Webifying the Computerized Execution of Clinical Practice Guidelines

  • Tiago Oliveira
  • Pedro Leão
  • Paulo Novais
  • José Neves
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 293)


The means through which Clinical Practice Guidelines are disseminated and become accessible are a crucial factor in their later adoption by health care professionals. Making these guidelines available in Clinical Decision Support Systems renders their application more personal and thus acceptable at the moment of care. Web technologies may play an important role in increasing the reach and dissemination of guidelines, but this promise remains largely unfulfilled. There is a need for a guideline computer model that can accommodate a wide variety of medical knowledge along with a platform for its execution that can be easily used in mobile devices. This work presents the CompGuide framework, a web-based and service-oriented platform for the execution of Computer-Interpretable Guidelines. Its architecture comprises different modules whose interaction enables the interpretation of clinical tasks and the verification of clinical constraints and temporal restrictions of guidelines represented in OWL. It allows remote guideline execution with data centralization, more suitable for a work environment where physicians are mobile and not bound to a machine. The solution presented in this paper encompasses a computer-interpretable guideline model, a web-based framework for guideline execution and an Application Programming Interface for the development of other guideline execution systems.


Computer-Interpretable Guidelines Clinical Decision Support Framework Web 


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  1. 1.
    Field, M.J., Lohr, K.: Guidelines for Clinical Practice: From Development to Use. The National Academy Press, Washington DC (1992)Google Scholar
  2. 2.
    Woolf, S.H., Grol, R., Hutchinson, A., Eccles, M., Grimshaw, J.: Potential benefits, limitations, and harms of clinical guidelines. BMJ Br. Med. J. 318(7182), 527–530 (1999)CrossRefGoogle Scholar
  3. 3.
    Latoszek-Berendsen, A., Tange, H., van den Herik, H.J., Hasman, A.: From clinical practice guidelines to computer-interpretable guidelines. A literature overview. Methods Inf. Med. 49(6), 550–570 (2010)CrossRefGoogle Scholar
  4. 4.
    Samwald, M., Fehre, K., de Bruin, J., Adlassnig, K.-P.: The Arden Syntax standard for clinical decision support: Experiences and directions. J. Biomed. Inform. (February 2012)Google Scholar
  5. 5.
    Peleg, M., Boxwala, A.A., Ogunyemi, O., Zeng, Q., Tu, S., Lacson, R., Bernstam, E., Ash, N., Mork, P., Ohno-Machado, L., et al.: GLIF3: the evolution of a guideline representation format. In: Proceedings of the AMIA Symposium, p. 645 (2000)Google Scholar
  6. 6.
    Balser, M., Duelli, C., Reif, W.: Formal Semantics of Asbru – An Overview. Science (80) (2002)Google Scholar
  7. 7.
    Vier, E., Fox, J., Johns, N., Lyons, C., Rahmanzadeh, A., Wilson, P.: PROforma: systems. Comput. Methods Programs Biomed. 2607(97) (1997)Google Scholar
  8. 8.
    Ram, P., Berg, D., Tu, S., Mansfield, G., Ye, Q., Abarbanel, R., Beard, N.: Executing clinical practice guidelines using the SAGE execution engine. Stud. Health Technol. Inform. 107(pt. 1), 251–255 (2004)Google Scholar
  9. 9.
    Isern, D., Moreno, A.: Computer-based execution of clinical guidelines: a review. Int. J. Med. Inform. 77(12), 787–808 (2008)CrossRefGoogle Scholar
  10. 10.
    Oliveira, T., Novais, P., Neves, J.: Development and implementation of clinical guidelines: An artificial intelligence perspective. Artif. Intell. Rev. (March 2013)Google Scholar
  11. 11.
    Peleg, M.: Computer-interpretable clinical guidelines: A methodological review. J. Biomed. Inform. 46(4), 744–763 (2013)CrossRefGoogle Scholar
  12. 12.
    Oliveira, T., Novais, P., Neves, J.: Representation of Clinical Practice Guideline Components in OWL. In: Pérez, J.B., et al. (eds.) Trends in Pract. Appl. of Agents & Multiagent Syst. AISC, vol. 221, pp. 77–85. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  13. 13.
    Gutiérrez, P.: OpenEHR-Gen Framework (2010)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Tiago Oliveira
    • 1
  • Pedro Leão
    • 2
    • 3
    • 4
  • Paulo Novais
    • 1
  • José Neves
    • 1
  1. 1.CCTC/Department of InformaticsUniversity of MinhoBragaPortugal
  2. 2.School of Health SciencesUniversity of MinhoBragaPortugal
  3. 3.Life and Health Sciences Research InstituteHospital of BragaBragaPortugal
  4. 4.ICVS/3B’s - PT Government Associate LaboratoryBragaPortugal

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