Morgan Stanley Global Healthcare Conference | New York 2025

Terence Flynn: Welcome to Thoughts on the Market. I'm Terence Flynn, Morgan Stanley's U.S. Biopharma Analyst.

Erin Wright: And I'm Erin Wright, U.S. Healthcare Services Analyst.

Terence Flynn: Thanks for joining us. We're actually in the midst of the second day of Morgan Stanley's annual Global Healthcare Conference, where we hosted over 400 companies. And there are a number of important themes that we discussed, including healthcare policy and capital allocation.

Now, today on the show, we're going to discuss one of these themes, healthcare spending, which is one of the most pressing challenges facing the U.S. economy today.

It is Tuesday, September 9th at 8am in New York.

Imagine getting a bill for a routine doctor's visit and seeing a number that makes you do a double take. Maybe it's $300 for a quick checkup or thousands of dollars for a simple procedure.

For many Americans, those moments of sticker shock aren't rare. They are the reality.

Now with healthcare costs in the U.S. higher than many other peer countries on a percentage of GDP basis, it's no wonder that everyone – not just investors – is asking; not just, ‘Why is this happening?’ But ‘How can we fix it?’ And that's why we're talking about AI today. Could it be the breakthrough needed to help rein in those costs and reshape how care is delivered?

Now I'm going to go over to you, Erin. Why is U.S. healthcare spending growing so rapidly compared to peer countries?

Erin Wright: Clearly, the aging population in the U.S. and rising chronic disease burden here are clearly driving up demand for healthcare. We're seeing escalating demand across the senior population, for instance. It's coinciding with greater utilization of more sophisticated therapeutics and services. Overall, it's straining the healthcare system.

We are seeing burnout in labor constraints at hospitals and broader health systems overall. Net-net, the U.S. spent 18 percent of GDP on healthcare in 2023, and that's compared to only 11 percent for peer countries. And it's projected to reach 25 to 30 percent of GDP by 2050. So, the costs are clearly escalating here.

Terence Flynn: Thanks, Erin. That's a great way to frame the problem. Now, as we think about AI, where does that come in to help potentially bend the cost curve?

Erin Wright: We think AI can drive meaningful efficiencies across healthcare delivery, with estimated savings of about [$]300 to [$]900 billion by 2050.

So, the focus areas include here: staffing, supply chain, scheduling, adherence. These are where AI tools can really address some of these inefficiencies in care and ultimately drive health outcomes. There are implementation costs and risks for hospitals, but we do think the savings here can be substantial.

Terence Flynn: Great. Well, let's unpack that a little bit more now. So, if you think about the biggest cost buckets in hospitals, where can AI help out?

Erin Wright: The biggest cost bucket for a hospital today clearly is labor. It represents about half of spend for a hospital. AI can optimize staffing, reduce burnout with a new scribe and some of these scribe technologies that are out there, and more efficient healthcare record keeping. I mean, this can really help to drive meaningful cost savings.

Just to add another discouraging data point for you, there's estimated to be a shortage of about 10,000 critical healthcare workers in 2028. So, AI can help to address that. AI tools can be used across administrative functions as well. That accounts for about 15 to 20 percent of spend for a hospital. So, we see substantial savings as well across drugs, supplies, lab testing, where AI can reduce waste and improve adherence overall.

Terence Flynn: Great. Maybe we'll pivot over to the managed care and value-based care side now. How is AI being used in these verticals, Erin?

Erin Wright: For a healthcare insurer – and they're facing many challenges right now as well – AI can help personalize care plans. And they can support better predictive analytics and ultimately help to optimize utilization trends. And it can also help to facilitate value-based care arrangements, which can ultimately drive better health outcomes and bend the cost curve. And ultimately that's the key theme that we're trying to focus on here.

So, I'll turn it over to you, Terence, now. While hospitals and payers could see notable benefits from AI, the biopharma side of the equation is just as critical here. Especially when it comes to long-term cost containment. You've been closely tracking how AI is transforming drug development. What exactly are you seeing?

