Evidence map›Paper›PMID 39300487›Full record

ArticleBMC health services research2024

Measuring and optimizing the spatial accessibility of primary health care in remote and rural areas: a case study of Liannan Yao Autonomous County in China.

Lulu Liu, Yaowen Chen, Haiqing Xiang, Jiawei Zhong, Peng Zhou, Yu Xiao, Lan Wang, Ying Sun

Abstract read
In one paragraph

Article in BMC health services research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Study on edge villages based on cross-region healthcare-seeking behavior.International journal of health geographics · 2025
    Article
  5. Article
  6. Article
  7. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Lulu LiuSchool of Mechanics and Constructions Engineering, Jinan University, Guangzhou, 510000, China.
Yaowen ChenSchool of Mechanics and Constructions Engineering, Jinan University, Guangzhou, 510000, China.
Haiqing XiangThe First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou, 510000, China. 56789201@qq.com.
Jiawei ZhongSchool of Mechanics and Constructions Engineering, Jinan University, Guangzhou, 510000, China.
Peng ZhouSchool of Mechanics and Constructions Engineering, Jinan University, Guangzhou, 510000, China.
Yu XiaoSchool of Mechanics and Constructions Engineering, Jinan University, Guangzhou, 510000, China.
Lan WangSchool of Mechanics and Constructions Engineering, Jinan University, Guangzhou, 510000, China.
Ying SunSchool of culture tourism and geography, Guangdong University of Finance & Economics, Guangzhou, 510000, China.

Funding

Guangdong Provincial Philosophy and Social Sciences Planning Leading Group Office GD22CGL33Guangzhou Municipal Science and Technology Bureau 202201011084Office of the Guangzhou Social Science Planning Leadership Group 2024GZYB22
6 · The paper itself

Abstract

The need for equitable access to primary healthcare services in the current global context has attracted widespread attention, prompting nations to continuously enhance their grassroots medical service levels. In response, China launched the "Healthy China" initiative, which prioritizes the enhancement of national health as a core goal of the healthcare system and uses this opportunity to deepen reforms aimed at strengthening primary care. However, in remote and rural areas, the optimization of medical resource allocation and the achievement of balanced service development remain critical challenges owing to limited resources. This study selected Liannan Yao Autonomous County, which is situated in the northwestern corner of Guangdong Province, as a case study due to its remote mountainous location, underdeveloped economy, and minority region characteristics. Through field research and interviews, this study thoroughly explored the needs of both supply and demand, factoring in elements such as the service capability of healthcare facilities and residents' travel thresholds to enhance the two-step floating catchment area model, thus making it more applicable to remote villages. By integrating electric bikes and cars, which are the primary means of transportation in rural areas, this study conducted a thorough analysis and comparison of the accessibility of medical services in Liannan Yao Autonomous County (Liannan County) . The results reveal significant disparities in healthcare accessibility, an uneven distribution of medical resources, and varying impacts of transportation conditions and facility service capabilities on accessibility. Notably, the study revealed that improving transportation conditions alone has limited effects in rural areas; the key lies in balancing medical service capabilities and the rationality of overall layouts. From the perspectives of equity and efficiency, this study employs the equitable coverage model and the efficiency-driven model to construct two scenarios, comparing accessibility changes in Liannan County under both conditions and proposing strategies to improve the spatial layout of local healthcare facilities. This research not only deepens the understanding of healthcare service accessibility in rural areas but also provides a scientific basis for optimizing resource allocation and enhancing primary medical services, offering valuable guidance and reference for Liannan County and other similar rural regions.

Indexed as

Health Services AccessibilityPrimary Health CareRural Health ServicesChinaHumansOrganizational Case StudiesRural Population2SFCAPrimary health careRemote and rural areaResource optimization allocationSpatial accessibility

Identifiers

PMID39300487
PMCPMC11414241

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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.