From Fitness Trackers to Clinical Tools: The Future of Wearable Healthcare

The Promise That's Driving the Push

Imagine a world where your watch catches an irregular heartbeat months before your next medical check-up, or helps you with better glucose control before prediabetes becomes the real thing. That's the vision now shared by device manufacturers, clinical researchers, and laboratory medicine professionals alike — and the medical need for it is staggering. In the United States, 38 million people live with diabetes and 98 million more are prediabetic, costing $413 billion in 2022 alone [1, 2]. Heart disease and stroke claim over 944,800 lives annually, with cardiovascular costs projected to hit $2 trillion by 2050 [3-5]. These are not problems that can be solved inside hospitals. If wearables could reliably monitor chronic conditions between appointments, they could shift healthcare from reactive crisis management to something closer to continuous prevention.

But can today's smartwatches actually deliver on that promise? That's the question at the heart of a new opinion paper from the International Federation of Clinical Chemistry's (IFCC) Committee on Mobile Health [6]. Led by Gammie and 16 co-authors spanning institutions across twelve countries, the paper catalogued the health features of 30 smartwatch models from over 20 manufacturers — Apple, Samsung, Fitbit, Garmin, Huawei, Withings, and others — and assessed the barriers standing between these consumer devices and the medical record. Their verdict: the technology is promising, but the industry's lack of standardization, combined with unresolved questions around accuracy, regulation, data ownership, and digital equity, means we're still some way from being able to trust a wrist-worn sensor the way we trust a lab result.

What's Actually on Your Wrist

If you own a smartwatch, you might assume it's tracking most of what matters about your health. The reality is more uneven than the marketing suggests. The paper's device survey found that while some features are near-universal, the metrics with the greatest clinical value are the ones least likely to be on your wrist [6]:

Across all 30 models, the paper counted 28 distinct health-related metrics — but not a single one was available on every device. That is the standardization gap in a nutshell. Two watches from different manufacturers might both claim to track "heart health," yet use fundamentally different sensors, algorithms, and reporting formats. For a consumer choosing a device, this inconsistency is an inconvenience at most. For a healthcare system trying to integrate wearable data into patient records, it's a serious obstacle.

One metric in the above table warrants a closer look: blood glucose. No smartwatch on the market can measure your blood sugar on its own. The devices that advertise glucose tracking either let you manually log readings or display data from a separate continuous glucose monitor (CGM) worn elsewhere on your body. The Apple–Dexcom G7 partnership, for instance, shows CGM readings on the Apple Watch screen — but the measurement is coming from an implanted sensor, not the watch itself. This illustrates the level of regulation and sensor precision that any wrist-worn device would need to achieve before standalone glucose monitoring becomes possible. The stakes are high — an inaccurate reading could lead someone with diabetes to take the wrong insulin dose. That risk prompted the FDA to issue an explicit safety communication in 2024, warning consumers not to rely on smartwatches or smart rings for glucose measurement [7].

Can You Trust the Numbers?

Even the features that are well established come with important caveats. Take heart rate — the one metric nearly every smartwatch offers. Most devices measure it using photoplethysmography (PPG), which shines green light through the skin and detects changes in blood volume. At rest, PPG is reasonably accurate. But go for a run, hit the gym, or even gesture vigorously during a conversation, and the signal gets noisy. Wrist movements interfere with the light sensor, and accuracy can drop precisely when you'd most want reliable data. A smaller number of watches — 13 of 30 in the survey — include ECG sensors that read the heart's electrical activity directly, offering a cleaner signal. But even these provide only a single-lead reading, a far cry from the 12-lead ECG you'd receive in a clinic.

Then there's the human side of accuracy. Calorie and distance estimates depend on user-entered demographic data (height, weight, stride length) that is often inaccurate or outdated. These sound like minor annoyances, but if wearable data is to support clinical decision-making, even small systematic errors become consequential.

A more practical limitation rarely gets airtime: battery life. Most smartwatches last between 18 hours and 7 days on a full charge, depending on how many features are active — with the Withings ScanWatch 2 as a 30-day outlier. If continuous health monitoring is the clinical goal, daily charging means daily data gaps. The paper argues that clinical-grade use would at minimum require devices to log when charging interrupts data collection, so that clinicians can spot the holes in a patient's record rather than mistaking them for stable health.

From Wrist to Medical Record

Say a smartwatch could produce perfectly accurate, clinically relevant data. The next challenge would be getting it into a format your doctor can actually use. Right now, that's harder than it sounds. When you pair your watch with the manufacturer's app, you're typically consenting — somewhere in the terms of service most people skip — to the manufacturer's ownership of your health data. If your GP or cardiologist wanted to incorporate your watch data into your medical record, they would need a formal data-sharing agreement with the smartwatch company, subject to privacy regulations and consent frameworks. In practice, that means wearable health data lives in a proprietary silo: you can see it in Fitbit's app or Apple Health, but it doesn't flow into the same system as your blood work, imaging, and prescriptions.

