are 
available via the internet on the CMS website), the FY 2023 HCO 
fixed-loss amount for LTCH PPS standard Federal payment rate cases 
of $38,518 (as discussed in section V.D.3. of the Addendum to this 
final rule), and the FY 2023 COLA factors (shown in the table in 
section V.C. of the Addendum to this final rule) to adjust the FY 
2023 nonlabor-related share (32.0 percent) for LTCHs located in 
Alaska and Hawaii. We noted that in modeling payments for HCO cases 
for LTCH PPS standard Federal payment rate cases, we inflated 
charges reported on the FY 2021 claims by the charge inflation 
factors in section V.D.3.b. of the Addendum to this final rule. We 
also noted that in modeling payments for HCO cases for LTCH PPS 
standard Federal payment rate cases, we estimated the cost of each 
case by multiplying the inflated charges by the adjusted CCRs that 
we determined using our finalized methodology described in section 
V.D.3.b. of the Addendum to this final rule.
    The impacts that follow reflect the estimated ``losses'' or 
``gains'' among the various classifications of LTCHs from FY 2022 to 
FY 2023 based on the payment rates and policy changes applicable to 
LTCH PPS standard Federal payment rate cases presented in this final 
rule. Table IV illustrates the estimated aggregate impact of the 
change in LTCH PPS payments for LTCH PPS standard Federal payment 
rate cases among various classifications of LTCHs. (As discussed 
previously, these impacts do not include LTCH PPS site neutral 
payment rate cases.)
     The first column, LTCH Classification, identifies the 
type of LTCH.
     The second column lists the number of LTCHs of each 
classification type.
     The third column identifies the number of LTCH cases 
expected to meet the LTCH PPS standard Federal payment rate 
criteria.
     The fourth column shows the estimated FY 2022 payment 
per discharge for LTCH cases expected to meet the LTCH PPS standard 
Federal payment rate criteria (as described previously).
     The fifth column shows the estimated FY 2023 payment 
per discharge for LTCH cases expected to meet the LTCH PPS standard 
Federal payment rate criteria (as described previously).
     The sixth column shows the percentage change in 
estimated payments per discharge for LTCH cases expected to meet the 
LTCH PPS standard Federal payment rate criteria from FY 2022 to FY 
2023 due to the annual update to the standard Federal rate (as 
discussed in section V.A.2. of the Addendum to this final rule).
     The seventh column shows the percentage change in 
estimated payments per discharge for LTCH PPS standard Federal 
payment rate cases from FY 2022 to FY 2023 for changes to the area 
wage level adjustment (that is, the updated hospital wage data and 
labor-related share) and the application of the corresponding budget 
neutrality factor (as discussed in section V.B.6. of the Addendum to 
this final rule).
     The eighth column shows the percentage change in 
estimated payments per discharge for LTCH PPS standard Federal 
payment rate cases from FY 2022 (Column 4) to FY 2023 (Column 5) for 
all changes.
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d. Results

    Based on the FY 2021 LTCH cases (from 337 LTCHs) that were used 
for the analyses in this final rule, we have prepared the following 
summary of the impact (as shown in Table IV) of the LTCH PPS payment 
rate and policy changes for LTCH PPS standard Federal payment rate 
cases presented in this final rule. The impact analysis in Table IV 
shows that estimated payments per discharge for LTCH PPS standard 
Federal payment rate cases are projected to increase 2.3 percent, on 
average, for all LTCHs from FY 2022 to FY 2023 as a result of the 
payment rate and policy changes applicable to LTCH PPS standard 
Federal payment rate cases

[[Page 49491]]

presented in this final rule. This estimated 2.3 percent increase in 
LTCH PPS payments per discharge was determined by comparing 
estimated FY 2023 LTCH PPS payments (using the finalized payment 
rates and factors discussed in this final rule) to estimated FY 2022 
LTCH PPS payments for LTCH discharges which will be LTCH PPS 
standard Federal payment rate cases if the dual rate LTCH PPS 
payment structure was or had been in effect at the time of the 
discharge (as described in section I.J.3. of this Appendix).
    As stated previously, we are finalizing the update the LTCH PPS 
standard Federal payment rate for FY 2023 by 3.8 percent. For LTCHs 
that fail to submit quality data under the requirements of the LTCH 
QRP, as required by section 1886(m)(5)(C) of the Act, a 2.0 
percentage point reduction is applied to the annual update to the 
LTCH PPS standard Federal payment rate. Consistent with Sec.  
412.523(d)(4), we also are applying a budget neutrality factor for 
changes to the area wage level adjustment of 1.0004304 (discussed in 
section V.B.6. of the Addendum to this final rule), based on the 
best available data at this time, to ensure that any changes to the 
area wage level adjustment will not result in any change (increase 
or decrease) in estimated aggregate LTCH PPS standard Federal 
payment rate payments. As we also explained earlier in this section 
of the final rule, for most categories of LTCHs (as shown in Table 
IV, Column 6), the estimated payment increase due to the 3.8 percent 
annual update to the LTCH PPS standard Federal payment rate is 
projected to result in approximately a 3.6 percent increase in 
estimated payments per discharge for LTCH PPS standard Federal 
payment rate cases for all LTCHs from FY 2022 to FY 2023. We note 
our estimate of the changes in payments due to the update to the 
LTCH PPS standard Federal payment rate also includes estimated 
payments for short-stay outlier (SSO) cases, a portion of which are 
not affected by the annual update to the LTCH PPS standard Federal 
payment rate, as well as the reduction that is applied to the annual 
update for LTCHs that do not submit the required LTCH QRP.

(1) Location

    Based on the most recent available data, the vast majority of 
LTCHs are located in urban areas. Only approximately 5 percent of 
the LTCHs are identified as being located in a rural area, and 
approximately 4 percent of all LTCH PPS standard Federal payment 
rate cases are expected to be treated in these rural hospitals. The 
impact analysis presented in Table IV shows that the overall average 
percent increase in estimated payments per discharge for LTCH PPS 
standard Federal payment rate cases from FY 2022 to FY 2023 for all 
hospitals is 2.3 percent. The projected increase for urban and rural 
hospitals, respectively, is 2.3 and 2.2.

(2) Participation Date

    LTCHs are grouped by participation date into four categories: 
(1) before October 1983; (2) between October 1983 and September 
1993; (3) between October 1993 and September 2002; and (4) October 
2002 and after. Based on the best available data, the categories of 
LTCHs with the largest expected percentage of LTCH PPS standard 
Federal payment rate cases (approximately 41 percent and 44 percent, 
respectively) are in LTCHs that began participating in the Medicare 
program between October 1993 and September 2002 and after October 
2002. These LTCHs are expected to experience an increase in 
estimated payments per discharge for LTCH PPS standard Federal 
payment rate cases from FY 2022 to FY 2023 of 2.5 percent and 2.1 
percent, respectively. LTCHs that began participating in the 
Medicare program between October 1983 and September 1993 are 
projected to experience an increase in estimated payments per 
discharge for LTCH PPS standard Federal payment rate cases from FY 
2022 to FY 2023 of 2.6 percent, as shown in Table IV. Approximately 
3 percent of LTCHs began participating in the Medicare program 
before October 1983, and these LTCHs are projected to experience an 
increase in estimated payments per discharge for LTCH PPS standard 
Federal payment rate cases from FY 2022 to FY 2023 of 1.2 percent.

(3) Ownership Control

    LTCHs are grouped into three categories based on ownership 
control type: voluntary, proprietary, and government. Based on the 
best available data, approximately 16 percent of LTCHs are 
identified as voluntary (Table IV). The majority (approximately 81 
percent) of LTCHs are identified as proprietary, while government 
owned and operated LTCHs represent approximately 3 percent of LTCHs. 
Based on ownership type, proprietary LTCHs are expected to 
experience an increase in payments to LTCH PPS standard Federal 
payment rate cases of 2.4 percent. Voluntary LTCHs are expected to 
experience an increase in payments to LTCH PPS standard Federal 
payment rate cases from FY 2022 to FY 2023 of 1.6 percent. 
Meanwhile, government owned and operated LTCHs are expected to 
experience an increase in payments to LTCH PPS standard Federal 
payment rate cases from FY 2022 to FY 2023 of 1.9 percent.

(4) Census Region

    The comparisons by region show that the changes in estimated 
payments per discharge for LTCH PPS standard Federal payment rate 
cases from FY 2022 to FY 2023 are projected to range from an 
increase of 0.9 percent in the West North Central region to a 2.9 
percent increase in the Pacific region. These regional variations 
are primarily due to the changes to the area wage adjustment and 
estimated changes in outlier payments.

