[Federal Register: August 15, 2005 (Volume 70, Number 156)]
[Rules and Regulations]
[Page 47879-48006]
From the Federal Register Online via GPO Access [wais.access.gpo.gov]
[DOCID:fr15au05-9]
[[Page 47879]]
-----------------------------------------------------------------------
Part II
Department of Health and Human Services
-----------------------------------------------------------------------
Centers for Medicare & Medicaid Services
-----------------------------------------------------------------------
42 CFR Part 412
Medicare Program; Inpatient Rehabilitation Facility Prospective Payment
System for FY 2006; Final Rule
[[Page 47880]]
-----------------------------------------------------------------------
DEPARTMENT OF HEALTH AND HUMAN SERVICES
Centers for Medicare & Medicaid Services
42 CFR Part 412
[CMS-1290-F]
RIN 0938-AN43
Medicare Program; Inpatient Rehabilitation Facility Prospective
Payment System for FY 2006
AGENCY: Centers for Medicare & Medicaid Services (CMS), HHS.
ACTION: Final rule.
-----------------------------------------------------------------------
SUMMARY: This final rule will update the prospective payment rates for
inpatient rehabilitation facilities for Federal fiscal year 2006 as
required under section 1886(j)(3)(C) of the Social Security Act (the
Act). Section 1886(j)(5) of the Act requires the Secretary to publish
the classification and weighting factors for the inpatient
rehabilitation facilities case-mix groups and a description of the
methodology and data used in computing the prospective payment rates
for that fiscal year.
In addition, we are implementing new policies and are changing
existing policies regarding the prospective payment system within the
authority granted under section 1886(j) of the Act.
DATES: These regulations are effective October 1, 2005. The updated IRF
prospective payment rates are applicable for discharges on or after
October 1, 2005 and on or before September 30, 2006 (FY 2006).
FOR FURTHER INFORMATION CONTACT: Pete Diaz, (410) 786-1235. Susanne
Seagrave, (410) 786-0044. Mollie Knight, (410) 786-7948 for information
regarding the market basket and labor-related share. August Nemec,
(410) 786-0612 for information regarding the tier comorbidities. Zinnia
Ng, (410) 786-4587 for information regarding the wage index and Core-
Based Statistical Areas (CBSAs).
SUPPLEMENTARY INFORMATION:
Table of Contents
I. Background
A. General Overview of the Current Inpatient Rehabilitation
Facility Prospective Payment System (IRF PPS)
B. Requirements for Updating the Prospective Payment Rates for
IRFs
C. Operational Overview of the Current IRF PPS
D. Summary of the FY 2006 Proposed Update to the IRF PPS
II. Provisions of the Proposed Regulations
III. Analysis of and Responses to Public Comments
IV. Research to Support Refinements of the Current IRF PPS
V. Refinements to the Patient Classification System
A. Changes to the IRF Classification System
1. Development of the IRF Classification System
2. Description and Methodology Used To Develop the IRF
Classification System in the August 7, 2001 Final Rule
a. Rehabilitation Impairment Categories
b. Functional Status Measures and Age
c. Comorbidities
d. Development of CMG Relative Weights
e. Overview of Development of the CMG Relative Weights
B. Changes to the Existing List of Tier Comorbidities
1. Changes to Remove Codes That Are Not Positively Related to
Treatment Costs
2. Changes to Move Dialysis to Tier One
3. Changes to Move Comorbidity Codes Based on Their Marginal
Cost
C. Changes to the CMGs
1. Changes for Updating the CMGs
2. Use of a Weighted Motor Score Index and Correction to the
Treatment of Unobserved Transfer to Toilet Values
3. Changes for Updating the Relative Weights
VI. FY 2006 Federal Prospective Payment Rates
A. Reduction of the Standard Payment Amount to Account for
Coding Changes
B. Adjustments to Determine the FY 2006 Standard Payment
Conversion Factor
1. Market Basket Used for IRF Market Basket Index
a. Overview of the RPL Market Basket
b. Methodology for Operating Portion of the RPL Market Basket
c. Methodology for Capital Proportion of the RPL Market Basket
d. Labor-Related Share
2. Area Wage Adjustment
a. Revisions of the IRF PPS Geographic Classification
b. Current IRF PPS Labor Market Areas Based on MSAs
c. Core-Based Statistical Areas (CBSAs)
d. Revisions of the IRF PPS Labor Market Areas
i. New England MSAs
ii. Metropolitan Divisions
iii. Micropolitan Areas
e. Implementation of the CBSA-Based Labor Market Areas
f. Wage Index Data
3. Teaching Status Adjustment
4. Adjustment for Rural Location
5. Adjustment for Disproportionate Share of Low-Income Patients
6. Update to the Outlier Threshold Amount
7. Budget Neutrality Factor Methodology for Fiscal Year 2006
8. Description of the Methodology Used to Implement the Changes
in a Budget Neutral Manner
9. Description of the IRF Standard Payment Conversion Factor for
Fiscal Year 2006
10. Example of the Methodology for Adjusting the Federal
Prospective Payment Rates
VII. Quality of Care in IRFs
VIII. Miscellaneous Comments Within the Scope of the Proposed Rule
IX. Miscellaneous Comments Outside the Scope of the Proposed Rule
X. Provisions of the Final Regulations
XI. Collection of Information Requirements
XII. Regulatory Impact Analysis
Acronyms
Because of the many terms to which we refer by acronym in this
final rule, we are listing the acronyms used and their corresponding
terms in alphabetical order below.
ADC Average Daily Census
AHA American Hospital Association
AMI Acute Myocardial Infarction
BBA Balanced Budget Act of 1997 (BBA), Pub. L. 105-33
BBRA Medicare, Medicaid, and SCHIP [State Children's Health
Insurance Program] Balanced Budget Refinement Act of 1999, Pub. L.
106-113
BIPA Medicare, Medicaid, and SCHIP [State Children's Health
Insurance Program] Benefits Improvement and Protection Act of 2000,
Pub. L. 106-554
BLS Bureau of Labor Statistics
CART Classification and Regression Trees
CBSA Core-Based Statistical Areas
CCR Cost-to-charge ratio
CMGs Case-Mix Groups
CMI Case Mix Index
CMSA Consolidated Metropolitan Statistical Area
CPI Consumer Price Index
DSH Disproportionate Share Hospital
ECI Employment Cost Index
FI Fiscal Intermediary
FIM Functional Independence Measure (FIMTM is a
registered trademark of UDSMR)
FIM-FRGs Functional Independence Measures-Function Related Groups
FRG Function Related Group
FTE Full-time equivalent
FY Federal Fiscal Year
GME Graduate Medical Education
HCRIS Healthcare Cost Report Information System
HIPAA Health Insurance Portability and Accountability Act
HHA Home Health Agency
IME Indirect Medical Education
IFMC Iowa Foundation for Medical Care
IPF Inpatient Psychiatric Facility
IPPS Inpatient Prospective Payment System
IRF Inpatient Rehabilitation Facility
IRF-PAI Inpatient Rehabilitation Facility-Patient Assessment
Instrument
IRF-PPS Inpatient Rehabilitation Facility-Prospective Payment System
IRVEN Inpatient Rehabilitation Validation and Entry
LIP Low-income percentage
MEDPAR Medicare Provider Analysis and Review
MSA Metropolitan Statistical Area
NECMA New England County Metropolitan Area
NOS Not Otherwise Specified
NTIS National Technical Information Service
OMB Office of Management and Budget
OSCAR Online Survey, Certification, and Reporting
PAI Patient Assessment Instrument
PLI Professional Liability Insurance
[[Page 47881]]
PMSA Primary Metropolitan Statistical Area
PPI Producer Price Index
PPS Prospective Payment System
RIC Rehabilitation Impairment Category
RPL Rehabilitation Hospital, Psychiatric Hospital, and Long-Term
Care Hospital Market Basket
TEFRA Tax Equity and Fiscal Responsibility Act
TEP Technical Expert Panel
I. Background
We received approximately 55 timely items of correspondence on the
Inpatient Rehabilitation Facility Prospective Payment System for FY
2006 proposed rule (70 FR 30188). Summaries of the public comments and
our responses to those comments are set forth below under the
appropriate section heading of this final rule.
A. General Overview of the Current Inpatient Rehabilitation Facility
Prospective Payment System (IRF PPS)
Section 4421 of the Balanced Budget Act of 1997 (BBA) (Pub. L. 105-
33), as amended by section 125 of the Medicare, Medicaid, and SCHIP
[State Children's Health Insurance Program] Balanced Budget Refinement
Act of 1999 (BBRA) (Pub. L. 106-113), and by section 305 of the
Medicare, Medicaid, and SCHIP Benefits Improvement and Protection Act
of 2000 (BIPA) (Pub. L. 106-554), provides for the implementation of a
per discharge prospective payment system (PPS), through section 1886(j)
of the Social Security Act (the Act), for inpatient rehabilitation
hospitals and inpatient rehabilitation units of a hospital (hereinafter
referred to as IRFs).
Payments under the IRF PPS encompass inpatient operating and
capital costs of furnishing covered rehabilitation services (that is,
routine, ancillary, and capital costs) but not costs of approved
educational activities, bad debts, and other services or items outside
the scope of the IRF PPS. Although a complete discussion of the IRF PPS
provisions appears in the August 7, 2001 final rule, we are providing
below a general description of the IRF PPS.
The IRF PPS, as described in the August 7, 2001 final rule, uses
Federal prospective payment rates across 100 distinct case-mix groups
(CMGs). Ninety-five CMGs were constructed using rehabilitation
impairment categories, functional status (both motor and cognitive),
and age (in some cases, cognitive status and age may not be a factor in
defining a CMG). Five special CMGs were constructed to account for very
short stays and for patients who expire in the IRF.
For each of the CMGs, we developed relative weighting factors to
account for a patient's clinical characteristics and expected resource
needs. Thus, the weighting factors account for the relative difference
in resource use across all CMGs. Within each CMG, the weighting factors
were ``tiered'' based on the estimated effects that certain
comorbidities have on resource use.
The Federal PPS rates were established using a standardized payment
amount (previously referred to as the budget-neutral conversion
factor). The standardized payment amount was previously called the
budget neutral conversion factor because it reflected a budget
neutrality adjustment for FYs 2001 and 2002, as described in Sec.
412.624(d)(2) of our regulations. However, the statute requires a
budget neutrality adjustment only for FYs 2001 and 2002. Accordingly,
for subsequent years we believe it is more consistent with the statute
to refer to the standardized payment as the standardized payment
conversion factor, rather than refer to it as a budget neutral
conversion factor (see 68 FR 45674, 45684 and 45685). Therefore, we
will refer to the standardized payment amount in this final rule as the
standard payment conversion factor.
For each of the tiers within a CMG, the relative weighting factors
were applied to the standard payment conversion factor to compute the
unadjusted Federal prospective payment rates. Under the current system,
adjustments that accounted for geographic variations in wages (wage
index), the percentage of low-income patients, and location in a rural
area were applied to the IRF's unadjusted Federal prospective payment
rates. In addition, adjustments were made to account for the early
transfer of a patient, interrupted stays, and high cost outliers.
Lastly, the IRF's final prospective payment amount was determined
under the transition methodology prescribed in section 1886(j) of the
Act. Specifically, for cost reporting periods that began on or after
January 1, 2002 and before October 1, 2002, section 1886(j)(1) of the
Act and as specified in Sec. 412.626 provide that IRFs transitioning
into the PPS would receive a ``blended payment.'' For cost reporting
periods that began on or after January 1, 2002 and before October 1,
2002, these blended payments consisted of 66\2/3\ percent of the
Federal IRF PPS rate and 33\1/3\ percent of the payment that the IRF
would have been paid had the IRF PPS not been implemented. However,
during the transition period, an IRF with a cost reporting period
beginning on or after January 1, 2002 and before October 1, 2002 could
have elected to bypass this blended payment and be paid 100 percent of
the Federal IRF PPS rate. For cost reporting periods beginning on or
after October 1, 2002 (FY 2003), the transition methodology expired,
and payments for all IRFs consist of 100 percent of the Federal IRF PPS
rate.
We established a CMS Web site that contains useful information
regarding the IRF PPS. The Web site URL is http://www.cms.hhs.gov/providers/irfpps/default.asp
and may be accessed to download or view
publications, software, and other information pertinent to the IRF PPS.
B. Requirements for Updating the Prospective Payment Rates for IRFs
On August 7, 2001, we published a final rule entitled ``Medicare
Program; Prospective Payment System for Inpatient Rehabilitation
Facilities'' in the Federal Register (66 FR at 41316), that established
a PPS for IRFs as authorized under section 1886(j) of the Act and
codified at subpart P of part 412 of the Medicare regulations. In the
August 7, 2001 final rule, we set forth the per discharge Federal
prospective payment rates for fiscal year (FY) 2002 that provided
payment for inpatient operating and capital costs of furnishing covered
rehabilitation services (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 IRF PPS. The
provisions of the August 7, 2001 final rule were effective for cost
reporting periods beginning on or after January 1, 2002. On July 1,
2002, we published a correcting amendment to the August 7, 2001 final
rule in the Federal Register (67 FR at 44073). Any references to the
August 7, 2001 final rule in this final rule include the provisions
effective in the correcting amendment.
Section 1886(j)(5) of the Act and Sec. 412.628 of the regulations
require the Secretary to publish the classifications and weighting
factors for the IRF CMGs and a description of the methodology and data
used in computing the prospective payment rates for the upcoming FY. On
August 1, 2002, we published a notice in the Federal Register (67 FR at
49928) to update the IRF Federal prospective payment rates from FY 2002
to FY 2003 using the methodology as described in Sec. 412.624. As
stated in the August 1, 2002 notice, we used the same classifications
and weighting factors for the IRF CMGs that were set forth in the
August 7, 2001 final rule to update the IRF Federal prospective payment
rates from FY 2002
[[Page 47882]]
to FY 2003. We have continued to update the prospective payment rates
each year in accordance with the methodology set forth in the August 7,
2001 final rule.
We published a proposed rule in the Federal Register (70 FR 30189)
to update the IRF Federal prospective payment rates from FY 2005 to FY
2006, and we proposed revisions to the methodology described in Sec.
412.624.
C. Operational Overview of the Current IRF PPS
As described in the August 7, 2001 final rule, upon the admission
and discharge of a Medicare Part A fee-for-service patient, the IRF is
required to complete the appropriate sections of a patient assessment
instrument, the Inpatient Rehabilitation Facility-Patient Assessment
Instrument (IRF-PAI). All required data must be electronically encoded
into the IRF-PAI software product. Generally, the software product
includes patient grouping programming called the GROUPER software. The
GROUPER software uses specific Patient Assessment Instrument (PAI) data
elements to classify (or group) the patient into a distinct CMG and
account for the existence of any relevant comorbidities.
The GROUPER software produces a 5-digit CMG number. The first digit
is an alpha-character that indicates the comorbidity tier. The last 4
digits represent the distinct CMG number. (Free downloads of the
Inpatient Rehabilitation Validation and Entry (IRVEN) software product,
including the GROUPER software, are available at the CMS Web site at
http://www.cms.hhs.gov/providers/irfpps/default.asp).
Once the patient is discharged, the IRF completes the Medicare
claim (UB-92 or its equivalent) using an alphanumeric CMG code and
sends it to the appropriate Medicare fiscal intermediary (FI). (Claims
submitted to Medicare must comply with both the Administrative
Simplification Compliance Act (ASCA), Pub. L. 107-105, and the Health
Insurance Portability and Accountability Act of 1996 (HIPAA), Pub. L.
104-191. Section 3 of ASCA requires the Medicare Program, subject to
subsection (H), to deny payment under Part A or Part B for any expenses
for items or services ``for which a claim is submitted other than in an
electronic form specified by the Secretary.'' Subsection (h) provides
that the Secretary shall waive such denial in two types of cases and
may also waive such denial ``in such unusual cases as the Secretary
finds appropriate.'' See also, 68 FR 48805 (August 15, 2003). Section 3
of ASCA operates in the context of the Administrative Simplification
provisions of HIPAA, which include, among others, the transactions and
code sets standards requirements codified as 45 CFR part 160 and 162,
subparts A and I through R (generally known as the Transactions Rule).
The Transactions Rule requires covered entities, including covered
providers, to conduct covered electronic transactions according to the
applicable transaction standards. See the program claim memoranda
issued and published by CMS at http://www.cms.hhs.gov/providers/edi/default.asp
(http://www.cms.hhs.gov/provider/edi/default.asp) and
listed in the addenda to the Medicare Intermediary Manual, Part 3,
section 3600. Instructions for the limited number of claims submitted
to Medicare on paper are located in section 3604 of Part 3 of the
Medicare Intermediary Manual.
The Medicare Fiscal Intermediary (FI) processes the claim through
its software system. This software system includes pricing programming
called the PRICER software. The PRICER software uses the CMG code,
along with other specific claim data elements and provider-specific
data, to adjust the IRF's prospective payment for interrupted stays,
transfers, short stays, and deaths and then applies the applicable
adjustments to account for the IRF's wage index, percentage of low-
income patients, rural location, and outlier payments.
D. Summary of the FY 2006 Proposed Update to the IRF PPS
In the FY 2006 proposed rule (70 FR 30188), we proposed a number of
refinements to the IRF PPS case-mix classification system (the CMGs and
the corresponding relative weights) and the case-level and facility-
level adjustments. The refinements that we proposed were based on
analyses by RAND using calendar year 2002 and FY 2003 data.
Several new developments warranted proposing these refinements,
including--(1) The availability of more recent 2002 and 2003 data; (2)
better coding of comorbidities and patient severity; (3) more complete
data; (4) new data sources for imputing missing values; and (5)
improved statistical approaches.
Our proposals included the following key changes:
The FY 2006 IRF PPS proposed rule (70 FR 30188, 30234 through
30241) included a proposal to adopt OMB's Core Based Statistical Area
(CBSA) market area definitions in a budget neutral manner. This
geographic adjustment is made using a 1-year lag of the pre-
reclassification hospital wage index (FY 2001 hospital wage data).
The FY 2006 proposed rule (70 FR 30188, 30222) also included a
proposal to implement a payment adjustment to account for changes in
coding. We proposed to reduce the standard payment amount by 1.9
percent to account for changes in coding following implementation of
the IRF PPS. The analysis conducted by CMS's contractor found that the
real change in the case-mix was between negative 2.4 percent and
positive 1.5 percent, with the rest of the change (between 1.9 percent
and 5.8 percent) attributable to coding changes. CMS proposed to reduce
the standard payment amount by the lowest of these estimates.
In addition, in the FY 2006 proposed rule (70 FR 30188), we
proposed modifications to the case mix groups, tier comorbidities, and
relative weights. The proposed rule included a number of adjustments to
the IRF classification system that are designed to improve the system's
ability to predict IRF costs. The new data indicate that moving or
eliminating some comorbidity codes from the tiers, redefining the case
mix groups, and other minor changes to the system could improve the
ability of the classification system to ensure that Medicare payments
to IRFs continue to be aligned with the costs of care.
In addition, the FY 2006 IRF PPS proposed rule (70 FR 30188, 30241)
contained a proposal to implement a new teaching status adjustment for
IRFs, similar to the one recently adopted for inpatient psychiatric
facilities. We proposed to implement the teaching status adjustment in
a budget neutral manner.
The FY 2006 IRF PPS proposed rule (70 FR 30188, 30222) also
contained a proposal to revise the market basket. We proposed to use a
new market basket reflecting the operating and capital cost structures
for rehabilitation, psychiatric, and long term care hospitals to update
IRF payment rates. The proposed new market basket excludes cancer
hospitals and children's hospitals. For the FY 2006 proposed rule (70
FR 30188), we proposed a market basket increase for FY 2006 of 3.1
percent.
In the FY 2006 proposed rule (70 FR 30188, 30244 through 30246), we
also proposed to update the rural adjustment (from 19.1 percent to 24.1
percent), the low-income patient adjustment (from an exponent of 0.484
to an exponent of 0.636), and the outlier threshold amount (from
$11,211 to $4,911). We proposed to implement the changes to the rural
and low-income percentage updates in a budget neutral manner.
[[Page 47883]]
Lastly, in the FY 2006 proposed rule (70 FR 30188), we estimated
that the proposed changes would increase costs to the Medicare program
for IRF services in FY 2006 by $180 million over FY 2005 levels. The
estimated increased cost to the Medicare program was due to the
estimated IRF market basket of 3.1 percent, the 1.9 percent reduction
to the standard payment amount to account for changes in coding that
affect total estimated aggregate payments, and the update to the
outlier threshold amount. We proposed to make the changes to the IRF
labor-related share and the wage indices, the case mix groups, tier
comorbidities, and relative weights, the new IME adjustment, the
updated rural adjustment, and the updated LIP adjustment in a budget
neutral manner. Thus, these proposed changes would have no overall
effect on estimated costs to the Medicare program.
II. Provisions of the Proposed Regulations
In the FY 2006 proposed update to the IRF PPS (70 FR 30188),
hereinafter referred to as the FY 2006 proposed rule, we proposed to
make revisions to the regulations to implement the proposed PPS for
IRFs for FY 2006 and subsequent fiscal years. Specifically, we proposed
to make conforming changes in 42 CFR part 412. These proposed revisions
and others are discussed in detail below.
A. Section 412.602 Definitions
In Sec. 412.602, we proposed to revise the definitions of ``Rural
area'' and ``Urban area'' to read as follows:
Rural area means: For cost-reporting periods beginning on or after
January 1, 2002, with respect to discharges occurring during the period
covered by such cost reports but before October 1, 2005, an area as
defined in Sec. 412.62(f)(1)(iii). For discharges occurring on or
after October 1, 2005, rural area means an area as defined in Sec.
412.64(b)(1)(ii)(C).
Urban area means: For cost-reporting periods beginning on or after
January 1, 2002, with respect to discharges occurring during the period
covered by such cost reports but before October 1, 2005, an area as
defined in Sec. 412.62(f)(1)(ii). For discharges occurring on or after
October 1, 2005, urban area means an area as defined in Sec.
412.64(b)(1)(ii)(A) and Sec. 412.64(b)(1)(ii)(B).
B. Section 412.622 Basis of Payment
In this section, we proposed to correct the cross references in
paragraphs (b)(1) and (b)(2)(i). In paragraph (b)(1), we proposed to
remove the cross references ``Sec. 413.85 and Sec. 413.86 of this
chapter'' and add in their place ``Sec. 413.75 and Sec. 413.85 of
this chapter.'' In paragraph (b)(2)(i), we proposed to remove the cross
reference ``Sec. 413.80 of this chapter'' and add in its place ``Sec.
413.89 of this chapter.''
C. Section 412.624 Methodology for Calculating the Federal Prospective
Payment Rates
In this section, we proposed to make the following revisions:
In paragraph (d)(1), remove the cross reference to
``paragraph (e)(4)'' and add in its place ``paragraph (e)(5).''
Add a new paragraph (d)(4).
Redesignate paragraphs (e)(4) and (e)(5) as paragraphs
(e)(5) and (e)(6).
Add a new paragraph (e)(4).
Revise newly redesignated paragraph (e)(5).
Revise newly redesignated paragraph (e)(6).
Add a new paragraph (e)(7).
In paragraph (f)(2)(v), remove the cross references to
``paragraphs (e)(1), (e)(2), and (e)(3) of this section'' and add in
their place ``paragraphs (e)(2), (e)(3), (e)(4), and (e)(7) of this
section.''
D. Additional Changes
We also proposed the following changes:
Reduce the standard payment amount by 1.9 percent to
account for coding changes.
Revise the comorbidity tiers and CMGs.
Use a weighted motor score index in assigning patients to
CMGs.
Update the relative weights.
Update payments for rehabilitation facilities using a
market basket reflecting the operating and capital cost structures for
the RPL market basket.
Provide the weights and proxies to use for the FY 2002-
based RPL market basket.
Indicate the methodology for the capital portion of the
RPL market basket.
Adopt the new geographic labor market area definitions as
specified in Sec. 412.64(b)(1)(ii)(A)-(C).
Use the New England MSAs as determined under the proposed
new CBSA-based labor market area definitions.
Implement a budget neutral 3 year hold harmless policy for
FY 2005 rural IRFs redesignated as urban in FY 2006.
Use FY 2001 acute care hospital wage data in computing the
FY 2006 IRF PPS payment rates.
Implement a teaching status adjustment.
Update the formulas used to compute the rural and the LIP
adjustments to IRF payments.
Update the outlier threshold amount to maintain total
estimated outlier payments at 3 percent of total estimated payments.
Revise the methodology for computing the standard payment
conversion factor (for FY 2006 only) to make the CMG and tier changes,
the teaching status adjustment, and the updates to the rural and LIP
adjustments in a budget neutral manner.
III. Analysis of and Responses to Public Comments
As stated above, we received approximately 55 timely items of
correspondence containing multiple comments on the FY 2006 proposed
rule (70 FR 30188) from providers, health industry organizations, the
Medicare Payment Advisory Commission, and others. In general,
commenters expressed some concerns about our proposals in light of
other changes occurring in the IRF PPS at this time and suggested that
we wait to implement the proposals until other recent IRF policy
changes are fully implemented. However, many commenters supported the
proposed changes to the facility-level adjustments. Summaries of the
public comments received on the proposed provisions and our responses
to those comments are provided in the appropriate sections of the
preamble of this final rule.
IV. Research To Support Refinements of the Current IRF PPS
As described in the August 7, 2001 final rule, we contracted with
the RAND Corporation to analyze IRF data to support our efforts in
developing the CMG patient classification system and the IRF PPS. Since
then, we have continued our contract with RAND to support us in
developing potential refinements to the classification system and the
PPS. RAND has also developed a system to monitor the effects of the IRF
PPS on patients' access to IRF care and other post-acute care services.
1. History of RAND's Research on the IRF PPS
In 1995, RAND began extensive research, sponsored by us, on the
development of a per-discharge based PPS using a patient classification
system known as Functional Independence Measures--Function Related
Groups (FIM-FRGs) for IRFs. The results of RAND's earliest research,
using 1994 data, were released in September 1997 and are contained in
two reports available through the National Technical Information
Service (NTIS). The reports are: Classification System
[[Page 47884]]
for Inpatient Rehabilitation Patients--A Review and Proposed Revisions
to the Function Independence Measure--Function Related Groups, NTIS
order number PB98-105992INZ, and Prospective Payment System for
Inpatient Rehabilitation, NTIS order number PB98-106024INZ.
In July 1999, we contracted with RAND to update its earlier
research. The update included an analysis of Functional Independence
Measure (FIM) data, the Function Related Groups (FRGs), and the model
rehabilitation PPS using 1996 and 1997 data. The purpose of updating
the earlier research was to develop the underlying data necessary to
support the Medicare IRF PPS based on CMGs for the November 3, 2000
proposed rule (65 FR at 66313). RAND expanded the scope of its earlier
research to include the examination of several payment elements, such
as comorbidities, facility-level adjustments, and implementation
issues, including evaluation and monitoring. Then, to develop the
provisions of the August 7, 2001 final rule (66 FR 41316, 41323), RAND
did similar analysis on calendar year 1998 and 1999 Medicare Provider
Analysis and Review (MedPAR) files and patient assessment data.
We have continued to contract with RAND to help us identify
potential refinements to the IRF PPS. The refinements we proposed to
make to the IRF PPS, and which we are finalizing in this final rule,
are based on the analyses and recommendations from RAND. In addition,
RAND sought advice from a technical expert panel (TEP), which reviewed
their methodology and findings.
2. Data Files Used for Analysis of the Current IRF PPS
RAND conducted updated analyses of the patient classification
system, case mix and coding changes, and facility-level adjustments for
the IRF PPS using data from calendar year 2002 and FY 2003. This is the
first time CMS or RAND has had data generated by IRFs after the
implementation of the IRF PPS that are available for data analysis.
Public comments and our responses on RAND's research to support the
proposed refinements are summarized below:
Comment: Several commenters expressed concerns about basing the
refinements that we proposed in the FY 2006 proposed rule (70 FR 30188)
on analyses of calendar year 2002 and FY 2003 data, which do not
reflect IRF case mix changes currently taking place in response to our
recent enforcement of the classification criterion, commonly known as
the ``75 percent rule.'' These commenters suggested that we wait for
analysis of future data (CY 2005 or beyond) to become available before
implementing refinements to the IRF PPS.
Response: As discussed in the August 7, 2001 final rule (66 FR
41316), we used RAND's analysis of calendar year 1998 and 1999 Medicare
Provider Analysis and Review (MedPAR) files and patient assessment data
to develop the initial classification system and prospective payment
amounts for the IRF PPS. These data were from a period of time before
the IRF PPS when IRFs' reimbursement was based on costs, subject to
certain limits, rather than on prospective payment amounts.
Furthermore, we used the best available 1998 and 1999 data from a time
period that also preceded enforcement of the 75 percent rule
requirements. Today, we have 2002 and 2003 data that represents all
Medicare-covered IRF cases in a post-PPS environment and, therefore,
portrays a recent and complete picture of IRFs' patient populations. In
addition, the IRF payment system has undergone a major transformation
since the 1998 and 1999 data in the form of a change from a cost-based
payment system to a PPS that became effective with the cost reporting
periods beginning on or after January 1, 2002. Because of this
transformation, we believe the data we have on which to base
refinements to the IRF PPS will help ensure that IRF PPS payments
accurately reflect the costs of care in an IRF.
This is because these data allow RAND to obtain precision in their
analyses, and ensures that the data are not over- or under-representing
particular types of facilities or patients. We believe it is
appropriate and necessary to implement refinements to the IRF PPS at
this time, based on the best available data we have from calendar year
2002 and FY 2003. Since analysis of this data indicates that we have an
opportunity at this time, through the proposed refinements, to improve
the alignment between IRF payments and the cost of care, we believe it
is important to proceed with the refinements discussed in this final
rule.
However, we agree with the commenters that we should continue to
collect the best available data we can to monitor the IRF PPS and
ensure that IRF payments are appropriately aligned with costs of care
and that Medicare patients continue to have appropriate access to IRF
services. We will, whenever necessary, use the best data available in
the future to propose appropriate refinements that will further improve
the alignment between IRF payments and the costs of care. Thus, to the
extent changes in case mix occur due to enforcement of the 75 percent
rule, these changes should appear in later data that we will use to
propose refinements in the future.
Comment: Several commenters noted that 98 IRF providers in RAND's
analysis data affiliated with HealthSouth decided to omit home office
cost data from the 2002 and 2003 cost reports that were filed with us.
The commenters questioned whether this omission might have affected the
results of RAND's analysis and, therefore, our proposed policies.
Response: After publication of the FY 2006 proposed rule (70 FR
30188), we learned that 98 providers in our data file that were
affiliated with HealthSouth omitted home office cost data from the 2002
and 2003 cost reports that were filed with us and that RAND used in the
analysis of the FY 2006 proposed rule (70 FR 30188). These data were a
voluntary omission on the part of these providers, but nevertheless
affect some of the distributional policies (that is, the proposed
teaching status adjustment, the proposed changes to the rural and LIP
adjustments, and the proposed change to the outlier threshold)
contained in the proposed rule. However, because RAND used the
hospital-specific relative value method (that is, the methodology that
effectively controls for inter-hospital variation while estimating the
relative costs of different types of patients within each hospital) for
all of the proposed changes to the classification system described in
section V of this final rule (that is, the proposed changes to the tier
comorbidities, the proposed changes to the CMG definitions, the
proposed weighted motor score methodology, the proposed change to the
coding of the transfer-to-toilet item, and the proposed update of the
relative weights), these proposed changes would not have been affected
by the omission of the home office cost data. In other words, RAND
examined the relative costs of patients within each IRF, so the fact
that the omission of HealthSouth's home office costs caused total costs
to be understated in the cost report data would not have mattered for
the proposed classification system changes described in section V of
this final rule.
In addition, the omission of the home office cost data would have
no effect on the proposed 1.9 percent reduction to the standard payment
amount (discussed in section VI.A of this final rule) because cost
report data were not
[[Page 47885]]
used in the analysis that supports this proposed reduction.
Although the omission of the home office cost data, in theory,
could have had some effect on the estimates of the proposed FY 2002-
based RPL market basket (discussed in section VI.B.1 of this final
rule), our Office of the Actuary conducted some preliminary analyses of
the effects on the market basket calculation and, based on these
analyses, determined that these effects would likely be small. Home
office costs represent only one of many cost categories (including, but
not limited to, salaries, benefits, professional liability insurance,
and pharmacueticals) that are used to develop the cost category
weights. We believe the absence of HealthSouth home office costs in
this market basket has a minor impact on the distribution of these
weights and, by extension, the final market basket update itself. Thus,
we did not believe it was necessary to recalculate the market basket.
Finally, since the facility-level adjustments we proposed in the FY
2006 proposed rule (70 FR 30188) were calculated using regression
analysis based on the relative total costs associated with care in
different types of IRFs (that is, urban/rural, teaching/non-teaching,
low DSH percentage/high DSH percentage), the omission of HealthSouth's
home office costs had some effect on the results of these analyses. The
largest example is for the cost differential between urban and rural
facilities in our analysis. Since the providers that omitted the home
office cost data were largely urban facilities, their lower reported
total cost data caused the differential between urban and rural
facilities to be larger in the initial analyses. The same was true, to
a lesser extent, with the teaching status adjustment and the LIP
adjustment.
Furthermore, the omission of the home office cost data caused
overall reported costs to be lower in these facilities and, therefore,
affected the cost-to-charge ratios computed for these facilities for
FYs 2002 and 2003. We used these cost-to-charge ratios to determine the
proposed update to the outlier threshold amount. Therefore, analysis of
the data indicates that the outlier threshold amount we proposed in the
FY 2006 proposed rule (70 FR 30188) was affected by the omission of the
home office cost data.
Given that the facility-level adjustments, such as the rural, LIP,
and teaching status adjustments, and the outlier threshold amount for
all IRFs were likely affected by the decision of this one large for-
profit chain provider to omit home office cost data from the FY 2002
and FY 2003 cost reports, we believe it is appropriate for us to
recalculate the values for these adjustments and for the outlier
threshold using data that accounts for the omitted home office costs.
Thus, we obtained the FY 2004 HealthSouth home office cost statement
and, from this cost report statement, compiled the home office cost
data for each of the individual HealthSouth IRF providers listed. Of
the 98 providers that omitted home office cost data for FYs 2002 and
2003, 92 of the providers have had home office cost data reported on
the FY 2004 home office cost statement; and six providers did not have
any home office cost information for FY 2004.
We considered several options with respect to incorporating the
missing HealthSouth home office costs into the data RAND used to
conduct the analyses for this final rule. First, we considered the
option of removing all of the HealthSouth cost report data from the
analysis and re-computing the facility-level adjustments (that is, the
rural adjustment, the LIP adjustment, and the teaching status
adjustment) and the outlier threshold without the HealthSouth cost
report data. Dropping all of the cost report data for 98 of the 1,188
facilities in RAND's analysis file, especially when they are large
urban facilities, would seem to skew the data even further because we
would be leaving out a substantial amount of cost report data connected
with one specific type of IRF provider (i.e., urban IRFs). Leaving out
the data for these facilities would make other types of IRFs that are
left in the data appear to have more of an effect on the regression
analysis than they actually do. Since we were hoping to reduce the bias
in the data, rather than increase the bias, we generally rejected this
option.
The second option we considered was to update the analysis using FY
2004 data for all providers and re-compute the facility-level
adjustments and the outlier threshold using the FY 2004 cost report
data. Unfortunately, the FY 2004 data have only recently been submitted
by all IRF providers, and it would have been impossible for RAND and
CMS to have completed all the necessary re-analysis of all of the
proposed policies with the FY 2004 cost report data for all IRF
providers in time for the proposed policies to be implemented in FY
2006.
The third option we considered was to use the FY 2004 home office
cost data that we were able to obtain from the HealthSouth home office
cost statement for 92 of the 98 HealthSouth IRF providers, standardize
all of the other cost report data from FY 2003 for the 98 HealthSouth
providers and the other non-HealthSouth providers using the most recent
market basket for FY 2004, and fill in the FY 2004 home office cost
data for the 92 HealthSouth providers for which we had data. This
option enabled us to meet the October 1 implementation date of our
updates as well as to make those updates and payment adjustments as
accurate as possible. Next, we considered two options for treating the
six HealthSouth facilities for which we did not have FY 2004 home
office cost data: We considered leaving those six IRFs' cost data as
is, without adding any home office cost data since we had none from FY
2004 to add. The other option we considered for treating these six
facilities was to take the average home office costs as a percentage of
total costs for the 92 facilities (which came to approximately 13
percent) and use this as an estimate of home office costs for the 6
facilities. We chose the second of the two options, which meant that we
inflated total costs for those six facilities by the average of about
13 percent, because it seemed inappropriate to ignore the fact that
cost data was missing for these six facilities and 13 percent appeared
to be a reasonable estimate of home office costs generally for IRFs
(from the general analysis we were able to perform).
Because we believe the data file that results from the third option
is more complete than the data RAND previously used to compute the
proposed facility-level adjustments and the proposed outlier threshold
amount for the FY 2006 proposed rule (70 FR 30188), we used the data
from the third option described above to re-compute the values for the
teaching status adjustment (described in more detail in section VI.B.3
of this final rule), the rural adjustment (described in more detail in
section VI.B.4 of this final rule), the LIP adjustment (described in
more detail in section VI.B.5 of this final rule), and the outlier
threshold amount (described in more detail in section VI.B.6 of this
final rule). Because the values of these adjustments have changed, we
also re-computed the budget neutrality factors and, thus, the standard
payment conversion factor.
Comment: Several commenters requested that we make IRF claims data,
IRF-PAI data, patient-specific CMG data, and cost report files
available to the public so that the public would have the opportunity
to recreate the analyses used in developing the proposed refinements
for the FY 2006 proposed rule (70 FR 30188).
Response: The data files mentioned by the commenters are generally
available (and were generally available
[[Page 47886]]
during the comment period for the FY 2006 proposed rule (70 FR 30188))
to the public through CMS's standard data distribution systems. More
information on CMS's data distribution policies is available on CMS's
website at http://www.cms.hhs.gov/researchers/statsdata.asp.
Comment: A few commenters requested that we make available RAND's
research using FY 2003 data. They noted that 3 of the 4 reports
published on RAND's website for public access are based on analysis of
calendar year 2002 data. One of RAND's publicly available reports is
based on analysis of FY 2003 data.
Response: We asked RAND to use the best available, most current
data possible for the analyses contained in the FY 2006 proposed rule
(70 FR 30188) and this final rule. This was generally FY 2003 data.
The updated analysis is generally not contained in RAND's reports,
and RAND has indicated to CMS that they have no plans to publish the
updated analyses (using the FY 2003 data) after publication of the
final rule. However, RAND informed us that, in all of the FY 2003
analyses for the FY 2006 proposed rule (70 FR 30188) and for this final
rule, they used the identical methodologies presented in the reports
available on RAND's website and reviewed by RAND's technical expert
panel. The only change was that RAND used updated data from FY 2003
(and FY 2004 HealthSouth home office cost data, as discussed above).
Thus, interested parties should examine the reports available on RAND's
website for the detailed methodology used to develop the proposed and
final revisions. In addition, interested parties may contact RAND
directly for more information regarding the analysis of FY 2003 data.
Comment: One commenter asked whether a large number of short period
cost reports for periods ending in 2001 might have affected RAND's
research findings and, if so, how RAND handled this issue in the data.
Response: We were unable to find any reasons for the unusually
large number of short period cost reports the commenter is indicating
for cost report periods ending in 2001. However, since some of RAND's
analysis for this final rule was based on calendar year 2002 data, and
the majority of RAND's analysis for this final rule was based on FY
2003 data, we do not believe that a spike in the number of short period
cost reports in 2001 would have had an effect on RAND's analyses.
V. Refinements to the Patient Classification System
A. Changes to the IRF Classification System
1. Development of the IRF Classification System
Section 1886(j)(2)(A)(i) of the Act, as amended by section 125 of
the Medicare, Medicaid, and SCHIP Balanced Budget Refinement Act of
1999 requires the Secretary to establish ``classes of patient
discharges of rehabilitation facilities by functional-related groups
(each referred to as a case-mix group or CMG), based on impairment,
age, comorbidities, and functional capability of the patients, and such
other factors as the Secretary deems appropriate to improve the
explanatory power of functional independence measure-function related
groups.'' In addition, the Secretary is required to establish a method
of classifying specific patients in IRFs within these groups as
specified in Sec. 412.620.
In the August 7, 2001 final rule (66 FR at 41342), we implemented a
methodology to establish a patient classification system using CMGs.
The CMGs are based on the FIM-FRG methodology and reflect refinements
to that methodology.
In general, a patient is first placed in a major group called a
rehabilitation impairment category (RIC) based on the patient's primary
reason for inpatient rehabilitation, (for example, a stroke). The
patient is then placed into a CMG within the RIC, based on the
patient's ability to perform specific activities of daily living, and
sometimes the patient's cognitive ability and/or age. Other special
circumstances, such as the occurrence of very short stays, or cases
where the patient expired, are also considered in determining the
appropriate CMG.
We explained in the August 7, 2001 final rule that further analysis
of FIM and Medicare data may result in refinements to CMGs. In the
August 7, 2001 final rule, we used the most recent FIM and Medicare
data available at that time (that is 1998 and 1999 data). Developing
the CMGs with the 1998 and 1999 data resulted in 95 CMGs based on the
FIM-FRG methodology. The data also supported the establishment of five
additional special CMGs that improved the explanatory power of the FIM-
FRGs. We established one additional special CMG to account for very
short stays and four additional special CMGs to account for cases where
the patient expired. In addition, we established a payment of an
additional amount for patients with at least one relevant comorbidity
in certain CMGs.
2. Description and Methodology Used To Develop the IRF Classification
System in the August 7, 2001 Final Rule
a. Rehabilitation Impairment Categories
In the first step to develop the CMGs, the FIM data from 1998 and
1999 were used to group patients into RICs. Specifically, the
impairment code from the assessment instrument used by clients of UDSmr
and Healthsouth indicates the primary reason for the inpatient
rehabilitation admission. This impairment code is used to group the
patient into a RIC. Currently, we use 21 RICs for the IRF PPS.
b. Functional Status Measures and Age
After using the RIC to define the first division among the
inpatient rehabilitation groups, we used functional status measures and
age to partition the cases further. In the August 7, 2001 final rule,
we used 1998 and 1999 Medicare bills with corresponding FIM data to
create the CMGs and more thoroughly examine each item of the motor and
cognitive measures. Based on the data used for the August 7, 2001 final
rule, we found that we could improve upon the CMGs by making a slight
modification to the motor measure. We modified the motor measure by
removing the transfer to tub/shower item because we found that an
increase in a patient's ability to perform functional tasks with less
assistance for this item was associated with an increase in cost,
whereas an increase in other functional items decreased costs. We
describe below the statistical methodology (Classification and
Regression Trees (CART)) that we used to incorporate a patient's
functional status measures (modified motor score and cognitive score)
and age into the construction of the CMGs in the August 7, 2001 final
rule.
We used the CART methodology to divide the rehabilitation cases
further within each RIC. (Further information regarding the CART
methodology can be found in the seminal literature on CART
(Classification and Regression Trees, Leo Breiman, Jerome Friedman,
Richard Olshen, Charles Stone, Wadsworth Inc., Belmont CA, 1984: pp.
78-80).) We chose to use the CART method because it is useful in
identifying statistical relationships among data and, using these
relationships, constructing a predictive model for organizing and
separating a large set of data into smaller, similar groups. Further,
in constructing the CMGs, we analyzed the extent to which the
independent
[[Page 47887]]
variables (motor score, cognitive score, and age) helped predict the
value of the dependent variable (the log of the cost per case). The
CART methodology creates the CMGs that classify patients with
clinically distinct resource needs into groups. CART is an iterative
process that creates initial groups of patients and then searches for
ways to divide the initial groups to decrease the clinical and cost
variances further and to increase the explanatory power of the CMGs.
Our current CMGs are based on historical data. In order to develop a
separate CMG, we need to have data on a sufficient number of cases to
develop coherent groups. Therefore, we are removing these codes from
the tiers that increase payment.
c. Comorbidities
Under the statutory authority of section 1886(j)(2)(C)(i) of the
Act, we proposed to make several changes to the comorbidity tiers
associated with the CMGs for comorbidities that are not positively
related to treatment costs, or their excessive use is questionable, or
their condition could not be differentiated from another condition.
Specifically, section 1886(j)(2)(C)(i) of the Act provides the
following: The Secretary shall from time to time adjust the
classifications and weighting factors established under this paragraph
as appropriate to reflect changes in treatment patterns, technology,
case mix, number of payment units for which payment is made under this
title and other factors that may affect the relative use of resources.
The adjustments shall be made in a manner so that changes in aggregate
payments under the classification system are a result of real changes
and are not a result of changes in coding that are unrelated to real
changes in case mix.
A comorbidity is a specific patient condition that is secondary to
the patient's principal diagnosis or impairment that is used to place a
patient into a RIC. A patient could have one or more comorbidities
present during the inpatient rehabilitation stay. Our analysis for the
August 7, 2001 final rule found that the presence of a comorbidity
could have a major effect on the cost of furnishing inpatient
rehabilitation care. We also stated that the effect of comorbidities
varied across RICs, significantly increasing the costs of patients in
some RICs, while having no effect in others. Therefore, for the August
7, 2001 final rule, we linked frequently occurring comorbidities to
impairment categories in order to ensure that all of the chosen
comorbidities were not an inherent part of the diagnosis that assigns
the patient to the RIC.
Furthermore, in the August 7, 2001 final rule, we indicated that
comorbidities can affect cost per case for some of the CMGs, but not
all. When comorbidities substantially increased the average cost of the
CMG and were determined to be clinically relevant (not inherent in the
diagnosis in the RIC), we developed CMG relative weights adjusted for
comorbidities (Sec. 412.620(b)).
d. Development of CMG Relative Weights
Section 1886(j)(2)(B) of the Act requires that an appropriate
relative weight be assigned to each CMG. Relative weights account for
the variance in cost per discharge and resource utilization among the
payment groups and are a primary element of a case-mix adjusted PPS.
The establishment of relative weights helps ensure that beneficiaries
have access to care and receive the appropriate services that are
commensurate to other beneficiaries that are classified in the same
CMG. In addition, prospective payments that are based on relative
weights encourage provider efficiency and, hence, help ensure a fair
distribution of Medicare payments. Accordingly, as specified in Sec.
412.620(b)(1), we calculate a relative weight for each CMG that is
proportional to the resources needed by an average inpatient
rehabilitation case in that CMG. For example, cases in a CMG with a
relative weight of 2, on average, will cost twice as much as cases in a
CMG with a relative weight of 1. We discuss the details of developing
the relative weights below.
As indicated in the August 7, 2001 final rule, we believe that the
RAND analysis has shown that CMGs based on function-related groups
(adjusted for comorbidities) are effective predictors of resource use
as measured by proxies such as length of stay and costs. The use of
these proxies is necessary in developing the relative weights because
data that measure actual nursing and therapy time spent on patient
care, and other resource use data, are not available.
e. Overview of Development of the CMG Relative Weights
As indicated in the August 7, 2001 final rule, to calculate the
relative weights, we estimate operating (routine and ancillary
services) and capital costs of IRFs. For this final rule as we
indicated in the FY 2006 proposed rule (70 FR 30188), we use the same
method for calculating the cost of a case that we outlined in the
August 7, 2001 final (66 FR at 41351 through 43153). We obtained cost-
to-charge ratios for ancillary services and per diem costs for routine
services from the most recent available cost report data. We then
obtain charges from Medicare bill data and derived corresponding
functional measures from the FIM data. We omit data from rehabilitation
facilities that are classified as all-inclusive providers from the
calculation of the relative weights, as well as from the parameters
that we use to define transfer cases, because these facilities are paid
a single, negotiated rate per discharge and therefore do not maintain a
charge structure. For ancillary services, we calculate both operating
and capital costs by converting charges from Medicare claims into costs
using facility-specific, cost-center specific cost-to-charge ratios
obtained from cost reports. Our data analysis for the August 7, 2001
final rule showed that some departmental cost-to-charge ratios were
missing or found to be outside a range of statistically valid values.
For anesthesiology, a value greater than 10, or less than 0.01, is
found not to be statistically valid. For all other cost centers, values
greater than 10 or less than 0.5 are found not to be statistically
valid. In the August 7, 2001 final rule, we replaced individual cost-
to-charge ratios outside of these thresholds. The replacement value
that we used for these aberrant cost-to-charge ratios was the mean
value of the cost-to-charge ratio for the cost-center within the same
type of hospital (either freestanding or unit). For routine services,
per diem operating and capital costs are used to develop the relative
weights. In addition, per diem operating and capital costs for special
care services are used to develop the relative weights. (Special care
services are furnished in intensive care units. We note that less than
1 percent of rehabilitation days are spent in intensive care units.)
Per diem costs are obtained from each facility's Medicare cost report
data. We use per diem costs for routine and special care services
because, unlike for ancillary services, we could not obtain cost-to-
charge ratios for these services from the cost report data. To estimate
the costs for routine and special care services included in developing
the relative weights, we sum the product of routine cost per diem and
Medicare inpatient days and the product of the special care per diem
and the number of Medicare special care days.
In the August 7, 2001 final rule, we used a hospital specific
relative value method to calculate relative weights.
[[Page 47888]]
For the FY 2006 proposed rule (70 FR 30188) and this final rule, we
used the following basic steps to calculate the relative weights as
indicated in the August 7, 2001 final rule (at 66 FR 41316, 41351
through 41352).
The first step in calculating the CMG weights is to estimate the
effect that comorbidities have on costs. The second step required us to
adjust the cost of each Medicare discharge (case) to reflect the
effects found in the first step. In the third step, the adjusted costs
from the second step were used to calculate ``relative adjusted
weights'' in each CMG using the hospital-specific relative value
method. The final steps are to calculate the CMG relative weights by
modifying the ``relative adjusted weight'' with the effects of the
existence of the comorbidity tiers (explained below) and normalizing
the weights to 1.
