Phillip O. Coffin, MD; Sean D. Sullivan, PhD
Disclaimer: The authors had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Grant Support: By grant 5T32AI007140-33 from the National Institute of Allergy and Infectious Diseases at the National Institutes of Health.
Potential Conflicts of Interest: None disclosed. Forms can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M12-1737.
Reproducible Research Statement: Study protocol: Not applicable. Statistical code: Mathematical operations available from Dr. Coffin (e-mail, email@example.com). Data set: Input parameters and sources provided in the text and Appendix.
Requests for Single Reprints: Phillip O. Coffin, MD, San Francisco Department of Public Health, 25 Van Ness Avenue, Suite 500, San Francisco, CA 94102; e-mail, firstname.lastname@example.org.
Current Author Addresses: Dr. Coffin: San Francisco Department of Public Health, 25 Van Ness Avenue, Suite 500, San Francisco, CA 94102.
Dr. Sullivan: Pharmaceutical Outcomes Research and Policy Program, University of Washington, 1959 NE Pacific Street, Box 357630, Seattle, WA 98195-7630.
Author Contributions: Conception and design: P.O. Coffin, S.D. Sullivan.
Analysis and interpretation of the data: P.O. Coffin, S.D. Sullivan.
Drafting of the article: P.O. Coffin.
Critical revision of the article for important intellectual content: P.O. Coffin, S.D. Sullivan.
Final approval of the article: P.O. Coffin, S.D. Sullivan.
Provision of study materials or patients: P.O. Coffin.
Statistical expertise: P.O. Coffin, S.D. Sullivan.
Obtaining of funding: P.O. Coffin.
Administrative, technical, or logistic support: P.O. Coffin.
Collection and assembly of data: P.O. Coffin.
This article has been corrected. The original version (PDF) is appended to this article as a Supplement.
Opioid overdose is a leading cause of accidental death in the United States.
To estimate the cost-effectiveness of distributing naloxone, an opioid antagonist, to heroin users for use at witnessed overdoses.
Integrated Markov and decision analytic model using deterministic and probabilistic analyses and incorporating recurrent overdoses and a secondary analysis assuming heroin users are a net cost to society.
Published literature calibrated to epidemiologic data.
Hypothetical 21-year-old novice U.S. heroin user and more experienced users with scenario analyses.
Naloxone distribution for lay administration.
Overdose deaths prevented and incremental cost-effectiveness ratio (ICER).
In the probabilistic analysis, 6% of overdose deaths were prevented with naloxone distribution; 1 death was prevented for every 227 naloxone kits distributed (95% CI, 71 to 716). Naloxone distribution increased costs by $53 (CI, $3 to $156) and quality-adjusted life-years by 0.119 (CI, 0.017 to 0.378) for an ICER of $438 (CI, $48 to $1706).
Naloxone distribution was cost-effective in all deterministic and probabilistic sensitivity and scenario analyses, and it was cost-saving if it resulted in fewer overdoses or emergency medical service activations. In a “worst-case scenario” where overdose was rarely witnessed and naloxone was rarely used, minimally effective, and expensive, the ICER was $14 000. If national drug-related expenditures were applied to heroin users, the ICER was $2429.
Limited sources of controlled data resulted in wide CIs.
Naloxone distribution to heroin users is likely to reduce overdose deaths and is cost-effective, even under markedly conservative assumptions.
National Institute of Allergy and Infectious Diseases.
Coffin PO, Sullivan SD. Cost-Effectiveness of Distributing Naloxone to Heroin Users for Lay Overdose Reversal. Ann Intern Med. 2013;158:1–9. doi: 10.7326/0003-4819-158-1-201301010-00003
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Published: Ann Intern Med. 2013;158(1):1-9.
Emergency Medicine, Healthcare Delivery and Policy, High Value Care, Tobacco, Alcohol, and Other Substance Abuse.
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