Hello, and welcome to today's webinar, Utilizing Electronic Health Records to Identify People with Diabetes at Risk for Therapeutic Inertia. This session is brought to you by the American Diabetes Association's Overcoming Therapeutic Inertia Initiative, supported in part by Sanofi Diabetes and Novo Nordisk. Hi, I'm Kevin Peterson, the Vice President of Primary Care at the American Diabetes Association, and I'll be moderating today's program. Today, we're joined by two experts who will highlight the criteria for therapeutic inertia and showcase workflows to effectively use data to identify and intervene in the care of people at the highest risk. Today's panel presenters include Chavi Mehta, the Medical Director of Quality at the Palo Alto Foundation Medical Group in California. It's a large multi-specialty group in Northern California affiliated with Sutter Health. She's been working on addressing clinical inertia in the treatment of diabetes and improving comprehensive care for people with diabetes, focusing on cardiovascular risk reduction. She's been part of the ADA's Overcoming Therapeutic Inertia Initiative since it began. Nei Lane Ong is a primary care diabetologist at the Mohawk Valley Health System in Central New York. He's been serving as the co-leader in the Glycemic Management Team, which is a quality improvement team for hospitalized patients with diabetes. Dr. Ong has volunteered for the American Diabetes Association Overcoming Therapeutic Initiative since it began. Listed here on this slide are the faculty disclosures. No disclosures to make. By participating in today's webinar, you'll be able to recognize how to use electronic health records data to identify people at risk for therapeutic inertia, recall how to interpret and analyze data and create reports to integrate those into your practice, and identify effective workflow models that can be used by the diabetes care team to leverage your EHR. Today's session will be recorded, so the recording will be available for viewing on the Overcoming Therapeutic Inertia website. And we'd invite you to visit the Overcoming Therapeutic Inertia website. It's therapeuticinertia.diabetes.org for downloadable resources that will support your practice. We'll be hosting a quality Q&A session at the end of today's presentation, so please use the Q&A feature to submit your questions. We'll try to address as many of those questions as we can at the end of the presentations. So let's get started. I'll turn it over to you, Dr. Ahn. Thank you very much, Dr. Peterson, for your introduction. So I will start with a little bit overview of what the therapeutic inertia, what is this important and stuff, before we go to the today's topic. So as we all see here, this is the data from New England Journal of Medicine articles published in 2021. So this study looked at the A1c trend in the U.S. adults from 1999 to 2018. So in this period of time, you know, as you all see, there is no significant changes in A1c trend in U.S. adults in the population level. So one thing we have to keep in mind is during that same period of time, we have newer medications, we have newer technologies, we have newer approach to, you know, diabetic education, nutrition, and other healthcare approaches. And if you look at individual medications and technologies, not just in pre-FDA approval trials, but also in the post-marketing real-world data show that those medication works, those medication will bring down A1c to better level, to the control level. But, you know, that does not translate to population level A1c trend, as you all see in this slide. So why is it? So there may be some, you know, different, you know, the contributing factors to that. But what we find out in other researchers are that, you know, one of the research, for example, in 2014, there was one paper looking at, you know, retrospective analysis of the insurance claim data for 90,000 people. So what they look at is whether those patients, those people with diabetes got appropriate A1c check according to ADA recommendation, which is if A1c is above target, you should probably get an A1c check every three months. And if A1c is within target, you can check, you know, you can relax the frequency to maybe every six months. So do they get A1c check as per ADA recommendations? And they also look at if A1c is above target, that's their, you know, did their treatment change? You know, is there any like treatment modifications? So what they found out is only 6.8% of 80,000 people have, you know, appropriate A1c check, which is maybe four times in a year, if A1c is above target, and maybe at least two years, if A1c is at target. And they look at those who have a higher A1c, how many percentage of them get a treatment modification after A1c is not at target. So only 38.9% got, you know, treatment modified after we found out that A1c is high. So there's another study in fact, you know, first published in Diabetes Care in 2013 by Dr. Kunti and group. So what they look at is those who are diagnosed with diabetes, those who are already on one oral hypoglycemic agent, but their A1c is at not at target. So they're defined by more than 7%, or the 7.5%, or more than 8%. And they follow and see how long does it take to add second hypoglycemic agent. So it took about 1.6 to 2.9 years, not months, it's years, 1.6 to 2.9 years to add the second agent. And then they continue following up. And then it took about seven years to add the third medication, although A1c is still above 7.5%. So which shows that although there are new medications, new technologies out there, the usage of those medications and technologies and other innovative, you know, approach in diabetes management, that management might not be utilized effectively. So that's one of the reasons why the ADA organized this, you know, Overcoming Therapeutic Inertia initiative. And Therapeutic Inertia in diabetes care is defined as a delay or inaction to initiate intercified or de-intercified therapy in a timely manner when the glycemic treatment