Medicare Program; FY 2024 Inpatient Psychiatric Facilities Prospective Payment System-Rate Update, 51054-51162 [2023-16083]

Agencies

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

[Federal Register Volume 88, Number 147 (Wednesday, August 2, 2023)]
[Rules and Regulations]
[Pages 51054-51162]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2023-16083]



[[Page 51053]]

Vol. 88

Wednesday,

No. 147

August 2, 2023

Part III





Department of Health and Human Services





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Centers for Medicare & Medicaid Services





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42 CFR Part 412





Medicare Program; FY2024 Inpatient Psychiatric Facilities Prospective 
Payment System--Rate Update; Final Rule

Federal Register / Vol. 88 , No. 147 / Wednesday, August 2, 2023 / 
Rules and Regulations

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DEPARTMENT OF HEALTH AND HUMAN SERVICES

Centers for Medicare & Medicaid Services

42 CFR Part 412

[CMS-1783-F]
RIN 0938-AV06


Medicare Program; FY 2024 Inpatient Psychiatric Facilities 
Prospective Payment System--Rate Update

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 updates the prospective payment rates, the 
outlier threshold, and the wage index for Medicare inpatient hospital 
services provided by Inpatient Psychiatric Facilities (IPF), which 
include psychiatric hospitals and excluded psychiatric units of an 
acute care hospital or critical access hospital. Additionally, this 
final rule rebases and revises the IPF market basket to reflect a 2021 
base year. These changes will be effective for IPF discharges occurring 
during the Fiscal Year (FY) beginning October 1, 2023 through September 
30, 2024 (FY 2024). In addition, this final rule discusses quality 
measures and reporting requirements under the Inpatient Psychiatric 
Facilities Quality Reporting (IPFQR) Program with changes beginning 
with the FY 2025 payment determination through changes beginning with 
the FY 2028 payment determination.

DATES: These regulations are effective on October 1, 2023.

FOR FURTHER INFORMATION CONTACT: Mollie Knight (410) 786-7948 or 
Bridget Dickensheets (410) 786-8670, for information regarding the 
market basket update or the labor-related share.
    Nick Brock (410) 786-5148 or Theresa Bean (410) 786-2287, for 
information regarding the regulatory impact analysis.
    Lauren Lowenstein-Turner, (410) 786-4507, for information regarding 
the inpatient psychiatric facilities quality reporting program.

SUPPLEMENTARY INFORMATION:

Availability of Certain Tables Exclusively Through the Internet on the 
CMS Website

    Addendum A to this final rule summarizes the fiscal year (FY) 2024 
IPF PPS payment rates, outlier threshold, cost of living adjustment 
factors (COLA) for Alaska and Hawaii, national and upper limit cost-to-
charge ratios, and adjustment factors. In addition, Addenda B to this 
final rule show the complete listing of ICD-10 Clinical Modification 
(CM) and Procedure Coding System (PCS) codes, the FY 2024 IPF PPS 
comorbidity adjustment, and electroconvulsive therapy (ECT) procedure 
codes. Addenda A and B to this final rule are available online at: 
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/tools.html.
    Tables setting forth the FY 2024 Wage Index for Urban Areas Based 
on Core Based Statistical Area (CBSA) Labor Market Areas and the FY 
2024 Wage Index Based on CBSA Labor Market Areas for Rural Areas are 
available exclusively through the internet, on the CMS website at 
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/IPFPPS/WageIndex.html.

I. Executive Summary

A. Purpose

    This final rule rebases and revises the market basket for the 
Inpatient Psychiatric Facility Prospective Payment System (IPF PPS) to 
reflect a 2021 base year, revises the labor-related share, and updates 
the prospective payment rates, the outlier threshold, and the wage 
index for Medicare inpatient hospital services provided by Inpatient 
Psychiatric Facilities (IPFs) for discharges occurring during FY 2024, 
(beginning October 1, 2023 through September 30, 2024). This rule also 
modifies our regulations to make it easier for hospitals to open new 
excluded psychiatric units paid under the IPF PPS. In addition, this 
final rule includes a summary of the public comments received to inform 
revisions to IPF PPS payments for FY 2025, as required by the 
Consolidated Appropriations Act, 2023 (hereafter referred to as CAA, 
2023) (Pub. L. 117- 328). Lastly, this final rule discusses quality 
measures and reporting requirements under the Inpatient Psychiatric 
Facilities Quality Reporting (IPFQR) Program.

B. Summary of the Major Provisions

1. Inpatient Psychiatric Facilities Prospective Payment System (IPF 
PPS)
    For the IPF PPS, we are finalizing our proposal to--
     Modify the regulations to allow the status of a hospital 
psychiatric unit to be changed from not excluded to excluded, and 
therefore paid under the IPF PPS, at any time during a cost reporting 
period if certain requirements are met.
     Rebase and revise the IPF market basket to reflect a 2021 
base year.
     Adjust the 2021-based IPF market basket update (3.5 
percent) for economy-wide productivity (0.2 percentage point) as 
required by section 1886(s)(2)(A)(i) of the Social Security Act (the 
Act), resulting in a final IPF payment rate update of 3.3 percent for 
FY 2024.
     Make technical rate setting updates: The IPF PPS payment 
rates will be adjusted annually for inflation, as well as statutory and 
other policy factors.
    This rule updates:
    ++ The IPF PPS Federal per diem base rate from $865.63 to $895.63.
    ++ The IPF PPS Federal per diem base rate for providers who failed 
to report quality data to $878.29.
    ++ The electroconvulsive therapy (ECT) payment per treatment from 
$372.67 to $385.58 .
    ++ The ECT payment per treatment for providers who failed to report 
quality data to $378.12.
    ++ The labor-related share from 77.4 percent to 78.7 percent.
    ++ The wage index budget-neutrality factor to 1.0016.
    ++ The fixed dollar loss threshold amount from $24,630 to $33,470 
to maintain estimated outlier payments at 2 percent of total estimated 
aggregate IPF PPS payments.
2. Inpatient Psychiatric Facilities Quality Reporting (IPFQR) Program
    For the IPFQR Program, we are finalizing our proposals to--
     Adopt the Facility Commitment to Health Equity measure 
beginning with the FY 2026 payment determination;
     Adopt the Screening for Social Drivers of Health measure 
beginning with voluntary reporting of calendar year (CY) 2024 data 
followed by mandatory reporting of CY 2025 data for the FY 2027 payment 
determination;
     Adopt the Screen Positive Rate for Social Drivers of 
Health measure beginning with voluntary reporting of CY 2024 data 
followed by mandatory reporting of CY 2025 data for the FY 2027 payment 
determination;
     Adopt the Psychiatric Inpatient Experience (PIX) survey to 
measure patient experience of care in the IPF setting beginning with 
voluntary reporting of CY 2025 data followed by mandatory reporting of 
CY 2026 data for the FY 2028 payment determination;
     Modify the Coronavirus disease 2019 (COVID-19) Vaccination 
Coverage Among Health Care Personnel (HCP) measure to align the measure 
with updated measure specifications developed by the Centers for 
Disease Control and Prevention (CDC), which

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address refinements reflecting the availability, and FDA authorization, 
of Moderna and Pfizer-BioNTech COVID-19 vaccines for use as booster 
doses, beginning with fourth quarter CY 2023 data for the FY 2025 
payment determination and, following this first single-quarter 
reporting period, reporting for the full calendar year beginning with 
CY 2024 data for the FY 2026 payment determination;
     Remove the following two measures beginning with the FY 
2025 payment determination and subsequent years:
    ++ Patients Discharged on Multiple Antipsychotic Medications with 
Appropriate Justification (HBIPS-5); and
    ++ Tobacco Use Brief Intervention Provided or Offered and Tobacco 
Use Brief Intervention Provided (TOB-2/2a) measure;
     Adopt a data validation pilot program starting with data 
submitted in CY 2025 and continuing until a full data validation 
program is proposed and adopted in future rulemaking; and
     Codify the IPFQR Program's procedural requirements related 
to statutory authority, participation and withdrawal, data submission, 
quality measure retention and removal, extraordinary circumstances 
exceptions, and public reporting at 42 CFR 412.433 Procedural 
requirements under the IPFQR Program.

C. Summary of Impacts
[GRAPHIC] [TIFF OMITTED] TR02AU23.000

II. Background

A. Overview of the Legislative Requirements of the IPF PPS

    Section 124 of the Medicare, Medicaid, and State Children's Health 
Insurance Program Balanced Budget Refinement Act of 1999 (BBRA) (Pub. 
L. 106-113) required the establishment and implementation of an IPF 
PPS. Specifically, section 124 of the BBRA mandated that the Secretary 
of the Department of Health and Human Services (the Secretary) develop 
a per diem payment perspective system (PPS) for inpatient hospital 
services furnished in psychiatric hospitals and excluded psychiatric 
units including an adequate patient classification system that reflects 
the differences in patient resource use and costs among psychiatric 
hospitals and excluded psychiatric units. ``Excluded psychiatric unit'' 
means a psychiatric unit of an acute care hospital or of a Critical 
Access Hospital (CAH), which is excluded from payment under the 
Inpatient Prospective Payment System (IPPS) or CAH payment system, 
respectively. These excluded psychiatric units will be paid under the 
IPF PPS.
    Section 405(g)(2) of the Medicare Prescription Drug, Improvement, 
and Modernization Act of 2003 (MMA) (Pub. L. 108-173) extended the IPF 
PPS to psychiatric distinct part units of CAHs.
    Sections 3401(f) and 10322 of the Patient Protection and Affordable 
Care Act (Pub. L. 111-148) as amended by section 10319(e) of that Act 
and by section 1105(d) of the Health Care and Education Reconciliation 
Act of 2010 (Pub. L. 111-152) (hereafter referred to jointly as ``the 
Affordable Care Act'') added subsection (s) to section 1886 of the 
Social Security Act (the Act).
    Section 1886(s)(1) of the Act titled, ``Reference to Establishment 
and Implementation of System,'' refers to section 124 of the BBRA, 
which relates to the establishment of the IPF PPS.
    Section 1886(s)(2)(A)(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 IPF PPS for the rate year (RY) beginning in 2012 (that 
is, a RY that coincides with a FY) and each subsequent RY.
    Section 1886(s)(2)(A)(ii) of the Act required the application of an 
``other adjustment'' that reduced any update to an IPF PPS base rate by 
a percentage point amount specified in section 1886(s)(3) of the Act 
for the RY beginning in 2010 through the RY beginning in 2019. As noted 
in the FY 2020 IPF PPS final rule, for the RY beginning in 2019, 
section 1886(s)(3)(E) of the Act required that the other adjustment 
reduction be equal to 0.75 percentage point; that was the final year 
the statute required the application of this adjustment. Because FY 
2021 was a RY beginning in 2020, FY 2021 was the first-year section 
1886(s)(2)(A)(ii) of the Act did not apply since its enactment.
    Sections 1886(s)(4)(A) through (D) of the Act require that for RY 
2014 and each subsequent RY, IPFs that fail to report required quality 
data with respect to such a RY will have their annual update to a 
standard Federal rate for discharges reduced by 2.0 percentage points. 
This may result in an annual update being less than 0.0 for a RY, and 
may result in payment rates for the upcoming RY being less than such 
payment rates for the preceding RY. Any reduction for failure to report 
required quality data will apply only to the RY involved, and the 
Secretary will not consider such reduction in computing the payment 
amount for a subsequent RY. Section 4125 of division FF, title IV, 
subtitle C, the CAA, 2023 requires that not later than FY 2028 each IPF 
will submit data through the use of a standardized assessment 
instrument which includes data on functional status; cognitive 
function; special services treatments, and interventions for 
psychiatric conditions; impairments; and other categories deemed 
appropriate. In addition, section 4125 of the CAA, 2023 requires that a 
patients' perspective of care quality measure be added to the IPFQR 
Program not later than for FY 2031. Information regarding the newly

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adopted Psychiatric Inpatient Experience (PIX) survey measure is 
provided in section VI.D.5 of this final rule.
    Section 4125 of the CAA, 2023 also requires revisions to the 
Medicare prospective payment system (PPS) for psychiatric hospitals and 
psychiatric units. Specifically, section 4125(a) of the CAA, 2023 
amends section 1886(s) of the Act by adding a new paragraph (5) that 
requires the Secretary to collect data and information beginning no 
later than October 1, 2023, as the Secretary determines appropriate, to 
inform revisions to IPF PPS payments. In addition, the Secretary is 
required to implement revisions to the methodology for determining the 
payment rates under the IPF PPS for FY 2025 as the Secretary determines 
appropriate.
    To implement and periodically update the IPF PPS, we have published 
various proposed and final rules and notices in the Federal Register. 
For more information regarding these documents, see the CMS website at 
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/?redirect=/InpatientPsychFacilPPS/.

B. Overview of the IPF PPS

    On November 15, 2004, we published the IPF PPS final rule in the 
Federal Register (69 FR 66922). The November 2004 IPF PPS final rule 
established the IPF PPS, as required by section 124 of the BBRA and 
codified at 42 CFR part 412, subpart N. The November 2004 IPF PPS final 
rule set forth the Federal per diem base rate for the implementation 
year (the 18-month period from January 1, 2005 through June 30, 2006), 
and provided payment for the inpatient operating and capital costs to 
IPFs for covered psychiatric services they furnish (that is, routine, 
ancillary, and capital costs, but not costs of approved educational 
activities, bad debts, and other services or items that are outside the 
scope of the IPF PPS). Covered psychiatric services include services 
for which benefits are provided under the fee-for-service Part A 
(Hospital Insurance Program) of the Medicare program.
    The IPF PPS established the Federal per diem base rate for each 
patient day in an IPF derived from the national average daily routine 
operating, ancillary, and capital costs in IPFs in FY 2002. The average 
per diem cost was updated to the midpoint of the first year under the 
IPF PPS, standardized to account for the overall positive effects of 
the IPF PPS payment adjustments, and adjusted for budget-neutrality.
    The Federal per diem payment under the IPF PPS is comprised of the 
Federal per diem base rate described previously and certain patient- 
and facility-level payment adjustments for characteristics that were 
found in the regression analysis to be associated with statistically 
significant per diem cost differences; with statistical significance 
defined as p less than 0.05. A complete discussion of the regression 
analysis that established the IPF PPS adjustment factors can be found 
in the November 2004 IPF PPS final rule (69 FR 66933 through 66936).
    The patient-level adjustments include age, Diagnosis-Related Group 
(DRG) assignment, and comorbidities, as well as adjustments to reflect 
higher per diem costs at the beginning of a patient's IPF stay and 
lower costs for later days of the stay. Facility-level adjustments 
include adjustments for the IPF's wage index, rural location, teaching 
status, a cost-of-living adjustment for IPFs located in Alaska and 
Hawaii, and an adjustment for the presence of a qualifying emergency 
department (ED).
    The IPF PPS has additional payment policies for outlier cases, 
interrupted stays, and a per treatment payment for patients who undergo 
ECT. During the IPF PPS mandatory 3-year transition period, stop-loss 
payments were also provided; however, since the transition ended as of 
January 1, 2008, these payments are no longer available.

C. Annual Requirements for Updating the IPF PPS

    Section 124 of the BBRA did not specify an annual rate update 
strategy for the IPF PPS and was broadly written to give the Secretary 
discretion in establishing an update methodology. In the November 2004 
IPF PPS final rule (69 FR 66922), we implemented the IPF PPS using the 
following update strategy:
     Calculate the final Federal per diem base rate to be 
budget-neutral for the 18-month period of January 1, 2005 through June 
30, 2006.
     Use a July 1 through June 30 annual update cycle.
     Allow the IPF PPS first update to be effective for 
discharges on or after July 1, 2006 through June 30, 2007.
    In developing the IPF PPS, and to ensure that the IPF PPS can 
account adequately for each IPF's case-mix, we performed an extensive 
regression analysis of the relationship between the per diem costs and 
certain patient and facility characteristics to determine those 
characteristics associated with statistically significant cost 
differences on a per diem basis. That regression analysis is described 
in detail in our November 28, 2003 IPF PPS proposed rule (68 FR 66923; 
66928 through 66933) and our November 15, 2004 IPF PPS final rule (69 
FR 66933 through 66960). For characteristics with statistically 
significant cost differences, we used the regression coefficients of 
those variables to determine the size of the corresponding payment 
adjustments.
    In the November 2004 IPF PPS final rule, we explained the reasons 
for delaying an update to the adjustment factors, derived from the 
regression analysis, including waiting until we have IPF PPS data that 
yields as much information as possible regarding the patient-level 
characteristics of the population that each IPF serves. We indicated 
that we did not intend to update the regression analysis and the 
patient-level and facility-level adjustments until we complete that 
analysis. Until that analysis is complete, we stated our intention to 
publish a notice in the Federal Register each spring to update the IPF 
PPS (69 FR 66966).
    On May 6, 2011, we published a final rule in the Federal Register 
titled, ``Inpatient Psychiatric Facilities Prospective Payment System--
Update for Rate Year Beginning July 1, 2011 (RY 2012)'' (76 FR 26432), 
which changed the payment rate update period to a RY that coincides 
with a FY update. Therefore, final rules are now published in the 
Federal Register in the summer to be effective on October 1st. When 
proposing changes in IPF payment policy, a proposed rule would be 
issued in the spring and the final rule in the summer to be effective 
on October 1st. For a detailed list of updates to the IPF PPS, we refer 
readers to our regulations at 42 CFR 412.428.
    The most recent IPF PPS annual update was published in a final rule 
on July 29, 2022 in the Federal Register titled, ``Medicare Program; FY 
2023 Inpatient Psychiatric Facilities Prospective Payment System--Rate 
Update and Quality Reporting--Request for Information'' (87 FR 46846), 
which updated the IPF PPS payment rates for FY 2023. That final rule 
updated the IPF PPS Federal per diem base rates that were published in 
the FY 2022 IPF PPS Rate Update final rule (86 FR 42608) in accordance 
with our established policies.

III. Analysis of and Responses to Public Comments

    We received 2,506 public comments that pertain to proposed IPF PPS 
payment policies, requests for information, and the proposed updates to 
the IPFQR Program. Comments were

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from Inpatient Psychiatric Facilities, health systems, national and 
state level provider and patient advocacy organizations, the Medicare 
Payment Advisory Commission (MedPAC), and individuals. We reviewed each 
comment and grouped related comments, after which we placed them in 
categories based on subject matter or section(s) of the regulation 
affected. Summaries of the public comments received and our responses 
to those comments are provided in the appropriate sections in the 
preamble of this final rule.

IV. Provisions of the FY 2024 IPF PPS Final Rule and Responses to 
Comments

A. Rebasing and Revising of the Market Basket for the IPF PPS

    1. Background
    Originally, the input price index used to develop the IPF PPS was 
the Excluded Hospital with Capital market basket. This market basket 
was based on 1997 Medicare cost reports for Medicare-participating 
inpatient rehabilitation facilities (IRFs), IPFs, long-term care 
hospitals (LTCHs), cancer hospitals, and children's hospitals. Although 
``market basket'' technically describes the mix of goods and services 
used in providing health care at a given point in time, this term is 
also commonly used to denote the input price index (that is, cost 
category weights and price proxies) derived from that market basket. 
Accordingly, the term ``market basket,'' as used in this document, 
refers to an input price index.
    Since the IPF PPS inception, the market basket used to update IPF 
PPS payments has been rebased and revised to reflect more recent data 
on IPF cost structures. We last rebased and revised the market basket 
applicable to the IPF PPS in the FY 2020 IPF PPS final rule (84 FR 
38426 through 38447), where we adopted a 2016-based IPF market basket. 
The 2016-based IPF market basket used Medicare cost report data for 
both Medicare-participating freestanding psychiatric hospitals and 
hospital-based psychiatric units. References to the historical market 
baskets used to update IPF PPS payments are listed in the FY 2016 IPF 
PPS final rule (80 FR 46656). For the FY 2024 IPF PPS proposed rule, we 
proposed to rebase and revise the IPF market basket to reflect a 2021 
base year.
2. Overview of the 2021-Based IPF Market Basket
    The 2021-based IPF market basket is a fixed-weight, Laspeyres-type 
price index. A Laspeyres price index 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.
    The index itself is constructed in three steps. First, a base 
period is selected (in the proposed rule, we proposed to use 2021 as 
the base period) and total base period costs are estimated for a set of 
mutually exclusive and exhaustive cost categories. Each category is 
calculated as a proportion of total costs. These proportions are called 
cost weights. Second, each cost category is matched to an appropriate 
price or wage variable, referred to as a price proxy. In nearly every 
instance, these price proxies are derived from publicly available 
statistical series that are published on a consistent schedule 
(preferably at least on a quarterly basis). Finally, the cost weight 
for each cost category is multiplied by the level of its respective 
price proxy. The sum of these products (that is, the cost weights 
multiplied by their price index levels) for all cost categories yields 
the composite index level of the market basket in a given period. 
Repeating this step for other periods produces a series of market 
basket levels over time. Dividing an index level for a given period by 
an index level for an earlier period produces a rate of growth in the 
input price index over that timeframe.
    As noted, the market basket is described as a fixed-weight index 
because it represents the change in price over time of a constant mix 
(quantity and intensity) of goods and services needed to provide IPF 
services. The effects on total costs resulting from changes in the mix 
of goods and services purchased subsequent to the base period are not 
measured. For example, an IPF hiring more nurses after the base period 
to accommodate the needs of patients will increase the volume of goods 
and services purchased by the IPF but will not be factored into the 
price change measured by a fixed-weight IPF market basket. Only when 
the index is rebased will changes in the quantity and intensity be 
captured, with those changes being reflected in the cost weights. 
Therefore, we rebase the market basket periodically so that the cost 
weights reflect recent changes in the mix of goods and services that 
IPFs purchase to furnish inpatient care between base periods.
3. Rebasing and Revising of the IPF Market Basket
    As discussed in the FY 2020 IPF PPS final rule (84 FR 38426 through 
38447), the 2016-based IPF market basket reflects the Medicare cost 
reports for both freestanding and hospital-based IPFs. Beginning with 
FY 2024, we proposed to rebase and revise the IPF market basket to a 
2021 base year reflecting the 2021 Medicare cost report data submitted 
by both freestanding and hospital-based IPFs. We provide a detailed 
description of our proposed methodology used to develop the 2021-based 
IPF market basket below. This proposed methodology is generally similar 
to the methodology used to develop the 2016-based IPF market basket. We 
solicited public comment on our proposed methodology for developing the 
2021-based IPF market basket.
    Comment: Several commenters supported CMS's proposal to rebase and 
revise the market basket to reflect more recent data, noting that the 
changes in the cost weights were consistent with their expectations or 
experience. One commenter, however, proposed that CMS wait to rebase 
the IPF market basket until FY 2022 data is available. The commenter 
stated that, due to the increased demand for hospital care during the 
initial year following the outbreak of COVID-19 in the United States, 
they assume that a base year of FY 2021 would not necessarily reflect 
costs in FY 2024. Though inflation was particularly high during FY 
2021, the commenter noted that FY 2022 would be further removed from 
the initial outbreak of COVID-19 in the United States and the massive 
changes in healthcare that occurred during that time. Similarly, one 
commenter supported the proposal to rebase but recommended CMS plan to 
rebase and revise the market basket and labor-related share to reflect 
a 2023 base year to fully incorporate the cost structures from the 
Public Health Emergency (PHE) as well as the evolving hospital 
workforce shortage.
    Response: We appreciate the commenters' support regarding the 
proposed IPF market basket. For the proposed rebasing and revising, we 
used the most current and complete set of Medicare cost report data 
(2021) at the time of rulemaking to determine the major base year cost 
weights (Wages and Salaries, Employee Benefits, Contract Labor, 
Professional Liability Insurance, Pharmaceuticals, Home Office/Related 
Organization Contract Labor, and Capital).
    As stated in the FY 2024 IPF PPS proposed rule (88 FR 21241), many 
commenters expressed concern in response to the FY 2023 IPF PPS 
proposed rule, in which we did not propose to rebase the IPF market 
basket.

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The commenters stated at that time that the 2016-based IPF market 
basket did not reflect the current costs of IPFs, particularly the use 
of contract labor. Therefore, based on the typical timeframe for 
rebasing the market baskets and in response to commenters' concerns 
expressed in FY 2023 IPF rulemaking, we proposed to rebase and revise 
the IPF market basket for FY 2024. We understand the commenters' 
concerns that the impact of the PHE may have resulted in increased 
costs compared to 2016. However, we believe it is appropriate to rebase 
the market basket regularly and to reflect more recent IPF cost 
structures. It has been our longstanding practice to rebase the IPF 
market basket (as well as other CMS market baskets) on a regular basis 
to ensure it reflects a more up-to-date input cost structure of IPFs so 
that the price change in the market basket best reflects input prices 
faced by IPFs. Because complete 2022 IPF Medicare cost report data is 
currently unavailable, we believe it is more appropriate to update the 
base year cost weights to 2021 to reflect changes over this period 
rather than to delay the rebasing for another year or two in order to 
use 2022 or 2023 Medicare cost report data as suggested by the 
commenter. We regularly rebase every 4 to 5 years because more recent 
data is typically more reflective of IPF cost structures. Therefore, we 
are using the most recent cost report data we have, which is 2021 cost 
report data, as it is more reflective of IPF cost structures than 2016 
data. For example, the 2021-based IPF market basket reflects the higher 
compensation cost weight (as compared to the 2016-based IPF market 
basket) as a result of an increase in the contract labor cost weight 
(calculated using the 2021 Medicare cost report data) as noted by the 
commenters in response to the FY 2023 IPF proposed rule (87 FR 46849). 
Additionally, we will continue to monitor the Medicare cost report data 
to assess whether a more frequent rebasing of the IPF market basket is 
appropriate through future notice and comment rulemaking.
    Final Decision: We are finalizing our proposal to rebase the IPF 
market basket to reflect a 2021 base year for FY 2024.
    We provide a summary of the more detailed public comments received 
on our proposed methodology for developing the 2021-based IPF market 
basket and our responses in the following sections.
a. Development of Cost Categories and Weights for the 2021-Based IPF 
Market Basket
(1) Use of Medicare Cost Report Data
    We proposed a 2021-based IPF market basket that consists of seven 
major cost categories and a residual derived from the 2021 Medicare 
cost reports (CMS Form 2552-10, OMB No. 0938-0050) for freestanding and 
hospital-based IPFs. The seven major cost categories are Wages and 
Salaries, Employee Benefits, Contract Labor, Pharmaceuticals, 
Professional Liability Insurance (PLI), Home Office/Related 
Organization Contract Labor, and Capital. The cost reports include 
providers whose cost reporting period began on or after October 1, 2020 
and before October 1, 2021. As noted previously, the current IPF market 
basket is based on 2016 Medicare cost reports and therefore, reflects 
the 2016 cost structure for IPFs. As described in the FY 2023 IPF PPS 
final rule (87 FR 46849), we received comments on the FY 2023 IPF PPS 
proposed rule (87 FR 19418 through 19419) where stakeholders expressed 
concern that the proposed market basket update inadequately reflected 
the input price inflation experienced by IPFs, particularly as a result 
of the COVID-19 PHE. These commenters stated that the PHE, along with 
inflation, has significantly driven up operating costs. Specifically, 
some commenters noted changes to labor markets that led to the use of 
more contract labor, a trend that we verified in analyzing the Medicare 
cost report data through 2021. Therefore, we believe it is appropriate 
to incorporate more recent data to reflect updated cost structures for 
IPFs, and so we proposed to use 2021 as the base year, because we 
believe that the Medicare cost reports for this year represent the most 
recent complete set of Medicare cost report data available for 
developing the proposed IPF market basket at the time of this 
rulemaking. Given the potential impact of the PHE on the Medicare cost 
report data, we will continue to monitor these data going forward, and 
any changes to the IPF market basket will be proposed in future 
rulemaking.
    Similar to the Medicare cost report data used to develop the 2016-
based IPF market basket, the Medicare cost report data for 2021 show 
large differences between some providers' Medicare length of stay (LOS) 
and total facility LOS. Our goal has always been to measure cost 
weights that are reflective of case mix and practice patterns 
associated with providing services to Medicare beneficiaries. 
Therefore, we proposed to limit our selection of Medicare cost reports 
used in the 2021-based IPF market basket to those facilities that had a 
Medicare LOS within a comparable range of their total facility average 
LOS. The Medicare average LOS for freestanding IPFs is calculated from 
data reported on line 14 of Worksheet S-3, part I. The Medicare average 
LOS for hospital-based IPFs is calculated from data reported on line 16 
of Worksheet S-3, part I. To derive the 2021-based IPF market basket, 
for those IPFs with an average facility LOS of greater than or equal to 
15 days, we proposed to include IPFs where the Medicare LOS is within 
50 percent (higher or lower) of the average facility LOS. For those 
IPFs whose average facility LOS is less than 15 days, we proposed to 
include IPFs where the Medicare LOS is within 95 percent (higher or 
lower) of the facility LOS. We proposed to apply this LOS edit to the 
data for IPFs to exclude providers that serve a population whose LOS 
will indicate that the patients served are not consistent with a LOS of 
a typical Medicare patient. This is the same LOS edit applied to the 
2016-based IPF market basket.
    Applying these trims to the approximate 1,370 total cost reports 
(freestanding and hospital-based) resulted in roughly 1,250 IPF 
Medicare cost reports with an average Medicare LOS of 13 days, average 
facility LOS of 10 days, and Medicare utilization (as measured by 
Medicare inpatient IPF days as a percentage of total facility days) of 
16 percent. Providers excluded from the 2021-based IPF market basket 
(about 120 Medicare cost reports) had an average Medicare LOS of 21 
days, average facility LOS of 41 days, and a Medicare utilization of 3 
percent. Of those excluded, about 62 percent of these were freestanding 
providers; on the other hand, freestanding providers represent about 38 
percent of all IPFs. We note that 70 percent of those excluded from the 
2016-based IPF market basket using this LOS edit were freestanding 
providers.
    We then proposed to use the cost reports for IPFs that met this 
requirement to calculate the costs for the seven major cost categories 
(Wages and Salaries, Employee Benefits, Contract Labor, Professional 
Liability Insurance, Pharmaceuticals, Home Office/Related Organization 
Contract Labor, and Capital) for the market basket. These are the same 
categories used for the 2016-based IPF market basket. Also, as 
described in section IV.A.3.a.(4) of this final rule, and as done for 
the 2016-based IPF market basket, we proposed to use the Medicare cost 
report data to calculate the detailed

[[Page 51059]]

capital cost weights for the Depreciation, Interest, Lease, and Other 
Capital-related cost categories. We also proposed to rename the Home 
Office Contract Labor cost category to the Home Office/Related 
Organization Contract Labor cost category to be more consistent with 
the Medicare cost report instructions.
    Similar to the 2016-based IPF market basket major cost weights, for 
the majority of the 2021-based IPF market basket cost weights, we 
proposed to divide the costs for each cost category by total Medicare 
allowable costs (routine, ancillary and capital)--costs that are 
eligible for payment through the IPF PPS (we noted that we use total 
facility medical care costs as the denominator to derive both the PLI 
and Home Office/Related Organization Contract Labor cost weights). We 
next describe our proposed methodology for deriving the cost levels 
used to derive the 2021-based IPF market basket.
(a) Total Medicare Allowable Costs
    For freestanding IPFs, we proposed that total Medicare allowable 
costs would be equal to the sum of total costs for the Medicare 
allowable cost centers as reported on Worksheet B, part I, column 26, 
lines 30 through 35, 50 through 76 (excluding 52 and 75), 90 through 
91, and 93.
    For hospital-based IPFs, we proposed that total Medicare allowable 
costs would be equal to the total costs for the IPF inpatient unit 
after the allocation of overhead costs (Worksheet B, part I, column 26, 
line 40) and a proportion of total ancillary costs reported on 
Worksheet B, part I, column 26, lines 50 through 76 (excluding 52 and 
75), 90 through 91, and 93.
    We proposed to calculate total ancillary costs attributable to the 
hospital-based IPF by first deriving an ``IPF ancillary ratio'' for 
each ancillary cost center. The IPF ancillary ratio is defined as the 
ratio of IPF Medicare ancillary costs for the cost center (as reported 
on Worksheet D-3, column 3 for hospital-based IPFs) to total Medicare 
ancillary costs for the cost center (equal to the sum of Worksheet D-3, 
column 3 for all relevant PPSs [that is, IPPS, IRF, IPF and skilled 
nursing facility (SNF)]). For example, if hospital-based IPF Medicare 
laboratory costs represent about 2 percent of the total Medicare 
laboratory costs for the entire facility, then the IPF ancillary ratio 
for laboratory costs would be 2 percent. We believe it is appropriate 
to use only a portion of the ancillary costs in the market basket cost 
weight calculations since the hospital-based IPF only utilizes a 
portion of the facility's ancillary services. We believe the ratio of 
reported IPF Medicare costs to reported total Medicare costs provides a 
reasonable estimate of the ancillary services utilized, and costs 
incurred, by the hospital-based IPF. We proposed that this IPF 
ancillary ratio for each cost center is also used to calculate Wages 
and Salaries and Capital costs as described below.
    Then, for each ancillary cost center, we proposed to multiply the 
IPF ancillary ratio for the given cost center by the total facility 
ancillary costs for that specific cost center (as reported on Worksheet 
B, part I, column 26) to derive IPF ancillary costs. For example, the 2 
percent IPF ancillary ratio for laboratory cost center would be 
multiplied by the total ancillary costs for laboratory (Worksheet B, 
part I, column 26, line 60). The IPF ancillary costs for each cost 
center are then added to total costs for the IPF inpatient unit after 
the allocation of overhead costs (Worksheet B, part I, column 26, line 
40) to derive total Medicare allowable costs.
    We proposed to use these methods to derive levels of total Medicare 
allowable costs for IPF providers. This is the same methodology used 
for the 2016-based IPF market basket. We proposed that these total 
Medicare allowable costs for the IPF will be the denominator for the 
cost weight calculations for the Wages and Salaries, Employee Benefits, 
Contract Labor, Pharmaceuticals, and Capital cost weights. With this 
work complete, we then set about deriving cost levels for the seven 
major cost categories and then derive a residual cost weight reflecting 
all other costs not classified.
(b) Wages and Salaries Costs
    For freestanding IPFs, we proposed to derive Wages and Salaries 
costs as the sum of routine inpatient salaries (Worksheet A, column 1, 
lines 30 through 35), ancillary salaries (Worksheet A, column 1, lines 
50 through 76 (excluding 52 and 75), 90 through 91, and 93), and a 
proportion of overhead (or general service cost centers in the Medicare 
cost reports) salaries. Since overhead salary costs are attributable to 
the entire IPF, we only include the proportion attributable to the 
Medicare allowable cost centers. We proposed to estimate the proportion 
of overhead salaries that are attributed to Medicare allowable costs 
centers by multiplying the ratio of Medicare allowable area salaries 
(Worksheet A, column 1, lines 30 through 35, 50 through 76 (excluding 
52 and 75), 90 through 91, and 93) to total non-overhead salaries 
(Worksheet A, column 1, line 200 less Worksheet A, column 1, lines 4 
through 18) times total overhead salaries (Worksheet A, column 1, lines 
4 through 18). This is a similar methodology as used in the 2016-based 
IPF market basket.
    For hospital-based IPFs, we proposed to derive Wages and Salaries 
costs as the sum of the following salaries attributable to the 
hospital-based IPF: Inpatient routine salary costs (Worksheet A, column 
1, line 40); overhead salary costs; ancillary salary costs; and a 
portion of overhead salary costs attributable to the ancillary 
departments.
(i) Overhead Salary Costs
    We proposed to calculate the portion of overhead salary cost 
attributable to hospital-based IPFs by first calculating an IPF 
overhead salary ratio, which is equal to the ratio of total facility 
overhead salaries (as reported on Worksheet A, column 1, lines 4-18) to 
total facility noncapital overhead costs (as reported on Worksheet A, 
column 1 and 2, lines 4-18). We then proposed to multiply this IPF 
overhead salary ratio by total noncapital overhead costs (sum of 
Worksheet B, part I, columns 4 through 18, line 40, less Worksheet B, 
part II, columns 4 through 18, line 40). This methodology assumes the 
proportion of total costs related to salaries for the overhead cost 
center is similar for all inpatient units (that is, acute inpatient or 
inpatient psychiatric).
(ii) Ancillary Salary Costs
    We proposed to calculate hospital-based IPF ancillary salary costs 
for a specific cost center (Worksheet A, column 1, lines 50 through 76 
(excluding 52 and 75), 90 through 91, and 93) as salary costs from 
Worksheet A, column 1, multiplied by the IPF ancillary ratio for each 
cost center as described in section IV.A.3.a.(1)(a) of this final rule. 
The sum of these costs represents hospital-based IPF ancillary salary 
costs.
(iii) Overhead Salary Costs for Ancillary Cost Centers
    We proposed to calculate the portion of overhead salaries 
attributable to each ancillary department (lines 50 through 76 
(excluding 52 and 75), 90 through 91, and 93) by first calculating 
total noncapital overhead cost attributable to each specific ancillary 
department (sum of Worksheet B, part I, columns 4-18, less Worksheet B, 
part II, column 26). We then identify the portion of these total 
noncapital overhead cost for each ancillary department that is 
attributable to the hospital-based IPF by multiplying these costs by 
the IPF ancillary ratio as described in section IV.A.3.a.(1)(a) of

[[Page 51060]]

this final rule. We then sum these estimated IPF Medicare allowable 
noncapital overhead costs for all ancillary departments (cost centers 
50 through 76, 90 through 91, and 93). Finally, we then identify the 
portion of these IPF Medicare allowable noncapital overhead cost that 
are attributable to Wages and Salaries by multiplying these costs by 
the IPF overhead salary ratio as described in section 
IV.A.3.a.(1)(b)(i) of this final rule. This is the same methodology 
used to derive the 2016-based IPF market basket.
(c) Employee Benefits Costs
    Effective with the implementation of CMS Form 2552-10, we began 
collecting Employee Benefits and Contract Labor data on Worksheet S-3, 
part V.
    For the 2021 Medicare cost report data, the majority of IPF 
providers did not report data on Worksheet S-3, part V. Two percent of 
freestanding IPFs and roughly 48 percent of hospital-based IPFs 
reported Employee Benefits data on Worksheet S-3, part V. Two percent 
of freestanding IPFs and roughly 13 percent of hospital-based IPFs 
reported Contract Labor data on Worksheet S-3, part V. We continue to 
encourage all providers to report these data on the Medicare cost 
report.
    For freestanding IPFs, we proposed that Employee Benefits cost 
would be equal to the data reported on Worksheet S-3, part V, column 2, 
line 2. We note that while not required to do so, freestanding IPFs 
also may report Employee Benefits data on Worksheet S-3, part II, which 
is applicable to only IPPS providers. Similar to the method for the 
2016-based IPF market basket, for those freestanding IPFs that report 
Worksheet S-3, part II, data, but not Worksheet S-3, part V, we 
proposed to use the sum of Worksheet S-3, part II, lines 17, 18, 20, 
and 22, to derive Employee Benefits costs.
    For hospital-based IPFs, we proposed to calculate total benefit 
cost as the sum of inpatient unit benefit cost, a portion of ancillary 
departments benefit costs, and a portion of overhead benefits 
attributable to both the routine inpatient unit and the ancillary 
departments. For those hospital-based IPFs that report Worksheet S-3, 
part V data, we proposed inpatient unit benefit costs be equal to 
Worksheet S-3, part V, column 2, line 3. Given the limited reporting on 
Worksheet S-3, part V, we proposed that for those hospital-based IPFs 
that do not report these data, we calculate inpatient unit benefits 
cost using a portion of benefits cost reported for Excluded areas on 
Worksheet S-3, part II. We proposed to calculate the ratio of inpatient 
unit salaries (Worksheet A, column 1, line 40) to total excluded area 
salaries (sum of Worksheet A, column 1, lines 20, 23, 40 through 42, 
44, 45, 46, 94, 95, 98 through 101, 105 through 112, 114, 115 through 
117, 190 through 194). We then proposed to apply this ratio to Excluded 
area benefits (Worksheet S-3, part II, column 4, line 19) to derive 
inpatient unit benefits cost for those providers that do not report 
benefit costs on Worksheet S-3, part V.
    We proposed the ancillary departments benefits and overhead 
benefits (attributable to both the inpatient unit and ancillary 
departments) costs are derived by first calculating the sum of 
hospital-based IPF overhead salaries as described in section 
IV.A.3.a.(1)(b)(i) of this final rule, hospital-based IPF ancillary 
salaries as described in section IV.A.3.a.(1)(b)(ii) of this final rule 
and hospital-based IPF overhead salaries for ancillary cost centers as 
described in section IV.A.3.a.(1)(b)(iii) of this final rule. This sum 
is then multiplied by the ratio of total facility benefits to total 
facility salaries, where total facility benefits is equal to the sum of 
Worksheet S- 3, part II, column 4, lines 17-25, and total facility 
salaries is equal to Worksheet S-3, part II, column 4, line 1.
(d) Contract Labor Costs
    Contract Labor costs are primarily associated with direct patient 
care services. Contract labor costs for other services such as 
accounting, billing, and legal are calculated separately using other 
government data sources as described in section IV.A.3.a.(3) of this 
final rule. To derive contract labor costs using Worksheet S-3, part V, 
data for freestanding IPFs, we proposed Contract Labor costs be equal 
to Worksheet S-3, part V, column 1, line 2. As we noted for Employee 
Benefits, freestanding IPFs also may report Contract Labor data on 
Worksheet S-3, part II, which is applicable to only IPPS providers. For 
those freestanding IPFs that report Worksheet S-3, part II data, but 
not Worksheet S-3, part V, we proposed to use the sum of Worksheet S-3, 
part II, column 4, lines 11 and 13, to derive Contract Labor costs.
    For hospital-based IPFs, we proposed that Contract Labor costs be 
equal to Worksheet S- 3, part V, column 1, line 3. Reporting of this 
data continues to be somewhat limited; therefore, we continue to 
encourage all providers to report these data on the Medicare cost 
report. Given the limited reporting on Worksheet S-3, part V, we 
proposed that for those hospital-based IPFs that do not report these 
data, we calculate Contract Labor costs using a portion of contract 
labor costs reported on Worksheet S-3, part II. We proposed to 
calculate the ratio of contract labor costs (Worksheet S-3, part II, 
column 4, lines 11 and 13) to PPS salaries (Worksheet S-3, part II, 
column 4, line 1 less the sum of Worksheet S-3, part II, column 4, 
lines 3, 401, 5, 6, 7, 701, 8, 9, 10 less Worksheet A, column 1, line 
20 and 23). We then proposed to apply this ratio to total inpatient 
routine salary costs (Worksheet A, column 1, line 40) to derive 
contract labor costs for those providers that do not report contract 
labor costs on Worksheet S-3, part V.
(e) Pharmaceuticals Costs
    For freestanding IPFs, we proposed to calculate pharmaceuticals 
costs using non-salary costs reported on Worksheet A, column 7, less 
Worksheet A, column 1, for the pharmacy cost center (line 15) and drugs 
charged to patients cost center (line 73).
    For hospital-based IPFs, we proposed to calculate pharmaceuticals 
costs as the sum of a portion of the non-salary pharmacy costs and a 
portion of the non-salary drugs charged to patient costs reported for 
the total facility. We proposed that non-salary pharmacy costs 
attributable to the hospital-based IPF would be calculated by 
multiplying total pharmacy costs attributable to the hospital-based IPF 
(as reported on Worksheet B, part I, column 15, line 40) by the ratio 
of total non-salary pharmacy costs (Worksheet A, column 2, line 15) to 
total pharmacy costs (sum of Worksheet A, columns 1 and 2 for line 15) 
for the total facility. We proposed that non-salary drugs charged to 
patient costs attributable to the hospital-based IPF would be 
calculated by multiplying total non-salary drugs charged to patient 
costs (Worksheet B, part I, column 0, line 73 plus Worksheet B, part I, 
column 15, line 73 less Worksheet A, column 1, line 73) for the total 
facility by the ratio of Medicare drugs charged to patient ancillary 
costs for the IPF unit (as reported on Worksheet D-3 for hospital-based 
IPFs, column 3, line 73) to total Medicare drugs charged to patient 
ancillary costs for the total facility (equal to the sum of Worksheet 
D-3, column 3, line 73 for all relevant PPS [that is, IPPS, IRF, IPF 
and SNF]).
(f) Professional Liability Insurance Costs
    For freestanding and hospital-based IPFs, we proposed that 
Professional Liability Insurance (PLI) costs (often referred to as 
malpractice costs) would be equal to premiums, paid losses and self-
insurance costs reported on Worksheet S-2, columns 1 through 3, line 
118--the same data used for the

[[Page 51061]]

2016-based IPF market basket. For hospital-based IPFs, we proposed to 
assume that the PLI weight for the total facility is similar to the 
hospital-based IPF unit since the only data reported on this worksheet 
is for the entire facility, as we currently have no means to identify 
the proportion of total PLI costs that are only attributable to the 
hospital-based IPF. However, when we derive the cost weight for PLI for 
both hospital-based and freestanding IPFs, we use the total facility 
medical care costs as the denominator as opposed to total Medicare 
allowable costs. For freestanding IPFs and hospital-based IPFs, we 
proposed to derive total facility medical care costs as the sum of 
total costs (Worksheet B, part I, column 26, line 202) less non-
reimbursable costs (Worksheet B, part I, column 26, lines 190 through 
201). Our assumption is that the same proportion of expenses are used 
among each unit of the hospital.
(g) Home Office/Related Organization Contract Labor Costs
    For hospital-based IPFs, we proposed to calculate the Home Office/
Related Organization Contract Labor costs using data reported on 
Worksheet S-3, part II, column 4, lines 1401, 1402, 2550, and 2551. 
Similar to the PLI costs, these costs are for the entire facility. 
Therefore, when we derive the cost weight for home office/related 
organization contract labor costs, we use the total facility medical 
care costs as the denominator (reflecting the total facility costs 
(Worksheet B, part I, column 26, line 202) less the nonreimbursable 
costs reported on lines 190 through 201).
(h) Capital Costs
    For freestanding IPFs, we proposed that capital costs would be 
equal to Medicare allowable capital costs as reported on Worksheet B, 
part II, column 26, lines 30 through 35, 50 through 76 (excluding 52 
and 75), 90 through 91, and 93.
    For hospital-based IPFs, we proposed that capital costs would be 
equal to IPF inpatient capital costs (as reported on Worksheet B, part 
II, column 26, line 40) and a portion of IPF ancillary capital costs. 
We calculate the portion of ancillary capital costs attributable to the 
hospital-based IPF for a given cost center by multiplying total 
facility ancillary capital costs for the specific ancillary cost center 
(as reported on Worksheet B, part II, column 26) by the IPF ancillary 
ratio as described in section IV.A.3.a.(1)(a) of this final rule.
(2) Final Major Cost Category Computation
    After we derive costs for each of the major cost categories and 
total Medicare allowable costs for each provider using the Medicare 
cost report data as previously described, we proposed to address data 
outliers using the following steps. First, for the Wages and Salaries, 
Employee Benefits, Contract Labor, Pharmaceuticals, and Capital cost 
weights, we first divide the costs for each of these five categories by 
total Medicare allowable costs calculated for the provider to obtain 
cost weights for the universe of IPF providers. We then proposed to 
trim the data to remove outliers (a standard statistical process) by: 
(1) requiring that major expenses (such as Wages and Salaries costs) 
and total Medicare allowable operating costs be greater than zero; and 
(2) excluding the top and bottom 5 percent of the major cost weight 
(for example, Wages and Salaries costs as a percent of total Medicare 
allowable operating costs). We note that missing values are assumed to 
be zero consistent with the methodology for how missing values were 
treated in the 2016-based IPF market basket. After these outliers have 
been excluded, we sum the costs for each category across all remaining 
providers. We then divide this by the sum of total Medicare allowable 
costs across all remaining providers to obtain a cost weight for the 
2021-based IPF market basket for the given category.
    The proposed trimming methodology for the Home Office/Related 
Organization Contract Labor and PLI cost weights are slightly different 
than the proposed trimming methodology for the other five cost 
categories as described above. For these cost weights, since we are 
using total facility medical care costs rather than Medicare allowable 
costs associated with IPF services, we proposed to trim the 
freestanding and hospital-based IPF cost weights separately.
    For the PLI cost weight, for each of the providers, we first divide 
the PLI costs by total facility medical care costs to obtain a PLI cost 
weight for the universe of IPF providers. We then proposed to trim the 
data to remove outliers by: (1) requiring that PLI costs are greater 
than zero and are less than total facility medical care costs; and (2) 
excluding the top and bottom 5 percent of the major cost weight 
trimming freestanding and hospital-based providers separately. After 
removing these outliers, we are left with a trimmed data set for both 
freestanding and hospital-based providers. We proposed to separately 
sum the costs for each category (freestanding and hospital-based) 
across all remaining providers. We next divide this by the sum of total 
facility medical care costs across all remaining providers to obtain 
both a freestanding cost weight and hospital-based cost weight. Lastly, 
we proposed to weight these two cost weights together using the 
Medicare allowable costs from the sample of freestanding and hospital-
based IPFs that passed the PLI trim (63 percent for hospital-based and 
37 percent for freestanding IPFs) to derive a PLI cost weight for the 
2021-based IPF market basket.
    For the Home Office/Related Organization Contract Labor cost 
weight, for each of the providers, we first divide the home office/
related organization contract labor costs by total facility medical 
care costs to obtain a Home Office/Related Organization Contract Labor 
cost weight for the universe of IPF providers. Similar to the other 
market basket costs weights, we proposed to trim the Home Office/
Related Organization Contract Labor cost weight to remove outliers. 
Since not all hospital-based IPFs will have home office/related 
organization contract labor costs (approximately 80 percent of 
hospital-based IPFs report having a home office), we proposed to trim 
the top one percent of the Home Office/Related Organization Contract 
Labor cost weight. Using this proposed methodology, we calculate a Home 
Office/Related Organization Contract Labor cost weight for hospital-
based IPFs of 5.1 percent.
    Freestanding IPFs are not required to complete Worksheet S-3, part 
II. Therefore, to estimate the Home Office/Related Organization 
Contract Labor cost weight for freestanding IPFs, we proposed the 
following methodology:
    Step 1: Using hospital-based IPFs with a home office and also 
passing the 1 percent trim as described, we calculate the ratio of the 
Home Office/Related Organization Contract Labor cost weight to the 
Medicare allowable non-salary, non-capital cost weight (Medicare 
allowable non-salary, non-capital costs as a percent of total Medicare 
allowable costs).
    Step 2: We identify freestanding IPFs that report a home office on 
Worksheet S-2, line 140--roughly 87 percent of freestanding IPFs. We 
proposed to calculate a Home Office/Related Organization Contract Labor 
cost weight for these freestanding IPFs by multiplying the ratio 
calculated in Step 1 by the Medicare allowable non-salary, noncapital 
cost weight for those freestanding IPFs with a home office.

[[Page 51062]]

    Step 3: We then calculate the freestanding IPF cost weight by 
multiplying the Home Office/Related Organization Contract Labor cost 
weight in Step 2 by the total Medicare allowable costs for freestanding 
IPFs with a home office as a percent of total Medicare allowable costs 
for all freestanding IPFs (87 percent), which derives a freestanding 
Home Office/Related Organization Contract Labor cost weight of 4.2 
percent.
    To calculate the overall Home Office/Related Organization Contract 
Labor cost weight for the 2021-based IPF market basket, we proposed to 
weight together the freestanding Home Office/Related Organization 
Contract Labor cost weight (4.2 percent) and the hospital-based Home 
Office Contract Labor/Related Organization cost weight (5.1 percent) 
using total Medicare allowable costs from the sample of hospital-based 
IPFs that passed the one percent trim and the universe of freestanding 
IPFs. The resulting overall cost weight for Home Office/Related 
Organization Contract Labor is 4.7 percent (4.2 percent x 44 percent + 
5.1 percent x 56 percent). This is the same methodology used to 
calculate the Home Office/Related Organization Contract Labor cost 
weight in the 2016-based IPF market basket.
    Finally, we proposed to calculate the residual ``All Other'' cost 
weight that reflects all remaining costs that are not captured in the 
seven cost categories listed. See Table 1 for the resulting cost 
weights for these major cost categories that we obtain from the 
Medicare cost reports.
[GRAPHIC] [TIFF OMITTED] TR02AU23.001

    As we did for the 2016-based IPF market basket, we proposed to 
allocate the Contract Labor cost weight to the Wages and Salaries and 
Employee Benefits cost weights based on their relative proportions 
under the assumption that contract labor costs are comprised of both 
wages and salaries, and employee benefits. The Contract Labor 
allocation proportion for Wages and Salaries is equal to the Wages and 
Salaries cost weight as a percent of the sum of the Wages and Salaries 
cost weight and the Employee Benefits cost weight. For the proposed 
rule, the rounded percentage is 79 percent; therefore, we proposed to 
allocate 79 percent of the Contract Labor cost weight to the Wages and 
Salaries cost weight and 21 percent to the Employee Benefits cost 
weight. This allocation was 81/19 in the 2016-based IPF market basket 
(84 FR 38430). Table 2 shows the Wages and Salaries and Employee 
Benefit cost weights after Contract Labor cost weight allocation for 
both the 2021-based IPF market basket and 2016-based IPF market basket.
[GRAPHIC] [TIFF OMITTED] TR02AU23.002

    We did not receive any comments on our proposed methodology for 
developing the major cost weights of the 2021-based IPF market basket. 
We are finalizing these major cost weights as proposed.
(3) Derivation of the Detailed Operating Cost Weights
    To further divide the ``All Other'' residual cost weight estimated 
from the 2021 Medicare cost report data into more detailed cost 
categories, we proposed to use the 2012 Benchmark Input-Output (I-O) 
``Use Tables/Before Redefinitions/Purchaser Value'' for North American 
Industry Classification System (NAICS) 622000, Hospitals, published by 
the Bureau of Economic Analysis (BEA). This data is publicly available 
at https://www.bea.gov/industry/io_annual.htm. For the 2016-based IPF 
market basket, we also used the 2012 Benchmark I-O data, the most 
recent data available at the time (84 FR 38431).
    The BEA Benchmark I-O data are scheduled for publication every 5 
years with the most recent data available for 2012. The 2012 Benchmark 
I-O data are derived from the 2012 Economic Census and are the building 
blocks for BEA's economic accounts. Thus, they represent the most 
comprehensive and complete set of data on the economic processes or 
mechanisms by which

[[Page 51063]]

output is produced and distributed.\1\ BEA also produces Annual I-O 
estimates; however, while based on a similar methodology, these 
estimates reflect less comprehensive and less detailed data sources and 
are subject to revision when benchmark data becomes available. Instead 
of using the less detailed Annual I-O data, we proposed to inflate the 
2012 Benchmark I-O data forward to 2021 by applying the annual price 
changes from the respective price proxies to the appropriate market 
basket cost categories that are obtained from the 2012 Benchmark I-O 
data. We repeat this practice for each year. We then proposed to 
calculate the cost shares that each cost category represents of the 
inflated 2012 data. These resulting 2021 cost shares are applied to the 
``All Other'' residual cost weight to obtain the detailed cost weights 
for the 2021-based IPF market basket. For example, the cost for Food: 
Direct Purchases represents 5.0 percent of the sum of the ``All Other'' 
2012 Benchmark I-O Hospital Expenditures inflated to 2021; therefore, 
the Food: Direct Purchases cost weight represents 5.0 percent of the 
proposed 2021-based IPF market basket's ``All Other'' cost category 
(16.7 percent), yielding a ``final'' Food: Direct Purchases cost weight 
of 0.8 percent in the 2021-based IPF market basket (0.05 * 16.7 percent 
= 0.8 percent).
---------------------------------------------------------------------------

    \1\ https://www.bea.gov/papers/pdf/IOmanual_092906.pdf.
---------------------------------------------------------------------------

    Using this methodology, we proposed to derive seventeen detailed 
IPF market basket cost category weights from the 2021-based IPF market 
basket residual cost weight (16.7 percent). These categories are: (1) 
Electricity and Other Non-Fuel Utilities; (2) Fuel: Oil and Gas; (3) 
Food: Direct Purchases; (4) Food: Contract Services; (5) Chemicals; (6) 
Medical Instruments; (7) Rubber and Plastics; (8) Paper and Printing 
Products; (9) Miscellaneous Products; (10) Professional Fees: Labor-
Related; (11) Administrative and Facilities Support Services; (12) 
Installation, Maintenance, and Repair Services; (13) All Other Labor-
Related Services; (14) Professional Fees: Nonlabor-Related; (15) 
Financial Services; (16) Telephone Services; and (17) All Other 
Nonlabor-Related Services.
    We did not receive any comments on our methodology to use the BEA 
I-O data to derive the detailed operating cost weights. We are 
finalizing this methodology as we proposed. We note that we did receive 
one comment on the derivation of the Professional Fees: Labor-Related 
cost weight, which we discuss in section IV.A.5 of this final rule.
(4) Derivation of the Detailed Capital Cost Weights
    As described in section IV.A.3.a.(2) of this final rule, we 
proposed a Capital-Related cost weight of 7.2 percent as obtained from 
the 2021 Medicare cost reports for freestanding and hospital-based IPF 
providers. We proposed to then separate this total Capital-Related cost 
weight into more detailed cost categories.
    Using 2021 Medicare cost reports, we are able to group Capital-
Related costs into the following categories: Depreciation, Interest, 
Lease, and Other Capital-Related costs. For each of these categories, 
we proposed to determine separately for hospital-based IPFs and 
freestanding IPFs what proportion of total capital-related costs the 
category represents.
    For freestanding IPFs, using Medicare Cost Report data on Worksheet 
A-7 part III, we proposed to derive the proportions for Depreciation 
(column 9), Interest (column 11), Lease (column 10), and Other Capital-
related costs (column 12 through 14), which is similar to the 
methodology used for the 2016-based IPF market basket.
    For hospital-based IPFs, data for these four categories are not 
reported separately for the hospital-based IPF; therefore, we proposed 
to derive these proportions using data reported on Worksheet A-7 for 
the total facility. We are assuming the cost shares for the overall 
hospital are representative for the hospital-based IPF unit. For 
example, if depreciation costs make up 60 percent of total capital 
costs for the entire facility, we believe it is reasonable to assume 
that the hospital-based IPF would also have a 60 percent proportion 
because it is a unit contained within the total facility. This is the 
same methodology used for the 2016-based IPF market basket (84 FR 
38431).
    To combine each detailed capital cost weight for freestanding and 
hospital-based IPFs into a single capital cost weight for the 2021-
based IPF market basket, we proposed to weight together the shares for 
each of the categories (Depreciation, Interest, Lease, and Other 
Capital-Related costs) based on the share of total capital costs each 
provider type represents of the total capital costs for all IPFs for 
2021. Applying this methodology results in proportions of total 
capital-related costs for Depreciation, Interest, Lease and Other 
Capital-Related costs that are representative of the universe of IPF 
providers. This is the same methodology used for the 2016-based IPF 
market basket (84 FR 38432).
    Lease costs are unique in that they are not broken out as a 
separate cost category in the 2021-based IPF market basket. Rather, we 
proposed to proportionally distribute these costs among the cost 
categories of Depreciation, Interest, and Other Capital-Related costs, 
reflecting the assumption that the underlying cost structure of leases 
is similar to that of Capital-Related costs in general. As was done for 
the 2016-based IPF market basket, we proposed to assume that 10 percent 
of the lease costs as a proportion of total Capital-Related costs 
represent overhead and assign those costs to the Other Capital-Related 
cost category accordingly. We proposed to distribute the remaining 
lease costs proportionally across the three cost categories 
(Depreciation, Interest, and Other Capital-Related) based on the 
proportion that these categories comprise of the sum of the 
Depreciation, Interest, and Other Capital-Related cost categories 
(excluding lease expenses). This would result in three primary Capital-
Related cost categories in the 2021-based IPF market basket: 
Depreciation, Interest, and Other Capital-Related costs. This is the 
same methodology used for the 2016-based IPF market basket (84 FR 
38432). The allocation of these lease expenses is shown in Table 3.
    Finally, we proposed to further divide the Depreciation and 
Interest cost categories. We proposed to separate Depreciation into the 
following two categories: (1) Building and Fixed Equipment; and (2) 
Movable Equipment. We proposed to separate Interest into the following 
two categories: (1) Government/Nonprofit; and (2) For-profit.
    To disaggregate the Depreciation cost weight, we need to determine 
the percent of total Depreciation costs for IPFs that is attributable 
to Building and Fixed Equipment, which we hereafter refer to as the 
``fixed percentage.'' For the 2021-based IPF market basket, we proposed 
to use slightly different methods to obtain the fixed percentages for 
hospital-based IPFs compared to freestanding IPFs.
    For freestanding IPFs, we proposed to use depreciation data from 
Worksheet A-7 of the 2021 Medicare cost reports. However, for hospital-
based IPFs, we determined that the fixed percentage for the entire 
facility may not be representative of the hospital-based IPF unit due 
to the entire facility likely employing more sophisticated movable 
assets that are not utilized by the hospital-based IPF. Therefore, for 
hospital-based IPFs, we proposed to

[[Page 51064]]

calculate a fixed percentage using: (1) building and fixture capital 
costs allocated to the hospital-based IPF unit as reported on Worksheet 
B, part I, column 1, line 40; and (2) building and fixture capital 
costs for the top five ancillary cost centers utilized by hospital-
based IPFs accounting for 82 percent of hospital-based IPF ancillary 
total costs: Clinic (Worksheet B, part I, column 1, line 90), Drugs 
Charged to Patients (Worksheet B, part I, column 1, line 73), Emergency 
(Worksheet B, part I, column 1, line 91), Laboratory (Worksheet B, part 
I, column 1, line 60) and Radiology--Diagnostic (Worksheet B, part I, 
column 1, line 54). We proposed to weight these two fixed percentages 
(inpatient and ancillary) using the proportion that each capital cost 
type represents of total capital costs in the 2021-based IPF market 
basket. We proposed to then weight the fixed percentages for hospital-
based and freestanding IPFs together using the proportion of total 
capital costs each provider type represents. For both freestanding and 
hospital-based IPFs, this is the same methodology used for the 2016-
based IPF market basket (84 FR 38432).
    To disaggregate the Interest cost weight, we determined the percent 
of total interest costs for IPFs that are attributable to government 
and nonprofit facilities, which is hereafter referred to as the 
``nonprofit percentage,'' as price pressures associated with these 
types of interest costs tend to differ from those for for-profit 
facilities. For the 2021-based IPF market basket, we proposed to use 
interest costs data from Worksheet A-7 of the 2021 Medicare cost 
reports for both freestanding and hospital-based IPFs. We proposed to 
determine the percent of total interest costs that are attributed to 
government and nonprofit IPFs separately for hospital-based and 
freestanding IPFs. We then proposed to weight the nonprofit percentages 
for hospital-based and freestanding IPFs together using the proportion 
of total capital costs that each provider type represents.
    Table 3 provides the proposed detailed capital cost share 
composition estimated from the 2021 IPF Medicare cost reports. These 
detailed capital cost share composition percentages are applied to the 
total Capital-Related cost weight of 7.2 percent explained in detail in 
sections IV.A.3.a.(1)(h) and IV.A.3.a.(2) of this final rule.
BILLING CODE 4120-010-P
[GRAPHIC] [TIFF OMITTED] TR02AU23.003

    We did not receive any comments on our proposed methodology for 
developing the detailed capital cost weights of the 2021-based IPF 
market basket. We are finalizing these detailed capital cost weights as 
proposed.
(5) 2021-Based IPF Market Basket Cost Categories and Weights
    Table 4 compares the cost categories and weights for the finalized 
2021-based IPF market basket compared to the 2016-based IPF market 
basket.

[[Page 51065]]

[GRAPHIC] [TIFF OMITTED] TR02AU23.004

b. Selection of Price Proxies
    After developing the cost weights for the 2021-based IPF market 
basket, we proposed to select the most appropriate wage and price 
proxies currently available to represent the rate of price change for 
each expenditure category. For the majority of the cost weights, we 
base the price proxies on Bureau of Labor Statistics (BLS) data and 
grouped them into one of the following BLS categories:
     Employment Cost Indexes (ECIs): measure the rate of change 
in employment wage rates and employer costs for employee benefits per 
hour worked. These indexes are fixed-weight indexes and strictly 
measure the change in wage rates and employee benefits per hour. ECIs 
are superior to Average Hourly Earnings (AHE) as price proxies for 
input price indexes because they are not affected by shifts in 
occupation or industry mix, and because they measure pure price change 
and are available by both occupational group and by industry. The 
industry ECIs are based on the NAICS and the occupational ECIs are 
based on the Standard Occupational Classification System (SOC).
     Producer Price Indexes (PPI): measure the average change 
over time in

[[Page 51066]]

the selling prices received by domestic producers for their output. The 
prices included in the PPI are from the first commercial transaction 
for many products and some services (https://www.bls.gov/ppi/).
     Consumer Price Indexes (CPIs): measure the average change 
over time in the prices paid by urban consumers for a market basket of 
consumer goods and services (https://www.bls.gov/cpi/). CPIs are only 
used when the purchases are similar to those of retail consumers rather 
than purchases at the wholesale level, or if no appropriate PPIs are 
available.
    We evaluated the price proxies using the criteria of reliability, 
timeliness, availability, and relevance:
     Reliability: indicates that the index is based on valid 
statistical methods and has low sampling variability. Widely accepted 
statistical methods ensure that the data were collected and aggregated 
in a way that can be replicated. Low sampling variability is desirable 
because it indicates that the sample reflects the typical members of 
the population. (Sampling variability is variation that occurs by 
chance because only a sample was surveyed rather than the entire 
population.)
     Timeliness: implies that the proxy is published regularly, 
preferably at least once a quarter. The market baskets are updated 
quarterly and, therefore, it is important for the underlying price 
proxies to be up-to-date, reflecting the most recent data available. We 
believe that using proxies that are published regularly (at least 
quarterly, whenever possible) helps to ensure that we are using the 
most recent data available to update the market basket. We strive to 
use publications that are disseminated frequently, because we believe 
that this is an optimal way to stay abreast of the most current data 
available.
     Availability: means that the proxy is publicly available. 
We prefer that our proxies are publicly available because this will 
help ensure that our market basket updates are as transparent to the 
public as possible. In addition, this enables the public to be able to 
obtain the price proxy data on a regular basis.
     Relevance: means that the proxy is applicable and 
representative of the cost category weight to which it is applied. The 
CPIs, PPIs, and ECIs that we proposed in this regulation meet these 
criteria. Therefore, we believe that they continue to be the best 
measure of price changes for the cost categories to which they would be 
applied.
    Table 13 lists all price proxies that we proposed to use for the 
2021-based IPF market basket. A detailed explanation of the price 
proxies we proposed for each cost category weight is provided below.
(1) Price Proxies for the Operating Portion of the 2021-Based IPF 
Market Basket
(a) Wages and Salaries
    There is not a published wage proxy that we believe represents the 
occupational distribution of workers in IPFs. To measure wage price 
growth in the 2021-based IPF market basket, we proposed to apply a 
proxy blend based on six occupational subcategories within the Wages 
and Salaries category, which would reflect the IPF occupational mix, as 
was done for the 2016-based IPF market basket.
    We proposed to use the National Industry-Specific Occupational 
Employment and Wage estimates for NAICS 622200, Psychiatric & Substance 
Abuse Hospitals, published by the BLS Occupational Employment and Wage 
Statistics (OEWS) program, as the data source for the wage cost shares 
in the wage proxy blend. We note that in the spring of 2021, the 
Occupational Employment Statistics (OES) program began using the name 
Occupational Employment and Wage Statistics (OEWS) to better reflect 
the range of data available from the program. Data released on or after 
March 31, 2021 reflect the new program name. We proposed to use May 
2021 OEWS data. Detailed information on the methodology for the 
national industry-specific occupational employment and wage estimates 
survey can be found at https://www.bls.gov/oes/current/oes_tec.htm. For 
the 2016-based IPF market basket, we used May 2016 OES data.
    Based on the OEWS data, there are six wage subcategories: 
Management; NonHealth Professional and Technical; Health Professional 
and Technical; Health Service; NonHealth Service; and Clerical. Table 5 
lists the 2021 occupational assignments for the six wage subcategories; 
these are the same occupational groups used in the 2016-based IPF 
market basket.

[[Page 51067]]

[GRAPHIC] [TIFF OMITTED] TR02AU23.005


[[Page 51068]]


[GRAPHIC] [TIFF OMITTED] TR02AU23.006

    Total expenditures by occupation (that is, occupational assignment) 
were calculated by taking the OEWS number of employees multiplied by 
the OEWS annual average salary. These expenditures were aggregated 
based on the six groups in Table 5. We next calculated the proportion 
of each group's expenditures relative to the total expenditures of all 
six groups. These proportions, listed in Table 6, represent the weights 
used in the wage proxy blend. We then proposed to use the published 
wage proxies in Table 6 for each of the six groups (that is, wage 
subcategories) as we believe these six price proxies are the most 
technically appropriate indices available to measure the price growth 
of the Wages and Salaries cost category. These are the same price 
proxies used in the 2016-based IPF market basket (84 FR 38437).

[[Page 51069]]

[GRAPHIC] [TIFF OMITTED] TR02AU23.007

    A comparison of the yearly changes from FY 2021 to FY 2024 for the 
2021-based IPF wage blend and the 2016-based IPF wage blend is shown in 
Table 7. The average annual growth rate is the same for both price 
proxies over 2021-2024.
[GRAPHIC] [TIFF OMITTED] TR02AU23.008

(b) Employee Benefits
    To measure benefits price growth in the 2021-based IPF market 
basket, we proposed to apply a benefits proxy blend based on the same 
six subcategories and the same six blend weights for the wage proxy 
blend. These subcategories and blend weights are listed in Table 8.
    The benefit ECIs, listed in Table 8, are not publicly available. 
Therefore, an ``ECIs for Total Benefits'' is calculated using publicly 
available ``ECIs for Total Compensation'' for each subcategory and the 
relative importance of wages within that subcategory's total 
compensation. This is the same benefits ECI methodology that we 
implemented in our 2016-based IPF market basket as well as used in the 
IPPS, SNF, Home Health Agency (HHA), IRF, LTCH, and End-Stage Renal 
Disease (ESRD) market baskets. We believe that the six price proxies 
listed in Table 8 are the most technically appropriate indices to 
measure the price growth of the Employee Benefits cost category in the 
2021-based IPF market basket.

[[Page 51070]]

[GRAPHIC] [TIFF OMITTED] TR02AU23.009

    A comparison of the yearly changes from FY 2021 to FY 2024 for the 
2021-based IPF benefit proxy blend and the 2016-based IPF benefit proxy 
is shown in Table 9. The average annual growth rate is the same for 
both price proxies over 2021 through 2024.
[GRAPHIC] [TIFF OMITTED] TR02AU23.010

(c) Electricity and Other Non-Fuel Utilities
    We proposed to use the PPI Commodity Index for Commercial Electric 
Power (BLS series code WPU0542) to measure the price growth of this 
cost category (which we proposed to rename from Electricity to 
Electricity and Other Non-Fuel Utilities). This is the same price proxy 
used in the 2016-based IPF market basket (84 FR 38438).
(d) Fuel: Oil and Gas
    Similar to the 2016-based IPF market basket, for the 2021-based IPF 
market basket, we proposed to use a blend of the PPI for Petroleum 
Refineries and the PPI Commodity for Natural Gas. Our analysis of the 
Bureau of Economic Analysis' 2012 Benchmark Input-Output data (use 
table before redefinitions, purchaser's value for NAICS 622000 
[Hospitals]), shows that Petroleum Refineries expenses account for 
approximately 90 percent and Natural Gas expenses account for 
approximately 10 percent of Hospitals' (NAICS 622000) total Fuel: Oil 
and Gas expenses. Therefore, we proposed to use a blend of 90 percent 
of the PPI for Petroleum Refineries (BLS series code PCU324110324110) 
and 10 percent of the PPI Commodity Index for Natural Gas (BLS series 
code WPU0531) as the price proxy for this cost category. This is the 
same blend that was used for the 2016-based IPF market basket (84 FR 
38438).
(e) Professional Liability Insurance
    We proposed to use the CMS Hospital Professional Liability Index to 
measure changes in PLI premiums. To generate this index, we collect 
commercial insurance premiums for a fixed level of coverage while 
holding non-price factors constant (such as a change in the level of 
coverage). This is the same proxy used in the 2016-based IPF market 
basket (84 FR 38438).
(f) Pharmaceuticals
    We proposed to use the PPI for Pharmaceuticals for Human Use, 
Prescription (BLS series code WPUSI07003) to measure the price growth 
of this cost category. This is the same proxy used in the 2016-based 
IPF market basket (84 FR 38438).

[[Page 51071]]

(g) Food: Direct Purchases
    We proposed to use the PPI for Processed Foods and Feeds (BLS 
series code WPU02) to measure the price growth of this cost category. 
This is the same proxy used in the 2016-based IPF market basket (84 FR 
38438).
(h) Food: Contract Purchases
    We proposed to use the CPI for Food Away From Home (BLS series code 
CUUR0000SEFV) to measure the price growth of this cost category. This 
is the same proxy used in the 2016-based IPF market basket (84 FR 
38438).
(i) Chemicals
    Similar to the 2016-based IPF market basket, we proposed to use a 
four-part blended PPI as the proxy for the chemical cost category in 
the 2021-based IPF market basket. The proposed blend is composed of the 
PPI for Industrial Gas Manufacturing, Primary Products (BLS series code 
PCU325120325120P), the PPI for Other Basic Inorganic Chemical 
Manufacturing (BLS series code PCU32518-32518-), the PPI for Other 
Basic Organic Chemical Manufacturing (BLS series code PCU32519-32519-), 
and the PPI for Other Miscellaneous Chemical Product Manufacturing (BLS 
series code PCU325998325998). For the 2021-based IPF market basket, we 
proposed to derive the weights for the PPIs using the 2012 Benchmark I-
O data.
    Table 10 shows the weights for each of the four PPIs used to create 
the blended Chemical proxy for the 2021-based IPF market basket. This 
is the same blend that was used for the 2016-based IPF market basket 
(84 FR 38439).
[GRAPHIC] [TIFF OMITTED] TR02AU23.011

(j) Medical Instruments
    We proposed to use a blended price proxy for the Medical 
Instruments category, as shown in Table 11. The 2012 Benchmark I-O data 
shows the majority of medical instruments and supply costs are for 
NAICS 339112--Surgical and medical instrument manufacturing costs 
(approximately 56 percent) and NAICS 339113--Surgical appliance and 
supplies manufacturing costs (approximately 43 percent). Therefore, we 
proposed to use a blend of these two price proxies. To proxy the price 
changes associated with NAICS 339112, we proposed to use the PPI for 
Surgical and medical instruments (BLS series code WPU1562). This is the 
same price proxy we used in the 2016-based IPF market basket. To proxy 
the price changes associated with NAICS 339113, we proposed to use a 
50/50 blend of the PPI for Medical and surgical appliances and supplies 
(BLS series code WPU1563) and the PPI for Miscellaneous products, 
Personal safety equipment and clothing (BLS series code WPU1571). We 
proposed to include the latter price proxy as it will reflect personal 
protective equipment including but not limited to face shields and 
protective clothing. The 2012 Benchmark I-O data does not provide 
specific expenses for these products; however, we recognize that this 
category reflects costs faced by IPFs.
[GRAPHIC] [TIFF OMITTED] TR02AU23.012

(k) Rubber and Plastics
    We proposed to use the PPI for Rubber and Plastic Products (BLS 
series code WPU07) to measure price growth of this cost category. This 
is the same proxy used in the 2016-based IPF market basket (84 FR 
38439).
(l) Paper and Printing Products
    We proposed to use the PPI for Converted Paper and Paperboard 
Products (BLS series code WPU0915) to measure the price growth of this 
cost category. This is the same proxy used in the 2016-based IPF market 
basket (84 FR 38439).
(m) Miscellaneous Products
    We proposed to use the PPI for Finished Goods Less Food and Energy 
(BLS series code WPUFD4131) to measure the price growth of this cost 
category. This is the same proxy used in the 2016-based IPF market 
basket (84 FR 38439).
(n) Professional Fees: Labor-Related
    We proposed to use the ECI for Total Compensation for Private 
Industry workers in Professional and Related (BLS series code 
CIU2010000120000I) to measure the price growth of this category. This 
is the same proxy used in the 2016-based IPF market basket (84 FR 
38439).

[[Page 51072]]

(o) Administrative and Facilities Support Services
    We proposed to use the ECI for Total Compensation for Private 
Industry workers in Office and Administrative Support (BLS series code 
CIU2010000220000I) to measure the price growth of this category. This 
is the same proxy used in the 2016-based IPF market basket (84 FR 
38439).
(p) Installation, Maintenance, and Repair Services
    We proposed to use the ECI for Total Compensation for Civilian 
workers in Installation, Maintenance, and Repair (BLS series code 
CIU1010000430000I) to measure the price growth of this cost category. 
This is the same proxy used in the 2016-based IPF market basket (84 FR 
38439).
(q) All Other: Labor-Related Services
    We proposed to use the ECI for Total Compensation for Private 
Industry workers in Service Occupations (BLS series code 
CIU2010000300000I) to measure the price growth of this cost category. 
This is the same proxy used in the 2016-based IPF market basket (84 FR 
38439).
(r) Professional Fees: Nonlabor-Related
    We proposed to use the ECI for Total Compensation for Private 
Industry workers in Professional and Related (BLS series code 
CIU2010000120000I) to measure the price growth of this category. This 
is the same proxy used in the 2016-based IPF market basket (84 FR 
38439).
(s) Financial Services
    We proposed to use the ECI for Total Compensation for Private 
Industry workers in Financial Activities (BLS series code 
CIU201520A000000I) to measure the price growth of this cost category. 
This is the same proxy used in the 2016-based IPF market basket (84 FR 
38439).
(t) Telephone Services
    We proposed to use the CPI for Telephone Services (BLS series code 
CUUR0000SEED) to measure the price growth of this cost category. This 
is the same proxy used in the 2016-based IPF market basket (84 FR 
38439).
(u) All Other: Nonlabor-Related Services
    We proposed to use the CPI for All Items Less Food and Energy (BLS 
series code CUUR0000SA0L1E) to measure the price growth of this cost 
category. This is the same proxy used in the 2016-based IPF market 
basket (84 FR 38439).
    We did not receive any comments on our proposed price proxies for 
the operating portion of the 2021-based IPF market basket. We are 
finalizing these price proxies as proposed.
    Table 13 lists all price proxies that we are finalizing for the 
2021-based IPF market basket.
(2) Price Proxies for the Capital Portion of the 2021-Based IPF Market 
Basket
(a) Capital Price Proxies Prior to Vintage Weighting
    We proposed to use the same price proxies for the capital-related 
cost categories in the 2021-based IPF market basket as were used in the 
2016-based IPF market basket, which are provided in Table 13 and 
described below. Specifically, we proposed to proxy:
     Depreciation: Building and Fixed Equipment cost category 
by BEA's Chained Price Index for Nonresidential Construction for 
Hospitals and Special Care Facilities (BEA Table 5.4.4. Price Indexes 
for Private Fixed Investment in Structures by Type).
     Depreciation: Movable Equipment cost category by the PPI 
for Machinery and Equipment (BLS series code WPU11).
     Nonprofit Interest cost category by the average yield on 
domestic municipal bonds (Bond Buyer 20-bond index).
     For-profit Interest cost category by the iBoxx AAA 
Corporate Bond Yield index
     Other Capital-Related cost category by the CPI-U for Rent 
of Primary Residence (BLS series code CUUS0000SEHA).
    We believe these are the most appropriate proxies for IPF capital-
related costs that meet our selection criteria of relevance, 
timeliness, availability, and reliability. We also proposed to vintage 
weight the capital price proxies for Depreciation and Interest to 
capture the long-term consumption of capital. This vintage weighting 
method is similar to the method used for the 2016-based IPF market 
basket (84 FR 38440) and is described below.
(b) Vintage Weights for Price Proxies
    Because capital is acquired and paid for over time, capital-related 
expenses in any given year are determined by both past and present 
purchases of physical and financial capital. The vintage-weighted 
capital-related portion of the 2021-based IPF market basket is intended 
to capture the long-term consumption of capital, using vintage weights 
for depreciation (physical capital) and interest (financial capital). 
These vintage weights reflect the proportion of capital-related 
purchases attributable to each year of the expected life of building 
and fixed equipment, movable equipment, and interest. We proposed to 
use vintage weights to compute vintage-weighted price changes 
associated with depreciation and interest expenses.
    Capital-related costs are inherently complicated and are determined 
by complex capital-related purchasing decisions, over time, based on 
such factors as interest rates and debt financing. In addition, capital 
is depreciated over time instead of being consumed in the same period 
it is purchased. By accounting for the vintage nature of capital, we 
are able to provide an accurate and stable annual measure of price 
changes. Annual non-vintage price changes for capital are unstable due 
to the volatility of interest rate changes, and therefore, do not 
reflect the actual annual price changes for IPF capital-related costs. 
The capital-related component of the 2021-based IPF market basket 
reflects the underlying stability of the capital-related acquisition 
process.
    The methodology used to calculate the vintage weights for the 2021-
based IPF market basket is the same as that used for the 2016-based IPF 
market basket (84 FR 38439 through 38441) with the only difference 
being the inclusion of more recent data. To calculate the vintage 
weights for depreciation and interest expenses, we first need a time 
series of capital-related purchases for building and fixed equipment 
and movable equipment. We found no single source that provides an 
appropriate time series of capital-related purchases by hospitals for 
all of the above components of capital purchases. The early Medicare 
cost reports did not have sufficient capital-related data to meet this 
need. Data we obtained from the American Hospital Association (AHA) do 
not include annual capital-related purchases. However, we are able to 
obtain data on total expenses back to 1963 from the AHA. Consequently, 
we proposed to use data from the AHA Panel Survey and the AHA Annual 
Survey to obtain a time series of total expenses for hospitals. We then 
proposed to use data from the AHA Panel Survey supplemented with the 
ratio of depreciation to total hospital expenses obtained from the 
Medicare cost reports to derive a trend of annual depreciation expenses 
for 1963 through 2020, which is the latest year of AHA data available. 
We proposed to separate these depreciation expenses into annual amounts 
of building and fixed equipment depreciation and movable equipment 
depreciation as determined earlier. From these annual depreciation 
amounts, we derive annual end-of-year

[[Page 51073]]

book values for building and fixed equipment and movable equipment 
using the expected life for each type of asset category. While data is 
not available that is specific to IPFs, we believe this information for 
all hospitals serves as a reasonable alternative for the pattern of 
depreciation for IPFs.
    To continue to calculate the vintage weights for depreciation and 
interest expenses, we also need to account for the expected lives for 
Building and Fixed Equipment, Movable Equipment, and Interest for the 
2021-based IPF market basket. We proposed to calculate the expected 
lives using Medicare cost report data from freestanding and hospital-
based IPFs. The expected life of any asset can be determined by 
dividing the value of the asset (excluding fully depreciated assets) by 
its current year depreciation amount. This calculation yields the 
estimated expected life of an asset if the rates of depreciation were 
to continue at current year levels, assuming straight-line 
depreciation. We proposed to determine the expected life of building 
and fixed equipment separately for hospital-based IPFs and freestanding 
IPFs, and then weight these expected lives using the percent of total 
capital costs each provider type represents. We proposed to apply a 
similar method for movable equipment. Using these proposed methods, we 
determined the average expected life of building and fixed equipment to 
be equal to 25 years, and the average expected life of movable 
equipment to be equal to 12 years. For the expected life of interest, 
we believe vintage weights for interest should represent the average 
expected life of building and fixed equipment because, based on 
previous research described in the FY 1997 IPPS final rule (61 FR 
46198), the expected life of hospital debt instruments and the expected 
life of buildings and fixed equipment are similar. We note that for the 
2016-based IPF market basket, the expected life of building and fixed 
equipment is 22 years, and the expected life of movable equipment is 11 
years (84 FR 38441).
    Multiplying these expected lives by the annual depreciation amounts 
results in annual year-end asset costs for building and fixed equipment 
and movable equipment. We then calculate a time series, beginning in 
1964, of annual capital purchases by subtracting the previous year's 
asset costs from the current year's asset costs.
    For the building and fixed equipment and movable equipment vintage 
weights, we proposed to use the real annual capital-related purchase 
amounts for each asset type to capture the actual amount of the 
physical acquisition, net of the effect of price inflation. These real 
annual capital-related purchase amounts are produced by deflating the 
nominal annual purchase amount by the associated price proxy as 
provided earlier in this final rule. For the interest vintage weights, 
we proposed to use the total nominal annual capital-related purchase 
amounts to capture the value of the debt instrument (including, but not 
limited to, mortgages and bonds). Using these capital-related purchase 
time series specific to each asset type, we proposed to calculate the 
vintage weights for building and fixed equipment, for movable 
equipment, and for interest.
    The vintage weights for each asset type are deemed to represent the 
average purchase pattern of the asset over its expected life (in the 
case of building and fixed equipment and interest, 25 years, and in the 
case of movable equipment, 12 years). For each asset type, we used the 
time series of annual capital-related purchase amounts available from 
2020 back to 1964. These data allow us to derive thirty-three 25-year 
periods of capital-related purchases for building and fixed equipment 
and interest, and forty-six 12-year periods of capital-related 
purchases for movable equipment. For each 25-year period for building 
and fixed equipment and interest, or 12-year period for movable 
equipment, we calculate annual vintage weights by dividing the capital-
related purchase amount in any given year by the total amount of 
purchases over the entire 25-year or 12-year period. This calculation 
is done for each year in the 25-year or 12-year period and for each of 
the periods for which we have data. We then calculate the average 
vintage weight for a given year of the expected life by taking the 
average of these vintage weights across the multiple periods of data. 
The vintage weights for the capital-related portion of the 2021-based 
IPF market basket and the 2016-based IPF market basket are presented in 
Table 12.

[[Page 51074]]

[GRAPHIC] [TIFF OMITTED] TR02AU23.013

    The process of creating vintage-weighted price proxies requires 
applying the vintage weights to the price proxy index where the last 
applied vintage weight in Table 12 is applied to the most recent data 
point. We have provided on the CMS website an example of how the 
vintage weighting price proxies are calculated, using example vintage 
weights and example price indices. The example can be found at https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/MedicareProgramRatesStats/MarketBasketResearch.html in the zip 
file titled ``Weight Calculations as described in the IPPS FY 2010 
Proposed Rule.''
    We did not receive any comments on our proposed price proxies for 
the capital portion of the 2021-based IPF market basket. We are 
finalizing these price proxies as proposed.
(3) Summary of Price Proxies of the 2021-Based IPF Market Basket
    Table 13 shows both the operating and capital price proxies that we 
are finalizing for the 2021-based IPF market basket.

[[Page 51075]]

[GRAPHIC] [TIFF OMITTED] TR02AU23.014


[[Page 51076]]


    After consideration of public comments, we are finalizing the 2021-
based IPF market basket as proposed.
4. FY 2024 Market Basket Update and Productivity Adjustment
a. FY 2024 Market Basket Update
    For FY 2024 (that is, beginning October 1, 2023 and ending 
September 30, 2024), we proposed to use an estimate of the proposed 
2021-based IPF market basket increase factor to update the IPF PPS base 
payment rate. Consistent with historical practice, we estimate the 
market basket update for the IPF PPS based on IHS Global Inc.'s (IGI) 
forecast. IGI is a nationally recognized economic and financial 
forecasting firm with which CMS contracts to forecast the components of 
the market baskets.
    Using IGI's fourth quarter 2022 forecast with historical data 
through the third quarter of 2022, the projected proposed 2021-based 
IPF market basket increase factor for FY 2024 was 3.2 percent. We also 
proposed that if more recent data were subsequently available (for 
example, a more recent estimate of the market basket increase factor) 
we would use such data, to determine the FY 2024 update in the final 
rule.
    Based on IGI's second quarter 2023 forecast with historical data 
through the first quarter of 2023, the 2021-based IPF market basket 
increase percentage for FY 2024 is 3.5 percent. For comparison, the 
current 2016-based IPF market basket is also projected to increase by 
3.5 percent in FY 2024 based on IGI's second quarter 2023 forecast. 
Table 14 compares the 2021-based IPF market basket and the 2016-based 
IPF market basket percent changes. On average, the two indexes produce 
similar updates to one another, with the 4-year average historical 
growth rates (for FY 2019-FY 2022) of the 2021-based IPF market basket 
being equal to 3.2 percent compared to the 2016-based IPF market basket 
with 3.2 percent.
[GRAPHIC] [TIFF OMITTED] TR02AU23.015

BILLING CODE 4120-010-C
b. Productivity Adjustment
    Section 1886(s)(2)(A)(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 IPF PPS for the RY beginning in 2012 (that is, a RY that 
coincides with a FY) and each subsequent RY. The statute defines the 
productivity adjustment to be equal to the 10-year moving average of 
changes in annual economy-wide, private nonfarm business multifactor 
productivity (as projected by the Secretary for the 10-year period 
ending with the applicable FY, year, cost reporting period, or other 
annual period) (the ``productivity adjustment''). The United States 
Department of Labor's Bureau of Labor Statistics (BLS) publishes the 
official measures of productivity for the United States economy. We 
note that previously the productivity measure referenced in section 
1886(b)(3)(B)(xi)(II) of the Act, 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) of the 
Act is now published by BLS as private nonfarm business total factor 
productivity. However, as mentioned above, the data and methods are 
unchanged. We refer readers to 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/

[[Page 51077]]

medicareprogramratesstats/marketbasketresearch. In addition, in the FY 
2022 IPF PPS final rule (86 FR 42611), we noted that effective with FY 
2022 and forward, CMS changed the name of this adjustment to refer to 
it as the productivity adjustment rather than the MFP adjustment.
    Using IGI's fourth quarter 2022 forecast, the 10-year moving 
average growth of TFP for FY 2024 was projected to be 0.2 percent. 
Thus, in accordance with section 1886(s)(2)(A)(i) of the Act, we 
proposed to calculate the FY 2024 market basket update, which is used 
to determine the applicable percentage increase for the IPF payments, 
using IGI's fourth quarter 2022 forecast of the proposed 2021-based IPF 
market basket. We proposed to then reduce this percentage increase by 
the estimated productivity adjustment for FY 2024 of 0.2 percentage 
point (the 10-year moving average growth of TFP for the period ending 
FY 2024 based on IGI's fourth quarter 2022 forecast). Therefore, the 
proposed FY 2024 IPF update was equal to 3.0 percent (3.2 percent 
market basket update reduced by the 0.2 percentage point productivity 
adjustment). Furthermore, we 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 productivity adjustment), we would use such data, if appropriate, 
to determine the FY 2024 productivity adjustment in the final rule.
    Using IGI's second quarter 2023 forecast, the 10-year moving 
average growth of TFP for FY 2024 is projected to be 0.2 percent. Thus, 
in accordance with section 1886(s)(2)(A)(i) of the Act, we calculate 
the FY 2024 market basket update, which is used to determine the 
applicable percentage increase for the IPF payments, using IGI's second 
quarter 2023 forecast of the 2021-based IPF market basket. We then 
reduce this percentage increase by the estimated productivity 
adjustment for FY 2024 of 0.2 percentage point (the 10-year moving 
average growth of TFP for the period ending FY 2024 based on IGI's 
second quarter 2023 forecast). Therefore, the FY 2024 IPF update is 
equal to 3.3 percent (3.5 percent market basket update reduced by the 
0.2 percentage point productivity adjustment).
    We invited public comment on our proposals for the FY 2024 market 
basket update and productivity adjustment. The following is a summary 
of the public comments received on the proposed FY 2024 market basket 
update and productivity adjustment.
    Comment: Several commenters expressed concern about the proposed 
2021-based IPF market basket increase factor for FY 2024 of 3.2 
percent. They stated that hospitals throughout the country face 
enormous cost pressures, with labor costs (due to increased demand and 
workforce shortages) leading to this dramatic increase in overall cost 
pressure. They also noted the significant cost increases for drugs, 
medical supplies, and personal protective equipment since before the 
PHE. The commenters stated that the cumulative effect of this 
inflationary pressure coupled with the proposed low Medicare payment 
increases for FY 2024 will continue to have negative effects on IPF 
operating margins. They cited that the Medicare Payment Advisory 
Commission determined that Medicare has failed to cover the cost of 
caring for patients in hospital-based and freestanding nonprofit IPFs 
since at least 2016.
    The commenters also noted that CMS proposed that if more recent 
data became available after the publication of the proposed rule and 
before the publication of the final rule that CMS would use such data 
to determine the FY 2024 update in the final rule. They recommended CMS 
use more recent data and implement a payment rate for FY 2024 that more 
accurately reflects current costs, rather than relying on data that 
preceded the extraordinary inflation they are experiencing. Some 
commenters suggested CMS use other methods to determine the market 
basket update, such as the average growth rate in allowable Medicare 
costs per risk-adjusted discharge for IPFs between FY 2019 and FY 2021 
to calculate the FY 2024 final rule market basket update. They stated 
that if CMS fails to provide an adequate market basket update, they are 
deeply concerned inadequate payments will result in reduced access to 
inpatient psychiatric services for Medicare beneficiaries.
    Response: We appreciate the commenters' concerns regarding 
inflationary pressure facing IPFs and the proposed FY 2024 market 
basket update. As stated in Section IV.A.2 in this final rule, the IPF 
market basket (including the proposed 2021-based and other CMS market 
baskets) is a fixed-weight, Laspeyres-type index that measures price 
changes over time. Since the inception of the IPF PPS, the IPF payment 
rates (with the exception of statutorily mandated updates) have been 
updated by a projection of a market basket percentage increase, which 
is designed to measure price inflation for IPF providers and does not 
reflect increases in costs associated with changes in the volume or 
intensity of input goods and services (such as the quantity of labor 
used). In this way, the IPF market basket is consistent in concept and 
methodology with market baskets used for other CMS PPS updates, 
including IPPS, SNF, and HHA. The longstanding IPF market basket 
methodology establishes a market basket that appropriately reflects 
expectations, based on the latest available data, of price inflation 
for IPF providers for FY 2024. It would be inappropriate for the IPF 
market basket to reflect the method proposed by the commenter where the 
update would be based on increases in Medicare allowable costs per 
risk-adjusted discharge from a past period, since that measure would 
incorporate changes in costs that are not solely reflective of price 
inflation that is intended to be captured by the market basket update 
in the IPF PPS.
    The projection of the 2021-based IPF market basket is based on the 
most recent forecast from IHS Global Inc.--a nationally recognized 
economic and financial forecasting firm with which CMS contracts to 
forecast the price proxies of the market baskets. For this final rule, 
based on the more recent IGI second quarter 2023 forecast with 
historical data through the first quarter of 2023, the projected 2021-
based IPF market basket increase factor for FY 2024 is 3.5 percent, 
which is 0.3 percentage point higher than the projected FY 2024 market 
basket increase factor in the proposed rule, and reflects an increase 
in compensation prices of 4.0 percent. We note that the 10-year 
historical average (2013-2022) growth rate of the 2021-based IPF market 
basket is 2.4 percent with an average growth rate in compensation 
prices of 2.5 percent.
    Therefore, consistent with our historical practice of estimating 
market basket increases based on the best available data, we are 
finalizing a market basket increase percentage of 3.5 percent for FY 
2024.
    Comment: Several commenters expressed concern about the application 
of the productivity adjustment, stating that the PHE has had 
unimaginable impacts on hospital productivity. They state that even 
before the PHE, OACT indicated that hospital productivity will be less 
than the general economy-wide productivity, which is the measure that 
is required by law to be used to derive the productivity adjustment. 
Given that CMS is required by statute to implement a productivity 
adjustment to the market basket update, commenters asked the agency to 
work with the Congress to permanently eliminate this unjustified

[[Page 51078]]

reduction to hospital payments. Further, they asked CMS to use its 
authority under section 1886(s) of the Act to remove the productivity 
adjustment for any fiscal year that was covered under PHE determination 
(that is, 2020 (0.4 percent), 2021 (0.0 percent), 2022 (0.7 percent), 
and 2023 (0.3 percent)) from the calculation of the market basket 
update for FY 2024 and any year thereafter.
    Response: Section 1886(s)(2)(A)(i) of the Act requires the 
application of the productivity adjustment described in section 
1886(b)(3)(xi)(II) of the Act. As required by statute, the FY 2024 
productivity adjustment is derived based on the 10-year moving average 
growth in economy-wide productivity for the period ending FY 2024. We 
recognize the concerns of the commenters regarding the appropriateness 
of the productivity adjustment; however, we are required pursuant to 
section 1886(s)(2)(A)(i) of the Act to apply the specific productivity 
adjustment described here. Because that provision specifically requires 
application of the productivity adjustment, we do not believe section 
1886(s) of the Act permits the Secretary discretion to remove it from 
the calculation of the market basket update.
    Comment: Commenters noted that CMS has underestimated the IPF 
market basket increase over the last several years. They encouraged CMS 
to utilize its exceptions and adjustments authority to apply a one-time 
adjustment to course correct for its significantly lower estimates of 
costs for FYs 2021 through 2023. They stated that failing to correct 
CMS's gross underestimation of the payment updates during the pandemic 
will further perpetuate inaccuracies in the payment rate moving 
forward, resulting in a permanent cut to IPF payments.
    Response: The IPF market basket updates are set prospectively, 
which 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 FY 2024 market basket update 
in this final rule reflects historical data through the first quarter 
of CY 2023 and forecasted data through the third quarter of CY 2024. 
While there is no precedent to adjust for market basket forecast error 
in the IPF payment update, a forecast error can be calculated by 
comparing 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. 
Regarding the comment that the IPF market basket increase over the last 
several years has been underestimated, we disagree with this assertion, 
as from 2012 through 2020, the forecasted market basket updates for 
each payment year for IPFs were higher than the actual market basket 
updates. For this final rule, we have incorporated more recent 
historical data and forecasts to capture the price and wage pressures 
facing IPFs. We believe IGI's second quarter 2023 forecast of the FY 
2024 percentage increase in the 2021-based IPF market basket is the 
best available projection of inflation to determine the applicable 
percentage increase for the IPF payments in FY 2024.
    Final Decision: After consideration of public comments, we are 
finalizing a FY 2024 IPF payment rate update of 3.3 percent (3.5 
percent IPF market basket percentage increase reduced by the 0.2 
percentage point productivity adjustment).
5. Labor-Related Share for FY 2024
    Due to variations in geographic wage levels and other labor-related 
costs, we believe that payment rates under the IPF PPS should continue 
to be adjusted by a geographic wage index, which applies to the labor-
related portion of the Federal per diem base rate (hereafter referred 
to as the labor-related share). The labor-related share is determined 
by identifying the national average proportion of total costs that are 
related to, influenced by, or vary with the local labor market. We 
proposed to continue to classify a cost category as labor-related if 
the costs are labor-intensive and vary with the local labor market.
    We proposed to include in the labor-related share the sum of the 
relative importance of the following cost categories: 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 Capital-Related cost weight from the 2021-based 
IPF market basket. These are the same categories as the 2016-based IPF 
market basket.
    Similar to the 2016-based IPF market basket, the 2021-based IPF 
market basket includes two cost categories for nonmedical Professional 
fees (including but not limited to, expenses for legal, accounting, and 
engineering services). These are Professional Fees: Labor-Related and 
Professional Fees: Nonlabor-Related. For the 2021-based IPF market 
basket, we proposed to estimate the labor-related percentage of non-
medical professional fees (and assign these expenses to the 
Professional Fees: Labor-Related services cost category) based on the 
same method that was used to determine the labor-related percentage of 
professional fees in the 2016-based IPF market basket.
    As was done in the 2016-based IPF market basket, we proposed to 
determine the proportion of legal, accounting and auditing, 
engineering, and management consulting services that meet our 
definition of labor-related services based on a survey of hospitals 
conducted by CMS in 2008. We notified the public of our intent to 
conduct this survey on December 9, 2005, (70 FR 73250) and did not 
receive any public comments in response to the notice (71 FR 8588). A 
discussion of the composition of the survey and post-stratification can 
be found in the FY 2010 IPPS/LTCH PPS final rule (74 FR 43850 through 
43856). Based on the weighted results of the survey, we determined that 
hospitals purchase, on average, the following portions of contracted 
professional services outside of their local labor market:
     34 percent of accounting and auditing services.
     30 percent of engineering services.
     33 percent of legal services.
     42 percent of management consulting services.
    We proposed to apply each of these percentages to the respective 
2012 Benchmark I-O cost category underlying the professional fees cost 
category to determine the Professional Fees: Nonlabor-Related costs. 
The Professional Fees: Labor-Related costs were determined to be the 
difference between the total costs for each Benchmark I-O category and 
the Professional Fees: Nonlabor-Related costs. This is the same 
methodology that we used to separate the 2016-based IPF market basket 
professional fees category into Professional Fees: Labor-Related and 
Professional Fees: Nonlabor-Related cost categories (84 FR 38445).
    Effective for transmittal 18, (https://www.cms.gov/Regulations-and-Guidance/Guidance/Transmittals/Transmittals/r18p240i) the hospital 
Medicare cost report (CMS Form 2552-10, OMB No. 0938-0050) is 
collecting information on whether a hospital purchased professional 
services (for example, legal, accounting, tax preparation, bookkeeping, 
payroll, advertising, and/or management/consulting services) from an 
unrelated organization and if the majority of these expenses were 
purchased from unrelated organizations located outside of the main 
hospital's local area labor market. We encourage all providers to 
provide this information so we can potentially use these data in future

[[Page 51079]]

rulemaking to determine the labor-related share.
    In the 2021-based IPF market basket, nonmedical professional fees 
that were subject to allocation based on these survey results represent 
3.3 percent of total costs (and are limited to those fees related to 
Accounting & Auditing, Legal, Engineering, and Management Consulting 
services). Based on our survey results, we proposed to apportion 2.1 
percentage points of the 3.3 percentage point figure into the 
Professional Fees: Labor-Related share cost category and designate the 
remaining 1.2 percentage point into the Professional Fees: Nonlabor-
Related cost category.
    In addition to the professional services listed, for the 2021-based 
IPF market basket, we proposed to allocate a proportion of the Home 
Office/Related Organization Contract Labor cost weight, calculated 
using the Medicare cost reports, into the Professional Fees: Labor-
Related and Professional Fees: Nonlabor-Related cost categories. We 
proposed to classify these expenses as labor-related and nonlabor-
related, as many facilities are not located in the same geographic area 
as their home office and, therefore, do not meet our definition for the 
labor-related share, which requires the services to be purchased in the 
local labor market.
    Similar to the 2016-based IPF market basket, we proposed for the 
2021-based IPF market basket to use the Medicare cost reports for both 
freestanding IPF providers and hospital-based IPF providers to 
determine the home office labor-related percentages. The Medicare cost 
report requires a hospital to report information regarding its home 
office provider. Using information on the Medicare cost report, we then 
compare the location of the IPF with the location of the IPF's home 
office. We proposed to classify an IPF with a home office located in 
its respective labor market if the IPF and its home office are located 
in the same metropolitan statistical area (MSA). We then determine the 
proportion of the Home Office/Related Organization Contract Labor cost 
weight that should be allocated to the labor-related share based on the 
percent of total Medicare allowable costs for those IPFs that had home 
offices located in their respective local labor markets of total 
Medicare allowable costs for IPFs with a home office. We determined an 
IPF's and its home office's MSA using their zip code information from 
the Medicare cost report. Using this methodology, we determined that 46 
percent of IPFs' Medicare allowable costs were for home offices located 
in their respective local labor markets. Therefore, we are allocating 
46 percent of the Home Office/Related Organization Contract Labor cost 
weight (2.1 percentage points = 4.7 percent times 46 percent) to the 
Professional Fees: Labor-Related cost weight and 54 percent of the Home 
Office/Related Organization Contract Labor cost weight to the 
Professional Fees: Nonlabor-Related cost weight (2.5 percentage points 
= 4.7 percent times 54 percent). The same methodology was used for the 
2016-based IPF market basket (84 FR 38445).
    In summary, we apportioned 2.1 percentage points of the non-medical 
professional fees and 2.1 percentage points of the Home Office/Related 
Organization Contract Labor cost weight into the Professional Fees: 
Labor-Related cost category. This amount was added to the portion of 
professional fees that we already identified as labor-related using the 
I-O data such as contracted advertising and marketing costs 
(approximately 0.5 percentage point of total costs), resulting in a 
Professional Fees: Labor-Related cost weight of 4.7 percent.
    Comment: One commenter appreciated CMS's proposal to increase the 
labor-related share based on data that better reflects increased labor 
costs as a percentage of an IPF's overall cost structure. However, they 
disagreed with CMS's proposal to exclude from the labor-related share 
the proportion of non-medical professional services fees presumed to 
have been purchased outside of the hospital's labor market. The 
commenter disagreed with CMS's assertion/assumption that services 
purchased from national firms are not affected by the local labor 
market. The commenter stated that when hospitals seek professional 
services, the services they are seeking (such as, accounting, 
engineering, or management consulting) typically are not so unique that 
they could only be provided by regional or national firms. The 
commenter stated that CMS's own survey data support this conclusion, as 
approximately 64 percent of these services are sourced from firms in 
the local market. The commenter stated that costs of services purchased 
from firms outside the hospital's labor market should be included with 
the labor-related share of costs.
    The commenter requested that CMS provide evidence that pricing for 
professional services provided by regional and national firms to 
hospitals is offered in a national market that is not subject to 
geographic cost variation. The commenter urged that, unless the agency 
can produce strong evidence that prices for professional services 
provided by firms outside of a hospital's local labor market are 
homogenous, CMS restore the 1.2 percentage points it proposed to 
reclassify to Professional Services: Nonlabor-Related to the 
Professional Services: Labor-Related category.
    Response: We respectfully disagree with the commenter and continue 
to believe it is appropriate that a proportion of Accounting & 
Auditing, Legal, Engineering, and Management Consulting services costs 
purchased by hospitals should be excluded from the labor-related share.
    As discussed in the RY 2007 IPF PPS final rule (71 FR 27061), RY 
2009 IPF PPS (73 FR 25719) and the RY 2010 IPF PPS notices (74 FR 
20373), to provide an adjustment for geographic wage levels, the labor-
related portion of an IPF's payment is adjusted using an appropriate 
wage index. The purpose of the labor-related share is to reflect the 
proportion of the national PPS base payment rate that is adjusted by 
the hospital's wage index (representing the relative costs of their 
local labor market to the national average). Therefore, we include a 
cost category in the labor-related share if the costs are labor-
intensive and vary with the local labor market.
    As acknowledged by the commenter and confirmed by the survey of 
hospitals conducted by CMS in 2008 (as stated above), professional 
services can be purchased from local firms as well as national and 
regional professional services firms. It is not necessarily the case, 
as asserted by the commenter, that these national and regional firms 
have fees that match those in the local labor market even though 
providers have the option to utilize those firms. That is, fees for 
services purchased from firms outside the local labor market may differ 
from those that would be purchased in the local labor market for any 
number of reasons (including but not limited to, the skill level of the 
contracted personnel, higher capital costs, etc.). As noted earlier in 
this section of this final rule, the definition for the labor-related 
share requires the services to be purchased in the local labor market; 
therefore, CMS's allocation of approximately 64 percent of the 
Professional Fees cost weight allocated to the Professional Fees: 
Labor-Related cost weight based on the 2008 survey results \2\ is 
consistent with the commenter's assertion that not all Professional 
Fees services are purchased

[[Page 51080]]

in the local labor market. We believe it is reasonable to conclude that 
costs of those professional services purchased directly within the 
local labor market are directly related to local labor market 
conditions (which are reflected in the IPF's respective wage index) 
and, thus, should be included in the labor-related share. The remaining 
approximately 36 percent of Professional Fees costs which are purchased 
outside the local labor market reflects different and additional 
factors outside the local labor market and, thus, should be excluded 
from the labor-related share. In addition, we note the compensation 
costs of professional services provided by hospital employees (which 
would reflect the local labor market) are included in the labor-related 
share, as they are included in the Wages and Salaries and Benefit cost 
weights.
---------------------------------------------------------------------------

    \2\ The 64 percent value is based on a survey conducted by CMS 
in 2008 as detailed in the FY 2010 IPPS/LTCH PPS final rule (74 FR 
43850 through 43856). This was also used to determine the 
Professional Fees: Labor-Related cost weight in the 2016-based IPF 
market basket.
---------------------------------------------------------------------------

    Therefore, for the reasons discussed, we believe our proposed 
methodology of allocating only a portion of Professional Fees to the 
Professional Fees: Labor-Related cost category is appropriate. As 
stated previously, effective for transmittal 18 (https://www.cms.gov/Regulations-and-Guidance/Guidance/Transmittals/Transmittals/r18p240i), 
the hospital Medicare Cost Report (CMS Form 2552-10, OMB No. 0938-0050) 
is collecting information on whether a hospital purchased professional 
services (for example, legal, accounting, tax preparation, bookkeeping, 
payroll, advertising, and/or management/consulting services) from an 
unrelated organization and if the majority of these expenses were 
purchased from unrelated organizations located outside of the main 
hospital's local area labor market. We encourage all providers to 
provide this information for potential use in future rulemaking to 
determine the labor-related share.
    Comment: One commenter did not support the proposed increase to the 
labor-related share. This commenter stated that any increase to the 
labor-related share percentage penalizes any facility that has a wage 
index less than 1.0. The commenter further stated that across the 
country, there is a growing disparity between high-wage and low-wage 
states that harms hospitals in many rural and underserved communities. 
The commenter stated that limiting the increase in the labor-related 
share would help mitigate that growing disparity and recommended that 
CMS consider excluding the labor portion of capital-related costs for 
FY 2024 and going forward.
    Response: As discussed in section IV.D.1.a, the IPF PPS wage index 
is applied to the labor-related portion of an IPF's payment to provide 
an adjustment for geographic wage levels. The methodology to use the 
relative importance values for the labor-related cost categories from 
the most recent IPF market basket is consistent with the determination 
of the labor-related share since the implementation of the IPF PPS in 
2007. The labor-related cost categories reflect IPF costs that are 
related to, influenced by, or vary with the local labor market, which 
would include a portion of the capital-related costs since the 
construction costs for capital infrastructure would be influenced by 
the local labor market. Therefore, we disagree with the commenter that 
we should exclude the labor portion of capital-related costs for FY 
2024 and going forward.
    Comment: One commenter disagreed with the assumption that home 
office compensation costs that occur outside of a hospital's labor 
market are not subject to geographic wage variation and stated that 
they do not believe that the proposed reclassification to the 
Professional Fees: Non-Labor-Related cost category is justified. The 
commenters stated that the proposed methodology fails to consider that 
the home office is essentially a part of the hospital, and thus the 
hospital, along with its home office, is operating in multiple labor 
markets. The commenters stated that the home office's portion of the 
hospital's labor costs should not be excluded from the labor-related 
share simply because they are not in the same labor market as the 
hospital.
    The commenter conducted their own analysis of the Medicare cost 
report data showing that providers with a home office outside of their 
local labor market had wage indexes both below 1 as well as greater 
than 1. The commenter stated that those hospitals in a labor market 
with a wage index greater than 1 had mean home office average hourly 
wage costs that were greater than the mean home office average hourly 
wage costs of those hospitals in a labor market with a wage index less 
than 1. The commenter claimed that these data indicate that, contrary 
to CMS' assertion, home office salary, wage, and benefit costs for 
hospitals with home offices outside of their labor market are subject 
to geographic wage variation. The commenter requested that CMS allocate 
the full 4.7 percentage points of the Home Office/Related Organization 
cost weight to the labor-related share.
    Response: As discussed in the RY 2007 IPF PPS final rule (71 FR 
27061), RY 2009 IPF PPS (73 FR 25719) and the RY 2010 IPF PPS notices 
(74 FR 20373), to provide an adjustment for geographic wage levels, the 
labor-related portion of an IPF's payment is adjusted using an 
appropriate wage index. Due to the variation in costs and because of 
the differences in geographic wage levels, in the November 15, 2004 IPF 
PPS final rule, we required that payment rates under the IPF PPS be 
adjusted by a geographic wage index. We proposed and finalized a policy 
to use the unadjusted, pre-floor, pre-reclassified IPPS hospital wage 
index (representing the wage level in the geographic area of the 
hospital compared to the national average hospital wage level as 
specified under Section 1886(d)(3)(E)) to account for geographic 
differences in IPF labor costs. Therefore, consistent with the 
definition of labor-related share used for IPPS hospitals, we have 
included a cost category in the labor-related share for IPFs if the 
costs are labor-intensive and vary with the local labor market (that 
is, the geographic area of the hospital).
    As the commenter stated, and as validated with the Medicare cost 
report data, a hospital's home office can be located outside the 
hospital's local labor market. For other types of professional 
services, we only include the costs for services purchased directly 
within the geographic area of the hospital in the labor-related share 
because they reflect the local labor market conditions that are 
consistent with the intent of the geographic adjustment. We believe it 
is reasonable to conclude that costs of those home office services 
purchased directly within the geographic area of the hospital should 
also be included in the labor-related share because they are impacted 
by local labor market conditions. As we have previously discussed in 
the RY 2007 final rule (71 FR 27066), we believe that the actual 
location of an IPF (as opposed to the location of affiliated providers) 
is most appropriate for determining the wage adjustment, because the 
prevailing wages in the area in which the IPF is located influence the 
cost of a case. And as we do for professional services, we believe home 
office costs that are not in the same geographic area as the hospital 
should be excluded from the labor-related share because they are 
influenced by factors outside of the hospital's local labor market. To 
implement this approach, we proposed a methodology that relies on the 
Medicare cost report data for hospitals reporting home office 
information to determine whether their home office is in the same 
geographic area of the hospital (which we define as the hospital's 
Metropolitan Statistical Area). Our methodology determined that 46 
percent of the Home Office/Related Organization cost weight (reflecting 
compensation costs) are associated with

[[Page 51081]]

the geographic area of the hospital, whereas the remaining 54 percent 
of home office costs are purchased outside the geographic area of the 
hospital. Therefore, we believe our proposed methodology of only 
allocating the portion of the Home Office/Related Organization cost 
weight (46 percent) into the Professional Fees: Labor-Related cost 
weight that are purchased in the same geographic area as the hospital 
is appropriate as it is consistent with the intent of the geographic 
adjustment. In addition, we note that the compensation costs for 
hospital employees, which would reflect the local labor market 
performing the same tasks as home office personnel are included in the 
labor-related share as they are included in the Wages and Salaries and 
Employee Benefits cost weights.
    As stated, we proposed to include in the labor-related share the 
sum of the relative importance 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 
Capital-Related cost weight from the 2021-based IPF market basket, as 
this meets our definition of the labor-related share with costs that 
are labor intensive and vary with the local labor market.
    Final Decision: After consideration of public comments, we are 
finalizing the 2021-based IPF market basket proposed labor-related cost 
categories and base year cost weights as proposed.
    We also proposed that if more recent data were subsequently 
available, we would use such data to determine the FY 2024 labor-
related share in the final rule. Based on IGI's second quarter 2023 
forecast for the 2021-based IPF market basket, the sum of the FY 2024 
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 75.6 percent. The portion of Capital-Related 
costs that is influenced by the local labor market is estimated to be 
46 percent, which is the same percentage applied to the 2016-based IPF 
market basket (84 FR 38446 through 38447). Since the relative 
importance for Capital-Related costs is 6.8 percent of the 2021-based 
IPF market basket in FY 2024, we took 46 percent of 6.8 percent to 
determine the labor-related share of Capital-Related costs for FY 2024 
of 3.1 percent. Therefore, the total labor-related share for FY 2024 
based on more recent data is 78.7 percent (the sum of 75.6 percent for 
the operating costs and 3.1 percent for the labor-related share of 
Capital-Related costs). Table 15 shows the FY 2024 labor-related share 
using the 2021-based IPF market basket relative importance and the FY 
2023 labor-related share using the 2016-based IPF market basket.
[GRAPHIC] [TIFF OMITTED] TR02AU23.016

    The FY 2024 labor-related share using the 2021-based IPF market 
basket is about 1.0 percentage point higher than the FY 2023 labor-
related share using the 2016-based IPF market basket. This higher 
labor-related share is primarily due to the incorporation of the 2021 
Medicare cost report data, which increased the Compensation cost weight 
by 0.9 percentage point compared to the 2016-based IPF market basket, 
as shown in Table 1 and Table 2 in section IV.A.3.a.(2) of this final 
rule.

B. Updates to the IPF PPS Rates for FY Beginning October 1, 2023

    The IPF PPS is based on a standardized Federal per diem base rate 
calculated from the IPF average per diem costs and adjusted for budget 
neutrality in the implementation year. The Federal per diem base rate 
is used as the standard payment per day under the IPF PPS and is 
adjusted by the patient-level and facility-level adjustments that are 
applicable to the IPF stay. A detailed explanation of how we calculated 
the average per diem cost appears in the November 2004 IPF PPS final 
rule (69 FR 66926).

[[Page 51082]]

1. Determining the Standardized Budget-Neutral Federal Per Diem Base 
Rate
    Section 124(a)(1) of the BBRA required that we implement the IPF 
PPS in a budget-neutral manner. In other words, the amount of total 
payments under the IPF PPS, including any payment adjustments, must be 
projected to be equal to the amount of total payments that would have 
been made if the IPF PPS were not implemented. Therefore, we calculated 
the budget neutrality factor by setting the total estimated IPF PPS 
payments to be equal to the total estimated payments that would have 
been made under the Tax Equity and Fiscal Responsibility Act of 1982 
(TEFRA) (Pub. L. 97-248) methodology had the IPF PPS not been 
implemented. A step-by-step description of the methodology used to 
estimate payments under the Tax Equity and Fiscal Responsibility Act 
(TEFRA) payment system appears in the November 2004 IPF PPS final rule 
(69 FR 66926).
    Under the IPF PPS methodology, we calculated the final Federal per 
diem base rate to be budget-neutral during the IPF PPS implementation 
period (that is, the 18-month period from January 1, 2005, through June 
30, 2006) using a July 1 update cycle. We updated the average cost per 
day to the midpoint of the IPF PPS implementation period (October 1, 
2005), and this amount was used in the payment model to establish the 
budget-neutrality adjustment.
    Next, we standardized the IPF PPS Federal per diem base rate to 
account for the overall positive effects of the IPF PPS payment 
adjustment factors by dividing total estimated payments under the TEFRA 
payment system by estimated payments under the IPF PPS. The information 
concerning this standardization can be found in the November 2004 IPF 
PPS final rule (69 FR 66932) and the RY 2006 IPF PPS final rule (71 FR 
27045). We then reduced the standardized Federal per diem base rate to 
account for the outlier policy, the stop loss provision, and 
anticipated behavioral changes. A complete discussion of how we 
calculated each component of the budget neutrality adjustment appears 
in the November 2004 IPF PPS final rule (69 FR 66932 through 66933) and 
in the RY 2007 IPF PPS final rule (71 FR 27044 through 27046). The 
final standardized budget-neutral Federal per diem base rate 
established for cost reporting periods beginning on or after January 1, 
2005, was calculated to be $575.95.
    The Federal per diem base rate has been updated in accordance with 
applicable statutory requirements and Sec.  412.428 through publication 
of annual notices or proposed and final rules. A detailed discussion on 
the standardized budget-neutral Federal per diem base rate and the ECT 
payment per treatment appears in the FY 2014 IPF PPS update notice (78 
FR 46738 through 46740). These documents are available on the CMS 
website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/.
    IPFs must include a valid procedure code for ECT services provided 
to IPF beneficiaries in order to bill for ECT services, as described in 
our Medicare Claims Processing Manual, Chapter 3, Section 190.7.3 
(available at https://www.cms.gov/Regulations-and-Guidance/Guidance/Manuals/Downloads/clm104c03.pdf.) There were no changes to the ECT 
procedure codes used on IPF claims as a result of the final update to 
the ICD-10-PCS code set for FY 2024. Addendum B to this final rule 
shows the ECT procedure codes for FY 2024 and is available on our 
website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/tools.html.
2. Update of the Federal Per Diem Base Rate and Electroconvulsive 
Therapy Payment Per Treatment
    The current (FY 2023) Federal per diem base rate is $865.63, and 
the ECT payment per treatment is $372.67. For the final FY 2024 Federal 
per diem base rate, we applied the payment rate update of 3.3 percent--
that is, the 2021-based IPF market basket increase for FY 2024 of 3.5 
percent less the productivity adjustment of 0.2 percentage point--and 
the wage index budget-neutrality factor of 1.0016 (as discussed in 
section IV.D.1 of this final rule) to the FY 2023 Federal per diem base 
rate of $865.63, yielding a final Federal per diem base rate of $895.63 
for FY 2024. Similarly, we applied the 3.3 percent payment rate update 
and the 1.0016 wage index budget-neutrality factor to the FY 2023 ECT 
payment per treatment of $372.67, yielding a final ECT payment per 
treatment of $385.58 for FY 2024.
    Section 1886(s)(4)(A)(i) of the Act requires that for RY 2014 and 
each subsequent RY, in the case of an IPF that fails to report required 
data under the IPFQR Program with respect to such RY, the Secretary 
will reduce any annual update to a standard federal rate for discharges 
during the RY by 2.0 percentage points. Therefore, we are applying a 
2.0 percentage points reduction to the Federal per diem base rate and 
the ECT payment per treatment as follows:
     For IPFs that fail requirements under the IPFQR Program, 
we applied a 1.3 percent payment rate update--that is, the IPF market 
basket increase for FY 2024 of 3.5 percent less the productivity 
adjustment of 0.2 percentage point for an update of 3.3 percent, and 
further reduced by 2.0 percentage points in accordance with section 
1886(s)(4)(A)(i) of the Act--and the wage index budget-neutrality 
factor of 1.0016 to the FY 2023 Federal per diem base rate of $865.63, 
yielding a Federal per diem base rate of $878.29 for FY 2024.
     For IPFs that fail to meet requirements under the IPFQR 
Program, we applied a 1.3 percent annual payment rate update and a 
1.0016 wage index budget-neutrality factor to the FY 2023 ECT payment 
per treatment of $372.67 yielding an ECT payment per treatment of 
$378.12 for FY 2024. Lastly, we proposed that if more recent data 
became available, we would use such data, if appropriate, to determine 
the FY 2024 Federal per diem base rate and ECT payment per treatment 
for the final rule.
    Finally, we note that in the April 10, 2023 IPF PPS proposed rule 
(88 FR 21259), there were two technical errors in describing the 
calculation of the FY 2024 proposed base rate and electroconvulsive 
therapy (ECT) payment per treatment for IPFs that fail to meet 
requirements under the Inpatient Psychiatric Facility Quality Reporting 
(IPFQR) Program. In describing the calculation of the FY 2024 Federal 
per diem base rate for IPFs that fail to meet requirements under the 
IPFQR Program, we inadvertently stated that we applied the market 
basket update, reduced by 2.0 percentage points to the FY 2024 Federal 
per diem base rate and FY 2024 ECT payment per treatment. In accordance 
with our longstanding methodology, and with the actual calculation of 
these proposed payment updates, the description of these calculations 
should have used the FY 2023 Federal per diem rate and FY 2023 ECT 
payment per treatment rather than the FY 2024 Federal per diem rate and 
ECT payment per treatment. To be clear, these errors only affected the 
description of the starting values from which the rates were 
calculated, and the calculations themselves, as well as the rates 
indicated in the proposed rule, were correct and consistent with our 
longstanding methodology for updating the IPF Federal per diem base 
rate and ECT payment per treatment.

[[Page 51083]]

C. Updates to the IPF PPS Patient-Level Adjustment Factors

1. Overview of the IPF PPS Adjustment Factors
    The IPF PPS payment adjustments were derived from a regression 
analysis of 100 percent of the FY 2002 Medicare Provider and Analysis 
Review (MedPAR) data file, which contained 483,038 cases. For a more 
detailed description of the data file used for the regression analysis, 
see the November 2004 IPF PPS final rule (69 FR 66935 through 66936). 
We proposed to use the existing regression-derived adjustment factors 
established in 2005 for FY 2024. However, we have used more recent 
claims data to simulate payments to finalize the outlier fixed dollar 
loss threshold amount and to assess the impact of the IPF PPS updates.
2. IPF PPS Patient-Level Adjustments
    The IPF PPS includes payment adjustments for the following patient-
level characteristics: Medicare Severity Diagnosis Related Groups (MS-
DRGs) assignment of the patient's principal diagnosis, selected 
comorbidities, patient age, and the variable per diem adjustments.
a. Update to MS-DRG Assignment
    We believe it is important to maintain for IPFs the same diagnostic 
coding and Diagnosis Related Group (DRG) classification used under the 
IPPS for providing psychiatric care. For this reason, when the IPF PPS 
was implemented for cost reporting periods beginning on or after 
January 1, 2005, we adopted the same diagnostic code set (ICD-9-CM) and 
DRG patient classification system (MS-DRGs) that were utilized at the 
time under the IPPS. In the RY 2009 IPF PPS notice (73 FR 25709), we 
discussed CMS's effort to better recognize resource use and the 
severity of illness among patients. CMS adopted the new MS-DRGs for the 
IPPS in the FY 2008 IPPS final rule with comment period (72 FR 47130). 
In the RY 2009 IPF PPS notice (73 FR 25716), we provided a crosswalk to 
reflect changes that were made under the IPF PPS to adopt the new MS-
DRGs. For a detailed description of the mapping changes from the 
original DRG adjustment categories to the current MS-DRG adjustment 
categories, we refer readers to the RY 2009 IPF PPS notice (73 FR 
25714).
    The IPF PPS includes payment adjustments for designated psychiatric 
DRGs assigned to the claim based on the patient's principal diagnosis. 
The DRG adjustment factors were expressed relative to the most 
frequently reported psychiatric DRG in FY 2002, that is, DRG 430 
(psychoses). The coefficient values and adjustment factors were derived 
from the regression analysis discussed in detail in the November 28, 
2003 IPF PPS proposed rule (68 FR 66923; 66928 through 66933) and the 
November 15, 2004 IPF PPS final rule (69 FR 66933 through 66960). 
Mapping the DRGs to the MS-DRGs resulted in the current 17 IPF MS-DRGs, 
instead of the original 15 DRGs, for which the IPF PPS provides an 
adjustment. For FY 2024, we did not propose any changes to the IPF MS-
DRG adjustment factors. Therefore, we are retaining the existing IPF 
MS-DRG adjustment factors.
    In the FY 2015 IPF PPS final rule published August 6, 2014, in the 
Federal Register titled, ``Inpatient Psychiatric Facilities Prospective 
Payment System--Update for FY Beginning October 1, 2014 (FY 2015)'' (79 
FR 45945 through 45947), we finalized conversions of the ICD-9-CM-based 
MS-DRGs to ICD-10-CM/PCS-based MS-DRGs, which were implemented on 
October 1, 2015. As discussed in the FY 2015 IPF PPS proposed rule (79 
FR 26047) in more detail, every year, changes to the ICD-10-CM and the 
ICD-10-PCS coding system are addressed in the IPPS proposed and final 
rules. The changes to the codes are effective October 1 of each year 
and must be used by acute care hospitals as well as other providers to 
report diagnostic and procedure information. In accordance with Sec.  
412.428(e), the IPF PPS has always incorporated ICD-10-CM and ICD-10-
PCS coding changes made in the annual IPPS update and will continue to 
do so. We will continue to publish coding changes in a Transmittal/
Change Request, similar to how coding changes are announced by the IPPS 
and LTCH PPS. The coding changes relevant to the IPF PPS are also 
published in the IPF PPS proposed and final rules, or in IPF PPS update 
notices. Further information on the ICD-10-CM/PCS MS-DRG conversion 
project can be found on the CMS ICD-10-CM website at https://www.cms.gov/Medicare/Coding/ICD10/ICD-10-MS-DRG-Conversion-Project.html.
    For FY 2024, we proposed to continue making the existing payment 
adjustment for psychiatric diagnoses that group to one of the existing 
17 IPF MS-DRGs listed in Addendum A. Addendum A is available on our 
website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/tools.html.. Psychiatric principal 
diagnoses that do not group to one of the 17 designated MS-DRGs will 
still receive the Federal per diem base rate and all other applicable 
adjustments, but the payment will not include an MS-DRG adjustment.
    As we did not propose any changes to the IPF MS-DRG adjustment 
factors, we are retaining the existing IPF MS-DRG adjustment factors 
for FY 2024.
    The diagnoses for each IPF MS-DRG will be updated as of October 1, 
2023, using the final FY 2024 IPPS ICD-10-CM/PCS code sets. The FY 2024 
IPPS/LTCH PPS final rule will include tables of the changes to the ICD-
10-CM/PCS code sets, which underlie the FY 2024 IPF MS-DRGs. Both the 
FY 2024 IPPS final rule and the tables of final changes to the ICD-10-
CM/PCS code sets, which underlie the FY 2024 MS-DRGs, will be available 
on the CMS IPPS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/.
Code First
    As discussed in the ICD-10-CM Official Guidelines for Coding and 
Reporting, certain conditions have both an underlying etiology and 
multiple body system manifestations due to the underlying etiology. For 
such conditions, the ICD-10-CM has a coding convention that requires 
the underlying condition be sequenced first followed by the 
manifestation. Wherever such a combination exists, there is a ``use 
additional code'' note at the etiology code, and a ``code first'' note 
at the manifestation code. These instructional notes indicate the 
proper sequencing order of the codes (etiology followed by 
manifestation). In accordance with the ICD-10-CM Official Guidelines 
for Coding and Reporting, when a primary (psychiatric) diagnosis code 
has a ``code first'' note, the provider will follow the instructions in 
the ICD-10-CM Tabular List. The submitted claim goes through the CMS 
processing system, which will identify the principal diagnosis code as 
non-psychiatric and search the secondary codes for a psychiatric code 
to assign a DRG code for adjustment. The system will continue to search 
the secondary codes for those that are appropriate for comorbidity 
adjustment.
    For more information on the code first policy, we refer our readers 
to the November 2004 IPF PPS final rule (69 FR 66945), and see sections 
I.A.13 and I.B.7 of the FY 2020 ICD-10-CM Coding Guidelines, available 
at https://www.cdc.gov/nchs/data/icd/10cmguidelines-FY2020_final.pdf. 
In the FY 2015 IPF PPS final rule, we provided a code first table for 
reference that highlights the same or similar manifestation codes where 
the code first

[[Page 51084]]

instructions apply in ICD-10-CM that were present in ICD-10-CM (79 FR 
46009). In FY 2018, FY 2019 and FY 2020, there were no changes to the 
final ICD-10-CM codes in the IPF Code First table. For FY 2021 and FY 
2022, there were 18 ICD-10-CM codes deleted from the final IPF Code 
First table. For FY 2023, there were 2 ICD-10-CM codes deleted and 48 
ICD-10-CM codes added to the IPF Code First table.
    For FY 2024, there were no proposed changes to the Code First 
Table. For this final rule, we are finalizing the deletion of 1 ICD-10-
CM code and the addition of 5 ICD-10-CM codes as ``code first'' codes. 
There are 26 codes whose ``code first'' codes are being updated in the 
IPF Code First Table to reflect these changes In accordance with our 
longstanding practice for the IPF PPS and with Sec.  412.428(e), we are 
adopting these latest ICD-10-CM changes for October, 2023 and 
describing these changes in this FY 2024 IPF PPS final rule. The FY 
2024 Code First table is shown in Addendum B on the CMS website at 
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/tools.html.
b. Payment for Comorbid Conditions
    The intent of the comorbidity adjustments is to recognize the 
increased costs associated with comorbid conditions by providing 
additional payments for certain existing medical or psychiatric 
conditions that are expensive to treat. In our RY 2012 IPF PPS final 
rule (76 FR 26451 through 26452), we explained that the IPF PPS 
includes 17 comorbidity categories and identified the new, revised, and 
deleted ICD-9-CM diagnosis codes that generate a comorbid condition 
payment adjustment under the IPF PPS for RY 2012 (76 FR 26451).
    Comorbidities are specific patient conditions that are secondary to 
the patient's principal diagnosis and that require treatment during the 
stay. Diagnoses that relate to an earlier episode of care and have no 
bearing on the current hospital stay are excluded and must not be 
reported on IPF claims. Comorbid conditions must exist at the time of 
admission or develop subsequently, and affect the treatment received, 
LOS, or both treatment and LOS.
    For each claim, an IPF may receive only one comorbidity adjustment 
within a comorbidity category, but it may receive an adjustment for 
more than one comorbidity category. Current billing instructions for 
discharge claims, on or after October 1, 2015, require IPFs to enter 
the complete ICD-10-CM codes for up to 24 additional diagnoses if they 
co-exist at the time of admission, or develop subsequently and impact 
the treatment provided.
    The comorbidity adjustments were determined based on the regression 
analysis using the diagnoses reported by IPFs in FY 2002. The principal 
diagnoses were used to establish the DRG adjustments and were not 
accounted for in establishing the comorbidity category adjustments, 
except where ICD-9-CM code first instructions applied. In a code first 
situation, the submitted claim goes through the CMS processing system, 
which will identify the principal diagnosis code as non-psychiatric and 
search the secondary codes for a psychiatric code to assign an MS-DRG 
code for adjustment. The system will continue to search the secondary 
codes for those that are appropriate for comorbidity adjustment.
    As noted previously, it is our policy to maintain the same 
diagnostic coding set for IPFs that is used under the IPPS for 
providing the same psychiatric care. The 17 comorbidity categories 
formerly defined using ICD-9-CM codes were converted to ICD-10-CM/PCS 
in our FY 2015 IPF PPS final rule (79 FR 45947 through 45955). The goal 
for converting the comorbidity categories is referred to as 
replication, meaning that the payment adjustment for a given patient 
encounter is the same after ICD-10-CM implementation as it would be if 
the same record had been coded in ICD-9-CM and submitted prior to ICD-
10-CM/PCS implementation on October 1, 2015. All conversion efforts 
were made with the intent of achieving this goal. For FY 2024, we 
proposed to use the same comorbidity adjustment factors in effect in FY 
2023. The FY 2024 comorbidity adjustment factors are found in Addendum 
A, available on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/tools.html.
    For FY 2024, we proposed to add 2 ICD-10-CM codes and remove 1 ICD-
10-CM code from the Chronic Renal Failure category. We did not receive 
any comments on this proposal, and we are finalizing these changes as 
proposed. In addition, we are adding 2 ICD-10-CM codes to the Chronic 
Obstructive Pulmonary Disease category, 1 ICD-10-CM code to the 
Infectious Disease category, 4 ICD-10-CM codes to the Poisoning 
category, 6 ICD-10-PCS codes for the Oncology Treatment Procedure 
category. For the Oncology Treatment Diagnosis Category, we are adding 
12 ICD-10-CM codes and deleting 2 ICD-10-CM codes. Finally, for the 
Acute Renal Failure Category, we are adding 1 ICD-10-CM code and 
deleting 1 ICD-10_CM code. In accordance with our longstanding practice 
for the IPF PPS and with Sec.  412.428(e), we are adopting these latest 
ICD-10-CM changes for October, 2023 and describing these changes in 
this FY 2024 IPF PPS final rule.
    The FY 2024 comorbidity codes are shown in Addenda B, available on 
the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/tools.html.
    In accordance with the policy established in the FY 2015 IPF PPS 
final rule (79 FR 45949 through 45952), we reviewed all new FY 2024 
ICD-10-CM codes to remove codes that were site ``unspecified'' in terms 
of laterality from the FY 2024 ICD-10-CM/PCS codes in instances where 
more specific codes are available. As we stated in the FY 2015 IPF PPS 
final rule, we believe that specific diagnosis codes that narrowly 
identify anatomical sites where disease, injury, or a condition exists 
should be used when coding patients' diagnoses whenever these codes are 
available. We finalized in the FY 2015 IPF PPS rule, that we will 
remove site ``unspecified'' codes from the IPF PPS ICD-10-CM/PCS codes 
in instances when laterality codes (site specified codes) are 
available, as the clinician should be able to identify a more specific 
diagnosis based on clinical assessment at the medical encounter. None 
of the finalized additions to the FY 2024 ICD-10-CM/PCS codes were site 
``unspecified'' by laterality; therefore, we are not removing any of 
the new codes.
c. Patient Age Adjustments
    As explained in the November 2004 IPF PPS final rule (69 FR 66922), 
we analyzed the impact of age on per diem cost by examining the age 
variable (range of ages) for payment adjustments. In general, we found 
that the cost per day increases with age. The older age groups are 
costlier than the under 45 age group, the differences in per diem cost 
increase for each successive age group, and the differences are 
statistically significant. For FY 2024, we proposed continuing to use 
the patient age adjustments currently in effect for FY 2023, as shown 
in Addendum A of this final rule (see https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/tools.html).
    As we did not propose any changes to the patient age adjustment 
factors, we are retaining the existing patient age adjustment factors 
for FY 2024.

[[Page 51085]]

d. Variable Per Diem Adjustments
    We explained in the November 2004 IPF PPS final rule (69 FR 66946) 
that the regression analysis indicated that per diem cost declines as 
the LOS increases. The variable per diem adjustments to the Federal per 
diem base rate account for ancillary and administrative costs that 
occur disproportionately in the first days after admission to an IPF. 
As discussed in the November 2004 IPF PPS final rule, we used a 
regression analysis to estimate the average differences in per diem 
cost among stays of different lengths (69 FR 66947 through 66950). As a 
result of this analysis, we established variable per diem adjustments 
that begin on day 1 and decline gradually until day 21 of a patient's 
stay. For day 22 and thereafter, the variable per diem adjustment 
remains the same each day for the remainder of the stay. However, the 
adjustment applied to day 1 depends upon whether the IPF has a 
qualifying ED. If an IPF has a qualifying ED, it receives a 1.31 
adjustment factor for day 1 of each stay. If an IPF does not have a 
qualifying ED, it receives a 1.19 adjustment factor for day 1 of the 
stay. The ED adjustment is explained in more detail in section IV.D.4 
of this final rule.
    For FY 2024, we proposed to use the variable per diem adjustment 
factors currently in effect in FY 2023, as shown in Addendum A to this 
final rule (available at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/tools.html). A complete 
discussion of the variable per diem adjustments appears in the November 
2004 IPF PPS final rule (69 FR 66946).
    As we did not propose any changes to the variable per diem 
adjustment factors, we are retaining the existing variable per diem 
adjustment factors for FY 2024.

D. Updates to the IPF PPS Facility-Level Adjustments

    The IPF PPS includes facility-level adjustments for the wage index, 
IPFs located in rural areas, teaching IPFs, cost of living adjustments 
for IPFs located in Alaska and Hawaii, and IPFs with a qualifying ED.
1. Wage Index Adjustment
a. Background
    As discussed in the RY 2007 IPF PPS final rule (71 FR 27061), RY 
2009 IPF PPS (73 FR 25719) and the RY 2010 IPF PPS notices (74 FR 
20373), to provide an adjustment for geographic wage levels, the labor-
related portion of an IPF's payment is adjusted using an appropriate 
wage index. Currently, an IPF's geographic wage index value is 
determined based on the actual location of the IPF in an urban or rural 
area, as defined in 42 CFR 412.64(b)(1)(ii)(A) and (C).
    Due to the variation in costs and because of the differences in 
geographic wage levels, in the November 15, 2004 IPF PPS final rule, we 
required that payment rates under the IPF PPS be adjusted by a 
geographic wage index. We proposed and finalized a policy to use the 
unadjusted, pre-floor, pre-reclassified IPPS hospital wage index to 
account for geographic differences in IPF labor costs. We implemented 
use of the pre-floor, pre-reclassified IPPS hospital wage data to 
compute the IPF wage index since there was not an IPF-specific wage 
index available. We believe that IPFs generally compete in the same 
labor market as IPPS hospitals, so the pre-floor, pre-reclassified IPPS 
hospital wage data should be reflective of labor costs of IPFs. We 
believe this pre-floor, pre-reclassified IPPS hospital wage index to be 
the best available data to use as proxy for an IPF specific wage index. 
As discussed in the RY 2007 IPF PPS final rule (71 FR 27061 through 
27067), under the IPF PPS, the wage index is calculated using the IPPS 
wage index for the labor market area in which the IPF is located, 
without considering geographic reclassifications, floors, and other 
adjustments made to the wage index under the IPPS. For a complete 
description of these IPPS wage index adjustments, we refer readers to 
the FY 2019 IPPS/LTCH PPS final rule (83 FR 41362 through 41390). Our 
wage index policy at Sec.  412.424(a)(2), requires that we use the best 
Medicare data available to estimate costs per day, including an 
appropriate wage index to adjust for wage differences.
    When the IPF PPS was implemented in the November 15, 2004 IPF PPS 
final rule, with an effective date of January 1, 2005, the pre-floor, 
pre-reclassified IPPS hospital wage index that was available at the 
time was the FY 2005 pre-floor, pre-reclassified IPPS hospital wage 
index. Historically, the IPF wage index for a given RY has used the 
pre-floor, pre-reclassified IPPS hospital wage index from the prior FY 
as its basis. This has been due in part to the pre-floor, pre-
reclassified IPPS hospital wage index data that were available during 
the IPF rulemaking cycle, where an annual IPF notice or IPF PPS final 
rule was usually published in early May. This publication timeframe was 
relatively early compared to other Medicare payment rules, because the 
IPF PPS follows a RY, which was defined in the implementation of the 
IPF PPS as the 12-month period from July 1 to June 30 (69 FR 66927). 
Therefore, the best available data at the time the IPF PPS was 
implemented was the pre-floor, pre-reclassified IPPS hospital wage 
index from the prior FY (for example, the RY 2006 IPF wage index was 
based on the FY 2005 pre-floor, pre-reclassified IPPS hospital wage 
index).
    In the RY 2012 IPF PPS final rule, we changed the reporting year 
timeframe for IPFs from a RY to the FY, which begins October 1 and ends 
September 30 (76 FR 26434 through 26435). In that RY 2012 IPF PPS final 
rule, we continued our established policy of using the pre-floor, pre-
reclassified IPPS hospital wage index from the prior year (that is, 
from FY 2011) as the basis for the FY 2012 IPF wage index. This policy 
of basing a wage index on the prior year's pre-floor, pre-reclassified 
IPPS hospital wage index has been followed by other Medicare payment 
systems, such as hospice and inpatient rehabilitation facilities. By 
continuing with our established policy, we remained consistent with 
other Medicare payment systems.
    In FY 2020, we finalized the IPF wage index methodology to align 
the IPF PPS wage index with the same wage data timeframe used by the 
IPPS for FY 2020 and subsequent years. Specifically, we finalized to 
use the pre-floor, pre-reclassified IPPS hospital wage index from the 
FY concurrent with the IPF FY as the basis for the IPF wage index. For 
example, the FY 2020 IPF wage index was based on the FY 2020 pre-floor, 
pre-reclassified IPPS hospital wage index rather than on the FY 2019 
pre-floor, pre-reclassified IPPS hospital wage index.
    We explained in the FY 2020 proposed rule (84 FR 16973), that using 
the concurrent pre-floor, pre-reclassified IPPS hospital wage index 
will result in the most up-to-date wage data being the basis for the 
IPF wage index. It will also result in more consistency and parity in 
the wage index methodology used by other Medicare payment systems. The 
Medicare SNF PPS already used the concurrent IPPS hospital wage index 
data as the basis for the SNF PPS wage index. Thus, the wage adjusted 
Medicare payments of various provider types will be based upon wage 
index data from the same timeframe. CMS proposed similar policies to 
use the concurrent pre-floor, pre-reclassified IPPS hospital wage index 
data in other Medicare payment systems, such as hospice and inpatient 
rehabilitation facilities. For FY 2024, we proposed to continue using 
the concurrent pre-floor, pre-reclassified IPPS hospital wage

[[Page 51086]]

index as the basis for the IPF wage index.
    We proposed to apply the IPF wage index adjustment to the labor-
related share of the national base rate and ECT payment per treatment. 
The labor-related share of the national rate and ECT payment per 
treatment would change from 77.4 percent in FY 2023 to 78.7 percent in 
FY 2024. This percentage reflects the labor-related share of the 2021-
based IPF market basket for FY 2024 (see section IV.A of this final 
rule).
    Comment: Several commenters urged CMS to revise the IPF wage index 
methodology. Specifically, a few commenters suggested CMS revise the 
policy so that the post-reclassification and post-floor hospital IPPS 
wage index is used to calculate the wage index for IPFs. The commenter 
believes that the continued use of the pre-reclassification and pre-
floor hospital inpatient wage index is unreasonable because it places 
IPFs at a disadvantage in the labor markets in which they operate 
relative to hospitals in the same markets.
    Other commenters suggested CMS exercise its authority to refine the 
IPF PPS by applying the pre-floor, pre-reclassified IPPS hospital wage 
index for the CBSA in which the nearest IPPS hospital is located where 
the pre-floor, pre-classified IPPS hospital wage index for the CBSA in 
which the IPF is located only includes data from a closed IPPS 
hospital. Commenters stated they believe the closed hospital data is 
more likely to be unreliable such that the application of the pre-
floor, pre-reclassified IPPS hospital wage index would result in an 
inappropriately deflated wage index value. Commenters further asserted 
that the closure of the only IPPS hospital in the CBSA would suggest 
that the community is currently underserved, and would make it 
particularly appropriate to ensure that aberrant wage index data does 
not serve as an impediment to new IPF services in a community.
    Response: We appreciate the commenters' recommendations. We did not 
propose the specific policies suggested by commenters, but we will take 
them into consideration to potentially inform future rulemaking. We do 
not believe that the continued use of the pre-reclassification and pre-
floor hospital inpatient wage index for FY 2024 is unreasonable or that 
this policy puts IPFs at a disadvantage relative to hospitals in the 
labor markets in which they operate. As we have previously discussed in 
the RY 2007 final rule (71 FR 27066), we believe that the actual 
location of an IPF (as opposed to the location of affiliated providers) 
is most appropriate for determining the wage adjustment, because the 
prevailing wages in the area in which the IPF is located influence the 
cost of a case. In that same RY 2007 final rule (71 FR 27066), we also 
stated that we believe the ``rural floor'' is required only for the 
acute care hospital payment system, because section 4410 of the 
Balanced Budget Act of 1997 (Pub. L. 105-33) applies specifically to 
acute care hospitals and not excluded hospitals and excluded units. As 
we have previously discussed, the IPF wage index is intended to be a 
relative measure of the value of labor in prescribed labor market areas 
(87 FR 46857). There is a variety of reasons why our longstanding IPF 
wage index policy has not applied floors or reclassifications, which as 
we previously noted, are not applied to the IPF wage index by statute. 
For example, applying floors and reclassifications to the IPF wage 
index would significantly increase administrative burden, both for IPFs 
and for CMS, that would be associated with IPFs reclassifying from one 
CBSA to another, and it would significantly increase the complexity of 
the methodology. Furthermore, because floors and reclassifications 
would be applied budget-neutrally under the wage index, these policies 
would increase the wage index for some IPFs while reducing IPF PPS 
payments for all other IPFs, which would upset the long-settled 
expectations with which IPFs across the country have been operating. 
For these reasons, we believe using the pre-floor, pre-reclassified 
IPPS hospital wage index is the most appropriate data to use as a proxy 
for an IPF wage index.
    Regarding the suggestion to apply the wage index for the CBSA of 
the nearest IPPS hospital in cases when an IPF's CBSA includes only a 
closed IPPS hospital, we disagree with the commenter that wage data 
from a hospital that has subsequently closed is more likely to be 
unreliable and that such data would inappropriately deflate the wage 
index for that CBSA. Rather, following the longstanding methodology for 
calculating the wage index, wage data from the period during which the 
hospital was open would be comparable to wage data from the same period 
for hospitals located in other geographical areas, and would provide an 
appropriate relative measure of the value of labor in that CBSA's labor 
market area compared to others. We do not believe that such wage data 
or the wage index of a CBSA in this situation would serve as an 
impediment for either new or existing IPF services in a community. In 
addition, we recognize that in some cases, the closure of the only IPPS 
hospital in the CBSA could suggest that the community is underserved; 
however, in other cases, the lack of an IPPS hospital could be due to 
other factors, such as when an area's only IPPS hospital converts to 
another hospital type such as a CAH. We note that at this time, there 
is only one urban CBSA with no IPPS hospitals; however, there are also 
no IPFs located in this CBSA.
    Lastly, as discussed in the FY 2024 IPPS proposed rule (88 FR 
26966) in constructing the proposed FY 2024 wage index, wage data was 
included for facilities that were IPPS hospitals in FY 2020, 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 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.
    Final Decision: After consideration of the comments received, we 
are finalizing our proposal for FY 2024 to continue to use the 
concurrent pre-floor, pre-reclassified IPPS hospital wage index as the 
basis for the IPF wage index.
    We will apply the IPF wage index adjustment to the labor-related 
share of the national base rate and ECT payment per treatment. The 
labor-related share of the national rate and ECT payment per treatment 
will change from 77.4 percent in FY 2023 to 78.7 percent in FY 2024. 
This percentage reflects the labor-related share of the 2021-based IPF 
market basket for FY 2024 (see section IV.A.5 of this final rule).
b. Office of Management and Budget (OMB) Bulletins
i. Background
    The wage index used for the IPF PPS is calculated using the 
unadjusted, pre-reclassified and pre-floor IPPS wage index data and is 
assigned to the IPF on the basis of the labor market area in which the 
IPF is geographically located. IPF labor market areas are delineated 
based on the CBSAs established by the OMB.
    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

[[Page 51087]]

between the decennial censuses through OMB Bulletins. These bulletins 
contain information regarding CBSA changes, including changes to CBSA 
numbers and titles. OMB bulletins may be accessed online at https://www.whitehouse.gov/wp-content/uploads/2020/03/Bulletin-20-01.pdf. In 
accordance with our established methodology, the IPF PPS has 
historically adopted any CBSA changes that are published in the OMB 
bulletin that corresponds with the IPPS hospital wage index used to 
determine the IPF wage index and, when necessary and appropriate, has 
proposed and finalized transition policies for these changes.
    In the RY 2007 IPF PPS final rule (71 FR 27061 through 27067), we 
adopted the changes discussed in the OMB Bulletin No. 03-04 (June 6, 
2003), which announced revised definitions for Micropolitan Statistical 
Areas and the creation of Micropolitan Statistical Areas and Combined 
Statistical Areas. In adopting the OMB CBSA geographic designations in 
RY 2007, we did not provide a separate transition for the CBSA-based 
wage index since the IPF PPS was already in a transition period from 
TEFRA payments to PPS payments.
    In the RY 2009 IPF PPS notice, we incorporated the CBSA 
nomenclature changes published in the most recent OMB bulletin that 
applied to the IPPS hospital wage index used to determine the current 
IPF wage index and stated that we expected to continue to do the same 
for all the OMB CBSA nomenclature changes in future IPF PPS rules and 
notices, as necessary (73 FR 25721).
    Subsequently, CMS adopted the changes that were published in past 
OMB bulletins in the FY 2016 IPF PPS final rule (80 FR 46682 through 
46689), the FY 2018 IPF PPS rate update (82 FR 36778 through 36779), 
the FY 2020 IPF PPS final rule (84 FR 38453 through 38454), and the FY 
2021 IPF PPS final rule (85 FR 47051 through 47059). We direct readers 
to each of these rules for more information about the changes that were 
adopted and any associated transition policies.
    In part due to the scope of changes involved in adopting the CBSA 
delineations for FY 2021, we finalized a 2-year transition policy 
consistent with our past practice of using transition policies to help 
mitigate negative impacts on hospitals of certain wage index policy 
changes. We applied a 5-percent cap on wage index decreases to all IPF 
providers that had any decrease in their wage indexes, regardless of 
the circumstance causing the decline, so that an IPF's final wage index 
for FY 2021 will not be less than 95 percent of its final wage index 
for FY 2020, regardless of whether the IPF was part of an updated CBSA. 
We refer readers to the FY 2021 IPF PPS final rule (85 FR 47058 through 
47059) for a more detailed discussion about the wage index transition 
policy for FY 2021.
    On March 6, 2020 OMB issued OMB Bulletin 20-01 (available on the 
web at https://www.whitehouse.gov/wp-content/uploads/2020/03/Bulletin-20-01.pdf). In considering whether to adopt this bulletin, we analyzed 
whether the changes in this bulletin would have a material impact on 
the IPF PPS wage index. This bulletin creates only one Micropolitan 
statistical area. As discussed in further detail in section IV.D.1.b.ii 
of this final rule, since Micropolitan areas are considered rural for 
the IPF PPS wage index, this bulletin has no material impact on the IPF 
PPS wage index. That is, the constituent county of the new Micropolitan 
area was considered rural effective as of FY 2021 and would continue to 
be considered rural if we adopted OMB Bulletin 20-01. Therefore, we did 
not propose to adopt OMB Bulletin 20-01 in the FY 2022 IPF PPS proposed 
rule.
    In the FY 2023 IPF PPS final rule (87 FR 46856 through 46859), we 
finalized a permanent 5-percent cap on any decrease to a provider's 
wage index from its wage index in the prior year, and we stated that we 
would apply this cap in a budget-neutral manner. Additionally, we 
finalized a policy that a new IPF would be paid the wage index for the 
area in which it is geographically located for its first full or 
partial FY with no cap applied because a new IPF would not have a wage 
index in the prior FY. We amended the IPF PPS regulations at Sec.  
412.424(d)(1)(i) to reflect this permanent cap on wage index decreases. 
We refer readers to the FY 2023 IPF PPS final rule for a more detailed 
discussion about this policy.
ii. Micropolitan Statistical Areas (MSA)
    OMB defines a ``Micropolitan Statistical Area'' as a CBSA 
associated with at least one urban cluster that has a population of at 
least 10,000, but less than 50,000 (75 FR 37252). We refer to these as 
Micropolitan Areas. After extensive impact analysis, consistent with 
the treatment of these areas under the IPPS as discussed in the FY 2005 
IPPS final rule (69 FR 49029 through 49032), we determined the best 
course of action would be to treat Micropolitan Areas as ``rural'' and 
include them in the calculation of each state's IPF PPS rural wage 
index. We refer the reader to the FY 2007 IPF PPS final rule (71 FR 
27064 through 27065) for a complete discussion regarding treating 
Micropolitan Areas as rural.
c. Adjustment for Rural Location
    In the November 2004 IPF PPS final rule, (69 FR 66954), we provided 
a 17 percent payment adjustment for IPFs located in a rural area. This 
adjustment was based on the regression analysis, which indicated that 
the per diem cost of rural facilities was 17 percent higher than that 
of urban facilities after accounting for the influence of the other 
variables included in the regression. This 17 percent adjustment has 
been part of the IPF PPS each year since the inception of the IPF PPS. 
For FY 2024, we proposed to apply a 17 percent payment adjustment for 
IPFs located in a rural area as defined at Sec.  412.64(b)(1)(ii)(C) 
(see 69 FR 66954 for a complete discussion of the adjustment for rural 
locations).
d. Budget Neutrality Adjustment
    Changes to the wage index are made in a budget-neutral manner so 
that updates do not increase expenditures. Therefore, for FY 2024, we 
proposed to apply a budget-neutrality adjustment in accordance with our 
existing budget-neutrality policy. This policy requires us to update 
the wage index in such a way that total estimated payments to IPFs for 
FY 2024 are the same with or without the changes (that is, in a budget-
neutral manner) by applying a budget-neutrality factor to the IPF PPS 
rates. We use the following steps to ensure that the rates reflect the 
FY 2024 update to the wage indexes (based on the FY 2020 hospital cost 
report data) and the labor-related share in a budget-neutral manner:
    Step 1: Simulate estimated IPF PPS payments, using the FY 2023 IPF 
wage index values (available on the CMS website) and labor-related 
share (as published in the FY 2023 IPF PPS final rule (87 FR 46846).
    Step 2: Simulate estimated IPF PPS payments using the FY 2024 IPF 
wage index values (available on the CMS website) and FY 2024 labor-
related share (based on the latest available data as discussed 
previously).
    Step 3: Divide the amount calculated in step 1 by the amount 
calculated in step 2. The resulting quotient is the FY 2024 budget-
neutral wage adjustment factor of 1.0016.
    Step 4: Apply the FY 2024 budget-neutral wage adjustment factor 
from step 3 to the FY 2023 IPF PPS Federal per diem base rate after the 
application of the market basket update described in section IV.A of 
this final rule, to determine the FY 2024 IPF PPS Federal per diem base 
rate.

[[Page 51088]]

2. Teaching Adjustment
a. Background
    In the November 2004 IPF PPS final rule, we implemented regulations 
at Sec.  412.424(d)(1)(iii) to establish a facility-level adjustment 
for IPFs that are, or are part of, teaching hospitals. The teaching 
adjustment accounts for the higher indirect operating costs experienced 
by hospitals that participate in graduate medical education (GME) 
programs. The payment adjustments are made based on the ratio of the 
number of fulltime equivalent (FTE) interns and residents training in 
the IPF and the IPF's average daily census.
    Medicare makes direct GME payments (for direct costs such as 
resident and teaching physician salaries, and other direct teaching 
costs) to all teaching hospitals including those paid under a PPS, and 
those paid under the TEFRA rate-of-increase limits. These direct GME 
payments are made separately from payments for hospital operating costs 
and are not part of the IPF PPS. The direct GME payments do not address 
the estimated higher indirect operating costs teaching hospitals may 
face.
    The results of the regression analysis of FY 2002 IPF data 
established the basis for the payment adjustments included in the 
November 2004 IPF PPS final rule. The results showed that the indirect 
teaching cost variable is significant in explaining the higher costs of 
IPFs that have teaching programs. We calculated the teaching adjustment 
based on the IPF's ``teaching variable'', which is (1 + [the number of 
FTE residents training in the IPF's average daily census]). The 
teaching variable is then raised to the 0.5150 power to result in the 
teaching adjustment. This formula is subject to the limitations on the 
number of FTE residents, which are described in this section of this 
final rule.
    We established the teaching adjustment in a manner that limited the 
incentives for IPFs to add FTE residents for the purpose of increasing 
their teaching adjustment. We imposed a cap on the number of FTE 
residents that may be counted for purposes of calculating the teaching 
adjustment. The cap limits the number of FTE residents that teaching 
IPFs may count for the purpose of calculating the IPF PPS teaching 
adjustment, not the number of residents teaching institutions can hire 
or train. We calculated the number of FTE residents that trained in the 
IPF during a ``base year'' and used that FTE resident number as the 
cap. An IPF's FTE resident cap is ultimately determined based on the 
final settlement of the IPF's most recent cost report filed before 
November 15, 2004 (69 FR 66955). A complete discussion of the temporary 
adjustment to the FTE cap to reflect residents due to hospital closure 
or residency program closure appears in the RY 2012 IPF PPS proposed 
rule (76 FR 5018 through 5020) and the RY 2012 IPF PPS final rule (76 
FR 26453 through 26456).
    In the regression analysis, the logarithm of the teaching variable 
had a coefficient value of 0.5150. We converted this cost effect to a 
teaching payment adjustment by treating the regression coefficient as 
an exponent and raising the teaching variable to a power equal to the 
coefficient value. We note that the coefficient value of 0.5150 was 
based on the regression analysis holding all other components of the 
payment system constant. A complete discussion of how the teaching 
adjustment was calculated appears in the November 2004 IPF PPS final 
rule (69 FR 66954 through 66957) and the RY 2009 IPF PPS notice (73 FR 
25721). As with other adjustment factors derived through the regression 
analysis, we do not plan to propose updates to the teaching adjustment 
factors until we more fully analyze IPF PPS data. Therefore, in this FY 
2024 final rule, we are retaining the coefficient value of 0.5150 for 
the teaching adjustment to the Federal per diem base rate.
    Comment: One commenter recommended CMS update its methodology for 
calculating the IPF teaching adjustment, particularly in recognition of 
the Congress authorizing the awarding of new Medicare-reimbursable 
residency positions under the CAA, 2023 and the Consolidated 
Appropriations Act, 2021 (hereafter referred to as CAA, 2021) (Pub. L. 
116-260). This commenter suggested CMS collect information on awards of 
new Medicare residency positions under section 126 of division CC, CAA, 
2021 and section 4122 of CAA, 2023 from those hospitals subject to the 
IPF so that it can provide resident FTE cap increases under the IPF for 
those hospitals that receive awards for psychiatry programs.
    One commenter requested that CMS permit IPFs to aggregate and 
adjust their FTE caps through affiliation agreements. The commenter 
noted training residents often indirectly increases the hospital's 
operational costs, but freestanding IPFs that take over this role are 
unable to receive any corresponding payment increase that was 
previously available to the host-hospital distinct part unit (DPU).
    Response: We appreciate the commenter's suggestion regarding 
potential changes to the IPF teaching adjustment to recognize new 
Medicare-reimbursable residency positions under the CAA, 2023 and the 
CAA, 2021. The CAA, 2021 and CAA, 2023 established resident slots for 
direct medical education and indirect medical education, which are paid 
under the IPPS. We will take this comment into consideration to 
potentially inform future rulemaking for the IPF PPS.
    Regarding the commenter's suggestion to recognize affiliation 
agreements, we did not propose to recognize affiliation agreements for 
the IPF PPS teaching adjustment and are not making a change to this 
policy. As we previously stated in the RY 2005 IPF PPS final rule (69 
FR 66956), our intent is not to affect affiliation agreements and 
rotational arrangements for hospitals that have residents that train in 
more than one hospital. We have not implemented a provision concerning 
affiliation agreements specifically pertaining to the FTE caps used in 
the teaching adjustment under the IPF PPS.
    Final Decision: We are finalizing as proposed to calculate the IPF 
teaching adjustment according to our established methodology.
3. Cost of Living Adjustment (COLA) for IPFs Located in Alaska and 
Hawaii
    The IPF PPS includes a payment adjustment for IPFs located in 
Alaska and Hawaii based upon the area in which the IPF is located. As 
we explained in the November 2004 IPF PPS final rule, the FY 2002 data 
demonstrated that IPFs in Alaska and Hawaii had per diem costs that 
were disproportionately higher than other IPFs. Other Medicare 
prospective payment systems (for example, the IPPS and LTCH PPS) 
adopted a COLA to account for the cost differential of care furnished 
in Alaska and Hawaii.
    We analyzed the effect of applying a COLA to payments for IPFs 
located in Alaska and Hawaii. The results of our analysis demonstrated 
that a COLA for IPFs located in Alaska and Hawaii will improve payment 
equity for these facilities. As a result of this analysis, we provided 
a COLA in the November 2004 IPF PPS final rule.
    A COLA for IPFs located in Alaska and Hawaii is made by multiplying 
the non-labor-related portion of the Federal per diem base rate by the 
applicable COLA factor based on the COLA area in which the IPF is 
located.
    The COLA factors through 2009 were published by the Office of 
Personnel Management (OPM), and the OPM memo showing the 2009 COLA 
factors is available at https://www.chcoc.gov/

[[Page 51089]]

content/nonforeign-area-retirement-equity-assurance-act.
    We note that the COLA areas for Alaska are not defined by county as 
are the COLA areas for Hawaii. In 5 CFR 591.207, the OPM established 
the following COLA areas:
     City of Anchorage, and 80-kilometer (50-mile) radius by 
road, as measured from the Federal courthouse.
     City of Fairbanks, and 80-kilometer (50-mile) radius by 
road, as measured from the Federal courthouse.
     City of Juneau, and 80-kilometer (50-mile) radius by road, 
as measured from the Federal courthouse.
     Rest of the state of Alaska.
    As stated in the November 2004 IPF PPS final rule, we update the 
COLA factors according to updates established by the OPM. However, 
sections 1911 through 1919 of the Non-foreign Area Retirement Equity 
Assurance Act, as contained in subtitle B of title XIX of the National 
Defense Authorization Act (NDAA) (Pub. L. 111-84, October 28, 2009), 
for FY 2010 transitions the Alaska and Hawaii COLAs to locality pay. 
Under section 1914 of NDAA, locality pay was phased in over a 3-year 
period beginning in January 2010, with COLA rates frozen as of the date 
of enactment, October 28, 2009, and then proportionately reduced to 
reflect the phase-in of locality pay.
    When we published the proposed COLA factors in the RY 2012 IPF PPS 
proposed rule (76 FR 4998), we inadvertently selected the FY 2010 COLA 
rates, which had been reduced to account for the phase-in of locality 
pay. We did not intend to propose the reduced COLA rates because that 
would have understated the adjustment. Since the 2009 COLA rates did 
not reflect the phase-in of locality pay, we finalized the FY 2009 COLA 
rates for RY 2010 through RY 2014.
    In the FY 2013 IPPS/LTCH final rule (77 FR 53700 through 53701), we 
established a new methodology to update the COLA factors for Alaska and 
Hawaii and adopted this methodology for the IPF PPS in the FY 2015 IPF 
PPS final rule (79 FR 45958 through 45960). We adopted this new COLA 
methodology for the IPF PPS because IPFs are hospitals with a similar 
mix of commodities and services. We believe it is appropriate to have a 
consistent policy approach with that of other hospitals in Alaska and 
Hawaii. Therefore, the IPF COLAs for FY 2015 through FY 2017 were the 
same as those applied under the IPPS in those years. As finalized in 
the FY 2013 IPPS/LTCH PPS final rule (77 FR 53700 and 53701), the COLA 
updates are determined every 4 years, when the IPPS market basket 
labor-related share is updated. Because the labor-related share of the 
IPPS market basket was updated for FY 2022, the COLA factors were 
updated in FY 2022 IPPS/LTCH rulemaking (86 FR 45547). As such, we also 
updated the IPF PPS COLA factors for FY 2022 (86 FR 42621 through 
42622) to reflect the updated COLA factors finalized in the FY 2022 
IPPS/LTCH rulemaking. Table 16 shows the IPF PPS COLA factors effective 
for FY 2022 through FY 2025.
[GRAPHIC] [TIFF OMITTED] TR02AU23.017

    The IPF PPS COLA factors for FY 2024 are also shown in Addendum A 
to this final rule, which is available at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/tools.html.
4. Adjustment for IPFs With a Qualifying Emergency Department (ED)
    The IPF PPS includes a facility-level adjustment for IPFs with 
qualifying EDs. We provide an adjustment to the Federal per diem base 
rate to account for the costs associated with maintaining a full-
service ED. The adjustment is intended to account for ED costs incurred 
by a psychiatric hospital with a qualifying ED or an excluded 
psychiatric unit of an IPPS hospital or a CAH, for preadmission 
services otherwise payable under the Medicare Hospital Outpatient 
Prospective Payment System (OPPS), furnished to a beneficiary on the 
date of the beneficiary's admission to the hospital and during the day 
immediately preceding the date of admission to the IPF (see Sec.  
413.40(c)(2)), and the overhead cost of maintaining the ED. This 
payment is a facility-level adjustment that applies to all IPF 
admissions (with one exception, which we described), regardless of 
whether a particular patient receives preadmission services in the 
hospital's ED.
    The ED adjustment is incorporated into the variable per diem 
adjustment for the first day of each stay for IPFs with a qualifying 
ED. Those IPFs with a qualifying ED receive an adjustment factor of 
1.31 as the variable per diem adjustment for day 1 of each patient 
stay. If an IPF does not have a qualifying ED, it receives an 
adjustment factor of 1.19 as the variable per diem adjustment for day 1 
of each patient stay.
    The ED adjustment is made on every qualifying claim except as 
described in

[[Page 51090]]

this section of this final rule. As specified in Sec.  
412.424(d)(1)(v)(B), the ED adjustment is not made when a patient is 
discharged from an IPPS hospital or CAH and admitted to the same IPPS 
hospital's or CAH's excluded psychiatric unit. We clarified in the 
November 2004 IPF PPS final rule (69 FR 66960) that an ED adjustment is 
not made in this case because the costs associated with ED services are 
reflected in the DRG payment to the IPPS hospital or through the 
reasonable cost payment made to the CAH.
    Therefore, when patients are discharged from an IPPS hospital or 
CAH and admitted to the same hospital's or CAH's excluded psychiatric 
unit, the IPF receives the 1.19 adjustment factor as the variable per 
diem adjustment for the first day of the patient's stay in the IPF. For 
FY 2024, we proposed to retain the 1.31 adjustment factor for IPFs with 
qualifying EDs. A complete discussion of the steps involved in the 
calculation of the ED adjustment factors are in the November 2004 IPF 
PPS final rule (69 FR 66959 through 66960) and the RY 2007 IPF PPS 
final rule (71 FR 27070 through 27072).
    As we did not propose any changes to the ED adjustment, we are 
retaining the existing ED adjustment for FY 2024.

E. Other Proposed Payment Adjustments and Policies

1. Outlier Payment Overview
    The IPF PPS includes an outlier adjustment to promote access to IPF 
care for those patients who require expensive care and to limit the 
financial risk of IPFs treating unusually costly patients. In the 
November 2004 IPF PPS final rule, we implemented regulations at Sec.  
412.424(d)(3)(i) to provide a per case payment for IPF stays that are 
extraordinarily costly. Providing additional payments to IPFs for 
extremely costly cases strongly improves the accuracy of the IPF PPS in 
determining resource costs at the patient and facility level. These 
additional payments reduce the financial losses that would otherwise be 
incurred in treating patients who require costlier care, and therefore, 
reduce the incentives for IPFs to under-serve these patients. We make 
outlier payments for discharges in which an IPF's estimated total cost 
for a case exceeds a fixed dollar loss threshold amount (multiplied by 
the IPF's facility-level adjustments) plus the Federal per diem payment 
amount for the case.
    In instances when the case qualifies for an outlier payment, we pay 
80 percent of the difference between the estimated cost for the case 
and the adjusted threshold amount for days 1 through 9 of the stay 
(consistent with the median LOS for IPFs in FY 2002), and 60 percent of 
the difference for day 10 and thereafter. The adjusted threshold amount 
is equal to the outlier threshold amount adjusted for wage area, 
teaching status, rural area, and the COLA adjustment (if applicable), 
plus the amount of the Medicare IPF payment for the case. We 
established the 80 percent and 60 percent loss sharing ratios because 
we were concerned that a single ratio established at 80 percent (like 
other Medicare PPSs) might provide an incentive under the IPF per diem 
payment system to increase LOS in order to receive additional payments.
    After establishing the loss sharing ratios, we determined the 
current fixed dollar loss threshold amount through payment simulations 
designed to compute a dollar loss beyond which payments are estimated 
to meet the 2 percent outlier spending target. Each year when we update 
the IPF PPS, we simulate payments using the latest available data to 
compute the fixed dollar loss threshold so that outlier payments 
represent 2 percent of total estimated IPF PPS payments.
2. Update to the Outlier Fixed Dollar Loss Threshold Amount
    In accordance with the update methodology described in Sec.  
412.428(d), we proposed to update the fixed dollar loss threshold 
amount used under the IPF PPS outlier policy. Based on the regression 
analysis and payment simulations used to develop the IPF PPS, we 
established a 2 percent outlier policy, which strikes an appropriate 
balance between protecting IPFs from extraordinarily costly cases while 
ensuring the adequacy of the Federal per diem base rate for all other 
cases that are not outlier cases.
    Our longstanding methodology for updating the outlier fixed dollar 
loss threshold involves using the best available data, which is 
typically the most recent available data. For the FY 2022 IPF PPS final 
rule, we finalized the use of FY 2019 claims rather than the more 
recent FY 2020 claims for updating the outlier fixed dollar loss 
threshold (86 FR 42623). We noted that our use of the FY 2019 claims to 
set the final outlier fixed dollar loss threshold for FY 2022 deviated 
from our longstanding practice of using the most recent available year 
of claims but remained otherwise consistent with the established 
outlier update methodology. We explained that we finalized our proposal 
to deviate from our longstanding practice of using the most recent 
available year of claims only because, and to the extent that, the 
``coronavirus disease 2019'' (abbreviated ``COVID-19'') Public Health 
Emergency (PHE) appeared to have significantly impacted the FY 2020 IPF 
claims. We further stated that we intended to continue to analyze 
further data in order to better understand both the short-term and 
long-term effects of the COVID-19 PHE on IPFs (86 FR 42624).
    In the FY 2023 IPF PPS final rule (87 FR 46862 through 46864) we 
noted that we observed an overall increase in average cost per day and 
an overall decrease in the number of covered days. However, we 
identified that some providers had significant increases in their 
charges, resulting in higher-than-normal estimated cost per day that 
would skew our estimate of outlier payments for FY 2022 and FY 2023. We 
finalized our proposal for FY 2023 to use the latest available FY 2021 
claims, in accordance with our longstanding practice, to simulate 
payments for determining the final FY 2023 IPF PPS outlier fixed dollar 
loss threshold amount. In addition, we finalized a methodology for FY 
2023 to exclude providers from our impact simulations whose change in 
simulated cost per day is outside 3 standard deviations from the mean.
    For the FY 2024 IPF PPS proposed rule, consistent with our 
longstanding practice, we analyzed the most recent available data for 
simulating IPF PPS payments in FY 2023. Based on an analysis of these 
updated data, we estimated that IPF outlier payments as a percentage of 
total estimated payments were approximately 3.0 percent in FY 2023. We 
analyzed the change in providers' charges from the FY 2021 claims that 
were used to simulate payments for determining the final FY 2023 IPF 
PPS outlier threshold, and the latest available FY 2022 claims. In 
contrast to our analysis of FY 2021 claims for the FY 2023 IPF PPS 
proposed and final rules, we did not find the same level of significant 
increases in charges in the FY 2022 claims that we believe would skew 
our estimate of outlier payments for FY 2023 and FY 2024. Therefore, we 
proposed to update the outlier threshold amount to $34,750. This would 
allow us to maintain estimated outlier payments at 2 percent of total 
estimated aggregate IPF payments for FY 2024. This proposed update was 
an increase from the FY 2023 threshold of $24,630. We solicited 
comments on this proposed increase to the outlier threshold for FY 
2024, and whether we should consider alternative methodologies for FY 
2024.

[[Page 51091]]

Specifically, we were interested in understanding whether commenters 
believe it would be appropriate to exclude providers from our FY 2024 
impact simulations whose change in simulated cost per day is outside 3 
standard deviations from the mean, following the same methodology we 
applied in FY 2023. We noted that our analysis for the FY 2024 proposed 
rule showed that the FY 2024 outlier fixed dollar loss threshold amount 
would be closer to $30,000 if we were to exclude providers based on the 
same methodology finalized for FY 2023. We were also interested in 
other methodologies that commenters believe might be appropriate to 
consider, including why commenters believe applying such a methodology 
would be appropriate for establishing the outlier threshold for FY 
2024.
    Comment: We received five comments in response to the FY 2024 IPF 
PPS pertaining to an alternative IPF PPS outlier policy. Commenters 
included state-level and national provider associations. One commenter 
stated the increase in the outlier threshold amount should be limited 
to no more than the market basket update for the year but did not 
provide a rationale for this suggestion. Two commenters recommended CMS 
mitigate the financial impact that imperfect outlier threshold 
estimates have on IPFs. Four commenters requested that CMS explain in 
greater detail the factors driving the increase and that CMS examine 
its methodology and consider making changes to mitigate increases to 
the outlier threshold. Commenters also requested information on how the 
proposed increase would affect the IPF field and its patients.
    Response: We appreciate the suggestions from commenters regarding 
mitigating the financial impact of the outlier threshold on IPFs and 
the use of alternative methodologies for estimating the outlier 
threshold. We are not finalizing any of the alternative methodologies 
that commenters suggested, but we are providing additional information 
about the drivers and impact of the increase to the outlier threshold, 
as commenters requested.
    As we previously noted in the FY 2023 final rule (87 FR 46863), we 
observed two main trends in the claims data for FY 2020 and FY 2021. In 
summary, these were an increase in average cost per day and a decrease 
in total IPF PPS payments corresponding with a decrease in covered IPF 
PPS days. Both of these trends continued in the FY 2022 claims data 
used for this FY 2024 IPF PPS final rule. First, we observed that 
average cost per day increased approximately 8 percent when comparing 
the simulated FY 2022 IPF PPS payments from the FY 2023 IPF PPS final 
rule to the simulated FY 2023 IPF PPS payments that we used to estimate 
the outlier percentage for this FY 2024 IPF PPS final rule. In the FY 
2022 IPF PPS proposed rule (86 FR 19526), we explained that we estimate 
the costs per case based on the covered charges on each IPF claim and 
the IPF's most recent CCR. The second continued trend that we observed 
was that the number of covered days continued to decrease in the FY 
2022 claims. The number of covered days in the FY 2022 claims were 
approximately 12 percent lower than the number of covered days in the 
FY 2021 claims used for FY 2023 final rulemaking, before applying the 
statistical trim for the FY 2023 IPF PPS final rule (87 FR 46862). This 
decrease in covered days corresponds with a decrease of approximately 
10 percent in the total simulated FY 2023 IPF PPS payments compared to 
total simulated FY 2022 IPF PPS payments used for FY 2023 final 
rulemaking. In addition, when comparing the data used for this FY 2024 
IPF PPS final rule with the statistically trimmed data used for the FY 
2023 IPF PPS final rule, the covered days for FY 2024 were 
approximately 8 percent lower than FY 2023, and total simulated FY 2023 
IPF PPS payments that we used to estimate the outlier percentage for 
this FY 2024 IPF PPS final rule were approximately 4 percent lower than 
total simulated FY 2022 IPF PPS payments. Because we calculate the 
outlier fixed dollar loss threshold amount so that outlier payments 
represent 2 percent of total estimated IPF PPS payments, the decrease 
to the number of days and total estimated IPF PPS payments increases 
the percentage of outlier payments relative to total payments, which 
contributes to the upward trend in the outlier fixed dollar loss 
threshold amount. In our simulated FY 2023 outlier payments using the 
FY 2023 IPF PPS outlier fixed dollar loss threshold of $24,630, we 
estimated that 5,817 cases will receive outlier payments, with a mean 
outlier payment amount per outlier case of $13,807.28. We observed that 
the distribution of simulated FY 2023 outlier payments is skewed right, 
which means that a large number of outlier cases receive relatively 
small amounts of outlier payments, and a smaller number of outlier 
cases receive relatively large outlier payments. Consequently, half of 
all simulated outlier cases receive outlier payments of $7,543.65 or 
less, and 559 cases receive outlier payments of $1,000 or less. We also 
observed that outlier payments are concentrated among certain types of 
IPFs. As shown in Table 40, in section VIII.C.2 of this final rule, 
urban government-owned IPF units are projected to experience the 
largest decreases in estimated payments as a result of the increase to 
the outlier fixed dollar loss threshold amount, because these providers 
had a larger share of outlier cases than other provider types. We did 
not observe that changes in case mix appear to be driving the increase 
in the outlier percentage. In the simulated FY 2023 IPF PPS payments, 
we observed that approximately 79 percent of outlier cases are for DRG 
885 (Psychoses), which aligns with the proportion of IPF PPS cases that 
typically receive that DRG. We estimate that the average outlier 
payment for cases with DRG 885 is $14,485.21, which is comparable to 
the average outlier payment for all cases.
    Regarding the suggestion to limit increases to the outlier 
threshold to no more than the market basket update, we are concerned 
that this methodology would not be technically appropriate for the IPF 
PPS outlier policy. As discussed earlier in this section, the 
longstanding IPF PPS 2-percent outlier policy was established based on 
the regression analysis and payment simulations used to develop the IPF 
PPS. We have previously explained that the 2-percent outlier policy 
strikes an appropriate balance between protecting IPFs from 
extraordinarily costly cases while ensuring the adequacy of the Federal 
per diem base rate for all other cases that are not outlier cases. Each 
year when we update the IPF PPS, we simulate payments using the latest 
available data to compute the fixed dollar loss threshold so that 
outlier payments represent 2 percent of total estimated IPF PPS 
payments. For this FY 2024 IPF PPS final rule, we have simulated 
payments using the latest available data, and these payment simulations 
indicate that an increase to the outlier fixed dollar loss threshold is 
necessary in order to maintain outlier payments at 2 percent of total 
payments. We are concerned that limiting increases to the outlier fixed 
dollar loss threshold to no more than the market basket update 
percentage would not appropriately target outlier payments such that 
they remain at 2 percent of total IPF PPS payments and that such a 
policy would increase outlier payments above the 2 percent target for 
FY 2024. As we noted in the prior paragraph, we observe that the 
increase in the outlier fixed dollar loss threshold is driven in part 
by a continual downward trend in

[[Page 51092]]

covered days over the past several years. We are concerned that it 
would not be appropriate to increase outlier payments to offset the 
fact that IPFs are providing fewer days of care for Medicare 
beneficiaries.
    Final Decision: After consideration of the comments received, we 
are finalizing our proposal to update the fixed dollar loss threshold 
amount used under the IPF PPS outlier policy. Based on the latest 
available data, we are finalizing an outlier fixed dollar loss 
threshold amount of $33,470 for FY 2024.
3. Update to IPF Cost-To-Charge Ratio Ceilings
    Under the IPF PPS, an outlier payment is made if an IPF's cost for 
a stay exceeds a fixed dollar loss threshold amount plus the IPF PPS 
amount. In order to establish an IPF's cost for a particular case, we 
multiply the IPF's reported charges on the discharge bill by its 
overall cost-to-charge ratio (CCR). This approach to determining an 
IPF's cost is consistent with the approach used under the IPPS and 
other PPSs. In the FY 2004 IPPS final rule (68 FR 34494), we 
implemented changes to the IPPS policy used to determine CCRs for IPPS 
hospitals, because we became aware that payment vulnerabilities 
resulted in inappropriate outlier payments. Under the IPPS, we 
established a statistical measure of accuracy for CCRs to ensure that 
aberrant CCR data did not result in inappropriate outlier payments.
    As indicated in the November 2004 IPF PPS final rule (69 FR 66961), 
we believe that the IPF outlier policy is susceptible to the same 
payment vulnerabilities as the IPPS; therefore, we adopted a method to 
ensure the statistical accuracy of CCRs under the IPF PPS. 
Specifically, we adopted the following procedure in the November 2004 
IPF PPS final rule:
     Calculated two national ceilings, one for IPFs located in 
rural areas and one for IPFs located in urban areas.
     Computed the ceilings by first calculating the national 
average and the standard deviation of the CCR for both urban and rural 
IPFs using the most recent CCRs entered in the most recent Provider 
Specific File (PSF) available.
    For FY 2024, we proposed to continue to follow this methodology.
    To determine the rural and urban ceilings, we multiplied each of 
the standard deviations by 3 and added the result to the appropriate 
national CCR average (either rural or urban). The upper threshold CCR 
for IPFs in FY 2024 is 2.1419 for rural IPFs, and 1.8026 for urban 
IPFs, based on CBSA-based geographic designations. If an IPF's CCR is 
above the applicable ceiling, the ratio is considered statistically 
inaccurate, and we assign the appropriate national (either rural or 
urban) median CCR to the IPF.
    We apply the national median CCRs to the following situations:
     New IPFs that have not yet submitted their first Medicare 
cost report. We continue to use these national median CCRs until the 
facility's actual CCR can be computed using the first tentatively or 
final settled cost report.
     IPFs whose overall CCR is in excess of three standard 
deviations above the corresponding national geometric mean (that is, 
above the ceiling).
     Other IPFs for which the Medicare Administrative 
Contractor (MAC) obtains inaccurate or incomplete data with which to 
calculate a CCR.
    We proposed to update the FY 2024 national median and ceiling CCRs 
for urban and rural IPFs based on the CCRs entered in the latest 
available IPF PPS PSF.
    Specifically, for FY 2024, to be used in each of the three 
situations listed previously, using the most recent CCRs entered in the 
CY 2022 PSF, we provided an estimated national median CCR of 0.5720 for 
rural IPFs and a national median CCR of 0.4200 for urban IPFs. These 
calculations are based on the IPF's location (either urban or rural) 
using the CBSA-based geographic designations. A complete discussion 
regarding the national median CCRs appears in the November 2004 IPF PPS 
final rule (69 FR 66961 through 66964).
4. Modification to the Regulation for Excluded Psychiatric Units Paid 
Under the IPF PPS
a. Background
    Under current regulation, in order to be excluded from the IPPS and 
paid under the IPF PPS or the IRF PPS, an IPF or IRF unit of a hospital 
must meet a number of requirements under 42 CFR 412.25. As discussed in 
the following paragraphs, both this regulation and the policies 
applying to excluded units (which include excluded IRF units and 
excluded IPF units) have been in effect since before both the IPF PPS 
and IRF PPS were established. Before the IRF PPS and the IPF PPS were 
established, excluded units were paid based on their costs, as reported 
on their Medicare cost reports, subject to certain facility-specific 
cost limits. These cost-based payments were determined separately for 
operating and capital costs. Thus, under cost-based payments, the 
process of allocating costs to an IPF unit for reimbursement created 
significant administrative complexity. This administrative complexity 
necessitated strict regulations that allowed hospitals to open a new 
IPPS-excluded unit only at the start of a cost reporting period.
    In the January 3, 1984 final rule (49 FR 235), CMS (then known as 
the Health Care Financing Administration) established policies and 
regulations for hospitals and units subject to and excluded from the 
IPPS. In that rule, we explained that section 1886(d) of the Act 
requires that the prospective payment system apply to inpatient 
hospital services furnished by all hospitals participating in the 
Medicare program except those hospitals or units specifically excluded 
by the law. We further explained our expectation that a hospital's 
status (that is, whether it is subject to, or excluded from, the 
prospective payment system) would generally be determined at the 
beginning of each cost reporting period. We also stated that this 
status would continue throughout the period, which is normally 1 year. 
Accordingly, we stated that changes in a hospital's (or unit's) status 
that result from meeting or failing to meet the criteria for exclusion 
would be implemented only at the start of a cost reporting period. 
However, we also acknowledged that under some circumstances involving 
factors external to the hospital, status changes could be made at times 
other than the beginning of the cost reporting period. For example, a 
change in status could occur if a hospital is first included under the 
prospective payment system and, after the start of its cost reporting 
period, is excluded because of its participation in an approved 
demonstration project or State reimbursement control program that 
begins after the hospital's cost reporting period has begun.
    In the 1993 IPPS final rule (57 FR 39798 through 39799), we 
codified our longstanding policies regarding when a hospital unit can 
change its status from not excluded to excluded. We explained in that 
final rule that since the inception of the PPS for operating costs of 
hospital inpatient services in October 1983, certain types of 
specialty-care hospitals and hospital units have been excluded from 
that system under section 1888(d)(1)(B) of the Act. We noted that these 
currently include psychiatric and rehabilitation hospitals and distinct 
part units, children's hospitals, and long-term care hospitals. We 
further explained that section 6004(a)(1) of Public Law 101-239 amended 
section 1886(d)(1)(B) of the Act to provide that certain cancer 
hospitals are also excluded. We noted that the preamble to the January 
3, 1984 final rule

[[Page 51093]]

implementing the PPS for operating costs (49 FR 235) stated that the 
status of a hospital or unit (that is, whether it is subject to, or 
excluded from, the PPS) will be determined at the beginning of each 
cost reporting period. We noted that that same 1984 final rule also 
provided that changes in a hospital's or unit's status that result from 
meeting or failing to meet the criteria for exclusion will be 
implemented prospectively only at the start of a cost reporting period, 
that is, starting with the beginning date of the next cost reporting 
period (49 FR 243). However, we noted that this policy was not set 
forth in the regulations. In that 1993 IPPS final rule, we stated that 
we proposed revising Sec. Sec.  412.22 and 412.25 to specify that 
changes in the status of each hospital or hospital unit would be 
recognized only at the start of a cost reporting period. We stated 
that, except in the case of retroactive payment adjustments for 
excluded rehabilitation units described in Sec.  412.30(c), any change 
in a hospital's or unit's compliance with the exclusion criteria that 
occurs after the start of a cost reporting period would not be taken 
into consideration until the start of the following period. We noted 
that this policy would also apply to any unit that is added to a 
hospital during the hospital's cost reporting period. We also stated 
that we proposed revising Sec.  412.25(a) to specify that as a 
requirement for exclusion, a hospital unit must be fully equipped and 
staffed, and be capable of providing inpatient psychiatric or 
rehabilitation care as of the first day of the first cost reporting 
period for which all other exclusion requirements are met. We explained 
that a unit that meets this requirement would be considered open 
regardless of whether there are any inpatients in the unit.
    In the same 1993 IPPS final rule, we responded to commenters who 
objected to this policy, stating that it unnecessarily penalizes 
hospitals for factors beyond their control, such as construction 
delays, that it discourages hospitals from making changes in their 
programs to meet community needs, or that it can place undue workload 
demands on regulatory agencies during certain time periods. In 
response, we explained that we believed that regulatory agencies, 
hospitals, and the public generally would benefit from policies that 
are clearly stated, can be easily understood by both hospitals and 
intermediaries, and can be simply administered. We stated that 
recognizing changes in status only at the beginning of cost reporting 
periods is consistent with these goals, while recognizing changes in 
the middle of cost reporting periods would introduce added complexity 
to the administration of the exclusion provisions. Therefore, we did 
not revise the proposed changes based on these comments.
    In the FY 2000 IPPS final rule (64 FR 41531 through 41532), we 
amended the regulations at Sec.  412.25(c) to allow a hospital unit to 
change from excluded to not excluded at any time during the cost 
reporting period. We explained the statutory basis and rationale for 
this change in the FY 2000 IPPS proposed rule (64 FR 24740) and noted 
that a number of hospitals suggested that we consider a change in our 
policy to recognize, for purposes of exclusion from the IPPS, 
reductions in number of beds in, or entire closure of, units at any 
time during a cost reporting period. In that FY 2000 IPPS proposed 
rule, we explained that hospitals indicated that the bed capacity made 
available as a result of these changes could be used as needed to 
provide additional services to meet patient needs in the acute care 
part of the hospital that is paid under the IPPS. We further explained 
that we evaluated the concerns of the hospitals and the effects on the 
administration of the Medicare program and the health care of 
beneficiaries of making these payment changes. As a result of that 
evaluation, we stated that we believed it was reasonable to adopt a 
more flexible policy in recognition of hospitals' changes in the use of 
their facilities. However, we noted that whenever a hospital 
establishes an excluded unit within the hospital, our Medicare fiscal 
intermediary would need to be able to determine costs of the unit 
separately from costs of the part of the hospital paid under the 
prospective payment system. At that time, we stated that the proper 
determination of costs ensured that the hospital was paid the correct 
amount for services in each part of the facility, and that payments 
under the IPPS did not duplicate payments made under the rules that 
were applicable to excluded hospitals and units, or vice versa. For 
this reason, we did not believe it would be appropriate to recognize, 
for purposes of exclusion from the IPPS, changes in the bed size or 
status of an excluded unit that are so frequent that they interfere 
with the ability of the intermediary to accurately determine costs. 
Moreover, we explained that section 1886(d)(1)(B) of the Act authorizes 
exclusion from the IPPS of specific types of hospitals and units, but 
not of specific admissions or stays, such as admissions for 
rehabilitation or psychiatric care, in a hospital paid under the IPPS. 
We stated that without limits on the frequency of changes in excluded 
units for purposes of proper Medicare payment, there was the potential 
for some hospitals to adjust the status or size of their excluded units 
so frequently that the units would no longer be distinct entities and 
the exclusion would effectively apply only to certain types of care.
    In the FY 2012 IRF PPS final rule (76 FR 47870), we began further 
efforts to increase flexibilities for excluded IPF and IRF units. In 
that rule, we explained that cost-based reimbursement methodologies 
that were in place before the IPF PPS and IRF PPS meant that the 
facilities' capital costs were determined, in part, by their bed size 
and square footage. Changes in the bed size and square footage would 
complicate the facilities' capital cost allocation. Thus, regulations 
at Sec.  412.25 limited the situations under which an IRF or IPF could 
change its bed size and square footage. In the FY 2012 IRF PPS final 
rule, we revised Sec.  412.25(b) to enable IRFs and IPFs to more easily 
adjust to beneficiary changes in demand for IRF or IPF services and 
improve beneficiary access to these services. We believed that the 
first requirement (that beds can only be added at the start of a cost 
reporting period) was difficult, and potentially costly, for IRFs and 
IPFs that were expanding through new construction because the exact 
timing of the end of a construction project is often difficult to 
predict. In that same FY 2012 IRF PPS final rule, commenters suggested 
that CMS allow new IRF units or new IPF units to open and begin being 
paid under their respective IRF PPS or IPF PPS at any time during a 
cost reporting period, rather than requiring that they could only begin 
being paid under the IRF PPS or the IPF PPS at the start of a cost 
reporting period. We believed that this suggestion was outside the 
scope of the FY 2012 IRF PPS proposed rule (76 FR 24214), because we 
did not propose any changes to the Sec.  412.25(c). However, we stated 
that we would consider this suggestion for possible inclusion in future 
rulemaking.
b. Current Challenges Related to Excluded Hospital Units (Sec. Sec.  
412.25(c)(1) and (c)(2))
    Currently, under Sec.  412.25(c)(1), a hospital can only start 
being paid under the IPF PPS or the IRF PPS for services provided in an 
excluded hospital unit at the start of a cost reporting period. 
Specifically, Sec.  412.25(c) limits when the status of hospital units 
may change for purposes of exclusion from the IPPS, as specified in 
Sec. Sec.  412.25(c)(1) and

[[Page 51094]]

412.25(c)(2). Section 412.25(c)(1) states that the status of a hospital 
unit may be changed from not excluded to excluded only at the start of 
the cost reporting period. If a unit is added to a hospital after the 
start of a cost reporting period, it cannot be excluded from the IPPS 
before the start of a hospital's next cost reporting period. Section 
412.25(c)(2) states the status of a hospital unit may be changed from 
excluded to not excluded at any time during a cost reporting period, 
but only if the hospital notifies the fiscal intermediary and the CMS 
Regional Office in writing of the change at least 30 days before the 
date of the change, and maintains the information needed to accurately 
determine costs that are or are not attributable to the excluded unit. 
A change in the status of a unit from excluded to not excluded that is 
made during a cost reporting period must remain in effect for the rest 
of that cost reporting period.
    In recent years, interested parties, such as hospitals, have 
written CMS to express concerns about what they see as the unnecessary 
restrictiveness of the requirements at Sec.  412.25(c). Based on this 
feedback, we continued to explore opportunities to reduce burden for 
providers and clinicians, while keeping patient-centered care a 
priority. For instance, we considered whether this regulation might 
create unnecessary burden for hospitals and potentially delay necessary 
psychiatric beds from opening and being paid under the IPF PPS. As we 
continued to review and reconsider regulations to identify ways to 
improve policy, we recognized that the requirement at Sec.  
412.25(c)(1), that hospital units can only be excluded at the start of 
a cost reporting period, may be challenging and potentially costly for 
facilities under some circumstances, for example, those that are 
expanding through new construction. Hospitals have indicated it is 
often difficult to predict the exact timing of the end of a 
construction project and construction delays may hamper a hospital's 
ability to have the construction of an excluded unit completed exactly 
at the start of a cost reporting period, which hospitals have said can 
lead to significant revenue loss if they are unable to be paid under 
the IPF PPS or IRF PPS until the start of the next cost reporting 
period.
    As previously stated, the requirements at Sec.  412.25(c) were 
established to manage the administrative complexity associated with 
cost-based reimbursement for excluded IPF and IRF units. Today, 
however, because IPF units are paid under the IPF PPS and IRF units are 
paid under the IRF PPS, cost allocation is not used for payment 
purposes. Because advancements in technology since the inception of the 
IPF PPS and IRF PPS have simplified the cost reporting process and 
enhanced communication between providers, Medicare contractors, and 
CMS, we are reconsidering whether it is necessary to continue to allow 
hospital units to become excluded only at the start of a cost reporting 
period.
c. Changes to Excluded Hospital Units (Sec. Sec.  412.25(c)(1) and 
(c)(2))
    We are committed to continuing to transform the health care 
delivery system and the Medicare program by putting additional focus on 
patient-centered care and working with providers, physicians, and 
patients to improve outcomes, while meeting relevant health care 
priorities and exploring burden reduction.
    In response to increased mental health needs, including the need 
for availability of inpatient psychiatric beds, we proposed changes to 
Sec.  412.25(c) to allow greater flexibility for hospitals to open 
excluded units, while minimizing the amount of effort Medicare 
contractors would need to spend administering the regulatory 
requirements. Although we are cognizant that there is need for mental 
health services and support for providers along a continuum of care, 
including a robust investment in community-based mental health 
services, this proposal was focused on inpatient psychiatric facility 
settings.
    We proposed that changes to Sec.  412.25(c) would apply to both 
IPFs and IRFs; therefore, revisions to Sec.  412.25(c) would also 
affect IRFs in similar ways. Readers should refer to the FY 2024 IRF 
PPS proposed rule (88 FR 20981 through 20984) for discussion of 
proposed revisions to Sec.  412.25(c) and unique considerations 
applicable to IRF units. As previously stated, the current requirements 
at Sec.  412.25(c)(1) were originally established to manage the 
administrative complexity associated with cost-based reimbursement for 
excluded IPF and IRF units. Because IPF and IRF units are no longer 
paid under cost-based reimbursement, but rather under the IPF PPS and 
IRF PPS respectively, we believe that the restriction that limits an 
IPF or IRF unit to being excluded only at the start of a cost reporting 
period is no longer necessary. We amended our regulations in the FY 
2012 IRF PPS final rule to address a regulation that, similarly, was 
previously necessary for cost-based reimbursement, but was not material 
to payment under the IRF PPS and IPF PPS. In that final rule, we 
explained that under cost-based payments, the facilities' capital costs 
were determined, in part, by their bed size and square footage. Changes 
in the bed size and square footage would complicate the facilities' 
capital cost allocation. We explained that under the IRF PPS and IPF 
PPS, a facility's bed size and square footage were not relevant for 
determining the individual facility's Medicare payment. Therefore, we 
believed it was appropriate to modify some of the restrictions on a 
facility's ability to change its bed size and square footage. 
Accordingly, we relaxed the restrictions on a facility's ability to 
increase its bed size and square footage. Under the revised 
requirements that we adopted in the FY 2012 IRF PPS final rule at Sec.  
412.25(b), an IRF or IPF can change (either increase or decrease) its 
bed size or square footage one time at any point in a given cost 
reporting period as long as it notifies the CMS Regional Office (RO) at 
least 30 days before the date of the proposed change, and maintains the 
information needed to accurately determine costs that are attributable 
to the excluded units.
    Similarly, in the case of the establishment of new excluded IPF and 
IRF units, we do not believe that the timing of the establishment of 
the new unit is material for determining the individual facility's 
Medicare payment under the IPF PPS or IRF PPS. We believe it would be 
appropriate to allow a unit to become excluded at any time in the cost 
reporting year. However, we also believe it is important to minimize 
the potential administrative complexity associated with units changing 
their excluded status.
    Accordingly, we proposed to modify the requirements currently in 
regulation at Sec.  412.25(c)(1) to allow a hospital to change the 
status of an IPF unit any time within the cost reporting year, as long 
as the hospital notifies the CMS Regional Office and Medicare 
Administrative Contractor (MAC) in writing of the change at least 30 
days before the date of the change, and that this change would remain 
in effect for the rest of that cost reporting year. We also proposed to 
maintain the current requirements of Sec.  412.25(c)(2) which specify 
that, if an excluded unit becomes not excluded during a cost reporting 
year, the hospital must notify the MAC and CMS Regional Office in 
writing of the change at least 30 days before the change, and this 
change would remain in effect for the rest of that cost reporting year. 
Finally, we proposed to consolidate the requirements for Sec.  
412.25(c)(1) and Sec.  412.25(c)(2) into a new Sec.  412.25(c)(2) that 
would apply to IPF units and

[[Page 51095]]

specify the requirements for an IPF unit to become excluded or not 
excluded. We stated that we believed this proposal would provide 
greater flexibility to hospitals to establish an excluded unit at a 
time other than the start of a cost reporting period. We solicited 
comments on the proposed changes.
    Comment: We received unanimous commenter support on the proposal to 
modify the requirements to allow a hospital to open a new IPF unit any 
time within the cost reporting year, as long as the hospital notifies 
the CMS Regional Office and MAC in writing of the change at least 30 
days before the date of the change. Commenters were appreciative of how 
this change would allow greater flexibility in how and when a unit 
could be designated to be excluded or not from the IPPS. Commenters 
also stated this change could alleviate the problem of limited bed 
availability by allowing hospitals to be more responsive to the need 
for inpatient psychiatric beds in their communities.
    Response: We thank commenters for their support and agree this 
modification will allow greater flexibility in how and when a unit 
could be designated to be excluded from the IPPS. We also agree this 
change will allow hospitals to be more responsive to the need for 
inpatient psychiatric beds.
    Comment: One commenter requested that CMS allow certain units that 
have changed their status to change their status back at least one time 
during the same cost reporting period. Specifically, they believe that 
units that experience a status change on the first day of the cost 
reporting period should have the opportunity to revert to their 
original designation one time throughout the cost reporting period. 
They further clarified that, if an IPF unit specifies and communicates 
with the appropriate parties before the beginning of the next cost 
reporting year that it would want to reclassify, and then when the cost 
reporting period begins decides to revert, it should be allowed the 
opportunity to make the necessary changes.
    Response: We do not fully understand the commenter's concern, but 
we believe the commenter is seeking clarification about whether a 
hospital unit would be permitted to change its status during the cost 
reporting year to revert to the status it held during the prior year. 
Under the proposed policy, a hospital unit would be permitted to change 
its status to either excluded or not excluded only one time during the 
cost reporting year, and would be required to maintain that status 
until the end of the cost reporting year. We are clarifying that 
changes made at the beginning of a cost reporting year would not limit 
the ability of the hospital unit to make a one-time status change 
during the same cost reporting year. Therefore, if the hospital unit 
starts the cost reporting year as excluded, it could become not 
excluded at any time during the cost reporting year; if the hospital 
unit starts the cost reporting year as not excluded, it could become 
excluded at any time during the cost reporting year.
    Final Decision: After consideration of the comments received, we 
are finalizing our proposal to modify the requirements currently in 
regulation at Sec.  412.25(c)(1) to allow a hospital to change the 
status of an IPF unit from not excluded to excluded any time within the 
cost reporting year. We are also finalizing as proposed that a hospital 
will be required to notify the CMS Regional Office and MAC in writing 
of the change at least 30 days before the date of the change, and that 
this change would remain in effect for the rest of that cost reporting 
year. In addition, we are finalizing our proposal to maintain the 
current requirements of Sec.  412.25(c)(2), which specify that, if an 
excluded unit becomes not excluded during a cost reporting year, the 
hospital must notify the MAC and CMS Regional Office in writing of the 
change at least 30 days before the change, and this change would remain 
in effect for the rest of that cost reporting year.
    Lastly, we proposed an identical policy for rehabilitation units of 
hospitals in the FY 2024 IRF PPS proposed rule, specifying that the 
regulatory provision that would pertain to IRF units would appear in 
Sec.  412.25(c)(1). We proposed discrete regulation text for each of 
the hospital unit types (that is, IRF units and IPF units) in order to 
solicit comments on issues that might impact one hospital unit type and 
not the other. We also stated that we may consider adopting one 
consolidated regulations text for both IRF and IPF units in the final 
rules if we finalize both of our proposals. We did not receive any 
comments regarding a consolidated regulation for both IRF and IPF 
units; nor did commenters raise any issues that would impact one 
hospital unit type and not the other. We are finalizing a consolidated 
regulation at Sec.  412.25(c) that applies to both IPF hospital units 
and IRF hospital units.

V. Existing Data Collection and Request for Information (RFI) To Inform 
Revisions to the IPF PPS as Required by the CAA, 2023

A. Changes to IPF PPS in the CAA, 2023

    As discussed in section IV.C.1 of this final rule, we proposed to 
continue using the existing regression-derived IPF PPS adjustment 
factors for FY 2024. In the FY 2023 IPF PPS proposed rule (87 FR 19428 
through 19429), we discussed the background of these current IPF PPS 
patient-level and facility-level adjustment factors, which are the 
regression-derived adjustment factors from the November 15, 2004 IPF 
PPS final rule and briefly discussed past analyses and areas of concern 
for future refinement, about which we previously solicited comments. 
Finally, in the FY 2023 proposed rule, we described the results of the 
latest analysis of the IPF PPS, which were summarized in a technical 
report posted to the CMS website \3\ accompanying the rule and 
solicited comments on certain topics from the report.
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    \3\ https://www.cms.gov/files/document/technical-report-medicare-program-inpatient-psychiatric-facilities-prospective-payment-system.pdf.
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    Section 4125 of the CAA, 2023 amended section 1886(s) of the Act to 
add new paragraph 1886(s)(5), which requires revisions to the 
methodology for determining the payment rates under the IPF PPS for FY 
2025 and future years as the Secretary determines appropriate. 
Specifically, new section 1886(s)(5)(A) of the Act requires the 
Secretary to collect data and information as the Secretary as 
determines appropriate to revise payments under the IPF PPS. This data 
collection is required to begin no later than October 1, 2023, which is 
the start of FY 2024. In addition, new section 1886(s)(5)(D) of the Act 
requires that the Secretary implement by regulation revisions to the 
methodology for determining the payment rates for psychiatric hospitals 
and psychiatric units (that is, under the IPF PPS), for rate year 2025 
(FY 2025) and for subsequent years if the Secretary determines it 
appropriate. The revisions may be based on a review of the data and 
information collection.
    As noted above, section 1886(s)(5)(A) of the Act requires the 
Secretary to begin collecting, by not later than October 1, 2023, data 
and information as appropriate to inform revisions to the IPF PPS. New 
section 1886(s)(5)(B) of the Act, as added by the CAA, 2023 lists the 
following types of data and information as a non-exhaustive list of

[[Page 51096]]

examples of what may be collected under this authority:
     Charges, including those related to ancillary services;
     The required intensity of behavioral monitoring, such as 
cognitive deficit, suicidal ideations, violent behavior, and need for 
physical restraint; and
     Interventions, such as detoxification services for 
substance abuse, dependence on respirator, total parenteral nutritional 
support, dependence on renal dialysis, and burn care.
    We note that our extensive years-long and ongoing data collection 
efforts are consistent with the types of data the CAA, 2023 suggests we 
might collect as well as the purpose for which the CAA, 2023 requires 
the data collection, as described in the following paragraphs.

B. Current Data and Information Collection Requirements

1. Charges, Including Those Related to Ancillary Services
    As specified at 42 CFR 413.20, hospitals are required to file cost 
reports on an annual basis and maintain sufficient financial records 
and statistical data for proper determination of costs payable under 
the Medicare program. Currently, IPFs and psychiatric units are 
required to report ancillary charges on cost reports.
    In general, most providers allocate their Medicare costs using 
costs and charges as described at 42 CFR 413.53(a)(1)(i) and referred 
to as the Departmental Method. For cost reporting periods beginning on 
or after October 1, 1982, the Departmental Method, which is the ratio 
of beneficiary charges to total patient charges for the services of 
each ancillary department, is applied to apportion the cost of the 
department. Added to this amount is the cost of routine services for 
program beneficiaries, determined on the basis of a separate average 
cost per diem for all patients for general routine patient care areas 
as required at Sec.  413.53(a)(1)(i) and (e).
    The Departmental Method for apportioning allowable cost between 
Medicare and non-Medicare patients under the program is not readily 
adaptable to those hospitals that do not have a charge structure. 
Current cost reporting rules allow hospitals that do not have a charge 
structure to file an all-inclusive cost report using an alternative 
cost allocation method. These alternative methods as described in the 
CMS Pub. 15-1, chapter 22 of the Provider Reimbursement Manual (PRM), 
Methods A, B and E, in order of preference, must be approved by the MAC 
after considering the data available and ascertaining which method can 
be applied to achieve equity, not merely greater reimbursement, in the 
allocation of costs for services rendered to Medicare beneficiaries.
    Method A (Departmental Statistical Method) is used in the absence 
of charge data and where adequate departmental statistics are 
available. Where Method A was not used, the MAC may have granted 
specific permission for a hospital to continue to use on a temporary 
basis a less sophisticated Method B (Sliding Scale) or E (Percentage of 
Per Diem). A provider that elects and is approved under Method A, may 
not change to a Method B or E in a subsequent year. These alternative 
methods of apportionment are limited and available only to those 
hospitals that do not and never have had a charge structure for 
individual services rendered. Historically, most hospitals that were 
approved to file all-inclusive cost reports were Indian Health Services 
hospitals, government-owned psychiatric and acute care hospitals, and 
nominal charge hospitals.
    In the FY 2016 IPF PPS final rule (80 FR 46693 through 46694), we 
discussed analysis conducted to better understand IPF industry 
practices for future IPF PPS refinements. This analysis revealed that 
in 2012 to 2013, over 20 percent of IPF stays show no reported 
ancillary costs, such as laboratory and drug costs, on cost reports or 
charges on claims. In the FY 2016 IPF PPS final rule (80 FR 46694), FY 
2017 IPF PPS final rule (81 FR 50513), FY 2018 IPF PPS final rule (82 
FR 36784), FY 2019 IPF PPS final rule (83 FR 38588) and FY 2020 IPF PPS 
final rule (84 FR 38458), we reminded providers that we pay only the 
IPF for services furnished to a Medicare beneficiary who is an 
inpatient of that IPF, except for certain professional services, and 
payments are considered to be payments in full for all inpatient 
hospital services provided directly or under arrangement (see 42 CFR 
412.404(d)), as specified in 42 CFR 409.10.
    On November 17, 2017, we issued Transmittal 12, which made changes 
to the hospital cost report form CMS-2552-10 (OMB No. 0938-0050), and 
included cost report Level I edit 10710S, effective for cost reporting 
periods ending on or after August 31, 2017. Edit 10710S required that 
cost reports from psychiatric hospitals include certain ancillary 
costs, or the cost report will be rejected. On January 30, 2018, we 
issued Transmittal 13, which changed the implementation date for 
Transmittal 12 to be for cost reporting periods ending on or after 
September 30, 2017. CMS suspended edit 10710S effective April 27, 2018, 
pending evaluation of the application of the edit to all-inclusive-rate 
providers. CMS issued Transmittal 15 on October 19, 2018, reinstating 
the requirement that cost reports from psychiatric hospitals, except 
all-inclusive rate providers, include certain ancillary costs. For 
details, we refer readers to see these Transmittals, which are 
available on the CMS website at https://www.cms.gov/regulations-and-guidance/guidance/transmittals.
2. Required Intensity of Behavioral Monitoring and Interventions
    As discussed in the November 2004 IPF PPS final rule (69 FR 66946), 
we encourage IPFs to code all diagnoses requiring active treatment 
during the IPF stay. These include ICD-10-CM codes that indicate the 
required intensity of behavioral monitoring, such as cognitive deficit, 
suicidal ideations, violent behavior, and need for physical restraint. 
The IPF PPS includes comorbidity and MS-DRG adjustment factors that 
increase IPF PPS payment for stays that include these codes. For 
example, ICD-10-CM codes X71 through X83 indicate self-harm. ICD-10-CM 
codes under R45 indicate emotional state including violent behavior. 
These and other ICD-10-CM codes indicate the required intensity of 
behavioral monitoring and should be reported on the IPF claims, if 
applicable.
    The presence of certain ICD-10-CM codes as a principal or comorbid 
condition is used to adjust IPF PPS payments to reflect the resource 
intensity associated with these conditions. For example, codes that 
group to MS-DRG 884 Organic Disturbances & Intellectual Disabilities, 
and codes that are included in the IPF comorbidity category for 
Developmental Disabilities, result in increased payment for IPF stays 
for patients with cognitive deficit.
    As we further discussed in the November 2004 IPF PPS final rule (69 
FR 66938 through 66944), we developed comorbidity categories based on 
the clinical expertise of physicians to identify conditions that would 
require comparatively more costly treatment during an IPF stay than 
other comorbid conditions. We used a regression analysis of 
administrative claims and cost report data to determine the adjustment 
factors associated with each comorbidity category. In addition, we used 
the same regression analysis to determine the adjustment factors 
associated with the 17 MS-DRGs that are included for payment 
adjustments

[[Page 51097]]

under the IPF PPS (as identified in Addendum A). As discussed in 
section IV.C.2.b of this final rule, we routinely update the ICD-10-CM 
codes that are included in the MS-DRGs and comorbidity categories.
    We also collect relevant demographic information such as patient 
age, and we collect information and adjust payment based on the length 
of IPF stays. Each of these adjustments reflects the difference in 
service intensity, as measured by increased or decreased costs, for 
different patients over the course of an IPF stay.
    In addition, IPFs and psychiatric units report on claims the ICD-
10-PCS codes for interventions including oncology treatment procedures, 
which is used for adjusting payment under the oncology comorbidity 
category, and ECT, which is paid for using a per treatment amount as 
discussed in section IV.B.2 of this final rule. Other ICD-10-CM 
diagnosis codes indicate the need for certain interventions, such as 
detoxification services or substance abuse (for example, F10.121, which 
is included in the drug and alcohol abuse comorbidity category), 
dependence on respirator (for example, Z99.11 included in the COPD 
category), and dependence on renal dialysis (for example, Z99.2 
included in the chronic renal failure category). We note that the IPS 
PPF does not currently adjust for burn care but recognize there are 
ICD-10-CM/PCS codes that denote conditions and procedures related to 
burn care. As discussed in the previous paragraph, the IPF PPS includes 
comorbidity adjustments that reflect the higher relative costs for 
active treatment of these conditions. IPF patients with these 
conditions are costlier to treat primarily because of the costs 
associated with interventions and longer lengths of stay.
3. Request for Information on Data and Information Collection
    As noted in section V.A of this final rule, our extensive years-
long and ongoing data collection efforts are consistent with the types 
of data that the CAA, 2023 suggests we might collect, as well as aligns 
with the purpose for which the CAA, 2023 requires the data collection. 
In this final rule, we are requesting information from the public to 
inform revisions to the IPF PPS required by section 4125(a) of the CAA, 
2023. We are seeking information about specific additional data and 
information psychiatric hospitals and psychiatric units might report 
that could be appropriate and useful to help inform possible revisions 
to the methodology for payment rates under the IPF PPS for FY 2025 and 
future years if determined appropriate by the Secretary.
    Section 1886(s)(5)(C) of the Act provides that the Secretary may 
collect additional data and information on cost reports, claims, or 
otherwise. Therefore, we also sought information about potential 
available data and information sources, including using additional 
elements of the current cost reports, claims, or other sources, taking 
into consideration factors such as the timing and availability of data, 
the quality of the potential data and information to be collected, and 
the potential administrative burden on providers, MACs, and CMS.
    We solicited comment on the following topics:
     What other data and information would be beneficial for 
informing revisions to the IPF PPS payment methodologies that are 
currently obtainable through claims or cost report information? What 
codes, conditions, or other indicators should we examine in order to 
potentially identify this data from existing sources?
     What other data and information would be beneficial for 
informing revisions to the IPF PPS payment methodologies that are not 
routinely coded on claims or identifiable through cost report 
information? What are some potential alternative sources we could 
consider for collecting these data and information?
     What data and information that is currently reported on 
claims data could be used to inform revisions to the IPF PPS payment 
methodologies?
     As we discussed in the FY 2024 IPF PPS proposed rule, the 
current IPF PPS payment adjustments were derived from a regression 
analysis based on the FY 2002 MedPAR data file. The adjustment factors 
included for payment were found in the regression analysis to be 
associated with statistically significant per diem cost differences; 
with statistical significance defined as p less than 0.05. Are there 
alternative methodological approaches or considerations that we should 
consider for future analysis?
     What if any additional data or information should we 
consider collecting that could address access to care in rural and 
isolated communities?
4. Request for Information About Charges for Ancillary Services
    In conjunction with the FY 2023 IPF PPS proposed rule (87 FR 19428 
through 19429), we posted a report on the CMS website that summarizes 
the results of the latest analysis of more recent IPF cost and claim 
information for potential IPF PPS adjustments and requested comments 
about the results summarized in the report. That report showed that 
approximately 23 percent of IPF stays were trimmed from the data set 
used in that analysis because they were stays at facilities where fewer 
than 5 percent of their stays had ancillary charges. This report is 
available online at https://www.cms.gov/medicare/inpatient-psychiatric-facility-pps/ipf-reports-and-educational-resources.
    In response to the comment solicitation, we received a comment from 
MedPAC regarding facilities that do not report ancillary charges on 
most or any of their claims. Ancillary services are the services for 
which charges are customarily made in addition to routine services. 
These include services such as labs, drugs, radiology, physical and 
occupational therapy services, and other types of services that 
typically vary between stays. Generally, based on the nature of IPF 
services and the conditions of participation \4\ applicable to IPFs, we 
expect to see ancillary services and correlating charges, such as labs 
and drugs, on most IPF claims. Our ongoing analysis has found that 
certain providers, especially for-profit freestanding IPFs, are 
consistently reporting no ancillary charges or very minimal ancillary 
charges. MedPAC stated that it is not known: whether IPFs fail to 
report ancillary charges separately because they were appropriately 
bundled with all other charges into an all-inclusive per diem rate; if 
no ancillary charges were incurred because the IPF cares for a patient 
mix with lower care needs or inappropriately stints on care; or if 
ancillary charges for services furnished during the IPF stay are 
inappropriately billed outside of the IPF base rate (unbundling). 
MedPAC recommended CMS conduct further investigation into the lack of 
certain ancillary costs and charges and whether IPFs are providing 
necessary care and appropriately billing for inpatient psychiatric 
services under the IPF PPS.
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    \4\ IPFs are subject to all hospital conditions of 
participation, including 42 CFR 482.25, which specifies that ``The 
hospital must have pharmaceutical services that meet the needs of 
the patients,'' and 482.27, which specifies that ``The hospital must 
maintain, or have available, adequate laboratory services to meet 
the needs of its patients.''
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    As discussed in the previous section of this FY 2024 IPF PPS final 
rule, we requested information related to the specific types of data 
and information specified in the CAA, 2023, including the reporting of 
charges for ancillary services, such as labs and drugs, on IPF claims. 
We are interested in better understanding IPF industry practices

[[Page 51098]]

pertaining to the billing and provision of ancillary services to inform 
future IPF PPS refinements. We are considering whether to require 
charges for ancillary services to be reported on claims and potentially 
reject claims if no ancillary services are reported, and whether to 
consider payment for such claims to be inappropriate or erroneous and 
subject to recoupment. Accordingly, we solicited comments on the 
following questions:
     What would be the appropriate level of ancillary charges 
CMS should expect to be reported on claims? Are there specific reasons 
that an IPF stay would include no ancillary services?
     What are the reasons that some providers are not reporting 
ancillary charges on their claims?
     Would it be appropriate for CMS to require and reject 
claims if there are no ancillary charges reported? Or should CMS 
consider adjusting payment to providers that do not report ancillary 
charges on their claims? For example, does the lack of ancillary 
charges on claims suggest a lack of reasonable and necessary treatment 
during the IPF stay, and would it be appropriate for CMS to only apply 
the IPF PPS patient-level adjustment factors for claims that include 
ancillary charges?

C. Social Drivers of Health

    Social drivers of health (SDOH), also known as social determinants 
of health, 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.\5\ Studies have shown that there is a correlation between the 
effects of low income and education and overall health status. One 
study derived that the lowest income and least educated individuals 
were consistently least healthy.\6\ We have previously demonstrated our 
commitment to advancing health equity and reducing health disparities. 
In the past, and in our ongoing efforts, we have strived to identify 
and implement policies, procedures, reporting protocols, and other 
initiatives in a number of our programs that address the impact of SDOH 
on an individual's health.
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    \5\ https://health.gov/healthypeople/priority-areas/social-determinants-health.
    \6\ Paula A. Braveman, Catherine Cubbin, Susan Egerter, David R. 
Williams, and Elsie Pamuk, 2010:
    Socioeconomic Disparities in Health in the United States: What 
the Patterns Tell Us American Journal of Public Health 100, 
S186_S196, https://doi.org/10.2105/AJPH.2009.166082.
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    For the IPF Quality Reporting Program, as discussed in section VI.D 
below of this final rule, we are adopting the Facility Commitment to 
Health Equity measure for the FY 2026 payment determination and 
subsequent years, the Screening for Social Drivers of Health measure 
beginning with voluntary reporting of data reflecting care provided in 
2024 beginning in CY 2025 with required reporting for the FY 2027 
payment determination and subsequent years, and the Screen Positive 
Rate for Social Drivers of Health measure beginning with voluntary 
reporting of data beginning in CY 2024 with required reporting for the 
FY 2027 payment determination and subsequent years.
    Additionally, in the technical report \7\ accompanying the FY 2023 
IPF PPS proposed rule, we explained that we analyzed the costs 
associated with SDOH but found that our analysis was confounded by a 
low frequency of IPF claims reporting the applicable ICD-10 diagnosis 
codes. In response to the FY 2023 IPF PPS proposed rule we received 10 
comments pertaining to the report on the analysis of patient-level and 
facility-level adjustment factors, and areas of interest for further 
research, including additional SDOH analysis.
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    \7\ https://www.cms.gov/files/document/technical-report-medicare-program-inpatient-psychiatric-facilities-prospective-payment-system.pdf.
---------------------------------------------------------------------------

    Working in collaboration with a contractor, subsequent analysis has 
shown that other SDOH codes, such as Z59.9 Problem related to housing 
and economic circumstances, unspecified, are associated with 
statistically significant, higher costs. In general, our analysis found 
that claims that included SDOH codes had lower costs than claims that 
did not include such codes. This finding is counterintuitive; however, 
we note that studies have found that there are disparities in the 
reporting of SDOH codes, such as homelessness.\8\ Additionally, our 
analysis found that certain codes were associated with increased cost 
for IPF treatment. Specifically, the below SDOH codes in the analysis 
were found to be statistically significant and had a stay count of 
greater than 100. These codes had an adjustment factor above 1, 
suggesting that these conditions may increase relative costliness of 
IPF stays:
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    \8\ https://aspe.hhs.gov/reports/health-conditions-among-individuals-history-homelessness-research-brief-0.
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     Z559 Problems related to education and literacy, 
unspecified.
     Z599 Problems related to housing and economic 
circumstances, unspecified.
     Z600 Problems of adjustment to life-cycle transitions.
     Z634 Disappearance and death of family member.
     Z653 Problems related to other legal circumstances.
     Z659 Problems related to unspecified psychosocial 
circumstances.
    We solicited comments on these findings and information about 
whether it would be appropriate to consider incorporating these codes 
into the IPF PPS in the future, for example as a patient-level 
adjustment. Specifically, for codes that are ``unspecified,'' we sought 
information about what types of conditions or circumstances these codes 
might represent. We sought any information that commenters could 
provide about the reasons for including these codes on claims. We also 
requested information on what factors commenters believe we should 
consider in order to better understand the cost regression results 
presented above.

D. Public Comments Received in Response to CY 2024 IPF PPS Proposed 
Rule

    We received 15 comments in response to the FY 2024 IPF PPS proposed 
rule pertaining to existing and future data collection to inform 
revisions to the IPF PPS as required by the CAA, 2023. Commenters 
offered various suggestions of patient characteristics and factors we 
could consider for analysis. Commenters included MedPAC, state-level 
and national provider and patient advocacy organizations, and health 
systems.
    We thank commenters for their detailed responses to this comment 
solicitation. We will take these comments into consideration to 
potentially inform future rulemaking.

VI. Inpatient Psychiatric Facility Quality Reporting (IPFQR) Program

A. Background and Statutory Authority

    The Inpatient Psychiatric Facility Quality Reporting (IPFQR) 
Program is authorized by section 1886(s)(4) of the Act, and it applies 
to psychiatric hospitals and psychiatric units paid by Medicare under 
the IPF PPS (see section VI.B. of this final rule). Section 
1886(s)(4)(A)(i) of the Act requires the Secretary to reduce by 2 
percentage points the annual update to the standard federal rate for 
discharges for the IPF occurring during such fiscal year \9\ for

[[Page 51099]]

any IPF that does not comply with quality data submission requirements 
under the IPFQR Program, set forth in accordance with section 
1886(s)(4)(C) of the Act, with respect to an applicable fiscal year.
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    \9\ We note that the statute uses the term ``rate year'' (RY). 
However, beginning with the annual update of the inpatient 
psychiatric facility prospective payment system (IPF PPS) that took 
effect on July 1, 2011 (RY 2012), we aligned the IPF PPS update with 
the annual update of the ICD codes, effective on October 1 of each 
year. This change allowed for annual payment updates and the ICD 
coding update to occur on the same schedule and appear in the same 
Federal Register document, promoting administrative efficiency. To 
reflect the change to the annual payment rate update cycle, we 
revised the regulations at 42 CFR 412.402 to specify that, beginning 
October 1, 2012, the IPF PPS RY means the 12-month period from 
October 1 through September 30, which we refer to as a ``fiscal 
year'' (FY) (76 FR 26435). Therefore, with respect to the IPFQR 
Program, the terms ``rate year,'' as used in the statute, and 
``fiscal year'' as used in the regulation, both refer to the period 
from October 1 through September 30. For more information regarding 
this terminology change, we refer readers to section III of the RY 
2012 IPF PPS final rule (76 FR 26434 through 26435).
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    Section 1886(s)(4)(C) of the Act requires IPFs to submit to the 
Secretary data on quality measures specified by the Secretary under 
section 1886(s)(4)(D) of the Act. Except as provided in section 
1886(s)(4)(D)(ii) of the Act, section 1886(s)(4)(D)(i) of the Act 
requires that any measure specified by the Secretary must have been 
endorsed by the consensus-based entity (CBE) with a contract under 
section 1890(a) of the Act. Section 1886(s)(4)(D)(ii) of the Act 
provides 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 CBE 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 refer readers to the FY 2019 IPF PPS final rule (83 FR 38589) 
for a more detailed discussion of the background and statutory 
authority of the IPFQR Program.
    For the IPFQR Program, we refer to the year in which an IPF would 
receive the 2-percentage point reduction to the annual update to the 
standard federal rate as the payment determination year. An IPF 
generally meets IPFQR Program requirements by submitting data on 
specified quality measures in a specified time and manner during a data 
submission period that occurs prior to the payment determination year. 
These data reflect a period prior to the data submission period during 
which the IPF furnished care to patients; this period is known as the 
performance period. For example, for a measure affecting FY 2026 
payment determination, for which CY 2024 is the performance period and 
for which data are required to be submitted in CY 2025, if an IPF did 
not submit the data for this measure as specified during CY 2025 (even 
if the IPF meets all other IPFQR Program requirements for the FY 2026 
payment determination) we would reduce by 2-percentage points that 
IPF's update for the FY 2026 payment determination year.
    In the FY 2024 IPF PPS proposed rule (88 FR 21273), we proposed to 
codify the IPFQR Program requirements governing IPF reporting on 
quality measures in a new regulation at Sec.  412.433, which is the 
section preceding our existing regulation governing reconsideration and 
appeals procedures for IPFQR Program decisions in our regulations at 
Sec.  412.434. Specifically, we proposed to codify a general statement 
of the IPFQR Program authority and structure at Sec.  412.433(a). 
Paragraph (a) will cite section 1886(s)(4) of the Act, which requires 
the Secretary to implement a quality reporting program for inpatient 
psychiatric hospitals and psychiatric units. Paragraph (a) will also 
state that IPFs paid under the IPF PPS as provided in section 
1886(s)(1) of the Act that do not report data required for the quality 
measures selected by the Secretary in a form and manner, and at a time 
specified by the Secretary will incur a 2.0 percentage point reduction 
to the annual update to the standard federal rate with respect to the 
applicable fiscal year.
    We solicited comments on this proposal.
    Comment: One commenter requested clarification regarding whether 
there are penalties for facilities that do not meet all the reporting 
requirements for a specific year.
    Response: The IPFQR Program is a pay-for-reporting program. IPFs 
are not, and will not be, penalized based on their performance on 
measures reported to CMS as part of the IPFQR Program. However, if an 
IPF does not comply with quality data submission requirements under the 
IPFQR Program for a given fiscal year, section 1886(s)(4)(A)(i) of the 
Act requires the Secretary to reduce by 2 percentage points the annual 
update to the standard federal rate for discharges for the IPF 
occurring during such fiscal year.
    We specifically proposed to codify established IPFQR Program 
requirements, particularly those set forth in the statute at section 
1886(s)(4) of the Act and our prior rulemaking, in a new regulation at 
Sec.  412.433. Our proposal to codify penalties for an IPF's failure to 
submit data as required by the IPFQR Program at Sec.  412.433(a) merely 
reiterates the penalty already required by the statute set forth at 
section 1886(s)(4) of the Act.
    Final Decision: After consideration of the public comments we 
received, we are finalizing codification of the IPFQR Program 
requirements governing IPF reporting on quality measures at a new 
regulation at Sec.  412.433. We are finalizing the regulation text as 
proposed except that we are correcting one typographical error in which 
the ``Act'' was inadvertently referred to as the ``act.''

B. Covered Entities

    In the FY 2013 IPPS/LTCH PPS final rule (77 FR 53645), we 
established that the IPFQR Program's quality reporting requirements 
cover those psychiatric hospitals and psychiatric units paid by 
Medicare under IPF PPS in accordance with Sec.  412.404(b). Generally, 
psychiatric hospitals and psychiatric units within acute care and 
critical access hospitals (CAHs) that treat Medicare patients are paid 
under the IPF PPS. Consistent with previous regulations, we continue to 
use the terms ``facility'' or ``IPF'' to refer to both inpatient 
psychiatric hospitals and psychiatric units. This usage follows the 
terminology in our IPF PPS regulations at Sec.  412.402. For more 
information on covered entities, we refer readers to the FY 2013 IPPS/
LTCH PPS final rule (77 FR 53645).

C. Previously Finalized Measures

    The current IPFQR Program includes 14 measures for the FY 2024 
payment determination. For more information on these measures, we refer 
readers to Table 20 of this final rule (see section VI.G of this final 
rule).

D. Measure Adoption

    We strive to put patients and caregivers first, ensuring they are 
empowered to partner with their clinicians in their healthcare 
decision-making 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 our 
programs. In combination with other efforts across HHS, we believe the 
IPFQR Program helps to incentivize IPFs to improve healthcare quality 
and value while giving patients and providers the tools and information 
needed to make the best individualized decisions. Consistent with these 
goals, our objective in selecting quality

[[Page 51100]]

measures for the IPFQR Program is to balance the need for information 
on the full spectrum of care delivery and the need to minimize the 
burden of data collection and reporting. We have primarily focused on 
measures that evaluate critical processes of care that have significant 
impact on patient outcomes and support CMS and HHS priorities for 
improved quality and efficiency of care provided by IPFs. When 
possible, we also propose to incorporate measures that directly 
evaluate patient outcomes and experience.
    We refer readers to the CMS National Quality Strategy,\10\ the 
Behavioral Health Strategy,\11\ the Framework for Health Equity,\12\ 
and the Meaningful Measures Framework \13\ for information related to 
our priorities in selecting quality measures.
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    \10\ Schreiber, M, Richards, A, et al. (2022). The CMS National 
Quality Strategy: A Person-Centered Approach to Improving Quality. 
Available at: https://www.cms.gov/blog/cms-national-quality-strategy-person-centered-approach-improving-quality. Accessed on 
February 20, 2023.
    \11\ CMS. (2022). CMS Behavioral Health Strategy. Available at 
https://www.cms.gov/cms-behavioral-health-strategy. Accessed on 
February 20, 2023.
    \12\ CMS. (2022). CMS Framework for Health Equity 2022-2032. 
Available at https://www.cms.gov/files/document/cms-framework-health-equity-2022.pdf. Accessed on February 20, 2023.
    \13\ CMS. (2022). Meaningful Measures 2.0: Moving from Measure 
Reduction to Modernization. Available at https://www.cms.gov/medicare/meaningful-measures-framework/meaningful-measures-20-moving-measure-reduction-modernization. Accessed on February 20, 
2023.
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1. Measure Selection Process
    Section 1890A of the Act requires that the Secretary establish and 
follow a pre-rulemaking process, in coordination with the consensus-
based entity (CBE) with a contract under section 1890 of the Act, to 
solicit input from certain groups regarding the selection of quality 
and efficiency measures for the IPFQR Program. Before being proposed 
for inclusion in the IPFQR Program, measures are placed on a list of 
Measures Under Consideration (MUC) list, which is published annually on 
behalf of CMS by the consensus-based entity (CBE),\14\ with which the 
Secretary must contract as required by section 1890(a) of the Act. 
Following publication on the MUC list, a multi-stakeholder group 
convened by the CBE reviews the measures under consideration for the 
IPFQR Program, among other federal programs, and provides input on 
those measures to the Secretary. We consider the input and 
recommendations provided by this multi-stakeholder group in selecting 
all measures for the IPFQR Program.
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    \14\ In previous years, we referred to the consensus-based 
entity by corporate name. We have updated this language to refer to 
the consensus-based entity more generally.
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    Information about the multi-stakeholder group's input on each of 
our newly adopted measures is described in the following subsections. 
In our evaluation of the IPFQR Program measure set, we identified four 
measures that we believe are appropriate for adoption for the IPFQR 
Program:
     Facility Commitment to Health Equity;
     Screening for Social Drivers of Health;
     Screen Positive Rate for Social Drivers of Health; and
     Psychiatric Inpatient Experience (PIX) Survey.
    These four measures are described in the following subsections.
2. Adoption of the Facility Commitment to Health Equity Measure 
Beginning With the CY 2024 Reporting Period (Data Submitted in CY 
2025)/FY 2026 Payment Determination
a. Background
    Significant and persistent disparities in healthcare outcomes exist 
in the United States. 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, or 
being near or below the poverty level, is often associated with worse 
health outcomes.15 16 17 18 19 20 21 22 23 24 Numerous 
studies have shown that among Medicare beneficiaries, racial and ethnic 
minority individuals often receive clinical care of lower quality, 
report having worse care experiences, and experience more frequent 
hospital readmissions and procedural 
complications.25 26 27 28 29 30 Readmission rates in the 
Hospital Readmissions Reduction Program have been shown to be higher 
among Black and Hispanic Medicare beneficiaries with common

[[Page 51101]]

conditions, including congestive heart failure and acute myocardial 
infarction. 31 32 33 34 35 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.\36\ Evidence of differences in quality of care received 
among people from racial and ethnic minority groups shows worse health 
outcomes, including a higher incidence of diabetes complications such 
as retinopathy.\37\ Additionally, inequities in the social drivers of 
health (SDOH) 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.\38\
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    \15\ 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: https://jamanetwork.com/journals/jama/fullarticle/645647. Accessed on February 13, 2023.
    \16\ 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. 
Accessed on February 13, 2023.
    \17\ 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: https://www.nejm.org/doi/10.1056/NEJMsa1405003. 
Accessed on February 13, 2023.
    \18\ Polyakova, M, Udalova V, 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. 
Available at: https://doi.org/10.1377/hlthaff.2020.02142. Accessed 
on February 14, 2023.
    \19\ 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. Accessed on 
February 14, 2023.
    \20\ 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 . Accessed on February 14, 
2023.
    \21\ 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. Available 
at: https://www.cdc.gov/mmwr/volumes/70/wr/mm7005a1.htm. Accessed on 
February 14, 2023.
    \22\ 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. Available at: https://www.medrxiv.org/content/10.1101/2020.07.21.20159327v1.full.pdf. 
Accessed on February 14, 2023.
    \23\ 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. Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5912720/. Accessed on February 
14, 2023.
    \24\ 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. Available at: https://doi.org/10.1037/hea0000268. Accessed o n 
February 14, 2023.
    \25\ 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 Accessed on February 14, 2023.
    \26\ CMS Office of Minority Health. (2018). Guide to Reducing 
Disparities in Readmissions. Available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/OMH_Readmissions_Guide.pdf. Accessed on February 14, 2023.
    \27\ Singh JA, Lu X, et al. (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: 
https://ard.bmj.com/content/73/12/2107.full. Accessed on February 
14, 2023.
    \28\ 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. Accessed on 
February 14, 2023.
    \29\ 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: https://jamanetwork.com/journals/jama/fullarticle/645647. Accessed on February 13, 2023.
    \30\ 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: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4107654/. Accessed on February 
14, 2023.
    \31\ 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://www.sciencedirect.com/science/article/pii/S0002870311003966?viewFullText=true. Accessed on 
February 14, 2023.
    \32\ Centers for Medicare & Medicaid Services. (2014). Medicare 
Hospital Quality Chartbook: Performance Report on Outcome Measures. 
Available at: https://www.hhs.gov/guidance/sites/default/files/hhs-guidance-documents/YNH_Chartbook_2014_508Compliant_FINAL.pdf. 
Accessed on February 14, 2023.
    \33\ CMS Office of Minority Health. (2018). Guide to Reducing 
Disparities in Readmissions. Available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/OMH_Readmissions_Guide.pdf. Accessed on February 14, 2023.
    \34\ 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. 
Accessed on February 14, 2023.
    \35\ 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: https://jamanetwork.com/journals/jama/fullarticle/645647. Accessed on February 13, 2023.
    \36\ 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. 
https://www.annalsthoracicsurgery.org/action/showPdf?pii=S0003-4975%2803%2901205-0. Accessed on February 14, 2023.
    \37\ Peek, ME, Odoms-Young, A, et al. (2010). Race and Shared 
Decision-Making: Perspectives of African-Americans with diabetes. 
Social Science & Medicine, 71(1), 1-9. Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2885527/. Accessed on February 
14, 2023.
    \38\ Department of Health and Human Services. (2023). Healthy 
People 2030: Social Determinants of Health. Available at: https://health.gov/healthypeople/priority-areas/social-determinants-health. 
Accessed on February 20, 2023.
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    Because we are working toward the goal of all patients receiving 
high-quality healthcare, regardless of individual characteristics, we 
are committed to supporting healthcare organizations in building a 
culture of safety and 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.
    In the FY 2022 IPF PPS final rule (86 FR 42625 through 42632), we 
summarized the comments we received in response to our Request for 
Information (RFI) on closing health equity gaps in our quality 
programs, specifically the IPFQR Program. In response to this RFI, 
several commenters recommended that we consider a measure of 
organizational commitment to health equity. These commenters further 
described how infrastructure supports delivery of equitable care. In 
the FY 2023 IPF PPS final rule (87 FR 46865 through 46873), we 
described our RFI on overarching principles for measuring equity and 
healthcare quality across our quality programs and summarized the 
comments we received in response to that RFI. Because we had 
specifically solicited comments on the potential for a structural 
measure assessing an IPF's commitment to health equity, many commenters 
provided input on a structural measure. While many commenters supported 
the concept, one commenter expressed concern with this measure concept 
and stated that there is no evidence that performance on this measure 
will lead to improved patient outcomes (87 FR 46872 through 46873). 
However, we believe that strong and committed leadership from IPF 
executives and board members is essential and can play a role in 
shifting organizational culture and advancing equity goals.
    Additionally, studies demonstrate that facility leadership can 
positively influence culture for better quality, patient outcomes, and 
experience of care.39 40 41 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 high-performing facilities with 
better patient outcomes.\42\ Therefore, we believe leadership 
commitment to health equity will have a parallel effect in contributing 
to a reduction in health disparities.
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    \39\ Bradley EH, Brewster AL, 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. Available at: https://qualitysafety.bmj.com/content/qhc/27/3/218.full.pdf. Accessed on February 14, 2023.
    \40\ 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. Available at: 
https://bmchealthservres.biomedcentral.com/articles/10.1186/s12913-017-2078-6. Accessed on February 14, 2023.
    \41\ Keroack MA, Youngberg BJ, et al. (2007). Organizational 
Factors Associated with High Performance in Quality and Safety in 
Academic Medical Centers. Acad Med., 82(12), 1178-86. Available at: 
https://journals.lww.com/academicmedicine/Fulltext/2007/12000/Organizational_Factors_Associated_with_High.14.aspx. Accessed on 
February 14, 2023.
    \42\ 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. Available at: https://onlinelibrary.wiley.com/doi/10.1111/1468-0009.12032. Accessed February 14, 2023.
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    Further, we note that the Agency for Healthcare Research and 
Quality (AHRQ) and The Joint Commission (TJC) identified that facility 
leadership plays an important role in promoting a culture of quality 
and safety.43 44 45 For instance, AHRQ research shows that a 
facility's board can influence quality and safety in a variety of ways, 
not only through strategic initiatives, but also through more direct 
interactions with frontline workers.\46\
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    \43\ 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. Accessed on February 14, 2023.
    \44\ Joint Commission on Accreditation of Healthcare 
Organizations, USA. The essential role of leadership in developing a 
safety culture. Sentinel Event Alert. 2017 (Revised June 2021). 
Available at: https://www.jointcommission.org/-/media/tjc/documents/resources/patient-safety-topics/sentinel-event/sea-57-safety-culture-and-leadership-final2.pdf. Accessed on February 15, 2023.
    \45\ See information on launch of new ``Health Care Equity 
Certification'' in July 2023 from Joint Commission on Accreditation 
of Healthcare Organizations, USA, available at: https://www.jointcommission.org/our-priorities/health-care-equity/health-care-equity-prepublication/. Accessed on February 15, 2023.
    \46\ Agency for Healthcare Research and Quality. Leadership Role 
in Improving Patient Safety. Patient Safety Primer. (2019). 
Available at: https://psnet.ahrq.gov/primer/leadership-role-improving-safety. Accessed on February 14, 2023.
    \47\ 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. Accessed on February 
15, 2023.
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    In addition, the Institute of Healthcare Improvement's (IHI's) 
research of 23 health systems throughout the United States and Canada 
shows that health equity must be a priority championed by leadership 
teams to improve both patient access to needed healthcare services and 
outcomes among populations that have been disadvantaged by the 
healthcare system.\47\ This IHI study specifically identified concrete 
actions to make advancing health equity a core strategy,

[[Page 51102]]

including establishing this goal as a leader-driven priority alongside 
organizational development structures and processes.\48\
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    \48\ 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. Accessed on February 
15, 2023.
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    Based upon these findings, we believe that IPF leadership can be 
instrumental in setting specific, measurable, attainable, realistic, 
and time-based (SMART) goals to assess progress towards achieving 
equity goals and ensuring high-quality care is accessible to all. 
Therefore, consistent with the Hospital Inpatient Quality Reporting 
(IQR) Program's adoption of an attestation-based structural measure in 
the FY 2023 IPPS/LTCH PPS final rule (87 FR 49191 through 49201), we 
proposed to adopt an attestation-based structural measure, Facility 
Commitment to Health Equity, to address health equity beginning with 
the CY 2024 reporting period/FY 2026 payment determination.
    The first pillar of our strategic priorities \49\ reflects our deep 
commitment to improvements in health equity by addressing the health 
disparities that underly our health system. In line with this strategic 
pillar, we developed this structural measure to assess facility 
commitment to health equity across five domains (described in Table 17 
in section VI.D.2.b of this final rule) 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 IPFs' leadership commitment to them is foundational.
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    \49\ 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. Accessed on February 15, 
2023. Also see https://www.cms.gov/cms-strategic-plan.
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    We also believe adoption of the Facility Commitment to Health 
Equity measure will incentivize IPFs to collect and utilize data to 
identify critical equity gaps, implement plans to address these gaps, 
and ensure that resources are dedicated toward addressing health equity 
initiatives. While many factors contribute to health equity, we believe 
this measure is an important step toward assessing IPFs' 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 IPFs to act on any one data element or domain, but instead 
encourages IPFs to analyze their own findings to understand if there 
are any demographic factors (for example, race, national origin, 
primary language, and ethnicity) as well as SDOHs (for example, housing 
status and food security) associated with underlying inequities and, in 
turn, develop solutions to deliver more equitable care. Thus, the 
Facility Commitment to Health Equity measure aims to support IPFs in 
leveraging available data, pursuing focused quality improvement 
activities, and promoting efficient and effective use of resources.
    The Facility Commitment to Health Equity measure aligns with the 
measure previously adopted in the Hospital IQR Program, and we refer 
readers to the FY 2023 IPPS/LTCH PPS final rule (87 FR 49191 through 
49201) for more information regarding the measure's adoption in the 
Hospital IQR Program. The five domains of the Facility Commitment to 
Health Equity 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.\50\
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    \50\ CMS. (2021). Building an Organizational Response to Health 
Disparities [Fact Sheet]. Available at: https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/Health-Disparities-Guide.pdf. 
Accessed on February 15, 2023.
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    The Facility Commitment to Health Equity 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.\51\ 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.\52\ We are addressing healthcare priorities and gaps with 
Meaningful Measures 2.0 by leveraging quality measures to promote 
equity and close gaps in care. The Facility 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 health equity.
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    \51\ Centers for Medicare & Medicaid Services. Meaningful 
Measures Framework. Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/CMS-Quality-Strategy. Accessed on February 
15, 2023.
    \52\ CMS. (2022). Meaningful Measures 2.0: Moving from Measure 
Reduction to Modernization. Available at https://www.cms.gov/medicare/meaningful-measures-framework/meaningful-measures-20-moving-measure-reduction-modernization. Accessed on February 20, 
2023.
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b. Overview of Measure
    The Facility Commitment to Health Equity measure will assess IPFs' 
commitment to health equity using a suite of equity-focused 
organizational competencies aimed at achieving health equity for 
populations that have been disadvantaged, marginalized, and underserved 
by the healthcare system. As previously noted, these populations 
include, but are not limited to, 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 17 sets 
forth the five attestation domains, and the elements within each of 
those domains, to which an IPF will affirmatively attest for the IPF to 
receive credit for that domain within the Facility Commitment to Health 
Equity measure.

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[[Page 51104]]


(1) Measure Calculation
    The Facility Commitment to Health Equity measure consists of five 
attestation-based questions, each representing a separate domain of the 
IPF's commitment to addressing health equity. Some of these domains 
have multiple elements to which an IPF will be required to attest. For 
an IPF to affirmatively attest ``yes'' to a domain, and receive credit 
for that domain, the IPF would evaluate and determine whether it 
engages in each of the elements that comprise that domain. Each of the 
domains will be represented in the denominator as a point, for a total 
of five points (that is, one point per domain).
    The numerator of the Facility Commitment to Health Equity measure 
will capture the total number of domain attestations that the IPF is 
able to affirm. An IPF that affirmatively attests to each element 
within the five domains will receive the maximum five points.
    An IPF will only receive a point for a domain if it attests ``yes'' 
to all related elements within that domain. There is no ``partial 
credit'' for elements. For example, for Domain 1 (``Facility commitment 
to reducing healthcare disparities is strengthened when equity is a key 
organizational priority''), an IPF will evaluate and determine whether 
its strategic plan meets each of the elements described in (A) through 
(D) (see Table 17 in section VI.D.2.b of this final rule). If the IPF's 
strategic plan meets all four of these elements, the IPF would 
affirmatively attest ``yes'' to Domain 1 and would receive one (1) 
point for that attestation. An IPF will not be able to receive partial 
credit for a domain. For example, if the IPF's strategic plan meets 
elements (A) and (B), but not (C) and (D), of Domain 1, then the IPF 
would not be able to affirmatively attest ``yes'' to Domain 1 and would 
not receive a point for that attestation, and instead would receive 
zero points for Domain 1.
    In response to our RFI on the potential for a structural measure 
assessing an IPF's commitment to health equity, several commenters 
expressed concern that such a measure would be difficult for IPFs to 
report because of the requirement to use certified electronic health 
record (EHR) technology for Domain 2 (87 FR 46972 through 46873). We 
believe that use of certified EHR technology is an important element of 
collecting valid and reliable demographic and social drivers of health 
data on patients served in an IPF and that use of this technology 
facilitates data analytics to ensure consistent, high-quality, 
equitable care. However, we recognize that some IPFs may face 
challenges to adopting certified EHR technology. We note that the IPFQR 
Program is a pay-for-reporting program, not a pay-for-performance 
program, and therefore IPFs that do not have certified EHR technology 
can attest that they satisfy the other domains, as applicable, and 
receive a score of 0-4 out of 5 without any penalties.
(2) Review by the Measure Applications Partnership (MAP) \53\
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    \53\ Interested parties convened by the consensus-based entity 
provide input and recommendations on the Measures under 
Consideration (MUC) list as part of the pre-rulemaking process 
required by section 1890A of the Act. We refer readers to https://p4qm.org/PRMR-MSR for more information.
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    We included the Facility Commitment to Health Equity measure on the 
publicly available MUC List, a list of measures under consideration for 
use in various Medicare programs.\54\ The specifications for the 
Facility Commitment to Health Equity measure, which were available 
during the review of the MUC List, are available on the CMS website at: 
https://mmshub.cms.gov/sites/default/files/map-hospital-measure-specifications-manual-2022.pdf.
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    \54\ Centers for Medicare & Medicaid Services. List of Measures 
Under Consideration for December 1, 2022. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
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    The CBE-convened MAP Health Equity Advisory Group reviewed the MUC 
List and the Facility Commitment to Health Equity measure (MUC 2022-
027) in detail on December 6 through 7, 2022.\55\ The MAP Health Equity 
Advisory Group raised concerns that this measure does not evaluate 
outcomes and may not directly address health inequities at a systemic 
level, but generally agreed that a structural measure such as this one 
represents progress toward improving equitable care.\56\
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    \55\ Centers for Medicare & Medicaid Services. 2022-2023 MAP 
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
    \56\ Centers for Medicare & Medicaid Services. 2022-2023 MAP 
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
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    In addition, on December 8 through 9, 2022, the MAP Rural Health 
Advisory Group reviewed the 2022 MUC List and expressed support for 
this measure as a step towards advancing access to and quality of care 
with the caveat that resource challenges exist in rural 
communities.\57\
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    \57\ Centers for Medicare & Medicaid Services. 2022-2023 MAP 
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
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    The MAP Hospital Workgroup reviewed the 2022 MUC List on December 
13 through 14, 2022.\58\ The MAP Hospital Workgroup recognized that 
reducing health care disparities would represent a substantial benefit 
to overall quality of care but expressed reservations about the 
measure's link to clinical outcomes. As stated in the MAP 
recommendations document, the MAP Hospital Workgroup members voted to 
conditionally support the Facility Commitment to Health Equity measure 
for rulemaking pending: (1) endorsement by the CBE; (2) commitment to 
consideration of equity related outcome measures in the future; (3) 
provision of more clarity on the Facility Commitment to Health Equity 
measure and supplementing interpretation with results; and (4) 
verification of accurate attestation by IPFs.\59\ Thereafter, the MAP 
Coordinating Committee deliberated on January 24 through 25, 2023 and 
ultimately voted to uphold the MAP Hospital Workgroup's recommendation 
to conditionally support the measure for rulemaking.\60\
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    \58\ Centers for Medicare & Medicaid Services. 2022-2023 MAP 
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
    \59\ Centers for Medicare & Medicaid Services. 2022-2023 MAP 
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
    \60\ Centers for Medicare & Medicaid Services. 2022-2023 MAP 
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
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    We believe that the Facility Commitment to Health Equity measure 
establishes an important foundation for prioritizing the achievement of 
health equity among IPFs participating in the IPFQR Program. Our 
approach to developing health equity measures has been incremental to 
date, but we see inclusion of such measures in the IPFQR Program as 
informing efforts to advance and achieve health equity not only among 
IPFs, but also other acute care settings. We believe this measure to be 
a building block that lays the groundwork for a future meaningful suite 
of measures that would assess IPF progress in providing high-quality 
healthcare for all patients regardless of social risk factors or 
demographic characteristics.
(3) CBE Endorsement
    We have not submitted this measure for CBE endorsement at this 
time.

[[Page 51105]]

Although section 1886(s)(4)(D)(i) of the Act generally requires that 
measures specified by the Secretary must be endorsed by the entity with 
a contract under section 1890(a) of the Act, section 1886(s)(4)(D)(ii) 
of the Act states 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 reviewed measures endorsed by consensus 
organizations and were unable to identify any other measures on this 
topic endorsed by a consensus organization, and therefore, we believe 
the exception in section 1886(s)(4)(D)(ii) of the Act applies.
c. Data Collection, Submission, and Reporting
    IPFs 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. For more 
information about our previously finalized policies related to 
reporting of structural measures, we refer readers to the FY 2014 IPPS/
LTCH PPS final rule (78 FR 50890 through 50901) and the FY 2015 IPF PPS 
final rule (79 FR 45963 through 45964 and 45976). Given the role of 
committed leadership in improving health outcomes for all patients, we 
proposed to adopt this measure beginning with attestations submitted to 
CMS in CY 2025 reflecting the CY 2024 reporting period and affecting 
the FY 2026 payment determination.
    We invited comments on our proposed adoption of the Facility 
Commitment to Health Equity Measure beginning with the FY 2026 payment 
determination.
    Comment: Many commenters supported adoption of the Facility 
Commitment to Health Equity measure. One commenter stated that 
alignment with other programs will support consistent measurement 
across the continuum of patient care. Several commenters stated that 
facilities' commitment to health equity is particularly important for 
IPFs because of health disparities experienced by patients with mental 
health conditions. Several commenters stated that the Facility 
Commitment to Health Equity measure is consistent with new standards 
from The Joint Commission. One commenter stated that facilities 
attesting to their commitment to health equity will help empower the 
healthcare workforce to recognize and eliminate health disparities.
    Response: We thank commenters for their support of our proposal to 
adopt the Facility Commitment to Health Equity measure and agree that 
this measure addresses a topic that is important for IPF patients and 
this setting.
    Comment: Other commenters recommended additional testing, 
specifically in the IPF setting, to ensure that this measure addresses 
unique challenges associated with treating the psychiatric patient 
population prior to adoption of this measure. Some of these commenters 
also recommended engaging IPFs to voluntarily test the measure to 
ensure usability, acceptability, and face validity are met for this 
setting.
    Response: We acknowledge that this measure was initially developed 
for the general acute care setting. While we recognize the value of 
measures undergoing testing and evaluation of validity and feasibility 
in the setting for which they are being adopted, given the urgency of 
achieving health equity and, as there are currently no other existing 
measures that address facility commitment to health equity, we believe 
it is important to implement this measure as soon as feasible. Strong 
and consistent facility leadership can be instrumental in establishing 
specific, measurable, and attainable goals to advance equity priorities 
and improve care for all patients in any care setting, including 
patients who receive care in inpatient psychiatric facilities. We 
believe that this measure is equally applicable to freestanding IPFs 
and psychiatric units within acute care facilities as it is to general 
acute care settings. Leaders of health services organizations across 
the health care system, including both IPFs and acute care hospitals, 
are likely to encounter the same challenges and use the same types of 
strategies to achieve organizational goals related to improving health 
equity within their respective organizations. We note that health 
equity is a critical topic for patients treated in IPFs and that there 
are high levels of health disparities experienced by this patient 
population. CMS will monitor measure implementation and data reporting 
as part of standard program and measure review and will consider 
updates to the measure if improvements are identified through this 
process.
    Comment: Many commenters expressed concern that this measure has 
not received endorsement by the CBE.
    Response: While we recognize the value of measures undergoing 
review for potential CBE endorsement, given the urgency of achieving 
health equity, we believe it is important to implement this measure 
beginning with the CY 2024 reporting period. We note that, in 
accordance with section 1886(s)(4)(D)(ii) 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 measures endorsed 
by consensus organizations and were unable to identify any other 
measures on this topic endorsed by a consensus organization, and 
therefore, we believe the exception in section 1886(s)(4)(D)(ii) of the 
Act applies.
    Comment: Some commenters recommended that CMS defer adoption of 
this measure until CMS and IPFs have reviewed the Hospital IQR 
Program's implementation of this measure to identify potential 
improvements to data collection processes that would reduce burden for 
IPFs. These commenters stated that IPFs often have fewer resources 
available for data collection relative to acute care hospitals.
    Response: We acknowledge commenters' desire to be able to learn 
from the experiences of acute care hospitals reporting this measure. We 
note that hospitals participating in the Hospital IQR Program will have 
already reported data on the similar Hospital Commitment to Health 
Equity measure for the FY 2025 payment determination (that is, data 
submitted in CY 2024 representing the CY 2023 performance period) (87 
FR 49201) before the reporting of the Facility Commitment to Health 
Equity Measure for the IPFQR Program begins with the FY 2026 payment 
determination. Given the timing of this similar measure in the Hospital 
IQR Program, we believe IPFs will have had the opportunity to learn 
from the experiences of acute care hospitals, including best practices 
for minimally burdensome assessment of performance on the required 
domains.
    Comment: Many commenters supported adoption of this measure on the 
condition that CMS commit to development and adoption of health equity 
related outcome measures in the future.
    Response: We 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

[[Page 51106]]

characteristics. This more comprehensive suite of measures could 
eventually include health equity related outcome measures.
    Comment: Many commenters recommended that CMS establish a process 
to ensure that results are publicly reported in a way that helps 
patients interpret IPF scores on the Facility Commitment to Health 
Equity measure.
    Response: We believe this measure will provide insightful 
information to healthcare providers and the public on the number of 
IPFs currently participating in health equity strategic planning, 
collecting data, using these 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.
    Comment: Many commenters recommended that prior to adoption of the 
Facility Commitment to Health Equity measure CMS identify a means to 
verify accurate attestation of commitment by IPFs.
    Response: We understand commenters' concerns regarding the accuracy 
of provider self-reported data. While we do not have a specific means 
to validate IPFs' attestation to this measure, we do require all IPFs 
participating in the IPFQR Program to complete the Data Accuracy and 
Completeness Acknowledgement (DACA) each year, which requires 
attestation that all of the information reported to CMS for the IPFQR 
Program is accurate and complete. For more information on the IPFQR 
Program's DACA requirements, we refer readers to the FY 2013 IPPS/LTCH 
PPS final rule (77 FR 53658).
    Comment: Several commenters recommended that CMS update the measure 
specifications so that IPFs without certified EHR technology are able 
to positively attest to all domains. These commenters expressed concern 
that public reporting of measure results for IPFs that do not 
positively attest to all domains because they are without access to 
certified EHR technology could lead the public to misinterpret the 
results as a lack of commitment to health equity when it is actually a 
resource limitation which, the commenters believed, is due to a lack of 
federal funding for EHR implementation.
    Response: We acknowledge that some IPFs may face challenges to 
adopting certified EHR technology. We note that the IPFQR Program is a 
pay-for-reporting program, not a pay-for-performance program, and 
therefore IPFs that do not have certified EHR technology can attest 
that they satisfy the other domains, as applicable, and receive a score 
of 0-4 out of 5 without any penalties. We understand the commenters' 
concern that the public may misinterpret IPFs' reported results that 
are due to resource limitations as a lack of commitment to health 
equity. To reduce the likelihood of misinterpretation, we intend to 
provide educational materials as part of our outreach and public 
reporting of this measure to ensure understanding and appropriate 
interpretation of publicly reported data.
    Comment: Some commenters recommended respecifying the measure so 
that IPFs are scored on a zero to eleven scale (one point for each 
element within a domain) as opposed to a zero to five scale (one point 
for each domain). Other commenters recommended only requiring 
attestation for 3 out of 5 domains. Some of these commenters stated 
that some domains are harder to achieve or have more required elements 
for attestation than others and expressed the belief that reducing the 
number of required domains would address this concern.
    Response: We believe the five domains of this measure are 
actionable focus areas, and assessment of facility 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 any identified gaps, and ensure 
that resources are dedicated toward addressing health equity 
initiatives. 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.\61\ We believe that accomplishing each element within a 
domain is important together with the other elements to help hospitals 
identify, prioritize, and take action on health disparities. 
Additionally, as discussed previously, we note that the IPFQR Program 
is a pay-for-reporting program, and IPFs are not scored based on their 
performance on measures.
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    \61\ 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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    Comment: Several commenters expressed concern that IPFs may not 
report the measure consistently, and one commenter recommended that CMS 
provide clarification of key terms (such as ``strategic plan'') to 
mitigate the risk of inconsistent reporting.
    Response: We note that Attestation Guidance for the similar measure 
adopted in the Hospital IQR Program (the Hospital Commitment to Health 
Equity measure), includes definitions of key terms including 
``strategic plan,'' which we define as ``a written plan to address 
health equity that is shared across the hospital'' (or facility in the 
case of IPFs).\62\ To help with consistent implementation, we will 
develop a similar Attestation Guidance document for IPFs as part of 
providing educational and training materials, and which will be 
conveyed through routine communication channels to IPFs, vendors, and 
QIOs, including, but not limited to, issuing memos, emails, and notices 
on a CMS website.
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    \62\ Available at: https://qualitynet.cms.gov/files/6481de126f7752001c37e34f?filename=AttstGdnceHCHEMeas_v1.1.pdf.
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    Comment: One commenter did not support adoption of the Facility 
Commitment to Health Equity measure and expressed their belief that 
there is insufficient evidence that this measure leads to improved 
patient outcomes.
    Response: We believe this measure is an important foundational 
measure for improving health equity among those that have been 
disadvantaged or underserved by the healthcare system. Furthermore, as 
discussed in section VI.D.2.a of the proposed rule, there is 
substantial research showing differences in care and experiences among 
these populations (88 FR 21274 through 21275). We also believe adoption 
of the Facility Commitment to Health Equity measure will incentivize 
IPFs to collect and utilize data to identify critical equity gaps, 
implement plans to address these gaps, and ensure that resources are 
dedicated toward addressing health equity initiatives. This measure 
aims to support IPFs in leveraging available data, pursuing focused 
quality improvement activities, and promoting efficient and effective 
use of resources. Through this measure, providers are encouraged to 
analyze their own data to understand the many factors, including race, 
ethnicity, and various social drivers of health, such as housing 
stability and food security, in order to deliver more equitable care. 
We believe the delivery of more equitable care will, in turn, improve 
patient outcomes.

[[Page 51107]]

    Final Decision: After consideration of the public comments we 
received, we are finalizing adoption of the Facility Commitment to 
Health Equity measure as proposed.
3. Adoption of the Screening for Social Drivers of Health Measure 
Beginning With Voluntary Reporting of CY 2024 Data Followed by 
Mandatory Reporting Beginning With CY 2025 Data/FY 2027 Payment 
Determination
a. Background
    Health-related social needs (HRSNs), which we define as individual-
level, adverse social conditions that negatively impact an individual 
person's health or healthcare, are significant risk factors associated 
with worse health outcomes as well as increased healthcare 
utilization.\63\ We believe that consistently pursuing identification 
of HRSNs would have two significant benefits. First, HRSNs 
disproportionately impact people who have historically been underserved 
by the healthcare system,\64\ and screening helps identify individuals 
who may have HRSNs. Second, screening for HRSNs could support ongoing 
IPF quality improvement initiatives by providing data with which to 
stratify patient risk and organizational performance. Further, we 
believe that IPFs collecting patient-level HRSN data through screening 
is essential for 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.
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    \63\ 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 on February 20, 2023.
    \64\ American Hospital Association. (2020). Health Equity, 
Diversity & Inclusion Measures for Hospitals and Health System 
Dashboards. December 2020. Available at: https://ifdhe.aha.org/system/files/media/file/2020/12/ifdhe_inclusion_dashboard.pdf. 
Accessed on February 20, 2023.
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    Health disparities manifest primarily as worse health outcomes in 
population groups where access to care is 
inequitable.65 66 67 68 69 Such differences persist across 
geography and healthcare settings irrespective of improvements in 
quality of care over time.70 71 72 Assessment of HRSNs is an 
essential mechanism for capturing the interaction between social, 
community, and environmental factors associated with health status and 
health outcomes.73 74 75
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    \65\ 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://www.ncbi.nlm.nih.gov/pmc/articles/PMC6784838/. 
Accessed on February 20, 2023.
    \66\ 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. Accessed on February 20, 2023.
    \67\ 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. Accessed on February 20, 
2023.
    \68\ 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: https://www.nejm.org/doi/10.1056/NEJMsa1405003. 
Accessed on February 13, 2023.
    \69\ 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. Accessed on February 20, 2023.
    \70\ 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. Accessed on February 20, 
2023.>
    \71\ Hill-Briggs, F. (2021). Social Determinants of Health and 
Diabetes: A Scientific Review. Diabetes Care. Available at: https://diabetesjournals.org/care/article/44/1/258/33180/Social-Determinants-of-Health-and-Diabetes-A. Accessed on February 20, 
2023.
    \72\ Khullar, D., MD. (2020). 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. Accessed on February 20, 
2023.
    \73\ 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. Accessed on February 20, 2023.
    \74\ 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. 
Accessed on February 20, 2023.
    \75\ 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 on February 2, 
2023.
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    Growing evidence demonstrates that specific HRSNs are directly 
associated with patient health outcomes as well as healthcare 
utilization, costs, and performance in quality-based payment 
programs.76 77 While widespread interest in addressing HRSNs 
exists, action is inconsistent.\78\
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    \76\ 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. https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2780864. 
Accessed on February 20, 2023.
    \77\ 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. Accessed on February 20, 2023.
    \78\ 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; https://jamanetwork.com/journals/jamanetworkopen/fullarticle/10.1001/jamanetworkopen.2019.11514. Accessed on February 20, 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.79 80 81 82 The persistent interactions 
among individuals' HRSNs, medical providers' practices and behaviors, 
and community resources significantly impact healthcare access, 
quality, and ultimately costs, as described in the CMS Equity Plan for 
Improving Quality in Medicare.83 84 In their 2018 survey, to 
which more than 8,500 physicians responded, the

[[Page 51108]]

Physicians Foundation found that almost 90 percent of these physician 
respondents reported their patients had a serious health problem linked 
to poverty or other social conditions.\85\ Additionally, associations 
among disproportionate health risk, hospitalization, and adverse health 
outcomes have been highlighted and magnified by the COVID-19 
pandemic.86 87
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    \79\ 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 
February 20, 2023.
    \80\ Khullar, D., MD. (2020). 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. Accessed on February 20, 
2023.
    \81\ 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. Accessed on February 20, 2023.
    \82\ 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 on February 20, 2023.
    \83\ Centers for Medicare & Medicaid Services. (2021). Paving 
the Way to Equity: A Progress Report. Available at: https://www.cms.gov/files/document/paving-way-equity-cms-omh-progress-report.pdf. Accessed on February 20, 2023.
    \84\ 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
. Accessed on February 20, 2023.
    \85\ 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 on February 20, 2023.
    \86\ 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 on February 20, 
2023.
    \87\ 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 
on February 20, 2023.
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    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 (that is, through screening, 
referral, and community navigation) on their health outcomes and 
related healthcare utilization and costs.\88\ \89\ \90\ \91\ 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 with over 600 clinical sites in 21 
states.\92\ The AHC Model had a 5-year period of performance that began 
in May 2017 and ended in April 2022, with beneficiary screening 
beginning in the summer of 2018.\93\ \94\ Evaluation of the AHC Model 
data is still underway.
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    \88\ 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. 
Accessed on February 20, 2023.
    \89\ Alley, D.E., Asomugha, C.N., et al. (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. Accessed on February 20, 
2023.
    \90\ 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. Accessed on February 20, 2023.
    \91\ 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 on February 20, 
2023.
    \92\ RTI International. (2020). Accountable Health Communities 
(AHC) Model Evaluation. Available at: https://innovation.cms.gov/data-and-reports/2020/ahc-first-eval-rpt. Accessed on February 20, 
2023.
    \93\ RTI International. (2020). Accountable Health Communities 
(AHC) Model Evaluation. Available at: https://innovation.cms.gov/data-and-reports/2020/ahc-first-eval-rpt. Accessed on February 20, 
2023.
    \94\ We note that the model officially concluded in April 2022, 
but many awardees have continued with no-cost extensions to continue 
utilizing unspent cooperative agreement funding and all awardees 
will conclude by April 2023.
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    Under the AHC Model, the following five core domains were selected 
to screen for HRSNs among Medicare and Medicaid beneficiaries: (1) food 
insecurity; (2) housing instability; (3) transportation needs; (4) 
utility difficulties; and (5) interpersonal safety. These domains were 
chosen based upon literature review and expert consensus utilizing the 
following criteria: (1) availability of high-quality scientific 
evidence linking a given HRSN to adverse health outcomes and increased 
healthcare utilization, including hospitalizations and associated 
costs; (2) ability for a given HRSN to be screened and identified in 
the inpatient setting prior to discharge, addressed by community-based 
services, and potentially improve healthcare outcomes, including 
reduced readmissions; and (3) evidence that a given HRSN is not 
systematically addressed by healthcare providers.\95\ 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.96 97 98
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    \95\ 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. Accessed on February 20, 2023.
    \96\ 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. Accessed on February 20, 2023.
    \97\ Centers for Medicare & Medicaid Services. (2021). 
Accountable Health Communities Model. Accountable Health Communities 
Model  CMS Innovation Center. Available at: https://innovation.cms.gov/innovation-models/ahcm. Accessed on February 20, 
2023.
    \98\ 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/. 
Accessed on February 20, 2023.
---------------------------------------------------------------------------

    These five evidence-based HRSN domains, which informed development 
of the two Social Drivers of Health measures adopted in the Hospital 
IQR Program and finalized here for the IPFQR Program, are described in 
Table 18. We note that while the measures were initially developed by 
The Health Initiative (THI), CMS has since assumed stewardship.
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    \99\ 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. Available at https://pubmed.ncbi.nlm.nih.gov/30222918/. Accessed on February 20, 2023.
    \100\ Hill-Briggs, F. (2021). Social Determinants of Health and 
Diabetes: A Scientific Review. Diabetes Care. Available at: https://diabetesjournals.org/care/article/44/1/258/33180/Social-Determinants-of-Health-and-Diabetes-A. Accessed on February 20, 
2023.
    \101\ 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/. 
Accessed on February 20, 2023.
    \102\ 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. 
Accessed on February 20, 2023.
    \103\ Hill-Briggs, F. (2021). Social Determinants of Health and 
Diabetes: A Scientific Review. Diabetes Care. Available at: https://diabetesjournals.org/care/article/44/1/258/33180/Social-Determinants-of-Health-and-Diabetes-A. Accessed on February 20, 
2023.
    \104\ 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. Available at https://pubmed.ncbi.nlm.nih.gov/30222918/. Accessed on February 20, 2023.
    \105\ 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. Accessed on February 20, 2023.
    \106\ https://ps.psychiatryonline.org/doi/10.1176/appi.ps.201300022?url_ver=Z39.88-2003&rfr_id=ori:rid:crossref.org&rfr_dat=cr_pub%20%200pubmed. 
Accessed on February 20, 2023.
    \107\ 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.
    \108\ 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/.
    \109\ 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.
    \110\ 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.
    \111\ 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.
    \112\ Housing Instability and Mental Health. UNC Greensboro. May 
7, 2021. Available at: https://chcs.uncg.edu/housing-instability-
mental-health/
#:~:text=Mental%20health%20is%20correlated%20with%20housing%20in%20se
veral,homeless%20population%20in%20America%20suffer%20a%20mental%20il
lness. Accessed on December 7, 2022.
    \113\ 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.
    \114\ 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.
    \115\ 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/.
    \116\ 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.
    \117\ 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.
    \118\ https://www.nami.org/Advocacy/Policy-Priorities/Supporting-Community-Inclusion-and-Non-Discrimination/Medicaid-Non-Emergency-Medical-Transportation.
    \119\ 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.
    \120\ 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.
    \121\ 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.
    \122\ 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.
    \123\ 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.
    \124\ https://ajph.aphapublications.org/doi/abs/10.2105/AJPH.2013.301680.
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    As a first step towards leveraging the opportunity to close equity 
gaps by identifying patients' HRSNs, we finalized the adoption of two 
evidence-based measures in the Hospital IQR Program--the Screening for 
Social Drivers of Health measure and the Screen Positive Rate for 
Social Drivers of Health measure (collectively, Social Drivers of 
Health measures)--and refer readers to the FY 2023 IPPS/LTCH PPS final 
rule (87 FR 49191 through 49220).
    Through adoption in the IPFQR Program, these two Social Drivers of 
Health measures (that is, the Screening for Social Drivers of Health 
measure discussed in this section and the Screen Positive Rate for 
Social Drivers of Health measure discussed in section VI.D.4 of this 
final rule) 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

[[Page 51111]]

HRSNs data. This activity aligns with our other efforts beyond the 
acute care setting, including the CY 2023 Medicare Advantage and Part D 
final rule in which we finalized the policy requiring that all Special 
Needs Plans (SNPs) include one or more questions on housing stability, 
food security, and access to transportation in their health risk 
assessment using questions from a list of screening instruments 
specified in sub-regulatory guidance (87 FR 27726 through 27740) as 
well as the CY 2023 Physician Fee Schedule (PFS) final rule in which we 
adopted the Screening for Social Drivers of Health measure in the 
Merit-based Incentive Payment System (MIPS) (87 FR 70054 through 
70055).
    The Social Drivers of Health measures (as set forth in this section 
VI.D.3 and section VI.D.4. of this final rule) will encourage IPFs to 
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 people with greatest risk, 
and improve the IPF's quality of care.125 126 127 128 
Further, these data could guide future public and private resource 
allocation to promote targeted collaboration among IPFs, health 
systems, community-based organizations, and others in support of 
improving patient outcomes. We believe that this screening is 
especially important for IPF patients because patients with psychiatric 
conditions have an increased risk of having HRSNs.\129\
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    \125\ Baker, M.C., Alberti, P.M., et al. (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. Accessed on February 20, 2023.
    \126\ Hammond, G., Johnston, K., et al. (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. 
Accessed on February 20, 2023.
    \127\ Hill-Briggs, F. (2021). Social Determinants of Health and 
Diabetes: A Scientific Review. Diabetes Care. Available at: https://diabetesjournals.org/care/article/44/1/258/33180/Social-Determinants-of-Health-and-Diabetes-A. Accessed on February 20, 
2023.
    \128\ 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/. Accessed on February 20, 2023.
    \129\ Adepoju, OE, Liaw, W, et al. (2022) Assessment of Unmet 
Health-Related Social Needs Among Patients with Mental Illness 
Enrolled in Medicare Advantage. Available at: https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2798096. 
Accessed on December 7, 2022.
---------------------------------------------------------------------------

    In the FY 2023 IPF PPS final rule, we observed that the Hospital 
IQR Program had proposed two Social Drivers of Health measures and 
stated that we would consider these measures for the IPFQR Program in 
the future (87 FR 46873). The first of these two measures is 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.
    Utilization of screening tools to identify the burden of unmet 
HRSNs can be a helpful first step for IPFs 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 and adopted for acute 
care hospitals in the Hospital IQR Program will illuminate their impact 
on health outcomes and disparities and the healthcare cost burden for 
IPFs, particularly for IPFs that serve patients with disproportionately 
high levels of social risk, given that patients with serious mental 
illness are especially vulnerable to and affected by HRSNs. In 
addition, data collection in the IPF care setting could inform 
meaningful and sustainable solutions for provider-types participating 
in other quality reporting programs to close equity gaps among the 
communities they serve.130 131 132 133 134
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    \130\ 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.
    \131\ 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.
    \132\ 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.
    \133\ 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.
    \134\ De Marchis, E., Knox, M., Hessler, D., WillardGrace, 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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    For data collection of the Screening for Social Drivers of Health 
measure, IPFs 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. One example of a 
potential screening tool for IPFs to collect data on the Screening for 
Social Drivers Health Measure is the AHC Model's standard 10-item AHC 
Health-Related Social Needs Screening Tool (AHC HRSN Screening Tool), 
which enables providers to identify HRSNs in the five core domains 
(described in Table 18) among community-dwelling Medicare, Medicaid, 
and dually eligible beneficiaries. The AHC Model, including its 
screening tool, was tested across many care delivery sites in diverse 
geographic locations across the United States. More than one million 
Medicare and Medicaid beneficiaries have been screened using the AHC 
HRSN Screening Tool, which was evaluated psychometrically and 
demonstrated evidence of both reliability and validity, including 
inter-rater reliability and concurrent and predictive validity. 
Moreover, the AHC HRSN Screening Tool can be implemented in a variety 
of places where patients seek healthcare, including inpatient 
psychiatric facilities.
    The intent of the Screening for Social Drivers of Health measure is 
to promote adoption of HRSN screening by IPFs. We encourage IPFs to use 
the screening as a basis for developing their own individual action 
plans (for example, navigation services and subsequent referral), as 
well as an opportunity to initiate or improve partnerships with 
community-based service providers. We believe that this measure will 
yield actionable information to close equity gaps by encouraging IPFs 
to identify patients with HRSNs, with a reciprocal goal of 
strengthening linkages between IPFs and local community-based partners 
to promptly connect patients and families to the support they need.
    Both the Screening for Social Drivers of Health measure and the 
Screen Positive Rate for Social Drivers of Health measure, discussed in 
VI.D.4. of this final rule, address our Meaningful Measures Framework's 
\135\ 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 our Meaningful Measures 
2.0, these Social Drivers of Health measures address the

[[Page 51112]]

equity priority area and align 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.'' \136\ Development, proposal, and 
adoption of these measures also aligns with our strategic pillar to 
advance health equity by addressing the health disparities that 
underlie our health system.\137\ Further, inclusion of these measures 
in the IPFQR Program aligns with these measures' adoption in the 
Hospital IQR Program in the FY 2023 IPPS/LTCH final rule (87 FR 49202 
through 49215).
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    \135\ Centers for Medicare & Medicaid Services. Meaningful 
Measures Framework. Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/CMS-Quality-Strategy.
    \136\ 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.
    \137\ 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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    The Screening for Social Drivers of Health measure (alongside the 
Screen Positive Rate for Social Drivers of Health measure described in 
section VI.D.4 of this final rule) will be the first measurement of 
social drivers of health in the IPFQR Program. We believe these 
measures are appropriate for measurement of the quality of care 
furnished by IPFs. Screening patients for HRSNs during inpatient 
hospitalization in an IPF will allow healthcare providers, including 
IPFs, to identify and potentially help address HRSNs for this medically 
underserved patient population as part of discharge planning and 
contribute to long-term improvements in patient outcomes. Identifying 
and addressing HRSNs for patients receiving care in IPFs could have a 
direct and positive impact on IPFs' quality performance because of 
improvements in patient outcomes that could occur when patients' HRSNs 
are reduced. Moreover, collecting aggregate data on the HRSNs of IPF 
patient populations via these measures is crucial in informing design 
of future measures that could enable us to set appropriate performance 
targets for IPFs with respect to closing the gap on health equity.
b. Overview of Measure
    The Screening for Social Drivers of Health measure assesses whether 
an IPF implements screening for all patients who 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, IPFs will provide: (1) the number of 
inpatients admitted to the facility who are 18 years or older at time 
of admission and who are screened for all 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 facility who are 18 years or older on 
the date they are admitted.
    Measure specifications for the Screening for Social Drivers of 
Health measure, which were available during the review of the MUC List, 
are available at https://mmshub.cms.gov/sites/default/files/map-hospital-measure-specifications-manual-2022.pdf.
(1) Measure Calculation
(a) Cohort
    The Screening for Social Drivers of Health measure assesses the 
total number of patients aged 18 years and older, screened for HRSNs 
(specifically, food insecurity, housing instability, transportation 
needs, utility difficulties, and interpersonal safety) during an IPF 
stay.
(b) Numerator
    The numerator of the Screening for Social Drivers of Health measure 
consists of the number of patients admitted to an IPF stay who are 18 
years or older on the date of admission and are screened during their 
IPF stay for all of the following five HRSNs: food insecurity, housing 
instability, transportation needs, utility difficulties, and 
interpersonal safety.
(c) Denominator
    The denominator of the Screening for Social Drivers of Health 
measure consists of the number of patients who are admitted to an IPF 
stay and who are 18 years or older on the date of admission. The 
following patients are 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 IPF stay.
(d) Calculation
    The Screening for Social Drivers of Health measure is calculated as 
the number of patients admitted to an IPF stay who are 18 years or 
older on the date of admission screened for all five HRSNs (food 
insecurity, housing instability, transportation needs, utility 
difficulties, and interpersonal safety) divided by the number of 
patients 18 years or older on the date of admission admitted to the 
IPF.
(2) Review by the Measure Applications Partnership
    We included the Screening for Social Drivers of Health measure on 
the publicly available ``List of Measures Under Consideration for 
December 1, 2022'' (MUC List), a list of measures under consideration 
for use in various Medicare programs.\138\ The CBE-convened MAP Health 
Equity Advisory Group reviewed the MUC List including the Screening for 
Social Drivers of Health measure (MUC 2022-053) in detail on December 6 
through 7, 2022.\139\ The MAP Health Equity Advisory Group expressed 
support for the collection of data related to social drivers of health, 
but raised concerns regarding public reporting of these data and 
potential repetition of asking patients the same questions across 
settings.\140\
---------------------------------------------------------------------------

    \138\ Centers for Medicare & Medicaid Services. List of Measures 
Under Consideration for December 1, 2022. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
    \139\ Centers for Medicare & Medicaid Services. 2022-2023 MAP 
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
    \140\ Centers for Medicare & Medicaid Services. 2022-2023 MAP 
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
---------------------------------------------------------------------------

    In addition, on December 8 through 9, 2022, the MAP Rural Health 
Advisory Group reviewed the 2022 MUC List and the MAP Hospital 
Workgroup did so on December 13 through 14, 2022.\141\ The MAP Rural 
Health Advisory Group noted some potential reporting challenges 
including the potential masking of health disparities that are 
underrepresented in some areas and that sample size and populations 
served may be an issue, but expressed that the Screening for Social 
Drivers of Health measure serves as a starting point to determine where 
screening is occurring. The MAP Hospital Workgroup expressed strong 
support for the measure but noted that interoperability will be 
important and cautioned about survey fatigue. The MAP Hospital 
Workgroup members conditionally supported the measure pending: (1) 
testing of the measure's reliability and validity; (2) endorsement by 
the CBE; (3) additional details on how potential tools map to the 
individual HRSNs, as well as best practices; (4) identification of 
resources that may be available to assist patients with identified 
HRSNs; and (5)

[[Page 51113]]

the measure's alignment with data standards, particularly the GRAVITY 
project.\142\ The GRAVITY project's mission statement is ``to serve as 
the open public collaborative advancing health and social data 
standardization for health equity.'' \143\ Thereafter, the MAP 
Coordinating Committee deliberated on January 24 through 25, 2023, and 
ultimately voted to uphold the MAP Hospital Workgroup's recommendation 
to conditionally support for rulemaking with the same conditions.\144\
---------------------------------------------------------------------------

    \141\ Centers for Medicare & Medicaid Services. 2022-2023 MAP 
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
    \142\ Centers for Medicare & Medicaid Services. 2022-2023 MAP 
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
    \143\ https://thegravityproject.net/.
    \144\ Centers for Medicare & Medicaid Services. 2022-2023 MAP 
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
---------------------------------------------------------------------------

    We believe this measure establishes an important foundation for 
prioritizing the achievement of health equity among IPFs. Our approach 
to developing health equity measures is incremental, and we believe 
that health care equity outcomes in the IPFQR Program will inform 
future efforts to advance and achieve health care equity by IPFs. We 
additionally believe this measure to be a building block that lays the 
groundwork for a future meaningful suite of measures that would assess 
IPF progress in providing high-quality healthcare for all patients, 
regardless of social risk factors or demographic characteristics.
(3) CBE Endorsement
    We have not submitted this measure for CBE endorsement at this 
time. Although section 1886(s)(4)(D)(i) of the Act generally requires 
that measures specified by the Secretary must be endorsed by the entity 
with a contract under section 1890(a) of the Act, section 
1886(s)(4)(D)(ii) of the Act, states 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 a measure that has been endorsed or adopted by a consensus 
organization identified by the Secretary. We reviewed measures endorsed 
by consensus organizations and were unable to identify any other 
measures on this topic endorsed by a consensus organization and 
therefore, we believe the exception in section 1886(s)(4)(D)(ii) of the 
Act applies.
c. Data Collection, Submission and Reporting
    We believe incremental implementation of the Screening for Social 
Drivers of Health measure, by permitting one year of voluntary 
reporting prior to mandatory reporting, will allow IPFs who are not yet 
screening patients for HRSNs to get experience with collecting data for 
this measure and equally allow IPFs who already undertake screening 
efforts to report data already being collected. Therefore, we proposed 
voluntary reporting of this measure beginning with the data collected 
in CY 2024, which would be reported to CMS in CY 2025, followed by 
mandatory reporting beginning with data collected in CY 2025, which 
would be reported to CMS in CY 2026 for the FY 2027 payment 
determination.
    Due to variability across IPFs and the populations they serve, and 
in alignment with the Hospital IQR Program, we will allow IPFs 
flexibility with the 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 for health-related social needs (HRSNs) 
already exist. For additional information on resources, we refer 
readers to evidence-based resources like the Social Interventions 
Research and Evaluation Network (SIREN) website, for example, for 
comprehensive information about the most widely used HRSN screening 
tools.145 146 SIREN contains descriptions of the content and 
characteristics of various tools, including information about intended 
populations, completion time, and number of questions.
---------------------------------------------------------------------------

    \145\ 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.
    \146\ 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 SDOH and healthcare delivery.
---------------------------------------------------------------------------

    We encourage IPFs to consider digital standardized screening tools 
and refer readers to the FY 2023 IPPS/LTCH PPS final rule (87 FR 49207 
through 49208) where we discuss how the use of certified health 
information technology (IT), including but not limited to certified EHR 
technology, can 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 also encourage readers to learn about the 
United States Core Data for Interoperability (USCDI) standard used in 
certified health IT and how this standard can support interoperable 
exchange of health and HRSN assessment data.\147\
---------------------------------------------------------------------------

    \147\ Office of the National Coordinator for Health IT (ONC). 
United States Core Data for Interoperability. Accessed at: https://www.healthit.gov/isa/united-states-core-data-interoperability-uscdi.
---------------------------------------------------------------------------

    We proposed that IPFs would report aggregate data on this measure, 
that is IPFs would report aggregated data for the numerator and the 
denominator to CMS (as described in section VI.D.3.b.(1). of this final 
rule) but would not be required to report patient-level data. IPFs are 
required to submit information for chart-abstracted measures once 
annually using a CMS-approved web-based data collection tool available 
within the HQR System (previously referred to as the QualityNet Secure 
Portal). We refer readers to section VI.I 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.
    We invited public comment on this proposal.
    Comment: Many commenters supported adoption of the Screening for 
Social Drivers of Health measure. Some commenters stated that screening 
for these HRSNs will help IPFs better understand patients' needs, 
improve care coordination with outpatient and community resources, 
increase the dignity and respect with which patients are treated, and 
support development of patient-centered treatment plans. One commenter 
stated that the data collected through these screenings could help IPFs 
shape facility level goals associated with health equity and empower 
the workforce to recognize and eliminate health disparities. One 
commenter specifically supported the flexibility with respect to tool 
selection and stated that this will help IPFs select the standardized 
screening instruments most applicable for their individual patient 
populations. Another commenter stated that discharge will not lead to 
positive patient outcomes if the patient is discharged to unstable 
conditions or without the transportation necessary to access support 
services.
    Response: We thank commenters for their support of the Screening 
for Social Drivers of Health measure. We agree that HRSNs are critical 
factors that

[[Page 51114]]

impact patient outcomes, and increased knowledge about patients' HRSNs 
will help IPFs shape goals associated with health equity. Further, we 
agree that collecting these data will help IPFs improve coordination 
with outpatient and community resources to better deliver patient-
centered care. Finally, we note that these activities would support 
IPFs' execution of responsibilities related to the required standard 
for social services under 42 CFR 482.62(f).
    Comment: Several commenters recommended that CMS conduct additional 
testing, specifically in the IPF setting, to ensure that the measure 
addresses the specific needs of the IPF patient population.
    Response: We acknowledge that this measure was initially developed 
for the general acute care setting. While we recognize the value of 
measures undergoing testing and evaluation of validity and feasibility 
in the setting for which they are being adopted, given the urgency of 
identifying and addressing HRSNs described in section VI.D.4.a of this 
final rule, and, as there are currently no other existing measures that 
address Screening for Social Drivers of Health, we believe it is 
important to implement this measure as soon as feasible. We believe 
that this measure is equally applicable to freestanding IPFs and 
psychiatric units within acute care facilities as to general acute care 
settings, because we believe that identifying the HRSNs of IPF patients 
will be equally valuable in understanding patients' needs, improving 
care coordination with outpatient and community resources, increasing 
the dignity and respect with which patients are treated, and supporting 
development of patient-centered treatment plans as identifying the 
HRSNs of acute care hospital patients. We note that identifying and 
addressing HRSNs is a critical topic for patients treated in IPFs and 
that there are high levels of health disparities experienced by this 
patient population. CMS will monitor measure implementation and data 
reporting as part of standard program and measure review and will 
consider updates to the measure if improvements are identified through 
this process.
    Comment: Many commenters expressed concern that this measure has 
not received endorsement by the CBE.
    Response: While we recognize the value of measures undergoing 
review for potential CBE endorsement, given the urgency of achieving 
health equity, we believe it is important to implement this measure 
with voluntary reporting beginning with the CY 2024 reporting period 
followed by mandatory reporting beginning with the CY 2025 reporting 
period/FY 2027 payment determination. We note that, under section 
1886(s)(4)(D)(ii) 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 measures endorsed by consensus 
organizations and were unable to identify any other measures on this 
topic endorsed by a consensus organization, and therefore, we believe 
the exception in section 1886(s)(4)(D)(ii) of the Act applies.
    Comment: Many commenters recommended extending the voluntary 
reporting phase for this measure.
    Response: 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 
therefore have determined that the proposed voluntary and mandatory 
reporting periods prioritize the urgency of capturing social drivers of 
health data and taking actionable steps towards closing the health 
equity gap.
    Comment: Some commenters recommended that CMS defer adoption of 
this measure until the Hospital IQR Program's voluntary reporting 
period for its version of this measure concludes to allow CMS and IPFs 
to identify best practices for screening patients and collecting HRSNs 
data in a minimally burdensome way. Some of these commenters stated 
that IPFs often have fewer resources available for such data collection 
relative to acute care hospitals. Other commenters recommended engaging 
IPFs to voluntarily test the measure to ensure usability, 
acceptability, and face validity are met for this setting.
    Response: We acknowledge commenters' desire to be able to learn 
from the experiences of acute care hospitals reporting this measure. 
Hospitals participating in the Hospital IQR Program that choose to 
voluntarily report this measure will have already reported data in CY 
2024 (87 FR 49207). Furthermore, the Hospital IQR Program finalized 
mandatory reporting of this measure for the FY 2026 payment 
determination (that is data submitted in CY 2025 representing the CY 
2024 performance period) (87 FR 49207). Given the timing of reporting 
this measure in the Hospital IQR Program, we believe that IPFs will 
have the opportunity to learn from the experiences of acute care 
hospitals, including best practices for collecting HRSNs data, prior to 
mandatory reporting for the IPFQR Program for the FY 2027 payment 
determination. Furthermore, we believe that the voluntary reporting of 
CY 2024 data submitted to CMS in CY 2025 for the IPFQR Program will 
provide additional opportunities to identify minimally burdensome 
screening instruments and data collection practices. Finally, we note 
that we will monitor measure implementation and data reporting as part 
of standard program and measure review and will consider updates to the 
measure if improvements are identified through this process. Therefore, 
we do not believe that the benefits of extending voluntary reporting of 
this measure in the IPFQR Program for more than one year outweigh the 
potential detriments associated with delay in measure adoption that 
extending the voluntary reporting period would require.
    Comment: Several commenters had recommendations related to the 
specifications for the Screening for Social Drivers of Health measure 
regarding the frequency and timing of administering these screenings. 
One commenter recommended not requiring individual patients to be 
screened more frequently than once per quarter so that patients who are 
readmitted or admitted to other settings over a short duration are not 
repeatedly screened when their HRSNs are unlikely to have changed. 
Another commenter recommended that for patients who have long stays 
(sometimes greater than one year) the measure should be updated to 
require an annual screening and screening at discharge. This commenter 
stated that for these patients screening at discharge would provide 
data which would inform discharge planning.
    Response: We understand the commenters' concerns, especially given 
the frequency of unmet HRSNs among psychiatric patients, regarding 
patients who may be screened frequently, or whose screening results may 
change significantly during their inpatient stay (such as those 
patients with long duration stays). We note that screening can occur 
any time during the hospital admission prior to discharge. Further, for 
patients frequently admitted to inpatient facilities, the IPF could 
confirm the current status of any previously reported HRSNs and inquire 
about other HRSNs not previously reported or that may have changed in 
the intervening period. For additional information on how to apply and 
report these screenings, we refer readers to the Hospital IQR Program's 
Frequently Asked Questions document regarding this measure in the 
Hospital IQR

[[Page 51115]]

Program, available at: We will develop a similar Frequently Asked 
Questions document for IPFs as part of providing educational and 
training materials; this document will be conveyed through routine 
communication channels to hospitals, vendors, and QIOs, including, but 
not limited to, issuing memos, emails, and notices on a CMS website.
    Comment: Several commenters recommended additional changes to the 
measure specifications. Due to the sensitive nature of screening for 
risk of interpersonal violence, commenters recommended changes that 
included removing this domain from the measure specifications, and 
updating the measure to ensure patient privacy when responding to this 
screening question, either by excluding patients who could not respond 
to the question confidentially, or by ensuring responses remain hidden 
in all records and handouts accessible to patients. One commenter 
recommended removing the exclusion language ``and lack of a guardian or 
caregiver available to do so on the patient's behalf'' because such a 
guardian or caregiver may provide inaccurate information about the 
patient's risk of interpersonal violence. One commenter recommended 
excluding patients coming from or being discharged to long-term care 
settings because these patients would be at lower risk for these five 
HRSNs. Another commenter recommended expanding the measure to include 
screening for lack of financial resources.
    Response: We have prioritized selection of the proposed five HRSN 
domains based on existing evidence from both the AHC Model, including 
recommendations from a technical expert panel (TEP) that informed the 
initial selection, and emerging evidence of correlations between given 
social drivers of health and worse health outcomes and social drivers 
of health for which interventions have shown marked improvements in 
health outcomes and healthcare utilization (88 FR 21280). Through this 
process we did not identify lack of financial resources as being one of 
the social drivers of health that met our criteria for selection (these 
criteria are set forth in section V.D.3.a. of the proposed rule and in 
section VI.D.3 of this final rule); therefore, we did not include it in 
the Screening for Social Drivers of Health measure. We note that while 
the Screening for Social Drivers of Health measure requires screening 
for the five identified HRSNs, IPFs may screen for additional HRSNs 
that they believe are relevant for their patient population and the 
community in which they serve, and that standardized screening 
instruments such as those available for screening for these five HRSNs 
may also include a screening for lack of financial resources. For 
example, the Accountable Health Communities screening tool includes 
questions for eight supplemental domains, including financial strain. 
Furthermore, we note that this measure is a first step towards 
development of a long-term strategy to integrate social drivers of 
health and HRSN data into quality performance measurement and is part 
of our broader commitment to health equity.
    We believe it is imperative that IPFs screen for all five domains 
established in this measure. We understand commenters' concerns 
regarding the sensitive nature of screening for risk of interpersonal 
violence and agree that patient safety must remain the IPF's principal 
concern. We recommend that IPFs ensure that patients feel that they are 
safe answering questions and remind patients that they may opt out of 
the screening for any reason. We note that, because IPFs likely are 
covered entities under the Health Insurance Portability and 
Accountability Act of 1996 (HIPAA) Rules (codified at 45 CFR parts 160 
and 164),\148\ information provided by patients in response to 
screening for this measure would be protected health information 
(PHI).\149\ Therefore, IPFs are responsible for adopting reasonable 
safeguards to ensure that patients' PHI is not impermissibly disclosed 
contrary to applicable confidentiality, security, and privacy laws.
---------------------------------------------------------------------------

    \148\ For more information on the three HIPAA rules, we refer 
readers to the HIPAA for Professionals site at: https://www.hhs.gov/hipaa/for-professionals/.
    \149\ https://www.hhs.gov/answers/hipaa/what-is-phi/.
---------------------------------------------------------------------------

    We do not believe it would be appropriate to remove the exclusion 
which would allow a caregiver or guardian to provide information on a 
patient's behalf if the patient is unable to do so. While we agree that 
the scenario presented by commenters (that is, a guardian or caregiver 
may provide inaccurate information about the patient's risk of 
interpersonal violence) is possible, we do not believe that the 
potential unintended consequence of capturing inaccurate data for this 
HRSN for a small portion of patients outweighs the potential benefit of 
capturing accurate data regarding all of these five HRSNs for as many 
patients as possible, including those who are unable to respond to the 
screening without the assistance of a caregiver or guardian.
    Finally, we believe that it is appropriate to assess the HRSNs of 
all eligible patients (that is, patients who are over 18 years of age 
at admission and do not meet the measure's exclusion criteria) 
including patients being admitted from or discharged to long-term care 
settings. While these patients are at lower risk during their stay in 
the long-term care facility, we believe it is appropriate for the IPF 
to assess the patient's overall risk of unmet HRSNs. We note, for 
example, that the AHC screening instrument assesses the patient's HRSNs 
over the past 12 months for the majority of the HRSNs included in this 
tool. Therefore, screening patients admitted from or being discharged 
to long-term care settings could help identify unmet HRSNs among this 
patient population. We will continue to take all concerns, comments, 
and suggestions into account and 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: One commenter recommended that the Screening for Social 
Drivers of Health measure be completed by a peer support specialist to 
engender trust and create a safe environment.
    Response: We agree with the commenter that it is important for the 
screening for HRSNs to be accomplished in a way that engenders trust 
and creates a safe environment. We recommend that IPFs evaluate the 
requirements for administration (such as whether the screening 
instrument can be administered by peer support specialists) as part of 
their instrument selection process. We note that the AHC instrument 
described in section VI.D.3 of this rule allows administration by 
clinicians and staff \150\ and would allow administration by peer 
support specialists.
---------------------------------------------------------------------------

    \150\ https://nam.edu/standardized-screening-for-health-related-social-needs-in-clinical-settings-the-accountable-health-communities-screening-tool/.
---------------------------------------------------------------------------

    Comment: One commenter recommended aligning SDOH related measures, 
including this one, across programs including programs for the 
ambulatory setting (including MIPS).
    Response: We agree with the commenter that addressing patients' 
HRSNs is important in all settings in which patients access care. We 
note that this measure was adopted into MIPS in the CY 2023 Physician 
Fee Schedule (PFS) final rule (87 FR 70055) as well as the Hospital IQR 
Program in the FY 2023 IPPS/LTCH PPS final rule (87 FR 49215). In 
addition, we have proposed to adopt this measure in the PPS-Exempt 
Cancer Hospital Quality Reporting Program in the FY 2024 IPPS/

[[Page 51116]]

LTCH PPS proposed rule (88 FR 27128) and the End-Stage Renal Disease 
Quality Incentive Program in the CY 2024 ESRD PPS proposed rule (88 FR 
42515). We note that only the IPFQR Program is the subject of this 
final rule, and the commenter's recommendation is therefore beyond the 
scope of this final rule.
    Comment: One commenter recommended against public reporting until a 
standardized, validated instrument is adopted so the data are collected 
using a uniform tool. One commenter requested that CMS provide guidance 
on which available, standardized assessment instruments address each of 
the domains.
    Response: We are sensitive to the concerns raised by commenters 
about the lack of clarity about which screening instrument IPFs should 
use in order to screen for HRSNs. We acknowledge the challenges that 
lack of standardization across screening instruments or data collection 
practices may introduce in the consistency of the information collected 
across IPFs. While we acknowledge the potential benefits of a single 
screening instrument or prescribed set of standards, we also recognize 
the benefits of providing IPFs 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. We encourage IPFs to prioritize screening tools that have 
undergone thorough 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.
    For selecting a screening tool, we suggest that IPFs refer to 
evidence-based resources for comprehensive information about the most 
widely used HRSN screening tools. For example, the Social Interventions 
Research and Evaluation Network (SIREN) website,\151\ housed at the 
Center for Health and Community at the University of California, San 
Francisco, contains descriptions of the content and characteristics of 
various tools, including information about intended populations, 
completion time, and number of questions.
---------------------------------------------------------------------------

    \151\ https://chc.ucsf.edu/siren.
---------------------------------------------------------------------------

    Comment: Several commenters stated that a measurement of whether a 
screening occurred does not indicate whether the needs have been met 
nor the impact of these specific HRSNs on the patient's health 
outcomes. Some of these commenters also stated that the lack of 
resources faced by IPFs may lead IPFs to screen for SDOH for which they 
are unable to assist patients. These commenters expressed concern that 
this may be frustrating for patients who would expect the IPF to 
address these needs after the screening.
    Response: During the development of both Social Drivers of Health 
measures, we gave this topic significant consideration. The intent of 
the two measures is to promote adoption of screening patients for HRSNs 
by healthcare providers as well as taking action to connect patients 
who identify one or more HRSNs with available resources. Evaluation of 
the AHC Model concluded that universal screening may identify needs 
that would otherwise remain undetected.\152\ 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 
collecting data from screening for HRSNs will be identification of 
opportunities to enable meaningful action, including prioritizing and 
investing in such resources. Beginning to collect the data on patients' 
HRSNs remains imperative and a crucial step in developing resources for 
advancing health equity. 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, as noted in the FY 2023 IPPS/LTCH PPS final rule, in which the 
Hospital IQR Program adopted these measures (87 FR 49213).
---------------------------------------------------------------------------

    \152\ RTI International. (2020). Accountable Health Communities 
(AHC) Model Evaluation. Available at: https://innovation.cms.gov/data-and-reports/2020/ahc-first-eval-rpt.
---------------------------------------------------------------------------

    Comment: One commenter requested clarification of whether the 
measure will represent the ``total number'' of patients screened for 
SDOH or the proportion of patients screened for SDOH.
    Response: IPFs will report the aggregate numerator for this measure 
(that is, the total number of patients admitted to an IPF stay who are 
18 years or older on the date of admission and screened for all five 
HRSNs), and the aggregate denominator (that is, number of patients who 
are admitted to an IPF stay and who are 18 years or older on the date 
of admission). Using these data and the denominator exclusions (that 
is, patients who opt-out of screening and 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 their behalf during 
their IPF stay), we will calculate the screening rate (that is, the 
proportion of patients screened for all five SDOH) for this measure.
    Comment: One commenter did not support this measure because of 
their concern that the specific HRSNs in the Screening for Social 
Drivers of Health measure are not completely aligned with the HL7 
Gravity Project.
    Response: We have prioritized the five HRSN domains in this measure 
based on existing evidence from the AHC Model including recommendations 
from a TEP that informed the initial selection. We commend additional 
initiatives currently underway to expand capabilities to capture 
additional social drivers of health data elements, including the 
Gravity Project. We note that the five domains covered by the Screening 
for Social Drivers of Health measure are included within the ``social 
risk domains'' of the Gravity Project. We support harmonization of data 
regarding HRSNs for interoperable electronic health information 
exchange that will meet information exchange standards.
    Comment: One commenter did not support this measure stating their 
belief that there is a lack of evidence that screening impacts quality 
of care provided by IPFs.
    Response: We note that the two Social Drivers of Health measures 
are derived from existing evidence from both the AHC Model and emerging 
evidence of correlations between the designated social 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 (88 FR 21280).
    Comment: One commenter did not support required reporting of these 
data because, while the commenter agreed that screening for SDOH is 
important and should be occurring in the IPF setting, the commenter 
expressed concern that reporting these data is too burdensome and takes 
away from patient care. Another commenter did not support the Screening 
for Social Drivers of Health measure because IPF stays are typically 
only a few days, and the commenter stated their belief that there is 
therefore insufficient time to complete these screenings during the 
stay.
    Response: While we understand implementation of HRSN screening 
processes and reporting of the SDOH measures is associated with some 
burden, as discussed in sections VII.B.

