ORIGINAL RESEARCH article
Front. Public Health
Sec. Disaster and Emergency Medicine
Volume 13 - 2025 | doi: 10.3389/fpubh.2025.1649542
Optimizing Automated External Defibrillator Deployment Within the Walking Golden Window for Out-of-Hospital Cardiac Arrest Cases: A Case Study From a Chinese city
Provisionally accepted
- 1Xuzhou Medical University, Xuzhou, China
- 2Xuzhou Municipal Emergency Medical Center, Xuzhou, China
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Background: Irreversible brain injury may begin 4-6 minutes after the onset of out-of-hospital cardiac arrest (OHCA) if no cardiopulmonary resuscitation (CPR) is provided. This period is commonly referred to as the "golden window" in China.Based on the walking distance within this window, we proposed an improved public access defibrillation (PAD) deployment strategy to enhance automated external defibrillator (AED) efficiency in typical Chinese cities.Methods: This observational study used two datasets (an AED inventory and an OHCA registry) to assess the current effectiveness of AED deployment in the urban area of the Xuzhou city, Jiangsu Province. Using Geographic Information System (GIS) to determine the optimal AED placement distance based on the golden window walking-route distance. We also used python to simulate the improved model.: In the model, A total of 1,350 OHCAs and 1,238 AEDs were included and 78.4% of OHCAs occurred in the community. The AED coverage rate within 100 m was 7.93% and 7.33% based on the straight-line model and walking-route model. The proportion of OHCAs where an AED was accessible within the walking distance of the golden window accounted for 53.04% on average, with an average of 1.19 AEDs per case. The optimal deployment distance for AEDs to achieve maximum efficiency and approximate the standards of developed cities (Average=1, Proportion=40%) is computed to be 270-280 m in straight line. The simulation demonstration of the improved model shows that the benefit is significantly improved. Conclusions: Our model verified the current mismatch between AED deployment and OHCA cases in Xuzhou city. Based on this, we proposed an improved allocation 2 model, which demonstrated the potential to optimize AED deployment more effectively. Furthermore, by integrating updated PAD strategies, our model can be further adapted to support drone-based AED delivery systems, offering a flexible and data-driven approach for future implementation.
Keywords: Automated external defibrillator, Out-of-Hospital Cardiac Arrest, Deployment, Geographical model, China, Public access defibrillation
Received: 18 Jun 2025; Accepted: 11 Aug 2025.
Copyright: © 2025 Qin, Li, ZHENG, Xu, Xu, Zhang, Lu, Yan, Xu and Zhao. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Yan Xu, Xuzhou Medical University, Xuzhou, China
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