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Journal Article

Citation

Mallory A, Kender A, Moorhouse K. Traffic Injury Prev. 2017; 18(Suppl 1): S1-S8.

Affiliation

National Highway Traffic Safety Administration.

Copyright

(Copyright © 2017, Informa - Taylor and Francis Group)

DOI

10.1080/15389588.2017.1309651

PMID

28340317

Abstract

OBJECTIVE: A multi-harm approach for analyzing crash and injury data was developed for the ultimate purpose of getting a richer picture of motor vehicle crash outcomes identifying research opportunities in crash safety.

METHODS: Methods were illustrated using a retrospective analysis of 69,597 occupant cases from NASS CDS (National Automotive Sampling System Crashworthiness Data System) from 2005 to 2015. Occupant cases were analyzed by frequency and severity of outcome: fatality, injury by AIS (Abbreviated Injury Scale), number of cases, attributable fatality, disability, and injury costs. Comparative analysis variables included pre-crash scenario, impact type, and injured body region.

RESULTS: Crash and injury prevention opportunities vary depending on the search parameters. For example, occupants in rear-end crash scenarios were more frequent than in any other pre-crash configuration, yet there were significantly more fatalities and serious injury cases in control loss, road departure, and opposite direction crashes. Fatality is most frequently associated with head and thorax injury, while disability is primarily associated with extremity injury. Costs attributed to specific body regions are more evenly distributed, dominated by injuries to the head, thorax, and extremities, but with contributions from all body regions. While AIS 3+ can be used as a single measure of harm, an analysis based on multiple measures of harm gives a much more detailed picture of the risk presented by a particular injury or set of crash conditions.

CONCLUSIONS: The developed methods represent a new approach to crash data mining that is expected to be useful for the identification of research priorities and opportunities for reduction of crashes and injuries. As the pace of crash safety improvement accelerates with innovations in both active and passive safety, these techniques for combining outcome measures for insights beyond fatality and serious injury will be increasingly valuable.


Language: en

Keywords

Crash data mining; NASS CDS; attributable fatality; cost; disability; epidemiology

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