While there is an abundance of hype surrounding the transformative potential of AI there is no doubt that it has the power to accelerate healthcare's transition to value-based care. Dr. Groves explores how AI can support healthcare organizations in achieving better patient outcomes while managing costs, and discusses the role of AI in alleviating administrative burdens for primary care physicians. We will discuss the potential of AI in addressing healthcare workforce shortages, sharing real-world examples of AI-driven interventions from his experience at Banner Health and Aetna. Dr. Groves emphasizes the importance of responsible and ethical AI use, outlining necessary safeguards and governance measures. Looking ahead, he envisions the integration of AI and value-based care reshaping the healthcare landscape, highlighting promising opportunities and potential pitfalls for leaders to navigate.
Robert Groves, MD, CMO EVP, Banner Aetna
Megan Antonelli ,Chief Executive Officer, HealthIMPACT
Harnessing AI s Potential_ Navigating the Future of Value-Based Healthcare
[00:00:30] Megan Antonelli: Hi, this is Megan Antonelli with Health Impact Live, where we explore the intersection of technology, innovation, and healthcare. Our guest today is Dr. Robert Groves, a physician, healthcare executive, and thought leader with over 30 years of experience in the healthcare industry. Dr. Groves spent 27 years in direct patient care and has held multiple leadership positions in a large integrated delivery system.
He is now the chief medical officer at Banner Aetna. Banner Aetner combines Banner Health's network of healthcare providers with Aetna's value based care models to deliver high quality, cost effective care. The Aetna Whole Health Banner Health Network, introduced in 2011, now covers more than 250, 000 members in the Phoenix and Tucson areas.
Dr. Groves is passionate about strategy and innovation, thriving at the intersection of people and technology. He constantly seeks ways to improve healthcare, and he is here today to talk to us about how he is doing that at Banner Aetna. Dr. Groves is passionate about strategy and innovation, thriving at the intersection of people and technology.
He constantly seeks ways to improve healthcare, and is here to talk to us today about how he's doing that at Banner Aetna. Hi, Robert. Thanks for being here today.
[00:01:43] Robert Groves: Hi, Megan. It's great to be here. Thanks for inviting me.
[00:01:46] Megan Antonelli: Yeah, it's good to have you back on the show. And, um, you know, it's exciting. There's so much exuberance, maybe a little bit of hype around AI.
Um, you know, and value based care has sort of been in that space of a hype cycle as well, but you've been working in it for real for a long time and seeing how that's going. So I'd love to hear, you know, your thoughts on kind that intersection of The promise of AI right now and what it means for value based care.
[00:02:12] Robert Groves: Yeah, I, you know, I think there are a number of ways that AI is going to transform the way that we deliver health care and get our information. I, I think that we are in a bit of a hype cycle right now. And it's interesting as you watch the evolution of, uh, technologies, uh, you know, I think it was Bill Gates who.
Who first said, uh, it takes forever to happen, but once it happens, uh, it happens in a big way, I paraphrase, but, uh, something along those lines. And I think that's what we're seeing with AI. I, you know, it seemed for, uh, an expended, uh, extended period of time there, like nothing was happening, but obviously there was lots happening behind the scenes that, you know, you know, broke out into the public consciousness with chat GPT.
And that seemed like a big step forward. And I think it is a big step forward, the transformer model, uh, that allowed, uh, AI to have far more context and it's, uh, uh, predictive algorithms, uh, was, was a big breakthrough, but it took a couple of years for people to take full advantage of that. Uh, now we've seen things like, well, uh, AI can pass the medical licensing exam, AI can pass the bar exam.
So we're getting into territory now that is much more interesting, uh, and to some threatening, uh, than where we've been before with AI. But let me say one thing about that AI, uh, we should define because, uh, artificial intelligence has been around for some time, uh, machine learning of various types and, and algorithmic, uh, protocols.
You know, every time you use Google maps or Apple maps, you're, you're looking at AI. Uh, so it's not like AI is new on the scene. What's new is the large language models. And that brings with it a whole bunch of promise and frankly, a whole bunch of peril. Uh, and we're going to slowly navigate that minefield.
