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Moving towards a new paradigm of creation, dissemination, and application of computer-interpretable medical knowledge

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Abstract

Computer-interpretable guidelines (CIGs) exploit the scientific strength of evidence-based medicine to make recommendations available in clinical decision support systems. However, systems that deploy them have not been widely successful, in part due to the limitations of CIG frameworks in the adoption of inclusive and open technologies and the use of artificial intelligence techniques as tools to make their systems stronger and more adaptable. In this work, we propose a web-based CIG framework to tackle some of these challenges and facilitate the integration of CIG-based advice not only in the everyday activities of health care professionals, but also in the lives of whoever may need it.

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References

  1. Adhikari, N.K.J., Beyene, J., Sam, J., Haynes, R.B.: Effects of computerized clinical decision support systems on practitioner performance. J. Am. Med. Assoc. 293(10), 1223–1238 (2005)

    Article  Google Scholar 

  2. Boxwala, A., Peleg, M., Tu, S., Ogunyemi, O., Zeng, Q.T., Wang, D., Patel, V.L., Greenes, R.A., Shortliffe, E.H.: GLIF3: a representation format for sharable computer-interpretable clinical practice guidelines. J. Biomed. Inform. 37(3), 147–61 (2004)

    Article  Google Scholar 

  3. Button, D.R., Fox, J.: The syntax and semantics of the PRO forma guideline modeling language. J. Am. Med. Inform. Assoc. 10(5), 433–443 (2003)

    Article  Google Scholar 

  4. Ciccaresea, P., Caffib, E., Boiocchia, L., Quaglinia, S., Stefanellia, M.: A guideline management system. In: Fieschi, M., Coiera, E., Jack Li, Y.-C. (eds.) Medinfo 2004, pp. 28–32. IOS Press (2004)

  5. Costa, R., Novais, P., Machado, J., Alberto, C., Neves, J.: Inter-organization cooperation for care of the elderly. In: Wang, W., Li, Y., Duan, Z., Yan, L., Li, H., Yang, X. (eds.) Integration and innovation orient to e-society. IFIP International Federation for Information Processing, vol 252, vol. 2, pp. 200–208. Springer, New York (2007)

    Google Scholar 

  6. de Clercq, P.A., Blom, J.A., Korsten, H.H.M., Hasman, A.: Approaches for creating computer-interpretable guidelines that facilitate decision support. Artif. Intell. Med. 31(1), 1–27 (2004)

    Article  Google Scholar 

  7. Goud, R., Hasman, A., Strijbis, A.M., Peek, N.: A parallel guideline development and formalization strategy to improve the quality of clinical practice guidelines. Int. J. Med. Inform. 78(8), 513–520 (2009)

    Article  Google Scholar 

  8. Isern, D., Moreno, A.: Computer-based execution of clinical guidelines: a review. Int. J. Med. Inform. 77(12), 787–808 (2008)

    Article  Google Scholar 

  9. Kaushal, R., Shojania, K.G., Bates, D.W.: Effects of computerized physician order entry and clinical decision support systems on medication safety: a systematic review. Arch. Intern. Med. 163(12), 1409–16 (2003)

    Article  Google Scholar 

  10. Kim, S., Haug, P.J., Rocha, R.A., Choi, I.: Modeling the Arden Syntax for medical decisions in XML. Int. J. Med. Inf. 77(10), 650–656 (2008)

    Article  Google Scholar 

  11. 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)

    Article  Google Scholar 

  12. Lima, L., Novais, P., Costa, R., Bulas Cruz, J., Neves, J.: Group decision making and quality-of-information in e-health systems. Log. J. IGPL 19(2), 315–332 (2011)

    Article  MathSciNet  Google Scholar 

  13. Miller, M., Kearney, N.: Guidelines for clinical practice: development, dissemination and implementation. Int. J. Nurs. Stud. 41(7), 813–821 (2004)

    Article  Google Scholar 

  14. Musen, M.A., Shahar, Y., Shortliffe, E.H.: Clinical decision-support systems. In: Shortlife, E., Cimino, J. (eds.) Biomedical informatics computer applications in health care and biomedicine, pp. 698–736. Springer, Berlin (2006)

    Google Scholar 

  15. Novais, P., Costa, R., Carneiro, D., Neves, J.: Inter-organization cooperation for ambient assisted living. J. Ambient. Intell. Smart Environ. 2(2), 179–195 (2010)

    Google Scholar 

  16. Oliveira, T., Novais, P., Neves, J.: Development and implementation of clinical guidelines: an artificial intelligence perspective. Artif. Intell. Rev. 42, 1–29 (2013a)

