Transformation of standardized clinical models based on OWL technologies: from CEM to OpenEHR archetypes

• Published in: Journal of the American Medical Informatics Association : JAMIA Vol. 22; no. 3; pp. 536 - 544
• Main Authors: Legaz-García, María del Carmen, Menárguez-Tortosa, Marcos, Fernández-Breis, Jesualdo Tomás, Chute, Christopher G, Tao, Cui
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 01.05.2015
• Subjects: Biological Ontologies; Electronic Health Records - standards; Internet; Programming Languages; Semantics; Special Focus on Standards; Systems Integration; semantic interoperability; archetype; electronic health records; OWL; Clinical Element Model
• ISSN: 1067-5027; 1527-974X
• DOI: 10.1093/jamia/ocu027

Introduction The semantic interoperability of electronic healthcare records (EHRs) systems is a major challenge in the medical informatics area. International initiatives pursue the use of semantically interoperable clinical models, and ontologies have frequently been 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 (CEMs) into openEHR archetypes. Methods 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 a way in which 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. Results We have devised 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. Conclusions We have been able to transform CEM into archetypes in an automatic, flexible, reusable transformation approach that 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.