AH014 - The Rise of Conversational AI: Healthcare Search & Patient Journeys Will Never Be the Same

April 19, 2024

Capital Rx

In this episode of the Astonishing Healthcare podcast, Christian Ward, Chief Data Officer at Yext, and Carrie Liken, Head of Yext's Healthcare Industry Practice, join Justin Venneri for a discussion about the search trends they see that reflect changing behavior and ultimately influence how people will find information online. Health systems and other healthcare providers must structure their data on the backend and get things lined up properly to ensure accurate search results in a GEO world.

The conversation delves into how to ground AI and prevent the 'hallucination' of information, as well as creative ways to use AI as its capabilities expand to include more senses! Christian and Carrie emphasize the need for organizations to embrace AI and employ a collaborative adoption strategy now rather than taking a wait-and-see approach. They also describe the impact of AI on healthcare journeys and how patients can be directed to the most appropriate resources, thereby reducing waste in the system. Listen below, and remember to subscribe on Apple, Spotify, or YouTube Music!


Lightly edited for clarity.

Justin Venneri: Hello and thank you for listening to this episode of the Astonishing Healthcare podcast. I'm Justin Venneri, Director of Communications at Capital Rx. And joining us from Yext today, which helps millions of businesses manage the knowledge about their business across all digital experiences, including search, chat and the web, are Christian Ward, who's Chief Data Officer, and Carrie Liken, Head of the Healthcare Industry Practice. Christian and Carrie, thanks for joining us today.

Christian Ward: Thanks, Justin.

Carrie Liken: Good to be here.

[00:53] Justin Venneri: Why don't we just start off with a little bit more about your backgrounds, and then we can get into some of the questions. Christian, you want to go first?

Christian Ward: Sure. So I'm chief data officer at Yext. I've been Yext, surprisingly, about a decade, which feels in Yext years like 70 years. But I've been in structured data really since I was about 23, which Justin and I worked together ages ago on Wall Street, where my background is really in signal processing and understanding different data points and how they're utilized in market to make decisions. And so, at Yext, I really focus on helping our clients, including our healthcare industry, but really all of the different industries at Yext, understand how do they manage their knowledge to put out the right signals into market in order to engage customers in their journey.

[01:39] Justin Venneri: Got it. And Carrie, you've got a pretty interesting background that I think a lot of our listeners will appreciate coming from Google. Give us a rundown on where you've been and what you do at Yext.

Carrie Liken: Sure. So, like Christian, I've been here for almost eight years. So, I'm coming up on my decade too. And it does feel like about 70 years. So, I'm the Head of Industry for Healthcare and I work on product strategy and go to market for Yext. And that means I get to work with our customers. I get to work with prospects. I get to work on the marketing team and develop thought leadership. I get to work with our product teams that I'm developing perspectives on what's going on in the market and bringing it back to our product teams that they can make adaptations and other adjustments to make a product that will actually develop solutions that Yext can solve for healthcare specifically.  

And Justin, you're right. I did spend time at Google. And while I was there, I spent eight and a half years working with healthcare organizations on the AdWords side of the business and started the provider practice within that side of the business, from zero customers to a multimillion-dollar business where we help them to move just little percentages at first of their traditional marketing dollars to digital. So, I've been talking about the digital patient journey for almost 20 years now, which is hard to believe. And I've seen the evolution of how people search.  

So how people actually searched in the early 2000s has changed profoundly. And so now at Yext, I get to continue to have that conversation and continue to see just the differences in how people are finding information, what they're doing, and then how organizations are actually able to tap into that. But the reason I came to Yext was that organizations had big problems actually managing their data on Google, and Google internally could not fix fix it. So that was the reason I made the leap.

[03:25] Justin Venneri: Okay. And that's a pretty good segue to my first question. Recently at the Yext summit, Christian, you highlighted some of the bigger picture trends that are going on, and Carrie mentioned how much things have changed. So what are you seeing in the data and the macro trends today that are influencing how people find things online?

Christian Ward: Yeah, so the Yext summit, for those that don't know, it was basically a few thousand people came to a digital summit. It's the first time we've done that. Most of our stuff is in person, but it was actually quite a turnout. And I think a lot of it is because of the trends, which is AI usage and how people are starting to use AI in market.  

