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Episode 2: My Data, My Health, My Self

We’re constantly collecting data about our health with brand new tools and methods. But how does this new data affect us individually and globally?

From a mindful cyborg to the creator of a smart tampon, we meet those who are collecting and analyzing health data with brand new technology. This episode explores how data may be the key in solving health problems all around the world.

CRISTINA QUINN: It was 2008. Chris Dancy was 39 years old working for a software company in Salt Lake City, Utah. And his health was not great.

CHRIS DANCY: I weighed 320 pounds. I smoked two packs of Marlboro Light one hundreds a day, sometimes three. I drank about 24 to 36 cans of Diet Coke a day.



CRISTINA QUINN: Was there a Costco near you or something?

CHRIS DANCY: I would just go to 7/11 cause you could get cigarettes and diet coke at the same time.

CHRIS DANCY: I mean I would spend garish amounts of money on alcohol on the weekends. I would just be drunk from, you know Thursday afternoon to Monday. And then in all sorts of recreational street drugs. I mean, 2008 was like the bottom of the bottom for me. It was really really ugly.

CRISTINA QUINN: And then, the bottom of the bottom — of the bottom came after Chris partied all night long with a group of friends. He blacked out, which wasn’t necessarily that unusual in those days.

But when he woke up and looked at Facebook  – he saw a photo. In the photo, he’s sitting on his porch, hunched over. He looks pretty wasted. He’s got a cigarette in one hand, a beer bottle beside him. His belly obscures a lot of his body. And he’s naked…except for a pink cowboy hat. It was time to make a change.

I’m Cristina Quinn and this is dot-future, a branded podcast from Microsoft and Gimlet Creative, about making the future happen. And the reason we’re starting in the past, on a show about the future, is because Chris had a choice to make.

The future doesn’t just happen.

It’s the result of a series of choices that we’re making right now. You can wait for the future to come to you, or you can engage with it, and get ahead of the curve.  Welcome to dot-future.

Today we’re talking about health. And specifically, about how we approach it in the digital age. There are new tools to consider for tracking and measuring our health, and then there are new IDEAS to consider — ways to look at the information we’re already generating, with our behavior or bodies — that help us understand our well being.

So back to Chris, our naked cowboy. I’m kidding, we’re not going to call him that.

CHRIS DANCY: Now I personally like mindful cyborg.

CRISTINA QUINN: Mindful cyborg. The reason he calls himself this is because he is so plugged in. Chris uses over 700 sensors and devices to track himself.  Devices that produce data that Chris credits with radically changing his life — and data that’s brought him a kind of notoriety in certain circles. Chris travels the world talking about being connected because he believes we’re facing a turning point in how we think about the data we collect about ourselves.

And Chris collects a lot of data. He’s got on three wearables, on the same wrist, all at the same time. And that doesn’t count the various sensors and smart devices scattered throughout his house — more on that later.

After he hit bottom in 2008, Chris decided to do something about his health. So, to solve the problem in front of him, he turned to his tech background. He created a dashboard.

Chris took inspiration from Maslow’s hierarchy of needs — you know shelter, water, food — and he made his own list.

So, in addition to tracking his health, he started tracking his finances, how much he was socializing, and even his spirituality. It was all color coded so he could tell which areas of his life he was doing well in, and which were being neglected.

He started measuring everything he could think of that related to the list — things happening inside of him, and around him:

CHRIS DANCY: What’s your heart rate, what’s your respiration, what’s your blood sugar? How hot is it? What’s the humidity? How bright is it? How loud is it?

CRISTINA QUINN: He took that information, and he used it.

CHRIS DANCY: Because I keep track of a lot of sets of data about myself it’s very easy for me to understand where behaviors are coming from and how to adjust them.

CRISTINA QUINN: And now, when you visit Chris at his house, it’s not piles of Diet Coke cans that you’re stepping over … it’s cords.

CHRIS DANCY: You ready for like the Willy Wonka of cyborgs?

CRISTINA QUINN: He gave us a tour of his home in Nashville.

