Most AI conversations in healthcare still focus on clinical tools, ambient documentation, or physician productivity.

But one of the most important transformations is happening inside the administrative infrastructure of U.S. health insurance.

I had several interesting conversatiuons this week with colleagues working in the US health insurance industry. America’s largest insurers are now racing to rebuild claims processing, prior authorisation, and reimbursement workflows around AI driven systems and spending billions of dollars on this effort.

What is emerging is an arms race of sorts and signifies a broader shift in who controls the infrastructure layer of healthcare administration.

The implications extend far beyond efficiency.

AI is increasingly influencing:

• how quickly care is approved

• how providers interact with payers

• and how patients experience the healthcare system itself

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What is structurally changing

Three structural shifts are now becoming visible.

1. Claims administration is becoming software defined

Historically, claims processing relied on large administrative teams manually reviewing:

• billing codes

• medical necessity documentation

• fraud indicators

• and reimbursement eligibility

AI is now automating significant parts of these workflows in real time.

That changes healthcare administration from a labour intensive process into scalable digital infrastructure.

2. Scale advantages are compounding

UnitedHealth Group, through Optum, is moving aggressively to build AI enabled claims and reimbursement infrastructure.

Its advantage is not just technology.
It is access to enormous proprietary datasets across insurance, pharmacy, care delivery, and analytics.

This creates a powerful flywheel:

1. More claims processed

2. More data collected

3. Better AI optimisation

4. Faster automation

5. Lower administrative costs

In healthcare reimbursement, AI may strengthen incumbents rather than disrupt them.

3. Administrative experience is becoming competitive strategy

Insurers increasingly understand that provider friction and claims delays are no longer just operational problems.

They are market differentiators.

Faster approvals, reduced administrative burden, and simpler digital workflows may increasingly influence employer and consumer plan selection.

The front door to healthcare administration is becoming digital.

Second-order effects across the ecosystem

If this trend accelerates, several downstream shifts become likely.

Payer infrastructure becomes a major AI deployment layer

Some of the largest AI adoption opportunities in healthcare may emerge through administrative systems rather than clinical workflows.

Regulatory scrutiny increases

As AI becomes more involved in reimbursement decisions, pressure around transparency, bias, and automated denials will intensify.

Several U.S. states are already limiting the use of AI as the sole basis for denying care decisions.

Demand grows for healthcare infrastructure vendors

Insurers modernising claims operations will create opportunities for companies focused on:

• workflow automation

• interoperability

• utilisation management

• reimbursement analytics

• and AI governance

What this means for EU healthtech leaders

Many European founders still approach the U.S. market primarily through clinical innovation narratives.

But some of the largest commercial opportunities may increasingly sit inside the administrative infrastructure layer of American healthcare.

Three implications stand out.

Reimbursement alignment matters more than ever

Clinical value alone is rarely enough in the U.S. market.
Operational and payer alignment increasingly determine adoption.

Infrastructure integration becomes critical

As payer workflows become more automated, companies that cannot integrate cleanly into reimbursement systems may struggle commercially.

AI adoption in healthcare may scale through operations first

Administrative healthcare may ultimately become one of the largest AI deployment environments in the industry.

That shift is already underway.

Handrails for leaders

1. Understand where payer infrastructure investment is accelerating
   That is where urgency and budget are likely to concentrate.

2. Design products for interoperability early
   Closed workflows will become increasingly difficult to scale.

3. Build around operational outcomes, not just engagement metrics
   Efficiency and reimbursement impact are becoming strategic priorities.

4. Treat AI governance as a commercial issue, not just a regulatory one
   Trust and transparency will increasingly influence adoption.

Closing thought

Healthcare has spent years talking about AI through a clinical lens.

But one of the most important transformations may happen inside the administrative machinery of the system itself.

Claims processing is only the beginning.

The insurers moving fastest are no longer behaving like traditional payers.

They are becoming infrastructure companies.

And the organisations that control the reimbursement layer may ultimately control far more than claims administration alone.

Author

Thomas Hennessy is Senior Advisor at Santegic, supporting companies with U.S. market entry, regulatory strategy, and commercial growth in health technology and MedTech.

Isomorphic Labs, the Google DeepMind spinout founded in 2021, is attempting something unusually ambitious, to build a broad, scalable pipeline of medicines designed primarily by artificial intelligence and to push those drugs into human trials.

Why This Matters Now

For several years, AI drug discovery has existed in a comfortable middle ground. Promising enough to attract capital. Early enough to avoid accountability.

That period is ending.

Isomorphic Labs, the Google DeepMind spinout built around AlphaFold, has confirmed it is preparing its first AI-designed molecules for human trials. Oncology candidates are first. The broader pipeline follows.

This is not a capability announcement. It is a transition from computation to clinical reality. And that transition changes how the entire sector should be read.

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System Level Analysis

The pharmaceutical industry has operated on a largely unchanged logic for decades. Identify a target. Screen compounds. Iterate through failure. The average drug takes ten to fifteen years and over a billion dollars to reach approval. Attrition across that pipeline is brutal.

What Isomorphic is testing is a different assumption altogether: that molecular design can be moved upstream, into software, before any physical synthesis occurs.

AlphaFold solved protein structure prediction. IsoDDE, Isomorphic’s proprietary engine, extends that into binding prediction, target identification, and molecular optimisation. The claim is not just speed. It is precision by design. Molecules engineered for potency and selectivity before they reach the lab.

The structural significance of this goes beyond Isomorphic itself.

Pharma has historically protected its position through scale. Large compound libraries. Deep clinical infrastructure. Regulatory relationships built over decades. If AI can compress discovery timelines from years to months, and do so with higher initial precision, then the competitive advantage of incumbency starts to erode.

Eli Lilly and Novartis have both signed major collaboration agreements with Isomorphic. That is not philanthropy. It is incumbents acquiring optionality in a model they cannot yet build internally.

The partnerships also reveal something important about where value is likely to accrue. Isomorphic brings the design engine. Pharma brings the clinical infrastructure, regulatory expertise, and commercial capability. For now, these are complementary. Over time, as AI platforms mature, that relationship will be renegotiated.

Second Order Effects

If Isomorphic’s first oncology trials produce credible early data, several things follow quickly.

• Valuations across the AI drug discovery space will reprice. Not because every platform suddenly works, but because proof of concept in humans changes the risk calculus fundamentally. Capital that has been waiting on the sidelines will move.

• The pressure on traditional CROs and discovery-stage service providers will intensify. If computational design can reduce wet lab iteration, the volume of traditional preclinical work contracts. That is a structural shift in the services economy around pharma.

• Regulatory bodies will be forced to catch up. The FDA and EMA are already watching AI-generated molecules closely. But trial data from an AI-first pipeline will accelerate the policy conversation around what evidence standards look like when the design process is itself algorithmic. This will not resolve quickly, but it will become urgent.

Within large pharma, the internal debate between building and buying AI capability will sharpen. Partnerships like those with Lilly and Novartis buy time. They do not resolve the underlying strategic question.

EU Implications

European healthtech leaders tend to watch developments like this as observers. They should not.

The EU has real strengths in AI research, in biological sciences, and in regulatory sophistication. But the commercial translation infrastructure is weaker. The gap between a technically credible platform and a fundable, scalable business is wider in Europe than in the US, and that gap is particularly pronounced in capital-intensive sectors like drug development.

There is also a framing problem. Much of the European conversation about AI in healthcare focuses on diagnostics, clinical decision support, and administrative efficiency. These are legitimate markets. But they are not where the deepest structural change is occurring. That change is happening in the drug pipeline itself.

EU and UK companies with capabilities in protein biology, molecular simulation, or AI-assisted target identification should be asking whether their technology has applications that sit closer to Isomorphic’s model than to a conventional medtech or digital health frame. The commercial ceiling is substantially different.

On the regulatory side, European leaders should pay attention to how the EMA responds to AI-designed molecule trials. The EMA has historically been more cautious than the FDA on novel modalities. That caution may slow market entry, but it also creates an opportunity to engage early and help shape the framework rather than react to it.

Investors in the EU and UK should be recalibrating how they assess platform risk in this space. The question is no longer whether AI can contribute to drug discovery. The question is now whether specific platforms can demonstrate clinical validity. That is a different due diligence frame.

Handrails for Leaders

1. Do not treat this as a biotech story. Treat it as a signal about where the AI platform economy in healthcare is heading. The companies that win will be those that own defensible positions in the design and prediction layer of drug development, not just the delivery layer.

2. If you are building in adjacent spaces, test your positioning against the Isomorphic model. Are you accelerating a process that AI will eventually replace? Or are you building something that becomes more valuable as AI-driven pipelines scale?

3. Engage with regulatory bodies now, before trial data begins to reshape the policy environment. The window for proactive input is closing.

4. Watch the Lilly and Novartis partnerships closely. The deal structures, milestone payments, and platform access terms will reveal how large pharma intends to price AI capability over time. That intelligence matters for anyone positioning in this space.