goals have not been met. So I'll talk a little bit more about timely manner in the next slide, but I just want to focus a few points here in this slide, which is it is important to intercify the treatment regimen when the, let's say A1c goal is not met, you know, A1c is high. And it's also important to de-intercify when hypoglycemia presents. So, sorry, we just talked with our moderator, Dr. Peterson. He was a part of a study, which is one of the landmark trials. And he found out that, you know, you know, if A1c is high, it's not good clinically, it can increase mortality morbidity. At the same time, if you have a lot of hypoglycemia, you can have, you know, bad consequences from it. So if, you know, as important as intercification of the treatment, de-intercification of the treatment, when hypoglycemia exists is also important. So, you know, that Therapeutic Inertia contributing factors might not just from the clinical related factors. They may be from the patient related factors. They may be, you know, something else, maybe system or relative factors, maybe payers, you know, not, you know, covering the insurance, you know, insurance not covering the medication and stuff like that. However, we should not underestimate the provider role in other factors as well. So we should, we should not just, you know, recommend or give the treatment regimen to the patient. And if the patient does not follow through, we should not just, you know, label non-compliance, not adherence, and then, you know, put the blame on the other side, because we, our role has much more, you know, much more than that, just, you know, recommendation. So whenever there is so-called non-adherence or non-compliance, we should probably look for more information. What is the barrier? Is there, you know, anything that you can fix? You know, our recommendation does not fit into the patient's lifestyle. Then how can we modify our recommendation? You know, if the insurance is not covering this particular medication, can we get a similar medication or can we do a prior authorization? So OTI initiative just had a few months ago on the prior authorization tips. So the webinar is on the OTI website. You can go and watch that too. So can we do something to overcome the therapeutic inertia, even though it might not directly related to, you know, to clinicians? So at the end of the day, you know, at the end of the visit, we just have to ask ourselves, we just have to ask myself, you know, did I do everything in my power to overcome therapeutic inertia, to make sure the patient received the appropriate treatment for better control of the A1C? So why do we care about the, you know, therapeutic inertia that much? So the data show that, you know, reduction in the A1C will help with reduction in the complications. So we are in the A1C-centric, you know, diabetes management. At this point, we might probably switch to, you know, TIR-centric. However, still, you know, this, the recommendation come from the LUNMAP trials, which was done maybe a couple of decades ago. So UKBDS and DCCT and all those trials show that if you can lower down the A1C, you are going to see a reduction in the complications. So in those trials, what they do is that there are two groups. One group got an intensive treatment so that they get a better A1C control, and the other group does not have that, you know, A1C control. So what they found out in the original trial is that the A1C reduction, you know, the better A1C, those who've got a better A1C, there is a reduction in incidence of macrovascular complications, such as retinopathy. So we know that A1C reduction helps, but they don't see any significant difference in terms of cardiovascular disease. But those two groups, like two cohorts were follow up. And then after 10 years, you know, UKBDS has a 10 years follow-up, DCCT has added, and then VA study has also 10 years, the study, which showed that at that point, at the follow-up point, the, you know, the patient, the patient in both group has a similar A1C now. So those who get a better A1C early on in the stage already had, you know, very comparable A1C with the other group. However, the benefits of having A1C control early on in the disease stage still have a protection effect and still have, you know, lower risk of incidence in terms of macrovascular disease. On top of that, those people would have a lower risk of cardiovascular disease as well. So the new term called legacy effect of metabolic memory, which means that A1C control is important, but not just A1C control anytime during the disease stage. Early A1C control is very important to prevent the complication at that time, as well as for the future. So another thing is an economic model. This is a study from 2020. So it shows that if you delayed treatment intensification for one year for 13.4 million people with type 2 diabetes, then you can, you know, lost 13,000 plus life use and 7.3 billion U.S. dollars a year. And ADA just reported a very interesting economic analysis report, not even a week ago, I think a week ago or so. So what they found out is that, you know, in 2022, the United States, you know, spent about 412 billion U.S. dollars to take care of people with diabetes. Out of that, 308 billion dollars were spent for direct medical care. And out of 308 billion dollars, only 17 percent of that money was spent for the medication and medications and the supply. So those are medication, those are the data show indirectly that we are not using those newer medications. Another thing is those newer medications are expensive. That's true. If more people use that, you are going to spend more money. However, we may be able to reduce the, you know, complications and the, you know, cost, which is related to treating the complications. So we might, even we spend the same amount of money, if the patient does not have complications, we'll be able to, you know, spare indirect medical costs like disability, you know, loss of labor, and also help in the clinical aspect and quality of