Güngör B, Deppenwiese N, Mang JM, Toddenroth D (2022)
Publication Type: Book chapter / Article in edited volumes
Publication year: 2022
Edited Volumes: pHealth 2022
Series: Studies in Health Technology and Informatics
Book Volume: 299
Pages Range: 217-222
DOI: 10.3233/SHTI220987
Mapping clinical attributes from hospital information systems to standardized terminologies may allow their scientific reuse for multicenter studies. The Unified Medical Language System (UMLS) defines synonyms in different terminologies, which could be valuable for achieving semantic interoperability between different sites. Here we aim to explore the potential relevance of UMLS concepts and associated semantic relations for widely used clinical terminologies in a German university hospital. To semi-automatically examine a sample of the 200 most frequent codes from Erlangen University Hospital for three relevant terminologies, we implemented a script that queries their UMLS representation and associated mappings via a programming interface. We found that 94% of frequent diagnostic codes were available in UMLS, and that most of these codes could be mapped to other terminologies such as SNOMED CT. We observed that all examined laboratory codes were represented in UMLS, and that various translations to other languages were available for these concepts. The classification that is most widely used in German hospital for documenting clinical procedures was not originally represented in UMLS, but external mappings to SNOMED CT allowed identifying UMLS entries for 90.5% of frequent codes. Future research could extend this investigation to other code sets and terminologies, or study the potential utility of available mappings for specific applications.
APA:
Güngör, B., Deppenwiese, N., Mang, J.M., & Toddenroth, D. (2022). Analysis of the Representation of Frequent Clinical Attributes in the Unified Medical Language System. In Bernd Blobel, Bian Yang, Mauro Giacomini (Eds.), pHealth 2022. (pp. 217-222).
MLA:
Güngör, Baris, et al. "Analysis of the Representation of Frequent Clinical Attributes in the Unified Medical Language System." pHealth 2022. Ed. Bernd Blobel, Bian Yang, Mauro Giacomini, 2022. 217-222.
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