Ergonomic and socioeconomic risk factors for hospital workers' compensation injury claims.
BACKGROUND
Hospital workers are a diverse population with high rates of musculoskeletal disorders (MSDs). The risk of MSD leading to workers' compensation (WC) claims is likely to show a gradient by socioeconomic status (SES) that may be partly explained by working conditions.


METHODS
A single community hospital provided workforce demographics and WC claim records for 2003-2005. An ergonomic job exposure matrix (JEM) was developed for these healthcare jobs from direct observation of physical workload and extraction of physical and psychosocial job requirements from the O*NET online database. Occupational exposures and SES categories were assigned to workers through their O*NET job titles. Univariate and multivariate Poisson regression analyses were performed to estimate the propensity to file an injury claim in relation to individual factors, occupational exposures, and SES.


RESULTS
The jobs with the highest injury rates were nurses, semi-professionals, and semi-skilled. Increased physical work and psychological demands along with low job tenure were associated with an increase in risk, while risk decreased with psychosocial rewards and supervisor support. Both occupational and individual factors mediated the relationship between SES and rate of injury claims.


CONCLUSIONS
Physical and organizational features of these hospital jobs along with low job tenure predicted WC injury claim risk and explained a substantial proportion of the effects of SES. Further studies that include lifestyle risk factors and control for prior injuries and co-morbidities are warranted to strengthen the current study findings.
Boyer
Jon
J
Department of Work Environment, University of Massachusetts Lowell, Lowell, Massachusetts 01854, USA. Jon_Boyer@uml.edu
Galizzi
Monica
M
Cifuentes
Manuel
M
d'Errico
Angelo
A
Gore
Rebecca
R
Punnett
Laura
L
Slatin
Craig
C
D000062:Accidents, Occupational / Q000191:economics* / Q000706:statistics & numerical data*; D000328:Adult; D019567:Back Injuries / Q000191:economics / Q000453:epidemiology; D003430:Cross-Sectional Studies; D006804:Ergonomics; D005260:Female; D006306:Health Surveys; D006801:Humans; D015994:Incidence; D007344:Insurance Claim Reporting / Q000191:economics* / Q000706:statistics & numerical data*; D016013:Likelihood Functions; D008297:Male; D008404:Massachusetts; D008875:Middle Aged; D009741:Nursing Staff, Hospital / Q000191:economics / Q000706:statistics & numerical data; D016273:Occupational Exposure / Q000191:economics / Q000706:statistics & numerical data; D010564:Personnel, Hospital / Q000191:economics* / Q000706:statistics & numerical data*; D012306:Risk; D012959:Socioeconomic Factors; D013180:Sprains and Strains / Q000191:economics / Q000453:epidemiology; D014942:Workers' Compensation / Q000191:economics* / Q000706:statistics & numerical data*; D016526:Workload / Q000191:economics / Q000706:statistics & numerical data; D014947:Wounds and Injuries / Q000191:economics* / Q000453:epidemiology*