Medicare Program; Inpatient Rehabilitation Facility Prospective Payment System for Federal Fiscal Year 2022 and Updates to the IRF Quality Reporting Program, 19086-19126 [2021-07343]

Agencies

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

[Federal Register Volume 86, Number 68 (Monday, April 12, 2021)]
[Proposed Rules]
[Pages 19086-19126]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2021-07343]



[[Page 19085]]

Vol. 86

Monday,

No. 68

April 12, 2021

Part II





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; Inpatient Rehabilitation Facility Prospective Payment 
System for Federal Fiscal Year 2022 and Updates to the IRF Quality 
Reporting Program; Proposed Rule

Federal Register / Vol. 86 , No. 68 / Monday, April 12, 2021 / 
Proposed Rules

[[Page 19086]]


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DEPARTMENT OF HEALTH AND HUMAN SERVICES

Centers for Medicare & Medicaid Services

42 CFR Part 412

[CMS-1748-P]
RIN 0938-AU38


Medicare Program; Inpatient Rehabilitation Facility Prospective 
Payment System for Federal Fiscal Year 2022 and Updates to the IRF 
Quality Reporting Program

AGENCY: Centers for Medicare & Medicaid Services (CMS), HHS.

ACTION: Proposed rule.

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SUMMARY: This proposed rule would update the prospective payment rates 
for inpatient rehabilitation facilities (IRFs) for Federal fiscal year 
(FY) 2022. As required by statute, this proposed rule includes the 
classification and weighting factors for the IRF prospective payment 
system's case-mix groups and a description of the methodologies and 
data used in computing the prospective payment rates for FY 2022. In 
addition, this proposed rule includes proposals for the IRF Quality 
Reporting Program (QRP).

DATES: To be assured consideration, comments must be received at one of 
the addresses provided below, no later than 5 p.m. on June 7, 2021.

ADDRESSES: In commenting, please refer to file code CMS-1748-P.
    Comments, including mass comment submissions, must be submitted in 
one of the following three ways (please choose only one of the ways 
listed):
    1. Electronically. You may submit electronic comments on this 
regulation to https://www.regulations.gov. Follow the ``Submit a 
comment'' instructions.
    2. By regular mail. You may mail written comments to the following 
address ONLY: Centers for Medicare & Medicaid Services, Department of 
Health and Human Services, Attention: CMS-1748-P, P.O. Box 8016, 
Baltimore, MD 21244-8016.
    Please allow sufficient time for mailed comments to be received 
before the close of the comment period.
    3. By express or overnight mail. You may send written comments to 
the following address ONLY: Centers for Medicare & Medicaid Services, 
Department of Health and Human Services, Attention: CMS-1748-P, Mail 
Stop C4-26-05, 7500 Security Boulevard, Baltimore, MD 21244-1850.
    For information on viewing public comments, see the beginning of 
the SUPPLEMENTARY INFORMATION section.

FOR FURTHER INFORMATION CONTACT: Gwendolyn Johnson, (410) 786-6954, for 
general information.
    Catie Cooksey, (410) 786-0179, for information about the IRF 
payment policies and payment rates.
    Kadie Derby, (410) 786-0468, for information about the IRF coverage 
policies.
    Ariel Adams, (410) 786-8571, for information about the IRF quality 
reporting program.

SUPPLEMENTARY INFORMATION: 
    Inspection of Public Comments: All comments received before the 
close of the comment period are available for viewing by the public, 
including any personally identifiable or confidential business 
information that is included in a comment. We post all comments 
received before the close of the comment period on the following 
website as soon as possible after they have been received: https://www.regulations.gov. Follow the search instructions on that website to 
view public comments. CMS will not post on Regulations.gov public 
comments that make threats to individuals or institutions or suggest 
that the individual will take actions to harm the individual. CMS 
continues to encourage individuals not to submit duplicative comments. 
We will post acceptable comments from multiple unique commenters even 
if the content is identical or nearly identical to other comments.

Availability of Certain Information Through the Internet on the CMS 
Website

    The IRF prospective payment system (IRF PPS) Addenda along with 
other supporting documents and tables referenced in this proposed rule 
are available through the internet on the CMS Website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientRehabFacPPS.
    We note that prior to 2020, each rule or notice issued under the 
IRF PPS has included a detailed reiteration of the various regulatory 
provisions that have affected the IRF PPS over the years. That 
discussion, along with detailed background information for various 
other aspects of the IRF PPS, is now available on the CMS Website at 
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientRehabFacPPS.

I. Executive Summary

A. Purpose

    This proposed rule would update the prospective payment rates for 
IRFs for FY 2022 (that is, for discharges occurring on or after October 
1, 2021, and on or before September 30, 2022) as required under section 
1886(j)(3)(C) of the Social Security Act (the Act). As required by 
section 1886(j)(5) of the Act, this proposed rule includes the 
classification and weighting factors for the IRF PPS's case-mix groups 
(CMGs) and a description of the methodologies and data used in 
computing the prospective payment rates for FY 2022. This proposed rule 
proposes to add one new measure to the IRF QRP and modify the 
denominator for another measure currently under the IRF QRP beginning 
with the FY 2023 IRF QRP. In addition, this proposed rule proposes to 
modify the number of quarters used for publicly reporting certain IRF 
QRP measures due to the public health emergency (PHE). Finally, we are 
seeking comment on the use of Health Level Seven International 
(HL7[supreg]) Fast Healthcare Interoperability Resources[supreg] 
(FHIR)-based standards in post-acute care, specifically the IRF QRP, 
and on our continued efforts to close the health equity gap.

B. Summary of Major Provisions

    In this proposed rule, we use the methods described in the FY 2021 
IRF PPS final rule (85 FR 48424) to update the prospective payment 
rates for FY 2022 using updated FY 2020 IRF claims and the most recent 
available IRF cost report data, which is FY 2019 IRF cost report data. 
This proposed rule proposes to update certain requirements for the IRF 
QRP, and also makes requests for information.

C. Summary of Impact

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[GRAPHIC] [TIFF OMITTED] TP12AP21.000

II. Background

A. Statutory Basis and Scope

    Section 1886(j) of the Act provides for the implementation of a 
per-discharge PPS for inpatient rehabilitation hospitals and inpatient 
rehabilitation units of a hospital (collectively, hereinafter referred 
to as IRFs). Payments under the IRF PPS encompass inpatient operating 
and capital costs of furnishing covered rehabilitation services (that 
is, routine, ancillary, and capital costs), but not direct graduate 
medical education costs, costs of approved nursing and allied health 
education activities, bad debts, and other services or items outside 
the scope of the IRF PPS. A complete discussion of the IRF PPS 
provisions appears in the original FY 2002 IRF PPS final rule (66 FR 
41316) and the FY 2006 IRF PPS final rule (70 FR 47880) and we provided 
a general description of the IRF PPS for FYs 2007 through 2019 in the 
FY 2020 IRF PPS final rule (84 FR 39055 through 39057).
    Under the IRF PPS from FY 2002 through FY 2005, the prospective 
payment rates were computed across 100 distinct CMGs, as described in 
the FY 2002 IRF PPS final rule (66 FR 41316). We constructed 95 CMGs 
using rehabilitation impairment categories (RICs), functional status 
(both motor and cognitive), and age (in some cases, cognitive status 
and age may not be a factor in defining a CMG). In addition, we 
constructed five special CMGs to account for very short stays and for 
patients who expire in the IRF.
    For each of the CMGs, we developed relative weighting factors to 
account for a patient's clinical characteristics and expected resource 
needs. Thus, the weighting factors accounted for the relative 
difference in resource use across all CMGs. Within each CMG, we created 
tiers based on the estimated effects that certain comorbidities would 
have on resource use.
    We established the Federal PPS rates using a standardized payment 
conversion factor (formerly referred to as the budget-neutral 
conversion factor). For a detailed discussion of the budget-neutral 
conversion factor, please refer to our FY 2004 IRF PPS final rule (68 
FR 45684 through 45685). In the FY 2006 IRF PPS final rule (70 FR 
47880), we discussed in detail the methodology for determining the 
standard payment conversion factor.
    We applied the relative weighting factors to the standard payment 
conversion factor to compute the unadjusted prospective payment rates 
under the IRF PPS from FYs 2002 through 2005. Within the structure of 
the payment system, we then made adjustments to account for interrupted 
stays, transfers, short stays, and deaths. Finally, we applied the 
applicable adjustments to account for geographic variations in wages 
(wage index), the percentage of low-income patients, location in a 
rural area (if applicable), and outlier payments (if applicable) to the 
IRFs' unadjusted prospective payment rates.
    For cost reporting periods that began on or after January 1, 2002, 
and before October 1, 2002, we determined the final prospective payment 
amounts using the transition methodology prescribed in section 
1886(j)(1) of the Act. Under this provision, IRFs transitioning into 
the PPS were paid a blend of the Federal IRF PPS rate and the payment 
that the IRFs would have received had the IRF PPS not been implemented. 
This provision also allowed IRFs to elect to bypass this blended 
payment and immediately be paid 100 percent of the Federal IRF PPS 
rate. The transition methodology expired as of cost reporting periods 
beginning on or after October 1, 2002 (FY 2003), and payments for all 
IRFs now consist of 100 percent of the Federal IRF PPS rate.
    Section 1886(j) of the Act confers broad statutory authority upon 
the Secretary to propose refinements to the IRF PPS. In the FY 2006 IRF 
PPS final rule (70 FR 47880) and in correcting amendments to the FY 
2006 IRF PPS final rule (70 FR 57166), we finalized a number of 
refinements to the IRF PPS case-mix classification system (the CMGs and 
the corresponding relative weights) and the case-level and facility-
level adjustments. These refinements included the adoption of the 
Office of Management and Budget's (OMB's) Core-Based Statistical Area 
(CBSA) market definitions; modifications to the CMGs, tier 
comorbidities; and CMG relative weights, implementation of a new 
teaching status adjustment for IRFs; rebasing and revising the market 
basket index used to update IRF payments, and updates to the rural, 
low-income percentage (LIP), and high-cost outlier adjustments. 
Beginning with the FY 2006 IRF PPS final rule (70 FR 47908 through 
47917), the market basket index used to update IRF payments was a 
market basket reflecting the operating and capital cost structures for 
freestanding IRFs, freestanding inpatient psychiatric facilities 
(IPFs), and long-term care hospitals (LTCHs) (hereinafter referred to 
as the rehabilitation, psychiatric, and long-term care (RPL) market 
basket). Any reference to the FY 2006 IRF PPS final rule in this 
proposed rule also includes the provisions effective in the correcting 
amendments. For a detailed discussion of the final key policy changes 
for FY 2006, please refer to the FY 2006 IRF PPS final rule.
    The regulatory history previously included in each rule or notice 
issued under the IRF PPS, including a general description of the IRF 
PPS for FYs 2007 through 2020, is available on the CMS website at 
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientRehabFacPPS.
    In late 2019, the United States began responding to an outbreak of 
a virus named ``SARS-CoV-2'' and the disease it causes, which is named 
``coronavirus disease 2019'' (abbreviated ``COVID-19''). Due to our 
prioritizing efforts in support of containing and combatting the PHE 
for COVID-19, and devoting significant resources to that end, we 
published two interim final rules with comment period affecting IRF 
payment and conditions for participation. The

[[Page 19088]]

interim final rule with comment period (IFC) entitled, ``Medicare and 
Medicaid Programs; Policy and Regulatory Revisions in Response to the 
COVID-19 Public Health Emergency'', published on April 6, 2020 (85 FR 
19230) (hereinafter referred to as the April 6, 2020 IFC), included 
certain changes to the IRF PPS medical supervision requirements at 42 
CFR 412.622(a)(3)(iv) and 412.29(e) during the PHE for COVID-19. In 
addition, in the April 6, 2020 IFC, we removed the post-admission 
physician evaluation requirement at Sec.  412.622(a)(4)(ii) for all 
IRFs during the PHE for COVID-19. In the FY 2021 IRF PPS final rule, to 
ease documentation and administrative burden, we also removed the post-
admission physician evaluation documentation requirement at 42 CFR 
412.622(a)(4)(ii) permanently beginning in FY 2021.
    A second IFC entitled, ``Medicare and Medicaid Programs, Basic 
Health Program, and Exchanges; Additional Policy and Regulatory 
Revisions in Response to the COVID-19 Public Health Emergency and Delay 
of Certain Reporting Requirements for the Skilled Nursing Facility 
Quality Reporting Program'' was published on May 8, 2020 (85 FR 27550) 
(hereinafter referred to as the May 8, 2020 IFC). Among other changes, 
the May 8, 2020 IFC included a waiver of the ``3-hour rule'' at Sec.  
412.622(a)(3)(ii) to reflect the waiver required by section 3711(a) of 
the Coronavirus Aid, Relief, and Economic Security Act (CARES Act) 
(Pub. L. 116-136, enacted on March 27, 2020). In the May 8, 2020 IFC, 
we also modified certain IRF coverage and classification requirements 
for freestanding IRF hospitals to relieve acute care hospital capacity 
concerns in states (or regions, as applicable) that are experiencing a 
surge during the PHE for COVID-19. In addition to the policies adopted 
in our IFCs, we responded to the PHE with numerous blanket waivers \1\ 
and other flexibilities,\2\ some of which are applicable to the IRF 
PPS.
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    \1\ CMS, ``COVID-19 Emergency Declaration Blanket Waivers for 
Health Care Providers,'' (updated Feb. 19 2021) (available at 
https://www.cms.gov/files/document/summary-covid-19-emergency-declaration-waivers.pdf).
    \2\ CMS, ``COVID-19 Frequently Asked Questions (FAQs) on 
Medicare Fee-for-Service (FFS) Billing,'' (updated March 5, 2021) 
(available at https://www.cms.gov/files/document/03092020-covid-19-faqs-508.pdf).
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B. Provisions of the PPACA and the Medicare Access and CHIP 
Reauthorization Act of 2015 (MACRA) Affecting the IRF PPS in FY 2012 
and Beyond

    The Patient Protection and Affordable Care Act (PPACA) (Pub. L. 
111-148) was enacted on March 23, 2010. The Health Care and Education 
Reconciliation Act of 2010 (Pub. L. 111-152), which amended and revised 
several provisions of the PPACA, was enacted on March 30, 2010. In this 
proposed rule, we refer to the two statutes collectively as the 
``Patient Protection and Affordable Care Act'' or ``PPACA''.
    The PPACA included several provisions that affect the IRF PPS in 
FYs 2012 and beyond. In addition to what was previously discussed, 
section 3401(d) of the PPACA also added section 1886(j)(3)(C)(ii)(I) of 
the Act (providing for a ``productivity adjustment'' for FY 2012 and 
each subsequent FY). The productivity adjustment for FY 2022 is 
discussed in section V.B. of this proposed rule. Section 
1886(j)(3)(C)(ii)(II) of the Act provides that the application of the 
productivity adjustment to the market basket update may result in an 
update that is less than 0.0 for a FY and in payment rates for a FY 
being less than such payment rates for the preceding FY.
    Sections 3004(b) of the PPACA and section 411(b) of the MACRA (Pub. 
L. 114-10, enacted on April 16, 2015) also addressed the IRF PPS. 
Section 3004(b) of PPACA reassigned the previously designated section 
1886(j)(7) of the Act to section 1886(j)(8) of the Act and inserted a 
new section 1886(j)(7) of the Act, which contains requirements for the 
Secretary to establish a QRP for IRFs. Under that program, data must be 
submitted in a form and manner and at a time specified by the 
Secretary. Beginning in FY 2014, section 1886(j)(7)(A)(i) of the Act 
requires the application of a 2 percentage point reduction to the 
market basket increase factor otherwise applicable to an IRF (after 
application of paragraphs (C)(iii) and (D) of section 1886(j)(3) of the 
Act) for a FY if the IRF does not comply with the requirements of the 
IRF QRP for that FY. Application of the 2 percentage point reduction 
may result in an update that is less than 0.0 for a FY and in payment 
rates for a FY being less than such payment rates for the preceding FY. 
Reporting-based reductions to the market basket increase factor are not 
cumulative; they only apply for the FY involved. Section 411(b) of the 
MACRA amended section 1886(j)(3)(C) of the Act by adding paragraph 
(iii), which required us to apply for FY 2018, after the application of 
section 1886(j)(3)(C)(ii) of the Act, an increase factor of 1.0 percent 
to update the IRF prospective payment rates.

C. Operational Overview of the Current IRF PPS

    As described in the FY 2002 IRF PPS final rule (66 FR 41316), upon 
the admission and discharge of a Medicare Part A fee-for-service (FFS) 
patient, the IRF is required to complete the appropriate sections of a 
Patient Assessment Instrument (PAI), designated as the IRF-PAI. In 
addition, beginning with IRF discharges occurring on or after October 
1, 2009, the IRF is also required to complete the appropriate sections 
of the IRF-PAI upon the admission and discharge of each Medicare 
Advantage (MA) patient, as described in the FY 2010 IRF PPS final rule 
(74 FR 39762 and 74 FR 50712). All required data must be electronically 
encoded into the IRF-PAI software product. Generally, the software 
product includes patient classification programming called the Grouper 
software. The Grouper software uses specific IRF-PAI data elements to 
classify (or group) patients into distinct CMGs and account for the 
existence of any relevant comorbidities.
    The Grouper software produces a five-character CMG number. The 
first character is an alphabetic character that indicates the 
comorbidity tier. The last four characters are numeric characters that 
represent the distinct CMG number. A free download of the Grouper 
software is available on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientRehabFacPPS/Software.html. The Grouper software is also embedded in the internet 
Quality Improvement and Evaluation System (iQIES) User tool available 
in iQIES at https://www.cms.gov/medicare/quality-safety-oversight-general-information/iqies.
    Once a Medicare Part A FFS patient is discharged, the IRF submits a 
Medicare claim as a Health Insurance Portability and Accountability Act 
of 1996 (HIPAA) (Pub. L. 104-191, enacted on August 21, 1996) -
compliant electronic claim or, if the Administrative Simplification 
Compliance Act of 2002 (ASCA) (Pub. L. 107-105, enacted on December 27, 
2002) permits, a paper claim (a UB-04 or a CMS-1450 as appropriate) 
using the five-character CMG number and sends it to the appropriate 
Medicare Administrative Contractor (MAC). In addition, once a MA 
patient is

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discharged, in accordance with the Medicare Claims Processing Manual, 
chapter 3, section 20.3 (Pub. 100-04), hospitals (including IRFs) must 
submit an informational-only bill (type of bill (TOB) 111), which 
includes Condition Code 04 to their MAC. This will ensure that the MA 
days are included in the hospital's Supplemental Security Income (SSI) 
ratio (used in calculating the IRF LIP adjustment) for FY 2007 and 
beyond. Claims submitted to Medicare must comply with both ASCA and 
HIPAA.
    Section 3 of the ASCA amended section 1862(a) of the Act by adding 
paragraph (22), which requires the Medicare program, subject to section 
1862(h) of the Act, to deny payment under Part A or Part B for any 
expenses for items or services for which a claim is submitted other 
than in an electronic form specified by the Secretary. Section 1862(h) 
of the Act, in turn, provides that the Secretary shall waive such 
denial in situations in which there is no method available for the 
submission of claims in an electronic form or the entity submitting the 
claim is a small provider. In addition, the Secretary also has the 
authority to waive such denial in such unusual cases as the Secretary 
finds appropriate. For more information, see the ``Medicare Program; 
Electronic Submission of Medicare Claims'' final rule (70 FR 71008). 
Our instructions for the limited number of Medicare claims submitted on 
paper are available at https://www.cms.gov/manuals/downloads/clm104c25.pdf.
    Section 3 of the ASCA operates in the context of the administrative 
simplification provisions of HIPAA, which include, among others, the 
requirements for transaction standards and code sets codified in 45 CFR 
part 160 and part 162, subparts A and I through R (generally known as 
the Transactions Rule). The Transactions Rule requires covered 
entities, including covered healthcare providers, to conduct covered 
electronic transactions according to the applicable transaction 
standards. (See the CMS program claim memoranda at https://www.cms.gov/ElectronicBillingEDITrans/ and listed in the addenda to the Medicare 
Intermediary Manual, Part 3, section 3600).
    The MAC processes the claim through its software system. This 
software system includes pricing programming called the ``Pricer'' 
software. The Pricer software uses the CMG number, along with other 
specific claim data elements and provider-specific data, to adjust the 
IRF's prospective payment for interrupted stays, transfers, short 
stays, and deaths, and then applies the applicable adjustments to 
account for the IRF's wage index, percentage of low-income patients, 
rural location, and outlier payments. For discharges occurring on or 
after October 1, 2005, the IRF PPS payment also reflects the teaching 
status adjustment that became effective as of FY 2006, as discussed in 
the FY 2006 IRF PPS final rule (70 FR 47880).

