Agent-based Modeling and Simulation Software Architecture for Health Care

Karam Mustapha, Jean-Marc Frayret


Health Care (HC) organizational structure and related management policies are essential factors of HC system. They can be tested through simulations in order to improve HC performance. To simplify the design of these simulations we have proposed a modelling approach based on an additional structure. The modelling approach considers the complexity of the modelling process, where in the various models are developed. This approach is organized according to two main abstraction levels, a conceptual level and a simulation level. We developed a computer simulation environment of patient care trajectories using the agent in order to evaluate new ap-proaches to increase hospital productivity and adapt hospital clinical practice conditions for the elderly and pa-tients with multiple chronic diseases. For that, we have developed a multi-agent framework to simulate the ac-tivities and roles in a HC system. This framework can be used to assist the collaborative scheduling of com-plex tasks that involve multiple personals and resources. In addition, it can be used to study the efficiency of the HC system and the influence of different policies.


  1. Bernon C., Gleizes M. P., Picard G. and Glize P., 2002. The Adelfe Methodology for an Intranet System Design. In Proc. of the Fourth International BiConference Workshop on Agent-Oriented Information Systems (AOIS), Toronto, Canada.
  2. Chao S. and Wong F., 2009. A Multi-Agent Learning Paradigm for Medical Data Mining Diagnostic Workbench.
  3. Devi M. S. and Mago V., 2005. "Multi-agent model for Indian rural health care," Leadership in Health Services, vol. 18, pp. 1-11.
  4. Ferber J., Stratulat T. and Tranier J., 2009. Towards an integral approach of organizations in multi-agents systems: the MASQ approach. Semantics and dynamics of organizational models in Virginia Dignum.
  5. Foster D., McGregor C. and El-Masri S., 2005. A Survey of Agent-Based Intelligent Decision Support Systems to Support Clinical Management and Research. In: Proceedings of the 2nd International Workshop on Multi-Agent Systems for Medicine, Computational Biology, and Bioinformatics, 16-34.
  6. Figueredo G. P. and Aickelin U., 2011. "Comparing system dynamics and agent-based simulation for tumour growth and its interactions with effector cells," in Proceedings of the 2011 Summer Computer Simulation Conference, pp. 52-59.
  7. Fujimoto R., 2000. Parallel and distributed simulation systems. John Wiley & Sons, Inc. USA.
  8. Gaud N., Galland S. and Koukam A., 2008. Towards a Multilevel Simulation Approach based on Holonic Multi-agent. Published in the 10th International Conference on Computer Modeling and Simulation (EUROSIM/ UKSiM?08), pp. 180-185, England. April 1-3.
  9. Gilli Q., Mustapha K., Frayret J. M., Lahrichi N., and Karimi E., 2014. Agent-Based Simulation of Colorectal Cancer Care Trajectory: Patient Model. CIRRELT (Interuniversity Research Centre on Enterprise Networks, Logistics and Transportation).
  10. Gupta S., Sarkar A., Pramanik I., and Mukherjee B., 2012. Implementation Scheme for Online Medical Diagnosis System Using Multi Agent System with JADE. Intemational Journal of Scientific and Research Publications, Volume 2, Issue 6,.ISSN 2250-3153, June.
  11. Gupta S. and Mukhopadhyay S.. 2012 Multi Agent System Based Clinical Diagnosis Systm: An Algorithmic Approach. International Journal of Engineering Research and Applications (IJERA) ISSN: 2H8-9622. Vol.2. Issue 5, pp. 1474-1477, September- October.
  12. Gupta S. and Pujari S., 2009. A Multi-Aged: Based Scheme for Heath Care and Clinical Diagnosis System, IAMA-09. ieeexplore. ISBN: 978-1-4244-4710-7. July.
  13. Han B-M., Song S.-J., Kyu Min Lee, Jang Kyung-Soo and Shin Dong-Ryeol, 2006. Multi Agent System based Efficient Healthcare Service. ICACT 2006, ISBN 89- 551 9-1 29-4.Feb. 20-22.
  14. Heun J. M., Grothey A., Branda M. E., Goldberg R. M., and Sargent D. J., "Tumor status at 12 weeks predicts survival in advanced colorectal cancer: Findings from NCCTG N9741," The oncologist, vol. 16, pp. 859-867, 2011.
  15. Hübner J. F., Sichman J. S., and Boissier O., 2007. Developing Organised Multi-Agent Systems Using the Moise+ Model: Programming Issues at the System and Agent Levels, Int. J. Accounting, Auditing and Performance Evaluation, 1(3/4):370-395.
  16. Iantovics B. 2008. The CMDS Medical Diagnosis System. Ninth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, IEEE.
  17. Iwata K., Kawasaki K., and Shigesada N., 2000. "A dynamical model for the growth and size distribution of multiple metastatic tumors," Journal of theoretical biology, vol. 203, pp. 177-186.
  18. Jennings N. R., Sycara K., and M. Wooldridge, 1998. "A roadmap of agent research and development," Autonomous agents and multi-agent systems, vol. 1, pp. 7-38.
