Morgan Stanley Research and Investment Management analysts discuss how AI can keep costs down for the industry and give patients a more personalized experience.

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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 Monday, December 9th 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.

We call it the retailization of health care. 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 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, to – 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 owe 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 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 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 crea