Transformation of Standardized Clinical Models based on OWL technologies: from CEM to OpenEHR archetypes
(Paper submitted to Special Focus Issue on Biomedical Data Standards @ Journal of the American Medical Informatics Association )
Mari Carmen Legaz-García1*, Cui Tao2, Marcos Menárguez-Tortosa1, Jesualdo Tomás Fernández-Breis1, Christopher G. Chute3
- Departamento de Informática y Sistemas, Universidad de Murcia, IMIB-Arrixaca, 30100,
- School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX
- Department of Health Science Research, Mayo Clinic, Rochester, MN
* Correspondence author
Mari Carmen Legaz-García, Departamento de Informática y Sistemas, Universidad de Murcia, 30100,
phone: +34 868 88 8787
fax: +34 868 88 41 51
The semantic interoperability of Electronic Healthcare Records (EHR) systems is a major challenge in the medical informatics area. International initiatives pursue the use of semantically interoperable clinical models and ontologies have been frequently used in semantic interoperability efforts. The objective of this paper is to propose a generic, ontology-based, flexible approach for supporting the automatic transformation of clinical models, which is illustrated for the transformation of Clinical Element Models (CEM) into openEHR archetypes.
Our transformation method exploits the fact that the information models of the most relevant EHR specifications are available in the Web Ontology Language (OWL). The transformation approach is based on defining mappings between those ontological structures. We propose how CEM entities can be transformed into openEHR by using transformation templates and OWL as common representation formalism. The transformation architecture exploits the reasoning and inferencing capabilities of OWL technologies.
We have obtained a generic, flexible approach for the transformation of clinical models, implemented for the unidirectional transformation from CEM to openEHR, a series of reusable transformation templates, a proof-of-concept implementation, and a set of openEHR archetypes that validate the methodological approach.
We have been able to transform CEM into archetypes in an automatic, flexible, reusable transformation approach which could be extended to other clinical model specifications. We exploit the potential of OWL technologies for supporting the transformation process. We believe that our approach could be useful for international efforts in the area of semantic interoperability of EHR systems.