(5) Bed Size

    LTCHs are grouped into six categories based on bed size: 0-24 
beds; 25-49 beds; 50-74 beds; 75-124 beds; 125-199 beds; and greater 
than 200 beds. We project that LTCHs with 125-199 beds will 
experience the lowest increase in payments for LTCH PPS standard 
Federal payment rate cases, 1.9 percent. LTCHs with 0-24 beds are 
projected to experience the largest increase in payments of 3.0 
percent. The remaining bed size categories are projected to 
experience an increase in payments in the range of 2.1 to 2.6 
percent.

4. Effect on the Medicare Program

    As stated previously, we project that the provisions of this 
final rule will result in an increase in estimated aggregate LTCH 
PPS payments to LTCH PPS standard Federal payment rate cases in FY 
2023 relative to FY 2022 of approximately $61 million (or 
approximately 2.3 percent) for the 339 LTCHs in our database. 
Although, as stated previously, the hospital-level impacts do not 
include LTCH PPS site neutral payment rate cases, we estimate that 
the provisions of this final rule will result in an increase in 
estimated aggregate LTCH PPS payments to site neutral payment rate 
cases in FY 2023 relative to FY 2022 of approximately $9 million (or 
approximately 2.8 percent) for the 339 LTCHs in our database. (As 
noted previously, we estimate payments to site neutral payment rate 
cases in FY 2023 represent approximately 11 percent of total 
estimated FY 2023 LTCH PPS payments.) Therefore, we project that the 
provisions of this final rule will result in an increase in 
estimated aggregate LTCH PPS payments for all LTCH cases in FY 2023 
relative to FY 2022 of approximately 71 million (or approximately 
2.4 percent) for the 339 LTCHs in our database.

5. Effect on Medicare Beneficiaries

    Under the LTCH PPS, hospitals receive payment based on the 
average resources consumed by patients for each diagnosis. We do not 
expect any changes in the quality of care or access to services for 
Medicare beneficiaries as a result of this final rule, but we 
continue to expect that paying prospectively for LTCH services will 
enhance the efficiency of the Medicare program. As discussed 
previously, we do not expect the continued implementation of the 
site neutral payment system to have a negative impact on access to 
or quality of care, as demonstrated in areas where there is little 
or no LTCH presence, general short-term acute care hospitals are 
effectively providing treatment for the same types of patients that 
are treated in LTCHs.

K. Effects of Requirements for the Hospital Inpatient Quality 
Reporting (IQR) Program

    In section IX.E. of the preamble of this final rule, we discuss 
our current requirements and newly finalized requirements for 
hospitals to report quality data under the Hospital IQR Program to 
receive the full annual percentage increase for the FY 2023 payment 
determination and subsequent years.
    In this final rule, we are adopting the following measures: (1) 
Hospital Commitment to Health Equity, beginning with the CY 2023 
reporting period/FY 2025 payment determination; (2) Screening for 
Social Drivers of Health beginning with voluntary reporting in the 
CY 2023 reporting period and mandatory reporting beginning with the 
CY 2024 reporting period/FY 2026 payment determination; (3) Screen 
Positive Rate for Social Drivers of Health beginning with voluntary 
reporting in the CY 2023 reporting period and mandatory reporting 
beginning with the CY 2024 reporting period/FY 2026 payment 
determination; (4) Cesarean Birth electronic clinical quality

[[Page 49492]]

measure (eCQM) with inclusion in the eCQM measure set beginning with 
the CY 2023 reporting period/FY 2025 payment determination, and 
mandatory reporting beginning with the CY 2024 reporting period/FY 
2026 payment determination; (5) Severe Obstetric Complications eCQM 
with inclusion in the eCQM measure set beginning with the CY 2023 
reporting period/FY 2025 payment determination, and mandatory 
reporting beginning with the CY 2024 reporting period/FY 2026 
payment determination; (6) Hospital-Harm--Opioid-Related Adverse 
Events eCQM with inclusion in the eCQM measure set beginning with 
the CY 2024 reporting period/FY 2026 payment determination; (7) 
Global Malnutrition Composite Score eCQM with inclusion in the eCQM 
measure set beginning with the CY 2024 reporting period/FY 2026 
payment determination; (8) Hospital-Level, Risk Standardized 
Patient-Reported Outcomes Performance Measure (PRO-PM) Following 
Elective Primary Total Hip Arthroplasty (THA) and/or Total Knee 
Arthroplasty (TKA), beginning with two voluntary periods followed by 
mandatory reporting beginning with the reporting period which runs 
from July 1, 2025 through June 30, 2026, impacting the FY 2028 
payment determination; (9) Medicare Spending Per Beneficiary (MSPB) 
Hospital beginning with the FY 2024 payment determination; and (10) 
Hospital-Level Risk-Standardized Complications Rate (RSCR) Following 
Elective Primary THA/TKA beginning with the FY 2024 payment 
determination. We are refining two current measures beginning with 
the FY 2024 payment determination: (1) Hospital-Level, Risk-
Standardized Payment Associated with an Episode of Care for Primary 
Elective THA/TKA; and (2) Excess Days in Acute Care (EDAC) After 
Hospitalization for Acute Myocardial Infarction (AMI). We are also: 
(1) Establishing a hospital designation related to maternal care to 
be publicly-reported on a public-facing website beginning in Fall 
2023, and sought comments on other potential associated activities 
regarding this designation; (2) modifying our eCQM reporting and 
submission requirements whereby we are increasing the total number 
of eCQMs to be reported from four to six eCQMs beginning with the CY 
2024 reporting period/FY 2026 payment determination; (3) modifying 
our case threshold exemptions and zero denominator declaration 
policies for hybrid measures as we believe they are not applicable 
for those measure types beginning with the FY 2026 payment 
determination; (4) adopting reporting and submission requirements 
for PRO-PMs; and (5) modifying our eCQM validation policy to 
increase the reporting of medical requests from 75 percent of 
records to 100 percent of records beginning with the FY 2025 payment 
determination.
    As shown in the summary table in section XII.B.4. of the 
preamble of this final rule, we estimate a total information 
collection burden increase for 3,150 IPPS hospitals of 746,300 hours 
at a cost of $23,437,906 annually associated for our finalized 
policies and updated burden estimates across a 4-year period from 
the CY 2023 reporting period/FY 2025 payment determination through 
the CY 2026 reporting period/FY 2028 payment determination, compared 
to our currently approved information collection burden estimates.
    In section IX.E.5.a. of the preamble of this final rule, we are 
adopting the Hospital Commitment to Health Equity structural 
measure. In order for hospitals to receive a point for each of the 
five domains in the measure, affirmative attestations are required 
for each of the elements within a domain. For hospitals that are 
unable to attest affirmatively for an element, there are likely to 
be additional costs associated with activities such as updating 
hospital policies, engaging senior leadership, participating in new 
quality improvement activities, performing additional data analysis, 
and training staff. The extent of these costs will vary from 
hospital to hospital depending on what activities the hospital is 
already performing, hospital size, and the individual choices each 
hospital makes in order to meet the criteria necessary to attest 
affirmatively.
    In section IX.E.5.b.(1). of the preamble of this final rule, we 
are adopting the Screening for Social Drivers of Health measure. For 
hospitals that are not currently administering some screening 
mechanism and elect to begin doing so as a result of this policy, 
there will be some non-recurring costs associated with changes in 
workflow and information systems to collect the data. The extent of 
these costs is difficult to quantify as different hospitals may 
utilize different modes of data collection (for example paper-based, 
electronically patient-directed, clinician-facilitated, etc.). In 
addition, depending on the method of data collection utilized, the 
time required to complete the survey may add a negligible amount of 
time to patient visits.
    In section IX.E.5.g. of the preamble of this final rule, we are 
adopting the THA/TKA PRO-PM. For hospitals that are not currently 
collecting this data and elect to begin doing so as a result of this 
policy, there will be some non-recurring costs associated with 
changes in workflow and information systems to collect the data. The 
extent of these costs is difficult to quantify as different 
hospitals may utilize different modes of data collection (for 
example paper-based, electronically patient-directed, clinician-
facilitated, etc.). While we assume the majority of hospitals will 
report data for this measure via the HQR System, we assume some 
hospitals may elect to submit measure data via a third-party CMS-
approved survey vendor, for which there are associated costs. Under 
OMB control number 0938-0981 for the HCAHPS Survey measure 
(expiration date September 30, 2024), an estimate of approximately 
$4,000 per hospital is used to account for these costs. This 
estimate originates from 2012, therefore, to account for inflation 
(assuming end of CY 2012 to end of CY 2021), we adjust the price 
using the Bureau of Labor Statistics Consumer Price Index and 
estimate an updated cost of approximately $4,856 ($4,000 x 121.4 
percent).\1172\
---------------------------------------------------------------------------

