Devil's advocate: diabetics do not want data logs, they want a better/longer healthy life. I do not have diabetes, but I would rather have an insulin pump that maintains glucose levels by itself than a meter that allows me to monitor them.
And yes, that pump will be imperfect, but it probably will do a better job than you can do yourself, let alone than you will do yourself.
I know that, traditionally, patients used glucose level measurements, stared at the numbers, guessed at what caused them and then tried to correct for similar future events, but AFAIK, that has never been very effective. It did give you some sense of being in control, but that was more an illusion than reality. e.g: your blood sugar is high. Is that because you drank a beer last night, because you went to bed late, because you did not sleep well, because you are stressed about something, because you had a fever two days before, because you took the bus to the train station?
However, except from the truly bloody obvious, that didn't help much maintaining blood sugar levels, unless you lived like a robot. Normal daily schedules simply vary too much to allow you to determine the true cause of atypical blood sugar level variations.
IMO, the time of stand-alone glucose meters has passed, and I do not see how having users process logs will help improve their lives. Reading individual measurements definitely will, but that is so that you can react at short notice, and adjust insulin intake.
I've been a diabetic for 14 years and that's exactly how I feel. The only way I can have perfect glucose levels is to live like a robot: wake up every day at the same time, eat exactly the same measured amount of food, check my glucose level every time my alarm beeps and do nothing out of the ordinary.
I'm trying to exercise more and the diabetes is the biggest barrier, I'm like a roller coaster right now.
I don't want to stare at a graph and do even more calculations, I want those calculations done by a machine, which can infuse insuline constantly and use more or less depending on my glucose trend.
There are new technologies out there, like this CGM [1] (continuous glucose monitor) which is very small and wireless (minilink minimed) which IIRC can work with an insulin pump (there is one that's very similar, wireless too, with a reservoir for three days of insulin)
Couple of points -
Yes, pumps give better control, yes it would be a lot better if it were a closed loop system between a continous monitor and a pump with a human confirmation point with suggested actions. We are a little way off that being supported by insurance/healthcare systems as cost effective, so really I am talking about the table as it is set up right now.
There are a number of biological factors that can make a difference, but for type 1 diabetics, the point should be that you know the ratio of carbohydrates eaten to insulin to take. This can vary, but good data helps you get the ratio right. It can also identify if you have high glucose points that match your circadian rhythm, or if you're becoming hypoglycaemic at a certain point regularly and just haven't mentally joined the dots.
Now, yes, you could do all of this through a log book on paper. I could sit down for a half hour each month and look for trends. But, I take readings on a device with digitised output between 4 and 8 times per day. I don't want to have to go analogue with that, I essentially want the blood glucose equivalent of google analytics. I can account for unusual variations (cycled for 10 miles/got blind drunk/etc.) much better if I have a dataset that demonstrates what the benchmark should be.
> I do not have diabetes, but I would rather have an insulin pump that maintains glucose levels by itself than a meter that allows me to monitor them.
This does not align with the practical reality of diabetics or the biological reality of what pumps and sensors do. The situation is much better now with continuous sensors, which display a graph with a sample every 5 minutes with alarms for high, low, and changing too fast.
But you cannot take the human out of the decision process because the most important information needed to decide how much insulin to give is what (ie how much carbohydrate) you're eating, because the effect of insulin is delayed too much. Trying to make decisions from glucose measurements alone is completely inadequate. People are trying to do this anyways, by using dual pumps giving both insulin and glucagon (glucagon has the opposite effect as insulin). This hasn't left the research stages and I don't think it'll work very well.
Great post - All the points you raise are valid. I've been in this business for 8 years, seen a dozen products (HW/SW/Apps) go through FDA/CE approval and end up on store shelves. I co-designed the only product at the Apple retail stores that use blood as a user interface. Most engineers/product people in the industry share your frustration. We're keenly aware of the problems, but it's a problem with the ecosystem and hard to solve at a startup scale.
Basically, we're seeing little movement because open data has huge perceived risks and minute upside.
