Applying Machine Learning to Workers' Compensation Data to Identify Industry-Specific Ergonomic and Safety Prevention Priorities: Ohio, 2001 to 2011.

Journal: Journal of occupational and environmental medicine
Published Date: Jan 1, 2018

Abstract

OBJECTIVE: This study leveraged a state workers' compensation claims database and machine learning techniques to target prevention efforts by injury causation and industry.

Authors

  • Alysha R Meyers
    National Institute for Occupational Safety and Health, Division of Surveillance, Hazard Evaluations, and Field Studies, Center for Workers' Compensation Studies, Cincinnati, Ohio (Drs Meyers, Wurzelbacher, Ms Tseng); Ohio Bureau of Workers' Compensation, Division of Safety and Hygiene, Pickerington, Ohio (Dr Al-Tarawneh, Mr Lampl, Mr Robins); National Institute for Occupational Safety and Health, Office of the Director, Economic Research Support Office, Cincinnati, Ohio (Dr Bushnell); National Institute for Occupational Safety and Health, Division of Safety Research, Morgantown, West Virginia (Dr Bell); National Institute for Occupational Safety and Health, Division of Surveillance, Hazard Evaluations, and Field Studies, Cincinnati, Ohio (Dr Bertke, Ms Raudabaugh, Dr Schnorr); Taiwan Centers for Disease Control, Taipei City, Taiwan (Dr Wei).
  • Ibraheem S Al-Tarawneh
  • Steven J Wurzelbacher
  • P Timothy Bushnell
  • Michael P Lampl
  • Jennifer L Bell
  • Stephen J Bertke
  • David C Robins
  • Chih-Yu Tseng
  • Chia Wei
  • Jill A Raudabaugh
  • Teresa M Schnorr

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