Extraction and Prevalence of Structured Data Elements in Free-Text Clinical Trial Eligibility Criteria.

Gulden C, Landerer I, Nassirian A, Altun FB, Andrae J (2019)

Publication Type: Book chapter / Article in edited volumes

Publication year: 2019

Journal

Studies in health technology and informatics IOS Press; 1999

Publisher: IOS Press

Edited Volumes: ICT for Health Science Research

Series: Studies in Health Technology and Informatics

Book Volume: 258

Pages Range: 226-230

DOI: 10.3233/978-1-61499-959-1-226

Abstract

Understanding the prevalence of structured data elements within clinical trial eligibility criteria is a crucial step for prioritizing integration efforts to supported automated patient recruitment into clinical trials based on electronic health record data. In this work, we extract data elements from 50 clinical trials using a collaborative, crowd-sourced, and iterative method. A total of 1.120 criteria were analyzed, and 204 unique data elements were extracted. The most prevalent elements were diagnosis code, procedure code, and medication code, occurring in 414 (37 %), 112 (10 %), and 91 (8 %) of eligibility criteria respectively. The results of this study may aid in optimizing data integration and documentation efforts in the EHR to support clinical trial eligibility determination.

Authors with CRIS profile

Christian Gulden Lehrstuhl für Medizinische Informatik

Involved external institutions

Universitätsklinikum Frankfurt am Main (KGU) DE Germany (DE) Albert-Ludwigs-Universität Freiburg DE Germany (DE) Technische Universität Dresden DE Germany (DE)

How to cite

APA:

Gulden, C., Landerer, I., Nassirian, A., Altun, F.B., & Andrae, J. (2019). Extraction and Prevalence of Structured Data Elements in Free-Text Clinical Trial Eligibility Criteria. In Amnon Shabo, Inge Madsen, Hans-Ulrich Prokosch, Kristiina Häyrinen, Klaus-Hendrik Wolf, Fernando Martin-Sanchez, Matthias Löbe, Thomas M. Deserno (Eds.), ICT for Health Science Research. (pp. 226-230). IOS Press.

MLA:

Gulden, Christian, et al. "Extraction and Prevalence of Structured Data Elements in Free-Text Clinical Trial Eligibility Criteria." ICT for Health Science Research. Ed. Amnon Shabo, Inge Madsen, Hans-Ulrich Prokosch, Kristiina Häyrinen, Klaus-Hendrik Wolf, Fernando Martin-Sanchez, Matthias Löbe, Thomas M. Deserno, IOS Press, 2019. 226-230.

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