Hybrid Simulation of Mental Healthcare Systems: Modelling Integrated Care Pathways
PhD candidate: Youssef Elwan
Mental healthcare systems are complex adaptive environments shaped by the interplay between individual behavioral dynamics and organizational operational processes. Optimizing such systems requires methodological tools capable of capturing this multi-level complexity in a coherent and integrated way. This PhD project develops a hybrid simulation framework — combining Agent-Based Modelling (ABM) and Discrete Event Simulation (DES) — to model, analyse, and evaluate mental healthcare pathways, with the broader goal of supporting evidence-based design of integrated care interventions.
The framework operates across two abstraction levels: the individual micro-level, capturing mental health help-seeking behaviour through established behavioral theories, and the operational level, representing care pathways, resource allocation, and service flows. Empirical grounding is achieved through a combination of process mining of clinical event-log data, participatory stakeholder co-design, and survival analysis to model therapy adherence and treatment dropout. Together, these methods allow the simulation to reflect both the human and systemic dimensions of mental healthcare delivery.
The research is applied to a real-world case in the Netherlands, where integrated primary mental healthcare models are being piloted, serving as a vehicle for developing and validating the broader methodological framework. Ultimately, this work contributes to the growing literature on hybrid simulation in healthcare and offers a transferable methodology for evaluating complex health system interventions across different contexts and settings.
