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Title: Defining and estimating reliability in hierarchical logistic regression models for health care provider profiling Authors:  Susan Paddock - NORC at the University of Chicago (United States) [presenting]
John Adams - Kaiser Permanente Bernard J Tyson School of Medicine (United States)
Jessica Hwang - Stanford University (United States)
Abstract: In health care provider profiling, the reliability of a performance measure indicates whether observed differences in patient outcomes can be attributed to genuine differences in quality across providers. While reliability is easy to define, estimate, and interpret when the outcome of interest is continuous, and a hierarchical linear model can be assumed, several different definitions and estimators of reliability are in use for performance measures based on binary outcomes. We compare these candidate definitions and estimators when a hierarchical logistic regression model is assumed for the binary outcome. The salient differences between various definitions are demonstrated in simulations and on a data set of Florida primary care physicians treating Medicare fee-for-service beneficiaries.