 Hello, welcome everyone to our panel today. We're so excited to bring to you an exciting conversation with perspectives from around the globe about fixing health care digitally. My name is Sarah Kehalani-Goo. I'm the editor-in-chief of Axios News out of Washington, DC. And I'm thrilled to be here with you to welcome our audience in the room, as well as those who are joining us on livestream. Please join the conversation by using the hashtag WEF24. Now, let's go ahead and get started. We have a lot to cover, and I'd like to start by introducing my esteemed guest here today to join us on the stage. First, we have with us Dr. Gianrico Farugia. He's the president and CEO of the Mayo Clinic of the United States. We have next to him, Kristoff Weber. He's the CEO and president of Takeda Pharmaceuticals of Japan and also Boston. And next to him, we have EU Commissioner Stella Kiriakides. She oversees health and food safety for the EU. And last but not least, we have Minister Paula Ingebire. She is in charge of information, communication, technology, and innovation at Rwanda. Welcome to all of you. It's nice to have you. Well, I know that we're talking about digital health care, but really at WEFT this year, of course, AI has dominated the conversation. We can't escape it. So let's go ahead and start there. And I'd like to start with you first, Mr. Gianrico Farugia. First of all, the Mayo Clinic sits an interesting point of health care with both research and delivery of services. I've read about your investments in an AI technology firm to both scan images, scan records, for example, and also on the research side, looking into ways to detect cardiovascular disease. So I'd love to know your perspective about how you're trying to approach AI responsibly and what your real goals are, both with employees and with patients. Well, first of all, thank you and thank you for having this. I'll start off by saying something that I've said before, which is that it's very hard if you want to expect AI to fix every problem within health care. And therefore, it's very important to understand that there are going to be excellent uses for AI, but it's not going to be the fix for everything. And in fact, there's so much good that has happened in health care, but still, there are so many other issues that need to be fixed, disparities, inequalities, access, that you have to also first fix the underlying architecture of health care before we can bolt on AI to it. Why do I say that? Because that really applies now to how we, and I suspect many others, look at AI, which is that it is a remarkable opportunity to transform health care. But we have to do it in a way that's sustainable. And for us, what we've been advocating for is the fact that you cannot wait until every single legitimate concern has been ironed out. Why? Because the need is so big. And therefore, in health care, we have to embrace AI while at the same time we work together on regulations. But unless you embrace the fact that AI is truly an opportunity to transform health care, we'll be missing out a lot. That's the approach we've taken. And for example, you mentioned in artificial intelligence and in the heart. Two years ago, in a similar panel, I had mentioned that a simple electrocardiogram to have lead very cheap enables us now to predict heart failure five years ahead of symptoms and ahead of conventional testing. That information placed on a platform then resulted in other algorithms based on the same data now being able to predict silent atrial fibrillation, heart arrhythmias, valvular heart disease. But then most interestingly, and I think this is where the opportunity in AI is, liver doctors found they could diagnose from the same electrocardiogram liver disease. Blood doctors found they could diagnose blood disorders from that same heart, from that same electrocardiogram. And that's the true promise of AI, which is that it can scale in ways that other ways cannot scale. Now, as we evolve, I think we've got to do two things. One, we have to make sure that we validate what we're doing. And as part of that, we've been proud to help set up something called the Coalition for Health AI, now 1,200 organizations strong. But at the same time, we also need to internally stand up and be able to self-regulate so that we can create an environment where AI can do what it's supposed to do and what it can do, which is transform our current inability to deliver on what our consumers want. And what you just mentioned sounds like a lot of research in particular is on hyperspeed, which is exciting to think about. So give me a prediction going, let's say we're here a year from now. Where do you feel like we're going to make the most progress, at least in the Mayo Clinic? Well, I'd say that what used to be a forward-looking question is no longer a forward-looking question. AI has transformed healthcare. It has transformed our ability to create better outcomes. It has transformed our ability to increase productivity. And it has transformed our ability to scale in ways we couldn't do before. For Mayo Clinic, we have about 200 algorithms that run every day in our practice. And increasingly, you'll find other health organizations that are increasingly saying the same thing. Everybody in gerentive AI looks at the easy parts, relatively easy parts, which is administrative burden, very important. But I think the opportunities are much greater than that and they're bringing predictive and gerentive AI together in ways that now begin to enable us to look at diseases differently than we looked at, where now AI helping us is enabling us to find solutions that before were beyond what we were able to incrementally do. So we have over 200 engineers in AI at Mayo Clinic. And their job is within the clinical departments, walk around the patients, walk with our physicians so that they can identify the problems and then solve them together. And Mr. Weber, let's bring you into this conversation because at Mayo Clinic, obviously, we already talked