United States Government Accountability Office

GAO Report to Congressional Committees

MEDICARE

Focus on Physician 

Practice Patterns Can 

Lead to Greater 

Program Efficiency 

April 2007 

 

GAO-07-307 
What GAO Found

United States Government Accountability Office

Why GAO Did This Study

Highlights

Accountability Integrity Reliability

April 2007

MEDICARE

Focus on Physician Practice Patterns 

Highlights of GAO-07-307, a report to Can Lead to Greater Program Efficiency 

congressional committees 

The Medicare Prescription Drug, 

Improvement, and Modernization 

Act of 2003 (MMA) directed GAO to 

study the compensation of

physicians in traditional fee-for 

service (FFS) Medicare. GAO

explored linking physician 

compensation to efficiency—

defined as providing and ordering a 

level of services that is sufficient to 

meet a patient’s health care needs

but not excessive, given the 

patient’s health status. In this 

report, GAO (1) estimates the 

prevalence in Medicare of 

physicians who are likely to

practice inefficiently, (2) examines 

physician-focused strategies used 

by health care purchasers to 

encourage efficiency, and

(3) examines the potential for CMS

to profile physicians for efficiency

and use the results. To do this, 

GAO developed a methodology 

using 2003 Medicare claims data to 

compare generalist physicians’ 

Medicare practices with those of 

their peers in 12 metropolitan

areas. GAO also examined 10

health care purchasers that profile 

physicians for efficiency. 

What GAO Recommends

Given the contribution of 

physicians to Medicare spending in 

total, GAO recommends that CMS 

develop a system that identifies 

individual physicians with 

inefficient practice patterns and, 

seeking legislative changes as

necessary, uses the results to 

improve the efficiency of care

financed by Medicare. 

Based on 2003 Medicare claims data, GAO’s analysis found outlier generalist 

physicians—physicians who treat a disproportionate share of overly 

expensive patients—in all 12 metropolitan areas studied. Outlier generalists 

and other generalists saw similar numbers of Medicare patients and their 

respective patients averaged the same number of office visits. However, after

taking health status and location into account, GAO found that Medicare 

patients who saw an outlier generalist—compared with those who saw other 

generalists—were more likely to have been hospitalized, more likely to have 

been hospitalized multiple times, and more likely to have used home health 

services. By contrast, they were less likely to have been admitted to a skilled 

nursing facility. 

Certain public and private health care purchasers routinely evaluate 

physicians in their networks using measures of efficiency and other factors. 

The 10 health care purchasers in our study profiled physicians—that is, 

compared physicians’ performance to an efficiency standard to identify 

those who practiced inefficiently. To measure efficiency, the purchasers we

spoke with generally compared actual spending for physicians’ patients to 

the expected spending for those same patients, given their clinical and 

demographic characteristics. Most of the 10 purchasers also evaluated 

physicians on quality. To encourage efficiency, all 10 purchasers linked their 

physician evaluation results to a range of incentives—from steering patients 

toward the most efficient providers to excluding physicians from the 

purchaser’s provider network because of inefficient practice patterns. 

CMS has tools available to evaluate physicians’ practices for efficiency but 

would likely need additional authorities to use results in ways similar to 

other purchasers. CMS has a comprehensive repository of Medicare claims 

data to compute reliable efficiency measures for most physicians serving

Medicare patients and has substantial experience using methods that adjust 

for differences in patients’ health status. However, CMS may not currently 

have the flexibility that other purchasers have to link physician profiling 

results to a range of incentives encouraging efficiency. Implementation of 

other strategies to encourage efficiency would likely require legislation. 

CMS said that our recommendation was timely and that our focus on the 

need for risk adjustment in measuring physician resource use was 

particularly helpful. However, CMS only discussed using profiling results for 

educating physicians. GAO believes that the optimal profiling effort would 

include financial or other incentives to encourage efficiency and would 

measure the effort’s impact on Medicare. GAO concurs with CMS that this 

effort would require adequate funding. 

www.gao.gov/cgi-bin/getrpt?GAO-07-307.

To view the full product, including the scope 

and methodology, click on the link above. 

For more information, contact A. Bruce 

Steinwald at (202) 512-7101 or 

steinwalda@gao.gov. 
Contents 

Letter 1

Results in Brief 5

Background 7

Physicians Who Treated a Disproportionate Share of Overly

Expensive Patients Were Found in Each of 12 Areas Studied 10 

Health Care Purchasers Used Physician Profiling Results to 

Encourage Efficient Medical Practice 13 

CMS Has Tools Available to Profile Physicians for Efficiency, but 

May Need Some Additional Authorities to Use Results in Ways 

Similar to Other Purchasers 17 

Conclusions 21

Recommendation for Executive Action 22 

Agency and Professional Association Comments and Our 

Evaluation 22

Appendix I Methodology for Identifying Physicians with a 

Disproportionate Share of Overly Expensive 

Beneficiaries 26 

Appendix II Health Care Purchaser Program Characteristics 34 

Appendix III Distribution of Physicians by Their Proportion 

of Overly Expensive Beneficiaries by Metropolitan 

Area 37 

Appendix IV Comments from the Centers for Medicare & 

Medicaid Services 44 

Appendix V GAO Contact and Staff Acknowledgments 47 

Page i GAO-07-307 Physician Efficiency in Medicare
Tables 

Table 1: Percentage of Outlier Physicians in 12 Metropolitan Areas, 

2003 12 

Table 2: Proportion of Overly Expensive Beneficiaries and Outlier 

Threshold Value by CBSA 33 

Table 3: Characteristics of Health Care Purchasers’ Physician

Profiling Programs 35 

Figures 

Figure 1: Average Medicare Expenditures, by Quintile, for 

Beneficiaries of Nearly Average Health Status 11 

Figure 2: Distribution of Total Per-Beneficiary Medicare 

Expenditures for Survivors for Risk Categories 1-10 28 

Figure 3: Distribution of Total Per-Beneficiary Medicare 

Expenditures for Survivors for Risk Categories 11-31 29 

Figure 4: Actual and Simulated Distribution of Generalists by their 

Medicare Practice’s Proportion of Overly Expensive 

Beneficiaries in a Hypothetical Metropolitan Area 32 

Figure 5: Percentage of Generalist Physicians by Their Medicare 

Practice’s Proportion of Overly Expensive Beneficiaries—

Albuquerque, N.Mex. 37 

Figure 6: Percentage of Generalist Physicians by Their Medicare 

Practice’s Proportion of Overly Expensive Beneficiaries—

Baton Rouge, La. 38 

Figure 7: Percentage of Generalist Physicians by Their Medicare 

Practice’s Proportion of Overly Expensive Beneficiaries—

Cape Coral, Fla. 38 

Figure 8: Percentage of Generalist Physicians by Their Medicare 

Practice’s Proportion of Overly Expensive Beneficiaries—

Columbus, Ohio 39 

Figure 9: Percentage of Generalist Physicians by Their Medicare 

Practice’s Proportion of Overly Expensive Beneficiaries—

Des Moines, Iowa 39 

Figure 10: Percentage of Generalist Physicians by Their Medicare 

Practice’s Proportion of Overly Expensive Beneficiaries—

Miami, Fla. 40 

Figure 11: Percentage of Generalist Physicians by Their Medicare 

Practice’s Proportion of Overly Expensive Beneficiaries—

Phoenix, Ariz. 40 

Page ii GAO-07-307 Physician Efficiency in Medicare
Figure 12: Percentage of Generalist Physicians by Their Medicare 

Practice’s Proportion of Overly Expensive Beneficiaries—

Pittsburgh, Pa. 41 

Figure 13: Percentage of Generalist Physicians by Their Medicare 

Practice’s Proportion of Overly Expensive Beneficiaries—

Portland, Maine 41 

Figure 14: Percentage of Generalist Physicians by Their Medicare 

Practice’s Proportion of Overly Expensive Beneficiaries—

Riverside, Calif. 42 

Figure 15: Percentage of Generalist Physicians by Their Medicare 

Practice’s Proportion of Overly Expensive Beneficiaries—

Sacramento, Calif. 42 

Figure 16: Percentage of Generalist Physicians by Their Medicare 

Practice’s Proportion of Overly Expensive Beneficiaries—

Springfield, Mass. 43 

Abbreviations 

ACP American College of Physicians 

AMA American Medical Association 

BIPA Medicare, Medicaid, and SCHIP Benefits Improvement 

 and Protection Act of 2000 

CMS Centers for Medicare & Medicaid Services 

FFS fee-for-service 

MMA Medicare Prescription Drug, Improvement, and 

 Modernization Act of 2003 

MedPAC Medicare Payment Advisory Commission 

SGR sustainable growth rate 

This is a work of the U.S. government and is not subject to copyright protection in the 

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Page iii GAO-07-307 Physician Efficiency in Medicare 
United States Government Accountability Office

Washington, DC 20548 

April 30, 2007

Congressional Committees 

In recent years, we and others have reported that the Medicare program is 

unsustainable in its present form.1

 Because of rising health care costs and 

the aging of baby boomers into eligibility for Medicare, future program 

spending is projected to encumber an escalating share of the government’s 

resources.2

 In their 2006 annual report, the Medicare Trustees found that 

Part B assets now are substantially below appropriate levels and that 

Medicare’s Hospital Insurance Trust Fund—which funds the Medicare 

Part A program—will be exhausted in 2018.3

 They concluded that 

Medicare’s financial challenges call for timely and effective action, and 

that reforms must be prompt to allow time for health care providers, 

beneficiaries, and taxpayers to adjust their expectations. Similarly, in 2006

testimony, the Comptroller General noted that dramatic health care reform

would require a long transition period, arguing for acting sooner rather 

than later.4

 1

GAO, Suggested Areas for Oversight for the 110th Congress, GAO-07-235R (Washington

D.C.: Nov. 17, 2006); GAO, 21st Century Challenges: Reexamining the Base of the Federal 

Government, GAO-05-325SP (Washington, D.C.: Feb. 2005); Congressional Budget Office, 

The Long-Term Budget Outlook (Washington D.C.: Dec. 2005); The Wall Street Journal, 

“Greenspan Expresses Concerns On Derivatives, Medicare Costs,” May 19, 2006, p. A7; USA

Today, “Bernanke: Savings situation getting dire,” October 5, 2006, 

http://www.usatoday.com/money/economy/fed/2006-10-04-bernanke-retirementprograms_x.htm (accessed Dec. 13, 2006). 

2

GAO, 21st Century: Addressing Long-Term Fiscal Challenges Must Include a Reexamination of Mandatory Spending, GAO-06-456T (Washington, D.C.: Feb. 15, 2006). 

3

See Boards of Trustees of the Federal Hospital Insurance and Federal Supplementary 

Medical Insurance Trust Funds, 2006 Annual Report of the Boards of Trustees of the 

Federal Hospital Insurance and Federal Supplementary Medical Insurance Trust Funds 

(Washington D.C.: May 1, 2006). Medicare Part A pays for inpatient hospital stays, skilled 

nursing facility care, hospice care, and some home health care. Part B finances physician, 

outpatient hospital, home health care, and other services. 

