Using ontologies to improve semantic interoperability in health data
- PMID: 26245245
- DOI: 10.14236/jhi.v22i2.159
Using ontologies to improve semantic interoperability in health data
Abstract
The present-day health data ecosystem comprises a wide array of complex heterogeneous data sources. A wide range of clinical, health care, social and other clinically relevant information are stored in these data sources. These data exist either as structured data or as free-text. These data are generally individual person-based records, but social care data are generally case based and less formal data sources may be shared by groups. The structured data may be organised in a proprietary way or be coded using one-of-many coding, classification or terminologies that have often evolved in isolation and designed to meet the needs of the context that they have been developed. This has resulted in a wide range of semantic interoperability issues that make the integration of data held on these different systems changing. We present semantic interoperability challenges and describe a classification of these. We propose a four-step process and a toolkit for those wishing to work more ontologically, progressing from the identification and specification of concepts to validating a final ontology. The four steps are: (1) the identification and specification of data sources; (2) the conceptualisation of semantic meaning; (3) defining to what extent routine data can be used as a measure of the process or outcome of care required in a particular study or audit and (4) the formalisation and validation of the final ontology. The toolkit is an extension of a previous schema created to formalise the development of ontologies related to chronic disease management. The extensions are focused on facilitating rapid building of ontologies for time-critical research studies.
Keywords: data integration; electronic health records; interoperability; ontology; semantic.
Comment in
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In this issue: Ontologies a key concept in informatics and key for open definitions of cases, exposures, and outcome measures.J Innov Health Inform. 2015 Jul 10;22(2):170. doi: 10.14236/jhi.v22i2.170. J Innov Health Inform. 2015. PMID: 26245238 No abstract available.
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