AI has proven that it can save time, improve outcomes, and free clinicians to focus on patients, not processes — but most of those healthcare gains have come at the point of care, in individual departments, one tool at a time. The next frontier is building the platform that makes AI foundational across the entire system, so insights compound rather than accumulate in silos. In this intimate dinner in partnership with Philips, we will hear from healthcare leaders about what it takes to get there: the governance frameworks, the workflow integration, and the organizational conditions that turn AI from a collection of promising tools into the infrastructure that powers better care for more people.
Speakers:
Kevin Mahoney, Chief Executive Officer University of Pennsylvania Health System
Jeff DiLullo, Chief Region Leader, North America, Philips
Brian Donley, President & CEO, NewYork-Presbyterian

From Tools to Platform: AI's Next Frontier in Healthcare

Conferences

First of all, thank you very much for joining us on, um, this special night. I'm wearing one half of the colors that, uh, I think a lot of New Yorkers have tonight. I'm Diane Brady, executive editorial director at Fortune. Um, first I want to thank Phillips. Uh, for, uh, this is, um, this is my favorite dinner, and I know, I know if you could say, oh, she always says that, but it actually is, this is our 3rd dinner together, and I, what I love as a journalist is it's so interesting the conversations up here but the conversations around the table because I talk, we talk about AI all the time. I do think the use cases in healthcare and in hospital systems are fascinating and the changes that. We've seen just in the space of a year so I'm looking forward to a great conversation. Let me, um, first of all start we're gonna let these gentlemen get seated, but, um, just to let you know everything up here I'm gonna report on. I do a daily newsletter, um, and so that part feel free to heckle and it might get in the story, but everything around the table's Chatham House, so that's just to encourage a free flow of conversation and let me now turn fresh from his daughter's wedding. To, uh, Jeff Delulo, who is executive vice president, chief region leader for Phillips North America, and, um, thanks, and gentlemen, you can get seated and let Jeff give some opening remarks. My opening remarks are very simple. Thank you for being here, Shez. Thank you for being a great partner as we, uh, try to evangelize what we're doing, uh, for the to help you in the industry, but the power of the, the meeting will not be in this panel. The power of tonight's dinner will be at the conversation at the table. So let's get started. Excellent. Well, let, I feel I should have immediately to my left here will be Kevin Mahoney, chief executive officer of the University of Pennsylvania Health System. Kevin, good to see you. So I will confess that I'm a 76ers fan, so getting off of Penny. And everybody wearing blue killed me, killed me, hurt, you know what, it, it, it only happened in Phillips, but it only happens once in a generation. So you'll be, you'll be good on that, um, and then, uh, two generations, and Doctor Brian Donnelly, president and CEO of New York Press. Cafeterion, um, and of course Jeff you together I think you both represent, um, obviously incredible innovation. Let's just get straight to it. I wanna start, um, well, let me, if you don't mind, Jeff, I'm gonna start with you just quickly. I'd like you to level set the, um, if you don't mind the future health index. I was fascinated just to see the progress that has been made and then I wanna go to you two gentlemen to talk about what you're seeing. What have you seen this time last year feels like it's a very different discussion. So if you don't mind just sharing some tidbits. Well, yeah, thanks Adam, and uh while we were sitting here last year talking about the last year's report, it was really a step forward in trust in AI, and it was uh uh we talked about the the difference between practitioners who were gaining trust in AI and how the general population quite, quite didn't have it, and we talked about the. The need for physicians to be the vehicle by which they build confidence. This year, massive difference where we're talking about true adoption and what we call the AI dividend now because we're actually starting to see the return. We're seeing the return in the way people are adopting it into clinical workflow. We're seeing the return in terms of more patients to be seen and more patient time. We're seeing a return in terms of better diagnostic quality and we're seeing returns in terms of. Health and well-being of a clinical work staff, which is a major undercurrent of the problem in healthcare delivery today, is we don't have enough and we're burning people out, and I know you all deal with that every day. Well, and let's take it down to the ground. What are you seeing? Well, let me first say I'm a much newer CEO than Kevin is, so I would never say that I'm not a Knicks fan. But I spent 25 years in Cleveland, Ohio, and I wasn't really happy in the last series. I mean, I would, I also would agree with Jeff though, seriously, I'm, uh, excited to be here