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5
Geographic Practice Cost Indexes
F
ee-for-service Medicare payments to physicians and certain other licensed clinical prac-
titioners (including nurse practitioners, physician assistants, clinical nurse specialists, and
occupational and physical therapists) are adjusted for geographic differences in market
conditions and business costs. These geographic adjustments are intended to ensure that pay-
ment to providers reflects the local costs of providing care, so that the Medicare program does
not overpay in certain areas and underpay in others.
Each of the three components of the Medicare Physician Fee Schedule (PFS)—physician
work, practice expense (PE), and malpractice (MP) insurance—is adjusted for differences across
geographic areas in the input prices related to each component. When they are combined,
these three components are known as the geographic adjustment factor (GAF).1
This chapter describes the history, intent, and evolution of the geographic practice cost
indexes (GPCIs) to provide background and context for the committee’s findings and recom-
mendations about improving the accuracy of payment. The committee sought to develop a uni-
form and consistent approach to the GPCIs and the hospital wage index (HWI) (see Chapter 3)
by employing comparable data sources and methods.
Throughout its deliberations about the GPCIs, the committee has made a distinction
between geographic adjustments that are designed to adjust payments for input price differ-
ences that providers face, and those that might be made to help address perceived workforce
shortages and achieve other policy goals. While the committee acknowledged that both cost and
access are part of its charge, it took the position that preserving access to care in nonmetropoli-
tan areas should be done explicitly rather than using the GPCIs to address both cost differences
and access issues (Zuckerman and Maxwell, 2004). The committee viewed the combination
1 Unless otherwise specified, the term “practitioners” is used to describe both physicians and other eligible clinical
practitioners who are permitted to furnish services and bill Medicare under the Physician Fee Schedule (CMS, 2009).
Physician assistants must be supervised by a physician, but nurse practitioners and certain other practitioners may
practice independently if their state laws allow it and may therefore bill Medicare directly. Their payment is a set
percentage of the Physician Fee Schedule.
113
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114 GEOGRAPHIC ADJUSTMENT IN MEDICARE PAYMENT
of the two sets of issues as conceptually problematic by making it difficult to distinguish the
level of resources being allocated to each objective, which affected the determination of the
accuracy of payment.
Accordingly, the committee’s conceptual distinction is reflected in the structure of its
reports. The committee’s phase 1 report addresses geographic differences in input prices,
focusing on improving accuracy by relying on the best possible input price measures from
an independent source. Phase 2 of the committee’s work will address broader policy issues,
including workforce supply and access to care in the context of geographic adjustment. For
example, physician practices have an increasingly diverse mix of employment arrangements,
and advanced practitioners such as nurse practitioners contribute to the work component as
well as the practice component of physician work. Accordingly, the phase 2 report will also
consider the impact of the committee’s phase 1 report recommendations on geographic
adjustment to fee-for-service payment in the context of current market trends toward delivery
system integration.
GEOGRAPHIC ADJUSTMENTS TO FEE-FOR-SERVICE PAYMENTS
Fee-for-service Medicare payments to practitioners are based on the PFS. The PFS is based
on a list of more than 7,000 distinct services defined according to the nomenclature of the
Current Procedural Terminology (CPT®) codes developed by the American Medical Associa-
tion (AMA) (2011a). CMS uses the CPT® codes to create an expanded coding system called
the Healthcare Common Procedure Coding System (HCPCS) and assigns HCPCS codes to the
7,000+ procedures that Medicare recognizes in its fee-for-service payment system.
Medicare payment for physicians and other licensed health practitioners for each service is
based on submission of a claim using one or more HCPCS codes (CMS, 2011a). Each HCPCS
code has an assigned number of relative value units (RVUs) that represents the cost of resources
required to provide a particular procedure or service relative to the resources associated with
other procedures or services. For example, a follow-up office visit and a cataract removal require
different amounts of resources than those needed to perform a colonoscopy, so all are assigned
different RVUs (MedPAC, 2008). The total RVUs for a procedure are subdivided into the three
components of the PFS: physician work, PE, and MP insurance:
• Physician work RVUs reflect the time, skill, effort, judgment, and stress associated with
providing one service relative to other services.
• Practice expense RVUs address the direct costs of providing a service and the
indirect costs of maintaining a clinical practice, including administrative and clinical staff
compensation (salary and benefits), rent, and supplies and equipment (CMS, 2010a).
For most services, there are different PE RVUs for services provided in facility settings
and in office settings. Practice expenses associated with supplies and equipment are not
adjusted geographically because they are typically purchased in a national market with
practically uniform prices across areas.
• Malpractice premium RVUs represent payment for professional liability insurance
(PLI), also known as MP insurance (CMS, 2010a). The mean MP premium for each
payment area is weighted for state- and insurer-specific specialty mix and adjusted for
each insurer’s market share (O’Brien-Strain et al., 2010).
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GEOGRAPHIC PRACTICE COST INDEXES
Before Medicare pays for a service, the RVUs for that service are adjusted for geographic
differences in input prices and for provider type (e.g., physician, nurse practitioner, podiatrist,
and others who can bill Medicare independently). Policy adjustments are also made, such as
for services furnished in a provider shortage area. Then, the sum of the three geographically
adjusted total RVUs is multiplied by a conversion factor (CF) that determines Medicare payment
in dollars (see Appendix B).
Physician services include office visits, surgical procedures, and a broad range of other services
provided in offices, hospitals, clinics, post-acute care settings, and other clinical settings (MedPAC,
2007). For most physician services in most settings, Medicare pays the provider 80 percent of
the fee schedule amount and the Medicare beneficiary is responsible for the remaining 20 per-
cent2 (MedPAC, 2010) after meeting the $162 deductible (HHS, 2011). Medicare pays nurse
practitioners, physician assistants, and clinical nurse specialists at 85 percent of the physicians’
fees, after the deductible is met (MedPAC, 2010). However, their services can be paid at 100
percent of the physicians’ fees if they are “incident to” services, or services that are rendered by
a nurse, and billed by the supervising physician (MedPAC, 2010).
Payment Methodology
Medicare pays for physicians’ services under Section 1848 of the Social Security Act, which
requires that payments be based on national uniform RVUs (CMS, 2010b; Hsiao et al., 1988).
The basic concepts and methodology of the current Medicare physician payment approach,
known as the Resource-Based Relative Value Scale (RBRVS), were enacted in the Omnibus Budget
Reconciliation Act of 1989 (OBRA) and implemented by the Centers for Medicare and Medicaid
Services (CMS) in 1992. The change was intended to make Medicare payments more equitable
by basing them on relative input use rather than on historical prices, and to reflect local varia-
tion in input prices. Additional statutory changes that affect geographic adjustment have been
made over the years (see Box 5-1).
CMS is required by law to update the GPCIs that adjust these RVU-based fees every 3 years.
The CY 2011 final PFS rule implemented the following changes to the adjustment factors in
response to new statutory requirements in the Patient Protection and Affordable Care Act (ACA):
• Extended the GPCI work floor of 1.0 through FY 2011, in accordance with a provision
in the Medicaid and Medicare Extension Act of 2010;
• Kept the permanent 1.5 GPCI work floor for Alaska in effect; and
• Established a permanent, non-budget neutral floor of 1.0 for practice expense for
“frontier” states (Montana, Nevada, North Dakota, South Dakota, and Wyoming).
