Evaluating spatial accessibility to healthcare services from the lens of emergency hospital visits based on floating car data

Wei, Jiao; Huang, Weiping; Fan, Hongchao

doi:10.1080/17538947.2021.2014578

Cited by 20 publications

(9 citation statements)

References 70 publications

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“…Specifically, in the three time periods of 9:00-9:10, 12:00-12:10, and 15:00-15:10, the increase in the pick-up ratio is relatively low, at 127.0%; in the three time periods of 0:00-0:10, 3:00-3:10, and 6:00-6:10, the pick-up ratio increased by 466.0%, which was more than three times that of the former. The above findings are consistent with the characteristics of residents' travel; that is, residents' demand for taxi travel is relatively average during the day, and drivers are more likely to pick up passengers in various regions of the city [35]. However, from midnight From Figure 11, it can be seen that the taxi accessible range boundary and the real-time pick-up ratio from the initial grid, grid 330, are different in different periods, and the pickup ratio of the optimal cruising area is effectively improved compared with the initial grid.…”

Section: ) Identification Of Optimal Cruising Area In Different Time ...supporting

confidence: 79%

“…Specifically, in the three time periods of 9:00-9:10, 12:00-12:10, and 15:00-15:10, the increase in the pick-up ratio is relatively low, at 127.0%; in three time periods of 0:00-0:10, 3:00-3:10, and 6:00-6:10, the pickup ratio increased by 466.0%, which was more than three times that of the former. The above findings are consistent with the characteristics of residents' travel; that is, residents' demand for taxi travel is relatively average during the day, and drivers are more likely to pick up passengers in various regions of the city [35]. However, from midnight to early morning, different from traditional modes of transportation such as public transportation and the subway, the demand for taxi travel is still relatively strong, but the distribution of travel is no longer scattered, and it is concentrated in nightlife-rich areas such as an urban central business district [36].…”

Section: ) Identification Of Optimal Cruising Area In Different Time ...supporting

confidence: 79%

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The Real-Time Dynamic Prediction of Optimal Taxi Cruising Area Based on Deep Learning

Wang,

et al. 2024

Sustainability

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A real-time, effective, and dynamic taxi cruising recommendation strategy is essential to solving the problem of taxi cruising passenger difficulty and urban road traffic congestion. This study focuses on two aspects of the real-time accessible range and pick-up ratio (PR) and proposes a real-time dynamic identification method for taxi optimal cruise-seeking area. Firstly, based on the cumulative opportunity method, a univariate temporal convolutional network (UTCN) accessible range dynamic prediction model is proposed to predict the real-time accessible range of taxis. Secondly, based on the gradient boosting decision tree (GBDT) model, the influencing factors with a high correlation with the PR are selected from the four dimensions of traffic characteristics, environmental meteorology, and time and space variables. Then, a multivariate univariate temporal convolutional network (MTCN) global grid PR prediction model is constructed, and the optimal taxi cruising area is identified based on the maximum PR. The results show that the taxi accessible range and PR of the same grid in different periods change with time, and based on the model comparison, the accessible range and PR prediction results of UTCN and MTCN algorithms in different periods are the best to identify the optimal cruising area of taxis in different periods. The main contribution of this study is that the proposed optimal cruising area prediction model has timeliness, accessibility, and dynamics. It can not only improve the probability of taxis receiving passengers and avoid taxis cruising aimlessly, but also solve the shortage of taxis in hotspots, thus shortening the waiting time of passengers. This provides a scientific basis for improving taxi cruising efficiency and the government’s formulation of taxi operation management policies, which can effectively promote the sustainable development of urban traffic.

