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Methodology
Original research
Prescription opioid overdose and adverse effect hospitalisations among injured workers in eight states (2010–2014)
  1. Jeanne M Sears1,2,
  2. Sheilah Hogg-Johnson2,3,
  3. Ryan A Sterling4,
  4. Deborah Fulton-Kehoe4,
  5. Gary M Franklin4,5
  1. 1Department of Health Services, University of Washington, Seattle, Washington, USA
  2. 2Institute for Work and Health, Toronto, Ontario, Canada
  3. 3Canadian Memorial Chiropractic College, Toronto, Ontario, Canada
  4. 4Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, USA
  5. 5Washington Department of Labor and Industries, Tumwater, Washington, USA
  1. Correspondence to Dr Jeanne M Sears, Department of Health Services, University of Washington, Seattle, WA 98195, USA; jeannes{at}uw.edu

Abstract

Objective High-risk opioid prescribing practices in workers’ compensation (WC) settings are associated with excess opioid-related morbidity, longer work disability and higher costs. This study characterises the burden of prescription opioid-related hospitalisations among injured workers.

Methods Hospital discharge data for eight states (Arizona, Colorado, Michigan, New Jersey, New York, South Carolina, Utah and Washington) were obtained from the State Inpatient Databases, Healthcare Cost and Utilization Project, Agency for Healthcare Research and Quality. We calculated 5-year (2010–2014) average annual rates of prescription opioid overdose/adverse effect (AE) hospitalisations. Injured workers were identified using payer (WC) and external cause codes.

Results State-level average annual prescription opioid overdose/AE hospitalisation rates ranged from 0.3 to 1.2 per 100 000 employed workers. Rates for workers aged ≥65 years old were two to six times the overall rates. Among those hospitalised with prescription opioid overdose/AEs, injured workers were more likely than other inpatients to have a low back disorder diagnosis, and less likely to have an opioid dependence/abuse or cancer diagnosis, or a fatal outcome. Averaged across states, WC was the primary expected payer for <1% of prescription opioid overdose/AE hospitalisations vs 6% of injury hospitalisations.

Conclusions Population-based estimates of prescription opioid morbidity are almost nonexistent for injured workers; this study begins to fill that gap. Rates for injured workers increased markedly with age but were low relative to inpatients overall. Research is needed to assess whether WC as payer adequately identifies work-related opioid morbidity for surveillance purposes, and to further quantify the burden of prescription opioid-related morbidity.

  • epidemiology
  • occupational health practice
  • pharmacology
  • health services research
  • health surveillance

https://doi.org/10.1136/oemed-2020-106472

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    Footnotes

    • Contributors JMS conceived of and designed the study, was responsible for data management and data analysis, and drafted the initial manuscript. SH-J and DF-K assisted with the study design and statistical methods. RAS assisted with background literature review and constructing population denominators. All authors assisted with the interpretation of the results, edited the manuscript for important intellectual content and approved the final manuscript as submitted.

    • Funding This work was supported by the National Institute for Occupational Safety and Health (NIOSH, under grant number R03OH010943). Its contents are solely the responsibility of the authors and do not necessarily represent the official views of NIOSH.

    • Competing interests None declared.

    • Patient consent for publication Not required.

    • Ethics approval This study did not involve identifiable human subjects and thus did not require institutional review board approval.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Data availability statement Data may be obtained from a third party and are not available from the authors. Hospital discharge data are available for purchase directly from the Healthcare Cost and Utilization Project, Agency for Healthcare Research and Quality (https://www.hcup-us.ahrq.gov/databases.jsp).