By statute, any changes to the GPCIs that do not explicitly receive additional funding must
be budget neutral. In practice, budget neutrality requires that the total amount of payment be
unaffected by new adjustments, so that any adjustment upward for one payment area must
2 Participating providers receive the Medicare Part B allowed amount as payment in full for services and bill the
beneficiary only for any coinsurance or deductible that may apply. Payment for nonparticipating physicians (those who
have not signed a Participating Payment Agreement with the Part B enrollment department at CMS) is 5 percent below
the Medicare Physician Fee Schedule amount (CMS, 2009), but these physicians are permitted to bill patients up to
15 percent in excess of the fee schedule amount (https://www.cms.gov/mlnproducts/downloads/physicianguide.pdf).
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116 GEOGRAPHIC ADJUSTMENT IN MEDICARE PAYMENT
BOX 5-1
Geographic Practice Cost Index Timeline of Events
1989: The U.S. Congress requires that the U.S. Department of Health and Human Services
(HHS) account for physician work, practice expenses, and malpractice expenses when calcu-
lating the geographic practice cost indexes (GPCIs) (Omnibus Budget Reconciliation Act of
1989. P.L. 101-239, December 19, 1989).
1992: Section 1848 of the Social Security Act establishes a fee schedule for physicians’ services.
1996: The Health Care Financing Administration reduces the number of payment areas from
210 to 89 (CMS, 1996).
1997: The U.S. Congress requires the Centers for Medicare and Medicaid Services (CMS) to
implement resource-based malpractice relative value units (RVUs) for all services provided,
effective in the year 2000 (The Balanced Budget Act of 1997. P.L. 105-33, August 5, 1997).
2003: The U.S. Congress mandates review of the practice expense GPCI (Medicare Prescrip-
tion Drug, Improvement, and Modernization Act of 2003. P.L. 108-173, December 8, 2003).
2005: The Government Accountability Office (GAO) reports that the GPCIs are sound con-
ceptually but that data and data collection methods could be improved, such as by collecting
more data on physician assistant wages and using commercial rent data rather than residential
rent rates (GAO, 2005).
2007: GAO recommends that CMS design a uniform approach to defining payment areas, so
that there is consistency from state to state, and that CMS base its locality structure on the
most recent data (GAO, 2007).
2007: The Medicare Payment Advisory Commission recommends that CMS exclude expenses
that do not vary geographically (including supplies and medical equipment) from the GPCI
formulas to improve their accuracy (MedPAC, 2007).
2008: Acumen report for CMS evaluates four smoothing techniques, and concludes that each
method would significantly reduce large disparities between payment areas (O’Brien-Strain
et al., 2008).
2010: On behalf of HHS Secretary Kathleen Sebelius, CMS commissions the Institute of Medi-
cine to evaluate the accuracy of the geographic adjustment factors in a 2-year study.
2010: The U.S. Congress passes the Patient Protection and Affordable Care Act of 2010, which
establishes a wage index floor of 1.0 for frontier states, sets a practice expense GPCI floor for
frontier states, and extends the work GPCI floor through December 31, 2010 (P.L. 111-148).
2010: In November 2010, CMS posts the final Physician Fee Schedule rule with comment pe-
riod for the 2011 GPCI. The Final Rule describes updates to GPCI weights and includes new
regulations in response to provisions in the Patient Protection and Affordable Care Act of 2010
(CMS, 2010b).
2011: On July 8, 2011, CMS issues the CY 2012 Physician Fee Schedule Proposed Rule, which
proposes to change the GPCI cost share weights by decreasing the weight for work and increas-
ing the practice expense (PE) weight; to add a new category for contract labor as a component
of the PE; and to use American College of Surgeons (ACS) residential rent data for the office
rent component of the GPCI.
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GEOGRAPHIC PRACTICE COST INDEXES
be paid for by a downward adjustment for other areas. This requirement creates significant
tensions among providers in high- versus low-cost areas.3
Another major source of disagreement is whether the geographic adjusters should be used
as policy levers to help influence provider supply, particularly in nonmetropolitan areas. Some
rural health policy experts and practitioners argue that because earning potential influences
physicians’ decisions on where to practice, and because many private payers use Medicare prices
as a basis for setting their own rates, the geographic adjustments should be used as policy tools
to encourage physicians to practice in nonmetropolitan areas (Iowa Medical Society, 2010;
MacKinney et al., 2003). Using the geographic price adjusters to raise payments in provider
shortage areas has been called into question by others on the grounds that it is inconsistent with
the underlying purpose of input price adjustments and reduces payment accuracy (Schwartz,
2010).
Another source of long-standing dissatisfaction over the geographic adjustment factors has
been the use of proxy data from sources other than physician practices to measure geographic
variation in the price of some inputs. Among practitioners, the complexity of the index con-
struction and the lack of direct public access to some of the sources of data used for the index
calculations have also been grounds for criticism.
The committee’s principles value transparency to stakeholders, but they also assign a high
priority to the task of improving accuracy by relying on the best possible input price measures
from an independent source. In the view of the committee members, proxy data for physician
earnings are more accurate than are data on costs paid by providers because the proxy data
are independent of local business decisions or other requirements, such as state laws on staff-
ing ratios, which do not necessarily reflect input prices across labor markets. The committee
also made a distinction between geographic payments that are intended to adjust payments
for input prices and those adjustments that might be made to help reach policy goals, such as
addressing shortages of clinical practitioners to maintain or improve access to care. Such policy
adjustments will be addressed in the phase 2 report.
Payment Areas
The GPCI payment adjustments are made for 89 different geographic areas in the United
States, also known as payment areas (or localities). Some are defined according to metropoli-
tan areas, but there are 34 statewide payment areas that include both metropolitan and non-
metropolitan areas (see Figure 1-5 in Chapter 1). Practice input prices may vary substantially
within payment areas, particularly in the statewide areas. For example, although Texas has
eight areas (Brazoria, Dallas, Galveston, Houston, Beaumont, Fort Worth, Austin, and the rest
of Texas), San Antonio—the 25th largest metropolitan area in the country and the 3rd largest
metropolitan area in Texas—is included within the “rest of Texas” payment area, despite the fact
that practitioners there are unlikely to face prices equivalent to those in the nonmetropolitan
areas of Texas.
Historically, CMS has relied on the advice of state medical associations when deciding
whether to make changes to statewide payment areas. However, as the Texas example shows,
statewide payment areas do not necessarily represent economically integrated areas with simi-
lar relative wages and rents, and they may not be the most accurate basis for adjustment. In
3 See, for example, statements to the IOM Committee on Geographic Adjustment Factors in Medicare Payment from
Senator Grassley (2011), Eneida Roldan (2011), and Alice Tolbert Coombs (2010).
