All right, good afternoon, everybody. Good afternoon to all of our colleagues here on the table, too. And good afternoon to all of the attendees here at HHS in Atlanta. And good afternoon to anyone who may be listening in virtually as well. I've collected radio stories for three years in my life. But I'm actually a very good DJ. But this is not about the tokens or the praise, as much as I say, as I want to be. My name is Anthony Johnson. I'm a musician. I'm a musician. And I'm developing a three-line beat for the bass drum, the Johnston Johnston. And I'm joined here today by some esteemed colleagues. I'm stuck with Dr. Jacqueline Chabadie. And she is the new cardiologist and nursing clinical lead. Thank you, Jacqueline, for being here. And, yes, he's the industry rising. I go, oh, my gosh, I'm so proud. I'm so thrilled with the improvement I saw. And, yes, thank you for being here. And Dr. Jacqueline Chabadie is also a cardiologist, a medical physiologist, as well as the agency medical director for the Kansas City Medical Institute. We've got a few esteemed panelists. And each, we're going to do a Q&A towards the end. When you want to talk, use the microphone. Use the microphone. So, what we're going to do, we're here today to discuss patients, digital tools, patient perspective, the ability of clinicians and institutions of care to utilize these tools and to connect with the patients and to incorporate their perspective into the workstreams, not only about the importance of patient perspective, but most importantly to discuss what the future perhaps could hold as we're drowning in a world of applications of our apps, I guess that's what my kids would say. So, without further ado, I will give the panelists the chance to express their initial comments or initial thoughts. And then we'll go ahead and provide some open place to start the conversation a little bit between now and the state of affairs and then dive into the future or the promising future of affairs. And we'll have a fun conversation for about 30 minutes. We'll appreciate questions. You can use the app. One of my colleagues here who helped us with that is technologically challenged in a technology-heavy meeting. But thank you all. So, without further ado, any initial comments from my colleagues? Yeah, I'm going to go first because I feel like I'm sort of a quasi-consumer of health care information to my patients. I just want to thank Google. For the leadership that you guys have taken in public education, patient education. So, it's not that decent access to knowledge that patients needed. And then you stepped into the lab and you came to Apple. What you have done really getting personalized access of health care data and enabling positive behaviors. And really sort of opening up that facet of patient-orientedness. I think it is fantastic. And so, a big round of applause to these two big giants who have really brought in some major partnerships in how much information access that we have. So, I just don't know. I don't really see the dark wheels of health care providers. And I don't really think they have reached the strengths of some of the big technology companies like you two to take health care delivery to the next level. A lot of what we're doing, a lot of what I'm talking about. So, thank you. Awesome. And I just kind of see a mix of that. But I agree with your commentary. There is a confusing image of what has to be done here. And I just don't think there's a very analytic image of that. Is there a technology to net this stuff to make sure that it works? And if it's not, how is it going to work? Is there a separate tool? Is there some noise reduction? Is there safety? I just think the part that said the technologies are great, the health care industry and the patients are going to have to pile up to make all this stuff work. So, I just think these conversations are really interesting because I'm hoping to learn what we should be doing as a global technology provider to make this easier for people with real jobs. So, I'm a safety net clinician. I take care of Medicaid patients on Monday mornings before I switch over to be a Googler. And the disparity kind of in the gaps between the work I do in clinic and then what I do at Google, I think are really emblematic of this struggle and opportunity that we face. There's so much technology. There's so much potential for data and making sense of data. At the end of the day, how we practice this is so far behind that it's really hard for me to reconcile some of the work that we do. You can ask an innovator. They can go out. The engineers I work with are kind of heartbroken to see that they're always going to personalize treatment plan for cholesterol or hypertension or diabetes. Is that gold standard? It's population-based. And there's no other one yet. So, my hope is that there is an innovation revolution with the way that we treat patients because it's really hard to have the technology kind of drag down the clinical standards or worker standards. They take longer to justify, but referring to population-level risk equations or professional guidelines is very particularly challenging to kind of truly bring consumers or patients into visualized experiences. So, they're not quite in sync yet. So, I think I'm really looking towards my professional and academic colleagues to look up the data, sort of find different ways of validating the data, be more iterative so that we don't have to refer to