ArticlePharmacoepidemiology and drug safety2024
Extracting forced vital capacity from the electronic health record through natural language processing in rheumatoid arthritis-associated interstitial lung disease.
Article in Pharmacoepidemiology and drug safety, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 17 citations in OpenAlex.
- Natural language processing to enhance rheumatoid arthritis care in clinical studies: a scoping review of applications, data, approaches, challenges and future directions.Rheumatology international · 2026Article
- Heterogeneity of Rheumatoid Arthritis-Associated Interstitial Lung Disease by Longitudinal Forced Vital Capacity Trajectory and Associations With Disease Outcomes.Arthritis care & research · 2026Article
- Article
- Non-TNFi biologic and targeted synthetic DMARDs in rheumatoid arthritis-associated interstitial lung disease: A propensity score-matched, active-comparator, new-user study.Seminars in arthritis and rheumatism · 2025Article
- Advanced therapies in US veterans with rheumatoid arthritis-associated interstitial lung disease: a retrospective, active-comparator, new-user, cohort study.The Lancet. Rheumatology · 2025Observational
- The Veterans Affairs Rheumatoid Arthritis Registry: A unique population in rheumatoid arthritis research.Seminars in arthritis and rheumatism · 2025Review
- Review
- Large language models and rheumatology: are we there yet?Rheumatology advances in practice · 2025Review
- Current application, possibilities, and challenges of artificial intelligence in the management of rheumatoid arthritis, axial spondyloarthritis, and psoriatic arthritis.Therapeutic advances in musculoskeletal disease · 2025Review
- Development and validation of a pulmonary function test data extraction tool for the US department of veterans affairs electronic health record.BMC research notes · 2024Article
- Advancing rheumatology with natural language processing: insights and prospects from a systematic review.Rheumatology advances in practice · 2024Review
Corrections and comments
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Authors and funding
11 authors at 6 institutions in 1 country.
Funding
Abstract
purposeTo develop a natural language processing (NLP) tool to extract forced vital capacity (FVC) values from electronic health record (EHR) notes in patients with rheumatoid arthritis-interstitial lung disease (RA-ILD).
methodsWe selected RA-ILD patients (n = 7485) in the Veterans Health Administration (VA) between 2000 and 2020 using validated ICD-9/10 codes. We identified numeric values in proximity to FVC string patterns from clinical notes in the EHR. Subsequently, we performed processing steps to account for variability in note structure, related pulmonary function test (PFT) output, and values copied across notes, then assigned dates from linked administrative procedure records. NLP-derived FVC values were compared to values recorded directly from PFT equipment available on a subset of patients.
resultsWe identified 5911 FVC values (n = 1844 patients) from PFT equipment and 15 383 values (n = 4982 patients) by NLP. Among 2610 date-matched FVC values from NLP and PFT equipment, 95.8% of values were within 5% predicted. The mean (SD) difference was 0.09% (5.9), and values strongly correlated (r = 0.94, p < 0.001), with a precision of 0.87 (95% CI 0.86, 0.88). NLP captured more patients with longitudinal FVC values (n = 3069 vs. n = 1164). Mean (SD) change in FVC %-predicted per year was similar between sources (-1.5 [30.0] NLP vs. -0.9 [16.6] PFT equipment; standardized response mean = 0.05 for both).
conclusionsNLP of EHR notes increases the capture of accurate, longitudinal FVC values by three-fold over PFT equipment. Use of this NLP tool can facilitate pharmacoepidemiologic research in RA-ILD and other lung diseases by capturing this critical measure of disease severity.
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