Medicare Program; FY 2025 Inpatient Psychiatric Facilities Prospective Payment System-Rate Update, 23146-23224 [2024-06764]
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DEPARTMENT OF HEALTH AND
HUMAN SERVICES
Centers for Medicare & Medicaid
Services
42 CFR Part 412
[CMS–1806–P]
RIN 0938–AV32
Medicare Program; FY 2025 Inpatient
Psychiatric Facilities Prospective
Payment System—Rate Update
Centers for Medicare &
Medicaid Services (CMS), Department
of Health and Human Services (HHS).
ACTION: Proposed rule.
AGENCY:
This rulemaking proposes to
update the prospective payment rates,
the outlier threshold, and the wage
index for Medicare inpatient hospital
services provided by Inpatient
Psychiatric Facilities (IPF), which
include psychiatric hospitals and
excluded psychiatric units of an acute
care hospital or critical access hospital.
This rulemaking also proposes to revise
the patient-level adjustment factors, the
Emergency Department adjustment, and
the payment amount for
electroconvulsive therapy. These
proposed changes would be effective for
IPF discharges occurring during the
fiscal year beginning October 1, 2024
through September 30, 2025 (FY 2025).
In addition, this proposed rule seeks to
adopt a new quality measure and
modify reporting requirements under
the IPF Quality Reporting Program
beginning with the FY 2027 payment
determination. Furthermore, this
proposed rule solicits comments
through Requests for Information (RFIs)
regarding potential future revisions to
the IPF PPS facility-level adjustments
and regarding the development of a
standardized IPF Patient Assessment
Instrument.
DATES: To be assured consideration,
comments must be received at one of
the addresses provided below, by May
28, 2024.
ADDRESSES: In commenting, please refer
to file code CMS–1806–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
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SUMMARY:
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Health and Human Services, Attention:
CMS–1806–P, P.O. Box 8010, Baltimore,
MD 21244–8010.
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–1806–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:
Nick Brock (410) 786–5148, for
information regarding the inpatient
psychiatric facilities prospective
payment system (IPF PPS).
Kaleigh Emerson (470) 890–4141, for
information regarding the inpatient
psychiatric facilities quality reporting
program (IPFQR).
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
commenter will take actions to harm an
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.
Plain Language Summary: In
accordance with 5 U.S.C. 553(b)(4), a
plain language summary of this rule
may be found at https://
www.regulations.gov/.
Availability of Certain Tables
Exclusively Through the Internet on the
CMS Website
Addendum A to this proposed rule
summarizes the proposed FY 2025
Inpatient Psychiatric Facilities
Prospective Payment System (IPF PPS)
payment rates, outlier threshold, cost of
living adjustment factors for Alaska and
Hawaii, national and upper limit cost-
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to-charge ratios, and adjustment factors.
In addition, Addendum B to this
proposed rule shows the complete
listing of ICD–10 Clinical Modification
and Procedure Coding System codes,
the FY 2025 IPF PPS comorbidity
adjustment, and electroconvulsive
therapy procedure codes. The A and B
Addenda are available on the CMS
website at: https://www.cms.gov/
Medicare/Medicare-Fee-for-ServicePayment/InpatientPsychFacilPPS/
tools.html.
Tables setting forth the FY 2025 Wage
Index for Urban Areas Based on CoreBased Statistical Area Labor Market
Areas, the FY 2025 Wage Index Based
on CBSA Labor Market Areas for Rural
Areas, and a county-level crosswalk of
the FY 2024 CBSA Labor Market Areas
to the FY 2025 CBSA Labor Market
Areas are available exclusively through
the internet, on the CMS website at
https://www.cms.gov/Medicare/
Medicare-Fee-for-Service-Payment/
IPFPPS/WageIndex.html.
I. Executive Summary
A. Purpose
This proposed rule would update the
prospective payment rates, the outlier
threshold, and the wage index for
Medicare inpatient hospital services
provided by Inpatient Psychiatric
Facilities (IPFs) for discharges occurring
during fiscal year (FY) 2025, (beginning
October 1, 2024 through September 30,
2025). We are proposing to adopt the
Core-Based Statistical Area (CBSA)
Labor Market Areas for the IPF PPS
wage index as defined in the Office of
Management and Budget (OMB)
Bulletin 23–01. In addition, this rule
includes a proposal to refine the patientlevel adjustment factors and increase
the payment amount for
electroconvulsive therapy (ECT)
treatments. We are not proposing
changes to the facility-level adjustment
factors for FY 2025; however, this
proposed rule presents the results of our
latest analysis and includes a request for
information relating to those results.
This rule also includes a clarification of
the eligibility criteria for an IPF to be
approved to file all-inclusive cost
reports. In addition, this proposed rule
includes a request for information
regarding the creation of a patient
assessment instrument (PAI) as
mandated by Section 4125 of the
Consolidated Appropriations Act
(CAA), 2023 (hereafter referred to as
CAA, 2023) (Pub. L. 117–328). Lastly,
this proposed rule discusses quality
measures and reporting requirements
under the Inpatient Psychiatric
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B. Summary of the Major Provisions
1. Inpatient Psychiatric Facilities
Prospective Payment System (IPF PPS)
For the IPF PPS, we are:
• Proposing to revise the patient-level
IPF PPS adjustment factors and increase
the ECT per treatment payment amount.
• Proposing to update the IPF PPS
wage index to use the CBSAs defined
within OMB Bulletin 23–01.
• Clarifying the eligibility criteria for
an IPF to be approved to file allinclusive cost reports. Only a
government-owned or tribally owned
facility will be able to satisfy these
criteria and will be eligible to file its
cost report using an all-inclusive rate or
no charge structure.
• Soliciting comments to inform
elements to be included in the IPF
patient assessment instrument, which
the CAA, 2023 requires the Centers for
Medicare & Medicaid Services (CMS) to
develop for FY 2028.
• Soliciting comments to inform
future refinements to the IPF PPS
facility-level adjustment factors.
• Making technical rate setting
updates: The IPF PPS payment rates are
adjusted annually for inflation, as well
as statutory and other policy factors.
This rule proposes to update:
++ The IPF PPS Federal per diem
base rate from $895.63 to $874.93.
++ The IPF PPS Federal per diem
base rate for providers who failed to
report quality data to $857.89.
++ The ECT payment per treatment
from $385.58 to $660.30.
++ The ECT payment per treatment
for providers who failed to report
quality data to $647.45.
++ The labor-related share from 78.7
percent to 78.8 percent.
++ The wage index budget neutrality
factor to 0.9998. This proposed rule
would apply a refinement
standardization factor of 0.9514.
++ The fixed dollar loss threshold
amount from $33,470 to $35,590, to
maintain estimated outlier payments at
Provision Description
FY 2025 IPF PPS payment update
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A. Overview of the Legislative
Requirements of the IPF PPS
Section 124 of the Medicare,
Medicaid, and State Children’s Health
Insurance Program Balanced Budget
Refinement Act of 1999 (BBRA) (Pub. L.
106–113) required the establishment
and implementation of an IPF PPS.
Specifically, section 124 of the BBRA
mandated that the Secretary of the
Department of Health and Human
Services (the Secretary) develop a per
diem payment perspective system (PPS)
for inpatient hospital services furnished
in psychiatric hospitals and excluded
psychiatric units including an adequate
patient classification system that reflects
the differences in patient resource use
and costs among psychiatric hospitals
and excluded psychiatric units.
‘‘Excluded psychiatric unit’’ means a
psychiatric unit of an acute care
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hospital or of a Critical Access Hospital
(CAH), which is excluded from payment
under the Inpatient Prospective
Payment System (IPPS) or CAH
payment system, respectively. These
excluded psychiatric units will be paid
under the IPF PPS.
Section 405(g)(2) of the Medicare
Prescription Drug, Improvement, and
Modernization Act of 2003 (MMA) (Pub.
L. 108–173) extended the IPF PPS to
psychiatric distinct part units of CAHs.
Sections 3401(f) and 10322 of the
Patient Protection and Affordable Care
Act (Pub. L. 111–148) as amended by
section 10319(e) of that Act and by
section 1105(d) of the Health Care and
Education Reconciliation Act of 2010
(Pub. L. 111–152) (hereafter referred to
jointly as ‘‘the Affordable Care Act’’)
added subsection (s) to section 1886 of
the Act.
Section 1886(s)(1) of the Act titled
‘‘Reference to Establishment and
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2. Inpatient Psychiatric Facilities
Quality Reporting (IPFQR) Program
For the IPFQR Program, we are
proposing to:
• Adopt the 30-Day RiskStandardized All-Cause Emergency
Department (ED) Visit Following an IPF
Discharge measure beginning with the
FY 2027 payment determination; and
• Modify reporting requirements to
require IPFs to submit patient-level data
on a quarterly basis.
We also refer readers to our RFI in
which we solicit comments to inform
elements to be included in the IPF
patient assessment instrument, which
the CAA, 2023 requires the Centers for
Medicare & Medicaid Services (CMS) to
develop and implement for Rate Year
(RY) 2028.
C. Summary of Impacts
Total Transfers & Cost Reductions
The overall economic impact of this proposed
rule is an estimated $70 million in increased
payments to IPFs during FY 2025.
The overall economic impact of the IPFQR
Program proposals in this proposed rule is an
estimated increase of 800 hours of
information collection burden resulting in a
cost increase of $41,696.
FY2025 IPFQR Program update
II. Background
2 percent of total estimated aggregate
IPF PPS payments.
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Implementation of System,’’ refers to
section 124 of the BBRA, which relates
to the establishment of the IPF PPS.
Section 1886(s)(2)(A)(i) of the Act
requires the application of the
productivity adjustment described in
section 1886(b)(3)(B)(xi)(II) of the Act to
the IPF PPS for the rate year (RY)
beginning in 2012 (that is, a RY that
coincides with a FY) and each
subsequent RY.
Section 1886(s)(2)(A)(ii) of the Act
required the application of an ‘‘other
adjustment’’ that reduced any update to
an IPF PPS base rate by a percentage
point amount specified in section
1886(s)(3) of the Act for the RY
beginning in 2010 through the RY
beginning in 2019. As noted in the FY
2020 Inpatient Psychiatric Facilities
Prospective Payment System and
Quality Reporting Updates for fiscal
year Beginning October 1, 2019 final
rule, for the RY beginning in 2019,
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Facilities Quality Reporting (IPFQR)
Program.
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section 1886(s)(3)(E) of the Act required
that the other adjustment reduction be
equal to 0.75 percentage point; that was
the final year the statute required the
application of this adjustment. Because
FY 2021 was a RY beginning in 2020,
FY 2021 was the first year section
1886(s)(2)(A)(ii) of the Act did not apply
since its enactment.
Sections 1886(s)(4)(A) through (D) of
the Act require that for RY 2014 and
each subsequent RY, IPFs that fail to
report required quality data with respect
to such a RY will have their annual
update to a standard Federal rate for
discharges reduced by 2.0 percentage
points. This may result in an annual
update being less than 0.0 for a RY, and
may result in payment rates for the
upcoming RY being less than such
payment rates for the preceding RY.
Any reduction for failure to report
required quality data will apply only to
the RY involved, and the Secretary will
not consider such reduction in
computing the payment amount for a
subsequent RY. Additional information
about the specifics of the current IPFQR
Program is available in the FY 2020
Inpatient Psychiatric Facilities
Prospective Payment System and
Quality Reporting Updates for fiscal
year Beginning October 1, 2019 (FY
2020) final rule (84 FR 38459 through
38468).
Section 4125 of the Consolidated
Appropriations Act, 2023 (CAA, 2023)
(Pub. L. 117–328), which amended
section 1886(s) of the Act, requires CMS
to revise the Medicare prospective
payment system for psychiatric
hospitals and psychiatric units.
Specifically, section 4125(a) of the CAA,
2023 added section 1886(s)(5)(A) of the
Act to require the Secretary to collect
data and information, as the Secretary
determines appropriate, to revise
payments under the IPF PPS. CMS
discussed this data collection last year
in the FY 2024 IPF PPS final rule, as
CMS was required to begin collecting
this data and information not later than
October 1, 2024. As discussed in that
rule, the Agency has already been
collecting data and information
consistent with the types set forth in the
CAA, 2023 as part of our extensive and
years-long analyses and consideration of
potential payment system refinements.
We refer readers to the FY 2024
Inpatient Psychiatric Facilities
Prospective Payment System—Rate
Update (FY 2024 IPF PPS) final rule (88
FR 51095 through 51098) where we
discussed existing data collection and
requested information to inform future
IPF PPS revisions.
In addition, section 1886(s)(5)(D) of
the Act, as added by section 4125(a) of
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the CAA, 2023 requires that the
Secretary implement revisions to the
methodology for determining the
payment rates under the IPF PPS for
psychiatric hospitals and psychiatric
units, effective for RY 2025 (FY 2025).
The revisions may be based on a review
of the data and information collected
under section 1886(s)(5)(A) of the Act.
As discussed in section III.C of this FY
2025 IPF PPS proposed rule, we are
proposing revisions to the IPF PPS
patient-level adjustment factors based
on a review of cost and claims data.
Section 4125(b) of the CAA, 2023
amended section 1886(s)(4) of the Act
by inserting a new subparagraph (E),
which requires IPFs participating in the
IPFQR Program to collect and submit to
the Secretary standardized patient
assessment data, using a standardized
patient assessment instrument, for RY
2028 (FY 2028) and each subsequent
rate year. IPFs must submit such data
with respect to at least the admission
and discharge of an individual, or more
frequently as the Secretary determines
appropriate. For IPFs to meet this new
data collection and reporting
requirement for RY 2028 and each
subsequent rate year, the Secretary must
implement a standardized patient
assessment instrument that collects data
with respect to the following categories:
functional status; cognitive function and
mental status; special services,
treatments, and interventions; medical
conditions and comorbidities;
impairments; and other categories as
determined appropriate by the
Secretary. This patient assessment
instrument must enable comparison of
such patient assessment data that IPFs
submit across all such IPFs to which
such data are applicable.
Section 4125(b) of the CAA, 2023
further amended section 1886(s) of the
Act by adding a new subparagraph (6)
that requires the Secretary to implement
revisions to the methodology for
determining the payment rates for
psychiatric hospitals and psychiatric
units (that is, payment rates under the
IPF PPS), effective for RY 2031 (FY
2031), as the Secretary determines to be
appropriate, to take into account the
patient assessment data described in
paragraph (4)(E)(ii).
To implement and periodically
update the IPF PPS, we have published
various proposed and final rules and
notices in the Federal Register. For
more information regarding these
documents, we refer readers to the CMS
website at https://www.cms.gov/
Medicare/Medicare-Fee-for-ServicePayment/InpatientPsychFacilPPS/
index.html?redirect=/
InpatientPsychFacilPPS/.
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B. Overview of the IPF PPS
On November 15, 2004, we published
the RY 2005 IPF PPS final rule in the
Federal Register (69 FR 66922). The RY
2005 IPF PPS final rule established the
IPF PPS, as required by section 124 of
the BBRA and codified at 42 CFR part
412, subpart N. The RY 2005 IPF PPS
final rule set forth the Federal per diem
base rate for the implementation year
(the 18-month period from January 1,
2005 through June 30, 2006) and
provided payment for the inpatient
operating and capital costs to IPFs for
covered psychiatric services they
furnish (that is, routine, ancillary, and
capital costs, but not costs of approved
educational activities, bad debts, and
other services or items that are outside
the scope of the IPF PPS). Covered
psychiatric services include services for
which benefits are provided under the
fee-for-service Part A (Hospital
Insurance Program) of the Medicare
program.
The IPF PPS established the Federal
per diem base rate for each patient day
in an IPF derived from the national
average daily routine operating,
ancillary, and capital costs in IPFs in FY
2002. The average per diem cost was
updated to the midpoint of the first year
under the IPF PPS, standardized to
account for the overall positive effects of
the IPF PPS payment adjustments, and
adjusted for budget neutrality.
The Federal per diem payment under
the IPF PPS is comprised of the Federal
per diem base rate described previously
and certain patient- and facility-level
payment adjustments for characteristics
that were found in the regression
analysis to be associated with
statistically significant per diem cost
differences, with statistical significance
defined as p less than 0.05. A complete
discussion of the regression analysis
that established the IPF PPS adjustment
factors can be found in the RY 2005 IPF
PPS final rule (69 FR 66933 through
66936).
The patient-level adjustments include
age, Diagnosis-Related Group (DRG)
assignment, and comorbidities, as well
as adjustments to reflect higher per
diem costs at the beginning of a
patient’s IPF stay and lower costs for
later days of the stay. Facility-level
adjustments include adjustments for the
IPF’s wage index, rural location,
teaching status, a cost-of-living
adjustment for IPFs located in Alaska
and Hawaii, and an adjustment for the
presence of a qualifying emergency
department (ED).
The IPF PPS provides additional
payment policies for outlier cases,
interrupted stays, and a per treatment
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payment for patients who undergo ECT.
During the IPF PPS mandatory 3-year
transition period, stop-loss payments
were also provided; however, since the
transition ended as of January 1, 2008,
these payments are no longer available.
C. Annual Requirements for Updating
the IPF PPS
Section 124 of the BBRA did not
specify an annual rate update strategy
for the IPF PPS and was broadly written
to give the Secretary discretion in
establishing an update methodology.
Therefore, in the RY 2005 IPF PPS final
rule, we implemented the IPF PPS using
the following update strategy:
• Calculate the final Federal per diem
base rate to be budget neutral for the 18month period of January 1, 2005
through June 30, 2006.
• Use a July 1 through June 30 annual
update cycle.
• Allow the IPF PPS first update to be
effective for discharges on or after July
1, 2006 through June 30, 2007.
The RY 2005 final rule (69 FR 66922)
implemented the IPF PPS. In developing
the IPF PPS, and to ensure that the IPF
PPS can account adequately for each
IPF’s case-mix, we performed an
extensive regression analysis of the
relationship between the per diem costs
and certain patient and facility
characteristics to determine those
characteristics associated with
statistically significant cost differences
on a per diem basis. That regression
analysis is described in detail in our RY
2004 IPF proposed rule (68 FR 66923;
66928 through 66933) and our RY 2005
IPF final rule (69 FR 66933 through
66960). For characteristics with
statistically significant cost differences,
we used the regression coefficients of
those variables to determine the size of
the corresponding payment
adjustments.
In the RY 2005 IPF final rule, we
explained the reasons for delaying an
update to the adjustment factors,
derived from the regression analysis,
including waiting until we have IPF PPS
data that yields as much information as
possible regarding the patient-level
characteristics of the population that
each IPF serves. We indicated that we
did not intend to update the regression
analysis and the patient-level and
facility-level adjustments until we
complete that analysis. Until that
analysis is complete, we stated our
intention to publish a notice in the
Federal Register each spring to update
the IPF PPS (69 FR 66966).
On May 6, 2011, we published a final
rule in the Federal Register titled,
‘‘Inpatient Psychiatric Facilities
Prospective Payment System—Update
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for Rate Year Beginning July 1, 2011 (RY
2012)’’ (76 FR 26432), which changed
the payment rate update period to a RY
that coincides with a FY update.
Therefore, final rules are now published
in the Federal Register in the summer
to be effective on October 1st. When
proposing changes in IPF payment
policy, a proposed rule is issued in the
spring, and the final rule in the summer
to be effective on October 1st. For a
detailed list of updates to the IPF PPS,
we refer readers to our regulations at 42
CFR 412.428. Beginning October 1,
2012, we finalized that we would refer
to the 12-month period from October 1
through September 30 as a ‘‘fiscal year’’
(FY) rather than a RY (76 FR 26435).
Therefore, in this final rule we refer to
rules that took effect after RY 2012 by
the FY, rather than the RY, in which
they took effect.
The most recent IPF PPS annual
update was published in a final rule on
August 2, 2023 in the Federal Register
titled, ‘‘Medicare Program; FY 2024
Inpatient Psychiatric Facilities
Prospective Payment System—Rate
Update’’ (88 FR 51054), which updated
the IPF PPS payment rates for FY 2024.
That final rule updated the IPF PPS
Federal per diem base rates that were
published in the FY 2023 IPF PPS Rate
Update final rule (87 FR 46846) in
accordance with our established
policies.
III. Provisions of the Proposed
Regulations
A. Proposed FY 2025 Market Basket
Update and Productivity Adjustment for
the IPF PPS
1. Background
Originally, the input price index used
to develop the IPF PPS was the
Excluded Hospital with Capital market
basket. This market basket was based on
1997 Medicare cost reports for
Medicare-participating inpatient
rehabilitation facilities (IRFs), IPFs,
long-term care hospitals (LTCHs),
cancer hospitals, and children’s
hospitals. Although ‘‘market basket’’
technically describes the mix of goods
and services used in providing health
care at a given point in time, this term
is also commonly used to denote the
input price index (that is, cost category
weights and price proxies) derived from
that market basket. Accordingly, the
term ‘‘market basket,’’ as used in this
document, refers to an input price
index.
Since the IPF PPS inception, the
market basket used to update IPF PPS
payments has been rebased and revised
to reflect more recent data on IPF cost
structures. We last rebased and revised
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the IPF market basket in the FY 2024
IPF PPS rule, where we adopted a 2021based IPF market basket, using Medicare
cost report data for both Medicare
participating freestanding psychiatric
hospitals and psychiatric units. We refer
readers to the FY 2024 IPF PPS final
rule for a detailed discussion of the
2021-based IPF PPS market basket and
its development (88 FR 51057 through
51081). References to the historical
market baskets used to update IPF PPS
payments are listed in the FY 2016 IPF
PPS final rule (80 FR 46656).
2. Proposed FY 2025 IPF Market Basket
Update
For FY 2025 (beginning October 1,
2024 and ending September 30, 2025),
we are proposing to update the IPF PPS
payments by a market basket increase
factor with a productivity adjustment as
required by section 1886(s)(2)(A)(i) of
the Act. Consistent with historical
practice, we are proposing to estimate
the market basket update for the IPF
PPS based on the most recent forecast
available at the time of rulemaking from
IHS Global Inc. (IGI). IGI is a nationally
recognized economic and financial
forecasting firm with which CMS
contracts to forecast the components of
the market baskets and productivity
adjustment. For the proposed rule,
based on IGI’s fourth quarter 2023
forecast with historical data through the
third quarter of 2023, the 2021-based
IPF market basket increase factor for FY
2025 is 3.1 percent.
Section 1886(s)(2)(A)(i) of the Act
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 (MFP) (as projected by the
Secretary for the 10-year period ending
with the applicable FY, year, cost
reporting period, or other annual
period) (the ‘‘productivity adjustment’’).
The United States Department of Labor’s
Bureau of Labor Statistics (BLS)
publishes the official measures of
productivity for the United States
economy. We note that previously the
productivity measure referenced in
section 1886(b)(3)(B)(xi)(II) of the Act
was published by BLS as private
nonfarm business MFP. Beginning with
the November 18, 2021 release of
productivity data, BLS replaced the
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term ‘‘multifactor productivity’’ with
‘‘total factor productivity’’ (TFP). BLS
noted that this is a change in
terminology only and will not affect the
data or methodology. As a result of the
BLS name change, the productivity
measure referenced in section
1886(b)(3)(B)(xi)(II) of the Act is now
published by BLS as private nonfarm
business TFP. However, as mentioned
previously, the data and methods are
unchanged. We refer readers to
www.bls.gov for the BLS historical
published TFP data. A complete
description of IGI’s TFP projection
methodology is available on the CMS
website at https://www.cms.gov/dataresearch/statistics-trends-and-reports/
medicare-program-rates-statistics/
market-basket-research-andinformation. In addition, in the FY 2022
IPF final rule (86 FR 42611), we noted
that effective with FY 2022 and forward,
CMS changed the name of this
adjustment to refer to it as the
productivity adjustment rather than the
MFP adjustment.
Section 1886(s)(2)(A)(i) of the Act
requires the application of the
productivity adjustment described in
section 1886(b)(3)(B)(xi)(II) of the Act to
the IPF PPS for the RY beginning in
2012 (a RY that coincides with a FY)
and each subsequent RY. For this
proposed rule, based on IGI’s fourth
quarter 2023 forecast, the proposed
productivity adjustment for FY 2025
(the 10-year moving average of TFP for
the period ending FY 2025) is projected
to be 0.4 percent. Accordingly, we are
proposing to reduce the 3.1 percent IPF
market basket increase by this 0.4
percentage point productivity
adjustment, as mandated by the Act.
This results in a proposed FY 2025 IPF
PPS payment rate update of 2.7 percent
(3.1¥0.4 = 2.7). We are also proposing
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that if more recent data become
available, we would use such data, if
appropriate, to determine the FY 2025
IPF market basket increase and
productivity adjustment for the final
rule.
We solicit comment on the proposed
IPF market basket increase and
productivity adjustment for FY 2025.
3. Proposed FY 2025 IPF Labor-Related
Share
Due to variations in geographic wage
levels and other labor-related costs, we
believe that payment rates under the IPF
PPS should continue to be adjusted by
a geographic wage index, which would
apply to the labor-related portion of the
Federal per diem base rate (hereafter
referred to as the labor-related share).
The labor-related share is determined by
identifying the national average
proportion of total costs that are related
to, influenced by, or vary with the local
labor market. We are proposing to
continue to classify a cost category as
labor-related if the costs are laborintensive and vary with the local labor
market.
Based on our definition of the laborrelated share and the cost categories in
the 2021-based IPF market basket, we
are proposing to continue 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: LaborRelated Services; and a portion of the
Capital-Related relative importance
from the 2021-based IPF market basket.
For more details regarding the
methodology for determining specific
cost categories for inclusion in the
labor-related share based on the 2021-
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based IPF market basket, we refer
readers to the FY 2024 IPF PPS final
rule (88 FR 51078 through 51081).
The relative importance reflects the
different rates of price change for these
cost categories between the base year
(FY 2021) and FY 2025. Based on IGI’s
fourth quarter 2023 forecast of the 2021based IPF market basket, the sum of the
FY 2025 relative importance moving
average 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 is 75.7
percent. We are proposing, consistent
with prior rulemaking, that the portion
of Capital-Related costs that are
influenced by the local labor market is
46 percent. Since the relative
importance for Capital-Related costs is
6.8 percent of the 2021-based IPF
market basket for FY 2025, we are
proposing to take 46 percent of 6.8
percent to determine a labor-related
share of Capital-Related costs for FY
2025 of 3.1 percent. Therefore, we are
proposing a total labor-related share for
FY 2025 of 78.8 percent (the sum of 75.7
percent for the labor-related share of
operating costs and 3.1 percent for the
labor-related share of Capital-Related
costs). We are also proposing that if
more recent data become available, we
would use such data, if appropriate, to
determine the FY 2025 labor-related
share for the final rule. For more
information on the labor-related share
and its calculation, we refer readers to
the FY 2024 IPF PPS final rule (88 FR
51078 through 51081).
Table 1 shows the proposed FY 2025
labor-related share and the final FY
2024 labor-related share using the 2021based IPF market basket relative
importance.
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TABLE 1: FY 2025 Proposed IPF Labor-Related Share and FY 2024 IPF Labor-Related Share
Wages and Salaries
Relative importance,
proposed labor-related share
FY 2025 1
53.6
Relative importance,
labor-related share FY
2024 2
53.4
Employee Benefits
14.1
14.2
Professional Fees: Labor-Related
4.7
4.7
Administrative and Facilities Support Services
0.6
0.6
Installation, Maintenance and Repair Services
1.2
1.2
All Other Labor-Related Services
1.5
1.5
75.7
75.6
3.1
3.1
78.8
78.7
Subtotal
Labor-related portion of Capital-Related (.46)
Total Labor-Related Share
Based on the 4th quarter 2023 IHS Global Inc. forecast of the 2021-based IPF market basket.
Based on the 2nd quarter 2023 IHS Global Inc. forecast of the 2021-based IPF market basket.
We solicit comment on the proposed
labor-related share for FY 2025.
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B. Proposed Revisions to the IPF PPS
Rates for FY Beginning October 1, 2024
The IPF PPS is based on a
standardized Federal per diem base rate
calculated from the IPF average per
diem costs and adjusted for budget
neutrality in the implementation year.
The Federal per diem base rate is used
as the standard payment per day under
the IPF PPS and is adjusted by the
patient-level and facility-level
adjustments that are applicable to the
IPF stay. A detailed explanation of how
we calculated the average per diem cost
appears in the RY 2005 IPF PPS final
rule (69 FR 66926).
1. Determining the Standardized Budget
Neutral Federal per Diem Base Rate
Section 124(a)(1) of the BBRA
required that we implement the IPF PPS
in a budget neutral manner. In other
words, the amount of total payments
under the IPF PPS, including any
payment adjustments, must be projected
to be equal to the amount of total
payments that would have been made if
the IPF PPS were not implemented.
Therefore, we calculated the budget
neutrality factor by setting the total
estimated IPF PPS payments to be equal
to the total estimated payments that
would have been made under the Tax
Equity and Fiscal Responsibility Act of
1982 (TEFRA) (Pub. L. 97–248)
methodology had the IPF PPS not been
implemented. A step-by-step
description of the methodology used to
estimate payments under the TEFRA
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payment system appears in the RY 2005
IPF PPS final rule (69 FR 66926).
Under the IPF PPS methodology, we
calculated the final Federal per diem
base rate to be budget neutral during the
IPF PPS implementation period (that is,
the 18-month period from January 1,
2005 through June 30, 2006) using a July
1 update cycle. We updated the average
cost per day to the midpoint of the IPF
PPS implementation period (October 1,
2005), and this amount was used in the
payment model to establish the budget
neutrality adjustment.
Next, we standardized the IPF PPS
Federal per diem base rate to account
for the overall positive effects of the IPF
PPS payment adjustment factors by
dividing total estimated payments under
the TEFRA payment system by
estimated payments under the IPF PPS.
The information concerning this
standardization can be found in the RY
2005 IPF PPS final rule (69 FR 66932)
and the RY 2006 IPF PPS final rule (71
FR 27045). We then reduced the
standardized Federal per diem base rate
to account for the outlier policy, the
stop loss provision, and anticipated
behavioral changes. A complete
discussion of how we calculated each
component of the budget neutrality
adjustment appears in the RY 2005 IPF
PPS final rule (69 FR 66932 through
66933) and in the RY 2007 IPF PPS final
rule (71 FR 27044 through 27046). The
final standardized budget neutral
Federal per diem base rate established
for cost reporting periods beginning on
or after January 1, 2005 was calculated
to be $575.95.
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The Federal per diem base rate has
been updated in accordance with
applicable statutory requirements and
42 CFR 412.428 through publication of
annual notices or proposed and final
rules. A detailed discussion on the
standardized budget neutral Federal per
diem base rate and the ECT payment per
treatment appears in the FY 2014 IPF
PPS update notice (78 FR 46738 through
46740). These documents are available
on the CMS website at https://
www.cms.gov/Medicare/Medicare-Feefor-Service-Payment/
InpatientPsychFacilPPS/.
As discussed in section III.B.2 of this
proposed rule, we are proposing to
revise the patient-level adjustment
factors and increase the ECT payment
amount for FY 2025. Section
1866(s)(5)(D)(iii) of the Act, as added by
section 4125(a) of the CAA, 2023,
requires that revisions to the IPF PPS
adjustment factors must be made
budget-neutrally. Therefore, as
discussed in section III.F of this
proposed rule, we are proposing to
apply a standardization factor to the FY
2025 base rate that takes these
refinements into account to keep total
IPF PPS payments budget neutral.
2. Proposed Increase in the
Electroconvulsive Therapy (ECT)
Payment per Treatment
a. Background
In the RY 2005 IPF PPS final rule (69
FR 66951), we analyzed the costs of IPF
stays that included ECT treatment using
the FY 2002 MedPAR data. based on
comments we received on the RY 2005
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2.
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IPF PPS proposed rule. Consistent with
the comments we received about ECT,
our analysis and review indicated that
cases with ECT treatment are
substantially more costly than cases
without ECT treatment. Based on this
analysis, in that final rule we finalized
an additional payment for each ECT
treatment furnished during the IPF stay.
This ECT payment per treatment is
made in addition to the per diem and
outlier payments under the IPF PPS. To
receive the payment per ECT treatment,
IPFs must indicate on their claims the
revenue code and procedure code for
ECT (Rev Code 901; procedure code
90870) and the number of units of ECT,
that is, the number of ECT treatments
the patient received during the IPF stay.
To establish the ECT per treatment
payment, we used the pre-scaled and
pre-adjusted median cost for procedure
code 90870 developed for the Hospital
Outpatient Prospective Payment System
(OPPS), based on hospital claims data.
We explained in the RY 2005 IPF PPS
final rule that we used OPPS data
because after a careful review and
analysis of IPF claims, we were unable
to separate out the cost of a single ECT
treatment (69 FR 66922). We used the
unadjusted hospital claims data under
the OPPS because we did not want the
ECT payment under the IPF PPS to be
affected by factors that are relevant to
OPPS, but not specifically applicable to
IPFs. The median cost was then
standardized and adjusted for budget
neutrality. We also adjusted the ECT
rate for wage differences in the same
manner that we adjust the per diem rate.
Since the ECT payment rate was
established in the RY 2005 IPF PPS rule,
it has been updated annually by
application of each year’s market basket,
productivity adjustment, and wage
index budget neutrality factor to the
previous year’s ECT payment rate
(referred to as our ‘‘standard
methodology’’ in this section). While
the ECT payment rate has been updated
each year by these factors, we have not
recalculated the ECT payment per
treatment based on more recent cost
data since the establishment of the IPF
PPS.
b. Proposed Increase to the
Electroconvulsive Therapy Payment per
Treatment
For this FY 2025 IPF PPS proposed
rule, we analyzed data in both the IPF
PPS and the OPPS. In the IPF PPS
setting, our analysis of recent IPF PPS
data indicates that IPF costs have
increased for stays that include ECT
treatments. As discussed in the next
paragraph, our analysis of these costs
leads us to consider whether the current
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payment per treatment for ECT is
aligned with the additional costs
associated with stays that include ECT
treatments. We began by analyzing IPF
stays with ECT treatment using the CY
2022 Medicare Provider and Analysis
Review (MedPAR) data. IPF stays with
ECT treatment comprised about 1.7
percent of all stays, which is a decrease
from the FY 2002 MedPAR data
discussed in the RY 2005 IPF PPS final
rule, where stays with ECT treatment
were 6.0 percent of all IPF stays. A total
of 288 IPF facilities had stays with ECT
treatment in 2022, with an average 6.7
units of ECT per stay. We compared the
total cost for stays with and without
ECT treatment, and found that IPF stays
with ECT treatment were approximately
three times more costly than IPF stays
without ECT treatment ($44,687.50 per
stay vs. $15,432.30 per stay). Most of the
variance in cost was due to differences
in the IPF length of stay (LOS) (28.00
days for stays with ECT treatment vs.
13.43 days for stays without ECT
treatment). We note that the IPF PPS
makes additional per diem payments for
longer lengths of stay, which makes the
total payment larger for a longer stay.
However, we also observed that there
are differences in the per-day cost for
stays with and without ECT. We
calculated the average cost per day for
stays with and without ECT treatment
and found that stays with ECT treatment
have an average cost per day of
$1,595.76, while stays without ECT
treatment have an average cost per day
of $1,149.51.
Furthermore, as we discuss in section
III.C.3.d.(2) of this proposed rule, our
latest regression analysis includes a
control variable to account for the
presence of ECT during an IPF stay.
That control variable indicates that,
holding all other patient-level and
facility-level factors constant, there is a
statistically significant increase in cost
per day for IPF stays that include ECT,
further demonstrating that resource use
is higher for IPF stays with ECT than
those without ECT. As we previously
noted in the RY 2005 IPF PPS final rule
(69 FR 66922), IPF claims and cost data
are not sufficiently granular to identify
the per-treatment cost of ECT.
Therefore, we examined the difference
in ancillary costs for IPF stays with and
without ECT treatment. In the CY 2022
MedPAR data, the ancillary costs per
IPF stay with ECT treatment were
$7,116.85 higher than ancillary costs per
IPF stay without ECT treatment. The
ancillary costs were calculated as
follows: for each ancillary department
(for example, drugs or labs), the charges
were multiplied by the department-level
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CCR, and those department-level costs
were summed across departments for
each stay. The average ancillary costs
per stay were calculated accordingly for
stays with and without ECT treatment,
revealing that average ancillary costs per
day are three times higher for stays with
ECT treatment: $99.36 for stays without
ECT treatment versus $301.77 for stays
with ECT treatment. Accounting for
differences in length of stay between
stays with and without ECT, the average
additional ancillary cost per ECT unit
was approximately $849.72.
Application of our standard
methodology for updating the ECT
payment would result in an FY 2025
payment of $377.54 per ECT treatment
(based on the FY 2024 ECT payment
amount of $385.58, increased by the
market basket update of 2.7 percent and
reduced by the FY 2025 wage index
budget neutrality factor of 0.9998 and a
refinement standardization factor of
0.9536, which is the standardization
factor that would account for all other
proposed refinements without
increasing the ECT per treatment). As
we noted above, this ECT payment
would be added to the per diem and any
applicable outlier payments for the
entire stay. CMS considered this rate in
proposing to adjust the ECT per
treatment rate. However, the analysis of
ancillary costs for IPF stays with ECT
treatment suggested that a further
increase to the current ECT payment
amount per treatment could better align
IPF PPS payments with the increased
costs of furnishing ECT. The ancillary
cost data show that costs for furnishing
ECT have risen by a factor greater than
the standard methodology for updating
the rate would adjust for.
It continues to be the case that, as we
discussed in the RY 2005 IPF PPS final
rule, current IPF cost and claims data
are not sufficiently granular to identify
the per-treatment cost of ECT. We
believe that using the costs in the OPPS
setting are the most accurate for
purposes of updating the ECT per
treatment rate because we believe this
treatment requires comparable resources
when performed in outpatient and
inpatient settings. Thus, we analyzed
the most recent OPPS cost information
to consider changes to the ECT payment
per treatment for FY 2025.
The original methodology for
determining the ECT payment per
treatment was based on the median cost
for procedure code 90870 developed for
the OPPS, as discussed in the RY 2005
IPF PPS final rule (69 FR 66951). Since
that time, the OPPS has adopted certain
changes to its methodology for
calculating costs. In the CY 2013 OPPS/
ASC final rule with comment period (77
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FR 68259 through 68270), CMS
finalized a methodology for developing
the relative payment weights for
Ambulatory Payment Classifications
using geometric mean costs instead of
median costs. We explained that
geometric means better capture the
range of costs associated with providing
services, including those cases where
very efficient hospitals have provided
services at much lower costs. While
medians and geometric means both
capture the impact of uniform changes,
that is, those changes that influence all
providers, only geometric means
capture cost changes that are introduced
slowly into the system on a case-by-case
or hospital-by-hospital basis, allowing
us to detect changes in the cost of
services earlier.
We believe the rationale for using
geometric mean cost in the OPPS setting
as the underpinning methodology for
establishing payments applies equally to
the costs of providing ECT on a per
treatment basis under the IPF PPS.
Therefore, in considering changes for
the IPF PPS ECT payment per treatment
for FY 2025, we compared the costs
observed in the IPF setting to the
geometric mean cost for an ECT
treatment posted as part of the CY 2024
OPPS/ASC update, which is based on
CY 2022 outpatient hospital claims.
Although we are proposing to increase
the ECT payment with reference to the
CY 2024 OPPS ECT geometric mean cost
for FY 2025, we are not proposing to
adopt the OPPS rate (which is distinct
from the geometric mean cost) for the
ECT payment per treatment for FY 2025
because the final OPPS rates include
policy decisions and payment rate
updates that are specific to the OPPS.
We intend to continue to monitor the
costs associated with ECT treatment and
may propose adjustments in the future
as needed.
The pre-scaled and pre-adjusted CY
2024 OPPS geometric mean cost for ECT
is $675.93. Comparatively, the FY 2024
IPF ECT payment rate was $385.58 (88
FR 51054). As discussed in the prior
paragraphs, our analysis of updated
ancillary cost data indicates that the IPF
PPS ECT payment rate per treatment,
when updated according to the standard
methodology alone, has not kept pace
with the cost of furnishing the treatment
in the IPF setting. As we stated
previously, we believe this treatment
requires comparable resources when
performed in outpatient and inpatient
settings. Therefore, we are proposing to
use the pre-scaled and pre-adjusted CY
2024 OPPS geometric mean cost of
$675.93 as the basis for the IPF PPS ECT
payment per treatment in FY 2025, as
discussed below. We are proposing to
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update $675.93 by the FY 2025 IPF PPS
payment rate update of 2.7 percent (3.1
percent IPF market basket increase,
reduced by the 0.4 percentage point
productivity adjustment), and the wage
index budget neutrality factor of 0.9998
for FY 2025, in alignment with our
current standard methodology.
To account for budget neutrality, as
discussed in section III.F of this
proposed rule, we are proposing to
apply a refinement standardization
factor to the FY 2025 IPF PPS Federal
per diem base rate and to the ECT
payment amount per treatment to
account for this proposed change to the
ECT payment amount per treatment and
all proposed changes to the patient-level
adjustment factors and to the ED
adjustment factor for FY 2025. We note
that this proposed increase to the ECT
per treatment amount would be
associated with a minor decrease to the
IPF Federal per diem base rate as a
result of the refinement standardization
factor (0.9514 instead of 0.9536). We
estimate that this change would increase
payments for IPFs that provide ECT, and
would decrease payments for IPFs that
do not provide ECT. However, the
decrease in payments associated with
this change would be no more than
approximately 0.2 percent, which
would be offset by various other
proposed changes such as the proposed
wage index changes, proposed revisions
to the IPF PPS patient-level
adjustments, and the proposed market
basket increase for FY 2025.
We note that we have monitored the
provision of ECT through analysis of
claims data since the beginning of the
IPF PPS, and have not observed any
indicators that payment is
inappropriately incentivizing the
provision of ECT to IPF patients. We
intend to continue monitoring the
provision of ECT through further
analysis of IPF PPS claims data.
A detailed discussion of the
distributional impacts of this proposed
change is found in section VIII.C of this
proposed rule. We welcome comments
regarding our analysis, including any
comments that could inform our
understanding of where ECT costs are
allocated in cost reports in order to
potentially inform improved collection
of data on ECT treatment costs in the
IPF setting. We also welcome comments
on whether it may be appropriate to
collect additional ECT-specific costs on
the hospital cost report. Lastly, we are
proposing that if more recent data
become available, we would use such
data, if appropriate, to determine the FY
2025 Federal per diem base rate and
ECT payment per treatment for the FY
2025 IPF PPS final rule.
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23153
IPFs must include a valid procedure
code for ECT services provided to IPF
beneficiaries to bill for ECT services, as
described in our Medicare Claims
Processing Manual, Chapter 3, Section
190.7.3 (available at https://
www.cms.gov/Regulations-andGuidance/Guidance/Manuals/
Downloads/clm104c03.pdf). There were
no changes to the ECT procedure codes
used on IPF claims in the final update
to the ICD–10–PCS code set for FY 2024.
Addendum B to this proposed rule
shows the ECT procedure codes for FY
2025 and is available on the CMS
website at https://www.cms.gov/
Medicare/Medicare-Fee-for-ServicePayment/InpatientPsychFacilPPS/
tools.html.
3. Proposed Update of the Federal per
Diem Base Rate and Electroconvulsive
Therapy Payment per Treatment
The current (FY 2024) Federal per
diem base rate is $895.63 and the ECT
payment per treatment is $385.58. For
the proposed FY 2025 Federal per diem
base rate, we applied the payment rate
update of 2.7 percent,—that is, the
proposed 2021-based IPF market basket
increase for FY 2025 of 3.1 percent
reduced by the proposed productivity
adjustment of 0.4 percentage point—the
proposed wage index budget neutrality
factor of 0.9998 (as discussed in section
III.D.1 of this proposed rule), and a
proposed refinement standardization
factor of 0.9514 (as discussed in section
III.F of this proposed rule) to the FY
2024 Federal per diem base rate of
$895.63, yielding a proposed Federal
per diem base rate of $874.93 for FY
2025. As discussed in section III.B.2 of
this proposed rule, we are proposing to
increase the ECT payment per treatment
for FY 2025 in addition to our routine
updates to the rate. We applied the
proposed 2.7 percent payment rate
update, the proposed 0.9998 wage index
budget neutrality factor, and the
proposed 0.9514 refinement
standardization factor to the proposed
payment per treatment based on the CY
2024 OPPS geometric mean cost of
$675.93, yielding a proposed ECT
payment per treatment of $660.30 for FY
2025.
Section 1886(s)(4)(A)(i) of the Act
requires that for RY 2014 and each
subsequent RY, in the case of an IPF
that fails to report required quality data
with respect to such RY, the Secretary
will reduce any annual update to a
standard Federal rate for discharges
during the RY by 2.0 percentage points.
Therefore, we are applying a 2.0
percentage point reduction to the
annual update to the Federal per diem
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base rate and the proposed ECT
payment per treatment as follows:
• For IPFs that fail to report required
data under the IPFQR Program, we
would apply a 0.7 percent payment rate
update—that is, the proposed IPF
market basket increase for FY 2025 of
3.1 percent reduced by the proposed
productivity adjustment of 0.4
percentage point for an update of 2.7
percent, and further reduced by 2.0
percentage points in accordance with
section 1886(s)(4)(A)(i) of the Act. We
would also apply the proposed
refinement standardization factor of
0.9514 and the proposed wage index
budget neutrality factor of 0.9998 to the
FY 2024 Federal per diem base rate of
$895.63, yielding a proposed Federal
per diem base rate of $857.89 for FY
2025.
• For IPFs that fail to report required
data under the IPFQR Program, we
would apply the proposed 0.7 percent
annual payment rate update, the
proposed 0.9514 refinement
standardization factor, and the proposed
0.9998 wage index budget neutrality
factor to the proposed payment per
treatment based on the CY 2024 OPPS
geometric mean cost of $675.93,
yielding a proposed ECT payment per
treatment of $647.45 for FY 2025.
We are proposing that if more recent
data become available, we would use
such data, if appropriate, to determine
the FY 2025 Federal per diem base rate
and ECT payment per treatment for the
FY 2025 IPF final rule.
C. Proposed Updates and Revisions to
the IPF PPS Patient-Level Adjustment
Factors
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1. Overview of the IPF PPS Adjustment
Factors and Proposed Revisions
The current (FY 2024) IPF PPS
payment adjustment factors were
derived from a regression analysis of
100 percent of the FY 2002 Medicare
Provider and Analysis Review
(MedPAR) data file, which contained
483,038 cases. For a more detailed
description of the data file used for the
regression analysis, we refer readers to
the RY 2005 IPF PPS final rule (69 FR
66935 through 66936).
For FY 2025, we are proposing to
implement revisions to the methodology
for determining payment rates under the
IPF PPS. As we noted earlier in this FY
2025 IPF PPS proposed rule, section
1886(s)(5)(D) of the Act, as added by
section 4125(a) of the CAA, 2023
requires that the Secretary implement
revisions to the methodology for
determining the payment rates under
the IPF PPS for psychiatric hospitals
and psychiatric units, effective for RY
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2025 (FY 2025). The revisions may be
based on a review of the data and
information collected under section
1886(s)(5)(A) of the Act. Accordingly,
we are proposing to revise the patientlevel IPF PPS payment adjustment
factors as discussed in section III.C.4. of
this proposed rule, effective for FY
2025. We have developed proposed
adjustment factors based on a regression
analysis of IPF cost and claims data,
which is discussed in greater detail in
the following sections of this proposed
rule. The primary sources of this
analysis are CY 2019 through 2021
MedPAR files and Medicare cost report
data (CMS Form 2552–10, OMB No.
0938–0050) 1 from the FY 2019 through
2021 Hospital Cost Report Information
System (HCRIS). For each year (2019
through 2021), if a provider did not
have a Medicare cost report for that
year, we used the provider’s most recent
available Medicare cost report prior to
the year for which a Medicare cost
report was missing, going back to as
early as 2018. Section III.C.3 of this
proposed rule discusses the
development of the proposed revised
case-mix adjustment regression.
2. History of IPF PPS Cost and Claims
Analyses
In the FY 2023 IPF PPS proposed rule
(87 FR 19428 through 19429), we briefly
discussed past analyses and areas of
interest for future refinement, about
which we previously solicited
comments. CMS also released a
technical report posted to the CMS
website 2 accompanying the rule,
summarizing these analyses. In that
same proposed rule, we described the
results of the agency’s latest analysis of
the IPF PPS and solicited comments on
certain topics from the report. We
summarized the considerations and
findings related to our analyses of the
IPF PPS adjustment factors in the FY
2023 IPF PPS final rule (46864 through
46865).
In the FY 2024 IPF PPS proposed rule
(88 FR 21269 through 21272), we
requested information from the public
to inform revisions to the IPF PPS
required by the CAA, 2023. Specifically,
we sought information about which data
and information would be most
appropriate and useful for the purposes
of refining IPF PPS payments. We
requested information related to the
specific types of data and information
mentioned in the CAA, 2023. We also
solicited comments on the reporting of
1 https://www.reginfo.gov/public/do/
PRAViewICR?ref_nbr=202206-0938-017.
2 https://www.cms.gov/files/document/technicalreport-medicare-program-inpatient-psychiatricfacilities-prospective-payment-system.pdf.
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ancillary charges, such as labs and
drugs, on IPF claims. Lastly, we
presented and solicited comments on
the latest results of our analysis of social
drivers of health (SDOH).
In response to the requests for
information, commenters offered a
number of suggestions for further
analysis, including recommendations to
consider adjusting payment for patients
with sleep apnea, violent behavior, and
patients that transfer from an acute care
unit. We discuss the analysis conducted
and our findings, as related to patientlevel adjustment factors, in section
III.C.3 of this proposed rule.
The primary goal in refining the IPF
PPS payment adjustment factors is to
pay each IPF an appropriate amount for
the efficient delivery of care to Medicare
beneficiaries. The system must be able
to account adequately for each IPF’s
case-mix to allow for both fair
distribution of Medicare payments and
access to adequate care for those
beneficiaries who require more costly
care. As required by section
1886(s)(5)(D)(iii) of the Act, as added by
section 4125(a) of the CAA, 2023,
proposed revisions to the IPF PPS
adjustment factors must be budget
neutral. As discussed in section III.F of
this proposed rule, we are applying a
refinement standardization factor to the
proposed IPF PPS payment rates to
maintain budget neutrality for FY 2025.
3. Development of the Proposed Revised
Case-Mix Adjustment Regression
To ensure that the IPF PPS continues
to account adequately for each IPF’s
case-mix, we performed an extensive
regression analysis of the relationship
between the per diem costs and both
patient and facility characteristics to
identify those characteristics associated
with statistically significant cost
differences. We discuss the results of
this regression analysis in section
III.C.3.e. of this proposed rule. We
further discuss proposed revisions to
the IPF PPS patient-level adjustment
factors based on this regression analysis
in section III.C.4 of this proposed rule.
As discussed in greater detail in
section III.C.3.c. of this proposed rule,
we computed a per diem cost for each
Medicare inpatient psychiatric stay,
including routine operating, ancillary,
and capital components using
information from the CY 2019 through
CY 2021 MedPAR files and data from
the 2019 through 2021 Medicare cost
reports, backfilling with Medicare cost
reports from the most recent prior year
when necessary.
We began with a 100 percent sample
of the CY 2019 through CY 2021
MedPAR data files, which contain a
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total of 1,111,459 stays from 1,684 IPFs.
As discussed in section III.C.3.b. of this
proposed rule, we applied several data
restrictions and exclusions to obtain the
set of data used for our regression
analysis. The MedPAR data files used
for this regression analysis contain a
total of 806,611 stays from 1,643 IPFs,
which reflect the removal of 41
providers and 304,848 stays with
missing or erroneous data. To include as
many IPFs as possible in the regression,
we used the cost report information for
each provider corresponding to the year
of claims, when available, and
substituted the most recent prior
available cost report information for
routine cost and ancillary cost to charge
ratios if the corresponding year’s data
was not available.
a. Data Sources
For the regression analysis, we chose
to use a combined set of CY 2019
through 2021 MedPAR data. Our
analysis showed that using a combined
set of data from multiple years yields
the most stable and consistent result.
When we looked at the results for each
year individually, we found that some
DRGs and comorbidity categories were
not statistically significant due in part to
small sample size. In addition, during
FY 2020, the U.S. healthcare system
undertook an unprecedented response
to the Public Health Emergency (PHE)
declared by the Secretary of the
Department of Health and Human
Services on January 31, 2020 in
response to the outbreak of respiratory
disease caused by a novel (new)
coronavirus that has been named ‘‘SARS
CoV 2’’ and the disease it causes, which
has been named ‘‘coronavirus disease
2019’’ (abbreviated ‘‘COVID–19’’). We
believe the aggregated three-year
regression serves to smooth the impact
of changes in utilization driven by the
COVID–19 PHE, as well as significant
changes in staffing and labor costs that
commenters noted in response to the FY
2023 and FY 2024 IPF PPS proposed
rules. As discussed earlier in this
proposed rule, we used 2019 through
2021 Medicare cost report data to retain
as many records as possible for analysis.
We also used several other data
sources to identify the IPF population
for analysis and to construct variables in
the regression model:
• Provider of Services (POS) File: The
POS file contains facility characteristics
including name, address, and types of
services provided.
• Provider Specific Data for Public
Use Files for the IPF PPS: The Provider
Specific File (PSF) contains data used to
calculate COLA factors and identify the
Core-Based Statistical Area (CBSA).
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CBSA is used to match providers with
corresponding wage index data, which
is used to adjust the calculation of the
Federal per diem base rate to account
for geographic differences in costs.
• Common Working File (CWF)
Inpatient Claims Data: The CWF
contains data regarding ECT treatments
provided during an IPF stay.
Among the 1,643 providers included
in the regression analysis sample, the
majority had their most recent Medicare
cost report information corresponding to
the year of the MedPAR data file.
Specifically, for the CY 2019 MedPAR
data file, 99.5 percent (1,551 providers)
used FY 2019 Medicare cost reports,
and 0.5 percent (8 providers) used FY
2018 Medicare cost reports. For CY
2020, 99.7 percent (1,523 providers)
used FY 2020 Medicare cost reports,
and 0.3 percent (5 providers) used FY
2019 Medicare cost reports. For CY
2021, 97.6 percent (1,435 providers)
used FY 2021 Medicare cost reports,
and 2.4 percent (35 providers) used FY
2020 Medicare cost reports. This
approach allowed us to use the most
current and relevant cost report data,
ensuring the robustness and accuracy of
our analysis.
b. Trims and Assumptions
To identify the IPF population for
analysis, we matched MedPAR records
to facility-level information from
Medicare cost reports, the POS file, and
the PSF. We included MedPAR stays
that met the following criteria:
• Hospital CMS Certification Number
(CCN) contains ‘‘40,’’ ‘‘41,’’ ‘‘42,’’ ‘‘43,’’
or ‘‘44’’ in the third and fourth position
or a special unit code of ‘‘S’’ or ‘‘M’’ for
psychiatric unit or psychiatric unit in a
critical access hospital.
• Beneficiary primary payer code is
equal to ‘‘Z’’ or blank, indicating
Medicare is the primary payer.
• Group Health Organization (GHO)
paid code is equal to zero or blank,
indicating that a GHO has not paid the
facility for the stay.
• National Claims History (NCH)
claim type code is equal to ‘‘60,’’ an
inpatient claim.
• Number of utilization days was
greater than zero.
To promote the accuracy and
completeness of data included in the
regression model, we completed a series
of trimming steps to remove missing
and outlier data. Before any trims or
exclusions were applied, there were
1,684 providers in the MedPAR data
file. First, we matched facilities from the
MedPAR dataset to the most recent
Medicare cost report file available from
CY 2018 to CY 2021, and excluded
facilities that did not have a Medicare
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cost report available from 2018 to 2021.
If facilities had more than one Medicare
cost report in a given year, we used the
Medicare cost report representing the
longest time span. We identified 1
provider in CY 2019, 5 providers in CY
2020, and 4 providers in CY 2021 that
had no available Medicare cost report
information. In total, we excluded data
from 5 unique providers that had no
available Medicare cost report
information from CY 2019 to CY 2021.
Next, we trimmed facilities with
extraordinarily high or low costs per
day. We removed facilities with outlier
routine per diem costs, defined as those
falling outside of the range of the mean
logarithm of routine costs per diem plus
or minus 3.00 standard deviations. We
also removed stays with outlier total per
diem costs, defined as those falling
outside the range of the mean per diem
cost by facility type (psychiatric
hospitals and psychiatric units) plus or
minus 3.00 standard deviations. The
average and standard deviations of the
total per diem cost (routine and
ancillary costs) were computed
separately for stays in psychiatric
hospitals and psychiatric units because
we did not want to systematically
exclude a larger proportion of cases
from one type of facility. In applying
these trims across all three data years
used in our regression model, there
were 104 providers with routine per
diem costs outside 3.00 standard
deviations from the mean, and 47
providers with total per diem costs
outside 3.00 standard deviations from
the mean. Specifically, this includes 24
providers in CY 2019, 41 providers in
CY 2020, and 39 providers in CY 2021
excluded for outlier routine per diem
costs. We identified 25 providers in CY
2019, 1 provider in CY 2020, and 21
providers in CY 2021 that we excluded
for outlier total per diem costs. In total,
we excluded data from 23 unique
providers with outlier routine per diem
costs and 8 unique providers with
outlier total per diem costs.
We also removed stays at providers
without a POS file or PSF. There were
5 providers without a POS file or PSF
during the period CY 2019 to CY 2021;
therefore, we are excluding data from
these 5 providers. Only 1 unique
provider was entirely excluded with no
POS file or PSF from CY 2019 to CY
2021. Additionally, 1 provider was
excluded because no stays had one of
the recognized IPF PPS DRGs assigned.
In summary, the application of these
data preparation steps resulted in
excluding 5 providers because they did
not have a cost report available from
2018 to 2021, 23 providers with routine
per diem costs outside 3.00 standard
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deviations from the mean, and 8
providers with total per diem costs
outside 3.00 standard deviations from
the mean. We also excluded 1 provider
without a POS file or PSF, 1 provider
with no stays with IPF PPS DRGs, and
3 providers based on IPF stays
restrictions. In total, the exclusion of
these 41 providers resulted in the
removal of 304,848 stays from our
original total of 1,111,459 stays.
We considered trimming stays from
facilities where 95 percent or more of
stays had no ancillary charges because
we assumed that the cost data from
these facilities were inaccurate or
incomplete. This is the trimming
methodology that we applied to the
analysis described in the technical
report released along with the FY 2023
IPF PPS proposed rule. As previously
discussed, the IPF PPS regression model
uses the sum of routine and ancillary
costs as the dependent variable, and we
assumed that data from facilities
without ancillary charge data would be
inadequate to capture variation in costs.
When we examined the claims from
2018, which we used for prior analysis,
this trimming step resulted in removing
almost one-quarter of total stays from
the unrestricted 2018 MedPAR dataset
(82,491 out of 364,080 total stays). This
trimming step also resulted in
disproportionate exclusion of certain
types of facilities, particularly
freestanding psychiatric hospitals that
were for-profit or government-operated,
as well as all-inclusive rate providers.
Approximately 55 percent of stays from
freestanding facilities would be
removed, compared to just 0.3 percent
of stays in psychiatric units. In the
analysis described in the FY 2023 IPF
PPS proposed rule (87 FR 19429), we
attempted to address this
disproportionate removal of stays by
facility type by applying weights by
facility type and ownership in the
regression model to account for
excluded providers and to avoid biasing
the sample towards stays from providers
in psychiatric units.
In response to the analysis described
in the FY 2023 IPF PPS proposed rule
(87 FR 19429), commenters raised
concerns about the large number of
stays excluded from the regression
analysis, and questioned whether the
ancillary charge data were truly missing,
as all-inclusive rate providers are not
required to report separate ancillary
charges. We agree that this trimming
step reduces the representativeness of
the IPF population used in the
regression model and may increase the
potential for bias of the regression
coefficients used for payment
adjustments. Furthermore, as discussed
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in section III.E.4. of this proposed rule,
we are clarifying cost reporting
requirements and implementing
operational changes that we believe will
increase the accuracy of the cost
information reported in the future.
Specifically, CMS will issue
instructions to the MACs and put in
place edits for cost reporting periods
beginning on or after October 1, 2024,
ensuring that only government-owned
or tribally owned IPF hospitals will be
permitted to file an all-inclusive cost
report. All other IPF hospitals would be
required to have a charge structure and
to report ancillary costs and charges on
their cost reports. We expect that this
proposed change would support
increased accuracy of future payment
refinements to the IPF PPS.
When we examined the claims from
CY 2019 to CY 2021, this trimming step
would have resulted in a loss of a
significant number of providers (324
providers in CY 2019, 330 providers in
CY 2020, and 336 providers in CY
2021). Due to the concerns that
commenters previously raised (which
we summarized in the FY 2024 IPF PPS
final rule (88 FR 51097 through 51098)),
and to include as many claims as
possible in the regression analysis, we
have not trimmed stays from facilities
with zero or minimal ancillary charges.
As a result, we observed a significant
reduction in data loss when comparing
our latest regression model with the
model described in the FY 2023 IPF PPS
proposed rule. By including, rather than
trimming, facilities with low or no
ancillary charge data, we prevented the
loss of 288 providers across the three
years, allowing for a more inclusive
analysis. These providers accounted for
approximately 194,673 stays included
in our data set.
We present our regression results in
section III.C.3.e. of this proposed rule
without the application of any trimming
or subsequent weighting to account for
the removal of stays from facilities with
zero or minimal ancillary charges.
c. Calculation of the Dependent Variable
The IPF PPS regression model uses
the natural logarithm of per diem total
cost as the dependent variable. We
computed a per diem cost for each
Medicare inpatient psychiatric stay,
including routine operating, ancillary,
and capital components, using
information from the combined CY 2019
through 2021 MedPAR file and data
from the 2018 through 2021 Medicare
cost reports. For each MedPAR CY, we
examined the corresponding Medicare
cost report, and if a provider’s cost-tocharge ratio was missing from the
matching year’s cost report, we looked
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at the provider’s cost report from the
prior year to obtain the most recent costto-charge value for the provider. We
applied a prior-year cost-to-charge ratio
to 8 providers from the CY 2019
MedPAR claims, 5 providers from the
CY 2020 MedPAR claims, and 35
providers from the CY 2021 MedPAR
claims.
To calculate the total cost per day for
each inpatient psychiatric stay, routine
costs were estimated by multiplying the
routine cost per day from the IPF’s
Medicare cost report (Worksheet D–1,
Part II, column 1, line 38) by the number
of Medicare covered days in the
MedPAR stay record. Ancillary costs
were estimated by multiplying each
departmental cost-to-charge ratio
(calculated by dividing the amount
obtained from Worksheet C, columns 5,
by the sum of Worksheet C, columns 6
and 7) by the corresponding ancillary
charges in the MedPAR stay record. The
total cost per day was calculated by
summing routine and ancillary costs for
the stay and dividing it by the number
of Medicare covered days for each day
of the stay.
To address extreme cost-to-charge
ratios, we winsorized the distributions
of the 17 ancillary cost centers from
Worksheet C of the cost report at the
2nd and 98th percentiles. That is, if the
cost-to-charge ratio was missing and
there was a charge on the claim, the
cost-to-charge ratio was imputed to the
calculated median value for each
respective cost center.
The total cost per day (also referred to
as per diem cost) was adjusted for
differences in cost across geographic
areas using the FY 2019 through 2021
IPF wage index and COLA
corresponding to each MedPAR data
year. We adjusted the labor-related
portion of the per diem cost using the
IPF wage index to account for
geographic differences in labor cost and
adjusted the non-labor portion of the per
diem cost by the COLA adjustment
factors for IPFs in Alaska and Hawaii.
We used IPF PPS labor-related share
and non-labor-related share finalized for
each year, FY 2019 through FY 2021, to
determine the amount of the per diem
cost that is adjusted by the wage index
and the COLA, respectively. We
calculated the adjusted cost using the
following formula:
Wage adjusted per diem cost = per diem
cost/(wage index * labor-related
share + COLA * (1-labor-related
share)).
d. Independent Variables
Independent variables in the
regression model are patient-level and
facility-level characteristics that affect
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the dependent variable in the model,
which is per diem cost. As discussed in
the following sections, the updated
regression model for this proposed rule
includes adjustment-related variables
and control variables. Adjustment
related variables are used for adjusting
payment, and as we discuss in section
III.C.4 of this proposed rule, we are
proposing to revise the IPF PPS patientlevel adjustment factors based on the
regression results for many of the
adjustment-related variables in the
model. Control variables are used to
account for variation in the dependent
variable that is associated with factors
outside the adjustment factors of the
payment model.
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(1) Adjustment-Related Variables
Patient-level adjustment-related
variables included in the regression
model are variables for DRG assignment,
comorbidity categories, age, and length
of stay. We note that facility-level
adjustment-related variables for rural
status and teaching status are also
included in the model; however, we are
not proposing revisions to the rural or
teaching adjustments for FY 2025. We
discuss the latest results of the
regression analysis for facility-level
adjustments in greater detail in section
IV.A. of this proposed rule.
(2) Control Variables
The regression model used to
determine IPF PPS payment
adjustments in the RY 2005 IPF PPS
final rule (69 FR 66922) included
control variables to account for
facilities’ occupancy rate, a control
variable to indicate if the patient
received ECT, and a control variable for
IPFs that do not bill for ancillary
charges. In the updated regression
model for this FY 2025 IPF PPS
proposed rule, we have removed the
occupancy control variables and the
control variable for IPFs that do not bill
for ancillary charges. In addition, we
have retained the control variable for
patients receiving ECT and added
control variables for the data year. We
also added a control variable for the
presence of ED charges on the claim. We
discuss considerations related to these
control variables and others in the
following paragraphs.
The 2004 regression model included
two control variables for occupancy
rate. One was a continuous variable for
the facility’s logarithmic-transformed
occupancy rate. The other was a
categorical variable indicating a facility
had an occupancy rate below 30
percent. Both of these variables were
found to be associated with statistically
significant increases in cost. In the RY
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2005 IPF PPS final rule, we adopted the
structural approach and included these
control variables in the regression. We
explained that it was appropriate to
control for variations in the occupancy
rate in estimating the effects of the
payment variables on per diem cost to
avoid compensating facilities for
inefficiency associated with
underutilized fixed costs (69 FR 66934).
As we discussed in the FY 2023 IPF PPS
proposed rule, our analysis found that
the occupancy control variables were
associated with rural status. We
solicited comments on the potential
removal of the occupancy control
variables from the model (87 FR 19429).
In response, we received several
comments in support of removing the
occupancy control variables, due to the
relationship between these control
variables and the rural adjustment (87
FR 46865). Commenters cited the
importance of rural IPFs as the primary
points of care and access for many
Medicare beneficiaries who cannot
travel to urban areas for mental health
services. We considered the potential
negative impact to rural facilities of
retaining the occupancy control
variables in the regression model. We
agree with the commenters who noted
the importance of maintaining stability
in payments for rural IPFs; therefore, we
did not include any occupancy control
variables in our regression model.
In addition, we considered including
a control variable for IPFs that do not
bill for ancillary services. As we
discussed in the RY 2005 IPF PPS final
rule (69 FR 66936), we included
variables in the regression to control for
psychiatric hospitals that do not bill
ancillary costs. However, at that time,
the number of IPFs who did not bill for
ancillary costs was relatively small and
consisted mostly of governmentoperated facilities. As we discuss later
in section III.E.4 of this proposed rule,
an increasing number of IPFs have
stopped reporting ancillary charges on
their claims, which means that ancillary
cost information is not available for
stays at these IPFs.
We considered whether to include a
control variable for facilities that do not
report ancillary charges. We considered
that the inclusion of a control variable
would only account for differences in
the level of cost between IPFs with and
without reported ancillary costs and
would not facilitate comparison of costs
between all IPFs in our sample. In
addition, we found that facilities that
did not report ancillary charges also
tended to have lower routine costs; that
is, our analysis showed that these
facilities would have overall lower costs
per day, regardless of whether ancillary
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costs were considered in the cost
variable. We considered that the
inclusion of a control variable in the
regression model would account for
these differences in overall cost, which
would impact the size of paymentrelated adjustment factors that are
correlated with the prevalence of
missing ancillary charge data. For this
reason, in developing a regression
model for proposing revisions to the IPF
PPS, we did not include a control
variable to account for facilities that
report zero or minimal ancillary
charges.
As noted earlier, the original model
also included a control variable for the
presence of ECT. This is because ECT is
paid on a per-treatment basis under the
IPF PPS. As discussed in more detail in
section III.B.2. of this FY 2025 IPF PPS
proposed rule, we continue to observe
that IPF stays with ECT have
significantly higher costs per day. We
are proposing to continue paying for
ECT on a per-treatment basis; therefore,
we included a control variable to
account for the additional costs
associated with ECT, which would
continue to be paid for outside the
regression model.
Similarly, we included a control
variable for stays with emergency
department (ED)-related charges. The
original model did not include an ED
control variable, because ED costs were
excluded from the dependent variable of
IPF per diem costs. Our regression
model for this FY 2025 IPF PPS
proposed rule includes all costs
associated with each IPF stay, including
ED costs. As discussed in section III.D.4.
of this proposed rule, we are proposing
to calculate the ED adjustment in
accordance with our longstanding
methodology, separate from the
regression model. However, we
included a control variable for stays
with ED charges to control for the
additional costs associated with ED
admissions, which are paid under the
ED adjustment outside the regression
model.
Lastly, we included control variables
for the data year. Because the model
used a combined set of data from 3
years, these control variables are
included in the model to account for
differences in cost levels between 2019,
2020, and 2021, which would be driven
by economic inflation and other
external factors unrelated to the
independent variables in the regression
model.
e. Regression Results
Table 2 presents the results of our
regression model. We discuss these
results and our related proposals to
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revise the IPF PPS patient-level
adjustment factors in section III.C.4 of
this proposed rule.
This regression model includes a total
of 806,611 stays, and the r-squared
value of the model is 0.32340, meaning
that the independent variables included
in the regression model can explain
approximately 32.3 percent of the
variation in per diem cost among IPF
stays.
Except for the teaching variable, each
of the adjustment factors in Table 2 is
the exponentiated regression coefficient
of our regression model, which as we
previously noted uses the natural
logarithm of per diem total cost as the
dependent variable. We present the
exponentiated regression results, as
these most directly translate to the way
that IPF PPS adjustment factors are
calculated for payment purposes. That
is, the exponentiated adjustment factors
presented below represent a percentage
increase or decrease in per diem cost for
IPF stays with each characteristic. In the
case of the teaching variable, the result
in Table 2 is the un-exponentiated
regression coefficient. As discussed in
section III.D of this proposed rule, the
current IPF PPS teaching adjustment is
calculated as 1 + a facility’s ratio of
interns and residents to beds, raised to
the power of 0.5150. The coefficient for
teaching status presented in Table 2 can
be interpreted in the same way.
For certain categorical variables,
including DRG, age, length of stay, and
the year control variables, results for the
reference groups are not shown in Table
2. The DRG reference group is DRG 885,
because this DRG represents the
majority of IPF PPS stays. The age
reference group is the Under 45
category, because this group is
associated with the lowest costs after
accounting for all other patient
characteristics in the model. The
reference group for length of stay is 10
days, which corresponds to the
reference group used in the original
regression model from the RY 2005 IPF
PPS final rule. Lastly, the year control
reference group is CY 2021. Each of
these reference groups not shown in
Table 2 effectively has an adjustment
factor of 1.00 in the regression model.
As shown in Column 5 of Table 2, we
considered the regression factors to be
statistically significant when the p-value
was less than or equal to the
significance level of 0.05 (*), 0.01 (**),
and 0.001 (***). Columns 6 and 7 of
Table 2 show the lower and upper
bounds of the 95-percent confidence
interval (CI).
BILLING CODE 4120–01–P
Description
Number
%of
Adjustment
of Stays
Stays
Factors
Degenerative nervous system
disorders w MCC
Degenerative nervous system
disorders w/out MCC
OR procedures with principal
diagnosis of mental health
Acute adjustment reaction and
osvchosocial dvsfunction
4,287
40,584
751
7,529
Depressive neuroses
23,566
Neuroses except depressive
10,143
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Disorders of personality and
impulse control
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5,804
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Significance 1
CI Lower
Bound
CI Upper
Bound
0.5%
1.12818
***
1.09253
1.16500
5.0%
1.11030
***
1.07727
1.14434
0.1%
1.28830
***
1.24616
1.33185
0.9%
1.07632
**
1.02387
1.13146
2.9%
1.06153
***
1.03586
1.08784
1.3%
1.02156
0.96798
1.07811
0.7%
1.17059
1.13015
1.21249
Fmt 4701
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E:\FR\FM\03APP2.SGM
***
03APP2
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Table 2: IPF PPS Per Diem Cost Regression Results with Data from CY 2019 through
CY 2021
Description
Organic distmbances and
intellectual disabilitv
Behavioral and developmental
disorders
Other mental disorder diagnoses
Alcohol, Drug Abuse or
Denendence, Left AMA
Alcohol, Drug Abuse or
Denendence w rehab therapy
Alcohol, Drug Abuse or
Dependence w/out rehab therapy
wMCC
Alcohol, Drug Abuse or
Dependence w/out rehab Uierapy
w/outMCC
Poisoning and toxic effects of
drugswMCC
Poisoning and toxic effects of
drugs w/out MCC
Signs and Symptoms w MCC
Signs and Symptoms w/out MCC
Age 45 to 54 years
Stays
Factors
55,842
1,582
321
3 060
12 361
891
34,767
137
843
58
805
94 473
Age 70 to 79 years
126 280
Age over 79 years
87 442
Acute Renal Failure
19,064
Artificial Openings - Digestive &
Urinarv
Cardiac conditions
3,713
22,152
Conduct Disorder
5,113
Chronic Renal Failure
46,274
Coagulation Factor Deficit
492
Chronic Obstructive Pulmonary
Disease
Developmental Disabilities
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of Stays
68136
Age 65 to 69 years
11,994
27,020
Uncontrolled Diabetes
21,939
Drug/Alcohol Induced Mental
Disorders
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Adjustment
74 512
Age 60 to 64 years
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%of
121498
Age 55 to 59 years
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Frm 00015
Significance 1
CI Lower
Bound
CI Upper
Bound
6.9%
1.08234
***
1.05502
1.11038
0.2%
1.06940
***
1.03421
1.10578
0.0%
1.12075
0.92590
1.35661
0.4%
0.86061
***
0.81619
0.90745
1.5%
0.89569
***
0.84258
0.95215
0.1%
1.02242
0.98132
1.06523
4.3%
0.94524
***
0.91415
0.97738
0.0%
1.19428
***
1.12732
1.26521
0.1%
1.11591
***
1.08122
1.15172
0.0%
1.12739
**
1.03077
1.23307
0.1%
1.09033
**
1.02230
1.16289
15.1%
1.01993
***
1.01372
1.02617
9.2%
1.04746
***
1.03741
1.05762
8.4%
1.06561
***
1.05234
1.07904
11.7%
1.08783
***
1.07098
1.10495
15.7%
1.11724
***
1.09341
1.14158
10.8%
1.12790
***
1.09902
1.15754
2.4%
1.06093
***
1.03735
1.08503
0.5%
1.07435
***
1.05526
1.09379
2.7%
1.04946
***
1.03362
1.06554
0.6%
0.98245
0.93588
1.03134
5.7%
1.07955
1.06588
1.09340
0.1%
1.01663
0.98084
1.05373
1.5%
1.06933
1.04771
1.09140
3.3%
1.02102
0.99556
1.04712
2.7%
1.05366
***
1.03528
1.07238
7.4%
0.96084
**
0.93690
0.98538
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***
***
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23160
Description
Eating Disorder
of Stays
Stays
Factors
38 562
Severe Protein Malnutrition
5 119
Oncology Treatment
12
Poisoning
5 966
Severe Musculoskeletal &
Connective Tissue Disease
4 272
Trachcostomy
304
Intensive Management for HighRisk Behavior
ECT Indicator
19,884
12,654
ER Indicator
261643
Rural
101,483
Teaching Status
155 458
Length of stay - l day
16 891
Length of stay - 2 days
28 370
Length of stay - 3 days
42 298
Length of stay - 4 days
48187
Length of stay - 5 days
54 187
Length of stay - 6 days
59 215
Length of stay - 7 days
63,095
Length of stay - 8 days
51,491
Length of stay - 9 days
42,855
Length of stay - 11 days
35,092
Length of stay - 12 days
32,030
Length of stay - 13 days
32,356
Length of stay - 14 days
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Adjustment
223
Infectious diseases
34,727
Length of stay - 15 days
24,919
Length of stay - 16 days
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%of
2,812
Gangrene
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18,907
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Significance 1
CI Lower
Bound
CI Upper
Bound
0.3%
1.09353
***
1.05295
1.13567
0.0%
1.11781
***
1.05627
1.18294
4.8%
1.01549
0.99930
1.03193
0.6%
1.16750
***
1.12231
1.21452
0.0%
1.45578
***
1.20449
1.75949
0.7%
1.16190
***
1.13990
1.18432
0.5%
1.04856
***
1.03163
1.06577
0.0%
1.09464
***
1.04885
1.14244
2.5%
1.06997
***
1.03021
1.11128
1.6%
1.33080
***
1.27553
1.38846
32.4%
1.38913
***
1.34596
1.43369
12.6%
1.19139
***
1.12333
1.26357
19.3%
0.72862
***
0.57860
0.87864
2.1%
1.27494
***
1.24324
1.30744
3.5%
1.20173
***
1.17710
1.22688
5.2%
1.14873
***
1.12808
1.16976
6.0%
1.11669
***
1.09984
1.13381
6.7%
1.08356
***
1.06837
1.09897
7.3%
1.06079
***
1.04833
1.07340
7.8%
1.02646
***
1.01538
1.03767
6.4%
1.01682
***
1.00766
1.02605
5.3%
1.00908
**
1.00225
1.01596
4.4%
0.99518
0.98910
1.00130
4.0%
0.99592
0.98943
1.00245
4.0%
0.99819
0.98886
1.00761
4.3%
0.99885
0.98382
1.01412
3.1%
0.98872
0.97489
1.00275
2.3%
0.98779
0.97362
1.00216
Fmt 4701
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Description
Number
%of
Adjustment
of Stays
Stays
Factors
Length of stay - 17 days
16,128
Length of stay - 18 days
14,191
Length of stay - 19 days
13 085
Length of stay - 20 days
13 302
Length of stay - 21 days
12 628
Length of stay - greater or equal
to 22 days
113 912
CY2019 Stay
330 574
Significance 1
CI Lower
Bound
CI Upper
Bound
2.0%
0.98944
0.97588
1.00318
1.8%
0.98559
0.97134
1.00005
1.6%
0.98792
0.97199
1.00411
1.6%
0.98446
0.96789
1.00130
1.6%
0.98476
0.96361
1.00637
14.1%
0.98771
0.96017
1.01604
41.0%
0.89833
0.88733
0.90947
***
***
0.94041
0.95822
32.1%
0.94927
259 052
1 Statistical significance based on p-value less than or equal to the significance level of 0.05 (*), 0.01 (**), and 0.001
(***)
BILLING CODE 4120–01–C
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4. Proposed Updates and Revisions to
the IPF PPS Patient-Level Adjustments
The IPF PPS includes payment
adjustments for the following patientlevel characteristics: Medicare Severity
Diagnosis Related Groups (MS–DRGs)
assignment of the patient’s principal
diagnosis, selected comorbidities,
patient age, and the variable per diem
adjustments. As discussed in section
III.C.3. of this proposed rule, we are
proposing to derive updated IPF PPS
adjustment factors for FY 2025 using a
regression analysis of data from the CY
2019 through 2021 MedPAR data files
and Medicare cost report data from the
2018 through FY 2021 Hospital Cost
Report Information System (HCRIS).
