AI’s Impact on the Health Care Investment Landscape

Tony Roth, Chief Investment Officer

Tom Lawry, Managing Director, Second Century Tech

Tony Roth

Welcome back to capital considerations. I'm Tony Roth, your host. I'm excited to be joined today by Tom Lawry, who has been helping shape the future of health care and artificial intelligence long before most of the industry caught up.

Tom is a globally recognized advisor on AI driven healthcare transformation and the bestselling author of Hacking Healthcare and Healthcare Nation. His work has appeared everywhere from Harvard Business Review to Forbes, and he's been named one of the most influential voices in AI and digital Health by the Harris Poll. Tom, welcome to the show.

Tom Lawry

Hey it’s great to be here. Thanks for the invite.

Tony Roth

So I thought I would kick it off with a little anecdote that some of our listeners have probably heard from me already. What's interesting to me about the impact of technology and AI specifically on healthcare is that there are sort of two kinds of values or benefits, if you will, as I think about it, that we can derive and try to put our fingers on. One is better outcomes, better quality healthcare, and the other is, more efficiency, better revenue, better opportunities for health care companies, etc. And many of the things that we're going to talk about today have implications or have characteristics that impact both of those things.

So recently, I went to the UPENN Outpatient complex and Radnor, Pennsylvania because I cut my finger about a month earlier, my finger was still hurting me and I went in and I spoke to a an RN registered nurse, and took about 5 min and I explained what had happened and it gave her a lot of information. And at the end of the day, the computer told her that, hey, if you really think, that the patient, you know, needs a treatment plan, you might want to suggest an x ray because maybe he has a septic arthritis, but you can probably wait on that, and it clearly wasn't infected or anything, and it took about 5 min and I didn't need to see a dr. because there was a treatment plan prescribed. In the background, there were doctors that were off site that were checking all these, these situations. And so when I walked out of that experience, I was really fascinated by the fact that not only did the AI create significant efficiency in the ways that I've just described, but it also potentially created better health care as well, and I think that may be what we could do Tom, is sort of segment health care into a few areas. Maybe health care delivery, like the example I just gave, pharma, devices and then maybe insurance and payments, but let's just start with delivery. When you think about how healthcare is delivered and you think about AI, where are we? Are we in the first inning of improvement? Do you see bigger improvement on the quality of health care delivery or do you think it's more on efficiency? Take us through, you know, how you're thinking about it.

Tom Lawry

Yeah, well let's just let's just riff on your story for a minute, because in that are, are probably several lessons. One, to your point, in general at a high level, the use of AI in in health and medicine, I mean the holy grail really is the quest to be better and better takes on many dimensions. So what you just said about, you're sitting there with a human provider, they're looking at your finger, they're looking at your record, you know, they, they maybe using some form of AI to see if there's anything else they should be thinking about. I t's a really great story because it represents the essence of how AI drives value when it comes to clinical care.

For the most part, and I think it's interesting the American Medical Association coined the term augmented intelligence rather than artificial intelligence probably 15 years ago in their first white paper. But I think it's a good way of, of starting this conversation where done right AI doesn't replace that clinician, the dr. or nurse, instead, they augment those humans to be better at the things they care about. Second, any time and it's still being talked about and written about, but anytime I hear the things like, well, maybe we should be training fewer radiologists because AI will replace them, it tells me two things. One, they don't understand what AI is good at and what humans are good at. And two, they probably don't really understand what radiologists actually do. I mean the beauty of AI is this, our human brain is such an amazing organ, it reached a point of figuring out how to outsource things that previously only human brains could do, which is what we call AI. So things like pattern recognition, variance analysis, sorting through all kinds of data on a massive basis that a human can never go through and spot patterns that's really good at. But at the same time, and I think your story illustrates this, humans are uniquely qualified with things like wisdom and judgment and common sense and experience. And when you bring those two things together, that's when AI magic happens.

And the whole point of this is AI done right is where we take the best of what it does and bring it in behind those clinicians, those knowledge workers and healthcare to make them better at what they do. That's the way it adds value and when processes are set up to take advantage of that, that is truly when AI is augmenting all those skills that are unique to that dr. and that nurse.

Tony Roth

When you think about my example and what you said, would you say that AI in the, in the delivery context of healthcare is really going to ensure that the patient receives sort of the best possible diagnosis coupled with a more efficient or a, a more proximate, chronologically speaking treatment plan, it's going to help that whole ecosystem so that somebody walks in without even seeing a dr. because in my example, the computer will listen to what I said and it suggested a treatment plan that was then reviewed off site by doctors very efficiently. I got a diagnosis without even seeing a dr. that took advantage of all that wisdom that had been accumulated with a treatment plan that was really laid out right in front of me. Like obviously again not a grave situation, but representative.

