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In this paper we present the costs of defensive medicine in thirty-five clinical specialties to determine whether malpractice liability reforms would greatly reduce health care costs. Defensive medicine includes tests and procedures ordered by physicians principally to reduce perceived threats of medical malpractice liability. The practice is commonly assumed to increase health care costs. The results of studies of the costs of defensive medicine have been inconsistent. We found that estimated savings resulting from a 10 percent decline in medical malpractice premiums would be less than 1 percent of total medical care costs in every specialty. These savings are lower than most previous estimates, and they suggest that the presumed impact of tort reform on health care costs may be overstated. [ABSTRACT FROM AUTHOR]

Objective. To determine whether additional risk adjustment is necessary in economic profiling of physicians when claims data are already grouped into episodes of care, and to measure effects of risk adjustment on cost efficiency rankings of physicians. Data Sources. Four years of inpatient, outpatient, professional, and pharmacy claims data from a mixed model HMO. Study Design. Claims data were processed through Symmetry Health Data Systems' episode treatment group (ETG) grouper to define episodes of care and Symmetry's episode risk group (ERG) software to define measures of patients' health risk scores. For each episode type (ETG), ETG-mean expected costs were calculated as the mean costs of all episodes of that type, and risk-adjusted expected costs were calculated using three alternative risk model formulations. Data Collection. Within specialties, physicians were ranked from most cost efficient to least cost efficient, based on standardized difference between actual and expected costs. ETG-mean based rankings were compared with risk-adjusted rankings. Analyses were performed for cardiologists, family practitioners, general surgeons, and neurologists. Principal Findings. With all three risk models, risk scores were essentially unrelated to episode costs in approximately three-fourths of episode categories (ETGs). In a sample of ETGs for which risks–costs relationships appeared to exist, split sample validation showed the relationships to be unstable or spurious in all except one ETG. Within specialties, risk-adjusted cost efficiency rankings differ little from ETG-mean adjusted rankings. Conclusions. Depending upon the purpose for which economic profiling is performed, additional risk adjustment, beyond that already provided by episode grouping, may be unnecessary. Additional research may be needed to identify and validate ETG-level relationships between patient risks and episode costs. [ABSTRACT FROM AUTHOR]

To investigate whether different risk-adjustment methodologies and economic profiling or “practice efficiency” metrics produce differences in practice efficiency rankings for a set of primary care physicians (PCPs). Twelve months of claims records (inpatient, outpatient, professional, and pharmacy) for an independent practice association HMO. Patient risk scores obtained with six profiling risk-adjustment methodologies were used in conjunction with claims cost tabulations to measure practice efficiency of all primary care physicians who managed 25 or more members of an HMO. For each of the risk-adjustment methodologies, two measures of “efficiency” were constructed: the standardized cost difference between total observed (standardized actual) and total expected costs for patients managed by each PCP, and the ratio of the PCP's total observed to total expected costs (O/E ratio). Primary care physicians were ranked from most to least efficient according to each risk-adjusted measure, and level of agreement among measures was tested using weighted kappa. Separate rankings were constructed for pediatricians and for other primary care physicians. Moderate to high levels of agreement were observed among the six risk-adjusted measures of practice efficiency. Agreement was greater among pediatrician rankings than among adult primary care physician rankings, and, with the standardized difference measure, greater for identifying the least efficient than the most efficient physicians. The O/E ratio was shown to be a biased measure of physician practice efficiency, disproportionately targeting smaller sized panels as outliers. Although we observed moderate consistency among different risk-adjusted PCP rankings, consistency of measures does not prove that practice efficiency rankings are valid, and health plans should be careful in how they use practice efficiency information. Indicators of practice efficiency should be based on the standardized cost difference, which controls for number of patients in a panel, instead of O/E ratio, which does not. [ABSTRACT FROM AUTHOR]

For more than 10 years, reports comparing quality of care in hospitals have been disseminated to the public. The most commonly used measure in these reports is hospital mortality rate. Despite the resources devoted to analyzing and disseminating mortality data, little attention has been given to the question of their validity as a quality measure. In this article, the authors synthesize findings from 18 articles identified as providing information relevant to this issue. From this renew, the authors find evidence that poor quality care increases patients' risk of mortality and that, on average quality of care provided in hospitals identified as high-mortality rate outliers is poorer than that provided in low-mortality rate outlier hospitals. Nevertheless, a clear conclusion from these studies is that when used as a measure of quality for individual hospitals, risk-adjusted mortality rates ate seriously inaccurate. Publication of hospital mortality rates misinforms the public about hospital quality. [ABSTRACT FROM AUTHOR]

A response to a letter to the editor about an article on the reliability of using episode-grouping software for physician cost profiling in the March 18, 2010 issue is presented.

