How to Build Trustworthy HealthTech People Trust | Blush & Bloom Podcast | Ep. 41

Healthtech has never been easier to build. AI tools can turn an idea into a working prototype in a matter of weeks, and founders are shipping faster than ever. Yet a working prototype is not the same as a product that people trust with the most sensitive data they own: their health.

In this episode of Blush & Bloom, host Gigi Kenneth talks with Piotr Zając, HealthTech Director at Monterail and the former founder of Untitled Kingdom, the digital health agency Monterail acquired in late 2024. Over more than 15 years, Piotr and his teams have shipped 75 plus digital health products, from connected devices to remote patient monitoring and digital therapeutics.

Together they get into what it actually takes to build health products that work clinically, technically, and commercially, and why the answer almost always comes back to trust, health outcomes, and the people who will eventually use the thing you are building.

In This Episode, We Cover:

• The two mistakes healthtech founders make most often
• Why vibe coding is risky when your product holds health data
• How to protect sensitive health data, including a real menstrual tracking scenario
• Why accessibility and cultural context change how you design health apps
• Why wearables produce huge signal but very little insight
• What makes femtech different from the rest of digital health
• Lessons from more than a decade of building and leading a health company

What mistakes do healthtech founders make most often?

The two most common mistakes, Piotr says, are building before you know whether you are solving the right problem, and building before you know who will pay. It is easy to be dazzled by new technology and forget the health outcome, which is the thing that actually matters.

He describes a simple model that keeps founders honest: the healthtech triad of patient, payer, and provider. In every healthtech product, one of those three has to pay, whether through a subscription, reimbursement, or a provider using the tool to serve patients. Skip that question and you can build something exciting that no one will fund.

Why is vibe coding risky in healthtech?

Because health data is not ordinary data. As a European Union citizen, Piotr frames health data as the most precious data a person can possess, which means how you store, share, and transfer it carries real consequences. Vibe coding makes it easy to forget those security patterns entirely.

He shares a sharp example. When abortion protections shifted in the United States, some period tracking apps reassured users that their data was safe because it sat on European servers. As Piotr explains, bilateral agreements between the US and the EU meant that promise did not fully hold. Working with one startup, his team designed a safeguard: if a court requested a user's data, the app would first notify that user and offer to permanently delete their records, so there would be nothing left to hand over.

Vibe coding carries a second, quieter risk too: sameness. When every app looks and behaves alike, design stops accounting for the people who do not live inside tech.

"Garbage in, garbage out. When you're vibe coding, you need to know what to put into the model and how to supervise the outcome."

For health products, that supervision has to include real medical expertise. Piotr's advice is to bring in clinicians and product people who can validate whether your app truly works for everyone it claims to serve.

🔒 Protecting sensitive health data starts with asking for less

One of the clearest takeaways is about onboarding. Too many teams, Piotr says, ask for too much too early. You download an app and immediately get hit with requests to connect Apple Health, your sleep data, your sexual health data, and more, before you understand what any of it is for.

"They're asking too much too early. I think this is the biggest problem."

The fix is to earn trust before asking for data. Explain the health outcome, why the data is needed, how it will be used, and whether it will be stored. He points to research showing people share financial data far more freely than health data, which they guard closely unless they are already sick. Respecting that instinct, and treating health data as something the user owns and controls, is the foundation of a trustworthy product.

🌍 Why does accessibility and cultural context matter so much?

Because a health product is only useful if the person in front of it can actually use it. Piotr contrasts a tech-fluent young founder in San Francisco with a 76 year old farmer in North Carolina, who both may need the same tool but experience it very differently. Age, ability, culture, and religion all change how an app should communicate.

The point is vivid with intimate products. The copy and experience for something like a pelvic floor trainer will differ across regions, from more liberal markets to places where the topic is taboo. Thoughtful design meets people where they are rather than assuming everyone reads the interface the same way.

Why do wearables produce so much data but so little insight?

Wearables generate an enormous stream of signal and very little insight. A watch or a recovery band captures millions of snapshots, but a single data point on its own is close to meaningless without context.

"The data stream without the context is rubbish."

Piotr's reframing is that the real question is not what you can measure, but what decision the data enables or improves. A heart rate spike means one thing on a departing airplane and something entirely different while you are relaxing in bed. Trends over months can be genuinely useful, and he shares a case where a clinician caught a problem precisely because a wearable trend contradicted a clean one-off test. Individual snapshots, though, mostly add noise to appointments that already run just 12 to 15 minutes.

💗 What makes femtech different?

For most of digital health's history, Piotr notes, investors and builders effectively ignored that 51 percent of society are women, with different bodies, biology, and hormones. That neglect created a deep trust deficit, which also means loyalty runs much stronger once you actually earn it.

He reflects on 11 years working with Elvie, beginning in 2013 when the team was just five people. Femtech data is deeply intimate, spanning reproductive health, sexual health, and cycle tracking, which raises the stakes on privacy. Building well in this space, he says, demands both clinical depth and radical design empathy, and those rarely live in the same team. The payoff, from a discreet, silent breast pump a mother can use anywhere, is technology that genuinely changes lives.

🧭 What advice does he have for new healthtech founders?

Leadership is lonely, and most of your decisions will be wrong, which is fine, because a wrong decision beats no decision. Surround yourself with people smarter than you, trust your gut once you truly believe in what you are building, and do not get too attached to any single technology, because it will change within a couple of years.

Above all, start from the health outcome for the patient rather than the excitement of the tech. Piotr also notes you can usually tell when a founder is building for investors instead of for patients, and those turn out to be very different products.

FAQ

What is the healthtech triad? It is the model of patient, payer, and provider. In any healthtech product, one of the three has to pay, whether through a subscription, reimbursement, or a provider using the tool to serve patients. Founders who ignore this build products no one funds.

Is it safe to vibe code a health product? Not without safeguards. Health data is highly sensitive, and fast AI-assisted building makes it easy to skip security and accessibility. Piotr recommends involving clinicians and product experts to validate the medical side and supervise what goes into and comes out of the model.

Why don't doctors always trust wearable data? A single wearable snapshot has little clinical value and appointments are short, often 12 to 15 minutes. Long-term trends can be useful, but isolated data points without context tend to add noise rather than insight.

How should apps ask for sensitive health data? Ask for less, later. Build trust first by explaining the health outcome, why the data is needed, how it will be used, and whether it is stored, rather than demanding every connection during onboarding.

What makes femtech different from other digital health? It serves the roughly 51 percent of people historically overlooked by mainstream medicine, its data is deeply intimate, and it demands both clinical depth and design empathy. The trust deficit is higher, and loyalty is stronger once earned.

💬 Final Thoughts

Piotr's throughline is simple and hard to live up to: trustworthy healthtech starts with the health outcome and the person, not the technology. Ask whether you are solving a real problem, who will pay for it, and whether the people you claim to serve can actually use what you build. Do that, ask for data only once you have earned it, and treat wearable signal as a question rather than an answer, and you move from an exciting prototype toward a product people can genuinely rely on.

👥 Connect with the Guest

Piotr Zając: https://www.linkedin.com/in/zajacp/

Gigi Kenneth (Host): https://www.linkedin.com/in/gigikenneth

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