Literature DB >> 11003333

Harborview assessment for risk of mortality: an improved measure of injury severity on the basis of ICD-9-CM.

T A West1, F P Rivara, P Cummings, G J Jurkovich, R V Maier.   

Abstract

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-9CM) 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 ICD9-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.

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Mesh:

Year:  2000        PMID: 11003333     DOI: 10.1097/00005373-200009000-00022

Source DB:  PubMed          Journal:  J Trauma        ISSN: 0022-5282


  9 in total

1.  Diagnosis based injury severity scaling: investigation of a method using Australian and New Zealand hospitalisations.

Authors:  S Stephenson; G Henley; J E Harrison; J D Langley
Journal:  Inj Prev       Date:  2004-12       Impact factor: 2.399

2.  Scoring system for traumatic liver injury (SSTLI) in polytraumatic patients: a predictor of mortality.

Authors:  H H Kim; J H Kim; C-Y Park; H M Cho
Journal:  Eur J Trauma Emerg Surg       Date:  2014-10-21       Impact factor: 3.693

3.  Comorbidity and age are both independent predictors of length of hospitalization in trauma patients.

Authors:  Eric Bergeron; André Lavoie; Lynne Moore; David Clas; Michel Rossignol
Journal:  Can J Surg       Date:  2005-10       Impact factor: 2.089

4.  Patterns of errors contributing to trauma mortality: lessons learned from 2,594 deaths.

Authors:  Russell L Gruen; Gregory J Jurkovich; Lisa K McIntyre; Hugh M Foy; Ronald V Maier
Journal:  Ann Surg       Date:  2006-09       Impact factor: 12.969

5.  Traumatic injury mortality prediction (TRIMP-ICDX): A new comprehensive evaluation model according to the ICD-10-CM codes.

Authors:  Guohu Zhang; Muding Wang; Degang Cong; Yunji Zeng; Wenhui Fan
Journal:  Medicine (Baltimore)       Date:  2022-08-05       Impact factor: 1.817

6.  Evaluation of probability of survival using trauma and injury severity score method in severe neurotrauma patients.

Authors:  Jung-Ho Moon; Bo-Ra Seo; Jae-Won Jang; Jung-Kil Lee; Hyung-Sik Moon
Journal:  J Korean Neurosurg Soc       Date:  2013-07-31

Review 7.  Systematic review of predictive performance of injury severity scoring tools.

Authors:  Hideo Tohira; Ian Jacobs; David Mountain; Nick Gibson; Allen Yeo
Journal:  Scand J Trauma Resusc Emerg Med       Date:  2012-09-10       Impact factor: 2.953

8.  The Low Fall as a Surrogate Marker of Frailty Predicts Long-Term Mortality in Older Trauma Patients.

Authors:  Ting Hway Wong; Hai V Nguyen; Ming Terk Chiu; Khuan Yew Chow; Marcus Eng Hock Ong; Gek Hsiang Lim; Nivedita Vikas Nadkarni; Dianne Carrol Tan Bautista; Jolene Yu Xuan Cheng; Lynette Mee Ann Loo; Dennis Chuen Chai Seow
Journal:  PLoS One       Date:  2015-09-01       Impact factor: 3.240

9.  Artificial intelligence to predict in-hospital mortality using novel anatomical injury score.

Authors:  Wu Seong Kang; Heewon Chung; Hoon Ko; Nan Yeol Kim; Do Wan Kim; Jayun Cho; Hongjin Shim; Jin Goo Kim; Ji Young Jang; Kyung Won Kim; Jinseok Lee
Journal:  Sci Rep       Date:  2021-12-07       Impact factor: 4.379

  9 in total

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