Analysis of the GLARE and GPROVE Approaches to Clinical Guidelines

  • Alessio Bottrighi
  • Federico Chesani
  • Paola Mello
  • Marco Montali
  • Stefania Montani
  • Sergio Storari
  • Paolo Terenziani
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5943)


Clinical guidelines (GLs) play an important role in medical practice, and computerized support to GLs is now one of the most central areas of research in Artificial Intelligence in medicine. In recent years, many groups have developed different computer-assisted management systems of GL. Each approach has its own peculiarities and thus a comparison is necessary. Many possible aspects can be analyzed, but a first analysis has probably to consider the GL models, i.e. the representation formalisms provided. To this end, Peleg and al. [4] have analyzed and compared six different frameworks. In this paper, we analyse also GLARE and GPROVE on the basis of the same methodology. Moreover, we extend such analysis by considering the tools and the facilities that GLARE and GPROVE provide to support the use of GLs. The final goal of our analysis is to exploit the differences between these two systems and if they can be fruitfully integrated.


clinical guideline computer-assisted guideline manager guideline model decision support verification 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Gordon, C., Christensen, J.P. (eds.): Health Telematics for Clinical Guidelines and Protocols. IOS Press, Amsterdam (1995)Google Scholar
  2. 2.
    Fridsma, D.B. (Guest ed.): Special Issue on Workflow Management and Clinical Guidelines. Journal of the American Medical Informatics Association 22(1), 1–80 (2001)Google Scholar
  3. 3.
    ten Teije, A., Miksch, S., Lucas, P. (eds.): Computer-based medical guidelines and protocols: a primer and current trends. IOS Press, Amsterdam (2008)Google Scholar
  4. 4.
    Peleg, M., Tu, S., Bury, J., Ciccarese, P., Fox, J., Greenes, R.A., Hall, R., Johnson, P.D., Jones, N., Kumar, A., Miksch, S., Quaglini, S., Seyfang, A., Shortliffe, E.H., Stefanelli, M.: Comparing computer-interpretable guideline models: a case-study approach. Journal of the American Medical Informatics Association 10(1), 52–68 (2003)CrossRefGoogle Scholar
  5. 5.
    Miksch, S., Shahar, Y., Johnson, P.: Asbru: a task-specific, intention-based, and time-oriented language for representing skeletal plans. In: Proc. 7th Workshop on Knowledge Engeneering Methods and Languages, pp. 9–20 (1997)Google Scholar
  6. 6.
    Musen, M.A., Tu, S.W., Das, A.K., Shahar, Y.: EON: a component-based approach to automation of protocol-directed therapy. Journal of the American Medical Informatics Association 3(6), 367–388 (1996)CrossRefGoogle Scholar
  7. 7.
    Ohno-Machado, L., Gennari, J.H., Murphy, S., Jain, N.L., Tu, S.W., Oliver, D.E., et al.: The guideline interchange format: a model for representing guidelines. JAMIA 5(4), 357–372 (1998)Google Scholar
  8. 8.
    Peleg, M., Boxawala, A.A., et al.: GLIF3: The evolution of a guideline representation format. In: Proc. AMIA 2000, pp. 645–649 (2000)Google Scholar
  9. 9.
    Quaglini, S., Stefanelli, M., Cavallini, A., Miceli, G., Fassino, C., Mossa, C.: Guideline-based careflow systems. Artificial Intelligence in Medicine 20(1), 5–22 (2000)CrossRefGoogle Scholar
  10. 10.
    Johnson, P.D., Tu, S.W., Booth, N., Sugden, B., Purves, I.N.: Using scenarios in chronic disease management guidelines for primary care. In: Proc. AMIA Annu. Fall Symp., pp. 389–393 (2000)Google Scholar
  11. 11.
    Fox, J., Johns, N., Rahmanzadeh, A., Thomson, R.: Disseminating medical knowledge: the PROforma approach. Artificial Intelligence in Medicine 14, 157–181 (1998)CrossRefGoogle Scholar
  12. 12.
    Chesani, F., Lamma, E., Mello, P., Montali, M., Storari, S., Baldazzi, P., Manfredi, M.: Compliance checking of cancer-screening careflows: an approach based on computational logic. In: ten Teije, A., Miksch, S., Lucas, P. (eds.) Computer-based medical guidelines and protocols: a primer and current trends. IOS Press, Amsterdam (2008)Google Scholar
  13. 13.
    Isern, D., Moreno, A.: Distributed guideline-based health care system. In: Proceedings of 4th International Conference on Intelligent Systems Design and Applications, ISDA 2004, pp. 145–150. IEEE Press, Budapest (2004)Google Scholar
  14. 14.
    Skonetzki, S., Gausepohl, H.J., van der Haak, M., Knaebel, S., Linderkamp, O., Wetter, T.: HELEN, a Modular Framework for Representing and Implementing Clinical Practice Guidelines. Methods Inf. Med. 43, 413–426 (2004)Google Scholar
  15. 15.
