Managing Theoretical Single-Disease Guideline Recommendations for Actual Multiple-Disease Patients

  • Gersende Georg
  • Brigitte Séroussi
  • Jacques Bouaud
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2780)


Situations managed by clinical practice guidelines (CPGs) usually correspond to general descriptions of theoretical patients that suffer from only one disease in addition to the specific pathology CPGs focus on. When building knowledge bases, the lack of decision support for complex multiple-disease patients is usually transferred to computer-based systems. Starting from a GEM-encoded instance of CPGs, we developed a module that automatically generated IF-THEN-WITH decision rules. A two-stage unification process has been implemented. All the rules whose IF-part was in partial matching with a patient clinical profile were triggered. A synthesis of triggered rules has then been performed to eliminate redundancies and incoherence. All remaining, eventually competitive, recommendations are finally displayed to physicians leaving them the control and the responsibility of handling the controversy and thus the opportunity to make informed decisions.


Inference Engine Partial Match Relevant Recommendation Trigger Rule Numerous Disorder 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Feldman, R.D., Campbell, N., Larochelle, P., Bolli, P., Burgess, E.D., Carruthers, S.G., et al.: Recommandations de 1999 pour le traitement de l’hypertension artérielle au Canada. CMAJ 161(12), SF1-25 (1999); URL:
  2. 2.
    Shiffman, R.N., Karras, B.T., Agrawal, A., Chen, R., Marenco, L., Nath, S.: GEM: a proposal for a more comprehensive guideline document model using XML. J. Am. Med. Inform. Assoc. 7(5), 488–498 (2000)Google Scholar
  3. 3.
    Georg, G., Séroussi, B., Bouaud, J.: Interpretative framework of chronic disease management to guide textual guideline GEM-encoding. In: Baud, R., Fieschi, M., Le Beux, P., Ruch, P. (eds.) Proceedings of MIE 2003, pp. 531–536. IOS Press, Amsterdam (2003)Google Scholar
  4. 4.
    Zadeh, L.A.: Fuzzy sets. Information and Control 8(3), 338–353 (1965)zbMATHCrossRefMathSciNetGoogle Scholar
  5. 5.
    Liu, J.C.S., Shiffman, R.N.: Operationalization of clinical practice guidelines using fuzzy logic. J. Am. Med. Inform. Assoc. 4(4), 283–287 (1997)Google Scholar
  6. 6.
    Séroussi, B., Bouaud, J., Dréau, H., Falcoff, H., Riou, C., Joubert, M., Simon, C., Simon, G., Venot, A.: ASTI: A guideline-based drug-ordering system for primary care. In: Patel V.L., Rogers R., Haux R. (eds) Medinfo 84(1), 528–532 (2001)Google Scholar
  7. 7.

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Gersende Georg
    • 1
  • Brigitte Séroussi
    • 1
  • Jacques Bouaud
    • 1
  1. 1.STIM, DPA / DSI / AP-HPMission Recherche en Sciences et Technologies de l’Information MédicaleParisFrance

Personalised recommendations