life. So some of the, you know, the studies are not mentioned in this particular slide desk, but if you go to the OTI website, you'll be able to see all the information there. So this is a little bit overview of the therapeutic inertia. So, but today's topic is more like our personal connection with the TI. So we know that TI exists, TI is bad. We need to do something about TI in the population level. How about our personal connection, personal relationship with the TI? So, you know, if do our, you know, the patients we are taking care in our clinic, in our healthcare system, in our hospital system, do they have TI too or not? If so, how many percentage are in TI? So there may be some ways we can find out. So Dr. Shami Mehta is going to, you know, share some, you know, some tips, how we can utilize the EHR to find out our patients in our clinic has TI or not. Dr. Mehta. Thank you, Dr. Ong. So thank you for, for helping us define therapeutic inertia, the burden of therapeutic inertia that we face and the dangers of therapeutic inertia, including the diabetes complications and the mortality and the huge economic burden that you mentioned. So it highlights the importance of it and that we need to do something about it. So kind of moving on to the, to the, to the next part of this webinar is that how can we utilize the EMR to identify patients who may be experiencing therapeutic inertia? And, and what are some of the workflows that we can develop? So from the EMR, from the EHR perspective, there could be three definitions of therapeutic inertia. The first one, pretty simple for patient has had no A1C measurement in the last six months. The second definition could be that the patient has had two A1C measurements and they are both greater than eight. So definitely there's something happening here. The patient is not meeting it's meeting their glycemic control goal. And the third definition, which is a little bit more specific is that no medication changes within three to six months after A1C greater than eight. Now I did say that this medic, this third definition of TI is a little bit more specific, but it does have some limitations as far as the EMR, as far as the EHR is concerned, EHR is concerned. And the way I see, say that is because the EMR or the EHR or the EMR, they, they can pick up or they are, they are, they can pull discrete data. So for example if you have a patient whose A1C is not well controlled, they are on metformin and you added a new prescription of let's say a GLP-1 receptor agonist, the EMR will be able to pull that information. If you have a patient who is, for example, let's say on metformin 500 milligrams and you escalated their treatment to metformin 1000 milligrams and you send in a new prescription, most of the EHRs will be able to pull that discrete data. But if you gave patient verbal instructions, and as we all do in our clinical practices, that we ask them to ramp up their insulin or change their insulin dose from, let's say 10 to 14 units, or ask them to increase the dose of the medications verbally, then those are the type of medication changes that can be missed by the EMR. So these are sort of the three definitions of EM, of therapeutic inertia that we can utilize our EMR for. Now, next slide, I'm going to talk about the diabetes registry, right. So where do we start? How do we sort of like, you know, get a set of our, or a data set of our patients who may be experiencing therapeutic inertia. So we have to start with the diabetes registry which is basically the repository of your patients who have diabetes and you can choose to include type 1 diabetes and type 2 diabetes and you know both or either or. Now the diabetes registry is important as far as the clinical management of patients with diabetes is concerned or quality of care. Now for creation of the diabetes registries there are some inclusion and exclusion criterias that you can utilize. On the slide you can see some examples of the inclusion criterias. So for example you may include all the patients with certain ICD-10 diagnosis code sets which are pertinent to the diagnosis of diabetes. You may include patients in addition the patients who have diabetes on their problem list. You could capture claims that are coming back from encounter diagnosis. So you have a clinician who saw a patient with diabetes coded for a diabetes ICD-10 diagnosis in their visit and a claim was made for that. You could also include some visit criteria and by visit criteria what I mean is that you know is is kind of putting some sort of guardrails around the population that you want to capture. So for example you could say that you want to capture patients who have had one or two visits in the past like 12 to 18 months with a primary care provider or an endocrinologist or a nephrologist or a cardiologist within your system. So what that will help you do is that you will be able to capture the patients who are active part of your system but let's say patients who have left your system or who are now part of who are not part of your clinic anymore you can filter them out so that there is less data noise. You can also include the inclusion criteria could be patients with diabetes medications. I did put insurance enrollment in there because let's say if you want to specifically look at your senior population or your ACO population then you have the ability to create a separate registry for those patients as well. Now the inclusion criteria could be and or so you could have you could say okay I want patients who have had like two visits with a primary care physician or an endocrinologist, nephrologist, cardiologist you choose depending on on your system plus diabetes on their problem list. So you could be creative and and see what is the inclusion criteria that you want. There are some exclusion criterias that you always want to put in like you want to exclude patients who are on hospice or pregnant patients because they're the care of diabetes and pregnant patient is a very specific and different and you