CHRIS DANCY: So In here..*CLOSET OPENING*. Dum dum dum. So I’ve got one two three four five shelves full of technology.

CRISTINA QUINN: Chris’s closet is like a museum of wearables past – it’s got smartwatch prototypes, headbands that measure brain waves, and even lasers that help him measure the environment around him. Most of this tech is obsolete now, he’s keeping most of this stuff as memorabilia. But he still uses some of it…

CHRIS DANCY: This is awesome. This little pill here.**NAT SOUND** What that does is it’s got a sensor inside it and you swallow it and it measures things that goes through your body. And then in here next to my bed so some people have books in their bookshelf. I actually have hundreds and hundreds of chargers. If I need to recharge I can just do it right next to my bed.

CRISTINA QUINN: Every sensor and wire is here to help Chris get information and use it to adjust his behavior or environment, to subtly coax him into living his best life. Besides weight and heart rate, he checks his blood oxygen levels, calorie-intake, and monitors his sleeping habits. He tracks how much music he listens to, which apps he’s using the most on his phone, even how much light he’s exposed to.

For most of us, this isn’t normal behavior. It’s extreme. For Chris, it’s helped him gain control over his life. This data lets him make sophisticated connections about his health. So, for example, he learned that when he’s eating in a noisy room, he tends to eat more quickly. And eating quickly makes him feel hungry again sooner.

His environment affects how he feels — sometimes negatively, but also positively.  And his analysis can help him optimize his environment to help him live a better life.

CHRIS DANCY: The other thing that happens is I have aroma therapies in my house …little diffusers that are plugged on the wall there. They’re on Wemo switches. They release scents at the same time, to slowly start getting me ready for bed. So think of it as a soft notification. At night you know around 9:30 my phone does this little lullaby so I’m like ding ding ding.


CHRIS DANCY: So it’s all about kind of getting me ready for bed.

CRISTINA QUINN: Having all of this data has helped Chris come up with a bunch of solutions. But it’s also created new questions and caused some hiccups.

CHRIS DANCY: In the beginning I signed up for like big data services like I had this thing called Flu Near You and like I’d call my doctor and say you know the flu is a block away I have it. And he was like why do you say that? Do you have any symptoms like? No, but I can tell it’s coming I’ve got the data to prove it.

CRISTINA QUINN: His doctor felt like Chris’s data was second guessing his medical training.  And so …

CHRIS DANCY: I was fired. I was fired from my first doctor. But he told me after almost 20 years of being my doctor that he didn’t want to see me anymore.

CRISTINA QUINN: Chris found a new doctor who wasn’t afraid to take on him and his data. But he’s also a little more sympathetic now, to the challenges that he can present to doctors.

CHRIS DANCY: He tells me all the time that he gets quote unquote Fitbitted. So patients come in with their weaponized you know Fitbit data and say give me Ambien. Look at this. Or you know I need fat pills. Look at this. I always tell people I wasn’t wrong, I was just early.

CRISTINA QUINN: Chris has decided that he’s not going to let any of the data around him go to waste. He’s going to collect every last bit and use it to optimize his life. There are lots of people like Chris. This is a movement.  It’s called the quantified self and it includes a range of folks – from people who track their steps every day to people who measure themselves to the nth degree like Chris.

The term “quantified self” was coined by journalist Gary Wolf.

GARY WOLF: To know thyself functioned both as a mandate and also a warning.

CRISTINA QUINN: This is Gary. He’s been working in the quantified self movement for over 10 years, and organizes meet-ups around the world where, people come together to discuss experiences, tools, and methods in what’s often called “life-logging.”

Gary’s a big advocate for folks who collect data about themselves, and then create and test hypotheses. He believes that people like Chris Dancy could eventually produce scientific knowledge that benefits everyone if only there was a way to share and discuss their results.

GARY WOLF: Where for instance do those discoveries get published and how do they get disseminated? Not everybody who makes those discoveries is going to be a Ph.D. or an M.D. or aspire to publish in an academic journal. That doesn’t mean that their discoveries don’t need to be shared.