5. Do not assume clinical success is certain. Isomorphic’s trials are a test, not a confirmation. Build scenario thinking around both outcomes.

Closing Thought

The question for the last decade has been whether AI could contribute meaningfully to drug discovery. That question is about to be answered in the clinic.

The more important question is what happens to the economics, the relationships, and the competitive structure of the entire pharmaceutical industry if the answer is yes.

That is the shift worth preparing for now.

Author

Thomas Hennessy is Senior Advisor at Santegic, supporting companies with U.S. market entry, regulatory strategy, and commercial growth in health technology and MedTech.

Reach out to Tom directly, or learn more at www.santegic.com.

For decades, women’s health has sat at the margins of healthcare systems, underfunded, under researched, and often treated as a niche.

Midi Health reaching a $1 billion valuation is not just a company milestone. It is a signal that capital is finally starting to take this category seriously.

This moment is worth paying attention to, not because of the headline number alone, but because of what it represents about where the market is heading.

What Midi Health actually does

Founded in 2021, Midi Health is a telehealth company focused on perimenopause and menopause care, an area that has historically lacked structured, accessible support.

The company provides virtual consultations with clinicians, hormonal and non hormonal treatment plans, and preventive midlife health services. Its care is covered by insurance across the United States.

A key part of its model is the use of AI to support delivery. Midi has built a proprietary chatbot trained on vetted medical data, alongside tools to train clinicians at scale and systems to automate workflows and operations.

This combination of clinical care and technology has enabled rapid growth, with more than 20,000 patients served per week, and positions the company as an AI enabled healthcare platform rather than a single condition provider.

Its latest $100 million Series D round has now taken it past the $1 billion mark.

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What is structurally changing

This milestone sits within a broader set of shifts that are reshaping how women’s health is understood and funded.

First, the category itself is being redefined. Women’s midlife health is no longer seen as a niche concern but as a large and historically underserved market with significant unmet need.

Second, demand is becoming more visible and more organised. Employers, insurers, and patients are increasingly recognising menopause care as an essential component of health benefits, not an optional extra.

Third, technology is enabling new delivery models. AI supported systems allow companies to scale care, train clinicians more efficiently, and standardise quality in ways that were previously difficult to achieve.

Finally, there is growing ambition to build platforms rather than point solutions. Companies like Midi are expanding beyond menopause into broader lifelong women’s health, reflecting a more integrated view of care.

A Moment of Validation for the Category

Seen through this lens, the $1 billion valuation is less about financial optics and more about validation.

It signals that investors now recognise the scale and importance of women’s health as a core part of the healthcare system.

It reflects confidence that new models of care delivery, particularly those combining clinical services with technology, can address longstanding gaps.

It also creates visibility. Milestones like this tend to draw more founders, more operators, and more capital into the space, accelerating innovation across the category.

For a segment that has historically struggled to attract attention, that shift matters.

Second order effects across the ecosystem

The impact of this kind of milestone extends beyond a single company.

More capital flowing into women’s health increases the likelihood of better products, more specialised services, and improved access for patients.

It encourages employers and insurers to take these services seriously, integrating them more deeply into benefit structures.

It also sets a precedent for how large this category can become. When one company reaches scale, it reshapes expectations for what others can achieve.

Over time, this can help build a more complete ecosystem, spanning prevention, treatment, and long term health management for women across different life stages.

What this means for healthtech leaders

For founders and operators, this is a signal to pay closer attention to where structural gaps still exist in healthcare.

Some of the most impactful opportunities are not in entirely new categories, but in areas that have been consistently overlooked.

For investors, it highlights the importance of recognising where historical underinvestment has created space for meaningful growth.

For healthcare leaders more broadly, it reinforces that addressing underserved populations is not just a social imperative, but increasingly a commercial one.

Closing thought

Midi Health’s rise to a $1 billion valuation should be seen for what it is.

A sign that women’s health is moving from the margins toward the centre of healthcare innovation and investment.

The real significance of this moment is not the number itself, but what it unlocks.

More attention, more capital, and more ambition directed toward a category that has needed all three for a long time.

If that momentum continues, this milestone may end up being less about one company, and more about a long overdue shift in the system.

Author

Thomas Hennessy is Senior Advisor at Santegic, supporting companies with U.S. market entry, regulatory strategy, and commercial growth in health technology and MedTech.

Reach out to Tom directly, or learn more at www.santegic.com.

For years, “digital health” has largely meant incremental change layered onto analogue systems.

This week, the Centers for Medicare & Medicaid Services (CMS) signalled something more fundamental.

A move toward a “digital-first” healthcare ecosystem, anchored by a Medicare App Library designed to connect patients directly with approved digital tools.

This is not just a new initiative.
It is a shift in how access to care is structured and who controls it.

What is structurally changing

Three structural shifts are now becoming visible:

1. The interface with the patient is moving upstream
Care is no longer anchored solely in provider settings.
CMS is enabling a model where patients engage through approved digital applications as a first touchpoint, not a downstream layer.

2. Distribution is being redefined at the payer level
By curating and legitimising an app ecosystem, CMS is creating a new distribution channel into Medicare populations.
This shifts influence away from individual providers toward payer-mediated access.

3. Interoperability is becoming a prerequisite, not a feature
A functional app ecosystem depends on shared data infrastructure.
This accelerates the move away from fragmented systems toward environments where integration is expected not optional.

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Second-order effects across the ecosystem

If this model scales, several downstream shifts become likely.

A payer-mediated app economy begins to form
Approval pathways, reimbursement alignment, and CMS endorsement will increasingly determine which digital health companies gain traction.

The front door to care becomes competitive
Access may shift from provider-controlled channels to digital interfaces, where engagement, UX, and outcomes drive utilisation.

Data becomes the central asset and tension point
Continuous engagement generates continuous data.
Ownership, consent, and governance will move from abstract concerns to operational realities.

Quality assurance becomes a system-level risk
Curated ecosystems introduce platform-level accountability questions:

• Who validates these tools?

• Who is responsible when outcomes fall short?

What this means for EU Healthtech leaders

For EU-based companies looking at the US, this is a directional signal not a one-off development.

Distribution strategy needs to evolve
Winning may increasingly depend on access to payer ecosystems, not just provider sales.

Reimbursement alignment becomes non-negotiable
Tools that do not map clearly to reimbursable pathways risk being excluded from these environments.

Regulatory and commercial strategy are converging
Approval is no longer just about compliance it is directly tied to market access and scale.

The underlying principle remains:

In the US, market entry is not about demand. It is about system fit.

Handrails for leaders

1. Map your pathway into CMS and payer ecosystems early
   This cannot be an afterthought.

2. Design for interoperability from day one
   Closed architectures will struggle in a platform-driven model.

3. Be explicit about data governance and trust
   This will become a core differentiator.

4. Focus on outcomes, not just engagement metrics
   Inclusion will depend on demonstrable impact.

Closing thought

Healthcare has talked about “going digital” for years.

What CMS is now signalling is something more fundamental:

Not digitising existing workflows
But redefining the front door to care.

The question is no longer whether this shift happens.

It’s who aligns early enough to benefit from it.

Author

Thomas Hennessy is Senior Advisor at Santegic, supporting companies with U.S. market entry, regulatory strategy, and commercial growth in health technology and MedTech.

Reach out to Tom directly or learn more at

A recent pilot in Utah is quietly crossing a line that, until now, still felt firmly human.

The state has launched a one-year programme allowing an AI chatbot from Legion Health to renew certain psychiatric prescriptions without direct physician oversight. The scope is deliberately narrow: only 15 lower-risk maintenance medications, only for existing prescriptions, and only for patients who meet tightly defined stability criteria. High-risk drugs, controlled substances and new diagnoses are excluded.

On the surface, that may look like a highly constrained use case.

But that is exactly how major change usually enters healthcare: constrained, validated, then scaled.

The real story here is not antidepressants.

It is that a U.S. state is now testing whether clinical authority itself can be delegated to AI.

What is structurally changing

Utah’s rationale is easy to understand.

The U.S. mental health system is under sustained pressure: provider shortages, long wait times and large populations without reliable access to routine care. State officials have positioned the pilot to reduce cost, speed access and free clinicians to focus on higher-risk cases. The programme also requires identity verification, symptom screening, escalation triggers and close human review of the first 1,250 requests.

In other words, this is not AI as documentation support.

This is not AI as workflow optimisation. This is AI being tested as a frontline clinical actor inside a live care pathway. That distinction matters.

For the last two years, much of the AI conversation in healthcare has centred on efficiency: ambient scribes, coding support, inbox management, prior authorisation and administrative burden reduction.

Utah is pointing somewhere more consequential.

The next phase is not just AI helping clinicians work faster. It is AI beginning to take on bounded clinical decisions itself.

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Second-order effects across the ecosystem

If this pilot demonstrates acceptable safety, improved access and lower cost, the implications extend well beyond psychiatry.