may want to exclude patients who are like who have certain frailty diagnosis or who have advanced dementia and so forth because you know as Dr. Ong mentioned it's not only the escalation of treatment but also de-intensification because these this is the group of patients who may be candidates for de-intensification so you might want to include them in your first you might want to exclude them or include them depending on what you're trying to do. Now the key point with the diabetes registry is that it helps you take care of your total population of diabetes and not just the patients who are coming in who have an appointment with you. So you are able to identify patients who are not who are missing appointments who are not taking the medications there are some barriers to that they're not getting the labs that you have ordered so it helps you to identify them and bring them back into the circle of care so to say. So that's the key point with the diabetes registries that you have a sort of like a like a higher level view of your total population of total population of your patients with diabetes. So now moving on to the next topic so it's the next point so now that you have your repository or your collection of patients with diabetes and you have your inclusion and exclusion criterias on how you want to define your particular population now you want to you want now more clinical information associated with these group of patients because you know the clinical information that will help you with clinical decision making and improving care of these patients. Now most of the EMRs will have information columns readily available and these can be pulled into the report and if you want any custom information then you can work with your EMR partners to to get that information but these are the set of some of the recommended data columns so to say that we that we recommend that should be part of your part of your therapeutic inertia report or your diabetes report. Last two A1C measurements and dates of A1C measurements, last two blood pressure measurement dates, last two blood pressure measurements and their dates I think there's a little typo on the slide there, whether the patient is on a statin therapy or not particularly if the patient is greater than 40 years old, what was their last GFR, what was their last microalbumin creatinine ratio, whether these patients have atherosclerotic cardiovascular disease or not because you know as the guidelines have changed we are now you know like we don't want to be just A1C focused but we also want to look at the complete cardiovascular risk reduction for a patient, are we doing enough, are we doing the guide, the standards of care that we should do for patients with atherosclerotic cardiovascular disease and to that point do we have the risk scores, the ASCVD risk scores, you could also include information like if the patients are on a GLP-1 receptor agonist, if the patients are on a SGLT2 inhibitors or not, you could also include information like date of their comprehensive and dilated eye exam and also when did they last see their primary care provider, when did they last see an endocrinologist or diabetologist, whoever you have in your system, when did they last see their certified diabetes care and education specialist because that's a big component of diabetes care as well. So these are some of the recommended clinical information data columns if you will that you want included in your report. So now that we have talked about the diabetes registry and the data columns that we need, I will go over in the next few slides and show you some examples of the reports that can be generated and what are some of the workflows that you could implement in your clinic, in your organization, in your system. So this is one example of the diabetes report. This is the EMR generated diabetes report. So you can see here there's the last A1C, there's the date of the last A1C, blood pressure, the last PP date, when did they see their last PCP, and you know when was, you know, there's a diabetes complication score which is EMR generated. So you can see that there's a bunch of information on there and remember that this is just a snapshot of the whole report. The report has many more data columns so unfortunately they won't fit into my slide. And another thing to remember is that most of these EMR reports will be dynamic. So what I mean by dynamic is that let's say if a patient had a new A1C test that they did, then the report will get automatically updated. And if they had a new blood pressure which was recorded in your system, if they saw their PCP already, then all these things will get updated automatically and you will have like, you know, the most recent information, if you will, from these reports. So based on these reports, one of the suggested workflows could be that you could sort this list by A1C because, you know, we're still kind of in the glycemic-centric approach to TI. So you could sort this list by A1C, you could filter the patients who have had no appointments, you could make sure that their lab orders are in, and you could outreach these patients with no appointments. You could do a bulk outreach. What I mean by bulk outreach is that the EMRs have the capability to send an online message in bulk to all the patients that you want. Or for certain high-risk patients, you could do telephone calls. You could call them and encourage them to come in for their appointments. And you could use this opportunity to not only make sure that these patients are seeing their PCPs, but also that they are seeing that they have had a reference for diabetes education. So in our clinic, that's what we did. When we called the patients, we said, hey, you need to come in and see your PCP, but did you have your diabetes education? Did you see the CDCES? And if not, then that was an opportunity to place a referral in. So you could bulk message them, you could bulk, you know, like you could do telephone calls based on risk stratification and taking