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Dan Housman: Welcome to the Novel Cohorts Podcast. Today we have Ömer Saka. Ömer and I worked together back when I was at Deloitte and he’s a partner at PwC. He’s an expert in health economics and Real-World Evidence in general. One of the things I’ve always loved working with Ömer, he’s very innovative, creative, and for us here in the United States, he knows a lot more about Europe than we do in terms of how things work out there.

Ömer Saka: I need to live up to these expectations now Dan!

Dan: So thanks for coming on to speak to us today. Can you tell us a bit about your background? You know where you’re working, what’s your role?

Ömer: Sure. Thank you for the introduction and it’s always been a pleasure. Even after a few years, we both left Deloitte to still come across and have the chance to work together and we do work together. Perhaps we can talk about this a little bit during the podcast, and I studied medicine. And around the time I finished I was approaching the finishing line of medical studies was late 90s, early 2000s, the concept of blockbuster drugs were becoming a lot more of a reality. And several of the healthcare systems interestingly, starting from Australia, Canada, particularly even before the UK, they were adopting practices to actually understand the value for money for the for such expensive drugs, obviously expensive drugs back 20 years ago, meant something very different to what they mean today, as you very well know. However, they were expensive enough to justify a systematic analysis. I was at that point, the head of public health for the International Medical Organization which was a unit United Nations recognized body. And I was working with WHO with that title in Copenhagen, WHO European regional office. So, several of the people I had been working with, had the foresight to suggest a career choice for myself either clinical pathway or some other options. Around that time an organization that we will talk a little bit about the National Institute for Health and Clinical Excellence, NICE was formed and several of my friends happened to be recruited there. So together with the advice I’ve received from colleagues, but also because of the developments around me, I decided to take a career in economics of healthcare. Several different names are mentioned for this path in our technology assessment. Economic investigation model, the methods cost effectiveness analysis on so forth. So I took that path six, seven years in academia, which I would like to talk a little bit about, because that kind of brings me to our topic of today, Real World Evidence, and then two years with the government in the UK. And then 10 years at Deloitte one year at an innovative pharmaceutical company, and immune oncology area particularly and about a year in PwC.

Dan: Great, so, you know, you’re in Europe and Switzerland.

Ömer: That’s right. I’ve pretty much all my career was based in Europe. As a young medic, I had ventured into all the territories. And back about 14-15 years ago, I did have a few months residency in Boston, learning some of the methods with great colleagues who are actually also some of the founders of the concepts we use in in how we use Real World Evidence in cost effectiveness analysis on economic evaluation. But yes, most of my life, definitely all of my professional life, is spent in Europe in the bigger European countries, mainly UK, Belgium, economy wise, more affluent ones you could say I guess, and I live in Switzerland. I lived in Copenhagen for a while, did a part of my medical studies in Italy. And so but I had the also chance to work with the health care systems of Poland, of healthcare systems of Spain, the Scandinavian countries, Turkey, which is in the hinterland of Europe as well, as you know, and even around the Eastern European countries, some of the smaller ones like Croatia, Bulgaria.

Dan: So what do you think is very different from the US and Europe in terms of Real World Data.

