Helping Diabetics Deal with Data Overload

One of type-1 diabetics' biggest hurdles is making sense of mountains of sometimes chaotic-seeming data.   

Brian Buntz

"I have to quantify myself just to stay alive," says Chris Snider, who serves on the executive board of the Stanford Medicine X conference and has been living with type-1 diabetes since 2002. "That is an interesting perspective to bring to the Quantified Self community," he adds, who also serves as an associate editor for the self-tracking movement of the same name.  

Snider is scheduled to speak in San Francisco on the unique struggles of diabetics at a Stanford Medicine X Meetup this week (Ed note: I'll be there, so I look forward to meeting any local medical device professionals who can make it), notes that the majority of people who track data from their wearables and other health-tracking devices aren't dealing with life-threatening diseases.

Patients who must self track health metrics can feel overwhelmed by the volume of data they must monitor. "The extent that I self track kind of ebbs and flows depending on how much I want to pay attention to," Snider says, who juggles data from a traditional blood glucose meter, a continuous glucose monitor, as well as a Misfit Flash fitness tracker. "There is a threshold of how much I can pay attention to and still lead a moderately healthy life."

The volume of data Snider monitors ebbs and flows with his level of enthusiasm for data tracking. "There will be a monthlong period where I am super focused on it and then I will get a little burnt out on it. Sometimes I don't want to be as enthusiastic about all of these data points because they are always coming whether I want it or not," he says.

Snider is happy with how diabetes technology is evolving, yet notes that interoperability of various devices has been a hurdle in the past. "We have access to most of our data; it is just a matter of putting it into the proper context to make sense of it," he says.

Medical device companies and startups would be well served by helping diabetics better make sense of their data, better filtering out the most relevant data points from the noise.

One company known as Tidepool (San Francisco) has been a trailblazer in this regard. Prior to Tidepool, it was a struggle to integrate data from different diabetes devices, which often had proprietary software. "You could download all of this data--have all of these different PDFs and print outs--and it was nearly impossible to make sense of it. With Tidepool, you can put them onto the same timeline and see what is happening with all of this different data," Snider explains. Tidepool now has access to all of the data from all of the big diabetes technology companies but one.

Despite breakthroughs like Tidepool, it can still be difficult for type-1 diabetics to draw firm conclusions from the data they are gathering. "It is sort of like doing algebra. You have the formulas and you are working to get a certain output based on a certain input," he says.

While the prospect of keeping a blood glucose level in between a high and low threshold may seem straightforward, it can often be a challenge. "It gets tricky when you see swings that happen over the course of a week and you want to fix those," Snider says. "There are settings on the pump that can help manage that. If I am smart about what I am eating, that will also help improve my blood glucose control."

Yet there is still some amount of chaos involved. There are many factors involved in proper diabetes control and sometimes patients can do everything they are supposed to and still have uneven results in monitoring their blood glucose levels. "What you do on Monday may be great, but if you do everything exactly the same on Tuesday, there is a good chance you won't get the same results," Snider says. "There is a lot that can be done to try to mitigate that variability, and more of that will come from artificial pancreas type technology, which could improve that. But there is still a portion of diabetes control that doesn't play by the rules and that is kind of an everlasting annoyance."

Brian Buntz is the editor-in-chief of MPMN and Qmed. Follow him on Twitter at @brian_buntz.

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