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Published on: September 20, 2018
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Unhealthy alcohol use detection in electronic health records: A comparative study using natural language processing
Xintong Ju1, Jake Solka1, Katherine Weber2
1Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA.
Drug and Alcohol Dependence
|October 18, 2025
Summary
Natural Language Processing (NLP) significantly improves identification of unhealthy alcohol use in primary care compared to structured data (SD). NLP captures more cases, especially those with lower severity alcohol use disorder (AUD), complementing traditional screening.
Area of Science:
- Clinical Informatics
- Public Health
- Digital Health
Background:
- Unhealthy alcohol use, including risky alcohol use and alcohol use disorder (AUD), is often under-identified in primary care.
- Structured data (SD) methods have limitations in capturing the full scope of unhealthy alcohol use.
- Natural Language Processing (NLP) offers a promising avenue for identifying unhealthy alcohol use from clinical notes.
Purpose of the Study:
- To prospectively evaluate the performance of SD and NLP in identifying unhealthy alcohol use in primary care patients.
- To compare the number of positive cases identified by SD and NLP approaches.
Main Methods:
- Extracted electronic health record (EHR) data from a large Midwestern Health System (N=133,144).
- Applied both SD (diagnostic codes, alcohol screening scores) and NLP-based approaches for case identification.
- Recruited 170 participants (85 by SD, 85 by NLP) for gold-standard self-report measures.
Main Results:
- SD identified 820 cases, while NLP identified 48,262 cases of unhealthy alcohol use in the full EHR sample.
- Among SD-identified participants, 41.18% reported AUD and 28.82% reported risky alcohol use.
- Among NLP-identified participants, 20% reported AUD and 27.06% reported risky alcohol use; SD-identified participants had more AUD symptoms and mental health difficulties.
Conclusions:
- NLP substantially expands the identification of unhealthy alcohol use in primary care, capturing cases missed by SD.
- NLP is particularly effective for identifying patients with lower severity alcohol use disorder.
- NLP can serve as a valuable complement to traditional screening methods for comprehensive detection of unhealthy alcohol use.
Keywords:
Alcohol useAlcohol use disorderArtificial intelligenceElectronic health recordsEmerging technologiesNatural language processingMore Related Videos
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