care of the patients this way. So moving on to the next example. So this is, again, another example of the diabetes report that you can see. You can see that this shows columns of A1C control, the GFR values, the, you know, if they had blood pressure was elevated. And in addition, you can see that this report also has pulled if the patients have atherosclerotic cardiovascular disease. Now, a lot of EMRs will calculate the atherosclerotic cardiovascular disease risk score for automatically, and that can be pulled in as well. And you can see if these patients, if they are on SGLT2 or GLP1 receptor agonists or not. The green dots indicate that this patient is compliant and the red dots is where the opportunities are. So again, you know, one of the suggested workflows could be that you could sort the list by last two A1C greater than eight. And I mean, eight is not like a magic number. It could be 7.5 or seven if you want to capture those patients between A1C7 and eight who are, who may kind of like, you know, if not taken care of may fall, you know, may have, you know, worsening of their glycemic control. And then you can see who, and who are the patients among that, that have ASCVD, and they are not on the appropriate standard of care, recommended treatment of GLP1 receptor agonists or SGLT2 and outreach these patients, encourage them to come in, have discussions with their clinician on these medications. And that gives an opportunity to prescribe these medications and for better like cardiovascular risk reduction, for better glycemic control, CKD, you know, the comprehensive care for our patients with diabetes. Now, this is another example of the report. So what, again, the same information is here, A1C control, you know, blood pressure control, the PCP visit, endocrinology visit. But what I want to highlight is that you could utilize these reports, not only just from the perspective of glycemic control, but also take a holistic approach to the patient and say, okay, I'm going to see patients who are not, who have had poor glycemic control, but also look at like their cardiovascular side, see if their blood pressures are controlled or not, if they're on a statin or not. And when I do that, when the outreach is done, then you could approach the patient or discuss the patient, all the things that might be, you know, all the care gaps that might need to be closed. So we're talking about more of a, like a comprehensive, a more holistic view of diabetes care and not just the glycemic control. This is another example of the report that was generated. You can see that here there are many more, many other clinical parameters like microalbumin, CHEM7, you know, the creatinine levels. And so, so basically we want to make sure that the patients are getting the necessary labs that are needed. So we can look at these additional parameters, whether the patient has had their CHEM panel checked or not, whether they have had, you know, their GFRs checked, microalbumins checked or not, and, and that they are coming in to see their clinicians to, and their care teams to talk about, to talk about, talk about like, you know, decisions that need to be made or the care that needs to be escalated. Now, the, another key thing for when you're utilizing these reports is that, you know, we all know that diabetes care is a team-based approach. It's a team-based kind of like, you know, concept and, and, and a patient is just well, is, is well served only by a team. You know, you need your clinician, you need our, the, your, your, you know, we need our CDCES to provide the diabetes education, provide the comprehensive care to the patient. We need like, you know, they need their podiatrist, we need the ophthalmologist. So it's, it's like a team-based approach. So you want to make sure that the, that there is agreed upon guidelines or, or standards of care, which are agreed upon within that team. And everybody's following that same set of guidelines. You know, American Diabetes ADA has this wonderful set of guidelines that they publish every year. And, and we, for example, will, will follow those, or if your organization has their own sort of guidelines, which they have created, but the key is that everybody should be following the same treatment algorithm. And, and so as to streamline the team-based approach with, with your clinicians, with your RNs, with the CDCESs, with your case managers, you know, anybody who is part of the diabetes care team. Now, the last slide that I have is, is, is like that you can utilize, you saw the data that you have now for all your, for your population of patients with diabetes. Now you can use that same data to generate clinician-level reports in your organization. And the idea of generating clinician-level reports is not to be punitive, but, but the idea is to identify the best practice. Idea is to identify which team, care team is doing the best, which is, and, and see what they're doing. What is their secret sauce? And, and then spread that, spread that best practice across your clinic or across your system or across your organization. Now we have, there is variation in practice in all organizations. So the idea is to find that positive deviant and to spread that practice across, across all, like, you know, across everybody, because, you know, within a given group or within a given sort of clinic, everybody should have the same mix of patients. So, so we are looking at like variation in practice and trying to kind of identify which team is doing the best practice. So this is what I have for, from, from the, from the technical part of it, like how you can utilize your EMR, how you can create, create a diabetes registry, build reports out of it and utilize these reports in, in kind of in, in live dynamic reports within your clinics to, to create workflows that will improve therapeutic inertia and improve quality of care for your patients with diabetes. So I'm going to pass it back to Dr. Ong for the, to go a little bit more about the workflows and talk about