The likely next steps are not difficult to imagine:

• Routine prescription renewals in other specialties

• Chronic disease management for stable patients

• AI-led triage and intake in primary care

• Preventive monitoring workflows at scale

That is when the strategic conversation changes.

Because once AI is permitted to act not simply recommend the market is no longer just about productivity software.

It becomes about:

• Clinical accountability

• Regulatory thresholds

• Malpractice exposure

• Trust architecture

• Payer acceptance

• Workflow ownership inside care delivery

This is why the Utah pilot matters so much.

It is effectively a live regulatory and commercial test case for whether AI can move from the periphery of care into the clinical core.

What this means for EU healthtech leaders

For European founders, the instinct may be to view this as a uniquely American edge case.

That would be the wrong read.

The U.S. often serves as the earliest proving ground for new care models when access constraints and market incentives are strong enough. If this works, it will not remain a mental health story for long.

The important question is not whether you would build this exact product.

It is whether your company is positioned for a world in which AI is increasingly allowed to own bounded clinical workflows, not just support them.

That creates opportunity in several layers:

• Safety and escalation infrastructure

• Auditability and explainability

• Clinical governance tooling

• Risk stratification engines

• Outcome monitoring and compliance frameworks

In short: if AI is going to sit inside care delivery, the enabling infrastructure around it becomes strategically important.

Handrails for leaders

A few practical filters for how to think about this:

1. Do not reduce this to a mental health headline. This is a precedent story, not a category story.

2. Watch the workflow, not just the model. The real value will sit in governance, escalation and integration.

3. Regulation will follow outcomes. If safety and cost data are positive, expansion will come faster than many expect.

4. Trust will become a product feature. Clinical adoption will depend on transparency, audit trails and clear accountability.

5. Be careful with “AI clinician” narratives. The winners may be the infrastructure layers that make bounded autonomy safe, not the flashiest front-end brand.

Closing thought

This is not about whether AI can refill Prozac.

It is about whether healthcare is ready for a world where some clinical decisions are increasingly made without a clinician directly in the loop.

Utah has moved that debate from theory into practice.

If the pilot succeeds, this will not be remembered as a niche mental health experiment.

It will be remembered as one of the early moments when healthcare began to redraw the boundary between assistance and autonomy.

Author

Thomas Hennessy is Senior Advisor at Santegic, supporting companies with U.S. market entry, regulatory strategy, and commercial growth in health technology and MedTech.

Reach out to Tom directly or learn more at www.santegic.com.

Luxury healthcare is no longer a fringe category in the U.S.

From concierge primary care and private specialty clinics to full-body MRIs, high-frequency diagnostics and subscription-based longevity programmes, a premium tier of care is scaling quickly. What was once reserved for ultra-high-net-worth individuals is increasingly moving into mainstream consumer health and, in some cases, employer-sponsored offerings.

But the real signal here is not the rise of “VIP medicine”.

It is the emergence of a different care model entirely: one that is continuous rather than episodic, preventive rather than reactive, and designed around consumer expectations rather than institutional constraints.

For healthtech leaders, that distinction matters.

The most durable opportunity is unlikely to be in building the next luxury clinic. It is far more likely to be in building the infrastructure that makes this model scalable.

What is structurally changing

Luxury healthcare is succeeding because it addresses pain points the traditional system still struggles to solve: poor access, short transactional appointments, fragmented journeys and limited continuity.

In contrast, premium models are winning on experience and coordination:

• relationship-driven care

• integrated diagnostics and monitoring

• personalised treatment pathways

• seamless, consumer-grade delivery

That is not just a pricing shift. It is an operating model shift.

At a system level, we are watching healthcare move from episodic encounters to continuous management.

As with most healthcare transitions, two layers are emerging at once:

1. the visible layer : clinics, services, branded patient experiences

2. the invisible layer : data, coordination, workflows and infrastructure

The visible layer is getting the headlines. The invisible layer is where the real strategic value will sit.

Where the real opportunity is

If this category continues to grow, several infrastructure gaps become increasingly important.

First, care navigation.
Many premium models work because complexity is absorbed by human coordination. Patients are not left to navigate referrals, testing, follow-up and behaviour change on their own. That creates an opening for digital care orchestration platforms that can act as the “quarterback” across fragmented providers.

Second, longitudinal data aggregation.
Luxury care often generates rich streams of data across labs, imaging, wearables and sometimes genomics. But the data remains fragmented. The company that can aggregate, normalise and make that information clinically useful over time begins to own one of the most valuable assets in healthcare: the longitudinal patient record.

Third, provider enablement.
Many of these clinics are still operationally immature. They offer strong patient experience, but often rely on manual processes behind the scenes. Tools that standardise workflows, improve care coordination, track outcomes and support patient engagement may become the picks-and-shovels layer for the entire segment.

Second-order effects across the ecosystem

The important strategic point is this: what starts in premium healthcare rarely stays there.

Historically, higher-end segments often act as test environments for new delivery models. They prove demand, validate willingness to pay and allow care redesign before models move downstream.

If luxury healthcare proves that continuous, data-rich and preventive care drives better engagement or lower downstream cost, employers and payers will pay attention.

That creates a second wave of opportunity:

• employer benefit integration

• payer-facing analytics and ROI measurement

• hybrid human + AI service models that reduce delivery cost

• broader distribution into less affluent populations

In other words, the premium market may be the commercial proving ground, but the larger market will be built when the underlying model becomes more accessible.

What this means for EU healthtech leaders

For European founders, the temptation may be to view luxury healthcare as an interesting but niche U.S. phenomenon.

That would be a mistake.

The U.S. is often where new healthcare consumption behaviours become visible first, especially when they emerge outside traditional reimbursement structures. Luxury healthcare is one of those signals.

The lesson is not to copy the front-end clinic model.

The lesson is to ask: which capabilities being proven in premium care will eventually need to exist at scale across broader populations?

That is where the opportunity sits:

• infrastructure over facilities

• enablement over ownership

• scalable software over localised service delivery

Handrails for leaders

A few practical filters for founders evaluating this space:

1. Avoid confusing premium pricing with defensibility. High willingness to pay does not automatically create a durable moat.

2. Be cautious on clinic-heavy models. Standalone care delivery can be capital intensive and hard to scale.

3. Prioritise infrastructure that travels. The best businesses here will support multiple providers, not depend on owning one.

4. Watch for payer relevance early. If outcomes can eventually be measured and translated into cost avoidance, the market gets much larger.

5. Focus on repeatable operational value. Consumer experience matters, but workflow leverage and data utility are what make businesses durable.

Closing thought

Luxury healthcare is easy to dismiss as a market built for the top 1%.

That misses the point.

What we are really seeing is an early testing ground for the future of care: more personalised, more preventive, more continuous and far more consumer driven.

The visible brands may capture attention.

Author

Thomas Hennessy is Senior Advisor at Santegic, supporting companies with U.S. market entry, regulatory strategy, and commercial growth in health technology and MedTech.

Reach out to Tom directly or learn more at www.santegic.com.

A recent Washington Post piece captured a shift that has been building for years, but now feels increasingly difficult to ignore: technology is changing how people age.

For a long time, the assumption was that ageing eventually meant moving deeper into institutional care.

That assumption is weakening.

Across the U.S. and other mature health systems, more older adults are remaining at home for longer, supported by a growing layer of accessible technologies designed to preserve independence, reduce risk and extend functional living.

That is not simply a consumer trend.

It is an early signal that the home is becoming a more important site of care delivery, particularly for ageing populations.

For healthtech leaders, that matters because “age tech” may sound like a niche category. In reality, it increasingly looks like enabling infrastructure for a broader shift in how care will be delivered.

What is structurally changing

A new generation of tools is making ageing in place more viable at scale.

That includes remote monitoring, medication adherence systems, assistive devices, simplified communication tools and smart home supports designed to reduce friction for older adults and their caregivers.

Individually, many of these products can seem incremental.

Collectively, they point to something larger.

The care model is moving away from an assumption that ageing must be managed primarily through institutional settings, and towards a model where the home plays a more central role in safety, continuity and day-to-day support.

That changes the strategic importance of technologies that can support monitoring, communication, adherence and independence outside traditional clinical environments.

The real signal is adoption, not novelty

The most important shift here may not be the technology itself.

It is the growing evidence that older adults are increasingly open to using it.

If roughly two-thirds of older adults now say technology improves their lives, the old assumption that adoption is the main barrier becomes harder to defend.

That matters because the bottleneck is no longer simply whether older adults will engage.

The more important question is whether health systems, payers and technology companies are building products and workflows that can support ageing in place in a way that is scalable, intuitive and operationally useful.

In other words, demand is beginning to catch up with capability.

That is when markets tend to accelerate.

Second-order effects across the care ecosystem

If ageing in place becomes the default model for a larger share of the population, several second-order effects follow.