about some research that is your area of specialty. I was fascinated to read about how you're applying AI to your clinical trials as one example. Can you share a little bit about that? Yes, sure. It's data on AI allows us to be much more efficient. I think there are two domains here. It's about efficiency gain, or you can call it productivity. And we think that in our company, we can gain overall 30% efficiency gain in a few years. Not only in the research, in development, but also in manufacturing, for example, across all our value chain. So that's one area. It's potentially a significant efficiency gain. The other area is that, like Janry mentioned, it will allow us to do new things that we have never done before. And it will allow us to discover new molecules that don't exist today. Eventually, there will be new targets that will be discovered by AI. So I think that that's another element. It will take probably a bit longer to get there, but that's also very exciting. And would you take that 30% out? When you think about what that means for life-saving drugs or disease-preventing diseases or addressing disease, that's pretty amazing when you think about the end user, what it means for global health care for patients. So have you done that math? Have you looked at what kind of impact that could make? Yes. It's still early, but we think that it will allow us to accelerate the development of new medicines. So instead of taking 10 to 15 years, perhaps we'll do it faster. It will allow us to be more targeted and to make sure that the patient is the one benefiting from the medicines. We are still today sometimes not so well targeted with the way we develop medicines. It will also hopefully reduce our attrition, so our failure rate. And so it could really transform the productivity of the company. Great. I would love to bring in the government perspective on the health care to commissioner. We've talked about speed in bringing health care products to market, drugs to market. But I also know the EU has been concerned about guardrails on AI. Of course, in health care, we have a lot of privacy concerns, data privacy concerns. How are you thinking about this when you think about working with private industry? I was listening very carefully to the interventions so far. And I think that it's not an either or situation. I think we all can see that we live in a constantly changing world and the world where digital health and health data and AI is really revolutionizing in what we can offer to patients at so many different levels. And saying that it's not an either or in terms of AI, I believe that we can have all the potential that AI offers us and have the guardrails in place. And the EU is the first time in the world that we now have an AI regulation act trying to put this framework into place. So I think I believe strongly that innovation is only important in that it reaches patients, in that it is able to really offer what we want for patients. And in Europe, at the moment and since the pandemic, which has revolutionized the way we see digital care and health care and AI in so many different ways, we have come forward with a proposal to build up a European health data space. Now, this is one of the key pillars of the European Health Union that we are putting together. Health is a member of state's competence. Many may be aware of this. But we have seen what we can do the European level to really help member states to come on board so that we fight inequity. And I think that this is a part of a project that we've been working on and a proposal that is out there. I won't go into details. I can come back to it. But it basically does two things. It has one part, which is the use of personal data. So it's called My Health at EU. And it aims to join the health data systems across the member states. So, for example, if a patient or a citizen is traveling from Spain to another member state and they need to visit a doctor, they are able to have all their health records available for them. And that's imaging and everything, which would really save a great deal of also money for the health systems and not the need. And also, the second part is the secondary use of data. So much health data is out there. We saw it with COVID. We need to be able to pull this data so it can be used for innovation and research. So the digital world in terms of health data is really where we need to be looking forward. And we need to really harness all this potential in order to reach for the benefits of the citizens and the patients who are out there. Yeah, I think everyone can agree health care does suffer from a paperwork problem. So the lowest hanging fruit does seem to be about addressing that and efficiency and that space. I'd love to hear from you, Minister, about Rwanda, from a different point of the globe, has a universal health care system. And you've been experimenting with technology from end to end, it seems. So I'd love to hear your perspective about how you view the government's role in all of this in terms of bringing technology in. Are you more focused on the investment side or are you focused on the regulation side, both? Both. So maybe just to set some context, a lot of the work that we're doing in terms of achieving an end-to-end digitization of our health care ecosystem is largely built on the fact that for Rwanda, our policies of inclusion made sure that when we were looking at health care coverage, we made sure that every citizen in Rwanda has access to health care. And by doing that, a country that has achieved over 99% health care insurance for all our citizens. And so we've had to create a program that at least allows every citizen, regardless of where you are, urban or rural areas, at least access to basic health care services. Because of that, we're able then to think about how do we then digitize the process of being able to access some of these services? And I do agree with many of the speakers in this session where when it comes to emerging technologies, it's