[Federal Register: May 4, 2007 (Volume 72, Number 86)]
[Proposed Rules]
[Page 25355-25481]
From the Federal Register Online via GPO Access [wais.access.gpo.gov]
[DOCID:fr04my07-17]
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Part II
Department of Health and Human Services
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Centers for Medicare and Medicaid Services
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42 CFR Part 484
Medicare Program; Home Health Prospective Payment System Refinement and
Rate Update for Calendar Year 2008; Proposed Rule
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DEPARTMENT OF HEALTH AND HUMAN SERVICES
Centers for Medicare & Medicaid Services
42 CFR Part 484
[CMS-1541-P]
RIN 0938-AO32
Medicare Program; Home Health Prospective Payment System
Refinement and Rate Update for Calendar Year 2008
AGENCY: Centers for Medicare & Medicaid Services (CMS), HHS.
ACTION: Proposed rule.
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SUMMARY: This proposed rule would set forth an update to the 60-day
national episode rates and the national per-visit amounts under the
Medicare prospective payment system for home health services, effective
on January 1, 2008. As part of this proposed rule, we are also
proposing to rebase and revise the home health market basket to ensure
it continues to adequately reflect the price changes of efficiently
providing home health services. This proposed rule also would set forth
the refinements to the payment system. In addition, this proposed rule
would establish new quality of care data collection requirements.
DATES: To be assured consideration, comments must be received at one of
the addresses provided below, no later than 5 p.m. on July 3, 2007.
ADDRESSES: In commenting, please refer to file code CMS-1541-P. Because
of staff and resource limitations, we cannot accept comments by
facsimile (FAX) transmission.
You may submit comments in one of four ways (no duplicates,
please):
1. Electronically. You may submit electronic comments on specific
issues in this regulation to http://www.cms.hhs.gov/eRulemaking. Click
on the link ``Submit electronic comments on CMS regulations with an
open comment period.'' (Attachments should be in Microsoft Word,
WordPerfect, or Excel; however, we prefer Microsoft Word.)
2. By regular mail. You may mail written comments (one original and
two copies) to the following address ONLY: Centers for Medicare &
Medicaid Services, Department of Health and Human Services, Attention:
CMS-1541-P, P.O. Box 8012, Baltimore, MD 21244-8012.
Please allow sufficient time for mailed comments to be received
before the close of the comment period.
3. By express or overnight mail. You may send written comments (one
original and two copies) to the following address ONLY: Centers for
Medicare & Medicaid Services, Department of Health and Human Services,
Attention: CMS-1541-P, Mail Stop C4-26-05, 7500 Security Boulevard,
Baltimore, MD 21244-1850.
4. By hand or courier. If you prefer, you may deliver (by hand or
courier) your written comments (one original and two copies) before the
close of the comment period to one of the following addresses. If you
intend to deliver your comments to the Baltimore address, please call
telephone number (410) 786-7195 in advance to schedule your arrival
with one of our staff members. Room 445-G, Hubert H. Humphrey Building,
200 Independence Avenue, SW., Washington, DC 20201; or 7500 Security
Boulevard, Baltimore, MD 21244-1850.
(Because access to the interior of the HHH Building is not readily
available to persons without Federal Government identification,
commenters are encouraged to leave their comments in the CMS drop slots
located in the main lobby of the building. A stamp-in clock is
available for persons wishing to retain a proof of filing by stamping
in and retaining an extra copy of the comments being filed.)
Comments mailed to the addresses indicated as appropriate for hand
or courier delivery may be delayed and received after the comment
period.
Submission of comments on paperwork requirements. You may submit
comments on this document's paperwork requirements by mailing your
comments to the addresses provided at the end of the ``Collection of
Information Requirements'' section in this document.
For information on viewing public comments, see the beginning of
the SUPPLEMENTARY INFORMATION section.
FOR FURTHER INFORMATION CONTACT: Randy Throndset, (410) 786-0131.
General Issues: Sharon Ventura, (410) 786-1985.
Clinical (OASIS) Issues: Kathy Walch, (410) 786-7970.
Quality Issues: Doug Brown, (410) 786-0028.
Market Basket Update Issues: Mollie Knight, (410) 786-7948; and
Heidi Oumarou, (410) 786-7942.
SUPPLEMENTARY INFORMATION:
Submitting Comments: We welcome comments from the public on all
issues set forth in this rule to assist us in fully considering issues
and developing policies. You can assist us by referencing the file code
CMS-1541-P and the specific ``issue identifier'' that precedes the
section on which you choose to comment.
Inspection of Public Comments: All comments received before the
close of the comment period are available for viewing by the public,
including any personally identifiable or confidential business
information that is included in a comment. We post all comments
received before the close of the comment period on the following Web
site as soon as possible after they have been received: http://www.cms.hhs.gov/eRulemaking.
Click on the link ``Electronic Comments on
CMS Regulations'' on that Web site to view public comments.
Comments received timely will also be available for public
inspection as they are received, generally beginning approximately 3
weeks after publication of a document, at the headquarters of the
Centers for Medicare & Medicaid Services, 7500 Security Boulevard,
Baltimore, Maryland 21244, Monday through Friday of each week from 8:30
a.m. to 4 p.m. To schedule an appointment to view public comments,
phone 1-800-743-3951.
Table of Contents
I. Background
A. Requirements of the Balanced Budget Act of 1997 for Updating
the Prospective Payment System for Home Health Services
B. Deficit Reduction Act of 2005
C. Updates to the HH PPS
D. System for Payment of Home Health Services
E. Summary of Home Health Payment Research
II. Provisions of the Proposed Regulation
A. Refinements to the Home Health Prospective Payment System
1. Current Payment Model
2. Refinements to the Case-Mix Model
a. Analysis of Later Episodes
b. Addition of Variables
c. Addition of Therapy Thresholds
d. Determining the Case-Mix Weights
3. Description & Analysis of Case-Mix Coding Change Under the HH
PPS
a. Change in Case-Mix Group Frequencies
b. Health Characteristics Reported on the OASIS
c. Impact of the Context of OASIS Reporting
4. Partial Episode Payment Adjustment (PEP Adjustment) Review
5. Low-Utilization Payment Adjustment (LUPA) Review
6. Significant Change in Condition (SCIC) Adjustment Review
7. Non-Routine Medical Supply (NRS) Amounts Review
8. Outlier Payment Review
B. Rebasing and Revising the Home Health Market Basket
1. Background
2. Rebasing and Revising the Home Health Market Basket
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3. Price Proxies Used To Measure Cost Category Growth
4. Rebasing Results
5. Labor-Related Share
C. National Standardized 60-Day Episode Payment Rate
D. Proposed CY 2008 Rate Update by the Home Health Market Basket
Index (With Examples of Standard 60-Day and LUPA Episode Payment
Calculations)
E. Hospital Wage Index
1. Background
2. Update
F. Home Health Care Quality Improvement
III. Collection of Information Requirements
IV. Response to Comments
V. Regulatory Impact Analysis
A. Overall Impact
B. Anticipated Effects
C. Accounting Statement
I. Background
[If you choose to comment on issues in this section, please include
the caption ``BACKGROUND'' at the beginning of your comments.]
A. Requirements of the Balanced Budget Act of 1997 for Updating the
Prospective Payment System for Home Health Services
The Balanced Budget Act of 1997 (BBA) (Pub. L. 105-33) enacted on
August 5, 1997, significantly changed the way Medicare pays for
Medicare home health services. Until the implementation of a home
health prospective payment system (HH PPS) on October 1, 2000, home
health agencies (HHAs) received payment under a cost-based
reimbursement system. Section 4603 of the BBA governed the development
of the HH PPS.
Section 4603(a) of the BBA provides the authority for the
development of a PPS for all Medicare-covered home health services
provided under a plan of care that were paid on a reasonable cost basis
by adding section 1895, entitled ``Prospective Payment For Home Health
Services,'' to the Social Security Act (the Act).
Section 1895(b)(1) of the Act requires the Secretary to establish a
PPS for all costs of home health services paid under Medicare.
Section 1895(b)(3)(A) of the Act requires that (1) The computation
of a standard prospective payment amount include all costs for home
health services covered and paid for on a reasonable cost basis and be
initially based on the most recent audited cost report data available
to the Secretary, and (2) the prospective payment amounts be
standardized to eliminate the effects of case-mix and wage levels among
HHAs.
Section 1895(b)(3)(B) of the Act addresses the annual update to the
standard prospective payment amounts by the home health applicable
increase percentage as specified in the statute.
Section 1895(b)(4) of the Act governs the payment computation.
Sections 1895(b)(4)(A)(i) and (b)(4)(A)(ii) of the Act require the
standard prospective payment amount to be adjusted for case-mix and
geographic differences in wage levels. Section 1895(b)(4)(B) of the Act
requires the establishment of an appropriate case-mix adjustment factor
that explains significant variation in costs among different units of
services. Similarly, section 1895(b)(4)(C) of the Act requires the
establishment of wage adjustment factors that reflect the relative
level of wages, and wage-related costs applicable to home health
services furnished in a geographic area compared to the applicable
national average level. These wage-adjustment factors may be used by
the Secretary for the different geographic wage levels for purposes of
section 1886(d)(3)(E) of the Act.
Section 1895(b)(5) of the Act gives the Secretary the option to
make additions or adjustments to the payment amount otherwise made in
the case of outliers because of unusual variations in the type or
amount of medically necessary care. Total outlier payments in a given
fiscal year (FY) may not exceed 5 percent of total payments projected
or estimated.
In accordance with the statute, we published a final rule (65 FR
41128) in the Federal Register on July 3, 2000 to implement the HH PPS
legislation. This final rule established requirements for the new PPS
for home health services as required by section 4603 of the BBA, and as
subsequently amended by section 5101 of the Omnibus Consolidated and
Emergency Supplemental Appropriations Act (OCESAA) for Fiscal Year
1999, (Pub. L. 105-277), enacted on October 21, 1998; and by sections
302, 305, and 306 of the Medicare, Medicaid, and SCHIP Balanced Budget
Refinement Act (BBRA) of 1999, (Pub. L. 106-113), enacted on November
29, 1999. The requirements include the implementation of a PPS for home
health services, consolidated billing requirements, and a number of
other related changes. The HH PPS described in that rule replaced the
retrospective reasonable-cost-based system that was used by Medicare
for the payment of home health services under Part A and Part B.
For a complete and full description of the HH PPS as required by
the BBA, see the July 2000 HH PPS final rule.
B. Deficit Reduction Act of 2005
On February 8, 2006, the Deficit Reduction Act (DRA) of 2005 (Pub.
L. 109-171) was enacted. This legislation affected updates to HH
payment rates for CY 2006. The DRA also introduces home health care
quality data and its effects on payments to HHAs beginning in CY 2007.
Specifically, section 5201 of the DRA changed the CY 2006 update
from the applicable home health market basket percentage increase minus
0.8 percentage point to a 0 percent update.
In addition, section 5201 of the DRA amends section 421(a) of the
Medicare Prescription Drug, Improvement, and Modernization Act of 2003
(MMA) (Pub. L. 108-173, enacted on December 8, 2003). The amended
section 421(a) of the MMA requires that for home health services
furnished in a rural area (as defined in section 1886(d)(2)(D) of the
Act) on or after January 1, 2006 and before January 1, 2007, that the
Secretary increase the payment amount otherwise made under section 1895
of the Act for home health services by 5 percent. The statute waives
budget neutrality for purposes of this increase since it specifically
states that the Secretary must not reduce the standard prospective
payment amount (or amounts) under section 1895 of the Act applicable to
home health services furnished during a period to offset the increase
in payments resulting in the application of this section of the
statute.
The 0 percent update to the payment rates and the rural add-on
provisions of the DRA were implemented through Pub. L. 100-20, One Time
Notification, Transmittal 211 issued on February 10, 2006.
In addition, section 5201 of the DRA requires HHAs to submit data
for purposes of measuring health care quality. This requirement is
applicable for CY 2007 and each subsequent year. If an HHA does not
submit quality data, the home health market basket percentage increase
will be reduced 2 percentage points.
C. Updates to the HH PPS
As required by section 1895(b)(3)(B) of the Act, we have
historically updated the HH PPS rates annually in a separate Federal
Register document. In those documents, we also incorporated the
legislative changes to the system required by the statute after the
BBA, specifically the MMA. On November 9, 2006, we published a final
rule titled ``Medicare Program; Home Health Prospective Payment System
Rate Update for Calendar Year 2007 and Deficit Reduction Act of 2005
Changes
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to Medicare Payment for Oxygen Equipment and Capped Rental Durable
Medical Equipment; Final Rule'' (CMS-1304-F) (71 FR 65884) in the
Federal Register that updated the 60-day national episode rates and the
national per-visit amounts under the Medicare PPS for home health
services for CY 2007. In addition, this final rule ended the one-year
transition period that consisted of a blend of 50 percent of the new
area labor marker designations' wage index and 50 percent of the
previous area labor market designations' wage index. We also revised
the fixed dollar loss ratio, which is used in the calculation of
outlier payments. According to section 5201(c)(2) of the DRA, this
final rule also reduced, by 2 percentage points, the home health market
basket percentage increase to HHAs that did not submit required quality
data, as determined by the Secretary.
D. System for Payment of Home Health Services
Generally, Medicare makes payment under the HH PPS on the basis of
a national standardized 60-day episode payment rate that is adjusted
for case-mix and wage index. The national standardized 60-day episode
payment rate includes the six home health disciplines (skilled nursing,
home health aide, physical therapy, speech-language pathology,
occupational therapy, and medical social services) and medical
supplies. Durable medical equipment covered under home health is paid
for outside the HH PPS payment. To adjust for case mix, the HH PPS uses
an 80-category case-mix classification to assign patients to a home
health resource group (HHRG). Clinical, functional, and service
utilization are computed from responses to selected data elements in
the OASIS assessment instrument.
For episodes with four or fewer visits, Medicare pays on the basis
of a national per-visit amount by discipline, referred to as a LUPA.
Medicare also adjusts the national standardized 60-day episode payment
rate for certain intervening events that are subject to a partial
episode payment adjustment (PEP adjustment) or a significant change in
condition adjustment (SCIC adjustment). For certain cases that exceed a
specific cost threshold, an outlier adjustment may also be available.
E. Summary of Home Health Payment Research
The objective of a prospective payment system that is case-mix
adjusted is to predict resource costs of providing care to similar
types of patients and to align payments to those costs. As MEDPAC
points out in their December 2005 Report to Congress, if the case-mix
is not aligned appropriately to resource costs, then the PPS may
overpay for some services and underpay for others.
Since the July 3, 2000 final rule, we have stated our intention to
monitor the new PPS and make refinements to the system as needed. We
believe refinements are now needed to improve the performance and
appropriateness of the HH PPS, which has not undergone major
refinements since its implementation in October of 2000. The general
goal of any refinements would be to ensure that the payment system
continues to produce appropriate compensation for providers while
retaining opportunities to manage home health care efficiently. Also
important in any refinement is maintaining an appropriate degree of
operational simplicity. The analytic goals of our refinement research
included improving the accuracy of the case-mix model, understanding
the descriptive characteristics of the program and the use of payment
adjusters, understanding variations in HHA margins, and the simulation
of potential changes to payment methodology.
We contracted with Abt Associates, Inc., of Cambridge,
Massachusetts to conduct several analyses in order to achieve these
objectives. In particular, the Abt Associates analyses focused on the
resource needs of long stay patients; alternatives to the current
therapy threshold; the potential for a more extensive set of variables
to improve the accuracy of the Clinical on Top (COT) model used to
define the HHRG; alternative ways to account for non-routine medical
supplies (NRS); utilization and episode characteristics; and HHA
margins. In order to conduct these analyses, Abt Associates primarily
used data files created from a 20 percent sample of claims data
collected between 2001 and 2004, Outcome and Assessment Information Set
(OASIS) data linked to claims, and cost reports. For measures of
resource use, Abt Associates used weighted minutes for the case-mix
refinements research. For research on accounting for nonroutine
supplies costs, Abt Associates analyzed supplies charges reported on
claims after adjusting them using cost-to-charge ratios from selected
cost reports. These analyses are described in more detail in section
II.A.
In addition to these analyses, two Technical Expert Panel (TEP)
meetings were conducted, under contract with Abt Associates, on
December 15, 2005, and March 14, 2006. These TEP meetings provided an
opportunity for experts, industry representatives, and practitioners in
the field of home health care to provide feedback on Abt's research
examining the HH PPS and exploration of payment policy alternatives.
Abt considered this feedback when developing recommendations for
refinements to the HH PPS. The refinements to the HH PPS described in
the following sections are the culmination of substantial research
efforts focusing on several areas identified for possible improvements.
II. Provisions of the Proposed Regulation
[If you choose to comment on issues in this section, include the
caption ``PROVISIONS OF THE PROPOSED REGULATIONS'' at the beginning of
your comments.]
A. Refinements to the Home Health Prospective Payment System
The Medicare HH PPS has been in effect since October 1, 2000. As
set forth in the final rule published July 3, 2000 in the Federal
Register (65 FR 41128), the unit of payment under the Medicare HH PPS
is a national standardized 60-day episode payment rate. As set forth in
42 CFR 484.220, we adjust the national standardized 60-day episode
payment rate by a case-mix grouping and a wage index value based on the
site of service for the beneficiary. Since the July 3, 2000 final rule,
we have stated our intention to monitor the new PPS and make
refinements to the system as needed. We believe refinements are now
required to improve the performance and appropriateness of payment for
the HH PPS. After implementation of the HH PPS, we received a number of
public comments suggesting ways in which the payment system could be
improved. We took those comments into consideration as we proceeded to
explore the HH PPS for potential areas for refinement. This proposed
rule sets forth the first major refinements to the HH PPS since its
implementation in October of 2000. This proposed rule identifies seven
major areas of the HH PPS that were identified as possible areas for
refinement. Those areas are: (1) The case mix model; (2) changes in
case mix coding; (3) the PEP adjustment; (4) the LUPA; (5) the SCIC
adjustment; (6) method of accounting for NRS, and (7) the outlier
adjustment. While this proposed rule proposes to implement all of
refinements discussed in this rule effective January 1, 2008, we
recognize that there may be operational considerations, affecting CMS
or the
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industry, which could necessitate an implementation schedule that
results in certain refinements becoming effective on different dates (a
split-implementation). We would like to solicit suggestions and
comments from the public on this matter.
1. Current Payment Model
On July 3, 2000, we published a final rule (65 FR 41128) in the
Federal Register. In that rule, we described a system for home health
case-mix adjustment developed under a research contract with Abt
Associates, Inc., of Cambridge, Massachusetts. Using selected data
elements from the OASIS and an additional data element measuring
receipt of at least 10 visits for therapy services, the case-mix system
projects patient resource use based on patient characteristics. These
data elements were selected because they were shown to influence home
health resource utilization upon statistical analysis of data from
approximately 30,000 episodes. This model used data from first episodes
only and a relatively small set of clinical, functional, and service
utilization variables. Clinical judgment, the relative predictive value
of potential case-mix variables, their susceptibility to gaming and
subjectivity, and administrative implications were considered in the
final resolution of the elements retained in the final model.
The data elements are organized into three dimensions to capture
clinical severity factors, functional severity factors, and services
utilization factors influencing case-mix. In the clinical and
functional dimensions, each data element is assigned a score value
derived from multiple regression analysis of the Abt research data. The
score value measures the impact of the data element on total resource
use. Scores are also assigned to data elements in the services
utilization dimension. To find a patient's case-mix group, the case-mix
grouper software sums the patient's scores within each of the three
dimensions. The resulting sum is used to assign the patient to a
severity level in each dimension. There are four clinical severity
levels, five functional severity levels, and four services utilization
severity levels. Thus, there are 80 possible combinations of severity
levels across the three dimensions. Each combination defines one of the
80 HHRGs in the case-mix system. For example, a patient with high
clinical severity, moderate functional severity, and low services
utilization severity is placed in the same group with all other
patients whose summed scores place them in the same set of severity
levels for the three dimensions.
We summarized the performance of the final PPS model for the PPS
using the R-squared statistic. An initial episode was defined as the
first home health episode of care for a given beneficiary in a sequence
of adjacent episodes. For the purposes of our analysis, we defined a
sequence of adjacent episodes for a beneficiary as a series of claims
with no more than 60 days without home care between the end of one
episode, which is the 60th day (except for episodes that have been PEP-
adjusted), and the beginning of the next episode. At the time, based on
data from the model development sample, this model's R-squared
statistic was 0.34. In other words, the model explained 34 percent of
the variation in resource use.
2. Refinements to the Case-Mix Model
Extensive research has been conducted to investigate ways to
improve the performance of the case-mix model. We found that the
addition of separate regression equations to account for later episodes
and multiple therapy thresholds (replacing the current threshold of 10
therapy visits) significantly improved the fit and performance of the
case-mix model. Further, we expanded the set of variables to include
new diagnosis groups, comorbidities, and interactions, yielding models
that performed better in simulations. We feel that these changes would
improve the HH PPS by allowing more accurate case-mix adjustment
without providing incentives for providers to distort appropriate
patterns of care.
As with the original case-mix model, the general approach to
developing a case-mix model was to use patient data and other
appropriate data to create a regression model for resource use over the
course of a 60-day episode. Case-mix refinement analysis focused on
investigating resource use in episodes that occur later in treatment as
well as the initial episode; testing additional clinical, functional,
and demographic variables; exploring the effect of comorbidities; and
testing new therapy thresholds.
The basis for selecting these areas of analysis will be described
in sections II.2.a., II.2.b., and II.2.c.
As with our case-mix studies that resulted in the case-mix
methodology discussed in the July 3, 2000 HH PPS final rule, the
dependent variable in these refinement studies is an estimate of cost
known as resource cost. To derive the resource cost estimate, the total
minutes reported on the claim for each discipline's visits are
converted to a resource cost. Resource cost results from weighting each
minute by the national average labor market hourly rate for the
individual discipline that provided the minutes of care. Bureau of
Labor Statistics data are used to derive the hourly rate. The sum of
the weighted minutes is the total resource cost estimate for the claim.
This method standardizes the resource cost for all episodes in the
analysis file.
Based on the findings of our analysis of the case-mix adjustment
under HH PPS, which we describe in section II.A.2, we propose that the
case-mix adjustment be refined to incorporate an expanded set of case-
mix variables to capture the additional clinical conditions and
comorbidities; four separate regression models that recognize four
different types of episodes; and a graduated, three-threshold approach
to accounting for therapy utilization. We refer to the four separate
regression models in this proposed case-adjustment system as the four-
equation model. The first regression equation is for low-therapy
episodes (less than 14 therapy visits) that occur as the first or
second episode in a series of adjacent episodes (Episodes are
considered to be ``adjacent'' if they are separated by no more than a
60-day period between claims). The second regression equation is for
high-therapy episodes (14 or more therapy visits) occurring as the
first or second episode in a series of adjacent episodes. The third
equation is for low-therapy episodes (under 14 therapy visits)
occurring after the second episode in a series of adjacent episodes.
And the fourth equation is for high-therapy episodes (14 or more
therapy visits) occurring after the second episode in a series of
adjacent episodes. As described in further detail below, these
equations incorporate a graduated, three-threshold approach to
accounting for therapy utilization. The 153 case mix groups created
from the results of the four-equation model are also described below,
as is the method we used to form the groups.
a. Analysis of Later Episodes
As a starting point for our analysis, we examined the performance
of our original model using data, derived from the National Claims
History, reflecting the period after the HH PPS was initiated. These
data from the period after the commencement of the HH PPS, a large
random sample of claims from CY 2003, indicate the performance of the
case-mix model differs from the original estimate, which reflected data
from the time of the Abt case-mix study.
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The more recent data reflect both the inclusion of episodes beyond the
first episode as well as behavioral changes of health care providers
under the HH PPS. The R-squared statistic estimated from the more
recent data is approximately 0.21. An appropriate comparison with the
initial R-square statistic (0.34) is the R-squared value estimated from
the more recent data's initial episodes, which is 0.29. We therefore
believe the data reflect a more modest reduction in model performance
of 0.05. However, the value of the R-squared statistic calculated on
all the data, 0.21, is an indication that the case-mix model does not
fit non-initial episodes as well as it fits initial episodes.
Therefore, one focus of our refinement work was to investigate resource
use in episodes that occurred later in treatment as well as early
episodes.
Based on exploratory analysis, we defined ``early'' episodes to
include, not only the initial episode in a sequence of adjacent
episodes, but also the next adjacent episode, if any, that followed the
initial episode. ``Later'' episodes were defined as all adjacent
episodes beyond the second episode. When we analyzed the performance of
the case-mix model for later episodes, we determined there were two
important differences for episodes occurring later in the home health
treatment compared to earlier episodes: higher resource use per episode
and a different relationship between clinical conditions and resource
use.
Using a large, random sample of episodes, we found that the
estimated resource cost of early episodes is approximately 7 percent
lower than the estimated resource cost of later episodes. The current
case-mix model weights all episodes equally.
Furthermore, our exploratory regression models indicated that the
relationships between case-mix variables and resource use differed
between earlier and later episodes. This suggested that a scoring
system that differed for earlier and later episodes could potentially
perform better than a single scoring system. The system of four
separate regression equations allows the scores to differ according to
whether the episode is early or later. We recognize that this approach
introduces more complexity into the case-mix adjustment system.
However, less complex approaches that did not depend on separate
equations did not perform as well in terms of predictive accuracy; for
example, we explored using one equation in which we modeled additional
lump-sum costs due to the timing of an episode in a sequence of
adjacent episodes. This proved to be unsatisfactory because it
addressed only one of the two important differences presented by later
episodes, that is, their generally higher cost level.
For the purposes of payment, we propose to make changes to the
OASIS (see section III. Collection of Information Requirements), by
adding a new OASIS item to capture whether an episode is an early or
later episode. If an HHA is uncertain as to whether the episode is an
early or later episode, we propose to base payment as though the
episode were an early episode. Most patients do not have more than one
episode in a year. Consequently, we believe that selecting early as the
default is the best guess as to the eventual outcome of whether an
episode is early or later.
b. Addition of Variables
Since the system for case-mix adjustment was first implemented, we
have received comments suggesting ways in which case-mix adjustment may
be improved. Most of these comments requested that we add specific
variables or conditions to the case-mix model. We were also asked to
examine the appropriateness of including additional diagnosis groups,
comorbidities in general and specific comorbidities, for instance,
heart conditions, additional wound-related indicators, and other
patient characteristics. We considered these comments as we proceeded
to explore potential case-mix changes. We also considered comments
received during the initial rulemaking process, such as comments
pertaining to clinical issues and social characteristics such as
caregiver availability.
We evaluated variables for inclusion in a refined case-mix model in
much the same way that we did for the 2000 final rule, in that we
analyzed the relationship between resource use and patient
characteristics. Whereas the original case-mix study required us to
collect logs from a sample of episodes for the measure of resource use,
for this analysis, we were able to measure resource use directly from
the claims sample. The measures of patient characteristics come from
OASIS assessments. Under a contract with Fu Associates of Arlington,
Virginia, Standard Analytical Claims Files from the National Claims
History were cleaned, edited, and linked to the OASIS assessment
associated with the beginning of each claim period. Abt Associates
subsequently used these analytic files to draw large samples of claims
for analysis.
In the course of refining the current case-mix model, we continued
to monitor the performance of two special variables in explaining
resource use. These variables are dual-eligibility for Medicare and
Medicaid and caregiver support. The two variables are of interest to
some agencies because of their perceived impact on resource use and
overall profitability. Patients dually eligible for Medicare and
Medicaid may have health care needs that exceed the average needs due
to the health status and utilization differences associated with low-
income populations. Some agencies with caseloads containing large
numbers of dual eligibles have commented that they are penalized under
the HH PPS system because of their willingness to serve a disadvantaged
population without payments explicitly recognizing such agencies'
higher costs. We have also received comments that episodes involving
patients without a caregiver were underpaid by the HH PPS, and that
some agencies would be reluctant to admit such patients because of
financial implications. These commenters believe that the low admission
rate of patients without caregivers (about 2 percent of all episodes)
is evidence of this reluctance.
During our development of the original case-mix model implemented
in the July 2000 final rule, using the Abt Associates case-mix study
sample, we tested the Medicaid variable (which indicates whether
Medicaid was among the patient's payment sources). At that time, we
found that it did not contribute meaningfully in explaining variation
in resource use. Similarly, we tested the caregiver variable and it did
not contribute to explaining variation in resource cost, either.
Regarding the caregiver variable, we recognized in the July 3, 2000,
final rule that adjusting payment in response to the presence or
absence of a caregiver may be seen as inequitable. To the extent that
availability of caregiver services, particularly privately paid
services, reflects socioeconomic status differences, we indicated that
reducing payment for patients who have caregiver assistance may be
particularly sensitive in view of Medicare's role as an insurance
program rather than a social welfare program. Furthermore, we stated
that adjusting payment for caregiver factors would risk introducing new
and negative incentives into family and patient behavior. In the
discussion in the July 3, 2000 final rule (65 FR 41145), we also
indicated our belief that it is questionable whether Medicare should
adopt a payment policy that could weaken informal familial supports
currently benefiting patients at times when they are most vulnerable.
[[Page 25361]]
In our analysis for this proposed rule, we again tested variables
for dual eligibility and caregiver support. We operationalized the
Medicaid variable from the OASIS, using the presence of a Medicaid
number on the assessment as the indicator for Medicaid eligibility. We
found that Medicaid remains a marginal predictor at best, with a very
low score, after accounting for a broad range of clinical and
functional variables that predict resource use. We believe adding a
Medicaid variable is not justified in view of these results, especially
considering the added administrative burdens for both agencies and
Medicare that using such a variable would entail. These include costs
of ascertaining whether the reported Medicaid number is correct and
whether the eligibility status as reported on the assessment is
current.
We also operationalized a variable for support from a caregiver
from the OASIS assessment, item M0350, Assisting persons other than
home health agency staff. This variable identified patients without any
caregiver. While analyzing the payment adequacy of the four-equation
model (as explained further below) for patients without a caregiver we
found that, on average, episodes without caregivers would be
``underpaid''. However, the score to be gained by adding the variable
is not large (5 to 13 points, depending on the episode), and the
overall ability of the four-equation model to explain resource costs is
improved only minimally by adding this variable.
Therefore, we are not proposing that this variable be added to the
case-mix model. We continue to believe that including this kind of
variable in the case-mix system raises significant policy concerns. We
maintain that a case-mix adjustment should not discourage assistance
from family members of home care patients, nor should it make patients
feel there is some financial stake in how they report their familial
supports during their convalescence.
We continue to believe that adjusting payment in response to the
absence of a caregiver would introduce negative incentives with adverse
affects on home health Medicare beneficiaries. Furthermore, we are
doubtful that today's low rate of episodes without a caregiver (2 to 3
percent) reflects access barriers for these patients and nothing more.
We believe part of the reason for the low rate may be that under a
bundled payment system agencies are more careful about ascertaining
whether support is available and encourage use of caregivers within the
beneficiary's home.
For exploratory modeling of case-mix in our refinement work, in
addition to using existing case-mix variables from the OASIS, new
variables were created. Diagnosis codes reported on both the claims and
the OASIS were used extensively to form new or revised diagnosis groups
for inclusion in case-mix models. As a result, developmental models
included many new variables, including an expanded set of primary and
secondary diagnoses, as well as interaction terms that describe the
effect of combinations of patient conditions or characteristics on
resource cost. Using these new analytic files, it was possible to
explore some conditions that were too infrequent to study in the
original case-mix sample. For example, as suggested by commenters,
Abt's analysis tested the impact on resource use of having multiple
conditions from M0250, which reports on therapies received at home,
including intravenous infusion, and enteral and parenteral nutrition.
The results showed that a variable indicating the simultaneous presence
of multiple conditions from OASIS item M0250 did not improve the
accuracy of the case-mix model. However, we did find that having
separate scores for parenteral nutrition and IV therapy were not
necessary.
Abt's case-mix analysis focused on various issues, such as changes
to the list of conditions forming our diagnosis groups, additions of
comorbidities, prediction of therapy resources, and interactions. The
performance of each variable was scrutinized based on several criteria.
First, variables were assessed for statistical performance. Variables
that did not enhance the accuracy of the model were marked for
exclusion.
Variables were also assessed for policy appropriateness. Some
statistically significant variables were excluded if they offered
incentives for providers to distort patterns of good care or posed
excessive administrative burden on HHAs. In addition, some
statistically weak variables considered important for clinical or
policy reasons were added back to the model for further analysis.
We note we excluded a variable from this proposal, based in part on
concerns of excessive administrative burden. We propose to exclude
OASIS item M0175, which the case-mix system uses to identify the
patient's pre-admission location, from the case-mix models. Under this
proposal, there would be no case-mix score for M0175. Operational
experience with M0175 revealed that some agencies have encountered
difficulties in ascertaining precise information about the patient's
pre-admission location during the initial assessment. These
difficulties, suggestive of unforeseen administrative complexities,
contributed to our proposal to eliminate M0175 from the case-mix model.
In addition, the M0175 item did not perform well in the four-
equation model. We found that the results differed across the equations
in ways that were difficult to interpret. Moreover, the results showed
that the impact of including information from M0175 was small, both in
terms of case-mix scores and the overall payment accuracy of the case-
mix model.
In weighing the indications of administrative complexities due to
M0175 against the limited performance of M0175 in our analysis, we do
not find that the contribution of this item in explaining case-mix
justifies the operational challenge of achieving perfectly accurate
reporting for payment. Thus, as noted above, we are proposing to
eliminate it from the case-mix model. However, we continue to believe
that it is necessary for the conditions of participation and the OASIS
to require that agencies establish the patient's recent history of
health care before determining the plan of care. This determination
must be made with sufficient accuracy to allow appropriate planning,
even if precise dates and institutional certifications are not exactly
known. For example, it will be important to know the amount and types
of rehabilitation treatment the patient has received, the type of
institution that delivered the treatment, and how recently it was
delivered.
The final set of proposed clinical conditions resulting from our
exploratory series of analyses covers more types of conditions than
were used in the original case-mix model (Tables 2a and 2b). We
identified conditions from diagnosis codes on both claims and OASIS in
a linked sample of claims from FY 2003 (OASIS items M0230 and M0240,
Diagnoses and Severity Index). For example, heart and mental conditions
are now assigned case-mix scores. More wound conditions are assigned
scores, based on results from adding variables to indicate wound-
related diagnosis codes beyond those in the current HH PPS case-mix
model. (See Table 2b for diagnosis codes that define each condition in
the model.)
We also propose to assign scores to certain secondary diagnoses,
used to account for cost-increasing effects of comorbidities. An
example is secondary cancer diagnoses, whose cost-increasing effects
are not as large as those for primary cancer diagnoses. However, with
most diagnosis groups, we did not
[[Page 25362]]
make a distinction in the final model between primary placement and
secondary placement of a condition in the reported list of diagnoses.
We made case-by-case decisions on this question based on differences in
the impact on resource cost between the primary diagnosis and secondary
diagnosis. If differences were small, we combined cases reporting the
conditions, regardless of whether the listed position of the diagnosis
was primary or secondary. We believe this is an important protection
against unintended and undesirable incentive effects that could arise
if agencies perceive opportunities to change the placement of the
diagnosis due to nonclinical reasons. In a few instances, the reason
for combining the primary or secondary diagnoses was to improve the
robustness of the scores.
Finally, we also propose that a small number of interactions--
combinations of conditions in the same episode--be assigned scores, to
capture the synergistic effect on resource use of certain conditions
that coexist in the episode. In some instances, a condition appears as
an interaction with a functional limitation or a treatment variable
such as parenteral therapy. In Table 2a, the interaction scores are
added to the case-mix score whenever the two conditions defining the
interaction occur together in the episode. Interaction scores,
therefore, do not substitute for scores of other variables in Table 2a
that involve either only one or the other of the two conditions.
As noted earlier, we also found that, compared to early episodes,
later episodes could exhibit a different relationship between resource
costs and a condition. This is reflected in Table 2a by the absence of
a condition-related score from one or more of the four equations, or a
score that differs from one equation to another.
During the later phases of testing alternative formulations of an
expanded list of clinical conditions, we followed two rules in our
formation of diagnosis groups. These rules would ultimately affect the
operation of the case-mix grouper which would be created pursuant to
the revisions being proposed in this proposed rule. First, if an
episode record in our sample file listed both primary and secondary
diagnoses from the same diagnosis group, the model estimation procedure
recognized the primary diagnosis variable for that case but not the
secondary diagnosis variable. This means that an episode would not be
eligible to earn more than one score for the same diagnosis group. The
primary reason for this rule is that we are aware of diagnosis coding
conventions that would produce repeated instances of the same or
similar codes in the diagnosis list, and these conventions would build
redundancy into the modeling process. A major goal of the exploratory
modeling process was to investigate the impact of comorbidities by
recognizing secondary diagnoses, but redundancy inhibits our
achievement of that goal. Consequently, we sought to reduce this type
of redundancy. A further reason for adhering to this rule is to inhibit
a future decline in model performance, which might come about through
changes in coding behavior. If agencies were to perceive that redundant
coding boosts the episode score, they might engage in it more in the
future. The result would be a degradation in the ability of the case-
mix model to provide for accurate payment.
The second rule we used affected how we define the interactions
between conditions. The second rule is that, for purposes of forming
diagnosis groups to test interactions between conditions, cases with
either a primary or secondary diagnosis from the same diagnosis group
are combined into a single group. This means that mention of a given
diagnosis anywhere in the diagnosis list puts episodes in a single
group for that diagnosis, for purposes of analyzing interactions
between conditions. We believe this rule is consistent with our goal of
isolating effects of comorbidities. Specifically, because the reason
for studying interactions is to identify the effects of combinations of
conditions, we believe it is appropriate to measure the combinations,
regardless of the placement (that is, primary or secondary) of a
diagnosis on the claim. Further, combining the primary and secondary
diagnoses within groups increases the ability of the modeling process
to uncover meaningful interaction effects. The second rule also works
to keep the model as simple as possible. Simplicity helps to limit the
risk that the model would not fit well for later data sets. Simplicity
also limits the amount of added administrative burden that could come
from using a more-complex model.
Changes to the OASIS are needed to enable agencies to report
secondary case-mix diagnosis codes. Specifically, the addition of
secondary diagnoses to the case-mix system (see Table 2a, case-mix
adjustment variables and scores) requires that the OASIS allow for
reporting of instances in which a V-code is coded in place of a case-
mix diagnosis other than the primary diagnosis. A case-mix diagnosis is
a diagnosis that determines the HH PPS case-mix group. Currently, the
OASIS allows for reporting of instances of displacement involving
primary diagnosis only (M0245). Consequently, because of the nature and
significance of the changes needed, we are proposing to delete the
OASIS item M0245 and replace it with a new OASIS item. (see section
III. Collection of Information Requirements).
c. Addition of Therapy Thresholds
As set forth in the July 3, 2000 final rule (65 FR 1128), patients
were grouped according to their therapy utilization status in order to
ensure that patients who required therapy would maintain access to
appropriate services. Specifically, we defined a therapy threshold of
at least 8 hours of combined physical, speech, or occupational therapy
over the 60-day episode, to identify ``high'' therapy cases. The 8-hour
threshold was converted to a threshold of 10 therapy visits because the
average visit length for therapy noted in our data was approximately 48
minutes. We instituted the threshold based on clinical judgment about
the level of therapy that reflects a clear need for rehabilitation
services and that would reasonably be expected to result in meaningful
treatment over the course of 60 days.
Since the implementation of the therapy threshold in the HH PPS, we
have received comments from the public requesting that we study and
refine this approach to accounting for rehabilitation needs in the
case-mix system. Commenters have suggested that a single therapy
threshold did not fairly reflect the variation in therapy utilization
and need. Some commenters requested that we re-examine the 10-visit
threshold. Other commenters recommended that we work to eliminate the
therapy threshold, in part due to concerns that the therapy threshold
might introduce incentives to distort service delivery patterns for
payment purposes.
Our data analysis revealed evidence of undesirable incentives from
the 10-visit therapy threshold. Our analysis suggested that the 10-
visit therapy threshold might have distorted service delivery patterns.
In our analysis sample, of all episodes at or above the threshold, half
were concentrated in the range of 10 to 13 therapy visits. This range
had the highest concentration of therapy episodes among episodes with
at least one therapy visit. In contrast, a large analysis sample from a
period immediately preceding the HH PPS indicated that the highest
concentration of therapy episodes was in a range
[[Page 25363]]
below the 10-visit threshold--approximately 5 to 7 therapy visits.
Under the HH PPS, there were two peaks in the graphic depiction of
numbers of episodes according to the number of therapy visits delivered
during the episode. One peak was below the therapy threshold and the
other was the 10 to 13 visit peak above the therapy threshold. In the
pre-PPS sample, there was only one peak in the depiction, and it was
the concentration of episodes at 5 to 7 therapy visits--below the
current 10-visit therapy threshold. All of these results suggested that
the 10-visit threshold was responsible for a marked shift in
rehabilitation services delivery under the HH PPS, a shift that we
believe would probably not have occurred in the absence of the therapy
threshold. Commenters have reinforced our belief that the impact of the
single 10-visit threshold on therapy provision frequently distorted the
clinically based decision-making that should drive the delivery of
rehabilitation services.
In our early efforts to address problems inherent in using a
therapy threshold, we conducted analyses to identify new predictors of
therapy resource use, with the goal of achieving large gains in
explanatory power that would render the therapy threshold unnecessary.
We used predictor variables including pre-admission status on
activities of daily living (ADL), more diagnoses with a focus on
conditions such as stroke, and more OASIS variables. However, models
that included these particular explanatory variables predicted the
probability of using therapy, but not how much therapy would be used.
Successive studies to account for therapy resources followed the
goal of reducing the impact of a therapy threshold on the payment
weights. The main conclusion from these studies was that therapy
resources cannot be predicted with sufficient accuracy to eliminate the
need for therapy thresholds in the HH PPS case-mix system. Although we
tried several alternative approaches, no approach added sufficient
predictive power to the case-mix model. Therefore, continued analysis
focused primarily on refining the therapy threshold approach to reduce
undesirable incentives. This work involved experimentation with
alternative sets of thresholds consisting of more than one threshold.
After testing several sets of thresholds, and in consideration of
the comments received, we proceeded to construct case-mix models with
thresholds at 6, 14, and 20 therapy visits. We used these thresholds
based on data analysis and, in part, on policy considerations.
Data analysis suggested it would be appropriate to add new
thresholds both below and above the 10-visit level. One reason was that
our review of data from the HH PPS period showed agencies provided
large numbers of episodes with therapy visits in an interval below 10
visits. Moreover, data analysis suggested that, of all episodes with
numbers of therapy visits below the 10-visit therapy threshold, some
subsets did not receive an appropriate case-mix weight under the HH
PPS. Specifically, episodes with 6 to 9 therapy visits had resource
costs that seemingly exceeded the payment proxied in our analysis by
the predicted resource cost under the current case mix model. However,
we now believe that several common treatment plans require only about 6
visits, for example, assessments and treatment of certain types of
patients at high risk for falls. We are therefore proposing that one
threshold be added at 6 therapy visits.
In considering thresholds above the current 10-visit threshold, we
observed that nearly half of episodes involving therapy comprise
episodes with 6 to 13 therapy visits. Therefore, we are proposing a
second threshold at 14 therapy visits, which would have two advantages.
First, this range covers the two peaks (that is, the one we observed
below the 10-visit therapy threshold and the one we observed above the
10-visit threshold) in the distribution of therapy visits under the HH
PPS. By avoiding a therapy threshold within this range, we hope to
reduce the influence of payment incentives on treatment decisions.
Second, we believe that the interval of 6 to 13 therapy visits
represents a reasonable range of treatment levels for most
rehabilitation episodes. For example, the range of 6 to 13 therapy
visits encompasses typical treatment plans for both knee- and hip-
replacement patients. As we describe later in this section, we propose
to use further steps to address payment accuracy, by adding payment
gradations within the intervals bounded by the three thresholds we are
proposing.
We further observed that only a relatively small fraction of
patients use 14 or more therapy visits. While no bright-line tests are
available to distinguish a 14-visit case, we have received comments
indicating that medical review staff at the fiscal intermediaries will
have less difficulty judging appropriateness of treatment plans at this
level, because such plans are intensive and not the norm.
Additionally, although few episodes require 20 or more therapy
visits, we set the third therapy threshold at 20 visits. Our concern is
to ensure access to appropriate treatment in the rare cases where such
intensive treatment is necessary. Our analysis suggested that these
episodes are extremely costly for agencies, so a payment adjustment to
accommodate this service level is appropriate. Furthermore, commenters
indicated that, because only rare cases should warrant this high number
of therapy visits, monitoring of claims to prevent abuse of this
payment provision, using our medical review resources, is feasible
operationally.
Adding therapy thresholds in the revised case-mix regression model
improves the ability of the model to predict resource use. The R-
squared values for a three-therapy threshold model increased
substantially for both early and later episodes over the R-squared
values for a single therapy threshold model. In other words, using
additional therapy thresholds clearly improved the case-mix system's
ability to classify episodes into homogeneous cost groups.
The combined effect of the new therapy thresholds and payment
gradations (to be described below) is expected to reduce the
undesirable emphasis in treatment planning on a single therapy visit
threshold, and to restore the primacy of clinical considerations in
treatment planning for rehabilitation patients.
During the analysis of the therapy threshold, we considered ways to
provide for payment gradations between the therapy thresholds. We
sought a way to implement a gradual increase in payment (see Table 1)
between the proposed first and third therapy thresholds. We believe a
case-mix model that increases payment with each added visit between the
proposed first and third thresholds would achieve two goals. First, a
gradual increase better matches payments to costs than the therapy
thresholds alone. Second, a gradual increase avoids incentives for
providers to distort patterns of good care created by the increase in
payment that would occur at each proposed therapy threshold. However,
as a disincentive for agencies to deliver more than the appropriate,
clinically determined number of therapy visits, we are also proposing
that any per-visit increase incorporate a declining, rather than
constant, amount per added therapy visit. We implemented this in the
case-mix model by decreasing slightly the added amount per therapy
visit as the number of therapy visits grew above the proposed 6-visit
threshold. Specifically, we began with a value determined from our
sample--the estimated marginal
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resource cost incurred by adding a 7th therapy visit to the treatment
plan. This is the first additional visit above the proposed six-visit
therapy threshold. The estimated marginal cost of adding a 7th therapy
visit to an episode with six therapy visits was $36. Using this value
as our starting point, we required the case-mix model to add a slightly
lower value to the total episode resource cost with each additional
therapy visit provided, up to the 19th therapy visit. This proposed
approach imposes a deceleration of the growth in payment with each
additional therapy visit. However, this proposed approach does not
reduce total payments to home health providers, because the regression
analysis still predicts the full resource cost of the episode. Table 1
shows the values that we imposed in the four-equation model estimation
procedure to implement a deceleration in the added resource cost for
individual therapy visits between 6 and 20 therapy visits. The
individual values begin at $36 and then decline at a constant rate of
one resource cost dollar per therapy visit between 6 and 20 therapy
visits. These values represent the score that was imposed in the model
for adding each additional therapy visit. The case-mix model that
incorporates the imposed scores is called a ``restricted regression
model.'' The results of the restricted regression model of the four-
equation system, including scores for diagnoses and conditions, and R-
squared statistics, exhibited little change from imposing this pattern
of deceleration in cost growth due to additional therapy visits.
