Medicare Physician Fees: Geographic Adjustment Indices Are Valid 
in Design, but Data and Methods Need Refinement (11-MAR-05,	 
GAO-05-119).							 
                                                                 
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.				 
-------------------------Indexing Terms------------------------- 
REPORTNUM:   GAO-05-119 					        
    ACCNO:   A19136						        
  TITLE:     Medicare Physician Fees: Geographic Adjustment Indices   
Are Valid in Design, but Data and Methods Need Refinement	 
     DATE:   03/11/2005 
  SUBJECT:   Cost analysis					 
	     Data collection					 
	     Health care planning				 
	     Health services administration			 
	     Income statistics					 
	     Malpractice (medical)				 
	     Medical fees					 
	     Medicare						 
	     Physicians 					 
	     Price adjustments					 
	     Work measurement					 
	     Policy evaluation					 
	     Statistical methods				 
	     Standards (health care)				 

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GAO-05-119

                 United States Government Accountability Office

                     GAO Report to Congressional Committees

March 2005

MEDICARE PHYSICIAN FEES

  Geographic Adjustment Indices Are Valid in Design, but Data and Methods Need
                                   Refinement

                                       a

GAO-05-119

[IMG]

March 2005

MEDICARE PHYSICIAN FEES

Geographic Adjustment Indices Are Valid in Design, but Data and Methods Need
Refinement

                                 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 Median hourly wage for registered nurses

                      Oakland/Berkeley, California $29.16

Massachusetts, excluding metropolitan Boston 22.06

                            Fort Worth, Texas 21.26

                                New Mexico 19.83

                              South Carolina 19.60

Source: GAO analysis of data from CMS and U.S. Census Bureau.

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 highcost 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.

                 United States Government Accountability Office

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

1 3 4

13

21 29 30 31

Appendixes

                                       Appendix I: Appendix II: Appendix III:

Appendix IV:

Data and Methods

Rent Indexes and the Practice Expense GPCI

Comments from the Department of Health and Human Services

GAO Contact and Staff Acknowledgments

GAO Contact Acknowledgments

                                     37 41

42

48 48 48

Tables   Table 1: The Physician Work, Practice Expense, and Malpractice 
                      GPCIs for Five Payment Localities, 2004               8 
           Table 2: The Medicare Physician Fee for a Midlevel Office Visit 
                                                                        in 
                           Five Payment Localities, 2004                    9 
             Table 3: Geographic Differences in Hourly Wage for Registered 
                                    Nurses, 2000                           17 
               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                          22 
             Table 5: Data Sources Used in CMS's Construction of GPCIs     37 
            Table 6: Factors Explaining Variation in Physicians' Average   
                       Annual Income for 513 Geographic Areas              40 

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) 12

Contents

Figure 2: Variation in Private Plans' Physician Fees and Average

Medicare GPCI by Medicare Payment Locality, 2002 25 Figure 3: Number of
Retirements of Iowa Physicians and Standard

& Poors Composite Index of Stock Prices, 1993-2003 29

Abbreviations

AAFD American Academy of Family Physicians
ACS American Community Survey
AMA American Medical Association
CMS Centers for Medicare & Medicaid Services
CMSA consolidated metropolitan statistical area
CPI Consumer Price Index
FMR fair market rent
GAF geographic adjustment factor
GPCI geographic practice cost index
HCFA Health Care Financing Administration
HHS Department of Health and Human Services
HUD Department of Housing and Urban Development
MedPAC Medicare Payment Advisory Commission
MMA Medicare Prescription Drug, Improvement, and

Modernization Act of 2003 MSA metropolitan statistical area NAIC National
Association of Insurance Commissioners NECMA New England county
metropolitan area RVU relative value unit USPS United States Postal
Service

This is a work of the U.S. government and is not subject to copyright
protection in the United States. It may be reproduced and distributed in
its entirety without further permission from GAO. However, because this
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separately.

A

United States Government Accountability Office Washington, D.C. 20548

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))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.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.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

1The Health Care Financing Administration (HCFA) was renamed CMS on July
1, 2001.
2Pub. L. No. 108-173, S: 413(c), 117 Stat. 2066, 2277-78.
3The MMA directs us to examine the GPCIs' validity but does not define the
term.

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 20002002
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 2005.4

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 highcost areas. The work
GPCI does so by limiting downward cost

4Our work began in response to a request from the Senate Finance Committee
and continued pursuant to MMA.

