Ensuring timely and equitable access to primary care remains a central challenge for healthcare systems, particularly as providers retire, relocate, or enter the workforce unevenly across regions. Beyond determining how many providers are required, policymakers face the problem of allocating limited healthcare resources in a way that meaningfully improves access to care across space. Traditional planning approaches typically rely on static capacity indicators, which fail to capture how workforce changes dynamically affect patient access and provider workload.

We develop a data-driven digital twin of the Austrian primary care system in which patient access emerges from decentralized preferences over distance, availability, and local competition between providers.

Using this framework, we simulate physician retirement and entry and quantify how these supply-side changes propagate through accessibility and provider workload, capturing non-linear effects such as endogenous patient reallocation and organic uptake by new providers.

By linking workforce availability to system-level accessibility and stress dynamics, the model enables scenario-based evaluation of workforce planning strategies in terms of how effectively resources are deployed to improve access, rather than capacity alone.