Table 1.--Resource Cost Values Imposing Deceleration Trend in Four-
Equation Model
------------------------------------------------------------------------
Number of Resource cost
Equation and services utilization therapy visits values imposed
severity level in severity in regression
level procedure
------------------------------------------------------------------------
1st and 2nd Episodes, 6-13 Therapy
Visits
S3.............................. 7, 8, 9 36, 35, 34
S4.............................. 10 33
S5.............................. 11, 12, 13 32, 31, 30
1st and 2nd Episodes, 14-19 Therapy
Visits
S1*............................. 15 28
S2.............................. 16, 17 27, 26
S3.............................. 18, 19 25, 24
3rd+ Episodes, 6-13 Therapy Visits
S3.............................. 7, 8, 9 36, 35, 34
S4.............................. 10 33
S5.............................. 11, 12, 13 32, 31, 30
3rd+ Episodes, 14-19 Therapy Visits
S1*............................. 15 28
S2.............................. 16, 17 27, 26
S3.............................. 18, 19 25, 24
------------------------------------------------------------------------
* For the second and fourth equations of the four equation model, S1
includes 14 therapy visits, but no value was imposed in the regression
procedure for a 14th therapy visit because the regression intercept
estimate automatically includes the resource cost impact.
The case-mix model at this stage was very detailed, because it
included variables incorporating information about thresholds and
therapy visit counts. We were concerned that, without streamlining the
therapy-related information in the case-mix model, the ultimate system
of case-mix groups would contain an excessive number of case-mix
groups. We recognize an extremely large number of case-mix groups would
make the HH PPS complex to administer. Because the therapy-related
details of the case-mix model are based on numbers of therapy visits,
another issue would be that many case-mix groups would be
differentiated based on visit counts, thereby making the system
dependent on visits and less of a bundled system of services.
Therefore, in order to form case-mix groups from the results of the
case-mix model, we grouped the individual levels of therapy visits into
small aggregates (1, 2, or 3 visits) (see Table 1). By doing so, we
avoided creating a per-visit schedule of payment to account for therapy
visits. We implemented these aggregations as differing severity levels
at a subsequent stage of payment system development, the payment
regression, which is described later in this section.
The proposed four equation model, with multiple therapy thresholds
and payment graduation between those thresholds, adds a certain amount
of complexity to the HH PPS. Consequently, in order to group
beneficiaries into case-mix groups in this proposed four equation
model, we propose to make changes to the OASIS to capture the projected
number of total therapy visits for a given episode (see section III.
Collection of Information Requirements), as opposed to indicating if
there is a projected need for ten or more therapy visits (current OASIS
item M0825). Each severity level of the services utilization dimension
represents a different number of therapy visits (see also Table 3:
Severity Group Definitions: Four-Equation Model).
An additional aspect of our therapy threshold research addressed
changing the unit of measurement of therapy thresholds from visits to
minutes. In the July 2000 final rule, we indicated our intention to
continue study of the appropriate unit of measurement for therapy
services.
An important finding of our initial analyses on this question was
that the length of therapy visits in minutes, on average, exhibited
little change between the period covered by the original Abt Associates
case-mix study, and the HH PPS period, based on data through 2003. We
also found that the distribution of average therapy visit lengths was
highly similar under HH PPS, regardless of the total number of therapy
visits in the episode. A possible exception was episodes with 1 to 4
therapy visits, where a relatively high proportion of episodes (about
16 percent) had average therapy visit lengths of 30 minutes or less; no
more than 9 percent of remaining episodes (more than four therapy
visits) had averages of 30 minutes or less. There was also a slight
tendency for these short average visit
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lengths to become less frequent as the total therapy visit count per
episode grew. Overall, the data indicated that at least 85 percent of
episodes with therapy visits involved visits averaging at least 41
minutes. These results suggest that therapy practitioners tend to have
consistent session lengths across many types of episodes.
We are proposing no change in the current way in which we measure
therapy thresholds, which is based on counting therapy visits, in light
of our analysis indicating that individual therapy visits appear to
vary little in their length, regardless of the frequency of visits
during the 60-day episode, and our analysis indicating that average
visit lengths have remained stable since the time of the Abt case-mix
study. Additionally, we are concerned incentive issues would arise if
we changed the definition. The low variability in visit lengths appears
to be an indication that under current practices, therapy session
lengths are fairly uniform, regardless of the time period or intensity
of the rehabilitation course of treatment. These practices have arisen
out of clinical experience in the rehabilitation professions.
Introducing a minutes or time standard risks introducing new financial
incentives that might influence these widely held practices. We are
concerned that changing to a minutes standard might result in
financially driven pressures on clinical decisions concerning the
number of sessions in a patient's course of treatment, with potentially
adverse effects on beneficiary outcomes.
One of our original concerns in proposing a visit-based threshold
was that minutes unit reporting on the claims, which was a relatively
new requirement at that time, might be unreliable. (Section 1895(c)(2)
requires the claim to report the length of each billed visit as
measured in 15-minute increments.) Based upon our experiences using the
claims data in our research, we have no reason to believe this is a
problem. Moreover, we believe the dual requirements to report both
visit dates and minutes of each visit on Medicare claims should remain
in place because they provide important information for program
integrity activities and future research.
Based upon our analysis of the case-model described in section
II.A.2, we propose to use four separate equations to derive scores for
conditions including the proposed therapy thresholds. The proposed
first equation is for early episodes below the 14-visit therapy
threshold. The proposed second equation is for early episodes at or
above the 14-visit therapy threshold. The proposed third equation is
for later episodes below the 14-visit therapy threshold. The proposed
fourth equation is for later episodes above the 14-visit therapy
threshold. A threshold at 6 visits is accounted for by an indicator
variable in the proposed first and third equations, and a threshold at
20 visits is accounted for by an indicator variable in the proposed
second and fourth equations. In addition, therapy visit count variables
are added to the equations to model the graduated payment with each
therapy visit between 6 and 20 visits. Finally, as we explained above,
we imposed specific values for the coefficients of the therapy visit
count variables. The resulting four-equation model has an improved
statistical performance (an R-squared statistic of approximately 0.44)
over the current model (an R-squared statistic of 0.21). The primary
reason for the improvement in the proposed case-mix model fit (compared
to the R-square statistic of 0.21 cited earlier) is the four-equation
structure. This structure recognizes cost differences between early and
later episodes, and between therapy treatment plans above and below the
proposed 14-visit therapy threshold. Additional improvements come from
adding other therapy variables to the case-mix model, specifically, the
two additional thresholds (6 and 20 visits) and graduated payment--and
from the new case-mix variables discussed in section II.A.2.a of this
proposed rule.
We believe that in addition to improved statistical performance,
the proposed model would provide better incentives for the provision of
high-quality home health care without an undue increase in
administrative burden. For a more detailed discussion of the technical
aspects of the four-equation model go to the CMS Web site (http://www.cms.hhs.gov/hha.asp
) for a link to Abt's Technical Report.
Table 2a presents the full set of case-mix scores (other than the
imposed scores for therapy visits) and all clinical and functional
variables we are proposing for the refined case-mix model. In Table 2a,
the score is the value of the regression coefficient for the variable;
it measures the impact of the data element on total resource cost of
the episode. See Table 2b for an inclusive list of ICD-9-CM diagnosis
codes applicable for each scored condition variable in Table 2a. These
codes define the clinical condition variables in our proposed model. We
intend to continue to evaluate the appropriateness of these diagnosis
codes in Table 2b. We believe the HH PPS case-mix system should avoid,
to the fullest extent possible, nonspecific or ambiguous ICD-9-CM
codes, codes that represent general symptomatic complaints in the
elderly population, and codes that lack consensus for clear diagnostic
criteria within the medical community. We solicit detailed suggestions
from the public concerning codes that threaten to move the system away
from a foundation of reliable and meaningful diagnosis codes.
Compared to the original four diagnosis groups in the case-mix
model, the code groups in Table 2b incorporate additions and new group
placements for individual ICD-9-CM diagnosis codes. Two variables from
the original case mix system are not proposed: M0175, as noted earlier,
and M0610, behavioral problems, which did not perform well in our
studies. We believe that several additions to our diagnosis groups,
namely, two groups for psychiatric diagnoses, account for the
contribution of behavioral problems to resource cost variation.
We are aware that some of the diagnosis codes listed in Table 2b
are manifestation codes. The ICD-9-CM Official Guidelines for Coding
and Reporting requires that the underlying disease or condition code be
sequenced first, followed by the manifestation code. The underlying
disease codes associated with the manifestation codes are not listed in
Table 2b. However, appropriate sequencing was accounted for in our
analysis. When reporting certain conditions that have both an
underlying etiology and a body system manifestation due to the
underlying etiology, the appropriate sequencing should be followed
according to the ICD-9-CM Coding Guidelines.
For purposes of determining final estimates on which to base the
data set used in the final rule for CY 2008, we intend to update the
dataset used for the four-equation model to CY 2005; as noted above,
the proposal to use the four-equation model is based on linked claims
and OASIS data from FY 2003. We are aware that adding data from a later
period may result in some variations, including some significant
changes, in the scores presented in Table 2a. Some changes may occur
because, effective October 2003 (FY 2004), diagnosis coding
instructions on the OASIS assessment changed to allow for the use of
ICD-9-CM V-codes. V-codes, particularly those applicable to home health
services, do not in general describe disease states; rather, they
describe reasons for using services. The major use of V-codes in the
home health setting occurs when a person with current or resolving
disease or injury
[[Page 25366]]
encounters the health care system for specific aftercare of that
disease or injury. For example, V-code V57.21 is reportable when the
reason for the visit is ``encounter for occupational therapy.'' As
such, V-codes are less specific to the clinical condition of the
patient than are numeric diagnosis codes. A single V-code could
substitute for various numeric codes, each of which describes a
specific, different clinical condition.
Medical review activities revealed an inappropriate utilization of
V-codes following the effective date of V-codes on OASIS (October,
2003). In response to RHHI reports of increased provider non-compliance
with correct ICD-9-CM coding procedures related to V-codes, we posted
OASIS diagnosis training on the CMS Web site and promoted RHHI provider
educational efforts. Nonetheless, medical review activities continue to
report an excessive utilization of the V-57 codes, signaling a possible
non-compliance with correct coding practice related to the V-codes.
We are concerned that more use of V-codes could reduce data
adequacy for modeling the impacts of clinical conditions we are
proposing to use to predict resource use. One result, for example,
might be a markedly different score for some conditions with lower
reporting rates under the V-code instructions effective October 2003.
At this time, we do not know whether allowing V-codes on the OASIS,
along with the over-use of V-codes revealed by medical review
activities, significantly lowered the frequencies of non-V-code,
numeric diagnosis codes for the clinical conditions we propose to use
in the case mix model. Again, this could have occurred because of the
way V-codes can displace a numeric code in the diagnosis list. If we
find evidence that numeric codes' frequencies were reduced to the
extent that it strongly influenced the scores we present in this
proposal, we propose to base the refined system on the data from FY
2003.
BILLING CODE 4120-01-P
[[Page 25367]]
[GRAPHIC] [TIFF OMITTED] TP04MY07.000
[[Page 25368]]
[GRAPHIC] [TIFF OMITTED] TP04MY07.001
[[Page 25369]]
[GRAPHIC] [TIFF OMITTED] TP04MY07.002
[[Page 25370]]
[GRAPHIC] [TIFF OMITTED] TP04MY07.003
[[Page 25371]]
[GRAPHIC] [TIFF OMITTED] TP04MY07.004
[[Page 25372]]
[GRAPHIC] [TIFF OMITTED] TP04MY07.005
BILLING CODE 4120-01-C
Table 2b.--ICD-9-CM Diagnoses Included in the Diagnostic Categories for Case-Mix Adjustment Variables
----------------------------------------------------------------------------------------------------------------
ICD-9-CM
Diagnostic category code** Manifestation* Short description of ICD-9-CM code
----------------------------------------------------------------------------------------------------------------
Blindness and low vision......... 369.0 ..................... PROFOUND BLIND BOTH EYES
369.1 ..................... MOD/SEV W PROFND IMPAIR
369.2 ..................... MOD/SEV IMPAIR-BOTH EYES
369.3 ..................... BLINDNESS NOS, BOTH EYES
369.4 ..................... LEGAL BLINDNESS-USA DEF
950 ..................... INJURY TO OPTIC NERVE AND PATHWAYS
Blood disorders.................. 281 ..................... OTHER DEFICIENCY ANEMIAS
282 ..................... HEREDITARY HEMOLYTIC ANEMIAS
283 ..................... ACQUIRED HEMOLYTIC ANEMIAS
284 ..................... APLASTIC ANEMIA
285 ..................... OTHER AND UNSPECIFIED ANEMIAS
286 ..................... COAGULATION DEFECTS
287 ..................... PURPURA&OTHER HEMORRHAGIC CONDS
288 ..................... DISEASES OF WHITE BLOOD CELLS
289 ..................... OTH DISEASES BLD&BLD-FORMING ORGANS
Cancer and selected benign 140 ..................... MALIGNANT NEOPLASM OF LIP
neoplasms.
141 ..................... MALIGNANT NEOPLASM OF TONGUE
142 ..................... MALIG NEOPLASM MAJOR SALIV GLANDS
143 ..................... MALIGNANT NEOPLASM OF GUM
144 ..................... MALIGNANT NEOPLASM FLOOR MOUTH
145 ..................... MALIG NEOPLSM OTH&UNSPEC PART MOUTH
146 ..................... MALIGNANT NEOPLASM OF OROPHARYNX
147 ..................... MALIGNANT NEOPLASM OF NASOPHARYNX
148 ..................... MALIGNANT NEOPLASM OF HYPOPHARYNX
149 ..................... OTH MALIG NEO LIP-MOUTH-PHARYNX
150 ..................... MALIGNANT NEOPLASM OF ESOPHAGUS
151 ..................... MALIGNANT NEOPLASM OF STOMACH
152 ..................... MALIG NEOPLSM SM INTEST INCL DUODUM
153 ..................... MALIGNANT NEOPLASM OF COLON
154 ..................... MAL NEO RECT RECTOSIGMOID JUNC&ANUS
155 ..................... MALIG NEOPLASM LIVER&INTRAHEP BDS
156 ..................... MALIG NEOPLSM GALLBLADD&XTRAHEP BDS
157 ..................... MALIGNANT NEOPLASM OF PANCREAS
158 ..................... MALIG NEOPLASM RETROPERITON&PERITON
159 ..................... MAL NEO DIGES ORGANS&PANCREAS OTH
160 ..................... MAL NEO NASL CAV/MID EAR&ACSS SINUS
161 ..................... MALIGNANT NEO LARYNX*
162 ..................... MALIGNANT NEO TRACHEA/LUNG*
[[Page 25373]]
163 ..................... MALIGNANT NEOPL PLEURA*
164 ..................... MAL NEO THYMUS/MEDIASTIN*
165 ..................... OTH/ILL-DEF MAL NEO RESP*
170 ..................... MALIG NEOPLASM BONE&ARTICLR CART
171 ..................... MALIG NEOPLSM CNCTV&OTH SOFT TISSUE
172 ..................... MALIGNANT MELANOMA OF SKIN
173 ..................... OTHER MALIGNANT NEOPLASM OF SKIN
174 ..................... MALIGNANT NEOPLASM OF FEMALE BREAST
175 ..................... MALIGNANT NEOPLASM OF MALE BREAST
176 ..................... KAPOSIS SARCOMA
179 ..................... MALIG NEOPLASM UTERUS PART UNSPEC
180 ..................... MALIGNANT NEOPLASM OF CERVIX UTERI
181 ..................... MALIGNANT NEOPLASM OF PLACENTA
182 ..................... MALIGNANT NEOPLASM BODY UTERUS
183 ..................... MALIG NEOPLSM OVRY&OTH UTERN ADNEXA
184 ..................... MALIG NEOPLSM OTH&UNS FE GENIT ORGN
185 ..................... MALIGNANT NEOPLASM OF PROSTATE
186 ..................... MALIGNANT NEOPLASM OF TESTIS
187 ..................... MAL NEOPLSM PENIS&OTH MALE GNT ORGN
188 ..................... MALIGNANT NEOPLASM OF BLADDER
189 ..................... MAL NEO KIDNEY&OTH&UNS URIN ORGN
190 ..................... MALIGNANT NEOPLASM OF EYE
192.0 ..................... MALIGNANT NEOPLASM, CRANIAL NERVES
192.8 ..................... MALIGNANT NEOPLASM OTHER NERV SYS
192.9 ..................... MALIGNANT NEOPLASM, UNS PART NERV SYS
193 ..................... MALIGNANT NEOPLASM OF THYROID GLAND
194 ..................... MAL NEO OTH ENDOCRN GLND&REL STRCT
195 ..................... MALIG NEOPLASM OTH&ILL-DEFIND SITES
196 ..................... SEC&UNSPEC MALIG NEOPLASM NODES
197 ..................... SEC MALIG NEOPLASM RESP&DIGESTV SYS
198 ..................... SEC MALIG NEOPLASM OTHER SPEC SITES
199 ..................... MALIG NEOPLASM WITHOUT SPEC SITE
200 ..................... LYMPHOSARCOMA AND RETICULOSARCOMA
201 ..................... HODGKINS DISEASE
202 ..................... OTH MAL NEO LYMPHOID&HISTCYT TISS
203 ..................... MX MYELOMA&IMMUNOPROLIFERAT NEOPLSM
204 ..................... LYMPHOID LEUKEMIA
205 ..................... MYELOID LEUKEMIA
206 ..................... MONOCYTIC LEUKEMIA
207 ..................... OTHER SPECIFIED LEUKEMIA
208 ..................... LEUKEMIA OF UNSPECIFIED CELL TYPE
213 ..................... BEN NEOPLASM BONE&ARTICLR CARTILAGE
225.1 ..................... BEN NEOPLSM CRANIAL NERVES
225.8 ..................... BEN NEOPLSM OTH SPEC SITES
225.9 ..................... BEN NEOPLSM UNSPEC PART NERV SYS
230 ..................... CA IN SITU--DIGEST
231 ..................... CA IN SITU--RESP
232 ..................... CARCINOMA IN SITU OF SKIN
233 ..................... CA IN SITU--BREAST AND GU
234 ..................... CA IN SITU--OTH
Diabetes......................... 250 ..................... DIABETES MELLITUS
357.2 M.................... POLYNEUROPATHY IN DIABETES
362.01 M.................... BACKGROUND DIABETIC RETINOPATHY
362.02 M.................... PROLIFERATIVE DIABETIC RETINOPATHY
366.41 M.................... DIABETIC CATARACT
Dysphagia........................ 787.2 ..................... DYSPHAGIA
Gait Abnormality................. 781.2 ..................... ABNORM GAIT
Gastrointestinal disorders....... 002 ..................... TYPHOID AND PARATYPHOID FEVERS
003 ..................... OTHER SALMONELLA INFECTIONS
004 ..................... SHIGELLOSIS
005 ..................... OTHER FOOD POISONING
006 ..................... AMEBIASIS
007 ..................... OTHER PROTOZOAL INTESTINAL DISEASES
008 ..................... INTESTINAL INFS DUE OTH ORGANISMS
009 ..................... ILL-DEFINED INTESTINAL INFECTIONS
530 ..................... DISEASES OF ESOPHAGUS
531 ..................... GASTRIC ULCER
532 ..................... DUODENAL ULCER
533 ..................... PEPTIC ULCER, SITE UNSPECIFIED
534 ..................... GASTROJEJUNAL ULCER
[[Page 25374]]
535 ..................... GASTRITIS AND DUODENITIS
536 ..................... DISORDERS OF FUNCTION OF STOMACH
537 ..................... OTHER DISORDERS OF STOMACH&DUODENUM
540 ..................... ACUTE APPENDICITIS
541 ..................... APPENDICITIS, UNQUALIFIED
542 ..................... OTHER APPENDICITIS
543 ..................... OTHER DISEASES OF APPENDIX
555 ..................... REGIONAL ENTERITIS
556 ..................... ULCERATIVE COLITIS
557 ..................... VASCULAR INSUFFICIENCY OF INTESTINE
558 ..................... OTH NONINF GASTROENTERITIS&COLITIS
560 ..................... INTEST OBST W/O MENTION HERN
562 ..................... DIVERTICULA OF INTESTINE
564 ..................... FUNCTIONAL DIGESTIVE DISORDERS NEC
567 M.................... PERITONITIS
568 ..................... OTHER DISORDERS OF PERITONEUM
569 ..................... OTHER DISORDERS OF INTESTINE
570 ..................... ACUTE&SUBACUTE NECROSIS OF LIVER
571 ..................... CHRONIC LIVER DISEASE AND CIRRHOSIS
572 ..................... LIVER ABSC&SEQUELAE CHRON LIVR DZ
573 M.................... OTHER DISORDERS OF LIVER
574 ..................... CHOLELITHIASIS
575 ..................... OTHER DISORDERS OF GALLBLADDER
576 ..................... OTHER DISORDERS OF BILIARY TRACT
577 ..................... DISEASES OF PANCREAS
578 ..................... GASTROINTESTINAL HEMORRHAGE
579 ..................... INTESTINAL MALABSORPTION
783.2 ..................... ABNORMAL LOSS OF WEIGHT
Heart Disease.................... 410 ..................... ACUTE MYOCARDIAL INFARCTION
411 ..................... OTH AC&SUBAC FORMS ISCHEMIC HRT DZ
428 ..................... HEART FAILURE
Hypertension..................... 401 ..................... ESSENTIAL HYPERTENSION
402 ..................... HYPERTENSIVE HEART DISEASE
403 ..................... HYPERTENSIVE RENAL DISEASE
404 ..................... HYPERTENSIVE HEART&RENAL DISEASE
405 ..................... SECONDARY HYPERTENSION
Neuro 1--Brain disorders and 013 ..................... TB MENINGES&CNTRL NERV SYS
paralysis.
047 ..................... MENINGITIS DUE TO ENTEROVIRUS
046 ..................... SLOW VIRUS INFECTION CNTRL NERV SYS
048 ..................... OTH ENTEROVIRUS DZ CNTRL NERV SYS
049 ..................... OTH NON-ARTHROPOD BORNE VIRL DX-CNS
191 ..................... MALIGNANT NEOPLASM OF BRAIN
192.2 ..................... MALIG NEOPLSM SPINAL CORD
192.3 ..................... MALIG NEOPLSM SPINAL MENINGES
225.0 ..................... BEN NEOPLSM BRAIN
225.2 ..................... BEN NEOPLSM BRAIN MENINGES
225.3 ..................... BEN NEOPLSM SPINAL CORD
225.4 ..................... BEN NEOPLSM SPINAL CORD MENINGES
320.0 ..................... HEMOPHILUS MENINGITIS
320.1 ..................... PNEUMOCOCCAL MENINGITIS
320.2 ..................... STREPTOCOCCAL MENINGITIS
320.3 ..................... STAPHYLOCOCCAL MENINGITIS
320.7 M.................... MENINGITIS OTH BACT DZ CLASS ELSW
320.81 ..................... ANAEROBIC MENINGITIS
320.82 ..................... MENINGITIS DUE GM-NEG BACTER NEC
320.89 ..................... MENINGITIS DUE OTHER SPEC BACTERIA
320.9 ..................... MENINGITIS DUE UNSPEC BACTERIUM
321.0 M.................... CRYPTOCOCCAL MENINGITIS
321.1 M.................... MENINGITIS IN OTHER FUNGAL DISEASES
321.2 M.................... MENINGITIS DUE TO VIRUSES NEC
321.3 M.................... MENINGITIS DUE TO TRYPANOSOMIASIS
321.4 M.................... MENINGITIS IN SARCOIDOSIS
321.8 M.................... MENINGITIS-OTH NONBCTRL ORGNISMS CE
322 ..................... MENINGITIS OF UNSPECIFIED CAUSE
323.0 M.................... ENCEPHALITIS VIRAL DZ CLASS ELSW
323.1 M.................... ENCEPHALIT RICKETTS DZ CLASS ELSW
323.2 M.................... ENCEPHALIT PROTOZOAL DZ CLASS ELSW
323.4 M.................... OTH ENCEPHALIT DUE INF CLASS ELSW
323.5 ..................... ENCEPHALIT FOLLOW IMMUNIZATION PROC
323.6 M.................... POSTINFECTIOUS ENCEPHALITIS
[[Page 25375]]
323.7 M.................... TOXIC ENCEPHALITIS
323.8 ..................... OTHER CAUSES OF ENCEPHALITIS
323.9 ..................... ENCEPHALITUS NOS
324 ..................... INTRACRANIAL&INTRASPINAL ABSCESS
325 ..................... PHLEBIT&THRMBOPHLB INTRACRAN VENUS
326 ..................... LATE EFF INTRACRAN ABSC/PYOGEN INF
330.0 ..................... LEUKODYSTROPHY
330.1 ..................... CEREBRAL LIPIDOSES
330.2 M.................... CEREB DEGEN IN LIPIDOSIS
330.3 M.................... CERB DEG CHLD IN OTH DIS
330.8 ..................... CEREB DEGEN IN CHILD NEC
330.9 ..................... CEREB DEGEN IN CHILD NOS
334.1 ..................... HERED SPASTIC PARAPLEGIA
335 ..................... ANTERIOR HORN CELL DISEASE
336.1 ..................... VASCULAR MYELOPATHIES
336.2 M.................... SUBACUTE COMB DEGEN SPINL CRD DZ CE
336.3 M.................... MYELOPATHY OTH DISEASES CLASS ELSW
336.8 ..................... OTHER MYELOPATHY
336.9 ..................... UNSPECIFIED DISEASE OF SPINAL CORD
337.3 ..................... AUTONOMIC DYSREFLEXIA
344.1 ..................... PARAPLEGIA
344.8 ..................... LOCKED-IN STATE
344.9 ..................... PARALYSIS UNSPECIFIED
348 ..................... OTHER CONDITIONS OF BRAIN
349.82 ..................... OTH&UNSPEC DISORDERS NERVOUS SYSTEM
336.0 ..................... SYRINGOMYELIA AND SYRINGOBULBIA
344.0 ..................... QUADRAPLEGIA
741 ..................... SPINA BIFIDA
780.01 ..................... COMA
780.03 ..................... PERSISTENT VEGETATIVE STATE
806 ..................... FX VERT COLUMN W/SPINAL CORD INJURY
851 ..................... CEREBRAL LACERATION AND CONTUSION
852 ..................... SUBARACH SUB&XTRADURL HEMOR FLW INJ
853 ..................... OTH&UNS INTRACRAN HEMOR FLW INJURY
854 ..................... INTRACRAN INJURY OTH&UNSPEC NATURE
907.0 ..................... LATE EFF INTRACRANIAL INJURY
907.1 ..................... LATE EFFECT OF INJURY TO CRANIAL NERVE
907.2 ..................... LATE EFFECT OF SPINAL CORD INJURY
907.3 ..................... LATE EFFECT OF INJURY TO NERVE ROOT(S),
SPINAL PLEXUS(ES), AND OTHER NERVES OF
TRUNK
907.4 ..................... LATE EFFECT OF INJURY TO PERIPHERAL NERVE
OF SHOULDER GIRDLE AND UPPER LIMB
907.5 ..................... LATE EFFECT OF INJURY TO PERIPHERAL NERVE
OF PELVIC GIRDLE AND LOWER LIMB
907.9 ..................... LATE EFFECT OF INJURY TO OTHER AND
UNSPECIFIED NERVE
952 ..................... SP CRD INJR W/O EVIDENCE SP BN INJR
Neuro 2--Peripheral neurological 045 ..................... ACUTE POLIOMYELITIS
disorders.
332 ..................... PARKINSONS DISEASE
333 ..................... OTH XTRAPYRAMIDAL DZ&ABN MOVMNT D/O
334.0 ..................... FRIEDREICH'S ATAXIA
334.2 ..................... PRIMARY CEREBELLAR DEGEN
334.3 ..................... CEREBELLAR ATAXIA NEC
334.4 M.................... CEREBEL ATAX IN OTH DIS
334.8 ..................... SPINOCEREBELLAR DIS NEC
334.9 ..................... SPINOCEREBELLAR DIS NOS
337.0 ..................... IDIOPATH PERIPH AUTONOM NEUROPATHY
337.1 M.................... PRIPHERL AUTONOMIC NEUROPTHY D/O CE
337.20 ..................... UNSPEC REFLEX SYMPATHETIC DYSTROPHY
337.21 ..................... REFLX SYMPATHET DYSTROPHY UP LIMB
337.22 ..................... REFLX SYMPATHET DYSTROPHY LOW LIMB
337.29 ..................... REFLX SYMPATHET DYSTROPHY OTH SITE
337.9 ..................... UNSPEC DISORDER AUTONOM NERV SYSTEM
343 ..................... INFANTILE CEREBRAL PALSY
344.2 ..................... DIPLEGIA OF BOTH UPPER LIMBS
352 ..................... DISORDERS OF OTHER CRANIAL NERVES
353.0 ..................... BRACHIAL PLEXUS LESION
353.1 ..................... LUMBOSACRAL PLEXUS LESION
353.5 ..................... NEURALGIC AMYLOTROPHY
354.5 ..................... MONONEURITIS MULTIPLEX
[[Page 25376]]
355.2 ..................... OTHER LESION OF FEMORAL NERVE
355.9 ..................... LESION OF SCIATIC NERVE
356 ..................... HEREDIT&IDIOPATH PERIPH NEUROPATHY
357.0 ..................... ACUTE INFECTIVE POLYNEURITIS
357.1 M.................... POLYNEUROPATHY COLL VASC DISEASE
357.3 M.................... POLYNEUROPATHY IN MALIGNANT DISEASE
357.4 M.................... POLYNEUROPATHY OTH DZ CLASS ELSW
357.5 ..................... ALCOHOLIC POLYNEUROPATHY
357.6 ..................... POLYNEUROPATHY DUE TO DRUGS
357.7 ..................... POLYNEUROPATHY DUE OTH TOXIC AGENTS
357.82 ..................... CRIT ILLNESS NEUROPATHY
357.89 ..................... INFLAM/TOX NEUROPATHY
357.9 ..................... UNSPEC INFLAM&TOXIC NEUROPATHY
358.00 ..................... MYASTHENIA GRAVIS W/O ACUTE
358.01 ..................... MYASTHENIA GRAVIS W/ACUTE
358.1 M.................... MYASTHENIC SYNDROMES DZ CLASS ELSW
358.2 ..................... TOXIC MYONEURAL DISORDERS
358.9 ..................... UNSPECIFIED MYONEURAL DISORDERS
359.0 ..................... CONGEN HEREDIT MUSCULAR DYSTROPHY
359.1 ..................... HEREDITARY PROGRESSIVE MUSC DYSTROPH
359.3 ..................... FAMILIAL PERIODIC PARALYSIS
359.4 ..................... TOXIC MYOPATHY
359.5 M.................... MYOPATHY ENDOCRINE DZ CLASS ELSW
359.6 M.................... SX INFLAM MYOPATHY DZ CLASS ELSW
359.8 ..................... OTHER MYOPATHIES
359.9 ..................... UNSPECIFIED MYOPATHY
386.0 ..................... MENIERE'S DISEASE
386.2 ..................... VERTIGO OF CENTRAL ORIGIN
386.3 ..................... LABYRINTHITIS
392 ..................... RHEUMATIC CHOREA
953 ..................... INJURY TO NERVE ROOTS&SPINAL PLEXUS
954 ..................... INJR OTH NRV TRNK NO SHLDR&PLV GIRD
955.8 ..................... INJR PERIPH NRV SHLDR GIRDL&UP LIMB
956.0 ..................... INJR TO SCIATIC NERVE
956.1 ..................... INJ TO FEMORAL NERVE
956.8 ..................... INJR TO MULTIPLE PELVIC AND LE NERVES
Neuro 3--Stroke.................. 342 ..................... HEMIPLEGIA AND HEMIPARESIS
344.3 ..................... MONOPLEGIA OF LOWER LIMB
344.4 ..................... MONOPLEGIA OF UPPER LIMB
344.6 ..................... UNSPECIFIED MONOPLEGIA
430 ..................... SUBARACHNOID HEMORRHAGE
431 ..................... INTRACEREBRAL HEMORRHAGE
432 ..................... OTH&UNSPEC INTRACRANIAL HEMORRHAGE
433.01 ..................... OCCLUSION&STENOSIS BASILAR ART W INFARC
433.11 ..................... OCCLUSION&STENOSIS CAROTID ART W INFARC
433.21 ..................... OCCLUSION&STENOSIS VERTEBRAL ART W INFARC
433.31 ..................... OCCLUSION&STENOSIS MULT BILAT ART W INFARC
433.81 ..................... OCCLUSION&STENOSIS OTH PRECER ART W INFARC
434.01 ..................... CEREBRAL THROMBOSIS W INFARCTION
434.11 ..................... CEREBRAL EMBOLISM W INFARCTION
781.8 ..................... NEURO NEGLECT SYNDROME
436 ..................... ACUT BUT ILL-DEFINED CEREBRVASC DZ
438 ..................... LATE EFF CEREBROVASCULAR DZ
435 ..................... TRANSIENT CEREBRAL ISCHEMIA
Neuro 4--Multiple Sclerosis...... 340 ..................... MULTIPLE SCLEROSIS
341 M.................... OTH DEMYELINATING DZ CNTRL NERV SYS
Ortho 1--Leg Disorders........... 711.05 ..................... PYOGEN ARTHRITIS-PELVIS
711.06 ..................... PYOGEN ARTHRITIS-L/LEG
711.07 ..................... PYOGEN ARTHRITIS-ANKLE
711.15 M.................... REITER ARTHRITIS-PELVIS
711.16 M.................... REITER ARTHRITIS-L/LEG
711.17 M.................... REITER ARTHRITIS-ANKLE
711.25 M.................... BEHCET ARTHRITIS-PELVIS
711.26 M.................... BEHCET ARTHRITIS-L/LEG
711.27 M.................... BEHCET ARTHRITIS-ANKLE
711.35 M.................... DYSENTER ARTHRIT-PELVIS
711.36 M.................... DYSENTER ARTHRIT-L/LEG
711.37 M.................... DYSENTER ARTHRIT-ANKLE
711.45 M.................... BACT ARTHRITIS-PELVIS
711.46 M.................... BACT ARTHRITIS-L/LEG
[[Page 25377]]
711.47 M.................... BACT ARTHRITIS-ANKLE
711.55 M.................... VIRAL ARTHRITIS-PELVIS
711.56 M.................... VIRAL ARTHRITIS-L/LEG
711.57 M.................... VIRAL ARTHRITIS-ANKLE
711.65 M.................... MYCOTIC ARTHRITIS-PELVI
711.66 M.................... MYCOTIC ARTHRITIS-L/LEG
711.67 M.................... MYCOTIC ARTHRITIS-ANKLE
711.75 M.................... HELMINTH ARTHRIT-PELVIS
711.76 M.................... HELMINTH ARTHRIT-L/LEG
711.77 M.................... HELMINTH ARTHRIT-ANKLE
711.85 M.................... INF ARTHRITIS NEC-PELVI
711.86 M.................... INF ARTHRITIS NEC-L/LEG
711.87 M.................... INF ARTHRITIS NEC-ANKLE
711.95 ..................... INF ARTHRIT NOS-PELVIS
711.96 ..................... INF ARTHRIT NOS-L/LEG
711.97 ..................... INF ARTHRIT NOS-ANKLE
712.15 M.................... DICALC PHOS CRYST-PELVI
712.16 M.................... DICALC PHOS CRYST-L/LEG
712.17 M.................... DICALC PHOS CRYST-ANKLE
712.25 M.................... PYROPHOSPH CRYST-PELVIS
712.26 M.................... PYROPHOSPH CRYST-L/LEG
712.27 M.................... PYROPHOSPH CRYST-ANKLE
712.35 M.................... CHONDROCALCIN NOS-PELVI
712.36 M.................... CHONDROCALCIN NOS-L/LEG
712.37 M.................... CHONDROCALCIN NOS-ANKLE
712.85 ..................... CRYST ARTHROP NEC-PELVI
712.86 ..................... CRYST ARTHROP NEC-L/LEG
712.87 ..................... CRYST ARTHROP NEC-ANKLE
712.95 ..................... CRYST ARTHROP NOS-PELVI
712.96 ..................... CRYST ARTHROP NOS-L/LEG
712.97 ..................... CRYST ARTHROP NOS-ANKLE
716.05 ..................... KASCHIN-BECK DIS-PELVIS
716.06 ..................... KASCHIN-BECK DIS-L/LEG
716.07 ..................... KASCHIN-BECK DIS-ANKLE
716.15 ..................... TRAUM ARTHROPATHY-PELVIS
716.16 ..................... TRAUM ARTHROPATHY-L/LEG
716.17 ..................... TRAUM ARTHROPATHY-ANKLE
716.25 ..................... ALLERG ARTHRITIS-PELVIS
716.26 ..................... ALLERG ARTHRITIS-L/LEG
716.27 ..................... ALLERG ARTHRITIS-ANKLE
716.35 ..................... CLIMACT ARTHRITIS-PELVIS
716.36 ..................... CLIMACT ARTHRITIS-L/LEG
716.37 ..................... CLIMACT ARTHRITIS-ANKLE
716.45 ..................... TRANS ARTHROPATHY-PELVIS
716.46 ..................... TRANS ARTHROPATHY-L/LEG
716.47 ..................... TRANS ARTHROPATHY-ANKLE
716.55 ..................... POLYARTHRITIS NOS-PELVIS
716.56 ..................... POLYARTHRITIS NOS-L/LEG
716.57 ..................... POLYARTHRITIS NOS-ANKLE
716.67 ..................... MONOARTHRITIS NOS-ANKLE
716.85 ..................... ARTHROPATHY NEC-PELVIS
716.86 ..................... ARTHROPATHY NEC-L/LEG
716.87 ..................... ARTHROPATHY NEC-ANKLE
716.95 ..................... ARTHROPATHY NOS-PELVIS
716.96 ..................... ARTHROPATHY NOS-L/LEG
716.97 ..................... ARTHROPATHY NOS-ANKLE
717 ..................... INTERNAL DERANGEMENT OF KNEE
718.05 ..................... ART CARTIL DISORDER PELVIS AND THIGH
718.06 ..................... ART CARTIL DISORDER LOWER LEG
718.07 ..................... ART CARTIL DIS ANKLE FOOT
718.25 ..................... PATHOLOGIC DISLOCATION PELVIS AND THIGH
718.26 ..................... PATHOLOGIC DISLOCATION LOWER LEG
718.27 ..................... PATHOLOGIC DISLOCATION ANKLE FOOT
718.35 ..................... RECURRENT DISLOCATION PELVIS AND THIGH
718.36 ..................... RECURRENT DISLOCATION LOW LEG
718.37 ..................... RECURRENT DISLOCATION ANKLE FOOT
718.45 ..................... CONTRACTURE PELVIS AND THIGH
718.46 ..................... CONTRACTURE LOWER LEG
718.47 ..................... CONTRACTURE OF JOINT ANKLE FOOT
718.55 ..................... ANKYLOSIS OF PELVIS AND THIGH
[[Page 25378]]
718.56 ..................... ANKYLOSIS OF LOWER LEG
718.57 ..................... ANKYLOSIS OF JOINT ANKLE FOOT
718.85 ..................... OTHER DERANGEMENT OF PELVIS AND THIGH
718.86 ..................... OTHER DERANGEMENT OF JOINT OF LOWER LEG
718.87 ..................... OTH DERANGMENT JT NEC ANKLE FOOT
719.15 ..................... HEMARTHROSIS PELVIS AND THIGH
719.16 ..................... HEMARTHROSIS LOWER LEG
719.17 ..................... HEMARTHROSIS ANKLE AND FOOT
719.25 ..................... VILLONODULAR SYNOVITIS PELVIS AND THIGH
719.26 ..................... VILLONODULAR SYNOVITIS LOWER LEG
719.27 ..................... VILLONODULAR SYNOVITIS ANKLE AND FOOT
719.35 ..................... PALANDROMIC RHEUMATISM PELVIS AND THIGH
719.36 ..................... PALANDROMIC RHEUMATISM LOWER LEG
719.37 ..................... PALANDROMIC RHEUMATISM ANKLE AND FOOT
727.65 ..................... RUPTURE OF TENDON QUADRACEPS
727.66 ..................... RUPTURE OF TENDON PATELLAR
727.67 ..................... RUPTURE OF TENDON ACHILLES
727.68 ..................... RUPTURE OTHER TENDONS FOOT AND ANKLE
730.05 ..................... AC OSTEOMYELITIS-PELVIS
730.06 ..................... AC OSTEOMYELITIS-L/LEG
730.07 ..................... AC OSTEOMYELITIS-ANKLE
730.15 ..................... CHR OSTEOMYELIT-PELVIS
730.16 ..................... CHR OSTEOMYELIT-L/LEG
730.17 ..................... CHR OSTEOMYELIT-ANKLE
730.25 ..................... OSTEOMYELITIS NOS-PELVI
730.26 ..................... OSTEOMYELITIS NOS-L/LEG
730.27 ..................... OSTEOMYELITIS NOS-ANKLE
730.35 ..................... PERIOSTITIS-PELVIS
730.36 ..................... PERIOSTITIS-L/LEG
730.37 ..................... PERIOSTITIS-ANKLE
730.75 M.................... POLIO OSTEOPATHY-PELVIS
730.76 M.................... POLIO OSTEOPATHY-L/LEG
730.77 M.................... POLIO OSTEOPATHY-ANKLE
730.85 M.................... BONE INFECT NEC-PELVIS
730.86 M.................... BONE INFECT NEC-L/LEG
730.87 M.................... BONE INFECT NEC-ANKLE
730.95 ..................... BONE INFECT NOS-PELVIS
730.96 ..................... BONE INFECT NOS-L/LEG
730.97 ..................... BONE INFECT NOS-ANKLE
733.14 ..................... PATHOLOGIC FRACTURE OF NECK OF FEMUR
733.15 ..................... PATHOLOGIC FRACTURE OF FEMUR
733.16 ..................... PATHOLOGIC FRACTURE OF TIBIA OR FIBULA
733.42 ..................... ASEPTIC NECROSIS OF HEAD AND NECK OF FEMUR
733.43 ..................... ASEPTIC NECROSIS OF MEDIAL FEMORAL CONDYLE
808 ..................... FRACTURE OF PELVIS
820 ..................... FRACTURE OF NECK OF FEMUR
821 ..................... FRACTURE OTHER&UNSPEC PARTS FEMUR
822 ..................... FRACTURE OF PATELLA
823 ..................... FRACTURE OF TIBIA AND FIBULA
824 ..................... FRACTURE OF ANKLE
825 ..................... FRACTURE 1/MORE TARSAL&MT BNS
827 ..................... OTH MX&ILL-DEFINED FX LOWER LIMB
828 ..................... MX FX LEGS-LEG W/ARM-LEGS W/RIBS
835 ..................... DISLOCATION OF HIP
836 ..................... DISLOCATION OF KNEE
897 ..................... TRAUMATIC AMPUTATION OF LEG
928 ..................... CRUSHING INJURY OF LOWER LIMB
Ortho 2--Other Orthopedic 711.01 ..................... PYOGEN ARTHRITIS-SHLDER
disorders.
