Our view on the European healthcare landscape
Kinnevik’s healthcare team — Christian Scherrer, Maria Maras, Andrey Simeonov and Amanda Hillström — share their perspectives on the key developments shaping European healthcare today, and how these shifts will define the landscape for patients and providers for decades to come.
What structural changes are happening in European healthcare now that will matter in 5-10 years?
There is a profound structural change underway in European healthcare right now, driven by aging demographics, strained public budgets, and the maturity of technological adoption in the healthcare sector.
At the core of this change is the necessary pivot from episodic ‘sick care’ to preventative, data-driven, personalised care. Healthcare systems across France, Germany, the Nordics, and the UK are steadily shifting resources from high-cost, reactive, in-person settings toward home settings, proactive care and longitudinal chronic disease oversight. This will reward care delivery and software platforms capable of managing and improving the health of defined populations at a predictable cost.
Moreover, regulatory and labour dynamics are also amplifying and accelerating the adoption of technology in healthcare. Europe-wide initiatives including the European Health Data Space (EHDS) and country-specific initiatives including the NHS Federated Data Platform are creating the scalable guardrails and infrastructure required to unlock transformational adoption of software and AI. Other initiatives such as national patient records being increasingly “opt-out” by default and mandated interoperability will further facilitate this change. This foundation will be vital to the massive adoption of AI in healthcare, already underway, which will shift the technology from ‘AI as an assistant’ to “AI as the clinical workflow infrastructure” – software embedded directly into care delivery and operations, judged on clinical risk management, measurable ROI, and its ability to augment decisions rather than simply inform them. Companies like Tandem Health reflect this shift: starting with administrative burden reduction, they are embedding deeply into physicians’ workflows and building the trust required to expand into broader clinical infrastructure.
This shift is structural and necessary given these labour dynamics. Unlike other verticals, healthcare is mostly constrained by supply, not demand. In Europe, there is a shortage of roughly 1.2m doctors, nurses and midwives, compounded by an aging workforce and rising chronic disease burden. In that context, increased adoption of technology and the upskilling of the healthcare workforce in technological literacy will become a system necessity - a lever to expand effective clinical capacity.
Tandem Health is an AI-powered clinical documentation platform. It reduces administrative workload for doctors, helping them save time, reduce burnout, and to focus on patient care.
What major changes in regulation could fundamentally change the game (or vice versa)?
Regulation is no longer perceived as a mere obstacle to innovation in European healthcare. Digitalization has shifted from fragmented pilots to funded national programmes. Governments are no longer just encouraging digital health; they are mandating infrastructure.
As mentioned earlier, the European Health Data Space is a good example, a transformation similar to open banking. Closed EHR estates are being pushed toward API-addressable systems, lowering structural data silos and enabling applications to build on top of incumbents rather than replace them. As interoperability becomes policy, defensibility shifts. Data access alone will not be the moat. Workflow ownership, integration depth, auditability, and real-world model performance become the new competitive edge.
The EU AI Act reinforces this shift. High-risk medical AI systems will require governance, monitoring and post-market oversight, turning trust into a product necessity rather than an afterthought. This is not unique to Europe. Similar interoperability initiatives in the US are underway, notably through TEFCA and supporting iterative AI updates via the FDA. Across both regions, regulation is determining distribution. To enable scale, healthcare innovation will need to cleanly integrate into national rails and governance frameworks.
Oviva provides digital, clinically supervised weight management programs prescribed by doctors and funded by public healthcare systems. It helps patients treat obesity and improve their health while reducing long-term healthcare costs.
Why does the public market still struggle to price long-duration healthcare compounding?
The narrative in public markets remains cautious toward healthcare innovation, in part because these businesses need time to mature and prove their value-add, and in part because of the sector’s structural complexity. Reimbursement resets, integration investments and utilisation fluctuations can create short-term noise that masks the gradual strengthening of underlying economics.
It is true that healthcare companies need time to mature. Healthcare compounding looks messy before it looks inevitable. Evidence loops are long and clinical outcomes take time to validate. Utilization patterns and reimbursement contracts evolve over multi-year cycles. Margin expansion is driven by operational learning and optimization. Durability only becomes legible after repeated cycles of outcomes evidence, contract renewal, and efficiency gains.
At scale, however, the strongest digital care delivery companies resemble SaaS-like compounders – embedded workflows, high retention, data advantages and AI-driven operating leverage. Oviva shows how this can unfold: early investment in clinical evidence, deep integration into reimbursement systems and disciplined operational build-out over time create trust, increasingly predictable growth and structurally strong economics.
Public markets often price “AI exposure” quickly but discount healthcare delivery compounding because it requires patience and domain literacy. As resilience and sustained profitability are demonstrated over time, normalized multiples are likely to adjust. Healthcare compounding rarely looks exciting in year one - it looks inevitable in year ten.
The inevitable but underbuilt opportunity
The inevitable opportunity in healthcare is solving the capacity constraint. Every bottleneck – prior authorization, referrals, fragmented follow-ups, documentation burden – consumes scarce clinical time.
What remains underbuilt is the infrastructure to enhance the healthcare workforce – the reasoning and orchestration layer that connects patients, providers and payers in real time. This includes AI-native clinical operating systems embedded in provider workflows, payer-side automation that compresses authorization and approval cycles, continuous care models that shift from episodic visits to ongoing risk management, and real-time integration of longitudinal data into actionable decisions. The next decade will be defined by AI systems that expand effective clinical capacity.