    \1172\ U.S. Bureau of Labor Statistics. Historical CPI-U data. 
Accessed on March 10, 2022. Available at: https://www.bls.gov/cpi/tables/supplemental-files/historical-cpi-u-202112.pdf.
---------------------------------------------------------------------------

    We note that in sections IX.E.5.c., IX.E.5.d., IX.E.5.e, and 
IX.E.5.f. of the preamble of this final rule, we are adopting four 
new eCQMs. Similar to the FY 2019 IPPS/LTCH PPS final rule regarding 
removal of eCQM measures, while there is no change in information 
collection burden related to those finalized provisions, we believe 
that costs are multifaceted and include not only the burden 
associated with reporting, but also the costs associated with 
implementing and maintaining Hospital IQR Program measures in 
hospitals' EHR systems for all of the eCQMs available for use in the 
Hospital IQR Program (83 FR 41771). Additionally, two of the four 
eCQMs are mandatory beginning with the CY 2024 reporting period/FY 
2026 payment determination and for subsequent years; we account for 
the burden of collection of information in section XII.B.4. 
(Collection of Information) in our finalized policy to increase our 
eCQM reporting and submission requirements from four eCQMs to six 
eCQMs. Because hospitals are already reporting eCQMs, we do not 
believe there are any additional costs associated with increasing 
the number of eCQMs hospitals must report beyond the burden 
discussed in the collection of information section and the costs 
previously discussed related to adopting new eCQMs.
    Historically, 100 hospitals, on average, that participate in the 
Hospital IQR Program do not receive the full annual percentage 
increase in any fiscal year due to the failure to meet all 
requirements of the Hospital IQR Program. We anticipate that the 
number of hospitals not receiving the full annual percentage 
increase will be approximately the same as in past years.
    We received no comments on these effects.

L. Effects of Requirements for the PPS-Exempt Cancer Hospital 
Quality Reporting (PCHQR) Program

    In section IX.F. of the preamble of this final rule, we discuss 
our policies for the quality data reporting program for PPS-exempt 
cancer hospitals (PCHs), which we refer to as the PPS-Exempt Cancer 
Hospital Quality Reporting (PCHQR) Program. The PCHQR Program is 
authorized under section 1866(k) of the Act, which was added by 
section 3005 of the Affordable Care Act. There is no financial 
impact to PCH Medicare reimbursement if a PCH does not submit data.
    In section IX.F.4. of the preamble of this final rule, we are: 
(1) adopting and codifying a patient safety exception for the 
measure removal policy; (2) beginning public display of the End-of-
Life (EOL) measures with FY 2025 program year data; and (3) 
beginning public display of the 30-Day Unplanned Readmissions for 
Cancer Patients measures with FY 2024 program year data. These 
provisions do not result in additional financial impact beyond the 
information collection burden of 0 hours discussed in section 
XII.B.XX of the preamble of this final rule.
    We received no comments on these effects.

[[Page 49493]]

M. Effects of Requirements for the Long-Term Care Hospital Quality 
Reporting Program (LTCH QRP)

    In section IX.G. of the preamble of this proposed rule, we are 
soliciting comment on several issues but are not proposing any 
policy changes. Given that there are no costs for this provision.

N. Effects of Requirements Regarding the Medicare Promoting 
Interoperability Program

    In section IX.H. of this final rule, we are finalizing the 
following changes for eligible hospitals and critical access 
hospitals (CAHs) that attest to CMS under the Medicare Promoting 
Interoperability Program: (1) to require and modify the Electronic 
Prescribing Objective's Query of PDMP measure while maintaining the 
associated points at 10 points beginning with the electronic health 
record (EHR) reporting period in CY 2023 with modification for an 
additional exclusion based on public comment; (2) to expand the 
Query of Prescription Drug Monitoring Program (PDMP) measure to 
include not only Schedule II opioids, but also Schedule III, and IV 
drugs beginning with EHR reporting periods in CY 2023; (3) to add a 
new Health Information Exchange (HIE) Objective option, the Enabling 
Exchange Under Trusted Exchange Framework and Common Agreement 
(TEFCA) measure (requiring a yes/no response) beginning with EHR 
reporting periods in CY 2023; (4) to modify the Public Health and 
Clinical Data Exchange Objective by adding an Antibiotic Use and 
Resistance (AUR) measure in addition to the current four required 
measures (Syndromic Surveillance Reporting, Immunization Registry 
Reporting, Electronic Case Reporting, and Electronic Reportable 
Laboratory Result Reporting) with modification to begin with EHR 
reporting periods in CY 2024; (5) to consolidate the current options 
from three to two levels of active engagement for the Public Health 
and Clinical Data Exchange Objective and to require the reporting of 
active engagement for the measures under the objective beginning 
with EHR reporting periods in CY 2023 with modification to delay the 
requirement that eligible hospital and CAHs may spend only one EHR 
reporting period at the Pre-production and Validation level of 
active engagement per measure until EHR reporting period in CY 2024; 
(6) to institute public reporting of certain Medicare Promoting 
Interoperability Program data beginning from the CY 2023 EHR 
reporting period; (7) to modify the scoring methodology for the 
Promoting Interoperability Program beginning in the EHR reporting 
periods in CY 2023; and (8) to remove regulation text for the 
objectives and measures in the Medicare Promoting Interoperability 
Program from paragraph (e) under 42 CFR 495.24 and add new paragraph 
(f) beginning in CY 2023. We are also finalizing adoption of four 
eCQMs: (1) Severe Obstetric Complications eCQM with inclusion in the 
eCQM measure set beginning with the CY 2023 reporting period, 
followed by mandatory reporting beginning with the CY 2024 reporting 
period; (2) Cesarean Birth (ePC-02) eCQM with inclusion in the eCQM 
measure set beginning with the CY 2023 reporting period followed by 
mandatory reporting beginning with the CY 2024 reporting period; (3) 
Hospital-Harm--Opioid-Related Adverse Events eCQM with inclusion in 
the eCQM measure set beginning with the CY 2024 reporting period; 
and (4) Global Malnutrition Composite Score eCQM with inclusion in 
the eCQM measure set beginning with the CY 2024 reporting period. 
Lastly, we are finalizing a modification to our eCQM reporting and 
submission requirements whereby we are increasing the total number 
of eCQMs to be reported from four to six eCQMs beginning with the CY 
2024 reporting period.
    As shown in summary table in section XII.B.9.k. of the preamble 
of this final rule, we estimate a total information collection 
burden increase for 4,500 eligible hospitals and CAHs of 5,513 hours 
at a cost of $233,730 annually associated with our finalized 
policies and updated burden estimates across the CY 2023 and CY 2024 
EHR reporting periods compared to our currently approved information 
collection burden estimates. We refer readers to section XII.B.9. of 
the preamble of this final rule (information collection 
requirements) for a detailed discussion of the calculations 
estimating the changes to the information collection burden for 
submitting data to the Medicare.
    In section IX.H.4. of the preamble of this final rule, we are 
finalizing to add the Enabling Exchange Under TEFCA measure to the 
Health Information Exchange Objective. Eligible hospitals and CAHs 
currently may choose to report the two Support Electronic Referral 
Loop measures or may choose to report the HIE Bi-Directional 
Exchange measure. With the addition of this measure, eligible 
hospitals and CAHs would be able to choose to attest to Enabling 
Exchange Under TEFCA as an alternative to reporting on other 
measures in the objective and provide an opportunity for eligible 
hospitals and CAHs that are already voluntarily connecting to and 
exchanging information under TEFCA to earn credit for the Health 
Information Exchange Objective. Because attesting to this measure is 
voluntary and we assume eligible hospitals and CAHs would already be 
engaging in the activities necessary to attest ``yes'', we assume no 
additional financial impact as a result of this policy.
    In section IX.H.5.b. of the preamble of this final rule, we are 
finalizing the adoption of a new Antimicrobial Use and Resistance 
(AUR) Surveillance measure for eligible hospitals and CAHs under the 
Promoting Interoperability Program's Public Health and Clinical Data 
Exchange Objective with associated exclusions with modification to 
begin in the EHR reporting periods in CY 2024. To attest 
successfully, an eligible hospital or CAH must be in active 
engagement with CDC's National Healthcare Safety Network (NHSN) to 
submit AUR data and receive a report from NHSN indicating their 
successful submission of AUR data for the EHR reporting period. 
Participation in NHSN's surveillance requires the purchase or 
building of an AUR reporting solution. While thousands of hospitals 
have voluntarily done this to date, for hospitals who would be 
required to, we estimate the cost to range between $17,000 and 
$388,500 annually, with a median of $187,400.\1173\ We believe these 
associated costs are outweighed by the more than $4.6 billion in 
health care costs spent annually treating antibiotic resistance 
threats.\1174\
---------------------------------------------------------------------------