711.02 ..................... PYOGEN ARTHRITIS-UP/ARM
711.03 ..................... PYOGEN ARTHRITIS-FOREAR
711.04 ..................... PYOGEN ARTHRITIS-HAND
711.08 ..................... PYOGEN ARTHRITIS NEC
711.09 ..................... PYOGEN ARTHRITIS-MULT
711.10 M.................... REITER ARTHRITIS-UNSPEC
711.11 M.................... REITER ARTHRITIS-SHLDER
711.12 M.................... REITER ARTHRITIS-UP/ARM
711.13 M.................... REITER ARTHRITIS-FOREAR
711.14 M.................... REITER ARTHRITIS-HAND
711.18 M.................... REITER ARTHRITIS NEC
711.19 M.................... REITER ARTHRITIS-MULT
[[Page 25379]]
711.20 M.................... BEHCET ARTHRITIS-UNSPEC
711.21 M.................... BEHCET ARTHRITIS-SHLDER
711.22 M.................... BEHCET ARTHRITIS-UP/ARM
711.23 M.................... BEHCET ARTHRITIS-FOREAR
711.24 M.................... BEHCET ARTHRITIS-HAND
711.28 M.................... BEHCET ARTHRITIS NEC
711.29 M.................... BEHCET ARTHRITIS-MULT
711.30 M.................... DYSENTER ARTHRIT-UNSPEC
711.31 M.................... DYSENTER ARTHRIT-SHLDER
711.32 M.................... DYSENTER ARTHRIT-UP/ARM
711.33 M.................... DYSENTER ARTHRIT-FOREAR
711.34 M.................... DYSENTER ARTHRIT-HAND
711.38 M.................... DYSENTER ARTHRIT NEC
711.39 M.................... DYSENTER ARTHRIT-MULT
711.40 M.................... BACT ARTHRITIS-UNSPEC
711.41 M.................... BACT ARTHRITIS-SHLDER
711.42 M.................... BACT ARTHRITIS-UP/ARM
711.43 M.................... BACT ARTHRITIS-FOREARM
711.44 M.................... BACT ARTHRITIS-HAND
711.48 M.................... BACT ARTHRITIS NEC
711.49 M.................... BACT ARTHRITIS-MULT
711.50 M.................... VIRAL ARTHRITIS-UNSPEC
711.51 M.................... VIRAL ARTHRITIS-SHLDER
711.52 M.................... VIRAL ARTHRITIS-UP/ARM
711.53 M.................... VIRAL ARTHRITIS-FOREARM
711.54 M.................... VIRAL ARTHRITIS-HAND
711.58 M.................... VIRAL ARTHRITIS NEC
711.59 M.................... VIRAL ARTHRITIS-MULT
711.60 M.................... MYCOTIC ARTHRITIS-UNSPE
711.61 M.................... MYCOTIC ARTHRITIS-SHLDE
711.62 M.................... MYCOTIC ARTHRITIS-UP/AR
711.63 M.................... MYCOTIC ARTHRIT-FOREARM
711.64 M.................... MYCOTIC ARTHRITIS-HAND
711.68 M.................... MYCOTIC ARTHRITIS NEC
711.69 M.................... MYCOTIC ARTHRITIS-MULT
711.70 M.................... HELMINTH ARTHRIT-UNSPEC
711.71 M.................... HELMINTH ARTHRIT-SHLDER
711.72 M.................... HELMINTH ARTHRIT-UP/ARM
711.73 M.................... HELMINTH ARTHRIT-FOREAR
711.74 M.................... HELMINTH ARTHRIT-HAND
711.78 M.................... HELMINTH ARTHRIT NEC
711.79 M.................... HELMINTH ARTHRIT-MULT
711.80 M.................... INF ARTHRITIS NEC-UNSPE
711.81 M.................... INF ARTHRITIS NEC-SHLDE
711.82 M.................... INF ARTHRITIS NEC-UP/AR
711.83 M.................... INF ARTHRIT NEC-FOREARM
711.84 M.................... INF ARTHRITIS NEC-HAND
711.88 M.................... INF ARTHRIT NEC-OTH SIT
711.89 M.................... INF ARTHRITIS NEC-MULT
711.90 ..................... INF ARTHRITIS NOS-UNSPE
711.91 ..................... INF ARTHRITIS NOS-SHLDE
711.92 ..................... INF ARTHRITIS NOS-UP/AR
711.93 ..................... INF ARTHRIT NOS-FOREARM
711.94 ..................... INF ARTHRIT NOS-HAND
711.98 ..................... INF ARTHRIT NOS-OTH SIT
711.99 ..................... INF ARTHRITIS NOS-MULT
712.10 M.................... DICALC PHOS CRYST-UNSPE
712.11 M.................... DICALC PHOS CRYST-SHLDE
712.12 M.................... DICALC PHOS CRYST-UP/AR
712.13 M.................... DICALC PHOS CRYS-FOREAR
712.14 M.................... DICALC PHOS CRYST-HAND
712.18 M.................... DICALC PHOS CRY-SITE NE
712.19 M.................... DICALC PHOS CRYST-MULT
712.20 M.................... PYROPHOSPH CRYST-UNSPEC
712.21 M.................... PYROPHOSPH CRYST-SHLDER
712.22 M.................... PYROPHOSPH CRYST-UP/ARM
712.23 M.................... PYROPHOSPH CRYST-FOREAR
712.24 M.................... PYROPHOSPH CRYST-HAND
712.28 M.................... PYROPHOS CRYST-SITE NEC
712.29 M.................... PYROPHOS CRYST-MULT
[[Page 25380]]
712.30 M.................... CHONDROCALCIN NOS-UNSPE
712.31 M.................... CHONDROCALCIN NOS-SHLDE
712.32 M.................... CHONDROCALCIN NOS-UP/AR
712.33 M.................... CHONDROCALC NOS-FOREARM
712.34 M.................... CHONDROCALCIN NOS-HAND
712.38 M.................... CHONDROCALC NOS-OTH SIT
712.39 M.................... CHONDROCALCIN NOS-MULT
712.80 ..................... CRYST ARTHROP NEC-UNSPE
712.81 ..................... CRYST ARTHROP NEC-SHLDE
712.82 ..................... CRYST ARTHROP NEC-UP/AR
712.83 ..................... CRYS ARTHROP NEC-FOREAR
712.84 ..................... CRYST ARTHROP NEC-HAND
712.88 ..................... CRY ARTHROP NEC-OTH SIT
712.89 ..................... CRYST ARTHROP NEC-MULT
712.90 ..................... CRYST ARTHROP NOS-UNSPE
712.91 ..................... CRYST ARTHROP NOS-SHLDR
712.92 ..................... CRYST ARTHROP NOS-UP/AR
712.93 ..................... CRYS ARTHROP NOS-FOREAR
712.94 ..................... CRYST ARTHROP NOS-HAND
712.98 ..................... CRY ARTHROP NOS-OTH SIT
712.99 ..................... CRYST ARTHROP NOS-MULT
713.0 M.................... ARTHROP W ENDOCR/MET DI
713.1 M.................... ARTHROP W NONINF GI DIS
713.2 M.................... ARTHROPATH W HEMATOL DI
713.3 M.................... ARTHROPATHY W SKIN DIS
713.4 M.................... ARTHROPATHY W RESP DIS
713.5 M.................... ARTHROPATHY W NERVE DIS
713.6 M.................... ARTHROP W HYPERSEN REAC
713.7 M.................... ARTHROP W SYSTEM DIS NE
713.8 M.................... ARTHROP W OTH DIS NEC
714 ..................... RA&OTH INFLAM POLYARTHROPATHIES
715.15 ..................... OSTEOARTHROSIS, LOCALIZED, PRIMARY, PELVIS
AND THIGH
715.16 ..................... OSTEOARTHROSIS, LOCALIZED, PRIMARY, LOWER
LEG
715.25 ..................... OSTEOARTHROSIS, LOCALIZED, SECONDARY,
PELVIS AND THIGH
715.26 ..................... OSTEOARTHROSIS, LOCALIZED, SECONDARY,
LOWER LEG
715.35 ..................... OSTEOARTHROSIS, LOCALIZED, NOT SPEC
PRIMARY OR SECONDARY, PELVIS AND THIGH
715.36 ..................... OSTEOARTHROSIS, LOCALIZED, NOT SPEC
PRIMARY OR SECONDARY, LOWER LEG
715.95 ..................... OSTEOARTHROSIS, UNSPECIFIED, PELVIS AND
THIGH
715.96 ..................... OSTEOARTHROSIS, UNSPECIFIED, LOWER LEG
716.00 ..................... KASCHIN-BECK DIS-UNSPEC
716.01 ..................... KASCHIN-BECK DIS-SHLDER
716.02 ..................... KASCHIN-BECK DIS-UP/ARM
716.03 ..................... KASCHIN-BECK DIS-FOREARM
716.04 ..................... KASCHIN-BECK DIS-HAND
716.08 ..................... KASCHIN-BECK DIS NEC
716.09 ..................... KASCHIN-BECK DIS-MULT
716.10 ..................... TRAUM ARTHROPATHY-UNSPEC
716.11 ..................... TRAUM ARTHROPATHY-SHLDER
716.12 ..................... TRAUM ARTHROPATHY-UP/ARM
716.13 ..................... TRAUM ARTHROPATH-FOREARM
716.14 ..................... TRAUM ARTHROPATHY-HAND
716.18 ..................... TRAUM ARTHROPATHY NEC
716.19 ..................... TRAUM ARTHROPATHY-MULT
716.20 ..................... ALLERG ARTHRITIS-UNSPEC
716.21 ..................... ALLERG ARTHRITIS-SHLDER
716.22 ..................... ALLERG ARTHRITIS-UP/ARM
716.23 ..................... ALLERG ARTHRITIS-FOREARM
716.24 ..................... ALLERG ARTHRITIS-HAND
716.28 ..................... ALLERG ARTHRITIS NEC
716.29 ..................... ALLERG ARTHRITIS-MULT
716.30 ..................... CLIMACT ARTHRITIS-UNSPEC
716.31 ..................... CLIMACT ARTHRITIS-SHLDER
716.32 ..................... CLIMACT ARTHRITIS-UP/ARM
716.33 ..................... CLIMACT ARTHRIT-FOREARM
716.34 ..................... CLIMACT ARTHRITIS-HAND
[[Page 25381]]
716.38 ..................... CLIMACT ARTHRITIS NEC
716.39 ..................... CLIMACT ARTHRITIS-MULT
716.40 ..................... TRANS ARTHROPATHY-UNSPEC
716.41 ..................... TRANS ARTHROPATHY-SHLDER
716.42 ..................... TRANS ARTHROPATHY-UP/ARM
716.43 ..................... TRANS ARTHROPATH-FOREARM
716.44 ..................... TRANS ARTHROPATHY-HAND
716.48 ..................... TRANS ARTHROPATHY NEC
716.49 ..................... TRANS ARTHROPATHY-MULT
716.50 ..................... POLYARTHRITIS NOS-UNSPEC
716.51 ..................... POLYARTHRITIS NOS-SHLDER
716.52 ..................... POLYARTHRITIS NOS-UP/ARM
716.53 ..................... POLYARTHRIT NOS-FOREARM
716.54 ..................... POLYARTHRITIS NOS-HAND
716.58 ..................... POLYARTHRIT NOS-OTH SITE
716.59 ..................... POLYARTHRITIS NOS-MULT
716.60 ..................... MONOARTHRITIS NOS-UNSPEC
716.61 ..................... MONOARTHRITIS NOS-SHLDER
716.62 ..................... MONOARTHRITIS NOS-UP/ARM
716.63 ..................... MONOARTHRIT NOS-FOREARM
716.64 ..................... MONOARTHRITIS NOS-HAND
716.65 ..................... UNSPECIFIED MONOARTHRITIS, PELVIS AND
THIGH
716.66 ..................... UNSPECIFIED MONOARTHRITIS, LOWER LEG
716.68 ..................... MONOARTHRIT NOS-OTH SITE
716.80 ..................... ARTHROPATHY NEC-UNSPEC
716.81 ..................... ARTHROPATHY NEC-SHLDER
716.82 ..................... ARTHROPATHY NEC-UP/ARM
716.83 ..................... ARTHROPATHY NEC-FOREARM
716.84 ..................... ARTHROPATHY NEC-HAND
716.88 ..................... ARTHROPATHY NEC-OTH SITE
716.89 ..................... ARTHROPATHY NEC-MULT
716.90 ..................... ARTHROPATHY NOS-UNSPEC
716.91 ..................... ARTHROPATHY NOS-SHLDER
716.92 ..................... ARTHROPATHY NOS-UP/ARM
716.93 ..................... ARTHROPATHY NOS-FOREARM
716.94 ..................... ARTHROPATHY NOS-HAND
716.98 ..................... ARTHROPATHY NOS-OTH SITE
716.99 ..................... ARTHROPATHY NOS-MULT
718.01 ..................... ART CARTIL DISORDER SHOULDER
718.02 ..................... ART CARTIL DIS UPPER ARM
718.03 ..................... ART CARTIL DIS FOREARM
718.04 ..................... ART CARTIL DIS HAND
718.08 ..................... ART CART DIS OTH SITES
718.09 ..................... ART CART DIS MULT
718.1 ..................... LOOSE BODY IN JT
718.20 ..................... PATHOLOGIC DISLOCATION UNSPEC SITE
718.21 ..................... PATHOLOGIC DISLOCATION SHOULDER
718.22 ..................... PATHOLOGIC DISLOCATION UPPER ARM
718.23 ..................... PATHOLOGIC DISLOCATION FOREARM
718.24 ..................... PATHOLOGIC DISLOCATION HAND
718.28 ..................... PATHOLOGIC DISLOCATION OTH LOC
718.29 ..................... PATHOLOGIC DISLOCATION MULT LOC
718.30 ..................... RECURRENT DISLOCATION UNSPEC SITE
718.31 ..................... RECURRENT DISLOCATION SHOULDER
718.32 ..................... RECURRENT DISLOCATION UPPER ARM
718.33 ..................... RECURRENT DISLOCATION FOREARM
718.34 ..................... RECURRENT DISLOCATION HAND
718.38 ..................... RECURRENT DISLOCATION OTH LOC
718.39 ..................... RECURRENT DISLOCATION MULT LOC
718.40 ..................... CONTRACTURE OF JOINT UNSPEC SITE
718.41 ..................... CONTRACTURE SHOULDER
718.42 ..................... CONTRACTURE OF JOINT UPPER ARM
718.43 ..................... CONTRACTURE OF JOINT FOREARM
718.44 ..................... CONTRACTURE OF JOINT HAND
718.48 ..................... CONTRACTURE OF JOINT OTH LOC
718.49 ..................... CONTRACTURE OF JOINT MULT LOC
718.50 ..................... ANKYLOSIS OF JOINT UNSPEC SITE
718.51 ..................... ANKYLOSIS OF SHOULDER
718.52 ..................... ANKYLOSIS OF JOINT UPPER ARM
718.53 ..................... ANKYLOSIS OF JOINT FOREARM
[[Page 25382]]
718.54 ..................... ANKYLOSIS OF JOINT HAND
718.58 ..................... ANKYLOSIS OF JOINT OTH LOC
718.59 ..................... ANKYLOSIS OF JOINT MULT LOC
718.60 ..................... UNSPED 'INTRAPELVIC PROTRUSION ACETAB
718.7 ..................... DEV DISLOC JOINT
718.80 ..................... OTH DERANGMENT JT NEC UNSPEC SITE
718.81 ..................... OTHER DERANGEMENT OF SHOULDER
718.82 ..................... OTH DERANGMENT JT NEC UPPER ARM
718.83 ..................... OTH DERANGMENT JT NEC FOREARM
718.84 ..................... OTH DERANGMENT JT NEC HAND
718.88 ..................... OTH DERANGMENT JT NEC OTH LOC
718.89 ..................... OTH DERANGMENT JT NEC MULT LOC
718.9 ..................... UNSPEC DERANGMENT JT
719.1 ..................... HEMARTHROSIS UNSPECIFIED SITE
719.11 ..................... HEMARTHROSIS SHOULDER
719.12 ..................... HEMARTHROSIS UPPER ARM
719.13 ..................... HEMARTHROSIS FOREARM
719.14 ..................... HEMARTHROSIS HAND
719.18 ..................... HEMARTHROSIS OTHER SPECIFIED
719.19 ..................... HEMARTHROSIS MULTIPLE SITES
719.2 ..................... VILLONODULAR SYNOVITIS UNSPECIFIED SITE
719.21 ..................... VILLONODULAR SYNOVITIS SHOULDER
719.22 ..................... VILLONODULAR SYNOVITIS UPPER ARM
719.23 ..................... VILLONODULAR SYNOVITIS FOREARM
719.24 ..................... VILLONODULAR SYNOVITIS HAND
719.28 ..................... VILLONODULAR SYNOVITIS OTHER SITES
719.29 ..................... VILLONODULAR SYNOVITIS MULTIPLE SITES
719.3 ..................... PALANDROMIC RHEUMATISM UNSPECIFIED SITE
719.31 ..................... PALANDROMIC RHEUMATISM SHOULDER
719.32 ..................... PALANDROMIC RHEUMATISM UPPER ARM
719.33 ..................... PALANDROMIC RHEUMATISM FOREARM
719.34 ..................... PALANDROMIC RHEUMATISM HAND
719.38 ..................... PALANDROMIC RHEUMATISM OTHER SITES
719.39 ..................... PALANDROMIC RHEUMATISM MULTIPLE SITES
720.0 ..................... ANKYLOSING SPONDYLITIS
720.1 ..................... SPINAL ENTHESOPATHY
720.2 ..................... SACROILIITIS NEC
720.8 M.................... OTHER INFLAMMATORY SPONDYLOPATHIES
720.81 M.................... SPONDYLOPATHY IN OTH DI
720.89 ..................... OTHER INFLAMMATORY SPONDYLOPATHIES
720.9 ..................... UNSPEC INFLAMMATORY SPONDYLOPATHY
721 ..................... SPONDYLOSIS AND ALLIED DISORDERS
722.0 ..................... DISPLACEMENT OF CERVICAL INTERVERTEBRAL
DISC WITHOUT MYELOPATHY
722.1 ..................... DISPLACEMENT OF THORACIC OR LUMBAR
INTERVERTEBRAL DISC WITHOUT MYELOPATHY
722.2 ..................... DISPLACEMENT OF INTERVERTEBRAL DISC, SITE
UNSPECIFIED, WITHOUT MYELOPATHY
722.4 ..................... DEGENERATION OF CERVICAL INTERVERTEBRAL
DISC
722.5 ..................... DEGENERATION OF THORACIC OR LUMBAR
INTERVERTEBRAL DISC
722.6 ..................... DEGENERATION OF INTERVERTEBRAL DISC, SITE
UNSPECIFIED
722.7 ..................... INTERVERTEBRAL DISC DISORDER WITH
MYELOPATHY
722.8 ..................... POSTLAMINECTOMY SYNDROME
722.9 ..................... OTHER AND UNSPECIFIED DISC DISORDER
723.0 ..................... SPINAL STENOSIS OF CERVICAL REGION
723.1 ..................... CERVICALGIA
723.2 ..................... CERVICOCRANIAL SYNDROME
723.3 ..................... CERVICOBRACHIAL SYNDROME
723.4 ..................... BRACHIA NEURITIS OR RADICULITIS
723.5 ..................... TORTICOLLIS, UNSPECIFIED
723.6 ..................... PANNICULITIS SPECIFIED AS AFFECTING NECK
723.7 ..................... OSSIFICATION OF POSTERIOR LONGITUDINAL
LIGAMENT IN CERVICAL REGION
723.8 ..................... OTHER SYNDROMES AFFECTING CERVICAL REGION
723.9 ..................... UNSPEC MUSCULOSKEL SX OF NECK
724 ..................... OTHER&UNSPECIFIED DISORDERS OF BACK
725 ..................... POLYMYALGIA RHEUMATICA
726.0 ..................... ADHESIVE CAPSULITIS
[[Page 25383]]
726.10 ..................... DISORDERS OF BURSAE AND TENDONS
726.11 ..................... CALCIFYING TENDINITIS
726.12 ..................... BICIPITAL TENOSYNOVITIS
726.19 ..................... ROTATOR CUFF SYNDROME OTHER
727.61 ..................... COMPLETE RUPTURE OF ROTATOR CUFF
728.0 ..................... INFECTIVE MYOSITIS
728.10 ..................... CALCIFICATION AND OSSIFICATION,
UNSPECIFIED
728.11 ..................... PROGRESSIVE MYOSITIS OSSIFICANS
728.12 ..................... TRAUMATIC MYOSITIS OSSIFICATIONS
728.13 ..................... POST OP HETEROTOPIC CALCIFICATION
728.19 ..................... OTHER MUSCULAR CALCIFICATION AND
OSSIFICATION
728.2 ..................... MUSCULAR WASTING AND DISUSE ATROPHY
728.3 ..................... OTHER SPECIFIC MUSCLE DISORDERS
728.4 ..................... LAXITY OF LIGAMENT
728.5 ..................... HYPERMOBILITY SYNDROME
728.6 ..................... CONTRACTURE OF PALMAR FASCIA
730.00 ..................... AC OSTEOMYELITIS-UNSPEC
730.01 ..................... AC OSTEOMYELITIS-SHLDER
730.02 ..................... AC OSTEOMYELITIS-UP/ARM
730.03 ..................... AC OSTEOMYELITIS-FOREAR
730.04 ..................... AC OSTEOMYELITIS-HAND
730.08 ..................... AC OSTEOMYELITIS NEC
730.09 ..................... AC OSTEOMYELITIS-MULT
730.10 ..................... CHR OSTEOMYELITIS-UNSP
730.11 ..................... CHR OSTEOMYELIT-SHLDER
730.12 ..................... CHR OSTEOMYELIT-UP/ARM
730.13 ..................... CHR OSTEOMYELIT-FOREARM
730.14 ..................... CHR OSTEOMYELIT-HAND
730.18 ..................... CHR OSTEOMYELIT NEC
730.19 ..................... CHR OSTEOMYELIT-MULT
730.20 ..................... OSTEOMYELITIS NOS-UNSPE
730.21 ..................... OSTEOMYELITIS NOS-SHLDE
730.22 ..................... OSTEOMYELITIS NOS-UP/AR
730.23 ..................... OSTEOMYELIT NOS-FOREARM
730.24 ..................... OSTEOMYELITIS NOS-HAND
730.28 ..................... OSTEOMYELIT NOS-OTH SIT
730.29 ..................... OSTEOMYELITIS NOS-MULT
730.30 ..................... PERIOSTITIS-UNSPEC
730.31 ..................... PERIOSTITIS-SHLDER
730.32 ..................... PERIOSTITIS-UP/ARM
730.33 ..................... PERIOSTITIS-FOREARM
730.34 ..................... PERIOSTITIS-HAND
730.38 ..................... PERIOSTITIS NEC
730.39 ..................... PERIOSTITIS-MULT
730.70 M.................... POLIO OSTEOPATHY-UNSPEC
730.71 M.................... POLIO OSTEOPATHY-SHLDER
730.72 M.................... POLIO OSTEOPATHY-UP/ARM
730.73 M.................... POLIO OSTEOPATHY-FOREAR
730.74 M.................... POLIO OSTEOPATHY-HAND
730.78 M.................... POLIO OSTEOPATHY NEC
730.79 M.................... POLIO OSTEOPATHY-MULT
730.80 M.................... BONE INFECT NEC-UNSPEC
730.81 M.................... BONE INFECT NEC-SHLDER
730.82 M.................... BONE INFECT NEC-UP/ARM
730.83 M.................... BONE INFECT NEC-FOREARM
730.84 M.................... BONE INFECT NEC-HAND
730.88 M.................... BONE INFECT NEC-OTH SIT
730.89 M.................... BONE INFECT NEC-MULT
730.90 ..................... BONE INFEC NOS-UNSP SIT
730.91 ..................... BONE INFECT NOS-SHLDER
730.92 ..................... BONE INFECT NOS-UP/ARM
730.93 ..................... BONE INFECT NOS-FOREARM
730.94 ..................... BONE INFECT NOS-HAND
730.98 ..................... BONE INFECT NOS-OTH SIT
730.99 ..................... BONE INFECT NOS-MULT
731.0 ..................... OSTEITIS DEFORMANS W/O BN TUMR
731.1 M.................... OSTEITIS DEFORMANS DZ CLASS ELSW
731.2 ..................... HYPERTROPH PULM OSTEOARTHROPATHY
731.8 M.................... OTH BONE INVOLVEMENT DZ CLASS EL
732 ..................... OSTEOCHONDROPATHIES
[[Page 25384]]
733.10 ..................... PATHOLOGIC FRACTURE UNSPEC
733.11 ..................... PATHOLOGIC FRACTURE HUMERUS
733.12 ..................... PATHOLOGIC FRACTURE DISTAL RADIUS ULNA
733.13 ..................... PATHOLOGIC FRACTURE OF VERTEBRAE
733.19 ..................... PATHOLOGIC FRACTURE OTH SPEC SITE
800 ..................... FRACTURE OF VAULT OF SKULL
801 ..................... FRACTURE OF BASE OF SKULL
802 ..................... FRACTURE OF FACE BONES
803 ..................... OTHER&UNQUALIFIED SKULL FRACTURES
804 ..................... MX FX INVLV SKULL/FACE W/OTH BNS
805 ..................... FX VERT COLUMN W/O SP CRD INJR
807 ..................... FRACTURE RIB STERNUM LARYNX&TRACHEA
809 ..................... ILL-DEFINED FRACTURES BONES TRUNK
810 ..................... FRACTURE OF CLAVICLE
811 ..................... FRACTURE OF SCAPULA
812 ..................... FRACTURE OF HUMERUS
813 ..................... FRACTURE OF RADIUS AND ULNA
814 ..................... FRACTURE OF CARPAL BONE
815 ..................... FRACTURE OF METACARPAL BONE
816 ..................... FRACTURE ONE OR MORE PHALANGES HAND
817 ..................... MULTIPLE FRACTURES OF HAND BONES
818 ..................... ILL-DEFINED FRACTURES OF UPPER LIMB
819 ..................... MX FX UP LIMBS&LIMBS W/RIB&STERNUM
831 ..................... DISLOCATION OF SHOULDER
832 ..................... DISLOCATION OF ELBOW
833 ..................... DISLOCATION OF WRIST
837 ..................... DISLOCATION OF ANKLE
838 ..................... DISLOCATION OF FOOT
846 ..................... SPRAINS&STRAINS SACROILIAC REGION
847 ..................... SPRAINS&STRAINS OTH&UNS PART BACK
Psych 1--Affective and other 295 ..................... SCHIZOPHRENIA
psychoses, depression.
296 ..................... AFFECTIVE PSYCHOSES
297 ..................... DELUSIONAL DIS
298 ..................... OTH PSYCHOSES
311 ..................... DEPRESSIVE DISORDER NEC
Psych 2--Degenerative and other 331.0 ..................... ALZHEIMER'S DISEASE
organic psychiatric disorders.
331.11 ..................... PICK'S DISEASE
331.19 ..................... OTH FRONTO-TEMPORAL DEMENTIA
331.2 ..................... SENILE DEGENERAT BRAIN
331.3 ..................... COMMUNICAT HYDROCEPHALUS
331.4 ..................... OBSTRUCTIV HYDROCEPHALUS
331.7 M.................... CEREB DEGEN IN OTH DIS
331.81 ..................... REYE'S SYNDROME
331.82 ..................... DEMENTIA WITH LEWY BODIES
331.89 ..................... CEREB DEGENERATION NEC
331.9 ..................... CEREB DEGENERATION NOS
290.0 M.................... SENILE DEMENTIA, UNCOMPLICATED
290.10 M.................... PRESENILE DEMENTIA UNCOMP
290.11 M.................... PRESENILE DEMENTIA WITH DELIRIUM
290.12 M.................... PRESENILE DEMENTIA WITH DELUSIONAL
FEATURES
290.13 M.................... PRESENILE DEMENTIA WITH DEPRESSIVE
FEATURES
290.20 M.................... SENILE DEMENTIA WITH DELUSIONAL FEATURES
290.21 M.................... SENILE DEMENTIA WITH DEPRESSIVE FEATURES
290.3 M.................... SENILE DEMENTIA WITH DELIRIUM
290.40 M.................... VASCULAR DEMENTIA, UNCOMPLICATED
290.41 M.................... VASCULAR DEMENTIA, WITH DELIRIUM
290.42 M.................... VASCULAR DEMENTIA, WITH DELUSIONS
290.43 M.................... VASCULAR DEMENTIA, WITH DEPRESSED MOOD
291.1 ..................... ALCOHOL PSYCHOSIS
291.2 ..................... ALCOHOL DEMENTIA
292.8 ..................... DRUG PSYCHOSES
294.0 M.................... AMNESTIC DISORD OTH DIS
294.1 M.................... DEMENTIA
294.8 ..................... MENTAL DISOR NEC OTH DIS
294.9 ..................... MENTAL DISOR NOS OTH DIS
Pulmonary disorders.............. 491 ..................... CHRONIC BRONCHIT
492 ..................... EMPHYSEMA
493.2 ..................... ASTHMA
[[Page 25385]]
496 ..................... CHRONIC AIRWAY OBSTRUCTION NEC
Skin 1--Traumatic wounds, burns 870 ..................... OPEN WOUND OF OCULAR ADNEXA
and post-operative complications.
872 ..................... OPEN WOUND OF EAR
873 ..................... OTHER OPEN WOUND OF HEAD
874 ..................... OPEN WOUND OF NECK
875 ..................... OPEN WOUND OF CHEST
876 ..................... OPEN WOUND OF BACK
877 ..................... OPEN WOUND OF BUTTOCK
878 ..................... OPEN WND GNT ORGN INCL TRAUMAT AMP
879 ..................... OPEN WOUND OTH&UNSPEC SITE NO LIMBS
880 ..................... OPEN WOUND OF SHOULDER&UPPER ARM
881 ..................... OPEN WOUND OF ELBOW FOREARM&WRIST
882 ..................... OPEN WOUND HAND EXCEPT FINGER ALONE
883 ..................... OPEN WOUND OF FINGER
884 ..................... MX&UNSPEC OPEN WOUND UPPER LIMB
885 ..................... TRAUMATIC AMPUTATION OF THUMB
886 ..................... TRAUMATIC AMPUTATION OTHER FINGER
887 ..................... TRAUMATIC AMPUTATION OF ARM&HAND
890 ..................... OPEN WOUND OF HIP AND THIGH
891 ..................... OPEN WOUND OF KNEE, LEG , AND ANKLE
892 ..................... OPEN WOUND OF FOOT EXCEPT TOE ALONE
893 ..................... OPEN WOUND OF TOE
894 ..................... MX&UNSPEC OPEN WOUND LOWER LIMB
895 ..................... TRAUMATIC AMPUTATION OF TOE
896 ..................... TRAUMATIC AMPUTATION OF FOOT
941 ..................... BURN OF FACE, HEAD, AND NECK
942 ..................... BURN OF TRUNK
943 ..................... BURN UPPER LIMB EXCEPT WRIST&HAND
944 ..................... BURN OF WRIST AND HAND
945 ..................... BURN OF LOWER LIMB
946 ..................... BURNS OF MULTIPLE SPECIFIED SITES
948 ..................... BURN CLASS ACCORD-BODY SURF INVOLVD
949 ..................... BURN, UNSPECIFIED SITE
927 ..................... CRUSHING INJURY OF UPPER LIMB
951 ..................... INJURY TO OTHER CRANIAL NERVE
955.0 ..................... INJURY TO AXILLARY NERVE
955.1 ..................... INJURY TO MEDIAN NERVE
955.2 ..................... INJURY TO ULNAR NERVE
955.3 ..................... INJURY TO RADIAL NERVE
955.4 ..................... INJURY TO MUSCULOCUTANEOUS NERVE
955.5 ..................... INJURY TO CUTANEOUS SENSORY NERVE, UPPER
LIMB
955.6 ..................... INJURY TO DIGITAL NERVE
955.7 ..................... INJURY TO OTHER SPECIFIED NERVE(S)
SHOULDER GIRDLE AND UPPER LIMB
955.9 ..................... INJURY TO UNSPEC NERVE(S) SHOULDER GIRDLE
AND UPPER LIMB
956.2 ..................... INJURY TO POSTERIOR TIBIAL NERVE
956.3 ..................... INJURY TO PERONEAL NERVE
956.4 ..................... INJURY TO CUTANEOUS SENSORY NERVE, LOWER
LIMB
956.5 ..................... INJURY TO OTHER SPECIFIED NERVE(S) OF
PELVIC GIRDLE AND LOWER LIMB
956.9 ..................... INJURY TO UNSPECIFIED NERVE OF PELVIC
GIRDLE AND LOWER LIMB
998.1 ..................... HEMORR/HEMAT/SEROMA COMP PROC NEC
998.2 ..................... ACC PUNCT/LACRATION DURING PROC NEC
998.3 ..................... DISRUPTION OF OPERATION WOUND NEC
998.4 ..................... FB ACC LEFT DURING PROC NEC
998.5 ..................... POSTOPERATIVE INFECTION NEC
998.6 ..................... PERSISTENT POSTOPERATIVE FIST NEC
998.83 ..................... NON-HEALING SURGICAL WOUND NEC
Skin 2--Ulcers and other skin 440.23 ..................... ATHEROSCLER-ART EXTREM W/ULCERATION
conditions.
707.1 ..................... ULCER LOWER LIMBS EXCEPT DECUBITUS
707.8 ..................... CHRONIC ULCER OTHER SPECIFIED SITE
707.9 ..................... CHRONIC ULCER OF UNSPECIFIED SITE
681 ..................... CELLULITIS&ABSCESS OF FINGER&TOE
683 ..................... ACUTE LYMPHADENITIS
684 ..................... IMPETIGO
685 ..................... PILONIDAL CYST
686 ..................... OTH LOCAL INF SKIN&SUBCUT TISSUE
[[Page 25386]]
440.24 ..................... ATHERSCLER-ART EXTREM W/GANGRENE
785.4 M.................... GANGRENE
565 ..................... ANAL FISSURE AND FISTULA
566 ..................... ABSCESS OF ANAL AND RECTAL REGIONS
682 ..................... OTHER CELLULITIS AND ABSCESS
680 ..................... CARBUNCLE AND FURUNCLE
----------------------------------------------------------------------------------------------------------------
*We are aware that some of these codes or code categories involve manifestation codes. The ICD-9-CM Official
Guidelines for Coding and Reporting requires that the underlying disease or condition code be sequenced first
followed by the manifestation code. The underlying disease codes associated with the manifestation codes are
not listed in Table 2b, and these underlying codes were not specified in the analysis process. However, when
reporting certain conditions that have both an underlying etiology and body system manifestations due to the
underlying etiology, the appropriate sequencing must be followed according to the ICD-9-CM Coding Guidelines.
Equally important, the reported etiology must be valid for the manifestation specified.
**Note: ``ICD-9-CM Official Guidelines for Coding and Reporting'' dictate that a three-digit code is to be used
only if it is not further subdivided. Where fourth-digit subcategories and/or fifth-digit subclassifications
are provided, they must be assigned. A code is invalid if it has not been coded to the full number of digits
required for that code. Codes with three digits are included in ICD-9-CM as the heading of a category of codes
that may be further subdivided by the use of fourth and/or fifth digits, which provide greater detail. The
category codes listed in Table 2b include all the related 4- and 5-digit codes.
d. Determining the Case-Mix Weights
In the case-mix model adopted in July 2000, we examined the sum of
scores for the clinical dimension of the system, and the sum of scores
for the functional dimension, and determined ranges of scores to assign
a severity level. For example, in the original case-mix model adopted
in July 2000, severity levels ranged from minimum to high for the
clinical dimension. Severity levels were used to derive regression
coefficients for calculating case-mix relative weights. The calculated
coefficients from this regression, which we call the payment
regression, were displayed in the July 3, 2000 Federal Register (65 FR
41201) (``Regression Coefficients for Calculating Case-Mix Relative
Weights'').
Now using the proposed four-equation case-mix model, we again
derived severity levels for the clinical, functional, and services
utilization dimensions. We classified activities of daily living
variables as functional variables, diagnostic, interaction, and other
OASIS variables as clinical variables, and therapy-related variables
(threshold variables and visit count variables) as services utilization
variables. For each episode in the sample, we summed the variables'
scores by dimension. Then, we examined the range of summed scores
within each equation and threshold group of the sample, in order to
determine severity level intervals. We determined how many severity
levels to define for each of the equation/threshold groups based on the
relative number of episodes in a potential severity level, and on the
clustering of summed scores. In addition, for the services utilization
dimension, which is based only on therapy visit utilization, we defined
severity intervals based on relatively small aggregates (ones, twos,
and threes) of therapy visits above the six-visit threshold up to 13
visits (equations 1 and 3) and above the 14-visit therapy threshold, up
to 19 therapy visits (equations 2 and 4). Our goal was to ensure
payment graduation due to added numbers of therapy visits between
thresholds, without creating too many severity levels.
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We derived the relative payment weights for the proposed four-
equation model using the same kind of payment regression we employed in
July 2000. The sample episodes were classified into severity levels as
just described. We defined indicator variables for the payment
regression based on these severity classifications. The major
difference between the July 2000 payment regression and the one in this
[[Page 25388]]
proposal is that additional indicator variables were defined to
identify the episodes classified into each equation of the four-
equation model, as well as certain thresholds and therapy visit
intervals. Including the indicator variables allows us to combine
information derived from the four-equation model into a single payment
regression equation. For example, an indicator variable was created for
the group of later episodes below 14 therapy visits and, within this
group, indicator variables were created for the six-visit therapy
threshold and successive therapy-visit aggregates. See the table of
regression coefficients (Table 4) for the remaining indicator
variables; the indicator variables for the underlying four equations
are denoted by the terms ``constant'' and ``intercept.'' An additional
indicator variable denoted by a constant was used for all episodes with
at least 20 therapy visits; it is explained further below.
As with the original HH PSS rule, regression coefficients in Table
4 represent the average addition to resource cost due to each severity
level. (To show the coefficients in actual, as opposed to resource
cost, dollars, the coefficients were scaled by a multiplier
representing the ratio of the HH PPS average payment level to the Abt
Associates average resource cost level.) However, the severity level
coefficients in Table 4 are specific to the classification of the
episode in the four-equation model; for example, only for early
episodes below 14 therapy visits are the severity level coefficients
$861.74 for the third clinical severity level, and $219.44 for the
second functional severity level.
The lowest-severity case-mix group is the base group for the
payment regression, whose predicted cost is the regression intercept
value of $1,265.18. This group consists of the lowest clinical,
functional, and services utilization severity levels for episodes
classified as early episodes below the 14-visit therapy threshold
(Equation 1 of the four-equation model). The service severity level for
this group is severity level 1 (S1), which comprises episodes of 0 to 5
therapy visits.
To use the results of the payment regression for determining
payments, find the severity level coefficients for the applicable
equation and add those amounts to the regression intercept and to the
constant for the applicable equation. There is no constant for the
first equation/group, the early episodes below the 14-visit therapy
threshold; for this group, the constant is the regression intercept.
For example, later episodes below the 14-visit therapy threshold with
clinical severity level 2, functional severity level 1, and service
severity level 2 have the following scaled coefficients summed to
represent the resource cost: $1,265.18 for the regression intercept;
$139.26 for the second clinical severity level; $645.90 for the second
service severity level (6 therapy visits); and $210.94, a constant
amount for all later episodes below 14 therapy visits. The constant
incorporates the predicted average resource cost for the lowest
functional severity group. The predicted average resource cost,
$2,261.28, is the sum of these four coefficients from the regression.
Table 5 shows the results of the computational procedure for all
combinations of severity levels within each equation/threshold group.
Table 4.--Regression Coefficients for Calculating Case-Mix Relative
Weights
------------------------------------------------------------------------
------------------------------------------------------------------------
Intercept (constant for all case mix groups)............... $1,265.18
------------------------------------------------------------------------
1st and 2nd Episodes, 0 to 13
Therapy Visits
------------------------------------------------------------------------
C2......................................................... 380.66
C3......................................................... 861.74
F2......................................................... 219.44
F3......................................................... 379.06
S2 (6 therapy visits)...................................... 499.96
S3 (7-9 therapy visits).................................... 935.02
S4 (10 therapy visits)..................................... 1,375.38
S5 (11-13 therapy visits).................................. 1,755.92
------------------------------------------------------------------------
1st and 2nd Episodes, 14 to 19
------------------------------------------------------------------------
Therapy Visits
------------------------------------------------------------------------
Constant................................................... 2,171.56
C2......................................................... 534.70
C3......................................................... 1,246.47
F2......................................................... 268.36
F3......................................................... 425.68
S2 (16-17 therapy visits).................................. 425.49
S3 (18-19 therapy visits).................................. 698.92
------------------------------------------------------------------------
3rd+ Episodes, 0 to 13 Therapy Visits
------------------------------------------------------------------------
Constant................................................... 210.94
C2......................................................... 139.26
C3......................................................... 613.76
F2......................................................... 414.74
F3......................................................... 818.25
S2 (6 therapy visits)...................................... 645.90
S3 (7-9 therapy visits).................................... 1,083.30
S4 (10 therapy visits)..................................... 1,507.60
S5 (11-13 therapy visits).................................. 1,890.78
------------------------------------------------------------------------
3rd+ Episodes, 14 to 19 Therapy Visits
------------------------------------------------------------------------
Constant................................................... 2,178.93
C2......................................................... 672.65
C3......................................................... 1,392.59
F2......................................................... 390.72
F3......................................................... 687.07
S2 (16-17 therapy visits).................................. 292.06
S3 (18-19 therapy visits).................................. 712.62
------------------------------------------------------------------------
All Episodes, 20+ Therapy Visits
------------------------------------------------------------------------
Constant................................................... 3,996.82
C2......................................................... 578.49
C3......................................................... 1,383.67
F2......................................................... 485.73
F3......................................................... 1,043.13
------------------------------------------------------------------------
Note: Regression coefficients were scaled by multiplier representing the
ratio of the HH PS average payment level to the Abt Associates average
resource cost level.
The payment regression in Table 4 reflects a decision to group
together early and later episodes for purposes of deriving the payment
regression coefficients for episodes at or above the 20-visit therapy
threshold. This has the advantage of producing a lower number of case-
mix groups than we would have had without grouping. Earlier analysis
had revealed that the coefficients, predicted average resource cost,
and relative weights of the case-mix groups for episodes of 20 or more
therapy visits in Equations 2 (early episodes) and 4 (later episodes)
had very similar values. Specifically, of the 9 case groups defined for
these noted episodes in each equation (a total of 18 groups), the
relative weights did not differ by more than 3.5 percent for 7 pairs of
groups; in the remaining two pairs of groups, the difference was
slightly more than 7 percent. Because of the virtually identical
values, we specified our payment regression procedure to produce a
single set of case-mix groups for all episodes in the 20-visit
threshold group, with the result that the relative case-mix weights do
not differ according to whether the episode is early or later. This
final step produced a total of 153 case-mix groups.
The predicted average resource cost for each case-mix group is
shown in Table 5. As with the coefficients in Table 4, these values are
scaled up from the resource cost values used to model the case-mix,
using a single multiplier. The multiplier allows us to report the
coefficients and the predicted average resource cost using dollars of
the same magnitude as the payments we would make. It does not change
the relationships among the predicted average resource costs, which are
the values that determine the relative case mix weights.
We used the predicted average resource costs for the 153 case-mix
groups to calculate the relative case-mix weights. The relative case-
mix weight for a case-mix group is simply the predicted average
resource cost for the group divided by the sample's overall
[[Page 25389]]
average resource cost. Table 5 shows the final relative case-mix
weights, after we applied two further adjustments, the budget
neutrality adjustment and the adjustment for nominal changes in case-
mix coding, which are explained further in this section II.A.2.c.
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*Note: Case-mix weight is after applying budget neutrality
adjustment factor (see text for description of adjustment of the
weights). Predicted average cost is calculated from the regression
coefficients in Table 4.
The budget neutrality adjustment to the relative case-mix weights
is required to achieve no change in outlays when moving from the
original case-mix system to the proposed new case-mix system. The
process of revising the case-mix system results in relative weights
with an average value of 1.0 over all 1,656,551 sample episodes we used
to represent the totality of reimbursable episodes in the first year of
the new case-mix system. The budget neutrality adjustment restores the
average case-mix weight that results from the revision process to the
average level observed before implementing the proposed new case-mix
system. To implement the budget neutrality adjustment, we used the
constant budget neutrality factor to increase the weights for all 153
case-mix groups to the prior average level. The resulting adjusted
case-mix weights prevent total payments under the proposed revised HH
PPS system from dropping below a budget-neutral level. The budget
neutrality adjustment factor is 1.194227193.
Based upon our review of trends in the national average case-mix
index (CMI), we are proposing an additional adjustment to the HH PPS
national standardized rate to account for case-mix upcoding that is not
due to change in the underlying health status of home health users.
Section 1895(b)(3)(B)(iv) of the Act specifically provides the
Secretary with the authority to adjust the standard payment amount (or
amounts) if the Secretary determines that the case-mix adjustments
resulted (or would likely result in) a change in aggregate payments
that are the result of changes in the coding or classification of
different units of services that do not reflect real changes in case-
mix. The Secretary may then adjust the payment amount to eliminate the
effect of the coding or classification changes that do not reflect real
changes in case-mix. To identify whether such an adjustment factor was
needed, we first determined the current average case-mix weight per
paid episode.
The most recent available data from which to compute an average
case-mix weight, or case mix index, under the HH PPS is from 2003.
Using the most current available data from 2003, the average case-mix
weight per episode for initial episodes is 1.233. To proceed with this
analysis, next we determined the baseline year needed to evaluate the
trend in the average case-mix per episode.
There are two different baseline years that could be used to
measure the increase in case-mix:
1. A Cohort Admitted to Home Care From October 1997 to April 1998 (the
Abt Case-Mix Study Sample Which Was Used To Develop the Current Case-
Mix Model)
There are several advantages to using data from this period of time
as the baseline from which we measure the increase in case-mix. This
time period is free from any anticipatory response to the HH PPS, and
data from this time period were used to develop the original
[[Page 25393]]
HH PPS model. Also, this is the only nationally representative dataset
from the 1997-1998 time period that measures patient characteristics
using an OASIS assessment form comparable to the one adopted for the HH
PPS. Because the Abt case-mix dataset was used to determine the current
set of case-mix weights, the average case-mix weight in the sample
equals 1.0. The sample's value of 1.0 provides a starting point from
which to measure the increase in case-mix. The increase in the average
case-mix using this time period as the baseline results in a 23.3
percent increase (from 1.0 to 1.233).
However, agencies included in the sample were volunteers for the
study and cannot be considered a perfectly representative, unbiased
sample. Furthermore, the response to Balanced Budget Act of 1997
provisions such as the home health interim payment system (HH IPS)
during this period might produce data from this sample that reflect a
case-mix in flux; for example, venipuncture patients were suddenly no
longer eligible, and long-term-care patients were less likely to be
admitted. Therefore, we are not confident the trend in the CMI between
the time of the Abt Associates study and 2003 reflects only changes in
nominal coding practices, as will be explained in more detail further
below in this section. Therefore, we are not proposing to use this
baseline year to determine the baseline.
2. 12 Months Ending September 30, 2000 (HH IPS Baseline)
Analysis of a 1 percent sample of initial episodes from the 1999-
2000 data under the HH IPS revealed an average case-mix weight of
1.125. Standardized to the distribution of agency type (freestanding
proprietary, freestanding not-for-profit, hospital-based, government,
and SNF-based) that existed in 2003 under the HH PPS, the average
weight was 1.134. We note this time period is likely not free from
anticipatory response to the HH PPS, because we published our initial
HH PPS proposal on October 28, 1999. The increase in the average case-
mix using this time period as the baseline results in an 8.7 percent
increase (from 1.134 to 1.233; 1.233-1.134=0.099; 0.099/1.134=0.087;
0.087*100=8.7%).
Since the HH IPS, reported severity has increased as episodes have
shifted from low severity groups to high severity groups. Concurrently,
there has been a reduction in resource utilization. For example, the
number of visits per episode has significantly declined under the HH
PPS since 1999. This decline is illustrated in Table 6.
Table 6.--Average Number of Home Health Visits per Episode
------------------------------------------------------------------------
Total home
health
Year hisits
(excluding
LUPAs)
------------------------------------------------------------------------
1997....................................................... 36.04
1998....................................................... 31.56
IPS........................................................ 25.51
2001....................................................... 21.78
2002....................................................... 21.44
2003....................................................... 20.98
------------------------------------------------------------------------
We believe that change in case-mix between the time of the Abt
Associates case-mix study and the end of the HH IPS period reflected
substantial change in real case-mix. First, throughout most of this
period, HHAs had no incentive to bring about nominal changes in case-
mix because case-mix was not a part of the payment system at that time.
Dramatic changes in the home health benefit also became evident
under the HH IPS as a result of provisions of the Balanced Budget Act
of 1997. Venipuncture patients were suddenly no longer eligible;
members of this group often had multiple comorbidities and commonly
used substantial amounts of personal care. In addition, according to a
study in the literature, beneficiaries age 85 and older, as well as
beneficiaries dually eligible for Medicare and Medicaid, were slightly
less likely to be admitted to home care (McCall et al., 2003). Both of
these groups are associated with high needs for personal care services,
suggesting that long-term care patients were less likely to be admitted
under the HH IPS. The agency closure rates in States associated with
high utilization (for example, Louisiana, Oklahoma, and Texas) also
suggests that admissions among long-term care patients experienced
decline. The OASIS data comparing the case-mix sample and the HH IPS
period exhibit some consistency with these ideas, in that they indicate
substantial decline in admission of the kinds of patients likely to be
long-term homebound beneficiaries with chronic medical care needs--
patients with diabetes, impaired vision, parenteral nutrition, bowel
and urinary incontinence, behavioral problems, toileting dependency,
and more-severe transferring dependency.
Various studies are consistent with the incentives created by the
HH IPS per-beneficiary cost cap--particularly an incentive to admit
many different patients with low care needs and/or for short periods to
keep per-beneficiary costs low (MedPac, 1999; GAO, 1998; GAO, 1999;
Smith et al., 1999).
An important implication of these studies and our comparative OASIS
data is that patients with intensive or lengthy needs for nursing and
personal care services as opposed to short-term or rehabilitative needs
were less likely to be found in the national home care caseload as a
result of the HH IPS. This would mean that a larger share of patients
in the caseload would have acute, post-acute, and rehabilitative needs.
Practice patterns began to change concomitantly with the share of
visits shifting towards rehabilitation services and, to a lesser extent
skilled nursing. In 1997 through 1998, the average number of therapy
visits per 60-day period was about 3, whereas by the last year of the
HH IPS, it rose to 4.4, with growth moderating thereafter. Skilled
nursing visits declined from more than 12 at the beginning of the HH
IPS, and stabilized at slightly more than 9 under the HH PPS. Aide
visits declined by 44 percent from 1997 to 2000, the last year of the
HH IPS, and continued to decline at a slower rate under the HH PPS. An
issue in interpreting these trends in the utilization data is the
uncertainty about how much of the startling change in therapy provision
was driven by patient case-mix, and how much was driven by an
anticipatory response of the practice pattern itself to our proposals
for the original HH PPS case-mix system. By using a 10-visit therapy
threshold, the proposal installed a substantial payment increase for
high-therapy episodes. If providers started responding to the
incentives in the anticipated HH PPS even before it became effective,
then our measure of case-mix change between the time of the Abt
Associates case-mix study sample and the HH IPS baseline is affected by
provider behavioral change that is not strictly reflective of the case-
mix of the treated population.
