Optimised for the optimised
Do the privileged and "optimised" need yet another wellness app? Or do we — all of us — need more preventive healthcare and earlier diagnostics?
I keep coming back to this question, and every time I see a wellness-to-medical staged strategy pitched as the obvious path from one to the other, I push back — unless there is a genuinely clear, iterative, adaptive plan for that transition. I get why founders default to it: the financing world rewards it. But I don't think it gets us where we need to go.
A story that makes the point better than I can
The post that triggered this for me came from Spencer Keith Jones, a professional athlete (Denver Nuggets) and investor, reflecting on this year's Stanford Health Summit. He wears the best wearables on the planet — HRV, sleep, recovery, glucose, workload, all tracked in real time. And still, one story from the summit stuck with him: a researcher who died of a heart attack after a workout, despite years of wearable data. In the months before his death, his HRV had dropped, his resting heart rate had climbed, his gait had changed. The signal was there. It never surfaced back to him.
His conclusion is the one worth sitting with: this isn't a data shortage. It's a signal translation problem. We've built extraordinary tools for people who are already well-resourced and highly engaged with their health — and population-level outcomes (obesity, chronic disease, mental health) haven't meaningfully moved.
Why "wellness first, medical later" is a weaker plan than it sounds
The financing logic behind wellness-first strategies is understandable: ship an MVP, get consumer traction and data, use that as the springboard into diagnostics or therapeutics later. But by now, the "easy" problems in health tech have mostly been solved. What's left are the large-scale, multi-faceted ones — the kind design theorists Horst Rittel and Melvin Webber called "wicked problems" back in 1973, to describe issues in planning and social policy that are too complex and too tangled for a single clean solution. Pandemics, climate change, chronic disease, health disparities, AI literacy — these don't yield to an MVP. They need sustained, structural thinking, not a growth-stage pivot.
This is where my regulatory hat comes on. A wellness-to-medical roadmap isn't a UX decision — it's a regulatory step-change, and treating it as incremental is where I see founders get stuck.
The regulatory reality of "graduating" from wellness to medical
Under both the EU and US frameworks, "general wellness" and "medical device / diagnostic" sit on opposite sides of a hard line, not a gradient:
Quality management system. General wellness products carry no QMS obligation. The moment a product makes a diagnostic, therapeutic, or disease-prevention claim, it typically triggers ISO 13485-aligned QMS requirements — design controls, CAPA, traceability — that most consumer wellness teams haven't built and can't retrofit overnight.
Clinical evidence. Wellness claims can rely on general validation of a biomarker measurement. Medical claims require clinical evidence tied to the specific intended use — a materially different (and slower, costlier) evidentiary bar.
Classification jump, not classification drift. In the EU, this move can push a product from unregulated wellness straight to Class IIa or higher under MDR, with Notified Body involvement. In the US, FDA's own general wellness policy (which I've written about before) draws a similarly sharp enforcement-discretion line — useful while you're on the wellness side of it, largely irrelevant once you cross.
The gap is widening, not narrowing. The EU's 2025 wellness guidance leans harder on mechanism-of-action and technology; the US's leans harder on claims. A staged strategy calibrated for one market doesn't automatically transfer to the other.
None of this means the staged approach is wrong. It means it needs a real regulatory roadmap from day one — classification thresholds, evidence plan, QMS scaling — not a "we'll figure it out when we get there." I've seen too many teams get comfortable in wellness and never make the jump, because nobody mapped what the jump actually costs.
Whose problem are we solving, and who's paying for it to be solved?
This is also where the money sits, and it's worth naming plainly. US digital health funding hit $14.2B in 2025, a 35% jump over 2024's $10.5B, but the headline number masks a market splitting into "haves" and "have-nots," with capital concentrating in fewer, larger deals and mega-deals over $100M accounting for the highest share since 2021. AI-labelled health companies alone captured 54% of total 2025 funding. That's a lot of capital chasing tools for people who are already well-optimised, and comparatively little chasing scalable prevention for everyone else.
There's an older public health concept that captures the tension well: epidemiologist Geoffrey Rose's population-versus-high-risk framing. The high-risk strategy — targeting individuals already flagged as at-risk — remains the preferred approach in health care, while Rose's population strategy, which shifts the risk of the whole population even slightly, has struggled to gain traction despite stronger long-term evidence for it. Health tech investment has largely followed the high-risk, individually-optimised logic. Rose would have called that the wrong bet for population health, even if it's the more fundable one.
Where this leaves founders and investors
I don't have a tidy fix. But I think the mental model shift starts with a few honest questions before a wellness-to-medical roadmap gets pitched as the strategy:
Is there an actual regulatory pathway mapped for the transition, with classification and evidence milestones — or is "we'll add medical claims later" doing a lot of unexamined work?
Is the population you're building for the same population you intend to eventually serve, or are you optimising for engaged early adopters and hoping the model generalises?
Are you solving a problem that's genuinely hard to fund because it's structurally important — or genuinely hard to fund because it doesn't fit the return timeline investors want?
The sooner we're honest about which of those we're actually building, the sooner health tech starts creating value for the needs of this era, not the last one.
References
Rittel, H. W. & Webber, M. M. (1973). Dilemmas in a General Theory of Planning. Policy Sciences, 4(2), 155–169.
Rose, G. (1985). Sick Individuals and Sick Populations. International Journal of Epidemiology, 14(1), 32–38.
Rock Health, 2025 Year-End Digital Health Funding Overview: A Tale of Two Markets, January 2026 — rockhealth.com/insights
Spencer Keith Jones, LinkedIn post on the Stanford Health Summit and the signal-translation gap in consumer health tech — linkedin.com/in/skj21
Methodology note:This article is based on my original LinkedIn post (link), written in response to a post by Spencer Keith Jones, reflecting my professional experience and personal perspectives on health tech and regulatory strategy. AI assisted in elaborating the topic into a broader article by integrating background research, fact-checking, and additional regulatory and public-health context. All analysis and regulatory perspectives are my own, and all content has been reviewed by me for accuracy.
