Investigating the Characteristics of Urban Comprehensive Hospitals from a Supply–Demand Balance Perspective: A Case Study of Three Districts in Shenzhen Based on Multi-Source Data

Abstract

As an important public facility in cities, hospitals provide services that are vital to people’s lives. Big data is representative of geographic data from numerous sources. It has the advantages of large amounts of data, high timeliness, and abundant information, which may compensate for the inadequacy of traditional planning and design, which is overly subjective. Big data can be used to obtain large-scale human movement data to study hospital characteristics from a supply–demand balance perspective. Here, 182 comprehensive hospitals in three districts of Shenzhen were picked as an example, and multi-source data were introduced as a quantitative assessment tool to analyze them. First, the mobile public participation geographic information system (PPGIS) was researched and developed independently and used to collect volunteered geographic information (VGI) data, which was adopted to quantify hospital service supply. Second, the population’s demand for hospitals was characterized by the quantified point of interest (POI) data. Finally, the location entropy method was utilized to quantify the levels of supply and demand for comprehensive hospital services from a supply–demand balance perspective, which was used to guide the classification of the comprehensive hospitals. The result shows that: (1) the service scopes and the service pressure are different for the same type of comprehensive hospitals classified by the traditional method; (2) the spatial distribution of patients is related to land function; (3) the overlap area between the part with a high service pressure level in the comprehensive hospital and the part with high medical demand of the patient is prone to service blindness. This study paves a new way to optimize the spatial allocation of medical institutions or other types of public facilities, rationalize resource allocation, and alleviate urban transportation congestion.