It’s no secret the U.S. health crisis can be blamed largely on poor diet and lack of exercise. Do we know we should change our bad habits? Of course.
Everyone’s life depends on exercise, sleep, and nutrition. The data shows a 26–35% reduction in mortality if you just focus on two of those. We don’t have a pill for that. Exercise protects you from heart attacks, from cognitive decline, puts you in a better mood, and prevents major depressive episodes. These are insane effects, yet we can’t get people to do it.
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For most of the 93% of Americans who need it, motivation comes in the form of a frightening diagnosis from their doctor, who has the skills to direct their care but doesn’t really know them. In a healthcare ecosystem that puts them in exam rooms for an average of only 12 minutes, there is no point in even training them to get inside their patients’ heads.
Digital health was supposed to free up time for caregivers, but it simply isn’t designed to help them empower people. It succeeded at democratizing access to doctors and advanced diagnostics, but it failed at inspiring a shift to prevention through better lifestyle decisions. FitBits, Apple watches, and countless YouTube exercise videos—behavior hackers—also miss the boat when it comes to real behavioral change.
The 5% problem
The problem is, the technology is driven by what I call “the 5%.” The early adopting, highly motivated, fitness-obsessed few getting the tactics they crave. I have seen it firsthand; I used to have these patients. They would come into the clinic and they would spreadsheet out their blood pressure for me.
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They are not the problem. It’s the 93%, obviously. They’ve been provided the tools and plenty of information. But do they really need to be told their blood glucose is high because they just ate a tub of ice cream?
No matter how much data the AI has on you, missing is the personal relationship. Emerging tech, wearables—all that is great. But at the end of the day, so much of it still depends on interpersonal relationship building and leveraging, adding an intelligence layer to the loop.
What doctors need is to understand that they’re part of a larger team.
A team sport
This is why I have long said that health is a team sport. This is the mindset shift that needs to happen in medical school. Be good at what you’re really good at as a physician: medical management, the things you can’t behavior-change people out of. Be aware that there’s this other group of people and technology that can help.
So, what is that part of the team?
The science of behavior change has been missing the innovation of data to direct the coaching.
It’s helpful to consider the analogy of race car driver development. The tools are a dashboard full of dials that produce the data needed to figure out how to get the car around the track in the shortest time. It still needs a driver to analyze the data and physically move the car. That’s the innovative platform that’s been created: the car, the driver, and the data.
Applied to behavioral change, the platform’s layers of information go beyond patient surveys or step tracking. In sleep coaching, for example, asking a person how they feel is part of the evaluation equation. The data is REM versus deep sleep, sleep interruptions, waking, and consistency of sleep times. That’s the information needed to troubleshoot and tweak the strategy. It’s about overcoming small problems that add up to huge gains in people’s lifestyles.
Precision in medicine is about determining how an individual’s unique physiology responds to interventions, such as how they metabolize a drug. It also applies to the optimum amount of sleep. In sleep coaching, precision is not just data use, but knowing the person. The coach knows, say, that they have a dog. The dog jumping on and off the bed may be the sleep interruption culprit.
Sounds simple, but only the 5%-ers are likely to actually keep the dog out of the bedroom. The rest need that extra push.
That push is what’s different for everybody. We know the different techniques. We know how to persuade them. But we can also use the tools that are monitoring them in their home to help guide what we say and do. And that’s the perfect combination of precision behavior.
People already get this. Anyone whose kid played on a sports team expects the coach to treat each child differently, to know them and what motivates them. All that we need to do is apply that at scale to drive behaviors that are healthy.
The need to evolve digital health
So, yes, digital health can evolve—from the edge of data to the age of behavior. And the devices are part of that. The vast majority of people don’t want their life to be ruled by smart devices and “6,000 notifications every morning of what they already know they should do.They want what we might call an internally calculated behavior vector. They want their coach to have enough data to know this is the day they are likely to eat poorly at lunch and to reach out with a better option—a course correction. And ultimately they want someone who knows them and can gauge when it’s going to be a trying day. In the final analysis, that’s the smart guidance that will help increasingly busy people hack their behavior and take back control of their life.
Photo: Dilok Klaisataporn, Getty Images
Dr. Ravi Komatireddy, MD, MCTI, is a digital health entrepreneur who is currently the Founder and CEO of Daytona Health Inc., a digital health startup with a fresh take on using humans and algorithms to provide ultra-personalized coaching to upgrade people’s health behaviors and improve health, longevity, and performance.
He is a board-certified internal Medicine physician who trained at Dartmouth Hitchcock Medical Center and the University of California San Diego. Additionally, he was the first wireless digital health scholar at the Scripps Translational Science Institute, where he earned a masters in clinical translational investigation.
Previously, he co-founded and served as Chief Medical Officer of two funded digital health startups: Lumiata Inc., a big data, AI healthcare company focused on creating the world’s largest medical graph database, which was eventually used by the Google knowledge graph; and Reflexion Health Inc., a digital medicine, tele-health physical therapy solution using motion tracking cameras in the home.
His interests include aerospace medicine and developing world digital health. He received the first grant from the NASA flight opportunities program to advance research in digital health and human spaceflight and continues to work with NASA on a Covid-19 Taskforce. He helped introduce a digital health model to medical startups operating in Nairobi, Kenya health tech ecosystem.
He advises several Digital health startups and holds a volunteer faculty position at the University of California San Diego.