+ Open Data = Risk: The reason big device companies don't make open APIs for data is that it opens them up to risk. If some 3rd party creates software that uses device data and a patient ends up in a hospital, or worse, who will the family sue? The 2 person startup experimenting with health software, or the multi-billion dollar device company that didn't police every app made with their data? It's slightly irrational, but from the perspective of device company execs, opening data creates huge potential problems and risks with almost no upside. Also, the data privacy laws in the US and Europe scare/confuse many.
+ Open data attracts almost no customers: Unfortunately, there is no real money making/saving opportunity with data. A lot of promising concepts, but until there is a business model, there won't be a huge amount of focus on this area. Once there is, it will explode.
+ People won't pay for better products: Most people with diabetes have multiple meters, most of which they receive for free. The device companies work on a razors and blades model so are incented to keep costs down and use retrograde technology. When companies try to make higher quality products, relatively few people buy them.
So the best selling market today is a product that was originally designed to be a disposable meter for use in the 3rd world. It's super cheap and does the job while some of the awesome products you mentioned flounder.
Diabetes, and healthcare generally is a hugely complex market. The web of stakeholders blows the minds of most people who enter it. It will change eventually, but it's extremely difficult to bring a startup mentality to the industry because it usually requires thinking about physical manufacturing AND opening your company up to regulation AND operating in a Byzantine payment system. Possible, but improbable. If you're working on something in this area, we'd love to talk.
I get that. I really do, just wanted to vent!
My clinic showed me the iPhone one the other day, and honestly, I would add using the 30 pin connector in with the other proprietary cables thing. Which is a shame as it is /almost/ there.
Just presumably if your iPhone dies, then you can't test which is a potential problem.
Having a great meter with perfect connectivity would not solve the fundamental problem; you need to record and analyze more than just your glucose measurements. You need to record your glucose measurements, your medications (date, time, dosages), your diet, your exercise, and probably other things I haven't thought of yet. I use a simple set of utilities that make it easy to record date, time and tagged data (glucose, carbs, exercise, etc) in plain text files. That leaves me free to write software to analyze my data any way I want.
My goal is to create software that uses Bayesian algorithms to tell me exactly what I need to do (medications, diet, exercise) to keep my glucose measurements nice and flat.
You dont need a whole lot of technology beyond a good glucose meter, unless you are a data freak. I just keep a log on pieces of standard printer paper folded to a convenient size. I note the time, reading, insulin dosage, and anything unusual like pasta or a big desert. The main thing I use the record is to see what kind of corrective dosage I should use if my reading is too high or low. Usually it's less than I would have guessed.
The main thing that works is to maintain a consistent diet, timing of meals, exercise, and insulin dosage. I consulted with a dietician to plan my meals. It was simple and helped a log.
Alex, great article. Check out my startup Infometers.com. We are working to solve this problem and open access to the data siloed on glucose monitoring devices everywhere. Feel free to reach out :) Would love to chat more
For about 2 years I had to keep an old XP box in the corner just to boot it up every 90 days get the data off my wife's MiniMed meter and pump. They didn't support anything newer than XP until 2011, let alone any hope of not needing Windows.
What I would like to see is an integrated system where the a continuous monitoring device comes with the insulin pump and communicates with it automatically. I want open data as well and good software, but more importantly, I'd like to have a device that learns from my habits and recommends adjustments automatically. It would save me the hassle of having to pore through my glucose readings and think about everything every 1-2 weeks, which is what's required of me now to maintain my health (and which I'm negligent on).
And I'd like my insurance to cover it, but that's an entirely different story.
@russel - I think for Type 1 diabetes it would be nice to get a bit more data, I was on continuous monitoring for a week and it was incredibly helpful to see a bit more information than 4 readings per day.
I think with diabetes, I certainly want the data to be adaptive beyond "constant diet, timing of meals" etc.
@j_s - Yes, I think he makes some fantastic points.
@inetsee - Yes, lots more variables than BG readings, but getting that right is a good start.
@axsar - Thanks, will have a look, although it still relies on proprietary data cable.
hi, website does not list all the devices :). I will update it over the holidays downtime. Can you please send me an email with your meter name ( i think said you use the contour USB?)
The diabetes market is already being disrupted, by Dexcom, which makes continuous sensors, and which appears to be iterating every few years. You calibrate them every 12 hours or so, they last a week, and they give a sample every 5 minutes or so, at a cost of about $600+$100/week of consumables. The software isn't great, but it gets the job done and it'll download data over an included USB cable and export to CSV if you just want a spreadhsheet.
