Prevalence and Expenses of Outpatient Opioid Prescriptions, With Associated Sociodemographic, Economic, and Work Characteristics

Int J Health Serv. 2020 Jan;50(1):82-94. doi: 10.1177/0020731419881336. Epub 2019 Oct 11.

Abstract

Information on opioids obtained by workers is important for both health and safety. We examined the prevalence and total expenses of obtaining outpatient opioid prescriptions, along with associated sociodemographic, economic, and work characteristics, in national samples of U.S. workers. We used Medical Expenditure Panel Survey data (2007–2016) along with descriptive and multiple logistic regression. During the study period, an estimated 21 million workers (12.6%) aged 16 years or older obtained one or more outpatient opioid prescriptions, at an expense of $2.81 billion per year. Private health insurance covered half of the total opioid expenses for workers. The prevalence of obtaining opioid prescriptions was higher for women than for men, but men had higher opioid expenses. In addition, the prevalence of obtaining opioid prescriptions was higher for workers who were older; non-Hispanic white; divorced, separated, or widowed; and non-college-educated. There is an inverse relationship between family income and the likelihood of obtaining opioids. Compared to workers with private insurance, workers with public health insurance had higher expenses for opioid prescriptions. Finally, workers in occupations at higher risk for injury and illness – including construction and extraction; farming; service; and production, transportation, and material moving occupations – were more likely to obtain opioid prescriptions.

Keywords: MEPS; occupation; opioid expenses; opioid prescriptions; work.

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Analgesics, Opioid / administration & dosage*
  • Analgesics, Opioid / economics*
  • Fees, Pharmaceutical / statistics & numerical data
  • Female
  • Humans
  • Insurance Coverage / statistics & numerical data
  • Insurance, Pharmaceutical Services / statistics & numerical data
  • Logistic Models
  • Male
  • Medical Assistance / statistics & numerical data
  • Middle Aged
  • Occupations / statistics & numerical data*
  • Outpatients / statistics & numerical data*
  • Residence Characteristics
  • Sex Factors
  • Socioeconomic Factors
  • United States
  • Young Adult

Substances

  • Analgesics, Opioid