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Using the Fusion Proximal Area Method and Gravity Method to Identify Areas with Physician Shortages

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  • Xuechen Xiong
  • Chao Jin
  • Haile Chen
  • Li Luo

Abstract

Objectives: This paper presents a geographic information system (GIS)-based proximal area method and gravity method for identifying areas with physician shortages. The innovation of this paper is that it uses the appropriate methods to discover each type of health resource and then integrates all these methods to assess spatial access to health resources using population distribution data. In this way, spatial access to health resources for an entire city can be visualized in one neat package, which can help health policy makers quickly comprehend realistic distributions of health resources at a macro level. Methods: First, classify health resources according to the trade areas of the patients they serve. Second, apply an appropriate method to each different type of health resource to measure spatial access to those resources. Third, integrate all types of access using population distribution data. Results: In case study of Shanghai with the fusion method, areas with physician shortages are located primarily in suburban districts, especially in district junction areas. The result suggests that the government of Shanghai should pay more attention to these areas by investing in new or relocating existing health resources. Conclusion: The fusion method is demonstrated to be more accurate and practicable than using a single method to assess spatial access to health resources.

Suggested Citation

  • Xuechen Xiong & Chao Jin & Haile Chen & Li Luo, 2016. "Using the Fusion Proximal Area Method and Gravity Method to Identify Areas with Physician Shortages," PLOS ONE, Public Library of Science, vol. 11(10), pages 1-17, October.
    • Handle: RePEc:plo:pone00:0163504
    DOI: 10.1371/journal.pone.0163504
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    References listed on IDEAS

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    1. Peige Song & Yajie Zhu & Xi Mao & Qi Li & Lin An, 2013. "Assessing Spatial Accessibility to Maternity Units in Shenzhen, China," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-7, July.
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    Cited by:

    1. Lei Zhu & Shuang Zhong & Wei Tu & Jing Zheng & Shenjing He & Junzhe Bao & Cunrui Huang, 2019. "Assessing Spatial Accessibility to Medical Resources at the Community Level in Shenzhen, China," IJERPH, MDPI, vol. 16(2), pages 1-15, January.
    2. Rizwan Muhammad & Yaolong Zhao & Fan Liu, 2019. "Spatiotemporal Analysis to Observe Gender Based Check-In Behavior by Using Social Media Big Data: A Case Study of Guangzhou, China," Sustainability, MDPI, vol. 11(10), pages 1-30, May.
    3. Xuechen Xiong & Li Luo, 2020. "Inpatient Flow Distribution Patterns at Shanghai Hospitals," IJERPH, MDPI, vol. 17(7), pages 1-10, March.

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