A letter to the editor is presented in response to an article about the enactment of medical malpractice tort reforms by Mike Stinson and Katie O. Orrico in the September 2010 issue.

In an effort to rein in rising health care costs, health plans are using physician cost profiles as the basis for tiered networks that give patients incentives to visit low-cost physicians. Because physician cost profiles are often statistically unreliable some experts have argued that physician groups should be profiled instead. Using Massachusetts data, we evaluate the two options empirically. Although we find that physician-group profiles are statistically more reliable, the group profile is not a good predictor of individual physician performance within the group. Better methods for creating provider cost profiles are needed. [ABSTRACT FROM AUTHOR]

Background: Some health plans profile physicians on the basis of their relative costs and use these profiles to assign physicians to cost categories. Physician organizations have questioned whether the rules used to attribute costs to a physician affect the cost category to which that physician is assigned. Objective: To evaluate the effect of 12 different attribution rules on physician cost profiles. Design: Under each of the 12 attribution rules, a cost profile was created for the physicians in the aggregated claims database and the physicians were assigned to a cost category (high cost, average cost, low cost, or low sample size). The attribution rules differed by unit of analysis, signal for responsibility, number of physicians who can be assigned responsibility, and threshold value for assigning responsibility. Setting: Four commercial health plans in Massachusetts. Patients: 1.1 million adults continuously enrolled in 4 commercial health plans in 2004 and 2005. Measurements: Percentage of all episodes assigned to any physician and percentage of costs billed by a physician that were included in his or her own profile were calculated under each rule. The cost category assignments from a commonly used default rule were compared with those from each of the other 11 attribution rules and the rate of disagreement was calculated. Results: Percentage of episodes that could be assigned to a physician varied substantially across the 12 rules (range, 20% to 69%), as did the mean percentage of costs billed by a physician that were included in that physician's own cost profile (range, 13% to 60%). Depending on the alternate rule used, between 17% and 61% of physicians would be assigned to a different cost category than that assigned by using the default rule. Limitation: Results might differ if data from another state or from Medicare were used. Conclusion: The choice of attribution rule affects how costs are assigned to a physician and can substantially affect the cost category to which a physician is assigned. [ABSTRACT FROM AUTHOR]

Background: Insurance products with incentives for patients to choose physicians classified as offering lower-cost care on the basis of cost-profiling tools are increasingly common. However, no rigorous evaluation has been undertaken to determine whether these tools can accurately distinguish higher-cost physicians from lower-cost physicians. Methods: We aggregated claims data for the years 2004 and 2005 from four health plans in Massachusetts. We used commercial software to construct clinically homogeneous episodes of care (e.g., treatment of diabetes, heart attack, or urinary tract infection), assigned each episode to a physician, and created a summary profile of resource use (i.e., cost) for each physician on the basis of all assigned episodes. We estimated the reliability (signal-to-noise ratio) of each physician's cost-profile score on a scale of 0 to 1, with 0 indicating that all differences in physicians' cost profiles are due to a lack of precision in the measure (noise) and 1 indicating that all differences are due to real variation in costs of services (signal). We used the reliability results to estimate the proportion of physicians in each specialty whose cost performance would be classified inaccurately in a two-tiered insurance product in which the physicians with cost profiles in the lowest quartile were labeled as “lower cost.” Results: Median reliabilities ranged from 0.05 for vascular surgery to 0.79 for gastroenterology and otolaryngology. Overall, 59% of physicians had cost-profile scores with reliabilities of less than 0.70, a commonly used marker of suboptimal reliability. Using our reliability results, we estimated that 22% of physicians would be misclassified in a two-tiered system. Conclusions: Current methods for profiling physicians with respect to costs of services may produce misleading results. N Engl J Med 2010;362:1014-21. [ABSTRACT FROM AUTHOR]