D. Advancing Health Information Exchange

    The Department of Health and Human Services (HHS) has a number of 
initiatives designed to encourage and support the adoption of 
interoperable health information technology and to promote nationwide 
health information exchange to improve health care and patient access 
to their health information.
    To further interoperability in post-acute care settings, CMS and 
Office of the National Coordinator for Health Information Technology 
(ONC) participate in the Post-Acute Care Interoperability Workgroup 
(PACIO) (https://pacioproject.org/) to facilitate collaboration with 
industry stakeholders to develop FHIR standards. These standards could 
support the exchange and reuse of patient assessment data derived from 
the minimum data set (MDS), inpatient rehabilitation facility patient 
assessment instrument (IRF-PAI), long term care hospital continuity 
assessment record and evaluation (LCDS), outcome and assessment 
information set (OASIS), and other sources. The PACIO Project has 
focused on FHIR implementation guides for functional status, cognitive 
status and new use cases on advance directives and speech, and language 
pathology. We encourage post-acute care (PAC) provider and health IT 
vendor participation as these efforts advance.
    The CMS Data Element Library (DEL) continues to be updated and 
serves as the authoritative resource for PAC assessment data elements 
and their associated mappings to health IT standards such as Logical 
Observation Identifiers Names and Codes (LOINC) and Systematized 
Nomenclature of Medicine Clinical Terms (SNOMED). The DEL furthers CMS' 
goal of data standardization and interoperability. When combined with 
digital information systems that capture and maintain these coded 
elements, their standardized clinical content can reduce provider 
burden by supporting exchange of standardized healthcare data; 
supporting provider exchange of electronic health information for care 
coordination, person-centered care; and supporting real-time, data 
driven, clinical decision making. Standards in the Data Element Library 
(https://del.cms.gov/DELWeb/pubHome) can be referenced on the CMS 
website and in the ONC Interoperability Standards Advisory (ISA). The 
2021 ISA is available at https://www.healthit.gov/isa.
    The 21st Century Cures Act (Cures Act) (Pub. L. 114-255, enacted on 
December 13, 2016) requires HHS to take new steps to enable the 
electronic sharing of health information ensuring interoperability for 
providers and settings across the care continuum. The Cures Act 
includes a trusted exchange framework and common agreement (TEFCA) 
provision \3\ that will enable the nationwide exchange of electronic 
health information across health information networks and provide an 
important way to enable bi-directional health information exchange in 
the future. For more information on current developments related to 
TEFCA, we refer readers to https://www.healthit.gov/topic/interoperability/trusted-exchange-framework-and-common-agreement and 
https://rce.sequoiaproject.org/.
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    \3\ ONC, Draft 2 Trusted Exchange Framework and Common 
Agreement, https://www.healthit.gov/sites/default/files/page/2019-04/FINALTEFCAQTF41719508version.pdf.
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    The ONC final rule entitled, ``21st Century Cures Act: 
Interoperability, Information Blocking, and the ONC Health IT 
Certification Program'' final rule (85 FR 25642) published in the May 
1, 2020 Federal Register (hereinafter ``ONC Cures Act Final Rule'') 
implemented policies related to information blocking required under 
section 4003 of the 21st Century Cures Act. Information blocking is 
generally defined as a practice by a health IT developer of certified 
health IT, health information network, health information exchange, or 
health care provider that, except as required by law or specified by 
the Secretary of Health and Human Services (HHS) as a reasonable and 
necessary activity, is likely to interfere with access, exchange, or 
use of electronic health information. The definition of information 
blocking includes a knowledge standard, which is different for health 
care providers than for health IT developers of certified health IT and 
health information networks or health information exchanges. A 
healthcare provider must know that the practice is unreasonable as well 
as likely to interfere with access, exchange, or use of electronic 
health information. To deter information blocking, health IT developers 
of certified health IT, health information

[[Page 19090]]

networks and health information exchanges whom the HHS Inspector 
General determines, following an investigation, have committed 
information blocking, are subject to civil monetary penalties of up to 
$1 million per violation. Appropriate disincentives for health care 
providers need to be established by the Secretary through rulemaking. 
Stakeholders can learn more about information blocking at https://www.healthit.gov/curesrule/final-rule-policy/information-blocking. ONC 
has posted information resources including fact sheets (https://www.healthit.gov/curesrule/resources/fact-sheets), frequently asked 
questions (https://www.healthit.gov/curesrule/resources/information-blocking-faqs), and recorded webinars (https://www.healthit.gov/curesrule/resources/webinars).
    We invite providers to learn more about these important 
developments and how they are likely to affect IRFs.

III. Summary of Provisions of the Proposed Rule

    In this proposed rule, we are proposing to update the IRF PPS for 
FYs 2022 and 2023.
    The proposed policy changes and updates to the IRF prospective 
payment rates for FY 2022 are as follows:
     Update the CMG relative weights and average length of stay 
values for FY 2022, in a budget neutral manner, as discussed in section 
IV. of this proposed rule.
     Update the IRF PPS payment rates for FY 2022 by the market 
basket increase factor, based upon the most current data available, 
with a productivity adjustment required by section 1886(j)(3)(C)(ii)(I) 
of the Act, as described in section V. of this proposed rule.
     Update the FY 2022 IRF PPS payment rates by the FY 2022 
wage index and the labor-related share in a budget-neutral manner, as 
discussed in section V. of this proposed rule.
     Describe the calculation of the IRF standard payment 
conversion factor for FY 2022, as discussed in section V. of this 
proposed rule.
     Update the outlier threshold amount for FY 2022, as 
discussed in section VI. of this proposed rule.
     Update the cost-to-charge ratio (CCR) ceiling and urban/
rural average CCRs for FY 2022, as discussed in section VI. of this 
proposed rule.
    The proposed policy changes and updates to the IRF QRP for FYs 2022 
and 2023 are as follows:
     Propose revisions and updates to quality measures and 
reporting requirements under the IRF QRP, as well as make requests for 
information as discussed in section VII. of this proposed rule.

IV. Proposed Update to the Case-Mix Group (CMG) Relative Weights and 
Average Length of Stay Values for FY 2022

    As specified in Sec.  412.620(b)(1), we calculate a relative weight 
for each CMG that is proportional to the resources needed by an average 
inpatient rehabilitation case in that CMG. For example, cases in a CMG 
with a relative weight of 2, on average, will cost twice as much as 
cases in a CMG with a relative weight of 1. Relative weights account 
for the variance in cost per discharge due to the variance in resource 
utilization among the payment groups, and their use helps to ensure 
that IRF PPS payments support beneficiary access to care, as well as 
provider efficiency.
    In this proposed rule, we propose to update the CMG relative 
weights and average length of stay values for FY 2022. Typically, we 
use the most recent available data to update the CMG relative weights 
and average lengths of stay. As such, section 1886(j) of the Act 
confers broad statutory authority upon the Secretary to propose 
refinements to the IRF PPS. For FY 2022, we are proposing to use the FY 
2020 IRF claims and FY 2019 IRF cost report data. These data are the 
most current and complete data available at this time. Currently, only 
a small portion of the FY 2020 IRF cost report data are available for 
analysis, but the majority of the FY 2020 IRF claims data are available 
for analysis. We are proposing that if more recent data become 
available after the publication of this proposed rule and before the 
publication of the final rule, we would use such data to determine the 
FY 2022 CMG relative weights and average length of stay values in the 
final rule.
    We are proposing to apply these data using the same methodologies 
that we have used to update the CMG relative weights and average length 
of stay values each FY since we implemented an update to the 
methodology. The detailed CCR data from the cost reports of IRF 
provider units of primary acute care hospitals is used for this 
methodology, instead of CCR data from the associated primary care 
hospitals, to calculate IRFs' average costs per case, as discussed in 
the FY 2009 IRF PPS final rule (73 FR 46372). In calculating the CMG 
relative weights, we use a hospital-specific relative value method to 
estimate operating (routine and ancillary services) and capital costs 
of IRFs. The process to calculate the CMG relative weights for this 
proposed rule is as follows:
    Step 1. We estimate the effects that comorbidities have on costs.
    Step 2. We adjust the cost of each Medicare discharge (case) to 
reflect the effects found in the first step.
    Step 3. We use the adjusted costs from the second step to calculate 
CMG relative weights, using the hospital-specific relative value 
method.
    Step 4. We normalize the FY 2022 CMG relative weights to the same 
average CMG relative weight from the CMG relative weights implemented 
in the FY 2021 IRF PPS final rule (85 FR 48424).
    Consistent with the methodology that we have used to update the IRF 
classification system in each instance in the past, we propose to 
update the CMG relative weights for FY 2022 in such a way that total 
estimated aggregate payments to IRFs for FY 2022 are the same with or 
without the changes (that is, in a budget-neutral manner) by applying a 
budget neutrality factor to the standard payment amount. To calculate 
the appropriate budget neutrality factor for use in updating the FY 
2022 CMG relative weights, we use the following steps:
    Step 1. Calculate the estimated total amount of IRF PPS payments 
for FY 2022 (with no changes to the CMG relative weights).
    Step 2. Calculate the estimated total amount of IRF PPS payments 
for FY 2022 by applying the proposed changes to the CMG relative 
weights (as discussed in this proposed rule).
    Step 3. Divide the amount calculated in step 1 by the amount 
calculated in step 2 to determine the budget neutrality factor of 
1.0000 that would maintain the same total estimated aggregate payments 
in FY 2022 with and without the proposed changes to the CMG relative 
weights.

[[Page 19091]]

    Step 4. Apply the budget neutrality factor from step 3 to the FY 
2022 IRF PPS standard payment amount after the application of the 
budget-neutral wage adjustment factor.
    In section V.E. of this proposed rule, we discuss the proposed use 
of the existing methodology to calculate the proposed standard payment 
conversion factor for FY 2022.
    In Table 2, ``Proposed Relative Weights and Average Length of Stay 
Values for Case-Mix Groups,'' we present the proposed CMGs, the 
comorbidity tiers, the corresponding relative weights, and the average 
length of stay values for each CMG and tier for FY 2022. The average 
length of stay for each CMG is used to determine when an IRF discharge 
meets the definition of a short-stay transfer, which results in a per 
diem case level adjustment.
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    Generally, updates to the CMG relative weights result in some 
increases and some decreases to the CMG relative weight values. Table 2 
shows how we estimate that the application of the proposed revisions 
for FY 2022 would affect particular CMG relative weight values, which 
would affect the overall distribution of payments within CMGs and 
tiers. We note that, because we propose to implement the CMG relative 
weight revisions in a budget-neutral manner (as previously described), 
total estimated aggregate payments to IRFs for FY 2022 would not be 
affected as a result of the proposed CMG relative weight revisions. 
However, the proposed revisions would affect the distribution of 
payments within CMGs and tiers.
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    As shown in Table 3, 97.3 percent of all IRF cases are in CMGs and 
tiers that would experience less than a 5 percent change (either 
increase or decrease) in the CMG relative weight value as a result of 
the proposed revisions for FY 2022. The proposed changes in the average 
length of stay values for FY 2022, compared with the FY 2021 average 
length of stay values, are small and do not show any particular trends 
in IRF length of stay patterns.
    We invite public comment on our proposed updates to the CMG 
relative weights and average length of stay values for FY 2022.

V. Proposed FY 2022 IRF PPS Payment Update

A. Background

    Section 1886(j)(3)(C) of the Act requires the Secretary to 
establish an increase factor that reflects changes over time in the 
prices of an appropriate mix of goods and services for which payment is 
made under the IRF PPS. According to section 1886(j)(3)(A)(i) of the 
Act, the increase factor shall be used to update the IRF prospective 
payment rates for each FY. Section 1886(j)(3)(C)(ii)(I) of the Act 
requires the application of the productivity adjustment described in 
section 1886(b)(3)(B)(xi)(II) of the Act. Thus, in this proposed rule, 
we are proposing to update the IRF PPS payments for FY 2022 by a market 
basket increase factor as required by section 1886(j)(3)(C) of the Act 
based upon the most current data available, with a productivity 
adjustment as required by section 1886(j)(3)(C)(ii)(I) of the Act.
    We have utilized various market baskets through the years in the 
IRF PPS. For a discussion of these market baskets, we refer readers to 
the FY 2016 IRF PPS final rule (80 FR 47046).
    In FY 2016, we finalized the use of a 2012-based IRF market basket, 
using Medicare cost report (MCR) data for both freestanding and 
hospital-based IRFs (80 FR 47049 through 47068). Beginning with FY 
2020, we finalized a rebased and revised IRF market basket to reflect a 
2016 base year. The FY 2020 IRF PPS final rule (84 FR 39071 through 
39086) contains a complete discussion of the development of the 2016-
based IRF market basket.

B. Proposed FY 2022 Market Basket Update and Productivity Adjustment

    For FY 2022 (that is, beginning October 1, 2021 and ending 
September 30, 2022), we are proposing to update the IRF PPS payments by 
a market basket increase factor as required by section 1886(j)(3)(C) of 
the Act, with a productivity adjustment as required by section 
1886(j)(3)(C)(ii)(I) of the Act. For FY 2022, we are proposing to use 
the same methodology described in the FY 2021 IRF PPS final rule (85 FR 
48432 through 48433), with one proposed modification to the 2016-based 
IRF market basket.
    For the price proxy for the For-profit Interest cost category of 
the 2016-based IRF market basket, we are proposing to use the iBoxx AAA 
Corporate Bond Yield index instead of the Moody's AAA Corporate Bond 
Yield index. Effective for December 2020, the Moody's AAA Corporate 
Bond series is no longer available for use under license to IHS Global 
Inc. (IGI), the nationally-recognized economic and financial 
forecasting firm with which we contract to forecast the components of 
the market baskets and multi-factor productivity (MFP). Since IGI is no 
longer licensed to use and publish the Moody's series, IGI was required 
to discontinue the publication of the associated historical data and 
forecasts of this series. Therefore, IGI constructed a bond yield index 
(iBoxx) that closely replicates the Moody's corporate bond yield 
indices currently used in the market baskets.
    We compared the iBoxx AAA Corporate Bond Yield index with the

[[Page 19096]]

Moody's AAA Corporate Bond Yield index and found that the average 
growth rates in the history of the two series are very similar. Over 
the historical time period of FY 2001 to FY 2020, the 4-quarter percent 
change moving average growth in the iBoxx series was approximately 0.1 
percentage point higher, on average, than the Moody's series. However, 
given the relatively small weight for this cost category, replacing the 
Moody's series with the iBoxx series does not impact the historical 
top-line market basket increases when rounded to the nearest tenth of a 
percentage point over the past ten fiscal years (FY 2011 to FY 2020). 
Therefore, because the iBoxx AAA Corporate Bond Yield index captures 
the same technical concept as the current corporate bond proxy and 
tracks similarly to the current measure that is no longer available, we 
believe that using the iBoxx AAA Corporate Bond Yield index is 
technically appropriate to use in the 2016-based IRF market basket.
    Consistent with historical practice, we are proposing to estimate 
the market basket update for the IRF PPS for FY 2022 based on IGI's 
forecast using the most recent available data. Based on IGI's fourth 
quarter 2020 forecast with historical data through the third quarter of 
2020, the proposed 2016-based IRF market basket increase factor for FY 
2022 is projected to be 2.4 percent. We are also proposing that if more 
recent data become available after the publication of the proposed rule 
and before the publication of the final rule (for example, a more 
recent estimate of the market basket update), we would use such data, 
if appropriate, to determine the FY 2022 market basket update in the 
final rule.
    According to section 1886(j)(3)(C)(i) of the Act, the Secretary 
shall establish an increase factor based on an appropriate percentage 
increase in a market basket of goods and services. Section 
1886(j)(3)(C)(ii) of the Act then requires that, after establishing the 
increase factor for a FY, the Secretary shall reduce such increase 
factor for FY 2012 and each subsequent FY, by the productivity 
adjustment described in section 1886(b)(3)(B)(xi)(II) of the Act. 
Section 1886(b)(3)(B)(xi)(II) of the Act sets forth the definition of 
this productivity adjustment. The statute defines the productivity 
adjustment to be equal to the 10-year moving average of changes in 
annual economy-wide, private nonfarm business MFP (as projected by the 
Secretary for the 10-year period ending with the applicable FY, year, 
cost reporting period, or other annual period) (the ``MFP 
adjustment''). The U.S. Department of Labor's Bureau of Labor 
Statistics (BLS) publishes the official measure of private nonfarm 
business MFP. Please see https://www.bls.gov/mfp for the BLS historical 
published MFP data. A complete description of the MFP projection 
methodology is available on the CMS website at https://www.cms.gov/Research-Statistics-Dataand-Systems/Statistics-Trends-andReports/MedicareProgramRatesStats/MarketBasketResearch.html.
    Using IGI's fourth quarter 2020 forecast, the 10-year moving 
average growth of MFP for FY 2022 is projected to be 0.2 percent. Thus, 
in accordance with section 1886(j)(3)(C) of the Act, we are proposing 
to base the FY 2022 market basket update, which is used to determine 
the applicable percentage increase for the IRF payments, on IGI's 
fourth quarter 2020 forecast of the 2016-based IRF market basket. We 
are proposing to then reduce this percentage increase by the estimated 
MFP adjustment for FY 2022 of 0.2 percentage point (the 10-year moving 
average growth of MFP for the period ending FY 2022 based on IGI's 
fourth quarter 2020 forecast). Therefore, the proposed FY 2022 IRF 
update is equal to 2.2 percent (2.4 percent market basket update less 
0.2 percentage point MFP adjustment). Furthermore, if more recent data 
become available after the publication of the proposed rule and before 
the publication of the final rule (for example, a more recent estimate 
of the market basket and/or MFP), we would use such data, if 
appropriate, to determine the FY 2022 market basket update and MFP 
adjustment in the final rule.
    For FY 2022, the Medicare Payment Advisory Commission (MedPAC) 
recommends that we reduce IRF PPS payment rates by 5 percent. As 
discussed, and in accordance with sections 1886(j)(3)(C) and 
1886(j)(3)(D) of the Act, the Secretary is proposing to update the IRF 
PPS payment rates for FY 2022 by an adjusted market basket increase 
factor which, based on the most recently available data, is 2.2 
percent. Section 1886(j)(3)(C) of the Act does not provide the 
Secretary with the authority to apply a different update factor to IRF 
PPS payment rates for FY 2022.
    We invite public comment on our proposals.