Tom Lawry

You know, before you presented to UPENN, you did your own homework and you went on online and chances are you use some form of generative AI tool and plugged things in and you got information back, which is what many Americans and people around the world are doing today and which brings us back to people saying well this is eventually going to replace physicians and caregivers. And I'd go back to what I just defined when it comes to how AI adds value. A lot of times generative AI can be very convincing in what it's saying, whether it's to you as a consumer for advice, even when it's a physician looking for additional clinical decision support. But it's those unique things that humans are good at like that reasoning, that wisdom, that common sense, that can often make a key difference between doing what seems to be right according to AI, but could be very wrong when it comes to what you should be doing. And, and so I teach classes to physicians and other clinicians on AI bootcamps. One of the things we often do is I, and I've used AI to do this and I tell the story to your point of, you know, I've used AI in a lot of data and, I I've got conclusive almost perfect correlation on things like, did you know that for per capita cheese consumption in America is almost perfectly correlated to the number of people who die by becoming tangled into their bed sheets?

Tony Roth

Ha.

Tom Lawry

So think about that for a second.

Tony Roth

I shouldn’t laugh at that.

Tom Lawry

There are times where, you know, a physician or nurse, clinician with all of those things that are unique to them would look at something being recommended by AI and find it equally laughable to  per capital cheese consumption, correlating to people who die by becoming tangled into their bed sheets. And the point I'm trying to prove is done right, it's a matter of both, but it's mainly AI in service of all those things that we as humans are uniquely qualified to do.

Tony Roth

The reference to the cheese and the bed sheets is to simply say there's clearly no causality there, right?

Tom Lawry

You got it. Correlation does not mean causality, but it's just one of several examples of how things like generative AI in their in their quest to find knowledge and patterns can sometimes find patterns, but those have to be sorted through the lens and the filter of, you know, those things that still are unique to the brains of human beings, including those physicians who are highly trained, not just with the medical training but all of their experience, what they've seen and what we often refer to as wisdom and common sense, which is a big part of the treatment of any sort of medical condition.

Tony Roth

Okay, so I'm inferring from this that you don't feel that even with another five or ten years under its belt, the additional data, the additional refinement of the algorithms and the additional computing power, so on and so forth, that will be garnered over that period of time the next decade, let's say, will nonetheless, still not bring the machine to the more proximate area of the common sense of the dr. or the wisdom of the dr., and you've been in this for a long time. Many of us that are new to this say that that's what our answer would be. Oh, well, it's see, you know, it maybe coming up with some ridiculous conclusions, like Tony needs an x ray for septic arthritis, but in five years it will know enough not to suggest that because it will have had, you know, other Tony's that will have come in with, with silly, you know, finger problems that didn't have septic arthritis, so they'll eliminate that. Why do you feel that it's not going to move so quickly to replace that wisdom factor, that common sense factor?

Tom Lawry

Well, I think as it can continue to get more sophisticated, it's going to be able to mimic, not replace more of those human functions. But I, I guess I'd look at it two ways. One, what you're really talking about in my view is a little different topic that's not getting much exposure. I mean think about this, not too long ago, every decision in health and medicine, every decision large and small was made by a human. Today we have the ability for those, some of those decisions to be made by or supported by AI. So when I look at that, when I look at where we are and where we are going, and I also look at the unique nature of medicine, I think there's a whole branch of decision science we're not talking much about that's evolving, and so before all decisions were made by humans, today and going forward what we're really looking at is we need better processes. It's what I call creating systems that manage decisions about decisions. So think about it. You know, maybe your cut finger, that's a minor injury, and maybe things like that will be closer to automation with AI. But if you've got some type of diagnosis, you're a 52 year old woman with a one of a almost gazillion malignant breast lumps, AI can do a lot to bring together data suggesting some of the best treatment paths, not only based on outcome but based on the things that perhaps that woman wants, whether is it, you know, five year survival rate that's her key goal, is it a minimal impact on her, you know, her system as she’s going through treatment, but these are decisions that are very complex, AI can do a lot to aid, but in the end decisions like that to me, need to be human based where that clinician in conjunction with that patient is going to own that decision on best path, best treatment and frankly until the laws change, they're also going to have the legal liability to own those things. So, so making decisions about decisions is something that I think people should be thinking more about. And this is happening not just in medicine, but really across all industry. Finally to your point, if we take what you're saying or postulating to the extreme and I believe it is a risk factor, we may reach a point where people believe so much including clinicians that, you know, they're just going to go to AI and look for the answer, that we start getting into what's known as authority bias, where somehow we think because AI is so good and it's going through all of these data resources that I can't possibly comb through as a human, that the answer they bring back is right. And, and this is where once again, time and time again, and I've done this for a long time, I'm going to bet on AI will get better, but it will not replace those things that are uniquely human when it comes to what a dr. and what a nurse does. You know, let's check back in ten years, I'm pretty sure I'm right on this one.