Care moves further into the home and becomes more continuous rather than episodic.

Families and informal caregivers become more digitally connected participants in the care model.

Technology becomes more important as a force multiplier in systems already facing workforce shortages and rising chronic disease burden.

And the line between consumer technology and care infrastructure becomes less clear, especially where tools begin to influence medication adherence, fall prevention, remote monitoring or functional independence.

That is where much of the long-term strategic value is likely to be created.

What this means for EU healthtech leaders

For companies in Ireland, the UK and wider Europe, this is not just a U.S. consumer signal.

European systems are under the same structural pressure: ageing populations, workforce constraints, chronic disease growth and rising urgency around community-based care.

That means ageing in place is becoming less of a lifestyle preference and more of a system necessity.

The strategic opportunity is not to think narrowly about “age tech” as a standalone category.

It is to ask what tools become essential when the home becomes a more permanent and important site of care for an older population.

That opens a much broader opportunity across remote monitoring, caregiver enablement, medication adherence, accessibility, home-based care coordination and digital supports that reduce unnecessary escalation into higher-cost settings.

Handrails for leaders

1. Treat ageing in place as a care model, not a product niche
   The opportunity is broader than devices. This is about the infrastructure required to support home-based independence at scale.

2. Design for the wider support system
   Older adults may be the end user, but caregivers, providers and payers are often part of the value chain.

3. Build for operational relevance
   The strongest companies in this space will not just create usable tools. They will create tools that fit into care delivery, workforce constraints and funding realities.

4. Assume adoption is moving faster than old stereotypes suggest
   The demand side may be stronger than many product teams still assume.

Closing thought

For years, ageing in place was treated as an aspiration.

Increasingly, it is becoming the default direction of travel.

That matters because when the home becomes a more permanent site of care, technology stops being a convenience layer.

It becomes part of the infrastructure that makes the model work.

The strategic question for healthtech leaders is no longer whether this shift is coming.

It is who is building for it early enough to matter.

Author

Thomas Hennessy is Senior Advisor at Santegic, supporting companies with U.S. market entry, regulatory strategy, and commercial growth in health technology and MedTech.

Reach out to Tom directly, or learn more at www.santegic.com.

One of the most important U.S. market entry questions a healthtech founder can ask is often asked far too late:

Will this product require FDA regulatory approval?

In practice, it is an early commercial readiness question.

If the answer is yes, the U.S. strategy can change quickly. Timelines extend. Capital needs increase. Product claims may need to be narrowed. Clinical evidence expectations can rise. In some cases, the difference between a relatively straightforward go-to-market plan and a much more complex one comes down to whether the company assessed regulatory exposure early enough.

That is why founders should not wait until after partner outreach, investor discussions or pilot planning to address it.

Regulatory uncertainty can distort market entry strategy

FDA exposure is often treated as downstream legal work.

That misses the point.

If your product is likely to require formal FDA engagement, that can materially affect:

• launch timing

• fundraising needs

• product positioning

• evidence strategy

• buyer conversations

• partnership structure

This is not just a compliance issue.

It is a market entry design issue.

A company can spend months refining a U.S. strategy, only to discover that the commercial assumptions were built on the wrong regulatory foundation.

There are often relatively low-cost ways to get early clarity

The good news is that companies do not always need to commit to a full regulatory programme to understand the likely path.

In many cases, there are ways to seek early FDA feedback on whether a product is likely to require formal review, and what type of pathway may be relevant.

That can help determine whether:

• the product may not require clearance at all

• a narrower pathway may apply

• a 510(k) premarket notification may be required

• a more extensive regulatory route may be needed

For many digital health and medtech companies, the 510(k) question is often one of the first practical tests. If that pathway is in play, it has real implications for timelines, documentation, testing and commercial sequencing.

The point is simple.

Founders need to know early whether they are moving into regulated territory, because once they are, the go-to-market plan may need to change.

The value is strategic, not just regulatory

The real value of early FDA feedback is not simply getting a yes or no answer.

It is understanding how that answer changes the commercial path.

If no formal approval is likely needed, a company may be able to move faster into pilots or commercial testing.

If a 510(k) or another pathway looks likely, leadership may need to revisit:

• timing of U.S. entry

• fundraising plans

• product claims

• evidence generation

• pilot structure

• resource allocation

That is why regulatory exposure should be treated as an early go/no-go input for U.S. expansion.

Founders need to be careful how they ask

This is where discipline matters.

Yes, there are relatively efficient ways to test regulatory exposure.

But how the question is framed matters enormously.

If the engagement is too broad or loosely scoped, companies can create unnecessary complexity. Regulators may respond to a broader interpretation of the product than the company intends to commercialise, which can introduce recommendations that are not essential but may increase cost, time and distraction if treated as mandatory.

That is why early engagement needs to be highly prescriptive. I strongly suggest that companies pursuing a 510(k) do not take this on themselves. I recommend bringing in a specialty advisory group like Santegic to help with drafting a clear and concise submission. This will help to ensure that there is no confusion or misinterpretation by the FDA on the need for regulatory approval. The FDA is not unlike any other organisation in situations where there is ambiguity in that it could take the more conservative and possibly more regulated approach in its response.

The intended use, product claims and scope of the question all need to be tightly defined.

Done well, early FDA engagement can be a very effective de-risking exercise.

Done poorly, it can create a more expensive problem than the one the company was trying to solve.

What this means for EU healthtech leaders

For founders in Ireland, the UK and wider Europe, the lesson is straightforward.

Do not build a U.S. strategy first and test regulatory assumptions later.

If there is a relatively efficient way to determine whether FDA review may be required, that work should happen early enough to shape the strategy, not late enough to derail it.

In U.S. healthcare, regulatory work is often not a later-stage execution issue.

It is one of the earliest strategic filters.

Handrails for leaders

1. Ask the FDA question early
   If regulatory exposure could materially alter timing, cost or product claims, test it before the U.S. plan hardens.

2. Know whether 510(k) risk is in play
   For many digital health and medtech products, this is one of the first practical questions that can materially affect market entry design.

3. Be highly prescriptive
   Intended use, claims and scope matter. Poor framing can create avoidable cost and confusion.

4. Translate feedback into commercial decisions immediately
   FDA feedback should shape timing, capital planning, evidence strategy and go-to-market sequencing.

Closing thought

One of the most expensive mistakes in U.S. healthtech expansion is not always choosing the wrong regulatory path.

Often, it is waiting too long to test whether a regulatory path exists at all.

If there is a quick and relatively low-cost way to determine whether FDA review may be required, including whether a 510(k) pathway could come into play, that is not a side exercise.

It is one of the earliest and most valuable strategic tests a company can run.

Because strong U.S. market entry plans are built on early clarity, not late surprises.

Author

Thomas Hennessy is Senior Advisor at Santegic, supporting companies with U.S. market entry, regulatory strategy, and commercial growth in health technology and MedTech.

Reach out to Tom directly, or learn more at www.santegic.com.

The CMS 2026 Physician Fee Schedule Final Rule offers another signal that the U.S. healthcare system continues to accelerate its shift toward value based and risk-based care.

For health technology companies looking to expand their footprint in the United States, this policy movement matters more than it may appear at first glance.

The rule moves Medicare further toward performance-based reimbursement, clinician level accountability and integrated care delivery. Providers that demonstrate improved outcomes and more efficient care delivery are increasingly rewarded within the reimbursement framework.

Several policy signals are clear.

Greater emphasis is being placed on value and risk sharing rather than traditional fee for service billing.

Providers participating in alternative payment models are seeing stronger incentives tied to performance and cost management.

At the same time, CMS continues to expand its focus on chronic care management, prevention and care coordination within the Medicare Physician Fee Schedule, which governs payment for services delivered by physicians and other clinicians.

These adjustments reinforce a broader policy direction. Medicare reimbursement is increasingly structured around measurable outcomes and population level performance.

System Level Analysis

During the better part of a decade that I worked at CMS I came to realize that the Physician Fee Schedule is one of the most influential policy levers within the U.S. healthcare system.

Each annual rule does more than adjust reimbursement levels. It signals how CMS expects care delivery to evolve across the provider ecosystem.

The 2026 rule continues a multi year transition toward integrated care delivery models where providers are accountable for quality, cost and patient outcomes.

In this environment, physicians and health systems must increasingly manage populations rather than isolated clinical encounters. Performance measurement, care coordination and cost management become central operational capabilities rather than peripheral activities.

Reimbursement design therefore begins to shape technology adoption.

When payment rewards outcome improvement and cost control, providers look for infrastructure that enables those results at scale.

Second Order Effects Across the Ecosystem

Policy changes in Medicare reimbursement rarely affect only providers. They cascade across the broader healthcare ecosystem.

• As reimbursement shifts toward risk based arrangements, provider organisations require tools that support population health management, real time patient monitoring and continuous care coordination.

• Digital infrastructure becomes essential for tracking outcomes, identifying risk earlier and managing patients outside traditional care settings.