The technical fix sounds simple — agree on a common data format — but in practice it's anything but. Standards like FHIR (Fast Healthcare Interoperability Resources) exist to let different health systems talk to each other, yet most hospital record systems were never designed to absorb the large data-streams of heart rate, SpO₂, and sleep metrics from millions of wrist-worn sensors. Without careful filtering, clinicians risk being buried in noise rather than helped by it. And they'd need training too: a heart-rate-variability reading from a consumer watch doesn't carry the same weight as one from a clinical chest monitor, and treating them interchangeably could lead to unnecessary referrals — or missed warning signs.

Regulation adds a further layer of complexity. A manufacturer wanting to market health-monitoring features across multiple countries faces different approval bodies in each — FDA in the US, CE marking in Europe, PMDA in Japan — with each agency applying its own standards for safety and efficacy. This adds time and cost that hit smaller companies hardest. And for features where lives might be at stake — fall detection, arrhythmia alerts — the consequences of getting it wrong are lopsided: a false positive means an anxious trip to the ER, but a false negative from a device a patient has grown to trust could delay life-saving intervention.

The Double-Edged Sword

Even if every technical and regulatory hurdle were cleared tomorrow, a deeper question would still remain: does constant health monitoring actually make people healthier?

For many users, the answer is clearly yes. Daily activity goals, sleep scores, and heart rate trends can grow healthier habits and a greater sense of agency over one's own wellbeing. But a 2023 scoping review of 35 studies sounded a note of caution [8]. The review found that smartwatches are valuable monitoring tools, but warned against treating them as substitutes for clinical assessment. The concern is not just about accuracy — it's about what gets lost when a patient is reduced to a stream of data points. A heart rate graph doesn't capture how someone is sleeping emotionally. A step count doesn't reflect whether they're socially isolated. When wearable tracking starts replacing face-to-face visits rather than supplementing them, the reviewers argued, it risks violating a foundational principle of medicine: non-maleficence, or "first, do no harm".

And for some people, the harm can be surprisingly direct. Picture this: you're at your desk after lunch and your watch buzzes — your heart rhythm looks irregular. You check again ten minutes later. Still flagged. By mid-afternoon you're Googling "atrial fibrillation" and debating a trip to the emergency room. This is essentially what Rosman and colleagues documented in a study of patients with known atrial fibrillation — cases where continuous cardiac monitoring via commercial smartwatches triggered new-onset health anxiety, leading to compulsive wrist-checking and unnecessary medical visits [9]. The irony is that health-conscious consumers, the people most likely to own these devices, may also be the most vulnerable to this kind of feedback loop. The paper argues that manufacturers bear a responsibility here: algorithms should minimise false alarms, and when a notification does fire, it must include clear guidance on what — if anything — the user should do next [6].

And then there are the people who never get to worry about any of this, because they can't access the technology at all. A 2024 UK report found that 1.6 million people lack access to a smartphone, tablet, or PC, with 77% of those without basic digital skills aged over 65 [10]. That's precisely the population — older adults managing chronic conditions — that stands to benefit most from remote health monitoring. If the digital divide is this wide in the UK, the authors note, the barriers in lower-income countries are likely far greater. Their recommendation: build "poka-yoke" (error-proofing) design directly into health apps, creating interfaces intuitive enough that accurate data collection doesn't depend on the user's comfort with technology [6].

The paper's overarching message is one of cautious optimism. Smartwatches are not going to replace clinical medicine — nor should they. But they have a genuine opportunity to extend it: catching arrhythmias between appointments, flagging metabolic trends before they become crises, keeping elderly patients connected to their care team from home. The authors' conclusion is that realising this potential will require something the smartwatch industry has so far largely avoided: genuine, cross-sector collaboration between device manufacturers, clinicians, regulators, and the patients themselves, to build the shared standards that can make wearable data trustworthy enough to act on.

References

1. Centers for Disease Control and Prevention. "National Diabetes Statistics Report", U.S. Department of Health and Human Services (2023). https://www.cdc.gov/diabetes/php/data-research/index.html
2. Parker E.D. et al. "Economic costs of diabetes in the U.S. in 2022", Diabetes Care (2023). https://doi.org/10.2337/dci23-0085
3. Centers for Disease Control and Prevention, National Center for Health Statistics. "Multiple Cause of Death 2018–2022", CDC WONDER Online Database (2024). http://wonder.cdc.gov/mcd.html
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7. U.S. Food and Drug Administration. "Do Not Use Smartwatches or Smart Rings to Measure Blood Glucose Levels: FDA Safety Communication", (February 21, 2024). https://www.fda.gov/medical-devices/safety-communications/do-not-use-smartwatches-or-smart-rings-measure-blood-glucose-levels-fda-safety-communication
8. Hosseini M.M., Hosseini S.T., Qayumi K. & Hosseinzadeh S. "Smartwatches in healthcare medicine: assistance and monitoring; a scoping review", BMC Medical Informatics and Decision Making 23 (2023) 248. https://doi.org/10.1186/s12911-023-02350-w
9. Rosman L., Gehi A. & Lampert R. "When smartwatches contribute to health anxiety in patients with atrial fibrillation", Cardiovascular Digital Health Journal 1 (2020) 9–10. https://doi.org/10.1016/j.cvdhj.2020.06.004
10. Good Things Foundation. "Our Digital Nation", (2024). https://www.goodthingsfoundation.org/policy-and-research/research-and-evidence/research-2024/digital-nation