Our methodology for determining the IRF classification system
remains unchanged from the August 7, 2001 final rule.
B. Changes to the Existing List of Tier Comorbidities
1. Changes To Remove Codes That Are Not Positively Related to Treatment
Costs
While our methodology for this final rule for determining the tiers
remains unchanged from the August 7, 2001 final rule, as we indicated
in the FY 2006 proposed rule (70 FR 30188), RAND's analysis indicates
that 1.6 percent of FY 2003 cases received a tier payment (often in
tier one) that was not justified by any higher cost for the case.
Therefore, under statutory authority section 1886(j)(2)(C)(i) of the
Act, as we proposed in the FY 2006 proposed rule (70 FR 30188) we are
implementing several technical changes to the comorbidity tiers
associated with the CMGs. Specifically, the RAND analysis found that
the first 17 diagnoses shown in Table 1 below are no longer positively
related to treatment cost after controlling for CMG. The additional two
codes were also problematic. According to RAND, code 410.91 (AMI, NOS,
Initial) was not specific enough to be differentiated from other
related codes and code 260, Kwashiorkor, was found to be
unrealistically represented in the data according to the RAND technical
expert panel.
With respect to the eighteenth code in Table One, (410.X1) Specific
AMI, initial), we note that RAND found there is no clinical reason to
believe that this code differs in a rehabilitation environment from all
of the specific codes for initial AMI of the form 410.X1, where X is an
numeric digit. In other words, this code is indistinguishable from the
seventeenth code in Table One (410.91 AMI, NOS, initial). Following
this observation, RAND tested the other initial AMI codes as a single
group and found that they have no positive effect on case cost. Thus,
as we indicated in the FY 2006 proposed rule (70 FR 30188), we proposed
to remove ``AMI, NOS, initial'' from the tier list because it is not
positively related to treatment cost after controlling for the CMG. In
addition, for similar reasons, we proposed in the FY 2006 proposed rule
(70 FR 30188) to remove ``Specific AMI, initial from the tier list
since it is indistinguishable from ``AMI, NOS, initial.''
As we proposed in the FY 2006 proposed rule (70 FR 30188), with
respect to the last code in Table One (Kwashiorkor), we are removing
this code from the tier list as well. This comorbidity is positively
related to cost in our data. However, RAND's technical expert panel
(TEP) found the large number of cases coded with this rare disease to
be unrealistic and recommended that it be removed from the tier list.
Table 1 contains two malnutrition codes, and as we proposed in the
FY 2006 proposed rule (70 FR 30188), we are removing these two
malnutrition codes. As we stated in the FY 2006 Proposed Rule (70 FR
30188), removal of these codes where use is concentrated in specific
hospitals is particularly important because these hospitals are likely
receiving unwarrantedly high payments due to the tier one assignment of
these cases. Thus, because we believe the excess use of these two
comorbid conditions is inappropriate based on the findings of RAND's
TEP, they will be removed.
The data indicate large variation in the rate of increase from the
1999 data to the 2003 data across the conditions that make up the
tiers. The greatest increases were for miscellaneous throat conditions
and malnutrition, each of which were more than 10 times as frequent in
2003 as in 1999. The growth in these two conditions was far larger than
for any other condition. Many conditions, however, more than doubled in
frequency, including dialysis, cachexia, obesity, and the non-renal
complications of diabetes. The condition with the least growth, renal
complications of diabetes, may have been affected by improved coding of
dialysis.
As we proposed in the FY 2006 proposed rule (70 FR 30188), we are
finalizing changes to our initial list of diagnoses that deal with
tracheostomy cases. These rare cases were excluded from the pulmonary
RIC 15 in the August 7, 2001 final rule. The new data indicate that
they are more expensive than other cases in the same CMG in RIC 15, as
well as in other RICs. Therefore, we believe the data demonstrate that
tracheostomy cases should be added to the tier list for RIC 15 in order
to receive a higher payment. Finally, the new data indicate that DX
V55.0, ``attention to tracheostomy'' should be part of this condition
as these cases were and are as expensive as other tracheostomy cases.
Thus, since ``attention to tracheostomy'' is as expensive as other
tracheostomy cases, it is logical to group such similar cases together.
Therefore, we are finalizing our proposal to remove the RIC 15
exclusion for code V55.0 (attention to tracheostomy) so that code V55.0
can receive appropriate payment for the additional costs it incurs.
As we stated in the FY 2006 proposed rule (70 FR 30188), we believe
that the data provided by RAND support the removal of the codes in
Table 1 below because they either have no impact on cost after
controlling for their CMG or are indistinguishable from other codes or
are unrealistically overrepresented. Therefore, we are finalizing our
proposed policy to remove these codes from the tier list.
Table 1.--List of Codes To Be Removed From the Tier List
------------------------------------------------------------------------
ICD-9-CM code Abbreviated code title Condition
------------------------------------------------------------------------
235.1............. Unc behav neo oral/phar.. Miscellaneous throat
conditions.
933.1............. Foreign body in larynx... Miscellaneous throat
conditions.
934.1............. Foreign body bronchus.... Miscellaneous throat
conditions.
530.0............. Achalasia & cardiospasm.. Esophegeal conditions.
530.3............. Esophageal stricture..... Esophageal conditions.
530.6............. Acquired esophag Esophageal conditions.
diverticulum.
[[Page 47889]]
V46.1 *........... Dependence on respirator. Ventilator status.
799.4............. Cachexia................. Cachexia.
V49.75............ Status amputation below Amputation of LE.
knee.
V49.76............ Status amputation above Amputation of LE.
knee.
V49.77............ Status amputation hip.... Amputation of LE.
356.4............. Idiopathic progressive Meningitis and
polyneuropathy. encephalitis.
250.90............ Diabetes II, w Non-renal complications
unspecified of diabetes.
complications, not
stated as uncontrolled.
250.93............ Diabetes I, w unspecified Non-renal complications
complications, of diabetes.
uncontrolled.
261............... Nutritional Marasmus..... Malnutrition.
262............... Other severe protein Malnutrition.
calorie deficiency.
410.91............ AMI, NOS, initial........ Major comorbidities.
410.X1............ Specific AMI, initial.... Major comorbidities.
260............... Kwashiorkor.............. Malnutrition.
------------------------------------------------------------------------
* V46.11 and V46.12 were not in existence when the data used in the
analysis was collected. Since these codes are subcategories of code
V46.1 (the code we proposed to remove from the tiers that make
additional payment), they will be removed from the comorbidity tiers
as well.
We received numerous comments on the proposed changes to the
existing list of tier comorbidities which are summarized below:
Comment: One commenter remarked that kwashiorkor should be omitted
from the list of comorbidities to be deleted from the list of
comorbidities that increase the payment rate of the CMG because some of
the software packages used by the industry allow this code to be used
for the coding of the inpatient's comorbidities.
Response: We disagree with the commenter. Kwashiorkor is a severe
malnutrition of infants and young children, primarily in tropical and
subtropical regions, caused by deficiency in the quality and quantity
of protein in the diet. It is characterized by anemia, edema, potbelly,
loss of pigment in the skin, hair loss or change in hair color,
hypoalbuminemia, and bulky stools containing undigested food. In
addition, an inpatient with this condition most likely would not be
able to receive the three hours of intensive rehabilitation that is a
qualifying guideline to be an inpatient within an IRF. While protein
deficiencies may be noted in patients within an IRF, by definition, the
incidence of Kwashiorkor could not be as high as reported. Also, as
previously stated, RAND's TEP reported that the data indicate large
variation in the rate of increase across conditions. However, coding of
malnutrition increased by more than 10 times, and RAND found the large
number of cases coded with this rare disease to be unrealistic and
recommended that it be removed from the tier list. Consequently,
kwashiorkor will be eliminated from the list of comorbidities that
increase the payment rate of the CMG.
Comment: One commenter wrote that code V46.1 is listed in the
proposed list of codes to be removed from the tier list. Since this
code contains two other codes, the commenter wanted to know if it is
our intention to remove both codes in this category, namely V46.11
(Dependence on respirator, status) and V46.12 (Encounter for respirator
dependence during power failure) or just one of these codes.
Response: First, we want to explain how codes V46.11 and V46.12
became codes that are used to increase the CMG payment rate. In the
August 7, 2001 final rule (66 FR 41316), we published Appendix C that
listed the ICD-9-CM comorbid condition codes which are used to increase
the CMG payment rate. The ICD-9-CM codes of the comorbid conditions are
recorded by the IRF's staff on the IRF-PAI, and that data as well as
some other data recorded on the IRF-PAI is used to classify an
inpatient into a CMG payment rate. One of the codes we published as
part of Appendix C was V46.1. Each year the codes used in the ICD-9-CM
coding system undergo a review resulting in updates to some of the
existing codes. In accordance with a review that updated the ICD-9-CM
coding system V46.11 and V46.12 were added to the ICD-9-CM coding
system as subcategories of V46.1. We believe that the comorbid
condition represented by the code V46.11 or V46.12 is a derivative of
the comorbid condition represented by the code V46.1. Therefore, in
2005 we updated the CMG grouper software which resulted in the CMG
payment being increased by the same amount if the IRF-PAI data of an
inpatient included codes V46.1, or V46.11, or V46.12.
The analysis that our data contractor performed, using certain data
after the IRF PPS was implemented, shows that the comorbid condition
represented by code V46.1 does not have an effect upon treatment cost
after controlling for the CMG. Therefore, code V46.1 and its derivative
codes that comprise it (V46.11 and V46.12) will be removed from the
list of codes that are used by the IRF PPS to increase the CMG payment
rate.
Comment: Several commenters urged us to consider not removing codes
V49.75, V49.76, and V49.77 from the list of comorbidity codes that
increase the CMG payment because of concerns with the complexity of a
patient with an amputation.
Response: After controlling for the CMG, RAND found that these
codes do not impact cost. Further, IRFs do not incur additional costs
to treat these comorbidities after controlling for the CMG. This means
that the CMG to which the inpatient is assigned, already accounts for
the costs associated with the treatment of inpatients with an
amputation and no additional payment is needed beyond the CMG amount to
adequately reimburse for such a case. Therefore we are removing these
codes from the list of comorbidities that increase the CMG payment.
Comment: Several commenters mentioned a concern with the code
V497.7 in the table of codes to be removed. They believed it to be a
typographical error where the actual code to be removed is V49.77.
Response: We agree with the commenters and have made the correction
to the typographical error. The corrected code to be removed is V49.77.
Comment: Several commenters noted that there is a discrepancy with
code 428.3 (vocal cord paralysis, not otherwise specified) in CMS' list
of
[[Page 47890]]
codes being reassigned based on their marginal cost in the Comorbidity
Tier Reassignment Changes File found at http://www.cms.hhs.gov/providers/irfpps/fy06nprm.asp.
They stated that it should actually be
code 478.30 (vocal cord paralysis, not otherwise specified).
Response: We agree with the commenters and shall make the
appropriate corrections to the typographical error within the file.
Comment: Several commenters noted an error with the description of
meningitis and encephalitis for code 356.4 in the Comorbidity Tier
Reassignment Changes File found at http://www.cms.hhs.gov/providers/irfpps/fy06nprm.asp
.
Response: We agree with the commenters and the description will be
amended to read idiopathic progressive polyneuropathy for code 356.4.
Comment: Commenters expressed concern for the removal of codes
530.0 (achalasia and cardiospasm), 530.3 (stricture and stenosis of
esophagus) and 530.6 (diverticulum of esophagus) that are used to
record esophageal conditions because of costs associated with these
conditions and requested that they not be removed from the tier list
which increases payment for these comorbidities.
Response: After controlling for the CMG, RAND found that these
comorbidities do not positively impact costs, meaning that the CMG
encompasses sufficient payment to compensate for these comorbidities.
Therefore, we are removing codes 530.0, 530.3 and 530.6 from the list
of comorbidities that increase CMG payment.
Comment: Several commenters agreed with CMS' proposed policy to
remove malnutrition codes 261 (nutritional marasmus) and 262 (other
severe protein-calorie malnutrition), while others opposed the proposed
policy to remove these codes. In addition, several commenters suggested
that CMS examine the impact of malnutrition on increasing the length of
stay within an IRF.
Response: We acknowledge both opinions as expressed by the
different commenters. The RAND TEP, and our Medical Officers, believes
these codes are drastically overstated and inpatients with these levels
of malnutrition would not be candidates for three hours of intensive
therapy. In addition, after controlling for the CMG, both of these
codes do not positively affect payment. Therefore we believe it is
appropriate to remove malnutrition codes 261 and 262 from the list of
comorbidity codes that are used to increase the CMG payment rate.
Additionally, we will continue to examine the impact of comorbidities,
including malnutrition, upon IRF Medicare-covered inpatients.
Comment: One commenter suggested adding codes 250.91 and 250.92 to
the list of comorbidities to be removed from the list of codes used to
increase payment because they believe those codes to be similar in
description to codes 250.90 and 250.93.
Response: Only the first 17 codes within Table 1 were found to have
no positive effect on cost after controlling for the CMG. The data
analysis performed by RAND does not indicate that at this time 250.91
and 250.93 should be removed from the list of codes used to increase
the CMG payment rate because they continue to positively affect costs.
Therefore we believe it is inappropriate to remove them from the list
of comorbidities that impact cost. Consequently, we are not removing
any other codes from the list of codes used to increase the CMG payment
rate.
Comment: One commenter recommended that several codes be added to
our comorbidity tier system based upon suggestions from the RAND TEP,
namely codes 428.0 (congestive heart failure), V43.3 (heart valve
replacement), 250.1 (insulin dependent diabetes without mention of
complications, not stated as controlled) and 438.2X (hemi-paresis due
to an old stroke).
Response: After examining the RAND recommendations, our Medical
Officers felt that codes V43.3 and 438.2X were too vague and non-
descript to capture the necessary information needed for these codes to
be added to the list of codes used to increase the CMG payment rate.
However, in response to the comments our Medical Officers re-evaluated
the effect on cost by the comorbid condition represented by code 250.1
(insulin dependent diabetes without mention of complications, not
stated as controlled). They determined that code 250.1 should be added
to the list of codes used to increase the CMG payment rate. They also
determined that the code should be a tier 3 code because the other 250
series of codes related to diabetes are in tier 3. Therefore, this code
will be added as a tier 3 code to the list of codes used to increase
the CMG payment rate. There will be no excluded RICs with code 250.1.
After examining the comments, our Medical Officers continue to believe
that 428.9 (heart failure, unspecified), was too non-descript and
should not be added to the list of codes that can increase payment.
However, our Medical Officers agree with the commenter regarding other
numerous congestive heart failure codes including Code 428.1--Left
Heart Failure, Code 428.20--Systolic Heart Failure Unspecified, Code
428.21--Systolic Heart Failure Acute, Code 428.22--Systolic Heart
Failure Chronic, Code 428.23--Systolic Hear Failure Acute on Chronic,
Code 428.30--Diastolic Heart Failure Unspecified, Code 428.31--
Diastolic Heart Failure Acute, Code 428.32--Diastolic Heart Failure
Chronic, Code 428.33--Diastolic Heart Failure Acute on Chronic, Code
428.40--Combined Systolic and Diastolic Heart Failure Unspecified, Code
428.41--Combined Systolic and Diastolic Heart Failure Acute, Code
428.42--Combined Systolic and Diastolic Heart Failure Chronic, and Code
428.43--Combined Systolic and Diastolic Heart Failure Acute on Chronic,
largely due to the increased costs associated with these codes.
Therefore, these 428 cardiac codes will be added to the list of codes
used to increase the CMG payment rate as tier 3 codes because of their
similarity to certain cardiac codes with respect to resource
utilization. However, these codes will not be used to increase the CMG
payment rate if the CMG code is one of the CMG codes derived from RIC
14 (the cardiac RIC) because these cardiac codes costs have been
accounted for in the CMGs associated with RIC 14.
Comment: A commenter believes that the CMG payment rate should
include an adjustment for mental health problems, such as a depression.
The commenter believes that a patient's mental health status has an
effect on the patient treatment costs an IRF incurs.
Response: The significance and appropriateness of a patient's state
of mental health in response to an impairment that requires a patient
to undergo intensive inpatient rehabilitation is a subject that we
believe requires further study. Additional study will help to determine
the effect of the patient's state of mental health on treatment costs.
An ICD-9-CM code may be used to show that a patient is exhibiting signs
that a rehabilitation clinician believes indicate a mental disorder.
However, quantifying by use of ICD-9-CM codes the association between a
patient's state of mental health and how it affects a patient's
response to rehabilitation treatment is at best limited. For example,
we believe that in response to a stroke or hip fracture, or some other
impairment, a situational depression may be a rational response.
However, that does not mean that the IRF will incur additional costs
that were not already taken into account when the CMG payment rates
were developed. In addition, mental disorders vary greatly
[[Page 47891]]
in severity as does how a patient's functioning is affected by a mental
disorder.
There would have to be multiple factors taken into consideration
before any type of mental disorder could be added to the list of
comorbidities that would increase payment of the CMG. The data for a
complete psychiatric evaluation must be made available to correctly
code for these comorbidities. In addition, this is a budget neutral
system, and no additional funding will be added to the system. Under
our final rule, funds will not be added but simply be redistributed
among the comorbidities among the tiers that increase payment. This is
because the changes associated with the comorbidity tiers and CMGs are
done in a budget neutral manner. On the assumption that there is an
even distribution of these psychiatric patients among IRFs, and these
patients may receive the redistributed payment, the addition of these
codes may not contribute to an increased payment for inpatients with
these comorbid conditions and may affectively lower payments for CMG's
with other comorbid conditions because the same amount of funding is
distributed across more comorbid conditions. Also, few IRFs have
psychiatric personnel and rehabilitation doctors rarely have the time
required to observe the patient to make a complete psychiatric
evaluation and thus some codes may be assigned (or not assigned) in
error. In addition, RAND's TEP believed that it would be inappropriate
to use ICD-9-CM diagnoses to identify patients with affective
disorders. Therefore, in this final rule, we are not adding codes for
depression and mental disorders to the list of codes used to increase
payment.
Comment: We received comments to both challenge and support the
removal of certain comorbidity codes from the tier list including code
799.4 Cachexia, and code 933.1 (foreign body in larynx). Commenters
stated that these conditions required more resources, and thus
increased treatment costs. The other commenter stated that the CMG
already covered these costs.
Response: The data analysis did not show that the comorbid
conditions indicated by these codes increased the costs of treating an
inpatient with these comobidities after controlling for the CMG because
their CMG payment rate covers costs associated with their corresponding
treatment. The more recent RAND analysis found that after controlling
for the CMG, these comobidities do not impact cost. Therefore, we are
removing them from the comorbidity tiers that would increase payment.
Comment: One commenter made a general statement stating that the
list of comorbidities that comprise the tiers do not reflect the
challenges that contribute to higher costs in the rehabilitation
setting.
Response: We disagree with the commenter because the RAND
regression analyses show that the comorbid conditions that comprise the
tiers positively impact cost and provide additional payments for
services not included in the payment associated with the CMG.
Final Decision: In this final rule, we are adopting the proposal to
remove the comorbidity tier codes set forth in Table 1 of the FY 2006
proposed rule (70 FR 30188). We are also removing codes V46.11 and
V46.12 because they are subcategories of code V46.1, which has been
found to have no impact on cost after controlling for the CMG. We are
adding several codes that the RAND analyses found to positively impact
costs. We chose to add codes 250.1 (insulin dependent diabetes without
mention of complications, not stated as controlled), as well as
numerous congestive heart failure codes including Code 428.1--Left
Heart Failure, Code 428.20--Systolic Heart Failure Unspecified, Code
428.21--Systolic Heart Failure Acute, Code 428.22--Systolic Heart
Failure Chronic, Code 428.23--Systolic Heart Failure Acute on Chronic,
Code 428.30--Diastolic Heart Failure Unspecified, Code 428.31--
Diastolic Heart Failure Acute, Code 428.32--Diastolic Heart Failure
Chronic, Code 428.33--Diastolic Heart Failure Acute on Chronic, Code
428.40--Combined Systolic and Diastolic Heart Failure Unspecified, Code
428.41--Combined Systolic and Diastolic Heart Failure Acute, Code
428.42--Combined Systolic and Diastolic Heart Failure Chronic, and Code
428.43--Combined Systolic and Diastolic Heart Failure Acute on Chronic,
which our Medical Officers believe were specific enough to be used in
our list of codes that are used to increase the CMG payment amount.
2. Changes To Move Dialysis to Tier One
As we proposed in the FY 2006 proposed rule (70 FR 30188), we are
finalizing the movement of dialysis from comorbidity tier two to
comorbidity tier one, which is the tier associated with the highest
payment. The data from the RAND analysis show that patients on dialysis
cost more than the tier payment to which dialysis is currently
assigned, and should be moved into the highest paid tier because this
tier would more closely align payment with the cost of a case. Based on
RAND's analysis using 2003 data, a patient with dialysis costs 31
percent more than a non-dialysis patient in the same CMG and with the
same other accompanying comorbidities.
Overall, the largest increase in the cost of a condition occurs
among patients on dialysis, where the coefficient in the cost
regression increases by 93 percent, from 0.1400 to 0.2697. Part of the
explanation for the increased coefficient could be that some IRFs had
not borne all dialysis costs for their patients in the pre-PPS period,
which was the previous data analysis time period(because providers were
previously permitted to bill for dialysis separately). It is likely
that, in the 1999 data, some IRFs had not borne all dialysis costs for
their patients. Because the fraction of cases coded with dialysis
increased by 170 percent, it is also likely that improved coding was
part of the explanation for the increased coefficient. We believe a 170
percent increase is such a dramatic increase that it would be highly
unlikely that in the time periods used for the data analysis, 170
percent more patients needed dialysis when compared to the time period
before the implementation of the IRF PPS. We also believe that the
improved coding is likely due to the fact that higher costs are
associated with dialysis patients, and therefore IRFs, in an effort to
ensure that their payments cover these higher expenses better and more
carefully coded comorbidities whose presence resulted in higher PPS
payments.
Therefore we are moving dialysis patients to comorbidity tier one
will more adequately compensate IRFs for the extra cost of those
patients and thereby maintain or increase access to these services.
Comment: A number of commenters supported our decision to move
dialysis patients to tier one due to the increase cost of dialysis
patients.
Response: We agree with these commenters. The data analyses
performed by RAND found evidence that suggested that a dialysis patient
cost 31 percent more than a non-dialysis patient in the same CMG.
Therefore, as proposed in the FY 2006 proposed rule (70 FR 30188), we
are moving dialysis to tier 1 because the additional payment associated
with tier 1 more closely approximate the additional costs associated
with the treatment of an inpatient with this condition.
Final Decision: As proposed in the FY 2006 proposed rule (70 FR
30188), we are adopting the decision to move dialysis patients to
comorbidity tier one.
[[Page 47892]]
3. Changes To Move Comorbidity Codes Based on Their Marginal Cost
Under section 1886(j)(2)(C)(i) of the Act, as was proposed in the
FY 2006 proposed rule (70 FR 30188), we are refining how we pay for a
comorbidity based on marginal cost. A commonly understood definition of
marginal cost is the increase or decrease in costs as a result of one
higher or lower unit of a good or service. In this situation, we are
reassigning comorbidities to tiers based on their marginal costs, and
by this we mean the increase or decrease in costs as a result of one
higher or lower comorbidity tier. Payment for several comorbidities
would be more accurate if their tier assignments were changed, and
after examining RAND's data, we believe that of the FY 2003 cases, a
full 4 percent of cases should be associated with comorbidity tiers
that have a lower payment than the comorbidity tiers to which they were
assigned. Therefore, comorbidities would be more accurate if their tier
assignments were more appropriately based on their marginal costs.
As we proposed in the FY 2006 proposed rule (70 FR 30188),
comorbidity tier assignments in this final rule are based on the
results of statistical analyses RAND has performed under contract with
CMS, using as independent variables only the CMGs and conditions for
tiers. As we proposed in the FY 2006 proposed rule (70 FR 30188), tier
assignments of each of these conditions for the final rule are
determined based on the magnitude of their coefficients in RAND's
statistical analysis.
We believe the IRF PPS led to substantial changes in coding of
comorbidities between 1999 (pre-implementation of the IRF PPS) and 2003
(post-implementation of the IRF PPS). The percentage of cases with one
or more comorbidities increased from 16.79 percent according to the
data used to define the comorbidity tiers (1998 through 1999) to 25.51
percent in FY 2003. This is an increase of 52 percent in tier incidence
(52 = 100 x (25.51-16.79)/16.79). The recording of a tier one
comorbidity, the highest paid of the tiers, almost quadrupled during
this same time period. Although, improved coding likely increased the
recording of comorbidities, those coding the comorbidities may have
been motivated by the objective to use coding changes as a means to
increase the CMG payment.
The 2003 data provides an excellent comprehensive picture of the
costs that are associated with each of the comorbidities. We believe
this because CMS has data for 100 percent of the Medicare-covered IRF
cases. Therefore, as we indicated in the FY 2006 proposed rule, we
believe that using the 2003 data to assign the comorbidities to a
payment tier ensures heightened accuracy with respect to the matching
of payments to relative costs of a case.
We received several comments on the proposed changes to the
existing list identifying which tier is associated with a particular
comorbidity. The public comments are summarized below.
Comment: One commenter suggested that we postpone reassigning
comorbidity tiers based on their marginal costs, and again instead
perform the data analysis used to reassign the comorbidity codes based
on marginal costs using more current data.
Response: This final rule reflects the most recent analysis of
data. In the future, we will continue to perform data analyses and, as
necessary, adjust the payment rates to achieve the most accurate
payment. In this final rule, we are adopting the policy we proposed in
the FY 2006 proposed rule (70 FR 30188), and reassigning comorbidities
to tiers based on their marginal cost because we believe that this
reassignment is based on the best comprehensive post-PPS implementation
data that are available at this time.
Comment: One commenter recommended that we not reassign any
comorbidity codes based on their marginal costs under the premise that
there is no concrete evidence of upcoding.
Response: Taking into consideration that we believe that there has
been improved coding due to prospective payment based system, the
recommendations of RAND's technical expert panel, and the guidance of
our Medical Officers, we believe that the comorbidity codes should be
assigned based on their marginal costs in order to increase the
association between costs and payment.
Final Decision: In summary, we are adopting all of the proposals
set forth in the FY 2006 proposed rule (70 FR 30188), with regard to
the removal of the list of codes from comorbidity tiers that increase
payment, the movement of dialysis patients to tier one, the code V55.0
will no longer be excluded from RIC 15, and comorbidity codes will now
be reassigned based on their marginal costs.
C. Changes to the CMGs
Section 1886(j)(2)(C)(i) of the Act requires the Secretary from
time to time to adjust the classifications and weighting factors of
patients under the IRF PPS to reflect changes in treatment patterns,
technology, case mix, number of payment units for which payment is
made, and other factors that may affect the relative use of resources.
These adjustments shall be made in a manner so that changes in
aggregate payments under the classification system are the result of
real changes and not the result of changes in coding that are unrelated
to real changes in case mix.
In the FY 2006 proposed rule (70 FR 30188, 30196), in accordance
with section 1886(j)(2)(C)(i) of the Act and as specified in Sec.
412.620(c) and based on the research conducted by RAND, we proposed to
update the CMGs used to classify IRF patients for purposes of
establishing payment amounts. We also proposed to update the relative
weights associated with the payment groups based on FY 2003 Medicare
bill and patient assessment data. We proposed replacing the current
unweighted motor score index used to assign patients to CMGs with a
weighted motor score index that would improve our ability to accurately
predict the costs of caring for IRF patients, as described in detail
below. However, we proposed not to change the methodology for computing
the cognitive score index.
As described in the August 7, 2001 final rule, we contracted with
RAND to analyze IRF data to support our efforts in developing our
patient classification system and the IRF PPS. We continued our
contract with RAND to support us in developing potential refinements to
the classification system and the PPS. As part of this research, we
asked RAND to examine possible refinements to the CMGs to identify
potential improvements in the alignment between Medicare payments and
actual IRF costs. In conducting its research, RAND used a technical
expert panel (TEP) made up of experts from industry groups, other
government entities, academia, and other interested parties. The
technical expert panel reviewed RAND's methodologies and advised RAND
on many technical issues.
Several recent developments make significant improvements in the
alignment between Medicare payments and actual IRF costs possible.
First, when the IRF PPS was implemented in 2002, a new assessment
instrument was used to collect patient data, the IRF Patient Assessment
Instrument (IRF-PAI). The new instrument contained items that improved
the quality of the patient-level information available to researchers.
Second, more recent data are available on a larger patient
population. Until now, the design of the IRF PPS was based entirely on
1999 data on Medicare
[[Page 47893]]
rehabilitation patients from just a sample of hospitals (the best
available data at the time). Now, we have post-PPS data from 2002 and
2003 that describe the entire universe of Medicare-covered
rehabilitation patients.
Finally, we believe that improvements in the algorithms that
produced the initial CMGs, as described below, should lead to new CMGs
that better predict treatment costs in the IRF PPS.
Using the inpatient rehabilitation facility assessment instrument
before the PPS, which is commonly referred to as the FIM, and Medicare
data from 1998 and 1999, RAND helped us develop the original structure
of the IRF PPS. IRFs became subject to the PPS beginning with cost
reporting periods starting on or after January 1, 2002. The PPS is
based on assigning patients to particular CMGs that are designed to
predict the costs of treating particular Medicare patients according to
how well they function in four general categories: Transfers, sphincter
control, self-care (for example, grooming, eating), and locomotion.
Patient functioning is measured according to 18 categories of activity:
13 motor tasks, such as putting on clothing, and 5 cognitive tasks,
such as memory. The PPS is intended to align payments to IRFs as
closely as possible with the actual costs of treating patients. If the
PPS ``underpays'' for some kinds of care, IRFs have incentives to limit
access for patients requiring that kind of care because payments for a
particular case would be less than the costs of providing care, so an
IRF may try to limit its financial ``losses''; conversely, if the PPS
overpays, resources are wasted because IRFs' payments exceed the costs
of providing care for a particular case.
The fiscal year 2003 data file currently available for refining the
CMGs contains many more IRF cases and represents the universe of
Medicare-covered IRF cases, rather than a sample. The best available
data that CMS and RAND had for analysis in 1999 contained 390,048 IRF
cases, representing 64 percent of all Medicare-covered patients in
participating IRFs. The more recent data contain 523,338 IRF cases
(fiscal year 2003), representing all Medicare-covered patients in
participating IRFs. The larger file enables RAND to obtain greater
precision in the analysis and portrays a more recent and complete
picture of patients under the IRF PPS.
Also, the fiscal year 2003 data include more detailed information
about patients' level of functioning. For example, new variables are
included in the more recent data that provide further details on
patient functioning. Standard bowel and bladder scores on the FIM
instrument (used to assess patients before the IRF PPS), for example,
measured some combination of the level of assistance required and the
frequency of accidents (that is, soiling of clothes and surroundings).
New variables on the IRF-PAI instrument measure the level and the
frequency separately. Since measures of the level of assistance
required and the frequency of accidents contain slightly different
information about the expected costliness of an IRF patient, having
measures for these two variables separately provides additional
information to researchers.
Furthermore, additional optional information is recorded on the
health status of patients in the more recent data (for example,
shortness of breath, presence of ulcers, inability to balance).
1. Changes for Updating the CMGs
In the FY 2006 proposed rule (70 FR 30188), we proposed to revise
the definitions of the CMGs based on regression analysis by RAND of the
FY 2003 data. As described in the August 7, 2001 final rule, RAND
developed the original list of CMGs using FIM data from 1998 and 1999
(see the FY 2006 proposed rule (70 FR 30188, 30198 through 30202) for a
table of the original CMG listing).
Given the availability of more recent, post-PPS data, we asked RAND
to examine possible refinements to the CMGs to identify potential
improvements in the alignment between Medicare payments and actual IRF
costs. In addition to analyzing fiscal year 2003 data, RAND also
convened a TEP, made up of researchers from industry, provider
organizations, government, and academia, to provide support and
guidance through the process of developing possible refinements to the
PPS. Members of the TEP reviewed drafts of RAND's reports, offered
suggestions for additional analyses, and provided clinicians' views of
the importance and significance of various findings.
As we explained in the FY 2006 proposed rule (70 FR 30188), RAND's
analysis of the FY 2003 data, along with the support and guidance of
the TEP, strongly suggested the need to update the CMGs to better align
payments with costs under the IRF PPS. The other option we considered
before proposing to update the CMGs with the fiscal year 2003 data was
to maintain the same CMG structure but recalculate the relative weights
for the current CMGs using the 2003 data. After carefully reviewing the
results of RAND's regression analysis, which compared the predictive
ability of the CMGs under 3 scenarios (not updating the CMGs or the
relative weights, updating only the relative weights and not the CMGs,
and updating both the relative weights and the CMGs), as we stated in
the FY 2006 proposed rule (70 FR 30188), we believed and continue to
believe (based on RAND's analysis) that updating both the relative
weights and the CMGs will allow the classification system to do a
better job of reflecting changes in treatment patterns, technology,
case mix, and other factors which may affect the relative use of
resources.
We continue to believe it is appropriate to update both the CMGs
and the relative weights at this time because the 2003 data we now have
represent a more recent and broader set of data elements. The more
recent data include all Medicare-covered IRF cases rather than a
subset, allowing us to base the CMG changes on a complete picture of
the types of patients in IRFs. In designing the IRF PPS, we used the
best available data, but those data may not have contained a complete
picture of the types of patients in IRFs. Also, the improved clinical
coding of patient conditions in IRFs is better reflected in the more
recent data than it was in the best available data we had to design the
IRF PPS. In addition, changes in treatment patterns, technology, case
mix, and other factors affecting the relative use of resources in IRFs
since the IRF PPS was implemented likely require an update to the
classification system.
Prior to the finalization of the proposed changes contained in this
final rule, we paid IRFs based on 95 CMGs and 5 special CMGs developed
using the CART algorithm applied to 1999 data. The CART algorithm that
was used in designing the IRF PPS assigned patients to RICs according
to their age and their motor and cognitive FIM scores. CART produced
the partitions so that the reported wage-adjusted rehabilitation cost
of the patients was relatively constant within partitions. Then, a
subjective decision-making process was used to decrease the number of
CMGs (to ensure that the payment system did not become unduly
complicated), to enforce certain constraints on the CMGs (to ensure
that, for instance, IRFs were not paid more for patients who had fewer
comorbidities than for patients with more comorbidities), and to fit
the comorbidity tiers. Although the use of a subjective decision-making
process (rather than a computer algorithm) was very useful, there were
limitations. For example, it made it difficult to explore
[[Page 47894]]
the implications of variations to the CART models because an individual
person is not able to examine as many variations of a model in as short
a period of time as a computer program. Furthermore, the computer is
more efficient at accounting for all of the possible combinations and
interactions between important variables that affect patient costs.
In analyzing potential refinements to the IRF PPS, RAND created a
new algorithm that would be very useful in constructing the CMGs (the
new algorithm would be based on the CART methodology described in
detail in section V.A.2.b of this final rule). RAND applied the new
algorithm to the fiscal year 2003 IRF data. In the FY 2006 proposed
rule (70 FR 30188), we proposed to use RAND's new algorithm for
refinements to the CMGs. The algorithm is based entirely on an
iterative computerized process to decrease the number of CMGs, enforce
constraints on the CMGs, and assign the comorbidity tiers. At each step
in the process, the new CART algorithm produces all of the possible
combinations of CMGs using all available variables. It then selects the
variables and the CMG constructions that offer the best predictive
ability, as measured by the greatest decrease in the mean-squared
error. We proposed to place the following constraints on the algorithm,
based on RAND's analysis: (1) Neighboring CMGs would have to differ by
at least $1,500, unless eliminating the CMG would change the estimated
costs of patients in that CMG by more than $1,000; (2) estimated costs
for patients with lower motor or cognitive index scores (more
functionally dependent) would always have to be higher than estimated
costs for patients with higher motor or cognitive index scores (less
functionally dependent). We believe that the PPS should not pay more
for a patient who is less functionally dependent than for one who is
more functionally dependent; and (3) each CMG must contain at least 50
observations (for statistical validity).
RAND's technical expert panel, which included representatives from
industry groups, other government entities, academia, and other
researchers, reviewed and commented on these constraints and the rest
of RAND's proposed methodology (developed based on RAND's analysis of
the data) for updating the CMGs as RAND developed the improvements to
the CART methodology.
The following are the most substantial differences between the CMGs
used prior to October 1, 2005 and the proposed new CMGs for FY 2006:
Fewer CMGs than before (87 now compared with 95 in the
prior system). The 5 special CMGs for very short stay cases and cases
in which the patient expires would remain unchanged.
The number of CMGs under the RIC for stroke patients (RIC
1) would decrease from 14 to 10.
The cognitive index score would affect patient
classification in two of the RICs (RICs 1 and 2), whereas it previously
affected RICs 1, 2, 5, 8, 12, and 18.
A patient's age would now affect assignment for CMGs in
RICs 1, 4, and 8, whereas it previously affected assignment for CMGs in
RICs 1 and 4.
The primary objective in updating the CMGs is to better align IRF
payments with the costs of caring for IRF patients, given more recent
information. This requires that we improve the ability of the system to
predict patient costs. RAND's analysis suggests that the proposed new
CMGs clearly improve the ability of the payment system to predict
patient costs. The proposed new CMGs would greatly improve the
explanation of variance in the system.
Public comments and our responses on the proposed changes for
updating the CMGs are summarized below.
Comment: Several commenters raised concerns that the FY 2003 data
used to update the CMGs did not reflect the full enforcement of the 75
percent rule and that CMS should, therefore, wait until the data
reflect full enforcement before making any changes to the CMGs.
Response: We agree that additional changes to the CMGs may
potentially be necessary in the future if enforcement of the 75 percent
rule results in substantial changes to IRFs' patient populations.
However, we believe it is now appropriate to begin refining the system
because several recent developments make significant improvements in
the alignment between Medicare payments and actual IRF costs possible.
First, when the IRF PPS was implemented for cost reporting periods
beginning on or after January 1, 2002, a new recording instrument
called the IRF-PAI was used to collect patient data. The new instrument
contained questions that improved the quality of the patient-level
information available to researchers. The 2003 data used in the
proposed refinements reflects this data.
Second, more recent data are available on a larger patient
population. Until now, the design of the IRF PPS was based entirely on
1999 data on Medicare rehabilitation patients from just a sample of
hospitals. Even though this was the best available data at the time, we
now have post-PPS data from 2002 and 2003 that describe the entire
universe of Medicare-covered rehabilitation patients.
Finally, we believe that proposed improvements in the algorithms
that produced the initial CMGs, as described above, lead to new CMGs
that better predict treatment costs in the IRF PPS.
We further note that making refinements to the IRF patient
classification system now, based on post-PPS data, does not preclude us
from making future refinements to the system if IRFs' case mix and care
practices change over time. We will continue to monitor the IRF PPS,
and make refinements as needed, to ensure that IRF payments are aligned
as closely as possible with the costs of providing care.
Comment: One commenter believed that the proposed changes to the
CMGs would make IRF quality measurement more difficult over time
because the proposed changes to the CMG definitions would mean that a
case classified into a particular CMG (such as CMG 0107) before October
1, 2005 (when the proposed changes would be implemented) would not
necessarily be classified into CMG 0107 after October 1, 2005. Thus,
people attempting to create a one-for-one crosswalk between the CMGs
before October 1, 2005 and the proposed CMGs after October 1, 2005
would be unable to do so. The commenter noted that many quality
measurement tools currently being used by IRFs require such a one-for-
one crosswalk.
Response: We recognize the importance of monitoring IRF quality of
care over time. However, we do not believe that the proposed changes to
the CMGs inhibit the ability to monitor quality in IRFs over time.
Quality of care is not measured by a payment rate, but by data
reflecting various indicators of the treatment patients receive. In the
FY 2006 proposed rule (70 FR 30188), we did not propose changes to the
patient assessment form itself or changes to the coding of the
underlying data that is used to classify patients into CMGs. Therefore,
comparisons of the underlying patient classification data could still
be used to monitor quality in these facilities over time.
Comment: One commenter expressed concerns that the cognitive scores
are not used as often in the definitions of the proposed revisions to
the CMGs as they were in the original CMGs defined in the August 7,
2001 final rule. This commenter stated that the cognitive scores are
important predictors of how costly patients are likely to be in the IRF
setting. The commenter also stated that,
[[Page 47895]]
if cognitive scores are not used as often as motor scores for assigning
patients to CMGs, the reason may be that measures of patients'
cognitive abilities may not currently be as well developed as measures
of patients' motor abilities. Therefore, this commenter recommended
that we develop more sensitive measures that have better predictive
qualities.
Response: As we noted previously, the cognitive score used to
classify IRF patients into CMGs is made up of cognitive items from the
IRF-PAI. These cognitive items are generally indications of the
patient's mental functioning level, and are related to the patient's
ability to process and respond to empirical factual information, use
judgment, and accurately perceive what is happening. Patients'
cognitive functioning clearly affects their expected costliness in an
IRF. However, RAND's regression analysis, in which they explored the
relationship of the FIM motor and cognitive scores to cost, showed that
patients' cognitive scores generally did not predict patients' expected
costliness above and beyond what patients' motor scores already were
able to predict. Thus, we see no reason to use cognitive scores in CMG
definitions for which they do not add predictive ability. When the
cognitive scores add information that increases the predictive ability
of the classification system, we make use of this information in the
CMG assignment.
We agree with one of the commenter's points that the cognitive
score may not predict costs as well as the motor score because the
cognitive items may not be as sensitive to patients' cognitive status
as the motor items are to patients' physical functioning. We further
agree with the commenter that more work could be done to better
identify measures of cognitive functioning. Along these lines, CMS has
awarded a contract to the Research Triangle Institute (RTI) to perform
research and data analysis to support possible changes to the IRF-PAI
instrument that would better capture physical and cognitive functioning
information on IRF patients. CMS remains open to examining well-
constructed peer-reviewed studies by other types of providers,
researchers, and other interested parties in order to improve upon the
cognitive assessment functioning measures for the Medicare population.
Until then, we will use the best cognitive functioning information
available for IRF patients to classify patients into the most
appropriate CMGs so IRF payments align as closely as possible with the
costs of care in IRFs.
Final Decision: After carefully considering all the comments we
received on the proposed changes to the CMG definitions, we are
finalizing our decision to adopt the CMG definitions presented below in
Table 2. Based on RAND's regression analysis of FY 2003 data, the best
data available for analysis, we believe these changes will increase the
accuracy of IRF PPS payments.
Table 2.--Case Mix Groups (CMGs), With the Associated Rehabilitation Impairment Categories (RICs)
[Beginning with discharges on or after October 1, 2005]
--------------------------------------------------------------------------------------------------------------------------------------------------------
RIC CMG No. CMG description
--------------------------------------------------------------------------------------------------------------------------------------------------------
01 Stroke (Stroke)........................ 0101 Motor >51.05.
0102 Motor >44.45 & Motor <51.05 & Cognitive >18.5.
0103 Motor >44.45 & Motor <51.05 & Cognitive <18.5.
01 Stroke (Stroke)........................ 0104 Motor >38.85 & Motor <44.45.
0105 Motor >34.25 & Motor <38.85.
0106 Motor >30.05 & Motor <34.25.
0107 Motor >26.15 & Motor <30.05.
0108 Motor <26.15 & Age >84.5.
0109 Motor >22.35 & Motor <26.15 & Age <84.5.
0110 Motor < 22.35 & Age < 84.5.
02 Traumatic brain injury (TBI)........... 0201 Motor >53.35 & Cognitive >23.5.
0202 Motor >44.25 & Motor <53.35 & Cognitive >23.5.
0203 Motor >44.25 & Cognitive <23.5.
0204 Motor >40.65 & Motor <44.25.
0205 Motor >28.75 & Motor <40.65.
0206 Motor >22.05 & Motor <28.75.
0207 Motor < 22.05.
03 Nontraumatic brain injury (NTBI)....... 0301 Motor >41.05.
0302 Motor >35.05 & Motor <41.05.
0303 Motor >26.15 & Motor <35.05.
0304 Motor < 26.15.
04 Traumatic spinal cord injury (TSCI).... 0401 Motor >48.45.
0402 Motor >30.35 & Motor <48.45.
0403 Motor >16.05 & Motor <30.35.
0404 Motor <16.05 & Age >63.5.
0405 Motor < 16.05 & Age < 63.5.
05 Nontraumatic spinal cord injury (NTSCI) 0501 Motor >51.35.
05 Nontraumatic spinal cord injury (NTSCI) 0502 Motor >40.15 & Motor <51.35.
0503 Motor >31.25 & Motor <40.15.
0504 Motor >29.25 & Motor <31.25.
0505 Motor >23.75 & Motor <29.25.
0506 Motor < 23.75.
06 Neurological (Neuro)................... 0601 Motor >47.75.
0602 Motor >37.35 & Motor <47.75.
0603 Motor >25.85 & Motor <37.35.
0604 Motor < 25.85.
07 Fracture of LE (FracLE)................ 0701 Motor >42.15.
0702 Motor >34.15 & Motor <42.15.
0703 Motor >28.15 & Motor <34.15.
0704 Motor < 28.15.
08 Replacement of LE joint (RepLE)........ 0801 Motor >49.55.
[[Page 47896]]
0802 Motor >37.05 & Motor <49.55.
0803 Motor >28.65 & Motor <37.05 & Age >83.5.
0804 Motor >28.65 & Motor <37.05 & Age <83.5.
0805 Motor >22.05 & Motor <28.65.
0806 Motor < 22.05.
09 Other orthopedic(Ortho)................ 0901 Motor >44.75.
0902 Motor >34.35 & Motor <44.75.
0903 Motor >24.15 & Motor <34.35.
0904 Motor < 24.15.
10 Amputation, lower extremity (AMPLE).... 1001 Motor >47.65.
1002 Motor >36.25 & Motor <47.65.
1003 Motor < 36.25.
11 Amputation, other (AMP-NLE)............ 1101 Motor >36.35.
11 Amputation, other (AMP-NLE)............ 1102 Motor < 36.35.
12 Osteoarthritis (OsteoA)................ 1201 Motor >37.65.
1202 Motor >30.75 & Motor <37.65.
1203 Motor < 30.75.
13 Rheumatoid, other arthritis (RheumA)... 1301 Motor >36.35.
1302 Motor >26.15 & Motor <36.35.
1303 Motor < 26.15.
14 Cardiac (Cardiac)...................... 1401 Motor >48.85.
1402 Motor >38.55 & Motor <48.85.
1403 Motor >31.15 & Motor <38.55.
1404 Motor < 31.15.
15 Pulmonary (Pulmonary).................. 1501 Motor >49.25.
1502 Motor >39.05 & Motor <49.25.
1503 Motor >29.15 & Motor <39.05.
1504 Motor < 29.15.
16 Pain Syndrome (Pain)................... 1601 Motor >37.15.
1602 Motor >26.75 & Motor <37.15.
1603 Motor < 26.75.
17 Major multiple trauma, no brain injury 1701 Motor >39.25.
or spinal cord injury (MMT-NBSCI).
1702 Motor >31.05 & Motor <39.25.
1703 Motor >25.55 & Motor <31.05.
1704 Motor < 25.55.
18 Major multiple trauma, with brain or 1801 Motor >40.85.
spinal cord injury (MMT-BSCI).
1802 Motor >23.05 & Motor <40.85.
1803 Motor < 23.05.
19 Guillian Barre (GB).................... 1901 Motor >35.95.
19 Guillian Barre (GB..................... 1902 Motor >18.05 & Motor <35.95
1903 Motor < 18.05.
20 Miscellaneous (Misc)................... 2001 Motor >49.15.
2002 Motor >38.75 & Motor <49.15.
2003 Motor >27.85 & Motor <38.75.
2004 Motor < 27.85.
21 Burns (Burns).......................... 2101 Motor >0.
Special CMGs.............................. 5001 Short-stay cases, length of stay is 3 days or fewer.
5101 Expired, orthopedic, length of stay is 13 days or fewer.
5102 Expired, orthopedic, length of stay is 14 days or more.
5103 Expired, not orthopedic, length of stay is 15 days or fewer.
5104 Expired, not orthopedic, length of stay is 16 days or more.
--------------------------------------------------------------------------------------------------------------------------------------------------------
Note: CMG definitions use weighted motor scores, as defined below.
2. Use of a Weighted Motor Score Index and Change to the Treatment of
Unobserved Transfer to Toilet Values
In the FY 2006 proposed rule (70 FR 30188, 30210), we proposed to
use a weighted motor score index in assigning patients to CMGs, instead
of the motor score index previously used that treated all components
equally. We also proposed to change how the IRF PPS GROUPER software
would assign a value for the transfer-to-toilet item when it is coded
by the provider with a 0. We proposed that the software would assign
this item a value of 2 instead of a 1 when the activity is coded by the
provider with a 0. However, we proposed not to change the cognitive
score index. As described in detail below, we continue to believe that
a weighted motor score index, with the change to the scoring of the
transfer to toilet item when the provider records a 0 value for the
activity on the IRF-PAI, will improve the classification of patients
into CMGs, which in turn will improve the accuracy of payments to IRFs.
