Revealing the decision-making practices in automated external defibrillator deployment: insights from Shanghai, China.

Abstract

In recent years, the government has promoted the increased deployment of automated external defibrillators (AEDs) in public places with dense crowds, which is of great significance for ensuring that residents enjoy equal health rights. However, it is still unclear what factors decision-makers take into account when formulating deployment plans and whether these factors are related to local characteristics such as population distribution and socioeconomic conditions. Taking Shanghai, China as the research area, we adopted the kernel density estimation and spatial autocorrelation analysis to explore the spatial distribution characteristics of AEDs. We constructed a geographically weighted regression (GWR) model to identify the key factors influencing AED deployment. The results showed that AEDs in Shanghai presented obvious clustering distribution characteristics. The GWR model found that the factors considered by decision-makers in different regions when deploying AEDs followed the guidance of existing policies. It was also found that decision-makers in Shanghai mainly deployed more devices in areas with a high density of the elderly population, dense transportation networks, cultural and educational places, and transportation hubs with large population flows. However, it was observed that the city center might lack sufficient preparation for the elderly group. In order to allocate emergency medical resources more reasonably, it is very important to determine the practices of decision-makers in deploying AEDs. The GWR has shown the potential to evaluate and guide the local implementation of deployment plans.