If you’ve ever opened a patient’s chart and felt buried under a landslide of data (CGM trends, HRV curves, full-page lab panels), you’re not alone. As wearables give you more metrics to monitor, this issue is compounding.
We’ve reached a new clinical reality: more data, less clarity.
The question isn’t how to get more numbers. We’ve already gotten good at that. It’s how to make them mean something.
And that’s where AI steps in, surfacing the signals that matter most.
The New Role of Wearables
Wearables are evolving from wellness toys into diagnostic tools that drive behavioral change. They now stream real-time physiologic data that can:
Detect instability before symptoms appear
Track responses to lifestyle or peptide protocols
Personalize timing and dose of interventions
In functional and longevity care, that’s the holy grail: acting early, precisely, and confidently.
Even if you haven’t recommended these devices, your patients might already be using wearables like:
Oura, Whoop, or Garmin to track cardiometabolic data (e.g., HRV, VO₂max, and temperature variability for early recovery and illness signals)
Muse S or TruNeura to track neurocognitive data (e.g., EEG and reaction-time metrics to flag fatigue or neuroinflammatory change)
Levels, Supersapiens, or Lumen to track metabolic data (e.g., glucose and CO₂ exchange data, revealing metabolic flexibility)
The devices from these companies aren’t just gadgets. They’re continuous labs on your patient’s wrist (or elsewhere on their body). The trick is turning the resulting data from more noise to a tool for clinical decision support.
Closing the Loop: AI as the Clinician’s Lens
The flood of data means nothing without interpretation. Fortunately, you don’t have to do the work of analysis yourself. New AI-powered dashboards now unify wearables, labs, and patient-reported outcomes into one clinical view.
Instead of reading 20 pages, you might see:
“hsCRP trending ↑ 18%, HRV ↓ 12% — suggest early inflammatory response.”
Or:
“Cycle-phase sleep efficiency ↓ during luteal phase — consider progesterone or adaptogen support.”
These micro-insights change how you prep for visits. You walk in already knowing where the conversation—and the intervention—should go.
Why It Matters
When you leverage AI to make sense of wearables and lab data, you unlock wins for your patients and your practice. Those include:
Fewer unnecessary visits. Remote data replaces many in-office spot checks.
Earlier intervention. You see drift before disease.
Billable time. Continuous monitoring qualifies for RPM codes (99453–57).
Higher engagement. Wearables give patients a way to actively participate between appointments.
AI turns a data burden into a clinical superpower.
What’s Next
The next frontier is always-on sensing. As wearable tech advances, we should get continuous hormone, inflammatory, and metabolic tracking that feeds predictive models.
Imagine getting a prompt that reads:
“Pattern detected: HRV ↓ + temp ↑ + glucose variability ↑ = early flare. Adjust recovery protocol.”
That’s not science fiction. It’s the emerging norm.
Here’s your big takeaway: Data doesn’t heal people. Informed and personalized clinical decisions do.
AI’s role is to help you see patterns sooner, intervene more intelligently, and spend more time being the kind of clinician no algorithm can replace.
📙 Your Homework
Start small this week:
Pick one data stream and track it. You’re aiming to spot trends here, not for perfection.
Example: HRV, CGM
Use an data dashboard to observe. Or use AI to help you interpret the trends
Example: Heads Up Health, Guava, ChatGPT
For one patient, succinctly summarize the trend, and use it to inform how you personalize care for your patient.
Example: “Your recovery index on Whoop has dropped for three days. What’s happening with your sleep? Are you overtraining?”
How I AI with Crystal Brust, PA-C
On this week’s How I AI, we sat down with Crystal Brust, PA-C, founder of Farm to Functional Medicine.
Crystal works on the frontlines with perimenopausal women struggling with weight gain. Her approach is both innovative and grounded: she uses microdosed GLP-1s as a catalyst, but pairs them with the real foundations of long-term wellness — protein, strength training, fiber, and hydration.
What sets her care apart is how personalized it is. Every patient gets tailored guidance that fits their unique context — not a one-size-fits-all protocol.
That level of personalization takes time — unless you have help.
With Vibrant Practice, Crystal leverages AI assistance and scribing to prepare for visits, stay fully present during them, and still finish with beautifully structured SOAP notes. The AI doesn’t just document; it learns. After a year on the platform, Crystal says the scribe now “sounds like me” — mirroring her tone, phrasing, and clinical reasoning.
The result: more time for patients, less time charting, and a workflow that finally feels human again.
Crystal also notes that in the year she’s been using the platform, she’s noticed how the scribe has learned her voice.
Her philosophy:
If you want to explore how Vibrant, the AI-powered, all-in-one practice platform could support you, schedule some time with our team today.
This Week in Clinical AI
Researchers worry about clinical skill loss as healthcare providers lean more heavily on AI. Evidence is mounting that as more clinicians offload work to AI, they’re losing competency in both tasks and reasoning. Data already shows skill loss in interpreting electrocardiograms and radiological images and in colonoscopists detecting colon polyps.
ŌURA expands its functionality to better support preventive care. The wearable company launched a suite of new features: insights into cumulative stress and improved cycle insights, complete with a redesigned app. ŌURA also initiated a blood pressure profile study with the goal of deploying a future feature for wearers of the smart ring.
Experts predict explosive growth in the global AI healthcare market. As of now, that market is valued at $39.25 billion, which already represents a notable jump from its $29.01 billion valuation last year. But over the next seven years, reporting from Fortune Business Insights projects that the market will see a compound annual growth rate (CAGR) of 44%, landing it at $504.17 billion by 2032.
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