Video Translating Guidelines, Meta-Analysis, and Real World Trials to Guide Practical Aspects of Diabetes Care in the Managed Care/HMO Setting Play Pause Volume Quality 1080P 720P 576P Fullscreen Captions Transcript Chapters Slides Translating Guidelines, Meta-Analysis, and Real World Trials to Guide Practical Aspects of Diabetes Care in the Managed Care/HMO Setting Overview 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. Hi my name is ERic Cannon uh Chief Pharmacy Officer with Select Health and Intermountain Healthcare in Salt Lake City Utah. And today I'm going to be talking about applying sensor based glucose monitoring uh to reduce cost intensive adverse drug events and how it's associated with treatment. In my in my regular job we manage the pharmacy benefits and the PBM services for over a million members that are associated with select health and Intermountain Healthcare. So this topic is one that is very pertinent for us today. And even we'll review some literature research that was done at Intermountain Healthcare as part of this presentation. So, to set the stage, let's talk a little bit about the epidemiology of diabetes. U 9.3 of the population have diabetes. Uh the number that's always amazing to me is, there's about 8.1 million people that are undiagnosed If we break that down and look at it in terms of type one diabetes, that's about 1.25 million people. But we're gonna talk about some of the the adverse events or adverse impacts of diabetes. It's the leading cause of kidney failure. Ah It's the leading cause of new cases of blindness among adults. It's a major cause of heart disease and stroke. And it's the 7th leading cause of death. So if we break this down and look at the complications of diabetes, you can see on this side we've got hypertension, hyper epidemiologic heart disease and stroke, blindness, renal disease and amputations. On the next couple slides. I'm going to go into detail a little bit more on some of the research and what I'm trying to do is set the stage as we look at the data behind continuous glucose, monitoring what are the real benefits and what are the adverse events were trying to avoid. So let's start with a heart disease stroke, hypertension. Uh You know, 71 of people diagnosed greater than over the age of 18 Had blood pressure of 140 over 90. Um we're in the process of using blood pressure medications. This is old data from 2009 to 2012, but very relevant today. Uh these same numbers hold true. If we were to look at additional studies, if we look at cardiovascular death rates, It's about 1.7 times higher among adults Age 18 and older. There have been diagnosed with diabetes compared to peers that had not been diagnosed with diabetes. And then if we look at the hospitalization rate for heart attack, it's 1.8 times higher, uh Stroke 1.5 times higher. You get the idea that along with diabetes comes an increased risk of of all of these cardiovascular problems. If we look at blindness, as I mentioned early on, it's the leading cause of new cases of blindness among adults ages 20-74. Uh, if you look at the number of people greater than 44.2 million had diabetic retinopathy. Again, old numbers 2005-2008, but again, very relevant. Uh, today, as we look at this. Uh, and and then if you look at this, 4.4 of those with diabetes had advanced diabetic retinopathy that could lead to severe vision loss. Let's talk about renal disease. And again, you know, another area where diabetes is the leading cause of something. And in this instance it's kidney failure. We've got 49,000 people a little more than that with diabetes that are beginning treatment for end stage renal disease each year. And then of 228 people with the Srd due to diabetes were living on chronic dialysis. And you know, you think about that impact. My wife ran into someone in the neighborhood this morning who said her husband was on dialysis at home. And sometimes we don't think it's around us, it's all around us. And I think, you know, one of those things that really has a true impact in our lives. If we look at the death rate among people with diabetes 7th leading cause of death, uh you know, interestingly, 234,000 of those it was a contributing cause, But 69,000, almost 70,000 diabetes was the underlying cause of death. You know, we know this is probably under reported. And then uh the risk of death among those with diabetes is about twice that of people with a similar age, but without diabetes, Let's talk about the economics here. You know, total cost of diabetes annually is about $245 billion. 100 and 76 billion of that is in direct medical costs. So that's hospitalizations, emergency care, medications, office visits, all of those things run into work into that direct medical costs. We've got about $70 billion dollars in direct in direct medical costs. So that's things like absenteeism, reduced productivity or unemployment. So, uh if we really look at the cost, it is enormous. Uh where do those costs breakout? Uh Initially in this study, that was done by the american diabetes Association, um Inpatient care or hospitalizations were 43 of the costs. The number that was surprising to me, retail prescriptions were 18 of the cost. I've seen some numbers now that that 43 has come down a little bit in terms of hospitalizations and the cost of medications has gone up again. Diabetic medications and supplies physician office visits. You can see the breakdown here on the screen. So