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A conceptual framework for quality healthcare accessibility: a scalable approach for big data technologies

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A Commentary to this article was published on 08 February 2018

Abstract

Healthcare accessibility research has been of growing interest for scholars and practitioners. This manuscript classifies prior studies on the Floating Catchment Area methodologies, a prevalent class of methodologies that measure healthcare accessibility, and presents a framework that conceptualizes accessibility computation. We build the Floating Catchment Method General Framework as an IT artifact, following best practices in Design Science Research. We evaluate the utility of our framework by creating an instantiation, as an algorithm, and test it with large healthcare data sets from California. We showcase the practical application of the artifact and address the pressing issue of access to quality healthcare. This example also serves as a prototype for Big Data Analytics, as it presents opportunities to scale the analysis vertically and horizontally. In order for researchers to perform high impact studies and make the world a better place, an overarching framework utilizing Big Data Analytics should be seriously considered.

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Notes

  1. http://www.healthit.gov/providers-professionals/how-attain-meaningful-use, accessed on August 18, 2016

  2. http://quickfacts.census.gov/qfd/states/06000.html, accessed on August 18, 2016

  3. http://quickfacts.census.gov/qfd/states/06000.html, accessed on August 18, 2016

  4. http://www.oshpd.ca.gov/, accessed on August 18, 2016

  5. https://www.walkscore.com/, accessed on August 18, 2016

  6. http://www.sunnumber.com/, accessed on August 18, 2016

  7. http://quickfacts.census.gov/qfd/states/06000.html, accessed on August 18, 2016

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Authors and Affiliations

  1. Department of Information and Technology Management, Sykes College of Business, University of Tampa, Tampa, FL, USA

    Miloslava Plachkinova

  2. Center for Information Systems and Technology, Claremont Graduate University, Claremont, CA, USA

    Au Vo & Brian Hilton

  3. Department of Information Systems and Decision Sciences, Mihaylo College of Business and Economics, California State University Fullerton, Fullerton, CA, USA

    Rahul Bhaskar

Authors
  1. Miloslava Plachkinova
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  2. Au Vo
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  3. Rahul Bhaskar
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  4. Brian Hilton
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Correspondence to Miloslava Plachkinova.

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Plachkinova, M., Vo, A., Bhaskar, R. et al. A conceptual framework for quality healthcare accessibility: a scalable approach for big data technologies. Inf Syst Front 20, 289–302 (2018). https://doi.org/10.1007/s10796-016-9726-y

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  • DOI: https://doi.org/10.1007/s10796-016-9726-y

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