Will Semantic Web Technologies Work for the Development of ICD-11?

  • Tania Tudorache
  • Sean Falconer
  • Csongor Nyulas
  • Natalya F. Noy
  • Mark A. Musen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6497)


The World Health Organization is beginning to use Semantic Web technologies in the development of the 11th revision of the International Classification of Diseases (ICD-11). Health officials use ICD in all United Nations member countries to compile basic health statistics, to monitor health-related spending, and to inform policy makers. While previous revisions of ICD encoded minimal information about a disease, and were mainly published as books and tabulation lists, the creators of ICD-11 envision that it will become a multi-purpose and coherent classification ready for electronic health records. Most important, they plan to have ICD-11 applied for a much broader variety of uses than previous revisions. The new requirements entail significant changes in the way we represent disease information, as well as in the technologies and processes that we use to acquire the new content. In this paper, we describe the previous processes and technologies used for developing ICD. We then describe the requirements for the new development process and present the Semantic Web technologies that we use for ICD-11. We outline the experiences of the domain experts using the software system that we implemented using Semantic Web technologies. We then discuss the benefits and challenges in following this approach and conclude with lessons learned from this experience.


Domain Expert Electronic Health Record Content Model Beta Phase Access Policy 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Tania Tudorache
    • 1
  • Sean Falconer
    • 1
  • Csongor Nyulas
    • 1
  • Natalya F. Noy
    • 1
  • Mark A. Musen
    • 1
  1. 1.Stanford Center for Biomedical Informatics ResearchStanford University, USUSA

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