    Google Scholar 

  17. Oliveira, T., Novais, P., Neves, J.: Representation of clinical practice guideline components in OWL. In: Pérez, J.B., Hermoso, R., Moreno, M.N., Rodríguez, J.M.C., Hirsch, B., Mathieu, P., Campbell, A., Suarez-Figueroa, M.C., Ortega, A., Adam, E., Navarro, E. (eds.) Trends in practical applications of agents and multiagent systems SE-10, advances in intelligent systems and computing, vol. 221, pp. 77–85. Springer, Berlin (2013b)

    Chapter  Google Scholar 

  18. Oliveira, T., Leão, P., Novais, P., Neves, J.: Webifying the computerized execution of clinical practice guidelines. In: Bajo Perez, J., Corchado Rodríguez, J.M., Mathieu, P., Campbell, A., Ortega, A., Adam, E., Navarro, E.M., Ahrndt, S., Moreno, M.N., Julián, V. (eds.) Trends in practical applications of heterogeneous multi-agent systems. The PAAMS collection SE-18, Advances in intelligent systems and computing, vol 293. Springer, Berlin, pp. 149–156 (2014a)

  19. Oliveira, T., Satoh, K., Neves, J., Novais, P.: Applying speculative computation to guideline-based decision support systems. In: IEEE 27th international symposium on computer-based medical systems 2014 (CBMS), pp. 42–47, 2014b, doi:10.1109/CBMS.2014.32

  20. Oliveira, T., Novais, P., Neves, J.: Assessing an ontology for the representation of clinical protocols in decision support systems. In: Bajo, J., Hernández, J.Z., Mathieu, P., Campbell, A., Fernández-Caballero, A., Moreno, M.N., Julián, V., Alonso-Betanzos, A., Jiménez-López, M.D., Botti, V. (eds.) Trends in practical applications of agents, multi-agent systems and sustainability SE-6, advances in intelligent systems and computing, vol. 372, pp. 47–54. Springer, Berlin (2015)

  21. Peleg, M.: Computer-interpretable clinical guidelines: a methodological review. J. Biomed. Inform. 46(4), 744–763 (2013)

    Article  Google Scholar 

  22. Shahar, Y., Young, O., Shalom, E., Galperin, M., Mayaffit, A., Moskovitch, R., Hessing, A.: A framework for a distributed, hybrid, multiple-ontology clinical-guideline library, and automated guideline-support tools. J. Biomed. Inform. 37(5), 325–344 (2004)

    Article  Google Scholar 

  23. Shalom, E., Shahar, Y., Lunenfeld, E.: An architecture for a continuous, user-driven, and data-driven application of clinical guidelines and its evaluation. J. Biomed. Inform. 59, 130–148 (2015)

  24. Sintchenko, V., Coiera, E., Iredell, J.R., Gilbert, G.L.: Comparative impact of guidelines, clinical data, and decision support on prescribing decisions: an interactive Web experiment with simulated cases. J. Am. Med. Inform. Assoc. 11(1), 71–77 (2004)

    Article  Google Scholar 

  25. Ten Teije, A., Miksch, S., Lucas, P.: Computer-based medical guidelines and protocols: a primer and current trends, vol. 139. Ios Press Inc, Washington, D.C. (2008)

    Google Scholar 

  26. Terenziani, P., Montani, S., Bottrighi, A., Torchio, M., Molino, G., Correndo, G.: The GLARE approach to clinical guidelines: main features. Stud. Health Technol. Inform. 101(3), 162–6 (2004)

    Google Scholar 

  27. Tu, S.W., Campbell, J.R., Glasgow, J., Nyman, M.A., McClure, R., McClay, J., Parker, C., Hrabak, K.M., Berg, D., Weida, T., Mansfield, J.G., Musen, M.A., Abarbanel, R.M.: The SAGE guideline Model: achievements and overview. J. Am. Med. Inform. Assoc. JAMIA 14(5), 589–598 (2007)

    Article  Google Scholar 

  28. Wang, D., Peleg, M., Tu, S.W., Boxwala, A.A., Ogunyemi, O., Zeng, Q., Greenes, R.A., Patel, V.L., Shortliffe, E.H.: Design and implementation of the GLIF3 guideline execution engine. J. Biomed. Inform. 37(5), 305–318 (2004)

    Article  Google Scholar 

  29. Young, O., Shahar, Y.: The spock system : developing a runtime application engine for hybrid-asbru guidelines. Artif. Intell. Rev. 3581(1), 166–170 (2005)

    Google Scholar 

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Acknowledgments

This work has been supported by FCT–Fundação para a Ciência e Tecnologia within the Project Scope UID/CEC/00319/2013. The work of Tiago Oliveira is supported by an FCT grant with the reference SFRH/BD/85291/ 2012.

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Correspondence to Paulo Novais.

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Novais, P., Oliveira, T. & Neves, J. Moving towards a new paradigm of creation, dissemination, and application of computer-interpretable medical knowledge. Prog Artif Intell 5, 77–83 (2016). https://doi.org/10.1007/s13748-016-0084-2

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  • DOI: https://doi.org/10.1007/s13748-016-0084-2

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