Medical care utilization for work-related injuries in the United States 2002-2006.
OBJECTIVE
To examine racial-ethnic/gender differences in the odds of injury and in the odds of seeking medical treatment among workers in the United States.


METHODS
Logistic regression models were used to estimate the odds of having a work injury and the odds of seeking medical treatment for these injuries in a sample of non-Latino Black, Latino, and non-Latino white workers from the Medical Expenditure Panel Survey (2002-2006).


RESULTS
Significant variation in the odds of injury was observed across racial-ethnic/gender groups. Although race-gender groups had significant variation in the odds of experiencing a work injury, we found few differences in treatment seeking. Among the 6 subgroups, we found that white women were significantly less likely to report an injury and significantly more likely to seek treatment when injured. Having health insurance played a key role in utilization among injured workers. The odds of seeking treatment were 33% lower for uninsured workers compared with those with private insurance. Publicly insured workers were no different from privately insured workers.


CONCLUSIONS
Our study sheds light on current trends in work injuries and associated medical care utilization among a nationally representative sample of workers.
Berdahl
Terceira A
TA
Center for Financing, Access, and Cost Trends, Agency for Healthcare Research and Quality (AHRQ), Rockville, MD 20850, USA. terceira.berdahl@ahrq.hhs.gov
Zodet
Marc
M
D000062:Accidents, Occupational / Q000706:statistics & numerical data*; D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D044383:Black People / Q000706:statistics & numerical data; D005260:Female; D006296:Health Services / Q000706:statistics & numerical data*; D054624:Health Status Disparities; D054625:Healthcare Disparities / Q000706:statistics & numerical data; D006630:Hispanic or Latino / Q000706:statistics & numerical data; D006801:Humans; D007348:Insurance, Health / Q000706:statistics & numerical data; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D044469:Racial Groups / Q000706:statistics & numerical data; D012737:Sex Factors; D014481:United States / Q000453:epidemiology; D044465:White People / Q000706:statistics & numerical data; D014947:Wounds and Injuries / Q000453:epidemiology; D055815:Young Adult; D001741:Black or African American