Public Sector Analytics for Territorial Healthcare Planning: Federated Learning Under the European Health Data Space

• Het Rachhadiya

  Author

This paper applies public sector analytics to the challenges of demographic decline, population ageing, and progressive desertification of healthcare and social care services in many European territories. These trends threaten territorial cohesion and equitable access to care. The European Health Data Space (EHDS) establishes a new regulatory and infrastructural framework for primary and secondary use of health data across Member States, opening opportunities for advanced analytics under strict data protection safeguards. This paper argues that federated learning (FL), embedded within the EHDS governance framework, has the potential to serve as a policy data infrastructure to support territorial healthcare planning in ageing and shrinking regions. Public sector analytics components include long-term care demand forecasting, healthcare service availability indices, territorial inequality measurement, cross-regional benchmark comparisons, and policy intervention readiness scoring. Rather than focusing on algorithmic performance, we develop a conceptual model linking FL-enabled distributed analytics to concrete policy questions on care demand, service availability, and territorial inequalities in access. We first map the information needs of policy-makers dealing with demographic change and territorial cohesion, then analyse how EHDS provisions on secondary use, Health Data Access Bodies, and privacy-enhancing technologies can underpin multi-territorial FL projects. Building on this analysis, we propose a policy-oriented framework describing actors, processes, and outputs of EHDS-compliant FL initiatives aimed at informing regional and national health and social care strategies. We discuss implications for territorial cohesion, sustainability of health systems, and future research on governance of federated learning in European health data spaces.

1. Het Rachhadiya

   Het Rachhadiya is an independent researcher based in the United Kingdom, with research interests in artificial intelligence, business intelligence, data science, healthcare analytics, federated learning, multi-agent systems, cloud data platforms, and data-driven decision-making.

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