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118 GEOGRAPHIC ADJUSTMENT IN MEDICARE PAYMENT
recent rules, CMS (2010a) noted that changes in demographics and local economic conditions
have occurred since 1997, when the current payment area structure was developed and imple-
mented. These changes may have led to inconsistencies between payment differences and input
price differences that warrant reconsideration of the current configuration of payment areas.
The committee’s discussion and recommendations about revising payment area configura-
tions are the subjects of Chapter 2. Because hospitals and physicians essentially draw from the
same labor market, the committee recommends that the same set of payment areas be used for
the HWI and the GPCIs, and that metropolitan statistical areas (MSAs) and statewide non-MSAs
should serve as the basis for defining these labor markets. While the payment areas would stay
the same for the HWI, implementing this recommendation would mean that the GPCI payment
areas would expand from 89 to 441 areas, which would be a significant change. The impact
of the change in payment areas will be assessed in the phase 2 report.
GEOGRAPHIC ADJUSTMENT FACTOR COMPONENTS
As described above, the GAF is a combination of three independent GPCIs, each used to
adjust the fee schedule for geographic variation in input prices for a different component of
the cost of physician care.
The relative contribution of these three components varies by type of service and the set-
ting where it is provided. For example, the composition of the total RVU for the office visit code
99201 is roughly 40 percent work RVU, 57 percent PE RVU, and 3 percent malpractice RVU,
while the composition for the emergency room visit code 99283 is roughly 74 percent work,
21 percent PE, and 5 percent malpractice. Because each CPT code is composed of a different
mix of the three RVUs, and therefore the three GPCIs are combined in different proportions,
each code has a different average GAF.
When it was introduced, the RBRVS was seen as a significant improvement over the previ-
ous system, which was based on the customary, prevailing, and reasonable (CPR) physician
fees in each payment area. Payments based on the CPR method varied widely across areas but
were only partially explained by differences in practice costs (Physician Payment Review Com-
mission, 1991).
CMS updates the RBRVS to adjust values for new services and to reflect services that may be
overvalued or undervalued after considering the recommendations of the AMA/Specialty Society
Relative Value Scale Update Committee (RUC). The accuracy of the RUC’s valuation of services
has been another source of discussion and debate for some time. According to the Medicare
Payment Advisory Commission (MedPAC), the RUC process does not accurately identify services
that are overvalued and tends to recommend higher values for specialty care (MedPAC, 2006).
In its discussions about accuracy and the work adjustment, the committee acknowledged
the importance of the RVUs in the broader fee-for-service healthcare system, since most private
insurers use the RVUs as the basis for negotiating fees with physicians in their networks. While
the committee believes that further study of the accuracy of the RVUs is warranted in the near
future, that effort is beyond the scope of this committee’s charge.
GPCI Cost Share Weights
To set the relative importance of each input category, CMS bases the GPCI cost share weights
on those used in the Medicare Economic Index (MEI), which measures price differences (infla-
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tion) from year to year (rather than across geographic areas) in the cost of providing services
under the PFS (MaCurdy et al., 2011). The weight assigned to the GPCI for each component of
the Medicare PFS is based on the sum of the MEI cost shares of the inputs that comprise that
component. The MEI cost shares are updated annually to meet a statutory requirement, which
states that any prevailing charge levels beginning after June 30, 1973 may not exceed the level
from the previous year except to the extent that the Secretary find that a higher level is justified
by year-to-year economic changes based on appropriate economic index data (P.L. 74-271).
In CY 2011, the GPCI cost share weights were based on the 2000 base-year MEI weights,
reflecting physician expenses in 2000. In the PFS proposed rule for CY 2012, CMS announced
plans to update the GPCI cost share weights with the 2006 base-year MEI cost share weights,
which use more current practice expense data primarily from the 2006 AMA Physician Prac-
tice Information Survey (PPIS) (MaCurdy et al., 2011). This update would decrease the overall
weight assigned to physician work, increase the overall weight assigned to practice expense,
and disaggregate certain practice expense categories (see Table 5-1).
Within the practice expense component, the proposed rule for CY 2012 adds a new PE cost
category for purchased services. The purchased services index reflects regional variation in input
costs for contracted labor that would typically be outsourced, such as accounting, legal, and
building maintenance services. These industries are included in the “all other services” category
within the MEI office expense and the stand-alone “other professional expenses” category of
the MEI (MaCurdy et al., 2011).
No geographic adjustment is applied to the portion of payment that corresponds to inputs,
such as equipment and supplies that are generally purchased in national markets at prices that
do not vary systematically by geographic area (GAO, 2005). Because the physician work GPCI is
adjusted for only one-quarter of the geographic variation in the proxies used in the adjustment,
and no adjustment is applied to the equipment and supplies component of PE, only 48 percent
of the GPCI cost share weights were adjusted for geographic input price variation in 2011. The
changes in the proposed CY 2012 GAF would increase this percentage from 48 to 51 percent
in CY 2012 (see Table 5-1) (MaCurdy et al., 2011).
TABLE 5-1 Comparison of CY 2011 and Proposed CY 2012 Geographic Practice Cost Index
(GPCI) Cost Share Weights
Geographically Adjusted
Cost Share Weights (%) Cost Share Weights (%)
Current Rule Proposed Rule Current Rule Proposed Rule
Expense Category CY 2011 CY 2012 CY 2011 CY 2012
13.12a 12.00a
Physician Work 52.47 48.27
Practice Expense 43.67 47.44 30.86 34.39
Employee Compensation 18.65 19.15 18.65 19.15
Office Rent 12.21 10.22 12.21 10.22
5.01b
Purchased Services n/a 8.10 n/a
Equipment, Supplies, Other 12.81 9.97 0.0 0.0
Malpractice Insurance 3.87 4.30 3.87 4.30
Total 100.00 100.0 47.85 50.75
a Work
cost share weight with the one-quarter work adjustment.
b Only
62 percent of the purchased services index is adjusted for geographic variation in contracted services.
SOURCE: MaCurdy et al., 2011.
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120 GEOGRAPHIC ADJUSTMENT IN MEDICARE PAYMENT
WORK GPCI
The physician work GPCI is designed to reflect geographic differences in the cost of physi-
cian labor across areas in comparison to the national average (CMS, 2010a). The committee
discussed two key issues: (1) whether physician work should be adjusted for geographic differ-
ences in the price of physician labor and, if so, to what extent; and (2) what data should be
used in computing the work adjustment.
The physician work GPCI has some unique characteristics compared to the practice expense
GPCI. Practice costs such as office rent and wages of nonphysician personnel are determined in
local real estate and labor markets, where geographic variation in input prices is well understood
and reasonably well documented. Physician work costs are different, in that there is no broader
market for this input beyond medical practices, making the physician labor market distinctive.
Moreover, many physicians are self-employed and have an ownership interest in their
practice, and it is not uncommon for physicians in private practice to have a partial salary for
administrative or clinical responsibilities. Earnings of self-employed physicians, including those
in physician-owned groups, are therefore a combination of payment for their own labor and an
entrepreneurial return on investment in their business (Gillis et al., 1993). There are so many
variations in staffing arrangements in physician practices that physician income may not be
accurately described by a measure that is based solely on the payments that physicians receive
for providing services.
