Evaluating policies using agent-based simulations: investigating policies for continuity of care

Anticipating effects of proposed clinical policies is a difficult task. This study investigates the usefulness of agent‐based simulations for evaluating clinical policies. Two policies for continuity of care for patients with type 2 diabetes are investigated using an agent‐based simulation. Computational models of a dynamic decision environment were simulated to determine aggregated effects of individual care‐providing agents acting to achieve clinical goals. The simulated policies were: 1) continuous care (CC), where each patient was randomly assigned a specific physician model for care across visits; 2) opportunistic care (OC), where each patient on each visit was randomly assigned to a physician model for treatment. These policy scenarios are at the crux of a debate as to whether continuity of care needs to be administered by a single provider or by a single organisation (e.g., clinic). The study determines under which conditions CC and OC policies result in favourable patient outcomes.