Um, I think that what we'll see is, uh, Something like we saw with CHAT GPT, all of a sudden we will have, I don't know, something that you can put on your, uh, mobile phone that will do a better job of diagnosing disease than perhaps your, uh, your local primary care doc. I don't think that's a pipe dream. I think that's real.
I think it's coming. And why wouldn't it? If you have a An intelligence that can tap into the world's knowledge in a fraction of a second and, uh, and come back with answers. Uh, why wouldn't we use that? And why wouldn't that be better than the limited human mind at, at doing certain tasks? I, I think the, the bottom line on AI though, is we have to remember that it's a tool to serve human relationships.
And that's where we can get off track. If we don't remember that key item. Right,
[00:04:51] Megan Antonelli: and I think those relationships and, you know, the ability for clinicians to take in that information is still going to remain, you know, top of, you know, the most important thing. Right. Um, but. I think the access and getting some of those answers and convenience, you know, when you talk about experience and patient experience and, and also just, you know, the ability for the health care system to even see the, see everyone who, who has needs, right?
What are you seeing in terms of, you know, the technologies that are being evaluated at Banna Aetna to use, um, you know, what are some of the most, most interesting ones that you're, you're starting to see?
[00:05:28] Robert Groves: Well, you know, one of the developments that's been huge for health care is developments in computer vision, which is obviously an AI function and computers now are getting really good at dermatologic diagnoses from pictures.
They're getting really good. At, uh, reading, uh, high tech imaging exams, and they're getting really good at monitoring movement for lack of a better term, there are ways, uh, there are ways that computer vision using avatars, uh, can be set up in long term care facilities, or even in the home, to alert someone if you haven't moved properly that day, if your movement patterns have changed.
I mean, there are all sorts of applications. What we're using today. uh, Uh, in, in one of our partners in the network, uh, uh, Honor Health is using, uh, AI to, uh, to cue x rays. Let me say it that way. So, uh, the old traditional way of reviewing films, radiologists, you know, sit, you know, the old, uh, the old, uh, uh, visual that I have is sitting in a dark room throwing films up.
Well, they don't do that anymore. They're looking at their computer screen. But how do they know which films to review when? Well, what AI can do is go through the whole raft of films that have been catalogued and prepared for review by the radiologist, can look at those and look for ones that are either concerning or urgent.
and bring those to the top of the queue and even highlight those areas that the radiologist needs to look at. So, that improves efficiency significantly and it should improve accuracy over time as well. So, that's just one example of computer vision. I don't think that, uh, we have any place in the organization now that has released a large language But, uh, as you know, there are lots of bots already out there in healthcare, either, uh, like with 98.
6 at Banner Aetna that is gathering that that's a telemedicine company. It's gathering that information on past medical history. That's a bot that's AI that's doing that. The promise is that it's just going to get a lot better. And so instead of asking a whole raft of questions, it will be able to do what physicians have done and do a focused exam for a focused problem.
Uh, so again, improve the efficiency of that process as well. So I, uh, it's not ready for prime time yet, uh, but it's coming.
[00:07:49] Megan Antonelli: Right. And what about now? I know you were practicing physician for many years. I mean, in terms of, You know, one of the big, um, you know, sort of areas of focus and coding and, you know, sort of not just diagnosis, but on the, on this back end, the administrative burden that some of the physicians are feeling are, you know, where does the, you know, as a value based care, you know, payer organization, or is that something that you guys are looking at?
Is it, is it more, um, on the hospital side? What are, what are those, um, you know, innovations?
[00:08:13] Robert Groves: Yeah, there are, there are roles throughout the healthcare industry, if you will, and that includes payers, it includes providers, it includes pay voters like the, the one that I'm in. But, you know, some examples you, you raised a great one that ambient technology so that there's AI in the room.
listening to the conversation between physician and patient. And so we've changed the equation substantially because the physician is no longer staring at a computer, uh, at a computer screen, packing away at the keys. He's now engaged with the patient, having a real conversation. And the AI is in the background, picking up that conversation and formulating the note that is a result of that information exchange between patient and physician.
