Medicare Physician Fees
Geographic Adjustment Indices Are Valid in Design, but Data and Methods Need Refinement Gao ID: GAO-05-119 March 11, 2005The Medicare physician fee schedule adjusts physician fees for area differences in physicians' costs of operating a private medical practice. Three separate indices, known as geographic practice cost indices (GPCI), raise or lower Medicare fees in an area, depending on whether the area's physician practice costs are above or below the national average. The three GPCIs correspond to the three components of a Medicare fee: physician work, practice expense, and malpractice expense. Advocates for rural physicians have criticized the GPCIs, which lower fees in areas where costs are below the national average. The Medicare Prescription Drug, Improvement, and Modernization Act of 2003 directed GAO to evaluate Medicare's method of geographic adjustment. This report examines the extent to which Medicare's GPCIs are valid in their design and appropriate in the data and methods used in their construction, and affect physician incomes, location, recruitment, and retention.
The physician work GPCI, the practice expense GPCI, and the malpractice expense GPCI are valid in their fundamental design as tools to account for geographic cost differences. The three GPCIs as implemented appropriately reflect broad patterns of geographic differences in the costs of running a medical practice. For example, nurses' wages, which constitute a substantial share of physicians' practice expenses, vary across the nation and contribute to differences in practice expenses. In addition to adjusting for cost differences, the work GPCI is valid in that it also reflects a goal of protecting physician fees in low-cost areas from dropping to levels that could be considered unfair relative to fees in high-cost areas. The work GPCI does so by limiting downward cost adjustments. Despite the GPCIs' validity, however, data and methodology problems may detract from the GPCIs as measures of cost differences. For example, the wage data used in the work and practice expense GPCIs are not current, and the data used in the malpractice GPCI are incomplete. The Centers for Medicare & Medicaid Services (CMS) in the Department of Health and Human Services (HHS) has options to remedy some of these flaws. GPCIs appear to have a negligible bearing on physicians' decisions to locate in rural areas. Because Medicare revenue constitutes only part of a physician's income--typically 25 percent--the secondary impact of the GPCIs on a physician's income is generally modest, raising or lowering income by no more than 2 to 3 percent in most localities. GAO's interviews with physician recruitment experts and GAO's review of the literature indicate that income is only one of several factors--such as a spouse's employment opportunities, the quality of local schools, and the availability of other physicians to share night and weekend calls--that drive physicians' decisions to locate in rural areas.
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Director: Team: Phone:GAO-05-119, Medicare Physician Fees: Geographic Adjustment Indices Are Valid in Design, but Data and Methods Need Refinement
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Report to Congressional Committees:
March 2005:
Medicare Physician Fees:
Geographic Adjustment Indices Are Valid in Design, but Data and Methods
Need Refinement:
GAO-05-119:
GAO Highlights:
Highlights of GAO-05-119, a report to congressional committees
Why GAO Did This Study:
The Medicare physician fee schedule adjusts physician fees for area
differences in physicians‘ costs of operating a private medical
practice. Three separate indices, known as geographic practice cost
indices (GPCI), raise or lower Medicare fees in an area, depending on
whether the area‘s physician practice costs are above or below the
national average. The three GPCIs correspond to the three components of
a Medicare fee: physician work, practice expense, and malpractice
expense.
Advocates for rural physicians have criticized the GPCIs, which lower
fees in areas where costs are below the national average. The Medicare
Prescription Drug, Improvement, and Modernization Act of 2003 directed
GAO to evaluate Medicare‘s method of geographic adjustment. This report
examines the extent to which Medicare‘s GPCIs are valid in their design
and appropriate in the data and methods used in their construction, and
affect physician incomes, location, recruitment, and retention.
What GAO Found:
The physician work GPCI, the practice expense GPCI, and the malpractice
expense GPCI are valid in their fundamental design as tools to account
for geographic cost differences. The three GPCIs as implemented
appropriately reflect broad patterns of geographic differences in the
costs of running a medical practice. For example, nurses‘ wages, which
constitute a substantial share of physicians‘ practice expenses, vary
across the nation and contribute to differences in practice expenses.
(See table.)
Geographic Differences in Hourly Wage for Registered Nurses, 2000:
Medicare payment locality: Oakland/Berkeley, California;
Median hourly wage for registered nurses: $29.16.
Medicare payment locality: Massachusetts, excluding metropolitan
Boston;
Median hourly wage for registered nurses: $22.06.
Medicare payment locality: Fort Worth, Texas;
Median hourly wage for registered nurses: $21.26.
Medicare payment locality: New Mexico;
Median hourly wage for registered nurses: $19.83.
Medicare payment locality: South Carolina;
Median hourly wage for registered nurses: $19.60.
Source: GAO analysis of data from CMS and U.S. Census Bureau.
[End of table]
In addition to adjusting for cost differences, the work GPCI is valid
in that it also reflects a goal of protecting physician fees in low-
cost areas from dropping to levels that could be considered unfair
relative to fees in high-cost areas. The work GPCI does so by limiting
downward cost adjustments. Despite the GPCIs‘ validity, however, data
and methodology problems may detract from the GPCIs as measures of cost
differences. For example, the wage data used in the work and practice
expense GPCIs are not current, and the data used in the malpractice
GPCI are incomplete. The Centers for Medicare & Medicaid Services (CMS)
in the Department of Health and Human Services (HHS) has options to
remedy some of these flaws.
GPCIs appear to have a negligible bearing on physicians‘ decisions to
locate in rural areas. Because Medicare revenue constitutes only part
of a physician‘s income”typically 25 percent”the secondary impact of
the GPCIs on a physician‘s income is generally modest, raising or
lowering income by no more than 2 to 3 percent in most localities.
GAO‘s interviews with physician recruitment experts and GAO‘s review of
the literature indicate that income is only one of several factors”such
as a spouse‘s employment opportunities, the quality of local schools,
and the availability of other physicians to share night and weekend
calls”that drive physicians‘ decisions to locate in rural areas.
What GAO Recommends:
GAO recommends that HHS improve the GPCIs by augmenting the data and
refining the methods used to construct them. HHS characterized GAO‘s
findings as important but disagreed with most of the recommendations,
citing concerns about when they could be implemented. GAO holds that
its recommendations account for these timing issues.
www.gao.gov/cgi-bin/getrpt?GAO-05-119.
To view the full product, including the scope and methodology, click on
the link above. For more information, contact A. Bruce Steinwald at
(202) 512-7119.
[End of section]
Contents:
Letter:
Results in Brief:
Background:
GPCIs Are Generally Valid in Design, but CMS's Data and Methods Have
Weaknesses:
GPCIs Appear to Have Little Effect on Physicians' Incomes, Location,
Recruitment, and Retention:
Conclusions:
Recommendations for Executive Action:
Agency and Industry Comments and Our Evaluation:
Appendixes:
Appendix I: Data and Methods:
Appendix II: Rent Indexes and the Practice Expense GPCI:
Appendix III: Comments from the Department of Health and Human
Services:
Appendix IV: GAO Contact and Staff Acknowledgments:
GAO Contact:
Acknowledgments:
Tables Tables:
Table 1: The Physician Work, Practice Expense, and Malpractice GPCIs
for Five Payment Localities, 2004:
Table 2: The Medicare Physician Fee for a Midlevel Office Visit in Five
Payment Localities, 2004:
Table 3: Geographic Differences in Hourly Wage for Registered Nurses,
2000:
Table 4: Hypothetical Example of GPCIs' Effect on Income of Physicians
with Identical Number and Types of Services Who Derive One-Quarter of
Professional Income from Medicare, 2004:
Table 5: Data Sources Used in CMS's Construction of GPCIs:
Table 6: Factors Explaining Variation in Physicians' Average Annual
Income for 513 Geographic Areas:
Figures:
Figure 1: Effect of Different Policies Altering the Work GPCI on the
Weighted Average of the Three GPCIs in an Urban Area (Oakland/Berkeley,
California) and in a Relatively Rural Area (South Carolina):
Figure 2: Variation in Private Plans' Physician Fees and Average
Medicare GPCI by Medicare Payment Locality, 2002:
Figure 3: Number of Retirements of Iowa Physicians and Standard & Poors
Composite Index of Stock Prices, 1993-2003:
Letter March 11, 2005:
The Honorable Charles E. Grassley:
Chairman:
The Honorable Max Baucus:
Ranking Minority Member:
Committee on Finance:
United States Senate:
The Honorable Joe Barton:
Chairman:
The Honorable John D. Dingell:
Ranking Minority Member:
Committee on Energy and Commerce:
House of Representatives:
The Honorable William M. Thomas:
Chairman:
The Honorable Charles B. Rangel:
Ranking Minority Member:
Committee on Ways and Means:
House of Representatives:
Since 1992, when Medicare's physician fee schedule was put into place,
physicians' fees have been adjusted for area differences in physicians'
costs of operating a private medical practice. The purpose of this
adjustment is to help ensure that Medicare's payment is appropriate and
adequate in all areas. Three separate indices, known as geographic
practice cost indices (GPCI), are used in making the geographic fee
adjustments. These GPCIs raise or lower Medicare fees in an area,
depending on whether that area's costs of staff and other expenses--
including office rent, malpractice premiums, and the cost of
physicians' own time--are above or below the national average. The
three GPCIs correspond to the three main components of a Medicare fee:
physician work, practice expense, and malpractice expense. As part of
its responsibility to set and adjust Medicare fees, the Centers for
Medicare & Medicaid Services (CMS) in the Department of Health and
Human Services (HHS) determines the methodology used to develop the
GPCIs.
Since the implementation of the GPCIs, physician groups have expressed
concerns about the data and methods used to construct them. In 1991,
the year before the GPCIs' implementation, CMS (at the time called the
Health Care Financing Administration (HCFA))[Footnote 1] noted that the
cost would be prohibitive to collect the detailed locality-level data
needed to measure every area's staff costs and other expenses compared
to the national average. The agency therefore limited data sources to
those that existed and were readily available, selecting data proxies
for each GPCI. Physicians have viewed certain of these proxies as
detracting from the GPCIs as measures of cost differences. For example,
physician groups find fault with CMS's use of apartment rent as a proxy
for physician office rent in constructing the practice expense GPCI.
Groups representing physicians practicing in rural areas have also
questioned the GPCIs' fairness, as GPCIs adjust fees downward when an
area's costs and expenses are lower than the national average. The
contention is that setting Medicare fees higher in an urban area is
unfair because an internist in rural Maine, for example, does the same
work in providing care to a patient as an internist in Los Angeles.
Advocates for rural physicians also argue that GPCI-related disparities
in Medicare payment are jeopardizing the supply of physicians in rural
areas.
In the Medicare Prescription Drug, Improvement, and Modernization Act
of 2003 (MMA), Congress directed GAO to evaluate several issues related
to physician compensation, among them Medicare's method of geographic
adjustment and the potential for such adjustment to affect physician
location, recruitment, and retention--matters related to physician
supply.[Footnote 2] In this report, we examine (1) the extent to which
the GPCIs are valid in their fundamental design and appropriate in the
data and methods used to measure cost differences and (2) whether GPCIs
affect physician incomes, location, recruitment, and retention.
To assess the GPCIs' validity, we reviewed the design of each GPCI to
determine if the design was appropriate for achieving the intended
objectives in geographically adjusting physician fees.[Footnote 3] In
addition, we reviewed the data and methods that CMS used to construct
the GPCIs. These data included wage and malpractice premium data from
CMS as well as fair market rent (FMR) data from the Department of
Housing and Urban Development (HUD). We also reviewed an index of
geographic differences in commercial rents, using U.S. Postal Service
(USPS) data, in order to assess the rent component of the practice
expense GPCI.
