Healthcare policy making is complex, requiring both human expertise and data-driven support. Agent-based Social Simulations (ABSS) provide a powerful tool for testing the potential consequences of healthcare policy interventions in a controlled environment. By integrating computational modeling with expert knowledge, ABSS enable hybrid-human policy collaborations, where simulation results support human decision-making. This approach facilitates policy refinement and scenario analysis through participatory modeling, leading to more adaptive and socially sustainable policies. We argue that ABSS enhances decision-making by complementing simulation-based insights with qualitative expertise, enabling more sustainable and evidence-based healthcare policies.