actually for the table discussion and actually I'm here, uh, to learn, uh, from all of you. You know, being a new CEO, I'm seeing the same things, uh, that I think we're seeing across US healthcare. I did spend 5 years in London before I came to New York, and I'll tell you it's not just a US healthcare problem, it's actually an international problem. And our 3 big problems that we're working on our workforce, workforce strategy. You allude to that cost has to be a consideration. No one really wants to make that their main point. It has to be if we're going to have a sustainable mission in healthcare, specifically in nonprofit healthcare, and I think the third big problem we're working on is access. There's a lot of problems we're working on. But we're really trying to focus, uh, on how AI can help us with some major, major problems, uh, and getting to a point where we see the ROI on specific problems. Do you want to add to that? We were talking a little bit at the table. Talk about where you are and what's different from that. No, no, sure, I, so I will confess that I'm an old man. And I've been through this a lot. In my first job, Medicare was still paying its costs. And, and, and then DRGs came on. This is the end of American medicine as we know it. We're not in an AI moment. Like everybody keeps saying AI is gonna fix that. A, this is a moment for AI. We're in a moment where America can't afford its healthcare, and we need to use every tool we can, but if we think it's just. For open AI and F, uh, you know, people to make money on it, that's not what it's about. It's truly changing the way we care for people. Better outcomes and a lower cost. Can you talk a bit about, um, I think I absolutely agree, and I promise if I mention open AI or anthropic, you can, you, I'll put a little tip jar there. I put, but, um, I would love to hear about where is it making a difference, um, then in terms of addressing those needs you talk about labor cost, patient care delivery. Oh, look, uh, the obvious one is ambient listening. 15% reduction in time the doctors spent typing, 17% reduction in pajama time. That's all helping with the burnout. It's helping, it's helping remarkably with getting the data. We put up our, our new building, um, several years ago and we had a retreat on the, What would be the ideal patient experience? Well, wouldn't it be great if you had a cappuccino machine? Wouldn't it be great if we had sofas instead of chairs. You know, it'd be great when you walked in the exam room, the doctor knew who you were, why you were there, and everything in your history, and AI can do. Yeah. And, and it'll make the, the visit much more productive, uh, and, and, and that'll lead to reduced costs. You know, um, one of the things, Brian, last week I was in, uh, California and they're already creating new positions. You know, one company created 13 new positions around AI. I'd love to know, um, especially as a new CEO, are you creating, are you reorganizing in any way to actually try to lean into this? Are you creating new positions, hiring differently? Yeah, I, I would strongly support Kevin's comments. That AI is not an innovation strategy. It's not an IT strategy. It has to be an enterprise strategy, as you say that Kevin, about like you saw before where it's gonna be the end of medicine, you know, this has been going on. What we've been doing is going on for thousands of years. It's not going away to your point. You know what we're doing right now is we see and actually two of our outstanding people I know for sure here, but we're seeing in pockets where we're doing this right now, label the two, yeah, Serena Fay from Wild Cornell, thank you both, uh, for being here. Um, what we're seeing, uh, uh, and what we're focusing on is how we actually improve our AI literacy across the organization and all 45,000 people. And then we want to take the different tools and we've got to figure out how we get them on the platform and get them across the system and how they help the care model that we're designing, not that we change the care model to the AI tool, but we use the AI tools to help change our care model to develop a sustainable way of delivering care, of continuing research, because you know what we do phenomenally in this country is research and discovery and then certainly education. So we're talking about some of the pain points and where we are in this moment. I'm gonna start with you. What, what is, do you see as the pain point in getting to where you wanna go? No, I, I, I think it's too. I'm gonna build on what you said. I have more people coming into my office. I want to be the AI chief. You know, I, I, and no, like you're not gonna be the AI, well, the real chief AI officer, please stand up that, that there's a groundswell of I need positions, and, and that's just gonna be counter to what I'm trying to, uh, achieve. I think the real breakthrough is not going to be in the administrative side. We talk about that a lot. I think the real breakthrough would be on the clinical side. So our our our pathologists have tissue lab cortex. We were talking a little bit with my colleague from, uh, Sloan Kettering. They, they're able to go through the biobank. Epic