Exciting things are happening at Becker's Healthcare. Stay ahead of industry trends with the new Becker's CFO plus Revenue Cycle podcast, your go to source for insights from top healthcare finance leaders. Tune in wherever you get your podcasts. And don't miss the tenth annual Health IT plus Digital Health plus RCM conference, happening September 30 to 10/03/2025 in Chicago. Join thousands of executives, engage with industry leaders, and explore the future of health care innovation. Learn more about our upcoming events at beckershospitalreview.com. See you there. This is Laura Dirdle with the Becker's Healthcare podcast. I'm thrilled today to be joined by doctor Chen Kai Kao, chief medical information officer at UChicago Medicine. Kai, it's a pleasure to have you on the podcast today. Thank you so much, Laura. It was nice meeting you, you know, virtually. So thanks for having me. Absolutely. Absolutely. Well, I I'm excited for our conversation because I know you're doing some really cool things at UChicago Medicine, and certainly, we'll look forward to learning more about those, when you speak at our health IT digital health revenue cycle event later this year. But for our conversation here, before we begin, I was wondering, could you tell us a little bit more about UChicago Medicine and what makes it unique? Of course. So the University of Chicago Medicine health system is, you know, in Illinois, obviously, centered in the Hyde Park area in Chicago, but we also have satellite hospitals at Southwest Suburbs and also Northwest Indiana. We are a five hospital system, about 1,300 beds, and spread again across the State of Illinois and Indiana. I think I would say one thing unique in our institution is, like many others, we are very committed to patient care, but we do serve a relatively underserved population here. So there was one New York Times article citing the expectancy in the zip codes that we serve nearby was thirty years less than the zip codes in Downtown Chicago. So you speak to a lot of the resource differences, the digital literacy, digital equity differences and just all in all, I think signified the the challenges we we should face when we, you know, try to serve this community. Got it. That's helpful to know. And, you know, really an important population you serve as you mentioned, those who may not have access to care otherwise, especially, and then, truly, just a great academic health system, resource for the Hyde Park community. Now I'm curious. When you look back in the last year or so, what are the accomplishments that you're most proud of? Yeah. I think over the years, we we have, you know, have I think done a few things I think, you know, we feel very proud of. In my portfolio, I would say one thing that's relevant to what I just mentioned about serving the community, you know, in our area will be a hospital home program. So it's it's basically a program providing acute hospital level care in the patient's home. And we supply, obviously, you know, staff and resources like medications, meals, etcetera to the patient's home. We can do imaging and EKGs and other studies at home as well. And but like I mentioned, I think the geography that we serve posed a lot of challenges both from the patient's readiness to receive the type of services and also the recruitment for nurses who is willing to travel into these areas. But we've been fortunate to have a very strong team where we are really eager to serve our patients. We reach out to them passionately and introducing the program. And I'm proud to say that all the patients go through the program is very happy with the program. They really feel like this allowed them to be able to recover in their own home, you know, while, you know, really just enjoy the, you know, all the benefit being being at home, surrounded by, you know, your, loved ones and also be able to do the stuff they usually do. You know, watch the TV show you always watch, read the books they usually do while you're receiving all the care that's equivalent to the inpatient level care. And we are seeing, you know, so huge patient satisfaction, a lower readmission rate, and that's just, you know, overall very fulfilling. There's also a couple of other informatics related projects, that we implemented. One thing we'll highlight is called auto diagnosis. This is a project actually spearheaded by one of our physician builder, Doctor. Medcel Ocelli, really sort of building these auto diagnosis within the node templates to help reduce physician documentation burden. I mean, as we all get recognized, the documentation is a huge burden for the physician, not necessarily what we signed up for medical school for, but obviously it's an important task that we have to do every day. So the the project is basically allowing us to be able to help physician capture a company made diagnosis directly within their note templates and in the meantime reducing the core inquiries that people will be getting down the road. So it really helped reduce the burden and actually helped to make our notes better. So we since they have published the work, we actually soon to have, additional publications on this work coming up as well. We have shared that in a couple of different epic conferences, and actually was highlighted, I think, in one of the Becker newsletter before. And we have been working with some of the other institution who are interested in implementing the same, same sort of technology in their system as well. Last but not least, so clinical decision support is a big chunk of my portfolio. So we've been using decision support to help capture some of the stewardship requirements. So for example, last year there was a major blood culture shortage nationwide. So we're able to use DGN support to help reduce the blood culture bottle usage very significantly. And now we are spending to do more for daily labs and any other things to reduce these unnecessary labs, which will be important to solve to reduce the cost for the hospital. Also in the meantime, it's also reducing unnecessary blood draws or reduced ultraglionic anemia and obviously patient experience will be better without these additional plastics as well. So these