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Analyzing Physician Efficiency: Per-Capita Scoring

Posted Jan 18 2010 6:38am

How does one evaluate a physician’s efficiency level?  This process has five main dimensions.

  • Which resource use measurement methodology to use. There are two main profiling methodologies: per capita and episode-based.
  • How to account for differences in patient health status. This is done through risk adjustment.  However, choosing the proper risk adjustment method is crucial in order to produce accurate physician scores.
  • How to attribute resource use to physicians. Important attribution decisions include whether to assign a patient’s resource use: i) to the single physician who bears the greatest responsibility for the resource use, ii) to all physicians who bore any responsibility, or iii)  to all physicians who met a given threshold of responsibility.
  • What benchmark(s) to use. Should the benchmarks be evidence-based, set relative to peers, or established by consensus through organizations such as the National Quality Forum.
  • How to determine what is a sufficient sample size to ensure meaningful comparisons. This sample size can vary on two dimensions: i) the availability of enough data on each physician to compute a resource use measure and ii) a sufficient number of physicians to provide meaningful comparisons.

The GAO has a report analyzing whether physician resource utilization per-capita is stable over time.  The report looks at 4 specialties [cardiology, diagnostic radiology, internal medicine, and orthopedic surgery] in 4 metro areas [Miami, Phoenix, Pittsburgh, and Sacramento].  The data used include: (1) Medicare claims files; (2) Denominator File, a database that contains enrollment and entitlement status information for all Medicare beneficiaries in a given year; (3) Hierarchical Condition Category (HCC) files that summarize Medicare beneficiaries’ diagnoses; (4) files summarizing the institutional status of beneficiaries; and (5) Unique Physician Identification Number Directory, which contains information on physicians’ specialties.

Below are the specifications the GAO report uses to create physician scores.

  • Physician resource utilization is constructed on a per-capita basis.
  • Risk adjustment is constructed using Hierarchical Condition Categories (HCCs).  The risk adjustment model uses the same 70 HCCs as the model CMS uses to set managed care capitation rates.
  • Attribution is given to the physician with the highest Evaluation and Management (E&M) cost for each beneficiary [except for diagnostic radiology where the physician with the most Part B costs was attributed the individual’s annual cost].  However, very little of each individual’s annual cost was accounted for by the attributed physician.  Institutional services accounted for 54 percent of expenditures. On the other hand, “services provided by a particular physician in our study directly to that physician’s patients accounted for only 2 percent of total expenditures or about $350 for each beneficiary in a physician’s practice.  All other services—those provided by other physicians, home health care, hospice care, outpatient services, and durable medical equipment—accounted for the remaining 44 percent of expenditures.”
  • The benchmarks used was cost relative to one’s peers.  The report acknowledges that quality metrics should also be incorporated in the evaluation.  However, since there are few established quality metrics for most specialties, the potential for quality evaluation at this point is limited.
  • For the sample size, the GAO required physicians to have treated at least 100 Medicare patients each year in the study.  The meant that 28% of physicians were excluded from the sample in 2005 and 29% were excluded in 2006.

The report finds that “58 percent of physicians and 30 percent of beneficiaries were in the same quintile of resource use in 2005 and 2006. The pattern was even more pronounced for the top resource use quintile: 72 percent of physicians and 35 percent of beneficiaries remained in that quintile. If the level of physicians’ and beneficiaries’ resource use was purely random, only 20 percent would be expected to have remained in the same quintile.”

One important aspect of physician evaluation is whether or not these scores will actually change physician behavior.  The authors review of the literature finds that “feedback alone generally has no more than a moderate influence on physician behavior.”  It is possible, however, because most insurers have a small share of the physician’s business.  Feedback from Medicare, however, may lead to a more significant behavior changes because it is so large.

Also, it likely that disaggregated scores (by patient or by episode type) will have a larger effect on physician behavior than a single overall cost.  The more detail the physician can receive, the more he can learn how to alter his behavior.  In fact, the top five insurers actually provide patient-level detail in addition to the overall physician grade.

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