How Should Physician Work Be Geographically Adjusted?
The goal of geographic adjustment is to pay physicians at a level that is equivalent across
geographic areas, given cost of living differences and differences in amenities across geographic
areas. Since the implementation of the PFS and the RBRVS in 1992, there have been differences
of opinion about whether and how to make geographic adjustments to physician work pay-
ments and how much the adjustments should be. Committee members reflected the range of
opinions when the deliberations began, and there was support for full, partial, and no work
adjustment.
A full work adjustment would mean that variations in earnings would reflect the full extent
of differences in cost of living, as attenuated by area amenities. The rationale for a full work
adjustment is that compensation rates in the private sector, including the health care industry,
vary across labor markets. Public sector wage rates for a variety of occupations, ranging from
census workers to highly skilled professionals and managers, also vary geographically. Geo-
graphic variation in wages for nonphysician health care workers is recognized and reflected
in the geographic adjustment of hospital and physician office labor expenses. Furthermore, a
substantial and growing share of physicians (nearly 50 percent of new physicians, according
to the Medical Group Management Association [MGMA] [2010]), are employees who are paid
at locally prevailing salary scales.
A partial physician work adjustment of 25 percent has been in place since the work adjuster
was developed because there was such a wide variation in the earnings data used to calcu-
late the adjustment and policy makers would not support a full adjustment (Zuckerman and
Maxwell, 2004). Committee members supporting a partial adjustment took the position that an
adjustment was needed, but the data used to calculate the adjustment might not adequately
reflect the variation in compensation in different areas. Thus, the appropriate amount for the
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adjustment might be overstated or understated, especially if the market for physician services
was found to differ significantly from the market for other professional services.
There was also some support on the committee for no work adjustment. The argument
against any physician work adjustment is based on the view that physicians providing an
equivalent service for a federal program should receive the same reimbursement regardless of
where they are located; “work is work.” According to this view, Medicare’s work RVU already
takes into account physician work effort, and it takes no more or less effort to provide the same
medical service in different geographic areas (Goertz, 2010).
Given the variety of opinions, the committee turned first to a consideration of economic
theory and discussed the applicability of the labor economics theory of compensating wage
differentials, which addresses the relationship between wage rates and various attributes of a
particular job. The economic argument for adjusting Medicare physician payment across areas
is that, in general, compensation varies inversely with the affordability and desirability of an
area as a place to live and work. Thus, wages will tend to be lower if there is a lower cost of
living and greater availability of amenities. (See Appendix I and the discussion of the theory
of compensating wage differentials in Chapter 2.)
According to this theory, compensation for physician labor, like compensation for other
labor, should reflect the cost of living in an area, along with amenities that might affect wage
compensation, such as the quality of schools and housing, access to recreational facilities, and
professional opportunities. The theory implies that workers will accept lower monetary com-
pensation in return for amenities they value and will require higher compensation in return for
giving up amenities they value (Borjas, 2010; Ehrenberg and Smith, 2009). The theory further
holds that these differences not only reflect the requirements of the local labor market but also
are fair in that workers—especially relatively mobile professionals such as physicians—can move
between areas if they perceive their salaries are misaligned with amenities and costs of living.
The committee recognized that there may be substantial differences in preferences for ameni-
ties among individuals in the labor market. The committee also recognized that preferences for
amenities may differ among persons in professional occupations from those in other occupations
and also may differ between health professionals and those in other professions. The extent
to which such differences exist and are related to differences in compensation by occupation
in general and by profession in particular, however, has not yet been adequately measured.
Another perspective on geographic differences in the cost of providing services was pro-
vided in testimony from clinical practitioners about geographic differences in the requirements
for support services that are not adequately accounted for in the national average RVUs by
CPT code. For example, in rural areas, physicians can be isolated in solo or small practices with
few available professional resources to assist with discharge planning or family counseling.
In these circumstances, primary care providers take on many different roles that may not be
reimbursed (Iowa Medical Society, 2011). Providers in medically underserved urban areas may
also lack necessary supports—translators, for example (Flores, 2005), which increases the time
required to communicate with patients. While the committee acknowledges the potential for
such resource and payment gaps, its position is that payment for these support services is more
appropriately provided through a different targeted mechanism than through a geographic
adjuster focused on variation in input prices. These other issues will be examined further in the
committee’s phase 2 report.
The committee next sought to reconcile its differences by pursuing an evidence-based
approach to determining the level of desired adjustment, and whether it should be no adjust-
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122 GEOGRAPHIC ADJUSTMENT IN MEDICARE PAYMENT
ment, partial, or full adjustment. A study by the Center for Studying Health System Change
(HSC) found that mean physician incomes in metropolitan and nonmetropolitan areas were
not statistically significantly different (Reschovsky and Staiti, 2005).4 However, a finding of no
difference on average does not necessarily mean that there are no important differences among
individual metropolitan and nonmetropolitan areas that should be reflected in Medicare pay-
ments to providers. Another study found that primary care physicians (general practitioners,
family physicians, internists, and pediatricians) in nonmetropolitan areas earned about 5 percent
less than their urban counterparts did, after making similar adjustments to those made in the
HSC study (Weeks and Wallace, 2008). Neither study assessed possible differences among indi-
vidual metropolitan and nonmetropolitan areas. Data for both studies were more than 10 years
old and do not reflect the most recent trends in provider payment. The committee therefore
concluded that new empirical evidence will be needed to confirm the full extent of differences
in compensation across geographic areas.
After extensive discussion, the committee came to agreement that geographic areas vary
in terms of prices of goods and services and desirability in terms of places to live and work,
even if there are individual and professional differences in the ways that desirability is perceived
by health professionals. The committee was also in agreement about addressing in its phase 2
report differences in resource use and the ways that services are provided in medically under-
served areas.
Given the inconclusive empirical evidence on geographic variation in compensation, the
committee concluded that new empirical evidence will be needed to confirm the full extent of
differences in fee-for-service compensation of physicians and other clinicians across geographic
areas. The committee therefore recommended that the work adjustment should be based on a
set of principles involving accuracy, consistency, and transparency, as described in Chapter 1,
and a systematic empirical process to generate new empirical evidence about geographic varia-
tion in compensation.
To generate this new empirical evidence, the committee recommended a multiple regres-
sion model using the incomes of proxy or reference occupations to predict physician incomes
region by region. The approach is based on the logic of compensating wage differentials,
which suggests that anything less than a full cost of living adjustment should be offset by the
region’s desirable amenities. The proposed approach assumes that the preferences for amenities
among the individuals in the proxy occupations—and thus the offsets from a full cost of living
adjustment—are similar to those of physicians. If that were found not to be the case using proxy
data, the statistical model could systematically compare physician salary data from different
sources to improve the model’s explanatory power. The committee’s recommended approach
to testing various statistical models for predicting physician compensation is discussed in more
detail in the following section and in Appendix I.
How Much of the Variation in Physician Work Should Be Adjusted?
