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Comment on “A Conceptual Framework for Quality Healthcare Accessibility: a Scalable Approach for Big Data Technologies”

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  • Paul L. Delamater

    (University of North Carolina at Chapel Hill)

Abstract

ᅟFloating Catchment Area (FCA) metrics incorporate the supply of health care resources, potential population demand for those resources, and the distance separating people and supply locations to characterize the spatial accessibility of health care resources for populations. In this work, I challenge a number of assertions offered in a recently published FCA-based paper and provide a critique of the authors' proposed metric. Within my critique, I present a number of broad observations and recommendations regarding FCA metrics and their implementation in a Geographic Information System (GIS). In doing so, I aim to initiate a broader discussion of access to health care, spatial accessibility, and FCA metrics that transcends disciplinary boundaries.

Suggested Citation

  • Paul L. Delamater, 2018. "Comment on “A Conceptual Framework for Quality Healthcare Accessibility: a Scalable Approach for Big Data Technologies”," Information Systems Frontiers, Springer, vol. 20(2), pages 303-309, April.
    • Handle: RePEc:spr:infosf:v:20:y:2018:i:2:d:10.1007_s10796-018-9829-8
    DOI: 10.1007/s10796-018-9829-8
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    References listed on IDEAS

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    1. Langford, M. & Higgs, G. & Fry, R., 2012. "Using floating catchment analysis (FCA) techniques to examine intra-urban variations in accessibility to public transport opportunities: the example of Cardiff, Wales," Journal of Transport Geography, Elsevier, vol. 25(C), pages 1-14.
    2. Miloslava Plachkinova & Au Vo & Rahul Bhaskar & Brian Hilton, 2018. "A conceptual framework for quality healthcare accessibility: a scalable approach for big data technologies," Information Systems Frontiers, Springer, vol. 20(2), pages 289-302, April.
    3. Miloslava Plachkinova & Au Vo & Rahul Bhaskar & Brian Hilton, 0. "A conceptual framework for quality healthcare accessibility: a scalable approach for big data technologies," Information Systems Frontiers, Springer, vol. 0, pages 1-14.
    4. Khan, Abdullah A., 1992. "An integrated approach to measuring potential spatial access to health care services," Socio-Economic Planning Sciences, Elsevier, vol. 26(4), pages 275-287, October.
    5. Joseph, Alun E. & Bantock, Peter R., 1982. "Measuring potential physical accessibility to general practitioners in rural areas: A method and case study," Social Science & Medicine, Elsevier, vol. 16(1), pages 85-90, January.
    6. Paul L Delamater & Joseph P Messina & Sue C Grady & Vince WinklerPrins & Ashton M Shortridge, 2013. "Do More Hospital Beds Lead to Higher Hospitalization Rates? A Spatial Examination of Roemer’s Law," PLOS ONE, Public Library of Science, vol. 8(2), pages 1-16, February.
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    Cited by:

    1. Yoonchae Yoon & Jina Park, 2022. "Equitable City in an Aging Society: Public Transportation-Based Primary Care Accessibility in Seoul, Korea," Sustainability, MDPI, vol. 14(16), pages 1-17, August.
    2. Mitchell, Penelope & Samsel, Steven & Curtin, Kevin M. & Price, Ashleigh & Turner, Daniel & Tramp, Ryan & Hudnall, Matthew & Parton, Jason & Lewis, Dwight, 2022. "Geographic disparities in access to Medication for Opioid Use Disorder across US census tracts based on treatment utilization behavior," Social Science & Medicine, Elsevier, vol. 302(C).

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