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Geospatial Visualization of Mobile Stroke Unit Dispatches: A Method to Optimize Service Performance
James P Rhudy1, Anne W Alexandrov1,2, Joseph Rike1
1Department of Neurology, College of Medicine, University of Tennessee Health Science Center, Memphis, Tennessee, USA.
Mobile stroke units (MSU) provide faster acute ischemic stroke treatment. Geospatial analysis revealed distinct clusters for MSU dispatches and actual stroke cases, guiding optimized service delivery to underserved areas.
Area of Science:
- Emergency Medicine
- Neuroscience
- Public Health
Background:
- Rapid treatment of acute ischemic stroke is critical for patient outcomes.
- Mobile stroke units (MSU) offer faster treatment than standard emergency care.
- Geospatial analysis of MSU case distribution for service optimization is underreported.
Purpose of the Study:
- To analyze the geospatial distribution of mobile stroke unit (MSU) dispatches and confirmed stroke cases.
- To identify clusters of high incidence for both dispatches and true stroke cases.
- To inform optimization of MSU service delivery based on stroke burden.
Main Methods:
- Aggregated MSU dispatch and true stroke data by zip code for the first year.
- Calculated incidence rates and mapped distributions, symbolizing by standard deviation.
- Utilized local Moran's I, boxplots, and t-tests to confirm spatial clusters.
- Determined optimal service areas using drive times.
Main Results:
- A high dispatch incident rate cluster was identified around the MSU base in urban Memphis (5-min drive).
- A high true stroke rate cluster was found east of the base in suburban Memphis (10-min drive).
- True stroke cases occurred significantly further east compared to non-stroke dispatches (p=0.001785).
Conclusions:
- Geospatial analysis identified distinct patterns for MSU dispatches versus true stroke cases.
- Findings support optimizing MSU deployment and service areas to address geographic disparities.
- Understanding socio-spatial factors can improve 911 and MSU service utilization in urban and suburban areas.
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