Hospital readmission: Predicting the risk

This approach focused on identifying specific variables that predict the li kelihood of readmission. It involved clinical, utilization, and demographic variables that are generally available on hospital computer abstract datab ases. The approach included a process for identifying and comparing individ ual variables with the highest risk of readmission. It also contained a pro cedure for assembling risk populations including combinations of variables. The approach demonstrated the potential far using risk analysis to maximiz e the focus of clinical management on patient outcomes while reducing the a mount of resources required for this process.