Ömer: And I think you and I regularly debate about this, of course, when we’re not recording voices, it’s I need to, I need to think about some of these social debates you and I had, but I think there is one prominent difference that needs to be mentioned I think. Needless to say, the use of data and the use of data for commercial purposes is taken to me a lot more liberal in the US. So, the availability of data either to be inspired not necessarily always for decision making, but to be inspired about how diseases progress, how they provide outcomes, how patients actually end up in healthcare institutions. And perhaps because of the commercial or more heavily commercial nature of the American healthcare system such alleys of exploration are lot more available in the US. Now, of course, on top of this, like everybody knows there’s the regulatory hurdles that were established a couple years ago, particularly for Europe, with the deregulation that has led to several lines of debates on whether or not in Europeans are deploying Real World Evidence sufficiently or whether we’re creating too many regulatory hurdles. I don’t agree with those, but we’re not going to discuss that. I think one of the major differences, on the other hand is that Europe essentially takes a lot more of an organized approach, methodological approach, in building consensus, in understanding or averting risks around the use of Real World Evidence prior to actually setting off and deploying the data so liberally. Now, having said that, if you allow me, I will just go back very briefly to about six years I spent in academia with my colleagues, some of the top professors in the area for health economics and in several vascular medicine. I was the health economist in charge of the economic investigation of cerebral vascular diseases using South London Stroke Register and European Registers of Stroke EROS, as we know, the we did not call this Real World Evidence back then this is taking us back 14,15,16 odd years I mean, we refer to this as data. And the reason why I’m giving this example is this data set has been and still is hugely used. Some of the new therapies around oral anticoagulants the use of rtPA were actually assessed using this very valuable population-based patient registry, better restricted population. I mean, a very well-defined population area, very well-defined population coverage, you could even run prevalence and incidence studies on that database. So even though Europe has been perhaps if you evaluate from a health technology assessment perspective, a lot more prescriptive, which, according to some has restricted the amount of investigation we could do with Real World Evidence. Of course, the practice of using Real World Evidence in our decision making is not new. This particular example the use of South London Registry actually led to the whole assessment of provision of several vascular disease services all across England, back in 2005, which led to a huge amount of policy changes one of the most influential secretaries of health Lord Darzi was at the helm of this whole movement. And in a revision of evaluation of cerebral vascular disease services across the UK in 2010, again, Real World Evidence led the way to understand and devise, the successes of that policy, and to further the impact of the national cerebral vascular policy, national stroke policy on patients’ lives. So there are several examples like these in Europe. But I think when it comes to HTA, which we may talk about a little bit more. I think we got a bit more prescriptive in Europe.

Dan: So in Europe, I think Germany is the biggest market, is that right? What’s happening nowadays in Germany.

Ömer: So, I mean, I think none of the HTA agencies could really stand against the wave of the conventional Real World Evidence in our, you know, in our assessment of new technologies in our assessment or patient pathways, you know, we are either rules bound or not we are using Real World Evidence to understand the effectiveness of interventions to understand the epidemiology of diseases you know, naturally, prevalence and incidence we use this data in economic models. We use this data to try to understand the natural history of diseases, comorbidities, and we use real-evidence to define the differences in current practices now, So German healthcare system as you know, and I’m sure your audiences are to a certain extent are acquainted with this information as well. When healthcare financing system because of its historical makeup because of its historical structure, the Bismarckian, you know, The Iron Chancellor of Germany from the 19th century and is has always given more weight on the effectiveness on the efficacy of treatments and effective treatments obviously, you would be able to determine mainly by referring to clinical trials, etc. now, and but even the German healthcare system cannot resist the change, the deployment of data, the accumulation of data is a fast reaching Europe itself has been investing alongside the pharma industry in a common program called Innovative Medicines Initiative, the IMI program into translational medicine and the use of and more effective use of Real World Evidence, about $2 billion in each and every year. So it’s a hugely wide reaching program. So, Germany is reassessing its very tactical and risk averse, evaluation Real World Evidence. We are involved, I must admit and rather proudly, one of my colleagues, you have met also Dan, and a team all around him, we have been working with the largest neurologists data set, largest neurologists network, actually, which has a unified data set in Germany. And we are now in discussions with ECRIC on what would be the methodological. First of all, what are the methodological upsides and downsides of such a wide ranging and neurology database, which is initiated by a huge network of neurologists in Germany, and what would be the benefits of utilizing this data not just only for the assessment of new treatments, or perhaps the decisions on reimbursements of  these new treatments, but also retrospectively evaluate the benefit of some of the older treatments or some of the older pathways. I think there is a legal background to this change as well. Therefore, the utilization, we I think we will see a lot more of an open line of negotiation. We are in these conversations with my colleagues, not me personally, unfortunately, my German is a little bit rusty from many, many years ago. But, but if we are involved, of course, several of my contemporary health economist colleagues, they’re all involved in building such databases and deploying them for the benefit of patients.

Dan: Awesome. You’re like my go to health economist. So how do we define the value of products? And by understanding therapy areas, utilization patterns, drug compliance, how does that really work?

