IDEAS home Printed from https://ideas.repec.org/a/taf/raagxx/v110y2020i1p205-222.html
   My bibliography  Save this article

A Rational Agent Model for the Spatial Accessibility of Primary Health Care

Author

Listed:
  • James Saxon
  • Daniel Snow

Abstract

Accurate modeling of the spatial accessibility of health care is critical to measuring and responding to physician shortages. We develop a new model in which patients choose the primary care location that minimizes their combined accessibility and availability costs. This model offers several advantages with respect to existing access frameworks. It incorporates feedback between patient decisions and endogenizes the trade-off between travel times and congestion at the point of care. It allows for patients to seek care from their home or workplace and can account for multiple travel modes. Our open-sourced implementation scales efficiently to large areas and fine spatial granularity. Using distributed computing, we calculate travel times for this model at the census tract level for the entire United States, and we also make this resource available. We compare the results to those from existing primary care access models. Key Words: floating catchment areas, primary health care, rational agent models, spatial accessibility.

Suggested Citation

  • James Saxon & Daniel Snow, 2020. "A Rational Agent Model for the Spatial Accessibility of Primary Health Care," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 110(1), pages 205-222, January.
    • Handle: RePEc:taf:raagxx:v:110:y:2020:i:1:p:205-222
    DOI: 10.1080/24694452.2019.1629870
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/24694452.2019.1629870
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/24694452.2019.1629870?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. Shao, Yaxiong & Luo, Wei, 2022. "Supply-demand adjusted two-steps floating catchment area (SDA-2SFCA) model for measuring spatial access to health care," Social Science & Medicine, Elsevier, vol. 296(C).
    2. Ali Khosravi Kazazi & Fariba Amiri & Yaser Rahmani & Raheleh Samouei & Hamidreza Rabiei-Dastjerdi, 2022. "A New Hybrid Model for Mapping Spatial Accessibility to Healthcare Services Using Machine Learning Methods," Sustainability, MDPI, vol. 14(21), pages 1-18, October.
    3. Lin, Jie & Cromley, Gordon, 2023. "Using the transportation problem to build a congestion/threshold constrained spatial accessibility model," Journal of Transport Geography, Elsevier, vol. 112(C).
    4. Gordon Cromley & Jie Lin, 2023. "Examining the interplay between racial segregation patterns and access to hospital care," Environment and Planning B, , vol. 50(1), pages 117-129, January.
    5. G. Arbia & V. Nardelli & N. Salvini & I. Valentini, 2024. "New accessibility measures based on unconventional big data sources," Papers 2401.13370, arXiv.org.
    6. James Saxon & Julia Koschinsky & Karina Acosta & Vidal Anguiano & Luc Anselin & Sergio Rey, 2022. "An open software environment to make spatial access metrics more accessible," Journal of Computational Social Science, Springer, vol. 5(1), pages 265-284, May.
    7. Hu, Yujie & Wang, Changzhen & Li, Ruiyang & Wang, Fahui, 2020. "Estimating a large drive time matrix between ZIP codes in the United States: A differential sampling approach," Journal of Transport Geography, Elsevier, vol. 86(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:taf:raagxx:v:110:y:2020:i:1:p:205-222. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/raag .

    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.