How to get hospital AI from pilot to scale (Eyal ZImlichman, Sheba Medical Centre)

[00:00:00] Dear listeners, welcome to Faces of Digital Health, a podcast about digital health and how healthcare systems around the world adopt technology with me, Tjaša Zajc.

[00:00:09] If you're a chief information officer, chief digital officer, chief AI officer or whoever in a hospital or healthcare setting in charge of making decisions about AI deployment, you probably have a hard time deciding what really works, how does it compare to competitors and how do you know if an AI solution is going to stick.

[00:00:42] With the speed of AI development, the supply of solution is increasing as well. So how many startups actually succeed and how many solutions actually stay there beyond the pilot? I spoke with Professor Eyal Zimlichman, chief transformation innovation and AI officer at Sheba Medical Centre in Israel and the founder and director of ARK Innovation.

[00:01:09] According to Professor Zimlichman, around 30% of AI pilots fail. So in this discussion, you are going to learn more about how a hospital measures AI return on investment, what counts, is it the outcomes, costs, access, how does AI impact burnout and the impact on clinicians and their day-to-day life.

[00:01:37] We discussed open innovation and why healthcare systems distrust startups and much, much more. So enjoy the show to learn more about the regulatory perspective in different markets and how to invest in innovation going forward with the AI era. Enjoy the show. And if you haven't yet, check out our newsletter, which you can find at fodh.substack.com.

[00:02:07] We are on LinkedIn, YouTube, where you can watch the interviews in a video format. And if you will enjoy the show, make sure to subscribe to the podcast wherever you listen to it and leave a rating or a review. Any feedback and ideas are super valuable for me to know what else to cover, what to improve.

[00:02:31] And of course, just by liking the show, you support the creation of this content, which has been running for over 10 years by now. Now let's dive in the discussion with Eyal Zimlichman.

[00:02:58] Ehal, hi, and thank you so much for joining me on Faces of Digital Health. This is the second time that we are having a discussion for the podcast. The first time we spoke was in 2017, where when you were just in the process of establishing ARC or the Innovation Center inside the Shiba Medical Center,

[00:03:25] where you are the chief transformation and innovation officer. What has changed in the last 10 years on the hospital medical center level and on your observation of the digital health space as a whole? Let's start there. So thank you, first of all, for having me back on the podcast. It's a pleasure. And nine years is quite a long time. So many things have changed.

[00:03:54] I would say that from Sheba's and ARC perspective, Sheba has advanced considerably over that time frame, as it's very highly regarded as a very digital hospital, transformative hospital, both in terms of ranking on Newsweek and other rankings that exist around the world, but also in terms of our capacity to establish a blueprint for forward-thinking hospitals, which we have taken forward through ARC.

[00:04:21] So the hospital itself has evolved quite a bit over that time frame, where transformation has become really a cornerstone of what we do. And the use of digital and AI is really extremely central. And we can talk, of course, more about that. So that's on one angle. On the other, ARC itself has grown considerably. We built ARC from day one. We launched it officially, by the way, in 2019. But we built it from day one to serve as a global platform,

[00:04:48] focusing only on challenges that are global in nature. We're not dealing with any challenge that's local only, but only things that are shared across countries. And because we've built it in this fashion and really looking at collaboration as a central part of the strategy, we've been able to build ARC as a global platform with now 10 centers around the world in 10 different countries and many more partners.

[00:05:15] On top of that, we've been able to create more than 140 startup companies in the timeframe since 2019. The technology was able to impact 125 million patients worldwide. That technology coming out of ARC. And our training program for entrepreneurship for clinicians and frontline employees has already trained thousands around the world across the ARC global ecosystem. So ARC is growing very rapidly.

[00:05:43] And lastly, how has our world of innovation and transformation changed? Obviously, I can't complete this answer without saying the two famous letters A and I. And that's been a huge change. I'm also the chief AI officer at Shiba. And we have a full strategy on how to turn Shiba into an AI-based hospital. By the year 2030. And it's a major part of what ARC is doing with our partners around the world. And as we think about what has changed over the last nine years, since we last were here on this podcast,

[00:06:12] I think AI is the greatest opportunity. We knew it back then. We didn't know to what extent. And I think looking back retrospectively, this has been the major opportunity that now healthcare is facing in terms of really being able to make a difference. I definitely want to talk about the global expansion of ARC and what does that bring to the other partners in the ecosystem. But before we go into that, I can't skip the whole AI topic.