Ömer: So, traditionally speaking and I think this is going to build a very nice segue to Real World Evidence. So, when I say traditional, of course, you need to understand the institutional formation of the use of health economics or how technology assessment as we refer to nowadays is not that old. Of course theories of it is in you know, utilitarian economics is with Kenneth Arrow of Chicago School so there’s a whole equity related and the distribution of healthcare resources related research has been going on for decades naturally. But the deployment of this research the product of this research formerly being deployed in decision making is relatively new many say 25 years max, but really, it has been taking over decision processes very effectively for definitely the past 10 years. So now, what did we institutionally and organizationally do? We tried initially to understand, obviously, the ways to distribute our resources more effectively. There’s a certain budget allocates to healthcare everybody claims, and that budget needs to be allocated effectively across different diseases. Therefore, we attempted to develop a utility metrics that could equalize the measurement of outcomes across different therapy areas. We call these metrics with several different names, quality of life metrics, and I guess the most recognizable nomenclature, quality adjusted life years, of course, as a particular metric, is been the topic of debate for many, many years with its negatives and positives. Now, when it comes so the easy answer to your question is, we measure as in health economics, the value of treatment or the value of a therapy or the value of a clinical pathway, and any new venture basic it doesn’t have to be a drug or a medical device, it can be a new way of providing surgery is measured by comparing the quality comparing the improvement of quality of life that it generates in the patient is supplied to versus the patients who actually receive standard of care or all the way of managing these patients now, quality adjusted life years have been without sounding too politically incorrect have been insufficient in the face of huge developments, I will say particularly in the area of oncology, because the improvement of quality of life isn’t the only thing that we provide to patients. The improvement in their lifetime is not the only thing that we provide to patients, you know, safety metrics, improvement of data, overall activities of daily living, but a lot of proxy metrics or metrics we also need to understand how successful the very new therapies in oncology and some of the similar areas have been to therefore, on economics discipline is not it has been evolving in exploration of other metrics to define that value recently and the use of Real World Evidence have been particularly important in facilitating that development and one very prominent example of course is in the area of okay, perhaps we developed such standardized metrics like quality adjusted life years, but quality life years do not necessarily allow us to compare diseases with one another patient with you perhaps, but just suffice it to say that they don’t do it. And also quality adjusted life in their measurements have several simplifications and they do not necessarily bring forth the manifestation of  the outcomes in diseases to a sufficient degree in particularly diseases that are seen to be more quality of life or lifestyle diseases like atopic dermatitis, narcolepsy, where the payers do not understand the severe trouble the patients go through on the benefit of the treatments for these diseases for them. So what we do is we develop metrics and measures to understand patient’s complaints and we call this set of metrics as patient reported outcomes. Now, the deployment of Real World Evidence has been significant in this area, either retrospectively or prospectively, could we define cohorts of patients, which could we then extract their complaints accurately in a standardized form so that we can understand actually what’s the impact of a certain disease, on their, on the on the progression or continuation of their lives on their on their wellness all together. Now from this, from these type of metrics, we of course expand to a much wider use of Real World Evidence, particularly again, in measuring the resource consumption of patients when they’re actually receiving new therapies in a hospital setting or a clinical setting or even at their own home. Because clinical trials, of course, are restrictive, they, they’re very prescriptive in how they measure and how they even allocate resources to patients. There are very stringent rules on how a patient should see a physician how many times their test should be done versus, etc. When it’s made that there was evidence on the economy side, where we would be able to understand the value of either the increase in expenditure over on a patient who’s receiving a new therapy or perhaps the savings that could be achieved as the condition of the patient improves, as the patient manages to go back to work more regularly, as the patient achieves the activities of daily living with more success. So, you know, these kinds of and the pressure on the healthcare system, not just the German healthcare system, but the UK healthcare system too, is recognizing the fact that first of all, clinical trials do not provide sufficient data from that perspective. Secondly, it’s unavoidable that we’re going to need to follow these patient’s progression in order to ascertain the value that we had measured with efficacy. And it’s not a question of whether Real World Evidence should be deployed or could be deployed. It’s more like how should it be deployed, so that we ensure that the inherent biases that could exist in such data sets would be overcome.

Dan: So you know, most historical Real World Data has gone against claims data or administrative data sets of some sort. A lot of what you’re describing sounds like quality of life and patient reported type data. Can you talk about advanced data, the things that people are just now starting to get a hold off, to do this? What do they need? What kind of data and how is it working? or How could it work?

