Out-of-hospital cardiac arrest (OHCA) is a huge health issue affecting over 700,000 people annually in Europe and North America, of which 4000 arrests occurs every year in Denmark. Survival is low around 10%, but more than 50% may survive if defibrillated (shocked) by an automated external defibrillator (AED) within minutes. Despite huge investments in AED deployment less than 4% of all arrests are defibrillated before ambulance arrival. Therefore, new strategies aimed to increase bystander defibrillation are highly desirable. The overall purpose of the research program is to improve out-of-hospital cardiac arrest survival as well as improve neurological intact survival by engaging citizens in early resuscitation. This can be achieved through a multifaceted approach using 1) advanced, artificial intelligence deep learning systems to improve recognition of cardiac arrest during emergency calls; 2) optimal placement and accessibility of AEDs in society using machine learning programs; 3) using new technology to activate volunteer citizens to use AEDs before ambulance arrival through smartphone application systems; 4) testing a strategy of AED deployment combined with activation of local residents in selected residential areas normally not accessible for AED defibrillation; and 5) reaching OHCAs in areas with long ambulance response times and dismal survival chances using an innovative AED drone delivery system.
The nature of the research program is highly translational, meaning that the results can be directly implemented in daily practice leading to improved OHCA survival not only in Denmark, but also internationally.