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Visualizing and Validating Metadata Traceability within the CDISC Standards

The Food & Drug Administration has begun requiring that electronic submissions of regulated clinical studies utilize the Clinical Data Information Standards Consortium data standards. Within regulated clinical research, traceability is a requirement and indicates that the analysis results can be...

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Detalles Bibliográficos
Autores principales: Hume, Sam, Sarnikar, Surendra, Becnel, Lauren, Bennett, Dorine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Medical Informatics Association 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5543378/
https://www.ncbi.nlm.nih.gov/pubmed/28815125
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author Hume, Sam
Sarnikar, Surendra
Becnel, Lauren
Bennett, Dorine
author_facet Hume, Sam
Sarnikar, Surendra
Becnel, Lauren
Bennett, Dorine
author_sort Hume, Sam
collection PubMed
description The Food & Drug Administration has begun requiring that electronic submissions of regulated clinical studies utilize the Clinical Data Information Standards Consortium data standards. Within regulated clinical research, traceability is a requirement and indicates that the analysis results can be traced back to the original source data. Current solutions for clinical research data traceability are limited in terms of querying, validation and visualization capabilities. This paper describes (1) the development of metadata models to support computable traceability and traceability visualizations that are compatible with industry data standards for the regulated clinical research domain, (2) adaptation of graph traversal algorithms to make them capable of identifying traceability gaps and validating traceability across the clinical research data lifecycle, and (3) development of a traceability query capability for retrieval and visualization of traceability information.
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spelling pubmed-55433782017-08-16 Visualizing and Validating Metadata Traceability within the CDISC Standards Hume, Sam Sarnikar, Surendra Becnel, Lauren Bennett, Dorine AMIA Jt Summits Transl Sci Proc Articles The Food & Drug Administration has begun requiring that electronic submissions of regulated clinical studies utilize the Clinical Data Information Standards Consortium data standards. Within regulated clinical research, traceability is a requirement and indicates that the analysis results can be traced back to the original source data. Current solutions for clinical research data traceability are limited in terms of querying, validation and visualization capabilities. This paper describes (1) the development of metadata models to support computable traceability and traceability visualizations that are compatible with industry data standards for the regulated clinical research domain, (2) adaptation of graph traversal algorithms to make them capable of identifying traceability gaps and validating traceability across the clinical research data lifecycle, and (3) development of a traceability query capability for retrieval and visualization of traceability information. American Medical Informatics Association 2017-07-26 /pmc/articles/PMC5543378/ /pubmed/28815125 Text en ©2017 AMIA - All rights reserved. This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose
spellingShingle Articles
Hume, Sam
Sarnikar, Surendra
Becnel, Lauren
Bennett, Dorine
Visualizing and Validating Metadata Traceability within the CDISC Standards
title Visualizing and Validating Metadata Traceability within the CDISC Standards
title_full Visualizing and Validating Metadata Traceability within the CDISC Standards
title_fullStr Visualizing and Validating Metadata Traceability within the CDISC Standards
title_full_unstemmed Visualizing and Validating Metadata Traceability within the CDISC Standards
title_short Visualizing and Validating Metadata Traceability within the CDISC Standards
title_sort visualizing and validating metadata traceability within the cdisc standards
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5543378/
https://www.ncbi.nlm.nih.gov/pubmed/28815125
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