Topic Archives: QS Access Conversations

Diabetes Data For All

Blip One Day

Howard Look is the Founder and CEO of Tidepool, a non-profit, open source development organization dedicated to reducing the burden of type 1 diabetes by building a platform that can integrate all diabetes device data in a single location. Most importantly, he is the father of a daughter with type 1 diabetes. Howard understands the challenges of effectively managing diabetes, and the essential role data plays in the minute-by-minute management this disease requires. The challenge, however, is finding a way to easily access and understand all of the data generated by the various devices a person with diabetes has at their disposal. What follows is an edited transcript of our conversation with Howard about how Tidepool has been addressing access to diabetes device data for the diabetes community.

QS: You’ve been busy over the last year – can you catch us up on the latest from Tidepool?

Howard: We made significant strides at Tidepool in 2014. Most notably, we announced partnerships with Asante, Dexcom, Insulet, Tandem, and Abbott Diabetes Care, all of whom gave us their data protocols. No money changed hands with these agreements, they simply understand that liberating diabetes device data is a good thing. You will notice the absence of the two largest diabetes device manufacturers from that list: Medtronic, and Johnson & Johnson, who make Animas and LifeScan products. We’re still having active conversations with them both and are hopeful that they will also enter into data protocol agreements with us.

Howard Look, Founder and CEO of Tidepool

Howard Look, Founder and CEO of Tidepool

Additionally, we’re just starting to realize the potential for our platform in the research community when you have all of the data in one place. We’re supporting a study with the Jaeb Center for Health Research and T1D Exchange, the largest coordinating organizations for type 1 diabetes studies, by putting our software in 15 of the top diabetes clinics in the United States. Our software enables researchers to access the full range of diabetes devices in one place. They are no longer restricted to only certain insulin pumps and blood glucose meters because those were the only devices whose data they had the ability to access. Now, all diabetes data is on the table and we’re showing the true value of integrating data from multiple places.

QS: Can you speak a bit more on the idea of access and how integral that idea is to the work you’re doing?

Howard: At Tidepool, the idea of access speaks to the core of what we’re trying to accomplish and promote throughout the world of health care.

From a policy perspective, we believe that the therapy data generated by these devices does not belong to the company – it belongs to the patient. It’s their personal health data. When you consider insulin delivery, blood glucose values, basal rates, carbohydrates ingested, all of these data points related to diabetes management is patient-owned data. Simply put, if you show a number on the screen for the purpose of delivering therapy, that data belongs to the patient. This is the fundamental approach we’ve taken to conversations with device manufacturers. For other data, like internal device diagnostic data, it’s fair for a device maker to consider that proprietary and we will respect that.


This approach falls perfectly in line with one of the core tenants of HIPAA: Portability of Data. HIPAA guarantees people with diabetes the right to access to their data, which makes encounters with responses along the lines of “HIPAA regulations prevent us from giving you access to this information” particularly frustrating. There is no ambiguity in my mind that it is irresponsible to not give people with diabetes access to their data. Lack of access means you are forcing people to use terrible tools to compute their own insulin doses which has the potential for horrible outcomes, which makes things worse for everyone in the health care conversation.


By liberating data, we can create an ecosystem of software and application and devices that make managing diabetes easier.


QS: What are some of the biggest challenges you face in bringing your platform to market? Are they more technical or regulatory?

Howard:  When it comes to addressing a challenge as complicated as integrating all diabetes device data in a single location, there are many technological and political barriers that put up resistance along our way. But let me be clear, regulatory matters are not one of them. Believe it or not, working on FDA documentation is not difficult, and everyone I’ve spoken with at the FDA completely understands the value in data standards and liberating data from devices.


The FDA is not the problem.


For us, the biggest barriers we face are getting access to device data protocols and funding. That’s really it. When Medtronic and Johnson & Johnson formally make their data protocols available to us, we’ll consider that a job well done, but we’re not there yet. And funding as a non-profit is a constant battle that will not surprise anyone in the Silicon Valley. We’ve done a good job addressing both of these barriers, but there’s still work to be done.

