2006•Unpublished venueRequires access

Towards semantic interoperability in healthcare: ontology mapping from SNOMED-CT to HL7 version 3

Amanda Ryan

Open publisher page 41 citations

Abstract

One of the most successful Healthcare Information Models is version 2 of the Health Level 7 (HL7) standard. However, this standard has various problems, mainly its lack of semantic interoperability. This shortfall was addressed in HL7 Version 3, a newer standard which has been designed to solve this problem. Total semantic interoperability cannot be achieved without defined terminology, and to this end the use of the Systemised Nomenclature of Medicine - Clinical Terms (SNOMED-CT) is proposed. The difficulty arrives when deciding how to integrate the information model and the terminology. The line between where one ends and the other begins is often indistinct. This paper describes a proposal for normalising the two using ontology mapping and basing HL7 message models on SNOMED-CT concepts and their relationships, in an effort to further total semantic interoperability and seamless communication between healthcare entities.

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What this paper is about

One of the most successful Healthcare Information Models is version 2 of the Health Level 7 (HL7) standard. However, this standard has various problems, mainly its lack of semantic interoperability. This shortfall was addressed in HL7 Version 3, a newer standard which has been designed to solve this problem. Total semantic interoperability cannot be achieved without defined terminology, and to this end the use of the Systemised Nomenclature of Medicine - Clinical Terms (SNOMED-CT) is proposed. The difficulty arrives when deciding how to integrate the information model and the terminology. The line between where one ends and the other begins is often indistinct. This paper describes a proposal for normalising the two using ontology mapping and basing HL7 message models on SNOMED-CT concepts and their relationships, in an effort to further total semantic interoperability and seamless communication between healthcare entities.

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Available abstract

One of the most successful Healthcare Information Models is version 2 of the Health Level 7 (HL7) standard. However, this standard has various problems, mainly its lack of semantic interoperability. This shortfall was addressed in HL7 Version 3, a newer standard which has been designed to solve this problem. Total semantic interoperability cannot be achieved without defined terminology, and to this end the use of the Systemised Nomenclature of Medicine - Clinical Terms (SNOMED-CT) is proposed. The difficulty arrives when deciding how to integrate the information model and the terminology. The line between where one ends and the other begins is often indistinct. This paper describes a proposal for normalising the two using ontology mapping and basing HL7 message models on SNOMED-CT concepts and their relationships, in an effort to further total semantic interoperability and seamless communication between healthcare entities.

Key concepts: SNOMED CT, Systematized Nomenclature of Medicine, Terminology, Semantic interoperability, Interoperability, Computer science, Ontology, Information retrieval

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