ArticleScientific reports2024
Accessibility evaluation and multi-scenario optimization of medical services in underdeveloped city driven by multi-source data and latest policies for China.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Mobility-informed hospital siting for accessible and lower-carbon healthcare travel: an ensemble learning study in Tianjin, China.Frontiers in public health · 2026Article
- Prenatal diagnostic value of medium-coverage WGS and clinical Exome sequencing in fetal congenital heart disease.Future science OA · 2025Article
- Spatial optimization of hierarchical healthcare facilities driven by multi-source data: a case study of Shenyang, China.Frontiers in public health · 2025Article
- Implementation and improvement of policies for building healthy cities in China.Frontiers in public health · 2024Article
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8 authors.
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Abstract
Equitable and high-quality medical services are more urgent in underdeveloped cities for the higher population ageing and demanding social justice. However, there is little attention paid to the multi-level medical services, particularly regarding the time indicators under the latest policies for underdeveloped cities. The improved efforts were hampered partly by single scenario of location optimization, ignoring the integrated optimization for both road infrastructure and institution location. Toward the healthy China 2030 and rural revitalization policy, this study systematically investigated medical services for underdeveloped cities by constructing a multi-level evaluation and multi-scenario optimization framework with Geographical Information System technology in a case study of Xuchang City in China. Following the time goals from the latest policies, the services of high-quality hospitals and primary health centers were multi-level evaluated by network analysis method and further optimized through multi-scenario involving different new multi-level medical facilities and roads. Driven by urban-rural inequalities, candidate facilities were first selected based on multi-source data and then determined by location‑allocation analysis method, while new roads were assumed by space syntax method. The improvement rose rapidly and finally slowly with the increasing number of candidates. Few new roads and facilities could be more suitable, and the priority was explored under the local economy and planning. The findings could provide valuable support for urban healthy development under the latest policies.
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