That's one of the ways that I think AI can really, really help. Uh, you know, I had this notion back in the early nineties that we could do voice to data. And that day, uh, has finally arrived. It looks like where we're getting pretty good at being able to take language and translate that into data, uh, for a machine to manipulate, learn from, and spit out responses and answers.
So I think that's a great example of where AI can help. Um, you know, I'm going to go. a little bit tangential here and say, I've said many times that one of the big dangers of AI set aside cybersecurity and privacy and, you know, taking over the world and turning us all into paperclips, you know, those things, I, you know, they, they, uh, experts tell me those are, uh, real risks that we have to think about and prepare for.
I don't know about the paperclip thing, but, uh, the bottom line is the, one of the risks that I see. Is that in a fee for service system and, uh, an unbridled capitalist motive, uh, we'll simply end up seeing 40 patients a day instead of 20 because AI will dramatically improve our efficiency. I think that's a mistake.
I think if we do that, we've missed the boat. I think the idea here. is to use AI to enhance human relationships because it's through those relationships that trust develops. And if you want to talk about engagement, the biggest motivator, uh, is a trusted, uh, uh, advisor, if you will, which is what the physician can and should be to individual patients.
When you get that relationship with that trusted advisor, you're far more likely to pay attention to it and far more likely to do it. That takes time. And one of the things that we've taken away from physicians is time. Uh, 10 minute appointments, uh, for returned patients and 30 minute appointments for new patients, in my mind, just don't cut it.
I, I, uh, rarely spent less than 90 minutes on a new patient in, in my specialty of pulmonary and critical care. And I rarely had a follow up appointment that was over in 30 minutes. Uh, now that means that a lot of time during the day is spent on Interacting with patients as human beings, but I think that's the secret sauce for not only satisfied patients, but satisfied doctors and nurses.
A lot of the burnout that we see today is because it's become so. Rapid and formulaic that were simply, uh, you know, cogs in a wheel and that takes away a lot of that meaning and purpose that is buried in those human relationships that develop over time.
[00:11:17] Megan Antonelli: Yeah, I mean, obviously why clinicians get into healthcare and make those decisions to, you know, put in the time and the investment is for those personal connections.
And I think, you know, it's also 2 sides of the same coin, right? Because that trust element. I think a lot of the mistrust that even I have is that my physician doesn't have time, you know, they don't have the time to explore when I have a condition or my children have a condition, I will dig deep in the middle of reading Susanna Fox's book, rebel health, you know, and she talks about seekers and researchers and I've been all of those at different points in my life and depending on who's, you know, who's care I'm giving or caring about and.
You know, that time that you can take as an individual to research and to seek about your condition, a physician no longer has. So the hope would be that through the use of AI, the physician will have that time. And in fact, be able to build the trust because coming to you and saying, look, we've looked at all of these possible options with the help of AI.
And I think we've talked a little bit too about, and I'd love to hear your thoughts around You know, the discussion of how transparent do you have to be about the use of AI in these diagnosis and and and while some, you know, think of it as a negative to me, it's a positive. I want to know that you're using all of the latest tools to figure out the problem.
Where do you sit on that as as both a physician and as a administrator?
[00:12:44] Robert Groves: Yeah, I think again, framing, uh, artificial intelligence, large language models, uh, small language models, uh, computer vision, all of these are simply tools. And, and thinking of them as tools take some of the, uh, uh, some of the sting out of it.
No one would fault me for using Uh, there's a, uh, uh, an app, a site called up to date, uh, that has the most current information on specific diagnoses. Now, no one, uh, I, I think would fault me for going to up to date to brush up on a problem that I'm getting ready to see in the next patient. Uh, this is the same thing, except that it's far more effortless, far more rapid.
And far more complete, uh, uh, you know, once it, once it gets commercial grade, if you will, once it gets to that point where, uh, we don't have to worry about the, uh, some hallucinations. I think they're more akin to confabulation, which we're familiar with from, uh, from, uh, work in, uh, neuroscience. Uh, so once we get to the point where we understand those, where do they come from?
Why do they happen? Uh, How do we eliminate those or at least minimize them? Then I think we'll have a tool that's really fantastic to help us do the work that we want to do. And I, you know, it's not just about the accuracy of the diagnosis either. I want to tell a quick story about my initial interest in healthcare.
