Risk Stratification Model for Predicting Coronary Care Unit Readmission

BACKGROUND: Use of statistical models for assessing the clinical risk of readmission to medical and surgical intensive care units is well established. However, models for predicting risk of coronary care unit (CCU) readmission are rarely reported. Therefore, this study investigated the characteristics and outcomes of patients readmitted to CCU to identify risk factors for CCU readmission and to establish a scoring system for identifying patients at high risk for CCU readmission. METHODS: Medical data were collected for 27,841 patients with a history of readmission to the CCU of a single multi-center healthcare provider in Taiwan during 2001-2019. Characteristics and outcomes were compared between a readmission group and a non-readmission group. Data were segmented at a 9:1 ratio for model building and validation. RESULTS: The number of patients with a CCU readmission history after transfer to a standard care ward was 1,790 (6.4%). The eleven factors that had the strongest associations with CCU readmission were used to develop and validate a CCU readmission risk scoring and prediction model. When the model was used to predict CCU readmission, the receiver-operating curve characteristic was 0.7038 for risk score model group and 0.7181 for the validation group. A CCU readmission risk score was assigned to each patient. The patients were then stratified by risk score into low risk (0–12), moderate risk (13–31) and high risk (32–40) cohorts check scores, which showed that CCU readmission risk significantly differed among the three groups. CONCLUSIONS: This study developed a model for estimating CCU readmission risk. By using the proposed model, clinicians can improve CCU patient outcomes and medical care quality.