To classify a patient into a CMG, IRFs use the admission assessment
data from the IRF-PAI to score a patient's functional independence
measures. The
[[Page 47897]]
functional independence measures consist of what are termed ``motor''
items and ``cognitive'' items. In addition to the functional
independence measures, the patient's age may also influence the
patient's CMG classification. The motor items are generally indications
of the patient's physical functioning level. The cognitive items are
generally indications of the patient's mental functioning level, and
are related to the patient's ability to process and respond to
empirical factual information, use judgment, and accurately perceive
what is happening. The motor items are eating, grooming, bathing,
dressing upper body, dressing lower body, toileting, bladder
management, bowel management, transfer to bed/chair/wheelchair,
transfer to toilet, transfer to tub or shower, walking or wheelchair
use, and stair climbing. The cognitive items are comprehension,
expression, social interaction, problem solving, and memory. (The CMS
IRF-PAI manual includes more information on these items.) Each item is
generally recorded on the IRF-PAI and scored on a scale of 0 to 7, with
a 7 indicating complete independence in this area of functioning, a 1
indicating that a patient is very impaired in this area of functioning,
and a 0 indicating that the activity did not occur.
As explained in the August 7, 2001 final rule (66 FR 41349), the
instructions for the IRF-PAI required that providers record an 8 for an
item to indicate that the activity did not occur, as opposed to a 1
through 7 indicating that the activity occurred and the estimated level
of function connected with that activity. However, when the IRF-PAI
form was finalized, the code 8 had been removed and was replaced with
the code 0. Therefore, facilities now record a 0 when an activity does
not occur.
To determine the appropriate payment for patients for whom an
activity is coded as 0 (that is, the activity did not occur), we needed
to decide an appropriate way of changing the 0 to another code for
which payment could be assigned. As discussed in the August 7, 2001
final rule (66 FR at 41349), for purposes of classifying patients into
CMGs, we decided to assign a code of 1 (indicating that the patient
needed ``total assistance'') whenever a code of 0 appeared for one of
the items on the IRF-PAI used to determine payment. This was the most
conservative approach we could have taken based on the best available
data at the time because a value of 1 indicates that the patient needed
total assistance performing the task. The result of recoding a 0 as a 1
and using that value to classify a patient into a CMG is that the
provider might receive a higher payment for that item (although it
might not be the highest payment overall, depending on the patient's
other functional abilities and/or comorbidities).
In the FY 2006 proposed rule (70 FR 30188), we proposed to change
the way we treat a code of 0 on the IRF-PAI for the transfer to toilet
item. This is the only item that we proposed to change at this time
because RAND's regression analysis demonstrated that, of all the motor
score values, the evidence supporting a change in the motor score
values was the strongest with respect to this item. We proposed to
assign a code of 2, instead of a code of 1, to patients for whom a 0 is
recorded on the IRF-PAI for the transfer to toilet item (as discussed
below) because RAND's analysis of calendar year 2002 and FY 2003 data
indicates that patients for whom a 0 is recorded are more similar in
terms of their characteristics and costliness to patients with a
recorded score of 2 than to patients with a recorded score of 1. We
proposed to make this change to provide the most accurate payment for
each patient.
Using regression analysis on the calendar year 2002 and FY 2003
data, which is more complete and provides more detailed information on
patients' functional abilities than the FY 1999 data used to construct
the IRF PPS (even though the 1999 data were the best available data at
the time), RAND analyzed whether the assignment of 1 to items for which
a 0 is recorded on the IRF-PAI continues to correctly assign payments
based on patients' expected costliness. RAND examined all of the items
in the motor score index, focusing on how often a code of 0 appears for
the item, how similar patients with a code of 0 are to other patients
with the same characteristics that have a score of 1 though 7, and how
much a change in the item's score affects the prediction of a patient's
expected costliness. Based on RAND's regression analysis, we believed
and continue to believe it is appropriate to change the assignment of 0
on the transfer to toilet item from a 1 to a 2 for the purposes of
determining IRF payments.
Until now, the IRF PPS has used standard motor and cognitive
scores, the sum of either 12 or 13 motor items and the sum of 5
cognitive items, to assign patients to CMGs. This summing equally
weights the components of the indices. These indices have been accepted
and used for many years. Although the weighted motor score is an option
that has been considered before, most experts believed that the data
were not complete and accurate enough before the IRF PPS (although they
were the most complete and accurate data available at the time). Now,
it is believed that the data are complete and accurate enough to
support using a weighted motor score index.
In developing candidate indices that would weight the items in the
score, RAND had the following competing goals: developing indices that
would increase the predictive power of the system while at the same
time maintaining simplicity and transparency in the payment system. For
example, RAND found that an ``optimal'' weighting methodology from the
standpoint of predictive power would require computing 378 different
weights (18 different weights for the motor and cognitive indices that
could all differ across 21 RICs). Rather than introduce this level of
complexity to the system, RAND decided to explore simpler weighting
methodologies that would still increase the predictive power of the
system.
RAND used regression analysis to explore the relationship of the
FIM motor and cognitive scores to cost. The idea of these models was to
determine the impact of each of the FIM items on cost and then weight
each item in the index according to its relative impact on cost. Based
on the regression analysis, RAND was able to design a weighting
methodology for the motor score that could potentially be applied
uniformly across all RICs.
RAND assessed different weighting methodologies for both the motor
score index and the cognitive score index. They discovered that
weighting the motor score index improved the predictive ability of the
system, whereas weighting the cognitive score index did not.
Furthermore, the cognitive score index has never had much of an effect
(in some RICs, it has no effect) on the assignment of patients to CMGs
because the motor score tends to be much stronger at predicting a
patient's expected costs in an IRF than the cognitive score.
For these reasons, we proposed a weighting methodology for the
motor score index. We proposed to continue using the same methodology
we have been using since the IRF PPS was first implemented to compute
the cognitive score index (that is, summing the components of the
index) because, among other things, a change in methodology for
calculating this component of the system failed to improve the accuracy
of the IRF PPS payments. Therefore, it would be futile to expend
resources on changing this
[[Page 47898]]
method when it would not benefit the program.
Table 3 below shows the optimal weights from the regression
analysis for the components of the motor score, averaged across all
RICs and normalized to sum to 100.0, obtained through the regression
analysis. The weights relate to the FIM items' relative ability to
predict treatment costs. Table 3 indicates that dressing lower, toilet,
bathing, and eating are the most effective self-care items for
predicting costs; bowel and bladder control may not be effective at
predicting costs; and that the items grouped in the transfer and
locomotion categories might be somewhat more effective at predicting
costs than the other categories.
We are making no changes to Table 3, which was Table 5 in the FY
2006 proposed rule (70 FR 30188, 30211).
Table 3.-Optimal Weights, Averaged Across Rehabilitation Impairment
Categories (RICs)
[Motor Items]
------------------------------------------------------------------------
Average
Item type Functional independence optimal
item weight
------------------------------------------------------------------------
Self................................ Dressing lower......... 1.4
Self................................ Toilet................. 1.2
Self................................ Bathing................ 0.9
Self................................ Eating................. 0.6
Self................................ Dressing upper......... 0.2
Self................................ Grooming............... 0.2
Sphincter........................... Bladder................ 0.5
Sphincter........................... Bowel.................. 0.2
Transfer............................ Transfer to bed........ 2.2
Transfer............................ Transfer to toilet..... 1.4
Transfer............................ Transfer to tub........ (\1\)
Locomotion.......................... Walking................ 1.6
Locomotion.......................... Stairs................. 1.6
------------------------------------------------------------------------
\1\ Not included.
Based on RAND's analysis, we considered a number of different
candidate indices before we proposed using a weighted index. We
considered defining some simple combinations of the four item types
that make up the motor score index and assigning weights to the groups
of items instead of to the individual items. For example, we considered
summing the three transfer items together to form a group with a weight
of two, since they contributed about twice as much in the cost
regression as the self-care items. We also considered assigning the
self-care items a weight of one and the bladder and bowel items as a
group a weight close to zero, since they contributed little to
predicting cost in the regression analysis. We tried a number of
variations and combinations of this, but RAND's TEP generally rejected
these weighting schemes. They believed that introducing elements of
subjectivity into the development of the weighting scheme may invite
controversy, and that it is better to use an objective algorithm to
derive the appropriate weights. We agree that an objective weighting
scheme is best because it is based on regression analysis of the amount
that various components of the motor score index contribute to
predicting patient costs, using the best available data we have.
Therefore, we proposed to use a weighting scheme that applies the
average optimal weights. To develop the weighting scheme, RAND used
regression analysis to estimate the relative contribution of each item
to the prediction of costs. Based on this analysis, we proposed the
weighting scheme indicated in Table 3 above and in the following simple
equation:
Motor score index = 1.4*dressing lower + 1.2*toilet + 0.9*bathing +
0.6*eating + 0.2*dressing upper + 0.2*grooming + 0.5*bladder +
0.2*bowel + 2.2*transfer to bed + 1.4*transfer to toilet + 1.6*walking
+ 1.6*stairs.
Another reason we proposed to use a weighted motor score index to
assign patients to CMGs is that RAND's regression analysis showed that
it predicts costs better than the current unweighted motor score index.
Across all 21 RICs, the proposed weighted motor score index improves
the explanation of variance within each RIC by 9.5 percent, on average.
Public comments and our responses on the proposal to use a weighted
motor score index and to change the treatment of unobserved transfer to
toilet values are summarized below.
Comment: One commenter suggested that the optimal weights for the
bladder and bowel items may be too low because incontinence is the most
cited reason patients receive inpatient post-acute care.
Response: We believe that the weights for the bladder and bowel
items are appropriate since they were determined based on regression
analysis of the effects of these items on the prediction of IRF costs.
The purpose of the optimal weights for the proposed weighted motor
score index is not to indicate the reasons patients receive inpatient
post-acute care but rather to estimate the influence of various motor
score items on the expected costs of treating patients in the IRF
setting. While we do not disagree that incontinence may be a
significant reason that many patients receive post-acute care in an
inpatient setting, the optimal weights described above were obtained
from RAND's regression analysis of the functional items on patient
costs using FY 2003 data.
Comment: Several commenters were concerned that the proposed
weighted motor score is complex, creates added costs for providers,
will require retraining of staff, is not sensitive to differences among
RICs, and that RAND's technical expert panel did not support the
weighting methodology.
Response: We proposed a weighted motor score index because RAND's
analysis indicates that a weighted motor score index will improve the
classification of patients into CMGs, which in turn will improve the
accuracy of payments to IRFs.
As we stated earlier, in developing candidate indices that would
weight the items in the score, RAND had competing goals: To develop
indices that would increase the predictive power of the system while at
the same
[[Page 47899]]
time maintaining simplicity and transparency in the payment system. For
example, they found that an ``optimal'' weighting methodology from the
standpoint of predictive power would require computing 378 different
weights (18 different weights for the motor and cognitive indices that
could all differ across 21 RICs). Although this would have made the
score more sensitive to differences among RICs, as the commenter
requested, it would have made the score substantially more complex and
less transparent. Thus, we proposed a weighting methodology that
balances these two competing goals.
With regard to the commenter's statement regarding the lack of
support for the weighting methodology, RAND's technical expert panel
generally endorsed the particular weighting methodology we proposed to
implement. Furthermore, in the technical expert panel's discussions,
participants told RAND that the weighting methodology would not be
difficult for providers to implement. They stated that providers
typically have software that computes the motor score, and that
software would only require slight modifications to accommodate the new
weighting methodology. Staff members in IRFs that complete the patient
assessments would continue to input the same information they currently
do into the software and therefore, in general, staff should not need
to be retrained. We are not proposing any changes to how providers code
items on the IRF-PAI, only how the information is used to classify
patients into CMGs for determining the payment rate. We wish to point
out that the weighted motor score for classifying patients into CMGs
will be computed automatically by the GROUPER software, not by a
clinician. CMS will issue the new GROUPER software at no cost to
providers, and the new GROUPER software can be used in the same manner
as the old GROUPER software. Thus, the proposed change to the weighted
motor score index would not be expected to add to providers' costs.
However, CMS will assist providers in any training efforts that may be
required to implement the proposed new weighting methodology.
Comment: Two commenters raised concerns regarding the proposed
change in assignment of the transfer-to-toilet item. They indicated
that this change could artificially elevate the motor score, reduce
payments, and have a negative impact on severely ill patients,
specifically spinal cord injury patients.
Response: We proposed to assign the transfer-to-toilet item on the
IRF-PAI a value of 2, instead of 1, when the provider has recorded a
value of 0 (meaning the activity did not occur) because RAND's
regression analysis of calendar year 2002 and FY 2003 data indicates
that patients for whom a 0 is recorded are more similar in terms of
their characteristics and costliness to patients with a recorded score
of 2 than to patients with a recorded score of 1. We proposed to make
this change in order to provide the most accurate payment for each
patient.
We do not believe this proposed change will have a significant
effect on payment or on access to care for patients for the following
reasons: (1) The transfer-to-toilet item is only 1 of 12 items that
make up the motor score index, (2) we are only proposing to change the
score on this item by 1 point (which results in a 1.4 increase to the
weighted motor score index), and (3) this change will only affect those
patients for whom a 0 is recorded for this item (only about 2.8 percent
of all IRF cases RAND examined).
Furthermore, the payment for a particular patient with a 0 value
for this item would only change if the proposed 1.4 point increase in
the motor score index changes the patient's CMG classification. For
this to happen, the patient's motor score would have to be within 1.4
points of a CMG boundary. In particular, as the commenter noted the
example of spinal cord injury patients, we will use RIC 04 (traumatic
spinal cord injury) as an example. The difference in motor scores
values that would qualify a patient for CMG 0402 versus CMG 0401 is
18.1 points, and the difference in motor scores values that would
qualify a patient for CMG 0403 versus CMG 0402 is 14.3 points. Because
these ranges are relatively large, we believe patients will rarely
change CMGs as a result of a 1.4 point increase in the motor score
index.
We proposed this change in coding of the transfer-to-toilet item
because, based on RAND's analysis, we believe this proposed change will
improve the accuracy of payments in the IRF PPS. As always, we are
concerned that all patients have appropriate access to IRF services.
Accordingly, we will monitor the impact of this proposed change and the
other proposed changes to the IRF classification system finalized in
this final rule to ensure that patients continue to have adequate
access to IRF care.
Comment: One commenter was concerned that the weighted motor score
might disproportionately affect IRF payments for certain types of
patients with certain conditions, such as cognitively impaired patients
with significant lower body impairments or with significant
dysfunctions in upper body and bladder/bowel problems.
Response: We do not believe the weighted motor score methodology
will have a disproportionate affect on any particular groups of
patients. RAND's data analysis and RAND's technical expert panel did
not raise any concerns regarding any particular groups of patients that
would be unduly affected by these changes. We believe that the types of
patients the commenter mentioned were included in the data RAND used to
determine the optimal weights for the weighted motor score and to
calibrate the appropriate payments. The purpose of the proposed
weighted motor score, as with all of the proposed changes discussed in
this final rule, is to align payments more appropriately with the costs
of caring for all types of patients in IRFs. CMS will continue to
closely monitor the data to ensure that no groups of patients are
disproportionately affected by the change to a weighted motor score
index.
Comment: One commenter indicated that CMS, in proposing to
implement the weighted motor score, did not seek enough review from
experts who developed and researched the FIM items.
Response: As discussed in this final rule under section IV, we
contracted with RAND to examine potential refinements to the IRF PPS.
RAND sought advice from a technical expert panel, which reviewed their
methodology and findings regarding the proposed weighted motor score
methodology and generally endorsed the methodology we proposed in the
FY 2006 proposed rule (70 FR 30188). RAND's technical expert panel
included representatives from industry groups, other government
entities, academia, and other researchers, including members with
expertise in the FIM items. Thus, we believe RAND sought sufficient
review from experts in the field in developing the proposed weighted
motor score methodology.
Comment: One commenter requested that CMS remove the transfer to
tub item from the IRF-PAI, to reduce the length of the form, because
the transfer-to-tub item is not used in classifying patients into CMGs
for payment purposes.
Response: We did not propose any changes to the IRF-PAI. However,
we will take this comment into consideration in future reviews of the
IRF-PAI. We would need to more fully consider the benefits and costs of
removing this item from the IRF-PAI form to determine if this change is
appropriate.
[[Page 47900]]
Final Decision: After carefully considering all of the comments we
received on the proposed weighted motor score methodology, we are
finalizing our decision to adopt the methodology as described above.
Specifically, the weighted motor score index will be computed using the
following equation:
Motor score index = 1.4*dressing lower + 1.2*toilet + 0.9*bathing +
0.6*eating + 0.2*dressing upper + 0.2*grooming + 0.5*bladder +
0.2*bowel + 2.2*transfer to bed + 1.4*transfer to toilet + 1.6*walking
+ 1.6*stairs.
In addition, we are finalizing our decision to reassign a value of
2 instead of 1 when providers code a 0 for the transfer-to-toilet item
on a patient's IRF-PAI. Based on RAND's regression analysis of FY 2003
data, the best data available for analysis, we believe these changes
will increase the accuracy of IRF PPS payments.
3. Changes to the Relative Weights
In the FY 2006 proposed rule (70 FR 30188), we proposed to update
the relative weights assigned to each CMG. Section 1886(j)(2)(B) of the
Act requires that an appropriate relative weight be assigned to each
CMG. Relative weights that account for the variance in cost per
discharge and resource utilization among payment groups are a primary
element of a case-mix adjusted prospective payment system. The accuracy
of the relative weights helps to ensure that payments reflect as much
as possible the relative costs of IRF patients and, therefore, that
beneficiaries have access to care and receive the appropriate services.
Section 1886(j)(2)(C)(i) of the Act requires the Secretary from
time to time to adjust the classifications and weighting factors to
reflect changes in treatment patterns, technology, case mix, number of
payment units for which payment to IRFs is made, and other factors
which may affect the relative use of resources. In accordance with this
section of the Act, we proposed to recalculate a relative weight for
each CMG that is proportional to the resources needed by an average
inpatient rehabilitation case in that CMG. For example, cases in a CMG
with a relative weight of 2, on average, would cost twice as much as
cases in a CMG with a relative weight of 1. We did not propose to
change the methodology for calculating the relative weights, as
described in the August 7, 2001 final rule (66 FR 41316, 41351 through
41353) and consequently, we only proposed to update the relative
weights themselves.
As previously stated, we believe that improved coding of data, the
availability of more complete data, and changes to the tier
comorbidities and CMGs helped us decide to propose to update the
relative weights assigned to the CMGs so that they could continue to
accurately represent the differences in costs across CMGs and across
tiers. Therefore, we proposed to recalculate the relative weights.
However, we proposed no change to the methodology for calculating the
relative weights. Instead, we proposed to update the relative weights
(the relative weights that are multiplied by the standard payment
conversion factor to assign relative payments for each CMG and tier)
using the same methodology as described in the August 7, 2001 final
rule (66 FR 41316, 41351 through 41353) and as noted previously in
section V.C.3 of this final rule, using FY 2003 Medicare billing data.
To summarize, we proposed to use the following basic steps to update
the relative weights: The first step in calculating the CMG weights is
to estimate the effects that comorbidities have on costs. The second
step is to adjust the cost of each Medicare discharge (case) to reflect
the effects found in the first step. In the third step, the adjusted
costs from the second step are used to calculate ``relative adjusted
weights'' in each CMG using the hospital-specific relative value
method. The final steps are to calculate the CMG relative weights by
modifying the ``relative adjusted weight'' with the effects of the
existence of the comorbidity tiers (explained below) and normalize the
weights to 1.
We proposed to make the tier and the CMG changes in such a way that
total estimated aggregate payments to IRFs for FY 2006 would be the
same with or without the changes (that is, in a budget neutral manner)
for the following reasons. First, we believe that the results of RAND's
analysis of 2002 and 2003 IRF cost data suggest that additional money
does not need to be added to the IRF PPS. RAND's analysis found, for
example, that if all IRFs had been paid based on 100 percent of the IRF
PPS payment rates throughout all of 2002 (some IRFs were still
transitioning to PPS payments during 2002), PPS payments during 2002
would have been 17 percent higher than IRFs' costs. Furthermore, RAND
did not find evidence that the overall costliness of patients (average
case mix) in IRFs increased substantially in 2002 compared with 1999.
As discussed in detail in section VI.A of this final rule, RAND found
that real case mix increased by at most 1.5 percent, and may have
decreased by as much as 2.4 percent. The available evidence, therefore,
suggests that IRF PPS payments, in aggregate, are likely adequate to
pay for the types of patients IRFs treat.
The purpose of the CMG and tier changes is to ensure that the
existing resources already in the IRF PPS are distributed better among
IRFs according to the relative costliness of the types of patient they
treat. Section 1886(j)(2)(C)(i) of the Act confers broad statutory
authority upon the Secretary to adjust the classification and weighting
factors to account for relative resource use. Consistent with that
broad statutory authority, we proposed to update the relative weights
to more accurately reflect the IRF case mix.
To ensure that total estimated aggregate payments to IRFs do not
change, we proposed to apply a factor to the standard payment amount to
ensure that estimated aggregate payments due to the proposed changes to
the tier comorbidities, the CMGs, the weighted motor score, and the
relative weights for FY 2006 are not greater or less than those that
would have been made in FY 2006 without the proposed changes. In
section VI.B.7 and section VI.B.8 of this final rule, we discuss the
methodology and factor we proposed to apply to the standard payment
amount.
Public comments and our responses on the proposed changes for
updating the relative weights are summarized below.
Comment: Several commenters noted that, in many of the CMGs, the
average length of stay has decreased. One commenter suggested that
there might have been inconsistencies between the relative weights and
the average length of stay values reported in the proposed Table 6 in
the FY 2006 proposed rule (70 FR 30188, 30213 through 30219).
Response: RAND's analysis found that the average length of stay in
IRFs has decreased substantially in recent years. This decrease is
reflected in the average length of stay values for most of the CMGs in
the proposed Table 6 in the FY 2006 proposed rule (70 FR 30188, 30213
through 30219). However, with the exception of determining IRF payments
in certain transfer cases, the average length of stay does not affect
IRF payments. CMS does not require IRFs to treat these average length
of stay values as goals or targets for particular cases. IRFs are
generally free to treat particular patients for as few or as many days
as they deem medically appropriate. We encourage IRFs to admit patients
for the length of time that results in the best quality of care for the
patient. The
[[Page 47901]]
length of stay portion of the proposed Table 6 in the FY 2006 proposed
rule (70 FR 30188, 30213 through 30219) is provided for informational
purposes only.
The relative weights for each of the CMGs and tiers represent the
relative costliness of patients in those CMGs and tiers compared with
patients in other CMGs and tiers. The average length of stay for each
CMG and tier represents the average number of days patients in that CMG
and tier were treated in IRFs, based on the FY 2003 data. IRF PPS
payments are determined on a per-discharge basis, meaning that
providers are paid a pre-determined payment amount according to that
patient's CMG and tier classification, regardless of the number of days
the patient is treated in the IRF. The only exceptions to this general
policy are for very short-stay cases and for certain transfer cases.
Because payments are made on a per-discharge basis, there is not
necessarily any correlation between the number of days a patient is
treated in the IRF and the payment amount for that patient. If, for
example, the relative weight for a particular CMG in tier 1 is higher
than the relative weight for that same CMG in the no-comorbidity tier,
this means that cases in that CMG in tier 1 are expected to be more
costly for the IRF to treat than cases in that CMG in the no-
comorbidity tier. The average length of stay for patients in that CMG
in tier 1, however, could be lower than the average length of stay of
patients in that CMG in the no-comorbidity tier because the treatment
for patients in that CMG in tier 1 could be much more intensive for a
shorter period of time than the treatment for patients in the no-
comorbidity tier, who could require less-intensive treatment over a
longer period of time. Thus, the relative weights may not bear a
relationship to the length of stay, and the two need not be consistent
with each other.
Comment: Several commenters expressed concerns about decreases in
the relative weights for certain CMGs, particularly for the stroke and
traumatic brain injury CMGs. These commenters stated that, if the
relative weights and, consequently, the payment rates for certain CMGs
were to decrease, it could potentially lead to reduced access to IRF
care for patients in the affected CMGs.
Response: The commenters were not clear as to which CMG weights
they were using as a comparison with the proposed FY 2006 relative
weights in Table 6 of the FY 2006 proposed rule (70 FR 30188, 30213
through 30219). We believe that the commenter was comparing the
proposed FY 2006 relative weights published in the FY 2006 proposed
rule (70 FR 30188, 30213 through 30219) to the FY 2005 relative weights
published in the July 30, 2004 notice updating the payment rates (69 FR
45721). Because we proposed revised definitions of the CMGs, as
described in section V.C.1 of this final rule, the proposed new
relative weights for the proposed new CMGs cannot be compared with the
FY 2005 relative weights based on the FY 2005 CMG definitions. The
types of patients included in each CMG, as defined in Table 4 and Table
6 of the FY 2006 proposed rule (70 FR 30188, 30207 through 30210, 30213
through 30219) are likely not the same patients included in the CMGs
under the FY 2005 CMG definitions.
Furthermore, as previously stated, the improved coding of data, the
availability of more complete data, proposed changes to the tier
comorbidities and CMGs, and changes in IRF cost structures contributed
to our decision to propose to update the relative weights assigned to
the CMGs so that the weights continue to represent the differences in
costs across CMGs and across tiers. For these reasons, we have proposed
to recalculate the relative weights to ensure that IRF payments remain
aligned as closely as possible with the costs of care. We will continue
to monitor beneficiaries' access to IRF care to ensure that the changes
to the IRF classification system noted in this final rule do not impede
access to IRF care for Medicare beneficiaries in general or for
beneficiaries with any particular conditions. In particular, we believe
it is important to ensure that stroke patients have appropriate access
to rehabilitation services, as this population benefits considerably
from receiving prompt rehabilitation care.
Nevertheless, we asked RAND to review the average relative weights
for the stroke and traumatic brain injury RICs both under the FY 2005
CMG definitions and under the proposed new CMG definitions. The average
relative weights were essentially identical within these two RICs,
meaning that providers would use essentially the same relative weight
to calculate payments for an ``average'' stroke patient and an
``average'' traumatic brain injury patient in FY 2006 as they used to
calculate payments for the ``average'' stroke patient and the
``average'' traumatic brain injury patient in FY 2005. We believe,
based on RAND's regression analysis of FY 2003 data, that the proposed
changes to the classification system will improve the alignment of IRF
payments with the costs of care and, thereby, improve access to care
for IRF patients.
Comment: One commenter stated that if the proposed recalculation of
the relative weights were to result in lower payments for some patients
and, therefore, were to lead to payments that did not adequately cover
treatment costs for those patients, then patients' access to IRF care
might suffer. A couple of commenters requested that CMS phase in the
proposed changes to the classification system.
Response: We considered proposing a phase in of the proposed
changes to the classification system, but we believe a phase in of the
changes would have introduced undue complication to the classification
system because it would have required individual providers, fiscal
intermediaries, and CMS to compute two different sets of CMGs to
determine payments.
The intent of the proposed changes to the IRF classification
system, including the proposed recalculation of the relative weights,
was to ensure that IRF payments are aligned as closely as possible with
the costs of care. We believe these proposed revisions will help us to
ensure that IRF payments and costs continue to be aligned as
appropriately as possible. We will continue to monitor beneficiaries'
access to IRF care to ensure that the payment system continues to
provide such access to IRF care.
To assist providers in adopting the changes to the classification
system we are finalizing in this final rule, we will make the new
GROUPER and PRICER software available for download on the CMS Web site
as soon as possible and before implementation of the final changes.
Furthermore, our analysis of the impacts, detailed in section XII of
this final rule, indicate that aggregate effects on provider payments
of the proposed changes are expected to be small.
Comment: One commenter noted that the proposed relative weights for
the burn CMG (CMG 2101) for tier 1 and tier 2 are the same. The
commenter asked whether this could be an error.
Response: This was not an error. The FY 2003 data do not contain
enough patients in CMG 2101 in tiers 1 and 2 to estimate precise
relative weights for each tier. Accordingly, RAND combined patients in
these two tiers to estimate the proposed and final relative weights for
both tiers.
Comment: Several commenters requested that CMS make available to
the public the patient-level data on CMG assignments, the IRF-PAI data,
the MedPAR files, and the cost report data RAND used for their analysis
to enable the public to replicate RAND's analysis.
[[Page 47902]]
Response: The data files the commenters requested are generally
available (and were generally available during the comment period for
the FY 2006 proposed rule) through CMS's standard data distribution
systems. Please refer to CMS's Web site at http://www.cms.hhs.gov/researchers/statsdata.asp
for more information about obtaining data
from CMS.
Comment: One commenter asked if CMS could provide the standard
deviation information for the average length of stay information listed
for each CMG and tier.
Response: We will consider posting this type of information on our
Web site.
Comment: One commenter noted the operational challenges, such as
the large number of revisions that need to be made to the GROUPER
software, of implementing the changes to the IRF classification system
that CMS has proposed and further requested that CMS make available the
new CMG GROUPER to the public.
Response: We agree with the commenter that the operational issues
of implementing the proposed changes to the classification system may
be challenging, but we will provide the necessary assistance to ensure
a smooth transition to the new tiers and CMGs, the new weighted motor
score methodology, and the new relative weights. As is our practice, we
will make the new GROUPER and PRICER software available for download on
the CMS Web site as soon as possible and prior to implementation of the
finalized changes. In addition, we will evaluate whether provider,
fiscal intermediary, or regional office training may be required to
promote understanding of any final changes and assist in the
implementation of such changes. Our foremost goal will be to ensure a
smooth implementation of changes because we believe that any final
changes to the classification system will improve the accuracy of
payments in the IRF PPS.
Comment: Several commenters requested that CMS evaluate the effects
of the proposed changes to the IRF classification system after the
changes are implemented and propose additional refinements to the
classification system in future years, if necessary.
Response: We agree with the commenter that it will be important to
evaluate the effects of any changes to the classification system to
ensure that IRF payments continue to be aligned as closely as possible
with the costs of care. CMS intends to monitor the data carefully to
ensure that patients who require inpatient rehabilitation services have
adequate access to these services. We will propose refinements if, in
the future, we later identify the need to make modifications to the
classification system to ensure that IRF payments remain aligned with
the costs of care.
Final Decision: After carefully considering all the comments we
received on the proposed re-calculation of the relative weights, we are
finalizing our proposal to adopt the relative weights presented in
Table 4, without change. However, we note that, after reviewing the
average length of stay values in response to the comments we received,
we have made a slight revision to the methodology for computing the
average length of stay values reported in Table 4 to be consistent with
the way we presented average length of stay values in the August 7,
2001 final rule (66 FR 41316).
Table 4.--Relative Weights for Case-Mix Groups (CMGs)
----------------------------------------------------------------------------------------------------------------
CMG description Relative weights Average length of stay
(M = motor, C = -----------------------------------------------------------------------
CMG cognitive, A =
age) Tier 1 Tier 2 Tier 3 None Tier 1 Tier 2 Tier 3 None
----------------------------------------------------------------------------------------------------------------
0101.................. Stroke M > 51.05 0.7691 0.7299 0.6484 0.6350 8 11 9 9
0102.................. Stroke M > 44.45 0.9471 0.8989 0.7985 0.7820 11 15 11 10
and M < 51.05
and C > 18.5.
0103.................. Stroke M > 44.45 1.1162 1.0594 0.9411 0.9217 14 13 12 12
and M < 51.05
and C < 18.5.
0104.................. Stroke M > 38.85 1.1859 1.1255 0.9999 0.9792 13 14 13 13
and M < 44.45.
0105.................. Stroke M > 34.25 1.4233 1.3509 1.2001 1.1753 16 17 15 15
and M < 38.85.
0106.................. Stroke M > 30.05 1.6567 1.5724 1.3969 1.3680 18 20 18 18
and M < 34.25.
0107.................. Stroke M > 26.15 1.9121 1.8148 1.6122 1.5790 21 23 20 21
and M < 30.05.
0108.................. Stroke M < 26.15 2.2106 2.0981 1.8639 1.8254 27 29 24 24
and A > 84.5.
0109.................. Stroke M > 22.35 2.1976 2.0858 1.8529 1.8147 23 26 24 23
and M < 26.15
and A < 84.5.
0110.................. Stroke M < 22.35 2.6262 2.4926 2.2143 2.1686 30 33 28 28
and A < 84.5.
0201.................. Traumatic brain 0.8140 0.6826 0.6021 0.5648 10 9 9 8
injury M >
53.35 and C >
23.5.
0202.................. Traumatic brain 1.0437 0.8753 0.7720 0.7241 12 10 11 9
injury M >
44.25 and M <
53.35 and C >
23.5.
0203.................. Traumatic brain 1.2487 1.0472 0.9236 0.8664 15 15 12 12
injury M >
44.25 and C <
23.5.
0204.................. Traumatic brain 1.3356 1.1201 0.9879 0.9267 15 16 13 13
injury M >
40.65 and M <
44.25.
0205.................. Traumatic brain 1.6381 1.3738 1.2116 1.1365 17 18 16 15
injury M >
28.75 and M <
40.65.
0206.................. Traumatic brain 2.1379 1.7930 1.5814 1.4833 23 22 21 20
injury M >
22.05 and M <
28.75.
0207.................. Traumatic brain 2.7657 2.3194 2.0457 1.9188 35 29 26 25
injury M <
22.05.
0301.................. Non-traumatic 1.1293 0.9536 0.8440 0.7764 12 12 11 10
brain injury M
> 41.05.
0302.................. Non-traumatic 1.4729 1.2438 1.1008 1.0126 14 16 14 13
brain injury M
> 35.05 and M <
41.05.
0303.................. Non-traumatic 1.7575 1.4841 1.3136 1.2083 20 19 17 16
brain injury M
> 26.15 and M <
35.05.
0304.................. Non-traumatic 2.4221 2.0453 1.8103 1.6651 31 25 23 21
brain injury M
< 26.15.
0401.................. Traumatic spinal 0.9891 0.8517 0.7656 0.6837 12 12 10 10
cord injury M >
48.45.
0402.................. Traumatic spinal 1.3640 1.1746 1.0558 0.9428 19 16 14 12
cord injury M >
30.35 and M <
48.45.
0403.................. Traumatic spinal 2.3743 2.0446 1.8379 1.6412 22 24 23 22
cord injury M >
16.05 and M <
30.35.
0404.................. Traumatic spinal 4.2567 3.6656 3.2950 2.9424 51 46 39 37
cord injury M <
16.05 and A >
63.5.
0405.................. Traumatic spinal 3.2477 2.7967 2.5139 2.2449 32 38 33 28
cord injury M <
16.05 and A <
63.5.
0501.................. Non-traumatic 0.7705 0.6449 0.5641 0.5059 9 8 8 7
spinal cord
injury M >
51.35.
[[Page 47903]]
0502.................. Non-traumatic 1.0316 0.8634 0.7553 0.6774 13 12 10 9
spinal cord
injury M >
40.15 and M <
51.35.
0503.................. Non-traumatic 1.3676 1.1446 1.0013 0.8979 15 15 13 12
spinal cord
injury M >
31.25 and M <
40.15.
0504.................. Non-traumatic 1.7120 1.4328 1.2534 1.1240 20 19 16 15
spinal cord
injury M >
29.25 and M <
31.25.
0505.................. Non-traumatic 2.0289 1.6981 1.4855 1.3321 23 22 19 18
spinal cord
injury M >
23.75 and M <
29.25.
0506.................. Non-traumatic 2.7607 2.3106 2.0212 1.8126 29 28 25 23
spinal cord
injury M <
23.75.
0601.................. Neurological M > 0.8965 0.7331 0.6966 0.6493 11 10 9 9
47.75.
0602.................. Neurological M > 1.1925 0.9752 0.9267 0.8636 13 13 12 12
37.35 and M <
47.75.
0603.................. Neurological M > 1.5266 1.2484 1.1863 1.1056 16 17 15 15
25.85 and M <
37.35.
0604.................. Neurological M < 1.9539 1.5979 1.5183 1.4151 22 20 20 19
25.85.
0701.................. Fracture of 0.9055 0.7736 0.7265 0.6585 12 11 10 9
lower extremity
M > 42.15.
0702.................. Fracture of 1.1757 1.0044 0.9432 0.8549 13 14 13 12
lower extremity
M > 34.15 and M
< 42.15.
0703.................. Fracture of 1.4636 1.2504 1.1742 1.0643 16 17 15 14
lower extremity
M > 28.15 and M
< 34.15.
0704.................. Fracture of 1.7962 1.5345 1.4410 1.3062 20 20 19 18
lower extremity
M < 28.15.
0801.................. Replacement of 0.6561 0.5511 0.5109 0.4596 7 7 7 6
lower extremity
joint M > 49.55.
0802.................. Replacement of 0.8570 0.7198 0.6673 0.6004 10 10 9 8
lower extremity
joint M > 37.05
and M < 49.55.
0803.................. Replacement of 1.2707 1.0672 0.9894 0.8901 15 15 13 12
lower extremity
joint M > 28.65
and M < 37.05
and A > 83.5.
0804.................. Replacement of 1.1069 0.9296 0.8618 0.7754 13 12 11 10
lower extremity
joint M > 28.65
and M < 37.05
and A < 83.5.
0805.................. Replacement of 1.3937 1.1705 1.0852 0.9763 17 16 14 13
lower extremity
joint M > 22.05
and M < 28.65.
0806.................. Replacement of 1.6726 1.4047 1.3023 1.1716 18 19 17 15
lower extremity
joint M < 22.05.
0901.................. Other orthopedic 0.8412 0.7658 0.6805 0.6090 10 11 10 9
M > 44.75.
0902.................. Other orthopedic 1.1054 1.0063 0.8942 0.8002 13 13 12 11
M > 34.35 and M
< 44.75.
0903.................. Other orthopedic 1.4583 1.3276 1.1797 1.0557 18 19 16 15
M > 24.15 and M
< 34.35.
0904.................. Other orthopedic 1.8281 1.6643 1.4788 1.3234 25 23 20 19
M < 24.15.
1001.................. Amputation, 0.9638 0.8888 0.7931 0.7312 11 11 11 10
lower extremity
M > 47.65.
1002.................. Amputation, 1.2709 1.1719 1.0457 0.9641 14 15 14 13
lower extremity
M > 36.25 and M
< 47.65.
1003.................. Amputation, 1.7876 1.6483 1.4709 1.3561 19 22 19 18
lower extremity
M < 36.25.
1101.................. Amputation, non- 1.2544 1.0496 0.9189 0.8462 14 15 12 11
lower extremity
M > 36.35.
1102.................. Amputation, non- 1.8780 1.5713 1.3756 1.2668 19 19 18 17
lower extremity
M < 36.35.
1201.................. Osteoarthritis M 1.0184 0.8794 0.8106 0.7317 11 12 11 10
> 37.65.
1202.................. Osteoarthritis M 1.3181 1.1383 1.0492 0.9470 15 16 14 13
> 30.75 and M <
37.65.
1203.................. Osteoarthritis M 1.6238 1.4022 1.2925 1.1666 21 19 17 16
< 30.75.
1301.................. Rheumatoid, 1.0338 0.9617 0.8325 0.7358 12 13 11 10
other arthritis
M > 36.35.
1302.................. Rheumatoid, 1.4324 1.3325 1.1534 1.0195 15 18 15 14
other arthritis
M > 26.15 and M
< 36.35.
1303.................. Rheumatoid, 1.8308 1.7032 1.4743 1.3032 22 21 20 18
other arthritis
M < 26.15.
1401.................. Cardiac M > 0.8172 0.7352 0.6396 0.5806 10 9 9 8
48.85.
1402.................. Cardiac M > 1.1034 0.9926 0.8636 0.7839 12 13 12 11
38.55 and M <
48.85.
1403.................. Cardiac M > 1.3735 1.2356 1.0750 0.9759 16 16 14 13
31.15 and M <
38.55.
1404.................. Cardiac M < 1.7419 1.5671 1.3633 1.2376 21 20 18 16
31.15.
1501.................. Pulmonary M > 0.9222 0.8995 0.7687 0.7397 11 12 10 10
49.25.
1502.................. Pulmonary M > 1.1659 1.1371 0.9718 0.9352 12 15 12 12
39.05 and M <
49.25.
1503.................. Pulmonary M > 1.4269 1.3917 1.1894 1.1445 12 17 15 15
29.15 and M <
39.05.
1504.................. Pulmonary M < 1.8812 1.8348 1.5681 1.5089 21 22 20 18
29.15.
1601.................. Pain syndrome M 1.0065 0.8544 0.7731 0.6904 12 11 10 9
> 37.15.
1602.................. Pain syndrome M 1.3810 1.1724 1.0607 0.9473 15 17 14 13
> 26.75 and M <
37.15.
1603.................. Pain syndrome M 1.6988 1.4421 1.3048 1.1653 19 19 17 16
< 26.75.
1701.................. Major multiple 1.0102 0.9634 0.8323 0.7321 12 12 11 10
trauma without
brain or spinal
cord injury M >
39.25.
1702.................. Major multiple 1.3305 1.2688 1.0962 0.9643 14 16 15 13
trauma without
brain or spinal
cord injury M >
31.05 and M <
39.25.
1703.................. Major multiple 1.5832 1.5098 1.3043 1.1474 17 20 17 16
trauma without
brain or spinal
cord injury M >
25.55 and M <
31.05.
1704.................. Major multiple 1.9808 1.8889 1.6319 1.4355 26 26 21 20
trauma without
brain or spinal
cord injury M <
25.55.
1801.................. Major multiple 1.2118 0.9832 0.8245 0.7282 15 13 12 10
trauma with
brain or spinal
cord injury M >
40.85.
1802.................. Major multiple 1.9385 1.5728 1.3190 1.1649 20 21 18 16
trauma with
brain or spinal
cord injury M >
23.05 and M <
40.85.
[[Page 47904]]
1803.................. Major multiple 3.4784 2.8222 2.3668 2.0903 43 33 30 27
trauma with
brain or spinal
cord injury M <
23.05.
1901.................. Guillian Barre M 1.2362 1.0981 1.0677 0.9349 14 13 14 12
> 35.95.
1902.................. Guillian Barre M 2.3162 2.0574 2.0004 1.7515 27 25 24 23
> 18.05 and M <
35.95.
1903.................. Guillian Barre M 3.3439 2.9703 2.8881 2.5287 37 39 31 33
< 18.05.
2001.................. Miscellaneous M 0.8743 0.7387 0.6623 0.6047 10 10 9 8
> 49.15.
2002.................. Miscellaneous M 1.1448 0.9672 0.8671 0.7917 12 13 11 11
> 38.75 and M <
49.15.
2003.................. Miscellaneous M 1.4789 1.2495 1.1202 1.0227 16 16 15 14
> 27.85 and M <
38.75.
2004.................. Miscellaneous M 1.9756 1.6692 1.4964 1.3663 25 22 20 18
< 27.85.
2101.................. Burns M > 0..... 2.1858 2.1858 1.5910 1.4762 29 24 19 17
5001.................. Short-stay ....... ....... ....... 0.2201 ....... ....... ....... 2
cases, length
of stay is 3
days or fewer.
5101.................. Expired, ....... ....... ....... 0.6351 ....... ....... ....... 8
orthopedic,
length of stay
is 13 days or
fewer.
5102.................. Expired, ....... ....... ....... 1.6002 ....... ....... ....... 22
orthopedic,
length of stay
is 14 days or
more.
5103.................. Expired, not ....... ....... ....... 0.7204 ....... ....... ....... 8
orthopedic,
length of stay
is 15 days or
fewer.
5104.................. Expired, not ....... ....... ....... 1.8771 ....... ....... ....... 24
orthopedic,
length of stay
is 16 days or
more.
----------------------------------------------------------------------------------------------------------------
Based on RAND's regression analysis of FY 2003 data, the best data
available for analysis, we believe these changes will increase the
accuracy of IRF PPS payments.
VI. FY 2006 Federal Prospective Payment Rates
A. Reduction of the Standard Payment Amount To Account for Coding
Changes
In the FY 2006 proposed rule (70 FR 30188), we proposed to reduce
the standard payment amount by 1.9 percent to account for coding
changes. Section 1886(j)(2)(C)(ii) of the Act requires the Secretary to
adjust the per payment unit payment rate for IRF services to eliminate
the effect of coding or classification changes that do not reflect real
changes in case mix if the Secretary determines that changes in coding
or classification of patients have resulted or will result in changes
in aggregate payments under the classification system. As described
below, in accordance with this section of the Act and based on research
conducted by RAND under contract with us, we proposed to reduce the
standard payment amount for patients treated in IRFs by 1.9 percent.
We proposed to reduce the standard payment amount by 1.9 percent
because RAND's regression analysis of calendar year 2002 data found
that payments to IRFs were about $140 million more than expected during
2002 because of changes in the classification of patients in IRFs, and
that a portion of this increase in payments was due to coding changes
that do not reflect real changes in case mix. If IRF patients have more
costly impairments, lower functional status, or more comorbidities, and
thus require more resources in the IRF in 2002 than in 1999, we would
consider this a real change in case mix. Conversely, if IRF patients
have the same impairments, functional status, and comorbidities in 2002
as they did in 1999 but are coded differently resulting in higher
payment, we consider this a case mix increase due to coding. We believe
that changes in payment amounts should accurately reflect changes in
IRFs' patient case mix (that is, the true cost of treating patients),
and should not be influenced by changes in coding practices.
Under the IRF PPS, payments for each Medicare rehabilitation
patient are determined using a multi-step process. First, a patient is
assigned to a particular CMG and a tier based on as many as four
patient characteristics at admission: impairment, functional
independence, comorbidities, and age. The amount of the payment for
each patient is then calculated by taking the standard payment
conversion factor ($12,958 in FY 2005) and adjusting it by multiplying
by a relative weight, which depends on each patient's CMG and tier
assignment.
For example, an 80-year old hip replacement patient with a motor
score between 47 and 54 and no comorbidities would be assigned to a
particular CMG and tier based on these characteristics. The CMG and
tier to which he is assigned would have an associated relative weight,
in this case 0.5511 in FY 2005 (69 FR at 45725). This relative weight
would be multiplied by the standard payment conversion factor of
$12,958 to equal the payment of $7,141 in FY 2005 (0.5511 x $12,958 =
$7,141). However, based on the following discussion, we are lowering
the standard payment amount by 1.9 percent to account for coding
changes, as opposed to real case mix changes, that have increased
payments to IRFs.
As described in the August 7, 2001 final rule, we contracted with
RAND to analyze IRF data to support our efforts in developing the
classification system and the IRF PPS. We have continued our contract
with RAND to support us in developing potential refinements to the
classification system and the PPS for the FY 2006 proposed rule (70 FR
30188) and this final rule. As part of this research, we asked RAND to
examine changes in case mix and coding since the IRF PPS. To examine
these changes, RAND compared 2002 data from the first year of
implementation of the PPS with the 1999 (pre-PPS) data used to
construct the IRF PPS.
RAND's analysis of the 2002 data, as described in more detail
below, demonstrates that changes in the types of patients going to IRFs
and changes in coding both caused increases in payments to IRFs between
1999 and 2002. The 2002 data are more complete than the 1999 data that
were first used to design the IRF PPS because they include all
Medicare-covered IRF cases. Although the 1999 data we used in designing
the original standard payment rate for the IRF PPS were the best
available data we had at the time, they were based on a sample (64
percent) of IRF cases.
In addition, such review was necessary because, as explained below,
[[Page 47905]]
we believe that the implementation of the IRF PPS caused important
changes in coding. The IRF PPS likely improved the accuracy and
consistency of coding across IRFs, because of the educational programs
that were implemented in 2001 and 2002 and because items that
previously did not affect payments (such as comorbidities) became
important factors for determining the PPS payments. Since these items
now affect payments, there is greater incentive to code for them. In
addition, the IRF PPS changed the instructions for coding some of the
FIM items on the IRF-PAI, so that the same patient may have been
correctly coded differently in 2002 than in 1999.
Although we believe implementation of the IRF PPS resulted in
changes to how the patient assessment data have been coded,
implementation of the IRF PPS may have also caused changes in case mix
because it increased incentives for IRFs to take patients with greater
impairment, lower function, or comorbidities. Under the Tax Equity and
Fiscal Responsibility Act of 1982 (TEFRA) (Pub. L. 97-248), IRFs were
paid on the basis of Medicare reasonable costs limited by a facility-
specific target amount per discharge. IRFs were paid on a per discharge
basis without per discharge adjustments being made for the impairments,
functional status, or comorbidities of patients. Thus, IRFs had a
strong incentive to admit less costly patients to ensure that the costs
of treating patients did not exceed their TEFRA payments. Under the IRF
PPS, however, IRFs' PPS payments are tied directly to the principle
diagnosis and accompanying comorbidities of the patient. Thus, based on
the characteristics of the patients (that is, impairments, functional
status, and comorbidities), the more costly the patient is expected to
be, the higher the PPS payment. Therefore, IRFs may have greater
incentives than they had under TEFRA to admit more costly patients.
Thus, in light of these concerns, RAND performed an analysis using
IRF Medicare claims data matched with FIM and IRF-PAI data. Comparing
2002 data (post-PPS) with 1999 data (pre-PPS), RAND found that the
observed case mix the expected costliness of patients-in IRFs increased
by 3.4 percent between the two time periods. Thus, we paid 3.4 percent,
or about $140 million, more than expected during 2002 because of
changes in the classification of cases in IRFs. However, RAND found
little evidence that the patients admitted to IRFs in 2002 had higher
resource needs (that is, more impairments, lower functioning, or more
comorbidities) than the patients admitted in 1999. In fact, most of the
changes in case mix that RAND documented from the acute care hospital
records implied that IRF patients should have been less costly to treat
in 2002 than in 1999. For example, RAND found a 16 percent decrease in
the proportion of patients treated in IRFs following acute
hospitalizations for stroke, when it compared the results of the 2002
data with the 1999 data. Stroke patients tend to be relatively more
costly than other types of patients for IRFs because they tend to
require more intensive services than other types of patients. A
decrease in the proportion of stroke patients relative to other types
of patients, therefore, would likely contribute to a decrease in the
overall expected costliness of IRF patients. RAND also found a 22
percent increase in the proportion of cases treated in IRFs following a
lower extremity joint replacement. Lower extremity joint replacement
patients tend to be relatively less costly for IRFs than other types of
patients because their care needs tend to be less intensive than other
types of patients. For this reason, the increase in the proportion of
these patients treated in IRFs would suggest a decrease in the overall
expected costliness of IRF patients.
