[Federal Register Volume 88, Number 67 (Friday, April 7, 2023)]
[Proposed Rules]
[Pages 20950-21014]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2023-06968]



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Vol. 88

Friday,

No. 67

April 7, 2023

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 2024 and Updates to the IRF Quality 
Reporting Program; Proposed Rule

  Federal Register / Vol. 88 , No. 67 / Friday, April 7, 2023 / 
Proposed Rules  

[[Page 20950]]


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DEPARTMENT OF HEALTH AND HUMAN SERVICES

Centers for Medicare & Medicaid Services

42 CFR Part 412

[CMS-1781-P]
RIN 0938-AV04


Medicare Program; Inpatient Rehabilitation Facility Prospective 
Payment System for Federal Fiscal Year 2024 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 proposes updates to the prospective payment 
rates for inpatient rehabilitation facilities (IRFs) for Federal fiscal 
year (FY) 2024. As required by statute, this proposed rule includes the 
proposed 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 proposed prospective payment rates for 
FY 2024. It also proposes to rebase and revise the IRF market basket to 
reflect a 2021 base year. It also would modify the regulation regarding 
when IRF units can become excluded and paid under the IRF PPS. This 
proposed rule also includes updates 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 2, 2023.

ADDRESSES: In commenting, please refer to file code CMS-1781-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 http://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-1781-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-1781-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.
    Kim Schwartz, (410) 786-2571, and Gwendolyn Johnson, (410) 786-
6954, for information about the IRF coverage policies.
    Ariel Cress, (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: http://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 rulemaking proposes updates to the prospective payment rates 
for IRFs for FY 2024 (that is, for discharges occurring on or after 
October 1, 2023, and on or before September 30, 2024) 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 2024. It also proposes 
to rebase and revise the IRF market basket to reflect a 2021 base year. 
It also proposes to modify the regulation governing when an IRF unit 
can be excluded and paid under the IRF PPS. This proposed rule includes 
IRF QRP proposals for the FY 2025 IRF QRP and FY 2026 IRF QRP. This 
proposed rule would add two new measures to the IRF QRP, remove three 
measures from the IRF QRP, and modify one measure in the IRF QRP. This 
proposed rule also proposes to begin public reporting of four measures. 
In addition, this proposed rule includes an update on the Centers for 
Medicare and Medicaid Services' (CMS') efforts to close the health 
equity gap and requests information on principles CMS would use to 
select and prioritize IRF QRP quality measures in future years.

B. Summary of Major Provisions

    In this proposed rule, we use the methods described in the FY 2023 
IRF PPS final rule (87 FR 47038) to update the prospective payment 
rates for FY 2024 using updated FY 2022 IRF claims and the most recent 
available IRF cost report data, which is FY 2021 IRF cost report data. 
It also proposes to rebase and revise the IRF market basket to reflect 
a 2021 base year. It also proposes to modify the regulation governing 
when an IRF unit can be excluded and paid under the IRF PPS.
    Beginning with the FY 2025 IRF QRP, we propose to modify the COVID-
19 Vaccination Coverage among Healthcare Personnel measure, adopt the 
Discharge Function Score measure, and remove the Application of Percent 
of Long-Term Care Hospital Patients with an Admission and Discharge 
Functional Assessment and a Care Plan That Addresses Function measure, 
the IRF Functional Outcome Measure: Change in Self-Care Score for 
Medical Rehabilitation Patients (NQF #2633) and

[[Page 20951]]

the Functional Outcome Measure: Change in Mobility Score for Medical 
Rehabilitation Patients (NQF #2634) measures. Beginning with the FY 
2026 IRF QRP, we propose to adopt the COVID-19 Vaccine: Percent of 
Patients/Residents Who Are Up to Date measure. This proposed rule also 
proposes to begin public reporting of the Transfer of Health 
Information to the Patient-Post-Acute Care (PAC) and Transfer of Health 
Information to the Provider-PAC measures, the Discharge Function Score 
measure, and the COVID-19 Vaccine: Percent of Patients/Residents Who 
Are Up to Date measure. Finally, we are seeking input from interested 
parties on principles for selecting and prioritizing IRF QRP quality 
measures and concepts, and we provide an update on our continued 
efforts to close the health equity gap.

C. Summary of Impact

                        Table 1--Cost and Benefit
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    Provision description                   Transfers/costs
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FY 2024 IRF PPS payment rate   The overall economic impact of this final
 update.                        rule is an estimated $335 million in
                                increased payments from the Federal
                                Government to IRFs during FY 2024.
FY 2025 through FY 2026 IRF    The overall economic impact of this final
 QRP changes.                   rule is an estimated increase in cost to
                                IRFs of $31,412.56 beginning with the FY
                                2025 IRF QRP.
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II. Background

A. Statutory Basis and Scope for IRF PPS Provisions

    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). A general 
description of the IRF PPS for FYs 2020 through 2022, 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.
    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 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 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 final rule also 
includes the provisions effective in the correcting amendments. For a 
detailed discussion of the final key policy changes for FY

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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,\1\ 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 
Public Health Emergency (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 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.
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    \1\ Patel A, Jernigan DB. Initial Public Health Response and 
Interim Clinical Guidance for the 2019 Novel Coronavirus Outbreak--
United States, December 31, 2019-February 4, 2020. MMWR Morb Mortal 
Wkly Rep 2020;69:140-146. DOI http://dx.doi.org/10.15585/mmwr.mm6905e1.
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    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) 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 \2\ and 
other flexibilities,\3\ some of which are applicable to the IRF PPS. 
CMS finalized these policies in the Calendar Year 2023 Hospital 
Outpatient Prospective Payment and Ambulatory Surgical Center Payment 
Systems final rule with comment period (87 FR 71748).
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    \2\ 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).
    \3\ 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 Patient Protection and the Affordable Care Act and 
the Medicare Access and CHIP Reauthorization Act of 2015 (MACRA) 
Affecting the IRF PPS in FY 2012 and Beyond

    The Patient Protection and the Affordable Care Act (the Affordable 
Care Act or ACA) (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 Patient Protection 
and Affordable Care Act, 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 ``ACA''.
    The ACA 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 ACA 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 2024 is discussed in 
section V.D. 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 ACA 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 ACA 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.

[[Page 20953]]

A free download of the Grouper software is available on the CMS website 
at http://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 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 http://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 http://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 digital health information.
    To further interoperability in post-acute care settings, CMS and 
the Office of the National Coordinator for Health Information 
Technology (ONC) participate in the Post-Acute Care Interoperability 
Workgroup (PACIO) to facilitate collaboration with interested parties 
to develop Health Level Seven International[supreg] (HL7) Fast 
Healthcare Interoperability Resource[supreg] (FHIR) standards. These 
standards could support the exchange and reuse of patient assessment 
data derived from the post-acute care (PAC) setting assessment tools, 
such as the minimum data set (MDS), inpatient rehabilitation facility-
patient assessment instrument (IRF-PAI), Long-Term Care Hospital (LTCH) 
continuity assessment record and evaluation (CARE) Data Set (LCDS), 
outcome and assessment information set (OASIS), and other 
sources.4 5 The PACIO Project has focused on HL7 FHIR 
implementation guides for: functional status, cognitive status and new 
use cases on advance directives, re-assessment timepoints, and Speech, 
language, swallowing, cognitive communication and hearing (SPLASCH) 
pathology.\6\ We encourage PAC provider and health IT vendor 
participation as the efforts advance.
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    \4\ HL7 FHIR Release 4. Available at https://www.hl7.org/fhir/.
    \5\ HL7 FHIR. PACIO Functional Status Implementation Guide. 
Available at https://paciowg.github.io/functional-status-ig/.
    \6\ PACIO Project. Available at http://pacioproject.org/about/.
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    The CMS Data Element Library (DEL) continues to be updated and 
serves as a resource for PAC assessment data elements and their 
associated mappings to health IT standards such as Logical Observation 
Identifiers Names and Codes (LOINC) and Systematized Nomenclature of 
Medicine Clinical Terms (SNOMED).\7\ The DEL furthers CMS' goal of data 
standardization and interoperability. Standards in the DEL can be 
referenced on the CMS website and in the ONC Interoperability Standards 
Advisory (ISA). The 2023 ISA is available at https://www.healthit.gov/sites/isa/files/inline-files/2023%20Reference%20Edition_ISA_508.pdf.
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    \7\ Centers for Medicare & Medicaid Services. Newsroom. Fact 
sheet: CMS Data Element Library Fact Sheet. June 21, 2018. Available 
at https://www.cms.gov/newsroom/fact-sheets/cms-data-element-library-fact-sheet.
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    We are also working with ONC to advance the United States Core Data 
for Interoperability (USCDI), a standardized set of health data classes 
and constituent data elements for nationwide, interoperable health 
information exchange.\8\ We are collaborating with ONC and other 
federal agencies to define and prioritize additional data 
standardization needs and develop consensus on recommendations for 
future versions of the USCDI. We are also directly collaborating with 
ONC to build requirements to support data standardization and alignment 
with requirements for quality measurement. ONC has launched the USCDI+ 
initiative to support the identification and establishment of domain 
specific datasets that build on the core USCDI foundation.\9\ The 
USCDI+ quality

[[Page 20954]]

measurement domain currently being developed aims to support defining 
additional data specifications for quality measurement that harmonize, 
where possible, with other Federal agency data needs and inform 
supplemental standards necessary to support quality measurement, 
including the needs of programs supporting quality measurement for 
long-term and post-acute care.
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    \8\ USCDI. Available at https://www.healthit.gov/isa/united-states-core-data-interoperability-uscdi.
    \9\ USCDI+. Available at https://www.healthit.gov/topic/interoperability/uscdi-plus.
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    The 21st Century Cures Act (Cures Act) (Pub. L. 114-255, enacted 
December 13, 2016) required HHS and ONC to take steps to promote 
adoption and use of electronic health record (EHR) technology.\10\ 
Specifically, section 4003(b) of the Cures Act required ONC to take 
steps to advance interoperability through the development of a Trusted 
Exchange Framework and Common Agreement aimed at establishing full 
network-to network exchange of health information nationally. On 
January 18, 2022, ONC announced a significant milestone by releasing 
the Trusted Exchange Framework \11\ and Common Agreement Version 1.\12\ 
The Trusted Exchange Framework is a set of non-binding principles for 
health information exchange, and the Common Agreement is a contract 
that advances those principles. The Common Agreement and the Qualified 
Health Information Network Technical Framework Version 1 (incorporated 
by reference into the Common Agreement) establish the technical 
infrastructure model and governing approach for different health 
information networks and their users to securely share clinical 
information with each other, all under commonly agreed to terms. The 
technical and policy architecture of how exchange occurs under the 
Common Agreement follows a network-of-networks structure, which allows 
for connections at different levels and is inclusive of many different 
types of entities at those different levels, such as health information 
networks, healthcare practices, hospitals, public health agencies, and 
Individual Access Services (IAS) Providers.\13\ On February 13, 2023, 
HHS marked a new milestone during an event at HHS headquarters,\14\ 
which recognized the first set of applicants accepted for onboarding to 
the Common Agreement as Qualified Health Information Networks (QHINs). 
QHINs will be entities that will connect directly to each other to 
serve as the core for nationwide interoperability.\15\ For more 
information, we refer readers to https://www.healthit.gov/topic/interoperability/trusted-exchange-framework-and-common-agreement.
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    \10\ Sections 4001 through 4008 of Public Law 114-255. Available 
at https://www.govinfo.gov/content/pkg/PLAW-114publ255/html/PLAW-114publ255.htm.
    \11\ The Trusted Exchange Framework (TEF): Principles for 
Trusted Exchange (Jan. 2022). Available at https://www.healthit.gov/sites/default/files/page/2022-01/Trusted_Exchange_Framework_0122.pdf.
    \12\ Common Agreement for Nationwide Health Information 
Interoperability Version 1 (Jan. 2022). Available at https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf.
    \13\ The Common Agreement defines Individual Access Services 
(IAS) as ``with respect to the Exchange Purposes definition, the 
services provided utilizing the Connectivity Services, to the extent 
consistent with Applicable Law, to an Individual with whom the QHIN, 
Participant, or Subparticipant has a Direct Relationship to satisfy 
that Individual's ability to access, inspect, or obtain a copy of 
that Individual's Required Information that is then maintained by or 
for any QHIN, Participant, or Subparticipant.'' The Common Agreement 
defines ``IAS Provider'' as: ``Each QHIN, Participant, and 
Subparticipant that offers Individual Access Services.'' See Common 
Agreement for Nationwide Health Information Interoperability Version 
1, at 7 (Jan. 2022), https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf.
    \14\ ``Building TEFCA,'' Micky Tripathi and Mariann Yeager, 
Health IT Buzz Blog. February 13, 2023. https://www.healthit.gov/buzz-blog/electronic-health-and-medical-records/interoperability-electronic-health-and-medical-records/building-tefca.
    \15\ The Common Agreement defines a QHIN as ``to the extent 
permitted by applicable SOP(s), a Health Information Network that is 
a U.S. Entity that has been Designated by the RCE and is a party to 
the Common Agreement countersigned by the RCE.'' See Common 
Agreement for Nationwide Health Information Interoperability Version 
1, at 10 (Jan. 2022), https://www.healthit.gov/sites/default/files/page/2022-01/Common_Agreement_for_Nationwide_Health_Information_Interoperability_Version_1.pdf.
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    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 
FY 2024 and the IRF QRP for FY 2025 and FY 2026.
    The proposed policy changes and updates to the IRF prospective 
payment rates for FY 2024 are as follows:
     Update the CMG relative weights and average length of stay 
values for FY 2024, in a budget neutral manner, as discussed in section 
IV. of this proposed rule.
     Update the IRF PPS payment rates for FY 2024 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.
     Rebase and revise the IRF market basket to reflect a 2021 
base year, as discussed in section V. of this proposed rule.
     Update the FY 2024 IRF PPS payment rates by the FY 2024 
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 2024, as discussed in section V. of this 
proposed rule.
     Update the outlier threshold amount for FY 2024, as 
discussed in section VI. of this proposed rule.
     Update the cost-to-charge ratio (CCR) ceiling and urban/
rural average CCRs for FY 2024, as discussed in section VI. of this 
proposed rule.
     Describe the proposed modification to the regulation for 
IRF units to become excluded and paid under the IRF PPS as discussed in 
section VII. of this proposed rule.
    We also propose updates to the IRF QRP and request information in 
section VIII. of the proposed rule as follows:
     Modify the COVID-19 Vaccination Coverage among Healthcare 
Personnel measure beginning with the FY 2025 IRF QRP.
     Adopt the Discharge Function Score measure beginning with 
the FY 2025 IRF QRP.
     Remove the Application of Percent of Long-Term Care 
Hospital Patients with an Admission and Discharge Functional Assessment 
and a Care Plan That Addresses Function measure beginning with the FY 
2025 IRF QRP.
     Remove the IRF Functional Outcome Measure: Change in Self-
Care Score for Medical Rehabilitation Patients (NQF #2633) measure 
beginning with the FY 2025 IRF QRP.
     Remove the IRF Functional Outcome Measure: Change in 
Mobility Score for Medical Rehabilitation Patients (NQF #2634) measure 
beginning with the FY 2025 IRF QRP.
     Adopt the COVID-19 Vaccine: Percent of Patients/Residents 
Who Are Up to Date measure beginning with the FY 2026 IRF QRP.
     Request information on principles for selecting and 
prioritizing IRF QRP quality measures and concepts.
     Provide an update on our continued efforts to close the 
health equity gap.

IV. Proposed Update to the Case-Mix Group (CMG) Relative Weights and 
Average Length of Stay (ALOS) Values for FY 2024

    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

[[Page 20955]]

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 ALOS values for FY 2024. Typically, we use the most recent 
available data to update the CMG relative weights and average lengths 
of stay. For FY 2024, we are proposing to use the FY 2022 IRF claims 
and FY 2021 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 2022 IRF cost report data are available for analysis, but the 
majority of the FY 2022 IRF claims data are available for analysis. We 
are proposing that if more recent data became 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 2024 CMG 
relative weights and ALOS 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 ALOS 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 2024 CMG relative weights to the same 
average CMG relative weight from the CMG relative weights implemented 
in the FY 2023 IRF PPS final rule (87 FR 47038).
    Consistent with the methodology that we have used to update the IRF 
classification system in each instance in the past, we are proposing to 
update the CMG relative weights for FY 2024 in such a way that total 
estimated aggregate payments to IRFs for FY 2024 are the same with or 
without the changes (that is, in a budget-neutral manner) by applying a 
budget neutrality factor to the standard payment amount. To calculate 
the appropriate budget neutrality factor for use in updating the FY 
2024 CMG relative weights, we use the following steps:
    Step 1. Calculate the estimated total amount of IRF PPS payments 
for FY 2024 (with no changes to the CMG relative weights).
    Step 2. Calculate the estimated total amount of IRF PPS payments 
for FY 2024 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 
0.9999 that would maintain the same total estimated aggregate payments 
in FY 2024 with and without the proposed changes to the CMG relative 
weights.
    Step 4. Apply the budget neutrality factor from step 3 to the FY 
2024 IRF PPS standard payment amount after the application of the 
budget-neutral wage adjustment factor.
    In section V.G. of this proposed rule, we discuss the proposed use 
of the existing methodology to calculate the proposed standard payment 
conversion factor for FY 2024.
    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 ALOS 
values for each CMG and tier for FY 2024. The ALOS 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.
BILLING CODE 4120-01-C

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[GRAPHIC] [TIFF OMITTED] TP07AP23.000


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[GRAPHIC] [TIFF OMITTED] TP07AP23.001


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[GRAPHIC] [TIFF OMITTED] TP07AP23.002

BILLING CODE 4120-01-P

[[Page 20959]]

    Generally, updates to the CMG relative weights result in some 
increases and some decreases to the CMG relative weight values. Table 3 
shows how we estimate that the application of the proposed revisions 
for FY 2024 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 2024 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.

   Table 3--Distributional Effects of the Changes to the CMG Relative
                                 Weights
------------------------------------------------------------------------
                                                           Percentage of
    Percentage change in CMG relative        Number of    cases affected
                 weights                  cases affected     (percent)
------------------------------------------------------------------------
Increased by 15% or more................              81             0.0
Increased by between 5% and 15%.........           1,263             0.3
Changed by less than 5%.................         375,622            99.4
Decreased by between 5% and 15%.........             843             0.2
Decreased by 15% or more................               0             0.0
------------------------------------------------------------------------

    As shown in Table 3, 99.4 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 2024. The proposed changes in the ALOS 
values for FY 2024, compared with the FY 2023 ALOS 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 ALOS values for FY 2024.

V. Proposed FY 2024 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 a productivity adjustment described in 
section 1886(b)(3)(B)(xi)(II) of the Act. Thus, we propose to update 
the IRF PPS payments for FY 2024 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 data for both freestanding and hospital-
based IRFs (80 FR 47049 through 47068). In 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. Beginning with FY 2024, we are proposing to rebase and revise 
the IRF market basket to reflect a 2021 base year. In the following 
discussion, we provide an overview of the proposed market basket and 
describe the methodologies used to determine the operating and capital 
portions of the proposed 2021-based IRF market basket.

B. Overview of the Proposed 2021-Based IRF Market Basket

    The proposed 2021-based IRF market basket is a fixed-weight, 
Laspeyres-type price index. A Laspeyres price index measures the change 
in price, over time, of the same mix of goods and services purchased in 
the base period. Any changes in the quantity or mix of goods and 
services (that is, intensity) purchased over time relative to the base 
period are not measured.
    The index itself is constructed in three steps. First, a base 
period is selected (for the proposed IRF market basket in this proposed 
rule, we propose to use 2021 as the base period) and total base period 
costs are estimated for a set of mutually exclusive and exhaustive cost 
categories. Each category is calculated as a proportion of total costs. 
These proportions are called cost weights. Second, each cost category 
is matched to an appropriate price or wage variable, referred to as a 
price proxy. In almost every instance, these price proxies are derived 
from publicly available statistical series that are published on a 
consistent schedule (preferably at least on a quarterly basis). 
Finally, the cost weight for each cost category is multiplied by the 
level of its respective price proxy. The sum of these products (that 
is, the cost weights multiplied by their price index levels) for all 
cost categories yields the composite index level of the market basket 
in a given time period. Repeating this step for other periods produces 
a series of market basket levels over time. Dividing an index level for 
a given period by an index level for an earlier period produces a rate 
of growth in the input price index over that timeframe.
    As noted, the market basket is described as a fixed-weight index 
because it represents the change in price over time of a constant mix 
(quantity and intensity) of goods and services needed to provide IRF 
services. The effects on total costs resulting from changes in the mix 
of goods and services purchased subsequent to the base period are not 
measured. For example, an IRF hiring more nurses after the base period 
to accommodate the needs of patients would increase the volume of goods 
and services purchased by the IRF, but would not be factored into the 
price change measured by a fixed-weight IRF market basket. Only when 
the index is rebased would changes in the quantity and intensity be 
captured, with those changes being reflected in the cost weights. 
Therefore, we rebase the market basket periodically so that the cost 
weights reflect recent changes in the mix of goods and services that 
IRFs purchase to furnish inpatient care between base periods.

C. Proposed Rebasing and Revising of the IRF PPS Market Basket

    As discussed in the FY 2020 IRF PPS final rule (84 FR 39071 through 
39086), the 2016-based IRF market basket cost weights reflect the 2016 
Medicare cost report data submitted by both freestanding and hospital-
based facilities.

[[Page 20960]]

    Beginning with FY 2024, we are proposing to rebase and revise the 
2016-based IRF market basket cost weights to a 2021 base year 
reflecting the 2021 Medicare cost report data submitted by both 
freestanding and hospital-based IRFs. Below we provide a detailed 
description of our methodology used to develop the proposed 2021-based 
IRF market basket. This proposed methodology is generally similar to 
the methodology used to develop the 2016-based IRF market basket.
    We invite public comment on our proposed methodology for developing 
the 2021-based IRF market basket.
1. Development of Cost Categories and Weights for the Proposed 2021-
Based IRF Market Basket
a. Use of Medicare Cost Report Data
    We are proposing a 2021-based IRF market basket that consists of 
seven major cost categories and a residual derived from the 2021 
Medicare cost reports (CMS Form 2552-10, OMB No. 0938-0050) for 
freestanding and hospital-based IRFs. The seven major cost categories 
are Wages and Salaries, Employee Benefits, Contract Labor, 
Pharmaceuticals, Professional Liability Insurance (PLI), Home Office/
Related Organization Contract Labor, and Capital. The residual category 
reflects all remaining costs not captured in the seven cost categories. 
The 2021 cost reports include providers whose cost reporting period 
began on or after October 1, 2020, and before October 1, 2021. As noted 
previously, the current IRF market basket is based on 2016 Medicare 
cost reports and, therefore, reflects the 2016 cost structure for IRFs. 
As described in the FY 2023 IRF PPS final rule (87 FR 47049 through 
47050), we received comments on the FY 2023 IRF PPS proposed rule where 
stakeholders expressed concern that the proposed market basket update 
was inadequate relative to input price inflation experienced by IRFs, 
particularly as a result of the COVID-19 PHE. These commenters stated 
that the PHE, along with inflation, has significantly driven up 
operating costs. Specifically, some commenters noted changes to the 
labor markets that led to the use of more contract labor, a trend that 
we verified in analyzing the Medicare cost reports through 2021. 
Therefore, we believe it is appropriate to incorporate more recent data 
to reflect updated cost structures for IRFs and so we are proposing to 
use 2021 as the base year because we believe that the Medicare cost 
reports for this year represent the most recent, complete set of 
Medicare cost report data available for developing the proposed IRF 
market basket at the time of this rulemaking. Given the potential 
impact of the PHE on the Medicare cost report data, we will continue to 
monitor these data going forward and any changes to the IRF market 
basket will be proposed in future rulemaking.
    Since our goal is to establish cost weights that are reflective of 
case mix and practice patterns associated with the services IRFs 
provide to Medicare beneficiaries, as we did for the 2016-based IRF 
market basket, we are proposing to limit the cost reports used to 
establish the 2021-based IRF market basket to those from facilities 
that had a Medicare average length of stay (LOS) that was relatively 
similar to their facility average LOS. We believe that this requirement 
eliminates statistical outliers and ensures a more accurate market 
basket that reflects the costs generally incurred during a Medicare-
covered stay. The Medicare average LOS for freestanding IRFs is 
calculated from data reported on line 14 of Worksheet S-3, part I. The 
Medicare average LOS for hospital-based IRFs is calculated from data 
reported on line 17 of Worksheet S-3, part I. We propose to include the 
cost report data from IRFs with a Medicare average LOS within 15 
percent (that is, 15 percent higher or lower) of the facility average 
LOS to establish the sample of providers used to estimate the 2021-
based IRF market basket cost weights. We are proposing to apply this 
LOS edit to the data for IRFs to exclude providers that serve a 
population whose LOS would indicate that the patients served are not 
consistent with a LOS of a typical Medicare patient. We note that this 
is the same LOS edit that we applied to develop the 2016-based IRF 
market basket. This process resulted in the exclusion of about nine 
percent of the freestanding and hospital-based IRF Medicare cost 
reports. Of those excluded, about 15 percent were freestanding IRFs and 
85 percent were hospital-based IRFs. This ratio is relatively 
consistent with the universe of freestanding and hospital-based IRF 
cost reports where freestanding IRFs represent about 30 percent of the 
total.
    We then propose to use the cost reports for IRFs that met this LOS 
edit requirement to calculate the costs for the seven major cost 
categories (Wages and Salaries, Employee Benefits, Contract Labor, 
Professional Liability Insurance, Pharmaceuticals, Home Office/Related 
Organization Contract Labor, and Capital) for the market basket. These 
are the same categories used for the 2016-based IRF market basket. 
Also, as described in section V.C.1.d. of this proposed rule, and as 
done for the 2016-based IRF market basket, we are also proposing to use 
the Medicare cost report data to calculate the detailed capital cost 
weights for the Depreciation, Interest, Lease, and Other Capital-
related cost categories. We note that we are proposing to rename the 
Home Office Contract Labor cost category to the Home Office/Related 
Organization Contract Labor cost category to be more consistent with 
the Medicare cost report instructions.
    Similar to the 2016-based IRF market basket major cost weights, for 
the majority of the proposed 2021-based IRF market basket cost weights, 
we are proposing to divide the 2021 costs for each cost category by the 
2021 total Medicare allowable costs (routine, ancillary and capital) 
that are eligible for reimbursement through the IRF PPS (we note that 
we use total facility medical care costs as the denominator to derive 
both the PLI and Home Office/Related Organization Contract Labor cost 
weights). We next describe our proposed methodology for deriving the 
cost levels used to derive the proposed 2021-based IRF market basket.
(1) Total Medicare Allowable Costs
    For freestanding IRFs, we propose that total Medicare allowable 
costs would be equal to the sum of total costs for the Medicare 
allowable cost centers as reported on Worksheet B, part I, column 26, 
lines 30 through 35, 50 through 76 (excluding 52 and 75), 90 through 
91, and 93.
    For hospital-based IRFs, we propose that total Medicare allowable 
costs would be equal to the total costs for the IRF inpatient unit 
after the allocation of overhead costs (Worksheet B, part I, column 26, 
line 41) and a proportion of total ancillary costs reported on 
Worksheet B, part I, column 26, lines 50 through 76 (excluding 52 and 
75), 90 through 91, and 93.
    We propose to calculate total ancillary costs attributable to the 
hospital-based IRF by first deriving an ``IRF ancillary ratio'' for 
each ancillary cost center. The IRF ancillary ratio is defined as the 
ratio of IRF Medicare ancillary costs for the cost center (as reported 
on Worksheet D-3, column 3 for hospital-based IRFs) to total Medicare 
ancillary costs for the cost center (equal to the sum of Worksheet D-3, 
column 3 for all relevant PPSs [that is, inpatient prospective payment 
system (IPPS), IRF, IPF and skilled nursing facility (SNF)]). For 
example, if hospital-based IRF Medicare physical therapy costs 
represent about 30 percent of the total Medicare physical therapy costs 
for the entire facility, then the IRF ancillary

[[Page 20961]]

ratio for physical therapy costs would be 30 percent. We believe it is 
appropriate to use only a portion of the ancillary costs in the market 
basket cost weight calculations since the hospital-based IRF only 
utilizes a portion of the facility's ancillary services. We believe the 
ratio of reported IRF Medicare costs to reported total Medicare costs 
provides a reasonable estimate of the ancillary services utilized, and 
costs incurred, by the hospital-based IRF. We propose that this IRF 
ancillary ratio for each cost center is also used to calculate Wages 
and Salaries and Capital costs as described below.
    Then for each ancillary cost center, we propose to multiply the IRF 
ancillary ratio for the given cost center by the total facility 
ancillary costs for that specific cost center (as reported on Worksheet 
B, part I, column 26) to derive IRF ancillary costs. For example, the 
30 percent IRF ancillary ratio for physical therapy cost center would 
be multiplied by the total ancillary costs for physical therapy 
(Worksheet B, part I, column 26, line 66). The IRF ancillary costs for 
each cost center are then added to total costs for the IRF inpatient 
unit after the allocation of overhead costs (Worksheet B, part I, 
column 26, line 41) to derive total Medicare allowable costs.
    We propose to use these methods to derive levels of total Medicare 
allowable costs for IRF providers. This is the same methodology used 
for the 2016-based IRF market basket. We propose that these total 
Medicare allowable costs for the IRF will be the denominator for the 
cost weight calculations for the Wages and Salaries, Employee Benefits, 
Contract Labor, Pharmaceuticals, and Capital cost weights. With this 
work complete, we then set about deriving cost levels for the seven 
major cost categories and then derive a residual cost weight reflecting 
all other costs not classified.
(2) Wages and Salaries Costs
    For freestanding IRFs, we are proposing to derive Wages and 
Salaries costs as the sum of routine inpatient salaries (Worksheet A, 
column 1, lines 30 through 35), ancillary salaries (Worksheet A, column 
1, lines 50 through 76 (excluding 52 and 75), 90 through 91, and 93), 
and a proportion of overhead (or general service cost centers in the 
Medicare cost reports) salaries. Since overhead salary costs are 
attributable to the entire IRF, we only include the proportion 
attributable to the Medicare allowable cost centers. We are proposing 
to estimate the proportion of overhead salaries that are attributed to 
Medicare allowable costs centers by multiplying the ratio of Medicare 
allowable area salaries (Worksheet A, column 1, lines 30 through 35, 50 
through 76 (excluding 52 and 75), 90 through 91, and 93) to total non-
overhead salaries (Worksheet A, column 1, line 200 less Worksheet A, 
column 1, lines 4 through 18) times total overhead salaries (Worksheet 
A, column 1, lines 4 through 18). This is a similar methodology as used 
in the 2016-based IRF market basket.
    For hospital-based IRFs, we are proposing to derive Wages and 
Salaries costs as the sum of the following salaries attributable to the 
hospital-based IRF: inpatient routine salary costs (Worksheet A, column 
1, line 41); overhead salary costs; ancillary salary costs; and a 
portion of overhead salary costs attributable to the ancillary 
departments.
(a) Overhead Salary Costs
    We are proposing to calculate the portion of overhead salary costs 
attributable to hospital-based IRFs by first calculating an IRF 
overhead salary ratio, which is equal to the ratio of total facility 
overhead salaries (as reported on Worksheet A, column 1, lines 4-18) to 
total facility noncapital overhead costs (as reported on Worksheet A, 
column 1 and 2, lines 4-18). We then are proposing to multiply this IRF 
overhead salary ratio by total noncapital overhead costs (sum of 
Worksheet B, part I, columns 4 through 18, line 41, less Worksheet B, 
part II, columns 4 through 18, line 41). This methodology assumes the 
proportion of total costs related to salaries for the overhead cost 
center is similar for all inpatient units (that is, acute inpatient or 
inpatient rehabilitation).
(b) Ancillary Salary Costs
    We are proposing to calculate hospital-based IRF ancillary salary 
costs for a specific cost center (Worksheet A, column 1, lines 50 
through 76 (excluding 52 and 75), 90 through 91, and 93) as salary 
costs from Worksheet A, column 1, multiplied by the IRF ancillary ratio 
for each cost center as described in section V.C.1.a.(1) of this 
proposed rule. The sum of these costs represents hospital-based IRF 
ancillary salary costs.
(c) Overhead Salary Costs for Ancillary Cost Centers
    We are proposing to calculate the portion of overhead salaries 
attributable to each ancillary department (lines 50 through 76 
(excluding 52 and 75), 90 through 91, and 93) by first calculating 
total noncapital overhead costs attributable to each specific ancillary 
department (sum of Worksheet B, part I, columns 4-18 less, Worksheet B, 
part II, column 26). We then identify the portion of these total 
noncapital overhead costs for each ancillary department that is 
attributable to the hospital-based IRF by multiplying these costs by 
the IRF ancillary ratio as described in section V.C.1.a.(1) of this 
proposed rule. We then sum these estimated IRF Medicare allowable 
noncapital overhead costs for all ancillary departments (cost centers 
50 through 76, 90 through 91, and 93). Finally, we then identify the 
portion of these IRF Medicare allowable noncapital overhead costs that 
are attributable to Wages and Salaries by multiplying these costs by 
the IRF overhead salary ratio as described in section V.C.1.a.(2)(a) of 
this proposed rule. This is the same methodology used to derive the 
2016-based IRF market basket.
(3) Employee Benefits Costs
    Effective with the implementation of CMS Form 2552-10, we began 
collecting Employee Benefits and Contract Labor data on Worksheet S-3, 
part V.
    For the 2021 Medicare cost report data, 54 percent of providers 
reported Employee Benefits data on Worksheet S-3, part V; particularly, 
approximately 57 percent of freestanding IRFs and 53 percent of 
hospital-based IRFs reported Employee Benefits data on Worksheet S-3, 
part V. For comparison, for 2016, about 45 percent of providers 
reported Employee Benefits data on Worksheet S-3, part V. Again, we 
continue to encourage all providers to report these data on the 
Medicare cost report.
    For freestanding IRFs, we are proposing Employee Benefits costs 
would be equal to the data reported on Worksheet S-3, part V, column 2, 
line 2. We note that while not required to do so, freestanding IRFs 
also may report Employee Benefits data on Worksheet S-3, part II, which 
is applicable to only IPPS providers. Similar to the method for the 
2016-based IRF market basket, for those freestanding IRFs that report 
Worksheet S-3, part II, data, but not Worksheet S-3, part V, we are 
proposing to use the sum of Worksheet S-3, part II, lines 17, 18, 20, 
and 22, to derive Employee Benefits costs.
    For hospital-based IRFs, we are proposing to calculate total 
benefit costs as the sum of inpatient unit benefit costs, a portion of 
ancillary departments benefit costs, and a portion of overhead benefits 
attributable to both the routine inpatient unit and the ancillary 
departments. For those hospital-based IRFs that report Worksheet S-3, 
part V data, we are proposing inpatient unit

[[Page 20962]]

benefit costs be equal to Worksheet S-3, part V, column 2, line 4. 
Given the limited reporting on Worksheet S-3, part V, we are proposing 
that for those hospital-based IRFs that do not report these data, we 
calculate inpatient unit benefits costs using a portion of benefits 
costs reported for Excluded areas on Worksheet S-3, part II. We are 
proposing to calculate the ratio of inpatient unit salaries (Worksheet 
A, column 1, line 41) to total excluded area salaries (sum of Worksheet 
A, column 1, lines 20, 23, 40 through 42, 44, 45, 46, 94, 95, 98 
through 101, 105 through 112, 114, 115 through 117, 190 through 194). 
We then propose to apply this ratio to Excluded area benefits 
(Worksheet S-3, part II, column 4, line 19) to derive inpatient unit 
benefits costs for those providers that do not report benefit costs on 
Worksheet S-3, part V.
    We are proposing the ancillary departments benefits and overhead 
benefits (attributable to both the inpatient unit and ancillary 
departments) costs are derived by first calculating the sum of 
hospital-based IRF overhead salaries as described in section 
V.C.1.a.(2)(a) of this proposed rule, hospital-based IRF ancillary 
salaries as described in section V.C.1.a.(2)(b) of this proposed rule 
and hospital-based IRF overhead salaries for ancillary cost centers as 
described in section V.C.1.a.(2)(c) of this proposed rule. This sum is 
then multiplied by the ratio of total facility benefits to total 
facility salaries, where total facility benefits is equal to the sum of 
Worksheet S-3, part II, column 4, lines 17-25, and total facility 
salaries is equal to Worksheet S-3, part II, column 4, line 1.
(4) Contract Labor Costs
    Contract Labor costs are primarily associated with direct patient 
care services. Contract labor costs for other services such as 
accounting, billing, and legal are calculated separately using other 
government data sources as described in section V.C.1.c. of this 
proposed rule. To derive contract labor costs using Worksheet S-3, part 
V, data, for freestanding IRFs, we are proposing Contract Labor costs 
be equal to Worksheet S-3, part V, column 1, line 2. As we noted for 
Employee Benefits, freestanding IRFs also may report Contract Labor 
data on Worksheet S-3, part II, which is applicable to only IPPS 
providers. For those freestanding IRFs that report Worksheet S-3, part 
II data, but not Worksheet S-3, part V, we are proposing to use the sum 
of Worksheet S-3, part II, column 4, lines 11 and 13, to derive 
Contract Labor costs.
    For hospital-based IRFs, we are proposing that Contract Labor costs 
would be equal to Worksheet S-3, part V, column 1, line 4. For 2021 
Medicare cost report data, 30 percent of providers reported Contract 
Labor data on Worksheet S-3, part V; particularly, approximately 56 
percent of freestanding IRFs and 18 percent of hospital-based IRFs 
reported data on Worksheet S-3, part V. For comparison, for the 2016-
based IRF market basket, about 26 percent of providers reported 
Contract Labor data on Worksheet S-3, part V. We continue to encourage 
all providers to report these data on the Medicare cost report.
    Given the limited reporting on Worksheet S-3, part V, we are 
proposing that for those hospital-based IRFs that do not report these 
data, we calculate Contract Labor costs using a portion of contract 
labor costs reported on Worksheet S-3, part II. We are proposing to 
calculate the ratio of contract labor costs (Worksheet S-3, part II, 
column 4, lines 11 and 13) to PPS salaries (Worksheet S-3, part II, 
column 4, line 1 less the sum of Worksheet S-3, part II, column 4, 
lines 3, 401, 5, 6, 7, 701, 8, 9, 10 less Worksheet A, column 1, line 
20 and 23). We then propose to apply this ratio to total inpatient 
routine salary costs (Worksheet A, column 1, line 41) to derive 
contract labor costs for those providers that do not report contract 
labor costs on Worksheet S-3, part V.
(5) Pharmaceuticals Costs
    For freestanding IRFs, we are proposing to calculate 
pharmaceuticals costs using non-salary costs reported on Worksheet A, 
column 7, less Worksheet A, column 1, for the pharmacy cost center 
(line 15) and drugs charged to patients cost center (line 73).
    For hospital-based IRFs, we are proposing to calculate 
pharmaceuticals costs as the sum of a portion of the non-salary 
pharmacy costs and a portion of the non-salary drugs charged to patient 
costs reported for the total facility. We propose that non-salary 
pharmacy costs attributable to the hospital-based IRF would be 
calculated by multiplying total pharmacy costs attributable to the 
hospital-based IRF (as reported on Worksheet B, part I, column 15, line 
41) by the ratio of total non-salary pharmacy costs (Worksheet A, 
column 2, line 15) to total pharmacy costs (sum of Worksheet A, columns 
1 and 2 for line 15) for the total facility. We propose that non-salary 
drugs charged to patient costs attributable to the hospital-based IRF 
would be calculated by multiplying total non-salary drugs charged to 
patient costs (Worksheet B, part I, column 0, line 73 plus Worksheet B, 
part I, column 15, line 73 less Worksheet A, column 1, line 73) for the 
total facility by the ratio of Medicare drugs charged to patient 
ancillary costs for the IRF unit (as reported on Worksheet D-3 for 
hospital-based IRFs, column 3, line 73) to total Medicare drugs charged 
to patient ancillary costs for the total facility (equal to the sum of 
Worksheet D-3, column 3, line 73 for all relevant PPS (that is, IPPS, 
IRF, IPF and SNF).
(6) Professional Liability Insurance Costs
    For freestanding and hospital-based IRFs, we are proposing that 
Professional Liability Insurance (PLI) costs (often referred to as 
malpractice costs) would be equal to premiums, paid losses and self-
insurance costs reported on Worksheet S-2, columns 1 through 3, line 
118--the same data used for the 2016-based IRF market basket. For 
hospital-based IRFs, we are proposing to assume that the PLI weight for 
the total facility is similar to the hospital-based IRF unit since the 
only data reported on this worksheet is for the entire facility, as we 
currently have no means to identify the proportion of total PLI costs 
that are only attributable to the hospital-based IRF. However, when we 
derive the cost weight for PLI for both hospital-based and freestanding 
IRFs, we use the total facility medical care costs as the denominator 
as opposed to total Medicare allowable costs. For freestanding IRFs and 
hospital-based IRFs, we are proposing to derive total facility medical 
care costs as the sum of total costs (Worksheet B, part I, column 26, 
line 202) less non-reimbursable costs (Worksheet B, part I, column 26, 
lines 190 through 201).
(7) Home Office/Related Organization Contract Labor Costs
    For freestanding and hospital-based IRFs, we are proposing to 
calculate the home office/related organization contract labor costs 
using data reported on Worksheet S-3, part II, column 4, lines 1401, 
1402, 2550, and 2551. Similar to the PLI costs, these costs are for the 
entire facility. Therefore, when we derive the cost weight for Home 
Office/Related Organization Contract Labor costs, we use the total 
facility medical care costs as the denominator (reflecting the total 
facility costs less the non-reimbursable costs reported on lines 190 
through 201). Our assumption is that the same proportion of expenses 
are used among each unit of the hospital.

