In this episode of the Elevate Care Podcast, David Norris, CEO of Affineon Health, discusses the transformative role of AI in healthcare, particularly in alleviating provider burnout and enhancing patient care. He shares insights from his extensive experience in healthcare technology, emphasizing the need for innovative solutions to support healthcare providers overwhelmed by administrative tasks. The conversation explores how AI can streamline processes, improve patient communication, and ensure data privacy, while also addressing the challenges of adoption among healthcare professionals. Norris highlights the importance of creating a supportive environment for providers and the potential for AI to revolutionize patient-provider relationships in the future.
In this episode of the Elevate Care Podcast, David Norris, CEO of Affineon Health, discusses the transformative role of AI in healthcare, particularly in alleviating provider burnout and enhancing patient care. He shares insights from his extensive experience in healthcare technology, emphasizing the need for innovative solutions to support healthcare providers overwhelmed by administrative tasks. The conversation explores how AI can streamline processes, improve patient communication, and ensure data privacy, while also addressing the challenges of adoption among healthcare professionals. Norris highlights the importance of creating a supportive environment for providers and the potential for AI to revolutionize patient-provider relationships in the future.
Chapters:
00:00 AI in Healthcare: A New Era
04:45 Addressing Provider Burnout with AI Solutions
10:50 Operationalizing AI: Protocols and Provider Control
15:56 The Future of AI in Patient Care
21:58 Ensuring Data Privacy and Cybersecurity in AI
25:50 Looking Ahead: The Future of AI in Healthcare
About David Norris:
Mr. Norris is a CEO, investor, board member, advisor, and serial entrepreneur. Utilizing his extensive experience and network, he works closely with investors and boards to accelerate the growth of high potential companies. He has extensive governance experience on a wide range of boards and board committees.
As a serial entrepreneur, he has founded and built companies in a number of different industries and has extensive fund-raising experience, having raised capital from VC, private equity, strategic, angel, and debt sources.
Mr. Norris has held leadership positions in a number of companies including: Co-founder and CEO, Affineon Health, Chairman and CEO, Element3 Health (acquired 2022), Co-founder, Co-Founder and CEO of MD Insider (acquired by Accolade (NASDAQ:ACCD)), Co-founder and CEO of BlueCava (acquired by IDify/Adstra), Co-Founder and CEO of OnRequest Images, Co-Founder and CEO of ObjectSpace (acquired), VP/General Manager at Casco Signal Ltd (acquired by Alstom (ALO:EN)), and Toccata Systems (acquired by Chilton).
Mr. Norris has extensive international business experience, having lived and worked in Europe, Asia, and the United States. He is a regular speaker at industry conferences, has lectured at organizations such as Microsoft and the Harvard Business School, has appeared on business TV programs such as CNN, Bloomberg TV, and has been quoted in publications such as The Wall Street Journal and New York Times.
Mr. Norris has won various awards, including the Ernst and Young Entrepreneur of the Year, the Inc. 500, and The Software 500. He supports a number of charities including the American Diabetes Association and the National MS Society. Mr. Norris sits on a number of boards and is a senior advisor to a number of companies. He is also a very active cyclist.
AMN Healthcare Podcasts (00:00.076)
Welcome to the Elevate Care Podcast, the place where healthcare professionals and visionaries come together to explore healthcare innovation. I'm Nishant Savathson. I'm joined today by David Norris, the CEO and co-founder of Affinion Health. Welcome, David. Good morning. Nice to be here. So the topic for today is AI in healthcare, empowering providers and reducing burnout. AI, of course, has been pervasive. It's a big topic of conversation.
across many industry spaces and markets, but certainly in healthcare. Is that something you've been experiencing? Yeah, I think it's a pretty exciting time in healthcare because obviously over the last 20 years, there's been a lot of innovation and technology introductions in the healthcare, but AI represents the biggest opportunity to make a material difference. And so I'm super excited to be here at this place at this time in healthcare. It's just really, really exciting.