    \1173\ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5051263/.
    \1174\ https://www.cdc.gov/drugresistance/solutions-initiative/stories/partnership-estimates-healthcare-cost.html.
---------------------------------------------------------------------------

    In section IX.H.5.c. of the preamble of this final rule, we are 
finalizing to reduce the number of active engagement options from 
three to two and combine the ``completed registration to submit 
data'' option with the ``testing'' and validation option. Because 
these options were first available in 2016 and the vast majority of 
eligible hospitals and CAHs have completed the ``completed 
registration to submit data'' option in the years since, we believe 
any financial impact associated with this finalized policy to be 
negligible. Regarding the finalized policy to allow eligible 
hospitals and CAHs to spend only one EHR reporting period at the 
Pre-production and Validation phase, because the goal for all 
eligible hospitals and CAHs has historically been to eventually be 
at the Validated Data Production option, we do not believe there is 
any additional financial impact associated with this policy.
    In section IX.H.10.a.(2). of the preamble of this final rule, we 
are finalizing to adopt four new eCQMs. Similar to the FY 2019 IPPS/
LTCH PPS final rule regarding removal of eCQM measures, while there 
is no change in information collection burden related to those 
finalized provisions, we believe that costs are multifaceted and 
include not only the burden associated with reporting but also the 
costs associated with implementing and maintaining program measures 
in hospitals' EHR systems for all of the eCQMs available for use in 
the Promoting Interoperability Program (83 FR 41771). Additionally, 
for two of the four eCQMs being finalized as mandatory beginning 
with the CY 2024 reporting period and for subsequent years, we 
account for the burden of collection of information in section 
XII.B.9.e. (Collection of Information) in our finalized policy to 
increase our eCQM reporting and submission requirements from four 
eCQMs to six eCQMs.
    We received no comments on these effects.

O. Alternatives Considered

    This final rule contains a range of policies. It also provides 
descriptions of the statutory provisions that are addressed, 
identifies the finalized policies, and presents rationales for our 
decisions and, where relevant, alternatives that were considered.

1. Use of FY 2021 Data and Proposed Methodology Modifications for the 
FY 2023 IPPS and LTCH PPS Ratesetting

    In the FY 2022 IPPS/LTCH proposed rule (87 FR 28740), we 
explained that for the IPPS and LTCH PPS ratesetting, our 
longstanding goal is to use the best available data. We stated that 
given the persistence of the effects of the virus that causes COVID-
19 in the Medicare FY 2020 data, the Medicare FY 2021 data, and the 
CDC hospitalization data, coupled with the expectation for future

[[Page 49494]]

variants, we believe that it is reasonable to assume that some 
Medicare beneficiaries will continue to be hospitalized with COVID-
19 at IPPS hospitals and LTCHs in FY 2023. Accordingly, we stated we 
believe it is appropriate to use FY 2021 data, as the most recent 
available data during the period of the COVID-19 PHE, for purposes 
of the FY 2023 IPPS and LTCH PPS ratesetting.
    We also stated in the FY 2022 IPPS/LTCH proposed rule (87 FR 
28740), we believe it is reasonable to assume based on the 
information available at this time that there will be fewer COVID 19 
hospitalizations in FY 2023 than in FY 2021 given the more recent 
trends in the CDC hospitalization data since the Omicron variant 
peak in January, 2022. Accordingly, because we anticipate Medicare 
inpatient hospitalizations for COVID-19 will continue in FY 2023 but 
at a lower level, we proposed to use FY 2021 data for purposes of 
the FY 2023 IPPS and LTCH PPS ratesetting but with the following 
modifications to our usual ratesetting methodologies to account for 
the anticipated decline in COVID-19 hospitalizations of Medicare 
beneficiaries at IPPS hospitals and LTCHs as compared to FY 2021.
     Calculate the relative weights for FY 2023 by first 
calculating two sets of weights, one including and one excluding 
COVID-19 claims in the FY 2021 data, and then averaging the two sets 
of relative weights to determine the proposed FY 2023 relative 
weight values.
     Modify our methodologies for determining the FY 2023 
outlier fixed-loss amount for IPPS cases and LTCH PPS standard 
Federal payment rate cases to use charge inflation factors based on 
the increase in charges that occurred from FY 2018 to FY 2019, which 
is the last 1-year period prior to the COVID-19 PHE and to use CCR 
adjustment factors based on the change in CCRs that occurred between 
the March 2019 PSF and the March 2020 PSF, which is the last 1-year 
period prior to the COVID-19 PHE.
    We refer the reader to section II.E.2.c. of the preamble and 
section II.A.4.j. of the Addendum of this final rule for a complete 
discussion regarding these proposed modifications to our usual 
ratesetting methodologies.
    Alternatively, we considered not making any of these 
modifications to our usual methodologies for the calculation of the 
FY 2023 MS-DRG and MS-LTC-DRG relative weights or the usual 
methodologies used to determine the FY 2023 outlier fixed-loss 
amount for IPPS cases and LTCH PPS standard Federal payment rate 
cases. Specifically, under this alternative approach, we considered 
to--
     Calculate the relative weights using our usual 
methodology for FY 2023 by including all COVID-19 claims in the FY 
2021 data with no averaging of the relative weights as calculated 
with and without the COVID-19 cases to determine the FY 2023 
relative weight values; and
     Use the same data we would ordinarily use for purposes 
of this FY 2023 rulemaking to compute the charge inflation factors 
and CCR adjustment factors in determining the FY 2023 outlier fixed-
loss amount for IPPS cases and LTCH PPS standard Federal payment 
rate cases; specifically:
    ++ Charge inflation factors based on the increase in charges 
that occurred from FY 2020 to FY 2021, which is the latest full 
fiscal year period of MedPAR data available to determine the 
increase in charges.
    ++ CCR adjustment factors based on the change in CCRs that 
occurred between the December 2020 PSF and the December 2021 PSF, 
which is the latest 1-year period of the PSF to determine the 
adjustment factors to the CCRs for the proposed rule (for the final 
rule, we typically use updated PSF data to determine the CCR 
adjustment factor which for FY 2023 would be based on the change in 
CCRs that occurred between the March 2021 PSF and the March 2022 
PSF).
    We note the FY 2023 outlier fixed-loss amount would be 
significantly higher under this alternative considered.
    In order to facilitate comments on this alternative approach as 
well as comments on our proposed modifications to our usual 
methodologies, we made available additional files on the CMS website 
at https://www.cms.gov/medicare/medicare-fee-for-service-payment/
acuteinpatientpps, along with the data files and information for our 
proposed FY 2023 IPPS ratesetting. The LTCH PPS specific files were 
posted the CMS website at https://www.cms.gov/medicare/medicare-fee-for-service-payment/longtermcarehospitalpps, along with the data 
files and information for our proposed FY 2023 LTCH PPS ratesetting.
    Public comments were largely supportive of CMS use of FY 2021 
data including to determine the FY 2023 MS-DRG relative weights by 
averaging the relative weights as calculated with and without COVID-
19 cases in the FY 2021 data. Some commenters expressed concern 
about policies that may limit the reimbursement for COVID-19 cases. 
As discussed in section II.E. of the preamble of this final rule, 
and following our review of public comments, we are finalizing our 
proposal to determine the FY 2023 MS-DRG relative weights by 
averaging the relative weights as calculated with and without COVID-
19 cases in the FY 2021 data. We note, the finalization of our 
proposal to use FY 2021 data and to modify our methodology for 
determining the FY 2023 LTCH PPS MS-LTC-DRG relative weights is 
discussed in greater detail in section VIII.B. of the preamble of 
this final rule.
    As discussed in section II.A.4. and section V.D.3. of the 
addendum to this final rule, we received many comments supportive of 
our proposed modifications to our usual methodologies for 
determining the FY 2023 IPPS and LTCH PPS outlier fixed-loss 
amounts.
    As discussed in these sections, after considering comments 
received, we are finalizing our proposal to inflate the charges on 
the FY 2021 MedPAR claims using charge inflation factors computed by 
comparing the average covered charge per case in the March 2019 
MedPAR file of FY 2018 to the average covered charge per case in the 
March 2020 MedPAR file of FY 2019, which is the last 1-year period 
prior to the COVID-19 PHE. We also finalizing our proposal to adjust 
the CCRs from the March 2021 update of the PSF by comparing the 
percentage change in the national average case-weighted CCR from the 
March 2019 update of the PSF to the national average case-weighted 
CCR from the March 2020 update of the PSF, which is the last 1-year 
period prior to the COVID-19 PHE.
    We also received many comments that suggested other 
modifications CMS should make to our usual methodologies for 
determining the FY 2023 IPPS and LTCH PPS outlier fixed-loss 
amounts. As also discussed in section II.A.4. and section V.D.3. of 
the addendum to this final rule, in response to comments received, 
we are modifying our proposed methodologies for establishing the FY 
2023 IPPS and LTCH PPS outlier fixed-loss amounts. We specifically 
determined the FY 2023 IPPS and LTCH PPS outlier fixed-loss amounts 
as averages of these fixed-loss amounts calculated including and 
excluding COVID-19 claims. We believe this adjustment to our 
proposed methodology will better reflect a reasonable estimation of 
the case mix for FY 2023 based on the information available at this 
time and is also consistent with the approach we are finalizing for 
determining the FY 2023 IPPS MS-DRG and LTCH PPS MS-LTC-DRG relative 
weights.
    In addition, as discussed in section II.A.4 of the addendum to 
this final rule, in response to comments received, we are further 
modifying our proposed methodology for establishing the FY 2023 IPPS 
outlier fixed-loss amount. Specifically, when determining the FY 
2023 IPPS outlier fixed-loss amount, we included COVID-19 add-on 
payments which were not accounted for in our proposed methodology.