  19. Jones S. S. and Evans R. S., 2008 "An agent based simulation tool for scheduling emergency department physicians," in AMIA Annual Symposium Proceedings, p. 338.
  20. Kanagarajah A., Parker D., and Xu H., 2010. "Health care supply networks in tightly and loosely coupled structures: Exploration using agent-based modelling," International Journal of Systems Science, vol. 41, pp. 261-270.
  21. Kazar O., Sahnoun Z. and Frecon L.. 2008. Multi-agents system for medical diagnosis. International Conference on Intelligent System and Knowledge Engineering, Vol. 1, Pages1265 - 1270.
  22. Klusch M., Lodi S. and Moro G., 2003. The Role of Agents in Distributed Data Mining - Issues and Benefits. In: Proceedings of IEEE/WIC International Conference on Intelligent Agent Technology (IAT'03), 211-217.
  23. Knight V. A., Williams J. E., and Reynolds I., 2012. "Modelling patient choice in healthcare systems: Development and application of a discrete event simulation with agent-based decision making," Journal of Simulation, vol. 6, pp. 92-102.
  24. Krizmaric M., Zmauc T., Micetic-Turk D., Stiglic G., and Kokol P., 2005. "Time allocation simulation model of clean and dirty pathways in hospital environment," in Computer-Based Medical Systems, 2005. Proceedings. 18th IEEE Symposium on, pp. 123-127.
  25. Laskowski M., McLeod R. D., Friesen M. R., Podaima B. W., and Alfa A. S., 2009. "Models of emergency departments for reducing patient waiting times," PLoS One, vol. 4, p. e6127.
  26. Mahmud R., Aysa Abdul Halim Sithiq H., and Taharim H. M., 2009. A Hybrid Technology for a Multi agent Consultation System in Obesity Domain. World Academy of Science, Engineering and Technology.
  27. Mustafee N., Katsaliaki K., and Taylor S. J. E., 2010. "Profiling literature in healthcare simulation," Simulation, vol. 86, pp. 543-558.
  28. Nealon J. and Moreno A., 2003. "Agent-based applications in health care," in Applications of software agent technology in the health care domain, ed: Springer, pp. 3-18.
  29. Picard G., 2004. Méthodologie de développement de systèmes multi-agents adaptatifs et conception de logiciels à fonctionnalité émergente, thèse de doctorat, Université Paul Sabatier de Toulouse III.
  30. Quesnel G., Duboz R., Ramat E., and Traoré M.K., 2007. VLE: A Multimodeling and Simulation Environment. Proceedings of the Summer Simulation Multiconference (SummerSim'07), San Diego, California, USA, July 15-18, pp. 367-374.
  31. Rosa M. V., Cecilia D. Flores, Andre M. S., Louise J. S., Ladeira M. and Coelho H., 2003. A multi agent intelligent environment for medical knowledge. Artificial Intelligence in medicine, 335-366, Elsevier science B.V.
  32. Rimassa G., Bellifemine F., and Poggi A., JADE - A FIPA Compliant Agent Framework, PMAÌ99, p. 97-108, Londres, 1999.
  33. Stainsby H., Taboada M., and Luque E., "Towards an agent-based simulation of hospital emergency departments," in SCC IEEE International Conference on Services Computing, September 21, 2009 - September 25, 2009, Bangalore, India, 2009, pp. 536-539.
  34. Verga F., 2010. "Modélisation mathématique de processus métastatiques," Université de Provence-Aix-Marseille I.
  35. Van Cutsem E., Findlay M., Osterwalder B., Kocha W., Dalley D., Pazdur R., et al., "Capecitabine, an oral fluoropyrimidine carbamate with substantial activity in advanced colorectal cancer: results of a randomized phase II study," Journal of Clinical Oncology, vol. 18, pp. 1337-1345, 2000.
  36. Wooldridge M., Jennings N. and Kinny D., 2000. 'The Gaia methodology for agent -oriented analysis and design', Autonomous Agents and Multi-Agent Systems, vol. 3, n° 3, pp. 285-312.
  37. Zambonelli F., Jennings N.R. and Wooldridge M., 2003. 'Developing Multiagent Systems: The Gaia Methodology', ACM Transactions on Software Engineering and Methodology, vol. 12, n° 3, pp. 317-370.
  38. Zhang W. and Yao Z., 2010. "A reformed lattice gas model and its application in the simulation of evacuation in hospital fire," in IEEE International Conference on Industrial Engineering and Engineering Management, IEEM2010, December 7, Macao, China, pp. 1543- 1547.

Paper Citation

in Harvard Style

Mustapha K. and Frayret J. (2016). Agent-based Modeling and Simulation Software Architecture for Health Care . In Proceedings of the 6th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH, ISBN 978-989-758-199-1, pages 89-100. DOI: 10.5220/0005972600890100

in Bibtex Style

author={Karam Mustapha and Jean-Marc Frayret},
title={Agent-based Modeling and Simulation Software Architecture for Health Care},
booktitle={Proceedings of the 6th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH,},

in EndNote Style

JO - Proceedings of the 6th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH,
TI - Agent-based Modeling and Simulation Software Architecture for Health Care
SN - 978-989-758-199-1
AU - Mustapha K.
AU - Frayret J.
PY - 2016
SP - 89
EP - 100
DO - 10.5220/0005972600890100