When the geographic adjuster for physician work was originally developed, it was based on
nonphysician professional earnings that ranged from 28 percent above the national average, in
Manhattan, New York, to 16 percent below the national average, in rural Missouri (Zuckerman
and Maxwell, 2004). Policy makers concluded that the range appeared too large, and Congress
4 The study used self-reported data on net income from the 2000–2001 HSC Community Tracking Study Physician
Survey, adjusting for hours worked, specialty, practice ownership, and payer mix, factors that also affect physician income.
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required that the physician work GPCI reflect only one-quarter of the variation observed in
professional earnings. This reduced the range to 9 percent above average for Manhattan and
5 percent below average for rural Missouri (Zuckerman and Maxwell, 2004).
Over time, Congress further limited the extent of geographic adjustments to physician work.
In addition to the one-quarter work adjustment, two additional statutory provisions limited
downward adjustments to the work component of physician fees. First, section 1848(e)(1)(G)
of the Social Security Act requires that the state of Alaska receive a permanent 1.5 work GPCI
floor for services furnished beginning January 2009, meaning that physician payment will
remain above the national average of 1.0. Second, a provision in the Medicaid and Medicare
Extension Act of 2010 extended the 1.0 temporary work GPCI floor, enacted in the Medicare
Modernization Act (MMA) through December 31, 2011. These provisions raised Medicare fees
to physicians in low-cost areas and narrowed urban-rural fee differences (GAO, 2005).
The congressional decision to adjust for one-quarter of the variation in physician work was
the result of political compromise rather than empirical evidence. One subsequent study in
the early 1990s found that the one-quarter work adjustment was a better fit than was the full
adjustment or no adjustment in a statistical model relating the work GPCI and physician net
hourly earnings as measured by the AMA’s Socioeconomic Monitoring System survey in 1990
and 1991 (Gillis et al., 1993). After adjustment with the one-quarter work GPCI, physician
earnings still varied, though less so than for the other levels of work adjustment. However, this
study did not attempt to estimate the optimal fraction for the adjustment or assess the proxy
occupations selected, and the committee was reluctant to draw firm conclusions from one study
with data that are now more than 20 years old.
The committee therefore concluded that the one-quarter work adjustment lacks empirical
foundation and sought to develop an alternative using statistical modeling based on multiple
regression, a standard statistical technique that allows testing and modeling of independent or
explanatory variables to predict a dependent or outcome variable. The inputs to the analysis
would be indexes representing the ratio of median compensation for an occupation in each pay-
ment area to the national mean of these median compensation levels, both for physicians and
for the proxy occupations. Preferably, if appropriate data can be found, these income indexes
should be calculated based on employed professionals. The statistical analysis would then be a
linear regression5 to determine which occupations’ earnings best track physician earnings, then
creating an adjustment index based on geographic variation in earnings in the other occupa-
tions. (The analysis is summarized in this section and described in detail in Appendix I.)
After fitting this linear statistical model, there are at least two ways to use the fitted regres-
sion model to calculate the work adjustment. One approach is to calculate an index to represent
the predicted value for physician compensation from the regression model. This resembles the
committee’s approach for nonphysician labor expense in the PE GPCI, but with an important
difference. For nonphysician labor expense, the geographic adjustment is based on the weighted
average hourly wage of health care workers in each geographic area relative to the weighted
average national wage for those same health care workers, where the weights used for the
averaging are national employment for all occupations in all physician offices.
The committee also discussed a second approach to the work adjustment, in which the
relative weights for each of the seven reference (proxy) occupations would be derived from
5 A linear regression model is used to explain the relationship between two or more variables by using a straight
line to plot the strength of the relationship. For example, linear regression can be used to fit a predictive model to an
observed data set of independent and dependent variables.
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TABLE 5-4 Continued
134
U.S. Department American
of Housing Housing Survey Basic Allowance for MGMA
and Urban (U.S. Census General Services Housing U.S. Postal Physician Cost
Development Bureau and Administration (U.S. Department Service Survey for Single-
(HUD) HUD) (GSA) of Defense) (USPS) Specialty Practice REIS, Inc.
Demographics Only collects data Federal Excludes All USPS Nonmetropolitan Metropolitan
on 2-bedroom government “undesirable” properties (<50,000): 21.15% areas
residential buildings only; neighborhoods (leased and
units; excludes does not reflect owned) Metropolitan
new units traditional market (50,000–250,000):
(<2 years old), behavior or 29.29%
units below the all geographic
public housing regions Metropolitan
rent threshold, (250,000–1,000,000):
and units with 32.67%
renters who have
occupied the Metropolitan
unit longer than (>1,000,000):
15 months 16.88%
Sample size 530 metropolitan National: 55,000 All federal 400 military housing 25,300+ 1,871 practices 169 MSAs
areas and 2,045 housing units; government areas (in the United leased total; Reis,
nonmetropolitan Metropolitan: buildings States), defined by properties, Inc. samples
county areas 4,100 units zip code 8,500+ 40% of each
owned region each
properties quarter
Available to Yes, free of Yes, free of Limited data are Yes, free of charge Yes, free of Yes, for a fee: rent
public charge charge available charge as a percentage of
physician operational
expense
NOTE: MGMA = Medical Group Management Association; MSA = metropolitan statistical area.
SOURCES: GSA (2010), HUD (2011a), MGMA Cost Survey for Single-Specialty Practices: 2010 Report on 2009 Data, U.S. Census Bureau (2008), U.S. Department of Defense
(2009), and USPS (2011).
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GEOGRAPHIC PRACTICE COST INDEXES
commercial rental rates for properties larger than 10,000 square feet in metropolitan areas, but
has limited information for nonmetropolitan areas.
Data from MGMA’s Cost Survey for Single-Specialty Practices do reflect physicians’ actual
rental costs. However, the MGMA (2010) cost survey has a low response rate (19.06 percent),
and the 2009 data are limited in sample size (n = 1,871) and representativeness. Specifically,
sample sizes by state appear to be uneven, with 10 states having fewer than 10 observations
each. In addition, as discussed elsewhere in the phase 1 report, the committee preferred an
independent source of data that would accurately reflect input prices faced by providers, not
the costs incurred by providers.
In addition to reviewing the limitations of the individual data sources, the committee also
compared HUD’s data with the REIS, Inc. and USPS data for a select number of metropolitan
areas. The REIS, Inc. and USPS data on commercial rents were expressed in price per square
foot, while HUD’s data were expressed as price per entire residential unit. In order to compare
the data, the committee standardized the different units by converting the data into index
values (see Table 5-5). The analysis shows substantial variation across the three sources, with
HUD data providing higher index values in metropolitan markets in California, but lower values
in other locations, such as Chicago and Raleigh-Durham.
In the CY 2012 PFS proposed rule, CMS proposed replacing HUD data with ACS residential
rent data on the grounds that ACS data provide more detailed geographic information, rely
on more current survey data, and will serve as a more standardized data source in the event
that ACS wage data are adapted to compute the employee wage index and work GPCI (CMS,
2011b). It was estimated that 26 percent of localities would experience a change in their office
rent index that would be greater than 5 percent if ACS data were used (MaCurdy et al., 2011).