[00:06:40] And given that you've been doing this for such a long time, how do you measure the return on investment? How do you make sure that the technology also has tangible numbers behind it? Because that's one of the biggest struggles that CEOs and CFOs are faced with when they're thinking of what to implement next. So I think, first of all, as we put together a strategy, we need to think where do we have substantial evidence or at least emerging evidence.

[00:07:10] I can't say substantial because this whole field is relatively new. But where do we have emerging evidence that AI can really help? And when I say help, of course, like other provider organizations, we're focused on a couple of items. When we say return on investment, it's not only financial. Of course, impact on outcomes for our patients, driving patient-centered care, driving value, reducing cost. These are all the things that we're focused on. And also providing or improving the provider experience.

[00:07:40] How do we reduce burnout for our clinicians? So these are the things we're tracking and measuring and where we're focusing to try and drive solutions. I can give you a couple of examples. One of the technologies that came out of Shiba and Arc back in the days in 2017 is a company called AIDOC, AI DOC, that I'm sure many of the listeners are familiar with. We've done a clinical trial with AIDOC. And for those of you that are not familiar with the technology,

[00:08:05] it's an AI in radiology that was established primarily for emergency conditions in the emergency setting, emergency departments and so on. We found that implementing this technology in the emergency department to detect stroke earlier has led to a 30% reduction in mortality. 30% reduction in mortality for patients with a neurologic stroke. We actually published this work in a scientific journal. And that has created quite a bit of interest around the world.

[00:08:34] And the technology itself, of course, has become very well known and deployed now in more than 2,000 hospitals around the world. But the impact, the clinical impact, the return on investment clinically is immense. Because if you multiply 30% reduction in mortality times 2,000 hospitals around the world, you understand that this AI algorithm is actually saving hundreds of thousands of patients globally.

[00:08:58] And this is something that not many of us can actually say that we can contribute to saving hundreds of thousands of lives. So this is one way to measure the impact. And we're very busy trying to measure as much as we can and show the proof of concept that is created. On the financial side, there are technologies that help us improve access to patients, help us improve efficiency of operating rooms, help us improve efficiency of ambulatory services at large.

[00:09:27] We've been deploying these technologies at, for example, ambient technology in the ambulatory setting to reduce the length of time for medical appointment because physicians don't need to type in the entire encounter into the electronic chart. It's now being summarized and entered automatically, which reduces time as well as improves the patient experience and reduce the burnout that is associated with the administrative tasks that physicians need to undertake.

[00:09:57] So all these are being measured. And this is where we're focusing our efforts right now to try and deploy ambient broadly across the Shiba system and with our partners around the world. When you came to Shiba in 2013, you came from the patient safety side. So you spent a lot of time just researching and working on how can we prevent medication and other errors.

[00:10:22] And anytime we implement a new technology, it also has negative side effects. In the past, we had illegible prescriptions. Now doctors, then doctors typed fast. Now they speak and ambient technology can also get names of drugs or diagnosis wrong.

[00:10:41] There was just this week, I think, or recently, this article for the UK market that basically warns how patients notice errors in their medical records just because we do expect human to be in the loop and to check all the notes that the scribes are doing. But we also know that doctors are humans, so they might at one point get technology fatigue and just confirm things that are done with the technology.

[00:11:11] So just from those two perspectives, how do you look at changes in patient safety with AI and what kind of measures do you take at Shiba to make sure that those errors are mitigated and minimal? That's a great question. Every technology we introduce, we have a whole governing structure at Shiba that looks at the deployment of AI technology from a patient safety lens.

[00:11:38] And the person who's in charge of approving every technology to be used at Shiba is our chief quality officer. Not our chief AI officer, which is my role, but the chief quality officer, which is a role I did in the past. And that's something that we've introduced and we're working with many of our partners to do the same. The idea is that there's a whole governing structure that is a structured approach to how to introduce AI,

[00:12:02] how to approve AI, how to track AI ongoing to make sure that we're aware of any patient safety issues and we can counter that and react to that ahead of time. And for example, if we have an AI that we introduce into Shiba, we will always introduce it for something between 3 to 12 months, depending on the risk, and then we'll reassess. We will look at the data, we look at errors, we measure the accuracy,

[00:12:29] and then we make another decision whether or not to extend the approval for the deployment of AI further. And this is what we've done. Specifically with ambient technology, there are big differences. I don't want to go into specific names of companies, but there are big differences between the different companies in the accuracy. And again, what we've done at Shiba is we've looked into several of those solutions that exist in the market.

