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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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2016
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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. |
format | Online Article Text |
id | pubmed-6516724 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
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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