Healthcare network resilience analysis under equipment failure and patients’ preferences

We propose a resilience analysis framework to assess the resilience of an elective healthcare network subject to low-impact-high-frequency (LIHF) disruptions, thereby identifying the most critical facility, considering both the impact of disturbances and the probability of their occurrence. The proposed framework combines agent-based simulation with design of experiment (DOE) and patient behaviour modelling. The framework has been tested with data from a real case, demonstrating its usefulness for conducting resilience analyses and prioritising resilience-enhancing actions to improve network performance. Two resilience-enhancing actions with different characteristics have been tested. The distinctive feature of the framework is the consideration of patient preferences in the simulation, allowing patients to be considered as active actors who can influence the behaviour of the system during a disturbance.