The proposal was in response to an Affordable Care Act mandate for CMS to explore using ACS
data for portions of the PE GPCI (CMS, 2011b).
On the basis of its analyses for this study, the committee concluded that all of these sources
had significant limitations. Most of them are not geographically complete, as they do not reflect
market prices in both metropolitan and nonmetropolitan areas. Each source of data also yields
a substantially different wage index, which indicates that they may not be representative of
the market in which physicians rent space. Small sample sizes, low response rates, and sample
biases also led the committee to conclude that these surveys do not accurately represent the
physician population.
A variety of possible alternative sources of data were discussed. The committee favored adding
a question on commercial rent prices to an existing federal survey, but no current survey was
found that would be appropriate. The committee also considered the CMS proposal to mount
a physician cost survey, but found data on costs incurred by providers to be less accurate than
an independent source of data on prices faced by providers in the commercial market. Another
problem with using practice data as a basis for market rent is that many physician practices pay
rent to properties in which they have a partial ownership interest, and additional income produced
through these arrangements may not have been excluded from self-reported data.
The committee also discussed whether the use of residential or commercial rent data would be
more accurate conceptually, given that empirical comparisons of the available sources would
be problematic for a variety of reasons. The committee concluded that the cost of space is not
adequately addressed with residential data only. Therefore, the committee recommends that a
new source of commercial rent data be developed for the PE GPCI.
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136 GEOGRAPHIC ADJUSTMENT IN MEDICARE PAYMENT
TABLE 5-5 Comparison of Rent Data for Selected Markets Using Different Data Sources
REIS, Inc.
“Best “Effective USPS HUD
Metro Area, match” rent”/ Un- median Un- median Un-
Using Reis CBSA sq ft, weighted lease cost/ weighted residential weighted
Description code commercial index sq ft index 2-bdr rent index
Atlanta 12060 $16.67 0.860 $7.69 1.487 $1,502.00 1.024
Austin 12420 $20.46 1.056 $8.16 1.578 $1,395.00 0.951
Baltimore 12580 $18.46 0.953 $2.72 0.526 $1,622.00 1.106
Birmingham 13820 $15.54 0.802 $0.94 0.182 $1,060.00 0.723
Boston 14484 $28.82 1.488 $5.05 0.977 $1,826.00 1.245
Chicago 16974 $20.84 1.076 $5.59 1.081 $1,242.00 0.847
District of Columbia 47894 $41.13 2.123 $3.65 0.706 $1,885.00 1.285
Indianapolis 26900 $13.97 0.721 $4.79 0.926 $1,062.00 0.724
Kansas City 28140 $14.47 0.747 $3.29 0.636 $1,139.00 0.777
Lexington (KY) 30460 $13.22 0.682 $3.88 0.750 $1,023.00 0.698
Little Rock 30780 $12.90 0.666 $1.02 0.197 $1,043.00 0.711
Miami 33124 $4.03 1.240 $3.84 0.743 $1,639.00 1.118
Milwaukee 33340 $13.82 0.713 $2.56 0.495 $1,091.00 0.744
Minneapolis 33460 $16.47 0.850 $5.17 1.000 $1,279.00 0.872
Nashville 34980 $15.50 0.800 $6.26 1.211 $1,123.00 0.766
New Orleans 35380 $14.97 0.773 $8.85 1.711 $1,394.00 0.951
New York 35644 $43.68 2.255 $2.69 0.520 $1,907.00 1.300
Oakland-East Bay 36084 $20.06 1.035 $5.42 1.048 $2,064.00 1.407
Omaha 36540 $13.35 0.689 $4.62 0.893 $1,078.00 0.735
Portland (OR) 38900 $16.85 0.870 $5.03 0.973 $1,385.00 0.944
Raleigh-Durham 39580 $15.73 0.812 $6.87 1.329 $1,165.00 0.794
Salt Lake City 41620 $14.18 0.732 $6.06 1.172 $1,264.00 0.862
San Antonio 41700 $15.47 0.799 $10.52 2.034 $1,193.00 0.814
San Diego 41740 $22.63 1.168 $4.63 0.895 $2,213.00 1.509
San Francisco 41884 $29.41 1.518 $4.69 0.907 $2,715.00 1.851
San Jose 41940 $22.30 1.151 $4.95 0.957 $2,638.00 1.799
Seattle 42644 $23.12 1.193 $6.78 1.311 $1,800.00 1.227
St. Louis 41180 $15.40 0.795 $5.13 0.992 $1,086.00 0.741
Tampa-St. Petersburg 45300 $16.94 0.874 $4.57 0.884 $1,278.00 0.871
Wichita 48620 $10.80 0.557 $9.71 1.878 $883.00 0.602
Unweighted average $19.37 1.000 $5.17 1.000 $1,466.00 1.000
Minimum $10.80 0.557 $0.94 0.182 $883.00 0.602
25th percentile $14.60 0.753 $3.85 0.745 $1,099.00 0.749
Median $16.57 0.855 $4.99 0.965 $1,278.50 0.872
75th percentile $21.94 1.132 $6.21 1.201 $1,759.75 1.200
Maximum $43.68 2.255 $10.52 2.034 $2,715.00 1.851
NOTE: CBSA = core-based statistical area; HUD = U.S. Department of Housing and Urban Development.
SOURCE: RTI Analysis unpublished commercial rental data from REIS, Inc., USPS (2011), and fair market rent data from
HUD (2011b).
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GEOGRAPHIC PRACTICE COST INDEXES
PROFESSIONAL LIABILITY INSURANCE
Physicians purchase professional liability or MP insurance to protect themselves from pos-
sible financial losses due to MP lawsuits. The majority of physicians’ MP insurance policies
provide coverage for $1 million per incident and $3 million per year (GAO, 2003). This is the
standard for comparing costs from place to place.
The MP premiums that physicians pay are likely to vary depending both on their specialties
and on the location of their medical practices (Jena et al., 2011). For example, specialists who
conduct medical interventions that are more likely to result in medical malpractice claims, such
as obstetricians, neurosurgeons, and orthopedic surgeons, pay higher premiums than do pri-
mary care physicians who do more clinical evaluation and management and fewer claim-prone
procedures. MP premiums vary greatly from region to region. In 2010, on average, a general
surgeon practicing in Miami–Dade County, Florida, might have faced an annual premium of
$192,982 for liability insurance, whereas a general surgeon practicing in Nebraska paid $10,928
for the same liability coverage (Lowes, 2010).
The level of physicians’ concerns about the risk of malpractice litigation has been found
to be high across a range of specialties, practice settings, and geographic areas at the state
level, with wide state-to-state variation in the liability environments (Carrier et al., 2010). One
reason for the geographic differences in MP premiums is that states have different tort laws
governing medical malpractice and medical malpractice insurance. Medical liability and medi-
cal malpractice insurance are subject to state laws and regulations. Ultimately, the degree to
which states monitor MP insurance carriers, control premium prices, and interpret liability can
substantially affect MP premiums (Sloan and Chepke, 2008). The concentration of specialists
and claims experience in a given location could also affect premiums. If an area has a high
concentration of specialists with high liability risk, then the insurance carrier may charge them
higher premiums to cover higher anticipated losses.