[00:12:54] And we did find a big gap in terms of accuracy of, as you were saying, medication names and so on. And we chose the one that we thought was the most accurate. And the staff is, I have to say, is pretty happy with the technology and the way that it's performing. There are a lot of other additional benefits that come from ambient technology.

[00:13:15] What we found was that the documentation is much, much better than before using ambient because it captures much more data. It enters that data into the medical chart and we're able to acknowledge a lot of the things that otherwise the doctors would not enter. For example, if we're explaining to a patient side effects of a certain medication, that's not always entered into the chart manually by the doctor.

[00:13:42] But the ambient captures that and logs the fact that actually the doctor has gone through the full explanation of what the risk and benefits are for every treatment that we offer. So we think that improved documentation has a huge impact to improve quality and improve patient safety. And that's something that we're gaining through using ambient. Could there be mistakes? Of course, there could be. But they need to be measured against the chance of a human mistake without using ambient.

[00:14:12] And as we make quite a bit of mistakes already, it's not that humans are perfect. Far from it. And overall, I would say that the idea is that we want to get ambient to a point where when we look at the net effect, it has a positive effect on patient safety and quality.

[00:14:27] One of the things that has been mentioned on the U.S. market is that exactly because ambient scribes capture more data than the manual recording of doctor's notes would, that is potentially having an impact on how much healthcare costs because healthcare providers can now charge for more things because more things are documented. Obviously, there's a different healthcare system in Israel.

[00:14:56] So I don't know if that is a relevant challenge in your case as well. As you're saying, it's a different payment system. Israel is much more similar to Europe in that regard. And of course, in Europe, that doesn't exist. And I think also in the U.S., this is changing the payment system in the U.S. as well, where you move away from fee-for-service to pay for performance and capitation. And I think that's something that we're going to see fade away or be reduced.

[00:15:26] In hospitalization, for example, right now, hospitals cannot charge for every service they provide. If they do an ECG, they don't charge extra for it in an inpatient setting, only in an outpatient. So things are changing, but you're right, it has a lot of impact. I think we're going to see a huge or at least a considerable reduction in malpractice because of the improved documentation. A lot of malpractice suits, we lose those and we have to pay because we were fined, but we never registered.

[00:15:55] Again, patients could sue you for not explaining to them the risks of surgery. And they would win in court if you haven't registered that you've went through all the risks. Now it's all captured. So I think we're going to see a major reduction in malpractice suits, which will offset some of the maybe increased increases in billing that you might see in the U.S. Absolutely. You mentioned earlier that when you're implementing a new technology,

[00:16:24] you take time to evaluate it, 3 to 12 months, and then you decide what to do next. And one of the things people would love to hear more about, but nobody really is open to talking about it, is examples of pilots that didn't scale and why they didn't scale.

[00:16:41] Do you by any chance have an example of where you tried something out and it turned out that it's not good enough for a larger scale implementation? Yes. We have a couple of examples like that. I don't know. Again, I won't mention names of companies, of course, but specifically we both internally developed as well as external. We have quite a large capacity for internal development.

[00:17:09] We have an AI center with about 60, 6-0 employees, full-time employees. And so we develop a lot of things in-house as well. One of our earlier attempts, we actually built an algorithm that would alert clinicians in the emergency department. When they're about to discharge a patient, if the risk for mortality on that patient in the next 30 days is over a certain threshold,

[00:17:33] we wanted to have that clinician appreciate that and know that maybe he's making a mistake by discharging the patient. That was something we introduced. And actually, at the end of the day, a couple of months later, we ended up removing it because it created too much noise. And the doctors really said, listen, it's not really helpful. We had some patients obviously be hospitalized just because the score was a little higher and nobody really understood why they needed to be hospitalized.

[00:17:59] And so after using it, again, taking it through the committee I mentioned, this was one of our earlier attempts to taking a technology through the AI committee we established. After introducing it and providing a six-month period for this to run, when we came back to the committee, we made a decision not to continue with deployment of the technology because of the concerns that were brought up. So that's an internally developed solution. We also have solutions that we brought from the market.

[00:18:28] For example, solutions that help us evaluate patients before they come in and have them scan their documents and then run summarization on top of paper documents that patients are coming in with, where again, we found that to be not as accurate as we would like. And it ended up not saving time for the physicians, which is what we were hoping to achieve. And we ended up not using the technology or after the pilot. So we did not scale up.