In contrast to the 13.4 percent increase that we consider a real
case-mix change, we believe that the 8.7 percent increase in the
national case-mix index between the HH IPS baseline and CY 2003 cannot
be considered a real increase in case-mix. The trend data on visits
(Table 6), resource data (presented below), and our analysis of changes
in rates of health characteristics on OASIS assessments and changes in
reporting practices (presented in section II.A.3.c of this proposed
rule) all lead to the conclusion that the underlying case-mix of the
population of home health users actually was essentially stable between
the IPS baseline and CY 2003. Our research shows that HHAs have reduced
services (see Tables 6 and 7) while the CMI continued to rise (see
Table 7). We would normally expect
[[Page 25394]]
growth in the CMI to be accompanied by more consumption of services;
but, to the contrary, we measure slightly lower resource consumption.
This is indicated by the data in Table 7 that illustrates, by quarter,
the average resource cost per episode as well as the average CMI for
initial (admissions) episodes and all episodes. (Note: In Table 7, the
CMI data for the HH IPS quarters are not adjusted for distribution of
agency types; that is, they do not reflect the adjustment to the HH IPS
baseline that we cited earlier, which caused the HH IPS baseline to
increase to 1.134 from 1.125). In addition, in Table 7, the average
resource cost is not adjusted for wage inflation. If the average
resource cost had been adjusted for wage inflation, there would be an
even larger reduction in resource cost between the HH IPS and HH PPS.)
Table 7.--Average Resource Cost and CMI
----------------------------------------------------------------------------------------------------------------
Average
Period resources CMI admissions CMI all
----------------------------------------------------------------------------------------------------------------
HH IPS:
1999Q4...................................................... $477.06 1.1278 1.0823
2000Q1...................................................... 467.70 1.1074 1.0815
2000Q2...................................................... 466.59 1.1223 1.0982
2000Q3...................................................... 469.52 1.1453 1.1138
HH PPS:
2000Q4...................................................... N/A N/A N/A
2001Q1...................................................... 432.84 1.1841 1.1622
2001Q2...................................................... 440.73 1.1910 1.1774
2001Q3...................................................... 445.59 1.1965 1.1724
2001Q4...................................................... 446.93 1.2003 1.1818
2002Q1...................................................... 452.48 1.2052 1.1800
2002Q2...................................................... 453.89 1.1999 1.1835
2002Q3...................................................... 456.69 1.2099 1.1832
2002Q4...................................................... 460.10 1.2213 1.1957
2003Q1...................................................... 453.74 1.2152 1.1889
2003Q2...................................................... 459.97 1.2295 1.2018
2003Q3...................................................... 458.86 1.2302 1.2002
2003Q4...................................................... 462.59 1.2465 1.2159
----------------------------------------------------------------------------------------------------------------
According to the data in Table 7, in Year 2 (2002) of HH PPS, home
health resources per episode for new admissions were approximately 2
percent lower than they were in the year immediately before
implementation of HH PPS. At the same time, the national case-mix index
for new admissions rose by approximately 0.02 per year. (The national
case-mix index for all episodes, new and continuing, rose by
approximately 0.01 per year.) By Year 3 (2003) of the HH PPS, home
health resources per admission episode rose slightly above the Year 2
level, and then stabilized at levels similar to the HH IPS. The
national CMI for new admissions continued to rise by about 0.02 per
year (with the CMI for all episodes rising by about 0.01 per year).
Therefore, based upon our trend analysis described above, we
believe the change in the case-mix index between the Abt case-mix
sample (a cohort admitted between October 1997 and April 1998) and the
HH IPS period (the 12 months ending September 30, 2000) is due to real
case-mix change. We take this view, even though we understand that
there may be some issue as to whether this period was affected by
nominal case-mix change due to providers' anticipating, in the last
year of HH IPS, the forthcoming case-mix system, with its incentives to
intensify rehabilitation services. This change from these two periods
is from 1.00 to 1.134, an increase of 13.4 percent. However, we are not
proposing to adjust for case-mix change based on this change in values.
However, we are proposing that the 8.7 percent of case-mix change that
occurred between the 12 months ending September 30, 2000 (HH IPS
baseline, CMI=1.134), and the most recent available data from 2003
(CMI=1.233), be considered a nominal change in the CMI that does not
reflect a ``real'' change in case-mix.
In addition to the trend analysis above, we conducted several
additional kinds of analyses of data and documentary materials related
to home health case mix coding change. These analyses are described in
detail in section II.A.3.e. The results support our view that the
change in the CMI since the HH IPS baseline mostly reflects provider
responses to the changes that accompanied the HH PPS, including
particulars of the payment system itself and changes to OASIS reporting
requirements. Our analyses indicated generally modest changes in
overall OASIS health characteristics between the two periods noted
above, a specific pattern of changes in scaled OASIS responses that is
not indicative of material worsening of presenting health status,
various changes in the OASIS reporting instructions that help account
for numerous coding changes we observe, and a large increase in post-
surgical patients with their traditionally lower case-mix index.
Our past experience establishing other prospective payment systems
also led us to believe a proposal to make this adjustment for nominal
change in case-mix is warranted. In other systems, Medicare payments
were almost invariably found to be affected by nominal case-mix change.
We are considering several options for implementing this case-mix
adjustment. These options include incorporating the entire -8.7 percent
adjustment in CY 2008, incorporating an adjustment of -5.0 percent in
CY 2008 and an adjustment of -2.7 percent in CY 2009, and incorporating
an adjustment of -4.35 percent in CY 2008 and an adjustment of -4.35
percent in CY 2009. However, because of the potential impact our
proposed adjustment may have on providers, we are proposing and
requesting comment on whether to adjust for the nominal increase in
national average CMI by gradually reducing the national standardized
60-day episode payment rate over 3 years. During that period we would
continue to update our estimate of nominal case-mix change and adjust
the national standardized 60-day episode payment
[[Page 25395]]
rate accordingly for any nominal change in case-mix that might occur.
We propose to implement a 3-year phase-in of the total downward
adjustment for nominal changes in case-mix by reducing the national
standardized 60-day episode payment rate by 2.75 percent each year up
to and including CY 2010. This annual reduction percent is based on our
current estimate of the nominal change in case-mix that has occurred
between the HH IPS baseline (+0.099) and 2003. However, if, at the time
of publication of the final CY 2008 HH PPS rule, updates of the
national claims data to 2005 indicate that the nominal change in case-
mix between the HH IPS baseline and 2005 is not +0.099, we would revise
the percentage reduction in the next year's update. The revision would
be determined by the ratio of the updated 3-year annual reduction
factor to the previous year's annual reduction factor. For example, the
scheduled annual reduction factor is now estimated to be 0.9725
(equivalent to a 2.75 percent reduction); for CY 2008 we would multiply
this reduction factor by the ratio of the updated reduction factor to
0.9725. For the CY 2010 rule, which governs the third and final year of
the case-mix adjustment transition period, we would obtain the CY 2007
national average CMI to compute the updated value for nominal case-mix
adjustment. Again, we would form the ratio of the updated adjustment
factor to the previous year's effective adjustment factor. The annual
updating procedure avoids a large reduction for the final year of the
phase-in, in the event that the CY 2007 national average case-mix index
reflects continued growth since CY 2005. The calculation of the
adjusted national prospective 60-day episode payment rate for case-mix
and area wage levels is set forth in Sec. 484.220. We are proposing to
revise Sec. 484.220 to address changes to case-mix that are not a real
change in case-mix.
CMS proposes to adjust the national prospective 60-day episode
payment rate to account for the following:
HHA case-mix using a case-mix index to explain the
relative resource utilization of different patients. To address changes
to the case-mix that were a result of changes in the coding or
classification of different units of service that did not reflect real
changes in case-mix, the national prospective 60-day episode payment
rate will be adjusted downward as follows:
--For CY 2008 the adjustment is 2.75 percent.
--For CY 2009 and CY 2010, the adjustment is 2.75 percent in each year.
Geographic differences in wage levels using an appropriate
wage index based on the site of service of the beneficiary.
We plan to continue to monitor changes in the national average CMI
to determine if any adjustment for nominal change in case-mix is
warranted in the future.
Accordingly, based upon our analysis and conclusions, we are
proposing a new set of case-mix weights that reflect the four-equation
model and a payment adjustment for the nominal change in the case-mix
index described above. We arrived at these weights, listed in Table 5,
by first determining relative weights for each of the 153 groups using
the four-equation model and the payment regression. The definition for
each of these groups based on clinical, functional, and service
severity levels is described in Table 5. Each of these relative weights
was adjusted by multiplying it by an adjustment factor to make the
proposed payments budget-neutral to current estimated payments for CY
2008. This budget neutrality factor raised the proposed average case-
mix weight to the case-mix index reflected by the most recent data
available from 2003. The proposed budget-neutrality factor for 2008 is
1.194227193. Each budget neutral, adjusted, weight in Table 5 was
calculated in the following manner: Relative Weight x 1.194227193.
References to literature cited in this section:
N. McCall et al., ``Utilization of Home Health Services before and
after the Balanced Budget Act of 1997: What Were the Initial
Effects?'' Health Services Research, Feb. 2003: 85-106.
MedPac, Report to the Congress: Selected Medicare Issues, June 1999:
105-115.
General Accounting Office (GAO), ``Medicare Home Health Benefit:
Impact of Interim Payment System and Agency Closures on Access to
Services,'' GAO/HEHS-98-238, Sept. 1998.
General Accounting Office (GAO), ``Medicare Home Health Agencies:
Closures Continue, with Little Evidence Beneficiary Access Is
Impaired,'' GAO/HEHS-99-120, May 1999.
B.M. Smith et al., ``An Examination of Medicare Home Health
Services: A Descriptive Study of the Effects of the Balanced Budget
Act Interim Payment System on Access to and Quality of Care,''
Center for Health Services Research and Policy, George Washington
University, Sept. 1999.
3. Description and Analysis of Case-Mix Coding Change under the HH PPS
As stated in section II.A.2.c of this proposed rule, under section
1895(b)(3)(B)(iv) of the Act, we are proposing a reduction in HH PPS
national standardized 60-Day episode payment rate to offset a change in
coding practice that has resulted in significant growth in the national
case-mix index (CMI) since the inception of the HH PPS that is not
related to ``real'' change in case mix. The factor was determined by
calculating the change in the national CMI between the HH IPS and the
HH PPS.
In this section II.A.3, for purposes of illuminating the sources of
CMI increase in terms of the case-mix system itself, we identify the
severity levels with the largest growth between the two periods. We
will provide, in Table 8, the percentage change in volume for each of
the 80 case-mix groups, and summary statistics of the changes. Table 9
shows the rates of all OASIS assessment items in the two time periods.
We will explain below our inferences from Table 9 about the comparative
health status of the populations treated in the two time periods.
Subsequent to that, we will explain our analysis of the changes to
OASIS reporting instructions that were likely to have affected reported
case mix. We also describe analyses we performed to quantify the effect
on the CMI of increases in post-surgical episodes in the national
caseload, and our interpretation of the analyses. We conclude with a
summary and interpretation of our key findings from the descriptive
analysis of OASIS assessment data, analysis of OASIS reporting
instructions, and analysis of changes in post-surgical volume.
In making these analyses, we reviewed data from two samples. The
first, the HH IPS sample, is the same sample used in section II.A.2.c
of this proposed rule for determining the IPS baseline that we used to
determine the proposed adjustment for nominal change in case-mix. The
HH IPS sample is a 1 percent random sample of claims (total number of
18,480) with its matched start of care OASIS assessments from the 12
months immediately preceding HH PPS. We matched the assessments to
determine what the patient's case-mix group would have been had HH PPS
been in effect. To simulate 60-day episodes from actual claims we used
the same method that was used to create the initial development sample
for the HH PPS case-mix system. In performing the simulation, we took
into account the timing of the start of care in relation to previous
service periods, and used only 60-day periods that would have
corresponded to initial episodes in a sequence of adjacent episodes
that consisted of one or more simulated episodes. We considered initial
episodes as the first episodes that follow
[[Page 25396]]
periods of at least 60 days without receiving home health service.
The second sample is a 20 percent sample of FY 2003 claims for
initial episodes again matched to start of care OASIS assessments. In
both samples, we corrected any initial errors in determining the
beneficiary's pre-admission location that affected the HHRG before
determining the HHRG. We made the correction by consulting the sample
member's claims history for information about previous inpatient stays.
a. Change in Case-Mix Group Frequencies
Table 8 presents the share of the population assigned to each
severity level of the case-mix system's three dimensions (clinical,
functional, and service). The table indicates there was a strong shift
away from the lowest-severity case-mix groups towards higher severity
level between the two sample periods. Growth of the two highest
severity levels of the clinical domain was approximately 23 percent;
for every 100 beneficiaries, 8 additional beneficiaries were classified
to the highest two clinical dimensions in 2003 compared to the HH IPS
period.
Growth of the functional severity levels F2 and F3 totaled 12
percent. The 12 percent growth in share was concentrated in F2. Share
growth for F2 and F3 was offset by a decline for the two lowest
functional severity levels and, potentially, a tiny decline in share
for the severest functional level, F4. Notwithstanding the small
decrease in the share assigned to F4, for every hundred beneficiaries,
about 7 additional beneficiaries were classified to the higher severity
levels F2 and F3.
The data also indicate that the proportion of patients with a prior
SNF or rehabilitation facility discharge in the 14 days before
admission, but no hospital discharge in that period, grew by 25 percent
for episodes below the 10-visit therapy threshold, and 64 percent for
episodes above the 10-visit therapy threshold. These patients receive a
higher case-mix score than patients from all other pre-admission
locations on the OASIS (including inpatient discharge).
In addition, the table indicates growth in the high-therapy groups
(levels S2 and S3) of 30 percent. This means that for every hundred
beneficiaries, 8 additional beneficiaries were assigned to receive at
least 10 therapy visits in 2003 compared to the HH IPS period. Under
the HH PPS, approximately 35 percent of patients in their initial
episode received at least 10 therapy visits.
Table 8.--Comparison of Severity Level Prevalence, HH IPS Sample and 2003 HH PPS Sample
----------------------------------------------------------------------------------------------------------------
HH IPS HH PPS 2003
(percent) (percent) Difference
----------------------------------------------------------------------------------------------------------------
All C0................................ Min..................... 29.69 22.07 -7.62
All C1................................ Low..................... 36.49 36.19 -0.31
All C2................................ Mod..................... 28.91 35.50 6.58
All C3................................ High.................... 4.91 6.25 1.34
All F0................................ Min..................... 9.27 6.15 -3.12
All F1................................ Low..................... 28.57 25.40 -3.17
All F2................................ Mod..................... 45.18 51.30 6.12
All F3................................ High.................... 10.39 10.83 0.44
All F4................................ Max..................... 6.60 6.33 -0.27
All S0................................ Min..................... 65.74 55.87 -9.87
All S1................................ Low..................... 7.40 9.22 1.83
All S2................................ Mod..................... 19.94 23.59 3.64
All S3................................ High.................... 6.92 11.32 4.40
----------------------------------------------------------------------------------------------------------------
Table 9 shows the shares of total episodes for the complete set of
80 original case-mix groups, during both the HH IPS and the HH PPS FY
2003. Table 9 also displays each group's case-mix weight. Ten groups
had no change in their share of episodes between the HH IPS period and
the HH PPS period in the table. Of the remaining 70 groups, 38 groups,
slightly more than half, had a larger share of total episodes under HH
PPS than the HH IPS. However, decline in share of total episodes was
associated with minimal or low clinical severity (C0 and C1). Only 8 of
40 groups with moderate (C2) or high (C3) clinical severity had
decrease in their share of episodes under HH PPS, with most of the
remaining moderate or high clinical severity groups having a share
increase. As noted above, growth in functional severity level F2 almost
entirely offset the loss of population from groups F0 and F1. Only
three of 16 groups in the functional severity level F2 experienced a
decline in episode shares, and this was concentrated entirely in the
two lowest clinical severity groups.
We summarized the association between case-mix group severity and
change in episode share by calculating the rate ratio for growth in
episode shares. We sorted the groups by case-mix weight and divided the
groups into the top 40 weights of the 80-group case-mix system and the
remaining 40 weights. The rate ratio was determined by dividing the
growth in total share of the top 40 weights by the growth in total
share for the remaining 40 weights. The groups with the 40 smallest
weights have mostly reductions in episode shares (24 of 40 have
reductions), and the groups with the largest 40 weights have mostly
increases in episode shares (24 of 40 groups). The rate ratio for
positive changes was 1.71, which means that as a group the top 40 case-
mix weights were about 70 percent more likely than the bottom 40 to
have an increase in share of total episodes.
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b. Health Characteristics Reported on the OASIS
To further our understanding of the relative roles of case-mix
change and coding changes that might be responsible for the .0991
increase of the national HHRG CMI, we analyzed the HH IPS and HH PPS
samples' health characteristics, based on the start-of-care OASIS
assessment. We compared the proportion of start-of-care assessments
that had each OASIS characteristic, using data from our HH IPS and HH
PPS 2003 samples. We used the wound-related OASIS data to compute
statistics on changes in numbers of wounds. The results are shown in
Table 10 and discussed below. (Items scored in the HH PPS 80 group
case-mix system are shown in bold.) Table 10: Comparison of rates of
response categories on OASIS Start of Care Assessments, HH IPS Sample
and 2003 HH PPS Sample
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In general, the results showed that health characteristics as
measured by the OASIS items were stable or changed little. Exceptions
to the general findings were indications that the HH PPS population
included:
More post-acute and more post-surgical patients;
More patients that had a recent history of post-acute
institutional care;
More patients with a recent change in medical or treatment
regimen;
More patients in the orthopedic diagnosis group defined
under the PPS system's clinical dimension; and
More patients assessed with dependencies in Activities of
Daily Living (ADLs) and Instrumental Activities of Daily Living (IADLs)
as of 14 days before the assessment. The proportion of patients using
at least 10 therapy visits also rose noticeably.
Otherwise, the rate comparisons of OASIS items are generally
unremarkable. Several measures usually reflective of a more compromised
health status, including ADL limitations, incontinence, pain, short
life expectancy, and diagnosis severity had a somewhat higher rate in
the HH PPS sample than the HH IPS sample.
[[Page 25419]]
However, various physiologic measures and risk factors showed little or
no change, including urinary tract infection, visual and aural
functioning, dyspnea, bowel ostomy, bowel incontinence, obesity,
alcoholism, drug dependence, depressive symptoms, behavioral problem
frequency, use of home oxygen, infusion therapy, and nutritional
therapies. In addition, the probability that a patient used psychiatric
nursing was reduced, from 2 percent to 1 percent.
The current HH PPS case-mix system recognizes four types of
diagnoses for purposes of assigning patients to case-mix groups:
diabetes, orthopedic conditions, neurological conditions, and burns and
trauma. These diagnoses were found to be associated with higher-than-
average resource costs in the original case-mix research. The data in
Table 10 indicate that the share of patients assigned to the four case-
mix diagnosis groups grew by 23 percent. This change was due to an
additional 7 per hundred patients assigned to the orthopedic diagnosis
group, and an additional 2 per hundred assigned to the diabetes
diagnosis group. The share of patients assigned to the neurological
diagnosis group remained unchanged (at 8 per hundred), and the share of
patients assigned to the burns/trauma diagnosis group declined by 2 per
hundred.
There are two important reasons why we believe these changes
reflect mostly nominal, as opposed to real, underlying case-mix change.
First, the notable increase in the proportion of orthopedic diagnoses
is due at least in part to the listing of the diagnosis code for
abnormality of gait in this diagnosis group. The diagnosis code for
abnormality of gait (781.2) is commonly used to indicate that the
primary reason for the home health treatment is rehabilitation services
(for example, physical therapy). Detailed analysis shows that this use
of this code grew by 50 percent between the HH IPS period and the early
years of the HH PPS. We believe agencies had an incentive to use this
code on Medicare claims to support treatment plans that included large
amounts of rehabilitation services. This code could be used even if the
underlying condition was not orthopedic. Second, the decline in burns/
trauma assignment may be due in part to agencies' early confusion about
how to use the ICD-9-CM coding system when a patient has an open wound
not due to an injury. We believe traumatic open wounds were thus
overreported early in HH PPS. However, with educational efforts
initiated by CMS and the home health industry after HH PPS began,
understanding and application of the coding instructions for traumatic
wound diagnoses improved, resulting in a lower, and more accurate, rate
of reported burns/trauma cases, which we believe is now more
representative and not an actual change in case-mix.
Other wound-related items varied in the types of change they
experienced. The basic wound-related item measuring the presence of a
skin disturbance or lesion (M0440) increased by 15 percentage points;
however, this measure is general and covers a broad range of both
clinically significant and insignificant problems. We note the three
detailed series of OASIS items following M0440, that is, surgical
wounds, pressure ulcers, and stasis ulcers, had varying results. The
proportion of patients with pressure ulcers increased from 5.4 percent
to 6.6 percent with more than half of the pressure ulcers at Stage 2.
(Pressure ulcers are staged using four levels, 1 to 4, in order of
increasing severity.) The average number of pressure ulcers per hundred
patients increased from 9.2 to 11.1. Pressure ulcers per 100 persons
with any pressure ulcers were 1.70 in the HH IPS sample and 1.68 in HH
PPS sample. Excluding the approximately 5 percent of pressure ulcers
that were unobservable, the average number of stage 1 and stage 2
pressure ulcers per patient with pressure ulcers did not change; the
number of stage 3 and stage 4 pressure ulcers per patient with pressure
ulcers declined by 13 percent and 27 percent, respectively. In terms of
the overall population, stage 1 and stage 2 pressure ulcers per
beneficiary increased by about 23 percent between the HH IPS and HH
PPS; stage 3 pressure ulcers per beneficiary increased 7 percent; and
stage 4 pressure ulcers decreased by 11 percent. There was no change in
the item measuring the healing status of the most problematic pressure
ulcer.
Review of these data suggest to us that the population of home
health beneficiaries was more likely to include pressure ulcer patients
under HH PPS, that such patients had about the same number of pressure
ulcers per person in both periods, and that the pressure ulcer stage
tended to be of lower severity, on average, under HH PPS compared to
the HH IPS. We note that under OASIS coding policy, there is ``no
reverse staging'' of pressure ulcers, which means that a healed
pressure ulcer could be recorded and contribute to the statistics.
Therefore, because of such policy, from these statistics it is
difficult to draw conclusions about change in the burden of care
related to pressure ulcers under the HH PPS.
We also found little change in numbers of stasis ulcers reported or
their overall seriousness. The proportion of patients with any stasis
ulcers was 3 percent under the HH IPS and 2 percent under HH PPS.
Furthermore, while some patients have more than one stasis ulcer, the
number of stasis ulcers per 100 patients decreased from approximately
5.0 to 4.5. The status of the most problematic stasis ulcer (if any)
did not change. The stasis ulcer decline may be attributable in part to
improved knowledge among agency clinical staff in distinguishing among
different types of ulcers.
Based on the HH IPS and the HH PPS samples, the case-mix of the
population of home health beneficiaries clearly shifted towards more
post-surgical patients, with a possible indication that the average
patient's healing status worsened. The proportion of patients with any
surgical wounds increased from 22.7 percent to 30.0 percent. The number
of surgical wounds per hundred patients increased from 37.4 to 49.2,
due entirely to the increased numbers of post-surgical patients; there
was no change in the estimated average number of surgical wounds per
person with any surgical wound (our estimate assumed patients recorded
as having at least one unobservable surgical wound had only one such
wound). There was a 6 percentage point increase in the probability that
the most problematic surgical wound's healing status would be in an
early stage of healing (indicated on the OASIS by the response category
``early/partial granulation,'' which refers to the type of newly
forming tissue which may be visible in a healing wound), and a 1
percentage point increase in the probability that the wound's healing
status would be ``not healing''. This amounts to a 13 percent increase
in the share of most-problematic surgical wounds assigned to the two
less-favorable healing categories, early and partial granulation or not
healing.
Our review of current functional measures also showed mixed
results, with some (grooming, upper body dressing, meal preparation,
laundry, telephone use, independence with inhalant, and injective
medications) exhibiting minor or little change. Other measures
experienced negative and sometimes substantial change (transferring,
ambulation, feeding, and housekeeping). In both the HH IPS and the HH
PPS sample periods, prior functional measures were almost invariably
reflective of a better average prior status (as of the 14 days before
the assessment) compared to the current status. However, in the HH PPS
sample,
[[Page 25420]]
the overall difference between prior and current status is less than in
the HH IPS sample. In other words, average current status is reported
as generally more functionally impaired under HH PPS than under the HH
IPS, and accordingly, average prior status reflects a different
relationship to current status in the two sample periods. We believe
this pattern may reflect better understanding of the definition and
interpretation of the prior status items as agencies became more
familiar with the assessment.
We also found that quite a few items with scaled responses
indicated a decline in the numbers of patients at the best end of the
scale (for example, independent in bathing), as well as a decline or
stability in the numbers (usually very small numbers) at the worst end
of the scale (for example, totally dependent in bathing). Often, the
decline in numbers of patients at the best end was offset by increased
numbers rated just below the best end of the scale. This pattern was
evident with measures of primary and secondary diagnosis symptom
severity, cognitive functioning, confusion, hearing, speech, current
upper and lower body dressing, current bathing, current toileting,
current transferring, current ambulation, and several of the prior
function-related items.
Table 10 results indicated a pattern of change in functional
severity away from the two lowest severity groups and towards the
middle severity group. The shift towards the middle severity group
could be explainable by seemingly minimal changes in a person's ADL
ratings. The examples below show how an incremental change in reported
dependency on a single functional item in the HHRG system could change
the case-mix group functional severity to F2 from F1. For a
hypothetical individual in the second-lowest functional severity group
(F1), a single added limitation (that is, going from independence to a
minimal limitation) could result in the individual moving from severity
category F1 into severity category F2. Similarly, in the case of
transferring or locomotion, a score change that is due only to going
from one level of limitation to the next worst level could possibly
result in the individual moving from severity category F1 into severity
category F2.
The three prognosis-related items also showed mixed results, with
the overall and rehabilitative prognosis items changing minimally and
the life expectancy item indicating a more than two-fold increase in
the proportion of the population of home health beneficiaries with a
life expectancy below 6 months. We believe that as agencies
increasingly recognized that the life expectancy item was used in
measuring adverse events under the Outcome-based Quality Improvement
(OBQM) system, which commenced in the early years of HH PPS, agencies
became more careful to record the prognosis accurately.
We discuss below some of the influences on the reporting of the
OASIS health characteristics since the HH PPS began. Our conclusion
from review of the changes in rates of OASIS characteristics, however,
is that it is far from certain that the essential health status and
service needs of the population of home health beneficiaries changed
dramatically under the HH PPS. A very substantial majority of the OASIS
characteristics rates noted for 2003 in Table 10 were within 2
percentage points of their initial value at the HH IPS baseline. Also,
few OASIS items experienced more than moderate adverse change. Included
within our analysis of adverse changes were several items unrelated to
the HHRG system, including diagnosis symptom severity, recent regimen
or treatment change, feeding, housekeeping, laundry, life expectancy,
and various prior functional status items. Items with adverse change
that are related to the HHRG system include use of post-acute
institutional care, orthopedic cases, incontinence, pain, surgical
wound healing status, and transferring.
c. Impact of the Context of OASIS Reporting
As noted above, some items with adverse changes are related to the
HHRG system. We believe that some of these changes are a likely result
of more care being taken in conducting the assessment. Agencies were
exposed to OASIS training and educational initiatives in the early HH
PPS period and, beginning with the HH PPS, agencies had an incentive to
ensure they did not overlook items that could affect the HHRG. The new
emphasis on proper application of OASIS guidelines was later reinforced
when CMS began to implement outcome-based quality reporting (OBQI) in
early 2002.
We further believe that, to some extent, incentives brought by the
payment and quality program changes interacted with the subjective
aspects of the assessment process to cause nominal coding change. The
process of coding, especially diagnosis coding and determining certain
rating scales, entails some discretion by the agency. With diagnosis
coding, patients may have more than one diagnosis that can reasonably
be called the primary diagnosis. The significant growth in orthopedic
diagnosis codes partly reflects the ambiguity in the diagnosis
assignment process itself, particularly in the context of a system
where financial incentives to choose one diagnosis over another may be
operating. Furthermore, scales of ADL functioning can be difficult to
apply with some patients because of daily variability in their status
and the multiple dimensions of the functional item. This difficulty may
also result in a bias towards selecting a more-severe rating in the
context of the financial incentives of the HH PPS. We believe that such
bias was likely reinforced by the financial incentive created by the
10-visit therapy threshold. As a result of that incentive, high-therapy
treatment plans became more common under HH PPS. OASIS coding practices
regarding ``functional status'' could have changed in ways to make
coding more harmonious with the new emphasis on therapy in treatment
plans.
Not only is the process of coding likely subject to discretion,
several issuances providing official guidance on specific OASIS items
released early in the HH PPS could have caused some clinicians to
downgrade patients in their assessment of the specific item.
Instructions regarding the dressing, bathing, toileting, transferring,
and locomotion items, assessment items all used in the HH PPS case-mix
system, were amended in August 2000 in such a way that the concept of
performing the function safely was highlighted prominently in the item-
by-item instructions. (See M0650 to M0700 in Chapter 8 at http://www.cms.hhs.gov/apps/hha/usermanu.asp
).
This change alone arguably emphasized the concept that ``safety''
is a consideration in assessing the patient's ability to perform the
activity and in determining the functional item on the OASIS. Thus, it
seems a likely contributing factor in explaining why the OASIS data in
Table 10 show a strong tendency for several ADL statistics to shift
away from the completely independent level. In terms of impact on the
patient's case-mix group, it should be noted that the case-mix score
for most of these items becomes a positive value if the assessing
clinician selects any response category other than the one indicating
that the patient is able to function independently. (Note: Selecting
``unknown'' does not add to the case-mix score.)
Another change in OASIS instructions affected the pain item, M0420,
in August 2000. The section on Assessment Strategies offered additional
strategies for assessing pain in a
[[Page 25421]]
nonverbal patient, such as facial expression and physiological
indicators (for example, perspiration, pallor). If many clinicians were
not using these strategies during the HH IPS period, it is likely that
fewer patients would have been assessed to have pain. The strategies
section also introduced the term ``well controlled'' in referring to
pain assessment, by adding the following sentence: ``Pain that is well
controlled with treatment may not interfere with activity or movement
at all.'' If, as a result of this guidance, clinicians began taking
into account patient adherence to pain medication, one result could
have been more patients were assessed with pain. Adherence to pain
medication is an important issue in medicine, because many patients
experience side effects that may cause them to trade off pain control
for diminution of side effects.
The assessment instructions for incontinence were also amended in
August 2000. The Assessment Strategies section for M0520 included a new
statement: ``Urinary incontinence may result from multiple causes,
including physiologic reasons, cognitive impairments, or mobility
problems.'' This clarification could have potentially sensitized
clinicians to the idea that the definition of incontinence is not
simply about physiologic status (that is, bladder control), but instead
involves considerations such as mobility and cognition that can
intervene to produce wetting on clothing. Because more patients were
assessed as incontinent in the HH PPS period according to M0520 (which
is not used in the case-mix system), the OASIS skip pattern drew more
responses for M0530, the case-mix item used to assess the type of
incontinence. A similar change in the Assessment Strategies section was
made for M0540, bowel incontinence, with the potentially similar impact
of increasing the reported rate.
Finally, two changes to the OASIS manual in August 2000 could have
expanded the number of patients reported to have surgical wounds. The
first change affecting surgical wounds was to expand the definition to
read: ``Medi-port sites and other implanted infusion devices or venous
access devices are considered surgical wounds.'' The possible impact on
the national case-mix index of broadening this instruction is that more
openings in the skin would be considered surgical wounds, requiring
more assessments to respond to OASIS item M0488, a case-mix variable,
provided that the site is the most problematic surgical wound under the
expanded definition. It is possible for the healing status of these
types of openings to be ``fully granulating'' (with no case-mix score
available), at a stage of ``early or partial granulation'' (a score of
7), or even ``not healing'' (a score of 15). For example, a central
line site being held open by the line itself may not reach a fully
granulating state, or a site that has become infected may be assessable
as ``not healing.'' Before these clarifications, it may not have
occurred to many assessing clinicians to classify these device-related
sites as surgical wounds, so it seems reasonable to assume that more
surgical wounds would be reported after the manual change, and to
assume that some of these would add to the higher rates of wounds
reported to be not healing or in early healing stages.
The second manual change was a new bulleted item in the OASIS
response-specific instructions: ``A muscle flap performed to surgically
replace a pressure ulcer is a surgical wound and is no longer a
pressure ulcer.'' We note it is not uncommon for home health patients
to be admitted after hospitalization for pressure ulcer procedures,
such as debridements or grafts. While the OASIS manual change noted
that debridements do not change the classification of the pressure
ulcer to a surgical wound, the muscle flap does change the
classification. Again, we would expect this technical clarification to
have added to the reported number of surgical wounds.
Another OASIS manual change added the statement that ``A PICC line
is not a surgical wound, as it is peripherally inserted, although it is
considered a skin lesion (see M0440).'' The PICC line is a common
method of delivering antibiotic treatment intravenously at home.
However, using the same reasoning about the perception of device-
related openings before the issuance of the August 2000 manual, we
believe it is unlikely that the peripherally inserted central catheters
(PICC) line clarification caused reduction in reported surgical wounds
as it would not have originally occurred to many assessing clinicians
to have classified it as such in the first place.
The changes to the OASIS manual instructions noted in this section
present concrete potential causes of increased OASIS reporting rates
for case-mix items measuring ADL dependencies, pain, incontinence, and
surgical wounds. While it is difficult to know with data available how
much of the reported increase is traceable to these clarifications, we
believe that in the environment at the time the HH PPS was initiated,
which included strong efforts in the public and private sectors to
educate home health agencies on the proper application of OASIS, the
changes must have had some impact. To the extent that the result was a
new approach to classifying patients for purposes of the OASIS items
involved, we note the increased item reporting rates may not represent
an actual material change in the health status of the population under
treatment in home care. Given the potential impact of OASIS reporting
instructions on case-mix, we will continue to monitor appropriate
requirements in an effort to promote effectiveness in the HH PPS
payment methodology. Clarifications to the ``OASIS Implementation
Manual'' are issued administratively through normal operating
procedures.
Impact of more post-surgical patients
We also reviewed the increase in rates of post-surgical patients
that occurred under the HH PPS to improve our understanding of how this
increase contributed to the growth in the case-mix index between the
IPS baseline and the 2003 HH PPS period. Being a patient with a
surgical wound does not in and of itself increase the case-mix score.
However, if the surgical wound is not assigned to the best healing
status on the OASIS assessment, the score will increase. Therefore, an
increase in the proportion of post-surgical patients makes more
episodes eligible for an addition to the score based on the healing
status. Furthermore, data shown in Table 10 indicate that under the HH
PPS, post-surgical patients were more likely to be assessed with a
healing status that impacts upon a case-mix score. Because surgical
patients have historically had other characteristics associated with
relatively low resource use, we hypothesized that a higher occurrence
of surgical wound patients would not necessarily lead to a rise in the
overall CMI.
We analyzed the extent to which the severity of HHRG-related OASIS
items is due to the increased presence of post-surgical patients, of
whom many would have mobility restrictions, pain, and an evolving
surgical wound status in the early post-acute phase. First, we analyzed
the relationship between having a surgical wound and having a
characteristic indicative of increased severity. Second, we
recalculated the average case-mix change under two alternative
assumptions: (1) The higher share of post-surgical cases is entirely
responsible for the changed CMI; (2) growth in the CMI for post-
surgical patients was the same as growth in the CMI for non-surgical
patients. The second assumption would reveal the potential effect of a
faster worsening of
[[Page 25422]]
presenting health status through time among post-surgical patients
compared to non-surgical patients.
As expected, post-surgical patients exhibited certain
characteristics at different rates. Specifically, compared to non-
surgical patients, they were slightly less likely to have no home
therapies (M0250), about 40 percent more likely to have frequent pain
(M0420), nearly three times as likely to have a bowel ostomy, nearly
twice as likely to have come from an inpatient rehabilitation facility
and to have intractable pain, and 15 percent less likely to be
independent in lower body dressing. Many other characteristics were
less prevalent among post-surgical patients, such as having any
pressure or stasis ulcers; dyspnea; urinary and bowel incontinence;
behavioral problems (M0610); upper body dressing, toileting, and
ambulation functional limitations.
If we make the first assumption, that the only cause of change in
the national CMI under the HH PPS was the increased share of post-
surgical patients in the population of home health users, then the
national case-mix under the HH PPS sample should have been slightly
below the CMI of the HH IPS sample. This is because the CMI for post-
surgical patients is smaller than the CMI for non-surgical patients,
and because even under the HH PPS the share of post-surgical patients
is a minority of all patients. However, in actuality, as stated in
section II.A.2.b of this proposed rule, the national CMI increased by
0.099 between the HH IPS sample and the 2003 HH PPS sample.
Post-surgical patients' CMI grew slightly faster than non-surgical
patients' CMI over this period. This may represent a change in the mix
of post-surgical patients, or it may represent stronger effects of
changed coding practices on post-surgical patients than on non-surgical
patients. If we make the second assumption--that the growth rate of
post-surgical patients' case mix was the same as the growth rate of
non-surgical patients' case mix--then the increase in the national CMI
should have been marginally smaller than 0.099 (smaller by about one-
half of 1 percent). Because our second assumption caused a very small
reduction in the CMI increase, we conclude that only a very small
portion of the substantial growth in CMI might be attributable to
having more severe surgical patients under HH PPS compared to HH IPS.
We believe one possible contributing factor in the slightly faster
growth in the CMI for surgical patients was uncertainty about how to
assess the healing status of a surgical wound. As noted above, twice as
many surgical wounds judged ``most problematic'' were assigned a status
of ``not healing'' under the HH PPS than under the HH IPS. Fifty
percent more surgical wounds were assigned a status of ``early and
partial granulation,'' under the HH PPS. A recent clarification in the
guidance for assessing healing status is significant, we believe, in
understanding this change. In July 2006 the Wound Ostomy and Continence
Nurses Society (WOCN), a national source of expertise in wound
assessment, and one that CMS encouraged agencies to consult, issued a
change in guidance on surgical wound assessment. Before that time,
criteria for a status of ``non-healing'' in a wound closed by primary
intention were the following: ``incisional separation OR incisional
necrosis OR signs or symptoms of infection OR no palpable healing
ridge'' (WOCN Society OASIS Guidance Document--Spring 2001). Criteria
for a status of ``fully granulating/healing'' were: ``incision well-
approximated with complete epithelialization of incision; no signs or
symptoms of infection; healing ridge well-defined.'' The July 2006
revision removed all references to a ``healing ridge'' due to the lack
of scientific evidence supporting its use as a sign of wound healing.
Many surgical wounds will not exhibit a healing ridge, though the wound
is actually healing. To the extent that assessing clinicians paid
heightened attention to the now-outdated WOCN guidance in adapting to
the HH PPS, it is likely that they applied the pre-2006 criteria, with
the result that the national OASIS rate for the healing status of
surgical wounds indicated more wounds ``not healing'' or at a stage of
``early and partial granulation.''
In summary, based upon our above discussion of review of the data
on OASIS items and our discussion of reasons for coding change, we
conclude that growth in the national average CMI reflects, to a very
large extent, coding practice changes against a background of new
financial incentives. The impact of these forces is evidenced by mostly
incremental changes in home health population rates of case-mix
relevant items and not to actual changes in health status. Other than
the increase in reported numbers of surgical wound patients, changes in
numbers and characteristics of wound care patients documented on the
OASIS were modest. While there was substantially more use of aggressive
treatment plans involving at least 10 therapy visits, the pattern of
decline in many ADL, IADL and other scale ratings is suggestive of
added numbers of marginally limited patients, not severely limited
patients. Moreover, scale ratings for ADL measures, an important part
of the case-mix system, were likely affected by the manual changes
noted above emphasizing that safety is a consideration in determining
the rating. Lastly, we found that the higher rate of reported post-
surgical patients does not contribute to CMI change. Accordingly, as
noted previously, we are proposing to adjust the national standardized
60-day episode payment amount to reflect the nominal change in the CMI.
4. Partial Episode Payment Adjustment (PEP Adjustment) Review
In our July 3, 2000 final rule (65 FR 41128), we described a PEP
adjustment under the PPS. The PEP adjustment provides a simplified
approach to the episode definition and accounts for key intervening
events in a patient's care defined as a beneficiary elected transfer,
or a discharge and return to the same HHA that warrants a new start of
care for payment purposes, OASIS, and physician certification of the
new plan of care. When a new 60-day episode begins, the original
national standardized 60-day episode payment rate is proportionally
adjusted to reflect the length of time the beneficiary remained under
the agency's care before the intervening event. The proportional
payment is the PEP adjustment.
The PEP-adjusted episode is paid based on the span of days
including start of care date or first billable service date through and
including the last billable service date under the original plan of
care before the intervening event. The PEP-adjusted payment is
calculated by using the span of days (first billable service date
through the last billable service date) under the original plan of care
as a proportion of 60. The proportion is then multiplied by the
original case-mix and wage-adjusted national standardized 60-day
episode payment rate. This method of proration in relation to the span
of days between the first and last billable service date assumes that
the rate of visits through time is constant during the episode period.
Since the July 2000 final rule, we have received comments and
correspondence pertaining to the PEP adjustment. These have guided our
research efforts since the HH PPS has been in place. Through a contract
with Abt Associates, descriptive analysis has been conducted on a large
sample of claims linked to OASIS assessments from the first 3 years of
the HH PPS in an effort to better understand the patient
characteristics associated with PEP-adjusted episodes and the
circumstances under which PEP-
[[Page 25423]]
adjusted episodes occur. Analysis of patient characteristics revealed
no appreciable differences between patients in normal episodes and
patients in PEP episodes with regard to conditions or clinical
characteristics. (Normal episodes are defined as home health episodes
of care that are not subject to any of the payment systems adjustments
(for instance, LUPAs, PEPs, SCICs).) The mix of visits for PEP episodes
is similar to that of normal episodes.
Additionally, analysis of a 20 percent sample of 2003 episodes
showed that approximately 3 percent of all episodes were PEP-adjusted.
Of those, three types of PEP-adjusted episodes were identified:
approximately 55 percent of PEP-adjusted episodes involved a discharge
and return to the same HHA; about 42 percent involved transfers to
other agencies; and approximately 3 percent involved a move to managed
care. Regarding the circumstances under which PEP-adjusted episodes
occur, analysis showed the incidence of inpatient utilization during
the 60 days following the first day of a PEP-adjusted episode was 14.5
percent which is lower than the incidence during normal episodes (21.4
percent). The lower incidence of hospitalizations for patients with
PEP-adjusted episodes may indicate that these patients are in better
health than the average home health patient. Along with the patient
characteristics we examined, this seems to suggest that patients
experiencing PEP episodes are not necessarily very different from the
overall population of home health beneficiaries.
As part of our research efforts, we also examined the different
components that make up PEP episodes. Our analysis showed that PEP-
adjusted episodes have significantly shorter service periods on average
(approximately 23.4 days) than all episodes other than LUPAs and SCIC
episodes (42.0 days). The average of 23.4 days was calculated by
dividing PEP episodes into their four components. The number of days
between the start of the episode and the first billable visit averaged
0.2 days, or 0.4 percent of a full 60-day episode. The paid days, or
the days between the first billable and last billable visit days,
averaged 23.4 days or 38.9 percent of a full 60-day episode. The number
of days between last billable visit to the new episode from-date
averaged 17.9 days, or 29.9 percent of a full 60-day episode. Finally,
the number of days between the from-date of the new episode from-date
to the first episode's original day 60 averaged 18.5 days or 30.8
percent of a full 60-day episode. Under the current system, payment for
a PEP episode is adjusted to reflect the paid days only (23.4 days on
average).
We further examined the number of visits that occurred during PEP
episodes. We found that an average of 13.8 visits occur during PEP
episodes. We recognize that this average represents 75 percent of the
average number of visits for normal episodes, while the number of paid
days represents less than 40 percent of the normal 60-day episode.
Thus, the average proration fraction is about 40 percent of the normal
episode payment while the number of visits is approximately 75 percent
of the number delivered during the average normal episode.
Additionally, the average number of minutes per visit during a PEP
episode is slightly longer than that of a normal episode for most types
of visits. Both results provide evidence that there is some front-
loading of visits compared to normal episodes, causing PEP episodes to
have a faster average rate of visits during the span of days used to
prorate the episode payment. Because the PEP adjustment proration
methodology does not take visit occurrence into account, commenters
have argued that, PEP episodes appear to be systematically
``underpaid''.
As we described in the July 3, 2000 final rule, the decision to use
the span of billable visit dates was made because of the HHA's
involvement in decisions influencing the intervening events for a
beneficiary who elected transfer or discharge and returned to the same
HHA during the same 60-day episode period. Agencies have some
flexibility in discharge decisions that affect the likelihood of
incurring a partial episode, whether or not a hospital stay intervenes.
They also have indirect influence on a beneficiary's decision to
transfer to another home care provider through the quality of care they
provide. Current data suggest that PEP episodes are rare and,
therefore, the current PEP policy may be serving as a deterrent to
premature discharge. We believe that the PEP adjustment is provided in
a manner that maintains the opportunity for Medicare patients to choose
the provider with which they feel most comfortable. Therefore, we are
proposing that the current system of proportional payments based on
billable visit dates continue to be the payment methodology for PEP
episodes. It should also be noted that in many cases, an HHA receives
payment for an additional full episode which it might not have received
had the first episode not been subject to a PEP adjustment. We will
continue to research the nature of HHA resource use during and
following PEP episodes, as well as explore alternative methodologies
for payment adjustment.
At this time, our analysis of PEP episodes does not suggest a more
appropriate alternative payment policy. We believe that many
alternative proration rules that we could devise would likely introduce
adverse incentives into the HH PPS. For example, a proposal to pay PEP
episodes amounts proportional to the average visit accrual rate we
observe for PEP episodes would provide agencies with a financial
incentive to reduce visits in the first few weeks of the episode and/or
to time the date discharge in relation to the new, prorated schedule of
payments. For many types of patients, such a delivery pattern would
likely worsen patient outcomes. We would like to solicit suggestions
and comments from the public on this matter to guide our continued
efforts to improve the PEP adjustment policy.
5. Low-Utilization Payment Adjustment (LUPA) Review
In our July 3, 2000 final rule (65 FR 4117), we described a low-
utilization payment to be implemented under the HH PPS. The LUPA was
established to reduce the national standardized 60-day episode payment
rate regardless if the episode is adjusted as a PEP adjustment or SCIC
adjustment when minimal services are provided during a 60-day episode.
LUPAs are episodes with four or fewer visits. Payments under a LUPA
episode are made on a per-visit basis by discipline. For the July 2000
final rule, the per-visit rates were determined from the audited cost
report sample we used to design the HH PPS. (The same rates were used
in calculating the standard episode amount.)
