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Over the Christmas and New Year’s holiday, my family and I did something refreshingly simple: we stayed home. No travel, no airplanes and security lines, no packing and re-packing...no sense that we needed to go somewhere to recharge. We slept. A lot. The kind of sleep that comes from having nowhere to be and nothing urgent waiting in the morning.
As the days slowed down, I found myself thinking a lot about sleep. Over the holiday, I re-read Why We Sleep by Matthew Walker, a book that feels less like popular science and more like a warning label for modern life. And in parallel, a close friend I work out with introduced me to her Oura ring, walking me through how she uses it to understand and visualize not just her daily activity, but also her sleep quality. I learned the phase "sleep debt."
What began as a holiday reset quickly turned into a broader realization: sleep has become one of the most visible, measurable, and discussed aspects of personal health. And for those of us in insights and analytics, that matters more than we may fully appreciate.
Here’s a simple observation: if you want to strike up a genuine conversation with someone -- at work, at the gym, at a dinner party -- ask them how they’re sleeping.
Not “How are you?” or “How’s work?” but “How have you been sleeping lately?”
The responses are almost always thoughtful, personal, and revealing. People talk about stress, parenting, aging parents, training for races, menopause, travel, alcohol, anxiety, screens, and ambition. Sleep has become a socially acceptable proxy for discussing physical, emotional, and cognitive health.
That universality is precisely why sleep is such an instructive category for understanding where healthcare is heading.
Matthew Walker’s Why We Sleep synthesizes decades of research showing that sleep underpins nearly every physiological system. Sleep deprivation impairs glucose metabolism, increases cardiovascular risk, weakens immune response, and disrupts emotional regulation. Poor sleep compromises learning and memory consolidation, and chronic disruption is linked to neurodegenerative processes, including impaired clearance of beta-amyloid in Alzheimer’s disease.
What struck me on this re-read, however, is how closely the science now aligns with what consumer health technology (like the Oura, or my Garmin watch) is making visible. The mechanisms Walker describes -- fragmentation, circadian misalignment, cumulative sleep debt -- are no longer abstract concepts. They are metrics on a dashboard.
Sleep, once subjective and retrospective, has become quantified and longitudinal.
My research team and I have spent years conducting foundational research across sleep-related categories: insomnia, narcolepsy, and sleep disturbances associated with neurodegenerative diseases such as Alzheimer’s-related insomnia and sundowning. We’ve rigorously mapped patient journeys, diagnostic delays, OTC and Rx treatment behaviors, adherence challenges, and unmet needs. We’ve supported launches, including newer MOAs like the DORAs.
But the context surrounding those journeys has shifted dramatically.
Just a few years ago, most sleep-related buying processes kicked off with subjective dissatisfaction -- “I’m exhausted,” “I can’t stay asleep,” “Something feels off.” Today, an increasing number of consumers cultivate months or years of data from wearables like Oura, Apple Watch, Garmin, and others. That data doesn’t simply inform awareness; it shapes beliefs and the conversations that result.
Patients are no longer just reporting symptoms. They are presenting evidence.
As we move into 2026, consumer health technology can no longer be treated as background noise in buying process and patient journey research, particularly in conditions that are monitorable via a range of devices.
These devices now influence:
In other words, wearables are shaping not just what patients do, but how they interpret what happens next.
For insights and analytics professionals, this shift has profound methodological implications.
Are our foundational studies explicitly accounting for wearable usage? Are we segmenting patients based on their relationship with health data: trackers, optimizers, skeptics, and avoiders? Are we exploring how patients reconcile discrepancies between how they feel, what their device says, and what their HCP recommends?
Equally important: are we understanding how healthcare providers interpret, or discount, consumer-generated data?
Ignoring this layer risks building buying process models that feel increasingly out of sync with reality.
Sleep is not unique. It is simply ahead.
Cardiovascular health, metabolic disease, mental health, women’s health, and even oncology are seeing early signals of similar disruption. As consumer health tech expands its scope, the boundary between “medical” and “consumer” data continues to blur.
The implication is clear: real-world evidence is no longer something that begins only after a prescription is written. It often starts at the consumer level, long before formal diagnosis.
That quiet holiday -- filled with sleep, reading, and unhurried conversations -- reinforced something I’ve seen repeatedly over the years: meaningful shifts in healthcare rarely arrive fully formed. They emerge through behavior change, technology adoption, and subtle shifts in how people understand their own bodies.
Sleep, once invisible or amorphous, is now measurable. Once episodic, now continuous. Once discussed only in exam rooms, now shared freely in everyday conversation.
As we head into 2026, our challenge as insights and analytics leaders is not simply to acknowledge consumer health technology, but to integrate it thoughtfully into how we study behavior, design research, and inform strategy.
Sometimes the most important signal isn’t found in a dataset or a model. Sometimes it starts with a simple question:
“How have you been sleeping lately?”