Having the support of the two biggest philanthropic organizations in the type 1 diabetes world, Juvenile Diabetes Research Foundation (JDRF) and the Helmsley Charitable Trust, has made a huge difference for us. I cannot overstate how important the support of these two groups has been to our mission. Their grants send a loud and clear message that they believe in our mission and they want this to happen. Saying things like “this is what patients want” is one thing, but when we have the backing of the JDRF and Helmsley, our mission is given much more credibility.


QS: There are a number of moving parts in the Tidepool equation – the patient community, regulatory agencies, the diabetes device manufacturers, and the researchers looking to Tidepool to make data collection easier for their work – what message do you have for these groups?

Howard: At the end of the day, my message to the patient community is keep demanding your data. It’s yours. Simple as that. Engaged patients who understand and want to be involved have better outcomes, but in order to do that you need access to data and software and tools to take care of yourself.

My message to regulators: keep doing what you’re doing. I know you understand the value in liberating data, of device data standards, of agile software development, and that access regulation gets in the way of progress and innovation, and is harmful to patients. Keep this conversation going and together we can usher in a new era of access.

To the device makers: publish your device data protocols for existing devices, adopt standards like Bluetooth Smart and IEEE 11073, adopt cloud service protocols like OAuth2 and Rest API’s to enable access to their data. I believe a rising tide raises all boats, and enabling an ecosystem of access will increase adoption of your insulin pumps and continuous glucose monitors.

And to the science community, this is the world of big data and open data, we’re going to do our part by asking our users if they will donate their data to an anonymized research database and if they want to donate their identified data to the T1D Exchange. We should be getting as much data into the research world as possible, while respecting privacy issues, and you should be part of that collective.

QS:  Do you have any final thoughts for the Quantified Self community?

Howard: Ten years ago, you had to be a multi-million dollar device company in order to do any of the things the QS community is capable of today. Now? You can buy some parts off of sites like SparkFun and build your own medical devices now. Now it’s about acknowledging that the more we enable that interconnectivity we encourage people to tinker, even with life and death things like insulin delivery, the collective intelligence of the community is going to cause great solutions to come out of all this.

For more information about Tidepool, visit and @tidepool_org.

We invite you to share your data access stories, and this article with the #qsaccess hashtag and follow along on and our Access Matters Medium publication.

Posted in QS Access, QS Access Conversations | Tagged , , , , | Leave a comment

Open Research, Open Data, Open Humans

“Open Humans aims to break down data silos in human health and research. We believe data has a huge potential to live and grow beyond the boundaries a single study or program. Our online portal allows members to aggregate data from the research they participate in. By connecting individuals willing to share existing research data about themselves with researchers who are interested in using that data, data can be re-used and built upon.” —

On March 24, 2015 the Open Humans Network officially opened their virtual doors and began allowing individuals to sign up and engage in a new model of participatory research. We spoke with Co-founder & Principal Investigator of the Public Data Sharing study, Madeleine Ball, Ph.D. about Open Humans, what it means for research, and what we can look foward to from this exciting initiative. The following is an edited transcript of that conversation.

It’s been a lot of work up to this point.

We’re grateful to have the funding support of two organizations to help get this off the ground, the Knight Foundation and the Robert Wood Johnson Foundation. It’s been a lot of work to get to this point, from hiring Beau Gunderson as our Senior Software Gardener to launching with our first three studies. We’re excited to be partnering with the Harvard Personal Genomes Project, the American Gut study, and the GoViral study. These are the seed studies, what we’ll build off of in the coming months and years. Today, we’re excited to start letting participants in these projects, and all individuals interested in participating in research, know about Open Humans.

This is an open invitation to join us.

