Wearables are turning passive monitoring into daily clinical data
AliveCor’s devices now capture about a million electrocardiograms each week from users around the world, a scale that would have been hard to imagine when Ben Green was making house calls as a family physician in 2009. His memory of a woman with atrial fibrillation, repeated emergency room visits, and normal heart rates at the hospital remains the kind of bedside story that explains why wearable data matter. A handheld pulse oximeter gave that patient a way to check her own heart rate, report it back, and avoid unnecessary trips to the emergency department. The device did not replace clinical judgment; it extended it into the patient’s home.
Green described that moment as a turning point in how clinicians think about personal devices. Once patients can collect meaningful physiologic information between visits, the conversation changes from retrospective guesswork to shared decision-making. In arrhythmia care, where symptoms can come and go before a tracing is captured, that shift can be decisive. A wearable can turn a vague complaint into a documented rhythm strip, and a documented rhythm strip can change management.
Engagement depends on whether patients want to return to the data
At MedCity News’ INVEST Digital Health conference in Dallas, Green joined Tanvi Jayaraman, clinical lead for health AI at Oura, and Patrick Sheehan, vice president of value-based care at Withings, for a discussion moderated by Ken Nelson, partner at Nelson Ventures. The conversation moved quickly past novelty and into the harder problem: keeping people engaged with devices months and years after the first download or unboxing.
Oura’s strategy rests on making the experience feel useful without making it feel intrusive. The company’s smart ring focuses on sleep, cardiovascular health, and metabolic health, and Jayaraman said the product is designed to let users engage on their own terms. The ring does not buzz constantly or force repeated interaction. It stays in the background while the app surfaces data when the user is ready to look.
That design choice matters in chronic monitoring. Patients are far more likely to remain active when a device feels like a coach rather than an alarm system. Oura has also linked its ring with Stelo, Dexcom’s continuous glucose monitor, so users can view glucose data inside the Oura app. Meal photos and nutrition data can then be layered against the glucose curve, creating a more interpretable picture of how food, timing, and physiology interact. For people trying to understand metabolic responses in real time, the feedback loop is immediate and personal.
Consumer adoption often rises when the data answer a question the user actually has.
Clinicians need usable data, not just more data
Sheehan framed the Withings approach as consumer-grade technology with medical credibility behind it. The company sells connected scales and smartwatches with FDA approvals and authorizations, then allows patients to expand into additional monitoring tools, including blood pressure measurement for people living with hypertension. The ecosystem is built to start simple and then widen as clinical needs evolve.
The clinician side of the equation is just as important. Sheehan said the data collected by these devices can help physicians prescribe and titrate medications, but only if the information is presented in a form they trust and can act on quickly. Withings uses the data not only for the patient experience but also for physician engagement, and the company has seen strong retention from clinicians when readings are brought back into the electronic medical record.
Green echoed that point from the perspective of an arrhythmia-focused company. Wearable readings can be helpful, but they can also be confusing or unfamiliar to physicians who have not trained with these tools. AliveCor maintains a cardiologist network that can review ECGs asynchronously and provide live consults when needed. The network is meant to bridge the gap between consumer-collected data and clinical interpretation. Educational materials matter too, because raw data without context can stall adoption instead of speeding care.
In practice, the workflow challenge is not whether a patient can record a number. It is whether a clinician can trust the number, understand the device, and respond without creating extra administrative burden.
Prevention, prediction, and the next version of cardiovascular care
Jayaraman said Oura’s physician team is thinking about prevention years before disease becomes visible in the traditional sense. That approach reflects a growing belief that wearable technology can help identify risk patterns early enough to change behavior before a diagnosis arrives. For patients, that may mean learning how sleep, activity, recovery, or metabolic trends affect long-term risk. For clinicians, it creates a new class of longitudinal data that may be more revealing than a single office reading.
Green pushed the concept further, envisioning a future in which patients can learn about cardiovascular disease risk as easily as they check a credit score. AliveCor already has ECG models that can predict mortality and heart disease, positioning the company in what he described as the prediction business. The implication is substantial: if a consumer can see cardiovascular risk in a quantified, repeatable way, preventive care may become more concrete and less abstract.
Still, the path to routine use is not straightforward. Sheehan pointed to a familiar barrier in digital health: many physicians are not digital natives, and they may need support to interpret what wearable data mean in daily practice. Withings has built a medical group of digital-native physicians partly to address that divide. The panel’s broader message was less about gadgetry than about translation—between patients and devices, between devices and clinicians, and between data and action.
The technology is already producing a flood of information. The unresolved question is how health systems will make that information clinically usable without overwhelming the people expected to interpret it.