The per-visit amounts include payment for (1) Non-routine medical
supplies (NRS) paid under a home health plan of care, (2) NRS possibly
unbundled to Part B, and (3) a per-visit ongoing OASIS reporting
adjustment as discussed in the July 3, 2000 final rule (65 FR 41180).
The LUPA payment rates are not case-mix adjusted. As discussed in the
July 3, 2000 HH PPS final rule, a standardization factor used to adjust
the LUPAs was calculated using national claims data for episodes
containing four or fewer visits. This standardization factor includes
adjustments only for the wage index.
The per-visit rates originally listed in the July 2000 rule have
been updated in the same manner as the standard episode amount.
Additionally, the payments are adjusted by the wage index in the same
manner as the standard episode amount.
[[Page 25424]]
As part of our ongoing research of the HH PPS and to analyze the
general appropriateness of an adjustment for low-utilization episodes,
Abt Associates analyzed a 20 percent sample of home health episodes
covering more than three years of experience under the HH PPS. The
analysis file was the Fu Associates analytical file linking OASIS with
home health claims. This allowed the grouping of LUPAs into categories
for analysis of patient characteristics. There were approximately
179,845 LUPA episodes in this file, accounting for approximately 13
percent of episodes.
The analysis revealed minor differences between patients in LUPA
episodes and patients in normal episodes. Although, overall, patients
in LUPA episodes on average had somewhat lower clinical and functional
severity, a substantial number of patients were in high severity
groups. LUPA episodes were also just as likely as normal episodes to
include a hospital stay during the 60-day episode. We believe that some
LUPAs result from the hospitalization of the patient before a
significant number of visits have been delivered.
One indication from these data is that LUPAs are serving as a low-
end outlier payment for certain episodes that incur unexpectedly low
costs. Other LUPAs result from expected care patterns for patients with
conditions such as neurogenic bladder and pernicious anemia. The
incidence of LUPAs has changed little since the HH PPS began, which
suggests that LUPA episodes are not excessively vulnerable to
incentives to manipulate care plans for payment purposes. However, we
continue to believe that the distinction between LUPAs and full
episodes requires sustained monitoring through medical review and other
activities. Further, we are aware of the potential for inappropriate
admissions into LUPA episodes among patients with questionable medical
necessity for home health care.
Since the HH PPS went into effect, we have received comments and
correspondence pertaining to the LUPA policy. In particular, these have
focused on the suggestion that LUPA payment rates do not adequately
account for the front-loading of costs in an episode. Further,
commenters suggested that because of the small number of visits in a
LUPA episode, HHAs have little opportunity to spread the costs of
lengthy initial visits over a full episode. CMS has also received
comments regarding the appropriateness of the 4-visit threshold for
LUPAs. CMS is not proposing to modify the 4-visit threshold for LUPA
episodes in this proposed rule. We did look at, and consider, the 4-
visit threshold and possible alternatives to that threshold in our
analysis of LUPA episodes. Increasing the 4-visit threshold to some
number greater than 4 would result in a HH PPS in which we have an even
greater percentage of LUPA, which are per-visit reimbursed episodes and
could be interpreted as a move closer toward a per-visit payment
system. This is not the direction we want to go with a bundled
prospective payment system as is the HH PPS. Conversely, decreasing the
4-visit threshold to some number less than 4 would result in an
overpayment of episodes, in that episodes with 4 visits would then
receive a full episode payment. As a result, we have concentrated our
efforts to address the payment of certain types of LUPA episodes, in
particular, LUPA episodes occurring as the only episode and
circumstances where a LUPA episode is the initial episode in a sequence
of adjacent episodes.
To examine this assertion, Abt Associates conducted a descriptive
analysis of LUPA episodes. Of particular interest are the findings
pertaining to the average visit length of LUPAs occurring in the
initial episode of a sequence of adjacent episodes or occurring as the
only episode (constituting approximately 59 percent of all LUPA
episodes). An examination of visit log data predating the HH PPS, used
for the original Abt case-mix study (July 2000 Final Rule), revealed
that the average visit length for nursing for an initial assessment is,
on average, twice as long as the length for other nursing visits.
Likewise, an initial assessment visit made by a physical therapist
averaged 25 percent more than other physical therapy visits. These
estimates paralleled findings from a 2001 Government Accountability
Office (GAO) study that reported that the OASIS added an average of 40
minutes to a typical start of care visit. We found that the average
visit lengths in initial and only episode LUPAs are 16 to 18 percent
higher than the average visit length in initial non-LUPA episodes. In
comparison, the average visit length for LUPA episodes that occurred
between initial and ending episodes in a sequence of adjacent episodes
(approximately 24 percent of all LUPAs) or at the end of a sequence of
adjacent episodes (approximately 17 percent of all LUPAs) is less than
or about equal to average visit lengths for corresponding non-LUPA
episodes.
The results of this data analysis suggest that initial and only
episode LUPAs require longer visits, on average, than non-LUPA
episodes, and that the longer average visit length is due to the start
of care visit, when the case is opened and the initial assessment takes
place. We agree with commenters to the extent that these analyses of
initial and only episode LUPA episodes indicate that payments for such
episodes may not offset the full cost of initial visits. This is likely
due to the fact that the LUPA per-visit payment rates were originally
set based on the costs of an average visit, not the costs of the subset
of visits incurred by patients receiving four or fewer visits during an
initial or only episode LUPA; for these patients, a large share of
total visits comprises initial visits. However, the comparisons of
average minutes per visit for LUPA episodes occurring within or at the
end of a sequence of episodes do not support a proposal for payment
increases for those types of LUPAs.
Based upon our initial review that initial or only episode LUPAs
may not reflect the full costs incurred for the visits delivered, we
then conducted further analysis to determine an appropriate payment
increase for initial or only episode LUPAs. Analyzing a 10 percent
sample of 2003 episodes, we found that 75 percent of LUPA episodes
involved nursing without physical therapy while 15 percent of LUPAs
involved physical therapy without skilled nursing. Almost all of the
remaining 10 percent of episodes involved a mix of physical therapy and
skilled nursing. Although the discipline that delivered the initial
visit may not be identified in the sample file, for deriving payment
rates based upon our analysis noted above, we have assumed the share of
initial assessment visits from skilled nursing is 80 percent and the
share of initial assessment visits from physical therapy is 20 percent.
We then used these percentages to calculate the estimated value of 40
minutes added to the initial visit for start of care episodes. We
relied upon the GAO report noted above, as the basis for the estimate
of 40 minutes. For this calculation, we multiplied the current per-
visit rate by the percentage increase in the average visit length. The
average visit length was calculated from all non-LUPA episodes in the
Abt sample file. Specifically, we multiplied, for the value of extra
skilled nursing visits, the LUPA base rate of $105.07 for skilled
nursing (trended forward from the original rate of $98.85) by the
percentage over average skilled nursing visit length (0.860215) and by
the share of initial assessment visits from skilled nursing (0.80). The
product was $72.31. Next, we multiplied, for the value of
[[Page 25425]]
extra physical therapy minutes, the LUPA base rate of $114.89 for
physical therapy (trended forward to CY 2008 from the original rate of
$108.08) by the percentage over average physical therapy visit length
(0.858369) and by the share of initial assessment visits from physical
therapy (0.20). The product was $19.72. Finally, we summed these
weighted values to calculate a total average value of $92.03 ($72.31 +
$19.72 = $92.03).
In the July 3, 2000, HH PPS final rule (65 FR 41187), we adjusted
the per-visit rate by 1.05 to account for outlier payments. Therefore,
we are proposing to multiply the $92.03 by 1.05 and then reduce this
amount to account for the estimated percentage of outlier payments as a
result of the current FDL ratio of 0.67 (see section II.A.8. of this
proposed regulation), resulting in an amount of $92.63.
Given the findings from the descriptive analysis of LUPA episodes
and total average value of excess visit length for initial visits in
certain LUPA episodes, we propose an increase of $92.63 for LUPA
episodes that occur as the only episode or the initial episode during a
sequence of adjacent episodes. Again, as defined in section II.A.2 of
this proposed rule, a sequence of adjacent episodes is defined as a
series of claims with no more than 60 days between the end of one
episode and the beginning of the next episode (except for episodes that
have been PEP-adjusted). In Sec. 484.230, we are proposing to add a
third, fourth, and fifth sentence after the second sentence to define
the term ``sequence of adjacent episodes'' for the purpose of
identifying situations where the LUPA is the beneficiary's only episode
or the initial episode in a sequence of adjacent episodes. We propose
to pay an additional low-utilization payment adjustment LUPA episodes
which are either the only episode or the initial episode in a sequence
of adjacent episodes, and note the additional payment for such LUPA
episodes will be updated annually by the home health market basket
percentage increase. As with the other components of the LUPA
methodology, this increase for situations where a LUPA is the only
episode or the initial episode in a sequence of adjacent episodes will
be wage-adjusted. We believe this increase allows HHAs fair
compensation for the cost of lengthier start of care visits in LUPA
episodes. To maintain budget neutrality, we further propose that the
national standardized 60-day episode payment rate be reduced. We
determined the budget neutral national standardized 60-day episode
payment rate that compensates for the extra payment of $92.63, as well
as for other proposed changes in this proposed rule, from simulating
the new payment system on our 2003 claims sample. The results are shown
in the section II. D.
We are soliciting comments on our methodology for arriving at an
adjustment to achieve fair compensation for the cost of lengthier start
of care visits in LUPA episodes. An alternative methodology is basing
the estimated additional time on claims-based reports of lengths of the
first visit in initial and only episode LUPAs. We expect to test the
adequacy of such an alternative methodology using a large,
representative CY 2005 claims sample that would be available before the
final rule. We are specifically soliciting comments on alternative
methodologies.
6. Significant Change in Condition (SCIC) Review
The SCIC adjustment occurs when a beneficiary experiences a SCIC
during the 60-day episode that was not envisioned in the original plan
of care. In our final rule published July 3, 2000 in the Federal
Register (65 FR 41128), we established the SCIC adjustment to be the
proportional payment adjustment reflecting the time both before and
after the patient experienced a SCIC during the 60-day episode. In
order to receive a new case-mix assignment for purposes of SCIC payment
during the 60-day episode, the HHA must complete an OASIS and obtain
the necessary physician orders reflecting the significant change in
treatment in the patient's plan of care.
Currently, the SCIC adjustment is calculated in two parts. The
first part of the SCIC adjustment reflects the adjustment to the level
of payment before the significant change in the patient's condition
during the 60-day episode. The second part of the SCIC adjustment
reflects the adjustment to the level of payment after the significant
change in the patient's condition occurs during the 60-day episode.
The first part of the SCIC adjustment is determined by taking the
span of days (first billable service date through the last billable
service date) before the patient's SCIC as a proportion of 60
multiplied by the original episode payment amount. The original episode
payment level is proportionally adjusted using the span of time the
patient was under the care of the HHA before the SCIC that required an
OASIS, physician orders indicating the need for a change in the
treatment plan, and the new case-mix assignment for the remainder of
the 60-day episode.
The second part of the SCIC adjustment reflects the time the
patient is under the care of the HHA after the patient experienced a
SCIC during the 60-day episode that required the new case-mix
assignment. The second part of the SCIC adjustment is a proportional
payment adjustment reflecting the time the patient will be under the
care of the HHA after the SCIC and continuing until another significant
change or until the end of the 60-day episode. Once the HHA completes
the OASIS, determines the new case-mix assignment, and obtains the
necessary physician change orders reflecting the need for a new course
of treatment, the second part of the SCIC adjustment begins. The second
part of the SCIC adjustment is determined by taking the span of days
(first billable service date through the last billable service date)
after the patient experiences the SCIC through the balance of the 60-
day episode (or until the next significant change, if any) as a
proportion of 60 multiplied by the new episode payment level resulting
from the significant change.
Since we proposed the SCIC adjustment in October 1999 (64 FR
58134), we have received comments and correspondence regarding the
appropriateness and the complexity of the SCIC adjustment methodology.
These suggestions expressed concerns that SCIC adjustments may be
difficult to apply appropriately. Additionally, analysis of HHA margins
using a sample of approximately 2,500 cost reports suggested that SCIC
episodes did not necessarily account for the cost associated with a
patient in a SCIC episode. These concerns guided our descriptive
analysis of SCIC episodes and our investigation of possible
alternatives to SCIC adjustment.
The SCIC policy was designed and implemented primarily to protect
HHAs from receiving a lower, inadequate payment for a patient that
unexpectedly got worse and became more expensive to the agency during
the course of a 60-day episode. While it is also possible that a
patient could become unexpectedly better, resulting in a patient
needing far fewer resources and costing the agency less, such instances
were expected to be few. For patients who experienced an unexpected
adverse significant change in condition, but the agency would actually
receive lower payments when applying the computation for deriving a
SCIC payment, agencies were instructed that they did not have to report
a SCIC.
Abt Associates, under contract to CMS to conduct analysis and
simulation of refinements to HH PPS, first conducted several
descriptive analyses
[[Page 25426]]
examining the payment accuracy for SCIC-adjusted episodes. As with the
LUPA, they used the Fu Associates' large analytic file consisting of
home health claims linked to OASIS. Analyses included examination of
trends in rates and other utilization statistics relating to SCIC
episodes, OASIS characteristics for SCIC episodes, and estimation of
margins for SCIC episodes.
Results of the analyses indicated that SCIC episodes have been
declining since HH PPS began. Approximately 3.7 percent of episodes
were reported as SCIC episodes in the first quarter of the HH PPS
(October 1, 2000, to December 31, 2000); they decreased to 2.1 percent
of episodes by the first quarter of CY 2004. SCIC episodes tended to be
longer than the average episode (excluding LUPAs), and were more likely
to occur in facility-based agencies and rural agencies. There was some
evidence that the percentage of episodes in the highest category of the
services utilization dimension of the case-mix system increased for
SCIC episodes over time. SCIC episodes had a higher likelihood of using
at least 10 therapy visits, and this excess grew over time. Overall,
patients experiencing SCIC episodes differed little in terms of case-
mix characteristics from the average home health patient, except for a
higher incidence of dyspnea, ADL limitations, and those recently
discharged from acute care.
The margin analysis suggested that, on average, SCIC episodes had
negative margins, even though the SCIC payment policy allows agencies
to avoid declaring a SCIC if an episode that experiences an adverse
significant change in condition would be paid less than the original
case-mix adjusted payment. One reason for the negative margin estimate
appears to be that in some cases agencies inappropriately applied the
SCIC adjustment for patients experiencing a significant adverse change,
when in doing so the agency actually received lower payments for those
patients. Also, the proportional payment policy, which reduces payment
in proportion to the number of days between the last visit before the
significant change in condition and the first visit following the
significant change, results in increasingly lower payments as the
number of days between the last and next visit increases. In contrast,
a normal episode payment is not affected by periods when visits do not
occur.
As noted above, we believe that HHAs have had difficulty in
interpreting when to apply the SCIC adjustment policy. Agencies also
reported additional administrative burdens from adhering to the policy.
Furthermore, there has been a 2 percent decline in use of the SCIC
adjustments since the implementation of the HH PPS. We have received
comments that stated eliminating the SCIC policy altogether might be
better than having a SCIC policy that is difficult to understand and
adhere to. Given these concerns, we decided to focus our analysis on
simulating the impact of eliminating the SCIC adjustment policy. We
performed this simulation by repricing SCIC claims to use the first
HHRG during the episode for determining the payment, and eliminating
any proration. We then compared the total expenditures before and after
making this change.
The results of eliminating the SCIC policy suggested little impact
on outlays--an increase of 0.5 percent of total payments. The
difference in total payments was less than one-half of one percent for
all categories of agencies (urban versus rural, by size, and
ownership).
Based on these findings, we are proposing to eliminate the SCIC
adjustment from the HH PPS. Specifically, we are proposing in Sec.
484.205 to remove paragraph (e) concerning the SCIC adjustment policy
from the HHA PPS. We are also proposing to redesignate paragraph (f) as
paragraph (e). In addition, we are proposing to amend our regulations
at Sec. 484.205 by removing paragraph (a)(3) and redesignating
paragraph (a)(4) as paragraph (a)(3). Furthermore, we proposing to
revise paragraph (b) introductory text to read as follows: ``(b)
Episode payment. The national prospective 60-day episode payment
represents payment in full for all costs associated with furnishing
home health services previously paid on a reasonable cost basis (except
the osteoporosis drug listed in section 1861(m) of the Act as defined
in section 1861(kk) of the Act) as of August 5, 1997 unless the
national 60-day episode payment is subject to a low-utilization payment
adjustment set forth in Sec. 484.230, a partial episode payment
adjustment set forth at Sec. 484.235, or an additional outlier payment
set forth in Sec. 484.240. All payments under this system may be
subject to a medical review adjustment reflecting beneficiary
eligibility, medical necessity determinations, and HHRG assignment. DME
provided as a home health service as defined in section 1861(m) of the
Act continues to be paid the fee schedule amount.'' We are also
proposing to remove Sec. 484.237 relating to the methodology used for
the calculation of the significant change in condition payment
adjustment.
Episodes that are currently SCIC adjusted would be treated as
normal episodes and will receive payment for the entire 60-day period
based on the initial, and only, HHRG code. The national standardized
60-day episode payment rate in section II.A.2.c of the proposed rule
takes into account this proposed change in SCIC policy and is,
therefore, slightly lower than it would have been without proposing
this change. We believe the elimination of the SCIC adjustment policy
would have a minor impact on home health agency operations and
revenues, because SCIC episodes are very infrequent. Our estimate of
the cost of eliminating the SCIC policy, implemented in a budget
neutral manner as a reduction to the national standardized 60-day
payment rate, is presented in section II.D and reported in the
accompanying table (Table 23b). The estimated reduction is $15.71. We
discussed this proposal at a meeting with the contractor's TEP in March
2006. We received favorable feedback noting that our proposal would be
an appropriate simplification of the HH PPS.
7. Non-Routine Medical Supply (NRS) Amounts Review
As described in the HH PPS final rule published in the Federal
Register (65 FR 41180) and modified in the June 1, 2001, correction
notice (66 FR 32777), the NRS amounts included in the per-episode
payment and initially paid on a reasonable cost basis under a home
health plan of care, were calculated by summing the NRS costs using
audited cost reports from 1997. The NRS costs for all the providers in
that audited cost report sample were then weighted to represent the
national population and updated to FY 2001. That weighted total was
divided by the number of episodes for the providers in the audited cost
report sample, to obtain the average cost per episode of NRS reported
as costs on the cost report. This amount was $43.54.
The possible unbundled NRS, billed under Medicare Part B and not
reflected in on the home health cost report, were also included in the
HH PPS national standardized 60-day episode payment rate by summing the
allowed charges for 176 Healthcare Common Procedure Coding System
(HCPCS) codes, reflecting NRS codes, in CY 1998 for beneficiaries under
a home health plan of care. That total was divided by the total number
of episodes in CY 1998 from the episode database, to obtain the average
cost of unbundled NRS per episode. This amount was $6.08.
The total of the two amounts $43.54 and $6.08, or $49.62, was added
to the national total prospective payment
[[Page 25427]]
amount per 60-day episode for CY 2001 (before standardization). The
standardized amount has been subsequently updated annually.
Since the proposal and adoption of this methodology for payment of
NRS, we have received comments expressing concern about the cost of
supplies for certain patients with ``high'' supply costs. In
particular, commenters were concerned about the adequacy of payment for
some patients with pressure ulcers, stasis ulcers, other ulcers,
wounds, burns or trauma, cellulitis, and skin cancers.
In general, NRS use is unevenly distributed across episodes of care
in home health. While most patients do not use NRS, many use a small
amount, and a small number of patients use a large amount of NRS. The
payment for NRS included in the HH PPS standardized payment rate does
not reflect this distributional variation. Furthermore, the current
case-mix adjustment of the standardized amount, which effectively
adjusts the NRS payment we originally included, may not be the most
appropriate way to account for NRS costs.
In order to investigate the performance of the payment methodology
for NRS and to explore an approach to case-mix adjustment of the NRS
component of the payment, our contractor, Abt Associates, performed
several analyses of the current system. The analysis file was
constructed by Abt Associates from a sample of 2001 cost reports, which
were needed to determine cost-to-charge ratios. The cost reports were
then linked to claims. The claims came from an analytic file
constructed by Fu Associates that links home health claims and OASIS.
The cost report sample was analyzed to detect or correct extremely
implausible cost data (that is, if cost report erroneously inverted
ratio of costs to charges, this was corrected). Many cost reports were
dropped after this initial analysis because the cost-to-charge ratio
for nonroutine medical supplies was zero. Then, we retrieved Medicare
claims for patients admitted to the agencies with remaining cost
reports, in order to ensure that the cost report totals for non-routine
supplies were consistent with total charges for non-routine supplies
that we obtained from the provider's claims. Additional cost reports
were dropped from the sample at this step. At the end of this process,
from an initial sample of 2,864 cost reports, 1,207 cost reports were
considered usable.
The cost report data were then merged with a random sample of data
from 496,237 ``normal'' home health episodes from the same set of
agencies used in the sample data. Normal episodes were defined as
episodes that did not include additional adjustments such as LUPAs or
PEP adjustments. ``Cost-to-charge'' ratios generated from the cost
reports were used to estimate NRS costs for the episodes in the sample.
The exploration of case-mix adjustment for NRS costs was conducted
in a manner similar to the way Abt Associates developed the initial
case-mix model. We created regression equations that used OASIS
measures to predict episode-level NRS costs. One equation used the
current case-mix variables. This equation explained approximately 10
percent of the variation in NRS costs in this data sample. This
provided a baseline against which to judge the performance of set
variables that differ from the set used in the current HH PPS case-mix
system.
Models were developed after creating additional variables from
OASIS items and targeting certain conditions expected to be predictors
of NRS use based on clinical considerations. Many of these conditions
were skin-related.
The end result of the model exploration process was two versions of
the ``best-fitting'' variable set. This best fitting variable set
consisted of more than two dozen indicators for diagnoses, wound
conditions, and certain prosthetics captured on the OASIS. The
variables could be used as the basis for improved prediction of NRS
costs. These variables represent measurable conditions that have been
the subject of extensive education by CMS in its administration of the
OASIS system, and by others such as the ICD-9-CM coding committee with
its interest in coding accuracy. Therefore, we believe this variable
set would be the basis for a methodology to account for NRS costs that
is feasible to administer and does not create significant new payment
concerns.
The first alternative model using the best-fitting variables
divided episodes into two episode groups, with one group containing
first and second episodes (early), and the second containing third and
later episodes (later). The second alternative model does not
distinguish between early and later episodes. These ``best fit'' models
were then used to construct a scoring system. Each condition in the
best-fit models was assigned one point for each $5 increment in NRS
cost as determined from the model results. For example, if a variable
representing a clinical condition predicted a $50 increase in cost, an
episode with that variable would be given 10 points. We summed the
condition-specific scores for each episode. We then placed those sums
into five severity groups. For the model that separated early from
later episodes we defined 10 severity groups, five for early episodes
and 5 for later episodes. This system explained about 13.7 percent of
NRS cost variation in the sample. The model that pooled all episodes
had 5 severity groups and explained 13.0 percent of the variation in
NRS costs.
We note, because there is a limited performance advantage of the
two-episode group model over the single model, we are proposing to use
the simpler model that pays all episodes, whether early or later
episodes, using the same set of severity groups. Table 11 shows the
relative weights and payment weights for the five severity levels in
the proposed NRS model, and Table 12a sets forth the NRS scores for the
five-group model. We will continue to evaluate the ICD-9-CM codes
listed for each group (Table 12b) to ensure as much as possible that
condition-related scores are based on ICD-9-CM codes that are specific,
unambiguous, and use diagnostic criteria widely accepted within the
medical community. In addition to refining the list of conditions
contained within each diagnostic group (Table 12b), we intend to
continue to study ways of improving the statistical performance of all
the variables represented in Table 12a. We solicit public comment to
help inform our efforts. We also intend to update the data base upon
which our payment proposal for NRS is based. Our ability to update the
data files will depend on the quality of data available in claims and
cost reports for succeeding years. If the data are not found to be
sufficiently complete and accurate, we would use the existing data for
any final revisions that result from further analysis and public
comments.
In addition to computing the R-square statistic as a summary of the
system's performance, we examined the improvements in payment accuracy
for NRS costs per episode, according to selected characteristics of the
episode. The magnitude of change is difficult to report with a high
degree of certainty because of the limited data resources available for
these analyses.
We found that under our proposal NRS payments for episodes
reporting no NRS charges on the episode claim would better reflect the
absence of NRS costs incurred in such an episode, by having their
payment for NRS reduced. For the remaining claims--those reporting any
amount of NRS costs--on average we estimate that NRS payments would
come significantly closer to their estimated NRS costs under the
proposed
[[Page 25428]]
new system of accounting for NRS. For the subgroups of episodes with
the OASIS conditions listed in Table 11, under our proposal, the
difference between the estimate of average NRS costs incurred and the
proposed amount to account for those NRS costs would decrease in a
similar manner, with some differences becoming even smaller.
However, our ability to predict NRS costs remains limited. We have
not yet developed a statistical model that has performed with a high
degree of predictive accuracy. Some of the reasons for this result
include the limited data available to model NRS costs, and the
likelihood that OASIS does not have any measures available for some
kinds of NRS. Nevertheless, we are proposing to change the payment
system because the majority of episodes do not incur any NRS costs, and
the current payment system overcompensates these episodes. Further, we
believe the proposed approach is appropriate to the extent that we have
developed a way to account for NRS costs that is based on measurable
conditions, is feasible to administer, and offers HHAs some protection
against episodes with extremely high NRS costs. As we noted earlier in
this section, we will continue to look into ways to improve the
predictive model we are proposing to account for NRS costs. We solicit
suggestions and comments from the public on this matter.
In the course of conducting the NRS analysis, we discovered a
possible source of error in reporting on claims. Data analysis
suggested that enteral nutrition patients were incurring higher NRS
costs than average and, in our model, could be assigned a moderate
score for NRS cost. However, we did not find evidence from our analyses
that any category of NRS other than enteral supplies would
systematically account for the NRS finding in the model for enteral
nutrition patients. These patients often have a very compromised health
status, including skin and other conditions that are already accounted
for in our model. Further, we explored other possibilities to determine
if information was missing from the model. If available, such
information could be added to the model to explain the scores we found
for the enteral nutrition variable. However, we did not gather any
information that produced any additional hypotheses. An important
remaining hypothesis is that some providers are reporting enteral
supplies charges for these patients in error; in fact, at least one
large provider has indicated this was the case. We are proposing to
exclude the enteral nutrition variable from the model to ensure
compliance with the statute and regulations governing enteral
nutrition, as noted below; but, we welcome comments on this issue.
As we stated in the final HH PPS rule dated July 3, 2000 (65 FR
41139), ``Part B services such as parenteral or enteral nutrition are
neither currently covered as home health services nor defined as non-
routine medical supplies. Parenteral or enteral nutrition would
therefore not be subject to the requirements governing home health
consolidated billing.''
If the patient requires medical supplies that are currently covered
and paid for under the Medicare home health benefit during a certified
episode under HH PPS, the billing for those medical supplies falls
under the auspices of the HHA due to the consolidated billing
requirements. As parenteral and enteral nutrition are not covered or
paid for under the Medicare home health benefit, they should be billed
separately by the supplier or provider. Because we assumed that some
providers are reporting these supplies in error, we believe it is
important to again note the Medicare coverage requirements for
parenteral and enteral nutrition to prevent any potential future
reporting errors.
Medicare's coverage guidelines for enteral nutrition state:
``Coverage of nutritional therapy as a Part B benefit is provided under
the prosthetic device benefit provision which requires that the patient
must have a permanently inoperative internal body organ or function
thereof. Therefore, enteral and parenteral nutritional therapy is not
covered under Part B in situations involving temporary impairments.''
The National Coverage Decision (NCD) provides guidance in applying the
definition of temporary impairment: ``Coverage of such therapy,
however, does not require a medical judgment that the impairment giving
rise to the therapy will persist throughout the patient's remaining
years. If the medical record, including the judgment of the attending
physician, indicates that the impairment will be of long and indefinite
duration, the test of permanence is considered met.'' (See Medicare
National Coverage Determinations [NCD] Manual, Pub. 100-03, Section
180.2, Chapter 1 (Part 3). Section 1842(s) of the Act implements the
fee schedule for parenteral and enteral nutrition (PEN) nutrients,
equipment and supplies. The general payment rules for PEN effective on
or after January 1, 2002, are stipulated in Sec. 414.102 and Sec.
414.104.
The following is the list of HCPCS codes which may be used to claim
reimbursement for enteral nutrition. Providers may claim reimbursement
for it on the UB-92 claim form if they report the appropriate HCPCS
code and revenue center code. Payment is made by the RHHI under the
Medicare Fee Schedule.
BILLING CODE 4120-01-P
[[Page 25429]]
[GRAPHIC] [TIFF OMITTED] TP04MY07.034
Notwithstanding our proposal to exclude enteral nutrition from the
list of conditions included as NRS, we now describe our proposed
revision to the payment methodology to account for NRS costs. We
propose to account for
[[Page 25430]]
NRS costs based on five severity groups and a national conversion
factor. Table 12a shows the condition-specific scores derived from the
NRS model. Table 12b shows the ICD-9-CM diagnosis codes used to define
conditions that are based on diagnosis codes. The sum of scores for
each episode is then used to group episodes into one of five severity
groups, as follows: Group 0 if the sum is zero; group 1 for 1 to 16;
group 2 for 17 to 34; group 3 for 35 to 59; and group 4 for 60 or more.
We defined these five scoring levels from examining the distribution of
scores in our analysis sample. Most of the episodes (64 percent, see
Table 11) fell into the group with a score of zero (that is, no
conditions listed in Table 12b were reported on the OASIS assessment).
For purposes of payment, relative weights were calculated for each
severity group based on the estimated average NRS cost, divided by the
overall average in the sample. The relative weights are listed below in
Table 11.
To derive payment, each relative weight is multiplied by the
conversion factor. We calculated the conversion factor by inflating the
original allowance included in the episode base rate ($49.62) by the
total percentage increase since October 2000 using the statutory market
basket updates. We take the inflated conversion factor of $53.91 and
multiply it by 1.05 to account for the initial outlier payment noted in
the July 3, 2000 final rule (65 FR 41187). We then take that product
and multiply it by 0.958614805 to account for the estimated percentage
of outlier payments as a result of the current FDL ratio of 0.67. To
further adjust for the nominal change in case-mix, we multiply the
$54.26 by 0.9725 for a proposed NRS conversion factor of $52.77.
Because the market for most NRS is national, we do not propose to have
a geographic adjustment to the conversion factor. We plan to continue
to monitor NRS costs to determine if any adjustment for the NRS weights
is warranted in the future.
We determined the budget-neutral national standardized 60-day
episode payment rate that compensates for the payments for NRS under
the proposed new case-mix-adjusted HH PPS as part of the simulation of
all proposed changes on our 2003 claims sample. The results are shown
in section II.D.
For an example of calculating an HH PPS payment using the NRS
proposed payment methodology see section II.D.
We do not propose to apply the five-level NRS payment approach to
LUPA episodes. In the original design of the HH PPS, $1.94 was built
into the per-visit rates used to pay for visits in a LUPA episode. This
amount was the sum of $1.71, the average cost per visit for NRS
reported as costs on the cost report, and $.23, the average cost per
visit for NRS possibly unbundled and billed separately to Part B and
reimbursed on the fee schedule. Recent analysis shows that NRS charges
for non-LUPA episodes are almost 3 times higher than that for LUPA
episodes. In general, approximately 1 in 5 LUPAs report NRS while 1 in
3 non-LUPA episodes report NRS. Our proposal is to redistribute the
$53.96 currently paid to all non-LUPA episodes. Given that LUPA
episodes, by nature, are of extremely low visit volume, we do not
propose to redistribute that $1.94 now paid to LUPA episodes. We
believe an attempt to develop a model for redistributing the small
amount of NRS payments ($1.94) paid to LUPA episodes would be
unproductive.
Furthermore, we are also concerned that additional payment for
LUPAs to account for NRS costs could promote increases in medically
unnecessary home health episodes. In proposing refinements for LUPA
payments, as discussed in section II.A.5 of this proposed rule, we are
aware of the potential for increases in medically unnecessary LUPA
episodes that could result from our proposal for increased LUPA payment
for only or initial LUPA episodes. Providing for additional NRS
payments for such LUPAs could only adversely add to this potential.
Consequently, we are not proposing any additional payments for NRS
costs for LUPA episodes. However, we are specifically soliciting
comment on alternative approaches for NRS payment in LUPAs.
We also considered proposing an outlier policy for NRS costs, but
we believe one is not administratively feasible at this time. An
outlier policy for NRS costs would depend on having an infrastructure,
including a reporting system for the extensive range of nonroutine
supplies used in home health care, and a basis for assigning allowable
costs for those supply items. At this time, this kind of infrastructure
is not sufficiently developed. Many types of NRS cannot be coded under
the existing reporting system, the HCPCS system, and reliable cost data
are limited. Therefore, at this time, we also believe an outlier policy
for NRS cost would be premature. We also recognize the additional
administrative burdens on agencies that would exist under such an
outlier policy.
While we are not proposing an outlier policy for NRS costs, we
nonetheless urge agencies to provide cost data on cost reports and
charge data on all claims (including LUPA claims) with the utmost
precision for possible future use in developing payment proposals for
NRS under the HH PPS.
Table 11.--Proposed Relative Weights for Non-Routine Medical Supplies
----------------------------------------------------------------------------------------------------------------
Percentage of Points Relative
Severity level episodes (scoring) weight Payment amount
----------------------------------------------------------------------------------------------------------------
0............................................... 63 0 0.2456 $12.96
1............................................... 17 1-16 1.0356 54.65
2............................................... 12 17-34 2.0746 109.48
3............................................... 5 35-59 4.0776 215.17
4............................................... 3 60+ 6.9612 367.34
----------------------------------------------------------------------------------------------------------------
Note: Proposed conversion factor = $52.77.
Table 12a.--NRS Case-Mix Adjustment Variables and Scores
------------------------------------------------------------------------
Description Score
------------------------------------------------------------------------
SELECTED SKIN CONDITIONS:
1................... Primary diagnosis = Anal fissure, 19
fistula and abscess.
2................... Primary diagnosis = Cellulitis and 13
abscess.
3................... Primary diagnosis = Gangrene........... 11
4................... Primary diagnosis = Malignant neoplasms 16
of skin.
[[Page 25431]]
5................... Primary diagnosis = Non-pressure and 9
non-stasis ulcers.
6................... Primary diagnosis = Other infections of 19
skin and subcutaneous tissue.
7................... Primary diagnosis = Post-operative 32
Complications 1.
8................... Primary diagnosis = Post-operative 22
Complications 2.
9................... Primary diagnosis = Traumatic Wounds 16
and Burns.
10.................. Other diagnosis = Anal fissure, fistula 9
and abscess.
11.................. Other diagnosis = Cellulitis and 6
abscess.
12.................. Other diagnosis = Gangrene............. 11
13.................. Other diagnosis = Non-pressure and non- 8
stasis ulcers.
14.................. Other diagnosis = Other infections of 7
skin and subcutaneous tissue.
15.................. Other diagnosis = Post-operative 15
Complications 1.
16.................. Other diagnosis = Post-operative 15
Complications 2.
17.................. Other diagnosis = Traumatic Wounds and 7
Burns.
18.................. M0450 = 1 pressure ulcer, stage 1 or 2. 12
19.................. M0450 = 2 or 3 pressure ulcers, stage 1 20
or 2.
20.................. M0450 = 4+ pressure ulcers, stage 1 or 31
2.
21.................. M0450 = 1 or 2 pressure ulcers, stage 3 41
or 4.
22.................. M0450 = 3 pressure ulcers, stage 3 or 4 75
23.................. M0450 = 4+ pressure ulcers, stage 3 or 80
4.
24.................. M0450 = 5+ pressure ulcers, stage 3 or 143
4.
25.................. M0450e = 1(unobserved pressure 18
ulcer(s)).
26.................. M0476 = 2 (status of most problematic 18
stasis ulcer: early/partial
granulation).
27.................. M0476 = 3 (status of most problematic 28
stasis ulcer: not healing).
28.................. M0488 = 3 (status of most problematic 18
surgical wound: not healing).
29.................. M0488 = 2 (status of most problematic 5
surgical wound: early/partial
granulation).
OTHER CLINICAL FACTORS:
30.................. M0550 = 1 (ostomy not related to inpt 21
stay/no regimen change).
31.................. M0550 = 2 (ostomy related to inpt stay/ 35
regimen change).
32.................. Any ``Selected Skin Conditions'' (see 24
rows 1 to 29 above) AND M0550=1(ostomy
not related to inpt stay/no regimen
change).
33.................. Any ``Selected Skin Conditions'' (see 8
rows 1 to 29 above) AND M0550=2
(ostomy related to inpt stay/regimen
change).
34.................. M0250 (Therapy at home) =1 (IV/ 11
Infusion).
35.................. M0470 = 2 or 3 (2 or 3 stasis ulcers).. 17
36.................. M0470 = 4 (4 stasis ulcers)............ 34
37.................. M0520 = 2 (patient requires urinary 17
catheter).
------------------------------------------------------------------------
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[[Page 25433]]
[GRAPHIC] [TIFF OMITTED] TP04MY07.036
[[Page 25434]]
[GRAPHIC] [TIFF OMITTED] TP04MY07.037
*Note: ``ICD-9-CM Official Guidelines for Coding and Reporting''
dictate that a three-digit code is to be used only if it is not
further subdivided. Where fourth-digit subcategories and/or fifth-
digit subclassifications are provided, they must be assigned. A code
is invalid if it has not been coded to the full number of digits
required for that code. Codes with three digits are included in ICD-
9-CM as the heading of a category of codes that may be further
subdivided by the use of fourth and/or fifth digits, which provide
greater detail. The category codes listed in Table 12b include all
the related 4- and 5-digit codes.
8. Outlier Payment Review
Section 1895(b)(5) of the Act allows for the provision of an
addition or adjustment to the regular 60-day case-mix and wage-adjusted
episode payment amount in the case of episodes that incur unusually
large costs due to patient home health care needs. This section further
stipulates that total outlier payments in a given CY may not exceed 5
percent of total projected estimated HH PPS payments.
In the July 2000 final rule, we described a method for determining
outlier payments. Under this system, outlier payments are made for
episodes whose estimated cost exceeds a threshold amount. The episode's
estimated cost is the sum of the national wage-adjusted per-visit
payment amounts for all visits delivered during the episode. The
outlier threshold for each case-mix group, PEP adjustment, or total
SCIC adjustment is defined as the national standardized 60-day episode
payment rate, PEP adjustment, or total SCIC adjustment for that group
plus a fixed dollar loss (FDL) amount. Both components of the outlier
threshold are wage-adjusted.
The wage-adjusted FDL amount represents the amount of loss that an
agency must experience before an episode becomes eligible for outlier
payments. The FDL is computed by multiplying the wage-adjusted national
standardized 60-day episode payment amount by the FDL ratio, which is a
proportion expressed in terms of the national standardized episode
payment amount. The outlier payment is defined to be a proportion of
the wage-adjusted estimated costs beyond the wage-adjusted threshold.
The proportion of additional costs paid as outlier payments is referred
to as the loss-sharing ratio. The FDL ratio and the loss-sharing ratio
were selected so that the estimated total outlier payments would not
exceed the 5 percent level.
For a given level of outlier payments, there is a trade-off between
the values selected for the FDL ratio and the loss-sharing ratio. A
high FDL ratio reduces the number of episodes that may receive outlier
payments, but makes it possible to select a higher loss-sharing ratio
and, therefore, increase outlier payments for outlier episodes.
Alternatively, a lower FDL ratio means that more episodes may qualify
for outlier payments, but outlier payments per episode must be lower.
As a result of public comments on the October 28, 1999 proposed rule,
and in our July 2000 final rule, we made the decision to attempt to
cover a relatively high proportion of the costs of outlier cases for
the most expensive episodes that would qualify for outlier payments
within the 5 percent constraint.
We chose a value of 0.80 for the loss-sharing ratio, which is
relatively high, but preserves incentives for agencies to attempt to
provide care efficiently for outlier cases. It was also consistent with
the loss-sharing ratios used in other Medicare PPS outlier policies.
Having made this decision, we estimated the value of the FDL ratio that
would yield estimated total outlier payments that were projected to be
no more than 5 percent of total HH PPS payments. The resulting value
for the FDL ratio was 1.13.
When the data became available, we performed an analysis of CY 2001
home health claims data. This analysis revealed that outlier episodes
represented approximately 3 percent of total episodes and 3 percent of
total HH PPS payments. Additionally, we performed the same analysis on
CY 2002 and CY 2003 home health claims data and found the number of
outlier episodes and payments held at approximately 3 percent of total
episodes and total HH PPS payments, respectively. Based on these
analyses and comments we received, we decided that an update to the FDL
ratio would be appropriate.
To that end, for the October 2004 final rule, we performed data
analysis on CY 2003 HH PPS analytic data. The results of this analysis
indicated that a FDL ratio of 0.70 is consistent with the existing
loss-sharing ratio of 0.80 and a projected target percentage of
estimated outlier payments of no more than 5 percent. Consequently, we
updated the FDL ratio from the initial ratio of 1.13 to the FDL ratio
of 0.70. Our analysis showed that reducing the FDL ratio from 1.13 to
0.70 would increase the percentage of episodes that qualified for
outlier episodes from 3.0 percent to approximately 5.9 percent. A FDL
ratio of 0.70 also better met the estimated 5 percent target of outlier
payments to total HH PPS payments. We believed that this updated FDL
ratio of 0.70 preserved a reasonable degree of cost sharing, while
allowing a greater number of episodes to qualify for outlier payments.
Our CY 2006 update to the HH PPS rates (70 FR 68132) changed the
FDL ratio from 0.70 to 0.65 to allow even more home health episodes to
qualify for outlier payments and to better meet the estimated 5 percent
target of outlier payments to total HH PPS payments. For the CY 2006
update, we used CY 2004 home health claims data.
In our CY 2007 update to the HH PPS rates (71 FR 65884) we again
changed the FDL ratio from 0.65 to 0.67 to better meet the estimated 5
percent target of outlier payments to total HH PPS payments. For the CY
2007 update, we used CY 2005 home health claims data.
Under the HH PPS, outlier payments have thus far not exceeded 5
percent of total HH PPS payments. However, preliminary analysis shows
that outlier payments, as a percentage of total HH PPS payments, have
increased on a yearly basis. With outlier payments having increased in
recent years, and given the unknown effects that the proposed
refinements of this rule may have on outliers, we are proposing to
maintain the FDL ratio of 0.67. By maintaining the FDL ratio of 0.67,
we believe we will continue to meet the statutory requirement of having
an outlier payment outlay that does not exceed 5 percent of total HH
PPS payments, while still providing for an adequate number of episodes
to qualify for outlier payments. Some preliminary analysis shows the
FDL ratio could be as low as 0.42 in a refined HH PPS. We believe that
analysis of more recent data could indicate that a change in the FDL
ratio is appropriate. Consequently for the final rule, we will rely on
the latest
[[Page 25435]]
data and best analysis available at the time to estimate outlier
payments and update the FDL ratio if appropriate.
Because payment for NRS was included in the base rate of the
national standardized 60-day episode payment rate, under the refined
system proposed in this proposed rule, both the proposed national
standardized 60-day episode payment rate and the proposed computed NRS
amount contribute towards reaching the outlier threshold in the outlier
payment calculation.
B. Rebasing and Revising of the Home Health Market Basket
1. Background
Section 1895(b)(3)(B) of the Act, as amended by section 701(b)(3)
of the MMA, requires the standard prospective payment amounts to be
adjusted by a factor equal to the applicable home health market basket
increase for CY 2008.
Effective for cost reporting periods beginning on or after July 1,
1980, we developed and adopted an HHA input price index (that is, the
home health ``market basket''). Although ``market basket'' technically
describes the mix of goods and services used to produce home health
care, this term is also commonly used to denote the input price index
derived from that market basket. Accordingly, the term ``home health
market basket'' used in this document refers to the HHA input price
index.
The percentage change in the home health market basket reflects the
average change in the price of goods and services purchased by HHAs in
providing an efficient level of home health care services. We first
used the home health market basket to adjust HHA cost limits by an
amount that reflected the average increase in the prices of the goods
and services used to furnish reasonable cost home health care. This
approach linked the increase in the cost limits to the efficient
utilization of resources. For a greater discussion on the home health
market basket, see the notice with comment period published in the
Federal Register on February 15, 1980 (45 FR 10450, 10451), the notice
with comment period published in the Federal Register on February 14,
1995 (60 FR 8389, 8392), and the notice with comment period published
in Federal Register on July 1, 1996 (61 FR 34344, 34347). Beginning
with the FY 2002 HH PPS payments, we used the home health market basket
to update payments under the HH PPS. We last rebased the home health
market basket effective with the CY 2005 update. For more information
on the HH PPS home health market basket, see our proposed rule
published in the Federal Register on June 2, 2004 (69 FR 31251, 31255).
The home health market basket is a fixed-weight Laspeyres-type
price index; its weights reflect the cost distribution for the base
year while current period price changes are measured. The home health
market basket is constructed in three steps. First, a base period is
selected and total base period expenditures are estimated for mutually
exclusive and exhaustive spending categories based upon the type of
expenditure. Then the proportion of total costs that each spending
category represents is determined. These proportions are called cost or
expenditure weights.
The second step essential for developing an input price index is to
match each expenditure category to an appropriate price/wage variable,
called a price proxy. These proxy variables are drawn from publicly
available statistical series published on a consistent schedule,
preferably at least quarterly.
In the third and final step, the price level for each spending
category is multiplied by the expenditure weight for that category. The
sum of these products for all cost categories yields the composite
index level in the market basket in a given year. Repeating the third
step for other years will produce a time series of market basket index
levels. Dividing one index level by an earlier index level will produce
rates of growth in the input price index.
We described the market basket as a fixed-weight index because it
answers the question of how much more or less it would cost, at a later
time, to purchase the same mix of goods and services that was purchased
in the base period. As such, it measures ``pure'' price changes only.
The effects on total expenditures resulting from changes in the
quantity or mix of goods and services purchased subsequent to the base
period are, by design, not considered.
2. Rebasing and Revising the Home Health Market Basket
We believe that it is desirable to rebase the home health market
basket periodically so the cost category weights reflect changes in the
mix of goods and services that HHAs purchase in furnishing home health
care. We based the cost category weights in the current home health
market basket on FY 2000 data. We are proposing to rebase and revise
the home health market basket to reflect FY 2003 Medicare cost report
data, the latest available and most complete data on the structure of
HHA costs.
The terms ``rebasing'' and ``revising,'' while often used
interchangeably, actually denote different activities. The term
``rebasing'' means moving the base year for the structure of costs of
an input price index (that is, in this exercise, we are proposing to
move the base year cost structure from FY 2000 to FY 2003). The term
``revising'' means changing data sources, cost categories, and/or price
proxies used in the input price index.
For this proposed revising and rebasing, we modified the wages and
salaries and benefits cost categories in order to reflect a new data
source on the occupational mix of HHAs. We mainly relied on this
alternative proposed data source to construct the cost weights for the
blended wage and benefit index. We are not proposing any changes to the
price proxies used in the HH market basket or the HH blended wage and
benefit proxies.