not a question of just deploying them, it's figuring out what is the best technology where to address a problem that we're looking at. Now, I'll give you a couple of examples and I'll talk about what we're doing both on the policy and regulation side, but also in terms of the actual programs that we're implementing. But I'll start with the programs. When, I think when you read about Rwanda and our technological development progress, one thing that will stand out is the zip line story, where it was the use of drones for logistical services. And so when we started to engage with zip line, they had this proposal. We had a challenge of close to 500 health care facilities, especially in rural parts of the country, where road access was still a challenge. And so what that also meant was that being able to deliver the necessary products, medical products, was a bit of a challenge. And so we had a logistics problem. One of the ways was to, how do we create road infrastructure as quick as possible and massively scale it across the country? How much investment is going to get into that? But that wouldn't be the only thing to provide easy access of medical products. We needed to think about cold room storage, infrastructure for almost every health facility. And so when you look at all those kind of investments and how long it was going to take us to really ensure that we can close on this big challenge that we had, zip line offered us a great opportunity. And that's why we call ourselves a lab, a proof of concept country, because we wanted to test it and see what are the gains. And so with zip line, we've been able to deliver. We started with blood products, and now we're delivering almost a big range of medical products to these health facilities. And we were able to, even in terms of impact, move from delivering these products in three and a half hours to as short as 23 minutes. And this is an on demand service that we're able to provide. So how did that help us? Clearly, when we started working with zip line, we didn't have any regulations or policies around drone services. And it was a big contestious issue, similar to what we have with the AI landscape around not having globally agreed on drone regulations. So we could have chosen to wait and see until someone figures out the regulations, someone tests it elsewhere and try and replicate it back home. But because it was solving an immediate and urgent problem, we decided to use that use case to develop what we called performance best regulations. And so those have given birth to many other countries that are able to benchmark these policies and regulations to create similar ones for the different drone use cases. Now another example I'd like to share is also around AI, where we had about 13 radiologists for a population of close to 14 million people. So we're talking about one radiologist for one million people. And so you can imagine the bulk of work. So for us, it was very clear that we were able to build an AI model that helps these radiologists to quickly analyze and figure out which cases are critical and bring them to the front and deal with them. It's a better use case on how we apply AI. And so because we're looking at that particular use case, we're then able to quickly accelerate the development of our data protection and privacy laws because that had to do with a lot of personal data that was going to be used as we do this kind of analysis. And so for us as a proof of concept hub, it's been a question of driving a parallel process. Sometimes you don't know what to regulate, but at least you need to have actual use cases that you're implementing that will inform the policies and the regulations that you put in place. Thank you so much for sharing about Zipline. I think that's really fascinating and interesting solve to the problem of access in a physical geographical sense. And we haven't talked about that part of how technology can really address the access issue. I wonder if you have any thoughts on that from from the hospital perspective. Maybe, you know, access can be about geography. It can also be about reaching people who don't, as in the United States, not everyone has healthcare. So the Zipline story is one that really resonates with what we're trying to do, which is create a different architecture for healthcare and that different architecture for healthcare then can be used in a much more scalable way. You, I love the way you said it, is you know, you need to have something to regulate to regulate and therefore you have to keep innovating. I think that's where healthcare comes in. I think healthcare has an obligation to stand up, have an opinion and as a result of that opinion, then be able to work with partners that disagree with us in order to create sustainable solutions that are digital or they are AI based or sometimes both. And in order to do that, we have to be ready to not only do proof of principle studies and pilots, but we also have to be ready to pivot as the data tells us to do otherwise. And in healthcare that sometimes then take a little longer than in other places. It is essential for healthcare to distinguish in this digital revolution the difference between being skeptical, which is healthy, it's required and being cynical because there is a little bit of cynicism around AI about digital, about its ability to truly level the playing field to reduce the digital divide. And I think while you can be skeptical, you cannot ignore the fact that there are now many, many examples of where outcomes have been better for people. I use that ECG example from Mayo Clinic that was taken up in Nigeria to detect peripartum heart failure for women who just had a baby or just about to have a baby because that's the scalability. And when you do that, what you have to make sure is that there is both the ability to validate and the willingness to self-regulate even as you participate in more global regulation. And validation I think is going to be a very important part of our future, making