Phillip O Coffin1, Sean D Sullivan. 1. Substance Use Research Unit, San Francisco Department of Public Health, San Francisco, CA, USA.
Abstract
OBJECTIVE: To evaluate the cost-effectiveness of distributing naloxone to illicit opioid users for lay overdose reversal in Russian cities. METHOD: This study adapted an integrated Markov and decision analytic model to Russian cities. The model took a lifetime, societal perspective, relied on published literature, and was calibrated to epidemiologic findings. RESULTS: For each 20% of heroin users reached with naloxone distribution, the model predicted a 13.4% reduction in overdose deaths in the first 5 years and 7.6% over a lifetime; on probabilistic analysis, one death would be prevented for every 89 naloxone kits distributed (95% CI = 32-260). Naloxone distribution was cost-effective in all deterministic and probabilistic sensitivity analyses and cost-saving if resulting in a reduction in overdose events. Naloxone distribution increased costs by US$13 (95% CI = US$3-US$32) and QALYs by 0.137 (95% CI = 0.022-0.389) for an incremental cost of US$94 per QALY gained (95% CI = US$40-US$325). In a worst-case scenario where overdose was rarely witnessed and naloxone was rarely used, minimally effective, and expensive, the incremental cost was US$1987 per QALY gained. If national expenditures on drug-related HIV, tuberculosis, and criminal justice were applied to heroin users, the incremental cost was US$928 per QALY gained. CONCLUSIONS: Naloxone distribution to heroin users for lay overdose reversal is highly likely to reduce overdose deaths in target communities and is robustly cost-effective, even within the constraints of this conservative model.
OBJECTIVE: To evaluate the cost-effectiveness of distributing naloxone to illicit opioid users for lay overdose reversal in Russian cities. METHOD: This study adapted an integrated Markov and decision analytic model to Russian cities. The model took a lifetime, societal perspective, relied on published literature, and was calibrated to epidemiologic findings. RESULTS: For each 20% of heroin users reached with naloxone distribution, the model predicted a 13.4% reduction in overdose deaths in the first 5 years and 7.6% over a lifetime; on probabilistic analysis, one death would be prevented for every 89 naloxone kits distributed (95% CI = 32-260). Naloxone distribution was cost-effective in all deterministic and probabilistic sensitivity analyses and cost-saving if resulting in a reduction in overdose events. Naloxone distribution increased costs by US$13 (95% CI = US$3-US$32) and QALYs by 0.137 (95% CI = 0.022-0.389) for an incremental cost of US$94 per QALY gained (95% CI = US$40-US$325). In a worst-case scenario where overdose was rarely witnessed and naloxone was rarely used, minimally effective, and expensive, the incremental cost was US$1987 per QALY gained. If national expenditures on drug-related HIV, tuberculosis, and criminal justice were applied to heroin users, the incremental cost was US$928 per QALY gained. CONCLUSIONS:Naloxone distribution to heroin users for lay overdose reversal is highly likely to reduce overdose deaths in target communities and is robustly cost-effective, even within the constraints of this conservative model.
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