[[Page 20963]]

(8) Capital Costs
    For freestanding IRFs, we are proposing that capital costs would be 
equal to Medicare allowable capital costs as reported on Worksheet B, 
part II, column 26, lines 30 through 35, 50 through 76 (excluding 52 
and 75), 90 through 91, and 93.
    For hospital-based IRFs, we are proposing that capital costs would 
be equal to IRF inpatient capital costs (as reported on Worksheet B, 
part II, column 26, line 41) and a portion of IRF ancillary capital 
costs. We calculate the portion of ancillary capital costs attributable 
to the hospital-based IRF for a given cost center by multiplying total 
facility ancillary capital costs for the specific ancillary cost center 
(as reported on Worksheet B, part II, column 26) by the IRF ancillary 
ratio as described in section V.C.1.a.(1) of this proposed rule. For 
example, if hospital-based IRF Medicare physical therapy costs 
represent 30 percent of the total Medicare physical therapy costs for 
the entire facility, then 30 percent of total facility physical therapy 
capital costs (as reported in Worksheet B, part II, column 26, line 66) 
would be attributable to the hospital-based IRF.
b. Final Major Cost Category Computation
    After we derive costs for each of the major cost categories and 
total Medicare allowable costs for each provider using the Medicare 
cost report data as previously described, we propose to address data 
outliers using the following steps. First, for the Wages and Salaries, 
Employee Benefits, Contract Labor, Pharmaceuticals, and Capital cost 
weights, we first divide the costs for each of these five categories by 
total Medicare allowable costs calculated for the provider to obtain 
cost weights for the universe of IRF providers. We then propose to trim 
the data to remove outliers (a standard statistical process) by: (1) 
requiring that major expenses (such as Wages and Salaries costs) and 
total Medicare allowable operating costs be greater than zero; and (2) 
excluding the top and bottom five percent of the major cost weight (for 
example, Wages and Salaries costs as a percent of total Medicare 
allowable operating costs). We note that missing values are assumed to 
be zero consistent with the methodology for how missing values were 
treated in the 2016-based IRF market basket. After these outliers have 
been excluded, we sum the costs for each category across all remaining 
providers. We then divide this by the sum of total Medicare allowable 
costs across all remaining providers to obtain a cost weight for the 
proposed 2021-based IRF market basket for the given category.
    The proposed trimming methodology for the Home Office/Related 
Organization Contract Labor and PLI cost weights is slightly different 
than the proposed trimming methodology for the other five cost 
categories as described above. For these cost weights, since we are 
using total facility medical care costs rather than Medicare allowable 
costs associated with IRF services, we are proposing to trim the 
freestanding and hospital-based IRF cost weights separately.
    For the PLI cost weight, for each of the providers, we first divide 
the PLI costs by total facility medical care costs to obtain a PLI cost 
weight for the universe of IRF providers. We then propose to trim the 
data to remove outliers by: (1) requiring that PLI costs are greater 
than zero and are less than total facility medical care costs; and (2) 
excluding the top and bottom five percent of the major cost weight 
trimming freestanding and hospital-based providers separately. After 
removing these outliers, we are left with a trimmed data set for both 
freestanding and hospital-based providers. We are then proposing to 
separately sum the costs for each category (freestanding and hospital-
based) across all remaining providers. We next divide this by the sum 
of total facility medical care costs across all remaining providers to 
obtain both a freestanding cost weight and hospital-based cost weight. 
Lastly, we are proposing to weight these two cost weights together 
using the Medicare allowable costs from the sample of freestanding and 
hospital-based IRFs that passed the PLI trim (59 percent for hospital-
based and 41 percent for freestanding IRFs) to derive a PLI cost weight 
for the proposed 2021-based IRF market basket.
    For the Home Office/Related Organization Contract Labor cost 
weight, for each of the providers, we first divide the home office/
related organization contract labor costs by total facility medical 
care costs to obtain a Home Office/Related Organization Contract Labor 
cost weight for the universe of IRF providers. We are then proposing to 
trim only the top 1 percent of providers to exclude outliers while also 
allowing providers who have reported zero home office costs to remain 
in the Home Office/Related Organization Contract Labor cost weight 
calculations as not all providers will incur home office/relation 
organization contract labor costs. After removing these outliers, we 
are left with a trimmed data set for both freestanding and hospital-
based providers. We are then proposing to separately sum the costs for 
each category (freestanding and hospital-based) across all remaining 
providers. We next divide this by the sum of total facility medical 
care costs across all remaining providers to obtain a freestanding cost 
weight and hospital-based cost weight. Lastly, we are proposing to 
weight these two cost weights together using the Medicare allowable 
costs from the sample of freestanding and hospital-based IRFs that 
passed the Home Office/Related Organization Contract Labor cost weight 
trim (68 percent for hospital-based and 32 percent for freestanding 
IRFs) to derive a Home Office/Related Organization Contract Labor cost 
weight for the proposed 2021-based IRF market basket.
    Finally, we propose to calculate the residual ``All Other'' cost 
weight that reflects all remaining costs that are not captured in the 
seven cost categories listed. See Table 4 for the resulting cost 
weights for these major cost categories that we obtain from the 
Medicare cost reports.

[[Page 20964]]



  Table 4--Major Cost Categories as Derived From Medicare Cost Reports
------------------------------------------------------------------------
                                          Proposed 2021-
                                             based IRF    2016-based IRF
          Major cost categories            market basket   market basket
                                             (percent)       (percent)
------------------------------------------------------------------------
Wages and Salaries......................            46.6            47.1
Employee Benefits.......................            11.6            11.3
Contract Labor..........................             2.0             1.0
Professional Liability Insurance                     0.8             0.7
 (Malpractice)..........................
Pharmaceuticals.........................             4.7             5.1
Home Office/Related Organization                     5.4             3.7
 Contract Labor.........................
Capital.................................             8.6             9.0
All Other...............................            20.4            22.2
------------------------------------------------------------------------
* Total may not sum to 100 due to rounding.

    As we did for the 2016-based IRF market basket, we are proposing to 
allocate the Contract Labor cost weight to the Wages and Salaries and 
Employee Benefits cost weights based on their relative proportions 
under the assumption that contract labor costs are comprised of both 
wages and salaries and employee benefits. The Contract Labor allocation 
proportion for Wages and Salaries is equal to the Wages and Salaries 
cost weight as a percent of the sum of the Wages and Salaries cost 
weight and the Employee Benefits cost weight. For this proposed rule, 
this rounded percentage is 80 percent; therefore, we are proposing to 
allocate 80 percent of the Contract Labor cost weight to the Wages and 
Salaries cost weight and 20 percent to the Employee Benefits cost 
weight. This allocation was 81/19 in the 2016-based IRF market basket 
(84 FR 39076). Table 5 shows the Wages and Salaries and Employee 
Benefit cost weights after Contract Labor cost weight allocation for 
both the proposed 2021-based IRF market basket and 2016-based IRF 
market basket.

  Table 5--Wages and Salaries and Employee Benefits Cost Weights After
                        Contract Labor Allocation
------------------------------------------------------------------------
                                          Proposed 2021-
          Major cost categories              based IRF    2016-based IRF
                                           market basket   market basket
------------------------------------------------------------------------
Wages and Salaries......................            48.2            47.9
Employee Benefits.......................            11.9            11.4
------------------------------------------------------------------------

c. Derivation of the Detailed Operating Cost Weights
    To further divide the ``All Other'' residual cost weight estimated 
from the 2021 Medicare cost report data into more detailed cost 
categories, we propose to use the 2012 Benchmark Input-Output (I-O) 
``Use Tables/Before Redefinitions/Purchaser Value'' for North American 
Industry Classification System (NAICS) 622000, Hospitals, published by 
the Bureau of Economic Analysis (BEA). This data is publicly available 
at http://www.bea.gov/industry/io_annual.htm. For the 2016-based IRF 
market basket, we also used the 2012 Benchmark I-O data, the most 
recent data available at the time (84 FR 39076).
    The BEA Benchmark I-O data are scheduled for publication every 5 
years with the most recent data available for 2012. The 2012 Benchmark 
I-O data are derived from the 2012 Economic Census and are the building 
blocks for BEA's economic accounts. Thus, they represent the most 
comprehensive and complete set of data on the economic processes or 
mechanisms by which output is produced and distributed.\16\ BEA also 
produces Annual I-O estimates; however, while based on a similar 
methodology, these estimates reflect less comprehensive and less 
detailed data sources and are subject to revision when benchmark data 
becomes available. Instead of using the less detailed Annual I-O data, 
we propose to inflate the 2012 Benchmark I-O data forward to 2021 by 
applying the annual price changes from the respective price proxies to 
the appropriate market basket cost categories that are obtained from 
the 2012 Benchmark I-O data. We repeat this practice for each year. We 
then propose to calculate the cost shares that each cost category 
represents of the inflated 2012 data. These resulting 2021 cost shares 
are applied to the All Other residual cost weight to obtain the 
detailed cost weights for the proposed 2021-based IRF market basket. 
For example, the cost for Food: Direct Purchases represents 5.0 percent 
of the sum of the ``All Other'' 2012 Benchmark I-O Hospital 
Expenditures inflated to 2021; therefore, the Food: Direct Purchases 
cost weight represents 5.0 percent of the 2021-based IRF market 
basket's ``All Other'' cost category (20.4 percent), yielding a 
``final'' Food: Direct Purchases cost weight of 1.0 percent in the 
proposed 2021-based IRF market basket (0.05 * 20.4 percent = 1.0 
percent).
---------------------------------------------------------------------------

    \16\ http://www.bea.gov/papers/pdf/IOmanual_092906.pdf.
---------------------------------------------------------------------------

    Using this methodology, we propose to derive seventeen detailed IRF 
market basket cost category weights from the proposed 2021-based IRF 
market basket residual cost weight (20.4 percent). These categories 
are: (1) Electricity and Other Non-Fuel Utilities, (2) Fuel: Oil and 
Gas (3) Food: Direct Purchases, (4) Food: Contract Services, (5) 
Chemicals, (6) Medical Instruments, (7) Rubber and Plastics, (8) Paper 
and Printing Products, (9) Miscellaneous Products, (10) Professional 
Fees: Labor-related, (11) Administrative and Facilities Support 
Services, (12) Installation, Maintenance, and Repair Services, (13) All 
Other Labor-related Services, (14) Professional Fees: Nonlabor-related, 
(15) Financial Services, (16) Telephone Services, and (17) All Other 
Nonlabor-related Services.

[[Page 20965]]

d. Derivation of the Detailed Capital Cost Weights
    As described in section V.C.1.b. of this proposed rule, we are 
proposing a Capital-Related cost weight of 8.6 percent as obtained from 
the 2021 Medicare cost reports for freestanding and hospital-based IRF 
providers. We are proposing to then separate this total Capital-Related 
cost weight into more detailed cost categories.
    Using 2021 Medicare cost reports, we are able to group Capital-
Related costs into the following categories: Depreciation, Interest, 
Lease, and Other Capital-Related costs. For each of these categories, 
we are proposing to determine separately for hospital-based IRFs and 
freestanding IRFs what proportion of total capital-related costs the 
category represents.
    For freestanding IRFs, using Medicare cost report data on Worksheet 
A-7 part III, we are proposing to derive the proportions for 
Depreciation (column 9), Interest (column 11), Lease (column 10), and 
Other Capital-related costs (column 12 through 14), which is similar to 
the methodology used for the 2016-based IRF market basket.
    For hospital-based IRFs, data for these four categories are not 
reported separately for the hospital-based IRF; therefore, we are 
proposing to derive these proportions using data reported on Worksheet 
A-7 for the total facility. We are assuming the cost shares for the 
overall hospital are representative for the hospital-based IRF unit. 
For example, if depreciation costs make up 60 percent of total capital 
costs for the entire facility, we believe it is reasonable to assume 
that the hospital-based IRF would also have a 60 percent proportion 
because it is a unit contained within the total facility. This is the 
same methodology used for the 2016-based IRF market basket (84 FR 
39077).
    To combine each detailed capital cost weight for freestanding and 
hospital-based IRFs into a single capital cost weight for the proposed 
2021-based IRF market basket, we are proposing to weight together the 
shares for each of the categories (Depreciation, Interest, Lease, and 
Other Capital-related costs) based on the share of total capital costs 
each provider type represents of the total capital costs for all IRFs 
for 2021. Applying this methodology results in proportions of total 
capital-related costs for Depreciation, Interest, Lease and Other 
Capital-related costs that are representative of the universe of IRF 
providers. This is the same methodology used for the 2016-based IRF 
market basket (84 FR 39077).
    Lease costs are unique in that they are not broken out as a 
separate cost category in the proposed 2021-based IRF market basket. 
Rather, we are proposing to proportionally distribute these costs among 
the cost categories of Depreciation, Interest, and Other Capital-
Related costs, reflecting the assumption that the underlying cost 
structure of leases is similar to that of capital-related costs in 
general. As was done under the 2016-based IRF market basket, we are 
proposing to assume that 10 percent of the lease costs as a proportion 
of total capital-related costs represents overhead and assign those 
costs to the Other Capital-Related cost category accordingly. We 
propose to distribute the remaining lease costs proportionally across 
the three cost categories (Depreciation, Interest, and Other Capital-
Related) based on the proportion that these categories comprise of the 
sum of the Depreciation, Interest, and Other Capital-related cost 
categories (excluding lease expenses). This would result in three 
primary capital-related cost categories in the proposed 2021-based IRF 
market basket: Depreciation, Interest, and Other Capital-Related costs. 
This is the same methodology used for the 2016-based IRF market basket 
(84 FR 39077). The allocation of these lease expenses is shown in Table 
6.
    Finally, we are proposing to further divide the Depreciation and 
Interest cost categories. We are proposing to separate Depreciation 
into the following two categories: (1) Building and Fixed Equipment and 
(2) Movable Equipment. We are proposing to separate Interest into the 
following two categories: (1) Government/Nonprofit and (2) For-profit.
    To disaggregate the Depreciation cost weight, we need to determine 
the percent of total Depreciation costs for IRFs that is attributable 
to Building and Fixed Equipment, which we hereafter refer to as the 
``fixed percentage.'' For the proposed 2021-based IRF market basket, we 
are proposing to use slightly different methods to obtain the fixed 
percentages for hospital-based IRFs compared to freestanding IRFs.
    For freestanding IRFs, we are proposing to use depreciation data 
from Worksheet A-7 of the 2021 Medicare cost reports. However, for 
hospital-based IRFs, we determined that the fixed percentage for the 
entire facility may not be representative of the hospital-based IRF 
unit due to the entire facility likely employing more sophisticated 
movable assets that are not utilized by the hospital-based IRF. 
Therefore, for hospital-based IRFs, we are proposing to calculate a 
fixed percentage using: (1) building and fixture capital costs 
allocated to the hospital-based IRF unit as reported on Worksheet B, 
part I, column 1, line 41, and (2) building and fixture capital costs 
for the top five ancillary cost centers utilized by hospital-based IRFs 
accounting for 78 percent of hospital-based IRF ancillary total costs: 
Physical Therapy (Worksheet B, part I, column 1, line 66), Drugs 
Charged to Patients (Worksheet B, part I, column 1, line 73), 
Occupational Therapy (Worksheet B, part I, column 1, line 67), 
Laboratory (Worksheet B, part I, column 1, line 60) and Clinic 
(Worksheet B, part I, column 1, line 90). We propose to weight these 
two fixed percentages (inpatient and ancillary) using the proportion 
that each capital cost type represents of total capital costs in the 
proposed 2021-based IRF market basket. We are proposing to then weight 
the fixed percentages for hospital-based and freestanding IRFs together 
using the proportion of total capital costs each provider type 
represents. For both freestanding and hospital-based IRFs, this is the 
same methodology used for the 2016-based IRF market basket (84 FR 
39077).
    To disaggregate the Interest cost weight, we determined the percent 
of total interest costs for IRFs that are attributable to government 
and nonprofit facilities, which is hereafter referred to as the 
``nonprofit percentage,'' as price pressures associated with these 
types of interest costs tend to differ from those for for-profit 
facilities. For the 2021-based IRF market basket, we are proposing to 
use interest costs data from Worksheet A-7 of the 2021 Medicare cost 
reports for both freestanding and hospital-based IRFs. We are proposing 
to determine the percent of total interest costs that are attributed to 
government and nonprofit IRFs separately for hospital-based and 
freestanding IRFs. We then are proposing to weight the nonprofit 
percentages for hospital-based and freestanding IRFs together using the 
proportion of total capital costs that each provider type represents.
    Table 6 provides the proposed detailed capital cost share 
composition estimated from the 2021 IRF Medicare cost reports. These 
detailed capital cost share composition percentages are applied to the 
total Capital-Related cost weight of 8.6 percent calculated using the 
methodology described in section V.C.1.a.(8) of this proposed rule.

[[Page 20966]]



 Table 6--Capital Cost Share Composition for the Proposed 2021-Based IRF
                              Market Basket
------------------------------------------------------------------------
                                       Capital cost       Capital cost
                                    share composition  share composition
                                       before lease       after lease
                                         expense            expense
                                        allocation         allocation
                                        (percent)          (percent)
------------------------------------------------------------------------
Depreciation......................                 48                 70
    Building and Fixed Equipment..                 30                 44
    Movable Equipment.............                 18                 26
Interest..........................                 10                 14
    Government/Nonprofit..........                  5                  7
    For Profit....................                  5                  7
    Lease.........................                 34  .................
Other Capital-related costs.......                  8                 16
------------------------------------------------------------------------
* Detail may not add to total due to rounding.


e. Proposed 2021-Based IRF Market Basket Cost Categories and Weights

    Table 7 compares the cost categories and weights for the proposed 
2021-based IRF market basket compared to the 2016-based IRF market 
basket.
BILLING CODE 4120-01-P
[GRAPHIC] [TIFF OMITTED] TP07AP23.003


[[Page 20967]]


BILLING CODE 4120-01-C
2. Selection of Price Proxies
    After developing the cost weights for the proposed 2021-based IRF 
market basket, we select the most appropriate wage and price proxies 
currently available to represent the rate of price change for each 
expenditure category. For the majority of the cost weights, we base the 
price proxies on U.S. Bureau of Labor Statistics (BLS) data and group 
them into one of the following BLS categories:
     Employment Cost Indexes. Employment Cost Indexes (ECIs) 
measure the rate of change in employment wage rates and employer costs 
for employee benefits per hour worked. These indexes are fixed-weight 
indexes and strictly measure the change in wage rates and employee 
benefits per hour. ECIs are superior to Average Hourly Earnings (AHE) 
as price proxies for input price indexes because they are not affected 
by shifts in occupation or industry mix, and because they measure pure 
price change and are available by both occupational group and by 
industry. The industry ECIs are based on the NAICS and the occupational 
ECIs are based on the Standard Occupational Classification System 
(SOC).
     Producer Price Indexes. Producer Price Indexes (PPIs) 
measure the average change over time in the selling prices received by 
domestic producers for their output. The prices included in the PPI are 
from the first commercial transaction for many products and some 
services (https://www.bls.gov/ppi/).
     Consumer Price Indexes. Consumer Price Indexes (CPIs) 
measure the average change over time in the prices paid by urban 
consumers for a market basket of consumer goods and services (https://www.bls.gov/cpi/). CPIs are only used when the purchases are similar to 
those of retail consumers rather than purchases at the producer level, 
or if no appropriate PPIs are available.
    We evaluate the price proxies using the criteria of reliability, 
timeliness, availability, and relevance:
     Reliability. Reliability indicates that the index is based 
on valid statistical methods and has low sampling variability. Widely 
accepted statistical methods ensure that the data were collected and 
aggregated in a way that can be replicated. Low sampling variability is 
desirable because it indicates that the sample reflects the typical 
members of the population. (Sampling variability is variation that 
occurs by chance because only a sample was surveyed rather than the 
entire population.)
     Timeliness. Timeliness implies that the proxy is published 
regularly, preferably at least once a quarter. The market baskets are 
updated quarterly, and therefore, it is important for the underlying 
price proxies to be up-to-date, reflecting the most recent data 
available. We believe that using proxies that are published regularly 
(at least quarterly, whenever possible) helps to ensure that we are 
using the most recent data available to update the market basket. We 
strive to use publications that are disseminated frequently, because we 
believe that this is an optimal way to stay abreast of the most current 
data available.
     Availability. Availability means that the proxy is 
publicly available. We prefer that our proxies are publicly available 
because this will help ensure that our market basket updates are as 
transparent to the public as possible. In addition, this enables the 
public to be able to obtain the price proxy data on a regular basis.
     Relevance. Relevance means that the proxy is applicable 
and representative of the cost category weight to which it is applied. 
The CPIs, PPIs, and ECIs that we have selected to propose in this 
regulation meet these criteria. Therefore, we believe that they 
continue to be the best measure of price changes for the cost 
categories to which they would be applied.
    Table 11 lists all price proxies that we propose to use for the 
proposed 2021-based IRF market basket. Below is a detailed explanation 
of the price proxies we are proposing for each cost category weight.
a. Price Proxies for the Operating Portion of the Proposed 2021-Based 
IRF Market Basket
(1) Wages and Salaries
    We are proposing to continue to use the ECI for Wages and Salaries 
for All Civilian workers in Hospitals (BLS series code 
CIU1026220000000I) to measure the wage rate growth of this cost 
category. This is the same price proxy used in the 2016-based IRF 
market basket (84 FR 39080).
(2) Benefits
    We are proposing to continue to use the ECI for Total Benefits for 
All Civilian workers in Hospitals to measure price growth of this 
category. This ECI is calculated using the ECI for Total Compensation 
for All Civilian workers in Hospitals (BLS series code 
CIU1016220000000I) and the relative importance of wages and salaries 
within total compensation. This is the same price proxy used in the 
2016-based IRF market basket (84 FR 39080).
(3) Electricity and Other Non-Fuel Utilities
    We are proposing to continue to use the PPI Commodity Index for 
Commercial Electric Power (BLS series code WPU0542) to measure the 
price growth of this cost category (which we are proposing to rename 
from Electricity to Electricity and Other Non-Fuel Utilities). This is 
the same price proxy used in the 2016-based IRF market basket (84 FR 
39080).
(4) Fuel: Oil and Gas
    Similar to the 2016-based IRF market basket, for the 2021-based IRF 
market basket, we are proposing to use a blend of the PPI for Petroleum 
Refineries and the PPI Commodity for Natural Gas. Our analysis of the 
Bureau of Economic Analysis' 2012 Benchmark Input-Output data (use 
table before redefinitions, purchaser's value for NAICS 622000 
[Hospitals]), shows that Petroleum Refineries expenses account for 
approximately 90 percent and Natural Gas expenses account for 
approximately 10 percent of Hospitals' (NAICS 622000) total Fuel: Oil 
and Gas expenses. Therefore, we propose to use a blend of 90 percent of 
the PPI for Petroleum Refineries (BLS series code PCU324110324110) and 
10 percent of the PPI Commodity Index for Natural Gas (BLS series code 
WPU0531) as the price proxy for this cost category. This is the same 
blend that was used for the 2016-based IRF market basket (84 FR 39080).
(5) Professional Liability Insurance
    We are proposing to continue to use the CMS Hospital Professional 
Liability Index to measure changes in PLI premiums. To generate this 
index, we collect commercial insurance premiums for a fixed level of 
coverage while holding non-price factors constant (such as a change in 
the level of coverage). This is the same proxy used in the 2016-based 
IRF market basket (84 FR 39080).
(6) Pharmaceuticals
    We are proposing to continue to use the PPI for Pharmaceuticals for 
Human Use, Prescription (BLS series code WPUSI07003) to measure the 
price growth of this cost category. This is the same proxy used in the 
2016-based IRF market basket (84 FR 39080).
(7) Food: Direct Purchases
    We are proposing to continue to use the PPI for Processed Foods and 
Feeds (BLS series code WPU02) to measure the price growth of this cost 
category. This is the same proxy used in the 2016-based IRF market 
basket (84 FR 39080).

[[Page 20968]]

(8) Food: Contract Purchases
    We are proposing to continue to use the CPI for Food Away From Home 
(BLS series code CUUR0000SEFV) to measure the price growth of this cost 
category. This is the same proxy used in the 2016-based IRF market 
basket (84 FR 39080).
(9) Chemicals
    Similar to the 2016-based IRF market basket, we are proposing to 
use a four-part blended PPI as the proxy for the chemical cost category 
in the proposed 2021-based IRF market basket. The proposed blend is 
composed of the PPI for Industrial Gas Manufacturing, Primary Products 
(BLS series code PCU325120325120P), the PPI for Other Basic Inorganic 
Chemical Manufacturing (BLS series code PCU32518-32518-), the PPI for 
Other Basic Organic Chemical Manufacturing (BLS series code PCU32519-
32519-), and the PPI for Other Miscellaneous Chemical Product 
Manufacturing (BLS series code PCU325998325998). For the proposed 2021-
based IRF market basket, we are proposing to derive the weights for the 
PPIs using the 2012 Benchmark I-O data.
    Table 8 shows the weights for each of the four PPIs used to create 
the proposed blended Chemical proxy for the proposed 2021 IRF market 
basket. This is the same blend that was used for the 2016-based IRF 
market basket (84 FR 39080).

                  Table 8--Blended Chemical PPI Weights
------------------------------------------------------------------------
                                          Proposed 2021-
                                             based IRF
                  Name                        weights          NAICS
                                             (percent)
------------------------------------------------------------------------
PPI for Industrial Gas Manufacturing....              19          325120
PPI for Other Basic Inorganic Chemical                13          325180
 Manufacturing..........................
PPI for Other Basic Organic Chemical                  60          325190
 Manufacturing..........................
PPI for Other Miscellaneous Chemical                   8          325998
 Product Manufacturing..................
------------------------------------------------------------------------

(10) Medical Instruments
    We are proposing to use a blended price proxy for the Medical 
Instruments category, as shown in Table 9. The 2012 Benchmark I-O data 
shows the majority of medical instruments and supply costs are for 
NAICS 339112--Surgical and medical instrument manufacturing costs 
(approximately 56 percent) and NAICS 339113--Surgical appliance and 
supplies manufacturing costs (approximately 43 percent). Therefore, we 
are proposing to use a blend of these two price proxies. To proxy the 
price changes associated with NAICS 339112, we are proposing using the 
PPI for Surgical and medical instruments (BLS series code WPU1562). 
This is the same price proxy we used in the 2016-based IRF market 
basket. To proxy the price changes associated with NAICS 339113, we are 
proposing to use a 50/50 blend of the PPI for Medical and surgical 
appliances and supplies (BLS series code WPU1563) and the PPI for 
Miscellaneous products, Personal safety equipment and clothing (BLS 
series code WPU1571). We are proposing to include the latter price 
proxy as it would reflect personal protective equipment including but 
not limited to face shields and protective clothing. The 2012 Benchmark 
I-O data does not provide specific expenses for these products; 
however, we recognize that this category reflects costs faced by IRFs.

            Table 9--Blended Medical Instruments PPI Weights
------------------------------------------------------------------------
                                          Proposed 2021-
                                             based IRF
                  Name                        weights          NAICS
                                             (percent)
------------------------------------------------------------------------
PPI--Commodity--Surgical and medical                  56          339112
 instruments............................
PPI--Commodity--Medical and surgical                  22          339113
 appliances and supplies................
PPI--Commodity--Miscellaneous products-               22
 Personal safety equipment and clothing.
------------------------------------------------------------------------

(11) Rubber and Plastics
    We are proposing to continue to use the PPI for Rubber and Plastic 
Products (BLS series code WPU07) to measure price growth of this cost 
category. This is the same proxy used in the 2016-based IRF market 
basket (84 FR 39081).
(12) Paper and Printing Products
    We are proposing to continue to use the PPI for Converted Paper and 
Paperboard Products (BLS series code WPU0915) to measure the price 
growth of this cost category. This is the same proxy used in the 2016-
based IRF market basket (84 FR 39081).
(13) Miscellaneous Products
    We are proposing to continue to use the PPI for Finished Goods Less 
Food and Energy (BLS series code WPUFD4131) to measure the price growth 
of this cost category. This is the same proxy used in the 2016-based 
IRF market basket (84 FR 39081).
(14) Professional Fees: Labor-Related
    We are proposing to continue to use the ECI for Total Compensation 
for Private Industry workers in Professional and Related (BLS series 
code CIU2010000120000I) to measure the price growth of this category. 
This is the same proxy used in the 2016-based IRF market basket (84 FR 
39081).
(15) Administrative and Facilities Support Services
    We are proposing to continue to use the ECI for Total Compensation 
for Private Industry workers in Office and Administrative Support (BLS 
series code CIU2010000220000I) to measure the price growth of this 
category. This is the same proxy used in the 2016-based IRF market 
basket (84 FR 39081).
(16) Installation, Maintenance, and Repair Services
    We are proposing to continue to use the ECI for Total Compensation 
for

[[Page 20969]]

Civilian workers in Installation, Maintenance, and Repair (BLS series 
code CIU1010000430000I) to measure the price growth of this cost 
category. This is the same proxy used in the 2016-based IRF market 
basket (84 FR 39081).
(17) All Other: Labor-Related Services
    We are proposing to continue to use the ECI for Total Compensation 
for Private Industry workers in Service Occupations (BLS series code 
CIU2010000300000I) to measure the price growth of this cost category. 
This is the same proxy used in the 2016-based IRF market basket (84 FR 
39081).
(18) Professional Fees: Nonlabor-Related
    We are proposing to continue to use the ECI for Total Compensation 
for Private Industry workers in Professional and Related (BLS series 
code CIU2010000120000I) to measure the price growth of this category. 
This is the same proxy used in the 2016-based IRF market basket (84 FR 
39081).
(19) Financial Services
    We are proposing to continue to use the ECI for Total Compensation 
for Private Industry workers in Financial Activities (BLS series code 
CIU201520A000000I) to measure the price growth of this cost category. 
This is the same proxy used in the 2016-based IRF market basket (84 FR 
39081).
(20) Telephone Services
    We are proposing to continue to use the CPI for Telephone Services 
(BLS series code CUUR0000SEED) to measure the price growth of this cost 
category. This is the same proxy used in the 2016-based IRF market 
basket (84 FR 39081).
(21) All Other: Nonlabor-Related Services
    We are proposing to continue to use the CPI for All Items Less Food 
and Energy (BLS series code CUUR0000SA0L1E) to measure the price growth 
of this cost category. This is the same proxy used in the 2016-based 
IRF market basket (84 FR 39081).
b. Price Proxies for the Capital Portion of the Proposed 2021-Based IRF 
Market Basket
(1) Capital Price Proxies Prior to Vintage Weighting
    We are proposing to continue to use the same price proxies for the 
capital-related cost categories in the proposed 2021-based IRF market 
basket as were used in the 2016-based IRF market basket, which are 
provided in Table 11 and described below. Specifically, we are 
proposing to proxy:
     Depreciation: Building and Fixed Equipment cost category 
by BEA's Chained Price Index for Nonresidential Construction for 
Hospitals and Special Care Facilities (BEA Table 5.4.4. Price Indexes 
for Private Fixed Investment in Structures by Type).
     Depreciation: Movable Equipment cost category by the PPI 
for Machinery and Equipment (BLS series code WPU11).
     Nonprofit Interest cost category by the average yield on 
domestic municipal bonds (Bond Buyer 20-bond index).
     For-profit Interest cost category by the iBoxx AAA 
Corporate Bond Yield index.
     Other Capital-Related cost category by the CPI-U for Rent 
of Primary Residence (BLS series code CUUS0000SEHA).
    We believe these are the most appropriate proxies for IRF capital-
related costs that meet our selection criteria of relevance, 
timeliness, availability, and reliability. We are also proposing to 
continue to vintage weight the capital price proxies for Depreciation 
and Interest to capture the long-term consumption of capital. This 
vintage weighting method is similar to the method used for the 2016-
based IRF market basket (84 FR 39082) and is described below.
(2) Vintage Weights for Price Proxies
    Because capital is acquired and paid for over time, capital-related 
expenses in any given year are determined by both past and present 
purchases of physical and financial capital. The vintage-weighted 
capital-related portion of the proposed 2021-based IRF market basket is 
intended to capture the long-term consumption of capital, using vintage 
weights for depreciation (physical capital) and interest (financial 
capital). These vintage weights reflect the proportion of capital-
related purchases attributable to each year of the expected life of 
building and fixed equipment, movable equipment, and interest. We are 
proposing to use vintage weights to compute vintage-weighted price 
changes associated with depreciation and interest expenses.
    Capital-related costs are inherently complicated and are determined 
by complex capital-related purchasing decisions, over time, based on 
such factors as interest rates and debt financing. In addition, capital 
is depreciated over time instead of being consumed in the same period 
it is purchased. By accounting for the vintage nature of capital, we 
are able to provide an accurate and stable annual measure of price 
changes. Annual non-vintage price changes for capital are unstable due 
to the volatility of interest rate changes, and therefore, do not 
reflect the actual annual price changes for IRF capital-related costs. 
The capital-related component of the proposed 2021-based IRF market 
basket reflects the underlying stability of the capital-related 
acquisition process.
    The methodology used to calculate the vintage weights for the 
proposed 2021-based IRF market basket is the same as that used for the 
2016-based IRF market basket (84 FR 39082 through 39083) with the only 
difference being the inclusion of more recent data. To calculate the 
vintage weights for depreciation and interest expenses, we first need a 
time series of capital-related purchases for building and fixed 
equipment and movable equipment. We found no single source that 
provides an appropriate time series of capital-related purchases by 
hospitals for all of the above components of capital purchases. The 
early Medicare cost reports did not have sufficient capital-related 
data to meet this need. Data we obtained from the American Hospital 
Association (AHA) do not include annual capital-related purchases. 
However, we are able to obtain data on total expenses back to 1963 from 
the AHA. Consequently, we are proposing to use data from the AHA Panel 
Survey and the AHA Annual Survey to obtain a time series of total 
expenses for hospitals. We are then proposing to use data from the AHA 
Panel Survey supplemented with the ratio of depreciation to total 
hospital expenses obtained from the Medicare cost reports to derive a 
trend of annual depreciation expenses for 1963 through 2020, which is 
the latest year of AHA data available. We propose to separate these 
depreciation expenses into annual amounts of building and fixed 
equipment depreciation and movable equipment depreciation as determined 
earlier. From these annual depreciation amounts, we derive annual end-
of-year book values for building and fixed equipment and movable 
equipment using the expected life for each type of asset category. 
While data is not available that is specific to IRFs, we believe this 
information for all hospitals serves as a reasonable alternative for 
the pattern of depreciation for IRFs.
    To continue to calculate the vintage weights for depreciation and 
interest expenses, we also need to account for the expected lives for 
Building and Fixed Equipment, Movable Equipment, and Interest for the 
proposed 2021-based IRF market basket. We are proposing to calculate 
the expected lives using Medicare cost report data from Worksheet A-7 
part III for freestanding and hospital-based IRFs.

[[Page 20970]]

The expected life of any asset can be determined by dividing the value 
of the asset (excluding fully depreciated assets) by its current year 
depreciation amount. This calculation yields the estimated expected 
life of an asset if the rates of depreciation were to continue at 
current year levels, assuming straight-line depreciation. We are 
proposing to determine the expected life of building and fixed 
equipment separately for hospital-based IRFs and freestanding IRFs, and 
then weight these expected lives using the percent of total capital 
costs each provider type represents. We are proposing to apply a 
similar method for movable equipment. Using these proposed methods, we 
determined the average expected life of building and fixed equipment to 
be equal to 25 years, and the average expected life of movable 
equipment to be equal to 12 years. For the expected life of interest, 
we believe vintage weights for interest should represent the average 
expected life of building and fixed equipment because, based on 
previous research described in the FY 1997 IPPS final rule (61 FR 
46198), the expected life of hospital debt instruments and the expected 
life of buildings and fixed equipment are similar. We note that for the 
2016-based IRF market basket, the expected life of building and fixed 
equipment is 22 years, and the expected life of movable equipment is 11 
years (84 FR 39082) using the 2016 Medicare cost report data for 
freestanding and hospital-based IRFs.
    Multiplying these expected lives by the annual depreciation amounts 
results in annual year-end asset costs for building and fixed equipment 
and movable equipment. We then calculate a time series, beginning in 
1964, of annual capital purchases by subtracting the previous year's 
asset costs from the current year's asset costs.
    For the building and fixed equipment and movable equipment vintage 
weights, we are proposing to use the real annual capital-related 
purchase amounts for each asset type to capture the actual amount of 
the physical acquisition, net of the effect of price inflation. These 
real annual capital-related purchase amounts are produced by deflating 
the nominal annual purchase amount by the associated price proxy as 
provided earlier in this proposed rule. For the interest vintage 
weights, we are proposing to use the total nominal annual capital-
related purchase amounts to capture the value of the debt instrument 
(including, but not limited to, mortgages and bonds). Using these 
capital-related purchase time series specific to each asset type, we 
are proposing to calculate the vintage weights for building and fixed 
equipment, for movable equipment, and for interest.
    The vintage weights for each asset type are deemed to represent the 
average purchase pattern of the asset over its expected life (in the 
case of building and fixed equipment and interest, 25 years, and in the 
case of movable equipment, 12 years). For each asset type, we used the 
time series of annual capital-related purchase amounts available from 
2020 back to 1964. These data allow us to derive thirty-three 25-year 
periods of capital-related purchases for building and fixed equipment 
and interest, and forty-six 12-year periods of capital-related 
purchases for movable equipment. For each 25-year period for building 
and fixed equipment and interest, or 12-year period for movable 
equipment, we calculate annual vintage weights by dividing the capital-
related purchase amount in any given year by the total amount of 
purchases over the entire 25-year or 12-year period. This calculation 
is done for each year in the 25-year or 12-year period and for each of 
the periods for which we have data. We then calculate the average 
vintage weight for a given year of the expected life by taking the 
average of these vintage weights across the multiple periods of data. 
The vintage weights for the capital-related portion of the proposed 
2021-based IRF market basket and the 2016-based IRF market basket are 
presented in Table 10.

[[Page 20971]]

[GRAPHIC] [TIFF OMITTED] TP07AP23.004

    The process of creating vintage-weighted price proxies requires 
applying the vintage weights to the price proxy index where the last 
applied vintage weight in Table 10 is applied to the most recent data 
point. We have provided on the CMS website an example of how the 
vintage weighting price proxies are calculated, using example vintage 
weights and example price indices. The example can be found at http://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/MedicareProgramRatesStats/MarketBasketResearch.html in the zip 
file titled ``Weight Calculations as described in the IPPS FY 2010 
Proposed Rule.''
c. Summary of Price Proxies of the Proposed 2021-Based IRF Market 
Basket
    Table 11 shows both the operating and capital price proxies for the 
proposed 2021-based IRF market base.
BILLING CODE 4120-01-C

[[Page 20972]]

[GRAPHIC] [TIFF OMITTED] TP07AP23.005

BILLING CODE 4120-01-D
    We invite public comment on our proposal to rebase and revise the 
IRF market basket to reflect a 2021 base year.

[[Page 20973]]

D. Proposed FY 2024 Market Basket Update and Productivity Adjustment

1. Proposed FY 2024 Market Basket Update
    For FY 2024 (that is, beginning October 1, 2023 and ending 
September 30, 2024), we are proposing to use an estimate of the 
proposed 2021-based IRF market basket increase factor to update the IRF 
PPS base payment rate as required by section 1886(j)(3)(C)(i) of the 
Act. Consistent with historical practice, we are proposing to estimate 
the market basket update for the IRF PPS based on IHS Global Inc.'s 
(IGI's) forecast using the most recent available data. IGI is a 
nationally recognized economic and financial forecasting firm with 
which CMS contracts to forecast the components of the market baskets.
    Based on IGI's fourth quarter 2022 forecast with historical data 
through the third quarter of 2022, the proposed 2021-based IRF market 
basket increase factor for FY 2024 is 3.2 percent. Therefore, 
consistent with our historical practice of estimating market basket 
increases based on the best available data, we are proposing a market 
basket increase factor of 3.2 percent for FY 2024. We are also 
proposing that if more recent data are subsequently available (for 
example, a more recent estimate of the market basket) we would use such 
data, if appropriate, to determine the FY 2024 update in the final 
rule. For comparison, the current 2016-based IRF market basket is also 
projected to increase by 3.2 percent in FY 2024 based on IGI's fourth 
quarter 2022 forecast. Table 12 compares the proposed 2021-based IRF 
market basket and the 2016-based IRF market basket percent changes. On 
average, the two indexes produce similar updates to one another, with 
the 4-year average historical growth rates (for FY 2019-FY 2022) of the 
proposed 2021-based IRF market basket being equal to 3.2 percent 
compared to the 2016-based IRF market basket with 3.1 percent.

   Table 12--Proposed 2021-Based IRF Market Basket and 2016-Based IRF
         Market Basket Percent Changes, FY 2019 Through FY 2026
------------------------------------------------------------------------
                                          Proposed 2021-
                                             based IRF    2016-based IRF
            Fiscal year (FY)               market basket   market basket
                                           index percent   index percent
                                              change          change
------------------------------------------------------------------------
                             Historical data
------------------------------------------------------------------------
FY 2019.................................             2.4             2.3
FY 2020.................................             2.1             2.1
FY 2021.................................             2.8             2.7
FY 2022.................................             5.3             5.3
                                         -------------------------------
    Average 2019-2022...................             3.2             3.1
------------------------------------------------------------------------
                                Forecast
------------------------------------------------------------------------
FY 2023.................................             4.6             4.6
FY 2024.................................             3.2             3.2
FY 2025.................................             2.9             2.9
FY 2026.................................             2.8             2.8
                                         -------------------------------
    Average 2023-2026...................             3.4             3.4
------------------------------------------------------------------------
Note that these market basket percent changes do not include any further
  adjustments as may be statutorily required.
Source: IHS Global Inc. 4th quarter 2022 forecast.

2. Proposed Productivity Adjustment
    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 multifactor productivity 
(as projected by the Secretary for the 10-year period ending with the 
applicable FY, year, cost reporting period, or other annual period) 
(the ``productivity adjustment''). The U.S. Department of Labor's 
Bureau of Labor Statistics (BLS) publishes the official measures of 
productivity for the U.S. economy. We note that previously the 
productivity measure referenced in section 1886(b)(3)(B)(xi)(II) of the 
Act, was published by BLS as private nonfarm business multifactor 
productivity. Beginning with the November 18, 2021 release of 
productivity data, BLS replaced the term multifactor productivity (MFP) 
with total factor productivity (TFP). BLS noted that this is a change 
in terminology only and will not affect the data or methodology. As a 
result of the BLS name change, the productivity measure referenced in 
section 1886(b)(3)(B)(xi)(II) is now published by BLS as private 
nonfarm business total factor productivity. However, as mentioned 
above, the data and methods are unchanged. Please see www.bls.gov for 
the BLS historical published TFP data. A complete description of IGI's 
TFP projection methodology is available on the CMS website at https://www.cms.gov/Research-Statistics-Dataand-Systems/Statistics-Trends-andReports/MedicareProgramRatesStats/MarketBasketResearch. In addition, 
in the FY 2022 IRF final rule (86 FR 42374), we noted that effective 
with FY 2022 and forward, CMS changed the name of this adjustment to 
refer to it as the productivity adjustment rather than the MFP 
adjustment.
    Using IGI's fourth quarter 2022 forecast, the 10-year moving 
average growth of TFP for FY 2024 is projected

[[Page 20974]]

to be 0.2 percent. Thus, in accordance with section 1886(j)(3)(C) of 
the Act, we are proposing to calculate the FY 2024 market basket 
update, which is used to determine the applicable percentage increase 
for the IRF payments, using IGI's fourth quarter 2022 forecast of the 
proposed 2021-based IRF market basket. We are proposing to then reduce 
this percentage increase by the estimated productivity adjustment for 
FY 2024 of 0.2 percentage point (the 10-year moving average growth of 
TFP for the period ending FY 2024 based on IGI's fourth quarter 2022 
forecast). Therefore, the proposed FY 2024 IRF update is equal to 3.0 
percent (3.2 percent market basket update reduced by the 0.2 percentage 
point productivity adjustment). Furthermore, we are 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 and/or productivity adjustment), 
we would use such data, if appropriate, to determine the FY 2024 market 
basket update and productivity adjustment in the final rule.
    For FY 2024, 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 2024 by a productivity-adjusted IRF market 
basket increase factor of 3.0 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 2024.
    We invite public comment on our proposals for the FY 2024 market 
basket update and productivity adjustment.

E. Proposed Labor-Related Share for FY 2024

    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 inpatient rehabilitation facilities' costs that 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 propose to 
continue to classify a cost category as labor-related if the costs are 
labor-intensive and vary with the local labor market. As stated in the 
FY 2020 IRF PPS final rule (84 FR 39087), the labor-related share was 
defined as the sum of the relative importance of Wages and Salaries, 
Employee Benefits, Professional Fees: Labor-related Services, 
Administrative and Facilities Support Services, Installation, 
Maintenance, and Repair Services, All Other: Labor-related Services, 
and a portion of the Capital Costs from the 2016-based IRF market 
basket.
    Based on our definition of the labor-related share and the cost 
categories in the proposed 2021-based IRF market basket, we are 
proposing to include in the labor-related share for FY 2024 the sum of 
the FY 2024 relative importance of Wages and Salaries, Employee 
Benefits, Professional Fees: Labor-related, Administrative and 
Facilities Support Services, Installation, Maintenance, and Repair 
Services, All Other: Labor-related Services, and a portion of the 
Capital-Related cost weight from the proposed 2021-based IRF market 
basket.
    Similar to the 2016-based IRF market basket (84 FR 39087), the 
proposed 2021-based IRF market basket includes two cost categories for 
nonmedical Professional Fees (including, but not limited to, expenses 
for legal, accounting, and engineering services). These are 
Professional Fees: Labor-related and Professional Fees: Nonlabor-
related. For the proposed 2021-based IRF market basket, we propose to 
estimate the labor-related percentage of non-medical professional fees 
(and assign these expenses to the Professional Fees: Labor-related 
services cost category) based on the same method that was used to 
determine the labor-related percentage of professional fees in the 
2016-based IRF market basket.
    As was done in the 2016-based IRF market basket (84 FR 39087), we 
propose to determine the proportion of legal, accounting and auditing, 
engineering, and management consulting services that meet our 
definition of labor-related services based on a survey of hospitals 
conducted by us in 2008, a discussion of which can be found in the FY 
2010 IPPS/LTCH PPS final rule (74 FR 43850 through 43856). Based on the 
weighted results of the survey, we determined that hospitals purchase, 
on average, the following portions of contracted professional services 
outside of their local labor market:
     34 percent of accounting and auditing services.
     30 percent of engineering services.
     33 percent of legal services.
     42 percent of management consulting services.
    We are proposing to apply each of these percentages to the 
respective Benchmark I-O cost category underlying the professional fees 
cost category to determine the Professional Fees: Nonlabor-related 
costs. The Professional Fees: Labor-related costs were determined to be 
the difference between the total costs for each Benchmark I-O category 
and the Professional Fees: Nonlabor-related costs. This is the same 
methodology that we used to separate the 2016-based IRF market basket 
professional fees category into Professional Fees: Labor-related and 
Professional Fees: Nonlabor-related cost categories (84 FR 39087).
    Effective for transmittal 18 (https://www.cms.gov/Regulations-and-Guidance/Guidance/Transmittals/Transmittals/r18p240i), the hospital 
Medicare Cost Report (CMS Form 2552-10, OMB No. 0938-0050) is 
collecting information on whether a hospital purchased professional 
services (for example, legal, accounting, tax preparation, bookkeeping, 
payroll, advertising, and/or management/consulting services) from an 
unrelated organization and if the majority of these expenses were 
purchased from unrelated organizations located outside of the main 
hospital's local area labor market. We encourage all providers to 
provide this information so we can potentially use in future rulemaking 
to determine the labor-related share.
    In the proposed 2021-based IRF market basket, nonmedical 
professional fees that are subject to allocation based on these survey 
results represent 4.0 percent of total costs (and are limited to those 
fees related to Accounting & Auditing, Legal, Engineering, and 
Management Consulting services). Based on our survey results, we 
propose to apportion approximately 2.6 percentage points of the 4.0 
percentage point figure into the Professional Fees: Labor-related share 
cost category and designate the remaining 1.4 percentage point into the 
Professional Fees: Nonlabor-related cost category.
    In addition to the professional services listed, for the 2021-based 
IRF market basket, we are proposing to allocate a proportion of the 
Home Office/Related Organization Contract Labor cost weight, calculated 
using the Medicare cost reports as stated above, into the Professional 
Fees: Labor-related and Professional Fees: Nonlabor-related cost 
categories. We are proposing to

[[Page 20975]]

classify these expenses as labor-related and nonlabor-related as many 
facilities are not located in the same geographic area as their home 
office, and therefore, do not meet our definition for the labor-related 
share that requires the services to be purchased in the local labor 
market.
    Similar to the 2016-based IRF market basket, we are proposing for 
the 2021-based IRF market basket to use the Medicare cost reports for 
both freestanding IRF providers and hospital-based IRF providers to 
determine the home office labor-related percentages. The Medicare cost 
report requires a hospital to report information regarding their home 
office provider. For the proposed 2021-based IRF market basket, we are 
proposing to start with the sample of IRF providers that passed the top 
1 percent trim used to derive the Home Office/Related Organization 
Contract Labor cost weight as described in section V.C.1.b. of this 
proposed rule. Using information on the Medicare cost report, for 
freestanding and hospital-based providers separately, we first compare 
the location of the IRF with the location of the IRF's home office and 
classify an IRF based on whether their home office is located in the 
hospital facility's same Metropolitan Statistical Area. For both 
freestanding and hospital-based providers, we are proposing to multiply 
each provider's Home Office/Related Organization Contract Labor cost 
weight (calculated using data from the total facility) by Medicare 
allowable total costs. We then calculate the proportion of Medicare 
allowable home office compensation costs that these IRFs represent of 
total Medicare allowable home office compensation costs. We propose to 
multiply this percentage (45 percent) by the Home Office/Related 
Organization Contract Labor cost weight (5.4 percent) to determine the 
proportion of costs that should be allocated to the labor-related 
share. Therefore, we are allocating 2.4 percentage points of the Home 
Office/Related Organization Contract Labor cost weight (5.4 percent 
times 45 percent) to the Professional Fees: Labor-related cost weight 
and 3.0 percentage points of the Home Office/Related Organization 
Contract Labor cost weight to the Professional Fees: Nonlabor-related 
cost weight (5.4 percent times 55 percent). For the 2016-based IRF 
market basket, we used a similar methodology (84 FR 39088) and 
determined that 42 percent of the 2016-based Home Office/Related 
Organization Contract Labor cost weight should be allocated to the 
labor-related share.
    In summary, we apportioned 2.6 percentage points of the non-medical 
professional fees and 2.4 percentage points of the Home Office/Related 
Organization Contract Labor cost weight into the Professional Fees: 
Labor-related cost category. This amount was added to the portion of 
professional fees that was identified to be labor-related using the I-O 
data such as contracted advertising and marketing costs (approximately 
0.6 percentage point of total costs) resulting in a Professional Fees: 
Labor-related cost weight of 5.6 percent.
    As stated previously, we are proposing to include in the labor-
related share the sum of the relative importance of Wages and Salaries, 
Employee Benefits, Professional Fees: Labor-Related, Administrative and 
Facilities Support Services, Installation, Maintenance, and Repair 
Services, All Other: Labor-related Services, and a portion of the 
Capital-Related cost weight from the proposed 2021-based IRF market 
basket. The relative importance reflects the different rates of price 
change for these cost categories between the base year (2021) and FY 
2024. Based on IGI's fourth quarter 2022 forecast for the proposed 
2021-based IRF market basket, the sum of the FY 2024 relative 
importance for Wages and Salaries, Employee Benefits, Professional 
Fees: Labor-related, Administrative and Facilities Support Services, 
Installation Maintenance & Repair Services, and All Other: Labor-
related Services is 70.3 percent. The portion of Capital costs that is 
influenced by the local labor market is estimated to be 46 percent, 
which is the same percentage applied to the 2016-based IRF market 
basket (84 FR 39088 through 39089). Since the relative importance for 
Capital is 8.2 percent of the proposed 2021-based IRF market basket in 
FY 2024, we took 46 percent of 8.2 percent to determine the proposed 
labor-related share of Capital for FY 2024 of 3.8 percent. Therefore, 
we are proposing a total labor-related share for FY 2024 of 74.1 
percent (the sum of 70.3 percent for the operating costs and 3.8 
percent for the labor-related share of Capital). Table 13 shows the FY 
2024 labor-related share using the proposed 2021-based IRF market 
basket relative importance and the FY 2023 labor-related share using 
the 2016-based IRF market basket relative importance.

Table 13--Proposed FY 2024 IRF Labor-Related Share and FY 2023 IRF Labor-
                              Related Share
------------------------------------------------------------------------
                                              FY 2024
                                          proposed labor-  FY 2023 final
                                           related share   labor related
                                                \1\          share \2\
------------------------------------------------------------------------
Wages and Salaries......................            48.9            48.7
Employee Benefits.......................            11.9            11.3
Professional Fees: Labor-related \3\....             5.5             4.9
Administrative and Facilities Support                0.7             0.8
 Services...............................
Installation, Maintenance, and Repair                1.5             1.6
 Services...............................
All Other: Labor-related Services.......             1.8             1.9
                                         -------------------------------
    Subtotal............................            70.3            69.2
------------------------------------------------------------------------
Labor-related portion of capital (46%)..             3.8             3.7
                                         -------------------------------
    Total Labor-Related Share...........            74.1            72.9
------------------------------------------------------------------------
\1\ Based on the proposed 2021-based IRF Market Basket, IHS Global, Inc.
  4th quarter 2022 forecast.
\2\ Based on the 2016-based IRF market basket as published in the
  Federal Register (87 FR 47052).
\3\ Includes all contract advertising and marketing costs and a portion
  of accounting, architectural, engineering, legal, management
  consulting, and home office/related organization contract labor costs.

    The FY 2024 labor-related share using the proposed 2021-based IRF 
market basket is 1.2 percentage point higher than the FY 2023 labor-
related share using the 2016-based IRF market basket. This higher 
labor-related share is

[[Page 20976]]

primarily due to the incorporation of the 2021 Medicare cost report 
data, which increased the Compensation cost weight by approximately 0.8 
percentage point compared to the 2016-based IRF market basket as shown 
in Table 4 and Table 5 in section V.C.1.b. of this proposed rule.
    We invite public comment on the proposed labor-related share for FY 
2024.

F. Proposed Wage Adjustment for FY 2024

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.
    In the FY 2023 IRF PPS final rule (87 FR 47054 through 47056) we 
finalized a policy to apply a 5-percent cap on any decrease to a 
provider's wage index from its wage index in the prior year, regardless 
of the circumstances causing the decline. Additionally, we finalized a 
policy that a new IRF would be paid the wage index for the area in 
which it is geographically located for its first full or partial FY 
with no cap applied because a new IRF would not have a wage index in 
the prior FY. Also, in the FY 2023 IRF PPS final rule, we amended the 
regulations at Sec.  412.624(e)(1)(ii) to reflect this permanent cap on 
wage index decreases. A full discussion of the adoption of this policy 
is found in the FY 2023 IRF PPS final rule.
    For FY 2024, we propose to maintain the policies and methodologies 
described in the FY 2023 IRF PPS final rule (87 FR 47038) 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 2024 
pre-reclassification and pre-floor hospital wage index data. In 
accordance with section 1886(d)(3)(E) of the Act, the FY 2024 pre-
reclassification and pre-floor hospital wage index is based on data 
submitted for hospital cost reporting periods beginning on or after 
October 1, 2019, and before October 1, 2020 (that is, FY 2020 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 2024 IRF 
PPS wage index.
    We invite public comment on our proposals regarding the Wage 
Adjustment for FY 2024.
2. Core-Based Statistical Areas (CBSAs) for the FY 2024 IRF Wage Index
    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 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

[[Page 20977]]

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 an IRF'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 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 did not propose to adopt the revised 
OMB delineations identified in OMB Bulletin No. 20-01 for FY 2022 or 
2023, and for these reasons CMS is likewise not making such a proposal 
for FY 2024.
3. IRF Budget-Neutral Wage Adjustment Factor Methodology
    To calculate the wage-adjusted facility payment for the payment 
rates set forth in this proposed rule, we multiply the proposed 
unadjusted Federal payment rate for IRFs by the FY 2024 labor-related 
share based on the proposed 2021-based IRF market basket relative 
importance (74.1 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.E. 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) and 
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 2024 IRF standard 
payment conversion factor reflects the proposed update to the wage 
indexes (based on the FY 2020 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 2023 (as 
published in the FY 2023 IRF PPS final rule (87 FR 47038)).
    Step 2. Calculate the total amount of estimated IRF PPS payments 
using the FY 2024 wage index values (based on updated hospital wage 
data and considering the permanent cap on wage index decreases policy) 
and the proposed FY 2024 labor-related share of 74.1 percent.
    Step 3. Divide the amount calculated in step 1 by the amount 
calculated in step 2. The resulting quotient is the proposed FY 2024 
budget-neutral wage adjustment factor of 1.0032.
    Step 4. Apply the budget neutrality factor from step 3 to the FY 
2024 IRF PPS standard payment amount after the application of the 
increase factor to determine the proposed FY 2024 standard payment 
conversion factor.
    We discuss the calculation of the standard payment conversion 
factor for FY 2024 in section V.G. of this proposed rule.
    We invite public comment on the proposed IRF wage adjustment for FY 
2024.

G. Description of the Proposed IRF Standard Payment Conversion Factor 
and Payment Rates for FY 2024

    To calculate the proposed standard payment conversion factor for FY 
2024, as illustrated in Table 14, we begin by applying the proposed 
increase factor for FY 2024, as adjusted in accordance with sections 
1886(j)(3)(C) of the Act, to the standard payment conversion factor for 
FY 2023 ($17,878). Applying the proposed 3.0 percent increase factor 
for FY 2024 to the standard payment conversion factor for FY 2023 of 
$17,878 yields a standard payment amount of $18,414. Then, we apply the 
proposed budget neutrality factor for the FY 2024 wage index (taking 
into account the permanent cap on wage index decreases policy), and 
labor-related share of 1.0032, which results in a standard payment 
amount of $18,473. We next apply the proposed budget neutrality factor 
for the CMG relative weights of 0.9999, which results in the standard 
payment conversion factor of $18,471 for FY 2024.
    We invite public comment on the proposed FY 2024 standard payment 
conversion factor.

    Table 14--Calculations To Determine the Proposed FY 2024 Standard
                        Payment Conversion Factor
------------------------------------------------------------------------
               Explanation for adjustment                  Calculations
------------------------------------------------------------------------
Standard Payment Conversion Factor for FY 2023..........         $17,878
Proposed Market Basket Increase Factor for FY 2024               x 1.030
 (3.2%), reduced by 0.2 percentage point for the
 productivity adjustment as required by section
 1886(j)(3)(C)(ii)(I) of the Act........................
Budget Neutrality Factor for the Updates to the Wage            x 1.0032
 Index and Labor-Related Share..........................
Budget Neutrality Factor for the Revisions to the CMG           x 0.9999
 Relative Weights.......................................
                                                         ---------------
Proposed FY 2024 Standard Payment Conversion Factor.....        = 18,471
------------------------------------------------------------------------

    After the application of the proposed CMG relative weights 
described in section IV. of this proposed rule to the FY 2024 standard 
payment conversion factor ($18,471), the resulting unadjusted IRF 
prospective payment rates for FY 2024 are shown in Table 15.

[[Page 20978]]

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[[Page 20979]]


[GRAPHIC] [TIFF OMITTED] TP07AP23.007

BILLING CODE 4120-01-C

H. Example of the Methodology for Adjusting the Proposed Prospective 
Payment Rates

    Table 16 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 16.
    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 0.8353, and a rural adjustment of 14.9 
percent. Facility B, an urban teaching hospital, has a DSH percentage 
of 15 percent

[[Page 20980]]

(which would result in a LIP adjustment of 1.0454 percent), a wage 
index of 0.8804, and a teaching status adjustment of 0.0784.
    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 16. Then, 
we multiply the proposed labor-related share for FY 2024 (74.1 percent) 
described in section V.E. of this proposed rule by the 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 16 illustrates the components of the 
adjusted payment calculation.

   Table 16--Example of Computing the FY 2024 IRF Prospective Payment
------------------------------------------------------------------------
 
------------------------------------------------------------------------
Steps                              Rural Facility A
                                   (Spencer Co., IN)
                                   Urban Facility B
                                  (Harrison Co., IN)
------------------------------------------------------------------------
1 Unadjusted Payment............  ......  $28,870.17  ......  $28,870.17
2 Labor-Related Share...........  x       0.741       x       0.741
3 Labor Portion of Payment......  =       $21,392.80  =       $21,392.80
4 CBSA-Based Wage Index.........  x       0.8353      x       0.8804
5 Wage-Adjusted Amount..........  =       $17,869.40  =       $18,834.22
6 Non-Labor Amount..............  +       $7,477.37   +       $7,477.37
7 Wage-Adjusted Payment.........  =       $25,346.78  =       $26,311.59
8 Rural Adjustment..............  x       1.149       x       1.000
9 Wage- and Rural-Adjusted        =       $29,123.45  =       $26,311.59
 Payment.
10 LIP Adjustment...............  x       1.0156      x       1.0454
11 Wage-, Rural- and LIP-         =       $29,577.77  =       $27,506.14
 Adjusted Payment.
12 Wage- and Rural-Adjusted       ......  $29,123.45  ......  $26,311.59
 Payment.
13 Teaching Status Adjustment...  x       0           x       0.0784
14 Teaching Status Adjustment     =       $0.00       =       $2,062.83
 Amount.
15 Wage-, Rural-, and LIP-        +       $29,577.77  +       $27,506.14
 Adjusted Payment.
16 Total Adjusted Payment.......  =       $29,577.77  =       $29,568.97
------------------------------------------------------------------------

    Thus, the proposed adjusted payment for Facility A would be 
$29,577.77, and the proposed adjusted payment for Facility B would be 
$29,568.97.

VI. Proposed Update to Payments for High-Cost Outliers Under the IRF 
PPS for FY 2024

A. Update to the Outlier Threshold Amount for FY 2024

    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 2023 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, 85 FR 48444, 86 FR 42362, and 87 FR 47038, 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 2024, we propose 
to use FY 2022 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 41362 through 41363), which is also the same methodology that we 
used to update the outlier threshold amounts for FYs 2006

[[Page 20981]]

through 2023. 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 2024, we estimated the amount of FY 2024 IRF PPS aggregate and 
outlier payments using the most recent claims available (FY 2022) and 
the proposed FY 2024 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 estimated that IRF 
outlier payments as a percentage of total estimated payments would be 
approximately 2.3 percent in FY 2023. Therefore, we propose to update 
the outlier threshold amount from $12,526 for FY 2023 to $9,690 for FY 
2024 to maintain estimated outlier payments at approximately 3 percent 
of total estimated aggregate IRF payments for FY 2024. Furthermore, we 
are proposing that if more recent data become available after the 
publication of the proposed rule and before the publication of the 
final rule, we would use such data, if appropriate, to determine the FY 
2024 outlier threshold amount in the final rule.

B. Proposed Update to the IRF Cost-to-Charge Ratio Ceiling and Urban/
Rural Averages for FY 2024

    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 FR45692 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 2024, 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 2024, as discussed below in this section.
     Other IRFs for which accurate data to calculate an overall 
CCR are not available.
    Specifically, for FY 2024, we propose to estimate a national 
average CCR of 0.487 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 0.398 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 2021). This 
includes all IRFs whose cost reporting periods begin on or after 
October 1, 2020, and before October 1, 2021. If, for any IRF, the FY 
2021 cost report was missing or had an ``as submitted'' status, we used 
data from a previous FY's (that is, FY 2004 through FY 2020) 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 2021 cost report data for this proposed 
rule, we estimate a national average CCR of 0.487 for rural IRFs, and a 
national average CCR of 0.398 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 1.45 for FY 2024. This 
means that, if an individual IRF's CCR were to exceed this ceiling of 
1.45 for FY 2024, 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 2024 
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 2024.

VII. Proposed Modification to the Regulation for Excluded Inpatient 
Rehabilitation Facility Units Paid Under the IRF PPS

A. Background

    Under current regulation, to be excluded from the IPPS, and to be 
paid under the IRF PPS or the IPF PPS, an IRF or IPF unit of a hospital 
must meet a number of requirements under Sec.  412.25. Both this 
regulation and the policies applying to excluded units (which include 
excluded IRF units and excluded IPF units) have been in effect since 
before both the IRF PPS and IPF PPS were established, as discussed in 
the following paragraphs of this section. Before the IRF PPS and the 
IPF PPS were established, excluded units were paid based on their 
costs, as reported on their Medicare cost reports, subject to certain 
facility-specific cost limits. These cost-based payments were 
determined separately for operating and capital costs. Thus, under 
cost-based payments, the process of allocating costs to an IRF or IPF 
unit for reimbursement created significant administrative complexity. 
This administrative complexity necessitated strict regulations that 
allowed hospitals to open a new IPPS-excluded unit only at the start of 
a cost reporting period.
    In the January 3, 1984 final rule (49 FR 235), CMS (then known as 
the Health Care Financing Administration) established policies and 
regulations for hospitals and units subject to and excluded from the 
IPPS. In that rule, we explained that section 1886(d) of the Act 
requires that the prospective payment system apply to inpatient 
hospital services furnished by all hospitals participating in the 
Medicare program except those hospitals or units specifically excluded 
by the law. We further explained our expectation that a hospital's 
status (that is, whether it is subject to, or excluded from, the

[[Page 20982]]

prospective payment system) would generally be determined at the 
beginning of each cost reporting period. We also stated that this 
status would continue throughout the period, which is normally 1 year. 
Accordingly, we stated that changes in a hospital's (or unit's) status 
that result from meeting or failing to meet the criteria for exclusion 
would be implemented only at the start of a cost reporting period. 
However, we also acknowledged that under some circumstances involving 
factors external to the hospital, status changes could be made at times 
other than the beginning of the cost reporting period. For example, a 
change in status could occur if a hospital is first included under the 
prospective payment system and, after the start of its cost reporting 
period, is excluded because of its participation in an approved 
demonstration project or State reimbursement control program that 
begins after the hospital's cost reporting period has begun.
    In the FY 1993 IPPS final rule (57 FR 39798 through 39799), we 
codified our longstanding policies regarding when a hospital unit can 
change its status from not excluded to excluded. We explained in that 
final rule that since the inception of the prospective payment system 
for operating costs of hospital inpatient services in October 1983, 
certain types of specialty-care hospitals and hospital units have been 
excluded from that system under section 1888(d)(1)(B) of the Act. We 
noted that these currently include psychiatric and rehabilitation 
hospitals and distinct part units, children's hospitals, and long-term 
care hospitals. We further explained that section 6004(a)(1) of the 
Omnibus Budget Reconciliation Act of 1989, (Pub. L. 101-239, enacted 
December 19, 1989) amended section 1886(d)(1)(B) of the Act to provide 
that certain cancer hospitals are also excluded. We noted that the 
preamble to the January 3,1984 final rule implementing the prospective 
payment system for operating costs (49 FR 235) stated that the status 
of a hospital or unit (that is, whether it is subject to, or excluded 
from, the prospective payment system) will be determined at the 
beginning of each cost reporting period. We noted that that same 1984 
final rule also provided that changes in a hospital's or unit's status 
that result from meeting or failing to meet the criteria for exclusion 
will be implemented prospectively only at the start of a cost reporting 
period, that is, starting with the beginning date of the next cost 
reporting period (49 FR 243). However, we noted that this policy was 
not set forth in the regulations. In the FY 1993 final rule, we stated 
that we proposed revising Sec. Sec.  412.22 and 412.25 to specify that 
changes in the status of each hospital or hospital unit would be 
recognized only at the start of a cost reporting period. We stated that 
except in the case of retroactive payment adjustments for excluded 
rehabilitation units described in Sec.  412.30(c), any change in a 
hospital's or unit's compliance with the exclusion criteria that occurs 
after the start of a cost reporting period would not be considered 
until the start of the following period. We noted that this policy 
would also apply to any unit that is added to a hospital during the 
hospital's cost reporting period. We also stated that we proposed 
revising Sec.  412.25(a) to specify that as a requirement for 
exclusion, a hospital unit must be fully equipped and staffed, and be 
capable of providing inpatient psychiatric or rehabilitation care, as 
of the first day of the first cost reporting period for which all other 
exclusion requirements are met. We explained that a unit that meets 
this requirement would be considered open regardless of whether there 
are any inpatients in the unit.
    In the same FY 1993 IPPS final rule, we responded to commenters who 
objected to this policy, stating that it unnecessarily penalizes 
hospitals for factors beyond their control, such as construction 
delays, that it discourages hospitals from making changes in their 
programs to meet community needs, or that it can place undue workload 
demands on regulatory agencies during certain time periods. In 
response, we explained that we believed that regulatory agencies, 
hospitals, and the public generally would benefit from policies that 
are clearly stated, can be easily understood by both hospitals and 
intermediaries, and can be simply administered. We stated that 
recognizing changes in status only at the beginning of cost reporting 
periods is consistent with these goals, while recognizing changes in 
the middle of cost reporting periods would introduce added complexity 
to the administration of the exclusion provisions. Therefore, we did 
not revise the proposed changes based on these comments.
    In the FY 2000 IPPS final rule (64 FR 41531 through 41532), we 
amended the regulations at Sec.  412.25(c) to allow a hospital unit to 
change from excluded to not excluded at any time during the cost 
reporting period. We explained the statutory basis and rationale for 
this change in the FY 2000 IPPS proposed rule (64 FR 24740), and noted 
that a number of hospitals suggested that we consider a change in our 
policy to recognize, for purposes of exclusion from the IPPS, 
reductions in number of beds in, or entire closure of, units at any 
time during a cost reporting period. In that FY 2000 IPPS proposed 
rule, we explained that hospitals indicated that the bed capacity made 
available as a result of these changes could be used, as they need 
them, to provide additional services to meet patient needs in the acute 
care part of the hospital that is paid under the IPPS. We further 
explained that we evaluated the concerns of the hospitals and the 
effect on the administration of the Medicare program and the health 
care of beneficiaries of making these payment changes. As a result of 
that evaluation, we stated that we believed it was reasonable to adopt 
a more flexible policy in recognition of hospitals' changes in the use 
of their facilities. However, we noted that whenever a hospital 
establishes an excluded unit within the hospital, our Medicare fiscal 
intermediary would need to be able to determine costs of the unit 
separately from costs of the part of the hospital paid under the 
prospective payment system. At that time, we stated that the proper 
determination of costs ensured that the hospital was paid the correct 
amount for services in each part of the facility, and that payments 
under the IPPS did not duplicate payments made under the rules that 
were applicable to excluded hospitals and units, or vice versa. For 
this reason, we stated that we did not believe it would be appropriate 
to recognize, for purposes of exclusion from the IPPS, changes in the 
bed size or status of an excluded unit that are so frequent that they 
interfere with the ability of the intermediary to accurately determine 
costs. Moreover, we explained that section 1886(d)(1)(B) of the Act 
authorizes exclusion from the IPPS of specific types of hospitals and 
units, but not of specific admissions or stays, such as admissions for 
rehabilitation or psychiatric care, in a hospital paid under the IPPS. 
We stated that without limits on the frequency of changes in excluded 
units for purposes of proper Medicare payment, there was the potential 
for some hospitals to adjust the status or size of their excluded units 
so frequently that the units would no longer be distinct entities and 
the exclusion would effectively apply only to certain types of care.
    In the FY 2012 IRF PPS final rule (76 FR 47870), we began further 
efforts to increase flexibilities for excluded IPF and IRF units. In 
that rule, we explained that cost-based reimbursement methodologies 
that were in place before the IPF PPS and IRF PPS meant that the

[[Page 20983]]

facilities' capital costs were determined, in part, by their bed size 
and square footage. Changes in the bed size and square footage would 
complicate the facilities' capital cost allocation. Thus, the 
regulations at Sec.  412.25 limited the situations under which an IRF 
or IPF could change its bed size and square footage. In the FY 2012 IRF 
PPS final rule, we revised Sec.  412.25(b) to enable IRFs and IPFs to 
more easily adjust to beneficiary changes in demand for IRF or IPF 
services, and improve beneficiary access to these services. We believed 
that the first requirement (that beds can only be added at the start of 
a cost reporting period) was difficult, and potentially costly, for 
IRFs and IPFs that were expanding through new construction because the 
exact timing of the end of a construction project is often difficult to 
predict.
    In that same FY 2012 IRF PPS final rule, commenters suggested that 
CMS allow new IRF units or new IPF units to open and begin being paid 
under their respective IRF PPS or IPF PPS at any time during a cost 
reporting period, rather than requiring that they could only begin 
being paid under the IRF PPS or the IPF PPS at the start of a cost 
reporting period. In response, we stated that we believed that this 
suggestion was outside the scope of the FY 2012 IRF PPS proposed rule 
(76 FR 24214) because we did not propose any changes to the regulations 
in Sec.  412.25(c). However, we stated that we would consider this 
suggestion for possible inclusion in future rulemaking. Within the FY 
2018 IRF PPS proposed rule (82 FR 20690, 20742 through 20743), CMS 
published a request for information (RFI) on ways to reduce burden for 
hospitals, physicians, and patients; improve the quality of care; 
decrease costs; and ensure that patients and their providers and 
physicians are making the best health care choices possible. In 
response to the RFI, we received comments from IRF industry 
associations, state and national hospital associations, industry groups 
representing hospitals, and individual IRF providers. One of the 
comments we received in response to the RFI suggested allowing new IRF 
units to become excluded and be paid under the IRF PPS at any time 
during the cost reporting period, rather than only at the start of a 
cost reporting period, which the commenter believed would increase 
flexibility and eliminate a policy that may impose higher costs for 
providers while harmonizing an IRF payment system versus the IPPS 
payment system across all new IRF units.

