title: Motor vehicle crashes in roadway construction workzones: an analysis using narrative text from insurance claims.
abstract: Motor vehicle travel through roadway construction workzones has been shown to increase the risk of a crash. The number of workzones has increased due to recent congressional funding in 1991 for expanded roadway maintenance and repair. In this paper, we describe the characteristics and costs of motor vehicle crashes in roadway construction workzones. As opposed to using standard accident codes to identify accident types, automobile insurance claims files from 1990-93 were searched to identify records with the keyword "construction" in the accident narrative field. A total of 3,686 claims were used for the analysis of crashes. Keywords from the accident narrative field were used to identify five pre-crash vehicle activities and five crash types. We evaluated misclassification error by reading 560 randomly selected claims and found it to be only 5%. For each of four years, 1990-93, there was a total of 648,996,977 and 1,065 crashes, respectively. There was a 70% increase in the crash rate per 10,000 personal insured vehicles from 1990-93 (2.1-3.6). Most crashes (26%) involved a stopped or slowing vehicle in the workzone. The most common crash (31%) was a rear-end collision. The most costly pre-crash activity was a major judgment error on the part of a driver (n = 120, median cost = $2,628). An overturned vehicle was the most costly crash type (n = 16, median cost = $4,745). In summary, keyword text analysis of accident narrative data used in this study demonstrated its utility and potential for enhancing injury epidemiology. The results suggest interventions are needed to respond to growing traffic hazards in construction workzones.
authors.affiliation: Liberty Mutual Research Center for Safety and Health, Hopkinton, MA 01748, USA.
authors.forename: G S
authors.initials: GS
authors.lastname: Sorock
authors.forename: T A
authors.initials: TA
authors.lastname: Ranney
authors.forename: M R
authors.initials: MR
authors.lastname: Lehto
mesh_terms: D000063:Accidents, Traffic / Q000191:economics / Q000523:psychology / Q000706:statistics & numerical data*; D000293:Adolescent; D000328:Adult; D000368:Aged; D001334:Automobile Driving / Q000523:psychology; D015982:Bias; D005160:Facility Design and Construction; D005260:Female; D005379:Financing, Construction; D006801:Humans; D007344:Insurance Claim Reporting / Q000706:statistics & numerical data*; D008297:Male; D008875:Middle Aged; D011159:Population Surveillance / Q000379:methods; D012307:Risk Factors; D014186:Transportation; D014481:United States / Q000453:epidemiology