Europe is trying to do something genuinely hard: get 27 sovereign nations, each with its own language, healthcare system, and political culture, to share health data seamlessly. The European Health Data Space (EHDS) is the vehicle for that ambition, and it’s an impressive one. But ambition and implementation are two very different things.
I got a firsthand look at that gap this past fall in Copenhagen, at a symposium hosted under the Danish Presidency of the Council of the EU. Policy leaders, health authorities, and standards organizations were all in the room, working to advance the EHDS conversation. J2 Interactive was among a small number of non-European voices invited to contribute through our involvement with the HL7 FHIR Vulcan Accelerator, which focuses on the secondary use of health data for clinical research. What struck me most wasn’t the ambition in the room. It was the urgency. European stakeholders are acutely aware that the U.S. and the East are already operating at scale on health data interoperability. The gap is real, and people feel it.
So let me offer something concrete: a model that works.
The U.S. Health Information Exchange (HIE) model gets a bad rap sometimes, largely because American healthcare in general gets a bad rap (often deservedly). But underneath the fragmentation and the complexity, the country has spent nearly two decades building HIEs that actually function: systems that aggregate data from disparate sources, normalize it into something usable, and make it available for clinical care, research, and population analytics.
What makes the HIE model worth examining isn’t any one implementation. It’s the pattern itself: the combination of interoperability standards, governance structure, and operational discipline that makes health data sharing sustainable at scale. That pattern is exportable. And Europe needs it.
Here’s what that pattern actually looks like in practice.
What the HIE Model Gets Right
Data aggregation and harmonization. A mature HIE pulls from hospital EHRs (Epic, Cerner, and their peers), ambulatory systems, and mental health providers, then normalizes all of it using terminologies like LOINC, SNOMED CT, and HL7 FHIR. The result is a unified longitudinal care record that’s usable for both clinical and research purposes.
This matters enormously for Europe, where poor data quality and heterogeneity are persistent problems, especially when trying to do secondary use for clinical trials or population health work. The HIE model demonstrates that harmonization is achievable (not easy, but achievable) with the right ingestion pipelines, validation processes, and governance in place.
Patient matching and consent management. Cross-border data sharing raises genuinely complicated questions about patient identity and consent. Many EU nations have national health IDs, but those mechanisms break down at borders. U.S. HIEs have developed sophisticated patient matching algorithms and consent frameworks that work across decentralized systems, with auditable chains of custody that can satisfy regulators, institutions, and patients alike.
In Europe, where data sovereignty is a deeply held value (and a legal requirement), this kind of transparent, portable consent model isn’t optional. It’s fundamental.
HL7 FHIR as infrastructure, not just aspiration. FHIR adoption is accelerating globally, and Europe is part of that wave. In Copenhagen, proof-of-concept projects showed how FHIR repositories can serve as foundational infrastructure, with analytics tools, machine learning workflows, and observational study platforms plugging in downstream. FHIR isn’t a silver bullet: it works best when paired with complementary standards like HL7v2 and CDA. But as a foundation, it makes scalable, secure data access genuinely achievable.
A scalable, layered architecture. One of the most useful things about the U.S. HIE model is how it scales. There’s a natural three-tier structure: local HIEs aggregate across a single integrated delivery network, regional HIEs federate data across multiple competing systems, and national networks provide record location and exchange capabilities across the country.
Europe could adopt a similar layered approach: regional exchanges organized around language, culture, or disease focus, eventually integrating into the broader EHDS framework. You don’t have to solve everything at once. You build up.
The public utility mindset. This is the one that’s hardest to export, because it’s cultural as much as technical. A successful HIE isn’t just a platform. It’s an ecosystem with outreach staff, legal counsel, and compliance officers. U.S. HIEs have matured into trusted public utilities, supporting care delivery, research, and public health surveillance simultaneously.
In Copenhagen, European stakeholders openly acknowledged the need for this kind of shift: away from fragmented, siloed systems and toward shared public infrastructure. Transparency, auditability, and genuine governance aren’t nice-to-haves. They’re what builds trust with both institutions and the public.
Five Things European Leaders Should Take Away
Based on nearly two decades of building and supporting HIEs, here’s what I’d tell European health data leaders directly.
Start with reuse, not reinvention. The U.S. HIE pattern works. Not because of any specific product, but because of its emphasis on interoperability, governance, and trust. Adapt it, localize it… but don’t start from scratch when you don’t have to.
Invest in standards and infrastructure together. FHIR alone isn’t enough. A complete HIE ecosystem requires data quality tools, consent systems, and governance frameworks. Standards without infrastructure are just documents.
Design for scale from day one. Whether you’re starting with a disease cohort, a research use case, or a single region, build with the future in mind. HIEs grow organically, but they scale efficiently only when grounded in a common architecture from the start.
Engage stakeholders beyond IT. Legal teams, policymakers, and clinicians all play critical roles in building a sustainable HIE. The “people problem” is routinely harder than the technical one. Plan for it.
Make secondary use a first-class use case. EHDS isn’t just a clinical initiative. Research, public health surveillance, and real-world evidence generation should be core design goals, not features added later. If secondary use is an afterthought, the data infrastructure will reflect that.
Where This Leaves Europe
Europe isn’t starting from zero. The Nordic countries in particular have sophisticated health data systems that are genuinely world-class. But connecting those systems, standardizing their outputs across borders, and governing them transparently at a pan-European scale… that’s a different and harder problem.
The U.S. HIE experience offers a playbook for how to get there. Not a prescription, and certainly not a perfect model, but a tested pattern with real lessons embedded in it. If the EU can combine its strong social contract around healthcare with the proven interoperability frameworks that U.S. HIEs have spent two decades refining, it has a genuine shot at leading the world in ethical, effective health data use.
That would be worth the hard work it takes to get there.
