Objectives: To determine the cost-effectiveness of pharmacy-based intranasal naloxone distribution to high-risk prescription opioid (RxO) users.
Methods: We developed a Markov model with an attached tree for pharmacy-based naloxone distribution to high-risk RxO users using 2 approaches: one-time and biannual follow-up distribution. The Markov structure had 6 health states: high-risk RxO use, low-risk RxO use, no RxO use, illicit opioid use, no illicit opioid use, and death. The tree modeled the probability of an overdose happening, the overdose being witnessed, naloxone being available, and the overdose resulting in death. High-risk RxO users were defined as individuals with prescription opioid doses greater than or equal to 90 morphine milligram equivalents (MME) per day. We used a monthly cycle length, lifetime horizon, and US healthcare perspective. Costs (2018) and quality-adjusted life-years (QALYs) were discounted 3% annually. Microsimulation was performed with 100 000 individual trials. Deterministic and probabilistic sensitivity analyses were conducted.
Results: One-time distribution of naloxone prevented 14 additional overdose deaths per 100 000 persons, with an incremental cost-effectiveness ratio (ICER) of $56 699 per QALY. Biannual follow-up distribution led to 107 additional lives being saved with an ICER of $84 799 per QALY compared with one-time distribution. Probabilistic sensitivity analyses showed that a biannual follow-up approach would be cost-effective 50% of the time at a willingness-to-pay (WTP) threshold of $100 000 per QALY. Naloxone effectiveness and proportion of overdoses witnessed were the 2 most influential parameters for biannual distribution.
Conclusion: Both one-time and biannual follow-up naloxone distribution in community pharmacies would modestly reduce opioid overdose deaths and be cost-effective at a WTP of $100 000 per QALY.
Keywords: cost-effectiveness; naloxone; overdose; pharmacists.
Copyright © 2020 ISPOR–The Professional Society for Health Economics and Outcomes Research. Published by Elsevier Inc. All rights reserved.