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As I sometimes say, technology doesn't need a living wage,

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and if we're going to shift care from physicians to technology, we want to do that in a way that is very cost-effective,

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so that we have, you know, we free up resources to spend on other high-value care elsewhere.

Unknown Speaker 0:27
Welcome to Off the Chart, a business of medicine podcast featuring lively and informative conversations with healthcare experts, opinion leaders, and practicing physicians about the challenges facing doctors and medical practices. My name is Austin Latrell. I'm the associate editor of Medical Economics, and I'd like to thank you for joining us today. In today's episode, Medical Economics Managing Editor Todd Shryock sat down with Caroline Pearson, Executive Director of the Peterson Health Technology Institute, to talk about their new report on how healthcare should pay for clinical AI. Pearson's argument is that the payment model, not the technology, is what will ultimately decide whether AI brings costs down or becomes the next thing driving them up. Today, they get into why paying for AI under fee-for-service could inflate costs rather than lower them. The difference between AI that assists a physician and AI that acts on its own. Who's on the hook when an autonomous AI tool makes a bad call on a patient's medication? And a new Medicare model that lets technology companies get paid directly with no physician in the middle.

Unknown Speaker 1:17
With all that said, Caroline, thank you for joining us. And now let's get into the episode.

Unknown Speaker 1:35
I'm here with Caroline Pearson, Executive Director of the Peterson Health Technology Institute, to talk about payment for clinical AI. Carolyn, thanks for joining me. I'm so glad to be here. Thanks for having me. So, for physicians, what should be the biggest takeaway from your report on AI and reimbursement?

Unknown Speaker 1:55
Well,

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we have found that the potential for clinical AI to improve care is tremendous, but under the current payment models, we often lack the incentives to adopt that technology.

Unknown Speaker 2:09
And the payment models that we do have available to us risk really raising healthcare costs. So we're calling for a real reconsideration of how we want to pay for health tech to achieve the benefits that we all are looking for.

Unknown Speaker 2:24
The report mentioned that AI should be lowering costs, not inflating them.

Unknown Speaker 2:30
Are there any signs that an AI payment model is is heading towards inflation and instead of you know lowering costs?

Unknown Speaker 2:38
Yeah. So today we still have most of our healthcare that is paid for in fee-for-service models,

Unknown Speaker 2:45
and those payment rates are generally set on the basis of clinician time and effort that is expected for any given service or intervention. The tricky thing about technology is that, of course, the marginal cost of deploying the technology is relatively low,

Unknown Speaker 3:01
and so you can act. You actually have low time and effort, but an ability to bill a service many, many times. You know, very cheaply, and so you just sort of do the math and say, okay, that you know, technology on a fee-for-service chassis could really increase costs, and we do see that happening in cases like remote patient monitoring and some other limited uses,

Unknown Speaker 3:25
and so you really want to say, how do we think about the outcomes that we're looking for in in technology based care, and how can we encourage

Unknown Speaker 3:34
a more value based payment system?

Unknown Speaker 3:37
If AI lets doctors see more patients for the same pay per visit, is that bad for physicians or good for them and bad for the system?

Unknown Speaker 3:47
Well, generally, if we could see more patients, if we actually improved access to care,

Unknown Speaker 3:52
that would be great because we could stretch our our precious healthcare workforce further. So I think that's not really the source of the concern. The source of the concern is really where AI may be increasing the amount of revenue per visit, but not actually improving the number of patients that are being seen or improving the clinical outcomes in those same visits. The

Unknown Speaker 4:18
report talks about assistive AI and autonomous AI

Unknown Speaker 4:22
can you kind of explain the difference? And does the former eventually lead to the latter?

Unknown Speaker 4:27
I think in some cases it will, and in some cases we may always want to prioritize assistive AI. So, you know, assistive AI is really

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human clinicians using AI to make their job faster,

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more efficient, or you know more accurate. So

Unknown Speaker 4:47
you know there's administrative tools to to help with diagnosis or research on appropriate treatment patterns,

Unknown Speaker 4:55
and there can be management tools that extend care

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into the patient environment.

Unknown Speaker 5:00
So those would all be assistive. They're still being deployed, overseen, and billed by the sort of supervising physician.

Unknown Speaker 5:09
Autonomous AI would really enable technology to deliver some facets of care independently, and I think the easiest way to think about that

Unknown Speaker 5:20
is certain common forms of medication prescribing or medication titration. Think about, you know, some urgent care use cases, or even something like titrating medications for hypertension, where

Unknown Speaker 5:33
you know an AI tool could be doing that independently while the patient remains under the primary care of therapy.

Unknown Speaker 5:47
Hey there, Keith Reynolds here, and welcome to the P2 Management Minute. In just 60 seconds, we deliver proven, real-world tactics you can plug into your practice today. Whether that means speeding up check-in, lifting staff morale, or nudging patient satisfaction north, no theory, no fluff, just the kind of guidance that fits between appointments and moves the needle before lunch. But the best ideas don't all come from our newsroom; they come from you. Got a clever workflow hack, an employee engagement win, or a lesson learned the hard way? I want to feature it. Shoot me an email at kreynolds@mjhlifesciences.com with your topic, a quick outline, or even a smartphone clip, we'll handle the rest and get your insights in front of your peers nationwide. Let's make every minute count together. Thanks for watching, and I'll see you in the next P2 Management Minute.

Unknown Speaker 6:38
Do you think there will ever be a time where billing codes might be modified, so doctors would get paid for reviewing an AI recommendation.