We’re also working to make it easier for research partners to join the Open Humans Network. We’ve already started receiving interest from researchers that want to integrate with Open Humans or start working with our already growing public data sets. We’ve set parameters regarding how you have to behave as a study as well as how researchers looking to work with our members should engage with us. (You can find out more about that here.)

For members who sign up with us we’ve developed methods for them to control access to their data. Whether that is data from personal health devices and apps like Runkeeper (adding this to our next project), genetic data, or other data sources derived from participating studies, each individual member will have the ability to establish a peer-to-peer interaction. Members can allow access to some data, but not others. They may choose to release some or all of their data publicly, or the may choose to only share with one study. In the end it’s up to them and their individuals goals.


What excites me about Open Humans is the potential we have to transform future research studies — from how they treat data to how they think about data sharing. We’re building our system so that participants are central to the data process. A good example of this when researchers use our member’s data they must also agree to return any new data that results from their research back to the original participant. This decentralization of data is a key component of our design. No single person, researchers, or study has all the data.

We’ve also built in the ability for researchers to contact our members who contribute data. The idea that researchers must come up with all the right questions before starting a study is a recipe for failure. Researchers are not psychic, that can’t forsee what interesting questions might come up in the future. By opening up the ability for these connections to take place in the design of Open Humans, we’re creating the ability to continue asking questions of specific individuals, or groups of people, far in to the future.

We’re founded on the principle of transparency. You as a researcher, or participant member can see what we’re all about. You can even see our Open Human member profiles (Madeleine BallJason BobeBeau Gunderson). We worked with Marcia Hoffman, special counsel to the Electronic Frontier Foundation, to develop our Terms of Use and Data Use Policies so that they’re readable and easily understood. We want people to read them, we want them to ask us questions. We want people to be engaged and involved.

I think this work is creating a new form of data sharing that will unlock a world of new exciting possibilities. Our hope is that when participants start getting data back from studies, and have the ability to use it and share it how they wish, that participation in research will be more rewarding. This model helps participants become a respected member of the evolving research conversations happening all over world. We know a lot of people don’t participate in research, even researchers who rely on participants don’t participate in studies. Hopefully this work will help move the needle.

It’s wonderful to see the long scroll of members.

As of this writing the Open Humans Network has over 200 individuals who have created member profiles. If you’re interested in participating in open research you can learn more and sign up here. If you are a researcher or personal data company interested in integrating with Open Humans you can get in touch with the team here.

We invite you to share your data access stories, and this article with the #qsaccess hashtag and follow along here, on Medium, and @quantifiedself.

Posted in QS Access, QS Access Conversations | Tagged , , , , , , | 2 Comments

Better by Default: An Access Conversation with John Wilbanks

Photo by Joi Ito

Photo by Joi Ito

John Wilbanks is the Chief Commons Officer for Sage Bionetworks. You may not recognize John’s name or the name of his organization, but after today, you may want to commit it to memory. On March 9, 2014 Tim Cook introduced us to the idea of ResearchKit and then turned it over to Jeff Williams who described the new initiative and the five applications that were launched in collaboration with leading academic labs, advocacy groups, and research organizations. Sage Bionetworks is responsible for two of those apps, and John is responsible for leading design and development of many of the novel research tools and methods used by Sage. The following is an edited transcript of a conversation we had with John after the announcement.

Parkinson mPower App

This is Big

Think about what we’re doing in the context of it being open source. ResearchKit is going to be great for the QS community. They are perfectly suited to take advantage of ResearchKit. Let’s look at the five apps that were released today. They cover complex, but ubiquitious diseases. Plus the diseases are a great fit for the technology and sensor capabilities. But what is going to be amazing is when ResearchKit is released as open source. Anyone will have the ability to reskin these existing five apps to make novel research tools. Our Parkinson’s app might become a Huntington’s app. Our breast cancer app measures cognition really well, maybe it gets reskinned into a focused cognition tool. The app that focuses on diabetes could become a diet research app.