However, we have used more recent
claims (specifically, the December, 2023
update of the FY 2023 IPF PPS MedPAR
claims) and cost data from the January,
2024 update of the provider-specific file
(PSF) to simulate payments to finalize
the outlier fixed dollar loss threshold
amount and to assess the impact of the
IPF PPS updates. More information
about the data used for the impact
simulations is found in section VIII.C of
this FY 2025 IPF PPS proposed rule. As
discussed in section III.C.3. of this
proposed rule, by adjusting for DRGs,
comorbidities, age, and length of the
stay, along with the facility-level
variables and control variables in the
model, we were able to explain
approximately 32.3 percent of the
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variation in per diem cost among IPF
stays.
In addition, we are proposing routine
coding updates for FY 2025 for our
longstanding code first and IPF PPS
comorbidities. Furthermore, as
discussed in section III.C.4.a.(2) of this
proposed rule, we are proposing to
adopt a sub-regulatory process for future
routine coding updates.
a. Proposed Updated and Revisions to
MS–DRG Assignment
(1) Background
We believe it is important to maintain
for IPFs the same diagnostic coding and
DRG classification used under the IPPS
for providing psychiatric care. For this
reason, when the IPF PPS was
implemented for cost reporting periods
beginning on or after January 1, 2005,
we adopted the same diagnostic code set
(ICD–9–CM) and DRG patient
classification system (MS–DRGs) that
were utilized at the time under the IPPS.
In the RY 2009 IPF PPS notice (73 FR
25709), we discussed CMS’s effort to
better recognize resource use and the
severity of illness among patients. CMS
adopted the new MS–DRGs for the IPPS
in the FY 2008 IPPS final rule with
comment period (72 FR 47130). In the
RY 2009 IPF PPS notice (73 FR 25716),
we provided a crosswalk to reflect
changes that were made under the IPF
PPS to adopt the new MS–DRGs. For a
detailed description of the mapping
changes from the original DRG
adjustment categories to the current
MS–DRG adjustment categories, we
PO 00000
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refer readers to the RY 2009 IPF PPS
notice (73 FR 25714).
The IPF PPS includes payment
adjustments for designated psychiatric
DRGs assigned to the claim based on the
patient’s principal diagnosis. The DRG
adjustment factors were expressed
relative to the most frequently reported
psychiatric DRG in FY 2002, that is,
DRG 430 (psychoses). The coefficient
values and adjustment factors were
derived from the regression analysis
discussed in detail in the RY 2004 IPF
proposed rule (68 FR 66923; 66928
through 66933) and the RY 2005 IPF
final rule (69 FR 66933 through 66960).
Mapping the DRGs to the MS–DRGs
resulted in the current 17 IPF MS–
DRGs, instead of the original 15 DRGs,
for which the IPF PPS provides an
adjustment.
In the FY 2015 IPF PPS final rule
published August 6, 2014 in the Federal
Register titled, ‘‘Inpatient Psychiatric
Facilities Prospective Payment
System—Update for FY Beginning
October 1, 2014 (FY 2015)’’ (79 FR
45945 through 45947), we finalized
conversions of the ICD–9–CM–based
MS–DRGs to ICD–10–CM/PCS–based
MS–DRGs, which were implemented on
October 1, 2015. Further information on
the ICD–10–CM/PCS MS–DRG
conversion project can be found on the
CMS ICD–10–CM website at https://
www.cms.gov/medicare/coding-billing/
icd-10-codes/icd-10-ms-drg-conversionproject.
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(2) Proposal To Adopt Sub-Regulatory
Process for Publication of Coding
Changes
As discussed in the FY 2015 IPF PPS
proposed rule (79 FR 26047) every year,
changes to the ICD–10–CM and the ICD–
10–PCS coding system have been
addressed in the IPPS proposed and
final rules. The changes to the codes are
effective October 1 of each year and
must be used by acute care hospitals as
well as other providers to report
diagnostic and procedure information.
In accordance with § 412.428(e), we
have historically described in the IPF
PPS proposed and final rules the ICD–
10–CM coding changes and DRG
classification changes that have been
discussed in the annual proposed and
final hospital IPPS regulations. This has
typically involved a discussion in the
proposed rule about coding updates to
be effective October 1 of each year, with
a summary of comments in the final rule
along with a description of additional
finalized codes for October.
In the FY 2022 IPPS/LTCH PPS final
rule (86 FR 44950 through 44956), we
adopted an April 1 implementation date
for ICD–10–CM diagnosis and ICD–10–
PCS procedure code updates in addition
to the annual October 1 update of ICD–
10–CM diagnosis and ICD–10–PCS
procedure codes, beginning with April
1, 2022. In that rule, we noted the intent
of this April 1 implementation date is to
allow flexibility in the ICD–10 code
update process. Currently, as noted
earlier in this proposed rule, the IPF
PPS uses the IPPS DRG assignments,
which are applied to IPF PPS claims;
these DRG assignments reflect the
change in process that the IPPS adopted
for FY 2022. To maintain consistency
with IPPS policy, we are proposing to
follow the same process beginning in FY
2025. This means that for routine coding
updates that incorporate new or revised
codes, we are proposing to adopt these
changes through a sub-regulatory
process. Beginning in FY 2025, we
would operationalize such coding
changes in a Transmittal/Change
Request, which would align with the
way coding changes are announced
under the IPPS.
For example, we are proposing that
for April 2025, we would adopt routine
coding updates for the IPF PPS
comorbidity categories, code first
policy, ECT code list, and DRG
assignment via sub-regulatory guidance.
These coding updates would take effect
April 1, 2025. In accordance with
§ 412.428(e), we would describe these
coding changes, along with any coding
updates that would be effective for
October 1, 2025, in the FY 2026 IPF PPS
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proposed rule. We would summarize
and respond to any comments on these
April and October coding changes in the
FY 2026 IPF PPS final rule.
The proposed update aims to allow
flexibility in the ICD–10 code update
process for the IPF PPS and reduces the
lead time for making routine coding
updates to the IPF PPS code first list,
comorbidities, and ECT coding
categories. In addition, the IPPS subregulatory process continues to manage
DRG assignment changes which apply
to the DRG assignments used in the IPF
PPS. Finally, we are clarifying that we
would only apply this sub-regulatory
process for routine coding updates. Any
future substantive revisions to the IPF
PPS DRG adjustments, comorbidities,
code first policy, or ECT payment policy
would be proposed through notice and
comment rulemaking. We solicit public
comments on this proposal.
(3) Routine Coding Updates for DRG
Assignments
The diagnoses for each IPF MS–DRG
will be updated as of October 1, 2024,
using the final IPPS FY 2025 ICD–10–
CM/PCS code sets. The FY 2025 IPPS/
LTCH PPS final rule will include tables
of the changes to the ICD–10–CM/PCS
code sets that underlie the proposed FY
2025 IPF MS–DRGs. Both the FY 2025
IPPS final rule and the tables of final
changes to the ICD–10–CM/PCS code
sets, which underlie the FY 2025 MS–
DRGs, will be available on the CMS
IPPS website at https://www.cms.gov/
medicare/payment/prospectivepayment-systems/acute-inpatient-pps.
(4) Code First
As discussed in the ICD–10–CM
Official Guidelines for Coding and
Reporting, certain conditions have both
an underlying etiology and multiple
body system manifestations due to the
underlying etiology. For such
conditions, the ICD–10–CM has a
coding convention that requires the
underlying condition be sequenced first,
followed by the manifestation.
Wherever such a combination exists,
there is a ‘‘use additional code’’ note at
the etiology code, and a ‘‘code first’’
note at the manifestation code. These
instructional notes indicate the proper
sequencing order of the codes (etiology
followed by manifestation). In
accordance with the ICD–10–CM
Official Guidelines for Coding and
Reporting, when a primary (psychiatric)
diagnosis code has a code first note, the
provider will follow the instructions in
the ICD–10–CM Tabular List. The
submitted claim goes through the CMS
processing system, which will identify
the principal diagnosis code as non-
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Fmt 4701
Sfmt 4702
psychiatric and search the secondary
codes for a psychiatric code to assign a
DRG code for adjustment. The system
will continue to search the secondary
codes for those that are appropriate for
comorbidity adjustment. For more
information on the code first policy, we
refer readers to the RY 2005 IPF PPS
final rule (69 FR 66945). We also refer
readers to sections I.A.13 and I.B.7 of
the FY 2020 ICD–10–CM Coding
Guidelines, which is available at https://
www.cdc.gov/nchs/data/icd/
10cmguidelinesFY2020_final.pdf. In the
FY 2015 IPF PPS final rule, we provided
a code first table for reference that
highlights the same or similar
manifestation codes where the code first
instructions apply in ICD–10–CM that
were present in ICD–10–CM (79 FR
46009). In FY 2018, FY 2019, and FY
2020, there were no changes to the final
ICD–10–CM codes in the IPF Code First
table. For FY 2021 and FY 2022, there
were 18 ICD–10–CM codes deleted from
the final IPF Code First table. For FY
2023, there were 2 ICD–10–CM codes
deleted and 48 ICD–10–CM codes added
to the IPF Code First table. For FY 2024,
there were no proposed changes to the
Code First Table.
We are proposing to continue our
existing code first policy. As outlined in
our proposal to incorporate a subregulatory process for the publication of
coding changes, we are proposing to
adopt a sub-regulatory approach to
handle the coding updates, which
removes the requirement to discuss
coding updates in the Federal Register
during regulatory updates prior to
implementation, which would mirror
the approach taken by the IPPS. The
proposed FY 2025 Code First table is
shown in Addendum B on the CMS
website at https://www.cms.gov/
Medicare/Medicare-FeeforServicePayment/
InpatientPsychFacilPPS/tools.html.
(5) Proposed Revisions to MS–DRG
Adjustment Factors
For FY 2025, we are proposing to
revise the payment adjustments for
designated psychiatric DRGs assigned to
the claim based on the patient’s
principal diagnosis, following our
longstanding policy of using the ICD–
10–CM/PCS–based MS–DRG system. As
discussed in the following paragraphs,
we are proposing to maintain DRG
adjustments for 15 of the existing 17 IPF
MS–DRGs for which we currently adjust
payment in FY 2024. We are proposing
to replace two existing DRGs with two
new DRGs to reflect changes in coding
practices over time and proposing to
add two DRGs that are associated with
poisoning. We are also proposing to
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revise the adjustment factors for the
DRG adjustments as described in Table
3, based on the results of our latest
regression analysis described in Section
III.C.3 of this proposed rule. Addendum
A is available on the CMS website at
https://www.cms.gov/medicare/
payment/prospective-payment-systems/
inpatient-psychiatric-facility/tools-andworksheets. The website includes the
proposed DRG adjustment factors for FY
2025. In accordance with our
longstanding policy, we are proposing
that psychiatric principal diagnoses that
do not group to one of the 19 proposed
designated MS–DRGs would still
receive the Federal per diem base rate
and all other applicable adjustments;
however, the payment would not
include an MS–DRG adjustment.
(a) Proposed Replacement of DRGs
We are proposing to remove DRGs 080
(Nontraumatic stupor & coma w MCC)
and 081 (Nontraumatic stupor & coma
w/o MCC), and to replace these with
DRGs 947 (Signs and Symptoms w
MCC) and 948 (Signs and Symptoms w/
out MCC). As previously discussed, we
observed that the number of cases in
DRGs 080 and 081 have decreased
significantly since 2004. We selected
DRGs 947 and 948 as the most clinically
appropriate replacements, because most
of the ICD–10–CM codes that previously
grouped to DRGs 080 or 081 now group
to DRGs 947 or 948. Table 3 compares
the current adjustment factors for DRGs
080 and 081 to the regression-derived
adjustment factors for DRGs 947 and
948. As shown in Table 3, the proposed
adjustment factors for DRGs 947 and
23163
948 would each be greater than the
current DRG adjustment for DRGs 080
and 081. Therefore, we are proposing
that claims with DRGs 080 or 081 would
still receive the Federal per diem base
rate and all other applicable
adjustments; however, the payment
would not include an MS–DRG
adjustment.
As discussed in section III.F of this
proposed rule, we are proposing to
implement this revision to the DRG
adjustments budget-neutrally. A
detailed discussion of the distributional
impacts of this proposed change is
found in section VIII.C of this proposed
rule. Lastly, we are proposing that if
more recent data become available, we
would use such data, if appropriate, to
determine the FY 2025 DRG adjustment
factors.
Table 3: Proposed Replacements for DRG Adjustments
Description
Current
#of
%
Proposed
Adjustment
Stays
of Stays
Adjustment
Factors
CY
CY 2019-
Factors
2019-
CY 2021
CY 2021
(b) Proposed Additions of DRGs
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We are proposing to recognize DRG
adjustments for two DRGs associated
with poisoning; specifically, DRG 917
(Poisoning and toxic effects of drugs w
MCC) and 918 (Poisoning and toxic
effects of drugs w/out MCC). As
discussed earlier in this proposed rule,
we have identified that a small but
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1.07
1
0.00%
NIA
1.07
1
0.00%
NIA
NIA
58
0.01%
1.13
NIA
805
0.10%
1.09
increasing number of IPF stays contain
these poisoning-related DRG
assignments, and that stays with these
DRGs have increased costs per day that
are statistically significant. Table 4
summarizes the frequency of these stays
and the proposed adjustment factors for
FY 2025. As discussed in section III.F of
this proposed rule, we are proposing to
implement this revision to the DRG
PO 00000
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Fmt 4701
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adjustments budget-neutrally. A
detailed discussion of the distributional
impacts of this proposed change is
found in section VIII.C of this proposed
rule.
Lastly, we are proposing that if more
recent data become available, we would
use such data, if appropriate, to
determine the FY 2025 DRG adjustment
factors.
E:\FR\FM\03APP2.SGM
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DRG 080- Nontraumatic stupor &
comawMCC
DRG 081-Nontraumatic stupor &
comawloMCC
DRG 94 7-Signs and Symptoms w
MCC
DRG 948-Signs and Symptoms wlout
MCC
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Table 4: Proposed Additions for DRG Adjustments
Current
Adjustment
Factors
DRG 917-Poisoning and toxic effects
of drugs w MCC
DRG 918-Poisoning and toxic effects
of drugs wlout MCC
(c) Proposed Revisions to Adjustment
Factors for Existing DRG Adjustments
lotter on DSK11XQN23PROD with PROPOSALS2
We are proposing to revise the
adjustment factors for the remaining 15
of the existing 17 DRGs that currently
receive a DRG adjustment in FY 2024.
These proposed revisions are based on
the results of our latest regression
analysis described in section III.C.3 of
this proposed rule.
As previously discussed, our analysis
found that some of the adjustment
factors in the regression model for DRGs
that currently receive an adjustment are
no longer statistically significant.
Specifically, we found that the
adjustment factors for DRG 882
(Neuroses except depressive), DRG 887
(Other mental disorder diagnoses), and
DRG 896 (Alcohol, Drug Abuse or
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%
of Stays
CY2019CY2021
Proposed
Adjustment
Factors
NIA
#of
Stays
CY
2019CY2021
137
0.02%
1.19
NIA
843
0.10%
1.12
Dependence w/out rehab therapy w
MCC) were not statistically significant.
For each of these DRGs, we examined
whether the current adjustment factor
falls within the confidence interval for
our latest regression analysis. The
current adjustment for DRG 882 is 1.02,
and this falls within the confidence
interval of 0.96798 to 1.07811 for the
latest regression model discussed in
section III.C.3 of this proposed rule. We
believe it would be appropriate to
maintain the current adjustment factor
of 1.02 for DRG 882, because the latest
regression results indicate that the
current adjustment factor would be a
reasonable approximation of the
increased costs associated with DRG
882. For DRGs 887 and 896; however,
the current adjustment factors (0.92 and
0.88, respectively) do not fall within the
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confidence interval for each of these
DRGs. Therefore, we are proposing to
apply an adjustment factor of 1.00 for
IPF stays with these DRGs.
Table 5 summarizes the frequency of
these stays and the proposed adjustment
factors for FY 2025. As discussed in
section III.F of this proposed rule, we
are proposing to implement this
revision to the DRG adjustments budgetneutrally. A detailed discussion of the
distributional impacts of this proposed
change is found in section VIII.C of this
proposed rule.
Lastly, we are proposing that if more
recent data become available, we would
use such data, if appropriate, to
determine the FY 2025 DRG adjustment
factors.
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Table 5: Proposed Updates to Existing DRG Adjustments
Current
Adjustment
Factors
DRG 056-Degenerative nervous
system disorders w MCC
DRG 057-Degenerative nervous
system disorders w/out MCC
DRG 876-OR procedure with
principal dia!!Iloses of mental illness
DRG 880-Acute adjustment reaction
and nsvchosocial dysfunction
DRG 881-Depressive neuroses
DRG 882-Neuroses except
depressive
DRG 883-Disorders of
personality and impulse control
DRG 884-Organic disturbances
and intellectual disabilities
DRG 885-Psychoses
DRG 886-Behavioral and
developmental disorders
DRG 887-0ther mental disorder
dirumoses
DRG 894-Alcohol, Drug Abuse
or Dependence, Left AMA
DRG 895-Alcohol, Drug Abuse
or Dependence w rehab theranv
DRG 896-Alcohol, Drug Abuse
or Dependence w/out rehab
therapy w MCC
DRG 897-Alcohol, Drug Abuse
or Dependence w/out rehab
therapy w/out MCC
BILLING CODE 4120–01–C
b. Proposed Payment for Comorbid
Conditions
lotter on DSK11XQN23PROD with PROPOSALS2
(1) Proposed Revisions to Comorbidity
Adjustments
The intent of the comorbidity
adjustments is to recognize the
increased costs associated with
comorbid conditions by providing
additional payments for certain existing
medical or psychiatric conditions that
are expensive to treat.
Comorbidities are specific patient
conditions that are secondary to the
patient’s principal diagnosis and that
require treatment during the stay.
Diagnoses that relate to an earlier
episode of care and have no bearing on
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%
of Stays
CY2019CY2021
Proposed
Adjustment
Factors
1.05
#of
Stays
CY
2019CY2021
4,287
0.53%
1.13
1.05
40,584
5.03%
1.11
1.22
751
0.09%
1.29
1.05
7,529
0.93%
1.08
0.99
1.02
23,566
10,143
2.92%
1.26%
1.06
1.02
5,804
0.72%
1.17
1.03
55,842
6.92%
1.08
1.00
0.99
603,280
1,582
74.79%
0.20%
1.00
1.07
0.92
321
0.04%
1.00
0.97
3,060
0.38%
0.86
1.02
12,361
1.53%
0.90
0.88
891
0.11%
1.00
0.88
34,767
4.31%
0.95
the current hospital stay are excluded
and must not be reported on IPF claims.
Comorbid conditions must exist at the
time of admission or develop
subsequently, and affect the treatment
received, LOS, or both treatment and
LOS.
The current comorbidity adjustments
were determined based on the
regression analysis using the diagnoses
reported by IPFs in FY 2002. The
principal diagnoses were used to
establish the DRG adjustments and were
not accounted for in establishing the
comorbidity category adjustments,
except where ICD–9–CM code first
instructions applied. In a code first
situation, the submitted claim goes
through the CMS processing system,
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1.02
which identifies the principal diagnosis
code as non-psychiatric and searches
the secondary codes for a psychiatric
code to assign an MS–DRG code for
adjustment. The system continues to
search the secondary codes for those
that are appropriate for a comorbidity
adjustment.
In our RY 2012 IPF PPS final rule (76
FR 26451 through 26452), we explained
that the IPF PPS includes 17
comorbidity categories and identified
the new, revised, and deleted ICD–9–
CM diagnosis codes that generate a
comorbid condition payment
adjustment under the IPF PPS for RY
2012 (76 FR 26451).
As discussed in section C.4.a.(1) of
this proposed rule, it is our policy to
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maintain the same diagnostic coding set
for IPFs that is used under the IPPS for
providing the same psychiatric care.
The 17 comorbidity categories formerly
defined using ICD–9–CM codes were
converted to ICD–10–CM/PCS in our FY
2015 IPF PPS final rule (79 FR 45947
through 45955). The goal for converting
the comorbidity categories is referred to
as replication, meaning that the
payment adjustment for a given patient
encounter is the same after ICD–10–CM
implementation as it would be if the
same record had been coded in ICD–9–
CM and submitted prior to ICD–10–CM/
PCS implementation on October 1,
2015. All conversion efforts were made
with the intent of achieving this goal.
For each claim, an IPF may receive
only one comorbidity adjustment within
a comorbidity category, but it may
receive an adjustment for more than one
comorbidity category. Current billing
instructions for discharge claims, on or
after October 1, 2015, require IPFs to
enter the complete ICD–10–CM codes
for up to 24 additional diagnoses if they
co-exist at the time of admission, or
develop subsequently and impact the
treatment provided.
As previously discussed in section
III.C.4.a.(2) of this proposed rule, we are
proposing to adopt an April 1
implementation date for ICD–10–CM
diagnosis and ICD–10–PCS procedure
code updates, in addition to the annual
October 1 update, beginning with April
1, 2025 for the IPF PPS. For FY 2025
and future years, coding updates related
to the IPF PPS comorbidity categories
would be adopted following a subregulatory process as discussed earlier
in this proposed rule.
For FY 2025, we are proposing to
revise the comorbidity adjustment
factors based on the results of the 2019
through 2021 regression analysis
described in section III.C.3.e. of this
proposed rule. We are also proposing
additions and changes to the
comorbidity categories for which we
adjust payment based on our analysis of
ICD–10–CM codes currently included in
each category as well as public
comments received in response to the
FY 2022 and FY 2023 IPF PPS proposed
rules.
Based on analysis of the ICD–10–CM
codes, we considered the statistical
significance of the adjustment factor and
whether the current (FY 2024)
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adjustment factor fell within the
confidence interval in the 2019 through
2021 regression to determine the FY
2025 IPF PPS proposed comorbidity
categories and adjustment factors. As
previously discussed for the DRG
adjustment factors, when the regression
factor is not statistically significant, but
the current adjustment factor is within
the confidence interval, we are
proposing to maintain the current
adjustment factor. When a regression
factor is not statistically significant and
the current adjustment factor is not
within the confidence interval, we are
proposing to remove the comorbidity
category.
Specifically, we are proposing to
increase the adjustment factors for the
Gangrene, Severe Protein Malnutrition,
Oncology Treatment, Poisoning, and
Tracheostomy comorbidity categories
based on the adjustment factors derived
from the regression analysis discussed
in section III.C.3 of this proposed rule.
For these comorbidity categories, the
regression results produced a
statistically significant increase in the
adjustment factors.
We are proposing to remove the
comorbidity categories for the
Coagulation Factor Deficit, Drug/
Alcohol Induced Mental Disorders, and
Infectious Diseases adjustment factors
because the regression factor for the
ICD–10–CM codes associated with
Coagulation Factor Deficit and
Infectious Diseases were not statistically
significant, and the current adjustment
factors did not fall within the
confidence intervals in the 2019 through
2021 regression.
The current adjustment factor for
Drug/Alcohol Induced Mental Disorders
is 1.03; however, the adjustment factor
derived from our latest regression
results was statistically significant at
0.96084, meaning payments would be
reduced if we applied the regressionderived adjustment factor as a
comorbidity adjustment for this
category. In order to understand the
drivers of changing costs for the Drug/
Alcohol Induced Mental Disorders
comorbidity category, we examined a
subset of ICD–10–CM codes within the
comorbidity category associated with
opioid disorders which make up the
majority of stays that qualify for the
current Drug/Alcohol Induced Mental
Disorders comorbidity adjustment.
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These opioid disorder codes are listed
in Table 6. When we separately
analyzed these codes associated with
opioid disorder, the results suggested
that patients with opioid disorder are
significantly less expensive than
patients without opioid disorder.
Because stays with opioid disorders
make up the majority of stays in the
Drug/Alcohol Induced Mental Disorders
comorbidity category, we observe a
statistically-significant negative
adjustment factor for the comorbidity
category overall. The application of a
comorbidity adjustment derived from
our latest regression analysis would
result in reduced payments for all stays
in this comorbidity category. We do not
believe it is appropriate to apply
negative adjustment factors (that is,
adjustment factors less than 1.00) for
comorbidities because that would result
in reduced rather than increased
payments. Although we apply
adjustment factors less than 1.00 for
DRGs, this is because the DRG
adjustment reflects the cost of stays
relative to stays with the baseline DRG
885. In contrast, comorbidity
adjustments reflect the cost relative to a
stay with no comorbidities. A negative
payment adjustment would not be
consistent with the intent of a
comorbidity adjustment, which is
intended to provide additional
payments to providers to account for the
costs of treating patients with comorbid
conditions. Therefore, we have not
historically included any negative
adjustment factors for comorbid
conditions.
Therefore, we are proposing to
remove the Drug/Alcohol Induced
Mental Disorders comorbidity category
beginning in FY 2025. IPF stays that
include these codes as a non-principal
diagnosis would no longer receive the
current Drug/Alcohol Induced Mental
Disorders comorbidity category
adjustment factor of 1.03; nor would
they receive a reduction in payment.
However, many IPF stays that include
these ICD–10–CM diagnosis codes as a
principal diagnosis would continue to
receive a DRG adjustment. We refer
readers to section III.C.3.a of this
proposed rule for a detailed discussion
of proposed DRG adjustments under the
IPF PPS.
BILLING CODE 4120–01–P
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Table 6: ICD-10-CM Codes for Opioid Disorder
Fl 1259
Fll229
Fl 193
Fll251
Fl 1250
Fll29
Fl 1288
Fll220
Fll282
Fll921
Fll221
Fll951
Flll4
Fll94
Fll 151
Flll3
Flll0
Fll99
Fll929
Fll922
Description
Opioid dependence with withdrawal
Opioid dependence, uncomplicated
Opioid dependence with opioid-induced mood disorder
Opioid dependence w opioid-induced psychotic disorder, unsp
Opioid dependence with intoxication, unspecified
Opioid use, unspecified with withdrawal
Opioid depend w opioid-induc psychotic disorder w hallucin
Opioid depend w opioid-induc psychotic disorder w delusions
Opioid dependence with unspecified opioid-induced disorder
Opioid dependence with other opioid-induced disorder
Opioid dependence with intoxication, uncomplicated
Opioid dependence with opioid-induced sleep disorder
Opioid use, unspecified with intoxication delirium
Opioid dependence with intoxication delirium
Opioid use, unsp w opioid-induc psych disorder w hallucin
Opioid abuse with opioid-induced mood disorder
Opioid use, unspecified with opioid-induced mood disorder
Opioid abuse w opioid-induced psychotic disorder w hallucin
Opioid abuse with withdrawal
Opioid abuse, uncomplicated
Opioid use, unsp with unspecified opioid-induced disorder
Opioid use, unspecified with intoxication, unspecified
Opioid use, unsp w intoxication with perceptual disturbance
lotter on DSK11XQN23PROD with PROPOSALS2
BILLING CODE 4120–01–C
We believe removal of the Drug/
Alcohol Induced Mental Disorders
comorbidity category under the IPF PPS
would more appropriately align
payment with resource use, as reflected
in the latest regression results. As
previously discussed in section III.F of
this proposed rule, all of these proposed
revisions would be applied budgetneutrally. Therefore, we believe the
removal of the Drug/Alcohol Induced
Mental Disorders comorbidity
adjustment would appropriately
increase the IPF PPS Federal per diem
base rate and thereby increase payment
for IPF stays that are costlier. However,
we are soliciting comments on whether
a lack of ancillary charge data may be
contributing to the results of our
regression analysis as it relates to opioid
disorders. We note that our analysis of
the ICD–10–CM codes associated with
opioid disorder also indicates that there
is significant overlap between facility
characteristics and stays including
opioid disorder diagnoses. In particular,
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for-profit freestanding IPFs were found
to serve the majority of patients with
opioid disorders. As discussed in
section III.E.4 of this proposed rule, our
ongoing analysis has found an increase
in the number of for-profit freestanding
IPFs that are consistently reporting no
ancillary charges or very minimal
ancillary charges on their cost report. As
a result, we have previously noted that
data that is necessary for accurate
Medicare ratesetting is excluded from
the information these facilities are
reporting.
As stated previously, the regression
factor for Drug/Alcohol Induced Mental
Disorders was statistically significant,
but is less than 1, meaning payments
would be reduced if we applied it as a
comorbidity adjustment. We are
interested in understanding whether
there is data and information that could
better inform our understanding of the
costs of treating these conditions. In
addition, we are interested in
understanding whether commenters
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believe it may be more appropriate to
maintain the existing Drug/Alcohol
Induced Mental Disorders comorbidity
category adjustment factor of 1.03, given
that many providers that treat these
patients also report minimal or no
ancillary charges on their claims and
cost reports. We note that if we were to
maintain the adjustment factor of 1.03
for these IPF stays, we expect it would
have a negative impact on the
refinement standardization factor,
thereby slightly reducing the IPF PPS
Federal per diem base rate and ECT per
treatment amount.
We are also proposing to modify the
Eating and Conduct Disorders
comorbidity category and redesignate it
as the Eating Disorders comorbidity
category. That is, we are proposing to
remove conduct disorders from the
codes eligible for a comorbidity
adjustment. When we separately
analyzed the ICD–10–CM codes for
eating disorders (specifically, F5000
Anorexia nervosa, unspecified, F5001
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ICD-10-CM Code
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Fll20
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Anorexia nervosa, restricting type,
F5002 Anorexia nervosa, binge eating/
purging type, and F509 Eating disorder,
unspecified) and conduct disorders
(F631 Pyromania, F6381 Intermittent
explosive disorder, and F911 Conduct
disorder, childhood-onset type), our
regression results identified a positive,
statistically significant adjustment factor
associated with eating disorders. In
contrast, conduct disorders had a
negative and non-significant factor.
These results suggest that eating
disorders are associated with an
increased level of resource use
compared to conduct disorders, and that
only eating disorders have an increase
resource use at a level that is
statistically significant. Based on these
findings, we are proposing to remove
conduct disorders from the proposed
newly designated Eating Disorders
comorbidity category.
In addition, we are proposing to
modify the Chronic Obstructive
Pulmonary Disease comorbidity
category to include ICD–10–CM codes
associated with sleep apnea
(specifically, G4733 Obstructive sleep
apnea (adult) (pediatric), 5A09357
Assistance with Respiratory Ventilation,
<24 Hrs, CPAP, Z9981 Dependence on
supplemental oxygen, and Z9989
Dependence on other enabling
machines and devices). In response to
the FY 2023 and FY 2024 IPF PPS
proposed rules, commenters requested
that CMS analyze the additional cost
associated with patients with sleep
apnea. Patients with sleep apnea often
need to use a continuous positive
airway pressure (CPAP) machine with a
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cord to manage their condition. Based
on the clinical expertise of CMS
Medical Officers, we determined that
patients with sleep apnea in the IPF
setting would have increased ligature
risk (that is, anything that could be used
to attach a cord, rope, or other material
for the purpose of hanging or
strangulation), similar to the risk
associated with patients in the IPF
setting that have chronic obstructive
pulmonary disease. We expect the
additional staffing resources involved in
treating IPF patients with sleep apnea
would be similar to the resources
involved in treating IPF patients with
chronic obstructive pulmonary disease,
as patients with chronic obstructive
pulmonary disease may also require the
presence of an additional device with a
cord in the patient’s room, such as a
bilevel positive airway pressure (BiPAP)
machine. We evaluated adding codes
associated with sleep apnea to our
regression model, on the basis of our
expectation that we would observe
higher costs associated with these codes
that would be comparable to the costs
associated with chronic obstructive
pulmonary disease. The results of our
2019 through 2021 regression model
suggest that sleep apnea is in fact
associated with an increased level of
resource use. Therefore, we are
proposing to redesignate the Chronic
Obstructive Pulmonary Disease category
as the Chronic Obstructive Pulmonary
Disease and Sleep Apnea comorbidity
category.
Further, we analyzed costs associated
with the ICD–10–CM codes in Table 7
that indicate high-risk behavior. In
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response to the FY 2023 and FY 2024
IPF PPS proposed rules, commenters
requested that CMS analyze the
additional cost associated with patients
exhibiting violent behavior during their
stay in an IPF. We considered these
comments in coordination with CMS
Medical Officers, and determined that
patients exhibiting violent behavior
would require more intensive
management during an IPF stay. We
determined that certain ICD–10–CM
codes could describe the types of highrisk behaviors that require intensive
management during an IPF stay. These
could include patients exhibiting
violent behavior as well as other highrisk, non-violent behaviors. We
examined ICD–10–CM codes in the R45
code family (Symptoms and Signs
Related to Emotional State) that could
indicate high-risk behavior during an
IPF stay, which would lead to increased
resource use. The regression analysis
found that several codes, R451
Restlessness and agitation, R454
Irritability and anger, and R4584
Anhedonia codes are associated with a
statistically significant adjustment
factor. In other words, patients
presenting with restlessness and
agitation, irritability and anger, or
anhedonia are more costly than patients
who do not present these conditions.
Therefore, we are proposing to add a
new comorbidity category recognizing
the costs associated with Intensive
Management for High-Risk Behavior.
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Table 7:ICD-10-CM Codes for High-Risk Behavior Analyzed
ICD-10-
Description
Proposed Action for FY 2025
CM Code
Intensive Management for HighRisk Behavior Comotbidity
R45
Symptoms and signs involving emotional state
R450
Nervousness
R451
Restlessness and agitation
R452
Unhappiness
R453
Demoralization and apathy
R454
Irritability and anger
R455
Hostility
R456
Violent behavior
R457
State of emotional shock and stress, unspecified
R458
Other symptoms and signs involving emotional state
R4581
Low self-esteem
R4582
Worries
R4583
Excessive crying of child, adolescent or adult
R4584
Anhedonia
R4585
Homicidal and suicidal ideations
R45850
Homicidal ideations
R45851
Suicidal ideations
R4586
Emotional lability
R4587
Impulsiveness
R4589
Other symptoms and signs involving emotional state
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Add
Add
Lastly, we are proposing to maintain
the adjustment factors for the
Developmental Disabilities and
Uncontrolled Diabetes comorbidity
categories. Based on the regression
analysis, the Developmental Disabilities
comorbidity category adjustment factor
was not statistically significant;
however, the current adjustment factor
is within the confidence interval. As
discussed in section III.C.3.a of this
proposed rule, a non-statistically
significant adjustment factor within the
confidence interval indicates that the
current adjustment factor would be a
reasonable approximation of the
increased costs. The Uncontrolled
Diabetes comorbidity category
VerDate Sep<11>2014
Add
adjustment factor did not change from
the current adjustment factor based on
the 2019 through 2021 regression.
We are also proposing to decrease the
adjustment factors for the following
comorbidity categories: Renal Failure—
Acute, Artificial Openings—Digestive &
Urinary, Cardiac conditions, Renal
Failure—Chronic, Chronic Obstructive
Pulmonary Disease, Infectious Diseases,
and Severe Musculoskeletal &
Connective Tissue Diseases.
The regression analysis found the
Renal Failure—Acute, Artificial
Openings—Digestive & Urinary, Cardiac
conditions, Renal Failure—Chronic,
Chronic Obstructive Pulmonary Disease,
Infectious Diseases, and Severe
PO 00000
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Fmt 4701
Sfmt 4702
Musculoskeletal & Connective Tissue
Diseases comorbidity categories resulted
in a statistically significant adjustment
factor. While payment would still be
increased when the claim includes one
of these comorbidity categories, the
proposed adjustment factors for FY 2025
would be less than the current
adjustment factors for these categories.
The proposed FY 2025 comorbidity
adjustment factors are displayed in
Table 8, and can be found in Addendum
A, available on the CMS website at
https://www.cms.gov/medicare/
payment/prospective-payment-systems/
inpatient-psychiatric-facility/tools-andworksheets.
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Table 8: Comparison of FY 2024 and Proposed FY 2025 IPF PPS Comorbidity Category
Adjustments
Current Adjustment
Factor
1.11
Proposed FY 2025
Adjustment Factor
1.06
Artificial Openings - Digestive & Urinary
1.08
1.07
Cardiac Conditions
1.11
1.05
Renal Failure, Chronic
1.11
1.08
Renal Failure, Acute
Coagulation Factor Deficit
1.13
Chronic Obstructive Pulmonary Disease
1.12
NIA
NIA
Chronic Obstructive Pulmonary Disease and Sleep Apnea
1.07
Developmental Disabilities
1.04
1.04
Uncontrolled Diabetes
1.05
1.05
Drug/Alcohol Induced Mental Disorders
1.03
Eating and Conduct Disorders
1.12
NIA
NIA
NIA
Eating Disorders
1.09
Gangrene
1.10
Infectious Diseases
1.07
Severe Protein Malnutrition
1.13
1.17
Oncology Treatment
1.07
1.46
Poisoning
1.11
1.16
Severe Musculoskeletal & Connective Tissue Diseases
1.09
1.05
Tracheostomy
1.06
1.09
NIA
Intensive Management for High-Risk Behavior
BILLING CODE 4120–01–C
As discussed in section III.F of this
proposed rule, we are proposing to
implement revisions to the comorbidity
category adjustments budget-neutrally.
A detailed discussion of the
distributional impacts of these proposed
changes is found in section VIII.C of this
proposed rule.
We solicit comments on these
proposed revisions to the comorbidity
category adjustment factors. Lastly, we
are proposing that if more recent data
become available, we would use such
data, if appropriate, to determine the
final FY 2025 comorbidity category
adjustment factors.
lotter on DSK11XQN23PROD with PROPOSALS2
NIA
(2) Proposed Coding Updates for FY
2025
For FY 2025, we are proposing to add
2 ICD–10–CM/PCS codes to the
Oncology Treatment comorbidity
category. The proposed FY 2025
comorbidity codes are shown in
Addenda B, available on the CMS
website at https://www.cms.gov/
medicare/payment/prospectivepayment-systems/inpatient-psychiatricfacility/tools-and-worksheets.
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In accordance with the policy
established in the FY 2015 IPF PPS final
rule (79 FR 45949 through 45952), we
reviewed all new FY 2025 ICD–10–CM
codes to remove codes that were site
‘‘unspecified’’ in terms of laterality from
the FY 2023 ICD–10–CM/PCS codes in
instances where more specific codes are
available. As we stated in the FY 2015
IPF PPS final rule, we believe that
specific diagnosis codes that narrowly
identify anatomical sites where disease,
injury, or a condition exists should be
used when coding patients’ diagnoses
whenever these codes are available. We
finalized in the FY 2015 IPF PPS rule,
that we would remove site
‘‘unspecified’’ codes from the IPF PPS
ICD–10–CM/PCS codes in instances
when laterality codes (site specified
codes) are available, as the clinician
should be able to identify a more
specific diagnosis based on clinical
assessment at the medical encounter.
There were no proposed changes to the
FY 2025 ICD–10–CM/PCS codes,
therefore, we are not proposing to
remove any of the new codes.
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1.12
NIA
1.07
c. Proposed Patient Age Adjustments
As explained in the RY 2005 IPF PPS
final rule (69 FR 66922), we analyzed
the impact of age on per diem cost by
examining the age variable (range of
ages) for payment adjustments. In
general, we found that the cost per day
increases with age. The older age groups
are costlier than the under 45 age group,
the differences in per diem cost increase
for each successive age group, and the
differences are statistically significant.
While our regression analysis of CY
2019 through CY 2021 data supports
maintaining a payment adjustment
factor based on age as was established
in the RY 2005 IPF PPS final rule, the
results suggest that revisions to the
adjustment factor for age are warranted.
For FY 2025, we are proposing to
revise the patient age adjustments as
shown in Addendum A of this proposed
rule, which is available on the CMS
website at (see https://www.cms.gov/
medicare/payment/prospectivepayment-systems/inpatient-psychiatricfacility/tools-and-worksheets). We are
proposing to adopt the patient age
adjustments derived from the regression
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model using a blended set of 2019
through 2021 data, as discussed in
section III.C.3 of this proposed rule.
Table 9 summarizes the current and
proposed patient age adjustment factors
for FY 2025. As discussed in section
III.F of this proposed rule, we are
proposing to implement this revision to
the patient age adjustments budgetneutrally. A detailed discussion of the
distributional impacts of this proposed
change is found in section VIII.C of this
proposed rule.
We solicit comment on these
proposed revisions to the patient age
23171
adjustment factors. Lastly, we are
proposing that if more recent data
become available, we would use such
data, if appropriate, to determine the
final FY 2025 patient age adjustment
factors.
Table 9: Proposed Updates to Patient Age Adjustments
Current
#
%
Proposed
Adjustme
of
of
Adjustment
nt
Stays CY
Stays
Factors
Factors
2019-CY
CY
2021
2019-
Age (in years)
CY2021
1.00
1.01
50 and under 55
1.02
45 and under 55
NIA
121,498
15.06%
1.02
55 and under 60
1.04
74,512
9.24%
1.05
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1.00
60 and under 65
1.07
68,136
8.45%
1.07
1.10
94,473
11.71%
1.09
70 and under75
1.13
75 and under 80
1.15
70 and under 80
NIA
126,280
15.66%
1.12
80 and over
1.17
87,442
10.84%
1.13
We explained in the RY 2005 IPF PPS
final rule (69 FR 66946) that the
regression analysis indicated that per
diem cost declines as the LOS increases.
The variable per diem adjustments to
the Federal per diem base rate account
for ancillary and administrative costs
that occur disproportionately in the first
days after admission to an IPF. As
discussed in the RY 2005 IPF PPS final
rule, where a complete discussion of the
variable per diem adjustments can be
found, we used a regression analysis to
estimate the average differences in per
diem cost among stays of different
lengths (69 FR 66947 through 66950).
As a result of this analysis, we
established variable per diem
adjustments that begin on day 1 and
decline gradually until day 21 of a
patient’s stay. For day 22 and thereafter,
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29.04%
65 and under 70
d. Proposed Variable Per Diem
Adjustments
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the variable per diem adjustment
remains the same each day for the
remainder of the stay. However, the
adjustment applied to day 1 depends
upon whether the IPF has a qualifying
ED. If an IPF has a qualifying ED, it
receives a 1.31 adjustment factor for day
1 of each stay. If an IPF does not have
a qualifying ED, it receives a 1.19
adjustment factor for day 1 of the stay.
The ED adjustment is explained in more
detail in section III.D.4 of this proposed
rule.
For FY 2025, we are proposing to
revise the variable per diem adjustment
factors as indicated in the table below,
and shown in Addendum A to this rule,
which is available on the CMS website
at https://www.cms.gov/medicare/
payment/prospective-payment-systems/
inpatient-psychiatric-facility/tools-andworksheets. We are proposing to
increase the adjustment factors for days
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1 through 9. As shown in Table 10, the
results of the latest regression analysis
indicate that there is not a statistically
significant decrease in cost per day after
day 10; therefore, we are proposing that
days 10 and above would receive a 1.00
adjustment. Table 10 summarizes the
current and proposed variable per diem
adjustment factors for FY 2025. As
discussed in section III.F of this
proposed rule, we are proposing to
implement this revision to the variable
per diem adjustments budget-neutrally.
A detailed discussion of the
distributional impacts of this proposed
change is found in section VIII.C of this
proposed rule.
We solicit comments on these
proposed revisions to the variable per
diem adjustment factors. Lastly, we are
proposing that if more recent data
become available, we would use such
data, if appropriate, to determine the
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final FY 2025 variable per diem
adjustment factors.
Table 10: Proposed Updates to Variable Per Diem Adjustments
Description
Current
#
%
Proposed
Adjustment
of
of
Adjustment
Factors
Stays CY
Stays CY
Factors
2019-CY 2021
2019-CY
2021
Length of stay - 1 day
without ED
Length of stay - 1 day
1.19
17,141
2.09%
1.27
1.31
NIA
NIA
1.53
Length of stay - 2 days
1.12
28,370
3.52%
1.20
Length of stay - 3 days
1.08
42,298
5.24%
1.15
Length of stay - 4 days
1.05
48,187
5.97%
1.12
Length of stay - 5 days
1.04
54,187
6.72%
1.08
Length of stay - 6 days
1.02
59,215
7.34%
1.06
Length of stay - 7 days
1.01
63,095
7.82%
1.03
Length of stay - 8 days
1.01
51,491
6.38%
1.02
Length of stay - 9 days
1.00
42,855
5.31%
1.01
Length of stay - greater than or
eaual to 10 davs
1.00-0.92
400,022
49.59%
1.00
D. Proposed Updates to the IPF PPS
Facility-Level Adjustments
1. Wage Index Adjustment
The IPF PPS includes facility-level
adjustments for the wage index, IPFs
located in rural areas, teaching IPFs,
cost of living adjustments for IPFs
located in Alaska and Hawaii, and IPFs
with a qualifying ED. We are proposing
to use the existing regression-derived
facility-level adjustment factors
established in the RY 2005 IPF final rule
for FY 2025.
As previously discussed, in section
I.A of this proposed rule, we are
proposing to revise the methodology for
determining payments under the IPF
PPS as required by the CAA, 2023. We
are not proposing changes to the
facility-level adjustment factors for rural
location and teaching status for FY
2025; however, section IV.A of this
proposed rule includes a request for
information regarding potential future
updates to these facility-level
adjustments. We are particularly
interested in comments on the results of
our updated regression analysis as they
apply to facility-level adjustors.
As discussed in the RY 2007 IPF PPS
final rule (71 FR 27061), and the RY
2009 IPF PPS (73 FR 25719) and RY
2010 IPF PPS notices (74 FR 20373), to
provide an adjustment for geographic
wage levels, the labor-related portion of
an IPF’s payment is adjusted using an
appropriate wage index. Currently, an
IPF’s geographic wage index value is
determined based on the actual location
of the IPF in an urban or rural area, as
defined in § 412.64(b)(1)(ii)(A) and (C).
Due to the variation in costs and
because of the differences in geographic
wage levels, in the RY 2005 IPF PPS
final rule, we required that payment
rates under the IPF PPS be adjusted by
a geographic wage index. We proposed
and finalized a policy to use the
unadjusted, pre-floor, pre-reclassified
IPPS hospital wage index to account for
geographic differences in IPF labor
costs. We implemented use of the prefloor, pre-reclassified IPPS hospital
wage data to compute the IPF wage
index since there was not an IPF-
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a. Background
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specific wage index available. We
believe that IPFs generally compete in
the same labor market as IPPS hospitals
therefore, the pre-floor, pre-reclassified
IPPS hospital wage data should be
reflective of labor costs of IPFs. We
believe this pre-floor, pre-reclassified
IPPS hospital wage index to be the best
available data to use as proxy for an IPFspecific wage index. As discussed in the
RY 2007 IPF PPS final rule (71FR 27061
through 27067), under the IPF PPS, the
wage index is calculated using the IPPS
wage index for the labor market area in
which the IPF is located, without
considering geographic reclassifications,
floors, and other adjustments made to
the wage index under the IPPS. For a
complete description of these IPPS wage
index adjustments, we refer readers to
the FY 2019 IPPS/LTCH PPS final rule
(83 FR 41362 through 41390). Our wage
index policy at § 412.424(a)(2) provides
that we use the best Medicare data
available to estimate costs per day,
including an appropriate wage index to
adjust for wage differences.
When the IPF PPS was implemented
in the RY 2005 IPF PPS final rule, with
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an effective date of January 1, 2005, the
pre-floor, pre-reclassified IPPS hospital
wage index that was available at the
time was the FY 2005 pre-floor, prereclassified IPPS hospital wage index.
Historically, the IPF wage index for a
given RY has used the pre-floor, prereclassified IPPS hospital wage index
from the prior FY as its basis. This has
been due in part to the pre-floor, prereclassified IPPS hospital wage index
data that were available during the IPF
rulemaking cycle, where an annual IPF
notice or IPF final rule was usually
published in early May. This
publication timeframe was relatively
early compared to other Medicare
payment rules because the IPF PPS
follows a RY, which was defined in the
implementation of the IPF PPS as the
12-month period from July 1 to June 30
(69 FR 66927). Therefore, the best
available data at the time the IPF PPS
was implemented was the pre-floor, prereclassified IPPS hospital wage index
from the prior FY (for example, the RY
2006 IPF wage index was based on the
FY 2005 pre-floor, pre-reclassified IPPS
hospital wage index).
In the RY 2012 IPF PPS final rule, we
changed the reporting year timeframe
for IPFs from a RY to FY, which begins
October 1 and ends September 30 (76
FR 26434 through 26435). In that FY
2012 IPF PPS final rule, we continued
our established policy of using the prefloor, pre-reclassified IPPS hospital
wage index from the prior year (that is,
from FY 2011) as the basis for the FY
2012 IPF wage index. This policy of
basing a wage index on the prior year’s
pre-floor, pre-reclassified IPPS hospital
wage index has been followed by other
Medicare payment systems, such as
hospice and inpatient rehabilitation
facilities. By continuing with our
established policy, we remained
consistent with other Medicare payment
systems.
In FY 2020, we finalized the IPF wage
index methodology to align the IPF PPS
wage index with the same wage data
timeframe used by the IPPS for FY 2020
and subsequent years. Specifically, we
finalized the use of the pre-floor, prereclassified IPPS hospital wage index
from the FY concurrent with the IPF FY
as the basis for the IPF wage index. For
example, the FY 2020 IPF wage index
was based on the FY 2020 pre-floor, prereclassified IPPS hospital wage index
rather than on the FY 2019 pre-floor,
pre-reclassified IPPS hospital wage
index.
We explained in the FY 2020
proposed rule (84 FR 16973), that using
the concurrent pre-floor, pre-reclassified
IPPS hospital wage index will result in
the most up-to-date wage data being the
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basis for the IPF wage index. We noted
that it would also result in more
consistency and parity in the wage
index methodology used by other
Medicare payment systems. We
indicated that the Medicare skilled
nursing facility (SNF) PPS already used
the concurrent IPPS hospital wage index
data as the basis for the SNF PPS wage
index. We proposed and finalized
similar policies to use the concurrent
pre-floor, pre-reclassified IPPS hospital
wage index data in other Medicare
payment systems, such as hospice and
inpatient rehabilitation facilities. Thus,
the wage adjusted Medicare payments of
various provider types are based upon
wage index data from the same
timeframe. For FY 2025, we are
proposing to continue to use the
concurrent pre-floor, pre-reclassified
IPPS hospital wage index as the basis
for the IPF wage index.
In the FY 2023 IPF PPS final rule (87
FR 46856 through 46859), we finalized
a permanent 5-percent cap on any
decrease to a provider’s wage index
from its wage index in the prior year,
and we stated that we would apply this
cap in a budget neutral manner. In
addition, we finalized a policy that a
new IPF would be paid the wage index
for the area in which it is geographically
located for its first full or partial FY
with no cap applied because a new IPF
would not have a wage index in the
prior FY. We amended the IPF PPS
regulations at § 412.424(d)(1)(i) to reflect
this permanent cap on wage index
decreases. We refer readers to the FY
2023 IPF PPS final rule for a more
detailed discussion about this policy.
We are proposing to apply the IPF
wage index adjustment to the laborrelated share of the national IPF PPS
base rate and ECT payment per
treatment. The proposed labor-related
share of the IPF PPS national base rate
and ECT payment per treatment is 78.8
percent in FY 2025. This percentage
reflects the labor-related share of the
2021-based IPF market basket for FY
2025 and is 0.1 percentage point higher
than the FY 2024 labor-related share
(see section III.A.3 of this proposed
rule).
b. Office of Management and Budget
(OMB) Bulletins
(1) Background
The wage index used for the IPF PPS
is calculated using the unadjusted, prereclassified and pre-floor IPPS wage
index data and is assigned to the IPF
based on the labor market area in which
the IPF is geographically located. IPF
labor market areas are delineated based
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on the Core-Based Statistical Area
(CBSAs) established by the OMB.
Generally, OMB issues major
revisions to statistical areas every 10
years, based on the results of the
decennial census. However, OMB
occasionally issues minor updates and
revisions to statistical areas in the years
between the decennial censuses through
OMB Bulletins. These bulletins contain
information regarding CBSA changes,
including changes to CBSA numbers
and titles. OMB bulletins may be
accessed online at https://
www.whitehouse.gov/omb/informationfor-agencies/bulletins/. In accordance
with our established methodology, the
IPF PPS has historically adopted any
CBSA changes that are published in the
OMB bulletin that corresponds with the
IPPS hospital wage index used to
determine the IPF wage index and,
when necessary and appropriate, has
proposed and finalized transition
policies for these changes.
In the RY 2007 IPF PPS final rule (71
FR 27061 through 27067), we adopted
the changes discussed in the OMB
Bulletin No. 03–04 (June 6, 2003),
which announced revised definitions
for Metropolitan Statistical Areas
(MSAs), and the creation of
Micropolitan Statistical Areas and
Combined Statistical Areas. In adopting
the OMB CBSA geographic designations
in RY 2007, we did not provide a
separate transition for the CBSA-based
wage index since the IPF PPS was
already in a transition period from
TEFRA payments to PPS payments.
In the RY 2009 IPF PPS notice, we
incorporated the CBSA nomenclature
changes published in the most recent
OMB bulletin that applied to the IPPS
hospital wage index used to determine
the current IPF wage index and stated
that we expected to continue to do the
same for all the OMB CBSA
nomenclature changes in future IPF PPS
rules and notices, as necessary (73 FR
25721).
Subsequently, CMS adopted the
changes that were published in past
OMB bulletins in the FY 2016 IPF PPS
final rule (80 FR 46682 through 46689),
the FY 2018 IPF PPS rate update (82 FR
36778 through 36779), the FY 2020 IPF
PPS final rule (84 FR 38453 through
38454), and the FY 2021 IPF PPS final
rule (85 FR 47051 through 47059). We
direct readers to each of these rules for
more information about the changes that
were adopted and any associated
transition policies.
As discussed in the FY 2023 IPF PPS
final rule, we did not adopt OMB
Bulletin 20–01, which was issued
March 6, 2020, because we determined
this bulletin had no material impact on
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the IPF PPS wage index. This bulletin
creates only one Micropolitan statistical
area, and Micropolitan areas are
considered rural for the IPF PPS wage
index. That is, the constituent county of
the new Micropolitan area was
considered rural effective as of FY 2021
and would continue to be considered
rural if we adopted OMB Bulletin 20–
01.
Finally, on July 21, 2023, OMB issued
Bulletin 23–01, which revises the CBSA
delineations based on the latest
available data from the 2020 census.
This bulletin contains information
regarding updates of statistical area
changes to CBSA titles, numbers, and
county or county equivalents.
(2) Proposed Implementation of New
Labor Market Area Delineations
We believe it is important for the IPF
PPS to use, as soon as is reasonably
possible, the latest available labor
market area delineations to maintain a
more accurate and up-to-date payment
system that reflects the reality of
population shifts and labor market
conditions. We believe that using the
most current delineations would
increase the integrity of the IPF PPS
wage index system by creating a more
accurate representation of geographic
variations in wage levels. We have
carefully analyzed the impacts of
adopting the new OMB delineations and
find no compelling reason to delay
implementation. Therefore, we are
proposing to implement the new OMB
delineations as described in the July 21,
2023, OMB Bulletin No. 23–01, effective
beginning with the FY 2025 IPF PPS
wage index. We are proposing to adopt
the updates to the OMB delineations
announced in OMB Bulletin No. 23–01
effective for FY 2025 under the IPF PPS.
As previously discussed, we finalized
a 5-percent permanent cap on any
decrease to a provider’s wage index
from its wage index in the prior year.
For more information on the permanent
5-percent cap policy, we refer readers to
the FY 2023 IPF PPS final rule (87 FR
46856 through 46859). In addition, we
are proposing to phase out the rural
adjustment for IPFs that are
transitioning from rural to urban based
on these CBSA revisions, as discussed
in section III.D.1.c. of this proposed
rule.
(a) Micropolitan Statistical Areas
OMB defines a ‘‘Micropolitan
Statistical Area’’ as a CBSA associated
with at least one urban cluster that has
a population of at least 10,000, but less
than 50,000 (75 FR 37252). We refer to
these as Micropolitan Areas. After
extensive impact analysis, consistent
with the treatment of these areas under
the IPPS as discussed in the FY 2005
IPPS final rule (69 FR 49029 through
49032), we determined the best course
of action would be to treat Micropolitan
Areas as ‘‘rural’’ and include them in
the calculation of each state’s IPF PPS
rural wage index. We refer readers to the
FY 2007 IPF PPS final rule (71 FR 27064
through 27065) for a complete
discussion regarding treating
Micropolitan Areas as rural. We are not
proposing any changes to this policy for
FY 2025.
(b) Change to County-Equivalents in the
State of Connecticut
The June 6, 2022 Census Bureau
Notice (87 FR 34235 through 34240),
OMB Bulletin No. 23–01 replaced the 8
counties in Connecticut with 9 new
‘‘Planning Regions.’’ Planning regions
now serve as county-equivalents within
the CBSA system. We have evaluated
the changes and are proposing to adopt
the planning regions as county
equivalents for wage index purposes.
We believe it is necessary to adopt this
migration from counties to planning
region county-equivalents to maintain
consistency with OMB updates. We are
providing the following crosswalk for
each county in Connecticut with the
current and proposed FIPS county and
county-equivalent codes and CBSA
assignments.
Table 11: Change to County-Equivalents in the State of Connecticut
Current County
09003 HARTFORD
25540
09015 WINDHAM
49340
09005 LITCHFIELD
7
09001 FAIRFIELD
14860
09001 FAIRFIELD
14860
09011 NEWLONDON
35980
09013 TOLLAND
25540
09009 NEWHAVEN
35300
09009 NEWHAVEN
35300
09007 MIDDLESEX
25540
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Proposed Planning
Proposed
Region Area (County
FIPS
Equivalent)
09110
CAPITOL
NORTHEASTERN
09150
CONNECTICUT
NORTHWEST
09160
HILLS
WESTERN
09190
CONNECTICUT
GREATER
09120
BRIDGEPORT
SOUTHEASTERN
09180
CONNECTICUT
09110
CAPITOL
NAUGATUCK
09140
VALLEY
SOUTH CENTRAL
09170
CONNECTICUT
LOWER
09130
CONNECTICUT
RIVER VALLEY
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7
7
14860
14860
35980
25540
47930
35300
25540
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Current
CBSA
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(c) Urban Counties That Would Become
Rural Under the Revised OMB
Delineations
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As previously discussed, we are
proposing to implement the new OMB
labor market area delineations (based
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upon OMB Bulletin No. 23–01)
beginning in FY 2025. Our analysis
shows that a total of 53 counties (and
county equivalents) and 15 providers
are located in areas that were previously
considered part of an urban CBSA but
would be considered rural beginning in
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FY 2025 under these revised OMB
delineations. Table 12 lists the 53 urban
counties that would be rural if we
finalize our proposal to implement the
revised OMB delineations.
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Table 12: Counties Previously Considered Part of an Urban CBSA that Would Become
Rural Areas Under Revised 0MB Delineations
VerDate Sep<11>2014
01129
County /County
Eauivalent
WASHINGTON
AL
33660
Labor Market Area
Mobile, AL
05025
CLEVELAND
AR
38220
Pine Bluff, AR
05047
FRANKLIN
AR
22900
Fort Smith, AR-OK
05069
JEFFERSON
AR
38220
Pinc Bluff, AR
05079
LINCOLN
AR
38220
Pine Bluff, AR
10005
SUSSEX
DE
41540
Salisbury, MD-DE
13171
LAMAR
GA
12060
16077
POWER
ID
38540
Atlanta-Sandy Springs-Alpharetta,
GA
Pocatello, ID
17057
FULTON
IL
37900
Peoria, IL
17077
JACKSON
IL
16060
Carbondale-Marion, IL
17087
JOHNSON
IL
16060
Carbondale-Marion, IL
17183
VERMILION
IL
19180
Danville, IL
17199
WILLIAMSON
IL
16060
Carbondale-Marion, IL
18121
PARKE
IN
45460
Terre Haute, IN
18133
PUTNAM
IN
26900
Indianapolis-Cannel-Anderson, IN
18161
UNION
IN
17140
Cincinnati, OH-KY-IN
21091
HANCOCK
KY
36980
Owensboro, KY
21101
HENDERSON
KY
21780
Evansville, TN-KY
22045
IBERIA
LA
29180
Lafayette, LA
24001
ALLEGANY
MD
19060
Cumberland, MD-WV
24047
WORCESTER
MD
41540
Salisbury, MD-DE
25011
FRANKLIN
MA
44140
Springfield, MA
26155
SHIAWASSEE
MT
29620
Lansing-East Lansing, MT
27075
LAKE
MN
20260
Duluth, MN-WI
28031
COVINGTON
MS
25620
Hattiesburg, MS
31051
DIXON
NE
43580
Sioux City, IA-NE-SD
36123
YATES
NY
40380
Rochester, NY
37049
CRAVEN
NC
35100
New Bem,NC
37077
GRANVILLE
NC
20500
Durham-Chapel Hill, NC
37085
HARNETT
NC
22180
Fayetteville, NC
37087
HAYWOOD
NC
11700
Asheville, NC
37103
JONES
NC
35100
NewBem,NC
37137
PAMLICO
NC
35100
New Bem,NC
42037
COLUMBIA
PA
14100
Bloomsburg-Berwick, PA
42085
MERCER
PA
49660
42089
MONROE
PA
20700
Youngstown-Warren-Boardman,
OH-PA
East Stroudsburg, PA
42093
MONTOUR
PA
14100
Bloomsburg-Berwick, PA
18:57 Apr 02, 2024
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42103
County/County
Eauivalent
PIKE
PA
35084
Labor Market Area
Newark, NJ-PA
45027
CLARENDON
SC
44940
Sumter, SC
48431
STERLING
TX
41660
San Angelo, TX
49003
BOXELDER
UT
36260
Ogden-Clearfield, UT
51113
MADISON
VA
47894
51175
SOUTHAMPTON
VA
47260
51620
FRANKLIN CITY
VA
47260
54035
JACKSON
WV
16620
Washington-Arlington-Alexandria,
DC-VA-MD-WV
Virginia Beach-Norfolk-Newport
News VA-NC
Virginia Beach-Norfolk-Newport
News VA-NC
Charleston, WV
54043
LINCOLN
WV
16620
Charleston, WV
54057
MINERAL
WV
19060
Cumberland, MD-WV
55069
LINCOLN
WI
48140
Wausau-Weston, WI
72001
ADJUNTAS
PR
38660
Ponce,PR
72055
GUANICA
PR
49500
Yauco,PR
72081
LARES
PR
10380
Aguadilla-Isabela, PR
72083
LASMARIAS
PR
32420
Mayagiiez, PR
72141
UTUADO
PR
10380
Aguadilla-Isabela, PR
lotter on DSK11XQN23PROD with PROPOSALS2
We are proposing that the wage data
for all providers located in the counties
listed above would now be considered
rural, beginning in FY 2025, when
calculating their respective state’s rural
wage index. This rural wage index value
would also be used under the IPF PPS.
We recognize that rural areas typically
have lower area wage index values than
urban areas, and providers located in
these counties may experience a
negative impact in their IPF payment
due to the proposed adoption of the
revised OMB delineations. However, as
discussed in section III.D.1.c of this
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State
Current CBSA
proposed rule, providers located in
these counties would receive a rural
adjustment beginning in FY 2025,
which would mitigate the impact of
decreases to the wage index for these
providers. In addition, the permanent 5percent cap on wage index decreases
under the IPF PPS would further
mitigate large wage index decreases for
providers in these areas.
(d) Rural Counties That Would Become
Urban Under the Revised OMB
Delineations
As previously discussed, we are
proposing to implement the new OMB
PO 00000
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labor market area delineations (based
upon OMB Bulletin No. 23–01)
beginning in FY 2025. Analysis of these
OMB labor market area delineations
shows that a total of 54 counties (and
county equivalents) and 10 providers
are located in areas that were previously
considered rural but would now be
considered urban under the revised
OMB delineations. Table 13 lists the 54
rural counties that would be urban if we
finalize our proposal to implement the
revised OMB delineations.
E:\FR\FM\03APP2.SGM
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23177
23178
Federal Register / Vol. 89, No. 65 / Wednesday, April 3, 2024 / Proposed Rules
Table 13: Counties that Would Gain Urban Status Under Revised 0MB Delineations
01087
County/County
EQuivalent
Macon
01127
Walker
AL
13820
Birmingham, AL
12133
Washington
FL
37460
Panama City-Panama City Beach, FL
13187
Lumpkin
GA
12054
Atlanta-Sandy Springs-Roswell, GA
15005
17053
Kalawao
Ford
HI
IL
27980
16580
Kahului-Wailuku HI
Champaign-Urbana, IL
17127
Massac
IL
37140
Paducah, KY-IL
18159
Tipton
IN
26900
Indianapolis-Carmel-Greenwood, IN
18179
Wells
IN
23060
Fort Wayne, IN
20021
Cherokee
KS
27900
Joplin, MO-KS
21007
Ballard
KY
37140
Paducah, KY-IL
21039
Carlisle
KY
37140
Paducah, KY-IL
21127
Lawrence
KY
26580
Huntington-Ashland, WV-KY-OH
21139
Livingston
KY
37140
Paducah, KY-IL
21145
Mc Craken
KY
37140
Paducah, KY-IL
21179
Nelson
KY
31140
Louisville/Jefferson County, KY-IN
22053
Jefferson Davis
LA
29340
Lake Charles, LA
22083
Richland
LA
33740
Monroe,LA
26015
Barry
MI
24340
Grand Rapids-Wyoming-Kentwood, MI
26019
Benzie
MI
45900
Traverse City, MI
26055
Grand Traverse
MI
45900
Traverse City, MI
26079
Kalkaska
MI
45900
Traverse City, MI
26089
Leelanau
MI
45900
Traverse City, MI
27133
Rock
MN
43620
Sioux Falls, SD-MN
28009
Benton
MS
32820
Memphis, TN-MS-AR
28123
Scott
MS
27140
Jackson,MS
30007
Broadwater
MT
25740
Helena, MT
30031
Gallatin
MT
14580
Bozeman,MT
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New
CBSA
AL
12220
Auburn-Opelika, AL
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State
New
CBSA
30043
County/County
EQuivalent
Jefferson
MT
25740
Helena, MT
30049
Lewis and Clark
MT
25740
Helena, MT
30061
Mineral
MT
33540
Missoula, MT
32019
Lyon
NV
39900
Reno,NV
37125
Moore
NC
38240
Pinehurst-Southern Pines, NC
38049
McHenry
ND
33500
Minot,ND
38075
Renville
ND
33500
Minot,ND
38101
Ward
ND
33500
Minot, ND
39007
Ashtabula
OH
17410
Cleveland, OH
39043
Erie
OH
41780
Sandusky, OH
41013
Crook
OR
13460
Bend,OR
41031
Jefferson
OR
13460
Bend,OR
42073
Lawrence
PA
38300
Pittsburgh, PA
45087
Union
SC
43900
Spartanburg, SC
46033
Custer
SD
39660
Rapid City, SD
47081
Hickman
TN
34980
Nashville-Davidson--Murfreesboro--Franklin, TN
48007
Aransas
TX
18580
Corpus Christi, TX
48035
Bosque
TX
47380
Waco, TX
48079
Cochran
TX
31180
Lubbock, TX
48169
Garza
TX
31180
Lubbock, TX
48219
Hockley
TX
31180
Lubbock, TX
48323
Maverick
TX
20580
Eagle Pass, TX
48407
San Jacinto
TX
26420
Houston-Pasadena-The Woodlands, TX
51063
Floyd
VA
13980
Blacksburg-Christiansburg-Radford, VA
51181
Surry
VA
47260
Virginia Beach-Chesapeake-Norfolk, VA-NC
55123
Vernon
Wl
29100
La Crosse-Onalaska, WI-MN
We are proposing that when
calculating the area wage index,
beginning with FY 2025, the wage data
for providers located in these counties
would be included in their new
respective urban CBSAs. Typically,
providers located in an urban area
receive a wage index value higher than
or equal to providers located in their
state’s rural area. We also note that
providers located in these areas would
no longer be considered rural beginning
in FY 2025. We refer readers to section
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Labor Market Area
III.D.1.c of this proposed rule for a
discussion of the proposed policy to
phase out the payment of the rural
adjustment for providers in these areas.
(e) Urban Counties That Would Move to
a Different Urban CBSA Under the New
OMB Delineations
In certain cases, adopting the new
OMB delineations would involve a
change only in CBSA name and/or
number, while the CBSA continues to
encompass the same constituent
counties. For example, CBSA 10540
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Sfmt 4702
(Albany-Lebanon, OR) would
experience a change to its name, and
become CBSA 10540 (Albany, OR),
while its one constituent county would
remain the same. Table 14 shows the
current CBSA code and our proposed
CBSA code where we are proposing to
change either the name or CBSA
number only. We are not discussing
further in this section these proposed
changes because they are
inconsequential changes with respect to
the IPF PPS wage index.
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23180
Federal Register / Vol. 89, No. 65 / Wednesday, April 3, 2024 / Proposed Rules
Table 14: Current CBSAs and their New CBSA Codes and Titles
10540
12420
12540
15260
16540
16984
19430
19740
21820
22660
23224
24860
25940
26380
29820
31020
34740
35840
36084
36540
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39340
39540
41620
42680
42700
44420
44700
47220
48300
48424
Current CBSA Title
Albany-Lebanon, OR
Austin-Round RockGeorgetown, TX
Bakersfield, CA
Brunswick, GA
ChambersburgWaynesboro, PA
Chicago-NapervilleEvanston, IL
Dayton-Kettering, OH
Denver-AuroraLakewood, CO
Fairbanks, AK
Fort Collins, CO
Frederick-GaithersburgRockville MD
Greenville-Anderson, SC
Hilton Head IslandBluffton, SC
Houma-Thibodaux, LA
Las Vegas-HendersonParadise NV
Longview, WA
Muskegon, MI
North Port-SarasotaBradenton, FL
Oakland-BerkeleyLivermore, CA
Omaha-Council Bluffs,
NE-IA
Provo-Orem, UT
Racine, WI
Salt Lake City, UT
Sebastian-Vero Beach,
FL
Sebring-Avon Park, FL
Staunton, VA
Stockton, CA
Vineland-Bridgeton, NJ
Wenatchee, WA
West Palm Beach-Boca
Raton-Boynton Beach,
FL
In some cases, if we adopt the new
OMB delineations, counties would shift
between existing and new CBSAs,
VerDate Sep<11>2014
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18:57 Apr 02, 2024
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Proposed CBSA Title
10540
12420
Albany, OR
Austin-Round Rock-San Marcos, TX
12540
15260
16540
Brunswick-St. Simons, GA
16984
Chicago-Naperville-Schaumburg, lL
19430
19740
Dayton-Kettering-Beavercreek, OH
21820
22660
23224
Fairbanks-College, AK
Frederick-Gaithersburg-Bethesda, MD
24860
25940
Hilton Head Island-Bluffton-Port Royal, SC
26380
29820
Bakersfield-Delano, CA
Chambersburg, PA
Denver-Aurora-Centennial, CO
Fort Collins-Loveland, CO
Greenville-Anderson-Greer, SC
Houma-Bayou Cane-Thibodaux, LA
Las Vegas-Henderson-North Las Vegas, NV
31020
34740
35840
North Port-Bradenton-Sarasota, FL
36084
Oakland-Fremont-Berkeley, CA
36540
Omaha, NE-IA
39340
39540
41620
42680
Provo-Orem-Lehi, UT
42700
44420
44700
47220
48300
48424
Longview-Kelso, WA
Muskegon-Norton Shores, MI
Racine-Mount Pleasant, WI
Salt Lake City-Murray, UT
Sebastian-Vero Beach-West Vero Corridor, FL
Sebring, FL
Staunton-Stuarts Draft, VA
Stockton-Lodi, CA
Vineland, NJ
Wenatchee-East Wenatchee, WA
West Palm Beach-Boca Raton-Delray Beach, FL
changing the constituent makeup of the
CBSAs. We consider this type of change,
where CBSAs are split into multiple
PO 00000
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Fmt 4701
Sfmt 4702
new CBSAs, or a CBSA loses one or
more counties to another urban CBSA to
be significant modifications.
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Federal Register / Vol. 89, No. 65 / Wednesday, April 3, 2024 / Proposed Rules
Table 15 lists the urban counties that
would move from one urban CBSA to
another newly proposed or modified
23181
CBSA if we adopted the new OMB
delineations.
Table 15: Urban Counties That Would Move to a Newly Proposed or Modified CBSA
Under Revised 0MB Delineations
County Name
State
Current
CBSA
06039
MADERA
CA
31460
11001
THE DISTRICT
DC
47894
12053
HERNANDO
FL
45300
12057
HILLSBOROUGH
FL
45300
12101
PASCO
FL
45300
12103
PINELLAS
FL
45300
12119
SUMTER
FL
45540
13013
BARROW
GA
12060
13015
BARTOW
GA
12060
13035
BUTTS
GA
12060
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Current
CBSA
Name
Madera, CA
Proposed
CBSACode
23420
Fresno, CA
Washington
-ArlingtonAlexandria,
DC-VAMD-WV
Tampa-St.
PetersburgClearwater,
FL
Tampa-St.
PetersburgClearwater,
FL
Tampa-St.
PetersburgClearwater,
FL
Tampa-St.
