A Hybrid Simulation Approach for Modeling Critical Care Delivery in ICU

Critical care delivery entails a complex human-centric system. Patients and a multidisciplinary care team are the major autonomous agents in the system. Their actions and interactions with each other and the environment drive the dynamic evolution of the system and determine the system outcomes (e.g., patient outcome, provider burnout, care quality, system efficiency). The objective of this study was to model critical care delivery in an ICU to provide decision support to ICU resource management. A hybrid simulation approach combining agent-based simulation for modeling patients and care providers, and discrete event simulation for modeling care pathways was developed. This approach leverages clinical knowledge for modeling individual patient trajectories and care services endogenized from patient needs. It allows us to understand how the arrival flow of patients, the patient disease condition, and the care protocols jointly affect ICU census and provider workload, and build a pathway towards digital twinning of ICUs.