Medicare
Focus on Physician Practice Patterns Can Lead to Greater Program Efficiency Gao ID: GAO-07-307 April 30, 2007The 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 the Centers for Medicare and Medicaid Services (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.
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.
RecommendationsOur recommendations from this work are listed below with a Contact for more information. Status will change from "In process" to "Open," "Closed - implemented," or "Closed - not implemented" based on our follow up work.
Director: Team: Phone:GAO-07-307, Medicare: Focus on Physician Practice Patterns Can Lead to Greater Program Efficiency
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Report to Congressional Committees:
United States Government Accountability Office:
GAO:
April 2007:
Medicare:
Focus on Physician Practice Patterns Can Lead to Greater Program
Efficiency:
GAO-07-307:
GAO Highlights:
Highlights of GAO-07-307, a report to congressional committees
Why GAO Did This Study:
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 Found:
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.
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.
[Hyperlink, http://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.
[End of section]
Contents:
Letter:
Results in Brief:
Background:
Physicians Who Treated a Disproportionate Share of Overly Expensive
Patients Were Found in Each of 12 Areas Studied:
Health Care Purchasers Used Physician Profiling Results to Encourage
Efficient Medical Practice:
CMS Has Tools Available to Profile Physicians for Efficiency, but May
Need Some Additional Authorities to Use Results in Ways Similar to
Other Purchasers:
Conclusions:
Recommendation for Executive Action:
Agency and Professional Association Comments and Our Evaluation:
Appendix I: Methodology for Identifying Physicians with a
Disproportionate Share of Overly Expensive Beneficiaries:
Appendix II: Health Care Purchaser Program Characteristics:
Appendix III: Distribution of Physicians by Their Proportion of Overly
Expensive Beneficiaries by Metropolitan Area:
Appendix IV: Comments from the Centers for Medicare & Medicaid
Services:
Appendix V: GAO Contact and Staff Acknowledgments:
Tables:
Table 1: Percentage of Outlier Physicians in 12 Metropolitan Areas,
2003:
Table 2: Proportion of Overly Expensive Beneficiaries and Outlier
Threshold Value by CBSA:
Table 3: Characteristics of Health Care Purchasers' Physician Profiling
Programs:
Figures:
Figure 1: Average Medicare Expenditures, by Quintile, for Beneficiaries
of Nearly Average Health Status:
Figure 2: Distribution of Total Per-Beneficiary Medicare Expenditures
for Survivors for Risk Categories 1-10:
Figure 3: Distribution of Total Per-Beneficiary Medicare Expenditures
for Survivors for Risk Categories 11-31:
Figure 4: Actual and Simulated Distribution of Generalists by their
Medicare Practice's Proportion of Overly Expensive Beneficiaries in a
Hypothetical Metropolitan Area:
Figure 5: Percentage of Generalist Physicians by Their Medicare
Practice's Proportion of Overly Expensive Beneficiaries--Albuquerque,
N.Mex.
Figure 6: Percentage of Generalist Physicians by Their Medicare
Practice's Proportion of Overly Expensive Beneficiaries--Baton Rouge,
La.
Figure 7: Percentage of Generalist Physicians by Their Medicare
Practice's Proportion of Overly Expensive Beneficiaries--Cape Coral,
Fla.
Figure 8: Percentage of Generalist Physicians by Their Medicare
Practice's Proportion of Overly Expensive Beneficiaries--Columbus,
Ohio:
Figure 9: Percentage of Generalist Physicians by Their Medicare
Practice's Proportion of Overly Expensive Beneficiaries--Des Moines,
Iowa:
Figure 10: Percentage of Generalist Physicians by Their Medicare
Practice's Proportion of Overly Expensive Beneficiaries--Miami, Fla.
Figure 11: Percentage of Generalist Physicians by Their Medicare
Practice's Proportion of Overly Expensive Beneficiaries--Phoenix, Ariz.
Figure 12: Percentage of Generalist Physicians by Their Medicare
Practice's Proportion of Overly Expensive Beneficiaries--Pittsburgh,
Pa.
Figure 13: Percentage of Generalist Physicians by Their Medicare
Practice's Proportion of Overly Expensive Beneficiaries--Portland,
Maine:
Figure 14: Percentage of Generalist Physicians by Their Medicare
Practice's Proportion of Overly Expensive Beneficiaries--Riverside,
Calif.