4

GAO-06-456T. 

Page 1 GAO-07-307 Physician Efficiency in Medicare 
Experts agree that physicians play a central role in the generation of 

health care expenditures in total.5

 Their services are estimated to account

for 20 percent of total health care expenditures, whereas their influence is

estimated to account for up to 90 percent of this spending.6

 For example, 

physicians refer patients to other physicians; they admit patients to 

hospitals, skilled nursing facilities, and hospices; and they order services 

delivered by other health care providers, such as imaging studies, 

laboratory tests, and home health services. 

Based on the centrality of the physician’s role with respect to the 

consumption of health care services, some public and private health care 

purchasers have initiated programs to identify “efficient” physicians and 

encourage patients to obtain care from these physicians. (For the 

purposes of this report, efficiency means providing and ordering a level of

services that is sufficient to meet a patient’s health care needs but not 

excessive, given the patient’s health status.) These purchasers identify 

efficient physicians by examining data obtained from medical claims to 

measure an individual’s performance relative to a benchmark, a method 

known as profiling. Physician profiling activities occur in Medicare today, 

but they focus largely on improper billing practices rather than on efficient 

care delivery. Some policymakers have suggested using a profiling 

approach in Medicare to pay physicians based on their meeting quality and

efficiency performance standards.7

 As a practical matter, such an approach

would be carried out by the Centers for Medicare & Medicaid Services 

(CMS), the agency responsible for administering the Medicare program. 

The Medicare Prescription Drug, Improvement, and Modernization Act of 

2003 (MMA) required us to study aspects of physician compensation, 

pertaining only to physicians serving beneficiaries in traditional fee-for-

 5

GAO, Comptroller General’s Forum on Health Care: Unsustainable Trends Necessitate 

Comprehensive and Fundamental Reforms to Control Spending and Improve Value, 

GAO-04-793SP (Washington D.C.: May 1, 2004); Laura A. Dummit, Medicare Physician

Payments and Spending, National Health Policy Forum, Issue Brief Number 815 

(Washington D.C.: Oct. 9, 2006). 

6

John M. Eisenberg, Doctors’ Decisions and the Cost of Medical Care: The Reasons for 

Doctors’ Practice Patterns and Ways to Change Them, Health Administration Press

Perspectives (Ann Arbor, Mich.: 1986); Gail R. Wilensky and Louis F. Rossiter, “The

Relative Importance of Physician-induced Demand in the Demand for Medical Care,”

Milbank Memorial Fund Quarterly: Health and Society, 61(2): 252-277, spring 1983. 

7

See H.R. 3617, 109th Cong. §2 (2005). 

Page 2 GAO-07-307 Physician Efficiency in Medicare 
service (FFS) Medicare.8,9

 As discussed with the committees of

jurisdiction, this report explores key concepts involved in linking 

assessments of individual physicians’ performance—particularly measures 

of efficiency—to their compensation. Specifically, this report (1) estimates 

the prevalence in Medicare of physicians who are likely to practice 

medicine inefficiently, (2) examines physician-focused strategies used by

public and private sector health care purchasers to encourage efficient 

medical care, and (3) examines the potential for CMS to profile physicians 

in traditional FFS Medicare for efficiency and use the results in ways that 

are similar to other purchasers that encourage efficiency. 

To estimate the prevalence in Medicare of physicians likely to practice 

medicine inefficiently, we developed a profiling methodology using claims 

data for beneficiaries in the traditional FFS program. We considered the 

experience of other purchasers that conduct such analyses and used an 

approach that was feasible and practical for our purposes. We focused our 

analysis on generalists—physicians who described their specialty as 

general practice, internal medicine, or family practice—in 12 metropolitan 

areas.10 We selected areas that were diverse geographically and in terms of 

Medicare spending per beneficiary. Using 2003 Medicare claims data, we 

examined the degree to which a generalist physician treated a large 

proportion of Medicare patients for whom Medicare spending was 

 8

Pub. L. No. 108-173, § 953, 117 Stat. 2066, 2428. With respect to physician compensation, 

the MMA included the requirement under which the current study was done as well as 

several other requirements, which directed us to study the following: the system for 

annually adjusting physicians’ fees and alternatives to this system (Pub. L. No. 108-173, §

953, 117 Stat. 2066, 2427-28), access to physician services by beneficiaries in Medicare’s 

FFS program (Pub. L. No. 108-173, § 604, 117 Stat. 2066, 2301-02), and adjustments in 

physician fees for area differences in physicians’ costs of operating a private medical 

practice (Pub. L. No. 108-173, § 413(c), 117 Stat. 2066, 2277-78). In response, we issued 

three reports: Medicare Physician Payments: Concerns about Spending Target System 

Prompt Interest in Considering Reforms, GAO-05-85 (Washington D.C.: Oct. 8, 2004); 

Medicare Physician Services: Use of Services Increasing Nationwide and Relatively Few

Beneficiaries Report Major Access Problems, GAO-06-704 (Washington D.C.: July 21, 2006); 

and Medicare Physician Fees: Geographic Adjustment Indices Are Valid in Design, but 

Data and Methods Need Refinement, GAO-05-119 (Washington D.C.: Mar. 11, 2005). 

9

In 2005, most Medicare beneficiaries (88 percent) were in traditional Medicare FFS. The 

rest were enrollees in Medicare Advantage plans, which include managed care plans,

private FFS plans, and Medical Savings Account/High Deductible plans. 

10These metropolitan areas included Albuquerque, N.M.; Baton Rouge, La.; Des Moines, 

Iowa; Phoenix, Ariz.; Miami, Fla.; Springfield, Mass.; Cape Coral, Fla.; Riverside, Calif.; 

Pittsburgh, Pa.; Columbus, Ohio; Sacramento, Calif.; and Portland, Maine. 

Page 3 GAO-07-307 Physician Efficiency in Medicare 
unusually high, given their health status.11 To identify such patients, we 

assigned health status scores to all beneficiaries in the 12 areas, using a 

risk adjustment method similar to the one CMS uses to adjust payments 

for Medicare enrollees in managed care plans.12 We grouped these patients 

into 31 cohorts by health status to remove differences in spending 

associated with differences in health status. We then identified within each 

cohort the top 20 percent of beneficiaries ranked by spending for all 

Medicare services and referred to these beneficiaries as “overly expensive” 

compared with others of similar health status. We linked these overly 

expensive patients to the physicians they saw and computed the 

percentage they represented of each physician’s Medicare practice. We 

determined whether a generalist physician had a Medicare practice that, 

relative to the physician’s peers in the same metropolitan area, included a

percentage of overly expensive patients that was higher than would occur 

by chance if these patients were randomly distributed across the area’s 

generalist physicians.13 We identified these physicians as “outliers” relative 

to the practice patterns prevailing in their area and concluded that they 

were likely to practice medicine inefficiently.14 Our results are not 

statistically generalizable beyond the 12 areas we studied. 

We ensured the reliability of the claims data used in this report by 

performing appropriate electronic data checks and by interviewing agency

officials who were knowledgeable about the data. The encounter and cost 

information in the claims data we used are generally considered to be 

reliable, as they are used by the Medicare program as a record of payments 

to health care providers and are closely monitored by both CMS and 

Medicare’s fiscal intermediaries and carriers—contractors that process, 

review, and pay claims for Medicare-covered services. In addition, we 

examined the claims data files for obvious errors, missing values, and 

values outside of expected ranges. We also interviewed experts at CMS 

 11We excluded generalist physicians from our study whose practices did not include a

sufficient number of Medicare patients to ensure the statistical reliability of our analysis. 

12To account for differences in health status, CMS uses a risk adjustment tool that assigns 

Medicare enrollees a health status score based on their diagnoses and demographic 

characteristics. 

13We defined “higher” by setting a threshold percentage of overly expensive patients for 

each area that would be exceeded by no more than 1 percent of generalist physicians if 

overly expensive patients were randomly distributed across all generalist physicians. 

14See appendix I for further discussion of our methodology. 

Page 4 GAO-07-307 Physician Efficiency in Medicare 
who regularly use the claims data for evaluation and analysis. We found 

the claims data were sufficiently reliable for the purpose of our analyses.

To examine physician-focused strategies used by public and private health

care purchasers to encourage efficient medical care, we interviewed 

representatives of 10 health care purchasers,15 including 5 commercial 

health plans, 1 provider network, 1 trust fund jointly managed by 

employers and a union, and 3 government agencies—2 in U.S. states and 1 

in a Canadian province.16 On the basis of discussions with industry experts, 

we selected these plans because their physician profiling programs 

explicitly assess efficiency—unlike many such programs that assess 

quality only. To examine the potential for profiling in Medicare and using 

the results to encourage efficiency, we reviewed CMS program guidelines 

and memoranda, interviewed CMS officials, and analyzed how certain 

components of physician-focused payment strategies would fit with 

structural features of the Medicare program. 

We conducted our work from September 2005 through April 2007 in 

accordance with generally accepted government auditing standards. 

In each of the 12 metropolitan areas studied, we found generalist 

physicians who, relative to their peers in the same area, treated a 

disproportionate share of overly expensive Medicare patients. To identify

such patients while accounting for differences in health status, we 

grouped beneficiaries into 31 health status cohorts and designated, for 

each cohort, the top 20 percent of beneficiaries, ranked by Medicare 

spending, as “overly expensive.” We linked these patients to the physicians 

who saw them and identified the physicians whose Medicare practice 

included a percentage of overly expensive patients that was higher than 

would occur by chance for their area. We concluded that these physicians 

were likely to practice medicine inefficiently. 

Results in Brief 

 15In this report we use the term purchaser to mean health plans as well as agencies that 

manage care purchased from health plans; one of the entities we interviewed is a provider 

network that contracts with several insurance companies to provide care to their enrollees. 

16Aetna, BlueCross BlueShield of Texas, Health Insurance BC (British Columbia, Canada),

Greater Rochester Independent Practice Association, HealthPartners, Massachusetts 

Group Insurance Commission, Minnesota Advantage Health Plan, PacifiCare Health 

Systems, UnitedHealthcare, and the Hotel Employees and Restaurant Employees 

International Union Welfare Fund. 

Page 5 GAO-07-307 Physician Efficiency in Medicare 
Certain public and private health care purchasers routinely evaluate 

physicians in their networks using measures of efficiency and other 

factors. The 10 health care purchasers in our study profiled physicians—

that is, compared physicians’ performance to an efficiency standard to 

identify those who practiced inefficiently. To measure efficiency, the

purchasers we spoke with generally compared actual spending for 

physicians’ patients to the expected spending for those same patients, 

given their clinical and demographic characteristics. Most of the 10 we 

spoke with also evaluated physicians on quality. To encourage efficiency,

all 10 purchasers linked their physician evaluation results to a range of 

incentives—from steering patients toward the most efficient providers to 

excluding physicians from the purchaser’s provider network because of

inefficient practice patterns. 

CMS has tools to profile physicians for efficiency but would likely need 

additional authorities to use results in ways similar to other purchasers. 