[[Page 51117]]

and VIII.A of this final rule, we believe the benefits outweigh the 
burden, as screening for and identifying patients' HRSNs is a critical 
step towards treating the whole patient, improving clinical outcomes, 
improving equitable care, and ultimately eliminating disparities in 
health outcomes among populations that have been historically 
underserved by the healthcare system.
    We note that screening can occur any time during the IPF admission 
prior to discharge and that, for example, the AHC Screening Tool 
addresses these 5 HRSNs using a total of 10 questions. Therefore, we 
believe that IPFs will be able to find sufficient time during the 
patient's IPF stay to administer this or a similar screening tool for 
SDOH.
    Final Decision: After consideration of the public comments we 
received, we are finalizing adoption of the Screening for Social 
Drivers of Health measure as proposed.
4. Adoption of the Screen Positive Rate for Social Drivers of Health 
Measure Beginning With Voluntary Reporting of CY 2024 Data and Followed 
by Mandatory Reporting Beginning With CY 2025 Data/FY 2027 Payment 
Determination
a. Background
    The impact of social risk factors on health outcomes has been well-
established in the literature.153 154 155 156 157 The 
Physicians Foundation reported that 73 percent of the physician 
respondents to the 2021 iteration of their annual survey agreed that 
social risk factors like housing instability and food insecurity would 
drive health services demand.\158\ Recognizing the need for a more 
comprehensive approach to eliminating the health equity gap, we have 
prioritized quality measures that would capture social risk factors and 
facilitate assessment of their impact on health outcomes and 
disparities and healthcare utilization and costs.159 160 161 
Specifically, in the inpatient setting, we aim to encourage systematic 
identification of patients' HRSNs (as defined in section VI.D.3.a. of 
this final rule) as part of discharge planning with the intention of 
promoting linkages with relevant community-based services that address 
those needs and support improvements in health outcomes following 
discharge from the IPF.
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    \153\ 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.
    \154\ 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.
    \155\ 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.
    \156\ 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.
    \157\ 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.
    \158\ 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.
    \159\ 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.
    \160\ 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.
    \161\ 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 measure (discussed 
previously in section VI.D.3. of this final rule) enables 
identification of individuals with HRSNs, use of the Screen Positive 
Rate for Social Drivers of Health measure would allow IPFs to capture 
the magnitude of these needs and even estimate the impact of 
individual-level HRSNs on healthcare utilization when evaluating 
quality of care.162 163 164 The Screen Positive Rate for 
Social Drivers of Health measure will require IPFs to report the rates 
of patients who screened positive for each of the five core HRSNs. 
Reporting the screen positive rate for each of the five core HRSNs will 
inform actionable planning by IPFs towards closing health equity gaps 
unique to the populations they serve and enable the development of 
individual patient action plans (including navigation and referral 
services).
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    \162\ 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.
    \163\ 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.
    \164\ 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 IPF PPS final rule (86 FR 42625 through 42632) and 
the FY 2023 IPF PPS final rule (87 FR 46865 through 46873), we 
discussed our ongoing consideration of potential approaches that could 
be implemented to address health equity through the IPFQR Program. 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 measure assesses the percent of patients admitted to the IPF 
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 five HRSNs, 
including food insecurity, housing instability, transportation needs, 
utility difficulties, or interpersonal safety (reported as five 
separate rates).\165\
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    \165\ 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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    We refer readers to section VI.D.3 of this final rule where we 
previously discussed the screening and identification process resulting 
in the selection of these five domains associated with the Screen for 
Social Drivers of Health measure. The Screening for Social Drivers of 
Health measure forms the basis of this Screen Positive Rate for Social 
Drivers of Health measure. That is, the number of patients screened for 
all five HRSNs in the Screening for Social Drivers of Health measure is 
the denominator of the Screen Positive Rate for Social Drivers of 
Health measure described here.
    The COVID-19 pandemic underscored the overwhelming impact that 
these five core domains of HRSNs have on disparities, health risk, 
healthcare access, and health outcomes, including premature 
mortality.166 167

[[Page 51118]]

Adoption of the Screen Positive Rate for Social Drivers of Health 
measure will encourage IPFs 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 useful for 
patients by providing data transparency and signifying IPFs' 
familiarity, expertise, and commitment regarding these health equity 
issues. This measure also has the potential to reduce healthcare 
provider burden and burnout, including among IPFs and their staff, by 
both acknowledging patients' non-clinical needs that nevertheless 
greatly contribute to adverse clinical outcomes and linking providers 
with community-based organizations to enhance patient-centered 
treatment and discharge planning.168 169 170 Finally, we 
believe the Screen Positive Rate for Social Drivers of Health measure 
has the potential to facilitate data-informed collaboration with 
community-based services and focused community investments, including 
the development of pathways and infrastructure to connect patients to 
local community resources.
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    \166\ 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.
    \167\ 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.
    \168\ 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.
    \169\ De Marchis, E., Knox, M., Hessler, D., WillardGrace, 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.
    \170\ 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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    Ultimately, we are focused on supporting effective and sustainable 
collaboration between healthcare delivery and local community-based 
services organizations to meet the unmet needs of people they serve. 
Reporting data from both the Screening for Social Drivers of Health and 
the Screen Positive Rate for Social Drivers of Health measures will 
enable both identification and quantification of the levels of unmet 
HRSNs among communities served by IPFs. These two Social Drivers of 
Health measures harmonize, as it is important to know both whether 
screening occurred and the results from the screening in order to 
develop sustainable solutions. We believe that there are multiple 
benefits to increasing IPFs' understanding of their patients' HRSNs. 
First, we believe that this could lead to increased clinical-community 
collaborations and an associated increase in system capacity and 
community investments. Second, we believe this in turn could yield a 
net reduction in costly healthcare utilization by promoting more 
appropriate healthcare service consumption.\171\
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    \171\ 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.
---------------------------------------------------------------------------

    Pursuant to our Meaningful Measures 2.0 Framework and in alignment 
with the measures previously adopted for hospitals participating in the 
Hospital IQR Program, the Screen Positive Rate for Social Drivers of 
Health measure will address the equity priority area and align 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.'' \172\ Under 
our Meaningful Measures Framework, the Screen Positive Rate for Social 
Drivers of Health measure will address the quality priority of ``Work 
with Communities to Promote Best Practices of Healthy Living'' through 
the Meaningful Measures Area of ``Equity of Care.'' \173\ Adoption of 
this measure will also align with our strategic pillar to advance 
health equity by addressing the health disparities that underlie our 
health system.\174\
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    \172\ 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.
    \173\ 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.
    \174\ 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 measure is 
intended to enhance standardized data collection that can identify 
individuals who are at higher risk for poor health outcomes related to 
HRSNs who would benefit from connection via the IPF to targeted 
community-based services.\175\ The measure identifies the proportion of 
patients admitted to an IPF stay who are 18 years or older on the date 
of admission to the IPF who screened positive for one or more of the 
following five HRSNs: food insecurity, housing instability, 
transportation needs, utility difficulties, and interpersonal safety.
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    \175\ 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.
---------------------------------------------------------------------------

    Consistent with the Hospital IQR Program, which adopted this 
measure in the FY 2023 IPPS/LTCH PPS final rule (87 FR 49215 through 
49220), we will require IPFs to report this measure as five separate 
rates. Specifically, IPFs will report the number of patients who 
screened positive for food insecurity, the number of patients who 
screened positive for housing instability, the number of patients who 
screened positive for transportation needs, the number of patients who 
screened positive for utility difficulties, and the number of patients 
who screened positive for interpersonal safety. We note that this 
measure is intended to provide information to IPFs on the level of 
unmet HRSNs among patients served, and not for comparison between IPFs.
    The specifications for the Screen Positive Rate for Social Drivers 
of Health measure, which were available during the review of the MUC 
List, are available at: https://mmshub.cms.gov/sites/default/files/map-hospital-measure-specifications-manual-2022.pdf.
(1) Measure Calculation
(a) Cohort
    The Screen Positive Rate for Social Drivers of Health measure is a 
process measure that provides information on the percent of patients, 
18 years or older on the date of admission for an IPF stay, who were 
screened for all five HRSNs,\176\ and who screen positive for one or 
more of the following five HRSNs: food insecurity; housing instability; 
transportation needs; utility difficulties; or interpersonal safety.
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    \176\ We have updated this language to read ``all five HRSNs'' 
as opposed to ``an HRSN'' to update the language on the 2022 MUC 
List: https://mmshub.cms.gov/sites/default/files/2022-MUC-List.xlsx.
---------------------------------------------------------------------------

(b) Numerator
    The numerator consists of the number of patients admitted for an 
IPF stay who are 18 years or older on the date of admission, who were 
screened for an HRSN, and who screen positive for having an unmet need 
in one or more of the following five HRSNs (calculated separately): The 
number of patients who screened positive for food insecurity, the 
number of patients who screened positive for housing instability, the 
number of patients who screened positive for transportation needs, the

[[Page 51119]]

number of patients who screened positive for utility difficulties, and 
the number of patients who screened positive for interpersonal safety. 
IPFs will report the number of patients who screened positive for 
having unmet needs in each of the five HRSNs as a separate numerator. A 
patient who screened positive for more than one unmet HRSN will be 
included in the numerator for each of those HRSNs. For example, a 
patient who screened positive for food insecurity, housing instability, 
and transportation needs would be included in each of these numerators.
(c) Denominator
    The denominator consists of the number of patients admitted for an 
IPF stay who are 18 years or older on the date of admission and are 
screened for all five HRSNs (food insecurity, housing instability, 
transportation needs, utility difficulties and interpersonal safety) 
\177\ during their IPF stay. The following patients are 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.
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    \177\ We have updated this language to read ``all five HRSNs'' 
as opposed to ``an HRSN'' to update the language on the 2022 MUC 
List: https://mmshub.cms.gov/sites/default/files/2022-MUC-List.xlsx.
---------------------------------------------------------------------------

(d) Calculation
    The results of this measure are calculated as five separate rates. 
Each rate is derived from the number of patients admitted for an IPF 
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 (that 
is, the number of patients who screened positive for food insecurity, 
the number of patients who screened positive for housing instability, 
the number of patients who screened positive for transportation needs, 
the number of patients who screened positive for utility difficulties, 
and the number of patients who screened positive for interpersonal 
safety) divided by the number of patients 18 years or older on the date 
of admission screened for all five HRSNs. The measure is reported as 
five separate rates--one for each HRSN, each calculated with the same 
denominator.
(2) Review by the Measure Applications Partnership
    We included the Screen Positive Rate for Social Drivers of Health 
measure on the publicly available MUC List, a list of measures under 
consideration for use in various Medicare programs.\178\ The CBE-
convened MAP Health Equity Advisory Group reviewed the MUC List and the 
Screen Positive Rate for Social Drivers of Health measure (MUC 2022-
050) in detail on December 6 through 7, 2022.\179\ The MAP Health 
Equity Advisory Group expressed support for the collection of data 
related to social drivers of health, but raised concerns regarding 
public reporting of these data and potential repetition of asking 
patients the same questions across settings.\180\
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    \178\ Centers for Medicare & Medicaid Services. List of Measures 
Under Consideration for December 1, 2022. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
    \179\ Centers for Medicare & Medicaid Services. 2022-2023 MAP 
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
    \180\ Centers for Medicare & Medicaid Services. 2022-2023 MAP 
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
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    In addition, on December 8 through 9, 2022, the MAP Rural Health 
Advisory Group reviewed the 2022 MUC List, which was also reviewed by 
the MAP Hospital Workgroup on December 13 through 14, 2022.\181\ The 
MAP Rural Health Advisory Group noted potential reporting challenges 
including the potential masking of health disparities that are 
underrepresented in some areas and that sample size and populations 
served may be an issue but also expressed support that the measure 
seeks to advance the drivers of health and serves as a starting point 
to determine where screening is occurring. The MAP Hospital Workgroup 
recommended conditional support of the measure for rulemaking pending: 
(1) endorsement by the CBE to address reliability and validity 
concerns; (2) attentiveness to how results are shared and 
contextualized for public reporting; and (3) examination of any 
differences in reported rates by reporting process (that is, to assess 
whether reported rates are the same or different across IPFs and other 
facilities that may use different processes to report their data).\182\ 
Thereafter, the MAP Coordinating Committee deliberated on January 24 
through 25, 2023, and ultimately voted to conditionally support the 
Screen Positive Rate for Social Drivers of Health measure for 
rulemaking with the same conditions.\183\
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    \181\ Centers for Medicare & Medicaid Services. 2022-2023 MAP 
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
    \182\ Centers for Medicare & Medicaid Services. 2022-2023 MAP 
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
    \183\ Centers for Medicare & Medicaid Services. 2022-2023 MAP 
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
---------------------------------------------------------------------------

    We agree with the MAP Coordinating Committee's support for the 
proposed Screen Positive Rate for Social Drivers of Health measure. We 
believe this measure, alongside the Screening for Social Drivers of 
Health measure, establishes an important foundation to prioritizing the 
achievement of health equity among IPFs participating in the IPFQR 
Program. Our approach to developing health equity measures is 
incremental, and we believe that health equity outcomes in the IPFQR 
Program will inform future efforts to advance and achieve health equity 
by IPFs. We believe this measure to be a building block that lays the 
groundwork for a future meaningful suite of measures that would assess 
IPF progress in providing high-quality healthcare for all patients, 
regardless of social risk factors or demographic characteristics.
(3) CBE Endorsement
    We have not submitted this measure for CBE endorsement at this 
time. Although section 1886(s)(4)(D)(i) of the Act generally requires 
that measures specified by the Secretary must be endorsed by the entity 
with a contract under section 1890(a) of the Act, section 
1886(s)(4)(D)(ii) of the Act states 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 a measure that has been endorsed or adopted by a consensus 
organization identified by the Secretary. We reviewed measures endorsed 
by consensus organizations and were unable to identify any other 
measures on this topic endorsed by a consensus organization; therefore, 
we believe the exception in section 1886(s)(4)(D)(ii) of the Act 
applies.
c. Data Collection, Submission, and Reporting
    We believe incremental implementation of the Screen Positive Rate 
for Social Drivers of Health measure, by permitting one year of 
voluntary reporting prior to mandatory reporting, will allow IPFs who 
are not

[[Page 51120]]

yet screening patients for HRSNs to get experience with the measure and 
equally allow IPFs who already undertake screening efforts to report 
data already being collected. Therefore, we proposed voluntary 
reporting of this measure, along with the Screening for Social Drivers 
of Health measure described in section VI.D.3 of this final rule, 
beginning with the data collected in CY 2024, which will be reported to 
CMS in CY 2025 followed by mandatory reporting beginning with data 
collected in CY 2025, which will be reported to CMS in CY 2026 and 
affect FY 2027 payment determination.
    While this measure will require IPFs to collect patient-level data 
on their patients' social drivers of health screening results, we 
proposed to adopt this measure as an aggregate measure (that is, IPFs 
would be required to submit only numerator results for each of the five 
screening areas and the number of patients screened for all five of the 
HRSNs). IPFs are required to submit information for aggregate chart-
abstracted measures once annually using a CMS-approved web-based data 
collection tool available within the HQR System (previously referred to 
as the QualityNet Secure Portal). We refer readers to section VI.I 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.
    We invited public comment on our proposal.
    We note that we have addressed comments that broadly referred to 
both the Screening for Social Drivers of Health measure and the Screen 
Positive Rate for Social Drivers of Health measure in the previous 
section of this final rule (VI.D.3.).
    Comment: Many commenters supported adoption of the Screen Positive 
Rate for Social Drivers of Health measure. Some commenters stated that 
knowing which patients have each of these HRSNs will help IPFs better 
understand patients' needs, improve care coordination with outpatient 
and community resources, increase the dignity and respect with which 
patients are treated, and support development of patient-centered 
treatment plans.
    Response: We thank commenters for their support of the Screen 
Positive Rate for Social Drivers of Health measure. We agree that HRSNs 
are critical factors that impact patient outcomes, and increased 
knowledge about patients' HRSNs will help IPFs shape goals associated 
with health equity. Further, we agree that collecting these data will 
help IPFs improve coordination with outpatient and community resources 
to better deliver patient-centered care.
    Comment: One commenter stated that access to these data will be 
useful for patient advocates to be able to identify IPFs that are more 
experienced with treating patients with more intensive resource needs.
    Response: We agree with the commenter that publicly reporting these 
data might help patients with more intensive resource needs select IPFs 
that are more familiar with treating patients with that level of need. 
We note, however, that the measure is intended to provide information 
to IPFs on the level of unmet need among their patients and potentially 
in the community, and not for comparison between IPFs (88 FR 21286).
    Comment: Some commenters expressed concern that publicly reporting 
these data may lead to inaccurate perceptions of the quality of care at 
IPFs that treat high volumes of patients who screen positive for one or 
more HRSNs. Several of these commenters stated that IPF patients may 
also have more unmet HRSNs than those at acute care hospitals so the 
data may be further misleading if the two settings are compared.
    Response: We appreciate the commenters' concerns. The measure is 
intended to provide information to IPFs on the level of unmet need 
among their patients and potentially in the community, and not for 
comparison between IPFs (88 FR 21286). 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 and patient advocates. 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.
    Comment: One commenter expressed the belief that reporting five 
separate rates, individually reflecting the proportion of patients who 
screened positive for each of the five HRSNs, is a flawed methodology 
because it may not yield reliable and valid comparisons. Another 
commenter expressly supported reporting five separate rates for this 
measure to improve transparency.
    Response: We believe that reporting a separate screen positive rate 
for each of the five HRSNs will provide important information to IPFs, 
the communities that they serve, and policy makers. Because different 
community-based resources are appropriate to address each of the five 
HRSNs, we believe that reporting each of these rates separately will 
provide reliable and valid information to identify which communities 
are most in need of which resources to better enable support in 
addressing the most prevalent HRSNs.
    Comment: Several commenters recommended that we develop outcome 
measures related to each of the five HRSNs for future adoption in this 
and other quality reporting programs.
    Response: We thank commenters for their feedback. We view the two 
Social Drivers of Health measures as a first step towards development 
of a long-term strategy to integrate social drivers of health data into 
IPF quality performance measurement as part of our broader commitment 
to health equity. We will continue to take all comments, concerns, and 
suggestions into account and will consider them as part of any 
potential new measure development in future notice-and-comment 
rulemaking.
    Comment: One commenter requested clarification on how to define a 
positive screening on a tool with a reporting scale.
    Response: Because the reported value of screening results could 
vary among different screening tools or instruments, we recommend that 
IPFs carefully review the supporting materials that accompany each tool 
to understand how to properly administer the instrument and interpret 
results when selecting a screening instrument for their patient 
population.
    Comment: One commenter did not support adoption of the Screen 
Positive Rate for Social Drivers of Health measure because the 
commenter expressed their belief that only IPFs would be able to use 
the data regarding their patient population and that they will already 
have the data from performing the screening.
    Response: We respectfully disagree and believe that there are 
multiple interested parties who will be able to use data regarding 
IPFs' patient populations, including patients and their caregivers, 
patient advocacy organizations, local community services organizations, 
and federal, state, and local policy makers. We also believe that the 
measure will facilitate systematic gathering of such data in a manner 
that provides information to IPFs on the level of unmet need among 
their patients that many IPFs do not compile currently.
    Final Decision: After consideration of the public comments we 
received, we

[[Page 51121]]

are finalizing adoption of the Screen Positive Rate for Social Drivers 
of Health measure as proposed.
5. Adoption of the Psychiatric Inpatient Experience (PIX) Survey 
Beginning With Voluntary Reporting of CY 2025 Data Followed by 
Mandatory Reporting Beginning With CY 2026 Data/FY 2028 Payment 
Determination
a. Background
    We believe that a comprehensive approach to quality must include 
directly reported feedback regarding facility, provider, and payer 
performance. Therefore, we have consistently stated our commitment to 
identifying an appropriate patient experience of care measure for the 
IPF setting and adopting this measure in the IPFQR Program at the first 
opportunity (77 FR 53646, 78 FR 50897, 79 FR 45964 through 45965, 80 FR 
46714 through 46715, 82 FR 38470 through 38471, 83 FR 38596, 84 FR 
38467, 85 FR 47043, 86 FR 42654 through 42656, and 87 FR 46846).
    In the FY 2014 IPPS/LTCH PPS final rule, we adopted a voluntary 
information collection regarding whether IPFs participating in the 
IPFQR Program assess patient experience of inpatient behavioral health 
services using a standardized instrument and for IPFs that answer 
``Yes'' to indicate the name of the survey that they administer (78 FR 
50896 through 50897). In the FY 2015 IPF PPS final rule, we adopted 
this information collection as the Assessment of Patient Experience of 
Care measure beginning with the FY 2016 payment determination (79 FR 
45964 through 45965). Data collected for the FY 2018 payment 
determination (that is, data collected in CY 2016) showed that while 
the majority of IPFs (approximately 76 percent) were collecting patient 
experience of care data through a standardized instrument, there was a 
wide variation in the instrument being used. The data for CY 2016 
indicated that the most widely used survey instrument was not in the 
public domain and was used by less than 30 percent of the IPFs that 
used a patient experience survey. In the FY 2015 IPF PPS final rule, we 
indicated our intention to adopt a standardized measure of patient 
experience of care for the IPFQR Program (79 FR 45964 through 45965).
    In the FY 2019 IPF PPS final rule, we removed the Assessment of 
Patient Experience of Care measure from the IPFQR Program, because we 
believed that we had collected sufficient information to inform 
development of a patient experience of care measure (83 FR 38596 
through 38597). In the FY 2020 IPF PPS final rule, we summarized our 
analysis of the results of the Assessment of Patient Experience of Care 
measure and requested feedback on potential adoption of the Hospital 
Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey 
for the IPFQR Program (84 FR 38467). In response to our request, many 
commenters expressed concern that the HCAHPS survey was not specified 
for the IPF setting and recommended that CMS identify a survey that has 
been developed for and tested in the IPF setting. Furthermore, in the 
FY 2021 IPF PPS proposed rule, we did not propose any updates to the 
IPFQR Program; however, we received many comments requesting that we 
adopt a patient experience of care measure in the IPFQR Program, which 
we summarized in the FY 2021 IPF PPS final rule (85 FR 47043). We 
received similar input strongly advocating for a patient experience of 
care measure for the IPFQR Program in response to a solicitation of 
comments on potential measures for the IPFQR Program in the FY 2022 IPF 
PPS proposed rule (86 FR 19511 through 19512), which we summarized in 
the FY 2022 IPF PPS final rule (86 FR 42654 through 42656). Many of 
these comments were from patients and their families and described how 
meaningful such a measure would be for individuals who receive services 
from IPFs. Though we did not solicit input on a patient experience of 
care measure in the FY 2023 IPF PPS proposed rule, we received many 
comments strongly recommending that we adopt such a measure, which we 
summarized in the FY 2023 IPF PPS final rule (87 FR 46846). Since 
publication of the FY 2023 IPF PPS final rule, section 4125(c) of the 
Consolidated Appropriations Act, 2023 (Pub. L. 117-328) was enacted, 
which amends section 1886(s)(4) of the Act to require that the quality 
measures specified for the IPFQR Program must include a quality measure 
of patients' perspective on care not later than the FY 2031 payment 
determination.
    We have continued to review publicly available patient experience 
of care instruments to identify such an instrument specified for, and 
tested in, the IPF setting. In our review, we identified the 
Psychiatric Inpatient Experience (PIX) survey as a publicly available 
survey instrument developed for and tested in the IPF setting. Pursuant 
to the Meaningful Measures 2.0 Framework, this measure addresses the 
``Person-Centered'' priority area, as well as the ``Individual and 
Caregiver Voice'' foundation and aligns with our commitment to 
prioritize outcome and patient-reported measures.\184\ This measure 
also aligns with the CMS National Quality Strategy Goal 4 ``Foster 
Engagement.'' It also supports the Behavioral Health Strategy goal of 
``Strengthen Equity and Quality in Behavioral Health Care.'' \185\ 
Furthermore, this measure supports the new Universal Foundation domain 
of ``Person-Centered Care.'' \186\
---------------------------------------------------------------------------

    \184\ 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.
    \185\ CMS. (2022). CMS Behavioral Health Strategy. Available at 
https://www.cms.gov/cms-behavioral-health-strategy. Accessed on 
February 20, 2023.
    \186\ https://www.nejm.org/doi/full/10.1056/NEJMp2215539.
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b. Overview of Measure
    The PIX survey was developed by a team at the Yale University, Yale 
New Haven Psychiatric Hospital to address the gap in available 
experience of care surveys, specifically the lack of publicly 
available, minimally burdensome, psychometrically validated surveys 
specified for the IPF setting.\187\ The interdisciplinary team that 
developed this survey, including researchers and clinicians, conducted 
the following steps in developing the survey: (1) literature review; 
(2) patient focus groups; (3) solicitation of input from a patient and 
family advisory council; (4) review of content validity with an expert 
panel; (5) development of survey; and (6) survey testing within the 
Yale New Haven Psychiatric Hospital system.\188\
---------------------------------------------------------------------------

    \187\ Klemanski DH, Barnes T, Bautista C, Tancreti C, Klink B, 
Dix E. Development and Validation of the Psychiatric Inpatient 
Experience (PIX) Survey: A Novel Measure of Patient Experience 
Quality Improvement. Journal of Patient Experience. 2022;9. 
doi:10.1177/23743735221105671
    \188\ Klemanski DH, Barnes T, Bautista C, Tancreti C, Klink B, 
Dix E. Development and Validation of the Psychiatric Inpatient 
Experience (PIX) Survey: A Novel Measure of Patient Experience 
Quality Improvement. Journal of Patient Experience. 2022;9. 
doi:10.1177/23743735221105671.
---------------------------------------------------------------------------

    The resulting survey contains 23 items in four domains. Patients 
can respond to each of the 23 items using a five-point Likert scale 
(that is, strongly disagree, somewhat disagree, neutral, somewhat 
agree, strongly agree) or choose that the item does not apply. The four 
domains are:
     Relationship with Treatment Team;
     Nursing Presence;
     Treatment Effectiveness; and
     Healing Environment.\189\
---------------------------------------------------------------------------

    \189\ Klemanski DH, Barnes T, Bautista C, Tancreti C, Klink B, 
Dix E. Development and Validation of the Psychiatric Inpatient 
Experience (PIX) Survey: A Novel Measure of Patient Experience 
Quality Improvement. Journal of Patient Experience. 2022;9. 
doi:10.1177/23743735221105671.

---------------------------------------------------------------------------

[[Page 51122]]

    The PIX survey is distributed to patients by administrative staff 
at a time beginning 24 hours prior to planned discharge. The survey, 
which is available in both English and Spanish and in accessible 
formats can be completed prior to discharge using either a paper copy 
of the survey or an electronic version of the survey via tablet 
computer.\190\ For a complete list of survey questions, including which 
questions are elements of each domain, we refer readers to the 
description of the survey in the Journal of Patient Experience: .
---------------------------------------------------------------------------

    \190\ Klemanski DH, Barnes T, Bautista C, Tancreti C, Klink B, 
Dix E. Development and Validation of the Psychiatric Inpatient 
Experience (PIX) Survey: A Novel Measure of Patient Experience 
Quality Improvement. Journal of Patient Experience. 2022;9. 
doi:10.1177/23743735221105671.
---------------------------------------------------------------------------

(1) Measure Calculation
(a) Cohort
    The cohort for this measure is all patients discharged from an IPF 
during the reporting period who do not meet one of the following 
exclusions: (1) patients who are under 13 years of age at time of 
discharge, and (2) patients who are unable to complete the survey due 
to cognitive or intellectual limitations. The sampling procedures that 
IPFs can apply to the PIX survey measure are described in section 
VI.I.6 of this final rule.
(b) Calculation
    The measure will be reported as five separate rates, one for each 
of the four domains of the PIX survey and one overall rate. Each of 
these rates will be calculated from patient responses on the PIX survey 
and then publicly reported on the Care Compare website (or successor 
CMS website). We will report the mean rates for each domain as well as 
the overall mean rate on the Care Compare website (or successor CMS 
website). To calculate the mean scores, we will assign a numerical 
value ranging from 1 (Strongly Disagree) to 5 (Strongly Agree). We will 
then calculate the average response by adding the values of all 
responses and dividing that value by the number of responses, excluding 
questions that were omitted or to which the patient selected ``Does Not 
Apply.''
(2) Review by the Measure Applications Partnership (MAP)
    We included the PIX survey measure on the publicly available ``List 
of Measures Under Consideration for December 1, 2022'' (MUC List), a 
list of measures under consideration for use in various Medicare 
programs.\191\ The CBE-convened Measure Applications Partnership (MAP) 
reviewed the MUC List and discussed the potential use of the PIX survey 
for the IPFQR Program.
---------------------------------------------------------------------------

    \191\ Centers for Medicare & Medicaid Services. List of Measures 
Under Consideration for December 1, 2022. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
---------------------------------------------------------------------------

    The MAP Health Equity Advisory Group agreed that well-constructed 
patient experience of care measures are an important indicator of 
quality care. Overall, the MAP Health Equity Advisory Group expressed 
that this measure is a ``step in the right direction for behavioral 
health.'' \192\
---------------------------------------------------------------------------

    \192\ Centers for Medicare & Medicaid Services. 2022-2023 MAP 
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
---------------------------------------------------------------------------

    In addition, on December 8 through 9, 2022, the MAP Rural Health 
Workgroup reviewed the 2022 MUC List and expressed support for this 
measure, with patient support being especially strong. Some members of 
the MAP Rural Health Advisory Group were concerned about operational 
challenges, specifically costs related to implementation and 
maintenance and potential bias if the surveying occurs prior to 
discharge.\193\
---------------------------------------------------------------------------

    \193\ Centers for Medicare & Medicaid Services. 2022-2023 MAP 
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
---------------------------------------------------------------------------

    The MAP Hospital workgroup reviewed the 2022 MUC List on December 
13 through 14, 2022. The MAP Hospital workgroup conditionally supported 
the measure for rulemaking, while emphasizing the importance of 
including patient reported experience of care data in the IPFQR 
Program. The MAP Hospital workgroup's conditions for support included 
endorsement by the CBE and additional testing data for this measure, 
specifically: (1) data from testing of the measure in a variety of 
settings (including urban, rural, safety net providers, and others), 
(2) data regarding survey results depending on the timing of survey 
administration (pre- versus post-discharge), (3) data regarding patient 
factors (for example, voluntary versus involuntary admissions), and (4) 
data regarding of mode of administration (for example, email versus 
mail) that may affect performance.\194\ Thereafter, the MAP 
Coordinating Committee deliberated on January 24 through 25, 2023 and 
ultimately voted to uphold the Hospital Workgroup's recommendation to 
conditionally support the PIX survey measure for rulemaking pending the 
same conditions as the MAP Hospital workgroup.\195\
---------------------------------------------------------------------------

    \194\ Centers for Medicare & Medicaid Services. 2022-2023 MAP 
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
    \195\ Centers for Medicare & Medicaid Services. 2022-2023 MAP 
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
---------------------------------------------------------------------------

    We believe that the testing that has been conducted on the PIX 
survey demonstrates that it is a valid and reliable tool for measuring 
patient experience of care in IPFs, and that the results from this 
initial testing are generalizable across IPFs. However, we agree with 
the MAP Hospital workgroup that additional testing of this measure 
could help better understand measure results, including any differences 
in measure results that were not analyzed during the PIX survey's 
initial testing. Therefore, the measure developer intends to conduct 
additional testing of the PIX survey prior to public reporting of the 
measure data, and we proposed a voluntary reporting period before 
beginning mandatory reporting of the PIX survey.\196\
---------------------------------------------------------------------------

    \196\ We note that in the FY 2024 IPF PPS proposed rule we 
inadvertently stated in section V.5.b.(2) ``Review by the MAP'' of 
the proposal that we were providing a two-year voluntary reporting 
period (88 FR 21289), which was inconsistent with our proposal to 
provide a one-year voluntary reporting period (88 FR 21290). As 
noted throughout the proposed rule, we proposed that voluntary 
reporting would begin with CY 2025 data and mandatory reporting 
would begin with CY 2026 data. We have corrected the above error 
here.
---------------------------------------------------------------------------

(3) CBE Endorsement
    The measure developer has not submitted this measure for CBE 
endorsement at this time. The developer does intend to submit this 
measure for endorsement in the future, following additional testing as 
recommended by the MAP Hospital workgroup. Although section 
1886(s)(4)(D)(i) of the Act generally requires that measures specified 
by the Secretary must be endorsed by the entity with a contract under 
section 1890(a) of the Act, section 1886(s)(4)(D)(ii) of the Act states 
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 a measure that has 
been endorsed or adopted by a consensus organization identified by the 
Secretary.
    We reviewed measures endorsed by consensus organizations and were

[[Page 51123]]

unable to identify any other measures on this topic endorsed by a 
consensus organization. We did identify the Experience of Care and 
Health Outcomes (ECHO) Survey measure (CBE #008); however, this measure 
has had its endorsement removed as of the spring 2020 cycle. 
Additionally, the ECHO Survey was developed and tested for outpatient 
behavioral health, not the inpatient setting. Additionally, we 
identified the Patient Experience of Psychiatric Care as Measured by 
the Inpatient Consumer Survey (ICS) measure (CBE #0726). This measure 
has also had its endorsement removed as of the spring 2018 cycle. As 
neither of these two measures is endorsed at this time, we believe the 
exception in section 1886(s)(4)(D)(ii) of the Act applies.
c Data Collection, Submission and Reporting
    IPFs will be responsible for administering the survey and 
collecting data on survey responses, because the PIX survey is 
administered beginning 24 hours prior to a patient's planned discharge. 
Therefore, IPFs will collect the data in a manner similar to the 
collection of data for chart-abstracted measures or other patient 
screening measures. That is, the IPFs will collect data in the facility 
and then report these data to CMS using the methods described in 
section VI.I.4 of this final rule, ``Data Submission Requirements,'' 
under ``Procedural Requirements.''
    Because we anticipate that many IPFs, which already administer 
different patient experience of care survey instruments to their 
patients, will need to transition to the PIX survey, we proposed a 
voluntary reporting period beginning with data from CY 2025, which will 
be reported to CMS in CY 2026. We will then require IPFs to report data 
for the PIX survey measure beginning with data collected during CY 
2026, to be reported to CMS during CY 2027 and affecting the FY 2028 
payment determination.
    We invited comments on our proposal.
    Comment: Many commenters strongly supported the PIX survey measure. 
These commenters expressed that the measure addresses a long-standing 
measure gap in the IPFQR Program, which these commenters characterized 
as discriminatory, and specifically supported the PIX survey instrument 
because it was developed with input from people with lived experience 
in the IPF setting. Some of these commenters representing patients and 
their families provided descriptions of their own and their family 
members' lived experiences to explain how important such a survey 
opportunity would be to IPF patients. Some commenters stated that 
patients are especially vulnerable during inpatient treatment and that 
psychological distress can be exacerbated in this setting. These 
commenters expressed that collecting data regarding the patients' 
experiences of care can improve patient-centered, trauma-informed care 
in which patients are treated with dignity and respect. Other 
commenters stated that formal patient feedback motivates improved care. 
One commenter stated that collection and public reporting of these data 
would assist community-based providers in identifying IPFs to which to 
refer patients. Other commenters stated that surveying IPF patients 
regarding their experience of care is a form of treating them with 
dignity and respect, empowering them, and showing that their 
experiences are important. Several commenters stated that survey data 
can be tied to other data sets to support research. Another commenter 
expressed that IPFs will be able to compare themselves to other IPFs, 
which could motivate quality improvement.
    Response: We thank commenters for their support of the PIX survey 
measure. We agree that adoption of a patient experience of care measure 
for the IPF setting addresses a long-standing measure gap, encourages 
patient-centered care, and shows that we believe that the patient's 
experience is a critical element of providing quality care.
    Comment: Some commenters expressed concern regarding measuring 
patient experience of care prior to discharge. Some of these commenters 
expressed that patients may feel unsafe responding honestly at any 
point prior to discharge because of a fear of retaliation for 
unfavorable responses. These commenters recommended providing an option 
for patients to respond post-discharge (such as providing a paper copy 
of the survey with a sealable, addressed envelope to return the survey 
after completing it). Another commenter stated that the setting in 
which the survey is administered, and time provided to complete the 
survey, could lead to variation in results and recommended 
administering the survey post-discharge. Many commenters recommended 
allowing vendors to collect and report the data for IPFs. Other 
commenters were specifically concerned regarding the 24 hours prior to 
discharge time period for administering the survey. Some of these 
commenters stated that there are many clinical activities occurring 
during this phase of the patient's stay and that adding another step 
may be burdensome for staff and patients. Other commenters concerned 
about the 24 hour prior to discharge time period expressed that 
discharge timelines are often uncertain, and therefore it may be 
difficult to know when the 24 hours prior to discharge window has 
started, especially for patients with long stays.
    Response: We would like to clarify that, if it is not possible for 
a patient to complete the survey prior to discharge, the facility 
should provide a sealable, addressed envelope for the patient to return 
the survey following discharge. This situation could apply in 
situations in which the patient would prefer more time or privacy to 
complete the survey, in situations in which there are competing 
clinical priorities prior to discharge, or in situations in which there 
is uncertainty regarding the timing of a patient's discharge. However, 
we caution IPFs that relying exclusively on the mail-back option may 
prevent the IPF from meeting the measure's minimum sampling 
requirements. If the IPF is able to meet the minimum sampling 
requirements and chooses to use a vendor to receive paper surveys, 
aggregate and analyze data provided through the surveys, or to report 
these data to CMS on the IPF's behalf, that would be consistent with 
the measure methodology and specifications.
    Comment: Many commenters expressed support for surveying patients 
regarding their experience of care, but expressed that they already 
have tools or vendors in place and that transitioning to the PIX survey 
would be disruptive. Some commenters specifically stated that this 
transition would disrupt their historical trend data. One commenter 
expressed concern that patients complete too many experience surveys 
and recommended that CMS select one tool based on an evaluation of all 
current surveys. Some commenters expressed a preference for a CAHPS 
survey because these surveys are used in other care settings and are 
the core element of the CMS Foundational Measurement Strategy to 
address the person-centered care domain. Other commenters stated that 
patients with primary psychiatric diagnoses continue to be excluded 
from HCAHPS and that, even if this exclusion were removed, by adopting 
the PIX survey, data about patient experience in an IPF would not be 
comparable to data regarding patient experience in general acute care 
hospitals. Other commenters recommended that CMS allow IPFs to select 
their own patient experience instrument provided that it addresses

[[Page 51124]]

the domains addressed by the PIX survey.
    Response: We recognize that many IPFs already use patient 
experience of care survey instruments or vendors to administer and 
collect survey instruments on behalf of IPFs, and that there is a 
burden for these IPFs to transition to a new survey instrument and 
administration and collection process. We further recognize that 
historical quality improvement trend data and analytical processes may 
be impacted for these IPFs who already use other patient experience of 
care survey instruments. We considered allowing IPFs to select their 
own patient experience data collection instrument provided that it 
addresses the domains addressed by the PIX survey. However, we believe 
that using a single, standardized instrument to assess patient 
experience of care across both freestanding IPFs and those psychiatric 
units in acute care hospitals will provide comparability of experience 
data. We believe that publicly reporting patient experience of care 
data that allows for comparisons between IPFs will be most meaningful 
to patients and their caregivers, and will allow IPFs to compare their 
measure results to similar IPFs as part of their quality improvement 
initiative. We understand commenters' concern that by adopting a 
different patient experience of care measure in the IPF setting than 
that for general acute care hospitals (that is, the HCAHPS survey) 
measure results will not be comparable across these settings, even if 
HCAHPS is expanded to patients with primary psychiatric diagnoses in 
the general acute care setting. However, in response to our previous 
RFIs about incorporating a patient experience of care measure in the 
IPFQR Program, many commenters (representing patients, patient 
advocates, caregivers, IPFs, and provider associations) recommended 
that we adopt a patient experience of care measure that was developed 
specifically for patients receiving care in IPFs (84 FR 38467). These 
commenters stated that there are elements of care, such as group 
therapy, that are unique to the IPF setting and stated that a survey 
for this setting should specifically address these elements of care. 
Because it was developed specifically for this setting, with input from 
patients and their caregivers, the PIX survey does include questions 
regarding these unique elements of care, whereas the HCAHPS survey does 
not.
    With respect to concerns regarding loss of trend data, we have 
proposed to adopt the measure for mandatory reporting beginning with CY 
2026 data (which will be submitted to CMS in CY 2027 and affect FY 2028 
payment determination) to provide additional time for IPFs to 
transition to this new survey. We wish to clarify that IPFs will be 
permitted to add questions to the survey, so if there are specific 
metrics that an IPF wishes to continue tracking, they will be able to 
do so. We believe that IPFs will have sufficient time prior to when 
mandatory reporting of this measure begins with the FY 2028 payment 
determination to determine which questions will be most appropriate to 
add to the survey without overburdening patients, or how to compare 
results from patient responses to the PIX survey to those of their 
existing surveys.
    We believe that the commenter who referenced the CMS Foundational 
Measurement Strategy was referring to the CMS Universal 
Foundation,\197\ which includes setting specific versions of the 
Consumer Assessment of Healthcare Providers and Systems (CAHPS) survey. 
We considered potential adoption of a CAHPS measure for the IPFQR 
Program and solicited comment on this in the FY 2020 IPF PPS proposed 
rule (84 FR 16986 through 16987) and summarized the responses to this 
request in the FY 2020 IPF PPS final rule (84 FR 38467). Following our 
review of the HCAHPS survey and responses to that request for 
information, we determined that the PIX survey is more appropriate for 
the IPFQR Program since it has been developed and tested specifically 
for IPFs and with the input of individuals with lived experience with 
care in this setting. Therefore, while the HCAHPS survey is appropriate 
for the general acute care setting, we believe that the PIX survey is a 
more appropriate instrument for measuring patient experience of care in 
the IPF setting.
---------------------------------------------------------------------------

    \197\ https://www.cms.gov/aligning-quality-measures-across-cms-universal-foundation.
---------------------------------------------------------------------------

    Comment: Many commenters expressed concern that the PIX survey has 
not been sufficiently tested for national implementation. These 
commenters specifically noted a lack of testing in diverse geographic 
settings (including testing for differences in performance in urban 
versus rural settings), lack of testing which compares this survey to 
other inpatient consumer surveys, lack of information about the 
correlation coefficients for the proposed domains, lack of reliability 
coefficients to determine the survey's internal consistency, lack of 
demographic data regarding patients who respond versus those who do 
not, lack of testing among the forensically and/or involuntarily 
admitted populations, lack of longitudinal testing, and lack of testing 
with facilities which have an average length of stay greater than 10 
days. Some commenters recommended additional testing with volunteer 
IPFs prior to implementation as a mandatory measure. Some of these 
commenters recommended postponing mandatory adoption to ensure 
sufficient testing. One commenter expressed concern that the PIX survey 
does not clearly connect questions to key outcomes, and recommended 
further research and testing to identify these connections.
    Response: We understand commenters' concerns regarding the testing 
of the PIX survey measure. We recognize that this is a relatively new 
instrument. We note that the measure developer is continuing to test 
this instrument to further address these questions and concerns prior 
to the national implementation of the measure. To increase time for 
testing and to better identify information that will need to be 
provided during education and outreach sessions prior to public 
reporting, we proposed and are adopting mandatory reporting of this 
measure for the FY 2028 payment determination, which would not require 
IPFs to begin administering and collecting responses to the PIX survey 
until CY 2026.
    Comment: Some commenters expressed concern that this survey 
instrument is only available in a limited number of languages and 
recommended translation into additional languages to improve 
accessibility for all patients. Some of these commenters recommended 
adding supportive services to help those with language barriers or 
limited health literacy complete the survey.
    Response: The measure developer has translated the survey from 
English into Spanish, Mandarin, and Farsi. The measure developer is 
currently working to translate the survey into other frequently 
requested languages (including, French, Arabic, and Japanese). For 
patients who have language barriers, the measure developer is currently 
developing survey administration guidelines for best practices in 
survey administration to enhance the accessibility of the PIX survey. 
These include but are not limited to screen readers, the use of visual 
cueing (for example, using simple emojis that correspond with the 
Likert scale options), and the ability to request assistance in 
completing the survey. Options for phone surveys and the use of 
interpreters will also be included in these guidelines. Finally, the 
measure developer will add a question to the survey to indicate if the 
survey was

[[Page 51125]]

completed with assistance. We anticipate that the updated survey will 
be available during FY 2023 so that IPFs can review it during their 
implementation planning in advance of the performance period for 
voluntary reporting (that is CY 2025).
    Comment: Some commenters requested clarification regarding whether 
facilities could add their own elements to the survey to maintain 
historical trend data regarding questions that are important among 
their specific patient populations. Other commenters specifically 
requested the inclusion of a free-text comment section.
    Response: Individual facilities can add supplemental items to the 
survey instrument provided that they do not amend or remove the key 
elements of the PIX survey in order to collect data for and report on 
this measure. We note that IPFs may not factor supplemental items into 
existing scoring procedures as this would affect reliability and 
validity of this measure. Furthermore, we encourage facilities to 
consider the number of supplemental questions so as not to overburden 
or fatigue patients in completing the survey instrument.
    Comment: One commenter recommended allowing patients to complete 
surveys regularly throughout their stay.
    Response: Although we believe that this may be unduly burdensome to 
patients and create administrative and logistical burden for 
facilities, this is not inconsistent with reporting data on the PIX 
survey for this measure if the IPF only includes data for surveys 
administered according to the PIX survey measure's guidelines 
(specifically, PIX surveys administered beginning 24 hours prior to 
discharge) in the measure results reported to CMS.
    Comment: Several commenters recommended additional questions, 
topics, and domains that they believe would be important to include in 
a patient experience of care survey for the IPF setting. These topics 
included: (1) data on racial and ethnic disparities in diagnosing, 
treating, and providing care; (2) addressing patients' spiritual needs; 
(3) progress towards remediating life circumstances that precipitated 
the hospitalization; (4) perceptions of discharge planning and 
aftercare; (5) follow-up appointment availability (were they offered 
and scheduled); (6) staff cultural competency; (7) family involvement 
in treatment; (8) nurses' performance; (9) quantity of food; (10) 
overall rating; (11) wait time; and (12) family and caregiver 
perspectives.
    Response: We note that the PIX survey was developed by an 
interdisciplinary team with input from patients and a patient and 
family advisory council to address items that are important to patients 
in this setting of care. However, as discussed previously, individual 
facilities can add supplemental items to the survey to address issues 
important to their patient populations or that are significant in the 
historical trend data.
    Comment: One commenter stated that frequency measurement (which 
asks patients to recall how often something happened) versus evaluative 
measurement (which asks patients to identify how well their needs were 
met) can influence the magnitude of differences when evaluating patient 
experience by race and ethnicity. This commenter specifically noted 
that evaluative measures are typically better at identifying 
disparities than frequency-based measures and recommended considering 
this in developing a survey for this setting.
    Response: The PIX survey uses an evaluative measurement (which asks 
patients to evaluate their experience of their care) approach with a 
Likert Scale (that is, strongly disagree, somewhat disagree, neutral, 
somewhat agree, strongly agree, and does not apply) versus a frequency 
style of evaluation (which asks patients to report whether or how 
frequently something occurred).
    We agree with the commenter that one strength of the evaluative 
measurement approach is the ability to better identify disparities and 
detect inequities and note that this was a factor in the survey design 
of the PIX survey.\198\
---------------------------------------------------------------------------

    \198\ Linacre JM. Optimizing rating scale category 
effectiveness. J Appl Meas. 2002;3(1):85-106. PMID: 11997586.
---------------------------------------------------------------------------

    Comment: Many commenters recommended that the survey be 
administered by a peer or advocate to reduce concerns regarding 
retaliation.
    Response: We appreciate this recommendation and believe that peer 
advocates could assist with survey administration with minimal 
training. The measure developer is currently developing survey 
administration guidelines which will incorporate information on the 
appropriate training for staff (including peer advocates) who will be 
responsible for survey administration. We anticipate that these 
guidelines will be available during FY 2023 so that IPFs can review 
them during their implementation planning in advance of the performance 
period for voluntary reporting (that is, CY 2025).
    Comment: Several commenters had questions regarding public 
reporting of these data for this measure. One commenter requested 
clarification regarding whether the data would be publicly reported. 
Another commenter recommended that the data be accompanied by patient 
demographic and clinical information to allow for stratification and 
analysis.
    Response: As described in section VI.H of the FY 2024 IPF PPS 
proposed rule, we have an established policy for publicly displaying 
the data submitted by IPFs for the IPFQR Program (88 FR 21299 through 
21300). Consistent with that policy, we intend to publicly report these 
data. Specifically, in accordance with section 1886(s)(4)(E) of the 
Act, data that an IPF submits to CMS for the IPFQR Program will be made 
publicly available on a CMS website after providing the IPF an 
opportunity to review the data to be made public. In the FY 2013 IPPS/
LTCH PPS final rule (77 FR 53653 through 53654), we adopted procedures 
for making data submitted under the IPFQR Program available to the 
public, after an IPF has the opportunity to review such data prior to 
public display, as required by section 1886(s)(4)(E) of the Act. We 
adopted modifications to these procedural requirements in the FY 2014 
IPPS/LTCH PPS final rule (78 FR 50897 through 50898), and the FY 2017 
IPPS/LTCH PPS final rule (81 FR 57248 through 57249). Specifically, 
IPFs will have a period of 30 days to review and submit corrections to 
errors resulting from CMS calculations prior to the data being made 
public.
    We agree that the intersectionality of patient characteristics, 
including the categorization of clinical populations would provide 
useful information for researchers and potentially for patients and 
caregivers in selecting a facility at which to receive care. However, 
we note that the survey is anonymous and therefore cannot be linked to 
patients' clinical data. The measure developer specifically omitted 
clinical characterizations because of patients' concerns regarding 
discrimination, retaliation, and uncertainty about their suspected 
versus diagnosed conditions. We will consider the appropriateness and 
feasibility of including demographic data with publicly reported 
measure results for future public reporting.
    Comment: Several commenters requested clarification on how the data 
would be collected and reported. Some of these commenters stated that 
IPFs with limited technological resources would find it hard to 
implement this survey. Some of these commenters further stated that 
without sufficient technological resources this survey

[[Page 51126]]

would be burdensome for IPFs to administer.
    Response: IPFs will collect data in the facility and then report 
these data to CMS using the methods described in section VI.I.4 of this 
final rule, that is ``Data Submission Requirements'' under ``Procedural 
Requirements.'' This aligns with previously finalized policies for 
submitting data on chart-abstracted measures. We recognize that this 
may be burdensome for IPFs; however, given the importance of including 
a patient experience of care measure in the IPFQR Program, we believe 
that the benefit of adopting this measure outweighs this burden.
    Comment: One commenter requested clarification regarding whether 
IPFs would be required to respond to patients to resolve issues 
identified in the PIX survey prior to the patient's discharge. Another 
commenter expressed concern that patients may include a threat to self 
or others in their survey response which would require IPFs to review 
responses to ensure that such threats were addressed prior to 
discharge.
    Response: We wish to clarify that the PIX survey is an anonymous 
survey. Therefore, it would not be possible for IPFs to address input 
from individual patients, either prior to or after discharge. We note 
that there are no questions on the PIX survey, which is a series of 23 
items to which patients respond using a five-point Likert scale (that 
is, strongly disagree, somewhat disagree, neutral, somewhat agree, 
strongly agree) or choose that the item does not apply, that address a 
patient's potential threat to self or others. We acknowledge the 
possibility that, during IPF staff's administration of the survey, the 
patient may express to the staff member a potential threat to self or 
others. However, we believe the IPF will be able to train its staff to 
appropriately respond to and notify clinical and other staff of the 
patient's potential threat to self or others as with any other 
situation where IPF staff interact with IPF patients.
    Comment: One commenter requested clarification regarding whether 
completing the survey would be mandatory for patients. Another 
commenter expressed concern that behavioral health patients often 
refuse to complete surveys.
    Response: We agree that some patients may choose not to complete a 
survey. We note that, consistent with our proposal in the FY 2024 IPF 
PPS proposed rule (88 FR 21301), we are requiring IPFs to develop 
sampling plans that ensure that IPFs are able to submit data for 300 
completed PIX surveys per year. IPFs would be required to sample from 
every month throughout the entire reporting period and not stop 
sampling or curtail ongoing interview activities once a certain number 
of completed surveys has been attained. We recommend that in developing 
sampling plans, IPFs consider the predicted rate of non-completion to 
ensure that they reach 300 completed PIX surveys.
    Comment: Several commenters requested clarification regarding 
whether patients would be able to have assistance, such as from a 
family member, friend, or peer support specialist, to complete the 
survey if the patient is unable to complete the survey. One commenter 
requested clarification regarding whether a parent or guardian would be 
required to complete the survey for minors.
    Response: The PIX survey is suitable for individuals of all ages 
within the measure cohort, which includes patients who are 13 or older 
at time of discharge. The survey was tested with adolescents aged 13 
to17 and testing found that they were able to complete it without any 
significant differences in scores compared to adults. Nonetheless, we 
understand that some individuals may require assistance, and patients 
must be offered the option to seek help from staff, a caregiver 
(including parents or guardians), or a peer. Additionally, the measure 
developer is updating the survey to include a question asking if the 
patient received any assistance while completing it. We anticipate that 
the updated survey will be available during FY 2023 so that IPFs can 
review it during their implementation planning in advance of the 
performance period for voluntary reporting (that is CY 2025)
    Comment: Several commenters expressed concern that the exclusion of 
patients who are unable to complete the survey due to cognitive or 
intellectual limitations could lead to subjective exclusions and create 
bias in the survey administration. Several of these commenters 
recommended removing this exclusion, and other commenters recommended 
providing standardized definitions that IPFs could apply.
    Response: The measure developer is currently developing guidelines 
for best practices in survey administration to enhance the 
accessibility of the PIX survey and sampling integrity. All patients, 
including people with intellectual and development disabilities, must 
have an opportunity to participate in or benefit from the survey equal 
to that afforded to others. We anticipate that these guidelines will be 
available during FY 2023 so that IPFs can review them during their 
implementation planning in advance of the performance period for 
voluntary reporting (that is, CY 2025). We will communicate the 
availability of these guidelines through regular sub-regulatory 
communications.
    We note that patients who are unable to complete the survey unaided 
on the basis of a disability must be offered reasonable modifications, 
such as the use of visual cueing (for example, using simple emojis that 
correspond with the Likert scale options). We believe that inclusivity 
is a key priority of adopting a patient experience of care survey and 
emphasize the importance of maximizing accessibility for all patients.
    Comment: Several commenters expressed concern that the data 
collected by this survey may not be sufficient to improve patient 
experience. Another commenter requested clarification regarding whether 
the survey has been shown to improve patient outcomes. One commenter 
expressed concern about the Healing Environment domain in the PIX 
survey instrument because regulations and licensing requirements 
heavily restrict the environment of the IPF. One commenter expressed 
concern that IPFs do not have the resources to improve care based on 
the results of the PIX survey.
    Response: We believe that a comprehensive approach to quality must 
include directly reported feedback from patients. We have consistently 
stated our commitment to identifying a patient experience of care 
measure for the IPF setting, and in our measure strategies, including 
the Meaningful Measures 2.0 Framework, the CMS National Quality 
Strategy, the Behavioral Health Strategy, and the Universal Foundation, 
we have consistently identified the need for person-centered care and 
engagement. Furthermore, we note that a review of 55 studies found that 
within these studies it was more common to find positive associations 
between patient experience and patient safety and clinical 
effectiveness than no associations.\199\ However, including a measure 
of patient experience demonstrates that a positive patient experience 
is an important goal in its own right. This is supported by 
consistently strong patient and caregiver input requesting such a 
measure be adopted in the IPFQR Program and emphasizing that such a 
measure is an important element of showing that we

[[Page 51127]]

believe that IPF patients should be treated with dignity and respect in 
an environment in which their voices matter as part of a patient-
centered care experience. Additionally, we believe that having a 
nationally standardized patient experience of care measure will allow 
IPFs to compare their patient experience results with the results of 
other IPFs. This will allow IPFs to identify opportunities for 
improvement, including to their Healing Environment score, within the 
regulatory and licensure constraints under which IPFs operate. That is, 
if other similar IPFs score higher in the Healing Environment domain 
despite operating within the same regulatory and licensure constraints, 
this will highlight the opportunity for the IPF to improve its Healing 
Environment.
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    \199\ Doyle, c. Lennox, L, and Bell, D. A systematic review of 
evidence on the links between patient experience and clinical safety 
and effectiveness. BMJ Open. Available at: https://bmjopen.bmj.com/content/3/1/e001570.
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    Comment: One commenter expressed concern that the domain names do 
not appear to match the substance of the questions within the domain. 
This commenter expressed concern that there may be overlap or 
inconsistencies between the use of ``treatment team'' and ``nursing 
team.''
    Response: We appreciate this concern; however, we believe the 
domain labels have been appropriately applied. Specifically, the four-
domain survey aligned with the theoretical basis of patient experience 
and was chosen through extensive focus group testing. Further, 
decisions around domains and their labels were based on the degree to 
which individual items statistically coalesced around central themes. 
We noted that patients in focus groups rarely distinguished roles among 
their care teams. Functionally, medical providers and social workers 
operate in a collaborative framework to guide treatment and coordinate 
aftercare. Thus, questions about patients' relationships with their 
treatment team center around their interactions with those who provide 
medical and therapeutic care. The Nursing Presence domain was 
identified as a separate domain due to the distinctive nature of 
nurses' roles in comprehensively caring for all patients on the unit in 
support of the treatment team. We agree with the measure developer that 
this important distinction merited a separate domain to represent the 
unique work of the varying team members with whom patients interact.
    Comment: Some commenters expressed concerns that this measure has 
not been endorsed by the CBE.
    Response: We note that following additional testing, the measure 
developer intends to submit this measure to the CBE for endorsement. 
While we recognize the value of measures undergoing CBE endorsement 
review, given the urgency of adopting a patient experience of care 
measure for this setting, as there are currently no CBE-endorsed 
measures that address IPF patient experience of care, we believe it is 
important to implement this measure beginning with voluntary reporting 
of CY 2025 data followed by mandatory reporting beginning with CY 2026 
data, reported to CMS in CY 2027 and affecting the FY 2028 payment 
determination. We note that under section 1886(s)(4)(D)(ii) 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 measures endorsed by consensus organizations and were unable 
to identify any other measures on this topic endorsed by a consensus 
organization, and therefore, we believe the exception in section 
1886(s)(4)(D)(ii) of the Act applies.
    Comment: One commenter requested clarification on who developed the 
survey, whether it is proprietary, and if so, how IPFs will obtain 
licenses to use the survey.
    Response: As described in the FY 2024 IPF PPS proposed rule (88 FR 
21288), the PIX survey was developed by a team at the Yale University, 
Yale New Haven Psychiatric Hospital and is in the public domain. We 
note that the measure developer is currently developing guidelines for 
best practices in survey administration, and we strongly encourage 
staff who will be responsible for administering the survey to review 
these guidelines as soon as they become available. Because the measure 
developer has made the PIX survey available in the public domain, there 
is no certification or license required to administer the PIX survey.
    Comment: One commenter expressed concern that there are too many 
questions for patients to complete.
    Response: We understand the importance of balancing the number of 
survey questions to improve completion rates with minimal burden to the 
patient, while including a sufficient range of questions to address the 
most important aspects of patients' experiences about the care they 
received. We note that the PIX survey has 23 items, which is comparable 
to the number of questions in other patient experience of care survey 
instruments. Specifically, two other surveys which address inpatient 
care include the HCAHPS survey, which has 29 questions, and the 
Inpatient Consumer Survey (ICS), which has 28 items.
    Comment: One commenter opposed adopting this survey in a pay-for-
performance program.
    Response: We note that the IPFQR Program is a pay-for-reporting 
program (that is, IPFs that comply with all requirements and submit 
required data under the IPFQR Program receive their full payment 
update) and that there are not currently any Medicare pay-for-
performance programs (that is, programs which adjust payment based on 
the performance on measures) which address the IPF setting.
    Comment: Some commenters requested clarification regarding whether 
the measure would be scored with ``top-box'' scoring or with mean 
scores, because the MUC List and the proposed rule described different 
methods.
    Response: We considered ``top-box'' scoring and mean scores as we 
identified an approach to adopting and publicly reporting the PIX 
survey measure in the IPFQR Program. Specifically, we considered 
modeling the ``top-box'' scoring used for reporting performance on the 
HCAHPS measure in which data are reported based on the percent of 
respondents who selected the most positive response (that is, the 
``top-box''). However, we believe that mean scores (that is, the 
numerical average calculated by assigning each response a numerical 
value from 1--the least positive, to 5 the most positive, summing the 
scores, and dividing that value by the number of responses) provide 
information that is more meaningful to patients and their caregivers 
who are more likely to be familiar with mean scores as opposed to 
``top-box'' scores. Therefore, we decided to propose mean scores, which 
we described in the FY 2024 IPF PPS proposed rule (88 FR 21289). We 
note that the MUC list submission acknowledged the possibility that 
mean scores would be useful for reporting with the statement that ``it 
may be useful for the distribution of total Likert-scale responses to 
be made available during initial implementation.''
    Comment: One commenter expressed support for reporting separate 
rates for each domain in addition to the overall rate. This commenter 
stated that this level of data will improve patient choice and support 
IPFs' quality improvement efforts.
    Response: We thank this commenter for the support and agree that 
the increased level of detail will improve patient choice and support 
IPF's quality improvement efforts.
    Comment: Several commenters requested clarification regarding

[[Page 51128]]

whether there will be a one-year or two-year voluntary reporting 
period.
    Response: We wish to clarify that, consistent with our proposal in 
the FY 2024 IPF PPS proposed rule (88 FR 21290), there will be a 1-year 
voluntary reporting period. IPFs that wish to participate in the 
voluntary reporting period will be able to report CY 2025 data to CMS 
in CY 2026. Beginning with CY 2026 data, which will be reported to CMS 
in CY 2027, all IPFs will be required to report these data to CMS and 
failure to do so would affect their payment determination for FY 2028.
    Comment: Several commenters expressed support for adoption of this 
measure for voluntary reporting of CY 2025 data in CY 2026 followed by 
mandatory reporting beginning with CY 2026 data affecting the FY 2028 
payment determination to ensure there is a patient experience measure 
in the IPFQR Program as soon as technically feasible.
    Response: We thank these commenters for their support.
    Final Decision: After consideration of the public comments we 
received, we are finalizing adoption of the PIX survey measure as 
proposed.

