Keywords: Future GPs, AI for Health, EU Health Tech, Smart Primary Care, GP-Led AI

Background:

The evolving healthcare landscape burdens family physicians (GPs) with increasing workloads and burnout, deterring the next generation. Simultaneously, Artificial Intelligence (AI) offers transformative potential for efficiency and clinical support. The European Health Data Space (EHDS) is establishing a crucial framework for secure, interoperable health data, foundational for ethical AI deployment and empowering GPs in a changing environment.

Research questions:

How can a European network, co-creating EHDS-conform AI tools with GPs and start-ups, effectively empower future family physicians and improve patient outcomes?

Method:

A participatory design approach will guide this network. It involves in-depth GP needs assessments and start-up engagement. Iterative co-creation workshops will develop EHDS-compliant AI tool MVPs. These will undergo pilot implementation in GP practices, evaluating impact on workload, decision-making, and patient satisfaction, followed by strategies for broader European scaling.

Results:

The network is anticipated to yield GP-centric, EHDS-conform AI tools, significantly reducing administrative burden and enhancing clinical decision support. This will empower family physicians, improve job satisfaction, and lead to better patient outcomes through more personalized and efficient care. It will also accelerate European health tech innovation.

Conclusions:

Establishing this European AI Innovation Network is crucial for empowering the next generation of family physicians. By fostering co-creation of EHDS-conform AI tools, it will alleviate GP pressures, enhance patient care, and position Europe as a leader in responsible digital health. This ensures a resilient and future-proof primary healthcare system.

Points for discussion:

How do we ensure these tools are not just technologically advanced but also genuinely intuitive, clinically relevant, and reduce, rather than increase, GP burden?

How can the network specifically address challenges like data heterogeneity across EU member states, differing national interpretations of regulations, and ensuring algorithmic fairness across diverse patient populations?

Successful pilots are a start, but how do we transition from individual projects to a sustainable, self-perpetuating ecosystem for AI innovation in primary care?