C. Proposed Labor-Related Share for FY 2022

    Section 1886(j)(6) of the Act specifies that the Secretary is to 
adjust the proportion (as estimated by the Secretary from time to time) 
of IRFs' costs which are attributable to wages and wage-related costs, 
of the prospective payment rates computed under section 1886(j)(3) of 
the Act, for area differences in wage levels by a factor (established 
by the Secretary) reflecting the relative hospital wage level in the 
geographic area of the rehabilitation facility compared to the national 
average wage level for such facilities. 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 are proposing to continue to classify a cost category as 
labor-related if the costs are labor-intensive and vary with the local 
labor market.
    Based on our definition of the labor-related share and the cost 
categories in the 2016-based IRF market basket, we calculate the 
proposed labor-related share for FY 2022 as the sum of the FY 2022 
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 relative 
importance from the 2016-based IRF market basket. For more details 
regarding the methodology for determining specific cost categories for 
inclusion in the 2016-based IRF labor-related share, see the FY 2020 
IRF PPS final rule (84 FR 39087 through 39089).
    The relative importance reflects the different rates of price 
change for these cost categories between the base year (2016) and FY 
2022. Based on IGI's fourth quarter 2020 forecast of the 2016-based IRF 
market basket, the sum of the FY 2022 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 
69.0 percent. We are proposing that the portion of Capital-Related 
costs that are influenced by the local labor market is 46 percent. 
Since the relative importance for Capital-Related costs is 8.4 percent 
of the 2016-based IRF market basket for FY 2022, we are proposing to 
take 46 percent of 8.4 percent to determine the labor-related share of 
Capital-Related costs for FY 2022 of 3.9 percent. Therefore, we are 
proposing a total labor-related share for FY 2022 of 72.9 percent (the 
sum of 69.0 percent for the labor-related share of operating costs and 
3.9 percent for the labor-related share of Capital-Related costs). We 
are proposing that if more recent data become available after 
publication of this proposed rule and before the publication of the 
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[[Page 19097]]

(for example, a more recent estimate of the labor-related share), we 
will use such data, if appropriate, to determine the FY 2022 IRF labor-
related share in the final rule.
    Table 4 shows the current estimate of the proposed FY 2022 labor-
related share and the FY 2021 final labor-related share using the 2016-
based IRF market basket relative importance.
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D. Proposed Wage Adjustment for FY 2022

1. Background
    Section 1886(j)(6) of the Act requires the Secretary to adjust the 
proportion of rehabilitation facilities' costs attributable to wages 
and wage-related costs (as estimated by the Secretary from time to 
time) by a factor (established by the Secretary) reflecting the 
relative hospital wage level in the geographic area of the 
rehabilitation facility compared to the national average wage level for 
those facilities. The Secretary is required to update the IRF PPS wage 
index on the basis of information available to the Secretary on the 
wages and wage-related costs to furnish rehabilitation services. Any 
adjustment or updates made under section 1886(j)(6) of the Act for a FY 
are made in a budget-neutral manner.
    For FY 2022, we propose to maintain the policies and methodologies 
described in the FY 2021 IRF PPS final rule (85 FR 48435) related to 
the labor market area definitions and the wage index methodology for 
areas with wage data. Thus, we propose to use the core based 
statistical areas (CBSAs) labor market area definitions and the FY 2022 
pre-reclassification and pre-floor hospital wage index data. In 
accordance with section 1886(d)(3)(E) of the Act, the FY 2022 pre-
reclassification and pre-floor hospital wage index is based on data 
submitted for hospital cost reporting periods beginning on or after 
October 1, 2017, and before October 1, 2018 (that is, FY 2018 cost 
report data).
    The labor market designations made by the OMB include some 
geographic areas where there are no hospitals and, thus, no hospital 
wage index data on which to base the calculation of the IRF PPS wage 
index. We propose to continue to use the same methodology discussed in 
the FY 2008 IRF PPS final rule (72 FR 44299) to address those 
geographic areas where there are no hospitals and, thus, no hospital 
wage index data on which to base the calculation for the FY 2022 IRF 
PPS wage index.
    We invite public comment on our proposals.
2. Core-Based Statistical Areas (CBSAs) for the FY 2022 IRF Wage Index
a. Background
    The wage index used for the IRF PPS is calculated using the pre-
reclassification and pre-floor inpatient PPS (IPPS) wage index data and 
is assigned to the IRF on the basis of the labor market area in which 
the IRF is geographically located. IRF labor market areas are 
delineated based on the CBSAs established by the OMB. The CBSA 
delineations (which were implemented for the IRF PPS beginning with FY 
2016) are based on revised OMB delineations issued on February 28, 
2013, in OMB Bulletin No. 13-01. OMB Bulletin No. 13-01 established 
revised delineations for Metropolitan Statistical Areas, Micropolitan 
Statistical Areas, and Combined Statistical Areas in the United States 
and Puerto Rico based on the 2010 Census, and provided guidance on the 
use of the delineations of these statistical areas using standards 
published in the June 28, 2010 Federal Register (75 FR 37246 through 
37252). We refer readers to the FY 2016 IRF PPS final rule (80 FR 47068 
through 47076) for a full discussion of our implementation of the OMB 
labor market area delineations beginning with the FY 2016 wage index.
    Generally, OMB issues major revisions to statistical areas every 10 
years, based on the results of the decennial census. Additionally, OMB 
occasionally issues updates and revisions to the statistical areas in 
between decennial censuses to reflect the recognition of new areas or 
the addition of counties to existing areas. In some instances, these 
updates merge formerly separate areas, transfer components of an area 
from one area to another, or drop components from an area. On July 15, 
2015, OMB issued OMB Bulletin No. 15-01, which provides minor updates 
to and supersedes OMB Bulletin No. 13-01 that was issued on February 
28, 2013. The attachment to OMB Bulletin No. 15-01 provides detailed 
information on the update to statistical areas since February 28, 2013. 
The updates provided in OMB Bulletin No. 15-01 are

[[Page 19098]]

based on the application of the 2010 Standards for Delineating 
Metropolitan and Micropolitan Statistical Areas to Census Bureau 
population estimates for July 1, 2012 and July 1, 2013.
    In the FY 2018 IRF PPS final rule (82 FR 36250 through 36251), we 
adopted the updates set forth in OMB Bulletin No. 15-01 effective 
October 1, 2017, beginning with the FY 2018 IRF wage index. For a 
complete discussion of the adoption of the updates set forth in OMB 
Bulletin No. 15-01, we refer readers to the FY 2018 IRF PPS final rule. 
In the FY 2019 IRF PPS final rule (83 FR 38527), we continued to use 
the OMB delineations that were adopted beginning with FY 2016 to 
calculate the area wage indexes, with updates set forth in OMB Bulletin 
No. 15-01 that we adopted beginning with the FY 2018 wage index.
    On August 15, 2017, OMB issued OMB Bulletin No. 17-01, which 
provided updates to and superseded OMB Bulletin No. 15-01 that was 
issued on July 15, 2015. The attachments to OMB Bulletin No. 17-01 
provide detailed information on the update to statistical areas since 
July 15, 2015, and are based on the application of the 2010 Standards 
for Delineating Metropolitan and Micropolitan Statistical Areas to 
Census Bureau population estimates for July 1, 2014 and July 1, 2015. 
In the FY 2020 IRF PPS final rule (84 FR 39090 through 39091), we 
adopted the updates set forth in OMB Bulletin No. 17-01 effective 
October 1, 2019, beginning with the FY 2020 IRF wage index.
    On April 10, 2018, OMB issued OMB Bulletin No. 18-03, which 
superseded the August 15, 2017 OMB Bulletin No. 17-01, and on September 
14, 2018, OMB issued OMB Bulletin No. 18-04, which superseded the April 
10, 2018 OMB Bulletin No. 18-03. These bulletins established revised 
delineations for Metropolitan Statistical Areas, Micropolitan 
Statistical Areas, and Combined Statistical Areas, and provided 
guidance on the use of the delineations of these statistical areas. A 
copy of this bulletin may be obtained at https://www.whitehouse.gov/wp-content/uploads/2018/09/Bulletin-18-04.pdf.
    To this end, as discussed in the FY 2021 IRF PPS proposed (85 FR 
22075 through 22079) and final (85 FR 48434 through 48440) rules, we 
adopted the revised OMB delineations identified in OMB Bulletin No. 18-
04 (available at https://www.whitehouse.gov/wp-content/uploads/2018/09/Bulletin-18-04.pdf) beginning October 1, 2020, including a 1-year 
transition for FY 2021 under which we applied a 5 percent cap on any 
decrease in a hospital's wage index compared to its wage index for the 
prior fiscal year (FY 2020). The updated OMB delineations more 
accurately reflect the contemporary urban and rural nature of areas 
across the country, and the use of such delineations allows us to 
determine more accurately the appropriate wage index and rate tables to 
apply under the IRF PPS.
    OMB issued further revised CBSA delineations in OMB Bulletin No. 
20-01, on March 6, 2020 (available on the web at https://www.whitehouse.gov/wp-content/uploads/2020/03/Bulletin-20-01.pdf). 
However, we have determined that the changes in OMB Bulletin No. 20-01 
do not impact the CBSA-based labor market area delineations adopted in 
FY 2021. Therefore, CMS is not proposing to adopt the revised OMB 
delineations identified in OMB Bulletin No. 20-01 for FY 2022.
4. Proposed Wage Adjustment
    To calculate the wage-adjusted facility payment for the proposed 
payment rates set forth in this proposed rule, we would multiply the 
proposed unadjusted Federal payment rate for IRFs by the FY 2022 labor-
related share based on the 2016-based IRF market basket relative 
importance (72.9 percent) to determine the labor-related portion of the 
standard payment amount. A full discussion of the calculation of the 
labor-related share is located in section V.C. of this proposed rule. 
We would then multiply the labor-related portion by the applicable IRF 
wage index. The wage index tables are available on the CMS website at 
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientRehabFacPPS/IRF-Rules-and-Related-Files.html.
    Adjustments or updates to the IRF wage index made under section 
1886(j)(6) of the Act must be made in a budget-neutral manner. We 
propose to calculate a budget-neutral wage adjustment factor as 
established in the FY 2004 IRF PPS final rule (68 FR 45689), codified 
at Sec.  412.624(e)(1), as described in the steps below. We propose to 
use the listed steps to ensure that the FY 2022 IRF standard payment 
conversion factor reflects the proposed update to the wage indexes 
(based on the FY 2018 hospital cost report data) and the proposed 
update to the labor-related share, in a budget-neutral manner:
    Step 1. Calculate the total amount of estimated IRF PPS payments 
using the labor-related share and the wage indexes from FY 2021 (as 
published in the FY 2021 IRF PPS final rule (85 FR 48424)).
    Step 2. Calculate the total amount of estimated IRF PPS payments 
using the proposed FY 2022 wage index values (based on updated hospital 
wage data) and the proposed FY 2022 labor-related share of 72.9 
percent.
    Step 3. Divide the amount calculated in step 1 by the amount 
calculated in step 2. The resulting quotient is the proposed FY 2022 
budget-neutral wage adjustment factor of 1.0027.
    Step 4. Apply the budget neutrality factor from step 3 to the FY 
2022 IRF PPS standard payment amount after the application of the 
increase factor to determine the proposed FY 2022 standard payment 
conversion factor.
    We discuss the calculation of the proposed standard payment 
conversion factor for FY 2022 in section V.E. of this proposed rule.
    We invite public comment on the proposed IRF wage adjustment for FY 
2022.

E. Description of the Proposed IRF Standard Payment Conversion Factor 
and Payment Rates for FY 2022

    To calculate the proposed standard payment conversion factor for FY 
2022, as illustrated in Table 5, we begin by applying the proposed 
increase factor for FY 2022, as adjusted in accordance with sections 
1886(j)(3)(C) of the Act, to the standard payment conversion factor for 
FY 2021 ($16,856). Applying the proposed 2.2 percent increase factor 
for FY 2022 to the standard payment conversion factor for FY 2021 of 
$16,856 yields a standard payment amount of $17,227. Then, we apply the 
proposed budget neutrality factor for the FY 2022 wage index, and 
labor-related share of 1.0027, which results in a standard payment 
amount of $17,273. We next apply the proposed budget neutrality factor 
for the CMG relative weights of 1.0000, which results in the standard 
payment conversion factor of $17,273 for FY 2022.
    We invite public comment on the proposed FY 2022 standard payment 
conversion factor.

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    After the application of the proposed CMG relative weights 
described in section IV. of this proposed rule to the proposed FY 2022 
standard payment conversion factor ($17,273), the resulting unadjusted 
IRF prospective payment rates for FY 2022 are shown in Table 6.
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F. Example of the Methodology for Adjusting the Proposed Prospective 
Payment Rates

    Table 7 illustrates the methodology for adjusting the proposed 
prospective payments (as described in section V. of this proposed 
rule). The following examples are based on two hypothetical Medicare 
beneficiaries, both classified into CMG 0104 (without comorbidities). 
The proposed unadjusted prospective payment rate for CMG 0104 (without 
comorbidities) appears in Table 7.
    Example: One beneficiary is in Facility A, an IRF located in rural 
Spencer County, Indiana, and another beneficiary is in Facility B, an 
IRF located in urban Harrison County, Indiana. Facility A, a rural non-
teaching hospital has a Disproportionate Share Hospital (DSH) 
percentage of 5 percent (which would result in a LIP adjustment of 
1.0156), a wage index of 0.8606, and a rural adjustment of 14.9 
percent. Facility B, an urban teaching hospital, has a DSH percentage 
of 15 percent (which would result in a LIP adjustment of 1.0454 
percent), a wage index of 0.8686, and a teaching status adjustment of 
0.0784.

[[Page 19102]]

    To calculate each IRF's labor and non-labor portion of the proposed 
prospective payment, we begin by taking the unadjusted prospective 
payment rate for CMG 0104 (without comorbidities) from Table 7. Then, 
we multiply the proposed labor-related share for FY 2022 (72.9 percent) 
described in section V.C. of this proposed rule by the proposed 
unadjusted prospective payment rate. To determine the non-labor portion 
of the proposed prospective payment rate, we subtract the labor portion 
of the Federal payment from the proposed unadjusted prospective 
payment.
    To compute the proposed wage-adjusted prospective payment, we 
multiply the labor portion of the proposed federal payment by the 
appropriate wage index located in the applicable wage index table. This 
table is available on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientRehabFacPPS/IRF-Rules-and-Related-Files.html.
    The resulting figure is the wage-adjusted labor amount. Next, we 
compute the proposed wage-adjusted Federal payment by adding the wage-
adjusted labor amount to the non-labor portion of the proposed Federal 
payment.
    Adjusting the proposed wage-adjusted Federal payment by the 
facility-level adjustments involves several steps. First, we take the 
wage-adjusted prospective payment and multiply it by the appropriate 
rural and LIP adjustments (if applicable). Second, to determine the 
appropriate amount of additional payment for the teaching status 
adjustment (if applicable), we multiply the teaching status adjustment 
(0.0784, in this example) by the wage-adjusted and rural-adjusted 
amount (if applicable). Finally, we add the additional teaching status 
payments (if applicable) to the wage, rural, and LIP-adjusted 
prospective payment rates. Table 7 illustrates the components of the 
adjusted payment calculation.
[GRAPHIC] [TIFF OMITTED] TP12AP21.010

    Thus, the proposed adjusted payment for Facility A would be 
$28,961.86, and the adjusted payment for Facility B would be 
$28,072.62.

VI. Proposed Update to Payments for High-Cost Outliers Under the IRF 
PPS for FY 2022

A. Proposed Update to the Outlier Threshold Amount for FY 2022

    Section 1886(j)(4) of the Act provides the Secretary with the 
authority to make payments in addition to the basic IRF prospective 
payments for cases incurring extraordinarily high costs. A case 
qualifies for an outlier payment if the estimated cost of the case 
exceeds the adjusted outlier threshold. We calculate the adjusted 
outlier threshold by adding the IRF PPS payment for the case (that is, 
the CMG payment adjusted by all of the relevant facility-level 
adjustments) and the adjusted threshold amount (also adjusted by all of 
the relevant facility-level adjustments). Then, we calculate the 
estimated cost of a case by multiplying the IRF's overall CCR by the 
Medicare allowable covered charge. If the estimated cost of the case is 
higher than the adjusted outlier threshold, we make an outlier payment 
for the case equal to 80 percent of the difference between the 
estimated cost of the case and the outlier threshold.
    In the FY 2002 IRF PPS final rule (66 FR 41362 through 41363), we 
discussed our rationale for setting the outlier threshold amount for 
the IRF PPS so that estimated outlier payments would equal 3 percent of 
total estimated payments. For the FY 2002 IRF PPS final rule, we 
analyzed various outlier policies using 3, 4, and 5 percent of the 
total estimated payments, and we concluded that an outlier policy set 
at 3 percent of total estimated payments would optimize the extent to 
which we could reduce the financial risk to IRFs of caring for high-
cost patients, while still providing for adequate payments for all 
other (non-high cost outlier) cases.
    Subsequently, we updated the IRF outlier threshold amount in the 
FYs 2006 through 2021 IRF PPS final rules and the FY 2011 and FY 2013 
notices (70 FR 47880, 71 FR 48354, 72 FR 44284, 73 FR 46370, 74 FR 
39762, 75 FR 42836, 76 FR 47836, 76 FR 59256, 77 FR 44618, 78 FR 47860, 
79 FR 45872, 80 FR 47036, 81 FR 52056, 82 FR 36238, 83 FR 38514, 84 FR 
39054, and 85 FR 48444,

[[Page 19103]]

respectively) to maintain estimated outlier payments at 3 percent of 
total estimated payments. We also stated in the FY 2009 final rule (73 
FR 46370 at 46385) that we would continue to analyze the estimated 
outlier payments for subsequent years and adjust the outlier threshold 
amount as appropriate to maintain the 3 percent target.
    To update the IRF outlier threshold amount for FY 2022, we propose 
to use FY 2020 claims data and the same methodology that we used to set 
the initial outlier threshold amount in the FY 2002 IRF PPS final rule 
(66 FR 41316 and 41362 through 41363), which is also the same 
methodology that we used to update the outlier threshold amounts for 
FYs 2006 through 2021. The outlier threshold is calculated by 
simulating aggregate payments and using an iterative process to 
determine a threshold that results in outlier payments being equal to 3 
percent of total payments under the simulation. To determine the 
outlier threshold for FY 2022, we estimate the amount of FY 2022 IRF 
PPS aggregate and outlier payments using the most recent claims 
available (FY 2020) and the proposed FY 2022 standard payment 
conversion factor, labor-related share, and wage indexes, incorporating 
any applicable budget-neutrality adjustment factors. The outlier 
threshold is adjusted either up or down in this simulation until the 
estimated outlier payments equal 3 percent of the estimated aggregate 
payments. Based on an analysis of the preliminary data used for the 
proposed rule, we estimate that IRF outlier payments as a percentage of 
total estimated payments would be approximately 3.3 percent in FY 2021. 
Therefore, we propose to update the outlier threshold amount from 
$7,906 for FY 2021 to $9,192 for FY 2022 to maintain estimated outlier 
payments at approximately 3 percent of total estimated aggregate IRF 
payments for FY 2022.
    We invite public comment on the proposed update to the FY 2022 
outlier threshold amount to maintain estimated outlier payments at 
approximately 3 percent of total estimated IRF payments.

