Identification of opioid use disorder using electronic health records: Beyond diagnostic codes.

ABSTRACT:

Background

We used structured and unstructured electronic health record (EHR) data to develop and validate an approach to identify moderate/severe opioid use disorder (OUD) that includes individuals without prescription opioid use or chronic pain, an underrepresented population.

Methods

Using electronic diagnosis grouper text from EHRs of ~1 million patients (2012-2020), we created indicators of OUD-with "tiers" indicating OUD likelihood-combined with OUD medication (MOUD) orders. We developed six sub-algorithms with varying criteria (multiple vs single MOUD orders, multiple vs single tier 1 indicators, tier 2 indicators, tier 3 and 4 indicators). Positive predictive values (PPVs) were calculated based on chart review to determine OUD status and severity. We compared demogra

SUBMITTER: Poulsen MN 

PROVIDER: S-EPMC10620734 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature