External validation of an opioid misuse machine learning classifier in hospitalized adult patients.

ABSTRACT:

Background

Opioid misuse screening in hospitals is resource-intensive and rarely done. Many hospitalized patients are never offered opioid treatment. An automated approach leveraging routinely captured electronic health record (EHR) data may be easier for hospitals to institute. We previously derived and internally validated an opioid classifier in a separate hospital setting. The aim is to externally validate our previously published and open-source machine-learning classifier at a different hospital for identifying cases of opioid misuse.

Methods

An observational cohort of 56,227 adult hospitalizations was examined between October 2017 and December 2019 during a hospital-wide substance use screening program with manual screening. Manually completed Drug Abuse Screening Tes

SUBMITTER: Afshar M 

PROVIDER: S-EPMC7967783 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature