Medicare Program; Inpatient Rehabilitation Facility Prospective Payment System for Federal Fiscal Year 2024 and Updates to the IRF Quality Reporting Program, 20950-21014 [2023-06968]
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20950
Federal Register / Vol. 88, No. 67 / Friday, April 7, 2023 / Proposed Rules
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
Centers for Medicare &
Medicaid Services (CMS), HHS.
ACTION: Proposed rule.
AGENCY:
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 https://www.regulations.gov. Follow
the ‘‘Submit a comment’’ instructions.
2. By regular mail. You may mail
written comments to the following
address ONLY: Centers for Medicare &
Medicaid Services, Department of
Health and Human Services, Attention:
CMS–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,
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SUMMARY:
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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: https://
www.regulations.gov. Follow the search
instructions on that website to view
public comments. CMS will not post on
Regulations.gov public comments that
make threats to individuals or
institutions or suggest that the
individual will take actions to harm the
individual. CMS continues to encourage
individuals not to submit duplicative
comments. We will post acceptable
comments from multiple unique
commenters even if the content is
identical or nearly identical to other
comments.
Availability of Certain Information
Through the Internet on the CMS
Website
The IRF prospective payment system
(IRF PPS) Addenda along with other
supporting documents and tables
referenced in this proposed rule are
available through the internet on the
CMS website at https://www.cms.gov/
Medicare/Medicare-Fee-for-ServicePayment/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-
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for-Service-Payment/InpatientRehab
FacPPS.
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
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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-PostAcute 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
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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
Provision description
Transfers/costs
FY 2024 IRF PPS payment rate update ............
The overall economic impact of this final rule is an estimated $335 million in increased payments from the Federal Government to IRFs during FY 2024.
The overall economic impact of this final rule is an estimated increase in cost to IRFs of
$31,412.56 beginning with the FY 2025 IRF QRP.
FY 2025 through FY 2026 IRF QRP changes ...
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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-Feefor-Service-Payment/InpatientRehab
FacPPS.
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.
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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 budgetneutral 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
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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 facilitylevel 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-ServicePayment/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
§ 412.622(a)(4)(ii) for all IRFs during the
PHE for COVID–19. In the FY 2021 IRF
PPS final rule, to ease documentation
and administrative burden, we also
removed the post-admission physician
evaluation documentation requirement
at 42 CFR 412.622(a)(4)(ii) permanently
beginning in FY 2021.
A second IFC entitled, ‘‘Medicare and
Medicaid Programs, Basic Health
Program, and Exchanges; Additional
Policy and Regulatory Revisions in
Response to the COVID–19 Public
Health Emergency and Delay of Certain
Reporting Requirements for the Skilled
Nursing Facility Quality Reporting
Program’’ was published on May 8, 2020
(85 FR 27550) (hereinafter referred to as
the May 8, 2020 IFC). Among other
changes, the May 8, 2020 IFC included
a waiver of the ‘‘3-hour rule’’ at
§ 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
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 https://
dx.doi.org/10.15585/mmwr.mm6905e1.
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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).
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)
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-19emergency-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-19faqs-508.pdf).
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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 fivecharacter 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.
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A free download of the Grouper
software is available on the CMS
website at https://www.cms.gov/
Medicare/Medicare-Fee-for-ServicePayment/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/qualitysafety-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
https://www.cms.gov/manuals/
downloads/clm104c25.pdf.
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Section 3 of the ASCA operates in the
context of the administrative
simplification provisions of HIPAA,
which include, among others, the
requirements for transaction standards
and code sets codified in 45 CFR part
160 and part 162, subparts A and I
through R (generally known as the
Transactions Rule). The Transactions
Rule requires covered entities, including
covered healthcare providers, to
conduct covered electronic transactions
according to the applicable transaction
standards. (See the CMS program claim
memoranda at https://www.cms.gov/
ElectronicBillingEDITrans/ and listed in
the addenda to the Medicare
Intermediary Manual, Part 3, section
3600).
The MAC processes the claim through
its software system. This software
system includes pricing programming
called the ‘‘Pricer’’ software. The Pricer
software uses the CMG number, along
with other specific claim data elements
and provider-specific data, to adjust the
IRF’s prospective payment for
interrupted stays, transfers, short stays,
and deaths, and then applies the
applicable adjustments to account for
the IRF’s wage index, percentage of lowincome 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 postacute 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® (HL7) Fast Healthcare
Interoperability Resource® (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
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20953
(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, reassessment 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.
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.
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
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 https://
pacioproject.org/about/.
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-dataelement-library-fact-sheet.
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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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 postacute care.
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
10 Sections 4001 through 4008 of Public Law 114–
255. Available at https://www.govinfo.gov/content/
pkg/PLAW-114publ255/html/PLAW114publ255.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
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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-exchangeframework-and-common-agreement.
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
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/interoper
ability-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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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 § 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
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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
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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 hospitalspecific 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:
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20955
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.
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Generally, updates to the CMG
relative weights result in some increases
and some decreases to the CMG relative
weight values. Table 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
20959
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 change in CMG relative weights
Increased by 15% or more ......................................................................................................................................
Increased by between 5% and 15% .......................................................................................................................
Changed by less than 5% .......................................................................................................................................
Decreased by between 5% and 15% ......................................................................................................................
Decreased by 15% or more ....................................................................................................................................
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
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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
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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
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Number of
cases affected
Percentage of
cases affected
(percent)
81
1,263
375,622
843
0
0.0
0.3
99.4
0.2
0.0
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.
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Beginning with FY 2024, we are
proposing to rebase and revise the 2016based 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 2016based IRF market basket.
We invite public comment on our
proposed methodology for developing
the 2021-based IRF market basket.
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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
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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 2016based 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 Medicarecovered 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
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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
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ddrumheller on DSK120RN23PROD with PROPOSALS2
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 hospitalbased 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
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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 nonoverhead 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 hospitalbased 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,
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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
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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.
ddrumheller on DSK120RN23PROD with PROPOSALS2
(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.
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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 nonsalary 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,
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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 hospitalbased 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 hospitalbased IRF. However, when we derive
the cost weight for PLI for both hospitalbased 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.
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(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 hospitalbased 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.
ddrumheller on DSK120RN23PROD with PROPOSALS2
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
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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 hospitalbased 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
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20963
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 hospitalbased 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.
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TABLE 4—MAJOR COST CATEGORIES AS DERIVED FROM MEDICARE COST REPORTS
Proposed
2021-based
IRF market
basket
(percent)
Major cost categories
Wages and Salaries ................................................................................................................................................
Employee Benefits ...................................................................................................................................................
Contract Labor .........................................................................................................................................................
Professional Liability Insurance (Malpractice) .........................................................................................................
Pharmaceuticals ......................................................................................................................................................
Home Office/Related Organization Contract Labor .................................................................................................
Capital ......................................................................................................................................................................
All Other ...................................................................................................................................................................
2016-based
IRF market
basket
(percent)
46.6
11.6
2.0
0.8
4.7
5.4
8.6
20.4
47.1
11.3
1.0
0.7
5.1
3.7
9.0
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-based
IRF market
basket
Major cost categories
Wages and Salaries ................................................................................................................................................
Employee Benefits ...................................................................................................................................................
ddrumheller on DSK120RN23PROD with PROPOSALS2
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 https://www.bea.gov/
industry/io_annual.htm. For the 2016based 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
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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
16 https://www.bea.gov/papers/pdf/IOmanual_
092906.pdf.
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48.2
11.9
2016-based
IRF market
basket
47.9
11.4
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).
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 Nonlaborrelated Services.
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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 hospitalbased 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 hospitalbased 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).
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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) Forprofit.
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 hospitalbased 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.
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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 hospitalbased 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 forprofit 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.
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TABLE 6—CAPITAL COST SHARE COMPOSITION FOR THE PROPOSED 2021-BASED IRF MARKET BASKET
Capital cost share
composition
before lease
expense
allocation
(percent)
Capital cost share
composition
after lease
expense
allocation
(percent)
48
30
18
10
5
5
34
8
70
44
26
14
7
7
..............................
16
Depreciation .................................................................................................................................................
Building and Fixed Equipment .............................................................................................................
Movable Equipment ..............................................................................................................................
Interest .........................................................................................................................................................
Government/Nonprofit ..........................................................................................................................
For Profit ...............................................................................................................................................
Lease ....................................................................................................................................................
Other Capital-related costs ..........................................................................................................................
* 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.
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BILLING CODE 4120–01–C
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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.)
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• 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-todate, 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 2021based 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).
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(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 2016based 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 2016based IRF market basket (84 FR 39080).
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(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 2016based IRF market basket (84 FR 39080).
(9) Chemicals
Similar to the 2016-based IRF market
basket, we are proposing to use a fourpart 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 weights
(percent)
Name
PPI
PPI
PPI
PPI
for
for
for
for
Industrial Gas Manufacturing ......................................................................................................................
Other Basic Inorganic Chemical Manufacturing .........................................................................................
Other Basic Organic Chemical Manufacturing ............................................................................................
Other Miscellaneous Chemical 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
19
13
60
8
NAICS
325120
325180
325190
325998
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 weights
(percent)
Name
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PPI—Commodity—Surgical and medical instruments ............................................................................................
PPI—Commodity—Medical and surgical appliances and supplies .........................................................................
PPI—Commodity—Miscellaneous products-Personal safety equipment and clothing ...........................................
(11) Rubber and Plastics
(13) Miscellaneous Products
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 2016based IRF market basket (84 FR 39081).
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).
(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).
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(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
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22
22
NAICS
339112
339113
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 2016based 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
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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 2016based 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 2016based 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 2016based 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 2016based 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 2016based IRF market basket (84 FR 39081).
ddrumheller on DSK120RN23PROD with PROPOSALS2
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 capitalrelated 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:
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• 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 capitalrelated 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 longterm 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 nonvintage price changes for capital are
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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 capitalrelated component of the proposed
2021-based IRF market basket reflects
the underlying stability of the capitalrelated 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 capitalrelated 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 2021based 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.
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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 straightline 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)
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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 capitalrelated 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.
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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 capitalrelated 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 25year 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.
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example vintage weights and example
price indices. The example can be found
at https://www.cms.gov/ResearchStatistics-Data-and-Systems/StatisticsTrends-and-Reports/MedicareProgram
RatesStats/MarketBasketResearch.html
in the zip file titled ‘‘Weight
Calculations as described in the IPPS FY
2010 Proposed Rule.’’
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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
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The process of creating vintageweighted 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
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BILLING CODE 4120–01–D
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We invite public comment on our
proposal to rebase and revise the IRF
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market basket to reflect a 2021 base
year.
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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 market
basket index
percent
change
Fiscal year
(FY)
2016-based
IRF market
basket index
percent
change
Historical data
FY
FY
FY
FY
2019
2020
2021
2022
...................................................................................................................................................................
...................................................................................................................................................................
...................................................................................................................................................................
...................................................................................................................................................................
2.4
2.1
2.8
5.3
2.3
2.1
2.7
5.3
Average 2019–2022 .........................................................................................................................................
3.2
3.1
...................................................................................................................................................................
...................................................................................................................................................................
...................................................................................................................................................................
...................................................................................................................................................................
4.6
3.2
2.9
2.8
4.6
3.2
2.9
2.8
Average 2023–2026 .........................................................................................................................................
3.4
3.4
Forecast
FY
FY
FY
FY
2023
2024
2025
2026
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.
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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
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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
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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-StatisticsDataand-Systems/Statistics-TrendsandReports/MedicareProgram
RatesStats/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
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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
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the local labor market. We propose to
continue to classify a cost category as
labor-related if the costs are laborintensive and vary with the local labor
market. As stated in the FY 2020 IRF
PPS final rule (84 FR 39087), the laborrelated 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 laborrelated 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: Laborrelated, 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: Laborrelated and Professional Fees: Nonlaborrelated. 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:
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• 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-andGuidance/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
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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 laborrelated 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 2021based IRF market basket to use the
Medicare cost reports for both
freestanding IRF providers and hospitalbased 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 hospitalbased 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: Laborrelated cost weight and 3.0 percentage
points of the Home Office/Related
Organization Contract Labor cost weight
to the Professional Fees: Nonlaborrelated 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: Laborrelated 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 2016based 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 laborrelated 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
ddrumheller on DSK120RN23PROD with PROPOSALS2
FY 2024
proposed
labor-related
share 1
FY 2023 final
labor related
share 2
Wages and Salaries ................................................................................................................................................
Employee Benefits ...................................................................................................................................................
Professional Fees: Labor-related 3 ..........................................................................................................................
Administrative and Facilities Support Services .......................................................................................................
Installation, Maintenance, and Repair Services ......................................................................................................
All Other: Labor-related Services ............................................................................................................................
48.9
11.9
5.5
0.7
1.5
1.8
48.7
11.3
4.9
0.8
1.6
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.
on the 2016-based IRF market basket as published in the Federal Register (87 FR 47052).
all contract advertising and marketing costs and a portion of accounting, architectural, engineering, legal, management consulting,
and home office/related organization contract labor costs.
2 Based
3 Includes
The FY 2024 labor-related share using
the proposed 2021-based IRF market
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basket is 1.2 percentage point higher
than the FY 2023 labor-related share
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using the 2016-based IRF market basket.
This higher labor-related share is
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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.
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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 § 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
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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 prereclassification 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
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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/wpcontent/uploads/2018/09/Bulletin-1804.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
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OMB Bulletin No. 18–04 (available at
https://www.whitehouse.gov/wpcontent/uploads/2018/09/Bulletin-1804.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/Bulletin20-01.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 laborrelated 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-ServicePayment/InpatientRehabFacPPS/IRFRules-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 § 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 laborrelated 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.
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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
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Explanation for adjustment
Calculations
Standard Payment Conversion Factor for FY 2023 ............................................................................................................................
Proposed Market Basket Increase Factor for FY 2024 (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 Index and Labor-Related Share ...................................................................
Budget Neutrality Factor for the Revisions to the CMG Relative Weights .........................................................................................
× 1.030
× 1.0032
× 0.9999
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
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FY 2024 standard payment conversion
factor ($18,471), the resulting
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$17,878
unadjusted IRF prospective payment
rates for FY 2024 are shown in Table 15.
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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
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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
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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
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(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 nonlabor 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 wageadjusted 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-andRelated-Files.html.
The resulting figure is the wageadjusted labor amount. Next, we
compute the proposed wage-adjusted
Federal payment by adding the wageadjusted 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 wageadjusted and rural-adjusted amount (if
applicable). Finally, we add the
additional teaching status payments (if
applicable) to the wage, rural, and LIPadjusted 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
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
Rural Facility A
(Spencer Co., IN)
Unadjusted Payment .............................................................................................
Labor-Related Share .............................................................................................
Labor Portion of Payment .....................................................................................
CBSA-Based Wage Index ....................................................................................
Wage-Adjusted Amount ........................................................................................
Non-Labor Amount ................................................................................................
Wage-Adjusted Payment ......................................................................................
Rural Adjustment ..................................................................................................
Wage- and Rural-Adjusted Payment ....................................................................
LIP Adjustment ....................................................................................................
Wage-, Rural- and LIP-Adjusted Payment .........................................................
Wage- and Rural-Adjusted Payment ..................................................................
Teaching Status Adjustment ...............................................................................
Teaching Status Adjustment Amount .................................................................
Wage-, Rural-, and LIP-Adjusted Payment ........................................................
Total Adjusted Payment ......................................................................................
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.
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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
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×
=
×
=
+
=
×
=
×
=
×
=
+
=
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
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$28,870.17
0.741
$21,392.80
0.8353
$17,869.40
$7,477.37
$25,346.78
1.149
$29,123.45
1.0156
$29,577.77
$29,123.45
0
$0.00
$29,577.77
$29,577.77
Urban Facility B
(Harrison Co., IN)
×
=
×
=
+
=
×
=
×
=
×
=
+
=
$28,870.17
0.741
$21,392.80
0.8804
$18,834.22
$7,477.37
$26,311.59
1.000
$26,311.59
1.0454
$27,506.14
$26,311.59
0.0784
$2,062.83
$27,506.14
$29,568.97
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
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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.
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B. Proposed Update to the IRF Cost-toCharge 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 facilityspecific 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.
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• 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
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20981
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
§ 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
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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
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proposed revising §§ 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 § 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
§ 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 § 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
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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
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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 § 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 § 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 § 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.
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B. Current Challenges Related To
Excluded Hospital Units (§ 412.25(c)(1)
and (c)(2))
Currently, under § 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,
§ 412.25(c) limits when the status of
hospital units may change for purposes
of exclusion from the IPPS, as specified
in § 412.25(c)(1) and § 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 § 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 § 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 § 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
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20983
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
§ 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 (§ 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 patientcentered 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 § 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 § 412.25(c) applies to
both IRFs and IPFs; therefore, revisions
to § 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
§ 412.25(c) and unique considerations
applicable to IPF units.
As discussed, the current
requirements of § 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
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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 § 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
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at § 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 § 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 § 412.25(c)(1) and § 412.25(c)(2) into
a new § 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 § 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
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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 § 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 § 412.634(b)(2).
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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.
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.
measure was submitted to the Measures
Under Consideration (MUC) List as the CrossSetting Discharge Function Score. Subsequent to
the MAP Workgroup meetings, the measure
developer modified the name.
21:49 Apr 06, 2023
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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
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/2019nCoV.aspx.
17 This
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Measure Proposals
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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).
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
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
19 Centers for Disease Control and Prevention.
COVID Data Tracker. March 21, 2023. https://
covid.cdc.gov/covid-data-tracker/#datatrackerhome.
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/factsheet-covid-19-public-health-emergency-transitionroadmap.html.
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/qs0-23-02all.pdf.
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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 PfizerBioNTech 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
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-keyaction-fight-against-covid-19-issuing-emergencyuse-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-19issuing-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-issuesemergency-use-authorization-third-covid-19vaccine.
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/pressannouncements/coronavirus-covid-19-update-fdatakes-key-action-approving-second-covid-19vaccine.
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-19update-fda-authorizes-emergency-use-novavaxcovid-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/newsevents/press-announcements/fda-authorizesbooster-dose-pfizer-biontech-covid-19-vaccinecertain-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/coronaviruscovid-19-update-fda-takes-additional-actions-usebooster-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/pressannouncements/coronavirus-covid-19-update-fdaexpands-eligibility-covid-19-vaccine-boosters.
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second booster dose of the PfizerBioNTech 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
(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. Twodose COVID–19 vaccines from PfizerBioNTech 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
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/pressannouncements/coronavirus-covid-19-update-fdaauthorizes-second-booster-dose-two-covid-19vaccines-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/pressannouncements/coronavirus-covid-19-update-fdaauthorizes-moderna-pfizer-biontech-bivalent-covid19-vaccines-use.
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.
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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.
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
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/.
38 Centers for Disease Control and Prevention.
Variants of the Virus. https://www.cdc.gov/
coronavirus/2019-ncov/variants/.
39 Food and Drug Administration. COVID–19
Bivalent Vaccine Boosters. https://www.fda.gov/
emergency-preparedness-and-response/
coronavirus-disease-2019-covid-19/covid-19bivalent-vaccine-boosters.
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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 PfizerBioNTech 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
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
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. PfizerBioNTech COVID–19 Vaccines. https://
www.fda.gov/emergency-preparedness-andresponse/coronavirus-disease-2019-covid-19/pfizerbiontech-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-covid19-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-authorizesmoderna-pfizer-biontech-bivalent-covid-19vaccines-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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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
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-specifications2022-2023.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-specifications2022-2023.pdf.
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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.
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 prerulemaking cycle for consideration by
the MAP. Interested parties submitted
three comments during the prerulemaking 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
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.
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/2022MUC-List-Overview.pdf.
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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.
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/LongTerm 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
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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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).
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
(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
51 2022–2023 MAP Final Recommendations.
https://mmshub.cms.gov/sites/default/files/20222023-MAP-Final-Recommendations-508.xlsx.
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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:
• 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. Postresidency 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.
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
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.
We refer readers to https://
www.cdc.gov/nhsn/nqf/ 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
52 Centers for Disease Control and Prevention.
Contraindications and precautions. https://
www.cdc.gov/vaccines/covid-19/clinicalconsiderations/interim-considerationsus.html#contraindications.
53 Centers for Disease Control and Prevention.
Contraindications and precautions. https://
www.cdc.gov/vaccines/covid-19/clinicalconsiderations/interim-considerationsus.html#contraindications.
54 The updated (bivalent) Moderna and PfizerBioNTech 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.
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.
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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 onefifth of IRF cases.57 For stroke patients,
rehabilitation has been shown to be the
most effective way to reduce strokeassociated 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
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
56 42
CFR 412.29.
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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57 Medicare
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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 crosssetting functional outcome measure
would align measure specifications
across settings, including the use of a
common set of standardized functional
assessment data elements.
(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
59 Centers for Medicare & Medicaid Services. 2022
Annual Call for Quality Measures Fact Sheet, p. 10.
https://www.cms.gov/files/document/mips-callquality-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.
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
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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 postacute care.62 63 64 Nonetheless, evidence
suggests that physical functional
abilities, including mobility and selfcare, are modifiable predictors of patient
outcomes across PAC settings, including
functional recovery or decline after
post-acute care,65 66 67 68
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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rehospitalization rates,69 70 71 discharge
to community,72 73 and falls.74
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
69 Li CY, Haas A, Pritchard KT, Karmarkar A, Kuo
YF, Hreha K, Ottenbacher KJ. Functional Status
Across Post-Acute Settings Is Associated With 30Day 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 HighIntensity 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.
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
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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
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.
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20991
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 crosssetting 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).
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 crosssetting 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 crosssetting 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
85 Discharge Function Score for Inpatient
Rehabilitation Facilities (IRFs) Technical Report.
https://www.cms.gov/files/document/irf-dischargefunction-score-technical-report-february-2023.pdf.
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-andSystems/Statistics-Trends-and-Reports/Reports/
Downloads/GAGE_PACPRD_RTC_Supp_Materials_
May_2011.pdf.
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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.
(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.
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TABLE 18—SPEARMAN’S RANK CORRELATION RESULTS OF DC FUNCTION MEASURE WITH PUBLICLY REPORTED IRF
QUALITY MEASURES
Measure—long name
Measure—short name
Discharge to Community—PAC IRF QRP .............................................................................................
IRF Functional Outcome Measure: Change in Self-Care Score for Medical Rehabilitation Patients ...
IRF Functional Outcome Measure: Change in Mobility Score for Medical Rehabilitation Patients ......
IRF Functional Outcome Measure: Discharge Self-Care Score for Medical Rehabilitation Patients ....
IRF Functional Outcome Measure: Discharge Mobility Score for Medical Rehabilitation Patients .......
Discharge to Community ............
Change in Self-Care Score ........
Change in Mobility Score ...........
Discharge Self-Care Score .........
Discharge Mobility Score ............
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
88 ‘‘Expected functional capabilities’’ is defined as
the predicted discharge function score.
