Ahead of the ambulance: Optimizing volunteer training

Emergency response for medical incidents is increasingly extended by community first responder (CFR) systems that dispatch nearby trained volunteers. The implementation of CFR systems has led to significant decreases in emergency response times, especially in rural areas where ambulances take longer to arrive. CFR systems that dispatch volunteers to various emergency types can increase their effectiveness by training their volunteers, enabling these volunteers to provide first aid for more emergency types. We study the problem of optimizing a CFR system's training strategy to maximize its effectiveness given a limited budget, where the effectiveness is measured by the probability that at least one volunteer arrives before the ambulance for any given incident. We introduce an optimization model that explicitly accounts for the heterogeneous nature of volunteers' availability and locations, as well as a solution approach that efficiently obtains optimal solutions for realistically-sized instances. We apply the optimization approach to a CFR system operating in Lincolnshire, United Kingdom. The results show that the optimization approach yields substantially larger improvements in the CFR system's effectiveness compared to several intuitive greedy training strategies. Additionally, dispatch restrictions to limit the workload of volunteers are shown to have important implications for the optimal training strategy.