Diabetes Blog Week is technically over, but I still want to write about one of the topics: my dream diabetes device.
I — In the past I’ve written about wanting an application that integrates all my current diabetes paraphernalia, my Carelink account, and my
mobile phone iPod. The goal was to have total diabetes awareness by tagging “interesting” events so that I can go back to the historical record the next time that thing occurs. “When I was sick how much extra insulin did I need to give?” “When I ate Indian food, what was an appropriate amount of insulin and how did I deliver it?” “What basal rates and carb amounts worked well for a triathlon?” Ask one of these questions, and see the BG values, bolus wizard details, and CGM traces for all of the events tagged with those keywords. It wouldn’t be a perfect solution to preventing all lows and highs, but it would surely be better than my own faulty memory.
I actually started writing the application and got all of the data into a MacOS application, but I got frustrated that I wasn’t going to be able to easily get the data from my computer onto my mobile device. So, as usual, I set it aside and got distracted by something else. That was a couple years ago. Since then iCloud came along and makes sharing this kind of data between devices much easier. Maybe someday—after I win the PowerBall lottery, perhaps—when I have limitless time and ambition, I will pick it back up. Or (better yet) I’ll become a venture capitalist whose first project is to fund the development of such an app. That way I can travel the world while other people do most of the coding for me. I’ll show up for design reviews to give insightful commentary and gather information for my TED talks.
II — Recently I’ve started working on another diabetes data project. Now that I have a newer Mac, I can run MATLAB again. Yay! It occurred to me, after reading a coworker’s at-work blog about telling stories with MATLAB, that it should be possible to integrate a lot of the disparate sources of data into one application (MATLAB) and try to reconstruct a day with diabetes and try to figure out a partial model for some of the stuff that currently requires a lot of trial and error. It’s not a perfect solution, but it’s a start.
The thing that makes this all possible is the fact that so many of the devices I use every day record and export data. My cycling GPS and Garmin running watch tell when I exercise, for how long, and at what intensity. My CGM records my blood sugar patterns, while my BG meters record the ground truth. My insulin pump tracks my basal insulin usage and all of my bolus wizard details, along with a host of other details. There’s a lot of data there that I can potentially synthesize and display in one view. And, because it’s MATLAB, I can define every last little thing about how I want the information displayed, what details I want to filter out, and what I want to try to highlight or search for.
III — But even with all of this data there are missing parts of the picture. Diabetes is a difficult disease to manage, in large part, because it’s integrated with almost every other part of life. Unfortunately, daily life is messy. There’s a lot of it that just isn’t easily tracked by devices—well, not yet. I’ve toyed with the idea of getting a FitBit device to keep track of some additional things, such as overall activity and sleep, but that still leaves a lot of things untracked, especially food: food that I don’t bolus for, such as glucose tablets, food during exercise, “just in case” snacks, the things that seem too small to worry about, etc. And then there’s swimming, stress, pain, illness, hydration, weight, and so on. I wish there were a way to keep track of all of that. (At least for a few days or a couple weeks while trying to figure out appropriate baselines or when changing my training load. Paying attention to all of that data every day could be a bit overwhelming.)
So I asked one of my bildr/maker-type friends if there were good hardware or software solutions for keeping track of any of this stuff, especially the food-related bits. There are hundred (if not thousands) of nutrition apps, but all of them I’ve seen are much more heavyweight than I want. Don’t make me select something that says which food I ate in order to give me all of the nutrition info or calorie count when all I really want to record is “At 11:25AM (give or take) I ate 15 grams of carbs that I didn’t bolus for.” The best that we could come up with at the time is a small notepad and pen to record stuff before transferring it manually into whatever computerized, MATLAB-based system that holds all of the other diabetes events.
Thinking about it on a bike ride a couple days later, it seems like it should be possible to have a little nanny app that pops up a few times a day asking questions. How is everything going? What time did you wake up this morning? How much sleep did you get? Feeling stressed? Eaten anything you didn’t bolus for in the last day that we haven’t already talked about? Do any swimming or yard work? How active have you been this afternoon? Any pain? Illness? Have you been drinking water?
Just a few judgment-free yes/no questions and easy-to-answer questions involving time and quantity, and voilà! instant context. I could probably make an iOS app to do that in a weekend (if I didn’t mind it looking crappy). But really that’s all of the data that my devices don’t give me now that I want to capture. Oh, and it should have a one-touch switch that turns it off so that I’m not bothered during the 95% of the year that I don’t want to keep track of all that stuff.
IV — As an aside, wouldn’t it be awesome if someday there were a Siri-like interface for diabetes?
“Hey, Siri. Remind what I did those times that I had barbecue at the office and everything went pretty well?”
“You estimated you ate 100 grams of carbs. You delivered ten units of insulin in a dual-wave pattern with two-thirds up-front and the remaining third over an hour. Here’s what your CGM trace looked like for the next six hours.”
“Thanks, Siri. I love you.”
“Hey, let’s keep things professional. I’m not that kind of robot.”
V — But all of this “Total Diabetes Awareness” and data fusion and mindfulness/memory apps got me thinking that the ideal diabetes
device system is one that wraps all of this up. It automatically keeps track of activity and food and active insulin and BG/CGM values and all of the other emotional intangibles.
But then I thought, keeping track of all that data in order to make better insulin dosing decisions is 20th century thinking. What I really want is a system that automatically regulates BG levels using two hormones, one that lowers blood glucose (via insulin) and one that raises it (via glucagon). Then the system can reach homeostasis all on its own.
Of course, an artificial pancreas that integrates everything together in a closed loop system needs believable inputs. BG meters and (especially) CGM sensors need to be much more accurate so that the system is given the right data to make the right decisions. It’s a bad thing when my CGM says I’m 40 mg/dL (2.2 mmol/L) when I’m really 140 (7.8) or, worse, vice versa. So obviously, an artificial pancreas that’s actually implanted and uses a semi-permeable membrane that lets more insulin seep out when it’s needed is the way to go.
And that’s when I realized the basic truth of diabetes technology: The ultimate diabetes device is a new pancreas.