James P Rhudy, Anne W Alexandrov, Joseph Rike, Tomas Bryndziar, Ana Hossein Zadeh Maleki, Victoria Swatzell, Wendy Dusenbury, E Jeffrey Metter, Andrei V Alexandrov
{"title":"移动行程单元调度的地理空间可视化:一种优化服务性能的方法。","authors":"James P Rhudy, Anne W Alexandrov, Joseph Rike, Tomas Bryndziar, Ana Hossein Zadeh Maleki, Victoria Swatzell, Wendy Dusenbury, E Jeffrey Metter, Andrei V Alexandrov","doi":"10.1159/000490581","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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>I</i>, boxplot inspection, and <i>t</i> test. We calculated service areas using drive times to meet dispatch and true stroke need.</p><p><strong>Results: </strong>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 (<i>p</i> = 0.001785).</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":46280,"journal":{"name":"Interventional Neurology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1159/000490581","citationCount":"8","resultStr":"{\"title\":\"Geospatial Visualization of Mobile Stroke Unit Dispatches: A Method to Optimize Service Performance.\",\"authors\":\"James P Rhudy, Anne W Alexandrov, Joseph Rike, Tomas Bryndziar, Ana Hossein Zadeh Maleki, Victoria Swatzell, Wendy Dusenbury, E Jeffrey Metter, Andrei V Alexandrov\",\"doi\":\"10.1159/000490581\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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>I</i>, boxplot inspection, and <i>t</i> test. We calculated service areas using drive times to meet dispatch and true stroke need.</p><p><strong>Results: </strong>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 (<i>p</i> = 0.001785).</p><p><strong>Conclusion: </strong>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.</p>\",\"PeriodicalId\":46280,\"journal\":{\"name\":\"Interventional Neurology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1159/000490581\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Interventional Neurology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1159/000490581\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2018/7/24 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Interventional Neurology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1159/000490581","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2018/7/24 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"Medicine","Score":null,"Total":0}
Geospatial Visualization of Mobile Stroke Unit Dispatches: A Method to Optimize Service Performance.
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.