Large research institutions are going to jump all over this, but I’m more excited about the idea that small groups of people who have a bit of technical skill can work together to reskin the apps and turn them into longitudinal studies of 20 or 50 people. There may be five of those small groups, maybe 100. We can then work to stich those groups together and learn even more.

So the rare and chronic disease folks and the tech and QS community are involved. Now we come to everyone else. Everyone who isn’t suffering or presenting with a medical issue. We have to figure out ways to get them to participate.

We have a long tradition of creating incentives to participate. There is no reason we can’t create novel incentive methods to bring people into research. Maybe you receive a federal income tax credit. Maybe you’re allowed to enroll in long term care insurance at a reduced rate. There are a lot of ways to bring people in and that’s not touching the innate altruism of people and their curiosity. We’re already seeing this with the Precision Medicine Initiative. People want to take part, they want to engage.

Once we start getting that engagement, and we begin to see a diverse ecology of applications built on top of ResearchKit, then we’ll start to see success. It may take a bit of time. It won’t happen with this iteration. Maybe not even the second, but when we get enough devices, apps, participants, and improved interoperability between them all we’ll start to see the power of network effects.

You have to remember, there are no “killer apps” without network effects. Email wasn’t a big deal in the late 80′s because you couldn’t reach anyone outside your system. But then the web came, we connected the dots, the nodes, and then there it was, the power of the newtork.

I see QS and our current state of devices, apps, and tools being very similar to all those nerds typing away in the 80′s. They were okay with what they had because they could work with it. Then the net came and you have more control and more interefaces. That leads to the killer apps. That’s why we’re building this, for the third or fourth wave.

Share the Journey app

Everything we’re doing, the whole stack working together, is new. Consenting participants using well-designed and open-source Participant-Centered Consent toolkits. Giving participants direct access to their data. Securely hosting automatically de-identified data in the cloud using our Bridge Server. None of these have been done before at the same time.

We’re a non-profit, so we can be this icebreaker. We can take these risks and experiment and iterate and learn. No one asks us how we’re going to make money. We have a different bottom line — what is best for everyone involved? That outlook gives us the freedom to do this work.

I’m honored to have the opportunity to create a product that pushed my beliefs: participants-centric principles. If you’re a participant, then you decide. You’re in control. You can do cool stuff with the data. You can stop answering questions whenever you want. You can delete the app. We live in a world in which the politics of technology are dicteated by code and they often don’t share those ideas. To get this opportunity is amazing.

These moments don’t happen often. This is IBM going open source in the late 90s. It’s that big. I wasn’t sure I was going to be a piece of something that big. We’re trying to change culture.

In 1998 Lawrence Lessig proposed the pathetic dot theory in his book, Code and Other Laws of CyberspaceHe theorized that four forces control what we do: Law, Architecture, Social Norms, and the Market. He went futher and differentiated west coast law, which was quickly becoming dominated by software code and east coast law, what we normally think of when we think of laws.

I think up until now we’ve failed to properly take up that lever, to use software code, west coast law, to express something better. People often forget that building software means expressing an opinion. We created our apps, our tools, our systems to reflect our opinion, that participants should be at the center of research. And then we’re giving it away. That’s our position, and it’s better by default.

But, we’ve just started. The fun now is that we get to test it. I’ve always said that we can’t screw it up any worse than it already is. This isn’t the end. It’s not finished. We’re going to keep changing and learning.

John can be found online at and @wilbanks.

We invite you to share your data access stories, and this article with the #qsaccess hashtag and follow along on and our Access Matters Medium publication.

Posted in QS Access, QS Access Conversations | Tagged , , , , , , , , , , | 1 Comment

What is in My Gut?


This past fall we learned about a unique study, conducted at Stanford University, designed to contribute to the understanding of the human microbiome. This study also has a component not common to academic research — data is being returned to the participants. Intrigued, I contacted the principle investigator, Les Dethlefson, to learn more.

