Abstract
Objectives
Emergency medical system for mass casualty incidents (EMS-MCIs) is a global issue. However, China lacks such studies extremely, which cannot meet the requirement of rapid decision-support system. This study aims to realize modeling EMS-MCIs in Shanghai, to improve mass casualty incident (MCI) rescue efficiency in China, and to provide a possible method of making rapid rescue decisions during MCIs.
Methods
This study established a system dynamics (SD) model of EMS-MCIs using the Vensim DSS program. Intervention scenarios were designed as adjusting scales of MCIs, allocation of ambulances, allocation of emergency medical staff, and efficiency of organization and command.
Results
Mortality increased with the increasing scale of MCIs, medical rescue capability of hospitals was relatively good, but the efficiency of organization and command was poor, and the prehospital time was too long. Mortality declined significantly when increasing ambulances and improving the efficiency of organization and command; triage and on-site first-aid time were shortened if increasing the availability of emergency medical staff. The effect was the most evident when 2,000 people were involved in MCIs; however, the influence was very small under the scale of 5,000 people.
Conclusion
The keys to decrease the mortality of MCIs were shortening the prehospital time and improving the efficiency of organization and command. For small-scale MCIs, improving the utilization rate of health resources was important in decreasing the mortality. For large-scale MCIs, increasing the number of ambulances and emergency medical professionals was the core to decrease prehospital time and mortality. For super-large-scale MCIs, increasing health resources was the premise.
Acknowledgments
This study was supported by National Natural Science Foundation of China (71233008, 91224005, and 71774167), Joint Research Project of Major Disease of Shanghai Health System (2013ZYJB0006), and the Major Project in the “12th Five-Year Plan” of the People’s Liberation Army (AWS12J002).
Author contributions
WY, YL, CH, XL, HC, CX, and LZ jointly completed this study. WY, YL, and CH contributed equally to this research. WY made substantial contributions to conception and design, establishing the model, intervention experiments, interpretation of results, drafting the manuscript, and revising it critically for important intellectual content. YL and CH made substantial contributions to conception and design, model validation, interpretation of results, and drafting the manuscript. HC and CX were involved in data collection and intervention experiments. LZ made substantial contributions to conception and design. All authors contributed toward data analysis, drafting and critically revising the paper and agree to be accountable for all aspects of the work.
Disclosure
The authors report no conflicts of interest in this work.