E. Modification of the COVID-19 Vaccination Coverage Among Healthcare 
Personnel (HCP) Measure Beginning With the Quarter 4 CY 2023 Reporting 
Period/FY 2025 Payment Determination

1. Background
    On January 31, 2020, the Secretary of the Department of Health and 
Human Services declared a public health emergency (PHE) for the United 
States in response to the global outbreak of SARS-COV-2, a novel (new) 
coronavirus that causes a disease named ``coronavirus disease 2019'' 
(COVID-19).\200\ Subsequently, multiple quality reporting programs 
including the Hospital IQR Program (86 FR 45374) and the IPFQR Program 
(86 FR 42633 through 42640) adopted the COVID-19 Vaccination Coverage 
Among Healthcare Personnel (HCP) measure. The COVID-19 Vaccination 
Coverage Among Healthcare Personnel (HCP) measure adopted in the IPFQR 
Program in the FY 2022 IPF PPS final rule (86 FR 42633 through 42650) 
requires each IPF to calculate the percentage of HCP eligible to work 
in the IPF for at least one day during the reporting period, excluding 
persons with contraindications to the COVID-19 vaccine, who have 
received a complete vaccination course against SARS-CoV-2 (86 FR 42633 
through 42640).
---------------------------------------------------------------------------

    \200\ U.S. Dept of Health and Human Services, Office of the 
Assistant Secretary for Preparedness and Response. (2020). 
Determination that a Public Health Emergency Exists. Available at: 
https://www.phe.gov/emergency/news/healthactions/phe/Pages/2019-nCoV.aspx.
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    COVID-19 has continued to spread domestically and around the world 
with more than 103.9 million cases and 1.13 million deaths in the 
United States as of June 19,2023.\201\ In recognition of the ongoing 
significance and complexity of COVID-19, the Secretary renewed the PHE 
on April 21, 2020, July 23, 2020, October 2, 2020, January 7, 2021, 
April 15, 2021, July 19, 2021, October 15, 2021, January 14, 2022, 
April 12, 2022, July 15, 2022, October 13, 2022, January 11, 2023, and 
February 9, 2023.\202\ While the PHE status ended on May 11, 2023,\203\ 
HHS has stated that the public health response to COVID-19 remains a 
public health priority with a whole of government approach to 
combatting the virus, including through vaccination efforts.\204\
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    \201\ Centers for Disease Control and Prevention. COVID Data 
Tracker. Accessed February 13, 2023. Available at: https://covid.cdc.gov/covid-data-tracker/#datatracker-home.
    \202\ U.S. Dept. of Health and Human Services. Office of the 
Assistant Secretary for Preparedness and Response. (2023). Renewal 
of Determination that a Public Health Emergency Exists. Available 
at: https://aspr.hhs.gov/legal/PHE/Pages/covid19-11Jan23.aspx.
    \203\ https://www.whitehouse.gov/wp-content/uploads/2023/01/SAP-H.R.-382-H.J.-Res.-7.pdf.
    \204\ U.S. Dept. of Health and Human Services. Fact Sheet: 
COVID-19 Public Health Emergency Transition Roadmap. February 9, 
2023. Available at: https://www.hhs.gov/about/news/2023/02/09/fact-sheet-covid-19-public-health-emergency-transition-roadmap.html.
---------------------------------------------------------------------------

    In the FY 2022 IPF PPS final rule (86 FR 42633 through 42635) and 
in our Revised Guidance for Staff Vaccination Requirements,\205\ we 
stated that vaccination is a critical part of the nation's strategy to 
effectively counter the spread of COVID-19. We continue to believe it 
is important to incentivize and track HCP vaccination through quality 
measurement across care settings, including IPFs, in order to protect 
HCP, patients, and caregivers, and to help sustain the ability of HCP 
to continue serving their communities throughout the PHE and beyond.
---------------------------------------------------------------------------

    \205\ Centers for Medicare & Medicaid Services. Revised Guidance 
for Staff Vaccination Requirements QSO-23-02-ALL. October 26, 2022. 
Available at: https://www.cms.gov/files/document/qs0-23-02-all.pdf.
---------------------------------------------------------------------------

    At the time we issued the FY 2022 IPF PPS final rule where we 
adopted the COVID-19 Vaccination Coverage Among Healthcare Personnel 
(HCP) measure, the Food and Drug Administration (FDA) had issued 
emergency use authorizations (EUAs) for initial and primary adult 
vaccines manufactured by Pfizer-BioNTech,\206\ Moderna,\207\ and 
Janssen.\208\ On August 23, 2021, the FDA issued an approval for the 
Pfizer-BioNTech vaccine, now marketed as Comirnaty.\209\ The FDA issued 
approval for the Moderna vaccine, marketed as Spikevax, on January 31, 
2022 \210\ and an EUA for the Novavax adjuvanted vaccine on July 13, 
2022.\211\ The FDA also issued EUAs for COVID-19 single vaccine booster 
doses in September 2021 \212\ and October 2021 \213\ for certain 
populations and in November 2021 \214\ for all individuals 18 years of 
age and older. EUAs were subsequently issued for a second vaccine 
booster dose in March 2022 \215\

[[Page 51129]]

and for bivalent or ``updated'' booster doses in August 2022.\216\
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    \206\ Food and Drug Administration. (December 2020). FDA Takes 
Key Action in Fight Against COVID-19 By Issuing Emergency Use 
Authorization for First COVID-19 Vaccine. Available at: https://www.fda.gov/news-events/press-announcements/fda-takes-key-action-fight-against-covid-19-issuing-emergency-use-authorization-first-covid-19.
    \207\ Food and Drug Administration. (December 2020). FDA Takes 
Additional Action in Fight Against COVID-19 By Issuing Emergency Use 
Authorization for Second COVID-19 Vaccine. Available at: https://www.fda.gov/news-events/press-announcements/fda-takes-additional-action-fight-against-covid-19-issuing-emergency-use-authorization-second-covid.
    \208\ Food and Drug Administration. (February 2021). FDA Issues 
Emergency Use Authorization for Third COVID-19 Vaccine. Available 
at: https://www.fda.gov/news-events/press-announcements/fda-issues-emergency-use-authorization-third-covid-19-vaccine.
    \209\ Food and Drug Administration. (August 2021). FDA Approves 
First COVID-19 Vaccine. Available at: https://www.fda.gov/news-events/press-announcements/fda-approves-first-covid-19-vaccine.
    \210\ Food and Drug Administration. (January 2022). Coronavirus 
(COVID-19) Update: FDA Takes Key Action by Approving Second COVID-19 
Vaccine. Available at: https:/www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-takes-key-action-approving-second-covid-19-vaccine.
    \211\ Food and Drug Administration. (July 2022). Coronavirus 
(COVID-19) Update: FDA Authorizes Emergency Use of Novavax COVID-19 
Vaccine, Adjuvanted. Available at: https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-authorizes-emergency-use-novavax-covid-19-vaccine-adjuvanted.
    \212\ Food and Drug Administration. (September 2021). FDA 
Authorizes Booster Dose of Pfizer-BioNTech COVID-19 Vaccine for 
Certain Populations. Available at: https://www.fda.gov/news-events/press-announcements/fda-authorizes-booster-dose-pfizer-biontech-covid-19-vaccine-certain-populations.
    \213\ Food and Drug Administration. (October 2021). Coronavirus 
(COVID-19) Update: FDA Takes Additional Actions on the Use of a 
Booster Dose for COVID-19 Vaccines. Available at: https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-takes-additional-actions-use-booster-dose-covid-19-vaccines.
    \214\ Food and Drug Administration. (November 2021). Coronavirus 
(COVID-19) Update: FDA Expands Eligibility for COVID-19 Vaccine 
Boosters. Available at: https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-expands-eligibility-covid-19-vaccine-boosters.
    \215\ Food and Drug Administration. (March 2022). Coronavirus 
(COVID-19) Update: FDA Authorizes Second Booster Dose of Two COVID-
19 Vaccines for Older and Immunocompromised Individuals. Available 
at: https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-authorizes-second-booster-dose-two-covid-19-vaccines-older-and.
    \216\ Food and Drug Administration. (August 2022). Coronavirus 
(COVID-19) Update: FDA Authorizes Moderna, Pfizer-BioNTech Bivalent 
COVID-19 Vaccines for Use as a Booster Dose. Available at: https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-authorizes-moderna-pfizer-biontech-bivalent-covid-19-vaccines-use.
---------------------------------------------------------------------------

    In the FY 2022 IPF PPS final rule, we stated that data 
demonstrating the effectiveness of COVID-19 vaccines to prevent 
asymptomatic infection or transmission of SARS-COV-2, the novel (new) 
coronavirus that causes COVID-19, were limited (86 FR 42634). While the 
impact of COVID-19 vaccines on asymptomatic infection and transmission 
was not yet fully known at the time of the FY 2022 IPF PPS final rule, 
there were robust data available on COVID-19 vaccine effectiveness 
across multiple populations against symptomatic infection, 
hospitalization, and death. Two-dose COVID-19 vaccines from Pfizer-
BioNTech and Moderna had been found to be 88 percent and 93 percent 
effective against hospitalization for COVID-19, respectively, over 6 
months for adults over age 18 without immunocompromising 
conditions.\217\ During a SARS-COV-2 surge in the spring and summer of 
2021, 92 percent of COVID-19 hospitalizations and 91 percent of COVID-
19-associated deaths were reported among persons not fully 
vaccinated.\218\ Real-world studies of population-level vaccine 
effectiveness indicated similarly high rates of effectiveness in 
preventing SARS-COV-2 infection among frontline workers in multiple 
industries, with a 90 percent effectiveness in preventing symptomatic 
and asymptomatic infection from December 2020 through August 2021.\219\ 
Vaccines have also been highly effective in real-world conditions (that 
is, vaccines have continued to be highly effective in conditions other 
than clinical trials) at preventing COVID-19 in HCP with up to 96 
percent effectiveness for fully vaccinated HCP, including those at risk 
for severe infection and those in racial and ethnic groups 
disproportionately affected by COVID-19.\220\ In the presence of high 
community prevalence of COVID-19, residents of nursing homes with low 
staff vaccination coverage had cases of COVID-19-related deaths 195 
percent higher than those among residents of nursing homes with high 
staff vaccination coverage.\221\ Currently available data demonstrate 
that COVID-19 vaccines are effective and prevent severe disease, 
including hospitalization, and death.
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    \217\ Centers for Disease Control and Prevention. (September 24, 
2021). Morbidity and Mortality Weekly Report (MMWR). Comparative 
Effectiveness of Moderna, Pfizer-BioNTech, and Janssen (Johnson & 
Johnson) Vaccines in Preventing COVID-19 Hospitalizations Among 
Adults Without Immunocompromising Conditions--United States, March-
August 2021. Available at: https://cdc.gov/mmwr/volumes/70/wr/mm7038e1.htm?s_cid=mm7038e1_w.
    \218\ Centers for Disease Control and Prevention. (September 10, 
2021). Morbidity and Mortality Weekly Report (MMWR). Monitoring 
Incidence of COVID-19 Cases, Hospitalizations, and Deaths, by 
Vaccination Status--13 U.S. Jurisdictions, April 4-July 17, 2021. 
Available at: https://cdc.gov.mmwr/volumes/70/wr/mm7037e1.htm.
    \219\ Centers for Disease Control and Prevention. (August 27, 
2021). Morbidity and Mortality Weekly Report (MMWR). Effectiveness 
of COVID-19 Vaccines in Preventing SARS-COV-2 Infection Among 
Frontline Workers Before and During B.1.617.2 (Delta) Variant 
Predominance--Eight U.S. Locations, December 2020-August 2021. 
Available at: https://cdc.gov/mmwr/volume/70/wr/mm7034e4.htm
    \220\ Pilishivi, T. et al. (December 2022). Effectiveness of 
mRNA Covid-19 Vaccine among U.S. Health Care Personnel. New England 
Journal of Medicine. 2021 Dec 16;385(25):e90. Available online at: 
https://pubmed.ncbi.nlm.nih.gov/34551224/.
    \221\ McGarry BE et al. (January 2022). Nursing Home Staff 
Vaccination and Covid-19 Outcomes. New England Journal of Medicine. 
2022 Jan 27;386(4):397-398. Available online at: https://pubmed.ncbi.nlm.nih.gov/34879189/.
---------------------------------------------------------------------------

    As SARS-COV-2 persists and evolves, our COVID-19 vaccination 
strategy must remain responsive. When we adopted the COVID-19 
Vaccination Coverage Among HCP measure in the FY 2022 IPF PPS final 
rule, we stated that the need for booster doses of the COVID-19 vaccine 
had not been established and no additional doses had been recommended 
(86 FR 42639). We also stated that we believed the numerator was 
sufficiently broad to include potential future boosters as part of a 
``complete vaccination course'' and that the measure was sufficiently 
specified to address boosters (86 FR 42639). Since we adopted the 
COVID-19 Vaccination Coverage Among HCP measure in the FY 2022 IPF PPS 
final rule, new variants of SARS-COV-2 have emerged around the world 
and within the United States. Specifically, the Omicron variant (and 
its related subvariants) is listed as a variant of concern by the 
Centers for Disease Control and Prevention (CDC) because it spreads 
more easily than earlier variants.\222\ Vaccine manufacturers have 
responded to the Omicron variant by developing bivalent COVID-19 
vaccines, which include a component of the original virus strain to 
provide broad protection against COVID-19 and a component of the 
Omicron variant to provide better protection against COVID-19 caused by 
the Omicron variant.\223\ These booster doses of the bivalent COVID-19 
vaccine have been shown to increase immune response to SARS-COV-2 
variants, including Omicron, particularly in individuals who are more 
than 6 months removed from receipt of their primary series.\224\ The 
FDA issued EUAs for two bivalent COVID-19 vaccine booster doses, one 
from Pfizer-BioNTech \225\ and one from Moderna,\226\ and strongly 
encourages anyone who is eligible to consider receiving a booster dose 
with a bivalent COVID-19 vaccine to provide better protection against 
currently circulating variants.\227\ COVID-19 booster doses are 
associated with a greater reduction in infections among HCP and their 
patients relative to those who only received primary series 
vaccination. One study showed a rate of breakthrough infections among 
HCP who received only the two-dose regimen of the COVID-19 vaccine of 
21.4 percent compared to a rate of 0.7 percent among HCP who received a 
third dose of the COVID-19 vaccine.\228\
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    \222\ Centers for Disease Control and Prevention. (August 2021). 
Variants of the Virus. Available at: https://www.cdc.gov/coronavirus/2019-ncov/variants/.
    \223\ Food and Drug Administration. (November 2022). COVID-19 
Bivalent Vaccine Boosters.
    \224\ Chalkias, S et al. (October 2022). A Bivalent Omicron-
Containing Booster Vaccine against Covid-19. N Engl J Med 2022; 
387:1279-1291. Available online at: https://www.nejm.org/doi/full/10.1056/NEJMoa2208343.
    \225\ Food and Drug Administration. (November 2022). Pfizer-
BioNTech COVID-19 Vaccines. Available at: https://www.fda.gov/emergency-preparedness-and-response/coronavirus-disease-2019-covid-19/pfizer-biontech-covid-19-vaccines.
    \226\ Food and Drug Administration. (November 2022). Moderna 
COVID-19 Vaccines. Available at: https://www.fda.gov/emergency-preparedness-and-response/coronavirus-disease-2019-covid-19/moderna-covid-19-vaccines.
    \227\ Food and Drug Administration. (August 2022). Coronavirus 
(COVID-19) Update: FDA Authorizes Moderna, Pfizer-BioNTech Bivalent 
COVID-19 Vaccines for Use as a Booster Dose. Available at: https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-authorizes-moderna-pfizer-biontech-bivalent-covid-19-vaccines-use.
    \228\ Oster Y et al. (May 2022). The effect of a third BNT162b2 
vaccine on breakthrough infections in health care workers: a cohort 
analysis. Clin Microbiol Infect. 2022 May;28(5): 735.e1-735.e3. 
Available online at: https://pubmed.ncbi.nlm.nih.gov/35143997/.
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    Despite the efficacy of COVID-19 vaccination generally, data 
submitted to the CDC via the National Healthcare Safety Network (NHSN) 
demonstrate clinically significant variation in booster dose 
vaccination rates across facilities, including IPFs. During the first 
quarter of 2022, IPFs reported a median

[[Page 51130]]

coverage rate of booster or additional dose(s) of 19.1 percent, with an 
interquartile range of 8.7 percent to 37.9 percent. These data, which 
show a performance gap in booster coverage, indicate that there is 
opportunity to improve booster vaccination coverage among HCP in 
IPFs.\229\
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    \229\ Measure Applications Partnership (MAP) Hospital Workgroup 
Preliminary Analyses. Available at: https://mmshub.cms.gov/sites/default/files/map-hospital-measure-specifications-manual-2022.pdf.
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    We believe that vaccination remains the most effective means to 
prevent the worst consequences of COVID-19, including severe illness, 
hospitalization, and death. Given the availability of vaccine efficacy 
data, EUAs issued by the FDA for bivalent boosters, the continued 
presence of SARS-COV-2 in the United States, and variance among rates 
of booster dose vaccination, it is important to modify the COVID-19 
Vaccination Coverage Among HCP measure to refer explicitly to HCP who 
receive primary series and booster vaccine doses in a timely manner. 
Given the persistent spread of COVID-19, we continue to believe that 
monitoring and surveillance of vaccination rates among HCP is important 
and provides patients, beneficiaries, and their caregivers with 
information to support informed decision-making.
    Beginning with the fourth quarter of the CY 2023 reporting period/
FY 2025 payment determination, we proposed to modify the COVID-19 
Vaccination Coverage Among HCP measure in the IPFQR Program to replace 
the term ``complete vaccination course'' with the term ``up-to-date'' 
in the HCP vaccination definition. We also proposed to update the 
numerator to specify the time frames within which an HCP is considered 
``up-to-date'' with recommended COVID-19 vaccines, including booster 
doses.
    In the FY 2022 IPF PPS final rule (86 FR 42638), we stated, and 
reiterate now, that the COVID-19 Vaccination Coverage Among HCP measure 
is a process measure that assesses HCP vaccination coverage rates. 
Unlike outcome measures, process measures do not assess a particular 
clinical outcome.
2. Overview of Measure
    The proposed COVID-19 Vaccination Coverage Among HCP measure is a 
process measure developed by the CDC to track COVID-19 vaccination 
coverage among HCP in settings such as acute care facilities, including 
IPFs, and post-acute care facilities.
    We refer readers to the FY 2022 IPF PPS final rule (86 FR 42635 
through 42636) for more information on the initial review of the 
current COVID-19 Vaccination Coverage Among HCP measure by the Measure 
Applications Partnership (MAP). We included an updated version of the 
proposed modification of the COVID-19 Vaccination Coverage Among HCP 
measure on the list of measures under consideration (MUC List), which 
is published annually on behalf of CMS by the CBE with which the 
Secretary must contract as required by section 1890(a) of the Act, for 
the 2022 to 2023 pre-rulemaking cycle for consideration by the MAP.
    In December 2022, the MAP Hospital Workgroup discussed the proposed 
modification of the COVID-19 Vaccination Coverage Among HCP measure. 
The MAP Hospital Workgroup stated that the proposed modification of the 
current measure captures ``up-to-date'' vaccination information in 
accordance with the CDC's recommendations, which have been updated 
since their initial development. Additionally, the MAP Hospital 
Workgroup appreciated that the modified measure's denominator is 
broader and simplified from seven categories of healthcare personnel to 
four.\230\
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    \230\ Centers for Medicare & Medicaid Services. 2022-2023 MAP 
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
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    During review on December 6 and 7, 2022, the MAP Health Equity 
Advisory Group highlighted the importance of COVID-19 measures and 
asked whether the proposed modified measure excludes individuals with 
contraindications to Food and Drug Administration (FDA) authorized or 
approved COVID-19 vaccines, and whether the measure will be stratified 
by demographic factors.\231\ The CDC, the measure developer for this 
measure, responded to the question regarding individuals with 
contraindications by confirming that HCP with contraindications to the 
vaccines are excluded from the measure denominator. The CDC further 
explained that the modified measure will not be stratified since the 
data are submitted at an aggregate rather than an individual level.
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    \231\ Centers for Medicare & Medicaid Services. 2022-2023 MAP 
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
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    During review on December 8 through 9, 2022, the MAP Rural Health 
Advisory Group expressed concerns about data collection burden, citing 
that collection is performed manually and that small rural hospitals 
may not have employee health software.\232\ The measure developer (that 
is, the CDC) acknowledged the challenge of getting adequate 
documentation and emphasized the goal to ensure the measure does not 
present a burden on providers. The measure developer also noted that 
the model used for this measure is based on the Influenza Vaccination 
Coverage Among HCP measure (CBE #0431), and it intends to utilize a 
similar approach to the modified COVID-19 Vaccination Coverage Among 
HCP measure if vaccination strategy becomes seasonal. The modified 
COVID-19 Vaccination Coverage Among HCP measure received conditional 
support for rulemaking pending testing indicating the measure is 
reliable and valid, and endorsement by the CBE. The MAP noted that the 
previous version of the measure received endorsement from the CBE (CBE 
#3636) \233\ and that the CDC intends to submit the proposed updated 
measure for endorsement.
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    \232\ Centers for Medicare & Medicaid Services. 2022-2023 MAP 
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
    \233\ Centers for Medicare & Medicaid Services. 2022-2023 MAP 
Final Recommendations. Available at: https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports. 
and CMS Measures Inventory Tool. Available at: https://cmit.cms.gov/cmit/#/MeasureView?variantId=5273§ionNumber=1.
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a. Measure Specifications
    The modification of the COVID-19 Vaccination Coverage Among HCP 
measure will require that IPFs continue to collect data at least one 
week each month for each of the three months in a quarter.
    The denominator is the number of HCP eligible to work in the 
facility for at least one day during the reporting period, excluding 
persons with contraindications to COVID-19 vaccination that are 
described by the CDC.\234\ There are not any changes to the denominator 
exclusions for the current COVID-19 Vaccination Coverage Among HCP 
measure, and the modified COVID-19 Vaccination Coverage Among HCP 
measure will continue to exclude otherwise denominator-eligible HCPs 
with contraindications as defined by the CDC.\235\ IPFs report the 
following four

[[Page 51131]]

categories of HCP to NHSN \236\; the first three categories are 
included in the measure denominator:
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    \234\ Centers for Disease Control and Prevention. (2022). 
Contraindications and precautions. Available at: https://www.cdc.gov/vaccines/covid-19/clinical-considerations/interim-considerations-us.html#contraindications.
    \235\ Centers for Disease Control and Prevention. (2022). 
Contraindications and precautions. Available at: https://www.cdc.gov/vaccines/covid-19/clinical-considerations/interim-considerations-us.html#contraindications.
    \236\ https://www.cdc.gov/nhsn/pdfs/nqf/covid-vax-hcpcoverage-rev-2023-508.pdf.
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    1. Employees: This category includes all persons who receive a 
direct paycheck from the IPF (that is, on the IPF's payroll), 
regardless of clinical responsibility or patient contact.
    2. Licensed independent practitioners (LIPs): This category 
includes physicians (MD, DO), advanced practice nurses, and physician 
assistants who are affiliated with the IPF but are not directly 
employed by it (that is, they do not receive a paycheck from the IPF), 
regardless of clinical responsibility or patient contact. Post-
residency fellows are also included in this category if they are not on 
the IPF's payroll.
    3. Adult students/trainees and volunteers: This category includes 
medical, nursing, or other health professional students, interns, 
medical residents, or volunteers aged 18 or older who are affiliated 
with the healthcare facility, but are not directly employed by it (that 
is, they do not receive a paycheck from the facility), regardless of 
clinical responsibility or patient contact.
    4. Other contract personnel: Contract personnel are defined as 
persons providing care, treatment, or services at the IPF through a 
contract who do not fall into any of the previously discussed 
denominator categories. Please note that this also includes vendors 
providing care, treatment, or services at the facility who may or may 
not be paid through a contract. Facilities are required to enter data 
on other contract personnel for submission in the NHSN application, but 
reporting for this category is not included in the COVID-19 Vaccination 
Coverage Among HCP measure.
    The numerator is the cumulative number of HCP in the denominator 
population who are ``up-to-date'' with CDC recommended COVID-19 
vaccines. IPFs would refer to the CDC's guidance, to determine the 
then-applicable definition of ``up-to-date,'' as of the first day of 
the applicable reporting quarter. The CDC's guidance can be found at: 
https://www.cdc.gov/nhsn/pdfs/hps/covidvax/UpToDateGuidance-508.pdf. 
For purposes of NHSN surveillance, the CDC used the following 
definition of ``up-to-date'' during the fourth quarter of CY 2022 
surveillance period (September 26, 2022 through December 25, 2022):
    1. Individuals who received an updated bivalent \237\ booster dose, 
or
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    \237\ The updated (bivalent) Moderna and Pfizer-BioNTech 
boosters target the most recent Omicron subvariants. The updated 
(bivalent) boosters were recommended by the CDC on 9/2/2022. As of 
this date, the original, monovalent mRNA vaccines are no longer 
authorized as a booster dose for people ages 12 years and older.
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    2a. Individuals who received their last booster dose less than 2 
months ago, or
    2b. Individuals who completed their primary series \238\ less than 
2 months ago.
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    \238\ Completing a primary series means receiving a two-dose 
series of a COVID-19 vaccine or a single dose of Janssen/J&J COVID-
19 vaccine.
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    Subsequent to the publication of the FY 2024 IPF PPS proposed rule, 
the CDC has updated the definition of ``up-to-date'' for the second 
quarter of CY 2023 surveillance period:
    1. Individuals who received an updated bivalent \239\ booster dose, 
or
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    \239\ The updated (bivalent) Moderna and Pfizer-BioNTech 
boosters target the most recent Omicron subvariants. The updated 
(bivalent) boosters were recommended by the CDC on 9/2/2022. As of 
this date, the original, monovalent mRNA vaccines are no longer 
authorized as a booster dose for people ages 12 years and older.
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    2. Individuals who completed their primary series \240\ less than 2 
months ago.
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    \240\ Completing a primary series means receiving a two-dose 
series of a COVID-19 vaccine or a single dose of Janssen/J&J COVID-
19 vaccine.
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    We refer readers to https://www.cdc.gov/nhsn/nqf/ for 
more details on the modified measure specifications.
    We proposed that public reporting of the modified version of the 
COVID-19 Vaccination Coverage Among HCP measure would begin with the 
October 2024 Care Compare refresh, or as soon as technically feasible 
after that refresh.
b. CBE Endorsement
    The current version of the COVID-19 Vaccination Coverage Among HCP 
measure received CBE endorsement (CBE #3636, ``Quarterly Reporting of 
COVID-19 Vaccination Coverage Among Healthcare Personnel'') on July 26, 
2022.\241\
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    \241\ CMS Measures Inventor Tool. COVID-19 Vaccination Coverage 
among Healthcare Personnel. Available at: https://cmit.cms.gov/cmit/#/MeasureView?variantId=5273§ionNumber=1.
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    Although section 1886(s)(4)(D)(i) of the Act generally requires 
that measures specified by the Secretary must be endorsed by the entity 
with a contract under section 1890(a) of the Act, section 
1886(s)(4)(D)(ii) of the Act states 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 a measure that has been endorsed or adopted by a consensus 
organization identified by the Secretary.
    We reviewed measures endorsed by consensus organizations and were 
unable to identify any other measures on this topic endorsed by a 
consensus organization; therefore, we believe the exception in section 
1886(s)(4)(D)(ii) of the Act applies. The CDC, as the measure 
developer, is currently pursuing endorsement for the modified version 
of the measure as the current version of the measure has already 
received endorsement.
3. Data Collection, Submission, and Reporting
    We refer readers to the FY 2022 IPF PPS final rule (86 FR 42636 
through 42640) for information on data submission and reporting of the 
current COVID-19 Vaccination Coverage Among HCP measure. While we did 
not propose any changes to the data submission or reporting process, we 
proposed that reporting of the updated modified measure would begin 
with the fourth quarter of CY 2023 reporting period for FY 2025 payment 
determination. Beginning with the FY 2026 payment determination, we 
proposed that IPFs would be required to submit data for the modified 
measure for the entire calendar year.
    Under the data submission and reporting process, IPFs collect the 
numerator and denominator for the COVID-19 Vaccination Coverage Among 
HCP measure for at least one self-selected week during each month of 
the reporting quarter and submit the data to the CDC's National Health 
Safety Network (NHSN) Healthcare Personnel Safety (HPS) Component 
before the quarterly deadline. If an IPF submits more than one week of 
data in a month, the CDC would use most recent week's data to calculate 
the measure results which would be publicly reported. Each quarter, the 
CDC calculates a single quarterly COVID-19 HCP vaccination coverage 
rate for each IPF, which is calculated by taking the average of the 
data from the three weekly rates submitted by the IPF for that quarter. 
CMS publicly reports each quarterly COVID-19 HCP vaccination coverage 
rate as calculated by the CDC based on the data IPFs submit to the NHSN 
(86 FR 42636 through 42640).
    We invited public comment on our proposal.
    Comment: Some commenters supported the proposed modification to the 
COVID-19 Vaccination Coverage Among HCP measure. One of these 
commenters stated that the modified specifications would lead to 
increased vaccination and booster adoption among

[[Page 51132]]

HCP. One commenter stated that patients with mental illness are more 
vulnerable to COVID-19 driving the increased need for their providers 
to be vaccinated.
    Response: We thank the commenters for their support. We agree that 
vaccination plays a critical part of the nation's strategy to 
effectively counter the spread of COVID-19. We continue to believe it 
is important to incentivize and track rates of vaccination among HCP 
through quality measurement across care settings, including the IPF 
setting, in order to protect healthcare workers, patients, and 
caregivers, and to help sustain the ability of HCP in each of these 
care settings to continue serving their communities.
    Comment: Several commenters did not support updating the 
specifications for the COVID-19 Vaccination Coverage Among HCP measure 
because the PHE has expired and the Conditions of Participation (COPs) 
for hospitals have been revised to no longer require reporting of these 
data. Some of these commenters requested clarification regarding 
whether the change in COPs means that we will remove the measure from 
our quality reporting programs. One commenter expressed concern that 
retaining measurement of COVID-19 Vaccination Coverage Among HCP after 
the vaccination requirement has been removed from COPs sends an 
inconsistent message regarding CMS's priorities.
    Response: As commenters noted, the PHE for COVID-19 expired on May 
11, 2023.\242\ Since May 11, 2023, some state and federal reporting 
requirements have changed. While CMS requirements for Medicare and 
Medicaid-certified providers and suppliers to ensure that their staff 
were fully vaccinated for COVID-19 have ended with the expiration of 
the COVID-19 PHE (88 FR 36488), CMS revised the hospital and critical 
access hospitals (CAHs) infection prevention and control Condition of 
Participation so that hospitals and CAHs will continue to report on a 
reduced number of COVID-19 data elements after the conclusion of the 
COVID- 19 PHE until April 30, 2024, unless the Secretary establishes an 
earlier end date.\243\ While these changes may impact certain aspects 
of facility reporting on COVID-19 data, we note that the reporting 
requirements of the IPFQR Program are distinct from those related to 
the expiration of the COVID-19 PHE and facilities participating in the 
IPFQR Program are required to report the COVID-19 Vaccination Coverage 
Among HCP measure. We further note that in our final rule removing 
staff vaccination requirements, we clarified that we were aligning our 
approach with that for other infectious diseases, specifically 
influenza, and that we would encourage ongoing COVID-19 vaccination 
through our quality reporting and value-based incentive programs (88 FR 
38486).
---------------------------------------------------------------------------

    \242\ U.S. Dept. of Health and Human Services. Fact Sheet: 
COVID-19 Public Health Emergency Transition Roadmap. February 9, 
2023. Available at: https://www.hhs.gov/about/news/2023/02/09/fact-sheet-covid-19-public-health-emergency-transition-roadmap.html.
    \243\ https://www.hhs.gov/about/news/2023/05/09/fact-sheet-end-of-the-covid-19-public-health-emergency.html.
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    We believe this measure continues to align with our goals to 
promote wellness and disease prevention. Under CMS' Meaningful Measures 
Framework 2.0, the COVID-19 Vaccination Coverage Among HCP measure 
addresses the quality priorities of ``Immunizations'' and ``Public 
Health'' through the Meaningful Measures Area of ``Wellness and 
Prevention.'' Under the National Quality Strategy, the measure 
addresses the goal of ``Safety'' under the priority area ``Safety and 
Resiliency.'' Our response to COVID-19 is not fully dependent on the 
emergency declaration for the COVID-19 PHE and, beyond the end of the 
COVID-19 PHE, we continue to work to protect individuals and 
communities from the virus and its worst impacts by supporting access 
to COVID-19 vaccines, treatments, and tests.
    Comment: Many commenters did not support updating the COVID-19 
Vaccination Coverage Among HCP measure because of concerns that the 
frequency of changes to the CDC's definition of ``up-to-date'' combined 
with the uncertainty around future vaccination schedules creates 
unnecessary burden for facilities. Some of these commenters recommended 
allowing voluntary reporting until the appropriate definitions and 
guidance are stable. One commenter stated that understanding how 
changing guidelines apply to all members of staff (such as those with 
risk factors) is burdensome. Others stated that publicly reporting 
these data may not be meaningful to consumers due to the changing 
definitions and the time lag between collection and public reporting.
    Response: Since the adoption of the current version of the measure, 
the public health response to COVID-19 has necessarily adapted to 
respond to the changing nature of the virus's transmission and 
community spread. When we finalized the adoption of the COVID-19 
Vaccination Coverage Among HCP measure in the FY 2022 IPF PPS final 
rule (86 FR 42640), we received several comments encouraging us to 
continue to update the measure as new evidence on COVID-19 continues to 
arise and we stated our intention to continue to work with partners 
including FDA and CDC to consider any updates to the measure in future 
rulemaking as appropriate. We believe that the measure modification 
aligns with the CDC's responsive approach to COVID-19 and will continue 
to support vaccination as the most effective means to prevent the worst 
consequences of COVID-19, including severe illness, hospitalization, 
and death. We agree with commenters who observe that there is a delay 
between data collection and public reporting for this measure and note 
that such a delay exists for all measures in the IPFQR Program. 
However, we believe that the data will provide meaningful information 
to consumers in making healthcare decisions because the data will be 
able to reflect differences between IPFs in COVID-19 vaccination 
coverage among HCP even if the data do not reflect immediate 
vaccination rates.
    Comment: Many commenters recommended that CMS reduce the mandatory 
reporting frequency to quarterly or to annually to reduce reporting 
burden for facilities. Some of these commenters stated that this 
mirrors the reporting schedule for the Influenza Vaccination Coverage 
Among HCP measure which is in some quality reporting programs.
    Response: As we stated in the FY 2024 IPF PPS proposed rule (88 FR 
21292), the measure developer noted that the model used for this 
measure is based on the Influenza Vaccination Coverage Among HCP 
measure (CBE #0431), and it intends to utilize a similar approach to 
the modified COVID-19 Vaccination Coverage Among HCP measure if 
vaccination strategy becomes seasonal. We continue to monitor COVID-19 
as part of our public health response and will consider information we 
collect to inform any potential action that may address seasonality in 
future rulemaking.
    Comment: Some commenters expressed concern that the COVID-19 
Vaccination Coverage Among HCP measure has not been endorsed by the 
CBE.
    Response: The current version of the measure received CBE 
endorsement (CBE #3636, ``Quarterly Reporting of COVID-19 Vaccination 
Coverage Among Healthcare Personnel'') on July 26, 2022. As we stated 
in the FY 2024 IPF PPS proposed rule (88 FR 21292 through 21293), in 
the case of a specified area or medical topic

[[Page 51133]]

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 discussed in section V.E.2.b. of the 
proposed rule (88 FR 21292 through 21293) and this final rule, we 
reviewed measures endorsed by consensus organizations and were unable 
to identify any other measures on this topic endorsed by a consensus 
organization; therefore, we believe the exception for non- CBE- 
endorsed measures applies. The measure steward, CDC, is currently 
pursuing endorsement for the modified version of the measure as the 
current version of the measure has already received endorsement.
    Comment: Some commenters recommended that CMS include an exclusion 
for sincerely held religious beliefs to adhere to HHS Office of Civil 
Rights Guidance. Some of these commenters also requested the measure be 
updated to track the number of HCP who decline vaccination. Several 
commenters stated that there are many factors beyond an IPF's control 
(such as weather, holidays, vaccine supply, etc.) that may affect 
performance on this measure.
    Response: We recognize that there are many reasons, including 
religious objections or concerns regarding an individual HCP's specific 
health status which may lead individual HCP to decline vaccination. The 
CDC's NHSN tool allows facilities to report on the number of HCP who 
were offered a vaccination but declined for religious or philosophical 
objections.\244\ We understand the commenters' concern that there are 
many factors outside of an IPF's control that could affect vaccination 
coverage; however, we believe that all IPFs face such concerns and that 
public reporting of these data can help patients and their caregivers 
identify which IPFs have better vaccination coverage among their HCP. 
Furthermore, we believe that reporting of the measure based on one week 
per month over three months will allow some seasonal or other effects 
to be mitigated. We wish to emphasize that neither the modified measure 
nor the current version of the measure mandate vaccines. The COVID-19 
Vaccination Coverage Among HCP measure only requires reporting of 
vaccination rates for successful program participation.
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    \244\ https://www.cdc.gov/nhsn/forms/COVIDVax.HCP_.FORM_May2022-508.pdf.
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    Final Decision: After consideration of the public comments we 
received, we are finalizing modification of the COVID-19 Vaccination 
Coverage Among HCP measure as proposed.

F. Removal or Retention of IPFQR Program Measures

1. Background
    In the FY 2018 IPPS/LTCH PPS final rule (82 FR 38463 through 38465) 
and FY 2019 IPF PPS final rule (83 FR 38591 through 38593), we adopted 
several considerations for removing or retaining measures within the 
IPFQR Program.
    Specifically, we have adopted eight factors that we consider when 
evaluating whether to propose a measure for removal from the IPFQR 
Program. These factors are: (1) measure performance among IPFs is so 
high and unvarying that meaningful distinctions and improvements in 
performance can no longer be made (``topped out'' measures); (2) 
measure does not align with current clinical guidelines or practice; 
(3) measure can be replaced by a more broadly applicable measure 
(across setting or populations) or a measure that is more proximal in 
time to desired patient outcomes for the particular topic; (4) measure 
performance or improvement does not result in better patient outcomes; 
(5) measure can be replaced by a measure more strongly associated with 
desired patient outcomes for the particular topic; (6) measure 
collection or public reporting leads to negative intended consequences 
other than patient harm; (7) measure is not feasible to implement as 
specified; and (8) the costs associated with a measure outweigh the 
benefit of its continued use in the program. For measure removal factor 
one, we specified that a measure is ``topped out'' if it meets the 
following criteria: (1) statistically indistinguishable performance at 
the 75th and 90th percentiles; and (2) the truncated coefficient of 
variation is less than or equal to 0.10.
    We also adopted three factors for consideration in determining 
whether to retain a measure in the IPFQR Program, even if the measure 
meets one or more factors for removal. These retention factors are: (1) 
measure aligns with other CMS and HHS policy goals, such as those 
delineated in the National Quality Strategy and CMS Quality Strategy; 
(2) measure aligns with other CMS programs, including other quality 
reporting programs; and (3) measure supports efforts to move IPFs 
towards reporting electronic measures. In the FY 2018 IPPS/LTCH PPS 
final rule (82 FR 38464), we stated that these removal and retention 
factors are considerations that we consider in balancing the benefits 
and drawbacks of removing or retaining measures on a case-by-case 
basis.
    Since adoption, we have not proposed any changes to these policies 
for removal or retention and refer readers to the FY 2018 IPPS/LTCH PPS 
final rule (82 FR 38463 through 38465) and the FY 2019 IPF PPS final 
rule (83 FR 38591 through 38593) for more information. We did not 
propose any updates to these measure retention and removal policies. We 
proposed to codify these previously adopted policies at Sec.  
412.433(e).
    We welcomed comments on this proposal.
    Comment: One commenter recommended an additional factor, relevance 
and importance of the measure to patients, for CMS to consider when 
deciding whether to remove or modify a measure in the IPFQR. The 
commenter stated this was consistent with TEPs which inform the measure 
development process and would improve the patient centeredness of the 
program.
    Response: We appreciate this recommendation and will consider it in 
the future as we continue to evaluate all elements of the IPFQR 
Program.
    Final Decision: After consideration of the public comments we 
received, we are finalizing codification of our measure retention and 
removal policies as proposed.
2. Measures for Removal
    We continue to evaluate our measure set against these removal and 
retention factors on an ongoing basis. In this continual evaluation of 
the IPFQR Program measure set under our Meaningful Measures Framework 
and according to our measure removal and retention factors, we 
identified two measures that we believe are appropriate to remove from 
the IPFQR Program beginning with the FY 2025 payment determination. Our 
discussion of these measures follows.
a. Removal of the Patients Discharged on Multiple Antipsychotic 
Medications With Appropriate Justification (HBIPS-5) (Previously 
Endorsed Under CBE #0560) Measure Beginning With FY 2025 Payment 
Determination

[[Page 51134]]

    As we assessed our existing measure set to ensure that it remains 
appropriate for the IPFQR Program, we determined that measure removal 
factor two (that is, measure does not align with current clinical 
guidelines or practice) applies to the Patients Discharged on Multiple 
Antipsychotic Medications with Appropriate Justification (HBIPS-5) (CBE 
#560) measure due to the American Psychiatric Association's (APA's) 
updated guidelines for patients with schizophrenia.
    We adopted the HBIPS-5 measure in the FY 2013 IPPS/LTCH PPS final 
rule as part of a set with the Patients Discharged on Multiple 
Antipsychotic Medications (HBIPS-4) (previously endorsed under CBE 
#0552) measure because of the belief that these two measures would help 
reduce unnecessary use of multiple antipsychotics, which would lead to 
better clinical outcomes and reduced side effects for patients (77 FR 
53649 through 53650). We subsequently removed the HBIPS-4 measure in 
the FY 2016 IPF PPS final rule (80 FR 46695 through 46696). As we 
described in that final rule, following our adoption of these measures, 
some experts, including the CBE, provided input that the HBIPS-4 
measure did not provide meaningful information about the quality of 
care received by IPF patients. This led to the removal of the HBIPS-4 
measure's CBE endorsement in January 2014. During the CBE's review of 
the HBIPS-4 measure in 2014, the CBE observed that the HBIPS-4 and 
HBIPS-5 measures could be collected and reported separately and 
expressed that the HBIPS-5 measure should be retained in the IPFQR 
Program as it continued to provide meaningful quality of care 
information (80 FR 046695 through 46696).
    Evidence supporting development and adoption of the HBIPS-5 measure 
included the APA Workgroup on Schizophrenia's 2004 Practice Guideline 
for the Treatment of Patients with Schizophrenia. These guidelines 
stated that the ``combinations of antipsychotics . . . should be 
justified by strong documentation that the patient is not equally 
benefited by monotherapy.'' \245\ In December 2019, the APA Board of 
Trustees approved updated guidelines for treatment of patients with 
schizophrenia.\246\ The updated guidelines are based on evolving 
clinical knowledge and have increased focus and specificity of 
recommendations for the use of pharmacotherapy; they also underscore 
the importance of patient preference and shared-decision making.\247\ 
These guidelines no longer contain the recommendation that combinations 
of antipsychotics should be justified by strong documentation that 
patients are not equally benefited by monotherapy. Therefore, the 
guidelines that originally supported the HBIPS-5 measure have changed 
substantially, and the HBIPS-5 measure is no longer aligned with 
current clinical guidelines and practice.
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    \245\ https://www.researchgate.net/publication/298561608_Practice_guideline_for_the_treatment_of_patients_with_schizophrenia_second_edition.
    \246\ https://ajp.psychiatryonline.org/doi/10.1176/appi.ajp.2020.177901.
    \247\ The American Psychiatric Association. Practice Guideline 
for the Treatment of Patients with Schizophrenia, Third Edition. 
Available at: https://psychiatryonline.org/doi/book/10.1176/appi.books.9780890424841. Accessed on February 15, 2023.
---------------------------------------------------------------------------

    Furthermore, the HBIPS-5 measure is no longer supported by the 
measure steward (that is, The Joint Commission), who withdrew it from 
the CBE endorsement process in 2019. As a result, the HBIPS-5 measure 
lost its CBE endorsement in October 2019.\248\ Subsequent to this, the 
CBE-convened MAP's discussion of measure set removal for 2021-2022 
included a discussion of this measure. Because the HBIPS-5 measure no 
longer aligns with clinical guidelines and is no longer CBE endorsed 
due to lack of support from the measure developer, the MAP recommended 
that the measure should be removed from the IPFQR Program.\249\
---------------------------------------------------------------------------

    \248\ CMS Measures Inventory Tool. Patients Discharged on 
multiple antipsychotic medications with appropriate justification. 
Available at: https://cmit.cms.gov/cmit/#/MeasureView?variantId=1141§ionNumber=1.
    \249\ MAP 2021-2022 Considerations for Implementing Measures in 
Federal Programs. Available at: https://mmshub.cms.gov/sites/default/files/map_2021-2022_considerations_for_implementing_measures_in_federal_programs_final_report.pdf.
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    We agree with the MAP's assessment that the measure no longer 
aligns with clinical guidelines and therefore proposed to remove the 
measure from the IPFQR Program beginning with the FY 2025 payment 
determination. We note that data for the FY 2024 payment determination 
represents care provided in CY 2022 and will be reported to CMS prior 
to the publication of this FY 2024 IPF PPS final rule; therefore, the 
FY 2025 payment determination is the first period for which we can 
remove this measure.
    We invited comments on our proposal.
    Comment: Many commenters supported removing HBIPS-5 from the IPFQR 
Program. These commenters agreed that the measure no longer aligns with 
the updated clinical guidance from the APA.
    Response: We thank these commenters for their support.
    Comment: Several commenters expressed concern about the long-term 
effects of psychotropic medications, especially antipsychotics, and 
recommended that CMS defer removal until additional research can be 
performed to ensure there are minimal long-term effects of 
antipsychotic medications.
    Response: We appreciate commenters' concern about the long-term 
effects of psychotropic medications. We note that our proposed removal 
of the measure was based on the updated APA guidelines for treatment of 
patients with schizophrenia. These guidelines underwent a rigorous 
review process prior to being updated, which included a review of the 
benefits and harms of each treatment.\250\
---------------------------------------------------------------------------

    \250\ https://www.psychiatry.org/File%20Library/Psychiatrists/Practice/Clinical%20Practice%20Guidelines/Guideline-Development-Process.pdf.
---------------------------------------------------------------------------

    Final Decision: After consideration of the public comments we 
received, we are finalizing removal of the Patients Discharged on 
Multiple Antipsychotic Medications with Appropriate Justification 
(HBIPS-5) measure as proposed.
b. Removal of the Tobacco Use Brief Intervention Provided or Offered 
and Tobacco Use Brief Intervention (TOB-2/2a) Measure Beginning With 
the FY 2025 Payment Determination
    We adopted the Tobacco Use Brief Intervention Provided or Offered 
and Tobacco Use Brief Intervention (TOB-2/2a) measure in the FY 2015 
IPF PPS final rule (79 FR 45971 through 45972) because of our belief 
that it is important to address the common comorbidity of tobacco use 
among IPF patients. The TOB-2/2a measure requires IPFs to chart-
abstract measure data on a sample of IPF patient records, in accordance 
with established sampling policies (80 FR 46717 through 46719). When we 
introduced the TOB-2/2a measure to the IPFQR Program, the benefits of 
this measure were high because IPF performance was not consistent with 
respect to, and there were no other measures addressing, provision of 
tobacco use cessation counseling or treatment. At the time, the TOB-2/
2a measure provided a means of distinguishing IPF performance 
regarding, and incentivized facilities to improve rates of, treatment 
for this common comorbidity. To further address tobacco use, we 
subsequently adopted the Tobacco Use Treatment Provided or Offered at 
Discharge and

[[Page 51135]]

Tobacco Use Treatment at Discharge (TOB-3/3a) measure in the FY 2016 
IPF PPS final rule (80 FR 46696 through 46699).
    In the FY 2022 IPF PPS proposed rule, we proposed to remove the 
Tobacco Use Brief Intervention Provided or Offered and Tobacco Use 
Brief Intervention (TOB-2/2a) measure from the IPFQR Program beginning 
with the FY 2024 payment determination under our measure removal factor 
8, the costs associated with a measure outweigh the benefit of its 
continued use in the program (86 FR 19508 through 19509). We expressed 
our belief that the quality improvement benefits from the TOB-2/2a 
measure had greatly diminished because performance had leveled off, 
that is overall performance on the measure was no longer improving. We 
took this to mean that most IPFs routinely offer tobacco use brief 
interventions.
    In the FY 2022 IPF PPS proposed rule, we also expressed our belief 
that the costs of maintaining this measure are high because costs are 
multi-faceted and include not only the IPFs' burden associated with 
reporting, but also our costs associated with implementing and 
maintaining the measure (86 FR 19508 through 19509). Additionally, we 
must expend resources in maintaining information collection systems, 
analyzing reported data, and providing public reporting of the 
collected information. We expressed that, for this measure, IPF 
information collection burden and related costs associated with 
reporting this measure to CMS were high because the measure is a chart-
abstracted measure. Furthermore, we observed CMS incurs costs 
associated with the program oversight of the measure for public 
display.
    However, in the FY 2022 IPF PPS final rule, we did not finalize our 
proposal to remove the Tobacco Use Brief Intervention Provided or 
Offered and Tobacco Use Brief Intervention (TOB-2/2a) measure (86 FR 
42648 through 42651). We stated that, following review of the public 
comments we received, we believed the benefits of continuing to 
encourage facilities to offer tobacco use brief interventions were 
greater than we had estimated. We noted that these benefits included 
the potential for IPFs to continue improving performance on the TOB-2/
2a measure, the importance of tobacco use interventions due to 
increased tobacco use during the COVID-19 pandemic, and this measure's 
potential influence on other quality improvement activities related to 
tobacco use.
    In our continual evaluation of the IPFQR Program measure set under 
our Meaningful Measures Framework and according to our measure removal 
and retention factors, we observed that having two measures addressing 
tobacco use, which are both associated with relatively high information 
collection burden, may not appropriately balance costs and benefits 
within the program. While we believe that both the TOB-2/2a measure and 
the TOB-3/3a measure address clinically important interventions to 
address smoking in this population, we believe that the overall cost 
associated with retaining both of these measures outweighs the benefit 
of having two measures to address treatment for the same comorbidity 
among the same patient population.
    Both measures capture information about tobacco cessation 
counseling and FDA-approved tobacco cessation medications. The 
difference between the measures is that the TOB-2/2a measure captures 
whether the tobacco cessation counseling and FDA-approved tobacco 
cessation medications were offered or refused during the inpatient 
stay, while the TOB-3/3a measure captures whether a referral to 
outpatient tobacco cessation counseling and FDA-approved tobacco 
cessation medications were offered or refused at the time of the 
patient's discharge.
    As we considered each of these measures, we determined that it 
would be more appropriate to retain the TOB-3/3a measure in the IPFQR 
Program, that is, to remove the TOB-2/2a measure instead of the TOB-3/
3a measure, because there is more opportunity for improvement on the 
TOB-3/3a measure. Specifically, the performance on the TOB-3/3a measure 
is lower than performance on the TOB-2/2a measure. National performance 
on TOB-2 and 2a measure and TOB-3 and 3a measure for the last five 
payment determination years in the IPFQR Program is presented in Table 
19. Given the relatively high performance on the TOB-2/2a measure 
compared to the TOB-3/3a measure, we believe that retaining the TOB-3/
3a measure, and removing the TOB-2/2a measure, would provide more 
opportunity to drive improvement among IPFs; therefore, would 
potentially impact more patients.
[GRAPHIC] [TIFF OMITTED] TR02AU23.023

    As described earlier in this section VI.F.2.b of this final rule, 
because the TOB-2/2a measure has a high cost (especially due to its 
high information collection burden), we believe that these high costs 
are no longer greater than the benefits of retaining this measure. 
Therefore, we believe measure removal factor 8 (that is, the costs 
associated with a measure outweigh the benefit of its continued use in 
the IPFQR Program), applies to the TOB-2/2a measure.
    Furthermore, the TOB-2/2a measure is no longer supported by the 
measure steward (that is, The Joint Commission), who withdrew it from 
the CBE endorsement process in 2018. Therefore, the TOB-2/2a measure 
has not been CBE endorsed since October 2018.\251\

[[Page 51136]]

Subsequent to this, the CBE-convened MAP's discussion of measure set 
removal for 2021and 2022 included a discussion of this measure. Because 
the TOB-2/2a measure is a high-cost measure and is no longer CBE 
endorsed, the MAP recommended that we remove the measure from the IPFQR 
Program.\252\
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    \251\ CMS Measures Inventory Tool. Tobacco Use Treatment 
Provided or Offered. Available at: https://cmit.cms.gov/cmit/#/MeasureView?variantId=1818§ionNumber=1.
    \252\ MAP 2021-2022 Considerations for Implementing Measures in 
Federal Programs. Available at: https://mmshub.cms.gov/sites/default/files/map_2021-2022_considerations_for_implementing_measures_in_federal_programs_final_report.pdf.
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    We agree with the MAP that this is a high-cost measure. 
Furthermore, we recognize that it is similar to the other tobacco use 
measure in the IPFQR Program measure set (that is, the TOB-3/3a 
measure) which we did not propose to remove. Therefore, we proposed to 
remove Tobacco Use Brief Intervention Provided or Offered and Tobacco 
Use Brief Intervention (TOB-2/2a) measure under our measure removal 
factor 8, ``the costs associated with a measure outweigh the benefit of 
its continued use in the program,'' beginning with FY 2025 payment 
determination. We note that data for the FY 2024 payment determination 
represents care provided in CY 2022 and will be reported to CMS prior 
to the publication of this FY 2024 IPF PPS final rule; therefore, the 
FY 2025 payment determination is the first period for which we can 
remove this measure.
    We invited public comment on this proposal.
    Comment: Many commenters supported removal of the TOB-2/2a measure 
because it will reduce burden with minimal impact on patient outcomes 
due to the retention of the TOB-3/3a measure. Some of these commenters 
stated that the TOB-3/3a measure has more room for improvement and is 
more likely to lead to improved patient outcomes.
    Response: We thank these commenters for their support.
    Comment: Many commenters opposed removal of the TOB-2/2a measure. 
These commenters stated that tobacco use is a common comorbidity among 
this patient population that leads to negative long-term health 
outcomes. These commenters expressed that the TOB-2/2a and TOB-3/3a 
measures both address important interventions to reduce tobacco use and 
therefore recommended retaining both measures. Some of these commenters 
expressed concern that, without the TOB-2/2a measure, IPFs will not 
offer tobacco use interventions in the inpatient setting which 
represents a missed opportunity to increase the likelihood that these 
patients will quit using tobacco. Some of these commenters stated that 
there is still room for improvement on the TOB-2/2a measure.
    Response: We agree with commenters that tobacco use is a common 
comorbidity among this patient population that leads to negative long-
term health outcomes. We remain committed to the screening, counseling 
and provision of smoking intervention services in this population of 
patients. We note that studies have demonstrated that during the acute 
hospital stay, there is no statistically significant increase in 
smoking cessation for non-intensive counseling interventions, such as 
brief intervention,\253\ which is what TOB-2/2a measures. We will 
retain TOB-3/3a which focuses on the provision of smoking cessation 
referral and treatment for smoking cessation at discharge, to be 
continued in the ambulatory setting, which studies have shown a greater 
benefit to the patient. Even though we are finalizing the removal of 
the TOB-2/2a measure, and therefore IPFs and IPFs will no longer be 
required to collect and submit TOB-2/2a data to CMS, IPFs are still 
encouraged to continue to provide smoking cessation counseling and 
brief interventions during the psychiatric stay as determined 
appropriate by the patient's provider and patient. We appreciate 
commenters concerns and will continue to monitor whether additional 
measures related to smoking cessation and/or intensive behavioral 
counseling are necessary. We also support the extensive other work that 
is being done by HHS and the broader Administration to reduce smoking, 
including the framework proposed by the Office of the Assistant 
Secretary for Health (OASH) (88 FR 42377).
---------------------------------------------------------------------------

    \253\ : Rigotti NA, Clair C, Munaf[ograve] MR, Stead LF. 
Interventions for smoking cessation in hospitalised patients. 
Cochrane Database Syst Rev. 2012 May 16;5(5):CD001837. doi: 10.1002/
14651858.CD001837.pub3. PMID: 22592676; PMCID: PMC4498489. Available 
at:: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4498489/.
---------------------------------------------------------------------------

    We agree with commenters that TOB-2/2a and TOB-3/3a both address 
important interventions (that is, tobacco use treatment brief 
intervention provided or offered during the inpatient stay and tobacco 
use treatment provided or offered at discharge) and that there is still 
room for improvement for both measures. While it is possible that, 
without the TOB-2/2a measure, some IPFs may stop providing inpatient 
tobacco use interventions prior to during the patient's discharge 
planning, we continue to believe that the benefit of having two 
measures to address this comorbidity does not outweigh the significant 
reporting burden for IPF's associated with these specific measures. We 
note that we believe that the benefits of tobacco use interventions 
during the inpatient stay are high; however, we do not believe the 
benefits of measuring these interventions along with similar 
interventions at discharge are sufficiently high to outweigh the 
burden.
    Final Decision: After consideration of the public comments we 
received, we are finalizing removal of the Tobacco Use Brief 
Intervention Provided or Offered and Tobacco Use Brief Intervention 
measure as proposed.

G. Summary of IPFQR Program Measures

1. IPFQR Program Measures for the FY 2024 Payment Determination
    We did not propose any changes to our measure set for the FY 2024 
payment determination. The 14 measures which will be in the program for 
FY 2024 payment determination are shown in Table 20.

[[Page 51137]]

[GRAPHIC] [TIFF OMITTED] TR02AU23.024

2. IPFQR Program Measures for the FY 2025 Payment Determination
    In this final rule. we are removing two measures for the FY 2025 
payment determination and subsequent years. We also are modifying one 
measure for the FY 2025 payment determination and subsequent years. The 
12 measures, which will be in the program for FY 2025 payment 
determination are shown Table 21.

[[Page 51138]]

[GRAPHIC] [TIFF OMITTED] TR02AU23.025

3. IPFQR Program Measures for the FY 2026 Payment Determination
    The measure set for FY 2026 payment determination and subsequent 
years will include 13 mandatory and two voluntary measures. This 
includes the 12 mandatory measures listed in Table 21 of this final 
rule for the FY 2025 payment determination and subsequent years, as 
well as the one mandatory measure and two voluntary measures we adopted 
for the FY 2026 payment determination and subsequent years. The 
measures which will be in the program for FY 2026 payment determination 
are shown Table 22.

[[Page 51139]]

[GRAPHIC] [TIFF OMITTED] TR02AU23.026

4. IPFQR Program Measures for the FY 2027 IPFQR Program's Payment 
Determination
    The measure set for the FY 2027 payment determination and 
subsequent years, will include 15 mandatory measures and one voluntary 
measure. This includes the 13 mandatory measures listed in Table 22 of 
this final rule for the FY 2026 payment determination and subsequent 
years, as well as the two measures which we are requiring for the FY 
2027 payment determination and subsequent years. It also includes the 
one new voluntary measure adopted in section VI.D.5 of this final rule. 
The measures which we are finalizing for the FY 2027 payment 
determination and subsequent years are shown Table 23.

[[Page 51140]]

[GRAPHIC] [TIFF OMITTED] TR02AU23.027

5. IPFQR Program Measures for the FY 2028 Payment Determination
    The measure set for the FY 2028 payment determination and 
subsequent years will include 16 mandatory measures. This includes the 
15 mandatory measures listed in Table 23 of this final rule for the FY 
2027 payment determination as well as the measure which we finalized 
beginning with the FY 2028 payment determination. The measures which 
will be in the program beginning with the FY 2028 payment determination 
are shown Table 24.

[[Page 51141]]

[GRAPHIC] [TIFF OMITTED] TR02AU23.028

H. Public Display and Review Requirements

    In the FY 2013 IPPS/LTCH PPS final rule (77 FR 53653 through 
53654), we adopted procedures for making data submitted under the IPFQR 
Program available to the public, after an IPF has the opportunity to 
review such data prior to public display, as required by section 
1886(s)(4)(E) of the Act. We adopted modifications to these procedural 
requirements in the FY 2014 IPPS/LTCH PPS final rule (78 FR 50897 
through 50898), and the FY 2017 IPPS/LTCH PPS final rule (81 FR 57248 
through 57249).
    Specifically, the IPFQR Program adopted a policy to provide IPFs a 
30-day period to review their data, and submit corrections to errors 
resulting from CMS calculations, prior to public display on a CMS 
website. The IPFQR Program notifies IPFs of the exact timeframes for 
this preview period and public display through subregulatory guidance. 
We did not propose any changes to these requirements.
    We proposed to codify the procedural requirements for public 
reporting of IPFQR Program data at Sec.  412.433(g). If finalized, 
paragraph (g) would provide that IPFs will have a period of 30 days

[[Page 51142]]

to review data on quality measures that CMS received under the IPFQR 
Program, and submit corrections to errors resulting from CMS 
calculations, prior to CMS publishing this data on a CMS website.
    We welcomed comments on our proposal to codify these policies.
    We did not receive any comments on this proposal.
    Final Decision: We are finalizing codification of these policies.

I. Form, Manner, and Timing of Quality Data Submission for the FY 2024 
Payment Determination and Subsequent Years

1. Procedural Requirements for the FY 2024 Payment Determination and 
Subsequent Years
    We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR 
53654 through 53655), the FY 2014 IPPS/LTCH PPS final rule (78 FR 50898 
through 50899), the FY 2018 IPPS/LTCH PPS final rule (82 FR 38471 
through 38472), and the FY 2022 IPF PPS final rule (86 FR 42656 through 
42657) for our previously finalized procedural requirements for 
participation in, and withdrawal from, the IPFQR Program, as well as 
data submission requirements. We did not propose any changes to our 
previously finalized procedural requirements.
    We proposed to codify these procedural requirements for 
participation in the IPFQR Program at Sec.  412.433(b) through (d). 
Paragraphs (b) through (d) will set forth the procedural requirements 
for an IPF to register for, or withdraw from, participation in the 
IPFQR Program and to submit the required data on measures in a form and 
manner and time specified by CMS.
    We welcomed comments on our proposal to codify these policies.
    We did not receive any comments on this proposal.
    Final Decision: We are finalizing codification of the procedural 
requirements for participation in the IPFQR Program at Sec.  412.433(b) 
through (d). We are finalizing the regulation text as proposed except 
to replace references to ``QualityNet'' with ``CMS-designated 
information system'' and update the description of the registration 
process because we inadvertently referred to QualityNet in the proposed 
rule. We have migrated to a new internet system for many quality 
reporting programs, and we use the term ``CMS-designated information 
system'' to refer both to that system and any future updates to it.
2. Data Submission Requirements for the FY 2025 Payment Determination 
and Subsequent Years
    We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR 
53655 through 53657), the FY 2014 IPPS/LTCH PPS final rule (78 FR 50899 
through 50900), the FY 2018 IPPS/LTCH PPS final rule (82 FR 38472 
through 38473), and the FY 2022 IPF PPS final rule (86 FR 42657 through 
42661) for our previously finalized data submission requirements.
    The measure we are modifying beginning with the FY 2025 payment 
determination--the COVID-19 Vaccination Coverage Among HCP measure--
requires facilities to report data on the number of HCP who have 
received a complete vaccination course of a COVID-19 vaccine through 
the Centers for Disease Control and Prevention's (CDC's) National 
Healthcare Safety Network (NHSN). We are updating this measure to no 
longer refer to ``complete vaccination course'' but instead to refer to 
``up-to-date'' vaccination, as described in section VI.E. of this final 
rule.
    We did not propose any updates to the form, manner, and timing of 
data submission for the COVID-19 Vaccination Coverage Among HCP measure 
and refer readers to the FY 2022 IPF PPS final rule (86 FR 42657) for 
these policies.
3. Data Submission Requirements for the FY 2026 Payment Determination 
and Subsequent Years
    In sections VI.D 3 and VI.D.4 of this final rule, we are adopting 
measures for voluntary reporting for the FY 2026 IPFQR Program and 
mandatory reporting for the FY 2027 IPFQR Program's payment 
determination and subsequent years. These measures are the Screening 
for Social Drivers of Health measure and Screen Positive Rate for 
Social Drivers of Health measure. We proposed that our previously 
finalized data submission requirements, specifically, our previously 
finalized data submission requirements for aggregate data reporting 
described in the FY 2018 IPPS/LTCH PPS final rule (82 FR 38472 through 
38473) would apply to these measures.
    We invited public comment on our proposal.
    We did not receive any public comments on this proposal.
    Final Decision: We are finalizing our proposal for data submission 
requirements for the FY 2026 payment determination and subsequent 
years.
4. Data Submission Requirements for the FY 2027 Payment Determination 
and Subsequent Years
    In section VI.D.5. of this final rule, we are adopting one patient-
reported measure, Psychiatric Inpatient Experience (PIX) measure for 
voluntary reporting beginning with the CY 2025 performance period (the 
data for which will be submitted to CMS during CY 2026) and mandatory 
reporting beginning with the FY 2028 payment determination (that is, 
data from the CY 2026 performance period submitted to CMS during CY 
2027). Because, unlike other patient experience of care measures, this 
measure is collected by facilities prior to discharge, we proposed that 
facilities would report these data using the patient-level data 
reporting described in the FY 2022 IPF PPS final rule (86 FR 42658 
through 42661).
    We invited public comment on our proposal.
    We did not receive any public comments on this proposal.
    Final Decision: We are finalizing our proposal for data submission 
requirements for the FY 2027 payment determination and subsequent 
years. We note that reporting these data will be voluntary for the FY 
2027 payment determination and will be mandatory beginning with the FY 
2028 payment determination.
5. Data Validation Pilot Beginning With Data Submitted in CY 2025
    As discussed in the FY 2019 IPF PPS final rule (83 FR 28607) and in 
the FY 2022 IPF PPS final rule (86 FR 42661), we are concerned that the 
ability to detect error is lower for aggregate measure data reporting 
than for patient-level data reporting (that is, data regarding each 
patient included in a measure and, for example, whether the patient was 
included in the numerator and denominator of the measure). In the FY 
2022 IPF PPS final rule, we noted that adoption of patient-level data 
requirements would enable us to adopt a data validation policy for the 
IPFQR Program in the future (86 FR 42661). We believe that it would be 
appropriate to develop such a policy incrementally through adoption of 
a data validation pilot prior to national implementation of data 
validation within the IPFQR Program. We sought public input on a 
potential data validation pilot, and many commenters supported the 
concept of data validation following implementation of patient-level 
reporting (86 FR 42661). In the FY 2022 IPF PPS final rule, we adopted 
mandatory patient-level reporting

[[Page 51143]]

beginning with data submitted in CY 2023 affecting the FY 2024 payment 
determination and reflecting care provided during CY 2022 (86 FR 42658 
through 42661).
    We are now finalizing a data validation pilot beginning with data 
submitted in CY 2025 (reflecting care provided during CY 2024). When we 
sought public comment on a data validation pilot in the FY 2022 IPF PPS 
proposed rule (86 FR 19515), we requested input on potential elements 
of such a pilot, including the number of measures and the number of 
participating IPFs. As summarized in the FY 2022 IPF PPS final rule (86 
FR 42661), one commenter recommended selecting two measures and 200 
IPFs for this pilot. We considered that recommendation; however, to 
align with validation policies in our other quality reporting programs, 
we decided to request a specific number of charts. Specifically, we 
proposed to request eight charts per quarter from each IPF as opposed 
to requesting all of the charts that each facility used to calculate 
one or more specific measures. We also decided to initiate our pilot 
with fewer IPFs than the commenter recommended to limit the burden 
associated with this pilot.
    We also reviewed the validation policies of other quality reporting 
programs. We specifically reviewed the Hospital IQR Program's chart-
abstracted measure validation policies described in the FY 2017 IPPS/
LTCH PPS final rule (81 FR 57179 through 57180), the Hospital IQR 
Program's pilot for eCQM validation described in the FY 2015 IPPS/LTCH 
PPS final rule (79 FR 50262 through 50273), the Hospital Outpatient 
Quality Reporting (OQR) Program's planned pilot of data validation as 
described in the CY 2009 OPPS/ASC final rule (73 FR 68502), and the 
Hospital OQR Program's finalized validation policies as described in 
the CY 2012 OPPS/ASC final rule (76 FR 74485) and the CY 2018 OPPS/ASC 
final rule (82 FR 59441 through 5944) because these programs are also 
pay-for-reporting programs, like the IPFQR Program.
    Following our review of the validation policies within these 
programs, we proposed a validation pilot in which we would randomly 
select on an annual basis up to 100 IPFs and request each selected IPF 
to provide to CMS eight charts per quarter, a total of 32 charts per 
year, used to calculate all chart-based measures beginning with data 
submitted in CY 2025. We believe that randomly selecting up to 100 IPFs 
would provide a sufficiently large set of IPFs to meaningfully test our 
validation procedures while minimizing burden for IPFs. We will specify 
the timeline and mechanism for submitting data in our data requests to 
individual IPFs that have been selected to participate in the 
validation pilot. We note that consistent with the Hospital IQR 
Program, we will reimburse IPFs for the cost of submitting charts for 
validation at a rate of $3.00 per chart (85 FR 58949).
    Because this is a voluntary pilot, we recognize that some selected 
IPFs will not participate; however, we believe that this pilot would be 
beneficial for IPFs that do participate as an opportunity to receive 
education and feedback on the data they submit prior to future proposal 
and adoption of a validation requirement in the IPFQR Program.
    We invited comments on our proposal.
    Comment: Several commenters expressed support for the data 
validation pilot.
    Response: We thank these commenters for their support.
    Comment: Several commenters provided recommendations for the data 
validation pilot. One commenter suggested allowing participants to opt 
into the pilot as opposed to selecting potential participants. One 
commenter requested that CMS ensure that the individuals doing the data 
validation have clinical expertise in the psychiatric setting to ensure 
appropriate interpretation of data. Another commenter recommended that 
CMS complete the pilot and analyze the data generated by the pilot 
prior to proposing and adopting a full data validation program.
    Response: We thank these commenters for their input. We note that 
the data validation pilot described in this section is based on 
validation programs in other quality reporting programs. We believe 
that selecting IPFs to participate will allow us to test our processes 
for selection and notification and therefore we believe that this will 
be a more effective test than allowing IPFs to opt into the pilot. We 
note that participation in the data validation pilot will be voluntary 
for the IPFs which we select. We will consider recommendations for 
qualifications for personnel to perform the data validation and for 
analysis of the results as we implement this program. We believe it is 
appropriate to develop a data validation policy incrementally through 
adoption of a data validation pilot prior to national implementation of 
data validation within the IPFQR Program. We intend to analyze data 
collected through this data validation pilot to inform development of a 
future nationally implemented data validation program. We note that 
while we will analyze data collected through the data validation pilot 
in developing the program for national implementation, the pilot will 
be ongoing until national implementation so that we can continue to 
collect data and IPFs can continue to receive education and feedback on 
the data they submit.
    Comment: One commenter expressed that a data validation pilot with 
payment ramifications is premature because patient-level data 
submission is still new to the IPFQR Program, because CMS has not 
sufficiently defined the pilot elements, and because it is unclear that 
there would be auditors with sufficient clinical expertise. Another 
commenter recommended that CMS use the data in the future IPF patient 
assessment instrument (PAI) to validate quality measure data. Another 
commenter recommended postponing this pilot until the financial and 
staffing shortages caused by the COVID-19 pandemic have been resolved.
    Response: We note that the participation in the data validation 
pilot is voluntary, and that IPFs will not receive any payment 
penalties during the data validation program's pilot period. With 
respect to the future IPF PAI, we will consider the potential interplay 
between data elements included in the PAI and IPFQR Program quality 
measure data for validation purposes, but believe those considerations 
are premature as a PAI has not yet been implemented for the IPF 
setting. Finally, we recognize that healthcare providers, including 
IPFs, are still recovering from the effects of the COVID-19 pandemic, 
but note that participation in the data validation pilot is voluntary.
    Comment: One commenter stated that the reimbursement rate of $3.00/
chart is insufficient to cover the time and materials associated with 
participating in the pilot.
    Response: We understand the commenters concern that $3.00/chart may 
not cover the time and materials associated with participating in the 
pilot. We note that this reimbursement is consistent with the 
reimbursement rates for submitting charts for validation in other 
quality reporting programs. However, we intend to use the pilot program 
to identify potential modifications prior to adopting a full validation 
program. We will consider the appropriateness of our reimbursement at 
that time.
    Final Decision: After consideration of the public comments we 
received, we are finalizing our data validation pilot as proposed.