The weights for this proposed revised and rebased home health
market basket are based off of the cost report data for freestanding
HHAs, whose cost reporting period began on or after October 1, 2002 and
before October 1, 2003. Using this methodology allowed our sample to
include HHA facilities with varying cost report years including, but
not limited to, the federal fiscal or calendar year. We refer to the
market basket as a fiscal year market basket because the base period
for all price proxies and weights are set to FY 2003. For this proposed
rebased and revised market basket, we reviewed HHA expenditure data for
the market basket cost categories.
We proposed to maintain our policy of using data from freestanding
HHAs because they better reflect HHAs actual cost structure. Expense
data for a hospital-based HHA are affected by the allocation of
overhead costs over the entire institution (including but not limited
to hospital, hospital-based skilled nursing facility, and hospital-
based HHA). Due to the method of allocation, total expenses will be
correct, but the individual components' expenses may be skewed.
Therefore, if data from hospital-based HHAs were included, the
resultant cost structure could be unrepresentative of the average HHA
costs.
Data on HHA expenditures for nine major expense categories (wages
and salaries, employee benefits, transportation, operation and
maintenance, administrative and general, insurance, fixed capital,
movable capital, and a residual ``all other'') were tabulated from the
FY 2003 Medicare HHA cost reports. As
[[Page 25436]]
prescription drugs and DME are not payable under the HH PPS, we
excluded those items from the home health market basket and from the
expenditures. Expenditures for contract services were also tabulated
from these FY 2003 Medicare HHA cost reports and allocated to wages and
salaries, employee benefits, administrative and general, and other
expenses. After totals for these cost categories were edited to remove
reports where the data were deemed unreasonable (for example, when
total costs were not greater than zero), we then determined the
proportion of total costs that each category represents. The
proportions represent the major rebased home health market basket
weights.
We determined the weights for subcategories (telephone, postage,
professional fees, other products, and other services) within the
combined administrative and general and other expenses using the latest
available (1997 Benchmark) U.S. Department of Commerce, Bureau of
Economic Analysis (BEA) Input-Output (I-O) Table, from which we
extracted data for HHAs. The BEA I-O data, which are updated at 5-year
intervals, were most recently described in the Survey of Current
Business article, ``Benchmark Input-Output Accounts of the U.S., 1997''
(December 2002). These data were aged from 1997 to 2003 using relevant
price changes.
The methodology we used to age the data applied the annual price
changes from the price proxies to the appropriate cost categories. We
repeated this practice for each year.
This work resulted in the identification of 12 separate cost
categories, the same number found in the FY 2000-based home health
market basket. The differences between the major categories for the
proposed FY 2003-based index and those used for the current FY 2000-
based index are summarized in Table 13. We have allocated the
contracted services weight to the wages and salaries, employee
benefits, and administrative and general and other expenses cost
categories in the proposed FY 2003-based index as we did in the FY
2000-based index.
Table 13.--Comparison Of 2000-Based and Proposed 2003-Based Home Health
Market Baskets Major Cost Categories and Weights
------------------------------------------------------------------------
Proposed 2003-
2000-Based based home
Cost categories home health health market
market basket basket
------------------------------------------------------------------------
Wages and Salaries, including allocated 65.766 64.484
contract services' labor...............
Employee Benefits, including allocated 11.009 12.598
contract services' labor...............
All Other Expenses including allocated 23.225 22.918
contract services' labor...............
-------------------------------
Total............................... 100.000 100.000
------------------------------------------------------------------------
The complete proposed 2003-based cost categories and weights are
listed in Table 14.
Table 14.--Cost Categories, Weights, and Price Proxies in Proposed 2003-
Based Home Health Market Basket
------------------------------------------------------------------------
Cost categories Weight Price proxy
------------------------------------------------------------------------
Compensation, including allocated 77.082 ......................
contract services' labor.
Wages and Salaries, including 64.484 Proposed Home Health
allocated contract services' labor. Occupational Wage
Index.
Employee Benefits, including 12.598 Proposed Home Health
allocated contract services' labor. Occupational Benefits
Index.
Operations & Maintenance........... 0.694 CPI-U Fuel & Other
Utilities.
Administrative & General & Other 16.712 ......................
Expenses including allocated
contract services' labor.
Telephone.......................... 0.785 CPI-U Telephone
Services.
Postage............................ 0.605 CPI-U Postage.
Professional Fees.................. 1.471 ECI for Compensation
for Professional and
Technical Workers.
Other Products..................... 7.228 CPI-U All Items Less
Food and Energy.
Other Services..................... 6.622 ECI for Compensation
for Service Workers.
Transportation..................... 2.494 CPI-U Private
Transportation.
Capital-Related.................... 3.018 ......................
Insurance.......................... 0.510 CPI-U Household
Insurance.
Fixed Capital...................... 1.618 CPI-U Owner's
Equivalent Rent.
Movable Capital.................... 0.890 PPI Machinery &
Equipment.
------------------------------------
Total.......................... 100.000 **
------------------------------------------------------------------------
** Figures may not sum to total due to rounding.
After we computed the FY 2003 cost category weights for the
proposed rebased home health market basket, we selected the most
appropriate wage and price indexes to proxy the rate of change for each
expenditure category. These price proxies are based on Bureau of Labor
Statistics (BLS) data and are grouped into one of the following BLS
categories:
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.
[[Page 25437]]
These indexes are fixed-weight indexes and strictly measure the change
in wage rates and employee benefits per hour. They are not affected by
shifts in skill mix. ECIs are superior to average hourly earnings as
price proxies for input price indexes for two reasons: (a) They measure
pure price change; and (b) they are available by occupational groups,
not just by industry.
Consumer Price Indexes--Consumer Price Indexes (CPIs)
measure change in the prices of final goods and services bought by the
typical consumer. Consumer price indexes are used when the expenditure
is more similar to that of a purchase at the retail level rather than
at the wholesale level, or if no appropriate Producer Price Indexes
(PPIs) were available.
Producer Price Indexes--PPIs are used to measure price
changes for goods sold in other than retail markets. For example, a PPI
for movable equipment is used rather than a CPI for equipment. PPIs in
some cases are preferable price proxies for goods that HHAs purchase at
wholesale levels. These fixed-weight indexes are a measure of price
change at the producer or at the intermediate stage of production.
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. Widely accepted statistical methods ensure that the data
were collected and aggregated in way that can be replicated. Low
sampling variability is desirable because it indicates that sample
reflects the typical members of the population. (Sampling variability
is variation that occurs by chance because a sample was surveyed rather
than the entire population.) Timeliness implies that the proxy is
published regularly, preferably at least once a quarter. The market
baskets are updated quarterly and therefore it is important the
underlying price proxies be up-to-date, reflecting the most recent data
available. We believe that using proxies that are published regularly
(at least quarterly, whenever possible) helps ensure that we are using
the most recent data available to update the market basket. We strive
to use publications that are disseminated frequently because we believe
that this is an optimal way to stay abreast of the most current data
available. Availability means that the proxy is publicly available. We
prefer that our proxies are publicly available because this will help
ensure that our market basket updates are as transparent to the public
as possible. In addition, this enables the public to be able to obtain
the price proxy data on a regular basis. 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
proposed in this regulation meet these criteria. Therefore, we believe
that they continue to be the best measure of price changes for the cost
categories to which they would be applied.
As part of the revising and rebasing of the home health market
basket, we are proposing to revise and rebase the home health blended
wage and salary index and the home health blended benefits index.
We would use these blended indexes as price proxies for the wages
and salaries and the employee benefits portions of the proposed FY
2003-based home health market basket, as we did in the FY 2000-based
home health market basket. The price proxies for these two cost
categories are the same as those used in the FY 2000-based home health
market basket but with occupational weights reflecting the FY 2003
occupational mix in HHAs. These proxies are a combination of health
industry specific and economy-wide proxies.
3. Price Proxies Used To Measure Cost Category Growth
Wages and salaries, including an allocation for contract
services' labor: For measuring price growth in the FY 2003-based home
health market basket, as we did in the FY 2000-based index, five price
proxies would be applied to the four occupational subcategories within
the wages and salaries component, and would be weighted to reflect the
HHA occupational mix. This approach was used because there is not a
wage proxy for home health care workers that reflects only wage changes
and not both wage and skill mix changes. The professional and technical
occupational subcategory is represented by a 50-50 blend of hospital
industry and economy-wide price proxies. Therefore, there are five
price proxies used for the four occupational subcategories. The
percentage change in the blended wages and salaries price is applied to
the wages and salaries component of the home health market basket,
which is described in Table 15.
Table 15.--Proposed Home Health Occupational Wages and Salaries Index
[Wages and salaries component of the proposed FY 2003-based home health
market basket]
------------------------------------------------------------------------
2000 2003
Cost category weight weight Price proxy
------------------------------------------------------------------------
Skilled Nursing & Therapists & 53.816 50.812 50
Other Professional/Technical, percent ECI for
including an allocation for Wages & Salaries
contract services' labor. in Private
Industry for
Professional,
Specialty &
Technical
Workers.
50
percent ECI for
Wages & Salaries
for Civilian
Hospital Workers.
Managerial/Supervisory, 7.431 9.007 ECI for Wages &
including an allocation for Salaries in
contract services' labor. Private Industry
for Executive,
Administrative &
Managerial
Workers.
Clerical, including an 6.822 7.596 ECI for Wages &
allocation for contract Salaries in
services' labor. Private Industry
for
Administrative
Support,
Including
Clerical Workers.
Service, including an 31.931 32.584 ECI for Wages &
allocation for contract Salaries in
services' labor. Private Industry
Service
Occupations.
-----------------------------------------
Total..................... 100.000 100.000
------------------------------------------------------------------------
Beginning with the FY 2001 Medicare cost report, the occupational
specific wage and benefit expenditure data was no longer collected in
the cost report. Previously, we used these data to estimate weights for
the home health blended wage and salary index and the home health
blended benefits index. We believed the options to obtain these data
were:
To obtain the home health occupational specific
expenditure data from an alternative source, or
To propose a change to the home health wages and salaries
and the home
[[Page 25438]]
health benefits proxy used in the market basket.
However, there is no publicly available data source that tracks
wage and salary price growth for the home health industry while holding
skill mix constant. There is also no publicly available data source
that tracks benefit price growth for the home health industry while
holding skill mix constant. Therefore, option 2 was not an viable
solution. Next, we investigated if there was home health occupational
specific expenditure data from an alternative source other than the
Medicare cost reports. We believe an alternative source exists in the
form of data from the November 2003 National industry-specific
occupational employment and wage estimates published by the BLS Office
of Occupational Employment Statistics (OES). Accordingly, we propose to
use that data to determine weights for the home health specific blended
wage and benefits proxy. Detailed information on the methodology for
the national industry-specific occupational employment and wage
estimates survey can be found at http://www.bls.gov/oes/current/oes_tec.htm
.
Therefore, the needed data on HHA expenditures for the four
occupational subcategories (managerial, professional and technical,
service, and clerical) for the wages and salaries component were
tabulated from the November 2003 OES data for North American Industrial
Classification System (NAICS) 621600, Home Health Care Services. We
assigned the occupations to the groups in a manner consistent with the
occupational groupings used in the Medicare cost report. Table 16 shows
the specific occupational assignments to the four CMS designated
subcategories.
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Total expenditures by occupation were calculated by taking the OES
number of employees multiplied by the OES annual average salary. The
wage and salary expenditures were aggregated based on the groupings in
table 14. Next, contract labor expenditures were obtained from the 1997
I-O for the home health industry, NAICS 621600 and aged forward to FY
2003 using the PPI for employment services. We then proportionally
allocated the contract labor to each of the four subcategories. We
determined the proportion of total wage costs (contract wages plus
[[Page 25440]]
industry wages) that each subcategory represents. These proportions
represent the major rebased and revised home health blended wage and
salary index weights.
We did not propose a change from our current blended measure
because we believe it reflects the competition between HHAs and
hospitals for registered nurses, while still capturing the overall wage
trends for professional and technical workers.
Employee benefits, including an allocation for contract
services' labor: For measuring employee benefits price growth in the FY
2003-based home health market basket, price proxies are applied to the
four occupational subcategories within the employee benefits component,
weighted to reflect the home health occupational mix. The professional
and technical occupational subcategory is represented by a blend of
hospital industry and economy-wide price proxies. Therefore, there are
five price proxies for four occupational subcategories. The percentage
change in the blended price of home health employee benefits is applied
to this component, which is described in Table 17.
Table 17.--Proposed Home Health Occupational Benefits Index
[Employee benefits component of the proposed 2003-based home health
market basket]
------------------------------------------------------------------------
2000 2003
Cost category weight weight Price proxy
------------------------------------------------------------------------
Skilled Nursing & Therapists & 53.492 50.506 50
Other Professional/Technical, percent ECI for
including an allocation for Benefits in
contract services' labor. Private Industry
for Professional,
Specialty
&Technical
Workers.
......... ......... 50
percent ECI for
Benefits for
Civilian Hospital
Workers.
Managerial/Supervisory, 7.232 8.766 ECI for Benefits
including an allocation for in Private
contract services' labor. Industry for
Executive,
Administrative &
Managerial
Workers.
Clerical, including an 6.941 7.698 ECI for Benefits
allocation for contract in Private
services' labor. Industry for
Administrative
Support,
Including
Clerical Workers.
Service, including an 32.362 33.024 ECI for Benefits
allocation for contract in Private
services' labor. Industry Service
Occupations.
-----------------------------------------
Total..................... 100.000 100.000
------------------------------------------------------------------------
After conducting research we could find no data source that exists
for benefit expenditures by occupation for the home health industry.
Thus, to construct weights for the home health occupational benefits
index we calculated the ratio of benefits to wages and salaries from
the 2000 Home health occupational wages and occupational benefits
indices for the four occupational subcategories. We then applied the
benefit-to-wage ratios to each of the four occupational subcategories
from the 2003 OES wage and salary weights. For example, the ratio of
benefits to wages from the 2000 home health occupational wage and
benefit indexes for home health managers is 0.973. We apply this ratio
to the 2003 OES weight for wages and salaries for home health managers,
9.007, to obtain a benefit weight in the home health occupational
benefit index for home health managers of 8.766 percent.
We are proposing to continue to use the same 50-50 split for
benefits for professional and technical workers (50 percent hospital
workers and 50 percent professional and technical workers) as we did in
the FY 2000-based market basket.
Operations and Maintenance: The percentage change in the
price of fuel and other utilities as measured by the Consumer Price
Index is applied to this component. The same proxy was used for the FY
2000-based market basket.
Telephone: The percentage change in the price of telephone
service as measured by the Consumer Price Index is applied to this
component. The same proxy was used for the FY 2000-based market basket.
Postage: The percentage change in the price of postage as
measured by the Consumer Price Index is applied to this component. The
same proxy was used for the FY 2000-based market basket.
Professional Fees: The percentage change in the price of
professional fees as measured by the ECI for compensation for
professional and technical workers is applied to this component. The
same proxy was used for the 2000-based market basket.
Other Products: The percentage change in the price for all
items less food and energy as measured by the Consumer Price Index is
applied to this component. The same proxy was used for the FY 2000-
based market basket.
Other Services: The percentage change in the employment
cost index for compensation for service workers is applied to this
component. The same proxy was used for the FY 2000-based market basket.
Transportation: The percentage change in the price of
private transportation as measured by the Consumer Price Index is
applied to this component. The same proxy was used for the FY 2000-
based market basket.
Insurance: The percentage change in the price of household
insurance as measured by the Consumer Price Index is applied to this
component. The same proxy was used for the FY 2000-based market basket.
Fixed capital: The percentage change in the price of an
owner's equivalent rent as measured by the Consumer Price Index is
applied to this component. The same proxy was used for the FY 2000-
based market basket.
Movable Capital: The percentage change in the price of
machinery and equipment as measured by the Producer Price Index is
applied to this component. The same proxy was used for the FY 2000-
based market basket.
As we did in the FY 2000-based home health market basket, we
allocated the Contract Services' share of home health agency
expenditures among wages and salaries, employee benefits,
administrative and general and other expenses.
Table 18 summarizes the proposed FY 2003-based proxies and compares
them to the FY 2000-based proxies.
[[Page 25441]]
Table 18.--Comparison of Price Proxies Used in the 2000-Based and the
Proposed 2003-Based Home Health Market Baskets
------------------------------------------------------------------------
2003-Based
Cost category 2000-Based price proposed price
proxy proxy
------------------------------------------------------------------------
Compensation, including
allocated contract services'
labor
Wages and Salaries, including Same................. Home Health
allocated contract services' Agency
labor Occupational
Wage Index.
Employee Benefits, including Same................. Home Health
allocated contract services' Agency
labor Occupational
Benefits Index.
Operations and Maintenance.... Same................. CPI-Fuel and
Other Utilities.
Administrative & General &
Other Expenses, including
allocated contract services'
labor
Telephone..................... Same................. CPI-U Telephone.
Postage....................... Same................. CPI-U Postage.
Professional Fees............. Same................. ECI for
Compensation for
Professional and
Technical
Workers.
Other Products................ Same................. CPI-U for All
Items Less Food
and Energy.
Other Services................ Same................. ECI for
Compensation for
Service Workers.
Transportation................ Same................. CPI-U Private
Transportation.
Capital-Related
Insurance..................... Same................. CPI-U Household
Insurance.
Fixed Capital................. Same................. CPI-U Owner's
Equivalent Rent.
Movable Capital............... Same................. PPI Machinery and
Equipment.
Contract Services............. Same................. Contained within
Wages &
Salaries,
Employee
Benefits,
Administrative &
General & Other
Expenses; see
those price
proxies.
------------------------------------------------------------------------
4. Rebasing Results
A comparison of the yearly changes from CY 2005 to CY 2008 for the
FY 2000-based home health market basket and the proposed FY 2003-based
home health market basket is shown in Table 19. The average annual
increase in the two market baskets is similar, and in no year is the
difference greater than 0.1 percentage point.
Table 19.--Comparison of The 2000-Based Home Health Market Basket and the Proposed 2003-Based Home Health Market
Basket, Percent Change, 2005-2008
----------------------------------------------------------------------------------------------------------------
Proposed home Difference
Home health health market (proposed 2003-
Fiscal years beginning October 1 market basket, basket, 2003- based less
2000-based based 2000-based)
----------------------------------------------------------------------------------------------------------------
Historical:
CY 2005......................................................... 3.1 3.1 0.0
CY 2006......................................................... 3.2 3.1 -0.1
CY 2007......................................................... 3.1 3.1 0.0
CY 2008......................................................... 2.9 2.9 0.0
Average Change: 2005-2008....................................... 3.1 3.1 0.0
----------------------------------------------------------------------------------------------------------------
Source: Global Insights, Inc, 4th Qtr, 2006.
Table 20 shows that the forecasted rate of growth for CY 2008,
beginning January 1, 2008, for the proposed rebased and revised home
health market basket is 2.9 percent, while the forecasted rate of
growth for the current 2000-based home health market basket is also 2.9
percent. As previously mentioned, we rebase the home health market
basket periodically so the cost category weights continue to reflect
changes in the mix of goods and services that HHAs purchase in
furnishing home health care.
Table 20.--Forecasted Annual Percent Change in the Current and Proposed Revised and Rebased Home Health Market
Baskets
----------------------------------------------------------------------------------------------------------------
Proposed home Difference
Home health health market (proposed 2003-
Calendar year beginning January 1 market basket, basket, 2003- based Less 2000-
2000-based based based)
----------------------------------------------------------------------------------------------------------------
January 2008, CY 2008........................................ 2.9 2.9 0.0
----------------------------------------------------------------------------------------------------------------
Source: Global Insights, Inc, 4th Qtr, 2006.
[[Page 25442]]
Table 21 shows the percent changes for CY 2008 for each cost
category in the home health market basket.
Table 21.--CY 2008 Forecasted Annual Percent Change for All Cost Categories in the Proposed 2003-Based Home
Health Market Basket
----------------------------------------------------------------------------------------------------------------
Forecasted
annual percent
Cost categories Weight Price proxy change for CY
2008
----------------------------------------------------------------------------------------------------------------
Total......................................... 100.00 ................................ 2.9
Compensation.................................. 77.082 ................................ 3.1
Wages and Salaries............................ 64.484 Proposed Home Health 2.9
Occupational Wage Index.
Employee Benefits............................. 12.598 Proposed Home Health 3.8
Occupational Benefits Index.
Operations & Maintenance...................... 0.694 CPI-U Fuel & Other Utilities.... 3.2
Administrative & General & Other Expenses..... 16.712 ................................ 2.6
Telephone..................................... 0.785 CPI-U Telephone Services........ 0.8
Postage....................................... 0.605 CPI-U Postage................... 4.8
Professional Fees............................. 1.471 ECI for Compensation for 3.0
Professional and Technical
Workers.
Other Products................................ 6.622 CPI-U All Items Less Food and 2.0
Energy.
Other Services................................ 7.228 ECI for Compensation for Service 3.1
Workers.
Transportation................................ 2.494 CPI-U Private Transportation.... 0.5
Capital-Related............................... 3.018 ................................ 1.8
Insurance..................................... 0.510 CPI-U Household Insurance....... 2.6
Fixed Capital................................. 1.618 CPI-U Owner's Equivalent Rent... 2.6
Movable Capital............................... 0.890 PPI Machinery & Equipment....... -0.3
----------------------------------------------------------------------------------------------------------------
Source: Global Insights, Inc, 4th Qtr, 2006.
5. Labor-Related Share
In the 2000-based home health market basket the labor-related share
was 76.775 percent while the remaining non-labor-related share was
23.225 percent. In the proposed revised and rebased home health market
basket, the labor-related share would be 77.082 percent. The labor-
related share includes wages and salaries and employee benefits. The
proposed non-labor-related share would be 22.918 percent. The increase
in the labor-related share using the FY 2003-based HH market basket is
primarily due to the increase in the benefit cost weight. Our
preliminary analysis of Medicare cost report data for skilled nursing
facilities and acute care hospitals also shows a similar upward trend
for the SNF and hospital benefit cost weights from FY 2000 to FY 2003.
Table 22 details the components of the labor-related share for the
FY 2000-based and proposed FY 2003-based home health market baskets.
Table 22.--Labor-Related Share of Current and Proposed Home Health
Market Baskets
------------------------------------------------------------------------
2000-based Proposed 2003-
Cost category market basket based market
weight basket weight
------------------------------------------------------------------------
Wages and Salaries...................... 65.766 64.484
Employee Benefits....................... 11.009 12.598
-------------------------------
Total Labor Related................. 76.775 77.082
-------------------------------
Total Non-Labor Related............. 23.225 22.918
------------------------------------------------------------------------
C. National Standardized 60-Day Episode Payment Rate
The Medicare HH PPS has been effective since October 1, 2000. As
set forth in the final rule published July 3, 2000 in the Federal
Register (65 FR 41128), the unit of payment under the Medicare HH PPS
is a national standardized 60-day episode payment rate. As set forth in
Sec. 484.220, we adjust the national standardized 60-day episode
payment rate by a case-mix grouping and a wage index value based on the
site of service for the beneficiary. The proposed CY 2008 HH PPS rates
use the case-mix methodology proposed in section II.A.2 of this
proposed rule and application of the wage index adjustment to the labor
portion of the HH PPS rates as set forth in the July 3, 2000 final
rule. As stated above, we are proposing to rebase and revise the home
health market basket, resulting in a revised and rebased labor related
share of 77.082 percent and a non-labor portion of 22.918 percent. We
multiply the national standardized 60-day episode payment rate by the
patient's applicable case-mix weight. We divide the case-mix adjusted
amount into a labor and non-labor portion. We multiply the labor
portion by the applicable wage index based on the site of service of
the beneficiary.
For CY 2008, we are proposing to base the wage index adjustment to
the labor portion of the HH PPS rates on the most recent pre-floor and
pre-reclassified hospital wage index as discussed in section II.B of
this proposed rule (not including any reclassifications under section
1886(d)(8)(B)) of the Act.
As discussed in the July 3, 2000 HH PPS final rule, for episodes
with four or
[[Page 25443]]
fewer visits, Medicare pays the national per-visit amount by
discipline, referred to as a LUPA. We update the national per-visit
amounts by discipline annually by the applicable home health market
basket percentage. We adjust the national per-visit amount by the
appropriate wage index based on the site of service for the beneficiary
as set forth in Sec. 484.230. We propose to adjust the labor portion
of the updated national per-visit amounts by discipline used to
calculate the LUPA by the most recent pre-floor and pre-reclassified
hospital wage index, as discussed in section II.D of this proposed
rule.
Medicare pays the 60-day case-mix and wage-adjusted episode payment
on a split percentage payment approach. The split percentage payment
approach includes an initial percentage payment and a final percentage
payment as set forth in Sec. 484.205(b)(1) and (b)(2). We may base the
initial percentage payment on the submission of a request for
anticipated payment and the final percentage payment on the submission
of the claim for the episode, as discussed in Sec. 409.43. The claim
for the episode that the HHA submits for the final percentage payment
determines the total payment amount for the episode and whether we make
an applicable adjustment to the 60-day case-mix and wage-adjusted
episode payment. The end date of the 60-day episode as reported on the
claim determines which CY rates Medicare will use to pay the claim.
We may also adjust the 60-day case-mix and wage-adjusted episode
payment based on the information submitted on the claim to reflect the
following:
A LUPA provided on a per-visit basis as set forth in Sec.
484.205(c) and Sec. 484.230.
A PEP adjustment as set forth in Sec. 484.205(d) and
Sec. 484.235.
An outlier payment as set forth in Sec. 484.205(f) and
Sec. 484.240.
Currently, we may also adjust the episode payment by a SCIC
adjustment as set forth in Sec. 484.202, but as noted in section
II.A.6 of this proposed rule, we are now proposing to remove the SCIC
adjustment from HH PPS.
This proposed rule reflects the proposed updated CY 2008 rates that
would be effective January 1, 2008.
D. Proposed CY 2008 Rate Update by the Home Health Market Basket Index
(With Examples of Standard 60-Day and LUPA Episode Payment
Calculations)
Section 1895(b)(3)(B) of the Act, as amended by section 5201 of the
DRA, requires for CY 2008 that the standard prospective payment amounts
be increased by a factor equal to the applicable home health market
basket update for those HHAs that submit quality data as required by
the Secretary. The applicable home health market basket update will be
reduced by 2 percentage points for those HHAs that fail to submit the
required quality data.
Proposed CY 2008 Adjustments
In calculating the annual update for the CY 2008 national
standardized 60-day episode payment rates, we are proposing to first
look at the CY 2007 rates as a starting point. The CY 2007 national
standardized 60-day episode payment rate is $2,339.00.
In order to calculate the CY 2008 national standardized 60-day
episode payment rate, we are proposing to first increase the CY 2007
national standardized 60-day episode payment rate ($2,339.00) by the
proposed estimated rebased and revised home health market basket update
of 2.9 percent for CY 2008.
Given this updated rate, we would then take a reduction of 2.75
percent to account for nominal change in case-mix. We would multiply
the resulting value by 1.05 and 0.958614805 to account for the
estimated percentage of outlier payments as a result of the current FDL
ratio of 0.67 (that is, $2,339.00 * 1.029 * .9725 * 1.05 *
0.958614805), to yield an updated CY 2008 national standardized 60-day
episode payment rate of $2,355.96 for episodes that begin in CY 2007
and end in CY 2008 (see Table 23a). For episodes that begin in CY 2007
and end in CY 2008, the new proposed 153 HHRG case-mix model (and
associated Grouper) would not yet be in effect. For that reason, we
propose that episodes that begin in CY 2007 and end in CY 2008 be paid
at the rate of $2,355.96, and be further adjusted for wage differences
and for case-mix, based on the current 80 HHRG case-mix model. We
recognize that the annual update for CY 2008 is for all episodes that
end on or after January 1, 2008 and before January 1, 2009. By paying
this rate ($2,355.96) for episodes that begin in CY 2007 and end in CY
2008, we will have appropriately recognized that these episodes are
entitled to receive the CY 2008 home health market, even though the new
case-mix model will not yet be in effect.
Table 23a.--Proposed National 60-Day Episode Amounts Updated by the Estimated Home Health Market Basket Update
for CY 2008, Before Case-Mix Adjustment, Wage Index Adjustment Based on the Site of Service for the Beneficiary
or Applicable Payment Adjustment for Episodes Beginning in CY 2007 and Ending in CY 2008
----------------------------------------------------------------------------------------------------------------
Proposed
national
Multiply by standardized
the proposed Reduce by 2.75 Adjusted to 60-day episode
Total CY 2007 national standardized 60-day estimated home percent for account for payment rate
episode payment rate health market nominal change the 5 percent for episodes
basket update in case-mix outlier policy beginning in
(2.9 percent) CY 2007 and
\1\ ending in CY
2008
----------------------------------------------------------------------------------------------------------------
$2,339.00....................................... x 1.029 x 0.9725 x 1.05 $2,355.96
x 0.958614805
----------------------------------------------------------------------------------------------------------------
\1\ The estimated home health market basket update of 2.9 percent for CY 2008 is based on Global Insight, Inc,
4th Qtr, 2006 forecast with historical data through 3rd Qtr, 2006.
Next, in order to establish new rates based on a proposed new case-
mix system, we again start with the CY 2007 national standardized 60-
day episode payment rate and increase that rate by the proposed
estimated rebased and revised home health market basket update (2.9
percent) ($2,339.00 * 1.029 = $2,406.83). We next have to put dollars
associated with the outlier targeted estimates back into the base rate.
In the 2000 HH PPS final rule (65 FR 41184), we divided the base rate
by 1.05 to account for the outlier target policy. Therefore, we are
proposing to
[[Page 25444]]
multiply the $2,406.83 by 1.05, resulting in $2,527.17. Next we need to
reduce this amount to pay for each of our proposed policies. As noted
previously, based upon our proposed change to the LUPA payment, the NRS
redistribution, the elimination of the SCIC policy, the amounts needed
to account for outlier payments, and the reduction accounting for
nominal change in case-mix, we would reduce the national standardized
60-day episode payment rate by $6.46, $40.88, $15.71, $94.02, and
$69.50, respectively. This results in a proposed CY 2008 updated
national standardized 60-day episode payment rate, for episodes
beginning and ending in CY 2008, of $2,300.60 (see Table 23b). These
episodes would be further adjusted for case-mix based on the proposed
153 HHRG case-mix model for episodes beginning and ending in CY 2008.
As we noted in section II.A.2.d., we increased the case-mix weights by
a budget neutrality factor of 1.194227193.
Table 23b.--Proposed National 60-Day Episode Amounts Updated by the Estimated Home Health Market Basket Update for CY 2008, Before Case-Mix Adjustment,
Wage Index Adjustment Based on the Site of Service for the Beneficiary or Applicable Payment Adjustment for Episodes Beginning and Ending in CY 2008
--------------------------------------------------------------------------------------------------------------------------------------------------------
Changes to account
for LUPA
adjustment
($6.46), NRS
payment ($40.88),
elimination of Proposed CY 2008
Adjusted to return Updated and SCIC policy national
Multiply by the the outlier funds outlier adjusted ($15.71), standardized 60-
Total CY 2007 national standardized 60-day episode proposed estimated to the national national maintaining a 0.67 day episode
payment rate home health market standardized 60- standardized 60- FDL ratio payment rate for
basket update day episode day episode ($94.02), and 2.75 episodes beginning
(2.9 percent) \1\ payment rate payment percent reduction and ending in CY
for nominal change 2008
in case-mix
($69.50) for
episodes beginning
and ending in CY
2008
--------------------------------------------------------------------------------------------------------------------------------------------------------
$2,339.00........................................... x 1.029 x 1.05 $2,527.17 -$226.57 $2,300.60
--------------------------------------------------------------------------------------------------------------------------------------------------------
\1\ The estimated home health market basket update of 2.9 percent for CY 2008 is based on Global Insight, Inc, 4th Qtr, 2006 forecast with historical
data through 3rd Qtr, 2006.
Under the HH PPS, NRS payment, which was $49.62 at the onset of the
HH PPS, has been updated yearly as part of the national standardized
60-day episode payment rate. As discussed previously in section
II.A.7., we propose to remove the current NRS payment amount portion
from the national standardized 60-day episode payment rate and add a
severity adjusted NRS payment amount subject to case-mix and wage
adjustment to the national standardized 60-day episode payment rate.
Therefore, to calculate an episode's prospective payment amount, the
NRS adjusted payment amount must first be calculated by multiplying the
episode's NRS weight (taken from Table 11 of this proposed rule) by the
NRS conversion factor. This NRS adjusted payment amount is then added
to, and, becomes a part of, the non-adjusted HH PPS standardized
prospective payment rate for CY 2008. Then, for any HHRG group, to
compute a case-mix adjusted payment, the sum of the non-adjusted
national standardized 60-day episode payment rate and the NRS adjusted
payment amount are multiplied by the appropriate case-mix weight taken
from Table 5. Finally, to compute a wage adjusted national standardized
60-day episode payment rate, that labor-related portion of the national
standardized 60-day episode payment rate for CY 2008 is multiplied by
the appropriate wage index factor listed in Addendum A. The product of
that calculation is added to the corresponding non-labor-related
amount. The resulting amount is the national case-mix and wage adjusted
national standardized 60-day episode payment rate for that particular
episode. The following example illustrates the computation described
above:
Example 1. An HHA is providing services to a Medicare
beneficiary in Grand Forks, ND. The national standardized payment
rate is $2,300.60 (see Table 23). The HHA determines that the
beneficiary is in his or her 3rd episode and thus falls under the
C1F3S3 HHRG for 3rd+ episodes with 0 to 13 therapy visits (Case Mix
Weight = 1.4815). It is also determined that the beneficiary falls
under NRS severity level 4. The NRS Severity Level
4 weight = 6.9612 and the NRS Conversion Factor = $52.77
(see Table 11).
BILLING CODE 4120-01-P
[[Page 25445]]
[GRAPHIC] [TIFF OMITTED] TP04MY07.039
[[Page 25446]]
National Per-visit Amounts Used to Pay LUPAs and Compute
Imputed Costs Used in Outlier Calculations
As discussed previously in this proposed rule, the policies
governing LUPAs and the outlier calculations set forth in the July 3,
2000 HH PPS final rule will continue (65 FR 41128) with an increase of
$92.63 for initial and only episode LUPAs during CY 2008. In
calculating the proposed CY 2008 national per-visit amounts used to
calculate payments for LUPA episodes and to compute the imputed costs
in outlier calculations, we are proposing to start with the CY 2007
per-visit amounts. We propose to increase the CY 2007 per-visit amounts
for each home health discipline for CY 2008 by the proposed estimated
rebased and revised home health market basket update (2.9 percent),
then multiply by 1.05 and 0.958614805 to account for the estimated
percentage of outlier payments as a result of the current FDL ratio of
0.67 (see Table 24).
Table 24.--Proposed National Per-Visit Amounts for LUPAs (Not Including the Increase in Payment for a
Beneficiary's Only Episode or the Initial Episode in a Sequence of Adjacent Episodes) and Outlier Calculations
Updated by the Estimated Home Health Market Basket Update for CY 2008, Before Wage Index Adjustment Based on the
Site of Service for the Beneficiary
----------------------------------------------------------------------------------------------------------------
Multiply by the
Final CY 2007 proposed Adjusted to Proposed CY
per-visit estimated home account for the 2008 per-visit
Home health discipline type amounts per 60- health market 5 percent payment amount
day episode for basket (2.9 outlier policy per discipline
LUPAs percent) \1\
----------------------------------------------------------------------------------------------------------------
Home Health Aide............................ $46.24 x 1.029 x 1.05 $47.91.
x 0.958614805
Medical Social Services..................... 163.68 x 1.029 x 1.05 169.53.
x 0.958614805
Occupational Therapy........................ 112.40 x 1.029 x 1.05 116.42.
x 0.958614805
Physical Therapy............................ 111.65 x 1.029 x 1.05 115.63.
x 0.958614805
Skilled Nursing............................. 102.11 x 1.029 x 1.05 105.76.
x 0.958614805
Speech-Language Pathology................... 121.22 x 1.029 x 1.05 125.55.
x 0.958614805
----------------------------------------------------------------------------------------------------------------
\1\ The estimated home health market basket update of 2.9 percent for CY 2008 is based on Global Insight, Inc,
4th Qtr, 2006 forecast with historical data through 3rd Qtr, 2006.
Payment for LUPA episodes is changed in that for LUPAs that occur
as initial episodes in a sequence of adjacent episodes or as the only
episode, we are proposing an increased payment amount (see section
II.A.5. of this proposed regulation) to the LUPA payment. Table 24
rates are before that adjustment and are the rates paid to all other
LUPA episodes. LUPA episodes that occur as the only episode or initial
episode in a sequence of adjacent episodes are adjusted by including
the proposed amount of $92.63 to the LUPA payment before adjusting for
wage index.
Example 2. An HHA is providing services to a Medicare
beneficiary in rural New Hampshire. During the 60-day episode the
beneficiary receives only 3 visits. It is the initial episode during
a sequence of adjacent episodes for this beneficiary.
BILLING CODE 4120-01-P
[[Page 25447]]
[GRAPHIC] [TIFF OMITTED] TP04MY07.040
Outlier payments are determined and calculated using the same
methodology that has been used since the implementation of the HH PPS.
E. Hospital Wage Index
Sections 1895(b)(4)(A)(ii) and (b)(4)(C) of the Act require the
Secretary to
[[Page 25448]]
establish area wage adjustment factors that reflect the relative level
of wages and wage-related costs applicable to the furnishing of home
health services and to provide appropriate adjustments to the episode
payment amounts under the HH PPS to account for area wage differences.
We apply the appropriate wage index value to the proposed labor portion
(77.082 percent; see Table 22) of the HH PPS rates based on the
geographic area where the beneficiary received the home health
services. As implemented under the HH PPS in the July 3, 2000 HH PPS
final rule, each HHA's labor market area is based on definitions of
Metropolitan Statistical Areas (MSAs) issued by the OMB.
In the August 11, 2004 IPPS final rule [69 FR 49206], revised labor
market area definitions were adopted at Sec. 412.64(b), which were
effective October 1, 2004 for acute care hospitals. The new standards,
Core Based Statistical Areas (CBSAs), were announced by OMB in late
2000 and were also discussed in greater detail in the July 14, 2005 HH
PPS proposed rule. For the purposes of the HH PPS, the term ``MSA-
based'' refers to wage index values and designations based on the
previous MSA designations. Conversely, the term ``CBSA-based'' refers
to wage index values and designations based on the new OMB revised MSA
designations which now include CBSAs. In the November 9, 2005 HH PPS
final rule (70 FR 68132), we implemented a 1-year transition policy
using a 50/50 blend of the CBSA-based wage index values and the MSA-
based wage index values for CY 2006. The one-year transition policy
ended in CY 2006. For CY 2008, we propose to use a wage index based
solely on the CBSA designations.
1. Background
As implemented under the HH PPS in the July 3, 2000 HH PPS final
rule, each HHA's labor market is determined based on definitions of
MSAs issued by OMB. In general, an urban area is defined as an MSA or
New England County Metropolitan Area (NECMA) as defined by OMB. Under
Sec. 412.64(b)(1)(ii)(C), a rural area is defined as any area outside
of the urban area. The urban and rural area geographic classifications
are defined in Sec. 412.64(b)(1)(ii)(A) and Sec. 412.64.(b)(1)(II)(C)
respectively, and have been used under the HH PPS since implementation.
Under the HH PPS, the wage index value used is based upon the
location of the beneficiary's home. As has been our longstanding
practice, any area not included in an MSA (urban area) is considered to
be non-urban Sec. 412.64(b)(1)(ii)(C) and receives the statewide rural
wage index value (see, for example, 65 FR 41173).
As discussed previously and set forth in the July 3, 2000 final
rule, the statute provides that the wage adjustment factors may be the
factors used by the Secretary for purposes of section 1886(d)(3)(E) of
the Act for hospital wage adjustment factors. As discussed in the July
3, 2000 final rule, we are proposing again to use the pre-floor and
pre-reclassified hospital wage index data to adjust the labor portion
of the HH PPS rates based on the geographic area where the beneficiary
receives home health services. We believe the use of the pre-floor and
pre-reclassified hospital wage index data results in the appropriate
adjustment to the labor portion of the costs as required by statute.
For the CY 2008 update to home health payment rates, we would continue
to use the most recent pre-floor and pre-reclassified hospital wage
index available at the time of publication.
In adopting the CBSA designations, we identified some geographic
areas where there are no hospitals, and thus no hospital wage data on
which to base the calculation of the home health wage index. Beginning
in CY 2006, we adopted a policy that, for urban labor markets without
an urban hospital from which a hospital wage index can be derived, all
of the urban CBSA wage index values within the State would be used to
calculate a statewide urban average wage index to use as a reasonable
proxy for these areas. Currently, the only CBSA that would be affected
by this policy is CBSA 25980, Hinesville, Georgia. We propose to
continue this policy for CY 2008.
2. Update
Currently, the only rural areas where there are no hospitals from
which to calculate a hospital wage index are Massachusetts and Puerto
Rico. For CY 2006, we adopted a policy in the HH PPS November 9, 2005
final rule (70 FR 68138) of using the CY 2005 pre-floor, pre-
reclassified hospital wage index value. In the August 3, 2006 proposed
rule, we again proposed to apply the CY 2005 pre-floor/pre-reclassified
hospital wage index to rural areas where no hospital wage data is
available. In response to commenters' concerns and in recognition that,
in the future, there may be additional rural areas impacted by a lack
of hospital wage data from which to derive a wage index, we adopted, in
the November 9, 2006 final rule (71 FR 65905), the following
methodology for imputing a rural wage index for areas where no hospital
wage data are available as an acceptable proxy. The methodology that we
implemented for CY 2007 imputed an average wage index value by
averaging the wage index values from contiguous CBSAs as a reasonable
proxy for rural areas with no hospital wage data from which to
calculate a wage index. We believe this methodology best meets our
criteria for imputing a rural wage index as well as representing an
appropriate wage index proxy for rural areas without hospital wage
data. Specifically, such a methodology uses pre-floor, pre-reclassified
hospital wage data, is easy to evaluate, is updateable from year to
year, and uses the most local data available. In determining an imputed
rural wage index, we define ``contiguous'' as sharing a border. For
Massachusetts, rural Massachusetts currently consists of Dukes and
Nantucket Counties. We determined that the borders of Dukes and
Nantucket counties are ``contiguous'' with Barnstable and Bristol
counties. We are again proposing to apply this methodology for imputing
a rural wage index for those rural areas without rural hospital wage
data. While we continue to believe that this policy could be readily
applied to other rural areas that lack hospital wage data (possibly due
to hospitals converting to a different provider type (such as a CAH)
that does not submit the appropriate wage data), we specifically
solicit comments on this issue.
However, as we noted in the HH PPS final rule for CY 2007, we did
not believe that this policy was appropriate for Puerto Rico. As noted
in the August 3, 2006 proposed rule, there are sufficient economic
differences between the hospitals in the United States and those in
Puerto Rico, including the fact that hospitals in Puerto Rico are paid
on blended Federal/Commonwealth-specific rates, that a separate
distinct policy for Puerto Rico is necessary. Consequently, any
alternative methodology for imputing a wage index for rural Puerto Rico
would need to take into account those differences. Our policy of
imputing a rural wage index by using an averaged wage index of CBSAs
contiguous to that rural area does not recognize the unique
circumstances of Puerto Rico. For CY 2008, we again propose to continue
to use the most recent wage index previously available for Puerto Rico
which is 0.4047.
The rural and urban hospital wage indexes can be found in Addenda A
and B of this proposed rule. For HH PPS rates addressed in this
proposed rule, we are using the 2007 pre-floor and pre-reclassified
hospital wage index data, as 2008 pre-floor and pre-reclassified
hospital wage index data are not yet
[[Page 25449]]
available. We propose to use the 2008 pre-floor and pre-reclassified
hospital wage index (not including any reclassification under section
1886(d)(8)(B) of the Act) to adjust rates for CY 2008 and will publish
those wage index values in the final rule.
F. Home Health Care Quality Improvement
Section 5201(c)(2) of the DRA added section 1895(b)(3)(B)(v)(II) to
the Act, requiring that ``each home health agency shall submit to the
Secretary such data that the Secretary determines are appropriate for
the measurement of health care quality. Such data shall be submitted in
a form and manner, and at a time, specified by the Secretary for
purposes of this clause.'' In addition, section 1895(b)(3)(B)(v)(I) of
the Act, as also added by section 5201(c)(2) of the DRA, dictates that
``for 2007 and each subsequent year, in the case of a home health
agency that does not submit data to the Secretary in accordance with
subclause (II) with respect to such a year, the home health market
basket percentage increase applicable under such clause for such year
shall be reduced by 2 percentage points.''
The OASIS data currently provide consumers and HHAs with 10
publicly-reported home health quality measures which have been endorsed
by the National Quality Forum (NQF). Reporting these quality data have
also required the development of several supporting mechanisms such as
the HAVEN software used to encode and transmit data using a CMS
standard electronic record layout, edit specifications, and data
dictionary. The HAVEN software includes the required OASIS data set
that has become a standard part of HHA operations. These early
investments in data infrastructure and supporting software that CMS and
HHAs have made over the past several years in order to create this
quality reporting structure have been successful in making quality
reporting and measurement an integral component of the HHA industry.
The 10 measures are--
Improvement in ambulation/locomotion;
Improvement in bathing;
Improvement in transferring;
Improvement in management of oral medications;
Improvement in pain interfering with activity;
Acute care hospitalization;
Emergent care;
Improvement in dyspnea;
Improvement in urinary incontinence; and
Discharge to community.
We are proposing to continue to use OASIS data and the current 10
quality measures, and to add two additional quality measures based on
those data for the CY 2008 HH PPS quality data reporting requirement.
Continuing to use the OASIS instrument ensures that providers will not
have an additional burden of reporting through a separate mechanism and
that the costs associated with the development and testing of a new
reporting mechanism can be avoided. Accordingly, for CY 2008, we
propose to continue to use submission of OASIS data to meet the
requirement that the HHA submit data appropriate for the measurement of
health care quality.
We specifically propose to add the following two additional quality
measures as data appropriate for measuring health care quality. Adding
new measures to the currently available outcome measures could broaden
the patient population we can assess, expand the types of quality care
we can measure, and capture an aspect of care directly under providers'
control. These two wound measures focus on a prevalent condition among
home health beneficiaries. We believe that by adding these two
measures, we can address agencies' ability to maintain patients in
their homes. These additional NQF endorsed measures that will provide a
more complete picture of the level of quality care delivered by HHAs
are the following:
Emergent Care for Wound Infections, Deteriorating Wound
Status; and
Improvement in Status of Surgical Wound.
The data elements used to calculate these measures are already
captured by the OASIS instrument and do not require additional
reporting or burden to HHAs.
Additionally, section 1895(b)(3)(B)(v)(II) of the Act provides the
Secretary with the discretion to submit the required data in a form,
manner, and time specified by him. We are proposing for CY 2008 to
consider OASIS data submitted by HHAs to CMS for episodes beginning on
or after July 1, 2006 and before July 1, 2007 as meeting the reporting
requirement for CY 2008. This reporting time period would allow 12 full
months of data and would provide us the time necessary to analyze and
make any necessary payment adjustments to the CY 2008 payment rates.
