Real-time clinical note monitoring to detect conditions for rapid follow-up: A case study of clinical trial enrollment in drug-induced torsades de pointes and Stevens-Johnson syndrome. (29th October 2020)

• Record Type: Journal Article
• Authors: DeLozier, Sarah; Speltz, Peter; Brito, Jason; Tang, Leigh Anne; Wang, Janey; Smith, Joshua C; Giuse, Dario; Phillips, Elizabeth; Williams, Kristina; Strickland, Teresa; Davogustto, Giovanni; Roden, Dan; Denny, Joshua C
• Is Part Of: Journal of the American Medical Informatics Association. Volume 28:Number 1(2021)
• Page Start: 126
• Page End: 131
• Publication Date: 2020-10-29
• Subjects: natural language processing -- patient selection -- rare diseases -- precision medicine -- data mining -- electronic health records; Medical informatics -- Periodicals; Information Services -- Periodicals; Medical Informatics -- Periodicals; Médecine -- Informatique -- Périodiques; Informatica; Geneeskunde; Informatique médicale; Computer network resources; Electronic journals; 610.285
• DOI: 10.1093/jamia/ocaa213
• Languages: English
• ISSNs: 1067-5027

Abstract

Abstract: Identifying acute events as they occur is challenging in large hospital systems. Here, we describe an automated method to detect 2 rare adverse drug events (ADEs), drug-induced torsades de pointes and Stevens-Johnson syndrome and toxic epidermal necrolysis, in near real time for participant recruitment into prospective clinical studies. A text processing system searched clinical notes from the electronic health record (EHR) for relevant keywords and alerted study personnel via email of potential patients for chart review or in-person evaluation. Between 2016 and 2018, the automated recruitment system resulted in capture of 138 true cases of drug-induced rare events, improving recall from 43% to 93%. Our focused electronic alert system maintained 2-year enrollment, including across an EHR migration from a bespoke system to Epic. Real-time monitoring of EHR notes may accelerate research for certain conditions less amenable to conventional study recruitment paradigms.