some social determinants of health. Thank you very much, Dr. Mehta. So Dr. Mehta already explained and shared the most important part of this webinar. So I'm going to go over three, four slides just to, you know, sum up some of the workflow. So first things I want to mention is a few things like how can we utilize this report and how to analyze the stuff. So who is responsible for this report, right? So this report is not an individual level report. It is more like a population high level report. So we are looking at the whole clinic, whole healthcare system. So the one who is responsible for quality of the overall patient care, it could be manager, it could be medical director. If it is a one clinician practice, maybe that clinician might probably want to look at that report. Or maybe if you have a quality department in your system, maybe the lead person of the quality, you know, team might be responsible for this report. Who can generate the report? There are two steps. One is to build up the initial report. So it will take time, it will take effort. So just for, you know, disclosure purpose, when we create the EHR practice guide, we discuss with some EHR company and also talk with different ADA, you know, experts and stuff. So our goal is just to have an ADA TI report embedded in the, you know, common EHRs, right? So we can just say that, okay, if you want to get the report, just talk to your EHR company, get the ADA TI report. We didn't get to that point, but we got a lot of information. We got a lot of useful information, which Dr. Mehta already, you know, shared with you. And those information will be available to download that on the OTI website. There is an EHR practice guide available on the OTI website with all the information there. So what you probably need for the initial report built up is you might need administrative support. You might need a leadership from your organization to support this process to happen. And you might need an IT person from your clinic or informatics or someone who can work with the IT report and stuff. And you will need a lot of help from your EHR company. So you will just have to mention, I need a report of, maybe you can get all those reports. So maybe I wanna report that, the list of the patients with those suggested columns, that list is all the patients we are taking care who has diabetes, or maybe all those patients, people with diabetes, but A1C above whatever target, as Dr. Mehta say, you can go eight, you can go nine, you can go 10, you can go seven or 7.5, whatever A1C target you want. And you can also add another things, although there's some limitations, those who have A1C above eight and no medication changes, which EHR can capture. So you have to talk to the EHR company, you have to give all those information. You can just get it from the OTI website and give it to them. But for the subsequent report, as Dr. Mehta mentioned, it will be automatically update. So it is easy to get the subsequent report. So based on your office workflow, maybe medical assistant or nursing team or QI team or someone from your team will be able to get the report generate very easily. So another thing is how often should the report be generated? So we recommend at least quarterly, but again, it depends on your office workflow. You can do every month, every two months, at least quarterly that we recommend. But most important thing is having the report and knowing 30% of our patient population has A1C that much or they are in TI will not fix anything. You need to analyze the report and you need to have action items and implement those. So it is better to time this report generations with the opportunity to share the information with the whole group. So if you have monthly clinic meeting or quarterly clinic meeting or something, maybe you should probably want to generate this report maybe a couple of weeks before that, analyze this and then see what action items we should focus on and then share with the group and then implement that change. So there are a few example of the teamwork workflow. Dr. Mehta already go over some of stuff, so I'm not going to go deep into each one. So those things are low hanging fruits, right? So you saw that there are like a hundred patients in my clinic who has diabetes and 20 of them don't have A1C in last six months, get A1C and depending on your workflow, right? So if you have ability to send a bulk message, you can do that. If the patient does not have that ability, if your EHR version does not have that ability, you might have to ask your office assistant to call them, whatever way is fit for your clinic workflow, get A1C done. If A1C is above certain level and there is no appointment scheduled, get the appointment scheduled. If patient has a IA1C, the patient has a TI and never had a visit with CDCS, get the visit done. So those kinds of things you can do it. Another thing is, as Dr. Mehta already mentioned in his part two, so the ADA published the standard of care recommendation every year. We are, I think we will get the 2024 very soon. They usually publish at the end of the year. So there are guidelines. So if we need to intensify the treatment regimen, how are we going to do that, right? So there are some guidelines that you can follow, ADA and other organizations also have recommendations. So for example, those patients who have diabetes who are in a TI report and also had a heart failure. And according to the latest recommendation, those who have a heart failure, even if A1C is a target, we should probably use STL-2 inhibitors, even unless there's a confirmed patient, right? So just look at your patient list. The patient has a heart failure, not on the STL-2 inhibitors and maybe that is significant portion of your patient has that problem. Maybe you might probably want to look deeper into that. Why is that? What is the reason? Is it because clinician don't know the recommendation? Then just disseminate that information to clinicians. It is because of the insurance problem. Can we do something