Unplanned readmissions after hospital discharge among patients identified as being at high risk for readmission using a validated predictive algorithm

BACKGROUND Unplanned hospital readmissions are common, expensive and often preventable. Strategies designed to reduce readmissions should target patients at high risk. The purpose of this study was to describe medical patients identified using a recently published and validated algorithm (the LACE index) as being at high risk for readmission and to examine their actual hospital readmission rates. METHODS We used population-based administrative data to identify adult medical patients discharged alive from 6 hospitals in Toronto, Canada, during 2007. A LACE index score of 10 or higher was used to identify patients at high risk for readmission. We described patient and hospitalization characteristics among both the high-risk and low-risk groups as well as the 30-day readmission rates. RESULTS Of 26 045 patients, 12.6% were readmitted to hospital within 30 days and 20.9% were readmitted within 90 days of discharge. High-risk patients (LACE ≥ 10) accounted for 34.0% of the sample but 51.7% of the patients who were readmitted within 30 days. High-risk patients were readmitted with twice the frequency as other patients, had longer lengths of stay and were more likely to die during the readmission. INTERPRETATION Using a LACE index score of 10, we identified patients with a high rate of readmission who may benefit from improved post-discharge care. Our findings suggest that the LACE index is a potentially useful tool for decision-makers interested in identifying appropriate patients for post-discharge interventions.