One of the areas that we talked about was just -- we see for a client, so part of our platform connects to Google to synchronize the businesses data or the hospital systems data or the doctor's clinic data, all with Google. But that means we also can see things like the searches that people are putting in, where they show up. One of the interesting trends that we see, or we saw really six months following the launch of GPT, which now feels like an eternity ago, but we started to see this big change where people were asking how and why questions, in fact, across millions of businesses -- so probably hundreds of millions of search queries -- we saw that the words how and why in these queries go up 38% in the first six months following chat GPT.

So in a way, what people are curious about now is you have Google bringing search generative experience, or SGE, to market, and that's where they're using their AI to answer questions at the top of the page. So, it's sort of pushing that classic market stuff down. And so, these two changes are interrelated, meaning people are starting to expect that they can say, why should I go to this physician? How can I get help with my healthcare insurance? How do I change my pharmacy prescription data? Like they're asking how and why? And that's really interesting because before AI, you didn't really ask how or why and expect an answer. If you said, how do I change my oil? You'd get a billion YouTube videos on other people changing their car's oil, but not how you change your oil. And so that's the big change.  

And I think that trend, I mean, it's, it's unbelievable how fast that trend is going to continue. So, I think more and more this AI, sort of as a stand in, is what everyone's trying to figure out and particularly interesting in the patient or a customer journey because you're talking about very personal information. But Carrie, do you want to add to that?

Carrie Liken: I was thinking as you were talking about just the changes that we've seen in the last, what is it, year and a half or so? I used to go to organizations when I was at Google early on in 2007, and I would talk to organizations about how people were searching for health care way back then. And I would say, well, they're searching for things like “cardiologist” -- simple, cardiologists. They just wanted to find a cardiologist, which the intent behind that was I want to find a cardiologist for myself or for my loved one, or I wanted to find a cardiologist near me. And we started to see the evolution of literally, “cardiologists near me” or “cardiologists with an available appointment” or “cardiologist who accepts insurance.” But if you notice, and Christian talks about this a lot, that type of search is very unnatural. It's, I want this. I want this, I want this. But it's not in a sentence. It's not in a language understanding that you would ask a human. You would say to a human or to a friend, “Hey, do you know a good cardiologist for my grandfather and somebody who might be at Mass General Hospital and who might be really good with bedside manner?” So, there was this weird way of inserting the search into Google to try to get what you needed.  

Now we're counseling organizations that, that how and that why is just the tip of the ice for, because people can now start to actually have that back and forth. We're noticing it on that new search generative experience that Google has even implemented on top of the regular blue links where you can actually now look at the results that are AI generated and you can continue to ask questions within that experience. You can start asking, “Who is the best? How can I find? Where is it?” You start to have a conversation with technology?  

I see that some organizations, they don't know what to do with it. They don't know how to think about it. A lot of organizations are waiting to see. A lot of industries are moving farther ahead than healthcare in this regard. But I think that we need to make sure that organizations are well advised on what it is that people are searching for and how they're searching for it, because it's so much more natural now to just get the information you need on so many different platforms, not just on Google and search.

[08:03] Justin Venneri: That makes sense. And it is fascinating to see that AI box pop up at the top of your search results and then be able to click into it and poke around and prompt it and ask the next question or the next logical question in the conversation. Christian, when you're talking to clients or when you're presenting on this topic, what are some of the things that you're thinking about, or what are you playing with, with generative AI online, and your conversational kind of prompts, how do you see this evolving from here?

Christian Ward: Yeah. So right now I think everyone should be sort of playing with these tools. I don't really care what industry, what your job is, even just to make bedtime stories for your kids. Like, it doesn't matter. You should be trying these tools. But what I really see right now, I think is about to change probably in the next three months. Right now we still have the problem of the evil blank box, which is you go to these tools and there's a blank box and it's sort of like, ask me anything. Well, that's not actually how humans typically operate, so we're still treating it like a discrete game, meaning search is a discrete game. I type in cardiologists and you return results. And then I make a move, then you make a move; they're discrete moves.  

What's about to happen is this is all about to turn into a continuous game, which is a completely different goal. Right? So discrete games. The goal of a discrete game, in game theory is to just finish the game. It's to end the game. It's to win. A continuous game, a lot of people don't realize, the goal of a continuous game is to keep playing. And so what's about to happen is all of this blank box stuff is going to go away. So you're going to turn on your AI and it's going to start asking you questions like, “Justin, how are you feeling today? Great. What can I help you with? Okay, what are you reading?” It's going to start prompting you. And so, in the past, it was humans had to prompt the machines. But in the next three to five months, I think you're going to see that the machines really start to prompt the human.  