CMS has a comprehensive repository of Medicare claims data to compute 

reliable efficiency measures for most physicians serving Medicare patients

and has substantial experience using methods that adjust for differences in 

patients’ health status. However, CMS may not currently have the 

flexibility that other purchasers have to link physician profiling results to a 

range of incentives encouraging efficiency. Although CMS has extensive 

experience in Medicare with physician education efforts, the

implementation of other strategies to encourage efficiency, for example, 

tying fee updates of individual physicians to meeting efficiency standards,

would likely require legislation providing additional authority to the 

agency. 

In our view, physician profiling offers a promising, targeted approach that 

could be one of an array of measures collectively aimed at realigning the

imbalance between Medicare’s outlays and revenues. Given the 

contribution of physicians to Medicare spending in total, we are 

recommending that CMS develop a profiling system that identifies 

individual physicians with inefficient practice patterns and, seeking 

legislative changes as necessary, uses the results to improve the efficiency

of care financed by Medicare. 

CMS said our recommendation was timely and characterized our focus on 

the need for risk adjustment in measuring physician resource use as 

particularly helpful. The agency also noted that nationwide dissemination 

of reports of physician resource use would generate significant recurring 

costs. While our report notes that CMS is familiar with key methodological

tools needed to conduct such an effort, we agree that any such 

Page 6 GAO-07-307 Physician Efficiency in Medicare 
undertaking would need to be adequately funded. The agency was silent 

on a strategy for using profiling results beyond physician education. We 

believe that the optimal profiling effort would include financial or other 

incentives to curb individual physicians’ inefficient practices and would 

measure the effort’s impact on Medicare spending. Both the American 

Medical Association (AMA) and the American College of Physicians (ACP) 

said that quality standards should be the primary focus of a physician 

profiling system. 

Since 1992, physicians in Medicare have been paid under a national fee 

schedule in conjunction with a system of spending targets. Under the 

design of the fee schedule and target system, annual adjustments 

(updates) to physician fees depend, in part, on whether actual spending 

has fallen below or exceeded the target. Fees are permitted to increase at

least as fast as the costs of providing physician services as long as the 

growth in volume and intensity of physician services remains below a 

specified rate—currently, a little more than 2 percent a year. If spending 

associated with volume and intensity grows faster than the specified rate, 

the target system reduces fee increases or causes fees to fall. The target 

system in place today, called the sustainable growth rate (SGR) system, 

was implemented in 1998. This system acts as a blunt instrument in that all 

physicians are subject to the consequences of excess spending—that is, 

downward fee adjustments—that may stem from the excessive use of 

resources by some physicians relative to their peers. 

Background 

Medicare spending on Part B physician services has grown rapidly in 

recent years. From 2000 through 2005, program spending for Part B FFS 

physician services grew at an average annual rate of 9.8 percent, outpacing 

average annual Medicare aggregate spending growth of 8.7 percent for this 

period. Since 2002, actual Medicare spending on physician services has 

exceeded SGR targets, and the SGR system has called for fee cuts to offset 

the excess spending. However, the cuts were overridden by administrative

action or the Congress five times during this period. In a 2004 report on 

the SGR system,17 we found that possible options to modify or eliminate 

the system would increase the growth in cumulative spending over a 

10-year period, usually by double-digit percentages. The difficulty of 

stabilizing physician fees in the face of the need to maintain fiscal 

 17GAO-05-85. 

Page 7 GAO-07-307 Physician Efficiency in Medicare 
discipline has spurred congressional interest in other ways to restrain 

spending growth. 

As concern about the long-term fiscal sustainability of Medicare has 

grown, so has the recognition that some of the spending for services 

provided and ordered by physicians may not be warranted. For example, 

the wide geographic variation in Medicare spending for physician 

services—unrelated to beneficiary health status or outcomes—provides 

evidence that health needs alone do not determine spending. Furthermore, 

several studies have shown that in some instances growth in the number 

of services provided may lead to medical harm.18 Payments under the 

Medicare program, however, generally do not foster individual physician

responsibility for quality, medical efficacy, or efficiency. In recognition of 

this, the Institute of Medicine has recently recommended that Medicare 

payment policies should be reformed to include a system for paying health

care providers differentially based on how well they meet performance 

standards for quality or efficiency or both.19 In April 2005, CMS initiated a 

demonstration mandated by the Medicare, Medicaid, and SCHIP Benefits 

Improvement and Protection Act of 2000 (BIPA) to test this approach.20

Under the Physician Group Practice demonstration, 10 large physician 

group practices, each comprising at least 200 physicians, are eligible for 

bonus payments if they meet quality targets and succeed in keeping the 

total expenditures of their Medicare population below annual targets.21

Several studies have found that Medicare and other purchasers could 

realize substantial savings if a portion of patients switched from less 

efficient to more efficient physicians. The estimates vary according to 

 18Elliott S. Fisher and H. Gilbert Welch, “Avoiding the Unintended Consequences of Growth 

in Medical Care: How Might More Be Worse?” Journal of the American Medical

Association, vol. 281, no. 5 (1999): 446-453; E.S. Fisher, et al., “The Implications of Regional 

Variations in Medicare Spending. Part 1: The Content, Quality, and Accessibility of Care,” 

Annals of Internal Medicine, vol. 138, no. 4 (2003): 273-287; E.S. Fisher, et al., “The 

Implications of Regional Variations in Medicare Spending. Part 2: Health Outcomes and 

Satisfaction with Care,” Annals of Internal Medicine, vol. 138, no. 4 (2003): 288-298; and 

Joseph P. Newhouse, Free for All? Lessons from the RAND Health Insurance Experiment

(Cambridge, Mass.: Harvard University Press, 1993). 

19Institute of Medicine, Rewarding Provider Performance: Aligning Incentives in

Medicare (Pathways to Quality Health Care Series) – Summary (Washington D.C.: 2007). 

20Pub. L. No. 106-554, app. F, § 412(a), 114 Stat. 2763, 2763A–509-515. 

21We are currently conducting a study of the demonstration, as required by BIPA 

(Pub. L. No. 106-554, app. F, § 412(b), 114 Stat. 2763, 2763A–515). 

Page 8 GAO-07-307 Physician Efficiency in Medicare 
assumptions about the proportion of beneficiaries who would change 

physicians.22 In 2003, the Consumer-Purchaser Disclosure Project, a 

partnership of consumer, labor, and purchaser organizations, asked 

actuaries and health researchers to estimate the potential savings to 

Medicare if a small proportion of beneficiaries started using more efficient 

physicians. The Project reported that Medicare could save between 2 and 

4 percent of total costs if 1 out of 10 beneficiaries moved to more efficient 

physicians. This conclusion is based on information received from one 

actuarial firm and two academic researchers. One researcher concluded, 

based on his simulations, that if 5 to 10 percent of Medicare enrollees 

switched to the most efficient physicians, savings would be 1 to 3 percent 

of program costs—which would amount to about $5 billion to $14 billion

in 2007. 

The Congress has also recently expressed interest in approaches to 

constrain the growth of physician spending. The Deficit Reduction Act of 

2005 required the Medicare Payment Advisory Commission (MedPAC) to 

study options for controlling the volume of physicians’ services under 

Medicare. One approach for applying volume controls that the Congress 

directed MedPAC to consider is a payment system that takes into account 

physician outliers.23

 22See Consumer-Purchaser Disclosure Project, More Efficient Physicians: A Path to 

Significant Savings in Health Care (Washington D.C.: July 2003). 

23Medicare Payment Advisory Commission, Report to the Congress: Assessing Alternatives 

to the Sustainable Growth Rate System (Washington, D.C.: Mar. 2007). 

Page 9 GAO-07-307 Physician Efficiency in Medicare 
In each of the 12 metropolitan areas studied, we found physicians who 

treated a disproportionate share of overly expensive patients. Using 2003 

Medicare claims data, we identified overly expensive beneficiaries in the 

12 areas and computed the percentage they represented in each generalist 

physician’s Medicare FFS practice. We then identified outlier generalist

physicians as those with practices that, relative to their peers, had a 

percentage of overly expensive patients that was unlikely to have occurred 

by chance. We concluded that such physicians are likely to practice an 

inefficient style of medicine. The proportion of generalist physicians found 

to be outliers varied across the 12 areas. In two areas, they accounted for 

more than 10 percent of the areas’ generalist physician population.24

We classified beneficiaries as overly expensive if their total Medicare 

expenditures—for services provided by all health providers, not just 

physicians—ranked in the top fifth of their health status cohort for 2003 

claims.25 We developed 31 health status cohorts of beneficiaries based on 

the diagnoses appearing on their Medicare claims and other factors.26

Within each health status cohort, we observed large differences in total 

Medicare spending across beneficiaries. For example, in one cohort of 

beneficiaries whose health status was about average, overly expensive 

beneficiaries—the top fifth ranked by expenditures—had average total 

expenditures of $24,574, as compared with the cohort’s bottom fifth, 

averaging $1,155.27 (See fig. 1.) This variation may reflect differences in the 

number and type of services provided and ordered by these patients’ 

physicians as well as factors not under the physicians’ direct control, such 

as a patient’s response to and compliance with treatment protocols. Overly 

expensive beneficiaries accounted for nearly one-half of total Medicare 

expenditures even though they represented only 20 percent of

beneficiaries in our sample. 

Physicians Who 

Treated a

Disproportionate 

Share of Overly

Expensive Patients 

Were Found in Each 

of 12 Areas Studied 

In Identifying Overly 

Expensive Beneficiaries, 

We Found Significant 

Variation in Medicare 

Spending on Patients with 

Similar Health Status 

 24The population of generalist physicians studied excluded those who had small Medicare 

practices (see app. I). 

25Expenditures identified were for services from inpatient hospital, outpatient, skilled 

nursing facility, physician, hospice, durable medical equipment, and home health providers.

26For decedents, we also took into account the number of months they were enrolled in

Medicare FFS during 2003. For more detail on the development of the cohorts, see 

appendix I.

27See figures 2 and 3 in appendix I for a depiction of beneficiary expenditures at the 20th,

50th, and 80th percentile for each health status cohort. 

Page 10 GAO-07-307 Physician Efficiency in Medicare 
Figure 1: Average Medicare Expenditures, by Quintile, for Beneficiaries of Nearly 

Average Health Status

0

5

10

15

20

25

Average Medicare expenditures (dollars in thousands)

Source: GAO analysis of 2003 Medicare claims and enrollment data.

Expenditure quintile

Highest

quintile

Fourth

quintile

Third

quintile

Second

quintile

Lowest

quintile

Note: Beneficiaries who died during 2003 are excluded in this figure. 

Outlier Physicians Were 

Present in Every 

Metropolitan Area 

Based on 2003 Medicare claims data, our analysis found outlier generalist 

physicians in all 12 metropolitan areas we studied. Our methodology 

assumed that, if overly expensive beneficiaries were distributed randomly 

across generalists, no more than 1 percent of generalists in any area would 

be designated as outliers. Across all areas, the actual percentage of outlier 

generalists ranged from 2 percent to over 20 percent. 