what are the costs incurred by people that have a diagnosis of diabetes? Well, average annual expenditures and again, this is an older study, but the numbers still proportionately are true. Almost $14,000 in annual expenses with almost 8000 of that directly attributed to diabetes. Uh More than one in five healthcare dollars in the U. S. Goes to care for people that have been diagnosed with diabetes. If you think about that one in five sounds like a lot, 20 of our health care costs are going to treat people with diabetes people. So what are some of the predictors of costs? And I think this is one of those things that is we talk about a disease state in order to really understand the benefits we may receive in treating that? What are the other things that help predict what the costs are? Um If in looking at a multi variant analysis, almost 1700 adults with diabetes uh for people that had coronary heart disease or hypertension, Their costs were increased by 300%. So $47,000 versus the $14,000. We talked about previously depression costs increased by 50%. 31 32,000 versus 21. And then patients that had a baseline A one C. Less than six had costs 11% below patients with the baseline. A one C. Of 10. And so we've got one more slide here. We'll look at in terms of what is the impact of a percent change in A one C. But you can clearly see it here. Um You know people that have an in control a one c. Their costs 11 less than somebody that's not in control. So I took this from the American diabetes Association's standards of medical care in diabetes. And it's really what is the assessment of glycemic control. And 2017 the D. A. Said there were two primary techniques available to patients and providers that was self monitoring of blood glucose and A one C. At the time. They said continuous glucose monitoring may have an important role assessing the effectiveness and safety of treatment in selected patients. Uh That's from 2017 and I'm sure you know, things from the American Diabetes Association of progressing with continuous glucose monitoring picking up more and more favor. And I think as we look at the numbers, we'll see why that is happening. So maybe to remind you. And this is an old old data came out right after I got out of pharmacy school A long time ago. But uh really looking at what's the impact of a one change in a one c. And you can kind of see the breakdown here between patients. So, Mean, charge per patient without complications. A one c. of six ah $8600. Mean charged per patient with complications almost $3900. Again that's at that A one C. Of six. But then take a look at it down at 10%. You can see that number is now pushing $12,000 instead of 8500. And in the case of complications, instead of being $3,900 or $39,000, it's almost $49,000. So clearly we know and you know, it's just kind of a common reminder for all of us that as we Lower A one C. Those costs reduce along with it. So let's look at the pooled analysis that was done in continuous glucose monitoring and comparing it uh to self monitoring of blood group group. Okay, I'm gonna start this one over. Sorry guys. Um So let's take a look now at the value of continuous glucose monitoring this. A meta analysis. Looking at the change in A one C. They're comparing continuous glucose monitoring to self monitoring. They're looking at it in Children, adolescents and adults all with type one diabetes. And you can see here that uh in Children and adolescents at the study, the analysis favorite continuous glucose monitoring In adults again favored using continuous glucose monitoring, And then in adults with compliance greater than 60 again favored continuous glucose monitoring. And I think being able to see continual drop in those numbers as we go down. Yeah. So uh let's take a look at this slide and okay, I'm gonna start over on this one too. Sorry, let's take a look at the effect of continuous glucose monitoring. This is on a one C. We've got 100 and 58 patients that were randomized to continuous glucose monitoring or usual care. So 105 in that C. G. M. Category 53 unusual care. Uh Looking at the C. G. M. Population, they had a baseline of 8.6. Actually both populations in this study had a baseline of 8.6 C. G. M. User saw a drop to 7.6 on their A. One C. And this is at 12 weeks. Uh And the usual care group also saw a drop but not as significant as we've seen with the continuous glucose monitoring group. Let's take this a little bit further. One of the things they did in this study was to look at the minutes per day That an individual is in a range that would be considered control. So 70 to 180 baseline for the continuous glucose group. They were at 660 minutes per day, that they were in the range of being controlled. The usual care group was at 650 minutes. But after 12 weeks in 24 weeks. And this is a pooled analysis of both 12 and 24 weeks. You can see That number jumps up to 736 minutes per day that are actually in range. And in the usual care group, they stayed flat At that 650 minute number. Now the other I guess measure here would be to say, are we preventing adverse effects or acute events In terms of hypoglycemia? And so again they looked at minutes per day with a blood glucose of less than 70. Um You can see that it was 65 minutes less than 70 and the C. G. M. Group 72 before and then after the CGM group dropped from 65 to 43 minutes. So a significant drop in the amount of minutes spent in that hypoglycemic