spectra all all the data quickly and find out that biomarkers that are pointing to a therapeutic response, right? You know, my father-in-law was dying from, uh, uh, collective duct cancer and the pathologist kept coming up with a better reading and the pathologist, or I'm sorry, the oncologist said to me it doesn't matter. I only have one tool. So you, you may have a more precise definition of what your dad's dying from, but we don't have any more tools. What, what lab cortex does using all that information, working with. Pharmaceutical, can we come up with new methods of, of treating, uh, the disease that'll have, and we were talking about ResMed and the standing, uh, ovation at, um, ASCO. Hopefully those will happen faster, faster and faster and quicker and. That's because of the advances in cancer research, right? The advances in, uh, the data collection. We have more data. As an industry, you could check a stick out. And we all talk about we've got to use it better. Gathering it at the patient level. And, and really getting in the genetic makeup. We, you can't do that fast enough, but AI, what large language models allow us to do that. Do you see a friction point? I'm gonna go to you, Jeff. Yeah, certainly. I think a big friction point is trust of, uh, clinicians, you know. And if the trust from the clinicians is there, and I think we have to continue, uh, to work on that. I think we have to be really, really hard on these tools to make sure they measure up to that and be careful of how fast we bring them in, knowing that you can't be too slow with it. I think trust is a really big, uh, point with it. go ahead, yeah, so, um. I know this is being taped and I'll probably get charged 4x from Epic for saying this. The number one pension point in my institution is Epic. Because people are inventing, innovating, coming up with the legacy system in place. I, I have one group, mostly in IT, Epic now, Epic forever, that an integrated solution is always better. And then I have physicians and other people. Let's innovate and come up with a better solution. But then you can't put it inside the Epic system, so, uh, it, it is continuing to be a major friction point for us because I have a lot of people wait. Let's just wait for Epic to come up with the tools. Like why are we out in front? Let's just wait and, and I that. That's in my top It's good to know. I, I, what would you say? Oh, I'm gonna take it a slightly different lens as a technology provider. What we're seeing is when they're, when, when the AI tooling comes alongside the clinical workflow and really embeds in the workflow, not the other way around, where you make the workflow meet the technology, we see high adoption. A third of folks have said they're, you know, you, you can read the report, but a third of folks have said I can see 5 more patients a week. Imagine that times hundreds of thousands of clinicians. Uh, people are getting hours and weeks of time back per year because of dictation and ambient and other things, and that's just scratching the surface. So imagine the productivity that we could create for an industry if we just do this effectively. But where I see friction in a lot of point solutions today from a technology lens is, how do you. Take that and learn from it, but no, that's not actual workflow. You really have to think bigger. You have to think enterprise. You have to think systemless platforming how health systems that are winning, winning the early battles here are thinking in terms of a system and how to integrate these into a platform of care along a patient longitudinal journey or service line journey. And they take taking a big picture and that's where we want to play as a as a technology provider because our view is it's always about the end to end workflow. It's not about the quality of a piece of data that you can get to diagnose and I think and productivity is very important in how we scale that, but I think what's also really important will help drive trust also and that to me this gets to the whole workforce problem we're having in healthcare is we've eroded out the meaning and purpose of the work. And so the meaning and the purpose of the work, which I said before has been here for thousands of years, is one person sitting with another at their greatest time of need they've probably ever had. And so I think what we have to do with these tools also is constantly focus how we can expand that time where an exchange of empathy happens between a patient and a provider, and I think it's important that the ROI is also thought in that way. What we look at from clinicians. we look at 4 phases, it's data collection, which is taking history, it's analyzing that data, and then it's interpreting what the analysis was and then it's counseling the patient. And what we find, I think, is that most clinicians are fine with getting rid of history-taking data collection. Analysis can clearly be done better by AI and give me more time for sitting with a patient for interpretation of the results and then counseling. Anything you'd want to add before we I do. One more pain point, which is regulation, whether it's from the state or Medicare and billing. We're putting in ambiance