it's a great pleasure for me to have an opportunity to present to the Association of managed care pharmacist Today I'm Richard Berg install. I'm the executive director of the International diabetes center in Minneapolis and part of a large multi specialty clinic which also has a health care plan associated with it. So I'm very familiar with these issues and it's really an important time to discuss the role of continuous glucose monitoring and its impact on on pharmacy, pharmacy management, decision making process uh and using C. G. M. To manage diabetes and improve care. So it's a great pleasure to talk with you today. This is a C E C M. E. Certified symposium. We thank Abbott for their support of hosting this and allowing us to have a dialogue with you today. There will be three speakers and I get the privilege of leading off and then there will be two more speakers who are really well versed in the managed care world and will bring additional insights into the role of C. G. M. In managed care in the Pharmacy Association. So really uh I look forward to their discussion as well. I would ask you to please complete the online survey and evaluation form. So if we continue to talk about this topic we can make it as pertinent and relevant as it can be. Uh It will be will be webcast so people can can look at it again. The power point slides if you find them helpful will be available and there is a Q. And a session so enter your questions and these will be used in future times to really dig into what's really on the minds of the audience today. So as I begin I'm going to focus on continuous glucose monitoring. I'm a clinician, I'm a researcher but I hope I understand the broader issues as well of deciding when is a new tool really helpful when can it really improve care and be cost effective as well. So we're going to look at that through that lens and talk about continuous glucose monitoring. So you have to decide uh in the next 25 minutes or so, whether you agree with what I wrote in 2018 that I felt a continuous glucose monitoring was really going to transform diabetes management. But you notice I I ended that with step by step. It is a step by step process and I consider you as a as a key part of that step by step process. It's one thing to develop the tools to know how to use them. It's another to get them implemented into practice to get them covered at the health plan level, at the pharmacy benefit level. So let's launch into this discussion and I know you hear about all kinds of new innovations. Um but I think you'll find this one to be one of the key ones of our decade of our century, even in type in diabetes management, these are my disclosures. Just to tell you, I've worked in this space for a number of decades now, from the research side to the training side and look forward to talking more with you about it today. I think the place to start is really what are the tools we have used for glucose management over the decades there? You're familiar with these. And it starts of course With the a. one c. and finger stick blood glucose monitoring. That A one C. Is so common to the clinicians, to the administrators, To the people who look at judging. Are you doing a good job with diabetes management, glucose control management? It's not so easy for patients to understand when you look at a hemoglobin molecule here and you say glucose attach us to the made a chain of the hemoglobin Patients kind of glaze over. But if you just tell them it's your average sugar over 2-3 months, they get that concept of the average test Finger stick, glucose monitoring has been around some 40 years. Um and there's lots of tools and and and choices that can be made. Here's what we see in the office. Just for your information, we see numbers. This is a good day, actually. Whole string of morning blood sugars. So the patients trying, they're making an effort. But I think you would agree with me if you saw this, you would say, well the mornings don't look great, but I really don't have a whole picture. I really don't know what's happening the rest of the day. Um But thank you for doing this. At least we'll take our best guess at what we should do. And then we move, we move forward a bit to the next one. We say, you know those butchers you were doing. This is a little educational tool that we use in our center is steeped in developing tools to try to get the message across to our patients. Um those blood sugars you were doing or those ones right in the middle there on the top panel here, uh and they look pretty good. But you know, if you had blood sugars done all through the day and night, you would realize that you're missing some lows, you're missing some hives. That those two or three blood sugars you got done in a day, we're just a snapshot and not really representative. So we're moving forward to aggregating the data. 14 days of Blood sugar has done every one minute to five minutes and putting it into a single page report. That's what we consider the aim. The goal. Can we get visualization of your glucose data That helps us make a clinical decision to reduce glycemic burden that you're facing? And that revolves around having a sensor, having a sensor that monitors the blood sugar continually. Um And we have at least four major players in the United