PetersburgClearwater,
FL
The
Villages. FL
AtlantaSandy
SpringsAlpharetta,
GA
AtlantaSandy
SpringsAlpharetta,
GA
AtlantaSandy
SpringsAlpharetta,
GA
47764
Washington, DCMD
45294
Tampa,FL
45294
Tampa,FL
45294
Tampa,FL
41304
St. PetersburgClearwater-Largo,
FL
48680
12054
Wildwood-The
Villages. FL
Atlanta-Sandy
Springs-Roswell,
GA
31924
Marietta, GA
12054
Atlanta-Sandy
Springs-Roswell,
GA
Sfmt 4725
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Proposed CBSA
Name
EP03AP24.020
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Code
23182
Federal Register / Vol. 89, No. 65 / Wednesday, April 3, 2024 / Proposed Rules
VerDate Sep<11>2014
County Name
Stale
Current
CBSA
13045
CARROLL
GA
12060
13057
CHEROKEE
GA
12060
13063
CLAYTON
GA
12060
13067
COBB
GA
12060
13077
COWETA
GA
12060
13085
DAWSON
GA
12060
13089
DEKALB
GA
12060
13097
DOUGLAS
GA
12060
13113
FAYETTE
GA
12060
13117
FORSYTH
GA
12060
13121
FULTON
GA
12060
18:57 Apr 02, 2024
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Current
CBSA
Name
AtlantaSandy
SpringsAlpharetta,
GA
AtlantaSandy
SpringsAlpharetta,
GA
AtlantaSandy
SpringsAlpharetta,
GA
AtlantaSandy
SpringsAlpharetta,
GA
AtlantaSandy
SpringsAlpharetta,
GA
AtlantaSandy
SpringsAlpharetta,
GA
AtlantaSandy
SpringsAlpharetta,
GA
AtlantaSandy
SpringsAlpharetta,
GA
AtlantaSandy
SpringsAlpharetta,
GA
AtlantaSandy
SpringsAlpharetta,
GA
AtlantaSandy
SpringsAlpharetta,
GA
Sfmt 4725
Proposed
CBSACode
Proposed CBSA
Name
12054
Atlanta-Sandy
Springs-Roswell,
GA
31924
Marietta, GA
12054
Atlanta-Sandy
Springs-Roswell,
GA
31924
Marietta, GA
12054
Atlanta-Sandy
Springs-Roswe11,
GA
12054
Atlanta-Sandy
Springs-Roswell,
GA
12054
Atlanta-Sandy
Springs-Roswell,
GA
12054
Atlanta-Sandy
Springs-Roswell,
GA
12054
Atlanta-Sandy
Springs-Roswell,
GA
12054
Atlanta-Sandy
Springs-Roswell,
GA
12054
Atlanta-Sandy
Springs-Roswell,
GA
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Federal Register / Vol. 89, No. 65 / Wednesday, April 3, 2024 / Proposed Rules
VerDate Sep<11>2014
County Name
Stale
Current
CBSA
13135
GWINNETT
GA
12060
13143
HARALSON
GA
12060
13149
HEARD
GA
12060
13151
HENRY
GA
12060
13159
JASPER
GA
12060
13199
MERIWETHER
GA
12060
13211
MORGAN
GA
12060
13217
NEWTON
GA
12060
13223
PAULDING
GA
12060
13227
PICKENS
GA
12060
13231
PIKE
GA
12060
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Current
CBSA
Name
AtlantaSandy
SpringsAlpharetta,
GA
AtlantaSandy
SpringsAlpharetta,
GA
AtlantaSandy
SpringsAlpharetta,
GA
AtlantaSandy
SpringsAlpharetta,
GA
AtlantaSandy
SpringsAlpharetta,
GA
AtlantaSandy
SpringsAlpharetta,
GA
AtlantaSandy
SpringsAlpharetta,
GA
AtlantaSandy
SpringsAlpharetta,
GA
AtlantaSandy
SpringsAlpharetta,
GA
AtlantaSandy
SpringsAlpharetta,
GA
AtlantaSandy
SpringsAlpharetta,
GA
Sfmt 4725
Proposed
CBSACode
Proposed CBSA
Name
12054
Atlanta-Sandy
Springs-Roswell,
GA
31924
Marietta, GA
12054
Atlanta-Sandy
Springs-Roswell,
GA
12054
Atlanta-Sandy
Springs-Roswell,
GA
12054
Atlanta-Sandy
Springs-Roswe11,
GA
12054
Atlanta-Sandy
Springs-Roswell,
GA
12054
Atlanta-Sandy
Springs-Roswell,
GA
12054
Atlanta-Sandy
Springs-Roswell,
GA
31924
Marietta, GA
12054
Atlanta-Sandy
Springs-Roswell,
GA
12054
Atlanta-Sandy
Springs-Roswell,
GA
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Code
23183
23184
Federal Register / Vol. 89, No. 65 / Wednesday, April 3, 2024 / Proposed Rules
VerDate Sep<11>2014
County Name
13247
ROCKDALE
GA
12060
13255
SPALDING
GA
12060
13297
WALTON
GA
12060
18073
JASPER
IN
23844
Current
CBSA
Name
AtlantaSandy
SpringsAlpharetta,
GA
AtlantaSandy
SpringsAlpharetta,
GA
AtlantaSandy
SpringsAlpharetta,
GA
Gary,IN
18089
LAKE
IN
23844
Gary, IN
29414
18111
NEWTON
IN
23844
Gary, IN
29414
18127
PORTER
IN
23844
Gary, IN
29414
21163
MEADE
KY
21060
31140
22103
ST.TAMMANY
LA
35380
25015
HAMPSHIRE
MA
44140
24009
CALVERT
MD
47894
24017
CHARLES
MD
47894
24033
PRINCE GEORGES
MD
47894
24037
ST.MARYS
MD
15680
37019
BRUNSWICK
NC
34820
Elizabethto
wn-Fort
Knox,KY
New
OrleansMetairie,
LA
Springfield,
MA
Washington
-ArlingtonAlexandria,
DC-VAMD-WV
Washington
-ArlingtonAlexandria,
DC-VAMD-WV
Washington
-ArlingtonAlexandria,
DC-VAMD-WV
CaliforniaLexington
Park,MD
Myrtle
Beach-
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State
Current
CBSA
Frm 00040
Fmt 4701
Sfmt 4725
Proposed
CBSACode
Proposed CBSA
Name
12054
Atlanta-Sandy
Springs-Roswell,
GA
12054
Atlanta-Sandy
Springs-Roswell,
GA
12054
Atlanta-Sandy
Springs-Roswell,
GA
29414
Lake County-Porter
County-Jasper
Countv. IN
Lake County-Porter
County-Jasper
Countv, IN
Lake County-Porter
County-Jasper
Countv, IN
Lake County-Porter
County-Jasper
Countv, IN
Louisville/Jefferson
County, KY-IN
43640
Slidell-MandevilleCovington, LA
11200
Amherst TownNorthamnton. MA
Lexington Parle, MD
30500
47764
Washington, DCMD
47764
Washington, DCMD
30500
Lexington Parle, MD
48900
Wilmington, NC
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Federal Register / Vol. 89, No. 65 / Wednesday, April 3, 2024 / Proposed Rules
VerDate Sep<11>2014
County Name
State
Current
CBSA
34009
CAPEMAY
NJ
36140
34023
MIDDLESEX
NJ
35154
34025
MONMOUTH
NJ
35154
34029
OCEAN
NJ
35154
34035
SOMERSET
NJ
35154
36027
DUTCHESS
NY
39100
36071
ORANGE
NY
39100
39035
CUYAHOGA
OH
17460
39055
GEAUGA
OH
17460
39085
LAKE
OH
17460
39093
LORAIN
OH
17460
39103
MEDINA
OH
17460
39123
OTTAWA
OH
45780
72023
CABOROJO
PR
41900
72059
GUAYANlLLA
PR
49500
72079
LAJAS
PR
41900
72111
PENUELAS
PR
49500
72121
SABANA GRANDE
PR
41900
72125
SAN GERMAN
PR
41900
18:57 Apr 02, 2024
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Current
CBSA
Name
ConwayNorth
Myrtle
Beach, SCNC
Ocean City,
NJ
New
BrunswickLakewood,
NJ
New
BrunswickLakewood,
NJ
New
BrunswickLakewood,
NJ
New
BrunswickLakewood,
NJ
Poughkeepsi
eNewburghMiddletown,
NY
Poughkeepsi
eNewburghMiddletown,
NY
ClevelandElvria OH
ClevelandElyria OH
ClevelandElvria OH
ClevelandElvria OH
ClevelandElvria, OH
Toledo, OH
Proposed
CBSACode
41780
Sandusky, OH
San
German.PR
Yauco,PR
32420
Mayagiicz, PR
38660
Ponce,PR
San
German,PR
Yauco, PR
32420
Mayagiiez, PR
38660
Ponce,PR
San
German,PR
San
German,PR
32420
Mayagiiez, PR
32420
Mayagiiez, PR
Sfmt 4725
12100
29484
Proposed CBSA
Name
Atlantic CityHammonton, NJ
Lakewood-New
Brunswick, NJ
29484
Lakewood-New
Brunswick, NJ
29484
Lakewood-New
Brunswick, NJ
29484
Lakewood-New
Brunswick, NJ
28880
Kiryas JoelPoughkeepsieNewburgh, NY
28880
Kiryas JoelPoughkeepsieNewburgh, NY
17410
Cleveland, OH
17410
Cleveland, OH
17410
Cleveland, OH
17410
Cleveland, OH
17410
Cleveland, OH
E:\FR\FM\03APP2.SGM
03APP2
EP03AP24.024
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County
Code
23185
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VerDate Sep<11>2014
County Name
State
Current
CBSA
72153
YAUCO
PR
49500
47057
GRAINGER
TN
34100
51510
ALEXANDRIA CITY
VA
47894
51013
ARLINGTON
VA
47894
51043
CLARKE
VA
47894
51047
CULPEPER
VA
47894
51059
FAIRFAX
VA
47894
51600
FAIRFAX CITY
VA
47894
51610
FALLS CHURCH
CITY
VA
47894
51061
FAUQUIER
VA
47894
51630
FREDERICKSBURG
CITY
VA
47894
51107
LOUDOUN
VA
47894
51683
MANASSAS CITY
VA
47894
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Current
CBSA
Name
Yauco,PR
Proposed
CBSACode
38660
Ponce,PR
Morristown,
TN
Washington
-ArlingtonAlexandria,
DC-VAMD-WV
Wasfilllb'1:0n
-Arlini,'1:onAlexandria,
DC-VAMD-WV
Washington
-ArlingtonAlexandria,
DC-VAMD-WV
Washington
-ArlingtonAlexandria,
DC-VAMD-WV
Washington
-ArlingtonAlexandria,
DC-VAMD-WV
Washington
-ArlingtonAlexandria,
DC-VAMD-WV
Washington
-Arlini,'1:onAlexandria,
DC-VAMD-WV
Washington
-ArlingtonAlexandria,
DC-VAMD-WV
Washington
-ArlingtonAlexandria,
DC-VAMD-WV
Washington
-ArlingtonAlexandria,
DC-VAMD-WV
Washington
-ArlingtonAlexandria,
28940
Knoxville, TN
11694
ArlingtonAlexandria-Reston,
VA-WV
11694
Arlini,'1:onAlexandria-Reston,
VA-WV
11694
ArlingtonAlexandria-Reston,
VA-WV
11694
ArlingtonAlexandria-Reston,
VA-WV
11694
ArlingtonAlexandria-Reston,
VA-WV
11694
ArlingtonAlexandria-Reston,
VA-WV
11694
ArlingtonAlexandria-Reston,
VA-WV
11694
ArlingtonAlexandria-Reston,
VA-WV
11694
ArlingtonAlcxandria-Rcston,
VA-WV
11694
ArlingtonAlexandria-Reston,
VA-WV
11694
ArlingtonAlexandria-Reston,
VA-WV
Sfmt 4725
E:\FR\FM\03APP2.SGM
Proposed CBSA
Name
03APP2
EP03AP24.025
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County
Code
Federal Register / Vol. 89, No. 65 / Wednesday, April 3, 2024 / Proposed Rules
County Name
Current
CBSA
51685
MANASSAS PARK
CITY
VA
47894
51153
PRINCE WILLIAM
VA
47894
51157
RAPPAHANNOCK
VA
47894
51177
SPOTSYLVANIA
VA
47894
51179
STAFFORD
VA
47894
51187
WARREN
VA
47894
53061
SNOHOMISH
WA
42644
55059
KENOSHA
WI
29404
54037
JEFFERSON
WV
47894
BILLING CODE 4120–01–C
lotter on DSK11XQN23PROD with PROPOSALS2
State
We have identified 68 IPF providers
located in the affected counties listed in
Table 15. If providers located in these
counties move from one CBSA to
another under the revised OMB
delineations, there may be impacts,
either negative or positive, upon their
specific wage index values.
VerDate Sep<11>2014
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Current
CBSA
Name
DC-VAMD-WV
Washington
-ArlingtonAlexandria,
DC-VAMD-WV
Washington
-ArlingtonAlexandria,
DC-VAMD-WV
Washington
-ArlingtonAlexandria,
DC-VAMD-WV
Washington
-ArlingtonAlexandria,
DC-VAMD-WV
Washington
-ArlingtonAlexandria,
DC-VAMD-WV
Washington
-ArlingtonAlexandria,
DC-VAMD-WV
SeattleBellevueKent. WA
Lake
CountyKenosha
County, ILWI
Washington
-ArlingtonAlexandria,
DC-VAMD-WV
c. Proposed Adjustment for Rural
Location
In the RY 2005 IPF PPS final rule, (69
FR 66954), we provided a 17-percent
payment adjustment for IPFs located in
a rural area. This adjustment was based
on the regression analysis, which
indicated that the per diem cost of rural
facilities was 17-percent higher than
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Proposed
CBSACode
Proposed CBSA
Name
11694
ArlingtonAlexandria-Reston,
VA-WV
11694
ArlingtonAlexandria-Reston,
VA-WV
11694
ArlingtonAlexandria-Reston,
VA-WV
11694
ArlingtonAlexandria-Reston,
VA-WV
11694
ArlingtonAlexandria-Reston,
VA-WV
11694
ArlingtonAlexandria-Reston,
VA-WV
21794
Everett, WA
28450
Kenosha, WI
11694
ArlingtonAlexandria-Reston,
VA-WV
that of urban facilities after accounting
for the influence of the other variables
included in the regression. This 17percent adjustment has been part of the
IPF PPS each year since the inception of
the IPF PPS. As discussed earlier in this
rule, we are proposing a number of
revisions to the patient-level adjustment
factors as well as changes to the CBSA
E:\FR\FM\03APP2.SGM
03APP2
EP03AP24.026
County
Code
23187
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Federal Register / Vol. 89, No. 65 / Wednesday, April 3, 2024 / Proposed Rules
delineations. In order to minimize the
scope of changes that would impact
providers in any single year, we are
proposing to use the existing regressionderived adjustment factor, which was
established in RY 2005, for FY 2025 for
IPFs located in a rural area as defined
at § 412.64(b)(1)(ii)(C). See 69 FR 66954
for a complete discussion of the
adjustment for rural locations. However,
as discussed in the section IV.A of this
FY 2025 IPF PPS proposed rule, we
have completed analysis of more recent
cost and claims information and are
soliciting comments on those results.
As proposed earlier in this proposed
rule, the adoption of OMB Bulletin No.
23–01 in accordance with our
established methodology would
determine whether a facility is classified
as urban or rural for purposes of the
rural payment adjustment in the IPF
PPS. Overall, we believe implementing
updated OMB delineations would result
in the rural payment adjustment being
applied where it is appropriate to adjust
for higher costs incurred by IPFs in rural
locations. However, we recognize that
implementing these changes would
have distributional effects among IPF
providers, and that some providers
would experience a loss of the rural
payment adjustment because of our
proposals. Therefore, we believe it
would be appropriate to consider, as we
have in the past, whether a transition
period should be used to implement
these proposed changes.
Prior changes to the CBSA
delineations have included a phase-out
policy for the rural adjustment for IPFs
transitioning from rural to urban status.
On February 28, 2013, OMB issued
OMB Bulletin No. 13–01, which
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. We adopted these new
OMB CBSA delineations in the FY 2016
IPF final rule (80 FR 46682 through
46689), and identified 105 counties and
37 IPFs that would move from rural to
urban status due to the new CBSA
delineations. To reduce the impact of
the loss of the 17-percent rural
adjustment, we adopted a budgetneutral 3-year phase-out of the rural
adjustment for existing FY 2015 rural
IPFs that became urban in FY 2016 and
that experienced a loss in payments due
to changes from the new CBSA
delineations. These IPFs received twothirds of the rural adjustment for FY
2016 and one-third of the rural
adjustment in FY 2017. For FY 2018,
these IPFs did not receive a rural
adjustment.
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For subsequent adoptions of OMB
Bulletin No. 15–01 for FY 2018 (82 FR
36779 through 36780), OMB Bulletin
17–01 for FY 2020 (84 FR 38453 through
38454), and OMB Bulletin 18–04 for FY
2021 (85 FR 47053 through 47059), we
identified that fewer providers were
affected by these changes than by the
changes relating to the adoption of OMB
Bulletin 13–01. We did not phase out
the rural adjustment when adopting
these delineation changes.
For facilities located in a county that
transitioned from rural to urban in
Bulletin 23–01, we considered whether
it would be appropriate to phase out the
rural adjustment for affected providers
consistent with our past practice of
using transition policies to help mitigate
negative impacts on hospitals of OMB
Bulletin proposals that have a material
effect on a number of IPFs. Adoption of
the updated CBSAs in Bulletin 23–01
will change the status of 10 IPF
providers currently designated as
‘‘rural’’ to ‘‘urban’’ for FY 2025 and
subsequent fiscal years. As such, these
10 newly urban providers will no longer
receive the 17-percent rural adjustment.
Consistent with the transition policy
adopted for IPFs in FY 2016 (80 FR
46682 through 4668980 FR 46682
through 46689), we are proposing a 3year budget neutral phase-out of the
rural adjustment for IPFs located in the
54 rural counties that will become urban
under the new OMB delineations, given
the potentially significant payment
impacts for these IPFs. We believe that
a phase-out of the rural adjustment
transition period for these 10 IPFs
specifically is appropriate because we
expect these IPFs will experience a
steeper and more abrupt reduction in
their payments compared to other IPFs.
Therefore, we are proposing to phase
out the rural adjustment for these
providers to reduce the impact of the
loss of the FY 2024 rural adjustment of
17-percent over FYs 2025, 2026, and
2027. This policy would allow IPFs that
are classified as rural in FY 2024 and
would be classified as urban in FY 2025
to receive two-thirds of the rural
adjustment for FY 2025. For FY 2026,
these IPFs would receive one-third of
the rural adjustment. For FY 2027, these
IPFs would not receive a rural
adjustment. We believe a 3-year budgetneutral phase-out of the rural
adjustment for IPFs that transition from
rural to urban status under the new
CBSA delineations would best
accomplish the goals of mitigating the
loss of the rural adjustment for existing
FY 2024 rural IPFs. The purpose of the
gradual phase-out of the rural
adjustment for these providers is to
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mitigate potential payment reductions
and promote stability and predictability
in payments for existing rural IPFs that
may need time to adjust to the loss of
their FY 2024 rural payment adjustment
or that experience a reduction in
payments solely because of this redesignation. This policy would be
specifically for rural IPFs that become
urban in FY 2025. We are not proposing
a transition policy for urban IPFs that
become rural in FY 2025 because these
IPFs will receive the full rural
adjustment of 17-percent beginning
October 1, 2024. We solicit comments
on this proposed policy.
d. Proposed Wage Index Budget
Neutrality Adjustment
Changes to the wage index are made
in a budget neutral manner so that
updates do not increase expenditures.
Therefore, for FY 2025, we are
proposing to continue to apply a budget
neutrality adjustment in accordance
with our existing budget neutrality
policy. This policy requires us to update
the wage index in such a way that total
estimated payments to IPFs for FY 2025
are the same with or without the
changes (that is, in a budget neutral
manner) by applying a budget neutrality
factor to the IPF PPS rates. We are
proposing to use the following steps to
ensure that the rates reflect the FY 2025
update to the wage indexes (based on
the FY 2021 hospital cost report data)
and the labor-related share in a budget
neutral manner:
Step 1: Simulate estimated IPF PPS
payments, using the FY 2024 IPF wage
index values (available on the CMS
website) and labor-related share (as
published in the FY 2024 IPF PPS final
rule (88 FR 51054).
Step 2: Simulate estimated IPF PPS
payments using the proposed FY 2025
IPF wage index values (available on the
CMS website), and the proposed FY
2025 labor-related share (based on the
latest available data as discussed
previously).
Step 3: Divide the amount calculated
in step 1 by the amount calculated in
step 2. The resulting quotient is the
proposed FY 2025 budget neutral wage
adjustment factor of 0.9995.
Step 4: Apply the FY 2025 budget
neutral wage adjustment factor from
step 3 to the FY 2024 IPF PPS Federal
per diem base rate after the application
of the IPF market basket increase
reduced by the productivity adjustment
described in section III.A of this
proposed rule to determine the FY 2025
IPF PPS Federal per diem base rate. As
discussed in section III.F of this
proposed rule, we are also proposing to
apply a refinement standardization
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Federal Register / Vol. 89, No. 65 / Wednesday, April 3, 2024 / Proposed Rules
factor to determine the FY 2025 IPF PPS
Federal per diem base rate.
2. Proposed Teaching Adjustment
Background
lotter on DSK11XQN23PROD with PROPOSALS2
In the RY 2005 IPF PPS final rule, we
implemented regulations at
§ 412.424(d)(1)(iii) to establish a facilitylevel adjustment for IPFs that are, or are
part of, teaching hospitals. The teaching
adjustment accounts for the higher
indirect operating costs experienced by
hospitals that participate in graduate
medical education (GME) programs. The
payment adjustments are made based on
the ratio of the number of fulltime
equivalent (FTE) interns and residents
training in the IPF and the IPF’s average
daily census.
Medicare makes direct GME payments
(for direct costs such as resident and
teaching physician salaries, and other
direct teaching costs) to all teaching
hospitals including those paid under a
PPS and those paid under the TEFRA
rate-of-increase limits. These direct
GME payments are made separately
from payments for hospital operating
costs and are not part of the IPF PPS.
The direct GME payments do not
address the estimated higher indirect
operating costs teaching hospitals may
face.
The results of the regression analysis
of FY 2002 IPF data established the
basis for the payment adjustments
included in the RY 2005 IPF PPS final
rule. The results showed that the
indirect teaching cost variable is
significant in explaining the higher
costs of IPFs that have teaching
programs. We calculated the teaching
adjustment based on the IPF’s ‘‘teaching
variable,’’ which is (1 + [the number of
FTE residents training in the IPF’s
average daily census]). The teaching
variable is then raised to the 0.5150
power to result in the teaching
adjustment. This formula is subject to
the limitations on the number of FTE
residents, which are described in this
section of this proposed rule.
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We established the teaching
adjustment in a manner that limited the
incentives for IPFs to add FTE residents
for the purpose of increasing their
teaching adjustment. We imposed a cap
on the number of FTE residents that
may be counted for purposes of
calculating the teaching adjustment. The
cap limits the number of FTE residents
that teaching IPFs may count for the
purpose of calculating the IPF PPS
teaching adjustment, not the number of
residents teaching institutions can hire
or train. We calculated the number of
FTE residents that trained in the IPF
during a ‘‘base year’’ and used that FTE
resident number as the cap. An IPF’s
FTE resident cap is ultimately
determined based on the final
settlement of the IPF’s most recent cost
report filed before November 15, 2004
(69 FR 66955). A complete discussion of
the temporary adjustment to the FTE
cap to reflect residents due to hospital
closure or residency program closure
appears in the RY 2012 IPF PPS
proposed rule (76 FR 5018 through
5020) and the RY 2012 IPF PPS final
rule (76 FR 26453 through 26456).
In the regression analysis that
informed the FY 2004 IPF PPS final
rule, the logarithm of the teaching
variable had a coefficient value of
0.5150. We converted this cost effect to
a teaching payment adjustment by
treating the regression coefficient as an
exponent and raising the teaching
variable to a power equal to the
coefficient value. We note that the
coefficient value of 0.5150 was based on
the regression analysis holding all other
components of the payment system
constant. A complete discussion of how
the teaching adjustment was calculated
appears in the RY 2005 IPF PPS final
rule (69 FR 66954 through 66957) and
the RY 2009 IPF PPS notice (73 FR
25721).
We are proposing to retain the
coefficient value of 0.5150 for the
teaching adjustment to the Federal per
diem base rate as we are not proposing
refinements to the facility-level payment
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23189
adjustments for rural location or
teaching status for FY 2025. As noted
earlier, given the scope of changes to the
wage index and patient-level adjustment
factors, we believe this will minimize
the total impacts to providers in any
given year.
3. Proposed Cost of Living Adjustment
for IPFs Located in Alaska and Hawaii
The IPF PPS includes a payment
adjustment for IPFs located in Alaska
and Hawaii based upon the area in
which the IPF is located. As we
explained in the RY 2005 IPF PPS final
rule, the FY 2002 data demonstrated
that IPFs in Alaska and Hawaii had per
diem costs that were disproportionately
higher than other IPFs. As a result of
this analysis, we provided a COLA in
the RY 2005 IPF PPS final rule. We refer
readers to the FY 2024 IPF PPS final
rule for a complete discussion of the
currently applicable COLA factors (88
FR 51088 through 51089).
We adopted a new methodology to
update the COLA factors for Alaska and
Hawaii for the IPF PPS in the FY 2015
IPF PPS final rule (79 FR 45958 through
45960). For a complete discussion, we
refer readers to the FY 2015 IPF PPS
final rule.
We also specified that the COLA
updates would be determined every 4
years, in alignment with the IPPS
market basket labor-related share update
(79 FR 45958 through 45960). Because
the labor-related share of the IPPS
market basket was updated for FY 2022,
the COLA factors were updated in FY
2022 IPPS/LTCH rulemaking (86 FR
45547). As such, we also finalized an
update to the IPF PPS COLA factors to
reflect the updated COLA factors
finalized in the FY 2022 IPPS/LTCH
rulemaking effective for FY 2022
through FY 2025 (86 FR 42621 through
42622). This is reflected in Table 16
below. We are proposing to maintain the
COLA factors in Table 16 for FY 2025
in alignment with the policy described
in this paragraph.
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Federal Register / Vol. 89, No. 65 / Wednesday, April 3, 2024 / Proposed Rules
Table 16: IPF PPS Cost-of-Living Adjustment Factors: IPFs Located in Alaska and Hawaii
FY 2022
through FY
2025
Area
Alaska:
City of Anchorage and 80-kilometer (50-mile) radius by road
City of Fairbanks and 80-kilometer (50-mile) radius by road
1.22
1.22
City of Juneau and 80-kilometer (50-mile) radius by road
Rest of Alaska
Hawaii:
City and County of Honolulu
County of Hawaii
County of Kauai
County of Maui and County of Kalawao
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4. Proposed Adjustment for IPFs With a
Qualifying ED
The IPF PPS includes a facility-level
adjustment for IPFs with qualifying EDs.
As defined in § 412.402, qualifying
emergency department means an
emergency department that is staffed
and equipped to furnish a
comprehensive array of emergency
services and meets the requirements of
42 CFR 489.24(b) and § 413.65.
We provide an adjustment to the
Federal per diem base rate to account
for the costs associated with
maintaining a full-service ED. The
adjustment is intended to account for
ED costs incurred by a psychiatric
hospital with a qualifying ED, or an
excluded psychiatric unit of an IPPS
hospital or a critical access hospital
(CAH), and the overhead cost of
maintaining the ED. This payment
applies to all IPF admissions (with one
exception which we describe in this
section), regardless of whether the
patient was admitted through the ED.
The ED adjustment is made on every
qualifying claim except as described in
this section of this proposed rule. As
specified at § 412.424(d)(1)(v)(B), the ED
adjustment is not made when a patient
is discharged from an IPPS hospital or
CAH, and admitted to the same IPPS
hospital’s or CAH’s excluded
psychiatric unit. We clarified in the RY
2005 IPF PPS final rule (69 FR 66960)
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that an ED adjustment is not made in
this case because the costs associated
with ED services are reflected in the
DRG payment to the IPPS hospital or
through the reasonable cost payment
made to the CAH.
a. Proposed Update for FY 2025
For FY 2025, we are proposing to
update the adjustment factor from 1.31
to 1.53 for IPFs with qualifying EDs
using the same methodology used to
determine ED adjustments in prior
years. Thus, we are proposing to use the
following steps, as used in prior years,
to calculate the updated ED adjustment
factor. (A complete discussion of the
steps involved in the calculation of the
ED adjustment factors can be found in
the RY 2005 IPF PPS final rule (69 FR
66959 through 66960) and the RY 2007
IPF PPS final rule (71 FR 27070 through
27072).)
Step 1: Estimate the proportion by
which the ED costs of a stay would
increase the cost of the first day of the
stay. Using the IPFs with ED admissions
in years 2019 through 2021, we divided
the average ED cost per stay when
admitted through the ED ($519.97) by
the average cost per day ($1,338.93),
which equals 0.39.
Step 2: Adjust the factor estimated in
step 1 to account for the fact that we
would pay the higher first day
adjustment for all cases in the qualifying
IPFs, not just the cases admitted through
the ED. Since on average, 66 percent of
the cases in IPFs with ED admissions
are admitted through the ED, we
multiplied 0.39 by 0.66, which equals
0.26.
Step 3: Add the adjusted factor
calculated in the previous 2 steps to the
variable per diem adjustment derived
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1.25
1.22
1.25
1.25
from the regression equation that we
used to derive our other payment
adjustment factors. As discussed in
section III.C.4.d. of this proposed rule,
the proposed first day payment factor
for FY 2025 is 1.27. Adding 0.26, we
obtained a first day variable per
adjustment for IPFs with a qualifying ED
equal to 1.53.
The ED adjustment is incorporated
into the variable per diem adjustment
for the first day of each stay for IPFs
with a qualifying ED. We are proposing
that those IPFs with a qualifying ED
would receive an adjustment factor of
1.53 as the variable per diem adjustment
for day 1 of each patient stay. If an IPF
does not have a qualifying ED, we are
proposing that it would receive an
adjustment factor of 1.27 as the variable
per diem adjustment for day 1 of each
patient stay, as discussed in section
III.C.4.d. of this proposed rule. As
discussed in section III.F of this
proposed rule, we are proposing to
implement this revision to the ED
adjustment budget—neutrally by
applying a refinement standardization
factor. A detailed discussion of the
distributional impacts of this proposed
change is found in section VIII.C of this
proposed rule.
We solicit comment on this proposal.
Lastly, we are proposing that if more
recent data become available, we would
use such data, if appropriate, to
determine the FY 2025 ED adjustment
factor.
b. Alternatives Considered
In response to the FY 2023 IPF PPS
proposed rule (87 FR 19428 through
19429) comment solicitation on our
technical report describing the analysis
of IPF PPS adjustments, two
E:\FR\FM\03APP2.SGM
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EP03AP24.027
The proposed IPF PPS COLA factors
for FY 2025 are also shown in
Addendum A to this proposed rule,
which is available on the CMS website
at https://www.cms.gov/Medicare/
Medicare-Fee-for-Service-Payment/
InpatientPsychFacilPPS/tools.html.
1.22
1.24
Federal Register / Vol. 89, No. 65 / Wednesday, April 3, 2024 / Proposed Rules
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commenters requested that we conduct
further analysis related to the exception
for the ED adjustment. These
commenters indicated that patients
transferred to an IPF from an acute care
unit or hospital often have higher costs
per stay than patients with similar
comorbidities admitted from the
community. Commenters requested that
CMS analyze data related to source of
admission and consider a payment
adjustment to account for the resources
used by these patients. In response to
these comments, we conducted a
regression analysis to investigate
whether the source of admission is a
statistically significant variable in the
cost of a patient’s care in an IPF. We
analyzed the following sources of
admission: clinic referral, transfer from
hospital (different facility), transfer from
a SNF or Intermediate Care Facility
(ICF), transfer from another health care
facility, court/law enforcement,
information not available, transfer from
hospital inpatient in the same facility,
transfer from ambulatory surgical
center, and transfer from hospice. In this
context, it is important to note that the
source of admission indicator ‘‘court/
law enforcement’’ is not the equivalent
of an involuntary admission; we do not
currently collect data on involuntary
admissions.
The regression analysis found that the
source of admission was not a
statistically significant factor in the cost
of care. The results for the two source
of admission variables that indicate
higher costs (transfer from hospital
inpatient in the same facility and
transfer from ambulatory surgical
center) are accounted for by the known
difference in cost structures between
hospital psychiatric units and
freestanding psychiatric hospitals. We
considered the results of our analysis, as
well as the potential that adjusting
payment based on source of admission
could inadvertently create incentives for
IPFs to prioritize certain admissions
over others. Based on these
considerations, we are not proposing to
add additional payment adjustments
based on source of admission (other
than the existing adjustment for a
qualifying ED) to the IPF PPS in FY
2025.
E. Other Proposed Payment
Adjustments and Policies
1. Outlier Payment Overview
The IPF PPS includes an outlier
adjustment to promote access to IPF
care for those patients who require
expensive care and to limit the financial
risk of IPFs treating unusually costly
patients. In the RY 2005 IPF PPS final
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rule, we implemented regulations at
§ 412.424(d)(3)(i) to provide a per case
payment for IPF stays that are
extraordinarily costly. Providing
additional payments to IPFs for
extremely costly cases strongly
improves the accuracy of the IPF PPS in
determining resource costs at the patient
and facility level. These additional
payments reduce the financial losses
that would otherwise be incurred in
treating patients who require costlier
care; therefore, reduce the incentives for
IPFs to under-serve these patients. We
make outlier payments for discharges in
which an IPF’s estimated total cost for
a case exceeds a fixed dollar loss
threshold amount (multiplied by the
IPF’s facility-level adjustments) plus the
federal per diem payment amount for
the case.
In instances when the case qualifies
for an outlier payment, we pay 80
percent of the difference between the
estimated cost for the case and the
adjusted threshold amount for days 1
through 9 of the stay (consistent with
the median LOS for IPFs in FY 2002),
and 60 percent of the difference for day
10 and thereafter. The adjusted
threshold amount is equal to the outlier
threshold amount adjusted for wage
area, teaching status, rural area, and the
COLA adjustment (if applicable), plus
the amount of the Medicare IPF
payment for the case. We established
the 80 percent and 60 percent loss
sharing ratios because we were
concerned that a single ratio established
at 80 percent (like other Medicare PPSs)
might provide an incentive under the
IPF per diem payment system to
increase LOS to receive additional
payments.
After establishing the loss sharing
ratios, we determined the current fixed
dollar loss threshold amount through
payment simulations designed to
compute a dollar loss beyond which
payments are estimated to meet the 2
percent outlier spending target. Each
year when we update the IPF PPS, we
simulate payments using the latest
available data to compute the fixed
dollar loss threshold so that outlier
payments represent 2 percent of total
estimated IPF PPS payments.
2. Proposed Update to the Outlier Fixed
Dollar Loss Threshold Amount
In accordance with the update
methodology described in § 412.428(d),
we are proposing to update the fixed
dollar loss threshold amount used under
the IPF PPS outlier policy. Based on the
regression analysis and payment
simulations used to develop the IPF
PPS, we established a 2 percent outlier
policy, which strikes an appropriate
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balance between protecting IPFs from
extraordinarily costly cases while
ensuring the adequacy of the federal per
diem base rate for all other cases that are
not outlier cases. We are proposing to
maintain the established 2 percent
outlier policy for FY 2025.
Our longstanding methodology for
updating the outlier fixed dollar loss
threshold involves using the best
available data, which is typically the
most recent available data. We note that
for FY 2022 and FY 2023 only, we made
certain methodological changes to our
modeling of outlier payments, and we
discussed the specific circumstances
that led to those changes for those years
(86 FR 42623 through 42624; 87 FR
46862 through 46864). We direct readers
to the FY 2022 and FY 2023 IPF PPS
proposed and final rules for a more
complete discussion.
We are proposing to update the IPF
outlier threshold amount for FY 2025
using FY 2023 claims data and the same
methodology that we have used to set
the initial outlier threshold amount each
year beginning with the RY 2007 IPF
PPS final rule (71 FR 27072 and 27073).
For this FY 2025 IPF PPS rulemaking,
consistent with our longstanding
practice, based on an analysis of the
latest available data (the December 2023
update of FY 2023 IPF claims) and rate
increases, we believe it is necessary to
update the fixed dollar loss threshold
amount to maintain an outlier
percentage that equals 2 percent of total
estimated IPF PPS payments. Based on
an analysis of these updated data, we
estimate that IPF outlier payments as a
percentage of total estimated payments
are approximately 2.1 percent in FY
2024. Therefore, we are proposing to
update the outlier threshold amount to
$35,590 to maintain estimated outlier
payments at 2 percent of total estimated
aggregate IPF payments for FY 2025.
This proposed rule update is an increase
from the FY 2024 threshold of $33,470.
Lastly, we are proposing that if more
recent data become available for the FY
2025 IPF PPS final rule, we would use
such data as appropriate to determine
the final outlier fixed dollar loss
threshold amount for FY 2025.
3. Proposed Update to IPF Cost-toCharge Ratio Ceilings
Under the IPF PPS, an outlier
payment is made if an IPF’s cost for a
stay exceeds a fixed dollar loss
threshold amount plus the IPF PPS
amount. To establish an IPF’s cost for a
particular case, we multiply the IPF’s
reported charges on the discharge bill by
its overall cost-to-charge ratio (CCR).
This approach to determining an IPF’s
cost is consistent with the approach
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used under the IPPS and other PPSs. In
the FY 2004 IPPS final rule (68 FR
34494), we implemented changes to the
IPPS policy used to determine CCRs for
IPPS hospitals, because we became
aware that payment vulnerabilities
resulted in inappropriate outlier
payments. Under the IPPS, we
established a statistical measure of
accuracy for CCRs to ensure that
aberrant CCR data did not result in
inappropriate outlier payments.
As indicated in the RY 2005 IPF PPS
final rule (69 FR 66961), we believe that
the IPF outlier policy is susceptible to
the same payment vulnerabilities as the
IPPS; therefore, we adopted a method to
ensure the statistical accuracy of CCRs
under the IPF PPS. Specifically, we
adopted the following procedure in the
RY 2005 IPF PPS final rule:
• Calculated two national ceilings,
one for IPFs located in rural areas and
one for IPFs located in urban areas.
• Computed the ceilings by first
calculating the national average and the
standard deviation of the CCR for both
urban and rural IPFs using the most
recent CCRs entered in the most recent
Provider Specific File (PSF) available.
For FY 2025, we are proposing to
continue following this methodology.
To determine the rural and urban
ceilings, we multiplied each of the
standard deviations by 3 and added the
result to the appropriate national CCR
average (either rural or urban). The
proposed upper threshold CCR for IPFs
in FY 2025 is 2.3362 for rural IPFs, and
1.8600 for urban IPFs, based on current
CBSA-based geographic designations. If
an IPF’s CCR is above the applicable
ceiling, the ratio is considered
statistically inaccurate, and we assign
the appropriate national (either rural or
urban) median CCR to the IPF.
We apply the national median CCRs
to the following situations:
• New IPFs that have not yet
submitted their first Medicare cost
report. We continue to use these
national median CCRs until the facility’s
actual CCR can be computed using the
first tentatively or final settled cost
report.
• IPFs whose overall CCR is in excess
of three standard deviations above the
corresponding national geometric mean
(that is, above the ceiling).
• Other IPFs for which the Medicare
Administrative Contractor (MAC)
obtains inaccurate or incomplete data
with which to calculate a CCR.
We are proposing to update the FY
2025 national median and ceiling CCRs
for urban and rural IPFs based on the
CCRs entered in the latest available IPF
PPS PSF.
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Specifically, for FY 2025, to be used
in each of the three situations listed
previously, using the most recent CCRs
entered in the CY 2023 PSF, we provide
an estimated national median CCR of
0.5720 for rural IPFs and a national
median CCR of 0.4200 for urban IPFs.
These calculations are based on the
IPF’s location (either urban or rural)
using the current CBSA-based
geographic designations. A complete
discussion regarding the national
median CCRs appears in the RY 2005
IPF PPS final rule (69 FR 66961 through
66964).
Lastly, we are proposing that if more
recent data become available, we would
use such data to calculate the rural and
urban national median and ceiling CCRs
for FY 2025.
4. Requirements for Reporting Ancillary
Charges and All-Inclusive Status
Eligibility Under the IPF PPS
a. Background
As discussed in section III.E.4.b of
this proposed rule, to analyze variation
in cost between patients with different
characteristics, it is crucial for us to
have complete cost information about
each patient, including data on ancillary
services provided. Currently, IPFs and
psychiatric units are required to report
ancillary charges on cost reports. As
specified at 42 CFR 413.20, hospitals are
required to file cost reports on an
annual basis and maintain sufficient
financial records and statistical data for
proper determination of costs payable
under the Medicare program.
However, our ongoing analysis has
found a notable increase in the number
of IPFs, specifically for-profit
freestanding IPFs, that appear to be
erroneously identifying on form CMS–
2552–10, Worksheet S–2, Part I, line
115, as eligible for filing all-inclusive
cost reports. These hospitals identifying
as eligible for filing all-inclusive cost
reports (indicating that they have one
charge covering all services) are
consistently reporting no ancillary
charges or very minimal ancillary
charges and are not using charge
information to apportion costs in their
cost report. Generally, based on the
nature of IPF services and the
conditions of participation applicable to
IPFs, we expect to see ancillary services
and correlating charges, such as labs
and drugs, on most IPF claims.3
3 IPFs are subject to all hospital conditions of
participation, including 42 CFR 482.25, which
specifies that ‘‘The hospital must have
pharmaceutical services that meet the needs of the
patients,’’ and 482.27, which specifies that ‘‘The
hospital must maintain, or have available, adequate
laboratory services to meet the needs of its
patients.’’
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In the FY 2016 IPF PPS final rule (80
FR 46693 through 46694), we discussed
analysis conducted to better understand
IPF industry practices for future IPF PPS
refinements. This analysis revealed that
in 2012 to 2013, over 20 percent of IPF
stays show no reported ancillary
charges, such as laboratory and drug
charges, on claims. In the FY 2016 IPF
PPS final rule (80 FR 46694), FY 2017
IPF PPS final rule (81 FR 50513), FY
2018 IPF PPS final rule (82 FR 36784),
FY 2019 IPF PPS final rule (83 FR
38588), and FY 2020 IPF PPS final rule
(84 FR 38458), we reminded providers
that we only pay the IPF for services
furnished to a Medicare beneficiary who
is an inpatient of that IPF, except for
certain professional services, and
payments are considered to be payments
in full for all inpatient hospital services
provided directly or under arrangement
(see 42 CFR 412.404(d)), as specified in
42 CFR 409.10.
On November 17, 2017, we issued
Transmittal 12, which made changes to
the hospital cost report form CMS–
2552–10 (OMB No. 0938–0050) and
included cost report level 1 edit 10710S,
effective for cost reporting periods
ending on or after August 31, 2017. Edit
10710S required that cost reports from
psychiatric hospitals include certain
ancillary costs or the cost report will be
rejected. On January 30, 2018, we issued
Transmittal 13, which changed the
implementation date for Transmittal 12
to be for cost reporting periods ending
on or after September 30, 2017. CMS
suspended edit 10710S effective April
27, 2018, pending evaluation of the
application of the edit to all-inclusive
rate providers. We issued Transmittal 15
on October 19, 2018, reinstating the
requirement that cost reports from
psychiatric hospitals, except allinclusive rate providers, include certain
ancillary costs. This requirement is still
currently in place. For details, we refer
readers to see these Transmittals, which
are available on the CMS website at
https://www.cms.gov/medicare/
regulations-guidance/transmittals.
Under IPF PPS regulations at 42 CFR
412.404(e), all inpatient psychiatric
facilities paid under the IPF PPS must
meet the recordkeeping and cost
reporting requirements as specified at
§ 413.24. Historically, in accordance
with § 413.24(a)(1), most hospitals that
were approved to file all-inclusive cost
reports were Indian Health Services
(IHS) hospitals, government-owned
psychiatric and acute care hospitals,
and nominal charge hospitals. Although
IPFs are no longer reimbursed on the
basis of reasonable costs, we continue to
expect that most IPFs, other than
government-owned or tribally owned
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IPFs, should report cost data that is
based on an approved method of cost
finding and on the accrual basis of
accounting. The option to elect to file an
all-inclusive rate cost report is limited
to providers that do not have a charge
structure and that, therefore, must use
an alternative statistic to apportion costs
associated with services rendered to
Medicare beneficiaries.
Current cost reporting rules allow
hospitals that do not have a charge
structure to file an all-inclusive cost
report using an alternative cost
allocation method. We refer readers to
the Provider Reimbursement Manual
(PRM) 15–1; chapter 22, § 2208 for
detailed information on the
requirements to file an alternative
method.
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b. Challenges Related to Missing IPF
Ancillary Cost Data
In general, most providers allocate
their Medicare costs using costs and
charges as described at § 413.53(a)(1)(i)
and referred to as the Departmental
Method, which is the ratio of
beneficiary charges to total patient
charges for the services of each ancillary
department. For cost reporting periods
beginning on or after October 1, 1982,
the cost report uses the Departmental
Method to apportion the cost of the
department to the Medicare program.
Added to this amount is the cost of
routine services for Medicare
beneficiaries, determined based on a
separate average cost per diem for all
patients for general routine patient care
areas as required at § 413.53(a)(1)(i) and
(e); and 15–1, chapter 22, § 2200.1.4
We use cost-to-charge ratios (CCRs)
from Medicare cost reports as the
method of establishing reasonable costs
for hospital services and as the basis for
ratesetting for several hospital
prospective payment systems. In
general, detailed ancillary cost and
charge information is necessary for
accurate Medicare ratesetting. When
hospitals identify as all-inclusive, they
are excluded from ratesetting because
they do not have CCRs but use an
alternative basis for apportioning costs.
When hospitals erroneously identify as
all-inclusive but have a charge structure,
data that is necessary for accurate
Medicare ratesetting is improperly
excluded.
4 IPFs are subject to all hospital conditions of
participation, including 42 CFR 482.25, which
specifies that ‘‘The hospital must have
pharmaceutical services that meet the needs of the
patients,’’ and 482.27, which specifies that ‘‘The
hospital must maintain, or have available, adequate
laboratory services to meet the needs of its
patients.’’
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Since the issuance of Transmittal 15,
we have continued to identify an
increase in the number of IPFs,
specifically for-profit freestanding IPFs,
that appear to be erroneously
identifying on form CMS- 2552–10,
Worksheet S–2, Part I, line 115, as filing
all-inclusive cost reports. In conjunction
with the FY 2023 IPF PPS proposed rule
(87 FR 19428 through 19429), we posted
a report on the CMS website that
summarizes the results of the latest
analysis of more recent IPF cost and
claim information for potential IPF PPS
adjustments and requested comments
about the results summarized in the
report. The report showed that
approximately 23 percent of IPF stays
were trimmed from the data set used in
that analysis because they were stays at
facilities where fewer than 5 percent of
their stays had ancillary charges. The
report is available on the CMS website
at https://www.cms.gov/medicare/
payment/prospective-payment-systems/
inpatient-psychiatric-facility/ipf-reportsand-educational-resources.
Section 4125 of the CAA, 2023
authorizes the Secretary to collect data
and information, specifically including
charges related to ancillary services, as
appropriate to inform revisions to the
IPF PPS.
In the FY 2024 IPF PPS proposed rule
(88 FR 21270 through 21272), we
included a request for information (RFI)
related to the reporting of charges for
ancillary services, such as labs and
drugs, on IPF claims. We were
interested in better understanding IPF
industry practices pertaining to the
billing and provision of ancillary
services to inform statutorily mandated
IPF PPS refinements. We stated that we
were considering whether to require
charges for ancillary services to be
reported on claims and potentially reject
claims if no ancillary services are
reported, and whether to consider
payment for such claims to be
inappropriate or erroneous and subject
to recoupment.
In response to the comment
solicitation, we received a comment
from MedPAC regarding facilities that
do not report ancillary charges on most
or any of their claims. MedPAC stated
that it is not known: whether IPFs fail
to report ancillary charges separately
because they were appropriately
bundled with all other charges into an
all-inclusive per diem rate; if no
ancillary charges were incurred because
the IPF cares for a patient mix with
lower care needs or inappropriately fails
to furnish the kinds of care reflected in
ancillary charges when medically
necessary; or if ancillary charges for
services furnished during the IPF stay
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23193
are inappropriately billed outside of the
IPF base rate (unbundling). MedPAC
recommended CMS conduct further
investigation into the lack of certain
ancillary charges and whether IPFs are
providing necessary care and
appropriately billing for inpatient
psychiatric services under the IPF PPS.
MedPAC also encouraged CMS to
require the reporting of ancillary
charges and clarify the requirements
related to IPFs’ ‘‘all-inclusive-rate’’
hospital status. MedPAC noted that it
observed in cost report data that IPFs
that previously were not all-inclusiverate hospitals have recently changed to
an all-inclusive-rate status. MedPAC
noted that the timing of many of these
changes appears to correspond to CMS’s
transmittals requiring ancillary services
to be reported on cost reports for IPFs
that do not have an all-inclusive rate.
Other commenters, including IPFs
and hospital associations, responded to
the RFI stating that the lack of ancillary
charges on claims does not indicate a
lack of services being provided. The
commenters strongly opposed any
claim-level editing and stated that
reporting ancillary charges at the claim
level would be inefficient and
burdensome, particularly for
government and IHS all-inclusive
hospitals.
c. Clarification of Eligibility Criteria for
the Option To Elect To File an AllInclusive Cost Report
After taking into consideration the
feedback we received from both
MedPAC and IPF providers, for FY 2025
we are clarifying the eligibility criteria
to be approved to file all-inclusive cost
reports. Only government-owned or
tribally owned facilities are able to
satisfy these criteria, and thus only
these facilities will be permitted to file
an all-inclusive cost report for cost
reporting periods beginning on or after
October 1, 2024.
We remind readers that in order to be
approved to file an all-inclusive cost
report, hospitals must either have an allinclusive rate (one charge covering all
services) or a no-charge structure.5 We
are clarifying that this does not mean
any hospital can elect to have an allinclusive rate or no-charge structure.
Our longstanding policy as discussed in
the PRM 15–1, chapter 22, § 2208.1,
only allows a hospital to use an allinclusive rate or no charge structure if
it has never had a charge structure in
place. In addition, we are clarifying that
our expectation is that any new IPF
would have the ability to have a charge
structure under which it could allocate
5 PRM
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costs and charges. As previously stated,
only a government-owned or tribally
owned facility will be able to satisfy
these criteria and will be eligible to file
its cost report using an all-inclusive rate
or no charge structure.
For cost reporting periods beginning
on or after October 1, 2024, we will
issue instructions to the MACs and put
in place edits to operationalize our
longstanding policy that only
government-owned or tribally owned
IPF hospitals are permitted to file an allinclusive cost report. All other IPF
hospitals must have a charge structure
and must report ancillary costs and
charges on their cost reports. IPFs that
have previously filed an all-inclusive
cost report erroneously will no longer be
able to do so. We further note that to the
extent government-owned or tribally
owned hospitals can report ancillary
charges on their cost reports, we
strongly encourage them to do so to
allow CMS to review and analyze
complete and accurate data.
We believe clarifying the current
eligibility criteria to be approved to file
all-inclusive cost reports and
implementing these operational changes
will appropriately require freestanding
IPFs with the ability to have a charge
structure, that is, all IPFs other than
those which are government-owned or
tribally owned, to track and report
ancillary charge information. In
addition, we expect that more IPFs
reporting ancillary charge information
will result in an increase of IPFs having
a CCR, which will in turn result in an
increased number of IPFs being
included in ratesetting. Therefore, we
believe these operational changes will
improve the quality of data reported,
which will result in increased accuracy
of future payment refinements to the IPF
PPS.
Furthermore, we believe collecting
charges of ancillary services from
freestanding IPFs supports the directive
for competition under the Executive
Order on Promoting Competition in the
American Economy as it facilitates
accurate payment, cost efficiency, and
transparency.6
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F. Refinement Standardization Factor
Section 1886(s)(5)(D)(iii) of the Act, as
added by section 4125(a) of the CAA,
2023, states that revisions in payment
implemented pursuant to section
1886(s)(5)(D)(i) for a rate year shall
result in the same estimated amount of
aggregate expenditures under this title
6 https://www.whitehouse.gov/briefing-room/
presidential-actions/2021/07/09/executive-orderon-promoting-competition-in-the-americaneconomy/.
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for psychiatric hospitals and psychiatric
units furnished in the rate year as would
have been made under this title for such
care in such rate year if such revisions
had not been implemented. We interpret
this to mean that revisions in payment
adjustments implemented for FY 2025
(and for any subsequent fiscal year)
must be budget neutral.
Historically, we have maintained
budget neutrality in the IPF PPS using
the application of a standardization
factor, which is codified in our
regulations at § 412.424(c)(5) to account
for the overall positive effects resulting
from the facility-level and patient-level
adjustments. As discussed in section
III.B.1 of this proposed rule, section
124(a)(1) of the BBRA required that we
implement the IPF PPS in a budget
neutral manner. In other words, the
amount of total payments under the IPF
PPS, including any payment
adjustments, must be projected to be
equal to the amount of total payments
that would have been made if the IPF
PPS were not implemented. Therefore,
we calculated the standardization factor
by setting the total estimated IPF PPS
payments, taking into account all of the
adjustment factors under the IPF PPS, to
be equal to the total estimated payments
that would have been made under the
Tax Equity and Fiscal Responsibility
Act of 1982 (TEFRA) (Pub. L. 97–248)
methodology had the IPF PPS not been
implemented. A step-by-step
description of the methodology used to
estimate payments under the TEFRA
payment system appears in the RY 2005
IPF PPS final rule (69 FR 66926).
We believe the budget neutrality
requirement of section 4125(a) of the
CAA, 2023 is consistent with our
longstanding methodology for
maintaining budget neutrality under the
IPF PPS. Therefore, for FY 2025, we are
proposing to apply a refinement
standardization factor in accordance
with our existing policy at
§ 412.424(c)(5). This policy requires us
to update IPF PPS patient-level
adjustment factors, ED adjustment, and
ECT per treatment amount as proposed
in this FY 2025 IPF PPS proposed rule,
in such a way that total estimated
payments to IPFs for FY 2025 are the
same with or without the changes (that
is, in a budget neutral manner) by
applying a refinement standardization
factor to the IPF PPS rates. We are
proposing to use the following steps to
ensure that the rates reflect the FY 2025
update to the patient-level adjustment
factors (as previously discussed in
section III.C and III.D of this proposed
rule, and summarized in Addendum A)
in a budget neutral manner:
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Step 1: Simulate estimated IPF PPS
payments using the FY 2024 IPF
patient-level and facility-level
adjustment factor values and FY 2024
ECT payment per treatment (available
on the CMS website).
Step 2: Simulate estimated IPF PPS
payments using the proposed FY 2025
IPF patient-level and facility-level
adjustment factor values (see
Addendum A of this proposed rule,
which is available on the CMS website)
and ECT per treatment amount based on
the CY 2022 geometric mean cost for
ECT under the OPPS.
Step 3: Divide the amount calculated
in step 1 by the amount calculated in
step 2. The resulting quotient is the
proposed FY 2025 refinement
standardization factor of 0.9514.
Step 4: Apply the FY 2025 refinement
standardization factor from step 3 to the
FY 2024 IPF PPS Federal per diem base
rate and ECT per treatment amount
(based on the CY 2022 geometric mean
cost for ECT under the OPPS), after the
application of the wage index budget
neutrality factor and the IPF market
basket increase reduced by the
productivity adjustment described in
section III.A of this proposed rule to
determine the FY 2025 IPF PPS Federal
per diem base rate and FY 2025 ECT
payment amount per treatment.
IV. Requests for Information (RFI) To
Inform Future Revisions to the IPF PPS
in Accordance With the CAA, 2023
As discussed in the following
sections, we are requesting information
on two main topics to inform future
revisions to the IPF PPS, in accordance
with the CAA, 2023. First, we are
requesting information regarding
potential revisions to the IPF PPS
facility-level adjustments. Second, we
are requesting information regarding the
development of a patient assessment
instrument under the IPFQR program.
Please note, each of these sections is
a request for information (RFI) only. In
accordance with the implementing
regulations of the Paperwork Reduction
Act of 1995 (PRA), specifically 5 CFR
1320.3(h)(4), this general solicitation is
exempt from the PRA. Facts or opinions
submitted in response to general
solicitations of comments from the
public, published in the Federal
Register or other publications,
regardless of the form or format thereof,
provided that no person is required to
supply specific information pertaining
to the commenter, other than that
necessary for self-identification, as a
condition of the agency’s full
consideration, are not generally
considered information collections and
therefore not subject to the PRA.
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Respondents are encouraged to provide
complete but concise responses. This
RFI is issued solely for information and
planning purposes; it does not
constitute a Request for Proposal (RFP),
applications, proposal abstracts, or
quotations. This RFI does not commit
the U.S. Government to contract for any
supplies or services or make a grant
award. Further, CMS is not seeking
proposals through this RFI and will not
accept unsolicited proposals.
Responders are advised that the U.S.
Government will not pay for any
information or administrative costs
incurred in response to this RFI; all
costs associated with responding to this
RFI will be solely at the interested
party’s expense. Not responding to this
RFI does not preclude participation in
any future procurement, if conducted. It
is the responsibility of the potential
responders to monitor this RFI
announcement for additional
information pertaining to this request.
Please note that CMS will not respond
to questions about the policy issues
raised in this RFI. CMS may or may not
choose to contact individual responders.
Such communications would only serve
to further clarify written responses.
Contractor support personnel may be
used to review RFI responses.
Responses to this notice are not offers
and cannot be accepted by the U.S.
Government to form a binding contract
or issue a grant. Information obtained as
a result of this RFI may be used by the
U.S. Government for program planning
on a non-attribution basis. Respondents
should not include any information that
might be considered proprietary or
confidential. This RFI should not be
construed as a commitment or
authorization to incur cost for which
reimbursement would be required or
sought. All submissions become U.S.
Government property and will not be
23195
returned. CMS may publicly post the
comments received, or a summary
thereof.
future based on the results of our latest
regression analysis in future years.
A. Request for Information Regarding
Revisions to IPF PPS Facility-Level
Adjustments
In our MedPAR data set, which
included data from CY 2019 through CY
2021, 101,483 stays, or 12.6 percent of
all stays, were at rural IPFs. Our
analysis shows that the regression
coefficient for rural stays is 1.19. This
means that holding all other variables
constant and controlling for area wage
differences, stays at rural IPFs have
approximately 19-percent higher cost
per day than stays at urban IPFs. As
previously discussed, we did not
include control variables in our
regression model to account for
occupancy rate. However, we note that
if we included these control variables,
we estimate the rural adjustment in the
regression would decrease to
approximately 1.13.
In addition, as discussed later in
section IV.A.3 of this proposed rule, we
evaluated the potential inclusion of a
new variable for facilities’ safety net
patient population, as measured by the
MSNI ratio. We observe that the
inclusion of the MSNI ratio in the
regression model would have an impact
on the rural adjustment factor. In the
regression model that includes the
MSNI ratio, the rural adjustment factor
is 1.16. In other words, if we were to
adopt an MSNI payment adjustment,
our FY 2025 regression model indicates
that the rural adjustment factor would
decrease relative to the rural adjustment
factor calculated without the MSNI
variable. However, for rural facilities
with a high level of safety net patients,
the combined effect of the rural
adjustment and a safety net adjustment
would increase payments. These results
are presented in Table 17, and we are
seeking public comments on these
results.
The CAA, 2023 added section
1886(s)(5)(D) to require CMS to revise
the IPF PPS methodology for
determining payment rates for FY 2025,
and for any subsequent FY as
determined appropriate by the
Secretary. As detailed in sections III.C
and III.D of this proposed rule, we are
proposing to revise the patient-level
payment adjustments in FY 2025 and
retain the current facility-level payment
adjustments for rural location and
teaching status. We have also conducted
analysis of the IPF PPS facility-level
adjustments using an updated
regression analysis of cost and claims
data for CY 2019 through 2021, as
discussed in section III.C.3. of this
proposed rule. The updated analysis
identified potential changes in the
regression factors for rural location and
teaching status and suggests there may
be value in including a new facilitylevel variable for safety net patient
population, based on the Medicare
Safety Net Index (MSNI) methodology
developed by MedPAC for the IPPS. We
note that the analysis of MSNI builds on
prior analysis that CMS conducted
regarding the applicability of an
adjustment for disproportionate share
intensity. Our review is ongoing and
may be used to inform future
rulemaking.
In the following sections, we describe
the results of our latest analysis and
request public comment on them. We
are interested in comments regarding
whether it would be appropriate to
consider proposing revisions to the IPF
PPS facility-level adjustments in the
1. Adjustment for Rural Location
Table 17: Rural Adjustment Factor Regression Results CY 2019-CY 2021
Updated Adjustment Factor without
MSNI payment
1.19
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1.17
We have modeled informational
impacts reflecting the potential change
in payments, as discussed in section
IV.A.4 of this proposed rule, though we
note future additional data and analysis
may produce results that differ from
those presented in this proposed rule.
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2. Teaching Adjustment
In the IPF PPS payment methodology,
the teaching status for each facility is
calculated as one plus the facility’s ratio
of intern and resident FTEs to the
average daily census (69 FR 66954
through 66955). The teaching variable
used in the regression is the natural log
of each facility’s teaching status,
resulting in a continuous variable with
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Updated Adjustment Factor with
MSNI payment
1.16
a distribution ranging from 0.0000 to
1.6079. The payment adjustment for
teaching status, as explained in section
III.D.2 of this proposed rule, is
calculated by raising a facility’s teaching
ratio to the power of the teaching status
coefficient derived from the regression
analysis.
In our updated regression analysis of
data for CY 2019 through CY 2021, there
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were 155,458 stays in teaching facilities,
comprising 19.3 percent of IPF stays for
the time period. As previously
discussed in this proposed rule, we
found that the occupancy variables used
in the original IPF PPS regression model
were correlated with rural status, and
have been removed in this updated
model. We note that if we were to
include occupancy control variables in
the regression model, the adjustment for
teaching status would increase to
1.0087.
The teaching status variable continues
to be statistically significant at the 0.001
level in all of our updated models; in
other words, we found that a facility’s
teaching status explains differences in
costs between IPF stays. As shown in
Table 18, the teaching status coefficient
would increase in either updated
regression model compared to its
current value.
Table 18: Teaching Status Adjustment Factor Regression Results CY 2019-CY 2021
Updated Adjustment Factor without
MSNI payment
0.7286
0.5150
As discussed in section IV.A.4. of this
proposed rule, we have modeled
informational impacts reflecting the
potential change in payments from these
adjustment factors. We are seeking
public comment on these results. We
note that future additional data and
analysis may produce results that differ
from those presented in this proposed
rule.
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3. Adjustment for Safety Net Patient
Population
a. Prior Analysis of Disproportionate
Share Hospital Status
In contrast to other Medicare hospital
payment systems, the IPF PPS does not
have an adjustment that recognizes
disproportionate share intensity.
Section 1886(s) of the Act does not
require any specific adjustment of this
type, nor does it require the use of any
particular methodology. In the past, we
have explored the application of the
disproportionate share hospital (DSH)
variable used in other Medicare
prospective payment systems (that is,
the sum of the proportion of Medicare
days of care provided to recipients of
Supplemental Security Income and the
proportion of the total days of care
provided to Medicaid beneficiaries) for
the IPF PPS. We refer readers to the RY
2005 IPF PPS final rule (69 FR 66958
through 66959) and the FY 2023 IPF
PPS final rule (87 FR 46865). For
psychiatric units, both proportions are
specific to the unit and not the entire
hospital.
In the RY 2005 IPF PPS final rule, we
explained that the DSH variable was
highly significant in our cost
regressions; however, we found that
facilities with higher DSH had lower per
diem costs. We note that the previously
cited study for the American Psychiatric
Association also found the same results.
The relationship of high DSH with
lower costs cannot be attributed to
downward bias in the Medicaid
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proportion due to the IMD exclusion.
This is because public psychiatric
hospitals already have lower costs on
average than other types of IPFs.
Therefore, if we had proposed a DSH
adjustment based on the regression
analysis, IPFs with high DSH shares
would have been paid lower per diem
rates (69 FR 66958).
In the FY 2023 IPF PPS proposed rule,
we summarized and discussed the
results of more recent analysis using
data from 2018 (87 FR 19428 through
19429). In response to that proposed
rule, commenters encouraged CMS to
continue evaluating ways to increase
IPF PPS payments for disproportionate
share intensity. MedPAC recommended
that we consider the applicability of the
MSNI, which has previously been
discussed in the context of the IPPS, to
the IPF PPS. As discussed in the
following paragraphs, we have
conducted analysis of the MSNI and are
soliciting comments on our findings.
b. Analysis of the Medicare Safety Net
Index in the IPF PPS
(1) Background
MSNI is an index that MedPAC
developed as its recommended
alternative to the current statutorily
required methodology for
disproportionate share payments to
IPPS hospitals. In their March 2023
Report to Congress, MedPAC
recommend that MSNI would better
target scarce Medicare resources to
support hospitals that are key sources of
care for low-income Medicare
beneficiaries and may be at risk of
closure.7 For further discussion of this
safety net index in the context of the
Medicare program, we refer readers to
7 Medicare Payment Advisory Commission.
(2023). Report to the Congress: Medicare Payment
Policy. Available at: https://www.medpac.gov/wpcontent/uploads/2023/03/Ch3_Mar23_MedPAC_
Report_To_Congress_SEC_v2.pdf. Accessed on
January 22, 2024.
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Updated Adjustment Factor with
MSNI payment
0.6955
the FY 2024 IPPS final rule (88 FR
58640), which includes a discussion of
how MSNI could be calculated for acute
care hospitals and an RFI on the
potential use of MSNI or other safety net
indicators in the IPPS, such as the area
deprivation index (ADI) or Social
Deprivation Index (SDI).
For our analysis, we constructed an
MSNI for each IPF in our data set,
which we calculated as the sum of three
ratios:
• The low-income subsidy (LIS)
volume ratio, which is the ratio of total
stays for low-income beneficiaries to a
facility’s total stays for Medicare
beneficiaries. For our analysis, lowincome beneficiaries are identified
based on dual-enrollment or enrollment
in Part D low-income subsidies, and
stays are identified from MedPAR
claims. This ratio was defined the same
way in the FY 2024 IPPS final rule’s
discussion of MSNI (88 FR 59306).
• The proportion of revenue spent on
uncompensated care (UCC), defined the
same way as it was in the FY 2024 IPPS
final rule’s discussion of MSNI (88 FR
59306). UCC and total revenue are
available data elements from the
hospital cost report, but only for the
acute care hospital. These elements are
not currently detailed at the level of the
IPF unit.
• The Medicare dependency ratio,
which is a hospital’s total covered days
for Medicare patients divided by its
total patient days. This information
comes from the hospital cost report. We
have also defined this ratio in the same
way as it was defined in the FY 2024
IPPS final rule’s discussion of MSNI (88
FR 59306).
The final MSNI score is calculated as:
LIS Volume Ratio + Proportion of
Revenue Spent on UCC ratio + 0.5 *
Medicare Dependency Ratio. This
formula follows MedPAC’s methodology
based on its analysis of data for the IPPS
hospital setting. As discussed in its
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March 2023 Report to Congress, the
Medicare Dependency Ratio is
multiplied by 0.5 because MedPAC’s
prior analysis of costs in the IPPS
setting found that the Medicare
Dependency Ratio had approximately
half the effect on cost as the other two
components of MSNI.
(2) Regression Analysis Results
The adjusted r-square, a measure of
how much of the variation in costs
between stays our model can explain,
increases by approximately 2.8 percent
when we add the variable for MSNI to
the updated model analyzing cost and
claims data for CY 2019 through CY
23197
2021. The adjusted r-square for the
model without the MSNI variable is
0.32340, while the adjusted r-square for
the model with the MSNI variable is
0.33250. Our regression analysis
indicates an MSNI coefficient of 0.5184,
which is statistically significant at the
.001 level.
Table 19: Example MSNI Payment Adjustments by Facility Type
Utban
MSNI
(1 + MSNI factor)A().5184
Section 1886(s)(5)(D)(iii) of the Act, as
added by section 4125(a) of the CAA,
2023, states that revisions in payment
implemented pursuant to section
1886(s)(5)(D)(i) for a rate year shall
result in the same estimated amount of
aggregate expenditures under this title
for psychiatric hospitals and psychiatric
units furnished in the rate year as would
have been made under this title for such
care in such rate year if such revisions
had not been implemented. Therefore,
our estimates of payments associated
with a potential MSNI payment
adjustment include the application of a
standardization factor, which we note
would reduce the IPF PPS Federal per
diem base rate by approximately $245.
Hospitals
0.8051
1.36
Rural
Units
0.9841
1.43
Total payments to IPFs would remain
the same, but there would be significant
distributional impacts, which would
reduce payments to IPFs with a lower
MSNI and increase payments to IPFs
with a higher MSNI. We refer readers to
section IV.A.4 of this proposed rule for
informational analysis and discussion of
the potential distributional impacts
estimated for the MSNI payment
adjustment.
We note that for certain elements of
the MSNI calculation, some data was
not available for IPFs at the same level
of detail available for IPPS hospitals. We
also identified that for some elements,
data reported by IPFs may be
incomplete. First, as mentioned above,
both UCC amounts and total revenue
Hospitals
0.8780
1.39
Units
0.9940
1.43
amounts are reported at the hospital
level only. As a result, we were able to
calculate a UCC ratio for IPF units based
on the overall ratio of the hospital’s
UCC to its revenues. This assumes that
a hospital’s overall UCC ratio would be
comparable to that of its IPF unit.
However, because we lack unit-level
data, we are not able to validate this
assumption. Table 20 shows that most
freestanding IPF hospitals are not
reporting any UCC, which leads to
lower MSNI values for these IPFs. We
recognize that the absence of UCC for
nonprofit IPFs, which we believe in fact
provide a significant amount of UCC,
may reflect differences in reporting,
rather than provision of UCC.
Table 20: Mean Values ofMSNI and its Components by Facility Type
There are also a number of key
differences between our analysis and
the way that MedPAC has
recommended that MSNI be applied to
payments in the IPPS setting. For the
IPPS, MedPAC recommends to the
Congress in their March 2023 report that
they create an MSNI pool of funds for
MSNI add-on payments of about $2
billion, which could be increased each
year by the market basket update.
MedPAC contemplates hospitals
choosing between an MSNI payment
and other special payment rates
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Hos itals
0.7296
Units
designed to protect access, for example,
in rural areas, or the adoption of a
percentage-based cap on all special
payment rates.8 In contrast, our
modeling of an MSNI payment
adjustment in the IPF PPS, assumes that
IPFs could be eligible for both an MSNI
payment and the payment adjustment
8 Medicare Payment Advisory Commission.
(2023). Report to the Congress: Medicare Payment
Policy. Available at: https://www.medpac.gov/wpcontent/uploads/2023/03/Ch3_Mar23_MedPAC_
Report_To_Congress_SEC_v2.pdf. Accessed on
January 22, 2024.
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Hos itals
Units
for rural location, for example, without
a cap imposed. Our modeling also
assumes that an MSNI payment
adjustment would be budget neutral; in
other words, the payment would not be
an add-on. In contrast to the
recommended approach for the IPPS,
which would come from a new funding
pool, we estimate that the application of
an MSNI adjustment would affect the
Federal IPF PPS per diem base rate. As
a result, the MSNI payment in our
model would represent a redistribution
of funds within the IPF PPS, as is
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statutorily required under section
4125(a) of the CAA, 2023.
We constructed the MSNI variable in
our regression model similarly to the
construction of the teaching adjustment
(that is, as the natural log of a facility’s
MSNI ratio plus 1). Consequently, a
payment adjustment derived from our
regression results would work like the
teaching status adjustment: the MSNI
adjustment factor is expressed in an unexponentiated form. A provider’s MSNI
factor plus one would be raised to the
power of the MSNI adjustment factor to
calculate the facility’s MSNI payment
adjustment.
We are considering the potential
operational changes that would be
necessary to implement an adjustment
for MSNI in the future. For example, we
anticipate the need to periodically
recalculate facilities’ MSNI ratios,
which could potentially correspond to a
facility’s cost report settlement process.
We also anticipate the need to develop
a reconciliation process, should such an
adjustment for MSNI be implemented in
the future. Further, we expect that
because a facility’s LIS ratio would not
be an available data element on the
hospital cost report, we may need to
develop and publish a facility-level file
with this information or consider
collecting additional data on the
hospital cost report. As discussed in the
following section, we are seeking public
comment on our regression results, as
well as our methodology used to
construct the MSNI variable for IPFs,
and on the operational considerations
we have noted. We note that future
additional data and analysis produce
results that differ from those presented
in this proposed rule.
(3) Request for Information
We are particularly seeking comment
on the following questions:
• Should we consider adjusting
payment using MedPAC’s MSNI
formula with adaptations, as described
above? What, if any, changes to the
methodology should we consider for the
IPF setting? For example, should we
develop a separate payment adjustment
for each component (that is, the lowincome ratio, uncompensated care ratio,
and Medicare dependency ratio)?
• We note that our construction of the
MSNI did not scale or index facilitylevel variables to a national standard or
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median value. We anticipate that doing
so would result in less of a change to the
IPF Federal per diem base rate but
would still result in comparable
distributional impacts (that is, IPFs with
lower MSNIs would receive lower
payments, and IPFs with higher MSNIs
would receive higher payments). Should
we consider scaling or indexing the
MSNI to a national average MSNI for all
IPFs?
• Is MedPAC’s MSNI formula, as
adapted, an accurate and appropriate
measure of the extent to which an IPF
acts as a safety-net hospital for Medicare
beneficiaries?
• Should additional data be collected
through the cost report to improve the
calculation of MSNI, such as collecting
UCC and revenue at the IPF unit level?
• Is the current cost report data
submitted by IPFs sufficiently valid and
complete to support the implementation
of an MSNI payment? We note our
concerns about the low or non-existent
amounts reported for uncompensated
care for freestanding IPFs and the use of
hospital-level UCC and revenue
amounts to calculate the UCC ratio for
IPF units.
• What administrative burden or
challenges might providers face in
reporting their UCC and low-income
patient stays?
• Would IPFs have the information
necessary to report their low-income
patient stays to CMS for the purpose of
the MSNI calculation? What challenges
might IPFs face in gathering and
reporting this information?
• In the FY 2023 IPPS proposed rule,
CMS noted that, when calculating the
MSNI, the following circumstances may
be encountered: new hospitals (for
example, hospitals that begin
participation in the Medicare program
after the available audited cost report
data), hospital mergers, hospitals with
multiple cost reports and/or cost
reporting periods that are shorter or
longer than 365 days, cost reporting
periods that span fiscal years, and
potentially aberrant data. How should
CMS consider addressing these
circumstances when calculating the
MSNI for IPFs?
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4. Informational Impacts of Potential
Facility-Level Revisions on IPF PPS
Payments
We estimate that an MSNI payment
adjustment in concert with the potential
rural payment adjustment and teaching
adjustments detailed in this section
would have a refinement
standardization factor of 0.7202. In
other words, adoption of these facilitylevel payment adjustments as described
in this section of this proposed rule
would decrease the Federal per diem
base rate by $244.81. In contrast, we
estimate that updating only the rural
and teaching adjustments without MSNI
would have a refinement
standardization factor of 0.9926, which
would decrease the Federal per diem
base rate by $6.48.
Estimates of distributional impacts by
facility type, location, ownership,
teaching status, and region are detailed
in Table 21. We are seeking public
comment on these informational
impacts to potentially inform future
rulemaking.
To illustrate the impacts of these
potential changes to the IPF PPS
facility-level adjustments, our analysis
begins with the same FY 2023 IPF PPS
claims (based on the 2023 MedPAR
claims, December 2023 update) as
discussed in section VIII.C of this
proposed rule. We begin with estimated
FY 2025 IPF PPS payments using these
2023 claims, the proposed FY 2025 IPF
PPS Federal per diem base rate and ECT
per treatment amount, the proposed
refinements to the FY 2025 IPF PPS
patient and facility level adjustment
factors, and the proposed FY 2025 IPF
PPS wage index. At each stage, total
outlier payments are maintained at 2
percent of total estimated FY 2025 IPF
PPS payments.
Each of the following changes is
added incrementally to this baseline
model in order for us to isolate the
effects of each change:
• The potential updates to the IPF
teaching adjustment and rural
adjustment, without the addition of an
adjustment for MSNI.
• Adding an adjustment for MSNI
and reducing the IPF rural adjustment
and teaching adjustment as shown in
the third column of Tables 17 and 18 of
this proposed rule.
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Table 21 - Informational Impacts of Potential Facility-Level Revisions
Update Rural Update Rural,
and Teaching, Teaching, and
Number of Facilities without MSNI
MSNI
Facility by Type
(2)
(1)
All Facilities
Overall
Impact
(6)
(4)
(3)
1,430
0.0
0.0
0.0
1.171
0.0
1.9
-2.3
-0.1
2.0
-2.7
Total Urban
Urban unit
Urban hospital
655
516
-0.1
0.1
-0.4
Total Rural
Rural unit
Rural hospital
259
199
60
0.9
1.0
0.9
-0.2
-0.4
0.3
0.7
0.5
1.2
117
98
301
1.4
-0.4
-0.7
-2.1
-2.5
-2.3
-0.7
-2.8
-3.0
30
12
18
0.9
0.8
0.9
-1.8
-2.6
2.0
-0.9
-1.7
2.9
95
436
124
1.0
0.0
-0.5
3.0
1.5
2.0
4.0
1.5
1.5
45
114
40
0.9
1.0
0.9
-0.5
-0.3
-0.5
0.5
0.6
0.4
1,230
-0.4
-0.4
-0.8
Bv Tvoe of Ownership:
Freestanding IPFs
Utban Psychiatric Hospitals
Government
Non-Profit
For-Profit
Rural Psvchiatric Hospitals
Government
Non-Profit
For-Profit
IPF Units
Utban
Government
Non-Profit
For-Profit
Rural
Government
Non-Profit
For-Profit
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Update Rural Update Rural,
and Teaching, Teaching,and
Overall
Facility by Type
Impact
Number of Facilities without MSNI
MSNI
Less than 10% interns and residents to beds 104
0.3
1.2
1.5
10% to 30% interns and residents to beds
71
2.2
3.0
5.3
More than 30% interns and residents to beds 25
9.8
-3.1
6.4
By Bed Size:
Psychiatric Hospitals
Beds: 0-24
Beds: 25-49
Beds: 50-75
Beds: 76 +
Psychiatric Units
Beds: 0-24
Beds: 25-49
Beds: 50-75
Beds: 76 +
BILLING CODE 4120–01–C
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B. Request for Information (RFI)—
Patient Assessment Instrument Under
IPFQR Program (IPF PAI) To Improve
the Accuracy of the PPS
Section 4125(b)(1) of CAA, 2023
amended section 1886(s)(4) of the Act,
by inserting a new paragraph (E), to
require IPFs participating in the IPFQR
Program to collect and submit to the
Secretary certain standardized patient
assessment data, using a standardized
patient assessment instrument (PAI)
developed by the Secretary, for RY 2028
(FY 2028) and each subsequent rate
year. IPFs must submit such data with
respect to at least the admission to and
discharge of an individual from the IPF,
or more frequently as the Secretary
determines appropriate. For IPFs to
meet this new data collection and
reporting requirement for RY 2028 and
each subsequent rate year, the Secretary
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193
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102
126
0.0
0.1
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0.1
0.0
-0.4
0.0
0.5
0.8
0.1
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-1.9
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-1.9
-0.6
1.9
0.5
0.9
0.2
-0.5
-1.9
-0.4
-1.9
-1.0
2.0
87
87
92
310
0.9
-0.4
-0.5
-0.4
-2.4
-2.3
-1.6
-2.1
-1.6
-2.7
-2.1
-2.5
450
234
98
72
0.1
0.3
0.4
0.3
-0.8
3.0
3.1
2.8
-0.7
3.3
3.5
3.1
must implement a standardized PAI that
collects data with respect to the
following categories: functional status;
cognitive function and mental status;
special services, treatments, and
interventions for psychiatric conditions;
medical conditions and comorbidities;
impairments; and other categories as
determined appropriate by the
Secretary. This IPF–PAI must enable
comparison of the patient assessment
data across all IPFs which submit these
data. In other words, the data must be
standardized such that data from IPFs
participating in the IPFQR Program can
be compared; the IPF–PAI each IPF
administers must be made up of
identical questions and identical sets of
response options to which identical
standards and definitions apply.