HHAs that meet the reporting requirement would be eligible for the full
home health market basket percentage increase.
We recognize, however, that the home health conditions of
participations (CoPs) in (42 CFR part 484) that require OASIS
submission also provide for exclusions from the CoP submission
requirement. Generally, agencies excluded from the CoP OASIS submission
requirement do not receive Medicare payments as they either do not
provide services to Medicare beneficiaries or the patients are not
receiving Medicare-covered home health services. Under the CoP,
agencies are excluded from the OASIS reporting requirement on
individual patients if--
Those patients are receiving only non-skilled services;
Neither Medicare nor Medicaid is paying for home health
care (patients receiving care under a Medicare or Medicaid Managed Care
Plan are not excluded from the OASIS reporting requirement);
Those patients are receiving pre- or post-partum services;
and
Those patients are under the age of 18 years.
We believe that the rationale behind the exclusion of these
agencies from submission of OASIS on patients which are excluded from
OASIS CoP submission is equally applicable to HHAs for quality
purposes. If an agency is not submitting OASIS for patients excluded
from OASIS submission for purposes of a CoP, we believe that the
submission of OASIS for quality measures for Medicare purposes is
likewise not necessary. Therefore, we propose that those agencies do
not need to submit quality measures for reporting purposes for those
patients who are excluded from the OASIS CoP submission.
Additionally, we propose that agencies newly certified (on or after
May 31, 2007 for payments to be made in CY 2008) be excluded from the
quality reporting requirement as data submission and analysis would not
be possible for an agency certified this late in the reporting time
period. We again propose that in future years, agencies that certify on
or after May 31 of the preceding year involved be excluded from any
payment penalty for quality reporting purposes for the following CY. We
note these exclusions only affect quality reporting requirements and do
not affect the agency's OASIS reporting responsibilities under the CoP.
We propose to require that all HHAs, unless covered by these
specific exclusions, meet the reporting requirement, or be subject to a
2 percent reduction in the home health market basket percentage
increase in accordance with section 895(b)(3)(B)(v)(I) of the Act. The
2 percent reduction would apply to all episode payments beginning on or
after
[[Page 25450]]
January 1, 2008. We provide the proposed reduced payment rates in
tables 25 and 26. We would reconcile the OASIS submissions with claims
data in order to verify full compliance with the quality reporting
requirements.
For episodes that begin in CY 2007 and end in CY 2008, the new
proposed 153 HHRG case-mix model (and associated Grouper) would not yet
be in effect. For that reason, we propose, for HHAs that do not submit
required quality data (for episodes that begin in CY 2007 and end in CY
2008), the following: First, we update the CY 2007 rate of $2,339.00 by
the home health market basket percentage update (2.9 percent) minus 2
percent, reduced by 2.75 percent to account for nominal change in case-
mix, and multiplied by 1.05 and 0.958614805 to account for the
estimated percentage of outlier payments as a result of the current FDL
ratio of 0.67 ($2,339.00 * 1.009 * .9725 * 1.05 * 0.958614805), to
yield an updated CY 2008 national standardized 60-day episode payment
rate of $2,310.17 for episodes that begin in CY 2007 and end in CY 2008
for HHAs that do not submit required quality data (see Table 25a).
These episodes would be further adjusted for case-mix based on the
80 HHRG case-mix model for episodes beginning in CY 2007 and ending in
CY 2008.
Table 25a.--For HHAs That Do Not Submit The Required Quality Data-Proposed National 60-Day Episode Amounts
Updated by the Estimated Home Health Market Basket Update for CY 2008, Minus 2 Percentage Points, For Episodes
that Begin in CY 2007 and End in CY 2008 Before Case-Mix Adjustment, Wage Index Adjustment Based on the Site of
Service for the Beneficiary or Applicable Payment Adjustment
----------------------------------------------------------------------------------------------------------------
Proposed
national
standardized
Multiply by 60-day episode
the proposed payment rate
estimated home Reduce by 2.75 Adjusted to for episodes
Total CY 2007 national standardized 60-Day health market percent for account for beginning in
episode payment rate basket update nominal change the 5 percent CY 2007 and
(2.9 in case-mix outlier policy ending in CY
percent)\1\ 2008 for HHAs
Minus 2 that do not
percent submit
required
quality data
----------------------------------------------------------------------------------------------------------------
$2,339.00....................................... x 1.009 x 0.9725 x 1.05 $2,310.17
x 0.958614805
----------------------------------------------------------------------------------------------------------------
\1\ The estimated home health market basket update of 2.9 percent for CY 2008 is based on Global Insight, Inc,
4th Qtr, 2006 forecast with historical data through 3rd Qtr, 2006.
Next, in order to establish new rates based on a proposed new case-
mix system, we again start with the CY 2007 national standardized 60-
day episode payment rate and increase that rate by the proposed
estimated rebased and revised home health market basket update (2.9
percent) minus 2 percent ($2,339.00 * 1.009 = $2,360.05). We next have
to put dollars associated with the outlier target estimate back into
the base rate. In the 2000 HH PPS final rule (65 FR 41184), we divided
the base rate by 1.05 to account for outlier payments. Therefore, we
are proposing to multiply the $2,360.05 by 1.05, resulting in
$2,478.05. Next we need to reduce this amount to pay for each of our
proposed policies. To do this, we take the payment adjustment amount to
pay for our proposed policies of this rule, determined in Table 23a of
$226.57, multiply it by (1/1.029) to take away the 2.9 percent
increase, and multiply that number by 1.009 to impose the 0.9 percent
update for episodes where HHAs have not submitted the required quality
data. This results in a payment adjustment amount of $222.17. Finally,
subtract the payment adjustment amount of $222.17 from $2,478.05, for a
final rate of $2,255.88 for HHAs that do not submit quality data, for
episodes that begin and end in CY 2008.
These episodes would be further adjusted for case-mix based on the
153 HHRG case-mix model for episodes beginning and ending in CY 2008.
As we noted in section II.A.2.d., we increased the case-mix weights by
a budget neutrality factor of 1.194227193.
[[Page 25451]]
Table 25b.--for HHAs That Do Not Submit The Requried Quality Data-Proposed National 60-day Episode Amounts Updated by the Estimated Home Health Market
Basket Update for CY 2008, Minus 2 Percentage Points, For Episodes that Begin and End in CY 2008, Before Case-Mix Adjustment, Wage Index Adjustment
Based on the Site of Service for the Beneficiary or Applicable Payment Adjustment
--------------------------------------------------------------------------------------------------------------------------------------------------------
Changes to
account for
LUPA adjustment
($6.46), NRS
payment
($40.88),
elimination of
SCIC policy
($15.71),
outlier target Proposed CY
Adjusted to Updated and ($94.02), and 2008 national
Multiply by the return the outlier 2.75 percent standardized 60-
proposed outlier funds adjusted reduction for day episode
Total CY 2007 national standardized 60-day episode payment rate estimated home to the national national nominal change payment rate
health market standardized 60- standardized 60- in case-mix for episodes
basket update day episode day episode ($69.50) = beginning and
(2.9 percent) 1 payment rate payment $226.57; minus ending in CY
2 percentage 2008
points off of
the home health
market basket
update (2.9
Percent) 1 for
episodes
beginning and
ending in CY
2008
--------------------------------------------------------------------------------------------------------------------------------------------------------
$2,339.00.......................................................... x 1.009 x 1.05 $2,478.05 -$222.17 $2,255.88
--------------------------------------------------------------------------------------------------------------------------------------------------------
1 The estimated home health market basket update of 2.9 percent for CY 2008 is based on Global Insight, Inc, 4th Qtr, 2006 forecast with historical data
through 3rd Qtr, 2006.
In calculating the proposed CY 2008 national per-visit amounts used
to calculate payments for LUPA episodes for HHAs that do not submit
required quality data and to compute the imputed costs in outlier
calculations for those episodes, we are proposing to start with the CY
2007 per-visit rates. We propose to multiply those amounts by the
proposed estimated home health market basket update (2.9 percent) minus
2 percentage points, then multiply by 1.05 and 0.958614805 to account
for the estimated percentage of outlier payments as a result of the
current FDL ratio of 0.67, to yield the updated per-visit amounts for
each home health discipline for CY 2008 for HHAs that do not submit
required quality data.
Table 26.--For HHAs That Do Not Submit the Required Quality Data-Proposed National Per-Visit Amounts for LUPAs
(Not Including the Increase in Payment for a Beneficiary's Only Episode or the Initial Episode in a Sequence of
Adjacent Episodes) and Outlier Calculations Updated by the Estimated Home Health Market Basket Update for CY
2008, Minus 2 Percentage Points, Before Wage Index Adjustment Based on the Site of Service for the Beneficiary
----------------------------------------------------------------------------------------------------------------
Proposed CY
2008 per-visit
payment amount
Multiply by the per discipline
Final CY 2007 proposed Adjusted to for a
per-visit estimated home account for the beneficiary who
Home health discipline type amounts per 60- health market 5 percent resides in a
day episode for basket (2.9 outlier policy non-MSA for
LUPAs percent) 1 HHAs that do
not submit
required
quality data
----------------------------------------------------------------------------------------------------------------
Home Health Aide............................ $46.24 x1.009 x1.05 $46.96
x0.958614805 .
Medical Social Services..................... 163.68 x1.009 x1.05 166.23
x 0.958614805 ...............
Occupational Therapy........................ 112.40 x1.009 x10.5 114.15
x0.958614805 ...............
Physical Therapy............................ 111.65 x1.009 x 1.05 113.39
x0.958614805 ...............
Skilled Nursing............................. 102.11 x1.009 x1.05 103.70
............... ............... x0.958614805 ...............
[[Page 25452]]
Speech-Language Pathology................... 121.22 x1.009 x1.05 123.11
x0.958614805 ...............
----------------------------------------------------------------------------------------------------------------
The estimated home health market basket update of 2.9 percent for CY 2008 is based on Global Insight, Inc, 4th
Qtr, 2006 forecast with historical data through 3rd Qtr, 2006.
Section 1895(b)(3)(B)(v)(III) of the Act further requires that the
``Secretary shall establish procedures for making data submitted under
subclause (II) available to the public.'' Additionally, the statute
requires that ``such procedures shall ensure that a home health agency
has the opportunity to review the data that is to be made public with
respect to the agency before such data being made public.'' To meet the
requirement for making such data public, we are proposing to continue
to use the Home Health Compare Web site whereby HHAs are listed
geographically.
Currently, the 10 existing quality measures are posted on the Home
Health Compare Web site. The Home Health Compare Web site will also
include the two proposed additional measures discussed earlier.
Consumers can search for all Medicare-approved home health providers
that serve their city or zip code and then find the agencies offering
the types of services they need as well as the proposed quality
measures. See http://www.medicare.gov/HHCompare/Home.asp. HHAs
currently have access (through the Home Health Compare contractor) to
their own agency's quality data (updated periodically) and we propose
to continue this process thus enabling each agency to know how it is
performing before public posting of data on the Home Health Compare Web
site.
Over the next year, we will be testing patient level process
measures for HHAs, as well as continuing to refine the current OASIS
tool in response to recommendations from a TEP conducted to review the
data elements that make up the OASIS tool. We expect to introduce these
complementary additional measures during CY 2008 to determine if they
should be incorporated into the statutory quality measure reporting
requirements. We hope to apply these measures to the CY 2010 reporting
period. Before usage in the HH PPS, we will test and refine these
measures to determine if they can more accurately reflect the level of
quality care being provided at HHAs without being overly burdensome
with the data collection instrument. To the extent that evidence-based
data are available on which to determine the appropriate measure
specifications, and adequate risk-adjustments are made, we anticipate
collecting and reporting these measures as part of each agency's home
health quality plan. We believe that future modifications to the
current OASIS tool, refinements to the possible responses as well as
adding new process measures will be made. In all cases, we anticipate
that any future quality measures should be evidence-based, clearly
linked to improved outcomes, and able to be reliably captured with the
least burden to the provider. We are also working on developing
measures of patient experience in the home health setting through the
development of the Home Health Consumer Assessment of Healthcare
Providers and Systems (CAHPS) Survey. We will be working with the
Agency for Healthcare Research and Quality (AHRQ) to field test this
instrument in summer/fall 2007. We anticipate implementing the Home
Health CAHPS Survey in late 2008 for potential application to the CY
2010 pay for reporting requirements.
III. Collection of Information Requirements
Under the Paperwork Reduction Act (PRA) of 1995, we are required to
provide 60-day notice in the Federal Register and solicit public
comment before a collection of information requirement is submitted to
the Office of Management and Budget (OMB) for review and approval. In
order to fairly evaluate whether an information collection should be
approved by OMB, section 3506(c)(2)(A) of the PRA of 1995 requires that
we solicit comment on the following issues:
The need for the information collection and its usefulness
in carrying out the proper functions of our agency.
The accuracy of our estimate of the information collection
burden.
The quality, utility, and clarity of the information to be
collected.
Recommendations to minimize the information collection
burden on the affected public, including automated collection
techniques.
Therefore, we are soliciting public comments on each of these
issues for the information collection requirements discussed below.
To implement the OASIS changes discussed in sections II.A.(2)(a),
II.A.(2)(b), and II.A.(2)(c) of this proposed rule, which are currently
approved in Sec. 484.55, Sec. 484.205, and Sec. 484.250, a few items
in the OASIS will need to be modified, deleted, or added. The
requirements and burden associated with the OASIS are currently
approved under OMB control number 0938-0760 with an expiration date of
August 31, 2007. We are soliciting public comment on each of the
proposed changes for the information collection requirements (ICRs) as
summarized and discussed below. For the purposes of soliciting public
review and comment, we have placed a current draft of the proposed
changes to the OASIS on the CMS Web site at: http://www.cms.hhs.gov/
[[Page 25453]]
PaperworkReductionActof1995/PRAL/list.aspTopOfPage.
As discussed in section II.A.(2)(a) of this proposed rule, in order
for the OASIS to have the information necessary to allow the grouper to
price-out the claim, we propose to make the following changes to the
OASIS to capture whether an episode is an early or later episode:
The creation of a new OASIS item to capture whether a particular
assessment, is for an episode considered to be an early episode or a
later episode in the patient's current sequence of adjacent Medicare
home health payment episodes. As defined in section II.A.1. of this
proposed rule, we defined a sequence of adjacent episodes for a
beneficiary as a series of claims with no more than 60-days without
home care between the end of one episode, which is the 60th day (except
for episode that have been PEP-adjusted), and the beginning of the next
episode. This definition holds true regardless of whether or not the
same HHA provided care for the entire sequence of adjacent episodes.
The HHA will chose from the options: ``Early'' for single episodes or
the first or second episode in a sequence of adjacent episodes,
``Later'' for third or later episodes, ``UK'' for unknown if the HHA is
uncertain as to whether the episode is an early or later episode (the
payment grouper software will default to the definition of an ``early''
episode), and ``NA'' for not applicable (no Medicare case-mix group to
be defined by this assessment).
As discussed in section II.A.(2)(b) of this proposed rule, we
propose to make changes to the OASIS in order to enable agencies to
report secondary case-mix diagnosis codes. The proposed changes clarify
how to appropriately fill out OASIS items M0230 and M0240, using ICD-9-
CM sequencing requirements if multiple coding is indicated for any
diagnosis. Additionally, if a V-code is reported in place of a case-mix
diagnosis for OASIS item M0230 or M0240, then the new optional OASIS
item (which is replacing existing OASIS item M0245) may then be
completed. A case-mix diagnosis is a diagnosis that determines the HH
PPS case-mix group.
As discussed in section II.A.(2)(c) of this proposed rule, we
propose to make changes to the OASIS to capture the projected total
number of therapy visits for a given episode. With the projected total
number of therapy visits, the payment grouper would be able to group
that episode into the appropriate case-mix group for payment. The
existing OASIS item M0825 asks an HHA if the projected number of
therapy visits would meet the therapy threshold or not. As noted
previously, we propose to delete OASIS item M0825 and replace it with a
new OASIS item. The OASIS item would ask the following: ``In the plan
of care for the Medicare payment episode for which this assessment will
define a case-mix group, what is the indicated need for therapy visits
(total of reasonable and necessary physical, occupational, and speech-
pathology visits combined)?'' The HHA would provide the total number of
projected therapy visits for that Medicare payment episode, unless not
applicable (that is, no case-mix group defined by this assessment). The
HHA would enter ``000'' if no therapy visits were projected for that
particular episode.
The burden associated with the proposed changes discussed in
sections II.A.(2)(a), II.A.(2)(b), and II.A.(2)(c) of this rule
includes possible training of staff, the time and effort associated
with downloading a new form and replacing previously pre-printed
versions of the OASIS, and utilizing updated vendor software. However,
as stated above, CMS would be removing or modifying existing questions
in the OASIS data set to accommodate the proposed requirements
referenced above. In addition, as a result of the proposed changes of
this rule, we expect that the claims processing system is expected to
automatically adjust the therapy visits, upward and downward on the
final claim, according to the information on the final claim.
Consequently, the HHA would no longer have to withdraw and resubmit
a revised claim when the number of therapy visits delivered to the
patient is higher than the level report on the RAP. Therefore, CMS
believes the burden increase associated with these changes is negated
by the removal or modification of several current data items.
We have submitted a copy of this proposed rule to OMB for its
review of the information collection requirements described above.
These requirements are not effective until OMB has approved them.
If you comment on any of these information collection and record
keeping requirements, please mail copies directly to the following:
Centers for Medicare & Medicaid Services, Office of Strategic
Operations and Regulatory Affairs, Regulations Development Group,
Attn.: Melissa Musotto, CMS-1541-P, Room C4-26-05, 7500 Security
Boulevard, Baltimore, MD 21244-1850; and Office of Information and
Regulatory Affairs, Office of Management and Budget, Room 10235, New
Executive Office Building, Washington, DC 20503, Attn: Carolyn Lovett,
CMS Desk Officer, (CMS-1541-P), carolyn_lovett@omb.eop.gov. Fax (202)
395-6974.
IV. Response to Comments
Because of the large number of public comments normally receive on
Federal Register documents, we are not able to acknowledge or respond
to them individually. We will consider all comments we receive by the
date and time specified in the DATES section of this proposed rule,
and, when we proceed with subsequent document, we will respond to the
comments in the preamble to that document.
V. Regulatory Impact Analysis
[If you choose to comment on issues in this section, please include
the caption ``REGULATORY IMPACT ANALYSIS'' at the beginning of your
comments.]
A. Overall Impact
We have examined the impacts of this rule as required by Executive
Order 12866 (September 1993, Regulatory Planning and Review), the
Regulatory Flexibility Act (RFA) (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.
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 (RIA) must be prepared for major rules with
economically significant effects ($100 million or more in any 1 year).
This proposed rule would be a major rule, as defined in Title 5, United
States Code, section 804(2), because we estimate the impact to the
Medicare program, and the annual effects to the overall economy, would
be more than $100 million. The update set forth in this proposed rule
would apply to Medicare payments under the HH PPS in CY 2008.
Accordingly, the following analysis describes the impact in CY 2008
only. We estimate that the net impact of the proposals in this rule,
including a 2.75 percent reduction to the case-mix weights to account
for nominal increase in case-mix, is estimated to be
[[Page 25454]]
approximately $140 million in CY 2008 expenditures. That estimate
incorporates the 2.9 percent home health market basket increase (an
estimated additional $410 million in CY 2008 expenditures attributable
only to the CY 2008 proposed estimated home health market basket
update), an estimated additional $130 million due to the increase in
the HH PPS rates as a result of maintaining a FDL ratio of 0.67, and
the 2.75 percent decrease (-$400 million for the first year of a 3-year
phase-in) to the HH PPS national standardized 60-day episode rate to
account for the nominal increase in case-mix under the HH PPS. Given
that we allowed for a FDL ratio of 0.67, all HH PPS rates were adjusted
slightly upward by a factor of 0.008614805. Column 6 of Table 27
displays a 0.95 percent increase in expenditures when comparing the CY
2007 current system to the proposed revised CY 2008 system. This
equates to approximately $140 million and is driven primarily by the
adjustment made to maintain the FDL ratio at 0.67 and partially by the
difference between the 2.9 percent update and the 2.75 percent
reduction to the HH PPS rates.
The RFA requires agencies to analyze options for regulatory relief
of small businesses. For purposes of the RFA, small entities include
small businesses, nonprofit organizations, and small governmental
jurisdictions. Most hospitals and most other providers and suppliers
are small entities, either by nonprofit status or by having revenues of
$6 million to $29 million in any 1 year. For purposes of the RFA,
approximately 75 percent of HHAs are considered small businesses
according to the Small Business Administration's size standards with
total revenues of $11.5 million or less in any 1 year. Individuals and
States are not included in the definition of a small entity. As stated
above, this proposed rule would have an estimated positive effect upon
small entities that are HHAs.
In addition, section 1102(b) of the Act requires us to prepare a
regulatory impact analysis if a rule may have a significant impact on
the operations of a substantial number of small rural hospitals. This
analysis must conform to the provisions of section 603 of the RFA. For
purposes of section 1102(b) of the Act, we define a small rural
hospital as a hospital that is located outside of a Metropolitan
Statistical Area and has fewer than 100 beds. We have determined that
this proposed rule would not have a significant economic impact on the
operations of a substantial number of small rural hospitals.
Section 202 of the Unfunded Mandates Reform Act of 1995 also
requires that agencies assess anticipated costs and benefits before
issuing any rule that may result in expenditure in any 1 year by State,
local, or tribal governments, in the aggregate, or by the private
sector, of $110 million. We believe this proposed rule would not
mandate expenditures in that amount.
Executive Order 13132 establishes certain requirements that an
agency must meet when it promulgates a proposed rule (and subsequent
final rule) that imposes substantial direct requirement costs on State
and local governments, preempts State law, or otherwise has Federalism
implications. We have determined that this proposed rule would not have
substantial direct effects on the rights, roles, and responsibilities
of States.
B. Anticipated Effects
This proposed rule would update the HH PPS rates contained in the
CY 2007 final rule (71 FR 65884, November 9, 2006). The impact analysis
of this proposed rule presents the refinement related policy changes
proposed in this rule. We use the best data available, but we do not
attempt to predict behavioral responses to these changes, and we do not
make adjustments for future changes in such variables as days or case-
mix.
This analysis incorporates the latest estimates of growth in
service use and payments under the Medicare home health benefit, based
on the latest available Medicare claims from 2003. 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 made by
the Congress, or changes specifically related to HHAs. In addition,
changes to the Medicare program may continue to be made as a result of
the BBA, the BBRA, the Medicare, Medicaid, and SCHIP Benefits
Improvement and Protection Act of 2000, the MMA, the DRA, or new
statutory provisions. Although these changes may not be specific to the
HH 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 HHAs.
Table 27 represents how home health agencies are likely to be
affected by the policy changes described in this rule. For each agency
type listed below, Table 27 displays the average case-mix index, both
under the current HH PPS case-mix system and the proposed CY 2008 HH
PPS case-mix system. For this analysis, we used the most recent data
available that linked home health claims and OASIS assessments, a 10
percent sample of episodes occurring in FY 2003. In Table 27, the
average case-mix is the same, in the aggregate, between the current HH
PPS system and the proposed revised HH PPS system, due to our
application of a budget neutrality factor for the case-mix weights.
Column one of this table classifies HHAs according to a number of
characteristics including provider type, geographic region, and urban
versus rural location. Column two displays the average case-mix weight
for each type of agency under the current payment system. Column three
displays the average case-mix weight for each type of agency
incorporating all of the changes/refinements discussed above. The
average case-mix weight for proprietary (for profit) agencies is
estimated to decrease from 1.2601 to 1.2227. Comparatively, the average
case-mix weight for voluntary non-profit agencies is estimated to
increase from 1.1404 to 1.1716. Rural agencies are estimated to
experience a decrease in their average case-mix from 1.1583 to 1.1417.
It is estimated that urban agencies would see a slight increase in
their average case-mix weight from 1.2032 to 1.2074. In particular, the
New England, Mid-Atlantic, East North Central, Mountain, and West North
Central areas of the country are estimated to see their average case-
mix increase under the proposed refinements of this rule. Conversely,
the West South Central, East South Central, Pacific, and South Atlantic
areas of the country are estimated to see their average case-mix
decrease as a result of proposed refinements of this rule. Both small
and large agencies are estimated to see decreases in their average
case-mix under the new proposed case-mix system, the only exception
being much larger agencies (200+ first episodes), which are estimated
to see an increase of their average case-mix from 1.1769 to 1.1920.
For the purposes of analyzing impacts on payments, we performed
three simulations and compared them to each other. The first simulation
estimated 2007 payments under the current system. The second simulation
estimated 2008 payments as though there would be no changes to the
payment system other than the rebased and revised home health market
basket increase of 2.9 percent. The second
[[Continued on page 25455]]
From the Federal Register Online via GPO Access [wais.access.gpo.gov]
]
[[pp. 25455-25481]] Medicare Program; Home Health Prospective Payment System
Refinement and Rate Update for Calendar Year 2008
[[Continued from page 25454]]
[[Page 25455]]
simulation produces an estimate of what total payments using the sample
data would be in 2008 without making any of the proposed changes
described in this proposed rule.
The third simulation estimates what total payments would be in
2008, using the proposed case-mix model, the proposed additional
payment for initial and only episode LUPA episodes, the proposed
removal of SCIC adjustments, and the proposed revised approach to
making NRS payments. The third simulation also assumed payments would
incorporate the rebased and revised home health market basket increase
of 2.9 percent, the current outlier threshold determined by a FDL ratio
of 0.67, and the 2.75 percent reduction in the national standardized
60-day episode payment rate to account for the proposed nominal change
in case-mix. All three simulations used the same CBSA wage index (we
used a crosswalk from the MSA reported on the 2003 claims to the CBSA
to determine the appropriate wage index). The results of comparing
these simulations are displayed in columns four, five, and six of Table
27.
Column four shows the percentage change in estimated total payments
in moving from CY 2007 to a CY 2008 system incorporating none of the
proposed refinements to the HH PPS except for the rebased and revised
home health market basket increase of 2.9 percent. Column five shows
the percentage change in estimated total payments in moving from a CY
2008 system that incorporates none of the proposed changes to the HH
PPS except for the rebased and revised home health market basket
increase of 2.9 percent to the proposed revised CY 2008 system of this
rule. Finally, column six shows the percentage change in estimated
total payments in moving from CY 2007 to the proposed revised CY 2008
system of this rule.
In general terms, the percentage change in estimated total payments
from CY 2007 to a CY 2008 system that incorporates none of the proposed
refinements to the HH PPS except for the rebased and revised home
health market basket update of 2.9 percent is approximately the home
health market basket increase of 2.9 percent. Some of the
classifications of HHAs show a slightly less than 2.9 percent increase
in this comparison, which is due to the CY 2007 system incorporating
the current labor share, which is slightly less than the labor share
being proposed for the CY 2008 system.
When comparing a CY 2008 system that incorporates none of the
refinements to the HH PPS except for the rebased and revised home
health market basket increase of 2.9 percent with the proposed revised
CY 2008 system of this rule, it is estimated that under the proposed
revised CY 2008 system of this rule, total estimated payments would
decrease by approximately 1.88 percent. Comparatively, the percentage
change in estimated total payments from CY 2007 to the proposed revised
CY 2008 system of this rule is an increase of just under 1 percent
(0.95 percent). All three simulations incorporate a FDL ratio of 0.67.
By maintaining the FDL ratio of 0.67, we believe we will continue to
meet the statutory requirement of having an outlier payment outlay that
does not exceed 5 percent of total HH PPS payments. In maintaining a
0.67 FDL ratio for CY 2008, in order to maintain budget neutrality
(other than the 2.75 percent reduction to the HH PPS rates to account
for nominal case-mix change), HH PPS rates are increased slightly, as
stated earlier in this section.
In general, voluntary non-profit HHAs (3.56 percent), facility-
based HHAs (3.50 percent), government owned HHAs (3.04 percent) and
free-standing HHAs (0.10 percent) are estimated to see an increase in
the percentage change in estimated total payments from CY 2007 to the
proposed revised CY 2008 system. Proprietary HHAs, on the other hand
are estimated to see a decrease of 1.90 percent in estimated total
payments from CY 2007 to the proposed revised CY 2008 system. The major
contributor to this decrease of 1.90 percent is the free-standing
proprietary HHAs, which are estimated to see a decrease of slightly
more than 2 percent in the percentage change in estimated total payment
from CY 2007 to the proposed revised CY 2008 system.
We note that some of these impacts are partly explained by practice
patterns associated with certain types of agencies. For example, LUPA
episodes are relatively common among nonprofit agencies and
freestanding government-owned agencies. Our proposal for an additional
payment for certain LUPA episodes would tend to increase payments for
such classes of agencies with higher-than-average LUPA rates, while
tending to decrease payments for agencies with comparatively low LUPA
rates. Similarly, the proposed elimination of the SCIC policy would
tend to favorably affect total payments for agencies with relatively
high rates of SCIC episodes, such as facility-based proprietary
agencies and facility-based government agencies. The percentage change
in estimated total payments from CY 2007 to a CY 2008 system that
incorporates all of the refinements to the HH PPS for rural HHAs is a
slight decrease of 0.50 percent, while for urban HHAs an increase of
1.26 percent is expected. Urban agencies have somewhat higher LUPA
rates than rural agencies, so urban agencies would be expected to
benefit, relative to rural agencies, from the proposal to make an
additional payment for certain LUPA episodes. Urban agencies are also
more likely to benefit from elimination of the SCIC policy. Urban
agencies are less likely to bill a SCIC episode than rural agencies.
However, when urban agencies do bill a SCIC episode the payment is
reduced more, on average, than when rural agencies bill a SCIC. The net
effect of these two components (relative frequency and payment impact
per SCIC episode) is a larger expected reduction for urban agencies
under the SCIC adjustment policy. Therefore, while both urban and rural
agencies benefit from eliminating the SCIC policy, urban agencies
benefit more.
HHAs in the North are expected to experience a percentage change
increase of 4.33 percent in estimated total payments from CY 2007 to
the proposed revised CY 2008 system. The only region estimated to
experience a decrease in the percentage change in estimated total
payments from CY 2007 to the proposed revised CY 2008 system is the
South. That percentage change is an estimated decrease of 1.84 percent.
It is estimated that New England and Mid Atlantic area HHAs will
experience percentage change increases of slightly more than 4 percent
(New England, 4.10 percent and the Mid-Atlantic, 4.45 percent) in
estimated total payments from CY 2007 to the proposed revised CY 2008
system. Conversely, West South Central HHAs are expected to experience
a decrease (-3.80 percent) in the percentage change in estimated total
payments from CY 2007 to the proposed CY 2008 system. In general,
smaller HHAs are expected to experience a decrease (ranging from -0.63
percent to -2.76 percent) for their percentage change in estimated
total payments from CY 2007 to the proposed revised CY 2008 system.
Conversely, larger HHAs are estimated to experience an increase
(ranging from 0.59 percent to 2.16 percent) in the percent change in
estimated total payments from CY 2007 to the proposed CY 2008 system.
BILLING CODE 4120-01-P
[[Page 25456]]
[GRAPHIC] [TIFF OMITTED] TP04MY07.041
[[Page 25457]]
[GRAPHIC] [TIFF OMITTED] TP04MY07.042
C. Accounting Statement
As Required by OMB Circular A-4 (available at http://
http://www.whitehouse.gov/omb/circulars/a004/a-4.pdf), in Table 28 below, we
have prepared an accounting statement showing the classification of the
expenditures associated with the provisions of this proposed rule. This
table provides our best estimate of the increase in Medicare payments
under the HH PPS as a result of the changes presented in this proposed
rule based on the data for 8,164 HHAs in our database. All expenditures
are classified as transfers to Medicare providers (that is, HHAs).
Table 28.--Accounting Statement: Classification of Estimated
Expenditures, From CY 2007 to CY 2008
[In millions]
------------------------------------------------------------------------
Category Transfers
------------------------------------------------------------------------
Annualized Monetized Transfers............ $140.
From Whom to Whom?........................ Federal Government to HHAs.
------------------------------------------------------------------------
In accordance with the provisions of Executive Order 12866, this
regulation was reviewed by the Office of Management and Budget.
List of Subjects in 42 CFR Part 484
Health facilities, Health professions, Medicare, and Reporting and
recordkeeping requirements.
For the reasons set forth in the preamble, the Centers for Medicare
& Medicaid Services would amend 42 CFR chapter IV as set forth below:
PART 484--HOME HEALTH SERVICES
1. The authority citation for part 484 continues to read as
follows:
Authority: Secs. 1102 and 1871 of the Social Security Act (42
U.S.C.1302 and 1395(hh)).
Subpart E--Prospective Payment System for Home Health Agencies
Sec. 484.205 [Amended]
2. Amend Sec. 484.205 by--
A. Removing paragraph (a)(3).
B. Redesignating paragraph (a)(4) as paragraph (a)(3).
C. Revising paragraph (b) introductory text.
D. Removing paragraph (e).
E. Redesignating paragraph (f) as paragraph (e).
The revisions read as follows:
Sec. 484.205 Basis of payment.
* * * * *
(b) Episode payment. The national prospective 60-day episode
payment represents payment in full for all costs associated with
furnishing home health services previously paid on a reasonable cost
basis (except the osteoporosis drug listed in section 1861(m) of the
Act as defined in section 1861(kk) of the Act) as of August 5, 1997
unless the national 60-day episode payment is subject to a low-
utilization payment adjustment set forth in Sec. 484.230, a partial
episode payment adjustment set forth at Sec. 484.235, or an additional
outlier payment set forth in Sec. 484.240. All payments under this
system may be
[[Page 25458]]
subject to a medical review adjustment reflecting beneficiary
eligibility, medical necessity determinations, and HHRG assignment. DME
provided as a home health service as defined in section 1861(m) of the
Act continues to be paid the fee schedule amount.
* * * * *
3. Revise Sec. 484.220 to read as follows:
Sec. 484.220 Calculation of the adjusted national prospective 60-day
episode payment rate for case-mix and area wage levels.
CMS adjusts the national prospective 60-day episode payment rate to
account for the following:
(a) HHA case-mix using a case-mix index to explain the relative
resource utilization of different patients. To address changes to the
case-mix that are a result of changes in the coding or classification
of different units of service that do not reflect real changes in case-
mix, the national prospective 60-day episode payment rate will be
adjusted downward as follows:
(1) For CY 2008 the adjustment is 2.75 percent.
(2) For CY 2009 and CY 2010, the adjustment is 2.75 percent in each
year.
(b) Geographic differences in wage levels using an appropriate wage
index based on the site of service of the beneficiary.
4. Amend Sec. 484.230 by adding a third, fourth, and fifth
sentence after the second sentence to read as follows:
Sec. 484.230 Methodology used for the calculation of the low-
utilization payment adjustment.
* * * For 2008 and subsequent calendar years, an amount will be
added to low-utilization payment adjustments for low-utilization
episodes that occur as the beneficiary's only episode or initial
episode in a sequence of adjacent episodes. For purposes of the home
health PPS, a sequence of adjacent episodes for a beneficiary is a
series of claims with no more than 60 days without home care between
the end of one episode, which is the 60th day (except for episodes that
have been PEP-adjusted), and the beginning of the next episode. This
additional amount will be updated annually after 2008 by a factor equal
to the applicable home health market basket percentage.
Sec. 484.237 [Removed]
5. Remove Sec. 484.237.
(Catalog of Federal Domestic Assistance Program No. 93.773,
Medicare--Hospital Insurance; and Program No. 93.774, Medicare--
Supplementary Medical Insurance Program)
Dated: February 15, 2007.
Leslie V. Norwalk,
Acting Administrator, Centers for Medicare & Medicaid Services.
Approved: April 2, 2007.
Michael O. Leavitt,
Secretary.
[[Page 25459]]
Note: The following addenda will not be published in the Code of
Federal Regulations.
Addendum A.--CY 2007 Wage Index for Rural Areas by CBSA; Applicable Pre-
Floor and Pre-Reclassified Hospital Wage Index
------------------------------------------------------------------------
Wage
CBSA code Nonurban area index
------------------------------------------------------------------------
01........................... Alabama....................... 0.7592
02........................... Alaska........................ 1.0661
03........................... Arizona....................... 0.8909
04........................... Arkansas...................... 0.7307
05........................... California.................... 1.1454
06........................... Colorado...................... 0.9325
07........................... Connecticut................... 1.1709
08........................... Delaware...................... 0.9706
10........................... Florida....................... 0.8594
11........................... Georgia....................... 0.7593
12........................... Hawaii........................ 1.0449
13........................... Idaho......................... 0.8120
14........................... Illinois...................... 0.8320
15........................... Indiana....................... 0.8539
16........................... Iowa.......................... 0.8682
17........................... Kansas........................ 0.7999
18........................... Kentucky...................... 0.7769
19........................... Louisiana..................... 0.7438
20........................... Maine......................... 0.8443
21........................... Maryland...................... 0.8927
22........................... Massachusetts \1\............. 1.0661
23........................... Michigan...................... 0.9063
24........................... Minnesota..................... 0.9153
25........................... Mississippi................... 0.7738
26........................... Missouri...................... 0.7927
27........................... Montana....................... 0.8590
28........................... Nebraska...................... 0.8678
29........................... Nevada........................ 0.8944
30........................... New Hampshire................. 1.0853
31........................... New Jersey \1,2\.............. .........
32........................... New Mexico.................... 0.8333
33........................... New York...................... 0.8232
34........................... North Carolina................ 0.8589
35........................... North Dakota.................. 0.7216
36........................... Ohio.......................... 0.8659
37........................... Oklahoma...................... 0.7629
38........................... Oregon........................ 0.9753
39........................... Pennsylvania.................. 0.8321
40........................... Puerto Rico \3\............... 0.4047
41........................... Rhode Island \2\.............. .........
42........................... South Carolina................ 0.8566
43........................... South Dakota.................. 0.8480
44........................... Tennessee..................... 0.7827
45........................... Texas......................... 0.7965
46........................... Utah.......................... 0.8141
47........................... Vermont....................... 0.9744
48........................... Virgin Islands................ 0.8467
49........................... Virginia...................... 0.7941
50........................... Washington.................... 1.0263
51........................... West Virginia................. 0.7607
52........................... Wisconsin..................... 0.9553
53........................... Wyoming....................... 0.9295
65........................... Guam.......................... 0.9611
------------------------------------------------------------------------
\1\ All counties within the State are classified as rural. No short-
term, acute care hospitals are located in the area(s). The rural wage
index for Massachusetts is imputed using the methodology discussed in
section II.E.2 of this rule.
\2\ All counties within the State are classified as urban.
\3\ All counties within the State are classified as rural. No short-
term, acute care hospitals are located in the area(s). We will
continue to use the wage index from CY 2005, which was the last year
in which we had ``rural'' hospital wage data for Puerto Rico.
Addendum B.--CY 2007 Wage Index for Urban Areas by CBSA; Applicable Pre-
Floor and Pre-Reclassified Hospital Wage Index
------------------------------------------------------------------------
Wage
CBSA code Urban area (constituent counties) index
------------------------------------------------------------------------
10180..................... Abilene, TX...................... 0.8001
Callahan County, TX.............
Jones County, TX................
Taylor County, TX...............
10380..................... Aguadilla-Isabela-San 0.3915
Sebasti[aacute]n, PR.
Aguada Municipio, PR............
Aguadilla Municipio, PR.........
A[ntilde]asco Municipio, PR.....
Isabela Municipio, PR...........
Lares Municipio, PR.............
Moca Municipio, PR..............
Rinc[oacute]n Municipio, PR.....
San Sebasti[aacute]n Municipio,
PR.
10420..................... Akron, OH........................ 0.8654
Portage County, OH..............
Summit County, OH...............
10500..................... Albany, GA....................... 0.8991
Baker County, GA................
Dougherty County, GA............
Lee County, GA..................
Terrell County, GA..............
Worth County, GA................
10580..................... Albany-Schenectady-Troy, NY...... 0.8720
Albany County, NY...............
Rensselaer County, NY...........
Saratoga County, NY.............
Schenectady County, NY..........
Schoharie County, NY............
10740..................... Albuquerque, NM.................. 0.9458
Bernalillo County, NM...........
Sandoval County, NM.............
Torrance County, NM.............
Valencia County, NM.............
10780..................... Alexandria, LA................... 0.8006
Grant Parish, LA................
Rapides Parish, LA..............
[[Page 25460]]
10900..................... Allentown-Bethlehem-Easton, PA-NJ 0.9947
Warren County, NJ...............
Carbon County, PA...............
Lehigh County, PA...............
Northampton County, PA..........
11020..................... Altoona, PA...................... 0.8812
Blair County, PA................
11100..................... Amarillo, TX..................... 0.9161
Armstrong County, TX............
Carson County, TX...............
Potter County, TX...............
Randall County, TX..............
11180..................... Ames, IA......................... 0.9760
Story County, IA................
11260..................... Anchorage, AK.................... 1.2024
Anchorage Municipality, AK......
Matanuska-Susitna Borough, AK...
11300..................... Anderson, IN..................... 0.8681
Madison County, IN..............
11340..................... Anderson, SC..................... 0.9017
Anderson County, SC.............
11460..................... Ann Arbor, MI.................... 1.0826
Washtenaw County, MI............
11500..................... Anniston-Oxford, AL.............. 0.7770
Calhoun County, AL..............
11540..................... Appleton, WI..................... 0.9455
Calumet County, WI..............
Outagamie County, WI............
11700..................... Asheville, NC.................... 0.9077
Buncombe County, NC.............
Haywood County, NC..............
Henderson County, NC............
Madison County, NC..............
12020..................... Athens-Clarke County, GA......... 0.9856
Clarke County, GA...............
Madison County, GA..............
Oconee County, GA...............
Oglethorpe County, GA...........
12060..................... Atlanta-Sandy Springs-Marietta, 0.9762
GA.
Barrow County, GA...............
Bartow County, GA...............
Butts County, GA................
Carroll County, GA..............
Cherokee County, GA.............
Clayton County, GA..............
Cobb County, GA.................
Coweta County, GA...............
Dawson County, GA...............
DeKalb County, GA...............
Douglas County, GA..............
Fayette County, GA..............
Forsyth County, GA..............
Fulton County, GA...............
Gwinnett County, GA.............
Haralson County, GA.............
Heard County, GA................
Henry County, GA................
Jasper County, GA...............
Lamar County, GA................
Meriwether County, GA...........
Newton County, GA...............
Paulding County, GA.............
Pickens County, GA..............
Pike County, GA.................
Rockdale County, GA.............
Spalding County, GA.............
Walton County, GA...............
12100..................... Atlantic City, NJ................ 1.1831
Atlantic County, NJ.............
12220..................... Auburn-Opelika, AL............... 0.8096
[[Page 25461]]
Lee County, AL..................
12260..................... Augusta-Richmond County, GA-SC... 0.9667
Burke County, GA................
Columbia County, GA.............
McDuffie County, GA.............
Richmond County, GA.............
Aiken County, SC................
Edgefield County, SC............
12420..................... Austin-Round Rock, TX............ 0.9344
Bastrop County, TX..............
Caldwell County, TX.............
Hays County, TX.................
Travis County, TX...............
Williamson County, TX...........
12540..................... Bakersfield, CA.................. 1.0726
Kern County, CA.................
12580..................... Baltimore-Towson, MD............. 1.0088
Anne Arundel County, MD.........
Baltimore County, MD............
Carroll County, MD..............
Harford County, MD..............
Howard County, MD...............
Queen Anne's County, MD.........
Baltimore City, MD..............
12620..................... Bangor, ME....................... 0.9712
Penobscot County, ME............
12700..................... Barnstable Town, MA.............. 1.2540
Barnstable County, MA...........
12940..................... Baton Rouge, LA.................. 0.8085
Ascension Parish, LA............
East Baton Rouge Parish, LA.....
East Feliciana Parish, LA.......
Iberville Parish, LA............
Livingston Parish, LA...........
Pointe Coupee Parish, LA........
St. Helena Parish, LA...........
West Baton Rouge Parish, LA.....
West Feliciana Parish, LA.......
12980..................... Battle Creek, MI................. 0.9763
Calhoun County, MI..............
13020..................... Bay City, MI..................... 0.9252
Bay County, MI..................
13140..................... Beaumont-Port Arthur, TX......... 0.8595
Hardin County, TX...............
Jefferson County, TX............
Orange County, TX...............
13380..................... Bellingham, WA................... 1.1105
Whatcom County, WA..............
13460..................... Bend, OR......................... 1.0743
Deschutes County, OR............
13644..................... Bethesda-Frederick-Gaithersburg, 1.0904
MD.
Frederick County, MD............
Montgomery County, MD...........
13740..................... Billings, MT..................... 0.8713
Carbon County, MT...............
Yellowstone County, MT..........
13780..................... Binghamton, NY................... 0.8786
Broome County, NY...............
Tioga County, NY................
13820..................... Birmingham-Hoover, AL............ 0.8994
Bibb County, AL.................
Blount County, AL...............
Chilton County, AL..............
Jefferson County, AL............
St. Clair County, AL............
Shelby County, AL...............
Walker County, AL...............
13900..................... Bismarck, ND..................... 0.7240
Burleigh County, ND.............
Morton County, ND...............
[[Page 25462]]
13980..................... Blacksburg-Christiansburg- 0.8213
Radford, VA.
Giles County, VA................
Montgomery County, VA...........
Pulaski County, VA..............
Radford City, VA................
14020..................... Bloomington, IN.................. 0.8533
Greene County, IN...............
Monroe County, IN...............
Owen County, IN.................
14060..................... Bloomington-Normal, IL........... 0.8945
McLean County, IL...............
14260..................... Boise City-Nampa, ID............. 0.9401
Ada County, ID..................
Boise County, ID................
Canyon County, ID...............
Gem County, ID..................
Owyhee County, ID...............
14484..................... Boston-Quincy, MA................ 1.1679
Norfolk County, MA..............
Plymouth County, MA.............
Suffolk County, MA..............
14500..................... Boulder, CO...................... 1.0350
Boulder County, CO..............
14540..................... Bowling Green, KY................ 0.8148
Edmonson County, KY.............
Warren County, KY...............
14740..................... Bremerton-Silverdale, WA......... 1.0914
Kitsap County, WA...............
14860..................... Bridgeport-Stamford-Norwalk, CT.. 1.2659
Fairfield County, CT............
15180..................... Brownsville-Harlingen, TX........ 0.9430
Cameron County, TX..............
15260..................... Brunswick, GA.................... 1.0165
Brantley County, GA.............
Glynn County, GA................
McIntosh County, GA.............
15380..................... Buffalo-Niagara Falls, NY........ 0.9424
Erie County, NY.................
Niagara County, NY..............
15500..................... Burlington, NC................... 0.8674
Alamance County, NC.............
15540..................... Burlington-South Burlington, VT.. 0.9475
Chittenden County, VT...........
Franklin County, VT.............
Grand Isle County, VT...........
15764..................... Cambridge-Newton-Framingham, MA.. 1.0970
Middlesex County, MA............
15804..................... Camden, NJ....................... 1.0393
Burlington County, NJ...........
Camden County, NJ...............
Gloucester County, NJ...........
15940..................... Canton-Massillon, OH............. 0.9032
Carroll County, OH..............
Stark County, OH................