Digitizing this data, making it accesible vs. having it as a printer paper folder, is the first step. Once we have the data, we need to make decisions based on it. Computers are a lot better analyzing 1000s data points from multiple vitals. Main problem is the device connectivity fragmentation.... at Infometers we are working to solve that problem. Reason I say this, send me a names of the diabetes monitor you use - I might already support it.
This post is laughably naive. Get out of your bubble. Very very very few diabetics (less than 1% is my guess) care about any of this data. All they want is a simple, cheap, quick, and painless glucose meter.
i think that's thinking inside the BOX or being satisfied with status quo. Most costs/pains of diabetes are from mistakes in care (~75%). The patient manages their condition day to day themselves (99%). Studies have shown that we can catch complications and improve lives by analyzing patient's glucometer data.
While I too hate PDF, let me say that a developer could take a PDF parser and since the PDF report is going to be static, it should be easy to extract the information.
As a developer with diabetes, rather than battle with the terrible software that comes with each meter (or at least, each one I've tried in the last 10 years), it's simply easier for me to enter the result into an app[1] on my phone. Yes, I'd rather not have an extra step, but it's so quick (a few seconds) and I always have my phone with me, that it isn't really that much of an inconvenience.
This way way, the process stays the same independent of what meter I use, the data is easily exportable and I don't need to use Accu-Check 360°, which is dire.
[+] [-] Someone|13 years ago|reply
And yes, that pump will be imperfect, but it probably will do a better job than you can do yourself, let alone than you will do yourself.
I know that, traditionally, patients used glucose level measurements, stared at the numbers, guessed at what caused them and then tried to correct for similar future events, but AFAIK, that has never been very effective. It did give you some sense of being in control, but that was more an illusion than reality. e.g: your blood sugar is high. Is that because you drank a beer last night, because you went to bed late, because you did not sleep well, because you are stressed about something, because you had a fever two days before, because you took the bus to the train station?
However, except from the truly bloody obvious, that didn't help much maintaining blood sugar levels, unless you lived like a robot. Normal daily schedules simply vary too much to allow you to determine the true cause of atypical blood sugar level variations.
IMO, the time of stand-alone glucose meters has passed, and I do not see how having users process logs will help improve their lives. Reading individual measurements definitely will, but that is so that you can react at short notice, and adjust insulin intake.
[+] [-] Adirael|13 years ago|reply
I've been a diabetic for 14 years and that's exactly how I feel. The only way I can have perfect glucose levels is to live like a robot: wake up every day at the same time, eat exactly the same measured amount of food, check my glucose level every time my alarm beeps and do nothing out of the ordinary.
I'm trying to exercise more and the diabetes is the biggest barrier, I'm like a roller coaster right now.
I don't want to stare at a graph and do even more calculations, I want those calculations done by a machine, which can infuse insuline constantly and use more or less depending on my glucose trend.
There are new technologies out there, like this CGM [1] (continuous glucose monitor) which is very small and wireless (minilink minimed) which IIRC can work with an insulin pump (there is one that's very similar, wireless too, with a reservoir for three days of insulin)
[1] http://www.diabeteshealth.com/media/images/article_images/50...
The problem? Price. Most insurances won't cover this, the initial purchase is not cheap and the maintenance cost a lot too.
[+] [-] blangry|13 years ago|reply
There are a number of biological factors that can make a difference, but for type 1 diabetics, the point should be that you know the ratio of carbohydrates eaten to insulin to take. This can vary, but good data helps you get the ratio right. It can also identify if you have high glucose points that match your circadian rhythm, or if you're becoming hypoglycaemic at a certain point regularly and just haven't mentally joined the dots.
Now, yes, you could do all of this through a log book on paper. I could sit down for a half hour each month and look for trends. But, I take readings on a device with digitised output between 4 and 8 times per day. I don't want to have to go analogue with that, I essentially want the blood glucose equivalent of google analytics. I can account for unusual variations (cycled for 10 miles/got blind drunk/etc.) much better if I have a dataset that demonstrates what the benchmark should be.
