Opioid-related Mortality in United States Death Certificate Data: A Quantitative Bias Analysis with Expert Elicitation of Bias Parameters

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Background: Opioid-related mortality is an important public health problem in the United States. Incidence estimates rely on death certificate data generated by health care providers and medical examiners. Opioid overdoses may be underreported when other causes of death appear plausible. We applied physician-elicited death certificate bias parameters to quantitative bias analyses assessing potential age-related differential misclassification in US opioid-related mortality estimates. Methods: We obtained cause-of-death data (US, 2017) from the National Center for Health Statistics and calculated crude opioid-related outpatient death counts by age category (25-54, 55-64, 65+). We elicited beliefs from 10 primary care physicians on sensitivity of opioid-related death classification from death certificates. We summarized elicited sensitivity estimates, calculated plausible specificity values, and applied resulting parameters in a probabilistic bias analysis. Results: Physicians estimated wide sensitivity ranges for classification of opioid-related mortality by death certificates, with lower estimated sensitivities among older age groups. Probabilistic bias analyses adjusting for physician-estimated misclassification indicated 3.1 times more (95% uncertainty interval: 1.2-23.5) opioid-related deaths than the observed death count in the 65+ age group. All age groups had substantial increases in bias-adjusted death counts. Conclusions: We developed and implemented a feasible method of eliciting physician expert opinion on bias parameters for sensitivity of a medical record-based death indicator and applied findings in quantitative bias analyses adjusting for differential misclassification. Our findings are consistent with the hypothesis that opioid-related mortality rates may be substantially underestimated, particularly among older adults, due to misclassification in cause-of-death data from death certificates.

Original languageEnglish (US)
Pages (from-to)421-429
Number of pages9
Issue number3
StatePublished - May 1 2023

Bibliographical note

Funding Information:
R.F.M.’s work was supported by the US National Library of Medicine (R01LM013049).

Publisher Copyright:
© 2023 Lippincott Williams and Wilkins. All rights reserved.


  • Cause of death
  • Data interpretation
  • Death certificates
  • Misclassification
  • Opioid epidemic
  • Opioid overdose
  • Sensitivity and specificity
  • Statistical

PubMed: MeSH publication types

  • Journal Article
  • Research Support, N.I.H., Extramural


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