We asked RAND to quantify the amount of the case mix change that
was due to real case mix change (that is, the extent to which IRF
patients had more impairments, lower functioning, or more
comorbidities) and the amount that was due to coding. However, while
the data permit RAND to observe the total change in expected costliness
of patients over time with some precision, estimating the amount of
this total change that is real and the amount that is due to coding
generally cannot be done with the same level of precision. Therefore,
in order to quantify the amounts that were due to real case mix change
and the amounts that were due to coding, RAND used two approaches to
give a range of estimates within which the correct estimates would
logically fall--(1) one that potentially underestimates the amount of
real case mix change and overestimates the amount of case mix change
due to coding; and (2) one that potentially overestimates real change
and underestimates change due to coding. These two approaches give us a
range of estimates, which should logically border the actual amount of
real case mix and coding change. The first approach uses the following
assumptions:
Changes over time in characteristics recorded during the
acute hospitalizations preceding the inpatient rehabilitation facility
stay were real case mix changes (as acute care hospitals had little
incentive to change their coding of patients in response to the IRF
PPS); and
Changes over time in IRF coding that did not correspond
with changes in the characteristics recorded during the acute
hospitalizations were attributable to changes in IRF coding practices.
To illustrate this point, suppose, for example, that the IRF
records showed that there were a greater number of patients with a
pulmonary condition in IRFs in 2002 than in 1999. Patients with a
pulmonary condition tend to be relatively more costly for IRFs to treat
than other types of patients, so an increase in the number of these
patients would indicate an increase in the costliness of IRF patients
(that is, an increase in IRFs' case mix). However, in 2002 IRFs had a
much greater incentive to record if patients had a pulmonary condition
than they did in 1999 because they got paid more for this condition in
2002, whereas they did not in 1999. Therefore, it is reasonable to
expect that some of the increase in the number of patients with a
pulmonary condition was due to the fact that IRFs were recording that
condition for patients more frequently, not that there were really more
patients of that type (although there may also have been some more
patients of that type). To determine the extent to which IRFs may have
just been coding that condition more often versus the extent to which
there actually may have been more patients with a pulmonary condition
going to IRFs than before, RAND looked at the one source of information
that we believe was least likely to be influenced by the incentive to
code patients with this condition more frequently in the IRF: the acute
care hospital record from the stay preceding the IRF stay. We believe
that the acute care hospitals are not likely to be influenced by IRF
PPS policies that only affect IRF payments (that is, changes in IRF
payment policies would not likely result in monetary benefits to the
acute care hospitals). Thus, if RAND found a substantial increase in
the number of IRF patients with a pulmonary condition in the acute care
hospital before going to the IRF, it would be reasonable to assume that
more patients with a pulmonary condition were going to IRFs (a real
increase in case mix). However, if there was little change in the
number of IRF patients with a pulmonary condition in the acute care
hospital before going to the IRF, then we believe it is reasonable to
assume that a portion of the increase in patients with a pulmonary
condition in IRFs was due to the incentives to code more of these
patients in the IRFs.
[[Page 47906]]
We believe that this first approach shows that both factors, real
case mix change and coding change, contributed to the amount of
observed change in 2002, the first IRF PPS rate year. However, these
estimates (based on the best available data) do not fully address all
of the variables that may have contributed to the change in case mix.
For example, the model does not account for the possibility that
patients could develop impairments, functional problems, or
comorbidities after they leave the acute care hospital (prior to the
IRF admission) that would make them more costly when they are in the
IRF. We note that the introduction of a new payment system may have
interrelated effects on providers as they adapt to new (or perceived)
program incentives. Thus, an analysis of first year experience may not
be fully representative of providers' behavior under a fully
implemented system. In addition, hospital coding practices may change
at a different rate in facilities where the IRF is a unit of an acute
care hospital compared with freestanding IRF hospitals. Finally, we
want to ensure that the rate reduction will not have an adverse effect
on beneficiaries' access to IRF care.
For the reasons described above, we believed and continue to
believe that we should provide some flexibility to account for the
possibility that some of the observed changes may be attributable to
other than coding changes. Thus, in determining the amount of the
reduction in the standard payment amount, we examined RAND's second
approach that recognizes the difficulty of precise measurement of real
case mix and coding changes. Using this second approach, RAND developed
an analytical procedure that allowed them to distinguish more fully
between real case mix change and coding change based on patient
characteristics. In part, this second approach involves analyzing some
specific examples of coding that we know have changed over time, such
as direct indications of improvements in impairment coding, changes in
coding instruction for bladder and bowel functioning, and dramatic
increases in coding of certain conditions that affect patients'
placement into tiers (resulting in higher payments).
Using the two approaches, RAND found that real case mix changes in
IRFs over this period ranged from a decrease of 2.4 percent (using the
first approach) to an increase of 1.5 percent (using the second
approach). This suggests that coding changes accounted for between 1.9
percent (if real case mix increased by 1.5 percent (that is, 3.4
percent minus 1.5 percent)) and 5.8 percent (if real case mix decreased
by 2.4 percent (that is, 3.4 percent plus 2.4 percent)) of the increase
in aggregate payments for 2002 compared with 1999. Thus, RAND
recommended decreasing the standard per discharge payment amount by
between 1.9 and 5.8 percent to adjust for the coding changes. We
proposed to reduce the standard payment amount by the lower of these
two numbers, 1.9 percent, because we believe it is a reasonable
estimate for the amount of coding change, based on RAND's analysis of
direct indications of coding change. That is, RAND analyzed specific
examples of coding that we know have changed over time, such as direct
indications of improvements in impairment coding, changes in coding
instructions for bladder and bowel functioning, and dramatic increases
in coding of certain conditions that affect patients' placement into
tiers (resulting in higher payments) in deriving the 1.9 percent
estimate.
We considered proposing a reduction to the standard payment amount
by an amount up to 5.8 percent because RAND's first approach suggested
that coding changes could possibly have been responsible for up to 5.8
percent of the observed increase in IRFs' case mix. Furthermore, a
separate analysis by RAND found that if all IRFs had been paid based on
100 percent of the IRF PPS payment rates throughout all of 2002 (some
IRFs were still transitioning to PPS payments during 2002), PPS
payments during 2002 would have been 17 percent higher than IRFs'
costs. This suggests that we could have proposed a reduction greater
than 1.9 and up to 5.8 percent.
We decided to propose a reduction of 1.9 percent, the lowest
possible amount of change attributable to coding change. The analyses
described here are only the first of an ongoing series of studies to
evaluate the existence and extent of payment increases due to coding
changes. We will continue to review the need for any further reduction
in the standard payment amount in subsequent years as part of our
overall monitoring and evaluation of the IRF PPS.
Therefore, for FY 2006, we proposed to reduce the standard payment
amount by the lowest amount (1.9 percent) attributable to coding
changes. We believe this approach, which is supported by RAND's
analysis of the data, will adequately adjust for the increased payments
to IRFs caused by purely coding changes, but will still provide the
flexibility to account for the possibility that some of the observed
changes in case mix may be attributed to other than coding changes.
Furthermore, we chose to propose a 1.9 percent reduction in the
standard payment amount to recognize that IRFs' current cost structures
may be changing as they strive to comply with other recent Medicare
policy changes, such as the criteria for IRF classification commonly
known as the ``75 percent rule.''
Public comments and our responses on the proposed reduction of the
standard payment amount to account for coding changes are summarized
below.
Comment: Several commenters objected to CMS implementing an across
the board reduction to payment rates to account for coding changes
until the full impact of CMS's recent decision to enforce the 75
percent rule is known. These commenters generally also noted that
RAND's analysis was based on 2002 data, which was the year facilities
were transitioning to the IRF PPS.
Response: We believe a 1.9 percent reduction to the standard
payment amount to account for coding changes is appropriate at this
time for the following reasons. First, CMS is required by statute
(section 1886(j)(2)(C)(ii) of the Act) to adjust payment rates for IRF
services if we find evidence that changes in coding (that do not
reflect real changes in case mix) have resulted or will result in
changes in aggregate payments under the IRF classification system. As
discussed in the proposed rule and above, CMS contracted with RAND to
examine changes in case mix and coding since the IRF PPS, using the
most current available data. Using regression analysis of calendar year
2002 data, RAND found that payments to IRFs were about $140 million
more than expected during 2002 because of changes in the classification
of patients in IRFs, and that a portion of this increase in payments
was due to coding changes that do not reflect real changes in case mix.
Specifically, RAND found that IRF payments were at least 1.9 percent
higher because of changes in coding, based on direct indications of
coding changes. Thus, we believe we have a responsibility to conform to
the requirements of the statute and accordingly adjust payment rates
for IRFs.
Second, analyses by RAND and by CMS's Office of the Actuary have
both shown high Medicare margins among IRFs since implementation of the
IRF PPS. RAND's analysis found that if all IRFs had been paid based on
100 percent of the IRF PPS payment rates throughout all of 2002 (some
IRFs were still transitioning to PPS payments during 2002), PPS
payments during 2002 would have been 17 percent higher than IRFs'
costs. An analysis by CMS's
[[Page 47907]]
Office of the Actuary supports these results. Given the evidence of
high Medicare margins among IRFs, we believe that a 1.9 percent
decrease in rates to account for coding changes will not affect
beneficiary access to IRF services because IRFs will continue to be
paid adequately to reflect the cost of resources needed to treat
Medicare beneficiaries.
Furthermore, we continue to find evidence that enforcement of the
75 percent rule between July 2004 and July 2005 at the 50 percent
compliance threshold did not have as large an impact on patients'
access to IRF care as some industry analysts contend. At this time, CMS
is finding no significant problems regarding access to care in IRFs; to
the contrary, the trend is toward increasing utilization in all
settings. For example, when we compared calendar years 2003 to 2004, we
found that the number of IRF cases increased about 1.2 percent. We do
not believe that beneficiary access to rehabilitation care will be
unduly affected when IRFs have to meet a compliance threshold of 60
percent for cost reporting periods starting between July 1, 2005 and
June 30, 2006. Based on the current available evidence, we do not
believe that simultaneously reducing the standard payment amount by 1.9
percent to adjust for coding changes and phasing in enforcement of the
75 percent rule will have an undue effect on beneficiary access to IRF
services. However, we will closely monitor the available data to ensure
that beneficiaries' access to rehabilitation care is maintained.
Finally, we believe that the fact that 2002 was the year IRFs were
transitioning to the IRF PPS further supports the finding that at least
1.9 percent of the payments in that year were due to coding changes and
not to real changes in case mix. IRFs had not fully transitioned to the
full Federal payment rates in 2002. Therefore, they were likely only
beginning to adjust to the new incentives of the IRF PPS and had only
begun changing their coding practices. Had the full Federal payment
rates for 2002 been fully implemented in 2002, then providers might
have changed their coding practices even more than they did in 2002.
Accordingly, RAND was likely only observing the initial provider
responses to the new IRF PPS. Because RAND's estimate of the 1.9
percent is based on direct indication of coding changes that occurred
in 2002, we believe that the 1.9 percent proposed reduction to the
standard payment amount is appropriate at this time. In the future, we
will examine later years of data in which providers were fully subject
to the IRF PPS and make any necessary adjustments to the standard
payment amount as we are required to do by statute to eliminate the
effect on payments of coding or classification changes that do not
reflect real changes in case mix.
Comment: A few commenters questioned RAND's assumption that
characteristics of the patients recorded during the acute
hospitalizations preceding the IRF stays are relevant for the condition
of those same patients in the IRF stays.
Response: RAND's methodology in which they assumed that patient
characteristics recorded during the acute hospitalizations preceding
the IRF stays were relevant for the case mix of patients in the IRF
stays produced a much higher estimate of the amount of coding change
than we proposed to adopt in the FY 2006 proposed rule (70 FR 30188,
30221 though 30222). This methodology suggested a 5.8 percent reduction
to the standard payment amount to account for coding change, as
discussed above. As explained in the FY 2006 proposed rule (70 FR
30188, 30222), we used the estimate of the amount of coding change from
RAND's second approach, which involved analyzing specific examples of
coding that we know have changed over time, such as direct indications
of improvements in impairment coding, changes in coding instructions
for bladder and bowel functioning, and dramatic increases in coding of
certain conditions that affect patients' placement into tiers
(resulting in higher payments). This second approach produced the 1.9
percent estimate we proposed to use to adjust the standard payment
amount.
Comment: One commenter requested that CMS conduct educational
efforts for providers that instruct providers on how to code patients
appropriately, rather than reducing the standard payment amount by 1.9
percent.
Response: As we discussed earlier in detail in this final rule
under section VI.A, we proposed to reduce the standard payment amount
by 1.9 percent to account for the effects of coding changes that
occurred between 1999 and 2002 that resulted in higher than expected
payments to IRFs, beginning in 2002. Section 1886(j)(2)(C)(ii) of the
Act requires the Secretary to make such an adjustment to eliminate the
effects of coding or classification changes that do not reflect real
changes in case mix if the Secretary determines that changes in coding
or classification of patients have resulted or will result in changes
in aggregate payments under the classification system. RAND's
regression analysis of calendar year 2002 data found that payments to
IRFs were about $140 million more than expected during 2002 because of
changes in the classification of patients in IRFs, and that a portion
of this increase was due to coding changes that do not reflect real
changes in case mix. Any provider education and training that CMS would
conduct now would not revise RAND's finding that, based upon calendar
year 2002 data, coding changes occurred that did not reflect real
changes in case mix.
However, we agree with the commenter that provider education and
training is important so that providers correctly code patients in
IRFs. For this reason, CMS conducted extensive provider training in
2002 when the IRF PPS was first implemented, and we will continue to
educate providers as to how to code the IRF-PAI items through our IRF-
PAI coding help desk. We are open to considering other methods of
provider education to encourage accurate provider coding. The primary
resource providers should refer to is the IRF-PAI manual when they have
questions regarding the correct way to code patients in IRFs. This
manual is available on CMS's Web site at http://www.cms.hhs.gov/providers/IRFPPS/IRFPAI-MANUAL040104.asp
and is updated regularly. The
1.9 percent reduction adjustment to the standard payment amount is not
intended to penalize providers for coding changes, but to reflect the
statutory mandate to adjust IRF PPS payments when the Secretary
determines that changes in coding or classification of patients have
resulted or will result in changes in aggregate payments under the
classification system.
Comment: One commenter questioned whether, in doing the analysis
described above, RAND accounted for the 1.16 percent behavioral offset
adjustment that CMS applied to the initial IRF PPS payment rates in the
August 7, 2001 final rule (66 FR 41316).
Response: As explained in detail in RAND's report entitled
``Preliminary Analyses of Changes in Coding and Case Mix Under the
Inpatient Rehabilitation Facility Prospective Payment System''
(available on RAND's Web site at http://www.rand.org/publications/TR/TR213/
), RAND accounted for the 1.16 percent behavioral offset
adjustment when they estimated the amount of observed case mix change
that was due to real case mix change and the amount that was due to
coding change. The range of estimates for the amount of case mix and
coding change that RAND developed and that is reported above in this
final rule contains an adjustment to
[[Page 47908]]
account for this behavioral offset. If RAND had not taken account of
the behavioral offset, their estimates of the amount of observed case
mix change that was due to coding change would have been larger than
noted in both the FY 2006 proposed rule (70 FR 30188) and in this final
rule.
Comment: One commenter suggested that the proposed 1.9 percent
reduction of the standard payment amount could be implemented without
undue hardship for facilities.
Response: We agree with the commenter. RAND estimates that if all
IRFs had been paid based on 100 percent of the IRF PPS payment rates
throughout all of 2002 (some IRFs were still transitioning to PPS
payments during 2002), PPS payments during 2002 would have been 17
percent higher than IRFs' costs. This suggests that IRF payments are
likely more than adequate to support this type of adjustment for coding
changes.
Final Decision: After carefully considering all the comments we
received on the proposed 1.9 percent reduction to the standard payment
amount to adjust for coding changes between 1999 and 2002 that did not
reflect real changes in case mix and resulted in increases in aggregate
payments under the IRF classification system, we are finalizing our
proposal to adopt the adjustment described above. In accordance with
section 1886(j)(2)(C)(ii) of the Act, and based on RAND's analysis of
2002 data compared with 1999 data, we believe this change is necessary
to allow payment amounts to accurately reflect changes in IRFs' patient
case mix (that is, the true cost of treating patients), and to ensure
that they are not influenced by changes in coding practices.
We are finalizing our methodology for reducing the standard payment
amount by 1.9 percent. First, we update the FY 2005 standard payment
conversion factor by the estimated FY 2006 market basket of 3.6 percent
(estimated for this final rule) to get the standard payment amount for
FY 2006 ($12,958*1.036 = $13,425). Next, we multiply the FY 2006
standard payment amount by 0.981, which reduces the standard payment
amount by 1.9 percent ($13,425*0.981 = $13,169). In section VI.B.7 of
this final rule, we will further adjust the $13,169 by the budget
neutrality factors for the wage index and the other final changes
outlined in this final rule that will result in the FY 2006 standard
payment conversion factor. In section VI.B.7 of this final rule, we
provide a step-by-step calculation that results in the FY 2006 standard
payment conversion factor.
B. Adjustments To Determine the FY 2006 Standard Payment Conversion
Factor
1. Market Basket Used for IRF Market Basket Index
Under the broad authority of section 1886(j)(3)(C) of the Act, the
Secretary establishes an increase factor that reflects changes over
time in the prices of an appropriate mix of goods and services included
in covered IRF services, which is referred to as a market basket index.
The market basket needs to include both operating and capital. Thus,
although the Secretary is required to develop an increase factor under
section 1886(j)(3)(C) of the Act, this provision gives the Secretary
discretion in the design of such factor.
The index currently used to update payments for rehabilitation
facilities is the excluded hospital including capital market basket.
This market basket is based on 1997 Medicare cost report data and
includes Medicare-participating rehabilitation (IRF), LTCH, psychiatric
(IPF), cancer, and children's hospitals.
We are unable to create a separate market basket specifically for
rehabilitation hospitals due to the small number of facilities and the
limited data that are provided (for instance, only about 25 percent of
rehabilitation facility cost reports reported contract labor cost data
for 2002). Since all IRFs are paid under the IRF PPS, nearly all LTCHs
are paid under the LTCH PPS, and IPFs for cost reporting periods
beginning on or after January 1, 2005 will be paid under the IPF PPS,
in the FY 2006 proposed rule (70 FR 30188), we proposed and are
finalizing to update payments for rehabilitation facilities using a
market basket reflecting the operating and capital cost structures for
IRFs, IPFs, and LTCHs, hereafter referred to as the RPL
(rehabilitation, psychiatric, long-term care) market basket. As
proposed and for this final rule, we are excluding children's and
cancer hospitals from the RPL market basket because their payments are
based entirely on reasonable costs subject to rate-of-increase limits
established under the authority of section 1886(b) of the Act, which is
implemented in Sec. 413.40 of the regulations. They are not reimbursed
under a prospective payment system. Also, the FY 2002 cost structures
for children's and cancer hospitals are noticeably different than the
cost structures of the IRFs, IPFs, and LTCHs. The services offered in
IRFs, IPFs, and LTCHs are typically more labor-intensive then those
offered in cancer and children's hospitals. Therefore, the compensation
cost weights for IRFs, IPFs, and LTCHs are larger than those in cancer
and children's hospitals. In addition, the depreciation cost weights
for IRFs, IPFs, and LTCHs are noticeably smaller than those for
children's and cancer hospitals.
In the following discussion, we provide a background on market
baskets and describe the methodologies we proposed and are finalizing
for purposes of determining the operating and capital portions of the
FY 2002-based RPL market basket.
a. Overview of the RPL Market Basket
The RPL market basket is a fixed weight, Laspeyres-type price index
that is constructed in three steps. First, a base period is selected
(in this case, FY 2002), and total base period expenditures are
estimated for a set of mutually exclusive and exhaustive spending
categories based upon type of expenditure. Then the proportion of total
operating costs that each category represents is determined. These
proportions are called cost or expenditure weights. Second, each
expenditure category is matched to an appropriate price or wage
variable, referred to as a price proxy. In nearly every instance, these
price proxies are price levels derived from publicly available
statistical series that are published on a consistent schedule,
preferably at least on a quarterly basis.
Finally, the expenditure weight for each cost category is
multiplied by the level of its respective price proxy for a given
period. The sum of these products (that is, the expenditure weights
multiplied by their price levels) for all cost categories yields the
composite index level of the market basket in a given period. Repeating
this step for other periods produces a series of market basket levels
over time. Dividing an index level for a given period by an index level
for an earlier period produces a rate of growth in the input price
index over that time period.
A market basket is described as a fixed-weight index because it
answers the question of how much it would cost, at another time, to
purchase the same mix of goods and services purchased to provide
hospital services in a base period. The effects on total expenditures
resulting from changes in the quantity or mix of goods and services
(intensity) purchased subsequent to the base period are not measured.
In this manner, the market basket measures only the pure price change.
Only when the index is rebased would the quantity and intensity effects
be captured in the cost weights. Therefore, we rebase the market basket
periodically so the cost weights reflect changes in the mix of
[[Page 47909]]
goods and services that hospitals purchase (hospital inputs) to furnish
patient care between base periods.
The terms rebasing and revising, while often used interchangeably,
actually denote different activities. Rebasing means moving the base
year for the structure of costs of an input price index (for example,
we are shifting the base year cost structure from FY 1997 to FY 2002).
Revising means changing data sources, methodology, or price proxies
used in the input price index. We are rebasing and revising the market
basket used to update the IRF PPS.
b. Methodology for Operating Portion of the RPL Market Basket
As proposed, the operating portion of the FY 2002-based RPL market
basket, which is being adopted in this final rule, consists of several
major cost categories derived from the FY 2002 Medicare cost reports
for IRFs, IPFs, and LTCHs: Wages, drugs, professional liability
insurance and a residual. We choose FY 2002 as the base year because we
believe this is the most recent, relatively complete year of Medicare
cost report data. Due to insufficient Medicare cost report data for
IRFs, IPFs, and LTCHs, cost weights for benefits, contract labor, and
blood and blood products were developed using the FY 2002-based IPPS
market basket (Section IV. Rebasing and Revision of the Hospital Market
Baskets IPPS Hospital Rule for FY 2006), which we explain in more
detail later in this section. For example, less than 30 percent of
IRFs, IPFs, and LTCHs reported benefit cost data in FY 2002. We have
noticed an increase in cost data for these expense categories over the
last 4 years. The next time we propose to rebase the RPL market basket,
there may be sufficient IRFs, IPFs, and LTCHs cost report data to
develop the weights for these expenditure categories.
Since the cost weights for the RPL market basket are based on
facility costs, as proposed and for this final rule, we are limiting
our sample to hospitals with a Medicare average length of stay within a
comparable range of the total facility average length of stay. We
believe this provides a more accurate reflection of the structure of
costs for Medicare treatments. Our goal is to measure cost shares that
are reflective of case mix and practice patterns associated with
providing services to Medicare beneficiaries.
As proposed, for this final rule, we are using those cost reports
for IRFs and LTCHs whose Medicare average length of stay is within 15
percent (that is, 15 percent higher or lower) of the total facility
average length of stay for the hospital. This is the same edit applied
to the FY 1992 and FY 1997 excluded hospital with capital market
baskets. We are using 15 percent because it includes those LTCHs and
IRFs whose Medicare LOS is within approximately 5 days of the facility
length of stay.
As proposed, for this final rule, we use a less stringent measure
of Medicare length of stay for IPFs whose average length of stay is
within 30 or 50 percent (depending on the total facility average length
of stay) of the total facility length of stay. This less stringent edit
allows us to increase our sample size by over 150 reports and produce a
cost weight more consistent with the overall facility. The edit we
applied to IPFs when developing the FY-1997 based excluded hospital
with capital market basket was based on the best available data at the
time.
The detailed cost categories under the residual (that is, the
remaining portion of the market basket after excluding wages and
salaries, drugs, and professional liability cost weights) are derived
from the FY 2002-based IPPS market basket and the 1997 Benchmark Input-
Output Tables published by the Bureau of Economic Analysis, U.S.
Department of Commerce. The FY 2002-based IPPS market basket is
developed using FY 2002 Medicare hospital cost reports with the most
recent and detailed cost data. The 1997 Benchmark I-O is the most
recent, comprehensive source of cost data for all hospitals. Consistent
with the proposed rule, cost weights for benefits, contract labor, and
blood and blood products for this final rule were derived using the FY
2002-based IPPS market basket. For example, the ratio of the benefit
cost weight to the wages and salaries cost weight in the FY 2002-based
IPPS market basket was applied to the RPL wages and salaries cost
weight to derive a benefit cost weight for the RPL market basket. As
proposed and for this final rule, the remaining operating cost
categories were derived using the 1997 Benchmark Input-Output Tables
aged to 2002 using relative price changes. (The methodology we used to
age the data involves applying the annual price changes from the price
proxies to the appropriate cost categories. We repeat this practice for
each year.) Therefore, this methodology results in roughly 59 percent
of the RPL market basket is accounted for by wages, drugs and
professional liability insurance data from FY 2002 Medicare cost report
data for IRFs, LTCHs, and IPFs.
Table 5 below sets forth the complete FY 2002-based RPL market
basket including cost categories, weights, and price proxies. For
comparison purposes, the corresponding FY 1997-based excluded hospital
with capital market basket is listed as well.
As proposed and for this final rule, wages and salaries are 52.895
percent of total costs for the FY 2002-based RPL market basket compared
to 47.335 percent for FY 1997-based excluded hospital with capital
market basket. Employee benefits are 12.982 percent for the FY 2002-
based RPL market basket compared to 10.244 percent for FY 1997-based
excluded hospital with capital market basket. As a result, compensation
costs (wages and salaries plus employee benefits) for the FY 2002-based
RPL market basket are 65.877 percent of costs compared to 57.579
percent for the FY 1997-based excluded hospital with capital market
basket. Of the 8 percentage point difference between the compensation
shares, approximately 3 percentage points are due to the new base year
(FY 2002 instead of FY 1997), 3 percentage points are due to the
revised length of stay edit and the remaining 2 percentage points are
due to the exclusion of other hospitals (that is, only including IRFs,
IPFs, and LTCHs in the market basket).
Following the table is a summary outlining the choice of the
proxies that we proposed and we are finalizing for the operating
portion of the RPL market basket. The price proxies for the capital
portion are described in more detail in the capital methodology
section. (See section III.B.1.c of this rule.)
[[Page 47910]]
Table 5.--FY 2002-Based RPL Market Basket Cost Categories, Weights and Proxies With FY 1997-Based Excluded
Hospital With Capital Market Basket Used for Comparison
----------------------------------------------------------------------------------------------------------------
FY 1997-based
excluded FY 2002-based
Expense categories hospital with RPL market FY 2002 RPL market basket price
capital market basket proxies
basket
----------------------------------------------------------------------------------------------------------------
Total.................................... 100.000 100.000
====================================
Compensation............................. 57.579 65.877
Wages and Salaries *................. 47.335 52.895 ECI--Wages and Salaries, Civilian
Hospital Workers.
Employee Benefits *.................. 10.244 12.982 ECI--Benefits, Civilian Hospital
Workers.
Professional fees Non-Medical *.......... 4.423 2.892 ECI--Compensation for
Professional, Specialty &
Technical Workers.
Utilities................................ 1.180 0.656
Electricity.......................... 0.726 0.351 PPI--Commercial Electric Power.
Fuel Oil, Coal, etc.................. 0.248 0.108 PPI Refined Petroleum Products.
Water and Sewage..................... 0.206 0.197 CPI-U--Water & Sewage
Maintenance.
Professional Liability Insurance......... 0.733 1.161 CMS--Professional Liability
Premium Index.
All Other Products and Services.......... 27.117 19.265
All Other Prod. Products................. 17.914 13.323
Pharmaceuticals...................... 6.318 5.103 PPI Prescription Drugs.
Food: Direct Purchase................ 1.122 0.873 PPI Processed Foods & Feeds.
Food: Contract Service............... 1.043 0.620 CPI-U Food Away From Home.
Chemicals............................ 2.133 1.100 PPI Industrial Chemicals.
Blood and Blood Products **.......... 0.748 ................
Medical Instruments.................. 1.795 1.014 PPI Medical Instruments &
Equipment.
Photographic Supplies................ 0.167 0.096 PPI Photographic Supplies.
Rubber and Plastics.................. 1.366 1.052 PPI Rubber & Plastic Products.
Paper Products....................... 1.110 1.000 PPI Converted Paper & Paperboard
Products.
Apparel.............................. 0.478 0.207 PPI Apparel.
Machinery and Equipment.............. 0.852 0.297 PPI Machinery & Equipment.
Miscellaneous Products............... 0.783 1.963 PPI Finished Goods less Food and
Energy.
All Other Services....................... 9.203 5.942
Telephone............................ 0.348 0.240 CPI-U--Telephone Services.
Postage.............................. 0.702 0.682 CPI-U--Postage.
All Other: Labor Intensive*.......... 4.453 2.219 ECI--Compensation for Private
Service Occupations.
All Other: Non-Labor Intensive....... 3.700 2.800 CPI-U All Items.
Capital-Related Costs.................... 8.968 10.149
Depreciation......................... 5.586 6.186
Fixed Assets......................... 3.503 4.250 Boeckh Institutional
Construction: 23 year useful
life.
Movable Equipment.................... 2.083 1.937 WPI--Machinery & Equipment: 11
year useful life.
Interest Costs....................... 2.682 2.775
Non-profit........................... 2.280 2.081 Average yield on domestic
municipal bonds (Bond Buyer 20
bonds)--vintage weighted (23
years).
For-profit........................... 0.402 0.694 Average yield on Moody's Aaa
bonds--vintage weighted (23
years).
Other Capital-Related Costs.......... 0.699 1.187 CPI-U--Residential Rent.
----------------------------------------------------------------------------------------------------------------
* Labor-related.
** Blood and blood related products is included in miscellaneous products.
Note: Due to rounding, weights may not sum to total.
Below we provide the proxies that we are using for the FY 2002-
based RPL market basket in this final rule. We made no changes to the
proposed price proxies in this final rule. With the exception of the
Professional Liability proxy, all the price proxies for the operating
portion of the RPL market basket are based on Bureau of Labor
Statistics (BLS) data and are grouped into one of the following BLS
categories:
Producer Price Indexes--Producer Price Indexes (PPIs)
measure price changes for goods sold in other than retail markets. PPIs
are preferable price proxies for goods that hospitals purchase as
inputs in producing their outputs because the PPIs would better reflect
the prices faced by hospitals. For example, we use a special PPI for
prescription drugs, rather than the Consumer Price Index (CPI) for
prescription drugs because hospitals generally purchase drugs directly
from the wholesaler. The PPIs that we use measure price change at the
final stage of production.
Consumer Price Indexes--Consumer Price Indexes (CPIs)
measure change in the prices of final goods and services bought by the
typical consumer. Because they may not represent the price faced by a
producer, we used CPIs only if an appropriate PPI was not available, or
if the expenditures were more similar to those of retail consumers in
general rather than purchases at the wholesale level. For example, the
CPI for food purchased away from home is used as a proxy for contracted
food services.
Employment Cost Indexes--Employment Cost Indexes (ECIs)
measure the rate of change in employee wage rates and employer costs
for employee benefits per hour worked. These indexes are fixed-weight
indexes and strictly measure the change in wage
[[Page 47911]]
rates and employee benefits per hour. Appropriately, they are not
affected by shifts in employment mix.
We evaluated the price proxies using the criteria of reliability,
timeliness, availability, and relevance. Reliability indicates that the
index is based on valid statistical methods and has low sampling
variability. Timeliness implies that the proxy is published regularly,
at least once a quarter. Availability means that the proxy is publicly
available. Finally, relevance means that the proxy is applicable and
representative of the cost category weight to which it is applied. The
CPIs, PPIs, and ECIs selected by us to be used in this regulation meet
these criteria.
We note that the proxies are the same as those used for the FY
1997-based excluded hospital with capital market basket. Because these
proxies meet our criteria of reliability, timeliness, availability, and
relevance, we believe they continue to be the best measure of price
changes for the cost categories. For further discussion on the FY 1997-
based excluded hospital with capital market basket, see the IPPS final
rule (67 FR at 50042), published in the Federal Register on August 1,
2002.
Wages and Salaries
For measuring the price growth in the FY 2002-based RPL market
basket, we use the ECI for wages and salaries for civilian hospital
workers as the proxy for wages for measuring the price growth of wages
in the FY 2002-based RPL market basket.
Employee Benefits
The FY 2002-based RPL market basket uses the ECI for employee
benefits for civilian hospital workers.
Nonmedical Professional Fees
The ECI for compensation for professional and technical workers in
private industry is applied to this category since it includes
occupations such as management and consulting, legal, accounting and
engineering services.
Fuel, Oil, and Gasoline
The percentage change in the price of gas fuels as measured by the
PPI (Commodity Code 0552) is applied to this component.
Electricity
The percentage change in the price of commercial electric power as
measured by the PPI (Commodity Code 0542) is applied to this
component.
Water and Sewerage
The percentage change in the price of water and sewage maintenance
as measured by the Consumer Price Index (CPI) for all urban consumers
(CPI Code CUUR0000SEHG01) is applied to this component.
Professional Liability Insurance
The FY 2002-based RPL market basket uses the percentage change in
the hospital professional liability insurance (PLI) premiums as
estimated by the CMS Hospital professional liability index for the
proxy of this category. In the FY 1997-based excluded hospital with
capital market basket, the same price proxy was used.
We continue to research options for improving our proxy for
professional liability insurance. This research includes exploring
various options for expanding our current survey, including the
identification of another entity that would be willing to work with us
to collect more complete and comprehensive data. We are also exploring
other options such as third party or industry data that might assist us
in creating a more precise measure of PLI premiums. At this time we
have not identified a preferred option, therefore, no change is
implemented in the proxy in this final rule.
Pharmaceuticals
The percentage change in the price of prescription drugs as
measured by the PPI (PPI Code PPI32541DRX) is used as a proxy
for this category. This is a special index produced by BLS and is the
same proxy used in the 1997-based excluded hospital with capital market
basket.
Food, Direct Purchases
The percentage change in the price of processed foods and feeds as
measured by the PPI (Commodity Code 02) is applied to this
component.
Food, Contract Services
The percentage change in the price of food purchased away from home
as measured by the CPI for all urban consumers (CPI Code
CUUR0000SEFV) is applied to this component.
Chemicals
The percentage change in the price of industrial chemical products
as measured by the PPI (Commodity Code 061) is applied to this
component. While the chemicals hospital's purchase include industrial
as well as other types of chemicals, the industrial chemicals component
constitutes the largest proportion by far. Thus, we believe that
commodity Code 061 is the appropriate proxy.
Medical Instruments
The percentage change in the price of medical and surgical
instruments as measured by the PPI (Commodity Code 1562) is
applied to this component.
Photographic Supplies
The percentage change in the price of photographic supplies as
measured by the PPI (Commodity Code 1542) is applied to this
component.
Rubber and Plastics
The percentage change in the price of rubber and plastic products
as measured by the PPI (Commodity Code 07) is applied to this
component.
Paper Products
The percentage change in the price of converted paper and
paperboard products as measured by the PPI (Commodity Code
0915) is used.
Apparel
The percentage change in the price of apparel as measured by the
PPI (Commodity Code 381) is applied to this component.
Machinery and Equipment
The percentage change in the price of machinery and equipment as
measured by the PPI (Commodity Code 11) is applied to this
component.
Miscellaneous Products
The percentage change in the price of all finished goods less food
and energy as measured by the PPI (Commodity Code SOP3500) is
applied to this component. Using this index removes the double-counting
of food and energy prices, which are captured elsewhere in the market
basket. The weight for this cost category is higher than in the 1997-
based index because the weight for blood and blood products (1.322) is
added to it. In the 1997-based excluded hospital with capital market
basket we included a separate cost category for blood and blood
products, using the BLS Producer Price Index for blood and derivatives
as a price proxy. A review of recent trends in the PPI for blood and
derivatives suggests that its movements may not be consistent with the
trends in blood costs faced by hospitals. While this proxy did not
match exactly with the product hospitals are buying, its trend over
time appears to be reflective of the historical price changes of blood
purchased by hospitals. However, an apparent divergence in trends in
the PPI for blood and derivatives and trends in blood costs faced by
hospitals over recent years led us to reevaluate whether the PPI for
blood and derivatives was an appropriate measure
[[Page 47912]]
of the changing price of blood. As discussed in the FY 2006 proposed
rule (70 FR 30188), we ran test market baskets classifying blood in 3
separate cost categories: Blood and blood products, contained within
chemicals as was done for the 1992-based excluded hospital with capital
market basket, and within miscellaneous products. These categories use
as proxies the following PPIs: the PPI for blood and blood products,
the PPI for chemicals, and the PPI for finished goods less food and
energy, respectively. Of these three proxies, the PPI for finished
goods less food and energy moved most like the recent blood cost and
price trends. In addition, the impact on the overall market basket by
using different proxies for blood was negligible, mostly due to the
relatively small weight for blood in the market basket.
Therefore, as proposed, for this final rule, we are using the PPI
for finished goods less food and energy for the blood proxy because we
believe it would best be able to proxy only price changes rather than
nonprice factors such as changes in quantities or required tests
associated with blood purchased by hospitals. We will continue to
evaluate this proxy for its appropriateness and will explore the
development of alternative price indexes to proxy the price changes
associated with this cost.
Telephone
The percentage change in the price of telephone services as
measured by the CPI for all urban consumers (CPI Code
CUUR0000SEED) is applied to this component.
Postage
The percentage change in the price of postage as measured by the
CPI for all urban consumers (CPI Code CUUR0000SEEC01) is
applied to this component.
All Other Services, Labor Intensive
The percentage change in the ECI for compensation paid to service
workers employed in private industry is applied to this component.
All Other Services, Nonlabor Intensive
The percentage change in the all-items component of the CPI for all
urban consumers (CPI Code CUUR0000SA0) is applied to this
component.
c. Methodology for Capital Portion of the RPL Market Basket
Unlike for the operating costs of the FY 2002-based RPL market
basket, we did not have IRFs, IPFs, and LTCHs FY 2002 Medicare cost
report data for the capital cost weights, due to a change in the FY
2002 cost reporting requirements. Rather, as was proposed, for this
final rule we are using these hospitals' expenditure data for the
capital cost categories of depreciation, interest, and other capital
expenses for the most recent year available (FY 2001), and aging the
data to a FY 2002 base year using relevant price proxies.
As proposed, for this final rule we calculated weights for the RPL
market basket capital costs using the same set of Medicare cost reports
used to develop the operating share for IRFs, IPFs, and LTCHs. As
proposed, for this final rule the resulting capital weight for the FY
2002 base year is 10.149 percent. This is based on FY 2001 Medicare
cost report data for IRFs, IPFs, and LTCHs, aged to FY 2002 using
relevant price proxies.
Lease expenses are not a separate cost category in the market
basket, but are distributed among the cost categories of depreciation,
interest, and other, reflecting the assumption that the underlying cost
structure of leases is similar to capital costs in general. We assumed
10 percent of lease expenses are overhead and assigned them to the
other capital expenses cost category as overhead. We base this
assignment of 10 percent of lease expenses to overhead on the common
assumption that overhead is 10 percent of costs. The remaining lease
expenses were distributed to the three cost categories based on the
weights of depreciation, interest, and other capital expenses not
including lease expenses.
Depreciation contains two subcategories: Building and fixed
equipment and movable equipment. As proposed, for this final rule the
split between building and fixed equipment and movable equipment was
determined using the FY 2001 Medicare cost reports for IRFs, IPFs, and
LTCHs. This methodology was also used to compute the 1997-based index
(67 FR at 50044).
As proposed, for this final rule total interest expense cost
category is split between the government/nonprofit and for-profit
hospitals. The 1997-based excluded hospital with capital market basket
allocated 85 percent of the total interest cost weight to the
government/nonprofit interest, proxied by average yield on domestic
municipal bonds, and 15 percent to for-profit interest, proxied by
average yield on Moody's Aaa bonds.
As proposed, for this final rule we derived the split using the
relative FY 2001 Medicare cost report data for IPPS hospitals on
interest expenses for the government/nonprofit and for-profit
hospitals. Due to insufficient Medicare cost report data for IRFs, IPFs
and LTCHs, as proposed and for this final rule, we used the same split
used in the IPPS capital input price index, which is 75-25. We believe
it is important that this split reflects the latest relative cost
structure of interest expenses for hospitals. Therefore, as proposed in
the FY 2006 proposed rule (70 FR 30188) we are using a 75-25 split to
allocate interest expenses to government/nonprofit and for-profit. See
the IPPS Rule for FY 2006, Section IV.D, Capital Input Price Index
Section (70 FR 23406).
Since capital is acquired and paid for over time, capital expenses
in any given year are determined by both past and present purchases of
physical and financial capital. The vintage-weighted capital index is
intended to capture the long-term consumption of capital, using vintage
weights for depreciation (physical capital) and interest (financial
capital). These vintage weights reflect the purchase patterns of
building and fixed equipment and movable equipment over time.
Depreciation and interest expenses are determined by the amount of past
and current capital purchases. Therefore, as proposed, for this final
rule we are using the vintage weights to compute vintage-weighted price
changes associated with depreciation and interest expense.
Vintage weights are an integral part of the FY 2002-based RPL
market basket. Capital costs are inherently complicated and are
determined by complex capital purchasing decisions, over time, based on
such factors as interest rates and debt financing. In addition, capital
is depreciated over time instead of being consumed in the same period
it is purchased. The capital portion of the FY 2002-based RPL market
basket reflects the annual price changes associated with capital costs,
and is a useful simplification of the actual capital investment
process. By accounting for the vintage nature of capital, we are able
to provide an accurate, stable annual measure of price changes. Annual
non-vintage price changes for capital are unstable due to the
volatility of interest rate changes and, therefore, do not reflect the
actual annual price changes for Medicare capital-related costs. The
capital component of the FY 2002-based RPL market basket reflects the
underlying stability of the capital acquisition process and provide
hospitals with the ability to plan for changes in capital payments.
To calculate the vintage weights for depreciation and interest
expenses, we need a time series of capital purchases for building and
fixed equipment and movable equipment. We found no single source that
provides the best time series of capital purchases by hospitals for all
[[Page 47913]]
of the above components of capital purchases. The early Medicare Cost
Reports did not have sufficient capital data to meet this need because
these data were not required. While the AHA Panel Survey provided a
consistent database back to 1963, it did not provide annual capital
purchases. The AHA Panel Survey provided a time series of depreciation
expenses through 1997 which could be used to infer capital purchases
over time. From 1998 to 2001, total hospital depreciation expenses were
calculated by multiplying the AHA Annual Survey total hospital expenses
by the ratio of depreciation to total hospital expenses from the
Medicare cost reports. Beginning in 2001, the AHA Annual survey began
collecting depreciation expenses. We hope to be able to use this data
in any future rebasings.
In order to estimate capital purchases from AHA data on
depreciation and interest expenses, the expected life for each cost
category (building and fixed equipment, movable equipment, and debt
instruments) is needed. Due to insufficient Medicare cost report data
for IRFs, IPFs and LTCHs, as proposed, for this final rule, we are
using FY 2001 Medicare cost reports for IPPS hospitals to determine the
expected life of building and fixed equipment and movable equipment. We
believe this data source reflects the latest relative cost structure of
depreciation expenses for hospitals. The expected life of any piece of
equipment can be determined by dividing the value of the asset
(excluding fully depreciated assets) by its current year depreciation
amount. This calculation yields the estimated useful life of an asset
if depreciation were to continue at current year levels, assuming
straight-line depreciation. From the FY 2001 Medicare cost reports for
IPPS hospitals the expected life of building and fixed equipment was
determined to be 23 years, and the expected life of movable equipment
was determined to be 11 years.
Between the publication of the June 24, 2005 proposed rule and this
final rule, we conducted a further review of the methodology used to
derive the useful life of an asset. Based on this brief analysis into
the capital cost structures of hospitals, we are not changing the
expected life of fixed and moveable assets for the final rule.
As proposed, for this final rule, we are using the fixed and
movable weights derived from FY 2001 Medicare cost reports for IRFs,
IPFs and LTCHs to separate the depreciation expenses into annual
amounts of building and fixed equipment depreciation and movable
equipment depreciation. By multiplying the annual depreciation amounts
by the expected life calculations from the FY 2001 Medicare cost
reports, year-end asset costs for building and fixed equipment and
movable equipment could be determined. We then calculated a time series
back to 1963 of annual capital purchases by subtracting the previous
year asset costs from the current year asset costs. From this capital
purchase time series we were able to calculate the vintage weights for
building and fixed equipment, movable equipment, and debt instruments.
Each of these sets of vintage weights are explained in detail below.
As proposed, for this final rule, for building and fixed equipment
vintage weights, the real annual capital purchase amounts for building
and fixed equipment derived from the AHA Panel Survey were used. The
real annual purchase amount was used to capture the actual amount of
the physical acquisition, net of the effect of price inflation. This
real annual purchase amount for building and fixed equipment was
produced by deflating the nominal annual purchase amount by the
building and fixed equipment price proxy, the Boeckh Institutional
Construction Index. This is the same proxy used for the FY 1997-based
excluded hospital with capital market basket. We believe this proxy
continues to meet our criteria of reliability, timeliness,
availability, and relevance. Since building and fixed equipment has an
expected life of 23 years, the vintage weights for building and fixed
equipment are deemed to represent the average purchase pattern of
building and fixed equipment over 23-year periods. With real building
and fixed equipment purchase estimates available back to 1963, sixteen
23-year periods are averaged to determine the average vintage weights
for building and fixed equipment that are representative of average
building and fixed equipment purchase patterns over time. Vintage
weights for each 23-year period are calculated by dividing the real
building and fixed capital purchase amount in any given year by the
total amount of purchases in the 23-year period. This calculation is
done for each year in the 23-year period, and for each of the sixteen
23-year periods. The average of each year across the sixteen 23-year
periods is used to determine the 2002 average building and fixed
equipment vintage weights.
As proposed, for this final rule, for movable equipment vintage
weights, the real annual capital purchase amounts for movable equipment
derived from the AHA Panel Survey were used to capture the actual
amount of the physical acquisition, net of price inflation. This real
annual purchase amount for movable equipment was calculated by
deflating the nominal annual purchase amount by the movable equipment
price proxy, the Producer Price Index for Machinery and Equipment. This
is the same proxy used for the FY 1997-based excluded hospital with
capital market basket. We believe this proxy, which meets our criteria,
is the best measure of price changes for this cost category. Since
movable equipment has an expected life of 11 years, the vintage weights
for movable equipment are deemed to represent the average purchase
pattern of movable equipment over 11-year periods. With real movable
equipment purchase estimates available back to 1963, twenty-eight 11-
year periods are averaged to determine the average vintage weights for
movable equipment that are representative of average movable equipment
purchase patterns over time. Vintage weights for each 11-year period
are calculated by dividing the real movable capital purchase amount for
any given year by the total amount of purchases in the 11-year period.
This calculation is done for each year in the 11-year period, and for
each of the twenty-eight 11-year periods. The average of each year
across the twenty-eight 11-year periods is used to determine the FY
2002 average movable equipment vintage weights.
As proposed, for this final rule, for interest vintage weights, the
nominal annual capital purchase amounts for total equipment (building
and fixed, and movable) derived from the AHA Panel and Annual Surveys
were used. Nominal annual purchase amounts were used to capture the
value of the debt instrument. Since hospital debt instruments have an
expected life of 23 years, the vintage weights for interest are deemed
to represent the average purchase pattern of total equipment over 23-
year periods. With nominal total equipment purchase estimates available
back to 1963, sixteen 23-year periods are averaged to determine the
average vintage weights for interest that are representative of average
capital purchase patterns over time. Vintage weights for each 23-year
period are calculated by dividing the nominal total capital purchase
amount for any given year by the total amount of purchases in the 23-
year period. This calculation is done for each year in the 23-year
period and for each of the sixteen 23-year periods. The average of the
sixteen 23-year periods is used to determine the FY 2002 average
interest vintage weights. The vintage weights for the index are
presented in Table 6 below.
[[Page 47914]]
In addition to the price proxies for depreciation and interest
costs described above in the vintage weighted capital section, as
proposed, for this final rule, we used the CPI-U for Residential Rent
as a price proxy for other capital-related costs. The price proxies for
each of the capital cost categories are the same as those used for the
IPPS final rule (67 FR at 50044) capital input price index.
