WEBVTT - Gift Cards for Your DNA Data

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<v Speaker 1>Selecting and selling your data. Data is the new natural

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<v Speaker 1>resource of our time. That's the most sought after information

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<v Speaker 1>on the black market now was more and more patient

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<v Speaker 1>information is shared on the internet. The lists are being sold.

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<v Speaker 1>We don't know who is buying them. It's not just

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<v Speaker 1>Facebook's Google, it's Amazon. It's also insurance companies, retail companies.

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<v Speaker 1>Believe it or not, when you go to the doctor,

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<v Speaker 1>the data from that doctor's visit is often sold to

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<v Speaker 1>companies that have nothing to do with treating any illness.

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<v Speaker 1>Electronic records companies, labs, pharmacies, insurers. They're all selling intimate

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<v Speaker 1>data about you. It's not only big data, but big business.

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<v Speaker 1>Welcome to Prognosis, bloom Brigs podcast about the intersection of

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<v Speaker 1>health and technology and the unexpected places it's taking us.

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<v Speaker 1>I'm your host, Michelle fay Cortes. This week, we're looking

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<v Speaker 1>at a new kind of healthcare data broker. These companies

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<v Speaker 1>don't just want to sell your data. They're also willing

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<v Speaker 1>to pay you for it. But that's not really the point.

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<v Speaker 1>Stay with us and we'll tell you what these companies

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<v Speaker 1>are really after. Here's Bloomberg's health reporter Kristen B. Brown

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<v Speaker 1>with the story. Okay, So I'm going to log into

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<v Speaker 1>my Nebula account and see more opportunities there are for

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<v Speaker 1>me to make some money off my DNA. That's the

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<v Speaker 1>sound of me hunched over my laptop on a rainy

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<v Speaker 1>Oakland afternoon, signing up to give my personal healthcare data away,

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<v Speaker 1>or rather I'm signing up to sell it. Okay. So

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<v Speaker 1>I'm going to take some surveys. Okay, So they want

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<v Speaker 1>to know approximately how often do you drink alcohol? M daily?

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<v Speaker 1>Are almost daily? Once twice a week, probably three or

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<v Speaker 1>four times for a week. Uh, how many glasses of

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<v Speaker 1>red wine do you drink? True white wine? I'm answering

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<v Speaker 1>surveys about my health on the website of a company

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<v Speaker 1>named Nebula Genomics. Nebula is one among a new breed

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<v Speaker 1>of health data brokers. Like more traditional health data brokers,

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<v Speaker 1>the company wants to profit off your data, in this

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<v Speaker 1>case by selling it to researchers, but it wants you

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<v Speaker 1>to profit off your data too. Nebula launched last fall

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<v Speaker 1>with a lot of buzz. It was spun out of

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<v Speaker 1>the lab of George Church, the Harvard geneticist as famous

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<v Speaker 1>for his work as he is throwing wild ideas out there,

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<v Speaker 1>like trying to resurrect the Wooly Mammoth Church, and many

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<v Speaker 1>others in the scientific community believe that the more people

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<v Speaker 1>share their genetic data, the sooner we will have treatments

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<v Speaker 1>and cures for devastating diseases. This is oversimplifying it a bit,

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<v Speaker 1>but the basic idea is that researchers could mine the

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<v Speaker 1>genomes of people who share the same conditions and look

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<v Speaker 1>for clues to treating those conditions, identifying the common bits

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<v Speaker 1>of their genetic code that could be linked to disease.

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<v Speaker 1>But if you want people to share their data, the

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<v Speaker 1>company reasons, you have to give them something for it.

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<v Speaker 1>This is a strategy long deployed among tech companies like

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<v Speaker 1>Facebook and Google. You give Facebook all that data, and

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<v Speaker 1>Facebook gives you access to Facebook. Nebula instead gives people

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<v Speaker 1>access to freehold genome sequencing. Eventually, it also plans to

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<v Speaker 1>offer other kinds of perks, like gift cards and money

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<v Speaker 1>for sharing your data. I caught up with Kamalabad, the

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<v Speaker 1>twenty four year old CEO of Nebula in San Francisco.