B. Current Challenges Related To Excluded Hospital Units (Sec.  
412.25(c)(1) and (c)(2))

    Currently, under Sec.  412.25(c)(1), a hospital can only start 
being paid under the IRF PPS or the IPF PPS for services provided in an 
excluded unit at the start of a cost reporting period. Specifically, 
Sec.  412.25(c) limits when the status of hospital units may change for 
purposes of exclusion from the IPPS, as specified in Sec.  412.25(c)(1) 
and Sec.  412.25(c)(2). Section 412.25(c)(1) states that the status of 
a hospital unit may be changed from not excluded to excluded only at 
the start of the cost reporting period. If a unit is added to a 
hospital after the start of a cost reporting period, it cannot be 
excluded from the IPPS before the start of a hospital's next cost 
reporting period. Under Sec.  412.25(c)(2), the status of a hospital 
unit may be changed from excluded to not excluded at any time during a 
cost reporting period, but only if the hospital notifies the fiscal 
intermediary and the CMS Regional Office in writing of the change at 
least 30 days before the date of the change, and maintains the 
information needed to accurately determine costs that are or are not 
attributable to the excluded unit. A change in the status of a unit 
from excluded to not excluded that is made during a cost reporting 
period must remain in effect for the rest of that cost reporting 
period.
    In recent years, interested parties, such as hospitals, have 
written to CMS to express concerns about what they see as the 
unnecessary restrictiveness of the requirements of Sec.  412.25(c). 
Based on this feedback, we continued to explore opportunities to reduce 
burden for providers and clinicians, while keeping patient-centered 
care a priority. For instance, we considered whether this regulation 
might create unnecessary burden for hospitals and could potentially 
delay necessary rehabilitation beds from opening and being paid under 
the IRF PPS. As we continued to review and reconsider regulations to 
identify ways to improve policy, we recognized that the requirement at 
Sec.  412.25(c)(1) that hospital units can only be excluded at the 
start of a cost reporting period, may be challenging to meet and 
potentially costly for facilities under some circumstances, for 
example, those that are expanding through new construction. Hospitals 
have indicated it is often difficult to predict the exact timing of the 
end of a construction project and construction delays may hamper a 
hospital's ability to have the construction of an excluded unit 
completed exactly at the start of a cost reporting period, which 
hospitals said can lead to significant revenue loss if they are unable 
to be paid under the IRF PPS or IPF PPS until the start of the next 
cost reporting period.
    As discussed, the requirements of Sec.  412.25(c) were established 
to manage the administrative complexity associated with cost-based 
reimbursement for excluded IRF and IPF units. Today, however, because 
IRF units are paid under the IRF PPS, and IPF units are paid under the 
IPF PPS, cost allocation is not used for payment purposes. Because 
advancements in technology since the inception of the IRF PPS and IPF 
PPS have simplified the cost reporting process and enhanced 
communication between providers, CMS, and Medicare contractors, we are 
reconsidering whether it is necessary to continue to allow hospital 
units to become excluded only at the start of a cost reporting period.

C. Proposed Changes To Excluded Hospital Units (Sec.  412.25(c)(1) and 
(c)(2))

    We are committed to continuing to transform the health care 
delivery system--and the Medicare program--by putting additional focus 
on patient-centered care and working with providers, physicians, and 
patients to improve outcomes, while meeting relevant health care 
priorities and reducing burden.
    In response to the need for availability of inpatient 
rehabilitation beds we are proposing changes to Sec.  412.25(c) to 
allow greater flexibility for hospitals to open excluded units, while 
minimizing the amount of effort Medicare contractors would need to 
spend administering the regulatory requirements. Although we are 
cognizant that there is a need for rehabilitative health services and 
support for providers along a continuum of care, including a robust 
investment in community-based rehabilitative services, this rule is 
focused on inpatient rehabilitation facility settings.
    We note that Sec.  412.25(c) applies to both IRFs and IPFs; 
therefore, revisions to Sec.  412.25(c) would also affect IPFs in 
similar ways. Readers should refer to the FY 2024 IPF PPS proposed rule 
for discussion of proposed revisions to Sec.  412.25(c) and unique 
considerations applicable to IPF units.
    As discussed, the current requirements of Sec.  412.25(c)(1) were 
originally established to manage the administrative complexity 
associated with cost-based reimbursement for excluded IPF and IRF 
units. Because IPF and IRF units are no longer paid under cost-based 
reimbursement, but rather under the IPF PPS and IRF PPS

[[Page 20984]]

respectively, we believe that the restriction that limits an IPF or IRF 
unit to being excluded only at the start of a cost reporting period is 
no longer necessary.
    We amended our regulations in the FY 2012 IRF PPS final rule to 
address a regulation that similarly was previously necessary for cost-
based reimbursement, but was not material to payment under the IRF PPS 
and IPF PPS. In that final rule, we explained that under cost-based 
payments, the facilities' capital costs were determined, in part, by 
their bed size and square footage. Changes in the bed size and square 
footage would complicate the facilities' capital cost allocation. We 
explained that under the IRF PPS and IPF PPS, however, a facility's bed 
size and square footage were not relevant for determining the 
individual facility's Medicare payment. Therefore, we believed it was 
appropriate to modify some of the restrictions on a facility's ability 
to change its bed size and square footage. Accordingly, we relaxed the 
restrictions on a facility's ability to increase its bed size and 
square footage. Under the revised requirements that we adopted in the 
FY 2012, IRF PPS final rule in Sec.  412.25(b), an IRF or IPF can 
change (either increase or decrease) its bed size or square footage one 
time at any point in a given cost reporting period as long as it 
notifies the CMS RO at least 30 days before the date of the proposed 
change, and maintains the information needed to accurately determine 
costs that are attributable to the excluded units.
    Similarly, in the case of the establishment of a new excluded IPF 
and IRF units, we do not believe that the timing of the establishment 
of the new unit is material for determining the individual facility's 
level of Medicare payment under the IRF PPS or IPF PPS. We believe it 
would be appropriate to allow a unit to become excluded at any time in 
the cost reporting year. However, we also believe it is important to 
minimize the potential administrative complexity associated with units 
changing their excluded status.
    Accordingly, we propose to amend the requirements currently in 
regulation at Sec.  412.25(c)(1) to allow a hospital to open a new IRF 
unit anytime within the cost reporting year, as long as the hospital 
notifies the CMS Regional Office and Medicare Administrative Contractor 
(MAC) in writing of the change at least 30 days before the date of the 
change. Additionally, we are proposing that if a unit becomes excluded 
during a cost reporting year, this change would remain in effect for 
the rest of that cost reporting year. We also propose to maintain the 
current requirements of Sec.  412.25(c)(2), which specify that, if an 
excluded unit becomes not excluded during a cost reporting year, the 
hospital must notify the MAC and the CMS Regional Office in writing of 
the change at least 30 days before the change, and this change would 
remain in effect for the rest of that cost reporting year. Finally, we 
propose to consolidate the requirements for Sec.  412.25(c)(1) and 
Sec.  412.25(c)(2) into a new Sec.  412.25(c)(1) that would apply to 
IRF units and specify the requirements for an IRF unit to become 
excluded or not excluded.
    We believe this proposal would provide IRFs greater flexibility 
when establishing an excluded unit at a time other than the start of a 
cost reporting period.
    As noted, we are proposing an identical policy for inpatient 
psychiatric units of hospitals in Sec.  412.25(c)(2) in the FY 2024 IPF 
PPS proposed rule.
    We are proposing discrete regulation text for each of the hospital 
unit types (that is, IRF units and IPF units) to solicit comment on 
issues that might affect one hospital unit type and not the other. 
However, we may consider adopting one consolidated regulation text for 
both IRF and IPF units in either the IRF or IPF final rules for both 
unit types if we finalize both of our proposals. We request public 
comments on finalizing a consolidated provision that would pertain to 
both IRF and IPF units.

VIII. 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. Section 1886(j)(7)(A)(i) of the Act requires the Secretary 
to reduce by 2 percentage points the annual increase factor for 
discharges occurring during a fiscal year (FY) for any IRF that does 
not submit data in accordance with the IRF QRP requirements set forth 
in subparagraphs (C) and (F) of section 1886(j)(7) of the Act. Section 
1890A of the Act requires that the Secretary establish and follow a 
pre-rulemaking process, in coordination with the consensus-based entity 
(CBE) with a contract under section 1890 of the Act, to solicit input 
from certain groups regarding he selection of quality and efficiency 
measures for the IRF QRP. We have codified our program requirements in 
our regulations at Sec.  412.634.
    In this proposed rule, we are proposing to adopt two new measures, 
remove three existing measures, and modify one existing measure. 
Second, we are seeking information on principles we could use to select 
and prioritize IRF QRP quality measures in future years. Third, we are 
providing an update on our efforts to close the health equity gap. 
Finally, we are proposing to begin public reporting of four measures. 
These proposals are further specified below.

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 2024 IRF QRP
    The IRF QRP currently has 18 measures for the FY 2024 IRF QRP, 
which are listed in Table 17. For a discussion of the factors used to 
evaluate whether a measure should be removed from the IRF QRP, we refer 
readers to Sec.  412.634(b)(2).

[[Page 20985]]

[GRAPHIC] [TIFF OMITTED] TP07AP23.008

C. Overview of IRF QRP Quality Measure Proposals

    In this proposed rule, we propose to adopt two new measures, remove 
three existing measures, and modify one existing measure for the FY 
2025 IRF QRP and the FY 2026 IRF QRP. Beginning with the FY 2025 IRF 
QRP we are proposing to (1) modify the COVID-19 Vaccination Coverage 
among Healthcare Personnel (HCP) measure, (2) adopt the Discharge 
Function Score measure,\17\ which we are specifying under sections 
1886(j)(7)(F) and 1899B(c)(1) of the Act, and (3) remove three current 
measures: (i) the Application of Percent of Long-Term Care Hospital 
(LTCH) Patients with an Admission and Discharge Functional Assessment 
and a Care Plan That Addresses Function measure, (ii) IRF Functional 
Outcome Measure: Change in Self-Care Score for Medical Rehabilitation 
Patients measure, and (iii) IRF Functional Outcome Measure: Change in 
Mobility Score for Medical Rehabilitation Patients measure.
---------------------------------------------------------------------------

    \17\ This measure was submitted to the Measures Under 
Consideration (MUC) List as the Cross-Setting Discharge Function 
Score. Subsequent to the MAP Workgroup meetings, the measure 
developer modified the name.
---------------------------------------------------------------------------

    We are proposing to add one new measure beginning with the FY 2026 
IRF QRP, the COVID-19 Vaccine: Percent of Patients/Residents Who Are Up 
to Date measure which we are specifying under sections 1886(j)(7)(F) 
and 1899B(d)(1) of the Act.
1. IRF QRP Quality Measure Proposals Beginning With the FY 2025 IRF QRP
a. Proposed Modification of the COVID-19 Vaccination Coverage Among 
Healthcare Personnel (HCP) Measure Beginning With the FY 2025 IRF QRP
(1) Background
    On January 31, 2020, the Secretary 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 
``coronavirus disease 2019'' (COVID-19).\18\ Subsequently, in the FY 
2022 IRF PPS final rule (86 FR 42385 through 42396), we adopted the 
COVID-19

[[Page 20986]]

Vaccination Coverage among Healthcare Personnel (HCP COVID-19 Vaccine) 
measure for the IRF QRP. The HCP COVID-19 Vaccine measure requires each 
IRF to submit data on the number of healthcare personnel (HCP) eligible 
to work in the IRF for at least one day during the reporting period, 
excluding persons with contraindications to the COVID-19 vaccine, who 
have received a complete vaccination course against SARS-CoV-2 (86 FR 
42389 through 42396).
---------------------------------------------------------------------------

    \18\ U.S. Department of Health and Human Services, Office of the 
Assistant Secretary for Preparedness and Response. Determination 
that a Public Health Emergency Exists. Available at https://aspr.hhs.gov/legal/PHE/Pages/2019-nCoV.aspx.
---------------------------------------------------------------------------

    Since that time, COVID-19 has continued to spread domestically and 
around the world with more than 103.8 million cases and 1.1 million 
deaths in the United States as of March 21, 2023.\19\ In recognition of 
the ongoing significance and complexity of COVID-19, the Secretary has 
renewed the PHE on April 21, 2020, July 23, 2020, October 2, 2020, 
January 7, 2021, April 15, 2021, July 19, 2021, October 15, 2021, 
January 14, 2022, April 12, 2022, July 15, 2022, October 13, 2022, 
January 11, 2023, and February 9, 2023.\20\ The Department of Health 
and Human Services (HHS) announced plans to let the PHE expire on May 
11, 2023 and stated that the public health response to COVID-19 remains 
a public health priority with a whole-of-government approach to 
combatting the virus, including through vaccination efforts.\21\
---------------------------------------------------------------------------

    \19\ Centers for Disease Control and Prevention. COVID Data 
Tracker. March 21, 2023. https://covid.cdc.gov/covid-data-tracker/#datatracker-home.
    \20\ U.S. Department of Health and Human Services. Office of the 
Assistant Secretary for Preparedness and Response. Renewal of 
Determination that a Public Health Emergency Exists. February 9, 
2023. https://aspr.hhs.gov/legal/PHE/Pages/COVID19-9Feb2023.aspx.
    \21\ U.S. Department of Health and Human Services. Fact Sheet: 
COVID-19 Public Health Emergency Transition Roadmap. February 9, 
2023. https://www.hhs.gov/about/news/2023/02/09/fact-sheet-covid-19-public-health-emergency-transition-roadmap.html.
---------------------------------------------------------------------------

    In the FY 2022 IRF PPS final rule (86 FR 42386 through 42396) and 
in the Guidance for Staff Vaccination Requirements,\22\ we stated that 
vaccination is a critical part of the nation's strategy to effectively 
counter the spread of COVID-19. We continue to believe it is important 
to incentivize and track HCP vaccination in IRFs through quality 
measurement in order to protect health care workers, patients, and 
caregivers, and to help sustain the ability of IRFs to continue serving 
their communities throughout the PHE and beyond. At the time we issued 
the FY 2022 IRF PPS final rule, the Food and Drug Administration (FDA) 
had issued emergency use authorizations (EUAs) for COVID-19 vaccines 
manufactured by Pfizer-BioNTech,\23\ Moderna,\24\ and Janssen.\25\ On 
August 23, 2021, the FDA issued an approval for the Pfizer-BioNTech 
vaccine, marketed as Comirnaty.\26\ The FDA issued approval for the 
Moderna vaccine, marketed as Spikevax, on January 31, 2022 \27\ and an 
EUA for the Novavax vaccine, on July 13, 2022.\28\ The FDA also issued 
EUAs for single booster doses of the then authorized COVID-19 vaccines. 
As of November 19,2021,29 30 31  a single booster dose of 
each COVID-19 vaccine was authorized for all eligible individuals 18 
years of age and older. EUAs were subsequently issued for a second 
booster dose of the Pfizer-BioNTech and Moderna vaccines in certain 
populations in March 2022.\32\ FDA first authorized the use of a 
booster dose of bivalent or ``updated'' COVID-19 vaccines from Pfizer-
BioNTech and Moderna in August 2022.\33\
---------------------------------------------------------------------------

    \22\ Centers for Medicare & Medicaid Services. Revised Guidance 
for Staff Vaccination Requirements QSO-23-02-ALL. October 26, 2022. 
https://www.cms.gov/files/document/qs0-23-02-all.pdf.
    \23\ Food and Drug Administration. FDA Takes Key Action in Fight 
Against COVID-19 By Issuing Emergency Use Authorization for First 
COVID-19 Vaccine. December 11, 2020. https://www.fda.gov/news-events/press-announcements/fda-takes-key-action-fight-against-covid-19-issuing-emergency-use-authorization-first-covid-19.
    \24\ Food and Drug Administration. FDA Takes Additional Action 
in Fight Against COVID-19 By Issuing Emergency Use Authorization for 
Second COVID-19 Vaccine. December 18, 2020. https://www.fda.gov/news-events/press-announcements/fda-takes-additional-action-fight-against-covid-19-issuing-emergency-use-authorization-second-covid.
    \25\ Food and Drug Administration. FDA Issues Emergency Use 
Authorization for Third COVID-19 Vaccine. February 27, 2021. https://www.fda.gov/news-events/press-announcements/fda-issues-emergency-use-authorization-third-covid-19-vaccine.
    \26\ Food and Drug Administration. FDA Approves First COVID-19 
Vaccine. August 23, 2021. https://www.fda.gov/news-events/press-announcements/fda-approves-first-covid-19-vaccine.
    \27\ Food and Drug Administration. Coronavirus (COVID-19) 
Update: FDA Takes Key Action by Approving Second COVID-19 Vaccine. 
January 21, 2022. https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-takes-key-action-approving-second-covid-19-vaccine.
    \28\ Food and Drug Administration. Coronavirus (COVID-19) 
Update: FDA Authorizes Emergency Use of Novavax COVID-19 Vaccine, 
Adjuvanted. July 13, 2022. https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-authorizes-emergency-use-novavax-covid-19-vaccine-adjuvanted.
    \29\ Food and Drug Administration. FDA Authorizes Booster Dose 
of Pfizer-BioNTech COVID-19 Vaccine for Certain Populations. 
September 22, 2021. https://www.fda.gov/news-events/press-announcements/fda-authorizes-booster-dose-pfizer-biontech-covid-19-vaccine-certain-populations.
    \30\ Food and Drug Administration. Coronavirus (COVID-19) 
Update: FDA Takes Additional Actions on the Use of a Booster Dose 
for COVID-19 Vaccines. October 20, 2021. https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-takes-additional-actions-use-booster-dose-covid-19-vaccines.
    \31\ Food and Drug Administration. Coronavirus (COVID-19) 
Update: FDA Expands Eligibility for COVID-19 Vaccine Boosters. 
November 19, 2021. https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-expands-eligibility-covid-19-vaccine-boosters.
    \32\ Food and Drug Administration. Coronavirus (COVID-19) 
Update: FDA Authorizes Second Booster Dose of Two COVID-19 Vaccines 
for Older and Immunocompromised Individuals. March 29, 2022. https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-authorizes-second-booster-dose-two-covid-19-vaccines-older-and.
    \33\ Food and Drug Administration. (August 2022). Coronavirus 
(COVID-19) Update: FDA Authorizes Moderna, Pfizer-BioNTech Bivalent 
COVID-19 Vaccines for Use as a Booster Dose. Available at https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-authorizes-moderna-pfizer-biontech-bivalent-covid-19-vaccines-use.
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(a) Measure Importance
    In the FY2022 IRF PPS final rule (86 FR 42401), we acknowledged 
that we were still learning how effective the vaccines were against new 
variants of the virus that cause COVID-19. While the impact of COVID-19 
vaccines on asymptomatic infection and transmission is not yet fully 
known, there are now robust data available across multiple populations 
on COVID-19 vaccine effectiveness against severe illness, 
hospitalization, and death. Two-dose COVID-19 vaccines from Pfizer-
BioNTech and Moderna were found to be 88 percent and 93 percent 
effective against hospitalization for COVID-19, respectively, over 6 
months for adults over age 18 without immunocompromising 
conditions.\34\ During a SARS-CoV-2 surge in the spring and summer of 
2021, 92 percent of COVID-19 hospitalizations and 91 percent of COVID-
19 associated deaths were reported among persons not fully 
vaccinated.\35\ Real-world studies of population-level vaccine 
effectiveness indicated similarly high rates of efficacy in preventing 
SARS-CoV-2 infection among frontline workers in multiple industries, 
with a 90 percent effectiveness in preventing symptomatic and 
asymptomatic infection from

[[Page 20987]]

December 2020 through August 2021.\36\ Vaccines have also been highly 
effective in real-world conditions at preventing COVID-19 in HCP with 
up to 96 percent efficacy for fully vaccinated HCP, including those at 
risk for severe infection and those in racial and ethnic groups 
disproportionately affected by COVID-19.\37\ Overall, data demonstrate 
that COVID-19 vaccines are effective and prevent severe disease, 
hospitalization, and death.
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    \34\ Centers for Disease Control and Prevention. (September 24, 
2021). Morbidity and Mortality Weekly Report (MMWR). Comparative 
Effectiveness of Moderna, Pfizer-BioNTech, and Janssen (Johnson & 
Johnson) Vaccines in Preventing COVID-19 Hospitalizations Among 
Adults Without Immunocompromising Conditions--United States, March-
August 2021. Available at https://cdc.gov/mmwr/volumes/70/wr/mm7038e1.htm?s_cid=mm7038e1_w.
    \35\ Centers for Disease Control and Prevention. (September 10, 
2021). Morbidity and Mortality Weekly Report (MMWR). Monitoring 
Incidence of COVID-19 Cases, Hospitalizations, and Deaths, by 
Vaccination Status--13 U.S. Jurisdictions, April 4-July 17, 2021. 
Available at https://www.cdc.gov/mmwr/volumes/70/wr/mm7037e1.htm.
    \36\ Centers for Disease Control and Prevention. Morbidity and 
Mortality Weekly Report (MMWR). Effectiveness of COVID-19 Vaccines 
in Preventing SARS-CoV-2 Infection Among Frontline Workers Before 
and During B.1.617.2 (Delta) Variant Predominance--Eight U.S. 
Locations, December 2020-August 2021. August 27, 2021. https://www.cdc.gov/mmwr/volumes/70/wr/mm7034e4.htm.
    \37\ Pilishivi, T. et al. Effectiveness of mRNA COVID-19 Vaccine 
among U.S. Health Care Personnel. New England Journal of Medicine. 
2021 Dec 16;385(25):e90. December 16, 2022. https://pubmed.ncbi.nlm.nih.gov/34551224/.
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    As SARS-CoV-2 persists and evolves, our COVID-19 vaccination 
strategy must remain responsive. When we adopted the HCP COVID-19 
Vaccine measure in the FY 2022 IRF PPS final rule, we stated that the 
need for booster doses of COVID-19 vaccines had not been established 
and no additional doses had been recommended (86 FR 42390). We also 
stated that we believed the numerator was sufficiently broad to include 
potential future boosters as part of a ``complete vaccination course'' 
and that the measure was sufficiently specified to address boosters (86 
FR 42390). Since we adopted the HCP COVID-19 Vaccine measure in the FY 
2022 IRF PPS final rule, new variants of SARS-CoV-2 have emerged around 
the world and within the United States. Specifically, the Omicron 
variant (and its related subvariants) is listed as a variant of concern 
by the Centers for Disease Control and Prevention (CDC) because it 
spreads more easily than earlier variants.\38\ Vaccine manufacturers 
have responded to the Omicron variant by developing bivalent COVID-19 
vaccines, which include a component of the original virus strain to 
provide broad protection against COVID-19 and a component of the 
Omicron variant to provide better protection against COVID-19 caused by 
the Omicron variant.\39\ These booster doses of the bivalent COVID-19 
vaccines have been shown to increase immune response to SARS-CoV-2 
variants, including Omicron, particularly in individuals that are more 
than 6 months removed from receipt of their primary series.\40\ The FDA 
issued EUAs for booster doses of two bivalent COVID-19 vaccines, one 
from Pfizer-BioNTech \41\ and one from Moderna \42\ and strongly 
encourages anyone who is eligible to consider receiving a booster dose 
with a bivalent COVID-19 vaccine to provide better protection against 
currently circulating variants.\43\ COVID-19 booster doses are 
associated with a greater reduction in infections among HCP relative to 
those who only received primary series vaccination, with a rate of 
breakthrough infections among HCP who received only a two-dose regimen 
of 21.4 percent compared to a rate of 0.7 percent among HCP who 
received booster doses of the COVID-19 vaccine.44 45 
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    \38\ Centers for Disease Control and Prevention. Variants of the 
Virus. https://www.cdc.gov/coronavirus/2019-ncov/variants/index.html.
    \39\ Food and Drug Administration. COVID-19 Bivalent Vaccine 
Boosters. https://www.fda.gov/emergency-preparedness-and-response/coronavirus-disease-2019-covid-19/covid-19-bivalent-vaccine-boosters.
    \40\ Chalkias S, Harper C, Vrbicky K, et al. A Bivalent Omicron-
Containing Booster Vaccine Against COVID-19. N Engl J Med. 2022 Oct 
6;387(14):1279-1291. doi: 10.1056/NEJMoa2208343. PMID: 36112399; 
PMCID: PMC9511634.
    \41\ Food and Drug Administration. Pfizer-BioNTech COVID-19 
Vaccines. https://www.fda.gov/emergency-preparedness-and-response/coronavirus-disease-2019-covid-19/pfizer-biontech-covid-19-vaccines.
    \42\ Food and Drug Administration. Moderna COVID-19 Vaccines. 
https://www.fda.gov/emergency-preparedness-and-response/coronavirus-disease-2019-covid-19/moderna-covid-19-vaccines.
    \43\ Food and Drug Administration. Coronavirus (COVID-19) 
Update: FDA Authorizes Moderna, Pfizer-BioNTech Bivalent COVID-19 
Vaccines for Use as a Booster Dose. August 31, 2022. https://www.fda.gov/news-events/press-announcements/coronavirus-covid-19-update-fda-authorizes-moderna-pfizer-biontech-bivalent-covid-19-vaccines-use.
    \44\ Oster Y, Benenson S, Nir-Paz R, Buda I, Cohen MJ. The 
effect of a third BNT162b2 vaccine on breakthrough infections in 
health care workers: a cohort analysis. Clin Microbiol Infect. 2022 
May;28(5):735.e1-735.e3. Available online at https://pubmed.ncbi.nlm.nih.gov/35143997/.
    \45\ Prasad N et al. (May 2022). Effectiveness of a COVID-19 
Additional Primary or Booster Vaccine Dose in Preventing SARS-CoV-2 
Infection Among Nursing Home Residents During Widespread Circulation 
of the Omicron Variant--United States, February 14-March 27, 2022. 
Morbidity and Mortality Weekly Report (MMWR). 2022 May 6;71(18):633-
637. doi: 10.1016/j.cmi.2022.01.019. PMID: 35143997; PMCID: 
PMC8820100.
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    We believe that vaccination remains the most effective means to 
prevent the severe consequences of COVID-19, including severe illness, 
hospitalization, and death. Given the availability of vaccine efficacy 
data, EUAs issued by the FDA for bivalent boosters, the continued 
presence of SARS-CoV-2 in the United States, and variance among rates 
of booster dose vaccination, it is important to update the 
specifications of the HCP COVID-19 Vaccine measure to reflect most 
recent guidance that explicitly specifies for HCP to receive primary 
series and booster vaccine doses in a timely manner. Given the 
persistent spread of COVID-19, we continue to believe that monitoring 
and surveillance is important and provides patients, beneficiaries, and 
their caregivers with information to support informed decision making. 
We propose to modify the HCP COVID-19 Vaccine measure to replace the 
term ``complete vaccination course'' with the term ``up to date'' in 
the HCP vaccination definition. We also propose to update the numerator 
to specify the time frames within which an HCP is considered up to date 
with recommended COVID-19 vaccines, including booster doses, beginning 
with the FY 2025 IRF QRP.
(b) Measure Testing
    The CDC conducted beta testing of the proposed modified HCP COVID-
19 Vaccine measure by assessing if the collection of information on 
additional/booster vaccine doses received by HCP was feasible, as 
information on receipt of booster vaccine doses is required for 
determining if HCP are up to date with the current COVID-19 vaccination 
recommendations. Feasibility was assessed by calculating the proportion 
of facilities that reported booster doses of the COVID-19 vaccine. The 
assessment was conducted in various facility types, including IRFs, 
using vaccine coverage data for the first quarter of calendar year (CY) 
2022 (January--March), which was reported through the CDC's National 
Healthcare Safety Network (NHSN). Feasibility of reporting booster 
doses of vaccine is evident by the fact that 63.9 percent of IRFs 
reported vaccination booster coverage data to the NHSN for the first 
quarter of 2022.\46\ Additionally, HCP COVID-19 Vaccine measure scores 
calculated using January 1--March 31, 2022 data had a median of 20.3 
percent and an interquartile range of 8.9 to 37.7 percent, indicating a 
measure performance gap as there are clinically significant differences 
in booster/additional dose vaccination coverage rates among IRFs.\47\
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    \46\ Centers for Medicare & Medicaid Services. Measure 
Application Partnership (MAP) Post-Acute Care/Long-Term Care: 2022-
2023 Measures Under Consideration (MUC) Cycle Measure 
Specifications. December 1, 2022. https://mmshub.cms.gov/sites/default/files/map-pac-muc-measure-specifications-2022-2023.pdf.
    \47\ Centers for Medicare & Medicaid Services. Measure 
Application Partnership (MAP) Post-Acute Care/Long-Term Care: 2022-
2023 Measures Under Consideration (MUC) Cycle Measure 
Specifications. December 1, 2022. https://mmshub.cms.gov/sites/default/files/map-pac-muc-measure-specifications-2022-2023.pdf.

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[[Page 20988]]

(2) Competing and Related Measures
    Section 1886(j)(7)(D)(i) of the Act and section 1899B(e)(2)(A) of 
the Act requires that, absent an exception under section 
1886(j)(7)(D)(i) and section 1899B(e)(2)(B) of the Act, measures 
specified under section 1899B of the Act must be endorsed by a 
consensus-based entity (CBE) with a contract under section 1890(a) of 
the Act. In the case of a specified area or medical topic determined 
appropriate by the Secretary for which a feasible and practical measure 
has not been endorsed, section 1886(j)(7)(D)(i) of the Act and section 
1899B(e)(2)(B) of the Act permit the Secretary to 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 current version of the HCP COVID-19 Vaccine (``Quarterly 
Reporting of COVID-19 Vaccination Coverage among Healthcare 
Personnel'') measure recently received endorsement by the CBE on July 
26, 2022.\48\ However, this measure received endorsement based on its 
specifications depicted in the FY 2022 IRF PPS final rule (86 FR 42386 
through 42396), and does not capture information about whether HCP are 
``up to date'' with their COVID-19 vaccinations. The proposed 
modification of this measure utilizes the term up to date in the HCP 
vaccination definition and updates the numerator to specify the time 
frames within which an HCP is considered up to date with recommended 
COVID-19 vaccines, including booster doses. We were unable to identify 
any CBE endorsed measures for IRFs that captured information on whether 
HCP are up to date with their COVID-19 vaccinations, and we found no 
other feasible and practical measure on this topic.
---------------------------------------------------------------------------

    \48\ National Quality Forum. 3636 Quarterly Reporting of COVID-
19 Vaccination Coverage among Healthcare Personnel. Accessed 
February 6, 2023. Available at https://www.qualityforum.org/QPS/3636.
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    Therefore, after consideration of other available measures, we find 
that the exception under section 1899B(e)(2)(B) of the Act applies and 
are proposing the modified measure, HCP COVID-19 Vaccine beginning with 
the FY 2025 IRF QRP. The CDC, the measure developer, is pursuing CBE 
endorsement for the modified version of the measure and is considering 
an expedited review process as the current version of the measure has 
already received endorsement.
(3) Measure Application Partnership (MAP) Review
    We refer readers to the FY 2022 IRF PPS final rule (86 FR 42387 
through 42388) for more information on the initial review of the HCP 
COVID-19 Vaccine measure by the Measure Application Partnership (MAP).
    The pre-rulemaking 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 
for use in the Medicare program, including our quality reporting 
programs. This allows interested parties to provide recommendations to 
the Secretary on the measures included on the list. We included an 
updated version of the HCP COVID-19 Vaccine measure on the MUC List, 
entitled ``List of Measures under Consideration for December 1, 2022'' 
\49\ for the 2022-2023 pre-rulemaking cycle for consideration by the 
MAP. Interested parties submitted three comments during the pre-
rulemaking process on the proposed modifications of the HCP COVID-19 
Vaccine measure, and support was mixed. One commenter noted the 
importance for HCP to be vaccinated against COVID-19 and supported 
measurement and reporting as an important strategy to help healthcare 
organizations assess their performance in achieving high rates of up to 
date vaccination of their HCP, while also noting that the measure would 
provide valuable information to the government as part of its ongoing 
response to the pandemic. This commenter also recommended the measure 
be used for internal quality improvement purposes rather than being 
publicly reported on Care Compare. Finally, this commenter also 
suggested that the measure should be stratified by social risk factors. 
However, two commenters supported less specific criteria for 
denominator and numerator inclusion. Specifically, one such commenter 
did not support the inclusion of unpaid volunteers in the measure 
denominator and found the measure's denominator to be unclear. Two 
commenters expressed concerns regarding burden of data collection, data 
lag, staffing challenges, and reportedly ``high rates of providers 
contesting penalties tied to the existing HCP COVID-19 Vaccine measure 
adopted in the FY 2022 IRF PPS final rule.'' One commenter recommended 
that the measure be recharacterized as a surveillance measure given 
what they referred to as a tenuous relationship between collected data 
and quality of care provided by IRFs. Finally, all three commenters 
raised concern about the difficulty of defining up to date for purposes 
of the measure.
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    \49\ Centers for Medicare & Medicaid Services. Overview of the 
List of Measures Under Consideration for December 1, 2022. CMS.gov. 
https://mmshub.cms.gov/sites/default/files/2022-MUC-List-Overview.pdf.
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    Shortly after publication of the MUC List, several MAP workgroups 
met to provide input on the modification we are proposing for the 
current HCP COVID-19 Vaccine measure. First, the MAP Health Equity 
Advisory Group convened on December 6-7, 2022. The MAP Health Equity 
Advisory Group questioned whether the measure excludes patients with 
contraindications to FDA authorized or approved COVID-19 vaccines, and 
whether the measure will be stratified by demographic factors. The 
measure developer (that is the CDC) confirmed that HCP with 
contraindications to the vaccines are excluded from the measure 
denominator, and responded that the measure will not be stratified by 
demographic factors since the data are submitted at an aggregate rather 
than an individual level.
    The MAP Rural Health Advisory Group met on December 8-9, 2022, 
during which a few members expressed concerns about data collection 
burden, given that small rural hospitals may not have employee health 
software. The measure developer acknowledged the challenge of getting 
adequate documentation and emphasized their goal is to ensure the 
measures do not present a burden on the provider. The measure developer 
also noted that the model used for the HCP COVID-19 Vaccine measure is 
based on the Influenza Vaccination Coverage among HCP measure (CBE 
#0431), and it intends to utilize a similar approach to the modified 
HCP COVID-19 Vaccine measure if vaccination strategy becomes seasonal. 
The measure developer acknowledged that if COVID-19 becomes seasonal, 
the measure model could evolve to capture seasonal vaccination.
    Next, the MAP Post-Acute Care/Long-Term Care (PAC/LTC) workgroup 
met on December 12, 2022 and provided input on the modification we are 
proposing for the HCP COVID-19 Vaccine measure. The MAP noted that the 
previous version of the measure received endorsement from the CBE (CBE 
#3636),\50\ and that the CDC intends to submit the updated measure for