Table 6.--CMS FY 2002-Based RPL Market Basket Capital Vintage Weights
--------------------------------------------------------------------------------------------------------------------------------------------------------
Fixed assets (23 year Movable assets (11 year Interest: capital-related
Year weights) weights) (23 year weights)
--------------------------------------------------------------------------------------------------------------------------------------------------------
1............................................................. 0.021 0.065 0.010
2............................................................. 0.022 0.071 0.012
3............................................................. 0.025 0.077 0.014
4............................................................. 0.027 0.082 0.016
5............................................................. 0.029 0.086 0.019
6............................................................. 0.031 0.091 0.023
7............................................................. 0.033 0.095 0.026
8............................................................. 0.035 0.100 0.029
9............................................................. 0.038 0.106 0.033
10............................................................ 0.040 0.112 0.036
11............................................................ 0.042 0.117 0.039
12............................................................ 0.045 ............................ 0.043
13............................................................ 0.047 ............................ 0.048
14............................................................ 0.049 ............................ 0.053
15............................................................ 0.051 ............................ 0.056
16............................................................ 0.053 ............................ 0.059
17............................................................ 0.056 ............................ 0.062
18............................................................ 0.057 ............................ 0.064
19............................................................ 0.058 ............................ 0.066
20............................................................ 0.060 ............................ 0.070
21............................................................ 0.060 ............................ 0.071
22............................................................ 0.061 ............................ 0.074
23............................................................ 0.061 ............................ 0.076
-------------------------------
Total..................................................... 1.0000 1.0000 1.0000
--------------------------------------------------------------------------------------------------------------------------------------------------------
The final FY 2006 update for IRF PPS using the FY 2002-based RPL
market basket is 3.6 percent. This is based on Global Insight's 2nd
quarter 2005 forecast, incorporating two more quarters of historical
data than published in the FY 2006 IRF proposed rule. This includes
increases in both the operating section and the capital section. Global
Insight, Inc. is a nationally recognized economic and financial
forecasting firm that contracts with CMS to forecast the components of
the market baskets. Using the current FY 1997-based excluded hospital
with capital market basket (66 FR at 41427), Global Insight's second
quarter 2005 forecast for FY 2006 is also 3.6 percent. Table 7 below
compares the FY 2002-based RPL market basket and the FY 1997-based
excluded hospital with capital market basket percent changes. For both
the historical and forecasted periods between FY 2000 and FY 2008, the
difference between the two market baskets is minor with the exception
of FY 2002 where the FY 2002-based RPL market basket increased three
tenths of a percentage point higher than the FY 1997-based excluded
hospital with capital market basket. This is primarily due to the FY
2002-based RPL market basket having a larger compensation (that is, the
sum of wages and salaries and benefits) cost weight than the FY 1997-
based index and the price changes associated with compensation costs
increasing much faster than the prices of other market basket
components. Also contributing is the all other nonlabor intensive cost
weight, which is smaller in the FY 2002-based RPL market basket than in
the FY 1997-based index, and the slower price changes associated with
these costs.
Table 7.--FY 2002-Based RPL Market Basket and FY 1997-Based Excluded Hospital With Capital Market Basket Percent
Changes, FY 2000-FY 2008
----------------------------------------------------------------------------------------------------------------
FY 1997-based excluded
Fiscal year (FY) Rebased FY 2002-based RPL hospital market basket with
market basket capital
----------------------------------------------------------------------------------------------------------------
Historical data: ............................ ............................
FY 2000......................................... 3.1 3.1
FY 2001......................................... 4.0 4.0
FY 2002......................................... 3.9 3.6
FY 2003......................................... 3.8 3.7
FY 2004......................................... 3.6 3.7
Average FYs 2000-2004........................... 3.7 3.6
Forecast: ............................ ............................
FY 2005......................................... 3.8 3.9
FY 2006......................................... 3.6 3.6
FY 2007......................................... 3.2 3.1
FY 2008......................................... 3.1 2.9
[[Page 47915]]
Average FYs 2005-2008........................... 3.4 3.4
----------------------------------------------------------------------------------------------------------------
Comment: One commenter recommended that the current update be
increased to reflect the differences between the updates given in FY
2004 and FY 2005 and the final market basket increases. Another
commenter recommended that CMS adopt a forecast error adjustment.
Response: There is currently no mechanism for adjusting for
forecast error in the IRF PPS. Also, the FY 2005 updates is not based
on historical data. The forecast error for FY 2005 will not be
available until we publish the 2005q4 forecast (with historical data
through 2005q3) version of the market basket. We have been actively
working with our contractor to minimize forecast error. The specific
details of our analysis are provided in the response to following
comment.
Comment: Several commenters requested that CMS review and revise
the methodology used to forecast the FY 2006 market basket. They are
concerned that the proposed FY 2006 update of 3.1 percent is a dramatic
underestimation. One commenter requested that CMS make the calculation
of the projected FY 2006 available to the public.
Response: Before we published the FY 2006 proposed rule, we had
been actively working with our forecasting firm, Global Insight, Inc.
(GII), to improve the forecasting accuracy of the market baskets. GII
is a nationally recognized economic and financial forecasting firm that
contracts with CMS to forecast the components of the market baskets.
Among other services GII provides to CMS, GII calculates projected
inflation factors for price proxies using models that take into account
sectoral, national, and global economic trends.
Over the last several years, dramatic fluctuations in the price of
certain costs have made it difficult to forecast price proxy inflation.
The driving force behind a significant portion of this uncertainty has
been the instability of energy costs. With our input and consultation,
however, GII recently re-evaluated and modified their forecasting
models to help improve their forecasting accuracy. Using these improved
forecasting models, GII calculated updated inflation factors for the
major cost categories in Table 8.
Table 8.--Comparison of the 4 Quarter Moving Average Percent Changes for Several Cost Category Weights Between
the FY 2006 Proposed and Final Rules
----------------------------------------------------------------------------------------------------------------
GII 2004q4
FY 2002-based forecast of FY GII 2005q2
Expense category cost weights 2006 (Proposed forecast of FY
Rule) 2006 (Final Rule)
----------------------------------------------------------------------------------------------------------------
Total--RPL02........................................... 100.00 3.1 3.6
Compensation........................................... 65.877 3.5 3.9
Utilities.............................................. 0.656 0.8 3.6
Professional Fees...................................... 2.892 3.6 3.8
Professional Liability Insurance....................... 1.161 8.4 5.2
All Other.............................................. 19.265 2.5 3.2
All Other Products..................................... 13.323 2.6 3.5
All Other Services..................................... 5.942 2.4 2.6
Capital................................................ 10.149 0.9 1.1
----------------------------------------------------------------------------------------------------------------
d. Labor-Related Share
Section 1886(j)(6) of the Act specifies that the Secretary shall
adjust the proportion (as estimated by the Secretary from time to time)
of rehabilitation facilities' costs which are attributable to wages and
wage-related costs, of the prospective payment rates computed under
paragraph (3) for area differences in wage levels by a factor
(established by the Secretary) reflecting the relative hospital wage
level in the geographic area of the rehabilitation facility compared to
the national average wage level for such facilities. Not later than
October 1, 2001 (and at least every 36 months thereafter), the
Secretary shall update the factor under the preceding sentence on the
basis of information available to the Secretary (and updated as
appropriate) of the wages and wage-related costs incurred in furnishing
rehabilitation services. Any adjustments or updates made under this
paragraph for a fiscal year shall be made in a manner that assures that
the aggregated payments under this subsection in the fiscal year shall
be made in a manner that assures that the aggregated payments under
this subsection in the fiscal year are not greater or less than those
that would have been made in the year without such adjustment.
The labor-related share is determined by identifying the national
average proportion of operating costs that are related to, influenced
by, or vary with the local labor market. Using our current definition
of labor-related, the labor-related share is the sum of the relative
importance of wages and salaries, fringe benefits, professional fees,
labor-intensive services, and a portion of the capital share from an
appropriate market basket. As proposed, for this final rule, we are
using the FY 2002-based RPL market basket costs to determine the labor-
related share for the IRF PPS. The labor-related share for FY 2006 is
the sum of the FY 2006 relative importance of each labor-related cost
category, and reflects the different rates of price change for these
cost categories between the base year (FY 2002) and FY 2006. For this
final rule, we are revising the labor-related share to reflect Global
Insight's second quarter 2005 forecast, incorporating two more quarters
of
[[Page 47916]]
historical data than published in the FY 2006 IRF proposed rule. Thus,
for this final rule, the sum of the relative importance for FY 2006 for
operating costs (wages and salaries, employee benefits, professional
fees, and labor-intensive services) is 71.708 percent, as shown in the
chart below. The portion of capital that is influenced by local labor
markets is estimated to be 46 percent, which is the same percentage
currently used in the IRF prospective payment system. Since the
relative importance for capital is 9.037 percent of the FY 2002-based
RPL market basket in FY 2006, we took 46 percent of 9.037 percent to
determine the capital labor-related share for FY 2006. The result is
4.157 percent, which we add to 71.708 percent for the operating cost
amount to determine the total labor-related share for FY 2006. Thus,
the labor-related share that we are using for IRF PPS in FY 2006 is
75.865 percent. This labor-related share is determined using the same
methodology as employed in calculating all previous IRF labor-related
shares (66 FR at 41357).
Table 9 below shows the final FY 2006 relative importance labor-
related share using the 2002-based RPL market basket and the labor-
related share using the FY 1997-based excluded hospital with capital
market.
Table 9.--Total Labor-Related Share
----------------------------------------------------------------------------------------------------------------
FY 1997 excluded
FY 2002-based RPL hospital with capital
Cost category market basket relative market basket relative
importance (percent) FY importance (percent) FY
2006 2006
----------------------------------------------------------------------------------------------------------------
Wages and salaries............................................ 52.592 48.185
Employee benefits............................................. 14.028 11.542
Professional fees............................................. 2.921 4.558
All other labor intensive services............................ 2.167 4.450
Subtotal.................................................. 71.708 68.735
==========================
Labor-related share of capital costs.......................... 4.157 3.289
--------------------------
Total..................................................... 75.865 72.024
----------------------------------------------------------------------------------------------------------------
Public comments that we received are summarized below.
Comment: Several commenters objected to our proposal to change the
labor-related share to 75.958 percent. One commenter suggested CMS
maintain the FY 2005 labor-related share of 72.359 percent until CMS
can develop an IRF-specific wage index. Another commenter stated there
is no precedent to change the labor-related share. Another commenter
requested that if CMS implemented a change in the LRS, they request a
transition where the transitional labor-related share would be composed
of 80 percent of the current labor-related share and 20 percent of the
proposed labor-related share.
Response: Identical to previous updates, the labor-related share is
calculated as the sum of the relative importance of those costs that
are related to, influenced by, or vary with the local labor market.
Specifically, the FY 2006 labor related share is equal to the relative
importance of wages and salaries, fringe benefits, professional fees,
labor-intensive services, and a portion of the capital share from the
RPL market basket.
We calculate the labor-related relative importance for FY 2006 in
four steps. First, we compute the FY 2006 price index level for the
total market basket and each cost category of the market basket.
Second, we calculate a ratio for each cost category by dividing the FY
2006 price index level for that cost category by the total market
basket price index level. Third, we determine the FY 2006 relative
importance for each cost category by multiplying this ratio by the base
year (FY 2002) weight. Finally, we sum the FY 2006 relative importance
for each of the labor-related cost categories (wages and salaries,
employee benefits, nonmedical professional fees, labor-intensive
services, and capital-related expenses) to produce the FY 2006 labor-
related relative importance.
The price proxies that move the different cost categories in the
market basket do not necessarily change at the same rate, and the
relative importance captures these changes. Accordingly, the relative
importance figure more closely reflects the cost share weights for FY
2006 when compared to the base year weights from the RPL market basket.
Thus, the LRS has been and should be revised with each fiscal year
update.
CMS disagrees with the commenter's suggestion to transition from
the FY 2005 to the FY 2006 labor-related share. We note the FY 2006
labor-related share is based on the same methodology used to calculate
the FY 2005 labor-related share (that is, it is composed of the costs
that are related to, influenced by, or vary with the local labor
market). Furthermore, the FY 2006 labor-related share is based on the
2002-based RPL market basket, which we believe adequately reflects the
current cost structures of Medicare-participating IRFs. Therefore, we
do not believe a transition is necessary.
Comment: Several commenters suggested that we include professional
liability insurance (PLI) in the labor-related share since these costs
are included in the wage index. The commenters also claim that
professional liability insurance costs are wage-related.
Response: The wage index includes, as a fringe benefit cost, PLI
for those policies that list actual names or specific titles of covered
employees (59 FR 45358). The benefit cost weight in the market basket,
included in the labor-related share, is also based on the same wage
index benefit data. Therefore, the labor-related share includes these
PLI costs. General PLI coverage maintained by hospitals is not
recognized as a wage-related cost for purposes of the wage index or
labor-related share.
Although general PLI costs do vary by geographic region, this
variance is primarily influenced by state legislation and risk level,
not by local wage rates. In fact, areas with high wage indices may have
low relative PLI costs. For example, the malpractice geographic price
indices, used in the Medicare physician payment system, for San
Francisco, Los Angeles, and Boston regions are below 1, while their
hospital wage indices for comparable areas are much greater than 1.
Comment: Several commenters recommended CMS delay the
implementation of the RPL market
[[Page 47917]]
basket until CMS has reviewed the accuracy of the cost report data.
Specifically, they requested CMS investigate HealthSouth's claim to
have omitted home office and some depreciation costs from their 2002
and 2003 Medicare cost reports.
Response: The FY 2006 market basket update is based on the RPL
market basket using FY 2002 Medicare cost report data. CMS has
determined that, in the absence of FY 2002 HealthSouth home office cost
report data, we will not incorporate preliminary FY 2004 HealthSouth
home office costs into the 2002-based RPL market basket. (Due to a
change in Medicare cost report requirements beginning with FY 2002, we
used FY 2001 capital costs aged to FY 2002 in the 2002-based RPL market
basket. Therefore, HealthSouth's depreciation costs were included in
the RPL market basket and reflected in the FY 2006 market basket
update.)
Home office costs represent only one of many cost categories
(including but not limited to salaries, benefits, professional
liability insurance, and pharmaceuticals) that are used to develop the
cost category weights. We believe the absence of HealthSouth home
office costs in this market basket has a minor impact on the
distribution of these weights and, by extension, the final market
basket update itself. When CMS receives full FY 2004 Medicare cost
report data from HealthSouth, we plan to re-evaluate this decision.
Final Decision: We are finalizing our decision to update payments
for rehabilitation facilities using the RPL market basket reflecting
the operating and capital cost structures for IRFs, IPFs, and LTCHs.
2. Area Wage Adjustment
Section 1886(j)(6) of the Act requires the Secretary to adjust the
proportion (as estimated by the Secretary from time to time) of
rehabilitation facilities' costs that are attributable to wages and
wage-related costs by a factor (established by the Secretary)
reflecting the relative hospital wage level in the geographic area of
the rehabilitation facility compared to the national average wage level
for those facilities. Not later than October 1, 2001 and at least every
36 months thereafter, the Secretary is required to update the factor
under the preceding sentence on the basis of information available to
the Secretary (and updated as appropriate) of the wages and wage-
related costs incurred in furnishing rehabilitation services. Any
adjustments or updates made under section 1886(j)(6) of the Act for a
FY shall be made in a manner that assures the aggregated payments under
section 1886(j)(6) of the Act are not greater or less than those that
will have been made in the year without such adjustment.
In our August 1, 2003 final rule (68 FR 45674), we acknowledged
that on June 6, 2003, the Office of Management and Budget (OMB) issued
``OMB Bulletin No. 03-04,'' announcing revised definitions of
Metropolitan Statistical Areas, and new definitions of Micropolitan
Statistical Areas and Combined Statistical Areas. A copy of the
Bulletin may be obtained at the following Internet address: http://www.whitehouse.gov/omb/bulletins/b03-04.html.
At that time, we did not
propose to apply these new definitions known as the Core-Based
Statistical Areas (CBSAs). After further analysis and discussed in
detail in section VI.B.2.d, we proposed to revised labor market area
definitions as a result of the OMB revised definitions to adjust the FY
2006 IRF PPS payment rate. In addition, the IPPS is applying these
revised definitions as discussed in the August 11, 2004 final rule (69
FR at 49207). We will adopt the CBSA-based geographic classifications
as proposed in the FY 2006 IRF PPS proposed rule (70 FR 30188) and
described below in section VI.B.2.d and section VI.B.2.e.
a. Revisions to the IRF PPS Geographic Classification
As discussed in the August 7, 2001 final rule, which implemented
the IRF PPS (66 FR at 41316), in establishing an adjustment for area
wage levels under Sec. 412.624(e)(1), the labor-related portion of an
IRF's Federal prospective payment is adjusted by using an appropriate
wage index. As set forth in Sec. 412.624(e)(1), an IRF's wage index is
determined based on the location of the IRF in an urban or rural area
as defined in Sec. 412.602 and further defined in Sec.
412.62(f)(1)(ii) and Sec. 412.62(f)(1)(iii) as urban and rural areas,
respectively. An urban area, under the IRF PPS, is defined in Sec.
412.62(f)(1)(ii) as a Metropolitan Statistical Area (MSA) or New
England County Metropolitan Area (NECMA) as defined by the Office of
Management and Budget (OMB). Under Sec. 412.62(f)(1)(iii), a rural
area is defined as any area outside of an urban area. In general, an
urban area is defined as a Metropolitan Statistical Area (MSA) or New
England County Metropolitan Area (NECMA) as defined by the Office of
Management and Budget. Under Sec. 412.62(f)(1)(iii), a rural area is
defined as any area outside of an urban area. The urban and rural area
geographic classifications defined in Sec. 412.62(f)(1)(ii) and
(f)(1)(iii), respectively, were used under the IPPS from FYs 1985
through 2004 (as specified in Sec. 412.63(b)), and have been used
under the IRF PPS since it was implemented for cost reporting periods
beginning on or after January 1, 2002.
The wage index used for the IRF PPS is calculated by using the
acute care IPPS wage index data on the basis of the labor market area
in which the acute care hospital is located, but without taking into
account geographic reclassification under sections 1886(d)(8) and
(d)(10) of the Act commonly referred to as ``pre-reclassification''. In
addition, Section 4410 of Pub. L. 105-33 (BBA) provides that for the
purposes of section 1886(d)(3)(E) of the Act, that the area wage index
applicable to hospitals located in an urban area of a State may not be
less than the area wage index applicable to hospitals located in rural
areas in the State. Consistent with past IRF policy, we treat this
provision, commonly referred to as the ``rural floor'', as applicable
to the acute inpatient hospitals and not IRFs. Therefore, the hospital
wage index used for IRFs is commonly referred to as ``pre-floor''
indicating that the ``rural floor'' provision is not applied. As a
result, the applicable IRF wage index value is assigned to the IRF on
the basis of the labor market area in which the IRF is geographically
located.
In the FY 2006 IRF PPS proposed rule (70 FR 30188, 30235), we
described the labor markets that have been used for area wage
adjustments under the IRF PPS since its implementation of cost
reporting periods beginning on or after January 1, 2002. Previously, we
have not described the labor market areas used under the IRF PPS in
detail. However, we published each area's wage index in the IRF PPS
final rules and update notices, each year and noted the use of the
geographic area in applying the wage index adjustment in the IRF PPS
payment examples in the final regulation implementing the IRF PPS (69
FR 41316, 41367 through 41368). The IRF industry has also understood
that the same labor market areas in use under the IPPS (from the time
the IRF PPS was implemented, for cost reporting periods beginning on or
after January 1, 2002) are used under the IRF PPS. The OMB adopted new
statistical area definitions (70 FR 30188, 30235-30238) and we proposed
to adopt the new labor market area definitions based on these areas
under the IRF PPS. Therefore, we are providing a more detailed
description of the current IRF PPS labor market areas in this final
rule, in order for the public to better understand the change to the
IRF PPS labor market areas.
[[Page 47918]]
The current IRF PPS labor market areas are defined based on the
definitions of MSAs, Primary MSAs (PMSAs), and NECMAs issued by the OMB
(commonly referred to collectively as ``MSAs''). These MSA definitions
are used before October 1, 2005, under the IRF PPS and other
prospective payment systems, such as LTCH, IPF, Home Health Agency
(HHA), and SNF (Skilled Nursing Facility) PPSs. In the IPPS final rule
(67 FR at 49026 through 49034), revised labor market area definitions
were adopted under the hospital IPPS (Sec. 412.64(b)), which are
effective October 1, 2004 for acute care hospitals. These new CBSA
standards were announced by the OMB late in 2000.
b. Current IRF PPS Labor Market Areas Based on MSAs
As mentioned earlier, since the implementation of the IRF PPS in
the August 7, 2001 IRF PPS final rule, we used labor market areas to
further characterize urban and rural areas as determined under Sec.
412.602 and further defined in Sec. 412.62(f)(1)(ii) and (f)(1)(iii)
for discharges before October 1, 2005. We defined labor market areas
under the IRF PPS based on the definitions of MSAs, PMSAs, and NECMAs
issued by the OMB, which is consistent with the IPPS approach. The OMB
also designates Consolidated MSAs (CMSAs). A CMSA is a metropolitan
area with a population of 1 million or more, comprising two or more
PMSAs (identified by their separate economic and social character). For
purposes of the wage index, we use the PMSAs rather than CMSAs because
they allow a more precise breakdown of labor costs (as described in
section VI.B.2.d.ii of this final rule). If a metropolitan area is not
designated as part of a PMSA, we use the applicable MSA.
These different designations use counties as the building blocks
upon which they are based. Therefore, IRFs are assigned to either an
MSA, PMSA, or NECMA based on whether the county in which the IRF is
located is part of that area. All of the counties in a State outside a
designated MSA, PMSA, or NECMA are designated as rural. For the
purposes of calculating the wage index, we combine all of the counties
in a State outside a designated MSA, PMSA, or NECMA together to
calculate the statewide rural wage index for each State.
c. Core-Based Statistical Areas (CBSAs)
OMB reviews its Metropolitan Area definitions preceding each
decennial census. As discussed in the IPPS final rule (69 FR at 49027),
in the fall of 1998, OMB chartered the Metropolitan Area Standards
Review Committee to examine the Metropolitan Area standards and develop
recommendations for possible changes to those standards. Three notices
related to the review of the standards, providing an opportunity for
public comment on the recommendations of the Committee, were published
in the Federal Register on the following dates: December 21, 1998 (63
FR at 70526); October 20, 1999 (64 FR at 56628); and August 22, 2000
(65 FR at 51060).
In the December 27, 2000 Federal Register (65 FR at 82228 through
82238), OMB announced its new standards. In that notice, OMB defines
CBSA, beginning in 2003, as ``a geographic entity associated with at
least one core of 10,000 or more population, plus adjacent territory
that has a high degree of social and economic integration with the core
as measured by commuting ties.'' The standards designate and define two
categories of CBSAs: MSAs and Micropolitan Statistical Areas (65 FR at
82235 through 82238).
According to OMB, MSAs are based on urbanized areas of 50,000 or
more population, and Micropolitan Statistical Areas (referred to in
this discussion as Micropolitan Areas) are based on urban clusters of
at least 10,000 population, but less than 50,000 population. Counties
that do not fall within CBSAs (either MSAs or Micropolitan Areas) are
deemed ``Outside CBSAs.'' In the past, OMB defined MSAs around areas
with a minimum core population of 50,000, and smaller areas were
``Outside MSAs.'' On June 6, 2003, OMB announced the new CBSAs,
comprised of MSAs and the new Micropolitan Areas based on Census 2000
data. (A copy of the announcement may be obtained at the following
Internet address: http://www.whitehouse.gov/omb/bulletins/fy04/b04-03.html.
)
The new CBSA designations recognize 49 new MSAs and 565 new
Micropolitan Areas, and revise the composition of many of the existing
MSAs. There are 1,090 counties in MSAs under the new CBSA designations
(previously, there were 848 counties in MSAs). Of these 1,090 counties,
737 are in the same MSA as they were prior to the change in
designations, 65 are in a different MSA, and 288 were not previously
designated to any MSA. There are 674 counties in Micropolitan Areas. Of
these, 41 were previously in an MSA, while 633 were not previously
designated to an MSA. There are five counties that previously were
designated to an MSA but are no longer designated to either an MSA or a
new Micropolitan Area: Carter County, KY; St. James Parish, LA; Kane
County, UT; Culpepper County, VA; and King George County, VA. For a
more detailed discussion of the conceptual basis of the new CBSAs,
refer to the IPPS final rule (67 FR at 49026 through 49034).
d. Revisions to the IRF PPS Labor Market Areas
In its June 6, 2003 announcement, OMB cautioned that these new
definitions ``should not be used to develop and implement Federal,
State, and local non-statistical programs and policies without full
consideration of the effects of using these definitions for such
purposes. These areas should not serve as a general-purpose geographic
framework for non-statistical activities, and they may or may not be
suitable for use in program funding formulas.''
We currently use MSAs to define labor market areas for purposes of
the wage index. In fact, MSAs are also used to define labor market
areas for purposes of the wage index for many of the other Medicare
prospective payment systems (for example, LTCH, SNF, HHA, IPF, and
Outpatient). While we recognize MSAs are not designed specifically to
define labor market areas, we believe they represent a reasonable and
appropriate proxy for this purpose, because they are based upon
characteristics we believe also generally reflect the characteristics
of unified labor market areas. For example, CBSAs reflect a core
population plus an adjacent territory that reflects a high degree of
social and economic integration. This integration is measured by
commuting ties, thus demonstrating that these areas may draw workers
from the same general areas. In addition, the most recent CBSAs reflect
the most up-to-date information. The OMB reviews its Metropolitan Area
(MA) definitions preceding each decennial census to reflect recent
population changes and the CBSAs are based on the Census 2000 data.
Thus, we proposed to adopt the new CBSA designations to define labor
market areas for the purposes of the IRF PPS.
Historically, Medicare PPSs have utilized MA definitions developed
by OMB. The labor market areas currently used under the IRF PPS are
based on the MA definitions issued by OMB. OMB reviews its MA
definitions preceding each decennial census to reflect more recent
population changes. Thus, the CBSAs are OMB's latest MA definitions
based on the Census 2000 data. Because we believe that the OMB's latest
MA designations more accurately reflect the local economies and wage
levels of the areas in which hospitals are currently located, we
proposed to adopt the
[[Page 47919]]
revised labor market area designations based on the OMB's CBSA
designations.
As specified in Sec. 412.624(e)(1), we explained in the August 7,
2001 final rule that the IRF PPS wage index adjustment was intended to
reflect the relative hospital wage levels in the geographic area of the
hospital as compared to the national average hospital wage level. Since
OMB's CBSA designations are based on Census 2000 data and reflect the
most recent available geographic classifications, we will adopt the
labor market area definitions used under the IRF PPS as proposed in the
FY 2006 IRF PPS proposed rule (70 FR 30188). Specifically, we will
revise the IRF PPS labor market definitions based on the OMB's new CBSA
designations effective for IRF PPS discharges occurring on or after
October 1, 2005. Accordingly, we will revise Sec. 412.602 to specify
that for discharges occurring on or after October 1, 2005, the
application of the wage index under the IRF PPS will be made on the
basis of the location of the facility in an urban or rural area as
defined in Sec. 412.64(b)(1)(ii)(A) through (C) as proposed in the FY
2006 IRF PPS proposed rule (70 FR 30188).
As a conforming change, we will revise Sec. 412.602, definitions
for rural and urban areas effective for discharges occurring on or
after October 1, 2005 will be defined in Sec. 412.64(b)(1)(ii)(A)
through (C) as proposed in the FY 2006 IRF PPS proposed rule (70 FR
30188) and adopted in this final rule. In addition (as proposed in the
FY 2006 IRF PPS proposed rule at 70 FR 30188), we will revise the
regulation text to explicitly reference urban and rural definitions for
a cost-reporting period beginning on or after January 1, 2002, with
respect to discharges occurring during the period covered by such cost
reports but before October 1, 2005 under Sec. 412.62(f)(1)(ii) and
Sec. 412.62(f)(1)(iii).
We note that these are the same labor market area definitions
(based on the OMB's new CBSA-based designations) implemented under the
IPPS at Sec. 412.64(b), which are effective for those hospitals
beginning October 1, 2004 as discussed in the IPPS final rule (69 FR at
49026 through 49034). The similarity between the IPPS and the IRF PPS
includes the adoption in the initial implementation of the IRF PPS of
the same labor market area definitions under the IRF PPS that existed
under the IPPS at that time, as well as the use of acute care
hospitals' pre-reclassification and pre-floor wage data in calculating
the IRF PPS wage index. In addition, the OMB's CBSA-based designations
reflect the most recent available geographic classifications and more
accurately reflects current labor markets. Therefore, we believe that
revising the IRF PPS labor market area definitions based on OMB's CBSA-
based designations are consistent with our historical practice of
modeling IRF PPS policy after IPPS policy.
In sections VI.B.2.d.i. through VI.B.2.d.iii of this final rule and
as described in the FY 2006 IRF PPS proposed rule (70 FR 30188), we
describe the composition of the IRF PPS labor market areas based on the
OMB's new CBSA designations.
i. New England MSAs
As stated above, in the August 7, 2001 final rule, we currently use
NECMAs to define labor market areas in New England, because these are
county-based designations rather than the 1990 MSA definitions for New
England, which used minor civil divisions such as cities and towns.
Under the current MSA definitions, NECMAs provided more consistency in
labor market definitions for New England compared with the rest of the
country, where MSAs are county-based. Under the new CBSAs, OMB has now
defined the MSAs and Micropolitan Areas in New England on the basis of
counties. The OMB also established New England City and Town Areas,
which are similar to the previous New England MSAs.
To create consistency among all labor market areas and to maintain
these areas on the basis of counties, we proposed to and are adopting
in this final rule to use the county-based areas for all MSAs in the
nation, including those in New England. Census has now defined the New
England area based on counties, creating a city- and town-based system
as an alternative. We believe that adopting county-based labor market
areas for the entire country except those in New England will lead to
inconsistencies in our designations. Adopting county-based labor market
areas for the entire country provides consistency and stability in the
Medicare payment program because all the labor market areas throughout
the country, including New England, will be defined using the same
system (that is, counties) rather than different systems in different
areas of the country, and minimizes programmatic complexity.
We have consistently employed a county-based system for New England
for precisely that reason: To maintain consistency with the labor
market area definitions used throughout the country. Because we have
never used cities and towns for defining IRF labor market areas,
employing a county-based system in New England maintains that
consistent practice. We note that this is consistent with the
implementation of the CBSA-based designations under the IPPS for New
England (see 69 FR at 49028). Accordingly, as specified in the FY 2006
proposed rule (70 FR 30188), we are using the New England MSAs as
determined under the new CBSA-based labor market area definitions in
defining the revised IRF PPS labor market areas in this final rule.
ii. Metropolitan Divisions
Under OMB's new CBSA designations, a Metropolitan Division is a
county or group of counties within a CBSA that contains a core
population of at least 2.5 million, representing an employment center,
plus adjacent counties associated with the main county or counties
through commuting ties. A county qualifies as a main county if 65
percent or more of its employed residents work within the county and
the ratio of the number of jobs located in the county to the number of
employed residents is at least 0.75. A county qualifies as a secondary
county if 50 percent or more, but less than 65 percent, of its employed
residents work within the county and the ratio of the number of jobs
located in the county to the number of employed residents is at least
0.75. After all the main and secondary counties are identified and
grouped, each additional county that already has qualified for
inclusion in the MSA falls within the Metropolitan Division associated
with the main/secondary county or counties with which the county at
issue has the highest employment interchange measure. Counties in a
Metropolitan Division must be contiguous (65 FR at 82236).
The construct of relatively large MSAs being comprised of
Metropolitan Divisions is similar to the current construct of the CMSAs
comprised of PMSAs. As noted above, in the past, OMB designated CMSAs
as Metropolitan Areas with a population of 1 million or more and
comprised of two or more PMSAs. Under the IRF PPS, we currently use the
PMSAs rather than CMSAs to define labor market areas because they
comprise a smaller geographic area with potentially varying labor costs
due to different local economies. We believe that CMSAs may be too
large of an area with a relatively large number of hospitals, to
accurately reflect the local labor costs of all the individual
hospitals included in that relatively ``large'' area. A large market
area designation increased the likelihood of including many hospitals
located in areas with very different labor market conditions within the
same
[[Page 47920]]
market area designation. This variation could increase the difficulty
in calculating a single wage index that will be relevant for all
hospitals within the market area designation. Similarly, we believe
that MSAs with a population of 2.5 million or greater may be too large
of an area to accurately reflect the local labor costs of all the
individual hospitals included in that relatively ``large'' area.
Furthermore, as indicated above, Metropolitan Divisions represent the
closest approximation to PMSAs, the building block of the current IRF
PPS labor market area definitions, and therefore, will most accurately
maintain our current structuring of the IRF PPS labor market areas. As
implemented under the IPPS (69 FR at 49029), we proposed and for this
final rule, we are using the Metropolitan Divisions where applicable
(as describe below) under the new CBSA-based labor market area
definitions.
In addition to being comparable to the organization of the labor
market areas under the current MSA designations (that is, the use of
PMSAs rather than CMSAs), we believe that using Metropolitan Divisions
where applicable (as described below) under the IRF PPS will result in
a more accurate adjustment for the variation in local labor market
areas for IRFs. Specifically, if we were to recognize the relatively
``larger'' CBSA that comprises two or more Metropolitan Divisions as an
independent labor market area for purposes of the wage index, it will
be too large and will include the data from too many hospitals to
compute a wage index that will accurately reflect the various local
labor costs of all the individual hospitals included in that relatively
``large'' CBSA.
As mentioned earlier, a large market area designation increases the
likelihood of including many hospitals located in areas with very
different labor market conditions within the same market area
designation. This variation could increase the difficulty in
calculating a single wage index that will be relevant for all hospitals
within the market area designation. Rather, by recognizing Metropolitan
Divisions where applicable (as described below) under the new CBSA-
based labor market area definitions under the IRF PPS, we believe that
in addition to more accurately maintaining the current structuring of
the IRF PPS labor market areas, the local labor costs will be more
accurately reflected, thereby resulting in a wage index adjustment that
better reflects the variation in the local labor costs of the local
economies of the IRFs located in these relatively ``smaller'' areas. In
section VI.B.2.d.ii.of this final rule, we describe where Metropolitan
Divisions will be applicable under the new CBSA-based labor market area
definitions under the IRF PPS final rule.
Under the OMB's CBSA-based designations, there are 11 MSAs
containing Metropolitan Divisions: Boston; Chicago; Dallas; Detroit;
Los Angeles; Miami; New York; Philadelphia; San Francisco; Seattle; and
Washington, DC. Although these MSAs were also CMSAs under the prior
definitions, in some cases their areas have been altered. Under the
current IRF PPS MSA designations, Boston is a single NECMA. Under the
CBSA-based labor market area designations, it is comprised of four
Metropolitan Divisions. Los Angeles will go from four PMSAs under the
current IRF PPS MSA designations to two Metropolitan Divisions under
the CBSA-based labor market area designations. The New York CMSA will
go from 15 PMSAs under the current IRF PPS MSA designations to four
Metropolitan Divisions under the CBSA-based labor market area
designations. The five PMSAs in Connecticut under the current IRF PPS
MSA designations will become separate MSAs under the CBSA-based labor
market area designations because two MSAs became separate MSAs. The
number of PMSAs in New Jersey, under the current IRF PPS MSA
designations will go from five to two, with the consolidation of two
New Jersey PMSAs (Bergen-Passaic and Jersey City) into the New York-
Wayne-White Plains, NY-NJ Division, under the CBSA-based labor market
area designations. In San Francisco, under the CBSA-based labor market
area designations there are only two Metropolitan Divisions. Currently,
there are six PMSAs, some of which are now separate MSAs under the
current IRF PPS labor market area designations.
Under the current IRF PPS labor market area designations,
Cincinnati, Cleveland, Denver, Houston, Milwaukee, Portland,
Sacramento, and San Juan are all designated as CMSAs, but will no
longer be designated as CMSAs under the CBSA-based labor market area
designations. As noted previously, the population threshold to be
designated a CMSA under the current IRF PPS labor market area
designations is 1 million. In most of these cases, counties currently
in a PMSA will become separate, independent MSAs under the CBSA-based
labor market area designations, leaving only the MSA for the core area
under the CBSA-based labor market area designations.
We note that subsequent to the publication of the FY 2006 IRF PPS
proposed rule (70 FR 30188), titles to certain CBSAs were changed based
on OMB Bulletin No. 05-02 (November 2004). The title changes listed
below are nomenclatures that do not result in substantive changes to
the CBSA-based designations. Thus, these changes are listed below and
will be incorporated into the FY 2007 CBSA-based urban wage index
tables.
CBSA 36740: Orlando-Kissimmee, FL
CBSA 37620: Parkersburg-Marietta-Vienna, WV-OH
CBSA 42060: Santa Barbara-Santa Monica, CA
CBSA 13644: Bethesda-Gaithersburg-Frederick, MD
CBSA 32580: McAllen-Edinburg-Mission, TX
CBSA 26420: Huston-Sugar Land-Baytown, TX
CBSA 35644: New York-White Plains-Wayne, NY-NJ
ii. Micropolitan Areas Under the New OMB CBSA-Based Designations,
Micropolitan
Areas are essentially a third area definition consisting primarily
of areas that are currently rural, but also include some or all of
areas that are currently designated as urban MSA. As discussed in
greater detail in the IPPS final rule (69 FR at 49029 through 49032),
how these areas are treated will have significant impacts on the
calculation and application of the wage index. Specifically, whether or
not Micropolitan Areas are included as part of the respective statewide
rural wage indices will impact the value of the statewide rural wage
index of any State that contains a Micropolitan Area because a
hospital's classification as urban or rural affects which hospitals'
wage data are included in the statewide rural wage index. As discussed
above in section VI.B.2.b of this final rule, we combine all of the
counties in a State outside a designated urban area to calculate the
statewide rural wage index for each State.
Including Micropolitan Areas as part of the statewide rural labor
market would result in an increase to the statewide rural wage index
because hospitals located in those Micropolitan Areas typically have
higher labor costs than other rural hospitals in the State.
Alternatively, if Micropolitan Areas were to be recognized as
independent labor market areas, because there would be so few hospitals
in those areas to complete a wage index, the wage indices for IRFs in
those areas could become relatively unstable as they might change
considerably from year to year.
Since the implementation of the IRF PPS, we used MSAs to define
urban labor market areas and group all the
[[Page 47921]]
hospitals in counties within each State that are not assigned to an MSA
into a statewide rural labor market area. Therefore, we used the terms
``urban'' and ``rural'' wage indices in the past for ease of reference.
However, the introduction of Micropolitan Areas by the OMB potentially
complicates this terminology because these areas include many hospitals
that are currently included in the statewide rural labor market areas.
We proposed to treat Micropolitan Areas as rural labor market areas
under the IRF PPS for the reasons outlined below. That is, counties
that are assigned to a Micropolitan Area under the CBSA-based
designations would be treated the same as other ``rural'' counties that
are not assigned to either an MSA or a Micropolitan Area. Therefore, in
determining an IRF's applicable wage index (based on IPPS hospital wage
index data) an IRF in a Micropolitan Area under OMB's CBSA designations
would be classified as ``rural'' and would be assigned the statewide
rural wage index for the State in which it resides.
In the IPPS final rule (69 FR at 49029 through 49032), we discuss
our evaluation of the impact of treating Micropolitan areas as part of
the statewide rural labor market area instead of treating Micropolitan
Areas as independent labor market areas for hospitals paid under the
IPPS. As an alternative to treating Micropolitan Areas as part of the
statewide rural labor market area for purposes of the IRF PPS, in the
FY 2006 proposed rule (70 FR 30188), we examined treating Micropolitan
Areas as separate (urban) labor market areas, just as we did when
implementing the revised labor market areas under the IPPS.
As discussed in greater detail in that same final rule, the
designation of Micropolitan Areas as separate urban areas for wage
index purposes will have a dramatic impact on the calculation of the
wage index. This is because Micropolitan areas encompass smaller
populations than MSAs, and tend to include fewer hospitals per
Micropolitan area. Currently, there are only 25 MSAs with one hospital
in the MSA. However, under the new CBSA-based definitions, there are
373 Micropolitan Areas with one hospital, and 49 MSAs with only one
hospital.
Since Micropolitan Areas encompass smaller populations than MSAs,
they tend to include fewer hospitals per Micropolitan Area, recognizing
Micropolitan Areas as independent labor market areas will generally
increase the potential for dramatic shifts in those areas' wage indices
from one year to the next because a single hospital (or group of
hospitals) could have a disproportionate effect on the wage index of
the area. The large number of labor market areas with only one hospital
and the increased potential for dramatic shifts in the wage indexes
from one year to the next is a problem for several reasons. First, it
creates instability in the wage index from year to year for a large
number of hospitals. Second, it reduces the averaging effect (this
averaging effect allows for more data points to be used to calculate
the representative standard of measured labor costs within a market
area) lessening some of the incentive for hospitals to operate
efficiently. This incentive is inherent in a system based on the
average hourly wages for a large number of hospitals, as hospitals
could profit more by operating below that average. In labor market
areas with a single hospital, high wage costs are passed directly into
the wage index with no counterbalancing averaging with lower wages paid
at nearby competing hospitals. Third, it creates an arguably
inequitable system when so many hospitals have wage indexes based
solely on their own wages, while other hospitals' wage indexes are
based on an average hourly wage across many hospitals. Therefore, in
order to minimize the potential instability in payment levels from year
to year, we believe it will be appropriate to treat Micropolitan Areas
as part of the statewide rural labor market area under the IRF PPS.
For the reasons noted above, and consistent with the treatment of
these areas under the IPPS, we proposed and are adopting Micropolitan
Areas as independent labor market areas under the IRF PPS. Under the
new CBSA-based labor market area definitions, Micropolitan Areas are
considered a part of the statewide rural labor market area.
Accordingly, we will determine an IRF PPS statewide rural wage index
using the acute-care IPPS hospital wage data (the rational for using
IPPS hospital wage data is discussed in section III.B.2.f of this final
rule) from hospitals located in non-MSA areas assign the statewide
rural wage index to IRFs located in those areas.
e. Implementation of the CBSA-Based Labor Market Areas
Under section 1886(j) of the Act, as added by section 4421 of the
Balanced Budget Act of 1997 (BBA) (Pub. L. 105-33) and as amended by
section 125 of the Medicare, Medicaid, and State Children's Health
Insurance Program (SCHIP) Balanced Budget Refinement Act of 1999 (BBRA)
(Pub. L. 106-113) and section 305 of the Medicare, Medicaid, and SCHIP
Benefits Improvement and Protection Act of 2000 (BIPA) (Pub. L. 106-
554), which requires the implementation of such prospective payment
system, the Secretary generally has broad authority in developing the
IRF PPS, including whether and how to make adjustments to the IRF PPS.
In the FY 2006 IRF PPS proposed rule (70 FR 30188), Table 3 listed
IRFs that submitted an IRF-PAI in the past 18-months. The data in Table
3 was obtained from a report we requested in February 2005 from the
Iowa Foundation for Medical Care (IFMC). IFMC is the CMS contractor
where the IRF-PAI database is located. Table 3 listed each IRF's
provider number; provider name; and State and county location; existing
MSA-based labor market area designation; and its CBSA-based
designation. The purpose of Table 3 was to only facilitate an
understanding of the policies related to the proposed change to the IRF
PPS labor market areas discussed above by illustrating an IRF's change
from the MSA-based designation to the proposed CBSA-based designation.
Thus, FIs will not be instructed to use Table 3 in the FY 2006 IRF PPS
proposed rule (70 FR 30188) to alter the information regarding an IRF's
State and county location or to make changes to the provider specific
file based on Table 3 of the FY 2006 IRF PPS proposed rule.
Table 1 of the addendum of this final rule is a crosswalk file of
all counties/areas in the United States, Guam, Puerto Rico, and the
Virgin Islands with the corresponding State and county code, county and
State name, FY 2006 MSA number, FY 2006 MSA-based urban or rural
designation, FY 2006 MSA-based wage index, FY 2006 CBSA-based wage
index, FY 2006 CBSA number, FY 2006 CBSA-based urban or rural
designation, and FY 2006 blended one-year transition wage index as
discussed below in Section VI.B.2.e. Table 1 of the addendum to this
final rule will be used by FIs to determine the FY 2006 one-year
transition wage index for IRFs located in areas as documented in the
FI's provider specific file.
When the revised labor market areas based on OMB's new CBSA-based
designations were adopted under the IPPS beginning on October 1, 2004,
a transition to the new designations was established due to the scope
and substantial implications of these new CBSA-based designations in
order to buffer the subsequent substantial impacts on numerous
hospitals. As discussed in the IPPS final rule (69 FR at 49032), during
FY 2005, a blend of
[[Page 47922]]
wage indices is calculated for those acute care IPPS hospitals
experiencing a drop in their wage index because of the adoption of the
new labor market areas. The most substantial decrease in wage index
impacts urban acute-care hospitals that were designated as rural under
the CBSA-based designations.
In the FY 2006 IRF PPS proposed rule (70 FR 30188), we recognize
that, just like IPPS hospitals, IRFs may experience decreases in their
wage index as a result of the labor market area changes. Our data
analysis for the FY 2006 IRF PPS proposed rule (70 FR 30188) indicated
that a majority of IRFs either expect no change in wage index or an
increase in wage index based on CBSA definitions. Based on this
analysis for the FY 2006 IRF PPS proposed rule (70 FR 30188), we found
a very small number of IRFs (3 percent) will experience a decline of 5
percent or more in the wage index based on CBSA designations. A 5
percent decrease in the wage index for an IRF may result in a
noticeable decrease in their wage index compared to what their wage
index would have been for FY 2006 under the MSA-based designations. We
also found that a very small number of IRFs (4 percent) would
experience a change in either rural or urban designation under the
CBSA-based definitions. Since a majority of IRFs would not be
significantly impacted by the labor market areas, we did not propose a
transition to the new CBSA-based labor market area, nor did we propose
to adopt a hold harmless policy, nor an ``out-commuting'' policy for
the purposes of the IRF PPS wage index.
Public comments and our responses on the proposed changes for
implementing the area wage adjustments are summarized below:
Comment: A large number of commenters urged CMS to develop a
transition policy or implement a similar transition policy as was
implemented under the IPPS to minimize the fiscal impact of the change
in wage index. Many advocated for a one-year transition with a blended
wage index, equal to 50 percent of the FY 2006 MSA wage index and 50
percent of the FY 2006 CBSA-based wage index. We also received a few
comments recommending a multi-year transition and possibly a permanent
blended wage index. Overall, commenters expressed concerns for IRFs
that would experience a significant decrease in the wage index. In
general, commenters request that we mitigate the impact of the change
from the MSA-based designation to the CBSA-based designations over time
with a transition policy.
Response: We recognize that some IRFs will experience decreases in
their applicable wage index as a result of the conversion from the MSA-
based designations to the CBSA-based designations. After further
analysis of various transition options suggested by commenters as well
as our further data analysis to support the policies in this final
rule, we considered various transition options to determine a
transition policy that would mitigate the impact on IRFs that would
experience a decrease in the wage index, and buffer the overall impact
on the unadjusted payment rate. Based on the commenters'
recommendations, we carefully reviewed various budget neutral
transition policies such as a blended wage index as well as a floor and
ceiling approach as discussed in detail below.
We reviewed a floor and ceiling transition policy option. Although
this option seemed to minimize the impact on IRFs, we found that this
approach would provide relief to IRFs that experience a decrease in the
wage index, but with respect to IRFs that would get a significant
increase in the wage index, it would also limit the amount they could
expect their wage index to increase. The difficulty of developing a
floor and ceiling transition policy is determining an appropriate floor
and a ceiling that would best mitigate IRFs that experience a decrease
in the wage index while lessening the overall impact on the unadjusted
base payment kept us from choosing this option.
Although a few commenters recommended a permanent blended wage
index (comprised of the MSA-based wage index and the CBSA-based wage
index), we do not believe this is appropriate. Beginning in FY 2006,
acute care hospital will receive 100 percent of the IPPS wage index
based on the new CBSA wage index. From FY 2006 and forward, CMS will no
longer maintain the geographic classifications based on MSAs.
Therefore, MSA-based wage indexes will not be able to reflect the same
amount of accuracy as they currently represent by having the
geographical classification updated annually. By developing a permanent
blended wage index, CMS would only be geographically updating the CBSA-
based areas and not the MSA-based areas. Consequently, we believe that
implementation of a permanent blended wage index would result in a wage
index that is not as accurate as a wage index based on the CBSA
methodology, as thoroughly discussed in section VI.B.2.d.
Several commenters suggested that IRFs be afforded the same
transition as adopted by IPPS (69 FR 48916, 49032-49034). Therefore,
another budget neutral one-year transition policy we considered would
blend the wage index for IRFs that would experience a reduction in the
wage index. The blended wage index would consist of 50 percent of the
FY 2006 MSA-based wage index and 50 percent of the FY 2006 CBSA-based
wage index (both based on the FY 2001 hospital wage data), only for
IRFs that experience a decrease due solely to the changes in the labor
market definitions. Although some commenters recommended this
transition policy, we believe that this would not allow all IRFs the
ability to transition from the MSA-based wage index to the CBSA-based
wage index because this transition policy only focuses on the blending
the wage index for IRFs that experience a decrease in the wage index.
In addition, we found that this would change the budget neutrality
factor applied to the base rates from 0.9996 if there was no transition
to 0.9977 under this transition policy. Therefore, the budget
neutrality factor under the transition policy for only those IRFs that
experience a decrease in the wage index would reduce the unadjusted
base rate by approximately more than 20 dollars. The overall impact
based on the reduction of the unadjusted base rate would result in all
IRFs experiencing a reduction in payments. Under this approach, we
found that IRFs would experience a significant reduction in the
unadjusted payment amount, which would not mitigate the change in
estimated payments for IRFs.
The last one-year budget neutral blended transition policy we
analyzed would allow all IRFs to transition from an MSA-based wage
index to a CBSA-based wage index. This transition policy would be
comprised of 50 percent of the FY 2006 MSA-based wage index and 50
percent of the FY 2006 CBSA-based wage index (both based on the FY 2001
hospital wage data) for all IRFs. As discussed in the FY 2006 IRF PPS
proposed rule (70 FR 30188), the one-year blended wage index for all
IRFs would result in a slight decrease of budget neutrality factor
applied to the base rates from 0.9996 if there was no transition to
0.9995 under this transition policy. As a result, the budget neutrality
factor applied to the unadjusted payment amount would reduce the
unadjusted payment amount by approximately 1 dollar as compared to
fully adopting the CBSA-based designations. This slight decrease to the
unadjusted payment amount will lessen the overall payment reduction
impact
[[Page 47923]]
on all providers--regardless of urban or rural designations.