[[Page 51144]]

6. Quality Measure Sampling Requirements
    We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR 
53657 through 53658), the FY 2014 IPPS/LTCH PPS final rule (78 FR 50901 
through 50902), the FY 2016 IPF PPS final rule (80 FR 46717 through 
46719), and the FY 2019 IPF PPS final rule (83 FR 38607 through 38608) 
for discussions of our previously finalized sampling policies.
    Because the Facility Commitment to Health Equity measure proposed 
in section VI.D.2 of this final rule is a structural attestation 
measure, these policies do not apply to that measure. Additionally, 
because the Screening for Social Drivers of Health measure (described 
in section VI.D.3 of this final rule) applies to all patients and the 
Screen Positive Rate for Social Drivers of Health measure (described in 
section VI.D.4 of this final rule) applies to all patients who have 
been screened for health-related social needs (HRSNs), our previously 
finalized sampling policies would not apply to these two measures. As 
described in the FY 2022 IPF PPS final rule, our sampling policies do 
not apply to the COVID-19 Vaccination Coverage Among Healthcare 
Personnel measure because the denominator is all healthcare personnel 
(86 FR 42661).
    Generally, we have applied our sampling procedures to chart-
abstracted measures, where appropriate (that is, where the measure does 
not require application to the entire patient population). However, 
because the PIX survey measure is a patient reported measure, we have 
considered whether our sampling procedures for chart-abstracted 
measures are appropriate for this measure. After consideration of our 
current sampling procedures and sampling for patient reported measures 
in other quality reporting programs (specifically, the requirements for 
reporting the HCAHPS measure), we proposed that the PIX survey measure 
(described in section VI.D.5 of this final rule) would be eligible for 
sampling but would not be included in the global sample. Instead, we 
proposed that sampling for this measure would align with sampling for 
the HCAHPS survey measure in acute care hospitals and the Hospital IQR 
Program as described in the HCAHPS Quality Assurance Guidelines.\254\ 
Specifically, we proposed to require IPFs to develop sampling plans 
that ensure that IPFs are able to submit data for 300 completed PIX 
surveys per year. IPFs will be required to sample from every month 
throughout the entire reporting period and not stop sampling or curtail 
ongoing interview activities once a certain number of completed surveys 
has been attained. IPFs that are unable to reach 300 completed surveys 
through sampling will be required to submit data on survey results for 
all eligible patient discharges.
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    \254\ HCHAPS Quality Assurance Guidelines, Version 17.0. March 
2022. Available at: https://hcahpsonline.org/globalassets/hcahps/quality-assurance/2022_qag_v17.0.pdf.
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    We invited public comment on our proposal.
    Comment: One commenter recommended allowing facilities to apply 
their sampling methodologies to the Screening for Social Drivers of 
Health measure and the Screen Positive Rate for Social Drivers of 
Health measure to reduce burden.
    Response: We acknowledge that applying sampling methodologies for 
these two measures would impact abstraction and reporting burden. We 
have proposed these measures to align with other quality reporting and 
value-based purchasing programs (specifically, the Hospital IQR 
Program) as well as the same measure proposals for the PPS-Exempt 
Cancer Hospital Quality Reporting Program in the FY 2024 IPPS/LTCH PPS 
proposed rule (88 FR 27122 through 27130) and the End-Stage Renal 
Disease (ESRD) Quality Incentive Program in the CY 2024 ESRD 
Prospective Payment System proposed rule (88 FR 42509 through 42518). 
We note that the Hospital IQR Program adopted these two measures 
without sampling in the FY 2023 IPPS/LTCH PPS final rule (87 FR 49191 
through 49220). We believe that adopting these measures consistently 
across programs will increase the cross-setting comparability of 
measure results for the Screening for Social Drivers of Health measure; 
provide more information regarding community needs for specific 
communities that are served by multiple healthcare organizations for 
the Screen Positive Rate for Social Drivers of Health measure; and 
ensure that we are consistently conveying the importance of identifying 
and addressing HRSNs across all settings.
    Comment: Several commenters recommended that CMS establish a 
statistically valid random sampling process for all IPFs to apply for 
the PIX survey measure to ensure that selection bias does not occur.
    Response: We will provide updated guidance for developing sampling 
plans and other implementation guidance for the PIX survey measure. 
This guidance will align with sampling guidance for the HCAHPS measure 
in the Hospital IQR Program.
    Comment: One commenter requested clarification regarding whether 
all patients would be eligible for inclusion in the sample for the PIX 
survey measure or only Medicare patients.
    Response: To the extent feasible we believe that it is important to 
include all patients in our quality reporting measures. While some 
measures do not allow inclusion of all patients (specifically, measures 
abstracted from Medicare claims data); there are no feasibility issues 
which require the PIX survey measure to be limited to patients covered 
by any specific payer. Therefore, all patients, regardless of payer, 
are included in the population from which the sample for this measure 
is selected.
    Comment: One commenter requested clarification regarding whether 
IPFs that were unable to reach 300 completed surveys would be 
penalized.
    Response: IPFs that are unable to reach 300 completed PIX surveys 
because of the size or characteristics of their patient population 
should submit data on all eligible patients. IPFs that meet this 
requirement would not be penalized for not submitting data on 300 
completed PIX surveys.
    Final Decision: We are finalizing our proposals related to sampling 
for the newly adopted measures.
7. Non-Measure Data Collection
    We refer readers to the FY 2015 IPF PPS final rule (79 FR 45973), 
the FY 2016 IPF PPS final rule (80 FR 46717), and the FY 2019 IPF PPS 
final rule (83 FR 38608) for our previously finalized non-measure data 
collection policies. We did not propose any changes to these policies.
8. Data Accuracy and Completeness Acknowledgement (DACA) Requirements
    We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR 
53658) for our previously finalized DACA requirements. We did not 
propose any changes to these policies.

J. Reconsideration and Appeals Procedures

    We refer readers to 42 CFR 412.434 for the IPFQR Program's 
reconsideration and appeals procedures. We did not propose any changes 
to these policies.

K. Extraordinary Circumstances Exceptions (ECE) Policy

    We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR 
53659 through 53660), the FY 2014 IPPS/LTCH PPS final rule (78 FR 
50903), the FY 2015 IPF PPS final rule (79 FR 45978), and the FY 2018 
IPPS/LTCH PPS final rule (82 FR 38473 through 38474) for our previously 
finalized Extraordinary

[[Page 51145]]

Circumstances Exceptions policies. We did not propose any changes to 
these policies.
    We proposed to codify the ECE policies at Sec.  412.433(f). As 
finalized, paragraph (f) provides that we may grant an exception to one 
or more data submission deadlines and requirements in the event of 
extraordinary circumstances beyond the control of the IPF either in 
response to a request by the IPF or at our discretion if we determine 
an extraordinary circumstance occurred.
    We solicited comments on our proposal to codify these policies.
    We did not receive any comments on this proposal.
    Final Decision: We are finalizing our proposal to codify these 
policies.

VII. Collection of Information Requirements

    Under the Paperwork Reduction Act of 1995 (PRA) (44 U.S.C. 3501 et 
seq.), we are required to provide 30-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. For the purposes of the PRA and this section 
of the preamble, collection of information is defined under 5 CFR 
1320.3(c) of the PRA's implementing regulations.
    To fairly evaluate whether an information collection should be 
approved by OMB, section 3506(c)(2)(A) of the PRA 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.
    Our April 10, 2023 (88 FR 21238) proposed rule solicited public 
comment on each of the aforementioned issues for the following sections 
of the rule that contained information collection requirements 
beginning in CY 2024 through CY 2027. A summary of these comments and 
our responses is in section VII.C of this final rule. The remaining 
provisions are not associated with any information collection 
requirements. In that regard they are not subject to the requirements 
of the PRA and are not addressed under this section of the preamble. 
For this rule's full burden implications, please see the Regulatory 
Impact Analysis under section VIII of this final rule.

A. Wage Estimates

    To derive average costs for this FY 2024 IPF PPS final rule, we 
used data from the U.S. Bureau of Labor Statistics' (BLS') May 2021 
National Occupational Employment and Wage Estimates for all salary 
estimates (https://www.bls.gov/oes/2021/may/oes292072.htm). In this 
regard, Table 25 presents BLS' median hourly wage for Medical Records 
Specialists \255\ (the occupation title that we have estimated is 
appropriate for completing data collection and reporting under the 
IPFQR Program), our estimated cost of fringe benefits and other 
indirect costs (calculated at 100 percent of salary), and our adjusted 
hourly wage.
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    \255\ We have previously estimated that labor performed could be 
accomplished by Medical Records and Health Information Technician 
staff and note that this BLS occupation category has been replaced 
with Medical Records Specialists.
[GRAPHIC] [TIFF OMITTED] TR02AU23.029

    As indicated, we are adjusting our hourly wage estimates by a 
factor of 100 percent. This is necessarily a rough adjustment, both 
because fringe benefits and other indirect costs vary significantly 
from employer to employer, and because methods of estimating these 
costs vary widely from study to study. Nonetheless, we believe that 
doubling the hourly wage to estimate the total cost is a reasonably 
accurate estimation method.
    In the FY 2022 IPF PPS final rule (86 FR 42662), which was the most 
recent rule in which we adopted updates to the IPFQR Program, we 
estimated that reporting measures for the IPFQR Program could be 
accomplished by a Medical Records and Health Information Technician 
(BLS Occupation Code: 29-2072) with a median hourly wage of $20.50/hour 
(BLS, May 2019). We note that since the publication of the FY 2022 IPF 
PPS final rule, the BLS occupation category of `Medical Records and 
Health Information Technician (BLS Occupation Code: 29-2071)' has been 
replaced with `Medical Records Specialist (BLS Occupation Code: 29-
2072). Therefore, in the FY 2024 IPF PPS proposed rule, we proposed to 
adjust our cost estimates using BLS' May 2021 median wage rate figure 
of $22.43/hour, an increase of $1.93/hour ($22.43/hour-$20.50/hour). 
When factoring in our overhead and other indirect cost adjustments, the 
wage is increased by $3.86/hour ($44.86/hour-$41.00/hour).
    We have also estimated the average hourly cost for patients 
undertaking administrative and other tasks on their own time. Based on 
recommendations from the Valuing Time in U.S. Department of Health and 
Human Services Regulatory Impact Analyses \256\ guidance we have 
estimated a post-tax wage of $20.71/hr. The Valuing Time in U.S. 
Department of Health and Human Services Regulatory Impact Analyses: 
Conceptual Framework and Best Practices identifies the approach for 
valuing time when individuals undertake activities on their own time. 
To derive the costs for patients, a measurement of the usual weekly 
earnings of wage and salary workers of $998, divided by 40 hours to 
calculate an hourly pre-tax wage rate of $24.95/hour. This rate is 
adjusted downwards by an estimate of the effective tax rate for median 
income households of about 17 percent, resulting in the post-tax hourly 
wage rate of $20.71/hour. Unlike our State and private sector wage 
adjustments, we are not adjusting beneficiary wages for fringe benefits 
and other indirect costs since the individuals' activities, if any, 
will occur outside the scope of their employment.
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    \256\ https://aspe.hhs.gov/sites/default/files/private/pdf/257746/VOT.pdf.

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[[Page 51146]]

B. Information Collection Requirements (ICRs) Regarding the IPFQR 
Program

    The following changes will be submitted to OMB for approval under 
control number 0938-1171 (CMS-10432). We are not making changes to any 
of the data collection instruments that are currently approved under 
that control number. We are, however, adopting one new instrument, the 
Psychiatric Inpatient Experience survey, to calculate the patient 
experience of care measure described in section VI.D.5 of this final 
rule.
    In section VII.B.1 of this final rule, we restate our currently 
approved burden estimates. In section VII.B.2 of this final rule, we 
estimate the changes in burden associated with the policies finalized 
in this rule and updated estimates for wage rates, facility counts, and 
case counts. Then in section VII.B.3 of this final rule, we provide an 
overview of the total estimated burden.
1. Currently Approved Burden
    For a detailed discussion of the burden for the IPFQR Program 
requirements that we have previously adopted, we refer readers to the 
FY 2022 IPF PPS final rule (86 FR 42661 through 42672).
    Table 26 provides an overview of our currently approved burden 
estimates.

[[Page 51147]]

[GRAPHIC] [TIFF OMITTED] TR02AU23.030


[[Page 51148]]


[GRAPHIC] [TIFF OMITTED] TR02AU23.031

2. Adjustments Due to Changes in This Final Rule
    We are finalizing provisions that impact policies beginning with 
the FY 2025 through FY 2028 payment determinations. For the purposes of 
calculating burden, we attribute the costs to the year in which the 
costs begin. For example, data submission for the measures that affect 
the FY 2025 payment determination occurs during CY 2024 and generally 
reflects care provided during CY 2023. The following discussion 
describes the burden changes for policies attributed to the year in 
which the costs begin. For the policies in this final rule, those years 
are CY 2024 through CY 2027.
    Additionally, in the FY 2022 IPF PPS final rule (86 FR 42661 
through 42672), which is the most recent rule that updated the IPFQR 
Program policies, we estimated that there were 1,634 participating IPFs 
and that (for measures that require reporting on the entire patient 
population) these IPFs will report on an average of 1,346 cases per 
IPF. In this FY 2024 IPF PPS final rule, we are adjusting our IPF count 
and case estimates by using the most recent data available. 
Specifically, we estimate that there are now approximately 1,596 
facilities (a decrease of 38 facilities) and an average of 1,261 cases 
per facility (a decrease of 85 cases per facility). We will update our 
estimates, as applicable, using these revised estimates in the 
following subsections.
a. Policies Affecting Data Reporting Beginning in CY 2023
    In section VI.E. of this final rule, we are modifying the COVID-19 
Vaccination Coverage Among Healthcare Personnel (HCP) measure beginning 
with data reflecting the fourth quarter of CY 2023 affecting the FY 
2025 payment determination. We do not believe that this modification 
(that is, a change in terminology to refer to ``up-to-date'' instead of 
``complete vaccination course'') will impact our currently approved IPF 
information collection requirements or burden estimates because the 
modified measure will be calculated using data already being submitted 
by IPFs to the CDC for healthcare safety surveillance under the CDC's 
OMB control number 0920-1317. In this regard, the CDC owns the 
requirements and burden that fall under that control number, including 
those of the COVID-19 Vaccination Coverage Among HCP measure.
b. Policies Affecting Burden Beginning With CY 2024
(1) Updates Affecting Facility Reporting Burden
    In section VI.F.2 of this final rule, we are removing two measures 
beginning with the FY 2025 payment determination. Data for these 
measures would have been submitted in CY 2024, so we are estimating the 
reduced burden to occur in CY 2024. The two measures are:
     Patients Discharged on Multiple Antipsychotic Medications 
with Appropriate Justification (HBIPS-5); and
     Tobacco Use Treatment Provided or Offered and Tobacco Use 
Treatment (TOB-2 and TOB-2a).
    Using our currently approved burden estimates as a baseline, the 
changes associated with removing these measures are: a decrease of 
1,990,212 responses, a decrease of 497,553 hours, and a decrease of 
$20,339,673 as set forth in Table 27.

[[Page 51149]]

[GRAPHIC] [TIFF OMITTED] TR02AU23.032

    Additionally, we are applying our updated wage rate (from $41.00/
hour to $44.86/hour), case count (from 1,346 to 1,261), and facility 
counts (from 1,634 to 1,596) to the remaining measure set and program 
requirements for data submission in CY 2024. See Table 28 and 29 for 
information on the effects of these updates. Specifically, we estimate 
that there are now approximately 1,596 facilities (a decrease of 38 
facilities) and an average of 1,261 cases per facility (a decrease of 
85 cases per facility). We also estimate a wage increase of $3.86/hour 
as described in section VI.A of this final rule. Our previous estimate 
shows that the two measures which do not allow sampling had 1,346 cases 
per measure and the six remaining measures which do allow sampling 
require 609 cases per measure per facility. We have estimated that 
these measures will take 0.25 hours per case. The effects of the 
updated hourly wage are set forth in Table 28.
[GRAPHIC] [TIFF OMITTED] TR02AU23.033

    The remaining calculations will use the updated hourly wage to 
calculate the effects of other updates.
    Our active burden estimates account for 1,346 cases for measures 
that do not allow sampling. Based on more recent data, we are updating 
our estimate for measures that do not allow sampling to 1,261 cases per 
IPF (a decrease of 85

[[Page 51150]]

cases for each of the 2 measures which do not allow sampling). This is 
equivalent to 138,890 cases across the 1,634 IPFs (85 cases x 1,634 
IPFs) in our previous estimate for each measure. We are not changing 
our estimated case counts for measures that allow sampling. We continue 
to assume an average of 0.25 hours of effort per case. Therefore, this 
change in cases reflects a total annual effort of 42.5 hours per 
facility (2 measures * 85 cases per measure * 0.25 hours per case) at a 
cost of $1,907 (42.5 hours * $44.86/hour).
    As indicated above we estimate a reduction of 38 facilities based 
on updated numbers. Table 29 shows the effects of this reduction in 
facilities on the reporting burden associated with each measure type.
[GRAPHIC] [TIFF OMITTED] TR02AU23.034

    We note that at 6,180 cases per facility, removing 38 facilities 
from our estimate removes a total of 234,840 cases (6,180 cases per 
facility * 38 facilities).
    The total effects of changes for the CY 2024 calendar year on our 
burden estimates are summarized in Table 30.
[GRAPHIC] [TIFF OMITTED] TR02AU23.035

(2) Updates Affecting Patient Survey Burden
    In section VI.D.3 of this final rule, we are adopting the Screening 
for Social Drivers of Health measure beginning with a voluntary data 
submission in CY 2025 (reflecting care provided in CY 2024). IPFs will 
be able to collect data and report the measure via multiple methods, 
potentially including administrative claims data, electronic clinical 
data, standardized patient assessments, or patient-reported data and 
surveys. For additional information on these methods, we refer readers 
to section VI.D.3.c of this final rule. We believe that most IPFs will 
likely collect data during the patient intake process. Because this 
measure reflects care provided in CY 2024, the burden for administering 
the screening to patients will occur during CY 2024.
    Under OMB Control Number 0938-1022 (CMS-10210) and the FY 2022 
IPPS/LTCH PPS final rule (87 FR 49385 through 49386), the Hospital IQR 
Program, which adopted the Screening for Social Drivers of Health 
measure, estimates that it will take 2 minutes (0.033 hr) per patient 
to complete the selected screening instrument. The Hospital IQR Program 
also estimated that during the voluntary reporting period roughly 50 
percent of hospitals will survey 50 percent of patients (87 FR 49385 
through 49386).
    We agree with these estimates and believe that a similar proportion 
of IPFs will participate in the voluntary reporting period. As 
described in section VII.A of this final rule, we estimate the cost of 
patients' time for completing surveys to be $20.71/hour. Using these 
estimates, we believe that during the voluntary reporting period the 
annual burden of surveying IPF patients will be 503,139 responses 
[(1,596 facilities x 50 percent of facilities) x (1,261 patients per 
facility x 50 percent of patients)], 16,604 hours (503,139 responses x 
0.033 hours/response] at a cost of $343,869 (16,604 hours x $20.71/
hour). These estimates are summarized in Table 31.

[[Page 51151]]

[GRAPHIC] [TIFF OMITTED] TR02AU23.036

c. Policies Affecting Burden Beginning With CY 2025
(1) Updates Affecting Facility Reporting Burden
    In section VI.I.5 of this final rule, we are adopting a data 
validation pilot for the IPFQR Program. Under this pilot we will 
reimburse hospitals directly for expenses associated with submission of 
charts for clinical process of care measure data validation. Because we 
will reimburse facilities directly for these expenses we do not believe 
that this pilot will increase information collection burden.
    In section VI.D.2. of this final rule, we are adopting the Facility 
Commitment to Health Equity measure beginning with the FY 2026 payment 
determination. Data for this attestation measure will be submitted 
during CY 2025. Consistent with our burden estimate from the Hospital 
IQR Program, when we adopted the similar Hospital Commitment to Health 
Equity measure in the FY 2023 IPPS/LTCH PPS final rule, we estimated an 
average of 10 minutes per facility for a medical records specialist to 
collect and report this information (87 FR 49385). We recognize that 
some IPFs may take more than 10 minutes to collect this information, 
especially in the first year of reporting; however, we believe that 
many IPFs will require less than 10 minutes. In addition, we believe 
that many IPFs will be able to submit similar responses in future 
years. Using the estimate of 10 minutes (0.167 hour) per IPF per year 
at $44.86/hour for a medical records specialist, we estimate that this 
policy will result in a total annual burden increase of 267 hours 
(0.167 hours x 1,596 IPFs) at a cost of $11,956.63 (267 hours x $44.86/
hour) across all participating IPFs.
    In sections VI.D.3 and VI.D.4 of this final rule, we are adopting 
the Screening for Social Drivers of Health measure and the associated 
Screen Positive Rate for Social Drivers of Health measure beginning 
with a voluntary data submission in CY 2025 (reflecting care provided 
in CY 2024). We described our anticipated burden (16,604 hours at a 
cost of $343,869) for administering the screening in the previous 
section because this burden will accrue during CY 2024. The burden 
associated with reporting each of these measures to CMS will occur 
during CY 2025. We anticipate that the burden for reporting the two 
measures will be consistent with the burden for other web-based 
submissions, such as the Facility Commitment to Health Equity measure 
described previously in this section and for similar measures adopted 
in the Ambulatory Surgical Center Quality Reporting (ASCQR) Program 
(OMB control number 0938-1270; CMS-10530), which we have estimated to 
have a reporting burden of 10 minutes (0.167 hours) per facility. We 
note that for the voluntary reporting year we have estimated only 50 
percent or 798 IPFs (1,596 IPFs x 0.50) will report these data. 
Therefore, we estimate the burden associated with reporting of each of 
these measures to be 133 hours (0.167 hr. x 798 IPFs) at a cost of 
$5,966 (133 hr. x $44.86/hour) for a medical records specialist) for 
the voluntary reporting period. These estimates are summarized in Table 
32. 
[GRAPHIC] [TIFF OMITTED] TR02AU23.037


[[Page 51152]]


(2) Updates Affecting Patient Survey Burden
    Beginning with CY 2025, IPFs will need to screen 100 percent of 
their patients to prepare for mandatory reporting of the Screening for 
Social Drivers of Health measure in CY 2026 (for the FY 2027 payment 
determination). Therefore, we estimate that 100 percent of IPFs will 
screen 100 percent of their patients. We recognize that this may be an 
overestimate as some IPFs may choose not to participate and some 
patients may opt out of screening or be unable to provide responses; 
however, we believe that the numbers of IPFs and patients opting out 
will be relatively small and therefore 100 percent will be a reasonable 
approximation.
    Using the facility counts (1,596 facilities), patient counts (1,261 
patients per facility), average hourly earnings ($20.71/hour), and time 
per response (10 min or 0.033 hours) described previously, we estimate 
the burden of surveying IPF patients for health-related social needs 
(HRSNs) under the Screening for Social Drivers of Health and Screen 
Positive Rate for Social Drivers of Health measures will be 66,414 
hours (1,596 facilities x 1,261 patients per facility x 0.033 hr) at a 
cost of $1,375,434 (66,414 hour x $20.71/hour) across all patients. We 
note that 16,604 hours and $343,960 of this burden was accounted for in 
our analysis of the burden of the voluntary reporting period described 
in section VII.B.2.c.(2). Therefore, the incremental burden of 
switching to mandatory reporting is 49,810 hours (66,414 hours-16,604 
hours) and $1,031,474 ($1,375,434-$343,960).
    Additionally, in section VI.D.5 of this final rule, we are adopting 
the Psychiatric Inpatient Experience (PIX) survey measure beginning 
with voluntary data submission in CY 2026. To prepare for data 
submission in 2026, IPFs will begin administering this survey in CY 
2025. We believe 50 percent or 798 (1,596 facilities x 0.50) of IPFs 
would begin collecting these data for the voluntary data submission 
period. We note that we proposed to allow IPFs with more than 300 
eligible discharges to sample, which would require these facilities to 
survey 300 patients. Because the questions on the PIX survey are 
similar in content and response options to the questions on the 
Hospital Consumer Assessment of Healthcare Providers and Systems 
(HCAHPS) survey, we believe that it will take patients a similar amount 
of time to respond to these questions. In the Information Collection 
Request associated with OMB control number 0938-0981 (CMS-10102), we 
have estimated this time to be 7.25 minutes (0.121 hours).
    Therefore, we believe that the burden associated with conducting 
the PIX survey in CY 2025 will be 28,967 hours (798 facilities x 300 
patients/facility x 0.121 hours/response) at a cost of $599,907 (28,967 
hours x $20.71/hour).
    Our estimates for the CY 2025 total patient survey burden changes 
are summarized in Table 33.
[GRAPHIC] [TIFF OMITTED] TR02AU23.038

d. Policies Affecting Burden Beginning With CY 2026
(1) Updates Affecting Facility Reporting Burden
    Beginning with CY 2026 data submission (affecting the FY 2027 
payment determination), we estimate that 100 percent of IPFs will 
submit data on the Screening for Social Drivers of Health measure and 
Screen Positive Rate for Social Drivers of Health measure. Because we 
have already accounted for 50 percent of facilities submitting 
voluntary data on these measures, the incremental burden is the burden 
associated with the remaining 50 percent of facilities submitting data; 
that is, we estimate this burden to be 266 hours at a cost of $11,933. 
We also believe that 50 percent of facilities will submit data on the 
PIX survey measure for the voluntary reporting period in CY 2025. 
Because the data for this measure will require calculating an average 
of scores across a sample of patient surveys, we anticipate that the 
information collection and reporting burden for this measure will be 
approximately 15 minutes (0.25 hours) per patient for whom they are 
reporting data. The burden associated with reporting the Screening for 
Social Drivers of Health measure, the Screen Positive Rate for Social 
Drivers of Health measure, and the PIX survey measure to CMS is 
described in Table 34.

[[Page 51153]]

[GRAPHIC] [TIFF OMITTED] TR02AU23.039

(2) Updates Affecting Patient Survey Burden
    Because reporting the PIX survey measure will be mandatory for the 
FY 2028 payment determination, the remaining 50 percent of facilities 
(those which did not participate in the voluntary reporting period) 
will begin surveying patients in CY 2026. To prepare for data 
submission of the PIX survey measure to CMS in CY 2027, IPFs that had 
not previously begun administering the PIX survey will begin 
administering this survey in CY 2026. The incremental burden of these 
50 percent of facilities administering the survey will be equivalent to 
the burden associated with the 50 percent of facilities that 
participated in the voluntary reporting in CY 2025. These estimates are 
summarized in Table 35.
[GRAPHIC] [TIFF OMITTED] TR02AU23.040

e. Policies Affecting Facility Reporting Burden Beginning With CY 2027
    For data submission occurring in CY 2027, submission on the PIX 
survey measure will be mandatory, therefore, we believe that an 
additional 50 percent of facilities will report the measure (that is, 
the 50 percent of facilities not previously accounted for under the 
voluntary reporting period). Therefore, we estimate that the 
incremental increase in burden for IPFs associated with this 
requirement will be reporting by the 50 percent of facilities that had 
not previously reported the PIX survey measure. This burden is set 
forth in Table 36.
[GRAPHIC] [TIFF OMITTED] TR02AU23.041


[[Page 51154]]


3. Overall Burden Summary
    Table 37 summarizes the incremental changes in burden for IPFs 
associated with policies for data collection and submission in CYs 2024 
through 2027 as well as updates to our estimated wage rate, facility 
counts, and case counts.
[GRAPHIC] [TIFF OMITTED] TR02AU23.042

    Table 38 summarizes the incremental changes in burden for patients 
due to data collection associated with proposed policies for data 
collection and submission in CYs 2024 through CY 2026.
[GRAPHIC] [TIFF OMITTED] TR02AU23.043

    Table 39 summarizes the total annual change in burden associated 
with the IPFQR Program's finalized policies in this final rule. These 
figures are calculated by adding the annual changes in Table 37 with 
the annual changes in Table 38. We note that these figures represent 
the changes to our previously approved burden (set forth in Table 26 of 
this final rule).

[[Page 51155]]

[GRAPHIC] [TIFF OMITTED] TR02AU23.044

C. Comments Received on the Proposed Collection of Information 
Requirements

    We solicited public comment on our estimated burden associated with 
the information collection requirements.
    The following comments were received.
    Comment: Several commenters expressed concern that the policies 
under the IPFQR Program will be burdensome, and some commenters 
specifically noted burden related to the PIX survey. One commenter 
expressed the belief that removing two measures while adopting four 
measures would increase overall burden.
    Response: We understand commenters' concerns that some of the 
policies under the IPFQR Program may contribute to IPF reporting 
burden. With respect to the PIX survey, we do not believe that 
administering a patient experience of care survey will be unduly 
burdensome for the majority of IPFs that previously self-reported that 
they already administer such a survey when responding to the IPFQR 
Program's former Assessment of Patient Experience of Care measure. We 
recognize that there will be some non-recurring burden for these IPFs 
to transition to the newly adopted survey. With respect to the concern 
that removing two measures while adopting four measures would increase 
the overall burden, we note that the measures we are removing are 
chart-abstracted measures with high reporting burden. We estimate that 
the newly adopted measures require less time to calculate and report. 
Therefore, we believe that our estimate that the overall burden of the 
IPFQR Program will be decreased by these policies is accurate.

VIII. Regulatory Impact Analysis

A. Statement of Need

    This rule finalizes updates to the prospective payment rates for 
Medicare inpatient hospital services provided by IPFs for discharges 
occurring during FY 2024 (October 1, 2023 through September 30, 2024). 
We are finalizing our proposal to apply a 2021-based IPF market basket 
increase for FY 2024 of 3.5 percent, less the productivity adjustment 
of 0.2 percentage point as required by 1886(s)(2)(A)(i) of the Act for 
a final total FY 2024 payment rate update of 3.3 percent. In this final 
rule, we are finalizing our proposal to update the outlier fixed dollar 
loss threshold amount, update the IPF labor-related share, and update 
the IPF wage index to reflect the FY 2024 hospital inpatient wage 
index. Section 1886(s)(3)(4) of the Act requires IPFs to report data in 
accordance with the requirements of the IPFQR 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.

B. Overall Impact

    We have examined the impacts of this 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), Executive Order 14094 entitled ``Modernizing 
Regulatory Review'' (April 6, 2023), 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). The 
Executive Order 14094 entitled ``Modernizing Regulatory Review'' 
(hereinafter, the Modernizing E.O.) amends section 3(f)(1) of Executive 
Order 12866 (Regulatory Planning and Review). The amended 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 $200 million or more in any 1 year (adjusted 
every 3 years by the Administrator of OIRA for changes in gross 
domestic product), or adversely affect in a material way the economy, a 
sector of the economy, productivity, competition, jobs, the 
environment, public health or safety, or State, local,

[[Page 51156]]

territorial, or tribal governments or communities; (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 legal or 
policy issues for which centralized review would meaningfully further 
the President's priorities or the principles set forth in the order, as 
specifically authorized in a timely manner by the Administrator of OIRA 
in each case.
    A regulatory impact analysis (RIA) must be prepared for major rules 
with significant regulatory action(s) and/or with significant effects 
as per section 3(f)(1) ($200 million or more in any 1 year). We 
estimate that the total impact of these changes for FY 2024 payments 
compared to FY 2023 payments will be a net increase of approximately 
$70 million. This reflects a $95 million increase from the update to 
the payment rates (+$100 million due to the FY 2024IPF market basket 
update of 3.5 percent, and -$5 million for the productivity adjustment 
of 0.2 percentage point), as well as a $25 million decrease as a result 
of the update to the outlier threshold amount. Outlier payments are 
estimated to change from 2.9 percent in FY 2023 to 2.0 percent of total 
estimated IPF payments in FY 2024.
    Based on our estimates, OMB's Office of Information and Regulatory 
Affairs has determined that this rulemaking is not significant per 
section 3(f)(1) as measured by the $200 million threshold or more in 
any 1 year. Nevertheless, this rule is a major rule, and accordingly, 
we have prepared a Regulatory Impact Analysis that to the best of our 
ability presents the costs and benefits of the rulemaking. Therefore, 
OMB has reviewed this final regulation, and we have provided the 
following assessment of its impact.

C. Detailed Economic Analysis

    In this section, we discuss the historical background of the IPF 
PPS and the impact of this final rule on the Federal Medicare budget 
and on IPFs.
1. Budgetary Impact
    As discussed in the November 2004 and RY 2007 IPF PPS final rules, 
we applied a budget neutrality factor to the Federal per diem base rate 
and ECT payment per treatment to ensure that total estimated payments 
under the IPF PPS in the implementation period will equal the amount 
that would have been paid if the IPF PPS had not been implemented. This 
Budget neutrality factor included the following components: Outlier 
adjustment, stop loss adjustment, and the behavioral offset. As 
discussed in the RY 2009 IPF PPS notice (73 FR 25711), the stop-loss 
adjustment is no longer applicable under the IPF PPS.
    As discussed in section III.D.1 of this final rule, we proposed to 
update the wage index and labor-related share in a budget neutral 
manner by applying a wage index budget neutrality factor to the Federal 
per diem base rate and ECT payment per treatment. Therefore, the 
budgetary impact to the Medicare program of this final rule will be due 
to the IPF market basket update for FY 2024 of 3.5 percent (see section 
IV.A.2 of this final rule) reduced by the productivity adjustment of 
0.2 percentage point as required by section 1886(s)(2)(A)(i) of the Act 
and the update to the outlier fixed dollar loss threshold amount.
    We estimate that the FY 2024 impact will be a net increase of $70 
million in payments to IPF providers. This reflects an estimated $95 
million increase from the update to the payment rates and a $25 million 
decrease due to the update to the outlier threshold amount to set total 
estimated outlier payments at 2.0 percent of total estimated payments 
in FY 2024. This estimate does not include the implementation of the 
mandatory 2.0 percentage point reduction of the productivity-adjusted 
IPF market basket update factor for any IPF that fails to meet the IPF 
quality reporting requirements (as discussed in section IV.B.2. of this 
final rule).
2. Impact on Providers
    To show the impact on providers of the changes to the IPF PPS 
discussed in this final rule, we compare estimated payments under the 
proposed IPF PPS rates and factors for FY 2024 versus those under FY 
2023. We determined the percent change in the estimated FY 2024 IPF PPS 
payments compared to the estimated FY 2023 IPF PPS payments for each 
category of IPFs. In addition, for each category of IPFs, we have 
included the estimated percent change in payments resulting from the 
final update to the outlier fixed dollar loss threshold amount; the 
updated wage index data including the final labor-related share; and 
the final IPF market basket update for FY 2024, as reduced by the final 
productivity adjustment according to section 1886(s)(2)(A)(i) of the 
Act.
    To illustrate the impacts of the FY 2024 changes in this final 
rule, our analysis begins with FY 2022 IPF PPS claims (based on the 
2022 MedPAR claims, March 2023 update). We estimate FY 2023 IPF PPS 
payments using these 2022 claims, the finalized FY 2023 IPF PPS Federal 
per diem base rates, and the finalized FY 2023 IPF PPS patient and 
facility level adjustment factors (as published in the FY 2023 IPF PPS 
final rule (87 FR 46846)). We then estimate the FY 2024 outlier 
payments based on these simulated FY 2023 IPF PPS payments using the 
same methodology that we used to set the initial outlier threshold 
amount in the RY 2007 IPF PPS final rule (71 FR 27072 and 27073), which 
is also the same methodology that we used to update the outlier 
threshold amounts for years 2008 through 2022, where total outlier 
payments are maintained at 2 percent of total estimated FY 2023 IPF PPS 
payments. We note that in the FY 2023 final rule (87 FR 46862 through 
46864) we excluded providers from our simulation of IPF PPS payments 
for FY 2022 and FY 2023 if their change in estimated average cost per 
day was outside 3 standard deviations from the mean. As discussed in 
section IV.E.2 of this final rule, we did not propose to apply this 
methodology for FY 2024.
    Each of the following changes is added incrementally to this 
baseline model in order for us to isolate the effects of each change:
     The update to the outlier fixed dollar loss threshold 
amount.
     The FY 2024 IPF wage index and the FY 2024 labor-related 
share.
     The IPF market basket update for FY 2024 of 3.5 percent 
less the productivity adjustment of 0.2 percentage point in accordance 
with section 1886(s)(2)(A)(i) of the Act for a final IPF payment rate 
update of 3.3 percent.
    Our column comparison in Table 40 illustrates the percent change in 
payments from FY 2023 (that is, October 1, 2022, to September 30, 2023) 
to FY 2024 (that is, October 1, 2023, to September 30, 2024) including 
all the payment policy changes.

[[Page 51157]]

[GRAPHIC] [TIFF OMITTED] TR02AU23.045


[[Page 51158]]


[GRAPHIC] [TIFF OMITTED] TR02AU23.046

3. Impact Results
    Table 40 displays the results of our analysis. The table groups 
IPFs into the categories listed here based on characteristics provided 
in the Provider of Services file, the IPF PSF, and cost report data 
from the Healthcare Cost Report Information System:
     Facility Type.
     Location.
     Teaching Status Adjustment.
     Census Region.
     Size.
    The top row of the table shows the overall impact on the 1,479 IPFs 
included in the analysis. In column 2, we present the number of 
facilities of each type that had information available in the PSF and 
had claims in the MedPAR dataset for FY 2022.
    In column 3, we present the effects of the update to the outlier 
fixed dollar loss threshold amount. We estimate that IPF outlier 
payments as a percentage of total IPF payments are 2.9 percent in FY 
2023. Therefore, we adjusted the outlier threshold amount to set total 
estimated outlier payments equal to 2.0 percent of total payments in FY 
2024. The estimated change in total IPF payments for FY 2024, 
therefore, includes an approximate 0.9 percent decrease in payments 
because we expect the outlier portion of total payments to decrease 
from approximately 2.9 percent to 2.0 percent.
    The overall impact of the estimated decrease to payments due to 
updating the outlier fixed dollar loss threshold (as shown in column 3 
of Table 3), across all hospital groups, is a 0.9 percentage point 
decrease. The largest decrease in payments due to this change is 
estimated to be 2.6 percent for urban government unit IPFs.
    In column 4, we present the effects of the budget-neutral update to 
the IPF wage index, the Labor-Related Share (LRS), and the 5-percent 
cap on any decrease to a provider's wage index from its wage index in 
the prior year. This represents the effect of using the concurrent 
hospital wage data as discussed in section IV.D.1.a of this final rule. 
That is, the impact represented in this column reflects the update from 
the FY 2023 IPF wage index to the FY 2024 IPF wage index, which 
includes basing the FY 2024 IPF wage index on the FY 2024 pre-floor, 
pre-reclassified IPPS hospital wage index data, applying a 5-percent 
cap on any decrease to a provider's wage index from its wage index in 
the prior year, and updating the LRS from 77.4 percent in FY 2023 to 
78.7 percent in FY 2024. We note that there is no projected change in 
aggregate payments to IPFs, as indicated in the first row of column 4; 
however, there will be distributional effects among different 
categories of IPFs. For example, we estimate the largest increase in 
payments to be 1.1 percent for Mid-Atlantic IPFs, and the largest 
decrease in payments to be 1.3 percent for freestanding, rural, for-
profit IPFs.
    Column 5 incorporates the FY 2024 IPF market basket update of 3.5 
percent reduced by 0.2 percentage point for the productivity adjustment 
as required by section 1886(s)(2)(A)(i) of the Act. This includes 
rebasing the IPF market basket to reflect a 2021 base year.
    Overall, IPFs are estimated to experience a net increase in 
payments as a result of the updates in this final rule. IPF payments 
are estimated to increase by 2.4 percent in urban areas and 2.0 percent 
in rural areas. The largest payment increases are estimated at 3.4 
percent for freestanding, urban, non-profit IPFs.
4. Effect on Beneficiaries
    Under the FY 2024 IPF PPS, IPFs will continue to receive payment 
based on the average resources consumed by patients for each day. Our 
longstanding payment methodology reflects the differences in patient 
resource use and costs among IPFs, as required under section 124 of the 
BBRA. We expect that updating IPF PPS rates in this final rule will 
improve or maintain beneficiary access to high quality care by ensuring 
that payment rates reflect the best available data on the resources 
involved in inpatient psychiatric care and the

[[Page 51159]]

costs of these resources. We continue to expect that paying 
prospectively for IPF services under the FY 2024 IPF PPS will enhance 
the efficiency of the Medicare program.
    As discussed in sections VI.D.3 and VI.D.4 of this final rule, we 
expect that additional IPFQR Program measures will support improving 
care for patients with health-related social needs. We also believe 
that our data validation pilot is an important step towards ensuring 
that the data beneficiaries and their caregivers access on Care Compare 
(or a successor CMS website) are accurate and reliable. Based on the 
input from patients and their caregivers regarding the importance of 
having a patient experience of care measure for the IPF setting in 
which they note many benefits (including, but not limited to helping 
patients select facilities in which to receive care, providing patients 
an opportunity to be heard, and increasing alignment between general 
acute and acute psychiatric settings). We believe that our PIX survey 
measure will have positive effects on patients and their caregivers. 
Therefore, we expect that the updates to the IPFQR Program will improve 
quality for beneficiaries.
5. Effects of the Updates to the IPFQR Program
    In section VI.D.3 of this final rule, we are adopting the Screening 
for Social Drivers of Health measure for the IPFQR Program beginning 
with voluntary reporting of CY 2024 data, and with mandatory reporting 
of CY 2025 data for the FY 2027 payment determination. For IPFs 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 facilities may utilize different modes of data 
collection (for example, paper-based, electronically patient-directed 
and clinician-facilitated). In addition, depending on the method of 
data collection utilized, the time mandatory to complete the survey may 
add a negligible amount of time to patient visits.
    In section VI.D.5 of this final rule, we are adopting the 
Psychiatric Inpatient Experience (PIX) survey measure. There may be 
some non-recurring costs associated with changes in workflow and 
information systems to administer this survey and collect the data. The 
extent of these costs is difficult to quantify as different facilities 
currently have different practices for surveying patients to gather 
information on their experiences of care.
    In addition, for the IPFQR Program, we are adopting the Facility 
Commitment to Health Equity measure and the Screen Positive for Social 
Drivers of Health measure, as well as to update the COVID-19 
Vaccination Coverage Among HCP measure. These updates will not impact 
providers workflows or information systems to collect or report the 
data, and because they represent processes of care or structural data 
that the IPFs will already have in place, we do not believe they will 
incur costs for providers beyond the recurring information collection 
costs (described in section VII.B of this final rule).
    Finally, we are removing two chart-abstracted measures from the 
IPFQR Program. We believe that the impact of removing the Tobacco Use 
Brief Intervention Provided or Offered and Tobacco Use Brief 
Intervention Provided (TOB-2/2a) measure will be minimal as we do not 
believe that IPFs will update their workflow to no longer provide brief 
tobacco cessation interventions to patients who use tobacco. However, 
we believe that there may be some simplification of workflows and 
clinical documentation associated with the removal of the Patients 
Discharged on Multiple Antipsychotic Medications with Appropriate 
Justification (HBIPS-5) measure because IPFs will no longer have to 
ensure the presence of appropriate documentation for the use of 
multiple antipsychotics. For more information on the updated clinical 
guidelines regarding polypharmacy for patients with schizophrenia, we 
refer readers to section VI.F.2.a of this final rule.
    As discussed in section IV.B.2 of this final rule and in accordance 
with section 1886(s)(4)(A)(i) of the Act, we will apply a 2-percentage 
point reduction to the FY 2024 market basket update for IPFs that have 
failed to comply with the IPFQR Program requirements for FY 2024, 
including reporting on the mandatory measures. In section IV.B.2 of 
this final rule, we discuss how the 2-percentage point reduction will 
be applied. For the FY 2023 payment determination, of the 1,596 IPFs 
eligible for the IPFQR Program, 6 IPFs did not receive the full market 
basket update because of the IPFQR Program; 2 of these IPFs chose not 
to participate and 4 did not meet the requirements of the program. 
Thus, we estimate that the IPFQR Program will have a negligible impact 
on overall IPF payments for FY 2024.
    Based on the IPFQR Program policies in this final rule, we estimate 
a total decrease in burden of 380,897 hours across all IPFs, resulting 
in a total decrease in information collection cost of $8.15 million 
across all IPFs. Further information on these estimates can be found in 
section VII.B of this final rule.
    We intend to closely monitor the effects of the IPFQR Program on 
IPFs and help facilitate successful reporting outcomes through ongoing 
stakeholder education, national trainings, and a technical help desk.
6. Regulatory Review Costs
    If regulations impose administrative costs on private entities, 
such as the time needed to read and interpret this final rule, we 
should estimate the cost associated with regulatory review. Due to the 
uncertainty involved with accurately quantifying the number of entities 
that will be directly impacted and will review this final rule, we 
assume that the total number of unique commenters on the most recent 
IPF PPS proposed rule will be the number of reviewers of this final 
rule. For this FY 2024 IPF PPS final rule, the most recent IPF PPS 
proposed rule was the FY 2024 IPF PPS proposed rule, and we received 
2,506 unique comments on this proposed rule. We acknowledge that this 
assumption may understate or overstate the costs of reviewing this 
final rule. It is possible that not all commenters reviewed the FY 2024 
IPF PPS proposed rule in detail, and it is also possible that some 
reviewers chose not to comment on that proposed rule. For these 
reasons, we thought that the number of commenters will be a fair 
estimate of the number of reviewers who are directly impacted by this 
final rule. We solicited comments on this assumption.
    We also recognize that different types of entities are in many 
cases affected by mutually exclusive sections of this final rule; 
therefore, for the purposes of our estimate, we assume that each 
reviewer reads approximately 50 percent of this final rule. Using the 
May, 2022 mean (average) wage information from the BLS for medical and 
health service managers (Code 11-9111), we estimate that the cost of 
reviewing this final rule is $123.06 per hour, including overhead and 
fringe benefits https://www.bls.gov/oes/current/oes119111.htm. Assuming 
an average reading speed of 250 words per minute, we estimate that it 
will take approximately 198 minutes (3.3 hours) for the staff to review 
half of this final rule (49,500), which contains a total of 
approximately 99,000 words. For each IPF that reviews the final rule, 
the estimated cost is (3.3 x $123.06) or

[[Page 51160]]

$406.10. Therefore, we estimate that the total cost of reviewing this 
final rule is $1,017,686.60 ($406.10 x 2,506 reviewers).

D. Alternatives Considered

    The statute does not specify an update strategy for the IPF PPS and 
is broadly written to give the Secretary discretion in establishing an 
update methodology. We continue to believe it is appropriate to 
routinely update the IPF PPS so that it reflects the best available 
data about differences in patient resource use and costs among IPFs as 
required by the statute. Therefore, we are finalizing our proposal to: 
Update the IPF PPS using the methodology published in the November 2004 
IPF PPS final rule; apply the 2021-based IPF market basket update for 
FY 2024 of 3.5 percent reduced by the productivity adjustment of 0.2 
percentage point as required by section 1886(s)(2)(A)(i) of the Act 
along with the wage index budget neutrality adjustment to update the 
payment rates; and use a FY 2024 IPF wage index which uses the FY 2024 
pre-floor, pre-reclassified IPPS hospital wage index as its basis.
    Lastly, we solicited comments on alternative methodologies that 
could be appropriate for establishing the FY 2024 outlier fixed dollar 
loss threshold.

E. Accounting Statement

    As required by OMB Circular A-4 (https://www.whitehouse.gov/wp-content/uploads/legacy_drupal_files/omb/circulars/A4/a-4.pdf), in Table 
41, we have prepared an accounting statement showing the classification 
of the expenditures associated with the updates to the IPF wage index 
and payment rates in this final rule. Table 41 provides our best 
estimate of the increase in Medicare payments under the IPF PPS as a 
result of the changes presented in this final rule and is based on 
1,479 IPFs with data available in the PSF and with claims in our FY 
2022 MedPAR claims dataset. Lastly, Table 41 also includes our best 
estimate of the costs of reviewing and understanding this final rule.
[GRAPHIC] [TIFF OMITTED] TR02AU23.047

F. Regulatory Flexibility Act

    The RFA requires agencies to analyze options for regulatory relief 
of small entities if a rule has a significant impact on a substantial 
number of small entities. For purposes of the RFA, small entities 
include small businesses, nonprofit organizations, and small 
governmental jurisdictions. Most IPFs and most other providers and 
suppliers are small entities, either by nonprofit status or having 
revenues of $8 million to $41.5 million or less in any 1 year. 
Individuals and states are not included in the definition of a small 
entity.
    Because we lack data on individual hospital receipts, we cannot 
determine the number of small proprietary IPFs or the proportion of 
IPFs' revenue derived from Medicare payments. Therefore, we assume that 
all IPFs are considered small entities.
    The Department of Health and Human Services generally uses a 
revenue impact of 3 to 5 percent as a significance threshold under the 
RFA. As shown in Table 40, we estimate that the overall revenue impact 
of this final rule on all IPFs is to increase estimated Medicare 
payments by 2.3 percent. As a result, since the estimated impact of 
this final rule is a net increase in revenue across almost all 
categories of IPFs, the Secretary has determined that this final rule 
will have a positive revenue impact on a substantial number of small 
entities.
    In addition, section 1102(b) of the Act requires us to prepare a 
regulatory impact analysis if a rule 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. For 
purposes of section 1102(b) of the Act, we define a small rural 
hospital as a hospital that is located outside of a metropolitan 
statistical area and has fewer than 100 beds. As discussed in section 
VIII.C.2 of this final rule, the rates and policies set forth in this 
final rule will not have an adverse impact on the rural hospitals based 
on the data of the 211 rural excluded psychiatric units and 61 rural 
psychiatric hospitals in our database of 1,479 IPFs for which data were 
available. Therefore, the Secretary has determined that this final rule 
will not have a significant impact on the operations of a substantial 
number of small rural hospitals.

G. Unfunded Mandate Reform Act (UMRA)

    Section 202 of the Unfunded Mandates Reform Act of 1995 (UMRA) 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 2023, that 
threshold is approximately $177 million. This final rule does not 
mandate any requirements for state, local, or tribal governments, or 
for the private sector. This final rule will not impose a mandate that 
will result in the expenditure by state, local, and tribal governments, 
in the aggregate, or by the private sector, of more than $177 million 
in any 1 year.

H. Federalism

    Executive Order 13132 establishes certain requirements that an 
agency must meet when it promulgates a proposed rule that imposes 
substantial direct requirement costs on state and local governments, 
preempts state law, or otherwise has Federalism implications. This 
final rule does not impose substantial direct costs on state

[[Page 51161]]

or local governments or preempt state law.
    Chiquita Brooks-LaSure, Administrator of the Centers for Medicare & 
Medicaid Services, approved this document on July 24, 2023.

List of Subjects in 42 CFR Part 412

    Administrative practice and procedure, Health facilities, Medicare, 
Puerto Rico, Reporting and recordkeeping requirements.

    For the reasons set forth in the preamble, the Centers for Medicare 
& Medicaid Services amends 42 CFR part 412 as set forth below:

PART 412--PROSPECTIVE PAYMENT SYSTEMS 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 412.25 is amended by revising paragraph (c) to read as 
follows:


Sec.  412.25  Excluded hospital units: Common requirements.

* * * * *
    (c) The status of a hospital unit may be changed from not excluded 
to excluded or excluded to not excluded at any time during a cost 
reporting period, but only if the hospital notifies the fiscal 
intermediary and the CMS Regional Office in writing of the change at 
least 30 days before the date of the change, and maintains the 
information needed to accurately determine costs that are or are not 
attributable to the hospital unit. A change in the status of a hospital 
unit from not excluded to excluded or excluded to not excluded that is 
made during a cost reporting period must remain in effect for the rest 
of that cost reporting period.
* * * * *


0
3. Section 412.433 is added to read as follows:


Sec.  412.433  Procedural requirements under the IPFQR Program.

    (a) Statutory authority. Section 1886(s)(4) of the Act requires the 
Secretary to implement a quality reporting program for inpatient 
psychiatric hospitals and psychiatric units. Under section 1886(s)(4) 
of the Act, for an IPF paid under the IPF PPS that fails to submit data 
required for the quality measures selected by the Secretary in a form 
and manner and at a time specified by the Secretary, we reduce the 
otherwise applicable annual update to the standard Federal rate by 2.0 
percentage points with respect to the applicable fiscal year.
    (b) Participation in the IPFQR Program. To participate in the IPFQR 
Program, an IPF (as defined under Sec.  412.402) that is paid under the 
IPF PPS must:
    (1) Register and maintain an account on the CMS-designated 
information system before beginning to report data, identification of a 
security official is necessary to complete such registration; and
    (2) Submit a notice of participation (NOP).
    (c) Withdrawal from the IPFQR Program. An IPF may withdraw from the 
IPFQR Program by changing the NOP status in the secure portion of the 
CMS-designated information system. The IPF may withdraw at any time up 
to and including August 15 before the beginning of each respective 
payment determination year. A withdrawn IPF is subject to a reduced 
annual payment update as specified under paragraph (a) of this section 
and is mandatory to renew participation as specified in paragraph (b) 
of this section in order to participate in any future year of the IPFQR 
Program.
    (d) Submission of IPFQR Program data. In general, except as 
provided in paragraph (f) of this section, IPFs that participate in the 
IPFQR Program must submit to CMS data on measures selected under 
section 1886(s)(4)(D) of the Act and specified non-measure data in a 
form and manner, and at a time specified by CMS.
    (e) Quality measure updates, retention, and removal. (1) General 
rule for updates to quality measures. CMS uses rulemaking to make 
substantive updates to the specifications of measures used in the IPFQR 
Program
    (2) General rule for the retention of quality measures. Quality 
measures adopted for the IPFQR Program measure set for a previous 
payment determination year are retained for use in subsequent payment 
determination years, except when they are removed, suspended, or 
modified as set forth in paragraph (3) of this section.
    (3) Measure removal, suspension, or modification through the 
rulemaking process. CMS will use the regular rulemaking process to 
remove, suspend, or modify quality measures in the IPFQR Program to 
allow for public comment.
    (i) Factors for consideration in removal or replacement of quality 
measures. CMS will weigh whether to remove or modify measures based on 
the following factors:
    (A) Factor 1: Measure performance among IPFs is so high and 
unvarying that meaningful distinctions and improvements in performance 
can no longer be made;
    (B) Factor 2: Measure does not align with current clinical 
guidelines or practice;
    (C) Factor 3: Measure can be replaced by a more broadly applicable 
measure (across settings or populations) or a measure that is more 
proximal in time to desired patient outcomes for the particular topic;
    (D) Factor 4: Measure performance or improvement does not result in 
better patient outcomes;
    (E) Factor 5: Measure can be replaced by a measure that is more 
strongly associated with desired patient outcomes for the particular 
topic;
    (F) Factor 6: Measure collection or public reporting leads to 
negative unintended consequences other than patient harm;
    (G) Factor 7: Measure is not feasible to implement as specified; 
and
    (H) Factor 8: The costs associated with a measure outweigh the 
benefit of its continued use in the program.
    (ii) Retention. CMS may retain a quality measure that meets one or 
more of the measure removal factors described in paragraph (i) of this 
subsection if the continued collection of data on the quality measure 
would align with other CMS and HHS policy goals, align with other CMS 
programs, or support efforts to move IPFs toward reporting electronic 
measures.
    (f) Extraordinary circumstances exception. CMS may grant an 
exception to one or more data submissions deadlines and requirements in 
the event of extraordinary circumstances beyond the control of the IPF, 
such as when an act of nature affects an entire region or locale or a 
systemic problem with one of CMS's data collection systems directly or 
indirectly affects data submission. CMS may grant an exception as 
follows:
    (1) Upon request by the IPF.
    (2) At the discretion of CMS. CMS may grant exceptions to IPFs that 
have not requested them when CMS determines that an extraordinary 
circumstance has occurred.

[[Page 51162]]

    (g) Public reporting of IPFQR Program data. Data that an IPF 
submits to CMS for the IPFQR Program will be made publicly available on 
a CMS website after providing the IPF an opportunity to review the data 
to be made public. IPFs will have a period of 30 days to review and 
submit corrections to errors resulting from CMS calculations prior to 
the data being made public.

Xavier Becerra,
Secretary, Department of Health and Human Services.
[FR Doc. 2023-16083 Filed 7-27-23; 4:15 pm]
BILLING CODE 4120-01-P