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Risk-adjusted quality measures are used to evaluate healthcare providerswhile controlling for factors beyond their control. Existing healthcareprovider profiling approaches typically assume that the risk adjustment isperfect and the between-provider variation in quality measures is entirely dueto the quality of care. However, in practice, even with very good models forrisk adjustment, some between-provider variation will be due to incomplete riskadjustment, which should be recognized in assessing and monitoring providers.Otherwise, conventional methods disproportionately identify larger providers asoutliers, even though their provider effects need not be "extreme.'' Motivatedby efforts to evaluate the quality of care provided by transplant centers, wedevelop a composite evaluation score based on a novel individualized empiricalnull method, which robustly accounts for overdispersion due to unobserved riskfactors, models the marginal variance of standardized scores as a function ofthe effective center size, and only requires the use of publicly-availablecenter-level statistics. The evaluations of United States kidney transplantcenters based on the proposed composite score are substantially different fromthose based on conventional methods. Simulations show that the proposedempirical null approach more accurately classifies centers in terms of qualityof care, compared to existing methods.

Composite Scores for Transplant Center Evaluation: A New Individualized Empirical Null Method