Establishment-level occupational safety analytics: Challenges and opportunities

Details

• Alternative Title:
  Int J Ind Ergon
• Personal Author:
  Foreman, Anne M. ; Friedel, Jonathan E. ; Ludwig, Timothy D. ; Ezerins, Maira E. ; Açikgöz, Yalçin ; Bergman, Shawn M. ; Wirth, Oliver
• Description:
  In occupational safety and health, big data and analytics show promise for the prediction and prevention of workplace injuries. Advances in computing power and analytical methods have allowed companies to reveal insights from the "big" data that previously would have gone undetected. Despite the promise, occupational safety has lagged behind other industries, such as supply chain management and healthcare, in terms of exploiting the potential of analytics and much of the data collected by organizations goes unanalyzed. The purpose of the present paper is to argue for the broader application of establishment-level safety analytics. This is accomplished by defining the terms, describing previous research, outlining the necessary components required, and describing knowledge gaps and future directions. The knowledge gaps and future directions for research in establishment-level analytics are categorized into readiness for analytics, analytics methods, technology integration, data culture, and impact of analytics.
• Keywords:
  Big Data Data Culture Injuries Near Misses Occupational Safety Safety Analytics
• Source:
  Int J Ind Ergon. 94
• Pubmed ID:
  37288316
• Pubmed Central ID:
  PMC10242415
• Document Type:
  Journal Article
• Funding:
  CC999999/ImCDC/Intramural CDC HHSUnited States/
• Volume:
  94
• Collection(s):
  CDC Public Access
• Main Document Checksum:
  urn:sha256:42bdc5cff0f5bd3858a277238849a2418cc3414101ad33d15fc82c49266fa559
• Download URL:
  https://stacks.cdc.gov/view/cdc/129637/cdc_129637_DS1.pdf
• File Type:
  [PDF - 225.95 KB ]