Tian Yu, Shen Zhuyi, Zhao Yinghao, Zhou Tianshu, Li Qiang, Zhang Mao, Li Jingsong
Engineering Research Center of EMR and Intelligent Expert System, Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China.
Research Center for Data Hub and Security, Zhejiang Lab, Hangzhou, China.
Heliyon. 2024 Oct 9;10(20):e39061. doi: 10.1016/j.heliyon.2024.e39061. eCollection 2024 Oct 30.
The frequency of mass gatherings is increasing. Such events often involve many people and carry the risk of mass casualty incidents, which require substantial medical resources from various healthcare institutions. The current medical system, while meeting daily needs, struggles to address the demand for a high volume of emergency resources and real-time data exchange.
The aim of this study was to develop an emergency medical information system for mass gatherings.
We developed an emergency medical information system for mass gatherings. Based on a unified prehospital and intrahospital emergency data exchange protocol, we can directly standardize medical information data and provide data support for the evacuation decision support algorithms of multiple institutions. Wearable devices, vehicle-mounted devices, video calling systems and surveillance systems are connected to capture real-time scenes.
We constructed the system via mobile applications and online platforms and deployed it in 3 hospitals, 5 ambulances and 17 on-site medical locations. We constructed a set of electronic medical records covering the whole first aid process according to the basic principles of first aid. The simulation results show that the proposed algorithm is suitable for mass gatherings. The overall survival rate of patients can be improved by 5 %, and the average evacuation efficiency of patients can be improved by 50 %. Furthermore, in a real-world environment, this method can ensure patient survival and achieve good convergence.
Our system is capable of providing robust medical information support for emergency medical services during large-scale assembly events, ensuring a visualized full-process emergency response and decision-making for the diversion and subsequent transport of a large patient population.
大规模集会的频率正在增加。此类活动通常涉及众多人员，存在大规模伤亡事件的风险，这需要各类医疗机构提供大量医疗资源。当前的医疗系统在满足日常需求的同时，难以应对大量应急资源需求和实时数据交换的要求。
本研究旨在开发一种用于大规模集会的紧急医疗信息系统。
我们开发了一种用于大规模集会的紧急医疗信息系统。基于统一的院前和院内应急数据交换协议，我们能够直接规范医疗信息数据，并为多个机构的疏散决策支持算法提供数据支持。连接可穿戴设备、车载设备、视频通话系统和监控系统以捕捉实时场景。
我们通过移动应用程序和在线平台构建了该系统，并将其部署在3家医院、5辆救护车和17个现场医疗点。我们根据急救基本原则构建了一套涵盖整个急救过程的电子病历。模拟结果表明，所提出的算法适用于大规模集会。患者的总体生存率可提高5%，患者的平均疏散效率可提高50%。此外，在实际环境中，该方法能够确保患者生存并实现良好的收敛。
我们的系统能够为大规模集会期间的紧急医疗服务提供强大的医疗信息支持，确保对大量患者的分流及后续转运进行可视化的全过程应急响应和决策。