That's terrific. Can you tell us a little bit about your journey in healthcare technology and how you got started? Sure. So I've been in healthcare over 20 years. I started off working on some of the early imaging solutions in healthcare and have worked on the provider side and the payer side quite a bit. I'd say my heart is on the provider side. I think doctors and providing teams have incredibly hard challenges and over
the last 20 years, their jobs gotten harder and harder. There's more documentation and more administrative systems that they have to do while also seeing tons of patients. So as a technologist, I kind of view it as our mission to equip them with the best tools possible. And AI is just a really, really exciting new technology that can help. Yeah, that's terrific. I couldn't agree with you more.
listeners will recall I've shared previously my wife is a physician too and any advancements that are deliberate on the technology side that helps make her life easier, I quickly hear about it. So it could be ambient scribing. And then when I heard about what your company does, was like, yep, I could see this being something that she'd be really, really interested in learning more about. Yeah. Well, I went out back.
AMN Healthcare Podcasts (02:19.106)
several years ago and spent a lot of time with providers just asking about the inbox. Hey, what do you think of the inbox? And the reaction I got was hilarious. There was more passionate hatred for the inbox than I have ever seen. The comments I'd get back was like, I hate it. It's the bane of my existence. I can never get caught up. And I was really taken back by how profound that reaction was.
And it was consistent across 100 % of the providers. It wasn't just a few. So that's what got me so excited about building this business. Yeah. I mean, you you could see it from both ends, right? From a, from a healthcare patient perspective, you know, the provider is much more accessible, which is terrific. And, you know, if you're someone like me, you're going to have a ton of questions, right? So once one question is answered, you ask the next one, the next one, the next one, and the provider on the backside, they're just not getting more time, right? So whether it's a chat message or an email,
And then of course you've got the in-person visits, all the charting. just feels like it's nonstop. So to hear that you and your teams are focused on providing relief, so providers can focus on providing care. I just couldn't think of a better solution or more opportune time. Yeah, I think it's interesting. The electronic health record introduction starting back 15 or 20 years ago was a good thing. It standardized patient charts and interact, kind of the ability to
share information across health systems. That's all good. One challenge though was that it didn't take a lot of input from providers. So it was more around billing. And so as providers have now, you know, had to experience the brunt of the introduction of EHRs, all of us as patients love it because we can send our doctors messages and ask them all kinds of things. But for them, they still have to see 20 patients a day and, you know, they still have to stay up late at night catching up on things. So
So in some sense, they sort of got squeezed in the middle between this rollout of EHRs and the demand to continue seeing more more patients. So it wasn't really fair for them. I agree. So you've touched on this a little bit so far, but if you kind of crystallize it, you think about physicians, providers, they're experiencing burnout. How does your solution specifically help them? So you talked about the pain points, of course, but where your solution's been in place. Can you share a little bit about how providers have reacted?
AMN Healthcare Podcasts (04:45.07)
Yeah, well, our solution is pretty exciting because if you think of it conceptually, it's very easy. If every provider out there could have a dedicated assistant to triage their inbox every day, they'd love that. But of course, there's not enough budget to hire an assistant for every provider out there. So what we've done is built an AI agent that can, under provider control, triage the inbox 24 hours a day, seven days a week.
cost about $2.50 a day. So this is a perfect example of how AI can help in an area where we're really giving providers the capability that they would love to have, they just haven't been able to afford. And the interesting side effect is that as our AI agents are triaging the inbox and sending messages to patients saying, we got your lab results back and they're normal, that
gives the patient better satisfaction because now they're getting a quicker response rather than having to wait a week. And we've probably all had that situation where you get lab results back and you're wondering like, hey, what does this mean? And your doctor is not telling you anything. And you're like getting a little more anxious and a little more anxious. We can actually resolve that now because with our AI agent, let's say a patient's, know, and light, let's say they have an LDL and it's slightly elevated or an HDL and with
the AI agent, we can very quickly send them a note going, hey, wow, that's slightly elevated. It's not clinically significant. You don't need to worry. So we bring the stress down for the patient. And we do that within a few minutes of the lab coming in, let's say on Sunday morning. So now the patient isn't sitting there worrying and getting ready to send a note to the doctor saying, what does this mean? And that then, of course, compounds the inbox problem. Yeah, no, I think that's terrific. There have been cases where
Family and friends will receive lab results before the doctors have been able to even see and review it themselves, right? So to your point They're left seeing 10 20 30 numbers try to interpret and you see one number that's off But it's about how it works collectively comprehensively in how you diagnose but if you have an AI agent that can in a more timely manner simply just in time effectively, I can see that actually just
AMN Healthcare Podcasts (07:05.644)
You're also solving for patient care outcomes with that, right? Not only are you helping alleviate provider burnout, but you're also solving for patient care outcomes, which is, end of the day, the goal too, right? So. Well, I think that's one of the areas that most people don't recognize is with AI, it can do a few things really, really well. Like in our system, we can speed read an entire patient chart, know, 10 years of history in three seconds. So.