are things I would just you know, maybe call out particularly, but there's really a lot going on, right now. That's great to hear. And, you know, really cool to, have the ability to leverage technology in ways that have a meaningful impact on patient care as well as the workflows on the clinical side. I I know reducing the burden on, clinicians, doctors, and nurses especially, is truly a mission for so many organizations overall. So that those are both great examples to hear about. I'm curious, looking ahead over the next twelve months or so, where do you see some of the big biggest growth opportunities for you and your teams? Yeah. So, with the joint partnership with, IT, marketing and informatics and data analytics, we formed what we call the Center for Digital Transformation. This is a center we established and to really help us adapt to the a lot of the new trend in the healthcare right now. So obviously lots of work about digital transformation about how we actually deploy this digital health and AI technology in the clinical care and really improve both the provider patient experience and improve the efficiency of the health system. So there's been a lot of initiatives sort of under the umbrella for this, what we call the CDP, Center for Digital Transformation. And we're also looking at how do we review the roadmap of the digital tools we are thinking about that can help bridge the gap and the pinpoint that we have in the system. We are looking at establishing AI governance for the increasing number of AI usage, right, almost in every industry. We're also looking at how we do a better job in terms of intaking some of these solutions. There's always lots of DG Health startups out there and they probably download a number in the last few years. So how do we making sure we have a process where we can broadly taking those in and in the meantime be able to evaluate them fairly and really factor into decisions about what's the best really to help solve the problems that we have in our health systems, what's the best model to work with the vendor to co develop some of these products, because there there's a lot of new technology and none of them are mature yet. In the meantime, we also have some homegrown resources that we can build things as well. So thinking about how we build, when do we build, when do we buy is also the other thing we want to sort of factor into this new process of that innovation intake. So that's I think that's a really exciting opportunity for our team to think about how we can help institution prioritize these opportunities and really help bridge the gap and make a true impact, on clinical care. I love that. I I think it's so critical, as you mentioned, to have, you know, the right evaluation process to bring in technologies because there are so much exciting things out there and new possibilities, especially with AI, and automation. But, you know, not everything is gonna be beneficial. And so being able to stay on track and really understand, what makes the most sense is so important. I'm curious. You mentioned, you know, getting some of the the governance processes in place, especially for AI use. Could you talk a little bit more about that and what those conversations have been like at UChicago Medicine? Yeah. So that's a great question regarding the AI governance. So maybe to start with, you know, thinking about why we need that. So, right, there's a lot of AI companies out there. And almost like when I go to a conference, it's like almost every company have AI tagged in their sort of product description. It's almost as if this is something that's universally used right now. But when we look at these AI solutions, first is, is it really addressing a critical problem that we have? And so secondly, is that problem really need to be solved by AI? So that will be an important piece that we need to tease out when we think about the intake, think about evaluating these solutions. But after we sort of decide, all right, there is a true pain point and problem we're trying to solve And we do need a solution in a place. And AI seem to be a potentially a good solution to solve the problem. We still would like to take a very thoughtful process in terms of validating is AI really delivering what it's supposed to do. So accuracy, completeness, right, all these type of evaluation about the effectiveness of AI. There's also a lot of risk assessments, especially nowadays with a lot of cyber security risk. So making sure we are reviewing this AI in a fair way to adjust assist their to assess their risk level based on whether the use of AI is susceptible, not susceptible and high risk versus low risk. And also in the meantime making sure they meet our security, privacy and asset standards are sort of an important piece in the intake of process as well. And last but not least, let's say something really works well in past all the risk assessments that we do, we still want to have a process to continue to monitor this AI moving forward to making sure they still perform as the same way we thought it would be in the beginning. Health system is constantly changing. So all these changes regardless of spending the new units, building a new hospital, adding additional outpatient site, we all potentially can change how AI model works. We want to be able to have some light of sight into that too. So these are the things we thought about having a strong AI governance. And again, the people who will be overseeing the AI governance will be multidisciplinary. So know, people with, you know, data science, you know, analytics backgrounds, informatics, ITs, and, you know, on security, privacy, and other stakeholders will also be involved as well. Got it. That's helpful to to know. Thank you so much for digging a little bit deeper in there. Now it really seems like a lot of opportunities out there, a lot of cool things that are happening, but I can imagine there are challenges as well. What are some of those challenges or roadblocks that you're anticipating in the coming year or so? Yeah. We are taking a very thoughtful way when we deploy this technology. So, you know, first, like we talk about, the patient community that we serve. Right? It's