As we develop the IPF–PAI, in
accordance with these new statutory
requirements, we seek to collect
information that will help us achieve
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the following goals: (1) improve the
quality of care in IPFs, (2) improve the
accuracy of the IPF PPS in accordance
with section 4125(b)(2) of CAA, 2023,
and (3) improve health equity.9 In this
Request for Information (RFI), we are
soliciting comments for development of
this IPF–PAI, in accordance with these
new statutory requirements, and to
achieve these goals.
This RFI consists of four sections. The
first section discusses a general
framework or set of principles for
development of the IPF–PAI. The
second section outlines potential
approaches that could be used to
develop the items or data elements that
9 For more information on our strategic goals to
improve health equity by expanding the collection,
reporting, and analysis of standardized data, we
refer readers to Priority 1 of our Framework for
Health Equity at https://www.cms.gov/priorities/
health-equity/minority-health/equity-programs/
framework.
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make up the PAI. This section also
discusses patient assessment data
elements in use in PAIs for skilled
nursing facilities and other healthcare
settings that could potentially be
adapted for use in the IPF–PAI. The
third section outlines potential
approaches that could be used to collect
patient assessment data. Finally, the
fourth section solicits public comment
on the principles and approaches listed
in the first three sections and seeks
other input regarding the IPF–PAI.
the following subsections, we believe
that these considerations are also
appropriate for the development of the
IPF–PAI. In addition, we seek to balance
the need to collect meaningful patient
data to improve care with the need to
minimize administrative burden. The
remainder of this section describes each
of these considerations in the context of
the IPF–PAI. As we discuss in section
IV.B.4.a of this proposed rule, we are
soliciting comment on these
considerations.
questions, so that certain sets of
questions are only indicated if the
questions are relevant to the patient.
Furthermore, we note that some data
elements may only be appropriate for
collection at certain times during the
patient’s stay (for example, only at
admission or only at discharge). We
solicit comments regarding the most
effective structure to employ in the
development of the IPF–PAI.
1. Framework for Development of the
IPF–PAI
We considered similar legislatively
derived PAIs previously implemented
for certain post-acute care (PAC)
providers to inform the goals and
guiding principles for the IPF–PAI
because of similarities of section 4125(b)
of CAA, 2023 to the Improving Medicare
Post-Acute Care Transformation Act of
2014 (IMPACT Act) (Pub. L. 113–185,
October 6, 2014), codified at section
1899B of the Act. Similar to section
4125(b) of CAA, 2023, section 1899B of
the Act requires certain PAC providers,
specifically home health agencies
(HHAs), skilled nursing facilities
(SNFs), inpatient rehabilitation facilities
(IRFs), and long-term care hospitals
(LTCHs), to submit certain standardized
patient assessment data (as set forth at
section 1899B(b)(1)(B)) using a
standardized PAI under the PAC
providers’ respective quality reporting
programs. While IPFs are acute care
providers and not PAC providers, given
the similarities between the CAA, 2023
and section 1899B of the Act, we
considered the goals and guiding
principles that we followed to
implement section 1899B of the Act for
certain PAC providers and examined
their applicability and appropriateness
for IPFs.
We previously identified four key
considerations when assessing
Standardized Patient Assessment Data
Elements for the PAC PAIs to collect: (1)
Overall clinical relevance; (2)
Interoperable exchange to facilitate care
coordination during transitions in care;
(3) Ability to capture medical
complexity and risk factors that can
inform both payment and quality; and
(4) Scientific reliability and validity,
general consensus agreement for its
usability.10 For the reasons discussed in
a. Overall Clinical Relevance
In each category of assessment
required by section 1886(s)(4)(E)(ii), as
added by section 4125(b) of CAA, 2023,
(functional status; cognitive function
and mental status; special services,
treatments, and interventions for
psychiatric conditions; medical
conditions and comorbidities;
impairments, and other categories as
determined appropriate by the
Secretary), we seek to establish
Standardized Patient Assessment Data
Elements that providers can use to
support high quality care and outcomes
in the IPF setting. As we evaluate
Standardized Patient Assessment Data
Elements in PAIs designed for other care
settings, we intend to work with CMS
Medical Officers, including
psychiatrists, to consider the clinical
relevance for IPF patients as a
determining factor in whether an item
merits inclusion in the IPF–PAI. For an
example of a PAI in use in another
setting, we refer readers to the IRF–PAI
instrument available at https://
www.cms.gov/files/document/irf-paiversion-40-eff-10012022-final.pdf. We
are particularly interested in learning
about specific instruments and tools in
each area of assessment that have high
clinical relevance in the IPF setting and
welcome comments regarding
Standardized Patient Assessment Data
Elements that may not be clinically
relevant to the IPF setting.
To ensure the clinical relevance of the
instrument across a diverse group of IPF
patients, we are considering structuring
the assessment with conditional
Interoperability is a key priority and
initiative at CMS. Across the
organization, we aim to promote the
secure exchange, access, and use of
electronic health information to support
better informed decision making and a
more efficient healthcare system. As a
part of this effort, we make
interoperability a priority for
standardized data collection. We intend
to ensure that the IPF–PAI meets Health
Level 7® (HL7®) Fast Healthcare
Interoperability Resources® (FHIR®)
standards.
As part of our interoperability
considerations, we are interested in
whether Standardized Patient
Assessment Data Elements already in
use in the CMS Data Element Library
(DEL) are appropriate and clinically
relevant for the IPF setting. In CY 2021,
approximately 8,000 admissions to IPFs
were individuals transferred from SNFs
or IRFs. We are interested in whether
Standardized Patient Assessment Data
Elements already used in the DEL can
be used to better support
interoperability between providers,
given the high number of transfers.
10 We refer readers to the Prospective Payment
System and Consolidated Billing for Skilled
Nursing Facilities; Updates to the Quality Reporting
Program and Value-Based Purchasing Program for
Federal fiscal year 2020 final rule (84 FR 38767);
the Medicare Program; Inpatient Rehabilitation
Facility (IRF) Prospective Payment System for
Federal fiscal year 2020 and Updates to the IRF
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Quality Reporting Program final rule (84 FR 39110),
the Medicare and Medicaid Programs; CY 2020
Home Health Prospective Payment System Rate
Update; Home Health Value-Based Purchasing
Model; Home Health Quality Reporting
Requirements; and Home Infusion Therapy
Requirements CY 2020 final rule (84 FR 60567), and
the Medicare Program; Hospital Inpatient
Prospective Payment Systems for Acute Care
Hospitals and the Long-Term Care Hospital
Prospective Payment System and Policy Changes
and fiscal year 2020 Rates; Quality Reporting
Requirements for Specific Providers; Medicare and
Medicaid Promoting Interoperability Programs
Requirements for Eligible Hospitals and Critical
Access Hospitals final rule (84 FR 42537).
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b. Interoperability
c. Ability To Capture Medical
Complexity and Risk Factors
We intend to expand our efforts to
refine the IPF PPS to increase the
accuracy of the payment system by
better identifying patient characteristics
that best predict resource use during an
IPF stay. To identify Standardized
Patient Assessment Data Elements that
would help predict resource use, we
intend to evaluate Standardized Patient
Assessment Data Elements for their
ability to explain medical complexity,
the need for special services and
treatments, and to measure case-mix
differences that impact costs. It is our
expectation that an IPF–PAI that
effectively differentiates treatment
needs between patients will also help
IPFs plan and distribute their resources.
Our hope is that the IPF–PAI can
therefore integrate with IPFs’ business
practices. In addition, Standardized
Patient Assessment Data Elements that
capture patient risk factors can
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contribute to quality of care and patient
safety.
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d. Scientific Reliability and Validity
Standardized Patient Assessment Data
Elements considered for inclusion in the
IPF–PAI must be scientifically reliable
and valid in IPF settings. We intend to
draw on our significant experience in
development of quality measures in the
IPFQR Program and development of
Standardized Patient Assessment Data
Elements for other PAIs, such as the
IRF–PAI and the Minimum Data Set
(MDS) (the PAI for SNFs), in our
development of Standardized Patient
Assessment Data Elements for the IPF–
PAI.11 It is important to note that the
statutorily required timeframe for
implementation of the IPF–PAI for RY
2028 limits our ability to develop and
test a full battery of new Standardized
Patient Assessment Data Elements for
the launch of the IPF–PAI. We
anticipate the need and opportunity for
incremental revisions to the IPF–PAI in
the future.
We anticipate that our development
process for new Standardized Patient
Assessment Data Elements will include
working with teams of researchers for
each category including a group of
advisors made up of clinicians and
academic researchers for each team with
expertise in IPFs. We expect to convene
a Technical Expert Panel (TEP) to
provide expert input on new and
existing Standardized Patient
Assessment Data Elements that merit
consideration for inclusion and testing,
including environmental scans and
reviews of scientific literature. In an
ideal scenario, Standardized Patient
Assessment Data Elements would be
tested in a representative sample of IPFs
for appropriateness in different IPF
settings and across a range of patients.
Standardized Patient Assessment Data
Elements would be tested for inter-rater
(that is, consistency in results regardless
of who is administering the assessment)
and inter-organizational reliability, for
validity in all IPF settings, for internal
consistency, and for breadth of
application among a range of IPF
patients. We anticipate that
Standardized Patient Assessment Data
11 For more information on other PAIs, we refer
readers to https://www.cms.gov/medicare/payment/
prospective-payment-systems/inpatientrehabilitation/pai (for the IRF–PAI), to https://
www.cms.gov/medicare/quality/home-health/oasisdata-sets (for the OASIS data set for HHAs), to
https://www.cms.gov/medicare/quality/long-termcare-hospital/ltch-care-data-set-ltch-qrp-manual
(for the CARE data set for LTCHs), and to https://
www.cms.gov/medicare/quality/nursing-homeimprovement/resident-assessment-instrumentmanual (for the Minimum Data Set (MDS) Resident
Assessment Instrument (RAI)).
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Elements would also need to be tested
for their ability to detect differences
among patients and costs of treatment.
Due to the constraints of the statutorily
required implementation timeframe, it
may not be possible to complete all
testing before launching the IPF–PAI.
The process for scientifically testing
each question and set of responses is
lengthy and resource-intensive. This
process is based on the steps for quality
measure development described in the
Blueprint Measure Lifecycle,12
developed by the CMS Measures
Management System. These steps
include literature review and
environmental scanning; various levels
of field testing to understand the ‘‘real
world’’ performance of the data
elements; and iterative expert and
interested parties engagement to include
broader perspectives on topics,
candidate data elements, and
interpretation of testing results. If
appropriate, using data currently
collected by IPFs or Standardized
Patient Assessment Data Elements that
have been tested and validated for use
in other clinical settings can reduce
these timeframes because test data are
already available.
e. Administrative Burden
In evaluating Standardized Patient
Assessment Data Elements for inclusion
in the IPF–PAI, we are considering the
burden of data collection through the
PAI and aiming to minimize additional
burden by considering whether any data
that is currently collected through
IPFQR Program measures or on IPF
claims could be collected as
Standardized Patient Assessment Data
Elements to avoid duplication of data
that IPFs are already reporting. We are
also considering how collecting some
data for some IPFQR Program measures
through the IPF–PAI and collecting
other data through the Hospital Quality
Reporting (HQR) system would affect
the reporting burden for participating
IPFs. Licensing, permissions costs, or
copyright restrictions that would add to
administrative costs and burdens are
also a consideration as we evaluate
existing PAIs and mechanisms or tools
for submitting IPF–PAI data.
As we develop the IPF–PAI, we are
interested in receiving information
about how to find a balance between
collecting the most relevant and useful
information and the administrative
burden of administering the assessment
and submitting the assessment data.
12 https://mmshub.cms.gov/blueprint-measurelifecycle-overview.
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2. Elements of the IPF–PAI
Section 1886(s)(4)(E)(ii) of the Act,
added by section 4125(b)(1)(C) of the
CAA, 2023, requires that the
standardized patient assessment data to
be collected in the IPF–PAI must be
with respect to six enumerated
categories.
a. Functional Status
The first enumerated category of data
for the IPF–PAI is functional status.
Section 1886(s)(4)(E)(ii)(I) of the Act
provides that functional status may
include mobility and self-care at
admission to a psychiatric hospital or
unit and before discharge from a
psychiatric hospital or unit. We note
that information in this category is
generally found in a patient’s discharge
summary and are interested in learning
about standardized elements that
correspond to functional status as
relevant to IPFs. We are interested in
what assessments may be currently in
use in the IPF setting and meet criteria
for inclusion in the IPF–PAI.
b. Cognitive Function and Mental Status
The second enumerated category of
data for the IPF–PAI is cognitive
function and mental status. Section
1886(s)(4)(E)(ii)(II) of the Act provides
that cognitive function may include the
ability to express ideas and to
understand, and mental status may
include depression and dementia. We
note that in the IPF setting, a patient’s
diagnoses, which can be abstracted from
their medical chart, provide some
information related to this category. We
are aware that IPFs may be currently
assessing cognitive function using
existing instruments. We are interested
in hearing from IPFs about which
instruments are currently in use to
measure cognitive function in IPFs and
which have high clinical relevance for
the IPF setting.
c. Special Services, Treatments, and
Interventions
The third enumerated category of data
for the IPF–PAI is special services,
treatments, and interventions for
psychiatric conditions. Section
1886(s)(4)(E)(ii)(III) of the Act neither
addresses what these terms mean nor
provides any illustrative examples. As
discussed in section V.C. of this rule,
the IPFQR Program already collects
information about the use of restraint
and seclusion through quality measures
(Hospital Based Inpatient Psychiatric
Services (HBIPS)–2, Hours of Physical
Restraint, and HBIPS–3, Hours of
Seclusion Use), while claims include
information about ECT treatments
provided. Other areas of interest in this
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category may include high-cost
medications, use of chemical restraints,
one-to-one observation, and high-cost
technologies. We are interested in
whether these or any other special
services, treatments, or interventions
should be considered for inclusion in
the IPF–PAI.
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d. Medical Conditions and
Comorbidities
The fourth enumerated category of
data for the IPF–PAI is medical
conditions and comorbidities. Section
1886(s)(4)(E)(ii)(IV) of the Act provides
that medical conditions and
comorbidities may include diabetes,
congestive heart failure, and pressure
ulcers. We note that IPF claims record
a significant number of medical
conditions and comorbidities to receive
the payment adjustment for
comorbidities in the IPF PPS and
conditions that are relevant to the IPF
stay. In reviewing Standardized Patient
Assessment Data Elements listed in this
category in PAIs in use in PAC settings,
we observed that these PAIs include
Standardized Patient Assessment Data
Elements regarding pain interference in
this category, such as the effect of pain
on sleep, pain interference with therapy
activities, and pain interference with
day-to-day activities. We are interested
in learning from commenters whether
these existing data elements from the
PAC settings would be clinically
relevant for inclusion in this category
for the IPF–PAI.
e. Impairments
The fifth enumerated category of data
for the IPF–PAI is impairments. Section
1886(s)(4)(E)(ii)(V) of the Act provides
that impairments may include
incontinence and an impaired ability to
hear, see, or swallow. PAIs in use in
other settings include Standardized
Patient Assessment Data Elements
regarding hearing and vision (for
example, Section B, ‘‘Hearing, Speech,
and Vision’’ of the IRF–PAI Version 4.2
(Effective October 1, 2024)).13 We are
interested both in whether Standardized
Patient Assessment Data Elements
regarding additional impairments merit
consideration for the IPF–PAI, and
whether the Standardized Patient
Assessment Data Elements regarding
hearing and vision included in the IRF–
PAI are appropriate for the IPF setting.
We note that the Standardized Patient
Assessment Data Element categories are
not intended to be duplicative, so we
would seek to avoid any overlap in
measuring cognitive deficits in the
13 https://www.cms.gov/files/document/irf-paiversion-42-effective-10-01-24.pdf.
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Cognitive Function category with the
Impairments category.
f. Other Categories Deemed Appropriate
The sixth enumerated category of data
for the IPF–PAI is other categories as
determined appropriate by the
Secretary. We believe this provision
allows for flexibility to include
additional areas in the IPF–PAI.
One of our strategic priorities, as laid
out in the CMS Strategic Plan,14 reflects
our deep commitment to improvements
in health equity by addressing the
health disparities that underlie our
health system. In line with that strategic
priority, we are interested in
Standardized Patient Assessment Data
Elements that would provide insight
about any demographic factors (for
example, race, national origin, primary
language, ethnicity, sexual orientation,
and gender identity) as well as SDOH
(for example, housing status and food
security) associated with underlying
inequities. We are also interested in
whether there are Standardized Patient
Assessment Data Elements that would
provide insight into special
interventions that IPFs are providing to
support patients after discharge which
could serve to potentially reduce the
incidence of readmissions.
We note that, beginning with
mandatory reporting of CY 2025 data for
FY 2027 payment determination, the
IPFQR Program includes the Screening
for SDOH measure, which assesses the
percentage of patients, aged 18 years
and over at the time of admission, who
are screened for five specific healthrelated social needs (HRSNs)—food
insecurity, housing instability,
transportation needs, utility difficulties,
and interpersonal safety, but which does
not require reporting of that information
at the patient-level (88 FR 51117).
Furthermore, we note that PAIs adopted
for the PAC settings discussed
previously include collection of SDOH
data under section 1899B(b)(1)(B)(vi) of
the Act, which contains a similar
provision for other categories deemed
appropriate by the Secretary.15
14 The CMS Strategic Plan. Available at https://
www.cms.gov/about-cms/what-we-do/cms-strategicplan. Accessed February 20, 2024.
15 For further information detailing the rationale
for adopting SDOH Standardized Patient
Assessment Data Elements in these settings, we
refer readers to the Prospective Payment System
and Consolidated Billing for Skilled Nursing
Facilities; Updates to the Quality Reporting
Program and Value-Based Purchasing Program for
Federal fiscal year 2020 final rule (84 FR 38805
through 38817); the Medicare Program; Inpatient
Rehabilitation Facility (IRF) Prospective Payment
System for Federal fiscal year 2020 and Updates to
the IRF Quality Reporting Program final rule (84 FR
39149 through 38161), the Medicare and Medicaid
Programs; CY 2020 Home Health Prospective
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We note that, if we deem it
appropriate to add a SDOH category for
the IPF–PAI and these SDOH data are
included as Standardized Patient
Assessment Data Elements in the PAI,
they could potentially be used to risk
adjust or stratify measures collected for
the IPFQR Program. We are interested in
learning whether using some of these
SDOH data adopted in other PAIs to risk
adjust or stratify these measures would
make the measures in the IPFQR
Program more meaningful.
3. Implementation of the PAI—Data
Submission
We plan to develop flexible methods
for providers to submit IPF–PAI data to
CMS, including batch uploads in
specified formats and a portal for
submission of files. We welcome public
comment on tools and methods for
submission of data that balance
administrative burden and ease of use.
4. Request for Information on IPF–PAI
In this proposed rule, we are
requesting information from the public
to inform the selection of Standardized
Patient Assessment Data Elements to be
collected on the IPF–PAI and the
implementation process. We are seeking
information about PAIs IPFs currently
use upon admission and discharge, as
well as information about how IPFs
estimate resource needs to determine
capacity before a patient is admitted.
We are also seeking information about
methods for IPFs to submit patient
assessment data and the potential
administrative burden on IPFs, MACs,
and CMS. Finally, we are seeking input
on the relationship between the IPF–PAI
and the measures within the IPFQR
Program.
We solicit comment on the following
topics:
a. Principles for Selecting Standardized
Patient Assessment Data Elements
• To what extent do you agree with
the principles for selecting and
developing Standardized Patient
Assessment Data Elements for the IPF–
PAI?
• What, if any, principles should
CMS eliminate from the Standardized
Payment System Rate Update; Home Health ValueBased Purchasing Model; Home Health Quality
Reporting Requirements; and Home Infusion
Therapy Requirements CY 2020 final rule (84 FR
60597 through 60608), and the Medicare Program;
Hospital Inpatient Prospective Payment Systems for
Acute Care Hospitals and the Long-Term Care
Hospital Prospective Payment System and Policy
Changes and fiscal year 2020 Rates; Quality
Reporting Requirements for Specific Providers;
Medicare and Medicaid Promoting Interoperability
Programs Requirements for Eligible Hospitals and
Critical Access Hospitals final rule (84 FR 42577
through 42588).
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services and treatments (such as HBIPS–
2 Hours of Physical Restraint Use and
HBIPS–3 Hours of Seclusion Use) meet
the criteria for inclusion in the IPF–PAI?
Patient Assessment Data Element
selection criteria?
• What, if any, principles should
CMS add to the Standardized Patient
Assessment Data Element selection
criteria?
b. Patient Assessments Recommended
for Use in the IPF–PAI
• Are there PAIs currently available
for use, or that could be adapted or
developed for use in the IPF–PAI, to
assess patients’: (1) functional status; (2)
cognitive function and mental status; (3)
special services, treatments, and
interventions for psychiatric conditions;
(4) medical conditions and
comorbidities; (5) impairments; (6)
health disparities; or (7) other areas not
mentioned in this RFI?
c. Functional Status Standardized
Patient Assessment Data Elements
• What aspects of function are most
predictive of medical complexity or
increased resource needs to treat a
patient in the IPF setting?
• Which of the Standardized Patient
Assessment Data Elements related to
mobility (that is, the ability to toilet
transfer, walk 10 feet, car transfer, walk
10 feet on an uneven surface, 1 step up
(that is, a curb), 4 steps up, 12 steps up,
and pick up an object) currently
collected by PAC settings in their
respective PAIs are clinically relevant in
the IPF setting? Do they otherwise meet
the principles for inclusion in the IPF–
PAI?
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d. Cognitive Function and Mental Status
Standardized Patient Assessment Data
Elements
• What aspects of cognitive function
and mental status are most predictive of
medical complexity or increased
resource needs to treat a patient in the
IPF setting?
• What components or instruments
are used to assess cognitive function,
mental status, or a combination thereof
upon admission? What, if any,
differences are there between
assessments administered at admission
and at discharge? What are the
components of the mental status
assessments administered at admission
and discharge?
e. Special Services, Treatments, and
Interventions for Psychiatric Conditions
Standardized Patient Assessment Data
Elements
• What special services, treatments,
and interventions are most predictive of
increased resource intensity during an
IPF stay?
• Do data currently collected as part
of the IPFQR Program related to special
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f. Medical Conditions and
Comorbidities Standardized Patient
Assessment Data Elements
• Is the Standardized Patient
Assessment Data Element regarding
pain interference (effect on sleep,
interference with therapy activities,
interference with day-to-day activities)
currently collected by PAC settings in
their respective PAIs clinically relevant
in the IPF setting? Does it otherwise
meet the criteria for inclusion in the
IPF–PAI?
• Do the medical conditions and
comorbidities coded on IPF claims meet
the criteria for inclusion in the IPF–PAI?
operationalize? We are particularly
interested in impacts to facilities of
varying sizes and ownership
characteristics.
• What forms of training and
guidance would be most useful for CMS
to provide to support IPFs in the
implementation of the IPF–PAI?
g. Impairments Standardized Patient
Assessment Data Elements
• Are Standardized Patient
Assessment Data Elements related to
impairments (that is, the ability to hear
and see in adequate light) currently
collected PAC settings in their
respective PAIs clinically relevant in the
IPF setting? Do they otherwise meet the
principles for inclusion in the IPF–PAI?
• What impairments are most
predictive of increased resource
intensity during an IPF stay?
j. Relationship to the IPFQR Program
• Would having some measures
which require data submission through
the HQR system and having other
measures, which require data collection
and submission through the IPF–PAI
increase operational complexity or
administrative burden? If so, how would
you recommend mitigating this
complexity or burden?
• Would any of the current chartabstracted measures be easier to report
through the IPF–PAI? If so, which
measures?
• Would any of the current measures
in the program be more meaningful if
they were stratified or risk-adjusted
using data from the required patient
assessment categories or other categories
not specified by the CAA, 2023 that
should be added to the IPF–PAI?
• What new measure concepts, which
would use data collected through
Standardized Patient Assessment Data
Elements in the IPF–PAI, should we
consider?
h. Other Categories of Standardized
Patient Assessment Data Elements
V. Inpatient Psychiatric Facility Quality
Reporting (IPFQR) Program
• What other assessment elements
would contribute to the clinical utility
of the IPF–PAI?
• What other assessment elements
would best capture medical complexity
in the interest of refining and improving
the accuracy of the IPF PPS?
• What other assessment elements
would inform CMS’s understanding of
health equity for IPF patients?
• Are there special interventions that
IPFs provide which support patients
after discharge, and which could serve
to reduce the incidence of hospital
readmissions for psychiatric conditions?
What, if any, assessment elements
would inform CMS’s understanding of
such interventions?
A. Background and Statutory Authority
The Inpatient Psychiatric Facility
Quality Reporting (IPFQR) Program is
authorized by section 1886(s)(4) of the
Act, and it applies to psychiatric
hospitals and psychiatric units paid by
Medicare under the IPF PPS (see section
II.A. of this proposed rule for a detailed
discussion of entities covered under the
IPF PPS). Section 1886(s)(4)(A)(i)
requires the Secretary to reduce by 2
percentage points the annual update to
the standard Federal rate for discharges
occurring during such rate year 16 for
i. Implementation
• We anticipate that IPFs will need to
make changes to systems and processes
and train staff in order to administer the
assessment and submit assessment data
by the implementation date. What
operational or practical limitations
would IPFs face in making those
necessary changes? Are there particular
categories of Standardized Patient
Assessment Data Elements that would
be more or less feasible for IPFs to
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16 We note that the statute uses the term ‘‘rate
year’’ (RY). However, beginning with the annual
update of the inpatient psychiatric facility
prospective payment system (IPF PPS) that took
effect on July 1, 2011 (RY 2012), we aligned the IPF
PPS update with the annual update of the ICD
codes, effective on October 1 of each year. This
change allowed for annual payment updates and
the ICD coding update to occur on the same
schedule and appear in the same Federal Register
document, promoting administrative efficiency. To
reflect the change to the annual payment rate
update cycle, we revised the regulations at 42 CFR
412.402 to specify that, beginning October 1, 2012,
the IPF PPS RY means the 12-month period from
October 1 through September 30, which we refer to
as a ‘‘fiscal year’’ (FY) (76 FR 26435). Therefore,
with respect to the IPFQR Program, the terms ‘‘rate
year,’’ as used in the statute, and ‘‘fiscal year’’ as
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any IPF that does not comply with
quality data submission requirements
under IPFQR program, set forth in
section 1886(s)(4)(C) of the Act, with
respect to an applicable rate year.
Section 1886(s)(4)(C) of the Act
requires IPFs to submit to the Secretary
data on quality measures specified by
the Secretary under section
1886(s)(4)(D) of the Act. Except as
provided in section 1886(s)(4)(D)(ii) of
the Act, section 1886(s)(4)(D)(i) of the
Act requires that any measure specified
by the Secretary must have been
endorsed by the consensus-based entity
(CBE) with a contract under section
1890(a) of the Act. Section
1886(s)(4)(D)(ii) of the Act provides that,
in the case of a specified area or medical
topic determined appropriate by the
Secretary for which a feasible and
practical measure has not been endorsed
by the CBE with a contract under
section 1890(a) of the Act, the Secretary
may specify a measure that is not
endorsed as long as due consideration is
given to measures that have been
endorsed or adopted by a consensus
organization identified by the Secretary.
Section 4125(b)(1) of CAA, 2023
amended section 1886(s)(4) of the Act,
by inserting a new paragraph (E), to
require IPFs participating in the IPFQR
Program to collect and submit to the
Secretary certain standardized patient
assessment data, using a standardized
patient assessment instrument (PAI)
developed by the Secretary, for RY 2028
(FY 2028) and each subsequent rate
year. We refer readers to section IV.B of
this proposed rule in which we solicit
public comment on the development of
this PAI.
We refer readers to the FY 2019 IPF
PPS final rule (83 FR 38589) for a
discussion of the background and
statutory authority of the IPFQR
Program. We have codified procedural
requirements and reconsideration and
appeals procedures for IPFQR Program
decisions in our regulations at 42 CFR
412.433 and 412.434. Consistent with
previous IPFQR Program regulations, we
refer to both inpatient psychiatric
hospitals and psychiatric units as
‘‘facilities’’ or ‘‘IPFs.’’ This usage
follows the terminology in our IPF PPS
regulations at § 412.402.
For additional information on
procedural requirements related to
statutory authority, participation and
withdrawal, data submission, quality
measure retention and removal,
extraordinary circumstances exceptions,
used in the regulation, both refer to the period from
October 1 through September 30. For more
information regarding this terminology change, we
refer readers to section III of the RY 2012 IPF PPS
final rule (76 FR 26434 through 26435).
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and public reporting we refer readers to
42 CFR 412.433 Procedural
requirements under the IPFQR Program.
For the IPFQR Program, we refer to
the year in which an IPF would receive
the 2-percentage point reduction to the
annual update to the standard Federal
rate as the payment determination year.
An IPF generally meets IPFQR Program
requirements by submitting data on
specified quality measures in a specified
time and manner during a data
submission period that occurs prior to
the payment determination year. These
data reflect a period prior to the data
submission period during which the IPF
furnished care to patients; this period is
known as the performance period. For
example, for a measure for which CY
2025 is the performance period which is
required to be submitted in CY 2026 and
affects FY 2027 payment determination,
if an IPF did not submit the data for this
measure as specified during CY 2026
(and meets all other IPFQR Program
requirements for the FY 2027 payment
determination) we would reduce by 2percentage points that IPF’s update for
the FY 2027 payment determination
year.
B. Measure Adoption
We strive to put patients and
caregivers first, ensuring they are
empowered to partner with their
clinicians in their healthcare decision
making using information from data
driven insights that are increasingly
aligned with meaningful quality
measures. We support technology that
reduces burden and allows clinicians to
focus on providing high-quality
healthcare for their patients. We also
support innovative approaches to
improve quality, accessibility, and
affordability of care while paying
particular attention to improving
clinicians’ and beneficiaries’
experiences when interacting with our
programs. In combination with other
efforts across HHS, we believe the
IPFQR Program helps to incentivize
IPFs to improve healthcare quality and
value while giving patients and
providers the tools and information
needed to make the best individualized
decisions. Consistent with these goals,
our objective in selecting quality
measures for the IPFQR Program is to
balance the need for information on the
full spectrum of care delivery and the
need to minimize the burden of data
collection and reporting. We have
primarily focused on measures that
evaluate critical processes of care that
have significant impact on patient
outcomes and support CMS and HHS
priorities for improved quality and
efficiency of care provided by IPFs.
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23205
When possible, we also propose to
incorporate measures that directly
evaluate patient outcomes and
experience. We refer readers to the CMS
National Quality Strategy,17 the
Behavioral Health Strategy,18 the
Framework for Health Equity,19 and the
Meaningful Measures Framework 20 for
information related to our priorities in
selecting quality measures.
1. Measure Selection Process
Section 1890A(a) of the Act requires
that the Secretary establish and follow
a pre-rulemaking process, in
coordination with the CBE contracted
under 1890(a) of the Act, to solicit input
from multi-stakeholder groups on the
selection of quality and efficiency
measures for the IPFQR Program. Before
being proposed for inclusion in the
IPFQR Program, measures are placed on
a list of Measures Under Consideration
(MUC list), which is published
annually. Following publication on the
MUC list, a multi-stakeholder group
convened by the CBE reviews the
measures under consideration for the
IPFQR Program, among other federal
programs, and provides input on those
measures to the Secretary. Under the
Partnership for Quality Measurement
(PQM), which is convened by the entity
which currently holds the contract
under 1890(a) of the Act, this process is
known as the Pre-Rulemaking Measure
Review (PRMR). We consider the input
and recommendations provided by this
multi-stakeholder group in selecting all
measures for the IPFQR Program,
including the 30-Day Risk-Standardized
All-Cause Emergency Department (ED)
Visit Following an IPF Discharge
measure discussed in this proposed
rule.
17 Schreiber, M, Richards, A, et al. (2022). The
CMS National Quality Strategy: A Person-Centered
Approach to Improving Quality. Available at:
https://www.cms.gov/blog/cms-national-qualitystrategy-person-centered-approach-improvingquality.
18 CMS. (2022). CMS Behavioral Health Strategy.
Available at https://www.cms.gov/cms-behavioralhealth-strategy.
19 CMS. (2022). CMS Framework for Health
Equity 2022–2032. Available at https://
www.cms.gov/files/document/cms-frameworkhealth-equity-2022.pdf.
20 CMS. (2023). Meaningful Measures 2.0: Moving
from Measure Reduction to Modernization.
Available at https://www.cms.gov/medicare/
quality/meaningful-measures-initiative/meaningfulmeasures-20. Accessed on March 20, 2024.
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2. Proposal To Adopt the 30-Day RiskStandardized All-Cause ED Visit
Following an IPF Discharge Measure
Beginning With the CY 2025
Performance Period/FY 2027 Payment
Determination
a. Background
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We have consistently stated our
commitment to identifying measures
that examine the care continuum for
patients with mental health conditions
and substance use disorders and to
quantify outcomes following IPFdischarge (see for example, the adoption
of the Medication Continuation
Following Hospitalization in an IPF
measure in the FY 2020 IPF PPS Final
Rule, 84 FR 38460 through 38462). Postdischarge outcomes are an important
part of our measurement strategy
because patient-centered discharge
planning and coordination of care for
patients with any combination of mental
health conditions and substance use
disorders improves long-term outcomes,
including reducing readmissions and
other post-discharge acute care
services.21 22
Although not all post-discharge acute
care visits are preventable, there are
actions that the IPF can take to
maximize the chance for patients’
successful community reintegration.23
For example, care transition models to
reduce the need for additional acute
care following an inpatient stay have
been adapted to the inpatient
psychiatric setting. To implement these
models, IPFs may need to consider how
to include the patient and their
caregivers, including family, in
discharge planning, how to
communicate with post-discharge
providers, and how to ensure wholeperson care for patients during and
following their discharge.24 Specifically,
21 Nelson, E.A. Maruish, M.E., Axler, J.L. Effects
of Discharge Planning with Outpatient
Appointments on Readmission Rates. https://
ps.psychiatryonline.org/doi/10.1176/
appi.ps.51.7.885.
22 Steffen S, Ko
¨ sters M, Becker T, Puschner B.
Discharge planning in mental health care: a
systematic review of the recent literature. Acta
Psychiatr Scand. 2009 Jul;120(1):1–9. doi: 10.1111/
j.1600–0447.2009.01373.x. Epub 2009 Apr 8. PMID:
19486329.
23 Haselden, M., Corbeil, T., Tang, F., Olfson, M.,
Dixon, L.B., Essock, S.M., Wall, M.M., Radigan, M.,
Frimpong, E., Wang, R., Lamberti, S., Schneider, M.,
& Smith, T.E. (2019). Family Involvement in
Psychiatric Hospitalizations: Associations With
Discharge Planning and Prompt Follow-Up Care.
Psychiatric Services, 70(10), 860–866. https://
doi.org/10.1176/appi.ps.201900028.
24 Pincus, Harold, Care Transition Interventions
to Reduce Psychiatric Re-Hospitalizations. National
Association of State Mental Health Program
Directors. 2015. Available at https://nasmhpd.org/
sites/default/files/Assessment%20%233_
Care%20Transitions%20Interventions
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IPFs may need to assist patients in
connecting with outpatient providers,
such as coordinating with the patient
and their caregiver to schedule the
patient’s first post-discharge follow-up
appointment, arranging for the patient’s
intensive outpatient (IOP) care, or
connecting to peer support services.
Additionally, IPFs may need to identify
and address barriers patients may face
in accessing medications and adhering
to scheduled post-discharge follow-up
appointments. Barriers may include
financial factors, transportation, and
childcare, which may necessitate
support from social services, beginning
during hospitalization and continuing
after discharge.25 26 Barriers may also
include the patient’s concerns regarding
the stigmatization associated with
seeking care post-discharge. This can be
addressed through treatment provided
during the IPF stay.27 28 Improvements
in patient experience of care and
patient-centeredness of care have been
associated with improved follow-up
post-discharge and a reduction in
patients requiring post-discharge acute
care.29 30 In summary, by proactively
addressing potential barriers to postcharge care, improving patient
experience of care and patientcenteredness of care, and implementing
care transition models, IPFs can reduce
the need for post-discharge acute care.
The IPFQR Program currently has
three measures that assess post%20toReduce%20Psychiatric
%20Rehospitalization.pdf. Accessed on January 23,
2024.
25 Allen, E.M., Call, K.T., Beebe, T.J., McAlpine,
D.D., & Johnson, P.J. (2017). Barriers to Care and
Healthcare Utilization among the Publicly Insured.
Medical Care, 55(3), 207–214. doi:10.1097/
MLR.0000000000000644.
26 Mutschler, C., Lichtenstein, S., Kidd, S.A., &
Davidson, L. (2019). Transition experiences
following psychiatric hospitalization: A systematic
review of the literature. Community Mental Health
Journal, 55(8), 1255–1274. doi:10.1007/s10597–
019–00413–9.
27 Allen, E.M., Call, K.T., Beebe, T.J., McAlpine,
D.D., & Johnson, P.J. (2017). Barriers to Care and
Healthcare Utilization among the Publicly Insured.
Medical Care, 55(3), 207–214. doi:10.1097/
MLR.0000000000000644.
28 Mutschler, C., Lichtenstein, S., Kidd, S.A., &
Davidson, L. (2019). Transition experiences
following psychiatric hospitalization: A systematic
review of the literature. Community Mental Health
Journal, 55(8), 1255–1274. doi:10.1007/s10597–
019–00413–9.
29 Donisi V, Tedeschi F, Wahlbeck K, Haaramo P,
Amaddeo F. Pre-discharge factors predicting
readmissions of psychiatric patients: a systematic
review of the literature. BMC Psychiatry. 2016 Dec
16;16(1):449. doi: 10.1186/s12888–016–1114–0.
PMID: 27986079; PMCID: PMC5162092.
30 Morgan C Shields, Mara A G Hollander, Alisa
B Busch, Zohra Kantawala, Meredith B Rosenthal,
Patient-centered inpatient psychiatry is associated
with outcomes, ownership, and national quality
measures, Health Affairs Scholar, Volume 1, Issue
1, July 2023, qxad017, https://doi.org/10.1093/
haschl/qxad017.
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discharge outcomes: (1) Follow-up After
Psychiatric Hospitalization (FAPH); (2)
Medication Continuation Following
Inpatient Psychiatric Discharge; and (3)
Thirty Day All-Cause Unplanned
Readmission Following Psychiatric
Hospitalization (CBE #2860, the IPF
Unplanned Readmission measure). Each
of these measures serves a unique role
in assessing care coordination and postdischarge outcomes.
The FAPH measure, which we
adopted in the FY 2022 IPF PPS Final
Rule (86 FR 42640 through 42645), uses
Medicare FFS claims to determine the
percentage of inpatient discharges from
an IPF stay for which the patient
received a follow-up visit for treatment
of mental illness. The FAPH measure
represents an important component of
post-discharge care coordination,
specifically the transition of care to an
outpatient provider. However, this
measure does not quantify patient
outcomes.
The Medication Continuation
Following Inpatient Psychiatric
Discharge measure, which we adopted
in FY 2020 IPF PPS Final Rule (84 FR
38460 through 38465), assesses whether
patients admitted to IPFs with diagnoses
of Major Depressive Disorder (MDD),
schizophrenia, or bipolar disorder filled
at least one evidence-based medication
prior to discharge or during the postdischarge period. Medication
continuation is important for patients
discharged from the IPF setting with
these disorders because of significant
negative outcomes associated with nonadherence to medication regimes.
However, this measure does not
quantify patient outcomes with respect
to the use of acute care services postdischarge.
The IPF Unplanned Readmission
measure, which we adopted in the FY
2017 IPPS/LTCH PPS final rule (81 FR
57241 through 57246), assesses
outcomes associated with worsening
condition, potentially due to
insufficient discharge planning and
post-discharge care coordination, by
assessing post-discharge use of acute
care. The IPF Unplanned Readmission
measure estimates the incidence of
unplanned, all-cause readmissions to
IPFs or short-stay acute care hospitals
following discharge from an eligible IPF
index admission. A readmission is
defined as any admission that occurs
within 3 to 30 days after the discharge
date from an eligible index admission to
an IPF, except those considered
planned.31 However, this measure does
not quantify the proportion of patients
18 and older with an ED visit, without
31 https://p4qm.org/measures/2860.
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subsequent admission, within 30 days
of discharge from an IPF. Without
collecting this information in a measure,
we believe there is a gap in our
understanding regarding patients’
successful reintegration into their
communities following their IPF
discharge.
To further understand this gap, we
analyzed post-discharge outcomes using
claims data. In this analysis, we
determined that, for patients discharged
from IPFs, the risk-adjusted rate of ED
visits after an IPF discharge between
June 1, 2019 and July 31, 2021
(excluding the first two quarters of 2020
due to the COVID–19 public health
emergency) was 20.7 percent. The rate
of readmissions captured under the IPF
Unplanned Readmission measure for
this same period was 20.1 percent.32
This means that approximately 40
percent of patients discharged from an
IPF had either an ED visit or an
unplanned readmission within 30-days
of IPF discharge, but only about half of
those visits are being captured in the
publicly reported IPF Unplanned
Readmission measure. Visits to an ED
within 30 days of discharge from an IPF
(regardless of whether that visit results
in a hospital readmission, observation
stay, discharge, or patient leaving
without being seen) often indicate
deteriorating or heightened mental or
physical health needs. That is, these
visits often represent a patient seeking
care for symptoms that were present
during the patient’s stay in the IPF,
regardless of whether the symptom was
the reason for the admission, that have
become worse for the patient in the time
since discharge. Therefore, we believe
that IPFs and the public would benefit
from having these data made publicly
available to inform care decisions and
quality improvement efforts.
Specifically, members of the public
could use these data to inform care
decisions and IPFs could use these data
to compare their performance to that of
similar IPFs. For example, by having
these data publicly reported IPFs could
compare their performance with that of
other IPFs with similar patient
populations, a comparison which is not
possible without this measure. If IPFs
identified that other IPFs with similar
patient populations had better rates of
post-discharge ED visits (that is, other
IPFs had fewer patients seek care in an
ED within 30 days of discharge from the
IPF), the IPF could identify a need to
evaluate discharge planning and postdischarge care coordination to identify
32 As depicted in the April 2023 file available at
https://data.cms.gov/provider-data/archived-data/
hospitals.
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process changes which could improve
outcomes.
To address this gap, we developed
and are proposing the inclusion of the
new, claims-based 30-Day RiskStandardized All-Cause ED Visit
Following an IPF Discharge measure
(the IPF ED Visit measure) in the IPFQR
program beginning with the CY 2025
performance period/FY 2027 payment
determination. This proposed IPF ED
Visit measure aims to provide
information to patients, caregivers, other
members of the public, and IPFs about
the proportion of patients who seek care
in ED in the 30 days following discharge
from an IPF, but are not admitted as an
inpatient to an acute care hospital or
IPF. This proposed measure would
assess the proportion of patients 18 and
older with an ED visit, including
observation stays, for any cause, within
30 days of discharge from an IPF,
without subsequent admission.
We recognize that not all postdischarge ED visits are preventable, nor
are all post-discharge ED visits
associated with the initial IPF
admission. However, we developed an
all-cause ED visit rate, as opposed to a
more narrowly focused measure of ED
admissions for mental health or
substance use concerns, for three
primary reasons. First, such a measure
aligns most closely with the IPF
Unplanned Readmission measure as this
measure is also an all-cause measure.
Second, an all-cause measure
emphasizes the importance of wholeperson care for patients. Whole-person
care, during the inpatient stay and
through referral at discharge, includes
addressing the conditions that may
jeopardize a patient’s health, but are not
the reason for admission to the IPF, if
the IPF has reason to identify these
conditions during the course of
treatment. For example, if an IPF were
to identify through metabolic screening
that a patient has diabetes, it would be
appropriate for that IPF to recommend
appropriate follow-up for that patient,
such as with a primary care provider,
endocrinologist, or dietician. Such postdischarge coordination of care could
prevent the patient from seeking acute
care after discharge from the IPF for
complications of diabetes, such as
diabetic ketoacidosis. Third, this
measure includes ED visits for all
conditions because patients visiting the
ED may do so for physical symptoms
associated with a mental health
condition or substance use disorder. An
example is a patient with anxiety that
presents to the ED with chest pain and
shortness of breath. If the clinician
documents the primary diagnosis as
chest pain (R07.9) or shortness of breath
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(R06.02), the patient would not be
included in a mental health and
substance use-specific IPF ED Visit
measure, despite their history of anxiety
(F41.9), a potential contributor to their
presenting symptoms at the ED. We
recognize that it is possible that such a
visit may not be related to the patient’s
anxiety. However, while not all acute
care visits after discharge from an IPF
are preventable or necessarily related to
the quality of care provided by the IPF,
there is evidence that improvements in
the quality of care for patients in the IPF
setting can reduce rates of patients
seeking acute care after discharge from
an IPF, representing an improved
outcome for patients.33
Additionally, we considered whether
30 days was an appropriate timeframe
for this measure. That is, we sought to
identify whether a measure that
assessed post-discharge ED visits over a
period shorter or longer than 30 days
would be more appropriate. Because
IPFs are already familiar with
interpreting data for the 30-day period
in the IPF Unplanned Readmission
measure, we determined that it would
be appropriate to maintain the 30-day
period for the IPF ED Visit measure.
Additionally, by maintaining the same
timeframe as the IPF Unplanned
Readmission measure, we can provide
IPFs and patients with a more complete
picture of acute care among IPF patients
after discharge from the IPF.
Pursuant to the Meaningful Measures
2.0 Framework (a CMS initiative that
identifies priority domains for measures
within CMS Programs 34), this measure
addresses the ‘‘Seamless Care
Coordination’’ and the ‘‘PersonCentered Care’’ quality domains by
encouraging facilities to provide patientcentric discharge planning and support
post-discharge care transitions. The IPF
ED Visit measure also aligns with the
CMS National Quality Strategy Goals 35
of ‘‘Engagement’’ and ‘‘Outcomes and
Alignment.’’ It supports outcomes and
33 See for instance Chung, D.T., Ryan, C.J., HadziPavlovic, D., Singh, S.P., Stanton, C., & Large, M.M.
(2017). Suicide rates after discharge from
psychiatric facilities: A systematic review and metaanalysis. JAMA Psychiatry, 74(7), 694–702. https://
doi.org/10.1001/jamapsychiatry.2017.1044 or
Durbin, J., Lin, E., Layne, C., et al. (2007). Is
readmission a valid indicator of the quality of
inpatient psychiatric care? Journal of Behavioral
Health Services Research, 34, 137–150. doi:10.1007/
s11414- 007–9055–5.
34 https://www.cms.gov/medicare/quality/
meaningful-measures-initiative/meaningfulmeasures-20.
35 Schreiber, M, Richards, A, et al. (2022). The
CMS National Quality Strategy: A Person-Centered
Approach to Improving Quality. Available at:
https://www.cms.gov/blog/cms-national-qualitystrategy-person-centered-approach-improvingquality.
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alignment because this measure
provides a quantified estimate of one
post-discharge outcome that patients
may experience, that is a post-discharge
acute care visit that does not result in
an admission. It also supports the
Behavioral Health Strategy 36 domains
of ‘‘Quality of Care’’ and ‘‘Equity and
Engagement’’ because engaging patients
to improve post-discharge outcomes is
an element of providing quality care.
Furthermore, similar to the Meaningful
Measures domain of ‘‘Person-Centered
Care,’’ this measure supports the
Universal Foundation domain of
‘‘Person-Centered Care.’’
lotter on DSK11XQN23PROD with PROPOSALS2
b. Overview of Measure
The IPF ED Visit measure was
developed with input from clinicians,
patients, and policy experts; the
measure was subject to the prerulemaking process required by section
1890A of the Act, as discussed further
in section V.B.1 of this rule. Consistent
with the CMS key elements of the CMS
Measure Development Lifecycle,37 we
began with measure conceptualization
during which we performed a targeted
literature review and solicited input
from a behavioral health technical
expert panel (TEP). This allowed us to
ensure that this topic addresses a gap
that is important to interested parties.
After confirming this, we developed the
measure specifications for the IPF ED
Visit measure. With these specifications,
we issued a 30-day call for public
comment in the Federal Register and
performed empirical testing using
claims data, including modeling for
risk-adjustment. After refining the
measure specifications based on testing
and public comment, we performed an
equity analysis in which we tested the
risk-adjustment methodology to ensure
that the measure does not reflect access
issues related to patient demographics
instead of quality of care. By following
steps in accordance with the Measure
Development Lifecycle, we sought to
ensure that this is a vetted, valid,
reliable, and ready-to-implement
claims-based measure which would
assess the proportion of patients 18 and
older with an ED visit, including
observation stays, for any cause, within
30 days of discharge from an IPF,
without subsequent admission. By using
the same definitions of index admission
and patient populations as those used in
the IPF Unplanned Readmission
measure, we have designed the IPF ED
36 CMS. (2022). CMS Behavioral Health Strategy.
Available at https://www.cms.gov/cms-behavioralhealth-strategy.
37 https://mmshub.cms.gov/blueprint-measurelifecycle-overview.
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Visit measure to complement the IPF
Unplanned Readmission measure to the
extent possible. We have also sought to
minimize administrative burden by
developing this as a claims-based
measure so that it adds no information
collection burden to clinicians and staff
working in the IPF setting.
(1) Measure Calculation
The focus population for this measure
is adult Medicare FFS patients with a
discharge from an IPF. The measure is
based on all eligible index admissions
from the focus population. An eligible
index admission is defined as any IPF
admission for which the patient meets
the following criteria: (1) age 18 or older
at admission; (2) discharged alive from
an IPF; (3) enrolled in Medicare FFS
Parts A and B during the 12 months
before the admission date, the month of
admission, and at least one month after
the month of discharge from the index
admission (that is, the original stay in
an IPF); and (4) discharged with a
principal diagnosis that indicates a
psychiatric disorder. Excluded from the
measure are patients discharged against
medical advice (AMA) from the IPF
index admission (because the IPF may
not have had the opportunity to conduct
full discharge planning for these
patients); patients with unreliable data
regarding death demographics or a
combination thereof in their claims
record (because these data are
unreliable, they may lead to
inaccuracies in the measure
calculation); patients who expired
during the IPF stay (because postdischarge care is not applicable to these
patients); patients with a discharge
resulting in a transfer to another care
facility (because the receiving care
facility would be responsible for
discharge planning for these patients);
and patients discharged but readmitted
within 3 days of discharge, also known
as an interrupted stay (because
interrupted stays are often reflective of
patient needs outside of the IPF, such as
treatment for another condition).
To calculate the measure, we would
use the following data sources which
are all available from Medicare
administrative records and data
submitted by providers through the
claims process: (1) Medicare beneficiary
and coverage files, which provide
information on patient demographic,
enrollment, and vital status information
to identify the measure population and
certain risk factors; (2) Medicare FFS
Part A records, which contain final
action claims submitted by acute care
and critical access hospitals, IPFs, home
health agencies, and skilled nursing
facilities to identify the measure
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population, readmissions, and certain
risk factors; and (3) Medicare FFS Part
B records, which contain final action
claims submitted by physicians,
physician assistants, clinical social
workers, nurse practitioners, and other
outpatient providers to identify certain
risk factors. To ensure that diagnoses
result from encounters with providers
trained to establish diagnoses, this
measure would not use claims for
services such as laboratory tests,
medical supplies, or other ambulatory
services. Index admissions and ED visits
would be identified in the Medicare FFS
Part A records. Comorbid conditions for
risk-adjustment would be identified in
the Medicare Part A and Part B records
in the 12 months prior to admission,
including the index admission.
Demographic and FFS enrollment data
would be identified in the Medicare
beneficiary and coverage files.
To calculate the IPF ED Visit measure,
CMS would: (1) identify all IPF
admissions in the one-year performance
period; (2) apply inclusion and
exclusion criteria to identify index
admissions; (3) identify ED visits and
observation stays within 30 days of
discharge from each index admission;
(4) identify risk factors in the 12 months
prior to index admission and during the
index admission; and (5) run
hierarchical logistic regression to
compute the risk-standardized ED visit
rate for each IPF.38 This hierarchical
logistic regression would allow us to
apply the risk-adjustment factors
developed in measure testing to ensure
that measure results are comparable
across IPFs regardless of the clinical
complexity of each IPF’s patient
population.
(2) Pre-Rulemaking Measure Review and
Measure Endorsement
As required under section 1890A of
the Act, the CBE established the
Partnership for Quality Measurement
(PQM) to convene clinicians, patients,
measure experts, and health information
technology specialists to participate in
the pre-rulemaking process and the
measure endorsement process. The prerulemaking process, also called the PreRulemaking Measure Review (PRMR),
includes a review of measures
published on the publicly available list
of Measures Under Consideration (MUC
List) by one of several committees
convened by the PQM for the purpose
38 For an example of the hierarchal logistic riskadjustment algorithm, we refer readers to the
algorithm for the IPF Unplanned Readmission
measure at https://www.cms.gov/medicare/qualityinitiatives-patient-assessment-instruments/
hospitalqualityinits/downloads/inpatientpsychiatric-facility-readmission-measure.zip.
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lotter on DSK11XQN23PROD with PROPOSALS2
of providing multi-stakeholder input to
the Secretary on the selection of quality
and efficiency measures under
consideration for use in certain
Medicare quality programs, including
the IPFQR Program. The PRMR process
includes opportunities for public
comment through a 21-day public
comment period, as well as public
listening sessions. The PQM posts the
compiled comments and listening
session inputs received during the
public comment period and the
listening sessions within five days of the
close of the public comment period.39
More details regarding the PRMR
process may be found in the CBE’s
Guidebook of Policies and Procedures
for Pre-Rulemaking Measure Review
and Measure Set Review, including
details of the measure review process in
Chapter 3.40
The CBE-established PQM also
conducts the measure endorsement and
maintenance (E&M) process to ensure
measures submitted for endorsement are
evidence-based, reliable, valid,
verifiable, relevant to enhanced health
outcomes, actionable at the caregiverlevel, feasible to collect and report, and
responsive to variations in patient
characteristics, such as health status,
language capabilities, race or ethnicity,
and income level, and are consistent
across types of health care providers,
including hospitals and physicians (see
section 1890(b)(2) of the Act). The PQM
convenes several E&M project groups
twice yearly, formally called E&M
Committees, each comprised of an E&M
Advisory Group and an E&M
Recommendations Group, to vote on
whether a measure meets certain quality
measure criteria. More details regarding
the E&M process may be found in the
E&M Guidebook, including details of
the measure endorsement process in the
section titled, ‘‘Endorsement and
Review Process.’’ 41
As part of the PRMR process, the IPF
ED Visit measure was reviewed during
the PRMR Hospital Recommendation
Group meeting on January 18, 2024. For
the voting procedures of the PRMR and
E&M process, the PQM utilized the
Novel Hybrid Delphi and Nominal
Group (NHDNG) multi-step process,
which is an iterative consensus-building
39 These materials are available at the PRMR
section of the PQM website: https://p4qm.org/
PRMR.
40 https://p4qm.org/sites/default/files/2023-09/
Guidebook-of-Policies-and-Procedures-for-PreRulemaking-Measure-Review-%28PRMR%29-andMeasure-Set-Review-%28MSR%29-Final_0.pdf.
41 The Partnership for Quality Measurement.
(October 2023). Endorsement and Maintenance
(E&M) Guidebook. Available at: https://p4qm.org/
sites/default/files/2023-12/Del-3-6-Endorsementand-Maintenance-Guidebook-Final__0.pdf.
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approach aimed at a minimum of 75
percent agreement among voting
members, rather than a simple majority
vote, and supports maximizing the time
spent to build consensus by focusing
discussion on measures where there is
disagreement. For example, the PRMR
Hospital Recommendation Group can
reach consensus and have the following
voting results: (A) Recommend, (B)
Recommend with conditions (with 75
percent of the votes cast as recommend
with conditions or 75 percent between
recommend and recommend with
conditions), and (C) Do not recommend.
If no voting category reaches 75 percent
or greater (including the combined [A]
Recommend and [B] Recommend with
conditions) the PRMR Hospital
Recommendation Group did not come
to consensus and the voting result is
‘‘Consensus not reached.’’ Consensus
not reached signals continued
disagreement amongst the committee
despite being presented with
perspectives from public comment,
committee member feedback and
discussion, and highlights the multifaceted assessments of quality measures.
More details regarding the PRMR voting
procedures may be found in Chapter 4
of the PQM Guidebook of Policies and
Procedures for Pre-Rulemaking Measure
Review and Measure Set Review.42
More details regarding the E&M voting
procedures may be found in the PQM
Endorsement and Maintenance (E&M)
Guidebook.43 The PRMR Hospital
Recommendation Group 44 reached
consensus and recommended including
this measure in the IPFQR Program with
conditions.
Seven members of the group
recommended adopting the measure
into the IPFQR program without
conditions; eleven members
recommended adoption with
conditions; and one committee member
voted not to recommend the measure for
adoption. Taken together, 94.73 percent
of the votes were between recommend
& recommend with conditions.
The conditions specified by the PRMR
Hospital Recommendation Group were:
(1) that the measure be considered for
endorsement by a consensus-based
entity; and (2) further consideration of
how the measure addresses 72-hour
transfers to the ED. We have taken those
considerations into account and are
proposing this measure for adoption
because we believe we have adequately
addressed the concerns raised by those
considerations.
44 We note that the PRMR Hospital
Recommendation Group was previously the
Measure Applications Partnership (MAP) Hospital
Workgroup under the pre-rulemaking process
followed by the previous CBE.
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23209
To address the first condition, we
have submitted the measure to the CBE
for consideration. For more information
on submission to and consideration by
the CBE we refer readers to section
V.B.2.b.(3) of this rule.
The second voting condition
requested that we further consider how
the measure addresses 72-hour transfers
to the ED because of concerns that IPFs
may appear to have worse performance
if ‘‘interrupted stays’’ are not excluded
from the measure. An ‘‘interrupted stay’’
occurs when a patient is discharged
from an IPF and readmitted to the same
IPF within 72 hours. This frequently
occurs when a patient needs medical
treatment that is beyond the scope of the
IPF, such as care in an ED for an
emergent health issue. We believe that
this concern is sufficiently addressed in
the ED Visit measure’s specifications
because these ‘‘interrupted stays’’ are
excluded from the measure, as
described in section V.B.2.b.(1) of this
rule. This exclusion is defined as an
index admission with a readmission on
Days 0, 1, or 2 post-discharge. In other
words, patients transferred to the ED
and subsequently readmitted to the IPF
within 72 hours are excluded from the
measure. Therefore ‘‘interrupted stays’’
are excluded from the measure as per
the group’s recommendation.
(3) CBE Endorsement
Section 1886(s)(4)(D)(i) of the Act
generally requires that measures
specified by the Secretary shall be
endorsed by the entity with a contract
under section 1890(a) of the Act (that is,
the CBE). After a measure has been
submitted to the CBE, the committee
responsible for reviewing the measure
evaluates the measure on five domains:
(1) Importance; (2) Feasibility; (3)
Scientific Acceptability (that is,
reliability and validity); (4) Equity; and
(5) Use and Usability. Committee
members evaluate whether the measure
the domain is ‘‘Met’’, ‘‘Not Met but
Addressable’’ or ‘‘Not Met’’ for each
domain using a set of criteria provided
by the CBE.45 When a measure is
submitted it is assigned to one of the
CBE’s projects based on where in the
patient’s healthcare experience the
measure has the most relevance. The
five projects are (1) Primary Prevention;
(2) Initial Recognition and Management;
(3) Management of Acute Events,
Chronic Disease, Surgery, Behavioral
Health; (4) Advanced Illness and PostAcute Care; and (5) Cost and Efficiency.
The measure developer submitted the
measure for CBE endorsement
consideration in the Fall 2023 review
45 https://p4qm.org/EM.
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cycle. The measure was assigned to the
Cost and Efficiency Project. The CBE
Cost and Efficiency Endorsement
committee met on January 31, 2024 and
did not reach consensus regarding the
IPF ED Visit measure, with 60.6 percent
voting in favor of endorsement or
endorsement with conditions and the
remaining members voting to not
endorse, which is below the 75 percent
threshold necessary for the endorsement
of the measure, as described in V.B.2.b.
During the Cost and Efficiency
Endorsement committee’s meeting,
members of the committee discussed
whether an all-cause measure was
appropriate and whether IPFs are able to
implement interventions to reduce postdischarge acute care.46
As discussed in section V.B.2.a of this
proposed rule, an all-cause measure
would complement the IPF Unplanned
Readmission measure, would emphasize
whole-person care, and would capture
visits to the ED for patients with
physical symptoms associated with
mental health conditions. Additionally,
evidence shows that there are
interventions that reduce post-discharge
acute care. These include adopted care
transition models, proactively
connecting patients with post-discharge
providers, identifying and addressing
patients’ barriers to post-discharge care,
and focusing on providing patient-
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46 For information about the Cost and Efficiency
endorsement review we refer readers to the meeting
summary, available at https://p4qm.org/sites/
default/files/Cost%20and%20Efficiency/material/
EM-Cost-and-Efficiency-Fall2023-EndorsementMeeting-Summary.pdf.
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centered care and improving patient
experience of care.
Although section 1886(s)(4)(D)(i) of
the Act generally requires that measures
specified by the Secretary shall be
endorsed by the entity with a contract
under section 1890(a) of the Act, section
1886(s)(4)(D)(ii) of the Act states that, in
the case of a specified area or medical
topic determined appropriate by the
Secretary for which a feasible and
practical measure has not been endorsed
by the entity with a contract under
section 1890(a) of the Act, the Secretary
may specify a measure that is not so
endorsed as long as due consideration is
given to a measure that has been
endorsed or adopted by a consensus
organization identified by the Secretary.
We have determined that this is an
appropriate topic for the adoption of a
measure absent CBE endorsement
because where possible we focus on
measures that assess patient outcomes.
Unplanned use of acute care after
discharge from an IPF is often
associated with worsening condition,
potentially due to insufficient discharge
planning and post-discharge care
coordination. While the IPFQR Program
currently has a measure that assesses
unplanned readmissions after discharge
from an IPF, there is a gap in the
measure set with respect to unplanned
ED visits without a subsequent
admission to an acute care hospital or
IPF. The IPF ED Visit measure fills that
gap. We also reviewed CBE-endorsed
measures and were unable to identify
any other CBE-endorsed measures that
assess outcomes that solely result in a
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patient’s ED visit after the patient’s
discharge from an IPF. The only
endorsed measure that we identified
that addresses an IPF patient seeking
acute care after discharge is the IPF
Unplanned Readmission measure. As
we discussed previously, the IPF
Unplanned Readmission measure does
not assess ED visits that do not result in
an admission. Therefore, we believe that
the IPF ED Visit measure is an
important complement to the IPF
Unplanned Readmission measure. We
did not find any other measures that
assess post-discharge ED visits without
a subsequent admission, and therefore
the exception in section 1886(s)(4)(D)(ii)
of the Act applies.
c. Data Collection, Submission, and
Reporting
Because all files used to calculate the
IPF ED Visit measure are available on
Medicare claims, this measure requires
no additional data collection or
submission by IPFs. We are proposing a
reporting period beginning with data
from CY 2025 performance period/FY
2027 payment determination year.
C. Summary of IPFQR Program
Measures for the FY IPFQR Program
We are proposing one new measure
for the FY 2027 IPFQR Program. If we
finalize adoption of this measure, the
FY 2027 IPFQR Program measure set
would include 16 mandatory and one
voluntary measure. Table 22 sets forth
the measures in the FY 2027 IPFQR
Program.
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TABLE 22: IPFQR PROGRAM MEASURE SET FOR THE FY 2027 IPFQR PROGRAM
CBE #
Measure ID
Measure
0640
0641
NIA
NIA*
HBIPS-2
HBIPS-3
FAPH
SUB-2 and SUB-2a
NIA*
SUB-3 and SUB-3a
NIA*
TOB-3 and TOB-3a
1659
NIA*
IMM-2
NIA
NIA
2860
NIA
NIA
NIA
NIA
3205*
NIA
NIA
NIA
NIA
Med Cont.
NIA
Facility Commitment
Screening for SDOH
Screen Positive
Hours of Physical Restraint Use
Hours of Seclusion Use
Follow-Up After Psychiatric Hospitalization
Alcohol Use Brief Intervention Provided or Offered and SUB-2a Alcohol
Use Brief Intervention
Alcohol and Other Drug Use Disorder Treatment Provided or Offered at
Discharge and SUB-3a Alcohol and Other Drug Use Disorder Treatment at
Discharge
Tobacco Use Treatment Provided or Offered at Discharge and TOB-3a
Tobacco Use Treatment at Discharge
Influenza Immunization
Transition Record with Specified Elements Received by Discharged
Patients (Discharges from an Inpatient Facility to Home/Self Care or Any
Other Site of Care)
Screening for Metabolic Disorders
Thirty-Day All-Cause Unplanned Readmission Following Psychiatric
Hospitalization in an Inpatient Psychiatric Facility
30-Day Risk-Standardized All-Cause Emergency Department Visit
Following an Inpatient Psychiatric Facility Discharge measure 1
Medication Continuation Following Inpatient Psychiatric Discharge
Modified COVID-19 Healthcare Personnel (HCP) Vaccination Measure
Facility Commitment to Health Equity
Screening for Social Drivers of Health
Screen Positive Rate for Social Drivers of Health
BILLING CODE 4120–01–C
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D. Proposal To Modify Data Submission
Requirements for the FY 2027 Payment
Determination and Subsequent Years
Section 1886(s)(4)(C) of the Act
requires the submission of quality data
in a form and manner, and at a time,
specified by the Secretary. In the
Medicare Program; Hospital Inpatient
Prospective Payment Systems for Acute
Care Hospitals and the Long-Term Care
Hospital Prospective Payment System
and fiscal year 2013 Rates; Hospitals’
Resident Caps for Graduate Medical
Education Payment Purposes; Quality
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Reporting Requirements for Specific
Providers and for Ambulatory Surgical
Centers (FY 2013 IPPS/LTCH PPS) final
rule (77 FR 53655), we specified that
data must be submitted between July 1
and August 15 of the calendar year
preceding a given payment
determination year (for example, data
were required to be submitted between
July 1, 2015 and August 15, 2015 for the
FY 2016 payment determination). In the
Medicare Program; Hospital Inpatient
Prospective Payment Systems for Acute
Care Hospitals and the Long-Term Care
Hospital Prospective Payment System
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and fiscal year 2014 Rates; Quality
Reporting Requirements for Specific
Providers; Hospital Conditions of
Participation; Payment Policies Related
to Patient Status (FY 2014 IPPS/LTCH
PPS) final rule (78 FR 50899), we
clarified that this policy applied to all
future years of data submission for the
IPFQR Program unless we changed the
policy through future rulemaking.
In the FY 2018 IPF PPS final rule (82
FR 38472 through 38473) we updated
this policy by stating that the data
submission period will be a 45-day
period beginning at least 30 days
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EP03AP24.034
Psychiatric Inpatient Experience Survey 2
NIA
PIX
* Measure is no longer endorsed by the CBE but was endorsed at the time of adoption. We note that although
section 1886(s)(4)(D)(i) of the Act generally requires measures specified by the Secretary be endorsed by the
entity with a contract under section be endorsed by the entity with a contract under section 1890(a) of the Act,
section 1886(s)(4)(D)(ii) states that in the case of a specified area or medical topic determined appropriate by
the Secretary for which a feasible and practical measure has not been endorsed by the entity with a contract
under section 1890(a) of the Act, the Secretary may specify a measure that is not so endorsed as long as due
consideration is given to measures that have been endorsed or adopted by a consensus organization identified by
the Secretary. We attempted to find available measures for each of these clinical topics that have been endorsed
or adopted by a consensus organization and found no other feasible and practical measures on the topics for the
IPF setting.
1 Measure proposed for adoption in Section V.B.2. of this proposed rule.
2 We note that the PIX measure will become mandatory for the FY 2028 payment determination, as finalized in
the FY 2024 IPF PPS Final Rule (88 FR 51128).
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following the end of the data collection
period and that we will provide
notification of the exact dates through
subregulatory means.
In the FY 2022 IPF PPS Final Rule (86
FR 42658 through 42661), we finalized
voluntary patient-level data reporting
for the FY 2023 payment determination
and mandatory patient-level data
reporting for chart-abstracted measures
within the IPFQR Program beginning
with FY 2024 payment determination
and subsequent years. The measures
currently in the IPFQR Program affected
by this requirement are set forth in
Table 23.
TABLE 23: IPFQR PROGRAM MEASURES REQURING PATIENT-LEVEL DATA
SUBMISSION
NIA*
SUB-3 and SUB-3a
NIA*
TOB-3 and TOB-3a
1659
NIA*
IMM-2
NIA
NIA
NIA
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As we have gained experience with
patient-level data submission for the
IPFQR program, during the voluntary
data submission period for FY 2023
(which occurred in CY 2022) and the
first mandatory data submission period
for FY 2024 (which occurred in CY
2023), we have observed that annual
data submission periods require IPFs to
store large volumes of patient data to
prepare for transmission to CMS.
Furthermore, the volume of data
associated with all IPFs reporting a full
year of patient-level data during one
data submission period creates the risk
that systems will be unable to handle
the volume of data.
We have reviewed how other quality
reporting programs that require patientlevel data submission address these
concerns and determined that the
Hospital Inpatient Quality Reporting
(IQR) Program (78 FR 50811) and the
Hospital Outpatient Quality Reporting
(OQR) Program (72 FR 66872) both
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Measure
Hours of Physical Restraint Use (numerator only)
Hours of Seclusion Use (numerator only)
Alcohol Use Brief Intervention Provided or Offered and SUB-2a Alcohol
Use Brief Intervention
Alcohol and Other Drug Use Disorder Treatment Provided or Offered at
Discharge and SUB-3a Alcohol and Other Drug Use Disorder Treatment at
Discharge
Tobacco Use Treatment Provided or Offered at Discharge and TOB-3a
Tobacco Use Treatment at Discharge
Influenza Immunization
Transition Record with Specified Elements Received by Discharged
Patients (Discharges from an Inpatient Facility to Home/Self Care or Any
Other Site of Care)
Screening for Metabolic Disorders
require quarterly submission of patientlevel data. As we considered requiring
quarterly reporting for the IPFQR
Program, we also determined that
increasing the frequency of data
submission would allow additional
analysis of measure trends over time.
We believe that having additional data
points (from additional quarters of data)
could allow for more nuanced analyses
of the IPFQR Program’s measures.
Specifically, we would be able to better
identify quarterly highs or lows that
may be less apparent when data are
combined over a full year. We recognize
that, if we update data reporting
requirements to require reporting four
times per year instead of once per year,
then IPFs would need to meet four
incremental deadlines instead of one
deadline, and that this increases the risk
that an individual IPF may fail to
submit data specified for the measures
and not receive its full market basket
update. However, we believe that this
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risk is low because IPFs already have
experience submitting some data
required by the IPFQR Program on a
more frequent basis. Specifically, the
COVID–19 Healthcare Personnel (HCP)
Vaccination Measure is currently
reported into the CDC’s National
Healthcare Safety Network (NHSN) for
one week per month resulting in a
quarterly measure result (as originally
adopted in the FY 2022 IPF PPS final
rule (86 FR 42636) and restated in the
FY 2024 IPF PPS final rule (88 FR 51131
through 51132). In addition, if this
proposal for quarterly data submission
is finalized, data submission for each
calendar quarter would be required
during a period of at least 45 days
beginning three months after the end of
the calendar quarter. Table 24
summarizes these proposed deadlines
for the CY 2025 and CY 2026
performance periods:
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CBE#
Measure ID
Required Measures
0640
HBIPS-2
0641
HBIPS-3
SUB-2 and SUB-2a
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TABLE 24: QUARTERLY SUBMISSION DEADLINES FOR CY 2025 AND CY 2026
PERFORMANCE PERIODS
January 1, 2025-March 31, 2025 (Ql 2025)
November 15, 2025
April 1, 2025 - June 30, 2025 (Q2 2025)
November 15, 2025
July 1, 2025 - September 30, 2025 (Q3 2025)
February 15, 2026
October 1, 2025 - December 31, 2025 (Q4 2025)
May 15, 2026
January 1, 2026-March 31, 2026 (Ql 2026)
August 15, 2026
April 1, 2026 - June 30, 2026 (Q2 2026)
November 15, 2026
July 1, 2026 - September 30, 2026 (Q3 2026)
February 15, 2027
October 1, 2026 - December 31, 2026 (Q4 2026)
May 15, 2027
Furthermore, we are proposing that
all data which continue to be reported
on an annual basis (that is, non-measure
data, aggregate measures, and
attestations) would be required to be
reported concurrently with the data
from the fourth quarter of the applicable
year. For example, data reflecting the
entirety of CY 2025 (that is, nonmeasure data, aggregate measures, and
attestations) would be required by the
Q4 2025 submission deadline (that is,
May 15, 2026).
We welcome comments on this
proposal.
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VI. Collection of Information
Requirements
Under the Paperwork Reduction Act
of 1995 (PRA) (44 U.S.C. 3501 et seq.),
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. For the
purposes of the PRA and this section of
the preamble, collection of information
is defined under 5 CFR 1320.3(c) of the
PRA’s implementing regulations.
To fairly evaluate whether an
information collection should be
approved by OMB, section 3506(c)(2)(A)
of the 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.
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• 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.
We are soliciting public comment (see
section VI.C of this proposed rule) on
each of these issues for the following
sections of this document that contain
information collection requirements.
Comments, if received, will be
responded to within the subsequent
final rule.
The following changes will be
submitted to OMB for review under
control number 0938–1171 (CMS–
10432). We are not proposing any
changes that would change any of the
data collection instruments that are
currently approved under that control
number.
In section VI.2 of this proposed rule,
we restate our currently approved
burden estimates. In section VI.3 of this
proposed rule, we estimate the changes
in burden associated with update more
recent wage rates. Then in section VI.4
of this proposed rule, we estimate the
changes in burden associated with the
policies proposed in this proposed rule.
A. Wage Estimates
In the FY 2024 IPF PPS final rule, we
utilized the median hourly wage rate for
Medical Records Specialists, in
accordance with the Bureau of Labor
Statistics (BLS), to calculate our burden
estimates for the IPFQR Program (88 FR
51145). While the most recent data from
the BLS reflects a mean hourly wage of
$24.56 per hour for all medical records
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specialists, $26.06 is the mean hourly
wage for ‘‘general medical and surgical
hospitals,’’ which is an industry within
medical records specialists.47 We
believe the industry of ‘‘general medical
and surgical hospitals’’ is more specific
to the IPF setting for use in our
calculations than other industries that
fall under medical records specialists,
such as ‘‘office of physicians’’ or
‘‘nursing care facilities (skilled nursing
facilities).’’ We calculated the cost of
indirect costs, including fringe benefits,
at 100 percent of the median hourly
wage, consistent with previous years.
This is necessarily a rough adjustment,
both because fringe benefits and other
indirect costs vary significantly by
employer and methods of estimating
these costs vary widely in the literature.
Nonetheless, we believe that doubling
the hourly wage rate ($26.06 × 2 =
$52.12) to estimate total cost is a
reasonably accurate estimation method.
Accordingly, unless otherwise specified,
we will calculate cost burden to IPFs
using a wage plus benefits estimate of
$52.12 per hour throughout the
discussion in this section of this rule for
the IPFQR Program.
Some of the activities previously
finalized for the IPFQR Program require
beneficiaries to undertake tasks such as
responding to survey questions on their
own time. In the FY 2024 IPF PPS final
rule, we estimated the hourly wage rate
for these activities to be $20.71/hr (88
FR 51145). We are updating that
estimate to a post-tax wage of $24.04/hr.
