Prediction of potentially avoidable readmission risk in a division of general internal medicine.

Introduction: The 30-day post-discharge readmission rate is a quality indicator that may reflect suboptimal care. The computerised algorithm SQLape® can retrospectively identify a potentially avoidable readmission (PARA) with high sensitivity and specificity. We retrospectively analysed the hospital stays of patients readmitted to the Department of Internal Medicine of the CHUV (Centre Hospitalier Universitaire Vaudois) in order to quantify the proportion of PARAs and derive a risk prediction model.

New approaches to reimbursement schemes based on patient classification systems and their comparison.

We propose reimbursement schemes based on patient classification systems (PCSs) that include adjustments for length of stay (LOS) and exceptional costs and are designed to minimize undesirable effects of economic incentives. In addition, a statistical approach to compare the schemes and the underlying PCSs is proposed, where costs and LOSs for two successive years are used. The first year data provides estimates of the class cost means and the next year's reimbursements which are compared with the second year's costs.