An automated electronic tool to assess the risk of 30-day readmission: Validation of predictive performance

Objective: To validate an electronic tool created to identify inpatients who are at risk of readmission within 30 days and quantify the predictive performance of the readmission risk score (RRS). Methods: Retrospective cohort study including inpatients who were discharged between 1 Nov 2012 and 31 Dec 2012. The ability of the RRS to discriminate between those who did and did not have a 30-day urgent readmission was quantified by the c statistic. Calibration was assessed by plotting the observed and predicted probability of 30-day urgent readmission. Predicted probabilities were obtained from generalized estimating equations, clustering on patient. Results: Of 1689 hospital inpatient discharges (1515 patients), 159 (9.4%) had a 30-day urgent readmission. The RRS had some discriminative ability (c statistic: 0.612; 95% confidence interval: 0.570-0.655) and good calibration. Conclusions: Our study shows that the RRS has some discriminative ability. The automated tool can be used to estimate the probability of a 30-day urgent readmission.