B. Proposed Update to the IRF Cost-to-Charge Ratio Ceiling and Urban/
Rural Averages for FY 2022

    CCRs are used to adjust charges from Medicare claims to costs and 
are computed annually from facility-specific data obtained from MCRs. 
IRF specific CCRs are used in the development of the CMG relative 
weights and the calculation of outlier payments under the IRF PPS. In 
accordance with the methodology stated in the FY 2004 IRF PPS final 
rule (68 FR 45674, 45692 through 45694), we propose to apply a ceiling 
to IRFs' CCRs. Using the methodology described in that final rule, we 
propose to update the national urban and rural CCRs for IRFs, as well 
as the national CCR ceiling for FY 2022, based on analysis of the most 
recent data available. We apply the national urban and rural CCRs in 
the following situations:
     New IRFs that have not yet submitted their first MCR.
     IRFs whose overall CCR is in excess of the national CCR 
ceiling for FY 2022, as discussed below in this section.
     Other IRFs for which accurate data to calculate an overall 
CCR are not available.
    Specifically, for FY 2022, we propose to estimate a national 
average CCR of 0.478 for rural IRFs, which we calculated by taking an 
average of the CCRs for all rural IRFs using their most recently 
submitted cost report data. Similarly, we propose to estimate a 
national average CCR of 0.393 for urban IRFs, which we calculated by 
taking an average of the CCRs for all urban IRFs using their most 
recently submitted cost report data. We apply weights to both of these 
averages using the IRFs' estimated costs, meaning that the CCRs of IRFs 
with higher total costs factor more heavily into the averages than the 
CCRs of IRFs with lower total costs. For this proposed rule, we have 
used the most recent available cost report data (FY 2019). This 
includes all IRFs whose cost reporting periods begin on or after 
October 1, 2018, and before October 1, 2019. If, for any IRF, the FY 
2019 cost report was missing or had an ``as submitted'' status, we used 
data from a previous FY's (that is, FY 2004 through FY 2018) settled 
cost report for that IRF. We do not use cost report data from before FY 
2004 for any IRF because changes in IRF utilization since FY 2004 
resulting from the 60 percent rule and IRF medical review activities 
suggest that these older data do not adequately reflect the current 
cost of care. Using updated FY 2019 cost report data for this proposed 
rule, we estimate a national average CCR of 0.478 for rural IRFs, and a 
national average CCR of 0.393 for urban IRFs.
    In accordance with past practice, we propose to set the national 
CCR ceiling at 3 standard deviations above the mean CCR. Using this 
method, we propose a national CCR ceiling of 1.34 for FY 2022. This 
means that, if an individual IRF's CCR were to exceed this ceiling of 
1.34 for FY 2022, we will replace the IRF's CCR with the appropriate 
proposed national average CCR (either rural or urban, depending on the 
geographic location of the IRF). We calculated the proposed national 
CCR ceiling by:
    Step 1. Taking the national average CCR (weighted by each IRF's 
total costs, as previously discussed) of all IRFs for which we have 
sufficient cost report data (both rural and urban IRFs combined).
    Step 2. Estimating the standard deviation of the national average 
CCR computed in step 1.
    Step 3. Multiplying the standard deviation of the national average 
CCR computed in step 2 by a factor of 3 to compute a statistically 
significant reliable ceiling.
    Step 4. Adding the result from step 3 to the national average CCR 
of all IRFs for which we have sufficient cost report data, from step 1.
    We are also proposing that if more recent data become available 
after the publication of this proposed rule and before the publication 
of the final rule, we would use such data to determine the FY 2022 
national average rural and urban CCRs and the national CCR ceiling in 
the final rule.
    We invite public comment on the proposed update to the IRF CCR 
ceiling and the urban/rural averages for FY 2022.

VII. Inpatient Rehabilitation Facility (IRF) Quality Reporting Program 
(QRP)

A. Background and Statutory Authority

    The Inpatient Rehabilitation Facility Quality Reporting Program 
(IRF QRP) is authorized by section 1886(j)(7) of the Act, and it 
applies to freestanding IRFs, as well as inpatient rehabilitation units 
of hospitals or Critical Access Hospitals (CAHs) paid by Medicare under 
the IRF PPS. Under the IRF QRP, the Secretary must reduce by 2 
percentage points the annual increase factor for discharges occurring 
during a fiscal year for any IRF that does not submit data in 
accordance with the IRF QRP requirements established by the Secretary. 
For more information on the background and statutory authority for the 
IRF QRP, we refer readers to the FY 2012 IRF PPS final rule (76 FR 
47873 through 47874), the CY 2013 Hospital Outpatient Prospective 
Payment System/Ambulatory Surgical Center (OPPS/ASC) Payment Systems 
and Quality Reporting Programs final rule (77 FR 68500 through 68503), 
the FY 2014 IRF PPS final rule (78 FR 47902), the FY 2015 IRF PPS final 
rule (79 FR 45908), the FY 2016 IRF PPS final rule (80 FR 47080 through 
47083), the FY 2017 IRF PPS final rule (81 FR 52080 through 52081), the 
FY 2018 IRF PPS final rule (82 FR 36269 through 36270),

[[Page 19104]]

the FY 2019 IRF PPS final rule (83 FR 38555 through 38556), and the FY 
2020 IRF PPS final rule (84 FR 39054 through 39165).

B. General Considerations Used for the Selection of Measures for the 
IRF QRP

    For a detailed discussion of the considerations we use for the 
selection of IRF QRP quality, resource use, or other measures, we refer 
readers to the FY 2016 IRF PPS final rule (80 FR 47083 through 47084).
1. Quality Measures Currently Adopted for the FY 2022 IRF QRP
    The IRF QRP currently has 17 measures for the FY 2022 program year, 
which are set out in Table 8.
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TP12AP21.011

BILLING CODE 4120-01-C

C. IRF QRP Quality Measure Proposals Beginning With the FY 2023 IRF QRP

    Section 1899B(h)(1) of the Act permits the Secretary to remove, 
suspend, or add quality measures or resource use or other measures 
described in sections 1899B(c)(1) and section 1899B(d)(1) of the Act 
respectively, so long as the Secretary publishes in the Federal 
Register (with a notice and comment period) a justification for such 
removal, suspension, or addition. We propose to adopt one new measure: 
The COVID-19 Vaccination Coverage among Healthcare Personnel (HCP) \4\ 
measure as an ``other'' measure under the resource use or other measure 
domain under section

[[Page 19105]]

1899B(d)(1) of the Act beginning with the FY 2023 IRF QRP. In 
accordance with section 1899B(a)(1)(B) of the Act, the data used to 
calculate this measure is standardized and interoperable. The proposed 
measure supports the Meaningful Measures domain of Promote Effective 
Prevention and Treatment of Chronic Disease. CMS identified the 
measure's concept as a priority in response to the current public 
health crisis. This process measure was developed with the Centers for 
Disease Control and Prevention (CDC) to track COVID-19 vaccination 
coverage among HCP in the IRF setting. This measure is described in 
more detail below.
---------------------------------------------------------------------------

    \4\ The measure steward changed the name of the measure from 
SARS-CoV-2 Vaccination Coverage among Healthcare Personnel to COVID-
19 Vaccination Coverage among Healthcare Personnel. There were no 
changes to the measure itself, other than the name change.
---------------------------------------------------------------------------

    In addition, we propose to update the denominator for one measure, 
the Transfer of Health (TOH) Information to the Patient-Post-Acute Care 
(PAC) measure to exclude patients discharged home under the care of an 
organized home health service or hospice.
1. Proposed COVID-19 Vaccination Coverage Among Healthcare Personnel 
(HCP) Measure Beginning With the FY 2023 IRF QRP
a. Background
    On January 31, 2020, the Secretary of the U.S. Department 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).\5\ COVID-19 is a contagious respiratory infection 
\6\ that can cause serious illness and death. Older individuals, racial 
and ethnic minorities, and those with underlying medical conditions are 
considered to be at higher risk for more serious complications from 
COVID-19.7 8 As of March 31, 2021, the U.S. reported over 30 
million cases of COVID-19 and over 548,000 COVID-19 deaths.\9\ 
Hospitals and health systems saw significant surges of COVID-19 
patients as community infection levels increased.\10\ In December 2020 
and January 2021, media outlets reported that more than 100,000 
Americans were in the hospital with COVID-19.\11\
---------------------------------------------------------------------------

    \5\ 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.
    \6\ Centers for Disease Control and Prevention. (2020). Your 
Health: Symptoms of Coronavirus. Available at https://www.cdc.gov/coronavirus/2019-ncov/symptoms-testing/symptoms.html.
    \7\ Centers for Disease Control and Prevention. (2020). Your 
Health: Symptoms of Coronavirus. Available at https://www.cdc.gov/coronavirus/2019-ncov/symptoms-testing/symptoms.html.
    \8\ Centers for Disease Control and Prevention (2021). Health 
Equity Considerations and Racial and Ethnic Minority Groups. 
Available at https://www.cdc.gov/coronavirus/2019-ncov/community/health-equity/race-ethnicity.html.
    \9\ Centers for Disease Control and Prevention. (2020). CDC 
COVID Data Tracker. Available at https://covid.cdc.gov/covid-data-tracker/#cases_casesper100klast7days.
    \10\ Associated Press. Tired to the Bone. Hospitals Overwhelmed 
with Virus Cases. November 18, 2020. Accessed on December 16, 2020, 
at https://apnews.com/article/hospitals-overwhelmed-coronavirus-cases-74a1f0dc3634917a5dc13408455cd895. Also see: New York Times. 
Just how full are U.S. intensive care units? New data paints an 
alarming picture. November 18, 2020. Accessed on December 16, 2020, 
at https://www.nytimes.com/2020/12/09/world/just-how-full-are-us-intensive-care-units-new-data-paints-an-alarming-picture.html.
    \11\ NPR. U.S. Hits 100,000 COVID-19 Hospitalizations, Breaks 
Daily Death Record. Dec. 2, 2020. Accessed on December 17, 2020 at 
https://www.npr.org/sections/coronavirus-live-updates/2020/12/02/941902471/u-s-hits-100-000-covid-19-hospitalizations-breaks-daily-death-record; The Wall Street Journal. Coronavirus Live Updates: 
U.S. Hospitalizations, Newly Reported Cases, Deaths Edge Downward. 
Accessed on January 11 at https://www.wsj.com/livecoverage/covid-2021-01-11.
---------------------------------------------------------------------------

    Evidence indicates that COVID-19 primarily spreads when individuals 
are in close contact with one another.\12\ The virus is typically 
transmitted through respiratory droplets or small particles created 
when someone who is infected with the virus coughs, sneezes, sings, 
talks or breathes.\13\ Experts believe that COVID-19 spreads less 
commonly through contact with a contaminated surface \14\ (although 
that is not thought to be a common way that COVID-19 spreads), and that 
in certain circumstances, infection can occur through airborne 
transmission.\15\ According to the CDC, those at greatest risk of 
infection are persons who have had prolonged, unprotected close contact 
(that is, within 6 feet for 15 minutes or longer) with an individual 
with confirmed SARS-CoV-2 infection, regardless of whether the 
individual has symptoms.\16\ Although personal protective equipment 
(PPE) and other infection-control precautions can reduce the likelihood 
of transmission in health care settings, COVID-19 can spread between 
health care personnel (HCP) and patients given the close contact that 
may occur during the provision of care.\17\ The CDC has emphasized that 
health care settings, including IRFs, can be high-risk places for 
COVID-19 exposure and transmission.\18\ Vaccination is a critical part 
of the nation's strategy to effectively counter the spread of COVID-19 
and ultimately help restore societal functioning.\19\
---------------------------------------------------------------------------

    \12\ Centers for Disease Control and Prevention. (2021). COVID-
19. Your Health. Frequently Asked Questions. Accessed on January 11, 
2021 at https://www.cdc.gov/coronavirus/2019-ncov/faq.html.
    \13\ Centers for Disease Control and Prevention (2021). COVID-
19. Your Health. Frequently Asked Questions. Accessed on January 11, 
2021 at https://www.cdc.gov/coronavirus/2019-ncov/faq.html.
    \14\ Centers for Disease Control and Prevention (2021). COVID-
19. Your Health. Frequently Asked Questions. Accessed on January 11, 
2021 at https://www.cdc.gov/coronavirus/2019-ncov/faq.html.
    \15\ Centers for Disease Control and Prevention. (2020). Centers 
for Disease Control Scientific Brief: SARS-CoV-2 and Potential 
Airborne Transmission. Available at https://www.cdc.gov/coronavirus/2019-ncov/more/scientific-brief-sars-cov-2.html.
    \16\ Centers for Disease Control and Prevention. (2020). 
Clinical Questions about COVID-19: Questions and Answers. Accessed 
on December 2, 2020 at https://www.cdc.gov/coronavirus/2019-ncov/hcp/faq.html.
    \17\ Centers for Disease Control and Prevention. (2020). Interim 
U.S. Guidance for Risk Assessment and Work Restrictions for 
Healthcare Personnel with Potential Exposure to COVID-19. Accessed 
on December 2 at https://www.cdc.gov/coronavirus/2019-ncov/hcp/guidance-risk-assesment-hcp.html.
    \18\ Dooling, K, McClung, M, et al. ``The Advisory Committee on 
Immunization Practices' Interim Recommendations for Allocating 
Initial Supplies of COVID-19 Vaccine--United States, 2020.'' Morb 
Mortal Wkly Rep. 2020; 69(49): 1857-1859.
    \19\ Centers for Disease Control and Prevention. (2020). COVID-
19 Vaccination Program Interim Playbook for Jurisdiction Operations. 
Accessed on December 18 at https://www.cdc.gov/vaccines/imz-managers/downloads/COVID-19-Vaccination-Program-Interim_Playbook.pdf.
---------------------------------------------------------------------------

    On December 11, 2020, the Food and Drug Administration (FDA) issued 
the first Emergency Use Authorization (EUA) for a COVID-19 vaccine in 
the United States.\20\ Subsequently, the FDA issued EUAs for additional 
COVID-19 vaccines. In issuing these EUAs, the FDA determined that it 
was reasonable to conclude that the known and potential benefits of 
each vaccine, when used as authorized to prevent COVID-19, outweighed 
its known and potential risks.21 22 23
---------------------------------------------------------------------------

    \20\ U.S. Food and Drug Administration. (2020). Pfizer-BioNTech 
COVID-19 Vaccine EUA Letter of Authorization. Available at https://www.fda.gov/media/144412/download.
    \21\ Ibid.
    \22\ U.S. Food and Drug Administration. (2021). ModernaTX, Inc. 
COVID-19 Vaccine EUA Letter of Authorization. Available at https://www.fda.gov/media/144636/download.
    \23\ U.S. Food and Drug Administration (2020). Janssen Biotech, 
Inc. COVID-19 Vaccine EUA Letter of Authorization. Available at 
https://www.fda.gov/media/146303/download.
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    As part of its national strategy to address COVID-19, the current 
administration stated that it would work with states and the private 
sector to execute an aggressive vaccination strategy and has outlined a 
goal of administering 200 million shots in 100 days.\24\ Although the 
goal of the U.S. government is to ensure that every

[[Page 19106]]

American who wants to receive a COVID-19 vaccine can receive one, 
federal agencies recommended that early vaccination efforts focus on 
those critical to the PHE response, including healthcare personnel 
(HCP),\25\ and individuals at highest risk for developing severe 
illness from COVID-19.\26\ For example, the CDC's Advisory Committee on 
Immunization Practices (ACIP) recommended that HCP should be among 
those individuals prioritized to receive the initial, limited supply of 
the COVID-19 vaccination, given the potential for transmission in 
health care settings and the need to preserve health care system 
capacity.\27\ Research suggests most states followed this 
recommendation,\28\ and HCP began receiving the vaccine in mid-December 
of 2020.\29\
---------------------------------------------------------------------------

    \24\ The White House. Remarks by President Biden on the COVID-19 
Response and the State of Vaccinations. March 29, 2021. Accessed at 
https://www.whitehouse.gov/briefing-room/speeches-remarks/2021/03/29/remarks-by-president-biden-on-the-covid-19-response-and-the-state-of-vaccinations/.
    \25\ Centers for Disease Control and Prevention. Glossary of 
Terms. https://cdc.gov/infectioncontrol/guidelines/healthcare-personnel/appendix/terminology.html.
    \26\ Health and Human Services, Department of Defense. (2020) 
From the Factory to the Frontlines: The Operation Warp Speed 
Strategy for Distributing a COVID-19 Vaccine. Accessed December 18 
at https://www.hhs.gov/sites/default/files/strategy-for-distributing-covid-19-vaccine.pdf; Centers for Disease Control 
(2020). COVID-19 Vaccination Program Interim Playbook for 
Jurisdiction Operations. Accessed December 18 at https://www.cdc.gov/vaccines/imz-managers/downloads/COVID-19-Vaccination-Program-Interim_Playbook.pdf.
    \27\ Dooling, K, McClung, M, et al. ``The Advisory Committee on 
Immunization Practices' Interim Recommendations for Allocating 
Initial Supplies of COVID-19 Vaccine--United States, 2020.'' Morb. 
Mortal Wkly Rep. 2020; 69(49): 1857-1859. ACIP also recommended that 
long-term care residents be prioritized to receive the vaccine, 
given their age, high levels of underlying medical conditions, and 
congregate living situations make them high risk for severe illness 
from COVID-19.
    \28\ Kates, J, Michaud, J, Tolbert, J. ``How Are States 
Prioritizing Who Will Get the COVID-19 Vaccine First?'' Kaiser 
Family Foundation. December 14, 2020. Accessed on December 16 at 
https://www.kff.org/policy-watch/how-are-states-prioritizing-who-will-get-the-covid-19-vaccine-first/.
    \29\ Associated Press. `Healing is Coming:' U.S. Health Workers 
Start Getting Vaccine. December 15, 2020. Accessed on December 16 at 
https://apnews.com/article/us-health-workers-coronavirus-vaccine-56df745388a9fc12ae93c6f9a0d0e81f.
---------------------------------------------------------------------------

    HCP are at risk of carrying COVID-19 infection to patients, 
experiencing illness or death as a result of COVID-19 themselves, and 
transmitting it to their families, friends, and the general public. We 
believe it is important to require that IRFs report COVID-19 HCP 
vaccination in order to assess whether they are taking steps to limit 
the spread of COVID-19 among their HCP, reduce the risk of transmission 
of COVID-19 within their facilities, and to help sustain the ability of 
IRFs to continue serving their communities throughout the PHE and 
beyond.
    We also believe that publishing facility level COVID-19 HCP 
vaccination rates on Care Compare would be helpful to many patients, 
including those who are at high-risk for developing serious 
complications from COVID-19, as they choose facilities from which to 
seek treatment. Under CMS' Meaningful Measures framework, the COVID-19 
Vaccination Coverage among Healthcare Personnel measure addresses the 
quality priority of ``Promote Effective Prevention & Treatment of 
Chronic Disease'' through the Meaningful Measures Area of ``Preventive 
Care.''
    Therefore, this rule proposes a new measure, COVID-19 Vaccination 
Coverage among HCP to assess the proportion of an IRF's healthcare 
workforce that has been vaccinated against COVID-19.
b. Stakeholder Input
    In the development and specification of the measure, a transparent 
process was employed to seek input from stakeholders and national 
experts and engage in a process that allows for pre-rulemaking input on 
each measure, under section 1890A of the Act.\30\ To meet this 
requirement, the following opportunity was provided for stakeholder 
input.
---------------------------------------------------------------------------

    \30\ Centers for Medicare & Medicaid Services. Pre-rulemaking. 
Accessed at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityMeasures/Pre-Rulemaking.
---------------------------------------------------------------------------

    The pre-rule making process includes making publicly available a 
list of quality and efficiency measures, called the Measures Under 
Consideration (MUC) List that the Secretary is considering adopting, 
through federal rulemaking process, for use in Medicare program(s). 
This allows multi-stakeholder groups to provide recommendations to the 
Secretary on the measures included on the list. The COVID-19 
Vaccination Coverage among Healthcare Personnel measure was included on 
the publicly available ``List of Measures under Consideration for 
December 21, 2020''.\31\ Five comments were received from industry 
stakeholders during the pre-rulemaking process on the COVID-19 
Vaccination Coverage among HCP measure, and support was mixed. 
Commenters generally supported the concept of the measure. However, 
there was concern about the availability of the vaccine and measure 
definition for HCP, and some commenters encouraged CMS to continue to 
update the measure as new evidence comes in.
---------------------------------------------------------------------------

