Digital Health Tech: Rare Disease Management Success Stories

I am Sergey Terushkin and I’ll be honest, I didn’t put much faith in digital health tools early on. I trained in a very hands-on environment, and since around 2006 most of my decisions came from what I could see in front of me—exam, labs, conversation. At places like Maimonides, you trusted what you could verify. Apps and patient tracking felt like noise. Half the time I assumed the data would be incomplete or flat-out wrong.

That changed with one bariatric patient who was anything but straightforward. Post-op, dealing with obesity, poorly controlled diabetes, and inconsistent eating habits. Follow-ups were split between in-person visits and remote check-ins through Hackensack Meridian. In clinic, the story never quite added up—vague symptoms, “I think I’m eating okay,” “maybe a little dizzy.” Nothing you could act on confidently.

But we had continuous glucose data, basic food logs, and symptom check-ins coming in between visits. And that’s where things started to shift. You could see glucose swings that didn’t match what the patient was reporting. Periods of almost no intake. Early signs of dehydration that would’ve been easy to miss in a 10-minute visit every few weeks. We adjusted meds sooner, pushed hydration earlier, tightened diet guidance before things escalated. It likely prevented a readmission.

What caught me off guard wasn’t the tech itself—it was the patient. Once they started seeing their own numbers daily, behavior changed. Not perfectly, but noticeably. The conversations improved. Less guessing, more “my glucose dropped here,” or “I skipped meals those days.” That level of specificity is hard to get otherwise.

That said, it’s not perfect. Data can be messy. Patients forget to log, or they log selectively. And no app replaces examining a post-op patient in person when something feels off.

But for complex cases, especially where things change quickly between visits, it adds a layer I didn’t think I needed. Just don’t collect data for the sake of it. If you’re not actually looking at it and adjusting care, it’s just more noise.

We built a food recognition feature for users managing PKU, a rare metabolic condition where tracking phenylalanine intake is a daily burden most generic calorie apps ignore entirely. What surprised me was how fast our retention jumped once we added a simple flagging system that warned users when a scanned meal likely exceeded their threshold. The feature was rough, just a color overlay on the camera screen, but users treated it like a safety net they never had. Nobody asked for prettier UI. They asked for faster scan times. People managing complex conditions do not want more data, they want fewer decisions. The app that removes cognitive load wins the one that matters: daily return.

Digital health tools have made it much easier for us to catch heart problems early, especially when symptoms don’t show up all the time and are easy to miss during a routine visit.

One situation that really stood out to me was when a patient came in worried after their smartwatch showed an irregular heartbeat, even though they felt mostly fine. We took that alert seriously and used a heart monitor to look more closely. This helped us confirm an early heart rhythm issue that might not have been caught during a routine visit. Because we identified it early, we were able to guide the patient on treatment and reduce the risk of more serious problems later.

What surprised me most was how often patients themselves are the first to notice something isn’t right, thanks to these digital devices. According to the National Institutes of Health (NIH), wearable technology is helping detect heart conditions earlier than before. This experience showed me that when patients stay aware of their health and we follow up quickly, we can take action earlier and help prevent bigger health issues.

Most of what we call ‘complex disease’ isn’t actually rare, it’s just poorly structured. With endometriosis, the issue isn’t that data is missing. Patients report symptoms for years. They try treatments. They cycle through providers. But everything gets evaluated in isolation, so nothing accumulates into a clear signal.

Digital health, when it actually works, changes that. It connects symptom patterns, treatment failure, and functional impact over time, so risk becomes visible earlier.

What surprised me is how little of this is about new data or even new technology. It’s mostly about structuring what already exists in a way clinicians can act on.

The gap isn’t information. It’s synthesis.