sure there are systems in place that are third party that enable independent validation to make sure it is fit for purpose as a digital tool. And that is not only fit for purpose but it actually does what it says it's going to do. And self-regulation is going to be really important and is really important so that then we can inform government, we can inform other parts of the other sectors on how together we can do something that doesn't regulate the present but for digital transformation needs to have the ability to regulate the future. Right, yes, but another part of that is also built like to address cynicism is building trust and being transparent as you mentioned as well. I'd love to hear from anybody at the panel about how do you do that? How do you ensure that it feels like we're at a moment we're entering this brave new world or wild west, however you want to think about it. And so wherever you sit in the healthcare industry whether that's development as research doctors who are overworked and maybe burnt out in patients who are skeptical or concerned about a new technology. I'd love to hear your perspectives about the trust piece of this. Mr. Weber, do you have thoughts? Well, it's a really very important topic because obviously people are more sensitive when it's about health, right? And it's about your data and it's an extremely sensitive topic. So first, you establish trust if there is transparency. Meaning that it's clear what is done with the data who has access to the data. The concept of data privacy is very, very important. So you need to establish this transparency. I think one area that we need to create actually more transparency and we need to work with regulators on that, it's about data ownership. I think data privacy has been the focus which is very, very important. But in many countries there is still there is still relative unclearity about data ownership. And when you ask patients about that data they always feel that they own that data meaning that this is their ownership. But in fact in reality in many countries it's not the case. The data is owned by other parties. And I think there is a bit of a vacuum right now on that topic and it's very important that we create clarity about data ownership because there will be a lot of value creation by multiple actors leveraging this data. So it's very important that we clarify that point in the future because this data will create so much value for the society, for multiple players. So clarifying that will be very important. Especially for a business like yours that's doing obviously products around the world and employees around the world as well. Yeah, but healthcare data is in many, many places. It's in hospitals, in insurance, in pharmaceutical companies. So I think clarifying that is extremely important. And there is anonymized data and there is non-anonymized data. And the data ownership might differ depending on what data we are talking about. Right, right. Commissioner do you have thoughts on that because you talked about the data, EU data rules as well as there's an AI one as well? I think this is really, this is central as you have said and what we're trying to, what we have put forward and we're trying to build through the European health data space is that the focus is always putting people at the center of what we're doing. And in order for this to really bring results, people need to trust the system. If they don't trust the system, it's not going to be able to bring the results that we would like it to bring. And for this, they need to be empowered and they need to be able to, as patients, fully control their own data, their own health data and to be able to exercise their rights. So there are a lot of safeguards in the proposal that we have put forward. And they will have the choice to be able to share their health data with the medical providers if they choose to. So I think that for us to be able to really make sure that we are putting into place a system that is interoperable between member states but is also going to serve patients, it has to be a system where citizens feel they can trust and health data is very, very sensitive. So they must feel that they can have the choice to control which data they want to share with who they want to share it and also have the choice if they don't want to share some of their data for any reason that they're in control. This is about empowering them. But this is the part which is on their personal use of health data. On the anonymous use of health data that comes for the secondary use and that is totally different. Where again, there must be the control so that they feel that they are protected when data is used for research and others. So maybe just in addition to what the rest have said and maybe a different take, when we talk about trust in the context of emerging technologies, I think we need to realize that it transcends the topic at hand of emerging technologies. If citizens don't trust their government on other things other than emerging technologies, then it's probably going to be even more difficult when it comes to how their data is being treated or who owns it and what's happening. And so in many ways, even as we address the issue of trust, it comes back to what is the social contract that governments have with their citizens? Can they trust what you say even beyond their own data, even beyond technologies or where you're going as a country, the promises that are being made to them? Once that's clear, I think a bit of awareness, a bit of transparency, a bit of education and then also being able to show value for what you're trying to do will go a long way in bridging whatever trust issues may emerge from these emerging technologies that we're dealing with today. It doesn't say it's going to be easy. I think what's also very important to do is when you look at the application of emerging technologies as policymakers, as governments, or even as corporates in the industry, you need to look at the ranking of what