A Semantic Clinical Knowledge Representation Framework for Effective Health Care Risk Management

  • Ermelinda Oro
  • Massimo Ruffolo
  • Domenico Sacca
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 21)


A process-oriented vision of clinical practices may allow to enhance patient safety by enabling better risks management capabilities. In the field of clinical information systems less attention has been paid to approaches aimed at reducing risks and errors by integrating both declarative and procedural aspects of medical knowledge. This work describes a semantic clinical knowledge representation framework that allows representing and managing, in a unified way, both medical knowledge and clinical processes and supports execution of clinical process taking into account risk handling. Framework features are presented by using a running example inspired by the clinical process adopted for caring breast neoplasm in the oncological ward of an Italian hospital. The example shows how the proposed framework can contribute to reduce risks.


Semantic Business Process Management Ontology Knowledge Representation and Reasoning Workflow Representation Logic Programming Health Care Information Systems 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Classification Commune des Actes Médicaux (CCAM),
  2. 2.
    Current Procedural Terminology (CPT): a registered trademark of the American Medical Association (AMA),
  3. 3.
    International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM),
  4. 4.
    World Health Organization (WHO),
  5. 5.
    Logical Observation Identifiers Names and Codes (LOINC),
  6. 6.
    The Office of Population Censuses and Surveys Classification of Surgical Operations and Procedures, 4th Revision (OPCS-4),
  7. 7.
    Systematized Nomenclature of Medicine-Clinical Terms,
  8. 8.
    Medical Subject headings (MeSH),
  9. 9.
    Unified medical Language System (UMLS),
  10. 10.
    Sackett, D.L., Rosenberg, W.M.C., Gray, M.J.A., Haynes, B.R., Richardson, S.W.: Evidence based medicine: what it is and what it isn’t. BMJ 312(7023), 71–72 (1996)CrossRefGoogle Scholar
  11. 11.
    Guide Line Interchange Format (GLIF),
  12. 12.
    Sutton, D.R., Fox, J.: The syntax and semantics of the proforma guideline modeling language. JAMIA 10(5), 433–443 (2003)Google Scholar
  13. 13.
    Pryor, T.A., Hripcsak, G.: The arden syntax for medical logic modules. Journal of Clinical Monitoring and Computing 10(4), 215–224 (1993)CrossRefGoogle Scholar
  14. 14.
    Health Level Seven (HL7),
  15. 15.
    Musen, M.A., Tu, S.W., Das, A.K., Shahar, Y.: Eon: A component-based approach to automation of protocol-directed therapy. JAMIA 3(6), 367–388 (1996)Google Scholar
  16. 16.
    Shahar, Y., Young, O., Shalom, E., Mayaffit, A., Moskovitch, R., Hessing, A., Galperin, M.: Degel: A hybrid, multiple-ontology framework for specification and retrieval of clinical guidelines. In: Dojat, M., Keravnou, E.T., Barahona, P. (eds.) AIME 2003. LNCS, vol. 2780, pp. 122–131. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  17. 17.
    Kawamoto, K., Lobach, D.F.: Design, implementation, use, and preliminary evaluation of sebastian, a standards-based web service for clinical decision support. In: AMIA Symp., pp. 380–384 (2005)Google Scholar
  18. 18.
    Georgakopoulos, D., Hornick, M., Sheth, A.: An overview of workflow management: from process modeling to workflow automation infrastructure. Distrib. Parallel Databases 3(2), 119–153 (1995)CrossRefGoogle Scholar
  19. 19.
    jBPM Process Definition Language (jPDL),
  20. 20.
    Ricca, F., Leone, N.: Disjunctive logic programming with types and objects: The dlv+ system. J. Applied Logic 5(3), 545–573 (2007)CrossRefGoogle Scholar
  21. 21.
    Eiter, T., Gottlob, G., Mannila, H.: Disjunctive Datalog. ACM Transactions on Database Systems 22(3), 364–418 (1997)CrossRefGoogle Scholar
  22. 22.
    Leone, N., Pfeifer, G., Faber, W., Eiter, T., Gottlob, G., Perri, S., Scarcello, F.: The dlv system for knowledge representation and reasoning. ACM Trans. Comp. Logic 7(3), 499–562 (2006)CrossRefGoogle Scholar
  23. 23.
    International Statistical Classification of Diseases and Related Health Problems 10th Revision,
  24. 24.
    Anatomical Therapeutic Chemical (ATC) and Defined Daily Dose (DDD) system,
  25. 25.
    Van der Aalst, W.M.P., Van Dongen, B.F., Herbst, J., Maruster, L., Schimm, G., Weijters, A.J.M.M.: Workflow mining: A survey of issues and approaches. Data Knowl. Eng. 47(2), 237–267 (2003)CrossRefGoogle Scholar
  26. 26.
    Gaaloul, W., Alaoui, S., Bana, K., Godart, C.: Mining workflow patterns through event-data analysis. Saint-w, 226–229 (2005)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Ermelinda Oro
    • 1
  • Massimo Ruffolo
    • 2
  • Domenico Sacca
    • 1
  1. 1.Department of Computer Science and System Science (DEIS)Italy
  2. 2.Institute of High Performance Computing and Networking of CNR (ICAR-CNR)University of CalabriaRende (CS)Italy

Personalised recommendations