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Section: ) Identification Of Optimal Cruising Area In Different Time ...supporting

confidence: 79%

Section: ) Identification Of Optimal Cruising Area In Different Time ...supporting

confidence: 79%

The Real-Time Dynamic Prediction of Optimal Taxi Cruising Area Based on Deep Learning

Wang,

et al. 2024

Sustainability

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Section: Discussionmentioning

confidence: 99%

“…First, the method used to calculate the travel cost fails to consider the timeliness and characteristics of the population. The time parameters of the 2SFCA should be based on residents' actual travel behavior for selection (Jiao et al., 2022 ; C. Li & Wang, 2022 ); however, we calculated the travel cost based on the average speed of different types of roads. On the contrary, the cost of accessing CHC services varies by population structure, such as age, gender, income, and so on, and we also need to conduct a specific travel cost analysis (Shao & Luo, 2022 ; F. Zhang et al., 2019 ).…”

Section: Discussionmentioning

confidence: 99%

Spatial Accessibility Evaluation and Location Optimization of Primary Healthcare in China: A Case Study of Shenzhen

Chen

Zeng²,

Wu³

et al. 2023

GeoHealth

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China has striven to improve its healthcare system by continuously reforming its health system and improving the quality of medical care (X. L. Li & Fu, 2017). Consequently, during the past decade, the overall public health of the Chinese population has improved significantly, with more than 95% of its citizens covered by the health insurance system. In addition, people are living longer because of access to more affordable and higher-quality healthcare services. However, despite these laudable achievements, distance and time are also important barriers hindering people's access to healthcare services (Song et al., 2022). People face long travel times to healthcare facilities when they are sick and seeking healthcare (Weiss et al., 2020). China is a vast country characterized by considerable regional differences. In general, rural and remote China are disadvantaged in the allocation of healthcare resources because of their underdeveloped economies and unfavorable geographic locations (C. Yang et al., 2022;Yip et al., 2019). However, the cost of healthcare facilities can also be heavy in densely populated cities as some areas lack sufficient health infrastructure, creating challenges for better healthy living across communities (

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“…For example, a study from Shenzhen, China, calculated the accessibility of high-level hospitals and analysed their spatial variation to ultimately identify underserved areas [11]. Another study explored the spatio-temporal distribution characteristics of nighttime hospitals and calculated their accessibility based on population density [12]. However, such studies have only looked at a single class of public service facility and have given less attention to evaluating the level of equity in different classes of public general hospitals.…”

Section: Introductionmentioning

confidence: 99%

Spatial Vertical Equity in Public General Hospitals: Towards a Sustainable Healthcare System

Jian

Yung

et al. 2023

Land

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The accessibility of public general hospitals is essential for the well-being of urban residents and for more equitable urban planning. However, public general hospitals and the associated spatial vertical equity are still not well known in developing countries. The objective of our study is to propose a theoretical framework to investigate the accessibility of public general hospitals and spatial vertical equity based on demographic dimensions. The main urban area of Wuhan is a suitable and representative example to explore this issue. An enhanced Gaussian two-step floating catchment area method, the Lorenz curve, and the Gini coefficient are employed in this study. The results indicate significant spatial heterogeneity in the accessibility of public general hospitals due to the dramatic transformation of urban planning and heterogeneous spatial structure. From a spatial vertical equity perspective, the spatial distribution of most public general hospitals does not take into account communities with a high proportion of minors and seniors. Compared with seniors, minors face more serious inequities in access to healthcare. The spatial distribution of only a few public general hospitals is prospective and inclined. Evidence-based policy implications are portrayed as a more equitable urban form and a sustainable healthcare system.

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Evaluating spatial accessibility to healthcare services from the lens of emergency hospital visits based on floating car data

Cited by 20 publications

References 70 publications

The Real-Time Dynamic Prediction of Optimal Taxi Cruising Area Based on Deep Learning

The Real-Time Dynamic Prediction of Optimal Taxi Cruising Area Based on Deep Learning

Spatial Accessibility Evaluation and Location Optimization of Primary Healthcare in China: A Case Study of Shenzhen

Spatial Vertical Equity in Public General Hospitals: Towards a Sustainable Healthcare System

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