LAUSR

BACKGROUND The ability to predict the need for discharge of trauma patients to a facility may help shorten hospital stay. This study aimed to determine the predictors of discharge to a facility and develop and validate a predictive scoring model, utilizing the Oklahoma Trauma Registry (OTR). METHODS A multivariate analysis of the OTR 2005-2013 determined independent predictors of discharge to a facility. A scoring model was developed, and positive and negative predictive values (PPV and NPV) were evaluated for 2014 patients. RESULTS 101,656 patients were analyzed. The scoring model included age≥50 years, lower extremity fracture, ICU stay≥5 days, pelvic fracture, intracranial hemorrhage, congestive heart failure, cardiac dysrhythmia, history of CVA or TIA, and ISS≥15, spine fracture, diabetes mellitus, hypertension, ischemic heart disease, and chronic obstructive pulmonary disease. Applying the model to 2014 patients, PPV for predicting discharge to a facility was 84.9% for scores≥15, and NPV was 90.5% for scores<8. CONCLUSION A scoring model including age, trauma severity, types of injury, and comorbidities could predict discharge of trauma patients to a facility. Further studies are needed to refine the efficacy of the model.