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<v Speaker 1>Our goal is, you know, can we build this essentially

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<v Speaker 1>a community of stakeholders that are willingly and transparently sharing

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<v Speaker 1>their genomic data. You know, the main interest or main

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<v Speaker 1>goal of nebulas to build data sets that enable scientists

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<v Speaker 1>to do interesting things right, whether it's rational drug design,

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<v Speaker 1>whether it's developing new use cases for precision medicine or

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<v Speaker 1>pharmaca genomics. All this relies on large scale data sets

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<v Speaker 1>that we don't really have access to today. In the

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<v Speaker 1>genomics world, Companies like twenty three and Me have figured

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<v Speaker 1>out that people will actually pay them to give away

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<v Speaker 1>their health data. Consumers shell out as much as a

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<v Speaker 1>hundred ninety nine bucks for twenty three and ME DNA test,

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<v Speaker 1>and twenty three and Me can turn around and sell

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<v Speaker 1>access to that information to pharmaceutical companies. Last year, and

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<v Speaker 1>Me into three hundred million dollar deal with Glaxo Smith

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<v Speaker 1>Klein to do just that. But Kamal says that's the

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<v Speaker 1>wrong approach. We think a pretty big flaw on the

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<v Speaker 1>existing model is that it's it's very transactional. Right. You

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<v Speaker 1>kind of swipe your credit card, you get one of

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<v Speaker 1>those spit kits, you spit in it, you send it back,

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<v Speaker 1>you get your report, and you say, you know, great,

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<v Speaker 1>that's it. Um what we want to incentivize people to

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<v Speaker 1>do is come back over time, learn more about themselves,

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<v Speaker 1>and share more information. That way, we can build a

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<v Speaker 1>longitudinal view of somebody's health. Nebula wants to track your

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<v Speaker 1>health over time to keep users coming back so that

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<v Speaker 1>researchers can get a more complete picture of it a

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<v Speaker 1>better data set. My own longitudinal health journey started with surveys,

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<v Speaker 1>lots of surveys. I took a survey about cancer. Have

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<v Speaker 1>I ever been diagnosed with cancer? No? And what about

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<v Speaker 1>my diet? How many tables means have cooked vegetables do

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<v Speaker 1>I eat first today? Table spoons? And my exercise habits?

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<v Speaker 1>How many days you walk for at least ten minutes

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<v Speaker 1>in a simple whole week. I like every day I

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<v Speaker 1>walked from the bar ten minutes. I gave no feel

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<v Speaker 1>information about my drinking habits and my medical history. I

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<v Speaker 1>also uploaded my twenty train MEE data, which gives the

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<v Speaker 1>company access to really intimate information about me, like whether

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<v Speaker 1>I'm at risk for Alzheimer's or diabetes. At the end

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<v Speaker 1>of all this, I had earned six hundred and fifty

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<v Speaker 1>credits of the one thousand credits you need to get

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<v Speaker 1>a free low grade whole genome sequencing instead of going

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<v Speaker 1>through all this. By the way, you can also just

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<v Speaker 1>buy the sequencing from Nebula for a hundred bucks. Recently,

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<v Speaker 1>the company also launched a subscription service, which gives you

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<v Speaker 1>access to things like new research about your genome and

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<v Speaker 1>priority to participate in research studies. Another pitch the company

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<v Speaker 1>makes is that if a researcher finds your information interesting,

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<v Speaker 1>they might pay for a clinical grade sequencing and share

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<v Speaker 1>that data with you. Comal told me that eventually there

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<v Speaker 1>will also be opportunities to improve your own health by

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<v Speaker 1>participating in research studies that, for example, give part have

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<v Speaker 1>spens wearables to track things like heart rate. But as

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<v Speaker 1>I was filling out all those surveys, I got the

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<v Speaker 1>distinct feeling that I probably wasn't all that interesting to researchers.