with a provider that's reviewing lab results. let's say lab results come back and they're a little bit more complicated, so they're not normal. One of the things that we can do is if you can imagine doing the data mining of going down to the patient chart, digging to the surface, all those things that are really important to know about that patient. And then within the context of that patient, looking at the lab results and surfacing the things that would be most important for the provider to consider.
is helpful. it's basically we're speed reading the chart and saying, hey, look here, this might be important. Now the provider can use their clinical expertise in a very focused way rather than having to sit there and spend 20 minutes trying to read 10 years of history. We can do that for them and allow them to really look at the things that are important. And that to me is, I often say making providers superhuman. That's what we should do is let them use their clinical expertise where they need to.
want to rather than filing some document they got copied on that they didn't even want to see in the first place, which happens a lot in health care. Sure. So maybe walk me through, you probably have different providers, physicians on different ends of the spectrum, right? Some are avid adopters of new technology and others are a little bit more cautious curious. So for the one that's a, if you think about it more broadly, do you,
How do you get folks over that adoption curve, right? If there's somebody that's kind of, you know, wants to see something more tried and true versus bold and new, just can you maybe walk me through sort of the journey y'all have been on there? Yeah, we work with a pretty broad set of providers. You know, we've got customers that have thousands and thousands of providers, and then we have individual practices that have like one or two docs. What we've seen has actually been very interesting from an AI perspective.
AMN Healthcare Podcasts (09:28.812)
You know, one might think that there would be the early adopters and then the late adopters, but we're really not seeing that. I think the problem of the inbox with providers is so profound that most providers just don't care what it's built using. It's kind of like an MRI machine. Like if you looked inside of an MRI machine, do you think there's any AI inside there? Well, sure, but they don't care. They just care, it do good imaging? And I think that's what we're seeing with this is they just won't help with the inbox.
The fact that it's AI, they don't really care. As long as it works and has reliable output, they don't really care. so we haven't, amazingly, we haven't seen that kind of typical early adopter curve. We've just seen doctors desperate for help. That's terrific. Kind of reminds you of the, you know, a lot of operators have this point of view, never let a good crisis go to waste. It sort of seems like there's enough pain in the system where people are just so open to...
a new and better way of doing things and doing them differently. as you do you have, does your AI have the intelligence to kind of scan through and say, hey, this is maybe a high risk sort of thing that it should be deferred for the provider to review themselves versus AI sort of like, or does it does your agent work in the sense that you provide a recommendation, the provider reviews it first before it's sent just.
Maybe walk me through how it's actually operationalized from that standpoint. Yeah, it's a great question. with a human, if you had a human triaging your inbox, you would say, hey, do these things and don't do those things. And so with AI, we do the same thing. It's done in a thing called a protocol. So we have a set of protocols that very specifically say what we should handle with AI and what we should not handle. And a great example would be, let's say you get a normal lab result back.
really would prefer not to spend time on this. Like, just tell the patient it's normal and move on. But there's certain cases where you don't want to do that. So an example would be if you had an analyte, let's say like a PSA, and the PSA moves a lot in a short period of time, but still normal. That's clinically important. So the protocol says that if that occurs, you need to leave that in the inbox and make sure that the provider sees it because that's very important.
AMN Healthcare Podcasts (11:47.628)
So the protocols are what give the providers complete control over what the system does. So it's not like the AI is off doing its own thing and trying to figure out what's important. The provider is saying, I want you to do these things, don't do those things. And that strict control, we believe, is where AI should be right now. AI is not perfect, and providers need to use their clinical expertise in a lot of areas.
I think has been the secret to why this solution has been so broadly adopted and so popular is that it's helping but not doing the work for the providers, doing what the provider says. Yeah, and the protocol is kind of a path to trust with the provider too, ultimately, right? That over time, I confidence levels will increase and it'll start to take on more more and more. Exactly, exactly.
So in our system, we handle some things automatically based on the provider's direction with the protocols. And then other things that are more complicated, we will do some of the legwork to prepare so that the provider can then review the right information faster. So we help on both sides, whether we can do it under provider control for the provider or whether we're just helping the provider. Smart. OK. So that kind of ties back to your comment earlier. You can review.
call it 20 pages within three seconds. And what you do is you surface the key details information for that provider to then make the call because the provider has maybe said, hey, when it looks like this, these are the protocols, I'll do it. But you're still helpful, right? So you're still reducing that time spent ultimately overall. So that's terrific. Yeah, exactly. And there's no magic to it. We're saving clicks and scrolls and all the kind of things that providers would otherwise have to do. in
And EHR, that's what takes a lot of time. When you get a provider having to go through 100 lab results every day, there's a lot of, I'm going to click on this, and then you have to wait for the EHR to load. It might be five seconds to load, and then you've got to go to another one. It all adds up. And one of the interesting things is we're saving about five hours a week for a provider today. And that's great.
AMN Healthcare Podcasts (14:01.55)
But one of the things that we're hearing from the providers that is really interesting is that we're reducing the cognitive load of how hard it is to do this so they can then use that energy when they're actually seeing patients or working on a complicated case. We're working with some providers to try to figure out how to measure this. It's really interesting that, believe it or not, some of the most mundane tasks eat away at providers' sort cognitive capability. I had a provider the other day say,
I'm a very different doctor at 8 a.m. than I am at 5 p.m., which is a little frightening if you have an appointment later in the day. So I think AI has a capability here not just to save time, but to save that cognitive ability so they can focus it in an area that's most important. Sure. No, I mean, I think about it myself personally. If I need time to think slow, I'm better in the morning. And if it's things that are thinking fast, I do it later in the day.
Provider you don't have the luxury of deliberately scheduling which cases you get at which times of the day is here You used action. Okay, interesting. I was just thinking through that out loud a little bit It's a little it's a little concerning like depending a lot of surgeries are scheduled first thing in the morning. This is a good thing, right? It's a question for you you talked about you know, possibly giving five hours back Do you anticipate they'll be able to keep those five hours or do you see hospital and healthcare systems?
giving them additional things to do to fill up those five hours. Just based on what you've seen, you've talked about 20 years in the space. And what I'm trying to get at is does the space and the market and the system start to recognize there's a limit in how do I manage and solve for provider burnout and start recognizing the value of these tools that are being. And what you try to balance it out against is ultimately all this stuff is a business too, right? So there's a productivity driver and a metric just
Just curious kind of how you think about that evolving or not over time. Yeah, it's a very insightful question and I two years ago had a, I think one impression and today I think I have a little bit different impression. So what we've seen with the large health systems is what you would expect. They care a lot about their providers and they care a lot about driving more revenue, which generally means more patient visits. So what I've seen is that
AMN Healthcare Podcasts (16:23.534)
Most of the systems that we work with that have thousands of providers really are more focused on giving the time back to the provider to balance their workload rather than trying to push them to see an extra three patients a day or something like that. And you could imagine both scenarios, and I don't think there's any one way that it would work, but I'd say right now 70%, 80 % of what I'm saying is.
They want to give providers a life back and use that to retain those providers because it's so expensive for them to replace a provider that burns out. I would have probably said two years ago, I probably would have said, you know, more of them would have tried to drive more revenue. But today we're not seeing that. We're seeing systems really try to take care of those providers, reduce burnout, give them ability to have dinner with their family and not have to go get in the inbox for another two hours.
That's what I'm seeing. Yeah, you're looking at the total cost and the cost of losing one is actually more expensive than an additional patient two or three to your point. Well, the quality of care to your earlier point, you can only do so much when you see so many patients. At some point, you become a less effective doctor at 5 p.m. So if you give people a little bit more time, and what you'll hear today is...
