Introduction Workers’ compensation data provide a source of information on occupational injuries and their burden on workers and the workplace. Many factors may influence ultimate outcome of the claim and disability status, including those external from the workplace. Occupational injury outcomes may be influenced by the health of communities in which employees live. We explored an exciting injury surveillance and analysis technique by coupling geographical information systems (GIS), workers’ compensation data, and community health assessment data to determine novel risk factors for occupational injury outcomes.
Methods Injured employee addresses from workers’ compensation data were geocoded using Esri Street Map. Geographic masking maintained individual-level confidentiality. Community health assessment categories included: health opportunities, healthy living, chronic disease/conditions, infectious disease, and injury and violence. We calculated rates and comparative risk of severity and disability duration of workers’ compensation claims based on community health assessment status. Using a negative binomial model, we estimated rate ratios (RR) and 95% confidence intervals (CI) as a function of claim rate. Cox proportional hazards regression assessed differences in duration of disability based on community health assessment status and estimated hazard ratios (HR) and 95% confidence intervals (CI).
Results Multiple categories of assessed community health indicators affected risk of severity, claim duration, and disability for occupational injury.
Discussion This innovative way of combining and visualising data may identify risk factors for occupational injury that may be spatially or community-based. The health of one’s community may play a role in both personal and occupational health. A holistic, total worker view should be considered for prevention of disability in workers’ compensation claims.
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