[00:18:53] We, on average, I would say about 30% of the pilots we try end up failing. And when I say failing, it means that we're making a decision not to deploy on a broad scale. It doesn't always mean that the technology is not good. Sometimes the human factor is not well engineered. It's not working with the existing workflows in a way that would promote large-scale implementation. And so there are different reasons. But I would say about 30% we end up discontinuing.

[00:19:22] What are you observing in other ARC centers across the world? You mentioned earlier that there's like several places that are using the innovation model. So what's the attitude towards this trial and error approach to innovation? I'm just wondering if you're noticing anything from the cultural perspective,

[00:19:47] how hesitant are people to just be aware that 30% of pilots are going to fail or even more and are not discouraged by that? Yeah, there's a lot of differences culturally. You could imagine because we work very global in the Far East, in North America, South America, Europe, of course, we see a lot of differences. There's differences in appetite to take risk. There's differences in appetite to just bring in technologies from the outside.

[00:20:16] One of the things that ARC is really pushing, that's part of our strategy, we call it open innovation, is the capacity to scout and bring in technology that exists outside, to deploy it within the healthcare system. Most healthcare systems around the world see startups in many ways as a nuisance. Somebody that comes knocking on your door and trying to ask for something when they're not invited. And we see it differently at ARC.

[00:20:43] We think that there's a huge amount of opportunity with technology that exists outside of our walls, and we should make an effort to find the right technology, to bring it in, to run a proof of concept, to show whether they work or not. And if they do, we put a large emphasis on large-scale implementation, because at the end of the day, we all know that that's the challenge, moving from pilots to large-scale implementation. And that's part of what we teach and bring into the other ARC centers around the world.

[00:21:10] And they have KPIs in terms of how many technologies are they bringing in, how many technologies they scale up, how many pilots they conduct, and so on. And we track that to make sure that it's not just about organic innovation, which everybody is much more excited about. When you can invent something, potentially take it to market, and potentially even see financial returns, obviously everybody is more excited about that.

[00:21:36] But most of the time, most organizations are not excited as much about open innovation. But if we are looking to transform, we need to be very good at being able to evaluate technology and scale up technology. And the Ambient example is a great one, or the ADOC example is a great one, where there is substantial evidence that this leads to a return on investment, both financially as well as the outcomes that we're looking to achieve.

[00:22:02] But still, we're not doing a perfect job at being able to implement and scale up. What is fueling the hesitancy towards open innovation, according to your observation, just globally? Yeah, I think just there's many reasons to it. I would think one is that we tend to be hesitant about startup companies. We're much more concerned about whether the company will survive and be able to support us in the future,

[00:22:32] whether or not their product is viable enough, is safe enough, whether or not they'll be able to support us in the way that we are supported if we go and buy a product from Microsoft, or a product or we buy a new MRI machine off from Philips or GE or Simmons. We still work much better when we work with large industry than we do with startups. We don't always have the right path even to bring in new technology. We have to go through a lot of committees and tenders and so on.

[00:23:00] Even if there's only a single supplier, we still have to go through and jump through a lot of whoops and convince many committees that there are no other solutions. It's a unique one, and we want to be the first to implement, and we want to be on the cutting edge. So I think that this trust, I think, on one hand, and also regulation, on the other hand, are two factors that prevent us from being able to open ourselves to new technologies.

[00:23:26] Speaking of regulation, in June, I think the ARC model was introduced to Charité in Berlin. So given that European regulation is famous for being strict and being complex, what are your observations so far in terms of what impact does regulation in Europe have on innovation that's different to other markets? To which extent is it easier to innovate elsewhere?

[00:23:56] If I'm not mistaken, when we spoke in 2017, you were explaining to me how you have the anonymized data approach that startups can access to test their solutions, and exactly this access to data from hospitals is a huge challenge in Europe where hospitals are data holders and need to protect their data. And yeah, in that sense, it's much more difficult to just innovate as an outsider. You're 100% right.

