title: Analysis of workers' compensation claims data for machine-related injuries in metal fabrication businesses.
abstract: Metal fabrication workers are at high risk for machine-related injury. Apart from amputations, data on factors contributing to this problem are generally absent.
  
  
  
  Narrative text analysis was performed on workers' compensation claims in order to identify machine-related injuries and determine work tasks involved. Data were further evaluated on the basis of cost per claim, nature of injury, and part of body.
  
  
  
  From an initial set of 4,268 claims, 1,053 were classified as machine-related. Frequently identified tasks included machine operation (31%), workpiece handling (20%), setup/adjustment (15%), and removing chips (12%). Lacerations to finger(s), hand, or thumb comprised 38% of machine-related injuries; foreign body in the eye accounted for 20%. Amputations were relatively rare but had highest costs per claim (mean $21,059; median $11,998).
  
  
  
  Despite limitations, workers' compensation data were useful in characterizing machine-related injuries. Improving the quality of data collected by insurers would enhance occupational injury surveillance and prevention efforts. Am. J. Ind. Med. 59:656-664, 2016. © 2016 Wiley Periodicals, Inc.
authors.affiliation: HealthPartners Institute, Bloomington, Minnesota.
authors.forename: Samuel C
authors.initials: SC
authors.lastname: Yamin
authors.affiliation: HealthPartners Institute, Bloomington, Minnesota.
authors.forename: Anca
authors.initials: A
authors.lastname: Bejan
authors.affiliation: HealthPartners Institute, Bloomington, Minnesota.
authors.forename: David L
authors.initials: DL
authors.lastname: Parker
authors.affiliation: HealthPartners Institute, Bloomington, Minnesota.
authors.forename: Min
authors.initials: M
authors.lastname: Xi
authors.affiliation: Division of Environmental and Occupational Health Sciences, School of Public Health, University of Illinois, Chicago, Chicago, Illinios.
authors.forename: Lisa M
authors.initials: LM
authors.lastname: Brosseau
mesh_terms: D000062:Accidents, Occupational / Q000706:statistics & numerical data*; D000293:Adolescent; D000328:Adult; D005260:Female; D006801:Humans; D007345:Insurance Claim Review / Q000706:statistics & numerical data*; D008297:Male; D008328:Man-Machine Systems; D008669:Metallurgy / Q000295:instrumentation / Q000706:statistics & numerical data*; D008875:Middle Aged; D060051:Occupational Injuries / Q000453:epidemiology* / Q000209:etiology; D014481:United States / Q000453:epidemiology; D014942:Workers' Compensation / Q000706:statistics & numerical data*; D055815:Young Adult
keywords: injury prevention; machine safeguarding; occupational safety; safety management; workers’ compensation