Uh, I, uh, you know, it's funny to think back, back in, uh, Um, the early days when I was a kid, I was probably 10 to 12 years old. My dad was a family practitioner. They called him a generalist then, or they called them, uh, Oh gosh. Uh, uh, uh, I can't remember the term for it now, but he was a general practitioner in, in Albany, Georgia, uh, trained in, in, uh, uh, internal medicine.
And he, uh, he had relationships with his patients. That's one of the things that drew me to him. uh, and to, uh, to medicine, uh, is his relationship with patients. I remember we were at morning report and yes, they had morning report in this community hospital in Albany, Georgia, uh, back in those days. And it was a very valuable aspect of care.
You know, all of the specialists would come in and hear what came in last night to the primary physicians, give advice, uh, consults were made, et cetera. Um, but we were in morning report one morning. I used to love to go on, uh, these visits with him and in house calls. And he said, I hope you're ready for this.
We're going on a house call. And I remember showing up at a house that I knew, because this is a guy who had, uh, uh, my mom loved to ride horses and she, uh, went there often to ride horses, but he had some problems, uh, with alcohol. And, uh, I remember going up to the house and. His wife was at the door, uh, in tears.
My dad hugged her and then went into the house. And here was this man who was six, six. I mean, a giant of a man crumpled in the corner. Um, and all he did was go over there and put his arm around him and say, it's going to be okay. And that you're never going to get AI to do. I mean, that is that the value of that human relationship and the impact that he had, uh, in those relationships is what drew me to medicine in the first place.
I don't want to lose that. I want to enhance that. The complexity of healthcare is far beyond the capacity of any human mind to completely grasp. Now we're going to need Tools to aid us in managing that knowledge, if you will. And that's the role that AI can take. And I hope that's where we keep it.
Right.
[00:15:58] Megan Antonelli: Yeah, well, it's certainly, you know, and I think it's, um, as it has, it's moved so fast, right? I mean, as you said, it was sort of like behind the scenes, but since November of 22, where Chachi Buti was released, and there's been this exuberance and hype, but at the same time, as you also said, um, That tool is not, it's not medical grade, if you will, it is certainly not commercial, commercial ready.
Right? Um, but getting to that place and, you know, sort of putting the tools together that have been working for years on clinical diagnosis and, and, um, then this sort of, you know, the user experience of what chat GPT provides does provide that vision for where, you know, You know, physicians and clinicians will have that time to give to the back to their patients.
Right? And that that ultimately is the goal. How does that, you know, I think it's it's a promise. It's fabulous. I think 1 of the problems in health care is, um, you know, where did the stakeholders fit in? Right? Where did the payment models adjust to to fix this? Right? Because yes, as you said, the natural tendency is just see more.
If there's more time, see more. Right. So how, how can hospitals payers, even patients prevent that from being the actual outcome?
[00:17:09] Robert Groves: Yeah. And I've, uh, I've, I've talked about this, uh, a few times before as well. I think that, uh, for medicine to really meet the promise, uh, and, and, uh, become again, uh, uh, the, the trusted respected profession that people look to in times of need.
Uh, we're going to have to change the way we pay for it. I mean, the, uh, the notion that fee for service and AI will mix. Well, I think is a, Is a false notion. I don't think the two go together. Well, I think what we'll end up with is, uh, increased productivity, which may help us with the caregiver and physician, nurses, respiratory therapists.
There are shortages in every category may help us with that, but it won't, um, it won't help us with burnout. It docs, et cetera. So I think we have to think about it again, as. Uh, that tool, which enhances human relationships, you know, it's interesting. I just, uh, uh, did an interview with Robert Pearl. Who's got a new book out chat, GPT MD, uh, Robert Pearl, for those who don't know him was the CEO of, uh, what was at the time, the largest medical group, uh, in the country, uh, Kaiser Permanente.
And he did that for 15 years, did a big turnaround. He's professor at Stanford in business and in, uh, and in medicine. Um, and you know, his notion is that the, uh, Kaiser like model is the ideal model for, uh, facilitating collaborative practice among caregivers. So they get a certain amount of money per head, if you will, per member, per month in advance, and here's the pool of money.
