Bayesian and Frequentist Methods for Provider Profiling Using Risk-Adjusted Assessments of Medical Outcomes

• Activity Number: 473
• Type: Contributed
• Date/Time: Wednesday, August 4, 2010 : 8:30 AM to 10:20 AM
• Sponsor: Health Policy Statistics Section
• Author(s): Michael Joseph Racz*+ and Joseph Sedransk
• Companies: Albany College of Pharmacy and Health Sciences and Case Western Reserve University
• Keywords: exchangeability ; hierarchical models ; random effect models ; report cards

Abstract

We propose a new method and compare conventional and Bayesian methodologies used or proposed for use for "provider profiling." The conventional statistical approaches to these assessments use likelihood-based frequentist methodologies, and the new Bayesian method is patterned after these. For each of three models we compare the frequentist and Bayesian approaches using data employed by New York State for reports that profile hospitals permitted to perform bypass surgery. Additional, constructed, data sets are used to sharpen our conclusions. Comparisons across different models are important because of current proposals to use random effect (exchangeable) models for profiling. We also summarize and discuss important issues in the conduct of provider profiling such as inclusion of provider characteristics in the model and choice of criteria for determining unsatisfactory performance.