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. Highrisk 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.
Background Telehealth is a rapidly growing modality for expanding healthcare access, especially in the post-COVID-19 era. However, telehealth requires high-quality broadband, thus making broadband a social determinant of health. The objective of this study was to evaluate the association between broadband access and telehealth utilization across the United States during the COVID-19 pandemic. Methods Using a cross-sectional, ecological study design, we merged county-level data on broadband capacity (Microsoft's Rural Broadband Initiative), telehealth utilization among Medicare Fee-for-Service beneficiaries from January through September 2020 (CareJourney), and county-level socioeconomic characteristics (Area Health Resources Files). Multivariable linear regression was used to estimate the association between broadband capacity, county-level characteristics, and telehealth utilization. Results Among the 3107 counties, those with the greatest broadband availability (quintile 5) had 47% higher telehealth utilization compared to counties with the least broadband availability (quintile 1). In the adjusted model, a 1 standard deviation (SD) increase in broadband access was associated with a 1.54 percentage point (pp) increase in telehealth utilization (P < 0.001). Rural county designation (−1.96 pp; P < 0.001) and 1 SD increases in average Medicare beneficiary age (−1.34 pp; P = 0.001), number of nursing home beds per 1000 individuals (−0.38 pp; P = 0.002), and proportion of Native Americans/Pacific Islanders (−0.59 pp; P < 0.001) were associated with decreased telehealth utilization. Conclusion The association between broadband access and telehealth utilization and the decreased telehealth utilization in rural areas highlight the importance of broadband access for healthcare access and the need to continue investing in broadband infrastructure to promote equitable healthcare access across populations.
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