P. Overall Conclusion

1. Acute Care Hospitals

    Acute care hospitals are estimated to experience an increase of 
approximately $1.4 billion in FY 2023, including operating, capital, 
and new technology changes, as well as increased GME payments under 
our changes in response to Milton S. Hershey Medical Center, et al. 
v. Becerra and payments under the new supplemental payment for IHS/
Tribal and Puerto Rico hospitals. The estimated change in operating 
payments is approximately $2.3 billion (discussed in section I.G. 
and I.H. of this Appendix). The estimated change in capital payments 
is approximately $0.039 billion (discussed in section I.I. of this 
Appendix). The estimated change in new technology add-on payments is 
approximately -$0.747 billion as discussed in section I.H. of this 
Appendix. The change in new technology add-on payments reflects the 
net impact of new applications under the alternative pathways and 
continuing new technology add-on payments. Total may differ from the 
sum of the components due to rounding.
    Table I. of section I.G. of this Appendix also demonstrates the 
estimated redistributional impacts of the IPPS budget neutrality 
requirements for the MS-DRG and wage index changes, and for the wage 
index reclassifications under the MGCRB.
    We estimate that hospitals would experience a 0.6 percent 
increase in capital payments per case, as shown in Table III. of 
section I.I. of this Appendix. We project that

[[Page 49495]]

there would be a $39 million increase in capital payments in FY 2023 
compared to FY 2022.
    The discussions presented in the previous pages, in combination 
with the remainder of this final rule, constitute a regulatory 
impact analysis.

2. LTCHs

    Overall, LTCHs are projected to experience an increase in 
estimated payments in FY 2023. In the impact analysis, we are using 
the finalized rates, factors, and policies presented in this final 
rule based on the best available claims and CCR data to estimate the 
change in payments under the LTCH PPS for FY 2023. Accordingly, 
based on the best available data for the 339 LTCHs included in our 
analysis, we estimate that overall FY 2023 LTCH PPS payments will 
increase approximately $71 million relative to FY 2022 primarily due 
to the annual update to the LTCH PPS standard Federal rate.

Q. Regulatory Review Cost Estimation

    If regulations impose administrative costs on private entities, 
such as the time needed to read and interpret a rule, we should 
estimate the cost associated with regulatory review. Due to the 
uncertainty involved with accurately quantifying the number of 
entities that would review the final rule, we assumed that the total 
number of timely pieces of correspondence on this year's proposed 
rule would be the number of reviewers of the final rule. We 
acknowledge that this assumption may understate or overstate the 
costs of reviewing the rule. It is possible that not all commenters 
reviewed this year's rule in detail, and it is also possible that 
some reviewers chose not to comment on the proposed rule. For these 
reasons, we believe that the number of past commenters would be a 
fair estimate of the number of reviewers of the final rule. We 
recognize that different types of entities are in many cases 
affected by mutually exclusive sections of the rule. Thus, for the 
purposes of our estimate we assume that each reviewer read 
approximately 50 percent of the proposed rule. Finally, in our 
estimates, we have used the 1,631 number of timely pieces of 
correspondence on the FY 2023 IPPS/LTCH PPS proposed rule as our 
estimate for the number of reviewers of the final rule. We continue 
to acknowledge the uncertainty involved with using this number, but 
we believe it is a fair estimate due to the variety of entities 
affected and the likelihood that some of them choose to rely (in 
full or in part) on press releases, newsletters, fact sheets, or 
other sources rather than the comprehensive review of preamble and 
regulatory text.
    Using the wage information from the BLS for medical and health 
service managers (Code 11-9111), we estimate that the cost of 
reviewing the final rule is $115.22 per hour, including overhead and 
fringe benefits (https://www.bls.gov/oes/current/oes_nat.htm). 
Assuming an average reading speed, we estimate that it would take 
approximately 30.06 hours for the staff to review half of this final 
rule. For each IPPS hospital or LTCH that reviews this final rule, 
the estimated cost is $3,463.34 (30.06 hours x $115.22). Therefore, 
we estimate that the total cost of reviewing this final rule is 
$5,648,700 ($3,463.34 x 1,631 reviewers).

II. Accounting Statements and Tables

A. Acute Care Hospitals

    As required by OMB Circular A-4 (available at https://www.whitehouse.gov/wp-content/uploads/legacy_drupal_files/omb/circulars/A4/a-4.pdf), in Table V. of this Appendix, we have 
prepared an accounting statement showing the classification of the 
expenditures associated with the provisions of this final rule as 
they relate to acute care hospitals. This table provides our best 
estimate of the change in Medicare payments to providers as a result 
of the changes to the IPPS presented in this final rule. All 
expenditures are classified as transfers to Medicare providers.
    As shown in Table V. of this Appendix, the net costs to the 
Federal Government associated with the policies in this final rule 
are estimated at $1.4 billion.
[GRAPHIC] [TIFF OMITTED] TR10AU22.248

B. LTCHs

    As discussed in section I.J. of this Appendix, the impact 
analysis of the payment rates and factors presented in this final 
rule under the LTCH PPS is projected to result in an increase in 
estimated aggregate LTCH PPS payments in FY 2023 relative to FY 2022 
of approximately $71 million based on the data for 339 LTCHs in our 
database that are subject to payment under the LTCH PPS. Therefore, 
as required by OMB Circular A-4 (available at https://www.whitehouse.gov/wp-content/uploads/legacy_drupal_files/omb/circulars/A4/a-4.pdf), in Table VI. of this Appendix, we have 
prepared an accounting statement showing the classification of the 
expenditures associated with the provisions of this final rule as 
they relate to the changes to the LTCH PPS. Table VI. of this 
Appendix provides our best estimate of the estimated change in 
Medicare payments under the LTCH PPS as a result of the payment 
rates and factors and other provisions presented in this final rule 
based on the data for the 339 LTCHs in our database. All 
expenditures are classified as transfers to Medicare providers (that 
is, LTCHs).
    As shown in Table VI. of this Appendix, the net cost to the 
Federal Government associated with the policies for LTCHs in this 
final rule are estimated at $71 million.
[GRAPHIC] [TIFF OMITTED] TR10AU22.249

III. Regulatory Flexibility Act (RFA) Analysis

    The RFA requires agencies to analyze options for regulatory 
relief of small entities. For purposes of the RFA, small entities 
include small businesses, nonprofit organizations, and small 
government jurisdictions. We estimate that most hospitals and most 
other providers and suppliers are small entities as that term is 
used in the RFA. The great majority of hospitals and most other 
health care providers and suppliers are small entities, either by 
being nonprofit organizations or by meeting the SBA definition of a 
small business (having