To examine the impact of GPCIs and other factors on geographic
differences in physicians' income, we examined data from the 2003 Area
Resource File, which is maintained by the Health Resources and Services
Administration; Medicare physician claims; and survey data from the
American Medical Association Physician Socioeconomic Statistics 2000-
2002 Edition. To assess the roles of market factors and GPCIs in
explaining the geographic variation in physician income, we obtained an
analysis commissioned by the Medicare Payment Advisory Commission
(MedPAC) comparing private insurers' fees to geographically adjusted
Medicare fees. To analyze the extent to which income, Medicare fees,
and other factors affect physician location, recruitment, and
retention, we reviewed relevant literature, including an analysis of
the retention of physicians from the University of Iowa Carver College
of Medicine. We also interviewed physician recruiters, physician
groups, and other experts on GPCI-related topics. We did not review
such non-GPCI factors as volume and type of service that may result in
geographic variations in Medicare payments to physicians because these
issues were outside our scope. For more details on our data and
methods, see appendix I. We performed our work according to generally
accepted government auditing standards from January 2003 through March
2005.[Footnote 4]
Results in Brief:
The work GPCI, the practice expense GPCI, and the malpractice GPCI are
valid in their fundamental design as tools to account for geographic
cost differences. The three GPCIs, as implemented, appropriately
reflect broad patterns of geographic differences in the costs of
running a medical practice. For example, nurses' median hourly wages
across the United States range widely--for example, in 2000, from
$19.60 in South Carolina to $29.16 in Oakland, California. Since
nurses' wages vary across the nation and constitute a significant share
of physicians' practice expenses, nurses' wages contribute to
geographic differences in practice expenses. In addition to adjusting
for cost differences, the work GPCI is valid in that it also reflects a
goal of protecting physician fees in low-cost areas from dropping to
levels that could be considered unfair relative to fees in high-cost
areas. The work GPCI does so by limiting downward cost adjustments.
However, problems with data and methodology underlying the GPCIs may
detract from the GPCIs as measures of cost differences. For example,
the wage data used in the work and practice expense GPCIs are not
current, and the data used in the malpractice GPCI are incomplete. CMS
has options to remedy these and other problems.
GPCIs appear to have a negligible bearing on matters of physician
supply--location, recruitment, and retention--in rural areas. Because
Medicare revenue constitutes only part of a physician's income--
typically 25 percent--the impact of the adjustment factors on
physicians' income is generally modest, raising or lowering income by
no more than 2 to 3 percent in most localities. Our interviews with
physician recruitment experts and published studies indicate that
income is only one of many factors affecting physicians' decisions to
locate in rural areas and in employers' successful efforts to recruit
and retain physicians. These factors include a spouse's employment
opportunities, the quality of local schools, and the availability of
other physicians to share night and weekend calls. Given GPCIs' limited
effect on physician income and income's secondary effect on physician
supply, GPCIs are not important factors in physician location,
recruitment, and retention.
We are making several recommendations to the Secretary of Health and
Human Services to improve the data and methods used to construct the
GPCIs. Among them, we recommend refining the practice expense GPCI by
augmenting wage data and replacing the rent index; we also recommend
refining the malpractice GPCI by making the input data more complete
and representative and by standardizing data collection. In commenting
on a draft of this report, HHS characterized our findings as important
but disagreed with most of our recommendations to refine the GPCIs'
input data and methods because of concerns about the timing of their
implementation. GAO contends that the steps recommended explicitly take
account of these timing issues. Two national physicians' associations
also reviewed the draft report, stating that it provided a good
description of the GPCIs and current GPCI issues. One of the
associations agreed with our analysis of the GPCIs' validity and of
their effect on physician location, while the other disputed the GPCIs'
validity and maintained that the physician fee for a service should be
the same, regardless of location.
Background:
The Medicare physician fee schedule has distinct payment rates for over
7,000 services, from office visits to complex surgical and diagnostic
procedures. It has been in effect since 1992, and, although there have
been some modifications, its basic structure has not changed.
Medicare Physician Payment:
Each of the more than 7,000 services on the Medicare physician fee
schedule has three relative value units (RVU), which correspond to the
three components of physician payment:
* Physician work--the financial value of physicians' time, skill, and
effort that are associated with providing the service.
* Practice expense--the costs incurred by physicians in employing
office staff, renting office space, and buying supplies and equipment.
* Malpractice expense--the premiums paid by physicians for professional
liability insurance.
On average across all procedures, work represents 52.5 percent of total
RVUs, practice expense represents 43.7 percent, and malpractice 3.9
percent.[Footnote 5]
Each RVU measures the relative costliness of providing a particular
service. For example, for a midlevel office visit for an established
patient,[Footnote 6] the most common Medicare procedure, the RVU for
the practice expense component is 0.71, meaning that this procedure is
half as costly as a chemotherapy infusion procedure[Footnote 7] with a
practice expense RVU of 1.42.
To calculate a fee for a service, each of the three RVUs for a service
is adjusted for geographic differences in resource costs and converted
into dollars. This process has several steps. First, each of the three
RVUs is multiplied by its geographic adjuster. Second, these adjusted
RVUs are added together. Third, that sum is converted into dollars
using a conversion factor--a dollar amount calculated by CMS that
translates each service's RVUs into a payment amount. The sum of these
adjusted RVUs for a particular service in a particular area, multiplied
by the conversion factor, results in the Medicare fee for that service
in that area.[Footnote 8] For example, in Cleveland, Ohio, in 2004, the
adjusted RVUs for a midlevel office visit sum to 1.37; multiplied by
the conversion factor ($37.3374), the Medicare fee for this procedure
in Cleveland is $51.13. By contrast, in Little Rock, Arkansas, where
practice costs are lower, the adjusted RVUs total 1.28, which the
conversion factor translates into the Medicare fee for a midlevel
office visit in Little Rock of $47.73. Updates that change the GPCIs'
values effectively redistribute payments among Medicare payment
localities but do not generally alter total Medicare outlays for
physicians' services.
The physician fee schedule was designed to increase payment rates for
primary care services compared to rates for services typically
performed by specialists. Rural physicians overall have benefited from
the introduction of the physician fee schedule, since the proportion of
physicians delivering mostly primary care--in particular, family and
general practice physicians--is higher in rural areas than in urban
areas.
GPCIs for Physician Work, Practice Expense, and Malpractice:
GPCIs adjust payments for differences among 89 distinct Medicare
payment localities (technically known as fee schedule areas) in
physicians' costs of providing Medicare services. Thirty-four of these
localities are statewide and include both urban and rural
areas.[Footnote 9] The remainder includes large metropolitan areas such
as Manhattan, New York, and smaller, less populated metropolitan areas
such as Santa Clara, California. These payment localities differ in
size, population density, and the extent to which they are urban or
rural. Practice costs tend to vary considerably within many payment
localities, especially those that contain both urban and rural areas.
The three GPCIs--work, practice expense, and malpractice--are numerical
factors expressed as the ratio of an area's cost to the national
average cost. For example, the practice expense GPCI for Cleveland,
Ohio, is 0.944, which means that the practice expense component of the
fee for a service is 5.6 percent below the national average. The work
GPCI measures the relative cost to a practice in a particular locality
of a physician's time, skill, and effort, while the practice expense
and malpractice GPCIs measure the relative costs of obtaining resources
to operate a practice and acquiring malpractice insurance. CMS is
required to review the GPCIs at least every 3 years and, based on that
review, may revise them using the most recent available data.
Unlike the other two GPCIs, the work GPCI measures relative costs
exclusively by an indirect measure: the relative wages of six
categories of nonphysician professional occupations, including lawyers,
architects, social workers, and teachers.[Footnote 10] Geographic
differences in the wages of the six professions are used to capture the
differences among geographic areas in living costs and the value of
amenities.[Footnote 11] These data are drawn from the decennial census;
consequently, CMS updates the work GPCI only once every 10 years. By
law, the work GPCI incorporates only one-quarter of the difference
between localities in the six professions' wages, meaning that a 20
percent difference in wages results in a 5 percent difference in the
work GPCI.
The practice expense GPCI is designed to adjust for geographic
differences in three types of costs incurred by a practice:
nonphysician staff wages, office rent, and costs of supplies and
equipment.
* In calculating the relative wages of nonphysician staff, CMS uses
wage data from the decennial census for four occupations: registered
nurses, licensed practical nurses, health technicians, and
administrative staff.
* In measuring physician office rent, CMS uses a proxy--HUD's FMR
residential index of the average rent for a two-bedroom
apartment.[Footnote 12] CMS relies on the FMR residential index because
measures of commercial office rent have not been available for
nonmetropolitan areas and for some metropolitan areas.
* In regard to the costs of supplies and equipment, CMS treats these
costs as uniform nationwide since it considers the market for these
items to be national, not local or regional.
The malpractice GPCI is based on average malpractice premiums in a
payment locality. CMS obtains premium data from state insurance
departments and private insurers. In calculating the average premium
for a payment locality, CMS weights the average malpractice premiums
for a county within a payment locality by total RVUs for the county--a
measure of the volume and complexity of Medicare services in the county.
Each GPCI varies by geographic area, as table 1 shows. The work and
practice expense GPCIs tend to be higher in large metropolitan areas
and lower in predominantly rural payment localities.
Table 1: The Physician Work, Practice Expense, and Malpractice GPCIs
for Five Payment Localities, 2004:
Payment locality[A]: Oakland/Berkeley, California;
Physician work: GPCI: 1.041;
Practice expense GPCI: 1.235;
Malpractice: GPCI: 0.669.
Payment locality[A]: Massachusetts, excluding metropolitan Boston area;
Physician work: GPCI: 1.010;
Practice expense GPCI: 1.129;
Malpractice: GPCI: 0.803.
Payment locality[A]: Fort Worth, Texas;
Physician work: GPCI: 1.000[B];
Practice expense GPCI: 0.981;
Malpractice: GPCI: 0.996.
Payment locality[A]: New Mexico;
Physician work: GPCI: 1.000[B];
Practice expense GPCI: 0.900;
Malpractice: GPCI: 0.898.
Payment locality[A]: South Carolina;
Physician work: GPCI: 1.000[B];
Practice expense GPCI: 0.904;
Malpractice: GPCI: 0.336.
Source: CMS.
[A] Selected localities represent the 90th, 75th, 50th, 25th, and 10th
percentiles of the Medicare payment localities ranked by the weighted
average of their GPCIs. Localities above the 90th percentile include
Manhattan, New York; San Francisco, California; Santa Clara,
California; San Mateo, California; New York City Suburbs/Long Island,
New York; Queens, New York; metropolitan Boston; and Northern New
Jersey. Those below the 10th percentile include Arkansas; Missouri,
excluding St. Louis and Kansas City; Mississippi; South Dakota;
Oklahoma; Nebraska; Idaho; and Iowa. Alaska was excluded from the
analysis because the MMA set Alaska's GPCIs at 1.67.
[B] MMA set a temporary floor of 1.00 for the physician work GPCI.
[End of table]
Applying the GPCIs to their respective RVUs for a single service, such
as a midlevel office visit, results in a Medicare fee that varies
geographically. (See table 2.) Since the work, practice expense, and
malpractice RVUs for a single service are the same in every payment
locality, this variation in the Medicare fee for that service mirrors
the variation in the GPCIs across payment localities. For example, for
Oakland the Medicare fee for a midlevel office visit is $59.32. By
contrast, for South Carolina the Medicare fee for the same office
visit, $49.14, is lower because the fee is calculated using different,
lower values for the GPCIs, which reflect lower practice costs.
Table 2: The Medicare Physician Fee for a Midlevel Office Visit in Five
Payment Localities, 2004:
Payment locality[A]: Oakland/Berkeley, California;
Medicare physician fee for: a midlevel office visit[B]: $59.32.
Payment locality[A]: Massachusetts, excluding metropolitan Boston area;
Medicare physician fee for a midlevel office visit[B]: $55.97.
Payment locality[A]: Fort Worth, Texas;
Medicare physician fee for a midlevel office visit[B]: $52.14.
Payment locality[A]: New Mexico;
Medicare physician fee for a midlevel office visit[B]: $49.88.
Payment locality[A]: South Carolina;
Medicare physician fee for a midlevel office visit[B]: $49.14.
Source: GAO calculation using CMS data.
