Ranking USRDS Provider-specific SMRs from 1998--2001

• Activity Number: 259
• Type: Topic Contributed
• Date/Time: Tuesday, August 9, 2005 : 10:30 AM to 12:20 PM
• Sponsor: Section on Bayesian Statistical Science
• Author(s): Rongheng Lin*+ and Thomas A. Louis and Susan M. Paddock and Greg Ridgeway
• Companies: Johns Hopkins University and Johns Hopkins University and RAND Corporation and RAND Corporation
• Keywords: Ranks/percentiles ; Bayesian hierarchical model ; Uncertainty assessments

Abstract

Provider profiling (i.e., ranking "league tables") is prevalent in health services research. Similarly, comparing educational institutions and identifying differentially expressed genes depend on ranking. Effective ranking procedures must be structured by a hierarchical (Bayesian) model and guided by a ranking-specific loss function. However, even optimal methods can perform poorly, and estimates must be accompanied by uncertainty assessments. We use the 1998--2001 Standardized Mortality Ratio (SMR) data from United States Renal Data System (USRDS) as a platform to identify issues and approaches. Our analyses extend \cite{liu:loui:2004} by combining evidence from multiple years via an AR(1) model; considering estimates that minimize errors in classifying providers above or below a percentile cutpoint and those that minimize rank-based, squared-error loss; considering ranks based on the posterior probability that a provider's SMR exceeds a threshold; comparing these ranks to those produced by ranking MLEs and ranking P-values associated with testing whether a provider's $ SMR = 1$; and comparing results for a parametric and a nonparametric prior.