Tracking Changes for Inter-Version Interoperability in Heterogeneous Evolving Medical Terminologies.
Autor: | Schäfermeier R; Institute for Medical Informatics, Statistics and Epidemiology (IMISE), Leipzig University, Leipzig, Germany., Beger C; Institute for Medical Informatics, Statistics and Epidemiology (IMISE), Leipzig University, Leipzig, Germany., Matthies F; Institute for Medical Informatics, Statistics and Epidemiology (IMISE), Leipzig University, Leipzig, Germany., Hoeffner K; Institute for Medical Informatics, Statistics and Epidemiology (IMISE), Leipzig University, Leipzig, Germany., Uciteli A; Institute for Medical Informatics, Statistics and Epidemiology (IMISE), Leipzig University, Leipzig, Germany. |
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Jazyk: | angličtina |
Zdroj: | Studies in health technology and informatics [Stud Health Technol Inform] 2024 Aug 30; Vol. 317, pp. 190-199. |
DOI: | 10.3233/SHTI240855 |
Abstrakt: | Introduction: Medical terminologies and code systems, which play a vital role in the health domain, are rarely static but undergo changes as knowledge and terminology evolves. This includes addition, deletion and relabeling of terms, and, if terms are organized hierarchically, changing their position. Tracking these changes may become important if one uses multiple versions of the same terminology and interoperability is desired. Method: We propose a new method for automatic change tracking between terminology versions. It consists of a declarative import pipeline, which translates source terminologies into a common data model. We then use semantic and lexical change detection algorithms. They produce an ontology-based representation of terminology changes, which can be queried using semantic query languages. Results: The method proves accurate in detecting additions, deletions, relocations and renaming of terms. In cases where inter-version term mapping information is provided by the publisher, we were able to highly enhance the ability to differentiate between simple additions/deletions and refinements/consolidation of terms. Conclusion: The method proves effective for semi-automatic change handling if term refinements and consolidation are relevant and for automatic change detection if additional mapping information is available. |
Databáze: | MEDLINE |
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