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Implementing an Integrative Multi-agent Clinical Decision Support System with Open Source Software

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Abstract

Clinical decision making is a complex multi-stage process. Decision support can play an important role at each stage of this process. At present, the majority of clinical decision support systems have been focused on supporting only certain stages. In this paper we present the design and implementation of MET3—a prototype multi-agent system providing an integrative decision support that spans over the entire decision making process. The system helps physicians with data collection, diagnosis formulation, treatment planning and finding supporting evidence. MET3 integrates with external hospital information systems via HL7 messages and runs on various computing platforms available at the point of care (e.g., tablet computers, mobile phones). Building MET3 required sophisticated and reliable software technologies. In the past decade the open source software movement has produced mature, stable, industrial strength software systems with a large user base. Therefore, one of the decisions that should be considered before developing or acquiring a decision support system is whether or not one could use open source technologies instead of proprietary ones. We believe MET3 shows that the answer to this question is positive.

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Notes

  1. Throughout the paper we refer to this product with its original and widely known name, Mirth.

  2. http://jade.tilab.com/

  3. http://search.hibernate.org/

  4. http://lucene.apache.org

  5. http://www.mirthproject.org

  6. http://java.sun.com/products/sjwtoolkit/

  7. http://www.cs.waikato.ac.nz/ml/weka/

  8. For more details on these methods please see [35].

References

  1. Patel, V. L., Kushniruk, A. W., Yang, S., and Yale, J. F., Impact of a computer-based patient record system on data collection, knowledge organization, and reasoning. J. Am. Med. Inform. Assoc. 7(6):569–85, 2000.

    Article  Google Scholar 

  2. Patel, V., Arocha, J. F., and Zhang, J., Thinking and reasoning in medicine. In: Holyoak, K., and Morrison, R. (Eds.), The Cambridge Handbook of Thinking and Reasoning. Cambridge University Press, Cambridge, pp. 727–50, 2005.

    Google Scholar 

  3. Field, M. J., and Lohr, K. N. (Eds.), Guidelines for Clinical Practice: From Development to Use. National Academy Press, Washington, D.C., 1992.

    Google Scholar 

  4. The Cochrane library. http://www.thecochranelibrary.com/.

  5. Sackett, D. L., Rosenberg, W., Gray, J. M., Haynes, R., and Richardson, W., Evidence based medicine: What it is and what it isn’t. Br. Med. J. 312:71–72, 1996.

    Article  Google Scholar 

  6. Berlin, A., Sorani, M., and Sim, I., A taxonomic description of computer-based clinical decision support systems. J. Biomed. Inform. 39(6):656–67, 2006.

    Article  Google Scholar 

  7. Sittig, D. F., Wright, A., Osheroff, J. A., Middleton, B., Teich, J. M., Ash, J. S., et al., Grand challenges in clinical decision support. J. Biomed. Inform. 41(2):387–92, 2008.

    Article  Google Scholar 

  8. Wilk, S., Michalowski, W., O’Sullivan, D., Farion, K., and Matwin, S., Engineering of a clinical decision support framework for the point of care use. AMIA Annu. Symp. Proc. 6:814–818, 2008.

    Google Scholar 

  9. Farion, K., Michalowski, W., Wilk, S., O’Sullivan, D., Rubin, S., and Weiss, D., Clinical decision support system for point of care use: Ontology driven design and software implementation. Methods Inf. Med. 48(4):381–390, 2009.

    Article  Google Scholar 

  10. Michalowski, W., Slowinski, R., Wilk, S., Farion, K., Pike, J., and Rubin, S., Design and development of a mobile system for supporting emergency triage. Methods Inf. Med. 44(1):14–24, 2005.

    Google Scholar 

  11. Moreno, A., Valls, A., Riaño, and D. PalliaSys: Agent-based proactive monitoring of palliative patients. In proceedings of IWPAAMS, Oct 20–21, León, Spain, 2005.

  12. Su, C., and Wua, C., JADE implemented mobile multi-agent based, distributed information platform for pervasive health care monitoring. Applied Soft Computing (In press).

  13. Moreno, A., Isern, D., and Sanchez, D., Provision of agent-based health care services. AI Commun. 16(3):167–178, 2003.

    MathSciNet  MATH  Google Scholar 

  14. Hudson, D. L., and Cohen, M. E., Use of intelligent agents in the diagnosis of cardiac disorders. Comput. Cardiol. 633–636, 2002.

  15. Godo, L., Puyol-Gruart, J., Sabater, J., Torra, V., Barrufet, P., and Fàbregas, X., A multi-agent system approach for monitoring the prescription of restricted use antibiotics. Artif. Intell. Med. 27(3):259–282, 2003.

    Article  Google Scholar 

  16. Hashmi, Z. I., Abidi, S. S. R., and Cheah, Y., An intelligent agent-based knowledge broker for enterprise-wide healthcare knowledge procurement. In Proceedings of 15th IEEE Symposium on Computer-Based Medical Systems. Maribor, Slovenia, 173, 2002.

  17. Bloodsworth, P., and Greenwood, S., COSMOA an ontology-centric multi-agent system for co-ordinating medical responses to large-scale disasters. AI Commun. 18(3):229–240, 2005.

    MathSciNet  Google Scholar 

  18. Cruz-Correia, R., Vieira-Marques, P., Costa, P., Ferreira, A., Oliveira-Palhares, E., Araújo, F., and Costa-Pereira, A., Integration of hospital data using agent technologies—A case study. AI Commun. 18(3):191–200, 2005.

