IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v15y2018i9p2051-d170808.html
   My bibliography  Save this article

Evaluating the Accessibility of Healthcare Facilities Using an Integrated Catchment Area Approach

Author

Listed:
  • Xiaofang Pan

    (Faculty of Information Engineering, China University of Geosciences, 388 Lumo Road, Wuhan 430074, China
    School of Geographic Sciences, Xinyang Normal University, 237 Nanhu Road, Xinyang 464000, China)

  • Mei-Po Kwan

    (Department of Geography and Geographic Information Science, University of Illinois at Urbana-Champaign, Natural History Building, MC-150, 1301 W Green Street, Urbana, IL 61801, USA
    Department of Human Geography and Spatial Planning, Utrecht University, P.O. Box 80125, 3508 TC Utrecht, The Netherlands)

  • Lin Yang

    (Faculty of Information Engineering, China University of Geosciences, 388 Lumo Road, Wuhan 430074, China
    State Key Laboratory of Geo-information Engineering, Xi’an 710054, China)

  • Shunping Zhou

    (Faculty of Information Engineering, China University of Geosciences, 388 Lumo Road, Wuhan 430074, China)

  • Zejun Zuo

    (Faculty of Information Engineering, China University of Geosciences, 388 Lumo Road, Wuhan 430074, China)

  • Bo Wan

    (Faculty of Information Engineering, China University of Geosciences, 388 Lumo Road, Wuhan 430074, China)

Abstract

Accessibility is a major method for evaluating the distribution of service facilities and identifying areas in shortage of service. Traditional accessibility methods, however, are largely model-based and do not consider the actual utilization of services, which may lead to results that are different from those obtained when people’s actual behaviors are taken into account. Based on taxi GPS trajectory data, this paper proposed a novel integrated catchment area (ICA) that integrates actual human travel behavior to evaluate the accessibility to healthcare facilities in Shenzhen, China, using the enhanced two-step floating catchment area (E2SFCA) method. This method is called the E2SFCA-ICA method. First, access probability is proposed to depict the probability of visiting a healthcare facility. Then, integrated access probability (IAP), which integrates model-based access probability (MAP) and data-based access probability (DAP), is presented. Under the constraint of IAP, ICA is generated and divided into distinct subzones. Finally, the ICA and subzones are incorporated into the E2SFCA method to evaluate the accessibility of the top-tier hospitals in Shenzhen, China. The results show that the ICA not only reduces the differences between model-based catchment areas and data-based catchment areas, but also distinguishes the core catchment area, stable catchment area, uncertain catchment area and remote catchment area of healthcare facilities. The study also found that the accessibility of Shenzhen’s top-tier hospitals obtained with traditional catchment areas tends to be overestimated and more unequally distributed in space when compared to the accessibility obtained with integrated catchment areas.