Terence Flynn: Yeah, a number of key constituents are leaning in here on AI in a number of different ways. I'd say the most meaningful way that could help bend the cost curve is on R&D productivity. As many people probably know, it can take a very long time for a drug to reach the market anywhere from eight to 10 years. And if AI can be used to improve that cycle time or boost the probability of success, the probability of a drug reaching the market – that could have a meaningful benefit on costs. And so, we think AI has the potential to increase drug approvals by 10 to 40 percent. And if that happens, you can ultimately drive cost savings of anywhere from [$]100 billion to [$]600 billion by 2050.

Erin Wright: Yeah, that sounds meaningful. How do you think additional drug approvals lead to meaningful cost savings in the healthcare system?

Terence Flynn: Look, I mean, high level medicines at their best cure disease or prevent people from being admitted to a hospital or seeking care to doctor's office. Equally important medicines can get people out of the hospital quicker and back to contributing or participating in society. And there's data out there in the literature showing that new drugs can reduce hospital stays by anywhere from 11 to 16 percent.

And so, if you think about keeping people out of hospitals or physician offices or reducing hospital stays, that really can result in meaningful savings. And that would be the result of more or better drugs reaching the market over the next decades.

Erin Wright: And how is the FDA now supporting or even helping to endorse AI driven drug development?

Terence Flynn: If companies are applying for more drug approvals here as a result of AI discovery capabilities without modernization, the FDA could actually become the bottleneck and limit the number of drugs approved each year.

And so, in June, the agency rolled out an AI tool called Elsa that's looking to improve the drug review timelines. Now, Elsa has the potential to accelerate these timelines for new therapies. It can take anywhere from six to 10 months for the FDA to actually approve a drug. And so, these AI tools could potentially help decrease those timelines.

Erin Wright: And are you actually seeing some of these biopharma companies actually investing in AI talent?

Terence Flynn: Yes, definitely. I mean, AI related job postings in our sector have doubled since 2021. Companies are increasingly hiring across the board for a number of different, parts of their workflow, including discovery, which we just talked about. But also, clinical trials, marketing, regulatory – a whole host of different job descriptions.

Erin Wright: So, whether it's optimizing hospital operations or accelerating drug discovery, AI is emerging as a powerful lever here – to bend the healthcare cost curve.

Terence Flynn: Exactly. The challenge is adoption, but the potential is transformative. Erin, thanks so much for taking the time to talk with us.

Erin Wright: Great speaking with you, Terence.

Terence Flynn: And thanks everyone for listening. If you enjoy Thoughts on the Market, please leave us a review wherever you listen and share the podcast with a friend or colleague today.

Craig Hettenbach: Welcome to Thoughts on the Market. I'm Craig Hettenbach, Morgan Stanley's U.S. healthcare technology and providers analyst.

Today I'm here with my colleague Steve Rodgers from Morgan Stanley Capital Partners to talk about a growing and underappreciated segment of healthcare – the behind-the-scenes technology that is transforming the sector to keep costs down and improve patient care.

It's Thursday, December 5th at 9am in New York.

In 2022, the size of the U.S. healthcare sector was [$]4.5 trillion and is projected to grow to  [$]6.8 trillion in 2030, accounting for 20 per cent of overall U.S. GDP.  We know that the U.S. population is aging, and we expect to see 71 million U.S. citizens age 65 and over by 2030. That puts ever growing demand on health care systems. 

So, Steve, you and your colleagues in investment management have been looking lately at key macro trends driving change in the healthcare sector.

What are these drivers and how do they work together?

Steve Rodgers: When we look at the health care landscape, we really think about four major macro trends. The first is cost containment. And this is just this simple idea that costs are escalating at an unsustainable rate.

The second is demographics; we also know that things like obesity is increasing the prevalence of chronic conditions and increasing the overall utilization, of the healthcare system. And so, we're looking at ways to invest behind that macro trend.

We've also identified something called consumerism. And consumerism stems from the reality that today, patients are taking more of a financial responsibility in their healthcare. And with that comes more decision making. So, the old days – where the patient received healthcare services, but the payer paid, and there was really no link between the two – have moved on.

