One Third of Alcohol Use Disorder Diagnoses are Missed by ICD Coding
Our model improves the identification of patients meeting AUD criteria, outperforming ICD codes in detecting cases of AUD. Detection discrepancy between ICD and free-text highlights clinician <i>under documentation</i>, not under recognition. Adjudication revealed model over-sensitivity to language around substance use, withdrawal, and chronic liver disease; future study requires application to a broader set of patient age and acuity. This model has the potential to improve rapid identification of patients with AUD and enhance treatment allocation.
Authors
- Stephanie Ruest (ORCID: https://orcid.org/0009-0006-2221-7309)
- Carsten Eickhoff (ORCID: https://orcid.org/0000-0001-9895-4061)
- Laura Mercurio (ORCID: https://orcid.org/0000-0003-4346-8773)
- Susan Duffy (ORCID: https://orcid.org/0000-0002-1705-7527)
- A. Serrano García
Institutions
- University of California, San Francisco (US)
- Providence College (US)
- Brown University (US)
- Rhode Island Hospital (US)
- Hasbro Children's Hospital (US)
- University of Tübingen (DE)
Publication Details
- Journal
- Substance Use & Addiction Journal
- Published
- 2024-11-07
- DOI
- https://doi.org/10.1177/29767342241288112
- Citations
- 7
- Primary Topic
- Alcohol Consumption and Health Effects
- Type
- article
- Field-Weighted Citation Impact
- 2.97
Funders
- National Institutes of Health
- National Institute on Drug Abuse
- National Institute of General Medical Sciences