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Score), and the IRF Functional Outcome
Measure: Discharge Mobility Score for
Medical Rehabilitation Patients measure
(Discharge Mobility 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
(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
89 Discharge Function Score for Inpatient
Rehabilitation Facilities (IRFs) Technical Report.
https://www.cms.gov/files/document/irf-dischargefunction-score-technical-report-february-2023.pdf.
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0.82
0.86
0.85
0.88
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 crosssetting 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
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.
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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.
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 crosssetting 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
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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
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20993
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.
Finally, we solicited feedback from
interested parties on the importance,
relevance, and applicability of a crosssetting functional outcome measure for
IRFs through an RFI in the FY 2023 IRF
PPS proposed rule (87 FR 20244).
Commenters were supportive of a crosssetting 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
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-SummaryReport-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-FunctionTEP-Summary-Report-Jan2022-508.pdf.
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-ListOverview.pdf.
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second commenter supported including
the measure in the IRF QRP measures
we propose through rulemaking.
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 riskadjusting the observed discharge scores
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(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
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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 settingspecific 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
(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
94 2022–2023 MAP Final Recommendations.
https://mmshub.cms.gov/sites/default/files/20222023-MAP-Final-Recommendations-508.xlsx.
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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 riskadjusting 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
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
95 Discharge Function Score for Inpatient
Rehabilitation Facilities (IRFs) Technical Report.
https://www.cms.gov/files/document/irf-dischargefunction-score-technical-report-february-2023.pdf.
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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.
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.
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
96 Discharge Function Score for Inpatient
Rehabilitation Facilities (IRFs) Technical Report.
https://www.cms.gov/medicare/quality-initiativespatient-assessment-instruments/irf-qualityreporting/irf-quality-reporting-program-measuresinformation-.
97 For more information on the factors CMS uses
to base decisions for measure removal, we refer
readers to § 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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20995
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.
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
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.
103 ‘‘Expected functional capabilities’’ is defined
as the predicted discharge function score.
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replaced with a measure that evaluates
the IRF’s outcome of care on a patient’s
function.
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 SelfCare 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
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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 SelfCare 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
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-PACFunction.pdf.
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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.
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
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
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-PACFunction.pdf.
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-PACFunction.pdf.
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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 SelfCare 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
ddrumheller on DSK120RN23PROD with PROPOSALS2
(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
107 Centers for Disease Control and Prevention.
COVID Data Tracker. https://covid.cdc.gov/coviddata-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/PolicyBrief-The-Impact-of-COVID-19-on-OlderPersons.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.
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mental health and well-being due to
social distancing.111
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–19associated hospitalization for adults
who were fully vaccinated was 76
percent among adults age 75 and
older.114
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,
111 United Nations. Policy Brief: The impact of
COVID–19 on older persons. May 2020. https://
unsdg.un.org/sites/default/files/2020-05/PolicyBrief-The-Impact-of-COVID-19-on-OlderPersons.pdf.
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-lesshospitalized.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. https://dx.doi.org/10.15585/
mmwr.mm7037e2.
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,
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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 nonvaccinated 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
(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
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. Covid19 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/#vaccineeffectiveness.
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., Rodrı
´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.
122 Centers for Disease Control and Prevention.
COVID–19 vaccinations in the United States.
COVID Data Tracker. https://covid.cdc.gov/coviddata-tracker/#vaccinations_vacc-people-boosterpercent-pop5.
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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
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-VaccinationAge-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/coronaviruscovid-19/issue-brief/deaths-among-older-adultsdue-to-covid-19-jumped-during-the-summer-of2022-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/#vaccinationdemographics-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 withinrural differences in COVID–19 vaccination rates. J
Rural Health. 2022 Sep;38(4):916–922. doi:
10.1111/jrh.12625. PMID: 34555222; PMCID:
PMC8661570.
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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
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
129 Centers for Disease Control and Prevention.
COVID Data Tracker. Vaccination Equity. https://
covid.cdc.gov/covid-data-tracker/#vaccinationequity.
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/#vaccinationequity.
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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–
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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
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
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/COVID19Patient-Level-Vaccination-TEP-Summary-ReportNovDec2021.pdf.
132 87 FR 20218.
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well as whether an IRF length of stay
would allow for meaningful distinctions
among IRFs (87 FR 47071).
(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
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
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-ListOverview.pdf.
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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
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-andreports.
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-andreports.
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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
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
136 CMS Measures Management System (MMS).
Measure Implementation: Pre-rulemaking MUC
Lists and MAP reports. https://mmshub.cms.gov/
measure-lifecycle/measure-implementation/prerulemaking/lists-and-reports.
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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
(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.
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,
137 2022–2023 MAP Final Recommendations.
https://mmshub.cms.gov/measure-lifecycle/
measure-implementation/pre-rulemaking/lists-andreports.
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/stayup-to-date.html (updated March 2, 2023).
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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-ResidentCOVID-Vaccine-Draft-Specs.pdf.139
available on the IRF QRP Measures and
Technical Information web page.
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 crosscomparisons 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.
In alignment with the CMS NQS, the
IRF QRP endeavors to move toward a
139 Patient-Resident-COVID-Vaccine-DraftSpecs.pdf. https://www.cms.gov/medicare/qualityinitiatives-patient-assessment-instruments/irfquality-reporting/irf-quality-reporting-programmeasures-information-.
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/cmsnational-quality-strategy-person-centeredapproach-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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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
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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©).142 Both the BIMS and CAM©
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© assesses the presence of delirium
and inattention, and level of
consciousness. While data from the
BIMS and CAM© are collected and
reported via the IRF–PAI, these items
have not been developed into specific
quality measures for the IRF QRP.
Alternative sources of information on
cognitive function include the PatientReported Outcomes Measurement
Information Set (PROMIS) Cognitive
Function forms and the PROMIS Neuro142 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-paiversion-40-eff-10012022-final.pdf.
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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 NeuroQoL, which was specifically designed
for use in patients with neurological
conditions, assesses patient perceptions
regarding oral expression, memory,
attention, decision-making, planning,
and organization.
The BIMS, CAM©, 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© (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©,
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
143 HealthMeasures. List of Adult Measures:
Available Neuro-QoLTM Measures for Adult SelfReport. https://www.healthmeasures.net/exploremeasurement-systems/neuro-qol/intro-to-neuro-qol/
list-of-adult-measures.
144 HealthMeasures. List of Adult Measures:
Available PROMIS® Measures for Adults. https://
www.healthmeasures.net/explore-measurementsystems/promis/intro-to-promis/list-of-adultmeasures.
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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improving or maintaining cognitive
functioning.
b. Behavioral and Mental Health
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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.
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 followup 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.
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.
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-assessmentreport.pdf.
149 Centers for Medicare & Medicaid Services.
Depression Screening Conducted and Follow-Up
Plan Documented. https://cmit.cms.gov/cmit/#/
MeasureView?variantId=3102§ionNumber=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.
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
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
150 Agency for Healthcare Research and Quality.
CAHPS Mental Health Care Surveys. May 2022.
https://www.ahrq.gov/cahps/surveys-guidance/
echo/.
151 HealthMeasures. Intro to PROMIS®. January
10, 2023. https://www.healthmeasures.net/exploremeasurement-systems/promis/intro-to-promis.
152 HealthMeasures. NIH Toolbox. February 9,
2023. https://www.healthmeasures.net/exploremeasurement-systems/nih-toolbox.
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 LongTerm 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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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.
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.
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
156 Centers for Medicare & Medicaid Services.
Inpatient Rehabilitation Facility (IRF) Experience of
Care. October 12, 2022. https://www.cms.gov/
medicare/quality-initiatives-patient-assessmentinstruments/irf-quality-reporting/irf-experience-ofcare-.
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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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:
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• 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
158 Centers for Medicare and Medicaid Services.
Health Equity. https://www.cms.gov/pillar/healthequity. October 3, 2022.
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21003
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 CMSsupported benefits, services, and
coverage.
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.
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,
159 Centers for Medicare & Medicaid Services.
CMS Framework for Health Equity 2022–2032.
https://www.cms.gov/files/document/cmsframework-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-orderadvancing-racial-equity-and-support-forunderserved-communities-through-the-federalgovernment/.
161 Centers for Medicare & Medicaid Services.
What Is the CMS National Quality Strategy? https://
www.cms.gov/Medicare/Quality-Initiatives-PatientAssessment-Instruments/Value-Based-Programs/
CMS-Quality-Strategy.
162 Turner A. The Business Case for Racial Equity:
A Strategy for Growth. April 24, 2018. W.K. Kellogg
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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.
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.
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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
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/.
164 Agency for Healthcare Research and Quality.
2022 National Healthcare Quality and Disparities
Report. November 2022. https://www.ahrq.gov/
research/findings/nhqrdr/nhqdr22/.
165 Agency for Healthcare Research and Quality.
2022 National Healthcare Quality and Disparities
Report. November 2022. https://www.ahrq.gov/
research/findings/nhqrdr/nhqdr22/.
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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.
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
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 § 412.634(b)(1) for information
regarding the current policies for
reporting IRF QRP data.
166 World Health Organization. Social
Determinants of Health. https://www.who.int/
health-topics/social-determinants-ofhealth#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.
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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
We invite public comments on our
proposal.
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-draftspecs.pdf.
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G. Policies Regarding Public Display of
Measure Data for the IRF QRP
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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
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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
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21005
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 60day 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
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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.
TABLE 19—U.S. BUREAU OF LABOR AND STATISTICS’ MAY 2021 NATIONAL OCCUPATIONAL EMPLOYMENT AND WAGE
ESTIMATES
Occupation
code
Occupation title
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Registered Nurse (RN) ....................................................................................
Licensed Vocational Nurse (LVN) ...................................................................
Speech Language Pathologist (SLP) ..............................................................
Physical Therapist (PT) ...................................................................................
Occupational Therapist (OT) ...........................................................................
29–1141
29–2061
29–1127
29–1123
29–1122
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 ×
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 $220,697.60 for all
IRFs annually based on the proposed
removal of the Application of
Functional Assessment/Care Plan
measure.
169 U.S. Bureau of Labor Statistics’ (BLS) May
2021 National Occupational Employment and Wage
Estimates. https://www.bls.gov/oes/current/oes_
nat.htm.
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Mean hourly
wage
($/hr)
$39.78
24.93
41.26
44.67
43.02
Overhead and
fringe benefit
($/hr)
$39.78
24.93
41.26
44.67
43.02
Adjusted
hourly wage
($/hr)
$79.56
49.86
82.52
89.34
86.04
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 SelfCare 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
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for other quality measures under the IRF
QRP. Therefore, we believe that the
proposal to remove the Change in SelfCare 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 ×
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 × 3,896 hours)/
1,128 IRFs) per IRF annually, or
$252,110.16 ($64.71/hr × 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
Proposal
Change in
annual burden
hours
Change in Burden associated with proposed removal of the Application of Functional Assessment/Care Plan measure beginning with the FY 2025 IRF QRP .................................................
Change in Burden associated with proposed Patient/Resident COVID–19 Vaccine measure beginning with the FY 2026 IRF QRP ..............................................................................................
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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
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Change in
annual cost
¥$195.65
¥2,560
¥$220,697.60
+3.5
+223.50
+3,896
+252,110.16
1.2
27.85
1,336
31,412.56
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
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Change in
annual cost
¥2.3
Total Change in burden for the IRF QRP 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.
All IRFs
Change in
annual burden
hours
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
§ 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).
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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
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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%20
of%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
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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
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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
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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 budgetneutral 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 forprofit 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
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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, laborrelated 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.
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4. Impact of the Proposed Update to the
Outlier Threshold Amount
for IRFs in the Urban Middle Atlantic
Region.
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.
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 budgetneutral 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.
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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 budgetneutral 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
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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
§ 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
§ 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
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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 speechlanguage 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.
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TABLE 22—U.S. BUREAU OF LABOR AND STATISTICS’ MAY 2021 NATIONAL OCCUPATIONAL EMPLOYMENT AND WAGE
ESTIMATES
Registered Nurse (RN) ....................................................................................
Licensed Vocational Nurse (LVN) ...................................................................
Speech Language Pathologist (SLP) ..............................................................
Physical Therapist (PT) ...................................................................................
Occupational Therapist (OT) ...........................................................................
With 511,938 admissions from 1,128
IRFs annually, we estimate an annual
burden decrease of 2,560 fewer hours
(511,938 admissions × .005 hours) and
a decrease of $220,697.60 [2,560 hours
× $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 ($220,697.60/1,128 IRFs).
As discussed in section VIII.C.1.d. of
this proposed rule, we propose to
remove two additional measures from
the IRF QRP, the Change in Self-Care
and Change in Mobility measures,
beginning with assessments completed
on October 1, 2023. However, the data
items used in the calculation of this
measure are used for other payment and
quality reporting purposes, and
therefore there is no change in burden
associated with this proposal.
9. Effects of Requirements for the IRF
QRP Beginning With FY 2026
As discussed in section VIII.C.2.a. of
this proposed rule, we propose to adopt
Mean hourly
wage
($/hr)
Occupation
code
Occupation title
29–1141
29–2061
29–1127
29–1123
29–1122
Overhead and
fringe benefit
($/hr)
$39.78
24.93
41.26
44.67
43.02
a measure, the Patient/Resident COVID–
19 Vaccine measure, beginning with the
FY 2026 IRF QRP and this proposal
would result in an increase of 0.3
minutes of clinical staff time beginning
with discharge assessments completed
on October 1, 2024. Although the
proposed increase in burden will be
accounted for in a revised information
collection request under OMB control
number (0938–0842), we are providing
impact information. We estimate the
data element for this quality measure
would be completed by registered
nurses (50 percent of the time or 0.15
minutes) or by licensed practical and
vocational nurses (50 percent of the
time or 0.15 minutes). For the purposes
of calculating the costs associated with
the collection of information
requirements, we obtained mean hourly
wages for these staff from the U.S.
Bureau of Labor Statistics’ (BLS) May
2021 National Occupational
Employment and Wage Estimates.171 To
Adjusted
hourly wage
($/hr)
$39.78
24.93
41.26
44.67
43.02
$79.56
49.86
82.52
89.34
86.04
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 × 0.005 hours) and an
increase of $252,110.16 ($64.71/hr ×
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).
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
Proposal
Change in
annual burden
hours
Change in Burden associated with proposed removal of the Application of Functional Assessment/Care Plan measure beginning with the FY 2025 IRF QRP .................................................
Change in Burden associated with proposed Patient/Resident COVID–19 Vaccine measure beginning with the FY 2026 IRF QRP ..............................................................................................
¥$220,697.60
+3.5
+223.50
+3,896
+252,110.16
1.2
27.85
1,336
31,412.56
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.
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Change in
annual cost
¥2,560
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
21:49 Apr 06, 2023
Change in
annual burden
hours
¥$195.65
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
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annual cost
¥2.3
Total increase in burden for the IRF QRP 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.
All IRFs
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-todate 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
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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
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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 toppedout 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 crosssetting 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
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Sfmt 4702
21013
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 ×
$115.22). Therefore, we estimate that
the total cost of reviewing this
regulation is $21,085.26 ($345.66 × 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.
E:\FR\FM\07APP2.SGM
07APP2
21014
Federal Register / Vol. 88, No. 67 / Friday, April 7, 2023 / Proposed Rules
TABLE 24—ACCOUNTING STATEMENT: CLASSIFICATION OF ESTIMATED EXPENDITURE
Category
Change in Estimated Transfers from FY 2023
IRF PPS to FY 2024 IRF PPS.
Estimated Costs Associated with the FY 2025
and FY 2026 IRF QRP.
Estimated Costs Associated with Review Cost
for FY 2024 IRF PPS.
G. Conclusion
ddrumheller on DSK120RN23PROD with PROPOSALS2
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.
VerDate Sep<11>2014
21:49 Apr 06, 2023
Jkt 259001
Transfers
Annualized Monetized Transfers ......................
$335 million.
From Whom to Whom? ....................................
Federal Government to IRF Medicare Providers.
$31,412.56.
Annualized monetized cost in FY 2025 and
FY 2026 for IRFs due to new quality reporting program requirements.
Cost associated with regulatory review cost ....
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
1. The authority citation for part 412
continues to read as follows:
■
Authority: 42 U.S.C. 1302 and 1395hh.
2. Amend § 412.25 by revising
paragraph (c)(1) to read as follows:
■
PO 00000
Frm 00066
Fmt 4701
Sfmt 9990
$21,085.26.
§ 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
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]]>Agencies
[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]
[[Page 20949]]
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.
-----------------------------------------------------------------------
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 https://www.regulations.gov. Follow the ``Submit a
comment'' instructions.
2. By regular mail. You may mail written comments to the following
address ONLY: Centers for Medicare & Medicaid Services, Department of
Health and Human Services, Attention: CMS-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: https://www.regulations.gov. Follow the search instructions on that website to
view public comments. CMS will not post on Regulations.gov public
comments that make threats to individuals or institutions or suggest
that the individual will take actions to harm the individual. CMS
continues to encourage individuals not to submit duplicative comments.
We will post acceptable comments from multiple unique commenters even
if the content is identical or nearly identical to other comments.
Availability of Certain Information Through the Internet on the CMS
Website
The IRF prospective payment system (IRF PPS) Addenda along with
other supporting documents and tables referenced in this proposed rule
are available through the internet on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientRehabFacPPS.
We note that prior to 2020, each rule or notice issued under the
IRF PPS has included a detailed reiteration of the various regulatory
provisions that have affected the IRF PPS over the years. That
discussion, along with detailed background information for various
other aspects of the IRF PPS, is now available on the CMS website at
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientRehabFacPPS.
I. Executive Summary
A. Purpose
This 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
------------------------------------------------------------------------
Provision description Transfers/costs
------------------------------------------------------------------------
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.
------------------------------------------------------------------------
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
[[Page 20952]]
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.
---------------------------------------------------------------------------
\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 https://dx.doi.org/10.15585/mmwr.mm6905e1.
---------------------------------------------------------------------------
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).
---------------------------------------------------------------------------
\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).
---------------------------------------------------------------------------
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 https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientRehabFacPPS/Software.html. The Grouper software is also
embedded in the internet Quality Improvement and Evaluation System
(iQIES) User tool available in iQIES at https://www.cms.gov/medicare/quality-safety-oversight-general-information/iqies.
Once a Medicare Part A FFS patient is discharged, the IRF submits a
Medicare claim as a Health Insurance Portability and Accountability Act
of 1996 (HIPAA) (Pub. L. 104-191, enacted on August 21, 1996)--
compliant electronic claim or, if the Administrative Simplification
Compliance Act of 2002 (ASCA) (Pub. L. 107-105, enacted on December 27,
2002) permits, a paper claim (a UB-04 or a CMS-1450 as appropriate)
using the five-character CMG number and sends it to the appropriate
Medicare Administrative Contractor (MAC). In addition, once a MA
patient is discharged, in accordance with the Medicare Claims
Processing Manual, chapter 3, section 20.3 (Pub. 100-04), hospitals
(including IRFs) must submit an informational-only bill (type of bill
(TOB) 111), which includes Condition Code 04 to their MAC. This will
ensure that the MA days are included in the hospital's Supplemental
Security Income (SSI) ratio (used in calculating the IRF LIP
adjustment) for FY 2007 and beyond. Claims submitted to Medicare must
comply with both ASCA and HIPAA.
Section 3 of the ASCA amended section 1862(a) of the Act by adding
paragraph (22), which requires the Medicare program, subject to section
1862(h) of the Act, to deny payment under Part A or Part B for any
expenses for items or services for which a claim is submitted other
than in an electronic form specified by the Secretary. Section 1862(h)
of the Act, in turn, provides that the Secretary shall waive such
denial in situations in which there is no method available for the
submission of claims in an electronic form or the entity submitting the
claim is a small provider. In addition, the Secretary also has the
authority to waive such denial in such unusual cases as the Secretary
finds appropriate. For more information, see the ``Medicare Program;
Electronic Submission of Medicare Claims'' final rule (70 FR 71008).
Our instructions for the limited number of Medicare claims submitted on
paper are available at https://www.cms.gov/manuals/downloads/clm104c25.pdf.
Section 3 of the ASCA operates in the context of the administrative
simplification provisions of HIPAA, which include, among others, the
requirements for transaction standards and code sets codified in 45 CFR
part 160 and part 162, subparts A and I through R (generally known as
the Transactions Rule). The Transactions Rule requires covered
entities, including covered healthcare providers, to conduct covered
electronic transactions according to the applicable transaction
standards. (See the CMS program claim memoranda at https://www.cms.gov/ElectronicBillingEDITrans/ and listed in the addenda to the Medicare
Intermediary Manual, Part 3, section 3600).
The MAC processes the claim through its software system. This
software system includes pricing programming called the ``Pricer''
software. The Pricer software uses the CMG number, along with other
specific claim data elements and provider-specific data, to adjust the
IRF's prospective payment for interrupted stays, transfers, short
stays, and deaths, and then applies the applicable adjustments to
account for the IRF's wage index, percentage of low-income patients,
rural location, and outlier payments. For discharges occurring on or
after October 1, 2005, the IRF PPS payment also reflects the teaching
status adjustment that became effective as of FY 2006, as discussed in
the FY 2006 IRF PPS final rule (70 FR 47880).
D. Advancing Health Information Exchange
The Department of Health and Human Services (HHS) has a number of
initiatives designed to encourage and support the adoption of
interoperable health information technology and to promote nationwide
health information exchange to improve health care and patient access
to their 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 https://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
[[Page 20956]]
[GRAPHIC] [TIFF OMITTED] TP07AP23.000
[[Page 20957]]
[GRAPHIC] [TIFF OMITTED] TP07AP23.001
[[Page 20958]]
[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 https://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\ https://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
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[[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]]
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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 https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/MedicareProgramRatesStats/MarketBasketResearch.html in the zip
file titled ``Weight Calculations as described in the IPPS FY 2010
Proposed Rule.''
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]]
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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.
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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).
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\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.
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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.
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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\
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\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/.
\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.
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\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.
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We refer readers to https://www.cdc.gov/nhsn/nqf/ 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.
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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).
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\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.
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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).
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\88\ ``Expected functional capabilities'' is defined as the
predicted discharge function score.
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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.
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(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.
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\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.
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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 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.
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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.
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\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.
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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. https://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§ionNumber=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/.
\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/.
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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.
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\164\ Agency for Healthcare Research and Quality. 2022 National
Healthcare Quality and Disparities Report. November 2022. https://www.ahrq.gov/research/findings/nhqrdr/nhqdr22/.
\165\ Agency for Healthcare Research and Quality. 2022 National
Healthcare Quality and Disparities Report. November 2022. https://www.ahrq.gov/research/findings/nhqrdr/nhqdr22/.
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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.
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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
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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.
---------------------------------------------------------------------------
\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
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[GRAPHIC] [TIFF OMITTED] TP07AP23.009
BILLING CODE 4120-01-C
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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
