ArticleBMC health services research2022
Supply-demand matching of medical services at a city level under the background of hierarchical diagnosis and treatment - based on Didi Chuxing Data in Haikou, China.
Article in BMC health services research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.
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Who cites it
22 citing papers in PubMed, 1 synthesis or guideline pooled it, 42 citations in OpenAlex.
- Pooled it
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- Spatial Accessibility and Supply-Demand Mismatch of Primary Healthcare Facilities in the Main Urban Area of Guangzhou.Journal of urban health : bulletin of the New York Academy of Medicine · 2026Article
- Temporal-spatial analysis and driving factors of coupling coordination between population and health services systems in China, 2010-2022.BMC health services research · 2026Article
- Quantitative evaluation of the medical resource allocation policy in China: a PMC-index model approach.Cost effectiveness and resource allocation : C/E · 2026Article
- Assessing the relationship between the hospital grading system and medical resource utilization: evidence from China.Cost effectiveness and resource allocation : C/E · 2026Article
- Towards efficient AED deployment: a multi-source data-driven geographic information approach.Frontiers in public health · 2026Article
- Impact of initial physician contact on later-life health service utilization: a life course perspective.BMC health services research · 2025Article
- Does population density impact maternal and child health? Mediating effects of the Universal Health Coverage Service Coverage Index.BMC public health · 2025Article
- The mismatch in hierarchical diagnosis and treatment construction and related reasons: a qualitative analysis from ZX City, Hubei Province.Frontiers in public health · 2025Article
- Article
- Research on the coupling measurement of medical education and health resource allocation under the background of healthy China.BMC medical education · 2024Article
- Analysis of factors influencing hospitalization cost of patients with distal radius fractures: an empirical study based on public traditional Chinese medicine hospitals in two cities, China.BMC health services research · 2024Article
- The economic effect of financial compensation in China's healthcare system: comprehensive insights regarding supply and demand factors.Health economics review · 2024Article
- Effectiveness of hierarchical medical system and economic growth: based on China's urban vs. rural health perspectives.Frontiers in public health · 2024Article
- Demands for Community Services and Associated Factors among Residents in Smart Communities: A Case Study of Xuzhou City.International journal of environmental research and public health · 2023Article
- Shared decision making in sarcopenia treatment.Frontiers in public health · 2023Review
- Patient allocation method in major epidemics under the situation of hierarchical diagnosis and treatment.BMC medical informatics and decision making · 2022Article
- Spatial Analysis on Supply and Demand of Adult Surgical Masks in Taipei Metropolitan Areas in the Early Phase of the COVID-19 Pandemic.International journal of environmental research and public health · 2022Article
- The impact of medical service on the return behavior: A city-level study in China.Frontiers in public health · 2022Article
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Authors and funding
5 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundImplementation of the Healthy China Strategy and the hierarchical diagnosis and treatment system has injected new vitality into medical services. Given the insufficient supply of medical services and increasing demand for medical treatment, exploring the supply-demand pattern of medical services has become an urgent theoretical and practical problem to be solved. The equity of healthcare facilities has received widespread attention, but due to limited data, there is little research on the supply-demand pattern of medical services. This study focuses on evaluating the supply-demand matching pattern of medical services at different levels in Haikou City with big geographic data and promoting the realization of a balance between medical supply and demand.
methodsThis study utilizes spatial data of medical institutions, Didi Chuxing Data, and population density data. Firstly, use the two-step floating catchment area method and GIS spatial analysis to explore characteristics of the supply-demand patterns of medical services at different levels in Haikou. Secondly, we mine residents' demand for medical treatment based on Didi Chuxing Data. Then combined with population density data, divide supply-demand matching of medical institutions into four types. Finally, propose optimization strategies for the problems.
resultsThe accessibility pattern of high-level medical institutions in Haikou presents high in the north and low in the south. The accessibility pattern of low-level medical institutions is the opposite. High-level medical institutions have a strong demand for medical treatment, which is less hampered by distance. The healthcare demand of low-level medical institutions is small, and they mainly are medium- and short-distance medical travel. The types of medical services at different levels are mainly "low supply - low demand" and "high supply - low demand" types.
conclusionsMedical services at different levels in Haikou are mainly in supply-demand imbalance. Therefore, we put forward optimization strategies to promote the equity of primary medical services, such as propelling the establishment and improvement of the hierarchical diagnosis and treatment system, building a new model of medical and health service supply, and strengthening balanced coverage of primary medical institutions. The mining of big geographic data is beneficial to alleviate the mismatch between medical supply and demand, although the data and methods need to be improved.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.