Medicare: Focus on Physician Practice Patterns Can Lead to Greater Program Efficiency
Published: 2007-04-30T00:00:00

Fast Facts:

Highlights:
section_title: Why GAO Did This Study
paragraphs: 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 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.
section_title: What GAO Found
paragraphs: 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.

section_title: Letter
paragraphs: In recent years, we and others have reported that the Medicare program is  unsustainable in its present form. 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. 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. 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.
Experts agree that physicians play a central role in the generation of  health care expenditures in total. 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. 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. 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. 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. 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. 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. 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. 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. 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, 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. 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.
subsections: section_title: Background
paragraphs: 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, 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. 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. 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.  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.
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. 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.
section_title: Physicians Who Treated a Disproportionate Share of Overly Expensive Patients Were Found in Each of 12 Areas Studied
paragraphs: 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.
subsections: section_title: In Identifying Overly Expensive Beneficiaries, We Found Significant Variation in Medicare Spending on Patients with Similar Health Status
paragraphs: 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. We developed 31 health status cohorts of beneficiaries based on  the diagnoses appearing on their Medicare claims and other factors.
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. (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.
section_title: Outlier Physicians Were Present in Every Metropolitan Area
paragraphs: 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. 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.
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.
section_title: Health Care Purchasers Used Physician Profiling Results to Encourage Efficient Medical Practice
paragraphs: 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.
subsections: section_title: Health Care Purchasers in Our Study Profiled Physicians across Several Dimensions to Evaluate Physician Performance
paragraphs: The 10 health care purchasers we examined used two basic profiling  approaches to identify physicians whose medical practices were  inefficient. 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.
section_title: Health Care Purchasers Linked Physician Profiling Results to Range of Incentives Encouraging Efficiency
paragraphs: 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. 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.
section_title: Physician Profiling Suggests Potential for Savings
paragraphs: 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.
section_title: CMS Has Tools Available to Profile Physicians for Efficiency, but May Need Some Additional Authorities to Use Results in Ways Similar to Other Purchasers
paragraphs: 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.
subsections: section_title: Medicare’s Data-Rich Environment Is Conducive to Profiling for Efficiency
paragraphs: 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.
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.
section_title: To Use Profiling Results in Medicare in Ways Similar to Other Purchasers Would Likely Require Additional Authorities
paragraphs: 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. 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, 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.
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, assign  physicians to tiers associated with varying beneficiary copayments, tie fee  updates of individual physicians to meeting performance standards, 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.
section_title: Conclusions
paragraphs: 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.
section_title: Recommendation for Executive Action
paragraphs: 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.
section_title: Agency and Professional Association Comments and Our Evaluation
paragraphs: 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).
subsections: section_title: CMS Comments
paragraphs: 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.
section_title: Professional Association Comments
paragraphs: 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.
section_title: Appendix I: Methodology for Identifying Physicians with a Disproportionate Share of Overly Expensive Beneficiaries
paragraphs: 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. 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. We analyzed the  Medicare practices of 7,105 physicians who provided services to 1,283,943  beneficiaries.
subsections: section_title: Method for Identifying Overly Expensive Beneficiaries
paragraphs: 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 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. 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. Figure 2 and figure 3 show the range of costs in the 31  risk categories for survivors in our sample.
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.
section_title: Method for Identifying Outlier Physicians
paragraphs: 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.
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.
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. We then determined the  percentage of generalists for each proportion of overly expensive  patients. 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.
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.)
section_title: Appendix II: Health Care Purchaser Program Characteristics
paragraphs: 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.
section_title: Appendix III: Distribution of Physicians by Their Proportion of Overly Expensive Beneficiaries by Metropolitan Area
paragraphs: 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.
section_title: Appendix IV: Comments from the Centers for Medicare & Medicaid Services
section_title: Appendix V: GAO Contact and Staff Acknowledgments
subsections: section_title: Acknowledgments
paragraphs: 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.