Apple Podcast
Spotify Podcast

Transcript

Dan Housman: Welcome to the Novel Cohorts Podcast. Today we have Ömer Saka with us. Ömer and I worked together back when I was at Deloitte. He is a partner at PwC and an expert in health economics and real-world evidence in general. One of the things I’ve always loved working with Ömer is that he’s very innovative and creative. For us people 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 Housman: So, thanks for coming on to speak with us today. Can you tell us a bit about your background, work experience and present role?

Ömer Saka: Sure. Thank you for the introduction and it’s always a pleasure. Even after a few years we both left Deloitte, we 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. I studied medicine and around the time, I was approaching the finishing line of medical studies back in the late 90s & early 2000s, the concept of blockbuster drugs were becoming a reality. Several healthcare systems interestingly, starting from Australia, Canada in particular, even before the UK, were adopting practices to understand the value for money for such expensive drugs. Obviously, expensive drugs back 20 years ago, meant something very different to what they mean today. However, they were expensive enough to justify a systematic analysis. I was at that point, the Head of Public Health for the International Medical Research Organization which was a United Nations recognized body. I was working with WHO with that title in Copenhagen WHO European Regional Office. So, several of the people I’ve been working with had the foresight to suggest 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 happen to be recruited there. So together with the advice I had received from colleagues and the developments around me, I decided to take a career in the Economics of Healthcare. Several different names are mentioned for this path in health technology assessment, economic investigation, model & methods of cost-effectiveness analysis and so on & so forth. So I took that path with 6-7 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. I spent two years with government in the UK, then ten years at Deloitte, one year at an innovative pharmaceutical company in immuno oncology, and about a year in PwC.

Dan Housman: Great! So, you’re in Europe and Switzerland.

Ömer Saka: That’s right. Pretty much all my career was based in Europe. As a young medic, I had ventured into all the territories. Fourteen – fifteen years ago, I did have a few months residency in Boston, learning some of the methods with great colleagues. Some of them were actually founders of the concepts like use of real-world evidence in cost effectiveness analysis and economic evaluation. But yes, all my professional life was spent in Europe. Mostly, in the bigger European countries, mainly UK and Belgium, economy wise more affluent ones you could say. I lived in Switzerland and Copenhagen for a while and did a part of my medical studies in Italy. I also had a chance to work with the healthcare systems of Poland, Spain, the Scandinavian countries and Turkey, and even around the Eastern European countries like Croatia and Bulgaria.

Dan Housman: What’s the difference between US and Europe in terms of real-world data?

Ömer Saka: I think you and I regularly debate about this when we’re not recording voices. 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. Needless to say, the use of data for commercial purposes is taken to be a lot more liberal in the US. The availability of data either to be inspired not necessarily always for decision making but to be inspired to understand disease progression, patient outcomes & reasons for their hospitalizations. Perhaps because of the 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, the regulatory hurdles that were established a couple of years ago particularly for Europe. The GDPR regulation that has led to several lines of debates on whether or not Europeans were sufficiently deploying real-world evidence or whether they were creating too many regulatory hurdles. I don’t agree with those, but we are not going to discuss that. I think one of the major differences is that Europe takes a lot more of an organized & methodological approach. Europe takes an organized approach in building consensus, understanding or averting risks around the use of real-world evidence prior to 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 including some of the top professors in the area for health economics and vascular medicines. I was the Health Economist in charge of the economic investigation of cerebral vascular diseases using South London Stroke Register and the European Registers of Stroke (EROS). We did not call this real-world evidence back then, we refer to this as data. The reason I’m giving this example is, this dataset has been and still is hugely used in some of the new therapies around oral anticoagulants. The use of rtPA were assessed using this valuable population-based patient registry on the restricted population. The database has very well-defined population coverage, you could even run prevalence and incidence studies on that database. Europe, from a health technology perspective, is a lot more prescriptive which has restricted the amount of investigation it could do with real-world evidence. Of course, the practice of using real-world evidence in our decision making is not new. This example of the use of the South London registry led to the whole assessment of the provision of several vascular disease services across England back in 2005. This 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. Real world evidence led the way in a revision of evaluation of cerebral vascular disease services across UK in 2010. Real world evidence helped in understanding and devising the success of that policy. It further impacted the National Cerebral Vascular Policy and the 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 Housman: In Europe, I think Germany is the biggest market? What’s happening nowadays in Germany?