    \31\ National Quality Forum. List of Measures Under 
Consideration for December 21, 2020. Accessed at https://www.cms.gov/files/document/measures-under-consideration-list-2020-report.pdf on January 12, 2021.
---------------------------------------------------------------------------

c. Measure Applications Partnership (MAP) Review
    When the Measure Applications Partnership (MAP) Post-Acute Care/
Long-Term Care (PAC-LTC) Workgroup convened on January 11, 2021, it 
reviewed the MUC List and the COVID-19 Vaccination Coverage among HCP 
measure. The MAP recognized that the proposed measure represents a 
promising effort to advance measurement for an evolving national 
pandemic and that it would bring value to the IRF QRP measure set by 
providing transparency about an important COVID-19 intervention to help 
limit COVID-19 infections.\32\ The MAP also stated that collecting 
information on COVID-19 vaccination coverage among healthcare personnel 
and providing feedback to facilities would allow facilities to 
benchmark coverage rates and improve coverage in their facility, and 
that reducing rates of COVID-19 in healthcare personnel may reduce 
transmission among patients and reduce instances of staff shortages due 
to illness.\33\
---------------------------------------------------------------------------

    \32\ Measure Applications Partnership. MAP Preliminary 
Recommendations 2020-2021. Accessed on February 3, 2021 at https://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=94650.
    \33\ Ibid.
---------------------------------------------------------------------------

    In its preliminary recommendations, the MAP PAC-LTC Workgroup did 
not support this measure for rulemaking, subject to potential for 
mitigation.\34\ To mitigate its concerns, the MAP believed that the 
measure needed well-documented evidence, finalized specifications, 
testing, and NQF endorsement prior to implementation.\35\ Subsequently, 
the MAP Coordinating Committee met on January 25, 2021, and reviewed 
the COVID-19 Vaccination Coverage among Healthcare Personnel measure. 
In the 2020-2021 MAP Final Recommendations, the MAP offered conditional 
support for rulemaking contingent on CMS bringing the measures back to 
the MAP once the specifications are further clarified. The final MAP 
report is available at https://www.qualityforum.org/Publications/2021/03/MAP_2020-2021_Considerations_for_Implementing_Measures_Final_Report_-_Clinicians,_Hospitals,_and_PAC-LTC.aspx.
---------------------------------------------------------------------------

    \34\ Ibid.
    \35\ Ibid.
---------------------------------------------------------------------------

    In response to the MAP request for CMS to bring the measure back 
once the specifications were further clarified, CMS met with the MAP 
Coordinating Committee on March 15, 2021. First,

[[Page 19107]]

CMS and CDC clarified the alignment of the COVID-19 Vaccination 
Coverage among HCP with the Influenza Vaccination Coverage among HCP 
(NQF #0431), an NQF-endorsed measure since 2012. The COVID-19 
Vaccination Coverage among HCP measure is calculated using the same 
approach as the Influenza Vaccination Coverage among HCP measure.\36\ 
The approach to identifying HCPs eligible for the COVID-19 vaccination 
is analogous to those used in the NQF endorsed flu measure which 
underwent rigorous review from technical experts about the validity of 
that approach and for which ultimately received NQF endorsement. More 
recently, prospective cohorts of health care personnel, first 
responders, and other essential and frontline workers over 13 weeks in 
eight U.S. locations confirmed that authorized COVID-19 vaccines are 
highly effective in real-world conditions. Vaccine effectiveness of 
full immunization with two doses of vaccines was 90 percent.\37\
---------------------------------------------------------------------------

    \36\ The Influenza Vaccination Coverage among Healthcare 
Personnel (NQF #0431) measure which is NQF endorsed and was adopted 
in the IRF QRP in the FY 2014 IRF PPS Final Rule (78 FR 47905 
through 47906), and in the LTCH QRP in the FY 2013 IPPS/LTCH PPS 
Final Rule (77 FR 53630 through 53631).
    \37\ Centers for Disease Control and Preventions. Morbidity and 
Mortality Weekly Report. March 29, 2021. Available at https://www.cdc.gov/mmwr/volumes/70/wr/mm7013e3.htm?s_cid=mm7013e3_w.
---------------------------------------------------------------------------

    Additionally, to support the measure's data element validity, CDC 
conducted testing of the COVID-19 vaccination numerator using data 
collected through the NHSN and independently reported through the 
Federal Pharmacy Partnership for Long-term Care Program for delivering 
vaccines to long-term care facilities. These are two completely 
independent data collection systems. In initial analyses of the first 
month of vaccination, the number of HCP vaccinated in approximately 
1,200 facilities, which had data from both systems, the number of HCP 
vaccinated was highly correlated between these two systems with a 
correlation coefficient of nearly 90 percent in the second 2 weeks of 
reporting. Of note, assessment of data element reliability may not be 
required by NQF if data element validity is demonstrated.\38\ In 
addition, for assessing the validity of new performance measure score 
(in this case, percentage COVID-19 vaccination coverage), NQF allows 
assessment by face validity (subjective determination by experts that 
the measure appears to reflect quality of care, done through a 
systematic and transparent process) \39\ and the MAP concurred with 
face validity of the measure of COVID-19 vaccination coverage. 
Materials from the March 15, 2021 MAP Coordinating Committee meeting 
are on the NQF website at https://www.qualityforum.org/ProjectMaterials.aspx?projectID=75367.
---------------------------------------------------------------------------

    \38\ National Quality Form. Key Points for Evaluating Scientific 
Acceptability. Revised January 3, 2020. https://
www.qualityforum.org/Measuring_Performance/Scientific_Methods_Panel/
Docs/
Evaluation_Guidance.aspx#:~:text=NQF%20is%20not%20prescriptive%20abou
t,reliability%20or%20validity%20testing%20results.&text=Reliability%2
0and%20validity%20must%20be,source%20and%20level%20of%20analysis).
    \39\ Ibid.
---------------------------------------------------------------------------

    This measure is not NQF endorsed, but CMS, in collaboration with 
the CDC, plans to submit the measure for NQF endorsement in the future.
d. Competing and Related Measures
    Section 1886(j)(7)(D)(i) of the Act requires that, absent an 
exception under section 1886(j)(7)(D)(ii) of the Act, measures 
specified by the Secretary under section 1886(j)(7)(D) of the Act be 
endorsed by the entity with a contract under section 1890(a) of the 
Act, currently the National Quality Forum (NQF). 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, 
section 1886(j)(7)(D)(ii) of the Act permits the Secretary to specify a 
measure that is not so endorsed, as long as due consideration is given 
to the measures that have been endorsed or adopted by a consensus 
organization identified by the Secretary. Section 1899B(e)(2)(A) of the 
Act requires that, subject to section 1899B(e)(2)(B) of the Act, each 
measure specified by the Secretary under section 1899B of the Act be 
endorsed by the entity with a contract under section 1890(a) of the 
Act. However, 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.
    The proposed COVID-19 Vaccination Coverage among HCP measure is not 
currently NQF endorsed and has not been submitted to the NQF for 
consideration, so we considered whether there are other available 
measures that assess COVID-19 vaccinations among HCP. After review of 
the NQF's consensus-endorsed measures, we were unable to identify any 
NQF endorsed measures for IRFs focused on capturing COVID-19 
vaccination coverage of HCP and we found no other feasible and 
practical measure on the topic of COVID-19 vaccination coverage among 
HCP, and we found no other feasible and practical measure on the topic 
of COVID-19 vaccination coverage among HCP. The only other vaccination 
coverage of HCP measure found was the Influenza Vaccination Coverage 
among Healthcare Personnel (NQF #0431) measure which is NQF endorsed 
and was adopted in the IRF QRP in the FY 2014 IRF PPS Final Rule (78 FR 
47905 through 47906).
    Given the novel nature of the SARS-CoV-2 virus, and the significant 
and immediate risk it poses in IRFs, we believe it is necessary to 
propose the measure as soon as possible. Therefore, after consideration 
of other available measures that assess COVID-19 vaccination rates 
among HCP, we believe the exception under section 1899B(e)(2)(B) of the 
Act applies. This proposed measure has the potential to generate 
actionable data on vaccination rates that can be used to target quality 
improvement among IRF providers.
e. Quality Measure Calculation
    The COVID-19 Vaccination Coverage among Healthcare Personnel (HCP) 
measure is a process measure developed by the CDC to track COVID-19 
vaccination coverage among HCP in facilities such as IRFs. Since this 
proposed measure is a process measure, rather than an outcome measure, 
it does not require risk-adjustment.
    The denominator would be the number of HCP eligible to work in the 
IRF for at least one day during the reporting period, excluding persons 
with contraindications to COVID-19 vaccination, that are described by 
the CDC.\40\
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    \40\ Centers for Disease Control and Prevention. Interim 
Clinical Considerations for Use of COVID-19 Vaccines Currently 
Authorized in the United Sates, Appendix B. Accessed at https://www.cdc.gov/vaccines/covid-19/info-by-product/clinical-considerations.html#Appendix-B.
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    The numerator would be the cumulative number of HCP eligible to 
work in the IRF for at least one day during the reporting period and 
who received a complete vaccination course against SARS-CoV-2. A 
complete vaccination course may require one or more doses depending on 
the specific vaccine used. The finalized measure specifications are 
available on the CDC website at https://www.cdc.gov/nhsn/nqf/.
    We propose that IRFs would submit data for the measure through the 
CDC/NHSN data collection and submission

[[Page 19108]]

framework.\41\ This framework is currently used for reporting the CAUTI 
(NQF #0138) and Influenza Vaccination Coverage among Healthcare 
Personnel (NQF #0431) measures. IRFs would use the COVID-19 vaccination 
data reporting module in the NHSN Healthcare Personnel Safety (HPS) 
Component to report the number of HCP eligible who have worked at the 
facility that week (denominator) and the number of those HCP who have 
received a completed COVID-19 vaccination course (numerator). IRFs 
would submit COVID-19 vaccination data for at least one week each 
month. If IRFs submit more than one week of data in a month, the most 
recent week's data would be used for measure calculation purposes. Each 
quarter, the CDC would calculate a summary measure of COVID-19 
vaccination coverage from the three monthly modules reported for the 
quarter. This quarterly rate would be publicly reported on the Care 
Compare website. Subsequent to the first refresh, one additional 
quarter of data would be added to the measure calculation during each 
advancing refresh, until the point four full quarters of data is 
reached. Thereafter, the measure would be reported using four rolling 
quarters of data on Care Compare.
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    \41\ Centers for Disease Control and Prevention. Surveillance 
for Weekly HCP COVID-19 Vaccination. Accessed at https://www.cdc.gov/nhsn/hps/weekly-covid-vac/ on February 10, 
2021.
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    For purposes of submitting data to CMS for the FY 2023 IRF QRP, 
IRFs would be required to submit data for the period October 1, 2021 
through December 31, 2021. Following the data submission quarter for 
the FY 2023 IRF QRP, subsequent compliance for the IRF QRP would be 
based on four quarters of such data submission. For more information on 
the measure's proposed public reporting period, we refer readers to 
section VII.G.2 of this proposed rule.
    We invite public comment on our proposal to add a new measure, 
COVID-19 Vaccination Coverage among Healthcare Personnel measure, to 
the IRF QRP beginning with the FY 2023 IRF QRP.
2. Proposed Update to the Transfer of Health (TOH) Information to the 
Patient--Post-Acute Care (PAC) Measure Beginning With the FY 2023 IRF 
QRP
    This rule proposes to update the Transfer of Health Information to 
the Patient--Post-Acute Care (PAC) measure denominator to exclude 
patients discharged home under the care of an organized home health 
service or hospice. This measure assesses for and reports on the timely 
transfer of health information, specifically transfer of a medication 
list. We adopted this measure in the FY 2020 IRF PPS final rule (84 FR 
39099 through 39107) beginning with the FY 2022 IRF QRP. It is a 
process-based measure that evaluates for the transfer of information 
when a patient is discharged from his or her current PAC setting to a 
private home/apartment, board and care home, assisted living, group 
home, transitional living, or home under the care of an organized home 
health service organization or hospice.
    This measure, adopted under section 1899B(c)(1)(E) of the Act, was 
developed to be a standardized measure for the IRF QRP, LTCH QRP, SNF 
QRP, and Home Health (HH) QRP. The measure is calculated by one 
standardized data element that asks, ``At the time of discharge, did 
the facility provide the patient's current reconciled medication list 
to the patient, family, and/or caregiver?'' The discharge location is 
captured by items on the Inpatient Rehabilitation Facility-Patient 
Assessment Instrument (IRF-PAI).
    Specifically, this rule proposes to update the measure denominator. 
Currently the measure denominators for both the TOH-Patient and the 
TOH-Provider measure assess the number of patients discharged home 
under the care of an organized home health service organization or 
hospice. In order to align the measure with the SNF QRP, LTCH QRP and 
HH QRP and avoid counting the patient in both TOH measures in the IRF 
QRP, this rule proposes to remove this location from the definition of 
the denominator for the TOH-Patient measure. Therefore, we are 
proposing to update the denominator for the TOH-Patient measure to only 
discharges to a private home/apartment, board and care home, assisted 
living, group home, or transitional living. For additional technical 
information regarding the TOH-Patient measure, we refer readers to the 
document titled ``Final Specifications for IRF QRP Quality Measures and 
Standardized Patient Assessment Data Elements (SPADEs)'' available at 
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/IRF-Quality-Reporting/Downloads/Final-Specifications-for-IRF-QRP-Quality-Measures-and-SPADEs.pdf.
    We are inviting public comment on our proposal to update the 
denominator of the Transfer of Health (TOH) Information to the 
Patient--Post-Acute Care (PAC) measure beginning with the FY 2023 IRF 
QRP.

D. IRF QRP Quality Measures Under Consideration for Future Years: 
Request for Information

    We are seeking input on the importance, relevance, appropriateness, 
and applicability of each of the measures and concepts under 
consideration listed in Table 9 for future years in the IRF QRP.
[GRAPHIC] [TIFF OMITTED] TP12AP21.012

    While we will not be responding to specific comments submitted in 
response to this Request for Information in the FY 2022 IRF PPS final 
rule, we intend to use this input to inform our future measure 
development efforts.

[[Page 19109]]

E. Fast Healthcare Interoperability Resources (FHIR) in Support of 
Digital Quality Measurement in Quality Programs--Request for 
Information

1. Background
    The IRF QRP is authorized by section 1886(j)(7) of the Act and 
furthers our mission to improve the quality of health care for 
beneficiaries through measurement, transparency, and public reporting 
of data. The IRF QRP and CMS's other quality programs are foundational 
for contributing to improvements in health care, enhancing patient 
outcomes, and informing consumer choice.
    In October 2017, we launched the Meaningful Measures Framework. 
This framework captures our vision to address health care quality 
priorities and gaps, including emphasizing digital quality measurement 
(dQM), reducing measurement burden, and promoting patient perspectives, 
while also focusing on modernization and innovation. The scope of the 
Meaningful Measures Framework has evolved to accommodate the changes in 
the health care environment, initially focusing on measure and burden 
reduction to include the promotion of innovation and modernization of 
all aspects of quality.\42\ There is a need to streamline our approach 
to data collection, calculation, and reporting to fully leverage 
clinical and patient-centered information for measurement, improvement, 
and learning.
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    \42\ Meaningful Measures 2.0: Moving from Measure Reduction to 
Modernization. Available at https://www.cms.gov/meaningful-measures-20-moving-measure-reduction-modernization.
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    In alignment with Meaningful Measures 2.0, we are seeking feedback 
on our future plans to define digital quality measures (dQMs) for the 
IRF QRP. We also are seeking feedback on the potential use of Fast 
Healthcare Interoperable Resources (FHIR) for dQMs within the IRF QRP 
aligning where possible with other quality programs. FHIR is a free and 
open source standards framework (in both commercial and government 
settings) created by Health Level Seven International (HL7[supreg]) 
that establishes a common language and process for all health 
information technology.
2. Definition of Digital Quality Measures
    We are considering adopting a standardized definition of Digital 
Quality Measures (dQMs) in alignment across quality programs, including 
the IRF QRP. We are considering in the future to propose the adoption 
within the IRF QRP the following definition: Digital Quality Measures 
(dQMs) are quality measures that use one or more sources of health 
information that are captured and can be transmitted electronically via 
interoperable systems.\43\ A dQM includes a calculation that processes 
digital data to produce a measure score or measure scores. Data sources 
for dQMs may include administrative systems, electronically submitted 
clinical assessment data, case management systems, EHRs, instruments 
(for example, medical devices and wearable devices), patient portals or 
applications (for example, for collection of patient-generated health 
data), health information exchanges (HIEs) or registries, and other 
sources. As an example, the quality measures calculated from patient 
assessment data submitted electronically to CMS would be considered 
digital quality measures.
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    \43\ Definition taken from the CMS Quality Conference 2021.
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3. Use of FHIR for Future dQMs in the IRF QRP
    One of the first areas CMS has identified relative to improving our 
digital strategy is through the use of Fast Healthcare Interoperability 
Resources (FHIR)-based standards to exchange clinical information 
through application programming interfaces (APIs), aligning with other 
programs where possible, to allow clinicians to digitally submit 
quality information one time that can then be used in many ways. We 
believe that in the future proposing such a standard within the IRF QRP 
could potentially enable collaboration and information sharing, which 
is essential for delivering high-quality care and better outcomes at a 
lower cost.
    We are currently evaluating the use of FHIR based APIs to access 
assessment data collected and maintained through the Quality 
Improvement and Evaluation System (QIES) and internet QIES (iQIES) 
health information systems and are working with healthcare standards 
organizations to assure that their evolving standards fully support our 
assessment instrument content. Further, as more IRFs are adopting EHRs, 
we are evaluating using the FHIR interfaces for accessing patient data 
(including standard assessments) directly from IRF EHRs. Accessing data 
in this manner could also enable the exchange of data for purposes 
beyond data reporting to CMS, such as care coordination further 
increasing the value of EHR investments across the healthcare 
continuum. Once providers map their EHR data to a FHIR API in standard 
FHIR formats it could be possible to send/receive the data needed for 
measures and other uses from their EHRs through FHIR APIs.
4. Future Alignment of Measures Across Reporting Programs, Federal and 
State Agencies, and the Private Sector
    We are committed to using policy levers and working with 
stakeholders to achieve interoperable data exchange and to transition 
to full digital quality measurement in our quality programs. We are 
considering the future potential development and staged implementation 
of a cohesive portfolio of dQMs across our quality programs (including 
the IRF QRP), agencies, and private payers. This cohesive portfolio 
would require, where possible, alignment of: (1) Measure concepts and 
specifications including narrative statements, measure logic, and value 
sets, and (2) the individual data elements used to build these measure 
specifications and calculate the measures. Further, the required data 
elements would be limited to standardized, interoperable elements to 
the fullest extent possible; hence, part of the alignment strategy will 
be the consideration and advancement of data standards and 
implementation guides for key data elements. We would coordinate 
closely with quality measure developers, federal and state agencies, 
and private payers to develop and to maintain a cohesive dQM portfolio 
that meets our programmatic requirements and that fully aligns across 
federal and state agencies and payers to the extent possible.
    We intend this coordination to be ongoing and allow for continuous 
refinement to ensure quality measures remain aligned with evolving 
healthcare practices and priorities (for example, patient reported 
outcomes (PROs), disparities, care coordination), and track with the 
transformation of data collection. This includes conformance with 
standards and health IT module updates, future adoption of technologies 
incorporated within the ONC Health IT Certification Program and may 
also include standards adopted by ONC (for example, to enable 
standards-based APIs). The coordination would build on the principles 
outlined in HHS' National Health Quality Roadmap.\44\ It would focus on 
the quality domains of safety, timeliness, efficiency, effectiveness, 
equitability, and patient-centeredness. It would leverage several 
existing federal and public-private efforts including our Meaningful

[[Page 19110]]

Measures 2.0 Framework; the Federal Electronic Health Record 
Modernization (DoD/VA); the Core Quality Measure Collaborative, which 
convenes stakeholders from America's Health Insurance Plans (AHIP), 
CMS, NQF, provider organizations, private payers, and consumers and 
develops consensus on quality measures for provider specialties; and 
the NQF-convened Measure Applications Partnership (MAP), which 
recommends measures for use in public payment and reporting programs. 
We would coordinate with HL7's ongoing work to advance FHIR resources 
in critical areas to support patient care and measurement such as 
social determinants of health. Through this coordination, we would 
identify which existing measures could be used or evolved to be used as 
dQMs, in recognition of current healthcare practice and priorities.
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    \44\ Department of Health and Human Services. National Health 
Quality Roadmap. May 15, 2020. Available at https://www.hhs.gov/sites/default/files/national-health-quality-roadmap.pdf.
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    This multi-stakeholder, joint federal, state, and industry effort, 
made possible and enabled by the pending advances towards true 
interoperability, would yield a significantly improved quality 
measurement enterprise. The success of the dQM portfolio would be 
enhanced by the degree to which the measures achieve our programmatic 
requirements as well as the requirements of other agencies and payers.
5. Solicitation of Comments
    We seek input on the following steps that would enable 
transformation of CMS' quality measurement enterprise to be fully 
digital:
     What EHR/IT systems do you use and do you participate in a 
health information exchange (HIE)?
     How do you currently share information with other 
providers?
     In what ways could we incentivize or reward innovative 
uses of health information technology (IT) that could reduce burden for 
post-acute care settings, including but not limited to IRFs?
     What additional resources or tools would post-acute care 
settings, including but not limited to IRFs, and health IT vendors find 
helpful to support the testing, implementation, collection, and 
reporting of all measures using FHIR standards via secure APIs to 
reinforce the sharing of patient health information between care 
settings?
     Would vendors, including those that service post-acute 
care settings, such as IRFs, be interested in or willing to participate 
in pilots or models of alternative approaches to quality measurement 
that would align standards for quality measure data collection across 
care settings to improve care coordination, such as sharing patient 
data via secure FHIR API as the basis for calculating and reporting 
digital measures?
    We plan to continue working with other agencies and stakeholders to 
coordinate and to inform our transformation to dQMs leveraging health 
IT standards. While we will not be responding to specific comments 
submitted in response to this Request for Information in the FY 2022 
IRF PPS final rule, we will actively consider all input as we develop 
future regulatory proposals or future subregulatory policy guidance. 
Any updates to specific program requirements related to quality 
measurement and reporting provisions would be addressed through 
separate and future notice- and-comment rulemaking, as necessary.

