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Evaluating Michigan's community hospital access: spatial methods for decision support.

Joseph P Messina1, Ashton M Shortridge, Richard E Groop

  • 1Department of Geography, Michigan State University, East Lansing, MI, USA. jpm@msu.edu

International Journal of Health Geographics
|September 26, 2006
PubMed
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Spatial analysis identified two underserved areas in Michigan, highlighting the need for improved community hospital access. This research aids policymakers in making data-driven decisions for better healthcare distribution.

Area of Science:

  • Geographic Information Systems (GIS)
  • Spatial Analysis
  • Health Services Research

Background:

  • Community hospital placement is influenced by geography and historical factors.
  • A Michigan committee sought spatial analysis methods to revise hospital approval procedures.
  • Objectives included population and hospital spatial pattern visualization and access assessment.

Purpose of the Study:

  • To visualize Michigan's population and community hospital distribution.
  • To develop a methodology for quantifying statewide hospital access.
  • To contrast current hospital distribution with a demand-optimized configuration.

Main Methods:

  • Developed an access-based model considering distance and road networks for travel time estimation.

Related Experiment Videos

  • Created a demand-based model allocating daily bed demand by ZIP code to the nearest facility.
  • Utilized spatial analysis techniques to identify under-served regions.

    • Main Results:

    • Two under-served areas were identified: one north/northeast of Detroit and another north of Grand Rapids.
    • The access-based model identified significant unmet demand within specific radii.
    • The demand-based model revealed 1,887 daily bed demands from centroids over 16.1 km from existing hospitals (12.7% of total demand).

    Conclusions:

    • Spatial modeling approaches effectively identify under-served areas for policymakers.
    • This research demonstrates the utility of spatial analysis in evidence-based policymaking for healthcare.
    • Informed decisions regarding community hospital placement can be made using scientific spatial assessments.