States. Adex calm their G six and G seven is coming soon. The Abbott freestyle library and the library to which is now available. Uh and Library three coming very soon. Um already available in europe. So they're small. They're accurate their factory calibrated. They're not invasive. You just put a patch on it goes straight to the cloud. So remember that that's the critical thing that this data is all hovering available in the cloud. Medtronic is in the game ever since. Since the onyx has an implanted system for those special situations where that might be helpful. So are we actually in need of a new, interesting tool? I continuous glucose monitoring and I'll bring you back to, well, how are we doing if we're doing fine of all the A. One CS are in control and we're not seeing complications and maybe we don't need a new tool. But let me just show you briefly what you deal with every day. I know. So I'm Just recapitulating for both of us here. Let's start with type two diabetes. That's 95 of the market. Um And we're not doing so well at reaching those A one C goals that everyone has agreed on, about 50% of the time we reach it. If you're on insulin, Only about 30 of the time are we reaching our a. one c goals, That doesn't mean insulin is not a good drug. It means we need better tools to visualize the glucose to know how to adjust the insulin to motivate patients to take their insulin adjusted appropriately. Now, you might say, I'll tell you my primary care colleagues tell me, well, There's more than just the a. one c. We monitor at the health land level. The A. B. CS. The A. One C. Yes, the blood pressure, the cholesterol. We're going to grade you on that. Whether you call it N. C. Q. A. Or you call it hideous or in Minnesota, we um lovingly call it the D five because we add smoking and aspirin to these abc. S. So guess what? When you look at the A. B. CS across the nation, across our organization, You see that the b. And the c. The blood pressure and cholesterol are actually getting better over the decades. From 2000 to 2016. And I have a some more data now, up to 2018. Um They're getting better. But look at the a. one c. It started to get better and then in this last five years it's actually gotten worse. So abcs are important. I wholeheartedly embrace it. Um but if you can get the A. One C down, you're going to have a better A one C panel. So glucose control is still important. Even if you're looking at the A. B. CS and I'll come back to the remote nature of this monitoring in a minute. There's one more thing that you're hearing about when you hear about diabetes today, it's cardiovascular disease and chronic kidney disease. And you I know have seen by now the american diabetes Association standards of care. New glucose lowering medication algorithm. This is the very latest January 2021 update. And basically not to go in any great detail. I'm just trying to make the point that the first question we are asking in primary care today is about do you have heart disease or kidney disease? Okay, that's really important. And you should help primary care understand how to ask that question because that's a selection of the right drugs to lower their risk of heart disease and kidney disease is important, but right behind that is are you reaching your glycemic goal? Because there's also I disease kidney disease due to high glucose neuropathy hypoglycemia. So, let me show you highlight this series of questions. Look at that on the algorithm. If your a one C. is above target, what should I do? So the A one C. Is critically important. Even these new algorithms because they all keep marching towards being sure you get the A one C controlled and we're not doing a terribly good job. I'm not so sure. That's the right language for these algorithms. This is my opinion now, But it's 35 years informed opinion. I'm wondering if that A one C above target should be, I don't know if it's going to be replaced but could also say or your GM I your glucose management at indicator, your estimated a one C based on C g M data. Is that above target? Maybe that would be a better tool to get us to goal? Or maybe we go all the way and say, is your time in range reaching target? Or even better we say, are you in range but not having hypoglycemia Because remember there's a whole part of this algorithm that talks about minimizing hypoglycemia, it's so dangerous. So I just want to put in your minds right now that Every algorithm is written around a one C. But there's a shift coming that that might not be the dominant discussion in the near future about achieving glycemic control. So that's type two diabetes. We've got a ways to go. We've talked about some tools that might be helpful and we're going to explore those in a minute. How about on the side of type one diabetes? Not as common but critically important. And these people need a lot of assistance and help from your groups in particular. We're not doing a very good job in Type one diabetes. Look at this curve of the average A one C. Um Over the years of different ages of patients, you can see the adolescents here um in orange in 2016. And then a couple of years later we thought we were doing better and we're actually doing worse. That green line is where we want to be and nobody's making it. The adults do a