[00:24:24] And again, because ARC is unique in its global approach because we work in so many different geographies, we're able to see that. And it wasn't me, but somebody referenced Europe as a regulation superpower, very strong in regulation. And I probably would agree to that. And I think it is holding back the innovation and the ability to push forward. We are part of another consortium, which is the Mayo Clinic platform you might be familiar with,

[00:24:50] which shares data in a very secure way in a federated approach across organizations around the world. Shiba is one of the founding members of Mayo Clinic platform. We were there from the start when the platform was first announced. There are no European partners currently that are part of Mayo Clinic platform. There are partners from all other parts of the world, but no European partners. And I think that is holding back, not just innovation and transformation,

[00:25:16] but also research and the ability to bring scientific discoveries and study certainly on large language, as we know is critical today for scientific discoveries. I think it is holding back some of the advancement. I do hope that we're going to see more clarity on regulations in Europe, more clarity. Because right now, I think the lack of clarity is just intimidating organizations to take a leap forward. And again, we see it with some of our partners in Europe. We also have an ARC site in Belgium,

[00:25:45] and we're working on other ARC sites in Europe as well that will be launched in 2027. And so we're seeing the same concern across the continent. How do you think that could be mitigated? Or are we just going to accept that it is what it is? I think, again, it's up to regulatory bodies, policymakers in Europe, to make sure that they're not flushing the baby with the dirty water. Yes, you need to have strong regulation,

[00:26:12] and regulation needs to support patient safety and patient privacy. That's what regulation is for, and it's extremely important for that. But I think that we're at a point where, again, there's a lot of uncertainty. And if you ask provider organizations and their legal advisors in Europe, they would tell you that they're not approving the use of some technologies, not because it's against regulation, but because the regulation is unclear. And that clarity needs policymakers to jump in

[00:26:40] and make the next effort to try and make sure that we're not, we're not in some ways holding back scientific discoveries, research, and innovation in Europe, where other parts of the world are pushing forward. Yeah, interpretation is a tricky thing because it can very easily differ based on the person, based on the country, which can lead to additional challenges. If you look back at the last nine years,

[00:27:09] is there anything that you consider as the biggest success of ARK? And what are potentially some of the challenges that you're still looking forward to tackling? Yes, I think the global footprint and the global expansion of ARK is a tribute to the success of the model. And we were very active, as you know, very well, because you came really in the early days. We were very active at Shiba, and we were able to create substantial evidence that the model is working,

[00:27:39] both on promoting transformation, as well as promoting economic growth. In a timeframe from 2019 to 2025, we created 135 startup companies that have grown in valuation in that timeframe by almost 7 billion US dollars, have raised about 2 billion in that timeframe, created 4,300 jobs in the high-tech industry. This is a hospital creating jobs in high-tech, not creating jobs for nurses and doctors,

[00:28:08] which is what we typically know how to do. 4,300 jobs locally in the high-tech industry, which is a huge push for the economy. And as I've mentioned before, impacted 125 million lives through the global expansion that ARK is providing. So I think that evidence and the numbers we reevaluate them once a year, they're continuously growing almost exponentially, has really driven the spread of ARK around the world and has brought so many other partners.

[00:28:36] We mentioned Berlin, Charité in Berlin and many others around the world, Sing Health in Singapore and Cedars-Sanai in Los Angeles and Albert Einstein in Sao Paulo. And then the list goes on and on to say basically, we want to achieve the same outcomes that ARK was able to achieve at Chiba. And that's why we've launched about three years ago a separate entity called ARK Global, which is tasked with setting up more ARK centers.

[00:29:04] We have about six, seven others right now in the pipeline, including countries like Sweden, Denmark, more in Germany, the US, of course, Canada, India, and other parts of the world. So that's growing very rapidly. And we'll be doing some announcements shortly on a couple of new sites we're setting up, but also countries, countries and provinces and states that are interested in seeing also the economic growth that ARK was able to achieve because as many municipalities and countries governments around the world

[00:29:32] are trying to promote economic growth through innovation and commercialization efforts, bringing in foreign investment and so on. And that's been a big success story at ARK and again, part of what made ARK so famous around the world. In one of the interviews, I remember you mentioned that basically when this whole initiative started, you were driving ideas from the desire to turn healthcare into an economic engine of growth.

