b'CARES 2023 Annual ReportEXPLORING DISPARITIES AND SOLUTIONS IN OUT-OF-HOSPITAL CARDIAC ARREST:A SPATIAL ANALYSIS APPROACHResearchers are actively studying ways to improve survival rates for out-of-hospital cardiac arrest (OHCA) by exploring various factors that influence survival, including both spatial and non-spatial elements. Non-spatial factors include patient attributes such as age, sex, and comorbidities, as well as the resuscitation process. Spatial factors include response time, transport distance, and differences between rural and urban areas. Notably, response time and transport distance significantly affect the time from 911 call to hospital admission. 1Efforts to reduce response times and allocate pre-hospital resources effectively require emergency medical services (EMS) to pinpoint communities at the highest risk of OHCA. 2This emphasis on high-risk areas is crucial for optimizing the first three links in the Chain of Survival early recognition and activation of the emergency response system, early CPR, and rapid defibrillation. Geographic information systems (GIS) can play a pivotal role in this by enabling the targeting of services at a more local level. By integrating data from various sources and utilizing spatial analysis, researchers can identify meaningful patterns, evaluate trends, and inform recommendations to improve OHCA response. This comprehensive approach, which considers both spatial and non-spatial factors, has the potential to lead to more effective planning and resource allocation, ultimately improving outcomes for OHCA patients.OHCAs at the census-tract level:Sasson et al. (2011) 3utilized CARES data from Fulton County, Georgia between 2005 and 2008 to investigate the impact of neighborhood characteristics on OHCA survival rates. Spatial analysis techniques, including multilevel Poisson regression and Empirical Bayes methods, were used to assess the stability of cardiac arrest incidence within census tracts and to analyze the variability in bystander CPR (bCPR) rates across neighborhoods. The results unveiled striking disparities in both OHCA incidence and bCPR rates across neighborhoods within Fulton County. The average census tract exhibited an adjusted incidence rate of 0.64 events per 1,000 people. Notable variability was observed across the 161 census tracts, with unadjusted rates varying between 0.04 to 2.11 per 1,000 persons. The mean number of cardiac arrests per census tract per year was 2.21, with 25 census tracts having more than twice that number in at least one of the three study years. The intraclass correlation coefficient for variation between census tracts was 0.36, indicating that neighborhoods with high incidence of cardiac arrest in one year were likely to have high rates the next year. Bystander CPR rates varied widely among neighborhoods as well, ranging from 0% to 100% (10% to 57% after adjustment), with an average rate of 25% for the entire sample. In a separate analysis of bCPR rates in Fulton County, Figure 1 illustrates the spatial distribution of bCPR rates.Figure 1. BCPR Rates of OHCA at Census Tract Level, Fulton County, GA, CARES 2011-2013. 48 49'