Too often, we look at the 7-day, 14-day, and 30-day trends on our blood glucose monitors, see numbers that look great (or horrid), and rather than seeing an A1c that confirms those readings, we get a number that would appear to have come completely out of left field. (Or Mars. Or the Andromeda Galaxy. It's hard to say exactly where.) We can either scratch our heads and wonder why the numbers aren't correlating, or we can take out our manual readings logs, our meter downloads, our CGM downloads, and our personal journals and try to figure "what we are doing wrong".

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Over the past few posts, you've seen me comment about diabetes technology -- mostly hardware and supplies -- in the context of a particular issue (hot weather or availability), but nothing really in terms of what I would like to see healthcare providers do in terms of better using existing technology, as well as what I should like to see pharmaceutical companies, software companies, and device manufacturers develop going forward. Because of the length of my wish list, I'm going to break this up into two posts.

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It's said that (for those of us with full visual faculties) we process something like 80% of what we learn visually. Color-coding, shading and graphs are some ways of marking differences between between values and degrees of value, helping us digest large amounts of complex information in a single glance. Consider the political map, with each country, state, county, or other subdivision in a different color. "Red" states and "blue" states. Degrees of obesity per state. And so on.

Consider the color-coded diagram of the human digestive system. Red stomach, yellow intestines, pink colon, green gallbladder, brown liver. What color is your pancreas? Do you want to color it in World Diabetes Day blue to indicate yours has died?

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Last weekend I joined many other computer and radio hobbyists at the Trenton Computer Festival for two days of talks, workshops, and parts-vendors. While I was not on the program this year, I found a number of interesting presentations offered, and I spent much of the weekend attending talks. Two of the themes explored were security and privacy, and communicating with nontraditional devices wirelessly using Internet protocols.

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There are enough issues with the data from our diabetes devices to make the average PWD's head spin.

First off, there's the sheer volume of it. Consider that the average glucometer burns through 1500 readings a year -- which hikes up somewhere closer to 6000 if you have type 1 diabetes and don't have a continuous monitor you can rely on. Then there are the carb counts, food data bases, multiple basal rates, special basal rates, bolus wizards, special bolus calculations, and the smartphone calendar alarm to manage them all. Those of us with type 2 diabetes may not have all the insulin data to collect, but we have instead the blood pressure data, and along with the caloric impact of the foods we eat, we have to capture the fat distribution and the sodium levels. For all of us who exercise regularly, there are the heart-rate monitor data, the treadmill, elliptical, and cyclocomputer statistics, and the rep charts for weights. (READ MORE)

Yesterday, I discussed how I'd like diabetes healthcare providers and the healthcare industry to better use existing tests and technologies, and how I believe our current crop of devices and programs might be developed in the near-term future. Today I'm going to discuss items that will take a bit longer to develop and get through FDA approval, or which may take technological and medical breakthroughs to bring to fruition.

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