Longitudinal profiles of health care providers

Abstract

Provider profiling is the activity of collecting, comparing and reporting quality of care measures for individuals, groups, agencies and institutions that provide health care services. Univariate provider profiles, such as hospital-specific mortality rates, have been constructed using cross-sectional data based on posterior summaries or maximum likelihood estimates. As data continue to be collected over time, the construction and interpretation of longitudinal profiles of health care providers will become increasingly important. Longitudinal series can be used to improve the precision of estimates - a feature that is particularly important for providers who treat a small number of patients per year. We extend and apply hierarchical models to examine and classify provider performance over time using two examples, one in the area of cardiology and the other in mental health. Performance is evaluated using the squared Mahalanobis distance and posterior probabilities based on this distance. By comparing providers based on level and temporal trend simultaneously, conservative but comprehensive assessments of performance are possible. Furthermore, the longitudinal profiles developed are easily interpreted and flexible, making them of practical use to policy-makers.