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:

o 	Physician work-the financial value of physicians' time, skill, and
effort that are associated with providing the service.

o 	Practice expense-the costs incurred by physicians in employing office
staff, renting office space, and buying supplies and equipment.

o 	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.5

Each RVU measures the relative costliness of providing a particular
service. For example, for a midlevel office visit for an established
patient,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 procedure7 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

5These percentages do not total to 100 percent due to rounding. The
percentages correspond to shares of the average cost of running a
physician practice.

6A 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.

7The 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.

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.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.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.

8The 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.

9HCFA 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).

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.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.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.

o 	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.

10The 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.

11This refers to the value-as perceived by these professionals-of a
locality's attributes, such as schools, entertainment, and quality of
professional colleagues.

o 	In measuring physician office rent, CMS uses a proxy-HUD's FMR
residential index of the average rent for a two-bedroom apartment.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.

o 	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 localitya

Physician work GPCI

Practice expense GPCI

Malpractice GPCI

              Oakland/Berkeley, California    1.041       1.235         0.669 
                  Massachusetts, excluding    1.010       1.129         0.803 
                  metropolitan Boston area                         
                         Fort Worth, Texas    1.000b      0.981         0.996 
                                New Mexico    1.000b      0.900         0.898 
                            South Carolina    1.000b      0.904         0.336 

Source: CMS.

aSelected 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

12The 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).

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.

bMMA set a temporary floor of 1.00 for the physician work GPCI.

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

Medicare physician fee for Payment localitya a midlevel office visitb

                      Oakland/Berkeley, California $59.32

            Massachusetts, excluding metropolitan Boston area 55.97

                            Fort Worth, Texas 52.14

                                New Mexico 49.88

                              South Carolina 49.14

Source: GAO calculation using CMS data.

aSelected 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.

bA 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.

Evolution of GPCIs	In the Omnibus Budget Reconciliation Act of 1989,13
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.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.

o 	The payment localities were consolidated in 1997, reducing the number
from 210 to 89.15 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.

13See Pub. L. No. 101-239, S: 6102(a), 103 Stat. 2106, 2169-84 (adding
section 1848 to the Social Security Act) (codified at 42 U.S.C. S: 1395w-4
(2000)).

14Specifically, 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.

15There were 240 payment localities before the physician fee schedule was
implemented; as of January 1, 1995, the number had been gradually reduced
to 210.

o 	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.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 1.17 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.

16MMA, S: 412, 117 Stat. at 2274 (to be codified at 42 U.S.C. S:
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.

17This weighted average for a locality is a measure of that locality's
Medicare fees relative to other localities' Medicare fees.

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)

                       Source: GAO analysis of CMS data.

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.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

18Council 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.

Medicare Incentive Payment program pays physicians 10 percent more than
the usual Medicare fee for services provided to beneficiaries in health
professional shortage areas.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.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

19The Health Resources and Services Administration designates areas having
a shortage of primary care providers as health professional shortage
areas. See 42 U.S.C. S: 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.

20MMA, S: 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.

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,21 which was last
administered in 2000.

21This form is given to a sample of about one in every six U.S. households
and contains questions on income, housing, and other issues.

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.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.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:

o 	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.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

22The 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.

23See GAO, American Community Survey: Key Unresolved Issues, GAO-05-82
(Washington, D.C.: Oct. 8, 2004).

24Elliott 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.

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.

o 	Using physicians' earnings would produce a circular measure: the work
adjustment would depend on past payments to physicians, including past
Medicare payments.25

Practice Expense GPCI Generally Valid in Design, but Can Be Better
Measured

Validity of Practice Expense GPCI

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.

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.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.

25See 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.)

26In 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.

Table 3: Geographic Differences in Hourly Wage for Registered Nurses, 2000

           Payment localitya Median hourly wage for registered nurses

                      Oakland/Berkeley, California $29.16

Massachusetts, excluding metropolitan Boston 22.06

                            Fort Worth, Texas 21.26

                                New Mexico 19.83

                              South Carolina 19.60

Source: GAO analysis of data from CMS and U.S. Census Bureau.

aSelected 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.

Measurement of Practice In the future, new data sources will become
available that could be used in

                                  Expense GPCI

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.27

27We 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.

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.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 The malpractice GPCI is valid in its fundamental
design, but issues Design, but CMS's Data and regarding the data and
methods used in constructing this GPCI reduce its

Methods Remain a Concern

28See GAO-05-82.

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 CMS's methods for collecting malpractice
premium data and aggregating

GPCI	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:

o 	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.

o 	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.

o 	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.)

o 	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 yearto-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 The impact of GPCIs on physicians' incomes is
generally modest, raising or Market Factors in Affecting lowering
physicians' incomes by no more than 2 to 3 percent in most Physicians'
Incomes localities.29 Physicians typically derive one-quarter of their
practice income

from Medicare.30 Table 4, which shows examples of income before and

after GPCIs' adjustment, demonstrates the GPCIs' effect on physicians'

29In this analysis, income refers to earnings of physicians.

