Literature DB >> 11079979

Knowledge representation and tool support for critiquing clinical trial protocols.

D L Rubin1, J Gennari, M A Musen.   

Abstract

The increasing complexities of clinical trials have led to increasing costs for investigators and organizations that author and administer those trials. The process of authoring a clinical trial protocol, the document that specifies the details of the study, is usually a manual task, and thus authors may introduce subtle errors in medical and procedural content. We have created a protocol inspection and critiquing tool (PICASSO) that evaluates the procedural aspects of a clinical trial protocol. To implement this tool, we developed a knowledge base for clinical trials that contains knowledge of the medical domain (diseases, drugs, lab tests, etc.) and of specific requirements for clinical trial protocols (eligibility criteria, patient treatments, and monitoring activities). We also developed a set of constraints, expressed in a formal language, that describe appropriate practices for authoring clinical trials. If a clinical trial designed with PICASSO violates any of these constraints, PICASSO generates a message to the user and a list of inconsistencies for each violated constraint. To test our methodology, we encoded portions of a hypothetical protocol and implemented designs consistent and inconsistent with known clinical trial practice. Our hope is that this methodology will be useful for standardizing new protocols and improving their quality.

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Year:  2000        PMID: 11079979      PMCID: PMC2243914     

Source DB:  PubMed          Journal:  Proc AMIA Symp        ISSN: 1531-605X


  9 in total

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Authors:  J Silva; R Wittes
Journal:  Proc AMIA Symp       Date:  1999

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Journal:  Methods Inf Med       Date:  1993-08       Impact factor: 2.176

Review 9.  Tracing expert thinking in clinical trial design.

Authors:  M H Malogolowkin; R S Horowitz; J A Ortega; S E Siegel; G D Hammond; J M Weiner
Journal:  Comput Biomed Res       Date:  1989-04
  9 in total
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6.  Leveraging Real-World Data for the Selection of Relevant Eligibility Criteria for the Implementation of Electronic Recruitment Support in Clinical Trials.

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  6 in total

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