Waiting in the office for your appointment for 30 minutes used to be a standard. Today, that's unacceptable because these patients will move to the next provider who's providing them a better retail experience.

The final macro driver we call enabling technology. Health care has lagged many other industry segments in the use of technology as a source of efficiency. I like to give the example of, of chemotherapy treatments, right? Technology would produce a new chemotherapy treatment, and while that's great for patient care and outcomes it actually could lead to increased costs to the system because it was an added route that people would go down.

Now there's technology which allows a provider to say, “Start with this one because of your genetic makeup.” And not only will you have a better outcome more quickly, but it will be less cost to the system. We're also seeing that kind of efficiency happen on the administrative side of healthcare as well.

The way we think about these macro trends and how they work together is really thinking about demand versus supply. So, we see demand drivers coming from demographics and consumerism. We see supply drivers coming from cost containment and really enabling technology has impacts on both demand and supply.

Craig Hettenbach: Let's focus more specifically on just how digitization and cost containment dovetail. When people talk about the impact of AI and ML on healthcare, typically the focus is on things like big pharma, medical equipment, and hospitals. But there's actually a whole intricate infrastructure that helps healthcare run.

Can you talk about these behind-the-scenes businesses and why investment managers are so interested in the opportunities they offer?

Steve Rodgers: Yeah, it's really important. We focus on investments that are using technology to enable their businesses. And so that's automation. That's machine learning. It's AI. But all of these technologies are being used behind the scenes to make care more efficient and they're a better use of our dollars.

For example the personalization of communications from health plans.

So historically a health plan would send the same communication, you know, the same form, to every patient.

Well now, technology allows the health plan, at the point of generating that communication, to know that information about the person that's getting it. And having the ability to personalize it in ways that might help them be more likely to interact with it. Maybe they're trying to get them to do something about their health. Well, they can take an administrative communication, you know, called an explanation of benefit, which really just explains how much you versus how much the health plan owes. And you can also add important information to that that might help you utilize your, benefits better.

Another example that we see is on the hospital side As people I think have heard, hospitals have been very inefficient, right? They pay bills, the wrong bills, they're duplicative invoices, , and there haven't been really good ways to figure that out. Well, we now have technology that can identify those duplicative invoices, that can actually identify that there are multiple contracts that they have with a vendor and direct them to use the cheapest one.

Last one that I would highlight is around the procurement of pharmaceuticals. So, again, if you imagine a hospital system that has 50 different hospitals and one person at each hospital might be buying the pharmaceuticals that fit to the needs they have in that facility. Well, now there's technology that's really helping consolidate those purchases, get the benefits of scale. Also tracking what is a very dynamic pricing market and figuring out today this channels is less costly than that one, so buy it from here; tomorrow it might be different.

We're seeing behind-the-scenes uses of technology in all of those types of areas, which are leading to efficiencies.

Craig Hettenbach: That's really interesting and I agree. Sometimes investors can overlook healthcare infrastructure as an area offering a lot of hidden growth. Let's take a subsector like Revenue Cycle Management or RCM. What is it exactly and what opportunities does it offer when it comes to technology and cost containment?

Steve Rodgers: What it is,It really is the whole process from start to finish of a healthcare episode. So, starting with something as simple as eligibility, or is this patient eligible for this procedure?

Then once that procedure happens, it has to be documented and coded and billed. And then once that bill goes out, that needs to be collected and, paid on. So, this whole process, is really how healthcare works and it's one of the most important business processes for healthcare companies.

And what we've seen with revenue cycle is it's been a very, historically, a very manual process that involved a lot of human effort. So early on, some of the most basic functions of revenue cycle were automated. So, the example I can give there would be the front-end entry of a claim.

So that used to be sent over by fax and a person would have to look at that and, type it into a computer, and start the processing that way. Well that, for a long time, that's now been automated with either what's called OCR, which is a scanning technology.

But even, you know, now, a lot of that's coming in digitally. But a lot of the rest of the process is still manual. And the reason is because the tasks are so complex. So, to resolve a claim, you often need to pull data from multiple sources. There'd be some subjective determinations about what's allowed or not allowed.

