Identification of out-of-hospital cardiac arrest clusters using a geographic information system

E Brooke Lerner1, Rollin J Fairbanks, Manish N Shah

  • 1Department of Emergency Medicine, University of Rochester, 601 Elmwood Avenue, Box 655, Rochester, NY 14642, USA. brooke_lerner@urmc.rochester.edu

Insights

Mapping out-of-hospital cardiac arrests (OHCAs) identified geographic clusters. These areas, with lower bystander CPR rates, may benefit from targeted prevention and educational programs.

Area of Science:

  • Public Health
  • Epidemiology
  • Geographic Information Systems (GIS)

Background:

  • Out-of-hospital cardiac arrest (OHCA) is a critical medical emergency.
  • Identifying geographic patterns of OHCAs and bystander CPR is crucial for targeted interventions.
  • Previous studies have not fully utilized GIS for detailed spatial analysis of OHCA clusters and bystander CPR rates.

Purpose of the Study:

  • To map all OHCAs in Rochester, New York, and identify geographic clusters.
  • To identify clusters of OHCAs where bystander cardiopulmonary resuscitation (CPR) was not administered.
  • To inform prevention efforts and resource allocation for OHCA in specific high-risk areas.

Main Methods:

  • Utilized ArcGIS to plot OHCA locations obtained from emergency medical services (EMS) records.
  • Employed kernel analysis to identify high-density clusters of OHCAs and areas lacking bystander CPR.
  • Calculated OHCA incidence using census block groups to account for population density.

Main Results:

  • Identified two significant clusters of OHCAs, with two block groups showing the highest incidence.
  • Found that 80% of OHCAs did not receive bystander CPR; kernel analysis revealed three high-density areas for these cases.
  • Cluster areas were socioeconomically disadvantaged, with lower income, higher poverty, more African American residents, and lower educational attainment.

Conclusions:

  • Geographic mapping effectively identifies OHCA clusters, guiding resource allocation.
  • Spatial analysis can pinpoint areas with low bystander CPR rates for targeted educational programs.
  • Overlaying census data with OHCA clusters reveals demographic and socioeconomic factors, differentiating clusters from mere population density effects.
Abstract

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