Identifying problematic concepts in SNOMED CT using a lexical approach

Ankur Agrawal, Yehoshua Perl, Gai Elhanan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Scopus citations


SNOMED CT (SCT) has been endorsed as a premier clinical terminology by many organizations with a perceived use within electronic health records and clinical information systems. However, there are indications that, at the moment, SCT is not optimally structured for its intended use by healthcare practitioners. A study is conducted to investigate the extent of inconsistencies among the concepts in SCT. A group auditing technique to improve the quality of SCT is introduced that can help identify problematic concepts with a high probability. Positional similarity sets are defined, which are groups of concepts that are lexically similar and the position of the differing word in the fully specified name of the concepts of a set that correspond to each other. A manual auditing of a sample of such sets found 38% of the sets exhibiting one or more inconsistent concepts. Group auditing techniques such as this can thus be very helpful to assure the quality of SCT, which will help expedite its adoption as a reference terminology for clinical purposes.

Original languageEnglish (US)
Title of host publicationMEDINFO 2013 - Proceedings of the 14th World Congress on Medical and Health Informatics
PublisherIOS Press
Number of pages5
ISBN (Print)9781614992882
StatePublished - 2013
Event14th World Congress on Medical and Health Informatics, MEDINFO 2013 - Copenhagen, Denmark
Duration: Aug 20 2013Aug 23 2013

Publication series

NameStudies in Health Technology and Informatics
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365


Other14th World Congress on Medical and Health Informatics, MEDINFO 2013

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management


  • Auditing
  • Electronic Health Record
  • Lexical Analysis
  • Meaningful Use
  • Quality Assurance


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