• Technology adoption increasingly follows reimbursement incentives.

• When providers operate under value-based contracts, they require systems capable of measuring performance across programmes, coordinating multidisciplinary care teams and reducing avoidable hospitalisations.

The commercial case for digital health infrastructure therefore strengthens as reimbursement reform accelerates.

Implications for EU Healthtech Companies

For European healthtech companies evaluating U.S. expansion, the Physician Fee Schedule is not simply a regulatory update.

It is a signal about how provider demand will evolve.

• Providers operating within value-based contracts increasingly need technology that enables population health management, outcome measurement and continuous patient engagement.

• Solutions focused on chronic disease management, remote monitoring, data analytics and care coordination align directly with the operational challenges created by these payment models.

For EU innovators, the strategic question is not whether value-based care will expand.

It is how well their products help providers succeed within risk bearing environments.

Companies that design their solutions around measurable performance improvement will be better positioned as Medicare reimbursement continues to evolve.

Handrails for Leaders

1. Map your solution against value-based care requirements within Medicare programmes.

2. Demonstrate measurable impact on cost, outcomes and patient engagement.

3. Design products that support population health management and longitudinal care.

4. Prepare evidence showing how technology enables providers to succeed within risk bearing contracts.

5. Engage early with provider organisations participating in alternative payment models.

Closing Thought

The 2026 Physician Fee Schedule reinforces a consistent policy trajectory within U.S. healthcare.

Reimbursement is gradually shifting toward models that reward outcomes, coordination and long-term population health performance.

As that transition continues, technology capable of helping providers manage risk, measure results and deliver more integrated care will move from optional infrastructure to operational necessity.

For healthtech innovators, the opportunity lies in helping providers succeed in that environment.

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Author

Thomas Hennessy is Senior Advisor at Santegic, supporting companies with U.S. market entry, regulatory strategy, and commercial growth in health technology and MedTech.

Reach out to Tom directly or learn more at www.santegic.com.

The current administration’s expanded Medicaid work requirements are set to take effect later this year.

Under the new rules, certain adults aged 19 to 64 will be required to complete at least 80 hours per month of work, education or community engagement activities to maintain eligibility.

The stated objective is to reduce federal spending.

The operational consequence is far more complex.

States will need to modernise ageing enrolment and eligibility systems, build new reporting and verification workflows, and expand administrative staffing to track compliance. Even with federal funding support, projected implementation costs nationally are substantial.

This is not only a policy adjustment. It is a stress test of Medicaid’s digital infrastructure.

System-Level Analysis

Work requirements shift Medicaid from primarily income-based eligibility verification toward continuous activity-based compliance monitoring.

That requires a fundamentally different operating model.

Much of the country’s Medicaid infrastructure was not designed for real-time eligibility verification, cross-agency data sharing or beneficiary-friendly digital reporting. Many systems remain fragmented across workforce agencies, education departments and Medicaid administrators.

To implement these requirements, states must now coordinate:

• Data from employment systems

• Education and training programme participation

• Community engagement verification

• Ongoing beneficiary reporting

This introduces new workflow complexity, identity management challenges and compliance oversight requirements.

The policy debate focuses on coverage and fiscal impact. The structural issue is administrative capability.

Second-Order Effects

When eligibility criteria become dynamic rather than static, technology moves from support function to core enforcement mechanism.

States will need:

• Automated tracking and verification tools

• Secure cross-agency data integration

• Beneficiary-facing digital reporting platforms

• Compliance analytics for oversight and audit readiness

Manual processing at scale becomes financially and politically unsustainable.

There is also reputational exposure. Poorly designed systems risk coverage gaps caused by paperwork failure rather than true ineligibility. That creates political and legal risk for states.

Operational fragility becomes visible when policy tightens.

EU Implications

For European healthtech and GovTech companies, this is not simply a U.S. welfare policy story. It is an infrastructure modernisation opportunity within one of the largest public insurance systems in the world.

Clear demand areas are emerging:

• Modern eligibility and enrolment platforms

• Automated compliance tracking and verification systems

• Secure data integration across workforce, education and Medicaid systems

• Beneficiary-facing digital tools that reduce administrative burden

• Analytics and reporting solutions for state agencies

EU firms with experience in public sector digital transformation, identity systems or secure data exchange may find receptive state partners.

However, success will depend on navigating procurement cycles, federal funding structures and political sensitivity around programme design.

Handrails for Leaders

1. Map which states are advancing implementation timelines and budget allocations.

2. Align product capabilities with federal compliance and reporting requirements.

3. Prioritise interoperability and secure data exchange architecture.

4. Design beneficiary interfaces that reduce administrative burden and minimise inadvertent coverage loss.

5. Prepare for long public procurement cycles and multi-stakeholder approval processes.

   Closing Thought

Expanded work requirements are framed as a fiscal measure.

In practice, they are forcing a digital reckoning inside Medicaid.

States cannot enforce activity-based eligibility with legacy infrastructure built for static income verification.

As Medicaid policy evolves, technology will determine whether implementation leads to administrative efficiency or systemic strain.

For companies operating at the intersection of healthtech and public sector infrastructure, this moment is less about ideology and more about capability.

Author

Thomas Hennessy is Senior Advisor at Santegic, supporting companies with U.S. market entry, regulatory strategy, and commercial growth in health technology and MedTech.

Reach out to Tom directly or learn more at www.santegic.com.

On 20 February 2026, the U.S. Supreme Court struck down the bulk of the Trump administration’s emergency tariffs imposed under the International Emergency Economic Powers Act. The Court ruled that the President lacked statutory authority to levy broad tariffs without clear congressional authorisation.

At first glance, this looks like relief.

For health technology and medical device companies, however, the ruling does not remove trade risk. It changes the structure of it.

Healthtech operates on long investment cycles, global supply chains and capital-intensive manufacturing. Trade policy is not peripheral for this sector. It is a cost input.

The invalidated tariffs had affected a wide range of imported medical devices and components. Industry groups warned that they were increasing costs for hospitals and complicating capital planning.

The Court removed the legal basis for those emergency measures. It did not remove the political appetite for tariff tools.

That distinction now sits at the centre of strategic planning.

What Is Structurally Changing

The ruling narrows one executive pathway. It does not narrow the broader policy objective of using trade instruments as leverage.

Three implications stand out.

1. Refund Uncertainty

The Court did not address whether companies will receive refunds for tariffs already paid.

This creates a practical dilemma.

Should companies book receivables?
Should prior duties be treated as sunk cost?
Should firms prepare for extended litigation?

In capital-intensive sectors such as medical devices, refund ambiguity affects margins, pricing assumptions and cash flow planning.

The relief is legal. The accounting remains unclear.

2. Policy Reconfiguration

Within hours of the ruling, the administration signalled alternative tariff strategies, including potential use of other trade statutes such as the Trade Expansion Act of 1962.

The executive route was blocked. The strategic objective was not.

Healthtech executives must now plan for tariff exposure through different legal mechanisms rather than assume the threat has disappeared.

3. Investment Friction

Economists consistently observe that uncertainty suppresses investment more effectively than tariffs themselves.

In healthtech, that translates into:

Delayed capital equipment decisions
Hesitation on R&D expansion
Cautious manufacturing siting decisions
Slower cross-border supplier commitments

The ruling reduced one variable. It increased volatility around the others.

Second-Order Effects Across the Ecosystem

Trade volatility changes behaviour before it changes law.

Boards incorporate political risk premiums into capital allocation.
Procurement teams seek contractual flexibility.
Investors adjust discount rates for cross-border exposure.

In complex manufacturing environments, unpredictability compounds across supply chains. Components cross borders multiple times. Each crossing now carries potential policy exposure.

Volatility itself becomes operational friction.

Implications for EU Healthtech Companies

For EU healthtech firms selling into the U.S., this is a commercial risk story with structural implications.

European manufacturers are deeply integrated into U.S. supply chains. Components, sub-assemblies and finished devices frequently move across jurisdictions during production.

Three risks stand out.

• Exposure to new tariff vehicles under alternative U.S. trade statutes.
  Supply contract hesitation from U.S. buyers wary of future cost swings.
  Strategic pressure to localise manufacturing within the U.S. to mitigate political risk.

• The absence of a stable tariff framework complicates bilateral planning and regulatory alignment discussions.

• For EU leaders, the central question is durability. How permanent is U.S. trade unpredictability as a structural feature of the market?

Handrails for EU Leaders

1. Model tariff volatility rather than tariff removal. Treat this ruling as a regime shifts in trade governance.

2. Stress-test U.S. exposure. Reassess pricing sensitivity, margin buffers and supply chain concentration.

3. Revisit localisation strategy. Manufacturing footprint decisions now carry political risk premiums.

4. Engage policy networks early. Trade measures are becoming sectoral tools, and healthtech must remain represented.

5. Avoid overcorrecting. Persistent uncertainty does not automatically equal structural decoupling.

Closing Thought

The Supreme Court’s ruling marked a constitutional check on executive trade authority.

