Mise en place d’une plateforme dédiée à la gestion des terminologies d’analyses biomédicales

  • Pierre-Yves Vandenbussche
  • Sylvie Cormont
  • Antoine Buemi
  • Jean Delahousse
  • Jean Charlet
  • Eric Lepage
Part of the Informatique et Santé book series (INFORMATIQUE, volume 1)

Abstract

Background and objectives. The AP-HP has developed a dictionary of biology independent from laboratory management systems (LMS). This dictionary is interfaced with the international nomenclature LOINC, and developed in collaboration with experts from all biological disciplines. Our goal is to establish a platform for publishing and maintaining the AP-HP laboratory data dictionary, which can satisfy both the requirements concerning the controlled vocabulary as those related to maintenance processes and distribution. Material and Methods. The complexity and volume of data show the need to establish a platform dedicated to the terminology management. This replaces the use of a spreadsheet tool that shows weaknesses in this case. After describing the dictionary, we identify requirements for the nomenclature management, and the inadequacy of existing software. Results. We describe how the modeling, data recovery and integration/verification steps in the new tool were used to meet these requirements. The core of our work is based on the modeling effort that takes into account multiple dimensions: (i) interoperability regarding data exchange standards, and (ii) dictionary evolution. This model has been implemented in the AP-HP context.

Keywords

Controlled vocabulary Authoring framework LOINC Biological Analysis Nomenclature Standardization 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Références

  1. [1]
    McDonald CJ, Huff SM, Suico JG et al. LOINC, a universal standard for identifying laboratory observations: a 5-year update. Clin Chem 2003; 49(4): 624–33CrossRefGoogle Scholar
  2. [2]
    Lin M, Vreeman D, McDonald C, Huff S. A Characterization of Local LOINC Mapping for Laboratory Tests in Three Large Institutions. Methods Inf Med 2010; 49(5)Google Scholar
  3. [3]
    Cormont S, Erman A, Burckel Y, Carayon A. Names-Lab: un modèle de normalisation des messages de biologie [Names-Lab: a model for the standardization of biology message exchanges]. Ann Biol Clin (Paris) 2002; 60(2): 173–81Google Scholar
  4. [4]
    Cormont S, Zweigenbaum P, Brunel L, Lepage É. Construction d’un référentiel francophone d’analyses biologiques lié à LOINC. Journées francophones d’informatique médical, Bamako, 11-12 janvier 2007Google Scholar
  5. [5]
    Daniel C, Buemi A, Mazuel L, Ouagne D, Charlet J. Functional requirements of terminology services for coupling interface terminologies to reference terminologies. Stud Health Technol Inform 2009; 150: 205–9Google Scholar
  6. [6]
    Si LE, Obrien A, Probets S. Integration of distributed terminology resources to facilitate subject cross-browsing for library portal systems. Aslib Proceedings 2010; 62(4/5): 415–427CrossRefGoogle Scholar
  7. [7]
    Isaac A, Schlobach S, Matthezing H, Zinn C. Integrated access to cultural heritage resources through representation and alignment of controlled vocabularies. Library Review 2009; 57(3): 187–199CrossRefGoogle Scholar
  8. [8]
    Macgregor G, Joseph A, Nicholson D. A skos core approach to implementing an m2m terminology mapping server. In: International Conference on Semantic Web and Digital Libraries (ICSD Proceedings of the) 2007; 21–23Google Scholar
  9. [9]
    Fung K, Bodenreider, O. Utilizing the UMLS for semantic mapping between terminologies. AMIA Annual Symposium Proceedings 2005; 266–270Google Scholar
  10. [10]
    Stenzhorn H, Bei§wanger E, Schulz, S. Towards a top-domain ontology for linking biomedical ontologies. Stud Health Technol Inform 2007; 129: 1225–1229Google Scholar
  11. [11]
    Gangemi A, Guarino N, Masolo C, Oltramari A, Schneider, L. Sweetening ontologies with DOLCE. Lecture notes in computer science, 2002; 166–181Google Scholar
  12. [12]
    Picca D, Gliozzo A, Gangemi A. LMM: an owl-dl metamodel to represent heterogeneous lexical knowledge. Proceedings of LREC, Marrakech, Morocco, 2008Google Scholar
  13. [13]
    Pathak J, Solbrig H, Buntrock J, Johnson T, Chute, C. LexGrid: A Framework for Representing, Storing, and Querying Biomedical Terminologies from Simple to Sublime. Journal of the American Medical Informatics Association 2009; 16: 305–315CrossRefGoogle Scholar
  14. [14]
    Aussenac-Gilles N. Méthodes ascendantes pour l’ingénierie des connaissances. Université Paul Sabatier, 2005Google Scholar
  15. [15]
    Miles A. SKOS: requirements for standardization. DC-2006: Proceedings of the International Conference on Dublin Core and Metadata Aplications 2006; 55–64Google Scholar
  16. [16]
    BS8723. Structured vocabularies for information retrieval, Part 4: Interoperability between vocabularies. British Standards Institution, 2008Google Scholar
  17. [17]
    Vandenbussche PY, Charlet J. Méta-modèle général de description de ressources terminologiques et ontologiques. In: Ingénierie de la Connaissance (IC), 2009Google Scholar
  18. [18]
    Noy N, Rector A. Defining N-ary relations on the Semantic Web: Use with individuals. W3C Working Draft, 2004Google Scholar
  19. [19]
    Vandenbussche PY, Charlet J. ConceptGroup pattern. Poster presentation. MedInfo, 2010Google Scholar

Copyright information

© Springer-Verlag France 2011

Authors and Affiliations

  • Pierre-Yves Vandenbussche
    • 1
    • 2
  • Sylvie Cormont
    • 3
  • Antoine Buemi
    • 3
  • Jean Delahousse
    • 1
  • Jean Charlet
    • 2
    • 4
  • Eric Lepage
    • 3
  1. 1.MondecaParisFrance
  2. 2.Inserm UMRS872 équipe 20ParisFrance
  3. 3.Centre de compétences et de servicesAssistance Publique-Hôpitaux de ParisParisFrance
  4. 4.Assistance Publique-Hôpitaux de ParisParisFrance

Personalised recommendations