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Cross border semantic interoperability for learning health systems: The EHR4CR semantic resources and services

With the development of platforms enabling the integration and use of phenome, genome, and exposome data in the context of international research, data management challenges are increasing, and scalable solutions for cross border and cross domain semantic interoperability need to be developed. Reusi...

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Autores principales: Daniel, Christel, Ouagne, David, Sadou, Eric, Paris, Nicolas, Hussain, Sajjad, Jaulent, Marie‐Christine, Kalra, Dipak
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6516724/
https://www.ncbi.nlm.nih.gov/pubmed/31245551
http://dx.doi.org/10.1002/lrh2.10014
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author Daniel, Christel
Ouagne, David
Sadou, Eric
Paris, Nicolas
Hussain, Sajjad
Jaulent, Marie‐Christine
Kalra, Dipak
author_facet Daniel, Christel
Ouagne, David
Sadou, Eric
Paris, Nicolas
Hussain, Sajjad
Jaulent, Marie‐Christine
Kalra, Dipak
author_sort Daniel, Christel
collection PubMed
description With the development of platforms enabling the integration and use of phenome, genome, and exposome data in the context of international research, data management challenges are increasing, and scalable solutions for cross border and cross domain semantic interoperability need to be developed. Reusing routinely collected clinical data, especially, requires computable portable phenotype algorithms running across different electronic health record (EHR) products and healthcare systems. We propose a framework for describing and comparing mediation platforms enabling cross border phenotype identification within federated EHRs. This framework was used to describe the experience gained during the EHR4CR project and the evaluation of the platform developed for accessing semantically equivalent data elements across 11 European participating EHR systems from 5 countries. Developers of semantic interoperability platforms are beginning to address a core set of requirements in order to reach the goal of developing cross border semantic integration of data.
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spelling pubmed-65167242019-06-26 Cross border semantic interoperability for learning health systems: The EHR4CR semantic resources and services Daniel, Christel Ouagne, David Sadou, Eric Paris, Nicolas Hussain, Sajjad Jaulent, Marie‐Christine Kalra, Dipak Learn Health Syst Technical Report With the development of platforms enabling the integration and use of phenome, genome, and exposome data in the context of international research, data management challenges are increasing, and scalable solutions for cross border and cross domain semantic interoperability need to be developed. Reusing routinely collected clinical data, especially, requires computable portable phenotype algorithms running across different electronic health record (EHR) products and healthcare systems. We propose a framework for describing and comparing mediation platforms enabling cross border phenotype identification within federated EHRs. This framework was used to describe the experience gained during the EHR4CR project and the evaluation of the platform developed for accessing semantically equivalent data elements across 11 European participating EHR systems from 5 countries. Developers of semantic interoperability platforms are beginning to address a core set of requirements in order to reach the goal of developing cross border semantic integration of data. John Wiley and Sons Inc. 2016-10-21 /pmc/articles/PMC6516724/ /pubmed/31245551 http://dx.doi.org/10.1002/lrh2.10014 Text en © 2016 The Authors. Learning Health Systems published by Wiley Periodicals, Inc. on behalf of the University of Michigan This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Technical Report
Daniel, Christel
Ouagne, David
Sadou, Eric
Paris, Nicolas
Hussain, Sajjad
Jaulent, Marie‐Christine
Kalra, Dipak
Cross border semantic interoperability for learning health systems: The EHR4CR semantic resources and services
title Cross border semantic interoperability for learning health systems: The EHR4CR semantic resources and services
title_full Cross border semantic interoperability for learning health systems: The EHR4CR semantic resources and services
title_fullStr Cross border semantic interoperability for learning health systems: The EHR4CR semantic resources and services
title_full_unstemmed Cross border semantic interoperability for learning health systems: The EHR4CR semantic resources and services
title_short Cross border semantic interoperability for learning health systems: The EHR4CR semantic resources and services
title_sort cross border semantic interoperability for learning health systems: the ehr4cr semantic resources and services
topic Technical Report
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6516724/
https://www.ncbi.nlm.nih.gov/pubmed/31245551
http://dx.doi.org/10.1002/lrh2.10014
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