To identify outlier generalist physicians, we compared the percentage of 

overly expensive beneficiaries in each physician’s Medicare practice to a

threshold value—the percentage of overly expensive beneficiaries in a 

physician’s Medicare practice that would be expected to occur less than 1 

Page 11 GAO-07-307 Physician Efficiency in Medicare 
time out of 100 by chance.28 We classified those who exceeded the 

threshold value for their metropolitan area as outliers. That is, all 

physicians had some overly expensive patients in their Medicare practice,

but outlier physicians had a much higher percentage of such patients. 

The Miami area had the highest percentage—almost 21 percent—of outlier 

generalists, followed by the Baton Rouge area at about 11 percent. (See 

table 1.) Across the other areas, the percentage of outliers ranged from 

2 percent to about 6 percent. 

Table 1: Percentage of Outlier Physicians in 12 Metropolitan Areas, 2003 

Metropolitan area Percentage of outlier physicians

Miami, Fla. 20.9

Baton Rouge, La. 11.2

Cape Coral, Fla. 6.3

Portland, Maine 5.8

Riverside, Calif. 5.8

Phoenix, Ariz. 5.2

Sacramento, Calif. 5.2

Des Moines, Iowa 4.8

Columbus, Ohio 4.6

Pittsburgh, Pa. 3.8

Springfield, Mass. 2.9

Albuquerque, N. Mex. 2.0

Source: GAO analysis of 2003 CMS claims and enrollment data. 

Note: Outlier percentages greater than 1 percent indicate that an area has an excessive number of 

outlier physicians. 

In 2003, outlier generalists’ Medicare practices were similar to those of 

other generalists, but the beneficiaries they treated tended to experience

higher utilization of certain services. Outlier generalists and other 

 28In determining the threshold value, we assumed that if all generalists practiced at a

similar level of efficiency, overly expensive beneficiaries would be randomly distributed 

across all generalists, within a geographic area. Under this assumption, in an area such as 

Phoenix, Ariz., where 19 percent of the beneficiaries were overly expensive, one would 

expect that the percentage of overly expensive patients in generalist physicians’ practices 

would cluster around 19 percent. However, no more than 1 percent of generalists would 

have practices in which more than 29 percent of the patients were overly expensive. See

appendix I for further detail on our methodology for calculating threshold values. 

Page 12 GAO-07-307 Physician Efficiency in Medicare 
generalists saw similar average numbers of Medicare patients (219 

compared with 235) and their patients averaged the same number of office 

visits (3.7 compared with 3.5). However, after taking into account 

beneficiary health status and geographic location, we found that 

beneficiaries who saw an outlier generalist, compared with those who saw 

other generalists, were 15 percent more likely to have been hospitalized, 

57 percent more likely to have been hospitalized multiple times, and 

51 percent more likely to have used home health services. By contrast, 

they were 10 percent less likely to have been admitted to a skilled nursing 

facility.29

Consistent with the premise that physicians play a central role in the 

generation of health care expenditures, some health care purchasers use 

physician profiling to promote efficiency. The 10 health care purchasers in 

our study profiled physicians—that is, compared physicians’ performance 

to an efficiency standard to identify those who practiced inefficiently. To

measure efficiency, the purchasers we spoke with generally compared 

actual spending for physicians’ patients to the expected spending for those 

same patients, given their clinical and demographic characteristics. Most 

of the 10 we spoke with also evaluated physicians on quality. The 

purchasers linked their efficiency profiling results and other measures to a 

range of physician-focused strategies to encourage the efficient provision 

of care. 

The 10 health care purchasers we examined used two basic profiling 

approaches to identify physicians whose medical practices were 

inefficient.30 One approach focused on the costs associated with treating a

specific episode of an illness—for example, a stroke or heart attack—and

assessing the physician’s performance based on the resources used during 

that episode. The other approach focused on costs, within a specific time 

period, associated with the patients in a physician’s practice. Both 

approaches shared common features. That is, both used information from 

medical claims data to measure resource use and account for differences

Health Care 

Purchasers Used 

Physician Profiling 

Results to Encourage 

Efficient Medical 

Practice 

Health Care Purchasers in 

Our Study Profiled 

Physicians across Several 

Dimensions to Evaluate 

Physician Performance 

 29These findings were derived from logistic regressions in which health status, geographic 

area, and beneficiary contact with an outlier generalist were the explanatory variables used

to predict whether a beneficiary was hospitalized, used home health services, or was

admitted to a skilled nursing facility. 

30See appendix II for the names and characteristics of these health care purchasers. 

Page 13 GAO-07-307 Physician Efficiency in Medicare 
in patients’ health status. In addition, both approaches assessed physicians

(or physician groups) based on the costs associated with services that they 

may not have provided directly, such as costs associated with a 

hospitalization or services provided by a different physician.

Although the method used by purchasers to estimate expected spending 

for patients varied, all used patient demographics and diagnoses. The 

programs generally computed efficiency measures as the ratio of actual to 

expected spending for patients of similar health status. Ratios greater than

1.0 (indicating that actual equals expected spending) suggest relative 

inefficiency while ratios below 1.0 suggest efficiency, although purchasers 

were free to set their own threshold. For example, one purchaser 

scrutinized physicians with scores above 1.2 for inefficient delivery of

care. Some purchasers also took account of additional information before 

making a final judgment. For example, two purchasers told us that they

reexamined the results for physicians who exceeded the threshold for 

inefficiency to see if there were factors, such as erroneous data, that made

an otherwise efficient provider appear inefficient. 

While our focus was on purchasers who profile for efficiency, purchasers 

in our study included quality measures as part of their profiling programs. 

For example, most purchasers evaluated physicians on one or more 

quality measures, such as whether patients with congestive heart failure 

were prescribed beta blockers. Some purchasers included factors related 

to patient access in their evaluations of physicians, such as whether the 

physician was in a specialty that was underrepresented within the network 

or within a particular geographic area covered by the network. 

Purchasers varied with respect to the types of physicians profiled for 

efficiency. All of the purchasers we interviewed profiled specialists and all 

but one also profiled primary care physicians. Several purchasers said they 

would only profile physicians who treated a minimum number of cases; 

for example, one did not profile psychiatrists because it felt the volume of

data was not sufficient to do statistical profiling. Typically such analyses 

require a minimum sample size to be valid. Purchasers differed on the 

inclusion of physician groups and individual practitioners. Four of the 

purchasers profiled physician group practices exclusively, three profiled 

individual physicians exclusively, and the remaining three profiled both.

To perform their profiling analyses, eight of the purchasers used episodegrouping models, which group claims into clinically distinct episodes of 

care—such as stroke—adjusted for case severity or patient health status. 

This approach can assign one physician primary responsibility for the 

Page 14 GAO-07-307 Physician Efficiency in Medicare 
episode even if the patient sees multiple physicians. Two purchasers used 

a population-based model, which aggregated patient claims data to classify 

a patient’s health status score for patients in the population to estimate 

expected expenditures for the patients a physician treats. 

Health Care Purchasers 

Linked Physician Profiling 

Results to Range of 

Incentives Encouraging 

Efficiency 

The health care purchasers we examined directly tied the results of their 

profiling methods to incentives that encourage physicians to practice 

efficiently. In some cases, purchasers implemented these incentives 

directly, while in other cases, incentives were implemented at the 

discretion of their clients.

31 We found that the incentives varied widely in 

design, application, and severity of consequences—from steering patients 

toward the most efficient providers to excluding a physician from the 

purchaser’s provider network because of inefficient practice patterns. The 

following were commonly reported incentives: 

• Physician education: Some health care purchasers told us that they 

shared their profiling results with physicians to encourage more efficient 

care delivery or to foster acceptance of the purchaser’s physician 

evaluation methods. For example, one purchaser’s profiling report 

compared a physician’s utilization patterns to a benchmark measure 

derived from the practice patterns of the physician’s peer group, such as 

cardiologists compared with other cardiologists in the network or primary 

care physicians compared with other primary care physicians in the 

network. No purchaser employed education as the sole method of 

motivating physicians to change their practice patterns. 

• Publicly designating physicians based on efficiency or quality: Some 

purchasers encouraged enrollees to get their care from certain physicians 

by designating in their physician directories those physicians who met 

quality or quality and efficiency standards. Other purchasers offered 

financial incentives to their enrollees to encourage them to patronize such 

physicians. The incentives may generate higher patient volume for the 

designated physicians, thereby achieving savings for the purchaser or their 

clients. 

• Using tiered arrangements to promote efficiency: Several purchasers 

used profiling results to group physicians in tiers—essentially groups of 

physicians ranked by their level of efficiency. Enrollees selecting 

physicians in the higher tiers compared with those in lower tiers will 

 31Clients can be employers or organizations that contract with the purchasers. 

Page 15 GAO-07-307 Physician Efficiency in Medicare 
obtain financial advantages—such as lower deductibles or copayments. 

From the purchaser’s point of view, tiering has the advantage of affording 

enrollees freedom of choice within the purchaser’s network, while making 

it advantageous for them to seek care from the network’s most efficient 

physicians. Several reported that a portion of their enrollees or employers 

of enrollees responded to the incentives offered by the tiered

arrangements to switch to more efficient physicians. 

• Bonuses and penalties: Two of the purchasers in our study used bonuses 

or financial penalties to encourage efficient medical practices. They 

awarded bonuses to physicians based on their efficiency and quality 

scores. To finance bonuses, one purchaser withholds 10 percent of each 

physician’s total reimbursement amount and with those funds pays 

bonuses to only those physicians who have high quality and efficiency 

scores. The amount withheld from physicians who did not meet standards 

serves as an implicit financial penalty. 

• Network exclusion: One purchaser terminated its contractual relationship 

with physicians in its network when it determined that the physicians 

were practicing inefficiently. In an effort to control costs, the purchaser 

stated that it excluded about 3 percent of the physicians in its network in 

2003. Although the purchaser has not ruled out similar actions in the 

future, it had not excluded additional physicians for reasons of 

inefficiency at the time of our interview. 

Evidence from our interviews with the health care purchasers in our study 

suggests that physician profiling programs may have the potential to 

generate savings for health care purchasers or their clients. Three of the 10

purchasers provided us with estimates of savings attributable to their 

physician-focused efficiency efforts. One placed more efficient physicians 

in a special network and reported that premiums for this network were 

3 to 7 percent lower than premiums for the network that includes the rest 

of its physicians. Another reported that growth in spending fell from 

12 percent to about 1 percent in the first year after it restructured its 

network as part of its efficiency program. By examining the factors that 

contributed to the reduction, an actuarial firm hired by the purchaser 

estimated that about three-quarters of the reduction in expenditure growth 

was most likely a result of the efficiency program. The third purchaser 

reported a “sentinel” effect—the effect of being scrutinized—resulting 

from its physician profiling efforts. This purchaser estimated that the 

sentinel effect associated with its physician efficiency program reduced 

spending by as much as 1 percent. Three other purchasers suggested their 

Physician Profiling 

Suggests Potential for 

Savings 

Page 16 GAO-07-307 Physician Efficiency in Medicare 
programs might have achieved savings for themselves or their clients but 

did not provide us with their savings estimates, while four said they had 

not yet attempted to measure savings at the time of our interviews. 