As described earlier in this chapter, the Omnibus Budget Reconciliation Act of 1989 (OBRA)
(1989) required CMS to establish a Medicare PFS that used GPCIs to measure cost differences in
physician work, practice expenses, and MP insurance and to adjust Medicare fees accordingly.
If geographic differences in MP premiums were not taken into account, physicians working
in areas with higher MP premiums would be subject to an additional practice cost not within
their control (GAO, 2005). The current MP insurance portion of the Medicare payment formula
consists of MP RVUs and the MP GPCIs, as discussed in the next section.
Malpractice GPCI Methodology and Data Collection
As of CY 2011, the MP cost share weight is 3.9 percent, which means that on average across
all procedures, MP costs represent 3.9 percent of the total RVUs. The MP GPCI is based on MP
premium data for 25 physician specialties collected from state insurance commissioners and
private insurers that are averaged for each payment area. When CMS calculates the mean MP
premium for each physician payment area, it is weighted for state- and insurer-specific specialty
mix and adjusted for each insurer’s market share (O’Brien-Strain et al., 2010).
In 2003, the U.S. Congress directed GAO to evaluate the Medicare GPCIs, including the
MP GPCI. The mandated review included an evaluation of the methods used to determine MP
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138 GEOGRAPHIC ADJUSTMENT IN MEDICARE PAYMENT
costs, a review of the increases in MP insurance premiums and the variation of premium costs
across states and physician specialty, and an evaluation of the MP GPCI and its relative weights.9
GAO recommended that CMS collect MP premium data more frequently from all states and
from insurers that account for at least 50 percent of the MP insurance business in a state (GAO,
2005). In addition, GAO advised that CMS should collect data on each insurer’s market share
by physician specialty, so that it could adjust average premiums for differences in specialty mix
(GAO, 2005). GAO also recommended that CMS standardize the procedures used to collect
data from insurers to improve the comparability of premiums within and between payment
areas (GAO, 2005).
In response, CMS increased the number of states from which it was able to collect pre-
mium data from 33 in 2004 to 49 in the 201210 GPCI update (O’Brien-Strain et al., 2010a).
Premium data were also collected from insurance carriers that represented 50 percent of the
market share, or from at least two operating MP insurers per state. In addition, CMS increased
the depth of the MP premium data from 20 specialties in 2009 to 25 specialties in 2012.
The primary sources used to collect market share data were the state departments of insur-
ance; an alternative source was the National Association of Insurance Commissioners’ market
share data. The primary source used to collect premium data was state rate filings, and the
alternative source for filling in any gaps was the 2005 to 2008 Medical Liability Monitor survey.
Conclusion
The MP component of the Medicare PFS has received little specific criticism lately. This may
reflect the small percentage of total RVU cost attributed to MP prices, or the perception that the
adjuster is accurately based on real data on insurance prices that physicians actually face. Given
the very short time frame of this study and the number of other issues under consideration, the
committee determined that it would make no recommendations about potential improvements
to the accuracy of the MP GPCI.
COMMITTEE RECOMMENDATIONS
The committee’s charge is to evaluate the sources of data and methods used to calculate
the GPCIs and to make recommendations about how to improve the accuracy of the geo-
graphic adjusters. In order to validate the use of geographic adjustment for the work and
practice expense GPCIs, the committee in its analyses first sought to confirm the degree of
metropolitan-nonmetropolitan and regional differences in physician compensation and in clini-
cal and administrative staff compensation.
The committee then considered the accuracy of a variety of data sources that had been
used or proposed for use in the GPCIs. The shortcomings of the available data on physician
compensation, staffing patterns, contract labor, and occupational mix for different types of
physician practices made it difficult to conduct thorough quantitative assessments.
The recommendations presented in this chapter relied on many of the same data sources
that were used for analyses presented in other chapters. As indicated in the discussion of the
committee’s principles in Chapter 1, these recommendations are intended to improve the accu-
racy of the GPCIs and also reflect the committee’s preferences for consistency in data sources
9 P.L. 108-173, § 403(c), 117 Stat. 2055, 2277-78.
10 Premium data from Mississippi and Puerto Rico were not collected.
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GEOGRAPHIC PRACTICE COST INDEXES
whenever possible. If the use of new data sources were to change the total payments, CMS
would need to make a budget neutrality adjustment to recalibrate payment levels, as required
by law.
In phase 2 of the study, the committee will consider the role of advanced practitioners in
different employment arrangements in physician practices. These analyses will be subject to
the availability of data and may include simulations and modeling with different types of prac-
titioners and practice settings. The committee will also consider recruitment and retention issues
across areas and review available data on how specialty and geographic location decisions are
made by the workforce, including contract labor. In addition, the committee will review the
impact of previous policy adjustments to address workforce shortages and other strategies to
address access to needed care in medically underserved areas.
Recommendation 5-1: The Geographic Practice Cost Index (GPCI) cost-share
weights for adjusting fee-for-service payments to practitioners should continue to
be national, including the three GPCIs (work, practice expense, and liability insur-
ance) and the categories within the practice expense (office rent and personnel).
Geographic adjustments should be made for the prices of inputs that are purchased and/or
produced locally and that vary from the national average. Inputs that are purchased in a national
market without systematic variation in prices across geographic areas should not be adjusted
geographically. In future Physician Fee Schedule (PFS) updates, the Centers for Medicare and
Medicaid Services (CMS) should take steps to ensure accuracy in distinguishing between national
and local market input prices. The statutory requirement to use the Medicare Economic Index
(MEI) cost- share weights as the source of GPCI cost-share weights is reasonable and should be
continued.
Recommendation 5-2: Proxies should continue to be used to measure geographic
variation in the physician work adjustment, but Centers for Medicare and Medic-
aid Services (CMS) should determine whether the seven proxies currently in use
should be modified.
Geographic variations in the price of physician time can be measured in two ways: by
directly measuring variation in physician income, or by using income data from proxy occu-
pations as indicators of variations in physician income. In keeping with its principles about
accuracy and independence of data sources, the committee prefers an independent source of
data that reflects geographic variation in compensation levels for comparable professions rather
than using physician compensation data that are affected by Medicare’s payment adjustments.
Therefore, the continued use of proxy data for rate-setting to avoid the circularity of using
physician income data is appropriate. However, in keeping with its principles of accuracy, con-
sistency, and transparency of data sources, the committee recommends that CMS empirically
reevaluate the accuracy of the seven proxies it currently employs using the most current Bureau
of Labor Statistics (BLS) Occupational Employment Statistics (OES) data. The statistical process
for this assessment is described in detail in Appendix I.
The committee recognizes that this empirical approach is conceptually challenging because
there is no obvious “gold standard” against which the proxy-based estimates can be judged.
Although the committee does not favor basing the geographic adjuster on actual physician
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140 GEOGRAPHIC ADJUSTMENT IN MEDICARE PAYMENT
incomes in each area, it would be useful to assess the extent to which the proxy-based esti-
mates are related to variation in physician compensation among geographic areas on a national
basis. This process would validate their status as proxies. If the proxy data were not found to
have predictive value for physician compensation, CMS might compare the predictive value of
physician salary data from several different sources, such as the Medical Group Management
Association (MGMA) and the American Community Survey (ACS). A proposed methodology
for such a reevaluation using statistical modeling is discussed in the section on the physician
work adjustment and is described in Recommendation 5-3 and Appendix I.
