Geographic Analysis of Trauma Readmissions in North Texas

Due to the high cost and increased risk of mortality associated with unplanned patient readmissions, research has been aimed to identify risk-factors in patients with high hospital utilization and recidivism. The primary aim of this study was to characterize readmissions across multiple institutions in patients initially admitted to a single urban Level I trauma center. Analysis was carried out to test the hypothesis that a patient’s geographic location of residence can be used to predict readmission rates. Data was queried from a regional database that is comprised of more than 150 hospitals in the North Texas region. Patient ZIP code and county of residence were analyzed using binary logistic regression to determine significance of predictability of readmission by patient geography. Additional variables such as demographics, diagnosis, Elixhauser comorbidities, and insurance were also analyzed to create a full clinical and geographic regression model describing patterns in readmissions.