table of content

• Why doesn’t a successful pilot guarantee adoption in healthcare? 
• Healthcare is an operational system, not a software market 
• What does interoperability mean in healthcare beyond APIs? 
• Who pays for digital health innovation? 
• Europe is not one healthcare market 
• How should healthtech companies design pilots for scale? 
• What makes healthcare technology successful in everyday care? 

Healthcare innovation often begins with a compelling promise: a technology works, the clinical rationale is sound, early users respond positively, and a pilot produces encouraging results. Yet none of these achievements guarantees that the solution will become part of everyday care. Healthcare organisations are complex operational systems, and existing workflows, limited resources, procurement processes, reimbursement models, regulatory requirements and deeply established ways of working all shape how they operate. As a result, even technically strong products can struggle once they leave a controlled pilot environment. The real challenge, therefore, is not simply proving that a digital health or AI solution can work, but demonstrating that it can fit into the system around it without creating additional friction for the people expected to use it.

This gap between technical success and real-world adoption is one of the recurring challenges highlighted by Estefanía ‘Nia’ Escobar-Kölle, Innovation Manager at Future4Care, in a recent episode of Beyond Delivery. Drawing on her experience across healthcare systems and international markets, she argues that companies often underestimate how differently healthcare behaves from a conventional software market. Adoption depends on understanding how care is delivered and financed, what infrastructure is already in place, and what a new solution will require from the clinical teams expected to use it. Addressing these conditions early is what begins to separate a promising experiment from a solution that can become part of routine care.

Why doesn’t a successful pilot guarantee adoption in healthcare? 

A successful pilot can demonstrate that a technology performs as intended, but it says far less about whether that technology can survive beyond a controlled test environment. In healthcare, the transition from validation to routine use introduces an entirely different set of questions, including whether clinicians have the capacity to use the solution, whether it fits existing care pathways and IT systems, whether there is a clear owner once the pilot ends, and whether continued use can be justified financially and operationally. NHS England’s review of real-world AI evaluations reflects this distinction particularly well, examining not only the effectiveness of technologies but also their fit with individual sites, barriers to implementation, scalability and long-term sustainability. It also shows how deployment can be undermined when implementation plans do not sufficiently account for existing clinical pathways or the capacity of adopting organisations. A pilot may therefore prove that a product works, while leaving unanswered the more consequential question of whether the healthcare system around it can realistically absorb it. 

The distinction becomes even clearer when companies design a pilot with scale in mind from the outset. As Escobar-Kölle points out, companies preparing for adoption ask operational questions early. Who will own the solution once the pilot ends? Which department will pay for it? What outcomes will justify continued investment? How will the technology integrate with existing systems? And what support will the organisation need once the supplier steps back? These questions may seem less exciting than model performance or product features. Yet they decide whether a pilot has a realistic path into routine use. Without clear ownership, budget, integration and success measures, even a positive pilot can remain a temporary experiment.

Healthcare is an operational system, not a software market 

The difficulty is amplified by the fact that healthcare organisations are already operating under considerable pressure, leaving little room for technologies that require additional attention rather than reducing existing workload. The OECD estimates that the EU faced a shortage of approximately 1.2 million doctors, nurses and midwives in 2022, a figure that helps put the implementation challenge into perspective.In an environment where staff shortages already constrain clinical capacity, every additional platform to open, alert to review, data point to monitor or process to document competes for time that clinicians need elsewhere. This is why organisations cannot judge the value of a digital health solution only by what it enables in isolation. Its impact also depends on what it asks of the organisation around it. Even a tool that aims to improve care can become another operational burden. This happens when its benefits rely on work that nobody has the capacity to do.

Remote patient monitoring illustrates this tension particularly well. A sensor may collect clinically useful information and support earlier discharge. But the technology only creates value if someone can interpret the data and act on it. Escobar-Kölle highlights the practical questions that often emerge at this stage. Does the hospital have staff who can monitor the data? Are the relevant software and alerting processes already in place? Can overstretched clinical teams realistically absorb another stream of information? The problem is not that the technology fails. It is that its operating model depends on resources the organisation may not have. Implementation exposes the gap between what a solution can do in theory and what a provider can sustain in practice.

What does interoperability mean in healthcare beyond APIs? 