[A] Selected localities represent the 90th, 75th, 50th, 25th, and 10th
percentiles of the Medicare payment localities ranked by the weighted
average of their GPCIs. Localities above the 90th percentile include
Manhattan, New York; San Francisco, California; Santa Clara,
California; San Mateo, California; New York City Suburbs/Long Island,
New York; Queens, New York; metropolitan Boston; and Northern New
Jersey. Those below the 10th percentile include Arkansas; Missouri,
excluding St. Louis and Kansas City; Mississippi; South Dakota;
Oklahoma; Nebraska; Idaho; and Iowa. Alaska was excluded from the
analysis because the MMA set Alaska's GPCIs at 1.67.
[B] A midlevel office visit is technically known as "office or other
outpatient visit for the evaluation and management of an established
patient." It is CPT code 99213.
[End of table]
Evolution of GPCIs:
In the Omnibus Budget Reconciliation Act of 1989,[Footnote 13] Congress
required the establishment of a national Medicare physician fee
schedule, which would allow for some variation in fees to reflect
physician practice cost differences across the country. It required the
use of the three GPCIs to measure these cost differences and adjust
fees accordingly. Before the physician fee schedule was established,
Medicare payments to physicians varied widely, not only between urban
and rural areas, but also among metropolitan areas and among rural
areas. In addition, variations in Medicare charges (the basis of
Medicare payments prior to the fee schedule) were largely not explained
by costs. When the physician fee schedule was established, there was
consensus among experts that the practice expense and malpractice
components of the Medicare physician fee be geographically adjusted in
line with underlying costs. In contrast, little agreement existed on
whether the work component should be adjusted, and a compromise was
struck: only one-quarter of the variation in the proxy for physicians'
earnings would constitute the work GPCI.[Footnote 14]
Changes made to GPCIs since their implementation have further limited
the extent of geographic adjustment and have tended to raise fees in
rural areas above what they would have been without the changes.
* The payment localities were consolidated in 1997, reducing the number
from 210 to 89.[Footnote 15] This consolidation generally resulted in
slightly higher GPCIs for smaller, more rural areas that were merged
into metropolitan or statewide areas. By contrast, urban areas that had
previously had their own geographic adjustment and were merged into
larger nonmetropolitan or statewide areas generally received a lower
GPCI due to the consolidation.
* In December 2003, Congress established a temporary floor for the work
GPCI of 1.0 as part of a package of payment increases to Medicare
providers in rural areas.[Footnote 16] This action further reduced
geographic variation by raising the work GPCI to 1.0 (which had been
the national average) in all payment localities where it would
otherwise have been less than 1.0.
The effects of the quarter-variation work GPCI and the temporary floor
for the work GPCI on the weighted average of the three GPCIs are
illustrated in figure 1.[Footnote 17] Figure 1 also shows the effect of
a hypothetical 100 percent work adjustment to the work GPCI (instead of
the current adjustment of 25 percent) and, alternatively, the effect of
a hypothetical elimination of the work GPCI.
Figure 1: Effect of Different Policies Altering the Work GPCI on the
Weighted Average of the Three GPCIs in an Urban Area (Oakland/Berkeley,
California) and in a Relatively Rural Area (South Carolina):
[See PDF for image]
[End of figure]
Geographic Distribution of Physicians and Federal Efforts to Augment
Rural Supply:
Differences in the geographic distribution of physicians are long-
standing and predate GPCIs and the Medicare physician fee schedule.
Compared to larger metropolitan areas, smaller metropolitan areas and
rural areas typically have had fewer physicians per capita. These
differences are greater for specialists than for primary care
physicians.[Footnote 18]
Several federal programs are designed to encourage physicians to
practice in areas with perceived shortages. Shortage areas are those
areas in which the physician-to-population ratio is below a threshold.
For example, the Medicare Incentive Payment program pays physicians 10
percent more than the usual Medicare fee for services provided to
beneficiaries in health professional shortage areas.[Footnote 19] For
2005 through 2007, MMA adds a 5 percent incentive to the Medicare fee
for primary care and specialist physicians providing services in
physician scarcity areas.[Footnote 20]
Other programs use different tools to address physician supply. For
example, the National Health Service Corps focuses on debt burden--
repaying the educational loans of physicians and other primary care
professionals who agree to provide primary health care in a health
professional shortage area for 2 years.
GPCIs Are Generally Valid in Design, but CMS's Data and Methods Have
Weaknesses:
In adjusting Medicare physician fees for geographic cost differences,
the GPCIs are valid in their fundamental design, but data weaknesses
detract from them as measures of cost differences. Specifically, the
work GPCI is generally valid as a tool to both adjust for cost
differences and bolster payments to physicians in low-cost areas by
limiting downward adjustments. The data used to construct the work GPCI
are not current, but new data sources will enable CMS to improve the
currency of the data used. The practice expense and malpractice GPCIs
are generally valid as tools to adjust for geographic differences in
office expenses and malpractice insurance premiums. Data to construct
the practice expense GPCI have been available only once each decade but
can be updated through a newly available data source. In addition, the
credibility of the practice expense GPCI could be enhanced with the use
of a newly available commercial rent index. The data CMS uses to
construct the malpractice GPCI have several weaknesses, which the
agency can remedy through increased methodological rigor.
Work GPCI Balances Two Objectives; New Data Source Will Make It More
Current:
Although critics of the work GPCI have disputed its validity, we found
that the work GPCI is generally valid as a tool to adjust for cost
differences and bolster payments to physicians in low-cost areas by
limiting downward adjustments. However, the data used to construct the
work GPCI are not current. A new data source that is expected to be
available soon has the potential to improve the currency of the data
used.
Validity of Work GPCI:
The work GPCI, which adjusts the component of the fee that reflects the
physician's time, is valid in its embodiment of two policy objectives.
The first is to pay physicians who perform the same services in
different areas the amount sufficient for them to supply these
services, while the second is to narrow the difference in fees between
rural and urban physicians. The work GPCI achieves each objective in
part: it raises fees in areas with higher living costs and lowers fees
in areas with lower costs--consistent with the concept of adjustment
for geographic cost differences; it also narrows the disparities in
fees between areas by limiting the full extent of downward adjustment
that would occur without such limits.
Under the work GPCI, downward adjustments to the work component of
physician fees are limited in three ways: the adjustment constitutes
only one-quarter of the variation in the proxy for physicians'
earnings, the temporary floor introduced in MMA prevents the work GPCI
from falling below 1.0, and the consolidation of payment localities has
resulted in higher GPCIs on average for the consolidated locality than
for the low-cost areas within it. As a result of these limits, the work
component of the 2004 fee for a midlevel office visit in Oakland/
Berkeley, California, for example, is $1.03 higher than in South
Carolina. Without the work GPCI limitations, the difference in the work
component of the fee would have been $6.71.
Measurement of Work GPCI:
The data used for the work GPCI are not sufficiently up-to-date. Since
1992, the source of wage data for the work GPCI has been the decennial
census's long form,[Footnote 21] which was last administered in 2000.
A new data source that is under development will make the work GPCI
more current. The Census Bureau plans to replace the long form with the
American Community Survey (ACS), an annual survey designed to produce
more current data. The ACS is designed as a continuous survey. For
larger communities (defined by Census as those with populations over
65,000), the ACS data are expected to yield usable estimates each year;
for smaller communities, data must be accumulated over 3 to 5 years,
depending upon community size.[Footnote 22] Beginning in 2010, CMS
should be able to use the ACS to construct GPCIs for all areas in the
nation, contingent upon the resolution of several technical issues
regarding the Census Bureau's implementation of the ACS. The Census
Bureau is working with government agencies that have used data from the
long form to transition to the ACS.[Footnote 23]
Compared to the decennial census, ACS data will be more up-to-date but
are unlikely to change the work GPCI substantially. The work GPCI is
based on relative wages--the average of the median hourly wages of six
nonphysician professional categories in a geographic area relative to
the national average. Relative wages are generally stable over time. If
this stability continues, the newer ACS data may not make much
difference quantitatively.
In constructing the work GPCI, CMS does not rely on direct measures of
physicians' earnings, which are contained in the decennial census data,
because of two drawbacks:
* Geographic differences in physician earnings are likely to be
misleading as a measure of geographic differences in living costs and
the value of amenities. Physicians' earnings by geographic area vary
with the volume of services provided to patients and the complexity and
costliness of these services.[Footnote 24] If the work GPCI was based
on physician earnings, these differences in the volume and intensity of
services could increase the work GPCI in high-expenditure areas and
lower it in low-expenditure areas. Similarly, since physicians'
earnings vary by specialty and the census data do not identify a
physician's specialty, geographic differences in the mix of specialties
could increase the work GPCI in areas with relatively large numbers of
high-earning specialists and lower it in areas with relatively few.
* Using physicians' earnings would produce a circular measure: the work
adjustment would depend on past payments to physicians, including past
Medicare payments.[Footnote 25]
Practice Expense GPCI Generally Valid in Design, but Can Be Better
Measured:
The practice expense GPCI is generally valid in its fundamental design
as a tool to geographically adjust physician office and other practice
expenses. However, the data CMS used to measure practice expense have
drawn criticism and may be improved by the availability of new data
sources.
Validity of Practice Expense GPCI:
In its fundamental design, the practice expense GPCI is generally valid
for the physician payment localities. These localities differ--
sometimes sharply--in rent for office space and wage rates for office
staff and nurses.[Footnote 26] For example, the median hourly wage for
registered nurses in 2000 was $29.16 in Oakland/Berkeley, California,
compared to $19.60 in South Carolina. (See table 3.) In taking account
of systematic differences in rent and wage rates, the practice expense
GPCI gives physicians who provide a particular Medicare service in
different geographic areas the ability to obtain roughly equivalent
amounts of office space, nurses' time, and other resources with their
Medicare fee.
Table 3: Geographic Differences in Hourly Wage for Registered Nurses,
2000:
Payment locality[A]: Oakland/Berkeley, California;
Median hourly wage for registered nurses: $29.16.
Payment locality[A]: Massachusetts, excluding;
metropolitan Boston;
Median hourly wage for registered nurses: $22.06.
Payment locality[A]: Fort Worth, Texas;
Median hourly wage for registered nurses: $21.26.
Payment locality[A]: New Mexico;
Median hourly wage for registered nurses: $19.83.
Payment locality[A]: South Carolina;
Median hourly wage for registered nurses: $19.60.
Source: GAO analysis of data from CMS and U.S. Census Bureau.
[A] Selected localities represent the 90th, 75th, 50th, 25th, and 10th
percentile of the Medicare payment localities ranked by the weighted
average of their GPCIs. Localities above the 90th percentile include
Manhattan, New York; San Francisco, California; Santa Clara,
California; San Mateo, California; New York City Suburbs/Long Island,
New York; Queens, New York; metropolitan Boston; and Northern New
Jersey. Those below the 10th percentile include Arkansas; Missouri,
excluding St. Louis and Kansas City; Mississippi; South Dakota;
Oklahoma; Nebraska; Idaho; and Iowa. Alaska was excluded from the
analysis because the MMA set Alaska's GPCIs at 1.67.
[End of table]
Measurement of Practice Expense GPCI:
In the future, new data sources will become available that could be
used in updating the practice expense GPCI. As with the work GPCI, the
shift from the decennial census long form to the ACS will produce wage
data for the practice expense GPCI that are more current and make it
possible to update this GPCI annually. The new ACS data may not alter
the practice expense GPCI much, since relative wages by geographic area
change little over time.
Nonetheless, opportunities exist to improve the data CMS uses to
measure geographic differences in the practice expense GPCI. First, CMS
does not use certain readily available data in constructing the wage
component of the practice expense GPCI. For example, data on one type
of nonphysician staff--physician assistants--are available from the
decennial census and are expected to be available from the ACS. These
data could be incorporated into the calculation of the practice expense
GPCI. Doing so would enhance its credibility, but the effect of the
inclusion of these data is likely to be slight.[Footnote 27]
Second, a new data source on commercial rent holds some promise for
improving measurement of one component of the practice expense GPCI
since the FMR index, which measures the rent of a two-bedroom
apartment, has several weaknesses as a measure of physician office
rent. This reliance on a residential rent index is a technical problem
that reduces the practice expense GPCI's credibility, as physician
offices are typically located in commercial buildings rather than in
physicians' personal residences. Further disadvantages of the FMR
include its focus on rents relevant to subsidized housing and HUD's
practice of permitting local public housing authorities, in some cases,
to affect an area's FMR by substituting other data. However,
systematic, representative data on physician office rent throughout the
country are not available, and data on commercial office rent have been
available only for metropolitan areas.
