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Symbiotic Simulation Decision Support System for Injury Prevention

  • Gokul Bhandari
  • Anne Snowdon
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 4)

Abstract

Symbiotic simulation decision support systems refer to a class of decision support systems in which there is a presence of beneficial feedback between a physical system and a simulation system. In this paper, we report the design and development of such a system in the area of injury prevention. Specifically, we used our decision support system to lower the occurrences of patient falls in hospitals and to minimize injury and death due to the improper use of child safety seats in vehicles. Empirical results from our study show a great potential of our DSS for assisting decision makers and stakeholders in the healthcare sector.

Keywords

Decision Support System Injury Prevention Road Safety Road Traffic Injury Safety Seat 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. Aydt, H., Turner, S.J., Cai, W.: Symbiotic simulation systems: An extended definition motivated by symbiosis in biology. In: 22nd Workshop on Principles of Advanced and Distributed Simulation, pp. 109–116. IEEE Computer Society, Los Alamitos (2008)CrossRefGoogle Scholar
  2. Blanquer, I., Hernandez, V., Segrelles, D., Robles, M., Garcia, J.M., Robledo, J.V.: Clinical decision support systems (CDSS) in GRID environments, from grid to healthgrid. In: Healthgrid, vol. 112, pp. 80–89 (2005)Google Scholar
  3. Fujimoto, R., Lunceford, D., Page, E., Uhrmacher, A.M.: Grand Challenges for Modeling and Simulation, Dagstuhl Report (August 2002)Google Scholar
  4. Gulich, M.: A simulation-based embedded system prototype. Master’s thesis, Royal Institute of Technology (KTH), Stockholm (2004)Google Scholar
  5. Huang, Q., Hallmats, J., Wallenius, K., Brynielsson, J.: Simulation-based decision support for command and control in joint operations. In: Proceedings of the 2003 European Simulation Interoperability Workshop, number 03E-SIW-091, Stockholm, Sweden, June 2003, pp. 591–599 (2003)Google Scholar
  6. Kennedy, C., Theodoropoulos, G., Sorge, V., Ferrari, E., Lee, P., Skelcher, C.: AIMSS: An Architecture for Data Driven Simulations in the Social Sciences. In: Shi, Y., et al. (eds.) ICCS 2007. LNCS, vol. 4487, pp. 1098–1105. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  7. Kobti, Z., Reynolds, R.G., Kohler, T.: A multi-agent simulation using cultural algorithms: The effect of culture on the resilience of social systems. In: IEEE Conference on Evolutionary Computation, CEC 2003, vol. 3, pp. 1988–1995 (2003)Google Scholar
  8. Kobti, Z., Snowdon, A.W., Kent, R.D., Dunlop, T., Rahaman, S.: A multi-agent model prototype for child vehicle safety injury prevention. In: Agent 2005 Conference on: Generative Social Processes, Models, and Mechanisms, Argonne National Laboratory, University of Chicago, Chicago (2005)Google Scholar
  9. Krug, E.G., Sharma, G.K., Lozano, R.: The Global Burden of Injuries. American Journal of Public Health 90(4), 523–526 (2000)CrossRefGoogle Scholar
  10. Leitch, K.: Reaching for the Top: A Report by the Advisor on Health Children and Youth, Health Canada (2008), http://www.hc-sc.gc/ahc-asc/media/nr-cp/2008/2008_51_e.html
  11. Low, M.Y.H., Lye, K.W., Lendermann, P., Turner, S.J., Chim, R.T.W., Leo, S.H.: An agent-based approach for managing symbiotic simulation of semiconductor assembly and test operation. In: Proceedings of the Fourth International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 85–92. ACM Press, New York (2005)CrossRefGoogle Scholar
  12. Mitchell, B., Yilmaz, L.: Symbiotic adaptive multisimulation: An autonomic simulation framework for real-time decision support under uncertainty. ACM Trans. Model. Comput. Simul. 19(1), Article 2, 31 pages (2008)CrossRefGoogle Scholar
  13. National Science Foundation: DDDAS: Dynamic data driven applications systems. Program Solicitation 05-570 (2005), http://www.nsf.gov/pubs/2005/nsf05570/nsf05570.htm
  14. Omar, W.M., Taleb-Bendiab, A.: Service oriented architecture for E-health support services based on grid computing. In: IEEE International Conference on Services Computing (SCC 2006), pp. 135–142 (2006)Google Scholar
  15. Skoglar, P., Nygards, J., Bjorstrom, R., Ogren, P., Hamberg, J., Hermansson, P., Ulvklo, M.: Path and sensor planning framework applicable to uav surveillance with EO/IR sensors. Technical report, FOI-Swedish Defence Research Agency, SE-581 11 Linkoping, Sweden (September 2005)Google Scholar
  16. Snowdon, A., Howard, A., Boase, P.: The development of a protocol for a national study of Canadian children’s safety in vehicles. In: 17th Canadian Multidisciplinary Road Safety Conference, Montreal, Quebec, June 10-12 (2007)Google Scholar
  17. Snowdon, A., Kolga, C., Hussein, A., High, L., Howard, A.: A National study of Canadian children’s safety in vehicles. In: 18th Canadian Multidisciplinary Road Safety Conference, Whistler, Columbia, June 8-10 (2008)Google Scholar
  18. Suzic, R., Wallenius, K.: Effects based decision support for riot control: Employing influence diagrams and embdedded simulation. In: Proceedings of MILCOM 2005, Atlantic City, New Jersey (October 2005)Google Scholar
  19. Von Lubitz, D., Wickramasinghe, N.: Network centric healthcare: Applying the tools, techniques, and strategies of knowledge management to create superior healthcare operations. International Journal of Electronic Healthcare 2(4), 415–429 (2006)Google Scholar
  20. Weber, K.: Crash protection for child passengers: A review of best practice. UMTRI Research Review 31(3), 1–27 (2000)Google Scholar
  21. World Health Organization: Overview Fact Sheet: Road Traffic Injuries (2004), http://www.who.int/world-healthday/previous/2004/en/traffic_facts_en.pdf

Copyright information

© Springer Berlin Heidelberg 2010

Authors and Affiliations

  • Gokul Bhandari
    • 1
  • Anne Snowdon
    • 1
  1. 1.University of WindsorCanada

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