Ernesto: Tell me about the Dynamics of Human Microbiota study.

les_dethlefsen_at_the_benchLes Dethlefsen: Since I joined the Relman Lab at Stanford, I’ve been looking at the human gut microbiota, focusing on what affects it and how it changes over time. In our study, we are looking at three different perturbations, deliberate changes to the gut ecology, to see how the microbiota population is affected.

We are very interested in the patterns that emerge. In people who have very stable gut microbiota, does their microbiota remain that way when they undergo diet shifts, a colon cleanout, or an antibiotic? Or maybe people who have a stable gut microbiota most of the time are the ones who are most affected by something unusual such as taking antibiotics. We just don’t know enough to understand these patterns right now. So, we’re really looking for basic ecological information.

Ernesto: If you look at the popular press, it seems the microbiome is the new golden child of biological life sciences. We’re even seeing companies in Silicon Valley get involved with this kind of work.

Les: It is broader than that. It really is a worldwide interest on the parts of both the scientific community and the public. And unfortunately, we are probably going to see some overhype, just as we did with the Human Genome Project. But I do believe this is a very important area. I think there will be a lot of payoffs and health impacts from this research, although it’s not going to be everything.

The shift that, I think, would be good for us to make intellectually is to get rid of the “us vs. them” thinking, because we are symbiotic organisms.

We have evolved with a native gut microbiota, and native microbiota is pretty much everywhere. We have evolved together, so it’s fallacious — an artifact of our past ignorance — that we don’t think of our microbes as part of our physiology.

Ernesto: It seems like exploring the deep sea, an unknown world that we’re just starting to peek into.

Les: It’s along those lines. You’re not wrong about that. But unlike, let’s say, the deep waters surrounding an undersea hydrothermal vent, we already know a lot about human physiology. There are a lot of molecular details and genetic pathways that we already have worked out. The context is somewhat understood.

And now, we have a reasonable start on the initial research: What microbes are present, and where? What’s the range of what we think is the normal distribution? We certainly don’t know enough, because we only know about people in the developed world. However, this may not represent all of human diversity or a very natural state of the gut microbiota.

Candida albicans

Candida albicans

Ernesto: Let’s get back to your study. You are asking participants to send microbiome data in the form of fecal matter and urine to your lab. What are you doing with those samples?

Les: We ask participants to provide both stool and urine samples. With the stool sample, we apply four different methodologies to turn it into data. One is the very common 16S ribosomal RNA (16S rRNA) gene sequencing approach. It’s relatively standard and inexpensive. It acts like an ID card for microbial taxa — telling us approximately what strains are present and in what relative abundance. We have a lot of data like that already for comparison.

sequencerThe second approach we will be applying is metagenomic sequencing, wherein we will be sequencing a random selection of all the genomes of the microbial types that are present. We can’t take this to completion, even with the dropping cost of sequencing, especially because there are some very, very rare microbes that we barely even have the chance to see at all. But we can get a pretty good swathe of genetic sequence data from all the microbes.

The third approach is even more ambitious. It’s called metatranscriptomics. Genes can be carried by any critter, you and I included, but not expressed. Knowing which genes are turned on, and to what extent they’re turned on is a better measure of the biological activity that is actually happening. The metagenome is a measure of potential activities, what the bugs can do. The metatranscriptome shows what the microbes are actually doing. Metatranscriptomics is even more challenging than metagenomics partly because of the nature of messenger RNA (mRNA). It’s a highly unstable molecule. There are technical challenges, but we’re ambitious enough to try to collect information on gene expression.

The fourth approach is not based on gene sequences, but on chemical composition. Metabolomics is the name given to a number of these approaches that are not directed to a specific chemical. These are techniques that try to measure a broad swathe of chemicals present in the environment and their relative abundance. This is a technology that we, in the Relman Lab, know very little about. We’re collaborating with the Nicholson Lab in Imperial College in London, and they will be doing the metabolomic analyses on the stool samples. That may be even closer to where the rubber meets the road — knowing not just the gene expression but also the resulting chemical changes that are happening in the environment.