[[Page 20989]]

endorsement. The PAC/LTC workgroup voted to support the staff 
recommendation of conditional support for rulemaking pending testing 
indicating the measure is reliable and valid, and endorsement by the 
consensus-based entity (CBE).
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    \50\ National Quality Forum. 3636 Quarterly Reporting of COVID-
19 Vaccination Coverage among Healthcare Personnel. Accessed 
February 6, 2023. https://www.qualityforum.org/QPS/3636.
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    Following the PAC/LTC workgroup meeting, a public comment period 
was held in which interested parties commented on the PAC/LTC 
workgroup's preliminary recommendations, and the MAP received three 
comments. Two supported the proposed modification of the HCP COVID-19 
Vaccine measure, one of which strongly supported the vaccination of HCP 
against COVID-19. Although these commenters supported the measure, one 
commenter recommended seeking NQF endorsement for the updated measure, 
and encouraged CMS to monitor any unintended consequences from the 
measure. Two commenters raised concerns with the measure's 
specifications. Specifically, one noted the denominator included a 
broad number of HCP, and another recommended a vaccination exclusion or 
exception for sincerely held religious beliefs. Finally, one commenter 
raised issues related to the time lag between data collection and 
public reporting on Care Compare and encouraged CMS to provide 
information as to whether the measure is reflecting vaccination rates 
accurately and encouraging HCP vaccination.
    The MAP Coordinating Committee convened on January 24-25, 2023, 
during which the proposed measure was placed on the consent calendar 
and received a final recommendation of conditional support for 
rulemaking pending testing indicating the measure is reliable and 
valid, and endorsement by the CBE. We refer readers to the final MAP 
recommendations, titled 2022-2023 MAP Final Recommendations.\51\
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    \51\ 2022-2023 MAP Final Recommendations. https://mmshub.cms.gov/sites/default/files/2022-2023-MAP-Final-Recommendations-508.xlsx.
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(4) Quality Measure Calculation
    The HCP COVID-19 Vaccine measure is a process measure developed by 
the CDC to track COVID-19 vaccination coverage among HCP in facilities 
such as IRFs. The HCP COVID-19 Vaccine measure is a process measure and 
is not risk-adjusted.
    The denominator would be the number of HCP eligible to work in the 
facility for at least one day during the reporting period, excluding 
persons with contraindications to COVID-19 vaccination that are 
described by the CDC.\52\ We believe it is necessary to allow IRFs to 
include all HCP within the facility in the reporting because all HCP 
would have access to and may interact with IRF patients. IRFs report 
the following four categories of HCP to NHSN; the first three are 
included in the measure denominator:
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    \52\ Centers for Disease Control and Prevention. 
Contraindications and precautions. https://www.cdc.gov/vaccines/covid-19/clinical-considerations/interim-considerations-us.html#contraindications.
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     Employees: Includes all persons who receive a direct 
paycheck from the reporting facility (that is, on the facility's 
payroll), regardless of clinical responsibility or patient contact.
     Licensed independent practitioners (LIPs): This includes 
physicians (MD, DO), advanced practice nurses, and physician assistants 
only who are affiliated with the reporting facility but are not 
directly employed by it (that is, they do not receive a direct paycheck 
from the facility), regardless of clinical responsibility or patient 
contact. Post-residency fellows are also included in this category if 
they are not on the facility's payroll.
     Adult students/trainees and volunteers: This includes all 
medical, nursing, or other health professional, students, interns, 
medical residents and volunteers aged 18 or over who are affiliated 
with the healthcare facility, but are not directly employed by it (that 
is, they do not receive a direct paycheck from the facility) regardless 
of clinical responsibility or patient contact.
     Other contract personnel: Contract personnel are defined 
as persons providing care, treatment, or services at the facility 
through a contract who do not fall into any of the above-mentioned 
denominator categories. This also includes vendors providing care, 
treatment, or services at the facility who may or may not be paid 
through a contract. Facilities are required to enter data on other 
contract personnel for submission in the NHSN application, but data for 
this category are not included in the HCP COVID-19 Vaccine measure.
    The denominator excludes denominator-eligible individuals with 
contraindications as defined by the CDC.\53\ We are not proposing any 
changes to the denominator exclusions.
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    \53\ Centers for Disease Control and Prevention. 
Contraindications and precautions. https://www.cdc.gov/vaccines/covid-19/clinical-considerations/interim-considerations-us.html#contraindications.
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    The numerator would be the cumulative number of HCP in the 
denominator population who are considered up to date with CDC 
recommended COVID-19 vaccines. Providers should refer to the definition 
of up to date as of the first day of the quarter, which can be found at 
https://www.cdc.gov/nhsn/pdfs/hps/covidvax/UpToDateGuidance-508.pdf. 
For the purposes of NHSN surveillance, individuals would have been 
considered up to date during in the Quarter 4 CY 2022 reporting period 
(surveillance period September 26, 2022-December 25, 2022) for the IRF 
QRP if they meet one of the following criteria in place at the time:
    1. Individuals who received an updated bivalent \54\ booster dose, 
or
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    \54\ The updated (bivalent) Moderna and Pfizer-BioNTech boosters 
target the most recent Omicron subvariants. The updated (bivalent) 
boosters were recommended by the CDC on September 2, 2022. As of 
this date, the original, monovalent mRNA vaccines are no longer 
authorized as a booster dose for people ages 12 years and older.
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    2a. Individuals who received their last booster dose less than 2 
months ago, or
    2b. Individuals who completed their primary series \55\ less than 2 
months ago.
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    \55\ Completing a primary series means receiving a two-dose 
series of a COVID-19 vaccine or a single dose of Janssen/J&J COVID-
19 vaccine.
---------------------------------------------------------------------------

    We refer readers to https://www.cdc.gov/nhsn/nqf/index.html for 
more details on the measure specifications.
    While we are not proposing any changes to the data submission or 
reporting process for the HCP COVID-19 Vaccine measure, we are 
proposing that for purposes of meeting FY 2025 IRF QRP compliance, IRFs 
would report individuals who are up to date beginning in quarter four 
of CY 2023. Under the data submission and reporting process, IRFs would 
collect the numerator and denominator for the modified HCP COVID-19 
Vaccine measure for at least one self-selected week during each month 
of the reporting quarter and submit the data to the NHSN Healthcare 
Personnel Safety (HPS) Component before the quarterly deadline. If an 
IRF submits more than 1 week of data in a month, the CDC would use the 
most recent week's data to calculate the measure. Each quarter, the CDC 
would calculate a single quarterly COVID-19 HCP vaccination coverage 
rate for each IRF, which would be calculated by taking the average of 
the data from the three weekly rates submitted by the IRF for that 
quarter. Beginning with the FY 2026 IRF QRP, we propose that IRFs would 
be required to submit data for the entire calendar year.
    We are also proposing that public reporting of the modified version 
of the HCP COVID-19 Vaccine measure would begin by the September 2024 
Care

[[Page 20990]]

Compare refresh or as soon as technically feasible.
    We invite public comment on our proposal to modify the COVID-19 
Vaccination Coverage among Healthcare Personnel (HCP) measure beginning 
with the FY 2025 IRF QRP.
b. Proposed Adoption of Discharge Function Score Measure Beginning With 
the FY 2025 IRF QRP
(1) Background
    IRFs provide rehabilitation therapy in a resource-intensive 
inpatient hospital environment to patients with complex nursing, 
medical management, and rehabilitation needs, who require and can 
reasonably be expected to benefit from the multidisciplinary care 
provided in an IRF. Patients tend to have neurological conditions such 
as stroke, spinal cord injury, and brain injury; degenerative 
conditions including multiple sclerosis; congenital deformities; 
amputations; burns; active inflammatory conditions; severe or advanced 
osteoarthritis; or knee and hip joint replacements.\56\ In 2019, the 
most common condition treated by IRFs was stroke, which accounted for 
about one-fifth of IRF cases.\57\ For stroke patients, rehabilitation 
has been shown to be the most effective way to reduce stroke-associated 
motor impairments. Addressing these impairments is crucial as 
functional deficits affect patients' mobility, their capabilities in 
daily life activities, and their participation in society, which can 
lead to a lower quality of life.\58\
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    \56\ 42 CFR 412.29.
    \57\ Medicare Payment Advisory Commission. Report to the 
Congress: Medicare and the Health Care Delivery System. June 2021. 
https://www.medpac.gov/wp-content/uploads/import_data/scrape_files/docs/default-source/reports/jun21_medpac_report_to_congress_sec.pdf.
    \58\ Hatem SM, Saussez G, Della Faille M, Prist V, Zhang X, 
Dispa D, Bleyenheuft Y. Rehabilitation of Motor Function After 
Stroke: A Multiple Systematic Review Focused on Techniques to 
Stimulate Upper Extremity Recovery. Front Hum Neurosci. 2016 Sep 
13;10:442. doi: 10.3389/fnhum.2016.00442. PMID: 27679565; PMCID: 
PMC5020059.
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    Section 1886(j)(7)(F)(i) of the Act, cross-referencing subsections 
(b), (c), and (d) of section 1899B of the Act, requires CMS to develop 
and implement standardized quality measures from five quality measure 
domains, including the domain of functional status, cognitive function, 
and changes in function and cognitive function, across post-acute care 
(PAC) settings, including IRFs. To satisfy this requirement, we adopted 
the Application of Percent of Long-Term Care Hospital (LTCH) Patients 
with an Admission and Discharge Functional Assessment and a Care Plan 
That Addresses Function (Application of Functional Assessment/Care 
Plan) measure for the IRF QRP in the FY 2016 IRF PPS final rule (80 FR 
47100 through 47111). While this process measure allowed for the 
standardization of functional assessments across assessment instruments 
and facilitated cross-setting data collection, quality measurement, and 
interoperable data exchange, we believe it is now topped out \59\ and 
are proposing to remove it in section VIII.C.1.c. of this proposed 
rule. While there are other outcome measures addressing functional 
status \60\ that can reliably distinguish performance among providers 
in the IRF QRP, these outcome measures are not cross-setting in nature 
because they rely on functional status items not collected in all PAC 
settings. In contrast, a cross-setting functional outcome measure would 
align measure specifications across settings, including the use of a 
common set of standardized functional assessment data elements.
---------------------------------------------------------------------------

    \59\ Centers for Medicare & Medicaid Services. 2022 Annual Call 
for Quality Measures Fact Sheet, p. 10. https://www.cms.gov/files/document/mips-call-quality-measures-overview-fact-sheet-2022.pdf.
    \60\ The measures include: Change in Self-Care Score for Medical 
Rehabilitation Patients (Change in Mobility for Medical 
Rehabilitation Patients, Discharge Self-Care Score for Medical 
Rehabilitation Patients), Discharge Mobility Score for Medical 
Rehabilitation Patients.
---------------------------------------------------------------------------

(a) Measure Importance
    Maintenance or improvement of physical function among older adults 
is increasingly an important focus of health care. Adults age 65 years 
and older constitute the most rapidly growing population in the United 
States, and functional capacity in physical (non-psychological) domains 
has been shown to decline with age.\61\ Moreover, impaired functional 
capacity is associated with poorer quality of life and an increased 
risk of all-cause mortality, postoperative complications, and cognitive 
impairment, the latter of which can complicate the return of a patient 
to the community from post-acute care.62 63 64 Nonetheless, 
evidence suggests that physical functional abilities, including 
mobility and self-care, are modifiable predictors of patient outcomes 
across PAC settings, including functional recovery or decline after 
post-acute care,65 66 67 68
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    \61\ High KP, Zieman S, Gurwitz J, Hill C, Lai J, Robinson T, 
Schonberg M, Whitson H. Use of Functional Assessment to Define 
Therapeutic Goals and Treatment. J Am Geriatr Soc. 2019 
Sep;67(9):1782-1790. doi: 10.1111/jgs.15975. Epub 2019 May 13. PMID: 
31081938; PMCID: PMC6955596.
    \62\ Clouston SA, Brewster P, Kuh D, Richards M, Cooper R, Hardy 
R, Rubin MS, Hofer SM. The Dynamic Relationship between Physical 
Function and Cognition in Longitudinal Aging Cohorts. Epidemiol Rev. 
2013;35(1):33-50. doi: 10.1093/epirev/mxs004. Epub 2013 Jan 24. 
PMID: 23349427; PMCID: PMC3578448.
    \63\ Michael YL, Colditz GA, Coakley E, Kawachi I. Health 
Behaviors, Social Networks, and Healthy Aging: Cross-Sectional 
Evidence from the Nurses' Health Study. Qual Life Res. 1999 
Dec;8(8):711-22. doi: 10.1023/a:1008949428041. PMID: 10855345.
    \64\ High KP, Zieman S, Gurwitz J, Hill C, Lai J, Robinson T, 
Schonberg M, Whitson H. Use of Functional Assessment to Define 
Therapeutic Goals and Treatment. J Am Geriatr Soc. 2019 
Sep;67(9):1782-1790. doi: 10.1111/jgs.15975. Epub 2019 May 13. PMID: 
31081938; PMCID: PMC6955596.
    \65\ Deutsch A, Palmer L, Vaughan M, Schwartz C, McMullen T. 
Inpatient Rehabilitation Facility Patients' Functional Abilities and 
Validity Evaluation of the Standardized Self-Care and Mobility Data 
Elements. Arch Phys Med Rehabil. 2022 Feb 11:S0003-9993(22)00205-2. 
doi: 10.1016/j.apmr.2022.01.147. Epub ahead of print. PMID: 
35157893.
    \66\ Hong I, Goodwin JS, Reistetter TA, Kuo YF, Mallinson T, 
Karmarkar A, Lin YL, Ottenbacher KJ. Comparison of Functional Status 
Improvements Among Patients With Stroke Receiving Postacute Care in 
Inpatient Rehabilitation vs Skilled Nursing Facilities. JAMA Netw 
Open. 2019 Dec 2;2(12):e1916646. doi: 10.1001/
jamanetworkopen.2019.16646. PMID: 31800069; PMCID: PMC6902754.
    \67\ Alcusky M, Ulbricht CM, Lapane KL. Postacute Care Setting, 
Facility Characteristics, and Poststroke Outcomes: A Systematic 
Review. Arch Phys Med Rehabil. 2018;99(6):1124-1140.e9. doi: 
10.1016/j.apmr.2017.09.005. PMID: 28965738; PMCID: PMC5874162.
    \68\ Chu CH, Quan AML, McGilton KS. Depression and Functional 
Mobility Decline in Long Term Care Home Residents with Dementia: a 
Prospective Cohort Study. Can Geriatr J. 2021;24(4):325-331. doi: 
10.5770/cgj.24.511. PMID: 34912487; PMCID: PMC8629506.

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[[Page 20991]]

rehospitalization rates,69 70 71 discharge to 
community,72 73 and falls.\74\
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    \69\ Li CY, Haas A, Pritchard KT, Karmarkar A, Kuo YF, Hreha K, 
Ottenbacher KJ. Functional Status Across Post-Acute Settings Is 
Associated With 30-Day and 90-Day Hospital Readmissions. J Am Med 
Dir Assoc. 2021 Dec;22(12):2447-2453.e5. doi: 10.1016/
j.jamda.2021.07.039. Epub 2021 Aug 30. PMID: 34473961; PMCID: 
PMC8627458.
    \70\ Middleton A, Graham JE, Lin YL, Goodwin JS, Bettger JP, 
Deutsch A, Ottenbacher KJ. Motor and Cognitive Functional Status Are 
Associated with 30-day Unplanned Rehospitalization Following Post-
Acute Care in Medicare Fee-for-Service Beneficiaries. J Gen Intern 
Med. 2016 Dec;31(12):1427-1434. doi: 10.1007/s11606-016-3704-4. Epub 
2016 Jul 20. PMID: 27439979; PMCID: PMC5130938.
    \71\ Gustavson AM, Malone DJ, Boxer RS, Forster JE, Stevens-
Lapsley JE. Application of High-Intensity Functional Resistance 
Training in a Skilled Nursing Facility: An Implementation Study. 
Phys Ther. 2020;100(10):1746-1758. doi: 10.1093/ptj/pzaa126. PMID: 
32750132; PMCID: PMC7530575.
    \72\ Minor M, Jaywant A, Toglia J, Campo M, O'Dell MW. Discharge 
Rehabilitation Measures Predict Activity Limitations in Patients 
with Stroke Six Months after Inpatient Rehabilitation. Am J Phys Med 
Rehabil. 2021 Oct 20. doi: 10.1097/PHM.0000000000001908. Epub ahead 
of print. PMID: 34686630.
    \73\ Dubin R, Veith JM, Grippi MA, McPeake J, Harhay MO, 
Mikkelsen ME. Functional Outcomes, Goals, and Goal Attainment among 
Chronically Critically Ill Long-Term Acute Care Hospital Patients. 
Ann Am Thorac Soc. 2021;18(12):2041-2048. doi: 10.1513/
AnnalsATS.202011-1412OC. PMID: 33984248; PMCID: PMC8641806.
    \74\ Hoffman GJ, Liu H, Alexander NB, Tinetti M, Braun TM, Min 
LC. Posthospital Fall Injuries and 30-Day Readmissions in Adults 65 
Years and Older. JAMA Netw Open. 2019 May 3;2(5):e194276. doi: 
10.1001/jamanetworkopen.2019.4276. PMID: 31125100; PMCID: 
PMC6632136.
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    The implementation of interventions that improve patients' 
functional outcomes and reduce the risks of associated undesirable 
outcomes as a part of a patient-centered care plan is essential to 
maximizing functional improvement. For many people, the overall goals 
of IRF care may include optimizing functional improvement, returning to 
a previous level of independence, or avoiding institutionalization. 
Several studies have reported that IRF care can improve patients' motor 
function at discharge for patients with various diagnoses, including 
traumatic brain injury and stroke.75 76 77 78 While patients 
generally improve in all functional domains at IRF discharge, evidence 
has shown that a significant number of patients continue to exhibit 
deficits in the domains of fall risk, gait speed, and cognition, 
suggesting the need for ongoing treatment. Assessing functional status 
as a health outcome in IRFs can provide valuable information in 
determining treatment decisions throughout the care continuum, such as 
the need for rehabilitation services and discharge 
planning,79 80 81 82 as well as provide information to 
consumers about the effectiveness of rehabilitation and other IRF 
services delivered. Because evidence shows that older adults experience 
aging heterogeneously and require individualized and comprehensive 
health care, functional status can serve as a vital component in 
informing the provision of health care and thus indicate an IRF's 
quality of care.83 84
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    \75\ Evans E, Krebill C, Gutman R, Resnik L, Zonfrillo MR, 
Lueckel SN, Zhang W, Kumar RG, Dams-O'Connor K, Thomas KS. 
Functional Motor Improvement during Inpatient Rehabilitation among 
Older Adults with Traumatic Brain Injury. PM R. 2022 Apr;14(4):417-
427. doi: 10.1002/pmrj.12644. PMID: 34018693; PMCID: PMC8606011.
    \76\ Kowalski RG, Hammond FM, Weintraub AH, Nakase-Richardson R, 
Zafonte RD, Whyte J, Giacino JT. Recovery of Consciousness and 
Functional Outcome in Moderate and Severe Traumatic Brain Injury. 
JAMA Neurol. 2021;78(5):548-557. doi: 10.1001/jamaneurol.2021.0084. 
PMID: 33646273; PMCID: PMC7922241.
    \77\ Li CY, Karmarkar A, Kuo YF, Haas A, Ottenbacher KJ. Impact 
of Self-Care and Mobility on One or More Post-Acute Care 
Transitions. J Aging Health. 2020;32(10):1325-1334. doi: 10.1177/
0898264320925259. PMID: 32501126; PMCID: PMC7718286.
    \78\ O'Dell MW, Jaywant A, Frantz M, Patel R, Kwong E, Wen K, 
Taub M, Campo M, Toglia J. Changes in the Activity Measure for Post-
Acute Care Domains in Persons With Stroke During the First Year 
After Discharge From Inpatient Rehabilitation. Arch Phys Med 
Rehabil. 2021 Apr;102(4):645-655. doi: 10.1016/j.apmr.2020.11.020. 
PMID: 33440132.
    \79\ Harry M, Woehrle T, Renier C, Furcht M, Enockson M. 
Predictive Utility of the Activity Measure for Post-Acute Care `6-
Clicks' Short Forms on Discharge Disposition and Effect on 
Readmissions: A Retrospective Observational Cohort Study. BMJ Open. 
2021;11:e044278. doi: 10.1136/bmjopen-2020-044278. PMID: 33478966; 
PMCID: PMC7825271.
    \80\ Chang FH, Lin YN, Liou TH, Lin JC, Yang CH, Cheng HL. 
Predicting Admission to Post-Acute Inpatient Rehabilitation in 
Patients with Acute Stroke. J Rehabil Med. 2020 Sep 
28;52(9):jrm00105. doi: 10.2340/16501977-2739. PMID: 32924065.
    \81\ Warren M, Knecht J, Verheijde J, Tompkins J. Association of 
AM-PAC ``6-Clicks'' Basic Mobility and Daily Activity Scores With 
Discharge Destination. Phys Ther. 2021 Apr;101(4): pzab043. doi: 
10.1093/ptj/pzab043. PMID: 33517463.
    \82\ Covert S, Johnson JK, Stilphen M, Passek S, Thompson NR, 
Katzan I. Use of the Activity Measure for Post-Acute Care ``6 
Clicks'' Basic Mobility Inpatient Short Form and National Institutes 
of Health Stroke Scale to Predict Hospital Discharge Disposition 
After Stroke. Phys Ther. 2020 Aug 31;100(9):1423-1433. doi: 10.1093/
ptj/pzaa102. PMID: 32494809.
    \83\ Criss MG, Wingood M, Staples WH, Southard V, Miller KL, 
Norris TL, Avers D, Ciolek CH, Lewis CB, Strunk ER. APTA Geriatrics' 
Guiding Principles for Best Practices in Geriatric Physical Therapy: 
An Executive Summary. J Geriatr Phys Ther. 2022 Apr-June;45(2):70-
75. doi: 10.1519/JPT.0000000000000342. PMID: 35384940.
    \84\ Cogan AM, Weaver JA, McHarg M, Leland NE, Davidson L, 
Mallinson T. Association of Length of Stay, Recovery Rate, and 
Therapy Time per Day With Functional Outcomes After Hip Fracture 
Surgery. JAMA Netw Open. 2020 Jan 3;3(1):e1919672. doi: 10.1001/
jamanetworkopen.2019.19672. PMID: 31977059; PMCID: PMC6991278.
---------------------------------------------------------------------------

    We are proposing to adopt the Discharge Function Score (DC 
Function) measure \85\ in the IRF QRP beginning with the FY 2025 IRF 
QRP. This assessment-based outcome measure evaluates functional status 
by calculating the percentage of IRF patients who meet or exceed an 
expected discharge function score. We are proposing that this measure 
would replace the topped-out Application of Functional Assessment/Care 
Plan cross-setting process measure. Like the Application of Functional 
Assessment/Care Plan cross-setting process measure, the proposed DC 
Function measure is calculated using standardized patient assessment 
data from the IRF Patient Assessment Instrument (IRF-PAI).
---------------------------------------------------------------------------

    \85\ Discharge Function Score for Inpatient Rehabilitation 
Facilities (IRFs) Technical Report. https://www.cms.gov/files/document/irf-discharge-function-score-technical-report-february-2023.pdf.
---------------------------------------------------------------------------

    The DC Function measure supports our current priorities. 
Specifically, the measure aligns with the Streamline Quality 
Measurement domain in CMS's Meaningful Measures 2.0 Framework in two 
ways. First, the proposed outcome measure could further CMS's objective 
to prioritize outcome measures by replacing the current cross-setting 
process measure (see section VIII.C.1.c. of this proposed rule). This 
proposed DC Function measure uses a set of cross-setting assessment 
items which would facilitate data collection, quality measurement, 
outcome comparison, and interoperable data exchange among PAC settings; 
existing functional outcome measures do not use a set of cross-setting 
assessment items. Second, this measure adds no additional provider 
burden since it would be calculated using data from the IRF-PAI that 
IRFs are already required to collect.
    The proposed DC Function measure would also follow a calculation 
approach similar to the existing functional outcome measures, which are 
endorsed by the CBE, with some modifications.\86\ Specifically, the 
measure (1) considers two dimensions of function \87\ (self-care and 
mobility activities) and (2) accounts for missing data by using 
statistical imputation to improve the validity of measure

[[Page 20992]]

performance. The statistical imputation approach recodes missing 
functional status data to the most likely value had the status been 
assessed, whereas the current imputation approach implemented in 
existing functional outcome measures recodes missing data to the lowest 
functional status. A benefit of statistical imputation is that it uses 
patient characteristics to produce an unbiased estimate of the score on 
each item with a missing value. In contrast, the current approach 
treats patients with missing values and patients who were coded to the 
lowest functional status similarly, despite evidence suggesting varying 
measure performance between the two groups, which can to lead less 
accurate measure performances.
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    \86\ The existing measures are the IRF Functional Outcome 
Measure: Discharge Self-Care Score for Medical Rehabilitation 
Patients measure (Discharge Self-Care Score), and the Inpatient 
Rehabilitation Facility (IRF) Functional Outcome Measure: Discharge 
Mobility Score for Medical Rehabilitation Patients measures 
(Discharge Mobility Score).
    \87\ Post-Acute Care Payment Reform Demonstration Report to 
Congress Supplement--Interim Report. May 2011. Available at https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/Reports/Downloads/GAGE_PACPRD_RTC_Supp_Materials_May_2011.pdf.
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(b) Measure Testing
    The measure development contractor used FY 2019 data to conduct 
testing on the DC Function measure to assess validity, reliability, and 
reportability, all of which informed interested parties' feedback and 
Technical Expert Panel (TEP) input (see section VIII.C.1.b.(3) of this 
proposed rule). Validity was assessed for the measure performance, the 
risk adjustment model, face validity, and statistical imputation 
models. Validity testing of measure performance entailed determining 
Spearman's rank correlations between the proposed measure's performance 
for providers with 20 or more stays and the performance of other 
publicly reported IRF quality measures. Results indicated that the 
proposed DC Function measure captures the intended outcome based on the 
directionalities and strengths of correlation coefficients and are 
further detailed below in Table 18.

  Table 18--Spearman's Rank Correlation Results of DC Function Measure
               With Publicly Reported IRF Quality Measures
------------------------------------------------------------------------
          Measure--long name              Measure--short name     [rho]
------------------------------------------------------------------------
Discharge to Community--PAC IRF QRP..  Discharge to Community..     0.25
IRF Functional Outcome Measure:        Change in Self-Care          0.82
 Change in Self-Care Score for          Score.
 Medical Rehabilitation Patients.
IRF Functional Outcome Measure:        Change in Mobility Score     0.86
 Change in Mobility Score for Medical
 Rehabilitation Patients.
IRF Functional Outcome Measure:        Discharge Self-Care          0.85
 Discharge Self-Care Score for          Score.
 Medical Rehabilitation Patients.
IRF Functional Outcome Measure:        Discharge Mobility Score     0.88
 Discharge Mobility Score for Medical
 Rehabilitation Patients.
------------------------------------------------------------------------

    Validity testing of the risk adjustment model showed good model 
discrimination as the measure model has the predictive ability to 
distinguish patients with low expected functional capabilities from 
those with high expected functional capabilities.\88\ The ratios of 
observed-to-predicted discharge function score across eligible stays, 
by deciles of expected functional capabilities, ranged from 0.99 to 
1.01. Both the Cross-Setting Discharge Function TEPs and patient-family 
feedback showed strong support for the face validity and importance of 
the proposed measure as an indicator of quality of care (see section 
VIII.C.1.b.(3) of this proposed rule). Lastly, validity testing of the 
measure's statistical imputation models indicated that the models 
demonstrate good discrimination and produce more precise and accurate 
estimates of function scores for items with missing scores when 
compared to the current imputation approach implemented in IRF QRP 
functional outcome measures, specifically the IRF Functional Outcome 
Measure: Change in Self-Care Score for Medical Rehabilitation Patients 
measure (Change in Self-Care Score), the IRF Functional Outcome 
Measure: Change in Mobility Score for Medical Rehabilitation Patients 
measure (Change in Mobility Score), the IRF Functional Outcome Measure: 
Discharge Self-Care Score for Medical Rehabilitation Patients measure 
(Discharge Self-Care Score), and the IRF Functional Outcome Measure: 
Discharge Mobility Score for Medical Rehabilitation Patients measure 
(Discharge Mobility Score).
---------------------------------------------------------------------------

    \88\ ``Expected functional capabilities'' is defined as the 
predicted discharge function score.
---------------------------------------------------------------------------

    Reliability and reportability testing also yielded results that 
support the proposed DC Function measure's scientific acceptability. 
Split-half testing revealed the proposed measure's excellent 
reliability, indicated by an intraclass correlation coefficient value 
of 0.95. Reportability testing indicated high reportability (98 
percent) of IRFs meeting the public reporting threshold of 20 eligible 
stays. For additional measure testing details, we refer readers to the 
document titled Discharge Function Score for Inpatient Rehabilitation 
Facilities (IRFs) Technical Report.\89\
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    \89\ Discharge Function Score for Inpatient Rehabilitation 
Facilities (IRFs) Technical Report. https://www.cms.gov/files/document/irf-discharge-function-score-technical-report-february-2023.pdf.
---------------------------------------------------------------------------

(2) Competing and Related Measures
    Section 1886(j)(7)(D)(i) of the Act and section 1899B(e)(2)(A) of 
the Act require that, absent an exception under section 
1886(j)(7)(D)(i) and 1899B(e)(2)(B) of the Act, measures specified 
under section 1886(j)(7)(D)(i) of the Act and section 1899B of the Act 
must be endorsed by the CBE with a contract under section 1890(a). 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 and section 
1899B(e)(2)(B) of the Act permit the Secretary to 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 CBE identified by the 
Secretary.
    The proposed DC Function measure is not CBE endorsed, so we 
considered whether there are other available measures that: (1) assess 
both functional domains of self-care and mobility in IRFs and (2) 
satisfy the requirement of the Act to develop and implement 
standardized quality measures from the quality measure domain of 
functional status, cognitive function, and changes in function and 
cognitive function across the PAC settings. While the Application of 
Functional Assessment/Care Plan measure assesses both functional 
domains and satisfies the Act's requirement, this current cross-setting 
process measure is not endorsed by a CBE and the performance on the 
Application of Functional Assessment/Care Plan measure among IRFs is so 
high and unvarying that this current measure does not offer meaningful 
distinctions in performance. Additionally, after review of other CBE 
endorsed measures, we were unable to identify any CBE endorsed measures 
for IRFs that meet the aforementioned requirements. While the IRF QRP 
includes CBE endorsed outcome measures addressing functional 
status,\90\

[[Page 20993]]

they each assess a single domain of function, and are not cross-setting 
in nature because they rely on functional status items not collected in 
all PAC settings.
---------------------------------------------------------------------------

    \90\ The measures include: Change in Self-Care Score for Medical 
Rehabilitation Patients Change in Mobility Score for Medical 
Rehabilitation Patients, Discharge Self-Care Score for Medical 
Rehabilitation Patients, and Discharge Mobility Score for Medical 
Rehabilitation Patients.
---------------------------------------------------------------------------

    Therefore, after consideration of other available measures, we find 
that the exception under section 1899B(e)(2)(B) of the Act applies and 
are proposing to adopt the DC Function measure beginning with the FY 
2025 IRF QRP. We intend to submit the proposed measure to the CBE for 
consideration of endorsement when feasible.
(3) Interested Parties and Technical Expert Panel (TEP) Input
    In our development and specification of this measure, we employed a 
transparent process in which we sought input from interested parties 
and national experts and engaged in a process that allowed for pre-
rulemaking input in accordance with section 1890A of the Act. To meet 
this requirement, we provided the following opportunities for input 
from interested parties: a patient and family/caregiver advocates (PFA) 
focus group, two TEPs, and public comments through a request for 
information (RFI). First, the measure development contractor convened a 
PFA focus group, during which patients and caregivers provided support 
for the proposed measure concept. Participants emphasized the 
importance of measuring functional outcomes and found self-care and 
mobility to be critical aspects of care. Additionally, they expressed a 
strong interest in metrics assessing the number of patients discharged 
from particular facilities with improvements in self-care and mobility, 
and their views of self-care and mobility aligned with the functional 
domains captured by the proposed measure. All feedback was used to 
inform measure development efforts. The measure development contractor 
for the DC Function measure subsequently convened TEPs on July 14-15, 
2021 and January 26-27, 2022 to obtain expert input on the development 
of a cross-setting function measure for use in the IRF QRP. The TEPs 
consisted of interested parties with a diverse range of expertise, 
including IRF and PAC subject matter knowledge, clinical expertise, 
patient and family perspectives, and measure development experience. 
The TEPs supported the proposed measure concept and provided 
substantive feedback regarding the measure's specifications and measure 
testing data.
    First, the TEP was asked whether they prefer a cross-setting 
measure that is modeled after the currently adopted Discharge Mobility 
Score and Discharge Self-Care Score measures, or one that is modeled 
after the currently adopted Change in Mobility Score and Change in 
Self-Care Score measures. With the Discharge Mobility Score and Change 
in Mobility Score measures and the Discharge Self-Care Score and Change 
in Self-Care Score measures being both highly correlated and not 
appearing to measure unique concepts, the TEP favored the Discharge 
Mobility Score and Discharge Self-Care Score measures over the Change 
in Mobility Score and Change in Self-Care Score measure and recommended 
moving forward with utilizing the Discharge Mobility Score and 
Discharge Self-Care Score measure concepts for the development of the 
cross-setting measure.
    Second, in deciding the standardized functional assessment data 
elements to include in the cross-setting measure, the TEP recommended 
removing redundant data elements. Strong correlations between scores of 
functional items within the same functional domain suggested that 
certain items may be redundant in eliciting information about patient 
function and inclusion of these items could lead to overrepresentation 
of a particular functional area. Subsequently, our measure development 
contractor focused on the Discharge Mobility Score measure as a 
starting point for cross-setting development due to the greater number 
of cross-setting standardized functional assessment data elements for 
mobility while also identifying redundant functional items that could 
be removed from a cross-setting functional measure.
    Third, the TEP supported including the cross-setting self-care 
items such that the cross-setting function measure would capture both 
self-care and mobility. Panelists agreed that self-care items added 
value to the measure and are clinically important to function. Lastly, 
the TEP provided refinements to imputation strategies to more 
accurately represent function performance across all PAC settings, 
including the support of using statistical imputation over the current 
imputation approach implemented in existing functional outcome measures 
in the PAC QRPs. We considered all the TEP's recommendations for 
developing a cross-setting function measure, and we applied their 
recommendations where technically feasible and appropriate. Summaries 
of the TEP proceedings titled Technical Expert Panel (TEP) for the 
Refinement of Long-Term Care Hospital (LTCH), Inpatient Rehabilitation 
Facility (IRF), Skilled Nursing Facility (SNF)/Nursing Facility (NF), 
and Home Health (HH) Function Measures Summary Report (July 2021 TEP) 
\91\ and Technical Expert Panel (TEP) for Cross-Setting Function 
Measure Development Summary Report (January 2022 TEP) \92\ are 
available on the CMS Measures Management System (MMS) Hub.
---------------------------------------------------------------------------

    \91\ Technical Expert Panel (TEP) for the Refinement of Long-
Term Care Hospital (LTCH), Inpatient Rehabilitation Facility (IRF), 
Skilled Nursing Facility (SNF)/Nursing Facility (NF), and Home 
Health (HH) Function Measures Summary Report (July 2021 TEP) is 
available at https://mmshub.cms.gov/sites/default/files/TEP-Summary-Report-PAC-Function.pdf.
    \92\ Technical Expert Panel (TEP) for Cross-Setting Function 
Measure Development Summary Report (January 2022 TEP) is available 
at https://mmshub.cms.gov/sites/default/files/PAC-Function-TEP-Summary-Report-Jan2022-508.pdf.
---------------------------------------------------------------------------

    Finally, we solicited feedback from interested parties on the 
importance, relevance, and applicability of a cross-setting functional 
outcome measure for IRFs through an RFI in the FY 2023 IRF PPS proposed 
rule (87 FR 20244). Commenters were supportive of a cross-setting 
functional outcome measure that is inclusive of both self-care and 
mobility items, but also provided information related to potential risk 
adjustment methodologies as well as other measures that could be used 
to capture functional outcomes across PAC settings (87 FR 47070).
(4) Measure Applications Partnership (MAP) Review
    Our pre-rulemaking process includes making publicly available a 
list of quality and efficiency measures, called the MUC List, that the 
Secretary is considering adopting for use in the Medicare program, 
including our quality reporting programs. This allows multi-interested 
parties to provide recommendations to the Secretary on the measures 
included on the list.
    We included the DC Function measure under the IRF QRP in the 
publicly available MUC List for December 1, 2022.\93\ After the MUC 
List was published, the CBE convened MAP received four comments from 
interested parties in the industry on the 2022 MUC List. Two commenters 
were supportive of the measure and two were not. Among the commenters 
in support of the measure, one commenter stated that function scores 
are the most meaningful outcome measure in the IRF setting, as they not 
only assess patient outcomes but also can be used for clinical 
improvement processes. Additionally, this commenter noted the measure's 
good reliability and validity and that the measure is feasible to 
implement. The

[[Page 20994]]

second commenter supported including the measure in the IRF QRP 
measures we propose through rulemaking.
---------------------------------------------------------------------------

    \93\ Centers for Medicare & Medicaid Services. Overview of the 
List of Measures Under Consideration for December 1, 2022. https://mmshub.cms.gov/sites/default/files/2022-MUC-List-Overview.pdf.
---------------------------------------------------------------------------