Two alternatives to the current rent index are available or will be
soon. First, in 2004, a potential measure of commercial office rent
nationwide became available: A researcher sponsored by the USPS created
an index of commercial rent for both urban and rural areas. (See app.
II.) This commercial rent index,which is based on rents paid by USPS
for post office space, is consistent with the pattern of higher rents
in large metropolitan areas than in rural areas. Although this rent
index is promising, before it could be incorporated into the practice
expense GPCI, CMS would need to ensure that the index was better than
the alternatives in terms of technical characteristics and credibility
and that it would be available for CMS's use in the future.
If the commercial rent index proves infeasible for use in the practice
expense GPCI, an apartment rent index constructed directly from ACS
rent data could be used, assuming that outstanding technical issues
regarding the Census Bureau's implementation of the ACS are
resolved.[Footnote 28] The ACS rent index would not have the
disadvantages of the FMR and could rely on standard methods of index
construction, rather than the distinctive methods used for the FMR.
Malpractice GPCI Valid in Design, but CMS's Data and Methods Remain a
Concern:
The malpractice GPCI is valid in its fundamental design, but issues
regarding the data and methods used in constructing this GPCI reduce
its credibility. The index can be improved by applying rigorous
procedures throughout the data collection and aggregation process.
Validity of Malpractice GPCI:
The malpractice GPCI's adjustment of Medicare physician fees for
geographic differences in malpractice expense is valid in its design
because it promotes a level playing field for physician practices in
different geographic areas where malpractice premiums vary widely. That
is, the malpractice GPCI permits Medicare fees to contribute Medicare's
share toward physicians buying a standard amount of malpractice
coverage, regardless of where physicians practice. Failure to take
these differences into account would penalize physicians in areas where
malpractice premiums are high. These average premium differences
between areas reflect differences in state law, decisions of state and
local courts, and the concentration of specialties--especially
orthopedic surgery and other specialties that often experience lawsuits.
Measurement of Malpractice GPCI:
CMS's methods for collecting malpractice premium data and aggregating
them into the malpractice GPCI contain several flaws. The collective
impact of these weaknesses on relative malpractice premiums is
uncertain.
Two weaknesses pertain to CMS's 2004 update of this GPCI and are
relatively broad in scope:
* CMS made two adjustments--once as required by law and once at its own
initiative--to deal with a potential problem: sharp changes in
physician fee schedule amounts due to the malpractice GPCI update. The
law requires that changes in GPCIs be phased in, half in the first year
and half in the second--when more than 1 year has elapsed since the
date of the last adjustment. In addition, CMS introduced an adjustment,
termed a "modulating factor," of 0.5, which further limited the change
in the malpractice GPCI. The result was that in 2004, physicians'
Medicare fees reflected only one-quarter of the change in the
malpractice GPCI, compared to the 2003 malpractice GPCI.
* CMS's measure of average malpractice premiums may understate or
overstate geographic differences in malpractice premiums, since CMS's
measure does not adjust for geographic differences between insurers in
the mix of specialties that they cover. For example, average
malpractice premiums paid by all physicians covered by a specific
insurer are likely to be overstated when that insurer has an above-
average proportion of physicians who are neurosurgeons and orthopedic
surgeons, whose premiums tend to be high. Likewise, average premiums
are likely to be understated when the proportion of such specialists
covered by a specific insurer is low.
Two flaws in calculating the malpractice GPCI were rooted in CMS's
process for updating premium data for 2002.
* One flaw--incomplete data--resulted from CMS's efforts to make the
malpractice GPCI more current. Due to concerns that malpractice premium
data were out-of-date, CMS's contractor collected malpractice premium
data for 2002. On the basis of those data and previously collected data
for 1999 through 2001, the contractor projected premiums by geographic
area for 2003 and calculated the malpractice GPCI for each payment
locality. However, the 2002 data were incomplete: CMS's contractor,
which allotted 7 weeks for data collection, was able to collect premium
data for only 33 states. The contractor imputed premiums for the other
17 states, the District of Columbia, and Puerto Rico. The imputation
method was reasonable, but CMS did not report on any tests of this
method's performance--for example, comparing actual 2001 data to
imputed 2001 data. CMS also did not report testing the accuracy of its
method of projecting 2003 premiums. For example, the 1999 through 2001
data could have been used to project 2002 premiums, which could have
been compared to the actual 2002 premiums for the payment localities
for which CMS has data. (See app. I.)
* The second flaw was that the 2002 data for the 33 states were
potentially unrepresentative, as CMS's contractor collected data from
only one insurer per state. Under its previous procedure, CMS collected
data from insurers that accounted for at least half of the malpractice
insurance business in a state.
Opportunities exist for CMS to improve the malpractice GPCI as a
measure of geographic differences in malpractice expenses. More
frequent data collection would likely enhance the credibility of the
malpractice GPCI among physicians, since malpractice premiums often
change each year--sometimes markedly--and the size of premium increases
often differs widely among states. Annual data collection would best
capture the year-to-year volatility of premium increases, but annual
data collection entails a greater commitment of CMS's resources.
Whatever the frequency of data collection, allowing more time to
collect the needed premium data and increasing efforts to follow up
with malpractice insurers and other sources of premium data could yield
more complete data. Collecting data on insurers that account for at
least half of malpractice business in a state, as CMS has done in the
past, would make CMS's malpractice data more representative. In
addition, collecting data on each insurer's market share by physician
specialty in each state would enable CMS to adjust average premiums for
differences in specialty mix among insurers. Finally, further
standardization of data and procedures for collecting data from
insurers would improve comparability of premiums within a payment
locality and between localities.
GPCIs Appear to Have Little Effect on Physicians' Incomes, Location,
Recruitment, and Retention:
The impact of GPCIs on physicians' incomes is generally modest and on
physician supply--location, recruitment, and retention--in rural areas
is negligible compared to other financial and nonfinancial factors.
Medicare is typically the source of only one-quarter of physicians'
income; consequently, GPCIs' effect on physicians' income is limited.
Income is only one of several factors that affect physicians' location
decisions. Nonfinancial factors, such as the quality of local schools
or spouses' employment opportunities, and other financial factors, such
as a community's average income level, are also major influences in
physicians' decisions to locate or remain in a rural area.
GPCIs Less Important than Market Factors in Affecting Physicians'
Incomes:
The impact of GPCIs on physicians' incomes is generally modest, raising
or lowering physicians' incomes by no more than 2 to 3 percent in most
localities.[Footnote 29] Physicians typically derive one-quarter of
their practice income from Medicare.[Footnote 30] Table 4, which shows
examples of income before and after GPCIs' adjustment, demonstrates the
GPCIs' effect on physicians' income by locality.[Footnote 31] For
illustrative purposes, the table assumes that the physicians provide
the same number and types of services in high-cost and low-cost areas.
It further assumes that these physicians would have an average income
of $150,000 without any geographic adjustment.
Table 4: Hypothetical Example of GPCIs' Effect on Income of Physicians
with Identical Number and Types of Services Who Derive One-Quarter of
Professional Income from Medicare, 2004:
Payment locality[A]: Oakland/Berkeley, California;
Income from identical physician practices[B]: Hypothetical income not
adjusted by GPCIs: $150,000;
Income from identical physician practices[B]: Hypothetical income
adjusted by GPCIs: $154,212.
Payment locality[A]: Massachusetts, excluding metropolitan Boston area;
Income from identical physician practices[B]: Hypothetical income not
adjusted by GPCIs: $150,000;
Income from identical physician practices[B]: Hypothetical income
adjusted by GPCIs: $152,060.
Payment locality[A]: Fort Worth, Texas;
Income from identical physician practices[B]: Hypothetical income not
adjusted by GPCIs: $150,000;
Income from identical physician practices[B]: Hypothetical income
adjusted by GPCIs: $149,720.
Payment locality[A]: New Mexico;
Income from identical physician practices[B]: Hypothetical income not
adjusted by GPCIs: $150,000;
Income from identical physician practices[B]: Hypothetical income
adjusted by GPCIs: $148,250.
Payment locality[A]: South Carolina;
Income from identical physician practices[B]: Hypothetical income not
adjusted by GPCIs: $150,000;
Income from identical physician practices[B]: Hypothetical income
adjusted by GPCIs: $147,493.
Source: GAO analysis of CMS and American Medical Association (AMA) data.
[A] Selected localities represent the 90th, 75th, 50th, 25th, and 10th
percentiles of the Medicare payment localities ranked by the weighted
average of their GPCIs.
[B] The typical (median) physician derives one-quarter of professional
income from Medicare. The Medicare proportion of practice income is
based on 1999 data, the most recent year for which data are available,
and is from the American Medical Association Physician Socioeconomic
Statistics 2000-2002 Edition.
[End of table]
For example, a physician in Oakland/Berkeley would earn $4,212 more
than a comparable physician in a locality with average practice costs.
By contrast, a physician in South Carolina would earn $2,507 less than
a comparable physician in a locality with average practice costs. These
differences in income would reflect differences in Medicare's measures
of the cost of running a medical practice.
Even when a sizable share of physicians' income comes from Medicare,
the GPCIs' effect on physicians' incomes is relatively modest. This
effect is illustrated by a hypothetical example of physicians in
different payment localities who provide the same number and types of
services, who would earn $150,000 if there were no geographic
adjustment of Medicare fees, and who derive 40 percent of their income
from Medicare. Such physicians in Oakland/Berkeley would receive $6,739
more income than comparable physicians in a locality with GPCIs
averaging 1.0, while such physicians in South Carolina would receive
$4,011 less.
Unlike the GPCIs, market factors have a substantial and statistically
significant impact on geographic differences in physicians' earnings.
We analyzed the geographic variation in physicians' earnings in
relation to the GPCIs and market factors and found that, controlling
for market factors, the GPCIs' effect on physicians' earnings was not
statistically significant. (For details of this analysis, see app. I.)
By contrast, we found that market factors were important. Specifically,
physician earnings were higher in areas where:
* the average income of the population was relatively high, as higher
income in a community is associated with higher demand for physicians'
services;
* the number of nurses was large relative to the population;
* the percentage of physicians was large in particular specialties,
such as cardiovascular surgeons, orthopedic surgeons, and
ophthalmologists; and:
* physicians experienced long working hours.
By contrast, physicians tended to have lower incomes in areas where
managed care penetration was high and the overall number of physicians
was large relative to the population.[Footnote 32]
Private plans' fees vary more than Medicare fees, suggesting that
market forces are more important than the GPCIs in accounting for
geographic differences in physicians' earnings. In a report for MedPAC,
Dyckman & Associates analyzed fee data for 2002 and found greater
variation in private plans' fees than in Medicare fees. The data on
private plans' fees were drawn from 33 health plans that enrolled 45
million people and were distributed throughout the country.[Footnote
33] Unlike Medicare, private health plans are able to adapt their fee
schedules to market forces. For example, private plans may pay
relatively lower fees in areas that experience high managed care
penetration and higher fees in areas where physicians have greater
market power. In contrast, Medicare fees by design do not vary
geographically in response to factors other than cost. Consequently,
Medicare's fees and private plans' fees would be expected to be
effectively unrelated across localities--as our statistical analysis
shows.[Footnote 34] (See fig. 2.) Because the variation in private
plans' fees across areas is greater than the variation in Medicare
fees, market factors--which do not affect Medicare fees--account for
much more of the variation in physician incomes than do the
GPCIs.[Footnote 35]
Figure 2: Variation in Private Plans' Physician Fees and Average
Medicare GPCI by Medicare Payment Locality, 2002:
[See PDF for image]
Note: The average Medicare GPCI--the weighted average of the GPCIs for
physician work, practice expense, and malpractice--summarizes the
extent of Medicare's geographic adjustment to its fees in a Medicare
payment locality. Each observation represents the average fee paid by a
private plan in a payment locality (relative to the national average of
private plan fees) and the average Medicare GPCI in that locality.
