Googling Service Boundaries for Endovascular Clot Retrieval Hub Hospitals in a Metropolitan Setting: Proof-of-Concept Study.

Background and Purpose: There is great interest in how endovascular clot retrieval hubs provide services to a population. We applied a computational method to objectively generate service boundaries for such endovascular clot retrieval hubs, defined by traveling time to hub.Methods: Stroke incidence...

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Publicado en:Stroke (00392499) Vol. 48; no. 5; pp. 1353 - 1362
Autores principales: Phan, Thanh G., Beare, Richard, Jian Chen, Clissold, Benjamin, Ly, John, Singhal, Shaloo, Ma, Henry, Srikanth, Velandai, Chen, Jian
Formato: pictorial research tables/charts Journal Article
Publicado: Lippincott Williams & Wilkins May2017
Acceso en línea:Ver este registro en EBSCOhost
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      dt: May2017
      vid: 48
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      pub: Lippincott Williams & Wilkins
      place: Baltimore, Maryland
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        10.1161/STROKEAHA.116.015323
        NLM28356438
        122680554
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        atl: Googling Service Boundaries for Endovascular Clot Retrieval Hub Hospitals in a Metropolitan Setting: Proof-of-Concept Study.
      aug:
        au:
          Phan, Thanh G.
          Beare, Richard
          Jian Chen
          Clissold, Benjamin
          Ly, John
          Singhal, Shaloo
          Ma, Henry
          Srikanth, Velandai
          Chen, Jian
        affil: Stroke Unit, Monash Health, Melbourne, Victoria, Australia
      sug:
        subj:
          Internet
          Transportation of Patients Statistics and Numerical Data
          Catchment Area (Health)
          Statistics Methods
          Stroke Therapy
          Hospitals Statistics and Numerical Data
          Models, Statistical
          Victoria
          Transportation of Patients Standards
          Human
      ab: Background and Purpose: There is great interest in how endovascular clot retrieval hubs provide services to a population. We applied a computational method to objectively generate service boundaries for such endovascular clot retrieval hubs, defined by traveling time to hub.Methods: Stroke incidence data merged with population census to estimate numbers of stroke in metropolitan Melbourne, Australia. Traveling time from randomly generated addresses to 4 endovascular clot retrieval-capable hubs (Royal Melbourne Hospital [RMH], Monash Medical Center [MMC], Alfred Hospital [ALF], and Austin Hospital [AUS]) estimated using Google Map application program interface. Boundary maps generated based on traveling time at various times of day for combinations of hubs.Results: In a 2-hub model, catchment was best distributed when RMH was paired with MMC (model 1a, RMH 1765 km2 and MMC 1164 km2) or with AUS (model 1c, RMH 1244 km2 and AUS 1685 km2), with no statistical difference between models (P=0.20). Catchment was poorly distributed when RMH was paired with ALF (model 1b, RMH 2252 km2 and ALF 676 km2), significantly different from both models 1a and 1c (both P<0.05). Model 1a had the greatest proportion of patients arriving within ideal time of 30 minutes followed by model 1c (P<0.001). In a 3-hub model, the combination of RMH, MMC, and AUS was superior to that of RMH, MMC, and ALF in catchment distribution and travel time. The method was also successfully applied to the city of Adelaide demonstrating wider applicability.Conclusions: We provide proof of concept for a novel computational method to objectively designate service boundaries for endovascular clot retrieval hubs.
      pubtype: Academic Journal
      doctype:
        pictorial
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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