Recommendation 5-3: The Centers for Medicare and Medicaid Services (CMS)
should consider an alternative method for setting the percentage of the work
adjustment based on a systematic empirical process.
The committee recommends that the work adjustment should be based on a systematic
empirical process that generates new evidence to confirm the extent of differences in compen-
sation across geographic areas. There is clearly a policy precedent for the current one-quarter
adjustment, given that the Geographic Practice Cost Indexes (GPCIs) have been updated six
times since the Physician Fee Schedule (PFS) was implemented, and the “quarter work” adjust-
ment has been in place by law throughout all of the updates. Many will view that precedent
as adequate justification for continuing the same approach.
The committee members did not think there is an adequate conceptual justification for
choosing that level of adjustment. However, based on the available empirical evidence, the
committee was unable to determine a more appropriate level for the adjustment.
The committee therefore advises CMS to test various statistical models using multiple
regression, a versatile technique that allows testing and modeling of multiple independent or
explanatory variables to predict a dependent or outcome variable (see Appendix I for more
detail). Once the necessary data are assembled, CMS has reviewed the data to ensure that they
are credible, and the model is estimated, CMS would determine the empirically derived percent-
age for the work adjustment by using the model that provides maximum explanatory power.
Several alternative data sets could be used for the modeling, each with different strengths,
weaknesses, and predictive power. At a minimum, the wage index data used in the modeling
would have to be adjusted to control for specialty mix, RVUs, and residency training status to
ensure that the variability in wages attributable to these non-geographical factors would not
affect the geographic adjuster based on the models.
While the committee strongly supports an empirical approach to determining the work
adjustment, it also acknowledges that it is impossible to determine in advance how much
predictive power the most appropriate statistical model may attain. If the correlations between
the proxy occupation wages and the physician wages were found to be low or not statistically
significant, for example, that might indicate that the factors determining physician wages are
too distinctive to be adequately captured by this methodology. The committee has considered
the possibility that geographical variations in the market for physician services or in amenities
(including professional amenities) valued by physicians might not parallel the corresponding
variations for other professionals. If that were found to be the case, CMS would need to re-
evaluate the use of the current proxies, as indicated in Recommendation 5-2. For purposes of
modeling (but not rate-setting), CMS might also compare the predictive power of different
sources of provider-generated data, such as Medical Group Management Association (MGMA)
survey data and American Community Survey (ACS) data, when they become available.
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GEOGRAPHIC PRACTICE COST INDEXES
Recommendation 5-4: The practice expense Geographic Practice Cost Index (GPCI)
should be constructed with the full range of occupations employed in physicians’
offices, each with a fixed national weight based on the hours of each occupation
employed in physicians’ offices nationwide.
The committee finds that independent, health-care-specific data from the Bureau of Labor
Statistics (BLS) provide the most conceptually appropriate measure of differences in wages for
health professional labor and clinical and administrative office staff. Although acknowledging
that there are some regional differences in occupational mix of employees in the limited data
available, the committee prefers a consistent set of national weights applied to wage data from
the full range of health sector occupations so that hourly wage comparisons can be made. The
exceptions are those health professionals who bill independently under Medicare Part B, whose
compensation should be captured through the work geographic practice cost index.
The expanded set of occupations will be a better reflection of the current workforce and a
broader range of health professions, which will help to improve accuracy of the adjustment. In
addition, the expansion will anticipate future changes in the workforce brought by changes in the
labor market, including the increasing demand for expertise in the adoption and use of health
information technology. Further study of the mix of occupations by specialties will be valuable
to determine whether geographic differences in approaches to clinical service integration and
care teams should be addressed in future assessments of the geographic adjustment factors.
Recommendation 5-5: The Centers for Medicare and Medicaid Services (CMS) and
the Bureau of Labor Statistics (BLS) should develop a data use agreement allow-
ing BLS to analyze confidential BLS data for CMS.
The committee recommends that the data source for office staff wages should be all health
sector employers’ wages and benefits data from the BLS. Comparable to the analyses and recom-
mendations about the Hospital Wage Index (HWI), the committee concluded that independent
data that reflect market prices faced by providers are more appropriate than provider data
on costs paid, because actual costs also reflect business decisions that are not necessarily an
accurate reflection of input prices. Further, the committee concluded that independent data on
health sector wages would be a closer proxy to physicians’ office staff wages than all-industry
data from BLS.
The committee recognizes that there is a need to increase coverage in areas where cur-
rent data are not made available in public data files by BLS because of the need to protect
confidentiality. Some areas have a very small number of providers; thus, increased sampling to
improve accuracy may not be possible. A data use or other formal agreement between CMS
and BLS would allow additional analyses to be conducted in the interest of improving transpar-
ency. Using all occupations instead of a limited number would be new, but BLS could compute
an index that includes all data, including those data that are suppressed due to confidentiality.
Recommendation 5-6: A new source of data should be developed to determine the
variation in the price of commercial office rent per square foot.
The committee reviewed several available sources of data to determine whether an accurate
alternative is available to replace the U.S. Department of Housing and Urban Development
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142 GEOGRAPHIC ADJUSTMENT IN MEDICARE PAYMENT
(HUD) residential data that are currently used in the practice expense geographic practice
cost index. These included rental data from the American Housing Survey (U.S. Census Bureau
and HUD), the General Services Administration (GSA), The Basic Allowance for Housing (U.S.
Department of Defense [DOD]), the U.S. Postal Service (USPS), the Medical Group Management
Association (MGMA) Physician Cost Survey, and REIS, Inc.
Each of these sources yielded a substantially different index, which indicates that they may
not be representative of the market in which physicians rent space. They also collected and
reported data differently (e.g., monthly rent v. price per square foot), which made comparisons
difficult. Based on the limitations associated with each data source, such as low response rates,
small sample sizes, and sample bias, the committee concluded that all of these sources would
be imperfect or geographically incomplete proxies for variation in physician office rental costs.
Because the committee also concluded that the cost of space is not adequately measured with
residential data, the committee recommends the development of a new data source.
Recommendation 5-7: Nonclinical labor-related expenses currently included under
practice expense (PE) office expenses should be geographically adjusted as part of
the wage component of the PE.
The update for the physician payment rule proposed for comment in July 2011 included
setting several labor-related expenses to a national index. These included occupations in the “All
Other, Labor-Related” category (e.g., security guard and janitor) and the “Other Professional
Expenses” category (e.g., accountants and attorneys). The Centers for Medicare and Medicaid
Services (CMS) proposed to create a new category for contracted/outsourced services for these
labor categories and to create a new purchased services index. Including professional and other
labor expenses in labor categories would promote consistency between labor-related hospital
and physician payment adjustments, and it would also take into account geographic variations
in wages for the services reflected in Bureau of Labor Statistics (BLS) data.
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