Development and validation of the urgency algorithm to predict compelling injuries

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Augenstein, Jeffrey¹; Digges, Kennerly¹; Ogata, Sandra¹; Perdeck, Elana¹; Stratton, James¹

Development and validation of the urgency algorithm to predict compelling injuries

Proceedings of the 17th International Technical Conference on the Enhanced Safety of Vehicles (ESV)

Affiliations

¹The William Lehman Injury Research Center, University of Miami School of Medicine, United States of America
Abstract

The URGENCY algorithm uses data from on-board crash recorders to assist in identifying crashes that are most likely to have time critical (compelling) injuries. The injury risks projected by using the NASS/CDS data are the basis for the URGENCY algorithm. This study applied the algorithm retrospectively to a population of injured occupants in the database from the University of Miami School of Medicine, William Lehman Injury Research Center (WLIRC). The population selected was adult occupants in frontal crashes that were protected by three point belts plus an air bag.

For the cases with greater than 50% predicted MAIS 3+ injury probability, 96% of the occupants in the study had MAIS 3+ injuries. . For the cases with less than 10% predicted MAIS 3+ injury probability, 63% did not have MAIS 3+ injuries. Most of the of MAIS 3+ injuries not predicted involved injuries in multiple impact crashes, pole crashes or close-in occupants injured by air bag deployment. Modifications to the URGENCY algorithm to include predictors for these three factors significantly improved accuracy of the MAIS 3+ injury predictions.
Links

URL: http://www-nrd.nhtsa.dot.gov/pdf/nrd-01/Esv/esv17/Proceed/00051.pdf

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Cited By (15)

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2015	Stitzel J, Weaver A, Schoell S, Barnard R, Talton J, Martin RS, Meredith JW. Occupant transportation decision algorithm: an advanced automatic crash notification algorithm developed and evaluated for motor vehicle crash occupant triage. In: Proceedings of the 24th International Technical Conference on the Enhanced Safety of Vehicles (ESV). June 8-11, 2015; Gothenburg, Sweden.
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2017	Stitzel J, Weaver A, Talton J, Barnard R, Schoell S, Martin RS, Meredith JW. Estimated triage improvement and societal cost savings with nationwide implementation of an advanced automatic crash notification algorithm in the U.S. In: Proceedings of the 25th International Technical Conference on the Enhanced Safety of Vehicles (ESV). June 5-8, 2017; Detroit, MI.
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2017	Piantini S, Mangini M, Baldanzini N, Pierini M, Franci A, Peris A. Prediction of motorcyclist serious injury in powered two‐wheeler to other vehicle urban crash. In: Proceedings of the 2017 International IRCOBI Conference on the Biomechanics of Injury. September 13-15, 2017; Antwerp, Belgium.54-62.