the old way, these population-level guidelines that I think are leaving a lot of people behind. Thank you for that. So, that's it for this answer. I'm excluding myself from the panel. Dr. Lacrimedia, I'll start with you. What is instant monitoring through digital health tools in clinic? And both of you, really, what are some of the gaps? What are some of the benefits? What are some of the things that we're doing right currently? And then some of the things, in your opinion, we're calling short. You know, I've seen the diseases that we deal with are chronic in nature. Often times, chronic diseases are managed really well out of real-time data, right? So, it's actually one of the key, you know, continuous glucose monitoring units. You know, there's still a lot of hypertension, blood pressure monitoring units that are going to be more dynamic in nature. And now, we'd be at room to both these wearables as well as implantable medical monitors that we have access to. And I just think that's what we're talking about, right? It's just not expanding to a proper drug. There's more data that we can write about based on assumptions and based on other things that we're dealing with, right? So, for example, I'll just give you a classic example. If you look at the care paradigm of interferon reaction as a unit, starting from resistance are about passing on peace, that's something that I don't really recall. I do want to add, that I'm also a pediatric electrophysiologist, and going back to these clinicians need to make a little bit more noise. And I will tell you, I think we're at the point where we all need to reach a self-determination point. And I would say to you, you told me who I should target with my roles, and I will go to that point, because we're at the point where there's so much that we need, and I think for all of us, it's coming from so many different places, right? So, in the adult electrophysiologist, we're just talking about using tools for everyone else that we know. Our patients are different than mine, and now we have to go outside to email those, and now we're at the point of doing our email into the recipient of the e-mail, of course, right? So, that's the key thing about it, that how do we, as clinicians, make, take advantage of the technology that you guys have created, and so that, and what I'm really saying, how do we get that better, right? As an electrophysiologist, I want access to all of that, but I want it to go into the medical record without me having to pull up the media tab all the time. Like, there are intelligent learning models that should be able to have that status. It's fine. It's kind of me opening up media, spending three minutes, and then seeing that status, and then opening an email for that patient saying, yeah, it's all right. Like, there's a better, more efficient way to do this, and then I just want to assert to my house that the two of you, as you guys are developing all of this, you can really use it for pediatric patients, right? Like, can we sort of change some of your algorithms to get to more folks like adults in that patient population, please? I know those requests I left were to some work there for a while, and I'd like to actually mention Silva for all this. I mean, I think the entropy that we see is by design, right? The financial incentives to keep things separate is by design, you know, into our ecosystems that provide services for interoperability because of the lack thereof. So, sometimes there's a, you know, a hub, a killer use case that kind of rises above the survey and helps justify why we should be working together. One of those use cases was COVID passports. You know, we all came together, all the companies came together, and said, we need to look at our state registry data and connect it with academic centers and connect it with our cloud platforms and send it to the federal agencies. That was all tough, but it wasn't a technical challenge. But there was a kind of call to arms for community's sake and everyone actually did the right thing. And I thought that was a beautiful time. I was there for all of that, helping with interoperability across the states and then supporting kind of at them and for that. So, I have to believe that those quote-unquote killer use cases can be justified maybe on a smaller scale. But when we have to do the right thing, companies can make change and they can do that. And maybe that starts with smaller scale. I don't know if our research projects are for WebRP or a really dedicated customer on one of our cloud systems, but I do think there are inroads for that, but the music world is a waste. We need to find the people who have the will. You know, these are not going to go somewhere. It's kind of a similar thing. It's a very similar place. Kind of in the same fashion as I was saying, a whole bunch of unnatural behavior happens. As we were at a new age of health care systems, we just saw the best of the best take a job. We saw an entire wave of the right-wing artists because competitors will, it was really cool. I mean, I've been working on that now. I'm also working on the health care and technology in the whole area. It'd be really cool to just watch people do the things that we know are going to happen. Well, I don't know if that sounds good or not. I don't think that's the thing we want to reach. I'm sorry, that's not the thing we want to reach. But to your point, what are the small lessons, those compelling events