2013-06-01 12:00 - Messages

Use of Workers’ Compensation Data for Occupational Safety and Health: Proceedings from June 2012 Workshop

The purpose for the June 2012 Use of Workers’ Compensation Data for Occupational Safety and Health Workshop was to explore ways in which workers’ compensation information can be used for public health research and surveillance.  Thirty-five poster and platform presentations described studies that utilized workers’ compensation information while exploring limitations of these resources.  The workshop proceedings contain summary articles for the presentations plus notes from the discussion groups for the 6 white papers that were drafted for the workshop. 
The workshop was co-sponsored by the Bureau of Labor Statistics (BLS), Council of State and Territorial Epidemiologists (CSTE), International Association of Industrial Accident Boards and Commissions (IAIABC), National Council on Compensation Insurance (NCCI), National Institute for Occupational Safety and Health (NIOSH), Occupational Safety and Health Administration (OSHA), and the Washington State Department of Labor and Industries, Safety and Health Assessment for Research and Prevention (SHARP) program. 

Source :  http://www.cdc.gov/NIOSH/docs/2013-147/pdfs/2013–147.pdf

Evaluation of occupational injuries with lost days among opencast coal mine workers through logistic regression models

Despite precautions, mining remains the most hazardous occupation, and coal mining is one of the most dangerous industries for non-fatal occupational accidents. Accidents are complicated events with many factors that affect their formation, and statistical evaluation of accident records can produce valuable information that may prevent such accidents. In this study, a logistic regression analysis method was applied to non-fatal occupational injuries from 1996 to 2009 in an opencast coal mine for Western Lignite Corporation (WLC) of Turkish Coal Enterprises (TKI). The accident records were categorized as occupation, area, reason, age, part of body and lost days, and the SPSS package program was used for statistical analyses. Logistic regression analyses were used to predict the probability of accidents that resulted in greater or less than 3 lost workdays. It is found that the job group with the highest probability of exposure to accidents with greater than 3 lost workdays for non-fatal injuries was the maintenance personnel and workers. The employees were primarily exposed to accidents caused by a mining machine, and the lower and upper extremities have the highest probability of exposure to such risks. Finally, an equation for calculating the probability of exposure to accidents with greater or less than 3 lost workdays was derived. Then, the equation was used to determine the important accident risk factors.

Source : Seyhan Onder, Safety Science, Vol. 59, Nov. 2013, p. 86-92, http://dx.doi.org/10.1016/j.ssci.2013.05.002.



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