Ömer: Very good. Very good point. Now, I have to say, if you’re talking about a European context, first of all, maybe let’s start from the beginning. In my previous answer, I attempted to give you an idea on the fundamental use of Real World Evidence to enhance the value of innovative treatments. Now, of course, a huge amount of investment made on innovative medicines initiative. The IMI program doesn’t just, you know, stay within this realm of investments. So they expand to beyond regional database, beyond primary care, beyond hospital based databases. They try to design disease specific cohorts, particularly for rare diseases and less regularly encountered problems. Population cohorts are the buyer banks are obviously more regularly used disease registries. They were solitary examples. Now they’re more integrated into the, into this broad range of data sources. However, beyond that, recently, I had the chance to complete a project which will be published very soon and I will be happy to actually if you think it would be helpful, I’d be happy to spend about 10 to 15 minutes discussing the outcomes of that study with you. We looked at the deployment of Artificial Intelligence on detecting sources of effectiveness, particularly when very rare diseases and the treatments for very rare diseases are going to be needed, European Investment in that area has been, from what we can determine, has been significantly less than the investment made in this bank in such ventures in the US and even in other countries like China, for example. Therefore, the networks and the data custodians are getting together particularly academically and particularly with European Union funding to develop use test and, you know, facilitate the sharing of such practices. And the reason why I can’t get into more details because the report is about to be published and I would love to spend more time with you on this particular aspects. Of course, you and I, you know, beyond the artificial intelligence, you and I talk about, you know, voice recognition technologies to deploy in patients with cognitive impairments. You and I, again talk about in sleep impaired patients the use of wearable technologies on determining the difference between you know, the sleep impairment that causes issues and sleeping moment that is more lifestyle bound. The however, could I tell you that there is a systematic and brave use of such more futuristic technologies in reimbursement or in determining the value of new drugs in Europe. I think this is still a bit of a development case. Again, you and I, if you recall two years ago, we worked on a very rare disease and gastrointestinal disease, periodontal fistulas. And in the deployment of that disease we anticipated the setting up of quite significant home-based patient follow up procedures so that periodontal treatment was not to be effective, immediate blips and notices could be raised so that the discomfort of the patient could be immediately recorded. But as you also know, when it came to payer conversations, some of these were a little bit beyond the schedule of implementation yet, but the frequency of these conversations are increasing, which is hopeful from our perspective.

Dan: Great, you know, you’re talking about rare diseases and genetic disorders. I think a lot of therapies are starting to target these because of gene therapy. What are you seeing as changing in terms of these rare diseases? What kinds of capabilities are being put together to support them?

Ömer: I think methodologically. one of the projects that was also funded by IMI has been very interesting in that particular area. The, you know, we are recognizing more and more that the old fashioned ways of recruiting patients for studies is not only reducing the speed with which we can carry out the studies, but it’s also actually extending the length of the studies beyond the period that should be required. So what’s happening in this field? Certainly, again, this whole movement started more in the US but we see a lot more of adherence of Early Access Programs in Europe meaning the regulator’s the HTA agencies realized that because of the speed of research in rare disease slow when a new drug actually would be available, the use of this drug should be facilitated by a regulated means to patients which may not have been captured for clinical trials. So the rise of early access programs is certainly one of the most interesting developments in the reimbursement space and something that is definitely, especially now that we’re on the brink of very expensive cell and gene therapies is going to be one of the door openers. Now, beyond that, I have been partnering with a company called MyTomorrows, a very very innovative company, you may have also come across with them funded by venture capital. Now, these folks in Holland, they have developed super interesting decision pathways to define patients with rare diseases from the way that they will be seeking information on the internet, because some of the times the patients suffering from rare disorders, they don’t even come across with the right physicians for their problems to be diagnosed accurately. So they don’t go to the specialized agencies. But now, with the deployment of technology within the realm of GDPR, obviously, we can recognize these patients, we can provide them options to join clinical trials, or if that doesn’t work, we could rapidly enroll them in some of these early access programs, and of course, the within the Early Access Programs. From a Real World Evidence perspective, one of the things that prospectively is hugely beneficial is by deploying these early access programs, we also start to venture into Real World Evidence much earlier, we don’t need to wait for long and long lasting, you know, arduous and complicated negotiation processes on what the price level should be, what should be the net price, what should be the list price, what would be the impact of listing price in England for reference pricing in other countries, so on so forth. So, the fact that we can recognize the rise of therapies, the speed with which these therapies are actually going through clinical trials and the need to deploy these therapies rapidly with patients is also helping the collection of Real World Evidence and also eventually of course, it’s helping us to separate wheat from chaff. As you could say, of course, if some of these therapies do not work, we should as payers should be able to put an end to it and the clinicians are, you know, should that be in be in a position to almost in a real life manner to be able to choose alternatives for the patients which provides, which provide better efficacy and effectiveness. So, from the rare diseases, I think and you know, again, that we are leaving so many details out in this conversation, we’re not talking about personalized care, we’re not talking about the practice of value based care which again, you and I have spent quite a bit of our professional time investigating. But if we’re going to just talk about the main skeleton of rare disease, I think that’s the situation.

