Cross border semantic interoperability for learning health systems: The EHR4CR semantic resources and services. Issue 1 (21st October 2016)

• Record Type: Journal Article
• Authors: Daniel, Christel; Ouagne, David; Sadou, Eric; Paris, Nicolas; Hussain, Sajjad; Jaulent, Marie‐Christine; Kalra, Dipak
• Is Part Of: Learning health systems. Volume 1:Issue 1(2017)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2016-10-21
• Subjects: biomedical research -- data integration and standardization -- electronic health records -- interoperability -- knowledge representation -- terminology as topic; Medical care -- Research -- Periodicals; Medical informatics -- Periodicals; Health planning -- Periodicals; 362.1068
• DOI: 10.1002/lrh2.10014
• Languages: English
• ISSNs: 2379-6146

Abstract

Abstract: 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.