Although a blended wage index for all IRFs would also help IRFs
that are adversely affected by the changes from MSAs to CBSAs, it would
reduce the expected higher CBSA wage index values for IRFs that are
positively affected by the changes (compared to fully adopting the
CBSA-based wage index). To clarify, a blended wage index for IRFs that
experience any increase due to the change from an MSA-based wage index
to a CBSA-based wage index would be lessened. Thus, this would allow
all IRFs one year to financially prepare for a change in wage index due
to the change from FY 2005 MSA-based to FY 2006 CBSA-based
designations--regardless of an increase or decrease in wage index.
In addition, although the blended wage index would limit the wage
index increase for IRFs that experience an increase due to the change
from an MSA-based wage index to a CBSA-based wage index during FY 2006,
these IRFs will continue to see an increase in their wage index.
However, the dampening effect of the blended wage index for IRFs that
experience an increase in their wage index does not significantly
impact these IRFs based solely on the wage index. The increase in the
wage index these IRFs would experience would still take effect because
the blended wage index would be an average of the MSA-based wage index
and a CBSA-based wage index and the CBSA-based wage index would be
greater than the MSA-based wage index. Therefore, IRFs in this scenario
would not be significantly impacted by a blended wage index. In other
words, IRFs that have higher CBSA wage index values and are subject to
the blend will continue to have a benefit of having their payment
derived, in part, from the higher CBSA wage index. We believe this
option helps create an equitable situation for all IRFs.
Many commenters urged and supported a transition to adopting the
CBSA-based designations. Thus, this blended wage index (50 percent of
the FY 2006 MSA-based wage index and 50 percent of the FY 2006 CBSA-
based wage index and both based on the FY 2001 hospital wage data)
would provide IRFs a one-year transition from the MSA-based
designations to the CBSA-based designations. In addition, the one year
transition of a blended wage for all IRFs would result in 93 percent of
all IRFs experiencing a wage index change between a decrease by up to 2
percent or an increase by up to 2 percent. In any given year, even
under the MSA-based wage index, many IRFs experience a 2 percent change
in wage index and this 2 percent change would most likely be a wage
index change that would not significantly impact IRF payments based
solely on the wage index. Thus, from year to year, almost all IRFs are
expected to experience a minimal change in wage index values. In
comparison, if we fully adopted the CBSA-based wage index without a
transition as proposed, 85 percent of the IRFs would experience a
change between a decrease by up to 2 percent or an increase by up to 2
percent. By providing a one year transition for all IRFs to receive a
blended wage index (50 percent of the FY 2006 MSA-based wage index and
50 percent of the FY 2006 CBSA-based wage index and both based on the
FY 2001 hospital wage data), a larger majority of IRFs will experience
a minimal change in wage index from FY 2005 to FY 2006.
We decided not to provide for a longer transition, as recommended
by a few commenters, because we have already, in effect, provided one
year at a higher wage index level for all IRFs by retaining the
previous labor market definitions for two years after the new labor
market definitions became available. For example, we did not implement
the new labor market area definitions as quickly as was done for
facilities paid under the IPPS. Furthermore, since most IRFs benefit
from a one year blended wage index, there will be minimal affect on
IRFs. Thus, a one year transition is sufficient to minimize the impact
of adopting the CBSA-based designations because we believe that the
transition period allows IRFs sufficient time to adjust their necessary
business practices. In addition to the one year blended wage index, we
are implementing a longer, 3-year hold harmless transition (as
discussed in this section below of this final rule (section VI.B.2.e))
for a group of IRFs that during FY 2005 are as designated as rural, and
for FY 2006 will be designated as urban under the new CBSA-based
geographic designation method. We are implementing a longer hold
harmless transition for these IRFs because, as a group they experience
a reduction in payments due to the labor market revisions and the loss
of the rural adjustment.
The statute confers broad authority to the Secretary under
1886(j)(6) of the Act to establish factor for area wage differences by
a factor such that budget neutral wage index options may be considered.
After consideration of the recommendations presented by the commenters
and based on our further analysis, we will implement a budget neutral
one-year transition policy such that a blended wage index (50 percent
of the FY 2006 MSA-based wage index and 50 percent of the FY 2006 CBSA-
based wage index that are both based on the FY 2001 hospital wage data)
will apply to all IRFs. This transition policy will be effective for
discharges occurring on or after October 1, 2005 and on or before
September 30, 2006. This transition will mitigate the large negative
impacts for IRFs that experience a decrease in the wage index and allow
all IRFs to transition from the MSA-based wage index to the CBSA-based
wage index for one-year. Therefore, for FY 2007 and subsequent years,
we will adopt the full CBSA-based wage index for all IRFs.
Comment: Several commenters requested CMS to consider a multi-year
hold harmless policy as was implemented by IPPS.
Response: As discussed in the August 11, 2004 IPPS final rule (69
FR at 49032), during FY 2005, a hold harmless policy was implemented to
minimize the overall impact of hospitals that were in FY 2004
designated as urban under the MSA designations, but will become rural
under the CBSA designations. In the same final rule, hospitals were
afforded a three-year hold harmless policy because the IPPS determined
that acute-care hospitals that changed designations from urban to rural
will be substantially impacted by the significant change in wage index.
Although we considered a hold harmless policy in our FY 2006 proposed
rule, we did not propose a hold harmless policy because we believed
that rural IRFs (under the MSA-based designations) that change to an
urban designation (based on the CBSA-based geographic classification)
would experience a significant increase to the wage index under the
CBSA-based designations that would mitigate a significant decrease in
payments. However, many commenters urged CMS to reconsider a hold
harmless policy because the commenters demonstrated that some rural
facilities would experience undue hardship with the loss of the rural
adjustment under Sec. 412.624(e)(3).
In our analysis (discussed in the FY 2006 IRF PPS proposed rule (70
FR 30188)), we found that 91 percent of rural facilities that would be
designated as urban under the CBSA-based definitions will experience an
increase in the wage index. A majority (74 percent) of rural facilities
that become urban will experience at least a 5 percent to 10 percent or
more increase in wage index. Although these rural IRFs experience wage
index increases, several commenters emphasized that a
[[Page 47924]]
majority of rural providers that change designations may experience a
wage index increase of at least 5 percent or more, the loss of the
rural adjustment would be such a large negative impact on the rural
IRFs that it may potentially cause undue hardship for these rural
facilities.
In response to the commenters concerns, we considered different
hold harmless policies such as a multi-year hold harmless policy as
well as a phase-out of the rural adjustment for rural IRFs under the
MSA-based designations that received a rural adjustment of 19.14
percent in FY 2005. A commenter recommended a phase-out of the FY 2005
rural adjustment of 19.14 percent because this option allows IRFs that
change designations, from rural to urban, time to adjust to the loss of
the 19.14 percent rural adjustment which would result in loss of
payments. Other commenters concurred that the loss of the FY 2005 rural
adjustment far exceeds the urban CBSA-based increase in wage index.
Thus, commenters believed that this would have significant payment
implications, particularly large negative impacts for rural IRFs that
change designations because they will experience significant payment
losses.
After further consideration of hold harmless policies as
recommended by commenters, we have decided to implement a hold harmless
policy to mitigate significant payment implications, particularly large
negative impacts. We will implement a 3 year budget neutral hold
harmless policy for those IRFs that meet the definition in Sec.
412.602 as rural in FY 2005 and will become urban under the FY 2006
CBSA-based designations. We will afford existing IRFs designated in FY
2005 as rural IRFs (pursuant to Sec. 412.602) and redesignated as an
urban facility in FY 2006 (pursuant to Sec. 412.602) in FY 2006, whose
payment is lower because of such redesignation, a 3 year time span to
adjust to the loss of the FY 2005 rural adjustment of 19.14 percent
because the loss of the 19.14 percent rural adjustment would result in
a significant loss of payments. This adjustment will be in addition to
the one-year blended wage index (comprised of FY 2006 MSA-based wage
index and FY 2006 CBSA-based wage index both based on FY 2001 hospital
data) for all IRFs.
Although our intent under our hold harmless policy is to mitigate
the negative payment effect upon a rural facility that is redesignated
as an urban facility (effective FY 2006), the hold harmless policy
should not result in an IRF that comes under the hold harmless policy
to realize greater payments than the IRF would have if instead the IRF
would have been paid under its rural designation in FY 2006 including
the FY 2005 rural adjustment of 19.14 percent. Therefore, we will make
the appropriate payment modification to the additional adjustment made
under our hold harmless policy so that an existing FY 2005 rural IRF
that is redesignated from rural to urban in FY 2006 will in FY 2006 or
FY 2007 not realize payments that are greater than what the payments
would have been if the facility would have instead been paid under its
rural designation in FY 2006 including the FY 2005 rural adjustment of
19.14 percent. In other words, if an existing FY 2005 IRF is
redesignated from rural to urban in FY 2006, and it will realize an
increase in payments during the one year transition due to the hold
harmless policy, it will not receive the full two-thirds of the 19.14
percent rural adjustment. However, if this same IRF realizes a decrease
in payment in FY 2007 solely because of such redesignation in FY 2006,
it will receive one-third of the 19.14 percent rural adjustment in such
case.
As stated above, the hold harmless policy is specifically for FY
2005 rural IRFs that become urban in FY 2006 and that experience a loss
in payment because of this redesignation. Thus, we are not implementing
a hold harmless policy for urban facilities (under the MSA-based
designation) that become rural (under the CBSA-based designation)
because these IRFs will receive the updated FY 2006 rural adjustment of
21.3 percent that they did not receive in FY 2005 as an urban facility.
The gain of this payment adjustment should more than mitigate the loss
of the wage index decreases associated with the rural designations. For
FY 2005, rural facilities that remain rural under the FY 2006 CBSA-
based designation, we are not extending the hold harmless policy for
these IRFs because these rural IRFs will receive the updated FY 2006
rural adjustment of 21.3 percent, which is higher than the FY 2005
rural adjustment of 19.14 percent. We are also not extending the hold
harmless policy for facilities that remain in their urban geographic
designations from the MSA-based designation to the CBSA-based
designation because we have mitigated the impact of the change in wage
index value by implementing a one year transition wage index (comprised
of 50 percent FY 2006 MSA-based wage index and 50 percent of the FY
2006 CBSA-based wage index) for all IRFs as discussed in detail above.
As was previously stated, the purpose of the hold harmless policy is to
mitigate the significant payment implications for existing rural IRFs
that may need time to adjust to the loss of their FY 2005 rural payment
adjustment that experience a reduction in payments solely because of
such redesignation. Our decision to implement the hold harmless policy
only for existing FY 2005 rural IRFs that will be adversely impacted,
is supported by comments received primarily requesting implementation
of a method that mitigates the adverse payment impacts because of the
loss of the rural adjustment.
Due to our review and analysis, we determined that a 3 year budget
neutral hold harmless policy would best accomplish the goals of
mitigating the loss of the rural adjustment for existing FY 2005 rural
IRFs. The incremental steps needed to reduce the impact of the loss of
the FY 2005 rural adjustment of 19.14 percent will be phased out for
years FY 2006, FY 2007, and FY 2008.
Thus, the budget neutral 3 year hold harmless policy will apply to
the existing FY 2005 rural IRFs (under the MSA-based designation) that
will change designations and experience a reduction in payments due to
the loss of the FY 2005 rural adjustment of 19.14 percent and meets the
intent of this policy. The hold harmless policy will allow existing FY
2005 rural IRFs adversely affected by the change in designation to
receive two-thirds of the FY 2005 rural adjustment of 19.14 percent
(specifically 12.76 percent hold harmless adjustment) for FY 2006 as
well as the blended wage index (comprised of 50 percent of the FY 2006
MSA-based wage index and 50 percent of the FY 2006 CBSA-based wage
index both based on FY 2001 hospital data). For FY 2007, existing FY
2005 rural IRFs that are a part of the FY 2006 hold harmless policy
will receive the full FY 2007 CBSA wage index and one-third of the FY
2005 rural adjustment of 19.14 percent (specifically, a 6.38 percent
hold harmless adjustment). For FY 2008, existing FY 2005 rural IRFs
that are a part of the FY 2006 hold harmless policy will receive the
full FY 2008 CBSA-based wage index without a rural adjustment as long
as the IRF is designated as urban under the FY 2008 CBSA-based
designation (illustrated in Table 10 below).
[[Page 47925]]
Table 10.--IRF 3-Year Hold Harmless Policy for IRFs Designated as Rural Under the MSA-Based Designation
----------------------------------------------------------------------------------------------------------------
FY 2006 FY 2007 FY 2008
----------------------------------------------------------------------------------------------------------------
50% of MSA Wage
Wage Index Index and 50% of Full FY 2007 CBSA Full FY 2008 CBSA
CBSA Wage Index Wage Index Wage Index
----------------------------------------------------------------------------------------------------------------
Rural Adjustment (Phase out)*................. 12.76 6.38 N/A
----------------------------------------------------------------------------------------------------------------
*Based on the FY 2005 Rural Adjustment of 19.14 percent.
As is shown by the table, making incremental reductions to the
19.14 percent rural adjustment that certain rural IRFs received during
FY 2005 results in these IRFs still being paid a portion of that rural
adjustment in FY 2006 and FY 2007.
We believe that an incremental reduction of the FY 2005 rural
adjustment of 19.14 percent is appropriate because of our analysis to
implement a one third compared to a two thirds hold harmless adjustment
of the 19.14 percent rural adjustment in FY 2006. We analyzed the 34
IRFs (in our analysis file) that would be impacted by the hold harmless
policy to determine the effect on their IRF PPS payments if we did not
implement a hold harmless policy. We also reviewed the payment impacts
on these IRFs if the hold harmless policy implemented one third of the
FY 2005 rural adjustment of 19.14 percent versus two thirds of the FY
2005 rural adjustment of 19.14 percent in FY 2006 (as described in the
section XII).
We found that if we did not adopt a hold harmless policy, the 34
rural IRFs that change designations from a rural facility (under the
MSA-based designations) to an urban facility (under the CBSA-based
designations) would experience a significant reduction in per case
payment. We also considered a one year hold harmless policy that would
allow the 34 IRFs in our analysis to receive a blended wage index as
well as only a one third of the FY 2005 rural adjustment of 19.14
percent. Based on our analysis, a one year hold harmless policy would
slightly mitigate the payment reductions for rural IRFs in our analysis
file.
Our analysis of whether a multi-year hold harmless policy would
provide a sufficient buffer to the loss of payments, found that a 3
year hold harmless policy of two thirds of the 19.14 percent rural
adjustment in the FY 2006 and one third in FY 2007 would be the most
appropriate. Based on a 3 year hold harmless policy, we found these
IRFs would be mitigated from significant payment reductions. We
determined that a 3 year hold harmless policy that provides two thirds
of the 19.14 percent adjustment in FY 2006 and one third in FY 2007
would appropriately mitigate the adverse payment impacts for existing
FY 2005 rural IRFs that are designated as urban IRFs in FY 2006.
To determine whether an existing FY 2005 rural IRF would meet part
of the criteria for the hold harmless policy, we have developed Table 2
in the addendum. Table 2 of this addendum is a crosswalk file of
counties/areas in the United States and Puerto Rico that would change
from a rural MSA-based designation to an urban area under the CBSA-
based designation. These areas are listed in Table 2 of the addendum to
identify areas affected by the budget neutral 3 year hold harmless
policy as described in this section. Table 2 of the addendum provides
the State and county code, State and county name, MSA number, MSA rural
designations, FY 2006 MSA-based wage index, FY 2006 CBSA-based wage
index, CBSA number, CBSA urban designations, and the applicable FY 2006
transition wage index as described in section VI.2.B.e. The FIs will
also be instructed to use Table 2 of the addendum to identify IRFs in
these areas that will be impacted by the budget neutral 3 year hold
harmless policy (as discussed in detail in this section) based on the
FI's existing data in the provider specific file.
As a conforming change to Sec. 412.624(e), we are finalizing the
hold harmless policy by adding new paragraph (e)(7). Paragraph (e)(7)
of Sec. 412.624(e) will read as follows: Adjustments for certain
facilities geographically redesignated in FY 2006.
(i) General. For a facility defined as an urban facility under
Sec. 412.602 in FY 2006 that was previously defined as a rural facility
in FY 2005 as the term rural was defined in FY 2005 under Sec. 412.602
and whose payment, after applying the adjustment under this paragraph,
will be lower only because of being defined as an urban facility in FY
2006 and it no longer qualified for the rural adjustment under
Sec. 412.624(e)(3) in FY 2006, CMS will adjust the facility's payment
using the following method:
(A) For discharges occurring on or after October 1, 2005, and on or
before September 30, 2006, the facility's payment will be increased by
an adjustment of two thirds of its prior FY 2005 19.14 percent rural
adjustment.
(B) For discharges occurring on or after October 1, 2006, and on or
before September 30, 2007, the facility's payment will be increased by
an adjustment of one third of its FY 2005 19.14 percent rural
adjustment.
(ii) Exception. For discharges occurring on or after October 1,
2005 and on or before September 30, 2007, facilities whose payments,
after applying the adjustment under this paragraph (e)(7)(i) of this
section, will be higher because of being defined as an urban facility
in FY 2006 and no longer being qualified for the rural adjustment under
412.624(e)(3) in FY 2006, CMS will adjust the facility's payment by a
portion of the applicable additional adjustment described in paragraph
(e)(7)(i)(A) and (e)(7)(i)(B) of this section as determined by us.
In addition, we did not receive comments regarding section 505 of
the MMA that established a new section 1886(d)(13) of the Act. As
discussed in the FY 2006 IRF PPS proposed rule (70 FR 30188), the new
section 1886(d)(13) requires that the Secretary establish a process to
make adjustments to the hospital wage index based on commuting patterns
of hospital employees. We believe that this requirement for an ``out-
commuting'' or ``out-migration'' adjustment applies specifically to the
IPPS. Therefore, we are not implementing such an adjustment for the IRF
PPS in this final rule.
Comment: A number of commenters advised us that Table 3 of the FY
2006 IRF PPS proposed rule contained a formatting problem that resulted
in provider numbers, provider names, state and county location, MSA-
based designation, and CBSA-based designations to be misaligned.
Response: Once this error was brought to our attention, we
immediately published a public use file on our webpage to show the
provider level
[[Page 47926]]
table as developed in Microsoft Excel. The web address for the FY 2006
IRF PPS proposed rule's public use files may be found at http://www.cms.hhs.gov
/providers/irfpps/fy06nprm.asp. Table 3, as published
in the FY 2006 IRF PPS proposed rule (70 FR 30188), was produced for
informational purposes only. Therefore, the information an IRF's FI has
on file for each IRF will not be altered based on Table 3. We will not
be reproducing a provider level table that crosswalks the MSA-based and
CBSA-based designations for this final rule as it was only published in
the proposed rule to help facilitate the public's understanding of the
proposed policy.
For the purposes of determining a wage index for FY 2006 IRF PPS
rate year, we will publish a crosswalk table (Table 1 of this addendum)
listing the State and county code, State and county name, the MSA-based
designations, CBSA-based designations and the blended wage index
(comprised of 50 percent of the FY 2006 MSA-based wage index and 50
percent of the FY 2006 CBSA-base wage index both based on the FY 2001
hospital wage data) for discharges occurring on or after October 1,
2005 and on or before September 30, 2006. In the FY 2006 IRF PPS
proposed rule (70 FR 30188), we published a FY 2006 CBSA urban and
rural wage index table to illustrate the proposed policy to fully adopt
the FY 2006 CBSA wage index. Since we are no longer fully adopting the
FY 2006 CBSA wage index, we will publish a table for FIs to determine
an IRFs blended wage index values for FY 2006 (specifically a blend of
50 percent FY 2006 MSA-based wage index and 50 percent of the FY 2006
CBSA-based wage index). Thus, Table 1 of this addendum will be used by
FIs to determine the FY 2006 one-year blended transitional wage index
(comprised of FY 2006 MSA-based and FY 2006 CBSA-based wage index) as
finalized in this rule.
Final Decision: In summary (as discussed in detail above in the
comments and responses, and based on further analysis of various policy
options to implement the CBSA-based designations), we will implement a
budget neutral one-year transition policy that blends the FY 2006 MSA-
based wage index and FY 2006 CBSA-based wage index (both based on FY
2001 hospital wage data) for discharges occurring on or after October
1, 2005 and on or before September 30, 2006 for all IRFs. In addition
to the blended wage index for FY 2006, we will implement a budget
neutral 3 year hold harmless policy for existing FY 2005 rural IRFs
that will lose the FY 2005 rural adjustment of 19.14 percent,
experience a loss in payments due to the change from an MSA-based rural
designation to a CBSA-based urban designation, and meets the intent of
the hold harmless policy (as discussed in detail above).
f. Wage Index Data
In the August 7, 2001 final rule, we established an IRF wage index
based on FY 1997 acute care hospital wage data to adjust the FY 2002
IRF payment rates. For the FY 2003 IRF PPS payment rates, we applied
the same wage adjustment as used for FY 2002 IRF PPS rates because we
determined that the application of the wage index and labor-related
share used in FY 2002 provided an appropriate adjustment to account for
geographic variation in wage levels that was consistent with the
statute. For the FY 2004 IRF PPS payment rates, we used the hospital
wage index based on FY 1999 acute care hospital wage data. For the FY
2005 IRF PPS payment rates, we used the hospital wage index based on FY
2000 acute care hospital wage data. As was proposed in the FY 2006 IRF
PPS proposed rule (70 FR 30188) and for this final rule, we will use FY
2001 acute care hospital wage data for FY 2006 IRF PPS payment rates
because it is the most recent final data available. As was proposed in
the FY 2006 IRF PPS proposed rule (70 FR 30188), and for this final
rule, we will adopt the methodology discussed in the proposed rule (70
FR at 30188, 30241) to calculate a wage index in the event that there
is no hospital data for an area (urban or rural) under the CBSA-based
designations (70 FR 30188, 30241).
A summary of public comments and our responses on the wage index
data are discussed below:
Comment: Many commenters argue that a majority of IRFs are hospital
units and should be treated the same as hospitals whereby IRFs should
be allowed to be reclassified to the same geographic area as the
hospital. One commenter urged CMS to develop instructions and begin
collecting IRF-specific wage index data in order to allow IRFs to
establish a geographic reclassification criteria for IRFs. Commenters
also urged CMS to use FY 2002 hospital wage data for the FY 2006 IRF
PPS rate year because it is more current than the finalized data
available. One commenter request that CMS develop a ``rural floor''
like that of IPPS.
Response: In the August 1, 2001 final rule (66 FR at 41358) we
established FY 2002 IRF PPS wage index values for the 2002 IRF PPS
fiscal year calculated from the same data used to compute the FY 2001
acute care hospital inpatient wage index data without taking into
account geographic reclassification under sections 1886(d)(8) and
(d)(10) of the Act and without applying the ``rural floor'' under
section 4410 of Pub. L. 105-33 (BBA) (as discussed in section VI.B.2.a
of this final rule). Acute care hospital inpatient wage index data is
also used to establish the wage index adjustment used in other PPSs
(for example, LTCH, IPF, HHA, and SNF). As we discussed in the August
7, 2001 final rule (66 FR at 41316, 41358), since hospitals that are
excluded from the IPPS are not required to provide wage-related
information on the Medicare cost report and because we would need to
establish instructions for the collection of this IRF data it is not
appropriate at this time to implement a wage index specific to IRF
facilities. Because we do not have an IRF specific wage index that we
can compare to the hospital wage index, we are unable to determine at
this time the degree, if any, to which the acute care hospital data
fully represent IRF wages or if a geographic reclassification
adjustment under the IRF PPS is appropriate.
Although commenters request CMS to develop a ``rural floor'' like
the IPPS, we believe the ``rural floor'' is applicable only to the
acute care hospital payment system. Furthermore, as stated in section
VI.B.2, section 4410 of the Balanced Budget Act of 1997 (Pub. L. 105-
33) applies specifically to acute care hospitals and not excluded
hospitals and excluded units. Thus, we believe that the acute care
hospital ``pre-reclassification and pre-floor'' wage data is the best
proxy and most appropriate wage index. In addition and as discussed
above in section VI.B.2.e we will implement a blended wage index to
mitigate the impacts an IRF may experience as a result of the change
from MSA-based designations to CBSA-based designations. Furthermore,
under the IRF PPS, IRFs are paid a rural adjustment under Sec.
412.624(e)(3) as discussed in detail in section VI.B.4 to account for
higher costs among rural facilities versus urban facilities.
Although commenters request instructions to be developed in order
to collect IRF specific wage data, we did not propose to develop
instructions at this time. At this time, we are unable to develop a
separate wage index for rehabilitation facilities. Further, in order to
accumulate the data needed, we would need to make modifications to the
cost report. In the future, we will continue to research wage data
specific to IRF facilities. Because we do not have an IRF specific wage
index that we can compare to the hospital wage index, we are unable to
determine at this time the degree to which the acute care hospital
[[Page 47927]]
data fully represents IRF wages. However, we continue to believe it is
an appropriate proxy because the hospital wage data is currently the
most appropriate data for adjusting payments made to IRFs.
Several comments request the ability to allow IRFs to reclassify
like that of acute care hospitals. To emphasize and as discussed in
section VI.B.2, we believe that actual location of an IRF as opposed to
the location of affiliated providers is most appropriate for
determining the wage adjustment because the data support the premise
that the prevailing wages in the area in which a facility is located
influences the cost of a case. As demonstrated by the update rural
adjustment and research conducted by RAND. The research and findings
that update the rural adjustment is discussed in detail in section
VI.B.4. We continue to review the facility adjustment to account for
higher costs in different types of IRFs by updating our facility
adjustments.
Final Decision: We believe that a wage index based on acute care
hospital wage data is the best proxy and most appropriate wage index to
use in adjusting payments to IRFs, since both acute care hospitals and
IRFs compete in the same labor markets. Since acute care hospitals
compete in the same labor market areas as IRFs, the wage data of acute
care hospitals would accurately capture the relationship of wages and
wage-related costs of IRF in an area as comparable to the national
average.
Therefore, as we proposed in the FY 2006 proposed rule (70 FR
30188) and for this final rule, we continue to believe that a wage
index based on acute care hospital data is the best and most
appropriate wage index to use in adjusting payments to IRFs, since both
acute care hospitals and IRFs compete in the same labor markets. Also,
we will continue to use the same method for calculating wage indices as
was indicated in the August 7, 2001 final rule (69 FR at 41357 through
41358). In addition, 1886(d)(8) and 1886(d)(10) of the Act which
permits reclassification is applicable only to inpatient acute care
hospitals at this time. The wage adjustment established under the IRF
PPS is based on an IRF's actual location without regard to the urban or
rural designation of any related or affiliated provider. Therefore, we
continue to believe reclassification of IRFs is inappropriate at this
time.
In adopting the CBSA-based designations, we recognize that there
may be geographic areas where there are no hospitals, and thus no
hospital wage data on which to base the calculation of the IRF PPS wage
index. We found that for FY 2006, this occurred in two States--
Massachusetts and Puerto Rico--where, using the CBSA-based
designations, there were no hospitals located in rural areas. If rural
IRFs open in Massachusetts or Puerto Rico for FY 2006, we proposed and
for this final rule, we are using the rural FY 2001 MSA-based hospital
wage data for Massachusetts and Puerto Rico to determine the wage index
of such IRFs. In other words, we proposed and as finalized in this
final rule, we will use the same wage data (the FY 2001 hospital wage
data) used to calculate the FY 2006 IRF wage index. However, as we
proposed in the FY 2006 proposed rule (70 FR 30188), for this final
rule, rather than using CBSA-based designations, we will use MSA-based
designations to determine the rural wage index of any States where
there is no wage data available under the CBSA-based designations. By
using such MSA-based designations there will be rural wage indices for
both Massachusetts and Puerto Rico. We believe this is the most
reasonable approach, as we are using the same hospital wage data used
to calculate the CBSA-based wage indices.
In the event this occurs in urban areas where IRFs are located, as
we proposed in the FY 2006 proposed rule (70 FR 30188), for this final
rule, we will use the average of the urban hospital wage data
throughout the State as a reasonable proxy for the urban areas without
hospital wage data. Therefore, urban IRFs located in geographic areas
without any hospital wage data will receive a wage index based on the
average wage index for all urban areas within the State. This does not
presently affect any urban IRFs for FY 2006 because there are no IRFs
located in urban areas without hospital wage data. However, the policy
will apply to future years when there may be urban IRFs located in
geographic areas with no corresponding hospital wage data.
We believe this policy is reasonable because it maintains a CBSA-
based wage index system, while creating an urban proxy for IRFs located
in urban areas without corresponding hospital wage data. We note that
we could not apply a similar averaging in rural areas, because in the
rural areas there is no State rural hospital wage data available for
averaging on a State-wide basis. For example, in Massachusetts and
Puerto Rico, using a CBSA-based designation system, there are simply no
rural hospitals in the State upon which we could base an average.
In addition, we note that the Secretary has broad authority under
1886(j)(6) to update the wage index on the basis of information
available to the Secretary (and updated as appropriate) of the wages
and wage-related costs incurred in furnishing rehabilitation services.
Therefore, for FY 2006, as we proposed in the FY 2006 proposed rule (70
FR 30188), for this final rule, we will use FY 2001 MSA-based hospital
wage data for rural Massachusetts and rural Puerto Rico in the event
there are rural IRFs in such States. To clarify for rural areas without
hospital wage data, we will use the most recent final years wage index
available. In addition, for FY 2006 and thereafter, we are finalizing
our proposed policy to calculate a statewide urban average in the event
that there exist urban IRFs in geographic areas with no corresponding
hospital wage data. Although we solicited comments on these approaches
to calculate the wage index values for areas without hospital wage data
for this and subsequent fiscal years, we did not receive any comments
regarding our proposed methodology as discussed in our FY 2006 IRF PPS
proposed rule. As a result, for any urban areas where there is no urban
hospital wage data, we will calculate an average of the urban hospital
wage data throughout the State as a reasonable proxy.
For the reasons discussed above, as we proposed in the FY 2006
proposed rule (70 FR 30188), for this final rule, we will continue the
use of the acute care hospital inpatient wage index data generated from
cost reporting periods beginning during FY 2001 without taking into
account geographic reclassification as specified under sections
1886(d)(8) and (d)(10) of the Act and without applying the ``rural
floor'' under section 4410 of Pub. L. 105-33 (BBA) (as discussed in
section VI.B.2.a of this final rule). We believe that data from FY 2001
cost reporting periods to determine the applicable wage index values
under the IRF PPS in this final rule are appropriate because these are
the most recent final available data. These data are the same FY 2001
acute care hospital inpatient wage data that were used to compute the
IPPS FY 2005 wage indices. The final IRF wage indices are computed as
follows:
Compute an average hourly wage for each urban and rural
area.
Compute a national average hourly wage.
Divide the average hourly wage for each urban and rural
area by the national average hourly wage--the result is a wage index
for each urban and rural area.
The one-year blended wage index values that are applicable for IRF PPS
discharges occurring on or after October
[[Page 47928]]
1, 2005 and on or before September 30, 2006 are shown in Table 1 of the
addendum of this final rule.
In addition, for this final rule as we proposed in the FY 2006
proposed rule (70 FR 30188), any adjustment or update to the IRF wage
index made as specified under section 1886(j)(6) of the Act will be
made in a budget neutral manner that assures that the estimated
aggregated payments under this subsection in the FY year are not
greater or less than those that will have been made in the year without
such adjustment. Therefore, as we proposed in the FY 2006 proposed rule
(70 FR 30188), for this final rule, we will calculate a budget-neutral
wage adjustment factor as specified in Sec. 412.624(e)(1). We will
continue to use the following steps to ensure that the FY 2006 IRF
standard payment conversion factor reflects the one-year blended FY
2006 MSA and CBSA wage indices (both based on FY 2001 hospital wage
data) and to the labor-related share in a budget neutral manner:
Step 1 Determine the total amount of the estimated FY 2005 IRF PPS
rates using the FY 2005 standard payment conversion factor and the
labor-related share and the wage indices from FY 2005 (as published in
the July 30, 2004 final notice).
Step 2 Calculate the total amount of estimated IRF PPS payments
using the FY 2005 standard payment conversion factor and the updated
CBSA-based FY 2006 labor-related share and FY 2006 blended wage indices
described above.
Step 3 Divide the amount calculated in step 1 by the amount
calculated in step 2, which equals the FY 2006 budget-neutral wage
adjustment factor of 0.9995 (as discussed in section VI.B.7 and
VI.B.8).
Step 4 Apply the FY 2006 budget-neutral wage adjustment factor from
step 3 to the FY 2005 IRF PPS standard payment conversion factor after
the application of the market basket update, described above, to
determine the FY 2006 standard payment conversion factor.
3. Teaching Status Adjustment
In the FY 2006 proposed rule (70 FR 30188), we proposed to
implement a teaching status adjustment for IRFs that are, or are part
of, teaching institutions. Section 1886(j)(3)(A)(v) of the Act requires
the Secretary to adjust the prospective payment rates for the IRF PPS
by such factors as the Secretary determines are necessary to properly
reflect variations in necessary costs of treatment among rehabilitation
facilities. Under this authority, in the August 7, 2001 final rule (66
FR 41316, 41359), we considered implementing an adjustment for IRFs
that are, or are part of, teaching institutions. However, because the
results of our regression analysis, using FY 1999 data, showed that the
indirect teaching cost variable was not significant, we did not
implement a payment adjustment for indirect teaching costs in that
final rule. The regression analysis conducted by RAND for the FY 2006
proposed rule (70 FR 30188), using FY 2003 data, shows that the
indirect teaching cost variable is significant in explaining the higher
costs of IRFs that have teaching programs. Therefore, we proposed to
establish a facility level adjustment to the Federal per discharge base
rate for IRFs that are, or are part of, teaching institutions for the
reasons discussed below (the ``teaching status adjustment'').
The purpose of the proposed teaching status adjustment is to
account for the higher indirect operating costs experienced by
facilities that participate in graduate medical education programs.
We proposed to implement the proposed teaching status adjustment in
a budget neutral manner (that is, keeping estimated aggregate payments
for FY 2006 with the proposed teaching adjustment the same as estimated
aggregate payments for FY 2006 without the proposed teaching
adjustment) for the reasons discussed below. (As a conforming change,
we proposed to revise Sec. 412.624 by adding a new section (e)(4) as
the teaching status adjustment. Specifically, Sec. 412.624(e)(4) would
be for discharges on or after October 1, 2005. We proposed to adjust
the Federal prospective payment on a facility basis by a factor that we
specified for facilities that are teaching institutions or units of
teaching institutions. We proposed that this adjustment be made on a
claim basis as an interim payment and the final payment in full for the
claim would be made during the final settlement of the cost report.
Thus, we proposed to redesignate the current (e)(4) and (e)(5) as
(e)(5) and (e)(6)).
Medicare makes direct graduate medical education (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 the IPPS, and those that were once paid under the TEFRA rate
of increase limits but are now paid under other PPSs. These direct GME
payments are made separately from payments for hospital operating costs
and are not part of the PPSs. However, the direct GME payments may not
address the higher indirect operating costs which may often be
experienced by teaching hospitals. For teaching hospitals paid under
the TEFRA rate-of-increase limits, Medicare did not make separate
medical education payments because payments to these hospitals were
based on the hospitals' reasonable costs. Because payments under TEFRA
were based on hospitals' reasonable costs, the higher indirect costs
that might be associated with teaching programs would automatically
have been factored into the TEFRA payments.
When the IRF PPS was implemented, we did not adjust payments to
IRFs for indirect medical education costs because we did not find that
adjustments for such costs were supported by the regression analyses or
by the impact analyses. As discussed in the August 7, 2001 final rule
(69 FR 41316, 41359), the indirect teaching variable was not
significant for either the fully specified regression or the payment
regression in RAND's analysis. Furthermore, the impacts among the
various classes of facilities reflecting the fully phased-in IRF PPS
illustrated that IRFs with the highest measure of indirect teaching
would lose approximately 2 percent of estimated payments under the IRF
PPS when compared with payments under TEFRA rate-of-increase limits.
These impacts did not account for changes in behavior that facilities
were likely to adopt in response to the inherent incentives of the IRF
PPS, and we believed that IRFs could change their behavior to mitigate
any potential reduction in payments.
The earlier research conducted by RAND was based on 1999 data and
on a sample of IRFs. RAND recently conducted research to support us in
developing potential refinements to the IRF classification system and
the PPS. The regression analysis conducted by RAND for this final rule,
using FY 2003 data, showed that the indirect teaching cost variable is
significant in explaining the higher costs of IRFs that have teaching
programs.
In conducting the analysis on the FY 2003 data, RAND used the
resident counts that were reported on the hospital cost reports
(worksheet S-3, Part 1, line 25, column 9 for freestanding IRF
hospitals and worksheet S-3, Part 1, line 14 (or line 14.01 for
subprovider 2), column 9 for rehabilitation units of acute care
hospitals). That is, for the freestanding rehabilitation hospitals,
RAND used the number of residents and interns reported for the entire
hospital. For the rehabilitation units of acute care hospitals, RAND
used the number of residents and interns reported for the
rehabilitation unit (reported separately
[[Continued on page 47929]]
From the Federal Register Online via GPO Access [wais.access.gpo.gov]
]
[[pp. 47929-47978]] Medicare Program; Inpatient Rehabilitation Facility Prospective
Payment System for FY 2006
[[Continued from page 47928]]
[[Page 47929]]
on the cost report from the number reported for the rest of the
hospital). RAND did not distinguish between different types of resident
specialties, nor did they distinguish among the different types of
services residents provide, because this information is not reported on
the cost reports.
RAND used regression analysis (with the logarithm of costs as the
dependent variable) to re-examine the effect of IRFs' teaching status
on the costs of care. With FY 2003 data that include all Medicare-
covered IRF discharges, RAND found a statistically significant
difference in costs between IRFs with teaching programs and those
without teaching programs in the regression analysis. The different
results obtained using the FY 2003 data (compared with the 1999 data)
may be due to improvements in IRF coding after implementation of the
IRF PPS. More accurately coded data may have allowed RAND to determine
better the differences in case mix among hospitals with and without
teaching programs, which would then have allowed the effect of whether
or not an IRF has a teaching program to become significant in the
regression analysis. There are two main reasons that indirect operating
costs may be higher in teaching hospitals: (1) Because the teaching
activities themselves result in inefficiencies that increase costs, and
(2) because patients needing more costly services tend to be treated
more often in teaching hospitals than in non-teaching hospitals, that
is, the case mix that is drawn to teaching hospitals. Quantifying more
precisely the amount of cost increase that is due to teaching
hospitals' case mix allows RAND to more precisely quantify the amount
of increase due to the inefficiencies associated with a teaching
program.
We proposed to treat the teaching status adjustment as an
additional payment to the Federal prospective payment rate, similar to
the IME payments made under the IPPS (see Sec. 412.105). In addition,
we proposed that the teaching status adjustments for the IRF PPS
facilities would be made on a claim basis as interim payments, but the
final payment in full for the cost reporting period would be made
through the cost report. The difference between those interim payments
and the actual teaching status adjustment amount computed in the cost
report would be adjusted through lump sum payments/recoupments when the
cost report is filed and later settled.
As in the IPF PPS, we proposed to calculate a teaching adjustment
based on the IRF's ``teaching variable,'' which would be one plus the
ratio of the number of FTE residents training in the IRF (subject to
limitations described further below) to the IRF's average daily census
(ADC). In RAND's cost regressions for the FY 2006 proposed rule (70 FR
30188), using data from FY 2003, the logarithm of the teaching variable
had a coefficient value of 1.083. We proposed to convert this cost
effect to a teaching status payment adjustment by treating the
regression coefficient as an exponent and raising the teaching variable
to a power equal to the coefficient value, then estimated at 1.083
(that is, the teaching status adjustment would be calculated by raising
the teaching variable (1 + FTE residents/ADC) to the 1.083 power). For
a facility with a teaching variable of 0.10, and using a coefficient
based upon the coefficient value (1.083) from the FY 2003 data, this
method would yield a 10.9 percent increase in the per discharge
payment; for a facility with a teaching variable of 0.05, the payment
would increase by 5.4 percent. We note that the coefficient value of
1.083 was based on regression analysis holding all other components of
the payment system constant. In the FY 2006 proposed rule (70 FR 30188)
we noted that, because we were proposing a number of other revisions to
the payment system, the coefficient value was subject to change for the
final rule depending on the other revisions included in the final rule.
Moreover, we noted that we had concerns that IRFs' responses to other
proposed changes described in the FY 2006 proposed rule (70 FR 30188)
would influence the effects of a teaching variable on IRFs' costs.
In addition, we proposed that the teaching adjustment limit the
incentives for IRFs to add FTE residents for the purpose of increasing
their teaching adjustment, as has been done in the payment systems for
psychiatric facilities and acute inpatient hospitals. Thus, we proposed
to impose a cap on the number of FTE residents that may be counted for
purposes of calculating the teaching adjustment, similar to that
established by sections 4621 (IME FTE cap for IPPS hospitals) and 4623
(direct GME FTE cap for all hospitals) of the BBA. We noted that the
FTE resident cap already applies to teaching hospitals, including IRFs,
for purposes of direct GME payments as specified in Sec. 413.75
through Sec. 413.83. The proposed cap would limit the number of
residents that teaching hospitals may count for the purposes of
calculating the IRF PPS teaching status adjustment, not the number of
residents teaching institutions can hire or train.
The proposed FTE resident cap would be identical in freestanding
teaching rehabilitation hospitals and in distinct part rehabilitation
units with GME programs. Similar to the regulations for counting FTE
residents under the IPPS as described in Sec. 412.105(f), we proposed
to calculate a number of FTE residents that trained in the IRF during a
``base year'' and use that FTE resident number as the cap. An IRF's FTE
resident cap would ultimately be determined based on the final
settlement of the IRF's most recent cost reporting period ending on or
before November 15, 2003. We also proposed that, similar to new IPPS
teaching hospitals, IRFs that first begin training residents after
November 15, 2003 would initially receive an FTE cap of ``0''. The FTE
caps for new IRFs (as well as existing IRFs) that start training
residents in a new GME program (as defined in Sec. 413.79(l)) may be
subsequently adjusted in accordance with the policies that are being
applied in the IPF PPS (as described in Sec.
412.424(d)(1)(iii)(B)(2)), which in turn are made in accordance with
the policies described in 42 CFR 413.79(e) for IPPS hospitals. However,
contrary to the policy for IME FTE resident caps under the IPPS, we
would not allow IRFs to aggregate the FTE resident caps used to compute
the IRF PPS teaching status adjustment through affiliation agreements.
We proposed these policies because we believe it is important to limit
the total pool of resident FTE cap positions within the IRF community
and avoid incentives for IRFs to add FTE residents in order to increase
their payments. In proposing not to allow affiliation agreements, we
also wanted to avoid the possibility of hospitals transferring
residents between IPPS and IRF training settings in order to increase
Medicare payments. We recognize that under the regulations applicable
to the IPPS IME adjustment, a new teaching hospital that trains
residents from an existing program (not a new program as defined in 42
CFR 413.79(l)) can receive an adjustment to its IME FTE cap by entering
into a Medicare GME affiliation agreement (see Sec. 412.105(f)(1)(vi),
Sec. 413.75(b), and Sec. 413.79(f)) with other hospitals. However,
this option would not be available to new teaching IRFs because, as
noted above, we proposed not to allow IRFs to aggregate the FTE
resident caps used to compute the IRF PPS teaching adjustment through
affiliation agreements.
We also proposed that residents with less than full-time status and
residents rotating through the rehabilitation hospital or unit for less
than a full year
[[Page 47930]]
be counted in proportion to the time they spend in their assignment
with the IRF (for example, a resident on a full-time, 3-month rotation
to the IRF would be counted as 0.25 FTEs for purposes of counting
residents to calculate the ratio). No FTE resident time counted for
purposes of the IPPS IME adjustment would be allowed to be counted for
purposes of the teaching status adjustment for the IRF PPS.
We proposed that the denominator used to calculate the teaching
status adjustment under the IRF PPS would be the IRF's average daily
census (ADC) from the current cost reporting period because it is
closely related to the IRF's patient load, which determines the number
of interns and residents the IRF can train. We also believe the ADC is
a measure that can be defined precisely and is difficult to manipulate.
Although the IPPS IME adjustment uses the hospital's number of beds as
the denominator, the capital PPS (as specified at Sec. 412.322) and
the IPF PPS (as specified at Sec. 412.424) both use the ADC as the
denominator for the indirect graduate medical education adjustments.
If a rehabilitation hospital or unit has more FTE residents in a
given year than in the base year (the base year being used to establish
the cap), we would base payments in that year on the lower number (the
cap amount). This approach would be consistent with the IME adjustment
under the IPPS and the IPF PPS. The IRF would be free to add FTE
residents above the cap amount, but it would not be allowed to count
the number of FTE residents above the cap for purposes of calculating
the teaching adjustment. This means that the cap would be an upper
limit on the number of FTE residents that may be counted for purposes
of calculating the teaching status adjustment. IRFs could adjust their
number of FTE residents counted for purposes of calculating the
teaching adjustment as long as they remained under the cap.
On the other hand, if a rehabilitation hospital or unit were to
have fewer FTE residents in a given year than in the base year (that
is, fewer residents than its FTE resident cap), an adjustment in
payments in that year would be based on the lower number (the actual
number of FTE residents the facility hires and trains). We proposed to
implement the teaching status adjustment in such a way that total
estimated aggregate payments to IRFs for FY 2006 would be the same with
and without the proposed adjustment (that is, in a budget neutral
manner). This is because we believe that the results of RAND's analysis
of 2002 and 2003 IRF cost data suggest that additional money does not
need to be added to the IRF PPS. RAND's analysis found, for example,
that if all IRFs had been paid based on 100 percent of the IRF PPS
payment rates throughout all of 2002 (some IRFs were still
transitioning to PPS payments during 2002), PPS payments during 2002
would have been 17 percent higher than IRFs' costs. We noted that we
were open to examining other evidence regarding the amount of aggregate
payments in the system.
An adjustment to payments based on an IRF's teaching status is
consistent with section 1886 (j)(3)(A)(v) of the Act, which confers
broad statutory authority upon the Secretary to adjust the per payment
unit payment rate by such factors as the Secretary determines are
necessary to properly reflect variations in necessary costs of
treatment among rehabilitation facilities.
In the FY 2006 proposed rule, we discussed some concerns we had
with implementing a teaching status adjustment at this time, including
concerns about the volatility of the data, concerns about the effect
that other proposed changes could have on the magnitude of the teaching
status adjustment, and concerns about the best way to count residents
who provide services to IRF patients. These concerns are described in
more detail in the FY 2006 proposed rule (70 FR 30188). As a result of
these concerns, we specifically solicited comments on our consideration
of a teaching status adjustment.
Public comments and our responses on the proposed teaching status
adjustment are summarized below.
Comment: Several commenters questioned CMS's rationale for not
allowing affiliation agreements, if CMS is only concerned about not
increasing the pool of residents in IRFs. One commenter suggested that
allowing affiliation agreements among IRFs would not necessarily
increase the total pool of residents in IRFs.
Response: In the FY 2006 proposed rule (70 FR 30188), we stated
that we are not allowing IRFs to enter into affiliation agreements with
IPPS hospitals for the purposes of aggregating the FTE resident caps
because we want to avoid the possibility that hospitals will transfer
residents between IPPS and IRF training settings in order to increase
Medicare payments. In deciding on our proposal not to allow affiliation
agreements under the IRF PPS, we considered several factors. First, in
general, we considered that IPPS hospitals provide training to
residents in a wide range of specialties. Because of the wide variety
of training provided, IPPS hospitals often need to send residents to
train at other hospitals, since the case mix of one hospital might not
be sufficiently broad to provide residents with an acceptable range of
training opportunities in a particular specialty. The broad nature of
the training offered at IPPS hospitals, and hence, the need to cross-
train residents, is a primary reason for permitting IPPS hospitals
under the Balanced Budget Act of 1997 to enter into GME affiliation
agreements with other IPPS hospitals. However, because IRFs are a
highly specialized type of provider, we do not believe that a
significant amount of cross-training is required among IRFs. Although
we imagine that there could be instances in which residents training in
one IRF could receive a different type of training experience in
another IRF, we believe these situations are likely to be limited and
do not warrant having an affiliation agreement policy to allow IRFs to
aggregate their FTE resident caps for the teaching status adjustment.
Furthermore, we note that even without a specific affiliations policy,
IRFs are not precluded from cross-training residents amongst themselves
or with IPPS hospitals. If cross-training is necessary, it can be done
in such a way that the overall number of FTE residents training in each
facility remains unchanged. Accordingly, we are finalizing our proposed
policy to not create a specific GME affiliation provision for the IRF
teaching status adjustment. In the future, if we find there is in fact
a need to allow affiliation agreements among IRFs, we may consider
revising this policy in a future rulemaking process.
Comment: Several commenters noted possible inaccuracies in the
teaching status information for a few of the facilities in the rate
setting file we posted on the CMS website in conjunction with the FY
2006 proposed rule (70 FR 30188).
Response: To clarify, the rate setting file posted on the CMS
website will not be used to determine payments for providers. The
fiscal intermediaries use their own data files to determine whether the
IRFs under their responsibility qualify for teaching status adjustment
payments and the amounts of any such payments. Therefore, if providers
have concerns about their particular teaching status data, they should
contact their fiscal intermediaries to ensure that the fiscal
intermediaries have the correct information.
With regard to the information in the rate setting file posted on
the CMS website, this information was used to compute the value of the
coefficient used as the exponent in the formula for
[[Page 47931]]
the proposed teaching status adjustment. Consequently, we asked RAND to
investigate the accuracy of the information. RAND has made the
appropriate corrections to the information and, using the revised
information, has recomputed the coefficient used as the exponent. Based
on this and the incorporation of the HealthSouth home office cost data
from FY 2004 (as described in detail in section IV of this final rule),
we have revised the exponent from 1.083, which is what we had proposed
in the FY 2006 proposed rule (70 FR 30188), to 0.9012 for this final
rule.
