Does a 4-variable prediction model accurately predict 30-day unplanned hospital readmission in adults with diabetes whose index admission is diabetes-related?
A 4-variable prediction model (length of stay, ischemic heart disease, peripheral vascular disease, and number of drugs) showed good internal and external validity for predicting 30-day unplanned readmission in adults hospitalized for diabetes-related conditions.
OBJECTIVE: The primary objective is to develop a prediction model of 30-day hospital readmission among adults with diabetes mellitus (DM) whose index admission was DM-related. The secondary aims are to internally and externally validate the prediction model and compare its performance with 2 existing models. RESEARCH DESIGN AND SETTING: Data of inpatients aged ≥ 18 years from 2008 to 2015 were extracted from the electronic medical record system of the National University Hospital, Singapore. Unplanned readmission within 30 days was calculated from the discharge date of the index hospitalization. Multivariable logistic regression and 10-fold cross-validation were performed. For external validation, simulations based on prevalence of 30-day readmission, and the regression coefficients provided by referenced papers were conducted. RESULTS: Eleven percent of 2355 patients reported 30-day readmission. The prediction model included 4 predictors: length of stay, ischemic heart disease, peripheral vascular disease, and number of drugs. C-statistics for the prediction model and 10-fold cross-validation were 0.68 (95% CI 0.66, 0.70) and 0.67 (95% CI 0.63 to 0.70), respectively. Those for the 3 simulated external validation data sets ranged from 0.64 to 0.68. CONCLUSION: The prediction model performs well with good internal and external validity for identifying patients with DM at risk of unplanned 30-day readmission.
Soh et al. (Thu,) studied this question.
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