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    Many patients with gout flares treated in the Emergency Department (ED) often do not receive optimal continuity of care after an ED visit. Thus, developing methods to identify patients with gout flares in the ED and referring them to appropriate outpatient gout care is required. While Natural Language Processing (NLP) has been used to detect gout flares retrospectively, it is much more challenging to identify patients prospectively during an ED visit where documentation is usually minimal. We annotate a corpus of ED triage nurse chief complaint notes for the presence of gout flares and implement a simple algorithm for gout flare ED alerts. We show that the chief complaint alone has strong predictive power for gout flares. We make available a de-identified version of this corpus annotated for gout mentions, which is to our knowledge the first free text chief complaint clinical corpus available. ©2020 AMIA - All rights reserved.

    Citation

    John D Osborne, James S Booth, Tobias O'Leary, Amy Mudano, Giovanna Rosas, Phillip J Foster, Kenneth G Saag, Maria I Danila. Identification of Gout Flares in Chief Complaint Text Using Natural Language Processing. AMIA ... Annual Symposium proceedings. AMIA Symposium. 2020;2020:973-982


    PMID: 33936473

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