title: An Analysis of Spatial Clustering of Stroke Types, In-hospital Mortality, and Reported Risk Factors in Alberta, Canada, Using Geographic Information Systems.
abstract: BACKGROUND
  Despite advances in the quality and delivery of stroke care, regional disparities in stroke incidence and outcome persist. Spatial analysis using geographic information systems (GIS) can assist in identifying high-risk populations and regional differences in efficacy of stroke care. The aim of this study was to identify and locate geographic clusters of high or low rates of stroke, risk factors, and in-hospital mortality across a provincial health care network in Alberta, Canada.
  
  
  METHODS
  This study employed a spatial epidemiological approach using population-based hospital administrative data. Getis-Ord Gi* and Spatial Scan statistics were used to identify and locate statistically significant "hot" and "cold" spots of stroke occurrence by type, risk factors, and in-hospital mortality.
  
  
  RESULTS
  Marked regional variations were found. East central Alberta was a significant hot spot for ischemic stroke (relative risk [RR] 1.43, p<0.001), transient ischemic attack (RR 2.25, p<0.05), and in-hospital mortality (RR 1.50, p<0.05). Hot spots of intracerebral hemorrhage (RR 1.80, p<0.05) and subarachnoid hemorrhage (RR 1.64, p<0.05) were identified in a major urban centre. Unexpectedly, stroke risk factor hot spots (RR 2.58, p<0.001) were not spatially associated (did not overlap) with hot spots of ischemic stroke, transient ischemic attack, or in-hospital mortality.
  
  
  CONCLUSIONS
  Integration of health care administrative data sets with geographic information systems contributes valuable information by identifying the existence and location of regional disparities in the spatial distribution of stroke occurrence and outcomes. Findings from this study raise important questions regarding why regional differences exist and how disparities might be mitigated.
authors.affiliation: 1Faculty of Medicine,Department of Community Health Sciences,University of Calgary,Calgary,Alberta,Canada.
authors.forename: Susan
authors.initials: S
authors.lastname: van Rheenen
authors.affiliation: 2Department of Clinical Neurosciences,Hotchkiss Brain Institute,University of Calgary,Calgary,Alberta,Canada.
authors.forename: Timothy W J
authors.initials: TW
authors.lastname: Watson
authors.affiliation: 3Department of Geography,University of Calgary,Calgary,Alberta,Canada.
authors.forename: Shelley
authors.initials: S
authors.lastname: Alexander
authors.affiliation: 4Department of Clinical Neurosciences,Community Health Sciences,Hotchkiss Brain Institute,University of Calgary,Calgary,Alberta,Canada.
authors.forename: Michael D
authors.initials: MD
authors.lastname: Hill
mesh_terms: D000367:Age Factors; D000368:Aged; D000416:Alberta / Q000453:epidemiology; D018672:Community Health Planning; D005260:Female; D040362:Geographic Information Systems; D054625:Healthcare Disparities / Q000706:statistics & numerical data*; D017052:Hospital Mortality; D006801:Humans; D002546:Ischemic Attack, Transient / Q000453:epidemiology; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D012189:Retrospective Studies; D012307:Risk Factors; D020521:Stroke / Q000145:classification / Q000453:epidemiology / Q000401:mortality
keywords: Cluster analysis; GIS; hot spot analysis; spatial epidemiology; stroke; stroke mortality