An unmanned emergency blood dispatch system based on an early prediction and fast delivery strategy: Design and development study. (June 2023)

• Record Type: Journal Article
• Authors: Xia, Jing; Li, Qiang; Tian, Yu; Zhao, Yinghao; Shen, Zhuyi; Zhou, Tianshu; Li, Jingsong
• Is Part Of: Computer methods and programs in biomedicine. Volume 235(2023)
• Publication Date: 2023-06
• Subjects: Hemorrhagic trauma patients -- Transfusion prediction model -- Unmanned aerial vehicles -- Dispatch system; Medicine -- Computer programs -- Periodicals; Biology -- Computer programs -- Periodicals; Computers -- Periodicals; Medicine -- Periodicals; Médecine -- Logiciels -- Périodiques; Biologie -- Logiciels -- Périodiques; Biology -- Computer programs; Medicine -- Computer programs; Periodicals; Electronic journals; 610.28
• DOI: 10.1016/j.cmpb.2023.107512
• Languages: English
• ISSNs: 0169-2607

Abstract

Highlights: An unmanned emergency blood dispatch system was designed for the fast delivery of blood resources and rapid emergency response to trauma events. Unmanned aerial vehicles (UAVs) and an early prediction model were introduced in the emergency medical services for trauma patients. Through the combination of an emergency transfusion prediction model and UAV-related dispatch algorithms, the proposed system improves first aid efficiency and quality for major hemorrhagic patients in both urban and rural scenarios. With the assistance of the system, emergency doctors at the injury scene can make decisions based on the comprehensive analysis of patients' status and the surrounding rescue conditions, especially when encountering mass casualties or casualties in remote areas. Abstract: Background and objective: For severe trauma patients, hemorrhage is the most common cause of medically preventable deaths. Early transfusion is beneficial to major hemorrhagic patients. However, the early supply of emergency blood products for major hemorrhagic patients is still a major problem in many areas. The aim of this study was to design and develop an unmanned emergency blood dispatch system for the fast delivery of blood resources and rapid emergency response to trauma events, especially those with mass hemorrhagic trauma patients and those occurred in remote areas. Methods: Based on the process of emergency medical services for trauma patients, we introduced unmanned aerial vehicle (UAV) and designed the main flowchart of the dispatch system, which combines an emergency transfusion prediction model and UAV-related dispatch algorithms to improve first aid efficiency and quality. The system identifies patients in need of emergency transfusion through a multidimensional prediction model. Then, by analyzing the blood center, hospitals and UAV stations nearby, the system recommends the patient's transfer destination for emergency transfusion and dispatch schemes of UAVs and trucks for a fast supply of blood products. Simulation experiments of urban and rural scenarios were conducted to evaluate the proposed system. Results: The developed emergency transfusion prediction model of the proposed system achieves a higher AUROC value of 0.8453 than a classical transfusion prediction score. In the urban experiment, by adopting the proposed system, the average wait time per patient decreased from 32 to 18 min, and the total time decreased from 42 to 29 min. Owing to the combination of the prediction and the fast delivery function, the proposed system took 4 and 11 min less wait time than the strategy with only the prediction function and the strategy with only the fast delivery function, respectively. In the rural experiment, for trauma patients requiring an emergency transfusion at 4 locations, the wait time for transfusion under the proposed system was 16.54, 17.08, 38.70 and 46.00 min less than that under the conventional strategy. The health status-related score increased by 6.9%, 0.9%, 19.1% and 36.7%, respectively. Conclusions: Experimental results demonstrate that the proposed system works well with a faster blood supply speed for severe hemorrhagic patients and better health status. With the assistance of the system, emergency doctors at the scene of an injury are able to comprehensively analyze patients' status and the surrounding rescue conditions and then make decisions, especially when encountering mass casualties or casualties in remote areas.