You know, you go to a doctor and say, hey, what do you do with the inbox? They'll say, well, I squeeze a little inbox time in before the patients and I squeeze a little in between patients and then I end up spending a lot of time after dinner. And so by taking five hours a week and just giving some of that time back, what you'll find is that they will take a moment. Maybe they'll have lunch at their desk where in the past they wouldn't even eat. And so it's all those little things that add up to try to really retain the quality physicians that these organizations have that they'll otherwise lose.
That's terrific. obviously very focused on provider kind of alleviating burnout and load with the inbox. Just where do you see broader adoptions of AI as you think about kind of the total workforce of healthcare more broadly? Just kind of where do see it starting today? And then maybe take a five, 10 year view, just given the current adoption rates you're seeing. Well, I think
AMN Healthcare Podcasts (18:38.574)
I kind of view the inbox as a starting point for the kind of things that we're doing to deliver value for the providers. We're moving in and we're about to introduce a CareGap closure solution that leverages the inbox as a way to help get patients to do those things that they might not have done. know, doctor orders a cologuard or a colonoscopy or a mammogram. 30, 40 % of the time, patients don't do it. And so we now have the ability to
help the providers, so think like making them superhuman, to send a very customized note to the patient articulating what was discussed in the last encounter and reinforcing that, hey, we really need to do this test. And AI is really good at having an empathetic side to the communication. So we can take an empathetic tone, like, hey, I know you're worried about the results. I know it might be a little scary, but we still need to do that test. And it's important.
And so by doing this, now you can go from solving an immediate pain point with the inbox to solving a bigger problem in closing care gaps, which a lot of large organizations struggle with how to do that. You've probably got a reminder from UnitedHealthcare, you should get your wellness check and delete, delete, delete. Nobody cares about that. That's a big problem.
I agree, especially for the UnitedHealthCares of the world. It's patient adherence to doctors orders is really what it comes down to. People get busy, they're well intended, and then you have different cultures. There's kind of cultural norms and how you handle that. So if you can leverage AI to sort of advance or improve upon patient adherence, I think you ultimately deliver better patient care, which is...
which is the ultimate goal. Exactly. It's interesting because my pup, you know, I take him to the vet and my vet follows up a lot more than any doctor I've ever seen. I mean, I get notes back, you know, how's Wolfie doing? How's that drug working? How's your feet? I'm like, wow. I mean, literally, wow. And then you go to your primary care physician and unless you send them a note saying you need something, you'll never get follow up. And so that's an example of why care gaps exist.
AMN Healthcare Podcasts (20:59.106)
because the doctor orders it. If you don't want to do it, they're like, it's up to you. You didn't do it. And what we're doing is introducing AI to help them. Let's say a provider has 3,000 patients on their panel. What we want to do is maintain a better relationship and more communication between the provider and the patient in between visits. How many times have you got a note from your doctor going, hey, it's great to see you. It's been three months. How are you feeling? Never happened. But with AI, it can.
Terrific. So you think about AI in cybersecurity specifically, there's data privacy, all these concerns. I think every other week you'll hear about some hospital healthcare system receiving an attack. Just what steps do you take with Afenion to solve for patient data privacy as well as cybersecurity? We took from the very beginning a very, very strong approach.
partially because of all of the attacks you read about, which are a little scary, but also it's just the right thing to do. So with our system, we bring in patient information, but we de-identified immediately so that everything inside of our system is dealing with information that doesn't have the specific name and identifiers for the patient. And that's critical, especially with AI, where you want to train a system on how to do certain things, but you don't want to...
really share that specific patient information that is really unnecessary. So in our system, we've taken a very strong approach. We're SOC 2 certified, so we went through a very rigorous process of putting in place those things to secure the information we have, and we de-identified it, and of course it's encrypted. So in the end, even if somebody broke in and they got a bunch of de-identified information, they wouldn't know what to do with it. So that...