Tony Roth

Okay, so we've talked about delivery of health care and how AI can, I think really take a much larger portion of the population and bring them to the apogee of delivery and get them with the right type of decision management, if you will, and sitting on top of the AI, a much higher percentage of the population can get better diagnoses faster, better treatment plans et cetera. Let's move now and talk about what the treatments are from a pharma standpoint or a surgical standpoint or a medical device standpoint, in other words, do you think that AI is going to play as significant a role there in expanding the tool kit of medicine.

Tom Lawry

The opportunities are almost limitless. So I've just talked about the difference between what AI does well and what humans. But when you bring those two things together, again, the best of AI coming in behind any clinician, any knowledge worker on healthcare to make them better at the things they care about, that's where there's so many possibilities. So, so today, right now we're, we're still in that phase where AI is very much the shiny object in health and medicine. So as we're recording this today, the largest health IT conference in the world is happening in Las Vegas. And it's got an exhibit hall that if you started walking in the morning and spent 8 hours walking up and down without even stopping, you couldn't get through all of the vendors. Every one of them pretty much are, are, you know, talking about the AI that's infused in their products, which is great and many of them are very useful. But the idea here is, we need to go from AI as the shiny object to AI with specific, well curated use cases. It's interesting one study shows the majority of AI investments were not tied to clinical or business goals. They were tied to fear of missing out. So that's changing. All of the advisory work I do with my clients, it's very grounded in in repeatable use cases where we can show measurable values. So when I look at that right now, some of the top things happening in the provider side are things like the use of what's known as ambient intelligence.

It is really going a long way to start giving physicians and nurses back their time. So think about it. Typically if you actually go in to see your primary care doctor I want you to think about this. When I go to my dr. and I, I love my primary care physician, whatever I actually go in, I'm in that little cubicle, he walks in and the only time I ever looks me in the eyes is when he walks in and says hi Tom, why are you here? After that, what does he do? He goes to the corner, he opens up his electronic medical record, and hunts and pecks and talks to me over his shoulder. So ambient intelligence allows them to walk in and have a conversation like doctors used to do, looking you in the eye, having a conversation, and in the background, AI is, is taking notes, recording all of this. When that dr. leaves is doing things like coming up with initial triage diagnosis, assigning an initial diagnostic code, flagging any follow up.

It's taking that away from the dr. at the end of their shift, they go through it and say yeah that's right and clicks ok. But in America many doctors spend more time doing administrative work than they do seeing patients. We have a huge shortage of doctors and nurses. It's going to get worse. We've got a huge issue with burnout that's getting worse instead of better. So, so imagine being able to eliminate that kind of work and free them up to spend more time with patients, more time doing research or actually, God forbid, something radical like getting home for dinner more often to be with their family. So these sound like small things, but they're extremely important when it comes to what's happening. You know, beyond that, we're seeing a lot of uptake in measurable value in things like AI doing what I call pre reads for diagnostic images and pathology. This is not replacing what radiologists or pathologists do, but it's allowing them to have a different starting point than if they're going in cold to look at an image. So the ability to spend more time doing that read using that wisdom and judgment or the ability to get through more reads per shift, is a definite measurable improvement. So these are just a few things. And then, we have to look at all specialties for not only how AI makes them better, but how they're going to change the very nature of these specialties. And one of the things I'm particularly excited about is the rise of a new specialty called oculomics. So, so quickly, you know, I was part of a support group working with some brilliant physicians and data scientists 17 years ago to say, can we take a picture of the back of the eye and, and use vision API to do pattern recognition to use the retina as a predictor of diabetic retinopathy leading cause of blindness in America. And you know that was one of several early groups that that proved that out. Today that's commonplace. You go to your eye doctor, you automatically get that taken. But here's the thing. We're, we're seeing new data to suggest that, you know, that same retina, image can not only help predict eye disease, it can predict things like risk rate your propensity for things like heart disease, neurological conditions. So this is what we're seeing. It's getting a lot of uptake as far as oculomics being basically use of data from the eye to make all kinds of other decisions on our health on chronic conditions. So as this happens, you know, I'm pointing out to everyone, how does this change these specialty practices? How does it change what the consumer can expect going forward?

