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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
Descripción
Sumario: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.