AI Article Synopsis
- This study explores how predicting trauma patients' need for discharge to a facility can help reduce hospital stays.
- A multivariate analysis of data from the Oklahoma Trauma Registry identified key factors like age, specific injuries, and existing health conditions that influence discharge decisions.
- The resulting scoring model demonstrated high predictive values, successfully identifying patients likely to need facility discharge, but further research is needed to improve its accuracy.
Article Abstract
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.
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| http://dx.doi.org/10.1016/j.amjsurg.2018.11.045 | DOI Listing |
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