Figure 15: Percentage of Generalist Physicians by Their Medicare
Practice's Proportion of Overly Expensive Beneficiaries--Sacramento,
Calif.
Figure 16: Percentage of Generalist Physicians by Their Medicare
Practice's Proportion of Overly Expensive Beneficiaries--Springfield,
Mass.
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:
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.[Footnote 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.[Footnote 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.[Footnote 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.[Footnote 4]
Experts agree that physicians play a central role in the generation of
health care expenditures in total.[Footnote 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.[Footnote 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.[Footnote 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-service (FFS) Medicare.[Footnote 8],[Footnote 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.[Footnote 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 unusually high,
given their health status.[Footnote 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.[Footnote 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.[Footnote 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.[Footnote 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 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,[Footnote 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.[Footnote 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.
Results in Brief:
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.
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 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.
Background:
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.
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,[Footnote 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 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.[Footnote
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.[Footnote 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.[Footnote 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.[Footnote 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
assumptions about the proportion of beneficiaries who would change
physicians.[Footnote 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.[Footnote 23]
Physicians Who Treated a Disproportionate Share of Overly Expensive
Patients Were Found in Each of 12 Areas Studied:
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.[Footnote 24]
In Identifying Overly Expensive Beneficiaries, We Found Significant
Variation in Medicare Spending on Patients with Similar Health Status:
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.[Footnote 25] We developed 31 health status cohorts of
beneficiaries based on the diagnoses appearing on their Medicare claims
and other factors.[Footnote 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.[Footnote 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.
Figure 1: Average Medicare Expenditures, by Quintile, for Beneficiaries
of Nearly Average Health Status:
[See PDF for image]
Source: GAO analysis of 2003 Medicare claims and enrollment data.
Note: Beneficiaries who died during 2003 are excluded in this figure.
[End of 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 time out of 100 by chance.[Footnote 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: Miami, Fla;
Percentage of outlier physicians: 20.9.
Metropolitan area: Baton Rouge, La;
Percentage of outlier physicians: 11.2.
Metropolitan area: Cape Coral, Fla;
Percentage of outlier physicians: 6.3.
Metropolitan area: Portland, Maine;
Percentage of outlier physicians: 5.8.
Metropolitan area: Riverside, Calif;
Percentage of outlier physicians: 5.8.
Metropolitan area: Phoenix, Ariz;
Percentage of outlier physicians: 5.2.
Metropolitan area: Sacramento, Calif;
Percentage of outlier physicians: 5.2.
Metropolitan area: Des Moines, Iowa;
Percentage of outlier physicians: 4.8.
Metropolitan area: Columbus, Ohio;
Percentage of outlier physicians: 4.6.
Metropolitan area: Pittsburgh, Pa;
Percentage of outlier physicians: 3.8.
Metropolitan area: Springfield, Mass;
Percentage of outlier physicians: 2.9.
Metropolitan area: Albuquerque, N. Mex;
Percentage of outlier physicians: 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.
[End of table]
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 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.[Footnote 29]
Health Care Purchasers Used Physician Profiling Results to Encourage
Efficient Medical Practice:
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.
Health Care Purchasers in Our Study Profiled Physicians across Several
Dimensions to Evaluate Physician Performance:
The 10 health care purchasers we examined used two basic profiling
approaches to identify physicians whose medical practices were
inefficient.[Footnote 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 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
episode-grouping 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 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.[Footnote 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
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.
Physician Profiling Suggests Potential for Savings:
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 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.
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 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.
Medicare's Data-Rich Environment Is Conducive to Profiling for
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:
* 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.
* 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.[Footnote 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 incentives for physicians to improve the efficiency of the
care they provide and order for Medicare beneficiaries.
To Use Profiling Results in Medicare in Ways Similar to Other
Purchasers Would Likely Require Additional Authorities:
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.[Footnote 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,[Footnote 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.[Footnote 35]
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,[Footnote 36] assign physicians to tiers associated
with varying beneficiary copayments, tie fee updates of individual
physicians to meeting performance standards,[Footnote 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 with advice and
recommendations concerning regulatory and other policy decisions.
Conclusions:
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 rank-order 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, 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.
Recommendation for Executive Action:
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.
Agency and Professional Association Comments and Our Evaluation:
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).
