title: Development of a robust mapping between AIS 2+ and ICD-9 injury codes.
abstract: Motor vehicle crashes result in millions of injuries and thousands of deaths each year in the United States. While most crash research datasets use Abbreviated Injury Scale (AIS) codes to identify injuries, most hospital datasets use the International Classification of Diseases, version 9 (ICD-9) codes. The objective of this research was to establish a one-to-one mapping between AIS and ICD-9 codes for use with motor vehicle crash injury research. This paper presents results from investigating different mapping approaches using the most common AIS 2+ injuries from the National Automotive Sampling System-Crashworthiness Data System (NASS-CDS). The mapping approaches were generated from the National Trauma Data Bank (NTDB) (428,637 code pairs), ICDMAP (2500 code pairs), and the Crash Injury Research and Engineering Network (CIREN) (4125 code pairs). Each approach may pair given AIS code with more than one ICD-9 code (mean number of pairs per AIS code: NTDB=211, ICDMAP=7, CIREN=5), and some of the potential pairs are unrelated. The mappings were evaluated using two comparative metrics coupled with qualitative inspection by an expert physician. Based on the number of false mappings and correct pairs, the best mapping was derived from CIREN. AIS and ICD-9 codes in CIREN are both manually coded, leading to more proper mappings between the two. Using the mapping presented herein, data from crash and hospital datasets can be used together to better understand and prevent motor vehicle crash injuries in the future.
authors: Health Sciences, Wake Forest University, Medical Center Boulevard, Winston-Salem, NC 27157, USA. rybarnar@wakehealth.edu
authors: Ryan T
authors: RT
authors: Barnard
authors: Kathryn L
authors: KL
authors: Loftis
authors: R Shayn
authors: RS
authors: Martin
authors: Joel D
authors: JD
authors: Stitzel
mesh_terms: D015998:Abbreviated Injury Scale; D000063:Accidents, Traffic; D059019:Clinical Coding; D016208:Databases, Factual; D006801:Humans; D038801:International Classification of Diseases; D014481:United States