Background: Physician cost profiles (also called efficiency or economic profiles) compare the costs of care provided by a physician to his or her peers. These profiles are increasingly being used as the basis for policy applications such as tiered physician networks. Tiers (low, average, high cost) are currently defined by health plans based on percentile cut-offs which do not account for statistical uncertainty. In this paper we compare the percentile cut-off method to another method, using statistical testing, for identifying high-cost or low-cost physicians. Methods: We created a claims dataset of 2004-2005 data from four Massachusetts health plans. We employed commercial software to create episodes of care and assigned responsibility for each episode to the physician with the highest proportion of professional costs. A physicians' cost profile was the ratio of the sum of observed costs divided by the sum of expected costs across all assigned episodes. We discuss a new method of measuring standard errors of physician cost profiles which can be used in statistical testing. We then assigned each physician to one of three cost categories (low, average, or high cost) using two methods, percentile cut-offs and a t-test (p-value ⩽ 0.05), and assessed the level of disagreement between the two methods. Results: Across the 8689 physicians in our sample, 29.5% of physicians were assigned a different cost category when comparing the percentile cut-off method and the t-test. This level of disagreement varied across specialties (17.4% gastroenterology to 45.8% vascular surgery). Conclusions: Health plans and other payers should incorporate statistical uncertainty when they use physician cost-profiles to categorize physicians into low or high-cost tiers. [ABSTRACT FROM AUTHOR]

A response by John L. Adams, Ateev Mehrotra and J. William Thomas to letters to the editor about their article "Physician Cost Profiling--Reliability and Risk of Misclassification" that was published in the March 18, 2010 issue is presented.

Background: Insurance products with incentives for patients to choose physicians classified as offering lower-cost care on the basis of cost-profiling tools are increasingly common. However, no rigorous evaluation has been undertaken to determine whether these tools can accurately distinguish higher-cost physicians from lower-cost physicians.Methods: We aggregated claims data for the years 2004 and 2005 from four health plans in Massachusetts. We used commercial software to construct clinically homogeneous episodes of care (e.g., treatment of diabetes, heart attack, or urinary tract infection), assigned each episode to a physician, and created a summary profile of resource use (i.e., cost) for each physician on the basis of all assigned episodes. We estimated the reliability (signal-to-noise ratio) of each physician's cost-profile score on a scale of 0 to 1, with 0 indicating that all differences in physicians' cost profiles are due to a lack of precision in the measure (noise) and 1 indicating that all differences are due to real variation in costs of services (signal). We used the reliability results to estimate the proportion of physicians in each specialty whose cost performance would be classified inaccurately in a two-tiered insurance product in which the physicians with cost profiles in the lowest quartile were labeled as "lower cost."Results: Median reliabilities ranged from 0.05 for vascular surgery to 0.79 for gastroenterology and otolaryngology. Overall, 59% of physicians had cost-profile scores with reliabilities of less than 0.70, a commonly used marker of suboptimal reliability. Using our reliability results, we estimated that 22% of physicians would be misclassified in a two-tiered system.Conclusions: Current methods for profiling physicians with respect to costs of services may produce misleading results. [ABSTRACT FROM AUTHOR]

Most current strategies to improve quality and efficiency in health-care delivery focus on measuring and improving physician practice. A new "second generation" of physician profiling--episode-based profiling--is moving beyond legacy "first-generation" physician profiles based on population health and preventive services measures. Episode-based profiling measures physician practice at the "episode of care" level with sophisticated analytic methods and tools using data from claim and other administrative data sets, and it has an underlying "theory of change" consistent with the evolution of the US health-care marketplace. While offering potential advantages in informing consumer choice and enabling practice improvement, episode-based profiling also has limitations and challenges, both analytically and in the process of physician engagement and improvement. Nonetheless, episode-based profiling is likely to continue to spread and have growing influence, and it has significant implications for research, policy, and clinical stakeholders. [ABSTRACT FROM AUTHOR]