47 Medical
E:\FR\FM\03APP2.SGM
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03APP2
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The Valuing Time in U.S. Department of
Health and Human Services Regulatory
Impact Analyses: Conceptual
Framework and Best Practices identifies
the approach for valuing time when
individuals undertake activities on their
own time.48 To derive the costs for
beneficiaries, we used a measurement of
the usual weekly earnings of wage and
salary workers of $1,118, divided by 40
hours to calculate an hourly pre-tax
wage rate of $27.95/hr.49 This rate is
adjusted downwards by an estimate of
the effective tax rate for median income
48 https://aspe.hhs.gov/reports/valuing-time-us-
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department-health-human-services-regulatoryimpact-analyses-conceptual-framework.
49 https://www.bls.gov/news.release/pdf/
wkyeng.pdf. Accessed January 1, 2024.
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households of about 14 percent
calculated by comparing pre- and posttax income,50 resulting in the post-tax
hourly wage rate of $24.04/hr. Unlike
our State and private sector wage
adjustments, we are not adjusting
beneficiary wages for fringe benefits and
other indirect costs since the
individuals’ activities, if any, would
occur outside the scope of their
employment.
B. Previously Finalized IPFQR Estimates
We are finalizing provisions that
impact policies beginning with the FY
50 https://www.census.gov/library/stories/2023/
09/median-household-income.html. Accessed
January 2, 2024.
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2027 payment determination. For the
purposes of calculating burden, we
attribute the costs to the year in which
the costs begin. Under our previously
finalized policies, data submission for
the measures that affect the FY 2027
payment determination occurs during
CY 2026 and generally reflects care
provided during CY 2025. If we finalize
our proposal to switch to quarterly
reporting in section XX.X of this
proposed rule, data submission for the
FY 2027 payment determination would
begin during CY 2025. Our currently
approved burden for CY 2025 is set
forth in Table 25.
BILLING CODE 4120–01–P
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TABLE 25: PREVIOUSLY IPFQR PROGRAM FOR CY 2025
Measure/Response
Description
Number
Respondents
Hours of Physical
Restraint Use
Hours of Seclusion
Use
Follow-Up After
Psychiatric
Hospitalization
Alcohol lJse Brief
Intervention Provided
or Offered and SUB2a Alcohol Use Brief
Intervention
Alcohol and Other
Drug Use Disorder
Treatment Provided
or Offered at
Discharge and SUH3a Alcohol and Other
Drug Use Disorder
Treatment at
Dischar!!e
Tobacco Use
Treatment Provided
or Offered at
Discharge and TOB3a Tobacco Use
Trealmenl al
Dischar!!e
Influenza
Immunization
Transition Record
with Specified
Elements Received by
Discharged Patients
( Discharges from an
Inpatient Facility to
Home/Self Care or
Any Other Site of
Care)
Screening for
Metabolic Disorders
Thirty-Day All-Cause
Unplanned
Readmission
Following Psychiatric
Hospitalization in an
Inpatient Psychiatric
Facilitv
30-Day RiskStandardized AllCause Emergency
Department Visit
Following an
Inpatient Psychiatric
Facility Discharge
Number of
Responses/
Respondent
Total
Annual
Responses
Time per
Response
(hrs)
Time per
Facility
(hrs)
Total
Annual
Time (hrs)
Applicable
Wage Rate
($,br)
Cost per
Facility
($)
Total Annual
Cost($)
1,596
1,261
2,012,556
0.25
315
503,139
44.86
14,142
22,570,816
1,596
1,261
2,012,556
0.25
315
503,139
44.86
14,142
22,570,816
1,596
0
0
0
0
0
44.86
0
0
1,596
609
971,964
0.25
152
242,991
44.86
6,830
10,900,576
1,596
609
971,964
0.25
152
242,991
44.86
6,830
10,900,576
1,596
609
971,964
0.25
152
242,991
44.86
6,830
10,900,576
1,596
609
971,964
0.25
152
242,991
44.86
6,830
10,900,576
1,596
609
971,964
0.25
152
242,991
44.86
6,830
10,900,576
1,596
609
971,964
0.25
152
242,991
44.86
6,830
10,900,576
1,596
0
0
0
0
0
44.86
0
0
1,596
0
0
0
0
0
44.86
0
0
1,596
0
0
0
0
0
44.86
0
0
1,596
0
0
0
0
0
44.86
0
0
1,596
I
1,596
0.167
0
267
44.86
7
11,957
Medication
Continuation
Following Inpatient
Psychiatric Discharge
Modified COVID-19
Healthcare Personnel
(HCP) Vaccination
Measure
Facility Commitment
to Health Eciuitv
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measure 1
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Measure/Response
Description
Screening for Social
Drivers of Health
Number
Respondents
Number of
Responses/
Respondent
798
Total
Annual
Responses
798
BILLING CODE 4120–01–C
C. Updates Due to More Recent
Information
In section VI.A of this proposed rule,
we described our updated wage rates
Time per
Response
(hrs)
Time per
Facility
(hrs)
0.167
0
Total
Annual
Time (hrs)
133
which increase from $44.86/hr to
$52.12/hr (an increase of $7.26/hr) for
activities performed by Medical Records
Specialists and from $20.71/hr to
$24.04/hr (an increase of $3.33/hr) for
Applicable
Wage Rate
($/hr)
44.86
Cost per
Facility
($)
7
Total Annual
Cost($)
5,978
activities performed by individuals. The
effects of these updates are set forth in
Table 26.
Total
Annual
Responses
Subtotal for Medical
Records Specialists
9,866,472
Subtotal for
Individuals
2,251,956
Totals
12,118,428
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D. Updates Due to Proposals in This
Proposed Rule
In section V.B.2 of this proposed rule,
we are proposing to adopt the 30-Day
Risk-Standardized All-Cause ED Visit
Following an IPF Discharge measure
beginning with the CY 2025
performance period/FY 2027 payment
determination. As described in section
V.B.2.c. of this preamble, we will
calculate the 30-Day Risk-Standardized
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Time Per
Respons
e (hrs)
Varies
Varies
Varies
Time per
Facility
(hrs)
Total
Annual
Time (hrs)
Change in
Applicable
Wage Rate
($/hr)
Change in
Cost per
Facility
($)
Change in
Total Annual
Cost($)
1,547
2,467,949
7.26
11,228
17,919,245
78
95,382
3.33
259
414,083
1,624
2,563,331
Varies
11,487
18,333,328
All-Cause ED Visit Following an
Inpatient Psychiatric Facility Discharge
measure using Medicare claims that
IPFs and other providers submit for
payment. Since this is a claims-based
measure there is no additional burden
outside of submitting a claim. The claim
submission is approved by OMB under
control number 0938–0050 (CMS–2552–
10). This rule does not warrant any
changes under that control number.
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In Section V.D. of this proposed rule,
we are proposing to require IPFs to
submit data on chart-abstracted
measures quarterly. In CY 2025, this
would equate to one additional data
submission period (that is, the reporting
period which would close on November
15, 2025 as set forth in Table 27). In CY
2026, there would be an additional two
data submission periods (for a total of
four annually). We estimate that the
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Measure/Response
Description
EP03AP24.039
TABLE 26: EFFECTS OF WAGE RATE UPDATES
Federal Register / Vol. 89, No. 65 / Wednesday, April 3, 2024 / Proposed Rules
increase in burden associated with the
increase in data submission periods is
approximately equal to the burden of
reporting one attestation measure
because both of these activities require
logging into and interacting with user
interfaces within the CMS data
reporting system (that is, the Hospital
Quality System—HQS). The effects of
this increase on the IPFQR Program for
23217
CY 2025 are set forth in Table 27. The
effects of this increase on the IPFQR
Program for CY 2026 are set forth in
Table 28.
TABLE 27: CY 2025 EFFECTS OF INCREASING BY ONE DATA SUBMISSION
PERIOD
Measure/Response
Description
Addition of one data
submission period
(for a total of 2)
Number
Respondents
Number of
Responses/
Respondent
Total
Aunual
Responses
1,596
1
1,596
Time per
Response
(hrs)
Time per
Facility
(hrs)
Total
Aunual
Time (hrs)
Applicable
Wage Rate
($/hr)
Cost per
Facility
($)
Total Annual
Cost($)
0.167
0.167
267
52.12
9
13,892
TABLE 28: CY 2025 EFFECTS OF INCREASING BY ONE DATA SUBMISSION
PERIOD
Addition of two data
submission periods
(for a total of 4)
Number
Respondents
Number of
Responses/
Respondent
Total
Annual
Responses
Time per
Response
(hrs)
Time per
Facility
(hrs)
Total
Annual
Time (hrs)
Applicable
Wage Rate
($/hr)
Cost per
Facility
($)
Total Aunual
Cost($)
1,596
2
3,192
0.167
0.334
533
52.12
17
27,783
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E. Consideration of Burden Related to
Clarification of Eligibility Criteria for the
Option To Elect To File an All-Inclusive
Cost Report
As discussed in section III.E.4 of this
proposed rule, we are clarifying the
eligibility criteria to be approved to file
all-inclusive cost reports. Only
government-owned and tribally owned
facilities are able to satisfy these criteria,
and thus only these facilities will be
permitted to file an all-inclusive cost
report for cost reporting periods
beginning on or after October 1, 2024.
We do not estimate any change in the
burden associated with the hospital cost
report (CMS–2552–10) OMB control
number 0938–0050. We anticipate that
IPFs which are currently filing allinclusive cost reports, but are not
government-owned or tribally owned,
would not incur additional burden
related to the submission of the cost
report. The approved burden estimate
associated with the submission of the
hospital cost report includes the same
amount of burden for the submission of
an all-inclusive cost report as for the
submission of a cost report with a
charge structure.
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We recognize that these IPFs would
be required to track ancillary costs and
charges using a charge structure;
however, we expect that any burden
associated with this tracking would be
part of the normal course of a hospital’s
activities.
F. Submission of PRA-Related
Comments
We have submitted a copy of this
proposed rule’s information collection
requirements to OMB for their review.
The requirements are not effective until
they have been approved by OMB.
To obtain copies of the supporting
statement and any related forms for the
proposed collections discussed above,
please visit the CMS website at https://
www.cms.gov/regulationsand-guidance/
legislation/
paperworkreductionactof1995/pralisting, or call the Reports Clearance
Office at 410–786–1326.
We invite public comments on these
potential information collection
requirements. If you wish to comment,
please submit your comments
electronically as specified in the DATES
and ADDRESSES sections of this
proposed rule and identify the rule
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(CMS–1806–P), the ICR’s CFR citation,
and OMB control number.
VII. 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.
VIII. Regulatory Impact Analysis
A. Statement of Need
This rule proposes updates to the
prospective payment rates for Medicare
inpatient hospital services provided by
IPFs for discharges occurring during FY
2025 (October 1, 2024 through
September 30, 2025). We are proposing
to apply the 2021-based IPF market
basket increase of 3.1 percent, reduced
by the productivity adjustment of 0.4
percentage point as required by
1886(s)(2)(A)(i) of the Act for a proposed
total FY 2025 payment rate update of
2.7 percent. In this proposed rule, we
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are proposing to update the outlier fixed
dollar loss threshold amount, update the
IPF labor-related share, adopt new
CBSA delineations based on OMB
Bulletin 23–01, and update the IPF wage
index to reflect the FY 2025 hospital
inpatient wage index. Section 1886(s)(4)
of the Act requires IPFs to report data
in accordance with the requirements of
the IPFQR Program for purposes of
measuring and making publicly
available information on health care
quality; and links the quality data
submission to the annual applicable
percentage increase.
B. Overall Impact
We have examined the impacts of this
rule as required by Executive Order
12866 on Regulatory Planning and
Review (September 30, 1993), Executive
Order 13563 on Improving Regulation
and Regulatory Review (January 18,
2011), Executive Order 14094 on
Modernizing Regulatory Review (April
6, 2023), the Regulatory Flexibility Act
(RFA) (September 19, 1980, Pub. L. 96–
354), section 1102(b) of the Social
Security Act, section 202 of the
Unfunded Mandates Reform Act of 1995
(March 22, 1995; Pub. L. 104–4), and
Executive Order 13132 on Federalism
(August 4, 1999).
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, as amended by Executive Order
14094, defines a ‘‘significant regulatory
action’’ as an action that is likely to
result in a rule that may: (1) have an
annual effect on the economy of $200
million or more (adjusted every 3 years
by the Administrator of OIRA for
changes in gross domestic product); or
adversely affect in a material way the
economy, a sector of the economy,
productivity, competition, jobs, the
environment, public health or safety, or
State, local, territorial, or tribal
governments or communities; (2) create
a serious inconsistency or otherwise
interfere with an action taken or
planned by another agency; (3)
materially alter the budgetary impacts of
entitlements, grants, user fees, or loan
programs or the rights and obligations of
recipients thereof; or (4) raise legal or
policy issues for which centralized
review would meaningfully further the
President’s priorities or the principles
set forth in Executive Order 12866. In
accordance with the provisions of
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Executive Order 12866, this regulation
was reviewed by the Office of
Management and Budget.
A regulatory impact analysis (RIA)
must be prepared for regulatory actions
that are significant under section 3(f)(1)
of Executive Order 12866. We estimate
that the total impact of these changes for
FY 2025 payments compared to FY 2024
payments will be a net increase of
approximately $70 million. This reflects
a $75 million increase from the update
to the payment rates (+$85 million from
the 4th quarter 2023 IGI forecast of the
2021-based IPF market basket of 3.1
percent, and -$10 million for the
productivity adjustment of 0.4
percentage point), as well as a $5
million decrease as a result of the
update to the outlier threshold amount.
Outlier payments are estimated to
change from 2.1 percent in FY 2024 to
2.0 percent of total estimated IPF
payments in FY 2025.
Based on our estimates, OMB’s Office
of Information and Regulatory Affairs
has determined that this rulemaking is
‘‘significant,’’ though not significant
under section 3(f)(1) of Executive Order
12866. Nevertheless, because of the
potentially substantial impact to IPF
providers, we have prepared a
Regulatory Impact Analysis that to the
best of our ability presents the costs and
benefits of the rulemaking. OMB has
reviewed these proposed regulations,
and the Departments have provided the
following assessment of their impact.
Nevertheless, because of the
potentially substantial impact to IPF
providers, we have prepared a
Regulatory Impact Analysis that to the
best of our ability presents the costs and
benefits of the rulemaking. Based on our
estimates, OMB’s Office of Information
and Regulatory Affairs has determined
that this rulemaking is ‘‘significant.’’
Therefore, OMB has reviewed these
proposed regulations, and the
Departments have provided the
following assessment of their impact.
C. Detailed Economic Analysis
In this section, we discuss the
historical background of the IPF PPS
and the impact of this proposed rule on
the Federal Medicare budget and on
IPFs.
1. Budgetary Impact
As discussed in the RY 2005 and RY
2007 IPF PPS final rules, we applied a
budget neutrality factor to the Federal
per diem base rate and ECT payment per
treatment to ensure that total estimated
payments under the IPF PPS in the
implementation period would equal the
amount that would have been paid if the
IPF PPS had not been implemented.
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This budget neutrality factor included
the following components: outlier
adjustment, stop-loss adjustment, and
the behavioral offset. As discussed in
the RY 2009 IPF PPS notice (73 FR
25711), the stop-loss adjustment is no
longer applicable under the IPF PPS.
As discussed in section III.D.1.d of
this proposed rule, we are proposing to
update the wage index and labor-related
share, as well as update the CBSA
delineations based on OMB Bulletin 23–
01, in a budget neutral manner by
applying a wage index budget neutrality
factor to the Federal per diem base rate
and ECT payment per treatment. In
addition, as discussed in section III.F of
this proposed rule, we are proposing to
apply a refinement standardization
factor to the Federal per diem base rate
and ECT payment per treatment to
account for the proposed revisions to
the ECT per treatment amount, ED
adjustment, and patient-level
adjustment factors (as previously
discussed in sections III.B, III.C, and
III.D of this proposed rule, and
summarized in Addendum A), which
must be made budget-neutrally.
Therefore, the budgetary impact to the
Medicare program of this proposed rule
would be due to the proposed market
basket update for FY 2025 of 3.1 percent
(see section III.A.2 of this proposed rule)
reduced by the productivity adjustment
of 0.4 percentage point required by
section 1886(s)(2)(A)(i) of the Act and
the update to the outlier fixed dollar
loss threshold amount.
We estimate that the FY 2025 impact
would be a net increase of $70 million
in payments to IPF providers. This
reflects an estimated $75 million
increase from the update to the payment
rates and a $5 million decrease due to
the update to the outlier threshold
amount to set total estimated outlier
payments at 2.0 percent of total
estimated payments in FY 2025. This
estimate does not include the
implementation of the required 2.0
percentage point reduction of the
productivity-adjusted market basket
update factor for any IPF that fails to
meet the IPF quality reporting
requirements (as discussed in section
III.B.2. of this proposed rule).
2. Impact on Providers
To show the impact on providers of
the changes to the IPF PPS discussed in
this proposed rule, we compare
estimated payments under the proposed
IPF PPS rates and factors for FY 2025
versus those under FY 2024. We
determined the percent change in the
estimated FY 2025 IPF PPS payments
compared to the estimated FY 2024 IPF
PPS payments for each category of IPFs.
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In addition, for each category of IPFs,
we have included the estimated percent
change in payments resulting from the
proposed update to the outlier fixed
dollar loss threshold amount; the
proposed revisions to the patient-level
adjustment factors, ED adjustment, and
ECT per treatment amount; the updated
wage index data including the proposed
labor-related share and the proposed
changes to the CBSA delineations; and
the proposed market basket increase for
FY 2025, as reduced by the proposed
productivity adjustment according to
section 1886(s)(2)(A)(i) of the Act.
To illustrate the impacts of the
proposed FY 2025 changes in this
proposed rule, our analysis begins with
FY 2023 IPF PPS claims (based on the
2023 MedPAR claims, December 2023
update). We estimate FY 2024 IPF PPS
payments using these 2023 claims, the
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finalized FY 2024 IPF PPS Federal per
diem base rate and ECT per treatment
amount, and the finalized FY 2024 IPF
PPS patient and facility level
adjustment factors (as published in the
FY 2024 IPF PPS final rule (88 FR
51054)). We then estimate the FY 2024
outlier payments based on these
simulated FY 2024 IPF PPS payments
using the same methodology as finalized
in the FY 2024 IPF PPS final rule (88 FR
51090 through 51092) where total
outlier payments are maintained at 2
percent of total estimated FY 2024 IPF
PPS payments.
Each of the following changes is
added incrementally to this baseline
model in order for us to isolate the
effects of each change:
• The proposed update to the outlier
fixed dollar loss threshold amount.
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• The proposed revisions to patientlevel adjustment factors, ED adjustment,
and the ECT per treatment amount.
• The proposed FY 2025 IPF wage
index, the proposed changes to the
CBSA delineations, and the proposed
FY 2025 labor-related share (LRS).
• The proposed market basket
increase for FY 2025 of 3.1 percent
reduced by the proposed productivity
adjustment of 0.4 percentage point in
accordance with section 1886(s)(2)(A)(i)
of the Act for a payment rate update of
2.7 percent.
Our proposed column comparison in
Table 29 illustrates the percent change
in payments from FY 2024 (that is,
October 1, 2023, to September 30, 2024)
to FY 2025 (that is, October 1, 2024, to
September 30, 2025) including all the
proposed payment policy changes.
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TABLE 29: FY 2025 TPF PPS PROPOSED PAYMENT IMPACTS
Number of
Facilities
Outlier
(2)
1,430
(3)
-0.1
(4)
0.0
(5)
0.0
(6)
2.6
Tolal Urban
Urban unit
Urban hospital
1 171
655
516
-0.1
-0.1
0.0
0.0
0.4
-0.5
-0.2
-0.5
0.2
2.4
2.5
2.3
Total Rural
Rural unit
Rural hospital
259
199
60
0.0
0.0
0.0
0.0
0.3
-0.7
1.3
1.1
1.7
4.0
4.1
3.7
By Type of
Ownership:
12014
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Refinement of
Patient-Level
Adjustments and Wage Index FY25,
ECT
LRS, and 5% Cap
Federal Register / Vol. 89, No. 65 / Wednesday, April 3, 2024 / Proposed Rules
Facility by Type 1
10%to 30%
interns and
residents to beds
More than 30%
interns and
residents to beds
BvRe!rlon:
New England
Mid-Atlantic
South Atlantic
East North
Central
East South
Central
West North
Central
West South
Central
Mountain
Pacific
Refinement of
Patient-Level
Adjustments and Wage Index FY25,
ECT
LRS and 5% Cap
Number of
Facilities
Outlier
71
-0.1
1.1
-1.2
2.4
25
-0.2
1.0
-1.1
2.4
102
193
226
-0.1
-0.1
0.0
0.8
0.2
0.4
-1.3
-1.5
0.9
2.1
1.2
4.0
228
0.0
0.0
0.2
2.9
140
0.0
-0.1
2.5
5.0
99
-0.1
1.1
0.3
3.9
214
102
126
0.0
0.0
--0.1
-1.0
-0.4
-0.5
1.7
1.1
-1.6
3.3
3.4
0.5
23221
Total Percent
Chane:e 2
By Bed Size:
Psychiatric
Hospitals
Beds: 0-24
87
0.0
-0.8
0.6
2.5
Beds: 25-49
87
0.0
1.0
2.6
-1.1
Beds: 50-75
92
0.0
-0.4
0.8
3.1
Beds: 76 +
310
0.0
-0.4
0.0
2.2
Psvchiatric Units
-0.1
Beds: 0-24
450
0.2
0.4
3.2
Beds: 25-49
234
-0.1
0.5
-0.7
2.4
Beds: 50-75
98
-0.1
0.7
0.2
3.5
Beds: 76 +
72
--0.2
0.5
-1.1
1.9
1 Providers in this table are classified as urban or rural based on the current CBSA delineations for FY 2024.
2 This column includes the impact of the updates in columns (3) through (6) above, and of the proposed IPF market
basket percentage increase for FY 2025 of 3 .1 percent, reduced by 0. 4 percentage point for the productivity
adjustment as required by section 1886(s)(2)(A)(i) of the Act.
Table 30 displays the results of our
analysis. The table groups IPFs into the
categories listed here based on
characteristics provided in the Provider
of Services file, the IPF PSF, and cost
report data from the Healthcare Cost
Report Information System:
• Facility Type.
• Location.
• Teaching Status Adjustment.
• Census Region.
• Size.
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The top row of the table shows the
overall impact on the 1,430 IPFs
included in the analysis. In column 2,
we present the number of facilities of
each type that had information available
in the PSF, had claims in the MedPAR
dataset for FY 2023. We note that
providers are assigned urban or rural
status in Table 30 based on the current
CBSA delineations for FY 2024.
In column 3, we present the effects of
the update to the outlier fixed dollar
loss threshold amount. We estimate that
IPF outlier payments as a percentage of
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total IPF payments are 2.1 percent in FY
2024. Therefore, we are proposing to
adjust the outlier threshold amount to
set total estimated outlier payments
equal to 2.0 percent of total payments in
FY 2025. The estimated change in total
IPF payments for FY 2025, therefore,
includes an approximate 0.1 percent
decrease in payments because we would
expect the outlier portion of total
payments to decrease from
approximately 2.1 percent to 2.0
percent.
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3. Impact Results
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The overall impact of the estimated
decrease to payments due to updating
the outlier fixed dollar loss threshold (as
shown in column 3 of Table 30), across
all hospital groups, is a 0.1 percent
decrease. The largest decrease in
payments due to this change is
estimated to be 0.2 percent for urban
government IPF units, IPFs with more
than 30 percent interns and residents to
beds, and IPF units with 76+ beds.
In column 4, we present the effects of
the proposed revisions to the patientlevel adjustment factors, ED adjustment,
and ECT per treatment amount and the
application of the refinement
standardization factor that is discussed
in section III.F of this proposed rule. We
estimate the largest payment increases
would be for rural freestanding
government-owned IPFs. Conversely,
we estimate that for-profit IPF hospitals
in rural areas would experience the
largest payment decrease. Payments to
IPF units in urban areas would increase
by 0.4 percent, and payments to IPF
units in rural areas would increase by
0.3 percent.
In column 5, we present the effects of
the proposed budget-neutral update to
the IPF wage index, the proposed LRS,
and the proposed changes to the CBSA
delineations for FY 2025. In addition,
this column includes the application of
the 5-percent cap on any decrease to a
provider’s wage index from its wage
index in the prior year as finalized in
the FY 2023 IPF PPS final rule (87 FR
46856 through 46859). The change in
this column represents the effect of
using the concurrent hospital wage data
as discussed in section III.D.1.a of this
proposed rule. That is, the impact
represented in this column reflects the
proposed update from the FY 2024 IPF
wage index to the proposed FY 2025 IPF
wage index, which includes basing the
FY 2025 IPF wage index on the FY 2025
pre-floor, pre-reclassified IPPS hospital
wage index data, applying a 5-percent
cap on any decrease to a provider’s
wage index from its wage index in the
prior year, and updating the LRS from
78.7 percent in FY 2024 to 78.8 percent
in FY 2025. We note that there is no
projected change in aggregate payments
to IPFs, as indicated in the first row of
column 5; however, there would be
distributional effects among different
categories of IPFs. For example, we
estimate the largest increase in
payments to be 2.9 percent for
freestanding rural for-profit IPFs, and
the largest decrease in payments to be
1.6 percent for IPFs located in the
Pacific region.
Overall, IPFs are estimated to
experience a net increase in payments of
2.6 percent as a result of the updates in
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this proposed rule. IPF payments are
therefore estimated to increase by 2.4
percent in urban areas and 4.0 percent
in rural areas. The largest payment
increase is estimated at 5.0 percent for
IPFs located in the East South Central
region.
4. Effect on Beneficiaries
Under the FY 2025 IPF PPS, IPFs will
continue to receive payment based on
the average resources consumed by
patients for each day. Our longstanding
payment methodology reflects the
differences in patient resource use and
costs among IPFs, as required under
section 124 of the BBRA. We expect that
updating IPF PPS rates in this rule will
improve or maintain beneficiary access
to high quality care by ensuring that
payment rates reflect the best available
data on the resources involved in
inpatient psychiatric care and the costs
of these resources. We continue to
expect that paying prospectively for IPF
services under the FY 2025 IPF PPS will
enhance the efficiency of the Medicare
program.
As discussed in sections V.B.2 of this
proposed rule, we expect that the
proposed additional IPFQR Program
measure will support improving
discharge planning and care
coordination to decrease the likelihood
that a patient will need to seek
emergency care within 30 days of
discharge from an IPF.
5. Effects of the Updates to the IPFQR
Program
In section V.B.2. of this rule, we are
proposing the 30-Day Risk-Standardized
All-Cause ED Visit Following an
Inpatient Psychiatric Facility Discharge
measure beginning with data from the
CY 2025 performance period for the FY
2027 payment determination. We do not
believe this update would impact
providers’ workflows or information
systems to collect or report the data
because this measure is calculated by
CMS using information that IPFs
already submit as part of the claims
process. There may be some effects of
this measure on IPF workflows and
clinical processes to improve care
coordination and discharge planning to
improve performance on the measure.
We are also proposing to adopt a
quarterly data submission requirement
for measures for which we require
patient-level data. We believe there may
be some non-recurrent costs associated
with training staff and updating
processes to submit these data more
frequently. We believe that the recurring
costs of these updates will be an
increase of 800 hours across all IPFs,
equating to change of $41,696.
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In accordance with section
1886(s)(4)(A) of the Act, we will apply
a 2-percentage point reduction to the FY
2025 market basket update for IPFs that
have failed to comply with the IPFQR
Program requirements for FY 2025,
including reporting on the mandatory
measures. For the FY 2024 payment
determination, of the 1,568 IPFs eligible
for the IPFQR Program, 194 IPFs did not
receive the full market basket update
because of the IPFQR Program; 42 of
these IPFs chose not to participate and
152 did not meet the requirements of
the program.
We intend to closely monitor the
effects of the IPFQR Program on IPFs
and help facilitate successful reporting
outcomes through ongoing education,
national trainings, and a technical help
desk.
6. Regulatory Review Costs
If regulations impose administrative
costs on private entities, such as the
time needed to read and interpret this
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 be directly impacted
and will review this proposed rule, we
assume that the total number of unique
commenters on the most recent IPF
proposed rule will be the number of
reviewers of this proposed rule. For this
FY 2025 IPF PPS proposed rule, the
most recent IPF proposed rule was the
FY 2024 IPF PPS proposed rule, and we
received 2,506 unique comments on this
proposed rule. We acknowledge that
this assumption may understate or
overstate the costs of reviewing this
proposed rule. It is possible that not all
commenters reviewed the FY 2024 IPF
proposed rule in detail, and it is also
possible that some reviewers chose not
to comment on that proposed rule. For
these reasons, we thought that the
number of commenters would be a fair
estimate of the number of reviewers
who are directly impacted by this
proposed rule. We are soliciting
comments on this assumption.
We also recognize that different types
of entities are in many cases affected by
mutually exclusive sections of this
proposed rule; therefore, for the
purposes of our estimate, we assume
that each reviewer reads approximately
50 percent of this proposed rule.
Using the May, 2022 mean (average)
wage information from the BLS for
medical and health service managers
(Code 11–9111), we estimate that the
cost of reviewing this proposed rule is
$123.06 per hour, including other
indirect costs https://www.bls.gov/oes/
current/oes119111.htm. Assuming an
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average reading speed of 250 words per
minute, we estimate that it would take
approximately 112 minutes (1.87 hours)
for the staff to review half of this
proposed rule, which contains a total of
approximately 56,000 words. For each
IPF that reviews the proposed rule, the
estimated cost is (1.87 × $123.06) or
$230.12. Therefore, we estimate that the
total cost of reviewing this proposed
rule is $576,680.72 ($230.12 × 2,506
reviewers).
D. Alternatives Considered
The statute gives the Secretary
discretion in establishing an update
methodology to the IPF PPS. We
continue to believe it is appropriate to
routinely update the IPF PPS so that it
reflects the best available data about
differences in patient resource use and
costs among IPFs, as required by the
statute. Therefore, we are proposing to:
update the IPF PPS using the
methodology published in the RY 2005
IPF PPS final rule (our ‘‘standard
methodology’’) pre-floor, prereclassified IPPS hospital wage index as
its basis, along with the proposed
changes to the CBSA delineations.
Additionally, we apply a 5-percent cap
on any decrease to a provider’s wage
index from its wage index in the prior
year. Lastly, we are proposing to revise
the patient-level adjustment factors, ED
adjustment, and to increase the ECT per
treatment amount for FY 2025
(reflecting the pre-scaled and preadjusted CY 2024 OPPS geometric mean
cost).
E. Accounting Statement
As required by OMB Circular A–4
(available at www.whitehouse.gov/sites/
whitehouse.gov/files/omb/circulars/A4/
a-4.pdf ), in Table 30, we have prepared
an accounting statement showing the
classification of the expenditures
associated with the updates to the IPF
wage index and payment rates in this
proposed rule. Table 30 provides our
best estimate of the increase in Medicare
payments under the IPF PPS as a result
of the changes presented in this
proposed rule and based on the data for
1,430 IPFs with data available in the
PSF, with claims in our FY 2023
MedPAR claims dataset. Lastly, Table
30 also includes our best estimate of the
costs of reviewing and understanding
this proposed rule.
TABLE 30: Accounting Statement: Classification of Estimated Costs, Savings, and
Transfers
Units
Low
estimate
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Period
covered
-
2022
-
r
70
-
-
FY 2025
-
FY 2025
hospitals as businesses having less than
$47 million.
Because we lack data on individual
hospital receipts, we cannot determine
the number of small proprietary IPFs or
the proportion of IPFs’ revenue derived
from Medicare payments. Therefore, we
assume that all IPFs are considered
small entities.
The Department of Health and Human
Services generally uses a revenue
impact of 3 to 5 percent as a significance
threshold under the RFA. As shown in
Table 30, we estimate that the overall
revenue impact of this proposed rule on
all IPFs is to increase estimated
Medicare payments by approximately
2.6 percent. As a result, since the
estimated impact of this proposed rule
is a net increase in revenue across
almost all categories of IPFs, the
Secretary has determined that this
proposed rule will have a positive
revenue impact on a substantial number
of small entities.
In addition, section 1102(b) of the Act
requires us to prepare a regulatory
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Discount
rate
-
Annualized Monetized Transfers
from Federal Government to IPF
Medicare Providers
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. The great
majority of hospitals and most other
health care providers and suppliers are
small entities, either by being nonprofit
organizations or by meeting the Small
Business Administration (SBA)
definition of a small business (having
revenues of less than $47 million in any
1 year).
According to the SBA’s website at
https://www.sba.gov/content/smallbusiness-size-standards, IPFs falls into
the North American Industrial
Classification System (NAICS) code
622210, Psychiatric and Substance
Abuse hospitals. The SBA defines small
Psychiatric and Substance Abuse
Year
dollars
U.5~
Regulatory Review Costs
F. Regulatory Flexibility Act
High
estimate
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Y LVD
impact analysis if a rule may have a
significant impact on the operations of
a substantial number of small rural
hospitals. This analysis must conform to
the provisions of section 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 discussed in
section VIII.C.2 of this proposed rule,
the rates and policies set forth in this
proposed rule will not have an adverse
impact on the rural hospitals based on
the data of the 199 rural excluded
psychiatric units and 60 rural
psychiatric hospitals in our database of
1,430 IPFs for which data were
available. Therefore, the Secretary has
determined that this proposed rule will
not have a significant impact on the
operations of a substantial number of
small rural hospitals.
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G. Unfunded Mandate Reform Act
(UMRA)
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Section 202 of the Unfunded
Mandates Reform Act of 1995 (UMRA)
also requires that agencies assess
anticipated costs and benefits before
issuing any rule whose mandates
require spending in any 1 year of $100
million in 1995 dollars, updated
annually for inflation. In 2023, that
threshold is approximately $183
million. This proposed rule does not
mandate any requirements for state,
local, or tribal governments, or for the
private sector. This proposed rule
would not impose a mandate that will
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result in the expenditure by state, local,
and tribal governments, in the aggregate,
or by the private sector, of more than
$183 million in any 1 year.
H. Federalism
Executive Order 13132 establishes
certain requirements that an agency
must meet when it promulgates a
proposed rule that imposes substantial
direct requirement costs on state and
local governments, preempts state law,
or otherwise has Federalism
implications. This proposed rule does
not impose substantial direct costs on
state or local governments or preempt
state law.
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In accordance with the provisions of
Executive Order 12866, this proposed
regulation was reviewed by the Office of
Management and Budget.
Chiquita Brooks-LaSure,
Administrator of the Centers for
Medicare & Medicaid Services,
approved this document on March 22,
2024.
Xavier Becerra,
Secretary, Department of Health and Human
Services.
[FR Doc. 2024–06764 Filed 3–28–24; 4:15 pm]
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Agencies
[Federal Register Volume 89, Number 65 (Wednesday, April 3, 2024)]
[Proposed Rules]
[Pages 23146-23224]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2024-06764]
[[Page 23145]]
Vol. 89
Wednesday,
No. 65
April 3, 2024
Part III
Department of Health and Human Services
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Centers for Medicare & Medicaid Services
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42 CFR Part 412
Medicare Program; FY 2025 Inpatient Psychiatric Facilities Prospective
Payment System--Rate Update; Proposed Rule
Federal Register / Vol. 89, No. 65 / Wednesday, April 3, 2024 /
Proposed Rules
[[Page 23146]]
-----------------------------------------------------------------------
DEPARTMENT OF HEALTH AND HUMAN SERVICES
Centers for Medicare & Medicaid Services
42 CFR Part 412
[CMS-1806-P]
RIN 0938-AV32
Medicare Program; FY 2025 Inpatient Psychiatric Facilities
Prospective Payment System--Rate Update
AGENCY: Centers for Medicare & Medicaid Services (CMS), Department of
Health and Human Services (HHS).
ACTION: Proposed rule.
-----------------------------------------------------------------------
SUMMARY: This rulemaking proposes to update the prospective payment
rates, the outlier threshold, and the wage index for Medicare inpatient
hospital services provided by Inpatient Psychiatric Facilities (IPF),
which include psychiatric hospitals and excluded psychiatric units of
an acute care hospital or critical access hospital. This rulemaking
also proposes to revise the patient-level adjustment factors, the
Emergency Department adjustment, and the payment amount for
electroconvulsive therapy. These proposed changes would be effective
for IPF discharges occurring during the fiscal year beginning October
1, 2024 through September 30, 2025 (FY 2025). In addition, this
proposed rule seeks to adopt a new quality measure and modify reporting
requirements under the IPF Quality Reporting Program beginning with the
FY 2027 payment determination. Furthermore, this proposed rule solicits
comments through Requests for Information (RFIs) regarding potential
future revisions to the IPF PPS facility-level adjustments and
regarding the development of a standardized IPF Patient Assessment
Instrument.
DATES: To be assured consideration, comments must be received at one of
the addresses provided below, by May 28, 2024.
ADDRESSES: In commenting, please refer to file code CMS-1806-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-1806-P, P.O. Box 8010,
Baltimore, MD 21244-8010.
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-1806-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:
Nick Brock (410) 786-5148, for information regarding the inpatient
psychiatric facilities prospective payment system (IPF PPS).
Kaleigh Emerson (470) 890-4141, for information regarding the
inpatient psychiatric facilities quality reporting program (IPFQR).
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 commenter will take actions to harm an 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.
Plain Language Summary: In accordance with 5 U.S.C. 553(b)(4), a
plain language summary of this rule may be found at https://www.regulations.gov/.
Availability of Certain Tables Exclusively Through the Internet on the
CMS Website
Addendum A to this proposed rule summarizes the proposed FY 2025
Inpatient Psychiatric Facilities Prospective Payment System (IPF PPS)
payment rates, outlier threshold, cost of living adjustment factors for
Alaska and Hawaii, national and upper limit cost-to-charge ratios, and
adjustment factors. In addition, Addendum B to this proposed rule shows
the complete listing of ICD-10 Clinical Modification and Procedure
Coding System codes, the FY 2025 IPF PPS comorbidity adjustment, and
electroconvulsive therapy procedure codes. The A and B Addenda are
available on the CMS website at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/tools.html.
Tables setting forth the FY 2025 Wage Index for Urban Areas Based
on Core-Based Statistical Area Labor Market Areas, the FY 2025 Wage
Index Based on CBSA Labor Market Areas for Rural Areas, and a county-
level crosswalk of the FY 2024 CBSA Labor Market Areas to the FY 2025
CBSA Labor Market Areas are available exclusively through the internet,
on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/IPFPPS/WageIndex.html.
I. Executive Summary
A. Purpose
This proposed rule would update the prospective payment rates, the
outlier threshold, and the wage index for Medicare inpatient hospital
services provided by Inpatient Psychiatric Facilities (IPFs) for
discharges occurring during fiscal year (FY) 2025, (beginning October
1, 2024 through September 30, 2025). We are proposing to adopt the
Core-Based Statistical Area (CBSA) Labor Market Areas for the IPF PPS
wage index as defined in the Office of Management and Budget (OMB)
Bulletin 23-01. In addition, this rule includes a proposal to refine
the patient-level adjustment factors and increase the payment amount
for electroconvulsive therapy (ECT) treatments. We are not proposing
changes to the facility-level adjustment factors for FY 2025; however,
this proposed rule presents the results of our latest analysis and
includes a request for information relating to those results. This rule
also includes a clarification of the eligibility criteria for an IPF to
be approved to file all-inclusive cost reports. In addition, this
proposed rule includes a request for information regarding the creation
of a patient assessment instrument (PAI) as mandated by Section 4125 of
the Consolidated Appropriations Act (CAA), 2023 (hereafter referred to
as CAA, 2023) (Pub. L. 117-328). Lastly, this proposed rule discusses
quality measures and reporting requirements under the Inpatient
Psychiatric
[[Page 23147]]
Facilities Quality Reporting (IPFQR) Program.
B. Summary of the Major Provisions
1. Inpatient Psychiatric Facilities Prospective Payment System (IPF
PPS)
For the IPF PPS, we are:
Proposing to revise the patient-level IPF PPS adjustment
factors and increase the ECT per treatment payment amount.
Proposing to update the IPF PPS wage index to use the
CBSAs defined within OMB Bulletin 23-01.
Clarifying the eligibility criteria for an IPF to be
approved to file all-inclusive cost reports. Only a government-owned or
tribally owned facility will be able to satisfy these criteria and will
be eligible to file its cost report using an all-inclusive rate or no
charge structure.
Soliciting comments to inform elements to be included in
the IPF patient assessment instrument, which the CAA, 2023 requires the
Centers for Medicare & Medicaid Services (CMS) to develop for FY 2028.
Soliciting comments to inform future refinements to the
IPF PPS facility-level adjustment factors.
Making technical rate setting updates: The IPF PPS payment
rates are adjusted annually for inflation, as well as statutory and
other policy factors. This rule proposes to update:
++ The IPF PPS Federal per diem base rate from $895.63 to $874.93.
++ The IPF PPS Federal per diem base rate for providers who failed
to report quality data to $857.89.
++ The ECT payment per treatment from $385.58 to $660.30.
++ The ECT payment per treatment for providers who failed to report
quality data to $647.45.
++ The labor-related share from 78.7 percent to 78.8 percent.
++ The wage index budget neutrality factor to 0.9998. This proposed
rule would apply a refinement standardization factor of 0.9514.
++ The fixed dollar loss threshold amount from $33,470 to $35,590,
to maintain estimated outlier payments at 2 percent of total estimated
aggregate IPF PPS payments.
2. Inpatient Psychiatric Facilities Quality Reporting (IPFQR) Program
For the IPFQR Program, we are proposing to:
Adopt the 30-Day Risk-Standardized All-Cause Emergency
Department (ED) Visit Following an IPF Discharge measure beginning with
the FY 2027 payment determination; and
Modify reporting requirements to require IPFs to submit
patient-level data on a quarterly basis.
We also refer readers to our RFI in which we solicit comments to
inform elements to be included in the IPF patient assessment
instrument, which the CAA, 2023 requires the Centers for Medicare &
Medicaid Services (CMS) to develop and implement for Rate Year (RY)
2028.
C. Summary of Impacts
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II. Background
A. Overview of the Legislative Requirements of the IPF PPS
Section 124 of the Medicare, Medicaid, and State Children's Health
Insurance Program Balanced Budget Refinement Act of 1999 (BBRA) (Pub.
L. 106-113) required the establishment and implementation of an IPF
PPS. Specifically, section 124 of the BBRA mandated that the Secretary
of the Department of Health and Human Services (the Secretary) develop
a per diem payment perspective system (PPS) for inpatient hospital
services furnished in psychiatric hospitals and excluded psychiatric
units including an adequate patient classification system that reflects
the differences in patient resource use and costs among psychiatric
hospitals and excluded psychiatric units. ``Excluded psychiatric unit''
means a psychiatric unit of an acute care hospital or of a Critical
Access Hospital (CAH), which is excluded from payment under the
Inpatient Prospective Payment System (IPPS) or CAH payment system,
respectively. These excluded psychiatric units will be paid under the
IPF PPS.
Section 405(g)(2) of the Medicare Prescription Drug, Improvement,
and Modernization Act of 2003 (MMA) (Pub. L. 108-173) extended the IPF
PPS to psychiatric distinct part units of CAHs.
Sections 3401(f) and 10322 of the Patient Protection and Affordable
Care Act (Pub. L. 111-148) as amended by section 10319(e) of that Act
and by section 1105(d) of the Health Care and Education Reconciliation
Act of 2010 (Pub. L. 111-152) (hereafter referred to jointly as ``the
Affordable Care Act'') added subsection (s) to section 1886 of the Act.
Section 1886(s)(1) of the Act titled ``Reference to Establishment
and Implementation of System,'' refers to section 124 of the BBRA,
which relates to the establishment of the IPF PPS.
Section 1886(s)(2)(A)(i) of the Act requires the application of the
productivity adjustment described in section 1886(b)(3)(B)(xi)(II) of
the Act to the IPF PPS for the rate year (RY) beginning in 2012 (that
is, a RY that coincides with a FY) and each subsequent RY.
Section 1886(s)(2)(A)(ii) of the Act required the application of an
``other adjustment'' that reduced any update to an IPF PPS base rate by
a percentage point amount specified in section 1886(s)(3) of the Act
for the RY beginning in 2010 through the RY beginning in 2019. As noted
in the FY 2020 Inpatient Psychiatric Facilities Prospective Payment
System and Quality Reporting Updates for fiscal year Beginning October
1, 2019 final rule, for the RY beginning in 2019,
[[Page 23148]]
section 1886(s)(3)(E) of the Act required that the other adjustment
reduction be equal to 0.75 percentage point; that was the final year
the statute required the application of this adjustment. Because FY
2021 was a RY beginning in 2020, FY 2021 was the first year section
1886(s)(2)(A)(ii) of the Act did not apply since its enactment.
Sections 1886(s)(4)(A) through (D) of the Act require that for RY
2014 and each subsequent RY, IPFs that fail to report required quality
data with respect to such a RY will have their annual update to a
standard Federal rate for discharges reduced by 2.0 percentage points.
This may result in an annual update being less than 0.0 for a RY, and
may result in payment rates for the upcoming RY being less than such
payment rates for the preceding RY. Any reduction for failure to report
required quality data will apply only to the RY involved, and the
Secretary will not consider such reduction in computing the payment
amount for a subsequent RY. Additional information about the specifics
of the current IPFQR Program is available in the FY 2020 Inpatient
Psychiatric Facilities Prospective Payment System and Quality Reporting
Updates for fiscal year Beginning October 1, 2019 (FY 2020) final rule
(84 FR 38459 through 38468).
Section 4125 of the Consolidated Appropriations Act, 2023 (CAA,
2023) (Pub. L. 117-328), which amended section 1886(s) of the Act,
requires CMS to revise the Medicare prospective payment system for
psychiatric hospitals and psychiatric units. Specifically, section
4125(a) of the CAA, 2023 added section 1886(s)(5)(A) of the Act to
require the Secretary to collect data and information, as the Secretary
determines appropriate, to revise payments under the IPF PPS. CMS
discussed this data collection last year in the FY 2024 IPF PPS final
rule, as CMS was required to begin collecting this data and information
not later than October 1, 2024. As discussed in that rule, the Agency
has already been collecting data and information consistent with the
types set forth in the CAA, 2023 as part of our extensive and years-
long analyses and consideration of potential payment system
refinements. We refer readers to the FY 2024 Inpatient Psychiatric
Facilities Prospective Payment System--Rate Update (FY 2024 IPF PPS)
final rule (88 FR 51095 through 51098) where we discussed existing data
collection and requested information to inform future IPF PPS
revisions.
In addition, section 1886(s)(5)(D) of the Act, as added by section
4125(a) of the CAA, 2023 requires that the Secretary implement
revisions to the methodology for determining the payment rates under
the IPF PPS for psychiatric hospitals and psychiatric units, effective
for RY 2025 (FY 2025). The revisions may be based on a review of the
data and information collected under section 1886(s)(5)(A) of the Act.
As discussed in section III.C of this FY 2025 IPF PPS proposed rule, we
are proposing revisions to the IPF PPS patient-level adjustment factors
based on a review of cost and claims data.
Section 4125(b) of the CAA, 2023 amended section 1886(s)(4) of the
Act by inserting a new subparagraph (E), which requires IPFs
participating in the IPFQR Program to collect and submit to the
Secretary standardized patient assessment data, using a standardized
patient assessment instrument, for RY 2028 (FY 2028) and each
subsequent rate year. IPFs must submit such data with respect to at
least the admission and discharge of an individual, or more frequently
as the Secretary determines appropriate. For IPFs to meet this new data
collection and reporting requirement for RY 2028 and each subsequent
rate year, the Secretary must implement a standardized patient
assessment instrument that collects data with respect to the following
categories: functional status; cognitive function and mental status;
special services, treatments, and interventions; medical conditions and
comorbidities; impairments; and other categories as determined
appropriate by the Secretary. This patient assessment instrument must
enable comparison of such patient assessment data that IPFs submit
across all such IPFs to which such data are applicable.
Section 4125(b) of the CAA, 2023 further amended section 1886(s) of
the Act by adding a new subparagraph (6) that requires the Secretary to
implement revisions to the methodology for determining the payment
rates for psychiatric hospitals and psychiatric units (that is, payment
rates under the IPF PPS), effective for RY 2031 (FY 2031), as the
Secretary determines to be appropriate, to take into account the
patient assessment data described in paragraph (4)(E)(ii).
To implement and periodically update the IPF PPS, we have published
various proposed and final rules and notices in the Federal Register.
For more information regarding these documents, we refer readers to the
CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/?redirect=/
InpatientPsychFacilPPS/.
B. Overview of the IPF PPS
On November 15, 2004, we published the RY 2005 IPF PPS final rule
in the Federal Register (69 FR 66922). The RY 2005 IPF PPS final rule
established the IPF PPS, as required by section 124 of the BBRA and
codified at 42 CFR part 412, subpart N. The RY 2005 IPF PPS final rule
set forth the Federal per diem base rate for the implementation year
(the 18-month period from January 1, 2005 through June 30, 2006) and
provided payment for the inpatient operating and capital costs to IPFs
for covered psychiatric services they furnish (that is, routine,
ancillary, and capital costs, but not costs of approved educational
activities, bad debts, and other services or items that are outside the
scope of the IPF PPS). Covered psychiatric services include services
for which benefits are provided under the fee-for-service Part A
(Hospital Insurance Program) of the Medicare program.
The IPF PPS established the Federal per diem base rate for each
patient day in an IPF derived from the national average daily routine
operating, ancillary, and capital costs in IPFs in FY 2002. The average
per diem cost was updated to the midpoint of the first year under the
IPF PPS, standardized to account for the overall positive effects of
the IPF PPS payment adjustments, and adjusted for budget neutrality.
The Federal per diem payment under the IPF PPS is comprised of the
Federal per diem base rate described previously and certain patient-
and facility-level payment adjustments for characteristics that were
found in the regression analysis to be associated with statistically
significant per diem cost differences, with statistical significance
defined as p less than 0.05. A complete discussion of the regression
analysis that established the IPF PPS adjustment factors can be found
in the RY 2005 IPF PPS final rule (69 FR 66933 through 66936).
The patient-level adjustments include age, Diagnosis-Related Group
(DRG) assignment, and comorbidities, as well as adjustments to reflect
higher per diem costs at the beginning of a patient's IPF stay and
lower costs for later days of the stay. Facility-level adjustments
include adjustments for the IPF's wage index, rural location, teaching
status, a cost-of-living adjustment for IPFs located in Alaska and
Hawaii, and an adjustment for the presence of a qualifying emergency
department (ED).
The IPF PPS provides additional payment policies for outlier cases,
interrupted stays, and a per treatment
[[Page 23149]]
payment for patients who undergo ECT. During the IPF PPS mandatory 3-
year transition period, stop-loss payments were also provided; however,
since the transition ended as of January 1, 2008, these payments are no
longer available.
C. Annual Requirements for Updating the IPF PPS
Section 124 of the BBRA did not specify an annual rate update
strategy for the IPF PPS and was broadly written to give the Secretary
discretion in establishing an update methodology. Therefore, in the RY
2005 IPF PPS final rule, we implemented the IPF PPS using the following
update strategy:
Calculate the final Federal per diem base rate to be
budget neutral for the 18- month period of January 1, 2005 through June
30, 2006.
Use a July 1 through June 30 annual update cycle.
Allow the IPF PPS first update to be effective for
discharges on or after July 1, 2006 through June 30, 2007.
The RY 2005 final rule (69 FR 66922) implemented the IPF PPS. In
developing the IPF PPS, and to ensure that the IPF PPS can account
adequately for each IPF's case-mix, we performed an extensive
regression analysis of the relationship between the per diem costs and
certain patient and facility characteristics to determine those
characteristics associated with statistically significant cost
differences on a per diem basis. That regression analysis is described
in detail in our RY 2004 IPF proposed rule (68 FR 66923; 66928 through
66933) and our RY 2005 IPF final rule (69 FR 66933 through 66960). For
characteristics with statistically significant cost differences, we
used the regression coefficients of those variables to determine the
size of the corresponding payment adjustments.
In the RY 2005 IPF final rule, we explained the reasons for
delaying an update to the adjustment factors, derived from the
regression analysis, including waiting until we have IPF PPS data that
yields as much information as possible regarding the patient-level
characteristics of the population that each IPF serves. We indicated
that we did not intend to update the regression analysis and the
patient-level and facility-level adjustments until we complete that
analysis. Until that analysis is complete, we stated our intention to
publish a notice in the Federal Register each spring to update the IPF
PPS (69 FR 66966).
On May 6, 2011, we published a final rule in the Federal Register
titled, ``Inpatient Psychiatric Facilities Prospective Payment System--
Update for Rate Year Beginning July 1, 2011 (RY 2012)'' (76 FR 26432),
which changed the payment rate update period to a RY that coincides
with a FY update. Therefore, final rules are now published in the
Federal Register in the summer to be effective on October 1st. When
proposing changes in IPF payment policy, a proposed rule is issued in
the spring, and the final rule in the summer to be effective on October
1st. For a detailed list of updates to the IPF PPS, we refer readers to
our regulations at 42 CFR 412.428. Beginning October 1, 2012, we
finalized that we would refer to the 12-month period from October 1
through September 30 as a ``fiscal year'' (FY) rather than a RY (76 FR
26435). Therefore, in this final rule we refer to rules that took
effect after RY 2012 by the FY, rather than the RY, in which they took
effect.
The most recent IPF PPS annual update was published in a final rule
on August 2, 2023 in the Federal Register titled, ``Medicare Program;
FY 2024 Inpatient Psychiatric Facilities Prospective Payment System--
Rate Update'' (88 FR 51054), which updated the IPF PPS payment rates
for FY 2024. That final rule updated the IPF PPS Federal per diem base
rates that were published in the FY 2023 IPF PPS Rate Update final rule
(87 FR 46846) in accordance with our established policies.
III. Provisions of the Proposed Regulations
A. Proposed FY 2025 Market Basket Update and Productivity Adjustment
for the IPF PPS
1. Background
Originally, the input price index used to develop the IPF PPS was
the Excluded Hospital with Capital market basket. This market basket
was based on 1997 Medicare cost reports for Medicare-participating
inpatient rehabilitation facilities (IRFs), IPFs, long-term care
hospitals (LTCHs), cancer hospitals, and children's hospitals. Although
``market basket'' technically describes the mix of goods and services
used in providing health care at a given point in time, this term is
also commonly used to denote the input price index (that is, cost
category weights and price proxies) derived from that market basket.
Accordingly, the term ``market basket,'' as used in this document,
refers to an input price index.
Since the IPF PPS inception, the market basket used to update IPF
PPS payments has been rebased and revised to reflect more recent data
on IPF cost structures. We last rebased and revised the IPF market
basket in the FY 2024 IPF PPS rule, where we adopted a 2021-based IPF
market basket, using Medicare cost report data for both Medicare
participating freestanding psychiatric hospitals and psychiatric units.
We refer readers to the FY 2024 IPF PPS final rule for a detailed
discussion of the 2021-based IPF PPS market basket and its development
(88 FR 51057 through 51081). References to the historical market
baskets used to update IPF PPS payments are listed in the FY 2016 IPF
PPS final rule (80 FR 46656).
2. Proposed FY 2025 IPF Market Basket Update
For FY 2025 (beginning October 1, 2024 and ending September 30,
2025), we are proposing to update the IPF PPS payments by a market
basket increase factor with a productivity adjustment as required by
section 1886(s)(2)(A)(i) of the Act. Consistent with historical
practice, we are proposing to estimate the market basket update for the
IPF PPS based on the most recent forecast available at the time of
rulemaking from IHS Global Inc. (IGI). IGI is a nationally recognized
economic and financial forecasting firm with which CMS contracts to
forecast the components of the market baskets and productivity
adjustment. For the proposed rule, based on IGI's fourth quarter 2023
forecast with historical data through the third quarter of 2023, the
2021-based IPF market basket increase factor for FY 2025 is 3.1
percent.
Section 1886(s)(2)(A)(i) of the Act 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 (MFP) (as projected by the Secretary for the 10-year
period ending with the applicable FY, year, cost reporting period, or
other annual period) (the ``productivity adjustment''). The United
States Department of Labor's Bureau of Labor Statistics (BLS) publishes
the official measures of productivity for the United States economy. We
note that previously the productivity measure referenced in section
1886(b)(3)(B)(xi)(II) of the Act was published by BLS as private
nonfarm business MFP. Beginning with the November 18, 2021 release of
productivity data, BLS replaced the
[[Page 23150]]
term ``multifactor productivity'' with ``total factor productivity''
(TFP). BLS noted that this is a change in terminology only and will not
affect the data or methodology. As a result of the BLS name change, the
productivity measure referenced in section 1886(b)(3)(B)(xi)(II) of the
Act is now published by BLS as private nonfarm business TFP. However,
as mentioned previously, the data and methods are unchanged. We refer
readers to www.bls.gov for the BLS historical published TFP data. A
complete description of IGI's TFP projection methodology is available
on the CMS website at https://www.cms.gov/data-research/statistics-trends-and-reports/medicare-program-rates-statistics/market-basket-research-and-information. In addition, in the FY 2022 IPF final rule
(86 FR 42611), we noted that effective with FY 2022 and forward, CMS
changed the name of this adjustment to refer to it as the productivity
adjustment rather than the MFP adjustment.
Section 1886(s)(2)(A)(i) of the Act requires the application of the
productivity adjustment described in section 1886(b)(3)(B)(xi)(II) of
the Act to the IPF PPS for the RY beginning in 2012 (a RY that
coincides with a FY) and each subsequent RY. For this proposed rule,
based on IGI's fourth quarter 2023 forecast, the proposed productivity
adjustment for FY 2025 (the 10-year moving average of TFP for the
period ending FY 2025) is projected to be 0.4 percent. Accordingly, we
are proposing to reduce the 3.1 percent IPF market basket increase by
this 0.4 percentage point productivity adjustment, as mandated by the
Act. This results in a proposed FY 2025 IPF PPS payment rate update of
2.7 percent (3.1-0.4 = 2.7). We are also proposing that if more recent
data become available, we would use such data, if appropriate, to
determine the FY 2025 IPF market basket increase and productivity
adjustment for the final rule.
We solicit comment on the proposed IPF market basket increase and
productivity adjustment for FY 2025.
3. Proposed FY 2025 IPF Labor-Related Share
Due to variations in geographic wage levels and other labor-related
costs, we believe that payment rates under the IPF PPS should continue
to be adjusted by a geographic wage index, which would apply to the
labor-related portion of the Federal per diem base rate (hereafter
referred to as the labor-related share). The labor-related share is
determined by identifying the national average proportion of total
costs that are related to, influenced by, or vary with the local labor
market. We are proposing to continue to classify a cost category as
labor-related if the costs are labor-intensive and vary with the local
labor market.
Based on our definition of the labor-related share and the cost
categories in the 2021-based IPF market basket, we are proposing to
continue 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 relative
importance from the 2021-based IPF market basket. For more details
regarding the methodology for determining specific cost categories for
inclusion in the labor-related share based on the 2021-based IPF market
basket, we refer readers to the FY 2024 IPF PPS final rule (88 FR 51078
through 51081).
The relative importance reflects the different rates of price
change for these cost categories between the base year (FY 2021) and FY
2025. Based on IGI's fourth quarter 2023 forecast of the 2021-based IPF
market basket, the sum of the FY 2025 relative importance moving
average 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 is 75.7 percent. We are proposing, consistent with
prior rulemaking, that the portion of Capital-Related costs that are
influenced by the local labor market is 46 percent. Since the relative
importance for Capital-Related costs is 6.8 percent of the 2021-based
IPF market basket for FY 2025, we are proposing to take 46 percent of
6.8 percent to determine a labor-related share of Capital-Related costs
for FY 2025 of 3.1 percent. Therefore, we are proposing a total labor-
related share for FY 2025 of 78.8 percent (the sum of 75.7 percent for
the labor-related share of operating costs and 3.1 percent for the
labor-related share of Capital-Related costs). We are also proposing
that if more recent data become available, we would use such data, if
appropriate, to determine the FY 2025 labor-related share for the final
rule. For more information on the labor-related share and its
calculation, we refer readers to the FY 2024 IPF PPS final rule (88 FR
51078 through 51081).
Table 1 shows the proposed FY 2025 labor-related share and the
final FY 2024 labor-related share using the 2021- based IPF market
basket relative importance.
[[Page 23151]]
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We solicit comment on the proposed labor-related share for FY 2025.
B. Proposed Revisions to the IPF PPS Rates for FY Beginning October 1,
2024
The IPF PPS is based on a standardized Federal per diem base rate
calculated from the IPF average per diem costs and adjusted for budget
neutrality in the implementation year. The Federal per diem base rate
is used as the standard payment per day under the IPF PPS and is
adjusted by the patient-level and facility-level adjustments that are
applicable to the IPF stay. A detailed explanation of how we calculated
the average per diem cost appears in the RY 2005 IPF PPS final rule (69
FR 66926).
1. Determining the Standardized Budget Neutral Federal per Diem Base
Rate
Section 124(a)(1) of the BBRA required that we implement the IPF
PPS in a budget neutral manner. In other words, the amount of total
payments under the IPF PPS, including any payment adjustments, must be
projected to be equal to the amount of total payments that would have
been made if the IPF PPS were not implemented. Therefore, we calculated
the budget neutrality factor by setting the total estimated IPF PPS
payments to be equal to the total estimated payments that would have
been made under the Tax Equity and Fiscal Responsibility Act of 1982
(TEFRA) (Pub. L. 97-248) methodology had the IPF PPS not been
implemented. A step-by-step description of the methodology used to
estimate payments under the TEFRA payment system appears in the RY 2005
IPF PPS final rule (69 FR 66926).
Under the IPF PPS methodology, we calculated the final Federal per
diem base rate to be budget neutral during the IPF PPS implementation
period (that is, the 18-month period from January 1, 2005 through June
30, 2006) using a July 1 update cycle. We updated the average cost per
day to the midpoint of the IPF PPS implementation period (October 1,
2005), and this amount was used in the payment model to establish the
budget neutrality adjustment.
Next, we standardized the IPF PPS Federal per diem base rate to
account for the overall positive effects of the IPF PPS payment
adjustment factors by dividing total estimated payments under the TEFRA
payment system by estimated payments under the IPF PPS. The information
concerning this standardization can be found in the RY 2005 IPF PPS
final rule (69 FR 66932) and the RY 2006 IPF PPS final rule (71 FR
27045). We then reduced the standardized Federal per diem base rate to
account for the outlier policy, the stop loss provision, and
anticipated behavioral changes. A complete discussion of how we
calculated each component of the budget neutrality adjustment appears
in the RY 2005 IPF PPS final rule (69 FR 66932 through 66933) and in
the RY 2007 IPF PPS final rule (71 FR 27044 through 27046). The final
standardized budget neutral Federal per diem base rate established for
cost reporting periods beginning on or after January 1, 2005 was
calculated to be $575.95.
The Federal per diem base rate has been updated in accordance with
applicable statutory requirements and 42 CFR 412.428 through
publication of annual notices or proposed and final rules. A detailed
discussion on the standardized budget neutral Federal per diem base
rate and the ECT payment per treatment appears in the FY 2014 IPF PPS
update notice (78 FR 46738 through 46740). These documents are
available on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/.
As discussed in section III.B.2 of this proposed rule, we are
proposing to revise the patient-level adjustment factors and increase
the ECT payment amount for FY 2025. Section 1866(s)(5)(D)(iii) of the
Act, as added by section 4125(a) of the CAA, 2023, requires that
revisions to the IPF PPS adjustment factors must be made budget-
neutrally. Therefore, as discussed in section III.F of this proposed
rule, we are proposing to apply a standardization factor to the FY 2025
base rate that takes these refinements into account to keep total IPF
PPS payments budget neutral.
2. Proposed Increase in the Electroconvulsive Therapy (ECT) Payment per
Treatment
a. Background
In the RY 2005 IPF PPS final rule (69 FR 66951), we analyzed the
costs of IPF stays that included ECT treatment using the FY 2002 MedPAR
data. based on comments we received on the RY 2005
[[Page 23152]]
IPF PPS proposed rule. Consistent with the comments we received about
ECT, our analysis and review indicated that cases with ECT treatment
are substantially more costly than cases without ECT treatment. Based
on this analysis, in that final rule we finalized an additional payment
for each ECT treatment furnished during the IPF stay. This ECT payment
per treatment is made in addition to the per diem and outlier payments
under the IPF PPS. To receive the payment per ECT treatment, IPFs must
indicate on their claims the revenue code and procedure code for ECT
(Rev Code 901; procedure code 90870) and the number of units of ECT,
that is, the number of ECT treatments the patient received during the
IPF stay.
To establish the ECT per treatment payment, we used the pre-scaled
and pre-adjusted median cost for procedure code 90870 developed for the
Hospital Outpatient Prospective Payment System (OPPS), based on
hospital claims data. We explained in the RY 2005 IPF PPS final rule
that we used OPPS data because after a careful review and analysis of
IPF claims, we were unable to separate out the cost of a single ECT
treatment (69 FR 66922). We used the unadjusted hospital claims data
under the OPPS because we did not want the ECT payment under the IPF
PPS to be affected by factors that are relevant to OPPS, but not
specifically applicable to IPFs. The median cost was then standardized
and adjusted for budget neutrality. We also adjusted the ECT rate for
wage differences in the same manner that we adjust the per diem rate.
Since the ECT payment rate was established in the RY 2005 IPF PPS
rule, it has been updated annually by application of each year's market
basket, productivity adjustment, and wage index budget neutrality
factor to the previous year's ECT payment rate (referred to as our
``standard methodology'' in this section). While the ECT payment rate
has been updated each year by these factors, we have not recalculated
the ECT payment per treatment based on more recent cost data since the
establishment of the IPF PPS.
b. Proposed Increase to the Electroconvulsive Therapy Payment per
Treatment
For this FY 2025 IPF PPS proposed rule, we analyzed data in both
the IPF PPS and the OPPS. In the IPF PPS setting, our analysis of
recent IPF PPS data indicates that IPF costs have increased for stays
that include ECT treatments. As discussed in the next paragraph, our
analysis of these costs leads us to consider whether the current
payment per treatment for ECT is aligned with the additional costs
associated with stays that include ECT treatments. We began by
analyzing IPF stays with ECT treatment using the CY 2022 Medicare
Provider and Analysis Review (MedPAR) data. IPF stays with ECT
treatment comprised about 1.7 percent of all stays, which is a decrease
from the FY 2002 MedPAR data discussed in the RY 2005 IPF PPS final
rule, where stays with ECT treatment were 6.0 percent of all IPF stays.
A total of 288 IPF facilities had stays with ECT treatment in 2022,
with an average 6.7 units of ECT per stay. We compared the total cost
for stays with and without ECT treatment, and found that IPF stays with
ECT treatment were approximately three times more costly than IPF stays
without ECT treatment ($44,687.50 per stay vs. $15,432.30 per stay).
Most of the variance in cost was due to differences in the IPF length
of stay (LOS) (28.00 days for stays with ECT treatment vs. 13.43 days
for stays without ECT treatment). We note that the IPF PPS makes
additional per diem payments for longer lengths of stay, which makes
the total payment larger for a longer stay. However, we also observed
that there are differences in the per-day cost for stays with and
without ECT. We calculated the average cost per day for stays with and
without ECT treatment and found that stays with ECT treatment have an
average cost per day of $1,595.76, while stays without ECT treatment
have an average cost per day of $1,149.51.
Furthermore, as we discuss in section III.C.3.d.(2) of this
proposed rule, our latest regression analysis includes a control
variable to account for the presence of ECT during an IPF stay. That
control variable indicates that, holding all other patient-level and
facility-level factors constant, there is a statistically significant
increase in cost per day for IPF stays that include ECT, further
demonstrating that resource use is higher for IPF stays with ECT than
those without ECT. As we previously noted in the RY 2005 IPF PPS final
rule (69 FR 66922), IPF claims and cost data are not sufficiently
granular to identify the per-treatment cost of ECT. Therefore, we
examined the difference in ancillary costs for IPF stays with and
without ECT treatment. In the CY 2022 MedPAR data, the ancillary costs
per IPF stay with ECT treatment were $7,116.85 higher than ancillary
costs per IPF stay without ECT treatment. The ancillary costs were
calculated as follows: for each ancillary department (for example,
drugs or labs), the charges were multiplied by the department-level
CCR, and those department-level costs were summed across departments
for each stay. The average ancillary costs per stay were calculated
accordingly for stays with and without ECT treatment, revealing that
average ancillary costs per day are three times higher for stays with
ECT treatment: $99.36 for stays without ECT treatment versus $301.77
for stays with ECT treatment. Accounting for differences in length of
stay between stays with and without ECT, the average additional
ancillary cost per ECT unit was approximately $849.72.
Application of our standard methodology for updating the ECT
payment would result in an FY 2025 payment of $377.54 per ECT treatment
(based on the FY 2024 ECT payment amount of $385.58, increased by the
market basket update of 2.7 percent and reduced by the FY 2025 wage
index budget neutrality factor of 0.9998 and a refinement
standardization factor of 0.9536, which is the standardization factor
that would account for all other proposed refinements without
increasing the ECT per treatment). As we noted above, this ECT payment
would be added to the per diem and any applicable outlier payments for
the entire stay. CMS considered this rate in proposing to adjust the
ECT per treatment rate. However, the analysis of ancillary costs for
IPF stays with ECT treatment suggested that a further increase to the
current ECT payment amount per treatment could better align IPF PPS
payments with the increased costs of furnishing ECT. The ancillary cost
data show that costs for furnishing ECT have risen by a factor greater
than the standard methodology for updating the rate would adjust for.
It continues to be the case that, as we discussed in the RY 2005
IPF PPS final rule, current IPF cost and claims data are not
sufficiently granular to identify the per-treatment cost of ECT. We
believe that using the costs in the OPPS setting are the most accurate
for purposes of updating the ECT per treatment rate because we believe
this treatment requires comparable resources when performed in
outpatient and inpatient settings. Thus, we analyzed the most recent
OPPS cost information to consider changes to the ECT payment per
treatment for FY 2025.
The original methodology for determining the ECT payment per
treatment was based on the median cost for procedure code 90870
developed for the OPPS, as discussed in the RY 2005 IPF PPS final rule
(69 FR 66951). Since that time, the OPPS has adopted certain changes to
its methodology for calculating costs. In the CY 2013 OPPS/ASC final
rule with comment period (77
[[Page 23153]]
FR 68259 through 68270), CMS finalized a methodology for developing the
relative payment weights for Ambulatory Payment Classifications using
geometric mean costs instead of median costs. We explained that
geometric means better capture the range of costs associated with
providing services, including those cases where very efficient
hospitals have provided services at much lower costs. While medians and
geometric means both capture the impact of uniform changes, that is,
those changes that influence all providers, only geometric means
capture cost changes that are introduced slowly into the system on a
case-by-case or hospital-by-hospital basis, allowing us to detect
changes in the cost of services earlier.
We believe the rationale for using geometric mean cost in the OPPS
setting as the underpinning methodology for establishing payments
applies equally to the costs of providing ECT on a per treatment basis
under the IPF PPS. Therefore, in considering changes for the IPF PPS
ECT payment per treatment for FY 2025, we compared the costs observed
in the IPF setting to the geometric mean cost for an ECT treatment
posted as part of the CY 2024 OPPS/ASC update, which is based on CY
2022 outpatient hospital claims. Although we are proposing to increase
the ECT payment with reference to the CY 2024 OPPS ECT geometric mean
cost for FY 2025, we are not proposing to adopt the OPPS rate (which is
distinct from the geometric mean cost) for the ECT payment per
treatment for FY 2025 because the final OPPS rates include policy
decisions and payment rate updates that are specific to the OPPS. We
intend to continue to monitor the costs associated with ECT treatment
and may propose adjustments in the future as needed.
The pre-scaled and pre-adjusted CY 2024 OPPS geometric mean cost
for ECT is $675.93. Comparatively, the FY 2024 IPF ECT payment rate was
$385.58 (88 FR 51054). As discussed in the prior paragraphs, our
analysis of updated ancillary cost data indicates that the IPF PPS ECT
payment rate per treatment, when updated according to the standard
methodology alone, has not kept pace with the cost of furnishing the
treatment in the IPF setting. As we stated previously, we believe this
treatment requires comparable resources when performed in outpatient
and inpatient settings. Therefore, we are proposing to use the pre-
scaled and pre-adjusted CY 2024 OPPS geometric mean cost of $675.93 as
the basis for the IPF PPS ECT payment per treatment in FY 2025, as
discussed below. We are proposing to update $675.93 by the FY 2025 IPF
PPS payment rate update of 2.7 percent (3.1 percent IPF market basket
increase, reduced by the 0.4 percentage point productivity adjustment),
and the wage index budget neutrality factor of 0.9998 for FY 2025, in
alignment with our current standard methodology.
To account for budget neutrality, as discussed in section III.F of
this proposed rule, we are proposing to apply a refinement
standardization factor to the FY 2025 IPF PPS Federal per diem base
rate and to the ECT payment amount per treatment to account for this
proposed change to the ECT payment amount per treatment and all
proposed changes to the patient-level adjustment factors and to the ED
adjustment factor for FY 2025. We note that this proposed increase to
the ECT per treatment amount would be associated with a minor decrease
to the IPF Federal per diem base rate as a result of the refinement
standardization factor (0.9514 instead of 0.9536). We estimate that
this change would increase payments for IPFs that provide ECT, and
would decrease payments for IPFs that do not provide ECT. However, the
decrease in payments associated with this change would be no more than
approximately 0.2 percent, which would be offset by various other
proposed changes such as the proposed wage index changes, proposed
revisions to the IPF PPS patient-level adjustments, and the proposed
market basket increase for FY 2025.
We note that we have monitored the provision of ECT through
analysis of claims data since the beginning of the IPF PPS, and have
not observed any indicators that payment is inappropriately
incentivizing the provision of ECT to IPF patients. We intend to
continue monitoring the provision of ECT through further analysis of
IPF PPS claims data.
A detailed discussion of the distributional impacts of this
proposed change is found in section VIII.C of this proposed rule. We
welcome comments regarding our analysis, including any comments that
could inform our understanding of where ECT costs are allocated in cost
reports in order to potentially inform improved collection of data on
ECT treatment costs in the IPF setting. We also welcome comments on
whether it may be appropriate to collect additional ECT-specific costs
on the hospital cost report. Lastly, we are proposing that if more
recent data become available, we would use such data, if appropriate,
to determine the FY 2025 Federal per diem base rate and ECT payment per
treatment for the FY 2025 IPF PPS final rule.
IPFs must include a valid procedure code for ECT services provided
to IPF beneficiaries to bill for ECT services, as described in our
Medicare Claims Processing Manual, Chapter 3, Section 190.7.3
(available at https://www.cms.gov/Regulations-and-Guidance/Guidance/Manuals/Downloads/clm104c03.pdf). There were no changes to the ECT
procedure codes used on IPF claims in the final update to the ICD-10-
PCS code set for FY 2024. Addendum B to this proposed rule shows the
ECT procedure codes for FY 2025 and is available on the CMS website at
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/tools.html.
3. Proposed Update of the Federal per Diem Base Rate and
Electroconvulsive Therapy Payment per Treatment
The current (FY 2024) Federal per diem base rate is $895.63 and the
ECT payment per treatment is $385.58. For the proposed FY 2025 Federal
per diem base rate, we applied the payment rate update of 2.7
percent,--that is, the proposed 2021-based IPF market basket increase
for FY 2025 of 3.1 percent reduced by the proposed productivity
adjustment of 0.4 percentage point--the proposed wage index budget
neutrality factor of 0.9998 (as discussed in section III.D.1 of this
proposed rule), and a proposed refinement standardization factor of
0.9514 (as discussed in section III.F of this proposed rule) to the FY
2024 Federal per diem base rate of $895.63, yielding a proposed Federal
per diem base rate of $874.93 for FY 2025. As discussed in section
III.B.2 of this proposed rule, we are proposing to increase the ECT
payment per treatment for FY 2025 in addition to our routine updates to
the rate. We applied the proposed 2.7 percent payment rate update, the
proposed 0.9998 wage index budget neutrality factor, and the proposed
0.9514 refinement standardization factor to the proposed payment per
treatment based on the CY 2024 OPPS geometric mean cost of $675.93,
yielding a proposed ECT payment per treatment of $660.30 for FY 2025.
Section 1886(s)(4)(A)(i) of the Act requires that for RY 2014 and
each subsequent RY, in the case of an IPF that fails to report required
quality data with respect to such RY, the Secretary will reduce any
annual update to a standard Federal rate for discharges during the RY
by 2.0 percentage points. Therefore, we are applying a 2.0 percentage
point reduction to the annual update to the Federal per diem
[[Page 23154]]
base rate and the proposed ECT payment per treatment as follows:
For IPFs that fail to report required data under the IPFQR
Program, we would apply a 0.7 percent payment rate update--that is, the
proposed IPF market basket increase for FY 2025 of 3.1 percent reduced
by the proposed productivity adjustment of 0.4 percentage point for an
update of 2.7 percent, and further reduced by 2.0 percentage points in
accordance with section 1886(s)(4)(A)(i) of the Act. We would also
apply the proposed refinement standardization factor of 0.9514 and the
proposed wage index budget neutrality factor of 0.9998 to the FY 2024
Federal per diem base rate of $895.63, yielding a proposed Federal per
diem base rate of $857.89 for FY 2025.
For IPFs that fail to report required data under the IPFQR
Program, we would apply the proposed 0.7 percent annual payment rate
update, the proposed 0.9514 refinement standardization factor, and the
proposed 0.9998 wage index budget neutrality factor to the proposed
payment per treatment based on the CY 2024 OPPS geometric mean cost of
$675.93, yielding a proposed ECT payment per treatment of $647.45 for
FY 2025.
