THE END OF THE INJURY SEVERITY SCORE (ISS) AND THE TRAUMA AND INJURY SEVERITY SCORE (TRISS) - ICISS, AN INTERNATIONAL CLASSIFICATION OF DISEASES, NINTH REVISION-BASED PREDICTION TOOL, OUTPERFORMS BOTH ISS AND TRISS AS PREDICTORS OF TRAUMA PATIENT SURVIVAL, HOSPITAL CHARGES, AND HOSPITAL LENGTH OF STAY

Introduction: Since their inception, the Injury Severity Score (ISS) a nd the Trauma and Injury Severity Score (TRISS) have been suggested as measures of the quality of trauma care, In concept, they are designed to accurately assess injury severity and predict expected outcomes, I CISS, an injury severity methodology based on International Classifica tion of Diseases, Ninth Revision, codes, has been demonstrated to be s uperior to ISS and TRISS, The purpose of the present study was to comp are the ability of TRISS to ICISS as predictors of survival and other outcomes of injury (hospital length of stay and hospital charges), It was our hypothesis that ICISS would outperform ISS and TRISS in each o f these outcome predictions, Methods: ''Training'' data for creation o f ICISS predictions were obtained from a state hospital discharge data base, ''Test'' data were obtained from a state trauma registry, ISS, TRISS, and ICISS were compared as predictors of patient survival, They were also compared as indicators of resource utilization by assessing their ability to predict patient hospital length of stay and hospital charges, Finally, a neural network was trained on the ICISS values an d applied to the test data set in an effort to further improve predict ive power, The techniques were compared by comparing each patient's ou tcome as predicted by the model to the actual outcome, Results: Seven thousand seven hundred five patients had complete data available for a nalysis, The ICISS was far more likely than ISS or TRISS to accurately predict every measure of outcome of injured patients tested, and the neural network further improved predictive power, Conclusion: In addit ion to predicting mortality, quality tools that can accurately predict resource utilization are necessary for effective trauma center qualit y-improvement programs, ICISS-derived predictions of survival, hospita l charges, and hospital length of stay consistently outperformed those of ISS and TRISS, The neural network-augmented ICISS was even better, This and previous studies demonstrate that TRISS is a limited techniq ue in predicting survival resource utilization, Because of the limitat ions of TRISS, it should be superseded by ICISS.