** I’m writing this from my viewpoint as a Type 1 diabetic and, as always, Your Diabetes May Vary
The Atlantic posted an article by Thomas Goetz, The Diabetic’s Paradox, that did a very good and accurate job of describing why data collection is the arch-enemy of many diabetics, even addressing the psycho-social aspects of the issue.
So let’s just say, for arguments sake, that we now have all this data. What now?
The analysis. Data by itself, with no analysis, is totally meaningless.
Analyzed data with no action is totally, well mostly, meaningless. Sometimes no action is the correct response.
When you do an analysis, you get results. Some results are “better” than others, or so we often lead ourselves to believe. Those results, like an A1c are often “guilt generators”. I, and many others, have often written how easily guilt becomes associated with diabetes. And I also completely agree with author Will Dubois that there are “No bad numbers, just good data”.
Besides the results, though, the sheer amount of data can be overwhelming! Glucose readings, carb counts, dosage calculations, lions and tigers and bears! Oh My!
I know, that’s pretty facetious, but honestly that is how I feel sometimes when I step back and look at all the simple number of data points involved in my daily care. And decisions based on those data points. How many carbs? What kind of carbs? How much protein and fat. What’s my carb ratio this time of day? Normal bolus or extended? Making the wrong decision can have tragic consequences.
We all SWAG at times… if we SWAG’d poorly, it is a Supremely Wild Assed Guess. If we SWAG not-so-poorly, it becomes a Surprisingly Wonderfully Accurate Guess. Some people are better SWAGgers than others. Personally, I tend to saunter but I have been know to meander from time to time.
There are about a zillion and three things that can influence all those various data points, many of them situational. And to me, those situational circumstances are the ones that tend to get lost in the shuffle. Honestly, if my meter, pump, and cgms didn’t keep it for me, I wouldn’t have any data to look at.
The large data samples we have really only give me, at least, a couple of ways of examining my data. If I’m wanting to look at detailed information I’ve found that I can really only look at the last two or three days at most, otherwise the amount of data makes it nearly impossible to keep track of. Also looking at just a few days allows me to remember some of that situational data which I didn’t write down. Things like “I mowed the lawn and got low” or “I guess that chocolate birthday cake was a little more carb loaded than I thought!”.
Where I find my most useful information is when I look at the larger set of data covering the last few weeks, not days. The trick is in how you look at it, you don’t go all the way down and look at each and every meter reading, you look at the averages. Averages, while being always wrong, can provide valuable information when looked at over time.
Looking at the average of all tests during a certain time-span, say an hour, can be very informational. Stringing 24 of those hour long time-spans together can show you a very accurate picture of how your numbers tend to vary over the course of a day. Understanding that variation is a very important result to me.
In my opinion, an A1c test is a pretty one-dimensional view of my control over the last three months. For example, I once had an A1c of 5.7 along with daily swings from 50 – 350. The 5.7 alone said I was kicking ass, the standard deviation (how wide the swings were) said I was getting my ass kicked.
I don’t sweat the A1c any more, I always want know my standard deviation, to lower it over that same three month time-span. The smaller my swings get, the less hypo- and hyper-glycemic episodes I have, the better I feel, the less I worry and the less guilt I generate for myself. The two results, when combined, give me what, I feel, is an accurate picture of my control for the last few months.
As someone who works in IT and is used to working with large data-sets, it is still possible to get lost in the details. This is one place where I love how my Endo and CDE look at the “big picture” and help me “see the forest”.
One thing that I have found is that, in general, if it gets too complicated to keep track of, I have done one of two things. I’m either approaching it from the wrong angle (ie solving the wrong problem) or I have been over-analyzing. My team helps me step back to get a clear look at what is going on, see what the real problem might be.
For example, do I need to increase my basal rate after lunch? No, I need to change from a normal bolus to an extended bolus because my lunch tends to be high-protein which means it is digested slower. And keep an eye on the carb ratio…
The devil is in the details, folks. We have all heard that before. What we don’t often hear, or perhaps recognize, is that we really need to understand what level of detail we work best at, at what level we need to work at to get the results best for us.
© 2013 Scott Strange, Strangely Diabetic and http://StrangelyDiabetic.com