Medicare’s data-rich environment is conducive to conducting profiling 

analyses designed to identify physicians whose medical practices are 

inefficient compared with their peers. CMS has a comprehensive 

repository of Medicare claims data and experience using key 

methodological tools. However, CMS may not have legislative authority to 

implement some of the incentives used by other health care purchasers to 

encourage efficiency. 

Fundamental to profiling physicians for efficiency is the ability to make 

statistical comparisons that enable health care purchasers to identify 

physicians practicing outside of established norms. CMS has the resources 

to make statistically valid comparisons, including comprehensive medical

claims information, tools to adjust for differences in patient health status, 

and sufficient numbers of physicians in most areas to construct adequate

sample sizes. As with the development of any new system, however, CMS 

would need to make choices about its design and implementation. 

Among the resources available to CMS are the following: 

CMS Has Tools 

Available to Profile 

Physicians for 

Efficiency, but May 

Need Some Additional 

Authorities to Use 

Results in Ways 

Similar to Other 

Purchasers 

Medicare’s Data-Rich 

Environment Is Conducive 

to Profiling for Efficiency 

• Comprehensive source of medical claims information: CMS maintains a 

centralized repository (database) of all Medicare claims that provides a 

comprehensive source of information on patients’ Medicare-covered 

medical encounters. The data are in a uniform format, as Medicare claim 

forms are standardized. In addition, the data are relatively recent: CMS 

states that 90 percent of clean claims are paid within 30 days and new 

information is added to the central database weekly. Using claims from the 

central database, each of which includes the beneficiary’s unique 

identification number, CMS can identify and link patients to the various 

types of services they received—including, for example, hospital, home 

health, and physician services—and to the physicians who treated them. 

Page 17 GAO-07-307 Physician Efficiency in Medicare 
• Data samples large enough to ensure meaningful comparisons across 

physicians: The feasibility of using efficiency measures to compare 

physicians’ performance depends on two factors—the availability of 

enough data on each physician to compute a reliable efficiency measure 

and numbers of physicians large enough to provide meaningful 

comparisons. In 2005, Medicare’s 33.6 million FFS enrollees were served 

by about 618,000 physicians. These figures suggest that CMS has enough 

clinical and expenditure data to compute reliable efficiency measures for 

most physicians billing Medicare. 

• Methods to account for differences in patient health status: Because 

sicker patients are expected to use more health care resources than 

healthier patients, patients’ health status needs to be taken into account to

make meaningful comparisons among physicians. The 10 health care 

purchasers we examined accounted for differences in patients’ health 

status through various risk adjustment methods. Medicare has significant 

experience with risk adjustment. Specifically, CMS has used increasingly

sophisticated risk adjustment methodologies over the past decade to set

payment rates for beneficiaries enrolled in managed care plans.32

To conduct profiling analyses, CMS would likely make methodological

decisions similar to those made by the health care purchasers we 

interviewed. For example, the health care purchasers we spoke with made 

choices about, among other things, whether to profile individual 

physicians or group practices; which risk adjustment tool was best suited 

for the purchaser’s physician and enrollee population; whether to measure 

costs associated with episodes of care or the costs, within a specific time 

period, associated with the patients in a physicians’ practice; and what 

criteria to use to define inefficient practices. 

CMS would also likely want to take steps similar to those of other 

purchasers to supplement its efficiency assessments with additional 

information before using the results to do more than share information 

with physicians. For example, some purchasers in our study reviewed 

their profiling results for physicians who did not meet the efficiency 

standard to validate the accuracy of their assessments. Such validation of

profiling results would be appropriate if CMS were to institute financial 

 32Our estimate of the prevalence of physicians likely to practice inefficiently, discussed 

earlier in this report, relied on a risk adjustment methodology similar to that CMS uses to 

adjust Medicare payments to health plans in Medicare Advantage. 

Page 18 GAO-07-307 Physician Efficiency in Medicare 
incentives for physicians to improve the efficiency of the care they provide 

and order for Medicare beneficiaries. 

Some of the actions health care purchasers take as a result of their 

physician profiling may not be readily adaptable to Medicare, given the 

program’s structural underpinnings, but they may be instructive in 

suggesting future directions for Medicare. Although Medicare has 

extensive experience with physician education efforts, the implementation

of other strategies to encourage efficiency would likely require legislation 

providing authority to the Secretary of Health and Human Services. 

Educational outreach to physicians has been a long-standing and 

widespread activity in Medicare as a means to change physician behavior 

based on profiling efforts to identify improper billing practices and 

potential fraud. Outreach includes letters sent to physicians alerting them 

to billing practices that are inappropriate.33 In some cases, physicians are 

given comparative information on how the physician varies from other 

physicians in the same specialty or locality with respect to use of a certain

service. A physician education effort based on efficiency profiling results 

would therefore not be a foreign concept in Medicare. For example, CMS 

could provide physicians a report that compares their practice’s efficiency

with that of their peers. This would enable physicians to see whether their 

practice style is outside the norm. In its March 2005 report to the 

Congress,34 MedPAC recommended that CMS measure resource use by 

physicians and share the results with them on a confidential basis. 

MedPAC suggested that such an approach would enable CMS to gain 

experience in examining resource use measures and identifying ways to 

refine them while affording physicians the opportunity to change 

inefficient practices.35

To Use Profiling Results in 

Medicare in Ways Similar 

to Other Purchasers Would 

Likely Require Additional 

Authorities 

 33Other forms of physician education include face-to-face meetings, telephone conferences, 

seminars, and workshops. 

34MedPAC, 2005. 

35In several testimonies before the Congress in the last half of 2005, CMS officials said that 

they were taking steps to implement this recommendation. See Value-Based Purchasing for

Physicians Under Medicare: Hearing Before the House Subcommittee on Health, 

Committee on Ways and Means, 109th Cong. (2005) (statement of Mark B. McClellan, MD, 

Ph.D., Administrator of CMS).

Page 19 GAO-07-307 Physician Efficiency in Medicare 
Another application of profiling results used by the purchasers we spoke 

with entailed sharing comparative information with enrollees. CMS has 

considerable experience comparing certain providers on quality measures 

and posting the results to a Web site. Currently, Medicare Web sites 

posting comparative information exist for hospitals, nursing homes, home 

health care agencies, dialysis facilities, and managed care plans. In its 

March 2005 report to the Congress, MedPAC noted that CMS could share

results of physician performance measurement with beneficiaries once the 

agency gained sufficient experience with its physician measurement tools. 

Several structural features of the Medicare program would appear to pose 

challenges to the use of other strategies designed to encourage efficiency.

These features include a beneficiary’s freedom to choose any licensed 

physician permitted to be paid by Medicare; the lack of authority to 

exclude physicians from participating in Medicare unless they engage in

unlawful, abusive, or unprofessional practices; and a physician payment 

system that does not take into account the efficiency of the care provided. 

Under these provisions, CMS would not likely be able—in the absence of 

additional legislative authority—to designate preferred providers,36 assign 

physicians to tiers associated with varying beneficiary copayments, tie fee 

updates of individual physicians to meeting performance standards,37 or 

exclude physicians who do not meet practice efficiency and quality 

criteria. 

Regardless of the use made of physician profiling results, the involvement 

of, and acceptance by, the physician community and other stakeholders of 

any actions taken is critical. Several purchasers described how they had

worked to get physician buy-in. They explained their methods to 

physicians and shared data with them to increase physicians’ familiarity 

with and confidence in the purchasers’ profiling. CMS has several avenues

for obtaining the input of the physician community. Among them is the 

federal rule-making process, which generally provides a comment period 

for all parties affected by prospective policy changes. In addition, CMS 

forms federal advisory committees—including ones composed of 

physicians and other health care practitioners—that regularly provide it 

 36Preferred providers refers to those providers who meet a purchaser’s utilization, price, 

and quality standards. Patients who choose providers who are not preferred are assessed 

higher copayments. 

37Medicare fee updates are annual adjustments made to physicians’ fees. 

Page 20 GAO-07-307 Physician Efficiency in Medicare 
with advice and recommendations concerning regulatory and other policy 

decisions. 

The health care spending levels predicted to overwhelm the Medicare 

program call for action to be taken promptly. To address this looming 

problem, no single action or reform is likely to suffice, and policymakers 

are seeking solutions among an array of reform proposals. Our findings 

suggest that physician profiling is one promising, targeted approach 

toward curbing excessive spending both for physician services and for the

services that physicians order. 

Our profiling of generalist physicians in 12 metropolitan areas found 

indications of inefficient physician practices occurring in areas with low 

spending per beneficiary as well as in areas with high spending. To ensure

that our estimates were fair, we adjusted them to account for the fact that 

some physicians have sicker patients than others; in addition, our 

efficiency standards were based on actual practices by local physicians 

rather than on a single measure applied to all physicians, regardless of 

geographic area. Notably, two areas—Miami and Baton Rouge—had 

particularly large proportions of outlier physicians compared with the 

other areas.

Some health care purchasers seek to curb inefficient practices through 

physician education and other measures directed at physicians’ income—

such as discouraging patients from obtaining care from physicians whom 

the purchaser, through profiling, ranks as inefficient. If similar approaches 

were adopted in Medicare—that is, profiling physicians for efficiency and 

strategically applying the results—the experience of other purchasers 

suggests that reductions in spending growth could be achieved. The 

adoption of a profiling system could require the modification of certain 

basic Medicare principles. For example, if CMS had the authority to rankorder physicians based on efficiency and tier beneficiary copayments 

accordingly, beneficiaries could retain the freedom to choose among 

providers but would be steered, through financial incentives, toward those 

identified as most efficient. CMS would likely find it desirable to base the

tiers on both quality and efficiency. It would also be important to develop 

an evaluation component to measure the profiling system’s impact on 

program spending and physician behavior. 

In addition, a physician profiling system in Medicare could work in ways 

that would be complementary to the SGR system. That is, if Medicare 

instituted a physician profiling system that resulted in gains in efficiency, 

Conclusions 

Page 21 GAO-07-307 Physician Efficiency in Medicare 
over time the rate of growth in volume and intensity of physician services

could decline and the SGR targets would be less likely to be exceeded. At 

the same time, under a profiling system that focused on total program 

expenditures, Medicare could experience a drop in unnecessary utilization 

of other services, such as hospitalizations and home health care. Although

savings from physician profiling alone would clearly not be sufficient to 

correct Medicare’s long-term fiscal imbalance, it could be an important 

part of a package of reforms aimed at future program sustainability. 

Given the contribution of physicians to Medicare spending in total, we 

recommend that the Administrator of CMS develop a profiling system that 

identifies individual physicians with inefficient practice patterns and, 

seeking legislative changes as necessary, use the results to improve the 

efficiency of care financed by Medicare. The profiling system should 

include the following elements: 

• total Medicare expenditures as the basis for measuring efficiency, 

• adjustments for differences in patients’ health status, 

• empirically based standards that set the parameters of efficiency, 

• a physician education program that explains to physicians how the 

profiling system works and how their efficiency measures compare with 

those of their peers, 

• financial or other incentives for individual physicians to improve the 

efficiency of the care they provide, and 

• methods for measuring the impact of physician profiling on program 

spending and physician behavior. 