[End of figure]
Effect of GPCIs on Physician Supply in Rural Areas Is Negligible:
Income is only one of several financial and nonfinancial factors that
affect physician supply--that is, location, recruitment, and retention.
Our interviews with representatives of national and regional recruiting
firms as well as several small surveys show that income, regardless of
its source, is generally not the primary factor influencing location,
recruitment, and retention in rural areas. Since Medicare GPCIs adjust
only a fraction of income and income's effect on physician location is
generally secondary, we believe that the effect of GPCIs on physician
location is negligible.
Location and Recruitment:
Physicians' decisions to locate and practice in a rural area are more
strongly related to local amenities and personal preferences than to
potential income. In our interviews with experienced recruiters from
four national and regional physician search firms that place physicians
in rural practices, all reported that income potential is important to
physicians seeking new positions or relocating. However, they said that
other factors--such as a spouse's employment opportunities, the quality
of the local schools, and the availability of other physicians to share
night and weekend calls--are more likely than geographic differences in
Medicare fees to drive physician location decisions. This information
is consistent with studies of physicians' location decisions. For
example, a 1994 survey of third-year family practice residents asked
the residents to rank the factors that were most important in choosing
their first practice site.[Footnote 36] Seven factors ranked higher
than the initial income guarantee, with the significant other's wishes
ranking highest. Other factors that ranked above income included a
medical community friendly to family physicians, recreation and
culture, proximity to family and friends, significant other's
employment, schools for children, and the size of the community.
Similarly, a study of family and general practice physicians in
nonmetropolitan Nebraska counties found that a rural or small town
lifestyle, sufficient personal time away from work, and a quality
school system were influential in location decisions.[Footnote 37]
Practice characteristics that influenced location decisions included
clinical autonomy, the opportunity to treat a variety of medical
conditions, and patient relationships.
According to recruiters we interviewed, efforts to attract physicians
to rural areas are more likely to succeed when candidates have grown up
in rural areas or have been trained at medical schools and residency
programs that stress family practice and service to rural communities.
This observation is consistent with the results of several studies
identifying factors that draw physicians to rural areas.[Footnote 38]
Recognizing the importance of medical education specifically oriented
to rural practice, several medical schools, including those at the
University of Nebraska and the University of Iowa, have established
programs aimed at training physicians to serve in their states' rural
areas.[Footnote 39]
Physician recruiters also told us that certain business policies
adopted by medical practices and hospitals in rural communities can
increase or diminish the success of their recruitment efforts. For
example, one expert in physician recruiting said that, in working with
communities and medical practices that were having difficulty
recruiting, he found two policies that discouraged recruiting: first,
employment contracts often had strict "noncompete" stipulations,
barring any physician who leaves the practice from working as a
physician elsewhere within a broad geographic area--for example, a 90-
mile radius; second, some practices required that physicians who
resigned pay for malpractice insurance to cover claims that might arise
from their work in the practice. He added that relaxing these
restrictions led to easier recruiting.
Retention:
As with physicians' decisions to locate in a rural area, physicians'
decisions to remain in a rural area reflect nonfinancial as well as
financial factors and are not typically driven by income alone. Several
of the recruiters we interviewed stressed that retaining new physicians
in rural practice depends on integrating them and their families into
the community. The Nebraska study of physicians in nonmetropolitan
counties found that, in general, the same factors that had caused
physicians to locate in rural counties contributed to their
satisfaction and, by extension, their willingness to remain in their
rural practices.[Footnote 40] The factors that had the least to do with
a physician's satisfaction included on-call hours, income level, and
opportunities for promotion.
Several financial issues distinct from Medicare fees--such as the size
of the patient base, the proportion of privately insured patients in
the base, and the size of medical malpractice premiums--can also
influence physicians' decisions to remain in rural practice. Several
programs, including the Medicare Incentive Payment Program, provide
financial incentives to physicians to practice or continue practicing
in underserved areas, many of which are rural. The broader economy may
also influence practice decisions by individual physicians. The
University of Iowa Carver College of Medicine maintains data on all
physician retirements in Iowa. In recent years, Iowa physicians'
decisions to retire--a factor in reducing the local physician supply--
appeared to reflect trends in the stock market: when the stock market
fell, retirements also fell. (See fig. 3.)
Figure 3: Number of Retirements of Iowa Physicians and Standard & Poors
Composite Index of Stock Prices, 1993-2003:
[See PDF for image]
[End of figure]
Conclusions:
The geographic adjustment of Medicare's physician fees is essential to
achieving the program's goal of ensuring that Medicare's payments are
adequate and appropriate in all areas. GPCIs adjust for known
differences in the cost of practicing medicine in different areas so
that physicians can procure approximately equivalent resources with
their Medicare fee to treat Medicare patients, regardless of location.
When Congress introduced the work GPCI's temporary floor, it raised
Medicare fees to physicians in low-cost areas, thereby narrowing urban-
rural fee differences. Nevertheless, because of issues regarding data
and methods, the credibility of GPCIs continues to be questioned. Our
analysis shows that opportunities exist to refine the GPCIs by
improving the currency of the data used to construct all three GPCIs,
improving the data used in the practice expense and malpractice GPCIs,
and improving the methods used in the malpractice GPCI. These
improvements would likely have only a marginal impact on Medicare fees
and physician incomes but may have a more significant effect on the
GPCIs' credibility with the physician community. Additional
improvements may be possible. For example, it would be desirable to
adjust CMS's malpractice premium data for differences in specialty mix
among insurers, but to do so CMS would first need to assess the
feasibility of collecting data on each insurer's market share by
physician specialty in each state. Similarly, it would be desirable to
collect malpractice premium data more frequently--annually or every 2
years--but CMS would need to weigh the costs and benefits of doing so.
GPCIs appear to have been a negligible factor in physician supply
matters--location, recruitment, or retention. Our work shows that GPCIs
generally have at most a minor effect on physician incomes, and income
has a secondary effect (compared to nonfinancial factors) on where
physicians choose to practice. Consequently, GPCIs generally have not
played a material role in physicians' decisions to locate or remain in
a rural area.
Recommendations for Executive Action:
We recommend that the Secretary of Health and Human Services seek to
improve the GPCIs' data and methods by taking the following six
actions:
* develop a plan for transitioning from the Census Bureau's decennial
census to the annual ACS for earnings and wage data, pending resolution
by the Census Bureau of key outstanding issues regarding the
implementation of the ACS;
* add data on physician assistants' wages to improve the measurement of
the practice expense GPCI;
* consider the feasibility of replacing the practice expense GPCI's
current rent index with a commercial rent index; if using a commercial
rent index is not feasible, consider a residential rent index directly
based on ACS data;
* collect malpractice premium data from all states;
* collect data from insurers that account for at least half of
malpractice business in a state; and:
* standardize collection of malpractice premium data.
Agency and Industry Comments and Our Evaluation:
We received written comments on a draft of this report from HHS (see
app. III) and oral comments from two national associations of
physicians--the American Medical Association (AMA) and the American
Academy of Family Physicians (AAFP).
HHS Comments and Our Evaluation:
While characterizing our findings as important, HHS stated that the
body of the report and the recommendations were phrased inconsistently,
with the recommendations generally less cautious than the body of the
report regarding the feasibility of refining the input data and methods
used in constructing the GPCIs. In our view, the recommendations and
the body of the report are consistent in characterizing the feasibility
of options. For example, in discussing the rent index, we take account
of feasibility in both the body of the report, where we suggest an
alternative if the commercial rent index is not feasible, and in the
recommendation. HHS disagreed with most of our recommendations. HHS's
disagreements with specific recommendations are as follows:
* American Community Survey. Regarding our recommendation that HHS
develop a plan for transitioning to the ACS for earnings and wage data,
HHS stated that such a plan seems premature, because the ACS data will
not be available until 2010. In our view, HHS should begin considering
how it will use ACS data because the Census Bureau's long form--the
current source of data for the work GPCI and the wage component of the
practice expense GPCI--will not be available in the future. We know of
no other source of wage and earnings data at the geographic level
needed for the GPCIs. Although sufficient ASC data for the smallest
communities (those with populations that are less than 20,000) will not
be available until 2010, annual data for communities with populations
of more than 65,000 will be available beginning with 2006.[Footnote 41]
The Census Bureau is working with federal agencies to achieve a smooth
transition to the ACS. In particular, the Census Bureau and HUD are
working together to transition to the use of the ACS in the calculation
of the FMRs beginning with 2006. We believe that it would be prudent
for the CMS component of HHS to also begin planning the GPCI transition
to the ACS.[Footnote 42]
* Physician assistants' wages. Regarding our recommendation that adding
data on physician assistants' wages would improve the measurement of
the practice expense GPCI, HHS has said it believes that the current
wage categories are representative of the typical private physician
practice. Nonetheless, HHS said that it will examine these categories
and the possible inclusion of physician assistants' wages.
Rent Index. Regarding our recommendation that HHS should, if feasible,
replace the practice expense GPCI's current apartment rent index with a
commercial rent index, HHS noted that it had investigated alternative
sources of rent data, including data supplied by the USPS, and none of
them was adequate. We are aware that, over a decade ago, HCFA sponsored
research on possible sources of rent data. In a 1994 report, HCFA
compared the GPCI rent index to commercial office rents from three
sources: USPS, General Services Administration, and the Building Owners
and Managers Association.[Footnote 43] The report concluded that the
HUD FMR, although imperfect, was preferable to any of the alternatives.
However, in our view, HHS should assess the rent index that a USPS-
sponsored researcher created recently based on post office data. HHS
should determine whether his rent index is preferable to the GPCI rent
index (the HUD FMR), since his index has national coverage and
methodological advantages over the postal data reviewed over 10 years
ago. We also recommended that, if a commercial rent index proves
infeasible, HHS should use the ACS. HHS said that it would investigate
the ACS as a source of rent data when it becomes available. In our
view, the ACS should be a fallback source if a commercial rent index is
not feasible, rather than the sole source considered.
* Completeness of malpractice premium data. Regarding our
recommendation that HHS should collect malpractice premium data from
all states, HHS noted that it had previously collected data from all
states but did not in 2002, because the attempt to make the data more
current imposed a short time frame. We agree that timeliness is
important but believe that completeness should not be compromised--
particularly in planning future updates. HHS further noted that it
imputed data for 17 states and did not agree with our concern in the
body of the report that the performance of the imputation method had
not been tested. In our view, the failure to collect data from 17
states is a methodological flaw, although our draft report recognized
that the incomplete premium data resulted from HHS's efforts to use
more current data--a desirable objective. The draft report did not
disagree with the imputation method, which it explicitly stated was
reasonable. However, we continue to believe that, given the importance
of the imputation, its performance should have been tested. Moreover,
if premium data used in the future are incomplete, the imputation
method would need to be tested.
* Representativeness of premium data collection. Regarding our
recommendation that HHS collect data from insurers that account for at
least half of malpractice insurance business in a state, HHS noted that
it had done so in its original data collection for 1999 to 2001.
However, in the 2002 supplemental collection, data were collected only
from a state's largest insurer, even if its market share was less than
half. In our view, to enhance the representativeness and credibility of
CMS's premium data, it is important that these data always represent at
least half of the malpractice insurance in a state.
* Standardization of malpractice premium data. Regarding our
recommendation that HHS standardize the collection of malpractice
premium data, HHS stated that it has done a more than adequate job of
standardizing the survey instrument for the collection of malpractice
premium data. However, we found that HHS has not demonstrated that it
has a standard protocol--procedures and survey instruments--for
collecting these data. In particular, neither CMS's regulation nor the
contractor's most recent report that updated the GPCIs contains a
protocol or a detailed description of premium data collection.
Publication of the protocol might help to make the malpractice GPCI
more transparent.
Industry Association Comments:
The two industry associations that commented varied in their
observations on the draft report. AMA stated that the draft report
provided a good description of the background and evolution of the
GPCIs. AMA agreed with our analysis of the GPCIs' validity and with our
finding that the GPCIs' role in influencing physician location is
negligible. However, AMA disagreed with our estimate of the GPCIs'
effect on physician income and suggested that our concerns about using
physicians' earnings for the work GPCI could be overcome by using
alternative earnings data. AAFP differed with our discussion of the
validity of the work GPCI. The associations also provided us with
technical comments, which we incorporated as appropriate. The
associations' major comments and our evaluation of those comments are
summarized below.