not exactly the most digitally, savvy population. So making sure every time we roll out something, we'll always have the digital equity things in mind that we want to make sure the things we deploy are benefiting all the patient population, maybe not all through the same venue, but always making sure there's a way to engage, making sure there's a way to help them navigate and benefit from all the new solution we deploy throughout the health systems. So I think that all the work around digital equity and try to overcome all the challenges from digital device, something I think we have seen since the pandemic and also something we're still compelled to continue to improve through our processes. And now with AI, right, there's even more thing to think about around the around like the biases, based on different gender, race, populations, etcetera, like how does AI use being properly governed to making sure that we are free of these biases or ethical concerns? It will be the other challenge we need to constantly test out and just be mindful of in our processes. So I would say I wouldn't say that's necessarily a challenge. Instead, I think these are all good questions that we have been solving over the years before you even have this technology. But really with all the tools in mind, how can we even use this tool in the right way to actually mitigate some of these gaps and make things better, not the other way around? It's just something we need to constantly be careful about and margin when we march forward. Got it. That's helpful to know. And and certainly, as you can imagine oh, I know a lot of goes into trying to figure out those AI models and, how you can do that in an equitable way, especially given how quickly the technology is evolving and changing. Yeah. Exactly. I mean, it's it's, rapid moving world right now. So, it's, again, both a challenge, but in the meantime, any excitement. I feel actually very fortunate to, live in this era where it's witnessed, like, all the Internet growth and now AI growth, and it's just gonna change a lot of things, which is super exciting. Absolutely. That's fantastic to hear. It is a great time to be in health care for sure. Now I'm curious from your perspective, given some of the, big, things that we're excited about as well as, you know, challenges that we just mentioned, What is the number one thing that you're doing right now to set UChicago Medicine up for long term success? Yeah. I will talk about one project I'm working on that's actually related to what we talk about. So we talk a lot about the use of AI is growing and there's more companies, there's more use cases here and there that's coming up as we speak. And we also talk about I mean, there's a lot of saying around people with the AI may replace the people who don't know how to use AI. And maybe in the future, there will be, you know, even more, AI and automation, right, in in the work. So I think, absolutely, what we want to do is making sure we elevate the AI literacy in our institution. Right? We want to train people to know how to make the best use of AI. AI is not perfect. So training them to understand what's the posting counts, what's the limitation, what does it mean by AI hallucinates. And but in the meantime with all of that, being able to use leveraging AI as most most likely your inexperienced intern. Someone is on your team. It's almost like your digital worker, but who is inexperienced, who is new to the team. So how do you train the AI to actually work with you to actually get things done more efficiently? That that will be sort of the goal. We we hoping that we, convey to our sort of colleagues. So one thing I'm working on is actually building up generative AI platform that will be HIPAA compliant and secure for internal use, which will allow us, meaning our staff and health care provider being able to upload certain information about PHEIs and be able to use that to do things, for example, like drafting some of the messages that we are about to send out in different formats, in different languages, in different type of literacy level, which allowed them to help improve some of this patient communication. Or for example, we are developing some of the modules to help drafting denial letters of appeals or for example answering some questions based on our policies and procedures. So while we are standing that platform up hopefully in the next few months, it's really coming up soon, we also want to pair that with staff communication, education about how you should use AI, right? How to prompt, what's the AI governance we've been talking about so far? And when you have questions, where do you reach out? And how do you use the tool better to your for your purposes to to boost your efficiency in every area. So that's something I think really exciting, and I think I'm gonna spend quite some time really to help stand it up and thinking about creating different use cases and, and training people to to make use of it. But what we do, I think it's gonna be really, improving a lot of efficiency issues that we have and really allowing people to really do things that are probably a license. Right? It's like you let AI to do a lot of these repetitive or something that's, you know, less, less challenging per se in terms of the complexity or originality. But, you know, reserving all your energy on something that really requires all these, you know, things, and the AI just help you out to save time. So, that's something I think really exciting, that I'm really working on right now that I think really would set our institution, at a really good start as we continue to, spend and, deploy additional AI solutions. That makes a lot of sense. You know, it's really, helpful to understand from a leadership context and perspective, how you're thinking about these things and really, really putting yourself in a strong position to continue to, advance this technology and bring it forward in a meaningful way. Kai, thank you so much for joining us on the podcast today. This has been such a fun conversation, and I look forward to connecting with you again soon. Thank you so much, Laura. And likewise here, meeting you, and, have a good day.