Impact of Socioeconomic Adjustment on Physicians' Relative Cost of Care
*RAND, Arlington, VA †Kaiser Permanente Center for Effectiveness and Safety Research, Oakland, CA ‡RAND, Pittsburgh, PA.Medical care (Impact Factor: 3.23). 04/2013; 51(5). DOI: 10.1097/MLR.0b013e31828d1251
BACKGROUND:: Ongoing efforts to profile physicians on their relative cost of care have been criticized because they do not account for differences in patients' socioeconomic status (SES). The importance of SES adjustment has not been explored in cost-profiling applications that measure costs using an episode of care framework. OBJECTIVES:: We assessed the relationship between SES and episode costs and the impact of adjusting for SES on physicians' relative cost rankings. RESEARCH DESIGN:: We analyzed claims submitted to 3 Massachusetts commercial health plans during calendar years 2004 and 2005. We grouped patients' care into episodes, attributed episodes to individual physicians, and standardized costs for price differences across plans. We accounted for differences in physicians' case mix using indicators for episode type and a patient's severity of illness. A patient's SES was measured using an index of 6 indicators based on the zip code in which the patient lived. We estimated each physician's case mix-adjusted average episode cost and percentile rankings with and without adjustment for SES. RESULTS:: Patients in the lowest SES quintile had $80 higher unadjusted episode costs, on average, than patients in the highest quintile. Nearly 70% of the variation in a physician's average episode cost was explained by case mix of their patients, whereas the contribution of SES was negligible. After adjustment for SES, only 1.1% of physicians changed relative cost rankings >2 percentiles. CONCLUSIONS:: Accounting for patients' SES has little impact on physicians' relative cost rankings within an episode cost framework.
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ABSTRACT: Previous research shows that patient socioeconomic status (SES) affects health care, but little is known about the relative effects of patient and physician practice SES among privately insured patients. To examine the effects of patient and physician practice SES on prevention, disease management, utilization, and cost expenditures. Cross-sectional analyses of claims data. Primary care physicians (568) and their adult managed care organization patients (437,743) in the Rochester, New York, area. Pap smears, mammograms, glycohemoglobins, and eye examinations for diabetics, physician visits, referrals, hospitalizations, costs standardized expenditures (diagnostic testing, office visits, and total), patient zip code-based SES, and physician practice SES (mean SES of patients in practice). After adjustment, lower SES patients had lower compliance with Pap smears, mammograms, and diabetic eye exams, and were less likely to have a referral or make any office visit, but were more likely to be hospitalized, and generated higher testing standardized expenditures. Lower physician practice SES was associated with lower adjusted Pap, mammogram, and glycohemoglobin compliance, lower office visit standardized expenditures, but higher diagnostic testing and total standardized expenditures. Patient SES effects were stronger for mammography, whereas physician practice SES effects were stronger for diagnostic testing costs. For the utilization indicators, the SES effects on utilization exhibited a linear gradient, whereas there was a threshold effect for costs. Patient and practice SES are independently associated with care among privately insured patients. These effects are not confined to the poorest patients but span the entire socioeconomic spectrum. Interventions to address these disparities need to be broad-based, but should also address the needs of practices with predominantly lower SES patients.Medical Care 08/2003; 41(7):842-52. DOI:10.1097/01.MLR.0000068542.47516.28 · 3.23 Impact Factor
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ABSTRACT: 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. To evaluate the effect of 12 different attribution rules on physician cost profiles. 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. Four commercial health plans in Massachusetts. 1.1 million adults continuously enrolled in 4 commercial health plans in 2004 and 2005. 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. 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. Results might differ if data from another state or from Medicare were used. 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. U.S. Department of Labor.Annals of internal medicine 05/2010; 152(10):649-54. DOI:10.1059/0003-4819-152-10-201005180-00005 · 17.81 Impact Factor
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ABSTRACT: 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. 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." 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. Current methods for profiling physicians with respect to costs of services may produce misleading results.New England Journal of Medicine 03/2010; 362(11):1014-21. DOI:10.1056/NEJMsa0906323 · 55.87 Impact Factor
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