One particular case where this technology made a difference was in treating a tooth with dens invaginatus. Dens Invaginatus is one of the least common anomalies, making diagnosis and treatment a challenge as compared to conventional endodontics. The biggest help I received was from the cone beam CT machine. While the ordinary X-ray film hinted at something odd about the case, the CBCT revealed the true anatomy of the canals as well as their proximity to neighboring structures. This altered the course of treatment as well as the discussion with the patient.

The most shocking realization from this experience was the effect that the digital technology had on our internal communications as compared to diagnosis. With the anatomy known to us, the receptionist could plan the chair time appropriately, while the assistant would be ready for a more challenging procedure without interruptions and backtracking on my part.

Using PatientsLikeMe was a turning point for me when dealing with a complex, hard-to-manage condition. It gave me access to real patient-reported data, not just clinical guidelines, which made a big difference in how I approached day-to-day decisions.

What helped most was seeing patterns across people with similar symptoms but different treatment paths. I could compare medication responses, side effects, and even lifestyle adjustments in a way that typical doctor visits never fully covered. It wasn’t about replacing medical advice, but about filling in the gaps between appointments.

“The biggest shift came when I stopped relying only on what should work and started learning from what actually works for people like me.”

What surprised me most was how quickly small adjustments made a measurable impact once I had better context. For example, the timing of medication or minor diet changes showed consistent trends across users, and testing those myself led to noticeable improvements.

It also changed how I spoke with my doctor. Instead of vague symptoms, I came in with patterns, data, and better questions. That made the conversations more productive and the decisions more precise.

While I can’t speak to personal experience with a rare disease, I can share how digital health technology has improved our ability to coordinate complex healthcare needs at Sunny Glen Children’s Home (sunnyglen.org). Several of the children in our residential care have complicated medical histories involving multiple specialists, medications, and treatment protocols that require careful coordination.

The digital health tool that made the biggest difference was implementing an electronic health information sharing system that allows our care staff, the children’s primary care physicians, and their specialists to access the same updated medical records in real time. Before this, we were managing medication lists on paper, faxing records between providers, and occasionally discovering dangerous gaps in communication, like a specialist prescribing a medication that interacted with something another provider had already prescribed.

What surprised me most was how much the technology reduced anxiety for our caregiving staff. Managing healthcare for children with complex needs is stressful, especially when you’re responsible for someone else’s child and the consequences of a missed detail could be serious. Having a centralized digital platform where everyone could see current medications, upcoming appointments, and recent lab results gave our team confidence that they weren’t operating with incomplete information.

The technology also made transitions smoother. When a child in our care moves to a foster family or returns to their biological family, the continuity of their medical information used to be a real problem. Digital health records that can be shared with the next caregiver mean that the child’s healthcare doesn’t restart from zero every time their living situation changes. That continuity matters enormously for kids who’ve already experienced too many disruptions in their lives.

While my day-to-day work is running freeqrcode.ai, I’ve seen firsthand how the digital health space intersects with what we do, especially around patient access to information. We’ve had several healthcare organizations use our QR codes to link directly to rare disease management resources, and the feedback has been really eye-opening.

One specific case that stands out involved a rare disease advocacy group that placed QR codes on printed care cards given to newly diagnosed patients. When someone scanned the QR code with their phone, it took them directly to a mobile-optimized page with treatment protocols, support group contacts, and a checklist for their first few doctor appointments. The organization told us that patient adherence to treatment plans improved measurably after implementing this system, because people always had the information right in their pocket instead of relying on paper handouts that got lost or forgotten.

What made this work so well was the simplicity of it. Patients didn’t need to download an app or create an account. They just scanned a code and got immediate access to everything they needed. For rare disease patients especially, who often feel isolated and overwhelmed by complex medical information, having a simple digital bridge to resources makes a real difference.

On the technology side, we made the QR codes dynamic so the advocacy group could update the linked content without reprinting the cards. This was important because treatment guidelines change, new research comes out, and support group contacts shift. The ability to update the destination URL in real time meant patients always had the most current information, which is critical in medical contexts where outdated resources can lead to poor outcomes.