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Clinical data interoperability based on archetype transformation

Interoperability scenario between two EHR systems based on dual-model architecture. The methodology proposed in this work for the exchange of data consists of two transformation steps: (1) archetype transformation and (2) data transformation. [Display omitted] ► In this paper we propose a method for...

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Bibliographic Details
Published in:Journal of biomedical informatics 2011-10, Vol.44 (5), p.869-880
Main Authors: Martinez Costa, Catalina, Menarguez-Tortosa, Marcos, Fernandez-Breis, Jesualdo Tomas
Format: Article
Language:English
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Summary:Interoperability scenario between two EHR systems based on dual-model architecture. The methodology proposed in this work for the exchange of data consists of two transformation steps: (1) archetype transformation and (2) data transformation. [Display omitted] ► In this paper we propose a method for transforming EHR extracts data from ISO 13606 from/to openEHR. ► The method for data transformation is based on the transformation of the archetype used for capturing the data and can be applied to other standards. ► The method has been implemented in the Poseacle Converter, which is publicly available. The semantic interoperability between health information systems is a major challenge to improve the quality of clinical practice and patient safety. In recent years many projects have faced this problem and provided solutions based on specific standards and technologies in order to satisfy the needs of a particular scenario. Most of such solutions cannot be easily adapted to new scenarios, thus more global solutions are needed. In this work, we have focused on the semantic interoperability of electronic healthcare records standards based on the dual model architecture and we have developed a solution that has been applied to ISO 13606 and openEHR. The technological infrastructure combines reference models, archetypes and ontologies, with the support of Model-driven Engineering techniques. For this purpose, the interoperability infrastructure developed in previous work by our group has been reused and extended to cover the requirements of data transformation.
ISSN:1532-0464
1532-0480
DOI:10.1016/j.jbi.2011.05.006