    Commenters not in support of the measure raised the following 
concerns: the need for more detailed measure specifications, the 
complexity of calculating the expected discharge score, the measure's 
validity and usability, and the differences in denominator populations 
across PAC settings. We were able to address these concerns during the 
MAP PAC/LTC workgroup meeting held on December 12, 2022. Specifically, 
we clarified that the technical reports include detailed measure 
specifications, and that expected discharge scores are calculated by 
risk-adjusting the observed discharge scores (see section 
VIII.C.1.b.(5) of this proposed rule). We also noted that the measure 
exhibits good validity (see section VIII.C.1.b(1)(b) of this proposed 
rule) and clarified that the wide range of expected scores does not 
indicate poor validity and is consistent with the range of observed 
scores. We also pointed out that the measure is highly usable since it 
is similar in design and complexity to existing function measures and 
its data elements are already in use. Lastly, we explained that the 
denominator population in each measure setting represents the assessed 
population within the setting and the measure satisfies the requirement 
of the Act for a cross-setting measure in the functional status domain.
    Shortly after, several CBE convened MAP workgroups met to provide 
input on the proposed DC Function measure. First, the MAP Health Equity 
Advisory Group convened on December 6-7, 2022. The MAP Health Equity 
Advisory Group did not share any health equity concerns related to the 
implementation of the DC Function measure, and only asked for 
clarification regarding measure specifications from the measure 
steward. The MAP Rural Health Advisory Group met on December 8-9, 2022, 
during which two of its members provided support for the DC Function 
measure and other MAP Rural Health Advisory Group members did not 
express rural health concerns regarding the measure.
    The MAP PAC/LTC workgroup met on December 12, 2022 and provided 
input on the proposed DC Function measure. During this meeting, we were 
able to address several concerns raised by interested parties after the 
publication of the MUC List. Specifically, we clarified that the 
expected discharge scores are not calculated using self-reported 
functional goals, and are simply calculated by risk-adjusting the 
observed discharge scores (see section VIII.C.1.b.(5) of this proposed 
rule). Therefore, we believe that these scores cannot be ``gamed'' by 
reporting less-ambitious functional goals. We also pointed out that the 
measure is highly usable as it is similar in design and complexity to 
existing function measures and that the data elements used in this 
measure are already in use on the IRF-PAI submitted by IRFs. Lastly, we 
clarified that the DC Function measure is intended to supplement, 
rather than replace, existing IRF QRP measures for self-care and 
mobility and implements improvements on the existing Discharge Self-
Care Score and Discharge Mobility Score measures that make the proposed 
measure more valid and harder to game.
    The MAP PAC/LTC workgroup went on to discuss several concerns with 
the DC Function measure, including (1) whether the measure is cross-
setting due to denominator populations that differ among settings, (2) 
whether the measure would adequately represent the full picture of 
function, especially for patients who may have a limited potential for 
functional gain, and (3) that the range of expected scores was too 
large to offer a valid facility-level score. We clarified that the 
denominator population in each measure-setting represents the assessed 
population within the setting and that the measure satisfies the 
requirement of section 1886(j)(7) of the Act for a cross-setting 
measure in the functional status domain specified under section 
1899B(c)(1) of the Act. Additionally, we noted that the TEP had 
reviewed the item set and determined that all the self-care and 
mobility items were suitable for all settings. Further, we clarified 
that, because the DC Function measure would assess whether a patient 
met or exceeded their expected discharge score, it accounts for 
patients who are not expected to improve. Lastly, we noted that the DC 
Function measure has a high degree of correlation with the existing 
function measures and that the measure exhibits good validity and 
clarified that the wide range of expected scores does not indicate poor 
validity and is consistent with the range of observed scores. The PAC/
LTC workgroup voted to support the staff recommendation of conditional 
support for rulemaking, with the condition that we seek CBE 
endorsement.
    In response to the MAP PAC/LTC workgroup's preliminary 
recommendation, the CBE received two comments in support of the MAP 
PAC/LTC workgroup's preliminary recommendation of conditional support 
for rulemaking. One commenter recommended the DC Function measure under 
the condition that the measure be reviewed and refined such that its 
implementation supports patient autonomy and results in care that 
aligns with patients' personal functional goals. The second commenter 
provided support for the DC Function measure under the condition that 
it produces statistically meaningful information that can inform 
improvements in care processes, while also expressing concern that the 
measure is not truly cross-setting because: (1) the measure utilizes 
different patient populations in each setting-specific denominator, (2) 
the risk-adjustment models use setting-specific covariates, and (3) 
using a single set of cross-setting Section GG self-care and mobility 
function items in our standardized patient assessment instruments is 
not appropriate since the items may not be relevant given the 
differences in each PAC resident/patient population.
    Finally, the MAP Coordinating Committee workgroup convened on 
January 24-25, 2023. At this meeting, one interested party indicated 
their lack of support for the PAC/LTC workgroup's preliminary 
recommendation. The commenter expressed concern that the proposed DC 
Function measure competes with existing self-care and mobility measures 
in the IRF QRP. We noted that we monitor measures to determine whether 
they meet any measure removal factors, set forth in 42 CFR 
413.360(b)(2), and when identified, we may remove such measures through 
the rulemaking process. We noted again that the TEP had reviewed the 
item set and determined that all the self-care and mobility items were 
suitable for all settings. The MAP Coordinating Committee members 
expressed support for our review of existing measures for potential 
removal, as well as for the proposed DC Function measure, favoring the 
implementation of a single, standardized function measure across PAC 
settings. The Coordinating Committee unanimously upheld the workgroup 
recommendation of conditional support for rulemaking. We refer readers 
to the final MAP recommendations titled, 2022-2023 MAP Final 
Recommendations.\94\
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    \94\ 2022-2023 MAP Final Recommendations. https://mmshub.cms.gov/sites/default/files/2022-2023-MAP-Final-Recommendations-508.xlsx.
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(5) Quality Measure Calculation
    The proposed DC Function measure is an outcome measure that 
estimates the percentage of IRF patients who meet or exceed an expected 
discharge score during the reporting period. The proposed measure's 
numerator is the

[[Page 20995]]

number of IRF stays with an observed discharge function score that is 
equal to or greater than the calculated expected discharge function 
score. The observed discharge function score is the sum of individual 
function item values at discharge. The expected discharge function 
score is computed by risk-adjusting the observed discharge function 
score for each IRF stay. Risk adjustment controls for patient 
characteristics such as admission function score, age, and clinical 
conditions. The denominator is the total number of IRF stays with an 
IRF-PAI record in the measure target period (four rolling quarters) 
that do not meet the measure exclusion criteria. For additional details 
regarding the numerator, denominator, risk adjustment, and exclusion 
criteria, refer to the Discharge Function Score for Inpatient 
Rehabilitation Facilities (IRFs) Technical Report.\95\
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    \95\ Discharge Function Score for Inpatient Rehabilitation 
Facilities (IRFs) Technical Report. https://www.cms.gov/files/document/irf-discharge-function-score-technical-report-february-2023.pdf.
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    The proposed DC Function measure implements a statistical 
imputation approach for handling ``missing'' standardized functional 
assessment data elements. The coding guidance for standardized 
functional assessment data elements allows for using ``Activity Not 
Attempted'' (ANA) codes, resulting in ``missing'' information about a 
patient's functional ability on at least some items, at admission and/
or discharge, for a substantive portion of IRF patients. Currently, 
functional outcome measures in the IRF QRP use a simple imputation 
method whereby all ANA codes or otherwise missing scores, on both 
admission and discharge records, are recoded to ``1'' or ``most 
dependent.'' Statistical imputation, on the other hand, replaces these 
missing values with a variable based on the values of other, non-
missing variables in the assessment and on the values of other 
assessments which are otherwise similar to the assessment with a 
missing value. Specifically, this proposed DC Function measure's 
statistical imputation allows missing values (that is, the ANA codes) 
to be replaced with any value from 1 to 6, based on a patient's 
clinical characteristics and codes assigned on other standardized 
functional assessment data elements. The measure implements separate 
imputation models for each standardized functional assessment data 
element used in the construction of the discharge score and the 
admission score. Relative to the current simple imputation method, this 
statistical imputation approach increases precision and accuracy and 
reduces the bias in estimates of missing item values. We refer readers 
to the Discharge Function Score for Inpatient Rehabilitation Facilities 
(IRFs) Technical Report \96\ for measure specifications and additional 
details.
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    \96\ Discharge Function Score for Inpatient Rehabilitation 
Facilities (IRFs) Technical Report. https://www.cms.gov/medicare/quality-initiatives-patient-assessment-instruments/irf-quality-reporting/irf-quality-reporting-program-measures-information-.
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    We invite public comment on our proposal to adopt the DC Function 
measure, beginning with the FY 2025 IRF QRP.
c. Proposed Removal of the Application of Percent of Long-Term Care 
Hospital Patients With an Admission and Discharge Functional Assessment 
and a Care Plan That Addresses Function Beginning With the FY 2025 IRF 
QRP
    We are proposing to remove the Application of Percent of Long-Term 
Care Hospital Patients with an Admission and Discharge Functional 
Assessment and a Care Plan That Addresses Function (Application of 
Functional Assessment/Care Plan) measure from the IRF QRP beginning 
with the FY 2025 IRF QRP. Section 412.634(b)(2) of our regulations 
specifies eight factors we consider for measure removal from the IRF 
QRP, and we believe this measure should be removed because it satisfies 
two of these factors.
    First, the Application of Functional Assessment/Care Plan measure 
meets the conditions for measure removal factor one: measure 
performance among IRFs is so high and unvarying that meaningful 
distinctions in improvements in performance can no longer be made.\97\ 
Second, this measure meets the conditions for measure removal factor 
six: there is an available measure that is more strongly associated 
with desired patient functional outcomes. We believe the proposed DC 
Function measure discussed in section VIII.C.1.b. of this proposed rule 
better measures functional outcomes than the current Application of 
Functional Assessment/Care Plan measure. We discuss each of these 
reasons in more detail below.
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    \97\ For more information on the factors CMS uses to base 
decisions for measure removal, we refer readers to Sec.  
412.364(b)(2). https://www.ecfr.gov/current/title-42/chapter-IV/subchapter-B/part-412/subpart-P/section-412.634.
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    In regard to removal factor one, the Application of Functional 
Assessment/Care Plan measure has become topped out, with average 
performance rates reaching nearly 100 percent over the past 3 years 
(ranging from 99.8 percent to 99.9 percent during CYs 2019-2021).\98\ 
\99\ \100\ For the 12-month period of third quarter of CY 2020 through 
second quarter of CY 2021 (July 1, 2020 through June 30, 2021), IRFs 
had an average score for this measure of 99.8 percent, with nearly 80 
percent of IRFs scoring 100 percent,\101\ and for CY 2021, IRFs had an 
average score of 99.9 percent, with nearly 78 percent of IRFs scoring 
100 percent.\102\ The proximity of these mean rates to the maximum 
score of 100 percent suggests a ceiling effect and a lack of variation 
that restricts distinction among IRFs.
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    \98\ Centers for Medicare & Medicaid Services. Inpatient 
Rehabilitation Facilities Data Archive, 2021, Annual Files National 
Data 07-21. https://data.cms.gov/provider-data/archived-data/inpatient-rehabilitation-facilities.
    \99\ Centers for Medicare & Medicaid Services. Inpatient 
Rehabilitation Facilities Data Archive, 2022, Annual Files National 
Data 04-22. https://data.cms.gov/provider-data/archived-data/inpatient-rehabilitation-facilities.
    \100\ Centers for Medicare & Medicaid Services. Inpatient 
Rehabilitation Facilities Data Archive, 2022, Annual Files National 
Data 09-22. https://data.cms.gov/provider-data/archived-data/inpatient-rehabilitation-facilities.
    \101\ Centers for Medicare & Medicaid Services. Inpatient 
Rehabilitation Facilities Data Archive, 2022, Annual Files Provider 
Data 04-22. https://data.cms.gov/provider-data/archived-data/inpatient-rehabilitation-facilities.
    \102\ Centers for Medicare & Medicaid Services. Inpatient 
Rehabilitation Facilities Data Archive, 2022, Annual Files Provider 
Data 09-22. https://data.cms.gov/provider-data/archived-data/inpatient-rehabilitation-facilities.
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    In regard to measure removal factor six, the DC Function measure is 
more strongly associated with desired patient functional outcomes than 
this current process measure, the Application of Functional Assessment/
Care Plan measure. As described in section VIII.C.b.(1)(b) of this 
proposed rule, the DC Function measure has the predictive ability to 
distinguish patients with low expected functional capabilities from 
those with high expected functional capabilities.\103\ We have been 
collecting standardized functional assessment elements across PAC 
settings since 2016 which has allowed for the development of the 
proposed DC Function measure and meets the statutory requirements to 
submit standardized patient assessment data and other necessary data 
with respect to the domain of functional status, cognitive function, 
and changes in function and cognitive function. In light of this 
development, this process measure, the Application of Functional 
Assessment/Care Plan measure which measures only whether a functional 
assessment is completed and a functional goal is included in the care 
plan, is no longer necessary, and can be

[[Page 20996]]

replaced with a measure that evaluates the IRF's outcome of care on a 
patient's function.
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    \103\ ``Expected functional capabilities'' is defined as the 
predicted discharge function score.
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    Because the Application of Functional Assessment/Care Plan measure 
meets measure removal factors one and six, we are proposing to remove 
it from the IRF QRP beginning with the FY 2025 IRF QRP. We are also 
proposing that public reporting of the Application of Functional 
Assessment/Care Plan measure would end by the September 2024 Care 
Compare refresh or as soon as technically feasible when public 
reporting of the proposed DC Function measure would begin (see section 
VIII.G.3. of this proposed rule).
    Under our proposal, IRFs would no longer be required to report a 
Self-Care Discharge Goal (that is, GG0130, Column 2) or a Mobility 
Discharge Goals (that is, GG0170, Column 2) on the IRF-PAI beginning 
with patients admitted on October 1, 2023. We would remove the items 
for Self-Care Discharge Goals (that is, GG0130, Column 2) and Mobility 
Discharge Goals (that is, GG0170, Column 2) with the next release of 
the IRF-PAI. Under our proposal, these items would not be required to 
meet IRF QRP requirements beginning with the FY 2025 IRF QRP.
    We invite public comment on our proposal to remove the Application 
of Functional Assessment/Care Plan measure from the IRF QRP beginning 
with the FY 2025 IRF QRP.
d. Proposed Removal of the IRF Functional Outcome Measure: Change in 
Self-Care Score for Medical Rehabilitation Patients and Removal of the 
IRF Functional Outcome Measure: Change in Mobility Score for Medical 
Rehabilitation Patients Beginning With the FY 2025 IRF QRP
    We are proposing to remove the IRF Functional Outcome Measure: 
Change in Self-Care Score for Medical Rehabilitation Patients (Change 
in Self-Care Score) and the IRF Functional Outcome Measure: Change in 
Mobility Score for Medical Rehabilitation Patients (Change in Mobility 
Score) measures from the IRF QRP beginning with the FY 2025 IRF QRP. 
Section 412.634(b)(2) of our regulations specifies eight factors we 
consider for measure removal from the IRF QRP. We propose removal of 
these measures because they satisfy measure removal factor eight: the 
costs associated with a measure outweigh the benefits of its use in the 
program.
    Measure costs are multifaceted and include costs associated with 
implementing and maintaining the measures. On this basis, we believe 
these measures should be removed for two reasons. First, the costs to 
IRFs associated with tracking similar or duplicative measures in the 
IRF QRP outweigh any benefit that might be associated with the 
measures. Second, the costs to CMS associated with program oversight of 
the measures, including measure maintenance and public display, 
outweigh the benefit of information obtained from the measures. We 
discuss each of these in more detail below.
    We adopted the Change in Self-Care Score and Change in Mobility 
Score measures in the FY 2016 IRF PPS final rule (80 FR 47112 through 
47118) under section 1888(e)(6)(B)(i)(II) of the Act because the 
measures meet the functional status, cognitive function, and changes in 
function and cognitive function domain under section 1899B(c)(1) of the 
Act. Two additional measures addressing the functional status, 
cognitive function, and changes in function and cognitive function 
domain were adopted in the same program year: the Application of IRF 
Functional Outcome Measure: Discharge Self-Care Score for Medical 
Rehabilitation Patients (Discharge Self-Care Score) and the Application 
of IRF Functional Outcome Measure: Discharge Mobility Score for Medical 
Rehabilitation Patients (Discharge Mobility Score) measures. Given that 
the primary goal of rehabilitation is improvement in functional status, 
IRF clinicians have traditionally assessed and documented individual 
patients' functional status at admission and discharge to evaluate the 
effectiveness of the rehabilitation care provided.
    We are proposing to remove the Change in Self-Care Score and Change 
in Mobility Score measures because we believe the IRF costs associated 
with tracking duplicative measures outweigh any benefit that might be 
associated with the measures. Since the adoption of these measures in 
2016, we have been monitoring the data and found that the scores for 
the two self-care functional outcome measures, Change in Self-Care 
Score and Discharge Self-Care Score, are very highly correlated in IRF 
settings (0.97).\104\ Similarly, in the monitoring data, we have found 
that, the scores for the two mobility score measures, Change in 
Mobility Score and Discharge Mobility Score, are very highly correlated 
in IRF settings (0.98).\105\ The high correlation between these 
measures suggests that the Change in Self-Care Score and Discharge 
Self-Care Score and the Change in Mobility Score and the Discharge 
Mobility Score measures provide almost identical information about this 
dimension of quality to IRFs and are therefore duplicative.
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    \104\ Acumen, LLC and Abt Associates. Technical Expert Panel 
(TEP) for the Refinement of Long-Term Care Hospital (LTCH), 
Inpatient Rehabilitation Facility (IRF), Skilled Nursing Facility 
(SNF)/Nursing Facility (NF), and Home Health (HH) Function Measures, 
July 14-15, 2021: Summary Report. February 2022. https://mmshub.cms.gov/sites/default/files/TEP-Summary-Report-PAC-Function.pdf.
    \105\ Acumen, LLC and Abt Associates. Technical Expert Panel 
(TEP) for the Refinement of Long-Term Care Hospital (LTCH), 
Inpatient Rehabilitation Facility (IRF), Skilled Nursing Facility 
(SNF)/Nursing Facility (NF), and Home Health (HH) Function Measures: 
July 14-15, 2021: Summary Report. February 2022. https://mmshub.cms.gov/sites/default/files/TEP-Summary-Report-PAC-Function.pdf.
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    Our proposal to remove the Change in Self-Care Score and the Change 
in Mobility Score measures is supported by feedback received from the 
TEP convened for the Refinement of LTCH, IRF, SNF/NF, and HH Function 
Measures. As described in section VIII.C.1.b(3) of this proposed rule, 
the TEP panelists were presented with analyses that demonstrated the 
``Change in Score'' and ``Discharge Score'' measure sets are highly 
correlated and do not appear to measure unique concepts, and they 
subsequently articulated that it would be sensible to retire either the 
``Change in Score'' or ``Discharge Score'' measure sets for both self-
care and mobility. Based on responses to the post-TEP survey, the 
majority of panelists (nine out of 12 respondents) suggested that only 
one measure is necessary. Of those nine respondents, six preferred 
retaining the ``Discharge Score'' measures over the ``Change in Score'' 
measures.\106\
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    \106\ Acumen, LLC and Abt Associates. Technical Expert Panel 
(TEP) for the Refinement of Long-Term Care Hospital (LTCH), 
Inpatient Rehabilitation Facility (IRF), Skilled Nursing Facility 
(SNF)/Nursing Facility (NF), and Home Health (HH) Function Measures, 
July 14-15, 2021: Summary Report. February 2022. https://mmshub.cms.gov/sites/default/files/TEP-Summary-Report-PAC-Function.pdf.
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    Additionally, we are proposing to remove the Change in Self-Care 
Score and Change in Mobility Score measures because the program 
oversight costs outweigh the benefit of information that CMS, IRFs, and 
the public obtain from the measures. We must engage in various 
activities when administering the QRPs, such as monitoring measure 
results, producing provider preview reports, and ensuring the accuracy 
of the publicly reported data. Because these measures essentially 
provide the same information to IRFs and consumers as the Discharge 
Self-Care Score and Discharge Mobility Score measures, the costs to CMS 
associated with measure maintenance and public display outweigh the 
benefit of

[[Page 20997]]

information obtained from the measures.
    Because these measures meet the criteria for measure removal factor 
eight, we are proposing to remove the Change in Self-Care Score and 
Change in Mobility Score measures from the IRF QRP beginning with the 
FY 2025 IRF QRP. We are also proposing that public reporting of the 
Change in Self-Care Score and the Change in Mobility Score measure 
would end by the September 2024 Care Compare refresh or as soon as 
technically feasible.
    We invite public comment on our proposal to remove the Change in 
Self-Care Score and Change in Mobility Score measures from the IRF QRP 
beginning with the FY 2025 IRF QRP.
2. IRF QRP Quality Measure Proposal Beginning With the FY 2026 IRF QRP
a. Proposed COVID-19 Vaccine: Percent of Patients/Residents Who Are Up 
to Date Measure Beginning With the FY 2026 IRF QRP
(1) Background
    COVID-19 has been and continues to be a major challenge for PAC 
facilities, including IRFs. The Secretary first declared COVID-19 a PHE 
on January 31, 2020. As of March 23, 2023, the U.S. has reported 
103,957,053 cumulative cases of COVID-19, and 1,123,613 total deaths 
due to COVID-19.\107\ Although all age groups are at risk of 
contracting COVID-19, older persons are at a significantly higher risk 
of mortality and severe disease following infection, with those over 
age 80 dying at five times the average rate.\108\ Older adults, in 
general, are prone to both acute and chronic infections owing to 
reduced immunity, and are a high-risk population.\109\ Adults age 65 
and older comprise over 75 percent of total COVID-19 deaths despite 
representing 13.4 percent of reported cases.\110\ COVID-19 has impacted 
older adults' access to care, leading to poorer clinical outcomes, as 
well as taking a serious toll on their mental health and well-being due 
to social distancing.\111\
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    \107\ Centers for Disease Control and Prevention. COVID Data 
Tracker. https://covid.cdc.gov/covid-data-tracker/#cases_totalcases.
    \108\ United Nations. Policy Brief: The impact of COVID-19 on 
older persons. May 2020. https://unsdg.un.org/sites/default/files/2020-05/Policy-Brief-The-Impact-of-COVID-19-on-Older-Persons.pdf.
    \109\ Lekamwasam R, Lekamwasam S. Effects of COVID-19 pandemic 
on health and wellbeing of older people: a comprehensive review. Ann 
Geriatr Med Res. 2020 Sep;24(3):166-172.doi: 10.4235/agmr.20.0027. 
PMID: 32752587; PMCID: PMC7533189.
    \110\ Centers for Disease Control and Prevention. Demographic 
trends of COVID-19 cases and deaths in the US reported to CDC. COVID 
Data Tracker. https://covid.cdc.gov/covid-data-tracker/#demographics.
    \111\ United Nations. Policy Brief: The impact of COVID-19 on 
older persons. May 2020. https://unsdg.un.org/sites/default/files/2020-05/Policy-Brief-The-Impact-of-COVID-19-on-Older-Persons.pdf.
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    Since the development of the vaccines to combat COVID-19, studies 
have shown they continue to provide strong protection against severe 
disease, hospitalization, and death in adults, including during the 
predominance of Omicron BA.4 and BA.5 variants.\112\ Initial studies 
showed the efficacy of FDA-approved or authorized COVID-19 vaccines in 
preventing COVID-19. Prior to the emergence of the Delta variant of the 
virus, vaccine effectiveness against COVID-19-associated 
hospitalization among adults age 65 and older was 91 percent for those 
who were fully vaccinated with an mRNA vaccine (Pfizer-BioNTech or 
Moderna), and 84 percent for those receiving a viral vector vaccine 
(Janssen). Adults age 65 and older who were fully vaccinated with an 
mRNA COVID-19 vaccine had a 94 percent reduction in risk of COVID-19 
hospitalization while those who were partially vaccinated had a 64 
percent reduction in risk.\113\ Further, after the emergence of the 
Delta variant, vaccine effectiveness against COVID-19-associated 
hospitalization for adults who were fully vaccinated was 76 percent 
among adults age 75 and older.\114\
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    \112\ Chalkias S, Harper C, Vrbicky K, et al. A Bivalent 
Omicron-Containing Booster Vaccine Against COVID-19. N Engl J Med. 
2022 Oct 6;387(14):1279-1291. doi: 10.1056/NEJMoa2208343. PMID: 
36112399; PMCID: PMC9511634.
    \113\ Centers for Disease Control and Prevention. Fully 
Vaccinated Adults 65 and Older Are 94% Less Likely to Be 
Hospitalized with COVID-19. April 28, 2021. https://www.cdc.gov/media/releases/2021/p0428-vaccinated-adults-less-hospitalized.html.
    \114\ Interim Estimates of COVID-19 Vaccine Effectiveness 
Against COVID-19-Associated Emergency Department or Urgent Care 
Clinic Encounters and Hospitalizations Among Adults During SARS-CoV-
2 B.1.617.2 (Delta) Variant Predominance--Nine States, June-August 
2021. (Grannis SJ, et al. MMWR Morb Mortal Wkly Rep. 
2021;70(37):1291-1293. http://dx.doi.org/10.15585/mmwr.mm7037e2.
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    More recently, since the emergence of the Omicron variants and 
availability of booster doses, multiple studies have shown that while 
vaccine effectiveness has waned, protection is higher among those 
receiving booster doses than among those only receiving the primary 
series.\115\ \116\ \117\ CDC data show that, among people age 50 and 
older, those who have received both a primary vaccination series and 
booster doses have a lower risk of hospitalization and dying from 
COVID-19 than their non-vaccinated counterparts.\118\ Additionally, a 
second vaccine booster dose has been shown to reduce risk of severe 
outcomes related to COVID-19, such as hospitalization or death.\119\ 
Early evidence also demonstrates that the bivalent boosters, 
specifically aimed to provide better protection against disease caused 
by Omicron subvariants, have been quite effective, and underscores the 
role of up to date vaccination protocols in effectively countering the 
spread of COVID-19.\120\ \121\
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    \115\ Surie D, Bonnell L, Adams K, et al. Effectiveness of 
monovalent mRNA vaccines against COVID-19-associated hospitalization 
among immunocompetent adults during BA.1/BA.2 and BA.4/BA.5 
predominant periods of SARS-CoV-2 Omicron variant in the United 
States--IVY Network, 18 states, December 26, 2021-August 31, 2022. 
MMWR Morb Mortal Wkly Rep. 2022;71(42):1327-1334. doi: 10.15585/
mmwr.mm7142a3.
    \116\ Andrews N, Stowe J, Kirsebom F, et al. Covid-19 vaccine 
effectiveness against the Omicron (B.1.1.529) variant. N Engl J Med. 
2022 Apr 21;386(16):1532-1546. doi 10.1056/NEJMoa2119451. PMID: 
35249272; PMCID: PMC8908811.
    \117\ Buchan SA, Chung H, Brown KA, et al. Estimated 
effectiveness of COVID-19 vaccines against Omicron or Delta 
symptomatic infection and severe outcomes. JAMA Netw Open. 2022 Sep 
1;5(9):e2232760.doi: 10.1001/jamanetworkopen.2022.32760. https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2796615. PMID: 
36136332; PMCID: PMC9500552.
    \118\ Centers for Disease Control and Prevention. Rates of 
laboratory-confirmed COVID-19 hospitalizations by vaccination 
status. COVID Data Tracker. 2023, February 9. Last accessed March 
22, 2023. https://covid.cdc.gov/covid-data-tracker/#covidnet-hospitalizations-vaccination.
    \119\ Centers for Disease Control and Prevention. COVID-19 
vaccine effectiveness monthly update. COVID Data Tracker. November 
10, 2022. https://covid.cdc.gov/covid-data-tracker/#vaccine-effectiveness.
    \120\ Chalkias S, Harper C, Vrbicky K, et al. A bivalent 
omicron-containing booster vaccine against COVID-19. N Engl J Med. 
2022 Oct 6;387(14):1279-1291. doi: 10.1056/NEJMoa2208343. PMID: 
36112399; PMCID: PMC9511634.
    \121\ Tan, S.T., Kwan, A.T., Rodr[iacute]guez-Barraquer, I. et 
al. Infectiousness of SARS-CoV-2 breakthrough infections and 
reinfections during the Omicron wave. Nat Med 29, 358-365 (2023). 
https://doi.org/10.1038/s41591-022-02138-x.
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(a) Measure Importance
    Despite the availability and demonstrated effectiveness of COVID-19 
vaccinations,, significant gaps continue to exist in vaccination 
rates.\122\ As of March 22, 2023, vaccination rates among people age 65 
and older are generally high for the primary vaccination series (94.3 
percent) but lower for the first booster (73.6 percent among those who 
received a primary series) and even lower for the second

[[Page 20998]]

booster (59.9 percent among those who received a first booster).\123\ 
Additionally, though the uptake in boosters among people age 65 and 
older has been much higher than among people of other ages, booster 
uptake still remains relatively low compared to primary vaccination 
among older adults.\124\ Variations are also present when examining 
vaccination rates by race, gender, and geographic location.\125\ For 
example, 66.2 percent of the Asian, non-Hispanic population have 
completed the primary series and 21.2 percent have received a bivalent 
booster dose, whereas 44.9 percent of the Black, non-Hispanic 
population have completed the primary series and only 8.9 percent have 
received a bivalent booster dose. Among Hispanic populations, 57.1 
percent of the population have completed the primary series, and 8.5 
percent have received a bivalent booster dose, while in White, non-
Hispanic populations, 51.9 percent have completed the primary series 
and 16.2 percent have received a bivalent booster dose.\126\ 
Disparities have been found in vaccination rates between rural and 
urban areas, with lower vaccination rates found in rural areas.\127\ 
\128\ Data shows that 55.2 percent of the eligible population in rural 
areas have completed the primary vaccination series, as compared to 
66.5 percent of the eligible population in urban areas.\129\ Receipt of 
bivalent booster doses among those eligible has been lower, with 18 
percent of urban population having received a booster dose, and 11.5 
percent of the rural population having received a booster dose.\130\
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    \122\ Centers for Disease Control and Prevention. COVID-19 
vaccinations in the United States. COVID Data Tracker. https://covid.cdc.gov/covid-data-tracker/#vaccinations_vacc-people-booster-percent-pop5.
    \123\ Centers for Disease Control and Prevention. COVID-19 
vaccination age and sex trends in the United States, national and 
jurisdictional. https://data.cdc.gov/Vaccinations/COVID-19-Vaccination-Age-and-Sex-Trends-in-the-Uni/5i5k-6cmh.
    \124\ Freed M, Neuman T, Kates J, Cubanski J. Deaths among older 
adults due to COVID-19 jumped during the summer of 2022 before 
falling somewhat in September. Kaiser Family Foundation. October 6, 
2022. https://www.kff.org/coronavirus-covid-19/issue-brief/deaths-among-older-adults-due-to-covid-19-jumped-during-the-summer-of-2022-before-falling-somewhat-in-september/.
    \125\ Saelee R, Zell E, Murthy BP, et al. Disparities in COVID-
19 Vaccination Coverage Between Urban and Rural Counties--United 
States, December 14, 2020-January 31, 2022. MMWR Morb Mortal Wkly 
Rep. 2022 Mar 4;71:335-340. doi: 10.15585/mmwr.mm7109a2. PMID: 
35239636; PMCID: PMC8893338.
    \126\ Centers for Disease Control and Prevention. COVID Data 
Tracker: Trends in demographic characteristics of people receiving 
COVID-19 vaccinations in the United States. https://covid.cdc.gov/covid-data-tracker/#vaccination-demographics-trends.
    \127\ Saelee R, Zell E, Murthy BP, et al. Disparities in COVID-
19 Vaccination Coverage Between Urban and Rural Counties--United 
States, December 14, 2020-January 31, 2022. MMWR Morb Mortal Wkly 
Rep. 2022 Mar 4;71:335-340. doi: 10.15585/mmwr.mm7109a2. PMID: 
35239636; PMCID: PMC8893338.
    \128\ Sun Y, Monnat SM. Rural-urban and within-rural differences 
in COVID-19 vaccination rates. J Rural Health. 2022 Sep;38(4):916-
922. doi: 10.1111/jrh.12625. PMID: 34555222; PMCID: PMC8661570.
    \129\ Centers for Disease Control and Prevention. COVID Data 
Tracker. Vaccination Equity. https://covid.cdc.gov/covid-data-tracker/#vaccination-equity.
    \130\ Centers for Disease Control and Prevention. Vaccination 
Equity. COVID Data Tracker; 2023, January 20. Last accessed January 
17, 2023. https://covid.cdc.gov/covid-data-tracker/#vaccination-equity.
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    We are proposing to adopt the COVID-19 Vaccine: Percent of 
Patients/Residents Who Are Up to Date (Patient/Resident COVID-19 
Vaccine) measure for the IRF QRP beginning with the FY 2026 IRF QRP. 
This proposed measure has the potential to increase COVID-19 
vaccination coverage of patients in IRFs, as well as prevent the spread 
of COVID-19 within the IRF patient population. The proposed Patient/
Resident COVID-19 Vaccine measure would also support the goal of CMS's 
Meaningful Measure Initiative 2.0 to ``Empower consumers to make good 
health care choices through patient-directed quality measures and 
public transparency objectives.'' The proposed Patient/Resident COVID-
19 Vaccine measure would be reported on Care Compare and would provide 
patients, including those who are at high risk for developing serious 
complications from COVID-19, and their caregivers, with valuable 
information they can consider when choosing an IRF. The proposed 
Patient/Resident COVID-19 Vaccine measure would also facilitate patient 
care and care coordination during the hospital discharge planning 
process. For example, a discharging hospital, in collaboration with the 
patient and family, could use this proposed measure's publicly reported 
information on Care Compare to coordinate care and ensure patient 
preferences are considered in the discharge plan. Additionally, the 
proposed Patient/Resident COVID-19 Vaccine measure would be an indirect 
measure of IRF action. Since the patient's COVID-19 vaccination status 
would be reported at discharge from the IRF, if a patient is not up to 
date with their COVID-19 vaccination per applicable CDC guidance at the 
time they are admitted, the IRF has the opportunity to educate the 
patient and provide information on why they should become up to date 
with their COVID-19 vaccination. IRFs may also choose to administer the 
vaccine to the patient prior to their discharge from the IRF or 
coordinate a follow-up visit for the patient to obtain the vaccine at 
their physician's office or local pharmacy.
(b) Item Testing
    The measure development contractor conducted testing of the 
proposed standardized patient/resident COVID-19 vaccination coverage 
assessment item for the proposed Patient/Resident COVID-19 Vaccine 
measure using patient scenarios, draft guidance manual coding 
instructions, and cognitive interviews to assess IRFs' comprehension of 
the item and the associated guidance. A team of clinical experts 
assembled by our measure development contractor developed these patient 
scenarios to represent the most common scenarios that IRFs would 
encounter. The results of the item testing demonstrated that IRFs that 
used the draft guidance manual coding instructions had strong agreement 
(that is, 84 percent) with the correct responses, supporting its 
reliability. The testing also provided information to improve both the 
item itself and the accompanying guidance.
(2) Competing and Related Measures
    Section 1886(j)(7)(D)(i) of the Act and section 1899B(e)(2)(A) of 
the Act require that, absent an exception under section 
1886(j)(7)(D)(i) and section 1899B(e)(2)(B) of the Act, measures 
specified under section 1886(j)(7)(D)(i) of the Act and section 1899B 
of the Act must be endorsed by a CBE with a contract under section 
1890(a) of the Act. In the case of a specified area or medical topic 
determined appropriate by the Secretary for which a feasible and 
practical measure has not been endorsed, section 1886(j)(7)(D)(i) of 
the Act and section 1899B(e)(2)(B) of the Act permit 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 CBE 
identified by the Secretary. The proposed Patient/Resident COVID-19 
Vaccine measure is not CBE endorsed, and after review of other CBE 
endorsed measures, we were unable to identify any CBE endorsed measures 
for IRFs focused on capturing COVID-19 vaccination coverage of IRF 
patients. We found only one related measure addressing COVID-19 
vaccination, the COVID-19 Vaccination Coverage among Healthcare 
Personnel measure, adopted for the FY 2023 IRF QRP (86 FR 42385 through 
42396), which captures the percentage of HCP who receive a complete 
COVID-19 primary vaccination course.
    Therefore, after consideration of other available measures that 
assess COVID-

[[Page 20999]]

19 vaccination rates among IRF patients, we believe the exception under 
section 1899B(e)(2)(B) of the Act applies. We intend to submit the 
proposed measure for consideration of endorsement by a CBE when 
feasible.
(3) Interested Parties and Technical Expert Panel (TEP) Input
    First, the measure development contractor convened a focus group of 
patient and family/caregiver advocates (PFAs) to solicit input. The 
PFAs felt a measure capturing raw vaccination rate, irrespective of IRF 
action, would be most helpful in patient and family/caregiver decision-
making. Next, TEP meetings were held on November 19, 2021 and December 
15, 2021 to solicit feedback on the development of patient/resident 
COVID-19 vaccination measures and assessment items for the PAC 
settings. The TEP panelists voiced their support for PAC patient/
resident COVID-19 vaccination measures and agreed that developing a 
measure to report the rate of vaccination in an IRF setting without 
denominator exclusions was an important goal. We considered the TEP's 
recommendations, and we applied the recommendations where technically 
feasible and appropriate. A summary of the TEP proceedings titled 
Technical Expert Panel (TEP) for the Development of Long-Term Care 
Hospital (LTCH), Inpatient Rehabilitation Facility (IRF), Skilled 
Nursing Facility (SNF)/Nursing Facility (NF), and Home Health (HH) 
COVID-19 Vaccination-Related Items and Measures Summary Report is 
available on the CMS MMS Hub.\131\
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    \131\ Technical Expert Panel (TEP) for the Development of Long-
Term Care Hospital (LTCH), Inpatient Rehabilitation Facility (IRF), 
Skilled Nursing Facility (SNF)/Nursing Facility (NF), and Home 
Health (HH) COVID-19 Vaccination-Related Items and Measures Summary 
Report. https://mmshub.cms.gov/sites/default/files/COVID19-Patient-Level-Vaccination-TEP-Summary-Report-NovDec2021.pdf.
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    To seek input on the importance, relevance, and applicability of a 
patient/resident COVID-19 vaccination coverage measure, we also 
solicited public comments in an RFI for publication in the FY 2023 IRF 
PPS proposed rule (87 FR 47038).\132\ Comments were generally positive 
on the concept of a measure addressing COVID-19 vaccination coverage 
among IRF patients. Some commenters included caveats with their support 
and requested further details regarding measure specifications and CBE 
endorsement. In addition, commenters voiced concerns regarding the 
evolving recommendations related to boosters and the definition of ``up 
to date,'' as well as whether an IRF length of stay would allow for 
meaningful distinctions among IRFs (87 FR 47071).
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    \132\ 87 FR 20218.
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(4) Measure Applications Partnership (MAP) Review
    The pre-rulemaking 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 for 
use in Medicare programs. This allows interested parties to provide 
recommendations to the Secretary on the measures included on the list. 
The Patient/Resident COVID-19 Vaccine measure was included on the 
publicly available 2022 MUC List for the IRF QRP.\133\
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    \133\ Centers for Medicare & Medicaid Services. (2022). Overview 
of the List of Measures Under Consideration for December 1, 2022. 
https://mmshub.cms.gov/sites/default/files/2022-MUC-List-Overview.pdf.
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    After the MUC List was published, the MAP received five comments 
from interested parties. Commenters were mostly supportive of the 
measure and recognized the importance of patients' COVID-19 
vaccination, and that measurement and reporting is one important method 
to help healthcare organizations assess their performance in achieving 
high rates of up to date vaccination. One commenter noted that patient 
engagement is critical at this stage of the pandemic, while another 
noted the criteria for inclusion in the numerator and denominator 
provide flexibility for the measure to remain relevant to current 
circumstances. Another commenter anticipated minimal implementation 
challenges, since healthcare providers are already asking for patients' 
COVID-19 vaccination status at intake. Commenters who were not 
supportive of the measure raised several issues, including that the 
measure does not capture quality of care, concern about the evolving 
definition of the term ``up to date,'' that data collection would be 
burdensome, that administering the vaccine could impact the IRF 
treatment plan, and that a measure only covering one quarter may not be 
meaningful.
    Subsequently, several MAP workgroups met to provide input on the 
proposed measure. First, the MAP Health Equity Advisory Group convened 
on December 6, 2022. One MAP Health Equity Advisory Group member noted 
that the percentage of true contraindications for the COVID-19 vaccine 
is low, and the lack of exclusions on the measure is reasonable in 
order to minimize variation in what constitutes a 
contraindication.\134\ Similarly, the MAP Rural Health Advisory Group 
met on December 8, 2022, and requested clarification of the term ``up 
to date'' and noted concerns with the perceived level of burden for 
collection of data.\135\ Next, the MAP PAC/LTC workgroup met on 
December 12, 2022. The MAP PAC/LTC workgroup's voting members raised 
concerns brought up in public comments, such as provider actionability, 
lack of denominator exclusions, requirements for assessing patient 
vaccination status, evolving COVID-19 vaccination recommendations, and 
data reporting frequency for this measure. Additionally, MAP PAC/LTC 
workgroup members noted the potential inability of IRFs to administer 
the vaccine due to the shorter average length of stay as compared to 
other PAC settings. In response to workgroup member feedback, we noted 
that the intent of the Patient/Resident COVID-19 Vaccine measure would 
be to promote transparency of data for patients to make informed 
decisions regarding care, and is not intended to be a measure of IRF 
action. We also explained that this measure does not have exclusions 
for patient refusal since this measure was intended to report raw rates 
of vaccination, and this information is important for consumer choice. 
Additionally, we believe that PAC providers, including IRFs, are in a 
unique position to leverage their care processes to increase 
vaccination coverage in their settings to protect patients and prevent 
negative outcomes. We also noted that collection of these data will not 
require additional documentation or proof of vaccination. We clarified 
that the Patient/Resident COVID-19 Vaccine measure would include the 
definition of up to date, so the measure would consider future changes 
in the CDC guidance regarding COVID-19 vaccination. We also clarified 
that the measure would continue to be a quarterly measure similar to 
the existing HCP COVID-19 Vaccine measure, as CDC has not determined 
whether COVID-19 is, or will be, a seasonal disease like influenza. 
Finally, we noted that the

