In 2012, Doug Kanter used no new medications for his Type 1 diabetes. He didn’t adopt a restrictive diet. He trained for a marathon, but he’d always been a runner and athlete. He didn’t use an artificial pancreas or smart contact lenses. His doctors didn’t suggest a new approach.
His A1C dropped nearly a full point to below six percent. (In case that last sentence doesn’t raise your eyebrows, it means that his blood sugar control was insanely good.)
So what changed? How did he achieve such stellar results?
For a full year, Doug Kanter collected information very, very carefully and interpreted it expertly. His year of data lives not on monotone printouts and spreadsheets, but on sweeping, colorful graphs and charts that show highs, lows, and trends. He collects not only blood sugar readings and insulin doses, but also what he calls “lifestyle data” — namely, what he eats and how much he exercises. With this lifestyle data, Kanter has a clearer notion of what’s going on as his blood sugar bounces, swings, and steadies.
With the success of this project, which began as a culmination of his graduate studies at New York University, Kanter is now building a company, Databetes, that aims to make this level of tracking and analysis more broadly accessible. In a Databetes world, we can all be data geeks with really excellent A1Cs.
A simple goal: understanding what happened
Kanter and the team he has assembled operate on the simple premise that by displaying more information in a way that makes sense, a motivated patient will detect patterns and naturally uncover methods of meeting blood sugar goals.
You get a sense for the power of Kanter’s graphical representation of his diabetes data by the wheel of information he recently assembled to sum up his 2012 data. It’s a far cry from the tiny, pixelated black screens with incomprehensible charts familiar to most diabetics. While the volume of Kanter’s individual data points is impressive and possibly overwhelming, the broad trends are clearly visible (though it’s probably a good idea to hear Kanter’s explanation of it all). The chart synthesizes 91,251 blood sugar readings with “data from the rest of his life,” including numbers such as a log of his running miles, approximations of carbohydrate consumption and hours slept, and notes about stress, jet lag, and life events.
The beauty is in its simplicity, and the simple goal is familiar to anyone with diabetes: Doug Kanter wants to get a better sense of what’s really happening. The cause and effect, the strategies that work, the restaurants and snacks that consistently trip him up…
“Never before in my 27 years as a Type 1 diabetes patient have I been able to step back and reflect on my health through an entire year’s worth of diabetes readings,” Kanter writes on his blog. He may not have measured every spike and crash, but he has come closer than ever before. Throughout the year, Kanter made small adjustments, often subconsciously, based on his observations. Slowly and steadily, he eliminated mistakes and figured out what works.
Kanter, who recently completed a graduate program in interactive telecommunications from NYU, crunches numbers like a pro. But those of us without a head for numbers or sophisticated software may run into some obstacles in an effort to manage diabetes with a data-driven approach.
That’s an opportunity gap that Kanter hopes to close with Databetes. The first software that Databetes plans to release will allow users to track food intake in a way that is most useful to people with diabetes, allowing for carb measurements and notation of insulin dosage.
Taking pictures of your food
While Kanter is a data aficionado, he also has an artistic eye, as you will see in the elegant representations featured on the Databetes website. He is an experienced photographer, and he lights up when he describes Meal Memory, an app that Databetes is currently rolling out. With Meal Memory, users can anchor their quantitative data — carb counts and blood sugar readings — to a photograph of their meal.
At first, I was skeptical. What good does a picture do me? I need carb counts, not a photo album.
But Kanter enthusiastically reeled off several points that won me over. A photo makes it easier to jot down the more detailed food data later, which would be especially nice when you’re out with friends.
“It’s easy to log the meal and it’s also easy to get back to what you’re doing,” he added.
Two hours later, the system sends you a reminder. It’s time to test your blood sugar again! Once you’ve done that, you’ll have readings for your blood sugar before and after the meal in addition to a photo (for the album).
And about that album. If you add to it regularly, you’ll compile a general visual sense for what you’re eating. If you scroll through all of your lunches and there are lots of hamburgers, well, you’ve eaten a lot of hamburgers. The human eye and brain can synthesize and detect patterns extremely well, and Meal Memory is designed to capitalize on that natural ability.
In Kanter’s words, “The system not only helps answer questions about each individual meal, but it also helps you reflect on your overall diet.”
Taking Databetes and data-driven blood sugar control to the next level
That year of collecting data required extreme diligence. Or, as Kanter summed it up, “It’s just kind of tedious.”
Though Kanter believes that others could be just as disciplined and consistent, he recognizes that ease of use and convenience will lead to broader uptake and, he hopes, better health outcomes for more people. So in the long term, he hopes to see Databetes develop a tool that synchronizes remotely with an insulin pump, CGM, or other device. With blood sugar readings and insulin dosage automatically recorded, the user would only have to add lifestyle data.
Kanter also hopes to use the tools he’s developing to generate nutritional recommendations or suggestions for individuals based on their blood sugar and past food intake. But this, too, is a long way off. He acknowledges that “the nutrition side of it is the most complicated.” For Databetes to suggest changes in lifestyle choices rather than simply aggregating and displaying current lifestyle choices, the U.S. Food and Drug Administration would have to approve the product.
What is perhaps most distinctive about Kanter’s approach is its apparent impact on his blood sugar control given its totally observational methodology. The only action required of the patient is the actual process of collecting data. In the absence of clinical studies, we can’t say for sure that data collection is directly or indirectly related to blood sugar levels. But it does stand to reason that motivated patients could better combine their medications and lifestyle choices by observing trends over time.
While Databetes stands out for its data-driven approach, various other companies are building tools meant to improve blood sugar control through non-medical user engagement. MySugr Companion functions as a diabetic logbook with a cheeky monster that bosses you around. PatientPartner, a story-driven multiple-choice game, has actually been shown in a clinical study to significantly reduce A1C measurements over time following only minutes of engagement.
Ultimately, Doug Kanter is working to realize his vision of a diabetic life with better information, of a feedback loop that empowers us to make increasingly strategic lifestyle choices, and a diabetes management system that includes software as sophisticated and effective as its hardware. By combining established technological capabilities, data analysis and visualization techniques, and basic knowledge about diabetes management, Kanter and his team at Databetes hope to see those insanely good A1C levels cropping up in all corners of the diabetes community.