We are proposing that if more recent data become available, we
would use such data, if appropriate, to determine the FY 2025 Federal
per diem base rate and ECT payment per treatment for the FY 2025 IPF
final rule.
C. Proposed Updates and Revisions to the IPF PPS Patient-Level
Adjustment Factors
1. Overview of the IPF PPS Adjustment Factors and Proposed Revisions
The current (FY 2024) IPF PPS payment adjustment factors were
derived from a regression analysis of 100 percent of the FY 2002
Medicare Provider and Analysis Review (MedPAR) data file, which
contained 483,038 cases. For a more detailed description of the data
file used for the regression analysis, we refer readers to the RY 2005
IPF PPS final rule (69 FR 66935 through 66936).
For FY 2025, we are proposing to implement revisions to the
methodology for determining payment rates under the IPF PPS. As we
noted earlier in this FY 2025 IPF PPS proposed rule, section
1886(s)(5)(D) of the Act, as added by section 4125(a) of the CAA, 2023
requires that the Secretary implement revisions to the methodology for
determining the payment rates under the IPF PPS for psychiatric
hospitals and psychiatric units, effective for RY 2025 (FY 2025). The
revisions may be based on a review of the data and information
collected under section 1886(s)(5)(A) of the Act. Accordingly, we are
proposing to revise the patient-level IPF PPS payment adjustment
factors as discussed in section III.C.4. of this proposed rule,
effective for FY 2025. We have developed proposed adjustment factors
based on a regression analysis of IPF cost and claims data, which is
discussed in greater detail in the following sections of this proposed
rule. The primary sources of this analysis are CY 2019 through 2021
MedPAR files and Medicare cost report data (CMS Form 2552-10, OMB No.
0938-0050) \1\ from the FY 2019 through 2021 Hospital Cost Report
Information System (HCRIS). For each year (2019 through 2021), if a
provider did not have a Medicare cost report for that year, we used the
provider's most recent available Medicare cost report prior to the year
for which a Medicare cost report was missing, going back to as early as
2018. Section III.C.3 of this proposed rule discusses the development
of the proposed revised case-mix adjustment regression.
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\1\ https://www.reginfo.gov/public/do/PRAViewICR?ref_nbr=202206-0938-017.
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2. History of IPF PPS Cost and Claims Analyses
In the FY 2023 IPF PPS proposed rule (87 FR 19428 through 19429),
we briefly discussed past analyses and areas of interest for future
refinement, about which we previously solicited comments. CMS also
released a technical report posted to the CMS website \2\ accompanying
the rule, summarizing these analyses. In that same proposed rule, we
described the results of the agency's latest analysis of the IPF PPS
and solicited comments on certain topics from the report. We summarized
the considerations and findings related to our analyses of the IPF PPS
adjustment factors in the FY 2023 IPF PPS final rule (46864 through
46865).
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\2\ https://www.cms.gov/files/document/technical-report-medicare-program-inpatient-psychiatric-facilities-prospective-payment-system.pdf.
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In the FY 2024 IPF PPS proposed rule (88 FR 21269 through 21272),
we requested information from the public to inform revisions to the IPF
PPS required by the CAA, 2023. Specifically, we sought information
about which data and information would be most appropriate and useful
for the purposes of refining IPF PPS payments. We requested information
related to the specific types of data and information mentioned in the
CAA, 2023. We also solicited comments on the reporting of ancillary
charges, such as labs and drugs, on IPF claims. Lastly, we presented
and solicited comments on the latest results of our analysis of social
drivers of health (SDOH).
In response to the requests for information, commenters offered a
number of suggestions for further analysis, including recommendations
to consider adjusting payment for patients with sleep apnea, violent
behavior, and patients that transfer from an acute care unit. We
discuss the analysis conducted and our findings, as related to patient-
level adjustment factors, in section III.C.3 of this proposed rule.
The primary goal in refining the IPF PPS payment adjustment factors
is to pay each IPF an appropriate amount for the efficient delivery of
care to Medicare beneficiaries. The system must be able to account
adequately for each IPF's case-mix to allow for both fair distribution
of Medicare payments and access to adequate care for those
beneficiaries who require more costly care. As required by section
1886(s)(5)(D)(iii) of the Act, as added by section 4125(a) of the CAA,
2023, proposed revisions to the IPF PPS adjustment factors must be
budget neutral. As discussed in section III.F of this proposed rule, we
are applying a refinement standardization factor to the proposed IPF
PPS payment rates to maintain budget neutrality for FY 2025.
3. Development of the Proposed Revised Case-Mix Adjustment Regression
To ensure that the IPF PPS continues to account adequately for each
IPF's case-mix, we performed an extensive regression analysis of the
relationship between the per diem costs and both patient and facility
characteristics to identify those characteristics associated with
statistically significant cost differences. We discuss the results of
this regression analysis in section III.C.3.e. of this proposed rule.
We further discuss proposed revisions to the IPF PPS patient-level
adjustment factors based on this regression analysis in section III.C.4
of this proposed rule.
As discussed in greater detail in section III.C.3.c. of this
proposed rule, we computed a per diem cost for each Medicare inpatient
psychiatric stay, including routine operating, ancillary, and capital
components using information from the CY 2019 through CY 2021 MedPAR
files and data from the 2019 through 2021 Medicare cost reports,
backfilling with Medicare cost reports from the most recent prior year
when necessary.
We began with a 100 percent sample of the CY 2019 through CY 2021
MedPAR data files, which contain a
[[Page 23155]]
total of 1,111,459 stays from 1,684 IPFs. As discussed in section
III.C.3.b. of this proposed rule, we applied several data restrictions
and exclusions to obtain the set of data used for our regression
analysis. The MedPAR data files used for this regression analysis
contain a total of 806,611 stays from 1,643 IPFs, which reflect the
removal of 41 providers and 304,848 stays with missing or erroneous
data. To include as many IPFs as possible in the regression, we used
the cost report information for each provider corresponding to the year
of claims, when available, and substituted the most recent prior
available cost report information for routine cost and ancillary cost
to charge ratios if the corresponding year's data was not available.
a. Data Sources
For the regression analysis, we chose to use a combined set of CY
2019 through 2021 MedPAR data. Our analysis showed that using a
combined set of data from multiple years yields the most stable and
consistent result. When we looked at the results for each year
individually, we found that some DRGs and comorbidity categories were
not statistically significant due in part to small sample size. In
addition, during FY 2020, the U.S. healthcare system undertook an
unprecedented response to the Public Health Emergency (PHE) declared by
the Secretary of the Department of Health and Human Services on January
31, 2020 in response to the outbreak of respiratory disease caused by a
novel (new) coronavirus that has been named ``SARS CoV 2'' and the
disease it causes, which has been named ``coronavirus disease 2019''
(abbreviated ``COVID-19''). We believe the aggregated three-year
regression serves to smooth the impact of changes in utilization driven
by the COVID-19 PHE, as well as significant changes in staffing and
labor costs that commenters noted in response to the FY 2023 and FY
2024 IPF PPS proposed rules. As discussed earlier in this proposed
rule, we used 2019 through 2021 Medicare cost report data to retain as
many records as possible for analysis.
We also used several other data sources to identify the IPF
population for analysis and to construct variables in the regression
model:
Provider of Services (POS) File: The POS file contains
facility characteristics including name, address, and types of services
provided.
Provider Specific Data for Public Use Files for the IPF
PPS: The Provider Specific File (PSF) contains data used to calculate
COLA factors and identify the Core-Based Statistical Area (CBSA). CBSA
is used to match providers with corresponding wage index data, which is
used to adjust the calculation of the Federal per diem base rate to
account for geographic differences in costs.
Common Working File (CWF) Inpatient Claims Data: The CWF
contains data regarding ECT treatments provided during an IPF stay.
Among the 1,643 providers included in the regression analysis
sample, the majority had their most recent Medicare cost report
information corresponding to the year of the MedPAR data file.
Specifically, for the CY 2019 MedPAR data file, 99.5 percent (1,551
providers) used FY 2019 Medicare cost reports, and 0.5 percent (8
providers) used FY 2018 Medicare cost reports. For CY 2020, 99.7
percent (1,523 providers) used FY 2020 Medicare cost reports, and 0.3
percent (5 providers) used FY 2019 Medicare cost reports. For CY 2021,
97.6 percent (1,435 providers) used FY 2021 Medicare cost reports, and
2.4 percent (35 providers) used FY 2020 Medicare cost reports. This
approach allowed us to use the most current and relevant cost report
data, ensuring the robustness and accuracy of our analysis.
b. Trims and Assumptions
To identify the IPF population for analysis, we matched MedPAR
records to facility-level information from Medicare cost reports, the
POS file, and the PSF. We included MedPAR stays that met the following
criteria:
Hospital CMS Certification Number (CCN) contains ``40,''
``41,'' ``42,'' ``43,'' or ``44'' in the third and fourth position or a
special unit code of ``S'' or ``M'' for psychiatric unit or psychiatric
unit in a critical access hospital.
Beneficiary primary payer code is equal to ``Z'' or blank,
indicating Medicare is the primary payer.
Group Health Organization (GHO) paid code is equal to zero
or blank, indicating that a GHO has not paid the facility for the stay.
National Claims History (NCH) claim type code is equal to
``60,'' an inpatient claim.
Number of utilization days was greater than zero.
To promote the accuracy and completeness of data included in the
regression model, we completed a series of trimming steps to remove
missing and outlier data. Before any trims or exclusions were applied,
there were 1,684 providers in the MedPAR data file. First, we matched
facilities from the MedPAR dataset to the most recent Medicare cost
report file available from CY 2018 to CY 2021, and excluded facilities
that did not have a Medicare cost report available from 2018 to 2021.
If facilities had more than one Medicare cost report in a given year,
we used the Medicare cost report representing the longest time span. We
identified 1 provider in CY 2019, 5 providers in CY 2020, and 4
providers in CY 2021 that had no available Medicare cost report
information. In total, we excluded data from 5 unique providers that
had no available Medicare cost report information from CY 2019 to CY
2021.
Next, we trimmed facilities with extraordinarily high or low costs
per day. We removed facilities with outlier routine per diem costs,
defined as those falling outside of the range of the mean logarithm of
routine costs per diem plus or minus 3.00 standard deviations. We also
removed stays with outlier total per diem costs, defined as those
falling outside the range of the mean per diem cost by facility type
(psychiatric hospitals and psychiatric units) plus or minus 3.00
standard deviations. The average and standard deviations of the total
per diem cost (routine and ancillary costs) were computed separately
for stays in psychiatric hospitals and psychiatric units because we did
not want to systematically exclude a larger proportion of cases from
one type of facility. In applying these trims across all three data
years used in our regression model, there were 104 providers with
routine per diem costs outside 3.00 standard deviations from the mean,
and 47 providers with total per diem costs outside 3.00 standard
deviations from the mean. Specifically, this includes 24 providers in
CY 2019, 41 providers in CY 2020, and 39 providers in CY 2021 excluded
for outlier routine per diem costs. We identified 25 providers in CY
2019, 1 provider in CY 2020, and 21 providers in CY 2021 that we
excluded for outlier total per diem costs. In total, we excluded data
from 23 unique providers with outlier routine per diem costs and 8
unique providers with outlier total per diem costs.
We also removed stays at providers without a POS file or PSF. There
were 5 providers without a POS file or PSF during the period CY 2019 to
CY 2021; therefore, we are excluding data from these 5 providers. Only
1 unique provider was entirely excluded with no POS file or PSF from CY
2019 to CY 2021. Additionally, 1 provider was excluded because no stays
had one of the recognized IPF PPS DRGs assigned.
In summary, the application of these data preparation steps
resulted in excluding 5 providers because they did not have a cost
report available from 2018 to 2021, 23 providers with routine per diem
costs outside 3.00 standard
[[Page 23156]]
deviations from the mean, and 8 providers with total per diem costs
outside 3.00 standard deviations from the mean. We also excluded 1
provider without a POS file or PSF, 1 provider with no stays with IPF
PPS DRGs, and 3 providers based on IPF stays restrictions. In total,
the exclusion of these 41 providers resulted in the removal of 304,848
stays from our original total of 1,111,459 stays.
We considered trimming stays from facilities where 95 percent or
more of stays had no ancillary charges because we assumed that the cost
data from these facilities were inaccurate or incomplete. This is the
trimming methodology that we applied to the analysis described in the
technical report released along with the FY 2023 IPF PPS proposed rule.
As previously discussed, the IPF PPS regression model uses the sum of
routine and ancillary costs as the dependent variable, and we assumed
that data from facilities without ancillary charge data would be
inadequate to capture variation in costs. When we examined the claims
from 2018, which we used for prior analysis, this trimming step
resulted in removing almost one-quarter of total stays from the
unrestricted 2018 MedPAR dataset (82,491 out of 364,080 total stays).
This trimming step also resulted in disproportionate exclusion of
certain types of facilities, particularly freestanding psychiatric
hospitals that were for-profit or government-operated, as well as all-
inclusive rate providers. Approximately 55 percent of stays from
freestanding facilities would be removed, compared to just 0.3 percent
of stays in psychiatric units. In the analysis described in the FY 2023
IPF PPS proposed rule (87 FR 19429), we attempted to address this
disproportionate removal of stays by facility type by applying weights
by facility type and ownership in the regression model to account for
excluded providers and to avoid biasing the sample towards stays from
providers in psychiatric units.
In response to the analysis described in the FY 2023 IPF PPS
proposed rule (87 FR 19429), commenters raised concerns about the large
number of stays excluded from the regression analysis, and questioned
whether the ancillary charge data were truly missing, as all-inclusive
rate providers are not required to report separate ancillary charges.
We agree that this trimming step reduces the representativeness of the
IPF population used in the regression model and may increase the
potential for bias of the regression coefficients used for payment
adjustments. Furthermore, as discussed in section III.E.4. of this
proposed rule, we are clarifying cost reporting requirements and
implementing operational changes that we believe will increase the
accuracy of the cost information reported in the future. Specifically,
CMS will issue instructions to the MACs and put in place edits for cost
reporting periods beginning on or after October 1, 2024, ensuring that
only government-owned or tribally owned IPF hospitals will be permitted
to file an all-inclusive cost report. All other IPF hospitals would be
required to have a charge structure and to report ancillary costs and
charges on their cost reports. We expect that this proposed change
would support increased accuracy of future payment refinements to the
IPF PPS.
When we examined the claims from CY 2019 to CY 2021, this trimming
step would have resulted in a loss of a significant number of providers
(324 providers in CY 2019, 330 providers in CY 2020, and 336 providers
in CY 2021). Due to the concerns that commenters previously raised
(which we summarized in the FY 2024 IPF PPS final rule (88 FR 51097
through 51098)), and to include as many claims as possible in the
regression analysis, we have not trimmed stays from facilities with
zero or minimal ancillary charges. As a result, we observed a
significant reduction in data loss when comparing our latest regression
model with the model described in the FY 2023 IPF PPS proposed rule. By
including, rather than trimming, facilities with low or no ancillary
charge data, we prevented the loss of 288 providers across the three
years, allowing for a more inclusive analysis. These providers
accounted for approximately 194,673 stays included in our data set.
We present our regression results in section III.C.3.e. of this
proposed rule without the application of any trimming or subsequent
weighting to account for the removal of stays from facilities with zero
or minimal ancillary charges.
c. Calculation of the Dependent Variable
The IPF PPS regression model uses the natural logarithm of per diem
total cost as the dependent variable. We computed a per diem cost for
each Medicare inpatient psychiatric stay, including routine operating,
ancillary, and capital components, using information from the combined
CY 2019 through 2021 MedPAR file and data from the 2018 through 2021
Medicare cost reports. For each MedPAR CY, we examined the
corresponding Medicare cost report, and if a provider's cost-to-charge
ratio was missing from the matching year's cost report, we looked at
the provider's cost report from the prior year to obtain the most
recent cost-to-charge value for the provider. We applied a prior-year
cost-to-charge ratio to 8 providers from the CY 2019 MedPAR claims, 5
providers from the CY 2020 MedPAR claims, and 35 providers from the CY
2021 MedPAR claims.
To calculate the total cost per day for each inpatient psychiatric
stay, routine costs were estimated by multiplying the routine cost per
day from the IPF's Medicare cost report (Worksheet D-1, Part II, column
1, line 38) by the number of Medicare covered days in the MedPAR stay
record. Ancillary costs were estimated by multiplying each departmental
cost-to-charge ratio (calculated by dividing the amount obtained from
Worksheet C, columns 5, by the sum of Worksheet C, columns 6 and 7) by
the corresponding ancillary charges in the MedPAR stay record. The
total cost per day was calculated by summing routine and ancillary
costs for the stay and dividing it by the number of Medicare covered
days for each day of the stay.
To address extreme cost-to-charge ratios, we winsorized the
distributions of the 17 ancillary cost centers from Worksheet C of the
cost report at the 2nd and 98th percentiles. That is, if the cost-to-
charge ratio was missing and there was a charge on the claim, the cost-
to-charge ratio was imputed to the calculated median value for each
respective cost center.
The total cost per day (also referred to as per diem cost) was
adjusted for differences in cost across geographic areas using the FY
2019 through 2021 IPF wage index and COLA corresponding to each MedPAR
data year. We adjusted the labor-related portion of the per diem cost
using the IPF wage index to account for geographic differences in labor
cost and adjusted the non-labor portion of the per diem cost by the
COLA adjustment factors for IPFs in Alaska and Hawaii. We used IPF PPS
labor-related share and non-labor-related share finalized for each
year, FY 2019 through FY 2021, to determine the amount of the per diem
cost that is adjusted by the wage index and the COLA, respectively. We
calculated the adjusted cost using the following formula:
Wage adjusted per diem cost = per diem cost/(wage index * labor-related
share + COLA * (1-labor-related share)).
d. Independent Variables
Independent variables in the regression model are patient-level and
facility-level characteristics that affect
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the dependent variable in the model, which is per diem cost. As
discussed in the following sections, the updated regression model for
this proposed rule includes adjustment-related variables and control
variables. Adjustment related variables are used for adjusting payment,
and as we discuss in section III.C.4 of this proposed rule, we are
proposing to revise the IPF PPS patient-level adjustment factors based
on the regression results for many of the adjustment-related variables
in the model. Control variables are used to account for variation in
the dependent variable that is associated with factors outside the
adjustment factors of the payment model.
(1) Adjustment-Related Variables
Patient-level adjustment-related variables included in the
regression model are variables for DRG assignment, comorbidity
categories, age, and length of stay. We note that facility-level
adjustment-related variables for rural status and teaching status are
also included in the model; however, we are not proposing revisions to
the rural or teaching adjustments for FY 2025. We discuss the latest
results of the regression analysis for facility-level adjustments in
greater detail in section IV.A. of this proposed rule.
(2) Control Variables
The regression model used to determine IPF PPS payment adjustments
in the RY 2005 IPF PPS final rule (69 FR 66922) included control
variables to account for facilities' occupancy rate, a control variable
to indicate if the patient received ECT, and a control variable for
IPFs that do not bill for ancillary charges. In the updated regression
model for this FY 2025 IPF PPS proposed rule, we have removed the
occupancy control variables and the control variable for IPFs that do
not bill for ancillary charges. In addition, we have retained the
control variable for patients receiving ECT and added control variables
for the data year. We also added a control variable for the presence of
ED charges on the claim. We discuss considerations related to these
control variables and others in the following paragraphs.
The 2004 regression model included two control variables for
occupancy rate. One was a continuous variable for the facility's
logarithmic-transformed occupancy rate. The other was a categorical
variable indicating a facility had an occupancy rate below 30 percent.
Both of these variables were found to be associated with statistically
significant increases in cost. In the RY 2005 IPF PPS final rule, we
adopted the structural approach and included these control variables in
the regression. We explained that it was appropriate to control for
variations in the occupancy rate in estimating the effects of the
payment variables on per diem cost to avoid compensating facilities for
inefficiency associated with underutilized fixed costs (69 FR 66934).
As we discussed in the FY 2023 IPF PPS proposed rule, our analysis
found that the occupancy control variables were associated with rural
status. We solicited comments on the potential removal of the occupancy
control variables from the model (87 FR 19429). In response, we
received several comments in support of removing the occupancy control
variables, due to the relationship between these control variables and
the rural adjustment (87 FR 46865). Commenters cited the importance of
rural IPFs as the primary points of care and access for many Medicare
beneficiaries who cannot travel to urban areas for mental health
services. We considered the potential negative impact to rural
facilities of retaining the occupancy control variables in the
regression model. We agree with the commenters who noted the importance
of maintaining stability in payments for rural IPFs; therefore, we did
not include any occupancy control variables in our regression model.
In addition, we considered including a control variable for IPFs
that do not bill for ancillary services. As we discussed in the RY 2005
IPF PPS final rule (69 FR 66936), we included variables in the
regression to control for psychiatric hospitals that do not bill
ancillary costs. However, at that time, the number of IPFs who did not
bill for ancillary costs was relatively small and consisted mostly of
government-operated facilities. As we discuss later in section III.E.4
of this proposed rule, an increasing number of IPFs have stopped
reporting ancillary charges on their claims, which means that ancillary
cost information is not available for stays at these IPFs.
We considered whether to include a control variable for facilities
that do not report ancillary charges. We considered that the inclusion
of a control variable would only account for differences in the level
of cost between IPFs with and without reported ancillary costs and
would not facilitate comparison of costs between all IPFs in our
sample. In addition, we found that facilities that did not report
ancillary charges also tended to have lower routine costs; that is, our
analysis showed that these facilities would have overall lower costs
per day, regardless of whether ancillary costs were considered in the
cost variable. We considered that the inclusion of a control variable
in the regression model would account for these differences in overall
cost, which would impact the size of payment-related adjustment factors
that are correlated with the prevalence of missing ancillary charge
data. For this reason, in developing a regression model for proposing
revisions to the IPF PPS, we did not include a control variable to
account for facilities that report zero or minimal ancillary charges.
As noted earlier, the original model also included a control
variable for the presence of ECT. This is because ECT is paid on a per-
treatment basis under the IPF PPS. As discussed in more detail in
section III.B.2. of this FY 2025 IPF PPS proposed rule, we continue to
observe that IPF stays with ECT have significantly higher costs per
day. We are proposing to continue paying for ECT on a per-treatment
basis; therefore, we included a control variable to account for the
additional costs associated with ECT, which would continue to be paid
for outside the regression model.
Similarly, we included a control variable for stays with emergency
department (ED)-related charges. The original model did not include an
ED control variable, because ED costs were excluded from the dependent
variable of IPF per diem costs. Our regression model for this FY 2025
IPF PPS proposed rule includes all costs associated with each IPF stay,
including ED costs. As discussed in section III.D.4. of this proposed
rule, we are proposing to calculate the ED adjustment in accordance
with our longstanding methodology, separate from the regression model.
However, we included a control variable for stays with ED charges to
control for the additional costs associated with ED admissions, which
are paid under the ED adjustment outside the regression model.
Lastly, we included control variables for the data year. Because
the model used a combined set of data from 3 years, these control
variables are included in the model to account for differences in cost
levels between 2019, 2020, and 2021, which would be driven by economic
inflation and other external factors unrelated to the independent
variables in the regression model.
e. Regression Results
Table 2 presents the results of our regression model. We discuss
these results and our related proposals to
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revise the IPF PPS patient-level adjustment factors in section III.C.4
of this proposed rule.
This regression model includes a total of 806,611 stays, and the r-
squared value of the model is 0.32340, meaning that the independent
variables included in the regression model can explain approximately
32.3 percent of the variation in per diem cost among IPF stays.
Except for the teaching variable, each of the adjustment factors in
Table 2 is the exponentiated regression coefficient of our regression
model, which as we previously noted uses the natural logarithm of per
diem total cost as the dependent variable. We present the exponentiated
regression results, as these most directly translate to the way that
IPF PPS adjustment factors are calculated for payment purposes. That
is, the exponentiated adjustment factors presented below represent a
percentage increase or decrease in per diem cost for IPF stays with
each characteristic. In the case of the teaching variable, the result
in Table 2 is the un-exponentiated regression coefficient. As discussed
in section III.D of this proposed rule, the current IPF PPS teaching
adjustment is calculated as 1 + a facility's ratio of interns and
residents to beds, raised to the power of 0.5150. The coefficient for
teaching status presented in Table 2 can be interpreted in the same
way.
For certain categorical variables, including DRG, age, length of
stay, and the year control variables, results for the reference groups
are not shown in Table 2. The DRG reference group is DRG 885, because
this DRG represents the majority of IPF PPS stays. The age reference
group is the Under 45 category, because this group is associated with
the lowest costs after accounting for all other patient characteristics
in the model. The reference group for length of stay is 10 days, which
corresponds to the reference group used in the original regression
model from the RY 2005 IPF PPS final rule. Lastly, the year control
reference group is CY 2021. Each of these reference groups not shown in
Table 2 effectively has an adjustment factor of 1.00 in the regression
model.
As shown in Column 5 of Table 2, we considered the regression
factors to be statistically significant when the p-value was less than
or equal to the significance level of 0.05 (*), 0.01 (**), and 0.001
(***). Columns 6 and 7 of Table 2 show the lower and upper bounds of
the 95-percent confidence interval (CI).
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4. Proposed Updates and Revisions to the IPF PPS Patient-Level
Adjustments
The IPF PPS includes payment adjustments for the following patient-
level characteristics: Medicare Severity Diagnosis Related Groups (MS-
DRGs) assignment of the patient's principal diagnosis, selected
comorbidities, patient age, and the variable per diem adjustments. As
discussed in section III.C.3. of this proposed rule, we are proposing
to derive updated IPF PPS adjustment factors for FY 2025 using a
regression analysis of data from the CY 2019 through 2021 MedPAR data
files and Medicare cost report data from the 2018 through FY 2021
Hospital Cost Report Information System (HCRIS). However, we have used
more recent claims (specifically, the December, 2023 update of the FY
2023 IPF PPS MedPAR claims) and cost data from the January, 2024 update
of the provider-specific file (PSF) to simulate payments to finalize
the outlier fixed dollar loss threshold amount and to assess the impact
of the IPF PPS updates. More information about the data used for the
impact simulations is found in section VIII.C of this FY 2025 IPF PPS
proposed rule. As discussed in section III.C.3. of this proposed rule,
by adjusting for DRGs, comorbidities, age, and length of the stay,
along with the facility-level variables and control variables in the
model, we were able to explain approximately 32.3 percent of the
variation in per diem cost among IPF stays.
In addition, we are proposing routine coding updates for FY 2025
for our longstanding code first and IPF PPS comorbidities. Furthermore,
as discussed in section III.C.4.a.(2) of this proposed rule, we are
proposing to adopt a sub-regulatory process for future routine coding
updates.
a. Proposed Updated and Revisions to MS-DRG Assignment
(1) Background
We believe it is important to maintain for IPFs the same diagnostic
coding and DRG classification used under the IPPS for providing
psychiatric care. For this reason, when the IPF PPS was implemented for
cost reporting periods beginning on or after January 1, 2005, we
adopted the same diagnostic code set (ICD-9-CM) and DRG patient
classification system (MS-DRGs) that were utilized at the time under
the IPPS. In the RY 2009 IPF PPS notice (73 FR 25709), we discussed
CMS's effort to better recognize resource use and the severity of
illness among patients. CMS adopted the new MS-DRGs for the IPPS in the
FY 2008 IPPS final rule with comment period (72 FR 47130). In the RY
2009 IPF PPS notice (73 FR 25716), we provided a crosswalk to reflect
changes that were made under the IPF PPS to adopt the new MS-DRGs. For
a detailed description of the mapping changes from the original DRG
adjustment categories to the current MS-DRG adjustment categories, we
refer readers to the RY 2009 IPF PPS notice (73 FR 25714).
The IPF PPS includes payment adjustments for designated psychiatric
DRGs assigned to the claim based on the patient's principal diagnosis.
The DRG adjustment factors were expressed relative to the most
frequently reported psychiatric DRG in FY 2002, that is, DRG 430
(psychoses). The coefficient values and adjustment factors were derived
from the regression analysis discussed in detail in the RY 2004 IPF
proposed rule (68 FR 66923; 66928 through 66933) and the RY 2005 IPF
final rule (69 FR 66933 through 66960). Mapping the DRGs to the MS-DRGs
resulted in the current 17 IPF MS-DRGs, instead of the original 15
DRGs, for which the IPF PPS provides an adjustment.
In the FY 2015 IPF PPS final rule published August 6, 2014 in the
Federal Register titled, ``Inpatient Psychiatric Facilities Prospective
Payment System--Update for FY Beginning October 1, 2014 (FY 2015)'' (79
FR 45945 through 45947), we finalized conversions of the ICD-9-CM-based
MS-DRGs to ICD-10-CM/PCS-based MS-DRGs, which were implemented on
October 1, 2015. Further information on the ICD-10-CM/PCS MS-DRG
conversion project can be found on the CMS ICD-10-CM website at https://www.cms.gov/medicare/coding-billing/icd-10-codes/icd-10-ms-drg-conversion-project.
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(2) Proposal To Adopt Sub-Regulatory Process for Publication of Coding
Changes
As discussed in the FY 2015 IPF PPS proposed rule (79 FR 26047)
every year, changes to the ICD-10-CM and the ICD-10-PCS coding system
have been addressed in the IPPS proposed and final rules. The changes
to the codes are effective October 1 of each year and must be used by
acute care hospitals as well as other providers to report diagnostic
and procedure information. In accordance with Sec. 412.428(e), we have
historically described in the IPF PPS proposed and final rules the ICD-
10-CM coding changes and DRG classification changes that have been
discussed in the annual proposed and final hospital IPPS regulations.
This has typically involved a discussion in the proposed rule about
coding updates to be effective October 1 of each year, with a summary
of comments in the final rule along with a description of additional
finalized codes for October.
In the FY 2022 IPPS/LTCH PPS final rule (86 FR 44950 through
44956), we adopted an April 1 implementation date for ICD-10-CM
diagnosis and ICD-10-PCS procedure code updates in addition to the
annual October 1 update of ICD-10-CM diagnosis and ICD-10-PCS procedure
codes, beginning with April 1, 2022. In that rule, we noted the intent
of this April 1 implementation date is to allow flexibility in the ICD-
10 code update process. Currently, as noted earlier in this proposed
rule, the IPF PPS uses the IPPS DRG assignments, which are applied to
IPF PPS claims; these DRG assignments reflect the change in process
that the IPPS adopted for FY 2022. To maintain consistency with IPPS
policy, we are proposing to follow the same process beginning in FY
2025. This means that for routine coding updates that incorporate new
or revised codes, we are proposing to adopt these changes through a
sub-regulatory process. Beginning in FY 2025, we would operationalize
such coding changes in a Transmittal/Change Request, which would align
with the way coding changes are announced under the IPPS.
For example, we are proposing that for April 2025, we would adopt
routine coding updates for the IPF PPS comorbidity categories, code
first policy, ECT code list, and DRG assignment via sub-regulatory
guidance. These coding updates would take effect April 1, 2025. In
accordance with Sec. 412.428(e), we would describe these coding
changes, along with any coding updates that would be effective for
October 1, 2025, in the FY 2026 IPF PPS proposed rule. We would
summarize and respond to any comments on these April and October coding
changes in the FY 2026 IPF PPS final rule.
The proposed update aims to allow flexibility in the ICD-10 code
update process for the IPF PPS and reduces the lead time for making
routine coding updates to the IPF PPS code first list, comorbidities,
and ECT coding categories. In addition, the IPPS sub-regulatory process
continues to manage DRG assignment changes which apply to the DRG
assignments used in the IPF PPS. Finally, we are clarifying that we
would only apply this sub-regulatory process for routine coding
updates. Any future substantive revisions to the IPF PPS DRG
adjustments, comorbidities, code first policy, or ECT payment policy
would be proposed through notice and comment rulemaking. We solicit
public comments on this proposal.
(3) Routine Coding Updates for DRG Assignments
The diagnoses for each IPF MS-DRG will be updated as of October 1,
2024, using the final IPPS FY 2025 ICD-10-CM/PCS code sets. The FY 2025
IPPS/LTCH PPS final rule will include tables of the changes to the ICD-
10-CM/PCS code sets that underlie the proposed FY 2025 IPF MS-DRGs.
Both the FY 2025 IPPS final rule and the tables of final changes to the
ICD-10-CM/PCS code sets, which underlie the FY 2025 MS-DRGs, will be
available on the CMS IPPS website at https://www.cms.gov/medicare/payment/prospective-payment-systems/acute-inpatient-pps.
(4) Code First
As discussed in the ICD-10-CM Official Guidelines for Coding and
Reporting, certain conditions have both an underlying etiology and
multiple body system manifestations due to the underlying etiology. For
such conditions, the ICD-10-CM has a coding convention that requires
the underlying condition be sequenced first, followed by the
manifestation. Wherever such a combination exists, there is a ``use
additional code'' note at the etiology code, and a ``code first'' note
at the manifestation code. These instructional notes indicate the
proper sequencing order of the codes (etiology followed by
manifestation). In accordance with the ICD-10-CM Official Guidelines
for Coding and Reporting, when a primary (psychiatric) diagnosis code
has a code first note, the provider will follow the instructions in the
ICD-10-CM Tabular List. The submitted claim goes through the CMS
processing system, which will identify the principal diagnosis code as
non-psychiatric and search the secondary codes for a psychiatric code
to assign a DRG code for adjustment. The system will continue to search
the secondary codes for those that are appropriate for comorbidity
adjustment. For more information on the code first policy, we refer
readers to the RY 2005 IPF PPS final rule (69 FR 66945). We also refer
readers to sections I.A.13 and I.B.7 of the FY 2020 ICD-10-CM Coding
Guidelines, which is available at https://www.cdc.gov/nchs/data/icd/10cmguidelinesFY2020_final.pdf. In the FY 2015 IPF PPS final rule, we
provided a code first table for reference that highlights the same or
similar manifestation codes where the code first instructions apply in
ICD-10-CM that were present in ICD-10-CM (79 FR 46009). In FY 2018, FY
2019, and FY 2020, there were no changes to the final ICD-10-CM codes
in the IPF Code First table. For FY 2021 and FY 2022, there were 18
ICD-10-CM codes deleted from the final IPF Code First table. For FY
2023, there were 2 ICD-10-CM codes deleted and 48 ICD-10-CM codes added
to the IPF Code First table. For FY 2024, there were no proposed
changes to the Code First Table.
We are proposing to continue our existing code first policy. As
outlined in our proposal to incorporate a sub-regulatory process for
the publication of coding changes, we are proposing to adopt a sub-
regulatory approach to handle the coding updates, which removes the
requirement to discuss coding updates in the Federal Register during
regulatory updates prior to implementation, which would mirror the
approach taken by the IPPS. The proposed FY 2025 Code First table is
shown in Addendum B on the CMS website at https://www.cms.gov/Medicare/Medicare-Fee-forServicePayment/InpatientPsychFacilPPS/tools.html.
(5) Proposed Revisions to MS-DRG Adjustment Factors
For FY 2025, we are proposing to revise the payment adjustments for
designated psychiatric DRGs assigned to the claim based on the
patient's principal diagnosis, following our longstanding policy of
using the ICD-10-CM/PCS-based MS-DRG system. As discussed in the
following paragraphs, we are proposing to maintain DRG adjustments for
15 of the existing 17 IPF MS-DRGs for which we currently adjust payment
in FY 2024. We are proposing to replace two existing DRGs with two new
DRGs to reflect changes in coding practices over time and proposing to
add two DRGs that are associated with poisoning. We are also proposing
to
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revise the adjustment factors for the DRG adjustments as described in
Table 3, based on the results of our latest regression analysis
described in Section III.C.3 of this proposed rule. Addendum A is
available on the CMS website at https://www.cms.gov/medicare/payment/prospective-payment-systems/inpatient-psychiatric-facility/tools-and-worksheets. The website includes the proposed DRG adjustment factors
for FY 2025. In accordance with our longstanding policy, we are
proposing that psychiatric principal diagnoses that do not group to one
of the 19 proposed designated MS-DRGs would still receive the Federal
per diem base rate and all other applicable adjustments; however, the
payment would not include an MS-DRG adjustment.
(a) Proposed Replacement of DRGs
We are proposing to remove DRGs 080 (Nontraumatic stupor & coma w
MCC) and 081 (Nontraumatic stupor & coma w/o MCC), and to replace these
with DRGs 947 (Signs and Symptoms w MCC) and 948 (Signs and Symptoms w/
out MCC). As previously discussed, we observed that the number of cases
in DRGs 080 and 081 have decreased significantly since 2004. We
selected DRGs 947 and 948 as the most clinically appropriate
replacements, because most of the ICD-10-CM codes that previously
grouped to DRGs 080 or 081 now group to DRGs 947 or 948. Table 3
compares the current adjustment factors for DRGs 080 and 081 to the
regression-derived adjustment factors for DRGs 947 and 948. As shown in
Table 3, the proposed adjustment factors for DRGs 947 and 948 would
each be greater than the current DRG adjustment for DRGs 080 and 081.
Therefore, we are proposing that claims with DRGs 080 or 081 would
still receive the Federal per diem base rate and all other applicable
adjustments; however, the payment would not include an MS-DRG
adjustment.
As discussed in section III.F of this proposed rule, we are
proposing to implement this revision to the DRG adjustments budget-
neutrally. A detailed discussion of the distributional impacts of this
proposed change is found in section VIII.C of this proposed rule.
Lastly, we are proposing that if more recent data become available, we
would use such data, if appropriate, to determine the FY 2025 DRG
adjustment factors.
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(b) Proposed Additions of DRGs
We are proposing to recognize DRG adjustments for two DRGs
associated with poisoning; specifically, DRG 917 (Poisoning and toxic
effects of drugs w MCC) and 918 (Poisoning and toxic effects of drugs
w/out MCC). As discussed earlier in this proposed rule, we have
identified that a small but increasing number of IPF stays contain
these poisoning-related DRG assignments, and that stays with these DRGs
have increased costs per day that are statistically significant. Table
4 summarizes the frequency of these stays and the proposed adjustment
factors for FY 2025. As discussed in section III.F of this proposed
rule, we are proposing to implement this revision to the DRG
adjustments budget-neutrally. A detailed discussion of the
distributional impacts of this proposed change is found in section
VIII.C of this proposed rule.
Lastly, we are proposing that if more recent data become available,
we would use such data, if appropriate, to determine the FY 2025 DRG
adjustment factors.
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(c) Proposed Revisions to Adjustment Factors for Existing DRG
Adjustments
We are proposing to revise the adjustment factors for the remaining
15 of the existing 17 DRGs that currently receive a DRG adjustment in
FY 2024. These proposed revisions are based on the results of our
latest regression analysis described in section III.C.3 of this
proposed rule.
As previously discussed, our analysis found that some of the
adjustment factors in the regression model for DRGs that currently
receive an adjustment are no longer statistically significant.
Specifically, we found that the adjustment factors for DRG 882
(Neuroses except depressive), DRG 887 (Other mental disorder
diagnoses), and DRG 896 (Alcohol, Drug Abuse or Dependence w/out rehab
therapy w MCC) were not statistically significant. For each of these
DRGs, we examined whether the current adjustment factor falls within
the confidence interval for our latest regression analysis. The current
adjustment for DRG 882 is 1.02, and this falls within the confidence
interval of 0.96798 to 1.07811 for the latest regression model
discussed in section III.C.3 of this proposed rule. We believe it would
be appropriate to maintain the current adjustment factor of 1.02 for
DRG 882, because the latest regression results indicate that the
current adjustment factor would be a reasonable approximation of the
increased costs associated with DRG 882. For DRGs 887 and 896; however,
the current adjustment factors (0.92 and 0.88, respectively) do not
fall within the confidence interval for each of these DRGs. Therefore,
we are proposing to apply an adjustment factor of 1.00 for IPF stays
with these DRGs.
Table 5 summarizes the frequency of these stays and the proposed
adjustment factors for FY 2025. As discussed in section III.F of this
proposed rule, we are proposing to implement this revision to the DRG
adjustments budget-neutrally. A detailed discussion of the
distributional impacts of this proposed change is found in section
VIII.C of this proposed rule.
Lastly, we are proposing that if more recent data become available,
we would use such data, if appropriate, to determine the FY 2025 DRG
adjustment factors.
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b. Proposed Payment for Comorbid Conditions
(1) Proposed Revisions to Comorbidity Adjustments
The intent of the comorbidity adjustments is to recognize the
increased costs associated with comorbid conditions by providing
additional payments for certain existing medical or psychiatric
conditions that are expensive to treat.
Comorbidities are specific patient conditions that are secondary to
the patient's principal diagnosis and that require treatment during the
stay. Diagnoses that relate to an earlier episode of care and have no
bearing on the current hospital stay are excluded and must not be
reported on IPF claims. Comorbid conditions must exist at the time of
admission or develop subsequently, and affect the treatment received,
LOS, or both treatment and LOS.
The current comorbidity adjustments were determined based on the
regression analysis using the diagnoses reported by IPFs in FY 2002.
The principal diagnoses were used to establish the DRG adjustments and
were not accounted for in establishing the comorbidity category
adjustments, except where ICD-9-CM code first instructions applied. In
a code first situation, the submitted claim goes through the CMS
processing system, which identifies the principal diagnosis code as
non-psychiatric and searches the secondary codes for a psychiatric code
to assign an MS-DRG code for adjustment. The system continues to search
the secondary codes for those that are appropriate for a comorbidity
adjustment.
In our RY 2012 IPF PPS final rule (76 FR 26451 through 26452), we
explained that the IPF PPS includes 17 comorbidity categories and
identified the new, revised, and deleted ICD-9-CM diagnosis codes that
generate a comorbid condition payment adjustment under the IPF PPS for
RY 2012 (76 FR 26451).
As discussed in section C.4.a.(1) of this proposed rule, it is our
policy to
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maintain the same diagnostic coding set for IPFs that is used under the
IPPS for providing the same psychiatric care. The 17 comorbidity
categories formerly defined using ICD-9-CM codes were converted to ICD-
10-CM/PCS in our FY 2015 IPF PPS final rule (79 FR 45947 through
45955). The goal for converting the comorbidity categories is referred
to as replication, meaning that the payment adjustment for a given
patient encounter is the same after ICD-10-CM implementation as it
would be if the same record had been coded in ICD-9-CM and submitted
prior to ICD-10-CM/PCS implementation on October 1, 2015. All
conversion efforts were made with the intent of achieving this goal.
For each claim, an IPF may receive only one comorbidity adjustment
within a comorbidity category, but it may receive an adjustment for
more than one comorbidity category. Current billing instructions for
discharge claims, on or after October 1, 2015, require IPFs to enter
the complete ICD-10-CM codes for up to 24 additional diagnoses if they
co-exist at the time of admission, or develop subsequently and impact
the treatment provided.
As previously discussed in section III.C.4.a.(2) of this proposed
rule, we are proposing to adopt an April 1 implementation date for ICD-
10-CM diagnosis and ICD-10-PCS procedure code updates, in addition to
the annual October 1 update, beginning with April 1, 2025 for the IPF
PPS. For FY 2025 and future years, coding updates related to the IPF
PPS comorbidity categories would be adopted following a sub-regulatory
process as discussed earlier in this proposed rule.
For FY 2025, we are proposing to revise the comorbidity adjustment
factors based on the results of the 2019 through 2021 regression
analysis described in section III.C.3.e. of this proposed rule. We are
also proposing additions and changes to the comorbidity categories for
which we adjust payment based on our analysis of ICD-10-CM codes
currently included in each category as well as public comments received
in response to the FY 2022 and FY 2023 IPF PPS proposed rules.
Based on analysis of the ICD-10-CM codes, we considered the
statistical significance of the adjustment factor and whether the
current (FY 2024) adjustment factor fell within the confidence interval
in the 2019 through 2021 regression to determine the FY 2025 IPF PPS
proposed comorbidity categories and adjustment factors. As previously
discussed for the DRG adjustment factors, when the regression factor is
not statistically significant, but the current adjustment factor is
within the confidence interval, we are proposing to maintain the
current adjustment factor. When a regression factor is not
statistically significant and the current adjustment factor is not
within the confidence interval, we are proposing to remove the
comorbidity category.
Specifically, we are proposing to increase the adjustment factors
for the Gangrene, Severe Protein Malnutrition, Oncology Treatment,
Poisoning, and Tracheostomy comorbidity categories based on the
adjustment factors derived from the regression analysis discussed in
section III.C.3 of this proposed rule. For these comorbidity
categories, the regression results produced a statistically significant
increase in the adjustment factors.
We are proposing to remove the comorbidity categories for the
Coagulation Factor Deficit, Drug/Alcohol Induced Mental Disorders, and
Infectious Diseases adjustment factors because the regression factor
for the ICD-10-CM codes associated with Coagulation Factor Deficit and
Infectious Diseases were not statistically significant, and the current
adjustment factors did not fall within the confidence intervals in the
2019 through 2021 regression.
The current adjustment factor for Drug/Alcohol Induced Mental
Disorders is 1.03; however, the adjustment factor derived from our
latest regression results was statistically significant at 0.96084,
meaning payments would be reduced if we applied the regression-derived
adjustment factor as a comorbidity adjustment for this category. In
order to understand the drivers of changing costs for the Drug/Alcohol
Induced Mental Disorders comorbidity category, we examined a subset of
ICD-10-CM codes within the comorbidity category associated with opioid
disorders which make up the majority of stays that qualify for the
current Drug/Alcohol Induced Mental Disorders comorbidity adjustment.
These opioid disorder codes are listed in Table 6. When we separately
analyzed these codes associated with opioid disorder, the results
suggested that patients with opioid disorder are significantly less
expensive than patients without opioid disorder. Because stays with
opioid disorders make up the majority of stays in the Drug/Alcohol
Induced Mental Disorders comorbidity category, we observe a
statistically-significant negative adjustment factor for the
comorbidity category overall. The application of a comorbidity
adjustment derived from our latest regression analysis would result in
reduced payments for all stays in this comorbidity category. We do not
believe it is appropriate to apply negative adjustment factors (that
is, adjustment factors less than 1.00) for comorbidities because that
would result in reduced rather than increased payments. Although we
apply adjustment factors less than 1.00 for DRGs, this is because the
DRG adjustment reflects the cost of stays relative to stays with the
baseline DRG 885. In contrast, comorbidity adjustments reflect the cost
relative to a stay with no comorbidities. A negative payment adjustment
would not be consistent with the intent of a comorbidity adjustment,
which is intended to provide additional payments to providers to
account for the costs of treating patients with comorbid conditions.
Therefore, we have not historically included any negative adjustment
factors for comorbid conditions.
Therefore, we are proposing to remove the Drug/Alcohol Induced
Mental Disorders comorbidity category beginning in FY 2025. IPF stays
that include these codes as a non-principal diagnosis would no longer
receive the current Drug/Alcohol Induced Mental Disorders comorbidity
category adjustment factor of 1.03; nor would they receive a reduction
in payment. However, many IPF stays that include these ICD-10-CM
diagnosis codes as a principal diagnosis would continue to receive a
DRG adjustment. We refer readers to section III.C.3.a of this proposed
rule for a detailed discussion of proposed DRG adjustments under the
IPF PPS.
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We believe removal of the Drug/Alcohol Induced Mental Disorders
comorbidity category under the IPF PPS would more appropriately align
payment with resource use, as reflected in the latest regression
results. As previously discussed in section III.F of this proposed
rule, all of these proposed revisions would be applied budget-
neutrally. Therefore, we believe the removal of the Drug/Alcohol
Induced Mental Disorders comorbidity adjustment would appropriately
increase the IPF PPS Federal per diem base rate and thereby increase
payment for IPF stays that are costlier. However, we are soliciting
comments on whether a lack of ancillary charge data may be contributing
to the results of our regression analysis as it relates to opioid
disorders. We note that our analysis of the ICD-10-CM codes associated
with opioid disorder also indicates that there is significant overlap
between facility characteristics and stays including opioid disorder
diagnoses. In particular, for-profit freestanding IPFs were found to
serve the majority of patients with opioid disorders. As discussed in
section III.E.4 of this proposed rule, our ongoing analysis has found
an increase in the number of for-profit freestanding IPFs that are
consistently reporting no ancillary charges or very minimal ancillary
charges on their cost report. As a result, we have previously noted
that data that is necessary for accurate Medicare ratesetting is
excluded from the information these facilities are reporting.
As stated previously, the regression factor for Drug/Alcohol
Induced Mental Disorders was statistically significant, but is less
than 1, meaning payments would be reduced if we applied it as a
comorbidity adjustment. We are interested in understanding whether
there is data and information that could better inform our
understanding of the costs of treating these conditions. In addition,
we are interested in understanding whether commenters believe it may be
more appropriate to maintain the existing Drug/Alcohol Induced Mental
Disorders comorbidity category adjustment factor of 1.03, given that
many providers that treat these patients also report minimal or no
ancillary charges on their claims and cost reports. We note that if we
were to maintain the adjustment factor of 1.03 for these IPF stays, we
expect it would have a negative impact on the refinement
standardization factor, thereby slightly reducing the IPF PPS Federal
per diem base rate and ECT per treatment amount.
We are also proposing to modify the Eating and Conduct Disorders
comorbidity category and redesignate it as the Eating Disorders
comorbidity category. That is, we are proposing to remove conduct
disorders from the codes eligible for a comorbidity adjustment. When we
separately analyzed the ICD-10-CM codes for eating disorders
(specifically, F5000 Anorexia nervosa, unspecified, F5001
[[Page 23168]]
Anorexia nervosa, restricting type, F5002 Anorexia nervosa, binge
eating/purging type, and F509 Eating disorder, unspecified) and conduct
disorders (F631 Pyromania, F6381 Intermittent explosive disorder, and
F911 Conduct disorder, childhood-onset type), our regression results
identified a positive, statistically significant adjustment factor
associated with eating disorders. In contrast, conduct disorders had a
negative and non-significant factor. These results suggest that eating
disorders are associated with an increased level of resource use
compared to conduct disorders, and that only eating disorders have an
increase resource use at a level that is statistically significant.
Based on these findings, we are proposing to remove conduct disorders
from the proposed newly designated Eating Disorders comorbidity
category.
In addition, we are proposing to modify the Chronic Obstructive
Pulmonary Disease comorbidity category to include ICD-10-CM codes
associated with sleep apnea (specifically, G4733 Obstructive sleep
apnea (adult) (pediatric), 5A09357 Assistance with Respiratory
Ventilation, <24 Hrs, CPAP, Z9981 Dependence on supplemental oxygen,
and Z9989 Dependence on other enabling machines and devices). In
response to the FY 2023 and FY 2024 IPF PPS proposed rules, commenters
requested that CMS analyze the additional cost associated with patients
with sleep apnea. Patients with sleep apnea often need to use a
continuous positive airway pressure (CPAP) machine with a cord to
manage their condition. Based on the clinical expertise of CMS Medical
Officers, we determined that patients with sleep apnea in the IPF
setting would have increased ligature risk (that is, anything that
could be used to attach a cord, rope, or other material for the purpose
of hanging or strangulation), similar to the risk associated with
patients in the IPF setting that have chronic obstructive pulmonary
disease. We expect the additional staffing resources involved in
treating IPF patients with sleep apnea would be similar to the
resources involved in treating IPF patients with chronic obstructive
pulmonary disease, as patients with chronic obstructive pulmonary
disease may also require the presence of an additional device with a
cord in the patient's room, such as a bilevel positive airway pressure
(BiPAP) machine. We evaluated adding codes associated with sleep apnea
to our regression model, on the basis of our expectation that we would
observe higher costs associated with these codes that would be
comparable to the costs associated with chronic obstructive pulmonary
disease. The results of our 2019 through 2021 regression model suggest
that sleep apnea is in fact associated with an increased level of
resource use. Therefore, we are proposing to redesignate the Chronic
Obstructive Pulmonary Disease category as the Chronic Obstructive
Pulmonary Disease and Sleep Apnea comorbidity category.
Further, we analyzed costs associated with the ICD-10-CM codes in
Table 7 that indicate high-risk behavior. In response to the FY 2023
and FY 2024 IPF PPS proposed rules, commenters requested that CMS
analyze the additional cost associated with patients exhibiting violent
behavior during their stay in an IPF. We considered these comments in
coordination with CMS Medical Officers, and determined that patients
exhibiting violent behavior would require more intensive management
during an IPF stay. We determined that certain ICD-10-CM codes could
describe the types of high-risk behaviors that require intensive
management during an IPF stay. These could include patients exhibiting
violent behavior as well as other high-risk, non-violent behaviors. We
examined ICD-10-CM codes in the R45 code family (Symptoms and Signs
Related to Emotional State) that could indicate high-risk behavior
during an IPF stay, which would lead to increased resource use. The
regression analysis found that several codes, R451 Restlessness and
agitation, R454 Irritability and anger, and R4584 Anhedonia codes are
associated with a statistically significant adjustment factor. In other
words, patients presenting with restlessness and agitation,
irritability and anger, or anhedonia are more costly than patients who
do not present these conditions. Therefore, we are proposing to add a
new comorbidity category recognizing the costs associated with
Intensive Management for High-Risk Behavior.
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Lastly, we are proposing to maintain the adjustment factors for the
Developmental Disabilities and Uncontrolled Diabetes comorbidity
categories. Based on the regression analysis, the Developmental
Disabilities comorbidity category adjustment factor was not
statistically significant; however, the current adjustment factor is
within the confidence interval. As discussed in section III.C.3.a of
this proposed rule, a non-statistically significant adjustment factor
within the confidence interval indicates that the current adjustment
factor would be a reasonable approximation of the increased costs. The
Uncontrolled Diabetes comorbidity category adjustment factor did not
change from the current adjustment factor based on the 2019 through
2021 regression.
We are also proposing to decrease the adjustment factors for the
following comorbidity categories: Renal Failure--Acute, Artificial
Openings--Digestive & Urinary, Cardiac conditions, Renal Failure--
Chronic, Chronic Obstructive Pulmonary Disease, Infectious Diseases,
and Severe Musculoskeletal & Connective Tissue Diseases.
The regression analysis found the Renal Failure--Acute, Artificial
Openings--Digestive & Urinary, Cardiac conditions, Renal Failure--
Chronic, Chronic Obstructive Pulmonary Disease, Infectious Diseases,
and Severe Musculoskeletal & Connective Tissue Diseases comorbidity
categories resulted in a statistically significant adjustment factor.
While payment would still be increased when the claim includes one of
these comorbidity categories, the proposed adjustment factors for FY
2025 would be less than the current adjustment factors for these
categories. The proposed FY 2025 comorbidity adjustment factors are
displayed in Table 8, and can be found in Addendum A, available on the
CMS website at https://www.cms.gov/medicare/payment/prospective-payment-systems/inpatient-psychiatric-facility/tools-and-worksheets.
[[Page 23170]]
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As discussed in section III.F of this proposed rule, we are
proposing to implement revisions to the comorbidity category
adjustments budget-neutrally. A detailed discussion of the
distributional impacts of these proposed changes is found in section
VIII.C of this proposed rule.
We solicit comments on these proposed revisions to the comorbidity
category adjustment factors. Lastly, we are proposing that if more
recent data become available, we would use such data, if appropriate,
to determine the final FY 2025 comorbidity category adjustment factors.
(2) Proposed Coding Updates for FY 2025
For FY 2025, we are proposing to add 2 ICD-10-CM/PCS codes to the
Oncology Treatment comorbidity category. The proposed FY 2025
comorbidity codes are shown in Addenda B, available on the CMS website
at https://www.cms.gov/medicare/payment/prospective-payment-systems/inpatient-psychiatric-facility/tools-and-worksheets.
In accordance with the policy established in the FY 2015 IPF PPS
final rule (79 FR 45949 through 45952), we reviewed all new FY 2025
ICD-10-CM codes to remove codes that were site ``unspecified'' in terms
of laterality from the FY 2023 ICD-10-CM/PCS codes in instances where
more specific codes are available. As we stated in the FY 2015 IPF PPS
final rule, we believe that specific diagnosis codes that narrowly
identify anatomical sites where disease, injury, or a condition exists
should be used when coding patients' diagnoses whenever these codes are
available. We finalized in the FY 2015 IPF PPS rule, that we would
remove site ``unspecified'' codes from the IPF PPS ICD-10-CM/PCS codes
in instances when laterality codes (site specified codes) are
available, as the clinician should be able to identify a more specific
diagnosis based on clinical assessment at the medical encounter. There
were no proposed changes to the FY 2025 ICD-10-CM/PCS codes, therefore,
we are not proposing to remove any of the new codes.
c. Proposed Patient Age Adjustments
As explained in the RY 2005 IPF PPS final rule (69 FR 66922), we
analyzed the impact of age on per diem cost by examining the age
variable (range of ages) for payment adjustments. In general, we found
that the cost per day increases with age. The older age groups are
costlier than the under 45 age group, the differences in per diem cost
increase for each successive age group, and the differences are
statistically significant. While our regression analysis of CY 2019
through CY 2021 data supports maintaining a payment adjustment factor
based on age as was established in the RY 2005 IPF PPS final rule, the
results suggest that revisions to the adjustment factor for age are
warranted.
For FY 2025, we are proposing to revise the patient age adjustments
as shown in Addendum A of this proposed rule, which is available on the
CMS website at (see https://www.cms.gov/medicare/payment/prospective-payment-systems/inpatient-psychiatric-facility/tools-and-worksheets).
We are proposing to adopt the patient age adjustments derived from the
regression
[[Page 23171]]
model using a blended set of 2019 through 2021 data, as discussed in
section III.C.3 of this proposed rule. Table 9 summarizes the current
and proposed patient age adjustment factors for FY 2025. As discussed
in section III.F of this proposed rule, we are proposing to implement
this revision to the patient age adjustments budget-neutrally. A
detailed discussion of the distributional impacts of this proposed
change is found in section VIII.C of this proposed rule.
We solicit comment on these proposed revisions to the patient age
adjustment factors. Lastly, we are proposing that if more recent data
become available, we would use such data, if appropriate, to determine
the final FY 2025 patient age adjustment factors.
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d. Proposed Variable Per Diem Adjustments
We explained in the RY 2005 IPF PPS final rule (69 FR 66946) that
the regression analysis indicated that per diem cost declines as the
LOS increases. The variable per diem adjustments to the Federal per
diem base rate account for ancillary and administrative costs that
occur disproportionately in the first days after admission to an IPF.
As discussed in the RY 2005 IPF PPS final rule, where a complete
discussion of the variable per diem adjustments can be found, we used a
regression analysis to estimate the average differences in per diem
cost among stays of different lengths (69 FR 66947 through 66950). As a
result of this analysis, we established variable per diem adjustments
that begin on day 1 and decline gradually until day 21 of a patient's
stay. For day 22 and thereafter, the variable per diem adjustment
remains the same each day for the remainder of the stay. However, the
adjustment applied to day 1 depends upon whether the IPF has a
qualifying ED. If an IPF has a qualifying ED, it receives a 1.31
adjustment factor for day 1 of each stay. If an IPF does not have a
qualifying ED, it receives a 1.19 adjustment factor for day 1 of the
stay. The ED adjustment is explained in more detail in section III.D.4
of this proposed rule.
For FY 2025, we are proposing to revise the variable per diem
adjustment factors as indicated in the table below, and shown in
Addendum A to this rule, which is available on the CMS website at
https://www.cms.gov/medicare/payment/prospective-payment-systems/inpatient-psychiatric-facility/tools-and-worksheets. We are proposing
to increase the adjustment factors for days 1 through 9. As shown in
Table 10, the results of the latest regression analysis indicate that
there is not a statistically significant decrease in cost per day after
day 10; therefore, we are proposing that days 10 and above would
receive a 1.00 adjustment. Table 10 summarizes the current and proposed
variable per diem adjustment factors for FY 2025. As discussed in
section III.F of this proposed rule, we are proposing to implement this
revision to the variable per diem adjustments budget-neutrally. A
detailed discussion of the distributional impacts of this proposed
change is found in section VIII.C of this proposed rule.
We solicit comments on these proposed revisions to the variable per
diem adjustment factors. Lastly, we are proposing that if more recent
data become available, we would use such data, if appropriate, to
determine the
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final FY 2025 variable per diem adjustment factors.
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D. Proposed Updates to the IPF PPS Facility-Level Adjustments
The IPF PPS includes facility-level adjustments for the wage index,
IPFs located in rural areas, teaching IPFs, cost of living adjustments
for IPFs located in Alaska and Hawaii, and IPFs with a qualifying ED.
We are proposing to use the existing regression-derived facility-level
adjustment factors established in the RY 2005 IPF final rule for FY
2025.
As previously discussed, in section I.A of this proposed rule, we
are proposing to revise the methodology for determining payments under
the IPF PPS as required by the CAA, 2023. We are not proposing changes
to the facility-level adjustment factors for rural location and
teaching status for FY 2025; however, section IV.A of this proposed
rule includes a request for information regarding potential future
updates to these facility-level adjustments. We are particularly
interested in comments on the results of our updated regression
analysis as they apply to facility-level adjustors.
1. Wage Index Adjustment
a. Background
As discussed in the RY 2007 IPF PPS final rule (71 FR 27061), and
the RY 2009 IPF PPS (73 FR 25719) and RY 2010 IPF PPS notices (74 FR
20373), to provide an adjustment for geographic wage levels, the labor-
related portion of an IPF's payment is adjusted using an appropriate
wage index. Currently, an IPF's geographic wage index value is
determined based on the actual location of the IPF in an urban or rural
area, as defined in Sec. 412.64(b)(1)(ii)(A) and (C).
Due to the variation in costs and because of the differences in
geographic wage levels, in the RY 2005 IPF PPS final rule, we required
that payment rates under the IPF PPS be adjusted by a geographic wage
index. We proposed and finalized a policy to use the unadjusted, pre-
floor, pre-reclassified IPPS hospital wage index to account for
geographic differences in IPF labor costs. We implemented use of the
pre-floor, pre-reclassified IPPS hospital wage data to compute the IPF
wage index since there was not an IPF-specific wage index available. We
believe that IPFs generally compete in the same labor market as IPPS
hospitals therefore, the pre-floor, pre-reclassified IPPS hospital wage
data should be reflective of labor costs of IPFs. We believe this pre-
floor, pre-reclassified IPPS hospital wage index to be the best
available data to use as proxy for an IPF-specific wage index. As
discussed in the RY 2007 IPF PPS final rule (71FR 27061 through 27067),
under the IPF PPS, the wage index is calculated using the IPPS wage
index for the labor market area in which the IPF is located, without
considering geographic reclassifications, floors, and other adjustments
made to the wage index under the IPPS. For a complete description of
these IPPS wage index adjustments, we refer readers to the FY 2019
IPPS/LTCH PPS final rule (83 FR 41362 through 41390). Our wage index
policy at Sec. 412.424(a)(2) provides that we use the best Medicare
data available to estimate costs per day, including an appropriate wage
index to adjust for wage differences.
When the IPF PPS was implemented in the RY 2005 IPF PPS final rule,
with
[[Page 23173]]
an effective date of January 1, 2005, the pre-floor, pre-reclassified
IPPS hospital wage index that was available at the time was the FY 2005
pre-floor, pre-reclassified IPPS hospital wage index. Historically, the
IPF wage index for a given RY has used the pre-floor, pre-reclassified
IPPS hospital wage index from the prior FY as its basis. This has been
due in part to the pre-floor, pre-reclassified IPPS hospital wage index
data that were available during the IPF rulemaking cycle, where an
annual IPF notice or IPF final rule was usually published in early May.
This publication timeframe was relatively early compared to other
Medicare payment rules because the IPF PPS follows a RY, which was
defined in the implementation of the IPF PPS as the 12-month period
from July 1 to June 30 (69 FR 66927). Therefore, the best available
data at the time the IPF PPS was implemented was the pre-floor, pre-
reclassified IPPS hospital wage index from the prior FY (for example,
the RY 2006 IPF wage index was based on the FY 2005 pre-floor, pre-
reclassified IPPS hospital wage index).
In the RY 2012 IPF PPS final rule, we changed the reporting year
timeframe for IPFs from a RY to FY, which begins October 1 and ends
September 30 (76 FR 26434 through 26435). In that FY 2012 IPF PPS final
rule, we continued our established policy of using the pre-floor, pre-
reclassified IPPS hospital wage index from the prior year (that is,
from FY 2011) as the basis for the FY 2012 IPF wage index. This policy
of basing a wage index on the prior year's pre-floor, pre-reclassified
IPPS hospital wage index has been followed by other Medicare payment
systems, such as hospice and inpatient rehabilitation facilities. By
continuing with our established policy, we remained consistent with
other Medicare payment systems.
In FY 2020, we finalized the IPF wage index methodology to align
the IPF PPS wage index with the same wage data timeframe used by the
IPPS for FY 2020 and subsequent years. Specifically, we finalized the
use of the pre-floor, pre-reclassified IPPS hospital wage index from
the FY concurrent with the IPF FY as the basis for the IPF wage index.
For example, the FY 2020 IPF wage index was based on the FY 2020 pre-
floor, pre-reclassified IPPS hospital wage index rather than on the FY
2019 pre-floor, pre-reclassified IPPS hospital wage index.
We explained in the FY 2020 proposed rule (84 FR 16973), that using
the concurrent pre-floor, pre-reclassified IPPS hospital wage index
will result in the most up-to-date wage data being the basis for the
IPF wage index. We noted that it would also result in more consistency
and parity in the wage index methodology used by other Medicare payment
systems. We indicated that the Medicare skilled nursing facility (SNF)
PPS already used the concurrent IPPS hospital wage index data as the
basis for the SNF PPS wage index. We proposed and finalized similar
policies to use the concurrent pre-floor, pre-reclassified IPPS
hospital wage index data in other Medicare payment systems, such as
hospice and inpatient rehabilitation facilities. Thus, the wage
adjusted Medicare payments of various provider types are based upon
wage index data from the same timeframe. For FY 2025, we are proposing
to continue to use the concurrent pre-floor, pre-reclassified IPPS
hospital wage index as the basis for the IPF wage index.
In the FY 2023 IPF PPS final rule (87 FR 46856 through 46859), we
finalized a permanent 5-percent cap on any decrease to a provider's
wage index from its wage index in the prior year, and we stated that we
would apply this cap in a budget neutral manner. In addition, we
finalized a policy that a new IPF would be paid the wage index for the
area in which it is geographically located for its first full or
partial FY with no cap applied because a new IPF would not have a wage
index in the prior FY. We amended the IPF PPS regulations at Sec.
412.424(d)(1)(i) to reflect this permanent cap on wage index decreases.
We refer readers to the FY 2023 IPF PPS final rule for a more detailed
discussion about this policy.
We are proposing to apply the IPF wage index adjustment to the
labor-related share of the national IPF PPS base rate and ECT payment
per treatment. The proposed labor-related share of the IPF PPS national
base rate and ECT payment per treatment is 78.8 percent in FY 2025.
This percentage reflects the labor-related share of the 2021-based IPF
market basket for FY 2025 and is 0.1 percentage point higher than the
FY 2024 labor-related share (see section III.A.3 of this proposed
rule).
b. Office of Management and Budget (OMB) Bulletins
(1) Background
The wage index used for the IPF PPS is calculated using the
unadjusted, pre-reclassified and pre-floor IPPS wage index data and is
assigned to the IPF based on the labor market area in which the IPF is
geographically located. IPF labor market areas are delineated based on
the Core-Based Statistical Area (CBSAs) established by the OMB.
Generally, OMB issues major revisions to statistical areas every 10
years, based on the results of the decennial census. However, OMB
occasionally issues minor updates and revisions to statistical areas in
the years between the decennial censuses through OMB Bulletins. These
bulletins contain information regarding CBSA changes, including changes
to CBSA numbers and titles. OMB bulletins may be accessed online at
https://www.whitehouse.gov/omb/information-for-agencies/bulletins/. In
accordance with our established methodology, the IPF PPS has
historically adopted any CBSA changes that are published in the OMB
bulletin that corresponds with the IPPS hospital wage index used to
determine the IPF wage index and, when necessary and appropriate, has
proposed and finalized transition policies for these changes.
In the RY 2007 IPF PPS final rule (71 FR 27061 through 27067), we
adopted the changes discussed in the OMB Bulletin No. 03-04 (June 6,
2003), which announced revised definitions for Metropolitan Statistical
Areas (MSAs), and the creation of Micropolitan Statistical Areas and
Combined Statistical Areas. In adopting the OMB CBSA geographic
designations in RY 2007, we did not provide a separate transition for
the CBSA-based wage index since the IPF PPS was already in a transition
period from TEFRA payments to PPS payments.
In the RY 2009 IPF PPS notice, we incorporated the CBSA
nomenclature changes published in the most recent OMB bulletin that
applied to the IPPS hospital wage index used to determine the current
IPF wage index and stated that we expected to continue to do the same
for all the OMB CBSA nomenclature changes in future IPF PPS rules and
notices, as necessary (73 FR 25721).
Subsequently, CMS adopted the changes that were published in past
OMB bulletins in the FY 2016 IPF PPS final rule (80 FR 46682 through
46689), the FY 2018 IPF PPS rate update (82 FR 36778 through 36779),
the FY 2020 IPF PPS final rule (84 FR 38453 through 38454), and the FY
2021 IPF PPS final rule (85 FR 47051 through 47059). We direct readers
to each of these rules for more information about the changes that were
adopted and any associated transition policies.
As discussed in the FY 2023 IPF PPS final rule, we did not adopt
OMB Bulletin 20-01, which was issued March 6, 2020, because we
determined this bulletin had no material impact on
[[Page 23174]]
the IPF PPS wage index. This bulletin creates only one Micropolitan
statistical area, and Micropolitan areas are considered rural for the
IPF PPS wage index. That is, the constituent county of the new
Micropolitan area was considered rural effective as of FY 2021 and
would continue to be considered rural if we adopted OMB Bulletin 20-01.
Finally, on July 21, 2023, OMB issued Bulletin 23-01, which revises
the CBSA delineations based on the latest available data from the 2020
census. This bulletin contains information regarding updates of
statistical area changes to CBSA titles, numbers, and county or county
equivalents.
(2) Proposed Implementation of New Labor Market Area Delineations
We believe it is important for the IPF PPS to use, as soon as is
reasonably possible, the latest available labor market area
delineations to maintain a more accurate and up-to-date payment system
that reflects the reality of population shifts and labor market
conditions. We believe that using the most current delineations would
increase the integrity of the IPF PPS wage index system by creating a
more accurate representation of geographic variations in wage levels.
We have carefully analyzed the impacts of adopting the new OMB
delineations and find no compelling reason to delay implementation.
Therefore, we are proposing to implement the new OMB delineations as
described in the July 21, 2023, OMB Bulletin No. 23-01, effective
beginning with the FY 2025 IPF PPS wage index. We are proposing to
adopt the updates to the OMB delineations announced in OMB Bulletin No.
23-01 effective for FY 2025 under the IPF PPS.
As previously discussed, we finalized a 5-percent permanent cap on
any decrease to a provider's wage index from its wage index in the
prior year. For more information on the permanent 5-percent cap policy,
we refer readers to the FY 2023 IPF PPS final rule (87 FR 46856 through
46859). In addition, we are proposing to phase out the rural adjustment
for IPFs that are transitioning from rural to urban based on these CBSA
revisions, as discussed in section III.D.1.c. of this proposed rule.
(a) Micropolitan Statistical Areas
OMB defines a ``Micropolitan Statistical Area'' as a CBSA
associated with at least one urban cluster that has a population of at
least 10,000, but less than 50,000 (75 FR 37252). We refer to these as
Micropolitan Areas. After extensive impact analysis, consistent with
the treatment of these areas under the IPPS as discussed in the FY 2005
IPPS final rule (69 FR 49029 through 49032), we determined the best
course of action would be to treat Micropolitan Areas as ``rural'' and
include them in the calculation of each state's IPF PPS rural wage
index. We refer readers to the FY 2007 IPF PPS final rule (71 FR 27064
through 27065) for a complete discussion regarding treating
Micropolitan Areas as rural. We are not proposing any changes to this
policy for FY 2025.
(b) Change to County-Equivalents in the State of Connecticut
The June 6, 2022 Census Bureau Notice (87 FR 34235 through 34240),
OMB Bulletin No. 23-01 replaced the 8 counties in Connecticut with 9
new ``Planning Regions.'' Planning regions now serve as county-
equivalents within the CBSA system. We have evaluated the changes and
are proposing to adopt the planning regions as county equivalents for
wage index purposes. We believe it is necessary to adopt this migration
from counties to planning region county-equivalents to maintain
consistency with OMB updates. We are providing the following crosswalk
for each county in Connecticut with the current and proposed FIPS
county and county-equivalent codes and CBSA assignments.
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(c) Urban Counties That Would Become Rural Under the Revised OMB
Delineations
As previously discussed, we are proposing to implement the new OMB
labor market area delineations (based upon OMB Bulletin No. 23-01)
beginning in FY 2025. Our analysis shows that a total of 53 counties
(and county equivalents) and 15 providers are located in areas that
were previously considered part of an urban CBSA but would be
considered rural beginning in FY 2025 under these revised OMB
delineations. Table 12 lists the 53 urban counties that would be rural
if we finalize our proposal to implement the revised OMB delineations.
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We are proposing that the wage data for all providers located in
the counties listed above would now be considered rural, beginning in
FY 2025, when calculating their respective state's rural wage index.
This rural wage index value would also be used under the IPF PPS. We
recognize that rural areas typically have lower area wage index values
than urban areas, and providers located in these counties may
experience a negative impact in their IPF payment due to the proposed
adoption of the revised OMB delineations. However, as discussed in
section III.D.1.c of this proposed rule, providers located in these
counties would receive a rural adjustment beginning in FY 2025, which
would mitigate the impact of decreases to the wage index for these
providers. In addition, the permanent 5-percent cap on wage index
decreases under the IPF PPS would further mitigate large wage index
decreases for providers in these areas.
(d) Rural Counties That Would Become Urban Under the Revised OMB
Delineations
As previously discussed, we are proposing to implement the new OMB
labor market area delineations (based upon OMB Bulletin No. 23-01)
beginning in FY 2025. Analysis of these OMB labor market area
delineations shows that a total of 54 counties (and county equivalents)
and 10 providers are located in areas that were previously considered
rural but would now be considered urban under the revised OMB
delineations. Table 13 lists the 54 rural counties that would be urban
if we finalize our proposal to implement the revised OMB delineations.
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We are proposing that when calculating the area wage index,
beginning with FY 2025, the wage data for providers located in these
counties would be included in their new respective urban CBSAs.
Typically, providers located in an urban area receive a wage index
value higher than or equal to providers located in their state's rural
area. We also note that providers located in these areas would no
longer be considered rural beginning in FY 2025. We refer readers to
section III.D.1.c of this proposed rule for a discussion of the
proposed policy to phase out the payment of the rural adjustment for
providers in these areas.
(e) Urban Counties That Would Move to a Different Urban CBSA Under the
New OMB Delineations
In certain cases, adopting the new OMB delineations would involve a
change only in CBSA name and/or number, while the CBSA continues to
encompass the same constituent counties. For example, CBSA 10540
(Albany-Lebanon, OR) would experience a change to its name, and become
CBSA 10540 (Albany, OR), while its one constituent county would remain
the same. Table 14 shows the current CBSA code and our proposed CBSA
code where we are proposing to change either the name or CBSA number
only. We are not discussing further in this section these proposed
changes because they are inconsequential changes with respect to the
IPF PPS wage index.
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In some cases, if we adopt the new OMB delineations, counties would
shift between existing and new CBSAs, changing the constituent makeup
of the CBSAs. We consider this type of change, where CBSAs are split
into multiple new CBSAs, or a CBSA loses one or more counties to
another urban CBSA to be significant modifications.
[[Page 23181]]
Table 15 lists the urban counties that would move from one urban
CBSA to another newly proposed or modified CBSA if we adopted the new
OMB delineations.
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We have identified 68 IPF providers located in the affected
counties listed in Table 15. If providers located in these counties
move from one CBSA to another under the revised OMB delineations, there
may be impacts, either negative or positive, upon their specific wage
index values.
c. Proposed Adjustment for Rural Location
In the RY 2005 IPF PPS final rule, (69 FR 66954), we provided a 17-
percent payment adjustment for IPFs located in a rural area. This
adjustment was based on the regression analysis, which indicated that
the per diem cost of rural facilities was 17-percent higher than that
of urban facilities after accounting for the influence of the other
variables included in the regression. This 17-percent adjustment has
been part of the IPF PPS each year since the inception of the IPF PPS.
As discussed earlier in this rule, we are proposing a number of
revisions to the patient-level adjustment factors as well as changes to
the CBSA
[[Page 23188]]
delineations. In order to minimize the scope of changes that would
impact providers in any single year, we are proposing to use the
existing regression-derived adjustment factor, which was established in
RY 2005, for FY 2025 for IPFs located in a rural area as defined at
Sec. 412.64(b)(1)(ii)(C). See 69 FR 66954 for a complete discussion of
the adjustment for rural locations. However, as discussed in the
section IV.A of this FY 2025 IPF PPS proposed rule, we have completed
analysis of more recent cost and claims information and are soliciting
comments on those results.
As proposed earlier in this proposed rule, the adoption of OMB
Bulletin No. 23-01 in accordance with our established methodology would
determine whether a facility is classified as urban or rural for
purposes of the rural payment adjustment in the IPF PPS. Overall, we
believe implementing updated OMB delineations would result in the rural
payment adjustment being applied where it is appropriate to adjust for
higher costs incurred by IPFs in rural locations. However, we recognize
that implementing these changes would have distributional effects among
IPF providers, and that some providers would experience a loss of the
rural payment adjustment because of our proposals. Therefore, we
believe it would be appropriate to consider, as we have in the past,
whether a transition period should be used to implement these proposed
changes.