[[Page 49496]]

revenues of less than $8.0 million to $41.5 million in any 1 year). 
(For details on the latest standards for health care providers, we 
refer readers to page 38 of the Table of Small Business Size 
Standards for NAIC 622 found on the SBA website at https://www.sba.gov/sites/default/files/files/Size_Standards_Table.pdf.)
    For purposes of the RFA, all hospitals and other providers and 
suppliers are considered to be small entities. Because all hospitals 
are considered to be small entities for purposes of the RFA, the 
hospital impacts described in this final rule are impacts on small 
entities. Individuals and States are not included in the definition 
of a small entity. MACs are not considered to be small entities 
because they do not meet the SBA definition of a small business.
    HHS's practice in interpreting the RFA is to consider effects 
economically ``significant'' if greater than 5 percent of providers 
reach a threshold of 3 to 5 percent or more of total revenue or 
total costs. We believe that the provisions of this final rule 
relating to IPPS hospitals would have an economically significant 
impact on small entities as explained in this Appendix. Therefore, 
the Secretary has certified that this final rule will have a 
significant economic impact on a substantial number of small 
entities. For example, the majority of the 3,142 IPPS hospitals 
included in the impact analysis shown in ``Table I.--Impact Analysis 
of Proposed Changes to the IPPS for Operating Costs for FY 2023,'' 
on average are expected to see increases in the range of 2.6 
percent, primarily due to the hospital rate update, as discussed in 
section I.G. of this Appendix. On average, the rate update for these 
hospitals is estimated to be 4.2 percent.
    The 339 LTCH PPS hospitals included in the impact analysis shown 
in ``Table IV. Impact of Proposed Payment Rate and Policy Changes to 
LTCH PPS Payments and Policy Changes to LTCH PPS Payments for LTCH 
PPS Standard Payment Rate Cases for FY 2023 (Estimated FY 2023 
Payments Compared to Estimated FY 2022 Payments)'' on average are 
expected to see an increase of approximately 2.3 percent, primarily 
due to the 3.8 percent annual update to the LTCH PPS standard 
Federal payment rate for FY 2023 and the 1.2 percent decrease in 
high cost outlier payments as a percentage of total LTCH PPS 
standard Federal payment rate payments, as discussed in section I.J. 
of this Appendix.
    This final rule contains a range of policies. It provides 
descriptions of the statutory provisions that are addressed, 
identifies the proposed policies, and presents rationales for our 
decisions and, where relevant, alternatives that were considered. 
The analyses discussed in this Appendix and throughout the preamble 
of this final rule constitutes our regulatory flexibility analysis. 
We solicited public comments on our estimates and analysis of the 
impact of our proposals on small entities.

IV. Impact on Small Rural Hospitals

    Section 1102(b) of the Act requires us to prepare a regulatory 
impact analysis for any proposed or final rule that may have a 
significant impact on the operations of a substantial number of 
small rural hospitals. This analysis must conform to the provisions 
of section 604 of the RFA. With the exception of hospitals located 
in certain New England counties, for purposes of section 1102(b) of 
the Act, we define a small rural hospital as a hospital that is 
located outside of an urban area and has fewer than 100 beds. 
Section 601(g) of the Social Security Amendments of 1983 (Pub. L. 
98-21) designated hospitals in certain New England counties as 
belonging to the adjacent urban area. Thus, for purposes of the IPPS 
and the LTCH PPS, we continue to classify these hospitals as urban 
hospitals.
    As shown in Table I. in section I.G. of this Appendix, rural 
IPPS hospitals with 0-49 beds (358 hospitals) and 50-99 beds (201 
hospitals) are expected to experience an increase in payments from 
FY 2022 to FY 2023 of 0.9 percent and 1.3 percent, respectively, 
primarily driven by the hospital rate update and the expiration of 
the MDH provision, as discussed in section I.G of this Appendix. We 
refer readers to Table I. in section I.G. of this Appendix for 
additional information on the quantitative effects of the policy 
changes under the IPPS for operating costs.
    All rural LTCHs (17 hospitals) shown in Table IV. in section 
I.J. of this Appendix have less than 100 beds. These hospitals are 
expected to experience an increase in payments from FY 2022 to FY 
2023 of 2.2 percent, primarily due to the 3.8 percent annual update 
to the LTCH PPS standard Federal payment rate for FY 2023 and the 
projected 1.2 percent decrease in high cost outlier payments as a 
percentage of total LTCH PPS standard Federal payment rate payments, 
as discussed in section I.J. of this Appendix.

V. Unfunded Mandates Reform Act Analysis

    Section 202 of the Unfunded Mandates Reform Act of 1995 (Pub. L. 
104-4) also requires that agencies assess anticipated costs and 
benefits before issuing any rule whose mandates require spending in 
any 1 year of $100 million in 1995 dollars, updated annually for 
inflation. In 2022, that threshold level is approximately $165 
million. This final rule would not mandate any requirements that 
meet the threshold for State, local, or tribal governments, nor 
would it affect private sector costs.

VI. Executive Order 13132

    Executive Order 13132 establishes certain requirements that an 
agency must meet when it promulgates a proposed rule (and subsequent 
final rule) that imposes substantial direct requirement costs on 
state and local governments, preempts state law, or otherwise has 
federalism implications. This final rule would not have a 
substantial direct effect on state or local governments, preempt 
states, or otherwise have a federalism implication.

VII. Executive Order 13175

    Executive Order 13175 directs agencies to consult with Tribal 
officials prior to the formal promulgation of regulations having 
tribal implications. Section 1880(a) of the Act states that a 
hospital of the Indian Health Service, whether operated by such 
Service or by an Indian tribe or tribal organization, is eligible 
for Medicare payments so long as it meets all of the conditions and 
requirements for such payments which are applicable generally to 
hospitals. Consistent with section 1880(a) of the Act, this this 
final rule contains general provisions also applicable to hospitals 
and facilities operated by the Indian Health Service or Tribes or 
Tribal organizations under the Indian Self-Determination and 
Education Assistance Act.
    In the years prior to this rulemaking and during this 
rulemaking, we have engaged in consultation with Tribal officials on 
the methodology for determining uncompensated care payments to IHS 
and Tribal hospitals. Tribal officials have expressed concern over 
the long-term financial disruption to these hospitals if the use of 
low-income insured days as a proxy for the uncompensated care costs 
of IHS and Tribal hospitals were to be discontinued and data on 
uncompensated care costs from Worksheet S-10 were to be used to 
determine uncompensated care payments to IHS and Tribal hospitals. 
As discussed in section IV.D of the preamble of this final rule, 
beginning in FY 2023, we are discontinuing the use of low-income 
insured days as a proxy for the uncompensated care costs of IHS and 
Tribal hospitals and will begin using data on uncompensated care 
costs from Worksheet S-10 to determine uncompensated care payments 
to IHS and Tribal hospitals. However, as discussed in section IV.E. 
of the preamble of this final rule, after considering input received 
from our consultations with Tribal officials, we are also 
establishing a new supplemental payment for IHS/Tribal hospitals 
beginning in FY 2023 to avoid undue long-term financial disruption 
to these hospitals as a result of discontinuing the use of low-
income insured days as a proxy for uncompensated care.

VIII. Executive Order 12866

    In accordance with the provisions of Executive Order 12866, the 
Office of Management and Budget reviewed this final rule.

Appendix B: Recommendation of Update Factors for Operating Cost Rates 
of Payment for Inpatient Hospital Services

I. Background

    Section 1886(e)(4)(A) of the Act requires that the Secretary, 
taking into consideration the recommendations of MedPAC, recommend 
update factors for inpatient hospital services for each fiscal year 
that take into account the amounts necessary for the efficient and 
effective delivery of medically appropriate and necessary care of 
high quality. Under section 1886(e)(5) of the Act, we are required 
to publish update factors recommended by the Secretary in the 
proposed and final IPPS rules. Accordingly, this Appendix provides 
the recommendations for the update factors for the IPPS national 
standardized amount, the hospital-specific rate for SCHs and MDHs, 
and the rate-of-increase limits for certain hospitals excluded from 
the IPPS, as well as LTCHs. In prior years, we made a recommendation 
in the IPPS proposed rule

[[Page 49497]]

and final rule for the update factors for the payment rates for IRFs 
and IPFs. However, for FY 2023, consistent with our approach for FY 
2022, we are including the Secretary's recommendation for the update 
factors for IRFs and IPFs in separate Federal Register documents at 
the time that we announce the annual updates for IRFs and IPFs. We 
also discuss our response to MedPAC's recommended update factors for 
inpatient hospital services.