We obtained written comments on a draft of this report from CMS (see 

app. IV). We obtained oral comments from representatives of the 

American College of Physicians (ACP) and the American Medical 

Association (AMA). 

Recommendation for 

Executive Action 

Agency and 

Professional 

Association 

Comments and Our 

Evaluation 

Page 22 GAO-07-307 Physician Efficiency in Medicare 
CMS stated that our recommendation was very timely and that it fits into 

efforts the agency is pursuing to improve the quality and efficiency of care 

paid for by Medicare. CMS also found our focus on the need for risk 

adjustment in measuring physician resource use to be particularly helpful. 

CMS noted that its current measurement efforts involve evaluation of 

“episode grouper” technology, which examines claims data for a given

episode of care, and called it a promising approach. We do not disagree, 

but we also believe that approaches involving the measurement of total 

patient expenditures are equally promising. 

CMS said that the agency would incur significant recurring costs to 

develop reports on physician resource use, disseminate them to physicians 

nationwide, and evaluate the impact of the program. While our report 

notes that CMS is familiar with key methodological tools needed to 

conduct such an effort, we agree that any such undertaking would need to 

be adequately funded. CMS was silent on a strategy for using profiling 

results beyond physician education. We believe that the optimal profiling 

effort would include financial or other incentives to curb individual 

physicians’ inefficient practices and would measure the effort’s impact on 

Medicare spending. 

AMA and ACP raised three principal concerns about physician profiling: 

the relative importance of quality and efficiency, the adequacy of risk 

adjustment methods, and the ways profiling results would be used. Both 

said that quality standards should be the primary focus of a physician 

profiling system. AMA said including incentives that promote the provision 

of high-quality care might increase costs initially but could reduce costs in 

the long term. Although we agree that quality is an important measure of 

physician performance, given growing concern about Medicare’s fiscal 

sustainability, we believe that a focus on the efficient delivery of care is 

essential. 

With regard to the use of risk adjustment methods in assessing physician

efficiency, both AMA and ACP said that this technique has significant 

shortcomings. For example, AMA said that diagnostic information 

included in the claims data used in risk adjustment may not adequately 

capture differences in patient health status. AMA also said that these data

lack information on other factors that affect health status and spending, 

such as differences in patient compliance with medical advice. ACP 

echoed this concern. We believe that these claims data limitations are not

of sufficient importance to preclude their use for profiling physicians 

treating Medicare patients. As our report notes, risk adjustment methods 

CMS Comments 

Professional Association 

Comments 

Page 23 GAO-07-307 Physician Efficiency in Medicare 
using claims information are now used by many private payers in 

measuring physician resource use. Moreover, Medicare currently uses one 

such risk adjustment method to set payment rates for managed care plans. 

Finally, both AMA and ACP expressed reservations about linking the 

results of profiling to physician reimbursement. The AMA stated that it

was acceptable to use profiling results for the purpose of physician 

education, but an exclusive focus on costs was not. Although all of the 

purchasers we interviewed included physician education in their profiling 

programs, none of them relied on it as the sole means for encouraging 

physicians to practice efficiently. Similarly, we believe that, to restrain the 

growth in Medicare expenditures, a physician profiling system would need 

financial or other incentives to motivate physicians to practice medicine

efficiently.

We are sending a copy of this report to the Administrator of CMS. We will 

also provide copies to others on request. In addition, this report is 

available at no charge on the GAO Web site at http://www.gao.gov. 

If you or your staff have questions about this report, please contact me at

(202) 512-7101 or steinwalda@gao.gov. Contact points for our Offices of 

Congressional Relations and Public Affairs may be found on the last page 

of this report. GAO staff who made key contributions to this report are 

listed in appendix IV. 

A. Bruce Steinwald 

Director, Health Care 

Page 24 GAO-07-307 Physician Efficiency in Medicare 
List of Committees 

The Honorable Max Baucus 

Chairman 

The Honorable Charles E. Grassley 

Ranking Member 

Committee on Finance 

United States Senate 

The Honorable John D. Dingell 

Chairman 

The Honorable Joe L. Barton 

Ranking Member 

Committee on Energy and Commerce 

House of Representatives 

The Honorable Charles B. Rangel 

Chairman 

The Honorable Jim McCrery 

Ranking Member 

Committee on Ways and Means 

House of Representatives 

The Honorable Frank J. Pallone, Jr.

Chairman 

The Honorable Nathan Deal 

Ranking Member 

Subcommittee on Health

Committee on Energy and Commerce 

House of Representatives 

The Honorable Pete Stark 

Chairman 

The Honorable Dave Camp 

Ranking Member 

Subcommittee on Health

Committee on Ways and Means 

House of Representatives 

Page 25 GAO-07-307 Physician Efficiency in Medicare 
Appendix I: Methodology for Identifying 

Physicians with a Disproportionate Share of 

Overly Expensive Beneficiaries 

Page 26 GAO-07-307 Physician Efficiency in Medicare 

Appendix I: Methodology for Identifying 

Physicians with a Disproportionate Share of 

Overly Expensive Beneficiaries 

We developed a methodology to identify physicians whose practices were 

composed of a disproportionate number of overly expensive 

beneficiaries—that is, beneficiaries whose costs rank them in the top 

20 percent when compared to the costs of other beneficiaries with similar 

health status. We focused our analysis on generalists—physicians who 

described their specialty as general practice, internal medicine, or family 

practice—in the following 12 metropolitan areas: Albuquerque, N.M.; 

Baton Rouge, La.; Des Moines, Iowa; Phoenix, Ariz.; Miami, Fla.; 

Springfield, Mass.; Cape Coral, Fla.; Riverside, Calif.; Pittsburgh, Pa.; 

Columbus, Ohio; Sacramento, Calif.; and Portland, Maine.1

 We selected

these metropolitan areas to obtain a sample of physicians that was 

geographically diverse and represented a range in average Medicare 

spending per beneficiary. We assigned physicians to a particular 

metropolitan area based on where the plurality of their Medicare 

expenditures was generated. Our results are not statistically generalizable. 

To conduct our analysis, we obtained 2003 Centers for Medicare & 

Medicaid Services (CMS) data from the following sources: (1) the 

Standard Analytic Files, a repository of Medicare claims information that 

include data on physician/supplier, durable medical equipment, skilled 

nursing, home health, hospice, and hospital inpatient and outpatient 

services and (2) the Denominator File, a database that contains enrollment 

and entitlement status information for all Medicare beneficiaries enrolled 

and/or entitled in a given year. To assess beneficiary health status, we used 

commercially available software developed by DxCG, Inc. This software 

uses beneficiary characteristics—age, sex, and Medicaid status—and 

diagnosis codes included on medical claims to assign each beneficiary a 

single health “risk score”—a summary measure of the beneficiary’s current

health status corresponding to the beneficiary’s expected health care costs 

relative to the costs of the average Medicare beneficiary.2

 We analyzed the

 1

These areas were based on the following Core-Based Statistical Areas (an umbrella term 

for micropolitan and metropolitan statistical areas): Albuquerque, N.M.; Baton Rouge, La.; 

Des Moines, Iowa; Phoenix-Mesa-Scottsdale, Ariz.; Miami-Fort Lauderdale-Miami Beach, 

Fla.; Springfield, Mass.; Cape Coral-Fort Myers, Fla.; Riverside-San Bernardino-Ontario,

Calif.; Pittsburgh, Pa.; Columbus, Ohio; Sacramento–Arden-Arcade–Roseville, Calif.; and

Portland-South Portland-Biddeford, Maine.

2

For example, a beneficiary with a risk score of .5 is expected to have one-half the health 

care costs of the average Medicare beneficiary, whereas a beneficiary with a score of 2 is 

expected to have costs that are twice the national average. CMS uses such measures to 

prospectively set payment rates for managed care plans, known as Medicare Advantage. 
Appendix I: Methodology for Identifying 

Physicians with a Disproportionate Share of 

Overly Expensive Beneficiaries 

Medicare practices of 7,105 physicians who provided services to 1,283,943

beneficiaries. 

Because our method for identifying overly expensive beneficiaries 

requires comparable information on total beneficiary costs, we developed 

a slightly different methodology for two groups of beneficiaries—survivors 

(beneficiaries who did not die in 2003) and decedents (beneficiaries who 

died in 2003). Decedents typically have annualized costs that are much 

higher than survivors3

 but usually have less than 12 months of Medicare 

enrollment in their last year of life. We included survivors in our analysis if 

they had (1) 12 months of Medicare fee-for-service (FFS) enrollment in 

2003 and (2) were not covered by other health insurance for which 

Medicare was determined to be a secondary payer.4

 Decedents were 

included if they were continuously enrolled in Medicare FFS as of January 

2003 and met the second criterion. Beneficiaries included in our analysis 

had at least one office visit with a generalist physician in one of the 

selected metropolitan areas. 

Using DxCG software, we examined the diagnosis codes on survivors’ 

2003 hospital inpatient, outpatient, and physician claims and generated a 

separate health risk score for each beneficiary. The risk scores reflect the 

level of a beneficiary’s relative health status, and in our analysis, ranged 

from .01 (very healthy) to 30.84 (extremely ill). Next, using their risk 

scores, we assigned survivors into 1 of 31 discrete risk categories. The 

categories were ordered in terms of health status from very healthy 

(category 1) to extremely ill (category 31). Finally, we calculated each 

survivor’s total 2003 Medicare costs from all types of providers (hospital 

inpatient, outpatient, physician, durable medical equipment, skilled 

nursing facility, home health, and hospice). We included costs from all 

Medicare claims submitted on survivors’ behalf, including claims from

locations outside the selected metropolitan areas. Within each risk 

category, we ranked survivors by their total costs. Survivors who ranked 

in the top 20 percent of their assigned risk category were designated as 

Method for Identifying 

Overly Expensive 

Beneficiaries 

 3

GAO, Medicare+Choice: Payments Exceed Cost of Fee-for-Service Benefits, Adding 

Billions to Spending, GAO/HEHS-00-161 (Washington D.C.: Aug. 23, 2000). 

4

We excluded beneficiaries for whom Medicare was a secondary payer because we were 

not able to determine their total costs. Such persons, though eligible for Medicare, may

have some of their health care costs covered by employer-sponsored or other private 

insurance. We also excluded beneficiaries who had End Stage Renal Disease. 

Page 27 GAO-07-307 Physician Efficiency in Medicare 
Appendix I: Methodology for Identifying 

Physicians with a Disproportionate Share of 

Overly Expensive Beneficiaries 

overly expensive.5 Figure 2 and figure 3 show the range of costs in the 31 

risk categories for survivors in our sample. 

Figure 2: Distribution of Total Per-Beneficiary Medicare Expenditures for Survivors 

for Risk Categories 1-10 

0

2

4

6

8

10

12

14

80th percentile

Median

20th percentile

1 2 3 4 5 6 7 8 9 10

Medicare expenditures (dollars in thousands)

Risk category

Source: GAO analysis of 2003 Medicare claims.