Here's how you can take care of your patients. Well, AI helps in a couple of ways there. First of all, uh, it should do a much better job of predictive analytics. In other words, predicting what that should cost over the next year. So getting that payment, right. But what it does is it eliminates so many games.
I mean, the game we have. around coding today. There are whole industries whose job it is to go back through your record retrospectively at the end of the year and make everybody as sick as possible. Now, what do I mean by that? What they'll try to do is justify any code that they can, uh, to increase the amount of money received because it's not just fee, uh, for service.
Now there are, uh, risk adjusters And, uh, those risk adjusters determine the amount of money you get for the patient population that you serve. Uh, I understand it, but, uh, my bias is get it right the first time. No going back, you know, there's, uh, it's all of that money that goes to an industry that, that, uh, you know, plays those games.
And by the way, there's going to be AI on both sides. We're going to have AI wars and prior authorization. where the delivery system is trying to use AI to get everything approved. Uh, the payer system is trying to use AI to get everything, you know, not everything, but, but to deny, uh, and, uh, we're going to have those kinds of AI wars.
I would much rather see us focusing on What is the most efficient and economical way to take care of this population? How will AI help us predict, uh, what's going to happen so that we can get those numbers, right? And then physicians can just take care of patients. They don't have to worry about, gosh, do I need to, to fill out these 80 things to make sure I can bill a nine, nine, two, you know, nine, five, or.
whatever it is that you're trying to code for, they can worry about what's best for the patient. They won't have to worry about prior authorization for a CT scan. If you really need one, order it. It comes out of that pool of money that's available to you to take care of the patients. If we don't change the compensation model, then we're not going to get what we want out of AI.
That's my opinion.
[00:20:49] Megan Antonelli: Right. 100%. And I mean, I love where you've gone with that. Because I think that a lot of that, which is the reality of healthcare, right? I mean, that is the reality of how healthcare gets delivered in this country in terms of payment and risk adjustment and how many people are in that process.
That is really the, you know, the crux of healthcare. Of where many of those issues lie and where this, you know, the stakeholders incentives diverge. Right? So, I guess my question and I know it's a hard 1, but is it how do we get to that point? Where does the change need to happen? Because there's been a lot of discussion and work to make value based care a reality.
[00:21:20] Robert Groves: Right
[00:21:21] Megan Antonelli: and now here we are many years later from the point where it was introduced. You have organizations like banner at Kaiser is still exist. It's still thriving. You know, they are practicing it. It's practiced in pockets, but still there's. You know, a lot of resistance and there's still, you know, majority of fee for service model.
So where does the change need to happen and how, I mean, how can we shape that dialogue? You know, I mean, particularly, you know, even from my perspective, you know, we try to bring it forward and it's interesting where there's pockets of interest in it, but then there's others who just say, you know, let's innovate, you know, we'll innovate out of it, but we can't, that is literally the, the crux of the issue.
[00:22:04] Robert Groves: Yeah, it really is. And, uh, the fee for service system is so embedded in our current model that it's hard, uh, to extract from that system and convert to something, uh, more useful. I, I think that, uh, uh, you know, even when you look at, you say, well, there's already, you know, the government is outsourcing, uh, Medicare through Medicare Advantage.
But even that system is fee for service based. And what I mean by that is the, the calculations are made based on RVUs, relative value units, fee for service. And then there's some sort of bonus that's added on to that for Uh, uh, uh, severity of illness, if you will. And that's the whole game about, you know, coding to make, uh, uh, folks look as sick as possible when you, you know, you ask for your paycheck.
I think now with the government funding more than half of, uh, uh, the health care, um, compensation in the country, that it's going to take a move, uh, by Medicare. Medicaid and those programs away from fee for service. Plus, you know, money tied to metrics. I don't think that's the right way to deliver health care.
And part of it is my concern about what happens to metrics when you put large dollars beside hitting those metrics. Everything else falls to the side. There's a You know, a single focus or, you know, if it's five metrics or 20 metrics, there's where all of the focus is going to be. It's not going to be on relationships.
