Assessing the Spatial Accessibility of Urban Medical Facilities in Multi-Level and Multi-Period Scales Based on Web Mapping API and an Improved Potential Model

Abstract

Urban medical facilities are an irreplaceable foundation for ensuring higher levels of public health and medical equity. Hospital accessibility has an extremely important impact on the allocation efficiency and fairness of medical facilities. Although critical, previous studies on accessibility have often overlooked the layout of medical facilities at different levels and the accurate measures of travel time to hospitals, which are both the most critical and fundamental indicators when assessing hospital accessibility. To avoid these pitfalls, this study considers the Shijingshan District, Beijing, China, as an empirical case and proposes an improved potential model based on Web Mapping API (Application Programming Interface) to assess the hospital accessibility of hospitals at different levels during different time periods. Results show that there are significant spatial and temporal differences in hospital accessibility in Shijingshan District, and traffic congestion and the layout of medical facilities are the two most important factors affecting hospital accessibility. This study further improves the hospital accessibility assessment method, with the findings provide a spatial decision support system for urban planners and policymakers regarding optimizing the spatial structure and layout of transportation systems and medical facilities.

The Seasonal Migrants Spatially Affect the Park Green Space Accessibility and Equity under Different Travel Modes: Evidence from Sanya, China

“…Therefore, the MMGa2SFCA method was proposed in this study to accurately assess changes in PGS accessibility and equity in cities receiving seasonal migrants, with fine-scale spatial units of residential areas presenting population distribution, real-time traffic from the web map API, and travel mode preferences from surveys and official statistics. The average travel time of PT and driving varied with the peak hours, which is in agreement with previous studies [55,56]. In line with the general characteristics of undeveloped areas without significant topographic relief, the order of the average travel time of each mode was driving, riding, PT, and walking, thereby corroborating the findings of a previous study [39].…”

“…Moreover, the accuracy of travel time, which changes significantly due to the influx of seasonal migrants, is crucial for reliable PGS accessibility measurements. Thus, fine-scale population distribution and travel mode preferences are essential for obtaining more reliable PGS accessibility via the web map API [39,[55][56][57].…”

Advancing Urban Healthcare Equity Analysis: Integrating Public Participation GIS with Fuzzy Best–Worst Decision-Making

“…The research employed the k-nearest neighbours algorithm and the Fuzzy Inference System (FIS) as analytical methods. In China, researchers such as Lu et al (2019) [2], Ni et al (2019) [16], and Wang et al (2022) [17] have used travel time criterion to assess patients' accessibility to medical centres in urban and rural areas. Neisani Samani and Alesheikh (2019) [3] investigated healthcare system inequities by considering citizens' preferences.…”