Identifying High-Risk Cardiac Arrest Neighborhoods Using Social Vulnerability Index and Geospatial Analysis.

Abstract

Background: Identifying high-risk locations for out-of-hospital cardiac arrest (OHCA) is essential for targeted community interventions. We aimed to use the Social Vulnerability Index (SVI) and geospatial mapping of OHCA data to locate high-risk neighborhoods in Birmingham, Alabama, for community training programs.

Methods: A retrospective observational analysis was conducted using nontraumatic OHCA cases in adults (≥18 years) in Birmingham from January 1, 2020 to December 31, 2023. Census tracts served as proxies for neighborhoods. A 5-step process identified high-risk tracts: (1) OHCA incidents were geocoded in ArcGIS and assigned a geographic identifier by census tract; (2) SVI data were merged with each record; (3) the Getis-Ord GI* statistic identified a hot spot with 99% confidence; (4) tracts with an SVI >90th percentile within the hot spot were flagged; and (5) excess relative risk rates were calculated and stratified by quintiles. The primary outcome was high-risk census tracts defined by hot spot location, high SVI, and high relative risk.

Results: A total of 966 OHCA cases from 115 census tracts were included. Hot spot analysis identified 30 tracts (26.1%) with high-risk characteristics. Within these, 17 tracts had an SVI >90th percentile, and 10 tracts had an excess relative risk in the top quintile. Hot spot tracts had a higher proportion of Black residents and lower cardiopulmonary resuscitation rates. No significant difference in survival outcomes were observed; however, the overall neurologically intact survival was 1.2%.

Conclusions: Multiple neighborhoods in Birmingham exhibit extreme levels of social vulnerability and excess relative risk of OHCA, making them ideal candidates for community training initiatives.