about it? Is there any prior authorization tips that we can get patient what they want, what they need? Right? Or maybe, so for example, the patient has a high TMI. Recommendation is to use dual GIP, GLP agonist or GLP agonist. The patient, those high percentage of the people are not getting that. And the reason is, the patients are afraid of that. The patient does not know how to inject. So having a demo pen, train the nursing staff to teach how to use the injection at the clinic, will it help? So a few tips that as a teamwork, what we can do. Or how about if you have a pharmacist in your health system, can pharmacist help with that? So stuff like that, I think that will be very useful, very useful, some teamwork from this report. So another thing is we can also look at the social determinants, right? So if you look at the TI report and particular insurance holder has high TI rate compared to others, what is the issue? Can we talk to the company? So again, this is the population, it's not individual. So out of 50% of the TI patients has a particular insurance, then there may be something going on. So you might probably want to look deeper, chart review, what is the problem? Is clinician trying to prescribe medication but it's not getting approved? Then what is the way? Maybe just changing the terms might probably help. Just sending the note, faxing the note to the insurance company might probably help. So those kinds of things you'll be able to help. Another example is the food insecurity, right? So majority of the people in the TI has the food insecurity, maybe having the information of the local food banks and disseminating this information to the nursing staff and have a flyer out and then give it to the patients, maybe that might probably help. So those are the things that you can use this report to help overcome the therapeutic inertia. So here there's a link, the ADA has the webpage that you can find those kinds of information. So in conclusion, so if you think that getting this report is useful, please start talking to your clinic people, get, organize the team, talk to your EHR company and try to get this report. I think it will help. We are doing the right things to help the people with diabetes and also maybe it might save money for our health system and also for national and the worldwide as well. And when we get the report, we have to analyze this. So if there is a failure to follow the standard of care, whether it is checking A1C or intensifying the treatment regimen or delay in referral to whatever specialty or CDCES or social service, then why is the problem, right? So what is the barrier? And then if we can fix it, they're trying to fix that, not all the problems we will be able to do it, but whatever we can within our ability, if we can solve, if we can overcome, and if we all work together to tackle the therapeutic inertia and we hope that we'll have a better future for all people with diabetes. So thank you very much. That's all for the presentation. Well, thank you so much, Dr. Mehta and Dr. Ong. That's a great summary. I love the presentation. For our audience, if you haven't already done so, please ask your questions for today's panelists and put them in the Q&A box. As we gather those questions and as those questions come in, I'd like to remind everybody to check out the therapeuticinertia.diabetes.org website where you can find resources and tools to use in your practice. That was such an important summary and reminder that we need to identify the patients with diabetes in our panel, and we need to proactively reach out to help them. Could you kind of walk through a typical workflow of what you might see in a clinical practice? Sure. So I'll give you a example of a workflow that we adopted in our organization. So we wanted to specifically look at cardiovascular risk reduction for our patients with diabetes and whether we have these patients on appropriate therapy or not. So we were able to gather data at the population level for our patients with diabetes who had atherosclerotic cardiovascular disease and see whether they were on GLP-1 receptor agonists or not. So that was part one, like setting the stage, knowing the kind of like the volume of patients that we need to address, what is the burden that we are looking at? Now, the second part of it was like, okay, what do we do about it? So what we did was that we had to educate all our clinicians on these newer guidelines. So we partnered with our endocrinologist across the system to provide that education to the physicians in terms of lunchtime meetings, educational meetings, and specifically addressing the use of GLP-1 and SGLT2 inhibitors for our patients with diabetes with ASCVD. The second we did was we actively outreached these patients, created some scripts for them, saying that we're talking about cardiovascular risk reduction and these are the medications that are important for you. You're a candidate for them. Please talk to your PCPs about them or your endocrinologist about them. So we had that patient level education or information. We had the clinician level education that we approached and we did it all like parallel because you want that, the buzz of information across your organization. So we did that in parallel. And then we kind of followed our data and we did see a substantial increase in the number of patients who were prescribed these medications. Obviously we did have barriers like insurance barriers, cost barriers, or patient refusing. Patients are fearful of injectable therapy and so forth, but that education to the clinicians to say, hey, see, these are the new guidelines. These are the technologies accessible. It's pretty easy to use. And then we made sure that there were resources available to our clinicians to, let's say they could refer patients to our CDCS for injection training and so forth. So kind of like a comprehensive approach, planning it that way. And we do have workflows in our clinics where if a patient comes in, if they have diabetes and if