It's not going to be on, uh, the experience of care. It's going to be, we need to make sure these gaps are closed. So we get every dollar do us. And we're going to need to make sure that we get every diagnosis possible on this set of patients. So we get every dollar do us. We've got to get away from that system and that's going to take a groundswell.
of public, uh, uh, interest in moving that, uh, needle and moving that dial. Um, I think, uh, one of the most disastrous, uh, ideas out there right now, uh, and I'm sorry about this, but is Medicare for All. because then we will lock in a flawed system. If you're going to have Medicare for all, it needs to be under a different payment system, or it simply doesn't have a chance to work the way we want it to.
And it will continue to eat up a fifth of the economy or more, uh, over time. Now we've kind of gotten to a plateau where 20 percent of GDP is, is where we've been for a few years, but There's no reason it has to stay there. Uh, and it, we, you know, the recent inflation in healthcare, labor costs, et cetera, are, are making it tough.
But when you add, uh, big dollars, you know, if you're talking 15% of your income, 20%, 30%, 40% to a bonus at the end of the year. Or an upfront payment that's a clawback at the end of the year, you immediately. First of all, you change the metric. It's not going to be the same metric. You thought you were measuring.
It will get massaged. It will get tweaked just like we do today with severity adjustment. Uh, and, uh, you know, it takes the focus away from all of the things that create. a good physician patient relationship because the focus is now on a handful of things that determine the paycheck. Um, Robert Pearl put it nicely when I was talking to him.
He said, um, incentives, monetary incentives work. They just don't give you what you thought you were going to get and that's exactly true in my view. And I think it contributes to burnout. The sword of Damocles hanging over you for the entire year as you determine if you will have the income that you're used to, or if it will be that minus 20 percent this year because you missed on some metric target.
Now, don't get me wrong, I'm not against metrics. I love metrics. I want to use them to improve how I do, how everybody does. But if you show that to me and my colleagues, and just show us where we stand, We're going to look at the guy at the top and say, how did he get there? I want to talk to him because I know I'm good.
I want to be better. Uh, and we've watched that play out. Brent James has tons of examples of using metrics on the front line to improve care without tying large dollars to him. And, you know, these are somewhat controversial positions on, uh, you know, uh, per member per month, upfront payments and on the elimination of these large sums of money tied to metrics.
They go together. If we want to get away from fee for service, we have to get away from, uh, uh, uh, value based care with that, you know, hit this metric and we'll give you a bonus. I, you know, and what's the evidence that, uh, that we need to change? Well, we've been doing this for decades now. You know, we've been talking about value based care.
We've been basing it on fee for service. We've been increasing the amount of money available for hitting certain metrics. And yes, it'll hit those metrics as newly defined and massaged and perhaps without all of the other stuff that goes with being a good physician. So I think both of those things have to shift and that's a tall order, as you pointed out.
Right
[00:26:44] Megan Antonelli: now. Absolutely. And I mean, I think it's exactly there. And so much of the innovation and the hype cycle and the discussions that we have, they don't get to this, right? You know, you know, when a lot of the new innovators, the unicorns, they don't come in and say, we're going to fix this. You know, people who have been in healthcare for a long time know that these are the issues that need to be fixed.
To then, you know, sort of appreciate the value and the promise of technology and everything that we can bring to it. But until we get at some of these, um, more, you know, systemic issues, um, it's, it's going to be, it's going to be tough. I think, um, the power of AI, you know, and I'd love to hear your thoughts on this, but the power of AI to, in some way, expose this, um, Challenge on both sides will be an interesting thing.
So I'd love to hear how how you think that could happen over the next, you know, things are moving so fast. I think, you know, initially, I was thinking 5 to 10, but maybe it's 2 to 5 years
[00:27:36] Robert Groves: that
[00:27:36] Megan Antonelli: we could see that happen.
[00:27:37] Robert Groves: Yeah. Yeah. I, I think that, um, AI will expose that whether we'll respond to it or not is yet to be determined.
