The problem of readmission, wherein patients are readmitted for the same or a related condition shortly after discharge, has become a challenge worldwide from care quality and financial perspectives. In this study, we explore 30-day readmission data for predicting who is likely to be readmitted and understanding key factors contributing to preventable readmissions using the developmental trajectory of creatinine level as a key laboratory marker of serious illness and a potential predictor of future readmission. Using Electronic Health Record data on 928 patients over ten different visits to emergency departments across Israel, we apply a semi-parametric, statistical, group-based trajectory model to elicit three distinct creatinine-based trajectories over time with differing 30-day readmission rates for males and females. Analysis of readmission risk stratification of the patient population using other relevant factors is ongoing research.
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