F. Closing the Health Equity Gap in Post-Acute Care Quality Reporting 
Programs--Request for Information

1. Background
    Significant and persistent inequities in health outcomes exist in 
the United States. In recognition of persistent health disparities and 
the importance of closing the health equity gap, we request information 
on revising several CMS programs to make reporting of health 
disparities based on social risk factors and race and ethnicity more 
comprehensive and actionable for providers and patients. 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; or being near or below the poverty level is often associated 
with worse health outcomes.45 46 47 48 We are committed to 
achieving health equity by improving data collection to better measure 
and analyze disparities across programs and 
policies.49 50 51 52 53 54 Such disparities in health 
outcomes are the result of a number of factors, but importantly for CMS 
programs, although not the sole determinant, poor access and provision 
of lower quality health care contribute to health disparities. For 
instance, numerous studies have shown that among Medicare 
beneficiaries, racial and ethnic minority individuals often receive 
lower quality of care, report lower experiences of care, and experience 
more frequent hospital readmissions and operative 
complications.55 56 57 58 59 60 Readmission rates for common 
conditions in the Hospital Readmissions Reduction Program are higher 
for black Medicare beneficiaries and higher for Hispanic Medicare 
beneficiaries with Congestive Heart Failure and Acute Myocardial 
Infarction.61 62 63 64 65 Studies have also

[[Page 19111]]

shown that African Americans are significantly more likely than white 
Americans to die prematurely from heart disease and stroke.\66\ The 
COVID-19 pandemic has further illustrated many of these longstanding 
health inequities with higher rates of infection, hospitalization, and 
mortality among black, Latino, and Indigenous and Native American 
persons relative to white persons.67 68 As noted by the 
Centers for Disease Control ``long-standing systemic health and social 
inequities have put many people from racial and ethnic minority groups 
at increased risk of getting sick and dying from COVID-19''.\69\ One 
important strategy for addressing these important inequities is by 
improving data collection to allow for better measurement and reporting 
on equity across post-acute care programs and policies.
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    \45\ Joynt KE, Orav E, Jha AK. Thirty-Day Readmission Rates for 
Medicare Beneficiaries by Race and Site of Care. JAMA. 2011; 
305(7):675-681.
    \46\ Lindenauer PK, Lagu T, Rothberg MB, et al. Income 
Inequality and 30 Day Outcomes After Acute Myocardial Infarction, 
Heart Failure, and Pneumonia: Retrospective Cohort Study. British 
Medical Journal. 2013; 346.
    \47\ Trivedi AN, Nsa W, Hausmann LRM, et al. Quality and Equity 
of Care in U.S. Hospitals. New England Journal of Medicine. 2014; 
371(24):2298-2308.
    \48\ Polyakova, M., et al. Racial Disparities In Excess All-
Cause Mortality During The Early COVID-19 Pandemic Varied 
Substantially Across States. Health Affairs. 2021; 40(2): 307-316.
    \49\ Centers for Medicare & Medicaid Services. CMS Quality 
Strategy. 2016. Available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/Downloads/CMS-Quality-Strategy.pdf.
    \50\ Report to Congress: Improving Medicare Post-Acute Care 
Transformation (IMPACT) Act of 2014 Strategic Plan for Accessing 
Race and Ethnicity Data. January 5, 2017. Available at https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/Research-Reports-2017-Report-to-Congress-IMPACT-ACT-of-2014.pdf.
    \51\ Rural Health Research Gateway. Rural Communities: Age, 
Income, and Health Status. Rural Health Research Recap. November 
2018.
    \52\ https://www.minorityhealth.hhs.gov/assets/PDF/Update_HHS_Disparities_Dept-FY2020.pdf.
    \53\ www.cdc.gov/mmwr/volumes/70/wr/mm7005a1.htm.
    \54\ Poteat TC, Reisner SL, Miller M, Wirtz AL. COVID-19 
Vulnerability of Transgender Women With and Without HIV Infection in 
the Eastern and Southern U.S. Preprint. medRxiv. 
2020;2020.07.21.20159327. Published 2020 Jul 24. doi:10.1101/
2020.07.21.20159327.
    \55\ Martino, SC, Elliott, MN, Dembosky, JW, Hambarsoomian, K, 
Burkhart, Q, Klein, DJ, Gildner, J, and Haviland, AM. Racial, 
Ethnic, and Gender Disparities in Health Care in Medicare Advantage. 
Baltimore, MD: CMS Office of Minority Health. 2020.
    \56\ Guide to Reducing Disparities in Readmissions. CMS Office 
of Minority Health. Revised August 2018. Available at https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/OMH_Readmissions_Guide.pdf.
    \57\ Singh JA, Lu X, Rosenthal GE, Ibrahim S, Cram P. Racial 
disparities in knee and hip total joint arthroplasty: An 18-year 
analysis of national Medicare data. Ann Rheum Dis. 2014 
Dec;73(12):2107-15.
    \58\ Rivera-Hernandez M, Rahman M, Mor V, Trivedi AN. Racial 
Disparities in Readmission Rates among Patients Discharged to 
Skilled Nursing Facilities. J Am Geriatr Soc. 2019 Aug;67(8):1672-
1679.
    \59\ Joynt KE, Orav E, Jha AK. Thirty-Day Readmission Rates for 
Medicare Beneficiaries by Race and Site of Care. JAMA. 
2011;305(7):675-681.
    \60\ Tsai TC, Orav EJ, Joynt KE. Disparities in surgical 30-day 
readmission rates for Medicare beneficiaries by race and site of 
care. Ann Surg. Jun 2014;259(6):1086-1090.
    \61\ Rodriguez F, Joynt KE, Lopez L, Saldana F, Jha AK. 
Readmission rates for Hispanic Medicare beneficiaries with heart 
failure and acute myocardial infarction. Am Heart J. Aug 
2011;162(2):254-261 e253.
    \62\ Centers for Medicare and Medicaid Services. Medicare 
Hospital Quality Chartbook: Performance Report on Outcome Measures; 
2014.
    \63\ Guide to Reducing Disparities in Readmissions. CMS Office 
of Minority Health. Revised August 2018. Available at https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/OMH_Readmissions_Guide.pdf.
    \64\ Prieto-Centurion V, Gussin HA, Rolle AJ, Krishnan JA. 
Chronic obstructive pulmonary disease readmissions at minority-
serving institutions. Ann Am Thorac Soc. Dec 2013;10(6):680-684.
    \65\ Joynt KE, Orav E, Jha AK. Thirty-Day Readmission Rates for 
Medicare Beneficiaries by Race and Site of Care. JAMA. 
2011;305(7):675-681.
    \66\ HHS. Heart disease and African Americans. (March 29, 2021). 
https://www.minorityhealth.hhs.gov/omh/browse.aspx?lvl=4&lvlid=19.
    \67\ https://www.cms.gov/files/document/medicare-covid-19-data-snapshot-fact-sheet.pdf.
    \68\ Ochieng N, Cubanski J, Neuman T, Artiga S, and Damico A. 
Racial and Ethnic Health Inequities and Medicare. Kaiser Family 
Foundation. February 2021. Available at https://www.kff.org/medicare/report/racial-and-ethnic-health-inequities-and-medicare/.
    \69\ https://www.cdc.gov/coronavirus/2019-ncov/community/health-equity/race-ethnicity.html.
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    We are also committed to achieving equity in health care outcomes 
for our beneficiaries by supporting providers in quality improvement 
activities to reduce health inequities, enabling them to make more 
informed decisions, and promoting provider accountability for health 
care disparities.70 71 For the purposes of this rule, we are 
using a definition of equity established in Executive Order 13985, as 
``the consistent and systematic fair, just, and impartial treatment of 
all individuals, including individuals who belong to underserved 
communities that have been denied such treatment, such as Black, 
Latino, and Indigenous and Native American persons, Asian Americans and 
Pacific Islanders and other persons of color; members of religious 
minorities; lesbian, gay, bisexual, transgender, and queer (LGBTQ+) 
persons; persons with disabilities; persons who live in rural areas; 
and persons otherwise adversely affected by persistent poverty or 
inequality.'' \72\ We note that this definition was recently 
established by the current administration, and provides a useful, 
common definition for equity across different areas of government, 
although numerous other definitions of equity exist.
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    \70\ https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/Downloads/CMS-Quality-Strategy.pdf.
    \71\ Report to Congress: Improving Medicare Post-Acute Care 
Transformation (IMPACT) Act of 2014 Strategic Plan for Accessing 
Race and Ethnicity Data. January 5, 2017. Available at https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/Research-Reports-2017-Report-to-Congress-IMPACT-ACT-of-2014.pdf.
    \72\ https://www.federalregister.gov/documents/2021/01/25/2021-01753/advancing-racial-equity-and-support-for-underserved-communities-through-the-federal-government.
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    Our ongoing commitment to closing the equity gap in CMS quality 
programs is demonstrated by a portfolio of programs aimed at making 
information on the quality of health care providers and services, 
including disparities, more transparent to consumers and providers. The 
CMS Equity Plan for Improving Quality in Medicare outlines a path to 
equity which aims to support Quality Improvement Networks and Quality 
Improvement Organizations (QIN-QIOs); federal, state, local, and tribal 
organizations; providers; researchers; policymakers; beneficiaries and 
their families; and other stakeholders in activities to achieve health 
equity. The CMS Equity Plan includes three core elements: (1) 
Increasing understanding and awareness of disparities; (2) developing 
and disseminating solutions to achieve health equity; and (3) 
implementing sustainable actions to achieve health equity.\73\ The CMS 
Quality Strategy and Meaningful Measures Framework \74\ include 
elimination of racial and ethnic disparities as a central principle. 
Our ongoing commitment to closing the health equity gap in the IRF QRP 
is demonstrated by the adoption of standardized patient assessment data 
elements (SPADEs) which include several social determinants of health 
(SDOH) that were finalized in the FY 2020 IRF PPS final rule for the 
IRF QRP (84 FR 39149 through 39161).
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    \73\ Centers for Medicare & Medicaid Services Office of Minority 
Health. The CMS Equity Plan for Improving Quality in Medicare. 
https://www.cms.gov/About-CMS/Agency-Information/OMH/OMH_Dwnld-CMS_EquityPlanforMedicare_090615.pdf.
    \74\ https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/MMF/General-info-Sub-Page.
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    We continue to work with federal and private partners to better 
leverage data on social risk to improve our understanding of how these 
factors can be better measured in order to close the health equity gap. 
Among other things, we have developed an Inventory of Resources for 
Standardized Demographic and Language Data Collection \75\ and 
supported collection of specialized International Classification of 
Disease, 10th Edition, Clinical Modification (ICD-10-CM) codes for 
describing the socioeconomic, cultural, and environmental determinants 
of health. We continue to work to improve our understanding of this 
important issue and to identify policy solutions that achieve the goals 
of attaining health equity for all patients.
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    \75\ Centers for Medicare and Medicaid Services. Building an 
Organizational Response to Health Disparities Inventory of Resources 
for Standardized Demographic and Language Data Collection. 2020. 
https://www.cms.gov/About-CMS/Agency-Information/OMH/Downloads/Data-Collection-Resources.pdf.
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2. Solicitation of Public Comment
    Under authority of the IMPACT Act and section 1886(j)(7) of the 
Act, we are seeking comment on the possibility of revising measure 
development, and the collection of other SPADEs that address gaps in 
health equity in the IRF QRP. Any potential health equity data 
collection or measure reporting within a CMS program that might result 
from public comments received in response to this solicitation would be 
addressed through a separate notice-and-comment rulemaking in the 
future.
    Specifically, we are inviting public comment on the following:
     Recommendations for quality measures or measurement 
domains that address health equity, for use in the IRF QRP.
     As finalized in the FY 2020 IRF PPS Final Rule (84 FR 
39149 through 39161), IRFs must report certain standardized patient 
assessment data (SPADEs) on SDOH, including race, ethnicity, preferred 
language, interpreter services, health literacy, transportation and 
social isolation.\76\ CMS is seeking guidance on any additional items, 
including SPADEs that could be used to assess health equity in the care 
of IRF patients, for use in the IRF QRP.
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    \76\ In response to the COVID-19 PHE, CMS released an Interim 
Final Rule (85 FR 27595 through 27597) which delayed the compliance 
date for the collection and reporting of the SDOH for at least one 
full fiscal year after the end of the PHE.
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     Recommendations for how CMS can promote health equity in 
outcomes among IRF patients. For example, we are interested in feedback 
regarding whether including facility-level quality measure results 
stratified by social risk

[[Page 19112]]

factors and social determinants of health (for example, dual 
eligibility for Medicare and Medicaid, race) in confidential feedback 
reports could allow facilities to identify gaps in the quality of care 
they provide. (For example, methods similar or analogous to the CMS 
Disparity Methods \77\ which provide hospital-level confidential 
results stratified by dual eligibility for condition-specific 
readmission measures which are currently included in the Hospital 
Readmission Reduction Program (see 84 FR 42496 through 42500)).
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    \77\ https://qualitynet.cms.gov/inpatient/measures/disparity-methods/methodology.
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     Methods that commenters or their organizations use in 
employing data to reduce disparities and improve patient outcomes, 
including the source(s) of data used, as appropriate.
     Given the importance of structured data and health IT 
standards for the capture, use, and exchange of relevant health data 
for improving health equity, the existing challenges providers 
encounter for effective capture, use, and exchange of health 
information, such as data on race, ethnicity, and other social 
determinants of health, to support care delivery and decision making.
    While we will not be responding to specific comments submitted in 
response to this Request for Information in the FY 2022 IRF PPS final 
rule, we intend to use this input to inform future policy development. 
We look forward to receiving feedback on these topics, and note for 
readers that responses to the RFI should focus on how they could be 
applied to the quality reporting program requirements. Please note that 
any responses provided will not impact payment decisions.

G. Form, Manner, and Timing of Data Submission Under the IRF QRP

1. Background
    We refer readers to the regulatory text at 42 CFR[thinsp]412.634(b) 
for information regarding the current policies for reporting IRF QRP 
data.
2. Proposed Schedule for Data Submission of the COVID-19 Vaccination 
Coverage Among Healthcare Personnel Measure With the FY 2023 IRF QRP
    As discussed in section VII.C.1 of this proposed rule, we are 
proposing to adopt the COVID-19 Vaccination Coverage among HCP measure 
beginning with the FY 2023 IRF QRP. Given the time-sensitive nature of 
this measure in light of the PHE, this rule proposes an initial data 
submission period from October 1, 2021 through December 31, 2021. 
Starting in CY 2022, IRFs would be required to submit data for the 
entire calendar year beginning with the FY 2024 IRF QRP.
    IRFs would submit data for the measure through the CDC/NHSN web-
based surveillance system. IRFs currently utilize the NHSN for purposes 
of meeting other IRF QRP requirements.\78\ IRFs would use the COVID-19 
vaccination data reporting module in the NHSN Healthcare Personnel 
Safety (HPS) Component to report the cumulative number of HCP eligible 
to work in the healthcare facility for at least 1 day during the 
reporting period, excluding persons with contraindications to COVID-19 
vaccination (denominator) and the cumulative number of HCP eligible to 
work in the IRF for at least 1 day during the reporting period and who 
received a complete vaccination course against COVID-19 (numerator). 
IRFs would submit COVID-19 vaccination data through the NHSN for at 
least one week each month and the CDC would report to CMS quarterly.
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    \78\ Centers for Disease Control and Prevention. Surveillance 
for Weekly HCP COVID-19 Vaccination. Accessed at https://www.cdc.gov/nhsn/hps/weekly-covid-vac/ on February 10, 
2021.
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    We invite public comment on this proposal.