that break these barriers? Whatever barrier that we're talking about, we've talked about 23 so far, what are the small lessons about? How are we able to collectively deal with that? How are we getting the regulators to go, you know, all right, that's key. We'll reach a link at the start of the year, and we'll do it quickly. I wish I had an easier answer. So many of you are going to say, you can tell I'm not from the U.S. or the States, but I'm not from the States. I went to medical office in the U.K., which is a completely different financial model that's a model that broadly incentivized just incentivized this growing tech activity. Interestingly, though, I think there's two different reasons. And I'm not going to get into the muscle of it. It's the technology that we've got. We've got regulation. Regulation made it go. Regulation made it go. The way health care was funded and built. But sometimes there's little things that get people to say, hang on, what are the things that I ever think? You know what? You're not going to try to change the people. Please do the work and just keep talking about it. Thank you for that. And for those who are right around the table, you mentioned a lot of artificial expressions and their animation, which includes moving the finger off the state button, and that's where the gaps come from. But that's because we're passionate about this now. And as I see a sea of blue headsets around the room, which are basically listening to us, I thank you all for that. And please come closer if you need to, stick your head up and use the motions. Oh, that's cool. That was awesome. Thank you. Yeah. That's awesome. And if you can tell me what you think, I'm not going to ask much to you. I'm going to go down here. Thank you. The consumer-grade data going into your EHR. I think one of the concerns that we have is that our patients expect, we believe as clinicians that our patients expect that the consumer data will be treated with the same regard as the inpatient data. But I have to believe that maybe we're just not setting the right expectations for patients. A lot of our, you know, we're not patient monitoring. We learned that a lot of us is being around the expectation setting in terms of like the timing of response or the limitation of the data output. If we have consumer-grade data in an EHR, I think that just requires a cultural shift that maybe that data is attended to at the SLA, so to speak, is a little bit lower, or we have some level of uncertainty around the data that opportunistically needs it when it's there. But like we kind of re-imagine our relationship to consumer-grade data and see it for, it's good when it's available in high quality, but sometimes it's not, you know, it's not as we want to get to it for various reasons. And if the patients accept kind of, well, accept it for what it is, and they don't expect 24-7 coverage, then I think we can make more headway. But I think it's kind of around re-studying how we treat that data and stop comparing it to kind of gold standard inpatient data. All right, and there's a couple of slides I would like to run across to let you set this up. B, maybe it's the best thing to do is, I mean, yes, we are in the early days, so we just started this journey to just incorporating patient-only consumer-grade data into the electronic health records so that this really becomes a key continuum from the hospital to home, and then maybe they'll do hospitals at home, which is a popular concept that's actually marginal. But I see the problem is that there is incentives for interpretation of this data, that's coming in from this patient-only patient monitoring the rates and the blood pressure, so the blood glucose and all of this stuff that we're having. There's an investment for, and there's a positive incentive for physicians to maybe look at that. And then that is translating into an actionable item, really be in a real chain inpatient behavior The incentive is not for the patient, the patient's incentive is more on those healthcare professionals or healthcare institutions' incentive is bigger because they're not paying dollars for it. How do we change it in the universe? You incentivize the patient to actually consume the data, all the data, how do you exchange, how maybe that results in reduction in premiums for health insurance premiums, or something else that can be given back to the patient during the inpatient behavior? Well, the better part of it is, plus healthcare institutions are, and the technology companies, so they create processes that turns out to be easy enough for a patient to come up with a change, right? So we're shifting the focus from healthcare institutions and healthcare professionals back to the patient's utilizing technology. Think of it for a, I'm not, think of it for a conference, tell you, they're watching you driving and you're recording yourself as you're driving and all that, because it's really taking away your rights. So it's definitely out there. Okay, and I'll pause very quickly if there's any questions on the app, if anybody is checking and not intended, but they said one thing, or it might. Okay, question in the app, what role do you see AI and machine learning playing in not just tracking health metrics, but actively influencing patient behavior to improve long-term health outcomes? Nicola, we attempt to answer this question. I'm going to contextualize it a little bit, because it is our sort of, the shifting