AMA's main concern was that we understated the GPCIs' effect on
physician income. AMA cited three reasons that the range of the GPCIs'
effect was greater than we estimated. Their reasons and our responses
are as follows:
1. According to AMA, in general the GPCIs' effect on physician income
is closer to 5 percent than to the 2 to 3 percent we reported, because
the GPCIs should be applied only to gross revenue, not net income.
Since physicians' gross revenue is about twice net income on average,
according to AMA, the GPCIs' true effect is about twice our estimate.
We agree that Medicare's geographic fee adjustments directly affect a
physician practice's gross revenue. However, in assessing the effect of
GPCIs on physician net income, we took account of geographic
differences in both physician revenue and physician expenses, whereas
AMA's approach assumes physician expenses are the same in all
localities. Not to account for geographic differences in expenses
(using the GPCIs) would ignore the fact that the GPCIs track
significant differences across localities in physicians' expenses, such
as nurses' wages and rent.
2. AMA stated, as did AAFP, that the GPCIs' effect on fees is amplified
beyond their effect on Medicare fees because some private plans and
state Medicaid programs base their physician fees on Medicare fees. In
AMA's view, the draft report should address the tendency of other
payers to follow Medicare's lead and therefore the draft report
understated the GPCIs' effect. Our analysis of private plan fees,
however, found effectively no relationship between private plans' fees
and Medicare fees in different localities. While some private plans
have adopted Medicare's RVU scale or a variant, fewer have adopted the
GPCIs. This is consistent with the data on private plan fees that we
reviewed, showing that Medicare fees and private plan fees are
effectively unrelated across localities. (See fig. 2.) Similarly, a
study published in 2000 found that Medicaid fees did not track Medicare
fees: for the same services, Medicaid fees as a proportion of Medicare
fees varied widely across states, ranging in 1998 from 34 percent in
New Jersey to 126 percent in Alaska.[Footnote 44]
3. AMA maintained that rural physicians and certain specialists, such
as internists and cardiologists, derive more of their income from
Medicare than the 25 percent average we cited. We agree that various
specialties have had an average Medicare share of practice income of
more than 40 percent, including ophthalmology, cardiovascular disease,
urological surgery, and general internal medicine.[Footnote 45] Our
analysis showed that the GPCIs' effect on the income of physicians who
derive 40 percent of their income from Medicare was still relatively
modest.
AMA also disagreed with our finding that basing the work GPCI on
measures of earnings of nonphysicians has advantages, compared to
relying on direct measures of physician earnings from the decennial
census. AMA suggested three alternative measures on which to base the
work GPCI: (1) salaries of employed physicians, which in AMA's view
would permit CMS to bypass the circularity issue associated with the
direct use of physician earnings; (2) surveys of physician income
conducted by physician recruitment firms; and (3) salary data from the
Medical Group Management Association's Physician Compensation and
Production Survey. We do not consider any of these alternatives to be
preferable to nonphysician earnings as a basis for the work GPCI. In
the case of employed physicians' salaries, circularity is obscured but
not avoided. Neither the MGMA survey nor physician recruitment firm
surveys are statistically representative and therefore are not adequate
as data sources for the work GPCI.
AAFP commented on the draft report's discussion of the work GPCI and
its validity. AAFP's policy is that identical physician services should
be reimbursed the same, regardless of location. AAFP stated that no
geographic adjustment should be applied unless it addresses a specific
policy concern, such as physician shortages. Consistent with the MMA's
mandate to us, we examined the GPCIs to determine whether they were
valid in their fundamental design and appropriate in the data and
methods used to measure cost differences. Our research on this issue
led us to conclude that adjusting Medicare physician fees for
geographic cost differences is essential to achieving Medicare's goal
of ensuring that fees are adequate and appropriate in all areas.
We are sending copies of this report to the Secretary of Health and
Human Services, the Administrator of CMS, and appropriate congressional
committees. We will also make copies available to others upon request.
The report is available at no charge on the GAO Web site at [Hyperlink,
http://www.gao.gov].
If you or your staffs have questions about this report, please call me
at (202) 512-7119. Another contact and staff acknowledgments are listed
in appendix IV.
Signed by:
A. Bruce Steinwald:
Director, Health Care--Economic and Payment Issues:
[End of section]
Appendixes:
Appendix I: Data and Methods:
This appendix describes the data and methods we used to assess the
GPCIs' data and methods, to compare fees paid by private insurers to
geographically adjusted Medicare physician fees, and to assess the
effect of GPCIs on physicians' incomes.
Construction of the GPCIs:
We reviewed the data and methods used by CMS to construct the GPCIs. To
analyze the GPCI methodology, we examined reports of the Health Care
Financing Administration (HCFA) and the HCFA and CMS contractors that
had produced and updated the GPCIs. We relied most on information in
the report on the fourth GPCI update, which CMS used to develop the
2005 indexes.[Footnote 46] The data described in that report are drawn
from government sources (see table 5). We did not independently
establish the reliability of data used in the GPCIs.
Table 5: Data Sources Used in CMS's Construction of GPCIs:
Index: All GPCIs;
Purpose: Weight variables used in constructing GPCI by county total of
RVUs for each component (work, practice expense, malpractice);
Data: 2002 work, practice expense, and malpractice components of RVUs
by county.
Index: All GPCIs;
Purpose: Crosswalk counties to Medicare payment localities;
Data: List of U.S. counties, list of payment localities.
Index: All GPCIs;
Purpose: Crosswalk Census Bureau's 545 work areas-- consolidated
metropolitan statistical areas (CMSA), metropolitan statistical areas
(MSA), New England county metropolitan areas (NECMA), and rural
balances--to U.S. counties;
Data: List of CMSAs, MSAs, and rural state balances; list of U.S.
counties.
Index: Work GPCI;
Purpose: Construct index of 6 professions' earnings;
Data: 2000 decennial census data on earnings of 6 professional
categories for 545 work areas.
Index: Work GPCI;
Purpose: Weight earnings of each professional category by its share of
employees;
Data: Share of employees in each of 6 professional categories.
Index: Practice expense GPCI;
Purpose: Construct employee wage index of 4 nonphysician occupations;
Data: Decennial census data on wages of 4 occupations for 545 work
areas.
Index: Practice expense GPCI;
Purpose: Weight earnings of each of 4 nonphysician occupations by its
share of employees;
Data: 2000 decennial census data on share of employees in each of 4
nonphysician categories.
Index: Practice expense GPCI;
Purpose: Obtain rent index;
Data: 2004 HUD fair market rent (FMR) Index for two-bedroom apartments
for all counties in the United States.
Index: Practice expense GPCI;
Purpose: Combine components of practice expense into the practice
expense index, using the cost shares of these components;
Data: Cost shares of these components.
Index: Malpractice GPCI;
Purpose: Construct malpractice premium price index;
Data: Malpractice premiums and premiums as adjusted by CMS contractor
for 20 specialty groups for at least 2 carriers per state for 1999-2001
and 1 carrier per state for 2002.
Index: Malpractice GPCI;
Purpose: Crosswalk insurers' rate area to counties;
Data: List of each insurer's rating territories, list of U.S. counties.
Index: Malpractice GPCI;
Purpose: Weight each insurer's premiums by market share;
Data: Market share for each insurer for which 2001 premiums were
obtained, except 14 states where 2001 market share was unavailable--8
states provided BearingPoint their 2000 market shares as the most
current market shares data available, and BearingPoint used National
Association of Insurance Commissioners (NAIC) 2000 market share data to
identify insurers for the remaining 6 states.
Source: GAO analysis of CMS documents.
[End of table]
Comparing Geographically Adjusted Medicare and Private Insurance
Physician Fees:
To compare the geographic variation in Medicare physician fees with the
geographic variation in fees paid by private insurers, we obtained
analyses of a sample of private plans' physician fee schedules obtained
in 2002.[Footnote 47] These analyses were commissioned by MedPAC and
carried out by Dyckman & Associates--referred to here as Dyckman. For
this analysis, Dyckman:
* mapped fee schedules from private plans in its sample to Medicare fee
schedules for the same localities and determined that its sample had 68
usable fee schedules for 36 Medicare payment localities,[Footnote 48]
* calculated for each fee schedule a private fee index--the ratio of
the average private fee to the national average, and:
* compared the private fee index to the weighted average of the three
GPCIs in that Medicare payment locality.
In calculating the average private fee, Dyckman:
* classified 89 commonly used Medicare procedures into 6 types of
services;
* calculated the mean of private plans' fees that operate in each one
of the 36 Medicare payment localities;[Footnote 49] and:
* calculated the national mean of private plans' fees, weighting the
mean of private plans' fees in each Medicare payment locality by its
total RVUs.
Factors Affecting Geographic Difference in Physicians' Income:
To determine the effect of GPCIs and other factors on physicians'
income, we estimated a model of average physician income in 513
geographic areas.[Footnote 50] We controlled for factors that affect
physicians' income, such as physicians' location, their hours of work,
their specialties,[Footnote 51] the extent of their competition, as
measured by the relative number of physicians to the population in an
area, and the availability of nurses.[Footnote 52] Table 6 presents our
analysis showing that most factors, but not GPCIs, are statistically
significant.
Table 6: Factors Explaining Variation in Physicians' Average Annual
Income for 513 Geographic Areas:
Factors: GPCI--weighted average of work, practice expense, and
malpractice GPCIs[A];
Coefficient: -3,414.99;
p < |t|: 0.92.
Factors: Average Medicare payment for physicians' services per
beneficiary (2002)[A];
Coefficient: 7.26;
p < |t|: 0.19.
Factors: Located in metropolitan statistical area (MSA);
Coefficient: 17,471.71;
p < |t|: 0.00.
Factors: Average weekly work hours for physicians in the area;
Coefficient: 1,521.77;
p < |t|: 0.00.
Factors: Percentage of physicians who belong to selected specialty
categories[B];
Coefficient: 2,032.36;
p < |t|: 0.00.
Factors: Average managed care penetration[C] (%);
Coefficient: -505.42;
p < |t|: 0.00.
Factors: Number of patient-care physicians per 1,000 population[D];
Coefficient: -4,625.12;
p < |t|: 0.00.
Factors: Percentage of physicians who are non-patient-care physicians[
E];
Coefficient: -1,580.44;
p < |t|: 0.00.
Factors: Number of nurses[F] per 1,000 population;
Coefficient: 2,239.46;
p < |t|: 0.00.
Factors: Average annual income for all civilians in the area;
Coefficient: 1.81;
p < |t|: 0.00.
Factors: Constant[A];
Coefficient: 4,299.85;
p < |t|: 0.89.
Source: GAO analysis of the 2002 Area Resource File, the 2000 decennial
census, and the 5 percent sample of 2002 Medicare physician claims.
Note: The 513 areas are a subset of the 545 work areas (consolidated
metropolitan statistical areas (CMSA), metropolitan statistical areas
(MSA), New England county metropolitan areas (NECMA), and rural state
balances in a state) for which complete data were available. The
adjusted R2for the estimated model is .41.
[A] Factor is not statistically significant: p-value greater than .05.
[B] These specialties are cardiovascular surgery, orthopedic surgery,
dermatology, ophthalmology, neurosurgery, neurology, pulmonary disease,
plastic surgery, gastroenterology, obstetrics/gynecology, and
colon/rectal surgery.
[C] The proportion of an area's population enrolled in a managed care
organization.
[D] Patient-care physicians include office-based physicians, hospital
residents, and hospital full-time staff physicians.
[E] Non-patient-care physicians include those whose major professional
activity is research, medical education, or administration.
[F] Nurses include registered nurses, licensed practical nurses, and
nurse practitioners.