range. Whereas the usual care group actually saw an increase from 72 to 80 minutes. Uh in terms of having those high folklife seismic events. Yeah. So let's look at this and you know, initially most of the studies we've looked at here have been in Type one diabetics. Uh we know that type ones represent about five of the diabetic population. So let's let's take a look at the other 95 of the population. Ah No surprise the numbers are very similar here. You know, they were looking at a baseline compared to day 215 to 230. Uh Somewhere in there you can see a one c for the continuous glucose group dropped from 8.6 to 8.2. Uh The usual care group actually saw an increase. Not much of an increase 8.6 to 8.7. But there was an increase. Ah I think the important piece here that really came out of this though was severe hypoglycemia only happened in one control group patient. And at the end of the day, there was no difference in advance Where glucose was less than 70. They didn't see any diabetic ketoacidosis. They didn't see any hyper a smaller hyperlocal hyperglycemia either. So uh I saw some improvements, but then some of those other things that we would have been looking to see, you know, in terms of severe hypoglycemia, really didn't see any differences. This is the study I mentioned early on that was done by Intermountain Healthcare uh was published this last fall in september was published online. Uh One of the things they looked at was what are the what are the limitations of past research? As I mentioned, there was a heavy focus on the Type one diabetics We know most of our population were treating as Type two. Uh There was limited evaluation in terms of an integrated delivery network. And so, you know, there's a lot of things that come with an integrated delivery network. So along with that is data. We can talk about the clinical impact on care. We can talk about utilization, we can measure cost all at the same time. Uh This research was not focused on patients greater than 65 although there were patients that were greater than 65. And we'll talk about that. Uh Medicare advantage population here. When we look at the results, you see 99 patients enrolled uh In the continuous glucose. And excuse me, there are 99 patients enrolled, 50 on c. g. m and 49 on self monitoring. Uh of that 99 patients, 93 of them had type two diabetes and six had type one. So what were the results? Well, both groups saw a reduction in their A one C's the C. G. M. Arm, 0.6 reduction in a one c. The self monitoring arm reduction of -1 or minus 0.1. That was significant. One of the things though that was interesting to me was in the C. G. M. Arm. The odds of experiencing a glycemic excursion event uh were reduced by 5.15 every 30 days. So this is a reduction of 5.1 every 30 days month over month. And at some point I would assume that bottoms out. But interesting finding there. So in terms of these events, what did it mean in terms of the data? You can see that any visit at all within the integrated delivery network. Ah The C. G. M. Group finished 56 visits during the period of the study versus the self monitoring group. That was at seven. You can see primary care visits just above just below two versus three. And the self monitoring uh specialty visits uh 2.6 in the continuous glucose arm, 3.2 in the self monitoring E. D. Visits were reduced, labs ordered were reduced. So um this is where that kind of point about the Medicare advantage members comes in ah What we saw was A $417 per member per month reduction in expense for the non Medicare advantage members. And that was the bulk of the study. And so for each member in the study, We saw a monthly reduction of $417 ah In looking at the Medicare advantage population though, we did see an increase in cost, but it was a very small, modest increase of cost just among those patients using uh C. G. M. S. Or self monitoring. So if you were to spread that across the population, probably know it cost impact at all. One way or the other. Let's take a look here at another set of data retrospective. Real world study Looking at just over 2400 patients with type two diabetes that were on either short or rapid acting insulin. So focusing on the more severe type two population, they measured six months before they went on to see GM. In six months after they went on A C. G. M. And they were looking at acute diabetic related events. And they were looking at reductions in all cause inpatient hospitalization. If we break down what were those acute events? They were hypoglycemia, hypoglycemic coma, clinical hyperglycemia, diabetic ketoacidosis and hyper osmolarity. So that's the breakdown of what they were measuring. When we see where the results actually came out. Those adverse events from diabetes decreased from 0.18 events per patient per year. Uh 20.72 with a p value less than 0.1 If we look at the hospitalization rate I'll cause hospitalization. Again it decreased from .42 events per patient per year down to point to a three against significant at .001. So let's talk quickly about the cost effectiveness. One of those things that I think we all focus on uh and this is, you know, making some assumptions that A. C. G. M. Is cost effective at a threshold of $100,000 per quality. Um In looking at it uh in those patients that have an A. One C. Greater than seven, we can expect a reduction of about .53 in that a one c. Uh The Icer 6 98,079 per quali. There was a large degree of uncertainty