that I mentioned earlier, and the question came in the app, no pun intended, where patients are tired of apps, not just clinically or health apps, but in general. So the question for the panelists is, what is the next level of engaging the patients? How do we keep them engaged with models that require less output participation, perhaps to collect more information, the right information that is useful in practice? What does the future look like? Where do we go from apps, and how do we do that? And then along the lines of the question, how do we continue to be connected to the patient from a clinical perspective in a healthy and enduring way? Thank you. Hello, everyone. So connecting it to the AI question, and the intervention question, because it's in the audience section, technology, for me, is my answer. AI's predicted algorithms, AI has been driving health care change, and technology change for 10, 20, I don't know, 30 more years. It's predictable. It's all the things you need in a class that's in turn on. You probably start it running on your own whilst you're a professor, so you just don't even know about it. And if you want to be obsessed about alternative AI and this next-generation thing, which is magical, which is really cool stuff, but it is my silver bullet to change some of the things that predictive AI has been doing for the last 20 or 30 years. It does amazing things, and it is not predictable. And that's why we're all working on several ways to try to help it become more predictable, help it be more co-operative, more consistent, all those ways that's really important in the world of care. However, it's not too often. There are loads of use cases where I've been at this next-generation AI to really help with patient education, patient information, patient connection. You know, we always talk about telekinesis, you know, you need a human to verify, to affirm what the machine has said, actually, anything you need to work out as well, is the patient knows. There are a number of clinicals where the machine can do some straightforward things with AI, so even if it's connecting across silos and making, connecting, so it's hard to rely on alternative theory. The patient just knows when a source makes it, doesn't make any sense, or isn't tuned up. So, in other words, we just don't use telekinesis to help here, and we have to do it together, and that's not a job, and that's not a thing. At a lower level, for the patient, there are places in education, there are a lot of clinical workloads today that can make patients' lives instead of patients' own kind, you know, as they interact with you. As we all work together to get this next-generation of, frankly, medical software to go to the point where it can tell us how much time is left, as we need to. And that's not an easy mission, it doesn't, and it'd be better, probably, on this thing. But we're doing it carefully, we're saying it's important, in this context, probably, I know you have a context, so it's all right. I'll add to that, maybe some other ways of contextualizing it, are what are these lower-risk opportunities, both from a regulatory perspective, but also an innovation and technical feasibility perspective. So, a lot of the work that I'm currently working on behind the scenes involves general wellness, or health promotion, or health literacy use cases. Of course, there's, you know, the operations compliance, there's, one or two other, so it is, there's, you know, grant applications, there's other kind of content generation use cases, but in the case of health promotion, we know that people like companionship, they like constant encouragement. It may not be my generation, maybe my generation, but they really are an avatar, not just like the movies we've seen, where they're referencing this type of phenomenon, where they have that kind of continuous planning around, and there are some apps that are doing that these days, but maybe it won't be an app that is, you know, the form doctor 20 years from now, but that kind of constant encouragement, that coach, the inner voice that we'd like to have, it's sometimes not speaking to us the way it should, but it would be a positive inner voice all the time that was externalized. I just think that there's a lot of opportunity with general wellness, even in its current form, to provide motivation for daily step count, for walking, for getting consistent sleep, for going to bed at the same time, and this stuff, I mean, I think from, I'm projecting as a general cardiologist, well, I'm not, I'm assuming this is what I do, this feels like we're making very big steps, but I think from a societal perspective, and also from a feasibility one, from a risk perspective, it's the best place to start. I mean, I don't know, I guess I've been calling, I've been living on a basis of our expectations of this, we're talking about the future, I guess. I've always been calling, I've always been calling. So, I was gonna make such a question, so again, we'll start off, AI being a sort of a depository of health metrics that could be used to becoming a tool that would drive behavior and change. I think we start moving in the direction, and the industry requires a critical amount of infrastructure and constructs that need to be built. And this is based on, let's talk about the five M, big five M, and how they depend on the disease-based outcomes or predictive analysis, I think that's relatively easy, right? So, I think we're