[End of table]
[End of section]
Appendix II: Rent Indexes and the Practice Expense GPCI:
We reviewed the FMR, the rent index used in the 2004 practice expense
GPCI. The FMR was developed to serve a specific purpose in the HUD
Housing Choice Voucher program: setting the amounts in different parts
of the country of rent vouchers that aid lower income families in
renting housing. The use of different sources in different areas for
developing and updating this special purpose index, as well as the
process for requesting changes to it, raises questions about its
suitability as a component of the practice expense GPCI. Specifically,
the FMR uses decennial census data, supplemented with data from the
American Housing Surveys for the largest metropolitan areas and from
telephone surveys (conducted using random digit dialing) for other
areas to establish base-year estimates. Changes may be made to the
proposed rates if localities are dissatisfied with these rates and
submit supporting data. The FMR is updated from two sources: regional
random digit dialing surveys in some areas and the Consumer Price Index
(CPI) for rents and utilities data where available.
We wanted to identify a commercial rent index--on its face, a more
appropriate proxy for physician office rent. We found only one source
of commercial rent that was available nationally for both urban and
rural areas. The USPS has data on rent of post offices throughout the
country and has sponsored work by Anthony M. Yezer, Professor of
Economics at George Washington University, to create a rent index with
national coverage.[Footnote 53] To construct a county-level rent index
for a property with standardized characteristics, Professor Yezer
estimated a statistical model. The model controlled for differences in
physical characteristics of the property such as interior space,
setting of the building, parking provision, and provisions of the
lease, including length and terms. The model's predicted level of rent
for property used as post office space, holding constant these physical
characteristics and lease terms, was used to calculate an index of rent
in a county or group of counties relative to the average. Our
preliminary exploration of this commercial rent index suggests that,
potentially, it could be an improvement on the residential rent index
used currently for the practice expense GPCI. In order to use these
data, CMS would have to assure itself of the data's credibility and
technical merits and their availability to CMS on a periodic basis.
[End of section]
Appendix III: Comments from the Department of Health and Human
Services:
DEPARTMENT OF HEALTH & HUMAN SERVICES:
Office of Inspector General:
Washington, D.C. 20201:
JAN 12 2005:
Mr. A. Bruce Steinwald:
Director, Health Care-Economic and Payment Issues:
U.S. Government Accountability Office:
Washington, DC 20548:
Dear Mr. Steinwald:
Enclosed are the Department's comments on your draft report entitled,
"Medicare Physician Fees-Geographic Adjustment Indices Are Valid in
Design but Data and Methods Need Refinement" (GAO-05-119). The comments
represent the tentative position of the Department and are subject to
reevaluation when the final version of this report is received.
The Department provided several technical comments directly to your
staff.
The Department appreciates the opportunity to comment on this draft
report before its publication.
Sincerely,
Signed by:
Daniel R. Levinson:
Acting Inspector General:
Enclosure:
The Office of Inspector General (OIG) is transmitting the Department's
response to this draft report in our capacity as the Department's
designated focal point and coordinator for Government Accountability
Office reports. OIG has not conducted an independent assessment of
these comments and therefore expresses no opinion on them.
COMMENTS OF THE DEPARTMENT OF HEALTH AND HUMAN SERVICES ON THE U.S.
GOVERNMENT ACCOUNTABILITY OFFICE'S DRAFT REPORT: "MEDICARE PHYSICIAN
FEES-GEOGRAPHIC ADJUSTMENTS INDICES ARE VALID IN DESIGN BUT DATA AND
METHODS NEED REFINEMENT" (GAO-05-119):
The Department of Health and Human Services (HHS) appreciates the
opportunity to comment on this U.S. Government Accountability Office's
(GAO's) draft report.
This report makes several important findings. One key finding is that
the geographic adjustments to the physician fee schedule, required by
the Medicare Prescription Drug, Improvement, and Modernization Act of
2003 (MMA) statute, are not important factors in physician location,
recruitment, and retention. The report points out that since Medicare
revenues constitute only about 25 percent of a physician's income,
changes in the geographic practice costs indices (GPCIs) generally have
only modest impact on physicians' incomes. The report indicates that
GAO's interviews with physician recruitment experts and review of
published studies indicate that income is only one of numerous factors
that affect physician decisions to locate in rural areas. Other factors
that do affect physician location decisions include: a spouse's
employment opportunities; the quality of local schools; and the
availability of other physicians to share night and weekend calls.
A second key GAO finding is that the geographic adjustment indices used
by Medicare are valid. The MMA statute requires use of three different
indices to adjust for differences in costs among geographic areas under
the physician fee schedule: (1) for physician work (a physician's time
and effort); (2) for practice costs other than malpractice; and (3) for
malpractice. The report indicates: "The three GPCIs as implemented
appropriately reflect broad patterns of geographic differences in the
costs of running a practice."
The report also recommends certain refinements to the data and methods
used to construct the GPCIs. Since their inception, HHS, Centers for
Medicare & Medicaid Services (CMS) has consistently sought alternative
data sources that could improve the GPCIs. HHS looks forward to
exploring the alternatives suggested by GAO but we note that the
suggestion that might have the biggest impact is to use a survey that
has not yet been conducted and won't be available until 2010. We agree
with the GAO's assessment that their recommendations would unlikely
change the GPCIs significantly.
GAO Recommendation:
We recommend that the Secretary of HHS seek to improve the GPCIs' data
and methods by taking the following six actions:
* Develop a plan for transitioning from the Census Bureau's decennial
census to the annual American Community Survey (ACS) for earnings and
wage data, pending resolution by the Census bureau of key outstanding
issues regarding the implementation of the ACS.
HHS Response:
CMS has consistently sought valid, representative data sources that are
more current than the decennial census in past GPCI updates. This was
stated in our final rule, published on November 15, 2004, (page 66262).
As the report indicates, the ACS is still under development. The
earliest the ACS data would be available to CMS is 2010, and we plan to
review the ACS as a potential data source at that time. While the ACS
is a very interesting possibility to consider for future use, such use
would be years away. Without any analysis of survey results, the
recommendation for "developing a plan for transitioning" to ACS seems
premature. It would not be prudent for CMS to commit to using ACS at
this point.
GAO Recommendation:
* Add data on physician assistants' wages to improve the measurement of
the practice expense GPCI.
HHS Response:
We include employee categories in the wage index component of the
practice expense GPCI that have been determined to be most typically
present in a physician's private practice. GAO does not discuss whether
physician assistants constitute a "typical" staff available in a
private physician practice.
Although we believe the current wage categories are representative of
the typical private physician practice, we will examine the current
occupational wage categories utilized in the construction of the
practice expense GPCI and the possible inclusion of physician
assistants' wages.
GAO Recommendation:
* Replace the practice expense GPCI's current rent index with a
commercial rent index, if feasible, or if that is not feasible, a
residential rent index using ACS data.
HHS Response:
As we have discussed previously in the Federal Register with regard to
updating the GPCIs, for constructing the rental portion of the practice
expense GPCIs, we need and have searched for commercial rental data
that are widely and consistently available across all fee schedule
areas. To date, we have explored numerous alternative rental data
sources including: the U.S. Postal Service, General Services
Administration, Internal Revenue Service, etc. None of these sources
contained sufficient data for nonmetropolitan areas, nor did any
contain data for all metropolitan areas.
The alternative commercial rent data sources we have examined to date
are not reflective of the average commercial space in the area, but
rather the particular type of space most relevant to the needs of the
particular source's clients. Additionally, none of the data sources
contained sufficient sample sizes at the county level.
While we recognize that apartment rents are not a perfect proxy for
physician office rents, there are no existing national studies that
present reliable retail and business rental data. Additionally, the
GPCIs measure relative differences among areas. We believe that
commercial rents will generally vary among areas as residential rates
vary. As noted previously, we intend to analyze the ACS data when they
become available.
GAO Recommendation:
* Collect malpractice premium data from all States.
HHS Response:
The GAO report focuses on the severe time limit imposed on the
collection of malpractice premium data. According to the GAO report,
the contractor had only 7 weeks to collect the premium data. This short
timeframe led to a truncated data collection and limited the database
to only 33 States.
This short timeframe was not associated with our original data
collection, but was instead associated with a supplementary data
collection. Originally, the premium data to be utilized in the updated
malpractice GPCIs was for the years 1999 through 2001. This original
survey was conducted over the period of 1 year and premium data were
collected from all States and territories with the exception of
Kentucky, New Hampshire, New Mexico, and the District of Columbia
(which did not respond).
At the urging of the medical community and numerous congressional
representatives, CMS re-surveyed the 52 States and territories in an
attempt to collect more current, 2002, premium data. Over this 7-week
period we were able to collect 2002 premium data from 33 States. As
stated previously, this supplemental data collection effort was at the
urging of the medical community and various congressional
representatives in an attempt to capture the escalating premiums which
were occurring nationwide.
For the remaining 17 States and the District of Columbia, and Puerto
Rico, for which we were unable to collect premium data, the 2002 data
were imputed. GAO expressed concerns that the imputation methodology
was not tested and described possible tests that could be carried out.
As described in our March 12, 2004, "Fourth Update to the Geographic
Practice Cost Indices Report," which we shared with GAO, we chose the
imputation technique that we believed most accurately portrayed the
actual 2002 premiums. It is not clear from the report that the
techniques proposed by GAO would provide a more accurate tool in
estimating the premiums for the States that failed to respond to our
survey requests. Also, use of more recent data that includes some trend
projection also needs to be weighed against using complete but outdated
data (e.g., should one use more recent data even if some such data are
reasonably imputed or should one use only unimputed data if such data
are more outdated). We recommend that the report characterize this as a
choice rather than as a flaw.
Also, the report suggests collecting data on each insurer's market
share by physician specialty in each State, as well as collecting data
more frequently. It is not clear that insurers would readily divulge
their market share by physician specialty in each State. Moreover, the
burden on insurers to furnish this information is not identified.
Insurers voluntarily provide this information now. More frequent data
collection requests as well as more detailed information on their
business might make insurers reluctant to respond. The report does not
present these downsides to the recommendations.
GAO Recommendation:
* Collect data from insurers that account for at least half of
malpractice business in a State.
HHS Response:
The original data collection effort did adhere to the 51 percent market-
share criteria. The supplementary premium data collection which was to
capture more recent premiums did not obtain 51 percent market share in
all instances. CMS did ensure that the 2002 premium data collected were
from the dominant insurer in each respective State.
GAO Recommendation:
* Standardize collection of malpractice premium data.
HHS Response:
We currently operate under a stringent approach that begins with the
State Departments of Insurance (DOT). The State DOI is contacted and a
short telephone survey is administered to identify who the contact
persons are and if the State DOI has available the premium information
that CMS is requesting. In the event that the State DOT does have the
information available, this telephone survey is immediately followed up
with a mail survey that outlines the scope of the data collection
effort, the reasons we are requesting such data, and the ensured
confidentiality of all premium data. In the event that the State DOI
does not have the information available, the preceding steps are
duplicated at the private insurer level. CMS believes that we have done
a more than adequate job of standardizing our survey instrument for the
collection of malpractice premium data.
HHS General Comments:
The report recommends certain refinements to the data and methods used
to construct the GPCIs. We would note, however, that while the summary,
conclusions, and recommendations of the report suggest "data and
methodology problems" and that the Secretary "has options to remedy
some of these flaws," the body of the report is more cautious and
caveated about the feasibility of some of the suggested options. Also,
the report characterizes the GPCIs as having weaknesses and implies
that fixes are available. However, when one looks at the "fixes"
suggested, the ones that would impact the biggest components of the
GPCls are too far away and/or exploratory to be considered fixes. We
recommend more consistency in characterization.
[End of section]
Appendix IV: GAO Contact and Staff Acknowledgments:
GAO Contact:
Jonathan Ratner, (202) 512-7107:
Acknowledgments:
In addition to the person named above, key contributors to this report
were Dae Park, Phyllis Thorburn, Bobbi Buckner Bentz, Hannah Fein, Ba
Lin, and Mary Reich.
(290266):
FOOTNOTES
[1] The Health Care Financing Administration (HCFA) was renamed CMS on
July 1, 2001.
[2] Pub. L. No. 108-173, § 413(c), 117 Stat. 2066, 2277-78.
[3] The MMA directs us to examine the GPCIs' validity but does not
define the term.
[4] Our work began in response to a request from the Senate Finance
Committee and continued pursuant to MMA.
[5] These percentages do not total to 100 percent due to rounding. The
percentages correspond to shares of the average cost of running a
physician practice.
