HLTH 2023 is in full swing. Here's what I saw from the floor.
Today in health. It, what I saw at the health 2023 conference. My name is bill Russell. I'm a former CIO for a 16 hospital system. And creator of this week health. Instead of channels and events. Dedicated to transforming healthcare. One connection at a time. We want to thank our show sponsors. We're investigating, developing the next generation of health leaders. Short test artist site parlay it's certified health, notable and service. Now check them out at this week. Health. Dot com slash today. As you know, we set a goal to raise. $50,000 this year for childhood cancer. In a partnership with Alex's lemonade stand and we are up over $55,000. In fact, We've got another $5,000 pledge today. , and, , that's exciting. That takes us up over $60,000. We ask you to join us. We'd like to plow through that number. Hit our website, top writing and calm. You're going to see a logo from the lemonade. Stand, click on that to give today. We believe in the generosity of our community and we thank you in advance. , one last thing. Share this podcast with a friend or colleague use it as a foundation for daily or weekly discussions on topics that are relevant to you and the industry. They can subscribe wherever you listen to podcasts. All right. Attended the health 2023 conference out here in Vegas. And. It was interesting. I would say there was a ton of announcements. There was a lot of players here. , I will say that the healthcare providers. , the statistics I heard. We're essentially. I don't know, 60% vendors. 30%. , investors. 10% providers and that felt about right to me. And it wasn't necessarily CEO's walking around. Although I did run into a couple of them. There were, , Obviously the investment partners. For the health systems that have investment funds, we're here as well. And, , innovation. Teams we're here. , looking at, , the various solutions. Cause there was a ton of solutions here. Bottom line, but one of the things I heard consistently from the. , Vendors who the vendor partners who had booths at this conference where the buyers were not at this conference, that does not mean that it's not a valuable conference. It is a valuable conference. There's two things that really happened at this conference. One is you get to hang out with investors and those are current investors or past investors. And you get to give them an update. It's a place where they all congregate and you can, , seek out new money as well as talk to the existing money that you have. The second thing is partnerships. So vendor partners are looking for strategic partnerships that help them to go deeper within healthcare systems. And there are a lot of those conversations. Happening here. But if your intention is to get in front of buyers, that really doesn't happen here. I know they, they have a lot of programs and whatnot, and they, they. To, to try to bring buyers. And sellers together, but that is probably not this conference. I will say in contrast five, is that conference. Because it has partnered with chime. You'll have a fair number of buyers at that conference. Now, I don't know. , the quality of those conversations, but regardless buyers and the vendor partners are there. So if that's what you're looking for out of a conference, that's going to be a better conference for you than this one would be. , with that being said, what were the, the general themes we did? , I think we did about 10 again, we cater to healthcare providers. We could have had conversations with pharma. We could add direct to consumer. There's a ton of med devices here. , you know, there was two toilet. , companies that were doing. , passive monitoring. Can, you know, when you sit down, you essentially. , take readings and, you know, in a passive form, they are collecting a lot of information, a lot of new devices and, , you know, remote patient monitoring type. , devices. , specialty type devices and whatnot. , You know, some data things going on, some security things going on. But for the most part, the, the theme. Had to be AI. Just across the board. We had a great conversation with a sheesh, a treasure. And they, , UC Davis and the UC system. Has launched a program called valid AI. Which is designed to share insights and learnings of our progress around AI so that health systems can progress faster. So we share. Our successes, our shortcomings, we share. , our research and those kinds of things. Now that doesn't mean that we still can't, , pull out our intellectual property and, , and, , Establish a market for some of the things that are specific to our health system. But the, the approach to AI and our findings and implementation and how we gain adoption and how we provide transparency. And around the algorithms and transparency around the bias and those kinds of things that the goal of validate, I used to share those things. There were 30. , health systems and payers that have signed up, and they're a part of that. There's going to be a second part. That is a technology partners who are also going to. , head down that path. So again, very interesting conversation. , Trying to think who else we talked to there? You know, for the most part, as we've talked AI. With, , with the various organizations that were here and looking at the technology. There's a general sense that we are at a moment in healthcare. That AI. Along with the underlying infrastructure and the technology that exists around it. Has arrived. That doesn't mean we're ready to do. Full scale, implement this across the board, but it means that we're ready. To implement this. In ways. Now we still have to do the research. We still have to validate our findings. We still have to do pure research. Our peer reviewed. Studies