Evaluation of Natural Language Processing for the Identification of Crohn Disease-Related Variables in Spanish Electronic Health Records: A Validation Study for the PREMONITION-CD Project.

Autor:	Montoto C; Takeda Farmacéutica España S.A., Madrid, Spain., Gisbert JP; Hospital Universitario de La Princesa, Madrid, Spain.; Instituto de Investigación Sanitaria Princesa (IIS-IP), Madrid, Spain.; Universidad Autónoma de Madrid, Madrid, Spain.; Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), Madrid, Spain., Guerra I; Hospital Universitario de Fuenlabrada, Madrid, Spain., Plaza R; Hospital Universitario Infanta Leonor, Madrid, Spain., Pajares Villarroya R; Hospital Universitario Infanta Sofía, Madrid, Spain., Moreno Almazán L; Hospital Universitario HM Montepríncipe, Madrid, Spain., López Martín MDC; Hospital Universitario Infanta Elena, Madrid, Spain., Domínguez Antonaya M; Hospital Universitario Rey Juan Carlos, Madrid, Spain., Vera Mendoza I; Hospital Universitario Puerta de Hierro Majadahonda, Madrid, Spain., Aparicio J; Takeda Farmacéutica España S.A., Madrid, Spain., Martínez V; Takeda Farmacéutica España S.A., Madrid, Spain., Tagarro I; Takeda Farmacéutica España S.A., Madrid, Spain., Fernandez-Nistal A; Takeda Farmacéutica España S.A., Madrid, Spain., Canales L; Department of Software and Computing System, University of Alicante, Alicante, Spain., Menke S; MedSavana SL, Madrid, Spain., Gomollón F; Hospital Clínico Universitario Lozano Blesa, Zaragoza, Spain.; Instituto de Investigación Sanitaria Aragón (IISA), Zaragoza, Spain.; Universidad de Zaragoza, Zaragoza, Spain.; Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), Zaragoza, Spain.
Jazyk:	angličtina
Zdroj:	JMIR medical informatics [JMIR Med Inform] 2022 Feb 18; Vol. 10 (2), pp. e30345. Date of Electronic Publication: 2022 Feb 18.
DOI:	10.2196/30345
Abstrakt:	Background: The exploration of clinically relevant information in the free text of electronic health records (EHRs) holds the potential to positively impact clinical practice as well as knowledge regarding Crohn disease (CD), an inflammatory bowel disease that may affect any segment of the gastrointestinal tract. The EHRead technology, a clinical natural language processing (cNLP) system, was designed to detect and extract clinical information from narratives in the clinical notes contained in EHRs. Objective: The aim of this study is to validate the performance of the EHRead technology in identifying information of patients with CD. Methods: We used the EHRead technology to explore and extract CD-related clinical information from EHRs. To validate this tool, we compared the output of the EHRead technology with a manually curated gold standard to assess the quality of our cNLP system in detecting records containing any reference to CD and its related variables. Results: The validation metrics for the main variable (CD) were a precision of 0.88, a recall of 0.98, and an F1 score of 0.93. Regarding the secondary variables, we obtained a precision of 0.91, a recall of 0.71, and an F1 score of 0.80 for CD flare, while for the variable vedolizumab (treatment), a precision, recall, and F1 score of 0.86, 0.94, and 0.90 were obtained, respectively. Conclusions: This evaluation demonstrates the ability of the EHRead technology to identify patients with CD and their related variables from the free text of EHRs. To the best of our knowledge, this study is the first to use a cNLP system for the identification of CD in EHRs written in Spanish. (©Carmen Montoto, Javier P Gisbert, Iván Guerra, Rocío Plaza, Ramón Pajares Villarroya, Luis Moreno Almazán, María Del Carmen López Martín, Mercedes Domínguez Antonaya, Isabel Vera Mendoza, Jesús Aparicio, Vicente Martínez, Ignacio Tagarro, Alonso Fernandez-Nistal, Lea Canales, Sebastian Menke, Fernando Gomollón, PREMONITION-CD Study Group. Originally published in JMIR Medical Informatics (https://medinform.jmir.org), 18.02.2022.)
Databáze:	MEDLINE
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