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A Hybrid Approach for the Verification of Integrity Constraints in Clinical Practice Guidelines

  • Marco Iannaccone
  • Massimo Esposito
  • Giuseppe De Pietro
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8073)

Abstract

In the last decade, clinical practice guidelines are increasingly implemented in decision support systems able to promote their better integration into the clinical workflow. Despite the attempts involved to detect malformed, incomplete, or even inconsistent implementations of computerized guidelines, none of these solutions is concerned with directly embedding the theoretic semantics of a formal language as the basis of a guideline formalism in order to easily and directly support its verification. In such a direction, this paper proposes a formal framework which has been seamlessly embedded into a standards-based verifiable guideline model, named GLM-CDS (GuideLine Model for Clinical Decision Support). Such a framework hybridizes the theoretic semantics of ontology and rule languages to codify clinical knowledge in the form of a process-like model and, contextually, specify a set of integrity constraints to help to detect violations, errors and/or missing information. Its strong point relies on the capability of automatically verifying guidelines and, thus, supporting developers without the necessary technical background to construct them in a well-formed form. As a proof of concept, an actual guideline for Advanced Breast Cancer has been used to highlight some malformed implementations violating integrity constraints defined in GLM-CDS.

Keywords

Clinical Practice Guidelines Decision Support Systems Knowledge Verification Ontology Rules 

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References

  1. 1.
    Institute of Medicine, Crossing the Quality Chasm: A New Health System for the 21st Century. National Academy Press, Washington, DC (2001)Google Scholar
  2. 2.
    Field, M.J., Lohr, K.N.: Guidelines for Clinical Practice: From Development to Use. Institute of Medicine, National Academy Press, Washington, DC (1992)Google Scholar
  3. 3.
    Sonnenberg, F.A., Hagerty, C.G.: Computer-interpretable clinical practice guidelines: Where are we and where are we going? In: Kulikowski, C., Haux, R. (eds.) IMIA Yearbook of Medical Informatics 2006. Methods Inf. Med., vol. 45(suppl. 1), pp. 145–158 (2006)Google Scholar
  4. 4.
    Minutolo, A., Esposito, M., De Pietro, G.: KETO: A Knowledge Editing Tool for Encoding Condition–Action Guidelines into Clinical DSSs. In: Corchado, E., Snášel, V., Abraham, A., Woźniak, M., Graña, M., Cho, S.-B. (eds.) HAIS 2012, Part III. LNCS (LNAI), vol. 7208, pp. 352–364. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  5. 5.
    Pérez, B., Porres, I.: Authoring and verification of clinical guidelines: A model driven approach. Journal of Biomedical Informatics 43(4), 520–536 (2010)CrossRefGoogle Scholar
  6. 6.
    Bottrighi, A., Giordano, L., Molino, G., Montani, S., Terenziani, P., Torchio, M.: Adopting model checking techniques for clinical guidelines verification. Artif. Intell. Med. 48(1), 1–19 (2010)CrossRefGoogle Scholar
  7. 7.
    Iannaccone, M., Esposito, M., De Pietro, G.: A Standards-based Verifiable Guideline Model for Decision Support in Clinical Applications. In: Proc. of the Joint International Workshop KR4HC/ProHealth 2013 (2013)Google Scholar
  8. 8.
    Health Level 7. HL7 Virtual Medical Record (vMR) Project Wiki, http://wiki.hl7.org/index.php?title=Virtual_Medical_Record_(vMR) Google Scholar
  9. 9.
    Hommersom, A., Lucas, P.J., Van Bommel, P.: Checking the quality of clinical guidelines using automated reasoning tools. Theory Pract. Logic Program. 8(5-6), 611–641 (2008)zbMATHCrossRefGoogle Scholar
  10. 10.
    Shiffman, R., Greenes, R.: Improving clinical guidelines with logic and decision-table techniques. Med. Decision Making 14, 245–254 (1994)CrossRefGoogle Scholar
  11. 11.
    Quaglini, S., Saracco, R., Stefanelli, M., Fassino, C.: Supporting tools for guideline development and dissemination. In: Proc. of Artificial Intelligence in Medicine, pp. 39–50 (1997)Google Scholar
  12. 12.
    Miller Jr., D.W., Frawley, S.J., Miller, P.: Using semantic constraints to help verify the completeness of a computer-based clinical guideline for childhood immunization. Comp. Meth. Prog. Biomed. 58, 267–280 (1999)CrossRefGoogle Scholar
  13. 13.
    Duftschmid, G., Miksch, S.: Knowledge-based verification of clinical guidelines by detection of anomalies. Artif. Intell. Med. 22, 23–41 (2001)CrossRefGoogle Scholar
  14. 14.
    Isern, D., Moreno, A.: Computer-based execution of clinical guidelines: a review. Int. J. Med. Inform. 77, 787–808 (2008)CrossRefGoogle Scholar
  15. 15.
    Schmitt, J., Hoffmann, A., Balser, M., Reif, W., Marcos, M.: Interactive Verification of Medical Guidelines. In: Misra, J., Nipkow, T., Sekerinski, E. (eds.) FM 2006. LNCS, vol. 4085, pp. 32–47. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  16. 16.
    Hommersom, A.J., Groot, P., Lucas, P.J.F., Balser, M., Schmitt, J.: Verification of medical guidelines using background knowledge in task networks. IEEE Transactions on Knowledge and Data Engineering 19(6), 832–846 (2006)CrossRefGoogle Scholar
  17. 17.
    Ten Teije, A., Marcos, M., Balser, M., van Croonenborg, J., Duelli, C., van Harmelen, F., Lucas, P., Miksch, S., Reif, W., Rosenbrand, K., Seyfang, A.: Improving medical protocols by formal methods. Artificial Intelligence in Medicine 36(3), 193–209 (2006)CrossRefGoogle Scholar
  18. 18.
    Bäumler, S., Balser, M., Dunets, A., Reif, W., Schmitt, J.: A verification of medical guidelines by model checking – A case study. In: Valmari, A. (ed.) SPIN 2006. LNCS, vol. 3925, pp. 219–233. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  19. 19.
    Groot, P., Hommersom, A., Lucas, P., Serban, R., ten Teije, A., van Harmelen, F.: The role of model checking in critiquing based on clinical guidelines. In: Bellazzi, R., Abu-Hanna, A., Hunter, J. (eds.) AIME 2007. LNCS (LNAI), vol. 4594, pp. 411–420. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  20. 20.
    Prez, B., Porres, I.: Authoring and verification of clinical guidelines: A model driven approach. Journal of Biomedical Informatics 43(4), 520–536 (2010)CrossRefGoogle Scholar
  21. 21.
    Regenstrief Institute, Inc and the LOINC Committee. Logical Observation Identifiers Names and Codes (LOINC), http://loinc.org/
  22. 22.
    International Health Terminology Standards Development Organisation. Systematized Nomenclature of Medicine (SNOMED), http://www.ihtsdo.org/snomed-ct/
  23. 23.
    Health Level 7. HL7 Reference Information Model, Version 3, http://www.hl7.org/implement/standards/rim.cfm

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Marco Iannaccone
    • 1
  • Massimo Esposito
    • 1
  • Giuseppe De Pietro
    • 1
  1. 1.National Research Council of ItalyInstitute for High Performance Computing and Networking (ICAR)NaplesItaly

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