Predicting and differentiating opioid and non-opioid drug poisonings using health records data.

ABSTRACT:

Introduction

To facilitate effective targeting of overdose prevention programs, this research developed and evaluated prediction models to identify people at highest risk of specific types of drug overdose or poisoning. Using samples of mental health specialty visits and general medical visits with mental health or substance use diagnoses, this research examined how well prediction models using health records data perform in predicting either any drug poisoning or opioid-involved poisoning and how the specific predictors of opioid-involved poisoning differ from general predictors of any drug poisoning.

Methods

Records data regarding mental health and general medical visits between 2015 and 2019 in four large health systems were used to develop two-step models predicting any

SUBMITTER: Simon GE 

PROVIDER: S-EPMC12758642 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature