PREDICTING SURVIVAL OF VICTIMS OF MOTOR-VEHICLE CRASHES IN NEW-YORK-STATE

This study assesses the relative ability of three different models to predict in-hospital mortality for victims of motor vehicle crashes. Th e first two models, the trauma and injury severity score (TRISS) and a severity characterization of trauma (ASCOT), are models that have bee n used in many earlier studies and have been quoted extensively in the literature. The third model, which is developed in this study, uses e ssentially the same risk factors as the other two studies, but employs them in a different manner. In order to provide a fair comparison, ne w (logistic regression) model coefficients are fit to the first two mo dels using the study data. The models are compared with respect to typ ical criteria for assessing the fit of logistic regression models as w ell as their ability to predict mortality for various subsets of serio usly injured patients. The study concludes that the new model provides a substantially more accurate prediction of mortality, and that it ma y be wise for regions attempting to assess relative outcomes in their subregions to develop statistical models that are tailored to their ow n patients. (C) 1997 Elsevier Science Ltd. All rights reserved.