II. Inpatient Hospital Update for FY 2023

A. FY 2023 Inpatient Hospital Update

    As discussed in section IV.A. of the preamble to this final 
rule, for FY 2023, consistent with section 1886(b)(3)(B) of the Act, 
as amended by sections 3401(a) and 10319(a) of the Affordable Care 
Act, we are setting the applicable percentage increase by applying 
the following adjustments in the following sequence. Specifically, 
the applicable percentage increase under the IPPS is equal to the 
rate-of-increase in the hospital market basket for IPPS hospitals in 
all areas, subject to a reduction of one-quarter of the applicable 
percentage increase (prior to the application of other statutory 
adjustments; also referred to as the market basket update or rate-
of-increase (with no adjustments)) for hospitals that fail to submit 
quality information under rules established by the Secretary in 
accordance with section 1886(b)(3)(B)(viii) of the Act and a 
reduction of three-quarters of the applicable percentage increase 
(prior to the application of other statutory adjustments; also 
referred to as the market basket update or rate-of-increase (with no 
adjustments)) for hospitals not considered to be meaningful 
electronic health record (EHR) users in accordance with section 
1886(b)(3)(B)(ix) of the Act, and then subject to an adjustment 
based on changes in economy-wide productivity (the productivity 
adjustment). Section 1886(b)(3)(B)(xi) of the Act, as added by 
section 3401(a) of the Affordable Care Act, states that application 
of the productivity adjustment may result in the applicable 
percentage increase being less than zero. (We note that section 
1886(b)(3)(B)(xii) of the Act required an additional reduction each 
year only for FYs 2010 through 2019.)
    We note that, in compliance with section 404 of the MMA, in the 
FY 2022 IPPS/LTCH PPS final rule (86 FR 45194 through 45204), we 
replaced the 2014-based IPPS operating and capital market baskets 
with the rebased and revised 2018-based IPPS operating and capital 
market baskets beginning in FY 2022.
    In the FY 2023 IPPS/LTCH PPS proposed rule, in accordance with 
section 1886(b)(3)(B) of the Act, we proposed to base the proposed 
FY 2023 market basket update used to determine the applicable 
percentage increase for the IPPS on IGI's fourth quarter 2021 
forecast of the 2018-based IPPS market basket rate-of-increase with 
historical data through third quarter 2021, which was estimated to 
be 3.1 percent. In accordance with section 1886(b)(3)(B) of the Act, 
as amended by section 3401(a) of the Affordable Care Act, in section 
IV.B. of the preamble of the FY 2023 IPPS/LTCH PPS proposed rule, 
based on IGI's fourth quarter 2021 forecast, we proposed a 
productivity adjustment of 0.4 percentage point for FY 2023. We also 
proposed that if more recent data subsequently became available, we 
would use such data, if appropriate, to determine the FY 2023 market 
basket update and productivity adjustment for the FY 2023 IPPS/LTCH 
PPS final rule.
    In the FY 2023 IPPS/LTCH PPS proposed rule, based on IGI's 
fourth quarter 2021 forecast of the 2018-based IPPS market basket 
update and the productivity adjustment, depending on whether a 
hospital submits quality data under the rules established in 
accordance with section 1886(b)(3)(B)(viii) of the Act (hereafter 
referred to as a hospital that submits quality data) and is a 
meaningful EHR user under section 1886(b)(3)(B)(ix) of the Act 
(hereafter referred to as a hospital that is a meaningful EHR user), 
we presented four applicable percentage increases that could be 
applied to the standardized amount.
    In accordance with section 1886(b)(3)(B) of the Act, as amended 
by section 3401(a) of the Affordable Care Act, we are establishing 
the applicable percentages increase for the FY 2023 updates based on 
IGI's second quarter 2022 forecast of the 2018-based IPPS market 
basket of 4.1 percent and the productivity adjustment of 0.3 
percentage point, as discussed in section V.A of the preamble of 
this final rule, depending on whether a hospital submits quality 
data under the rules established in accordance with section 
1886(b)(3)(B)(viii) of the Act and is a meaningful EHR user under 
section 1886(b)(3)(B)(ix) of the Act, as shown in the table in this 
section.
[GRAPHIC] [TIFF OMITTED] TR10AU22.250

B. Update for SCHs for FY 2023

    Section 1886(b)(3)(B)(iv) of the Act provides that the FY 2023 
applicable percentage increase in the hospital-specific rate for 
SCHs equals the applicable percentage increase set forth in section 
1886(b)(3)(B)(i) of the Act (that is, the same update factor as for 
all other hospitals subject to the IPPS).
    Under current law, the MDH program is effective for discharges 
through September 30, 2022, as discussed in the FY 2019 IPPS/LTCH 
PPS final rule (83 FR 41429 through 41430). Therefore, under current 
law, the MDH program will expire at the end of FY 2022. We refer 
readers to section V.D. of the preamble of this final rule for 
further discussion of the expiration of the MDH program.
    As previously stated, the update to the hospital specific rate 
for SCHs is subject to section 1886(b)(3)(B)(i) of the Act, as 
amended by sections 3401(a) and 10319(a) of the Affordable Care Act. 
Accordingly, depending on whether a hospital submits quality data 
and is a meaningful EHR user, we are establishing the same four 
applicable percentage increases in the previous table for the 
hospital-specific rate applicable to SCHs.

C. FY 2023 Puerto Rico Hospital Update

    Because Puerto Rico hospitals are no longer paid with a Puerto 
Rico-specific standardized amount under the amendments to section 
1886(d)(9)(E) of the Act, there is no longer a need for us to make 
an update to the Puerto Rico standardized amount. Hospitals in 
Puerto Rico are now paid 100 percent of the national standardized 
amount and, therefore, are subject to the same update to the 
national standardized amount discussed under section IV.A.1. of the 
preamble of this final rule.
    In addition, as discussed in section IV.A.2. of the preamble of 
this final rule, section 602 of Public Law 114-113 amended section 
1886(n)(6)(B) of the Act to specify that subsection (d) Puerto Rico 
hospitals are eligible for incentive payments for the meaningful use 
of certified EHR technology, effective beginning FY 2016. In 
addition, section 1886(n)(6)(B) of the Act was amended to specify 
that the adjustments to the applicable percentage increase under 
section 1886(b)(3)(B)(ix) of the Act apply to

[[Page 49498]]

subsection (d) Puerto Rico hospitals that are not meaningful EHR 
users, effective beginning FY 2022.
    Accordingly, for FY 2022, section 1886(b)(3)(B)(ix) of the Act 
in conjunction with section 602(d) of Public Law 114-113 requires 
that any subsection (d) Puerto Rico hospital that is not a 
meaningful EHR user as defined in section 1886(n)(3) of the Act and 
not subject to an exception under section 1886(b)(3)(B)(ix) of the 
Act will have ``three-quarters'' of the applicable percentage 
increase (prior to the application of other statutory adjustments), 
or three-quarters of the applicable market basket rate-of-increase, 
reduced by 33\1/3\ percent. The reduction to three-quarters of the 
applicable percentage increase for subsection (d) Puerto Rico 
hospitals that are not meaningful EHR users increases to 66\2/3\ 
percent for FY 2023, and, for FY 2024 and subsequent fiscal years, 
to 100 percent. In the FY 2019 IPPS/LTCH PPS final rule, we 
finalized the payment reductions (83 FR 41674).
    Based on IGI's fourth quarter 2021 forecast of the 2018-based 
IPPS market basket update with historical data through third quarter 
2021, in the FY 2023 IPPS/LTCH PPS proposed rule, in accordance with 
section 1886(b)(3)(B) of the Act, as previously discussed, for 
Puerto Rico hospitals, we proposed a market basket update of 3.1 
percent and a productivity adjustment of 0.4 percentage point. 
Therefore, for FY 2023, depending on whether a Puerto Rico hospital 
is a meaningful EHR user, we stated that there are two possible 
applicable percentage increases that can be applied to the 
standardized amount. Based on these data, we determined the 
following proposed applicable percentage increases to the 
standardized amount for FY 2023 for Puerto Rico hospitals:
     For a Puerto Rico hospital that is a meaningful EHR 
user, we proposed an applicable percentage increase to the FY 2023 
operating standardized amount of 2.7 percent (that is, the FY 2023 
estimate of the proposed market basket rate-of-increase of 3.1 
percent less an adjustment of 0.4 percentage point for the proposed 
productivity adjustment).
     For a Puerto Rico hospital that is not a meaningful EHR 
user, we proposed an applicable percentage increase to the operating 
standardized amount of 1.15 percent (that is, the FY 2023 estimate 
of the proposed market basket rate-of-increase of 3.1 percent, less 
an adjustment of 1.55 percentage point (the proposed market basket 
rate-of-increase of 3.1 percent x 0.75 x (\2/3\) for failure to be a 
meaningful EHR user), and less an adjustment of 0.4 percentage point 
for the proposed productivity adjustment).
    As noted previously, we proposed that if more recent data 
subsequently became available, we would use such data, if 
appropriate, to determine the FY 2023 market basket update and the 
productivity adjustment for the FY 2023 IPPS/LTCH PPS final rule.
    As discussed in section V.A.1. of the preamble of this final 
rule, based on more recent data available for this FY 2023 IPPS/LTCH 
PPS final rule (that is, IGI's second quarter 2022 forecast of the 
2018-based IPPS market basket rate-of-increase with historical data 
through the first quarter of 2022), we estimate that the FY 2023 
market basket update used to determine the applicable percentage 
increase for the IPPS is 4.1 percent less a productivity adjustment 
of 0.3 percentage point. Therefore, in accordance with section 
1886(b)(3)(B) of the Act, for this final rule, for Puerto Rico 
hospitals the more recent update of the market basket update is 4.1 
percent and a productivity adjustment of 0.3 percentage point. For 
FY 2023, depending on whether a Puerto Rico hospital is a meaningful 
EHR user, there are two possible applicable percentage increases 
that can be applied to the standardized amount. Based on these data, 
we determined the following applicable percentage increases to the 
standardized amount for FY 2023 for Puerto Rico hospitals:
     For a Puerto Rico hospital that is a meaningful EHR 
user, an applicable percentage increase to the FY 2023 operating 
standardized amount of 3.8 percent (that is, the FY 2023 estimate of 
the market basket rate-of-increase of 4.1 percent less an adjustment 
of 0.3 percentage point for the productivity adjustment).
     For a Puerto Rico hospital that is not a meaningful EHR 
user, an applicable percentage increase to the operating 
standardized amount of 1.75 percent (that is, the FY 2023 estimate 
of the market basket rate-of-increase of 4.1 percent, less an 
adjustment of 2.05 percentage point (the market basket rate of-
increase of 4.1 percent x 0.75 x (\2/3\) for failure to be a 
meaningful EHR user), and less an adjustment of 0.3 percentage point 
for the productivity adjustment).