    MathSciNet  Google Scholar 

  19. Hogarth, M. A., and Turner, S., A study of clinically related open source software projects. Proceedings of AMIA Symposium, 330–334, 2005.

  20. Wright, A., and Sittig, D. F., A four-phase model of the evolution of clinical decision support architectures. Int. J. Med. Inform. 77(10):641–9, 2008.

    Article  Google Scholar 

  21. Chu, S. C., From component-based to service oriented software architecture for healthcare. In Proceedings of 7th International Workshop on Enterprise Networking and Computing in Healthcare Industry. HEALTHCOM 96–100, 2005.

  22. Weiss G., A modern approach to distributed artificial intelligence. MIT, 1999.

  23. Payne, T. R., Web services from an agent perspective. IEEE Intell. Syst. 23(2):12–4, 2008.

    Article  Google Scholar 

  24. Garcia-Ojeda, J. C., DeLoach, S. A., Robby, Oyenan, W. H., and Valenzuela, J., O-MaSE: a customizable approach to developing multi-agent development processes. In: Luck, M. (Ed.), Agent-oriented software engineering VIII: the 8th International Workshop on Agent Oriented Software Engineering (AOSE). Springer-Verlag, Berlin, pp. 1–15, 2008.

    Google Scholar 

  25. Woodridge, M., Jennings, N. R., and Kinny, D., The Gaia methodology for agent-oriented analysis and design. Autonomous Agents and Multi-Agent Systems (AAMAS) 3(3):285–312, 2000.

    Article  Google Scholar 

  26. Bresciani, P., Perini, A., Giorgini, P., Giunchiglia, F., and Mylopoulos, J., TROPOS: An agent-oriented software development methodology. In Journal of Autonomous Agents and Multi-Agent Systems. Kluwer Academic Publishers, May 2004.

  27. Iglesias, C. A., Garijo, M., Centeno-González, J., and Velasco, J. R., Analysis and design of multiagent systems using MAS-Common KADS, Proceedings of the 4th International Workshop on Intelligent Agents IV, Agent Theories, Architectures, and Languages, Lecture Notes In Computer Science, vol. 1365. Springer-Verlag London, UK, pp. 313–327, 1997.

    Google Scholar 

  28. Foster, I., Jennings, N. R., and Kesselman C., Brain meets brawn: why Grid and agents need each other. In Proceedings 3rd International Conference on Autonomous Agents and Multi-Agent Systems, New York, US, 2004.

  29. Kawamoto, K., and Lobach, D. F., Proposal for fulfilling strategic objectives of the U.S. roadmap for national action on decision support through a service-oriented architecture leveraging HL7 services. J. Am. Med. Inform. Assoc. 14(2):146–155, 2007.

    Article  Google Scholar 

  30. Wilk, S., Slowinski, R., Michalowski, W., and Greco, S., Supporting triage of children with abdominal pain in the emergency room. Eur. J. Oper. Res. 160(3):696–709, 2005.

    Article  MATH  Google Scholar 

  31. Michalowski, W., Wilk, S., Farion, K., Pike, J., Rubin, S., and Slowinski, R., Development of a decision algorithm to support emergency triage of scrotal pain and its implementation in the MET system. INFOR 43(4):287–301, 2005.

    Google Scholar 

  32. Farion, K., Michalowski, W., Wilk, S., O’Sullivan, D., and Matwin, S., A tree-based decision model to support prediction of the severity of asthma exacerbations in children. J Med Syst, 2009 (in press).

  33. Farion, K., Michalowski, W., Rubin, S., Wilk, S., Corell, R., and Gaboury, I., Prospective evaluation of the MET-AP system providing triage plans for acute pediatric abdominal pain. Int. J. Med. Inform. 77(3):208–218, 2008.

    Article  Google Scholar 

  34. Canadian Association of Emergency Physicians: Guidelines for Emergency Management of Paediatric Asthma. Available at http://www.caep.ca/.

  35. Bellifemine, F. L., Caire, G, and Greenwood, D., Developing multi-agent systems with JADE. Wiley, 2004.

  36. Krishnamurthy, S., A managerial overview of open source software. Bus. Hor. 46(5):47–56, 2003.

    Article  Google Scholar 

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Acknowledgments

The research presented here was supported by NSERC-CIHR program. The authors would like to thank the MET3 programming team of Tomasz Buchert, Bartosz Kukawka, and Tomasz Maciejewski. The second author acknowledges the support of the Polish Ministry of Science and Higher Education (grant N N519 314435).

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Authors and Affiliations

  1. University of Ottawa, Ottawa, ON, Canada

    Jelber Sayyad Shirabad & Wojtek Michalowski

  2. Poznan University of Technology, Poznan, Poland

    Szymon Wilk

  3. Children’s Hospital of Eastern Ontario, Ottawa, ON, Canada

    Ken Farion

Authors
  1. Jelber Sayyad Shirabad
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  2. Szymon Wilk
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  3. Wojtek Michalowski
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  4. Ken Farion
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Corresponding author

Correspondence to Jelber Sayyad Shirabad.

Additional information

Research described in this paper was conducted while Dr. Wilk was a postdoctoral fellow at the Telfer School of Management, University of Ottawa.

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Sayyad Shirabad, J., Wilk, S., Michalowski, W. et al. Implementing an Integrative Multi-agent Clinical Decision Support System with Open Source Software. J Med Syst 36, 123–137 (2012). https://doi.org/10.1007/s10916-010-9452-9

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