they have care gaps, then our MAs do a lot of like pending orders and so forth so that there's a reminder for the clinician, but that's one specific example of the workflow. So we have some questions coming in. So I'm going to start reflecting some questions from the audience. And one of those is, do we have good evidence that this actually works or could all of the barriers be due to other problems like insurance or inequity or overburdened clinicians, things like that? So I think I touched that point in my part as well. So we cannot solve all the problems for sure, that's a fact, but sometimes those things that we think it is out of our control, but actually it's not. For example, insurance coverage, that's true. If the insurance is not paying for it, we might not be able to do anything, but if it is, again, this is a population health report, right? So significant amount of people getting this insurance plan is not getting what the GLP-1 or SGLT-2 inhibitors, maybe it will be a good idea to talk to the insurance company and see what they want, right? So if they want metformin trials, we can do the metformin trials and then get the GLP-1 or SGLT-2, something like that. So we might not be able to fix all the problems, but we try our best, and then the things that we cannot do, we cannot fix, but we can let it be. But again, sometimes we try to underestimate our role. We just say that, okay, we prescribe the medication, insurance doesn't pay, what can we do? We stop at that point. So we should probably find out what is the barrier and then try to fix it if we can. Yeah, great advice. So one of the questions is, well, why doesn't this stuff come built in the EHR? I mean, shouldn't the EHRs be doing this? So I can answer that. So there are some out-of-box products that the EMRs, EHRs might have. Like they might have already inbuilt diabetes registry based on their criteria, their inclusion and exclusion criterias. And a lot of these data columns are already available. So it's not that you have to build them, they're already available, but you do need some help from like a EHR analytics person or somebody to kind of help you learn how to pull these data columns and make your report. But some of the EMRs may have some sort of out-of-box diabetes registry with all these data columns available as well. So we need help from you. So that's the thing. EHR also look for demand, right? So me and Shabi once said they won't build for us, right? But if 150 people, 150 healthcare system in the United States want that, they will make it available for everyone. So if you think that this is useful, please ask for that. More and more demand going into the EHR company, they will make it available to everyone. So if the EHRs, some of the EHRs, maybe they can calculate a cardiovascular risk. Is that important to have as part of this, a calculator for cardiovascular risk, or do we go to outside cardiovascular risk estimators? What's the role of the cardiovascular risk calculators? So I think you could utilize the, a lot of EMRs have the inbuilt ASCVD risk calculator, the one that is the American Heart Association risk calculator that we use as a standard. And those are the, that information can be pulled into the reports because the EMR automatically calculates the ASCVD risk score for the patient. And that can be used to calculate and that can be utilized for identifying patients who may be candidates for GLP-1 receptor agonists or like statin therapy, for example, or blood pressure control and so forth. So there is value in having them, but you could also have a column for patients with existing ASCVD, right? So there are like two grade, almost like two, it's a gradation, people who are at high risk for ASCVD and patients who already have ASCVD. Could you remind us a little bit about why GLP-1s and SGLT2s are important to follow? So we now have very convincing data. I don't want to quote all the trials that we have had for GLP-1 and SGLT2 receptor agonists that these drugs are very effective. We, very effective in preventing, preventing like a cardiovascular event, especially in patients who have had a previous ASCVD event and SGLT2 in particular are proven to be very effective in preventing progression of CKD. So these are the two sort of like, you know, atherosclerotic cardiovascular disease, a patient with diabetes, we say that they are coronary artery disease equivalent. So that's, you know, coronary artery disease equivalent so that their risk for cardiovascular event is as bad as if somebody already had an event. And obviously chronic kidney disease is one of the complication of longstanding diabetes. And the whole idea of glycemic control, as Nalin sort of said in his slides, is preventing complications because that's where the burden is, that's where the mortality is. So we have overwhelming evidence that the use of these drugs will prevent these major complications. And you have the added benefit of weight loss with some of the GLP1 receptor agonists. So I think it's important and that's what the ADA guidelines also say. The ADA guidelines have overwhelmingly pointed that out. So even patients, you know, GLP1 receptor agonists could be your first line treatment. I think we're just getting to the end of it. We could discuss this for a long time and I really appreciate a great presentation and a discussion, Dr. Ong and Dr. Mehta. Thank you again to Sanofi Diabetes and to Nova Nordisk for their support for today's program. I also want to thank all of you for joining us. Following the webinar, you'll be receiving an email with a link to complete a brief survey. And I encourage you to complete that survey and provide any feedback and any comments that you have. This concludes our program. We really look forward to connecting with you again on a future ADA session. Enjoy the rest of your day.

electronic health records

therapeutic inertia

diabetes care

American Diabetes Association

workflow strategies

at-risk individuals

EHR data analysis

workflow models

patient outcomes