Naloxone Distribution Models in the United States: A Scoping Review.

Abstract

Background: Increasing naloxone distribution is a high priority means to mitigating opioid overdose rates in the United States. Since a variety of naloxone distribution models exist, with differences in infrastructure and funding between states and health-systems, it is important to review their differences and understand the strengths and barriers to widespread implementation of each model.

Methods: The following 4 databases were searched for articles reporting on naloxone distribution models: (1) PubMed/Medline (National Library of Medicine), (2) Embase (Elsevier), (3) Scopus (Elsevier), and (4) the Cochrane library. Reports from all years written in English that discussed naloxone distribution models in the United States were included, as were all study designs.

Results: Of 5825 articles initially identified, 173 were selected for full text review. Of these, 49 met full criteria and were included for data extraction and analysis. Most distribution models occurred in community-based opioid education and naloxone distribution programs and in community pharmacies via a standing order/statewide protocol. Most programs reported strengths related to feasibility, but frequently reported cost as a limitation. Fewer studies described distribution models in ambulatory care or hospital settings, though these studies also highlighted strengths related to feasibility, particularly with support from working partners, and when utilizing an interprofessional care approach. Few studies reported health/economic outcomes data associated with naloxone distribution, such as changes in the number of patient/layperson access, the number of opioid overdose reversals, or cost-savings.

Conclusions: This review outlines the many ways in which naloxone is distributed in the United States and emphasizes a need for improved outcomes data collecting/reporting in the various settings where naloxone is distributed. This would allow for future studies to evaluate which distribution model factors are associated with improvements in health outcomes, such as increased layperson access, and lower opioid overdose/mortality rates.