Uh, but you think about all of the places that AI can help with future models in terms of predicting, uh, uh, uh, health care usage over a population, uh, making predictions about what, uh, moves in social determinants, what, uh, uh, what communities can do to improve the overall health over time. I mean, remember all of what we do, the four and a half trillion.
is all essentially rescue medicine. Even though we talk about, uh, uh, uh, you know, health, uh, maintenance and those sorts of things, we're not doing that, that happens in the community that happens in the habits you develop as you are growing up. That happens with economic opportunity. Those are the things where, uh, we're going to miss the boat.
If we don't realize that that's a foundational piece of the health of the population. If you want to look at longevity and health span, look to social determinants, uh, because the rescue medicine is only going to contribute maybe 15%. Uh, the rest of it is going to be genetics. It's going to be environment and it's going to be habits.
And those habits are established. And, uh, in culture and they're established by, uh, uh, hope for the future, those habits don't just appear. They are cultivated by how we treat our citizens.
[00:28:57] Megan Antonelli: Right yeah, no, I mean, it doesn't end to some degree that all of that the risk and the risk assessments and how sick a population is comes to that.
Right? So, on that side of things where you're evaluating. You know, the risk of your population that you're caring for. You know, and I think to pull back, you know, just the, the risk discussion and the trust discussion and the time and then the incentives. Right. So I w I could talk about this all day, but I love it.
But, um, as we, you know, sort of wrap up here, um, tell us a little bit about, you know, what, you know, what, what are you working on and, and what, you know, what, what is making you, we always like to focus on the good things. So this is one of the big problems. Let's just close with them. You know, what is what's the bright spot?
[00:29:36] Robert Groves: Yeah, you know, a couple of projects that I'm excited about. One is the reintroduction of community into the process. We've got something called the banner at the kitchen. That's a. I know this sounds strange when we're talking about A. I, but it's part of my conviction that human relationships are critically important to driving health.
And so we're bringing at risk diabetics together in a cooking show like experience. They've got a chef, they've got a nutritionist, they come together, they have their own cookbook. And they have experiential learning about how to cook a healthy meal. Many of these folks have never even been taught how to cook.
And so we're teaching them how to cook. That's durable information. They'll carry that home. They'll teach their family. They'll teach their friends. And old fashioned person to person viral spread is what we count on. And now we're moving into banner at an active. The other big project that I'm excited about is I believe now is the time to learn about the large language models in AI.
And if you're a large organization of any kind, frankly, and certainly in healthcare, now is the time that you ought to be going out to those that are skilled in this in the market and saying, hey, let's learn together how to create some tools here. that actually make life better for our patients. So, uh, I can't say a lot more than that right now, but I'm very interested in, in partnering with, uh, uh, some of the organizations that are capable of making this happen and saying, let's learn together.
Let's co develop this. You know, my bias is that, uh, uh, the best way to do that, frankly, is to create an equity model. So that, uh, health systems can buy in, if you will, and have some ownership in the final product. Uh, you know, I know that rubs some the wrong way in terms of non profits, but I'm talking about human nature here.
You know, we want health systems to be engaged in developing the product. And if they've got a stake in it, they're far more likely to I mean, one of the problems we have is priorities. Uh, if you go to an I. T. department at any delivery system, they've got 30 things that they're working on today. And you add one more and they roll their eyes and say, you know, where is it going to come from?
Uh, A. I. can help us with that too. As you know, A. I. can code. Uh, it can write code. Uh, and, and so there's lots of streamlining that's possible. There's lots of opportunity that's possible. But really the bottom line is, is how do we frame it? How do we frame the use of AI? How do we keep it as a tool that supports our notion that human relationships are what give life meaning and purpose?
And without that, all you've got is, you know, going through the motions. And I want to get away from going through the motions, which is where I think we are today in the delivery of healthcare and get back to human relationships. foundational to healing.
[00:32:21] Megan Antonelli: Beautiful. Well, that is a wonderful note to, to stop on.
And so thank you so much, Robert, you know, just great insights and, you know, your experience and what you've brought to, to all of this is, is, um, just insightful and, and actionable. So I appreciate that. And I look forward to chatting again sometime soon.
[00:32:38] Robert Groves: Thank you, Megan.