Risk mitigation guidance and safer supply prescribing among young people who use drugs in the context of COVID-19 and overdose emergencies

在新冠疫情和药物过量紧急情况下,为吸毒青少年提供风险缓解指导和更安全的药物供应处方

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Abstract

Across North America, overlapping overdose and COVID-19 emergencies have had a substantial impact on young people who use drugs (YPWUD). New risk mitigation guidance (RMG) prescribing practices were introduced in British Columbia, Canada, in 2020 to allow people to decrease risk of overdose and withdrawal and better self-isolate. We examined how the prescribing of hydromorphone tablets specifically impacted YPWUD's substance use and care trajectories. Between April 2020 and July 2021, we conducted virtual interviews with 30 YPWUD who had accessed an RMG prescription of hydromorphone in the previous six months and 10 addiction medicine physicians working in Vancouver. A thematic analysis was conducted. YPWUD participants highlighted a disjuncture between RMG prescriptions and the safe supply of unadulterated substances such as fentanyl, underscoring that having access to the latter is critical to reducing their reliance on street-based drug markets and overdose-related risks. They described re-appropriating these prescriptions to meet their needs, stockpiling hydromorphone so that it could be used as an "emergency backup" when they were unable to procure unregulated, illicit opioids. In the context of entrenched poverty, hydromorphone was also used to generate income for the purchase of drugs and various necessities. For some YPWUD, hydromorphone prescriptions could be used alongside opioid agonist therapy (OAT) to reduce withdrawal and cravings and improve adherence to OAT. However, some physicians were wary of prescribing hydromorphone due to the lack of evidence for this new approach. Our findings underscore the importance of providing YPWUD with a safe supply of the substances they are actively using alongside a continuum of substance use treatment and care, and the need for both medical and community-based safe and safer supply models.

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