Interoperability in healthcare is more than a technical question of whether two systems can exchange data. As Escobar-Kölle argues, a technically feasible integration can still fail. It may add another disconnected platform or force clinicians to switch between systems. It may also assume infrastructure the organisation does not yet have. Recent OECD work makes a similar distinction. It frames interoperability as part of a shift from facility-based health information systems to integrated digital health ecosystems. In these ecosystems, data can follow patients across the care continuum. Seen from this perspective, interoperability is not simply about connecting software. It is about making technology compatible with the wider environment where clinicians deliver care. This includes existing systems, workflows, responsibilities and the people who will use them.

At European level, the European Health Data Space is intended to address some of this fragmentation by creating a common framework for the secure exchange and use of electronic health data and by supporting a more interoperable market for electronic health record systems. The regulation entered into force in March 2025, although its implementation is deliberately gradual, with key requirements coming into application in stages from 2029 onwards. This represents an important step towards making health data more accessible across systems and borders, but it does not remove the organisational dimension of interoperability. Common standards can make it easier for systems to communicate, yet healthcare providers will still need to determine how new technologies fit into existing clinical processes, who is responsible for them and whether their introduction genuinely simplifies the way they deliver care. In other words, better infrastructure can lower the technical barriers to adoption, but it cannot by itself ensure that a solution becomes part of everyday practice.

Who pays for digital health innovation? 

Even when a technology fits clinical workflows and delivers measurable value, adoption still depends on whether there is a viable way to pay for it. Healthcare makes this particularly complex because the person using a solution, the organisation purchasing it and the entity ultimately funding the service may all be different. Escobar-Kölle stresses that companies therefore need to understand the economic buyer, the source of the budget and the relevant reimbursement pathway long before they assume that clinical interest will translate into a sustainable business model. This is not a minor commercial detail: WHO Europe has highlighted reimbursement as a key factor in access to digital health technologies, while also highlighting considerable differences in reimbursement approaches across the countries studied. 

Europe is not one healthcare market 

A common mistake for healthtech companies expanding internationally is to treat Europe as a single healthcare market. They assume they can simply reproduce a successful model from one country to another. However, as Escobar-Kölle points out, reimbursement structures, procurement processes and clinical pathways can differ substantially between countries. So can decision-making dynamics, even where countries share broadly similar principles of universal healthcare. As a result, a solution that fits the UK system may struggle in Germany, France or the Nordics. There, it may need a different commercial model, implementation approach or route to adoption. International expansion in healthcare is therefore less about replication than adaptation. After all, entering a new country often means entering a different operational system altogether.

Initiatives such as the European Health Data Space may make cross-border data exchange more consistent, but they do not turn Europe into a single healthcare system. EU countries retain primary responsibility for organising and delivering health services and medical care, which means that financing structures, purchasing decisions and routes to adoption remain largely shaped at national level. For healthtech companies, this distinction matters because greater technical harmonisation does not automatically create commercial or operational harmonisation. A product may become easier to integrate across borders while still requiring a different implementation and market access strategy in each country. 

How should healthtech companies design pilots for scale? 

Digital health companies should therefore start planning for scale before they launch a pilot, not after it succeeds. Their evidence needs to show more than technical performance. It should also cover the value a technology delivers to the health and care system. Equally, it should address the practical side of deploying it. NICE’s Evidence Standards Framework reflects this broader view. When it assesses digital health technologies, it looks at performance and economic impact, but also at design and deployment. Thinking about these requirements early helps companies design pilots that test the conditions for real adoption. Otherwise, they risk producing encouraging results that they cannot translate into routine use.

What makes healthcare technology successful in everyday care? 

Ultimately, the solutions most likely to endure are not always the most technologically advanced. Instead, they are the ones that reduce friction within the system around them. Escobar-Kölle describes successful products as those that integrate naturally into existing workflows and fit the infrastructure already in place. Crucially, they reduce the burden on clinical teams rather than simply redistributing it. In that sense, the best technology can become almost invisible. It supports care without constantly demanding attention, extra steps or behaviour change from the people using it. For healthtech companies, this shifts the definition of success beyond technical sophistication alone. The real question is whether the product can become a sustainable part of everyday healthcare.

Want to hear more about what separates scalable healthtech solutions from promising experiments? Estefanía ‘Nia’ Escobar-Kölle, Innovation Manager at Future4Care, also discusses procurement, reimbursement, interoperability and international expansion. Listen to the full Beyond Delivery episode, “Why healthcare innovation fails after the pilot”, on Spotify, YouTube or Apple Podcasts.

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