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Background Mathematical optimization of automated external defibrillator (AED) placement may improve AED accessibility and out-of-hospital cardiac arrest (OHCA) outcomes compared with American Heart Association (AHA) and European Resuscitation Council (ERC) placement guidelines. We conducted an in silico trial (simulated prospective cohort study) comparing mathematically optimized placements with placements derived from current AHA and ERC guidelines, which recommend placement in locations where OHCAs are usually witnessed. Methods and Results We identified all public OHCAs of presumed cardiac cause from 2008 to 2016 in Copenhagen, Denmark. For the control, we computationally simulated placing 24/7-accessible AEDs at every unique, public, witnessed OHCA location at monthly intervals over the study period. The intervention consisted of an equal number of simulated AEDs placements, deployed monthly, at mathematically optimized locations, using a model that analyzed historical OHCAs before that month. For each approach, we calculated the number of OHCAs in the study period that occurred within a 100-m route distance based on Copenhagen's road network of an available AED after it was placed ("OHCA coverage"). Estimated impact on bystander defibrillation and 30-day survival was calculated by multivariate logistic regression. The control scenario involved 393 AEDs at historical, public, witnessed OHCA locations, covering 15.8% of the 653 public OHCAs from 2008 to 2016. The optimized locations provided significantly higher coverage (24.2%; P <0.001). Estimated bystander defibrillation and 30-day survival rates increased from 15.6% to 18.2% ( P <0.05) and from 32.6% to 34.0% ( P <0.05), respectively. As a baseline, the 1573 real AEDs in Copenhagen covered 14.4% of the OHCAs. Conclusions Mathematical optimization can significantly improve OHCA coverage and estimated clinical outcomes compared with a guidelines-based approach to AED placement.

Background: Automated external defibrillators (AEDs) are often placed in areas of low risk and limited temporal availability. Mathematical optimization can improve AED accessibility but has not been compared with current practices., Objectives: This study sought to determine whether, compared with real AED locations, optimized AED locations improve coverage of out-of-hospital cardiac arrests (OHCAs)., Methods: The authors conducted the first retrospective in silico trial of an AED placement intervention. This study identified all public OHCAs of presumed cardiac cause and real AED deployed (control group) from 2007 to 2016 in Copenhagen, Denmark. Optimization models trained on historical OHCAs (1994 to 2007) were used to optimize an equal number of AEDs to the control group in locations with availabilities based on building hours (intervention #1) or 24/7 access (intervention #2). The 2 interventions and control scenario were compared using the number of OHCAs that occurred within 100 m of an accessible AED ("OHCA coverage") during the 2007 to 2016 period. Change in bystander defibrillation and 30-day survival were estimated using multivariate logistic regression., Results: There were 673 public OHCAs and 1,573 registered AEDs from 2007 to 2016. OHCA coverage of real AED placements was 22.0%. OHCA coverage of interventions #1 and #2 was significantly higher at 33.4% and 43.1%, respectively; relative gains of 52.0% to 95.9% (p < 0.001). Bystander defibrillation increased from 14.6% (control group) to 22.5% to 26.9% (intervention #1 to intervention #2); relative increase of 52.9% to 83.5% (p < 0.001). The 30-day survival rates increased from 31.3% (control group) to 34.7% to 35.4%, which is a relative increase of 11.0% to 13.3% (p < 0.001)., Conclusions: Optimized AED placements increased OHCA coverage by approximately 50% to 100% over real AED placements, leading to significant predicted increases in bystander defibrillation and 30-day survival., (Copyright © 2019 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Aims: Mathematical optimization of automated external defibrillator (AED) placements has the potential to improve out-of-hospital cardiac arrest (OHCA) coverage and reverse the negative effects of limited AED accessibility. However, the generalizability of optimization approaches has not yet been investigated. Our goal is to examine the performance and generalizability of a spatiotemporal AED placement optimization methodology, initially developed for Toronto, Canada, to the new study setting of Copenhagen, Denmark., Methods: We identified all public OHCAs (1994-2016) and all registered AEDs (2016) in Copenhagen, Denmark. We calculated the coverage loss associated with limited temporal accessibility of registered AEDs, and used a spatiotemporal optimization model to quantify the potential coverage gain of optimized AED deployment. Coverage gain of spatiotemporal deployment over a spatial-only solution was quantified through 10-fold cross-validation. Statistical testing was performed using χ 2 and McNemar's tests., Results: We found 2149 public OHCAs and 1573 registered AED locations. Coverage loss was found to be 24.4% (1104 OHCAs covered under assumed 24/7 coverage, and 835 OHCAs under actual coverage). The coverage gain from using the spatiotemporal model over a spatial-only approach was 15.3%. Temporal and geographical trends in coverage gain were similar to Toronto., Conclusions: Without modification, a previously developed spatiotemporal AED optimization approach was applied to Copenhagen, resulting in similar OHCA coverage findings as Toronto, despite large geographic and cultural differences between the two cities. In addition to reinforcing the importance of temporal accessibility of AEDs, these similarities demonstrate the generalizability of optimization approaches to improve AED placement and accessibility., (Copyright © 2018 Elsevier B.V. All rights reserved.)