Literature DB >> 24261347

A comparison of KABCO and AIS injury severity metrics using CODES linked data.

Cynthia Burch1, Lawrence Cook, Patricia Dischinger.   

Abstract

OBJECTIVE: The research objective is to compare the consistency of distributions between crash assigned (KABCO) and hospital assigned (Abbreviated Injury Scale, AIS) injury severity scoring systems for 2 states. The hypothesis is that AIS scores will be more consistent between the 2 studied states (Maryland and Utah) than KABCO.
METHODS: The analysis involved Crash Outcome Data Evaluation System (CODES) data from 2 states, Maryland and Utah, for years 2006-2008. Crash report and hospital inpatient data were linked probabilistically and International Classification of Diseases (CMS 2013) codes from hospital records were translated into AIS codes. KABCO scores from police crash reports were compared to those AIS scores within and between the 2 study states.
RESULTS: Maryland appears to have the more severe crash report KABCO scoring for injured crash participants, with close to 50 percent of all injured persons being coded as a level B or worse, and Utah observes approximately 40 percent in this group. When analyzing AIS scores, some fluctuation was seen within states over time, but the distribution of MAIS is much more comparable between states. Maryland had approximately 85 percent of hospitalized injured cases coded as MAIS = 1 or minor. In Utah this percentage was close to 80 percent for all 3 years. This is quite different from the KABCO distributions, where Maryland had a smaller percentage of cases in the lowest injury severity category as compared to Utah.
CONCLUSIONS: This analysis examines the distribution of 2 injury severity metrics different in both design and collection and found that both classifications are consistent within each state from 2006 to 2008. However, the distribution of both KABCO and Maximum Abbreviated Injury Scale (MAIS) varies between the states. MAIS was found to be more consistent between states than KABCO.

Entities:  

Keywords:  AIS; CODES; KABCO; data integration; serious injury

Mesh:

Year:  2014        PMID: 24261347     DOI: 10.1080/15389588.2013.854348

Source DB:  PubMed          Journal:  Traffic Inj Prev        ISSN: 1538-9588            Impact factor:   1.491


  2 in total

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Journal:  Am J Prev Med       Date:  2017-03-23       Impact factor: 5.043

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