Comment: Several commenters objected to our proposal to implement
the proposed teaching adjustment based on analysis of one year of data.
However, several other commenters suggested that such concerns were
unfounded and did not warrant overriding RAND's statistically valid
findings.
Response: Since publication of the FY 2006 proposed rule (70 FR
30188), RAND has further analyzed FY 2002 and FY 2003 data, and has
found that the teaching status variable is significantly related to
costs in both sets of data. Furthermore, we believe that IRFs with
teaching programs may have been underrepresented in the 1998 and 1999
data used to construct the IRF PPS, and that this may have contributed
to the lack of a statistically significant finding using the pre-PPS
data. In addition, the statistically significant difference in costs
between teaching and non-teaching facilities has been validated in
other inpatient settings, including IPPS hospitals and IPFs. Therefore,
we are reassured that this result does not represent an aberration
based on only a single year's data, but instead represents a result of
using more recent, more complete data. However, we will continue to
evaluate the need for this adjustment in the future. If we later find
that the other refinements described in this final rule constitute
enough of an improvement to the system by more appropriately accounting
for the variation in costs among different types of IRF patients that
the teaching status adjustment becomes unnecessary, we will consider
eliminating the adjustment in the future. However, we believe there is
enough evidence at this time that IRFs with teaching programs have
higher costs to implement the adjustment.
Comment: One commenter requested that CMS change the data that will
be used to establish the FTE resident cap for IRFs from our proposal to
use IRFs' most recent cost reporting periods ending on or before
November 15, 2003, to use IRFs' most recent cost reporting periods
ending on or before November 15, 2004 to ensure that the FTE resident
caps will be based on the most accurate historical resident count data
possible.
Response: We agree with this commenter and are revising our
methodology for setting the FTE resident cap accordingly. Since we
published the FY 2006 proposed rule (70 FR 30188), the FTE resident cap
used for the teaching status adjustment for IPFs has been set similarly
based on cost reporting periods ending on or before November 15, 2004.
We believe this change is appropriate and maintains consistency within
the Medicare program.
Comment: One commenter requested that CMS have a process in place
for re-examining the teaching status data, especially the data used to
set the FTE resident cap, so that facilities would have the opportunity
to rectify any problems with the data that might affect payments.
Response: We agree with this commenter. We recognize that there may
be problems with some of the resident count data on the historical cost
reports, since this data has not previously been used for payment
adjustments in the IRF PPS. For this reason, we proposed in the FY 2006
proposed rule (70 FR 30188) that an IRF's FTE resident cap would
ultimately be determined based on the final settlement of the IRF's
most recent cost reporting period ending on or before November 15, 2003
and, based on this and the previous comment (refer to the response
above), we are changing this to the final settlement of the IRF's most
recent cost reporting period ending on or before November 15, 2004. We
believe this will allow facilities the opportunity to ensure the
accuracy of the FTE resident count data before the final settlement of
the cost report data. In case this does not occur, we will authorize
the fiscal intermediaries to resolve any disputes that may occur
regarding the data used to set an IRF's FTE resident cap and correct
any inaccuracies.
With regard to the FTE resident count data or the average daily
census data used to compute an IRF's teaching status adjustment, we
specifically note in this final rule that any teaching status
adjustments for the IRF PPS facilities will be made on a claim basis as
interim payments, but the final payments in full for the cost reporting
periods will be made through the final settlement of the cost report.
The difference between the interim payments and the actual teaching
status adjustment amounts computed in the cost reports will be adjusted
through lump sum payments/recoupments when the cost report is filed and
later settled. We believe this process gives providers and fiscal
intermediaries ample opportunity to ensure that the data used to
compute the teaching status adjustment payments is as complete and
accurate as possible. As the proposed teaching status adjustment is
implemented, we will monitor the situation and issue further guidance
to the fiscal intermediaries as necessary to ensure fair and accurate
payments for this adjustment.
Comment: The majority of commenters expressed support for CMS
eventually implementing an IRF teaching status adjustment, especially
since teaching IRFs were likely underrepresented in the 1998 and 1999
data used in the August 7, 2001 final rule to design the IRF PPS.
However, while supporting the adjustment, several commenters suggested
that CMS wait to implement a teaching status adjustment for at least a
year, until data from FY 2004 (or later) can be analyzed.
Response: CMS considered carefully the suggestion to wait an
additional year or more before implementing the proposed teaching
status adjustment. However, RAND's regression analyses of calendar year
2002 and FY 2003 data both support the need for a teaching status
adjustment for IRFs because they both indicate that IRFs with teaching
programs have significantly higher costs than IRFs without teaching
programs. Given RAND's findings, we believe it is important to adjust
IRF payments accordingly in order to better align IRF payments with the
costs of care. In addition, we believe it is important to maintain
consistency with other parts of the Medicare program, such as the IPF
PPS that recently instituted a teaching status adjustment for IPFs
based on regression analysis that shows that IPFs with teaching
programs have significantly higher costs than IPFs without teaching
programs.
Comment: Several commenters strongly disagreed with the proposed
implementation of a teaching status adjustment for IRFs. Among the
reasons cited were that it was based on analysis of a single year of
data, that it would support inefficiencies in teaching hospitals (when
the purpose of a PPS is to encourage providers to operate efficiently),
that the data do not adequately support the need for a teaching status
adjustment, that it would reduce payments to non-teaching hospitals,
and that teaching hospitals would likely continue to operate even if
they do not receive the adjustment.
Response: We carefully considered these comments. However, we
continue
[[Page 47932]]
to believe that an IRF teaching status adjustment is warranted at this
time because RAND's regression analysis, based on calendar year 2002
and FY 2003 data shows that IRFs with teaching programs have
significantly higher costs than non-teaching IRFs. Although we do not
believe it is appropriate to encourage or perpetuate inefficiencies, we
believe that IRFs with teaching programs provide a valuable service to
beneficiaries and to the Medicare program. To the extent that the
residency training services, therefore, lead to higher indirect costs
of providing care, we believe it is important to recognize these
differences and encourage access to care in these facilities. While, as
one commenter notes, teaching IRFs more than likely would continue to
operate even without the IRF teaching status adjustment, the intent of
the adjustment is to better align payments in these facilities with the
costs of care.
Furthermore, we believe that IRFs with teaching programs may have
been underrepresented in the 1998 and 1999 data used to construct the
IRF PPS, and that this may have contributed to the lack of a
statistically significant finding using the pre-PPS data. In addition,
the statistically significant difference in costs between teaching and
non-teaching facilities has been validated in other inpatient settings,
including IPPS hospitals and IPFs.
We proposed, and are finalizing in this final rule, to implement
the IRF teaching status adjustment in a budget neutral manner in order
to ensure that estimated aggregate payments to IRFs for FY 2006 will be
the same with or without the teaching status adjustment. Given that the
impact on IRFs without teaching programs of this provision is not large
(see Table 13 of this final rule), we do not believe that implementing
the teaching status adjustment in a budget neutral manner will unduly
affect non-teaching IRFs. However, the teaching status adjustment will
help to better align payments with the costs of care in teaching IRFs.
Furthermore, we believe that a teaching status adjustment for IRFs
is consistent with the teaching status adjustment recently implemented
in the IPF PPS.
Comment: One commenter suggested that CMS track the percentage of
time residents spend in the rehabilitation unit of the hospital to
compute the teaching adjustment, instead of using the resident and
intern to ADC ratio we proposed in the proposed rule.
Response: This information is not currently captured in the cost
report data, which would make this suggestion substantially more
difficult to implement than the teaching status variable we proposed in
the FY 2006 proposed rule (70 FR 30188). We also believe that
collecting this type of information would impose additional costs on
acute care hospitals that have IRF units, because they would be
required to record the amount of time residents spend on rehabilitation
units. We also believe that it would be difficult if not impossible to
audit this type of information.
Comment: One commenter suggested that CMS focus the teaching
adjustment on rehabilitation education programs, to the exclusion of
other resident training programs.
Response: Information on resident specialties is not currently
reported in the cost report data. We believe that collecting and
reporting this new type of data would impose undue additional costs on
IRFs and on hospitals that have IRF units. Furthermore, we believe that
this policy would contradict the way that residency programs
traditionally operate because they require residents from different
specialties to rotate in different areas of the hospital to gain
experience in various areas of medicine.
Comment: One commenter recommended that an exception process be
allowed to enable IRF teaching programs to apply for an increase in
their cap should a compelling reason arise, such as an expansion of the
teaching hospital or unit or the addition of a new program.
Response: Similar to the GME resident cap policy for IPPS
hospitals, we will not allow exceptions to the FTE resident caps for
IRFs due to expansions of existing facilities or additions of new
teaching programs. As we indicated previously, we believe it is
important to limit the total pool of FTE resident cap positions within
the IRF community.
Final Decision: After carefully considering all of the comments we
received on the proposed IRF teaching status adjustment, we are
finalizing our decision to adopt the proposed policy in this final
rule, with the following revisions.
In RAND's most recent cost regressions using data from FY 2003,
including the HealthSouth home office cost data from FY 2004 (as
described in detail in section IV of this final rule), the logarithm of
the teaching variable has a coefficient value of 0.9012 (as opposed to
the coefficient value of 1.083 we proposed in the FY 2006 proposed rule
(70 FR 30188)). In the final policy, we are converting this cost effect
to a teaching status payment adjustment by treating the regression
coefficient as an exponent and raising the teaching variable to a power
equal to the coefficient value of 0.9012 (that is, the teaching status
adjustment would be calculated by raising the teaching variable (1 +
FTE residents/ADC) to the 0.9012 power).
Secondly, based on a commenter's suggestion, we are changing the
base period for determining an IRF's FTE resident cap from the final
settlement of the IRF's most recent cost reporting period ending on or
before November 15, 2003, which was what we had proposed in the FY 2006
proposed rule (70 FR 30188), to the final settlement of the IRF's most
recent cost reporting period ending on or before November 15, 2004.
Thus, the policy in the IRF PPS would be consistent with the FTE
resident cap policy in the IPF PPS.
4. Adjustment for Rural Location
In the FY 2006 proposed rule (70 FR 30188), we proposed to update
the adjustment to the Federal prospective payment amount for IRFs
located in rural areas from 19.14 percent to 24.1 percent, based on
analysis of FY 2003 data. Consistent with the broad statutory authority
conferred upon the Secretary in section 1886(j)(3)(A)(v) of the Act, we
adjust the Federal prospective payment amount associated with a CMG to
account for an IRF's geographic wage variation, low-income patients
and, if applicable, teaching status and location in a rural area, as
described in Sec. 412.624(e).
Under the broad statutory authority conferred upon the Secretary in
section 1886(j)(3)(A)(v) of the Act, we proposed to increase the
adjustment to the Federal prospective payment amount for IRFs located
in rural areas from 19.14 percent to 24.1 percent. We proposed this
change because RAND's regression analysis, using the best available
data we had (FY 2003), indicated that rural facilities had 24.1 percent
higher costs of caring for Medicare patients than urban facilities. We
noted that we proposed to use the same statistical approach, as
described in the November 3, 2000 proposed rule (65 FR 66304, 66356
through 66357) and adopted in the August 7, 2001 final rule (66 FR at
41359) to estimate the proposed update to the rural adjustment. The
statistical approach RAND used when the PPS was first implemented, for
the FY 2006 proposed rule (70 FR 30188), and for this final rule relies
on the coefficient determined from the regression analysis. The 19.14
percent rural adjustment has been applied to payments for IRFs located
in rural areas since the implementation of the IRF PPS. We noted that
the FY 2003 data are the best available data we have, just as the 1998
[[Page 47933]]
and 1999 data used in the initial development of the IRF PPS were the
best available data at that time.
We proposed to implement the proposed update to the rural
adjustment so that total estimated aggregate payments for FY 2006 are
the same with the proposed update to the adjustment as they would have
been without the proposed update to the adjustment (that is, in a
budget neutral manner). We proposed to make this update to the rural
adjustment in a budget neutral manner because we believed and continue
to believe that the results of RAND's analysis of 2002 and 2003 IRF
cost data (as discussed previously in section IV of this final rule)
suggest that additional money does not need to be added to the IRF PPS.
RAND's analysis found, for example, that if all IRFs had been paid
based on 100 percent of the IRF PPS payment rates throughout all of
2002 (some IRFs were still transitioning to PPS payments during 2002),
PPS payments during 2002 would have been 17 percent higher than IRFs'
costs.
This is consistent with section 1886(j)(3)(A)(v) of the Act which
confers broad statutory authority upon the Secretary to adjust the per
payment unit payment rate by such factors as the Secretary determines
are necessary to properly reflect variations in necessary costs of
treatment among rehabilitation facilities. To ensure that total
estimated aggregate payments to IRFs do not change, we proposed to
apply a factor to the standard payment amount to ensure that the
estimated aggregate payments under this subsection in the FY are not
greater or less than those that would have been made in the year
without the proposed update to the adjustment. In sections VI.B.7 and
VI.B.8 of this final rule, we discuss the methodology and factor we
proposed to apply to the standard payment amount.
Public comments and our responses on the proposed update to the
rural adjustment are summarized below.
Comment: Overall, commenters generally supported this proposal.
Some said that CMS should delay implementing the proposal until the
full effects of the 75 percent rule can be analyzed.
Response: For the reasons discussed in section IV of this final
rule, we do not believe we should wait until the full effects of the 75
percent rule can be analyzed before implementing any of the proposed
changes in this final rule. Making the changes now does not preclude us
from making additional revisions in the future if we find any potential
effects of the 75 percent rule on IRFs' case mix or cost structures
that would warrant such refinements.
Comment: One commenter expressed concerns that the proposed
increases to the facility-level adjustments would encourage
inefficiencies in the provision of care.
Response: While we agree with the commenter that one of the
purposes of a PPS is to encourage the efficient provision of services,
we also believe it is important to recognize that certain providers,
such as those operating in rural areas, may incur higher costs than
other providers, for reasons largely beyond their control. To encourage
the efficient provision of care in rural areas, so that Medicare
beneficiaries have adequate access to IRF services in these areas, we
believe it is important to recognize the differential in costs between
urban and rural providers.
Final Decision: After carefully considering all of the comments we
received on this proposed change to the rural adjustment, we are
finalizing our decision to adopt the update to the rural adjustment in
this final rule, with the following change.
In RAND's most recent cost regressions using data from FY 2003,
including the HealthSouth home office cost data from FY 2004 (as
described in detail in section IV of this final rule), rural facilities
were found to have 21.3 percent higher costs of caring for Medicare
patients than urban facilities (rather than the 24.1 percent we
proposed in the FY 2006 proposed rule (70 FR 30188)). Thus, we are
implementing a rural adjustment of 21.3 percent.
5. Adjustment for Disproportionate Share of Low-Income Patients
In the FY 2006 proposed rule (70 FR 30188), we proposed to update
the low-income patient (LIP) adjustment to the Federal prospective
payment rate, based on analysis of FY 2003 data. Consistent with the
broad statutory authority conferred upon the Secretary in section
1886(j)(3)(A)(v) of the Act, we adjust the Federal prospective payment
amount associated with a CMG to account for an IRF's geographic wage
variation, low-income patients and, if applicable, teaching status and
location in a rural area, as described in Sec. 412.624(e).
Under the broad statutory authority conferred upon the Secretary in
section 1886(j)(3)(A)(v) of the Act, we proposed to update the low-
income patient (LIP) adjustment to the Federal prospective payment rate
to account for differences in costs among IRFs associated with
differences in the proportion of low-income patients they treat. RAND's
regression analysis of 2003 data indicates that the LIP formula could
be updated to better distribute current payments among facilities
according to the proportion of low-income patients they treat. Although
the formula used prior to October 1, 2005 appropriately distributed
LIP-adjusted payments among facilities when the IRF PPS was first
implemented, we believe the formula should be updated from time to time
to reflect changes in the costs of caring for low-income patients.
The proposed LIP adjustment is based on the formula used to account
for the costs of furnishing care to low-income patients as discussed in
the August 7, 2001 final rule (67 FR at 41360). We proposed to update
the LIP adjustment from the power of 0.4838 to the power of 0.636.
Therefore, the formula we proposed to use to calculate the LIP
adjustment was as follows:
(1 + DSH patient percentage) raised to the power of (0.636)
[GRAPHIC] [TIFF OMITTED] TR15AU05.000
We note that we proposed to use the same statistical approach, as
described in the August 7, 2001 final rule (66 FR at 41359 through
41360), that was used to develop the original LIP adjustment. We note
that the FY 2003 data we proposed to use in calculating this adjustment
are the best available data, just as the 1998 and 1999 data used in the
initial development of the IRF PPS were the best available data at that
time.
We proposed to implement this update to the LIP adjustment so that
total estimated aggregate payments for FY 2006 would be the same with
the proposed update to the adjustment as they would have been without
the update to the adjustment (that is, in a budget neutral manner). We
proposed to make this proposed update to the LIP adjustment in a budget
neutral manner because we believed and continue to believe that the
results of RAND's analysis of 2002 and 2003 IRF cost data (as discussed
previously in this final rule) suggest that additional money does not
need to be added to the IRF PPS.
[[Page 47934]]
RAND's analysis found, for example, that if all IRFs had been paid
based on 100 percent of the IRF PPS payment rates throughout all of
2002 (some IRFs were still transitioning to PPS payments during 2002),
PPS payments during 2002 would have been 17 percent higher than IRFs'
costs.
This is consistent with section 1886 (j)(3)(A)(v) of the Act which
confers broad statutory authority upon the Secretary to adjust the per
payment unit payment rate by such factors as the Secretary determines
are necessary to properly reflect variations in necessary costs of
treatment among rehabilitation facilities. To ensure that total
estimated aggregate payments to IRFs do not change, we proposed to
apply a factor to the standard payment amount to ensure that the
estimated aggregate payments under this subsection in the FY are not
greater or less than those that would have been made in the year
without the proposed update to the adjustment. In sections VI.B.7 and
VI.B.8 of this final rule, we discuss the methodology and factor we
proposed to apply to the standard payment amount.
Public comments and our responses on the proposed update to the LIP
adjustment are summarized below.
Comment: Overall, commenters generally supported this proposal.
Some said that CMS should delay implementing the proposal until the
full effects of the 75 percent rule can be analyzed.
Response: For the reasons discussed in section IV of this final
rule, we do not believe we should wait until the full effects of the 75
percent rule can be analyzed before implementing any of the proposed
changes in this final rule. Making the changes now does not preclude us
from making additional revisions in the future if we find any potential
effects of the 75 percent rule on IRFs' case mix or cost structures
that would warrant such refinements.
Comment: One commenter expressed concerns that the proposed
increases to the facility-level adjustments would encourage
inefficiencies in the provision of care.
Response: While we agree with the commenter that one of the
purposes of a PPS is to encourage the efficient provision of services,
we also believe it is important to recognize that certain providers,
such as those providers that treat a higher proportion of low-income
patients, may incur higher costs than other providers, for reasons
largely beyond their control. To encourage the efficient provision of
care among providers that treat a large number of low-income patients,
so that low-income Medicare beneficiaries have adequate access to IRF
services, we believe it is important to recognize the higher costs
these providers incur.
Final Decision: After carefully considering all of the comments we
received on this proposed change to the LIP adjustment, we are
finalizing our decision to adopt the proposed policy in this final
rule, with the following change.
Based on RAND's most recent cost regressions using data from FY
2003, including the HealthSouth home office cost data from FY 2004 (as
described in detail in section IV of this final rule), we are updating
the LIP adjustment to the power of 0.6229 (rather than the value of
0.636 we proposed in the FY 2006 proposed rule (70 FR 30188)).
Therefore, the formula for calculating the LIP adjustment will be as
follows: (1 + DSH patient percentage) raised to the power of (0.6229)
where the DSH patient percentage =
[GRAPHIC] [TIFF OMITTED] TR15AU05.001
6. Update to the Outlier Threshold Amount
In the FY 2006 proposed rule (70 FR 30188), we proposed to update
the outlier threshold amount, based on analysis of FY 2003 data.
Consistent with the broad statutory authority conferred upon the
Secretary in sections 1886(j)(4)(A)(i) and 1886(j)(4)(A)(ii) of the
Act, we proposed to update the outlier threshold amount from the
$11,211 threshold amount for FY 2005 to $4,911 in FY 2006 to maintain
total estimated outlier payments at 3 percent of total estimated
payments. In the August 7, 2001 final rule, we discussed our rationale
for setting estimated outlier payments at 3 percent of total estimated
payments (66 FR at 41362). In the FY 2006 proposed rule (70 FR 30188),
we proposed to continue using 3 percent for the same reasons outlined
in the August 7, 2001 final rule. We believed and continue to believe
that it is necessary to update the outlier threshold amount because
RAND's analysis of the calendar year 2002 and FY 2003 data indicates
that total estimated outlier payments will not equal 3 percent of total
estimated payments in FY 2006 unless we update the outlier loss
threshold. We will continue to analyze the estimated outlier payments
for subsequent years and adjust as appropriate in order to maintain
estimated outlier payments at 3 percent of total estimated payments.
The reasons for estimated outlier payments not equaling 3 percent of
total estimated payments are discussed in more detail below.
Section 1886(j)(4) of the Act provides the Secretary with the
authority to make payments in addition to the basic IRF prospective
payments for cases incurring extraordinarily high costs. In the August
7, 2001 final rule, we codified at Sec. 412.624(e)(4) of the
regulations (which we proposed to redesignate as Sec. 412.624(e)(5) in
the FY 2006 proposed rule (70 FR 30188)) the provision to make an
adjustment for additional payments for outlier cases that have
extraordinarily high costs relative to the costs of most discharges.
Providing additional payments for outliers strongly improves the
accuracy of the IRF PPS in determining resource costs at the patient
and facility level because facilities receive additional compensation
over and above the adjusted Federal prospective payment amount for
uniquely high-cost cases. These additional payments reduce the
financial losses that would otherwise be caused by treating patients
who require more costly care and, therefore, reduce the incentives to
underserve these patients.
Under Sec. 412.624(e)(4) (which we proposed to redesignate as
Sec. 412.624(e)(5) in the FY 2006 proposed rule (70 FR 30188)), we
would make outlier payments for any discharges if the estimated cost of
a case exceeds the adjusted IRF PPS payment for the CMG plus the
adjusted threshold amount. In the FY 2006 proposed rule (70 FR 30188),
we proposed to make this $4,911, which would then be adjusted for each
IRF by the facility's wage adjustment, its LIP adjustment, its rural
adjustment, and its teaching status adjustment, if applicable. In the
FY 2006 proposed rule (70 FR 30188), we stated that we would calculate
the estimated cost of a case by multiplying the IRF's overall cost-to-
charge ratio by the Medicare allowable covered charge. In accordance
with Sec. 412.624(e)(4) (which we proposed in the FY 2006 proposed
rule (70 FR 30188) to
[[Page 47935]]
redesignate as Sec. 412.624(e)(5)), we also stated that we would pay
outlier cases 80 percent of the difference between the estimated cost
of the case and the outlier threshold (the sum of the adjusted IRF PPS
payment for the CMG and the adjusted fixed threshold dollar amount).
Consistent with the broad statutory authority conferred upon the
Secretary in sections 1886(j)(4)(A)(i) and 1886(j)(4)(A)(ii) of the
Act, and in accordance with the methodology stated in the August 1,
2003 final rule (68 FR at 45692 through 45693), we proposed in the FY
2006 proposed rule (70 FR 30188) to continue to apply a ceiling to an
IRF's cost-to-charge ratios (CCR). Also, in the August 1, 2003 final
rule (68 FR at 45693 through 45694), we stated the methodology we use
to adjust IRF outlier payments and the methodology we use to make these
adjustments. We indicated that the methodology is codified in Sec.
412.624(e)(4) (which we proposed in the FY 2006 proposed rule (70 FR
30188) to redesignate as Sec. 412.624(e)(5)) and Sec. 412.84(i)(3).
On February 6, 2004, we issued manual instructions in Change
Request 2998 stating that we would set forth the upper threshold
(ceiling) and the national CCRs applicable to IRFs in each year's
annual notice of prospective payment rates published in the Federal
Register. The upper threshold CCR for IRFs that we proposed in the FY
2006 proposed rule (70 FR 30188) for FY 2006 would be 1.52 based on
CBSA-based geographic designations. We proposed to base this upper
threshold CCR on the CBSA-based geographic designations because the
CBSAs are the geographic designations we proposed in the FY 2006
proposed rule (70 FR 30188) to adopt for purposes of computing the
proposed wage index adjustment to IRF payments for FY 2006.
In addition, in the FY 2006 proposed rule (70 FR 30188), we
proposed to update the national urban and rural CCRs for IRFs. Under
Sec. 412.624(e)(4) (which we proposed in the FY 2006 proposed rule (70
FR 30188) to redesignate as Sec. 412.624(e)(5)) and Sec.
412.84(i)(3), we proposed to apply the national CCRs to the following
situations:
New IRFs that have not yet submitted their first Medicare
cost report.
IRFs whose operating or capital CCR is in excess of 3
standard deviations above the corresponding national geometric mean.
Other IRFs for whom accurate data with which to calculate
either an operating or capital CCR (or both) are not available.
In the FY 2006 proposed rule (70 FR 30188), we proposed to use the
national CCR based on the facility location of either urban or rural in
each of the three situations cited above. Specifically, for FY 2006, we
estimated a proposed national CCR of 0.631 for rural IRFs and 0.518 for
urban IRFs. For new facilities, we proposed to use these national
ratios until the facility's actual CCR could be computed using the
first tentative settled or final settled cost report data, which would
then be used for the subsequent cost report period.
In the August 7, 2001 final rule (66 FR at 41362 through 41363), we
describe the process by which we calculate the outlier threshold. In
the FY 2006 proposed rule (70 FR 30188), we proposed to use this same
process for the FY 2006 IRF PPS. We proposed to simulate aggregate
payments with and without an outlier policy, and then apply an
iterative process to determine a threshold that would result in the
simulated outlier payments being equal to 3 percent of total simulated
payments under the simulation. In the FY 2006 proposed rule (70 FR
30188), we noted that the simulation analysis used to calculate the
proposed outlier threshold amount included all of the other proposed
changes to the PPS discussed in the FY 2006 proposed rule (70 FR
30188). As stated in the FY 2006 proposed rule (70 FR 30188), we
proposed to continue to analyze the estimated outlier payments for
subsequent years and adjust as appropriate in order to maintain
estimated outlier payments at 3 percent of total estimated payments.
In the FY 2006 proposed rule (70 FR 30188), we proposed to update
the threshold amount so that estimated outlier payments would continue
to equal 3 percent of total estimated payments under the IRF PPS. RAND
found that 2002 outlier payments were equal to 3.1 percent of total
payments in 2002. Nevertheless, the outlier loss threshold is affected
by cost-to-charge ratios because the cost-to-charge ratios are used to
compute the estimated cost of a case, which in turn is used to
determine if a particular case qualifies for an outlier payment or not.
For example, if the cost-to-charge ratio decreases, then the estimated
costs of a case with the same reported charges would decrease. Thus,
the chances that the case would exceed the outlier loss threshold and
qualify for an outlier payment would decrease, decreasing the
likelihood that the case would qualify for an outlier payment. If fewer
cases were to qualify for outlier payments, then total estimated
outlier payments could fall below 3 percent of total estimated
payments.
As we discussed in the FY 2006 proposed rule (70 FR 30188), our
analyses of cost report data from FY 1999 through FY 2002 (and
projections for FY 2004 through FY 2006) indicate that the overall
cost-to-charge ratios in IRFs have been falling since the IRF PPS was
implemented. We are still analyzing possible reasons for this finding.
However, because cost-to-charge ratios are used to determine whether a
particular case qualifies for an outlier payment, this drop in the
cost-to-charge ratios is likely responsible for much of the drop in
total estimated outlier payments below 3 percent of total estimated
payments. Thus, as we discussed in the FY 2006 proposed rule (70 FR
30188), the outlier threshold would need to be lowered for FY 2006 in
order that total estimated outlier payments would equal 3 percent of
total estimated payments.
In addition, we proposed in the FY 2006 proposed rule (70 FR 30188)
to adjust the outlier threshold for FY 2006 because RAND's analysis of
calendar year 2002 and FY 2003 data indicates that many of the other
proposed changes discussed in the FY 2006 proposed rule (70 FR 30188)
would affect what the outlier threshold would need to be in order for
total estimated outlier payments to equal 3 percent of total estimated
payments. The outlier loss threshold is affected by the definitions of
all other elements of the IRF PPS, including the structure of the CMGs
and the tiers, the relative weights, the policies for very short-stay
cases and for cases in which the patient expires in the facility (that
is, cases that qualify for the special CMG assignments), and the
facility-level adjustments (such as the rural adjustment, the LIP
adjustment, and the proposed teaching status adjustment). In the FY
2006 proposed rule (70 FR 30188), we proposed to change many of these
components of the IRF PPS. For the reasons discussed above and in the
FY 2006 proposed rule (70 FR 30188), then, we believed and continue to
believe that it is appropriate to update the outlier loss threshold for
FY 2006. We also stated in the FY 2006 proposed rule (70 FR 30188) that
we expect to continue to adjust the outlier threshold in the future
when the data indicate that total estimated outlier payments would
deviate from equaling 3 percent of total estimated payments.
Public comments and our responses on the proposed update to the
outlier threshold amount are summarized below.
[[Page 47936]]
Comment: One commenter suggested that CMS notify fiscal
intermediaries that, as a result of the lowering of the outlier
threshold amount, more cases would likely qualify for outlier payments.
Such notification would enable the fiscal intermediaries to adjust
their systems accordingly.
Response: We agree with the commenter's suggestion and will notify
the fiscal intermediaries about the change to the outlier threshold
amount and the implications of this for the number of cases that
qualify for outlier payments.
Comment: Several commenters requested that CMS incorporate any
unused outlier payments from years in which aggregate outlier payments
are below the 3 percent target back into the base payments.
Response: We have responded to similar comments a number of times
in the context of other prospective payment systems, including in rules
at 70 FR 24168, 24196-24197, 57 FR 39784, 58 FR 46347, 59 FR 45408, 60
FR 45856, 61 FR 27496, and 56 FR 43227, 61 FR 46229-46230. As we have
explained before and as explained below, we do not make adjustments to
PPS payment rates to account for differences between projected and
actual outlier payments in a previous year. We believe our outlier
policies are consistent with the statute and the goals of the
prospective payment system and are equitable.
In accordance with section 1886(j)(4) of the Act, we implemented
the IRF PPS outlier policy at 42 CFR 412.624(d)(1). These regulations
provide that CMS determines a reduction factor equal to the estimated
proportion of additional outlier payments described in paragraph (e)(4)
of this section (which is redesignated as (e)(5) in this final rule).
We set outlier criteria before the beginning of each fiscal year so
that outlier payments are projected to equal 3 percent of estimated
total IRF PPS payments. In doing so, we use the best available data at
the time to make our estimates. We do not believe that Congress
intended that the standardized amounts for a given fiscal year should
be adjusted (upward or downward) to reflect any difference between
projected and actual outlier payments for a past year. Payments for a
given discharge in a given fiscal year are generally intended to
reflect or address the average costs of that discharge in that year;
that goal would be undermined if we adjusted PPS payments to account
for ``underpayments'' or ``overpayments'' in other years.
Outlier payments are ``funded'' through a prospective adjustment to
the base rates. We do not set money aside into a discrete ``pool''
dedicated solely for outlier payments. Outlier payments are based on
estimates. If outlier payments for a given year turn out to be greater
than projected, we do not recoup money from hospitals; if outlier
payments for a given year are lower than projected, we do not make an
adjustment to account for the difference. If estimates turn out to be
inaccurate, we believe the more appropriate action is to continue to
examine the outlier policy and to try to refine the methodology for
setting outlier thresholds. Thus, consistent with this approach, for
this final rule we are finalizing our decision to update the outlier
threshold amount to $5,132 for FY 2006 to make estimated outlier
payments equal to 3 percent of total estimated IRF PPS payments in FY
2006.
Comment: One commenter indicated a concern about the methodology
used by CMS to estimate cost and charge growth for the purposes of
calculating the outlier threshold amount. This commenter recommended an
alternative methodology for the IPPS and encouraged CMS to apply that
same methodology to the IRF PPS to ensure that the full 3 percent of
outlier funds is used.
Response: We have reviewed the comments submitted for consideration
in the IPPS, and we appreciate the alternative methodologies suggested
by the commenters and have considered them carefully. The cost-to-
charge ratio applied to charges provides Medicare the most accurate
measure of a provider's per-case cost for the purpose of paying for
high-cost outlier cases at the point that we process the initial claim.
The cost-to-charge ratio is based on the providers' own cost and charge
information as reported by the providers. For the purposes of this
final rule, we have used the same methodology for projecting cost and
charge growth that is used in the IPPS and in other Medicare payment
systems, and we believe this methodology is appropriate for IRFs for
the same reasons it is appropriate for IPPS hospitals. This methodology
ensures that we pay the appropriate amounts over and above the standard
PPS payment amount for unusually high-cost cases.
Comment: Overall, commenters generally supported the proposal to
decrease the outlier threshold. Some said that CMS should delay
implementing the proposal until the full effects of the 75 percent rule
can be analyzed.
Response: For the reasons discussed in section IV of this final
rule, we do not believe we should wait until the full effects of the 75
percent rule can be analyzed before implementing any of the proposed
changes in this final rule. Making the changes now does not preclude us
from making additional revisions in the future if we find any potential
effects of the 75 percent rule on IRFs' case mix or cost structures
that would warrant such refinements.
Final Decision: After carefully considering all of the comments we
received on this proposed change to the outlier threshold amount, we
are finalizing our decision to adopt the proposed policy in this final
rule (including the redesignation of Sec. 412.624(e)(4) as Sec.
412.624(e)(5)), with the following change.
Using data from FY 2003, and including the HealthSouth home office
cost data from FY 2004 (as described in detail in section IV of this
final rule), RAND has calculated the outlier threshold amount of $5,132
(instead of the $4,911 outlier threshold amount we proposed in the FY
2006 proposed rule (70 FR 30188)) that would maintain estimated outlier
payments at 3 percent of total estimated IRF payments for FY 2006.
Therefore, we are finalizing our decision to set the FY 2006 outlier
loss threshold at $5,132.
In addition, we are finalizing our decision to adopt the proposed
upper threshold CCR for IRFs for FY 2006 of 1.52 based on CBSA-based
geographic designations. We are basing this upper threshold CCR on the
CBSA-based geographic designations because the CBSAs are the geographic
designations we are adopting (with a one-year transition policy as
described in section VI.B.2.e of this final rule) for the purposes of
computing the wage index adjustment to IRF payments for FY 2006.
We are also finalizing our decision to update the national urban
and rural CCRs for IRFs. Under Sec. 412.624(e)(4) (which we are
redesignating as Sec. 412.624(e)(5) in this final rule), we will apply
the national CCRs to the following situations:
New IRFs that have not yet submitted their first Medicare
cost report.
IRFs whose operating or capital CCR is in excess of 3
standard deviations above the corresponding national geometric mean.
Other IRFs for whom data with which to calculate either an
operating or capital CCR (or both) are not available.
The national CCR based on the facility location of either urban or
rural will be used in each of the three situations cited above.
Specifically, for FY 2006, we are adopting a national CCR of 0.631 for
[[Page 47937]]
rural IRFs and 0.518 for urban IRFs. For new facilities, we will use
these national ratios until the facility's actual CCR can be computed
using the first tentative settled or final settled cost report data,
which will then be used for the subsequent cost report period.
7. Budget Neutrality Factor Methodology for Fiscal Year 2006
In the FY 2006 proposed rule (70 FR 30188), we proposed to make a
revision (for FY 2006) to the methodology found in Sec. 412.624(d) in
order to make the proposed changes to the tiers and CMGs, the rural
adjustment, the LIP adjustment, and the proposed teaching status
adjustment in a budget neutral manner. Accordingly, we proposed to
revise Sec. 412.624(d) by adding a section Sec. 412.624(d)(4) for
fiscal year 2006 and, as applicable, for fiscal years thereafter to the
extent the adjustments are updated in the future. Specifically, we
proposed to revise the methodology found in Sec. 412.624(d) by adding
a new paragraph (d)(4). The addition of this paragraph would provide
for the application of a factor, as specified by the Secretary, which
would be applied to the standard payment amount in order to make the
proposed changes described in the preamble of the FY 2006 proposed rule
(70 FR 30188) in a budget neutral manner for FY 2006. In addition, this
paragraph would be used in future years if we propose refinements to
the above-cited adjustments.
Final Decision: We did not specifically receive any comments on the
proposed budget neutrality factor methodology for FY 2006. Therefore,
we are finalizing our decision to adopt this budget neutrality factor
methodology for FY 2006, with the change that we are incorporating
HealthSouth home office cost data from FY 2004 (as described in detail
in section IV of this final rule) into the data we used previously to
compute the budget neutrality factors. Based on RAND's analysis of FY
2003 data, including the HealthSouth home office cost data from FY 2004
(as described in detail in section IV of this final rule) and using the
methodology described in section VI.B.8 of this final rule, we will
apply the market basket increase factor (estimated for this final rule
to be 3.6 percent) to the standard payment conversion factor for FY
2005 ($12,958), which equals $13,425. Then, we will apply a one-time
reduction to the standard payment amount of 1.9 percent to adjust for
coding changes that increased payment to IRFs (as discussed in section
VI.A of this final rule), which equals $13,169. We will then apply the
budget neutral wage adjustment (as discussed in section VI.B.2.f of
this final rule) of 0.9995 to $13,169, which will result in a standard
payment amount of $13,163. For FY 2006 and any applicable FYs
thereafter, to the extent any of the adjustments are updated, we will
apply budget neutrality factors to the standard payment amount using
Sec. 412.624(c)(3)(ii), which incorporates by reference Sec.
412.624(d)(4), for the applicable changes to the tiers and CMGs, the
rural adjustment, the LIP adjustment, and the teaching status
adjustment we are finalizing in this final rule. We note that even if
we do not update any of the adjustments (and therefore utilize Sec.
412.624(d)(4)), we will use Sec. 412.624(c)(3) to update the payment
rates for FY 2006 and thereafter. The next section contains a detailed
explanation of these budget neutrality factors we are finalizing in
this final rule, including the steps for computing these factors and
how they will affect total estimated aggregate payments and estimated
payments to individual IRF providers. The factors we will apply (as
discussed in the next section) are 0.9995 for the tier and CMG changes,
0.9889 for the teaching status adjustment, 0.9961 for the change to the
rural adjustment, and 0.9851 for the change to the LIP adjustment. We
have combined these factors, by multiplying the four factors together,
into one budget neutrality factor for all four of these changes (0.9995
* 0.9889 * 0.9961 * 0.9851 = 0.9699). We will apply this overall budget
neutrality factor to $13,163, resulting in a standard payment
conversion factor for FY 2006 of $12,767. Note that the FY 2006
standard payment conversion factor will be lower than it was in FY 2005
because it needs to be reduced to ensure that estimated aggregate
payments for FY 2006 will remain the same as they otherwise would have
been without the proposed changes. If we do not decrease the standard
payment conversion factor, each of the changes we are finalizing in
this final rule would increase total estimated aggregate payments by
increasing payments to rural and teaching facilities, and to facilities
with a higher average case mix of patients and facilities that treat a
higher proportion of low-income patients. To assess how overall
estimated payments to a particular type of IRF will likely be affected
by any of the changes we are finalizing in this final rule, please see
Table 13 of this final rule.
The FY 2006 standard payment conversion factor would be applied to
each CMG relative weight shown in Table 4, Relative Weights for Case-
Mix Groups, to compute the unadjusted IRF prospective payment rates for
FY 2006 shown in Table 12. To further clarify, the budget neutrality
factors described above will only be applied for FY 2006 and in
applicable years thereafter to the extent the adjustments are updated.
Therefore, for fiscal years 2006 and thereafter, we will generally use
the methodology as described in Sec. 412.624(c)(3)(ii).
8. Description of the Methodology Used To Implement the Changes in a
Budget Neutral Manner
Section 1886(j)(2)(C)(i) of the Act confers broad statutory
authority upon the Secretary to adjust the classification and weighting
factors in order to account for relative resource use. In addition,
section 1886(j)(2)(C)(ii) provides that insofar as the Secretary
determines that such adjustments for a previous fiscal year (or
estimates of such adjustments for a future fiscal year) did (or are
likely to) result in a change in aggregated payments under the
classification system during the fiscal year that are a result of
changes in the coding or classification of patients that do not reflect
real changes in case mix, the Secretary shall adjust the per payment
unit payment rate for subsequent years to eliminate the effect of such
coding or classification changes. Similarly, section 1886(j)(3)(A)(v)
of the Act confers broad statutory authority upon the Secretary to
adjust the per discharge payment rate by such factors as the Secretary
determines are necessary to properly reflect variations in necessary
costs of treatment among IRFs. Consistent with this broad statutory
authority, we proposed in the FY 2006 proposed rule (70 FR 30188) to
better distribute aggregate payments among IRFs to more accurately
reflect their case mix and the increased costs associated with IRFs
that have teaching programs, are located in rural areas, or treat a
high proportion of low-income patients.
Furthermore, to ensure that total estimated aggregate payments to
IRFs would not change with these proposed changes, we also proposed in
the FY 2006 proposed rule (70 FR 30188) to apply a factor to the
standard payment amount for each of the proposed changes to ensure that
estimated aggregate payments in FY 2006 would not be greater or less
than those that would have been made in the year without the proposed
changes.
Final Decision: We did not specifically receive any comments on the
description of the methodology used to implement the changes in a
budget neutral manner. Therefore, we are finalizing our decision to
adopt this
[[Page 47938]]
budget neutrality factor methodology for FY 2006, with the change that
we are incorporating HealthSouth home office cost data from FY 2004 (as
described in detail in section IV of this final rule) into the data we
used previously to compute the budget neutrality factors. Based on
RAND's analysis of FY 2003 data, including the HealthSouth home office
cost data from FY 2004 (as described in detail in section IV of this
final rule) and using the methodology described below, we will apply
the budget neutrality factors to the standard payment amount for each
of the changes described below to ensure that estimated aggregate
payments in FY 2006 will be the same with or without the changes. We
are finalizing our decision in this final rule to calculate these four
factors using the following steps:
Step 1 Determine the FY 2006 IRF PPS standard payment amount using
the FY 2005 standard payment conversion factor increased by the
estimated market basket of 3.6 percent (estimated for this final rule)
and reduced by 1.9 percent to account for coding changes (as discussed
in section VI.A of this final rule).
Step 2 Multiply the CBSA-based budget neutrality factor discussed
in this preamble by the standard payment amount computed in step 1 to
account for the wage index and labor-related share (0.9995), as
discussed in section VI.B.2.f of this final rule.
Step 3 Calculate the estimated total amount of IRF PPS payments for
FY 2006 (with no change to the tiers and CMGs, no teaching status
adjustment, and no changes to the rural and LIP adjustments).
Step 4 Apply the new tier and CMG assignments (as discussed in
section V of this final rule) to calculate the estimated total amount
of IRF PPS payments for FY 2006.
Step 5 Divide the amount calculated in step 3 by the amount
calculated in step 4 to determine the factor (0.9995) that maintains
the same total estimated aggregate payments in FY 2006 with and without
the changes to the tier and CMG assignments.
Step 6 Apply the factor computed in step 5 to the standard payment
amount from step 2, and calculate estimated total IRF PPS payment for
FY 2006.
Step 7 Apply the change to the rural adjustment (as discussed in
section VI.B.4 of this final rule) to calculate the estimated total
amount of IRF PPS payments for FY 2006.
Step 8 Divide the amount calculated in step 6 by the amount
calculated in step 7 to determine the factor (0.9961) that keeps total
estimated payments in FY 2006 the same with and without the change to
the rural adjustment.
Step 9 Apply the factor computed in step 8 to the standard payment
amount from step 6, and calculate estimated total IRF PPS payment for
FY 2006.
Step 10 Apply the change to the LIP adjustment (as discussed in
section VI.B.5 of this final rule) to calculate the estimated total
amount of IRF PPS payments for FY 2006.
Step 11 Divide the amount calculated in step 9 by the amount
calculated in step 10 to determine the factor (0.9851) that maintains
the same total estimated aggregate payments in FY 2006 with and without
the change to the LIP adjustment.
Step 12 Apply the factor computed in step 11 to the standard
payment amount from step 9, and calculate estimated total IRF PPS
payments for FY 2006.
Step 13 Apply the teaching status adjustment (as discussed in
section VI.B.3 of this final rule) to calculate the estimated total
amount of IRF PPS payments for FY 2006.
Step 14 Divide the amount calculated in step 12 by the amount
calculated in step 13 to determine the factor (0.9889) that maintains
the same total estimated aggregate payments in FY 2006 with and without
the teaching status adjustment.
As discussed in section VI.B.9 of this final rule, the FY 2006 IRF
PPS standard payment conversion factor that accounts for the new tier
and CMG assignments, the changes to the rural and the LIP adjustments,
and the teaching status adjustment applies the following factors: the
market basket update, the reduction of 1.9 percent to account for
coding changes, the budget-neutral CBSA-based wage index and labor-
related share budget neutrality factor of 0.9995, the tier and CMG
changes budget neutrality factor of 0.9995, the rural adjustment budget
neutrality factor of 0.9961, the LIP adjustment budget neutrality
factor of 0.9851, and the teaching status adjustment budget neutrality
factor of 0.9889.
Each of these budget neutrality factors lowers the standard payment
amount. The budget neutrality factor for the tier and CMG changes
lowers the standard payment amount from $13,163 to $13,156. The budget
neutrality factor for the change to the rural adjustment lowers the
standard payment amount from $13,156 to $13,105. The budget neutrality
factor for the change to the LIP adjustment lowers the standard payment
amount from $13,105 to $12,910. Finally, the budget neutrality factor
for the teaching status adjustment lowers the standard payment amount
from $12,910 to $12,767. As indicated previously, the standard payment
conversion factor will be lowered in order to ensure that total
estimated payments for FY 2006 with the changes equal total estimated
payments for FY 2006 without the changes. This is because these four
changes would otherwise result in an increase, on average, to total
estimated aggregate payments to IRFs, because IRFs with teaching
programs, IRFs located in rural areas, IRFs with higher case mix, and
IRFs with higher proportions of low-income patients would receive
higher payments. To maintain the same total estimated aggregate
payments to all IRFs, then, we are redistributing payments among IRFs.
Thus, some redistribution of payments occurs among facilities, while
total estimated aggregate payments do not change. To determine how the
changes we are finalizing in this final rule are estimated to affect
payments among different types of facilities, please see Table 13 in
this final rule.
9. Description of the IRF Standard Payment Conversion Factor for Fiscal
Year 2006
In the August 7, 2001 final rule, we established a standard payment
amount referred to as the budget neutral conversion factor under Sec.
412.624(c). In accordance with the methodology described in Sec.
412.624(c)(3)(i), the budget neutral conversion factor for FY 2002, as
published in the August 7,2001 final rule, was $11,838.00. Under Sec.
412.624(c)(3)(i), this amount reflects, as appropriate, any adjustments
for outlier payments, budget neutrality, and coding and classification
changes as described in Sec. 412.624(d).
The budget neutral conversion factor is a standardized payment
amount and the amount reflects the budget neutrality adjustment for FY
2002. The statute required a budget neutrality adjustment only for FYs
2001 and 2002. Accordingly, we believed it was more consistent with the
statute to refer to the standard payment as a standard payment
conversion factor, rather than refer to it as a budget neutral
conversion factor. Consequently, we changed all references to budget
neutral conversion factor to ``standard payment conversion factor.''
Under Sec. 412.624(c)(3)(i), the standard payment conversion
factor for FY 2002 of $11,838 reflected the budget neutrality
adjustment described in Sec. 412.624(d)(2). Under the then existing
Sec. 412.624(c)(3)(ii), we updated the FY 2002 standard payment
conversion factor ($11,838) to FY 2003 by applying an increase factor
(the market basket) of
[[Page 47939]]
3.0 percent, as described in the update notice published in the August
1, 2002 Federal Register (67 FR at 49931). This yielded the FY 2003
standard payment conversion factor of $12,193.00 that was published in
the August 1, 2002 update notice (67 FR at 49931). The FY 2003 standard
payment conversion factor ($12,193) was used to update the FY 2004
standard payment conversion factor by applying an increase factor (the
market basket) of 3.2 percent and budget neutrality factor of 0.9954,
as described in the August 1, 2003 Federal Register (68 FR at 45689).
This yielded the FY 2004 standard payment conversion factor of $12,525
that was published in the August 1, 2003 Federal Register (68 FR at
45689). The FY 2004 standard payment conversion factor ($12,525) was
used to update the FY 2005 standard payment conversion factor by
applying an increase factor (the market basket) of 3.1 percent and
budget neutrality factor of 1.0035, as described in the July 30, 2004
Federal Register (69 FR at 45766). This yielded the FY 2005 standard
payment conversion factor of $12,958 as published in the July 30, 2004
Federal Register (69 FR at 45766).
In the FY 2006 proposed rule (70 FR 30188), we proposed to use the
revised methodology in accordance with Sec. 412.624(c)(3)(ii) and as
described in section VI.B.7 of the FY 2006 proposed rule (70 FR 30188)
to propose an update to the standard payment conversion factor for FY
2006.
Final Decision: We did not specifically receive any comments on the
proposed standard payment conversion factor for FY 2006. Therefore, we
are finalizing our decision to adopt the proposed methodology for
computing the standard payment conversion factor, with the change that
we are incorporating HealthSouth home office cost data from FY 2004 (as
described in detail in section IV of this final rule) into the FY 2003
data we used previously to compute the final standard payment
conversion factor for FY 2006. Based on RAND's analysis of FY 2003
data, including the HealthSouth home office cost data from FY 2004 (as
described in detail in section IV of this final rule) and using the
methodology we are finalizing in section VI.B.7 and section VI.B.8 of
this final rule, we will calculate the standard payment conversion
factor for FY 2006 by applying the market basket increase factor
(estimated for this final rule to be 3.6 percent) to the standard
payment conversion factor for FY 2005 ($12,958), which equals $13,425.
