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Evaluating health facility access using Bayesian spatial models and location analysis methods.

Nicholas J Tierney1,2,3, Antonietta Mira4,5, H Jost Reinhold4

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This study identifies priority areas for Automated External Defibrillator (AED) placement by combining demand, supply, and Out-of-Hospital Cardiac Arrest (OHCA) risk factors. Findings aid in optimizing AED deployment for improved survival rates.

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Area of Science:

  • Geospatial analysis
  • Public health preparedness
  • Emergency medical services

Background:

  • Floating catchment methods identify priority regions for Automated External Defibrillator (AED) deployment to improve Out-of-Hospital Cardiac Arrest (OHCA) survival.
  • Current methods model AED access as a supply-to-demand ratio but lack precise location identification and integration of OHCA risk factors like income and demographics.
  • Combining spatial risk factors with accessibility models can evaluate AED placement impact and identify coverage gaps.

Purpose of the Study:

  • To develop geospatial models of OHCA occurrence that incorporate and display uncertainty.
  • To evaluate AED placement methods using geospatial models of accessibility.
  • To identify communities with the greatest gap between AED demand and supply for targeted resource allocation.

Main Methods:

  • A geospatial model incorporating spatial correlation was used to describe OHCA occurrence, utilizing covariates for population density, age, financial strength, and land use.
  • Integrated Nested Laplacian Approximation (INLA) was employed for model fitting.
  • Optimization methods identified top AED locations, and access was calculated for current and proposed placements, with priority rankings based on access scores and predicted OHCA events.

Main Results:

  • Over 70% of 2802 OHCA events involved individuals over 65, with 64.28% occurring in rural areas.
  • AED supply was insufficient in most analyzed regions.
  • AED placement strategies prioritized high-need areas but concentrated more AEDs in regions with higher predicted OHCA counts.

Conclusions:

  • The developed methods integrate OHCA spatial risk factors and coverage to pinpoint areas needing AED resources.
  • This approach enhances understanding of how AED allocation strategies influence OHCA accessibility.
  • Findings offer significant practical value for communities in making informed AED placement decisions.