[6] A more complete description is "office or other outpatient visit
for the evaluation and management of an established patient." In the
American Medical Association (AMA) coding system, it is CPT code 99213.
In this report, a midlevel office visit refers to this CPT code.
[7] The full description is "infusion technique, initiation of
prolonged infusion (more than 8 hours) requiring the use of a portable
or implantable pump." It is CPT code 96425.
[8] The same fee would result from multiplying each of the three RVUs
by the conversion factor, multiplying each product by the corresponding
geographic adjuster, and adding the three components together.
[9] HCFA has stated that [it] "favors statewide localities because of
their understandability, simplicity, and ease of administration, and
because they reduce urban/rural payment differences." HCFA, Medicare
Program: Revisions to Payment Policies and Five-Year Review of and
Adjustments to the Relative Value Units Under the Physician Fee
Schedule for Calendar Year 1997, 61 Fed. Reg. 59,491, 59,497 (Nov. 22,
1996).
[10] The six categories are architecture and engineering; computer,
mathematical, and natural sciences; social scientists, social workers,
and lawyers; education, training, and library; registered nurses and
pharmacists; and writers, artists, and editors.
[11] This refers to the value--as perceived by these professionals--of
a locality's attributes, such as schools, entertainment, and quality of
professional colleagues.
[12] The Secretary of Housing and Urban Development is required to
publish the FMR index annually. The FMR index is used to determine
payment amounts for the Housing Choice Voucher program (formerly known
as the Section 8 housing program).
[13] See Pub. L. No. 101-239, § 6102(a), 103 Stat. 2106, 2169-84
(adding section 1848 to the Social Security Act) (codified at 42 U.S.C.
§ 1395w-4 (2000)).
[14] Specifically, the law required that the work GPCI for a given
payment locality was to be one-quarter of the relative cost of
physicians' work, compared to the national average.
[15] There were 240 payment localities before the physician fee
schedule was implemented; as of January 1, 1995, the number had been
gradually reduced to 210.
[16] MMA, § 412, 117 Stat. at 2274 (to be codified at 42 U.S.C. § 1395w-
4(e) (1)). The floor applies to payment for services furnished from
January 1, 2004, through December 31, 2006. The implementation of the
floor did not reduce the payments in payment localities where the work
GPCI was 1.0 or greater.
[17] This weighted average for a locality is a measure of that
locality's Medicare fees relative to other localities' Medicare fees.
[18] Council on Graduate Medical Education, Tenth Report, Physician
Distribution and Health Care Challenges in Rural and Inner-City Area
(Washington, D.C.: HHS, Public Health Service, Health Resources and
Services Administration, February 1998), xiv.
[19] The Health Resources and Services Administration designates areas
having a shortage of primary care providers as health professional
shortage areas. See 42 U.S.C. § 254e(a)(1) (2000). There are several
types, but the only ones covered by the Medicare incentive payment
program are areas with a shortage of primary care physicians or
psychiatrists.
[20] MMA, § 413(a), 117 Stat. at 2275-77. Physician scarcity areas,
defined by MMA, are of two types: primary care scarcity areas, which
are determined by the ratio of primary care physicians to Medicare
beneficiaries, and specialist care scarcity areas, which are determined
by the ratio of specialty care physicians to Medicare beneficiaries.
For both types, counties are ranked according to the ratio of
physicians to Medicare beneficiaries, and the counties with the lowest
ratios that represent 20 percent of Medicare beneficiaries are
designated as scarcity areas. A physician who practices in an area that
is both a shortage area and a scarcity area will receive a total
incremental incentive payment of 15 percent.
[21] This form is given to a sample of about one in every six U.S.
households and contains questions on income, housing, and other issues.
[22] The ACS is a continuous sample. Communities with populations less
than 20,000 will require 5 years of ACS data. Communities with
populations between 20,000 and 65,000 will require 3 years of ACS data.
[23] See GAO, American Community Survey: Key Unresolved Issues, GAO-05-
82 (Washington, D.C.: Oct. 8, 2004).
[24] Elliott S. Fisher and others, "The Implications of Regional
Variations in Medicare Spending. Part 1: The Content, Quality, and
Accessibility of Care," Annals of Internal Medicine, vol. 138, issue 4
(2003), 273-287.
[25] See W. Pete Welch, Stephen Zuckerman, and Gregory Pope, The
Geographic Medicare Economic Index: Alternative Approaches, Final
Report to the Health Care Financing Administration (Needham, Mass.:
Health Economics Research, and Washington, D.C.: The Urban Institute,
June 1989); and Hearing on Medicare's Geographic Cost Adjustors Before
the House Committee on Ways and Means, Subcommittee on Health, 107TH
Cong. 99-103 (July 23, 2002) (Statement of Stephen Zuckerman, Ph.D.,
Principal Research Associate, Urban Institute.)
[26] In creating its wage index for nonphysician employees, CMS
includes four occupations: registered nurses, licensed practical
nurses, health technicians, and administrative support staff. The wages
of these occupations, taken together, account for almost 43 percent of
the practice expense component.
[27] We did not investigate whether wages of other types of staff, such
as accountants, lawyers, or data technicians, should also be used in
constructing the wage component of the practice expense GPCI. We know
of no data source that would give the proportion of these types of
staff used by physicians' practices.
[28] See GAO-05-82.
[29] In this analysis, income refers to earnings of physicians.
[30] The Medicare proportion of practice income is based on 1999 data,
the most recent year for which data are available, and is from the
American Medical Association Physician Socioeconomic Statistics 2000-
2002 Edition.
[31] The examples in table 4 are relevant to most localities, since the
table includes localities at the 90TH percentile and at the 10TH
percentile, ranked by the weighted average of their GPCIs. Some
localities have average GPCIs higher than the 90TH percentile and
others have average GPCIs lower than the 10TH percentile. These outlier
GPCIs have larger effects on Medicare fees and physician incomes than
the effects shown in table 4. For example, for the New York City
suburbs--the locality at the 95TH percentile--the GPCIs raise
physicians' income by 4.5 percent; for South Dakota--the locality at
the 5TH percentile--they lower physicians' income by 1.9 percent. (All
comparisons are to a locality without any geographic adjustment.)
[32] For example, according to one expert, the oversupply of physicians
in some specialties, such as internal medicine and family practice, has
halted increases in physician salaries and even led to small decreases
of physician salaries in one state and in adjoining areas of
neighboring states. Our analysis excluded federal physicians and
nonpracticing physicians.
[33] The data are described in Dyckman & Associates, Survey of Health
Plans Concerning Physician Fees and Payment Methodology: A Study
Conducted by Dyckman & Associates for the Medicare Payment Advisory
Commission, No. 03-7 (Washington, D.C.: MedPAC, August 2003).
[34] For the same service, the difference in Medicare fees in two areas
reflects the two areas' Medicare GPCIs. The average Medicare GPCI--the
weighted average of GPCIs in an area--summarizes the extent of
Medicare's geographic adjustment to its fees in an area. To compute
this summary measure, each GPCI is multiplied by the share of costs
accounted for by its corresponding RVU. The weighted average of GPCIs
is often referred to as the geographic adjustment factor (GAF).
[35] If market forces affect fees, it might suggest that physicians in
rural areas--where there are fewer physicians--would have higher
incomes, because their private practice fees would be higher. A recent
study may provide some support for this view. According to this study,
physicians' average income, adjusted for the cost of living, is
significantly higher in rural areas than in urban areas. See James D.
Reschovsky and Andrea B. Staiti, Physician Incomes in Rural and Urban
America, No. 92 (Washington, D.C.: Center for Studying Health System
Change, January 2005).
[36] Anthony J. Costa and others, "To Stay or Not to Stay: Factors
Influencing Family Practice Residents' Choice of Initial Practice
Location," Family Medicine, vol. 28 (1996), 214-219.
[37] Suzanne M. Minarick and John C. Allen, "Factors Influencing the
Satisfaction and Retention of Nebraska's Rural Physicians" (Lincoln,
Neb.: University of Nebraska - Lincoln, June 2003), http: //
cari.unl.edu/rural-physician.htm (downloaded Aug. 27, 2004).
[38] See Howard K. Rabinowitz and others, "Critical Factors for
Designing Programs to Increase the Supply and Retention of Rural
Primary Care Physicians," Journal of the American Medical Association,
vol. 286, no. 9 (2001), 1041-1048.
[39] In addition, recruitment programs in several states seek to
increase the number of physicians in rural areas to improve their
residents' medical care. Historically, the federal government has
supported the recruitment of international medical graduates to rural
and underserved areas by waiving certain visa requirements.
[40] Minarick and Allen, "Factors Influencing the Satisfaction and
Retention of Nebraska's Rural Physicians."
[41] Funding for the ACS (for all persons except those living in group
quarters) was approved beginning with 2005.
[42] The Census Bureau told us that some parts of HHS have begun
working with Census to achieve a smooth transition.
[43] Debra A. Dayhoff and Gregory C. Pope, Comparison of GPCI Rental
Index to Three Sources of Commercial Office Rents: Final Report
(Waltham, Mass.: Health Economics Research, Inc., Sept. 14, 1994).
[44] Stephen Norton and Stephen Zuckerman, "Trends in Medicaid
Physician Fees, 1993 to 1998," Health Affairs, vol. 19, no. 4 (2000),
222-232.
[45] The Medicare proportion of practice income is based on 1999 data,
the most recent year for which data are available, and is from the
American Medical Association Physician Socioeconomic Statistics 2000-
2002 Edition. Specialist groups that derive more than 40 percent of
their revenue from Medicare include ophthalmologists (49 percent),
cardiovascular disease (46.6 percent), and urological surgeons (44.2
percent). Groups of internists with Medicare shares between 37 percent
and 47 percent include general internists and internists in the
cardiovascular and gastroenterology subspecialties. Florida is the only
area where revenue from Medicare averages more than 40 percent (40.3
percent) for all physicians, regardless of specialty.
[46] Shannon Slawter, Jim Moser, and Shihki Barcheck, Fourth Update to
the Geographic Practice Cost Index: Final Report (McLean, Va.:
BearingPoint, Jan. 15, 2004).
[47] These fee schedules had been collected for a study commissioned by
MedPAC in 2003. Details of the sample can be found in Zachary Dyckman
and Peggy Hess, Survey of Health Plans Concerning Physician Fees and
Payment Methodology (Washington, D.C.: Dyckman & Associates, August
2003).
[48] Based on the Fisher's exact test--a statistical test that is used
to determine if there is a nonrandom association between two
categorical variables--we concluded that the distribution of the GPCIs
in the 36 payment localities for which we had fee schedules did not
differ significantly from the distribution of the GPCIs in the other
localities. Dyckman subsequently eliminated one plan's fee schedule
from the analysis because it was an outlier.
[49] For each type of five services--surgery, laboratory and pathology,
radiology, assorted medical and diagnostic services, and other
evaluation and management--Dyckman calculated the unweighted average
private fee for services in that category. For the sixth type--office
visits--Dyckman calculated a weighted average, using frequency of each
individual service (such as a specific type of office visit) as the
weight. The six type-of-service categories were then weighted by each
category's total service use.
[50] The 513 geographic areas are a subset of the 545 work areas
(consolidated metropolitan statistical areas (CMSA), metropolitan
statistical areas (MSA), New England county metropolitan areas (NECMA),
and rural state balances in a state) for which complete data were
available.
[51] The specialties are cardiovascular surgery, orthopedic surgery,
dermatology, ophthalmology, neurosurgery, neurology, pulmonary disease,
plastic surgery, gastroenterology, obstetrics/gynecology, and
colon/rectal surgery.
[52] These factors had a significant effect on geographic difference in
physicians' income. Data on these factors were obtained from the 2002
Area Resource File and the 2000 decennial census. Information on
physician income was also taken from the 2000 decennial census.
[53] See Direct Testimony of Anthony M. Yezer Before the Postal Rate
Commission: Postal Rate and Fee Changes, Docket No. R2000-1
(Washington, D.C.: Jan. 12, 2000). The USPS agreed to permit Professor
Yezer to use these data to develop an index designed to meet the
requirements of the practice expense GPCI.
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