little better than the adolescence. But we have a long ways to go. Now. I'm going to ask you to look at that curve. Just pick the orange one for a moment. And if you squint if you look a little bit and you say. But within that curve is somebody doing all right and others not doing all right. So that's the average curve. Is there any hope for us in type one diabetes to flatten that curve out. So here's the answer. Here's the same data broken out now by therapy. And up at the very top is somebody taking multiple shots of insulin who has type one diabetes. They're really not doing that well if you give them a pump and green below that they do better. So you know your organizations are covering pumps and your managers are learning how to use pumps but now go down another notch and give them see GM either with your multiple daily injections or with their pump and all of a sudden they do better. It's the C. G. M. Is the continuous glucose monitoring that adds value beyond the pump or beyond the injections. So that's why we're really encouraging all type ones to think about C. G. M. Now this is a database correlation study So I'll show you one more slide not to get into all kinds of studies but I know you like the facts. You like the studies. This is a three year observation and look at the lower right. Just I'll show you that the red and the blue. It's the same answer finger sticks at the top and red here if you use multiple injections or you use a pump and you do and you monitor it by finger sticks you don't do so well if you add see Gm to your pump or to your daily injections all of a sudden you do better over three years. This is not just a flash in the pan of a quick clinical trial. So what was the answer for this for type one diabetes? The answer was C. G. M. 1st that we're asking all insurance companies were asking all clinicians to please have the discussion with their patients with Type one diabetes about considering C. G. M. It really makes a difference. Now. Is that the same in type two diabetes? Well that's where we've got some work to do and that's what we're going to discuss. Uh right now, I know the title of this talk talked about meta analysis as well and and bringing all the data to the table. So I'll show you one meta analysis. This is we've done enough. See GM worked out in the last 56 years that we can start compiling them. And this is all the studies of as of when was this? Published in 2020? Just a year ago. Now, that on the left shows the A. One C. Change on the right shows the time in range change and on the left you see the A. One C. Goes down in almost every trial that uses C. G. M. And there are some that it didn't change. But most of those trials where the A. One C. Didn't get better. It's because the focus was avoiding hypoglycemia. So you want the a. one c. to stay about where it is but get rid of the Hippo and on the right side says you wanted to go to the right side if it's improving because the time and range goes up, you have more time between 70 and 180. This is Type one and Type two. So the data is building to say This can help us do better than that. 50%. Um A one C reaching target. But is it really endorsed? Is this just some researchers opinions will know the american diabetes association Has now prominently put see GM into their standards of care. 2020 was a big year To say we now have 10 core CGM metrics that all clinicians should follow. And I think all health plans should follow. Although I'll give you the two or three that I think you really should follow. The 10 are helpful to get a big picture time and range. What's the target are we reaching it? How do you look at the data? There's a report called the ambulatory glucose profile which gladly the international diabetes center where I work has been played a major role in getting that report to people. It's a three page report. It has metrics at the top, it has a profile of two weeks of data visualized as if it were one single day where you can see the highs and lows and then it has all the daily views. I know there's some there's some case managers out there, some diabetes educators from pharmacists who play such a critical role in this management and they really like to look at the daily views to say our weekends different than weekdays are work days different than non work days. Is that thursday exercise session um causing lows or highs. So we're starting to learn what's important in the data, how to organize it. And I'll just show you those 10 metrics. I'm not going to spend a long time on it. But I want to point out a key one to you because in your position in your environment and this diabetes management uh community we live in. There is one called the glucose management indicator. It used to be called the estimated A one C. You take all your blood sugars and you estimate what the A. One C would be. We rename that the glucose management indicator. And that's a long story in and of itself. But um it was myself and and Roy Beck and others working with the Food and Drug Administration to come up with the term that was satisfactory to them. That didn't get confused with the a. one c. And yet gave us that same measure. You can take the average glucose from C. G. M. And converted into what an A. One C. Would be. And we call that the glucose