Ömer Saka: I think none of the HTA agencies could stand against the wave of conventional real-world evidence. In our assessment of new technologies or patient pathways, we are either rule-bound or not. We are using real-world evidence to understand the effectiveness of interventions, epidemiology of diseases, prevalence, incidence, natural history of disease and comorbidities. We are using this data in economic models and in defining the differences in current practices. So, in the German healthcare system, I’m sure your audiences are to a certain extent acquainted with this information as well. In the healthcare financing system because of its historical makeup, Bismarck, giant chancellor of Germany from the 19th century has always given more weight on the efficacy of treatments. An effective treatment determined mainly by referring to clinical trials, but even the German healthcare system cannot resist the change. The deployment and accumulation of the data is fast reaching. Europe, itself has been investing alongside with the pharma industry in a common program called Innovative Medicines Initiative (IMI). IMI program has been investing about $2 billion every year in translational medicine and more effective use of real-world evidence. It’s a huge wide-reaching program. Germany is reassessing its very tactical and risk-averse evaluation of the real-world evidence. I’ve been jointly working my colleague & his team with the largest neurologist’s data network, which has a unified data set in Germany. We are now in discussions with ECRIC on methodological upsides and downsides of such a wide-ranging neurology database. We are discussing the benefits of utilizing this data for assessment of new treatments and reimbursements decisions as well as old treatments & pathways. I think there is a legal background to this change as well. Therefore, we think will see a lot more of an open line of negotiation. We are in these conversations with my several of my contemporary health economist colleagues. They’re all involved in building such databases and deploying them for the benefit of patients.

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

Ömer Saka: Traditionally speaking, I think this is going to build a very nice segway to real-world evidence.  So when I say traditional, one needs to understand that the institutional formation of use of health economics or technology assessment is not that old. Of course, theories of it is, utilitarian economics with Kenneth Arrow of Chicago School. So, there’s whole equity & the distribution of healthcare resources related research has been going on for decades naturally. But the deployment and the product of this research formerly being deployed in decision making is relatively new, many say 25 years maximum. But really it has been taking over decision process very effectively from the past 10 years. So now, what institutionally and organizationally did we do? We initially tried to understand the ways to distribute our resources more effectively. There is a certain budget allocated to healthcare that everybody claims which 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. I guess the most recognizable nomenclature, quality-adjusted life years as a particular metric has been the topic of debate for many years with its negatives and positives. So, the easy answer to your question is we measure as in health economics the value of a treatment, therapy or of a clinical pathway. Any new venture, it doesn’t have to be a drug or a medical device, it could be a new way of providing surgery. It is measured by comparing the improvement of quality of life that it generates in patients it supplied to versus the patients who actually received the standard of care. Quality-adjusted life years have been insufficient in the face of huge developments. I will say particularly in oncology because the improvement of quality of life isn’t the only thing that we provide to patients. We provide safety metrics, improvement of data, and improvement in the overall activities of daily living. We also need to understand the success of new therapies in oncology and some of the similar areas. Therefore, health economics discipline is been evolving in an exploration of other metrics to define that value recently. The use of real-world evidence has been particularly important in facilitating that development. And one very prominent example in this area is development of standardized metrics like quality-adjusted life years (QALD). The quality-adjusted life years do not necessarily allow us to compare diseases with one another. Also, quality-adjusted life is the measurement that have several simplifications and they do not necessarily bring forth the manifestation of the outcomes in diseases to a sufficient degree. Particularly in diseases that are seen to be more quality of life or lifestyle diseases like atopic dermatitis, narcolepsy. In these types of diseases, payers do not understand the severe trouble the patients go through and the benefit of the treatments. So, 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 and extract their complaints accurately in a standardized form. This will allow us to understand the impact of a certain disease, their progression or continuation, and the overall wellness of patients. Now, from these types of metrics, we expand the use of real-world evidence. It could be used in measuring the resource consumption of patients receiving new therapies in a hospital or clinical setting or even at their own home. Because clinical trials are restrictive, they’re very prescriptive in how they measure and 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, etc.  On the economy side, real world evidence would able to understand the value of increased expenditure on a patient who is receiving a new therapy. It would also help in evaluating potential savings as a result of patient’s improved condition. So, the pressure is on both German & UK healthcare system in recognizing the fact that, first of all, clinical trials do not provide sufficient data from that perspective.  Secondly, it’s unavoidable that we need to follow patient’s progression to ascertain the value that we had measured with efficacy. It’s not a question of whether real-world evidence should be deployed or could be deployed. It’s more like how it should it be deployed so that we ensure that the inherent biases that could exist in such data sets would be overcome.

Dan Housman: So, 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 more about advanced data, the things that people are just now starting to get a hold off? What do they need? What kind of data and how is it working?

Ömer Saka: Very good point. Now, I have to say that 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 of 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 and IMI program stay within this realm of investments. So, they expand beyond regional databases, primary care, and hospital-based databases. They try to design disease-specific cohorts particularly for rare diseases and less regularly encountered problems. Bio banks are more regularly used. Disease registries, were more solitary examples, now they’re more integrated 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. I will 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 the treatments for very rare diseases are going to be needed. European investment in that area is significantly less than the investment made such ventures in the US and China. Therefore, the networks and the data custodians are getting together with European Union funding to develop use test and facilitate sharing of such practices. 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 these aspects. You and I talk beyond artificial intelligence, and voice recognition technologies to deploy in patients with cognitive impairments. You and I again talk about the use of wearable technologies in sleep impaired patients to determine the difference between the sleep impairment that causes issues and sleeping moment that is more lifestyle bound. There is a systematic and brave use of such 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, if you recall two years ago, we worked on a very rare disease, gastrointestinal disease, which is perianal fistulas. In deployment of that disease, we anticipated setting up of quite significant home-based patient follow up procedures. This was done to make sure that if the perianal fistulas treatment was not effective, immediate blips and notices could be raised and the discomfort of the patient could be immediately recorded. But as you also know, when it came to paying your conversations, some of these were a little bit beyond the schedule of implementation yet. The frequency of these conversations is increasing which is hopeful from our perspective.

Dan Housman: 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 do you think is changing in terms of these rare diseases? What kinds of capabilities are being put together to support them?

Ömer Saka: I think methodologically one of the projects that were also funded by IMI has been very interesting in that particular area. We are recognizing more and more of that the old fashioned ways of recruiting patients for studies. It 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, this whole movement started more in the US, but we see a lot more of adherence of Early Access Programs in Europe.  Regulators and HTA agencies realized that because of the speed of research in rare disease is 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 going to be one of the door openers, especially now that we’re on the brink of very expensive cell and gene therapies. Now, beyond that, I have been partnering with a company called Mitel, a very innovative company, funded by venture capital. These folks in Holland 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, don’t even come across with the right physicians for their problems to be diagnosed accurately. So, they don’t go to specialized agencies and now with the deployment of technology and within the realm of GPS and GPR, we can recognize these patients and provide them options to join clinical trials. We could rapidly enroll them in some of these early access programs. 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 more earlier. We don’t need to wait for long-lasting 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 or reference pricing in other countries? So on & so forth. The fact that payers recognized the rise of therapists, the speed with which these therapies are 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 helping us to separate the wheat from the chaff. As you could say if some of these therapies do not work, we should as payers can put an end to it and the clinicians should be in a position to be able to choose alternatives for the patients which provides better efficacy and effectiveness. From the rare diseases, I think 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 the rare disease, I think that’s the situation.

Dan Housman: Thanks. So that’s 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 are unable to get out to see a physician. That must be changing how real-world evidence and pharmaceutical companies are looking at clinical trials? What are your thoughts on all of that?

