JDR Vol.18 No.2 pp. 104-113
doi: 10.20965/jdr.2023.p0104


Modeling and Simulation of In-Hospital Disaster Medicine in a Mass Casualty Event for the Resilience Evaluation of BCPs

Mizuki Umemoto*1,†, Shunsuke Kadono*1, Taro Kanno*1, Kazumi Kajiyama*2, Sachika Sharikura*3, Ryoko Ikari*2, Masashi Yoneyama*3, and Sheuwen Chuang*4

*1The University of Tokyo
7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan

Corresponding author

*2Kitasato University Hospital, Sagamihara, Japan

*3Showa University Hospital, Tokyo, Japan

*4Taipei Medical University Hospital, Taipei, Taiwan

August 30, 2022
November 17, 2022
February 1, 2023
disaster prevention, earthquake, business continuity planning (BCP), mass casualty incident

In this study, we developed a simulation model of detailed in-hospital disaster response to a mass casualty incident based on the analysis of related documents and actual in-hospital disaster response training, aiming to assess the hospital’s response capacity under various disaster situations. This simulation model includes detailed models of patients, floor configurations, resources, and response tasks, which consider resource requirements for the treatment of different patients with various injuries and physical conditions. The model covers patients’ arrivals to hospitalization or discharge. We conducted simulations of the target hospital to test two resource allocation strategies under two patient scenarios. By comparing the results under different resource allocation strategies, we found that the X-ray photography examination capacity could become a fundamental bottleneck in responding to mass casualty incidents. Also, we found that the appropriate resource allocations and quick replenishment could alleviate the negative effect of resource shortages and maintain a higher performance. Furthermore, the results show that the length of stay can be heavily affected by the patients’ configuration. As a result, by monitoring and anticipating the situation, a resilient and responsive resource allocation strategy must be prepared to handle such uncertain disaster situations.

Cite this article as:
M. Umemoto, S. Kadono, T. Kanno, K. Kajiyama, S. Sharikura, R. Ikari, M. Yoneyama, and S. Chuang, “Modeling and Simulation of In-Hospital Disaster Medicine in a Mass Casualty Event for the Resilience Evaluation of BCPs,” J. Disaster Res., Vol.18 No.2, pp. 104-113, 2023.
Data files:
  1. [1] International Organization for Standardization (ISO), “ISO 22301:2019: Security and resilience – Business continuity management systems – Requirements,” 2019.
  2. [2] [Accessed August 20, 2022]
  3. [3] [Accessed August 20, 2022]
  4. [4] [Accessed August 20, 2022]
  5. [5] K. L. Fulmer, “Business continuity planning: A step-by-step guide with planning forms,” 3rd Edition, Rothstein Associates, Incorporated, 2007.
  6. [6] A. H. Kaji and R. J. Lewis, “Assessment of the reliability of the Johns Hopkins/Agency for healthcare research and quality hospital disaster drill evaluation tool,” Ann. Emerg. Med., Vol.52, No.3, pp. 204-210.e8, 2008.
  7. [7] G. P. Cimellaro and M. Piqué, “Resilience of a hospital Emergency Department under seismic event,” Adv. Struct. Eng., Vol.19, No.5, pp. 825-836, 2016.
  8. [8] A. Alsubaie, K. Alutaibi, and J. Marti, “Resources allocation in emergency response using an interdependencies simulation environment,” Proc. of 2015 IEEE Canada Int. Humanitarian Technology Conf. (IHTC2015), 2015.
  9. [9] Y. Wang, K. L. Luangkesorn, and L. Shuman, “Modeling emergency medical response to a mass casualty incident using agent-based simulation,” Socio-Econ. Plan. Sci., Vol.46, No.4, pp. 281-290, 2012.
  10. [10] H. Niessner, M. S. Rauner, and W. J. Gutjahr, “A dynamic simulation–optimization approach for managing mass casualty incidents,” Oper. Res. Health Care, Vol.17, pp. 82-100, 2018.
  11. [11] M. Bruneau and A. Reinhorn, “Exploring the concept of seismic resilience for acute care facilities,” Earthq. Spectra, Vol.23, No.1, pp. 41-62, 2007.
  12. [12] P. Trucco et al., “Assessing hospital adaptive resource allocation strategies in responding to mass casualty incidents,” Disaster Med. Public Health Prep., Vol.16, No.3, pp. 1105-1115, 2021.
  13. [13] T. Kanno et al., “Resource-centric business continuity and resiliency planning,” Proc. of the 8th. REA Symp. on Resilience Engineering, 2019.
  14. [14] S. Chuang et al., “Beyond surge: Coping with mass burn casualty in the closest hospital to the Formosa Fun Coast Dust Explosion,” Burns, Vol.45, No.4, pp. 964-973, 2019.
  15. [15] S. Chuang, D. D. Woods, H.-W. Ting, R. I. Cook, and J.-C. Hsu, “Coping with a mass casualty: Insights into a hospital’s emergency response and adaptations after the Formosa Fun Coast Dust Explosion,” Disaster Med. Public Health Prep., Vol.14, No.4, pp. 467-476, 2020.
  16. [16] J. Harada et al., “Modeling and simulation of disaster response in a large-scale hospital (1): Task analysis on in-hospital disaster response in a large-scale hospital,” Proc. of the 7th Int. Research Conf. on World Society of Disaster Nursing, (in press).
  17. [17] Y. Kondo, M. Ichikawa, H. Kondo, Y. Koido, and Y. Otomo, “Current disaster medicine in Japan and the change brought by information sharing,” J. Disaster Res., Vol.14, No.2, pp. 292-302, 2019.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on May. 10, 2024