Suggested Citation

  • Xiaofang Pan & Mei-Po Kwan & Lin Yang & Shunping Zhou & Zejun Zuo & Bo Wan, 2018. "Evaluating the Accessibility of Healthcare Facilities Using an Integrated Catchment Area Approach," IJERPH, MDPI, vol. 15(9), pages 1-21, September.
  • Handle: RePEc:gam:jijerp:v:15:y:2018:i:9:p:2051-:d:170808
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/15/9/2051/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/15/9/2051/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yang, Lin & Kwan, Mei-Po & Pan, Xiaofang & Wan, Bo & Zhou, Shunping, 2017. "Scalable space-time trajectory cube for path-finding: A study using big taxi trajectory data," Transportation Research Part B: Methodological, Elsevier, vol. 101(C), pages 1-27.
    2. Hyndman, Jilda C. G. & Holman, C. D'Arcy J. & Pritchard, Douglas A., 2003. "The influence of attractiveness factors and distance to general practice surgeries by level of social disadvantage and global access in Perth, Western Australia," Social Science & Medicine, Elsevier, vol. 56(2), pages 387-403, January.
    3. Shortt, Niamh K. & Moore, Adrian & Coombes, Mike & Wymer, Colin, 2005. "Defining regions for locality health care planning: a multidimensional approach," Social Science & Medicine, Elsevier, vol. 60(12), pages 2715-2727, June.
    4. Marta C. González & César A. Hidalgo & Albert-László Barabási, 2009. "Understanding individual human mobility patterns," Nature, Nature, vol. 458(7235), pages 238-238, March.
    5. Lovett, Andrew & Haynes, Robin & Sünnenberg, Gisela & Gale, Susan, 2002. "Car travel time and accessibility by bus to general practitioner services: a study using patient registers and GIS," Social Science & Medicine, Elsevier, vol. 55(1), pages 97-111, July.
    6. Shen, Yue & Kwan, Mei-Po & Chai, Yanwei, 2013. "Investigating commuting flexibility with GPS data and 3D geovisualization: a case study of Beijing, China," Journal of Transport Geography, Elsevier, vol. 32(C), pages 1-11.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Vidoli, Francesco & Auteri, Monica, 2022. "Health-care demand and supply at municipal level: A spatial disaggregation approach," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).
    2. Yuma Morisaki & Makoto Fujiu & Junichi Takayama & Masahiko Sagae & Kohei Hirako, 2023. "Quantitative Evaluation of Difficulty in Visiting Hospitals for Elderly Patients in Depopulated Area in Japan: Using National Health Insurance Data," Sustainability, MDPI, vol. 15(21), pages 1-16, October.
    3. Fangye Du & Jiaoe Wang & Haitao Jin, 2021. "Whether Public Hospital Reform Affects the Hospital Choices of Patients in Urban Areas: New Evidence from Smart Card Data," IJERPH, MDPI, vol. 18(15), pages 1-14, July.
    4. Wei, Zhongyu & Bai, Jianjun & Feng, Ruitao, 2022. "Evaluating the spatial accessibility of medical resources taking into account the residents' choice behavior of outpatient and inpatient medical treatment," Socio-Economic Planning Sciences, Elsevier, vol. 83(C).
    5. Ana Louro & Nuno Marques da Costa & Eduarda Marques da Costa, 2021. "From Livable Communities to Livable Metropolis: Challenges for Urban Mobility in Lisbon Metropolitan Area (Portugal)," IJERPH, MDPI, vol. 18(7), pages 1-22, March.
    6. Rajat Verma & Mithun Debnath & Shagun Mittal & Satish V. Ukkusuri, 2024. "Towards a generalized accessibility measure for transportation equity and efficiency," Papers 2404.04985, arXiv.org.
    7. Amritpal Kaur Khakh & Victoria Fast & Rizwan Shahid, 2019. "Spatial Accessibility to Primary Healthcare Services by Multimodal Means of Travel: Synthesis and Case Study in the City of Calgary," IJERPH, MDPI, vol. 16(2), pages 1-19, January.
    8. Meihan Jin & Lu Liu & De Tong & Yongxi Gong & Yu Liu, 2019. "Evaluating the Spatial Accessibility and Distribution Balance of Multi-Level Medical Service Facilities," IJERPH, MDPI, vol. 16(7), pages 1-19, March.
    9. Fangye Du & Jiaoe Wang & Yu Liu & Zihao Zhou & Haitao Jin, 2022. "Equity in Health-Seeking Behavior of Groups Using Different Transportations," IJERPH, MDPI, vol. 19(5), pages 1-16, February.
    10. Dan Zhao & Liu Shao & Jianwei Li & Lina Shen, 2024. "Spatial-Performance Evaluation of Primary Health Care Facilities: Evidence from Xi’an, China," Sustainability, MDPI, vol. 16(7), pages 1-14, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xuesong Gao & Hui Wang & Lun Liu, 2021. "Profiling Residents’ Mobility with Grid-Aggregated Mobile Phone Trace Data Using Chengdu as the Case," Sustainability, MDPI, vol. 13(24), pages 1-13, December.