Prior changes to the CBSA delineations have included a phase-out
policy for the rural adjustment for IPFs transitioning from rural to
urban status. On February 28, 2013, OMB issued OMB Bulletin No. 13-01,
which 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. We
adopted these new OMB CBSA delineations in the FY 2016 IPF final rule
(80 FR 46682 through 46689), and identified 105 counties and 37 IPFs
that would move from rural to urban status due to the new CBSA
delineations. To reduce the impact of the loss of the 17-percent rural
adjustment, we adopted a budget-neutral 3-year phase-out of the rural
adjustment for existing FY 2015 rural IPFs that became urban in FY 2016
and that experienced a loss in payments due to changes from the new
CBSA delineations. These IPFs received two-thirds of the rural
adjustment for FY 2016 and one-third of the rural adjustment in FY
2017. For FY 2018, these IPFs did not receive a rural adjustment.
For subsequent adoptions of OMB Bulletin No. 15-01 for FY 2018 (82
FR 36779 through 36780), OMB Bulletin 17-01 for FY 2020 (84 FR 38453
through 38454), and OMB Bulletin 18-04 for FY 2021 (85 FR 47053 through
47059), we identified that fewer providers were affected by these
changes than by the changes relating to the adoption of OMB Bulletin
13-01. We did not phase out the rural adjustment when adopting these
delineation changes.
For facilities located in a county that transitioned from rural to
urban in Bulletin 23-01, we considered whether it would be appropriate
to phase out the rural adjustment for affected providers consistent
with our past practice of using transition policies to help mitigate
negative impacts on hospitals of OMB Bulletin proposals that have a
material effect on a number of IPFs. Adoption of the updated CBSAs in
Bulletin 23-01 will change the status of 10 IPF providers currently
designated as ``rural'' to ``urban'' for FY 2025 and subsequent fiscal
years. As such, these 10 newly urban providers will no longer receive
the 17-percent rural adjustment. Consistent with the transition policy
adopted for IPFs in FY 2016 (80 FR 46682 through 4668980 FR 46682
through 46689), we are proposing a 3-year budget neutral phase-out of
the rural adjustment for IPFs located in the 54 rural counties that
will become urban under the new OMB delineations, given the potentially
significant payment impacts for these IPFs. We believe that a phase-out
of the rural adjustment transition period for these 10 IPFs
specifically is appropriate because we expect these IPFs will
experience a steeper and more abrupt reduction in their payments
compared to other IPFs. Therefore, we are proposing to phase out the
rural adjustment for these providers to reduce the impact of the loss
of the FY 2024 rural adjustment of 17-percent over FYs 2025, 2026, and
2027. This policy would allow IPFs that are classified as rural in FY
2024 and would be classified as urban in FY 2025 to receive two-thirds
of the rural adjustment for FY 2025. For FY 2026, these IPFs would
receive one-third of the rural adjustment. For FY 2027, these IPFs
would not receive a rural adjustment. We believe a 3-year budget-
neutral phase-out of the rural adjustment for IPFs that transition from
rural to urban status under the new CBSA delineations would best
accomplish the goals of mitigating the loss of the rural adjustment for
existing FY 2024 rural IPFs. The purpose of the gradual phase-out of
the rural adjustment for these providers is to mitigate potential
payment reductions and promote stability and predictability in payments
for existing rural IPFs that may need time to adjust to the loss of
their FY 2024 rural payment adjustment or that experience a reduction
in payments solely because of this re-designation. This policy would be
specifically for rural IPFs that become urban in FY 2025. We are not
proposing a transition policy for urban IPFs that become rural in FY
2025 because these IPFs will receive the full rural adjustment of 17-
percent beginning October 1, 2024. We solicit comments on this proposed
policy.
d. Proposed Wage Index Budget Neutrality Adjustment
Changes to the wage index are made in a budget neutral manner so
that updates do not increase expenditures. Therefore, for FY 2025, we
are proposing to continue to apply a budget neutrality adjustment in
accordance with our existing budget neutrality policy. This policy
requires us to update the wage index in such a way that total estimated
payments to IPFs for FY 2025 are the same with or without the changes
(that is, in a budget neutral manner) by applying a budget neutrality
factor to the IPF PPS rates. We are proposing to use the following
steps to ensure that the rates reflect the FY 2025 update to the wage
indexes (based on the FY 2021 hospital cost report data) and the labor-
related share in a budget neutral manner:
Step 1: Simulate estimated IPF PPS payments, using the FY 2024 IPF
wage index values (available on the CMS website) and labor-related
share (as published in the FY 2024 IPF PPS final rule (88 FR 51054).
Step 2: Simulate estimated IPF PPS payments using the proposed FY
2025 IPF wage index values (available on the CMS website), and the
proposed FY 2025 labor-related share (based on the latest available
data as discussed previously).
Step 3: Divide the amount calculated in step 1 by the amount
calculated in step 2. The resulting quotient is the proposed FY 2025
budget neutral wage adjustment factor of 0.9995.
Step 4: Apply the FY 2025 budget neutral wage adjustment factor
from step 3 to the FY 2024 IPF PPS Federal per diem base rate after the
application of the IPF market basket increase reduced by the
productivity adjustment described in section III.A of this proposed
rule to determine the FY 2025 IPF PPS Federal per diem base rate. As
discussed in section III.F of this proposed rule, we are also proposing
to apply a refinement standardization
[[Page 23189]]
factor to determine the FY 2025 IPF PPS Federal per diem base rate.
2. Proposed Teaching Adjustment
Background
In the RY 2005 IPF PPS final rule, we implemented regulations at
Sec. 412.424(d)(1)(iii) to establish a facility-level adjustment for
IPFs that are, or are part of, teaching hospitals. The teaching
adjustment accounts for the higher indirect operating costs experienced
by hospitals that participate in graduate medical education (GME)
programs. The payment adjustments are made based on the ratio of the
number of fulltime equivalent (FTE) interns and residents training in
the IPF and the IPF's average daily census.
Medicare makes direct GME payments (for direct costs such as
resident and teaching physician salaries, and other direct teaching
costs) to all teaching hospitals including those paid under a PPS and
those paid under the TEFRA rate-of-increase limits. These direct GME
payments are made separately from payments for hospital operating costs
and are not part of the IPF PPS. The direct GME payments do not address
the estimated higher indirect operating costs teaching hospitals may
face.
The results of the regression analysis of FY 2002 IPF data
established the basis for the payment adjustments included in the RY
2005 IPF PPS final rule. The results showed that the indirect teaching
cost variable is significant in explaining the higher costs of IPFs
that have teaching programs. We calculated the teaching adjustment
based on the IPF's ``teaching variable,'' which is (1 + [the number of
FTE residents training in the IPF's average daily census]). The
teaching variable is then raised to the 0.5150 power to result in the
teaching adjustment. This formula is subject to the limitations on the
number of FTE residents, which are described in this section of this
proposed rule.
We established the teaching adjustment in a manner that limited the
incentives for IPFs to add FTE residents for the purpose of increasing
their teaching adjustment. We imposed a cap on the number of FTE
residents that may be counted for purposes of calculating the teaching
adjustment. The cap limits the number of FTE residents that teaching
IPFs may count for the purpose of calculating the IPF PPS teaching
adjustment, not the number of residents teaching institutions can hire
or train. We calculated the number of FTE residents that trained in the
IPF during a ``base year'' and used that FTE resident number as the
cap. An IPF's FTE resident cap is ultimately determined based on the
final settlement of the IPF's most recent cost report filed before
November 15, 2004 (69 FR 66955). A complete discussion of the temporary
adjustment to the FTE cap to reflect residents due to hospital closure
or residency program closure appears in the RY 2012 IPF PPS proposed
rule (76 FR 5018 through 5020) and the RY 2012 IPF PPS final rule (76
FR 26453 through 26456).
In the regression analysis that informed the FY 2004 IPF PPS final
rule, the logarithm of the teaching variable had a coefficient value of
0.5150. We converted this cost effect to a teaching payment adjustment
by treating the regression coefficient as an exponent and raising the
teaching variable to a power equal to the coefficient value. We note
that the coefficient value of 0.5150 was based on the regression
analysis holding all other components of the payment system constant. A
complete discussion of how the teaching adjustment was calculated
appears in the RY 2005 IPF PPS final rule (69 FR 66954 through 66957)
and the RY 2009 IPF PPS notice (73 FR 25721).
We are proposing to retain the coefficient value of 0.5150 for the
teaching adjustment to the Federal per diem base rate as we are not
proposing refinements to the facility-level payment adjustments for
rural location or teaching status for FY 2025. As noted earlier, given
the scope of changes to the wage index and patient-level adjustment
factors, we believe this will minimize the total impacts to providers
in any given year.
3. Proposed Cost of Living Adjustment for IPFs Located in Alaska and
Hawaii
The IPF PPS includes a payment adjustment for IPFs located in
Alaska and Hawaii based upon the area in which the IPF is located. As
we explained in the RY 2005 IPF PPS final rule, the FY 2002 data
demonstrated that IPFs in Alaska and Hawaii had per diem costs that
were disproportionately higher than other IPFs. As a result of this
analysis, we provided a COLA in the RY 2005 IPF PPS final rule. We
refer readers to the FY 2024 IPF PPS final rule for a complete
discussion of the currently applicable COLA factors (88 FR 51088
through 51089).
We adopted a new methodology to update the COLA factors for Alaska
and Hawaii for the IPF PPS in the FY 2015 IPF PPS final rule (79 FR
45958 through 45960). For a complete discussion, we refer readers to
the FY 2015 IPF PPS final rule.
We also specified that the COLA updates would be determined every 4
years, in alignment with the IPPS market basket labor-related share
update (79 FR 45958 through 45960). Because the labor-related share of
the IPPS market basket was updated for FY 2022, the COLA factors were
updated in FY 2022 IPPS/LTCH rulemaking (86 FR 45547). As such, we also
finalized an update to the IPF PPS COLA factors to reflect the updated
COLA factors finalized in the FY 2022 IPPS/LTCH rulemaking effective
for FY 2022 through FY 2025 (86 FR 42621 through 42622). This is
reflected in Table 16 below. We are proposing to maintain the COLA
factors in Table 16 for FY 2025 in alignment with the policy described
in this paragraph.
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The proposed IPF PPS COLA factors for FY 2025 are also shown in
Addendum A to this proposed rule, which is available on the CMS website
at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/InpatientPsychFacilPPS/tools.html.
4. Proposed Adjustment for IPFs With a Qualifying ED
The IPF PPS includes a facility-level adjustment for IPFs with
qualifying EDs. As defined in Sec. 412.402, qualifying emergency
department means an emergency department that is staffed and equipped
to furnish a comprehensive array of emergency services and meets the
requirements of 42 CFR 489.24(b) and Sec. 413.65.
We provide an adjustment to the Federal per diem base rate to
account for the costs associated with maintaining a full-service ED.
The adjustment is intended to account for ED costs incurred by a
psychiatric hospital with a qualifying ED, or an excluded psychiatric
unit of an IPPS hospital or a critical access hospital (CAH), and the
overhead cost of maintaining the ED. This payment applies to all IPF
admissions (with one exception which we describe in this section),
regardless of whether the patient was admitted through the ED. The ED
adjustment is made on every qualifying claim except as described in
this section of this proposed rule. As specified at Sec.
412.424(d)(1)(v)(B), the ED adjustment is not made when a patient is
discharged from an IPPS hospital or CAH, and admitted to the same IPPS
hospital's or CAH's excluded psychiatric unit. We clarified in the RY
2005 IPF PPS final rule (69 FR 66960) that an ED adjustment is not made
in this case because the costs associated with ED services are
reflected in the DRG payment to the IPPS hospital or through the
reasonable cost payment made to the CAH.
a. Proposed Update for FY 2025
For FY 2025, we are proposing to update the adjustment factor from
1.31 to 1.53 for IPFs with qualifying EDs using the same methodology
used to determine ED adjustments in prior years. Thus, we are proposing
to use the following steps, as used in prior years, to calculate the
updated ED adjustment factor. (A complete discussion of the steps
involved in the calculation of the ED adjustment factors can be found
in the RY 2005 IPF PPS final rule (69 FR 66959 through 66960) and the
RY 2007 IPF PPS final rule (71 FR 27070 through 27072).)
Step 1: Estimate the proportion by which the ED costs of a stay
would increase the cost of the first day of the stay. Using the IPFs
with ED admissions in years 2019 through 2021, we divided the average
ED cost per stay when admitted through the ED ($519.97) by the average
cost per day ($1,338.93), which equals 0.39.
Step 2: Adjust the factor estimated in step 1 to account for the
fact that we would pay the higher first day adjustment for all cases in
the qualifying IPFs, not just the cases admitted through the ED. Since
on average, 66 percent of the cases in IPFs with ED admissions are
admitted through the ED, we multiplied 0.39 by 0.66, which equals 0.26.
Step 3: Add the adjusted factor calculated in the previous 2 steps
to the variable per diem adjustment derived from the regression
equation that we used to derive our other payment adjustment factors.
As discussed in section III.C.4.d. of this proposed rule, the proposed
first day payment factor for FY 2025 is 1.27. Adding 0.26, we obtained
a first day variable per adjustment for IPFs with a qualifying ED equal
to 1.53.
The ED adjustment is incorporated into the variable per diem
adjustment for the first day of each stay for IPFs with a qualifying
ED. We are proposing that those IPFs with a qualifying ED would receive
an adjustment factor of 1.53 as the variable per diem adjustment for
day 1 of each patient stay. If an IPF does not have a qualifying ED, we
are proposing that it would receive an adjustment factor of 1.27 as the
variable per diem adjustment for day 1 of each patient stay, as
discussed in section III.C.4.d. of this proposed rule. As discussed in
section III.F of this proposed rule, we are proposing to implement this
revision to the ED adjustment budget--neutrally by applying a
refinement standardization factor. A detailed discussion of the
distributional impacts of this proposed change is found in section
VIII.C of this proposed rule.
We solicit comment on this proposal. Lastly, we are proposing that
if more recent data become available, we would use such data, if
appropriate, to determine the FY 2025 ED adjustment factor.
b. Alternatives Considered
In response to the FY 2023 IPF PPS proposed rule (87 FR 19428
through 19429) comment solicitation on our technical report describing
the analysis of IPF PPS adjustments, two
[[Page 23191]]
commenters requested that we conduct further analysis related to the
exception for the ED adjustment. These commenters indicated that
patients transferred to an IPF from an acute care unit or hospital
often have higher costs per stay than patients with similar
comorbidities admitted from the community. Commenters requested that
CMS analyze data related to source of admission and consider a payment
adjustment to account for the resources used by these patients. In
response to these comments, we conducted a regression analysis to
investigate whether the source of admission is a statistically
significant variable in the cost of a patient's care in an IPF. We
analyzed the following sources of admission: clinic referral, transfer
from hospital (different facility), transfer from a SNF or Intermediate
Care Facility (ICF), transfer from another health care facility, court/
law enforcement, information not available, transfer from hospital
inpatient in the same facility, transfer from ambulatory surgical
center, and transfer from hospice. In this context, it is important to
note that the source of admission indicator ``court/law enforcement''
is not the equivalent of an involuntary admission; we do not currently
collect data on involuntary admissions.
The regression analysis found that the source of admission was not
a statistically significant factor in the cost of care. The results for
the two source of admission variables that indicate higher costs
(transfer from hospital inpatient in the same facility and transfer
from ambulatory surgical center) are accounted for by the known
difference in cost structures between hospital psychiatric units and
freestanding psychiatric hospitals. We considered the results of our
analysis, as well as the potential that adjusting payment based on
source of admission could inadvertently create incentives for IPFs to
prioritize certain admissions over others. Based on these
considerations, we are not proposing to add additional payment
adjustments based on source of admission (other than the existing
adjustment for a qualifying ED) to the IPF PPS in FY 2025.
E. Other Proposed Payment Adjustments and Policies
1. Outlier Payment Overview
The IPF PPS includes an outlier adjustment to promote access to IPF
care for those patients who require expensive care and to limit the
financial risk of IPFs treating unusually costly patients. In the RY
2005 IPF PPS final rule, we implemented regulations at Sec.
412.424(d)(3)(i) to provide a per case payment for IPF stays that are
extraordinarily costly. Providing additional payments to IPFs for
extremely costly cases strongly improves the accuracy of the IPF PPS in
determining resource costs at the patient and facility level. These
additional payments reduce the financial losses that would otherwise be
incurred in treating patients who require costlier care; therefore,
reduce the incentives for IPFs to under-serve these patients. We make
outlier payments for discharges in which an IPF's estimated total cost
for a case exceeds a fixed dollar loss threshold amount (multiplied by
the IPF's facility-level adjustments) plus the federal per diem payment
amount for the case.
In instances when the case qualifies for an outlier payment, we pay
80 percent of the difference between the estimated cost for the case
and the adjusted threshold amount for days 1 through 9 of the stay
(consistent with the median LOS for IPFs in FY 2002), and 60 percent of
the difference for day 10 and thereafter. The adjusted threshold amount
is equal to the outlier threshold amount adjusted for wage area,
teaching status, rural area, and the COLA adjustment (if applicable),
plus the amount of the Medicare IPF payment for the case. We
established the 80 percent and 60 percent loss sharing ratios because
we were concerned that a single ratio established at 80 percent (like
other Medicare PPSs) might provide an incentive under the IPF per diem
payment system to increase LOS to receive additional payments.
After establishing the loss sharing ratios, we determined the
current fixed dollar loss threshold amount through payment simulations
designed to compute a dollar loss beyond which payments are estimated
to meet the 2 percent outlier spending target. Each year when we update
the IPF PPS, we simulate payments using the latest available data to
compute the fixed dollar loss threshold so that outlier payments
represent 2 percent of total estimated IPF PPS payments.
2. Proposed Update to the Outlier Fixed Dollar Loss Threshold Amount
In accordance with the update methodology described in Sec.
412.428(d), we are proposing to update the fixed dollar loss threshold
amount used under the IPF PPS outlier policy. Based on the regression
analysis and payment simulations used to develop the IPF PPS, we
established a 2 percent outlier policy, which strikes an appropriate
balance between protecting IPFs from extraordinarily costly cases while
ensuring the adequacy of the federal per diem base rate for all other
cases that are not outlier cases. We are proposing to maintain the
established 2 percent outlier policy for FY 2025.
Our longstanding methodology for updating the outlier fixed dollar
loss threshold involves using the best available data, which is
typically the most recent available data. We note that for FY 2022 and
FY 2023 only, we made certain methodological changes to our modeling of
outlier payments, and we discussed the specific circumstances that led
to those changes for those years (86 FR 42623 through 42624; 87 FR
46862 through 46864). We direct readers to the FY 2022 and FY 2023 IPF
PPS proposed and final rules for a more complete discussion.
We are proposing to update the IPF outlier threshold amount for FY
2025 using FY 2023 claims data and the same methodology that we have
used to set the initial outlier threshold amount each year beginning
with the RY 2007 IPF PPS final rule (71 FR 27072 and 27073). For this
FY 2025 IPF PPS rulemaking, consistent with our longstanding practice,
based on an analysis of the latest available data (the December 2023
update of FY 2023 IPF claims) and rate increases, we believe it is
necessary to update the fixed dollar loss threshold amount to maintain
an outlier percentage that equals 2 percent of total estimated IPF PPS
payments. Based on an analysis of these updated data, we estimate that
IPF outlier payments as a percentage of total estimated payments are
approximately 2.1 percent in FY 2024. Therefore, we are proposing to
update the outlier threshold amount to $35,590 to maintain estimated
outlier payments at 2 percent of total estimated aggregate IPF payments
for FY 2025. This proposed rule update is an increase from the FY 2024
threshold of $33,470.
Lastly, we are proposing that if more recent data become available
for the FY 2025 IPF PPS final rule, we would use such data as
appropriate to determine the final outlier fixed dollar loss threshold
amount for FY 2025.
3. Proposed Update to IPF Cost-to-Charge Ratio Ceilings
Under the IPF PPS, an outlier payment is made if an IPF's cost for
a stay exceeds a fixed dollar loss threshold amount plus the IPF PPS
amount. To establish an IPF's cost for a particular case, we multiply
the IPF's reported charges on the discharge bill by its overall cost-
to-charge ratio (CCR). This approach to determining an IPF's cost is
consistent with the approach
[[Page 23192]]
used under the IPPS and other PPSs. In the FY 2004 IPPS final rule (68
FR 34494), we implemented changes to the IPPS policy used to determine
CCRs for IPPS hospitals, because we became aware that payment
vulnerabilities resulted in inappropriate outlier payments. Under the
IPPS, we established a statistical measure of accuracy for CCRs to
ensure that aberrant CCR data did not result in inappropriate outlier
payments.
As indicated in the RY 2005 IPF PPS final rule (69 FR 66961), we
believe that the IPF outlier policy is susceptible to the same payment
vulnerabilities as the IPPS; therefore, we adopted a method to ensure
the statistical accuracy of CCRs under the IPF PPS. Specifically, we
adopted the following procedure in the RY 2005 IPF PPS final rule:
Calculated two national ceilings, one for IPFs located in
rural areas and one for IPFs located in urban areas.
Computed the ceilings by first calculating the national
average and the standard deviation of the CCR for both urban and rural
IPFs using the most recent CCRs entered in the most recent Provider
Specific File (PSF) available.
For FY 2025, we are proposing to continue following this
methodology. To determine the rural and urban ceilings, we multiplied
each of the standard deviations by 3 and added the result to the
appropriate national CCR average (either rural or urban). The proposed
upper threshold CCR for IPFs in FY 2025 is 2.3362 for rural IPFs, and
1.8600 for urban IPFs, based on current CBSA-based geographic
designations. If an IPF's CCR is above the applicable ceiling, the
ratio is considered statistically inaccurate, and we assign the
appropriate national (either rural or urban) median CCR to the IPF.
We apply the national median CCRs to the following situations:
New IPFs that have not yet submitted their first Medicare
cost report. We continue to use these national median CCRs until the
facility's actual CCR can be computed using the first tentatively or
final settled cost report.
IPFs whose overall CCR is in excess of three standard
deviations above the corresponding national geometric mean (that is,
above the ceiling).
Other IPFs for which the Medicare Administrative
Contractor (MAC) obtains inaccurate or incomplete data with which to
calculate a CCR.
We are proposing to update the FY 2025 national median and ceiling
CCRs for urban and rural IPFs based on the CCRs entered in the latest
available IPF PPS PSF.
Specifically, for FY 2025, to be used in each of the three
situations listed previously, using the most recent CCRs entered in the
CY 2023 PSF, we provide an estimated national median CCR of 0.5720 for
rural IPFs and a national median CCR of 0.4200 for urban IPFs. These
calculations are based on the IPF's location (either urban or rural)
using the current CBSA-based geographic designations. A complete
discussion regarding the national median CCRs appears in the RY 2005
IPF PPS final rule (69 FR 66961 through 66964).
Lastly, we are proposing that if more recent data become available,
we would use such data to calculate the rural and urban national median
and ceiling CCRs for FY 2025.
4. Requirements for Reporting Ancillary Charges and All-Inclusive
Status Eligibility Under the IPF PPS
a. Background
As discussed in section III.E.4.b of this proposed rule, to analyze
variation in cost between patients with different characteristics, it
is crucial for us to have complete cost information about each patient,
including data on ancillary services provided. Currently, IPFs and
psychiatric units are required to report ancillary charges on cost
reports. As specified at 42 CFR 413.20, hospitals are required to file
cost reports on an annual basis and maintain sufficient financial
records and statistical data for proper determination of costs payable
under the Medicare program.
However, our ongoing analysis has found a notable increase in the
number of IPFs, specifically for-profit freestanding IPFs, that appear
to be erroneously identifying on form CMS-2552-10, Worksheet S-2, Part
I, line 115, as eligible for filing all-inclusive cost reports. These
hospitals identifying as eligible for filing all-inclusive cost reports
(indicating that they have one charge covering all services) are
consistently reporting no ancillary charges or very minimal ancillary
charges and are not using charge information to apportion costs in
their cost report. Generally, based on the nature of IPF services and
the conditions of participation applicable to IPFs, we expect to see
ancillary services and correlating charges, such as labs and drugs, on
most IPF claims.\3\
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\3\ IPFs are subject to all hospital conditions of
participation, including 42 CFR 482.25, which specifies that ``The
hospital must have pharmaceutical services that meet the needs of
the patients,'' and 482.27, which specifies that ``The hospital must
maintain, or have available, adequate laboratory services to meet
the needs of its patients.''
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In the FY 2016 IPF PPS final rule (80 FR 46693 through 46694), we
discussed analysis conducted to better understand IPF industry
practices for future IPF PPS refinements. This analysis revealed that
in 2012 to 2013, over 20 percent of IPF stays show no reported
ancillary charges, such as laboratory and drug charges, on claims. In
the FY 2016 IPF PPS final rule (80 FR 46694), FY 2017 IPF PPS final
rule (81 FR 50513), FY 2018 IPF PPS final rule (82 FR 36784), FY 2019
IPF PPS final rule (83 FR 38588), and FY 2020 IPF PPS final rule (84 FR
38458), we reminded providers that we only pay the IPF for services
furnished to a Medicare beneficiary who is an inpatient of that IPF,
except for certain professional services, and payments are considered
to be payments in full for all inpatient hospital services provided
directly or under arrangement (see 42 CFR 412.404(d)), as specified in
42 CFR 409.10.
On November 17, 2017, we issued Transmittal 12, which made changes
to the hospital cost report form CMS-2552-10 (OMB No. 0938-0050) and
included cost report level 1 edit 10710S, effective for cost reporting
periods ending on or after August 31, 2017. Edit 10710S required that
cost reports from psychiatric hospitals include certain ancillary costs
or the cost report will be rejected. On January 30, 2018, we issued
Transmittal 13, which changed the implementation date for Transmittal
12 to be for cost reporting periods ending on or after September 30,
2017. CMS suspended edit 10710S effective April 27, 2018, pending
evaluation of the application of the edit to all-inclusive rate
providers. We issued Transmittal 15 on October 19, 2018, reinstating
the requirement that cost reports from psychiatric hospitals, except
all-inclusive rate providers, include certain ancillary costs. This
requirement is still currently in place. For details, we refer readers
to see these Transmittals, which are available on the CMS website at
https://www.cms.gov/medicare/regulations-guidance/transmittals.
Under IPF PPS regulations at 42 CFR 412.404(e), all inpatient
psychiatric facilities paid under the IPF PPS must meet the
recordkeeping and cost reporting requirements as specified at Sec.
413.24. Historically, in accordance with Sec. 413.24(a)(1), most
hospitals that were approved to file all-inclusive cost reports were
Indian Health Services (IHS) hospitals, government-owned psychiatric
and acute care hospitals, and nominal charge hospitals. Although IPFs
are no longer reimbursed on the basis of reasonable costs, we continue
to expect that most IPFs, other than government-owned or tribally owned
[[Page 23193]]
IPFs, should report cost data that is based on an approved method of
cost finding and on the accrual basis of accounting. The option to
elect to file an all-inclusive rate cost report is limited to providers
that do not have a charge structure and that, therefore, must use an
alternative statistic to apportion costs associated with services
rendered to Medicare beneficiaries.
Current cost reporting rules allow hospitals that do not have a
charge structure to file an all-inclusive cost report using an
alternative cost allocation method. We refer readers to the Provider
Reimbursement Manual (PRM) 15-1; chapter 22, Sec. 2208 for detailed
information on the requirements to file an alternative method.
b. Challenges Related to Missing IPF Ancillary Cost Data
In general, most providers allocate their Medicare costs using
costs and charges as described at Sec. 413.53(a)(1)(i) and referred to
as the Departmental Method, which is the ratio of beneficiary charges
to total patient charges for the services of each ancillary department.
For cost reporting periods beginning on or after October 1, 1982, the
cost report uses the Departmental Method to apportion the cost of the
department to the Medicare program. Added to this amount is the cost of
routine services for Medicare beneficiaries, determined based on a
separate average cost per diem for all patients for general routine
patient care areas as required at Sec. 413.53(a)(1)(i) and (e); and
15-1, chapter 22, Sec. 2200.1.\4\
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\4\ IPFs are subject to all hospital conditions of
participation, including 42 CFR 482.25, which specifies that ``The
hospital must have pharmaceutical services that meet the needs of
the patients,'' and 482.27, which specifies that ``The hospital must
maintain, or have available, adequate laboratory services to meet
the needs of its patients.''
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We use cost-to-charge ratios (CCRs) from Medicare cost reports as
the method of establishing reasonable costs for hospital services and
as the basis for ratesetting for several hospital prospective payment
systems. In general, detailed ancillary cost and charge information is
necessary for accurate Medicare ratesetting. When hospitals identify as
all-inclusive, they are excluded from ratesetting because they do not
have CCRs but use an alternative basis for apportioning costs. When
hospitals erroneously identify as all-inclusive but have a charge
structure, data that is necessary for accurate Medicare ratesetting is
improperly excluded.
Since the issuance of Transmittal 15, we have continued to identify
an increase in the number of IPFs, specifically for-profit freestanding
IPFs, that appear to be erroneously identifying on form CMS- 2552-10,
Worksheet S-2, Part I, line 115, as filing all-inclusive cost reports.
In conjunction with the FY 2023 IPF PPS proposed rule (87 FR 19428
through 19429), we posted a report on the CMS website that summarizes
the results of the latest analysis of more recent IPF cost and claim
information for potential IPF PPS adjustments and requested comments
about the results summarized in the report. The report showed that
approximately 23 percent of IPF stays were trimmed from the data set
used in that analysis because they were stays at facilities where fewer
than 5 percent of their stays had ancillary charges. The report is
available on the CMS website at https://www.cms.gov/medicare/payment/prospective-payment-systems/inpatient-psychiatric-facility/ipf-reports-and-educational-resources.
Section 4125 of the CAA, 2023 authorizes the Secretary to collect
data and information, specifically including charges related to
ancillary services, as appropriate to inform revisions to the IPF PPS.
In the FY 2024 IPF PPS proposed rule (88 FR 21270 through 21272),
we included a request for information (RFI) related to the reporting of
charges for ancillary services, such as labs and drugs, on IPF claims.
We were interested in better understanding IPF industry practices
pertaining to the billing and provision of ancillary services to inform
statutorily mandated IPF PPS refinements. We stated that we were
considering whether to require charges for ancillary services to be
reported on claims and potentially reject claims if no ancillary
services are reported, and whether to consider payment for such claims
to be inappropriate or erroneous and subject to recoupment.
In response to the comment solicitation, we received a comment from
MedPAC regarding facilities that do not report ancillary charges on
most or any of their claims. MedPAC stated that it is not known:
whether IPFs fail to report ancillary charges separately because they
were appropriately bundled with all other charges into an all-inclusive
per diem rate; if no ancillary charges were incurred because the IPF
cares for a patient mix with lower care needs or inappropriately fails
to furnish the kinds of care reflected in ancillary charges when
medically necessary; or if ancillary charges for services furnished
during the IPF stay are inappropriately billed outside of the IPF base
rate (unbundling). MedPAC recommended CMS conduct further investigation
into the lack of certain ancillary charges and whether IPFs are
providing necessary care and appropriately billing for inpatient
psychiatric services under the IPF PPS.
MedPAC also encouraged CMS to require the reporting of ancillary
charges and clarify the requirements related to IPFs' ``all-inclusive-
rate'' hospital status. MedPAC noted that it observed in cost report
data that IPFs that previously were not all-inclusive-rate hospitals
have recently changed to an all-inclusive-rate status. MedPAC noted
that the timing of many of these changes appears to correspond to CMS's
transmittals requiring ancillary services to be reported on cost
reports for IPFs that do not have an all-inclusive rate.
Other commenters, including IPFs and hospital associations,
responded to the RFI stating that the lack of ancillary charges on
claims does not indicate a lack of services being provided. The
commenters strongly opposed any claim-level editing and stated that
reporting ancillary charges at the claim level would be inefficient and
burdensome, particularly for government and IHS all-inclusive
hospitals.
c. Clarification of Eligibility Criteria for the Option To Elect To
File an All-Inclusive Cost Report
After taking into consideration the feedback we received from both
MedPAC and IPF providers, for FY 2025 we are clarifying the eligibility
criteria to be approved to file all-inclusive cost reports. Only
government-owned or tribally owned facilities are able to satisfy these
criteria, and thus only these facilities will be permitted to file an
all-inclusive cost report for cost reporting periods beginning on or
after October 1, 2024.
We remind readers that in order to be approved to file an all-
inclusive cost report, hospitals must either have an all-inclusive rate
(one charge covering all services) or a no-charge structure.\5\ We are
clarifying that this does not mean any hospital can elect to have an
all-inclusive rate or no-charge structure. Our longstanding policy as
discussed in the PRM 15-1, chapter 22, Sec. 2208.1, only allows a
hospital to use an all-inclusive rate or no charge structure if it has
never had a charge structure in place. In addition, we are clarifying
that our expectation is that any new IPF would have the ability to have
a charge structure under which it could allocate
[[Page 23194]]
costs and charges. As previously stated, only a government-owned or
tribally owned facility will be able to satisfy these criteria and will
be eligible to file its cost report using an all-inclusive rate or no
charge structure.
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\5\ PRM 15-1, chapter 22, Sec. 2208.1.
---------------------------------------------------------------------------
For cost reporting periods beginning on or after October 1, 2024,
we will issue instructions to the MACs and put in place edits to
operationalize our longstanding policy that only government-owned or
tribally owned IPF hospitals are permitted to file an all-inclusive
cost report. All other IPF hospitals must have a charge structure and
must report ancillary costs and charges on their cost reports. IPFs
that have previously filed an all-inclusive cost report erroneously
will no longer be able to do so. We further note that to the extent
government-owned or tribally owned hospitals can report ancillary
charges on their cost reports, we strongly encourage them to do so to
allow CMS to review and analyze complete and accurate data.
We believe clarifying the current eligibility criteria to be
approved to file all-inclusive cost reports and implementing these
operational changes will appropriately require freestanding IPFs with
the ability to have a charge structure, that is, all IPFs other than
those which are government-owned or tribally owned, to track and report
ancillary charge information. In addition, we expect that more IPFs
reporting ancillary charge information will result in an increase of
IPFs having a CCR, which will in turn result in an increased number of
IPFs being included in ratesetting. Therefore, we believe these
operational changes will improve the quality of data reported, which
will result in increased accuracy of future payment refinements to the
IPF PPS.
Furthermore, we believe collecting charges of ancillary services
from freestanding IPFs supports the directive for competition under the
Executive Order on Promoting Competition in the American Economy as it
facilitates accurate payment, cost efficiency, and transparency.\6\
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\6\ https://www.whitehouse.gov/briefing-room/presidential-actions/2021/07/09/executive-order-on-promoting-competition-in-the-american-economy/.
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F. Refinement Standardization Factor
Section 1886(s)(5)(D)(iii) of the Act, as added by section 4125(a)
of the CAA, 2023, states that revisions in payment implemented pursuant
to section 1886(s)(5)(D)(i) for a rate year shall result in the same
estimated amount of aggregate expenditures under this title for
psychiatric hospitals and psychiatric units furnished in the rate year
as would have been made under this title for such care in such rate
year if such revisions had not been implemented. We interpret this to
mean that revisions in payment adjustments implemented for FY 2025 (and
for any subsequent fiscal year) must be budget neutral.
Historically, we have maintained budget neutrality in the IPF PPS
using the application of a standardization factor, which is codified in
our regulations at Sec. 412.424(c)(5) to account for the overall
positive effects resulting from the facility-level and patient-level
adjustments. As discussed in section III.B.1 of this proposed rule,
section 124(a)(1) of the BBRA required that we implement the IPF PPS in
a budget neutral manner. In other words, the amount of total payments
under the IPF PPS, including any payment adjustments, must be projected
to be equal to the amount of total payments that would have been made
if the IPF PPS were not implemented. Therefore, we calculated the
standardization factor by setting the total estimated IPF PPS payments,
taking into account all of the adjustment factors under the IPF PPS, to
be equal to the total estimated payments that would have been made
under the Tax Equity and Fiscal Responsibility Act of 1982 (TEFRA)
(Pub. L. 97-248) methodology had the IPF PPS not been implemented. A
step-by-step description of the methodology used to estimate payments
under the TEFRA payment system appears in the RY 2005 IPF PPS final
rule (69 FR 66926).
We believe the budget neutrality requirement of section 4125(a) of
the CAA, 2023 is consistent with our longstanding methodology for
maintaining budget neutrality under the IPF PPS. Therefore, for FY
2025, we are proposing to apply a refinement standardization factor in
accordance with our existing policy at Sec. 412.424(c)(5). This policy
requires us to update IPF PPS patient-level adjustment factors, ED
adjustment, and ECT per treatment amount as proposed in this FY 2025
IPF PPS proposed rule, in such a way that total estimated payments to
IPFs for FY 2025 are the same with or without the changes (that is, in
a budget neutral manner) by applying a refinement standardization
factor to the IPF PPS rates. We are proposing to use the following
steps to ensure that the rates reflect the FY 2025 update to the
patient-level adjustment factors (as previously discussed in section
III.C and III.D of this proposed rule, and summarized in Addendum A) in
a budget neutral manner:
Step 1: Simulate estimated IPF PPS payments using the FY 2024 IPF
patient-level and facility-level adjustment factor values and FY 2024
ECT payment per treatment (available on the CMS website).
Step 2: Simulate estimated IPF PPS payments using the proposed FY
2025 IPF patient-level and facility-level adjustment factor values (see
Addendum A of this proposed rule, which is available on the CMS
website) and ECT per treatment amount based on the CY 2022 geometric
mean cost for ECT under the OPPS.
Step 3: Divide the amount calculated in step 1 by the amount
calculated in step 2. The resulting quotient is the proposed FY 2025
refinement standardization factor of 0.9514.
Step 4: Apply the FY 2025 refinement standardization factor from
step 3 to the FY 2024 IPF PPS Federal per diem base rate and ECT per
treatment amount (based on the CY 2022 geometric mean cost for ECT
under the OPPS), after the application of the wage index budget
neutrality factor and the IPF market basket increase reduced by the
productivity adjustment described in section III.A of this proposed
rule to determine the FY 2025 IPF PPS Federal per diem base rate and FY
2025 ECT payment amount per treatment.
IV. Requests for Information (RFI) To Inform Future Revisions to the
IPF PPS in Accordance With the CAA, 2023
As discussed in the following sections, we are requesting
information on two main topics to inform future revisions to the IPF
PPS, in accordance with the CAA, 2023. First, we are requesting
information regarding potential revisions to the IPF PPS facility-level
adjustments. Second, we are requesting information regarding the
development of a patient assessment instrument under the IPFQR program.
Please note, each of these sections is a request for information
(RFI) only. In accordance with the implementing regulations of the
Paperwork Reduction Act of 1995 (PRA), specifically 5 CFR 1320.3(h)(4),
this general solicitation is exempt from the PRA. Facts or opinions
submitted in response to general solicitations of comments from the
public, published in the Federal Register or other publications,
regardless of the form or format thereof, provided that no person is
required to supply specific information pertaining to the commenter,
other than that necessary for self-identification, as a condition of
the agency's full consideration, are not generally considered
information collections and therefore not subject to the PRA.
[[Page 23195]]
Respondents are encouraged to provide complete but concise responses.
This RFI is issued solely for information and planning purposes; it
does not constitute a Request for Proposal (RFP), applications,
proposal abstracts, or quotations. This RFI does not commit the U.S.
Government to contract for any supplies or services or make a grant
award. Further, CMS is not seeking proposals through this RFI and will
not accept unsolicited proposals. Responders are advised that the U.S.
Government will not pay for any information or administrative costs
incurred in response to this RFI; all costs associated with responding
to this RFI will be solely at the interested party's expense. Not
responding to this RFI does not preclude participation in any future
procurement, if conducted. It is the responsibility of the potential
responders to monitor this RFI announcement for additional information
pertaining to this request. Please note that CMS will not respond to
questions about the policy issues raised in this RFI. CMS may or may
not choose to contact individual responders. Such communications would
only serve to further clarify written responses. Contractor support
personnel may be used to review RFI responses. Responses to this notice
are not offers and cannot be accepted by the U.S. Government to form a
binding contract or issue a grant. Information obtained as a result of
this RFI may be used by the U.S. Government for program planning on a
non-attribution basis. Respondents should not include any information
that might be considered proprietary or confidential. This RFI should
not be construed as a commitment or authorization to incur cost for
which reimbursement would be required or sought. All submissions become
U.S. Government property and will not be returned. CMS may publicly
post the comments received, or a summary thereof.
A. Request for Information Regarding Revisions to IPF PPS Facility-
Level Adjustments
The CAA, 2023 added section 1886(s)(5)(D) to require CMS to revise
the IPF PPS methodology for determining payment rates for FY 2025, and
for any subsequent FY as determined appropriate by the Secretary. As
detailed in sections III.C and III.D of this proposed rule, we are
proposing to revise the patient-level payment adjustments in FY 2025
and retain the current facility-level payment adjustments for rural
location and teaching status. We have also conducted analysis of the
IPF PPS facility-level adjustments using an updated regression analysis
of cost and claims data for CY 2019 through 2021, as discussed in
section III.C.3. of this proposed rule. The updated analysis identified
potential changes in the regression factors for rural location and
teaching status and suggests there may be value in including a new
facility-level variable for safety net patient population, based on the
Medicare Safety Net Index (MSNI) methodology developed by MedPAC for
the IPPS. We note that the analysis of MSNI builds on prior analysis
that CMS conducted regarding the applicability of an adjustment for
disproportionate share intensity. Our review is ongoing and may be used
to inform future rulemaking.
In the following sections, we describe the results of our latest
analysis and request public comment on them. We are interested in
comments regarding whether it would be appropriate to consider
proposing revisions to the IPF PPS facility-level adjustments in the
future based on the results of our latest regression analysis in future
years.
1. Adjustment for Rural Location
In our MedPAR data set, which included data from CY 2019 through CY
2021, 101,483 stays, or 12.6 percent of all stays, were at rural IPFs.
Our analysis shows that the regression coefficient for rural stays is
1.19. This means that holding all other variables constant and
controlling for area wage differences, stays at rural IPFs have
approximately 19-percent higher cost per day than stays at urban IPFs.
As previously discussed, we did not include control variables in our
regression model to account for occupancy rate. However, we note that
if we included these control variables, we estimate the rural
adjustment in the regression would decrease to approximately 1.13.
In addition, as discussed later in section IV.A.3 of this proposed
rule, we evaluated the potential inclusion of a new variable for
facilities' safety net patient population, as measured by the MSNI
ratio. We observe that the inclusion of the MSNI ratio in the
regression model would have an impact on the rural adjustment factor.
In the regression model that includes the MSNI ratio, the rural
adjustment factor is 1.16. In other words, if we were to adopt an MSNI
payment adjustment, our FY 2025 regression model indicates that the
rural adjustment factor would decrease relative to the rural adjustment
factor calculated without the MSNI variable. However, for rural
facilities with a high level of safety net patients, the combined
effect of the rural adjustment and a safety net adjustment would
increase payments. These results are presented in Table 17, and we are
seeking public comments on these results.
[GRAPHIC] [TIFF OMITTED] TP03AP24.028
We have modeled informational impacts reflecting the potential
change in payments, as discussed in section IV.A.4 of this proposed
rule, though we note future additional data and analysis may produce
results that differ from those presented in this proposed rule.
2. Teaching Adjustment
In the IPF PPS payment methodology, the teaching status for each
facility is calculated as one plus the facility's ratio of intern and
resident FTEs to the average daily census (69 FR 66954 through 66955).
The teaching variable used in the regression is the natural log of each
facility's teaching status, resulting in a continuous variable with a
distribution ranging from 0.0000 to 1.6079. The payment adjustment for
teaching status, as explained in section III.D.2 of this proposed rule,
is calculated by raising a facility's teaching ratio to the power of
the teaching status coefficient derived from the regression analysis.
In our updated regression analysis of data for CY 2019 through CY
2021, there
[[Page 23196]]
were 155,458 stays in teaching facilities, comprising 19.3 percent of
IPF stays for the time period. As previously discussed in this proposed
rule, we found that the occupancy variables used in the original IPF
PPS regression model were correlated with rural status, and have been
removed in this updated model. We note that if we were to include
occupancy control variables in the regression model, the adjustment for
teaching status would increase to 1.0087.
The teaching status variable continues to be statistically
significant at the 0.001 level in all of our updated models; in other
words, we found that a facility's teaching status explains differences
in costs between IPF stays. As shown in Table 18, the teaching status
coefficient would increase in either updated regression model compared
to its current value.
[GRAPHIC] [TIFF OMITTED] TP03AP24.029
As discussed in section IV.A.4. of this proposed rule, we have
modeled informational impacts reflecting the potential change in
payments from these adjustment factors. We are seeking public comment
on these results. We note that future additional data and analysis may
produce results that differ from those presented in this proposed rule.
3. Adjustment for Safety Net Patient Population
a. Prior Analysis of Disproportionate Share Hospital Status
In contrast to other Medicare hospital payment systems, the IPF PPS
does not have an adjustment that recognizes disproportionate share
intensity. Section 1886(s) of the Act does not require any specific
adjustment of this type, nor does it require the use of any particular
methodology. In the past, we have explored the application of the
disproportionate share hospital (DSH) variable used in other Medicare
prospective payment systems (that is, the sum of the proportion of
Medicare days of care provided to recipients of Supplemental Security
Income and the proportion of the total days of care provided to
Medicaid beneficiaries) for the IPF PPS. We refer readers to the RY
2005 IPF PPS final rule (69 FR 66958 through 66959) and the FY 2023 IPF
PPS final rule (87 FR 46865). For psychiatric units, both proportions
are specific to the unit and not the entire hospital.
In the RY 2005 IPF PPS final rule, we explained that the DSH
variable was highly significant in our cost regressions; however, we
found that facilities with higher DSH had lower per diem costs. We note
that the previously cited study for the American Psychiatric
Association also found the same results. The relationship of high DSH
with lower costs cannot be attributed to downward bias in the Medicaid
proportion due to the IMD exclusion. This is because public psychiatric
hospitals already have lower costs on average than other types of IPFs.
Therefore, if we had proposed a DSH adjustment based on the regression
analysis, IPFs with high DSH shares would have been paid lower per diem
rates (69 FR 66958).
In the FY 2023 IPF PPS proposed rule, we summarized and discussed
the results of more recent analysis using data from 2018 (87 FR 19428
through 19429). In response to that proposed rule, commenters
encouraged CMS to continue evaluating ways to increase IPF PPS payments
for disproportionate share intensity. MedPAC recommended that we
consider the applicability of the MSNI, which has previously been
discussed in the context of the IPPS, to the IPF PPS. As discussed in
the following paragraphs, we have conducted analysis of the MSNI and
are soliciting comments on our findings.
b. Analysis of the Medicare Safety Net Index in the IPF PPS
(1) Background
MSNI is an index that MedPAC developed as its recommended
alternative to the current statutorily required methodology for
disproportionate share payments to IPPS hospitals. In their March 2023
Report to Congress, MedPAC recommend that MSNI would better target
scarce Medicare resources to support hospitals that are key sources of
care for low-income Medicare beneficiaries and may be at risk of
closure.\7\ For further discussion of this safety net index in the
context of the Medicare program, we refer readers to the FY 2024 IPPS
final rule (88 FR 58640), which includes a discussion of how MSNI could
be calculated for acute care hospitals and an RFI on the potential use
of MSNI or other safety net indicators in the IPPS, such as the area
deprivation index (ADI) or Social Deprivation Index (SDI).
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\7\ Medicare Payment Advisory Commission. (2023). Report to the
Congress: Medicare Payment Policy. Available at: https://www.medpac.gov/wp-content/uploads/2023/03/Ch3_Mar23_MedPAC_Report_To_Congress_SEC_v2.pdf. Accessed on January
22, 2024.
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For our analysis, we constructed an MSNI for each IPF in our data
set, which we calculated as the sum of three ratios:
The low-income subsidy (LIS) volume ratio, which is the
ratio of total stays for low-income beneficiaries to a facility's total
stays for Medicare beneficiaries. For our analysis, low-income
beneficiaries are identified based on dual-enrollment or enrollment in
Part D low-income subsidies, and stays are identified from MedPAR
claims. This ratio was defined the same way in the FY 2024 IPPS final
rule's discussion of MSNI (88 FR 59306).
The proportion of revenue spent on uncompensated care
(UCC), defined the same way as it was in the FY 2024 IPPS final rule's
discussion of MSNI (88 FR 59306). UCC and total revenue are available
data elements from the hospital cost report, but only for the acute
care hospital. These elements are not currently detailed at the level
of the IPF unit.
The Medicare dependency ratio, which is a hospital's total
covered days for Medicare patients divided by its total patient days.
This information comes from the hospital cost report. We have also
defined this ratio in the same way as it was defined in the FY 2024
IPPS final rule's discussion of MSNI (88 FR 59306).
The final MSNI score is calculated as: LIS Volume Ratio +
Proportion of Revenue Spent on UCC ratio + 0.5 * Medicare Dependency
Ratio. This formula follows MedPAC's methodology based on its analysis
of data for the IPPS hospital setting. As discussed in its
[[Page 23197]]
March 2023 Report to Congress, the Medicare Dependency Ratio is
multiplied by 0.5 because MedPAC's prior analysis of costs in the IPPS
setting found that the Medicare Dependency Ratio had approximately half
the effect on cost as the other two components of MSNI.
(2) Regression Analysis Results
The adjusted r-square, a measure of how much of the variation in
costs between stays our model can explain, increases by approximately
2.8 percent when we add the variable for MSNI to the updated model
analyzing cost and claims data for CY 2019 through CY 2021. The
adjusted r-square for the model without the MSNI variable is 0.32340,
while the adjusted r-square for the model with the MSNI variable is
0.33250. Our regression analysis indicates an MSNI coefficient of
0.5184, which is statistically significant at the .001 level.
[GRAPHIC] [TIFF OMITTED] TP03AP24.030
Section 1886(s)(5)(D)(iii) of the Act, as added by section 4125(a)
of the CAA, 2023, states that revisions in payment implemented pursuant
to section 1886(s)(5)(D)(i) for a rate year shall result in the same
estimated amount of aggregate expenditures under this title for
psychiatric hospitals and psychiatric units furnished in the rate year
as would have been made under this title for such care in such rate
year if such revisions had not been implemented. Therefore, our
estimates of payments associated with a potential MSNI payment
adjustment include the application of a standardization factor, which
we note would reduce the IPF PPS Federal per diem base rate by
approximately $245. Total payments to IPFs would remain the same, but
there would be significant distributional impacts, which would reduce
payments to IPFs with a lower MSNI and increase payments to IPFs with a
higher MSNI. We refer readers to section IV.A.4 of this proposed rule
for informational analysis and discussion of the potential
distributional impacts estimated for the MSNI payment adjustment.
We note that for certain elements of the MSNI calculation, some
data was not available for IPFs at the same level of detail available
for IPPS hospitals. We also identified that for some elements, data
reported by IPFs may be incomplete. First, as mentioned above, both UCC
amounts and total revenue amounts are reported at the hospital level
only. As a result, we were able to calculate a UCC ratio for IPF units
based on the overall ratio of the hospital's UCC to its revenues. This
assumes that a hospital's overall UCC ratio would be comparable to that
of its IPF unit. However, because we lack unit-level data, we are not
able to validate this assumption. Table 20 shows that most freestanding
IPF hospitals are not reporting any UCC, which leads to lower MSNI
values for these IPFs. We recognize that the absence of UCC for
nonprofit IPFs, which we believe in fact provide a significant amount
of UCC, may reflect differences in reporting, rather than provision of
UCC.
[GRAPHIC] [TIFF OMITTED] TP03AP24.031
There are also a number of key differences between our analysis and
the way that MedPAC has recommended that MSNI be applied to payments in
the IPPS setting. For the IPPS, MedPAC recommends to the Congress in
their March 2023 report that they create an MSNI pool of funds for MSNI
add-on payments of about $2 billion, which could be increased each year
by the market basket update. MedPAC contemplates hospitals choosing
between an MSNI payment and other special payment rates designed to
protect access, for example, in rural areas, or the adoption of a
percentage-based cap on all special payment rates.\8\ In contrast, our
modeling of an MSNI payment adjustment in the IPF PPS, assumes that
IPFs could be eligible for both an MSNI payment and the payment
adjustment for rural location, for example, without a cap imposed. Our
modeling also assumes that an MSNI payment adjustment would be budget
neutral; in other words, the payment would not be an add-on. In
contrast to the recommended approach for the IPPS, which would come
from a new funding pool, we estimate that the application of an MSNI
adjustment would affect the Federal IPF PPS per diem base rate. As a
result, the MSNI payment in our model would represent a redistribution
of funds within the IPF PPS, as is
[[Page 23198]]
statutorily required under section 4125(a) of the CAA, 2023.
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\8\ Medicare Payment Advisory Commission. (2023). Report to the
Congress: Medicare Payment Policy. Available at: https://www.medpac.gov/wp-content/uploads/2023/03/Ch3_Mar23_MedPAC_Report_To_Congress_SEC_v2.pdf. Accessed on January
22, 2024.
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We constructed the MSNI variable in our regression model similarly
to the construction of the teaching adjustment (that is, as the natural
log of a facility's MSNI ratio plus 1). Consequently, a payment
adjustment derived from our regression results would work like the
teaching status adjustment: the MSNI adjustment factor is expressed in
an un-exponentiated form. A provider's MSNI factor plus one would be
raised to the power of the MSNI adjustment factor to calculate the
facility's MSNI payment adjustment.
We are considering the potential operational changes that would be
necessary to implement an adjustment for MSNI in the future. For
example, we anticipate the need to periodically recalculate facilities'
MSNI ratios, which could potentially correspond to a facility's cost
report settlement process. We also anticipate the need to develop a
reconciliation process, should such an adjustment for MSNI be
implemented in the future. Further, we expect that because a facility's
LIS ratio would not be an available data element on the hospital cost
report, we may need to develop and publish a facility-level file with
this information or consider collecting additional data on the hospital
cost report. As discussed in the following section, we are seeking
public comment on our regression results, as well as our methodology
used to construct the MSNI variable for IPFs, and on the operational
considerations we have noted. We note that future additional data and
analysis produce results that differ from those presented in this
proposed rule.
(3) Request for Information
We are particularly seeking comment on the following questions:
Should we consider adjusting payment using MedPAC's MSNI
formula with adaptations, as described above? What, if any, changes to
the methodology should we consider for the IPF setting? For example,
should we develop a separate payment adjustment for each component
(that is, the low-income ratio, uncompensated care ratio, and Medicare
dependency ratio)?
We note that our construction of the MSNI did not scale or
index facility-level variables to a national standard or median value.
We anticipate that doing so would result in less of a change to the IPF
Federal per diem base rate but would still result in comparable
distributional impacts (that is, IPFs with lower MSNIs would receive
lower payments, and IPFs with higher MSNIs would receive higher
payments). Should we consider scaling or indexing the MSNI to a
national average MSNI for all IPFs?
Is MedPAC's MSNI formula, as adapted, an accurate and
appropriate measure of the extent to which an IPF acts as a safety-net
hospital for Medicare beneficiaries?
Should additional data be collected through the cost
report to improve the calculation of MSNI, such as collecting UCC and
revenue at the IPF unit level?
Is the current cost report data submitted by IPFs
sufficiently valid and complete to support the implementation of an
MSNI payment? We note our concerns about the low or non-existent
amounts reported for uncompensated care for freestanding IPFs and the
use of hospital-level UCC and revenue amounts to calculate the UCC
ratio for IPF units.
What administrative burden or challenges might providers
face in reporting their UCC and low-income patient stays?
Would IPFs have the information necessary to report their
low-income patient stays to CMS for the purpose of the MSNI
calculation? What challenges might IPFs face in gathering and reporting
this information?
In the FY 2023 IPPS proposed rule, CMS noted that, when
calculating the MSNI, the following circumstances may be encountered:
new hospitals (for example, hospitals that begin participation in the
Medicare program after the available audited cost report data),
hospital mergers, hospitals with multiple cost reports and/or cost
reporting periods that are shorter or longer than 365 days, cost
reporting periods that span fiscal years, and potentially aberrant
data. How should CMS consider addressing these circumstances when
calculating the MSNI for IPFs?
4. Informational Impacts of Potential Facility-Level Revisions on IPF
PPS Payments
We estimate that an MSNI payment adjustment in concert with the
potential rural payment adjustment and teaching adjustments detailed in
this section would have a refinement standardization factor of 0.7202.
In other words, adoption of these facility-level payment adjustments as
described in this section of this proposed rule would decrease the
Federal per diem base rate by $244.81. In contrast, we estimate that
updating only the rural and teaching adjustments without MSNI would
have a refinement standardization factor of 0.9926, which would
decrease the Federal per diem base rate by $6.48.
Estimates of distributional impacts by facility type, location,
ownership, teaching status, and region are detailed in Table 21. We are
seeking public comment on these informational impacts to potentially
inform future rulemaking.
To illustrate the impacts of these potential changes to the IPF PPS
facility-level adjustments, our analysis begins with the same FY 2023
IPF PPS claims (based on the 2023 MedPAR claims, December 2023 update)
as discussed in section VIII.C of this proposed rule. We begin with
estimated FY 2025 IPF PPS payments using these 2023 claims, the
proposed FY 2025 IPF PPS Federal per diem base rate and ECT per
treatment amount, the proposed refinements to the FY 2025 IPF PPS
patient and facility level adjustment factors, and the proposed FY 2025
IPF PPS wage index. At each stage, total outlier payments are
maintained at 2 percent of total estimated FY 2025 IPF PPS payments.
Each of the following changes is added incrementally to this
baseline model in order for us to isolate the effects of each change:
The potential updates to the IPF teaching adjustment and
rural adjustment, without the addition of an adjustment for MSNI.
Adding an adjustment for MSNI and reducing the IPF rural
adjustment and teaching adjustment as shown in the third column of
Tables 17 and 18 of this proposed rule.
BILLING CODE 4120-01-P
[[Page 23199]]
[GRAPHIC] [TIFF OMITTED] TP03AP24.032
[[Page 23200]]
[GRAPHIC] [TIFF OMITTED] TP03AP24.033
BILLING CODE 4120-01-C
B. Request for Information (RFI)--Patient Assessment Instrument Under
IPFQR Program (IPF PAI) To Improve the Accuracy of the PPS
Section 4125(b)(1) of CAA, 2023 amended section 1886(s)(4) of the
Act, by inserting a new paragraph (E), to require IPFs participating in
the IPFQR Program to collect and submit to the Secretary certain
standardized patient assessment data, using a standardized patient
assessment instrument (PAI) developed by the Secretary, for RY 2028 (FY
2028) and each subsequent rate year. IPFs must submit such data with
respect to at least the admission to and discharge of an individual
from the IPF, or more frequently as the Secretary determines
appropriate. For IPFs to meet this new data collection and reporting
requirement for RY 2028 and each subsequent rate year, the Secretary
must implement a standardized PAI that collects data with respect to
the following categories: functional status; cognitive function and
mental status; special services, treatments, and interventions for
psychiatric conditions; medical conditions and comorbidities;
impairments; and other categories as determined appropriate by the
Secretary. This IPF-PAI must enable comparison of the patient
assessment data across all IPFs which submit these data. In other
words, the data must be standardized such that data from IPFs
participating in the IPFQR Program can be compared; the IPF-PAI each
IPF administers must be made up of identical questions and identical
sets of response options to which identical standards and definitions
apply.
As we develop the IPF-PAI, in accordance with these new statutory
requirements, we seek to collect information that will help us achieve
the following goals: (1) improve the quality of care in IPFs, (2)
improve the accuracy of the IPF PPS in accordance with section
4125(b)(2) of CAA, 2023, and (3) improve health equity.\9\ In this
Request for Information (RFI), we are soliciting comments for
development of this IPF-PAI, in accordance with these new statutory
requirements, and to achieve these goals.
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\9\ For more information on our strategic goals to improve
health equity by expanding the collection, reporting, and analysis
of standardized data, we refer readers to Priority 1 of our
Framework for Health Equity at https://www.cms.gov/priorities/health-equity/minority-health/equity-programs/framework.
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This RFI consists of four sections. The first section discusses a
general framework or set of principles for development of the IPF-PAI.
The second section outlines potential approaches that could be used to
develop the items or data elements that
[[Page 23201]]
make up the PAI. This section also discusses patient assessment data
elements in use in PAIs for skilled nursing facilities and other
healthcare settings that could potentially be adapted for use in the
IPF-PAI. The third section outlines potential approaches that could be
used to collect patient assessment data. Finally, the fourth section
solicits public comment on the principles and approaches listed in the
first three sections and seeks other input regarding the IPF-PAI.
1. Framework for Development of the IPF-PAI
We considered similar legislatively derived PAIs previously
implemented for certain post-acute care (PAC) providers to inform the
goals and guiding principles for the IPF-PAI because of similarities of
section 4125(b) of CAA, 2023 to the Improving Medicare Post-Acute Care
Transformation Act of 2014 (IMPACT Act) (Pub. L. 113-185, October 6,
2014), codified at section 1899B of the Act. Similar to section 4125(b)
of CAA, 2023, section 1899B of the Act requires certain PAC providers,
specifically home health agencies (HHAs), skilled nursing facilities
(SNFs), inpatient rehabilitation facilities (IRFs), and long-term care
hospitals (LTCHs), to submit certain standardized patient assessment
data (as set forth at section 1899B(b)(1)(B)) using a standardized PAI
under the PAC providers' respective quality reporting programs. While
IPFs are acute care providers and not PAC providers, given the
similarities between the CAA, 2023 and section 1899B of the Act, we
considered the goals and guiding principles that we followed to
implement section 1899B of the Act for certain PAC providers and
examined their applicability and appropriateness for IPFs.
We previously identified four key considerations when assessing
Standardized Patient Assessment Data Elements for the PAC PAIs to
collect: (1) Overall clinical relevance; (2) Interoperable exchange to
facilitate care coordination during transitions in care; (3) Ability to
capture medical complexity and risk factors that can inform both
payment and quality; and (4) Scientific reliability and validity,
general consensus agreement for its usability.\10\ For the reasons
discussed in the following subsections, we believe that these
considerations are also appropriate for the development of the IPF-PAI.
In addition, we seek to balance the need to collect meaningful patient
data to improve care with the need to minimize administrative burden.
The remainder of this section describes each of these considerations in
the context of the IPF-PAI. As we discuss in section IV.B.4.a of this
proposed rule, we are soliciting comment on these considerations.
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\10\ We refer readers to the Prospective Payment System and
Consolidated Billing for Skilled Nursing Facilities; Updates to the
Quality Reporting Program and Value-Based Purchasing Program for
Federal fiscal year 2020 final rule (84 FR 38767); the Medicare
Program; Inpatient Rehabilitation Facility (IRF) Prospective Payment
System for Federal fiscal year 2020 and Updates to the IRF Quality
Reporting Program final rule (84 FR 39110), the Medicare and
Medicaid Programs; CY 2020 Home Health Prospective Payment System
Rate Update; Home Health Value-Based Purchasing Model; Home Health
Quality Reporting Requirements; and Home Infusion Therapy
Requirements CY 2020 final rule (84 FR 60567), and the Medicare
Program; Hospital Inpatient Prospective Payment Systems for Acute
Care Hospitals and the Long-Term Care Hospital Prospective Payment
System and Policy Changes and fiscal year 2020 Rates; Quality
Reporting Requirements for Specific Providers; Medicare and Medicaid
Promoting Interoperability Programs Requirements for Eligible
Hospitals and Critical Access Hospitals final rule (84 FR 42537).
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a. Overall Clinical Relevance
In each category of assessment required by section
1886(s)(4)(E)(ii), as added by section 4125(b) of CAA, 2023,
(functional status; cognitive function and mental status; special
services, treatments, and interventions for psychiatric conditions;
medical conditions and comorbidities; impairments, and other categories
as determined appropriate by the Secretary), we seek to establish
Standardized Patient Assessment Data Elements that providers can use to
support high quality care and outcomes in the IPF setting. As we
evaluate Standardized Patient Assessment Data Elements in PAIs designed
for other care settings, we intend to work with CMS Medical Officers,
including psychiatrists, to consider the clinical relevance for IPF
patients as a determining factor in whether an item merits inclusion in
the IPF-PAI. For an example of a PAI in use in another setting, we
refer readers to the IRF-PAI instrument available at https://www.cms.gov/files/document/irf-pai-version-40-eff-10012022-final.pdf.
We are particularly interested in learning about specific instruments
and tools in each area of assessment that have high clinical relevance
in the IPF setting and welcome comments regarding Standardized Patient
Assessment Data Elements that may not be clinically relevant to the IPF
setting.
To ensure the clinical relevance of the instrument across a diverse
group of IPF patients, we are considering structuring the assessment
with conditional questions, so that certain sets of questions are only
indicated if the questions are relevant to the patient. Furthermore, we
note that some data elements may only be appropriate for collection at
certain times during the patient's stay (for example, only at admission
or only at discharge). We solicit comments regarding the most effective
structure to employ in the development of the IPF-PAI.
b. Interoperability
Interoperability is a key priority and initiative at CMS. Across
the organization, we aim to promote the secure exchange, access, and
use of electronic health information to support better informed
decision making and a more efficient healthcare system. As a part of
this effort, we make interoperability a priority for standardized data
collection. We intend to ensure that the IPF-PAI meets Health Level
7[supreg] (HL7[supreg]) Fast Healthcare Interoperability
Resources[supreg] (FHIR[supreg]) standards.
As part of our interoperability considerations, we are interested
in whether Standardized Patient Assessment Data Elements already in use
in the CMS Data Element Library (DEL) are appropriate and clinically
relevant for the IPF setting. In CY 2021, approximately 8,000
admissions to IPFs were individuals transferred from SNFs or IRFs. We
are interested in whether Standardized Patient Assessment Data Elements
already used in the DEL can be used to better support interoperability
between providers, given the high number of transfers.
c. Ability To Capture Medical Complexity and Risk Factors
We intend to expand our efforts to refine the IPF PPS to increase
the accuracy of the payment system by better identifying patient
characteristics that best predict resource use during an IPF stay. To
identify Standardized Patient Assessment Data Elements that would help
predict resource use, we intend to evaluate Standardized Patient
Assessment Data Elements for their ability to explain medical
complexity, the need for special services and treatments, and to
measure case-mix differences that impact costs. It is our expectation
that an IPF-PAI that effectively differentiates treatment needs between
patients will also help IPFs plan and distribute their resources. Our
hope is that the IPF-PAI can therefore integrate with IPFs' business
practices. In addition, Standardized Patient Assessment Data Elements
that capture patient risk factors can
[[Page 23202]]
contribute to quality of care and patient safety.
d. Scientific Reliability and Validity
Standardized Patient Assessment Data Elements considered for
inclusion in the IPF-PAI must be scientifically reliable and valid in
IPF settings. We intend to draw on our significant experience in
development of quality measures in the IPFQR Program and development of
Standardized Patient Assessment Data Elements for other PAIs, such as
the IRF-PAI and the Minimum Data Set (MDS) (the PAI for SNFs), in our
development of Standardized Patient Assessment Data Elements for the
IPF-PAI.\11\ It is important to note that the statutorily required
timeframe for implementation of the IPF-PAI for RY 2028 limits our
ability to develop and test a full battery of new Standardized Patient
Assessment Data Elements for the launch of the IPF-PAI. We anticipate
the need and opportunity for incremental revisions to the IPF-PAI in
the future.
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\11\ For more information on other PAIs, we refer readers to
https://www.cms.gov/medicare/payment/prospective-payment-systems/inpatient-rehabilitation/pai (for the IRF-PAI), to https://www.cms.gov/medicare/quality/home-health/oasis-data-sets (for the
OASIS data set for HHAs), to https://www.cms.gov/medicare/quality/long-term-care-hospital/ltch-care-data-set-ltch-qrp-manual (for the
CARE data set for LTCHs), and to https://www.cms.gov/medicare/quality/nursing-home-improvement/resident-assessment-instrument-manual (for the Minimum Data Set (MDS) Resident Assessment
Instrument (RAI)).
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We anticipate that our development process for new Standardized
Patient Assessment Data Elements will include working with teams of
researchers for each category including a group of advisors made up of
clinicians and academic researchers for each team with expertise in
IPFs. We expect to convene a Technical Expert Panel (TEP) to provide
expert input on new and existing Standardized Patient Assessment Data
Elements that merit consideration for inclusion and testing, including
environmental scans and reviews of scientific literature. In an ideal
scenario, Standardized Patient Assessment Data Elements would be tested
in a representative sample of IPFs for appropriateness in different IPF
settings and across a range of patients. Standardized Patient
Assessment Data Elements would be tested for inter-rater (that is,
consistency in results regardless of who is administering the
assessment) and inter-organizational reliability, for validity in all
IPF settings, for internal consistency, and for breadth of application
among a range of IPF patients. We anticipate that Standardized Patient
Assessment Data Elements would also need to be tested for their ability
to detect differences among patients and costs of treatment. Due to the
constraints of the statutorily required implementation timeframe, it
may not be possible to complete all testing before launching the IPF-
PAI.
The process for scientifically testing each question and set of
responses is lengthy and resource-intensive. This process is based on
the steps for quality measure development described in the Blueprint
Measure Lifecycle,\12\ developed by the CMS Measures Management System.
These steps include literature review and environmental scanning;
various levels of field testing to understand the ``real world''
performance of the data elements; and iterative expert and interested
parties engagement to include broader perspectives on topics, candidate
data elements, and interpretation of testing results. If appropriate,
using data currently collected by IPFs or Standardized Patient
Assessment Data Elements that have been tested and validated for use in
other clinical settings can reduce these timeframes because test data
are already available.
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\12\ https://mmshub.cms.gov/blueprint-measure-lifecycle-overview.
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e. Administrative Burden
In evaluating Standardized Patient Assessment Data Elements for
inclusion in the IPF-PAI, we are considering the burden of data
collection through the PAI and aiming to minimize additional burden by
considering whether any data that is currently collected through IPFQR
Program measures or on IPF claims could be collected as Standardized
Patient Assessment Data Elements to avoid duplication of data that IPFs
are already reporting. We are also considering how collecting some data
for some IPFQR Program measures through the IPF-PAI and collecting
other data through the Hospital Quality Reporting (HQR) system would
affect the reporting burden for participating IPFs. Licensing,
permissions costs, or copyright restrictions that would add to
administrative costs and burdens are also a consideration as we
evaluate existing PAIs and mechanisms or tools for submitting IPF-PAI
data.
As we develop the IPF-PAI, we are interested in receiving
information about how to find a balance between collecting the most
relevant and useful information and the administrative burden of
administering the assessment and submitting the assessment data.
2. Elements of the IPF-PAI
Section 1886(s)(4)(E)(ii) of the Act, added by section
4125(b)(1)(C) of the CAA, 2023, requires that the standardized patient
assessment data to be collected in the IPF-PAI must be with respect to
six enumerated categories.
a. Functional Status
The first enumerated category of data for the IPF-PAI is functional
status. Section 1886(s)(4)(E)(ii)(I) of the Act provides that
functional status may include mobility and self-care at admission to a
psychiatric hospital or unit and before discharge from a psychiatric
hospital or unit. We note that information in this category is
generally found in a patient's discharge summary and are interested in
learning about standardized elements that correspond to functional
status as relevant to IPFs. We are interested in what assessments may
be currently in use in the IPF setting and meet criteria for inclusion
in the IPF-PAI.
b. Cognitive Function and Mental Status
The second enumerated category of data for the IPF-PAI is cognitive
function and mental status. Section 1886(s)(4)(E)(ii)(II) of the Act
provides that cognitive function may include the ability to express
ideas and to understand, and mental status may include depression and
dementia. We note that in the IPF setting, a patient's diagnoses, which
can be abstracted from their medical chart, provide some information
related to this category. We are aware that IPFs may be currently
assessing cognitive function using existing instruments. We are
interested in hearing from IPFs about which instruments are currently
in use to measure cognitive function in IPFs and which have high
clinical relevance for the IPF setting.
c. Special Services, Treatments, and Interventions
The third enumerated category of data for the IPF-PAI is special
services, treatments, and interventions for psychiatric conditions.
Section 1886(s)(4)(E)(ii)(III) of the Act neither addresses what these
terms mean nor provides any illustrative examples. As discussed in
section V.C. of this rule, the IPFQR Program already collects
information about the use of restraint and seclusion through quality
measures (Hospital Based Inpatient Psychiatric Services (HBIPS)-2,
Hours of Physical Restraint, and HBIPS-3, Hours of Seclusion Use),
while claims include information about ECT treatments provided. Other
areas of interest in this
[[Page 23203]]
category may include high-cost medications, use of chemical restraints,
one-to-one observation, and high-cost technologies. We are interested
in whether these or any other special services, treatments, or
interventions should be considered for inclusion in the IPF-PAI.
d. Medical Conditions and Comorbidities
The fourth enumerated category of data for the IPF-PAI is medical
conditions and comorbidities. Section 1886(s)(4)(E)(ii)(IV) of the Act
provides that medical conditions and comorbidities may include
diabetes, congestive heart failure, and pressure ulcers. We note that
IPF claims record a significant number of medical conditions and
comorbidities to receive the payment adjustment for comorbidities in
the IPF PPS and conditions that are relevant to the IPF stay. In
reviewing Standardized Patient Assessment Data Elements listed in this
category in PAIs in use in PAC settings, we observed that these PAIs
include Standardized Patient Assessment Data Elements regarding pain
interference in this category, such as the effect of pain on sleep,
pain interference with therapy activities, and pain interference with
day-to-day activities. We are interested in learning from commenters
whether these existing data elements from the PAC settings would be
clinically relevant for inclusion in this category for the IPF-PAI.
e. Impairments
The fifth enumerated category of data for the IPF-PAI is
impairments. Section 1886(s)(4)(E)(ii)(V) of the Act provides that
impairments may include incontinence and an impaired ability to hear,
see, or swallow. PAIs in use in other settings include Standardized
Patient Assessment Data Elements regarding hearing and vision (for
example, Section B, ``Hearing, Speech, and Vision'' of the IRF-PAI
Version 4.2 (Effective October 1, 2024)).\13\ We are interested both in
whether Standardized Patient Assessment Data Elements regarding
additional impairments merit consideration for the IPF-PAI, and whether
the Standardized Patient Assessment Data Elements regarding hearing and
vision included in the IRF-PAI are appropriate for the IPF setting. We
note that the Standardized Patient Assessment Data Element categories
are not intended to be duplicative, so we would seek to avoid any
overlap in measuring cognitive deficits in the Cognitive Function
category with the Impairments category.
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\13\ https://www.cms.gov/files/document/irf-pai-version-42-effective-10-01-24.pdf.
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f. Other Categories Deemed Appropriate
The sixth enumerated category of data for the IPF-PAI is other
categories as determined appropriate by the Secretary. We believe this
provision allows for flexibility to include additional areas in the
IPF-PAI.
One of our strategic priorities, as laid out in the CMS Strategic
Plan,\14\ reflects our deep commitment to improvements in health equity
by addressing the health disparities that underlie our health system.
In line with that strategic priority, we are interested in Standardized
Patient Assessment Data Elements that would provide insight about any
demographic factors (for example, race, national origin, primary
language, ethnicity, sexual orientation, and gender identity) as well
as SDOH (for example, housing status and food security) associated with
underlying inequities. We are also interested in whether there are
Standardized Patient Assessment Data Elements that would provide
insight into special interventions that IPFs are providing to support
patients after discharge which could serve to potentially reduce the
incidence of readmissions.
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\14\ The CMS Strategic Plan. Available at https://www.cms.gov/about-cms/what-we-do/cms-strategic-plan. Accessed February 20, 2024.
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We note that, beginning with mandatory reporting of CY 2025 data
for FY 2027 payment determination, the IPFQR Program includes the
Screening for SDOH measure, which assesses the percentage of patients,
aged 18 years and over at the time of admission, who are screened for
five specific health-related social needs (HRSNs)--food insecurity,
housing instability, transportation needs, utility difficulties, and
interpersonal safety, but which does not require reporting of that
information at the patient-level (88 FR 51117). Furthermore, we note
that PAIs adopted for the PAC settings discussed previously include
collection of SDOH data under section 1899B(b)(1)(B)(vi) of the Act,
which contains a similar provision for other categories deemed
appropriate by the Secretary.\15\
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\15\ For further information detailing the rationale for
adopting SDOH Standardized Patient Assessment Data Elements in these
settings, we refer readers to the Prospective Payment System and
Consolidated Billing for Skilled Nursing Facilities; Updates to the
Quality Reporting Program and Value-Based Purchasing Program for
Federal fiscal year 2020 final rule (84 FR 38805 through 38817); the
Medicare Program; Inpatient Rehabilitation Facility (IRF)
Prospective Payment System for Federal fiscal year 2020 and Updates
to the IRF Quality Reporting Program final rule (84 FR 39149 through
38161), the Medicare and Medicaid Programs; CY 2020 Home Health
Prospective Payment System Rate Update; Home Health Value-Based
Purchasing Model; Home Health Quality Reporting Requirements; and
Home Infusion Therapy Requirements CY 2020 final rule (84 FR 60597
through 60608), and the Medicare Program; Hospital Inpatient
Prospective Payment Systems for Acute Care Hospitals and the Long-
Term Care Hospital Prospective Payment System and Policy Changes and
fiscal year 2020 Rates; Quality Reporting Requirements for Specific
Providers; Medicare and Medicaid Promoting Interoperability Programs
Requirements for Eligible Hospitals and Critical Access Hospitals
final rule (84 FR 42577 through 42588).