    Dube, K.: A Generic approach to supporting the management of computerised clinical guidelines and protocols, PhD thesis, Institute of Technology, Dublin, Ireland (2004)Google Scholar
  16. 16.
    Terenziani, P., Montani, S., Bottrighi, A., Molino, G., Torchio, M.: Applying artificial intelligence to clinical guidelines: the GLARE approach. In: ten Teije, A., Miksch, S., Lucas, P. (eds.) Computer-based medical guidelines and protocols: a primer and current trends. IOS Press, Amsterdam (2008)Google Scholar
  17. 17.
    De Clercq, P.A., Hasman, A., Blom, J.A., Korsten, H.H.M.: Design and implementation of a framework to support the development of clinical guidelines. International Journal of Medical Informatics 64, 285–318 (2001)CrossRefGoogle Scholar
  18. 18.
    Berg, D., Ram, P., Glasgow, J.: SAGEDesktop: an environment for testing clinical practice guidelines. In: Proceedings of 26th Annual Conference of the IEEE Engineering in Medicine and Biology Society (IEBMS 2004), San Francisco, USA, vol. 2, pp. 3217–3220. IEEE Press, Los Alamitos (2004)CrossRefGoogle Scholar
  19. 19.
    Chesani, F., De Matteis, P., Mello, P., Montali, M., Storari, S.: A framework for defining and verifying clinical guidelines: A case study on cancer screening. In: Esposito, F., Raś, Z.W., Malerba, D., Semeraro, G. (eds.) ISMIS 2006. LNCS (LNAI), vol. 4203, pp. 338–343. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  20. 20.
    Alberti, M., Chesani, F., Gavanelli, M., Lamma, E., Mello, P., Torroni, P.: Verifiable agent interaction in abductive logic programming: the SCIFF framework. ACM Transactions on Computational Logic 9(4), 1–43 (2008)MathSciNetCrossRefGoogle Scholar
  21. 21.
    Irwin, R.S., Boulet, L.S., Cloutier, M.M., et al.: Managing cough as a defense mechanism and as a symptom: a consensus panel report of the American College of Chest Physicians. Chest 114(2), 133–181 (1998)CrossRefGoogle Scholar
  22. 22.
    Irwin, R.S., Baumann, M.H., Bolser, D.C., Boulet, L.P., Braman, S.S., Brightling, C.E., Brown, K.K., Canning, B.J., Chang, A.B., Dicpinigaitis, P.V., Eccles, R., Brendle Glomb, W., Goldstein, L.B., Graham, L.M., Hargreave, F.E., Kvale, P.A., Zelman Lewis, S., McCool, F.D., McCrory, D.C., Prakash, U.B.S., Pratter, M.R., Rosen, M.J., Schulman, E., Shannon, J.J., Hammond, C.S., Tarlo, S.M.: Diagnosis and management of cough executive summary: ACCP evidence-based clinical practice guidelines. Chest 129, 1–23 (2006)CrossRefGoogle Scholar
  23. 23.
    Anselma, L., Terenziani, P., Montani, S., Bottrighi, A.: Towards a comprehensive treatment of repetitions, periodicity and temporal constraints in clinical guidelines. Artificial Intelligence in Medicine 38, 171–195 (2006)CrossRefGoogle Scholar
  24. 24.
    Jaffar, J., Maher, M.J.: Constraint logic programming: a survey. JLP 19-20, 503–582 (1994)MathSciNetCrossRefzbMATHGoogle Scholar
  25. 25.
    Montani, S., Terenziani, P.: Exploiting decision theory concepts within clinical guideline systems: towards a general approach. International Journal of Intelligent System 21, 585–599 (2006)CrossRefzbMATHGoogle Scholar
  26. 26.
    Protégé ontology editor,
  27. 27.
    The SCIFF abductive proof procedure,
  28. 28.
    Holzmann, G.J.: The SPIN Model Checker. Primer and Reference Manual. Addison-Wesley, Reading (2003)Google Scholar
  29. 29.
    Terenziani, P., Montani, S., Bottrighi, A., Torchio, M., Molino, G., Correndo, G.: A context-adaptable approach to clinical guidelines. In: Fieschi, M., et al. (eds.) Proc. MEDINFO 2004, pp. 169–173. IOS Press, Amsterdam (2004)Google Scholar
  30. 30.
    Terenziani, P., Montani, S., Bottrighi, A., Torchio, M., Molino, G.: Supporting physicians in taking decisions in clinical guidelines: the GLARE “what-if” facility. In: JAMIA Symposium supplement, pp. 772–776 (2002)Google Scholar
  31. 31.
    Bottrighi, A., Chesani, F., Mello, P., Molino, G., Montali, M., Montani, S., Storari, S., Terenziani, P., Torchio, M.: A Hybrid Approach to Clinical Guideline and to Basic Medical Knowledge Conformance. In: Combi, C., Shahar, Y., Abu-Hanna, A. (eds.) AIME 2009. LNCS (LNAI), vol. 5651, pp. 91–95. Springer, Berlin (2009)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Alessio Bottrighi
    • 1
  • Federico Chesani
    • 2
  • Paola Mello
    • 2
  • Marco Montali
    • 2
  • Stefania Montani
    • 1
  • Sergio Storari
    • 3
  • Paolo Terenziani
    • 1
  1. 1.DIUniv. Piemonte Orientale “A. Avogadro”AlessandriaItaly
  2. 2.DEISUniv. BolognaBolognaItaly
  3. 3.ENDIFUniv. FerraraFerraraItaly

Personalised recommendations