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Ontological Representation of Laboratory Test Observables: Challenges and Perspectives in the SNOMED CT Observable Entity Model Adoption

  • Mélissa MaryEmail author
  • Lina F. Soualmia
  • Xavier Gansel
  • Stéfan Darmoni
  • Daniel Karlsson
  • Stefan Schulz
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10259)

Abstract

The emergence of electronic health records has highlighted the need for semantic standards for representation of observations in laboratory medicine. Two such standards are LOINC, with a focus on detailed encoding of lab tests, and SNOMED CT, which is more general, including the representation of qualitative and ordinal test results. In this paper we will discuss how lab observation entries can be represented using SNOMED CT. We use resources provided by the Regenstrief Institute and SNOMED International collaboration, which formalize LOINC terms as SNOMED CT post-coordinated expressions. We demonstrate the benefits brought by SNOMED CT to classify lab tests. We then propose a SNOMED CT based model for lab observation entries aligned with the BioTopLite2 (BTL2) upper level ontology. We provide examples showing how a model designed with no ontological foundation can produce misleading interpretations of inferred observation results. Our solution based on a BTL2 conformant formal interpretation of SNOMED CT concepts allows representing lab test without creating unintended models. We argue in favour of an ontologically explicit bridge between compositional clinical terminologies, in order to safely use their formal representations in intelligent systems.

Keywords

Biomedical ontologies and terminologies LOINC SNOMED CT BioTopLite2 

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Department of System and DevelopmentbioMérieuxLa-Balme-Les-GrottesFrance
  2. 2.LITIS EA 4108, Normandy University, University of RouenRouenFrance
  3. 3.French National Institutes for Health (INSERM), LIMICS UMR_1142ParisFrance
  4. 4.Department of Biomedical Engineering/Health InformaticsLinköping UniversityLinköpingSweden
  5. 5.Institute of Medical Informatics, Statistics and DocumentationMedical University of GrazGrazAustria

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