A Generalized Nash Equilibrium-Seeking Scheme for Trauma Resuscitation
It addresses the problem of optimizing trauma resuscitation decisions for healthcare workers in safety-critical environments, but the approach is incremental as it applies existing game-theoretic methods to a new domain.
The paper formulates trauma resuscitation as a distributed generalized Nash equilibrium-seeking game to model healthcare worker decisions, aiming to improve patient outcomes by optimizing resource allocation under constraints.
Trauma resuscitation is a clinical process for treating life-threatening physiological disorders in safety-critical environments, driven by the experience of healthcare workers (HCWs). Designing and optimizing quantifiable metrics that accurately capture HCW decisions may augment current resuscitation procedures with the potential to improve patient outcomes. This motivates our socio-technical formulation of trauma resuscitation as a distributed generalized Nash equilibrium (GNE)-seeking game with coupled inequality constraints. This method is optimized over a time-varying communication graph. We introduce novel insights from clinical experience to model HCWs behavior. This work facilitates the best possible resuscitation outcome given HCWs workloads, schedules, competencies, and limited resources.