Predictive Factors and Models for Trauma Patient Disposition

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Hospital length of stay for trauma patients can be unnecessarily prolonged due to delays in disposition planning. Demographic characteristics, comorbidities, and other patient variables may help in planning early during hospitalization.


The data of 2836 trauma patients were retrospectively analyzed. Analysis of variance and the chi-square test were used to determine univariate predictors of discharge location (i.e., home, nonhome, and rehabilitation), and multivariable logistic regression was used to determine independent predictors. Clinical decision rules for discharge location were developed for two models: (1) a regular discharge (RD) model to predict discharge location based on demographic and clinical characteristics at the completion of hospital stay and (2) an admission planning discharge (APD) model based on data available shortly after admission.


The discharge locations differed on age, sex, certain comorbidities, and various hospital and clinical variables. Increased age, female sex, longer intensive care unit and hospital stays, and the comorbidities of neurologic deficiencies, coagulopathy, and diabetes were independent predictors of nonhome discharge in the RD model. For the APD model, increased age, female sex, the comorbidities of neurologic deficiencies, diabetes, coagulopathy, and obesity were independent predictors of nonhome discharge. The RD and APD models correctly predicted the discharge location 87.2% and 82.9% of the time, respectively.


Demographic and clinical information for trauma patients predicts disposition early in the hospital stay. If the clinical decision rules are validated, discharge steps can be taken earlier in the hospital course, resulting in increased patient satisfaction, timely rehabilitation, and cost savings.

Copyright © 2014 Elsevier Inc. All rights reserved.