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A Novel Approach for the Administration of Medications and Fluids in Emergency Scenarios and Settings
Published on: November 9, 2016
Design of an emergency medical information system for mass gatherings
Yu Tian1, Zhuyi Shen1, Yinghao Zhao2
1Engineering Research Center of EMR and Intelligent Expert System, Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China.
Background:
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.
Objective:
The aim of this study was to develop an emergency medical information system for mass gatherings.
Methods:
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.
Results:
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.
Conclusions:
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.
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