CRISTINA QUINN: And then there’s the flip side — maybe someone thinks they’ve discovered something cool, and they start telling everyone to change their behavior, but it’s just based on the study of one single person, doing a self-experiment.

GARY WOLF: We all benefit from having other people see our work and having it critically read. So, not only are there new tools, there are new people and the new tools and the new people together require a new infrastructure for making medical knowledge.

CRISTINA QUINN: Ultimately, the sample sizes of the experiments run by life loggers like Chris Dancy are too small to mean much. But Chris is onto something — for decades, scientists have been sampling the environment to monitor the spread of diseases and their carriers. It’s an idea that’s MOST powerful when you’re looking at data in the aggregate.  You know — a bunch of small pieces of information that reveal a pattern when you look at them together.  You’ve heard of this – it’s called BIG DATA.

ETHAN JACKSON: Yeah, so I’m Ethan Jackson. I’m the lead researcher at Microsoft for Project Premonition.

Project Premonition — the name sounds kind of spooky but what Ethan’s team is doing is trying to level up the way we detect epidemics because right now, the process is kind of slow.

ETHAN JACKSON: Today we detect epidemics after they’ve started when people are starting to show up at the hospital. And that detection is typically too far along in the epidemic to really to really stop it, particularly for diseases we haven’t seen before. You know developing a vaccine typically takes years even if we have a vaccine or some treatment that may work. Deploying it to enough people is very difficult to do once it’s already been detected in the hospital.

CRISTINA QUINN: So, Ethan’s team is using tools like cloud computing, machine learning and robots to track pathogens before they start showing up in people. Because diseases that turn into epidemics don’t come out of thin air — 60 to 75 percent of emerging diseases are caused by pathogens found in animals.  So to find out what diseases humans might get — you need to find out what diseases animals already have.  And the best way to do that? With blood.

But researchers can’t practically run around drawing blood from every woodland creature. Luckily, nature is already doing that.

ETHAN JACKSON: Nature invented the mosquito. It’s incredibly effective at sneaking around in the middle of the night, finding an animal, taking a blood sample and escaping. So we start to ask the question could we use mosquitoes as devices as part of the system that would go out into the environment and bring us back blood samples from animals that are hiding.

CRISTINA QUINN: As you may well know, mosquitoes regularly draw blood– in fact, they’re one of the ways that pathogens make their way from animals to humans — so if you can test the blood that mosquitoes bring back, and figure out where the mosquitoes were, you can determine what pathogens are in the environment.

But standard mosquito traps aren’t great — they trap all sorts of bugs that scientists don’t need. So, Ethan’s team went to the jungles of Grenada to learn how to build a better mosquito trap.

ETHAN JACKSON: Basically have this big bag of bugs. It has all sorts of things. A small percentage of those is mosquitos. And that’s one of the challenge in monitoring mosquitoes today is that you have a very complex mixture of insects that could potentially appear and you need actually a very skilled person to separate out the specimens that are interesting and the specimens that aren’t interesting.

CRISTINA QUINN: That’s really labor intensive. And moving the traps to where the more interesting mosquitoes are is also labor intensive.

Project Premonition is trying to build a smarter trap. With the help of a drone, the plan is to fly the smart trap to where mosquitoes are most likely to hang out. In the future, Ethan hopes the smart trap and drone will become one.

ETHAN JACKSON: It’s a sort of robotic field biologist that understands the insects that are flying around it in real time. It can tell them apart and make a decision about whether it wants to capture a specific insect or ignore one.

CRISTINA QUINN: Ethan says there’s been an “inflection point” in epidemic research. Three technologies are radically improving our ability to predict what pathogens will jump from animals to humans. The first:

ETHAN JACKSON: There’s been an explosion of systems that can go in the environment and collect new data sets.

CRISTINA QUINN: The second technology is gene sequencing. So, being able to extract genetic material from a biological sample, like a mosquito, and then turning it into digital data. That process is much faster and cheaper than it used to be.

