Semantic validation of the use of SNOMED CT in HL7 clinical documents

Abstract

<p>Abstract</p> <p>Background</p> <p>The HL7 Clinical Document Architecture (CDA) constrains the HL7 Reference Information model (RIM) to specify the format of HL7-compliant clinical documents, dubbed <it>CDA documents</it>. The use of clinical terminologies such as SNOMED CT<sup>® </sup>further improves interoperability as they provide a shared understanding of concepts used in clinical documents. However, despite the use of the RIM and of shared terminologies such as SNOMED CT<sup>®</sup>, gaps remain as to how to use both the RIM and SNOMED CT<sup>® </sup>in HL7 clinical documents. The HL7 implementation guide on <it>Using SNOMED CT in HL7 Version 3 </it>is an effort to close this gap. It is, however, a human-readable document that is not suited for automatic processing. As such, health care professionals designing clinical documents need to ensure validity of documents manually.</p> <p>Results</p> <p>We represent the CDA using the Ontology Web Language OWL and further use the OWL version of SNOMED CT<sup>® </sup>to enable the translation of CDA documents to so-called OWL <it>ontologies</it>. We formalize a subset of the constraints in the implementation guide on <it>Using SNOMED CT in HL7 Version 3 </it>as OWL <it>Integrity Constraints </it>and show that we can automatically validate CDA documents using OWL reasoners such as Pellet. Finally, we evaluate our approach via a prototype implementation that plugs in the Open Health Workbench.</p> <p>Conclusions</p> <p>We present a methodology to automatically check the validity of CDA documents which make reference to SNOMED CT<sup>® </sup>terminology. The methodology relies on semantic technologies such as OWL. As such it removes the burden from IT health care professionals of having to manually implement such guidelines in systems that use HL7 Version 3 documents.</p

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