H. Proposed Policies Regarding Public Display of Measure Data for the 
IRF QRP

1. Background
    Section 1886(j)(7)(E) of the Act requires the Secretary to 
establish procedures for making the IRF QRP data available to the 
public after ensuring that IRFs have the opportunity to review their 
data prior to public display. IRF QRP measure data are currently 
displayed on the Inpatient Rehabilitation Facilities website within 
Care Compare and the Provider Data Catalog. Both Care Compare and the 
Provider Data Catalog replaced IRF Compare and Data.Medicare.gov, which 
were both retired in December 2020. For a more detailed discussion 
about our policies regarding public display of IRF QRP measure data and 
procedures for the opportunity to review and correct data and 
information, we refer readers to the FY 2017 IRF PPS final rule (81 FR 
52125 through 52131).
2. Proposal for Public Reporting of the COVID-19 Vaccination Coverage 
Among Healthcare Personnel (HCP) Measure Beginning With the FY 2023 IRF 
QRP
    We propose to publicly report the COVID-19 Vaccination Coverage 
among Healthcare Personnel (HCP) measure beginning with the September 
2022 Care Compare refresh or as soon as technically feasible based on 
data collected for Q4 2021 (October 1, 2021 through December 31, 2021). 
If finalized as proposed, an IRF's HCP COVID-19 vaccination coverage 
rates would be displayed based on one quarter of data updated 
quarterly. Subsequent to this, one additional quarter of data would be 
added to the measure calculation during each advancing refresh, until 
the point four full quarters of data is reached. Thereafter, the 
measure would be reported using four rolling quarters of data.
    We invite public comment on the proposal for the public display of 
the measure, COVID-19 Vaccination Coverage among HCP.
3. Proposals for Public Reporting of Quality Measures in the IRF QRP 
With Fewer Quarters Due to COVID-19 Public Health Emergency (PHE) 
Exemptions
a. COVID-19 Public Health Emergency Temporary Exemptions
    Under the authority of section 319 of the Public Health Service 
Act, the Secretary of Health and Human Services declared a public 
health emergency (PHE) effective as of January 27, 2020. On March 13, 
2020, subsequent to a presidential declaration of national emergency 
under the Stafford Act, the Secretary invoked section 1135(b) of the 
Act (42 U.S.C. 1320b-5) to waive or modify the requirements of titles 
XVIII, XIX, and XXI of the Act and regulations related to the PHE for 
COVID-19, effective as of March 1, 2020.\79\ On March 27, 2020, we sent 
a guidance memorandum under the subject title, ``Exceptions and 
Extensions for Quality Reporting Requirements for Acute Care Hospitals, 
PPS-Exempt Cancer Hospitals, Inpatient Psychiatric Facilities, Skilled 
Nursing Facilities, Home Health Agencies, Hospices, Inpatient 
Rehabilitation Facilities, Long-Term Care Hospitals, Ambulatory 
Surgical Centers, Renal Dialysis Facilities, and MIPS Eligible 
Clinicians Affected by COVID-19'' to the Medicare Learning Network 
(MLN) Connects

[[Page 19113]]

Newsletter and Other Program-Specific Listserv Recipients,\80\ 
hereafter referred to as the March 27, 2020 CMS Guidance Memo. In that 
memo we granted an exception to the IRF QRP reporting requirements from 
Q4 2019 (October 1, 2019-December 31, 2019), Q1 2020 (January 1, 2020-
March 31, 2020), and Q2 2020 (April 1, 2020-June 30, 2020). We also 
stated that we would not publicly report any IRF QRP data that might be 
greatly impacted by the exceptions from Q1 and Q2 of 2020. This 
exception impacted the schedule for public reporting that would have 
included those two quarters of data.
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    \79\ https://www.phe.gov/emergency/news/healthactions/section1135/Pages/covid19-13March20.aspx.
    \80\ https://www.cms.gov/files/document/guidance-memo-exceptions-and-extensions-quality-reporting-and-value-based-purchasing-programs.pdf.
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    IRF quality measures are publicly reported on Care Compare. Care 
Compare uses four quarters of data for IRF-PAI assessment-based 
measures and eight quarters for claims-based measures. Table 10 
displays the original schedule for public reporting of IRF QRP 
measures.\81\
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    \81\ More information about the IRF QRP Public Reporting 
schedule can be found on the IRF QRP Public Reporting website at 
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/IRF-Quality-Reporting/IRF-Quality-Public-Reporting.
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    During 2020, we conducted testing to inform decisions about 
publicly reporting data for those refreshes, which include partially 
and/or fully exempt data (discussed below). The testing helped us 
develop a plan for posting data that are as up-to-date as possible and 
that also meet acceptable standards for public reporting. We believe 
that the plan allows us to provide consumers with helpful information 
on the quality of IRF care, while also making the necessary adjustments 
to accommodate the exemption provided IRFs. The following sections 
provide the results of our testing, and explains how we used the 
results to develop plans for accommodating exempt and partially-exempt 
data in public reporting.
b. Exempted Quarters
    In the March 27, 2020, Medicare Learning Network (MLN) Newsletter 
on Exceptions and Extensions for Quality Reporting Program (QRP) 
Requirements, we stated that we would not report any PAC quality data 
that might be greatly impacted by the exemptions granted for Quarter 1 
and Quarter 2 of 2020. Given the timing of the PHE onset, we determined 
that we would not use IRF-PAI assessments or IRF claims from Quarter 1 
and Quarter 2 of 2020 for public reporting, but that we would assess 
the COVID-19 PHE impact on data from Quarter 4 2019. Before proceeding 
with the December 2020 refresh, we conducted testing to ensure that, 
despite the voluntary nature of reporting for that quarter, public 
reporting would still meet our public reporting standards. We found the 
level of reporting, measured in the number of eligible stays and 
providers, and the reported outcomes, to be in line with

[[Page 19114]]

levels and trends observed in FY 2018 and FY 2019. We note that Quarter 
4 2019 ended before the onset of the COVID-19 pandemic in the United 
States. Thus, we proceeded with including these data in IRF QRP measure 
calculations for the December 2020 refresh.
c. Update on Data Freeze and Proposal for December 2021 Public 
Reporting Methodology for IRF Claims-Based and IRF-PAI Assessment-Based 
Measures
    In addition to the March 2021 refresh, there are several other 
forthcoming refreshes for which the original public reporting schedules 
included exempted quarters of IRF QRP data. The impacted refreshes for 
IRF-PAI assessment and claims based measures are outlined above (Table 
10). We determined that freezing the data displayed on the website with 
the December 2020 refresh values--that is, hold data constant after the 
December 2020 refresh data on the website without subsequent update--
would be the most straightforward, efficient, and equitable approach 
for IRFs. Thus, we decided that, for as many refreshes as necessary, we 
would hold data constant on the website with the December 2020 data, 
and communicate this decision to the public.
    Because December 2020 refresh data will become increasingly out-of-
date and thus less useful for consumers, we analyzed whether it would 
be possible to use fewer quarters of data for one or more refreshes and 
thus reduce the number of refreshes that continue to display December 
2020 data. Using fewer quarters of more up-to-date data requires that: 
(1) A sufficient percentage of IRFs would still likely have enough 
assessment data to report quality measures (reportability); and (2) 
fewer quarters would likely produce similar measure scores for 
providers, with similar reliability, and thus not unfairly represent 
the quality of care IRFs provide during the period reported in a given 
refresh (reliability).
    To assess these criteria, we conducted reportability and 
reliability analysis using 3 quarters of data in a refresh, instead of 
the standard 4 quarters of data for reporting assessment-based measures 
and using 6 quarters instead of 8 for claims-based measures. 
Specifically, we used historical data to calculate IRF-PAI assessment-
based and IRF claims-based measures under two scenarios:
    (1) Standard Public Reporting (SPR) Base Scenario: We used four 
quarters of CY 2019 data as a proxy alternative for the exempted 
quarters in CY 2020 in order to compare results. For assessment-based 
measures, the quarters used in this scenario are Q1 through Q4 2019. 
For claims-based measures, the quarters used in this scenario are Q1 
2018 through Q4 2019.
    (2) COVID-19 Affected Reporting (CAR) Scenario: We calculated IRF 
QRP measures using 3 quarters (Q2 2019 through Q4 2019) of IRF QRP data 
for assessment-based measures, and 6 quarters (Q1 2018 through Q4 2018 
and Q3 2019 through Q4 2019) for claims-based measures. The CAR 
scenario uses the most recently available data to simulate the public 
health emergency reality where quarters 1 and 2 of a calendar year must 
be excluded from calculation. Quarterly trends in IRF-PAI assessment-
based and IRF claims-based measures indicate that these measures do not 
exhibit substantial seasonal variation.
    To assess performance in these scenarios, we calculated the 
reportability as the percent of IRFs meeting the case minimum for 
public reporting (the public reporting threshold). To test the 
reliability of restricting the IRFs included in the SPR Base Scenario 
to those included in the CAR Scenario, we performed three tests on the 
set of IRFs included in both scenarios. First, we evaluated measure 
correlation using the Pearson and Spearman correlation coefficients, 
which assess the alignment of IRFs' provider scores. Second, for each 
scenario, we conducted a split-half reliability analysis and estimated 
intraclass correlation (ICC) scores, where higher scores imply better 
internal reliability. Modest differences in ICC scores between both 
scenarios would suggest that using fewer quarters of data does not 
impact the internal reliability of the results. Third, we estimated 
reliability scores where a higher value indicates that measure scores 
are relatively consistent for patients admitted to the same IRF and 
variation in the measure reflects true differences across providers. To 
calculate the reliability results, we restricted the IRFs included in 
the SPR scenario included in the CAR scenario.
    Our testing indicated that the expected impact of using fewer 
quarters of data on reportability and reliability of IRF-PAI 
assessment-based measures and IRF claims-based measures is acceptable.
    We are proposing to use the CAR scenario as the approach for the 
following affected refreshes: For IRF-PAI assessment-based measures, 
the affected refresh is the December 2021 refresh; for claims-based 
measures, the affected refreshes occur from December 2021 through June 
2023. For the earlier three affected refreshes (March, June, and 
September 2021), we decided to hold constant the Care Compare website 
with December 2020 data. We communicated this decision in a Public 
Reporting Tip Sheet, which is located at https://www.cms.gov/files/document/irfqrp-covid19prtipsheet-october-2020.pdf.
    Our proposal of the CAR approach for the affected refreshes would 
allow us to begin displaying more recent data in December 2021, rather 
than continue displaying December 2020 data (Q1 2019 through Q4 2019 
for assessment-based measures, Q4 2017 through Q3 2019 for claims-based 
measures). We believe that resuming public reporting refreshes starting 
in December 2021 with fewer quarters of data can assist consumers by 
providing more recent quality data as well as more actionable data for 
IRF providers. Our testing results indicate we can achieve these 
positive impacts with acceptable changes in reportability and 
reliability. Table 11 summarizes the revised schedule (that is, frozen 
data) and the proposed schedule (that is, using fewer quarters in the 
affected refreshes) for assessment-based measures. Table 12 summarizes 
the revised schedule (that is, frozen data) and the proposed schedule 
(that is, using fewer quarters in the affected refreshes) for claims-
based measures.
    We invite public comments on the proposal to use the CAR scenario 
to publicly report IRF measures for the December 2021-June 2023 
refreshes.
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[GRAPHIC] [TIFF OMITTED] TP12AP21.015

d. Update on Data Freeze and Proposal for December 2021 Public 
Reporting Methodology for NHSN-Based Measures
    CDC recommends using the four most recent non-contiguous non-
exempted quarters of data for NHSN reporting in the IRF QRP. This non-
contiguous compilation of quarterly reporting would continue until the 
time when four contiguous quarters of reporting resumes (based on CDC's 
review, this would occur in July 2022). Tables 13 and 14 display the 
original schedules for public reporting of IRF CDI NHSN and CAUTI NHSN 
measures and the HCP Influenza NHSN measure, respectively. Tables 15 
and 16 summarize the revised schedule and the proposed schedules for 
IRF CDI and CAUTI NHSN measures and the HCP Influenza measure, 
respectively.

[[Page 19116]]

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[[Page 19117]]


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BILLING CODE 4120-01-C

VIII. Collection of Information Requirements

    Under the Paperwork Reduction Act of 1995 (PRA), we are required to 
provide 60-day notice in the Federal Register and solicit public 
comment before a collection of information requirement is submitted to 
the OMB for review and approval. 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; and
     Recommendations to minimize the information collection 
burden on the affected public, including automated collection 
techniques.
    This proposed rule does not impose any new information collection 
requirements as outlined in the regulation. However, this proposed rule 
does make reference to an associated information collection that is not 
discussed in the regulation text contained in this document. The 
following is a discussion of this information collection, which has 
already received OMB approval.
    As stated in section VII.C. of this proposed rule, for purposes of 
calculating the IRF Annual Increase Factor (AIF), we propose that IRFs 
submit data on one new quality measure: COVID-19 Vaccination Coverage 
among Healthcare Personnel (HCP) beginning with the FY 2023 IRF QRP. 
The aforementioned measure will be collected via the following means.

A. COVID-19 Vaccination Coverage Among Healthcare Personnel (HCP) 
Measure

    The data source for this quality measure is the Centers for Disease 
Control and Prevention (CDC)/National Healthcare Safety Network (NHSN). 
Data collection by the NHSN occurs via a web-based tool hosted by the 
CDC. This reporting service is provided free of charge to healthcare 
facilities, including IRFs. IRFs currently utilize the NHSN for 
purposes of meeting other IRF QRP requirements.
    We note that the CDC would account for the burden associated with 
the COVID-19 Vaccination Coverage among HCP measure collection under 
OMB control number 0920-1317 (expiration 1/31/2024). Currently, the CDC 
does not estimate burden for COVID-19 vaccination reporting under the 
CDC PRA package currently approved under OMB control number 0920-1317 
because the agency has been granted a waiver under section 321 of the 
National Childhood Vaccine Injury Act of 1986 (Pub. L. 99-660, enacted 
on November 14, 1986 (NCVIA).\82\ However, we refer readers to section 
X.C.7. of this proposed rule, where CMS has provided an estimate of the 
burden and cost to IRFs, and the CDC will include it in a revised 
information collection request for 0920-1317.
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    \82\ Section 321 of the NCVIA provides the PRA waiver for 
activities that come under the NCVIA, including those in the NCVIA 
at section 2102 of the Public Health Service Act (42 U.S.C. 300aa-
2). Section 321 is not codified in the U.S. Code, but can be found 
in a note at 42 U.S.C. 300aa-1.
---------------------------------------------------------------------------

    In section VII.C.2. of this proposed rule, we are proposing to 
update the Transfer of Health (TOH) Information to the Patient--Post-
Acute Care (PAC) measure to exclude residents discharged home under the 
care of an organized home health service or hospice. This measure was 
adopted in the FY 2020 IRF PPS final rule (84 FR 39099 through 39107) 
and burden accounted for in OMB control number 0938-0842 (expiration 
December 31, 2022). The proposed update would not affect the 
information collection burden already established.
    If you comment on these information collection requirements, that 
is, reporting, recordkeeping or third-party disclosure requirements, 
please submit your comments as specified in the ADDRESSES section of 
this proposed rule.
    Comments must be received on/by June 7, 2021.

IX. Response to Comments

    Because of the large number of public comments we normally receive 
on Federal Register documents, we are not able to acknowledge or 
respond to them individually. We will consider all comments we receive 
by the date and time specified in the DATES section of this preamble, 
and, when we proceed with a subsequent document, we will respond to the 
comments in the preamble to that document.

X. Regulatory Impact Analysis

A. Statement of Need

    This proposed rule would update the IRF prospective payment rates 
for FY 2022 as required under section 1886(j)(3)(C) of the Act and in 
accordance with section 1886(j)(5) of the Act, which requires the 
Secretary to publish in the Federal Register on or before August 1 
before each FY, the classification and weighting factors for CMGs used 
under the IRF PPS for such

[[Page 19118]]

FY and a description of the methodology and data used in computing the 
prospective payment rates under the IRF PPS for that FY. This proposed 
rule would also implement section 1886(j)(3)(C) of the Act, which 
requires the Secretary to apply a MFP adjustment to the market basket 
increase factor for FY 2012 and subsequent years.
    Furthermore, this proposed rule would adopt policy changes under 
the statutory discretion afforded to the Secretary under section 
1886(j) of the Act.

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), the Regulatory Flexibility Act (RFA) (September 19, 
1980, Pub. L. 96-354), section 1102(b) of the Social Security Act, 
section 202 of the Unfunded Mandates Reform Act of 1995 (March 22, 
1995; Pub. L. 104-4), Executive Order 13132 on Federalism (August 4, 
1999), and the Congressional Review Act (5 U.S.C. 804(2)).
    Executive Orders 12866 and 13563 direct agencies to assess all 
costs and benefits of available regulatory alternatives and, if 
regulation is necessary, to select regulatory approaches that maximize 
net benefits (including potential economic, environmental, public 
health and safety effects, distributive impacts, and equity). Section 
3(f) of Executive Order 12866 defines a ``significant regulatory 
action'' as an action that is likely to result in a rule: (1) Having an 
annual effect on the economy of $100 million or more in any 1 year, or 
adversely and materially affecting a sector of the economy, 
productivity, competition, jobs, the environment, public health or 
safety, or state, local or tribal governments or communities (also 
referred to as ``economically significant''); (2) creating a serious 
inconsistency or otherwise interfering with an action taken or planned 
by another agency; (3) materially altering the budgetary impacts of 
entitlement grants, user fees, or loan programs or the rights and 
obligations of recipients thereof; or (4) raising novel legal or policy 
issues arising out of legal mandates, the President's priorities, or 
the principles set forth in Executive Order 12866.
    Section (6)(a) of Executive Order 12866 provides that a regulatory 
impact analysis (RIA) must be prepared for major rules with 
economically significant effects ($100 million or more in any 1 year). 
We estimate the total impact of the policy updates described in this 
proposed rule by comparing the estimated payments in FY 2022 with those 
in FY 2021. This analysis results in an estimated $160 million increase 
for FY 2022 IRF PPS payments. Additionally, we estimate that costs 
associated with the proposal to update the reporting requirements under 
the IRF QRP result in an estimated $487,338.96 addition to costs in FY 
2022 for IRFs. We estimate that this rulemaking is ``economically 
significant'' as measured by the $100 million threshold, and hence also 
a major rule under the Congressional Review Act. Also, the rule has 
been reviewed by OMB. Accordingly, we have prepared an RIA that, to the 
best of our ability, presents the costs and benefits of the rulemaking.