For healthtech, it did not restore stability. It reshaped the risk environment.

Emergency tariffs may have been curtailed. Trade manoeuvring remains.

In capital-intensive industries, volatility carries its own cost. That cost now needs to be embedded into strategy, investment planning and cross-border partnerships.

Author

Thomas Hennessy is Senior Advisor at Santegic, supporting companies with U.S. market entry, regulatory strategy, and commercial growth in health technology and MedTech.

Reach out to Tom directly, or learn more at www.santegic.com.

When I began my career at the Centres for Medicare and Medicaid Services (CMS), I worked in the Division of State Demonstrations and Waivers within Medicaid. At the time, only a handful of us reviewed and approved state proposals to test alternative delivery and payment approaches. I was responsible for the New England region and at the time Massachusetts was widely seen as the most progressive state in this nation, and many of its reforms later informed elements of the Affordable Care Act.

What has changed in recent years is scale and ambition.

Section 1115A authority, established originally under the Social Security Act (SSA), has evolved into the primary mechanism through which CMS tests structural reform across Medicare and Medicaid. Rather than isolated pilots, these demonstrations increasingly function as precursors to national policy direction.

For founders, operators and investors, this matters because innovation in U.S. healthcare is increasingly routed through these models.

What is structurally changing

Section 1115A provides CMS with flexibility to test alternative payment and delivery models outside traditional Medicare and Medicaid constraints. This authority now underpins many of the most consequential experiments in the system.

Several themes are emerging.

Acceleration of value-based care

Demonstration models increasingly reward quality, outcomes and total cost performance rather than service volume. Hospitals and physician groups operating under these models face stronger incentives to coordinate care, manage risk and invest in preventive infrastructure.

Integration of digital and remote technologies

Remote monitoring, artificial intelligence supported diagnostics and telehealth solutions are being embedded into model design. Technology adoption is therefore shaped by reimbursement structure rather than standalone enthusiasm.

Pharmaceutical pricing experimentation

Models such as GENEROUS, GLOBE and GUARD explore reimbursement approaches tied to value and, in some cases, international pricing benchmarks. These pilots signal ongoing willingness within CMS to test new approaches to drug pricing and outcomes-based payment.

Equity metrics embedded into reform

Many demonstrations incorporate explicit equity measures. Providers participating in these models must address disparities in access and outcomes, influencing care design and community engagement strategies.

The cumulative effect is that 1115A demonstrations now shape the commercial environment for providers, payers and technology partners.

Second-order effects across the ecosystem

When CMS pilots a model under 1115A authority, it sends a market signal.

• Investors adjust assumptions about future reimbursement norms. Health systems prioritise capabilities aligned with demonstration metrics. Digital health companies orient product design toward measurable cost and quality outcomes.

• Because successful demonstrations can be expanded nationally, participation becomes strategically valuable. Organisations involved early often gain operational learning, data assets and credibility that compound over time.

• For international companies, these waivers create structured entry points. Demonstration models offer defined parameters for collaboration, measurable outcome targets and a pathway to scale if results are validated.

This shifts innovation from abstract policy ambition to operational testing within live reimbursement environments.

Implications for EU healthtech companies

European founders often underestimate how central CMS demonstrations are to U.S. market evolution.

If your model supports chronic disease management, risk stratification, remote monitoring or pharmaceutical value assessment, it is likely to intersect with a demonstration framework.

• EU startups and scale-ups

Commercial success increasingly depends on alignment with reimbursement reform.
Handrail: Map your solution against active and upcoming CMS models and identify where your outcomes contribute to cost or quality metrics.

• EU digital health and chronic care companies

Technology adoption follows payment reform.
Handrail: Design your U.S. strategy around measurable performance improvement within defined risk models.

• EU pharmaceutical and MedTech innovators

Pricing and reimbursement experimentation may alter value expectations.
Handrail: Prepare evidence packages that demonstrate real-world outcomes aligned with CMS model objectives.

• EU investors and boards

Demonstration authority signals directional policy change.
Handrail: Assess portfolio exposure to emerging reimbursement structures rather than assuming fee-for-service stability.

Handrails for leaders

1. Understand which 1115A models are active in your target markets.

2. Align product metrics with CMS performance benchmarks.

3. Engage early with provider groups participating in demonstrations.

4. Prepare for national scaling if a model expands.

5. Build equity and access considerations into programme design from the outset.

Closing Thought

Section 1115A authority has evolved into a central lever of U.S. healthcare transformation. Through demonstration models, CMS is shaping payment incentives, digital integration, pharmaceutical pricing experimentation and equity priorities.

For innovators, these waivers function as structured laboratories for reform. The organisations that align early with these models will influence how scalable, patient-centred care is defined in the next phase of U.S. healthcare evolution.

Author

Thomas Hennessy is Senior Advisor at Santegic, supporting companies with U.S. market entry, regulatory strategy, and commercial growth in health technology and MedTech.

Reach out to Tom directly, or learn more at www.santegic.com.

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In early January I discussed in one of my weekly updates that it appeared that the subsidies for certain individuals on the exchanges would be eliminated. This is a follow up to that update as earlier this week . The Centres for Medicare and Medicaid Services has proposed a set of changes to the Affordable Care Act marketplaces that would alter how plans are structured, marketed, and regulated.

These proposals go beyond technical rule making. They affect how risk is distributed across enrolees, how insurers design products, and how intermediaries operate within the exchange ecosystem.

For healthtech companies, insurers, brokers, and EU firms engaging with the U.S. market, this is a signal that marketplace stability and structure remain fluid heading into 2026.

What is actually changing

Several elements of the proposal stand out:

Expanded access to catastrophic plans
CMS is proposing to broaden eligibility for catastrophic coverage, including for individuals over age 30 who do not qualify for subsidies under hardship criteria. Catastrophic plans carry lower premiums and significantly higher deductibles.

This increases the availability of lower upfront cost coverage, particularly for healthier or price sensitive individuals.

Removal of standardised plan design requirements
The proposal would repeal requirements that insurers offer standardised plan designs and would remove limits on nonstandard offerings. Carriers would gain greater flexibility in structuring benefits, cost sharing, and plan configurations.

Stronger market integrity controls
CMS is proposing tighter broker marketing oversight and stronger income verification during special enrolment periods. The stated goal is to reduce improper enrolments and fraud.

Taken together, these changes shift emphasis toward flexibility for insurers and stronger guardrails around enrolment integrity.

System level implications

• Plan standardisation under the ACA has functioned as a consumer navigation tool and as a market stabiliser. Removing it increases product design freedom but also increases variation.

• Greater catastrophic plan access may lower entry price points but could alter risk pool composition if healthier individuals migrate toward high-deductible options.

• Stricter verification and broker oversight may improve program integrity, but they may also slow enrolment processes and increase administrative friction.

• The direction of travel suggests a marketplace that is more flexible, more segmented, and more tightly monitored.

Second order effects

• If catastrophic enrolment expands meaningfully, the exchanges could see greater separation between lower risk and higher risk populations. That has implications for premium levels and insurer pricing strategies.

• Increased product variation may complicate consumer comparison, which historically affects take up and switching behaviour.

• More aggressive income verification may reduce improper enrolment, but it may also introduce delays that influence coverage continuity.

• For healthtech vendors tied to exchange populations, these shifts affect addressable population stability, member churn patterns, and payer budget predictability.

Implications for EU healthtech companies

• EU firms engaging the U.S. individual market often underestimate how regulatory adjustments cascade through enrolment, risk pools, and payer behaviour.

• If marketplace risk segmentation increases, payers may tighten utilisation management and ROI scrutiny.

• If enrolment processes become more stringent, sales cycles and partnership timelines may lengthen.

• Companies whose models depend heavily on subsidised exchange stability should reassess exposure scenarios under greater plan variability and shifting member composition.

Handrails for leaders

1. Map your exposure to exchange driven populations and revenue streams.

2. Model how risk pool shifts could affect payer behaviour and utilisation management priorities.

3. Engage early in comment periods when proposals materially affect your operating assumptions.

4. Design products and engagement strategies that remain viable under greater enrolment friction and member churn.

Closing thought

ACA marketplaces have always balanced access, affordability, and stability. These proposed CMS changes recalibrate that balance toward flexibility and tighter oversight.

For healthtech leaders, the lesson is to track not only policy headlines but structural signals. When plan design rules and enrolment controls shift, downstream demand patterns and payer incentives often shift with them.

Author

Thomas Hennessy is Senior Advisor at Santegic, supporting companies with U.S. market entry, regulatory strategy, and commercial growth in health technology and MedTech.

Reach out to Tom directly, or learn more at www.santegic.com.

In late 2025, one of the most consequential data security incidents in recent U.S. healthtech history came to light. TriZetto Provider Solutions, a Cognizant-owned company providing eligibility and revenue cycle services to healthcare organisations nationwide, disclosed a breach involving sensitive personal and protected health information held on behalf of its clients.