CMS Comments:
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.
Professional Association Comments:
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 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.
Signed by:
A. Bruce Steinwald:
Director, Health Care:
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:
[End of section]
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.[Footnote 38] 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.[Footnote 39] We
analyzed the Medicare practices of 7,105 physicians who provided
services to 1,283,943 beneficiaries.
Method for Identifying Overly Expensive 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 survivors[Footnote 40] 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.[Footnote 41] 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 overly expensive.[Footnote
42] 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:
[See PDF for image]
Source: GAo analysis of 2003 Medicare claims.
[End of figure]
Figure 3: Distribution of Total Per-Beneficiary Medicare Expenditures
for Survivors for Risk Categories 11-31:
[See PDF for image]
Source: GAO analysis of 2003 Medicare claims.
[End of figure]
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 Des Moines, Iowa, CBSA had the lowest
proportion with .13. The remaining areas had proportions that ranged
from .13 to .21.
Method for Identifying Outlier Physicians:
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.[Footnote 43]
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.[Footnote 44]
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.[Footnote 45] We then determined the percentage of
generalists for each proportion of overly expensive patients.[Footnote
46] 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.
Figure 4: Actual and Simulated Distribution of Generalists by their
Medicare Practice's Proportion of Overly Expensive Beneficiaries in a
Hypothetical Metropolitan Area:
[See PDF for image]
Source: GAO analysis.
[End of figure]
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.)
Table 2: Proportion of Overly Expensive Beneficiaries and Outlier
Threshold Value by CBSA:
CBSA: Miami-Fort Lauderdale-Miami Beach, Fla;
Proportion of overly expensive beneficiaries[A]: 0.28;
Outlier threshold value: 0.43.
CBSA: Riverside-San Bernardino-Ontario, Calif;
Proportion of overly expensive beneficiaries[A]: 0.21;
Outlier threshold value: 0.31.
CBSA: Cape Coral-Fort Myers, Fla;
Proportion of overly expensive beneficiaries[A]: 0.23;
Outlier threshold value: 0.30.
CBSA: Phoenix-Mesa-Scottsdale, Ariz;
Proportion of overly expensive beneficiaries[A]: 0.19;
Outlier threshold value: 0.29.
CBSA: Baton Rouge, La;
Proportion of overly expensive beneficiaries[A]: 0.19;
Outlier threshold value: 0.28.
CBSA: Pittsburgh, Pa;
Proportion of overly expensive beneficiaries[A]: 0.16;
Outlier threshold value: 0.26.
CBSA: Sacramento-Arden-Arcade-Roseville, Calif;
Proportion of overly expensive beneficiaries[A]: 0.16;
Outlier threshold value: 0.25.
CBSA: Columbus, Ohio;
Proportion of overly expensive beneficiaries[A]: 0.16;
Outlier threshold value: 0.25.
CBSA: Springfield, Mass;
Proportion of overly expensive beneficiaries[A]: 0.17;
Outlier threshold value: 0.25.
CBSA: Albuquerque, N.Mex;
Proportion of overly expensive beneficiaries[A]: 0.13;
Outlier threshold value: 0.22.
CBSA: Portland, Maine;
Proportion of overly expensive beneficiaries[A]: 0.13;
Outlier threshold value: 0.22.
CBSA: Des Moines, Iowa;
Proportion of overly expensive beneficiaries[A]: 0.13;
Outlier threshold value: 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 Phoenix-Mesa-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.
[End of table]
[End of section]
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.
Table 3: Characteristics of Health Care Purchasers' Physician Profiling
Programs:
Purchaser name: Aetna;
Approximate number of covered lives affected[A]: 500,000[B];
Approximate number of physicians profiled: 15,000;
Locations: Multistate[C];
Year physician profiling began: 2004;
Type of practice profiled: Group;
Quality measures used: Yes;
Unit of resource use employed to measure efficiency: Episode.
Purchaser name: BlueCross BlueShield of Texas;
Approximate number of covered lives affected[A]: 60,000;
Approximate number of physicians profiled: 26,000;
Locations: Texas;
Year physician profiling began: 2004;
Type of practice profiled: Group and individual;
Quality measures used: Yes;
Unit of resource use employed to measure efficiency: Episode.
Purchaser name: Greater Rochester Independent Practice Association;
Approximate number of covered lives affected[A]: 120,000;
Approximate number of physicians profiled: 640;
Locations: New York;
Year physician profiling began: 1996;
Type of practice profiled: Individual;
Quality measures used: Yes;
Unit of resource use employed to measure efficiency: Episode.
Purchaser name: Health Insurance BC (British Columbia, Canada);
Approximate number of covered lives affected[A]: 4,100,000;
Approximate number of physicians profiled: 8,000;
Locations: British Columbia;
Year physician profiling began: 1997;
Type of practice profiled: Individual;
Quality measures used: No;
Unit of resource use employed to measure efficiency: Patient.
Purchaser name: HealthPartners;
Approximate number of covered lives affected[A]: 650,000;
Approximate number of physicians profiled: 27,000;
Locations: Minnesota;
Year physician profiling began: 1989[D];
Type of practice profiled: Group;
Quality measures used: Yes;
Unit of resource use employed to measure efficiency: Episode.
Purchaser name: Hotel Employees and Restaurant Employees International
Union Welfare Fund;
Approximate number of covered lives affected[A]: 130,000;
Approximate number of physicians profiled: 2,000;
Locations: Nevada;
Year physician profiling began: 2000;
Type of practice profiled: Group and individual;
Quality measures used: Yes;
Unit of resource use employed to measure efficiency: Episode.
Purchaser name: Massachusetts Group Insurance Commission;
Approximate number of covered lives affected[A]: 268,000;
Approximate number of physicians profiled: 19,000;
Locations: Massachusetts;
Year physician profiling began: 2004;
Type of practice profiled: Individual;
Quality measures used: Yes;
Unit of resource use employed to measure efficiency: Episode.
Purchaser name: Minnesota Advantage Health Plan;
Approximate number of covered lives affected[A]: 115,000;
Approximate number of physicians profiled: [E];
Locations: Minnesota;
Year physician profiling began: 2002;
Type of practice profiled: Group[F];
Quality measures used: No;
Unit of resource use employed to measure efficiency: Patient.
Purchaser name: PacifiCare Health Systems[G];
Approximate number of covered lives affected[A]: 1,500,000[H];
Approximate number of physicians profiled: 14,000;
Locations: California; Year physician profiling began: 1993[I];
Type of practice profiled: Group;
Quality measures used: Yes;
Unit of resource use employed to measure efficiency: Episode.
Purchaser name: UnitedHealthcare;
Approximate number of covered lives affected[A]: 10,600,000;
Approximate number of physicians profiled: 80,000;
Locations: Multistate[J]; Year physician profiling began: 2005;
Type of practice profiled: Group and individual;
Quality measures used: Yes;
Unit of resource use employed to measure efficiency: 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.
[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.
[End of table]
[End of section]
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.
[See PDF for image]
Source: GAO analysis of 2003 Medicare claims data.
[End of figure]
Figure 6: Percentage of Generalist Physicians by Their Medicare
Practice's Proportion of Overly Expensive Beneficiaries--Baton Rouge,
La.
[See PDF for image]
Source: GAO analysis of 2003 Medicare claims data.
[End of figure]
Figure 7: Percentage of Generalist Physicians by Their Medicare
Practice's Proportion of Overly Expensive Beneficiaries--Cape Coral,
Fla.
[See PDF for image]
Source: GAO analysis of 2003 Medicare claims data.
[End of figure]
Figure 8: Percentage of Generalist Physicians by Their Medicare
Practice's Proportion of Overly Expensive Beneficiaries--Columbus,
Ohio:
[See PDF for image]
Source: GAO analysis of 2003 Medicare claims data.
[End of figure]
Figure 9: Percentage of Generalist Physicians by Their Medicare
Practice's Proportion of Overly Expensive Beneficiaries--Des Moines,
Iowa:
[See PDF for image]
Source: GAO analysis of 2003 Medicare claims data.
[End of figure]
Figure 10: Percentage of Generalist Physicians by Their Medicare
Practice's Proportion of Overly Expensive Beneficiaries--Miami, Fla.
[See PDF for image]
Source: GAO analysis of 2003 Medicare claims data.
[End of figure]
Figure 11: Percentage of Generalist Physicians by Their Medicare
Practice's Proportion of Overly Expensive Beneficiaries--Phoenix, Ariz.
[See PDF for image]
Source: GAO analysis of 2003 Medicare claims data.
[End of figure]
Figure 12: Percentage of Generalist Physicians by Their Medicare
Practice's Proportion of Overly Expensive Beneficiaries--Pittsburgh,
Pa.
[See PDF for image]
Source: GAO analysis of 2003 Medicare claims data.
[End of figure]
Figure 13: Percentage of Generalist Physicians by Their Medicare
Practice's Proportion of Overly Expensive Beneficiaries--Portland,
Maine:
[See PDF for image]
Source: GAO analysis of 2003 Medicare claims data.
[End of figure]
Figure 14: Percentage of Generalist Physicians by Their Medicare
Practice's Proportion of Overly Expensive Beneficiaries--Riverside,
Calif.
[See PDF for image]
Source: GAO analysis of 2003 Medicare claims data.
[End of figure]
Figure 15: Percentage of Generalist Physicians by Their Medicare
Practice's Proportion of Overly Expensive Beneficiaries--Sacramento,
Calif.
[See PDF for image]
Source: GAO analysis of 2003 Medicare claims data.
[End of figure]
Figure 16: Percentage of Generalist Physicians by Their Medicare
Practice's Proportion of Overly Expensive Beneficiaries--Springfield,
Mass.
[See PDF for image]
Source: GAO analysis of 2003 Medicare claims data.
[End of figure]
[End of section]
Appendix IV: Comments from the Centers for Medicare & Medicaid
Services:
Department Of Health & Human Services:
Centers for Medicare & Medicaid Services:
Administrator:
Washington, DC 20201:
To: A. Bruce Steinwald:
Director, Health Care:
From: Leslie V. Norwalk, Esq.
Acting Administrator:
Subject: Government Accountability Office's Draft Report: "MEDICARE:
Focus on Physician Practice Patterns Can Lead to Greater Program
Efficiency" (GAO-07-307):
The Centers for Medicare & Medicaid Services (CMS) appreciates the
opportunity to respond to the Government Accountability Office's draft
report entitled, "Medicare: Focus on Physician Practice Patterns Can
Lead to Greater Program Efficiency." This report studied the prevalence
of physicians in Medicare who are likely to practice inefficiently, the
existence of physician-focused strategies used by health care
purchasers to encourage efficiency and the potential for Medicare to
profile physicians for efficiency. We agree that, given the role of
physicians in driving total Medicare spending, there is opportunity to
increase the efficiency of the Medicare program by measuring and
reporting on physician resource use. In addition, we found the
attention in the report to the need for adequate risk adjustment for
physician resource use reports to be particularly helpful.
The CMS is in the process of transforming from a passive payer to an
active purchaser of health care services. To maximize the value of the
Medicare dollar, we are studying and implementing value-based
purchasing initiatives for various Medicare payment systems, including
physicians' services. Value-based purchasing links assessment of
performance, through the use of measures, to financial and other
incentives, such as public reporting. A comprehensive set of
performance measures includes not only measures of clinical
effectiveness and patient-centeredness, but also measures of resource
use. Thus, value-based purchasing recognizes the importance of
measuring and encouraging both the provision of high quality care and
the avoidance of unnecessary resource use in the provision of care.
GAO Recommendation:
The GAO recommends that CMS develop a system that identifies individual
physicians with inefficient practice patterns and to seek legislative
changes as necessary, to improve the efficiency of care financed by
Medicare.
CMS Response:
This is a very timely recommendation and fits into the broader work
that CMS is pursuing with regard to maximizing the value of the
services for which Medicare pays. Specifically, CMS is investigating
measuring individual physician resource use with the goal of improving
the quality and efficiency of care paid for by Medicare. We believe
that measuring resource use needs to maintain quality in the provision
of care to Medicare beneficiaries and encourage physicians focus on
efficiency. Consequently, our goals are to develop and implement
measures of physician resource use that are linked to our physician
quality measures.
A goal of resource use measurement is to provide information that is
meaningful, actionable, and fair to physicians in order to reduce
inefficient practice patterns. We have tested various approaches to
reporting of resource use with physician focus groups and have learned
that physicians understand their practices from a patient-by-patient
perspective, not from an aggregate statistics perspective.
Disseminating high-level outlier reports on total annual Medicare
expenditures would likely not provide adequate detail to make the
reports meaningful or actionable by physicians. We have also learned
that detailed data for a specific procedure or service out of context
limits the meaningfulness of the report and the ability of physicians
to act on the information. The physician focus groups also emphasized
that adequate risk adjustment is essential to creating a fair
measurement tool that can be used to compare actual to expected
resource use. They were skeptical that current risk adjustment
methodologies can adequately account for the complex variables among
patient populations.
Our current efforts to measure physician resource use involve
evaluation of episode grouper software products currently on the
market. In so doing, we are coordinating our episode grouper evaluation
closely with similar work being conducted by Medicare Payment Advisory
Commission, the Ambulatory Care Quality Alliance, National Committee
for Quality Assurance, National Quality Forum, and Agency for
Healthcare Research and Quality, among others. Episode grouper software
uses data from multiple claims streams to capture all of the services
and procedures associated with an episode of care. Those resources can
then be assigned to individual physicians, and the data can be used to
develop comparative reports. We are evaluating the extent to which
these episode groupers can handle Medicare data, and the risk
adjustment capabilities of those products. We believe that episode
grouper technology holds promise for the measurement of physician
resource use.
An issue in the routine, nationwide dissemination of reports of
physician resource use is the potential return on investment for the
Medicare program. There would be a significant and recurring cost to
designing the measurement tool, analyzing the data, populating the
reports, disseminating the reports, educating physicians on the use of
the information, and evaluating the impact of providing the information
on physician behavior. These factors would need to be considered.
In summary, we applaud GAO's focus on physician efficiency and the need
for robust risk adjustment in resource use reporting. We are also
committed to developing meaningful, actionable, and fair measurement
tools for physician resource use that, along with quality measures,
would provide a comprehensive assessment of physician performance. We
look forward to working with GAO as we move forward on these
initiatives.
[End of section]
Appendix V: GAO Contact and Staff Acknowledgments:
GAO Contact:
A. Bruce Steinwald, (202) 512-7101 or steinwalda@gao.gov:
Acknowledgments:
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.
FOOTNOTES
[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, Hyperlink,
http://www.usatoday.com/money/economy/fed/2006-10-04-bernanke-
retirement-programs_x.htm (accessed Dec. 13, 2006).
[2] GAO, 21st Century: Addressing Long-Term Fiscal Challenges Must
Include a Re-examination 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.
[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).
[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.
[10] These 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.
[11] We 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.
[12] To 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.
[13] We 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.
[14] See appendix I for further discussion of our methodology.
[15] In 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.
[16] Aetna, 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.
[17] GAO-05-85.
[18] Elliott 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).
[19] Institute of Medicine, Rewarding Provider Performance: Aligning
Incentives in Medicare (Pathways to Quality Health Care Series) -
Summary (Washington D.C.: 2007).
[20] Pub. L. No. 106-554, app. F, § 412(a), 114 Stat. 2763, 2763A-509-
515.
[21] We 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).
[22] See Consumer-Purchaser Disclosure Project, More Efficient
Physicians: A Path to Significant Savings in Health Care (Washington
D.C.: July 2003).
[23] Medicare Payment Advisory Commission, Report to the Congress:
Assessing Alternatives to the Sustainable Growth Rate System
(Washington, D.C.: Mar. 2007).
[24] The population of generalist physicians studied excluded those who
had small Medicare practices (see app. I).
[25] Expenditures identified were for services from inpatient hospital,
outpatient, skilled nursing facility, physician, hospice, durable
medical equipment, and home health providers.
[26] For 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.
[27] See 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.
[28] In 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.
[29] These 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.
[30] See appendix II for the names and characteristics of these health
care purchasers.
[31] Clients can be employers or organizations that contract with the
purchasers.
[32] Our 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.
[33] Other forms of physician education include face-to-face meetings,
telephone conferences, seminars, and workshops.
[34] MedPAC, 2005.
[35] In 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).
[36] Preferred 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.
[37] Medicare fee updates are annual adjustments made to physicians'
fees.
[38] 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.
[39] 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.
[40] 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).
[41] 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.
[42] 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.
[43] 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.
[44] Monte Carlo simulation is a statistical technique by which a
quantity is calculated repeatedly, using randomly selected "what-if"
scenarios for each calculation.
[45] 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.
[46] In determining the distribution of generalists, the proportion of
overly expensive beneficiaries was rounded to one-half percent
intervals.
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