Ontology Content Patterns as Bridge for the Semantic Representation of Clinical Information

C. Martínez-Costa; S. Schulz

doi:10.4338/ACI-2014-04-RA-0031

Applied Clinical Informatics, Inhaltsverzeichnis

Appl Clin Inform 2014; 05(03): 660-669
DOI: 10.4338/ACI-2014-04-RA-0031

Research Article

Schattauer GmbH

Ontology Content Patterns as Bridge for the Semantic Representation of Clinical Information

C. Martínez-Costa

¹Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Austria

,

S. Schulz

¹Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Austria

²Institute of Medical Biometry and Medical Informatics, Freiburg University Medical Center, Germany

› Institutsangaben

Abstract

Summary

Objective: Semantic interoperability of the Electronic Health Record (EHR) requires a rigorous and precise modelling of clinical information. Our objective is to facilitate the representation of clinical facts based on formal principles.

Methods: We here explore the potential of ontology content patterns, which are grounded on a formal and semantically rich ontology model and can be specialised and composed.

Results: We describe and apply two content patterns for the representation of data on tobacco use, rendered according to two heterogeneous models, represented in openEHR and in HL7 CDA. Finally, we provide some query exemplars that demonstrate a data interoperability use case.

Conclusion: The use of ontology content patterns facilitate the semantic representation of clinical information and therefore improve their semantic interoperability. There are open issues such as the scalability and performance of the approach if a logic-based language is used. Implementation decisions might determine the final degree of semantic interoperability, influenced by the state of the art of the semantic technologies.

Citation: Martínez-Costa C, Schulz S. Ontology content patterns as bridge for the semantic rRepresentation of clinical information Appl Clin Inf 2014; 5: 660–669

http://dx.doi.org/10.4338/ACI-2014-04-RA-0031

Keywords

Electronic Health Records - Semantics - SNOMED CT - Knowledge Representation - HL7 CDA - OpenEHR

Volltext

Referenzen

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