30The 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.

income by locality.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

Income from identical physician practicesb

                               Payment localitya

    Hypothetical income not adjusted by GPCIs Hypothetical income adjusted by
                                                                        GPCIs

                      Oakland/Berkeley, California   $150,000        $154,212 
             Massachusetts, excluding metropolitan    150,000         152,060 
                                       Boston area               
                                 Fort Worth, Texas    150,000         149,720 
                                        New Mexico    150,000         148,250 
                                    South Carolina    150,000         147,493 

Source: GAO analysis of CMS and American Medical Association (AMA) data.

aSelected localities represent the 90th, 75th, 50th, 25th, and 10th
percentiles of the Medicare payment localities ranked by the weighted
average of their GPCIs.

bThe 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 20002002
Edition.

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

31The 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.)

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

o 	the average income of the population was relatively high, as higher
income in a community is associated with higher demand for physicians'
services;

o  the number of nurses was large relative to the population;

o 	the percentage of physicians was large in particular specialties, such
as cardiovascular surgeons, orthopedic surgeons, and ophthalmologists; and

o  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.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.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.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

32For 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.

33The 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).

34For 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).

fees-account for much more of the variation in physician incomes than do
the GPCIs.35

Figure 2: Variation in Private Plans' Physician Fees and Average Medicare
GPCI by

Medicare Payment Locality, 2002

Private plans' average physician fee in a payment locality relative to
national average of private plan fees (percentage)

150

140

130

120

110

100

90

80

70

Average Medicare GPCI in a Medicare payment locality (percentage)

Source: Dyckman & Associates.

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.

35If 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).

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.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.37 Practice
characteristics that influenced location decisions included clinical
autonomy, the

36Anthony 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.

37Suzanne 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).

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.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.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

38See 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.

39In 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.

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.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.)

40Minarick and Allen, "Factors Influencing the Satisfaction and Retention
of Nebraska's Rural Physicians."

Figure 3: Number of Retirements of Iowa Physicians and Standard & Poors
Composite Index of Stock Prices, 1993-2003 Retirements of Iowa physicians
Standard & Poors index

90 80 70 60 50 40 30 20 10

0

1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003

Year

Retirements

Standard & Poors Source: GAO.

1600 1400 1200 1000

800 600 400

200 0

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:

o 	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;

o 	add data on physician assistants' wages to improve the measurement of
the practice expense GPCI;

o 	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;

o  collect malpractice premium data from all states;

o 	collect data from insurers that account for at least half of
malpractice business in a state; and

o  standardize collection of malpractice premium data.

Agency and Industry We received written comments on a draft of this report
from HHS (see app.

III) and oral comments from two national associations of
physicians-theComments and Our American Medical Association (AMA) and the
American Academy of Evaluation 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:

o 	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. 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

41Funding for the ACS (for all persons except those living in group
quarters) was approved beginning with 2005.

be prudent for the CMS component of HHS to also begin planning the GPCI
transition to the ACS.42

o 	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.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.

o 	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

42The Census Bureau told us that some parts of HHS have begun working with
Census to achieve a smooth transition.

43Debra 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).

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.

o 	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.

o 	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 The two industry associations that commented varied
in their observations

Comments 	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.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.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.

44Stephen Norton and Stephen Zuckerman, "Trends in Medicaid Physician
Fees, 1993 to 1998," Health Affairs, vol. 19, no. 4 (2000), 222-232.

45The 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.

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
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.

A. Bruce Steinwald Director, Health Care-Economic and Payment Issues

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.1 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              Purpose                           Data                
All GPCIs Weight variables used in        2002 work, practice expense, and 
             constructing GPCI              malpractice components of RVUs by 
                by county total of RVUs for                                   
                             each component              county
                (work, practice expense,    
                      malpractice)          
             Crosswalk counties to Medicare  List of U.S. counties, list of   
             payment                               payment localities         
                       localities           

Crosswalk Census Bureau's 545 work List of CMSAs, MSAs, and rural state
balances; list of U.S. counties
areas-consolidated metropolitan statistical
areas (CMSA), metropolitan statistical areas
(MSA), New England county metropolitan
areas (NECMA), and rural balances-to U.S.
counties

Work GPCI Construct index of 6 professions' earnings	2000 decennial census
data on earnings of 6 professional categories for 545 work areas

Weight earnings of each professional Share of employees in each of 6
professional categories category by its share of employees

1Shannon Slawter, Jim Moser, and Shihki Barcheck, Fourth Update to the
Geographic Practice Cost Index: Final Report (McLean, Va.: BearingPoint,
Jan. 15, 2004).