and the number one friction point is with our billing compliance officer. Who said you're going to gather so much more data that the two is going to become three, threes will become fours, fours will become fives, and you're going to get flagged. And, um, our, our regulations haven't kept up with, uh, you know, where, where we're at. Brian's an orthopedic surgeon. He knows when somebody comes in pretty much what, what they need. If they put that into medical chat, GPT, you could probably get the labs, the, the imaging you need, except it has to be ordered by a doctor. Um-hum. And you know, in Pennsylvania, the governor is putting in guardrails that AI can't do, do the ordering and so I, I think regulation getting regulations out of the 1970s into um the current environment will be a friction point that's gonna hold us back. And I'm sorry, I just have to add Kevin, Kevin always reminds more and more things. The other thing from a friction point is the pace of governance. And where governance is with innovation and I, and I think that's a really big friction point for us and it seems like it is for others. Well, we've seen incredible advances in, in the software certainly from where I sit and, and to your point, um, that hasn't kept up in most industries. Jeff, I wanna go to you again. What are you seeing or hearing in terms of, um, take us a little bit around the corner because I know we're gonna take this to the table, but where are you seeing the most traction with the people you speak to? Is it, I mean, because there doesn't seem to be this efficiency, there's the augmentation, there's the cognitive burden. I really like what Brian said people join this profession to sit in front of a human being and help them have a healthier life. That's what they, that's what they do. The fact that we can be more productive, we'll never have enough staff, we'll never have enough radiologists, we'll never have enough pathologists, it just will not be the case. So anything we can do to bridge that gap helps people spend more time either with more patients or spend more time with the patients in front of them to actually interact with them, look at their nonverbals, look at their body language, connect with them, and really have a diagnostic you can't get on a on a scan. And I think like what we're seeing, and I love the New York area because I honestly as a as a cohort I think this is one of the more progressive areas where people are really pushing the envelope on AI movement. We're going what I'm excited about is that we're moving away from the dialogue of point solutions and. Am I building some trust with pilots that don't go anywhere? 2, I'm actually seeing adoption because it's being designed around real workflow like end end workflow, and that's going to drive more impact, and impact begets impact, and I, I really, I feel like the flywheel is starting. That's exciting. It, it takes, I love how you talked about data layer, but keep in mind the whole object is to have a physician in front of a human being helping them be a healthier human being. And if that's where our design point is, we, we, uh, we have a lot of progress in the last year. Before we sit down, final thoughts. Yeah. So, I want us to be careful of the rhetoric. Um-hum. So, um, Doctor Zeke Emanuel, who, who's a friend of mine, he's always on TV. Uh, he works down at Penn and, Don't go into radiology. Like AI is going to replace radiologists. I had, I had another idea, which is let radiologists be doctors. OK. They see more lung nodules than anybody, but the way it is, they read it, it goes back to the thoracic surgeon, they schedule an appointment. So, I, I think we have to, don't fall prey to the rhetoric. It's not going to fix everything. Physicians are still going to be needed. But they're gonna have to learn new tools, but we're not. We're not throwing out the, the current healthcare system, but I just worry that everyone's getting a little carried away. If you've seen the New York Times today, University of, uh, California system. Um-hum. Went, went to all AI, and the editorial today is it's tearing it apart. And you know they had a $16.9 million investment with OpenAI and the faculty are like we didn't get a raise, but you got $16.9 million so I think we all just have to. Figure out how to use it in in our system, not change our system for AI. I mean, I probably on a similar thing that Kevin says, you know, first of all, appreciation to all of you because, you know, you're where a lot of our whole discovery is coming from. So thank you, uh, for that. AI has to continue to focus on how it enables our for us 45,000 people. To be better at what they do, they come to work every day and they wanna be better and better at what they do and I think AI the opportunity is for them to be better at what they do. It's not to replace people for what they do. Last word to you before we sit down, Jeff. Uh, human-centered AI enabled healthcare, and I love partnering with the health systems in this room because that's, we're all chasing the same thing. I can't wait to hear the discussion at the table. Great, thank you very much. Please join me in thanking our guests up here. We're gonna go to you now.