Background: Survival after out-of-hospital cardiac arrest (OHCA) depends heavily on early defibrillation. Reducing the time from cardiac arrest to defibrillation is a key factor in improving survival. In recent years, many countries have promoted early defibrillation through public automated external defibrillator (AED) networks. However, in practice, public access to and use of AEDs remain limited because of insufficient accessibility, uneven distribution, difficulties in locating devices, and delays in retrieval. With the development of drone technology, rapid drone-based AED delivery has been considered a potentially promising solution. Drones may bypass ground traffic congestion and reach the scene more quickly via aerial routes, allowing bystanders to use an AED under remote guidance. Although simulation studies, system optimization studies, and preliminary real-world applications of drone-delivered AEDs have been reported in other countries, this field remains exploratory in China. At present, most Chinese cities still rely mainly on conventional ambulance dispatch systems and fixed AED networks, both of which may be limited by urban traffic congestion, high population density, and uneven spatial distribution of AEDs. Objective: This prospective quasi-real-world simulation study in Wuhu, Anhui Province, China, aims to compare the time efficiency of a drone-based AED delivery pathway with that of a standard ground ambulance response pathway in simulated OHCA scenarios. The study will also evaluate the effects of geographic setting, traffic period, and different aerial delivery modes on delivery performance, in order to provide preliminary evidence for the deployment of drone-assisted emergency response networks in Chinese cities. Methods: This is an open-label, non-randomized, exploratory pilot feasibility study. The drone launch site will be located at a designated takeoff and landing area near the Emergency Department building of the Second Affiliated Hospital of Wannan Medical College. Simulated task endpoints will be selected within a 30-km one-way mission radius from the launch site. The study includes three sub-studies: (1) comparison of response efficiency between the drone pathway and the ground ambulance pathway in urban versus suburban locations; (2) comparison of response efficiency between the drone pathway and the ground ambulance pathway during peak versus off-peak traffic periods; and (3) comparison of operational time and success rate among three drone AED delivery modes, including winch lowering, low-altitude compartment retrieval, and direct landing. A total of 24 healthy volunteers will participate in the simulation tasks, and 1 to 3 professional drone operators will conduct flight operations. For each simulated task, a unified start command will be issued by the study coordinator, and the volunteer will receive the AED and complete electrode pad placement on the manikin. Primary Outcome: The primary outcome is the time from the unified simulated task start to completion of AED pad placement on the manikin chest.
Study Type
INTERVENTIONAL
Allocation
NON_RANDOMIZED
Purpose
HEALTH_SERVICES_RESEARCH
Masking
NONE
Enrollment
24
The drone platform is a DJI M400 operating along pre-specified flight routes and carrying a lightweight AED training device. The AED device used in this study is a Mindray BeneHeart series AED trainer, which is a simulation device rather than a live AED. Depending on the sub-study, one of three delivery modes will be used: winch lowering, low-altitude compartment retrieval, or direct landing. The mission will primarily be executed automatically based on preset flight routes, while the drone operator will monitor the mission and take over when necessary for safety or contingency management.
The control pathway will be simulated using a standard ambulance, a fixed ambulance crew, and a predefined operational workflow modeled on the local standard prehospital emergency response process.
The Second Affiliated Hospital of Wannan Medical College
Wuhu, Anhui, China
Time From Unified Simulated Task Start to AED Pad Placement on the Manikin Chest
Defined as the elapsed time from issuance of the unified simulated task start command by the study coordinator to completion of standard placement of both AED pads on the manikin chest. Time points will be recorded by the lead timekeeper using a standardized timing tool.
Time frame: Up to 30 minutes
Difference in Call-to-Pad-Placement Time Between Urban and Suburban Settings
Defined as the difference in elapsed time from the unified simulated task start to completion of AED pad placement on the manikin chest between urban and suburban scenarios in Sub-study 1, comparing the drone pathway with the standard ground ambulance response pathway.
Time frame: Up to 30 minutes
Difference in Call-to-Pad-Placement Time Between Peak and Off-Peak Traffic Periods
Defined as the difference in elapsed time from the unified simulated task start to completion of AED pad placement on the manikin chest between peak and off-peak traffic scenarios in Sub-study 2, comparing the drone pathway with the standard ground ambulance response pathway.
Time frame: Up to 30 minutes
Successful AED Delivery Rate by Drone Delivery Mode
Defined as the proportion of simulation tasks in Sub-study 3 in which the AED training device is successfully delivered to the designated volunteer according to the predefined workflow and is available for retrieval without safety-related interruption.
Time frame: Up to 30 minutes
AED Retrieval Time by Drone Delivery Mode
Defined as the elapsed time from drone arrival above the target area or at the landing point to successful retrieval of the AED training device by the designated volunteer in Sub-study 3.
Time frame: Up to 10 minutes
Stage-Specific Time Measures in the Drone Pathway
Includes dispatch delay, flight time, delivery delay, and volunteer pad-placement time in the drone pathway during each simulated task.
Time frame: Up to 30 minutes
Stage-Specific Time Measures in the Ground Ambulance Pathway
Includes dispatch delay, driving time, AED retrieval delay, and volunteer pad-placement time in the ground ambulance pathway during each simulated task in Sub-studies 1 and 2.
Time frame: Up to 30 minutes
Actual Flight Distance per Drone Mission
Defined as the actual flight distance traveled by the drone during each mission, measured in kilometers.
Time frame: During each drone mission, up to 60 minutes
Average Cruising Speed per Drone Mission
Defined as the average cruising speed of the drone during each mission, measured in kilometers per hour.
Time frame: During each drone mission, up to 60 minutes
Yanguoer Zhang
CONTACT
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