Predicting fatal opioid-involved overdoses: A social-ecological framework matched to a linked-data warehouse.

ABSTRACT:

Background

An estimated 60 million people used opioids non-medically worldwide in 2021. In 2019, opioid use disorder caused the loss of over 12.5 million healthy years of life due to disability and premature deaths, including those resulting from opioid-involved overdoses. Factors associated with opioid-involved overdoses are numerous, multi-layered, and interrelated. Using the social-ecological model as a foundation, we sought to comprehensively identify risk and preventive factors of fatal opioid-involved overdoses and operationalize them with quantifiable measures.

Methods

With our Community Advisory Board, investigators' expertise, and an examination of the literature, we created an expansive, opioid-overdose specific social-ecological model structured as a matrix, with

SUBMITTER: Bayly R 

PROVIDER: S-EPMC12002089 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature