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Harborview Assessment for Risk of Mortality: An Improved Measure of Injury Severity on the Basis of ICD-9-CM

West, T. Al MD, MPH; Rivara, Frederick P. MD, MPH; Cummings, Peter MD, MPH; Jurkovich, Gregory J. MD; Maier, Ronald V. MD

The Journal of Trauma: Injury, Infection, and Critical Care: September 2000 - Volume 49 - Issue 3 - p 530-541
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Background There have been several attempts to develop a scoring system that can accurately reflect the severity of a trauma patient’s injuries, particularly with respect to the effect of the injury on survival. Current methodologies require unreliable physiologic data for the assignment of a survival probability and fail to account for the potential synergism of different injury combinations. The purpose of this study was to develop a scoring system to better estimate probability of mortality on the basis of information that is readily available from the hospital discharge sheet and does not rely on physiologic data.

Methods Records from the trauma registry from an urban Level I trauma center were analyzed using logistic regression. Included in the regression were Internation Classification of Diseases-9th Rev (ICD-9-CM) codes for anatomic injury, mechanism, intent, and preexisting medical conditions, as well as age. Two-way interaction terms for several combinations of injuries were also included in the regression model. The resulting Harborview Assessment for Risk of Mortality (HARM) score was then applied to an independent test data set and compared with Trauma and Injury Severity Score (TRISS) probability of survival and ICD-9-CM Injury Severity Score (ICISS) for ability to predict mortality using the area under the receiver operator characteristic curve.

Results The HARM score was based on analysis of 16,042 records (design set). When applied to an independent validation set of 15,957 records, the area under the receiver operator characteristic curve (AUC) for HARM was 0.9592. This represented significantly better discrimination than both TRISS probability of survival (AUC = 0.9473, p = 0.005) and ICISS (AUC = 0.9402, p= 0.001). HARM also had a better calibration (Hosmer-Lemeshow statistic [HL] = 19.74) than TRISS (HL = 55.71) and ICISS (HL = 709.19). Physiologic data were incomplete for 6,124 records (38%) of the validation set; TRISS could not be calculated at all for these records.

Conclusion The HARM score is an effective tool for predicting probability of in-hospital mortality for trauma patients. It outperforms both the TRISS and ICD-9-CM Injury Severity Score (ICISS) methodologies with respect to both discrimination and calibration, using information that is readily available from hospital discharge coding, and without requiring emergency department physiologic data.

From the Department of Surgery, University of Texas Southwestern Medical Center, Dallas, Texas (T.A.W.) and Department of Surgery, University of Washington (R.V.M., G.J.J.) and Harborview Injury Prevention and Research Center (F.P.R., P.C.), Seattle, Washington.

Submitted for publication October 4, 1999.

Accepted for publication May 11, 2000.

Address for reprints: T. Al West, MD, MPH, Department of Surgery, University of Texas Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX 75235-9158.

© 2000 Lippincott Williams & Wilkins, Inc.