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access icon free To what extent can prescriptions be meaningfully exchanged between primary care terminologies? A case study of four western European classification systems

© The Institution of Engineering and Technology
Received 29/11/2016, Accepted 25/06/2017, Revised 06/06/2017, Published 14/07/2017

The diversity of terminologies used in primary care causes significant challenges regarding semantic interoperability. Attempts to address these challenges usually focus on the creation of metaterminologies, with the peculiarities of national variations of terminologies being overlooked. In this study the extent to which primary care data can be meaningfully exchanged between nationally implemented terminologies is assessed using a rule-based approach. To determine this, a model comprising primary care terminologies and including axioms to define their relations was developed. Generic metrics were designed to determine the completeness and accuracy of any two arbitrary vocabularies within an ontological model. These metrics were used on an implementation of the model to determine the data quality that is preserved when expressing similar data in different primary care terminologies. The results show that values of terminologies which are closely related can express each other's concepts relatively well. The authors conclude that the current state of accuracy and completeness between primary care terminologies does not allow for sufficiently meaningful semantic interoperability, but that their approach of mapping lower-level terminologies to each other next to an ontological approach may yield better results than relying solely on the latter.

Inspec keywords: open systems; health care; semantic networks; ontologies (artificial intelligence)

Other keywords: metaterminologies; nationally implemented terminologies; rule-based approach; generic metrics; ontological model; semantic interoperability; primary care terminologies; lower-level terminology mapping; data quality; western European classification systems; arbitrary vocabularies

Subjects: Biology and medical computing; Medical administration; Knowledge engineering techniques

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