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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...

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Published in:Medical care 2010-07, Vol.48 (7), p.645-651
Main Authors: Berdahl, Terceira A., Zodet, Marc
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Language:English
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Zodet, Marc
description 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.
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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. 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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.</description><subject>Accidents, Occupational - statistics &amp; numerical data</subject><subject>Adolescent</subject><subject>Adult</subject><subject>Age Factors</subject><subject>Aged</subject><subject>Black or African American</subject><subject>Black people</subject><subject>Black People - statistics &amp; numerical data</subject><subject>Construction industries</subject><subject>Female</subject><subject>Health care industry</subject><subject>Health insurance</subject><subject>Health Services - statistics &amp; numerical data</subject><subject>Health Status Disparities</subject><subject>Healthcare Disparities - statistics &amp; numerical data</subject><subject>Hispanic or Latino - statistics &amp; numerical data</subject><subject>Hispanics</subject><subject>Humans</subject><subject>Insurance, Health - statistics &amp; numerical data</subject><subject>Logistic Models</subject><subject>Male</subject><subject>Medical treatment</subject><subject>Men</subject><subject>Middle Aged</subject><subject>Modeling</subject><subject>Occupational accidents</subject><subject>Occupations</subject><subject>Physical trauma</subject><subject>Polls &amp; surveys</subject><subject>Racial Groups - statistics &amp; numerical data</subject><subject>Regression analysis</subject><subject>Sex Factors</subject><subject>Uninsured people</subject><subject>United States - epidemiology</subject><subject>White people</subject><subject>White People - statistics &amp; numerical data</subject><subject>Workplace diversity</subject><subject>Wounds and Injuries - epidemiology</subject><subject>Young Adult</subject><issn>0025-7079</issn><issn>1537-1948</issn><issn>1537-1948</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2010</creationdate><recordtype>article</recordtype><recordid>eNqFkM1KXDEYhoNY6tT2Dmw5uOnq6JeT5CSzlMFaYUTwhy5DTn6YjJkTm-Qg7ar34B32ShoZ24Ibs_kged73Cw9CBxiOMMz58cXy6ggGwMQSLLAZjMZ6B80wI7zFcyp20QygYy0HPt9D73JeA2BOWPcW7XXAqOgYn6HrC2u8VqFZqGSb2-KD_6mKj2PjYmq-xXTXXtmgijXN-biekre58WNTVhUe_dP1damvuenqst-_Huvo36M3ToVsPzzPfXT75fRm8bVdXp6dL06WraZAddsTRijpmRuwUUY4zrHTirpBA3eGE9Ez4Ybezg2lTBAlGBGOWC6owxyYI_vo87b3PsXvk81FbnzWNgQ12jhlyUk91QdU8vAFuY5TGuvnJOOcADBGK0S3kE4x52SdvE9-o9IPiUE-KZdVuXypvMY-PXdPw8aaf6G_jisgtsBDDMWmfBemB5vkyqpQVq91f9xG17nE9L-accAME_IHA0iYvg</recordid><startdate>20100701</startdate><enddate>20100701</enddate><creator>Berdahl, Terceira A.</creator><creator>Zodet, Marc</creator><general>Lippincott Williams &amp; Wilkins</general><general>Lippincott Williams &amp; Wilkins, Inc</general><general>Lippincott Williams &amp; Wilkins Ovid Technologies</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>K9.</scope><scope>7X8</scope></search><sort><creationdate>20100701</creationdate><title>Medical Care Utilization for Work-Related Injuries in the United States 2002–2006</title><author>Berdahl, Terceira A. ; Zodet, Marc</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c404c-63534365fb1dad8f771fca4fbc07fd738658fb6e9d44583a8538f3e784f1705f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Accidents, Occupational - statistics &amp; numerical data</topic><topic>Adolescent</topic><topic>Adult</topic><topic>Age Factors</topic><topic>Aged</topic><topic>Black or African American</topic><topic>Black people</topic><topic>Black People - statistics &amp; numerical data</topic><topic>Construction industries</topic><topic>Female</topic><topic>Health care industry</topic><topic>Health insurance</topic><topic>Health Services - statistics &amp; numerical data</topic><topic>Health Status Disparities</topic><topic>Healthcare Disparities - statistics &amp; numerical data</topic><topic>Hispanic or Latino - statistics &amp; numerical data</topic><topic>Hispanics</topic><topic>Humans</topic><topic>Insurance, Health - statistics &amp; numerical data</topic><topic>Logistic Models</topic><topic>Male</topic><topic>Medical treatment</topic><topic>Men</topic><topic>Middle Aged</topic><topic>Modeling</topic><topic>Occupational accidents</topic><topic>Occupations</topic><topic>Physical trauma</topic><topic>Polls &amp; surveys</topic><topic>Racial Groups - statistics &amp; numerical data</topic><topic>Regression analysis</topic><topic>Sex Factors</topic><topic>Uninsured people</topic><topic>United States - epidemiology</topic><topic>White people</topic><topic>White People - statistics &amp; numerical data</topic><topic>Workplace diversity</topic><topic>Wounds and Injuries - epidemiology</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Berdahl, Terceira A.</creatorcontrib><creatorcontrib>Zodet, Marc</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Health &amp; Medical Complete (Alumni)</collection><collection>MEDLINE - Academic</collection><jtitle>Medical care</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Berdahl, Terceira A.</au><au>Zodet, Marc</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Medical Care Utilization for Work-Related Injuries in the United States 2002–2006</atitle><jtitle>Medical care</jtitle><addtitle>Med Care</addtitle><date>2010-07-01</date><risdate>2010</risdate><volume>48</volume><issue>7</issue><spage>645</spage><epage>651</epage><pages>645-651</pages><issn>0025-7079</issn><issn>1537-1948</issn><eissn>1537-1948</eissn><coden>MELAAD</coden><abstract>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.</abstract><cop>United States</cop><pub>Lippincott Williams &amp; Wilkins</pub><pmid>20548257</pmid><doi>10.1097/MLR.0b013e3181dbdc1c</doi><tpages>7</tpages></addata></record>
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source JSTOR
subjects Accidents, Occupational - statistics & numerical data
Adolescent
Adult
Age Factors
Aged
Black or African American
Black people
Black People - statistics & numerical data
Construction industries
Female
Health care industry
Health insurance
Health Services - statistics & numerical data
Health Status Disparities
Healthcare Disparities - statistics & numerical data
Hispanic or Latino - statistics & numerical data
Hispanics
Humans
Insurance, Health - statistics & numerical data
Logistic Models
Male
Medical treatment
Men
Middle Aged
Modeling
Occupational accidents
Occupations
Physical trauma
Polls & surveys
Racial Groups - statistics & numerical data
Regression analysis
Sex Factors
Uninsured people
United States - epidemiology
White people
White People - statistics & numerical data
Workplace diversity
Wounds and Injuries - epidemiology
Young Adult
title Medical Care Utilization for Work-Related Injuries in the United States 2002–2006
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