MedicalResearch.com Interview with: Craig A Umscheid, MD, MSCE, FACP Assistant Professor of Medicine and Epidemiology Director, Center for Evidence-based Practice Medical Director, Clinical Decision Support Chair, Department of Medicine Quality Committee Senior Associate Director, ECRI-Penn AHRQ Evidence-based Practice Center University of Pennsylvania Philadelphia, PA 19104 MedicalResearch.com: What are the main findings of the study? Dr. Umscheid: We developed and successfully deployed into the electronic health record of the University of Pennsylvania Health System an automated prediction tool which identifies newly admitted patients who are at risk for readmission within 30 days of discharge.  Using local data, we found that having been admitted to the hospital two or more times in the 12 months prior to admission was the best way to predict which patients are at risk for being readmitted in the 30 days after discharge. Using this finding, our automated tool identifies patients who are “high risk” for readmission and creates a “flag” in their electronic health record (EHR). The flag appears next to the patient’s name in a column titled “readmission risk.” The flag can be double-clicked to display detailed information relevant to discharge planning.  In a one year prospective validation of the tool, we found that patients who triggered the readmission alert were subsequently readmitted 31 percent of the time. When an alert was not triggered, patients were readmitted only 11 percent of the time.  There was no evidence for an effect of the intervention on 30-day all-cause readmission rates in the 12-month period after implementation.