    2. Yang Xu & Shih-Lung Shaw & Ziliang Zhao & Ling Yin & Zhixiang Fang & Qingquan Li, 2015. "Understanding aggregate human mobility patterns using passive mobile phone location data: a home-based approach," Transportation, Springer, vol. 42(4), pages 625-646, July.
    3. Shenjing He & Chenxi Li & Yang Xiao & Qiyang Liu, 2022. "Examining neighborhood effects on residents’ daily activities in central Shanghai, China: Integrating “big data†and “thick dataâ€," Environment and Planning B, , vol. 49(7), pages 2011-2028, September.
    4. Liu, Lun & Gao, Xuesong & Zhuang, Jiexin & Wu, Wen & Yang, Bo & Cheng, Wei & Xiao, Pengfei & Yao, Xingzhu & Deng, Ouping, 2020. "Evaluating the lifestyle impact of China’s rural housing land consolidation with locational big data: A study of Chengdu," Land Use Policy, Elsevier, vol. 96(C).
    5. Gang Zhong & Tingting Yin & Jian Zhang & Shanglu He & Bin Ran, 2019. "Characteristics analysis for travel behavior of transportation hub passengers using mobile phone data," Transportation, Springer, vol. 46(5), pages 1713-1736, October.
    6. Kim, Kyoungok, 2018. "Exploring the difference between ridership patterns of subway and taxi: Case study in Seoul," Journal of Transport Geography, Elsevier, vol. 66(C), pages 213-223.
    7. Jeong-Hui Park & Eunhye Yoo & Youngdeok Kim & Jung-Min Lee, 2021. "What Happened Pre- and during COVID-19 in South Korea? Comparing Physical Activity, Sleep Time, and Body Weight Status," IJERPH, MDPI, vol. 18(11), pages 1-13, May.
    8. Matteo Böhm & Mirco Nanni & Luca Pappalardo, 2022. "Gross polluters and vehicle emissions reduction," Nature Sustainability, Nature, vol. 5(8), pages 699-707, August.
    9. Su, Rongxiang & Xiao, Jingyi & McBride, Elizabeth C. & Goulias, Konstadinos G., 2021. "Understanding senior's daily mobility patterns in California using human mobility motifs," Journal of Transport Geography, Elsevier, vol. 94(C).
    10. Robert Stewart & Marie Urban & Samantha Duchscherer & Jason Kaufman & April Morton & Gautam Thakur & Jesse Piburn & Jessica Moehl, 2016. "A Bayesian machine learning model for estimating building occupancy from open source data," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 81(3), pages 1929-1956, April.
    11. Arroyo Arroyo,Fatima & Fernandez Gonzalez,Marta & Matekenya,Dunstan & Espinet Alegre,Xavier, 2021. "Using Mobile Data to Understand Urban Mobility Patterns in Freetown, Sierra Leone," Policy Research Working Paper Series 9519, The World Bank.
    12. David Kofoed Wind & Piotr Sapiezynski & Magdalena Anna Furman & Sune Lehmann, 2016. "Inferring Stop-Locations from WiFi," PLOS ONE, Public Library of Science, vol. 11(2), pages 1-15, February.
    13. Zhou, Xingang & Yeh, Anthony G.O. & Yue, Yang, 2018. "Spatial variation of self-containment and jobs-housing balance in Shenzhen using cellphone big data," Journal of Transport Geography, Elsevier, vol. 68(C), pages 102-108.
    14. Maxime Lenormand & Miguel Picornell & Oliva G Cantú-Ros & Antònia Tugores & Thomas Louail & Ricardo Herranz & Marc Barthelemy & Enrique Frías-Martínez & José J Ramasco, 2014. "Cross-Checking Different Sources of Mobility Information," PLOS ONE, Public Library of Science, vol. 9(8), pages 1-10, August.
    15. Miotti, Marco & Needell, Zachary A. & Jain, Rishee K., 2023. "The impact of urban form on daily mobility demand and energy use: Evidence from the United States," Applied Energy, Elsevier, vol. 339(C).
    16. Zheng Yan & Wenqian Robertson & Yaosheng Lou & Tom W. Robertson & Sung Yong Park, 2021. "Finding leading scholars in mobile phone behavior: a mixed-method analysis of an emerging interdisciplinary field," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(12), pages 9499-9517, December.
    17. Daniel Oviedo & Luis A. Guzman, 2020. "Revisiting Accessibility in a Context of Sustainable Transport: Capabilities and Inequalities in Bogotá," Sustainability, MDPI, vol. 12(11), pages 1-22, June.
    18. Lee, Hasik & Park, Ho-Chul & Kho, Seung-Young & Kim, Dong-Kyu, 2019. "Assessing transit competitiveness in Seoul considering actual transit travel times based on smart card data," Journal of Transport Geography, Elsevier, vol. 80(C).
    19. Huang, Feihu & Qiao, Shaojie & Peng, Jian & Guo, Bing & Xiong, Xi & Han, Nan, 2019. "A movement model for air passengers based on trip purpose," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 798-808.
    20. Duan, Zhengyu & Zhao, Haoran & Li, Zhenming, 2023. "Non-linear effects of built environment and socio-demographics on activity space," Journal of Transport Geography, Elsevier, vol. 111(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:15:y:2018:i:9:p:2051-:d:170808. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.