You would then need to apply [it] against a multiple complex rules and benefits. And sometimes the sheer dollars involved would make it too risky to just pay that, that claim without someone actually looking at it. Really we're entering an automation cycle where some of these new technologies are making it possible to reliably automate these complex, more complex functions.

And so it's a combination of machine learning and AI, but it's really driving efficiencies that are really exciting from an investment perspective to us right now.

Craig Hettenbach: Got it. In addition to revenue cycle management, are there any other subsectors that look interesting to you right now?

Steve Rodgers: We also, we call it cost cycle management. This is the idea of applying the same principles that we're seeing in revenue cycle to the purchasing of providers. So that can be supply costs, inventory management. Another area that we think is interesting is self insured employer outsourcing. One of the main frustrations that we hear time and time again from self insured employers is that their employees are not utilizing the benefits that they have.

With technology, companies that are finding ways to get broader and better adoption; then in turn allowing these employers to see better utilization, which is going to lead to a healthier workforce and hopefully do so also, with some cost containment.

So Craig, it's clear that there's an overlap between what we look at from the investment management side and what you and your colleagues focus on in research. How do you think about analyzing how AI and machine learning are impacting healthcare?

Craig Hettenbach: Yeah, so for research across the department, we came up with a framework to look at and that's the NEXT framework. So number one, new business opportunities to evaluate. Number two, efficiencies. Number three, external productivity. And number four, content creation. So those are four things to help kind of frame what the opportunity set looks like, when leveraging AI and technology.

Steve Rodgers: And how does this framework apply to your space, healthcare services and technology specifically?

Craig Hettenbach: The second point of that next framework, the E for efficiencies, is something that we're already starting to see, the tangible benefits. And so, just to give you some context here, the CEO of a leading hospital, at a conference recently said that 25 to 30 per cent of overall healthcare costs are tied to administrative.

So there is a lot of low hanging fruit there. There's other areas within whether you think about things like prior authorizations that are still done, manually, either via fax, phone, email. Those are things that some, health plans and technology partners are looking to automate. So, I think the efficiencies – we’re still early on, but you're starting to see at least the business case in terms of investments there.

And then there's the longer term look on the clinical side. And I think the understanding there is that's going to take longer. An executive at a recent, industry conference I was at, I thought he said it best when he said, ‘You know, AI is going to save time before it saves lives

Steve Rodgers: How is this technology changing how physicians or providers do their jobs?

Craig Hettenbach: When we look at what's happened with physicians and nurses and still not too far removed from COVID and just burnout, it's palpable. And I think it's something that technology can certainly be used as an enhancer.

So ambient listening is a new technology when we think about, electronic health records.   Yes, it's great to get that information into that record, but it's also timely and consuming. And so, I think things like that – that can listen to and populate notes – is going to be,  a real time saver for both doctors and patients.

And on the patient side as well, when we think about just our experience, right? Healthcare just has a long ways to go in terms of response time. And that's something that I think more automation and technology, whether it's things like scheduling or check-ins and things like that, I think ultimately you'll see more technology deployed.

Okay, Steve. Are there any other potentially overlooked near term or longer-term pockets of opportunity within health care that you think investors should focus on?

Steve Rodgers: Yeah, I think a general rule for investors or, you know, a heuristic that they should think about is, really trying to invest behind the things that are providing – really trying to stay on the right side of healthcare. And so, when we look at things like cost containment, you know, we, see companies out there where they might be benefiting from inefficiency in the system. Those are things that I'd stay away from.

I'd focus on companies that are providing better quality care at a lower cost and staying on the right side of healthcare. Because I do believe that a lot of these investments – the AI, the technology – are going to drive efficiency and really eradicate some of these business models that are really taking advantage of the inefficiencies in the healthcare system.

Craig Hettenbach: Great, Steve, well that's very helpful and, and thanks for taking the time to talk today.

Steve Rodgers: Great speaking with you, Craig.

Craig Hettenbach: And thanks for listening. If you enjoy Thoughts on the Market, please leave us a review wherever you listen and share the podcast with a friend or colleagues today.