in this population uh definitely saw some adjustments that included improvements in quality of life, improvements in glucose control and reductions in microvascular complications. If we look at that population that already had an A. One C. That we would consider to be in control. Uh they were able to maintain an A. One C. At 6.5. Uh And in this population the Icer was $79,000 per quality adjusted life year. The confidence intervals were much narrower but still reflects some level of uncertainty. And you know, if it was really limited to preventing long term effects, if we're looking to see James to prevent long term effects Uh that I sir would exceed $700,000 per falling. Um Maybe to put that into perspective a little bit. So if we look at this and this is from the american diabetes association uh they're looking at two different trials the diabetes control and complications trial or the D. C. C. T. Uh Where the trend towards lower risk of C. D. S. Cardiovascular events with intensive control. Uh In the post year nine year post follow on from D. C. C. T. You can see that there was a 57% reduction in the risk of non fatal and my stroke or cardiovascular death. I think you know that follow on is really important because D. C. T. T. S. Told us There was a trend towards lower cardiovascular events. Uh but when they followed up after nine years there definitely was at a 57 reduction. So in conclusion diabetes will continue to have significant clinical and economic consequences. And as we work uh to manage the cost of our population, deliver improved outcomes. Uh diabetes will be one of those things that we need to focus on the costs along with morbidity and mortality or increased in patients with uncontrolled glucose levels. So anything we can do to improve those as something we want to do and then looking at continuous glucose monitoring. It offers an opportunity in selected patients to improve their glucose control, something that we believe in strongly. And we continue to put uh more patients onto the C. G. M. S and at the same time making sure this is the appropriate patient to go onto the product. That's the end of my presentation and thank you very much. I hope you've enjoyed the two previous presentations and now we're going to get um and a little bit of the practical side of this. The the focus of my presentation is a practical roadmap for applying pharma, co economic resource, utilization and registered data to support and facilitate see GM used and managed care setting. What I'm gonna do is run you through several areas. Um So the goals of my presentation include discussing the benefits and pitfalls of C. G. M. S. A pharmacy versus a medical benefit identified published literature demonstrating the cost effectiveness of C. G. M. And the diabetes in diabetes care populations for whom see GM may have shown clinical effectiveness, identify populations that had had been found uh to be useful and cost effective and then also demonstrate a practical approach that we at our health plan took um in assessing whether we wanted it as a farm. Akhil, I'm sorry, pharmaceutical or a medical benefit. So what are the the benefits and pitfalls of the C. G. M. Being placed on pharmacy or medical? Well, I think one of the obvious benefits is for patients. It's a convenience. They're going to the pharmacy to get medications, are going to the pharmacy to get their insulin um going to the pharmacy is is very routine and it's easy, it's local. Um lower patient costs. Oftentimes you're able to put these supplies on a fixed copay versus a medical coinsurance which couldn't save the patient money. The process is simplified because it's just like getting a prescription filled. There is also perhaps better time than this because rather than having to think ahead, send off into the mail or the ethernet for um your refill, you just go to local pharmacist if it's not ready, they'll call you also maybe some possible lower cost to the plans because the plans um may be able to reap some individual uh rebates or other discounts because now you can build very specifically what are some of the pitfalls? Uh I think one of the biggest pitfalls that you're going to see. What's it going to the pharmacy benefit is that it moves the the the device from a medical benefit to a pharmacy benefit. And not all health plans Have both the pharmacy and medical benefit for each one of their clients. We for instance have one large about 30,000 member group that is, we're just managing the pharmacy side for them. Um We're not managing the medical. So sometimes that can create some disconnects in the management of their diabetes as you're not sure exactly necessarily what what's occurring it's not mentioned here but it also can sometimes complicate the process for the provider's office where there used to sending things in one route. Now they have for some plans they have to go medical for some plans they have to go pharmacy. Changing the plan can also cause confusion for patients when they're used to doing things a certain way. And um the other part of it may be that not all of the C. G. M. Maybe on pharmacy benefit. Some of them may only be offered as a durable medical equipment medical benefit and thus that may not um work out in that you can't consolidate things as well as you'd like. That. Also then can cause some confusion for providers because they don't know which devices on which benefits as for medical coverage. The