Outpatient data obtained from the general medicine practice of an urban, health care facility are used to provide an application of empirical Bayes techniques in the estimation of physician "costliness." The results illustrate that application of the simplest empirical Bayes estimation procedure can provide more reasonable estimates of physician's utilization of resources than a standard estimation procedure. Empirical Bayes estimates are shown to adjust for potential instability in standard estimates that may arise from either a physician treating a small number of patients or an inappropriate case- mix adjustment. Using simulation, it is demonstrated that the empirical Bayes procedure can provide overall better estimates using fewer data than the standard procedure. This application, although somewhat limited in scope, should provide impetus for increased utilization of the numerous Bayesian and empirical Bayes techniques that currently exist in the statistical literature and pertain to small area estimation techniques.
1150, Ambulatory Care: economics, Bayes Theorem, better, Cost Savings, Diagnosis-Related Groups, Fees,Medical, Health, health care, Health Care Costs: statistics & numerical data, Hospitals,General: economics: utilization, Hospitals,Urban: economics: utilization, Human, Indiana, Medicine, Models,Econometric, patient, Patients, Physician's Practice Patterns: economics, ResNet, Support,U.S.Gov't,P.H.S., utilization