[00:30:01] The numbers speak for themselves, at least locally. Do you also observe that in other ARK centers? So you mentioned that a little bit at the end of your last answer, but maybe you can talk a little bit more about that, especially since, as we discussed before, in Europe, countries, institutions are struggling because of the regulation and just the different cultural context. That's a great question. So all of the centers that we've set up

[00:30:29] have very clear KPIs on both transformation and economic growth that they need to achieve on year one, year two, and so on. And so far, they're exceeding the KPIs that were set. So Shiba has a larger span of time we can measure against because we started ARK in 2019, but we started working on it as already before in 2017 to build it. So we have more time to show the numbers because, as I've said, they grow exponentially. The other sites have launched mostly

[00:30:58] over the last year or year and a half. So they're still ramping up activities, but we are seeing as a tribute to the success of the model that, again, the KPIs, for example, how many startups are started by the hospital, how many patents are registered, how many companies from outside sign commercial contracts, all these are measured through very clear KPIs for every ARK center. And we see for every ARK center, those KPIs not just met, but exceeded. And so I'm very confident

[00:31:28] that what we're going to see are the same outcomes that we've seen at Shiba, because again, there's a trajectory for every year and where they need to be. And within five to six years, they will all show a very strong return on investment and the economic growth that ARK at Shiba was able to achieve. When we talk about innovation, and especially given that you have a global overview of how different markets are doing, I do want to pick your brain and insights into your opinion

[00:31:58] and what you know about the Chinese market. I will have a speaker that works a lot there on the show soon, but all we know is that it seems that they are moving with light speed. AI doctors are something that is becoming common there. So what do you know about that market? What do you think is still possible in the West that we are not taking advantage of just yet? Yeah, first of all,

[00:32:27] I have to say I'm not a big expert on the Chinese market. We don't have an ARK center in China. Is it an ambition to have one? We're open to discuss, but so far there are differences that, and I would say regulation is one, IP policy and things like that that are very critical for ARK. And the IP, for example, is extremely important for ARK because of the spin-offs and the commercialization. And so we need to see, of course, how that matches up with the regulation in China. But I would say in general,

[00:32:56] when we talk about AI and you referenced AI doctors and so on, I think that one is we know China has the capacity to move very quickly on technology. We've seen it happens with other industries, not just in healthcare. If you come to Israel, you'll see every second car is a Chinese electric vehicle. So I think that's a tribute to their success in being able to move very quickly into those markets. And I think we'll see that in healthcare as well. My challenge is, again, with the regulation, and it's common to know that regulation in China

[00:33:25] is not as robust. If we talk about Europe being a regulation superpower, I think the US and Israel are pretty much in the center of that scale. And then China being on the other side of that scale, I think we need to get regulation right. It can't be too light. It can't be too restrictive. It needs to be in the right approach. And I think what we're seeing in China is that the regulation allows AI technology to move very quickly, but I'm not sure how much of that will be applicable

[00:33:54] as we try to take it to other countries with more strict regulations. Even the US and Israel, again, not just obviously Europe with much stricter regulation. So I think that's still something to watch out for and with the threats that AI is also posing and we're exposed to it more pronouncedly over the last couple of days with the big AI companies that are bringing this forward, rightly. I think that's something to watch and make sure that we're not overshooting and making AI a concern for patient safety.

[00:34:24] Absolutely. We are entering the final part of the discussion, so I guess my last question is just going to be what's on your roadmap for 2027? Where are the ambitions and hopes that you have in terms of the future development? So it's a good question because we're entering a substantial change in ARK Global, which is fueled mostly by the very large interest. I mentioned a couple of new countries we're now entering and ARK is substantially growing

[00:34:54] and in 2027 we're going to build a much larger platform that will allow us to scale up very quickly. We're talking about 10x scale-up compared to 2026 and that requires obviously quite a bit of infrastructure that we're now very busy building. We have an ARK Summit coming up next month, 22nd of October in Tel Aviv, where we're going to highlight for the first time and showcase the new strategy that ARK has put forward to allow this large scale-up, the 10x that I was mentioning. And we're going to put a bigger emphasis on AI.

[00:35:23] AI has been there from the start, from 2017, before generative AI came into all of our lives. But with generative AI and opportunities that offers to healthcare and the leadership position that ARK has taken with AI globally, that's going to be put front and center and we're going to double down on efforts on how to turn hospitals to be AI native or AI mature. Shiba has a whole plan to do that by 2030. We're tracking our progress. We have a maturation score which we're constantly tracking and to see where we are

[00:35:53] and where do we need to push forward to be on course to get to the ultimate goal by 2030. And we're going to be doing similarly with our other ARK centers around the world to get them all to push towards that AI maturation that we're all looking to achieve in healthcare. You've been listening to Faces of Digital Health, a proud member of the Health Podcast Network. If you enjoyed the show, do leave a rating or a review wherever you get your podcasts, subscribe to the show

[00:36:22] or follow us on LinkedIn. Additionally, check out our newsletter. You can find it at fodh.substack.com That's fodh.substack.com Stay tuned!