Characteristics of automated external defibrillator coverage in Philadelphia, PA, based on land use and estimated risk. (December 2016)

• Record Type: Journal Article
• Authors: Chrisinger, Benjamin W.; Grossestreuer, Anne V.; Laguna, Meredith C.; Griffis, Heather M.; Branas, Charles C.; Wiebe, Douglas J.; Merchant, Raina M.
• Is Part Of: Resuscitation. Volume 109(2016)
• Page Start: 9
• Page End: 15
• Publication Date: 2016-12
• Subjects: Automated external defibrillator -- Cardiac arrest -- Geographic information systems -- Land use; Resuscitation -- Periodicals; Resuscitation -- Periodicals; Réanimation -- Périodiques; Electronic journals; 616.025
• DOI: 10.1016/j.resuscitation.2016.09.021
• Languages: English
• ISSNs: 0300-9572

Abstract

Abstract: Aim: Approximately 424, 000 out-of-hospital cardiac arrests (OHCA) occur in the US annually. As automated external defibrillators (AED) are an important part of the community response to OHCA, we investigated how well the spatial demand (likelihood of OHCA) was met by the spatial supply (AEDs) in a dense urban environment. Methods: Using geographic information system (GIS) software, we applied kernel density and optimized hot spot procedures with two differently-sized radii to model OHCA incidence rates from existing studies, providing an estimate of OHCA likelihood at a given location. We compared these density maps to existing AED coverage in the study area. Descriptive statistics summarized coverage by land use. Results: With a 420-ft buffer, we found that 56.0% (79.9%, 840-ft buffer) of the land area in the city center was covered by existing AEDs at, though 70.1 (91.5)% of the OHCA risk was covered using kernel density and 79.8% (98.1) was covered using hot spot analysis. Conclusions: The difference in coverage by area and risk seems to indicate efficient placement of existing AEDs. Our findings also highlight the possible benefits to expanding the influence of AEDs by lowering search times, and identify opportunities to improve AED coverage in the study area. This article offers one method by which local officials can use spatial data to prioritize attention for AED placement and coverage.