15980..................... Cape Coral-Fort Myers, FL........ 0.9343
Lee County, FL..................
16180..................... Carson City, NV.................. 1.0026
Carson City, NV.................
16220..................... Casper, WY....................... 0.9145
Natrona County, WY..............
16300..................... Cedar Rapids, IA................. 0.8888
Benton County, IA...............
Jones County, IA................
Linn County, IA.................
16580..................... Champaign-Urbana, IL............. 0.9645
Champaign County, IL............
Ford County, IL.................
Piatt County, IL................
16620..................... Charleston, WV................... 0.8543
Boone County, WV................
[[Page 25463]]
Clay County, WV.................
Kanawha County, WV..............
Lincoln County, WV..............
Putnam County, WV...............
16700..................... Charleston-North Charleston, SC.. 0.9145
Berkeley County, SC.............
Charleston County, SC...........
Dorchester County, SC...........
16740..................... Charlotte-Gastonia-Concord, NC-SC 0.9555
Anson County, NC................
Cabarrus County, NC.............
Gaston County, NC...............
Mecklenburg County, NC..........
Union County, NC................
York County, SC.................
16820..................... Charlottesville, VA.............. 1.0125
Albemarle County, VA............
Fluvanna County, VA.............
Greene County, VA...............
Nelson County, VA...............
Charlottesville City, VA........
16860..................... Chattanooga, TN-GA............... 0.8948
Catoosa County, GA..............
Dade County, GA.................
Walker County, GA...............
Hamilton County, TN.............
Marion County, TN...............
Sequatchie County, TN...........
16940..................... Cheyenne, WY..................... 0.9060
Laramie County, WY..............
16974..................... Chicago-Naperville-Joliet, IL.... 1.0752
Cook County, IL.................
DeKalb County, IL...............
DuPage County, IL...............
Grundy County, IL...............
Kane County, IL.................
Kendall County, IL..............
McHenry County, IL..............
Will County, IL.................
17020..................... Chico, CA........................ 1.1054
Butte County, CA................
17140..................... Cincinnati-Middletown, OH-KY-IN.. 0.9601
Dearborn County, IN.............
Franklin County, IN.............
Ohio County, IN.................
Boone County, KY................
Bracken County, KY..............
Campbell County, KY.............
Gallatin County, KY.............
Grant County, KY................
Kenton County, KY...............
Pendleton County, KY............
Brown County, OH................
Butler County, OH...............
Clermont County, OH.............
Hamilton County, OH.............
Warren County, OH...............
17300..................... Clarksville, TN-KY............... 0.8436
Christian County, KY............
Trigg County, KY................
Montgomery County, TN...........
Stewart County, TN..............
17420..................... Cleveland, TN.................... 0.8110
Bradley County, TN..............
Polk County, TN.................
17460..................... Cleveland-Elyria-Mentor, OH...... 0.9400
Cuyahoga County, OH.............
Geauga County, OH...............
Lake County, OH.................
Lorain County, OH...............
[[Page 25464]]
Medina County, OH...............
17660..................... Coeur d'Alene, ID................ 0.9344
Kootenai County, ID.............
17780..................... College Station-Bryan, TX........ 0.9046
Brazos County, TX...............
Burleson County, TX.............
Robertson County, TX............
17820..................... Colorado Springs, CO............. 0.9701
El Paso County, CO..............
Teller County, CO...............
17860..................... Columbia, MO..................... 0.8543
Boone County, MO................
Howard County, MO...............
17900..................... Columbia, SC..................... 0.8934
Calhoun County, SC..............
Fairfield County, SC............
Kershaw County, SC..............
Lexington County, SC............
Richland County, SC.............
Saluda County, SC...............
17980..................... Columbus, GA-AL.................. 0.8239
Russell County, AL..............
Chattahoochee County, GA........
Harris County, GA...............
Marion County, GA...............
Muscogee County, GA.............
18020..................... Columbus, IN..................... 0.9318
Bartholomew County, IN..........
18140..................... Columbus, OH..................... 1.0107
Delaware County, OH.............
Fairfield County, OH............
Franklin County, OH.............
Licking County, OH..............
Madison County, OH..............
Morrow County, OH...............
Pickaway County, OH.............
Union County, OH................
18580..................... Corpus Christi, TX............... 0.8564
Aransas County, TX..............
Nueces County, TX...............
San Patricio County, TX.........
18700..................... Corvallis, OR.................... 1.1546
Benton County, OR...............
19060..................... Cumberland, MD-WV................ 0.8447
Allegany County, MD.............
Mineral County, WV..............
19124..................... Dallas-Plano-Irving, TX.......... 1.0076
Collin County, TX...............
Dallas County, TX...............
Delta County, TX................
Denton County, TX...............
Ellis County, TX................
Hunt County, TX.................
Kaufman County, TX..............
Rockwall County, TX.............
19140..................... Dalton, GA....................... 0.9093
Murray County, GA...............
Whitfield County, GA............
19180..................... Danville, IL..................... 0.9267
Vermilion County, IL............
19260..................... Danville, VA..................... 0.8451
Pittsylvania County, VA.........
Danville City, VA...............
19340..................... Davenport-Moline-Rock Island, IA- 0.8847
IL.
Henry County, IL................
Mercer County, IL...............
Rock Island County, IL..........
Scott County, IA................
19380..................... Dayton, OH....................... 0.9037
Greene County, OH...............
[[Page 25465]]
Miami County, OH................
Montgomery County, OH...........
Preble County, OH...............
19460..................... Decatur, AL...................... 0.8160
Lawrence County, AL.............
Morgan County, AL...............
19500..................... Decatur, IL...................... 0.8173
Macon County, IL................
19660..................... Deltona-Daytona Beach-Ormond 0.9264
Beach, FL.
Volusia County, FL..............
19740..................... Denver-Aurora, CO................ 1.0931
Adams County, CO................
Arapahoe County, CO.............
Broomfield County, CO...........
Clear Creek County, CO..........
Denver County, CO...............
Douglas County, CO..............
Elbert County, CO...............
Gilpin County, CO...............
Jefferson County, CO............
Park County, CO.................
19780..................... Des Moines, IA................... 0.9214
Dallas County, IA...............
Guthrie County, IA..............
Madison County, IA..............
Polk County, IA.................
Warren County, IA...............
19804..................... Detroit-Livonia-Dearborn, MI..... 1.0282
Wayne County, MI................
20020..................... Dothan, AL....................... 0.7381
Geneva County, AL...............
Henry County, AL................
Houston County, AL..............
20100..................... Dover, DE........................ 0.9848
Kent County, DE.................
20220..................... Dubuque, IA...................... 0.9134
Dubuque County, IA..............
20260..................... Duluth, MN-WI.................... 1.0042
Carlton County, MN..............
St. Louis County, MN............
Douglas County, WI..............
20500..................... Durham, NC....................... 0.9826
Chatham County, NC..............
Durham County, NC...............
Orange County, NC...............
Person County, NC...............
20740..................... Eau Claire, WI................... 0.9630
Chippewa County, WI.............
Eau Claire County, WI...........
20764..................... Edison, NJ....................... 1.1190
Middlesex County, NJ............
Monmouth County, NJ.............
Ocean County, NJ................
Somerset County, NJ.............
20940..................... El Centro, CA.................... 0.9076
Imperial County, CA.............
21060..................... Elizabethtown, KY................ 0.8698
Hardin County, KY...............
Larue County, KY................
21140..................... Elkhart-Goshen, IN............... 0.9426
Elkhart County, IN..............
21300..................... Elmira, NY....................... 0.8240
Chemung County, NY..............
21340..................... El Paso, TX...................... 0.9053
El Paso County, TX..............
21500..................... Erie, PA......................... 0.8828
Erie County, PA.................
21604..................... Essex County, MA................. 1.0419
Essex County, MA................
21660..................... Eugene-Springfield, OR........... 1.0877
[[Page 25466]]
Lane County, OR.................
21780..................... Evansville, IN-KY................ 0.9071
Gibson County, IN...............
Posey County, IN................
Vanderburgh County, IN..........
Warrick County, IN..............
Henderson County, KY............
Webster County, KY..............
21820..................... Fairbanks, AK.................... 1.1060
Fairbanks North Star Borough, AK
21940..................... Fajardo, PR...................... 0.4037
Ceiba Municipio, PR.............
Fajardo Municipio, PR...........
Luquillo Municipio, PR..........
22020..................... Fargo, ND-MN..................... 0.8251
Cass County, ND.................
Clay County, MN.................
22140..................... Farmington, NM................... 0.8589
San Juan County, NM.............
22180..................... Fayetteville, NC................. 0.8946
Cumberland County, NC...........
Hoke County, NC.................
22220..................... Fayetteville-Springdale-Rogers, 0.8865
AR-MO.
Benton County, AR...............
Madison County, AR..............
Washington County, AR...........
McDonald County, MO.............
22380..................... Flagstaff, AZ.................... 1.1601
Coconino County, AZ.............
22420..................... Flint, MI........................ 1.0969
Genesee County, MI..............
22500..................... Florence, SC..................... 0.8388
Darlington County, SC...........
Florence County, SC.............
22520..................... Florence-Muscle Shoals, AL....... 0.7844
Colbert County, AL..............
Lauderdale County, AL...........
22540..................... Fond du Lac, WI.................. 1.0064
Fond du Lac County, WI..........
22660..................... Fort Collins-Loveland, CO........ 0.9545
Larimer County, CO..............
22744..................... Fort Lauderdale-Pompano Beach- 1.0134
Deerfield Beach, FL.
Broward County, FL..............
22900..................... Fort Smith, AR-OK................ 0.7732
Crawford County, AR.............
Franklin County, AR.............
Sebastian County, AR............
Le Flore County, OK.............
Sequoyah County, OK.............
23020..................... Fort Walton Beach-Crestview- 0.8643
Destin, FL.
Okaloosa County, FL.............
23060..................... Fort Wayne, IN................... 0.9517
Allen County, IN................
Wells County, IN................
Whitley County, IN..............
23104..................... Fort Worth-Arlington, TX......... 0.9570
Johnson County, TX..............
Parker County, TX...............
Tarrant County, TX..............
Wise County, TX.................
23420..................... Fresno, CA....................... 1.0943
Fresno County, CA...............
23460..................... Gadsden, AL...................... 0.8066
Etowah County, AL...............
23540..................... Gainesville, FL.................. 0.9277
Alachua County, FL..............
Gilchrist County, FL............
23580..................... Gainesville, GA.................. 0.8959
Hall County, GA.................
23844..................... Gary, IN......................... 0.9334
[[Page 25467]]
Jasper County, IN...............
Lake County, IN.................
Newton County, IN...............
Porter County, IN...............
24020..................... Glens Falls, NY.................. 0.8325
Warren County, NY...............
Washington County, NY...........
24140..................... Goldsboro, NC.................... 0.9171
Wayne County, NC................
24220..................... Grand Forks, ND-MN............... 0.7949
Polk County, MN.................
Grand Forks County, ND..........
24300..................... Grand Junction, CO............... 0.9669
Mesa County, CO.................
24340..................... Grand Rapids-Wyoming, MI......... 0.9455
Barry County, MI................
Ionia County, MI................
Kent County, MI.................
Newaygo County, MI..............
24500..................... Great Falls, MT.................. 0.8598
Cascade County, MT..............
24540..................... Greeley, CO...................... 0.9602
Weld County, CO.................
24580..................... Green Bay, WI.................... 0.9787
Brown County, WI................
Kewaunee County, WI.............
Oconto County, WI...............
24660..................... Greensboro-High Point, NC........ 0.8866
Guilford County, NC.............
Randolph County, NC.............
Rockingham County, NC...........
24780..................... Greenville, NC................... 0.9432
Greene County, NC...............
Pitt County, NC.................
24860..................... Greenville, SC................... 0.9804
Greenville County, SC...........
Laurens County, SC..............
Pickens County, SC..............
25020..................... Guayama, PR...................... 0.3235
Arroyo Municipio, PR............
Guayama Municipio, PR...........
Patillas Municipio, PR..........
25060..................... Gulfport-Biloxi, MS.............. 0.8915
Hancock County, MS..............
Harrison County, MS.............
Stone County, MS................
25180..................... Hagerstown-Martinsburg, MD-WV.... 0.9039
Washington County, MD...........
Berkeley County, WV.............
Morgan County, WV...............
25260..................... Hanford-Corcoran, CA............. 1.0282
Kings County, CA................
25420..................... Harrisburg-Carlisle, PA.......... 0.9402
Cumberland County, PA...........
Dauphin County, PA..............
Perry County, PA................
25500..................... Harrisonburg, VA................. 0.9074
Rockingham County, VA...........
Harrisonburg City, VA...........
25540..................... Hartford-West Hartford-East 1.0894
Hartford, CT.
Hartford County, CT.............
Litchfield County, CT...........
Middlesex County, CT............
Tolland County, CT..............
25620..................... Hattiesburg, MS.................. 0.7430
Forrest County, MS..............
Lamar County, MS................
Perry County, MS................
25860..................... Hickory-Lenoir-Morganton, NC..... 0.9010
Alexander County, NC............
[[Page 25468]]
Burke County, NC................
Caldwell County, NC.............
Catawba County, NC..............
259801.................... Hinesville-Fort Stewart, GA...... 0.9178
Liberty County, GA..............
Long County, GA.................
26100..................... Holland-Grand Haven, MI.......... 0.9163
Ottawa County, MI...............
26180..................... Honolulu, HI..................... 1.1096
Honolulu County, HI.............
26300..................... Hot Springs, AR.................. 0.8782
Garland County, AR..............
26380..................... Houma-Bayou Cane-Thibodaux, LA... 0.8082
Lafourche Parish, LA............
Terrebonne Parish, LA...........
26420..................... Houston-Baytown-Sugar Land, TX... 1.0009
Austin County, TX...............
Brazoria County, TX.............
Chambers County, TX.............
Fort Bend County, TX............
Galveston County, TX............
Harris County, TX...............
Liberty County, TX..............
Montgomery County, TX...........
San Jacinto County, TX..........
Waller County, TX...............
26580..................... Huntington-Ashland, WV-KY-OH..... 0.8998
Boyd County, KY.................
Greenup County, KY..............
Lawrence County, OH.............
Cabell County, WV...............
Wayne County, WV................
26620..................... Huntsville, AL................... 0.9007
Limestone County, AL............
Madison County, AL..............
26820..................... Idaho Falls, ID.................. 0.9088
Bonneville County, ID...........
Jefferson County, ID............
26900..................... Indianapolis, IN................. 0.9896
Boone County, IN................
Brown County, IN................
Hamilton County, IN.............
Hancock County, IN..............
Hendricks County, IN............
Johnson County, IN..............
Marion County, IN...............
Morgan County, IN...............
Putnam County, IN...............
Shelby County, IN...............
26980..................... Iowa City, IA.................... 0.9714
Johnson County, IA..............
Washington County, IA...........
27060..................... Ithaca, NY....................... 0.9928
Tompkins County, NY.............
27100..................... Jackson, MI...................... 0.9560
Jackson County, MI..............
27140..................... Jackson, MS...................... 0.8271
Copiah County, MS...............
Hinds County, MS................
Madison County, MS..............
Rankin County, MS...............
Simpson County, MS..............
27180..................... Jackson, TN...................... 0.8853
Chester County, TN..............
Madison County, TN..............
27260..................... Jacksonville, FL................. 0.9166
Baker County, FL................
Clay County, FL.................
Duval County, FL................
Nassau County, FL...............
[[Page 25469]]
St. Johns County, FL............
27340..................... Jacksonville, NC................. 0.8231
Onslow County, NC...............
27500..................... Janesville, WI................... 0.9655
Rock County, WI.................
27620..................... Jefferson City, MO............... 0.8333
Callaway County, MO.............
Cole County, MO.................
Moniteau County, MO.............
Osage County, MO................
27740..................... Johnson City, TN................. 0.8043
Carter County, TN...............
Unicoi County, TN...............
Washington County, TN...........
27780..................... Johnstown, PA.................... 0.8620
Cambria County, PA..............
27860..................... Jonesboro, AR.................... 0.7662
Craighead County, AR............
Poinsett County, AR.............
27900..................... Joplin, MO....................... 0.8606
Jasper County, MO...............
Newton County, MO...............
28020..................... Kalamazoo-Portage, MI............ 1.0705
Kalamazoo County, MI............
Van Buren County, MI............
28100..................... Kankakee-Bradley, IL............. 1.0083
Kankakee County, IL.............
28140..................... Kansas City, MO-KS............... 0.9495
Franklin County, KS.............
Johnson County, KS..............
Leavenworth County, KS..........
Linn County, KS.................
Miami County, KS................
Wyandotte County, KS............
Bates County, MO................
Caldwell County, MO.............
Cass County, MO.................
Clay County, MO.................
Clinton County, MO..............
Jackson County, MO..............
Lafayette County, MO............
Platte County, MO...............
Ray County, MO..................
28420..................... Kennewick-Richland-Pasco, WA..... 1.0343
Benton County, WA...............
Franklin County, WA.............
28660..................... Killeen-Temple-Fort Hood, TX..... 0.8902
Bell County, TX.................
Coryell County, TX..............
Lampasas County, TX.............
28700..................... Kingsport-Bristol-Bristol, TN-VA. 0.7985
Hawkins County, TN..............
Sullivan County, TN.............
Bristol City, VA................
Scott County, VA................
Washington County, VA...........
28740..................... Kingston, NY..................... 0.9367
Ulster County, NY...............
28940..................... Knoxville, TN.................... 0.8249
Anderson County, TN.............
Blount County, TN...............
Knox County, TN.................
Loudon County, TN...............
Union County, TN................
29020..................... Kokomo, IN....................... 0.9669
Howard County, IN...............
Tipton County, IN...............
29100..................... La Crosse, WI-MN................. 0.9426
Houston County, MN..............
La Crosse County, WI............
[[Page 25470]]
29140..................... Lafayette, IN.................... 0.8932
Benton County, IN...............
Carroll County, IN..............
Tippecanoe County, IN...........
29180..................... Lafayette, LA.................... 0.8289
Lafayette Parish, LA............
St. Martin Parish, LA...........
29340..................... Lake Charles, LA................. 0.7914
Calcasieu Parish, LA............
Cameron Parish, LA..............
29404..................... Lake County-Kenosha County, IL-WI 1.0571
Lake County, IL.................
Kenosha County, WI..............
29460..................... Lakeland, FL..................... 0.8879
Polk County, FL.................
29540..................... Lancaster, PA.................... 0.9589
Lancaster County, PA............
29620..................... Lansing-East Lansing, MI......... 1.0088
Clinton County, MI..............
Eaton County, MI................
Ingham County, MI...............
29700..................... Laredo, TX....................... 0.7812
Webb County, TX.................
29740..................... Las Cruces, NM................... 0.9273
Dona Ana County, NM.............
29820..................... Las Vegas-Paradise, NV........... 1.1430
Clark County, NV................
29940..................... Lawrence, KS..................... 0.8366
Douglas County, KS..............
30020..................... Lawton, OK....................... 0.8066
Comanche County, OK.............
30140..................... Lebanon, PA...................... 0.8680
Lebanon County, PA..............
30300..................... Lewiston, ID-WA.................. 0.9854
Nez Perce County, ID............
Asotin County, WA...............
30340..................... Lewiston-Auburn, ME.............. 0.9126
Androscoggin County, ME.........
30460..................... Lexington-Fayette, KY............ 0.9181
Bourbon County, KY..............
Clark County, KY................
Fayette County, KY..............
Jessamine County, KY............
Scott County, KY................
Woodford County, KY.............
30620..................... Lima, OH......................... 0.9042
Allen County, OH................
30700..................... Lincoln, NE...................... 1.0092
Lancaster County, NE............
Seward County, NE...............
30780..................... Little Rock-North Little Rock, AR 0.8890
Faulkner County, AR.............
Grant County, AR................
Lonoke County, AR...............
Perry County, AR................
Pulaski County, AR..............
Saline County, AR...............
30860..................... Logan, UT-ID..................... 0.9022
Franklin County, ID.............
Cache County, UT................
30980..................... Longview, TX..................... 0.8788
Gregg County, TX................
Rusk County, TX.................
Upshur County, TX...............
31020..................... Longview, WA..................... 1.0011
Cowlitz County, WA..............
31084..................... Los Angeles-Long Beach-Glendale, 1.1760
CA.
Los Angeles County, CA..........
31140..................... Louisville, KY-IN................ 0.9119
Clark County, IN................
[[Page 25471]]
Floyd County, IN................
Harrison County, IN.............
Washington County, IN...........
Bullitt County, KY..............
Henry County, KY................
Jefferson County, KY............
Meade County, KY................
Nelson County, KY...............
Oldham County, KY...............
Shelby County, KY...............
Spencer County, KY..............
Trimble County, KY..............
31180..................... Lubbock, TX...................... 0.8613
Crosby County, TX...............
Lubbock County, TX..............
31340..................... Lynchburg, VA.................... 0.8694
Amherst County, VA..............
Appomattox County, VA...........
Bedford County, VA..............
Campbell County, VA.............
Bedford City, VA................
Lynchburg City, VA..............
31420..................... Macon, GA........................ 0.9520
Bibb County, GA.................
Crawford County, GA.............
Jones County, GA................
Monroe County, GA...............
Twiggs County, GA...............
31460..................... Madera, CA....................... 0.8155
Madera County, CA...............
31540..................... Madison, WI...................... 1.0840
Columbia County, WI.............
Dane County, WI.................
Iowa County, WI.................
31700..................... Manchester-Nashua, NH............ 1.0243
Hillsborough County, NH.........
Merrimack County, NH............
31900..................... Mansfield, OH.................... 0.9271
Richland County, OH.............
32420..................... Mayag[uuml]ez, PR................ 0.3848
Hormigueros Municipio, PR.......
Mayag[uuml]ez Municipio, PR.....
32580..................... McAllen-Edinburg-Pharr, TX....... 0.8773
Hidalgo County, TX..............
32780..................... Medford, OR...................... 1.0818
Jackson County, OR..............
32820..................... Memphis, TN-MS-AR................ 0.9373
Crittenden County, AR...........
DeSoto County, MS...............
Marshall County, MS.............
Tate County, MS.................
Tunica County, MS...............
Fayette County, TN..............
Shelby County, TN...............
Tipton County, TN...............
32900..................... Merced, CA....................... 1.1471
Merced County, CA...............
33124..................... Miami-Miami Beach-Kendall, FL.... 0.9813
Miami-Dade County, FL...........
33140..................... Michigan City-La Porte, IN....... 0.9118
LaPorte County, IN..............
33260..................... Midland, TX...................... 0.9786
Midland County, TX..............
33340..................... Milwaukee-Waukesha-West Allis, WI 1.0218
Milwaukee County, WI............
Ozaukee County, WI..............
Washington County, WI...........
Waukesha County, WI.............
33460..................... Minneapolis-St. Paul-Bloomington, 1.0946
MN-WI.
Anoka County, MN................
[[Page 25472]]
Carver County, MN...............
Chisago County, MN..............
Dakota County, MN...............
Hennepin County, MN.............
Isanti County, MN...............
Ramsey County, MN...............
Scott County, MN................
Sherburne County, MN............
Washington County, MN...........
Wright County, MN...............
Pierce County, WI...............
St. Croix County, WI............
33540..................... Missoula, MT..................... 0.8929
Missoula County, MT.............
33660..................... Mobile, AL....................... 0.7914
Mobile County, AL...............
33700..................... Modesto, CA...................... 1.1730
Stanislaus County, CA...........
33740..................... Monroe, LA....................... 0.7997
Ouachita Parish, LA.............
Union Parish, LA................
33780..................... Monroe, MI....................... 0.9708
Monroe County, MI...............
33860..................... Montgomery, AL................... 0.8009
Autauga County, AL..............
Elmore County, AL...............
Lowndes County, AL..............
Montgomery County, AL...........
34060..................... Morgantown, WV................... 0.8423
Monongalia County, WV...........
Preston County, WV..............
34100..................... Morristown, TN................... 0.7933
Grainger County, TN.............
Hamblen County, TN..............
Jefferson County, TN............
34580..................... Mount Vernon-Anacortes, WA....... 1.0518
Skagit County, WA...............
34620..................... Muncie, IN....................... 0.8562
Delaware County, IN.............
34740..................... Muskegon-Norton Shores, MI....... 0.9941
Muskegon County, MI.............
34820..................... Myrtle Beach-Conway-North Myrtle 0.8811
Beach, SC.
Horry County, SC................
34900..................... Napa, CA......................... 1.3375
Napa County, CA.................
34940..................... Naples-Marco Island, FL.......... 0.9941
Collier County, FL..............
34980..................... Nashville-Davidson-Murfreesboro, 0.9847
TN.
Cannon County, TN...............
Cheatham County, TN.............
Davidson County, TN.............
Dickson County, TN..............
Hickman County, TN..............
Macon County, TN................
Robertson County, TN............
Rutherford County, TN...........
Smith County, TN................
Sumner County, TN...............
Trousdale County, TN............
Williamson County, TN...........
Wilson County, TN...............
35004..................... Nassau-Suffolk, NY............... 1.2663
Nassau County, NY...............
Suffolk County, NY..............
35084..................... Newark-Union, NJ-PA.............. 1.1892
Essex County, NJ................
Hunterdon County, NJ............
Morris County, NJ...............
Sussex County, NJ...............
Union County, NJ................
[[Page 25473]]
Pike County, PA.................
35300..................... New Haven-Milford, CT............ 1.1953
New Haven County, CT............
35380..................... New Orleans-Metairie-Kenner, LA.. 0.8832
Jefferson Parish, LA............
Orleans Parish, LA..............
Plaquemines Parish, LA..........
St. Bernard Parish, LA..........
St. Charles Parish, LA..........
St. John the Baptist Parish, LA.
St. Tammany Parish, LA..........
35644..................... New York-Wayne-White Plains, NY- 1.3177
NJ.
Bergen County, NJ...............
Hudson County, NJ...............
Passaic County, NJ..............
Bronx County, NY................
Kings County, NY................
New York County, NY.............
Putnam County, NY...............
Queens County, NY...............
Richmond County, NY.............
Rockland County, NY.............
Westchester County, NY..........
35660..................... Niles-Benton Harbor, MI.......... 0.8915
Berrien County, MI..............
35980..................... Norwich-New London, CT........... 1.1932
New London County, CT...........
36084..................... Oakland-Fremont-Hayward, CA...... 1.5819
Alameda County, CA..............
Contra Costa County, CA.........
36100..................... Ocala, FL........................ 0.8867
Marion County, FL...............
36140..................... Ocean City, NJ................... 1.0472
Cape May County, NJ.............
36220..................... Odessa, TX....................... 1.0102
Ector County, TX................
36260..................... Ogden-Clearfield, UT............. 0.8995
Davis County, UT................
Morgan County, UT...............
Weber County, UT................
36420..................... Oklahoma City, OK................ 0.8843
Canadian County, OK.............
Cleveland County, OK............
Grady County, OK................
Lincoln County, OK..............
Logan County, OK................
McClain County, OK..............
Oklahoma County, OK.............
36500..................... Olympia, WA...................... 1.1081
Thurston County, WA.............
36540..................... Omaha-Council Bluffs, NE-IA...... 0.9450
Harrison County, IA.............
Mills County, IA................
Pottawattamie County, IA........
Cass County, NE.................
Douglas County, NE..............
Sarpy County, NE................
Saunders County, NE.............
Washington County, NE...........
36740..................... Orlando, FL...................... 0.9452
Lake County, FL.................
Orange County, FL...............
Osceola County, FL..............
Seminole County, FL.............
36780..................... Oshkosh-Neenah, WI............... 0.9315
Winnebago County, WI............
36980..................... Owensboro, KY.................... 0.8748
Daviess County, KY..............
Hancock County, KY..............
McLean County, KY...............
[[Page 25474]]
37100..................... Oxnard-Thousand Oaks-Ventura, CA. 1.1546
Ventura County, CA..............
37340..................... Palm Bay-Melbourne-Titusville, FL 0.9443
Brevard County, FL..............
37460..................... Panama City-Lynn Haven, FL....... 0.8027
Bay County, FL..................
37620..................... Parkersburg-Marietta, WV-OH...... 0.7978
Washington County, OH...........
Pleasants County, WV............
Wirt County, WV.................
Wood County, WV.................
37700..................... Pascagoula, MS................... 0.8215
George County, MS...............
Jackson County, MS..............
37860..................... Pensacola-Ferry Pass-Brent, FL... 0.8000
Escambia County, FL.............
Santa Rosa County, FL...........
37900..................... Peoria, IL....................... 0.8982
Marshall County, IL.............
Peoria County, IL...............
Stark County, IL................
Tazewell County, IL.............
Woodford County, IL.............
37964..................... Philadelphia, PA................. 1.0997
Bucks County, PA................
Chester County, PA..............
Delaware County, PA.............
Montgomery County, PA...........
Philadelphia County, PA.........
38060..................... Phoenix-Mesa-Scottsdale, AZ...... 1.0288
Maricopa County, AZ.............
Pinal County, AZ................
38220..................... Pine Bluff, AR................... 0.8383
Cleveland County, AR............
Jefferson County, AR............
Lincoln County, AR..............
38300..................... Pittsburgh, PA................... 0.8674
Allegheny County, PA............
Armstrong County, PA............
Beaver County, PA...............
Butler County, PA...............
Fayette County, PA..............
Washington County, PA...........
Westmoreland County, PA.........
38340..................... Pittsfield, MA................... 1.0266
Berkshire County, MA............
38540..................... Pocatello, ID.................... 0.9401
Bannock County, ID..............
Power County, ID................
38660..................... Ponce, PR........................ 0.4843
Juana D[iacute]az Municipio, PR.
Ponce Municipio, PR.............
Villalba Municipio, PR..........
38860..................... Portland-South Portland- 0.9909
Biddeford, ME.
Cumberland County, ME...........
Sagadahoc County, ME............
York County, ME.................
38900..................... Portland-Vancouver-Beaverton, OR- 1.1416
WA.
Clackamas County, OR............
Columbia County, OR.............
Multnomah County, OR............
Washington County, OR...........
Yamhill County, OR..............
Clark County, WA................
Skamania County, WA.............
38940..................... Port St. Lucie-Fort Pierce, FL... 0.9834
Martin County, FL...............
St. Lucie County, FL............
39100..................... Poughkeepsie-Newburgh-Middletown, 1.0911
NY.
Dutchess County, NY.............
[[Page 25475]]
Orange County, NY...............
39140..................... Prescott, AZ..................... 0.9836
Yavapai County, AZ..............
39300..................... Providence-New Bedford-Fall 1.0783
River, RI-MA.
Bristol County, MA..............
Bristol County, RI..............
Kent County, RI.................
Newport County, RI..............
Providence County, RI...........
Washington County, RI...........
39340..................... Provo-Orem, UT................... 0.9538
Juab County, UT.................
Utah County, UT.................
39380..................... Pueblo, CO....................... 0.8754
Pueblo County, CO...............
39460..................... Punta Gorda, FL.................. 0.9405
Charlotte County, FL............
39540..................... Racine, WI....................... 0.9356
Racine County, WI...............
39580..................... Raleigh-Cary, NC................. 0.9864
Franklin County, NC.............
Johnston County, NC.............
Wake County, NC.................
39660..................... Rapid City, SD................... 0.8833
Meade County, SD................
Pennington County, SD...........
39740..................... Reading, PA...................... 0.9623
Berks County, PA................
39820..................... Redding, CA...................... 1.3198
Shasta County, CA...............
39900..................... Reno-Sparks, NV.................. 1.1964
Storey County, NV...............
Washoe County, NV...............
40060..................... Richmond, VA..................... 0.9177
Amelia County, VA...............
Caroline County, VA.............
Charles City County, VA.........
Chesterfield County, VA.........
Cumberland County, VA...........
Dinwiddie County, VA............
Goochland County, VA............
Hanover County, VA..............
Henrico County, VA..............
King and Queen County, VA.......
King William County, VA.........
Louisa County, VA...............
New Kent County, VA.............
Powhatan County, VA.............
Prince George County, VA........
Sussex County, VA...............
Colonial Heights City, VA.......
Hopewell City, VA...............
Petersburg City, VA.............
Richmond City, VA...............
40140..................... Riverside-San Bernardino-Ontario, 1.0904
CA.
Riverside County, CA............
San Bernardino County, CA.......
40220..................... Roanoke, VA...................... 0.8647
Botetourt County, VA............
Craig County, VA................
Franklin County, VA.............
Roanoke County, VA..............
Roanoke City, VA................
Salem City, VA..................
40340..................... Rochester, MN.................... 1.1408
Dodge County, MN................
Olmsted County, MN..............
Wabasha County, MN..............
40380..................... Rochester, NY.................... 0.8994
Livingston County, NY...........
[[Page 25476]]
Monroe County, NY...............
Ontario County, NY..............
Orleans County, NY..............
Wayne County, NY................
40420..................... Rockford, IL..................... 0.9990
Boone County, IL................
Winnebago County, IL............
40484..................... Rockingham County-Strafford 1.0159
County, NH.
Rockingham County, NH...........
Strafford County, NH............
40580..................... Rocky Mount, NC.................. 0.8854
Edgecombe County, NC............
Nash County, NC.................
40660..................... Rome, GA......................... 0.9194
Floyd County, GA................
40900..................... SacramentoArden-ArcadeRoseville, 1.3373
CA.
El Dorado County, CA............
Placer County, CA...............
Sacramento County, CA...........
Yolo County, CA.................
40980..................... Saginaw-Saginaw Township North, 0.8874
MI.
Saginaw County, MI..............
41060..................... St. Cloud, MN.................... 1.0362
Benton County, MN...............
Stearns County, MN..............
41100..................... St. George, UT................... 0.9265
Washington County, UT...........
41140..................... St. Joseph, MO-KS................ 1.0118
Doniphan County, KS.............
Andrew County, MO...............
Buchanan County, MO.............
DeKalb County, MO...............
41180..................... St. Louis, MO-IL................. 0.9006
Bond County, IL.................
Calhoun County, IL..............
Clinton County, IL..............
Jersey County, IL...............
Macoupin County, IL.............
Madison County, IL..............
Monroe County, IL...............
St. Clair County, IL............
Crawford County, MO.............
Franklin County, MO.............
Jefferson County, MO............
Lincoln County, MO..............
St. Charles County, MO..........
St. Louis County, MO............
Warren County, MO...............
Washington County, MO...........
St. Louis City, MO..............
41420..................... Salem, OR........................ 1.0439
Marion County, OR...............
Polk County, OR.................
41500..................... Salinas, CA...................... 1.4338
Monterey County, CA.............
41540..................... Salisbury, MD.................... 0.8953
Somerset County, MD.............
Wicomico County, MD.............
41620..................... Salt Lake City, UT............... 0.9402
Salt Lake County, UT............
Summit County, UT...............
Tooele County, UT...............
41660..................... San Angelo, TX................... 0.8362
Irion County, TX................
Tom Green County, TX............
41700..................... San Antonio, TX.................. 0.8845
Atascosa County, TX.............
Bandera County, TX..............
Bexar County, TX................
Comal County, TX................
[[Page 25477]]
Guadalupe County, TX............
Kendall County, TX..............
Medina County, TX...............
Wilson County, TX...............
41740..................... San Diego-Carlsbad-San Marcos, CA 1.1354
San Diego County, CA............
41780..................... Sandusky, OH..................... 0.9302
Erie County, OH.................
41884..................... San Francisco-San Mateo-Redwood 1.5166
City, CA.
Marin County, CA................
San Francisco County, CA........
San Mateo County, CA............
41900..................... San Germ[aacute]n-Cabo Rojo, PR.. 0.4885
Cabo Rojo Municipio, PR.........
Lajas Municipio, PR.............
Sabana Grande Municipio, PR.....
San Germ[aacute]n Municipio, PR.
41940..................... San Jose-Sunnyvale-Santa Clara, 1.5543
CA.
San Benito County, CA...........
Santa Clara County, CA..........
41980..................... San Juan-Caguas-Guaynabo, PR..... 0.4452
Aguas Buenas Municipio, PR......
Aibonito Municipio, PR..........
Arecibo Municipio, PR...........
Barceloneta Municipio, PR.......
Barranquitas Municipio, PR......
Bayam[oacute]n Municipio, PR....
Caguas Municipio, PR............
Camuy Municipio, PR.............
Can[oacute]vanas Municipio, PR..
Carolina Municipio, PR..........
Cata[ntilde]o Municipio, PR.....
Cayey Municipio, PR.............
Ciales Municipio, PR............
Cidra Municipio, PR.............
Comer[iacute]o Municipio, PR....
Corozal Municipio, PR...........
Dorado Municipio, PR............
Florida Municipio, PR...........
Guaynabo Municipio, PR..........
Gurabo Municipio, PR............
Hatillo Municipio, PR...........
Humacao Municipio, PR...........
Juncos Municipio, PR............
Las Piedras Municipio, PR.......
Lo[iacute]za Municipio, PR......
Manat[iacute] Municipio, PR.....
Maunabo Municipio, PR...........
Morovis Municipio, PR...........
Naguabo Municipio, PR...........
Naranjito Municipio, PR.........
Orocovis Municipio, PR..........
Quebradillas Municipio, PR......
R[iacute]o Grande Municipio, PR.
San Juan Municipio, PR..........
San Lorenzo Municipio, PR.......
Toa Alta Municipio, PR..........
Toa Baja Municipio, PR..........
Trujillo Alto Municipio, PR.....
Vega Alta Municipio, PR.........
Vega Baja Municipio, PR.........
Yabucoa Municipio, PR...........
.................................
42020..................... San Luis Obispo-Paso Robles, CA.. 1.1599
San Luis Obispo County, CA......
42044..................... Santa Ana-Anaheim-Irvine, CA..... 1.1473
Orange County, CA...............
42060..................... Santa Barbara-Santa Maria-Goleta, 1.1092
CA.
Santa Barbara County, CA........
42100..................... Santa Cruz-Watsonville, CA....... 1.5458
[[Page 25478]]
Santa Cruz County, CA...........
42140..................... Santa Fe, NM..................... 1.0825
Santa Fe County, NM.............
42220..................... Santa Rosa-Petaluma, CA.......... 1.4464
Sonoma County, CA...............
42260..................... Sarasota-Bradenton-Venice, FL.... 0.9868
Manatee County, FL..............
Sarasota County, FL.............
42340..................... Savannah, GA..................... 0.9351
Bryan County, GA................
Chatham County, GA..............
Effingham County, GA............
42540..................... ScrantonWilkes-Barre, PA......... 0.8348
Lackawanna County, PA...........
Luzerne County, PA..............
Wyoming County, PA..............
42644..................... Seattle-Bellevue-Everett, WA..... 1.1434
King County, WA.................
Snohomish County, WA............
42680..................... Sebastian-Vero Beach, FL......... 0.9573
43100..................... Sheboygan, WI.................... 0.9027
Sheboygan County, WI............
43300..................... Sherman-Denison, TX.............. 0.8503
Grayson County, TX..............
43340..................... Shreveport-Bossier City, LA...... 0.8865
Bossier Parish, LA..............
Caddo Parish, LA................
De Soto Parish, LA..............
43580..................... Sioux City, IA-NE-SD............. 0.9201
Woodbury County, IA.............
Dakota County, NE...............
Dixon County, NE................
Union County, SD................
43620..................... Sioux Falls, SD.................. 0.9559
Lincoln County, SD..............
McCook County, SD...............
Minnehaha County, SD............
Turner County, SD...............
43780..................... South Bend-Mishawaka, IN-MI...... 0.9842
St. Joseph County, IN...........
Cass County, MI.................
43900..................... Spartanburg, SC.................. 0.9174
Spartanburg County, SC..........
44060..................... Spokane, WA...................... 1.0447
Spokane County, WA..............
44100..................... Springfield, IL.................. 0.8890
Menard County, IL...............
Sangamon County, IL.............
44140..................... Springfield, MA.................. 1.0079
Franklin County, MA.............
Hampden County, MA..............
Hampshire County, MA............
44180..................... Springfield, MO.................. 0.8469
Christian County, MO............
Dallas County, MO...............
Greene County, MO...............
Polk County, MO.................
Webster County, MO..............
44220..................... Springfield, OH.................. 0.8593
Clark County, OH................
44300..................... State College, PA................ 0.8784
Centre County, PA...............
44700..................... Stockton, CA..................... 1.1443
San Joaquin County, CA..........
44940..................... Sumter, SC....................... 0.8084
Sumter County, SC...............
45060..................... Syracuse, NY..................... 0.9692
Madison County, NY..............
Onondaga County, NY.............
Oswego County, NY...............
[[Page 25479]]
45104..................... Tacoma, WA....................... 1.0789
Pierce County, WA...............
45220..................... Tallahassee, FL.................. 0.8942
Gadsden County, FL..............
Jefferson County, FL............
Leon County, FL.................
Wakulla County, FL..............
45300..................... Tampa-St. Petersburg-Clearwater, 0.9144
FL.
Hernando County, FL.............
Hillsborough County, FL.........
Pasco County, FL................
Pinellas County, FL.............
45460..................... Terre Haute, IN.................. 0.8765
Clay County, IN.................
Sullivan County, IN.............
Vermillion County, IN...........
Vigo County, IN.................
45500..................... Texarkana, TX-Texarkana, AR...... 0.8104
Miller County, AR...............
Bowie County, TX................
45780..................... Toledo, OH....................... 0.9586
Fulton County, OH...............
Lucas County, OH................
Ottawa County, OH...............
Wood County, OH.................
45820..................... Topeka, KS....................... 0.8730
Jackson County, KS..............
Jefferson County, KS............
Osage County, KS................
Shawnee County, KS..............
Wabaunsee County, KS............
45940..................... Trenton-Ewing, NJ................ 1.0836
Mercer County, NJ...............
46060..................... Tucson, AZ....................... 0.9203
Pima County, AZ.................
46140..................... Tulsa, OK........................ 0.8103
Creek County, OK................
Okmulgee County, OK.............
Osage County, OK................
Pawnee County, OK...............
Rogers County, OK...............
Tulsa County, OK................
Wagoner County, OK..............
46220..................... Tuscaloosa, AL................... 0.8542
Greene County, AL...............
Hale County, AL.................
Tuscaloosa County, AL...........
46340..................... Tyler, TX........................ 0.8812
Smith County, TX................
46540..................... Utica-Rome, NY................... 0.8397
Herkimer County, NY.............
Oneida County, NY...............
46660..................... Valdosta, GA..................... 0.8369
Brooks County, GA...............
Echols County, GA...............
Lanier County, GA...............
Lowndes County, GA..............
46700..................... Vallejo-Fairfield, CA............ 1.5138
Solano County, CA...............
47020..................... Victoria, TX..................... 0.8560
Calhoun County, TX..............
Goliad County, TX...............
Victoria County, TX.............
47220..................... Vineland-Millville-Bridgeton, NJ. 0.9832
Cumberland County, NJ...........
47260..................... Virginia Beach-Norfolk-Newport 0.8790
News, VA-NC.
Currituck County, NC............
Gloucester County, VA...........
Isle of Wight County, VA........
James City County, VA...........
[[Page 25480]]
Mathews County, VA..............
Surry County, VA................
York County, VA.................
Chesapeake City, VA.............
Hampton City, VA................
Newport News City, VA...........
Norfolk City, VA................
Poquoson City, VA...............
Portsmouth City, VA.............
Suffolk City, VA................
Virginia Beach City, VA.........
Williamsburg City, VA...........
47300..................... Visalia-Porterville, CA.......... 0.9968
Tulare County, CA...............
47380..................... Waco, TX......................... 0.8633
McLennan County, TX.............
47580..................... Warner Robins, GA................ 0.8380
Houston County, GA..............
47644..................... Warren-Farmington Hills-Troy, MI. 1.0054
Lapeer County, MI...............
Livingston County, MI...........
Macomb County, MI...............
Oakland County, MI..............
St. Clair County, MI............
47894..................... Washington-Arlington-Alexandria, 1.1054
DC-VA-MD-WV.
District of Columbia, DC........
Calvert County, MD..............
Charles County, MD..............
Prince George's County, MD......
Arlington County, VA............
Clarke County, VA...............
Fairfax County, VA..............
Fauquier County, VA.............
Loudoun County, VA..............
Prince William County, VA.......
Spotsylvania County, VA.........
Stafford County, VA.............
Warren County, VA...............
Alexandria City, VA.............
Fairfax City, VA................
Falls Church City, VA...........
Fredericksburg City, VA.........
Manassas City, VA...............
Manassas Park City, VA..........
Jefferson County, WV............
.................................
47940..................... Waterloo-Cedar Falls, IA......... 0.8408
Black Hawk County, IA...........
Bremer County, IA...............
Grundy County, IA...............
48140..................... Wausau, WI....................... 0.9723
Marathon County, WI.............
48260..................... Weirton-Steubenville, WV-OH...... 0.8064
Jefferson County, OH............
Brooke County, WV...............
Hancock County, WV..............
48300..................... Wenatchee, WA.................... 1.0347
Chelan County, WA...............
Douglas County, WA..............
48424..................... West Palm Beach-Boca Raton- 0.9649
Boynton Beach, FL.
Palm Beach County, FL...........
48540..................... Wheeling, WV-OH.................. 0.7010
Belmont County, OH..............
Marshall County, WV.............
Ohio County, WV.................
48620..................... Wichita, KS...................... 0.9063
Butler County, KS...............
Harvey County, KS...............
Sedgwick County, KS.............
Sumner County, KS...............
[[Page 25481]]
48660..................... Wichita Falls, TX................ 0.8311
Archer County, TX...............
Clay County, TX.................
Wichita County, TX..............
48700..................... Williamsport, PA................. 0.8139
Lycoming County, PA.............
48864..................... Wilmington, DE-MD-NJ............. 1.0684
New Castle County, DE...........
Cecil County, MD................
Salem County, NJ................
48900..................... Wilmington, NC................... 0.9836
Brunswick County, NC............
New Hanover County, NC..........
Pender County, NC...............
49020..................... Winchester, VA-WV................ 1.0091
Frederick County, VA............
Winchester City, VA.............
Hampshire County, WV............
49180..................... Winston-Salem, NC................ 0.9276
Davie County, NC................
Forsyth County, NC..............
Stokes County, NC...............
Yadkin County, NC...............
49340..................... Worcester, MA.................... 1.0690
Worcester County, MA............
49420..................... Yakima, WA....................... 0.9848
Yakima County, WA...............
49500..................... Yauco, PR........................ 0.3854
Gu[aacute]nica Municipio, PR....
Guayanilla Municipio, PR........
Pe[ntilde]uelas Municipio, PR...
Yauco Municipio, PR.............
49620..................... York-Hanover, PA................. 0.9398
York County, PA.................
49660..................... Youngstown-Warren-Boardman, OH-PA 0.8802
Mahoning County, OH.............
Trumbull County, OH.............
Mercer County, PA...............
49700..................... Yuba City, CA.................... 1.0731
Sutter County, CA...............
Yuba County, CA.................
49740..................... Yuma, AZ......................... 0.9109
Yuma County, AZ ................
------------------------------------------------------------------------
\1\ At this time, there are no hospitals in these urban areas on which
to base a wage index. Therefore, the urban wage index value is based
on the average wage index of all urban areas within the State.
[FR Doc. 07-2167 Filed 4-27-07; 4:45 am]
BILLING CODE 4120-01-P