title: Feasibility of Extracting Key Elements from ClinicalTrials.gov to Support Clinicians' Patient Care Decisions.
abstract: Motivation:Clinicians need up-to-date evidence from high quality clinical trials to support clinical decisions. However, applying evidence from the primary literature requires significant effort.Objective:To examine the feasibility of automatically extracting key clinical trial information from ClinicalTrials.gov.Methods:We assessed the coverage of ClinicalTrials.gov for high quality clinical studies that are indexed in PubMed. Using 140 random ClinicalTrials.gov records, we developed and tested rules for the automatic extraction of key information.Results:The rate of high quality clinical trial registration in ClinicalTrials.gov increased from 0.2% in 2005 to 17% in 2015. Trials reporting results increased from 3% in 2005 to 19% in 2015. The accuracy of the automatic extraction algorithm for 10 trial attributes was 90% on average. Future research is needed to improve the algorithm accuracy and to design information displays to optimally present trial information to clinicians.
authors.affiliation: School of Information and Library Science, University of North Carolina, Chapel Hill,NC, USA.
authors.forename: Heejun
authors.initials: H
authors.lastname: Kim
authors.affiliation: Department of Biomedical Informatics, University of Utah, Salt Lake City, UT, USA.
authors.forename: Jiantao
authors.initials: J
authors.lastname: Bian
authors.affiliation: School of Information and Library Science, University of North Carolina, Chapel Hill,NC, USA.
authors.forename: Javed
authors.initials: J
authors.lastname: Mostafa
authors.affiliation: Division of Health and Biomedical Informatics, Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
authors.forename: Siddhartha
authors.initials: S
authors.lastname: Jonnalagadda
authors.affiliation: Division of Health and Biomedical Informatics, Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
authors.forename: Guilherme
authors.initials: G
authors.lastname: Del Fiol
mesh_terms: D000465:Algorithms; D002986:Clinical Trials as Topic / Q000592:standards / Q000706:statistics & numerical data*; D016208:Databases, Factual; D019317:Evidence-Based Medicine; D005240:Feasibility Studies; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods; D005791:Patient Care; D039781:PubMed