Assessing geographic variations on time loss claims in Washington state workers compensation using rural urban commuting area codes
Tuesday, November 5, 2013
Purpose Little is known about the effect of workers' residential location on their time loss claims due to work-related injuries. We examined 149,110 incident claims while adjusting for multiple risk factors in a large, population-based sample of Washington State workers' compensation State Fund claims during 2002-2008. Methods Claimants' residential addresses were geocoded with census tract and aggregated into Rural Urban Commuting Area Codes (RUCAs) which takes into account for tract-level work-commuting. We used multivariable quantile regressions to predict various percentiles of cumulative lost workdays by RUCAs. Results Compared to those who live in the Urban Core, with an average paid loss work days of 136, workers in other areas experienced longer average paid time loss days due to work-related injury, 159, 147, and 152 days for those who live in Sub Urban, Large Rural Town, and Small Town & Isolated Rural, respectively (p<0.001). The impact of residential location elevated as the duration of disability increased. Compared with Urban Core residents whose 80th percentile of compensated lost workdays was 176, workers in Sub Urban and Small Town & Isolated Rural had more than 30 days (p<0.001), and Large Rural Town more than 20 days of additional lost workdays (p<0.001) while adjusting for other important factors. Conclusions Residential location has a significant and time-varying impact on duration of work disability. Workers living in Sub Urban and Small Town & Isolated Rural areas represent a particularly vulnerable group with respect to risk of long-term work disability.
Occupational health and safety
Describe innovative methods on assessing the effect of workers’ residential location on their time loss claims due to work-related injuries by 1) geocoding worker’s residential location with census tract and aggregating into Rural Urban Commuting Area codes; 2) evaluating the time-varying effect of residential location using multivariable quantile regression.
Keyword(s): Occupational Surveillance, Disability
Presenting author's disclosure statement:
Qualified on the content I am responsible for because: Iâve been leading the project on exploring the methods of assessing occupational health disparities. Iâve been actively involved with the inception of this manuscript, developed the methods of geocoding and statistical analyses, conducted the analyses, and wrote up the manuscript.
Any relevant financial relationships? No
I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines,
and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed
in my presentation.