The scale of the incident matters, but the timing matters more. The breach occurred against a backdrop of rising regulatory scrutiny, expanding state privacy regimes, and growing dependence on third-party health IT vendors for core operational functions. What the TriZetto case exposes is not a single failure, but a set of systemic vulnerabilities that extend well beyond one company.

What is actually changing

The breach was discovered in October 2025, but forensic analysis later revealed that unauthorised access had likely been ongoing since November 2024. An attacker accessed data through a partner-facing web portal and remained undetected for close to a year.

The compromised data included patient names, dates of birth, Social Security numbers, insurance member identifiers, plan details, and eligibility-related protected health information. Subsequent disclosures by affected healthcare organisations suggest that more than 700,000 individuals may ultimately be impacted.

The most significant issue here is not the method of entry, but the duration. Prolonged undetected access points to limitations in how healthtech vendors monitorinternal systems, third-party portals, and anomalous behaviour across complex client environments. Traditional security controls were present, but visibility and response lagged behind the threat.

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Second-order effects and trade-offs

Extended dwell time materially increases downstream risk. Even without direct access to financial accounts, the combination of identity data and insurance information creates long-term exposure to identity theft, insurance fraud, and targeted social engineering. The value of this data persists, meaning affected individuals may face risk years after the initial breach.

Legal and regulatory consequences are already following. TriZetto and Cognizant face multiple class-action lawsuits alleging failure to safeguard data and delays in notification. More broadly, regulators are signalling heightened scrutiny of business associates under HIPAA, reinforcing that responsibility for security does not stop at the covered entity boundary.

For healthcare organisations, the incident sharpens an uncomfortable trade-off. Outsourcing core administrative and data-intensive functions delivers scale and efficiency, but also concentrates risk. When a single vendor sits upstream of thousands of providers, failures propagate quickly and widely.

Broader implications for the healthtech ecosystem

The TriZetto breach functions as a stress test for how the sector manages third-party risk.

• Vendor risk management practices are being exposed as uneven and, in many cases, outdated. Periodic assessments and contractual assurances are proving insufficient for vendors that operate continuously inside payer and provider workflows.

• Detection and monitoring capabilities are also under pressure. Static defences and scheduled audits struggle to identify slow, persistent intrusion. Behavioural analytics, continuous monitoring, and shared visibility across vendor ecosystems are becoming baseline expectations rather than advanced features.

• Trust and transparency are increasingly central. Timely disclosure and clear communication shape how patients, partners, and regulators respond. Delays or ambiguity compound reputational damage and regulatory exposure, even when remediation eventually occurs.

Implications for EU healthtech companies

• For EU companies operating in or entering the U.S. market, the TriZetto incident reinforces how security posture influences commercial credibility.

• U.S. buyers are paying closer attention to how vendors monitor access, manage third-party integrations, and detect anomalous behaviour over time. Security governance is becoming a proxy for operational maturity.

• EU firms with strong internal controls, audit discipline, and privacy-by-design practices may find this environment favourable, provided they can demonstrate continuous monitoring rather than static compliance. Conversely, companies relying on inherited infrastructure or opaque partner ecosystems may face longer sales cycles and deeper due diligence.

Handrails for leaders

1. Reassess third-party exposure.
   Map where sensitive data flows through vendors, portals, and subcontractors, and identify points where monitoring responsibility is unclear.

2. Strengthen detection, not just defences.
   Invest in tools and processes that surface abnormal behaviour early, particularly across partner-facing systems and long-lived credentials.

3. Clarify incident response expectations.
   Ensure notification timelines, escalation paths, and forensic access are contractually explicit with vendors.

4. Treat security as operational infrastructure.
   Cybersecurity in healthtech now directly affects patient trust, regulatory standing, and enterprise value.

Closing thought

The TriZetto breach is not just a cautionary tale about cybersecurity hygiene. It is a signal that scale, interconnectedness, and prolonged data retention have outpaced how the healthtech ecosystem detects and manages risk.

As digital health becomes more deeply embedded in care delivery and administration, data stewardship increasingly shapes trust in the system itself. Companies that invest early in visibility, governance, and accountability will be better positioned to operate — and scale — in an environment where security failures are no longer contained, forgiven, or abstract.

Author

Thomas Hennessy is Senior Advisor at Santegic, supporting companies with U.S. market entry, regulatory strategy, and commercial growth in health technology and MedTech.

Reach out to Tom directly, or learn more at www.santegic.com.

For much of the past decade, artificial intelligence in healthcare has been discussed as an emerging capability. Pilot projects, proofs of concept, and vendor-led innovation shaped much of the early conversation.

That phase is now giving way to a more institutional approach.

The U.S. Department of Health and Human Services has made AI a formal strategic priority across federal health agencies. This reflects a shift toward embedding AI into the operational fabric of organisations that shape regulation, reimbursement, public health, and care delivery at national scale.

When institutions of this size and influence move in this direction, it signals a change in how AI is expected to function within the healthcare system.

What the U.S. Department of Health and Human Services is doing

The new strategy focuses on enabling adoption rather than prescribing specific technical implementations.

Key areas of focus include:

• Modernising internal systems across agencies such as CMS, FDA, and CDC

• Using AI to analyse large and complex datasets more efficiently

• Reducing administrative burden across public health programmes

• Supporting research and operational decision-making at scale

The emphasis is on institutional readiness. AI is being positioned as a supporting capability within government healthcare functions, rather than as a standalone innovation programme.

Why this represents a structural shift

Federal health agencies influence how healthcare operates across the United States. Their internal practices shape expectations around:

• Evidence and reporting standards

• Administrative processes

• Procurement and partnership models

• Data governance and oversight

As AI becomes part of how these institutions operate, it increasingly shapes the assumptions and requirements faced by the wider ecosystem.

Over time, this influences how healthtech products are evaluated, integrated, and scaled.

How governance shapes this transition

The strategy reflects an effort to balance innovation with governance.

Health data is sensitive, public institutions are accountable, and decisions informed by AI carry legal and ethical implications. As a result, transparency, oversight, and auditability are treated as foundational requirements rather than secondary considerations.

This balance will play a central role in determining how quickly AI becomes trusted and embedded across public healthcare infrastructure.

Second-order effects worth paying attention to

Several downstream effects are likely to emerge.

First, standards and documentation will rise in importance as AI is operationalised within government systems.

Second, administrative and operational use cases are likely to lead adoption, particularly where AI can reduce friction and improve efficiency at scale.

Third, public–private collaboration will increase alongside scrutiny, with higher expectations placed on vendors engaging with federal agencies.

These dynamics favour organisations that treat AI as part of a broader operating system rather than as an isolated capability.

What this means for EU companies

EU startups and scale-ups

Federal adoption raises expectations around credibility and readiness.

Handrail: Prepare for U.S. buyers who expect strong AI governance, documentation, and operational maturity.

EU digital health and MedTech vendors

AI embedded in infrastructure influences procurement priorities.

Handrail: Position AI as an enabler of efficiency, reliability, and compliance.

EU investors and boards

Government posture shapes market expectations.

Handrail: Assess whether AI strategies are designed for regulated, large-scale environments.

What leaders should hold onto

As AI becomes embedded in healthcare policy and administration, success will increasingly depend on institutional fit.

Leaders should consider:

• Where AI genuinely reduces friction at scale

• How transparent and governable their systems are

• Whether solutions are designed for pilots or long-term integration

These considerations will shape which technologies endure as adoption deepens.

Closing thought

The U.S. Department of Health and Human Services’ AI strategy marks a transition point. Artificial intelligence is moving from experimentation toward infrastructure within U.S. healthcare.

As federal agencies incorporate AI into how they operate, expectations across the healthtech ecosystem will continue to evolve. Organisations that align early with these institutional realities will be better positioned as this next phase unfolds.

Author

Thomas Hennessy is Senior Advisor at Santegic, supporting companies with U.S. market entry, regulatory strategy, and commercial growth in health technology and MedTech.

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Why this space exists

Most people working in health technology do not struggle to keep up with the news. The harder part is working out what actually matters once the headlines fade.

Policy changes, regulatory updates, funding cycles, and technology shifts are constant. Some are meaningful. Others are noise. Many sit somewhere in between and only reveal their importance months later, once they interact with real systems and incentives.

Through my work with healthtech and MedTech companies across Europe and the U.S., I spend a lot of time in those in-between spaces. I help teams translate system-level change into product, commercial, and strategic decisions. That translation work is what this Substack is for.

I am starting it now because the gap between announcement and execution is growing. Health systems are under pressure, expectations on technology are rising, and cross-border complexity is becoming the norm rather than the exception. Clear thinking matters more than speed.

What kind of space this will be

This will be a place for considered analysis rather than commentary in the moment.