And that gets interesting, right? Because as Carrie just pointed out, for a lot of patient journeys, we've been trained this ridiculous child babble of “cardiologists near me.” That's not how I talk, it's babble. But the other really interesting problem is, today, if someone uses our platform and they type in something like, “my ankle hurts” or “ankle pain”, the problem is we return search results that say orthopedic surgeon and we list those. The problem is a lot of people know what an orthopedic surgeon is. And so we have immediately jumped over their reading level and their comprehension level. AI gives us an enormous opportunity to bring cognitive accessibility to really sometimes complex things.  

So, if I say my ankle hurts the AI, instead of saying orthopedic surgeon, it should be saying, “Well, is it high on your ankle or is it low on your ankle?” I say, what's the lower ankle? “Well, how did you hurt it”  “Well, I stepped off the stairs wrong this morning.” And it just keeps going. Right. And what it's doing is that continuous game is opening the opportunity to really actually give the person at their own cognitive level direction as to who they should speak to. And I think for Carrie and I both, we get excited about this because you're talking about completely rewriting the patient's journey to getting into the right area where a human can help them. And there's a lot of opportunity there.

[11:18] Justin Venneri: Carrie, do you see -- this, to me in marketing at a pharmacy benefit manager is fascinating, right, because people are always searching for or about the drugs or medications that they're being prescribed. But for the average patient in the average health systems community, how do you see something like this impacting the professionals that are working at that health system, that are trying to expand and improve their relationships with the patients in their communities?

Carrie Liken: So, a huge issue that healthcare organizations have is actually their inventory. And I talk about this. I heard a health system yesterday talk about this, and I've been talking about provider data as health system inventory for probably 5+ years, and only now, 5 years later, have I heard one health system, a very large one in the country, talk about how their provider data is their inventory. So they need to know what is the doctor's specialty, who accepts what appointments, and do they have availability, and what types of conditions does that provider treat and what insurances does the provider accept.  

If you think about the CVS's of the world, they know when they're running low on inventory. They know when they need to restock their shelves. They know what's selling faster than others, not even from a pharmacy side, but literally just the inventory on the retail side of that location. And so, provider data is really important. So when Christian's talking about having that conversation where you could say, my ankle hurts, and instead of receiving orthopedic surgeon as a result, if there were a world where a conversation could be had, where an organization could actually lead somebody and guide somebody down a path, or the AI can lead somebody and guide somebody down the path to saying urgent care versus orthopedic surgeon versus some other type of doctor, maybe it's just primary care. It comes down to the data. It comes down to that inventory. It comes down to organizations really knowing what individual doctors do, whether doctors are accepting those appointments, what conditions they treat.  

We hear about this a lot with things like spine issues, back issues. Is it an orthopedic surgeon or is it a neurologist, or is it a neurosurgeon? And a lot of times, then, if a patient who can't be led and guided down a path books an appointment, let's say, with a neurosurgeon, but really should have seen an orthopedic specialist, then that's a wasted appointment with the neurosurgeon. It's wasted time for the patient. It's longer time to actually get care for that patient, because then the patient has to go find an appointment somewhere else. It just becomes a lot of waste in the system.  

So, I think that if there were an opportunity to merge that guided environment, then we could guide people to the right person to be seen, we could get a lot of waste out of the system. But it comes down to organizations actually getting control of this. And a lot of organizations I've been talking to, it's like passing the hot potato. I don't own the data. Well. I don't own the data. IT doesn't own the data. Well, marketing doesn't own the data. Well, credentialing should own the data. Well, they don't own the perfect data. So nobody's taking ownership of that data. And until organizations do, we might have one of these butt head moments where the technology is moving so fast. But if the organizations can't actually get that data together to be able to facilitate inserting information into that guided pathway, we may not actually ever get there.  

So, there's that inherent challenge that organizations have. But it's amazing. Like, I think that there will be something that will be amazing at some point, and it's almost like search and chat will come together and then we'll be able to have that interaction. But you can't have a good interaction until you have good data.

[14:55] Justin Venneri: That's really interesting. And thinking about the ankle injury, Christian, is a good example. You talk a lot about maps, like on the back end, like knowledge grid or knowledge map, right? And forgive me if I'm saying that wrong, but it's interesting with the provider directory or library, there's all the partnerships too, right, Carrie? Like when you have physical therapy as part of the care team or as an affiliate, how do you make sure that all of that comes into that picture so that people can find the right thing? Maybe Christian, can you talk a little bit about the importance of structuring your data on the backend and getting things lined up properly so that those maps and those searches can lead down the right path?

