After the 23andMe genetic test told me I have a higher-than-average risk of heart disease, I decided to purchase an elliptical machine and now use it every day. Then I noticed that half of my office is competing for how many steps they take each week, using FitBit activity trackers. And I just read that PatientsLikeMe, a social networking site for people with chronic conditions, has launched a platform for conducting low-cost clinical trials and other medical studies about treatments and behavior.
On first glance these startups seem unrelated to each other. But in a very basic way, they have something powerful in common: consumer-centered, personally generated health data. They are capturing a new opportunity that could be worth billions of dollars. For instance, 23andMe expects to complete 1 million gene scans this year alone. By 2017, 500 million personal health tracking sensors are expected to be sold annually.
They also share another attribute: These products and services are commonly ignored or treated as toys or distractions by insurers, providers, and prestigious medical journals. But health-care stakeholders need to think about how to harness this trend and integrate these new tools into mainstream medicine. That’s because consumer-centered health data are about directly collecting and providing information in a way that enables two vital things: a shift toward healthier behavior, and evidence for suggesting new courses of treatment.
I’ve been thinking about these issues because I’ve been surprised by the motivational power of this type of information in my own life. Recently, figuring “why not for $99,” I spit into a tube and dropped it in the mail for my 23andme results. Two things I learned particularly stood out. The first was an increased risk of coronary heart disease. The second was an increased sensitivity to the blood thinner warfarin.
So what did I do with these data? For about five years, I’ve been absolutely pining for an elliptical machine. I knew that for my schedule and lifestyle, it would be the most effective way to make sure I got regular cardio exercise. But I also knew that there was no place to fit the thing in my small Boston-area townhouse, and these machines are really expensive. Somehow, though, my 23andme results pushed my ambivalence over the edge, and I figured out solutions to those “insurmountable” barriers. Finally, I’m exercising regularly.
The warfarin data point, on the other hand, is more difficult to figure out what to do with. Warfarin Misdosing can be very dangerous, so the best I can figure is that I should bring this information to the attention of a doctor if I’m ever in a relevant situation, which doesn’t feel like a particularly satisfying answer.
Clearly, we generate different kinds of consumer health data, and the extent to which individuals can act on this information varies. At one end of the spectrum, people can act as consumers, making choices about their environment, eating, exercise, and sleep. At the other end, people require the involvement of doctors or other care providers. And in the middle fall many conditions that have both lifestyle and medical components.
As more people use these products and as the data produced become increasingly valuable, the health-care system would do well to think about how to interact and benefit. For starters, consider these three functions:
Behavioral motivation: Methods that increase people’s motivation to behave in healthy ways are the Holy Grail of much of medicine. Personal health data tap into psychological responses that can act as an impetus for healthier behavior. It’s well known, for example, that tracking a behavior (e.g. how many steps you take in a day) tends to improve people’s choices.
Personalized information can shift healthy lifestyle choices from feeling very likely to be important to definitely important. For example, a family history of diabetes implies you should probably watch your weight, but a genetic test proves with certainty that you possess genes associated with diabetes. This is a mindset shift that prospect theory and associated behavioral economics research has shown strongly affects decision making. This fits especially well into such roles as those of diabetes nurse educators or the kind of health coaches promoted by such care models as Iora Health.
Data management: No one wants information overload. But as personally generated data become better and more common, providers will need the protocols, guidelines, and EMR (electronic medical record) tools to capture and make use of this information efficiently. Systematic ways of interacting with these data are especially important given today’s typically fragmented medical care, where cost pressures often lead to patients seeing a rotating cast of physicians’ assistants, nurse practitioners, and one-off, urgent-care physicians. Without this data management, information provided by patients will be lost, opening providers up to the risk of poor patient care and perhaps litigation.
Everyday personalized medicine: Consumer-centered health data smell a bit like a modern twist on the decades-old hope pinned on “personalized medicine.” Although important progress has been made in such areas as oncology, the everyday practice of medicine remains largely unchanged. Now we are finally beginning to have the tools that allow people to take control of their own personal health in a way so much more relevant than Googling symptoms and wading through the mass of reputable and less-reputable sites that come up. With systematic innovation, health-care providers may be able to leverage existing and new sources of personal health data to achieve more targeted and efficient medical care.
Evidence is mounting that this new market will develop quickly over the coming decade. What’s less evident is which players in the health-care ecosystem will join the new entrants in capturing this opportunity—one that also promises to lower health-care costs and improve patient outcomes.