Using concept hierarchies to improve calculation of patient similarity

Dominic Girardi, Sandra Wartner, Gerhard Halmerbauer, Margit Ehrenmüller, Hilda Kosorus, Stephan Dreiseitl

Research output: Contribution to journalArticlepeer-review

29 Citations (Scopus)


Objective We introduce a new distance measure that is better suited than traditional methods at detecting similarities in patient records by referring to a concept hierarchy. Materials and methods The new distance measure improves on distance measures for categorical values by taking the path distance between concepts in a hierarchy into account. We evaluate and compare the new measure on a data set of 836 patients. Results The new measure shows marked improvements over the standard measures, both qualitatively and quantitatively. Using the new measure for clustering patient data reveals structure that is otherwise not visible. Statistical comparisons of distances within patient groups with similar diagnoses shows that the new measure is significantly better at detecting these similarities than the standard measures. Conclusion The new distance measure is an improvement over the current standard whenever a hierarchical arrangement of categorical values is available.

Original languageEnglish
Pages (from-to)66-73
Number of pages8
JournalJournal of Biomedical Informatics
Issue number1
Publication statusPublished - 1 Oct 2016


  • Distance measure using concept hierarchy
  • ICD-10 taxonomy
  • Patient similarity calculation


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