Dan: Thanks. That’s pretty interesting. Now, one of the things we’ve talked about is that we’re on a podcast now everybody’s home. Telehealth seems to be booming all the sudden because there’s not a lot of alternatives for people who can’t get in to see a physician that must be changing how Real World Evidence and how pharmaceutical companies are looking at clinical trials. What are your thoughts on all that?

Ömer: I think this is mind-blowing area, in my opinion. And sadly, I must add, apart from the very acute interventions that were developed in Europe, we have we are yet to see mainstream accepted deployment of telemedicine. And of course, the reason why this topic came about very acutely is we all know all of your listeners are well aware is the is the COVID-19 shock that we have received in our lives in the past six months. With this shock, you know, we talked about the first wave, we tried to suppress that first wave of patients suffering from COVID-19 from hitting the hospitals all at once, therefore, depriving the limited resources that these hospitals have to utilize on these patients. So we managed it to a certain extent in Europe for sure there are success stories and less successful cases. But nevertheless, we didn’t manage that first wave. However, the occupancy rate in some of the hospitals dropped down to 15-20% levels now, no hospital with 15-20% occupancy could survive. But of course, if we are reducing the occupancy rate of hospitals to those levels, two questions emerge number one, that means, we are pushing out several elective cases, we are postponing them, which, you know, we had research he is yet to emerge Oxford University, the group in Oxford University is doing investigation into this area to understand that secondary impact of these elective procedures patients who needed urgent cardiovascular surgery, for example, what has the impact of them we do not know and of course, more, perhaps more long-term level patients who suffer from chronic diseases who may experience side effects, or he may experience a relapse of their symptoms. They have also been deprived of a regular contact with their physicians. Now telehealth is the one replacement that would change this picture. Regulation has been passed in the US also, there’s many examples in Europe. I know for a fact in Belgium, I worked with some of the physicians there is, of course tailored consultations, even the you know, the use of mobile phones to determine dermatological symptoms and their severity has even been deployed. Formally, to a certain extent informally to another extent. However, this is going to be anecdotal, I must say, because obviously as a part of my job, I’m in contact with both the pharmaceutical industry and the care providers. The implementation of durable solutions is yet to be discussed. I don’t think the industry has fully grasp, grasp the potential that telemedicine provides to them. I have been talking to colleagues and chronic care and they have already been complaining of the reduction and prescription refill prescriptions, you know, patients not necessarily coming to elderly patients particularly trying to minimize their contact with the outside world not getting their prescriptions filled, lowering their dosages to enable the drugs that to last longer. So the extreme amount of investigation that’s needed here, if telemedicine if we can take that opportunity, of course, telemedicine directly would impact on our understanding on how we manage patients telemedicine allows us to collect data more quickly more readily, especially if you can connect the telemedicine systems to our more conventional data collection methods if you can manage it, again in the continuum of value based care, this is something we’ve been anticipating for many years because communication methods allows us now to do this. But I personally as a professional serving in the area of market access health economics, I am yet to see emerging models that will be considered in an economic analysis that will descend from the use of telemedicine and one maybe interesting example, I can share with you an oncology intervention I’m working on recently, they wanted to underline the value they generate, because this particular drug doesn’t need to be administered as regularly as the competitive drug and naturally if the patients do not have to attend do not have to come to the clinic very often. And if there’s regular problems could be managed by telehealth that could reduce the risk of getting in touch with potential patients that’s all from COVID-19. Therefore, that reduces the risk of infection. And we’re now investigating whether or not we could actually make this a part of the overall economic investigation of the therapy. So there are very clear uses tangible cases are yet to emerge. But there’s definitely thinking on how telemedicine and telehealth and the enablement it will create will make its way to value assessment of new therapies.