still in the process of building those billion blocks of what is to be the future of what we have. So, I'm willing to start fast enough, but I think it's just a matter of thinking about it. Thank you. And beyond the stringent physical tests being liquidated was the next criteria to be a panelist. As you can tell, we're having some fun here. We're about three minutes away from wrapping this up, and that's where we're allowed to stay over time. But as we glance into the future and allow ourselves to contemplate and dream to some extent, we'll wish a challenge, and here's a question that came through the chat as well. Have we seen inconsistencies or problems with current consumer-based products, and how do we address those inconsistencies? How do we correct for them? What role do they play in developing the next gen of solutions? While we all agree that patient perspective is critical, bringing it in to the ground here or elsewhere in the right way, I guess, requires fixing the mistakes of the past as well as developing the vehicles of the future. So, I will head off to the panel for your last comments around this space. How do we move forward while taking the lessons, the current lessons with us? Yeah, as we've seen inconsistencies, and the answer has to be yes, otherwise there would be a lot of good product matches. There's some of that in Korea. However, there's a lot of products sometimes or we don't always get to see the matches that we're getting to see. It's a lot of monotony, right? It would be, so we have seen inconsistencies through the screen, through the system. So, I think it's probably a good idea to look at some of these inconsistencies and try to fix it. So, I think it's probably a good idea to look at where trusted solutions can be made by the trusted care provider that the patient trusts or contacts with to talk to and trust upon it. That can become the kind of things that we're doing now. We can't walk the way to get everywhere. Sometimes it's just the patients who don't want to go to work. They want a thing that we love. And then, let's try and find a way to get to this. I mean, I said it before. I said, oh, there's good tech here. There's health tech companies. There's providers, clinicians, more active providers, as in organizations and then clinicians and patients. We've got a really good opportunity to do something really cool there. That's how we can, you know, go in other places. That's the next. Yeah, I work in an information company and I think that the biggest remit for all of us here and the folks who work at information companies is to better educate ourselves as consumers, better educate our patients as to expectations and limitations of the technologies that are being used. We might call this digital literacy or digital health literacy, but we've been handed the keys to a very fast car. I know. I was not a driver. Clearly, not always wearing helmets. And so, I'm just humbled to be doing it and I like the opportunity but also the challenges of having access to all of this data. So, you know, often what this is happening in our schools and certainly as clinicians we should be doing this as well, but being very intellectual and self-reflective about our interactions with technology and our use of the data and encouraging our patients to be more self-aware of their practices because it's, you know, it's a pleasant easy, takes some time to learn and I'm still not a good driver. Not with my work. I'm really not a good driver. I'm not a good driver. It's just, I'm not a good driver. I'm not a good driver. I really don't think it's a bad idea to follow this up and what we've got to think about is we see it made sick that everything that we do is patient-centric, but oftentimes it's not. And so, we've got to really define that the best use of the centerfold is the practice that we're doing and also creating appropriate data software for the guidelines or these guide rules and really force interconnectability from one system to the other system, right? And this allows the community to say, this data has to be shared and when we mandate it in work, we'll take away some of the gaps in the process-specific information and I'm really creating a framework of really helping to create a construct that is reproducible, that can do all data time and time again, creating software for the example that I would give you as an example and this is just a finance system where every company have their own type of finance system. I agreed to be, to come just to see what is possible in uniform and what are the folks that are sharing, right? I think we're going to get there and I mean, that's a process that evolves from there. Thank you, everyone. I wanted to, in the spirit of collaboration and innovation together, just plug it in the team at Downtown Johnson of how very dedicated and capable and experienced people. So, we welcome any offering in that regard. Please connect with us. Please collaborate and work and let's make bigger and better things together. It's been a privilege and a matter of pleasure being with you today and thank you for everyone that joined and thank you to HRS for having us and giving us the opportunity to have such a fun and productive discussion and I look forward to connecting in the future. Thank you, everyone. Thank you.

health care

digital tools

patient perspectives

technology companies

AI

predictive algorithms

digital health literacy

electronic health records