Practical Heuristics for Victim Tagging During a Mass Casualty Incident Emergency Medical Response

Mass casualty incidents (MCIs) are a growing concern. Recent efforts to improve the MCI emergency medical response focus on resource allocation, responder coordination, or transportation efficiency, and often overlook the initial, yet critical, step of tagging victims on scene. Tagging victims in minimal time is vital in providing information that guides subsequent time-constrained response actions. In this paper we present a mathematical formulation of multi-agent victim tagging to minimize the time it takes for responders to tag all victims. Five distributed heuristics are formulated and evaluated with simulation experiments. The heuristics considered are on-the go, practical solutions that represent varying levels of situational uncertainty in the form of global or local communication capabilities, showcasing practical constraints. Extensive simulations demonstrate that local methods are more efficient for adaptive victim tagging, specifically choosing the nearest victim with the replanning option.