병원 밖 심정지 CoS의 행위자 기반 시스템다이내믹스 모델 개발 = Development of an Agent-based System Dynamics Model for the Chain of Survival in Out-of-Hospital Cardiac Arrest

다국어 초록 (Multilingual Abstract)

Out-of-hospital cardiac arrest (OHCA) is a highly time-dependent medical emergency, in which survival rates vary dramatically depending on whether appropriate interventions are delivered within the first few minutes. International cardiopulmonary resuscitation guidelines define the recognition of cardiac arrest and emergency activation, bystander cardiopulmonary resuscitation (CPR), use of an automated external defibrillator (AED), advanced resuscitation by emergency medical services (EMS), and post–resuscitation care in hospital as the “chain of survival” (CoS), emphasizing that all links must function sequentially and effectively. Despite this framework, overall OHCA survival remains low, and conventional statistical approaches have limited capacity to capture the complex interactions among individual stages of the CoS.
The purpose of this study was to conceptualize the OHCA chain of survival as a dynamic system and to develop an agent-based system dynamics model in which each cardiac arrest event is represented as an agent moving through a stock–flow diagram. Based on a review of the literature, OHCA epidemiological data, and previous studies on system dynamics and agent-based modeling, pathways from cardiac arrest recognition through bystander CPR, advanced resuscitation, and post–resuscitation care were modeled using an agent-based system dynamics approach.
n the baseline model, the estimated survival rate was 8.4%, consistent with previously reported OHCA survival rates. Among the CoS stages, the highest mortality was observed during the bystander CPR and defibrillation stage (30.9%), followed by the advanced resuscitation stage after hospital arrival (23.6%). Simulation results demonstrated that reducing delays in the initiation of bystander CPR led to a nonlinear increase in survival, whereas longer ambulance arrival times were associated with a gradual decline in survival. By quantifying stage-specific mortality contributions within the CoS, this model provides a useful framework for identifying priorities for intervention to improve OHCA outcomes.