management indicator. And without getting into big detail they don't always agree with the lab A one C. And people were upset about that. And yet it turns out that that's really important That sometimes your .5 off, your .7 off and that's really actually important. It doesn't mean the lab is wrong. It doesn't mean that C. G. M. Is wrong. It means that the glucose data and that individual is better expressed by the glucose management indicator than the lab A one C. Because the lab A one C. May be influenced by a hemoglobin apathy, by an iron deficiency by chronic renal disease by a different lifespan of the red cell. But the g. M. E. Is based on your real actual glucose. You're seeing not how well that glucose binds to hemoglobin. So if I had this patient here in front of me and their lab came back 74 and their glucose management indicated their estimated a one c from c jing Came back 6.7. I would I would look over here and say, Yep, that fits about 12 of people Have a difference of .7 in their a one c. This is not unusual. I would trust the gm me to be honest, because you've got to be careful. You're already at goal. And if you saw the 74 and said, I think I need to adjust the insulin. I think I need to add another medication to get under seven. You're putting that person at risk for hypoglycemia because they're already Actually exposed to glucose levels that give them about a 6.7 overall glucose exposure. So I know it's a little complicated but what I'm what I'm saying is don't always trust the lab one. See this G. M. E. Is probably a better personal indicator. The A. one c. is a perfect indicator for thousands of people put together in a clinical trial. But for that person that you're seeing in the health plan or you're seeing as a pharmacist helping manage their diabetes. The C. G. M. Data is much better. So what do I call the GMI? Just to put it in perspective for you? I call the GMI the personalized A one seat. It's your personal individualist A one C. Some people put it into that precision medicine category because we're all abuzz about precision medicine. I think CGM is the first major precision medicine tool in diabetes management. Later we'll get genetics and other ah mix. But right now it's C. G. M. Okay next is time and range. There's five different time in ranges in range above range below range and we'll talk briefly about them. Here is the picture from that ambulatory glucose profile or a G. P. Report. And I would encourage you to figure out a way to get this report available to your case managers to your clinicians So they can see these metrics. Remember I said there were 10 core metrics the A. D. A. And the diabetes community agreed upon. There. They are. They're all in this top panel of the GDP report there's 10 metrics and we have the targets in this box on the left here that tells you where you like your time in range to be Because look at this 47 And you'd say this person 47 of the time, 11 hours and 17 minutes out of 24 hours, they are in a good target zone. That's going to minimize the risk of complications. And then the patient says, what Well is that good? Is 47 where I want to be? Do I just have to get to 50? Do I have to be at 100 and so that's why over on the left here, we lay it out clearly. We want this to be greater than 70%. We want your lows to be under four or under 1%. So that's the key metrics we're looking for. So now for the clinicians in the room. So for people who aren't seeing patients day by day, bear with me for just two minutes here, I want to show you how easy it is to take an ambulatory glucose profile report and actually read it. So there's a lot of good numbers they're all interesting to track. But I would say you've got one minute in the office, go straight to this top bar, go straight to the time in range bar and just look at the green and the red. And here's the mantra that I came up with a few years ago and um some may like it, some may not, but it's more green and less red. We just wanted to get that green time and range as high as possible. We want to get the red, the low and very low as low as possible. So you look right here and you say do I have a problem? And you define problem? Why am I, am I reaching 70 or not? No. Am I Less than four for these two added together? No, I'm at 10 and my less than one for the very low, which is really dangerous. Those are the ones where you get the arrhythmia, you get the sudden death, the death in bed overnight. Yes, we've all seen that. I I'm sorry to say okay. So you go right here and you say do I have a problem? Then you've got to go to the next panel on the report and say okay, I understand I have a problem, but where is the problem? And within a 30 seconds you can look at this and say, oh I got some lows overnight and in the mid afternoon and I better address that first because that's an acute complication. But I also see some highs after breakfast and after dinner uh looks like this. Uh this person needs some attention to those mealtimes as well. That's comes next to get rid of the lows. Then treat these highs. Try to flatten out that curve. Okay, so I call that more green, less red. The flat, narrow in range. Sorry, I liked these little epidemics here, so I like to flatten this out, get it as narrow as possible. The shaded blue