[15:38] Christian Ward: Yeah, absolutely. So at Yext, we use knowledge graphs to structure our customers data. So, if it's a healthcare system, a lot of times you'll see a doctor to us as a type of entity in a knowledge graph. And then that doctor has a relationship, a connector to the facility where that doctor provides services. The services are also entities. The insurers are entities. The pharmacy plan is an entity.  

So, by doing that, what we have found is most AI platforms at this point are really focusing on what we call grounding. And grounding is this idea of, yes, the AI can talk to you, and yes, it can even mimic your reading level, but the AI needs to not make some things up. Most AI today that everyone's excited about, there's really large language model extensions where they're feeding it data. What we've found is that knowledge graphs in particular are a very good way to ground AI, to not go off the rails. In other words, the AI itself, you can say to it, hey, here's a graph, and it's highly structured.  

For example, if I were to say to the AI, hey, can you tell me about this bank? Well, if I say that to a fly-fishing website “bank” means something different than if I say to a financial institution and the structure tells the AI that. So there's a great deal of structure.  

Like, I know everyone's excited about AI, and you should be, but the reality is none of you have an AI strategy. I know it's going to sound really rude, but you don't. Your AI strategy is really just your data strategy. You need to get your data into a structure where when the new GPT-10 comes out, or Claude 48 or Lama 28, I don't care what it is, when those come out, you're just going to unplug the prior AI into your structured data and plug in the new AI into your structured data. You're going to upgrade, but you're probably not going to build a fine-tuned model. What you really need to do is build out your knowledge graph. Or again, you can use other tools, we use a knowledge graph, but the more structure you can lock down around that data, the less the AI has license to sort of expand upon it or perhaps actually corrupt it with statistics. That's the goal. You're always trying to find structures that the AI does not exceed its parameters when it's trying to answer questions.

[17:57] Justin Venneri: I would think that's exceptionally important in healthcare. Right, Carrie? How do you kind of talk people through that one?

Carrie Liken: It is because you don't want that hallucination to happen and organizations do need to control and to manage that. I even think about with the new search generative experience, even Google, and I can't, I don't know what's going on behind the scenes at Google, and it's been a long time since I've worked there, but I interpret what I see. But when I think about how Google is pulling information into that new SGE result, they've said we're pulling data from these key elements, we're pulling it from GBP, like Google Business Profiles, we're pulling the reviews from Google Business profiles, we're pulling the data itself. Like any of the content, we're pulling it from structured schema tagged content from a website. We're pulling it into this experience.  

And I like to say that Google's lazy. They would rather actually pull from a highly structured piece of data and put it into that result rather than try to make something up. And in healthcare especially, making it up is really dangerous. So, when we talk to organizations, like healthcare organizations, we try to emphasize how important it is to actually have that structured data at the ready, because the next thing will come. Christian talks about this I think. Did Gardner say that by 2026, is there going to be a 26% decline or decrease in searches or in search engine use? Because there's all of this proliferation of other places where you can find information.  

So, a healthcare organization needs to have the data in a structured format. We like to say the knowledge graph, but in any type of structured format, in order to say, well, if search is declining, well, what is increasing? We need to make sure that that data is getting there, too. And it has to be highly structured so that it can be read appropriate. So not only is it patient safety, but it's also organizational and brand safety that everyone needs to worry about. And we just need to make sure that patients are getting the right information.

[19:47] Justin Venneri: Got it. Christian, you want to maybe expand on that a little bit? Does it matter if it's Bing or Chrome or as you mentioned, there's how many different AI platforms people are using to just test the water now and see what they like interacting with -- Gemini now versus GPT-4. And by the way, I'll add some links to the show notes. You’re a great follow on LinkedIn with your just tips and tricks on how to use AI and work it into your daily life. But we'd love to hear your thoughts on that.

Christian Ward: So I think, as Carrie's pointing out, this is changing. And the statistic from Gartner was, it's kind of twofold. They say by 2026, the end of 2026, 25% of all search engine traffic will disappear. By 2028, 50% of all search traffic. (Gartner Predicts Search Engine Volume Will Drop 25% by 2026, Due to AI Chatbots and Other Virtual Agents.) 

