539 - HIMSS Europe 2025: Femtech, Synthetic Data, AI + more
What if the future of healthcare wasn’t just smarter but also more human, more just, and more connected?
During HIMSS Europe 2025 in Paris, a new wave of thinkers and builders met to discuss how we lift women’s health, govern AI, and define trust in tech.
In this episode of Talking HealthTech, Peter Birch speaks with Ida Tin from Femtech Assembly , Jessica Rose Morley, PhD from the Digital Ethics Center (DEC), Yale University , Sharmini Alagaratnam from DNV , and Ricardo Baptista Leite, M.D. from HealthAI - The Global Agency for Responsible AI in Health about the evolution of digital health in Europe, the future of femtech, responsible AI in healthcare, the challenges of synthetic data, and the importance of data governance.
Timestamps:
Check out even more of the discussions that Pete had during HIMSS Global Health Conference & Exhibition Europe in a dedicated playlist on our YouTube channel here.
From Niche to Necessity: Femtech’s Growing Role in Health Systems
Once seen as a niche focused on women’s self-tracking apps, femtech is now moving into the mainstream. Its growth is not only about business potential but also about recognising women’s health as a vital part of economic and social systems. Ida Tin, who coined the term ‘femtech’ and founded Clue, describes an early moment of frustration:
“There was a bunch of… other people building things for female health in the tech world and the way people perceived what we were doing was that it was very niche and maybe a little bit embarrassing too.”
Changing perceptions begins with language, but Ida believes the shift runs much deeper. She describes women’s health as “a societal infrastructure,” similar to energy grids or transport networks, which are essential for keeping everything else running smoothly.
That shift demands new ways of measuring value. Beyond counting profits, there’s a need to capture broader returns: healthier workforces, social resilience, and even ecological regeneration.
“If we really were to live according to [regenerative] principle, we would do a lot of things differently,” she suggests, tying body literacy to planetary health.
In 2024, McKinsey came out with a report underlining how underinvestment in women’s healthcare costs the world trillions. Over the years, it has become increasingly apparent that closing these gaps will not only save money but generate new value. Ida also highlights the need for richer, unbiased data in women’s health research and development:
“What I also think is really cool about synthetic data is that you can use it to fill in gaps where your real data doesn't exist. On edge cases, you know, in healthcare, rare disease perhaps. Or rare cancer types, where you just know you haven't got enough data, but you need it to be able to train algorithms or, you know, make better decisions.”
Why Bridging Gender Gaps in Health Is About More Than Equality
For Ida, addressing gender gaps in healthcare isn't just about fairness. She believes women’s health should be recognised as a driver of wider social progress. She referenced research that calculates a trillion-dollar annual penalty for nations that neglect women’s health and says:
“For society, it’s really expensive that women don't get adequate healthcare.”
The value proposition is two-fold: “You can make money by investing and you can save money by investing into women's health.” Modern femtech isn’t a charitable enterprise; it's a financial, social, and population health necessity. Yet Ida notes that cultural disconnects persist, impeding even basic conversations about physiology.
“Many women don't feel their own bodies very well and they definitely don't talk well about it. So this bridging between genders, I think, is a big part of this shift towards being regenerative.”
In this light, empowering women with data and diagnostic tools isn’t just about individual outcomes. It’s about repairing society’s foundational knowledge of itself.
AI and Patient Data: Progress, Protection, and Power
While femtech aims to amplify underrepresented voices, the data revolution rolling through Europe’s health sector raises a raft of new questions. Jess Morley, from Yale’s Digital Ethics Centre, unpacks the risks and responsibilities tied to secondary health data.
Secondary use refers to any use of data that goes beyond direct patient care, including research, public policy, and the development of AI. With the growth of large language models and federated learning, researchers often speak enthusiastically about the potential of "precision medicine." Yet Jess offers a note of caution:
“First of all, I get why that's exciting, but it is essentially marketing spiel, right? A lot of it is not really personalised medicine. It's much closer to targeted advertising and there are way more things that are far more complicated than are actually being played out in that type of narrative.”
Europe’s regulatory landscape is an advantage here, thanks to GDPR and the emerging AI Act, which place patient rights and transparency at the core. Still, significant risks remain. Health data are inherently sensitive, and conventional notions of privacy, such as who can access your records, are only the beginning.
“Where we are falling down though is that difference between privacy… but there's also who does what with it,” Jess notes.
Some tech firms may not see their innovations as ‘research’ in the classic sense, sidestepping longstanding ethical review safeguards.
Jess explains that much of what helps people stay healthy comes from broader population-level efforts, like access to clean water or affordable, nutritious food. “Why is it cheaper for me to buy McDonald’s than to buy organic vegetables?” she asks, pointing to the deeper, structural issues at play. She warns against putting too much focus on individual interventions or data-driven nudges while overlooking the bigger systemic factors that influence health.
The Limits of Personalised Medicine in a Public Health World
A key question is where resources should go: towards personalised care or broader public benefit. While new AI tools claim to predict and prevent health issues for individuals, the evidence suggests that combining lots of individual case studies doesn't always lead to better outcomes at the population level.
“Hundreds of healthy individuals does not make a population healthy,” says Jess.
Instead, the forces that shape public health, environment, income, education, and food systems require a collective response. That’s why she argues, “Code for we, not for me”, a reminder that shifting the focus from shiny, personalised solutions to wider, more inclusive interventions is key.
The Role of Certification and Synthetic Data in Strengthening Health Systems
For digital health to thrive, both patients and healthcare professionals need to trust not only the tools themselves but also the systems that support them. Sharmini Alagaratnam from DNV describes their work as delivering “an invisible trust layer.” The focus isn’t on flashy technology, but on quiet, thorough verification that ensures medical devices are safe, AI models are reliable, and data sets are truly representative.
