title: Binding SNOMED CT terms to archetype elements. Establishing a baseline of results.
abstract: BACKGROUND
  This article is part of the Focus Theme of METHODS of Information in Medicine on "Managing Interoperability and Complexity in Health Systems".
  
  
  BACKGROUND
  The proliferation of archetypes as a means to represent information of Electronic Health Records has raised the need of binding terminological codes - such as SNOMED CT codes - to their elements, in order to identify them univocally. However, the large size of the terminologies makes it difficult to perform this task manually.
  
  
  OBJECTIVE
  To establish a baseline of results for the aforementioned problem by using off-the-shelf string comparison-based techniques against which results from more complex techniques could be evaluated.
  
  
  METHODS
  Nine Typed Comparison METHODS were evaluated for binding using a set of 487 archetype elements. Their recall was calculated and Friedman and Nemenyi tests were applied in order to assess whether any of the methods outperformed the others.
  
  
  RESULTS
  Using the qGrams method along with the 'Text' information piece of archetype elements outperforms the other methods if a level of confidence of 90% is considered. A recall of 25.26% is obtained if just one SNOMED CT term is retrieved for each archetype element. This recall rises to 50.51% and 75.56% if 10 and 100 elements are retrieved respectively, that being a reduction of more than 99.99% on the SNOMED CT code set.
  
  
  CONCLUSIONS
  The baseline has been established following the above-mentioned results. Moreover, it has been observed that although string comparison-based methods do not outperform more sophisticated techniques, they still can be an alternative for providing a reduced set of candidate terms for each archetype element from which the ultimate term can be chosen later in the more-than-likely manual supervision task.
authors.affiliation: Idoia Berges, Computer Science Faculty, University of the Basque Country, Paseo Manuel de Lardizabal, 1, 20018 Donostia - San Sebastián, Spain, E-mail: idoia.berges@ehu.es.
authors.forename: I
authors.initials: I
authors.lastname: Berges
authors.forename: J
authors.initials: J
authors.lastname: Bermudez
authors.forename: A
authors.initials: A
authors.lastname: Illarramendi
mesh_terms: D057286:Electronic Health Records; D012660:Semantics; D039061:Systematized Nomenclature of Medicine; D018511:Systems Integration
keywords: Archetype; SNOMED CT