issues am I trying to solve for? What is the sensitivities around these issues? Can I start with the easier ones because along the way you're able to build the much needed trust and when you get to the more complex issues, which is where then you require that there's a bit of co-creation that happens with people who are potentially going to be beneficiaries of this technology that you're putting in place, co-creation not just for the products and services, but also when it comes to putting in place these regulations that are needed to enable this level of innovation to happen. And I know we've spent a lot of time on AI, rightly so, addressing the bigger sweep of this issue, but I also want to make sure we leave time to talk about other technological innovations taking place in healthcare that are still going to make an impact or that are still important and relevant that we shouldn't take our eye off of. And so I'd love to talk to you from the Mayo Clinic's perspective, where else do you see the most potential for progress in the short term? So it's a fascinating conversation because what it comes up to is how you define terms. So we talked about data ownership, but what does the identification actually mean? And also how do you have the flexibility to change your mind over a lifespan? When I look at where our transformation is going in healthcare, you see a lot of great examples. And one example, of course, being in genetic therapies that will completely change the lives of children. And therefore, there on the other hand, then you have to worry about the fact that the initial cost is so great that you need different mechanisms than currently there's no government system, there's no pair system that actually knows how to deal with that. I would actually, sir, if you give me opportunity, I'll take it in slightly different direction. I worry that healthcare transformation, including digital, is going to be held up in the next 10 years by the fact that the physical infrastructure in healthcare has not kept up with needs across the globe. And unless as nations we deal with the fact that our healthcare physical infrastructure is inadequate, we are not going to be able to get the benefits from all the other things we've been talking about. Those will then come on layered upon the fact that eventually most people do get sick, most people do need a place to go, and even as much as you can do digitally, you need to be able to embed a lot of what we do into that physical component. So I do worry about the physical component of healthcare actually constraining the digital transformation. I'll let Christoph and others talk about the fact that however, having said all that, biotherapeutics, a-sell your therapies, terranostics, we'll see massive improvements in the next years. And real quick, before we go to others, like in the structural, give us one or two things that is really standing in the way. Structure, physical. Yes, yes. So in the United States, the last infrastructure act for healthcare was in the late 1940s, and that kept on going. In the world, our infrastructure ages, not every year it ages by year because new buildings come in, but it's aging faster than we're replacing it. So we're currently in a situation where you cannot bring in digital tools into the hostel room. You cannot get rid of this divide between inpatient and outpatient. You cannot create a seamless opportunity and experience for patients between digital care, physical outpatient care, physical inpatient care, and then digital care again. The only way you can do that, in my view, is by actually rebuilding how we think of hospitals and we are just, because you gave me the opportunity, we just announced a $6 billion investment in redoing our infrastructure because we believe it is important, but we also understand that globally we're going to need governments to step up to be able to help solve the problem. Commissioner, do you have a response to that? Yes, so I am so glad that you raised that because I think it really is one of the huge challenges and almost an ethical challenge that we're all facing. And we need to really address the fact that we cannot allow the potential that we have in digitalization of healthcare and AI lead to inequity. And there has been, and we have seen this in order to be able to harness all the potential of what we're discussing, you need to also have the infrastructure, exactly as you have said. And we're, as European Union, working very strongly with member states in order to be able to strengthen their health systems to bring everyone on board. And not only within the European Health Union, digitalization of healthcare is a cornerstone of our global health strategy as well because otherwise we're going to really have a digital divide which is going to make things more difficult. And it is about bringing everyone on board but also educating and making sure that we have the capacity building for those who are working in the system to be able to follow what's going on. So there's a great deal that we need to do but I like to always see the glass half full. And I think that when we're faced with potential and challenges, let's see how we can actually move forward and not be held back by what we need to address. We will address it. And I just want to take one moment to see an example of what happened during the pandemic. When I, it was not there before, it became a way of life for many of us traveling within the European Union and not only. Within three months, we set up a digital COVID certificate that allowed people to travel and opened up economies and societies because we used digital healthcare in order to be able to allow this to happen. And now it's being taken over by WHO. There are over 80 countries on board. So we need to think out of the box. We need to move forward. We need to be aware of the dangers but let's not lose sight of the potential. This is what I would say. I think touching on the issue of infrastructure which I fully agree with and