MicrobeHeatMapMetabolomics takes us to the other type of sample we’re collecting: the urine samples. We aren’t doing this because we have an interest in the urinary microbiome itself, but because, as the Nicholson Lab suggested, the urine provides a more complete, integrated picture of the co-metabolism between the human host and most of the gut microbiota. So while metabolomics for the stool samples would primarily measure the gut microbial activity and what they contribute to the host’s physiology, the urine provides a more integrated picture about how the host metabolism works in concert with the gut microbiota.

Ernesto: If a participant is going to be contributing all of that data, will they have access to it?

Les: As someone with similar interests, I certainly knew that a huge motivation for people to join the study would be the access to their own data. We offer monetary compensation, but for the amount of time that will be spent in contributing samples, it is probably trivial. We knew we would attract the curious, scientifically inclined, and practising scientists. Of course, they would want to see their data.

The Institutional Review Board (IRB) was quite open to us sharing information with the participants about their own microbiota. It probably helped that there’s publicity  about ways people can get this information. There is the American Gut project, offering an assessment of your microbiota for a donation, and uBiome, a private company offering the same kind of service.

I, or another staff member of the study, are going to share this microbiota data with each participant in a conference call. So in effect, I’m going to be a microbiota counselor. It’s nowhere near as high-stakes as sharing genome information. We don’t know enough to say, for example, that this microbiome is definitively healthy, or that it’s unhealthy, or what the exact risks of diseases are due to this particular composition. So we will be putting this information in context, and we will be available as interpreters of the scientific literature. We may be able to say that there is a statistical association between a particular microbial group that someone may have in their gut and some health-related outcome.


Microbiome sequence data

Ernesto: Will participants be getting a copy of their data as well?

Les: Yes, we will provide that. I have an open source mentality. Added to that is the fact that there are many practicing scientists signing up for the study and saying they want data, not just a PDF summary. I am happy to provide the data in as raw a format as people want. They can get the raw sequence information, a low-level summary (which is the result of the first pass of data processing), or the final summary. I have permission and full intention to share all the data derived from a person’s samples with that person.

Ernesto: Do you think we will see this happening more in the future?

Les: I think we will probably see more of it in the future. We’re moving in the direction of access to information. The open source movement has reached the health and medical realm from its origins in tech and computing. I think the participatory nature of access to data and scientific information is a good thing. It has started, and I don’t see any way of reversing the trend. I would hope that it becomes the norm that there is some appropriate level of sharing, that research participants have access to their data if they wish, and in a way that lets them interpret that data appropriately.

I believe that people have a right to that level of knowledge about their bodies, and if we, scientists, are generating that knowledge, there’s no reason not to share it with the individuals.

The Dynamics of Human Microbiota study is currenlty recruiting participants. If you’re interested in learning more about the ecosystem within read more about the study and check to see if you’re eligible to participate here.

We invite you to share your data access stories, and this article with the #qsaccess hashtag and follow along on and @quantifiedself.



Posted in QS Access, QS Access Conversations | Tagged , , , , , , , , , , | Leave a comment

Do It Yourself Diabetes


Dana Lewis and Scott Leibrand are the creators of the amazing “Do-It-Yourself-Pancreas-System,” also known by #DIYPS. We had a few question for them.

Ernesto: Why build your own pancreas?

IMG_3561Dana: I’ve had Type 1 diabetes for about 12 years. I use an insulin pump and a continuous glucose monitor (CGM), but the devices are separate. They don’t talk to each other. I have to look at the data from the CGM and then make decisions about my insulin. I have to make about 300 decisions per day on average. It’s really fatiguing. So we created some algorithms that took my blood glucose data, the amount of insulin that I’ve given myself, and the amount of carbohydrates that I’ve decided that I’ve eaten, and ran them over and over again to give me a prediction of what my blood sugar was going to be and whether I need to take any action. Instead of having to constantly do the math myself, our system will push an alert to my phone or watch.