[[Page 21000]]

average 12-day length of stay at IRFs is generally longer than patient 
stays at acute care hospitals. Given that health care is a continuum 
and every contact along the continuum provides an opportunity to 
encourage vaccination, IRFs have sufficient time to act on the 
patient's vaccination status. However, the MAP PAC/LTC workgroup 
reached a 60 percent consensus on the vote of ``Do not support for 
rulemaking'' for this measure.\136\
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    \134\ CMS Measures Management System (MMS). Measure 
Implementation: Pre-rulemaking MUC Lists and MAP reports. Last 
accessed March 22, 2023. https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
    \135\ CMS Measures Management System (MMS). Measure 
Implementation: Pre-rulemaking MUC Lists and MAP reports. Last 
accessed March 22, 2023. https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
    \136\ CMS Measures Management System (MMS). Measure 
Implementation: Pre-rulemaking MUC Lists and MAP reports. https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
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    The MAP received four comments from industry commenters in response 
to the MAP PAC/LTC workgroup's recommendations. Interested parties 
generally understood the importance of COVID-19 vaccinations in 
preventing the spread of COVID-19, although a majority of commenters 
did not recommend the inclusion of the proposed Patient/Resident COVID-
19 Vaccine measure for the IRF QRP and raised several concerns. 
Specifically, commenters were concerned about vaccine hesitancy and 
providers' inability to influence results based on factors outside of 
their control. Commenters also noted that the measure has not been 
fully tested and encouraged CMS to monitor the measure for unintended 
consequences and ensure that the measure has meaningful results. One 
commenter raised concerns on whether patients' vaccination information 
would be easily available to IRFs as well as potential limitations with 
patients recounting vaccination status. One commenter was in support of 
the measure and provided recommendations for CMS to consider adding an 
exclusion for medical contraindications and submitting the measure for 
CBE endorsement.
    Finally, the MAP Coordinating Committee convened on January 24, 
2023, and noted concerns which were previously discussed in the MAP 
PAC/LTC workgroup, such as potential disruption to patient therapy due 
to vaccination and acuity of patients in the IRF setting. However, a 
MAP Coordinating Committee member noted that a patient's potential 
inability to complete rehabilitation was not a valid reason to withhold 
support of this measure, and that, because these patients have a high 
acuity, they are more vulnerable to COVID-19, further emphasizing the 
need to vaccinate them. MAP Coordinating Committee members also raised 
concerns discussed previously during the MAP PAC/LTC workgroup, 
including the shorter IRF length of stay and excluding medical 
contraindications from the denominator.
    The MAP Coordinating Committee recommended three mitigation 
strategies for the Patient/Resident COVID-19 Vaccine measure: (i) 
reconsider exclusions for medical contraindications, (ii) complete 
reliability and validity measure testing, and (iii) seek CBE 
endorsement. The MAP Coordinating Committee ultimately reached 81 
percent consensus on its voted recommendation of `Do not support with 
potential for mitigation.' Despite the MAP Coordinating Committee's 
vote, we believe it is still important to propose the Patient/Resident 
COVID-19 Vaccine measure for the IRF QRP. As we stated in section 
VIII.C.2.a.(3) of this proposed rule, we did not include exclusions for 
medical contraindications because the PFAs we met with told us that a 
measure capturing raw vaccination rate, irrespective of any medical 
contraindications, would be most helpful in patient and family/
caregiver decision-making. We do plan to conduct reliability and 
validity measure testing once we have collected enough data, and we 
intend to submit the proposed measure to the CBE for consideration of 
endorsement when feasible. We refer readers to the final MAP 
recommendations, titled 2022-2023 MAP Final Recommendations.\137\
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    \137\ 2022-2023 MAP Final Recommendations. https://mmshub.cms.gov/measure-lifecycle/measure-implementation/pre-rulemaking/lists-and-reports.
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(5) Quality Measure Calculation
    The proposed Patient/Resident COVID-19 Vaccine measure is an 
assessment-based process measure that reports the percent of stays in 
which patients in an IRF are up to date on their COVID-19 vaccinations 
per the CDC's latest guidance.\138\ This measure has no exclusions, and 
is not risk adjusted.
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    \138\ The definition of ``up to date'' may change based on CDC's 
latest guidelines and is available on the CDC web page, ``Stay Up to 
Date with COVID-19 Vaccines Including Boosters,'' at https://www.cdc.gov/coronavirus/2019-ncov/vaccines/stay-up-to-date.html 
(updated March 2, 2023).
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    The numerator for the proposed measure would be the total number of 
IRF stays in the denominator in which patients are up to date with 
their COVID-19 vaccination per CDC's latest guidance. The denominator 
for the proposed measure would be the total number of IRF stays 
discharged during the reporting period.
    The data source for the proposed Patient/Resident COVID-19 Vaccine 
measure is the IRF-PAI for IRF patients. For more information about the 
proposed data submission requirements, we refer readers to section 
VIII.F.3. of this proposed rule. For additional technical information 
about this proposed measure, we refer readers to the draft measure 
specifications document titled Patient-Resident-COVID-Vaccine-Draft-
Specs.pdf.\139\ available on the IRF QRP Measures and Technical 
Information web page.
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    \139\ Patient-Resident-COVID-Vaccine-Draft-Specs.pdf. https://www.cms.gov/medicare/quality-initiatives-patient-assessment-instruments/irf-quality-reporting/irf-quality-reporting-program-measures-information-.
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    We invite public comments on the proposal to adopt the Patient/
Resident COVID-19 Vaccine measure beginning with the FY 2026 IRF QRP.

D. Principles for Selecting and Prioritizing IRF QRP Quality Measures 
and Concepts Under Consideration for Future Years--Request for 
Information (RFI)

1. Background
    We have established a National Quality Strategy (NQS) \140\ for 
quality programs which support a resilient, high-value health care 
system promoting quality outcomes, safety, equity and accessibility for 
all individuals. The CMS NQS is foundational for contributing to 
improvements in health care, enhancing patient outcomes, and informing 
consumer choice. To advance these goals, leaders from across CMS have 
come together to move toward a building-block approach to streamline 
quality measures across our quality programs for the adult and 
pediatric populations. This ``Universal Foundation'' \141\ of quality 
measures will focus provider attention and reduce provider burden, as 
well as identify disparities in care, prioritize development of 
interoperable, digital quality measures, allow for cross-comparisons 
across programs, and help identify measurement gaps. The development 
and implementation of the Preliminary Adult and Pediatric Universal 
Foundation Measures will promote the best, safest, and most equitable 
care for individuals as we all come together on these critical quality 
areas.
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    \140\ Schreiber M, Richards AC, Moody-Williams J, Fleisher LA. 
The CMS National Quality Strategy: A Person-centered Approach to 
Improving Quality. Centers for Medicare & Medicaid ServicesBblog. 
June 6, 2022. https://www.cms.gov/blog/cms-national-quality-strategy-person-centered-approach-improving-quality.
    \141\ Jacobs DB, Schreiber M, Seshamani M, Tsai D, Fowler E, 
Fleisher LA. Aligning Quality Measures across CMS--The Universal 
Foundation. N Engl J Med. 2023 Mar 2; 338:776-779. doi: 10.1056/
NEJMp2215539. PMID: 36724323.
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    In alignment with the CMS NQS, the IRF QRP endeavors to move toward 
a

[[Page 21001]]

more parsimonious set of measures while continually improving the 
quality of health care for beneficiaries. The purpose of this RFI is to 
gather input on existing gaps in IRF QRP measures and to solicit public 
comment on fully developed IRF measures that are not part of the IRF 
QRP, fully developed quality measures in other programs that may be 
appropriate for the IRF QRP, and measurement concepts that could be 
developed into IRF QRP measures, to fill these measurement gaps in the 
IRF QRP. While we will not be responding to specific comments submitted 
in response to this RFI in the FY 2024 IRF PPS final rule, we intend to 
use this input to inform future policies.
    This RFI consists of three sections. The first section discusses a 
general framework or set of principles that CMS could use to identify 
future IRF QRP measures. The second section draws from an environmental 
scan conducted to identify measurement gaps in the current IRF QRP, and 
measures or measure concepts that could be used to fill these gaps. The 
final section solicits public comment on (1) the set of principles for 
selecting measures for the IRF QRP, (2) identified measurement gaps, 
and (3) measures that are available for immediate use, or that may be 
adapted or developed for use in the IRF QRP.
2. Guiding Principles for Selecting and Prioritizing Measures
    We have identified a set of principles to guide future IRF QRP 
measure set development and maintenance. These principles are intended 
to ensure that measures resonate with beneficiaries and caregivers, do 
not impose undue burden on IRFs, align with our PAC program goals, and 
can be readily operationalized. Specifically, measures incorporated 
into the IRF QRP should meet the following four objectives:
     Actionability: Optimally, IRF QRP measures should focus on 
structural elements, healthcare processes, and outcomes of care that 
have been demonstrated, such as through clinical evidence or other best 
practices, to be amenable to improvement and feasible for IRFs to 
implement.
     Comprehensiveness and Conciseness: IRF QRP measures should 
assess performance of all IRF core services using the smallest number 
of measures that comprehensively assess the value of care provided in 
IRF settings. Parsimony in the QRP measure set minimizes IRFs' burden 
resulting from data collection and submission.
     Focus on Provider Responses to Payment: The IRF PPS shapes 
incentives for care delivery. IRF performance measures should neither 
exacerbate nor induce unwanted responses to the payment systems. As 
feasible, measures should mitigate adverse incentives of the payment 
system.
     Compliance with Statutory Requirements and Key Program 
Goals: Measures must comply with the governing statutory authorities 
and our policy to align QRP measures with our broader policy 
initiatives, such as the Meaningful Measures Framework.
3. Gaps in IRF QRP Measure Set and Potential New Measures
    We conducted an environmental scan that utilized the previously 
listed principles and identified measurement gaps in the domains of 
cognitive function, behavioral and mental health, patient experience 
and patient satisfaction, and chronic conditions and pain management. 
We discuss each of these in more detail below.
a. Cognitive Function
    Illnesses associated with limitations in cognitive function, which 
may include stroke, dementia, and Alzheimer's disease, affect an 
individual's ability to think, reason, remember, problem-solve, and 
make decisions. Section 1886(j)(7) of the Act requires IRFs to submit 
data on quality measures under section 1899B(c)(1) of the Act, and 
cognitive function and changes in cognitive function are key dimensions 
of clinical care that are not currently represented in the IRF QRP.
    Under the IRF QRP, IRFs currently collect and report to CMS data on 
cognitive function using the Brief Interview for Mental Status (BIMS) 
and Confusion Assessment Method (CAM(copyright)).\142\ Both the BIMS 
and CAM(copyright) have been incorporated into the IRF-PAI as 
standardized patient assessment data elements. Scored by IRFs via 
direct observation, the BIMS is used to determine orientation and the 
ability to register and recall new information. The CAM(copyright) 
assesses the presence of delirium and inattention, and level of 
consciousness. While data from the BIMS and CAM(copyright) are 
collected and reported via the IRF-PAI, these items have not been 
developed into specific quality measures for the IRF QRP.
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    \142\ Centers for Medicare & Medicaid Services. Final Inpatient 
Rehabilitation Facility Patient Assessment Version 4.0. Effective 
October 1, 2022. https://www.cms.gov/files/document/irf-pai-version-40-eff-10012022-final.pdf.
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    Alternative sources of information on cognitive function include 
the Patient-Reported Outcomes Measurement Information Set (PROMIS) 
Cognitive Function forms and the PROMIS Neuro-Quality of Life (Neuro-
QoL) measures.143 144 Developed and tested with a broad 
range of patient populations, PROMIS Cognitive Function assesses 
cognitive functioning using items related to patient perceptions 
regarding performance of cognitive tasks, such as memory and 
concentration, and perceptions of changes in these activities. The 
Neuro-QoL, which was specifically designed for use in patients with 
neurological conditions, assesses patient perceptions regarding oral 
expression, memory, attention, decision-making, planning, and 
organization.
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    \143\ HealthMeasures. List of Adult Measures: Available Neuro-
QoLTM Measures for Adult Self-Report. https://www.healthmeasures.net/explore-measurement-systems/neuro-qol/intro-to-neuro-qol/list-of-adult-measures.
    \144\ HealthMeasures. List of Adult Measures: Available 
PROMIS[supreg] Measures for Adults. https://www.healthmeasures.net/explore-measurement-systems/promis/intro-to-promis/list-of-adult-measures.
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    The BIMS, CAM(copyright), PROMIS Cognitive Function short forms, 
and PROMIS Neuro-QoL include items representing different aspects of 
cognitive function, from which quality measures may be constructed. 
Although these assessment instruments have been subjected to 
feasibility, reliability, and validity testing, additional development 
and testing would be required prior to transforming the concepts 
reflected in the BIMS and CAM(copyright) (for example, temporal 
orientation, recall) into fully specified measures for implementation 
in the IRF QRP.
    Through this RFI, we are requesting comment on the availability of 
cognitive functioning measures outside of the IRF QRP that may be 
available for immediate use in the IRF QRP, or that may be adapted or 
developed for use in the IRF QRP, using the BIMS, CAM(copyright), 
PROMIS Cognitive Function forms, and PROMIS Neuro-QoL, or other 
instruments. In addition to comment on specific measures and 
instruments, we seek input on the feasibility of measuring improvement 
in cognitive functioning during an IRF stay, which typically averages 
less than 15 days; \145\ the cognitive skills (for example, executive 
functions) that are more likely to improve during an IRF stay; 
conditions for which measures of maintenance--rather than improvement 
in cognitive functioning--are more practical; and the types of 
intervention that have been demonstrated to assist in

[[Page 21002]]

improving or maintaining cognitive functioning.
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    \145\ Medicare Payment Advisory Commission. March 2022 Report to 
the Congress; Chapter 9. https://www.medpac.gov/wp-content/uploads/2022/03/Mar22_MedPAC_ReportToCongress_Ch9_SEC.pdf.
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b. Behavioral and Mental Health
    Estimates suggest that one in five Medicare beneficiaries has a 
``common mental health disorder'' and nearly 8 percent have a serious 
mental illness.\146\ Substance use disorders (SUDs) are also common. 
Research estimates that approximately 1.7 million Medicare 
beneficiaries (8 percent) reported a SUD in the past year, with 77 
percent attributed to alcohol use and 16 percent to prescription drug 
use.\147\ In some instances, such as following a knee replacement or 
stroke, patients may develop depression, anxiety, and/or SUDs. In other 
instances, patients may have been dealing with mental or behavioral 
health or SUD issues long before their post-acute admission. Left 
unmanaged, however, these conditions could make it difficult for 
affected patients to actively participate in medical rehabilitation or 
to adhere to the prescribed treatment regimen, thereby contributing to 
poor health outcomes.
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    \146\ Figueroa JF, Phelan J, Orav EJ, Patel V, Jha AK. 
Association of mental health disorders with health care spending in 
the Medicare population. JAMA Network Open. 2020 Mar 2;3(3):e201210. 
doi: 10.1001/jamanetworkopen.2020.1210. PMID: 32191329; PMCID: 
PMC7082719.
    \147\ Parish WJ, Mark TL, Weber EW, Steinberg DG. Substance Use 
Disorders Among Medicare Beneficiaries: Prevalence, Mental and 
Physical Comorbidities, and Treatment Barriers. Am J Prev Med. 2022 
Aug;63(2):225-232. doi: 10.1016/j.amepre.2022.01.021. PMID: 
35331570.
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    Information on the availability and appropriateness of behavioral 
health measures in PAC settings is limited, and the 2021 National 
Impact Assessment of the CMS Quality Measures Report \148\ identified 
PAC program measurement gaps in the areas of behavioral and mental 
health. Among the mental health quality measures in current use by 
other quality reporting programs, one Home Health QRP measure assesses 
the extent to which patients have been screened for depression and, if, 
positive, a follow-up plan is documented.\149\ Although it may be 
possible to adapt this depression screening measure for use in other 
PAC settings, this process measure does not directly assess performance 
in the management of depression and related mental health concerns.
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    \148\ Centers for Medicare & Medicaid Services. 2021 National 
Impact Assessment of the Centers for Medicare & Medicaid Services 
(CMS) Quality Measures Report. June 2021. https://www.cms.gov/files/document/2021-national-impact-assessment-report.pdf.
    \149\ Centers for Medicare & Medicaid Services. Depression 
Screening Conducted and Follow-Up Plan Documented. https://cmit.cms.gov/cmit/#/MeasureView?variantId=3102&sectionNumber=1.
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    Other instruments that may be adapted to assess management of 
mental health or SUDs in PAC settings include the Consumer Assessment 
of Healthcare Providers and Systems (CAHPS) Experience of Care and 
Health Outcomes Survey (ECHO), which consists of a series of questions 
that may be used to understand patients' perspectives concerning mental 
health services received; \150\ the PROMIS \151\ suite of instruments 
that may be used to monitor and evaluate mental health and quality of 
life; and the National Institutes of Health (NIH) Toolbox for the 
Assessment of Neurological and Behavioral Health Function,\152\ which 
was commissioned by the NIH Blueprint for Neuroscience Research and 
includes both stand-alone measures, and batteries of measures to assess 
emotional function and psychological well-being.
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    \150\ Agency for Healthcare Research and Quality. CAHPS Mental 
Health Care Surveys. May 2022. https://www.ahrq.gov/cahps/surveys-guidance/echo/index.html.
    \151\ HealthMeasures. Intro to PROMIS[supreg]. January 10, 2023. 
https://www.healthmeasures.net/explore-measurement-systems/promis/intro-to-promis.
    \152\ HealthMeasures. NIH Toolbox. February 9, 2023. https://www.healthmeasures.net/explore-measurement-systems/nih-toolbox.
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    Like other mental health issues, SUDs have been under studied in 
the IRF and other PAC settings, even though they are among the fastest 
growing disorders in the community dwelling older adult 
population.153 154 Left untreated, SUDs can lead to overdose 
deaths, emergency department visits, and hospitalizations. The 
Substance Abuse and Mental Health Services Administration (SAMHSA) was 
established by Congress in 1992 to make substance use and mental 
disorder information, services, and research more accessible. As part 
of its work, SAMHSA developed the Screening, Brief Intervention, and 
Referral to Treatment (SBIRT) approach to support providers in using 
early intervention with at-risk substance users before more severe 
consequences occur, and has a number of resources available.\155\
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    \153\ Desai A, Grossberg G. Substance Use Disorders in Postacute 
and Long-Term Care Settings. Psychiatr Clin North Am. 2022 
Sep;45(3):467-482. doi: 10.1016/j.psc.2022.05.005. PMID: 36055733.
    \154\ Sorrell JM. Substance Use Disorders in Long-Term Care 
Settings: A Crisis of Care for Older Adults. J Psychosoc Nurs Ment 
Health Serv. 2017 Jan 1;55(1):24-27. doi: 10.3928/02793695-20170119-
08. PMID: 28135388.
    \155\ Substance Abuse and Mental Health Services Administration. 
Resources for Screening, Brief Intervention, and Referral to 
Treatment (SBIRT). April 14, 2022. https://www.samhsa.gov/sbirt/resources.
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    We seek feedback on these and other measures or instruments that 
may be directly applied, adapted, or developed for use in the IRF QRP. 
Further, we seek comments on the degree to which measures have been or 
will require validation and testing prior to application in the IRF 
QRP. We seek input on the availability of data, the manner in which 
data could be collected and reported to CMS, and the burden imposed on 
IRFs.
c. Patient Experience and Patient Satisfaction
    Patient experience measures focus on how patients experienced or 
perceived selected aspects of their care, whereas patient satisfaction 
measures focus on whether a patient's expectations were met. 
Information on patient experience of care is typically collected via a 
number of instruments that rely on patient self-reported data. The most 
prominent among these is the CAHPS suite of surveys, although CAHPS 
instruments have not been developed for use in IRFs. However, we have 
developed the IRF Experience of Care Survey,\156\ which measures 
patient experience in terms of goal setting, communications with staff, 
respect and privacy received, ability to obtain assistance when needed, 
cleanliness of the facility, and other domains.
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    \156\ Centers for Medicare & Medicaid Services. Inpatient 
Rehabilitation Facility (IRF) Experience of Care. October 12, 2022. 
https://www.cms.gov/medicare/quality-initiatives-patient-assessment-instruments/irf-quality-reporting/irf-experience-of-care-.
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    One patient satisfaction measure that has been developed for use by 
SNFs and potentially could be adapted for use by IRFs is the CoreQ: 
Short Stay Discharge (CoreQ: SS DC) measure. The CoreQ: SS DC measure, 
which underwent 2017-2018 pre-rulemaking for the SNF QRP,\157\ assesses 
the level of satisfaction among SNF short-stay (less than 100 days) 
patients.
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    \157\ Centers for Medicare & Medicaid Services. List of Measures 
under Consideration for December 1, 2017. https://www.cms.gov/files/document/2017amuc-listclearancerpt.pdf.
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    We seek comment on the feasibility and challenges of adapting 
existing patient experience and patient satisfaction measures and 
instruments, such as the CMS IRF Experience of Care Survey and the 
CoreQ: SS DC measure, for use in the IRF QRP. We seek input on the 
extent to which patient experience measures offer IRFs sufficient 
information to assist in quality improvement, and the challenges of 
collecting and reporting patient experience and patient satisfaction 
data.
d. Chronic Conditions and Pain Management
    Despite the availability of measures focused on IRF clinical care, 
existing

[[Page 21003]]

IRF QRP measures do not directly address aspects of care rendered to 
populations with chronic conditions or IRFs' management of patients' 
pain. For example, the measures that address respiratory care relate to 
staff influenza and COVID-19 vaccination status. Although these 
measures target provider performance in preventing a respiratory 
illness with a potentially severe impact on morbidity and mortality, 
current measures fail to capture IRF performance in treatment or 
management of patients' chronic respiratory conditions, such as chronic 
obstructive pulmonary disease (COPD) or asthma.
    Existing IRF QRP measures also fail to capture concisely IRFs' 
actions with respect to patients' pain management, even though pain has 
been demonstrated to contribute to falls with major injury and 
restrictions in mobility and daily activity. However, a host of other 
factors also contribute to these measure domains, making it difficult 
to directly link provider actions to performance. Instead, a measure of 
IRFs' actions in reducing pain interference in daily activities, 
including the ability to sleep, would be a more concise measure of pain 
management. Beginning October 1, 2022, IRFs began collecting new 
standardized patient assessment data elements under the IRF QRP, 
including items that assess pain interference with (1) daily 
activities, (2) sleep, and (3) participation in therapy. The collection 
of this data may provide an opportunity to develop more concise 
measures of provider performance related to pain management in IRF 
patients (87 FR 39109 through 39161).
    Through this RFI, we are seeking input on measures of chronic 
condition and pain management for patients that may be used to assess 
IRF performance. Additionally, we seek general comment on the 
feasibility and challenges of measuring and reporting IRF performance 
on existing QRP measures, such as Discharge Self-Care Score and 
Discharge Mobility Score measures, for subgroups of patients defined by 
type of chronic condition. As examples, measures could assess discharge 
outcomes for IRF patients with a stroke diagnosis or for patients 
admitted with a diagnosis of multiple sclerosis.
4. Solicitation of Comments
    We invite general comments on the principles for identifying IRF 
QRP measures, as well as additional comments about measurement gaps, 
and suitable measures for filling these gaps. Specifically, we solicit 
comment on the following questions:

 Principles for Selecting and Prioritizing QRP Measures
    ++ To what extent do you agree with the principles for selecting 
and prioritizing measures?
    ++ Are there principles that you believe CMS should eliminate from 
the measure selection criteria?
    ++ Are there principles that you believe CMS should add to the 
measure selection criteria?
 IRF QRP Measurement Gaps
    ++ CMS requests input on the identified measurement gaps, including 
in the areas of cognitive function, behavioral and mental health, 
patient experience and patient satisfaction, and chronic conditions and 
pain management.
    ++ Are there gaps in the IRF QRP measures that have not been 
identified in this RFI?
 Measures and Measure Concepts Recommended for Use in the IRF 
QRP
    ++ Are there measures that you believe are either currently 
available for use, or that could be adapted or developed for use in the 
IRF QRP program to assess performance in the areas of (1) cognitive 
functioning, (2) behavioral and mental health, (3) patient experience 
and patient satisfaction, (4) chronic conditions, (5) pain management, 
or (6) other areas not mentioned in this RFI?

    CMS also seeks input on data available to develop measures, 
approaches for data collection, perceived challenges or barriers, and 
approaches for addressing challenges.

E. Health Equity Update

1. Background
    In the FY 2023 IRF PPS proposed rule (87 FR 20247 through 20254), 
we included an RFI entitled ``Overarching Principles for Measuring 
Equity and Healthcare Quality Disparities Across CMS Quality 
Programs.'' We define health equity as ``the attainment of the highest 
level of health for all people, where everyone has a fair and just 
opportunity to attain their optimal health regardless of race, 
ethnicity, disability, sexual orientation, gender identity, 
socioeconomic status, geography, preferred language, or other factors 
that affect access to care and health outcomes.'' \158\ We are working 
to advance health equity by designing, implementing, and 
operationalizing policies and programs that support health for all the 
people served by our programs and models, eliminating avoidable 
differences in health outcomes experienced by people who are 
disadvantaged or underserved, and providing the care and support that 
our enrollees need to thrive. Our goals outlined in the CMS Framework 
for Health Equity 2022-2023 \159\ are in line with Executive Order 
13985, ``Advancing Racial Equity and Support for Underserved 
Communities Through the Federal Government.'' \160\ The goals included 
in the CMS Framework for Health Equity serve to further advance health 
equity, expand coverage, and improve health outcomes for the more than 
170 million individuals supported by our programs, and set a foundation 
and priorities for our work, including: strengthening our 
infrastructure for assessment, creating synergies across the health 
care system to drive structural change, and identifying and working to 
eliminate barriers to CMS-supported benefits, services, and coverage.
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    \158\ Centers for Medicare and Medicaid Services. Health Equity. 
https://www.cms.gov/pillar/health-equity. October 3, 2022.
    \159\ Centers for Medicare & Medicaid Services. CMS Framework 
for Health Equity 2022-2032. https://www.cms.gov/files/document/cms-framework-health-equity-2022.pdf.
    \160\ The White House. Executive Order on Advancing Racial 
Equity and Support for Underserved Communities Through the Federal 
Government. Executive Order 13985, January 20, 2021. https://www.whitehouse.gov/briefing-room/presidential-actions/2021/01/20/executive-order-advancing-racial-equity-and-support-for-underserved-communities-through-the-federal-government/.
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    In addition to the CMS Framework for Health Equity, we seek to 
advance health equity and whole-person care as one of eight goals 
comprising the CMS National Quality Strategy (NQS).\161\ The NQS 
identifies a wide range of potential quality levers that can support 
our advancement of equity, including: (1) establishing a standardized 
approach for patient-reported data and stratification; (2) employing 
quality and value-based programs to address closing equity gaps; and 
(3) developing equity-focused data collections, regulations, oversight 
strategies, and quality improvement initiatives.
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    \161\ Centers for Medicare & Medicaid Services. What Is the CMS 
National Quality Strategy? https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Value-Based-Programs/CMS-Quality-Strategy.
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    A goal of this NQS is to address persistent disparities that 
underlie our healthcare system. Racial disparities, in particular, are 
estimated to cost the U.S. $93 billion in excess medical costs and $42 
billion in lost productivity per year, in addition to economic losses 
due to premature deaths.\162\ At the same time,

[[Page 21004]]

racial and ethnic diversity has increased in recent years with an 
increase in the percentage of people who identify as two or more races 
accounting for most of the change, rising from 2.9 percent to 10.2 
percent between 2010 and 2020.\163\ Therefore, we need to consider ways 
to reduce disparities, achieve equity, and support our diverse 
beneficiary population through the way we measure quality and display 
the data.
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    \162\ Turner A. The Business Case for Racial Equity: A Strategy 
for Growth. April 24, 2018. W.K. Kellogg Foundation and Altarum. 
https://altarum.org/RacialEquity2018.
    \163\ Agency for Healthcare Research and Quality. 2022 National 
Healthcare Quality and Disparities Report. November 2022. https://www.ahrq.gov/research/findings/nhqrdr/nhqdr22/index.html.
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    We solicited public comments via the aforementioned RFI on changes 
that we should consider in order to advance health equity. We refer 
readers to the FY 2023 IRF PPS final rule (87 FR 47072 through 47073) 
for a summary of the public comments and suggestions CMS received in 
response to the health equity RFI. We will take these comments into 
account as we continue to work to develop policies, quality measures, 
and measurement strategies on this important topic.
2. Anticipated Future State
    We are committed to developing approaches to meaningfully 
incorporate the advancement of health equity into the IRF QRP. One 
option we are considering is including social determinants of health 
(SDOH) as part of new quality measures.
    Social determinants of health are the conditions in the 
environments where people are born, live, learn, work, play, worship, 
and age that affect a wide range of health, functioning, and quality-
of-life outcomes and risks. They may have a stronger influence on the 
population's health and well-being than services delivered by 
practitioners and healthcare delivery organizations.\164\ Measure 
stratification is important for understanding differences in outcomes 
across different groups. For example, when pediatric measures over the 
past two decades are stratified by race, ethnicity, and income, they 
show that outcomes for children in the lowest income households and for 
Black and Hispanic children have improved faster than outcomes for 
children in the highest income households or for White children, thus 
narrowing an important health disparity.\165\ This analysis and 
comparison of the SDOH items in the assessment instruments support our 
desire to understand the benefits of measure stratification. Hospital 
providers receive such information in their confidential feedback 
reports and we think this learning opportunity would benefit post-acute 
care providers. The goals of the confidential reporting are to provide 
IRFs with their results; educate IRFs and offer the opportunity to ask 
questions; and solicit feedback from IRFs for future enhancements to 
the methods.
---------------------------------------------------------------------------

    \164\ Agency for Healthcare Research and Quality. 2022 National 
Healthcare Quality and Disparities Report. November 2022. https://www.ahrq.gov/research/findings/nhqrdr/nhqdr22/index.html.
    \165\ Agency for Healthcare Research and Quality. 2022 National 
Healthcare Quality and Disparities Report. November 2022. https://www.ahrq.gov/research/findings/nhqrdr/nhqdr22/index.html.
---------------------------------------------------------------------------

    We are considering whether health equity measures we have adopted 
for other settings, such as hospitals, could be adopted in post-acute 
care settings. We are exploring ways to incorporate SDOH elements into 
the measure specifications. For example, we could consider a future 
health equity measure like screening for social needs and 
interventions. With 30 percent to 55 percent of health outcomes 
attributed to SDOH,\166\ a measure capturing and addressing SDOH could 
encourage IRFs to identify patients' specific needs and connect them 
with the community resources necessary to overcome social barriers to 
their wellness. We could specify a health equity measure using the same 
SDOH data items that we currently collect as standardized patient 
assessment data elements under the IRF. These SDOH data items assess 
health literacy, social isolation, transportation problems, and 
preferred language (including need or want of an interpreter). We also 
see value in aligning SDOH data items across all care settings as we 
develop future health equity quality measures under our IRF QRP 
statutory authority. This would further the NQS to align quality 
measures across our programs as part of the Universal Foundation.\167\
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    \166\ World Health Organization. Social Determinants of Health. 
https://www.who.int/health-topics/social-determinants-of-health#tab=tab_1.
    \167\ Jacobs DB, Schreiber M, Seshamani M, Tsai D, Fowler E, 
Fleisher LA. Aligning Quality Measures across CMS--The Universal 
Foundation. N Engl J Med. 2023 Mar 2;338:776-779. doi: 10.1056/
NEJMp2215539. PMID: 36724323.
---------------------------------------------------------------------------

    As we move this important work forward, we will continue to take 
input from interested parties.

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

1. Background
    We refer readers to the regulatory text at Sec.  412.634(b)(1) for 
information regarding the current policies for reporting IRF QRP data.
2. Proposed Reporting Schedule for the IRF-PAI Assessment Data for the 
Discharge Function Score Measure Beginning With the FY 2025 IRF
    As discussed in section VIII.C.1.b. of this proposed rule, we are 
proposing to adopt the Discharge Function Score (DC Function) measure 
beginning with the FY 2025 IRF QRP. We are proposing that IRFs would be 
required to report these IRF-PAI assessment data related to the DC 
Function measure beginning with patients discharged on October 1, 2023, 
for purposes of the FY 2025 IRF QRP. Starting in CY 2024, IRFs would be 
required to submit data for the entire calendar year beginning with the 
FY 2026 IRF QRP. Because the DC Function measure is calculated based on 
data that are currently submitted to the Medicare program in the IRF-
PAI, there would be no new burden associated with data collection for 
this measure.
    We invite public comments on our proposal.
3. Proposed Reporting Schedule for the Data Submission of IRF-PAI 
Assessment Data for the COVID-19 Vaccine: Percent of Patients/Residents 
Who Are Up to Date Quality Measure Beginning With the FY 2026 IRF QRP
    As discussed in section VIII.C.2.a. of this proposed rule, we are 
proposing to adopt the COVID-19 Vaccine: Percent of Patients/Residents 
Who Are Up to Date (Patient/Resident COVID-19 Vaccine) measure 
beginning with the FY 2026 IRF QRP. We are proposing that IRFs would be 
required to report the IRF-PAI assessment data related to the Patient/
Resident COVID-19 Vaccine measure beginning with patients discharged on 
October 1, 2024 for purposes of the FY 2026 IRF QRP. Starting in CY 
2025, IRFs would be required to submit data for the entire CY beginning 
with the FY 2027 IRF QRP.
    We are also proposing to add a new item to the IRF-PAI in order for 
IRFs to report this measure. Specifically, a new item would be added to 
the IRF-PAI discharge assessment to collect information on whether a 
patient is up to date with their COVID-19 vaccine at the time of 
discharge from the IRF. A draft of the new item is available in the 
COVID-19 Vaccine: Percent of Patients/Residents Who Are Up to Date 
Draft Measure Specifications.\168\
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    \168\ COVID-19 Vaccine: Percent of Patients/Residents Who Are Up 
to Date. Draft Measure Specifications. https://www.cms.gov/files/document/patient-resident-covid-vaccine-draft-specs.pdf.
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    We invite public comments on our proposal.

