Advancing Personal Health Data Spaces: Governance, Interoperability, and Real-World Evidence for Learning Healthcare Systems

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Abstract
BACKGROUND: Healthcare systems increasingly generate large volumes of clinical, imaging, genomic, wearable and real-world healthcare data. However, fragmentation across healthcare infrastructures continues to limit interoperability, integrated evidence generation and coordinated patient management. OBJECTIVE: This commentary examines how Personal Health Data Spaces (PHDS) may support interoperable, patient-centred, and evidence-informed healthcare through the integration of governance, real-world evidence (RWE), artificial intelligence (AI) and health data infrastructures. APPROACH: Drawing on regulatory science, digital health policy, interoperability frameworks and RWE practice, this commentary proposes a conceptual framework for PHDS that distinguishes them from existing health data initiatives and presents an implementation-oriented roadmap for their adoption within learning healthcare systems. DISCUSSION: Personal Health Data Spaces may support continuity of care, multimodal evidence generation, regulatory science, AI-enabled analytics and personalised medicine across increasingly interconnected healthcare environments. However, their successful implementation depends on interoperable infrastructures, harmonised governance, methodological transparency, cybersecurity, workforce capability and meaningful multi-stakeholder collaboration to avoid reinforcing existing healthcare inequities and operational fragmentation. CONCLUSION: Personal Health Data Spaces represent a patient-centred operational framework for integrating healthcare data across clinical care, research, and regulatory decision-making, supporting the transition towards interoperable and continuously learning healthcare systems. Their long-term success will depend not only on technological capability, but also on trustworthy governance, scalable implementation strategies, and sustained public trust.

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