Now, this is Justin and I, we come from a financial services background and actually equity research and hedge fund signal processing together. But. So this is a signal, right? It's a very loud signal, and it's meant to grab a headline. But actually, when you look at this, it makes a ton of sense, which is from time long gone, there was dozens, hundreds of search engines. They all sort of coalesced into a centralized search ecosystem with Google at the center. But Google still checks all those other platforms, just like Carrie was explaining, in order to build its own signal strength and accuracy about objective knowledge – subjective knowledge, it handles very differently. But objective knowledge, like, what is this drug compound? What is it used for? There's a lot of objective facts that it can grab, even. What time does the x ray office open? There's very simple things like that.  

So, Google's always done it that way. But what's happening now is Google and everyone else is realizing you can't do this on an ad model anymore. I love Google. And tomorrow they could pivot, and they'll be just fine. But the reality is every business model that was based on ad revenue has given in to business models where ads are no longer supported. That is the fact. That is classic television commercials now. No commercials. We have Netflix. All of those models. Now, you can subsidize, but it's a different thing.  

And so when, even when Google wrote their paper about Google at Stanford, there was a paragraph in the appendix that says, if we choose to go an ad-based model route, there's a problem that it may corrupt the goals of people finding answers. They literally called it out when they created Google that an ad sponsored model is probably going to be bad in the end. And so what's starting to happen is we finally have the technology at scale through perplexity. Claude, Meta’s Llama, there's all these new tools, and they work better as long as they can get access to the same knowledge. So as Bing has opened it up to ChatGPT, and for everyone, I would say try chat GPT-4, right, pay the premium. 5 is coming out. It's $20 a month. Or you can buy the executive one where they don't store any of your data. I recommend that. But the reality is that is the smartest being you can work with as an assistant on the planet right now.  

Now, Claude 3 is another one. That's the opus model from Anthropic. And they just got a massive investment, anthropic of a few billion dollars. That's great for writing, so you can use different ones for different things. But if you pay $30 or $40 a month for Netflix for a bunch of crap content, pay the $20 to have the smartest being on the planet at your desk waiting to talk to you.  

But that's the type of thing I think you've got to start. But the decentralization of search, where, why do I want to talk to Google when I could talk to Stanford Health and get the answers from them like they're my health? I don't want Google's opinion and I don't want 48 ads. And I think that's what the market is about to experience.  

Now, as Carrie pointed out, that's a little scary because marketers are very comfy and cozy in their SEO,  SEM world. But this discomfort is actually a net good for humanity on a very big scale.  

One thing I always think about healthcare is the self-diagnosis -- remember the WebMD effect and everybody suddenly was sick with something -- well, AI in many ways, is actually going to be much better at that through prompt inversion, where it prompts you and helps you get to, hey, you don't have this. This is probably it. Do you want me to connect you with three or four doctors in your area? It doesn't need Google for that.  

So objective knowledge for these AI systems is where I think most healthcare systems -- pharmacies, payers, all of them -- should be focusing on. Get your objective knowledge out there as much as you can to ensure that you're showing up in all of these AI platforms.

[24:20] Justin Venneri: Carrie, anything you'd add on that?

Carrie Liken: Yeah, I'd emphasize, I mean, 120% agree. I'd emphasize the “get your objective knowledge together." What I see in healthcare is that that will then stymie and paralyze organizations because they say, well, then it's going to, we're going to commit this and we're going to take six years to get our objective knowledge together. My recommendation is always get started with what you have now, even though it's not perfect. So, get started and get moving while you're working on perfecting it at the same time. So don't wait, because waiting just means that you will become further and further behind in your information. Will not get out there. It's the only thing I would add.

[25:04] Justin Venneri: Got it? Yeah. It definitely seems like the more conversational things get online, the faster you kind of have to move or understand how to use it or how to put your information in the spot where it can be found by the person asking the question, is that fair?

Carrie Liken: It is fair. And I think the interesting thing is that healthcare tends to not move very fast, just in general. So, you know, with Moore's law and everything just, you know, exponentially moving in a direction where things are moving faster, fast, faster, and data is being stored. Healthcare is like, oh, shoot, we missed the boat. And then they really missed the boat.  

So just getting the information out there is just a good start, but it's really embracing it. And I think we see legal issues. General counsels tend not to understand this technology. Marketers, if they don't test it -- like Christian said, test it, work with it, play with it. If you're not doing that, and if IT teams are not doing that and they're not thinking about what the practical applications are, the consumers are doing it, the patients are doing it. So you're really in a mismatch. So getting out there, getting started, make sure obviously, you're doing it within the legal compact is very important. Don't wait.