Unknown Speaker 6:48
Yeah, we already see some codes like that. So remote patient monitoring

Unknown Speaker 6:53
pays physicians for not only reviewing patient data, but often we're seeing AI analysis of that data. So patients may be checking their blood pressure or their blood sugar at home. Readings are being uploaded, and then the AI is reviewing that data and flagging things for clinician. There are certainly other cases where you could have, you know, AI proposing diagnosis or treatment plans, and the doctor being paid to oversee it. And so some of those cases are going to be important, but we need to think about both what is the right value for those payments, and how do we make sure that the clinician oversight is very effective? Obviously, we know that the more we use AI, sometimes it's hard for people to stay kind of cognitively focused, and so we want to make sure that we're we're keeping our humans sharp focused and spending their time on the highest value clinical interventions.

Unknown Speaker 7:47
If an autonomous AI made a bad call on, say, a patient's medication,

Unknown Speaker 7:52
who would be liable there? The doctor, the health system, or the AI company? This is a major open area for legal work, so

Unknown Speaker 8:02
in most cases right now, it's not clear. Generally speaking, AI solutions like the prescribing needs to operate under the physician's malpractice insurance, and that would be the physician's liability.

Unknown Speaker 8:15
Certainly, physicians are concerned about that; they're not inside the black box of the algorithm, and so I think in many cases we are seeing a push to say how can that liability move to the technology

Unknown Speaker 8:28
vendor

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and what would that look like, but we don't have the legal infrastructure in most cases to do that today. So this is an area of a lot of additional work and regulation that's going to be needed.

Unknown Speaker 8:39
Is there any chance in the future that AI companies could just bill payers directly and kind of cut physicians out of the revenue?

Unknown Speaker 8:48
There is some potential for that. We've seen a couple of examples where things are headed that direction. So one example

Unknown Speaker 8:57
is the new Medicare model called the Access Model, which creates direct payments for technology-based care,

Unknown Speaker 9:06
and you know technology companies can sign up to be paid directly by Medicare for services provided for chronic care management if they deliver clinical outcomes as set forth by the program, and there doesn't need to be any sort of physician traditional Medicare physician in the mix on that,

Unknown Speaker 9:23
so that's really the beginning in the Medicare program. The other example that we saw recently is with Doctronic, which has been doing a pilot program for medication prescribing in Utah,

Unknown Speaker 9:35
and there, you know, the model would be that that you could see those prescriptions get reimbursed by a payer directly, so I think there's a lot of interest in this, and this is where we've been calling out the need to reimagine not only the rules around when when do we think that that would be beneficial, safe, and effective,

Unknown Speaker 9:54
and make sure that we preserve the role of the physician,

Unknown Speaker 9:59
but also what's the right.

Unknown Speaker 10:00
Payment level for that because

Unknown Speaker 10:02
you know as I sometimes say technology doesn't need a living wage,

Unknown Speaker 10:06
and if we're going to shift care from physicians to technology, we want to do that in a way that is very cost effective,

Unknown Speaker 10:14
so that we have you know we free up resources to spend on other high value care elsewhere.

Unknown Speaker 10:20
The report mentioned that ACOs

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didn't always embrace the technology, even when the incentives seemed to line up. Why was that?

Unknown Speaker 10:30
This is a bit of a mystery

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because you would hope that the ACOs

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would be sort of the first place where you would see some of the tech adoption, but I think this is one of the challenges with where we are in the development. So, in a fee-for-service model, lots of health systems are finding ways to deploy technology to increase their revenue.

Unknown Speaker 10:50
But in an ACO or other risk-based payment model, you really have to depend. You have to be confident that the technology is improving the clinical outcomes and reducing total cost of care. There's not a pure revenue play, and generally, I think the ACOs have not found that the evidence that is available to them about the performance of these technologies is compelling enough to

Unknown Speaker 11:12
drive further adoption. So that is certainly something that we want to both encourage more evidence generation and then really educate those ACOs

Unknown Speaker 11:21
about which technologies might be worth integrating into their care.

Unknown Speaker 11:25
Is there anything else that doctors need to know about this report that we haven't talked about?

Unknown Speaker 11:30
Well, I think you know this is a rapidly changing environment. There's going to be lots to to track and to worry about and to learn over the next few years, and so I would highlight that another important component, in addition to payment, is really going to be how we do change management. How do we support the existing clinical workforce in understanding how to use these tools and how to redesign their own care delivery to both maximize the benefit of the technology? I think we want to encourage folks to embrace the technology,

Unknown Speaker 12:01
but that really does require redesigning workflows and rethinking about how clinicians are spending their time. And so we're going to need to devote time and effort to that, both at at a system level and at an individual provider level, to make sure that we can do this right. Interesting. I appreciate your time. Thanks for joining me. Thanks so much, Todd. Good to see you.

Unknown Speaker 12:26
Once again, that was a conversation between Medical Economics Managing Editor Todd Shryock and Caroline Pearson, Executive Director of the Peterson Health Technology Institute. My name is Austin Latrell, and on behalf of the whole Medical Economics and Physicians Practice Teams, I'd like to thank you for listening to the show and ask that please subscribe so you don't miss the next episode.

Unknown Speaker 12:43
As always, be sure to check back on Monday and Thursday mornings for the latest conversations with experts sharing strategies, stories, solutions for your practice. You can find us by searching off the chart wherever you get your podcasts.

Unknown Speaker 12:54
Also, if you'd like the best stories that Medical Economics and Physicians Practice publish, delivered straight to your email six days of the week, subscribe to our newsletters at medicaleconomics.com and physicianspractice.com.

Unknown Speaker 13:05
Off the chart, a business of medicine podcast is executive produced by Chris Masalini and Keith Reynolds, and produced by Austin Latrell.

Unknown Speaker 13:11
Medical Economics and Physicians Practice are both members of the MJH Life Sciences family. Thank you.

Transcribed by https://otter.ai