Citation

Lane PL, Doig G, Stewart TC, Mikrogianakis A, Stefanits T. Accid. Anal. Prev. 1997; 29(1): 53-56.

Affiliation

Trauma Services, London Health Sciences Center, Ontario, Canada.

Copyright

(Copyright © 1997, Elsevier Publishing)

DOI

unavailable

PMID

9110040

Abstract

Early attempts to assess patient outcomes in trauma hospitals included morality reviews and expert panel chart audits. More recently, a statistical methodology combining the Revised Trauma Score and Injury Severity Score has been developed (TRISS). A modification of this methodology--TRISS-like analysis--allows the inclusion of patients who have required endotracheal intubation prior to the time of arrival at the trauma hospital. This study was undertaken to further improve this TRISS-like methodology by developing statistical coefficients based on regional data. It was hypothesized that his would allow the analysis to better identify those hospitals with significantly better worse outcomes than their peers. The Comprehensive Data Set of the Ontario Trauma Registry was accessed, which contains data on severely injured patients from all 11 lead trauma hospitals in the province. Three years' data were obtained, and checked for accuracy and completeness. Analysis was performed using the previously published coefficients. New coefficients were then derived, using regression analysis on the Ontario patient data. 5,258 of 6,389 files were complete and eligible for analysis. TRISS-like analysis resulted in an expected mortality of 21.2% (1115.6/5258) with a z score for the entire province of -14.102. Individual hospital scores were all negative (fewer deaths than expected), and 9/11 hospital scores were < -1.96 (statistically significant). The new coefficients were markedly different from those previously published, and their application resulted in an overall z score of 0.000. Institutional scores ranged from -3.309 to +4.686, with two hospitals < -1.96 and one > +1.96. The old coefficients predicted many more deaths than occurred in all of the hospitals. The new coefficients proved quite accurate overall in predicting outcomes, and identified one institution with significantly more deaths than would have been predicted for other hospitals in the province. Subsequently, a fourth year's data files were obtained, and used as a validation data set. The new coefficients again proved more useful than the original ones.