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Simplifying Complex Clinical Element Models to Encourage Adoption

Clinical Element Models (CEMs) were developed to provide a normalized form for the exchange of clinical data. The CEM specification is quite complex and specialized knowledge is required to understand and implement the models, which presents a significant barrier to investigators and study designers...

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Detalles Bibliográficos
Autores principales: Freimuth, Robert R., Zhu, Qian, Pathak, Jyotishman, Chute, Christopher G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Medical Informatics Association 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4419759/
https://www.ncbi.nlm.nih.gov/pubmed/25954573
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author Freimuth, Robert R.
Zhu, Qian
Pathak, Jyotishman
Chute, Christopher G.
author_facet Freimuth, Robert R.
Zhu, Qian
Pathak, Jyotishman
Chute, Christopher G.
author_sort Freimuth, Robert R.
collection PubMed
description Clinical Element Models (CEMs) were developed to provide a normalized form for the exchange of clinical data. The CEM specification is quite complex and specialized knowledge is required to understand and implement the models, which presents a significant barrier to investigators and study designers. To encourage the adoption of CEMs at the time of data collection and reduce the need for retrospective normalization efforts, we developed an approach that provides a simplified view of CEMs for non-experts while retaining the full semantic detail of the underlying logical models. This allows investigators to approach CEMs through generalized representations that are intended to be more intuitive than the native models, and it permits them to think conceptually about their data elements without worrying about details related to the CEM logical models and syntax. We demonstrate our approach using data elements from the Pharmacogenomics Research Network (PGRN).
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spelling pubmed-44197592015-05-07 Simplifying Complex Clinical Element Models to Encourage Adoption Freimuth, Robert R. Zhu, Qian Pathak, Jyotishman Chute, Christopher G. AMIA Jt Summits Transl Sci Proc Articles Clinical Element Models (CEMs) were developed to provide a normalized form for the exchange of clinical data. The CEM specification is quite complex and specialized knowledge is required to understand and implement the models, which presents a significant barrier to investigators and study designers. To encourage the adoption of CEMs at the time of data collection and reduce the need for retrospective normalization efforts, we developed an approach that provides a simplified view of CEMs for non-experts while retaining the full semantic detail of the underlying logical models. This allows investigators to approach CEMs through generalized representations that are intended to be more intuitive than the native models, and it permits them to think conceptually about their data elements without worrying about details related to the CEM logical models and syntax. We demonstrate our approach using data elements from the Pharmacogenomics Research Network (PGRN). American Medical Informatics Association 2014-04-07 /pmc/articles/PMC4419759/ /pubmed/25954573 Text en ©2014 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
Freimuth, Robert R.
Zhu, Qian
Pathak, Jyotishman
Chute, Christopher G.
Simplifying Complex Clinical Element Models to Encourage Adoption
title Simplifying Complex Clinical Element Models to Encourage Adoption
title_full Simplifying Complex Clinical Element Models to Encourage Adoption
title_fullStr Simplifying Complex Clinical Element Models to Encourage Adoption
title_full_unstemmed Simplifying Complex Clinical Element Models to Encourage Adoption
title_short Simplifying Complex Clinical Element Models to Encourage Adoption
title_sort simplifying complex clinical element models to encourage adoption
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4419759/
https://www.ncbi.nlm.nih.gov/pubmed/25954573
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