[[Page 21005]]

G. 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. For a more detailed discussion about our 
policies regarding public display of IRF QRP measure data and 
procedures for the IRF's opportunity to review and correct data and 
information, we refer readers to the FY 2017 IRF PPS final rule (81 FR 
52045 through 52048).
2. Proposed Public Reporting of the Transfer of Health (TOH) 
Information to the Provider--Post-Acute Care (PAC) Measure and TOH 
Information to the Patient--PAC Measure Measures Beginning With the FY 
2025 IRF QRP
    We are proposing to begin publicly displaying data for the 
measures, TOH Information to the Provider--PAC Measure (TOH--Provider) 
and TOH Information to the--Patient PAC Measure (TOH--Patient) 
beginning with the September 2024 Care Compare refresh or as soon as 
technically feasible.
    We adopted these measures in the FY 2020 IRF PPS final rule (84 FR 
39099 through 39107). In response to the COVID-19 PHE, we issued an 
interim final rule (85 FR 27595 through 27596) which delayed the 
compliance date for the collection and reporting of the TOH--Provider 
and TOH--Patient measures to October 1st of the year that is at least 
one full FY after the end of the COVID-19 PHE. Subsequently, the CY 
2022 Home Health PPS Rate Update final rule (86 FR 62381 through 62386) 
revised the compliance date for the collection and reporting of the 
TOH--Provider and TOH--Patient measures under the IRF QRP to October 1, 
2022. Data collection for these two assessment-based measures in the 
IRF QRP began with patients discharged on or after October 1, 2022.
    We are proposing to publicly display four rolling quarters of the 
data we receive for these two assessment-based measures, initially 
using data on discharges from January 1, 2023, through December 31, 
2023 (Quarter 1 2023 through Quarter 4 2023); and to begin publicly 
reporting data on these measures with the September 2024 refresh of 
Care Compare, or as soon as technically feasible. To ensure the 
statistical reliability of the data, we are proposing that we would not 
publicly report an IRF's performance on a measure if the IRF had fewer 
than 20 eligible cases in any four consecutive rolling quarters for 
that measure. IRFs that have fewer than 20 eligible cases would be 
distinguished with a footnote that states, ``The number of cases/
patient stays is too small to publicly report.''
    We invite public comment on our proposal for the public display of 
the TOH--Provider and TOH--Patient assessment-based measures.
3. Proposed Public Reporting of the Discharge Function Score Measure 
Beginning With the FY 2025 IRF QRP
    We are proposing to begin publicly displaying data for the 
Discharge Function Score (DC Function) measure beginning with the 
September 2024 refresh of Care Compare, or as soon as technically 
feasible, using data collected from January 1, 2023 through December 
31, 2023 (Quarter 1 2023 through Quarter 4 2023). We are proposing that 
an IRF's DC Function measure score would be displayed based on four 
quarters of data. Provider preview reports would be distributed to IRFs 
in June 2024, or as soon as technically feasible. Thereafter, an IRF's 
DC Function measure score would be publicly displayed based on four 
quarters of data and updated quarterly. To ensure the statistical 
reliability of the data, we are proposing that we would not publicly 
report an IRF's performance on the measure if the IRF had fewer than 20 
eligible cases in any quarter. IRFs that have fewer than 20 eligible 
cases would be distinguished with a footnote that states: ``The number 
of cases/patient stays is too small to report.''
    We invite public comment on the proposal for the public display of 
the DC Function assessment-based measure beginning with the September 
2024 refresh of Care Compare, or as soon as technically feasible.
4. Proposed Public Reporting of the COVID-19 Vaccine: Percent of 
Patients/Residents Who Are Up to Date Measure Beginning With the FY 
2026 IRF QRP
    We are proposing to begin publicly displaying data for the COVID-19 
Vaccine: Percent of Patients/Residents Who are Up to Date (Patient/
Resident COVID-19 Vaccine) measure beginning with the September 2025 
refresh of Care Compare, or as soon as technically feasible, using data 
collected for Q4 2024 (October 1, 2024 through December 31, 2024). We 
are proposing that an IRF's percent of patients who are up to date, as 
reported under the Patient/Resident COVID-19 Vaccine measure, would be 
displayed based on one quarter of data. Provider preview reports would 
be distributed to IRFs in June 2025 for data collected in Q4 2024, or 
as soon as technically feasible. Thereafter, the percent of IRF 
patients who are up to date with their COVID-19 vaccinations would be 
publicly displayed based on one quarter of data updated quarterly. To 
ensure the statistical reliability of the data, we are proposing that 
we would not publicly report an IRF's performance on the measure if the 
IRF had fewer than 20 eligible cases in any quarter. IRFs that have 
fewer than 20 eligible cases would be distinguished with a footnote 
that states: ``The number of cases/patient stays is too small to 
report.''
    We invite public comment on the proposal for the public display of 
the Patient/Resident COVID-19 Vaccine measure beginning with the 
September 2025 refresh of Care Compare, or as soon as technically 
feasible.

IX. Collection of Information Requirements

    Under the Paperwork Reduction Act of 1995, we are required to 
provide 60-day notice in the Federal Register and solicit public 
comment before a collection of information requirement is submitted to 
the Office of Management and Budget (OMB) for review and approval. In 
order to fairly evaluate whether an information collection should be 
approved by OMB, section 3506(c)(2)(A) of the Paperwork Reduction Act 
of 1995 requires that we solicit comment on the following issues:
     The need for the information collection and its usefulness 
in carrying out the proper functions of our agency.
     The accuracy of our estimate of the information collection 
burden.
     The quality, utility, and clarity of the information to be 
collected.
     Recommendations to minimize the information collection 
burden on the affected public, including automated collection 
techniques.
    This proposed rule refers to associated information collections 
that are not discussed in the regulation text contained in this 
document.

A. Requirements for Updates Related to the IRF QRP Beginning With the 
FY 2025 IRF QRP

    An IRF that does not meet the requirements of the IRF QRP for a 
fiscal year would receive a 2-percentage point reduction to its 
otherwise applicable annual increase factor for that fiscal year.
    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. In section VIII.C. of this proposed rule, we are

[[Page 21006]]

proposing to modify one measure, adopt three new measures, and remove 
three measures from the IRF QRP.
    As stated in section VIII.C.1.a. of this proposed rule, we propose 
that IRFs submit data on one modified quality measure, the COVID-19 
Vaccination Coverage among Healthcare Personnel (HCP) (HCP COVID-19 
Vaccine) measure beginning with the FY 2025 IRF QRP. The data is 
collected through the Centers for Disease Control and Prevention 
(CDC's) National Health Safety Network (NHSN). IRFs currently utilize 
the NHSN for purposes of meeting other IRF QRP requirements, including 
the current HCP COVID-19 Vaccine measure. IRFs would continue to submit 
the HCP COVID-19 Vaccine measure data to CMS through the NHSN. The 
burden associated with the HCP COVID-19 Vaccine measure is accounted 
for under the CDC's information collection request currently approved 
under OMB control number 0920-1317 (expiration date: January 31, 2024). 
Because we are not proposing any updates to the form, manner, and 
timing of data submission for this HCP COVID-19 Vaccine measure, there 
would be no increase in burden associated with the proposal, and refer 
readers to the FY 2022 IRF PPS final rule (86 FR 42399 through 42400) 
for these policies.
    In section VIII.C.1.b. of this proposed rule, we propose to adopt 
the Discharge Function Score (DC Function) measure beginning with the 
FY 2025 IRF QRP. This assessment-based quality measure would be 
calculated using data from the IRF Patient Assessment Instrument (IRF-
PAI) that are already reported to CMS for payment and quality reporting 
purposes, and the burden is accounted for in the information collection 
request currently approved under OMB control number 0938-0842 
(expiration date: August 31, 2025). There would be no additional burden 
for IRFs associated with this proposed DC Function measure since it 
does not require collection of new data elements.
    In section VIII.C.1.c. of this proposed rule, we also propose to 
remove the Application of Percent of Long-Term Care Hospital Patients 
with an Admission and Discharge Functional Assessment and a Care Plan 
That Addresses Function (Application of Functional Assessment/Care 
Plan) measure beginning with the FY 2025 IRF QRP. We believe that the 
removal of the Application of Functional Assessment/Care Plan measure 
would result in a decrease of 18 seconds (0.3 minutes or 0.005 hours) 
of clinical staff time at admission beginning with the FY 2025 IRF QRP. 
We believe the IRF-PAI item affected by the Application of Functional 
Assessment/Care Plan measure is completed by Occupational Therapists 
(OT), Physical Therapists (PT), Registered Nurses (RN), Licensed 
Practical and Licensed Vocational Nurses (LVN), and/or Speech-Language 
Pathologists (SLP) depending on the functional goal selected. We 
identified the staff type per item based on past IRF burden 
calculations in conjunction with expert opinion. Our assumptions for 
staff type were based on the categories generally necessary to perform 
an assessment. Individual providers determine the staffing resources 
necessary. Therefore, we averaged the national average for these labor 
types and established a composite cost estimate. This composite 
estimate was calculated by weighting each salary based on the following 
breakdown regarding provider types most likely to collect this data: OT 
45 percent; PT 45 percent; RN 5 percent; LVN 2.5 percent; SLP 2.5 
percent. For the purposes of calculating the costs associated with the 
collection of information requirements, we obtained mean hourly wages 
for these staff from the U.S. Bureau of Labor Statistics' (BLS) May 
2021 National Occupational Employment and Wage Estimates.\169\ To 
account for overhead and fringe benefits, we have doubled the hourly 
wage. These amounts are detailed in Table 19.
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    \169\ U.S. Bureau of Labor Statistics' (BLS) May 2021 National 
Occupational Employment and Wage Estimates. https://www.bls.gov/oes/current/oes_nat.htm.

   Table 19--U.S. Bureau of Labor and Statistics' May 2021 National Occupational Employment and Wage Estimates
----------------------------------------------------------------------------------------------------------------
                                                                                   Overhead and      Adjusted
                Occupation title                    Occupation      Mean hourly   fringe benefit    hourly wage
                                                       code        wage  ($/hr)        ($/hr)         ($/hr)
----------------------------------------------------------------------------------------------------------------
Registered Nurse (RN)...........................         29-1141          $39.78          $39.78          $79.56
Licensed Vocational Nurse (LVN).................         29-2061           24.93           24.93           49.86
Speech Language Pathologist (SLP)...............         29-1127           41.26           41.26           82.52
Physical Therapist (PT).........................         29-1123           44.67           44.67           89.34
Occupational Therapist (OT).....................         29-1122           43.02           43.02           86.04
----------------------------------------------------------------------------------------------------------------

    As a result of this proposal, the estimated burden and cost for 
IRFs for complying with requirements of the FY 2025 IRF QRP would 
decrease. Specifically, we believe that there would be a 0.005 hour 
decrease in clinical staff time to report data for each IRF-PAI 
completed at admission. Using data from calendar year 2021, we estimate 
511,938 admission assessments from 1,128 IRFs annually. This equates to 
a decrease of 2,560 hours in burden at admission for all IRFs (0.005 
hour x 511,938 admissions). Given 0.135 minutes of occupational 
therapist time at $86.04 per hour, 0.135 minutes of physical therapist 
time at $89.34 per hour, 0.015 minutes registered nurse time at $79.56 
per hour, 0.0075 minutes of licensed vocational nurse time at $49.86 
per hour, and 0.0075 minutes of speech language pathologist time at 
$82.52 per hour to complete an average of 454 IRF-PAI admission 
assessments per IRF per year, we estimate the total cost would be 
decreased by $195.65 ($220,697.60 total reduction/1,128 IRFs) per IRF 
annually, or $220,697.60 for all IRFs annually based on the proposed 
removal of the Application of Functional Assessment/Care Plan measure.
    In section VIII.C.1.d. of this proposed rule, we propose to remove 
the IRF Functional Outcome Measure: Change in Self-Care Score for 
Medical Rehabilitation Patients (Change in Self-Care Score) and the IRF 
Functional Outcome Measure: Change in Mobility Score for Medical 
Rehabilitation Patients (Change in Mobility Score) measures beginning 
with the FY 2025 IRF QRP. While these assessment-based quality measures 
are proposed for removal, the data elements used to calculate the 
measures would still be collected by IRFs for payment and quality 
reporting purposes, specifically

[[Page 21007]]

for other quality measures under the IRF QRP. Therefore, we believe 
that the proposal to remove the Change in Self-Care Score and Change in 
Mobility Score measures would not decrease burden for IRFs.
    In section VIII.C.2.a. of this proposed rule, we propose to adopt 
the COVID-19 Vaccine: Percent of Patients/Residents Who Are Up to Date 
(Patient/Resident COVID-19 Vaccine) measure beginning with the FY 2026 
IRF QRP. The proposed measure would be collected using the IRF-PAI. One 
data element would need to be added to the IRF-PAI at discharge in 
order to allow for collection of the Patient/Resident COVID-19 Vaccine 
measure, and we believe would result in an increase of 0.3 minutes of 
clinical staff time at discharge. We believe that the additional 
Patient/Resident COVID-19 Vaccine measure's data element would be 
completed equally by registered nurses and licensed vocational nurses. 
Mean hourly wages for these staff are detailed in Table 19. However, 
individual IRFs determine the staffing resources necessary. Using data 
from CY 2021, we estimate a total of 779,274 discharges on all patients 
regardless of payer from 1,128 IRFs annually. This equates to an 
increase of 3,896 hours in burden for all IRFs (0.005 hour x 779,274 
admissions). Given 0.15 minutes of registered nurse time at $79.56 per 
hour and 0.15 minutes of licensed vocational nurse time at $49.86 per 
hour to complete an average of 691 IRF-PAI discharge assessments per 
IRF per year, we estimate that the total cost of complying with the IRF 
QRP requirements would be increased by $223.50 [($64.71/hr x 3,896 
hours)/1,128 IRFs) per IRF annually, or $252,110.16 ($64.71/hr x 3,896 
hours) for all IRFs annually based on the proposed adoption of the 
Patient/Resident COVID-19 Vaccine measure. The information collection 
request approved under OMB control number 0938-0842 (expiration date: 
August 31, 2025) will be revised and sent to OMB for approval.
    In summary, under OMB control number (0938-0842), if the proposals 
for the IRF QRP are adopted as proposed, we estimate that there would 
be a cost increase of $27.85 per IRF ($31,412.56/1,128 IRFs). The total 
cost increase related to this information collection is approximately 
$31,412.56 and is summarized in Table 20.

                        Table 20--Proposals Associated With OMB Control Number 0938-0842
----------------------------------------------------------------------------------------------------------------
                                                              Per IRF                        All IRFs
                                                 ---------------------------------------------------------------
                    Proposal                         Change in                       Change in
                                                   annual burden     Change in     annual burden     Change in
                                                       hours        annual cost        hours        annual cost
----------------------------------------------------------------------------------------------------------------
Change in Burden associated with proposed                   -2.3        -$195.65          -2,560    -$220,697.60
 removal of the Application of Functional
 Assessment/Care Plan measure beginning with the
 FY 2025 IRF QRP................................
Change in Burden associated with proposed                   +3.5         +223.50          +3,896     +252,110.16
 Patient/Resident COVID-19 Vaccine measure
 beginning with the FY 2026 IRF QRP.............
                                                 ---------------------------------------------------------------
    Total Change in burden for the IRF QRP                   1.2           27.85           1,336       31,412.56
     associated with 0938-0842..................
----------------------------------------------------------------------------------------------------------------

    We invite public comments on the proposed information collection 
requirements.
    If you comment on these information collection, that is, reporting, 
recordkeeping or third-party disclosure requirements, please submit 
your comments electronically as specified in the ADDRESSES section of 
this proposed rule.
    Comments must be received on/by June 2, 2023.

X. 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.

XI. Regulatory Impact Analysis

A. Statement of Need

    This proposed rule would update the IRF prospective payment rates 
for FY 2024 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 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 
productivity adjustment to the market basket increase factor for FY 
2012 and subsequent years.
    Furthermore, this proposed rule proposes to adopt policy changes to 
the IRF QRP under the statutory discretion afforded to the Secretary 
under section 1886(j)(7) of the Act. This rule proposes updates to the 
IRF QRP requirements beginning with the FY 2025 IRF QRP and FY 2026 IRF 
QRP. We propose a modification to a current measure in the IRF QRP 
which we believe will encourage healthcare personnel to remain up to 
date with the COVID-19 vaccine, resulting in fewer cases, less 
hospitalizations, and lower mortality associated with the virus. We 
propose adoption of two new measures: one measure to maintain 
compliance with the requirements of section 1899B of the Act and 
replace the current cross-setting process measure with a measure that 
is more strongly associated with desired patient functional outcomes; 
and a second measure that supports the goals of CMS Meaningful Measures 
Initiative 2.0 to empower consumers with tools and information as they 
make healthcare choices as well as assist IRFs leverage their care 
processes to increase vaccination coverage in their settings to protect 
residents and prevent negative outcomes. We propose the removal of 
three measures from the IRF QRP as they meet the criteria specified at 
Sec.  412.634(b)(2) for measure removal.

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).

[[Page 21008]]

    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 (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 significant 
effects as per section 3(f)(1) Executive Order 12866 ($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 2024 with those in FY 2023. This analysis results in an estimated 
$335 million increase for FY 2024 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 
$31,783,532.15 additional cost in FY 2026 for IRFs. Based on our 
estimates OMB's Office of Information and Regulatory Affairs has 
reviewed and determined that this rulemaking is ``significant'' as per 
section 3(f)(1) of Executive Order 12866. 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 1,128 IRFs, of which approximately 51 
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 21, we estimate that the net 
revenue impact of the final rule on all IRFs is to increase estimated 
payments by approximately 3.7 percent. The rates and policies set forth 
in this proposed rule will not have a significant impact (not greater 
than 4 percent) on a substantial number of small entities. The 
estimated impact on small entities is shown in Table 21. 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 21, we estimate that the net revenue 
impact of this proposed rule on rural IRFs is to increase estimated 
payments by approximately 3.2 percent based on the data of the 134 
rural units and 12 rural hospitals in our database of 1,128 IRFs for 
which data were available. We estimate an overall impact for rural IRFs 
in all areas between 1.3 percent and 5.1 percent. As a result, we 
anticipate that this proposed rule will not have a significant impact 
on a substantial number of small entities.
    Section 202 of the Unfunded Mandates Reform Act of 1995 (Pub. L. 
104-04, enacted 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 2023, that threshold is 
approximately $177 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 2023 IRF PPS final rule (87 FR 47038). Specifically, this proposed 
rule would update the CMG relative weights and ALOS values, the wage 
index, and the outlier threshold for high-cost cases. This proposed 
rule would apply a productivity adjustment to the FY 2024 IRF market 
basket increase factor in accordance with section 1886(j)(3)(C)(ii)(I) 
of the Act. Further, this proposed rule proposes to rebase and revise 
the IRF market basket to reflect a 2021 base year. We are also 
proposing to modify the regulation governing when IRF units can be 
excluded and paid under the IRF PPS.
    We estimate that the impact of the changes and updates described in 
this proposed rule would be a net estimated increase of $335 million in 
payments to IRFs. The impact analysis in Table 21 of this proposed rule 
represents the projected effects of the updates to IRF PPS payments for 
FY 2024 compared with the estimated IRF PPS payments in FY 2023. 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

[[Page 21009]]

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 2024, we are proposing the 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 reducing the FY 2024 IRF market 
basket increase factor by a productivity adjustment in accordance with 
section 1886(j)(3)(C)(ii)(I) of the Act. We estimate the total increase 
in payments to IRFs in FY 2024, relative to FY 2023, would be 
approximately $335 million.
    This estimate is derived from the application of the proposed FY 
2024 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 
$270 million. However, there is an estimated $65 million increase 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 $335 million from FY 
2023 to FY 2024.
    The effects of the proposed updates that impact IRF PPS payment 
rates are shown in Table 21. 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 2.3 percent to 3.0 percent of 
total estimated payments for FY 2024, consistent with section 
1886(j)(4) of the Act.
     The effects of the proposed annual market basket update 
(using the proposed 2021-based 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)(ii)(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, accounting for the permanent cap on wage index 
decreases when applicable.
     The effects of the proposed budget-neutral changes to the 
CMG relative weights and ALOS values under the authority of section 
1886(j)(2)(C)(i) of the Act.
     The total change in estimated payments based on the FY 
2024 payment changes relative to the estimated FY 2023 payments.
3. Description of Table 21
    Table 21 shows the overall impact on the 1,128 IRFs included in the 
analysis.
    The next 12 rows of Table 21 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 982 IRFs located in 
urban areas included in our analysis. Among these, there are 645 IRF 
units of hospitals located in urban areas and 337 freestanding IRF 
hospitals located in urban areas. There are 146 IRFs located in rural 
areas included in our analysis. Among these, there are 134 IRF units of 
hospitals located in rural areas and 12 freestanding IRF hospitals 
located in rural areas. There are 455 for-profit IRFs. Among these, 
there are 420 IRFs in urban areas and 35 IRFs in rural areas. There are 
570 non-profit IRFs. Among these, there are 480 urban IRFs and 90 rural 
IRFs. There are 103 government-owned IRFs. Among these, there are 82 
urban IRFs and 21 rural IRFs.
    The remaining four parts of Table 21 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 21. 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 2024 analysis file.
     Column (3) shows the number of cases in each category in 
our FY 2024 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 ALOS 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 2024 to our estimates of payments per discharge in FY 2023.
    The average estimated increase for all IRFs is approximately 3.7 
percent. This estimated net increase includes the effects of the 
proposed IRF market basket update for FY 2024 of 3.0 percent, which is 
based on a proposed IRF market basket increase factor of 3.2 percent, 
less a 0.2 percentage point productivity adjustment, as required by 
section 1886(j)(3)(C)(ii)(I) of the Act. It also includes the 
approximate 0.7 percent overall increase in estimated IRF outlier 
payments from the proposed update to the outlier threshold amount. 
Since we are making the proposed updates to the IRF wage index, labor-
related share and the CMG relative weights in a budget-neutral manner, 
they would not be expected to affect total estimated IRF payments in 
the aggregate. However, as described in more detail in each section, 
they would be expected to affect the estimated distribution of payments 
among providers.
BILLING CODE 4120-01-P

[[Page 21010]]

[GRAPHIC] [TIFF OMITTED] TP07AP23.009

BILLING CODE 4120-01-C

[[Page 21011]]

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 21.
    For this proposed rule, we are using preliminary FY 2022 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 2.3 percent in FY 2023. Thus, we propose to adjust the outlier 
threshold amount in this proposed rule to maintain total estimated 
outlier payments equal to 3 percent of total estimated payments in FY 
2024. The estimated change in total IRF payments for FY 2024, 
therefore, includes an approximate 0.7 percentage point increase in 
payments because the estimated outlier portion of total payments is 
estimated to increase from approximately 2.3 percent to 3.0 percent.
    The impact of this proposed outlier adjustment update (as shown in 
column 4 of Table 21) is to increase estimated overall payments to IRFs 
by 0.7 percentage point.
5. Impact of the Proposed Wage Index, Labor-Related Share, and Wage 
Index Cap
    In column 5 of Table 21, we present the effects of the proposed 
budget-neutral update of the wage index and labor-related share, taking 
into account the permanent 5 percent cap on wage index decreases, when 
applicable. 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.E. of this proposed rule, we are proposing to 
update the FY 2024 labor-related share from 72.9 percent in FY 2023 to 
74.1 percent in FY 2024. In aggregate, we do not estimate that these 
proposed updates will affect overall estimated payments to IRFs. 
However, we do expect these updates to have small distributional 
effects. We estimate the largest decrease in payment from the update to 
the CBSA wage index and labor-related share to be a 2.5 percent 
decrease for IRFs in the Rural New England region and the largest 
increase in payment to be a 0.6 percent increase for IRFs in the Urban 
Middle Atlantic Region.
6. Impact of the Proposed Update to the CMG Relative Weights and ALOS 
Values
    In column 6 of Table 21, we present the effects of the proposed 
budget-neutral update of the CMG relative weights and ALOS 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, with the largest effect 
being an increase in payments of 0.3 percent to IRFs in the Rural New 
England region.
7. Effects of Proposed Modification of the Regulation for Excluded IRF 
Units Paid Under the IRF PPS
    As discussed in section VII. of this proposed rule, we are 
proposing to amend the regulation text at Sec.  412.25(c)(1) in this 
proposed rule.
    We do not anticipate a financial impact associated with the 
proposed modification of the regulation for excluded IRF units paid 
under the IRF PPS. In response to the need for availability of 
inpatient rehabilitation beds we are proposing changes to Sec.  
412.25(c) to allow greater flexibility for hospitals to open excluded 
units, while minimizing the amount of effort that Medicare contractors 
would need to spend administering the regulatory requirements. We 
believe this proposal would provide IRFs greater flexibility when 
establishing an excluded unit at a time other than the start of a cost 
reporting period.
8. Effects of Requirements for the IRF QRP Beginning With FY 2025
    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 VIII.A. of the 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 VIII.C.1.a. of this proposed rule, we 
propose to modify one measure in the IRF QRP beginning with the FY 2025 
IRF QRP, the HCP COVID-19 Vaccine measure. We believe that the burden 
associated with the IRF QRP is the time and effort associated with 
complying with the non-claims-based measures requirements of the IRF 
QRP. The burden associated with the COVID-19 Vaccination Coverage among 
HCP measure is accounted for under the CDC PRA package currently 
approved under OMB control number 0920-1317 (expiration August 1, 
2025).
    As discussed in section VIII.C.1.b. of this proposed rule, we 
propose that IRFs would collect data on one new quality measure, the DC 
Function measure, beginning with assessments completed on October 1, 
2023. However, the measure utilizes data items that IRFs already report 
to CMS for payment and quality reporting purposes, and therefore the 
burden is accounted for in the PRA package approved under OMB control 
number 0920-0842 (expiration August 31, 2025).
    As discussed in section VIII.C.1.c. of this proposed rule, we 
propose to remove the Application of Functional Assessment/Care Plan 
measure, from the IRF QRP and this proposal would result in a decrease 
of 0.3 minutes of clinical staff time beginning with admission 
assessments completed on October 1, 2023. Although the proposed 
decrease in burden will be accounted for in a revised information 
collection request under OMB control number (0938-0842), we are 
providing impact information. We believe the data element for this 
quality measure is completed by occupational therapists (45 percent of 
the time or 0.135 minutes), physical therapists (45 percent of the time 
or 0.135 minutes), registered nurses (5 percent of the time or 0.015 
minutes), licensed practical and vocational nurses (2.5 percent of the 
time or 0.0075 minutes), or by speech-language pathologists (2.5 
percent of the time or 0.0075 minutes). For the purposes of calculating 
the costs associated with the collection of information requirements, 
we obtained mean hourly wages for these staff from the U.S. Bureau of 
Labor Statistics' (BLS) May 2021 National Occupational Employment and 
Wage Estimates.\170\ To account for overhead and fringe benefits, we 
have doubled the hourly wage. These amounts are detailed in Table 22.
---------------------------------------------------------------------------

    \170\ U.S. Bureau of Labor Statistics' (BLS) May 2021 National 
Occupational Employment and Wage Estimates. https://www.bls.gov/oes/current/oes_nat.htm.

[[Page 21012]]



   Table 22--U.S. Bureau of Labor and Statistics' May 2021 National Occupational Employment and Wage Estimates
----------------------------------------------------------------------------------------------------------------
                                                                                   Overhead and      Adjusted
                Occupation title                    Occupation      Mean hourly   fringe benefit    hourly wage
                                                       code        wage  ($/hr)        ($/hr)         ($/hr)
----------------------------------------------------------------------------------------------------------------
Registered Nurse (RN)...........................         29-1141          $39.78          $39.78          $79.56
Licensed Vocational Nurse (LVN).................         29-2061           24.93           24.93           49.86
Speech Language Pathologist (SLP)...............         29-1127           41.26           41.26           82.52
Physical Therapist (PT).........................         29-1123           44.67           44.67           89.34
Occupational Therapist (OT).....................         29-1122           43.02           43.02           86.04
----------------------------------------------------------------------------------------------------------------

    With 511,938 admissions from 1,128 IRFs annually, we estimate an 
annual burden decrease of 2,560 fewer hours (511,938 admissions x .005 
hours) and a decrease of $220,697.60 [2,560 hours x $86.21/hr]. For 
each IRF we estimate an annual burden decrease of 2.3 hours (2,560 
hours/1,128 IRFs) at a savings of $195.65 ($220,697.60/1,128 IRFs).
    As discussed in section VIII.C.1.d. of this proposed rule, we 
propose to remove two additional measures from the IRF QRP, the Change 
in Self-Care and Change in Mobility measures, beginning with 
assessments completed on October 1, 2023. However, the data items used 
in the calculation of this measure are used for other payment and 
quality reporting purposes, and therefore there is no change in burden 
associated with this proposal.
9. Effects of Requirements for the IRF QRP Beginning With FY 2026
    As discussed in section VIII.C.2.a. of this proposed rule, we 
propose to adopt a measure, the Patient/Resident COVID-19 Vaccine 
measure, beginning with the FY 2026 IRF QRP and this proposal would 
result in an increase of 0.3 minutes of clinical staff time beginning 
with discharge assessments completed on October 1, 2024. Although the 
proposed increase in burden will be accounted for in a revised 
information collection request under OMB control number (0938-0842), we 
are providing impact information. We estimate the data element for this 
quality measure would be completed by registered nurses (50 percent of 
the time or 0.15 minutes) or by licensed practical and vocational 
nurses (50 percent of the time or 0.15 minutes). For the purposes of 
calculating the costs associated with the collection of information 
requirements, we obtained mean hourly wages for these staff from the 
U.S. Bureau of Labor Statistics' (BLS) May 2021 National Occupational 
Employment and Wage Estimates.\171\ To account for overhead and fringe 
benefits, we have doubled the hourly wage. These amounts are detailed 
in Table 22. With 779,274 discharges on all patients regardless of 
payer from 1,128 IRFs annually, we estimate an annual burden increase 
of 3,896 hours (779,274 discharges x 0.005 hours) and an increase of 
$252,110.16 ($64.71/hr x 3,896 hours). For each IRF we estimate an 
annual burden increase of 3.5 hours (3,896 hours/1,128 IRFs) at an 
additional cost of $223.50 ($252,110.16/1,128 IRFs).
---------------------------------------------------------------------------

    \171\ U.S. Bureau of Labor Statistics' (BLS) May 2021 National 
Occupational Employment and Wage Estimates. https://www.bls.gov/oes/current/oes_nat.htm.
---------------------------------------------------------------------------

    In summary, under OMB control number (0938-0842), if the proposals 
associated with the IRF QRP are adopted as proposed, we estimate an 
increase in programmatic impact for 1,128 IRFs. The total burden 
reduction is approximately $31,412.56 and is summarized in Table 23.

                       Table 23--Estimated IRF QRP Program Impacts for FY 2025 and FY 2026
----------------------------------------------------------------------------------------------------------------
                                                              Per IRF                        All IRFs
                                                 ---------------------------------------------------------------
                    Proposal                         Change in                       Change in
                                                   annual burden     Change in     annual burden     Change in
                                                       hours        annual cost        hours        annual cost
----------------------------------------------------------------------------------------------------------------
Change in Burden associated with proposed                   -2.3        -$195.65          -2,560    -$220,697.60
 removal of the Application of Functional
 Assessment/Care Plan measure beginning with the
 FY 2025 IRF QRP................................
Change in Burden associated with proposed                   +3.5         +223.50          +3,896     +252,110.16
 Patient/Resident COVID-19 Vaccine measure
 beginning with the FY 2026 IRF QRP.............
                                                 ---------------------------------------------------------------
    Total increase in burden for the IRF QRP                 1.2           27.85           1,336       31,412.56
     proposals associated with this proposed
     rule.......................................
----------------------------------------------------------------------------------------------------------------

    We invite public comments on the overall impact of the IRF QRP 
proposals for FY 2025 and FY 2026.

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 and services 
included in the covered IRF services.
    We are proposing to adopt a market basket increase factor for FY 
2024 that is based on a rebased and revised market basket reflecting a 
2021 base year. We considered the alternative of continuing to use the 
IRF market basket without rebasing to determine the market basket 
increase factor for FY 2024. However, we typically rebase and revise 
the market baskets for the various PPS every 4 to 5 years so that the 
cost weights and price proxies reflect more recent data. Therefore, we 
believe it is more technically appropriate to use a 2021-based IRF 
market basket since it allows for the FY 2024 market basket increase 
factor to reflect a more up-to-date cost structure experienced by IRFs.
    As noted previously 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

[[Page 21013]]

that reflects changes over time in the prices of an appropriate mix of 
goods and services included in the covered IRF services and 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 
2024. 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 
3.0 percent (which equals the 3.2 percent estimated IRF market basket 
increase factor for FY 2024 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 maintaining the existing CMG relative weights and 
average length of stay values for FY 2024. 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, we believe that it 
is appropriate to propose to update the CMG relative weights and 
average length of stay values at this time to ensure that IRF PPS 
payments continue to reflect as accurately as possible the current 
costs of care in IRFs.
    We considered maintaining the existing outlier threshold amount for 
FY 2024. However, analysis of updated FY 2023 data indicates that 
estimated outlier payments would be less than 3 percent of total 
estimated payments for FY 2024, by approximately 0.7 percent, unless we 
updated the outlier threshold amount. Consequently, we propose 
adjusting the outlier threshold amount in this proposed rule to reflect 
a 0.7 percent increase thereby setting the total outlier payments equal 
to 3 percent, instead of 2.3 percent, of aggregate estimated payments 
in FY 2024.
    We considered not modifying the regulation governing when IRF units 
can be excluded and paid under the IRF PPS. However, we believe that 
amending the regulation would provide hospitals greater flexibility 
when establishing an IRF.
    With regard to the proposal to modify the HCP COVID-19 Vaccine 
measure and to add the Patient/Resident COVID-19 Vaccine measure to the 
IRF QRP Program, the COVID-19 pandemic has exposed the importance of 
implementing infection prevention strategies, including the promotion 
of COVID-19 vaccination for HCP and patients/residents. We believe 
these measures would encourage healthcare personnel to get up to date 
with the COVID-19 vaccine and increase vaccine uptake in patients/
residents resulting in fewer cases, less hospitalizations, and lower 
mortality associated with the SARS-CoV-2 virus, but we were unable to 
identify any alternative methods for collecting the data. An 
overwhelming public need exists to target quality improvement among 
IRFs as well as provide data to patients and caregivers through 
transparency of data. Therefore, these proposed measures have the 
potential to generate actionable data on COVID-19 vaccination rates.
    The proposal to replace the topped-out Application of Functional 
Assessment/Care Plan process measure with the proposed DC Function 
measure, which has strong scientific acceptability, satisfies the 
requirement that there be at least one cross-setting function measure 
in the PAC QRPs, including the IRF QRP, that uses standardized 
functional assessment data elements from standardized patient 
assessment instruments. We considered the alternative of delaying the 
proposal of adopting the DC Function measure. However, given the 
proposed DC Function measure's strong scientific acceptability, the 
fact that it provides an opportunity to replace the current cross-
setting process measure (that is, the Application of Functional 
Assessment/Care Plan measure) with an outcome measure, and uses 
standardized functional assessment data elements that are already 
collected, we believe further delay of the DC Function measure is 
unwarranted. Further, the proposed removal of the Application of 
Functional Assessment/Care Plan measure meets measure removal factors 
one and six, and no longer provides meaningful distinctions in 
improvements in performance. Finally, the proposal to remove the Change 
in Self-Care Score and Change in Mobility Score measures meets measure 
removal factor eight, and the costs associated with a measure outweigh 
the benefits of its use in the program. Therefore, no alternatives were 
considered.

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 2024 IRF PPS proposed rule will be the number of 
reviewers of last year's 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 
2023 IRF PPS proposed rule in detail, and it is also possible that some 
reviewers chose not to comment on the FY 2023 proposed rule. For these 
reasons, we thought that the number of 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.
    Using the national mean hourly wage data from the May 2021 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 $115.22 per hour, including overhead and fringe benefits 
(https://www.bls.gov/oes/current/oes_nat.htm). Assuming an average 
reading speed, we estimate that it would take approximately 3 hours for 
the staff to review half of this proposed rule. For each reviewer of 
the rule, the estimated cost is $345.66 (3 hours x $115.22). Therefore, 
we estimate that the total cost of reviewing this regulation is 
$21,085.26 ($345.66 x 61 reviewers).

F. Accounting Statement and Table

    As required by OMB Circular A-4 (available at https://www.whitehouse.gov/wp-content/uploads/legacy_drupal_files/omb/circulars/A4/a-4.pdf), in Table 24 we have prepared an accounting 
statement showing the classification of the expenditures associated 
with the provisions of this proposed rule. Table 24 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 1,128 IRFs in our database.

[[Page 21014]]



 Table 24--Accounting Statement: Classification of Estimated Expenditure
------------------------------------------------------------------------
                                       Category            Transfers
------------------------------------------------------------------------
Change in Estimated Transfers     Annualized          $335 million.
 from FY 2023 IRF PPS to FY 2024   Monetized
 IRF PPS.                          Transfers.
                                  From Whom to Whom?  Federal Government
                                                       to IRF Medicare
                                                       Providers.
Estimated Costs Associated with   Annualized          $31,412.56.
 the FY 2025 and FY 2026 IRF QRP.  monetized cost in
                                   FY 2025 and FY
                                   2026 for IRFs due
                                   to new quality
                                   reporting program
                                   requirements.
Estimated Costs Associated with   Cost associated     $21,085.26.
 Review Cost for FY 2024 IRF PPS.  with regulatory
                                   review cost.
------------------------------------------------------------------------

G. Conclusion

    Overall, the estimated payments per discharge for IRFs in FY 2024 
are projected to increase by 3.7 percent, compared with the estimated 
payments in FY 2023, as reflected in column 7 of Table 21.
    IRF payments per discharge are estimated to increase by 3.8 percent 
in urban areas and 3.2 percent in rural areas, compared with estimated 
FY 2023 payments. Payments per discharge to rehabilitation units are 
estimated to increase 4.4 percent in urban areas and 3.5 percent in 
rural areas. Payments per discharge to freestanding rehabilitation 
hospitals are estimated to increase 3.4 percent in urban areas and 2.3 
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 5.1 percent increase 
for IRFs located in the Rural Mountain 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.
    Chiquita Brooks-LaSure, Administrator of the Centers for Medicare & 
Medicaid Services, approved this document March 30, 2023.

List of Subjects 42 CFR 412

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

    For the reasons set forth in the preamble, the Centers for Medicare 
& Medicaid Services proposes to amend 42 CFR chapter IV as set forth 
below:

PART 412--PROSPECTIVE PAYMENT SYSTEMS FOR INPATIENT HOSPITAL 
SERVICES

0
1. The authority citation for part 412 continues to read as follows:

    Authority:  42 U.S.C. 1302 and 1395hh.

0
2. Amend Sec.  412.25 by revising paragraph (c)(1) to read as follows:


Sec.  412.25  Excluded hospital units: Common requirements.

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

    Dated: March 30, 2023.
Xavier Becerra,
Secretary, Department of Health and Human Services.
[FR Doc. 2023-06968 Filed 4-3-23; 4:15 pm]
BILLING CODE 4120-01-P