                          Appendix I Data and Methods

                         (Continued From Previous Page)

                               Index Purpose Data

Practice Construct employee wage 
              index of 4            
      expense GPCI nonphysician     
             occupations            
       Weight earnings of each of 4    2000 decennial census data on share of 
                       nonphysician                    employees in each of 4 
        occupations by its share of                                           
                          employees          nonphysician categories

       Decennial census data on wages of 4 occupations for 545 work areas

Obtain rent index	2004 HUD fair market rent (FMR) Index for two-bedroom
apartments for all counties in the United States

Combine components of practice expense Cost shares of these components
into the practice expense index, using the
cost shares of these components

Malpractice Construct malpractice premium price index Malpractice premiums
and premiums as adjusted by CMS contractor for

GPCI	20 specialty groups for at least 2 carriers per state for 1999-2001
and 1 carrier per state for 2002

    Crosswalk insurers' rate area to counties List of each insurer's rating
                       territories, list of U.S. counties

Weight each insurer's premiums by market Market share for each insurer for
which 2001 premiums were obtained,

share	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.

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
2002.2 These analyses were commissioned by MedPAC and carried out by
Dyckman & Associates-referred to here as Dyckman. For this analysis,
Dyckman

o 	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,3

2These 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).

3Based 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.

                          Appendix I Data and Methods

o 	calculated for each fee schedule a private fee index-the ratio of the
average private fee to the national average, and

o 	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

o 	classified 89 commonly used Medicare procedures into 6 types of
services;

o 	calculated the mean of private plans' fees that operate in each one of
the 36 Medicare payment localities;4 and

o 	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 To determine the effect of GPCIs and other factors on
physicians' income,

Geographic Difference in 	we estimated a model of average physician income
in 513 geographic areas.5 We controlled for factors that affect
physicians' income, such as

Physicians' Income	physicians' location, their hours of work, their
specialties,6 the extent of their competition, as measured by the relative
number of physicians to the population in an area, and the availability of
nurses.7 Table 6 presents our

4For 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-ofservice categories were then weighted by each category's total
service use.

5The 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.

6The specialties are cardiovascular surgery, orthopedic surgery,
dermatology, ophthalmology, neurosurgery, neurology, pulmonary disease,
plastic surgery, gastroenterology, obstetrics/gynecology, and colon/rectal
surgery.

7These 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.

Appendix I Data and Methods

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 Coefficient p < |t| 
         GPCI-weighted average of work, practice expense,             
                                                      and             
                                       malpractice GPCIsa  -3,414.99     0.92 
        Average Medicare payment for physicians' services             
                                                      per             
                                      beneficiary (2002)a        7.26    0.19 
           Located in metropolitan statistical area (MSA)  17,471.71     0.00 
          Average weekly work hours for physicians in the  1,521.77      0.00 
                                                     area             
          Percentage of physicians who belong to selected             
                                                specialty             
                                              categoriesb  2,032.36      0.00 
                    Average managed care penetrationc (%)     -505.42    0.00 
              Number of patient-care physicians per 1,000  -4,625.12     0.00 
                                              populationd             
        Percentage of physicians who are non-patient-care  -1,580.44     0.00 
                                             physicians e             
                   Number of nursesf per 1,000 population  2,239.46      0.00 
           Average annual income for all civilians in the        1.81    0.00 
                                                     area             
                                                Constanta  4,299.85      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
R2 for the estimated model is .41.

aFactor is not statistically significant: p-value greater than .05.

bThese specialties are cardiovascular surgery, orthopedic surgery,
dermatology, ophthalmology, neurosurgery, neurology, pulmonary disease,
plastic surgery, gastroenterology, obstetrics/gynecology, and colon/rectal
surgery.

cThe proportion of an area's population enrolled in a managed care
organization.

dPatient-care physicians include office-based physicians, hospital
residents, and hospital full-time staff physicians.

eNon-patient-care physicians include those whose major professional
activity is research, medical education, or administration.

fNurses include registered nurses, licensed practical nurses, and nurse
practitioners.

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.1 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.

1See 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.

Appendix III

Comments from the Department of Health and Human Services

Appendix III
Comments from the Department of Health
and Human Services

Appendix III
Comments from the Department of Health
and Human Services

Appendix III
Comments from the Department of Health
and Human Services

Appendix III
Comments from the Department of Health
and Human Services

Appendix III
Comments from the Department of Health
and Human Services

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.

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