And if we want to take it just one step further, the FDA recentl approved an AI algorithm that allows you to take a picture of the back of the eye and clinically diagnose diabetic retinopathy from any handheld camera. So perhaps you've heard it here first, but I already believe that we already live in what the planet of the apps. I mean, think about everything you do with your smartphone. It's a smartphone because most of what you do, there's AI running. So I predict in the next few years there'll be an app on everyone's phone allows you to take a picture of the back of the eye. And will produce clinical grade information on a variety of health conditions. And what I'm suggesting is in the next five years, we're not going to get more efficient, we're actually going to be changing the nature of how medicine is practiced and how consumers experience it.

Tony Roth

Well, yeah, I mean it sounds like the AI itself is through the power of the statistical analysis and inference et cetera, it makes data that we didn't understand, by identifying the right, if you will, independent variables and attaching them to the right dependent variables using statistical concepts because that's what AI really is. It's just statistics and probability, right? So, by trying the data that was gleaned from the back of the eye and then seeing whether or not it correlates with these other diseases, and in fact, there are high correlations, all of a sudden we've been able to through AI create a whole other layer of relevant data to not just that specialty but many other specialties that may ramify out from that experience that that particular clinical situation has. And that's really exciting and it comes from delivery, and it comes from, I suppose, the ability of AI to generate a whole other layer of, of relevant information.

Tom Lawry

And again, if we spend more time looking at this, I, last year, I would just say I had a large association of eye doctors as a client and as we're going through this, it was frankly freaking some of them out to say this is going to ruin our practices. I was like, well, no, it's going to change your practice, but you know that example I gave of imagine an app on a phone that allows a consumer to take a picture of the back of the eye and produce clinical grade information on a variety of health conditions. So will it dramatically change things like referral practices? Yes. But imagine every time that happened and there's something that's clinical grade information that suggests something needs to be followed up on. Imagine your specialty, your practice being able to catch that slipstream from the moment that image is taken and get someone into the system earlier perhaps to diagnose and do a better job of forestalling or treating something. We've just potentially not already improved quality, we've improved that patient or consumer experience with that one change. And, and this is where, if all people think about is AI to make the current way healthcare works more efficient, that's what happens in the early phase of this, but I think in the next few years we're going to see it changing practice models and probably changing economic models, particularly here in the United States.

Tony Roth

So let's go back to some of the tools that clinicians use like pharmaceuticals or the availability of procedures with different devices and such. How is AI going to help expand that toolkit, will it? So maybe just talk a little bit about that for us.

Tom Lawry

Yeah, we spent a lot of time on provider leadership maybe to a little on pharma and life science. So, I mean, to your point, let's take a snapshot of how pharma and life science works today.

You know typically it's 15 to 16 years to bring a drug to market. An average of $3 billion to bring a single drug to market. Nine out of ten candidates fail before reaching patients and we're seeing increasing regulatory pressure. So, I think pharma is probably the highest risk business when it comes to a sub specialty within health and medicine. So, you know, our ability to say, well, what if we can use AI to make that more efficient? And some of that's not just efficiency and shareholder value of those companies, but what if we could actually help them drive better drugs faster to market? Especially around things like rare diseases where all of a sudden we're finding new opportunities to be better because we've got more efficient processes. So I, I look at things like and the data's there, there's one study that shows five out of 15 drug candidates in AI focused pharma companies advanced to clinical trials in under four years.

Compared with the historical average of about six. You know, there's some that are suggesting that AI efforts can reduce the time and cost of drug delivery by at least 20 and upwards of 50 %. So we're, we're seeing some of the early things. And then, you know, when it comes to AI opportunities in pharma, I mean typically when I look at the pharma industry I break it down to preclinical, clinical, marketing, and sales, and with each one of those things, there are opportunities. So, you know, things like, and I don't want to geek out on your show, but you look at things like molecular identification and the structure design. We've seen huge breakthroughs in the last couple years around protein development. And matter of fact, two years ago, won a Nobel Prize for some of this work, much of which was done for the first time because of AI. So we start looking at things like cloud design and the things drug companies are trying to do on development. I start looking at things like filling clinical trials and whether that's doing a much better job of getting all the right people at the right mix or whether it's the use of what's known as synthetic data or digital twins to start looking at the things clinical trials eventually will show, but to get out ahead of that and just be generally smarter.

But there are a host of things already happening. And again, I think everyone, you know, even the companies leaning in on the pharma's side are still very early in the journey.