 5

Our objective was to group together beneficiaries with generally similar health statuses. 

To assess whether our method of assigning beneficiaries to risk categories achieved this 

objective, we ranked beneficiaries within each risk category by their risk score and divided 

them into two equal-sized groups. Despite having slightly lower risk scores, beneficiaries

who were placed in the bottom half group were on average about 1 percent more likely to

be classified as overly expensive than beneficiaries in the top half group. Consequently, 

across all risk categories, beneficiaries had roughly the same chance of being classified as 

overly expensive based on their 2003 expenditures.

Page 28 GAO-07-307 Physician Efficiency in Medicare 
Appendix I: Methodology for Identifying 

Physicians with a Disproportionate Share of 

Overly Expensive Beneficiaries 

Figure 3: Distribution of Total Per-Beneficiary Medicare Expenditures for Survivors 

for Risk Categories 11-31

The methodology we used to identify decedents who were overly 

expensive was identical to that used for survivors, with one exception. 

Before ranking decedents by their total costs, we further divided them 

within each risk category by the number of months they were enrolled in

Medicare FFS during 2003. This was necessary because decedents varied

in the number of months they incurred health care costs. For example, 

decedents who died in October had up to 10 months to incur costs while 

those who died in January had 1 month or less to incur costs. 

The proportion of overly expensive beneficiaries varied across the areas 

we examined. We identified overly expensive beneficiaries within health 

status cohorts that spanned all 12 of the metropolitan areas. As a 

consequence, it was possible that some areas would have proportionately 

more overly expensive beneficiaries than others. For example, the Miami 

Fort Lauderdale-Miami Beach, Fla., Core-Based Statistical Area (CBSA) 

had the highest proportion of overly expensive beneficiaries, .28, and the 

0

50

100

150

200

250

80th percentile

Median

20th percentile

11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31

Medicare expenditures (dollars in thousands)

Risk category

Source: GAO analysis of 2003 Medicare claims.

Page 29 GAO-07-307 Physician Efficiency in Medicare 
Appendix I: Methodology for Identifying 

Physicians with a Disproportionate Share of 

Overly Expensive Beneficiaries 

Des Moines, Iowa, CBSA had the lowest proportion with .13. The 

remaining areas had proportions that ranged from .13 to .21.

For each generalist physician, we determined the proportion of his or her 

Medicare patients that were overly expensive. Physicians’ proportions of 

overly expensive beneficiaries varied substantially both across and within 

metropolitan areas. For example, in Miami, where the overall proportion 

of overly expensive patients was .28, individual physicians’ proportions 

ranged from .08 to .98. Similarly, in Sacramento, the overall proportion 

was .16, with individual physicians’ proportions ranging from .05 to .60. To 

ensure that our estimate of each physician’s proportion of overly 

expensive beneficiaries was statistically reliable, we excluded physicians

with small Medicare practices.6

We classified generalists as outliers if their practice was composed of such

a high proportion of overly expensive beneficiaries that the proportion 

would only be expected to occur by chance no more than 1 time out of 

100. In order to determine this proportion (threshold value) we conducted

separate Monte Carlo simulations for each area.

7

In each simulation, which we repeated 200 times for each metropolitan 

area, we randomly classified each of a generalist’s patients into one of two 

categories—overly expensive or other. The probability of a beneficiary 

being randomly assigned to the overly expensive category was equal to the 

proportion of physician-patient pairings in the metropolitan area in which 

the patient was an overly expensive beneficiary.8

 We then determined the 

Method for Identifying 

Outlier Physicians

 6

Because the composition of a physician’s practice may change during the year—a 

physician may acquire new patients while other patients may die or leave—the proportion 

of overly expensive patients associated with a particular physician can be treated as a 

sample statistic. To ensure reliability of this statistic, we limited our analysis to physicians 

who treated a substantial number of patients. We established a minimum practice size for 

physicians included in our analysis so that we would be 95 percent confident that our 

estimate of the true proportion of a physician’s practice comprised of overly expensive 

patients was accurate within 10 percent. See William G. Cochran, Sampling Techniques

(New York: John Wiley and Sons, 1977), 75-76. Because the precision of our estimate is a 

function of the overall proportion of overly expensive patients within a metropolitan area, 

the minimum sampling size varied across metropolitan areas.

7

Monte Carlo simulation is a statistical technique by which a quantity is calculated 

repeatedly, using randomly selected “what-if” scenarios for each calculation.

8

In the simulations, only the beneficiary’s status, in terms of being overly expensive, was

randomized. The numbers of patients in each generalist’s practice, and the number of 

generalists each patient saw, remained the same in each simulation. 

Page 30 GAO-07-307 Physician Efficiency in Medicare 
Appendix I: Methodology for Identifying 

Physicians with a Disproportionate Share of 

Overly Expensive Beneficiaries 

percentage of generalists for each proportion of overly expensive 

patients.9

 The results generated by each of the 200 simulations were 

averaged to determine an expected percentage of generalists at each 

proportion of overly expensive beneficiaries. We defined the outlier 

threshold value as the point in the expected distribution where only 

1 percent of physicians would have a proportion of overly expensive 

beneficiaries that large or larger. 

To illustrate our method, we present in figure 4 the actual and expected 

distributions of generalists in a hypothetical metropolitan area. The dotted 

line represents the distribution of generalists by their proportion of overly

expensive beneficiaries that would be expected if such patients were 

randomly distributed among generalists. The solid line shows the actual 

distribution of generalists by their proportion of overly expensive patients. 

The vertical line (outlier threshold value) denotes the 99th percentile of 

the expected distribution—.25. That is, by chance, only 1 percent of 

generalists would be expected to have a proportion of overly expensive 

beneficiaries greater than .25. As shown by the area under the solid line 

and to the right of the vertical line, about 11 percent of generalists in this 

hypothetical example had actual proportions of overly expensive 

beneficiaries that exceeded .25—these generalists would be classified as 

outliers in our analysis. 

 9

In determining the distribution of generalists, the proportion of overly expensive 

beneficiaries was rounded to one-half percent intervals.

Page 31 GAO-07-307 Physician Efficiency in Medicare 
Appendix I: Methodology for Identifying 

Physicians with a Disproportionate Share of 

Overly Expensive Beneficiaries 

Figure 4: Actual and Simulated Distribution of Generalists by their Medicare 

Practice’s Proportion of Overly Expensive Beneficiaries in a Hypothetical 

Metropolitan Area 

Table 2 shows that the proportion of overly expensive beneficiaries and 

the outlier threshold value varied across metropolitan areas. In general, 

areas that had higher proportions of overly expensive beneficiaries also 

had higher outlier threshold values. (See table 2.)

0

2

4

6

8

10

12

14

16

Percentage of generalists

Source: GAO analysis.

Proportion of overly expensive beneficiaries in a generalist’s Medicare practice

Actual distribution of generalists

Simulated distribution of generalists—overly expensive beneficiaries are 

randomly distributed across generalists

Outlier threshold: Only 1% of generalists in the simulation have a

proportion of overly expensive beneficiaries that exceeds this value.

Outlier generalists

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Page 32 GAO-07-307 Physician Efficiency in Medicare 
Appendix I: Methodology for Identifying 

Physicians with a Disproportionate Share of 

Overly Expensive Beneficiaries 

Table 2: Proportion of Overly Expensive Beneficiaries and Outlier Threshold Value 

by CBSA 

CBSA 

Proportion of 

overly expensive 

beneficiariesa

Outlier threshold

value

Miami-Fort Lauderdale-Miami Beach, Fla. 0.28 0.43

Riverside-San Bernardino-Ontario, Calif. 0.21 0.31

Cape Coral-Fort Myers, Fla. 0.23 0.30 

Phoenix-Mesa-Scottsdale, Ariz. 0.19 0.29

Baton Rouge, La. 0.19 0.28

Pittsburgh, Pa. 0.16 0.26

Sacramento–Arden-Arcade–Roseville, Calif. 0.16 0.25

Columbus, Ohio 0.16 0.25

Springfield, Mass. 0.17 0.25

Albuquerque, N.Mex. 0.13 0.22

Portland, Maine 0.13 0.22

Des Moines, Iowa 0.13 0.21

Source: GAO analysis of 2003 Medicare claims data.

a

The figures presented in this column reflect the proportion of beneficiaries in each metropolitan area

who were classified as overly expensive. By contrast, the outlier threshold values are based on the 

proportion of physician-beneficiary relationships in a metropolitan area that involved an overly 

expensive beneficiary. Because some beneficiaries saw more than one generalist in 2003, the 

proportion of overly expensive beneficiaries in an area may differ slightly from the proportion of 

doctor-patient relationships involving overly expensive beneficiaries. For example, in the PhoenixMesa-Scottsdale, Ariz., CBSA, where 19 percent of beneficiaries were overly expensive, 20 percent 

of physician-beneficiary relationships involved an overly expensive beneficiary. Overly expensive 

beneficiaries in that CBSA saw slightly more generalists than other beneficiaries and accounted for a 

proportionately larger share of all doctor-patient relationships than their share of the overall 

beneficiary population. 

Page 33 GAO-07-307 Physician Efficiency in Medicare 
Appendix II: Health Care Purchaser Program 

Characteristics

Page 34 GAO-07-307 Physician Efficiency in Medicare 

Appendix II: Health Care Purchaser Program 

Characteristics 

In 2005 and 2006 we interviewed representatives of 10 health care 

purchasers who had implemented a physician profiling program. We also 

conducted some follow-up contacts to ensure the data were current. We 

had at least one purchaser from each major geographic area of the country

as well as one Canadian province. These purchasers represented a mix of

traditional health insurance plans and organizations that arrange care for 

select groups of patients. Five were commercial health plans, three were 

government agencies, one was a provider network that contracts with 

several insurance companies to provide care to their enrollees, and one

was a trust-fund jointly managed by employers and a union. 