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<v Speaker 1>I exercise, I eat pretty well most of the time,

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<v Speaker 1>and my family has no history of inherited disease other

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<v Speaker 1>than really bad eyesight and pretty average health wise. Usually

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<v Speaker 1>people's data is only valuable and aggregate when combined with

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<v Speaker 1>data from millions of other people. Health data brokers are

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<v Speaker 1>nothing new. They've actually been around since the nineteen fifties,

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<v Speaker 1>but computers and then the Internet turned health data brokerage

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<v Speaker 1>into a multibillion dollar business. Here's how it works. Companies

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<v Speaker 1>collect de identified data from millions and millions of people,

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<v Speaker 1>often paying pennies per record your blood test results, hospital records,

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<v Speaker 1>prescription information. It all gets stripped of your name and

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<v Speaker 1>sold by data broker middleman like a c A pharmaceutical

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<v Speaker 1>company can buy access to your records to better sell

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<v Speaker 1>you drugs, even as it might be difficult for you

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<v Speaker 1>to get a copy of your own health care records

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<v Speaker 1>from your doctor. And the practice, by the way, is

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<v Speaker 1>totally legal under hip hop, the law that's been on

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<v Speaker 1>the book since nine to protect patient privacy. I talked

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<v Speaker 1>to Adam Tanner, who wrote a book about this. He

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<v Speaker 1>was on a cruise ship off the coats of Vietnam

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<v Speaker 1>when we talked. You go to the doctor's office, You

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<v Speaker 1>close the door. You expect only the doctor will know

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<v Speaker 1>what I'm telling about my health condition. But the doctor

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<v Speaker 1>is often recording onto a computer the details of the

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<v Speaker 1>of the patient's condition, and that's good to keep records

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<v Speaker 1>on what patients are about. Many of those systems, however,

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<v Speaker 1>those computer systems that connect doctors with hospitals and pharmacies

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<v Speaker 1>and so on. Many of them sell anonymized data about patients,

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<v Speaker 1>so it doesn't have your name in it, but it says,

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<v Speaker 1>here is a woman this age, living in this part

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<v Speaker 1>of town, and it joins records about you then with

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<v Speaker 1>other previous records about you. Adam told me that this

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<v Speaker 1>business really took off when records became digital. And digitization

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<v Speaker 1>of medicine is a good thing in general because it

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<v Speaker 1>keeps detailed records about you, but it has allowed this

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<v Speaker 1>side business to establish itself in the shadows that most

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<v Speaker 1>patients do not see, do not have a say in uh,

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<v Speaker 1>and indeed many health professionals don't know about this. Data

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<v Speaker 1>mostly gets used for marketing, and some of it can

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<v Speaker 1>be pretty intimate or embarrassing, even though it's stripped of

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<v Speaker 1>your name. These medical data dossiers usually include gender, age,

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<v Speaker 1>and partial zip codes. Studies have shown that it's not

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<v Speaker 1>always that hard to identify people based on it. One

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<v Speaker 1>should be concerned because health information is often our most

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<v Speaker 1>intimate information. You could be discriminated against the work, You

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<v Speaker 1>could be discriminated against socially. Once this kind of information

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<v Speaker 1>is out there in the ether, you can't put it back. Forever,

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<v Speaker 1>and just knowing this basic information could be damaging to you,

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<v Speaker 1>and it could be something relatively trivial. Adam makes a

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<v Speaker 1>good point here in his book, he talks about how

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<v Speaker 1>the actor Charlie Sheen wound up paying millions in bribes

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<v Speaker 1>to keep his own HIV diagnosis private. For those of

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<v Speaker 1>us that aren't famous, there is risk to life insurers,

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<v Speaker 1>for example, if they access this data, would legally be

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<v Speaker 1>allowed to discriminate against you based on it. But Adam

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<v Speaker 1>told me he could also imagine some less obvious ways

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<v Speaker 1>this data could be incriminating. I remember attending just a

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<v Speaker 1>few years ago a lecture at the university and the

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<v Speaker 1>woman was showing some videos on the internet, uh to

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<v Speaker 1>demonstrate a point in her lecture, and off to the

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<v Speaker 1>side of a YouTube video she was showing there was advertisement,

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<v Speaker 1>are you depressed? We have the answer to your mental

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<v Speaker 1>health issues. Um. Now, it could be a coincidence that

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<v Speaker 1>those ads were served, but I can't erase from my

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<v Speaker 1>mind the image that this is a person that may

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<v Speaker 1>have had that issue. At a time when Facebook and

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<v Speaker 1>Amazon and Google have woken people up to the value

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<v Speaker 1>of their data, this new crop of companies that want

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<v Speaker 1>to pay you for your data, are exploiting frustration with

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<v Speaker 1>this model. Here's comal again the way the process exists today,

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<v Speaker 1>no one is really winning except for these these intermediary

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<v Speaker 1>data brokers. So I think this idea of let's let's

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<v Speaker 1>empower patients to aggregate, curate, and share their their health

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<v Speaker 1>data is something that's becoming more common and more mainstream.

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<v Speaker 1>This is language you hear a lot in this world.

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<v Speaker 1>The websites for these companies are filled with trust inspiring

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<v Speaker 1>words like transparency and privacy. They promised control and ownership

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<v Speaker 1>over your data. They also suggest that your data will

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<v Speaker 1>be put to better use. The data bought and sold

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<v Speaker 1>by traditional healthcare data brokers is often riddled with errors

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<v Speaker 1>and without some serious looting, The people using I have

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<v Speaker 1>no way of following up with the people the data

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<v Speaker 1>come from if they want to ask follow up questions.

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<v Speaker 1>It also hasn't really delivered the scientific or medical benefits

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<v Speaker 1>that it could. Like I mentioned earlier, it mainly gets

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<v Speaker 1>used for commercial purposes. But I wondered if giving your

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<v Speaker 1>data away can ever really be an empowering move. Another

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<v Speaker 1>company I gave my data to Luna DNA actually got

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<v Speaker 1>permission from the Securities and Exchange Commission to give users

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<v Speaker 1>shares of the company in exchange for data. Luna's pitch

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<v Speaker 1>made me think of Facebook again and how surprised Facebook

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<v Speaker 1>users were when they realized exactly how their data was

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<v Speaker 1>being used, how they were paying for using the site.

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<v Speaker 1>Luna CEO Bob Kane told me that giving people an

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<v Speaker 1>ownership stake helps them trust that their data isn't being misused.

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<v Speaker 1>Our data is very much ours. It's as unique as

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<v Speaker 1>anything can get to defining us, and so it's one

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<v Speaker 1>of those rights that nobody can take away from us.

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<v Speaker 1>Una has set up a complicated corporate structure in order

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<v Speaker 1>to make this happen. The database itself is actually a

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<v Speaker 1>subsidiary of Luna, and that is what people get shares of.

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<v Speaker 1>Since soft launching earlier this year, the company has been

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<v Speaker 1>busy building partnerships with groups like Rare Disease Foundations, hoping

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<v Speaker 1>patients with those diseases will contribute data and eventually lead

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<v Speaker 1>to treatments. And when the database turns a profit by say,

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<v Speaker 1>selling information to researchers, everyone gets a cut. Yes, so

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<v Speaker 1>those shares are yours. They're non transferable because we don't

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<v Speaker 1>think you can transfer the right to control your data,

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<v Speaker 1>and they really represent your data in this system, and

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<v Speaker 1>you're consenting for your data to be used at a

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<v Speaker 1>population level to help researchers answer sort of higher level

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<v Speaker 1>questions about links between your genome and your health or

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<v Speaker 1>social determinants of health. How they're used is when we

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<v Speaker 1>sign up with a commercial company, for instance of pharma,

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<v Speaker 1>and they pay us to access to database. The proceeds

0:14:01.480 --> 0:14:04.839
<v Speaker 1>will be shared with the community based on your ownership.

0:14:05.480 --> 0:14:08.480
<v Speaker 1>I signed up for a Luna DNA account. I answered

0:14:08.480 --> 0:14:10.920
<v Speaker 1>a few surveys about my health and shared my twenty

0:14:10.960 --> 0:14:14.959
<v Speaker 1>three and me data. For that, I got fifty four shares.

0:14:15.640 --> 0:14:18.960
<v Speaker 1>According to Luna's filing with SEC. Each of those shares

0:14:19.000 --> 0:14:23.200
<v Speaker 1>are currently worth about seven cents. Based on those numbers,

0:14:23.320 --> 0:14:29.640
<v Speaker 1>your whole genome would be worth one dollars. There are

0:14:29.680 --> 0:14:33.880
<v Speaker 1>constantly new companies like Luna and Nebula popping up, and

0:14:33.920 --> 0:14:37.040
<v Speaker 1>I shared my data with a bunch of them. I

0:14:37.120 --> 0:14:39.640
<v Speaker 1>really wanted to get a sense of the entire landscape,

0:14:40.120 --> 0:14:42.080
<v Speaker 1>to see what you can get when you give your

0:14:42.080 --> 0:14:47.240
<v Speaker 1>own data away. Doc do AI gives people Amazon gift

0:14:47.240 --> 0:14:51.400
<v Speaker 1>cards for sharing data and participating in trials. I didn't

0:14:51.400 --> 0:14:54.200
<v Speaker 1>get anything for uploading my genome, and one of the

0:14:54.240 --> 0:14:57.160
<v Speaker 1>trials I enrolled in a waitlist for would only earn

0:14:57.240 --> 0:15:00.200
<v Speaker 1>me thirty of the one thousand points I would need

0:15:00.240 --> 0:15:04.160
<v Speaker 1>to get a ten dollar Amazon gift card. Another company,

0:15:04.160 --> 0:15:07.640
<v Speaker 1>in Blima, charges people to securely store their records on

0:15:07.680 --> 0:15:11.240
<v Speaker 1>the blockchain, but you can also earn cryptocurrency for sharing

0:15:11.240 --> 0:15:16.040
<v Speaker 1>your data. Yet another, Humanity dot co, pitches itself as

0:15:16.080 --> 0:15:19.440
<v Speaker 1>a go between brokering data for its users and helping

0:15:19.480 --> 0:15:23.600
<v Speaker 1>them get it cut. On the company's app and YouTube channel,

0:15:23.800 --> 0:15:27.280
<v Speaker 1>there were all these testimonials from people proclaiming that ownership

0:15:27.320 --> 0:15:30.560
<v Speaker 1>of data is a human right. I want to own.

0:15:30.640 --> 0:15:34.600
<v Speaker 1>I want to own my data. I want to earn

0:15:34.640 --> 0:15:38.560
<v Speaker 1>my data as my property because right now it is

0:15:38.640 --> 0:15:42.640
<v Speaker 1>quite unclear. But Humanity, like the other companies, is also

0:15:42.720 --> 0:15:45.840
<v Speaker 1>pretty early stage. There wasn't much I could do besides

0:15:45.880 --> 0:15:49.840
<v Speaker 1>pledge my enthusiasm for the idea. My little data brokering

0:15:49.880 --> 0:15:52.440
<v Speaker 1>experiment was starting to feel less like a mission of

0:15:52.440 --> 0:15:57.240
<v Speaker 1>self empowerment and more like a waste of time. I

0:15:57.280 --> 0:16:00.680
<v Speaker 1>talked with George Contreris, a law professor at the University

0:16:00.680 --> 0:16:03.640
<v Speaker 1>of Utah who thinks a lot about these things. He

0:16:03.800 --> 0:16:07.560
<v Speaker 1>was also skeptical. I mean the cynical view is that

0:16:07.640 --> 0:16:12.840
<v Speaker 1>these companies are cropping up so that they can monetize

0:16:12.880 --> 0:16:15.440
<v Speaker 1>the data, right, I mean, not not so that patients

0:16:15.560 --> 0:16:19.640
<v Speaker 1>can profit from the use of their health data, so

0:16:19.720 --> 0:16:23.040
<v Speaker 1>that these companies can become intermediaries and take a slice

0:16:23.760 --> 0:16:27.480
<v Speaker 1>of every data transaction that comes along. All of the

0:16:27.520 --> 0:16:30.280
<v Speaker 1>companies I talked to told me that people really shouldn't

0:16:30.320 --> 0:16:33.520
<v Speaker 1>be in it for the rewards anyway. It's about helping

0:16:33.520 --> 0:16:36.960
<v Speaker 1>the progress of science and medicine, and they want to

0:16:36.960 --> 0:16:40.200
<v Speaker 1>do it more transparently and in doing so also collect

0:16:40.280 --> 0:16:44.240
<v Speaker 1>higher quality data. But it's not the collecting health data

0:16:44.440 --> 0:16:49.200
<v Speaker 1>doesn't have legitimate justifications. George said, there's a doctor's office

0:16:49.200 --> 0:16:54.120
<v Speaker 1>and twenty people show up with the same strange flu symptoms.

0:16:54.280 --> 0:16:57.280
<v Speaker 1>We we want that doctor's office to report that to

0:16:57.320 --> 0:17:00.560
<v Speaker 1>the c DC, and we want them to figure out

0:17:00.560 --> 0:17:03.600
<v Speaker 1>what's going on and then to develop a vaccine. There

0:17:03.640 --> 0:17:08.400
<v Speaker 1>are a million contexts where it's important for health care

0:17:08.400 --> 0:17:12.199
<v Speaker 1>providers to be able to provide data. His issue was

0:17:12.240 --> 0:17:15.119
<v Speaker 1>more that this new breed of data brokers could actually

0:17:15.119 --> 0:17:18.680
<v Speaker 1>wind up making things more complicated by starting to treat

0:17:18.760 --> 0:17:22.600
<v Speaker 1>data like legal property. If your data is legal property.

0:17:22.880 --> 0:17:24.880
<v Speaker 1>All of a sudden, there are all these new issues,

0:17:25.000 --> 0:17:28.560
<v Speaker 1>like asking permission every time someone wants to use it

0:17:29.160 --> 0:17:32.560
<v Speaker 1>and figuring out things like who controls your data when

0:17:32.560 --> 0:17:35.800
<v Speaker 1>you die. If you are in a situation where the

0:17:35.880 --> 0:17:40.640
<v Speaker 1>centers for disease control, or hospitals or pharmaceutical companies vaccine

0:17:40.680 --> 0:17:44.960
<v Speaker 1>companies needed to figure out how to pay somebody every

0:17:45.000 --> 0:17:48.040
<v Speaker 1>time they wanted to use some data, you know the system.

0:17:48.240 --> 0:17:52.040
<v Speaker 1>The system would a become much less efficient and fee

0:17:52.040 --> 0:17:54.920
<v Speaker 1>would be come much more expensive. Both of those are

0:17:54.920 --> 0:17:59.160
<v Speaker 1>not good for public health, George said. Ironically, in this

0:17:59.200 --> 0:18:02.200
<v Speaker 1>new model, people might wind up giving away even more

0:18:02.320 --> 0:18:07.040
<v Speaker 1>information and having fewer protections for it. They're better protected

0:18:07.160 --> 0:18:10.520
<v Speaker 1>under the current system with HIPPA than they are with

0:18:10.720 --> 0:18:15.520
<v Speaker 1>these data brokers, who you know, are pretty uncontrolled, unregulated,

0:18:15.720 --> 0:18:20.040
<v Speaker 1>and you know you you basically just have to trust them,

0:18:20.080 --> 0:18:24.280
<v Speaker 1>although they're you know, they're really just profit oriented startups

0:18:24.320 --> 0:18:28.359
<v Speaker 1>at this point. Um so I would honestly rather trust

0:18:28.359 --> 0:18:31.760
<v Speaker 1>my hospital than than one of these data brokers to

0:18:32.520 --> 0:18:35.640
<v Speaker 1>use my data properly. I talked with a few other

0:18:35.720 --> 0:18:39.679
<v Speaker 1>experts in the space though that disagreed with George. Adam,

0:18:39.920 --> 0:18:42.280
<v Speaker 1>the guy who wrote the Health Data Book, and Eric Topol,

0:18:42.440 --> 0:18:45.439
<v Speaker 1>a geneticist who has written a lot about patient access

0:18:45.480 --> 0:18:49.520
<v Speaker 1>to data, both told me they were actually optimistic, so

0:18:49.560 --> 0:18:53.000
<v Speaker 1>long as these companies are transparent and give people choices

0:18:53.119 --> 0:18:56.600
<v Speaker 1>and how their data is used, the point of collecting

0:18:56.640 --> 0:19:00.000
<v Speaker 1>all this data, after all, to help advance science and medicine,

0:19:00.000 --> 0:19:04.120
<v Speaker 1>and to find cures for devastating diseases and understand more

0:19:04.200 --> 0:19:07.520
<v Speaker 1>about how the human body works. It's hard to argue

0:19:07.560 --> 0:19:12.040
<v Speaker 1>with that. But in reporting this story, I couldn't help

0:19:12.080 --> 0:19:15.920
<v Speaker 1>think about another story, the now famous story of Henrietta Lacks.

