Digital-twin co-simulation framework to support informed decision in healthcare planning and management

Abstract

This manuscript aims to show the proof-of-concept for the integration of digital twin (DT) and discrete event co-simulation through its application to forward simulation of physical activities of care providers and robots in an intensive care unit (ICU). Co-simulation focuses on modular integration of heterogeneous simulation components to capture the complexity inherent in systems. Advancing this conception, the proposed co-simulation attempted to narrow gaps with real-world systems by using DT while simultaneously leveraging the forward simulation capacity of discrete event simulation (DES). In particular, we created a co-simulation for human–robot interactions in a simulated ICU facility, which modeled the hospital layout including the facility, robot, avatars for healthcare professionals, equipment, patient bed, and vital signs, which comprise physical twin (PT). In addition, specific patient-care scenarios were defined to drive PT for which the states of interest were represented in the DT, and then used for a dynamic input to the discrete event co-simulation. At the onset of the co-simulation, the parameters needed to run DES were manually configured to align the parameters with those of the DT. For internal validation, this DES was replicated under different work-system policies, and the co-simulation outcomes were interpreted in clinical context. Our co-simulation approach has potential for application to a broader class of problems in healthcare planning and management by supporting informed decision-making. Methodologically, timely information exchanges of PT with DT, and ensuing model updates in the Discrete Event System Specification (DEVS) is a promising approach for co-simulation, to maintain robustness against perturbations to real-world systems.