Then, we will apply a one-time reduction to the standard payment amount
of 1.9 percent to adjust for coding changes that increased payment to
IRFs, which equals $13,169. We will then apply the budget neutral wage
adjustment of 0.9995 to $13,169, which will result in a standard
payment amount of $13,163. Next, we will apply a budget neutrality
factor for FY 2006 for the budget-neutral refinements to the tiers and
CMGs, the teaching status adjustment, the rural adjustment, and the
adjustment for the proportion of low-income patients (of 0.9699) to
$13,163, which will result in a standard payment conversion factor for
FY 2006 of $12,767. The FY 2006 standard payment conversion factor will
be applied to each CMG weight shown in Table 4 of this final rule,
Relative Weights for Case-Mix Groups, to compute the unadjusted IRF
prospective payment rates for FY 2006 shown in Table 12 of this final
rule.
10. Example of the Methodology for Adjusting the Federal Prospective
Payment Rates
To illustrate the methodology that we will use to adjust the
Federal prospective payments (as described in section VI.B.7 and
section VI.B.8 of this final rule), we provide an example in Table 11
below. Note that the methodology we are finalizing in this final rule
has changed somewhat from the methodology we proposed in the FY 2006
proposed rule (70 FR 30188) because, upon further analysis, CMS
discovered that the example used to illustrate the proposed adjustments
to the Federal prospective payments in the FY 2006 proposed rule (70 FR
30188) did not calculate payments as accurately as the one we are
finalizing in this final rule. Therefore, we have made a slight
adjustment to the methodology we are finalizing in this final rule to
ensure that payments are calculated as accurately as possible.
Accordingly, we will multiply the teaching status adjustment, if
applicable, by the wage adjusted Federal payment amount, rather than by
the rural and LIP adjusted Federal payment amount as we proposed in the
FY 2006 proposed rule (70 FR 30188), and add the resulting amount to
the FY 2006 adjusted Federal prospective payment to compute the total
FY 2006 adjusted Federal prospective payment (as illustrated in the
following example).
We summarize 3 examples for computing total FY 2006 adjusted
Federal prospective payment rates in Table 11 below. These examples are
based on 3 beneficiaries classified into CMG 0110 (without
comorbidities) receiving care in 3 different hypothetical IRFs. IRFs A,
B, and C have the following characteristics:
Facility A is a non-teaching IRF located in rural Duke
County, Massachusetts with a disproportionate share hospital (DSH)
adjustment of 5 percent (1.031) and the FY 2006 blended wage index of
1.0216;
Facility B is a teaching IRF located in urban Queens
County, New York with a disproportionate share hospital (DSH)
adjustment of 10 percent (1.0612) and a FY 2006 blended wage index of
1.3449. The teaching status adjustment of 1.0910 will also be applied;
and,
Facility C is a non-teaching IRF located in Kings County,
California with a disproportionate share hospital (DSH) adjustment of
20 percent (1.1203) and a FY 2006 blended wage index of 0.9797. The
Kings County, California IRF was designated as a rural facility in FY
2005 (based on the MSA designation), but is classified as urban in FY
2006 (based on the CBSA designation). Therefore, this IRF will receive
a hold harmless adjustment of 12.76 percent. The hold harmless
adjustment applies to IRFs that are defined as rural under Sec.
412.602 during FY 2005 and are classified as urban under Sec. 412.602
in FY 2006 (as discussed in detail in section VI.B.2.e).
To calculate each IRF's total adjusted Federal prospective payment,
we compute the wage-adjusted Federal prospective payment and multiply
the result by the appropriate low-income patient adjustment, and the
rural adjustment (if applicable). In order to calculate the teaching
hospital adjustment (if applicable), we multiply the teaching
adjustment by the Wage Adjusted Federal payment. Then, we apply the
amount to the Adjusted Rural and LIP Federal Prospective Payment Rate.
Table 11 illustrates the components of the adjusted payment
calculation.
Table 11.--Example of Computing an IRF's Federal Prospective Payment
----------------------------------------------------------------------------------------------------------------
Facility A Dukes Facility B Facility C Kings
County, MA Queens County, NY County, CA
----------------------------------------------------------------------------------------------------------------
Federal Prospective Payment............................ $27,686.52 $27,686.52 $27,686.52
[[Page 47940]]
Labor Share............................................ x 0.75865 x 0.75865 x 0.75865
Labor Portion of Federal Payment....................... = $21,004.38 = $21,004.38 = $21,004.38
FY 2006 Transition Wage Index (shown in Table 1 in the x 1.0216 x 1.3449 x 0.9797
addendum).............................................
Wage-Adjusted Amount................................... = $21,458.07 = $28,248.79 = $20,577.99
====================
Nonlabor Amount........................................ $6,682.14 $6,682.14 $6,682.14
Wage-Adjusted Federal Payment.......................... $28,140.21 $34,930.93 $27,260.13
Rural Adjustment....................................... x 1.2130 x 1.0000 x 1.1276
Subtotal........................................... = $34,134.08 = $34,930.93 = $30,738.52
LIP Adjustment......................................... 1.0310 1.0612 1.1203
====================
FY 2006 Adjusted Rural and LIP Federal Prospective $35,192.24 $37,068.70 $34,436.37
Payment Rate..........................................
Wage-Adjusted Federal Payment.......................... $28,140.21 $34,930.93 $27,260.13
Teaching status adjustment............................. x 1.0000 x 1.0900 x 1.0000
= $28,140.21 = $38,074.71 = $27,260.13
Teaching Status addition to FY 2006 Adjusted Rural and $0.00 $3,143.78 $0.00
LIP Federal Prospective Payment Rate..................
--------------------
Total FY 2006 Adjusted Federal Prospective Payment. $35,192.24 $40,212.49 $34,436.37
----------------------------------------------------------------------------------------------------------------
Thus, the adjusted payment for Facility A will be $35,192.24, the
adjusted payment for Facility B will be $40,212.49, and the adjusted
payment for Facility C will be $34,436.37.
Table 12.--FY 2006 Payment Rate Table Based on All Refinements
----------------------------------------------------------------------------------------------------------------
Payment Rate Payment Rate Payment Rate Payment Rate
CMG Tier 1 Tier 2 Tier 3 No Comorbidity
----------------------------------------------------------------------------------------------------------------
0101............................................ $9,819.10 $9,318.63 $8,278.12 $8,107.05
0102............................................ 12,091.63 11,476.26 10,194.45 9,983.79
0103............................................ 14,250.53 13,525.36 12,015.02 11,767.34
0104............................................ 15,140.39 14,369.26 12,765.72 12,501.45
0105............................................ 18,171.27 17,246.94 15,321.68 15,005.06
0106............................................ 21,151.09 20,074.83 17,834.22 17,465.26
0107............................................ 24,411.78 23,169.55 20,582.96 20,159.09
0108............................................ 28,222.73 26,786.44 23,796.41 23,304.88
0109............................................ 28,056.76 26,629.41 23,655.97 23,168.27
0110............................................ 33,528.70 31,823.02 28,269.97 27,686.52
0201............................................ 10,392.34 8,714.75 7,687.01 7,210.80
0202............................................ 13,324.92 11,174.96 9,856.12 9,244.58
0203............................................ 15,942.15 13,369.60 11,791.60 11,061.33
0204............................................ 17,051.61 14,300.32 12,612.52 11,831.18
0205............................................ 20,913.62 17,539.30 15,468.50 14,509.70
0206............................................ 27,294.57 22,891.23 20,189.73 18,937.29
0207............................................ 35,309.69 29,611.78 26,117.45 24,497.32
0301............................................ 14,417.77 12,174.61 10,775.35 9,912.30
0302............................................ 18,804.51 15,879.59 14,053.91 12,927.86
0303............................................ 22,438.00 18,947.50 16,770.73 15,426.37
0304............................................ 30,922.95 26,112.35 23,112.10 21,258.33
0401............................................ 12,627.84 10,873.65 9,774.42 8,728.80
0402............................................ 17,414.19 14,996.12 13,479.40 12,036.73
0403............................................ 30,312.69 26,103.41 23,464.47 20,953.20
0404............................................ 54,345.29 46,798.72 42,067.27 37,565.62
0405............................................ 41,463.39 35,705.47 32,094.96 28,660.64
0501............................................ 9,836.97 8,233.44 7,201.86 6,458.83
0502............................................ 13,170.44 11,023.03 9,642.92 8,648.37
0503............................................ 17,460.15 14,613.11 12,783.60 11,463.49
0504............................................ 21,857.10 18,292.56 16,002.16 14,350.11
0505............................................ 25,902.97 21,679.64 18,965.38 17,006.92
0506............................................ 35,245.86 29,499.43 25,804.66 23,141.46
0601............................................ 11,445.62 9,359.49 8,893.49 8,289.61
0602............................................ 15,224.65 12,450.38 11,831.18 11,025.58
0603............................................ 19,490.10 15,938.32 15,145.49 14,115.20
0604............................................ 24,945.44 20,400.39 19,384.14 18,066.58
0701............................................ 11,560.52 9,876.55 9,275.23 8,407.07
0702............................................ 15,010.16 12,823.17 12,041.83 10,914.51
0703............................................ 18,685.78 15,963.86 14,991.01 13,587.92
[[Page 47941]]
0704............................................ 22,932.09 19,590.96 18,397.25 16,676.26
0801............................................ 8,376.43 7,035.89 6,522.66 5,867.71
0802............................................ 10,941.32 9,189.69 8,519.42 7,665.31
0803............................................ 16,223.03 13,624.94 12,631.67 11,363.91
0804............................................ 14,131.79 11,868.20 11,002.60 9,899.53
0805............................................ 17,793.37 14,943.77 13,854.75 12,464.42
0806............................................ 21,354.08 17,933.80 16,626.46 14,957.82
0901............................................ 10,739.60 9,776.97 8,687.94 7,775.10
0902............................................ 14,112.64 12,847.43 11,416.25 10,216.15
0903............................................ 18,618.12 16,949.47 15,061.23 13,478.12
0904............................................ 23,339.35 21,248.12 18,879.84 16,895.85
1001............................................ 12,304.83 11,347.31 10,125.51 9,335.23
1002............................................ 16,225.58 14,961.65 13,350.45 12,308.66
1003............................................ 22,822.29 21,043.85 18,778.98 17,313.33
1101............................................ 16,014.92 13,400.24 11,731.60 10,803.44
1102............................................ 23,976.43 20,060.79 17,562.29 16,173.24
1201............................................ 13,001.91 11,227.30 10,348.93 9,341.61
1202............................................ 16,828.18 14,532.68 13,395.14 12,090.35
1203............................................ 20,731.05 17,901.89 16,501.35 14,893.98
1301............................................ 13,198.52 12,278.02 10,628.53 9,393.96
1302............................................ 18,287.45 17,012.03 14,725.46 13,015.96
1303............................................ 23,373.82 21,744.75 18,822.39 16,637.95
1401............................................ 10,433.19 9,386.30 8,165.77 7,412.52
1402............................................ 14,087.11 12,672.52 11,025.58 10,008.05
1403............................................ 17,535.47 15,774.91 13,724.53 12,459.32
1404............................................ 22,238.84 20,007.17 17,405.25 15,800.44
1501............................................ 11,773.73 11,483.92 9,813.99 9,443.75
1502............................................ 14,885.05 14,517.36 12,406.97 11,939.70
1503............................................ 18,217.23 17,767.83 15,185.07 14,611.83
1504............................................ 24,017.28 23,424.89 20,019.93 19,264.13
1601............................................ 12,849.99 10,908.12 9,870.17 8,814.34
1602............................................ 17,631.23 14,968.03 13,541.96 12,094.18
1603............................................ 21,688.58 18,411.29 16,658.38 14,877.39
1701............................................ 12,897.22 12,299.73 10,625.97 9,346.72
1702............................................ 16,986.49 16,198.77 13,995.19 12,311.22
1703............................................ 20,212.71 19,275.62 16,652.00 14,648.86
1704............................................ 25,288.87 24,115.59 20,834.47 18,327.03
1801............................................ 15,471.05 12,552.51 10,526.39 9,296.93
1802............................................ 24,748.83 20,079.94 16,839.67 14,872.28
1803............................................ 44,408.73 36,031.03 30,216.94 26,686.86
1901............................................ 15,782.57 14,019.44 13,631.33 11,935.87
1902............................................ 29,570.93 26,266.83 25,539.11 22,361.40
1903............................................ 42,691.57 37,921.82 36,872.37 32,283.91
2001............................................ 11,162.19 9,430.98 8,455.58 7,720.20
2002............................................ 14,615.66 12,348.24 11,070.27 10,107.63
2003............................................ 18,881.12 15,952.37 14,301.59 13,056.81
2004............................................ 25,222.49 21,310.68 19,104.54 17,443.55
2101............................................ 27,906.11 27,906.11 20,312.30 18,846.65
5001............................................ 0.00 0.00 0.00 2810.02
5101............................................ 0.00 0.00 0.00 18,108.32
5102............................................ 0.00 0.00 0.00 20,429.75
5103............................................ 0.00 0.00 0.00 9,197.35
5104............................................ 0.00 0.00 0.00 23,964.94
----------------------------------------------------------------------------------------------------------------
VII. Quality of Care in IRFs
The IRF-PAI is the patient data collection instrument for IRFs.
Currently, the IRF-PAI contains a blend of the functional independence
measures items and quality and medical needs questions. The quality and
medical needs questions (which are currently collected on a voluntary
basis) may need to be modified to encapsulate those data necessary for
calculation of quality indicators in the future.
We awarded a contract to the Research Triangle Institute (RTI) with
the primary tasks of identifying quality indicators pertinent to the
inpatient rehabilitation setting and determining what information is
necessary to calculate those quality indicators. These tasks included
reviewing literature and other sources for existing rehabilitation
quality indicators. It also involved identifying organizations involved
in measuring or monitoring quality of care in the inpatient
rehabilitation setting. In addition, RTI was tasked with performing
independent testing of the quality indicators identified in their
research.
Once RTI has issued a final report, taking into account and
responding to public comments in the Federal Register as part of the
Paperwork Reduction Act process, we will publish our rationale for
revising the IRF-PAI. Then in accordance with the Paperwork
[[Page 47942]]
Reduction Act, we will publish our proposed revisions to the IRF-PAI
and solicit public comments. The revised IRF-PAI will need to be
approved by OMB before it is used in IRFs.
We have supported the development of valid quality measures and
have been engaged in a variety of quality improvement efforts focused
in other post-acute care settings such as nursing homes. However, any
new quality-related data collected from the IRF-PAI would have to be
analyzed to determine the feasibility of developing a payment method
that accounts for the performance of the IRF in providing the necessary
rehabilitative care.
Medicare beneficiaries are the primary users of IRF services. Any
quality measures must be carefully constructed to address the unique
characteristics of this population. Similarly, we need to consider how
to design effective incentives; that is, superior performance measured
against pre-established benchmarks and/or performance improvements.
In addition, while our efforts to develop the various post-acute
care PPSs, including the IRF PPS, have generated substantial
improvements over the preexisting cost-based systems, each of these
individual systems was developed independently. As a result, we have
focused on phases of a patient's illness as defined by a specific site
of service, rather than on the entire post-acute episode. As the
differentiation among provider types (such as SNFs and IRFs) becomes
less pronounced, we need to investigate a more coordinated approach to
payment and delivery of post-acute services that focuses on the overall
post-acute episode.
This could entail a strategy of developing payment policy that is
as neutral as possible regarding provider and patient decisions about
the use of particular post-acute services. That is, Medicare should
provide payments sufficient to ensure that beneficiaries receive high
quality care in the most appropriate setting, so that admissions and
any transfers between settings occur only when consistent with good
care, rather than to generate additional revenues. In order to
accomplish this objective, we need to collect and compare clinical data
across different sites of service.
In fact, in the long run, our ability to compare clinical data
across care settings is one of the benefits that will be realized as a
basic component of the Department's interest in the use of a
standardized electronic health record (EHR) across all settings
including IRFs. It is also important to recognize the complexity of the
effort, not only in developing an integrated assessment tool that is
designed using health information standards, but in examining the
various provider-centric prospective payment methodologies and
considering payment approaches that are based on patient
characteristics and outcomes. MedPAC has recently taken a preliminary
look at the challenges in improving the coordination of our post-acute
care payment methods, and suggested that it may be appropriate to
explore additional options for paying for post-acute services. We agree
that CMS, in conjunction with MedPAC and other stakeholders, should
consider a full range of options in analyzing our post-acute care
payment methods, including the IRF PPS.
We also want to encourage incremental changes that will help us
build towards these longer term objectives. For example, medical
records tools are now available that could allow better coordinated
discharge planning procedures. These tools can be used to ensure
communication of a standardized data set that then can be used to
establish a comprehensive IRF care plan. Improved communications may
reduce the incidence of potentially avoidable re-hospitalizations and
other negative impacts on quality of care that occur when patients are
transferred to IRFs without a full explanation of their care needs. We
are looking at ways that Medicare providers can use these tools to
generate timely data across settings.
It is important to note that some of the ideas discussed above may
exceed our current statutory authority. However, we believe that it is
useful to encourage discussion of a broad range of ideas for debate of
the relative advantages and disadvantages of the various policies
affecting this important component of the health care sector. Thus, we
solicited comments on these and other approaches.
Comment: Most commenters were supportive of the concept of
providing incentives for high quality and improved patient outcomes
within the structure of Medicare's payment systems. Commenters were
also generally supportive of advancing approaches that resulted in more
consistent payments for similar services across the various post acute
care settings and a more seamless system of care, though several noted
important distinctions between the type of care provided in IRF
compared to other settings. For example, one commenter objected to the
implication that the differentiation among provider types (such as SNFs
and IRFs) could become less pronounced. This commenter stated that
there is a big difference in care and rehabilitation between these two
types of facilities and suggested that we ask patients about this
difference. Many Commenters noted that, in advancing these policy
goals, CMS should facilitate stakeholder input to ensure that the
knowledge and experience of providers, beneficiaries, and others with
critical knowledge is factored into the development process.
Response: CMS appreciates the thoughtful comments provided on these
important issues. By advancing a more seamless system of payments and
benefits in post acute care, Medicare can ensure that patients receive
high quality care in the most appropriate setting, and that decisions
about where patients receive care are guided by decisions of patients
and their families working with physicians, rather than in response to
financial incentives or barriers created by administrative guidelines.
In addition, pay for performance has the potential to promote real
improvements in quality and outcomes as demonstrated by the work CMS
has advanced already; for example, the Premier Hospital Demonstration.
We agree with commenters that CMS should involve stakeholders and
work collaboratively with providers, patients and practitioners in the
field to advance these objectives. In developing additional IRF-PAI
quality items and related quality measures through our research with
RTI, as described in section VII above, RTI has already begun to do
that by convening meetings of a Technical Expert Panel to consider the
critical methodological and clinical issues. The research we are
conducting through the RTI contract will provide data that will promote
and advance efforts to develop and consider pay for performance
approaches in IRFs, as well as approaches to measuring and rewarding
quality improvement more broadly in post acute care. We also agree
that, in developing a more integrated strategy for payment and care
delivery within Medicare's post acute benefits, it will be important to
consider not only how various provider types are similar but also how
they are different.
VIII. Miscellaneous Public Comments Within the Scope of the Proposed
Rule
Comment: We received a comment regarding a change made to Sec.
412.25(a) when the inpatient psychiatric facility (IPF) PPS was
published on November 15, 2004 (69 FR 66922). The commenter requested
that we add the reference to a rehabilitation unit that was removed by
the IPF PPS final rule.
Response: We agree with making the change requested by the
commenter.
[[Page 47943]]
Section 412.1 specifies the scope of part 412. In order to expand the
existing scope of part 412 the IPF PPS final rule revised Sec. 412.1
by redesignating paragraphs (a)(2) and (a)(3) as paragraphs (a)(3) and
(a)(4) and adding a new paragraph (a)(2). The added paragraph (a)(2)
specified that in accordance with section 124 of Pub. L. 106-113 we
were establishing a per diem prospective payment system for the
inpatient operating and capital costs of hospital inpatient services
furnished to Medicare beneficiaries by a psychiatric facility that
meets the conditions of subpart N of part 412. Redesignated as
paragraph (a)(3) is the paragraph that specifies the statutory basis
for the establishment of the IRF PPS.
In order to conform Sec. 412.25(a) to the revision we made as
stipulated above to Sec. 412.1 the IPF PPS final rule revised Sec.
412.25(a), which specifies the basis for exclusion from being paid
under the IPPS. Prior to publishing the IPF PPS final rule, Sec.
412.25(a) read as follows:
(a) Basis for exclusion. In order to be excluded from the
prospective payment systems specified in Sec. 412.1(a)(1), a
psychiatric or rehabilitation unit must meet the following
requirements.
When the IPF PPS final rule revised Sec. 412.25(a) the intended
purpose of the revision was to include a reference to new paragraph
(a)(2) that, as stipulated above, we had added to Sec. 412.1. However,
when we revised Sec. 412.25(a), we inadvertently removed the words
``or rehabilitation'' from the existing Sec. 412.25(a). Therefore, in
order to correct the inadvertent removal of the words ``or
rehabilitation'' from Sec. 412.25(a), we are making a technical
correction so that Sec. 412.25(a) will read as follows:
(a) Basis for exclusion. In order to be excluded from the
prospective payment systems as specified in Sec. 412.1(a)(1) and be
paid under the inpatient psychiatric facility prospective payment
system as specified in Sec. 412.1(a)(2) or the inpatient
rehabilitation facility prospective payment system as specified in
Sec. 412.1(a)(3), a psychiatric or rehabilitation unit must meet the
following requirements.
IX. Miscellaneous Public Comments Outside the Scope of the Proposed
Rule
Comment: We received a number of comments expressing concerns about
various aspects of CMS's enforcement of the 75 percent rule. Several
commenters stated that enforcement of the 75 percent rule would lead
many IRFs to close, would arbitrarily exclude patients in certain RICs
from receiving treatment in IRFs, and would create access to care
problems for patients.
Response: These comments are not specifically related to the
proposed changes to the IRF PPS that were discussed in the FY 2006
proposed rule (70 FR 30188). We responded to similar comments in the
May 7, 2004 final rule (69 FR 25752) that established the changes to
the criteria for being classified as an IRF. Because the responses to
these comments in the May 7, 2004 final rule are very lengthy, we refer
the reader to that final rule for the detailed responses to these and
other comments regarding the 75 percent rule.
Comment: One commenter asked that we provide the algorithm (that
is, the computer software) that the fiscal intermediaries use in their
presumptive determinations of IRF compliance with the 75 percent rule.
Response: We will take this into consideration, and may make the
computer software available to all interested parties at a future date.
Comment: One commenter suggested that CMS consider implementing a
cost-of-living adjustment for IRFs located in Alaska, to offset higher
non-labor costs in Alaska.
Response: In the August 7, 2001 final rule (66 FR 41316, 41361), we
referred to Section 1886(j)(4)(B), which authorizes, but does not
require, the Secretary to take into account the unique circumstances of
IRFs located in Alaska and Hawaii. In the data used to prepare the
August 7, 2001 final rule, there was only one IRF in Hawaii and one in
Alaska. In the August 7, 2001 final rule, we explained that, due to the
small number of IRFs in Alaska and Hawaii in the data, analyses were
inconclusive regarding whether a cost-of-living adjustment would
improve payment equity for these facilities. Therefore, we did not
implement an adjustment for facilities located in Alaska and Hawaii in
the August 7, 2001 final rule.
In the FY 2003 data used for the FY 2006 proposed rule (70 FR
30188) and for this final rule, there were 3 IRFs in Alaska and 1 IRF
in Hawaii. We continue to believe that this may be too small a number
of facilities for us to determine, based on analysis of the data,
whether a cost-of-living adjustment would improve payment equity for
these facilities. However, we will consider conducting such an analysis
in the future.
Comment: Some commenters suggested changes to the items on the IRF-
PAI, such as deleting the transfer to tub item and revising the
instructions for the items that describe preventable conditions that
occur on admission to the IRF and preventable conditions that occur
while the patient is in an IRF.
Response: We have contracted with the Research Triangle Institute
(RTI) to analyze and recommend changes to the IRF-PAI that would
improve our ability to assess quality of care in IRFs. Any changes to
the IRF-PAI that CMS might decide to propose in the future, based on
RTI's recommendations, would require clearance by the Office of
Management and Budget. However, we will take the commenters suggestions
into consideration.
Comment: Several commenters suggested that CMS allow general
hospitals to increase physiatrist training if they also decrease
training in one or more specialties reimbursed under the inpatient PPS.
Response: This comment does not relate to the IRF PPS and is
outside the scope of this rule. We will forward it to the component of
the Agency that works on the IPPS for their consideration.
IX. Provisions of the Final Regulations
The provisions of this final rule restate the provisions of the FY
2006 proposed rule (70 FR 30188), except as noted elsewhere in the
preamble. Following is a highlight of the changes we made from the
proposed rule:
We are adding 2 codes that were not on the proposed list
of ICD-9-CM codes to be removed from the comorbidity tiers (V46.11 and
V46.12). We are adding these codes to the list to be removed because
these codes are derived from code V46.1, which was determined by RAND
to have no positive impact on payment when controlling for the CMG.
We are adding the following codes to the list of
comorbidities we proposed in the proposed rule: 250.1 (insulin
dependent diabetes without mention of complications, not stated as
controlled), code 428.1-Left Heart Failure, code 428.20-Systolic Heart
Failure Unspecified, code 428.21-Systolic Heart Failure Acute, code
428.22-Systolic Heart Failure Chronic, code 428.23-Systolic Hear
Failure Acute on Chronic, code 428.30-Diastolic Heart Failure
Unspecified, code 428.31-Diastolic Heart Failure Acute, code 428.32-
Diastolic Heart Failure Chronic, code 428.33-Diastolic Heart Failure
Acute on Chronic, code 428.40-Combined Systolic and Diastolic Heart
Failure Unspecified, code 428.41-Combined Systolic and Diastolic Heart
Failure Acute, code 428.42-Combined Systolic and Diastolic Heart
Failure Chronic, and code 428.43-Combined Systolic and Diastolic Heart
Failure Acute on Chronic. For this final rule, we decided to add these
codes to the list of
[[Page 47944]]
comorbidities we proposed in the proposed rule because of the increased
costs associated with these codes. After receiving the comments to add
additional codes to the list of comorbidity codes used to increase the
CMG payment rate, our Medical Officers, similar to RAND's TEP, believe
that several of the codes suggested should be added to these tiers that
increase payment for the CMG.
We are updating the market basket estimate, based on the
FY 2002-based RPL market basket and the Global Insight's 2nd quarter
2005 forecast, to 3.6 percent (from 3.1 percent in the proposed rule).
We are changing our proposed policy to adopt the CBSA-
based wage index without a transition to implementing the CBSA-based
wage index with a budget neutral one-year blended wage index. Thus, the
FY 2006 wage index is comprised of 50 percent of the FY 2006 MSA-based
wage index and 50 percent of the FY 2006 CBSA-based wage index (both
based on FY 2001 hospital wage data) for all IRFs.
We are changing our proposed policy to not adopt a hold
harmless policy to adopting a budget neutral 3 year hold harmless
policy for FY 2005 rural IRFs that will be classified as urban under
the FY 2006 CBSA-based designations. The 3 year hold harmless policy
will only apply to existing rural FY 2005 IRFs that will experience a
decrease in payments due solely to the loss of the FY 2005 rural
adjustment of 19.14 percent because of the adoption of the CBSA-based
designations.
We are changing the exponent for the teaching status
adjustment formula to 0.9012 (from 1.083 in the proposed rule), based
on RAND's most recent cost regressions using data from FY 2003,
including the HealthSouth home office cost data from FY 2004 (as
described in detail in section IV of this final rule).
We are changing the rural adjustment to 21.3 percent (from
24.1 percent in the proposed rule), based on RAND's most recent cost
regressions using data from FY 2003, including the HealthSouth home
office cost data from FY 2004 (as described in detail in section IV of
this final rule).
We are changing the exponent for the LIP adjustment
formula to 0.6229 (from 0.636 in the proposed rule), based on RAND's
most recent cost regressions using data from FY 2003, including the
HealthSouth home office cost data from FY 2004 (as described in detail
in section IV of this final rule).
We are changing the outlier threshold amount to $5,132
(from $4,911 in the proposed rule), based on RAND's most recent cost
regressions using data from FY 2003, including the HealthSouth home
office cost data from FY 2004 (as described in detail in section IV of
this final rule).
We are changing the base period for determining an IRF's
FTE resident cap from the final settlement of the IRF's most recent
cost reporting period ending on or before November 15, 2003, which was
what we had proposed in the FY 2006 proposed rule, to the final
settlement of the IRF's most recent cost reporting period ending on or
before November 15, 2004.
We are changing the budget neutrality factors applied to
the standard payment amount in the methodology used to implement the
changes in a budget neutral manner (section VI.B.8 of this final rule)
to 0.9995 for the changes to the tier comorbidities and the CMGs,
0.9961 for the change to the rural adjustment, 0.9851 for the change to
the LIP adjustment, and 0.9889 for the implementation of the new
teaching status adjustment. These changes are necessary to ensure that
the tier and CMG changes, the rural adjustment change, the LIP
adjustment change, and the implementation of the new teaching status
adjustment will be done in a budget neutral manner for FY 2006 (that
is, such that estimated aggregate IRF payments for FY 2006 with the
changes will equal estimated aggregate IRF payment in FY 2006 without
the changes).
We are changing the budget neutrality factor for the wage
index changes for FY 2006 to 0.9995, to ensure that the wage index
changes described in section VI.B.2 of this final rule will be made in
a budget neutral manner.
We are changing the standard payment conversion factor for
FY 2006 to $12,767 (from $12,658 in the proposed rule), based on RAND's
most recent cost regressions using data from FY 2003, including the
HealthSouth home office cost data from FY 2004 (as described in detail
in section IV of this final rule).
X. Collection of Information Requirements
This document does not impose information collection and
recordkeeping requirements. Consequently, it need not be reviewed by
the Office of Management and Budget under the authority of the
Paperwork Reduction Act of 1995.
XI. Regulatory Impact Analysis
A. Introduction
The August 7, 2001 final rule established the IRF PPS for the
payment of Medicare services for cost reporting periods beginning on or
after January 1, 2002. We incorporated a number of elements into the
IRF PPS, such as case-level adjustments, a wage adjustment, an
adjustment for the percentage of low-income patients, a rural
adjustment, and an outlier payment policy. This final rule updates the
FY 2005 IRF PPS payment rates specified in the July 30, 2004 notice (69
FR 45721) and implements policy changes with regard to the IRF PPS
based on analyses conducted by RAND under contract with us on CY 2002
and FY 2003 data (updated from the 1999 data used to design the IRF
PPS).
In constructing these impacts, we do not attempt to predict
behavioral responses, nor do we make adjustments for future changes in
such variables as discharges or case-mix. We note that certain events
may combine to limit the scope or accuracy of our impact analysis,
because such an analysis is future-oriented and, thus, susceptible to
forecasting errors due to other changes in the forecasted impact time
period. Some examples of such possible events are newly legislated
general Medicare program funding changes by the Congress, or changes
specifically related to IRFs. In addition, changes to the Medicare
program may continue to be made as a result of the BBA, the BBRA, the
BIPA, or new statutory provisions. Although these changes may not be
specific to the IRF PPS, the nature of the Medicare program is such
that the changes may interact, and the complexity of the interaction of
these changes could make it difficult to predict accurately the full
scope of the impact upon IRFs.
We have examined the impacts of this final rule as required by
Executive Order 12866 (September 1993, Regulatory Planning and Review)
and the Regulatory Flexibility Act (RFA) and Impact on Small Hospitals
(September 19, 1980, Pub. L. 96-354), section 1102(b) of the Social
Security Act, the Unfunded Mandates Reform Act of 1995 (Pub. L. 104-4),
and Executive Order 13132.
1. Executive Order 12866
Executive Order 12866 (as amended by Executive Order 13258, which
merely reassigns responsibility of duties) directs 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). A
regulatory impact analysis
[[Page 47945]]
(RIA) must be prepared for major rules with economically significant
effects ($100 million or more in any 1 year).
We estimate that the cost to the Medicare program for IRF services
in FY 2006 will increase by $210 million over FY 2005 levels. The
updates to the IRF labor-related share and wage indices are made in a
budget neutral manner. We are making changes to the CMGs and the tiers,
the teaching status adjustment, and the rural and LIP adjustments in a
budget neutral manner (that is, in order that total estimated aggregate
payments with the changes equal total estimated aggregate payments
without the changes). This means that we are improving the distribution
of payments among facilities depending on the mix of patients they
treat, their teaching status, their geographic location (rural vs.
urban), and the percentage of low-income patients they treat, without
changing total estimated aggregate payments. To redistribute payments
among facilities, we lowered the base payment amount, which then gets
adjusted upward for each facility according to the facility's
characteristics. This redistribution will not, however, affect
estimated aggregate payments to facilities. Thus, the changes to the
IRF labor-related share and the wage indices, the changes to the CMGs,
the tiers, and the motor score index, the teaching status adjustment,
the update to the rural adjustment, and the update to the LIP
adjustment have no overall effect on estimated costs to the Medicare
program. Therefore, the estimated increased cost to the Medicare
program is due to the combined effect of the updated IRF market basket
of 3.6 percent, the 1.9 percent reduction to the standard payment
conversion factor to account for changes in coding that affect total
aggregate payments, and the update to the outlier threshold amount. We
have determined that this final rule is a major rule as defined in 5
U.S.C. 804(2). Based on the overall percentage change in payments per
case estimated using our payment simulation model (a 3.4 percent
increase), we estimate that the total impact of these changes for
estimated FY 2006 payments compared to estimated FY 2005 payments will
be approximately a $210 million increase. This amount does not reflect
changes in IRF admissions or case-mix intensity, which also may affect
the overall estimated change in payments from FY 2005 to FY 2006.
2. Regulatory Flexibility Act (RFA)
The RFA requires agencies to analyze the economic impact of our
regulations on small entities. If we determine that the regulation will
impose a significant burden on a substantial number of small entities,
we must examine options for reducing the burden. For purposes of the
RFA, small entities include small businesses, nonprofit organizations,
and government agencies. Most IRFs and most other providers and
suppliers are considered small entities, either by nonprofit status or
by having revenues of $6 million to $29 million in any 1 year. (For
details, see the Small Business Administration's regulation that set
forth size standards for health care industries at 65 FR 69432.)
Because we lack data on individual hospital receipts, we cannot
determine the number of small proprietary IRFs. Therefore, we assume
that all IRFs (approximate total of 1,200 IRFs, of which approximately
60 percent are nonprofit facilities) are considered small entities for
the purpose of the analysis that follows. Medicare fiscal
intermediaries and carriers are not considered to be small entities.
Individuals and States are not included in the definition of a small
entity.
3. Impact on Rural Hospitals
Section 1102(b) of the Act requires us to prepare a regulatory
impact analysis for any final rule that 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.
With the exception of hospitals located in certain New England
counties, for purposes of section 1102(b) of the Act, we previously
defined a small rural hospital as a hospital with fewer than 100 beds
that is located outside of a Metropolitan Statistical Area (MSA) or New
England County Metropolitan Area (NECMA). However, under the new labor
market definitions that we are adopting, we will no longer employ
NECMAs to define urban areas in New England. Therefore, for purposes of
this analysis, we now define a small rural hospital as a hospital with
fewer than 100 beds that is located outside of a Metropolitan
Statistical Area (MSA).
As discussed in detail below, the rates and policies set forth in
this final rule will not have an adverse impact on rural hospitals
based on the data of the 169 rural units and 21 rural hospitals in our
database of 1,188 IRFs for which data were available.
4. Unfunded Mandates Reform Act
Section 202 of the Unfunded Mandates Reform Act of 1995 (Pub. L.
104-4) also requires that agencies assess anticipated costs and
benefits before issuing any final rule that may result in expenditures
in any 1 year by State, local, or tribal governments, in the aggregate,
or by the private sector, of at least $110 million. This final rule
will not mandate any requirements for State, local, or tribal
governments, nor will it affect private sector costs.
5. Executive Order 13132
Executive Order 13132 establishes certain requirements that an
agency must meet when it promulgates a final rule that imposes
substantial direct requirement costs on State and local governments,
preempts State law, or otherwise has Federalism implications. We have
reviewed this final rule in light of Executive Order 13132 and have
determined that it will not have any negative impact on the rights,
roles, or responsibilities of State, local, or tribal governments.
6. Overall Impact
The following analysis, in conjunction with the remainder of this
document, demonstrates that this final rule is consistent with the
regulatory philosophy and principles identified in Executive Order
12866, the RFA, and section 1102(b) of the Act. We have determined that
the final rule has a significant economic impact on a substantial
number of small entities or a significant impact on the operations of a
substantial number of small rural hospitals.
B. Anticipated Effects of the Final Rule
We discuss below the impacts of this final rule on the budget and
on IRFs.
1. Basis and Methodology of Estimates
In this final rule, we are implementing policy changes and payment
rate updates for the IRF PPS. Based on the overall percentage change in
payments per discharge estimated using a payment simulation model
developed by RAND under contract with CMS (a 3.4 percent increase), we
estimate the total impact of these changes for estimated FY 2006
payments compared to estimated FY 2005 payments to be approximately a
$210 million increase. This amount does not reflect changes in hospital
admissions or case-mix intensity, which also may affect the overall
change in payments from FY 2005 to FY 2006.
We have prepared separate impact analyses of each of the changes to
the IRF PPS. RAND's payment simulation model relies on the most recent
available data (FY 2003) to enable us to estimate the impacts on
payments per discharge of certain changes we are implementing in this
final rule.
The data used in developing the quantitative analyses of estimated
changes in payments per discharge
[[Page 47946]]
presented below are taken from the FY 2003 MedPAR file and the most
current Provider-Specific File that is used for payment purposes. Data
from the most recently available IRF cost reports were used to estimate
costs and to categorize hospitals. The data also include the FY 2004
home office costs for HealthSouth facilities, as described in section
IV of the preamble to this final rule.
Our analysis has several qualifications. First, we do not make
adjustments for behavioral changes that hospitals may adopt in response
to the policy changes, and we do not adjust for future changes in such
variables as admissions, lengths of stay, or case-mix. Second, due to
the interdependent nature of the IRF PPS payment components, it is very
difficult to precisely quantify the impact associated with each change.
Using cases in the FY 2003 MedPAR file, we simulated payments under
the IRF PPS given various combinations of payment parameters.
The changes discussed separately below are the following:
The effects of the annual market basket update (using the
rehabilitation hospital, psychiatric hospital, and long-term care
hospital (RPL) market basket) to IRF PPS payment rates required by
sections 1886(j)(3)(A)(i) and 1886(j)(3)(C) of the Act.
The effects of applying the budget-neutral labor-related
share and wage index adjustment, as required under section 1886(j)(6)
of the Act.
The effects of the decrease to the standard payment amount
to account for the increase in estimated aggregate payments due to
changes in coding, as required under section 1886(j)(2)(C)(ii) of the
Act.
The effects of the budget-neutral changes to the tier
comorbidities, CMGs, motor score index, and relative weights, under the
authority of section 1886(j)(2)(C)(i) of the Act.
The effects of the one year budget-neutral transition
policy for adopting the new CBSA-based geographic area definitions
announced by OMB in June 2003.
The effects of the 3 year budget-neutral hold-harmless
policy for IRFs that are rural under Sec. 412.602 during FY 2005, but
are urban under Sec. 412.602 during FY 2006 and lose the rural
adjustment resulting in a loss of estimated IRF PPS payments and meets
the intent of the hold harmless policy.
The effects of the implementation of a budget-neutral
teaching status adjustment, as permitted under section 1886(j)(3)(A)(v)
of the Act.
The effects of the budget-neutral update to the percentage
amount by which payments are adjusted for IRFs located in rural areas,
as permitted under section 1886(j)(3)(A)(v) of the Act.
The effects of the budget-neutral update to the formula
used to calculate the payment adjustment for IRFs based on the
percentage of low-income patients they treat, as permitted under
section 1886(j)(3)(A)(v) of the Act.
The effects of the change to the outlier loss threshold
amount to maintain total estimated outlier payments at 3 percent of
total estimated payments to IRFs in FY 2006, consistent with section
1886(j)(4) of the Act.
The total change in estimated payments based on the FY
2006 policies relative to estimated payments based on FY 2005 policies.
To illustrate the impacts of the FY 2006 estimated changes, our
analysis begins with a FY 2005 baseline simulation model using: IRF
charges from FY 2003 inflated to FY 2005 using the market basket; the
FY 2005 PRICER; the estimated percent of outlier payments in FY 2005;
the FY 2005 CMG GROUPER (version 1.22); the MSA designations for IRFs
based on OMB's MSA definitions prior to June 2003; the FY 2005 wage
index; the FY 2005 labor-market share; the FY 2005 formula for the LIP
adjustment; and the FY 2005 percentage amount of the rural adjustment.
Each policy change is then added incrementally to this baseline
model, finally arriving at an FY 2006 model incorporating all of the
changes to the IRF PPS. This allows us to isolate the effects of each
change. Note that, in computing estimated payments per discharge for
each of the policy changes, the outlier loss threshold has been
adjusted so that estimated outlier payments are 3 percent of total
estimated payments.
Our final comparison illustrates the percent change in estimated
payments per discharge from FY 2005 to FY 2006. One factor that affects
the changes in IRFs' estimated payments from FY 2005 to FY 2006 is that
we currently estimate total outlier payments during FY 2005 to be 1.2
percent of total estimated payments. As discussed in the August 7, 2001
final rule (66 FR at 41362), our policy is to set total estimated
outlier payments at 3 percent of total estimated payments. Because
estimated outlier payments during FY 2005 were below 3 percent of total
payments, estimated outlier payments in FY 2006 are projected to
increase by an additional 1.8 percent over estimated payments in FY
2005 because of the change in the outlier loss threshold to achieve the
3 percent target.
2. Analysis of Table 13
Table 13 displays the results of our analysis. The table
categorizes IRFs by geographic location, including urban or rural
location and location with respect to CMS' nine regions of the country.
In addition, the table divides IRFs into those that are separate
rehabilitation hospitals (otherwise called freestanding hospitals in
this section), those that are rehabilitation units of a hospital
(otherwise called hospital units in this section), rural or urban
facilities by ownership (otherwise called for-profit, non-profit, and
government), and by teaching status. The top row of the table shows the
overall impact on the 1,188 IRFs included in the analysis.
The next twelve rows of Table 13 contain IRFs categorized according
to their geographic location, designation as either a freestanding
hospital or a unit of a hospital, and by type of ownership: All urban,
which is further divided into urban units of a hospital, urban
freestanding hospitals, by type of ownership, and rural, which is
further divided into rural units of a hospital, rural freestanding
hospitals, and by type of ownership. There are 998 IRFs located in
urban areas included in our analysis. Among these, there are 802 IRF
units of hospitals located in urban areas and 196 freestanding IRF
hospitals located in urban areas. There are 190 IRFs located in rural
areas included in our analysis. Among these, there are 169 IRF units of
hospitals located in rural areas and 21 freestanding IRF hospitals
located in rural areas. There are 354 for-profit IRFs. Among these,
there are 295 IRFs in urban areas and 59 IRFs in rural areas. There are
708 non-profit IRFs. Among these, there are 603 urban IRFs and 105
rural IRFs. There are 126 government-owned IRFs. Among these, there are
100 urban IRFs and 26 rural IRFs.
The following three parts of Table 13 show IRFs grouped by their
geographic location within a region, and the last part groups IRFs by
teaching status. First, IRFs located in urban areas are categorized
with respect to their location within a particular one of nine
geographic regions. Second, IRFs located in rural areas are categorized
with respect to their location within a particular one of the nine CMS
regions. In some cases, especially for rural IRFs located in the New
England, Mountain, and Pacific regions, the number of IRFs represented
is small. Finally, IRFs are grouped by teaching status, including non-
teaching IRFs, IRFs with an intern and resident to ADC ratio less than
10 percent, IRFs with an intern and resident to ADC ratio greater than
or
[[Page 47947]]
equal to 10 percent and less than or equal to 19 percent, and IRFs with
an intern and resident to ADC ratio greater than 19 percent.
Table 13.--Projected Impact of FY 2006 Refinements to the IRF PPS
--------------------------------------------------------------------------------------------------------------------------------------------------------
New CMG,
FY06 Wage new Teach.
Number of Number of Index and Outlier Market tiers, Rural New LIP Status 1.9% Total
Facility classification (1) IRFs (2) cases Labor- (5) Basket and motor adjust. adjust. adjust. reduct. change %
(3) share (6) score (8) (9) (10) (11) (12)
(4) (7)
--------------------------------------------------------------------------------------------------------------------------------------------------------
Total.......................... 1,188 461,738 0.0% 1.8% 3.6% 0.0% 0.0% 0.0% 0.0% -1.9% 3.4
Urban unit..................... 802 261,229 0.1 2.3 3.6 0.9 -0.2 0.1 0.5 -1.9 5.3
Rural unit..................... 169 34,664 -1.3 3.1 3.6 1.7 1.3 -0.1 -0.9 -1.9 5.5
Urban hospital................. 196 158,968 0.2 0.5 3.6 -1.7 0.0 -0.1 -0.5 -1.9 0.0
Rural hospital................. 21 6,877 -1.6 7.0 3.6 -0.7 1.3 0.0 -1.0 -1.9 6.5
Urban For-Profit............... 295 154,526 0.4 0.7 3.6 -1.8 0.0 0.0 -0.8 -1.9 0.0
Rural For-Profit............... 59 11,952 -1.9 3.8 3.6 0.2 1.3 0.2 -1.0 -1.9 4.2
Urban Non-Profit............... 603 237,384 0.0 2.1 3.6 1.0 -0.2 0.0 0.5 -1.9 5.0
Rural Non-Profit............... 105 23,793 -1.0 4.1 3.6 1.7 1.3 -0.3 -0.8 -1.9 6.7
Urban Government............... 100 28,287 -0.2 2.5 3.6 0.5 0.0 0.5 1.7 -1.9 6.7
Rural Government............... 26 5,796 -1.5 2.6 3.6 1.4 1.3 0.3 -1.0 -1.9 4.8
Urban.......................... 998 420,197 0.1 1.6 3.6 -0.1 -0.1 0.0 0.1 -1.9 3.2
Rural.......................... 190 41,541 -1.4 3.8 3.6 1.2 1.3 -0.1 -0.9 -1.9 5.7
Urban by region:
New England................ 35 20,612 -0.3 1.7 3.6 -0.7 -0.3 -0.3 -0.6 -1.9 1.1
Middle Atlantic............ 156 76,962 -0.4 2.0 3.6 1.1 -0.2 0.0 1.6 -1.9 5.8
South Atlantic............. 124 73,677 0.4 0.6 3.6 -0.5 0.1 0.0 -0.3 -1.9 1.9
East North Central......... 189 69,315 0.1 2.3 3.6 1.2 -0.2 -0.2 0.1 -1.9 4.9
East South Central......... 54 30,473 0.2 0.0 3.6 -1.4 0.4 0.1 -0.5 -1.9 0.6
West North Central......... 71 22,217 -0.1 2.1 3.6 0.6 -0.2 -0.1 0.1 -1.9 4.2
West South Central......... 184 76,088 0.5 1.8 3.6 -0.7 -0.3 -0.1 -0.5 -1.9 2.3
Mountain................... 69 24,287 -0.2 1.2 3.6 -2.2 -0.1 -0.1 -0.5 -1.9 -0.2
Pacific.................... 116 26,566 0.8 2.2 3.6 -0.8 -0.3 1.1 0.0 -1.9 4.7
Rural by region:
New England................ 4 924 0.4 2.1 3.6 1.7 1.2 -0.4 -0.9 -1.9 5.9
Middle Atlantic............ 19 5,377 -1.1 8.2 3.6 1.5 1.4 -0.4 -1.0 -1.9 10.3
South Atlantic............. 22 5,440 -1.0 2.5 3.6 1.2 1.3 0.1 -1.0 -1.9 4.8
East North Central......... 28 5,618 -1.0 3.0 3.6 1.9 1.2 -0.4 -0.9 -1.9 5.5
East South Central......... 20 5,362 -1.9 2.2 3.6 1.1 1.3 0.3 -0.7 -1.9 3.9
West North Central......... 30 5,351 -1.3 2.3 3.6 2.7 1.2 -0.2 -0.6 -1.9 5.8
West South Central......... 54 12,016 -1.7 4.3 3.6 0.3 1.3 0.1 -1.0 -1.9 4.9
Mountain................... 9 902 -3.2 9.4 3.6 2.6 1.2 -0.4 -0.9 -1.9 10.2
Pacific.................... 4 551 0.9 2.8 3.6 -2.7 1.1 -0.8 -0.8 -1.9 2.0
Teaching status:
Non-teaching............... 1,053 400,072 0.0 1.6 3.6 -0.1 0.0 -0.1 -0.9 -1.9 2.2
Resident to ADC less than 71 39,888 0.3 2.5 3.6 0.3 -0.3 0.2 2.2 -1.9 7.0
10%.......................
Resident to ADC 10%-19%.... 42 17,793 -0.9 2.8 3.6 0.4 -0.3 1.1 9.1 -1.9 14.3
Resident to ADC greater 22 3,985 -0.1 4.1 3.6 0.0 -0.3 1.1 19.5 -1.9 27.4
than 19%..................
---------------------------------------