Abstract WP73: Temporal Effects on Mobile Stroke “Hot” Zones Using a Geo-Spatial Software Analysis
Abstract only Background: We sought to identify variations of mobile stroke unit (MSU) hotspot activity based on time of day by using a geospatial analysis software. Methods: The Mobile Stroke Treatment Unit of metropolitan Columbus, Ohio, provides emergency stroke care coverage for 325 square miles...
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| Published in: | Stroke (1970) Vol. 55; no. Suppl_1 |
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| Main Authors: | , , , , , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
01-02-2024
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| Online Access: | Get full text |
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| Summary: | Abstract only
Background:
We sought to identify variations of mobile stroke unit (MSU) hotspot activity based on time of day by using a geospatial analysis software.
Methods:
The Mobile Stroke Treatment Unit of metropolitan Columbus, Ohio, provides emergency stroke care coverage for 325 square miles which spans 47 zip codes. Our MSU is operational from 0700-1900 and is dispatched for all 911 calls designated as probable or possible strokes. We retrospectively reviewed all MSU calls from May 2019 to June 2022. The calls were organized into zip codes and 3 time epochs (0700-1100, 1101-1500, 1501-1900). Our endpoint was to determine hotspots of MSU activity during these epochs using the ESRI/ArcGIS Online geospatial analysis software. Statistically significant hotspots are qualitatively defined as clustered regions with high activity and quantitatively defined as having a Gi Bin score > 2, which correlates to statistical confidence > 95%.
Results:
We received 5198 calls during our study period; 1535 from 0700-1100; 2002 from 1101-1500; 1661 from 1501-1900. All hotspots had an average separation of 6.2 miles. From 0700-1100, 5 zip codes (12.9% of calls) were considered hotpots (Figure-Top). From 1101-1500, 15 zip codes (44.7% of calls) were considered hotspots (Figure-Middle). From 1501-1900, 9 zip codes (34.1% of calls) were considered hotspots (Figure-Bottom). Five zip codes were statistical hotspots during the entire coverage period. Four additional zip codes also showed hotspot activity and overlapped 1101-1900 time epochs.
Conclusions:
Our study showed that hotspot activity can vary throughout the day and must be considered for strategic MSU deployment. Prospective validation is needed to determine if such strategic deployment is feasible and can improve clinical outcomes. |
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| ISSN: | 0039-2499 1524-4628 |
| DOI: | 10.1161/str.55.suppl_1.WP73 |