And the third:

ETHAN JACKSON: The third of course is cloud computing and machine learning, which allows us to take very large data sets and then reason about them in very complicated ways. I think when you put those three trends together it points towards better technologies to try to address a very complicated problem, which is predicting the movement of potential pathogens in space and time before they cause outbreaks in people.

CRISTINA QUINN: The hope is that someday class="emdash-wrap">systems—like Project class="emdash-wrap">Premonition—will be able to collect and analyze enough data from the environment so they can predict an outbreak, like a weather forecast, but for human diseases.

ETHAN JACKSON: If the temperature is like this and the humidity is like that and you’re in this location then you really have a high risk of possibly encountering a mosquito that might be dangerous. If you want to think about it like a map that changes in space and time like a weather forecast something that lets you wrap your head around what’s going on in the environment at a much larger scale.

CRISTINA QUINN: Ethan’s team is using big data to analyze biological information. But for some people, there can be a big gap between what we know about our bodies, and what we want to know.

That applies in particular to people looking to start families. For many of us, fertility is still a black box.

One woman is trying to change that.

RIDHI TARIYAL: I if I found out if I had a lower number of eggs than I should for my age group and ethnicity….maybe I would spend more time improving my dating profile.

CRISTINA QUINN: This is Ridhi Tariyal, and the reason she’s talking about her dating profile is because of how many eggs she has. Her fertility was the genesis of her company. She’s the CEO of NextGen Jane, a company that’s developing a way to help women track their own health and fertility without going to a doctor or a clinic.

Ridhi is an example of someone who’s hoping to use data to be proactive about health. To get information to help people plan and manage their lives, rather than just responding to health crises.

Ridhi was 33 years old, single with no children, and wanted to know how much time she had left to have kids. Did she really have to spruce up her dating profile? But when she went to her doctor with that question — the fertility one, not the dating one — the answer was disappointing.

RIDHI TARIYAL: I thought this would be an easy conversation and I asked her if there was some way I could help sort of mitigate my fears about you know how much longer I had to have kids and she said she didn’t know of anything.

CRISTINA QUINN: Ridhi couldn’t believe that was really true, so she went home and did some research. She found out there is a test – that measures what’s called the Anti-Mullerian class="emdash-wrap">Hormone—also known as AMH. Low AMH levels could indicate that a woman’s fertility is declining faster than average. So, Ridhi went back to her doctor to ask for the test.

RIDHI TARIYAL: Her response was I can’t prescribe that test to you until you’ve proven to me that you actually  are infertile meaning you have to go and try to have a child for a year and be unable to do so and then we’ll say you’re infertile and then insurance will start paying for your testing.

CRISTINA QUINN: Her doctor wouldn’t do the test. She could get the test at a fertility clinic but that was expensive too, and just on principle, it seemed weird to not be able to access information that was already in her body. It was frustrating, but also, it was perfect. Ridhi has a degree in “biomedical enterprise” — basically an MBA degree that allows students to focus on biomedical problems. And she was looking for a business problem to solve.

This was it — helping other women be more proactive about getting their data could be the foundation of a business. She just needed to figure out a way to make AMH readings easilyaccessible to women.

To do all of that – first, she would need blood.

RIDHI TARIYAL: There are moments where I had band aids on every finger because when we were trying to prove out whether or not you could you know use finger stick blood instead of venous blood. We needed a certain quantity of blood and I couldn’t get it with one finger stick, so I would poke myself 10 to 12 times.

CRISTINA QUINN: Venous blood is the blood from inside your veins, and getting it at home isn’t feasible for most people. So Ridhi mulled it over and realized there already was a way to get a large volume of blood. Every month. It occurred to Ridhi that what she needed was a “smart tampon.” Or rather, just a normal tampon and a “smart process” to test menstrual blood, for AMH. She would take something routine — like a period — and then turn it into a way to gather information.

Ridhi had solved the research problem. She’d solved the blood problem. But there was one more problem — the icky problem.

RIDHI TARIYAL: I called a really prominent lab who shall remain unnamed, and we told them what we were doing and we told them we’re using a tampon to do it. And they basically said you should stop now because no lab in America would ever touch a dirty tampon.