Dan: And I think my hope in all the telehealth is that it’s, there is always this lowest less rich data you get and you start with claims data, then you maybe go up to HR data where someone’s actually entering what clinically was evaluated by the physician. Then you get to physician notes where that’s the physician wrote down and great narrative form off the cut and paste. But if we start getting to real telemedicine, and there’s a way to extract the full richness of the encounter with video with audio, with the full text of what the patient actually said, and the clinician actually said to them, you know, might not first be specifically useful in health economics. But I have to imagine it’ll answer a lot of the questions we often hear about, well, I just don’t know where the real impact is on quality of life. We don’t have that data. It’s not stored in any record. So I think I’m hopeful that the ethics gets worked out, so that that rich information can be used in a way that’s productive to help patients and productive to help build better products. But who knows, I think it’s going to be complicated because, you know, tapping into people’s conversations may be really hard.

Ömer: I, you know, in defense of the payers landscape, I would like to say one thing here. And in my several conversations with colleagues in the industry, what I tried to underline was, you know, telemedicine is not a technology. It’s not just a computer, it’s not just being able to talk to your physician telemedicine is, you know, transferring data between physicians transferring data between institutions, telemedicine is being able to readily evaluate blood test results, it’s being able to understand the complaints of our patients readily. So basically, telemedicine is anything that speeds up the interaction between the patient and the care provider. Now, I have to say for my colleagues in the industry, and the weight is a little bit on their shoulders to first of all, I mean, they have obviously huge amounts of information. On the therapy areas that they work with, they do understand patient pathways. They do understand the shortcomings on the patient pathway sometimes with because of the efficacy effectiveness, but mostly because the healthcare systems are not geared up to deliver the best results for each patient, each patient’s problem. Therefore, I think the burden is a little bit with the industry to define the clusters of how technology that could be deployed on the payer-patient pathway, the potential ethical problems that can emerge, databases, but beyond databases, some obviously, informal practices that could also formulate around these practices the risky behavior that could be instigated and present pilot based suggestions to the payers, I think payers are willing to evaluate these options, but I believe that they are not receiving sufficient number of tangible suggestions that I’ve made that have been that are being presented to them. I think the industry is a bit more of a homework to do here.

Dan: Yeah, well, things may have gotten a bit kicked forward, but it’s still takes a while. You know, we know the direction, I think it’s headed.

Ömer: Direction it’s headed, yes.

Dan: So, you know, thanks a lot for taking the time with us. Now, maybe the last question, maybe end with you is sort of what are your thoughts on the big picture? You know, like, where do you think advanced Real World Data, advanced real world evidence will have a big impact in the future? Why are you in this game trying to make this work?

Ömer: I mean, frankly, speaking, I think we still I think the main problem is value based care. I think the main problem is it’s not the value of a pill. I talk quality adjusted life here. It’s not the value of infusion for cancer patient, but it’s the value of that we built within the healthcare system to, you know, lessen the pain of patients. I think, for me the biggest picture is and also maybe the most difficult aspect of change is in the more established medical practices. I think the answer is ventures like ITrom initiated by monitors Michael Porter, as you know, trying to determine metrics of value, not just related to a drug not just lead to treatment modality but related to the healthcare system, being able to understand readily and rapidly what are the main reasons why patients fall out of the healthcare system or they are not complying with their treatments or they are not getting the, the effectiveness, nowhere near as close to the efficacy results that the trials publish. The value based care can only be actualized. That’s the big game for me. If we, you know, stop talking about innovation in the sense that a new drug could generate for the patient but start talking about what are the gaps in care provision across the framework. And I think when the necessary the set of contractual agreements are made, that the stakeholders take responsibility in all of the continuum of care, I think that’s the biggest problem. You and I, I think our friendship depends on to a certain extent, our intellectual endeavors, but also this particular passion that I know you also share, on converting healthcare systems into one entity rather than hospitals or clinics here. Patients who have physicians or drugs here have a grantor I mean, we could talk for hours about this. There’s book chapters I’ve written about this, which I’d be more than happy to share with, with any of your audiences who would be interested But I think the focus should be on the methodological aspects of value based care and how new bits actually improve on our understanding of value based care.

Dan: Great, I think that’s a good place to leave it off. You know, it all boils down to truly delivering full value. So, thanks so much.

Ömer: Thank you for creating the audience and creating the platform for such conversations. I I’m looking forward to many years of conversations. Of course, if your audiences at hasquestions, do pass them on, I’d be happy.

Dan: Yeah, and I’m sure we’ll be working long past these gray hairs that are growing years from now.

Ömer: Thanks very much. Cheers.

Dan: Cheers. See you soon. Bye.