on how this AI is impacting healthcare. And the quality of the data and, and that is delivering, , to the providers at the point of care. But all those things being said, It's ready. There. There the technology. To enable the large language models and the, , the other. AI that we've been in the machine learning we've been using for years, the OCR, the NLP and whatnot. They're there. They're available. They're available to, , organizations who want to build out their own models. They're available to these partners for sure who have been integrating them. Into their models and they're looking at making things easier. Obviously the large language models have a natural language front end, which makes, , the ability to interact with the computer. Different. Right. This is what we've always dreamed of. This is the star Trek moment. Where we can literally talk to a computer and say, computer, give me the F the readings of this individual. The last four times they were in the office. And it's going to be able to go out there, query all of our structured and unstructured data and bring that information back. And that's the other paradigm. That we're seeing more and more. Which is essentially we're going away from the Google search library model, where you ask it a question and it comes back with 20 documents and says, Hey, pick the pick your favorite document. The answer is probably in one of these 20. Two. Essentially these, these new models. Again, we have to look at accuracy and whatnot, but these new models are coming back with answers. And in the models, we are developing for healthcare, their answers with, with references, to where they found the data. So you can find the answer, you can click or just say, elaborate on where you found that answer and it'll show you the PDF or the unstructured data that it came in on. And those kinds of things. It's pervasive. We saw AI N everything. From security to small devices to, , applications that are now on your mobile phone to. ,
I mean, you name it data. It's definitely being applied to data. , we spent some time with Microsoft. , early on in the week and looked at their Microsoft fabric. Solution heard from a health system that was implementing it, a couple of health systems that were implementing it. , we heard from nuance. , about the, the, , , co-pilot. , solution Zack's copilot solution that, , is going to allow them, , essentially drive the cost. Of taking the nuanced solution throughout your, the dragon experience. Across your enterprise and drive it down. By as much as a third or more. And so you're going to be able to implement that across more seats, because for the same amount of money that you were paying before, you're going to be able to get more licenses. Now, what we were hearing is again, that solution is ready for outpatient. , yeah, outpatient, but for inpatient, they're still a little bit more coding to do. And obviously there's just more complexities, more specialties, more complexity. Associated with that. So, That's going to take a little bit more time. At the end of the day, AI is coming into everything and the. The question becomes, where, where are we at with our readiness? Are we ready to implement? Do we have a strategy? Have we looked in it? , again, I come back to, and I've been talking about this a lot over the last couple of weeks. So forgive me if you've heard this before. There's a couple ways you can go. The easy button is. Let your vendors implement it. And pull it in through existing contracts. That is one of the ways to do it. There's a, , the, the hard button is essentially go out, hire the team, start building out your own custom LLMs and those kinds of things. I don't think we're going to be going in that direction. But there's also probably a middle section where essentially you, you decide, you know, what. , there's gotta be solutions that we absolutely get through our existing vendors. And then there's going to be some things that we want to create some custom solutions around. And there are partners around that. And I talked about what a, an AI enabled health system would look like last week. You can go and listen to that show and it's exciting. I mean, it's exciting to realize that we're going to be able to take the structured and unstructured data. We're going to be able to make that make meaning from that data and then query that data from all aspects of the health system. From general reporting to operations. To billing and coding to the patient. In an authenticated and unauthenticated manner. , it's just an exciting, , exciting time to be in healthcare. This is a moment in healthcare. That we were going to look to and say, this is the year that AI really started to take off. And I think five years from now, we're not even going to be able to recognize what we were doing today. We are now realizing the promise of digitizing healthcare. Yes. It's been a tough long. 15 years, 10, 15 years, whatever it's been since meaningful use. But we now are starting to see the fruits of that digitization. And it's because the technology has caught up and we now have tools to interact with it. In a, again, the way we interact with everything else in a natural language way. All right. That's all for today. That's probably my rundown for this. I might talk about, , I'm talking about this conference a little bit more through the remainder of the week. But, , that's all for today. So don't forget. Sure. Share this podcast with a friend or colleague, keep the conversation going. We want to thank our channel sponsors who are investing in our mission. They are short test our site parlance certified health. Notable and 📍 service now check them out at this week Health. Dot com slash today Thanks for listening That's all for now