Measuring spatial accessibility and within-province disparities in accessibility to county hospitals in Shaanxi Province of Western China based on web mapping navigation data

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Abstract

Background

The Chinese government proposed the “XIAO BING BU CHU CUN, DA BING BU CHU XIAN” initiative in 2016, which states the rate of health care service provided by county hospitals should reach 90% of overall health care service provision. The prerequisite for achieving this goal is that citizens should be able to access county hospitals’ services conveniently and impartially. However, little research has been done on the actual levels of the spatial accessibility of citizens to county hospitals in Western China. Therefore, we aimed to measure the spatial accessibility to county hospitals for county residents and to identify any regional disparities in Shaanxi Province in Western China.

Methods

We implemented a novel method – involving utilizing navigation data from the AutoNavi web mapping system (knows as Gaode map in Chinese) – to assess the time and distance from villages and neighborhoods to the county hospitals. The navigation data were collected by request through an application-programming-interface using a web crawler (web data extraction tool) in Python. The shortest driving time and distance were extracted from the navigation data. The travel impedance to the nearest provider (TINP) indicator was used to measure spatial accessibility.

Results

The results show that county residents in Western China’s Shaanxi Province have poor spatial accessibility to county hospitals. Only 68.8% of villages and neighborhoods are within 60 min travel time (based on driving mode) to a county hospital, while 13.4% of such villages and neighborhoods are beyond 90 min travel time. Moreover, a significant within-province disparity exists, with residents in the central area enjoying the best accessibility to county hospitals, while the northern and southern areas still need improvements in accessibility.

Conclusions

Focused health resource planning is required to improve the spatial accessibility to county hospitals and to eliminate regional disparities. Further studies are called for to integrate the navigation data of web mapping systems with GIS methods to the measure spatial accessibility of health facilities in more complex contexts.

Related collections

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Spatial accessibility of primary care: concepts, methods and challenges

Mark Guagliardo (2004)

Primary care is recognized as the most important form of healthcare for maintaining population health because it is relatively inexpensive, can be more easily delivered than specialty and inpatient care, and if properly distributed it is most effective in preventing disease progression on a large scale. Recent advances in the field of health geography have greatly improved our understanding of the role played by geographic distribution of health services in population health maintenance. However, most of this knowledge has accrued for hospital and specialty services and services in rural areas. Much less is known about the effect of distance to and supply of primary care on primary care utilization, particularly in the U.S. For several reasons the shortage of information is particularly acute for urban areas, where the majority of people live. First, explicit definitions and conceptualizations of healthcare access have not been widely used to guide research. An additional barrier to progress has been an overwhelming concern about affordability of care, which has garnered the majority of attention and research resources. Also, the most popular measures of spatial accessibility to care – travel impedance to nearest provider and supply level within bordered areas – lose validity in congested urban areas. Better measures are needed. Fortunately, some advances are occurring on the methodological front. These can improve our knowledge of all types of healthcare geography in all settings, including primary care in urban areas. This paper explains basic concepts and measurements of access, provides some historical background, outlines the major questions concerning geographic accessibility of primary care, describes recent developments in GIS and spatial analysis, and presents examples of promising work.

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Author and article information

Contributors

Zhongliang Zhou: zzliang1981@163.com

Journal

Journal ID (nlm-ta): Int J Equity Health

Journal ID (iso-abbrev): Int J Equity Health

Title: International Journal for Equity in Health

Publisher: BioMed Central (London )

ISSN (Electronic): 1475-9276

Publication date (Electronic): 18 June 2020

Publication date PMC-release: 18 June 2020

Publication date Collection: 2020

Volume: 19

Electronic Location Identifier: 99

Affiliations

[1 ]GRID grid.43169.39, ISNI 0000 0001 0599 1243, School of Public Policy and Administration, , Xi’an Jiaotong University, ; No.28 Xianning West Road, Xi’an, 710049 Shaanxi China

[2 ]GRID grid.412041.2, ISNI 0000 0001 2106 639X, Team IETO, Bordeaux Population Health Research Center, , University de Bordeaux, ; 33076 Bordeaux, France

[3 ]GRID grid.43169.39, ISNI 0000 0001 0599 1243, School of Public Health, Health Science Center, , Xi’an Jiaotong University, ; Xi’an, 710063 China

[4 ]GRID grid.411643.5, ISNI 0000 0004 1761 0411, School of Public Administration, , Inner Mongolia University, ; Hohhot, 010021 China

[5 ]GRID grid.4464.2, ISNI 0000 0001 2161 2573, Centre for HealthCare Innovation Research, Cass Business School & School of Health Sciences, City, , University of London, ; London, EC1V 0HB UK

[6 ]GRID grid.47100.32, ISNI 0000000419368710, Department of Health Policy and Management, , Yale School of Public Health, ; New Haven, CT 06520 USA

Article

Publisher ID: 1217

DOI: 10.1186/s12939-020-01217-0

PMC ID: 7302366

PubMed ID: 32552715

SO-VID: a52a70da-eff7-417b-a761-39f4fe482161

License:

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 24 February 2020

Date accepted : 10 June 2020