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Optimizing Mobile Health Clinic Placement via Geospatial Modeling.

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    Optimizing mobile health clinic (MHC) placement nearly doubles population coverage for uninsured residents, improving access to care. This spatial analytics framework enhances MHC utilization and reduces health disparities in underserved communities.

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    Area of Science:

    • Public Health
    • Spatial Analysis
    • Health Services Research

    Background:

    • Mobile health clinics (MHCs) offer vital community-based care to underserved populations facing access barriers.
    • Maximizing MHC coverage is crucial for improving preventive care and reducing health disparities.
    • Existing strategies for MHC placement and routing are limited.

    Purpose of the Study:

    • To present a framework for optimizing MHC placement and routing to increase service coverage and utilization.
    • To identify MHC locations that maximize access for uninsured populations within practical travel distances.
    • To evaluate the association between geographic coverage and MHC utilization for Hepatitis C Virus (HCV) screening.

    Main Methods:

    • Retrospective analysis of MHC deployments for HCV screening and treatment in South Carolina.
    • Utilized a location-allocation model to determine optimal MHC placement sites.
    • Compared service area population for model-proposed sites versus previous deployments.
    • Employed negative binomial mixed effects models to assess the impact of service area population on MHC utilization.

    Main Results:

    • Optimized MHC placements can nearly double population coverage, increasing access for uninsured residents by 90% (driving) and 135% (walking).
    • The framework reduces redundant service areas and average travel times without additional resources.
    • Greater geographic coverage in rural areas was significantly associated with higher MHC utilization for HCV screening.

    Conclusions:

    • The developed framework effectively connects spatial analytics with MHC service delivery for improved health outcomes.
    • This replicable tool supports strategic placement in high-need areas, reducing travel time and service redundancy.
    • The approach is adaptable to various travel modes, site types, and disease contexts, enhancing care for medically underserved populations.