In our second episode of QS Radio we shake things up a bit. We start with a brief discussion by co-host Steven Jonas about his experiences using the SunSprite light tracker and what he’s been learning. Next up, we have a great Toolmaker Talk with Kevin Holesh, the creator of Moment for iOS. Moment is a self-tracking app that helps you track how much you use your iOS devices (iPhone or iPad). Lastly, we wrap up with a short discussion about some interesting news and tidbits about personal data, self-tracking, and quantified self. Links to everything we discussed are below. Enjoy!
Don’t forget to register for the QS15 Conference and Exposition. If you’re interested in Quantified Self, self-tracking, and personal data there is no better place to meet expert users, advanced toolmakers, and learn first-hand through our may talks, sessions, and demos. Register now!
Across the world, six Quantified Self meetups are getting together this week.
Vienna will have two special guests. Friend of QS, Chris Dancy, will speak about what he’s learned from collecting personal data from 700 sensors and services. Christoph Fabienek will speak about data privacy and the internet. The QSXX group in San Francisco (more on QSXX) is keeping things casual with a happy hour meetup at a brewery, a format you may want to consider for your group to keep the conversation going.
How Networks Bring Down Experts by Max Borders. Max gets double points for this great piece on using networks and peer-to-peer learning for developing personal expertise. Loved the reference to the writing of Michael Polanyi.
Show&Tell Defining a New Indicator of Cardiovascular Endurance and Fitness by Marco Altini. Marco has been exploring fitness and heart rate variability detection using iOS applications. Recently he’s been using activity and HRV to examine a new method for determining fitness level. As per usual, Marco wrote an amazing and in-depth report using his own data to showcase what he’s learning from his new application.
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
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.
Who Owns Medical Records: 50 State Comparison by George Washington University’s Hirsh Health Law and Policy Program. You’ll never guess how many states have laws that give patients ownership rights for their medical records. Spoiler: ONE.
I believe that, fundamentally, data is all about helping people find new opportunities to pursue optimal health and participate in their own care. That means promoting ways to get, use, and share information about themselves easily and securely.
Technology That Prods You to Take Action, Not Just Collect Data by Natasha Singer. A nice article here that includes some great insights from our friend and community contributor, Natasha Dow Schüll. Are devices being “dumbed down” or are we when we “cede [our] free will to machine algorithms”? Only time will tell.
Can healthy people benefit from health apps? by Iltifat Husain & Des Spence. In this debate, Iltifat Husain and Des Spence discuss different types of health tools, applications, and devices being used by healthy individuals. Do they impact our health for the better? These two physicians duke it out through spoken and written word.
Excavating Old-School Self-Tracking Tools by Jamie Todd Rubin. A short but interesting thought experiment here by Jamie. What would happen if we analyzed the vast troves of “soft” data found in the diaries and journals? What could we find out about our past, our history?
Show&Tell How We Are Measuring Happiness at Whitesmith by Daniel F. Lopes. Another interesting example of using the workplace team communication tool, Slack, to gauge and collect information about the emotional wellbeing of employees.
Impact of music streaming on my listening habits by Maciej Konieczny. Maciej switched to streaming music in 2013, and it completely changed how he experienced music. In this great post Maciej he describes how exploring his music listening data (from Last.fm, of course), he was able to see just how his listening habits were impacted.
Quantified Self About Town by Changyeon Lee. This visualization is part of a project by Changyeon to map artificial light in New York City. Above you see a data visualization of artificial light data around the NYU Tisch Building
Catha Mullen has a long history with tracking, primarily from her experience as an elite-level distance runner. In this talk, presented at the Bay Area QS Meetup, she describes how tracking and data analysis helped her understand and improve her financial health.
Six Quantified Self groups are getting together this week for show&tell talks. Copenhagen, in particular, has a jam-packed program with four talks on walking while working, food tracking, heart rate visualization and stress monitoring.
To see when the next meetup in your area is, check the full list of the over 100 QS meetup groups in the right sidebar. Don’t see one near you? Why not start your own!
Last week, Turin had their very first show&tell meetup. It looks like it was a fantastic event in a fun venue, judging from the photos. If you organize a QS meetup, please post pictures of your event to the Meetup website. We love seeing them and will post them here. Photo credit: Luca De Marco and Livio Torrero.
In our first episode of QS Radio we hit the ground running with a great pair of interviews and some super interesting news and discussion about exciting self-tracking projects.
In our show&tell segment, we hear from Shannon Conners, a self-tracking enthusiast who’s been learning amazing things from tracking her diet, exercise, and weight for over four years. Jessica Richman, CEO and co-founder of uBiome, joins us for a short Toolmaker Talk where we learn about the importance of the microbiome and citizen science. To wrap up, Ernesto and Steven share a few interesting tech and self-tracking stories in a segment we call “What We’re Reading.”
We hope you enjoy this inaugural episode. Make sure to check the show notes below for links to items we discussed.
You can find out more about Shannon Conners and her self-tracking experience on the JMP blog. We spoke in particular about her excellent diet tree map visualization:
Anna Nicanorova is a data scientist. Starting in 2013 she started making an annual report, but what stuck by how difficult it was to access her own data she was collecting through different apps and services. Early this year she put together her 2014 annual report based on a few different tools and using If This Then That as a data backup service. In this short talk, presented at the New York QS meetup group, Anna describes her process, her data, and what she learned from examining a year in numbers.
We recently started a program to invite QS Toolmakers to contribute directly to funding our events. We call this program Friends of QS. If you would like to participate we invite you email us to learn more.