D. Update for Hospitals Excluded From the IPPS for FY 2023

    Section 1886(b)(3)(B)(ii) of the Act is used for purposes of 
determining the percentage increase in the rate-of-increase limits 
for children's hospitals, cancer hospitals, and hospitals located 
outside the 50 States, the District of Columbia, and Puerto Rico 
(that is, short-term acute care hospitals located in the U.S. Virgin 
Islands, Guam, the Northern Mariana Islands, and America Samoa). 
Section 1886(b)(3)(B)(ii) of the Act sets the percentage increase in 
the rate-of-increase limits equal to the market basket percentage 
increase. In accordance with Sec.  403.752(a) of the regulations, 
religious nonmedical health care institutions (RNHCIs) are paid 
under the provisions of Sec.  413.40, which also use section 
1886(b)(3)(B)(ii) of the Act to update the percentage increase in 
the rate-of-increase limits.
    Currently, children's hospitals, PPS-excluded cancer hospitals, 
RNHCIs, and short-term acute care hospitals located in the U.S. 
Virgin Islands, Guam, the Northern Mariana Islands, and American 
Samoa are among the remaining types of hospitals still paid under 
the reasonable cost methodology, subject to the rate-of-increase 
limits. In addition, in accordance with Sec.  412.526(c)(3) of the 
regulations, extended neoplastic disease care hospitals (described 
in Sec.  412.22(i) of the regulations) also are subject to the rate-
of-increase limits. As discussed in section VII. of the preamble of 
this final rule, we are finalizing to use the percentage increase in 
the 2018-based IPPS operating market basket to update the target 
amounts for children's hospitals, PPS-excluded cancer hospitals, 
RNHCIs, short-term acute care hospitals located in the U.S. Virgin 
Islands, Guam, the Northern Mariana Islands, and American Samoa, and 
extended neoplastic disease care hospitals for FY 2023 and 
subsequent fiscal years. Accordingly, for FY 2023, the rate-of-
increase percentage to be applied to the target amount for these 
children's hospitals, cancer hospitals, RNHCIs, extended neoplastic 
disease care hospitals, and short-term acute care hospitals located 
in the U.S. Virgin Islands, Guam, the Northern Mariana Islands, and 
American Samoa is the FY 2023 percentage increase in the 2018-based 
IPPS operating market basket. For this final rule, the current 
estimate of the IPPS operating market basket percentage increase for 
FY 2023 is 4.1 percent.

E. Update for LTCHs for FY 2023

    Section 123 of Public Law 106-113, as amended by section 307(b) 
of Public Law 106-554 (and codified at section 1886(m)(1) of the 
Act), provides the statutory authority for updating payment rates 
under the LTCH PPS.
    As discussed in section V.A. of the Addendum to this final rule, 
we are establishing an update to the LTCH PPS standard Federal 
payment rate for FY 2023 of 3.8 percent, consistent with section 
1886(m)(3) of the Act which provides that any annual update be 
reduced by the productivity adjustment described in section 
1886(b)(3)(B)(xi)(II) of the Act (that is, the productivity 
adjustment). Furthermore, in accordance with the LTCHQR Program 
under section 1886(m)(5) of the Act, we are reducing the annual 
update to the LTCH PPS standard Federal rate by 2.0 percentage 
points for failure of a LTCH to submit the required quality data. 
Accordingly, we are establishing an update factor of 1.038 in 
determining the LTCH PPS standard Federal rate for FY 2023. For 
LTCHs that fail to submit quality data for FY 2023, we are 
establishing an annual update to the LTCH PPS standard Federal rate 
of 1.8 percent (that is, the annual update for FY 2023 of 3.8 
percent less 2.0 percentage points for failure to submit the 
required quality data in accordance with section 1886(m)(5)(C) of 
the Act and our rules) by applying a update factor of 1.018 in 
determining the LTCH PPS standard Federal rate for FY 2023. (We note 
that, as discussed in section VII.D. of the preamble of this final 
rule, the update to the LTCH PPS standard Federal payment rate of 
3.8 percent for FY 2023 does not reflect any budget neutrality 
factors.)

III. Secretary's Recommendations

    MedPAC is recommending inpatient hospital rates be updated by 
the amount specified in current law. MedPAC's rationale for this 
update recommendation is described in more detail in this section of 
the final rule. As previously stated, section 1886(e)(4)(A) of the 
Act requires that the Secretary, taking into consideration the 
recommendations of MedPAC, recommend update factors for inpatient 
hospital services for each fiscal year

[[Page 49499]]

that take into account the amounts necessary for the efficient and 
effective delivery of medically appropriate and necessary care of 
high quality. Consistent with current law, depending on whether a 
hospital submits quality data and is a meaningful EHR user, we are 
recommending the four applicable percentage increases to the 
standardized amount listed in the table under section II. of this 
Appendix B. We are recommending that the same applicable percentage 
increases apply to SCHs.
    In addition to making a recommendation for IPPS hospitals, in 
accordance with section 1886(e)(4)(A) of the Act, we are 
recommending update factors for certain other types of hospitals 
excluded from the IPPS. Consistent with our policies for these 
facilities, we are recommending an update to the target amounts for 
children's hospitals, cancer hospitals, RNHCIs, short-term acute 
care hospitals located in the U.S. Virgin Islands, Guam, the 
Northern Mariana Islands, and American Samoa and extended neoplastic 
disease care hospitals of 4.1 percent.
    For FY 2023, consistent with policy set forth in section VII. of 
the preamble of this final rule, for LTCHs that submit quality data, 
we are recommending an update of 3.8 percent to the LTCH PPS 
standard Federal rate. For LTCHs that fail to submit quality data 
for FY 2023, we are recommending an annual update to the LTCH PPS 
standard Federal rate of 1.8 percent.

IV. MedPAC Recommendation for Assessing Payment Adequacy and Updating 
Payments in Traditional Medicare

    In its March 2022 Report to Congress, MedPAC assessed the 
adequacy of current payments and costs, and the relationship between 
payments and an appropriate cost base. MedPAC recommended an update 
to the hospital inpatient rates by the amount specified in current 
law. MedPAC stated that their payment adequacy indicators are mixed 
but generally positive, and MedPAC anticipates changes caused by the 
PHE to be temporary. MedPAC anticipates that their recommendation to 
update the IPPS payment rate by the amount specified under current 
law in 2023 will be enough to maintain beneficiaries' access to 
hospital inpatient and outpatient care and keep IPPS payment rates 
close to the cost of delivering high-quality care efficiently. We 
refer readers to the March 2022 MedPAC report, which is available 
for download at www.medpac.gov, for a complete discussion on these 
recommendations.
    Response: With regard to MedPAC's recommendation of an update to 
the hospital inpatient rates equal to the amount specified in 
current law, section 1886(b)(3)(B) of the Act sets the requirements 
for the FY 2023 applicable percentage increase. Therefore, 
consistent with the statute, we are establishing an applicable 
percentage increase for FY 2023 of 3.8 percent, provided the 
hospital submits quality data and is a meaningful EHR user 
consistent with these statutory requirements.
    We note that, because the operating and capital payments in the 
IPPS remain separate, we are continuing to use separate updates for 
operating and capital payments in the IPPS. The update to the 
capital rate is discussed in section III. of the Addendum to this 
final rule.

[FR Doc. 2022-16472 Filed 8-1-22; 4:15 pm]
BILLING CODE 4120-01-P