Wearable Activity Trackers: What Everyone Gets Wrong

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The most important person was completely missing in a lively discussion I had recently about activity trackers and other wearable data collection technology like the FitBit and Apple’s Watch plus mostly-theoretical devices that would improve chronic disease management.

The technology and healthcare folks in the room loved the idea of using activity trackers and other quasi-wearable technology like mobile apps on smartphones to reduce costs and improve client and patient health.

Unfortunately, the most important participant in health and wellness wasn’t even invited: the client/patient. So I did my best to stand in for that poor underrepresented soul, and shared Radial’s learnings from the last decade as we’ve worked with some of the smartest and most insightful health and wellness businesses out there.

Here’s my take on why activity trackers and other wearable data-collection technologies aren’t the silver bullets they’re cracked up to be:

1. Data scares most consumers

Most people have zero interest in tracking microdata about their lives. I repeat: ZERO interest. They are not data geeks. It’s just not how they’re wired, and you’re not gonna change that.

Matter of fact, they’re INTIMIDATED by data. Their numerical literacy is low. Their analytical skills are nonexistent. Their reaction to numbers verges on phobia. Remember, most folks can’t accurately interpret the nutrition label on a box of crackers, even if they have a college degree!

2. Even geeks have a limited attention span

Even people who love data typically have a limited attention span. Each gadget or datafeed mesmerizes them for a few months…and then they move on to something else.

3. Fitness and disease management: not the same

The wearable technology discussion typically conflates two wildly different segments: the fitness market and the condition management/disease management market. The needs of these markets are not remotely the same.

My old heart rate monitor sometimes thought my heart rate at the gym was over 200 beats per minute. In reality, it’s just confused by some random signal received from other gym equipment. Does it matter? Nope, I’m not making any important decisions based on the data. I just like to know my heart rate when I work out.

On the other hand, any device that directly modifies insulin doses for people with Type 1 diabetes is a Class III medical device requiring FDA approval, a multi-year process. That’s because equipment failures and software errors in these devices endanger lives. Those devices have to be pretty much bulletproof in every respect.

4. Fundamental misunderstandings

Folks who get excited about wearables in healthcare often describe a scenario where the device gathers patient data which is then remotely reviewed by a healthcare professional who intervenes as appropriate. There are two problems with this scenario.

First, the most common examples aren’t game-changers. They’re just improvements to existing technology like Holter monitors. The devices in this category are usually used for short-term diagnostic purposes, so they’re certainly not going to radically affect ongoing healthcare efficiency, effectiveness or cost.

Second, when the examples DO apply to chronic diseases, they often reflect a deep misunderstanding of how patients actually manage chronic health issues. These conditions often require a high degree of self-care decision-making that cannot possibly involve healthcare providers on a routine daily basis. (Plus, imagine the cost of THAT!)

For example, I saw a writeup this week about a proposed Apple Watch study of people with diabetes, which anticipates that doctors and nurses would respond to high and low blood sugars when detected by the Watch (with technology yet to be developed). That’s absurd. Both of those events can and should be treated independently by the patient most of the time. And periodic physician review of blood sugar patterns is already routine with existing technology. I’m having a hard time thinking of any significant improvement in health outcomes that’s likely to result in this example.

5. Not everything that counts matters…

There’s an implicit assumption in the conversation about wearable trackers: that if we had all this data, we’d know what to do with it.  Sadly, that’s just not true.

If you’re trying to improve your cardio capacity, a heart rate monitor is indeed useful. But managing chronic health challenges is more complicated. The physiological mechanism of action underlying many chronic health issues is simply not fully understood, so it’s tough to come up with truly useful technology. We’re shooting at a target while wearing a partial blindfold.

Plus, treatment of virtually all serious chronic health issues requires consideration of multiple dimensions. Simple mobile phone apps aren’t going to help these folks. Managing obesity, easily the most popular “condition management” target for activity trackers, requires more than food logs and exercise journals for many folks. The easy stuff — calorie lookups, for example — isn’t generally what moves the needle when you’re trying to manage chronic health problems.

For example, people with insulin-dependent diabetes make hundreds, perhaps thousands, of daily micro-decisions in a constant and only somewhat successful attempt to manually balance insulin, activity, food and the blood sugar effects of stress, sleep, illness, menstruation, and innumerable other factors. (In people without diabetes, the body handles all of these adjustments transparently.)

6. Not everything that matters can be counted…

But perhaps the most counterproductive assumption is this one: that all people require in order to achieve good — or at least better, or more stable — health is knowledge, data and information.

Yes, data is important, especially for certain health conditions. But optimal health requires far more than data, knowledge and information, particularly when health issues exist.

Healthcare is best viewed as a process that centers around the knowledge, feelings, beliefs, actions and life priorities of the individuals involved. It also requires understanding their environment and culture.

Healthcare in a vaccum can never succeed, and technology, no matter how cool, will never improve health in the absence of an understanding of these most human dimensions.