Mario Draghi’s recent report on European competitiveness makes the point with clarity: Europe is uniquely well-positioned to lead in data-driven healthcare, but the gap between potential and reality is widening. The United States and China are accelerating investment into applied AI and data ecosystems, while Europe has focused to date primarily on regulation, process harmonisation and ethical guardrails. These are necessary — but not sufficient to accelerate European innovation and strengthen competitiveness.
Europe’s current flagship policy initiatives — the AI Act and the European Health Data Space (EHDS) — are important steps. They aim to protect citizens, define trust, and enable data sharing across borders. But, taken in isolation, they do not solve the central strategic problem: Europe does not yet have sufficient infrastructure, incentives, or operating models to translate its health data into innovation at scale.
Moreover, most data used for research and care today captures only a fraction of the patient experience. Clinical records tend to reflect episodic, provider-recorded events. To support personalised care, long-term disease monitoring, prevention, and value-based delivery models, Europe must incorporate patient-generated data (such as continuous monitoring from wearables) and patient-reported outcomes (PROs) that capture symptoms, function, and quality of life in routine care. These data are essential to understanding the real burden of disease, the true impact of therapy, and the performance of health systems in improving lived health. But their value depends entirely on data quality — standardised collection protocols, clinician and patient facing systems that facilitate structured data entry, validated measures, semantic interoperability, and statistical treatment that avoids or mitigates bias. Without these, we risk producing evidence that is insufficiently robust to support reimbursement decisions, guideline development, or system-level planning. High-quality real-world evidence must become a core asset of European health systems, not a by-product.
The result is visible in pipelines and patents. In AI-enabled diagnostics, Europe lags far behind the US and increasingly behind China. In clinical development productivity, European pharmaceutical R&D efficiency trails that of American peers, despite similar scientific talent. Europe’s share of global clinical trials has been declining for some time. Start-ups spun out from European universities routinely relocate across the Atlantic once they begin to scale because that is where data liquidity, capital, and regulatory alignment support commercial deployment.
The heart of the issue is investment and incentives, not additional regulation.
What Europe needs now is a shift from regulatory focus to strategic industrial capability with the health of citizens at its core. To do this, one needs to focus on incentives that will stimulate a ‘Health Data Economy’ based on trust. This requires substantial investments and importantly incentives for hospitals and healthcare systems to improve data quality and share data.
This is why we are calling for a European Health Data Innovation Fund possibly managed by the European Investment Bank / European Investment Fund to serve as a catalyst for investments both public and private into the Health Data Infrastructure and Ecosystem. The key prerequisite for these investments to be successful and generate value both for society and investors are to make them conditional on a financing model that secures four things:
- Creates Incentives for High-Quality Data Curation at the Source.
Research-grade data do not emerge automatically from hospitals and health systems. Data quality must be designed for and the required efforts must be incentivised. This is why the model should reward health data creators and healthcare providers for contributing high-quality, interoperable, structured data that also capture patient generated data and patient reported outcomes. - Introduces incentives for Data Sharing among data holders.
Health data deliver much more value if they can be linked to data held in different data sets. With current information security measures this can still be done whilst protecting fully patients’ privacy and rights. However, the model should introduce incentives for data holders to share data sets and allow data linkage. Models such as the collecting societies for performing artists offer examples of how the value created can be shared among the various data providers. - Makes Data Access Decisions Faster, Transparent, and Risk-Based.
Current pathways to permit and provide data access are slow and unpredictable. Investments should be made conditional on the introduction of tiered pathways aligned to risk, with fast-track approvals for low-risk analytics and time-bound expert review for high-risk applications. - Ensures adherence to a Data Governance model that safeguards patient’s rights.
A health data economy can only flourish if it is built on a foundation of trust. As a result, an important conditionality for any investment would be to safeguard patient’s rights in order to ensure broad societal acceptability.
This agenda is not deregulatory. It is pro-innovation within strong ethical frameworks. Health data is becoming a strategic asset akin to energy or semiconductors. The countries that can turn real-world health data into rapid therapeutic development, predictive care models, and adaptive public health systems will not only improve health outcomes — they will define the next era of biomedical industry leadership.