Abstract
Decision-making is a crucial aspect of emergency response during mass casualty incidents (MCIs). MCIs require rapid decisions to be taken by geographically-dispersed teams in an environment characterized by insufficient information, ineffective collaboration and inadequate resources. Despite the increasing adoption of decision support systems in healthcare, there is limited evidence of their value in large-scale disasters. We conducted focus groups with emergency medical services and emergency department personnel who revealed that one of the main challenges in emergency response during MCIs is information management. Therefore, to alleviate the issues arising from ineffective information management, we propose R-CAST-MED, an intelligent agent architecture built on Recognition-Primed Decision-making (RPD) and Shared Mental Models (SMMs). A simulation of R-CAST-MED showed that this tool enabled efficient information management by identifying relevant information, inferring missing information and sharing information with other agents, which led to effective collaboration and coordination of tasks across teams.
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References
Hirshberg, A., Holcomb, J.B., Mattox, K.L.: Hospital Trauma Care in Multiple-Casualty Incidents. A Critical View Annals of Emergency Medicine 37(6), 647–652 (2001)
Aylwin, C.J., Konig, T.C., Brennan, N.W., Shirley, P.J., Davies, G., Walsh, M.S., Brohi, K.: Reduction in Critical Mortality in Mass Casualty Incidents: Analysis of Triage, Surge, and Resource Use After the London Bombings on July 7, 2005. In: Lancet, vol. 368(9554), pp. 2219–2225 (2006)
Asaeda, G.: The Day that the START Triage System Came to a STOP: Observations from the World Trade Center Disaster. Academic Emergency Medicine 9(3), 255–256 (2002)
Oster, N., Nierenberg, R., Menlove, S., Chason, K., Pruden, J.: Reflections: September 11, 2001 – What We Learned. Academic Emergency Medicine 9(3), 216 (2002)
Frize, M., Trigg, H.C.E., Solven, F.G., Stevenson, M., Nickerson, B.G.: Decision-Support Systems Designed for Critical Care. AMIA Fall Meeting (1997)
Stephenson, R., Anderson, P.S.: Disasters and the information technology revolution. Disasters 21, 305–334 (1997)
Gaynor, M., Seltzer, M., Moulton, S., Freedman, J.: A Dynamic, Data-Driven, Decision Support System for Emergency Medical Services. In: Sunderam, V.S., van Albada, G.D., Sloot, P.M.A., Dongarra, J.J. (eds.) ICCS 2005. LNCS, vol. 3515, pp. 703–711. Springer, Heidelberg (2005)
Guterman, J.J., Mankovich, N.J., Hiller, J.: Assessing the effectiveness of a computer-based decision support system for emergency department triage. IEEE (1993)
Michalowski, W., Rubin, S., Slowinski, R., Wilk, S.: Mobile Clinical Support System for Pediatric Emergencies. Decision Support Systems 36, 161–176 (2003)
Yen, J., Yin, J., Ioerger, T.R., Miller, M., Xu, D., Volz, R.A.: CAST: Collaborative Agents for Simulating Teamwork. In: Proceedings of the 7th International Joint Conference on Artificial Intelligence, pp. 1135–1142 (2001)
Klein, G.A.: Recognition-primed decisions. In: Advances in man-machine systems research, vol. 5, pp. 47–92. JAI Press, W. B. Rouse. Greenwich, CT (1989)
Cannon-Bowers, J.A., Salas, E., Converse, S.A.: Cognitive psychology and team training: Training shared mental models and complex systems. Human Factors Society Bulletin 33, 1–4 (1990)
McNeese, M.D., Bains, P., Brewer, I., Brown, C., Connors, E.S., Jefferson, T., et al.: The NeoCITIES simulation: Understanding the design and experimental methodology used to develop a team emergency management simulation. In: Proceedings of the 49th Annual Meeting of the Human Factors and Ergonomics Society, pp. 591–594 (2005)
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Zhu, S. et al. (2007). R-CAST-MED: Applying Intelligent Agents to Support Emergency Medical Decision-Making Teams. In: Bellazzi, R., Abu-Hanna, A., Hunter, J. (eds) Artificial Intelligence in Medicine. AIME 2007. Lecture Notes in Computer Science(), vol 4594. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73599-1_3
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DOI: https://doi.org/10.1007/978-3-540-73599-1_3
Publisher Name: Springer, Berlin, Heidelberg
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