CRISTINA QUINN: Again, it was so frustrating. The data was right there! But she couldn’t get to it.

RIDHI TARIYAL: We probably spent a night reveling in anger and then you know got up and said cool. It’s great if nobody else wants to do it. From a business perspective. We’d love that monopoly.

CRISTINA QUINN: NextGen Jane is about to do a third clinical trial of the smart tampon testing system. Ridhi’s goal is to have the technology refined, and available by 2021.

She’s hoping to raise at least 50 million dollars to bring the product to market — 50 million! It  seems kind of insane at first, but not when you consider that fertility is a huge factor for people who want families.

RIDHI TARIYAL: As an individual woman it’s really helpful in helping to lower my anxiety and I think that over time there’s going to be a need for women in general to become much more active agents in making these these tradeoffs and decisions about fertility

CRISTINA QUINN: Ridhi’s part of a movement of engineers and designers trying to unlock information that can help people not just have better health — but better lives.

RIDHI TARIYAL: This mommy tax that that women pay, a lot of social scientists, when they break it down and read the difference in gender pay actually comes down to the type of jobs women are choosing as well as the ability to have temporal flexibility in these jobs which both of these decisions are driven by the fact that they are the primary caretakers of both their children and their parents, and so they need more flexible hours and less demanding jobs.

CRISTINA QUINN: Having more precise data about your fertility before you ever want to have children means more control. It means being able to predict exactly when you’ll need more flexibility in your job. In the aggregate, giving women access to this kind of data and planning, could help get rid of that mommy tax and the pay disparity across gender.

Ending the wage gap is a lot to expect from a tampon. But it’s steps like these that get us closer to escaping what Ziad Sankari calls “the dark ages of data in medicine.”

ZIAD SANKARI: This is a true class="emdash-wrap">concern—helping people know what’s not otherwise easily decipherable from their bodies.

CRISTINA QUINN: Ziad is the founder of CardioDiagnostics.The company makes software that allows doctors to monitor a patient’s cardiac data in real time, remotely, because cardiac events tend to strike suddenly without warning.

With CardioDiagnostics, people can get similar monitoring to what they’d get in a hospital, without having to be in a hospital. Folks can go about their day, meet friends, play tennis, all under the watchful eye of remote medical personnel, and advanced algorithms.

The company works in conjunction with doctors because their medical knowledge is really important for interpreting data. But Ziad’s also hoping for a time in the near future when we’re all a little better at interpreting our own data.

Ziad compares our current relationship with data to the Dark Ages, when the Bible was locked up in a language that only certain people could access: Latin.

ZIAD SANKARI: in the Middle Ages, it was very difficult for people to read Latin, so people needed the help of priests to understand what God said in the Bible. And I see that we have a comparable scenario nowadays.

CRISTINA QUINN: Where we now may be akin to the moment when people said “Hey, we want that information! We want to read the Bible for ourselves!”

ZIAD SANKARI: Medicine is extremely difficult and only few people can read the data and it’s typically physicians and providers. We want to be able to use technology to make it easier for people to learn how to read the data and how to manage themselves easier and more efficiently. And once you do that that’s the true revolution in technology and healthcare.

Because once you’re empowered, you can make changes…big changes.

Dot-future is a co-production of Microsoft Story Labs and Gimlet Creative.

We were produced this week by Garrett Crowe and Katelyn Bogucki, with help from Victoria Barner, Frances Harlow, Nicole Wong, Abbie Ruzicka, Julia Botero and Jorge Estrada. Creative direction from Nazanin Rafsanjani. Production assistance from Kimberly Green, Ben Kuebrich and Thom Cody.

We were edited by Rachel Ward. Sound design and mix by Zac Schmidt. Our theme song was composed by The Album Leaf. Music from Whaltho, Lullatone and Marmoset.

Special thanks to Mark Drangsholt and Deborah Lupton.

Coming up next on dot-future …

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To learn more about the show, go to That’s d-o-t future dot net.

I’m Cristina Quinn. Thanks so much for listening!