Table 2 presents the basic characteristics of each purchaser’s profiling 

program and includes, among other things, (1) the approximate number of 

covered lives and physicians profiled; (2) the year the purchaser began

profiling physicians; (3) whether the purchaser profiled individual or 

group practices or both; (4) whether the purchaser also used quality 

measures, such as adherence to clinical practice guidelines, to evaluate 

physicians; and (5) the unit of resource use employed to measure 

efficiency. The purchasers with the classification of “Episode” used an 

episodic grouper, which links claims into an episode of care that may span

multiple encounters and multiple providers. By adjusting for the severity 

of like illnesses, episode groupers allow purchasers to measure payments 

to a particular physician or physician group relative to their peers. The 

purchasers with the classification “Patient” used a person-based method of

categorizing illness severity. This method allows the purchaser to compare 

actual expenditures relative to an estimate of what was expected to have

been spent given the level of “sickness” of the patients in a particular 

practice. 
Appendix II: Health Care Purchaser Program 

Characteristics

Table 3: Characteristics of Health Care Purchasers’ Physician Profiling Programs 

Purchaser name 

Approximate

number of 

covered lives 

affecteda

Approximate

number of 

physicians 

profiled Locations

Year 

physician

profiling 

began

Type of 

practice 

profiled 

Quality

measures 

used

Unit of 

resource

use 

employed

to measure 

efficiency 

Aetna 500,000b15,000 Multistatec2004 Group Yes Episode

BlueCross BlueShield 

of Texas 

60,000 26,000 Texas 2004 Group and

individual 

Yes Episode

Greater Rochester 

Independent Practice 

Association 

120,000 640 New York 1996 Individual Yes Episode

Health Insurance BC 

(British Columbia, 

Canada) 

4,100,000 8,000 British Columbia 1997 Individual No Patient

HealthPartners 650,000 27,000 Minnesota 1989dGroup Yes Episode

Hotel Employees and 

Restaurant 

Employees 

International Union 

Welfare Fund 

130,000 2,000 Nevada 2000 Group and

individual 

Yes Episode

Massachusetts Group 

Insurance 

Commission 

268,000 19,000 Massachusetts 2004 Individual Yes Episode

Minnesota Advantage 

Health Plan 

115,000 eMinnesota 2002 GroupfNo Patient

PacifiCare Health 

Systemsg

1,500,000h 14,000 California 1993i Group Yes Episode

UnitedHealthcare 10,600,000 80,000 Multistatej2005 Group and 

individual 

Yes Episode

Source: Health care purchasers. 

a

This column describes the total number of patients or plan members who are potentially affected by

the profiling program. In some cases, their exposure may be limited to having access to purchaser 

evaluations of the profiled physicians. 

b

This figure refers to the number of Aetna enrollees in plans that included the Aexcel network. 

c

In 2006, Aetna’s Aexcel network was available in Dallas, Tex.; Jacksonville, Fla.; Seattle, Wash.; 

Atlanta, Ga.; Connecticut; Houston, Tex.; Los Angeles, Calif.; metropolitan Washington, D.C.; 

metropolitan New York, N.Y.; Northern New Jersey; Arizona; Austin, Tex.; Chicago, Ill.; Cleveland, 

Ohio; Columbus, Ohio; Maine; Northern California; Orlando, Fla.; San Antonio, Tex.; South Florida; 

and Tampa, Fla.

d

HealthPartners began profiling at this time for more limited purposes, such as negotiating fee 

schedules, rather than trying to influence physician and patient behavior. 

e

Minnesota Advantage Health Plan had about 50 provider groups at the time of our interview, each of

which may have included physicians and institutional providers together. 

Page 35 GAO-07-307 Physician Efficiency in Medicare 
Appendix II: Health Care Purchaser Program 

Characteristics

f

Minnesota Advantage combined individual practitioners into a single entity for the purposes of

profiling. 

g

When we began our study, PacifiCare Health Systems and UnitedHealthcare were separate 

organizations with their own physician profiling programs. Although PacifiCare Health Systems

merged with UnitedHealth Group, of which UnitedHealthcare is a part, in December 2005, as of 

December 2006, the profiling programs continued to be separate. 

h

This figure represents the number of PacifiCare Health Systems enrollees who have access to some

profiling data. A smaller number of enrollees in select areas have reduced copayments if they

patronize physicians rated as higher quality, lower cost providers. 

i

PacifiCare Health Systems began profiling in 1993; in later years the effort was enhanced to include,

among other measures, indicators of quality, patient safety, and patient satisfaction.

j

UnitedHealthcare profiled physicians in their provider networks in Iowa, Illinois, Indiana, Kansas, 

Kentucky, Michigan, Ohio, Wisconsin, North Carolina, Washington, Florida, Georgia, Louisiana, 

Tennessee, Arizona, Colorado, Texas, Nebraska, Mississippi, and Utah. 

Page 36 GAO-07-307 Physician Efficiency in Medicare 
Appendix III: D

Their Proportio

B

istribution of Physicians by

n of Overly Expensive 

eneficiaries by Metropolitan Area 

Page 37 GAO-07-307 Physician Efficiency in Medicare 

Appendix III: Distribution of Physicians by 

Their Proportion of Overly Expensive 

Beneficiaries by Metropolitan Area 

This appendix displays the distribution of generalist physicians by the 

proportion of overly expensive beneficiaries in their Medicare practice for

each of the 12 metropolitan areas in our study. The vertical line in each 

chart represents the outlier threshold value for that area. If the proportion 

of overly expensive beneficiaries in a physician’s practice exceeded this 

value, then the physician was designated an outlier physician.

Figure 5: Percentage of Generalist Physicians by Their Medicare Practice’s Proportion of Overly Expensive Beneficiaries—

Albuquerque, N.Mex.

0

2

4

6

8

10

12

14

16

Percentage of generalists

Outlier threshold

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Source: GAO analysis of 2003 Medicare claims data.

Proportion of overly expensive beneficiaries in a generalist’s Medicare practice
Appendix III: Distribution of Physicians by

Their Proportion of Overly Expensive 

Beneficiaries by Metropolitan Area 

Figure 6: Percentage of Generalist Physicians by Their Medicare Practice’s Proportion of Overly Expensive Beneficiaries—

Baton Rouge, La. 

0

2

4

6

8

10

12

14

16

Percentage of generalists

Outlier threshold

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Source: GAO analysis of 2003 Medicare claims data.

Proportion of overly expensive beneficiaries in a generalist’s Medicare practice

Figure 7: Percentage of Generalist Physicians by Their Medicare Practice’s Proportion of Overly Expensive Beneficiaries—

Cape Coral, Fla. 

0

2

4

6

8

10

12

14

16

Percentage of generalists

Outlier threshold

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Source: GAO analysis of 2003 Medicare claims data.

Proportion of overly expensive beneficiaries in a generalist’s Medicare practice

Page 38 GAO-07-307 Physician Efficiency in Medicare 
Appendix III: Distribution of Physicians by

Their Proportion of Overly Expensive 

Beneficiaries by Metropolitan Area 

Figure 8: Percentage of Generalist Physicians by Their Medicare Practice’s Proportion of Overly Expensive Beneficiaries—

Columbus, Ohio 

0

2

4

6

8

10

12

14

16

Percentage of generalists

Outlier threshold

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Source: GAO analysis of 2003 Medicare claims data.

Proportion of overly expensive beneficiaries in a generalist’s Medicare practice

Figure 9: Percentage of Generalist Physicians by Their Medicare Practice’s Proportion of Overly Expensive Beneficiaries—

Des Moines, Iowa

0

2

4

6

8

10

12

14

16

Percentage of generalists

Outlier threshold

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Source: GAO analysis of 2003 Medicare claims data.

Proportion of overly expensive beneficiaries in a generalist’s Medicare practice

Page 39 GAO-07-307 Physician Efficiency in Medicare 
Appendix III: Distribution of Physicians by

Their Proportion of Overly Expensive 

Beneficiaries by Metropolitan Area 

Figure 10: Percentage of Generalist Physicians by Their Medicare Practice’s Proportion of Overly Expensive Beneficiaries—

Miami, Fla. 

0

2

4

6

8

10

12

14

16

Percentage of generalists

Outlier threshold

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Source: GAO analysis of 2003 Medicare claims data.

Proportion of overly expensive beneficiaries in a generalist’s Medicare practice

Figure 11: Percentage of Generalist Physicians by Their Medicare Practice’s Proportion of Overly Expensive Beneficiaries—

Phoenix, Ariz.

0

2

4

6

8

10

12

14

16

Percentage of generalists

Outlier threshold

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Source: GAO analysis of 2003 Medicare claims data.

Proportion of overly expensive beneficiaries in a generalist’s Medicare practice

Page 40 GAO-07-307 Physician Efficiency in Medicare 
Appendix III: Distribution of Physicians by

Their Proportion of Overly Expensive 

Beneficiaries by Metropolitan Area 

Figure 12: Percentage of Generalist Physicians by Their Medicare Practice’s Proportion of Overly Expensive Beneficiaries—

Pittsburgh, Pa. 

0

2

4

6

8

10

12

14

16

Percentage of generalists

Outlier threshold

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Source: GAO analysis of 2003 Medicare claims data.

Proportion of overly expensive beneficiaries in a generalist’s Medicare practice

Figure 13: Percentage of Generalist Physicians by Their Medicare Practice’s Proportion of Overly Expensive Beneficiaries—

Portland, Maine 

0

2

4

6

8

10

12

14

16

Percentage of generalists

Outlier threshold

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Source: GAO analysis of 2003 Medicare claims data.

Proportion of overly expensive beneficiaries in a generalist’s Medicare practice

Page 41 GAO-07-307 Physician Efficiency in Medicare 
Appendix III: Distribution of Physicians by

Their Proportion of Overly Expensive 

Beneficiaries by Metropolitan Area 

Figure 14: Percentage of Generalist Physicians by Their Medicare Practice’s Proportion of Overly Expensive Beneficiaries—

Riverside, Calif. 

0

2

4

6

8

10

12

14

16

Percentage of generalists

Outlier threshold

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Source: GAO analysis of 2003 Medicare claims data.

Proportion of overly expensive beneficiaries in a generalist’s Medicare practice

Figure 15: Percentage of Generalist Physicians by Their Medicare Practice’s Proportion of Overly Expensive Beneficiaries—

Sacramento, Calif. 

0

2

4

6

8

10

12

14

16

Percentage of generalists

Outlier threshold

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Source: GAO analysis of 2003 Medicare claims data.

Proportion of overly expensive beneficiaries in a generalist’s Medicare practice

Page 42 GAO-07-307 Physician Efficiency in Medicare 
Appendix III: Distribution of Physicians by

Their Proportion of Overly Expensive 

Beneficiaries by Metropolitan Area 

Figure 16: Percentage of Generalist Physicians by Their Medicare Practice’s Proportion of Overly Expensive Beneficiaries—

Springfield, Mass. 

0

2

4

6

8

10

12

14

16

Percentage of generalists

Outlier threshold

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Source: GAO analysis of 2003 Medicare claims data.

Proportion of overly expensive beneficiaries in a generalist’s Medicare practice

Page 43 GAO-07-307 Physician Efficiency in Medicare 
Appendix IV: Comments from the Centers for 

Medicare & Medicaid Services 

Page 44 GAO-07-307 Physician Efficiency in Medicare 

Appendix IV: Comments from the Centers for 

Medicare & Medicaid Services 
Appendix IV: Comments from the Centers for 

Medicare & Medicaid Services 

Page 45 GAO-07-307 Physician Efficiency in Medicare 
Appendix IV: Comments from the Centers for 

Medicare & Medicaid Services 

Page 46 GAO-07-307 Physician Efficiency in Medicare 
Appendix V: 

St

GAO Contact and 

aff Acknowledgments

Page 47 GAO-07-307 Physician Efficiency in Medicare 

Appendix V: GAO Contact and Staff 

Acknowledgments 

GAO Contact A. Bruce Steinwald, (202) 512-7101 or steinwalda@gao.gov

In addition to the contact above, James Cosgrove and Phyllis Thorburn, 

Assistant Directors, and Todd Anderson, Hannah Fein, Gregory Giusto, 

Richard Lipinski, and Eric Wedum made key contributions to this report. 

Acknowledgments 

(290413) 
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