Ömer Saka: I think this is a mind-blowing area in my opinion. And sadly, I must add apart from the very acute interventions that were developed in Europe we are yet to see the mainstream accepted deployment of telemedicine. The reason why this topic came about very acutely is we all know and all your listeners are well-aware of the COVID-19 shock that we have received in our lives in the past six months. With this shock, we talked about the first wave, we tried to suppress the 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. But nevertheless, we didn’t manage that first wave. However, the occupancy rate in some of the hospitals dropped down to 15-20% levels and no hospital at 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, on which research is yet to emerge. The group in Oxford University is doing investigation into this area to understand that secondary impact of these elective procedures on patients who needed urgent cardiovascular surgery. Perhaps more long-term level patients who suffer from chronic diseases who may experience side effects or relapse of their symptoms, were also been deprived of regular contact with their physicians. Telehealth is the one replacement that would change this picture. Regulation has been passed in the US. Also, there are many examples in Europe. I know for a fact in Belgium, I worked with some of the physicians, there are tailored consultations. 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 & the care providers and the implementation of durable solutions is yet to be discussed. I don’t think the industry has fully grasped the potential that telemedicine provides to them. I have been talking to colleagues in chronic care, they have already been complaining of the reduction in prescription refill. Patients are trying to minimize their contact with the outside world. They are not getting their prescriptions filled. Patients are lowering their dosages to enable the drugs to last longer. So, the extreme amount of investigation is needed here. Telemedicine directly would impact on our understanding on how we manage patients and allows us to collect data more quickly and readily. Especially, if we can connect the telemedicine systems to more conventional data collection methods. Again in the continuum of value-based care, this is something we’ve been anticipating for many years because communication methods allow us now to do this. But, I personally as a professional serving in the area of market access and health economics. I am yet to see emerging models that will be considered in economic analysis that will descend from the use of telemedicine. Maybe one interesting example, I can share with you on an oncology intervention, I’m working on recently. They wanted to underline the value they generate because of a drug that doesn’t need to be administered as regularly as the competitive drug. Naturally, if the patients do not have to come to the clinic very often and if their regular problems could be managed by telehealth, it could reduce the risk of getting in touch with potential COVID-19 patients. Therefore, that reduces the risk of infection. And we’re now investigating whether we could make this a part of the overall economic investigation of the therapy. So, there are very clear tangible cases that are yet to emerge. But there’s thinking on how telemedicine and telehealth enablement will make its way to value assessment of new therapies.

Dan Housman: I think my hope in all the telehealth is that, there is always this lowest, less rich data you get, starting with claims data, and then you maybe go up to EHR data where someone’s entering what clinically was valued by the physician. Then you get to physician notes where the physician wrote down a 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 & audio, and full text of what the patient said and then clinician said to them, might not first be specifically useful in health economics. But I must imagine it will 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’m hopeful that the ethics gets worked out so that rich information can be used in a way that’s productive to help patients and build better products. But who knows, I think it’s going to be complicated because tapping into people’s conversations may be hard.

Ömer Saka: In defense of the payer’s landscape, I would like to say one thing from my several conversations with colleagues in the industry. I tried to underline that telemedicine is not a just a technology. It’s not just a computer and it’s not just being able to talk to your physician. Telemedicine is transferring data between physicians and 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. Firstly, they have huge amounts of information in the therapy areas that they work with. They do understand patient pathways and shortcomings on patient pathways especially which was coming because of the efficacy & effectiveness. But mostly, because the healthcare systems are not geared up to deliver the best results for each patient’s problem. Therefore, I think the burden is a little bit with the industry to define the clusters of how the technology that could be deployed on the payer-patient pathway. The potential ethical problems that can emerge databases. But beyond databases, some informal practices that could also formulate around these practices. The risk 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 enough tangible suggestions that I’ve made. I think the industry needs a bit more homework to do here.

Dan Housman: Yeah, well, things may have gotten a bit kick forward, but it’s still taken a while. We know the direction, I think it’s headed.

Ömer Saka: Yes

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

Ömer Saka: I mean, frankly speaking, I think the main problem is value-based care. I think the main problem is not the value of a pill. It’s not the value of infusion for a cancer patient. But it’s the value that we built within the healthcare system to lessen the pain of patients. I think the most difficult aspect of change is in the more established medical practices. I think the answer is ventures like Itron initiated by Michael Porter, trying to determine metrics of value not just related to a drug not just lead to treatment modality. But it’s 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 getting the effectiveness nowhere near as close to the efficacy results that the trials published. The value-based care can only be actualized, that’s the big game for me. If we stop talking about innovation in the sense that a new drug could generate for patients, but start talking about what are the gaps in care provision across the framework. I think when the necessary 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 think our friendship depends on to a certain extent on our intellectual endeavors but also this passion that I know you also share on converting healthcare systems into one entity rather than hospitals or clinics or patients or physicians or drugs here. I mean we could talk for hours about this. There are book chapters, I’ve written about this, which I’d be more than happy to share 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 improve on our understanding of value-based care.

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

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

Dan Housman: Yeah and I am sure we’ll be working long past like these gray hairs that are grown. Thanks so much, Cheers! See you soon. Bye.