Identifying Patient-Reported Outcome Measure Documentation in Veterans Health Administration Chiropractic Clinic Notes: Natural Language Processing Analysis
We evaluated multiple NLP methods across a series of tasks, with optimal performance achieved using a rule-based method. By leveraging NLP approaches, we can overcome the challenges posed by unstructured clinical text notes to track documented PROM use. Overall documented use of PROMs in chiropractic notes was low and highlights a potential for quality improvement. This work represents a methodological advancement in the identification and monitoring of documented use of PROMs to ensure consistent, high-quality chiropractic care for veterans.
Authors
- Anthony J. Lisi (ORCID: https://orcid.org/0000-0003-1153-967X)
- Kelsey L. Corcoran (ORCID: https://orcid.org/0000-0003-0600-0063)
- Brian C. Coleman (ORCID: https://orcid.org/0000-0002-6926-5571)
- Cynthia Brandt (ORCID: https://orcid.org/0000-0001-8179-1796)
- Joseph L. Goulet (ORCID: https://orcid.org/0000-0002-0842-804X)
- Stephen L. Luther (ORCID: https://orcid.org/0000-0001-7524-7380)
Institutions
- University of South Florida (US)
- Edward Hines, Jr. VA Hospital (US)
- Yale University (US)
- VA Connecticut Healthcare System (US)
Publication Details
- Journal
- JMIR Medical Informatics
- Published
- 2025-04-02
- DOI
- https://doi.org/10.2196/66466
- Citations
- 3
- Primary Topic
- Clinical practice guidelines implementation
- Type
- article
- Field-Weighted Citation Impact
- 5.64