Ernesto: Does it dose you automatically?

Dana: Originally no, but more recently we’ve built a full closed loop version of #DIYPS, that is essentially an artificial pancreas, that talks to my pump and adjusts to give me a little more or a little less insulin.

Ernesto: Who writes the code?

Scott: I’m doing all the coding. I’m sure Dana could, but she has a lot going on and designs the algorithms. My title is Chief Spaghetti-Coder. This is the bleeding edge. It doesn’t need to be elegant code.

Ernesto: What have you learned from building your own pancreas?

Dana: The beauty of a CGM is that it gives you a data point every five minutes. Over the past year I’ve produced more than 130,000 data points of blood sugar levels alone. That gives me an incredible picture of what’s happening. With a traditional meter, it’s rare to find somebody who tests up to even 10 times a day. And the standard use for an insulin pump is very much “set it and forget it.” The #DIYPS allows me to customize without having to constantly adjust my insulin pump manually, and that frees me up to live my life, work, and do whatever it is that I want to do.

A visualization of Dana’s Data over the first year of the #DIYPS system.

A visualization of Dana’s Data over the first year of the #DIYPS system.

Ernesto: How did this project start?

Dana: We first started building the system just to make the alarms on the device louder, to wake me up because I would sleep through them. The device manufacturers didn’t seem to have a solution. Then we started looking at getting the data onto a computer so Scott would be able to view it. At the time, we had recently started dating, and he lives 20 miles away. I wanted him to be able to see what my blood glucose level was, so if it was low, he could text me; and if I didn’t respond, he could call 911. But we didn’t have a way to get the data off of the device.

Scott: The key moment was when we saw a tweet from John Costik, who was working on the Nightscout Project. Nightscout is open source code that helps people transmit their CGM data to other devices. I tweeted John right away: “Hey it would be awesome if we could get access to this code.” That’s really where it started. And along the way the whole process has been extremely public. We’ve been tweeting, blogging, and making everything we’ve been doing completely visible.

Ernesto: I’ve seen you tweet using the hashtag #wearenotwaiting. What does that mean?

Dana: #WeAreNotWaiting is a hashtag that was coined at a conference hosted by an online diabetes advocacy and information sharing community called For me it means that we’re not waiting for traditional device manufacturers to come out with the product. In three to ten years there’ll be devices like our artificial pancreas systems out in the market, being sold by companies approved by the FDA. I need to be alive when that system gets out in the market in, perhaps, five years.

I need to be alive when a cure becomes available.

Scott: Right about the time that we started working on #DIYPS, the Nightscout Project started to grow really quickly. There are now over 10,000 people in the CGM in the Cloud group. Over 2,000 people are using Nightscout to view their own or their loved ones’ blood sugar levels remotely on phones, watches, and other devices. This is real stuff that’s making a real difference in the world. And that’s only going to accelerate as more people do more interesting things like this closed loop that we’ve just done.

Ernesto: You’ve written about “data as free speech.” What do you mean? How can data be speech?

Dana: People often don’t understand why its legal for us to ‘hack’ a CGM and an insulin pump. (Note that hacking isn’t a negative thing; we’re just sharing the data across devices!) They assume that because all my DIY gadgets are not FDA-approved to use them the way I’m using them is somehow against the rules. But I can treat my own body, my own diabetes, the way I want to. And if I share my data, that’s obviously a kind of speech. But if we decide to share our code? I think the FDA sees this as a gray area. We very much want to continue our conversations with regulators.

Ernesto: Where do you see your project going?

