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Geospatial Visualization of Mobile Stroke Unit Dispatches: A Method to Optimize Service Performance.
Rhudy, James P; Alexandrov, Anne W; Rike, Joseph; Bryndziar, Tomas; Hossein Zadeh Maleki, Ana; Swatzell, Victoria; Dusenbury, Wendy; Metter, E Jeffrey; Alexandrov, Andrei V.
Afiliación
  • Rhudy JP; Department of Neurology, College of Medicine, University of Tennessee Health Science Center, Memphis, Tennessee, USA.
  • Alexandrov AW; Department of Neurology, College of Medicine, University of Tennessee Health Science Center, Memphis, Tennessee, USA.
  • Rike J; College of Nursing, University of Tennessee Health Science Center, Memphis, Tennessee, USA.
  • Bryndziar T; Department of Neurology, College of Medicine, University of Tennessee Health Science Center, Memphis, Tennessee, USA.
  • Hossein Zadeh Maleki A; Department of Neurology, College of Medicine, University of Tennessee Health Science Center, Memphis, Tennessee, USA.
  • Swatzell V; Internal Medicine Residency Program, College of Medicine, University of Tennessee Health Science Center, Memphis, Tennessee, USA.
  • Dusenbury W; Department of Neurology, College of Medicine, University of Tennessee Health Science Center, Memphis, Tennessee, USA.
  • Metter EJ; College of Nursing, University of Tennessee Health Science Center, Memphis, Tennessee, USA.
  • Alexandrov AV; Department of Neurology, College of Medicine, University of Tennessee Health Science Center, Memphis, Tennessee, USA.
Interv Neurol ; 7(6): 464-470, 2018 Oct.
Article en En | MEDLINE | ID: mdl-30410526
BACKGROUND: Timely treatment of acute ischemic stroke is crucial to optimize outcomes. Mobile stroke units (MSU) have demonstrated ultrafast treatment compared to standard emergency care. Geospatial analysis of the distribution of MSU cases to optimize service delivery has not been reported. METHODS: We aggregated all first-year MSU dispatch occurrences and all cases classified by clinical teams as true stroke by zip code and calculated dispatch and true stroke incidence rates. We mapped dispatch and stroke cases and symbolized incidence rates by standard deviation. We confirmed visual impressions of clusters from map inspection by local Moran's I, boxplot inspection, and t test. We calculated service areas using drive times to meet dispatch and true stroke need. RESULTS: A significant cluster of high dispatch incident rate was confirmed around our MSU base in urban Memphis within a 5-min driving area supporting the initial placement of the MSU based on 911 activation. A significant cluster of high true stroke rate was confirmed to the east of our MSU base in suburban Memphis within a 10-min driving area. Mean incident longitude of cases of true stroke versus disregarded status was significantly eastward (p = 0.001785). CONCLUSION: Our findings will facilitate determination of socio-spatial antecedents of neighborhood overutilization of 911 and MSU services in our urban neighborhoods and service delivery optimization to reach neighborhoods with true stroke burden.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Interv Neurol Año: 2018 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Interv Neurol Año: 2018 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Suiza