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Staffing and worker injury in nursing homes

Author

Listed:
  • Trinkoff, A.M.
  • Johantgen, M.
  • Muntaner, C.
  • Le, R.

Abstract

Objectives. We examined the relationship between nursing home staffing levels and worker injury rates in 445 nursing homes in 3 states. Methods. We obtained First Reports of Injury and workers' compensation data from 3 states (Ohio, West Virginia, and Maryland) for the year 2000. We then linked these data to Medicare's Online Survey, Certification and Reporting system to obtain nursing home staffing details and organizational descriptors. We used ordinary least squares and log-transformed regression models to examine the association between worker injury rate and nursing home staffing and organizational characteristics. Results. Total nursing hours per resident day were significantly associated with worker injury rates in nursing homes after we adjusted for organizational characteristics and state dummy variables (P = .0004). Conclusions. Our findings suggest that nursing home staffing levels have an important impact on worker health. These findings were supported for multiple facilities across different states; therefore, policies and resources that increase staffing levels in nursing homes are warranted.

Suggested Citation

  • Trinkoff, A.M. & Johantgen, M. & Muntaner, C. & Le, R., 2005. "Staffing and worker injury in nursing homes," American Journal of Public Health, American Public Health Association, vol. 95(7), pages 1220-1225.
  • Handle: RePEc:aph:ajpbhl:10.2105/ajph.2004.045070_4
    DOI: 10.2105/AJPH.2004.045070
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    Cited by:

    1. AnnMarie Lee Walton & Bonnie Rogers, 2017. "Workplace Hazards Faced by Nursing Assistants in the United States: A Focused Literature Review," IJERPH, MDPI, vol. 14(5), pages 1-25, May.
    2. Leticia Bergamin Januario & Kristina Karstad & Reiner Rugulies & Gunnar Bergström & Andreas Holtermann & David M. Hallman, 2019. "Association between Psychosocial Working Conditions and Perceived Physical Exertion among Eldercare Workers: A Cross-Sectional Multilevel Analysis of Nursing Homes, Wards and Workers," IJERPH, MDPI, vol. 16(19), pages 1-13, September.
    3. Muntaner, Carles & Li, Yong & Xue, Xiaonan & Thompson, Theresa & Chung, HaeJoo & O'Campo, Patricia, 2006. "County and organizational predictors of depression symptoms among low-income nursing assistants in the USA," Social Science & Medicine, Elsevier, vol. 63(6), pages 1454-1465, September.

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