Dana: I feel that every time I answer this question my answer changes, because my understanding of its potential is constantly changing. I never would have thought that any of what we’ve done was possible. Right now one of our goals is to make sure that the knowledge we gained about diabetes through our work with #DIYPS is adopted by clinicians, and that patients have access to this new information for treating diabetes. We’re also taking #DIYPS to a new level with #OpenAPS, an open and transparent effort to make safe and effective basic Artificial Pancreas System (APS) technology widely available to more quickly improve and save as many lives as possible and reduce the burden of Type 1 diabetes.

Dana with the #OpenAPS system.

Dana with the #OpenAPS system.

Scott: A few of months ago, at a conference convened by the advocacy group DiabetesMine, we got up and talked about our project, and I said: “I’m putting a stake in the ground that we’re going to make a closed loop artificial pancreas by August 1st, which is the date we’re getting married.” Everybody applauded and thought that was awesome. Then we went home. And we had it done in two weeks.

Dana: For anybody who wants to get involved in this, we would love to talk to you. There are so many people with diabetes and there is so much data that drives the management of this disease.

But there’s not a lot of awareness of how many diseases, including diabetes, could have their care revolutionized just by having better access to data.

That’s the thread of Quantified Self that I’m most interested in. The diabetes community happens to be one of the first to take advantage of what’s possible.

Dana tweeted her blood glucose data during this interview.

We invite you to share your data access stories, and this Access Conversation with the #qsaccess hashtag and follow along here in our Access Channel and @quantifiedself.


Posted in QS Access, QS Access Conversations | Tagged , , , , , , , | 2 Comments

My Device, My Body, My Data


In 2007, after collapsing while rushing to board a train, Hugo Campos was diagnosed with hypertrophic cardiomyopathy, and an ICD (implantable cardioverter defibrillator) was implanted in his chest to track and regulate his heart rhythm. To his great surprise, he discovered that it was very difficult to gain access to the data being generated inside his own body. Today we’re inaugurating what we hope will be a regular series of “QS Conversations” about data access with an interview with Hugo about his long battle for the right to see what’s happening inside himself.

Ernesto: Why does access to your ICD data seem so important to you?

campos_hugo_medx2014 copyHugo: I have a computer with firmware, processor and memory regulating my every heartbeat, wired into my heart, and buried inside my body. I can’t even see it. A corporation in the cloud, located out of state, has a wireless, transparent access to a device that’s implanted in my body, but the only control I have is to unplug the remote monitoring unit in my house to prevent them from getting the data. This creates a very unsettling feeling of not having autonomy. I’m paying thirty thousand dollars for a device, having it implanted inside my body, and then being locked out of it.

Ernesto: Was there something that happened that set you on this path?

Hugo: Yes. For a long time I’d been on my spouse’s health care plan, but when he decided to freelance and quit his job, I couldn’t get health insurance. This was before the Patient Protection and Affordable Care Act. Kaiser denied me because I had a heart condition. Anthem Blue Cross denied me as well. Now put yourself in my shoes. Here I am, being denied access to the device because the system “knows better” and I could harm myself, but now they can’t give me service at all.

Ernesto: You can only get access to your ICD through the medical system, but the medical system won’t take you because you have an ICD?

IMG_1542 copyHugo: Right, so I had to figure out a way to protect myself. I looked at it as kind of an extension of my Second Amendment rights. I’m not particularly pro-gun, but I look at it as the ability to defend myself. If the system was really unavailable, I have to at least be able to interrogate my ICD. So, I went on eBay and bought a pacemaker programmer that gave me full, unrestricted access to my implanted device. I can change its programming, shut it off, deliver therapy, and do as I wish. In fact, it’s the same machine that clinics use. I also went to Greenville, South Carolina, and took a class on how to program ICDs and pacemakers. I thought, “Okay, I may not become a cardiac electrophysiologist by any stretch of imagination, but”–to use the firearm metaphor again–”at least I have a basic understanding of gun safety so I don’t shoot myself.”

Continue reading

Posted in QS Access, QS Access Conversations | Tagged , , , , , , , , | Leave a comment