C. Anticipated Effects

1. Effects on IRFs
    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 IRFs and most other providers and 
suppliers are small entities, either by having revenues of $8.0 million 
to $41.5 million or less in any 1 year depending on industry 
classification, or by being nonprofit organizations that are not 
dominant in their markets. (For details, see the Small Business 
Administration's final rule that set forth size standards for health 
care industries, at 65 FR 69432 at https://www.sba.gov/sites/default/files/2019-08/SBA%20Table%20of%20Size%20Standards_Effective%20Aug%2019%2C%202019_Rev.pdf, effective January 1, 2017 and updated on August 19, 2019.) Because 
we lack data on individual hospital receipts, we cannot determine the 
number of small proprietary IRFs or the proportion of IRFs' revenue 
that is derived from Medicare payments. Therefore, we assume that all 
IRFs (an approximate total of 1,109 IRFs, of which approximately 54 
percent are nonprofit facilities) are considered small entities and 
that Medicare payment constitutes the majority of their revenues. HHS 
generally uses a revenue impact of 3 to 5 percent as a significance 
threshold under the RFA. As shown in Table 17, we estimate that the net 
revenue impact of this proposed rule on all IRFs is to increase 
estimated payments by approximately 1.8 percent. The rates and policies 
set forth in this proposed rule will not have a significant impact (not 
greater than 3 percent) on a substantial number of small entities. The 
estimated impact on small entities is shown in Table 17. MACs are not 
considered to be small entities. Individuals and states are not 
included in the definition of a small entity.
    In addition, section 1102(b) of the Act requires us to prepare an 
RIA 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 603 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 shown in Table 17, we estimate that the net revenue 
impact of this proposed rule on rural IRFs is to increase estimated 
payments by approximately 1.9 percent based on the data of the 133 
rural units and 12 rural hospitals in our database of 1,109 IRFs for 
which data were available. We estimate an overall impact for rural IRFs 
in all areas between 0.4 percent and 3.4 percent. As a result, we 
anticipate this proposed rule would have a positive impact on a 
substantial number of small rural hospitals.
    Section 202 of the Unfunded Mandates Reform Act of 1995 (Pub. L. 
104-04, enacted on March 22, 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 2021, that threshold is 
approximately $158 million. This proposed rule does not mandate any 
requirements for State, local, or tribal governments, or for the 
private sector.
    Executive Order 13132 establishes certain requirements that an 
agency must meet when it issues a proposed rule (and subsequent final 
rule) that imposes substantial direct requirement costs on state and 
local governments, preempts state law, or otherwise has federalism 
implications. As stated, this proposed rule would not have a 
substantial effect on state and local governments, preempt state law, 
or otherwise have a federalism implication.
2. Detailed Economic Analysis
    This proposed rule would update the IRF PPS rates contained in the 
FY 2021 IRF PPS final rule (85 FR 48424). Specifically, this proposed 
rule would update the CMG relative weights and average length of stay 
values, the wage

[[Page 19119]]

index, and the outlier threshold for high-cost cases. This proposed 
rule would apply a MFP adjustment to the FY 2022 IRF market basket 
increase factor in accordance with section 1886(j)(3)(C)(ii)(I) of the 
Act.
    We estimate that the impact of the changes and updates described in 
this proposed rule would be a net estimated increase of $160 million in 
payments to IRF providers. The impact analysis in Table 17 of this 
proposed rule represents the projected effects of the updates to IRF 
PPS payments for FY 2022 compared with the estimated IRF PPS payments 
in FY 2021. We determine the effects by estimating payments while 
holding all other payment variables constant. We use the best data 
available, but we do not attempt to predict behavioral responses to 
these changes, and we do not make adjustments for future changes in 
such variables as number of discharges or case-mix.
    We note that certain events may combine to limit the scope or 
accuracy of our impact analysis, because such an analysis is future-
oriented and, thus, susceptible to forecasting errors because of other 
changes in the forecasted impact time period. Some examples could be 
legislative changes made by the Congress to the Medicare program that 
would impact program funding, or changes specifically related to IRFs. 
Although some of these changes may not necessarily be specific to the 
IRF PPS, the nature of the Medicare program is such that the changes 
may interact, and the complexity of the interaction of these changes 
could make it difficult to predict accurately the full scope of the 
impact upon IRFs.
    In updating the rates for FY 2022, we are proposing standard annual 
revisions described in this proposed rule (for example, the update to 
the wage index and market basket increase factor used to adjust the 
Federal rates). We are also implementing a productivity adjustment to 
the FY 2022 IRF market basket increase factor in accordance with 
section 1886(j)(3)(C)(ii)(I) of the Act. We estimate the total increase 
in payments to IRFs in FY 2022, relative to FY 2021, would be 
approximately $160 million.
    This estimate is derived from the application of the FY 2022 IRF 
market basket increase factor, as reduced by a productivity adjustment 
in accordance with section 1886(j)(3)(C)(ii)(I) of the Act, which 
yields an estimated increase in aggregate payments to IRFs of $190 
million. However, there is an estimated $30 million decrease in 
aggregate payments to IRFs due to the proposed update to the outlier 
threshold amount. Therefore, we estimate that these updates would 
result in a net increase in estimated payments of $160 million from FY 
2021 to FY 2022.
    The effects of the proposed updates that impact IRF PPS payment 
rates are shown in Table 17. The following proposed updates that affect 
the IRF PPS payment rates are discussed separately below:
     The effects of the proposed update to the outlier 
threshold amount, from approximately 3.3 percent to 3.0 percent of 
total estimated payments for FY 2022, consistent with section 
1886(j)(4) of the Act.
     The effects of the proposed annual market basket update 
(using the IRF market basket) to IRF PPS payment rates, as required by 
sections 1886(j)(3)(A)(i) and (j)(3)(C) of the Act, including a 
productivity adjustment in accordance with section 1886(j)(3)(C)(i)(I) 
of the Act.
     The effects of applying the proposed budget-neutral labor-
related share and wage index adjustment, as required under section 
1886(j)(6) of the Act.
     The effects of the proposed budget-neutral changes to the 
CMG relative weights and average LOS values under the authority of 
section 1886(j)(2)(C)(i) of the Act.
     The total change in estimated payments based on the FY 
2022 payment changes relative to the estimated FY 2021 payments.
3. Description of Table 17
    Table 17 shows the overall impact on the 1,109 IRFs included in the 
analysis.
    The next 12 rows of Table 17 contain IRFs categorized according to 
their geographic location, designation as either a freestanding 
hospital or a unit of a hospital, and by type of ownership; all urban, 
which is further divided into urban units of a hospital, urban 
freestanding hospitals, and by type of ownership; and all rural, which 
is further divided into rural units of a hospital, rural freestanding 
hospitals, and by type of ownership. There are 964 IRFs located in 
urban areas included in our analysis. Among these, there are 662 IRF 
units of hospitals located in urban areas and 302 freestanding IRF 
hospitals located in urban areas. There are 145 IRFs located in rural 
areas included in our analysis. Among these, there are 133 IRF units of 
hospitals located in rural areas and 12 freestanding IRF hospitals 
located in rural areas. There are 404 for-profit IRFs. Among these, 
there are 370 IRFs in urban areas and 34 IRFs in rural areas. There are 
597 non-profit IRFs. Among these, there are 507 urban IRFs and 90 rural 
IRFs. There are 108 government-owned IRFs. Among these, there are 87 
urban IRFs and 21 rural IRFs.
    The remaining four parts of Table 17 show IRFs grouped by their 
geographic location within a region, by teaching status, and by DSH 
patient percentage (PP). First, IRFs located in urban areas are 
categorized for their location within a particular one of the nine 
Census geographic regions. Second, IRFs located in rural areas are 
categorized for their location within a particular one of the nine 
Census geographic regions. In some cases, especially for rural IRFs 
located in the New England, Mountain, and Pacific regions, the number 
of IRFs represented is small. IRFs are then grouped by teaching status, 
including non-teaching IRFs, IRFs with an intern and resident to 
average daily census (ADC) ratio less than 10 percent, IRFs with an 
intern and resident to ADC ratio greater than or equal to 10 percent 
and less than or equal to 19 percent, and IRFs with an intern and 
resident to ADC ratio greater than 19 percent. Finally, IRFs are 
grouped by DSH PP, including IRFs with zero DSH PP, IRFs with a DSH PP 
less than 5 percent, IRFs with a DSH PP between 5 and less than 10 
percent, IRFs with a DSH PP between 10 and 20 percent, and IRFs with a 
DSH PP greater than 20 percent.
    The estimated impacts of each policy described in this rule to the 
facility categories listed are shown in the columns of Table 17. The 
description of each column is as follows:
     Column (1) shows the facility classification categories.
     Column (2) shows the number of IRFs in each category in 
our FY 2022 analysis file.
     Column (3) shows the number of cases in each category in 
our FY 2022 analysis file.
     Column (4) shows the estimated effect of the proposed 
adjustment to the outlier threshold amount.
     Column (5) shows the estimated effect of the proposed 
update to the IRF labor-related share and wage index, in a budget-
neutral manner.
     Column (6) shows the estimated effect of the proposed 
update to the CMG relative weights and average LOS values, in a budget-
neutral manner.
     Column (7) compares our estimates of the payments per 
discharge, incorporating all of the policies reflected in this proposed 
rule for FY 2022 to our estimates of payments per discharge in FY 2021.
    The average estimated increase for all IRFs is approximately 1.8 
percent. This estimated net increase includes the effects of the 
proposed IRF market basket increase factor for FY 2022 of 2.2 percent 
update based on a IRF-specific

[[Page 19120]]

market basket estimate of 2.4 percent, less a 0.2 percentage point MFP 
adjustment, as required by section 1886(j)(3)(C)(ii)(I) of the Act. It 
also includes the approximate 0.3 percent overall decrease in estimated 
IRF outlier payments from the proposed update to the outlier threshold 
amount. Since we are making the updates to the IRF wage index, labor-
related share and the CMG relative weights in a budget-neutral manner, 
they will not be expected to affect total estimated IRF payments in the 
aggregate. However, as described in more detail in each section, they 
will be expected to affect the estimated distribution of payments among 
providers.
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BILLING CODE 4120-01-C
4. Impact of the Proposed Update to the Outlier Threshold Amount
    The estimated effects of the proposed update to the outlier 
threshold adjustment are presented in column 4 of Table 17.
    For this proposed rule, we are using preliminary FY 2020 IRF claims 
data, and, based on that preliminary analysis, we estimated that IRF 
outlier payments as a percentage of total estimated IRF payments would 
be 3.3 percent in FY 2022. Thus, we propose to adjust the outlier 
threshold amount in this

[[Page 19122]]

proposed rule to maintain total estimated outlier payments equal to 3 
percent of total estimated payments in FY 2022. The estimated change in 
total IRF payments for FY 2022, therefore, includes an approximate 0.3 
percentage point decrease in payments because the estimated outlier 
portion of total payments is estimated to decrease from approximately 
3.3 percent to 3 percent.
    The impact of this proposed outlier adjustment update (as shown in 
column 4 of Table 17) is to decrease estimated overall payments to IRFs 
by a 0.3 percentage point.
5. Impact of the Proposed Wage Index and Labor-Related Share
    In column 5 of Table 17, we present the effects of the proposed 
budget-neutral update of the wage index and labor-related share. The 
proposed changes to the wage index and the labor-related share are 
discussed together because the wage index is applied to the labor-
related share portion of payments, so the proposed changes in the two 
have a combined effect on payments to providers. As discussed in 
section V.C. of this proposed rule, we are proposing to update the 
labor-related share from 73.0 percent in FY 2021 to 72.9 percent in FY 
2022.
6. Impact of the Proposed Update to the CMG Relative Weights and 
Average LOS Values
    In column 7 of Table 17, we present the effects of the proposed 
budget-neutral update of the CMG relative weights and average LOS 
values. In the aggregate, we do not estimate that these proposed 
updates will affect overall estimated payments of IRFs. However, we do 
expect these updates to have small distributional effects.
7. Effects of Proposed Requirements for the IRF QRP for FY 2022
    In accordance with section 1886(j)(7)(A) of the Act, the Secretary 
must reduce by 2 percentage points the annual market basket increase 
factor otherwise applicable to an IRF for a fiscal year if the IRF does 
not comply with the requirements of the IRF QRP for that fiscal year. 
In section VII.A of this proposed rule, we discuss the method for 
applying the 2 percentage point reduction to IRFs that fail to meet the 
IRF QRP requirements. As discussed in section VII.C. of this proposed 
rule, we are proposing to add one measure to the IRF QRP beginning with 
the FY 2023 IRF QRP: COVID-19 Vaccination Coverage among Healthcare 
Personnel (HCP) measure.
    We believe that the burden associated with the IRF QRP is the time 
and effort associated with complying with the requirements of the IRF 
QRP. The proposed IRF QRP requirements add no additional burden to the 
active collection under OMB control number 0938-0842 (expiration 12/31/
2022). Currently, the CDC does not estimate burden for COVID-19 
vaccination reporting under the CDC PRA package currently approved 
under OMB control number 0920-1317 because the agency has been granted 
a waiver under section 321 of the NCVIA. However, CMS has provided an 
estimate of burden and cost for IRFs here, and the CDC will include it 
in a revised information collection request for 0920-1317. Consistent 
with the CDC's experience of collecting data using the NHSN, we 
estimate that it would take each IRF an average of 1 hour per month to 
collect data for the COVID-19 Vaccination Coverage among HCP measure 
and enter it into NHSN. We have estimated the time to complete this 
entire activity, since it could vary based on provider systems and 
staff availability. We believe it would take an administrative 
assistant from 45 minutes up to 1 hour and 15 minutes to enter this 
data into NHSN. For the purposes of calculating the costs associated 
with the collection of information requirements, we obtained mean 
hourly wages from the U.S. Bureau of Labor Statistics' May 2019 
National Occupational Employment and Wage Estimates.\83\ To account for 
overhead and fringe benefits, we have doubled the hourly wage. These 
amounts are detailed in Table 18.
---------------------------------------------------------------------------

    \83\ https://www.bls.gov/oes/current/oes_nat.htm. Accessed on 
March 30, 2021.
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    Based on the time range, it would cost each IRF between $27.47 and 
$45.78 each month or an average cost of $36.62 each month, and between 
$329.64 and $549.36 each year. We believe the data submission for the 
COVID-19 Vaccination Coverage among HCP measure would cause IRFs to 
incur additional average burden of 12 hours per year for each IRF and a 
total annual burden of 13,308 hours across all IRFs. The estimated 
annual cost across all 1,109 IRFs in the U.S. for the submission of the 
COVID-19 Vaccination Coverage among HCP measure would range from 
$365,570.76 and $609,240.24 with an average of $487,338.96.
    We recognize that many IRFs may also be reporting other COVID-19 
data to HHS. However, we believe the benefits of reporting data on the 
COVID-19 Vaccination Coverage among HCP measure to assess whether IRFs 
are taking steps to limit the spread of COVID-19 among their HCP, 
reduce the risk of transmission of COVID-19 within their facilities, 
and to help sustain the ability of IRFs to continue serving their 
communities throughout the PHE and beyond outweigh the costs of 
reporting. We welcome comments on the estimated time to collect data 
and enter it into NHSN.
D. Alternatives Considered
    The following is a discussion of the alternatives considered for 
the IRF PPS updates contained in this proposed rule.
    Section 1886(j)(3)(C) of the Act requires the Secretary to update 
the IRF PPS payment rates by an increase factor that reflects changes 
over time in the prices of an appropriate mix of goods

[[Page 19123]]

and services included in the covered IRF services.
    As noted previously in this proposed rule, section 
1886(j)(3)(C)(ii)(I) of the Act requires the Secretary to apply a 
productivity adjustment to the market basket increase factor for FY 
2022. Thus, in accordance with section 1886(j)(3)(C) of the Act, we 
propose to update the IRF prospective payments in this proposed rule by 
2.2 percent (which equals the 2.4 percent estimated IRF market basket 
increase factor for FY 2022 reduced by a 0.2 percentage point 
productivity adjustment as determined under section 
1886(b)(3)(B)(xi)(II) of the Act (as required by section 
1886(j)(3)(C)(ii)(I) of the Act)).
    We considered utilizing FY 2019 claims data to update the 
prospective payment rates for FY 2022 due to the potential effects of 
the PHE on the FY 2020 IRF claims data. However, it has been our long-
standing practice to utilize the most recent full fiscal year of data 
to update the prospective payment rates, as this data is generally 
considered to be the best overall predictor of experience in the 
upcoming fiscal year. Additionally, the FY 2019 data does not reflect 
any of the changes to the CMG definitions or the data used to classify 
IRF patients into CMGs that became effective in FY 2020 and will 
continue to be used in FY 2022. As such, we believe it would be 
appropriate to utilize FY 2020 data to update the prospective payment 
rates for FY 2022 at this time. While we believe maintaining our 
existing methodology of utilizing the most recent available IRF data to 
update the prospective payment rates for FY 2022 is appropriate, we are 
soliciting comment on the use of FY 2019 data to update the prospective 
payment rates for FY 2022.
    Table 19 shows the estimated effects of the use of FY 2019 data on 
particular aspects of the proposed FY 2022 IRF PPS compared to those 
utilizing FY 2020 data.
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    A comparison of the estimated impacts, using FY 2019 data, as shown 
in Table 20, or FY 2020 data, as shown in Table 17, indicates that 
overall IRF PPS payments and payments to all subgroups of IRF providers 
would increase if either data set is used. However, there will be 
distributional payment effects across providers due to the difference 
in estimated outlier payments under both scenarios. For more 
information on the estimated effects of utilizing FY 2019 to update the 
prospective payment rates for FY 2022, we refer readers to Table 20.
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BILLING CODE 4120-01-C
    We welcome comments from stakeholders regarding the use of FY 2019 
claims data to update the prospective payment rates for FY 2022.
    We considered maintaining the existing CMG relative weights and 
average length of stay values for FY

[[Page 19125]]

2022. However, in light of recently available data and our desire to 
ensure that the CMG relative weights and average length of stay values 
are as reflective as possible of recent changes in IRF utilization and 
case mix, at this time we believe that it is appropriate to propose to 
update the CMG relative weights and average length of stay values using 
FY 2020 claims data to ensure that IRF PPS payments continue to reflect 
as accurately as possible the current costs of care in IRFs.
    We also considered maintaining the existing outlier threshold 
amount for FY 2022. As outlier payments are a redistribution of 
payment, it is important to adjust the outlier threshold amount to 
maintain the targeted 3 percent outlier pool as closely as possible. 
Maintaining an outlier threshold that would yield estimated outlier 
payments greater than 3 percent would leave less payment available to 
cover the costs of non-outlier cases. Therefore, analysis of updated FY 
2020 data indicates that estimated outlier payments would be greater 
than 3 percent of total estimated payments for FY 2022, by 
approximately 0.3 percent. Consequently, we propose adjusting the 
outlier threshold amount in this proposed rule to reflect a 0.3 percent 
decrease thereby setting the total outlier payments equal to 3 percent, 
instead of 3.3 percent, of aggregate estimated payments in FY 2022.

E. Regulatory Review Costs

    If regulations impose administrative costs on private entities, 
such as the time needed to read and interpret this proposed rule, we 
should estimate the cost associated with regulatory review. Due to the 
uncertainty involved with accurately quantifying the number of entities 
that will review the rule, we assume that the total number of unique 
commenters on the FY 2021 IRF PPS proposed rule will be the number of 
reviewers of this proposed rule. We acknowledge that this assumption 
may understate or overstate the costs of reviewing this proposed rule. 
It is possible that not all commenters reviewed the FY 2021 IRF PPS 
proposed rule in detail, and it is also possible that some reviewers 
chose not to comment on the FY 2021 proposed rule. For these reasons, 
we thought that the number of past commenters would be a fair estimate 
of the number of reviewers of this proposed rule.
    We also recognize that different types of entities are in many 
cases affected by mutually exclusive sections of this proposed rule, 
and therefore, for the purposes of our estimate we assume that each 
reviewer reads approximately 50 percent of the rule. We sought comments 
on this assumption.
    Using the national mean hourly wage data from the May 2019 BLS for 
Occupational Employment Statistics (OES) for medical and health service 
managers (SOC 11-9111), we estimate that the cost of reviewing this 
rule is $110.74 per hour, including overhead and fringe benefits 
(https://www.bls.gov/oes/current/oes_nat.htm). Assuming an average 
reading speed, we estimate that it would take approximately 2 hours for 
the staff to review half of this proposed rule. For each IRF that 
reviews the rule, the estimated cost is $221.48 (2 hours x $110.74). 
Therefore, we estimate that the total cost of reviewing this regulation 
is $590,908.64 ($221.48 x 2,668 reviewers).

F. Accounting Statement and Table

    As required by OMB Circular A-4 (available at https://www.whitehouse.gov/sites/whitehouse.gov/files/omb/circulars/A4/a-4.pdf), in Table 21, we have prepared an accounting statement showing 
the classification of the expenditures associated with the provisions 
of this proposed rule. Table 21 provides our best estimate of the 
increase in Medicare payments under the IRF PPS as a result of the 
proposed updates presented in this proposed rule based on the data for 
1,109 IRFs in our database.
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G. Conclusion

    Overall, the estimated payments per discharge for IRFs in FY 2022 
are projected to increase by 1.8 percent, compared with the estimated 
payments in FY 2021, as reflected in column 7 of Table 17.
    IRF payments per discharge are estimated to increase by 1.8 percent 
in urban areas and 1.9 percent in rural areas, compared with estimated 
FY 2021 payments. Payments per discharge to rehabilitation units are 
estimated to increase 1.5 percent in urban areas and 1.7 percent in 
rural areas. Payments per discharge to freestanding rehabilitation 
hospitals are estimated to increase 2.1 percent in urban areas and 
increase 2.7 percent in rural areas.
    Overall, IRFs are estimated to experience a net increase in 
payments as a result of the proposed policies in this proposed rule. 
The largest payment increase is estimated to be a 3.4 percent increase 
for rural IRFs located in the rural South Atlantic region. The analysis 
above, together with the remainder of this preamble, provides an RIA.
    In accordance with the provisions of Executive Order 12866, this 
regulation was reviewed by OMB.


[[Page 19126]]


    Dated: March 29, 2021.
Elizabeth Richter,
Acting Administrator, Centers for Medicare & Medicaid Services.
    Dated: April 6, 2021.
Xavier Becerra,
Secretary, Department of Health and Human Services.
[FR Doc. 2021-07343 Filed 4-7-21; 4:15 pm]
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