Randomized clinical trials (RCTs) are one of the best sources of evidence for the scientific practice of medicine. However, it is increasingly becoming apparent that the reporting of trials is plagued by bias towards publication of positive trials, and by biased, selective reporting of trial designs and results. In response to this recognition, various international and legislative groups have proposed and implemented policies mandating trial registration and increased disclosure of trial results. In this climate of heightened attention to the importance and challenges of trial reporting, the Trial Bank Project offers a unique and significant solution. Specifically, we have developed the world's only computable RCT knowledge base (called RCT Bank) that can capture all the details of trial design, execution, and results that are needed to critically appraise a trial or to apply it to clinical care. With over 10,000 new RCTs completed worldwide each year, computer-based knowledge management of RCTs is necessary, and capturing trial information into detailed, computable knowledge bases is the only approach that will allow the full use of information technologies to advance clinical science and practice. The Trial Bank Project therefore addresses a grave, widely recognized problem, and does so by providing a strong trial-reporting informatics infrastructure upon which other informatics solutions can be built over time. Our prior work has demonstrated our ability to capture a capture a wide variety of trials into RCT Bank. We also demonstrated proof of concept for publishing RCTs as both traditional journal articles and as entries into RCT Bank. Users rated our trial-bank reports extremely favorably compared to traditional journal articles. This success has led to the creation of Open Trial Bank, an independent organization providing a global, open access, peer-reviewed repository of computable RCT protocols and results. This proposal seeks to further develop the informatics science underlying the Trial Bank Project, to solidify the foundation upon which computable trial protocols and results can be used to further clinical science and practice.
We aim to expand our data modeling, to test novel approaches to capturing trial protocol and results information in computable form at various points in the trial life cycle, and to demonstrate the benefits of computable trial information for computer-assisted quality evaluation and use of RCT evidence.

National Institute of Health (NIH)
National Library of Medicine (NLM)
Research Project (R01)
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Biomedical Library and Informatics Review Committee (BLR)
Program Officer
Sim, Hua-Chuan
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University of California San Francisco
Internal Medicine/Medicine
Schools of Medicine
San Francisco
United States
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Sim, Ida; Tu, Samson W; Carini, Simona et al. (2014) The Ontology of Clinical Research (OCRe): an informatics foundation for the science of clinical research. J Biomed Inform 52:78-91
Tu, Samson W; Peleg, Mor; Carini, Simona et al. (2011) A practical method for transforming free-text eligibility criteria into computable criteria. J Biomed Inform 44:239-50
Sim, Ida; Carini, Simona; Tu, Samson et al. (2010) The human studies database project: federating human studies design data using the ontology of clinical research. AMIA Jt Summits Transl Sci Proc 2010:51-5
Ross, Jessica; Tu, Samson; Carini, Simona et al. (2010) Analysis of eligibility criteria complexity in clinical trials. AMIA Jt Summits Transl Sci Proc 2010:46-50
Kiritchenko, Svetlana; de Bruijn, Berry; Carini, Simona et al. (2010) ExaCT: automatic extraction of clinical trial characteristics from journal publications. BMC Med Inform Decis Mak 10:56
de Bruijn, Berry; Carini, Simona; Kiritchenko, Svetlana et al. (2008) Automated information extraction of key trial design elements from clinical trial publications. AMIA Annu Symp Proc :141-5
Lee, Kirby; Bacchetti, Peter; Sim, Ida (2008) Publication of clinical trials supporting successful new drug applications: a literature analysis. PLoS Med 5:e191
Berlin, Amy; Sorani, Marco; Sim, Ida (2006) A taxonomic description of computer-based clinical decision support systems. J Biomed Inform 39:656-67
Sim, Ida; Olasov, Ben; Carini, Simona (2004) An ontology of randomized controlled trials for evidence-based practice: content specification and evaluation using the competency decomposition method. J Biomed Inform 37:108-19
Sim, Ida; Carini, Simona; Olasov, Ben et al. (2004) Trial bank publishing: phase I results. Medinfo 11:1476-80

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