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We note that, if we deem it appropriate to add a SDOH category for
the IPF-PAI and these SDOH data are included as Standardized Patient
Assessment Data Elements in the PAI, they could potentially be used to
risk adjust or stratify measures collected for the IPFQR Program. We
are interested in learning whether using some of these SDOH data
adopted in other PAIs to risk adjust or stratify these measures would
make the measures in the IPFQR Program more meaningful.
3. Implementation of the PAI--Data Submission
We plan to develop flexible methods for providers to submit IPF-PAI
data to CMS, including batch uploads in specified formats and a portal
for submission of files. We welcome public comment on tools and methods
for submission of data that balance administrative burden and ease of
use.
4. Request for Information on IPF-PAI
In this proposed rule, we are requesting information from the
public to inform the selection of Standardized Patient Assessment Data
Elements to be collected on the IPF-PAI and the implementation process.
We are seeking information about PAIs IPFs currently use upon admission
and discharge, as well as information about how IPFs estimate resource
needs to determine capacity before a patient is admitted. We are also
seeking information about methods for IPFs to submit patient assessment
data and the potential administrative burden on IPFs, MACs, and CMS.
Finally, we are seeking input on the relationship between the IPF-PAI
and the measures within the IPFQR Program.
We solicit comment on the following topics:
a. Principles for Selecting Standardized Patient Assessment Data
Elements
To what extent do you agree with the principles for
selecting and developing Standardized Patient Assessment Data Elements
for the IPF-PAI?
What, if any, principles should CMS eliminate from the
Standardized
[[Page 23204]]
Patient Assessment Data Element selection criteria?
What, if any, principles should CMS add to the
Standardized Patient Assessment Data Element selection criteria?
b. Patient Assessments Recommended for Use in the IPF-PAI
Are there PAIs currently available for use, or that could
be adapted or developed for use in the IPF-PAI, to assess patients':
(1) functional status; (2) cognitive function and mental status; (3)
special services, treatments, and interventions for psychiatric
conditions; (4) medical conditions and comorbidities; (5) impairments;
(6) health disparities; or (7) other areas not mentioned in this RFI?
c. Functional Status Standardized Patient Assessment Data Elements
What aspects of function are most predictive of medical
complexity or increased resource needs to treat a patient in the IPF
setting?
Which of the Standardized Patient Assessment Data Elements
related to mobility (that is, the ability to toilet transfer, walk 10
feet, car transfer, walk 10 feet on an uneven surface, 1 step up (that
is, a curb), 4 steps up, 12 steps up, and pick up an object) currently
collected by PAC settings in their respective PAIs are clinically
relevant in the IPF setting? Do they otherwise meet the principles for
inclusion in the IPF-PAI?
d. Cognitive Function and Mental Status Standardized Patient Assessment
Data Elements
What aspects of cognitive function and mental status are
most predictive of medical complexity or increased resource needs to
treat a patient in the IPF setting?
What components or instruments are used to assess
cognitive function, mental status, or a combination thereof upon
admission? What, if any, differences are there between assessments
administered at admission and at discharge? What are the components of
the mental status assessments administered at admission and discharge?
e. Special Services, Treatments, and Interventions for Psychiatric
Conditions Standardized Patient Assessment Data Elements
What special services, treatments, and interventions are
most predictive of increased resource intensity during an IPF stay?
Do data currently collected as part of the IPFQR Program
related to special services and treatments (such as HBIPS-2 Hours of
Physical Restraint Use and HBIPS-3 Hours of Seclusion Use) meet the
criteria for inclusion in the IPF-PAI?
f. Medical Conditions and Comorbidities Standardized Patient Assessment
Data Elements
Is the Standardized Patient Assessment Data Element
regarding pain interference (effect on sleep, interference with therapy
activities, interference with day-to-day activities) currently
collected by PAC settings in their respective PAIs clinically relevant
in the IPF setting? Does it otherwise meet the criteria for inclusion
in the IPF-PAI?
Do the medical conditions and comorbidities coded on IPF
claims meet the criteria for inclusion in the IPF-PAI?
g. Impairments Standardized Patient Assessment Data Elements
Are Standardized Patient Assessment Data Elements related
to impairments (that is, the ability to hear and see in adequate light)
currently collected PAC settings in their respective PAIs clinically
relevant in the IPF setting? Do they otherwise meet the principles for
inclusion in the IPF-PAI?
What impairments are most predictive of increased resource
intensity during an IPF stay?
h. Other Categories of Standardized Patient Assessment Data Elements
What other assessment elements would contribute to the
clinical utility of the IPF-PAI?
What other assessment elements would best capture medical
complexity in the interest of refining and improving the accuracy of
the IPF PPS?
What other assessment elements would inform CMS's
understanding of health equity for IPF patients?
Are there special interventions that IPFs provide which
support patients after discharge, and which could serve to reduce the
incidence of hospital readmissions for psychiatric conditions? What, if
any, assessment elements would inform CMS's understanding of such
interventions?
i. Implementation
We anticipate that IPFs will need to make changes to
systems and processes and train staff in order to administer the
assessment and submit assessment data by the implementation date. What
operational or practical limitations would IPFs face in making those
necessary changes? Are there particular categories of Standardized
Patient Assessment Data Elements that would be more or less feasible
for IPFs to operationalize? We are particularly interested in impacts
to facilities of varying sizes and ownership characteristics.
What forms of training and guidance would be most useful
for CMS to provide to support IPFs in the implementation of the IPF-
PAI?
j. Relationship to the IPFQR Program
Would having some measures which require data submission
through the HQR system and having other measures, which require data
collection and submission through the IPF-PAI increase operational
complexity or administrative burden? If so, how would you recommend
mitigating this complexity or burden?
Would any of the current chart-abstracted measures be
easier to report through the IPF-PAI? If so, which measures?
Would any of the current measures in the program be more
meaningful if they were stratified or risk-adjusted using data from the
required patient assessment categories or other categories not
specified by the CAA, 2023 that should be added to the IPF-PAI?
What new measure concepts, which would use data collected
through Standardized Patient Assessment Data Elements in the IPF-PAI,
should we consider?
V. Inpatient Psychiatric Facility Quality Reporting (IPFQR) Program
A. Background and Statutory Authority
The Inpatient Psychiatric Facility Quality Reporting (IPFQR)
Program is authorized by section 1886(s)(4) of the Act, and it applies
to psychiatric hospitals and psychiatric units paid by Medicare under
the IPF PPS (see section II.A. of this proposed rule for a detailed
discussion of entities covered under the IPF PPS). Section
1886(s)(4)(A)(i) requires the Secretary to reduce by 2 percentage
points the annual update to the standard Federal rate for discharges
occurring during such rate year \16\ for
[[Page 23205]]
any IPF that does not comply with quality data submission requirements
under IPFQR program, set forth in section 1886(s)(4)(C) of the Act,
with respect to an applicable rate year.
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\16\ We note that the statute uses the term ``rate year'' (RY).
However, beginning with the annual update of the inpatient
psychiatric facility prospective payment system (IPF PPS) that took
effect on July 1, 2011 (RY 2012), we aligned the IPF PPS update with
the annual update of the ICD codes, effective on October 1 of each
year. This change allowed for annual payment updates and the ICD
coding update to occur on the same schedule and appear in the same
Federal Register document, promoting administrative efficiency. To
reflect the change to the annual payment rate update cycle, we
revised the regulations at 42 CFR 412.402 to specify that, beginning
October 1, 2012, the IPF PPS RY means the 12-month period from
October 1 through September 30, which we refer to as a ``fiscal
year'' (FY) (76 FR 26435). Therefore, with respect to the IPFQR
Program, the terms ``rate year,'' as used in the statute, and
``fiscal year'' as used in the regulation, both refer to the period
from October 1 through September 30. For more information regarding
this terminology change, we refer readers to section III of the RY
2012 IPF PPS final rule (76 FR 26434 through 26435).
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Section 1886(s)(4)(C) of the Act requires IPFs to submit to the
Secretary data on quality measures specified by the Secretary under
section 1886(s)(4)(D) of the Act. Except as provided in section
1886(s)(4)(D)(ii) of the Act, section 1886(s)(4)(D)(i) of the Act
requires that any measure specified by the Secretary must have been
endorsed by the consensus-based entity (CBE) with a contract under
section 1890(a) of the Act. Section 1886(s)(4)(D)(ii) of the Act
provides that, in the case of a specified area or medical topic
determined appropriate by the Secretary for which a feasible and
practical measure has not been endorsed by the CBE with a contract
under section 1890(a) of the Act, the Secretary may specify a measure
that is not endorsed as long as due consideration is given to measures
that have been endorsed or adopted by a consensus organization
identified by the Secretary.
Section 4125(b)(1) of CAA, 2023 amended section 1886(s)(4) of the
Act, by inserting a new paragraph (E), to require IPFs participating in
the IPFQR Program to collect and submit to the Secretary certain
standardized patient assessment data, using a standardized patient
assessment instrument (PAI) developed by the Secretary, for RY 2028 (FY
2028) and each subsequent rate year. We refer readers to section IV.B
of this proposed rule in which we solicit public comment on the
development of this PAI.
We refer readers to the FY 2019 IPF PPS final rule (83 FR 38589)
for a discussion of the background and statutory authority of the IPFQR
Program. We have codified procedural requirements and reconsideration
and appeals procedures for IPFQR Program decisions in our regulations
at 42 CFR 412.433 and 412.434. Consistent with previous IPFQR Program
regulations, we refer to both inpatient psychiatric hospitals and
psychiatric units as ``facilities'' or ``IPFs.'' This usage follows the
terminology in our IPF PPS regulations at Sec. 412.402.
For additional information on procedural requirements related to
statutory authority, participation and withdrawal, data submission,
quality measure retention and removal, extraordinary circumstances
exceptions, and public reporting we refer readers to 42 CFR 412.433
Procedural requirements under the IPFQR Program.
For the IPFQR Program, we refer to the year in which an IPF would
receive the 2-percentage point reduction to the annual update to the
standard Federal rate as the payment determination year. An IPF
generally meets IPFQR Program requirements by submitting data on
specified quality measures in a specified time and manner during a data
submission period that occurs prior to the payment determination year.
These data reflect a period prior to the data submission period during
which the IPF furnished care to patients; this period is known as the
performance period. For example, for a measure for which CY 2025 is the
performance period which is required to be submitted in CY 2026 and
affects FY 2027 payment determination, if an IPF did not submit the
data for this measure as specified during CY 2026 (and meets all other
IPFQR Program requirements for the FY 2027 payment determination) we
would reduce by 2-percentage points that IPF's update for the FY 2027
payment determination year.
B. Measure Adoption
We strive to put patients and caregivers first, ensuring they are
empowered to partner with their clinicians in their healthcare decision
making using information from data driven insights that are
increasingly aligned with meaningful quality measures. We support
technology that reduces burden and allows clinicians to focus on
providing high-quality healthcare for their patients. We also support
innovative approaches to improve quality, accessibility, and
affordability of care while paying particular attention to improving
clinicians' and beneficiaries' experiences when interacting with our
programs. In combination with other efforts across HHS, we believe the
IPFQR Program helps to incentivize IPFs to improve healthcare quality
and value while giving patients and providers the tools and information
needed to make the best individualized decisions. Consistent with these
goals, our objective in selecting quality measures for the IPFQR
Program is to balance the need for information on the full spectrum of
care delivery and the need to minimize the burden of data collection
and reporting. We have primarily focused on measures that evaluate
critical processes of care that have significant impact on patient
outcomes and support CMS and HHS priorities for improved quality and
efficiency of care provided by IPFs. When possible, we also propose to
incorporate measures that directly evaluate patient outcomes and
experience. We refer readers to the CMS National Quality Strategy,\17\
the Behavioral Health Strategy,\18\ the Framework for Health
Equity,\19\ and the Meaningful Measures Framework \20\ for information
related to our priorities in selecting quality measures.
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\17\ Schreiber, M, Richards, A, et al. (2022). The CMS National
Quality Strategy: A Person-Centered Approach to Improving Quality.
Available at: https://www.cms.gov/blog/cms-national-quality-strategy-person-centered-approach-improving-quality.
\18\ CMS. (2022). CMS Behavioral Health Strategy. Available at
https://www.cms.gov/cms-behavioral-health-strategy.
\19\ CMS. (2022). CMS Framework for Health Equity 2022-2032.
Available at https://www.cms.gov/files/document/cms-framework-health-equity-2022.pdf.
\20\ CMS. (2023). Meaningful Measures 2.0: Moving from Measure
Reduction to Modernization. Available at https://www.cms.gov/medicare/quality/meaningful-measures-initiative/meaningful-measures-20. Accessed on March 20, 2024.
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1. Measure Selection Process
Section 1890A(a) of the Act requires that the Secretary establish
and follow a pre-rulemaking process, in coordination with the CBE
contracted under 1890(a) of the Act, to solicit input from multi-
stakeholder groups on the selection of quality and efficiency measures
for the IPFQR Program. Before being proposed for inclusion in the IPFQR
Program, measures are placed on a list of Measures Under Consideration
(MUC list), which is published annually. Following publication on the
MUC list, a multi-stakeholder group convened by the CBE reviews the
measures under consideration for the IPFQR Program, among other federal
programs, and provides input on those measures to the Secretary. Under
the Partnership for Quality Measurement (PQM), which is convened by the
entity which currently holds the contract under 1890(a) of the Act,
this process is known as the Pre-Rulemaking Measure Review (PRMR). We
consider the input and recommendations provided by this multi-
stakeholder group in selecting all measures for the IPFQR Program,
including the 30-Day Risk-Standardized All-Cause Emergency Department
(ED) Visit Following an IPF Discharge measure discussed in this
proposed rule.
[[Page 23206]]
2. Proposal To Adopt the 30-Day Risk-Standardized All-Cause ED Visit
Following an IPF Discharge Measure Beginning With the CY 2025
Performance Period/FY 2027 Payment Determination
a. Background
We have consistently stated our commitment to identifying measures
that examine the care continuum for patients with mental health
conditions and substance use disorders and to quantify outcomes
following IPF-discharge (see for example, the adoption of the
Medication Continuation Following Hospitalization in an IPF measure in
the FY 2020 IPF PPS Final Rule, 84 FR 38460 through 38462). Post-
discharge outcomes are an important part of our measurement strategy
because patient-centered discharge planning and coordination of care
for patients with any combination of mental health conditions and
substance use disorders improves long-term outcomes, including reducing
readmissions and other post-discharge acute care
services.21 22
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\21\ Nelson, E.A. Maruish, M.E., Axler, J.L. Effects of
Discharge Planning with Outpatient Appointments on Readmission
Rates. https://ps.psychiatryonline.org/doi/10.1176/appi.ps.51.7.885.
\22\ Steffen S, K[ouml]sters M, Becker T, Puschner B. Discharge
planning in mental health care: a systematic review of the recent
literature. Acta Psychiatr Scand. 2009 Jul;120(1):1-9. doi: 10.1111/
j.1600-0447.2009.01373.x. Epub 2009 Apr 8. PMID: 19486329.
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Although not all post-discharge acute care visits are preventable,
there are actions that the IPF can take to maximize the chance for
patients' successful community reintegration.\23\ For example, care
transition models to reduce the need for additional acute care
following an inpatient stay have been adapted to the inpatient
psychiatric setting. To implement these models, IPFs may need to
consider how to include the patient and their caregivers, including
family, in discharge planning, how to communicate with post-discharge
providers, and how to ensure whole-person care for patients during and
following their discharge.\24\ Specifically, IPFs may need to assist
patients in connecting with outpatient providers, such as coordinating
with the patient and their caregiver to schedule the patient's first
post-discharge follow-up appointment, arranging for the patient's
intensive outpatient (IOP) care, or connecting to peer support
services. Additionally, IPFs may need to identify and address barriers
patients may face in accessing medications and adhering to scheduled
post-discharge follow-up appointments. Barriers may include financial
factors, transportation, and childcare, which may necessitate support
from social services, beginning during hospitalization and continuing
after discharge.25 26 Barriers may also include the
patient's concerns regarding the stigmatization associated with seeking
care post-discharge. This can be addressed through treatment provided
during the IPF stay.27 28 Improvements in patient experience
of care and patient-centeredness of care have been associated with
improved follow-up post-discharge and a reduction in patients requiring
post-discharge acute care.29 30 In summary, by proactively
addressing potential barriers to post-charge care, improving patient
experience of care and patient-centeredness of care, and implementing
care transition models, IPFs can reduce the need for post-discharge
acute care.
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\23\ Haselden, M., Corbeil, T., Tang, F., Olfson, M., Dixon,
L.B., Essock, S.M., Wall, M.M., Radigan, M., Frimpong, E., Wang, R.,
Lamberti, S., Schneider, M., & Smith, T.E. (2019). Family
Involvement in Psychiatric Hospitalizations: Associations With
Discharge Planning and Prompt Follow-Up Care. Psychiatric Services,
70(10), 860-866. https://doi.org/10.1176/appi.ps.201900028.
\24\ Pincus, Harold, Care Transition Interventions to Reduce
Psychiatric Re-Hospitalizations. National Association of State
Mental Health Program Directors. 2015. Available at https://nasmhpd.org/sites/default/files/Assessment%20%233_Care%20Transitions%20Interventions%20toReduce%20Psychiatric%20Rehospitalization.pdf. Accessed on January 23, 2024.
\25\ Allen, E.M., Call, K.T., Beebe, T.J., McAlpine, D.D., &
Johnson, P.J. (2017). Barriers to Care and Healthcare Utilization
among the Publicly Insured. Medical Care, 55(3), 207-214.
doi:10.1097/MLR.0000000000000644.
\26\ Mutschler, C., Lichtenstein, S., Kidd, S.A., & Davidson, L.
(2019). Transition experiences following psychiatric
hospitalization: A systematic review of the literature. Community
Mental Health Journal, 55(8), 1255-1274. doi:10.1007/s10597-019-
00413-9.
\27\ Allen, E.M., Call, K.T., Beebe, T.J., McAlpine, D.D., &
Johnson, P.J. (2017). Barriers to Care and Healthcare Utilization
among the Publicly Insured. Medical Care, 55(3), 207-214.
doi:10.1097/MLR.0000000000000644.
\28\ Mutschler, C., Lichtenstein, S., Kidd, S.A., & Davidson, L.
(2019). Transition experiences following psychiatric
hospitalization: A systematic review of the literature. Community
Mental Health Journal, 55(8), 1255-1274. doi:10.1007/s10597-019-
00413-9.
\29\ Donisi V, Tedeschi F, Wahlbeck K, Haaramo P, Amaddeo F.
Pre-discharge factors predicting readmissions of psychiatric
patients: a systematic review of the literature. BMC Psychiatry.
2016 Dec 16;16(1):449. doi: 10.1186/s12888-016-1114-0. PMID:
27986079; PMCID: PMC5162092.
\30\ Morgan C Shields, Mara A G Hollander, Alisa B Busch, Zohra
Kantawala, Meredith B Rosenthal, Patient-centered inpatient
psychiatry is associated with outcomes, ownership, and national
quality measures, Health Affairs Scholar, Volume 1, Issue 1, July
2023, qxad017, https://doi.org/10.1093/haschl/qxad017.
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The IPFQR Program currently has three measures that assess post-
discharge outcomes: (1) Follow-up After Psychiatric Hospitalization
(FAPH); (2) Medication Continuation Following Inpatient Psychiatric
Discharge; and (3) Thirty Day All-Cause Unplanned Readmission Following
Psychiatric Hospitalization (CBE #2860, the IPF Unplanned Readmission
measure). Each of these measures serves a unique role in assessing care
coordination and post-discharge outcomes.
The FAPH measure, which we adopted in the FY 2022 IPF PPS Final
Rule (86 FR 42640 through 42645), uses Medicare FFS claims to determine
the percentage of inpatient discharges from an IPF stay for which the
patient received a follow-up visit for treatment of mental illness. The
FAPH measure represents an important component of post-discharge care
coordination, specifically the transition of care to an outpatient
provider. However, this measure does not quantify patient outcomes.
The Medication Continuation Following Inpatient Psychiatric
Discharge measure, which we adopted in FY 2020 IPF PPS Final Rule (84
FR 38460 through 38465), assesses whether patients admitted to IPFs
with diagnoses of Major Depressive Disorder (MDD), schizophrenia, or
bipolar disorder filled at least one evidence-based medication prior to
discharge or during the post-discharge period. Medication continuation
is important for patients discharged from the IPF setting with these
disorders because of significant negative outcomes associated with non-
adherence to medication regimes. However, this measure does not
quantify patient outcomes with respect to the use of acute care
services post-discharge.
The IPF Unplanned Readmission measure, which we adopted in the FY
2017 IPPS/LTCH PPS final rule (81 FR 57241 through 57246), assesses
outcomes associated with worsening condition, potentially due to
insufficient discharge planning and post-discharge care coordination,
by assessing post-discharge use of acute care. The IPF Unplanned
Readmission measure estimates the incidence of unplanned, all-cause
readmissions to IPFs or short-stay acute care hospitals following
discharge from an eligible IPF index admission. A readmission is
defined as any admission that occurs within 3 to 30 days after the
discharge date from an eligible index admission to an IPF, except those
considered planned.\31\ However, this measure does not quantify the
proportion of patients 18 and older with an ED visit, without
[[Page 23207]]
subsequent admission, within 30 days of discharge from an IPF. Without
collecting this information in a measure, we believe there is a gap in
our understanding regarding patients' successful reintegration into
their communities following their IPF discharge.
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\31\ https://p4qm.org/measures/2860.
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To further understand this gap, we analyzed post-discharge outcomes
using claims data. In this analysis, we determined that, for patients
discharged from IPFs, the risk-adjusted rate of ED visits after an IPF
discharge between June 1, 2019 and July 31, 2021 (excluding the first
two quarters of 2020 due to the COVID-19 public health emergency) was
20.7 percent. The rate of readmissions captured under the IPF Unplanned
Readmission measure for this same period was 20.1 percent.\32\ This
means that approximately 40 percent of patients discharged from an IPF
had either an ED visit or an unplanned readmission within 30-days of
IPF discharge, but only about half of those visits are being captured
in the publicly reported IPF Unplanned Readmission measure. Visits to
an ED within 30 days of discharge from an IPF (regardless of whether
that visit results in a hospital readmission, observation stay,
discharge, or patient leaving without being seen) often indicate
deteriorating or heightened mental or physical health needs. That is,
these visits often represent a patient seeking care for symptoms that
were present during the patient's stay in the IPF, regardless of
whether the symptom was the reason for the admission, that have become
worse for the patient in the time since discharge. Therefore, we
believe that IPFs and the public would benefit from having these data
made publicly available to inform care decisions and quality
improvement efforts. Specifically, members of the public could use
these data to inform care decisions and IPFs could use these data to
compare their performance to that of similar IPFs. For example, by
having these data publicly reported IPFs could compare their
performance with that of other IPFs with similar patient populations, a
comparison which is not possible without this measure. If IPFs
identified that other IPFs with similar patient populations had better
rates of post-discharge ED visits (that is, other IPFs had fewer
patients seek care in an ED within 30 days of discharge from the IPF),
the IPF could identify a need to evaluate discharge planning and post-
discharge care coordination to identify process changes which could
improve outcomes.
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\32\ As depicted in the April 2023 file available at https://data.cms.gov/provider-data/archived-data/hospitals.
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To address this gap, we developed and are proposing the inclusion
of the new, claims-based 30-Day Risk-Standardized All-Cause ED Visit
Following an IPF Discharge measure (the IPF ED Visit measure) in the
IPFQR program beginning with the CY 2025 performance period/FY 2027
payment determination. This proposed IPF ED Visit measure aims to
provide information to patients, caregivers, other members of the
public, and IPFs about the proportion of patients who seek care in ED
in the 30 days following discharge from an IPF, but are not admitted as
an inpatient to an acute care hospital or IPF. This proposed measure
would assess the proportion of patients 18 and older with an ED visit,
including observation stays, for any cause, within 30 days of discharge
from an IPF, without subsequent admission.
We recognize that not all post-discharge ED visits are preventable,
nor are all post-discharge ED visits associated with the initial IPF
admission. However, we developed an all-cause ED visit rate, as opposed
to a more narrowly focused measure of ED admissions for mental health
or substance use concerns, for three primary reasons. First, such a
measure aligns most closely with the IPF Unplanned Readmission measure
as this measure is also an all-cause measure. Second, an all-cause
measure emphasizes the importance of whole-person care for patients.
Whole-person care, during the inpatient stay and through referral at
discharge, includes addressing the conditions that may jeopardize a
patient's health, but are not the reason for admission to the IPF, if
the IPF has reason to identify these conditions during the course of
treatment. For example, if an IPF were to identify through metabolic
screening that a patient has diabetes, it would be appropriate for that
IPF to recommend appropriate follow-up for that patient, such as with a
primary care provider, endocrinologist, or dietician. Such post-
discharge coordination of care could prevent the patient from seeking
acute care after discharge from the IPF for complications of diabetes,
such as diabetic ketoacidosis. Third, this measure includes ED visits
for all conditions because patients visiting the ED may do so for
physical symptoms associated with a mental health condition or
substance use disorder. An example is a patient with anxiety that
presents to the ED with chest pain and shortness of breath. If the
clinician documents the primary diagnosis as chest pain (R07.9) or
shortness of breath (R06.02), the patient would not be included in a
mental health and substance use-specific IPF ED Visit measure, despite
their history of anxiety (F41.9), a potential contributor to their
presenting symptoms at the ED. We recognize that it is possible that
such a visit may not be related to the patient's anxiety. However,
while not all acute care visits after discharge from an IPF are
preventable or necessarily related to the quality of care provided by
the IPF, there is evidence that improvements in the quality of care for
patients in the IPF setting can reduce rates of patients seeking acute
care after discharge from an IPF, representing an improved outcome for
patients.\33\
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\33\ See for instance Chung, D.T., Ryan, C.J., Hadzi-Pavlovic,
D., Singh, S.P., Stanton, C., & Large, M.M. (2017). Suicide rates
after discharge from psychiatric facilities: A systematic review and
meta-analysis. JAMA Psychiatry, 74(7), 694-702. https://doi.org/10.1001/jamapsychiatry.2017.1044 or Durbin, J., Lin, E., Layne, C.,
et al. (2007). Is readmission a valid indicator of the quality of
inpatient psychiatric care? Journal of Behavioral Health Services
Research, 34, 137-150. doi:10.1007/s11414- 007-9055-5.
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Additionally, we considered whether 30 days was an appropriate
timeframe for this measure. That is, we sought to identify whether a
measure that assessed post-discharge ED visits over a period shorter or
longer than 30 days would be more appropriate. Because IPFs are already
familiar with interpreting data for the 30-day period in the IPF
Unplanned Readmission measure, we determined that it would be
appropriate to maintain the 30-day period for the IPF ED Visit measure.
Additionally, by maintaining the same timeframe as the IPF Unplanned
Readmission measure, we can provide IPFs and patients with a more
complete picture of acute care among IPF patients after discharge from
the IPF.
Pursuant to the Meaningful Measures 2.0 Framework (a CMS initiative
that identifies priority domains for measures within CMS Programs
\34\), this measure addresses the ``Seamless Care Coordination'' and
the ``Person-Centered Care'' quality domains by encouraging facilities
to provide patient-centric discharge planning and support post-
discharge care transitions. The IPF ED Visit measure also aligns with
the CMS National Quality Strategy Goals \35\ of ``Engagement'' and
``Outcomes and Alignment.'' It supports outcomes and
[[Page 23208]]
alignment because this measure provides a quantified estimate of one
post-discharge outcome that patients may experience, that is a post-
discharge acute care visit that does not result in an admission. It
also supports the Behavioral Health Strategy \36\ domains of ``Quality
of Care'' and ``Equity and Engagement'' because engaging patients to
improve post-discharge outcomes is an element of providing quality
care. Furthermore, similar to the Meaningful Measures domain of
``Person-Centered Care,'' this measure supports the Universal
Foundation domain of ``Person-Centered Care.''
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\34\ https://www.cms.gov/medicare/quality/meaningful-measures-initiative/meaningful-measures-20.
\35\ Schreiber, M, Richards, A, et al. (2022). The CMS National
Quality Strategy: A Person-Centered Approach to Improving Quality.
Available at: https://www.cms.gov/blog/cms-national-quality-strategy-person-centered-approach-improving-quality.
\36\ CMS. (2022). CMS Behavioral Health Strategy. Available at
https://www.cms.gov/cms-behavioral-health-strategy.
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b. Overview of Measure
The IPF ED Visit measure was developed with input from clinicians,
patients, and policy experts; the measure was subject to the pre-
rulemaking process required by section 1890A of the Act, as discussed
further in section V.B.1 of this rule. Consistent with the CMS key
elements of the CMS Measure Development Lifecycle,\37\ we began with
measure conceptualization during which we performed a targeted
literature review and solicited input from a behavioral health
technical expert panel (TEP). This allowed us to ensure that this topic
addresses a gap that is important to interested parties. After
confirming this, we developed the measure specifications for the IPF ED
Visit measure. With these specifications, we issued a 30-day call for
public comment in the Federal Register and performed empirical testing
using claims data, including modeling for risk-adjustment. After
refining the measure specifications based on testing and public
comment, we performed an equity analysis in which we tested the risk-
adjustment methodology to ensure that the measure does not reflect
access issues related to patient demographics instead of quality of
care. By following steps in accordance with the Measure Development
Lifecycle, we sought to ensure that this is a vetted, valid, reliable,
and ready-to-implement claims-based measure which would assess the
proportion of patients 18 and older with an ED visit, including
observation stays, for any cause, within 30 days of discharge from an
IPF, without subsequent admission. By using the same definitions of
index admission and patient populations as those used in the IPF
Unplanned Readmission measure, we have designed the IPF ED Visit
measure to complement the IPF Unplanned Readmission measure to the
extent possible. We have also sought to minimize administrative burden
by developing this as a claims-based measure so that it adds no
information collection burden to clinicians and staff working in the
IPF setting.
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\37\ https://mmshub.cms.gov/blueprint-measure-lifecycle-overview.
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(1) Measure Calculation
The focus population for this measure is adult Medicare FFS
patients with a discharge from an IPF. The measure is based on all
eligible index admissions from the focus population. An eligible index
admission is defined as any IPF admission for which the patient meets
the following criteria: (1) age 18 or older at admission; (2)
discharged alive from an IPF; (3) enrolled in Medicare FFS Parts A and
B during the 12 months before the admission date, the month of
admission, and at least one month after the month of discharge from the
index admission (that is, the original stay in an IPF); and (4)
discharged with a principal diagnosis that indicates a psychiatric
disorder. Excluded from the measure are patients discharged against
medical advice (AMA) from the IPF index admission (because the IPF may
not have had the opportunity to conduct full discharge planning for
these patients); patients with unreliable data regarding death
demographics or a combination thereof in their claims record (because
these data are unreliable, they may lead to inaccuracies in the measure
calculation); patients who expired during the IPF stay (because post-
discharge care is not applicable to these patients); patients with a
discharge resulting in a transfer to another care facility (because the
receiving care facility would be responsible for discharge planning for
these patients); and patients discharged but readmitted within 3 days
of discharge, also known as an interrupted stay (because interrupted
stays are often reflective of patient needs outside of the IPF, such as
treatment for another condition).
To calculate the measure, we would use the following data sources
which are all available from Medicare administrative records and data
submitted by providers through the claims process: (1) Medicare
beneficiary and coverage files, which provide information on patient
demographic, enrollment, and vital status information to identify the
measure population and certain risk factors; (2) Medicare FFS Part A
records, which contain final action claims submitted by acute care and
critical access hospitals, IPFs, home health agencies, and skilled
nursing facilities to identify the measure population, readmissions,
and certain risk factors; and (3) Medicare FFS Part B records, which
contain final action claims submitted by physicians, physician
assistants, clinical social workers, nurse practitioners, and other
outpatient providers to identify certain risk factors. To ensure that
diagnoses result from encounters with providers trained to establish
diagnoses, this measure would not use claims for services such as
laboratory tests, medical supplies, or other ambulatory services. Index
admissions and ED visits would be identified in the Medicare FFS Part A
records. Comorbid conditions for risk-adjustment would be identified in
the Medicare Part A and Part B records in the 12 months prior to
admission, including the index admission. Demographic and FFS
enrollment data would be identified in the Medicare beneficiary and
coverage files.
To calculate the IPF ED Visit measure, CMS would: (1) identify all
IPF admissions in the one-year performance period; (2) apply inclusion
and exclusion criteria to identify index admissions; (3) identify ED
visits and observation stays within 30 days of discharge from each
index admission; (4) identify risk factors in the 12 months prior to
index admission and during the index admission; and (5) run
hierarchical logistic regression to compute the risk-standardized ED
visit rate for each IPF.\38\ This hierarchical logistic regression
would allow us to apply the risk-adjustment factors developed in
measure testing to ensure that measure results are comparable across
IPFs regardless of the clinical complexity of each IPF's patient
population.
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\38\ For an example of the hierarchal logistic risk-adjustment
algorithm, we refer readers to the algorithm for the IPF Unplanned
Readmission measure at https://www.cms.gov/medicare/quality-initiatives-patient-assessment-instruments/hospitalqualityinits/downloads/inpatient-psychiatric-facility-readmission-measure.zip.
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(2) Pre-Rulemaking Measure Review and Measure Endorsement
As required under section 1890A of the Act, the CBE established the
Partnership for Quality Measurement (PQM) to convene clinicians,
patients, measure experts, and health information technology
specialists to participate in the pre-rulemaking process and the
measure endorsement process. The pre-rulemaking process, also called
the Pre-Rulemaking Measure Review (PRMR), includes a review of measures
published on the publicly available list of Measures Under
Consideration (MUC List) by one of several committees convened by the
PQM for the purpose
[[Page 23209]]
of providing multi-stakeholder input to the Secretary on the selection
of quality and efficiency measures under consideration for use in
certain Medicare quality programs, including the IPFQR Program. The
PRMR process includes opportunities for public comment through a 21-day
public comment period, as well as public listening sessions. The PQM
posts the compiled comments and listening session inputs received
during the public comment period and the listening sessions within five
days of the close of the public comment period.\39\ More details
regarding the PRMR process may be found in the CBE's Guidebook of
Policies and Procedures for Pre-Rulemaking Measure Review and Measure
Set Review, including details of the measure review process in Chapter
3.\40\
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\39\ These materials are available at the PRMR section of the
PQM website: https://p4qm.org/PRMR.
\40\ https://p4qm.org/sites/default/files/2023-09/Guidebook-of-Policies-and-Procedures-for-Pre-Rulemaking-Measure-Review-%28PRMR%29-and-Measure-Set-Review-%28MSR%29-Final_0.pdf.
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The CBE-established PQM also conducts the measure endorsement and
maintenance (E&M) process to ensure measures submitted for endorsement
are evidence-based, reliable, valid, verifiable, relevant to enhanced
health outcomes, actionable at the caregiver-level, feasible to collect
and report, and responsive to variations in patient characteristics,
such as health status, language capabilities, race or ethnicity, and
income level, and are consistent across types of health care providers,
including hospitals and physicians (see section 1890(b)(2) of the Act).
The PQM convenes several E&M project groups twice yearly, formally
called E&M Committees, each comprised of an E&M Advisory Group and an
E&M Recommendations Group, to vote on whether a measure meets certain
quality measure criteria. More details regarding the E&M process may be
found in the E&M Guidebook, including details of the measure
endorsement process in the section titled, ``Endorsement and Review
Process.'' \41\
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\41\ The Partnership for Quality Measurement. (October 2023).
Endorsement and Maintenance (E&M) Guidebook. Available at: https://p4qm.org/sites/default/files/2023-12/Del-3-6-Endorsement-and-Maintenance-Guidebook-Final__0.pdf.
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As part of the PRMR process, the IPF ED Visit measure was reviewed
during the PRMR Hospital Recommendation Group meeting on January 18,
2024. For the voting procedures of the PRMR and E&M process, the PQM
utilized the Novel Hybrid Delphi and Nominal Group (NHDNG) multi-step
process, which is an iterative consensus-building approach aimed at a
minimum of 75 percent agreement among voting members, rather than a
simple majority vote, and supports maximizing the time spent to build
consensus by focusing discussion on measures where there is
disagreement. For example, the PRMR Hospital Recommendation Group can
reach consensus and have the following voting results: (A) Recommend,
(B) Recommend with conditions (with 75 percent of the votes cast as
recommend with conditions or 75 percent between recommend and recommend
with conditions), and (C) Do not recommend. If no voting category
reaches 75 percent or greater (including the combined [A] Recommend and
[B] Recommend with conditions) the PRMR Hospital Recommendation Group
did not come to consensus and the voting result is ``Consensus not
reached.'' Consensus not reached signals continued disagreement amongst
the committee despite being presented with perspectives from public
comment, committee member feedback and discussion, and highlights the
multi-faceted assessments of quality measures. More details regarding
the PRMR voting procedures may be found in Chapter 4 of the PQM
Guidebook of Policies and Procedures for Pre-Rulemaking Measure Review
and Measure Set Review.\42\ More details regarding the E&M voting
procedures may be found in the PQM Endorsement and Maintenance (E&M)
Guidebook.\43\ The PRMR Hospital Recommendation Group \44\ reached
consensus and recommended including this measure in the IPFQR Program
with conditions.
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\44\ We note that the PRMR Hospital Recommendation Group was
previously the Measure Applications Partnership (MAP) Hospital
Workgroup under the pre-rulemaking process followed by the previous
CBE.
---------------------------------------------------------------------------
Seven members of the group recommended adopting the measure into
the IPFQR program without conditions; eleven members recommended
adoption with conditions; and one committee member voted not to
recommend the measure for adoption. Taken together, 94.73 percent of
the votes were between recommend & recommend with conditions.
The conditions specified by the PRMR Hospital Recommendation Group
were: (1) that the measure be considered for endorsement by a
consensus-based entity; and (2) further consideration of how the
measure addresses 72-hour transfers to the ED. We have taken those
considerations into account and are proposing this measure for adoption
because we believe we have adequately addressed the concerns raised by
those considerations.
To address the first condition, we have submitted the measure to
the CBE for consideration. For more information on submission to and
consideration by the CBE we refer readers to section V.B.2.b.(3) of
this rule.
The second voting condition requested that we further consider how
the measure addresses 72-hour transfers to the ED because of concerns
that IPFs may appear to have worse performance if ``interrupted stays''
are not excluded from the measure. An ``interrupted stay'' occurs when
a patient is discharged from an IPF and readmitted to the same IPF
within 72 hours. This frequently occurs when a patient needs medical
treatment that is beyond the scope of the IPF, such as care in an ED
for an emergent health issue. We believe that this concern is
sufficiently addressed in the ED Visit measure's specifications because
these ``interrupted stays'' are excluded from the measure, as described
in section V.B.2.b.(1) of this rule. This exclusion is defined as an
index admission with a readmission on Days 0, 1, or 2 post-discharge.
In other words, patients transferred to the ED and subsequently
readmitted to the IPF within 72 hours are excluded from the measure.
Therefore ``interrupted stays'' are excluded from the measure as per
the group's recommendation.
(3) CBE Endorsement
Section 1886(s)(4)(D)(i) of the Act generally requires that
measures specified by the Secretary shall be endorsed by the entity
with a contract under section 1890(a) of the Act (that is, the CBE).
After a measure has been submitted to the CBE, the committee
responsible for reviewing the measure evaluates the measure on five
domains: (1) Importance; (2) Feasibility; (3) Scientific Acceptability
(that is, reliability and validity); (4) Equity; and (5) Use and
Usability. Committee members evaluate whether the measure the domain is
``Met'', ``Not Met but Addressable'' or ``Not Met'' for each domain
using a set of criteria provided by the CBE.\45\ When a measure is
submitted it is assigned to one of the CBE's projects based on where in
the patient's healthcare experience the measure has the most relevance.
The five projects are (1) Primary Prevention; (2) Initial Recognition
and Management; (3) Management of Acute Events, Chronic Disease,
Surgery, Behavioral Health; (4) Advanced Illness and Post-Acute Care;
and (5) Cost and Efficiency.
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\45\ https://p4qm.org/EM.
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The measure developer submitted the measure for CBE endorsement
consideration in the Fall 2023 review
[[Page 23210]]
cycle. The measure was assigned to the Cost and Efficiency Project. The
CBE Cost and Efficiency Endorsement committee met on January 31, 2024
and did not reach consensus regarding the IPF ED Visit measure, with
60.6 percent voting in favor of endorsement or endorsement with
conditions and the remaining members voting to not endorse, which is
below the 75 percent threshold necessary for the endorsement of the
measure, as described in V.B.2.b. During the Cost and Efficiency
Endorsement committee's meeting, members of the committee discussed
whether an all-cause measure was appropriate and whether IPFs are able
to implement interventions to reduce post-discharge acute care.\46\
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\46\ For information about the Cost and Efficiency endorsement
review we refer readers to the meeting summary, available at https://p4qm.org/sites/default/files/Cost%20and%20Efficiency/material/EM-Cost-and-Efficiency-Fall2023-Endorsement-Meeting-Summary.pdf.
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As discussed in section V.B.2.a of this proposed rule, an all-cause
measure would complement the IPF Unplanned Readmission measure, would
emphasize whole-person care, and would capture visits to the ED for
patients with physical symptoms associated with mental health
conditions. Additionally, evidence shows that there are interventions
that reduce post-discharge acute care. These include adopted care
transition models, proactively connecting patients with post-discharge
providers, identifying and addressing patients' barriers to post-
discharge care, and focusing on providing patient-centered care and
improving patient experience of care.
Although section 1886(s)(4)(D)(i) of the Act generally requires
that measures specified by the Secretary shall be endorsed by the
entity with a contract under section 1890(a) of the Act, section
1886(s)(4)(D)(ii) of the Act states that, in the case of a specified
area or medical topic determined appropriate by the Secretary for which
a feasible and practical measure has not been endorsed by the entity
with a contract under section 1890(a) of the Act, the Secretary may
specify a measure that is not so endorsed as long as due consideration
is given to a measure that has been endorsed or adopted by a consensus
organization identified by the Secretary.
We have determined that this is an appropriate topic for the
adoption of a measure absent CBE endorsement because where possible we
focus on measures that assess patient outcomes. Unplanned use of acute
care after discharge from an IPF is often associated with worsening
condition, potentially due to insufficient discharge planning and post-
discharge care coordination. While the IPFQR Program currently has a
measure that assesses unplanned readmissions after discharge from an
IPF, there is a gap in the measure set with respect to unplanned ED
visits without a subsequent admission to an acute care hospital or IPF.
The IPF ED Visit measure fills that gap. We also reviewed CBE-endorsed
measures and were unable to identify any other CBE-endorsed measures
that assess outcomes that solely result in a patient's ED visit after
the patient's discharge from an IPF. The only endorsed measure that we
identified that addresses an IPF patient seeking acute care after
discharge is the IPF Unplanned Readmission measure. As we discussed
previously, the IPF Unplanned Readmission measure does not assess ED
visits that do not result in an admission. Therefore, we believe that
the IPF ED Visit measure is an important complement to the IPF
Unplanned Readmission measure. We did not find any other measures that
assess post-discharge ED visits without a subsequent admission, and
therefore the exception in section 1886(s)(4)(D)(ii) of the Act
applies.
c. Data Collection, Submission, and Reporting
Because all files used to calculate the IPF ED Visit measure are
available on Medicare claims, this measure requires no additional data
collection or submission by IPFs. We are proposing a reporting period
beginning with data from CY 2025 performance period/FY 2027 payment
determination year.
C. Summary of IPFQR Program Measures for the FY IPFQR Program
We are proposing one new measure for the FY 2027 IPFQR Program. If
we finalize adoption of this measure, the FY 2027 IPFQR Program measure
set would include 16 mandatory and one voluntary measure. Table 22 sets
forth the measures in the FY 2027 IPFQR Program.
BILLING CODE 4120-01-P
[[Page 23211]]
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BILLING CODE 4120-01-C
D. Proposal To Modify Data Submission Requirements for the FY 2027
Payment Determination and Subsequent Years
Section 1886(s)(4)(C) of the Act requires the submission of quality
data in a form and manner, and at a time, specified by the Secretary.
In the Medicare Program; Hospital Inpatient Prospective Payment Systems
for Acute Care Hospitals and the Long-Term Care Hospital Prospective
Payment System and fiscal year 2013 Rates; Hospitals' Resident Caps for
Graduate Medical Education Payment Purposes; Quality Reporting
Requirements for Specific Providers and for Ambulatory Surgical Centers
(FY 2013 IPPS/LTCH PPS) final rule (77 FR 53655), we specified that
data must be submitted between July 1 and August 15 of the calendar
year preceding a given payment determination year (for example, data
were required to be submitted between July 1, 2015 and August 15, 2015
for the FY 2016 payment determination). In the Medicare Program;
Hospital Inpatient Prospective Payment Systems for Acute Care Hospitals
and the Long-Term Care Hospital Prospective Payment System and fiscal
year 2014 Rates; Quality Reporting Requirements for Specific Providers;
Hospital Conditions of Participation; Payment Policies Related to
Patient Status (FY 2014 IPPS/LTCH PPS) final rule (78 FR 50899), we
clarified that this policy applied to all future years of data
submission for the IPFQR Program unless we changed the policy through
future rulemaking.
In the FY 2018 IPF PPS final rule (82 FR 38472 through 38473) we
updated this policy by stating that the data submission period will be
a 45-day period beginning at least 30 days
[[Page 23212]]
following the end of the data collection period and that we will
provide notification of the exact dates through subregulatory means.
In the FY 2022 IPF PPS Final Rule (86 FR 42658 through 42661), we
finalized voluntary patient-level data reporting for the FY 2023
payment determination and mandatory patient-level data reporting for
chart-abstracted measures within the IPFQR Program beginning with FY
2024 payment determination and subsequent years. The measures currently
in the IPFQR Program affected by this requirement are set forth in
Table 23.
[GRAPHIC] [TIFF OMITTED] TP03AP24.035
As we have gained experience with patient-level data submission for
the IPFQR program, during the voluntary data submission period for FY
2023 (which occurred in CY 2022) and the first mandatory data
submission period for FY 2024 (which occurred in CY 2023), we have
observed that annual data submission periods require IPFs to store
large volumes of patient data to prepare for transmission to CMS.
Furthermore, the volume of data associated with all IPFs reporting a
full year of patient-level data during one data submission period
creates the risk that systems will be unable to handle the volume of
data.
We have reviewed how other quality reporting programs that require
patient-level data submission address these concerns and determined
that the Hospital Inpatient Quality Reporting (IQR) Program (78 FR
50811) and the Hospital Outpatient Quality Reporting (OQR) Program (72
FR 66872) both require quarterly submission of patient-level data. As
we considered requiring quarterly reporting for the IPFQR Program, we
also determined that increasing the frequency of data submission would
allow additional analysis of measure trends over time. We believe that
having additional data points (from additional quarters of data) could
allow for more nuanced analyses of the IPFQR Program's measures.
Specifically, we would be able to better identify quarterly highs or
lows that may be less apparent when data are combined over a full year.
We recognize that, if we update data reporting requirements to require
reporting four times per year instead of once per year, then IPFs would
need to meet four incremental deadlines instead of one deadline, and
that this increases the risk that an individual IPF may fail to submit
data specified for the measures and not receive its full market basket
update. However, we believe that this risk is low because IPFs already
have experience submitting some data required by the IPFQR Program on a
more frequent basis. Specifically, the COVID-19 Healthcare Personnel
(HCP) Vaccination Measure is currently reported into the CDC's National
Healthcare Safety Network (NHSN) for one week per month resulting in a
quarterly measure result (as originally adopted in the FY 2022 IPF PPS
final rule (86 FR 42636) and restated in the FY 2024 IPF PPS final rule
(88 FR 51131 through 51132). In addition, if this proposal for
quarterly data submission is finalized, data submission for each
calendar quarter would be required during a period of at least 45 days
beginning three months after the end of the calendar quarter. Table 24
summarizes these proposed deadlines for the CY 2025 and CY 2026
performance periods:
[[Page 23213]]
[GRAPHIC] [TIFF OMITTED] TP03AP24.036
Furthermore, we are proposing that all data which continue to be
reported on an annual basis (that is, non-measure data, aggregate
measures, and attestations) would be required to be reported
concurrently with the data from the fourth quarter of the applicable
year. For example, data reflecting the entirety of CY 2025 (that is,
non-measure data, aggregate measures, and attestations) would be
required by the Q4 2025 submission deadline (that is, May 15, 2026).
We welcome comments on this proposal.
VI. Collection of Information Requirements
Under the Paperwork Reduction Act of 1995 (PRA) (44 U.S.C. 3501 et
seq.), 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. For the purposes of the PRA and this section
of the preamble, collection of information is defined under 5 CFR
1320.3(c) of the PRA's implementing regulations.
To fairly evaluate whether an information collection should be
approved by OMB, section 3506(c)(2)(A) of the 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.
We are soliciting public comment (see section VI.C of this proposed
rule) on each of these issues for the following sections of this
document that contain information collection requirements. Comments, if
received, will be responded to within the subsequent final rule.
The following changes will be submitted to OMB for review under
control number 0938-1171 (CMS-10432). We are not proposing any changes
that would change any of the data collection instruments that are
currently approved under that control number.
In section VI.2 of this proposed rule, we restate our currently
approved burden estimates. In section VI.3 of this proposed rule, we
estimate the changes in burden associated with update more recent wage
rates. Then in section VI.4 of this proposed rule, we estimate the
changes in burden associated with the policies proposed in this
proposed rule.
A. Wage Estimates
In the FY 2024 IPF PPS final rule, we utilized the median hourly
wage rate for Medical Records Specialists, in accordance with the
Bureau of Labor Statistics (BLS), to calculate our burden estimates for
the IPFQR Program (88 FR 51145). While the most recent data from the
BLS reflects a mean hourly wage of $24.56 per hour for all medical
records specialists, $26.06 is the mean hourly wage for ``general
medical and surgical hospitals,'' which is an industry within medical
records specialists.\47\ We believe the industry of ``general medical
and surgical hospitals'' is more specific to the IPF setting for use in
our calculations than other industries that fall under medical records
specialists, such as ``office of physicians'' or ``nursing care
facilities (skilled nursing facilities).'' We calculated the cost of
indirect costs, including fringe benefits, at 100 percent of the median
hourly wage, consistent with previous years. This is necessarily a
rough adjustment, both because fringe benefits and other indirect costs
vary significantly by employer and methods of estimating these costs
vary widely in the literature. Nonetheless, we believe that doubling
the hourly wage rate ($26.06 x 2 = $52.12) to estimate total cost is a
reasonably accurate estimation method. Accordingly, unless otherwise
specified, we will calculate cost burden to IPFs using a wage plus
benefits estimate of $52.12 per hour throughout the discussion in this
section of this rule for the IPFQR Program.
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\47\ Medical Records Specialists (bls.gov).
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Some of the activities previously finalized for the IPFQR Program
require beneficiaries to undertake tasks such as responding to survey
questions on their own time. In the FY 2024 IPF PPS final rule, we
estimated the hourly wage rate for these activities to be $20.71/hr (88
FR 51145). We are updating that estimate to a post-tax wage of $24.04/
hr.
[[Page 23214]]
The Valuing Time in U.S. Department of Health and Human Services
Regulatory Impact Analyses: Conceptual Framework and Best Practices
identifies the approach for valuing time when individuals undertake
activities on their own time.\48\ To derive the costs for
beneficiaries, we used a measurement of the usual weekly earnings of
wage and salary workers of $1,118, divided by 40 hours to calculate an
hourly pre-tax wage rate of $27.95/hr.\49\ This rate is adjusted
downwards by an estimate of the effective tax rate for median income
households of about 14 percent calculated by comparing pre- and post-
tax income,\50\ resulting in the post-tax hourly wage rate of $24.04/
hr. Unlike our State and private sector wage adjustments, we are not
adjusting beneficiary wages for fringe benefits and other indirect
costs since the individuals' activities, if any, would occur outside
the scope of their employment.
---------------------------------------------------------------------------
\48\ https://aspe.hhs.gov/reports/valuing-time-us-department-health-human-services-regulatory-impact-analyses-conceptual-framework.
\49\ https://www.bls.gov/news.release/pdf/wkyeng.pdf. Accessed
January 1, 2024.
\50\ https://www.census.gov/library/stories/2023/09/median-household-income.html. Accessed January 2, 2024.
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B. Previously Finalized IPFQR Estimates
We are finalizing provisions that impact policies beginning with
the FY 2027 payment determination. For the purposes of calculating
burden, we attribute the costs to the year in which the costs begin.
Under our previously finalized policies, data submission for the
measures that affect the FY 2027 payment determination occurs during CY
2026 and generally reflects care provided during CY 2025. If we
finalize our proposal to switch to quarterly reporting in section XX.X
of this proposed rule, data submission for the FY 2027 payment
determination would begin during CY 2025. Our currently approved burden
for CY 2025 is set forth in Table 25.
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C. Updates Due to More Recent Information
In section VI.A of this proposed rule, we described our updated
wage rates which increase from $44.86/hr to $52.12/hr (an increase of
$7.26/hr) for activities performed by Medical Records Specialists and
from $20.71/hr to $24.04/hr (an increase of $3.33/hr) for activities
performed by individuals. The effects of these updates are set forth in
Table 26.
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D. Updates Due to Proposals in This Proposed Rule
In section V.B.2 of this proposed rule, we are proposing to adopt
the 30-Day Risk-Standardized All-Cause ED Visit Following an IPF
Discharge measure beginning with the CY 2025 performance period/FY 2027
payment determination. As described in section V.B.2.c. of this
preamble, we will calculate the 30-Day Risk-Standardized All-Cause ED
Visit Following an Inpatient Psychiatric Facility Discharge measure
using Medicare claims that IPFs and other providers submit for payment.
Since this is a claims-based measure there is no additional burden
outside of submitting a claim. The claim submission is approved by OMB
under control number 0938-0050 (CMS-2552-10). This rule does not
warrant any changes under that control number.
In Section V.D. of this proposed rule, we are proposing to require
IPFs to submit data on chart-abstracted measures quarterly. In CY 2025,
this would equate to one additional data submission period (that is,
the reporting period which would close on November 15, 2025 as set
forth in Table 27). In CY 2026, there would be an additional two data
submission periods (for a total of four annually). We estimate that the
[[Page 23217]]
increase in burden associated with the increase in data submission
periods is approximately equal to the burden of reporting one
attestation measure because both of these activities require logging
into and interacting with user interfaces within the CMS data reporting
system (that is, the Hospital Quality System--HQS). The effects of this
increase on the IPFQR Program for CY 2025 are set forth in Table 27.
The effects of this increase on the IPFQR Program for CY 2026 are set
forth in Table 28.
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E. Consideration of Burden Related to Clarification of Eligibility
Criteria for the Option To Elect To File an All-Inclusive Cost Report
As discussed in section III.E.4 of this proposed rule, we are
clarifying the eligibility criteria to be approved to file all-
inclusive cost reports. Only government-owned and tribally owned
facilities are able to satisfy these criteria, and thus only these
facilities will be permitted to file an all-inclusive cost report for
cost reporting periods beginning on or after October 1, 2024.
We do not estimate any change in the burden associated with the
hospital cost report (CMS-2552-10) OMB control number 0938-0050. We
anticipate that IPFs which are currently filing all-inclusive cost
reports, but are not government-owned or tribally owned, would not
incur additional burden related to the submission of the cost report.
The approved burden estimate associated with the submission of the
hospital cost report includes the same amount of burden for the
submission of an all-inclusive cost report as for the submission of a
cost report with a charge structure.
We recognize that these IPFs would be required to track ancillary
costs and charges using a charge structure; however, we expect that any
burden associated with this tracking would be part of the normal course
of a hospital's activities.
F. Submission of PRA-Related Comments
We have submitted a copy of this proposed rule's information
collection requirements to OMB for their review. The requirements are
not effective until they have been approved by OMB.
To obtain copies of the supporting statement and any related forms
for the proposed collections discussed above, please visit the CMS
website at https://www.cms.gov/regulationsand-guidance/legislation/paperworkreductionactof1995/pra-listing, or call the Reports Clearance
Office at 410-786-1326.
We invite public comments on these potential information collection
requirements. If you wish to comment, please submit your comments
electronically as specified in the DATES and ADDRESSES sections of this
proposed rule and identify the rule (CMS-1806-P), the ICR's CFR
citation, and OMB control number.
VII. 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.
VIII. Regulatory Impact Analysis
A. Statement of Need
This rule proposes updates to the prospective payment rates for
Medicare inpatient hospital services provided by IPFs for discharges
occurring during FY 2025 (October 1, 2024 through September 30, 2025).
We are proposing to apply the 2021-based IPF market basket increase of
3.1 percent, reduced by the productivity adjustment of 0.4 percentage
point as required by 1886(s)(2)(A)(i) of the Act for a proposed total
FY 2025 payment rate update of 2.7 percent. In this proposed rule, we
[[Page 23218]]
are proposing to update the outlier fixed dollar loss threshold amount,
update the IPF labor-related share, adopt new CBSA delineations based
on OMB Bulletin 23-01, and update the IPF wage index to reflect the FY
2025 hospital inpatient wage index. Section 1886(s)(4) of the Act
requires IPFs to report data in accordance with the requirements of the
IPFQR Program for purposes of measuring and making publicly available
information on health care quality; and links the quality data
submission to the annual applicable percentage increase.
B. Overall Impact
We have examined the impacts of this rule as required by Executive
Order 12866 on Regulatory Planning and Review (September 30, 1993),
Executive Order 13563 on Improving Regulation and Regulatory Review
(January 18, 2011), Executive Order 14094 on Modernizing Regulatory
Review (April 6, 2023), the Regulatory Flexibility Act (RFA) (September
19, 1980, Pub. L. 96-354), section 1102(b) of the Social Security Act,
section 202 of the Unfunded Mandates Reform Act of 1995 (March 22,
1995; Pub. L. 104-4), and Executive Order 13132 on Federalism (August
4, 1999).
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, as amended by Executive Order 14094,
defines a ``significant regulatory action'' as an action that is likely
to result in a rule that may: (1) have an annual effect on the economy
of $200 million or more (adjusted every 3 years by the Administrator of
OIRA for changes in gross domestic product); or adversely affect in a
material way the economy, a sector of the economy, productivity,
competition, jobs, the environment, public health or safety, or State,
local, territorial, or tribal governments or communities; (2) create a
serious inconsistency or otherwise interfere with an action taken or
planned by another agency; (3) materially alter the budgetary impacts
of entitlements, grants, user fees, or loan programs or the rights and
obligations of recipients thereof; or (4) raise legal or policy issues
for which centralized review would meaningfully further the President's
priorities or the principles set forth in Executive Order 12866. In
accordance with the provisions of Executive Order 12866, this
regulation was reviewed by the Office of Management and Budget.
A regulatory impact analysis (RIA) must be prepared for regulatory
actions that are significant under section 3(f)(1) of Executive Order
12866. We estimate that the total impact of these changes for FY 2025
payments compared to FY 2024 payments will be a net increase of
approximately $70 million. This reflects a $75 million increase from
the update to the payment rates (+$85 million from the 4th quarter 2023
IGI forecast of the 2021-based IPF market basket of 3.1 percent, and -
$10 million for the productivity adjustment of 0.4 percentage point),
as well as a $5 million decrease as a result of the update to the
outlier threshold amount. Outlier payments are estimated to change from
2.1 percent in FY 2024 to 2.0 percent of total estimated IPF payments
in FY 2025.
Based on our estimates, OMB's Office of Information and Regulatory
Affairs has determined that this rulemaking is ``significant,'' though
not significant under section 3(f)(1) of Executive Order 12866.
Nevertheless, because of the potentially substantial impact to IPF
providers, we have prepared a Regulatory Impact Analysis that to the
best of our ability presents the costs and benefits of the rulemaking.
OMB has reviewed these proposed regulations, and the Departments have
provided the following assessment of their impact.
Nevertheless, because of the potentially substantial impact to IPF
providers, we have prepared a Regulatory Impact Analysis that to the
best of our ability presents the costs and benefits of the rulemaking.
Based on our estimates, OMB's Office of Information and Regulatory
Affairs has determined that this rulemaking is ``significant.''
Therefore, OMB has reviewed these proposed regulations, and the
Departments have provided the following assessment of their impact.
C. Detailed Economic Analysis
In this section, we discuss the historical background of the IPF
PPS and the impact of this proposed rule on the Federal Medicare budget
and on IPFs.
1. Budgetary Impact
As discussed in the RY 2005 and RY 2007 IPF PPS final rules, we
applied a budget neutrality factor to the Federal per diem base rate
and ECT payment per treatment to ensure that total estimated payments
under the IPF PPS in the implementation period would equal the amount
that would have been paid if the IPF PPS had not been implemented. This
budget neutrality factor included the following components: outlier
adjustment, stop-loss adjustment, and the behavioral offset. As
discussed in the RY 2009 IPF PPS notice (73 FR 25711), the stop-loss
adjustment is no longer applicable under the IPF PPS.
As discussed in section III.D.1.d of this proposed rule, we are
proposing to update the wage index and labor-related share, as well as
update the CBSA delineations based on OMB Bulletin 23-01, in a budget
neutral manner by applying a wage index budget neutrality factor to the
Federal per diem base rate and ECT payment per treatment. In addition,
as discussed in section III.F of this proposed rule, we are proposing
to apply a refinement standardization factor to the Federal per diem
base rate and ECT payment per treatment to account for the proposed
revisions to the ECT per treatment amount, ED adjustment, and patient-
level adjustment factors (as previously discussed in sections III.B,
III.C, and III.D of this proposed rule, and summarized in Addendum A),
which must be made budget-neutrally. Therefore, the budgetary impact to
the Medicare program of this proposed rule would be due to the proposed
market basket update for FY 2025 of 3.1 percent (see section III.A.2 of
this proposed rule) reduced by the productivity adjustment of 0.4
percentage point required by section 1886(s)(2)(A)(i) of the Act and
the update to the outlier fixed dollar loss threshold amount.
We estimate that the FY 2025 impact would be a net increase of $70
million in payments to IPF providers. This reflects an estimated $75
million increase from the update to the payment rates and a $5 million
decrease due to the update to the outlier threshold amount to set total
estimated outlier payments at 2.0 percent of total estimated payments
in FY 2025. This estimate does not include the implementation of the
required 2.0 percentage point reduction of the productivity-adjusted
market basket update factor for any IPF that fails to meet the IPF
quality reporting requirements (as discussed in section III.B.2. of
this proposed rule).
2. Impact on Providers
To show the impact on providers of the changes to the IPF PPS
discussed in this proposed rule, we compare estimated payments under
the proposed IPF PPS rates and factors for FY 2025 versus those under
FY 2024. We determined the percent change in the estimated FY 2025 IPF
PPS payments compared to the estimated FY 2024 IPF PPS payments for
each category of IPFs.
[[Page 23219]]
In addition, for each category of IPFs, we have included the estimated
percent change in payments resulting from the proposed update to the
outlier fixed dollar loss threshold amount; the proposed revisions to
the patient-level adjustment factors, ED adjustment, and ECT per
treatment amount; the updated wage index data including the proposed
labor-related share and the proposed changes to the CBSA delineations;
and the proposed market basket increase for FY 2025, as reduced by the
proposed productivity adjustment according to section 1886(s)(2)(A)(i)
of the Act.
To illustrate the impacts of the proposed FY 2025 changes in this
proposed rule, our analysis begins with FY 2023 IPF PPS claims (based
on the 2023 MedPAR claims, December 2023 update). We estimate FY 2024
IPF PPS payments using these 2023 claims, the finalized FY 2024 IPF PPS
Federal per diem base rate and ECT per treatment amount, and the
finalized FY 2024 IPF PPS patient and facility level adjustment factors
(as published in the FY 2024 IPF PPS final rule (88 FR 51054)). We then
estimate the FY 2024 outlier payments based on these simulated FY 2024
IPF PPS payments using the same methodology as finalized in the FY 2024
IPF PPS final rule (88 FR 51090 through 51092) where total outlier
payments are maintained at 2 percent of total estimated FY 2024 IPF PPS
payments.
Each of the following changes is added incrementally to this
baseline model in order for us to isolate the effects of each change:
The proposed update to the outlier fixed dollar loss
threshold amount.
The proposed revisions to patient-level adjustment
factors, ED adjustment, and the ECT per treatment amount.
The proposed FY 2025 IPF wage index, the proposed changes
to the CBSA delineations, and the proposed FY 2025 labor-related share
(LRS).
The proposed market basket increase for FY 2025 of 3.1
percent reduced by the proposed productivity adjustment of 0.4
percentage point in accordance with section 1886(s)(2)(A)(i) of the Act
for a payment rate update of 2.7 percent.
Our proposed column comparison in Table 29 illustrates the percent
change in payments from FY 2024 (that is, October 1, 2023, to September
30, 2024) to FY 2025 (that is, October 1, 2024, to September 30, 2025)
including all the proposed payment policy changes.
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3. Impact Results
Table 30 displays the results of our analysis. The table groups
IPFs into the categories listed here based on characteristics provided
in the Provider of Services file, the IPF PSF, and cost report data
from the Healthcare Cost Report Information System:
Facility Type.
Location.
Teaching Status Adjustment.
Census Region.
Size.
The top row of the table shows the overall impact on the 1,430 IPFs
included in the analysis. In column 2, we present the number of
facilities of each type that had information available in the PSF, had
claims in the MedPAR dataset for FY 2023. We note that providers are
assigned urban or rural status in Table 30 based on the current CBSA
delineations for FY 2024.
In column 3, we present the effects of the update to the outlier
fixed dollar loss threshold amount. We estimate that IPF outlier
payments as a percentage of total IPF payments are 2.1 percent in FY
2024. Therefore, we are proposing to adjust the outlier threshold
amount to set total estimated outlier payments equal to 2.0 percent of
total payments in FY 2025. The estimated change in total IPF payments
for FY 2025, therefore, includes an approximate 0.1 percent decrease in
payments because we would expect the outlier portion of total payments
to decrease from approximately 2.1 percent to 2.0 percent.
[[Page 23222]]
The overall impact of the estimated decrease to payments due to
updating the outlier fixed dollar loss threshold (as shown in column 3
of Table 30), across all hospital groups, is a 0.1 percent decrease.
The largest decrease in payments due to this change is estimated to be
0.2 percent for urban government IPF units, IPFs with more than 30
percent interns and residents to beds, and IPF units with 76+ beds.
In column 4, we present the effects of the proposed revisions to
the patient-level adjustment factors, ED adjustment, and ECT per
treatment amount and the application of the refinement standardization
factor that is discussed in section III.F of this proposed rule. We
estimate the largest payment increases would be for rural freestanding
government-owned IPFs. Conversely, we estimate that for-profit IPF
hospitals in rural areas would experience the largest payment decrease.
Payments to IPF units in urban areas would increase by 0.4 percent, and
payments to IPF units in rural areas would increase by 0.3 percent.
In column 5, we present the effects of the proposed budget-neutral
update to the IPF wage index, the proposed LRS, and the proposed
changes to the CBSA delineations for FY 2025. In addition, this column
includes the application of the 5-percent cap on any decrease to a
provider's wage index from its wage index in the prior year as
finalized in the FY 2023 IPF PPS final rule (87 FR 46856 through
46859). The change in this column represents the effect of using the
concurrent hospital wage data as discussed in section III.D.1.a of this
proposed rule. That is, the impact represented in this column reflects
the proposed update from the FY 2024 IPF wage index to the proposed FY
2025 IPF wage index, which includes basing the FY 2025 IPF wage index
on the FY 2025 pre-floor, pre-reclassified IPPS hospital wage index
data, applying a 5-percent cap on any decrease to a provider's wage
index from its wage index in the prior year, and updating the LRS from
78.7 percent in FY 2024 to 78.8 percent in FY 2025. We note that there
is no projected change in aggregate payments to IPFs, as indicated in
the first row of column 5; however, there would be distributional
effects among different categories of IPFs. For example, we estimate
the largest increase in payments to be 2.9 percent for freestanding
rural for-profit IPFs, and the largest decrease in payments to be 1.6
percent for IPFs located in the Pacific region.
Overall, IPFs are estimated to experience a net increase in
payments of 2.6 percent as a result of the updates in this proposed
rule. IPF payments are therefore estimated to increase by 2.4 percent
in urban areas and 4.0 percent in rural areas. The largest payment
increase is estimated at 5.0 percent for IPFs located in the East South
Central region.
4. Effect on Beneficiaries
Under the FY 2025 IPF PPS, IPFs will continue to receive payment
based on the average resources consumed by patients for each day. Our
longstanding payment methodology reflects the differences in patient
resource use and costs among IPFs, as required under section 124 of the
BBRA. We expect that updating IPF PPS rates in this rule will improve
or maintain beneficiary access to high quality care by ensuring that
payment rates reflect the best available data on the resources involved
in inpatient psychiatric care and the costs of these resources. We
continue to expect that paying prospectively for IPF services under the
FY 2025 IPF PPS will enhance the efficiency of the Medicare program.
As discussed in sections V.B.2 of this proposed rule, we expect
that the proposed additional IPFQR Program measure will support
improving discharge planning and care coordination to decrease the
likelihood that a patient will need to seek emergency care within 30
days of discharge from an IPF.
5. Effects of the Updates to the IPFQR Program
In section V.B.2. of this rule, we are proposing the 30-Day Risk-
Standardized All-Cause ED Visit Following an Inpatient Psychiatric
Facility Discharge measure beginning with data from the CY 2025
performance period for the FY 2027 payment determination. We do not
believe this update would impact providers' workflows or information
systems to collect or report the data because this measure is
calculated by CMS using information that IPFs already submit as part of
the claims process. There may be some effects of this measure on IPF
workflows and clinical processes to improve care coordination and
discharge planning to improve performance on the measure.
We are also proposing to adopt a quarterly data submission
requirement for measures for which we require patient-level data. We
believe there may be some non-recurrent costs associated with training
staff and updating processes to submit these data more frequently. We
believe that the recurring costs of these updates will be an increase
of 800 hours across all IPFs, equating to change of $41,696.
In accordance with section 1886(s)(4)(A) of the Act, we will apply
a 2-percentage point reduction to the FY 2025 market basket update for
IPFs that have failed to comply with the IPFQR Program requirements for
FY 2025, including reporting on the mandatory measures. For the FY 2024
payment determination, of the 1,568 IPFs eligible for the IPFQR
Program, 194 IPFs did not receive the full market basket update because
of the IPFQR Program; 42 of these IPFs chose not to participate and 152
did not meet the requirements of the program.
We intend to closely monitor the effects of the IPFQR Program on
IPFs and help facilitate successful reporting outcomes through ongoing
education, national trainings, and a technical help desk.
6. Regulatory Review Costs
If regulations impose administrative costs on private entities,
such as the time needed to read and interpret this 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 be directly impacted and will review this proposed rule, we
assume that the total number of unique commenters on the most recent
IPF proposed rule will be the number of reviewers of this proposed
rule. For this FY 2025 IPF PPS proposed rule, the most recent IPF
proposed rule was the FY 2024 IPF PPS proposed rule, and we received
2,506 unique comments on this proposed rule. We acknowledge that this
assumption may understate or overstate the costs of reviewing this
proposed rule. It is possible that not all commenters reviewed the FY
2024 IPF proposed rule in detail, and it is also possible that some
reviewers chose not to comment on that proposed rule. For these
reasons, we thought that the number of commenters would be a fair
estimate of the number of reviewers who are directly impacted by this
proposed rule. We are soliciting comments on this assumption.
We also recognize that different types of entities are in many
cases affected by mutually exclusive sections of this proposed rule;
therefore, for the purposes of our estimate, we assume that each
reviewer reads approximately 50 percent of this proposed rule.
Using the May, 2022 mean (average) wage information from the BLS
for medical and health service managers (Code 11-9111), we estimate
that the cost of reviewing this proposed rule is $123.06 per hour,
including other indirect costs https://www.bls.gov/oes/current/oes119111.htm. Assuming an
[[Page 23223]]
average reading speed of 250 words per minute, we estimate that it
would take approximately 112 minutes (1.87 hours) for the staff to
review half of this proposed rule, which contains a total of
approximately 56,000 words. For each IPF that reviews the proposed
rule, the estimated cost is (1.87 x $123.06) or $230.12. Therefore, we
estimate that the total cost of reviewing this proposed rule is
$576,680.72 ($230.12 x 2,506 reviewers).
D. Alternatives Considered
The statute gives the Secretary discretion in establishing an
update methodology to the IPF PPS. We continue to believe it is
appropriate to routinely update the IPF PPS so that it reflects the
best available data about differences in patient resource use and costs
among IPFs, as required by the statute. Therefore, we are proposing to:
update the IPF PPS using the methodology published in the RY 2005 IPF
PPS final rule (our ``standard methodology'') pre-floor, pre-
reclassified IPPS hospital wage index as its basis, along with the
proposed changes to the CBSA delineations. Additionally, we apply a 5-
percent cap on any decrease to a provider's wage index from its wage
index in the prior year. Lastly, we are proposing to revise the
patient-level adjustment factors, ED adjustment, and to increase the
ECT per treatment amount for FY 2025 (reflecting the pre-scaled and
pre-adjusted CY 2024 OPPS geometric mean cost).
E. Accounting Statement
As required by OMB Circular A-4 (available at www.whitehouse.gov/sites/whitehouse.gov/files/omb/circulars/A4/a-4.pdf ), in Table 30, we
have prepared an accounting statement showing the classification of the
expenditures associated with the updates to the IPF wage index and
payment rates in this proposed rule. Table 30 provides our best
estimate of the increase in Medicare payments under the IPF PPS as a
result of the changes presented in this proposed rule and based on the
data for 1,430 IPFs with data available in the PSF, with claims in our
FY 2023 MedPAR claims dataset. Lastly, Table 30 also includes our best
estimate of the costs of reviewing and understanding this proposed
rule.
[GRAPHIC] [TIFF OMITTED] TP03AP24.043
F. Regulatory Flexibility Act
The RFA requires agencies to analyze options for regulatory relief
of small entities if a rule has a significant impact on a substantial
number of small entities. For purposes of the RFA, small entities
include small businesses, nonprofit organizations, and small
governmental jurisdictions. The great majority of hospitals and most
other health care providers and suppliers are small entities, either by
being nonprofit organizations or by meeting the Small Business
Administration (SBA) definition of a small business (having revenues of
less than $47 million in any 1 year).
According to the SBA's website at https://www.sba.gov/content/small-business-size-standards, IPFs falls into the North American Industrial
Classification System (NAICS) code 622210, Psychiatric and Substance
Abuse hospitals. The SBA defines small Psychiatric and Substance Abuse
hospitals as businesses having less than $47 million.
Because we lack data on individual hospital receipts, we cannot
determine the number of small proprietary IPFs or the proportion of
IPFs' revenue derived from Medicare payments. Therefore, we assume that
all IPFs are considered small entities.
The Department of Health and Human Services generally uses a
revenue impact of 3 to 5 percent as a significance threshold under the
RFA. As shown in Table 30, we estimate that the overall revenue impact
of this proposed rule on all IPFs is to increase estimated Medicare
payments by approximately 2.6 percent. As a result, since the estimated
impact of this proposed rule is a net increase in revenue across almost
all categories of IPFs, the Secretary has determined that this proposed
rule will have a positive revenue impact on a substantial number of
small entities.
In addition, section 1102(b) of the Act requires us to prepare a
regulatory impact analysis if a rule may have a significant impact on
the operations of a substantial number of small rural hospitals. This
analysis must conform to the provisions of section 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 discussed in section
VIII.C.2 of this proposed rule, the rates and policies set forth in
this proposed rule will not have an adverse impact on the rural
hospitals based on the data of the 199 rural excluded psychiatric units
and 60 rural psychiatric hospitals in our database of 1,430 IPFs for
which data were available. Therefore, the Secretary has determined that
this proposed rule will not have a significant impact on the operations
of a substantial number of small rural hospitals.
[[Page 23224]]
G. Unfunded Mandate Reform Act (UMRA)
Section 202 of the Unfunded Mandates Reform Act of 1995 (UMRA) also
requires that agencies assess anticipated costs and benefits before
issuing any rule whose mandates require spending in any 1 year of $100
million in 1995 dollars, updated annually for inflation. In 2023, that
threshold is approximately $183 million. This proposed rule does not
mandate any requirements for state, local, or tribal governments, or
for the private sector. This proposed rule would not impose a mandate
that will result in the expenditure by state, local, and tribal
governments, in the aggregate, or by the private sector, of more than
$183 million in any 1 year.
H. Federalism
Executive Order 13132 establishes certain requirements that an
agency must meet when it promulgates a proposed rule that imposes
substantial direct requirement costs on state and local governments,
preempts state law, or otherwise has Federalism implications. This
proposed rule does not impose substantial direct costs on state or
local governments or preempt state law.
In accordance with the provisions of Executive Order 12866, this
proposed regulation was reviewed by the Office of Management and
Budget.
Chiquita Brooks-LaSure, Administrator of the Centers for Medicare &
Medicaid Services, approved this document on March 22, 2024.
Xavier Becerra,
Secretary, Department of Health and Human Services.
[FR Doc. 2024-06764 Filed 3-28-24; 4:15 pm]
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