FixAFib Connect•Heart care & AFib repair, between visits

Atrial fibrillation isn't something you fix once and move on from — it's managed daily, in the gap between a quarterly cardiology appointment and everything that happens in someone's actual life.

FixAFib Connect is the companion app for that gap: a guided way for patients to track symptoms and rhythm episodes, and for their care team to see patterns instead of a single snapshot.

Every FixAFib patient walks out of their first appointment with the same instructions: watch for symptoms, log episodes, come back in three months. In practice, almost no one does this reliably with a notebook or memory alone.

By the next visit, the details that mattered — when an episode happened, what triggered it, how long it lasted — were already gone. Clinicians were making decisions on incomplete information, and patients were left managing a frightening, invisible condition entirely on their own between visits.

I owned UX strategy and product design end-to-end: the patient-facing app, the symptom and episode-logging core loop, and the way that data surfaces to the care team — without designing a separate clinician product from scratch.

The constraint that shaped everything: this had to work for a patient population skewing older and less digitally confident, while still producing clean enough data for a cardiologist to act on in a five-minute review window.

Patients: often newly diagnosed, anxious about their heart rhythm, ranging from highly tech-comfortable to barely past a flip phone. Every screen needed to work for someone logging an episode at 2am, scared, with shaking hands.

Care teams: cardiologists and care coordinators with minutes, not hours, per patient. They didn't need more data — they needed the right three numbers, surfaced without digging.

Before any screens, I mapped the full loop: symptom onset → log → context capture (triggers, duration, severity) → pattern surfaced to the patient → flagged to the care team if it crossed a clinician-set threshold.

The flow had to fork gracefully — a patient mid-episode shouldn't be asked to fill out a form; a calm retrospective log the next morning could ask for more detail.

I started wireframes with the single highest-stakes moment — logging an episode in progress — and worked outward from there, rather than starting with onboarding like most teams default to.

Early low-fidelity passes tested how few taps a frightened, possibly dizzy patient could realistically manage, and how much could be inferred — time of day, recent activity — instead of asked.

The shipped core loop: one large, unmistakable button to log an episode in under five seconds, with optional context capture deferred to a calmer moment afterward.

On the care-team side, every patient's data rolls up into a simple rhythm timeline — frequency, duration, and trigger patterns at a glance, with automatic flags replacing the manual chart review clinicians were doing before.

TODO: drop in real hi-fi screens here once available — episode logging, the patient rhythm timeline, and the care-team dashboard view.

TODO: add real outcome metrics once available — e.g. logging adherence, reduction in missed episodes, clinician time saved per review, patient-reported confidence.

The hardest part of this project wasn't the interface — it was earning enough trust that a frightened patient would actually open the app during an episode instead of just calling a family member.

If I were starting over, I'd push even earlier for in-home testing with actual AFib patients rather than relying on clinician proxies for the first round of feedback — the gap between "this seems usable" and "I'd trust this mid-episode" turned out to be bigger than expected.