benefit I sort of, it's the flip side of the pharmacy benefit. Um It allows uh um the airlines, I should say with other medical supply acquisition processes so that um it's it's pretty consistent um and also keeps all the services with the same insurer rather than the potential as I've already mentioned of one uh insurer covering pharmacy and a different group covering the medical sign. It does add some complexity to the acquisition. Uh You've got to go to a different site, it separates the insulin therapies and their supplies from C. G. M. Which could also be a negative. Um And also what we've seen is uh DME manufacturers are very good at auto shipping. Um they send that 90 day supply whether you're using them or not because that's how they get paid. Um The other pitfall is less specific building building because you're using pick pick codes that are general instead of a specific NDC codes makes data analysis difficult so that you don't know which devices are being used by which patients necessarily. There are some ways to tell it. It just makes it more complex. So let's talk about the cost effectiveness literature. There are a lot of studies out there for both Type one and type two diabetics. So most of them focus on Type one diabetics. Um There are limitations to this literature. However many of the studies are european. If you're doing a cost effectiveness evaluation, it is very difficult to translate cost effectiveness in europe with the U. S. Because of the difference in the care delivery and the cost that is not translatable to how care is delivered in the U. S. Plus Our costs tend to be higher. Many are registries or non randomized and thus they have more inherent biases. You don't see a lot of randomized controlled trials in this space. Some and actually many of them are are based upon modeling of data rather than the actual analysis of the data itself. And and modeling has inherent problems with it. It's can be useful at times but it's hard to draw strong conclusions from some of that. And you'll see in some of the literature that I'm going to talk about how that can be a problem. Many studies are supported by device manufacturers and that's not in itself inherently evil. It's just that um there is this question as to what biases may be present because uh unintentional considerations that the authors or others are giving unknowingly to the fact that their support is derived from a device manufacturer. So inherently, people tend to discount studies supported by device manufacturers a little bit more than they do for those that are investigator led. Also, another limitation is the fact that most of the cost effectiveness is defined by icer or qualities and that's very useful in europe, particularly for equalities. But it doesn't actually reflect cost savings or two areas where we in the US maybe um concerned about which is health care, resource utilization because that's one of our issues. Lastly, the comparative effectiveness of the various diabetes management technologies is largely based on either the surrogate endpoints of hemoglobin, a one c reduction or reduced hypoglycemic events. Those can be estimated or modeled costs associated with them, um That can be both direct and indirect, these sort of indirect comparisons and the lack of actually looking at health resource utilization and their associated costs. Um get in the way of drawing strong conclusions. So let's talk about um one study that I think highlights the complexity of this sort of analysis of cost effectiveness. This is a study by peace um who uh they did a systematic review. You can see the inclusion criteria, their full or partial economic evaluations based on modeling or are cts of parallel and crossover study design six or more weeks in duration and included community dwelling adults with type wine. I think it's a nice inclusion criteria there They found 16,772 records that they could assess. However, when they started to filter it Um they got down to 152 potential eligible publications out of that 16,000 plus. They then further because only 114 of them reported clinical outcomes and three of them. Um We reported economic evaluations not based on modelling R. C. T. S. They were left which is 35 articles out of the 16,772. So you can see the quality of literature is suffering a little bit and it makes it difficult to draw a strong conclusion. The other thing of note is that the majority of the cost effectiveness analyses were based upon Markov models of 93 And 20 of these used the center of outcomes research evaluation or core diabetes model. So again now we're looking at modeling instead of actual um studies with firm endpoints. The other thing to note was there were only um I'll start this part over. Um The other thing to note is only eight of the studies were based out of the US. are only 23%. The rest were from the UK Europe Canada Australia and thus again, because of the disparity in how health care is delivered and the pricing of services in these different areas, it's hard to draw um strong conclusions from economic evaluations done in other countries. It's also important to note that 26 of these 35 studies had manufacturer support, again. causing one to pause a little bit and wonder now this systematic review did have some outcomes. And they did note that there was um a significant um range of Incredmental cost effectiveness ratios from $14,266 to $2,000,997,832. None of these were