is how much variability there is around this median line. So if you can get that type and inside that green, that's our goal. And then look for these patterns of is there a particular day to work on? Okay, so all of this is trying to get you to think about an evolving paradigm and you're really right in the middle of it now, we're at this exciting time that all of us together are going to have to figure this out. Are we moving from an A. One C. Management era to a continuous glucose monitoring management era? I think so. I wrote about it with my friend Dr Battellino and diabetes care a few months back. A one C. is going to be around for a long time as a long term risk manager a marker. But see GM is how you manage the disease. A one C. is not so good for management. It may be a risk marker. So A one C. 2 time and range. Are we ready to cross this bridge? Here's what primary care says. Uh can I just stay with my A one C please? I finally understand it. Can I stay with my A one C. As a management tool? And I'm sorry to say. The short answer is I don't think you're doing yourself a favor by staying with the A. One C. And here's the best way to look at it. Here's three patients. I happen to know these patients well. There are three of mine that I followed for 30 plus years And I thought I was doing a good job. You know, they all had an a. one c of 6.7. But you can see at a glance the patient at the bottom has nine times the rate of hypoglycemia here to find under 70. Then the patient at the top, the patient at the bottom has twice the glucose variability has, you know, a third last time and range. So if you're stuck with the a. one C, you're not going to do anything in these patients, they all look great to you. But if you're looking at the C G. M, you're definitely going to do something about those middle two and you're going to congratulate the one on top. So I circled hypoglycemia here. Is it really that big a deal? Do you in your position and managed care and pharmacy associations? Do you really care about hypoglycemia? Well you should this nice work out of Yale in Jama back a few years ago showed that in the blue um was the amount of hypoglycemia related um hospital admissions and then the orange was hyperglycemia. All of a sudden we've shifted. It's no longer just hyperglycemia coming in the door and ketoacidosis. We're worried about people are coming in for hypoglycemia. So yes if C. G. M. Can minimize that hypoglycemia, that's a tool well worth it. And so here's the data. I try to back up recommendations with data And look at the study that showed, I'm sorry for the million moles but under 70, under 60, under 50 all were reduced. All of those readings were reduced using C. G. M. So hypoglycemia is a major target for using C. G. M. To minimize the rate of hypoglycemia, hospital admissions um And hopefully cardiovascular death, death and bad etcetera. But then people ask me, well okay but this time and range thing, you know, it doesn't really correlate with complications because that's why we use A one C. If you could tell me that it correlates with complications and it's a good management tool. Now I'm going to think about monitoring, see GM and the Gm me more carefully. So I'll show you the data. Let's go back to the D. C. C. T. Which is a study that proved that A one C. Was important. I worked with dr beck again to look at that D. C. C. T. Data. Um and say Let's let's look at complications related not to their a. one c But to their time and range from their seven Glucose profiles. There were 1440 patients. They all did four Seven Point Glucose Profiles four times a year. So that's 40 profiles for 1440 patients. And amazingly The time they spend in range if you were at 70 time and range, remember I said that was the goal. You had a five chance of getting retinopathy. Whereas if you had 10 of time and range, you had 10 times the risk and the same with kidney disease as marked by micro albumin urea. So incredible correlation Type one diabetes I know but of time and range and complications. So now let's look again just last month. So the timing was good for recording this discussion with you because there's a really nice study in Type two diabetes over 6000 followed for 10 years. And these are what we call the survival curves. And we're looking at all cause mortality on the left and cardiovascular mortality on the right. And the green says I had a time and range of 85%. And the red says I had a time and range of less than 50 dramatic difference in survival. Um if you have more time and range, you have much higher survival rates With more time and range. And then I like this little insert they had in their figure that it crossed over at 70%. So we were pretty good. And are guessing I call it guessing informed, guessing uh to pick 70 as our as our target. Because above that you started to have increased mortality below that reduce mortality. So I think timing range is a pretty good marker and it's also a good management tool. So okay, back to the clinical, remember I'm a clinician at heart and I've looked at these numbers for years. So here's some finger stick glucose is and you say, oh gosh, I don't know exactly what it's telling me. This is a patient on insulin met foreman, a GLP 1 80 units of guarding. I don't know what I