[+] [-] jimrandomh|13 years ago|reply
This does not align with the practical reality of diabetics or the biological reality of what pumps and sensors do. The situation is much better now with continuous sensors, which display a graph with a sample every 5 minutes with alarms for high, low, and changing too fast.
But you cannot take the human out of the decision process because the most important information needed to decide how much insulin to give is what (ie how much carbohydrate) you're eating, because the effect of insulin is delayed too much. Trying to make decisions from glucose measurements alone is completely inadequate. People are trying to do this anyways, by using dual pumps giving both insulin and glucagon (glucagon has the opposite effect as insulin). This hasn't left the research stages and I don't think it'll work very well.
[+] [-] replicatorblog|13 years ago|reply
Basically, we're seeing little movement because open data has huge perceived risks and minute upside.
+ Open Data = Risk: The reason big device companies don't make open APIs for data is that it opens them up to risk. If some 3rd party creates software that uses device data and a patient ends up in a hospital, or worse, who will the family sue? The 2 person startup experimenting with health software, or the multi-billion dollar device company that didn't police every app made with their data? It's slightly irrational, but from the perspective of device company execs, opening data creates huge potential problems and risks with almost no upside. Also, the data privacy laws in the US and Europe scare/confuse many.
+ Open data attracts almost no customers: Unfortunately, there is no real money making/saving opportunity with data. A lot of promising concepts, but until there is a business model, there won't be a huge amount of focus on this area. Once there is, it will explode.
+ People won't pay for better products: Most people with diabetes have multiple meters, most of which they receive for free. The device companies work on a razors and blades model so are incented to keep costs down and use retrograde technology. When companies try to make higher quality products, relatively few people buy them.
So the best selling market today is a product that was originally designed to be a disposable meter for use in the 3rd world. It's super cheap and does the job while some of the awesome products you mentioned flounder.
Diabetes, and healthcare generally is a hugely complex market. The web of stakeholders blows the minds of most people who enter it. It will change eventually, but it's extremely difficult to bring a startup mentality to the industry because it usually requires thinking about physical manufacturing AND opening your company up to regulation AND operating in a Byzantine payment system. Possible, but improbable. If you're working on something in this area, we'd love to talk.
[+] [-] blangry|13 years ago|reply
[+] [-] axsar|13 years ago|reply
[+] [-] inetsee|13 years ago|reply
My goal is to create software that uses Bayesian algorithms to tell me exactly what I need to do (medications, diet, exercise) to keep my glucose measurements nice and flat.
[+] [-] j_s|13 years ago|reply
http://www.hanselman.com/blog/TheSadStateOfDiabetesTechnolog...
http://www.hanselman.com/blog/HackingDiabetes.aspx
[+] [-] russell|13 years ago|reply
The main thing that works is to maintain a consistent diet, timing of meals, exercise, and insulin dosage. I consulted with a dietician to plan my meals. It was simple and helped a log.
[+] [-] axsar|13 years ago|reply
[+] [-] codva|13 years ago|reply
Great article.
[+] [-] imcrs|13 years ago|reply
And I'd like my insurance to cover it, but that's an entirely different story.
[+] [-] gurvinder|13 years ago|reply
http://mydario.com/
[+] [-] blangry|13 years ago|reply
I think with diabetes, I certainly want the data to be adaptive beyond "constant diet, timing of meals" etc.
@j_s - Yes, I think he makes some fantastic points.
@inetsee - Yes, lots more variables than BG readings, but getting that right is a good start.
@axsar - Thanks, will have a look, although it still relies on proprietary data cable.
[+] [-] axsar|13 years ago|reply
[+] [-] jimrandomh|13 years ago|reply
[+] [-] axsar|13 years ago|reply
[+] [-] ivansavz|13 years ago|reply
[+] [-] dreamdu5t|13 years ago|reply
[+] [-] axsar|13 years ago|reply
[+] [-] ebiester|13 years ago|reply
Not that it's right, but it's possible.
[+] [-] petepete|13 years ago|reply
This way way, the process stays the same independent of what meter I use, the data is easily exportable and I don't need to use Accu-Check 360°, which is dire.
[1] https://play.google.com/store/apps/details?id=com.wonggordon...
[+] [-] brennanm|13 years ago|reply
[+] [-] pebb|13 years ago|reply