Hospital Clustering in the Treatment of Acute Myocardial Infarction Patients Via a Bayesian Semiparametric Approach

In this work, we develop Bayes rules for several families of loss functions for hospital report cards under a Bayesian semiparametric hierarchical model. Moreover, we present some robustness analysis with respect to the choice of the loss function, focusing on the number of hospitals our procedure identifies as “unacceptably performing”. The analysis is carried out on a case study dataset arising from MOMI (Month MOnitoring Myocardial Infarction in MIlan) survey on patients admitted with ST-Elevation Myocardial Infarction to the hospitals of Milan Cardiological Network. The major aim of this work is the ranking of the health-care providers performances, together with the assessment of the role of patients’ and providers’ characteristics on survival outcome.