cost savings, but some of them didn't add a lot of costs. Um it was less clear when you look at in flint pumps when combined with glucose sensors if they were cost effective and that once again, they were basing a lot of this on the impact on hemoglobin, A one C or hypoglycemia rates rather than health resource utilization. It was noted in the study that non integrated systems e multi dose insulin with um single measurement blood glucose had an adjusted icer of $269,000, whereas integrated systems with low glucose suspend feature um were noted to not feel be cost effective either. Um At 100 and 75 a range of 175 to 784 plus $1000 per quality. Um well above the thresholds that you're you're normally gonna see of 50 to $100,000. So again, this was a large system systematic review and um shows you the struggles. So let's talk about the populations who may have potential benefit from uh C. G. M. I think the obvious are the type one diabetics were uncontrolled despite evidence for strong efforts to manage their disease. That's sort of the standard population that we see it being used in. Also those with hypoglycemia unawareness. Again, they have a high health resource use. And literature is supported pretty well that that um this is a good technology in that circumstance. Another group is pregnant women with gestational diabetes or type one diabetes. And um there was the concept trial Which was published in 2017, which limits um which looked at this now, it was notable that in this trial they didn't improve the hemoglobin a one c that much. Um but the time for these women to have the range uh Of their blood sugar within the normal range was 68 compared to 61 otherwise. And they also had less hyperglycemia. The consequence of that was not so much on the patient themselves but on the neonatal or the infant. Um What they saw is a lot fewer uh infants that were large for gestational age time. In the I see you greater than 24 hours was reduced significantly and statistically significantly. And these these neonatal left the hospital sooner than those who didn't use a gm. All of those have costs associated with them and show the value of of using A C. G. M. In this population. The other population are young, Children with diabetes type one, especially between the ages of 2-6. And most of this comes from the fact that they can't communicate well. So um you're trying to to monitor and use the C. G. M. As a hypoglycemic alarm because they don't understand what they're sensing and they cannot communicate it adequately. And that's another area that we see a lot of you supported in the literature. A couple of less obvious areas include um adolescents and young adults. And in the study by lawful from 2020 they looked at this population and notably only 68 of this population, which was only 153 individuals, but 60 only 68 use their devices more than five days a week. This was the study that went on for six months and at the end of it The A. one c. was reduced from 8.9 to 8.5. Still not well controlled. And it really calls into question whether there's value in this population, which tend to be a little rebellious tends to uh not want to follow the rules. Um the other is the type one patients older than age 18 or older than age 60. Um And this was a study by Rudy. Uh and in in this study they looked at an older population, again, small, small number, but um they noted that this population um 97 of the population used their device six days a week or more. And there was a one C reduction of .4, but more importantly than the A one c reduction was that the time that they had their sugar less than 2 50 was quite significant, with a p value of 0.6 which is quite significant. They also noted that these individuals had less glycemic variability um And with the p value of .02 suggesting that their control is just more even keeled and it's felt that it's these excursions that lead to the complications more than the elevation of the sugar itself. Again, pointing to patients who could benefit from this, particularly if they're on multi dose insulin. Now there are some populations that um we're not as certain about And one is newly diagnosed diabetics. And um in a study by patent um In 2019 they looked at Children ages 5-9 that um Were newly diagnosed within the previous six months with type one diabetes. Um the average age was 7.5. Um and they noted that actually um the hemoglobin A one C in this population was increased by 0.4 compared to the controls after six months, suggesting there may not be a benefit of starting a C. G. M. S. Quite as soon in this population. Now this study had a lot of limitations to it. one. There was only 112 families involved, but also the demographics were very skewed. Um it was 88 White, almost completely suburban. And um, and the families Also, um, were uh, two parents. Um, there were there were no single family households and stuff. So it's hard to draw a strong conclusion from a study like that. Another area of uncertainty is Children under two. And in the McKinley study What they did, they looked at me unaids and they noted that they're just the inherent nature of how see G. M. S. works. Um, the interstitial space, um, there were limits with the technology. Now, this was a study from 2017 and that study um may not reflect current technology, but the literature suggests that the accuracy in this population is not ideal, in part because of the timeliness of the measures and the