The rise of synthetic data is changing how that work is done. Rather than depending solely on sensitive and identifiable patient information, researchers can now train algorithms using artificially generated datasets. This method not only strengthens privacy protections but also helps address gaps in real-world data, especially for rare conditions where patient numbers are limited.
“Synthetic data does add privacy,” Sharmini explains. “But what I also think is really cool about synthetic data is that you can use it to fill in your gaps where your real data doesn’t exist… That’s kind of the added value.”
The challenge is to set standards for what counts as “good enough” synthetic data: Is it representative? Is it biased? Does it behave like the real thing at the point of application?
Bridging Sectors: How Other Industries Can Shape Health Innovation
DNV’s experience in other essential sectors, such as maritime, energy, and others, offers valuable insights for healthcare. Years of experience developing digital twins for ship navigation, for instance, have helped shape healthcare simulations. However, as Sharmini notes, each sector faces its own unique set of risks. Even though health data is the largest and fastest-growing category of digital information worldwide, data sharing in healthcare remains a challenge. Furthermore, health data is also “potentially the data that's least used”, with strict regulations and institutional caution that often prevent this wealth of information from being fully utilised.
Unlocking the full potential of this data, without compromising privacy or trust, is the next big step. It could be the turning point that moves digital health from a side feature to a driving force in delivering better care.
From Hype to Impact: Governing AI in Healthcare
The AI "hype cycle" in health is moving at full speed. But turning pilot projects and technical breakthroughs into meaningful, responsible, and widespread change is still a major challenge, especially when it comes to making new tools practical, scalable, and trusted across different health systems. Ricardo Baptista Leite, leading the global agency HealthAI, highlights the stakes:
“AI is such a transformative technology or group of technologies that the opportunity is to redesign, to reimagine health altogether.”
But for this transformation to succeed, leaders need to start from purpose, not trends. As he wryly notes:
“Many times people say we want to use AI. And I ask them, why do you want to use AI? And the most common answer is because my boss is telling me I have to do something with AI.”
Ricardo highlights a global issue: a large share of health spending goes to areas that don’t actually improve outcomes. He sees AI as a chance to rethink more than just processes. It’s an opportunity to re-evaluate incentives, funding models, and even how we define health itself.
His organisation brings together a broad community of governments, regulators, civil society, and industry to build practical, ground-up frameworks for responsible AI. They are working on early warning systems to spot risks and supporting tools that meet regulatory standards. Crucially, the focus isn’t only on wealthier nations. Lower and middle-income countries may have the most to gain, since they’re not as constrained by outdated systems.
“They can actually reimagine how to deliver health and care altogether,” Baptista Leite says, “without the legacy systems that… have made health systems basically unsustainable.”
The Limits of Regulation and the Need for Global Alignment
European regulation, especially the AI Act, has become a key reference point for global standards, much like how GDPR set the benchmark for data privacy worldwide. Still, Ricardo is wary of “one size fits all” solutions. Context is crucial:
“You cannot try to force everyone down the same path…[we] tailor our technical assistance… adapt them to the local context.”
This is why regulators and standards bodies around the world are leaning toward flexible, risk-based approaches. The key challenge is finding the right balance between maintaining strong safeguards and staying agile enough to adopt effective tools, especially in areas that are currently underserved.
“With AI we can give access to better health outcomes…when the option is between AI and nothing, yes, even if the risk benefit ratio falls more on the benefit side, perhaps that's the way to go,” he reflects.
One of the most important pieces of the responsible AI puzzle is what happens after a tool is deployed. Ensuring safety doesn't end at approval. Ongoing, real-world monitoring is essential to catch issues early and maintain public trust. As Ricardo explains:
“The most important part with AI is the post-market surveillance, identifying through real-world data if something goes off and to detect that early on, that's in the interest of companies to avoid legal liability and reputational risk. It's in the interest of those managing the health system to avoid harm to patients. It's the interest of everyone to build trust towards these [tools].”
Co-Designing the Future of Healthcare
One clear theme emerges across these conversations: the future of healthcare innovation is collaborative, not competitive. It’s not about hero entrepreneurs or splashy apps; it’s about building bridges across gender, across sectors, and across borders. That means shared frameworks, inclusive language, and genuine engagement between regulators, technologists, clinicians, and communities.
“We created this feedback mechanism from the ground up and we believe in this bottom-up approach to be critical,” Ricardo notes.
Both Sharmini and Jesse echo this need for international and multi-sector partnerships, drawing in lessons from energy, finance, and even maritime risk management to inform health’s next evolution.
For those working within the health ecosystem, the call is to get involved. Engaging with communities of practice, joining collaborative regulatory networks, and championing the needs of underrepresented voices can help shape the rules of the road before they harden into inflexible regulatory structures.
Digital Health’s Next Chapter: Earning Trust, Creating Value
Europe’s digital health sector stands ready to move beyond the hype of new technologies. The true test will be how effectively it can build systems that are not only innovative but also trustworthy, inclusive, and responsive to real-world challenges. As Ida reminds us:
“It's important that women feel well so they can participate fully in society and be part of solving these huge challenges we have as a species and as a planet.”
Trust will play a central role in shaping the next era of healthcare, which needs to be built on ethical practice, strong governance, and a willingness to keep learning. The vision is clear: a health system that embraces diversity, supports responsible AI, uses synthetic data to improve safety and drive progress, and puts the public good at the centre of every decision. This vision isn't just possible, it's essential. If the sector moves forward with care, collaboration, and a clear sense of purpose, digital health can play a key role in building a healthier, fairer future across Europe and beyond.
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