Health Futures: Variations on a Theme

Today the majority of our health insights come from doctors and fitness instructors. We explain our goals and they make recommendations on how to get there: exercise more, eat more vegetables, and get more sleep. To track our progress, we manually record our measurements, diet, and workout routines. As we understand how our behavior affects our health, we can get more specific prescriptions and start seeing better results.

Mobile and wearable technology are the next iteration of this system. Our phones now have sensors that track physical activity. Wristbands and watches measure heartbeat and sleep habits. When paired with fitness apps, the devices we carry every day plot colorful graphs of our data and send it to the cloud for processing. We can track more behavior than ever before and, while there is still manual record keeping, this additional data helps get at specific insights faster.

Instead of looking outward on health issues, mobile technology is allowing users to take more control for themselves. This trend will continue as we collect more data and are able to derive more actionable insights. Projekt202 and The Livestrong Foundation put together a panel explore this kind of future. They discussed how fitness apps are used today, strategies for making them better, and what to expect once this technology becomes more commonplace.

Fitbit's personalized fitness dashboard. Source: Fitbit Inc.

Fitbit's personalized fitness dashboard. Source: Fitbit Inc.

In an event about data, it was a little shocking to hear the panelists say that the numbers are not important, at least not right now. It’s more important that users get insight into habits that might otherwise be invisible. Take number of steps, for example. At the end of the day, we can only say if we walked a lot or a little. We don’t think of our activity in precise measurements; any number is going to sound a bit arbitrary. The value in today's steps is comparing it with yesterday’s steps. As long as the measurement is consistent, we can observe trends over time, set goals, and track progress. While it’s important to walk often, there is no one size fits all. The numbers are specific to the user. Some people will realize they walk more on some days than others. Some people don’t walk enough at all. Access to this data will help them to be more proactive in the future.

The goal is to improve poor behavior. One of the panelists, Robin Krieglstein, says behavior can be broken down into motivation, a trigger, and an action. Developers can influence motivation by understanding the emotionality of the data. People feel more connected to activity data because it’s a kind of representation of themselves. With real-time processing, developers should find the moments when the data is most meaningful and present it as a trigger to inspire action. A simple example is to send a notification when the user has been more active today than they were yesterday at the same time. Encourage them to keep going. Or maybe send a notification when the user has been sitting for too long. You can get the user to go for a walk, moving them closer to their activity goals.

Kyle Samani, CEO of Pristine, thinks the second use case might come up more often. Sometimes, the data is going to be depressing. Few people are as active as they should be and it’s a bad user experience to open an app to be reminded of that. For apps to be successful, he suggests, they have to account for this failure and fold it into a narrative. Lark does this especially well. The secret is that it functions more like a messaging app than anything else. Users can explore their fitness habits by starting a conversation with a “personal trainer” robot, complete with typing indicators. Lark has a great way of saying, “Yeah, you’re not walking as much as you should, but you did better than yesterday.” The personal approach is motivating and reassuring, the perfect cushion for missed goals.

No matter how friendly, it feels a little weird to entrust a computer with health advice. Luckily, no one suggests people stop seeing a primary physician once they buy a Fitbit. It’s a supplemental device. The panelists were quick to note that while doctors have a deep knowledge of medical conditions, they are much less familiar with individual habits and lifestyles. Prescriptions are based off of general symptoms and general case studies. The data that comes out of an activity tracker is unique to the individual and can be used to give a more personalized prescription.

Some people call this precision medicine. It’s the idea that doctors will be able to pinpoint a patient's exact needs for their exact circumstance. However, Maninder “Mini” Kahlon, Vice Dean for Partnerships and Strategy at The University of Texas Dell Medical school, prefers the term precision health. She argues that doctors don’t just prescribe medicine, they prescribe lifestyle changes. Diabetes was used as an example where frequent exercise is important. But not every diabetes patient has the same lifestyle. More advanced data can give doctors the information they need to make the right kind of recommendation. If the patient is largely sedentary, it’s easier to confidently prescribe less medication and more exercise because the reality is that people rarely self-report as harshly as they should.

While in its infancy today, precision health will become more established with more data. Apple wants to help accelerate this process. Two weeks ago they launched a platform that helps medical institutions create survey-style apps. The platform, ResearchKit, utilizes the built in sensors and data collected in the iPhone and sends it to researchers. Medical institutions, long plagued by the slow pace of these studies, can now enter the world of continuous development. Data is available almost immediately and, as insights present themselves, they can iterate on the study to learn even more.

The greatest innovation of ResearchKit is that it makes these studies available in the app store. Rather than exhausting medical resources to find people, participants now come to them. In one day Stanford signed up 11,000 people for their cardiovascular study. Before ResearchKit, it would have taken a year and relied upon over 50 medical centers across the country. In the words of Alan Yeung, medical director at Stanford Cardiovascular Health, “that’s the power of the phone."

Stanford's My Heart Counts cardiovascular app, Source: Apple Inc.

Stanford's My Heart Counts cardiovascular app, Source: Apple Inc.

Precision health will also become more present in the fitness apps we use today. With more than our individual data at our disposal, we can understand our activity in a much greater context and make much healthier decisions. Christian Hernandez presents a great example of this in his post, The Age of Context:

In the future my Jawbone won’t simply count my steps, it will also be able to integrate with other data sets to generate personal health insights. It will have tracked over time that my blood pressure rises every morning at 9:20 after I have consumed the third coffee of the day. Comparing my blood rate to thousands of others of my age range and demographic background it will know that the levels are unhealthy and it will help me take a conscious decision not to consume that extra coffee through a notification. Data will derive insight and that insight will, hopefully, drive action.

None of this is a new innovation for healthcare. We are simply layering technology on top of our current way of doing things. As sensors improve and algorithms are refined, all the data we need will become available. The challenge will be how we use that data. Whether that means leveraging smarter notifications or building a narrative, we need to focus on  maximizing insights and encouraging healthier lifestyles. Our health is more than just a bunch of numbers. Hopefully by abstracting more clinical data analysis, prescriptions and interactions will become more personal than ever before.