limitations to the changes in their interstitial reflecting the changes in the blood also. So, um the other thing to be no to be noted in that circumstance is that um the Uh none of the diabetic uh see GM devices are FADA approved under age two. I don't believe so. The last uh group that's uncertain. And I and I think this is being explored as we've heard um are those that are Type two diabetics. And I think what we have to understand is There's type two diabetics that are on multi dose insulin which are very much like type one diabetics. And that population probably do the literature does support but those on basal insulin by itself. Um the the evidence is less clear um and Although it may improve hemoglobin. A one C the question there is whether it improves health resource utilization or or changes things mean meaningful fashion. Lastly, oral medications only. Uh the literature is scant in this area. Um There there have Carlson published to study, but Even in his study he doesn't define his type two diabetics and who he looked at and um One would argue that most type two diabetics aren't even doing finger stick glucose measurements to begin with. Um And as the drugs that are being used are moving away from the uh insulin secreted dogs like cell familiar areas um and moving to other mechanisms that don't have the potential for hypoglycemia. The need to monitor the sugars ask closely is lessened though. Certainly the importance of blood sugar excursions out and and great variation remain so. Um Sub populations demonstrating cost effectiveness. Let's talk about that for a moment. We do know that diabetic type one patients. The diamond trial is one trial that has demonstrated the cost effectiveness in this population. We had 100 and 58 patients. the type one, all of whom have their a one C. Greater than or equal to 7.5. They were placed on C. G. M. And after six months they were looked at, they saw that the total six month costs were 11,000 For the c. g m and 7.2. But 7200 for the control group. So the C. G. M. Was little more costly. But The lifetime complications from C. G. M. You increase your qualities by 0.54 which is not insignificant. So half a year And the incremental cost effectiveness ratio is 98,000 per quality for the overall population. So below that $100,000 threshold, there's been another pop study recently published by Intermountain Healthcare That looked at type one diabetic patients make um looked at 99 patients in a parallel randomized multi site prospective trial. So good trial design using C. G. M. Versus just standard blood glucose monitoring What they identified as an improvement in their hemoglobin. Anyone saved to a P value of 0.01. But they also identified a reduction in health resource utilization because of improved control. So their total visits were down. Emergency department encounters were down and the number of labs subsequently being done were also reduced. They identified that among non Medicare advantage patients per member per month savings and that's important to note savings. We're $417 per C. G. M. Compared to finger stick glucose. It costs a little bit more for Medicare than it did. Um For the commercial population, 70 of the C. G. M. users reported that the technology helped them better understand their their daily disease and also help them understand the effects of their diet on their sugars. Whereas only 16 of the finger stick glucose people had that um knowledge imparted upon them, so definitely showing the benefit in that Type one population. So other sub populations, we've already talked about the concept trial which is probably one of the better trials. And we've talked about type two diabetics. There aren't many studies. There was this one Spanish study by Garcia Lorenzo um in 2018 that looked at real time glucose monitoring. Again, the challenges there, you're talking about different health care delivery and you can see they did not identify in Type two diabetics that um use of C. G. M. Was cost effective with uh qualities of uh €180,553 per quality for the Type two diabetics um Type one diabetics. They identified it to be even less. But again, this study was looking at different cost structures and different care delivery that may impact it Fonda in 2016 also modeled some outcomes. And they suggested in type two diabetic that there could be some cost effectiveness is they have um noted that um the icer was $9300 uh Or $13,000 annually, Well $9 $9300 annually, or $13,030 per quality gained. So um again it it suggests there is some possibility here, but unanswered questions remain. So in the real world, that's where I live. Um Some people might not say that um what are the issues and barriers for using C. G. M. And becoming a standard of care? Um Most of the literature, if not all, demonstrate increased incremental costs, incremental costs in every setting. So it's not necessarily um cost savings um And that's in part because it's not taking into those long term issues with regards to vast micro and macro vascular complications that caused the greatest amount of costs. You spend a whole lot of money trying to present those large costs down the road. Um And health plans tend to be more concerned with short term cost productions because that's what what drives their decision making because members change plans. Um The other issue or barrier is devices traditionally considered DMI and cost reduction opportunities. I want to start