Hack Your Health: A Discussion with Thomas Goetz, Author of The Decision Tree
GS: If we’re at the early adopter end of the curve, what do you envision, when you hit the middle of the curve, how do you think both industry and consumer behavior and choices will be transformed?
TG: Oh I think it’s — my hope is that this is going to be an opportunity for people to engage with their health, make better choices, and have better health so that in general this, this isn’t going to a solution for everybody, nothing in health care is a solution for everybody. But I’m hopeful that it could be something where… You have a large recognition that this is an approach that works for people. That it’s something that you don’t need to sign up with a program, things like Weight Watchers have actually been using this approach for decades. So the idea again, the way technology gets in is, it takes these things that were once proprietary or refined kind of “expert class” and it democratizes them. So my hunch is that these principles will become more widespread and easier to engage in. To some extent though, we’ve been doing this for a long time. If you think about the last 20, 30 years we’ve gotten used to knowing what our blood pressure is and knowing what high blood pressure is and low blood pressure is. We’ve gotten used, many of us, to what our cholesterol count is and thinking about managing that. And those are metrics that years ago didn’t make any sense for people. People weren’t even aware that their doctor was testing them for these. So, the idea that we can become more quantitative and more at ease with data I think is something that has been proven to work well already.
GS: That actually does bring another question to mind which is, you know, as you mentioned, people may not have even paid attention to cholesterol that much until the recent past, and even more recently you start to hear talk about HDLs, LDLs, antioxidants. Over the course of your research — what do you think are some of the hot-button data that people are going to be paying more attention to in the future?
TG: That’s a good question. Really good question. What are the new metrics: To some extent, I think it’s going to fall in two classes. One is the things that we think of as pretty simple and basic that we don’t really measure right now. Like our sleep quality. It turns out you can measure your sleep quality with a little sensor, which again — these curves kick in. Sensors are getting cheaper and cheaper, so it won’t be that much of a big deal. Put on a little wrist band when we go to sleep, and to be able to measure sleep quality. That’s basically: do we rock, do we toss around in our sleep, and how long do we stay still? That gives you a pretty reliable indicator of how well you’re sleeping.
“If you think about the last 20, 30 years we’ve gotten used to knowing what our blood pressure is and knowing what high blood pressure is and low blood pressure is. We’ve gotten used, many of us, to what our cholesterol count is and thinking about managing that. And those are metrics that years ago didn’t make any sense for people. People weren’t even aware that their doctor was testing them for these. So, the idea that we can become more quantitative and more at ease with data I think is something that has been proven to work well already.”
That’s kind of one area, things like sleep, our calorie consumption on a daily basis — even when we’re not dieting, I think that will become more familiar and more normalized. And then there are all sorts of other metrics that I was thinking about, like the advent of fMRIs, and kind of understanding what parts of our brains are lighting up under certain stimulation and certain therapies. I think it will be easier for us to understand how our brain is working, and so there will be a whole kind of nomenclature to that. I think we’ll be in that sector, kind of brain function and things like that. I think we’ll be more at ease with all sorts of blood tests and biomarkers. There are any number of proteins that they are now associating with early precursors of risk for anything from heart disease and diabetes to cancer. So as we start to get these protein libraries, these libraries of biomarkers in place, we’ll be able to understand when we have a kind of high load of this biomarker or that one. Kind of the way that if your’re man over 50, you probably know what your PSA level is for your prostate. I think those are the two kind of zones it’s going to break down into.
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