Abstract #300290

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JSM 2003 Abstract #300290
Activity Number: 232
Type: Topic Contributed
Date/Time: Tuesday, August 5, 2003 : 10:30 AM to 12:20 PM
Sponsor: Section on Health Policy Statistics
Abstract - #300290
Title: Profiling Pharmacy Expenditures in Managed Health Care: Bayesian Inference for a Two-Part Hierarchical Model
Author(s): Min Zhang*+ and Robert L. Strawderman and Mark Cowen and Martin T. Wells
Companies: Cornell University and Cornell University and St. Joseph Mercy Hospital Ann Arbor and Cornell University
Address: Dept. of Biometrics, Ithaca, NY, 14853-7801,
Keywords: Profiling ; Pharmacy expenditure ; Managed health care ; Hierarchical model ; Intraclass correlation coefficient ; Ranking
Abstract:

Profiling is currently an important, and hotly debated, topic in health care and other industries that are looking for ways to control costs and increase profitability and service quality. This paper focuses on developing statistical methods appropriate for profiling physician contributions to patient pharmacy expenditures incurred in a managed care setting. A two-part hierarchical model with a correlated random effect structure is developed to account for the correlated, skewed, zero-inflated nature of cost data. Inference is conducted in a Bayesian framework using MCMC. Similarly to Normand, et al. (1997), provider-level performance indices appropriate for this model are constructed and their posterior distributions are obtained. Physicians are then ranked according to these measures, and the posterior distribution of these ranks subsequently serves as the basis for establishing a new financial incentive scheme for physicians. Finally, summary measures that attempt to capture the amount of variability in pharmacy expenditures attributable to physicians are also proposed and computed.

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