Tony Roth

You talk about the economics of healthcare, Tom? I think we should probably spend a little bit of time there maybe end on that, but it's you know, I would say that right now my experience, again, I'm a data point of one, but I think I'm fairly representative, is that the healthcare system is fundamentally broken from an economic standpoint in this country. So as an example, you know, my 19 year old went to the emergency room. She spent about 4 hours in the emergency room and she had a bill of $19000. And all they did was give her an ultrasound.

The outcome of that, and I'm going to I'm going to say this is as long as everyone promises not to turn me in. The outcome was the health care company paid some negotiated rate and then there was a stub amount that was not insignificant, that the hospital had charged me and the hospital called me up and after my non payment for three months and wanted to negotiate and I asked them, well, I said to them you've already gotten, you know, for 4 hours, you know, eleven or $12000 from the healthcare company, do you really think you're entitled to anything more than that and I never heard from them again. So, you know, it seems as though we're really in a very fundamentally broken economic situation, and I won't go on around the layers of health insurance issues that exist. Is there anything that could help us wend our way out of that problem or do you think that is endemic now?

Tom Lawry

Done right AI can do a lot to make the American health care system more efficient. It fundamentally will not change the these reasons why the system's broken and heading in the wrong direction. And this is where we have things like, you know, and I have the privilege of working around the world, so in the last year I just came back from South Africa. I've worked on Australia, Singapore, and our model is like no other model in the world. And so we have things like the break fix model. We spent almost 5 trillion a year. Of that $5 trillion, only 3% is invested in prevention. The rest goes to break fix where hospital organizations only make money if they take care of you when you're sick or injured.

And I'm the former hospital executive and a long time ago I used to go out to the Rotary Club and talk about how we cared about your health and wellness, and then I go back and then close the door and would have a meeting in the finance committee and I get beat up a little bit because we weren't making enough money, which meant I had to go out and recruit more invasive cardiologists and orthopedic surgeons to do hips, which is, you know what makes a lot of money. So, I mean, there are many things and having said that, I want to make sure everyone knows, you know, we have amazing pro some of the best caregivers in the world. We have good people doing their best to run a very broken system. So this is not, it's what I call the blame game, so many times people want to blame someone and it's no one's fault other than we we've got these wacky incentives that are driving good people in $5 trillion of your money in the wrong direction. So AI is going to help, but it won't fix those fundamentals. Something else has to change.

Tony Roth

So to wrap things up, we're all consumers of healthcare. We all get sick, we're all aging . Do you have any words of wisdom as we negotiate our own the system for ourselves, for our families?

And it's a bit of a leading question because my experience has been that, and it's been the case prior to AI and it's as much the case today in my limited experience with AI that everybody needs an advocate in the system if they have not a finger problem, but they actually have a an ill, a real illness, a serious illness in order to get the best outcomes. And, but that's my take on it. You have to be a smart consumer, you have to have smart advocates next to you to take advantage of the AI. What would you advise people to be thinking about as, as they and their loved ones negotiate the healthcare system in this country.

Tom Lawry

Well, I start at the macro level. I believe healthcare today is what civil rights was in the 1960s. It's a huge issue. It affects every person in America and it's not going in the right direction, all the data, whether it's costs, whether it's customer satisfaction. Did you know that the number one reason people go bankrupt in America is not because they go to Vegas is because they are someone they love, get sick.

We all know that I, I'm flabbergasted why more people aren't being more assertive like your story of, of, you know, saying to the hospital, I don't want to pay or I'm not going to pay. So until more people decide they're going to find their voice, I don't think much will change. Beyond that, yeah, being a smart assertive consumer is a great start, but I look at so many people who, who aren't doing that or frankly, who don't have a voice in America when it comes to what's happening to their health. But fundamentally the conversation you're raising today is the conversation every American should be thinking about.

What do you think is a consumer that's important to you and your family? That's where we should be spending more time and that's where more companies, if they're smart, are going to be chasing what those answers are rather than the system we have today.

Tony Roth

Well, one interpretation of your of your closing remarks, Tom, is to take a, a page out of our president's playbook and say that don't forget everything in life is a negotiation.

Tom Lawry

We should all be better negotiators at the things that impact our health.

Tony Roth

So on that note, I think we'll probably end because we're out of time, but we would love to have you back. So thank you so much for being here today, Tom and helping us understand this very fascinating and quickly evolving world of AI and healthcare.

Tom Lawry

Well, thank you for having me. I'd love to come back anytime.

Tony Roth

And with that, I wanted to remind our listeners to go to WilmingtonTrust.com for a full roundup of our thought leadership on the full range of investment-related topics as well as planning. So thank you so much. And we'll be back soon with another episode.

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