title: Textual inference for eligibility criteria resolution in clinical trials.
abstract: Clinical trials are essential for determining whether new interventions are effective. In order to determine the eligibility of patients to enroll into these trials, clinical trial coordinators often perform a manual review of clinical notes in the electronic health record of patients. This is a very time-consuming and exhausting task. Efforts in this process can be expedited if these coordinators are directed toward specific parts of the text that are relevant for eligibility determination. In this study, we describe the creation of a dataset that can be used to evaluate automated methods capable of identifying sentences in a note that are relevant for screening a patient's eligibility in clinical trials. Using this dataset, we also present results for four simple methods in natural language processing that can be used to automate this task. We found that this is a challenging task (maximum F-score=26.25), but it is a promising direction for further research.
authors.affiliation: Department of Computer Science and Engineering, The Ohio State University, Columbus, OH, USA. Electronic address: shivade@cse.ohio-state.edu.
authors.forename: Chaitanya
authors.initials: C
authors.lastname: Shivade
authors.affiliation: Department of Biomedical Informatics, The Ohio State University, Columbus, OH, USA.
authors.forename: Courtney
authors.initials: C
authors.lastname: Hebert
authors.affiliation: Department of Biomedical Informatics, The Ohio State University, Columbus, OH, USA; Clínica Alemana de Santiago, Facultad de Medicina Clínica Alemana, Universidad del Desarrollo, Santiago, Chile.
authors.forename: Marcelo
authors.initials: M
authors.lastname: Lopetegui
authors.affiliation: Department of Linguistics, The Ohio State University, Columbus, OH, USA.
authors.forename: Marie-Catherine
authors.initials: MC
authors.lastname: de Marneffe
authors.affiliation: Department of Computer Science and Engineering, The Ohio State University, Columbus, OH, USA.
authors.forename: Eric
authors.initials: E
authors.lastname: Fosler-Lussier
authors.affiliation: Department of Biomedical Informatics, The Ohio State University, Columbus, OH, USA.
authors.forename: Albert M
authors.initials: AM
authors.lastname: Lai
mesh_terms: D002986:Clinical Trials as Topic / Q000379:methods*; D057225:Data Mining / Q000379:methods*; D057286:Electronic Health Records / Q000458:organization & administration*; D004608:Eligibility Determination / Q000379:methods*; D006801:Humans; D009323:Natural Language Processing; D018579:Patient Selection; D010363:Pattern Recognition, Automated / Q000379:methods; D018875:Vocabulary, Controlled
keywords: Clinical trials; Electronic health records; Natural language processing; Textual inference