Predictive Inference for Identifying Outliers in Health Care Providers

• Activity Number: 400
• Type: Topic Contributed
• Date/Time: Tuesday, August 2, 2011 : 2:00 PM to 3:50 PM
• Sponsor: Section on Bayesian Statistical Science
• Author(s): Michael Joseph Racz*+ and Guofen Yan
• Companies: Albany College of Pharmacy and Health Sciences and University of Virginia
• Keywords: report cards ; posterior predictive probability ; residual

Abstract

Provider profiling is the evaluation of the performance of hospitals, doctors, and other medical practitioners to enhance the quality of care. Many jurisdictions have released public report cards comparing hospital or physician-specific outcomes. Given the importance of provider profiling, studying the methodology used and providing enhancements is essential. Ohlssen, Sharples and Spiegelhalter (2007) present an extensive, thoughtful evaluation of "provider profiling" methodology. In particular they are concerned about whether a putative outlier is really an outlier or an observation in the tail of the common distribution for all practitioners, and present methodology to address this issue. We evaluate the Ohlssen et al. (2007) methodology using both NYS bypass surgery data and simulated data of the same type as that used in Racz and Sedransk (2010). We also extend the Ohlssen et al. methodology to permit evaluation of important characteristics seemingly not covered by the Ohlssen et al. procedure.

Ohlssen(2007)JRSS A, 170, 865-890. Racz(2010) JASA, 105, 48-58