[26:11] Justin Venneri: And then my last question, I ask everybody this. So, I'll ask it in two different ways today because I have two awesome guests. So, Christian, first one, we'll start with you. I normally ask what the most astonishing thing you've seen is over your career in healthcare and then around the discussion topics. But let's just focus on AI. What's the most astonishing thing you found in using AI that you want to share with people?

Christian Ward: So probably one of the most amazing things thus far is the integration of multimodalities. So again, not everybody has this. Try it. You have to pay for a premium version of the AI but take a photo of anything and ask the AI to explain what's going on in the photo.  

So you're essentially tying vision to the AI. And what's likely to come out this summer is an addition of another modality. I call it touch. But basically, think of it this way. You could talk to your phone, and it will open your text app, it will type in the text, it will touch the screen. And once you start getting into that, where it can see, hear, touch and speak, I think that's when it's the most amazing thing thus far, which is you combine these additional sensory inputs.  

And so I've been using that a lot, which is I take photos at conferences, and I have the AI write Sherlock Holmesian mysteries about the people on stage, and then I send it to them. It's kind of a joke, but it's basically, it's unbelievable. I literally take a photo of a friend on stage giving a talk and then ask it to create a Holmesian mystery using only the information in the image. And it literally creates an intricate plot where, like the screen, whatever they're sharing, that's the person that attempts to kill them. It's absolutely amazing. And it's from one photo. So, I think you can get really creative with these tools, but you have to use them in order to get there.

[27:50] Justin Venneri: That is amazing. Carrie, how about you? But the version of this question for you would be, what's the most astonishing thing you've seen in your experience with healthcare organizations? Working with search, that you can share, of course.

Carrie Liken: Oh, gosh. Working with search. You know, I don't think I've seen anything astonishing, let's say from a marketing perspective. I think everyone's just dabbling in it. But AI is not new in healthcare.  

So, I think about probably what will come of how AI is used to diagnose, let's say, to read radiology scans or to take a look at big, massive amounts of data to be able to predict diseases earlier than they normally would if they were just using human capabilities. I feel like see, seeing that now and seeing how fast that's going now, I think that's the biggest thing. But unfortunately, I can't say anything from the marketing side because a lot of times organizations are saying we're just using it to write ad copy, we're using it to write some content. We're not really doing what Christian is talking about yet, because I don't think there's enough play that's taking place at this moment in time. Plus, there's a lot of fear, like I said before, about the legal implications of how to use it.

[29:02] Justin Venneri: That's interesting. Do you still see--  last question, not exactly, really -- but do you still see people really focused on SEO, on search and how are they doing anything different that you could share? Carrie, that would be just worth considering in the context of this overall shift in how people are finding things online.

Carrie Liken: Yeah, I think when I talk to organizations and I'm giving a talk about what's going on with SGE and how Google is taking steps to change the game and SEO and now organizations need to start thinking about the generative experience optimization or GEO, I think some organizations are saying, well, we're really well set up for this because we're not just putting content out there anymore. We are putting content and providers and locations. We're structuring our pages to have structured data that can be sent to Google to be able to optimize for SEO or GEO. Many organizations aren't yet doing that, though.  

So, I think there are things that they can be doing to do better. Some of them are starting to dabble a little bit, and it's interesting to see those that have IT and developers on the marketing team are doing this faster than those who have very separate entities. So marketing is doing its own thing. IT is doing its own thing. They're focusing on Epic and EMRs and other things, and then marketing's trying to just figure out what they're doing tomorrow as opposed to merging the two and really understanding what it is that they need to work on to make GEO a thing of the future.

Justin Venneri: All right, well, thank you both for joining me today on the Astonishing Healthcare podcast. Christian, Carrie, how, what's the best way for people to get in touch with you? I mentioned on you on LinkedIn, Christian. Carrie, same for you.

Carrie Liken: Any yeah, LinkedIn for me is good. Carrie Liken, same, same here.

Christian Ward: Christian Ward on LinkedIn is easiest.

Justin Venneri: Awesome. All right, well, thank you both very much. Have a great rest of your day. Thank you.

Christian Ward: Thank you, Justin.

Carrie Liken: Thank you.

For more information and to get in touch with Christian and Carrie:

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