should do. I wish I had a C. G. M. Okay you do. Here it is. Now look at the picture and you see Lows overnight. That's from that 80 units of guarding. But you needed the 80 units because you're trying to get the a one c. Down, it's still at 8%. So you'd be tempted to give more. But look what you're gonna do, you're gonna knock this person off the edge. They're going to not wake up one morning or they're going to have a severe seizure at night because you're trying to get their a one c down with more background insulin. You've already put in a GLP one to try to help with the meals. Look at this pattern, you know what it's called? Um If this is a classic pattern, that's that's called um over basil ization, you have too much basil insulin and you have the stair step pattern from breakfast to lunch to dinner. You go up and up and up. So I called the stair step, the american diabetes association calls it over basil ization. Um And and that's the picture on the left. I just showed you a minute ago, 46 time in range. We got to do better. What would you do? What would you do next? Well, I'll cut to the chase and say what we did was say cut that large in in half and put some mealtime insulin in your already on a GLP one. You could probably stop the GLP one if you don't if you didn't take it because you had heart disease, that would save you a lot of money if you took it because you had heart disease and keep it there. But add something to control the stair step blood sugars. So that's what we did New time and range 88%. The lows are 1%. They used to be 46 and 10%. So we've gotten rid of the major problem of the green and the red. We've got more green. We've got less red. What did the profile look like in this patient? Was it flat, narrow and in range? Well, we're darn darn close to that. We're pretty narrow. We're pretty we're pretty in range and we're almost flat. We got a little bump dinner still but it's still within the target range. So it is possible to use C. G. M. To help guide you to the goals were getting for more green less red, flat narrow and in range profiles you've got to titrate, you've got to adjust. So if you have any case managers, if you have pharmacists that are helping with this this is their job, look at this data. Um And I think what I'm going to say is look at the data in the cloud. We're in a whole new world now and you guys know it better than anybody. We're in this remote a virtual health telehealth world. And I helped write this article where we're just seeing the C. G. M. Data flowing in to the electronic medical record. People interacting with their health care provider virtually where I can sit in my office and look at the data and you can look at the data and we can have an informed discussion. You don't have to take a half day off of work, come into my office for 20 minutes to look at the data together. We can do it remotely. It's also an equity issue. This is the only place I have time to work that in. But people need this who don't have cars who aren't going to come into the office, Who aren't going to get an a. one c. measured in the lab. You can mail them A C. G. M. And you say oh that can't be true. Here's a study where you did with on duo has has this incredible um model of ship out of C. G. M. Monitor them remotely. Look at this A one CS were over nine. They dropped 2.6%. That's a reduction in risk and cost. And if you were under seven you really didn't improve your A. One C. Because you didn't want to you wanted to reduce hypoglycemia or keep it stable so the model can work and remote telehealth is critical and then I'll just close with this. It's all about cost as well. Right? It's got to pay off in the long run. So we did a study where we looked at a huge database and this was just featured you know uh Well I guess it's this month it came out last month featured this month by uh endocrine society. And just look at this picture. If you look at these enough Um you don't see many hazard ratios that get to get to 60 or 33 reduction in acute diabetes events, reduction in hospitalization for people who started a continuous glucose monitor. So we looked at the data six months before and six months after, we looked at it in the IBM Watson database, um 30 million individuals. Lots of people with diabetes. We looked at those with type two diabetes on insulin and look at their reduction in er visits and ambulance calls and look at their reduction in hospitalizations in the six months after they started C. G. M. So I hope this brings a full cycle and I'll close I'll close again with my thought that I I'm still convinced that C. G. M. Is transforming diabetes care. I'm think we are already crossing this bridge into the sea GM management era. I hope you agree with me and we'll work with us to figure out how to make that happen and we can get across this bridge if we need the G. M. E. To guide us over the bridge to get comfortable with the time and range and time below range, that's okay with me. We'll use the GMI but we'll get there. So I thank you for your attention. I hope you have questions that I'd be happy to help answer the ones you send in and I wish you well as you figure out the best ways to manage diabetes in your setting. Thank you very much.
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