0:19:16.880 --> 0:19:19.479
<v Speaker 1>Henriette A. Lacks was a black woman who died of

0:19:19.520 --> 0:19:22.439
<v Speaker 1>cancer in the South in the nineteen fifties after getting

0:19:22.480 --> 0:19:26.720
<v Speaker 1>pretty lacking medical treatment, But doctors harvested her cells, which

0:19:26.760 --> 0:19:30.280
<v Speaker 1>turned out to have some special characteristics. They didn't die.

0:19:31.440 --> 0:19:34.919
<v Speaker 1>The HeLa cells proved invaluable to medical research, and with

0:19:34.960 --> 0:19:38.640
<v Speaker 1>their help, many companies got rich. Well. Henrietta's family, at

0:19:38.640 --> 0:19:42.000
<v Speaker 1>times barely got by. What if the genome you were

0:19:42.000 --> 0:19:45.120
<v Speaker 1>paid twenty one for winds up leading to a billion

0:19:45.160 --> 0:19:49.199
<v Speaker 1>dollar cure. Most of us have pretty average datum, but

0:19:49.280 --> 0:19:52.000
<v Speaker 1>some of us don't. It was one thirty two year

0:19:52.040 --> 0:19:55.880
<v Speaker 1>old aerobics instructor in the Dallas suburbs that led researchers

0:19:55.920 --> 0:19:58.680
<v Speaker 1>to a mutation in the gene pc s K nine

0:19:59.119 --> 0:20:02.359
<v Speaker 1>that seems to low or levels of bad cholesterol. It

0:20:02.480 --> 0:20:05.480
<v Speaker 1>was a finding that led multiple companies to pursue therapies

0:20:05.720 --> 0:20:09.240
<v Speaker 1>that could one day rake in billions. If our medical

0:20:09.320 --> 0:20:12.000
<v Speaker 1>data does lead to a cure, should we get a cut.

0:20:19.520 --> 0:20:21.199
<v Speaker 1>At the end of all this, I had given my

0:20:21.240 --> 0:20:24.920
<v Speaker 1>health data away too many different companies, and in return,

0:20:25.080 --> 0:20:28.800
<v Speaker 1>I'd gotten halfway to a free DNA sequencing and fifty

0:20:28.840 --> 0:20:33.200
<v Speaker 1>four shares worth seven cents of hoop. These companies all

0:20:33.200 --> 0:20:36.119
<v Speaker 1>make the argument that this was empowering, that I was

0:20:36.160 --> 0:20:40.360
<v Speaker 1>taking control of my own information. I want to help

0:20:40.400 --> 0:20:44.240
<v Speaker 1>advance medical research, but there was something disingenuous about the

0:20:44.280 --> 0:20:49.480
<v Speaker 1>suggestion that sharing my information would be beneficial to me. Instead,

0:20:49.840 --> 0:20:52.719
<v Speaker 1>it felt like I had just been complicit in harvesting

0:20:52.760 --> 0:20:56.840
<v Speaker 1>my own information for other people to profit off. I

0:20:56.960 --> 0:21:16.679
<v Speaker 1>definitely did not feel empowered. And that's it for this

0:21:16.680 --> 0:21:20.560
<v Speaker 1>week's prognosis. Thanks for listening. Do you have a story

0:21:20.560 --> 0:21:23.679
<v Speaker 1>about healthcare in the US or around the world We

0:21:23.720 --> 0:21:26.480
<v Speaker 1>want to hear from you. Find me on Twitter at

0:21:26.520 --> 0:21:29.480
<v Speaker 1>the Cortes. If you were a fan of this episode,

0:21:29.680 --> 0:21:32.119
<v Speaker 1>please take a moment to rate and review us. It

0:21:32.200 --> 0:21:36.560
<v Speaker 1>helps new listeners find the show. This episode was produced

0:21:36.560 --> 0:21:39.680
<v Speaker 1>by Liz Smith. Our story editors were Drew Armstrong and

0:21:39.800 --> 0:21:44.120
<v Speaker 1>Rick Shine. Frances Glivie is head of Bloomberg Podcasts. We'll

0:21:44.160 --> 0:21:47.440
<v Speaker 1>be back on June six with our next episode. See

0:21:47.440 --> 0:21:47.720
<v Speaker 1>you then,