Abstract 22: Geospatial Modeling To Optimize Mobile Stroke Unit System Deployment In A Large Metropolitan Region

• Published in: Stroke (1970) Vol. 53; no. Suppl_1; p. A22
• Main Authors: Nour, May, Vassar, Stefanie D, Brown, Arleen F, Bosson, Nichole E, Chidester, Cathy, Liebeskind, David S, Kazan, Clayton, Sanko, Stephen, Eckstein, Marc, Gausche-Hill, Marianne, Saver, Jeffrey L
• Format: Journal Article
• Language: English
• Published: Lippincott Williams & Wilkins 01.02.2022
• DOI: 10.1161/str.53.suppl_1.22
• ISSN: 0039-2499

IntroductionTransition from evidence to practice is the next challenge for Mobile Stroke Units (MSUs) now that two controlled studies have shown improved outcomes (BEST-MSU and B_PROUD). This requires successful integration into EMS systems. We sought to utilize geospatial mapping to identify the most efficient number and positioning of MSUs in Los Angeles (LA) County to maximize patient access. MethodsLA County has one of the largest EMS systems in the US, comprising 88 cities, more than 4000 sq miles, and a population of 10.2 million. Using ESRI/ArcGIS software, we performed geospatial mapping of all 911 calls resulting in a final diagnosis stroke from July 2016 - June 2019, converting street addresses to latitude/longitude. Regional heatmaps of stroke call volume were generated for day/evening (7 am-10 pm) vs nighttime (10 pm-7 am) and ischemic vs hemorrhagic stroke, superimposed upon available stroke centers and neighborhood sociodemographic factors. Based on pilot experience, each MSU was projected to be able to service a 10-mile radius. ResultsAmong 10,818 EMS responses for acute cerebrovascular disease during the 3-year study period, calls occurred during day/evening in 84.5% and nighttime in 15.5%. Stroke type was ischemic in 78.8% and hemorrhagic in 21.2%. Heat maps revealed multifocal geographic hotspots, with most active locations somewhat different for day/evening vs night and ischemic vs hemorrhagic. The spatial analysis algorithm determined that optimal placement of 5 MSUs in highest incidence areas would provide coverage for 87.0% of county stroke events. Positioning of 2 additional units in geographically isolated perimeter areas increased coverage to 91.9% of stroke events (Figure). ConclusionsGeospatial modeling can delineate the most efficient positioning of MSU resources within regionalized EMS systems of stroke care. Optimal position varies with time of day and with prioritization of coverage for ischemic vs hemorrhagic stroke.