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Validation of a predictive model for automated external defibrillator placement in rural America
Greg Mears1, N Clay Mann, Dagan Wright
1Department of Emergency Medicine, University of North Carolina, Chapel Hill 27599-7594, USA. gdm@med.unc.edu
Objective:
The development of Automated External Defibrillators (AEDs) to treat out-of-hospital cardiac arrest (OOHCA) has greatly expanded the availability of life saving defibrillatory shocks in various settings. However, placement of AEDs in rural areas remains perplexing since OOHCAs are rare and unpredictable. We set out to develop a cost-effective rural AED placement model and to test the validity of the resulting model using OOHCAs attended by EMS.
Design:
A population-based cross-sectional study. Analytic Plan: An exhaustive literature search was conducted to identify community attributes correlated with successful placement of AEDs in rural regions. Identified attributes were characterized using U.S. Census and CDC heart disease mortality data to estimate the potential risk for AED use and applied this estimate to rural census tracts in all 50 states. Based upon risk, AEDS were assigned to each tract using a first responder model and cost effectiveness was assessed. Using Utah State EMS data, the predicted placement of AEDs in each tract was validated using the actual number of OOHCAs attended by EMS.
Results:
A total of 14,586 rural census tracts in 50 U.S. states were evaluated. On average, 2,600 AEDs were situated within each state. AED placement in rural areas proved as cost effective as health screening programs. In Utah, predicted AED placement correlated with the frequency of OOHCAs attended by EMS personnel (rho= 0.55, p < 0.001).
Conclusions:
The resulting model illustrates one potential way to determine the most beneficial location for rural AED placement.