that section over or that piece of the slide over unless you want me to do the whole slide over. Why don't we go ahead and start the slide from the beginning? All right. All right, very good. So let's talk about the real world now. What are the issues and barriers um with regarding moving um C. G. M. From medical to pharmacy? Well see Gm it is important to note that C. G. M. Is becoming a standard of care. It's replacing finger stick blood glucose is particularly as they have moved from having to do as many finger stick blood sugars to calibrate the C. G. M. Devices. Most of the literature however, has not been able to demonstrate cost savings. And that's because most of the literature focuses on the short term and not the long term costs, which is where most of the costs are with diabetes. Another barrier is that traditionally these devices are DME they're on the medical benefit and because of that, the codes used don't allow for cost production opportunities that exist on the pharmacy benefit by using NBC level billing. So it makes it harder to track products uh and and understand where those opportunities exist. Also. As I mentioned earlier in my presentation, not all members have a pharmacy benefit within the same plan. So for my plan to cover it on a pharmacy benefit may not impact members who are on my medical insurance. So pros and cons, I've gone through some of this earlier. There are no different than what we discussed. Um You could do NDC building, you can potentially lower the cost to members. You've got some contracting opportunities. Um and with the cons you do lose some coordination of care potentially. Um the auto fields may be an issue and uh in some instances to get those savings, you have to give up some of the controls you have in place on the medical side. And and that can be a challenge because that can increase utilization. So let's talk about some of the pricing. Now, what I have here is a slide that shows the pricing for dex calm On both the medical and the pharmacy benefit. As an example. Now these prices were taken uh from the first data bank in April 2020. They may be changed a little bit and they also reflect some of our own internal contracted pricing. Um you can see that to cut to the chase that the annual cost for the decks calm on the pharmacy benefit is 53 91 On the medical benefit at 71 41. So without any other change other than moving it to pharmacy, you end up um Saving approximately $1800. Now if we go on to look at the decks com versus uh freestyle lee brae on two on the pharmacy benefit, you can see that the library offers even more cost savings. Now I will say that these costs are not reflective of additional rebates that Dicks. Com is offering to move to the pharmacy benefit. So the disparity and cost that you see here is not um accurate. Um And I'm just not at liberty to share the actual cost differentials. But um let's just say that they're substantially more savings uh can be made by moving decks. Com uh to the pharmacy benefit than what you see here. All right, so the situation's been presented to us as a health plan. We were we were approached to possibly look at moving R. C. G. M. Uh to the particularly decks calm to the pharmacy benefit. The findings from the analysis for us. We were we were presented several scenarios um one of which had exclusivity excuse me, one which had exclusivity involved another one um which was less exclusive and allowed us to maintain some controls and and and some that that um allowed us to perhaps save even more but we lost some of our controls that we had in place on utilization. So um we noted that there would be potential savings to the member by the reduced cost share from a from a percentage uh co insurance on the medical benefit to affix copayment in our situation. The member convenience would be greatly improved, possibly leading to better adherence and compliance. Um significant potential cost savings by the plan could also be made by moving to an NDC billing model rather than the hit pick model. We also noted that there were additional rebates available to us by moving into pharmacy benefit. Um One of the considerations, as I've already mentioned is that we could have saved more money by removing some of the coverage criteria, but we were not ready to make that step and another is member disruption. They ban getting it through a certain supplier to, So to make that change over, you have to make sure that you've got a good communication plan. So our determination at the end of the day Was that we were going to move the decks Com 6 to the pharmacy benefit. We would leave freestyle, library and library to are already on the pharmacy benefit and we're not um on the medical benefits. So we did not make a change there. We were continuing to apply our authorization criteria. Uh we gave up a little bit to do that but we felt comfortable with that. But we also noted that we needed to maintain the Medtronic Guardian on the dems benefit as a non preferred product because of patients who are using um Medtronic insulin pumps. And this is a proprietary relationship that we did not want to um cause problems with or having to purchase a new insulin pump. So that's what came down in the long run. We looked at it, we maintained our coverage for those who we felt uh, comfortable with, and we went ahead and moved everything over to pharmacy, beginning this last January one. Published April 9, 2021 Created by