I'll probably also share examples of what we've done in Rwanda because the way we've structured our healthcare system is exactly to address this challenge of having physical infrastructure that is accessible for citizens, particularly in rural areas. And so what we have is a network of over 70,000 community health workers in a way that are mobile and so they're able to move around the household and provide this kind of fast hand service to the citizens that may be needing this kind of health service. But then the next layer is what we call health posts. And so the model that we've taken because I think like most governments, the challenge you will have is you need to have massive infrastructure deployed across the country. Do you have the financial resources to do that? I think no one has the financial resources to do that. And so the model that we've also picked on is how do we encourage private investments in being able to build up even social enterprise and NGOs to build these health posts in rural parts of the country and be able to manage them and sort of think of a sustainable financing model for doing that. And I want to highlight one particular example for a company that has a contract with our healthcare ministry to put in place around 200,000 health posts. And one of the things that they're doing that I find truly powerful is the ability to use satellite data to understand the population density in any single area because they need to identify in new locations where to place the health posts. But once they understand where do we have health posts where is the absence of a health post, where do we need to place one because you have sufficient people living around that don't have easy access. And when we talk about easy access, we're talking about a five minute walking distance at least. And once they've identified that data, they're able to also look at data around where are we most likely going to get landslides because sustainably, if you have to build this health post then you have a landslide, there's a problem. So being able to look at some of this environmental data, population density, mobility around it and that's how they're able to identify new locations that will be able to serve a good number of households and people across the country. And so I think in many ways to address this challenge, it's really, it requires a lot of creativity and thinking out of the box because traditional models will not be able to close the gap that we have. And what we continue to see is that the places that lack such infrastructure are the places that probably most likely need the infrastructure. Mm-hmm, that's great. We've covered a lot of ground. I know we're almost out of time. At Axios, the news company Ioversee, we talk about smart brevity. So I'd love to go to each of you in smart brevity if you give me in one sentence out of this conversation, what's one takeaway that you wanna leave this audience with about the promise of technology for healthcare in the short term? As healthcare systems, we need to stand up, own it and then be good representatives for the patients that we look after. Mm-hmm. All right, Mr. Weber. Healthcare will improve with data, technology, AI. There will be more innovation, longer life expectancy, less inequity because it will be more visible. So there will be a significant improvement. But we need to finance healthcare. And healthcare costs for all countries will increase faster than GDP. Mm-hmm. And I think there is a paradigm of financing that we need to make sure happen. Commissioner, one sentence to ensure that digital transformation benefits everyone. Simple, I like it. Simple. Minister. Healthcare financing, deployment of innovative technologies will truly transform healthcare industry. Wonderful. Well, this has been a great conversation. We're not done yet before we wrap. First of all, I wanna thank our panelists. And I also wanna turn it over for some final closing remarks from the Honorable Revanth Reddy, his Chief Minister of Telangana, India, and he will join us for some final remarks. Greetings. It's a pleasure to be here with all of you. I represent Telangana, a state in India as a Chief Minister. I come from a rural background. I understand problems of the poor people. They don't get good quality healthcare. It is very expensive. Poor people are not developing because of no good quality healthcare. My party, Congress, and my vision is to give good healthcare for all people. We have Rajiv Arogyashree, which pays for hospital bills for a piece one million for every poor person, every animal. Hyderabad is the capital of healthcare and software. My government wants to use technology to ensure healthcare for everybody using new PPP models. We will create digital health records for all citizens, 40 million people in my state for better planning and implementation. We will also ensure data security and privacy. Hyderabad makes 33% of all global vaccines and drug production. We are hosting BioAsia 2024 in February. It is all a platform for life sciences companies. I welcome all of you to come to Hyderabad and attend BioAsia. Let us together create impact. Business means impact. Telangana means impact. Thank you. Thank you so much. Before we go, I just want to thank the panelists. We covered, I was a little skeptical we were able to cover so much ground, but we really truly did from the private sector, from the public sector, from different corners of the globe. Thank you to our panelists for a great conversation. And I want to thank our audience for engaging with us. I'd like to let you know on behalf of the forum that they will be leading a digital healthcare transformation initiative through 2024. And they're open to engaging with key organizations for anyone interested in participating in the initiative. There's more information that could be found via top link and the forum website. So please reach out to the forum center for health and healthcare. This concludes our discussion. Thank you so much for joining us.