Most posts will start with a real signal, such as a regulatory shift, a policy direction, or a market movement, and work through what it changes in practice. The focus will be on consequences, trade-offs, and the decisions leaders may need to make as a result.

Content here will be grounded rather than speculative, pragmatic rather than promotional, and written with founders, operators, and investors in mind.

The aim is that if you spend a few minutes here, you leave with something clearer than when you arrived.

What you can expect

How often

I plan to publish one main piece each week, occasionally every two weeks when a topic benefits from more distance or depth.

How it is structured

Each article will follow a familiar rhythm:

• why a signal matters

• what is actually changing

• implications across U.S. and European health systems

• practical handrails for leaders

The structure will stay consistent so the thinking is easy to follow, even as topics change.

Who it is for

This is written for people building, running, backing, or advising health technology companies, particularly those operating across different healthcare systems.

Subscriptions

This publication is free. The intent is to make the thinking accessible and useful. If additional formats ever make sense, they will be optional and clearly defined.

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A note on perspective

My views are shaped by my advisory work at Santegic, where I support companies navigating U.S. market entry, regulatory strategy, and commercial growth. The insights here come from real conversations and real constraints rather than theory.

This Substack is not a company channel. It is a place to share thinking that sits around the work, including patterns I am seeing, questions that keep coming up, and signals that deserve closer attention.

Closing

This space will evolve over time. Some posts will be tightly focused, others more reflective. What will stay consistent is an effort to be clear, honest about uncertainty, and practical about what comes next.

If that is useful to you, I am glad you are reading.

“In a time of turbulence and change, it is more true than ever that knowledge is power” - John F. Kennedy

Tom Hennesy

Health insurance affordability in the United States is often framed as a policy issue. In practice, it functions as a market input.

In an earlier piece, I outlined how enhanced exchange subsidies quietly supported coverage stability, broadened risk pools, and gave payers and providers greater confidence in enrolment assumptions. With those subsidies scheduled to expire at the end of 2025 unless extended, the effects are no longer theoretical. Early changes in premiums and enrolment behaviour are already influencing how payers and health systems plan, spend, and buy.

With those enhanced subsidies scheduled to expire at the end of 2025, unless extended by Congress, the effects are no longer theoretical. Early changes in premiums and enrolment behaviour are already influencing how payers and health systems plan, spend, and buy.

For healthtech companies, this matters because coverage stability underpins predictable engagement, reliable reimbursement, and credible commercial timelines.

What is actually happening in the market

The early signals are aligning with prior projections.

Net premiums for many subsidised exchange enrollees are rising sharply. Price-sensitive households are reassessing coverage or exiting altogether. As healthier individuals drop out, risk pools tighten, increasing volatility for the remaining insured population.

Payers are responding rationally. When enrolment, utilisation, and risk mix become harder to forecast, caution increases. Budgets are revisited, pilots are scrutinised more closely, and longer-term commitments are delayed.

None of this reflects a sudden loss of interest in innovation. It reflects heightened uncertainty around who will be covered, how consistently, and at what cost.

Second-order effects and trade-offs

As affordability pressure builds, downstream effects are becoming visible across the healthtech market.

• Greater scrutiny on near-term return
  Buyers are prioritising technologies that demonstrate cost impact within a defined budget cycle. Solutions framed around longer-horizon prevention or engagement now face tougher justification unless they are clearly tied to utilisation reduction or operational savings.

• Slower and less predictable sales cycles
  Health systems and payers are extending decision timelines as they reassess enrolment assumptions and financial exposure. Deals are not necessarily disappearing, but they are taking longer and requiring more internal alignment.

• Reduced appetite for discretionary engagement
  When patients delay care or churn coverage, programmes that depend on sustained engagement become harder to scale. This shifts buyer preference toward tools embedded in core workflows rather than optional add-ons.

The environment increasingly favours solutions linked to utilisation management, cost containment, and operational efficiency rather than discretionary digital experiences.

Implications for EU healthtech companies

• For EU companies, exchange dynamics are easy to underestimate, particularly when viewed from outside the U.S. system.

• Coverage instability affects addressable populations, payer willingness to underwrite pilots, and confidence in multi-year programmes. Segments tied heavily to individual-market populations tend to feel these effects first, especially where engagement depends on continuous coverage.

• This does not mean the U.S. market is closing. It does mean that assumptions about demand stability and growth timing need to be revisited.

Handrails for leaders

1. Map your exposure to exchange-driven demand
   Identify which customers, regions, or user groups are most sensitive to affordability shifts and coverage churn.

2. Strengthen short-term proof points
   Buyers are looking for impact they can see within the current fiscal year. Make those outcomes explicit.

3. Rebalance go-to-market priorities where needed
   Employer-sponsored plans, Medicaid managed care, and integrated delivery systems offer different stability profiles than exchange-heavy markets.

4. Plan for volatility as a feature, not an exception
   Policy-driven changes tend to cascade quickly through enrolment, budgets, and utilisation. Build flexibility into commercial plans.

Closing thought

The end of enhanced exchange subsidies is already reshaping coverage behaviour and payer decision-making. This is less about tracking policy headlines and more about recognising when market fundamentals are shifting.

For healthtech leaders, the task is to adjust assumptions around demand predictability, buying timelines, and proof requirements. Companies that respond early, anchor value in near-term impact, and account for volatility explicitly will be better positioned to navigate the next phase of the U.S. market.

Author

Thomas Hennessy is Senior Advisor at Santegic supporting companies with U.S. market entry, regulatory strategy, and commercial growth in health technology and MedTech.

Reach out to Tom directly, or learn more at www.santegic.com.

Health insurance exchanges in the U.S. are often discussed as a policy issue rather than a market one. Coverage levels, subsidy structures, and eligibility thresholds tend to be treated as political variables, disconnected from how healthcare organisations and technology companies actually operate.

In practice, exchange dynamics play a quiet but foundational role in shaping the U.S. healthcare market. For healthtech companies in particular, subsidies influence who is insured, how consistently people stay covered, and how predictable demand is across populations.

Understanding this matters because coverage stability is one of the least visible, yet most important, inputs into healthtech adoption and scale.

What the enhanced subsidies changed

Enhanced premium tax credits introduced under the American Rescue Plan Act significantly altered the economics of individual market coverage. By reducing out-of-pocket premiums across income levels and removing the so-called subsidy cliff, these credits expanded eligibility and improved affordability for millions of people.

The immediate effects were widely reported. Enrolment on the exchanges increased, churn slowed, and uninsured rates declined.

The less visible effect was greater market stability.

When people can afford coverage:

• Risk pools are broader and healthier

• Insurers can price plans with more confidence

• Payers face less volatility in utilisation

• Providers and health systems see more predictable demandThat stability matters downstream.

Why healthtech depends on coverage stability

Healthtech companies rarely operate in isolation. Their success depends on:

• Insured populations who can access care

• Payers willing to reimburse or sponsor programmes

• Providers able to invest in new workflows

Stable coverage supports all three.

When coverage is predictable, payers are more willing to:

• Underwrite pilots

• Invest in preventive and digital programmes

• Take longer-term views on return on investment

When coverage is volatile, the opposite happens. Buyers become cautious, engagement drops, and budgets tighten.

Subsidies therefore function as a market stabiliser, even though they are not framed that way publicly.

Second-order effects worth paying attention to

Beyond enrolment numbers, enhanced subsidies create knock-on effects that are easy to overlook:

• Longer planning horizons for payers
  Stable enrolment allows payers to back interventions that take time to deliver value.

• Greater openness to innovation
  Predictable risk pools reduce the perceived downside of experimentation.

• Improved continuity of care
  Lower churn supports chronic disease management and longitudinal digital tools.

These effects do not show up immediately in policy debates, but they materially shape the conditions healthtech companies operate in.

What happens if that stability is removed

The risk in treating subsidies as temporary policy tools is that their withdrawal can reverse these dynamics quickly.

If affordability declines:

• Healthier, price-sensitive enrollees exit first

• Risk pools deteriorate

• Premiums rise

• Coverage becomes less predictable

That sequence has implications not just for patients, but for anyone building products or services that depend on consistent engagement and reimbursement.

Handrails for healthtech leaders

1. Treat coverage policy as a market signal, not background noise
   Shifts in “affordability” change the commercial environment.

2. Stress-test assumptions about insured populations
   Model what happens if coverage shrinks or churn increases.

3. Prioritise segments with structural stability
   Employer-sponsored and managed Medicaid markets behave differently from individual exchanges.

Closing thought

Exchange subsidies are often discussed in political terms, but their real impact is economic and operational. They shape who stays insured, how risk is pooled, and how confident buyers feel investing in new models of care.

For healthtech leaders, understanding these dynamics is less about policy alignment and more about market realism.

Author

Thomas Hennessy is Senior Advisor at Santegic supporting companies with U.S. market entry, regulatory strategy, and commercial growth in health technology and MedTech.

Reach out to Tom directly, or learn more at www.santegic.com.