Abstract
Rapid economic and social development has been accompanied by the occurrence of many major issues throughout the world. Specifically, there is an ever-increasing demand for emergent medical services among the public. In order to ensure timely responses to emergency demands, it is critical to reasonably configure the emergency stations. In general, emergency stations are mostly distributed according to the distribution of emergency demands and response time, which, however, fails to consider the negative impacts of randomly occurring emergency demands and traffic delays. In this study, first aid demands are combined with traffic states based on the spatiotemporal big data set covering model, which alleviates the negative impacts of randomly occurring first aid demands and traffic delay time on the planning of pre-hospital first aid stations. Moreover, the accuracy of the site selection model is improved, which meets the requirements that all randomly occurring simulated first aid demands can be approached within the target time under planning conditions and actual traffic constraints. Taking Nanjing City as an example, this study obtains multi-source big data, such as ambulance-carried GPS data from June 2018 to June 2019, Gaode Map-recorded traffic congestion data, and survey data of emergency rescue facilities. Basing on the processing and analysis of these data, it shows that first aid demands in Nanjing City are highly region-specific with high time delay. Various required factors are determined based on modeling and analysis, and the target time is agreed to be 8 min. The average vehicle speed on each road is calculated, accompanied by the establishment of an actual road network model. In this context, the transit time from the randomly distributed first aid stations to the hospital can be calculated, which are set to satisfy the model conditions so as to obtain the solution. Finally, such a solution is adjusted and verified according to the land-use situation. The results of this study, based on spatiotemporal big data, are expected to provide insights into improving the site selection model and enhancing efficiency while providing new technical methods.
Highlights
With the advancement in the global economy and people’s living standards, conflicts between resource exploitation and environmental protection have intensified
Where i is the label of a random simulated demand point, j is the label for a candidate station, V is the set of demand regions, M is the set of the new candidate sites, W is the set of planned emergency stations, H is the set of existing stations, tij is the travelling time from station j to demand region i, according to the actual road network model T, and xj is a 0–1 variable, which equals 1 if an alternative site j is enabled and 0 otherwise
This paper highlights the planning and site selection of first aid stations constrained by the emergency response time, so as to reduce the time consumed by the process to transfer patients to hospitals for medical emergency services after answering the emergency call and sending out the ambulance
Summary
With the advancement in the global economy and people’s living standards, conflicts between resource exploitation and environmental protection have intensified. Emergencies such as natural disasters, accidents, and infectious diseases continuously occur, causing huge economic losses and serious life threats. Pre-hospital care refers to medical activities prior to the arrival of patients at hospitals, including on-site care and monitoring during transit. The pre-hospital care system, the development of which is highly emphasized in countries all over the world, is an integral part of both the urban public security emergency system and the public health system It does directly impact the actual demands of health protection and safety of people, and is an important representation of public service equalization. It is necessary to study the reasonability of the emergency facility’s site selection to build a fair and accessible pre-hospital emergency network, so that any patient can receive timely and effective help when they need emergency treatment
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