That is our approach and I know every organization can't necessarily do that, but for us, that ensures a lot of security and safety for the patients that we deal with, you know, their private information. Okay, terrific. Just, you know, you talked about lot about how you get a lot of providers and physicians over the adoption curve for AI specific to your solution. When you think about more broader applications of AI across healthcare,
AMN Healthcare Podcasts (23:22.998)
Any advice that you would have for providers or physicians to help get them more comfortable with entertaining and it could be protocols as you suggested you use, but just any thoughts, suggestions you see there? Yeah, a couple of thoughts. One, more and more, it's common that organizations are forming an AI governance committee or board that can set in place some standards around across all the systems that you're adopting. What should you look for?
I think that's a reasonably good idea. A lot of large organizations have begun doing that, but some of the smaller ones haven't. And I think as practices are going to adopt more and more AI-based solutions, it's important to at least think about those key elements like what is it okay for it to do? What is it not okay for it to do? And what kind of transparency? If a patient's, one of the solutions we're introducing is a great example. We're introducing a voice agent that can call a patient and
tell you about your lab results. And the problem is fascinating because most of the time, most practices will have a staff, a little pool of people that call patients and they try to get you on the phone. And then they leave you a voicemail and then you call them back and they're on the phone with a different patient. So this is never ending phone tag. And that's frustrating for a patient. So with AI agents, you can actually just call the patient and talk to them. And if they call back, you can always answer the phone 100 % of the time.
So in that example, there's a transparency need, which is you're talking to a voice AI agent. So in our system, we identify right up front, I'm a voice AI agent for this practice, and I'm here to help you understand your lab results. And by doing that, that gives some transparency to the consumer that they're not talking to a human. Even though it may sound really good, it's not a human. So that's an example where practices need to be considerate around
putting in place some standards around like, should you disclose that or not? And I think that is really going to be critical as people adopt more more systems where there's AI everywhere, that concept of what is right for your practice, what should you do and what should you disclose? It's an exciting time. just, you you think about the future. I think it was the CEO of Google that described, you know, AI is the equivalent of fire.
AMN Healthcare Podcasts (25:50.286)
right in terms of the impact it can have broadly. I mean, just a little glimpse that you're giving us here on this podcast with your organization and your company. It's incredibly exciting. So, you know, with that said, when you think about if any and how, you know, what's next for you all. So you've started here. Can you talk about any key feature or capability releases that you have coming up around the corner? Well, we've got a lot. It's it's an exciting time. So we're really trying to help providers initially with the inbox and we do
things like prescription renewals and we help them with lab results, things like that. As I mentioned, we're introducing a voice agent to help call patients and we're doing a care gap closure. So those are a couple of features that are coming up later this year. As you look out over the next, two or three years, you can imagine the communications between the providers and the patients and how that could be improved. And so that's where we're going. Today, know, most
patients only talk to their doctor when something's wrong. You know, that's what happens, right? It's kind of like getting your car fixed. You go to the repair shop when it's broken. With, with Afenion, what we're really moving towards is helping to create better communications when things are not broken so that you can actually improve healthcare. And we've seen this over and over and over. A lot of patients will not go to the doctor. Something's bothering them, but you know, I don't want to bother my doctor and it's not that bad.
and those tend to become the worst problems that end up costing our healthcare system billions of dollars. We want to solve that problem. We want to create a communication between the patient and the provider that is a relationship, not just a, I'm broken, I need to get fixed. And that's a big thing and it's not going to happen overnight, but just imagine the scenario where you go to the doctor,
And then out of the blue, you get a message just checking in on how you're doing. That scenario today just doesn't happen in healthcare. We're going to make that happen. I love it. I love your solution. It's just so very thoughtfully done and it's a great application and use case. But I could also see it sort of being a cornerstone of the hospital healthcare system AI strategies for many of those that you're working with.
AMN Healthcare Podcasts (28:15.758)
David, thank you for spending time with us here today. Just really enjoyed the opportunity to meet, get to know you and learn more about your organization too. Well, it was a really good discussion and I appreciate you highlighting the kind of advancements that are occurring in healthcare. It's a very important topic and I'm glad to have been here. Thank you for joining us today on Elevate Care. If you found this episode valuable, please consider sharing it with a colleague and subscribing to our show on your favorite podcast platform.
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